Response:\\n document = Document.find_by_eid(session, eid)\\n if not document:\\n return Response(\\n {'message': 'The especified eid is not found on database'},\\n status=404,\\n )\\n return Response(sc.Document(document))\",\n \"def createDocument(self, document):\\n data = self.createDocumentAll([document])\\n try:\\n return data[0]\\n except: pass\",\n \"def document_type(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"document_type\\\")\",\n \"def get_doc(doc_id):\\n queue = get_doc_queue(app.config)\\n data = queue.get_by_id(doc_id)\\n if data:\\n return jsonify(doc=data)\\n return jsonify(err=f\\\"{doc_id} not found\\\"), 404\",\n \"def obj_get(self, request=None, **kwargs):\\n return Document(self.get_collection(request).find_one({\\n \\\"_id\\\": ObjectId(kwargs.get(\\\"pk\\\"))\\n }))\",\n \"def get_document(self):\\n return self.document\",\n \"def search_doc_type(self):\\n return self._meta.model_name\",\n \"def getdoc(doctype, name, user=None):\\n\\n\\timport webnotes\\n\\t\\n\\tif not (doctype and name):\\n\\t\\traise Exception, 'doctype and name required!'\\n\\t\\n\\tif not name: \\n\\t\\tname = doctype\\n\\n\\tif not webnotes.conn.exists(doctype, name):\\n\\t\\treturn []\\n\\n\\ttry:\\n\\t\\tbean = webnotes.bean(doctype, name)\\n\\t\\tbean.run_method(\\\"onload\\\")\\n\\n\\t\\tdoclist = bean.doclist\\n\\n\\t\\t# add file list\\n\\t\\tset_docinfo(doctype, name)\\n\\t\\t\\n\\texcept Exception, e:\\n\\t\\twebnotes.errprint(webnotes.utils.getTraceback())\\n\\t\\twebnotes.msgprint('Did not load.')\\n\\t\\traise e\\n\\n\\tif bean and not name.startswith('_'):\\n\\t\\twebnotes.user.update_recent(doctype, name)\\n\\t\\n\\twebnotes.response['docs'] = doclist\",\n \"def getdoc():\\n\\n\\timport webnotes\\n\\tfrom webnotes.utils import cint\\n\\t\\n\\tform = webnotes.form_dict\\n\\tdoctype, docname = form.get('doctype'), form.get('name')\\n\\tprefix = cint(form.get('from_archive')) and 'arc' or 'tab'\\n\\n\\tif not (doctype and docname):\\n\\t\\traise Exception, 'doctype and name required!'\\n\\t\\n\\tdoclist = []\\n\\t# single\\n\\tdoclist = load_single_doc(doctype, docname, (form.get('user') or webnotes.session['user']), prefix)\\n\\t\\n\\t# load doctype along with the doc\\n\\tif form.get('getdoctype'):\\n\\t\\timport webnotes.model.doctype\\n\\t\\tdoclist += webnotes.model.doctype.get(doctype)\\n\\n\\t# tag as archived\\n\\tif prefix == 'arc':\\n\\t\\tdoclist[0].__archived=1\\n\\n\\twebnotes.response['docs'] = doclist\",\n \"def get_document(self, doc_id, options=None):\\n path = urllib.quote_plus(str(doc_id))\\n try:\\n result = self.request(path, pylastica.request.Request.GET, query=options).data\\n except pylastica.exception.ResponseException:\\n raise pylastica.exception.NotFoundException(\\\"Document with id %s not found.\\\" % doc_id)\\n if result['found'] is None or result['found'] == '' or not result['found']:\\n raise pylastica.exception.NotFoundException(\\\"Document with id %s not found.\\\" % doc_id)\\n data = result['_source'] if '_source' in result else {}\\n document = pylastica.document.Document(doc_id, data, self.name, self.index)\\n document.version = result['_version']\\n return document\",\n \"def get_doc(ds, idx):\\n rtn = ds[idx]\\n if isinstance(rtn, dict):\\n rtn = rtn['text']\\n return rtn\",\n \"def _load_document(path, app):\\n start_inventor()\\n document_type_enum = {\\n 12289: 'UnnownDocument',\\n 12290: 'PartDocument',\\n 12291: 'AssemblyDocument',\\n 12292: 'DrawingDocument',\\n 12293: 'PresentationDocument',\\n 12294: 'DesignElementDocument',\\n 12295: 'ForeignModelDocument',\\n 12296: 'SATFileDocument',\\n 12297: 'NoDocument',\\n }\\n try:\\n app.Documents.Open(str(path))\\n document_type = document_type_enum[app.ActiveDocumentType]\\n doc = win32com.client.CastTo(app.ActiveDocument, document_type)\\n print(doc, document_type)\\n return doc\\n except:\\n print('unable to load file')\\n return None\",\n \"def _get_doc(results, index):\\n return results[index]\",\n \"def test_get_document(index_with_documents):\\n response = index_with_documents().get_document(\\\"500682\\\")\\n assert isinstance(response, Document)\\n assert hasattr(response, \\\"title\\\")\\n assert response.title == \\\"The Highwaymen\\\"\",\n \"def DocumentType(self, default='article'):\\n return self.data.get('document_type', [{}])\",\n \"def get_reference_for(document):\\n k = Factory.build('shared.doc_reference')\\n for key in ('name', 'canonical_name'):\\n conditional_copy(document, k, key)\\n if not getattr(k, 'canonical_name'):\\n if getattr(k,'name'):\\n setattr(k,'canonical_name',getattr(k,'name'))\\n for key in ('version',):\\n conditional_copy(document._meta, k, key)\\n for inkey, outkey in [('uid','id'),]:\\n conditional_copy(document._meta, k, inkey, outkey)\\n for inkey, outkey in [('type_key','type'),]:\\n setattr(k, outkey, getattr(document._osl,inkey))\\n return k\",\n \"def get_document(self, doc_uri: str) -> Document:\\n return self._docs.get(doc_uri) or self._create_document(doc_uri)\",\n \"def get_document_by_id(self, index: str, doc_id: str) -> Optional[Dict[str, Any]]:\\n try:\\n return self.__client__.get(index=index, id=doc_id)\\n except elasticsearch.exceptions.NotFoundError:\\n return None\",\n \"def get(self, index, id):\\n url = f'{self.host}{index}/_doc/{id}'\\n resp = requests.get(url)\\n return resp.json()\",\n \"def get_document(self, docid):\\n try:\\n return self.sql_session.query(Document).get(docid)\\n except OperationalError:\\n raise IOError(\\\"Sorry, this database is incompatible with the \\\"\\n \\\"current version of Luminoso. If you want, you can \\\"\\n \\\"delete the model directory and start again.\\\")\",\n \"def fetch_search_document(self, index):\\n assert self.pk, \\\"Object must have a primary key before being indexed.\\\"\\n client = get_client()\\n return client.get(\\n index=index,\\n doc_type=self.search_doc_type,\\n id=self.pk\\n )\",\n \"def documentdetail(request, docid):\\n\\tdocument = get_object_or_404(Document, pk=docid)\\n\\tif not request.user.has_perm('documents.view_document', obj=document):\\n\\t\\treturn HttpResponse(loader.render_to_string('401.html',\\n\\t\\t\\tRequestContext(request, {'error_message':\\n\\t\\t\\t\\t_(\\\"You are not allowed to view this document.\\\")})), status=401)\\n\\ttry:\\n\\t\\trelated = document.content_type.get_object_for_this_type(id=document.object_id)\\n\\texcept:\\n\\t\\trelated = ''\\n\\n\\treturn render_to_response(\\\"documents/docinfo.html\\\", RequestContext(request, {\\n\\t\\t'permissions_json': json.dumps(_perms_info(document, DOCUMENT_LEV_NAMES)),\\n\\t\\t'document': document,\\n\\t\\t'imgtypes': imgtypes,\\n\\t\\t'related': related\\n\\t}))\",\n \"def get_document(document_id: Optional[str] = None,\\n location: Optional[str] = None,\\n project: Optional[str] = None,\\n opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDocumentResult:\\n __args__ = dict()\\n __args__['documentId'] = document_id\\n __args__['location'] = location\\n __args__['project'] = project\\n opts = pulumi.InvokeOptions.merge(_utilities.get_invoke_opts_defaults(), opts)\\n __ret__ = pulumi.runtime.invoke('google-native:contentwarehouse/v1:getDocument', __args__, opts=opts, typ=GetDocumentResult).value\\n\\n return AwaitableGetDocumentResult(\\n cloud_ai_document=pulumi.get(__ret__, 'cloud_ai_document'),\\n content_category=pulumi.get(__ret__, 'content_category'),\\n create_time=pulumi.get(__ret__, 'create_time'),\\n creator=pulumi.get(__ret__, 'creator'),\\n display_name=pulumi.get(__ret__, 'display_name'),\\n display_uri=pulumi.get(__ret__, 'display_uri'),\\n disposition_time=pulumi.get(__ret__, 'disposition_time'),\\n document_schema_name=pulumi.get(__ret__, 'document_schema_name'),\\n inline_raw_document=pulumi.get(__ret__, 'inline_raw_document'),\\n name=pulumi.get(__ret__, 'name'),\\n plain_text=pulumi.get(__ret__, 'plain_text'),\\n properties=pulumi.get(__ret__, 'properties'),\\n raw_document_file_type=pulumi.get(__ret__, 'raw_document_file_type'),\\n raw_document_path=pulumi.get(__ret__, 'raw_document_path'),\\n reference_id=pulumi.get(__ret__, 'reference_id'),\\n text_extraction_disabled=pulumi.get(__ret__, 'text_extraction_disabled'),\\n text_extraction_enabled=pulumi.get(__ret__, 'text_extraction_enabled'),\\n title=pulumi.get(__ret__, 'title'),\\n update_time=pulumi.get(__ret__, 'update_time'),\\n updater=pulumi.get(__ret__, 'updater'))\",\n \"def get_type_from_doc(doc):\\n try:\\n return doc.replace('\\\\n',' ').split('-> ')[1].split(' ')[0]\\n except:\\n return None\",\n \"def GetDoc(index_wd, key, value):\\n # init code:\\n key = key.lower().strip()\\n value = value.strip()\\n docid_to_docno_path = os.path.join(index_wd, 'docid_to_docno.p')\\n docno_to_data_path = os.path.join(index_wd, 'docno_to_data.p')\\n # check to see what key is (docno or docid)\\n\\n # if docid, need to grab the docid_to_docno from disk\\n # Lookup via docid:\\n if key == 'docid':\\n docid_to_docno = pickle.load(open(docid_to_docno_path, \\\"rb\\\"))\\n value = int(value)\\n if value not in docid_to_docno:\\n print(\\\"The following docid: {} was not found.\\\".format(value))\\n return False\\n else:\\n docno = docid_to_docno[value]\\n #Lookup via docno:\\n elif key == 'docno':\\n docno = value\\n else:\\n print(\\\"The following key: {} is invalid. Pass: 'docid' or 'docno'\\\".format(key))\\n return False\\n docno_to_data = pickle.load(open(docno_to_data_path, \\\"rb\\\"))\\n\\n if docno not in docno_to_data:\\n print(\\\"The following docno: {} was not found.\\\".format(value))\\n return False\\n\\n doc_path = docno_to_data[docno]\\n\\n basepath = os.path.dirname(doc_path)\\n\\n if not os.path.exists(basepath):\\n print(\\\"The basepath {} does not exist.\\\".format(basepath))\\n return False\\n\\n metadata = MetaData(doc_path)\\n metadata.load()\\n metadata.meta_print()\\n return True\",\n \"async def get_document(self):\\n try:\\n document = await self.request.json()\\n except json.JSONDecodeError:\\n document = {}\\n\\n return document\",\n \"def get_document(self, doc_id: int) -> Optional[Users]:\\n try:\\n doc = self.session.query(CandidatesDocuments).get(doc_id)\\n\\n return doc\\n except Exception as excpt:\\n self.session.rollback()\\n print(f'Could not get doc: {excpt}')\\n\\n return None\",\n \"def get_document_or_404(id, db=None):\\n try:\\n return dbs[DEFAULT_DATABASE if db is None else db][id]\\n except ResourceNotFound:\\n raise Http404\",\n \"def get_document_from_xtracta(document_id):\\n response = None\\n response = requests.post(XTRACTA['url']+\\\"documents\\\",\\n data={\\\"submit\\\":\\\"Submit\\\",\\\\\\n \\\"api_key\\\":XTRACTA['key'],\\\\\\n \\\"document_id\\\":document_id})\\n return response\",\n \"def search_get():\\n return partial(\\n current_search_client.get, Vocabulary.index._name, doc_type=\\\"_doc\\\"\\n )\",\n \"def get_document(self, value, key='name'):\\n if value.endswith('.json'):\\n key = 'filename'\\n return [x for x in self.vocab if x[key] == value][0]\",\n \"def retrieve(document_id: str) -> Fulltext:\\n return current_session().retrieve(document_id)\",\n \"def retrieve_document(self, portal_name, content_id):\\n r = requests.get(\\n '/'.join([self.base_url, self.DOCUMENTS_ENDPOINT, portal_name, str(content_id)]))\\n return r.json()\",\n \"def document(self) -> str:\\n return pulumi.get(self, \\\"document\\\")\",\n \"def ensure_document(doclike):\\n if isinstance(doclike, dict):\\n return doclike\\n elif isinstance(doclike, str) and doclike.startswith(\\\"http\\\"):\\n try:\\n _json = requests.get(doclike).json()\\n except requests.RequestException as exc:\\n raise ValueError(str(exc))\\n except json.decoder.JSONDecodeError as exc:\\n raise ValueError(str(exc))\\n else: # possible it's an array, etc..\\n return ensure_document(_json)\\n raise TypeError(\\\"not a document.\\\")\",\n \"def get_by_id(key):\\n key = KeyModel(key)\\n key.validate()\\n return {\\\"text\\\": repository.get_doc(COLLECTION_NAME, key.to_dict())}\",\n \"async def read_block_document_by_name(\\n self,\\n name: str,\\n block_type_slug: str,\\n include_secrets: bool = True,\\n ):\\n try:\\n response = await self._client.get(\\n f\\\"/block_types/slug/{block_type_slug}/block_documents/name/{name}\\\",\\n params=dict(include_secrets=include_secrets),\\n )\\n except httpx.HTTPStatusError as e:\\n if e.response.status_code == status.HTTP_404_NOT_FOUND:\\n raise prefect.exceptions.ObjectNotFound(http_exc=e) from e\\n else:\\n raise\\n return BlockDocument.parse_obj(response.json())\",\n \"def document_search_cls(self):\\n return self.search_by_pid_type(DOCUMENT_PID_TYPE)\",\n \"def view_document(self, database, collection, _id):\\n r = self.__get_response(settings.VIW_DOC,\\n {\\\"db\\\": database, \\\"col\\\": collection, \\\"id\\\": str(_id)})\\n if r[\\\"status\\\"] == 200:\\n return r[\\\"result\\\"]\\n raise Exception(r[\\\"result\\\"][\\\"message\\\"])\",\n \"def getFirstDocument(address=\\\"\\\", database=\\\"\\\", collection=\\\"\\\"):\\n\\n document = []\\n client = connectMongo(address, database, collection)\\n\\n document.append(client.find_one())\\n\\n return document\",\n \"def doc(self):\\n doc = self.get('doc')\\n if doc:\\n from .config import defaults\\n return defaults.types.doc(doc)\",\n \"def document(self):\\n query = {\\\"_id\\\": ObjectId(self.document_id)}\\n return Document(get_collection(\\\"documents\\\").find_one(query))\",\n \"def _get(self, language):\\n document = self._data.get(language)\\n if not document:\\n document = self._data[self.getDefaultLanguage()]\\n return document\",\n \"def get(self, request, pk):\\n document = self.get_object(pk)\\n\\n if request.user.has_perm(Access.PERM_READ, document):\\n serializer = DocumentSerializer(document)\\n return Response(serializer.data)\\n\\n return Response(\\n status=status.HTTP_403_FORBIDDEN\\n )\",\n \"def getdocfield(fieldname):\\t\\t\\n\\tl = [d for d in doctype_dl if d.doctype=='DocField' and d.fieldname==fieldname]\\n\\treturn l and l[0] or None\",\n \"def get_from_sources(self,index,doc_type,document_id):\\n return self.sources.get(index, {}).get(doc_type, {}).get(document_id,{})\",\n \"def __call__(self, doc):\\n return doc\",\n \"def get_type(self):\\n\\n return ebooklib.ITEM_DOCUMENT\",\n \"def get_document_and_list_id_by_name(update, name_or_id):\\n document = get_document_by_name(update, name_or_id)\\n if not document:\\n return None, None\\n\\n logging.info('Document id: {0}'.format(document['id']))\\n\\n sc_web = SmartCATWeb(SMARTCAT_SESSION_FILE, SMARTCAT_EMAIL, SMARTCAT_PASSWORD,\\n SMARTCAT_API_USERNAME, SMARTCAT_API_PASSWORD)\\n\\n remove_lang = re.compile('_.{2}$')\\n response = sc_web.create_document_list_id(remove_lang.sub('', document['id']))\\n list_id = json.loads(response.content, encoding='utf-8')\\n if not list_id:\\n logging.warning('List id not found')\\n update.message.reply_text(NOTHING_FOUND)\\n return document, None\\n\\n return document, list_id\",\n \"def get_detail(self, request, **kwargs):\\n\\t\\tself.method_check(request, allowed=['get'])\\n\\t\\tdata = self.deserialize(request, request.raw_post_data, format=request.META.get('CONTENT_TYPE', 'application/json'))\\n\\t\\tdoc_node = Document.objects.get(CTS=data.get(\\\"CTS\\\"))\\t\\n\\t\\treturn self.create_response(request, data)\",\n \"def find_by_doc_reg_num(cls, doc_reg_num: str):\\n document = None\\n if doc_reg_num:\\n try:\\n document = cls.query.filter(Db2Document.document_reg_id == doc_reg_num).one_or_none()\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_doc_reg_num exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def get(self, *args):\\n return self.docs.get(*args)\",\n \"def document_view(self, doc_type, view, path, is_zip=False, **kwargs):\\n return self.get('fileops/documentView', api='CONV', params={\\n 'root': self.root,\\n 'path': path,\\n 'type': doc_type,\\n 'view': view,\\n 'zip': 1 if is_zip else 0,\\n }, **kwargs)\",\n \"def get_document_output(document_id: Optional[pulumi.Input[str]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n project: Optional[pulumi.Input[Optional[str]]] = None,\\n opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetDocumentResult]:\\n ...\",\n \"def find_by_id(cls, doc_id: str):\\n document = None\\n if doc_id:\\n try:\\n document = cls.query.get(doc_id)\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_id exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def _get_document(self, doc_uid, doc_type, row, mappings):\\n # Create document.\\n doc = pyesdoc.create(doc_type,\\n project=DOC_PROJECT,\\n source=DOC_SOURCE,\\n version=1,\\n uid=doc_uid)\\n\\n # Assign document dates.\\n try:\\n doc.meta\\n except AttributeError:\\n pass\\n else:\\n doc.meta.create_date = DOC_CREATE_DATE\\n doc.meta.update_date = DOC_UPDATE_DATE\\n\\n # Assign document author.\\n try:\\n doc.meta.author = DOC_AUTHOR_REFERENCE\\n except AttributeError:\\n pass\\n\\n # Set document attributes from mapped worksheet cells.\\n for mapping in mappings:\\n self._set_document_attribute(doc, row, mapping)\\n\\n return doc\",\n \"def get(**args):\\n\\tglobal _objstore\\n\\t_objstore = _objstore or ObjStore()\\n\\n\\treturn _objstore.get(args['type'], args['name'])\",\n \"def find_object(self, obj_type, obj_name):\\n try:\\n # Simply look it up by type and name.\\n obj = self.model_map['object'][obj_type][obj_name][1]\\n except KeyError:\\n # No dice. This object doesn't exist in the model.\\n obj = None\\n\\n return obj\",\n \"def documents(self, **kw):\\r\\n \\r\\n doc_reader = self.doc_reader\\r\\n return (doc_reader[docnum] for docnum in self.document_numbers(**kw))\",\n \"def document(url: str) -> Document:\\n return Document(url)\",\n \"def find_one():\\n fmter.tpl._straightline(\\\"one document\\\", 100)\\n result = users.find_one({})\\n print(type(result))\\n ppt(result)\\n \\n fmter.tpl._straightline(\\\"none result\\\", 100)\\n result = users.find_one({\\\"_id\\\": 100})\\n print(type(result))\\n ppt(result)\",\n \"def _doc_create(type, data):\\n doc = dict(data)\\n doc.update({'model_type': type})\\n return doc\",\n \"def get_docname_from_schema(doctype,config):\\n\\tfor coll in config[\\\"schema\\\"].keys():\\n\\t\\tfor doc in config[\\\"schema\\\"][coll].keys():\\n\\t\\t\\tif doctype == doc: return config[\\\"schema\\\"][coll][doc]\",\n \"def get_document_or_error(document_id):\\n\\ttry:\\n\\t\\tdocument = DocumentChat.objects.get(pk=document_id)\\n\\texcept DocumentChat.DoesNotExist:\\n\\t\\traise ClientError(\\\"ROOM_INVALID\\\", \\\"Invalid room.\\\")\\n\\treturn document\",\n \"def get_object(self, object_type, object_name, user_key = None):\\n\\t\\tobject_key = self._get_key(object_type,user_key)\\n\\n\\t\\ttarget_object = None\\n\\n\\t\\t#print object_type\\n\\t\\tfor item in self.data['all_%s' % object_type]:\\n\\t\\t\\t## Skip items without the specified key\\n\\t\\t\\tif not item.has_key(object_key):\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tif item[object_key] == object_name:\\n\\t\\t\\t\\ttarget_object = item\\n\\t\\t\\t## This is for multi-key items\\n\\t\\treturn target_object\",\n \"def get_doc(self, item_id, id_field=\\\"_id\\\", **kwargs):\\r\\n\\r\\n lg = logging.getLogger(\\\"%s.%s\\\" % (self.ln, inspect.stack()[0][3]))\\r\\n lg.setLevel(self.log_level)\\r\\n\\r\\n args = inspect.getargvalues(inspect.currentframe())[3]\\r\\n lg.debug(\\\"\\\\n****** Args *****:\\\\n%s\\\",\\r\\n pp.pformat(args))\\r\\n\\r\\n es = kwargs.get(\\\"es\\\",self.es)\\r\\n doc_type = kwargs.get(\\\"doc_type\\\", self.doc_type)\\r\\n if id_field == \\\"_id\\\":\\r\\n lg.debug(\\\"*** _id lookup: index: %s item_id: %s\\\",\\r\\n self.es_index,\\r\\n item_id)\\r\\n result = es.get(index=self.es_index,\\r\\n id=item_id)\\r\\n else:\\r\\n dsl = {\\r\\n \\\"query\\\": {\\r\\n \\\"constant_score\\\": {\\r\\n \\\"filter\\\": {\\r\\n \\\"term\\\": { id_field: item_id }\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n lg.debug(\\\"*** id_field lookup: index: %s item_id: %s \\\\nDSL: %s\\\",\\r\\n self.es_index,\\r\\n item_id,\\r\\n pp.pformat(dsl))\\r\\n result = es.search(index=self.es_index,\\r\\n doc_type=doc_type,\\r\\n body=dsl)\\r\\n result = first(result.get(\\\"hits\\\",{}).get(\\\"hits\\\",[]))\\r\\n lg.debug(\\\"\\\\tresult:\\\\n%s\\\", pp.pformat(result))\\r\\n return result\",\n \"def get_document_detail(\\n self,\\n project_id: int,\\n doc_id: int\\n ) -> requests.models.Response:\\n return self.get(\\n 'v1/projects/{project_id}/docs/{doc_id}'.format(\\n project_id=project_id,\\n doc_id=doc_id\\n )\\n )\",\n \"def doc(caesar, input):\\n name = input.group(1)\\n name = name.lower()\\n\\n if caesar.doc.has_key(name): \\n caesar.reply(caesar.doc[name][0])\\n if caesar.doc[name][1]: \\n caesar.say('e.g. ' + caesar.doc[name][1])\",\n \"def documento(self):\\n return self.persona.documento\",\n \"def new_document(klass, name=None, author=None):\\n doc = Factory.new_document(klass, author)\\n doc.name = name\\n doc._osl.id = uuid.uuid4()\\n return doc\",\n \"def document_details(context, document):\\n return {'document': document, 'request': context['request']}\",\n \"def test_client_document_retrieve(self):\\n pass\",\n \"def GetDocument(self):\\n return self.file\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8119024","0.7807013","0.7141701","0.71329045","0.6930829","0.69083655","0.68151665","0.6775295","0.67580533","0.66710275","0.666382","0.66597706","0.6616618","0.65856236","0.6542822","0.652078","0.64975977","0.6474223","0.64734006","0.64587903","0.64214313","0.64030534","0.6374441","0.6359206","0.6284757","0.62558776","0.62051034","0.6196493","0.6195949","0.6192447","0.6170991","0.61520785","0.61468744","0.6143605","0.61424845","0.6137711","0.6136083","0.6118797","0.6085487","0.6078359","0.6070601","0.6050327","0.60247636","0.60205084","0.59874696","0.59870577","0.59869736","0.59846145","0.5954276","0.5941582","0.59365094","0.5929358","0.59264684","0.5892709","0.5890287","0.588155","0.5876256","0.58702743","0.58536124","0.58527493","0.5844155","0.577542","0.5762365","0.5762292","0.5754636","0.57515454","0.57435536","0.5743066","0.5733717","0.57304347","0.57262003","0.5723805","0.5705892","0.5704273","0.56840634","0.56611645","0.5657388","0.5655367","0.56428075","0.5629433","0.5627675","0.5621555","0.5615535","0.56102777","0.55977607","0.5594439","0.55854094","0.55753535","0.55721116","0.55658","0.5564317","0.5561898","0.55582887","0.5557687","0.55487275","0.55298144","0.5528861","0.5514337","0.55068797","0.5502366"],"string":"[\n \"0.8119024\",\n \"0.7807013\",\n \"0.7141701\",\n \"0.71329045\",\n \"0.6930829\",\n \"0.69083655\",\n \"0.68151665\",\n \"0.6775295\",\n \"0.67580533\",\n \"0.66710275\",\n \"0.666382\",\n \"0.66597706\",\n \"0.6616618\",\n \"0.65856236\",\n \"0.6542822\",\n \"0.652078\",\n \"0.64975977\",\n \"0.6474223\",\n \"0.64734006\",\n \"0.64587903\",\n \"0.64214313\",\n \"0.64030534\",\n \"0.6374441\",\n \"0.6359206\",\n \"0.6284757\",\n \"0.62558776\",\n \"0.62051034\",\n \"0.6196493\",\n \"0.6195949\",\n \"0.6192447\",\n \"0.6170991\",\n \"0.61520785\",\n \"0.61468744\",\n \"0.6143605\",\n \"0.61424845\",\n \"0.6137711\",\n \"0.6136083\",\n \"0.6118797\",\n \"0.6085487\",\n \"0.6078359\",\n \"0.6070601\",\n \"0.6050327\",\n \"0.60247636\",\n \"0.60205084\",\n \"0.59874696\",\n \"0.59870577\",\n \"0.59869736\",\n \"0.59846145\",\n \"0.5954276\",\n \"0.5941582\",\n \"0.59365094\",\n \"0.5929358\",\n \"0.59264684\",\n \"0.5892709\",\n \"0.5890287\",\n \"0.588155\",\n \"0.5876256\",\n \"0.58702743\",\n \"0.58536124\",\n \"0.58527493\",\n \"0.5844155\",\n \"0.577542\",\n \"0.5762365\",\n \"0.5762292\",\n \"0.5754636\",\n \"0.57515454\",\n \"0.57435536\",\n \"0.5743066\",\n \"0.5733717\",\n \"0.57304347\",\n \"0.57262003\",\n \"0.5723805\",\n \"0.5705892\",\n \"0.5704273\",\n \"0.56840634\",\n \"0.56611645\",\n \"0.5657388\",\n \"0.5655367\",\n \"0.56428075\",\n \"0.5629433\",\n \"0.5627675\",\n \"0.5621555\",\n \"0.5615535\",\n \"0.56102777\",\n \"0.55977607\",\n \"0.5594439\",\n \"0.55854094\",\n \"0.55753535\",\n \"0.55721116\",\n \"0.55658\",\n \"0.5564317\",\n \"0.5561898\",\n \"0.55582887\",\n \"0.5557687\",\n \"0.55487275\",\n \"0.55298144\",\n \"0.5528861\",\n \"0.5514337\",\n \"0.55068797\",\n \"0.5502366\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.67501426"},"document_rank":{"kind":"string","value":"9"}}},{"rowIdx":25680,"cells":{"query":{"kind":"string","value":"Get a particular document when you know it's id"},"document":{"kind":"string","value":"def getbyid(self, id):\n\n return esd.retrieve(id)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_document_by_id(document_id):\n return Documents.query.filter_by(id=document_id).first()","def get_document(self, docid):\n raise NotImplementedError","def obj_get(self, request=None, **kwargs):\n return Document(self.get_collection(request).find_one({\n \"_id\": ObjectId(kwargs.get(\"pk\"))\n }))","def get_document(name):\n document = [d for d in documents if d.name == name]\n if len(document) > 0:\n return document[0]","def get(self, index, id):\n url = f'{self.host}{index}/_doc/{id}'\n resp = requests.get(url)\n return resp.json()","def document(self, document_id):\r\n return doc.Document(self, document_id)","def get_document_or_404(id, db=None):\n try:\n return dbs[DEFAULT_DATABASE if db is None else db][id]\n except ResourceNotFound:\n raise Http404","def get_document(eid, session: CondorSession) -> Response:\n document = Document.find_by_eid(session, eid)\n if not document:\n return Response(\n {'message': 'The especified eid is not found on database'},\n status=404,\n )\n return Response(sc.Document(document))","def get_document_by_id(self, index: str, doc_id: str) -> Optional[Dict[str, Any]]:\n try:\n return self.__client__.get(index=index, id=doc_id)\n except elasticsearch.exceptions.NotFoundError:\n return None","def get_doc(doc_id):\n queue = get_doc_queue(app.config)\n data = queue.get_by_id(doc_id)\n if data:\n return jsonify(doc=data)\n return jsonify(err=f\"{doc_id} not found\"), 404","def get_document(obj):\n try:\n return ES.get(\n index=obj.get_index_name(), doc_type=obj.get_document_type(), id=obj.pk)\n except NotFoundError:\n raise DocumentNotFound(obj.get_index_name(), obj.pk)","def retrieve(document_id: str) -> Fulltext:\n return current_session().retrieve(document_id)","def get(self, _id):\n try:\n doc = self._db[_id]\n # For speed testing\n del self._db[_id]\n except KeyError:\n return None\n else:\n return self._parse_doc(doc)","def get_by_id(key):\n key = KeyModel(key)\n key.validate()\n return {\"text\": repository.get_doc(COLLECTION_NAME, key.to_dict())}","def one(self):\n try:\n return self[0]\n except IndexError:\n raise self.document.DoesNotExist","def get_single_data(document_id):\n data = collection.find_one({'_id': ObjectId(document_id)})\n return data","def get(self, query_data=None, id_obj=None):\n if id_obj:\n return self.collection.find_one({'_id': id_obj})\n return self.collection.find_one(query_data)","def find_by_id(cls, doc_id: str):\n document = None\n if doc_id:\n try:\n document = cls.query.get(doc_id)\n except Exception as db_exception: # noqa: B902; return nicer error\n current_app.logger.error('Db2Document.find_by_id exception: ' + str(db_exception))\n raise DatabaseException(db_exception)\n if document:\n document.strip()\n return document","def get_document(self, doc_id, options=None):\n path = urllib.quote_plus(str(doc_id))\n try:\n result = self.request(path, pylastica.request.Request.GET, query=options).data\n except pylastica.exception.ResponseException:\n raise pylastica.exception.NotFoundException(\"Document with id %s not found.\" % doc_id)\n if result['found'] is None or result['found'] == '' or not result['found']:\n raise pylastica.exception.NotFoundException(\"Document with id %s not found.\" % doc_id)\n data = result['_source'] if '_source' in result else {}\n document = pylastica.document.Document(doc_id, data, self.name, self.index)\n document.version = result['_version']\n return document","def getDocument(self, key):\n data = self.client.get(self.name +\"/_all_docs\", {\n \"include_docs\": True,\n \"key\" : \"\\\"%s\\\"\" % util.quote(key),\n }).getBodyData()\n\n try:\n return data[\"rows\"][0]\n except: pass","def _get_doc_key(self, doc_id, key):\n cursor = self.connection.cursor()\n cursor.execute(\n \"SELECT {} FROM documents WHERE id = ?\".format(key),\n (normalize(doc_id),)\n )\n result = cursor.fetchone()\n cursor.close()\n return result if result is None else result[0]","def view_document(self, database, collection, _id):\n r = self.__get_response(settings.VIW_DOC,\n {\"db\": database, \"col\": collection, \"id\": str(_id)})\n if r[\"status\"] == 200:\n return r[\"result\"]\n raise Exception(r[\"result\"][\"message\"])","def retrieveById(self, doc_id=None):\n obj = self.find_one({'_id': doc_id if id else self.get('_id')})\n if obj:\n self._import(obj)\n return True\n return False","def get_document(self, type: Type, id: str,\n key: Optional[str] = None) -> Dict[str, Any]:\n document = None\n\n if report := self.client.document(f'{type}/{id}'):\n document = report.get().to_dict()\n\n return document.get(key) if key else document","def get_document(self, doc_id: int) -> Optional[Users]:\n try:\n doc = self.session.query(CandidatesDocuments).get(doc_id)\n\n return doc\n except Exception as excpt:\n self.session.rollback()\n print(f'Could not get doc: {excpt}')\n\n return None","def get(self, document_id):\n document_id = document_id.strip()\n if not document_id:\n return None\n\n connection = self.__get_database_connection()\n response = self.__make_request(connection, '/%s/%s' % (self.database_name, document_id))\n return response","def get_doc_id(self):\n return self.__doc_id","def _id(self, document):\n pass","def find_document(self):\n pass","def get_document(self, docid):\n try:\n return self.sql_session.query(Document).get(docid)\n except OperationalError:\n raise IOError(\"Sorry, this database is incompatible with the \"\n \"current version of Luminoso. If you want, you can \"\n \"delete the model directory and start again.\")","def get_document_by_name(update, name_or_id):\n sc_api = SmartCAT(SMARTCAT_API_USERNAME, SMARTCAT_API_PASSWORD)\n try:\n document = sc_api.project.get_document_by_name(SMARTCAT_PROJECT_ID, name_or_id)\n except SmartcatException as e:\n logging.error('Error getting document: {0} {1}'.format(e.code, e.message))\n update.message.reply_text(SHIT_HAPPENS)\n return None\n\n if not document:\n logging.warning('Document not found')\n update.message.reply_text(NOTHING_FOUND)\n return None\n\n return document","def get_document_by_name(label, doc_type):\n return Documents.query.filter_by(type=doc_type, label=label).first()","def document(self):\n query = {\"_id\": ObjectId(self.document_id)}\n return Document(get_collection(\"documents\").find_one(query))","def find_by_doc_id(cls, doc_reg_id: str):\n document = None\n if doc_reg_id:\n try:\n document = cls.query.filter(Db2Document.id == doc_reg_id).one_or_none()\n except Exception as db_exception: # noqa: B902; return nicer error\n current_app.logger.error('Db2Document.find_by_doc_id exception: ' + str(db_exception))\n raise DatabaseException(db_exception)\n if document:\n document.strip()\n return document","def get_object(id):","def get_document(self, *args, **kwargs):\n return self._documents_manager.get_document(*args, **kwargs)","def userDocumentId(self, id: str) -> str:","def get_named_document(self, entity, name):\n view = self.db.view(\"%s/name\" % entity, include_docs=True)\n result = view[name]\n if len(result) != 1:\n raise ValueError(\"no such %s document '%s'\" % (entity, name))\n return result.rows[0].doc","def get_publication_from_id_in_db(new_id: str) -> Union[None, Dict]:\n\n # db_publications = app.data.driver.db[\"publications\"]\n # try:\n # res = db_publications.find({\"id\": new_id}).limit(1).next()\n # except:\n # res = None\n # return res\n\n url = BaseConfig.DATAESR_PUBLICATIONS_URL\n url += '?where={{\"id\":\"{}\"}}'.format(new_id)\n r = requests.get(url)\n if r.status_code == 200:\n res = r.json()['data']\n else:\n res = []\n if len(res) > 1:\n print(\"ERROR more than one id - SHOULD NOT HAPPEN !!\")\n return res[0]\n elif len(res) == 1:\n return res[0]\n else:\n return None","def find_one():\n fmter.tpl._straightline(\"one document\", 100)\n result = users.find_one({})\n print(type(result))\n ppt(result)\n \n fmter.tpl._straightline(\"none result\", 100)\n result = users.find_one({\"_id\": 100})\n print(type(result))\n ppt(result)","def retrieve_document(self, portal_name, content_id):\n r = requests.get(\n '/'.join([self.base_url, self.DOCUMENTS_ENDPOINT, portal_name, str(content_id)]))\n return r.json()","def doc_id(self):\n return self._id","def get_document(self, url: str) -> Optional[Document]:\n return self._index.get(url, None)","def document_view(index_name, doc_type, doc_id):\n resp = es.get(index=index_name, doc_type=doc_type, id=doc_id)\n document = resp[\"_source\"]\n print(document)","def GetDocument(self, *args, **kwargs):\n pass","def document(self, **kw):\r\n \r\n for p in self.documents(**kw):\r\n return p","def get(self, id):\n if id == 'body':\n return document.body\n else:\n return self.instances[id]","def test_document_by_id_endpoint(self):\n\n # Grab a document by the ID.\n federal_document = self.federal_client.document_by_id(\n document_id='2020-17469',\n fields='all'\n )\n\n # Make sure we have a response.\n self.assertIsNotNone(federal_document)\n\n # And the document ID matches.\n self.assertEqual(federal_document['document_number'], '2020-17469')","def get_document(self):\n return self.document","def get(self, _id):","def get_document_from_xtracta(document_id):\n response = None\n response = requests.post(XTRACTA['url']+\"documents\",\n data={\"submit\":\"Submit\",\\\n \"api_key\":XTRACTA['key'],\\\n \"document_id\":document_id})\n return response","def get_document(self, metadata_field, field_val):\n\n if metadata_field not in self.metadata_fields:\n raise MissingMetadataError([metadata_field])\n\n if metadata_field == \"date\":\n field_val = int(field_val)\n\n for document in self.documents:\n if getattr(document, metadata_field) == field_val:\n return document\n\n raise ValueError(\"Document not found\")","def get_doc(self, item_id, id_field=\"_id\", **kwargs):\r\n\r\n lg = logging.getLogger(\"%s.%s\" % (self.ln, inspect.stack()[0][3]))\r\n lg.setLevel(self.log_level)\r\n\r\n args = inspect.getargvalues(inspect.currentframe())[3]\r\n lg.debug(\"\\n****** Args *****:\\n%s\",\r\n pp.pformat(args))\r\n\r\n es = kwargs.get(\"es\",self.es)\r\n doc_type = kwargs.get(\"doc_type\", self.doc_type)\r\n if id_field == \"_id\":\r\n lg.debug(\"*** _id lookup: index: %s item_id: %s\",\r\n self.es_index,\r\n item_id)\r\n result = es.get(index=self.es_index,\r\n id=item_id)\r\n else:\r\n dsl = {\r\n \"query\": {\r\n \"constant_score\": {\r\n \"filter\": {\r\n \"term\": { id_field: item_id }\r\n }\r\n }\r\n }\r\n }\r\n lg.debug(\"*** id_field lookup: index: %s item_id: %s \\nDSL: %s\",\r\n self.es_index,\r\n item_id,\r\n pp.pformat(dsl))\r\n result = es.search(index=self.es_index,\r\n doc_type=doc_type,\r\n body=dsl)\r\n result = first(result.get(\"hits\",{}).get(\"hits\",[]))\r\n lg.debug(\"\\tresult:\\n%s\", pp.pformat(result))\r\n return result","def fetch_search_document(self, index):\n assert self.pk, \"Object must have a primary key before being indexed.\"\n client = get_client()\n return client.get(\n index=index,\n doc_type=self.search_doc_type,\n id=self.pk\n )","def getDocument(cred, documentPath):\n url = cred.base_url + \"documents/\" + documentPath\n\n return makeRequest(cred, url, 'GET')","def get(self, id, model_type=None):\n # If collection is not specified, use the collection when this client is\n if not model_type:\n collection = self._collection\n else:\n collection = self._db[model_type]\n\n print 'mongo.get(): id={}'.format(id)\n if id:\n obj = collection.find_one({'_id': ObjectId(id)})\n if not obj:\n raise DbProviderError(\"DB record for {} is not found\".format(id))\n obj['_id'] = str(obj['_id'])\n else:\n obj = {}\n return obj","def getDocumentId(self): #$NON-NLS-1$\r","def get_request(self, request_id):\n doc_id = bson.objectid.ObjectId(request_id)\n coll = self._db.get_collection(COLLECTION_REQUEST)\n doc = coll.find_one(filter={\n '_id': doc_id\n })\n return doc","def get(cls, db, id):\n doc = cls.collection(db).find_one(filter={ '_id': ObjectId(id) })\n return Todo(**doc)","def get_id(doc = None, cursor = None):\n\tif cursor is None and doc is not None:\n\t\treturn doc['id']\n\telif doc is None and cursor is not None:\n\t\tallids = list()\n\t\tfor thisdoc in cursor:\n\t\t\tallids.append(thisdoc['id'])\n\t\treturn allids\n\telse:\n\t\tprint \"Supply any one argument only!\"","def getFirstDocument(address=\"\", database=\"\", collection=\"\"):\n\n document = []\n client = connectMongo(address, database, collection)\n\n document.append(client.find_one())\n\n return document","def query_by_id(doc_id):\n with Con(db = os.environ.get(\"MONGO_DB\"), host = os.environ.get(\"MONGO_URL\"), port = int(os.environ.get(\"MONGO_PORT\")), col = os.environ.get(\"MONGO_COL\")) as col:\n doc = col.find_one({'pmid': doc_id})\n doc_text = [v for k,v in doc['abstract'].iteritems()]\n doc_text = ' '.join(doc_text) + doc['title']\n return doc_text","def documentdetail(request, docid):\n\tdocument = get_object_or_404(Document, pk=docid)\n\tif not request.user.has_perm('documents.view_document', obj=document):\n\t\treturn HttpResponse(loader.render_to_string('401.html',\n\t\t\tRequestContext(request, {'error_message':\n\t\t\t\t_(\"You are not allowed to view this document.\")})), status=401)\n\ttry:\n\t\trelated = document.content_type.get_object_for_this_type(id=document.object_id)\n\texcept:\n\t\trelated = ''\n\n\treturn render_to_response(\"documents/docinfo.html\", RequestContext(request, {\n\t\t'permissions_json': json.dumps(_perms_info(document, DOCUMENT_LEV_NAMES)),\n\t\t'document': document,\n\t\t'imgtypes': imgtypes,\n\t\t'related': related\n\t}))","def get_document_detail(\n self,\n project_id: int,\n doc_id: int\n ) -> requests.models.Response:\n return self.get(\n 'v1/projects/{project_id}/docs/{doc_id}'.format(\n project_id=project_id,\n doc_id=doc_id\n )\n )","def get_id(self):\n return self[\"_id\"]","def doc_id(self):\n return self.properties.get('DocId', None)","async def get(self, id=None, alias=None, **kwargs):\n\n from jetengine import Q\n\n if id is None and not kwargs:\n raise RuntimeError(\"Either an id or a filter must be provided to get\")\n\n if id is not None:\n if not isinstance(id, ObjectId):\n id = ObjectId(id)\n\n filters = {\"_id\": id}\n else:\n filters = Q(**kwargs)\n filters = self.get_query_from_filters(filters)\n\n instance = await self.coll(alias).find_one(filters, projection=self._loaded_fields.to_query(self.__klass__))\n if instance is None:\n return None\n else:\n doc = self.__klass__.from_son(\n instance,\n # if _loaded_fields is not empty then\n # document is partly loaded\n _is_partly_loaded=bool(self._loaded_fields),\n # set projections for references (if any)\n _reference_loaded_fields=self._reference_loaded_fields,\n )\n if self.is_lazy:\n return doc\n else:\n await doc.load_references()\n return doc","def get(self, request, pk):\n document = self.get_object(pk)\n\n if request.user.has_perm(Access.PERM_READ, document):\n serializer = DocumentSerializer(document)\n return Response(serializer.data)\n\n return Response(\n status=status.HTTP_403_FORBIDDEN\n )","def get_document_by_legacy_recid(legacy_recid):\n search = DocumentSearch().query(\n 'bool',\n filter=[\n Q('term', legacy_recid=legacy_recid),\n ]\n )\n result = search.execute()\n hits_total = result.hits.total if lt_es7 else result.hits.total.value\n if not result.hits or hits_total < 1:\n click.secho(\n 'no document found with legacy recid {}'.format(legacy_recid),\n fg='red')\n raise DocumentMigrationError(\n 'no document found with legacy recid {}'.format(legacy_recid))\n elif hits_total > 1:\n click.secho(\n 'no document found with legacy recid {}'.format(legacy_recid),\n fg='red')\n raise DocumentMigrationError(\n 'found more than one document with recid {}'.format(legacy_recid))\n else:\n click.secho(\n '! document found with legacy recid {}'.format(legacy_recid),\n fg='green')\n return Document.get_record_by_pid(result.hits[0].pid)","def get_document_or_error(document_id):\n\ttry:\n\t\tdocument = DocumentChat.objects.get(pk=document_id)\n\texcept DocumentChat.DoesNotExist:\n\t\traise ClientError(\"ROOM_INVALID\", \"Invalid room.\")\n\treturn document","def get_document_and_list_id_by_name(update, name_or_id):\n document = get_document_by_name(update, name_or_id)\n if not document:\n return None, None\n\n logging.info('Document id: {0}'.format(document['id']))\n\n sc_web = SmartCATWeb(SMARTCAT_SESSION_FILE, SMARTCAT_EMAIL, SMARTCAT_PASSWORD,\n SMARTCAT_API_USERNAME, SMARTCAT_API_PASSWORD)\n\n remove_lang = re.compile('_.{2}$')\n response = sc_web.create_document_list_id(remove_lang.sub('', document['id']))\n list_id = json.loads(response.content, encoding='utf-8')\n if not list_id:\n logging.warning('List id not found')\n update.message.reply_text(NOTHING_FOUND)\n return document, None\n\n return document, list_id","def get_object(self):\n pk = self.kwargs.get('id')\n return get_object_or_404(Book, pk=pk)","async def get(self, collection: str, obj_id) -> dict:\n\t\tpass","def _get_doc(results, index):\n return results[index]","def get_doc(self, dtype, identity):\n if dtype == 'pii':\n doc = FullDoc(sd_pii = identity)\n elif dtype == 'doi':\n doc= FullDoc(doi = identity)\n\n if doc.read(ElsClient(self.API_list[0])):\n pass\n else:\n print (\"Read document failed.\")\n\n return doc","def open_document(self, id, **kw):\r\n\r\n #Getting the document directory path\r\n document_directory_path = request.env['npa.document'].get_document_directory_path()\r\n\r\n #Getting Document Record\r\n document_rec = request.env['npa.document'].search([('id','=',int(id))])\r\n #Checking if the file exists, and then fetching the document.\r\n if os.path.exists(document_rec.file_loc):\r\n with open(document_rec.file_loc, 'rb') as doc_file:\r\n filecontent = doc_file.read()\r\n if not filecontent:\r\n return request.not_found()\r\n else:\r\n if document_rec.file_name[-3:] == 'pdf':\r\n #Return the file and filename to the browser.\r\n return request.make_response(filecontent,\r\n [('Content-Type', 'application/pdf'),\r\n ('Content-Disposition', 'inline')])\r\n else:\r\n return request.make_response(filecontent,\r\n [('Content-Type', 'attachment'),\r\n ('Content-Disposition', 'inline')])\r\n else:\r\n msg = 'File document {0} not found in NFS server. Please check the file or upload again.'.format(document_rec.file_loc)\r\n return request.not_found(msg)","def find_index_with_document(document_id): \n client, index_name = connection_es()\n res = client.search(index = index_name+\"*\")\n\n for record in res['hits']['hits']:\n if record['_id'] in document_id:\n return record['_index']","def get(self, *args):\n return self.docs.get(*args)","def get_doc_from_MP(mp_id):\n apr=mpr.get_doc(mp_id)\n return apr","def find_by_id(cls, object_id):\n try:\n return mongo_db[cls.__collection__].find_one({\"_id\": ObjectId(object_id)})\n except InvalidId:\n # TODO: Log the exception\n print('Invalid bson id: {}'.format(object_id))\n return None","def updateDocument(self, document):\n data = self.updateDocumentAll([document])\n try:\n return data[0]\n except: pass","def article_by_id(self, id):\n return self.es.get(index=self.index, doc_type=self.doc_type, id=id)","def get_from_sources(self,index,doc_type,document_id):\n return self.sources.get(index, {}).get(doc_type, {}).get(document_id,{})","def get_object(self, id_):\n return self._objects.get(id_, None)","def get_task(task_id):\n return db.task.find_one({'_id': ObjectId(task_id)})","def test_select_id(self, document):\n assert document.select({\"_id\": 1}) == {\"_id\": 1}","def createDocument(self, document):\n data = self.createDocumentAll([document])\n try:\n return data[0]\n except: pass","def get_document(document_id: Optional[str] = None,\n location: Optional[str] = None,\n project: Optional[str] = None,\n opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDocumentResult:\n __args__ = dict()\n __args__['documentId'] = document_id\n __args__['location'] = location\n __args__['project'] = project\n opts = pulumi.InvokeOptions.merge(_utilities.get_invoke_opts_defaults(), opts)\n __ret__ = pulumi.runtime.invoke('google-native:contentwarehouse/v1:getDocument', __args__, opts=opts, typ=GetDocumentResult).value\n\n return AwaitableGetDocumentResult(\n cloud_ai_document=pulumi.get(__ret__, 'cloud_ai_document'),\n content_category=pulumi.get(__ret__, 'content_category'),\n create_time=pulumi.get(__ret__, 'create_time'),\n creator=pulumi.get(__ret__, 'creator'),\n display_name=pulumi.get(__ret__, 'display_name'),\n display_uri=pulumi.get(__ret__, 'display_uri'),\n disposition_time=pulumi.get(__ret__, 'disposition_time'),\n document_schema_name=pulumi.get(__ret__, 'document_schema_name'),\n inline_raw_document=pulumi.get(__ret__, 'inline_raw_document'),\n name=pulumi.get(__ret__, 'name'),\n plain_text=pulumi.get(__ret__, 'plain_text'),\n properties=pulumi.get(__ret__, 'properties'),\n raw_document_file_type=pulumi.get(__ret__, 'raw_document_file_type'),\n raw_document_path=pulumi.get(__ret__, 'raw_document_path'),\n reference_id=pulumi.get(__ret__, 'reference_id'),\n text_extraction_disabled=pulumi.get(__ret__, 'text_extraction_disabled'),\n text_extraction_enabled=pulumi.get(__ret__, 'text_extraction_enabled'),\n title=pulumi.get(__ret__, 'title'),\n update_time=pulumi.get(__ret__, 'update_time'),\n updater=pulumi.get(__ret__, 'updater'))","def test_get_document(index_with_documents):\n response = index_with_documents().get_document(\"500682\")\n assert isinstance(response, Document)\n assert hasattr(response, \"title\")\n assert response.title == \"The Highwaymen\"","def doc(obj):\n return Documentation.fromObject(obj).first","def resourceDocumentId(self, resource: Resource) -> str:","def get_doc(ds, idx):\n rtn = ds[idx]\n if isinstance(rtn, dict):\n rtn = rtn['text']\n return rtn","def find_doc(self, doc_type, property_name, property_value):\n try:\n self.client.connect()\n db = self.client[self.db_name]\n selector = {\n '_id': {'$gt': 0},\n 'type': doc_type,\n property_name: property_value\n }\n query = Query(db, selector=selector)\n for doc in query()['docs']:\n return doc\n return None\n finally:\n self.client.disconnect()","def get(self, docid):\n file = os.path.join(self.dirname, docid)\n with open(file,'r',encoding='utf-8') as f:\n text = f.read()\n return text","def get_log(ident):\n return logs_col.find_one({\"_id\": ObjectId(ident)})","def get_one(self, index, *args, **kw):\n person = M.People.query.get(index=index)\n log.debug('person {}'.format(person))\n if(person):\n kw['_id'] = person._id\n return super(PeopleAPIController, self).get_one(*args, **kw)","def get_document(self, doc_uri: str) -> Document:\n return self._docs.get(doc_uri) or self._create_document(doc_uri)","def get_doc_text(self, doc_id):\n cursor = self.connection.cursor()\n cursor.execute(\n \"SELECT text FROM documents WHERE id = ?\",\n (doc_id,)\n )\n result = cursor.fetchone()\n cursor.close()\n return result if result is None else result[0]","def identifier(self) -> str:\n return self.doc['id']","def find_by_doc_reg_num(cls, doc_reg_num: str):\n document = None\n if doc_reg_num:\n try:\n document = cls.query.filter(Db2Document.document_reg_id == doc_reg_num).one_or_none()\n except Exception as db_exception: # noqa: B902; return nicer error\n current_app.logger.error('Db2Document.find_by_doc_reg_num exception: ' + str(db_exception))\n raise DatabaseException(db_exception)\n if document:\n document.strip()\n return document","def retrieve(self, document_id: str) -> Fulltext:\n if not document_id: # This could use further elaboration.\n raise ValueError(\"Invalid value for document_id\")\n\n try:\n response = requests.get(urljoin(self.endpoint, document_id))\n except requests.exceptions.SSLError as ex:\n raise IOError(\"SSL failed: %s\" % ex)\n\n if response.status_code != HTTPStatus.OK:\n raise IOError(\n \"%s: could not retrieve fulltext: %i\"\n % (document_id, response.status_code)\n )\n try:\n data = response.json()\n except json.decoder.JSONDecodeError as ex:\n raise IOError(\n \"%s: could not decode response: %s\" % (document_id, ex)\n ) from ex\n return Fulltext(**data) # type: ignore\n # See https://github.com/python/mypy/issues/3937"],"string":"[\n \"def get_document_by_id(document_id):\\n return Documents.query.filter_by(id=document_id).first()\",\n \"def get_document(self, docid):\\n raise NotImplementedError\",\n \"def obj_get(self, request=None, **kwargs):\\n return Document(self.get_collection(request).find_one({\\n \\\"_id\\\": ObjectId(kwargs.get(\\\"pk\\\"))\\n }))\",\n \"def get_document(name):\\n document = [d for d in documents if d.name == name]\\n if len(document) > 0:\\n return document[0]\",\n \"def get(self, index, id):\\n url = f'{self.host}{index}/_doc/{id}'\\n resp = requests.get(url)\\n return resp.json()\",\n \"def document(self, document_id):\\r\\n return doc.Document(self, document_id)\",\n \"def get_document_or_404(id, db=None):\\n try:\\n return dbs[DEFAULT_DATABASE if db is None else db][id]\\n except ResourceNotFound:\\n raise Http404\",\n \"def get_document(eid, session: CondorSession) -> Response:\\n document = Document.find_by_eid(session, eid)\\n if not document:\\n return Response(\\n {'message': 'The especified eid is not found on database'},\\n status=404,\\n )\\n return Response(sc.Document(document))\",\n \"def get_document_by_id(self, index: str, doc_id: str) -> Optional[Dict[str, Any]]:\\n try:\\n return self.__client__.get(index=index, id=doc_id)\\n except elasticsearch.exceptions.NotFoundError:\\n return None\",\n \"def get_doc(doc_id):\\n queue = get_doc_queue(app.config)\\n data = queue.get_by_id(doc_id)\\n if data:\\n return jsonify(doc=data)\\n return jsonify(err=f\\\"{doc_id} not found\\\"), 404\",\n \"def get_document(obj):\\n try:\\n return ES.get(\\n index=obj.get_index_name(), doc_type=obj.get_document_type(), id=obj.pk)\\n except NotFoundError:\\n raise DocumentNotFound(obj.get_index_name(), obj.pk)\",\n \"def retrieve(document_id: str) -> Fulltext:\\n return current_session().retrieve(document_id)\",\n \"def get(self, _id):\\n try:\\n doc = self._db[_id]\\n # For speed testing\\n del self._db[_id]\\n except KeyError:\\n return None\\n else:\\n return self._parse_doc(doc)\",\n \"def get_by_id(key):\\n key = KeyModel(key)\\n key.validate()\\n return {\\\"text\\\": repository.get_doc(COLLECTION_NAME, key.to_dict())}\",\n \"def one(self):\\n try:\\n return self[0]\\n except IndexError:\\n raise self.document.DoesNotExist\",\n \"def get_single_data(document_id):\\n data = collection.find_one({'_id': ObjectId(document_id)})\\n return data\",\n \"def get(self, query_data=None, id_obj=None):\\n if id_obj:\\n return self.collection.find_one({'_id': id_obj})\\n return self.collection.find_one(query_data)\",\n \"def find_by_id(cls, doc_id: str):\\n document = None\\n if doc_id:\\n try:\\n document = cls.query.get(doc_id)\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_id exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def get_document(self, doc_id, options=None):\\n path = urllib.quote_plus(str(doc_id))\\n try:\\n result = self.request(path, pylastica.request.Request.GET, query=options).data\\n except pylastica.exception.ResponseException:\\n raise pylastica.exception.NotFoundException(\\\"Document with id %s not found.\\\" % doc_id)\\n if result['found'] is None or result['found'] == '' or not result['found']:\\n raise pylastica.exception.NotFoundException(\\\"Document with id %s not found.\\\" % doc_id)\\n data = result['_source'] if '_source' in result else {}\\n document = pylastica.document.Document(doc_id, data, self.name, self.index)\\n document.version = result['_version']\\n return document\",\n \"def getDocument(self, key):\\n data = self.client.get(self.name +\\\"/_all_docs\\\", {\\n \\\"include_docs\\\": True,\\n \\\"key\\\" : \\\"\\\\\\\"%s\\\\\\\"\\\" % util.quote(key),\\n }).getBodyData()\\n\\n try:\\n return data[\\\"rows\\\"][0]\\n except: pass\",\n \"def _get_doc_key(self, doc_id, key):\\n cursor = self.connection.cursor()\\n cursor.execute(\\n \\\"SELECT {} FROM documents WHERE id = ?\\\".format(key),\\n (normalize(doc_id),)\\n )\\n result = cursor.fetchone()\\n cursor.close()\\n return result if result is None else result[0]\",\n \"def view_document(self, database, collection, _id):\\n r = self.__get_response(settings.VIW_DOC,\\n {\\\"db\\\": database, \\\"col\\\": collection, \\\"id\\\": str(_id)})\\n if r[\\\"status\\\"] == 200:\\n return r[\\\"result\\\"]\\n raise Exception(r[\\\"result\\\"][\\\"message\\\"])\",\n \"def retrieveById(self, doc_id=None):\\n obj = self.find_one({'_id': doc_id if id else self.get('_id')})\\n if obj:\\n self._import(obj)\\n return True\\n return False\",\n \"def get_document(self, type: Type, id: str,\\n key: Optional[str] = None) -> Dict[str, Any]:\\n document = None\\n\\n if report := self.client.document(f'{type}/{id}'):\\n document = report.get().to_dict()\\n\\n return document.get(key) if key else document\",\n \"def get_document(self, doc_id: int) -> Optional[Users]:\\n try:\\n doc = self.session.query(CandidatesDocuments).get(doc_id)\\n\\n return doc\\n except Exception as excpt:\\n self.session.rollback()\\n print(f'Could not get doc: {excpt}')\\n\\n return None\",\n \"def get(self, document_id):\\n document_id = document_id.strip()\\n if not document_id:\\n return None\\n\\n connection = self.__get_database_connection()\\n response = self.__make_request(connection, '/%s/%s' % (self.database_name, document_id))\\n return response\",\n \"def get_doc_id(self):\\n return self.__doc_id\",\n \"def _id(self, document):\\n pass\",\n \"def find_document(self):\\n pass\",\n \"def get_document(self, docid):\\n try:\\n return self.sql_session.query(Document).get(docid)\\n except OperationalError:\\n raise IOError(\\\"Sorry, this database is incompatible with the \\\"\\n \\\"current version of Luminoso. If you want, you can \\\"\\n \\\"delete the model directory and start again.\\\")\",\n \"def get_document_by_name(update, name_or_id):\\n sc_api = SmartCAT(SMARTCAT_API_USERNAME, SMARTCAT_API_PASSWORD)\\n try:\\n document = sc_api.project.get_document_by_name(SMARTCAT_PROJECT_ID, name_or_id)\\n except SmartcatException as e:\\n logging.error('Error getting document: {0} {1}'.format(e.code, e.message))\\n update.message.reply_text(SHIT_HAPPENS)\\n return None\\n\\n if not document:\\n logging.warning('Document not found')\\n update.message.reply_text(NOTHING_FOUND)\\n return None\\n\\n return document\",\n \"def get_document_by_name(label, doc_type):\\n return Documents.query.filter_by(type=doc_type, label=label).first()\",\n \"def document(self):\\n query = {\\\"_id\\\": ObjectId(self.document_id)}\\n return Document(get_collection(\\\"documents\\\").find_one(query))\",\n \"def find_by_doc_id(cls, doc_reg_id: str):\\n document = None\\n if doc_reg_id:\\n try:\\n document = cls.query.filter(Db2Document.id == doc_reg_id).one_or_none()\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_doc_id exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def get_object(id):\",\n \"def get_document(self, *args, **kwargs):\\n return self._documents_manager.get_document(*args, **kwargs)\",\n \"def userDocumentId(self, id: str) -> str:\",\n \"def get_named_document(self, entity, name):\\n view = self.db.view(\\\"%s/name\\\" % entity, include_docs=True)\\n result = view[name]\\n if len(result) != 1:\\n raise ValueError(\\\"no such %s document '%s'\\\" % (entity, name))\\n return result.rows[0].doc\",\n \"def get_publication_from_id_in_db(new_id: str) -> Union[None, Dict]:\\n\\n # db_publications = app.data.driver.db[\\\"publications\\\"]\\n # try:\\n # res = db_publications.find({\\\"id\\\": new_id}).limit(1).next()\\n # except:\\n # res = None\\n # return res\\n\\n url = BaseConfig.DATAESR_PUBLICATIONS_URL\\n url += '?where={{\\\"id\\\":\\\"{}\\\"}}'.format(new_id)\\n r = requests.get(url)\\n if r.status_code == 200:\\n res = r.json()['data']\\n else:\\n res = []\\n if len(res) > 1:\\n print(\\\"ERROR more than one id - SHOULD NOT HAPPEN !!\\\")\\n return res[0]\\n elif len(res) == 1:\\n return res[0]\\n else:\\n return None\",\n \"def find_one():\\n fmter.tpl._straightline(\\\"one document\\\", 100)\\n result = users.find_one({})\\n print(type(result))\\n ppt(result)\\n \\n fmter.tpl._straightline(\\\"none result\\\", 100)\\n result = users.find_one({\\\"_id\\\": 100})\\n print(type(result))\\n ppt(result)\",\n \"def retrieve_document(self, portal_name, content_id):\\n r = requests.get(\\n '/'.join([self.base_url, self.DOCUMENTS_ENDPOINT, portal_name, str(content_id)]))\\n return r.json()\",\n \"def doc_id(self):\\n return self._id\",\n \"def get_document(self, url: str) -> Optional[Document]:\\n return self._index.get(url, None)\",\n \"def document_view(index_name, doc_type, doc_id):\\n resp = es.get(index=index_name, doc_type=doc_type, id=doc_id)\\n document = resp[\\\"_source\\\"]\\n print(document)\",\n \"def GetDocument(self, *args, **kwargs):\\n pass\",\n \"def document(self, **kw):\\r\\n \\r\\n for p in self.documents(**kw):\\r\\n return p\",\n \"def get(self, id):\\n if id == 'body':\\n return document.body\\n else:\\n return self.instances[id]\",\n \"def test_document_by_id_endpoint(self):\\n\\n # Grab a document by the ID.\\n federal_document = self.federal_client.document_by_id(\\n document_id='2020-17469',\\n fields='all'\\n )\\n\\n # Make sure we have a response.\\n self.assertIsNotNone(federal_document)\\n\\n # And the document ID matches.\\n self.assertEqual(federal_document['document_number'], '2020-17469')\",\n \"def get_document(self):\\n return self.document\",\n \"def get(self, _id):\",\n \"def get_document_from_xtracta(document_id):\\n response = None\\n response = requests.post(XTRACTA['url']+\\\"documents\\\",\\n data={\\\"submit\\\":\\\"Submit\\\",\\\\\\n \\\"api_key\\\":XTRACTA['key'],\\\\\\n \\\"document_id\\\":document_id})\\n return response\",\n \"def get_document(self, metadata_field, field_val):\\n\\n if metadata_field not in self.metadata_fields:\\n raise MissingMetadataError([metadata_field])\\n\\n if metadata_field == \\\"date\\\":\\n field_val = int(field_val)\\n\\n for document in self.documents:\\n if getattr(document, metadata_field) == field_val:\\n return document\\n\\n raise ValueError(\\\"Document not found\\\")\",\n \"def get_doc(self, item_id, id_field=\\\"_id\\\", **kwargs):\\r\\n\\r\\n lg = logging.getLogger(\\\"%s.%s\\\" % (self.ln, inspect.stack()[0][3]))\\r\\n lg.setLevel(self.log_level)\\r\\n\\r\\n args = inspect.getargvalues(inspect.currentframe())[3]\\r\\n lg.debug(\\\"\\\\n****** Args *****:\\\\n%s\\\",\\r\\n pp.pformat(args))\\r\\n\\r\\n es = kwargs.get(\\\"es\\\",self.es)\\r\\n doc_type = kwargs.get(\\\"doc_type\\\", self.doc_type)\\r\\n if id_field == \\\"_id\\\":\\r\\n lg.debug(\\\"*** _id lookup: index: %s item_id: %s\\\",\\r\\n self.es_index,\\r\\n item_id)\\r\\n result = es.get(index=self.es_index,\\r\\n id=item_id)\\r\\n else:\\r\\n dsl = {\\r\\n \\\"query\\\": {\\r\\n \\\"constant_score\\\": {\\r\\n \\\"filter\\\": {\\r\\n \\\"term\\\": { id_field: item_id }\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n lg.debug(\\\"*** id_field lookup: index: %s item_id: %s \\\\nDSL: %s\\\",\\r\\n self.es_index,\\r\\n item_id,\\r\\n pp.pformat(dsl))\\r\\n result = es.search(index=self.es_index,\\r\\n doc_type=doc_type,\\r\\n body=dsl)\\r\\n result = first(result.get(\\\"hits\\\",{}).get(\\\"hits\\\",[]))\\r\\n lg.debug(\\\"\\\\tresult:\\\\n%s\\\", pp.pformat(result))\\r\\n return result\",\n \"def fetch_search_document(self, index):\\n assert self.pk, \\\"Object must have a primary key before being indexed.\\\"\\n client = get_client()\\n return client.get(\\n index=index,\\n doc_type=self.search_doc_type,\\n id=self.pk\\n )\",\n \"def getDocument(cred, documentPath):\\n url = cred.base_url + \\\"documents/\\\" + documentPath\\n\\n return makeRequest(cred, url, 'GET')\",\n \"def get(self, id, model_type=None):\\n # If collection is not specified, use the collection when this client is\\n if not model_type:\\n collection = self._collection\\n else:\\n collection = self._db[model_type]\\n\\n print 'mongo.get(): id={}'.format(id)\\n if id:\\n obj = collection.find_one({'_id': ObjectId(id)})\\n if not obj:\\n raise DbProviderError(\\\"DB record for {} is not found\\\".format(id))\\n obj['_id'] = str(obj['_id'])\\n else:\\n obj = {}\\n return obj\",\n \"def getDocumentId(self): #$NON-NLS-1$\\r\",\n \"def get_request(self, request_id):\\n doc_id = bson.objectid.ObjectId(request_id)\\n coll = self._db.get_collection(COLLECTION_REQUEST)\\n doc = coll.find_one(filter={\\n '_id': doc_id\\n })\\n return doc\",\n \"def get(cls, db, id):\\n doc = cls.collection(db).find_one(filter={ '_id': ObjectId(id) })\\n return Todo(**doc)\",\n \"def get_id(doc = None, cursor = None):\\n\\tif cursor is None and doc is not None:\\n\\t\\treturn doc['id']\\n\\telif doc is None and cursor is not None:\\n\\t\\tallids = list()\\n\\t\\tfor thisdoc in cursor:\\n\\t\\t\\tallids.append(thisdoc['id'])\\n\\t\\treturn allids\\n\\telse:\\n\\t\\tprint \\\"Supply any one argument only!\\\"\",\n \"def getFirstDocument(address=\\\"\\\", database=\\\"\\\", collection=\\\"\\\"):\\n\\n document = []\\n client = connectMongo(address, database, collection)\\n\\n document.append(client.find_one())\\n\\n return document\",\n \"def query_by_id(doc_id):\\n with Con(db = os.environ.get(\\\"MONGO_DB\\\"), host = os.environ.get(\\\"MONGO_URL\\\"), port = int(os.environ.get(\\\"MONGO_PORT\\\")), col = os.environ.get(\\\"MONGO_COL\\\")) as col:\\n doc = col.find_one({'pmid': doc_id})\\n doc_text = [v for k,v in doc['abstract'].iteritems()]\\n doc_text = ' '.join(doc_text) + doc['title']\\n return doc_text\",\n \"def documentdetail(request, docid):\\n\\tdocument = get_object_or_404(Document, pk=docid)\\n\\tif not request.user.has_perm('documents.view_document', obj=document):\\n\\t\\treturn HttpResponse(loader.render_to_string('401.html',\\n\\t\\t\\tRequestContext(request, {'error_message':\\n\\t\\t\\t\\t_(\\\"You are not allowed to view this document.\\\")})), status=401)\\n\\ttry:\\n\\t\\trelated = document.content_type.get_object_for_this_type(id=document.object_id)\\n\\texcept:\\n\\t\\trelated = ''\\n\\n\\treturn render_to_response(\\\"documents/docinfo.html\\\", RequestContext(request, {\\n\\t\\t'permissions_json': json.dumps(_perms_info(document, DOCUMENT_LEV_NAMES)),\\n\\t\\t'document': document,\\n\\t\\t'imgtypes': imgtypes,\\n\\t\\t'related': related\\n\\t}))\",\n \"def get_document_detail(\\n self,\\n project_id: int,\\n doc_id: int\\n ) -> requests.models.Response:\\n return self.get(\\n 'v1/projects/{project_id}/docs/{doc_id}'.format(\\n project_id=project_id,\\n doc_id=doc_id\\n )\\n )\",\n \"def get_id(self):\\n return self[\\\"_id\\\"]\",\n \"def doc_id(self):\\n return self.properties.get('DocId', None)\",\n \"async def get(self, id=None, alias=None, **kwargs):\\n\\n from jetengine import Q\\n\\n if id is None and not kwargs:\\n raise RuntimeError(\\\"Either an id or a filter must be provided to get\\\")\\n\\n if id is not None:\\n if not isinstance(id, ObjectId):\\n id = ObjectId(id)\\n\\n filters = {\\\"_id\\\": id}\\n else:\\n filters = Q(**kwargs)\\n filters = self.get_query_from_filters(filters)\\n\\n instance = await self.coll(alias).find_one(filters, projection=self._loaded_fields.to_query(self.__klass__))\\n if instance is None:\\n return None\\n else:\\n doc = self.__klass__.from_son(\\n instance,\\n # if _loaded_fields is not empty then\\n # document is partly loaded\\n _is_partly_loaded=bool(self._loaded_fields),\\n # set projections for references (if any)\\n _reference_loaded_fields=self._reference_loaded_fields,\\n )\\n if self.is_lazy:\\n return doc\\n else:\\n await doc.load_references()\\n return doc\",\n \"def get(self, request, pk):\\n document = self.get_object(pk)\\n\\n if request.user.has_perm(Access.PERM_READ, document):\\n serializer = DocumentSerializer(document)\\n return Response(serializer.data)\\n\\n return Response(\\n status=status.HTTP_403_FORBIDDEN\\n )\",\n \"def get_document_by_legacy_recid(legacy_recid):\\n search = DocumentSearch().query(\\n 'bool',\\n filter=[\\n Q('term', legacy_recid=legacy_recid),\\n ]\\n )\\n result = search.execute()\\n hits_total = result.hits.total if lt_es7 else result.hits.total.value\\n if not result.hits or hits_total < 1:\\n click.secho(\\n 'no document found with legacy recid {}'.format(legacy_recid),\\n fg='red')\\n raise DocumentMigrationError(\\n 'no document found with legacy recid {}'.format(legacy_recid))\\n elif hits_total > 1:\\n click.secho(\\n 'no document found with legacy recid {}'.format(legacy_recid),\\n fg='red')\\n raise DocumentMigrationError(\\n 'found more than one document with recid {}'.format(legacy_recid))\\n else:\\n click.secho(\\n '! document found with legacy recid {}'.format(legacy_recid),\\n fg='green')\\n return Document.get_record_by_pid(result.hits[0].pid)\",\n \"def get_document_or_error(document_id):\\n\\ttry:\\n\\t\\tdocument = DocumentChat.objects.get(pk=document_id)\\n\\texcept DocumentChat.DoesNotExist:\\n\\t\\traise ClientError(\\\"ROOM_INVALID\\\", \\\"Invalid room.\\\")\\n\\treturn document\",\n \"def get_document_and_list_id_by_name(update, name_or_id):\\n document = get_document_by_name(update, name_or_id)\\n if not document:\\n return None, None\\n\\n logging.info('Document id: {0}'.format(document['id']))\\n\\n sc_web = SmartCATWeb(SMARTCAT_SESSION_FILE, SMARTCAT_EMAIL, SMARTCAT_PASSWORD,\\n SMARTCAT_API_USERNAME, SMARTCAT_API_PASSWORD)\\n\\n remove_lang = re.compile('_.{2}$')\\n response = sc_web.create_document_list_id(remove_lang.sub('', document['id']))\\n list_id = json.loads(response.content, encoding='utf-8')\\n if not list_id:\\n logging.warning('List id not found')\\n update.message.reply_text(NOTHING_FOUND)\\n return document, None\\n\\n return document, list_id\",\n \"def get_object(self):\\n pk = self.kwargs.get('id')\\n return get_object_or_404(Book, pk=pk)\",\n \"async def get(self, collection: str, obj_id) -> dict:\\n\\t\\tpass\",\n \"def _get_doc(results, index):\\n return results[index]\",\n \"def get_doc(self, dtype, identity):\\n if dtype == 'pii':\\n doc = FullDoc(sd_pii = identity)\\n elif dtype == 'doi':\\n doc= FullDoc(doi = identity)\\n\\n if doc.read(ElsClient(self.API_list[0])):\\n pass\\n else:\\n print (\\\"Read document failed.\\\")\\n\\n return doc\",\n \"def open_document(self, id, **kw):\\r\\n\\r\\n #Getting the document directory path\\r\\n document_directory_path = request.env['npa.document'].get_document_directory_path()\\r\\n\\r\\n #Getting Document Record\\r\\n document_rec = request.env['npa.document'].search([('id','=',int(id))])\\r\\n #Checking if the file exists, and then fetching the document.\\r\\n if os.path.exists(document_rec.file_loc):\\r\\n with open(document_rec.file_loc, 'rb') as doc_file:\\r\\n filecontent = doc_file.read()\\r\\n if not filecontent:\\r\\n return request.not_found()\\r\\n else:\\r\\n if document_rec.file_name[-3:] == 'pdf':\\r\\n #Return the file and filename to the browser.\\r\\n return request.make_response(filecontent,\\r\\n [('Content-Type', 'application/pdf'),\\r\\n ('Content-Disposition', 'inline')])\\r\\n else:\\r\\n return request.make_response(filecontent,\\r\\n [('Content-Type', 'attachment'),\\r\\n ('Content-Disposition', 'inline')])\\r\\n else:\\r\\n msg = 'File document {0} not found in NFS server. Please check the file or upload again.'.format(document_rec.file_loc)\\r\\n return request.not_found(msg)\",\n \"def find_index_with_document(document_id): \\n client, index_name = connection_es()\\n res = client.search(index = index_name+\\\"*\\\")\\n\\n for record in res['hits']['hits']:\\n if record['_id'] in document_id:\\n return record['_index']\",\n \"def get(self, *args):\\n return self.docs.get(*args)\",\n \"def get_doc_from_MP(mp_id):\\n apr=mpr.get_doc(mp_id)\\n return apr\",\n \"def find_by_id(cls, object_id):\\n try:\\n return mongo_db[cls.__collection__].find_one({\\\"_id\\\": ObjectId(object_id)})\\n except InvalidId:\\n # TODO: Log the exception\\n print('Invalid bson id: {}'.format(object_id))\\n return None\",\n \"def updateDocument(self, document):\\n data = self.updateDocumentAll([document])\\n try:\\n return data[0]\\n except: pass\",\n \"def article_by_id(self, id):\\n return self.es.get(index=self.index, doc_type=self.doc_type, id=id)\",\n \"def get_from_sources(self,index,doc_type,document_id):\\n return self.sources.get(index, {}).get(doc_type, {}).get(document_id,{})\",\n \"def get_object(self, id_):\\n return self._objects.get(id_, None)\",\n \"def get_task(task_id):\\n return db.task.find_one({'_id': ObjectId(task_id)})\",\n \"def test_select_id(self, document):\\n assert document.select({\\\"_id\\\": 1}) == {\\\"_id\\\": 1}\",\n \"def createDocument(self, document):\\n data = self.createDocumentAll([document])\\n try:\\n return data[0]\\n except: pass\",\n \"def get_document(document_id: Optional[str] = None,\\n location: Optional[str] = None,\\n project: Optional[str] = None,\\n opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDocumentResult:\\n __args__ = dict()\\n __args__['documentId'] = document_id\\n __args__['location'] = location\\n __args__['project'] = project\\n opts = pulumi.InvokeOptions.merge(_utilities.get_invoke_opts_defaults(), opts)\\n __ret__ = pulumi.runtime.invoke('google-native:contentwarehouse/v1:getDocument', __args__, opts=opts, typ=GetDocumentResult).value\\n\\n return AwaitableGetDocumentResult(\\n cloud_ai_document=pulumi.get(__ret__, 'cloud_ai_document'),\\n content_category=pulumi.get(__ret__, 'content_category'),\\n create_time=pulumi.get(__ret__, 'create_time'),\\n creator=pulumi.get(__ret__, 'creator'),\\n display_name=pulumi.get(__ret__, 'display_name'),\\n display_uri=pulumi.get(__ret__, 'display_uri'),\\n disposition_time=pulumi.get(__ret__, 'disposition_time'),\\n document_schema_name=pulumi.get(__ret__, 'document_schema_name'),\\n inline_raw_document=pulumi.get(__ret__, 'inline_raw_document'),\\n name=pulumi.get(__ret__, 'name'),\\n plain_text=pulumi.get(__ret__, 'plain_text'),\\n properties=pulumi.get(__ret__, 'properties'),\\n raw_document_file_type=pulumi.get(__ret__, 'raw_document_file_type'),\\n raw_document_path=pulumi.get(__ret__, 'raw_document_path'),\\n reference_id=pulumi.get(__ret__, 'reference_id'),\\n text_extraction_disabled=pulumi.get(__ret__, 'text_extraction_disabled'),\\n text_extraction_enabled=pulumi.get(__ret__, 'text_extraction_enabled'),\\n title=pulumi.get(__ret__, 'title'),\\n update_time=pulumi.get(__ret__, 'update_time'),\\n updater=pulumi.get(__ret__, 'updater'))\",\n \"def test_get_document(index_with_documents):\\n response = index_with_documents().get_document(\\\"500682\\\")\\n assert isinstance(response, Document)\\n assert hasattr(response, \\\"title\\\")\\n assert response.title == \\\"The Highwaymen\\\"\",\n \"def doc(obj):\\n return Documentation.fromObject(obj).first\",\n \"def resourceDocumentId(self, resource: Resource) -> str:\",\n \"def get_doc(ds, idx):\\n rtn = ds[idx]\\n if isinstance(rtn, dict):\\n rtn = rtn['text']\\n return rtn\",\n \"def find_doc(self, doc_type, property_name, property_value):\\n try:\\n self.client.connect()\\n db = self.client[self.db_name]\\n selector = {\\n '_id': {'$gt': 0},\\n 'type': doc_type,\\n property_name: property_value\\n }\\n query = Query(db, selector=selector)\\n for doc in query()['docs']:\\n return doc\\n return None\\n finally:\\n self.client.disconnect()\",\n \"def get(self, docid):\\n file = os.path.join(self.dirname, docid)\\n with open(file,'r',encoding='utf-8') as f:\\n text = f.read()\\n return text\",\n \"def get_log(ident):\\n return logs_col.find_one({\\\"_id\\\": ObjectId(ident)})\",\n \"def get_one(self, index, *args, **kw):\\n person = M.People.query.get(index=index)\\n log.debug('person {}'.format(person))\\n if(person):\\n kw['_id'] = person._id\\n return super(PeopleAPIController, self).get_one(*args, **kw)\",\n \"def get_document(self, doc_uri: str) -> Document:\\n return self._docs.get(doc_uri) or self._create_document(doc_uri)\",\n \"def get_doc_text(self, doc_id):\\n cursor = self.connection.cursor()\\n cursor.execute(\\n \\\"SELECT text FROM documents WHERE id = ?\\\",\\n (doc_id,)\\n )\\n result = cursor.fetchone()\\n cursor.close()\\n return result if result is None else result[0]\",\n \"def identifier(self) -> str:\\n return self.doc['id']\",\n \"def find_by_doc_reg_num(cls, doc_reg_num: str):\\n document = None\\n if doc_reg_num:\\n try:\\n document = cls.query.filter(Db2Document.document_reg_id == doc_reg_num).one_or_none()\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_doc_reg_num exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def retrieve(self, document_id: str) -> Fulltext:\\n if not document_id: # This could use further elaboration.\\n raise ValueError(\\\"Invalid value for document_id\\\")\\n\\n try:\\n response = requests.get(urljoin(self.endpoint, document_id))\\n except requests.exceptions.SSLError as ex:\\n raise IOError(\\\"SSL failed: %s\\\" % ex)\\n\\n if response.status_code != HTTPStatus.OK:\\n raise IOError(\\n \\\"%s: could not retrieve fulltext: %i\\\"\\n % (document_id, response.status_code)\\n )\\n try:\\n data = response.json()\\n except json.decoder.JSONDecodeError as ex:\\n raise IOError(\\n \\\"%s: could not decode response: %s\\\" % (document_id, ex)\\n ) from ex\\n return Fulltext(**data) # type: ignore\\n # See https://github.com/python/mypy/issues/3937\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8036257","0.78460073","0.7527839","0.74206144","0.72871727","0.72503227","0.72271115","0.7211136","0.7207188","0.7205287","0.7191581","0.716146","0.71606684","0.71544635","0.71252185","0.7115029","0.7100616","0.706832","0.70278084","0.7019712","0.696564","0.69574773","0.6941492","0.69185084","0.6862651","0.6858101","0.6855012","0.68453026","0.6835959","0.6828564","0.6819349","0.6795383","0.67922723","0.67512393","0.67504126","0.67459744","0.6724133","0.66585356","0.66552967","0.66472465","0.6631095","0.66084146","0.65887326","0.6573385","0.6538139","0.65307003","0.6511786","0.6504852","0.6501688","0.64994085","0.6496416","0.64891684","0.6480651","0.6462718","0.6454746","0.6439578","0.64313745","0.6412416","0.6398516","0.63899285","0.63742095","0.63742024","0.6370701","0.63520825","0.6326438","0.63177276","0.6315151","0.6303762","0.63021004","0.6290414","0.62667793","0.6266566","0.6258264","0.62556493","0.62442046","0.6242738","0.624236","0.6239102","0.62146074","0.62074506","0.6196783","0.61865443","0.61765695","0.61542124","0.6122305","0.6119093","0.61042655","0.60959333","0.60907036","0.6079747","0.60769707","0.60732675","0.6052373","0.60294944","0.6020146","0.6014405","0.6009416","0.600552","0.59986615","0.598475","0.5978174"],"string":"[\n \"0.8036257\",\n \"0.78460073\",\n \"0.7527839\",\n \"0.74206144\",\n \"0.72871727\",\n \"0.72503227\",\n \"0.72271115\",\n \"0.7211136\",\n \"0.7207188\",\n \"0.7205287\",\n \"0.7191581\",\n \"0.716146\",\n \"0.71606684\",\n \"0.71544635\",\n \"0.71252185\",\n \"0.7115029\",\n \"0.7100616\",\n \"0.706832\",\n \"0.70278084\",\n \"0.7019712\",\n \"0.696564\",\n \"0.69574773\",\n \"0.6941492\",\n \"0.69185084\",\n \"0.6862651\",\n \"0.6858101\",\n \"0.6855012\",\n \"0.68453026\",\n \"0.6835959\",\n \"0.6828564\",\n \"0.6819349\",\n \"0.6795383\",\n \"0.67922723\",\n \"0.67512393\",\n \"0.67504126\",\n \"0.67459744\",\n \"0.6724133\",\n \"0.66585356\",\n \"0.66552967\",\n \"0.66472465\",\n \"0.6631095\",\n \"0.66084146\",\n \"0.65887326\",\n \"0.6573385\",\n \"0.6538139\",\n \"0.65307003\",\n \"0.6511786\",\n \"0.6504852\",\n \"0.6501688\",\n \"0.64994085\",\n \"0.6496416\",\n \"0.64891684\",\n \"0.6480651\",\n \"0.6462718\",\n \"0.6454746\",\n \"0.6439578\",\n \"0.64313745\",\n \"0.6412416\",\n \"0.6398516\",\n \"0.63899285\",\n \"0.63742095\",\n \"0.63742024\",\n \"0.6370701\",\n \"0.63520825\",\n \"0.6326438\",\n \"0.63177276\",\n \"0.6315151\",\n \"0.6303762\",\n \"0.63021004\",\n \"0.6290414\",\n \"0.62667793\",\n \"0.6266566\",\n \"0.6258264\",\n \"0.62556493\",\n \"0.62442046\",\n \"0.6242738\",\n \"0.624236\",\n \"0.6239102\",\n \"0.62146074\",\n \"0.62074506\",\n \"0.6196783\",\n \"0.61865443\",\n \"0.61765695\",\n \"0.61542124\",\n \"0.6122305\",\n \"0.6119093\",\n \"0.61042655\",\n \"0.60959333\",\n \"0.60907036\",\n \"0.6079747\",\n \"0.60769707\",\n \"0.60732675\",\n \"0.6052373\",\n \"0.60294944\",\n \"0.6020146\",\n \"0.6014405\",\n \"0.6009416\",\n \"0.600552\",\n \"0.59986615\",\n \"0.598475\",\n \"0.5978174\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":25681,"cells":{"query":{"kind":"string","value":"Set up the templates"},"document":{"kind":"string","value":"def _settemplates(self, onecol, twocol):\n\n self.template = \"\"\"\n <table class=\"f\"><tbody>\n %s\n %s\n </tbody></table>\n \"\"\" % (self.header, onecol)\n\n # This is suitable for two column width.\n self.wide_template = \"\"\"\n <table class=\"f\"><tbody>\n %s\n %s\n </tbody></table>\n \"\"\" % (self.header.replace(\"1\", \"2\"), twocol)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def setup_templates(self):\n self.libs[\"template\"] = (\"#libs/templates/include\", None, \"\")\n self[\"CPPPATH\"].append(\"#libs/templates/include\")","def setUp(self):\n print \"Setting Up: %s\" % self.id()\n # render the template\n g.render_template(self.template_file,\n self.template_vars,\n self.output_file,\n self.search_path)\n\n # read the resulting config file built from template\n self.output_config = g.load_config(self.output_file)\n g.show_config(self.output_config)","def setUp(self):\r\n capa_path = capa.__path__[0]\r\n self.template_path = os.path.join(capa_path,\r\n 'templates',\r\n self.TEMPLATE_NAME)\r\n with open(self.template_path) as f:\r\n self.template = MakoTemplate(f.read())","def __fill_all_templates__(self,configs):\n template_dir = configs['system'].get('Common_directories','template')\n sample_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','sample'))\n system_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','system'))\n qsub_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','bcbio'))\n self.__fill_template__(sample_template,self.sample_file)\n self.__fill_template__(system_template,self.systems_file)\n self.__fill_template__(qsub_template,self.qsub_file)","def use_templates(self, templates):\n self.htmls = templates","def _set_templates(spm_dir=SPM_DIR):\n global EPI_TEMPLATE, T1_TEMPLATE, GM_TEMPLATE, WM_TEMPLATE, CSF_TEMPLATE\n\n spm_version = _get_version_spm(SPM_DIR)\n\n # Set the tpm and template paths according to SPM version\n if spm_version == 'spm12':\n template_path = 'toolbox/OldNorm'\n tpm_path = 'toolbox/OldSeg'\n else:\n template_path = 'templates'\n tpm_path = 'tpm'\n\n # configure template images\n EPI_TEMPLATE = os.path.join(SPM_DIR, template_path, 'EPI.nii')\n SPM_T1_TEMPLATE = os.path.join(SPM_DIR, template_path, 'T1.nii')\n T1_TEMPLATE = \"/usr/share/data/fsl-mni152-templates/avg152T1.nii\"\n if not os.path.isfile(T1_TEMPLATE):\n T1_TEMPLATE += '.gz'\n if not os.path.exists(T1_TEMPLATE):\n T1_TEMPLATE = SPM_T1_TEMPLATE\n GM_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'grey.nii')\n WM_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'white.nii')\n CSF_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'csf.nii')","def setUp(self):\n BuilderTestsMixin.setUp(self)\n self.builder = DocBuilder()\n self.howtoDir = FilePath(self.mktemp())\n self.howtoDir.createDirectory()\n self.templateFile = self.howtoDir.child(\"template.tpl\")\n self.templateFile.setContent(self.template)","def __init__(self, template_dirs=[], include_comments=False,\n include_introspection_server=False):\n # Flag to enable rendering of header and footer comments in templates\n self._include_comments = include_comments\n\n # Flag to enable inclusion of introspection server (for use with\n # smach_viewer)\n self._include_introspection_server = include_introspection_server\n\n # Create list of any custom user-defined template dirs + default\n # template dir\n self._template_dirs = (\n template_dirs +\n [os.path.join(os.path.dirname(os.path.realpath(__file__)),\n 'templates')])\n\n # Create template loader for the template directories\n template_loaders = [\n jinja2.FileSystemLoader(template_dir)\n for template_dir in self._template_dirs]\n self._template_loader = jinja2.ChoiceLoader(template_loaders)\n\n # Create an environment for reading and parsing templates, including\n # the SkipBlockExtension class to allow for skipping certain blocks.\n self._template_env = (\n jinja2.Environment(loader=self._template_loader,\n extensions=[jinja2.ext.do,\n SkipBlockExtension],\n trim_blocks=False,\n lstrip_blocks=True))\n\n # Skip comment blocks as required\n if not self._include_comments:\n self._template_env.skip_blocks.append('upper_comments')\n self._template_env.skip_blocks.append('lower_comments')\n\n # Skip introspection server blocks as required\n if not self._include_introspection_server:\n self._template_env.skip_blocks.append('introspection_server')\n self._template_env.skip_blocks.append('spin')\n\n # Register custom tests with the environment\n self._template_env.tests['expression'] = expression\n self._template_env.tests['not_string'] = not_string\n\n # Register custom filters with the environment\n self._template_env.filters['exptostr'] = exptostr\n\n # Create a template references cache dictionary\n # to be indexed by template names.\n self._template_ref_names_cache = {}\n\n # Create a template block names cache dictionary\n # to be indexed by template names.\n self._template_block_names_cache = {}\n\n # Create a template block cache dictionary\n # to be indexed by tuples of the form (template_name, block_name)\n self._template_block_cache = {}\n\n pass","def run():\r\n template_locations = settings.MAKO_TEMPLATES\r\n for namespace, directories in template_locations.items():\r\n clear_lookups(namespace)\r\n for directory in directories:\r\n add_lookup(namespace, directory)","def test_register_template(self):\n pass","def __init__(self, ctx, verbose=0) -> None:\n\n self.__ctx__ = ctx\n TemplateHandler.templates_path = ctx.obj['TEMPLATES_FOLDER']\n self.verbose = verbose\n\n self.validate_templates_path()\n if len(TemplateHandler.templates) == 0:\n self.load_templates()","def get_templates(self):\n\n data = self.request_from_server('templates')\n self.templates = data","def main(temp_dir, extensions, template):\n env = load_env(template_dir=temp_dir)\n if not template:\n # Get all the templates and return a dict with enumerated \n # templates names\n ext = extensions if extensions else []\n template_dict = get_templates(env, extensions=ext)\n # Echo the content of the template directory by enumerating \n # the templates and a simple list join\n temp_list = list()\n for x in template_dict.items():\n num = str(x[0])\n # Remove whitespace, underscores and capitalize words\n temp_name = x[1].strip().replace(\"_\", \" \").title()\n temp_string = \"{}. {}\".format(num, temp_name)\n temp_list.append(temp_string)\n click.echo(\"\\n\".join(temp_list))\n # Prompt the user to give the number of the template\n temp_num = click.prompt(\n \"Choose a templeta by entering the number of the template.\",\n type=int\n )\n # Get the template from the template dictionary\n template = template_dict.get(temp_num)\n # Get the variables\n temp_vars = get_vars(template, env)\n # Crate a dict with variables and let the user input the variables\n vars_to_render = dict()\n for var in temp_vars:\n user_var = click.prompt(\"{}?\".format(var.capitalize()))\n vars_to_render[var] = user_var\n # Get the template\n temp = env.get_template(template)\n # Render the template\n click.echo(temp.render(vars_to_render))","def _setup(self):\n self._raw_top_dir = os.path.join(self._snippets_dir,\"raw\",\"dynamic\")\n if not os.path.exists(self._raw_top_dir):\n os.mkdir(self._raw_top_dir)\n\n self._trec_top_dir = os.path.join(self._snippets_dir,\"trec\",\"dynamic\")\n if not os.path.exists(self._trec_top_dir):\n os.mkdir(self._trec_top_dir)\n\n self._temp_top_dir = os.path.join(self._snippets_dir,\"temp\",\"dynamic\")\n if not os.path.exists(self._temp_top_dir):\n os.mkdir(self._temp_top_dir)\n\n self._snippet_result_top_dir = os.path.join(self._snippets_dir,\"result\",\"dynamic\")\n if not os.path.exists(self._snippet_result_top_dir):\n os.mkdir(self._snippet_result_top_dir)\n\n self._snippet_index_top_dir = os.path.join(self._snippets_dir,\"index\",\"dynamic\")\n if not os.path.exists(self._snippet_index_top_dir):\n os.mkdir(self._snippet_index_top_dir)\n\n self._para_top_dir = os.path.join(self._snippets_dir,\"para\",\"dynamic\")\n if not os.path.exists(self._para_top_dir):\n os.mkdir(self._para_top_dir)","def test_create_template_for_all_namespaces(self):\n pass","def main():\n VALIDATE_TEMPLATE(TEMPLATES)","def main():\n VALIDATE_TEMPLATE(TEMPLATES)","def site_setup(self, tmpdir):\n templates = tmpdir.mkdir(\"templates\")\n templates.join(\"def.html\").write(\"{{ content }}\")\n\n content = tmpdir.mkdir(\"content\")\n output = tmpdir.mkdir(\"output\")\n config_dict = {\n \"theme_dir\": str(templates),\n \"default_template\": \"def.html\",\n \"content\": str(content)\n }\n config_file = tmpdir.join(\"config.yml\")\n config_file.write(yaml.dump(config_dict))\n config = SiteConfig(str(config_file))\n s_gen = SiteGenerator(config)\n return templates, content, output, s_gen","def render_templates(self):\n\n # dockerfile\n try:\n t = self.templates.get_template(\n 'docker/dockerfiles/{}.dockerfile.template'.format(self.repo)\n )\n except TemplateNotFound:\n t = self.templates.get_template(\n 'docker/dockerfiles/default.dockerfile.template'\n )\n\n self.files.append({\n 'name': 'Dockerfile',\n 'content': t.render(commit=self.commit),\n })\n\n # gunicorn\n t = self.templates.get_template(\n 'docker/gunicorn/gunicorn.conf.py'\n )\n self.files.append({\n 'name': 'gunicorn.conf.py',\n 'content': t.render(),\n })\n\n t = self.templates.get_template(\n 'docker/gunicorn/gunicorn.sh'\n )\n self.files.append({\n 'name': 'gunicorn.sh',\n 'content': t.render(),\n 'mode': 0555,\n })\n\n # nginx\n t = self.templates.get_template(\n 'docker/nginx/app.nginx.conf'\n )\n self.files.append({\n 'name': 'app.nginx.conf',\n 'content': t.render(),\n })\n\n t = self.templates.get_template(\n 'docker/nginx/nginx.sh'\n )\n self.files.append({\n 'name': 'nginx.sh',\n 'content': t.render(),\n 'mode': 0555,\n })\n\n # cron/, etc/ iif there exists a `self.repo` directory\n def _filter(p):\n return (\"cron/\" in p or \"etc/\" in p) and (self.repo in p) and \\\n (not os.path.basename(p).startswith('.'))\n\n for t in self.templates.list_templates(\n filter_func=_filter):\n\n self.files.append({\n 'name': os.path.basename(t),\n 'content': self.templates.get_template(t).render(),\n })","def init_templates( path=\"boilerplate\" ):\n global template_env\n template_loader = jinja2.FileSystemLoader(searchpath=\"boilerplate\" )\n template_env = jinja2.Environment(\n loader=template_loader,\n lstrip_blocks=True\n )","def __setup_template(self):\n template = Template()\n template.add_description(\"Service VPC - used for services\")\n\n template.add_metadata({\n \"Build\": \"development\",\n \"DependsOn\": [],\n \"Environment\": \"ApiDev\",\n \"Revision\": \"develop\",\n \"StackName\": \"ApiDev-Dev-VPC\",\n \"StackType\": \"InfrastructureResource\",\n \"TemplateBucket\": \"cfn-apidev\",\n \"TemplateName\": \"VPC\",\n \"TemplatePath\": \"ApiDev/Dev/VPC\"\n })\n\n vpc = template.add_resource(\n ec2.VPC(\n \"VPC\",\n CidrBlock=\"10.0.0.0/16\",\n EnableDnsHostnames=\"true\",\n EnableDnsSupport=\"true\",\n InstanceTenancy=\"default\",\n Tags=self.__get_tags(\"ServiceVPC\"),\n )\n )\n\n instance_sg = template.add_resource(\n ec2.SecurityGroup(\n \"BastionSG\",\n GroupDescription=\"Used for source/dest rules\",\n Tags=self.__get_tags(\"VPC-Bastion-SG\"),\n VpcId=Ref(\n vpc\n )\n ),\n )\n\n cw_alarm_topic = template.add_resource(\n Topic(\n \"CloudWatchAlarmTopic\",\n TopicName=\"ApiDev-Dev-CloudWatchAlarms\",\n )\n )\n\n dhcp_options = template.add_resource(\n ec2.DHCPOptions(\n \"DhcpOptions\",\n DomainName=Join(\n \"\",\n [\n Ref(\"AWS::Region\"),\n \".compute.internal\"\n ]\n ),\n DomainNameServers=[\"AmazonProvidedDNS\"],\n Tags=self.__get_tags(\"DhcpOptions\"),\n )\n )\n\n gateway = template.add_resource(\n ec2.InternetGateway(\n \"InternetGateway\",\n Tags=self.__get_tags(\"InternetGateway\")\n )\n )\n\n nat_emergency_topic = template.add_resource(\n Topic(\n \"NatEmergencyTopic\",\n TopicName=\"ApiDev-Dev-NatEmergencyTopic\",\n )\n )\n\n vpc_dhcp_options_assoc = template.add_resource(\n ec2.VPCDHCPOptionsAssociation(\n \"VpcDhcpOptionsAssociation\",\n DhcpOptionsId=Ref(\n dhcp_options\n ),\n VpcId=Ref(\n vpc\n )\n )\n )\n\n vpc_gw_attachment = template.add_resource(\n ec2.VPCGatewayAttachment(\n \"VpcGatewayAttachment\",\n InternetGatewayId=Ref(\n gateway\n ),\n VpcId=Ref(\n vpc\n )\n )\n )\n\n vpc_network_acl = template.add_resource(\n ec2.NetworkAcl(\n \"VpcNetworkAcl\",\n Tags=self.__get_tags(\"NetworkAcl\"),\n VpcId=Ref(\n vpc\n )\n )\n )\n\n vpc_network_acl_rules = template.add_resource([\n ec2.NetworkAclEntry(\n \"VpcNetworkAclInboundRulePublic443\",\n CidrBlock=\"0.0.0.0/0\",\n Egress=\"false\",\n NetworkAclId=Ref(\n vpc_network_acl\n ),\n PortRange=ec2.PortRange(\n From=\"443\",\n To=\"443\",\n ),\n Protocol=\"6\",\n RuleAction=\"allow\",\n RuleNumber=20001\n ),\n ec2.NetworkAclEntry(\n \"VpcNetworkAclInboundRulePublic80\",\n CidrBlock=\"0.0.0.0/0\",\n Egress=\"false\",\n NetworkAclId=Ref(\n vpc_network_acl\n ),\n PortRange=ec2.PortRange(\n From=\"80\",\n To=\"80\",\n ),\n Protocol=\"6\",\n RuleAction=\"allow\",\n RuleNumber=20000\n ),\n ec2.NetworkAclEntry(\n \"VpcNetworkAclOutboundRule\",\n CidrBlock=\"0.0.0.0/0\",\n Egress=\"true\",\n NetworkAclId=Ref(\n vpc_network_acl\n ),\n Protocol=\"-1\",\n RuleAction=\"allow\",\n RuleNumber=30000\n ),\n ec2.NetworkAclEntry(\n \"VpcNetworkAclSsh\",\n CidrBlock=\"127.0.0.1/32\",\n Egress=\"false\",\n NetworkAclId=Ref(\n vpc_network_acl\n ),\n PortRange=ec2.PortRange(\n From=\"22\",\n To=\"22\",\n ),\n Protocol=\"6\",\n RuleAction=\"allow\",\n RuleNumber=10000\n )\n ])\n\n template.add_output([\n Output(\n \"BastionSG\",\n Value=Ref(instance_sg)\n ),\n Output(\n \"CloudWatchAlarmTopic\",\n Value=Ref(cw_alarm_topic)\n ),\n Output(\n \"InternetGateway\",\n Value=Ref(gateway)\n ),\n Output(\n \"NatEmergencyTopicARN\",\n Value=Ref(nat_emergency_topic)\n ),\n Output(\n \"VPCID\",\n Value=Ref(vpc)\n ),\n Output(\n \"VPCName\",\n Value=Ref(\"AWS::StackName\")\n ),\n Output(\n \"VpcNetworkAcl\",\n Value=Ref(vpc_network_acl)\n )\n\n ])\n\n return template","def __init__(self, settings):\n self.mylookup = TemplateLookup(\n directories = [join(settings['root'],rpath) for rpath in settings['view_paths']],\n output_encoding='utf-8')\n \n self.routes = []\n self._part_matcher = re.compile(r'{.*?}')\n self.error_handler = noop","def __init__(self, *args, **kwargs):\r\n super(ServeeAdminSite, self).__init__(*args, **kwargs)\r\n\r\n self.name = \"servee\"\r\n self.app_name = \"servee\"\r\n self.uses_wysiwyg = \"servee.wysiwyg\" in settings.INSTALLED_APPS\r\n\r\n self.index_template = [\"servee/index.html\", \"admin/index.html\"]\r\n self.login_template = [\"servee/login.html\", \"admin/login.html\"]\r\n self.logout_template = [\"servee/logout.html\", \"admin/logout.html\"]\r\n self.password_change_template = [\"servee/password_change.html\", \"admin/password_change.html\"]\r\n self.password_change_done_template = [\"servee/password_change_done.html\", \"admin/password_change_done.html\"]","def load_templates(self):\n TemplateHandler.templates = []\n for template in os.listdir(TemplateHandler.templates_path):\n template_config = self.load_template_conf(template)\n if template_config is None:\n continue\n TemplateHandler.templates.append(template_config)","def update():\n if Project.use_templates:\n defaults = _project_defaults()\n\n template = Template()\n\n for template_dir in [os.path.abspath(os.path.join(herringlib, 'herringlib', 'templates'))\n for herringlib in HerringFile.herringlib_paths]:\n\n info(\"template directory: %s\" % template_dir)\n # noinspection PyArgumentEqualDefault\n template.generate(template_dir, defaults, overwrite=False)","def __init__(self, name, template_folder):\n super().__init__(name)","def prepare(self):\n self.parse_template()\n self.build_argparser()\n self.parse_arguments()\n self.render_template()\n self.update_relation()","def startup(self, title=None, author=None, uid=None):\n title, author, uid = self._collect_metadata(title, author, uid)\n self._generate_skeleton(title, author, uid, from_dirpath=TEMPLATE_DIRPATH)","def __init__(self, template_name):\n # self.env = Environment(loader=PackageLoader(\n # package, path))\n # self.template = self.env.get_template(template_name)\n with open(template_name, 'r', encoding='UTF-8') as f:\n self.template = Template(f.read())","def __init__(self, template_dir=None, package_name=None):\r\n self._template_dir = template_dir\r\n self._package_name = package_name\r\n self._pystache_renderer = pystache.Renderer(search_dirs=template_dir)","def html_template_file(self):\n pass","def main():\r\n return render_template(\"UI.html\")","def _load_templates(cls):\n if cls._raw_templates is None:\n cls._raw_templates = fetch_rrlyrae_templates()","def init():\n defaults = _project_defaults()\n\n if Project.prompt:\n defaults['name'] = prompt(\"Enter the project's name:\", defaults['name'])\n defaults['package'] = prompt(\"Enter the project's package:\", defaults['package'])\n defaults['author'] = prompt(\"Enter the project's author:\", defaults['author'])\n defaults['author_email'] = prompt(\"Enter the project's author's email:\", defaults['author_email'])\n defaults['description'] = prompt(\"Enter the project's description:\", defaults['description'])\n\n # print(\"defaults:\\n{defaults}\".format(defaults=pformat(defaults)))\n\n if Project.use_templates:\n\n template = Template()\n\n for template_dir in [os.path.abspath(os.path.join(herringlib, 'herringlib', 'templates'))\n for herringlib in HerringFile.herringlib_paths]:\n\n info(\"template directory: %s\" % template_dir)\n # noinspection PyArgumentEqualDefault\n template.generate(template_dir, defaults, overwrite=False)","def load_templates(self):\n\n self.templates = []\n\n if os.path.exists(\"question_templates.txt\"):\n for line in open(\"question_templates.txt\", \"r\"):\n self.templates.append(line.replace(\"\\n\", \"\"))","def test_functionality(self):\n self.templateName = \"Test Template\"\n self.browserObject = globalVars.browserObject\n\n self.preRunSetup()\n \n self.runTestCase()\n \n self.postRunCleanup()","def __init__(self):\n super().__init__()\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\n\n step1 = PrepareAppConfTransfiguration()\n step2 = ConfReaderToContextTransfiguration()\n step3 = ValidateCollectionTags()\n step4 = AttributeChainedTransfiguration('mbean')\n step5 = AttributeChainedTransfiguration('connection')\n\n self.add(step1)\n self.add(step2)\n self.add(step3)\n self.add(step4)\n self.add(step5)","def test_config(self):\n self.assertEqual(self.view.template_name, \"resources/templanguage_admin.html\")","def setup_theme(app):\r\n theme = app.config['THEME']\r\n app.template_folder = os.path.join('themes', theme, 'templates')\r\n app.static_folder = os.path.join('themes', theme, 'static')","async def setup(self):\n load_base_templates()\n uris = URI.gather()\n for uri, resource in uris.items():\n methods = resource.methods\n if \"get\" not in methods:\n methods[\"get\"] = None\n\n for method in methods.keys():\n self.app.add_routes([\n getattr(aioweb, method)(uri, resource.process)\n ])\n self.app.add_routes([aioweb.get(\"/hello\", hello)])\n\n # TMP code\n max_age = 3600 * 24 * 365 # 1 year\n setup(self.app, PonyStorage(max_age=max_age))\n self.preparing_task = asyncio.create_task(self.prepare_web())","def _setup(self):\n self._raw_dir = os.path.join(self._snippets_dir,\"raw\",\"static\")\n if not os.path.exists(self._raw_dir):\n os.mkdir(self._raw_dir)\n\n self._trec_dir = os.path.join(self._snippets_dir,\"trec\",\"static\")\n if not os.path.exists(self._trec_dir):\n os.mkdir(self._trec_dir)\n\n self._temp_dir = os.path.join(self._snippets_dir,\"temp\",\"static\")\n if not os.path.exists(self._temp_dir):\n os.mkdir(self._temp_dir)\n\n self._para_dir = os.path.join(self._snippets_dir,\"para\",\"static\")\n if not os.path.exists(self._para_dir):\n os.mkdir(self._para_dir)\n\n self._snippet_result_dir = os.path.join(self._snippets_dir,\"result\",\"static\")\n if not os.path.exists(self._snippet_result_dir):\n os.mkdir(self._snippet_result_dir)\n\n self._snippet_index_dir = os.path.join(self._snippets_dir,\"index\",\"static\")\n if not os.path.exists(self._snippet_index_dir):\n os.mkdir(self._snippet_index_dir)\n\n \n\n\n self._index_para = os.path.join(self._para_dir,\"index_para\")\n\n self._temp_query_para = os.path.join(self._para_dir,\"temp_query_para\")\n\n self._index_list = os.path.join(self._para_dir,\"static_index_list\")\n \n self._orf = os.path.join(self._snippet_result_dir,\"orf\")\n\n self._oqf = os.path.join(self._temp_dir,\"oqf\")\n \n self._temp_output = os.path.join(self._temp_dir,\"temp_output\")\n\n with open(self._index_list,\"w\") as f:\n f.write(self._snippet_index_dir+\"\\n\")\n\n self._temp_query_builder = IndriQueryFactory(count=10000,\n rule=self._retrieval_method)\n\n self._oqf_builder = IndriQueryFactory(count=30,\n rule=self._retrieval_method)","def __init__(self, template_path=None):\n if template_path:\n self.template_env = Environment(\n loader=FileSystemLoader(template_path),\n autoescape=select_autoescape([\"html\", \"xml\"]),\n )\n self.template_list = self.template_env.list_templates()\n else:\n # Loading built-in templates from the genalog package\n self.template_env = Environment(\n loader=PackageLoader(\"genalog.generation\", \"templates\"),\n autoescape=select_autoescape([\"html\", \"xml\"]),\n )\n # Remove macros and css templates from rendering\n self.template_list = self.template_env.list_templates(\n filter_func=DocumentGenerator._keep_template\n )\n\n self.set_styles_to_generate(DEFAULT_STYLE_COMBINATION)","def test_create_template_subsciption(self):\n pass","def main():\n\n return render_template(\"index.html\", title=\"Home\", heading=\"Dublin Bus\")","def create_template(self, path: Path, dot_cookietemple: Optional[dict]) -> None:\n self.web_struct.language = cookietemple_questionary_or_dot_cookietemple(function='select',\n question='Choose between the following languages',\n choices=['python'],\n default='python',\n dot_cookietemple=dot_cookietemple,\n to_get_property='language')\n\n # prompt the user to fetch general template configurations\n super().prompt_general_template_configuration(dot_cookietemple)\n\n # switch case statement to prompt the user to fetch template specific configurations\n switcher: Dict[str, Any] = {\n 'python': self.web_python_options,\n }\n switcher.get(self.web_struct.language)(dot_cookietemple) # type: ignore\n # call handle function for specified language\n self.__getattribute__(f'handle_web_project_type_{self.web_struct.language}')(dot_cookietemple)\n # call handle function for specified webtype according to the chosen language\n self.__getattribute__(f'handle_{self.web_struct.webtype.lower()}_{self.web_struct.language}')(dot_cookietemple)\n # call option function for specified framework (if any)\n framework = self.web_struct.web_framework.lower()\n if framework:\n self.__getattribute__(f'{self.web_struct.webtype.lower()}_{framework}_options')(dot_cookietemple)\n\n self.web_struct.is_github_repo, self.web_struct.is_repo_private, self.web_struct.is_github_orga, self.web_struct.github_orga = \\\n prompt_github_repo(dot_cookietemple)\n # if repo owner is a github orga, update username\n if self.web_struct.is_github_orga:\n self.web_struct.github_username = self.web_struct.github_orga\n # create the project (TODO COOKIETEMPLE: As for now (only Flask) this works. Might need to change this in future.\n super().create_template_with_subdomain_framework(self.TEMPLATES_WEB_PATH, self.web_struct.webtype, self.web_struct.web_framework.lower())\n # clean project for advanced or basic setup\n self.basic_or_advanced_files_with_frontend(self.web_struct.setup_type, self.web_struct.frontend.lower())\n\n # switch case statement to fetch the template version\n switcher_version = {\n 'python': self.WEB_WEBSITE_PYTHON_TEMPLATE_VERSION\n }\n\n self.web_struct.template_version, self.web_struct.template_handle\\\n = switcher_version.get(self.web_struct.language), f'web-{self.web_struct.webtype}-{self.web_struct.language.lower()}' # type: ignore\n\n # perform general operations like creating a GitHub repository and general linting\n super().process_common_operations(path=Path(path).resolve(), domain='web',\n subdomain=self.web_struct.webtype,\n language=self.web_struct.language,\n dot_cookietemple=dot_cookietemple)","def create_templates(self):\n for name, params in list_registered_templates():\n if self['templates'].filter(theme=self, name=name).count() == 0:\n self['templates'].create(theme=self, name=name)","def __init__(self):\n super().__init__()\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\n\n step1 = PrepareAppConfTransfiguration()\n step2 = ConfReaderToContextTransfiguration()\n step3 = AttributeChainedTransfiguration('mbean')\n\n self.add(step1)\n self.add(step2)\n self.add(step3)","def __init__(self):\n super().__init__()\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\n\n step1 = CommonMBeansChainedTransfiguration()\n step2 = SpliByApplicationTransfiguration()\n step3 = ConsolidateToFinalOutput()\n\n self.add(step1)\n self.add(step2)\n self.add(step3)","def _buildjinja2_templates(self):\n templates = self.embryo.templates\n\n # if templates is a module extract its public string attributes\n # into the templates dict expected below.\n if isinstance(templates, ModuleType):\n tmp_templates = {}\n for k in dir(templates):\n v = getattr(templates, k)\n if (not k.startswith('_')) and isinstance(v, (str, Template)):\n tmp_templates[k] = v\n templates = tmp_templates\n\n # load the jinja2 templates contained in the module, either in the form\n # of Template objects or strings.\n loaded_templates = {}\n jinja_env = build_env()\n\n if templates:\n for k, v in templates.items():\n say('loading template: {}'.format(k))\n if isinstance(v, Template):\n loaded_templates[k] = v\n elif isinstance(v, str):\n try:\n loaded_templates[k] = jinja_env.from_string(v)\n except Exception as exc:\n source = exc.source.split('\\n')[exc.lineno - 1]\n shout(f'error \"{exc.message}\", line {exc.lineno} {source}')\n\n self.jinja2_templates = loaded_templates","def _setup_jinja(manager: ConfigServiceManager, app: web.Application):\n\n tpl_path = manager.env.get('TEMPLATE_PATH')\n if not tpl_path:\n tpl_path = os.path.join(manager.config_root, 'templates')\n # load default templates provided by package\n loader = PackageLoader('vonx', 'templates')\n if tpl_path:\n # load custom templates if present\n # may want to use a resource loader if tpl_path looks like a package name (has a colon)\n loader = ChoiceLoader([\n loader,\n FileSystemLoader(tpl_path)\n ])\n filters = {\"jsonify\": json.dumps}\n aiohttp_jinja2.setup(app, loader=loader, filters=filters)","def __init__(self, *args, **kwargs):\r\n if not kwargs.get('no_django', False):\r\n overrides = {k: getattr(edxmako, k, None) for k in DJANGO_VARIABLES}\r\n overrides['lookup'] = edxmako.LOOKUP['main']\r\n kwargs.update(overrides)\r\n super(Template, self).__init__(*args, **kwargs)","def run(self):\n make_sure_path_exists(OUT_FOLDER)\n\n if self.config['type'] == 'website':\n make_sure_path_exists(self.config['out_folder'])\n\n\n for file in self.config['bodies']:\n if file['type'] == 'content':\n self.pandoc_file(file)\n if self.config['type'] == 'website':\n shutil.copyfile(file['generated'], os.path.join(self.config['out_folder'], os.path.basename(file['source'])))\n\n if self.config['type'] == 'website':\n return\n\n for file in self.config['abstract']:\n self.pandoc_file(file)\n for file in self.config['summary']:\n self.pandoc_file(file)\n\n template = LATEX_JINJA_ENV.get_template(self.config['template_file'])\n\n logging.info('Rendering template')\n out = template.render(**self.config)\n with open(self.config['name'] + self.get_file_extension(), 'w') as file:\n file.write(out)\n\n if not self.args.pandoc:\n logging.info('Rendering latex')\n self.write()\n if not self.args.fast:\n logging.info('Rendering latex, again')\n self.write() # twice for the toc\n\n logging.info('Done!')","def update_views():\n # replace Supervisor main entry\n here = os.path.abspath(os.path.dirname(__file__))\n # set main page\n VIEWS['index.html'] = {'template': os.path.join(here, 'ui/index.html'),\n 'view': SupvisorsView}\n # set address /processpage\n VIEWS['procaddress.html'] = {'template': os.path.join(\n here, 'ui/procaddress.html'),\n 'view': ProcAddressView}\n # set address/host page\n VIEWS['hostaddress.html'] = {'template': os.path.join(\n here, 'ui/hostaddress.html'),\n 'view': HostAddressView}\n # set application page\n VIEWS['application.html'] = {'template': os.path.join(\n here, 'ui/application.html'),\n 'view': ApplicationView}\n # set fake page to export images\n VIEWS['process_cpu.png'] = {'template': os.path.join(\n here, 'ui/empty.html'),\n 'view': ProcessCpuImageView}\n VIEWS['process_mem.png'] = {'template': os.path.join(\n here, 'ui/empty.html'),\n 'view': ProcessMemoryImageView}\n VIEWS['address_cpu.png'] = {'template': os.path.join(\n here, 'ui/empty.html'),\n 'view': AddressCpuImageView}\n VIEWS['address_mem.png'] = {'template': os.path.join(\n here, 'ui/empty.html'),\n 'view': AddressMemoryImageView}\n VIEWS['address_io.png'] = {'template': os.path.join(\n here, 'ui/empty.html'),\n 'view': AddressNetworkImageView}","def get_templates(self):\n\n\t\tif not os.path.isdir('./repo'): os.mkdir('./repo')\n\t\ttemps = self.settings['template']\n\t\t#---ensure that the template object is always in a list\n\t\tif len(temps) == 2 and type(temps[0])==str and type(temps[1])==str: temps = [temps]\n\t\tself.template = []\n\t\tfor t in temps:\n\t\t\tprint 'retrieving '+str(t[0])\n\t\t\t#---check if in repo and move\n\t\t\tif not os.path.isfile(self.rootdir+t[0]+'.pdb') and os.path.isfile('./repo/'+t[0]+'.pdb'):\n\t\t\t\tcopy('./repo/'+t[0]+'.pdb',self.rootdir+t[0]+'.pdb')\n\t\t\t\t#---fasta retrieval is deprecated\n\t\t\t\tif 0: copy('./repo/'+t[0]+'.fasta',self.rootdir+t[0]+'.fasta')\n\t\t\telif not os.path.isfile(self.rootdir+t[0]+'.pdb'):\n\t\t\t\tresponse = urllib2.urlopen('http://www.rcsb.org/pdb/files/'+t[0]+'.pdb')\n\t\t\t\tpdbfile = response.read()\n\t\t\t\twith open(self.rootdir+t[0]+'.pdb','w') as fp: fp.write(pdbfile)\n\t\t\t\tcopy(self.rootdir+t[0]+'.pdb','./repo/'+t[0]+'.pdb')\n\t\t\tself.template.append(t)","def prepare(self, **template_parameters: Any) -> None:\n\n self._body_plain = render_template(self._body_template_base_path + '.txt', **template_parameters)\n self._body_html = render_template(self._body_template_base_path + '.html', **template_parameters)","def controls_setup(self):\n\n self.drain_types = container.AdminDashboardSubmodule(\n self, alias=\"Drain Types Submodule\",\n css_selector='tr.CodeDrainType')\n self.depot_types = container.AdminDashboardSubmodule(\n self, alias=\"Depot Types Submodule\",\n css_selector='tr.CodeJobType')\n self.file_types = container.AdminDashboardSubmodule(\n self, alias=\"File Types Submodule\",\n css_selector='tr.CodeFileType')\n self.job_types = container.AdminDashboardSubmodule(\n self, alias=\"Job Types Submodule\",\n css_selector='tr.CodeJobType')\n self.paving_colours = container.AdminDashboardSubmodule(\n self, alias=\"Paving Colours Submodule\",\n css_selector='tr.CodePavingColour')\n self.paving_types = container.AdminDashboardSubmodule(\n self, alias=\"Paving Types Submodule\",\n css_selector='tr.CodePavingType')\n self.repair_types = container.AdminDashboardSubmodule(\n self, alias=\"Repair Types Submodule\",\n css_selector='tr.CodeRepairType')\n self.subbie_types = container.AdminDashboardSubmodule(\n self, alias=\"Subbie Types Submodule\",\n css_selector='tr.CodeSubbieType')\n self.task_types = container.AdminDashboardSubmodule(\n self, alias=\"Task Types Submodule\",\n css_selector='tr.CodeTaskType')","def createBasicRenderSetup():\n\n pass","def setUpClass(cls):\n print \"Setting Up Class: %s\" % cls.__name__\n\n # Setting class attributes for use across all test methods\n cls.config_file = ('supporting_files/templates/'\n 'glusto_templates-vars.yml')\n config = g.load_config(cls.config_file)\n g.show_config(config)\n if config:\n g.update_config(config)\n\n cls.template_vars = g.config['templates']\n cls.template_file = ('templates/'\n 'glusto_templates-template.jinja')\n cls.search_path = 'supporting_files'\n cls.output_file = '/tmp/glusto_templates-output.yml'","def __init__(self, template_env):\r\n self._template_env = template_env\r\n self._pythons = []","def generate_webpages(self):\n if self.add_to_existing:\n self.add_existing_data()\n self.make_home_pages()\n self.make_1d_histogram_pages()\n self.make_corner_pages()\n self.make_config_pages()\n if self.make_comparison:\n self.make_comparison_pages()\n if self.make_interactive:\n self.make_interactive_pages()\n if self.publication:\n self.make_publication_pages()\n if self.gwdata is not None:\n self.make_detector_pages()\n self.make_error_page()\n self.make_version_page()\n if self.notes is not None:\n self.make_notes_page()\n self.make_downloads_page()\n self.generate_specific_javascript()","def test_create_namespaced_template(self):\n pass","def load_template_files(self):\n templates = dict()\n template_path = settings.CUSTOM_VERTO_TEMPLATES\n templates.update(self.read_template_files(template_path))\n if hasattr(self, \"extra_converter_templates_directory\"):\n directory = self.extra_converter_templates_directory\n template_path = os.path.join(template_path, directory)\n templates.update(self.read_template_files(template_path))\n return templates","def update_views():\n # replace Supervisor main entry\n here = path.abspath(path.dirname(__file__))\n # set main page\n VIEWS['index.html'] = {'template': path.join(here, 'ui/index.html'), 'view': SupvisorsView}\n # set address /processpage\n VIEWS['procaddress.html'] = {'template': path.join(here, 'ui/procaddress.html'), 'view': ProcAddressView}\n # set address/host page\n VIEWS['hostaddress.html'] = {'template': path.join(here, 'ui/hostaddress.html'), 'view': HostAddressView}\n # set application page\n VIEWS['application.html'] = {'template': path.join(here, 'ui/application.html'), 'view': ApplicationView}\n # set fake page to export images\n VIEWS['process_cpu.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': ProcessCpuImageView}\n VIEWS['process_mem.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': ProcessMemoryImageView}\n VIEWS['address_cpu.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressCpuImageView}\n VIEWS['address_mem.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressMemoryImageView}\n VIEWS['address_io.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressNetworkImageView}","def init(depot):\n global tlookup\n pkg.server.feed.init(depot)\n tlookup = mako.lookup.TemplateLookup(directories=[depot.web_root])","def test_custom_templates_and_themes(self):\n new_templates_dir = os.path.join(self.temp_usable_dir, 'templates')\n manage_tmpl_file = os.path.join(new_templates_dir, 'manage/custom.py_tmpl')\n repository_tmpl_file = os.path.join(new_templates_dir, 'repository/custom/README')\n script_tmpl_file = os.path.join(new_templates_dir, 'script/custom.py_tmpl')\n sql_script_tmpl_file = os.path.join(new_templates_dir, 'sql_script/custom.py_tmpl')\n\n MANAGE_CONTENTS = 'print \"manage.py\"'\n README_CONTENTS = 'MIGRATE README!'\n SCRIPT_FILE_CONTENTS = 'print \"script.py\"'\n new_repo_dest = self.tmp_repos()\n new_manage_dest = self.tmp_py()\n\n # make new templates dir\n shutil.copytree(migrate.versioning.templates.__path__[0], new_templates_dir)\n shutil.copytree(os.path.join(new_templates_dir, 'repository/default'),\n os.path.join(new_templates_dir, 'repository/custom'))\n\n # edit templates\n f = open(manage_tmpl_file, 'w').write(MANAGE_CONTENTS)\n f = open(repository_tmpl_file, 'w').write(README_CONTENTS)\n f = open(script_tmpl_file, 'w').write(SCRIPT_FILE_CONTENTS)\n f = open(sql_script_tmpl_file, 'w').write(SCRIPT_FILE_CONTENTS)\n\n # create repository, manage file and python script\n kw = {}\n kw['templates_path'] = new_templates_dir\n kw['templates_theme'] = 'custom'\n api.create(new_repo_dest, 'repo_name', **kw)\n api.script('test', new_repo_dest, **kw)\n api.script_sql('postgres', 'foo', new_repo_dest, **kw)\n api.manage(new_manage_dest, **kw)\n\n # assert changes\n self.assertEqual(open(new_manage_dest).read(), MANAGE_CONTENTS)\n self.assertEqual(open(os.path.join(new_repo_dest, 'manage.py')).read(), MANAGE_CONTENTS)\n self.assertEqual(open(os.path.join(new_repo_dest, 'README')).read(), README_CONTENTS)\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/001_test.py')).read(), SCRIPT_FILE_CONTENTS)\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/002_foo_postgres_downgrade.sql')).read(), SCRIPT_FILE_CONTENTS)\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/002_foo_postgres_upgrade.sql')).read(), SCRIPT_FILE_CONTENTS)","def test_render_all_templates():\n assert templates.xhook__initialize({})\n assert templates.xhook__handlers({})\n assert templates.xhook__enable()\n assert templates.xhook__release()\n assert templates.asserts__call_count({})\n assert templates.asserts__calls({})","def main():\n return render_template(\"main.html\")","def main():\n return render_template(\"main.html\")","def __init__(self, out_dir):\n self.env = Environment(loader=PackageLoader(\"emu\", \"templates\"))\n self.dest = out_dir","def __init__(self, config):\n\n with open(config) as file:\n self.config = yaml.load(file, Loader=yaml.FullLoader)\n\n self.contents = []\n\n self.templateLoader = jinja2.FileSystemLoader(searchpath=\"./\")\n self.templateEnv = jinja2.Environment(loader=self.templateLoader)","def setup( self ):","def create_base_templates(outdir, templateEnv):\n for file in ME_TEMPLATES:\n filename = os.path.join(outdir, ME_FILENAME.format(file))\n template = templateEnv.get_template(file + '.go.jinja')\n\n with open(filename, 'w') as f:\n output = template.render(copyright=COPYRIGHT,\n generator_warning=GENERATOR_WARNING,\n package_name=PACKAGE_NAME)\n f.write(output)\n pass","def update_config(self, config):\n toolkit.add_template_directory(config, 'templates')\n toolkit.add_resource('fanstatic', 'mingus')\n return","def controls_setup(self):\n\n self.client_name = element.Link(self, css_selector='th:nth-child(1) > a', alias=\"Admin Client Name Link\")\n self.xero_customer = element.Caption(self, css_selector='td:nth-child(2)', alias=\"Xero Customer\")\n self.send_invoices = element.Image(self, css_selector='td:nth-child(3) img', alias=\"Send Invoices Check Mark\")\n self.part_a_required = element.Image(self, css_selector='td:nth-child(4) img',\n alias=\"Part A Required Check Mark\")\n self.they_supply_pump = element.Image(self, css_selector='td:nth-child(5) img',\n alias=\"They Supply Pump Check Mark\")\n self.active_start_date = element.Link(self, css_selector='td:nth-child(6)', alias=\"Active Start Date Text\")\n self.active_end_date = element.Link(self, css_selector='td:nth-child(6)', alias=\"Active End Date Text\")","def configure(self):\n inject(self.urls, self.names_for(\"urls\"))\n inject(self.models, self.names_for(\"models\"))\n self.load_admin()","def _load_template(self):\n filename = os.path.join(get_conf('DEFAULT_TEMPLATE_PATH'), self._template, '__init__.ini')\n cf = ApplicationConf.get_instance()\n with comp_open(filename, mode='r') as fp:\n content = fp.read()\n content = content.format(**cf)\n conf = CompConfigParser(allow_no_value=True)\n conf.read_string(content, '__init__.ini')\n ini = {'dirs': [], 'files': [], 'binaries': []}\n if conf.has_section('dirs'):\n for key in conf.options('dirs'):\n ini['dirs'].append(key)\n if conf.has_section('files'):\n for key in conf.options('files'):\n ini['files'].append(self.__remap(key))\n if conf.has_section('binaries'):\n for key in conf.options('binaries'):\n ini['binaries'].append(self.__remap(key))\n if isinstance(self._ini, dict):\n self._ini.update(ini)\n else:\n self._ini = ini","def index():\n return render_template('home.jinja2')","def controls_setup(self):\n\n self.subbie_name = element.Link(self, css_selector='th:nth-child(1) > a', alias=\"Admin Subbie Name Link\")\n self.type = element.Caption(self, css_selector='td:nth-child(2)', alias=\"Subbie Type\")\n self.username = element.Caption(self, css_selector='td:nth-child(3)', alias=\"Username\")\n self.email = element.Caption(self, css_selector='td:nth-child(4)', alias=\"Email\")\n self.active_start_date = element.Link(self, css_selector='td:nth-child(5)', alias=\"Active Start Date Text\")\n self.active_end_date = element.Link(self, css_selector='td:nth-child(6)', alias=\"Active End Date Text\")","def controls_setup(self):\n\n self.supervisor_name = element.Link(self, css_selector='th:nth-child(1) > a',\n alias=\"Admin Supervisor Name Link\")\n self.username = element.Caption(self, css_selector='td:nth-child(2)', alias=\"Username\")\n self.email = element.Caption(self, css_selector='td:nth-child(3)', alias=\"Email\")\n self.active_start_date = element.Link(self, css_selector='td:nth-child(4)', alias=\"Active Start Date Text\")\n self.active_end_date = element.Link(self, css_selector='td:nth-child(5)', alias=\"Active End Date Text\")","def _ProcessTemplate(self,topdir):\n self.dicomdir = \"%s/anatomicals\" % self.topdir\n self.rawdir = \"%s/raw\" % topdir\n self.rawdirs = {}\n tmplt = self._GetTemplate()\n if self.opts.outdir is not None:\n# Override template output directory.\n tmplt['top_outdir'] = self.opts.outdir\n self.tmplt = tmplt\n if len(tmplt['top_outdir']) == 0:\n tmplt['top_outdir'] = os.path.realpath(self.topdir)\n raise RuntimeError('Template file must specify an output directory.')\n tmplt['top_outdir'] = os.path.realpath(tmplt['top_outdir'])\n if '/home' in tmplt['top_outdir'][:7]:\n raise RuntimeError('Image data cannot be stored in the /home partition. Change the \"top_outdir\" entry in the template file: %s.' % (' '.join(self.templates)))\n# tmplt['subject'] = 'orig'\n self.procdir = os.path.abspath(\"%s/%s\" % \\\n (tmplt['top_outdir'],tmplt['subject']))\n target = os.path.abspath('%s/../..' % tmplt['top_outdir'])\n if not ismounted(target):\n raise RuntimeError('Could not access partition at %s' % target)\n\n self.anatdir = \"%s/anat\" % self.procdir\n self.fmapdir = \"%s/%s\" % (self.procdir,tmplt['fmap']['outdir'])\n self.dtidir = \"%s/%s\" % (self.procdir,tmplt['dti']['outdir'])\n self.logdir = \"%s/%s\" % (self.procdir,tmplt['logdir'])\n self.skip = tmplt.get('skip', DEFAULT_SKIP)\n self.acq_tr = tmplt.get('acq_tr',None)\n self.episetup_dir = \"%s/%s\" % (self.procdir,tmplt['first_epi'])\n self.fsl_cmpblty = tmplt.get('fsl_compatibility',False)\n self.epi_file_format = self.tmplt['epi_file_format']\n self.censor_thresh = tmplt.get('censor_threshold', 2.)\n self.censor_interleave = tmplt.get('censor_interleave', True)\n# self.server_userid = self.tmplt.get('server_userid','default')\n\n# Overide flags for aligning EPIs and skull-stripping with command-\n# line options.\n if self.opts.align_fmaps:\n self.align_fmaps = True\n else:\n self.align_fmaps = self.tmplt.get('epi_align', False)\n\n if self.opts.no_align_fmaps:\n self.no_align_fmaps = True\n else:\n self.no_align_fmaps = self.tmplt.get('no_epi_align', False)\n\n if self.opts.skull_strip:\n self.skull_strip = True\n else:\n self.skull_strip = self.tmplt.get('skull_strip', False)\n\n# Create log file now so it can be used immediately.\n if not os.path.exists(self.logdir):\n if self.verbose:\n print 'mkdir %s' % self.logdir\n if not self.opts.fake_opts:\n self.MakeDir(self.logdir)\n\n self._ProcessTemplateEpiInfo()","def build(self):\n self.logger.debug(\"run\")\n\n self.onInit()\n self.work()\n \n self.afterWork()\n\n template = Templateengine(self.currenttemplate)\n template.readTemplateFile()\n contenttype = self.settings.contenttype \n self.defaultTemplateParameter()\n \n try:\n self.content = template.get(self.tplparam)\n except Exception as ex:\n Emergency.stop(ex)\n\n self.onDone()\n \n self.logger.debug(\"done\")","def main(\n files: List[Path] = typer.Argument(default=None, dir_okay=False, exists=True),\n template: Optional[str] = typer.Option(\n None, '--template', help='Name of template file'\n ),\n logo: Optional[str] = typer.Option(None, '--logo', help='Name of logo file'),\n logo_width: Optional[str] = typer.Option(\n None, '--logo-width', help='Logo width (default 35mm)'\n ),\n highlight_style: Optional[str] = typer.Option(None, '--highlight-style',\n help='Specify coloring style to be used in highlighting source code'),\n syntax_definition: Optional[str] = typer.Option(None, '--syntax-definition',\n help='Specify a directory which contains syntax definition files'),\n no_toc: bool = typer.Option(\n False, '--no-toc', help='table of contents in PDF document'\n ),\n no_number_sections: bool = typer.Option(False, '--no-number-sections', help='no section numbering'),\n\n no_titlepage: bool = typer.Option(False, '--no-titlepage', help='title in PDF document'),\n tex_file: bool = typer.Option(\n False, '--tex', help='create TeX file instead of PDF document'\n ),\n email: Optional[str] = typer.Option(None, '--email', help='Author email'),\n company: Optional[str] = typer.Option(None, '--company', help='Name of company'),\n department: Optional[str] = typer.Option(\n None, '--department', help='Name of department'\n ),\n confidential: bool = typer.Option(\n False, '--confidential', help='indicate confidential'\n ),\n debug: bool = typer.Option(False, '--debug', help='turns debugging on'),\n pdf_engine: str = typer.Option(\n 'xelatex',\n '--pdf-engine',\n help='Specify pdf engine, one of lualatex, xelatex or tectonic ',\n ),\n _version: bool = typer.Option(\n None, '-V', '--version', callback=version_callback, help='Show version and exit'\n ),\n):\n\n if not files:\n typer.echo('Error: Must specify at least one .md file.')\n raise typer.Abort()\n\n mdfiles: List[str] = [str(md) for md in files]\n\n template = template or os.environ.get('MD2PDF_TEMPLATE')\n if template is None:\n print('No template specified')\n sys.exit(1)\n\n email = email or os.environ.get('MD2PDF_AUTHOR_EMAIL')\n footer_center = ''\n\n # command line overwrites `MD2PDF_PDF_ENGINE`. if both are not given\n # then `xelatex` is the default\n pdf_engine = pdf_engine or os.environ.get('MD2PDF_PDF_ENGINE') or 'xelatex'\n # check that pdf-engine is one of the following\n if pdf_engine not in ['xelatex', 'lualatex', 'tectonic']:\n print('--pdf-engine must be one of \"xelatex\", \"lualatex\", \"tectonic\"')\n sys.exit(1)\n\n ext = '.pdf'\n if tex_file:\n ext = '.tex'\n\n if len(mdfiles) == 1:\n toml_file = os.path.splitext(mdfiles[0])[0] + '.toml'\n\n if os.path.exists(toml_file):\n print(f'TOML file {toml_file} found')\n parsed_toml = toml.load(toml_file)\n default_val = parsed_toml.get('default')\n if default_val is None:\n print(f'No file names found in {toml_file}')\n else:\n mdfiles = default_val.get('files')\n\n for mdf in mdfiles:\n print(f'Compiling {mdf}')\n\n main_mdfile = os.path.realpath(mdfiles[0])\n\n outfile = Path(main_mdfile).stem + ext\n\n year = date.today().year\n\n company = company or os.environ.get('MD2PDF_COMPANY')\n department = department or os.environ.get('MD2PDF_DEPARTMENT')\n\n if company:\n if confidential:\n footer_center = f'© Copyright {year} {company}'\n else:\n footer_center = f'{year} {company}'\n\n pdcmd = PandocCmd(outfile)\n pdcmd.append(f'--template={template}')\n pdcmd.append(f'--pdf-engine={pdf_engine}')\n\n pdcmd.set_v('footer-center', footer_center)\n pdcmd.set_v('company', company)\n pdcmd.set_v('department', department)\n\n syntax_definition = syntax_definition or os.environ.get('MD2PDF_SYNTAX_DEFINITION_DIR')\n if syntax_definition is not None:\n add_syntax_definition(pdcmd, syntax_definition)\n\n pdcmd.append('--highlight-style')\n highlight_style = highlight_style or os.environ.get('MD2PDF_HIGHLIGHT_STYLE')\n if highlight_style is None:\n pdcmd.append('pygments')\n else:\n check_highlight_style(highlight_style)\n pdcmd.append(highlight_style)\n\n if not no_number_sections:\n pdcmd.append('--number-sections')\n\n if no_titlepage:\n pdcmd.set_m('titlepage', 'false')\n\n logo = logo or os.environ.get('MD2PDF_LOGO')\n pdcmd.set_v('logo', logo)\n\n logo_width = logo_width or os.environ.get('MD2PDF_LOGO_WIDTH')\n pdcmd.set_v('logo-width', logo_width)\n\n pdcmd.set_m('email', email)\n\n if not no_toc:\n pdcmd.append('--toc')\n\n pdcmd.extend(mdfiles)\n\n if debug:\n print(' '.join(pdcmd.pandoc))\n\n\n pdcmd.run()","def call(self, **kwargs):\n # Get additional resources links\n css = []\n for path in (\"creative/vendor/bootstrap/css/bootstrap.min.css\",\n \"creative/vendor/font-awesome/css/font-awesome.min.css\",\n \"creative/vendor/magnific-popup/magnific-popup.css\",\n \"creative/css/creative.css\"):\n css.append(self._cw.data_url(path))\n js = []\n for path in (\"creative/vendor/jquery/jquery.min.js\",\n \"creative/vendor/bootstrap/js/bootstrap.min.js\",\n \"creative/vendor/scrollreveal/scrollreveal.min.js\",\n \"creative/vendor/magnific-popup/jquery.magnific-popup.min.js\",\n \"creative/js/creative.js\"):\n js.append(self._cw.data_url(path))\n\n # Format template\n template = self._cw.vreg.template_env.get_template(\"startup.jinja2\")\n html = template.render(\n header_url=self._cw.data_url(\"creative/img/neurospin.jpg\"),\n login_url=self._cw.build_url(\n \"login\", __message=u\"Please login with your account.\"),\n contact_email=self._cw.vreg.config.get(\n \"administrator-emails\", \"noreply@cea.fr\"),\n css_url=css,\n js_url=js)\n self.w(html)","def test_home_route_uses_right_templates(self):\n response = self.client.get(\"/\")\n self.assertTemplateUsed(response, \"layout.html\")","def _GetTemplate(self):\n# First read default template.\n tmplt = self._LoadTemplate(c.preproc_template_default)\n tmplt['proc'] = self.topdir\n self.template_type = 'default'\n\n self.templates = []\n if self.template_file is not None:\n tmplt.update(self._LoadTemplate(self.template_file))\n self.template_type = 'command-line'\n self.templates.append(os.path.abspath(self.template_file))\n found_template = True\n else:\n# Find a study specific template file.\n study_template_file = self._FindTemplateFile('%s/..' % self.topdir)\n if study_template_file is not None:\n# Merge study template into default, study template has precedence.\n if self.verbose:\n print \"Using study template at \" + study_template_file\n tmplt.update(self._LoadTemplate(study_template_file))\n self.template_type = 'study-specific'\n self.templates.append(os.path.abspath(study_template_file))\n found_template = True\n else:\n found_template = False\n# Now look for a subject-specific template file.\n subject_template_file = self._FindTemplateFile('%s' % self.topdir)\n if subject_template_file is not None:\n# Merge subject template, subject template has precedence.\n if self.verbose:\n print \"Using subject-specific template at %s\" % \\\n subject_template_file\n tmplt.update(self._LoadTemplate(subject_template_file))\n self.template_type = 'study-specific'\n self.templates.append(os.path.abspath(subject_template_file))\n found_template = True\n\n if not found_template:\n raise RuntimeError('Could not find template file.')\n\n if tmplt.get('subject','same') == 'same':\n# Default subdirectory is same as data directory.\n tmplt['subject'] = self.topdir.split('/')[-1]\n else:\n if not isinstance(tmplt['subject'],str):\n errstr = 'preprocess: Invalid subject number. Be sure to ' + \\\n 'enclose the subject number item with double quotes.'\n raise RuntimeError(errstr)\n\n# Keys that apply to all EPIs.\n self.fsl_flip = tmplt.get('fsl_flip', False)\n if self.fsl_flip:\n self.flip_opts = '-LT'\n else:\n self.flip_opts = ''\n\n# Replace strings with python types.\n for key in tmplt.keys():\n if tmplt[key] == 'None':\n tmplt[key] = None\n elif key == 'True':\n tmplt[key] = True\n elif key == 'False':\n tmplt[key] = False\n return tmplt","def preRunSetup(self):\n self.logDesc(\"Pre Run Setup\")\n #Check for current logged in user\n self.verifyCurrentUser(userRole='Administrator', loginAsUser=True)\n #Creates Sample Template if not exists\n self.createSampleTemplate(templateName=self.templateName)","def run(self):\n self.render_templates()\n self.create_docker_context()\n self.build()\n self.push()","def test_correct_main_page_template(self):\n response = self.client.get('/')\n self.assertTemplateUsed(response, 'main.html')","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass"],"string":"[\n \"def setup_templates(self):\\n self.libs[\\\"template\\\"] = (\\\"#libs/templates/include\\\", None, \\\"\\\")\\n self[\\\"CPPPATH\\\"].append(\\\"#libs/templates/include\\\")\",\n \"def setUp(self):\\n print \\\"Setting Up: %s\\\" % self.id()\\n # render the template\\n g.render_template(self.template_file,\\n self.template_vars,\\n self.output_file,\\n self.search_path)\\n\\n # read the resulting config file built from template\\n self.output_config = g.load_config(self.output_file)\\n g.show_config(self.output_config)\",\n \"def setUp(self):\\r\\n capa_path = capa.__path__[0]\\r\\n self.template_path = os.path.join(capa_path,\\r\\n 'templates',\\r\\n self.TEMPLATE_NAME)\\r\\n with open(self.template_path) as f:\\r\\n self.template = MakoTemplate(f.read())\",\n \"def __fill_all_templates__(self,configs):\\n template_dir = configs['system'].get('Common_directories','template')\\n sample_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','sample'))\\n system_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','system'))\\n qsub_template = os.path.join(template_dir,configs['pipeline'].get('Template_files','bcbio'))\\n self.__fill_template__(sample_template,self.sample_file)\\n self.__fill_template__(system_template,self.systems_file)\\n self.__fill_template__(qsub_template,self.qsub_file)\",\n \"def use_templates(self, templates):\\n self.htmls = templates\",\n \"def _set_templates(spm_dir=SPM_DIR):\\n global EPI_TEMPLATE, T1_TEMPLATE, GM_TEMPLATE, WM_TEMPLATE, CSF_TEMPLATE\\n\\n spm_version = _get_version_spm(SPM_DIR)\\n\\n # Set the tpm and template paths according to SPM version\\n if spm_version == 'spm12':\\n template_path = 'toolbox/OldNorm'\\n tpm_path = 'toolbox/OldSeg'\\n else:\\n template_path = 'templates'\\n tpm_path = 'tpm'\\n\\n # configure template images\\n EPI_TEMPLATE = os.path.join(SPM_DIR, template_path, 'EPI.nii')\\n SPM_T1_TEMPLATE = os.path.join(SPM_DIR, template_path, 'T1.nii')\\n T1_TEMPLATE = \\\"/usr/share/data/fsl-mni152-templates/avg152T1.nii\\\"\\n if not os.path.isfile(T1_TEMPLATE):\\n T1_TEMPLATE += '.gz'\\n if not os.path.exists(T1_TEMPLATE):\\n T1_TEMPLATE = SPM_T1_TEMPLATE\\n GM_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'grey.nii')\\n WM_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'white.nii')\\n CSF_TEMPLATE = os.path.join(SPM_DIR, tpm_path, 'csf.nii')\",\n \"def setUp(self):\\n BuilderTestsMixin.setUp(self)\\n self.builder = DocBuilder()\\n self.howtoDir = FilePath(self.mktemp())\\n self.howtoDir.createDirectory()\\n self.templateFile = self.howtoDir.child(\\\"template.tpl\\\")\\n self.templateFile.setContent(self.template)\",\n \"def __init__(self, template_dirs=[], include_comments=False,\\n include_introspection_server=False):\\n # Flag to enable rendering of header and footer comments in templates\\n self._include_comments = include_comments\\n\\n # Flag to enable inclusion of introspection server (for use with\\n # smach_viewer)\\n self._include_introspection_server = include_introspection_server\\n\\n # Create list of any custom user-defined template dirs + default\\n # template dir\\n self._template_dirs = (\\n template_dirs +\\n [os.path.join(os.path.dirname(os.path.realpath(__file__)),\\n 'templates')])\\n\\n # Create template loader for the template directories\\n template_loaders = [\\n jinja2.FileSystemLoader(template_dir)\\n for template_dir in self._template_dirs]\\n self._template_loader = jinja2.ChoiceLoader(template_loaders)\\n\\n # Create an environment for reading and parsing templates, including\\n # the SkipBlockExtension class to allow for skipping certain blocks.\\n self._template_env = (\\n jinja2.Environment(loader=self._template_loader,\\n extensions=[jinja2.ext.do,\\n SkipBlockExtension],\\n trim_blocks=False,\\n lstrip_blocks=True))\\n\\n # Skip comment blocks as required\\n if not self._include_comments:\\n self._template_env.skip_blocks.append('upper_comments')\\n self._template_env.skip_blocks.append('lower_comments')\\n\\n # Skip introspection server blocks as required\\n if not self._include_introspection_server:\\n self._template_env.skip_blocks.append('introspection_server')\\n self._template_env.skip_blocks.append('spin')\\n\\n # Register custom tests with the environment\\n self._template_env.tests['expression'] = expression\\n self._template_env.tests['not_string'] = not_string\\n\\n # Register custom filters with the environment\\n self._template_env.filters['exptostr'] = exptostr\\n\\n # Create a template references cache dictionary\\n # to be indexed by template names.\\n self._template_ref_names_cache = {}\\n\\n # Create a template block names cache dictionary\\n # to be indexed by template names.\\n self._template_block_names_cache = {}\\n\\n # Create a template block cache dictionary\\n # to be indexed by tuples of the form (template_name, block_name)\\n self._template_block_cache = {}\\n\\n pass\",\n \"def run():\\r\\n template_locations = settings.MAKO_TEMPLATES\\r\\n for namespace, directories in template_locations.items():\\r\\n clear_lookups(namespace)\\r\\n for directory in directories:\\r\\n add_lookup(namespace, directory)\",\n \"def test_register_template(self):\\n pass\",\n \"def __init__(self, ctx, verbose=0) -> None:\\n\\n self.__ctx__ = ctx\\n TemplateHandler.templates_path = ctx.obj['TEMPLATES_FOLDER']\\n self.verbose = verbose\\n\\n self.validate_templates_path()\\n if len(TemplateHandler.templates) == 0:\\n self.load_templates()\",\n \"def get_templates(self):\\n\\n data = self.request_from_server('templates')\\n self.templates = data\",\n \"def main(temp_dir, extensions, template):\\n env = load_env(template_dir=temp_dir)\\n if not template:\\n # Get all the templates and return a dict with enumerated \\n # templates names\\n ext = extensions if extensions else []\\n template_dict = get_templates(env, extensions=ext)\\n # Echo the content of the template directory by enumerating \\n # the templates and a simple list join\\n temp_list = list()\\n for x in template_dict.items():\\n num = str(x[0])\\n # Remove whitespace, underscores and capitalize words\\n temp_name = x[1].strip().replace(\\\"_\\\", \\\" \\\").title()\\n temp_string = \\\"{}. {}\\\".format(num, temp_name)\\n temp_list.append(temp_string)\\n click.echo(\\\"\\\\n\\\".join(temp_list))\\n # Prompt the user to give the number of the template\\n temp_num = click.prompt(\\n \\\"Choose a templeta by entering the number of the template.\\\",\\n type=int\\n )\\n # Get the template from the template dictionary\\n template = template_dict.get(temp_num)\\n # Get the variables\\n temp_vars = get_vars(template, env)\\n # Crate a dict with variables and let the user input the variables\\n vars_to_render = dict()\\n for var in temp_vars:\\n user_var = click.prompt(\\\"{}?\\\".format(var.capitalize()))\\n vars_to_render[var] = user_var\\n # Get the template\\n temp = env.get_template(template)\\n # Render the template\\n click.echo(temp.render(vars_to_render))\",\n \"def _setup(self):\\n self._raw_top_dir = os.path.join(self._snippets_dir,\\\"raw\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._raw_top_dir):\\n os.mkdir(self._raw_top_dir)\\n\\n self._trec_top_dir = os.path.join(self._snippets_dir,\\\"trec\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._trec_top_dir):\\n os.mkdir(self._trec_top_dir)\\n\\n self._temp_top_dir = os.path.join(self._snippets_dir,\\\"temp\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._temp_top_dir):\\n os.mkdir(self._temp_top_dir)\\n\\n self._snippet_result_top_dir = os.path.join(self._snippets_dir,\\\"result\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._snippet_result_top_dir):\\n os.mkdir(self._snippet_result_top_dir)\\n\\n self._snippet_index_top_dir = os.path.join(self._snippets_dir,\\\"index\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._snippet_index_top_dir):\\n os.mkdir(self._snippet_index_top_dir)\\n\\n self._para_top_dir = os.path.join(self._snippets_dir,\\\"para\\\",\\\"dynamic\\\")\\n if not os.path.exists(self._para_top_dir):\\n os.mkdir(self._para_top_dir)\",\n \"def test_create_template_for_all_namespaces(self):\\n pass\",\n \"def main():\\n VALIDATE_TEMPLATE(TEMPLATES)\",\n \"def main():\\n VALIDATE_TEMPLATE(TEMPLATES)\",\n \"def site_setup(self, tmpdir):\\n templates = tmpdir.mkdir(\\\"templates\\\")\\n templates.join(\\\"def.html\\\").write(\\\"{{ content }}\\\")\\n\\n content = tmpdir.mkdir(\\\"content\\\")\\n output = tmpdir.mkdir(\\\"output\\\")\\n config_dict = {\\n \\\"theme_dir\\\": str(templates),\\n \\\"default_template\\\": \\\"def.html\\\",\\n \\\"content\\\": str(content)\\n }\\n config_file = tmpdir.join(\\\"config.yml\\\")\\n config_file.write(yaml.dump(config_dict))\\n config = SiteConfig(str(config_file))\\n s_gen = SiteGenerator(config)\\n return templates, content, output, s_gen\",\n \"def render_templates(self):\\n\\n # dockerfile\\n try:\\n t = self.templates.get_template(\\n 'docker/dockerfiles/{}.dockerfile.template'.format(self.repo)\\n )\\n except TemplateNotFound:\\n t = self.templates.get_template(\\n 'docker/dockerfiles/default.dockerfile.template'\\n )\\n\\n self.files.append({\\n 'name': 'Dockerfile',\\n 'content': t.render(commit=self.commit),\\n })\\n\\n # gunicorn\\n t = self.templates.get_template(\\n 'docker/gunicorn/gunicorn.conf.py'\\n )\\n self.files.append({\\n 'name': 'gunicorn.conf.py',\\n 'content': t.render(),\\n })\\n\\n t = self.templates.get_template(\\n 'docker/gunicorn/gunicorn.sh'\\n )\\n self.files.append({\\n 'name': 'gunicorn.sh',\\n 'content': t.render(),\\n 'mode': 0555,\\n })\\n\\n # nginx\\n t = self.templates.get_template(\\n 'docker/nginx/app.nginx.conf'\\n )\\n self.files.append({\\n 'name': 'app.nginx.conf',\\n 'content': t.render(),\\n })\\n\\n t = self.templates.get_template(\\n 'docker/nginx/nginx.sh'\\n )\\n self.files.append({\\n 'name': 'nginx.sh',\\n 'content': t.render(),\\n 'mode': 0555,\\n })\\n\\n # cron/, etc/ iif there exists a `self.repo` directory\\n def _filter(p):\\n return (\\\"cron/\\\" in p or \\\"etc/\\\" in p) and (self.repo in p) and \\\\\\n (not os.path.basename(p).startswith('.'))\\n\\n for t in self.templates.list_templates(\\n filter_func=_filter):\\n\\n self.files.append({\\n 'name': os.path.basename(t),\\n 'content': self.templates.get_template(t).render(),\\n })\",\n \"def init_templates( path=\\\"boilerplate\\\" ):\\n global template_env\\n template_loader = jinja2.FileSystemLoader(searchpath=\\\"boilerplate\\\" )\\n template_env = jinja2.Environment(\\n loader=template_loader,\\n lstrip_blocks=True\\n )\",\n \"def __setup_template(self):\\n template = Template()\\n template.add_description(\\\"Service VPC - used for services\\\")\\n\\n template.add_metadata({\\n \\\"Build\\\": \\\"development\\\",\\n \\\"DependsOn\\\": [],\\n \\\"Environment\\\": \\\"ApiDev\\\",\\n \\\"Revision\\\": \\\"develop\\\",\\n \\\"StackName\\\": \\\"ApiDev-Dev-VPC\\\",\\n \\\"StackType\\\": \\\"InfrastructureResource\\\",\\n \\\"TemplateBucket\\\": \\\"cfn-apidev\\\",\\n \\\"TemplateName\\\": \\\"VPC\\\",\\n \\\"TemplatePath\\\": \\\"ApiDev/Dev/VPC\\\"\\n })\\n\\n vpc = template.add_resource(\\n ec2.VPC(\\n \\\"VPC\\\",\\n CidrBlock=\\\"10.0.0.0/16\\\",\\n EnableDnsHostnames=\\\"true\\\",\\n EnableDnsSupport=\\\"true\\\",\\n InstanceTenancy=\\\"default\\\",\\n Tags=self.__get_tags(\\\"ServiceVPC\\\"),\\n )\\n )\\n\\n instance_sg = template.add_resource(\\n ec2.SecurityGroup(\\n \\\"BastionSG\\\",\\n GroupDescription=\\\"Used for source/dest rules\\\",\\n Tags=self.__get_tags(\\\"VPC-Bastion-SG\\\"),\\n VpcId=Ref(\\n vpc\\n )\\n ),\\n )\\n\\n cw_alarm_topic = template.add_resource(\\n Topic(\\n \\\"CloudWatchAlarmTopic\\\",\\n TopicName=\\\"ApiDev-Dev-CloudWatchAlarms\\\",\\n )\\n )\\n\\n dhcp_options = template.add_resource(\\n ec2.DHCPOptions(\\n \\\"DhcpOptions\\\",\\n DomainName=Join(\\n \\\"\\\",\\n [\\n Ref(\\\"AWS::Region\\\"),\\n \\\".compute.internal\\\"\\n ]\\n ),\\n DomainNameServers=[\\\"AmazonProvidedDNS\\\"],\\n Tags=self.__get_tags(\\\"DhcpOptions\\\"),\\n )\\n )\\n\\n gateway = template.add_resource(\\n ec2.InternetGateway(\\n \\\"InternetGateway\\\",\\n Tags=self.__get_tags(\\\"InternetGateway\\\")\\n )\\n )\\n\\n nat_emergency_topic = template.add_resource(\\n Topic(\\n \\\"NatEmergencyTopic\\\",\\n TopicName=\\\"ApiDev-Dev-NatEmergencyTopic\\\",\\n )\\n )\\n\\n vpc_dhcp_options_assoc = template.add_resource(\\n ec2.VPCDHCPOptionsAssociation(\\n \\\"VpcDhcpOptionsAssociation\\\",\\n DhcpOptionsId=Ref(\\n dhcp_options\\n ),\\n VpcId=Ref(\\n vpc\\n )\\n )\\n )\\n\\n vpc_gw_attachment = template.add_resource(\\n ec2.VPCGatewayAttachment(\\n \\\"VpcGatewayAttachment\\\",\\n InternetGatewayId=Ref(\\n gateway\\n ),\\n VpcId=Ref(\\n vpc\\n )\\n )\\n )\\n\\n vpc_network_acl = template.add_resource(\\n ec2.NetworkAcl(\\n \\\"VpcNetworkAcl\\\",\\n Tags=self.__get_tags(\\\"NetworkAcl\\\"),\\n VpcId=Ref(\\n vpc\\n )\\n )\\n )\\n\\n vpc_network_acl_rules = template.add_resource([\\n ec2.NetworkAclEntry(\\n \\\"VpcNetworkAclInboundRulePublic443\\\",\\n CidrBlock=\\\"0.0.0.0/0\\\",\\n Egress=\\\"false\\\",\\n NetworkAclId=Ref(\\n vpc_network_acl\\n ),\\n PortRange=ec2.PortRange(\\n From=\\\"443\\\",\\n To=\\\"443\\\",\\n ),\\n Protocol=\\\"6\\\",\\n RuleAction=\\\"allow\\\",\\n RuleNumber=20001\\n ),\\n ec2.NetworkAclEntry(\\n \\\"VpcNetworkAclInboundRulePublic80\\\",\\n CidrBlock=\\\"0.0.0.0/0\\\",\\n Egress=\\\"false\\\",\\n NetworkAclId=Ref(\\n vpc_network_acl\\n ),\\n PortRange=ec2.PortRange(\\n From=\\\"80\\\",\\n To=\\\"80\\\",\\n ),\\n Protocol=\\\"6\\\",\\n RuleAction=\\\"allow\\\",\\n RuleNumber=20000\\n ),\\n ec2.NetworkAclEntry(\\n \\\"VpcNetworkAclOutboundRule\\\",\\n CidrBlock=\\\"0.0.0.0/0\\\",\\n Egress=\\\"true\\\",\\n NetworkAclId=Ref(\\n vpc_network_acl\\n ),\\n Protocol=\\\"-1\\\",\\n RuleAction=\\\"allow\\\",\\n RuleNumber=30000\\n ),\\n ec2.NetworkAclEntry(\\n \\\"VpcNetworkAclSsh\\\",\\n CidrBlock=\\\"127.0.0.1/32\\\",\\n Egress=\\\"false\\\",\\n NetworkAclId=Ref(\\n vpc_network_acl\\n ),\\n PortRange=ec2.PortRange(\\n From=\\\"22\\\",\\n To=\\\"22\\\",\\n ),\\n Protocol=\\\"6\\\",\\n RuleAction=\\\"allow\\\",\\n RuleNumber=10000\\n )\\n ])\\n\\n template.add_output([\\n Output(\\n \\\"BastionSG\\\",\\n Value=Ref(instance_sg)\\n ),\\n Output(\\n \\\"CloudWatchAlarmTopic\\\",\\n Value=Ref(cw_alarm_topic)\\n ),\\n Output(\\n \\\"InternetGateway\\\",\\n Value=Ref(gateway)\\n ),\\n Output(\\n \\\"NatEmergencyTopicARN\\\",\\n Value=Ref(nat_emergency_topic)\\n ),\\n Output(\\n \\\"VPCID\\\",\\n Value=Ref(vpc)\\n ),\\n Output(\\n \\\"VPCName\\\",\\n Value=Ref(\\\"AWS::StackName\\\")\\n ),\\n Output(\\n \\\"VpcNetworkAcl\\\",\\n Value=Ref(vpc_network_acl)\\n )\\n\\n ])\\n\\n return template\",\n \"def __init__(self, settings):\\n self.mylookup = TemplateLookup(\\n directories = [join(settings['root'],rpath) for rpath in settings['view_paths']],\\n output_encoding='utf-8')\\n \\n self.routes = []\\n self._part_matcher = re.compile(r'{.*?}')\\n self.error_handler = noop\",\n \"def __init__(self, *args, **kwargs):\\r\\n super(ServeeAdminSite, self).__init__(*args, **kwargs)\\r\\n\\r\\n self.name = \\\"servee\\\"\\r\\n self.app_name = \\\"servee\\\"\\r\\n self.uses_wysiwyg = \\\"servee.wysiwyg\\\" in settings.INSTALLED_APPS\\r\\n\\r\\n self.index_template = [\\\"servee/index.html\\\", \\\"admin/index.html\\\"]\\r\\n self.login_template = [\\\"servee/login.html\\\", \\\"admin/login.html\\\"]\\r\\n self.logout_template = [\\\"servee/logout.html\\\", \\\"admin/logout.html\\\"]\\r\\n self.password_change_template = [\\\"servee/password_change.html\\\", \\\"admin/password_change.html\\\"]\\r\\n self.password_change_done_template = [\\\"servee/password_change_done.html\\\", \\\"admin/password_change_done.html\\\"]\",\n \"def load_templates(self):\\n TemplateHandler.templates = []\\n for template in os.listdir(TemplateHandler.templates_path):\\n template_config = self.load_template_conf(template)\\n if template_config is None:\\n continue\\n TemplateHandler.templates.append(template_config)\",\n \"def update():\\n if Project.use_templates:\\n defaults = _project_defaults()\\n\\n template = Template()\\n\\n for template_dir in [os.path.abspath(os.path.join(herringlib, 'herringlib', 'templates'))\\n for herringlib in HerringFile.herringlib_paths]:\\n\\n info(\\\"template directory: %s\\\" % template_dir)\\n # noinspection PyArgumentEqualDefault\\n template.generate(template_dir, defaults, overwrite=False)\",\n \"def __init__(self, name, template_folder):\\n super().__init__(name)\",\n \"def prepare(self):\\n self.parse_template()\\n self.build_argparser()\\n self.parse_arguments()\\n self.render_template()\\n self.update_relation()\",\n \"def startup(self, title=None, author=None, uid=None):\\n title, author, uid = self._collect_metadata(title, author, uid)\\n self._generate_skeleton(title, author, uid, from_dirpath=TEMPLATE_DIRPATH)\",\n \"def __init__(self, template_name):\\n # self.env = Environment(loader=PackageLoader(\\n # package, path))\\n # self.template = self.env.get_template(template_name)\\n with open(template_name, 'r', encoding='UTF-8') as f:\\n self.template = Template(f.read())\",\n \"def __init__(self, template_dir=None, package_name=None):\\r\\n self._template_dir = template_dir\\r\\n self._package_name = package_name\\r\\n self._pystache_renderer = pystache.Renderer(search_dirs=template_dir)\",\n \"def html_template_file(self):\\n pass\",\n \"def main():\\r\\n return render_template(\\\"UI.html\\\")\",\n \"def _load_templates(cls):\\n if cls._raw_templates is None:\\n cls._raw_templates = fetch_rrlyrae_templates()\",\n \"def init():\\n defaults = _project_defaults()\\n\\n if Project.prompt:\\n defaults['name'] = prompt(\\\"Enter the project's name:\\\", defaults['name'])\\n defaults['package'] = prompt(\\\"Enter the project's package:\\\", defaults['package'])\\n defaults['author'] = prompt(\\\"Enter the project's author:\\\", defaults['author'])\\n defaults['author_email'] = prompt(\\\"Enter the project's author's email:\\\", defaults['author_email'])\\n defaults['description'] = prompt(\\\"Enter the project's description:\\\", defaults['description'])\\n\\n # print(\\\"defaults:\\\\n{defaults}\\\".format(defaults=pformat(defaults)))\\n\\n if Project.use_templates:\\n\\n template = Template()\\n\\n for template_dir in [os.path.abspath(os.path.join(herringlib, 'herringlib', 'templates'))\\n for herringlib in HerringFile.herringlib_paths]:\\n\\n info(\\\"template directory: %s\\\" % template_dir)\\n # noinspection PyArgumentEqualDefault\\n template.generate(template_dir, defaults, overwrite=False)\",\n \"def load_templates(self):\\n\\n self.templates = []\\n\\n if os.path.exists(\\\"question_templates.txt\\\"):\\n for line in open(\\\"question_templates.txt\\\", \\\"r\\\"):\\n self.templates.append(line.replace(\\\"\\\\n\\\", \\\"\\\"))\",\n \"def test_functionality(self):\\n self.templateName = \\\"Test Template\\\"\\n self.browserObject = globalVars.browserObject\\n\\n self.preRunSetup()\\n \\n self.runTestCase()\\n \\n self.postRunCleanup()\",\n \"def __init__(self):\\n super().__init__()\\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\\n\\n step1 = PrepareAppConfTransfiguration()\\n step2 = ConfReaderToContextTransfiguration()\\n step3 = ValidateCollectionTags()\\n step4 = AttributeChainedTransfiguration('mbean')\\n step5 = AttributeChainedTransfiguration('connection')\\n\\n self.add(step1)\\n self.add(step2)\\n self.add(step3)\\n self.add(step4)\\n self.add(step5)\",\n \"def test_config(self):\\n self.assertEqual(self.view.template_name, \\\"resources/templanguage_admin.html\\\")\",\n \"def setup_theme(app):\\r\\n theme = app.config['THEME']\\r\\n app.template_folder = os.path.join('themes', theme, 'templates')\\r\\n app.static_folder = os.path.join('themes', theme, 'static')\",\n \"async def setup(self):\\n load_base_templates()\\n uris = URI.gather()\\n for uri, resource in uris.items():\\n methods = resource.methods\\n if \\\"get\\\" not in methods:\\n methods[\\\"get\\\"] = None\\n\\n for method in methods.keys():\\n self.app.add_routes([\\n getattr(aioweb, method)(uri, resource.process)\\n ])\\n self.app.add_routes([aioweb.get(\\\"/hello\\\", hello)])\\n\\n # TMP code\\n max_age = 3600 * 24 * 365 # 1 year\\n setup(self.app, PonyStorage(max_age=max_age))\\n self.preparing_task = asyncio.create_task(self.prepare_web())\",\n \"def _setup(self):\\n self._raw_dir = os.path.join(self._snippets_dir,\\\"raw\\\",\\\"static\\\")\\n if not os.path.exists(self._raw_dir):\\n os.mkdir(self._raw_dir)\\n\\n self._trec_dir = os.path.join(self._snippets_dir,\\\"trec\\\",\\\"static\\\")\\n if not os.path.exists(self._trec_dir):\\n os.mkdir(self._trec_dir)\\n\\n self._temp_dir = os.path.join(self._snippets_dir,\\\"temp\\\",\\\"static\\\")\\n if not os.path.exists(self._temp_dir):\\n os.mkdir(self._temp_dir)\\n\\n self._para_dir = os.path.join(self._snippets_dir,\\\"para\\\",\\\"static\\\")\\n if not os.path.exists(self._para_dir):\\n os.mkdir(self._para_dir)\\n\\n self._snippet_result_dir = os.path.join(self._snippets_dir,\\\"result\\\",\\\"static\\\")\\n if not os.path.exists(self._snippet_result_dir):\\n os.mkdir(self._snippet_result_dir)\\n\\n self._snippet_index_dir = os.path.join(self._snippets_dir,\\\"index\\\",\\\"static\\\")\\n if not os.path.exists(self._snippet_index_dir):\\n os.mkdir(self._snippet_index_dir)\\n\\n \\n\\n\\n self._index_para = os.path.join(self._para_dir,\\\"index_para\\\")\\n\\n self._temp_query_para = os.path.join(self._para_dir,\\\"temp_query_para\\\")\\n\\n self._index_list = os.path.join(self._para_dir,\\\"static_index_list\\\")\\n \\n self._orf = os.path.join(self._snippet_result_dir,\\\"orf\\\")\\n\\n self._oqf = os.path.join(self._temp_dir,\\\"oqf\\\")\\n \\n self._temp_output = os.path.join(self._temp_dir,\\\"temp_output\\\")\\n\\n with open(self._index_list,\\\"w\\\") as f:\\n f.write(self._snippet_index_dir+\\\"\\\\n\\\")\\n\\n self._temp_query_builder = IndriQueryFactory(count=10000,\\n rule=self._retrieval_method)\\n\\n self._oqf_builder = IndriQueryFactory(count=30,\\n rule=self._retrieval_method)\",\n \"def __init__(self, template_path=None):\\n if template_path:\\n self.template_env = Environment(\\n loader=FileSystemLoader(template_path),\\n autoescape=select_autoescape([\\\"html\\\", \\\"xml\\\"]),\\n )\\n self.template_list = self.template_env.list_templates()\\n else:\\n # Loading built-in templates from the genalog package\\n self.template_env = Environment(\\n loader=PackageLoader(\\\"genalog.generation\\\", \\\"templates\\\"),\\n autoescape=select_autoescape([\\\"html\\\", \\\"xml\\\"]),\\n )\\n # Remove macros and css templates from rendering\\n self.template_list = self.template_env.list_templates(\\n filter_func=DocumentGenerator._keep_template\\n )\\n\\n self.set_styles_to_generate(DEFAULT_STYLE_COMBINATION)\",\n \"def test_create_template_subsciption(self):\\n pass\",\n \"def main():\\n\\n return render_template(\\\"index.html\\\", title=\\\"Home\\\", heading=\\\"Dublin Bus\\\")\",\n \"def create_template(self, path: Path, dot_cookietemple: Optional[dict]) -> None:\\n self.web_struct.language = cookietemple_questionary_or_dot_cookietemple(function='select',\\n question='Choose between the following languages',\\n choices=['python'],\\n default='python',\\n dot_cookietemple=dot_cookietemple,\\n to_get_property='language')\\n\\n # prompt the user to fetch general template configurations\\n super().prompt_general_template_configuration(dot_cookietemple)\\n\\n # switch case statement to prompt the user to fetch template specific configurations\\n switcher: Dict[str, Any] = {\\n 'python': self.web_python_options,\\n }\\n switcher.get(self.web_struct.language)(dot_cookietemple) # type: ignore\\n # call handle function for specified language\\n self.__getattribute__(f'handle_web_project_type_{self.web_struct.language}')(dot_cookietemple)\\n # call handle function for specified webtype according to the chosen language\\n self.__getattribute__(f'handle_{self.web_struct.webtype.lower()}_{self.web_struct.language}')(dot_cookietemple)\\n # call option function for specified framework (if any)\\n framework = self.web_struct.web_framework.lower()\\n if framework:\\n self.__getattribute__(f'{self.web_struct.webtype.lower()}_{framework}_options')(dot_cookietemple)\\n\\n self.web_struct.is_github_repo, self.web_struct.is_repo_private, self.web_struct.is_github_orga, self.web_struct.github_orga = \\\\\\n prompt_github_repo(dot_cookietemple)\\n # if repo owner is a github orga, update username\\n if self.web_struct.is_github_orga:\\n self.web_struct.github_username = self.web_struct.github_orga\\n # create the project (TODO COOKIETEMPLE: As for now (only Flask) this works. Might need to change this in future.\\n super().create_template_with_subdomain_framework(self.TEMPLATES_WEB_PATH, self.web_struct.webtype, self.web_struct.web_framework.lower())\\n # clean project for advanced or basic setup\\n self.basic_or_advanced_files_with_frontend(self.web_struct.setup_type, self.web_struct.frontend.lower())\\n\\n # switch case statement to fetch the template version\\n switcher_version = {\\n 'python': self.WEB_WEBSITE_PYTHON_TEMPLATE_VERSION\\n }\\n\\n self.web_struct.template_version, self.web_struct.template_handle\\\\\\n = switcher_version.get(self.web_struct.language), f'web-{self.web_struct.webtype}-{self.web_struct.language.lower()}' # type: ignore\\n\\n # perform general operations like creating a GitHub repository and general linting\\n super().process_common_operations(path=Path(path).resolve(), domain='web',\\n subdomain=self.web_struct.webtype,\\n language=self.web_struct.language,\\n dot_cookietemple=dot_cookietemple)\",\n \"def create_templates(self):\\n for name, params in list_registered_templates():\\n if self['templates'].filter(theme=self, name=name).count() == 0:\\n self['templates'].create(theme=self, name=name)\",\n \"def __init__(self):\\n super().__init__()\\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\\n\\n step1 = PrepareAppConfTransfiguration()\\n step2 = ConfReaderToContextTransfiguration()\\n step3 = AttributeChainedTransfiguration('mbean')\\n\\n self.add(step1)\\n self.add(step2)\\n self.add(step3)\",\n \"def __init__(self):\\n super().__init__()\\n TemplateEngineFactory.register_factory('Jinja2Engine', Jinja2Engine.Factory)\\n\\n step1 = CommonMBeansChainedTransfiguration()\\n step2 = SpliByApplicationTransfiguration()\\n step3 = ConsolidateToFinalOutput()\\n\\n self.add(step1)\\n self.add(step2)\\n self.add(step3)\",\n \"def _buildjinja2_templates(self):\\n templates = self.embryo.templates\\n\\n # if templates is a module extract its public string attributes\\n # into the templates dict expected below.\\n if isinstance(templates, ModuleType):\\n tmp_templates = {}\\n for k in dir(templates):\\n v = getattr(templates, k)\\n if (not k.startswith('_')) and isinstance(v, (str, Template)):\\n tmp_templates[k] = v\\n templates = tmp_templates\\n\\n # load the jinja2 templates contained in the module, either in the form\\n # of Template objects or strings.\\n loaded_templates = {}\\n jinja_env = build_env()\\n\\n if templates:\\n for k, v in templates.items():\\n say('loading template: {}'.format(k))\\n if isinstance(v, Template):\\n loaded_templates[k] = v\\n elif isinstance(v, str):\\n try:\\n loaded_templates[k] = jinja_env.from_string(v)\\n except Exception as exc:\\n source = exc.source.split('\\\\n')[exc.lineno - 1]\\n shout(f'error \\\"{exc.message}\\\", line {exc.lineno} {source}')\\n\\n self.jinja2_templates = loaded_templates\",\n \"def _setup_jinja(manager: ConfigServiceManager, app: web.Application):\\n\\n tpl_path = manager.env.get('TEMPLATE_PATH')\\n if not tpl_path:\\n tpl_path = os.path.join(manager.config_root, 'templates')\\n # load default templates provided by package\\n loader = PackageLoader('vonx', 'templates')\\n if tpl_path:\\n # load custom templates if present\\n # may want to use a resource loader if tpl_path looks like a package name (has a colon)\\n loader = ChoiceLoader([\\n loader,\\n FileSystemLoader(tpl_path)\\n ])\\n filters = {\\\"jsonify\\\": json.dumps}\\n aiohttp_jinja2.setup(app, loader=loader, filters=filters)\",\n \"def __init__(self, *args, **kwargs):\\r\\n if not kwargs.get('no_django', False):\\r\\n overrides = {k: getattr(edxmako, k, None) for k in DJANGO_VARIABLES}\\r\\n overrides['lookup'] = edxmako.LOOKUP['main']\\r\\n kwargs.update(overrides)\\r\\n super(Template, self).__init__(*args, **kwargs)\",\n \"def run(self):\\n make_sure_path_exists(OUT_FOLDER)\\n\\n if self.config['type'] == 'website':\\n make_sure_path_exists(self.config['out_folder'])\\n\\n\\n for file in self.config['bodies']:\\n if file['type'] == 'content':\\n self.pandoc_file(file)\\n if self.config['type'] == 'website':\\n shutil.copyfile(file['generated'], os.path.join(self.config['out_folder'], os.path.basename(file['source'])))\\n\\n if self.config['type'] == 'website':\\n return\\n\\n for file in self.config['abstract']:\\n self.pandoc_file(file)\\n for file in self.config['summary']:\\n self.pandoc_file(file)\\n\\n template = LATEX_JINJA_ENV.get_template(self.config['template_file'])\\n\\n logging.info('Rendering template')\\n out = template.render(**self.config)\\n with open(self.config['name'] + self.get_file_extension(), 'w') as file:\\n file.write(out)\\n\\n if not self.args.pandoc:\\n logging.info('Rendering latex')\\n self.write()\\n if not self.args.fast:\\n logging.info('Rendering latex, again')\\n self.write() # twice for the toc\\n\\n logging.info('Done!')\",\n \"def update_views():\\n # replace Supervisor main entry\\n here = os.path.abspath(os.path.dirname(__file__))\\n # set main page\\n VIEWS['index.html'] = {'template': os.path.join(here, 'ui/index.html'),\\n 'view': SupvisorsView}\\n # set address /processpage\\n VIEWS['procaddress.html'] = {'template': os.path.join(\\n here, 'ui/procaddress.html'),\\n 'view': ProcAddressView}\\n # set address/host page\\n VIEWS['hostaddress.html'] = {'template': os.path.join(\\n here, 'ui/hostaddress.html'),\\n 'view': HostAddressView}\\n # set application page\\n VIEWS['application.html'] = {'template': os.path.join(\\n here, 'ui/application.html'),\\n 'view': ApplicationView}\\n # set fake page to export images\\n VIEWS['process_cpu.png'] = {'template': os.path.join(\\n here, 'ui/empty.html'),\\n 'view': ProcessCpuImageView}\\n VIEWS['process_mem.png'] = {'template': os.path.join(\\n here, 'ui/empty.html'),\\n 'view': ProcessMemoryImageView}\\n VIEWS['address_cpu.png'] = {'template': os.path.join(\\n here, 'ui/empty.html'),\\n 'view': AddressCpuImageView}\\n VIEWS['address_mem.png'] = {'template': os.path.join(\\n here, 'ui/empty.html'),\\n 'view': AddressMemoryImageView}\\n VIEWS['address_io.png'] = {'template': os.path.join(\\n here, 'ui/empty.html'),\\n 'view': AddressNetworkImageView}\",\n \"def get_templates(self):\\n\\n\\t\\tif not os.path.isdir('./repo'): os.mkdir('./repo')\\n\\t\\ttemps = self.settings['template']\\n\\t\\t#---ensure that the template object is always in a list\\n\\t\\tif len(temps) == 2 and type(temps[0])==str and type(temps[1])==str: temps = [temps]\\n\\t\\tself.template = []\\n\\t\\tfor t in temps:\\n\\t\\t\\tprint 'retrieving '+str(t[0])\\n\\t\\t\\t#---check if in repo and move\\n\\t\\t\\tif not os.path.isfile(self.rootdir+t[0]+'.pdb') and os.path.isfile('./repo/'+t[0]+'.pdb'):\\n\\t\\t\\t\\tcopy('./repo/'+t[0]+'.pdb',self.rootdir+t[0]+'.pdb')\\n\\t\\t\\t\\t#---fasta retrieval is deprecated\\n\\t\\t\\t\\tif 0: copy('./repo/'+t[0]+'.fasta',self.rootdir+t[0]+'.fasta')\\n\\t\\t\\telif not os.path.isfile(self.rootdir+t[0]+'.pdb'):\\n\\t\\t\\t\\tresponse = urllib2.urlopen('http://www.rcsb.org/pdb/files/'+t[0]+'.pdb')\\n\\t\\t\\t\\tpdbfile = response.read()\\n\\t\\t\\t\\twith open(self.rootdir+t[0]+'.pdb','w') as fp: fp.write(pdbfile)\\n\\t\\t\\t\\tcopy(self.rootdir+t[0]+'.pdb','./repo/'+t[0]+'.pdb')\\n\\t\\t\\tself.template.append(t)\",\n \"def prepare(self, **template_parameters: Any) -> None:\\n\\n self._body_plain = render_template(self._body_template_base_path + '.txt', **template_parameters)\\n self._body_html = render_template(self._body_template_base_path + '.html', **template_parameters)\",\n \"def controls_setup(self):\\n\\n self.drain_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Drain Types Submodule\\\",\\n css_selector='tr.CodeDrainType')\\n self.depot_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Depot Types Submodule\\\",\\n css_selector='tr.CodeJobType')\\n self.file_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"File Types Submodule\\\",\\n css_selector='tr.CodeFileType')\\n self.job_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Job Types Submodule\\\",\\n css_selector='tr.CodeJobType')\\n self.paving_colours = container.AdminDashboardSubmodule(\\n self, alias=\\\"Paving Colours Submodule\\\",\\n css_selector='tr.CodePavingColour')\\n self.paving_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Paving Types Submodule\\\",\\n css_selector='tr.CodePavingType')\\n self.repair_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Repair Types Submodule\\\",\\n css_selector='tr.CodeRepairType')\\n self.subbie_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Subbie Types Submodule\\\",\\n css_selector='tr.CodeSubbieType')\\n self.task_types = container.AdminDashboardSubmodule(\\n self, alias=\\\"Task Types Submodule\\\",\\n css_selector='tr.CodeTaskType')\",\n \"def createBasicRenderSetup():\\n\\n pass\",\n \"def setUpClass(cls):\\n print \\\"Setting Up Class: %s\\\" % cls.__name__\\n\\n # Setting class attributes for use across all test methods\\n cls.config_file = ('supporting_files/templates/'\\n 'glusto_templates-vars.yml')\\n config = g.load_config(cls.config_file)\\n g.show_config(config)\\n if config:\\n g.update_config(config)\\n\\n cls.template_vars = g.config['templates']\\n cls.template_file = ('templates/'\\n 'glusto_templates-template.jinja')\\n cls.search_path = 'supporting_files'\\n cls.output_file = '/tmp/glusto_templates-output.yml'\",\n \"def __init__(self, template_env):\\r\\n self._template_env = template_env\\r\\n self._pythons = []\",\n \"def generate_webpages(self):\\n if self.add_to_existing:\\n self.add_existing_data()\\n self.make_home_pages()\\n self.make_1d_histogram_pages()\\n self.make_corner_pages()\\n self.make_config_pages()\\n if self.make_comparison:\\n self.make_comparison_pages()\\n if self.make_interactive:\\n self.make_interactive_pages()\\n if self.publication:\\n self.make_publication_pages()\\n if self.gwdata is not None:\\n self.make_detector_pages()\\n self.make_error_page()\\n self.make_version_page()\\n if self.notes is not None:\\n self.make_notes_page()\\n self.make_downloads_page()\\n self.generate_specific_javascript()\",\n \"def test_create_namespaced_template(self):\\n pass\",\n \"def load_template_files(self):\\n templates = dict()\\n template_path = settings.CUSTOM_VERTO_TEMPLATES\\n templates.update(self.read_template_files(template_path))\\n if hasattr(self, \\\"extra_converter_templates_directory\\\"):\\n directory = self.extra_converter_templates_directory\\n template_path = os.path.join(template_path, directory)\\n templates.update(self.read_template_files(template_path))\\n return templates\",\n \"def update_views():\\n # replace Supervisor main entry\\n here = path.abspath(path.dirname(__file__))\\n # set main page\\n VIEWS['index.html'] = {'template': path.join(here, 'ui/index.html'), 'view': SupvisorsView}\\n # set address /processpage\\n VIEWS['procaddress.html'] = {'template': path.join(here, 'ui/procaddress.html'), 'view': ProcAddressView}\\n # set address/host page\\n VIEWS['hostaddress.html'] = {'template': path.join(here, 'ui/hostaddress.html'), 'view': HostAddressView}\\n # set application page\\n VIEWS['application.html'] = {'template': path.join(here, 'ui/application.html'), 'view': ApplicationView}\\n # set fake page to export images\\n VIEWS['process_cpu.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': ProcessCpuImageView}\\n VIEWS['process_mem.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': ProcessMemoryImageView}\\n VIEWS['address_cpu.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressCpuImageView}\\n VIEWS['address_mem.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressMemoryImageView}\\n VIEWS['address_io.png'] = {'template': path.join(here, 'ui/empty.html'), 'view': AddressNetworkImageView}\",\n \"def init(depot):\\n global tlookup\\n pkg.server.feed.init(depot)\\n tlookup = mako.lookup.TemplateLookup(directories=[depot.web_root])\",\n \"def test_custom_templates_and_themes(self):\\n new_templates_dir = os.path.join(self.temp_usable_dir, 'templates')\\n manage_tmpl_file = os.path.join(new_templates_dir, 'manage/custom.py_tmpl')\\n repository_tmpl_file = os.path.join(new_templates_dir, 'repository/custom/README')\\n script_tmpl_file = os.path.join(new_templates_dir, 'script/custom.py_tmpl')\\n sql_script_tmpl_file = os.path.join(new_templates_dir, 'sql_script/custom.py_tmpl')\\n\\n MANAGE_CONTENTS = 'print \\\"manage.py\\\"'\\n README_CONTENTS = 'MIGRATE README!'\\n SCRIPT_FILE_CONTENTS = 'print \\\"script.py\\\"'\\n new_repo_dest = self.tmp_repos()\\n new_manage_dest = self.tmp_py()\\n\\n # make new templates dir\\n shutil.copytree(migrate.versioning.templates.__path__[0], new_templates_dir)\\n shutil.copytree(os.path.join(new_templates_dir, 'repository/default'),\\n os.path.join(new_templates_dir, 'repository/custom'))\\n\\n # edit templates\\n f = open(manage_tmpl_file, 'w').write(MANAGE_CONTENTS)\\n f = open(repository_tmpl_file, 'w').write(README_CONTENTS)\\n f = open(script_tmpl_file, 'w').write(SCRIPT_FILE_CONTENTS)\\n f = open(sql_script_tmpl_file, 'w').write(SCRIPT_FILE_CONTENTS)\\n\\n # create repository, manage file and python script\\n kw = {}\\n kw['templates_path'] = new_templates_dir\\n kw['templates_theme'] = 'custom'\\n api.create(new_repo_dest, 'repo_name', **kw)\\n api.script('test', new_repo_dest, **kw)\\n api.script_sql('postgres', 'foo', new_repo_dest, **kw)\\n api.manage(new_manage_dest, **kw)\\n\\n # assert changes\\n self.assertEqual(open(new_manage_dest).read(), MANAGE_CONTENTS)\\n self.assertEqual(open(os.path.join(new_repo_dest, 'manage.py')).read(), MANAGE_CONTENTS)\\n self.assertEqual(open(os.path.join(new_repo_dest, 'README')).read(), README_CONTENTS)\\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/001_test.py')).read(), SCRIPT_FILE_CONTENTS)\\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/002_foo_postgres_downgrade.sql')).read(), SCRIPT_FILE_CONTENTS)\\n self.assertEqual(open(os.path.join(new_repo_dest, 'versions/002_foo_postgres_upgrade.sql')).read(), SCRIPT_FILE_CONTENTS)\",\n \"def test_render_all_templates():\\n assert templates.xhook__initialize({})\\n assert templates.xhook__handlers({})\\n assert templates.xhook__enable()\\n assert templates.xhook__release()\\n assert templates.asserts__call_count({})\\n assert templates.asserts__calls({})\",\n \"def main():\\n return render_template(\\\"main.html\\\")\",\n \"def main():\\n return render_template(\\\"main.html\\\")\",\n \"def __init__(self, out_dir):\\n self.env = Environment(loader=PackageLoader(\\\"emu\\\", \\\"templates\\\"))\\n self.dest = out_dir\",\n \"def __init__(self, config):\\n\\n with open(config) as file:\\n self.config = yaml.load(file, Loader=yaml.FullLoader)\\n\\n self.contents = []\\n\\n self.templateLoader = jinja2.FileSystemLoader(searchpath=\\\"./\\\")\\n self.templateEnv = jinja2.Environment(loader=self.templateLoader)\",\n \"def setup( self ):\",\n \"def create_base_templates(outdir, templateEnv):\\n for file in ME_TEMPLATES:\\n filename = os.path.join(outdir, ME_FILENAME.format(file))\\n template = templateEnv.get_template(file + '.go.jinja')\\n\\n with open(filename, 'w') as f:\\n output = template.render(copyright=COPYRIGHT,\\n generator_warning=GENERATOR_WARNING,\\n package_name=PACKAGE_NAME)\\n f.write(output)\\n pass\",\n \"def update_config(self, config):\\n toolkit.add_template_directory(config, 'templates')\\n toolkit.add_resource('fanstatic', 'mingus')\\n return\",\n \"def controls_setup(self):\\n\\n self.client_name = element.Link(self, css_selector='th:nth-child(1) > a', alias=\\\"Admin Client Name Link\\\")\\n self.xero_customer = element.Caption(self, css_selector='td:nth-child(2)', alias=\\\"Xero Customer\\\")\\n self.send_invoices = element.Image(self, css_selector='td:nth-child(3) img', alias=\\\"Send Invoices Check Mark\\\")\\n self.part_a_required = element.Image(self, css_selector='td:nth-child(4) img',\\n alias=\\\"Part A Required Check Mark\\\")\\n self.they_supply_pump = element.Image(self, css_selector='td:nth-child(5) img',\\n alias=\\\"They Supply Pump Check Mark\\\")\\n self.active_start_date = element.Link(self, css_selector='td:nth-child(6)', alias=\\\"Active Start Date Text\\\")\\n self.active_end_date = element.Link(self, css_selector='td:nth-child(6)', alias=\\\"Active End Date Text\\\")\",\n \"def configure(self):\\n inject(self.urls, self.names_for(\\\"urls\\\"))\\n inject(self.models, self.names_for(\\\"models\\\"))\\n self.load_admin()\",\n \"def _load_template(self):\\n filename = os.path.join(get_conf('DEFAULT_TEMPLATE_PATH'), self._template, '__init__.ini')\\n cf = ApplicationConf.get_instance()\\n with comp_open(filename, mode='r') as fp:\\n content = fp.read()\\n content = content.format(**cf)\\n conf = CompConfigParser(allow_no_value=True)\\n conf.read_string(content, '__init__.ini')\\n ini = {'dirs': [], 'files': [], 'binaries': []}\\n if conf.has_section('dirs'):\\n for key in conf.options('dirs'):\\n ini['dirs'].append(key)\\n if conf.has_section('files'):\\n for key in conf.options('files'):\\n ini['files'].append(self.__remap(key))\\n if conf.has_section('binaries'):\\n for key in conf.options('binaries'):\\n ini['binaries'].append(self.__remap(key))\\n if isinstance(self._ini, dict):\\n self._ini.update(ini)\\n else:\\n self._ini = ini\",\n \"def index():\\n return render_template('home.jinja2')\",\n \"def controls_setup(self):\\n\\n self.subbie_name = element.Link(self, css_selector='th:nth-child(1) > a', alias=\\\"Admin Subbie Name Link\\\")\\n self.type = element.Caption(self, css_selector='td:nth-child(2)', alias=\\\"Subbie Type\\\")\\n self.username = element.Caption(self, css_selector='td:nth-child(3)', alias=\\\"Username\\\")\\n self.email = element.Caption(self, css_selector='td:nth-child(4)', alias=\\\"Email\\\")\\n self.active_start_date = element.Link(self, css_selector='td:nth-child(5)', alias=\\\"Active Start Date Text\\\")\\n self.active_end_date = element.Link(self, css_selector='td:nth-child(6)', alias=\\\"Active End Date Text\\\")\",\n \"def controls_setup(self):\\n\\n self.supervisor_name = element.Link(self, css_selector='th:nth-child(1) > a',\\n alias=\\\"Admin Supervisor Name Link\\\")\\n self.username = element.Caption(self, css_selector='td:nth-child(2)', alias=\\\"Username\\\")\\n self.email = element.Caption(self, css_selector='td:nth-child(3)', alias=\\\"Email\\\")\\n self.active_start_date = element.Link(self, css_selector='td:nth-child(4)', alias=\\\"Active Start Date Text\\\")\\n self.active_end_date = element.Link(self, css_selector='td:nth-child(5)', alias=\\\"Active End Date Text\\\")\",\n \"def _ProcessTemplate(self,topdir):\\n self.dicomdir = \\\"%s/anatomicals\\\" % self.topdir\\n self.rawdir = \\\"%s/raw\\\" % topdir\\n self.rawdirs = {}\\n tmplt = self._GetTemplate()\\n if self.opts.outdir is not None:\\n# Override template output directory.\\n tmplt['top_outdir'] = self.opts.outdir\\n self.tmplt = tmplt\\n if len(tmplt['top_outdir']) == 0:\\n tmplt['top_outdir'] = os.path.realpath(self.topdir)\\n raise RuntimeError('Template file must specify an output directory.')\\n tmplt['top_outdir'] = os.path.realpath(tmplt['top_outdir'])\\n if '/home' in tmplt['top_outdir'][:7]:\\n raise RuntimeError('Image data cannot be stored in the /home partition. Change the \\\"top_outdir\\\" entry in the template file: %s.' % (' '.join(self.templates)))\\n# tmplt['subject'] = 'orig'\\n self.procdir = os.path.abspath(\\\"%s/%s\\\" % \\\\\\n (tmplt['top_outdir'],tmplt['subject']))\\n target = os.path.abspath('%s/../..' % tmplt['top_outdir'])\\n if not ismounted(target):\\n raise RuntimeError('Could not access partition at %s' % target)\\n\\n self.anatdir = \\\"%s/anat\\\" % self.procdir\\n self.fmapdir = \\\"%s/%s\\\" % (self.procdir,tmplt['fmap']['outdir'])\\n self.dtidir = \\\"%s/%s\\\" % (self.procdir,tmplt['dti']['outdir'])\\n self.logdir = \\\"%s/%s\\\" % (self.procdir,tmplt['logdir'])\\n self.skip = tmplt.get('skip', DEFAULT_SKIP)\\n self.acq_tr = tmplt.get('acq_tr',None)\\n self.episetup_dir = \\\"%s/%s\\\" % (self.procdir,tmplt['first_epi'])\\n self.fsl_cmpblty = tmplt.get('fsl_compatibility',False)\\n self.epi_file_format = self.tmplt['epi_file_format']\\n self.censor_thresh = tmplt.get('censor_threshold', 2.)\\n self.censor_interleave = tmplt.get('censor_interleave', True)\\n# self.server_userid = self.tmplt.get('server_userid','default')\\n\\n# Overide flags for aligning EPIs and skull-stripping with command-\\n# line options.\\n if self.opts.align_fmaps:\\n self.align_fmaps = True\\n else:\\n self.align_fmaps = self.tmplt.get('epi_align', False)\\n\\n if self.opts.no_align_fmaps:\\n self.no_align_fmaps = True\\n else:\\n self.no_align_fmaps = self.tmplt.get('no_epi_align', False)\\n\\n if self.opts.skull_strip:\\n self.skull_strip = True\\n else:\\n self.skull_strip = self.tmplt.get('skull_strip', False)\\n\\n# Create log file now so it can be used immediately.\\n if not os.path.exists(self.logdir):\\n if self.verbose:\\n print 'mkdir %s' % self.logdir\\n if not self.opts.fake_opts:\\n self.MakeDir(self.logdir)\\n\\n self._ProcessTemplateEpiInfo()\",\n \"def build(self):\\n self.logger.debug(\\\"run\\\")\\n\\n self.onInit()\\n self.work()\\n \\n self.afterWork()\\n\\n template = Templateengine(self.currenttemplate)\\n template.readTemplateFile()\\n contenttype = self.settings.contenttype \\n self.defaultTemplateParameter()\\n \\n try:\\n self.content = template.get(self.tplparam)\\n except Exception as ex:\\n Emergency.stop(ex)\\n\\n self.onDone()\\n \\n self.logger.debug(\\\"done\\\")\",\n \"def main(\\n files: List[Path] = typer.Argument(default=None, dir_okay=False, exists=True),\\n template: Optional[str] = typer.Option(\\n None, '--template', help='Name of template file'\\n ),\\n logo: Optional[str] = typer.Option(None, '--logo', help='Name of logo file'),\\n logo_width: Optional[str] = typer.Option(\\n None, '--logo-width', help='Logo width (default 35mm)'\\n ),\\n highlight_style: Optional[str] = typer.Option(None, '--highlight-style',\\n help='Specify coloring style to be used in highlighting source code'),\\n syntax_definition: Optional[str] = typer.Option(None, '--syntax-definition',\\n help='Specify a directory which contains syntax definition files'),\\n no_toc: bool = typer.Option(\\n False, '--no-toc', help='table of contents in PDF document'\\n ),\\n no_number_sections: bool = typer.Option(False, '--no-number-sections', help='no section numbering'),\\n\\n no_titlepage: bool = typer.Option(False, '--no-titlepage', help='title in PDF document'),\\n tex_file: bool = typer.Option(\\n False, '--tex', help='create TeX file instead of PDF document'\\n ),\\n email: Optional[str] = typer.Option(None, '--email', help='Author email'),\\n company: Optional[str] = typer.Option(None, '--company', help='Name of company'),\\n department: Optional[str] = typer.Option(\\n None, '--department', help='Name of department'\\n ),\\n confidential: bool = typer.Option(\\n False, '--confidential', help='indicate confidential'\\n ),\\n debug: bool = typer.Option(False, '--debug', help='turns debugging on'),\\n pdf_engine: str = typer.Option(\\n 'xelatex',\\n '--pdf-engine',\\n help='Specify pdf engine, one of lualatex, xelatex or tectonic ',\\n ),\\n _version: bool = typer.Option(\\n None, '-V', '--version', callback=version_callback, help='Show version and exit'\\n ),\\n):\\n\\n if not files:\\n typer.echo('Error: Must specify at least one .md file.')\\n raise typer.Abort()\\n\\n mdfiles: List[str] = [str(md) for md in files]\\n\\n template = template or os.environ.get('MD2PDF_TEMPLATE')\\n if template is None:\\n print('No template specified')\\n sys.exit(1)\\n\\n email = email or os.environ.get('MD2PDF_AUTHOR_EMAIL')\\n footer_center = ''\\n\\n # command line overwrites `MD2PDF_PDF_ENGINE`. if both are not given\\n # then `xelatex` is the default\\n pdf_engine = pdf_engine or os.environ.get('MD2PDF_PDF_ENGINE') or 'xelatex'\\n # check that pdf-engine is one of the following\\n if pdf_engine not in ['xelatex', 'lualatex', 'tectonic']:\\n print('--pdf-engine must be one of \\\"xelatex\\\", \\\"lualatex\\\", \\\"tectonic\\\"')\\n sys.exit(1)\\n\\n ext = '.pdf'\\n if tex_file:\\n ext = '.tex'\\n\\n if len(mdfiles) == 1:\\n toml_file = os.path.splitext(mdfiles[0])[0] + '.toml'\\n\\n if os.path.exists(toml_file):\\n print(f'TOML file {toml_file} found')\\n parsed_toml = toml.load(toml_file)\\n default_val = parsed_toml.get('default')\\n if default_val is None:\\n print(f'No file names found in {toml_file}')\\n else:\\n mdfiles = default_val.get('files')\\n\\n for mdf in mdfiles:\\n print(f'Compiling {mdf}')\\n\\n main_mdfile = os.path.realpath(mdfiles[0])\\n\\n outfile = Path(main_mdfile).stem + ext\\n\\n year = date.today().year\\n\\n company = company or os.environ.get('MD2PDF_COMPANY')\\n department = department or os.environ.get('MD2PDF_DEPARTMENT')\\n\\n if company:\\n if confidential:\\n footer_center = f'© Copyright {year} {company}'\\n else:\\n footer_center = f'{year} {company}'\\n\\n pdcmd = PandocCmd(outfile)\\n pdcmd.append(f'--template={template}')\\n pdcmd.append(f'--pdf-engine={pdf_engine}')\\n\\n pdcmd.set_v('footer-center', footer_center)\\n pdcmd.set_v('company', company)\\n pdcmd.set_v('department', department)\\n\\n syntax_definition = syntax_definition or os.environ.get('MD2PDF_SYNTAX_DEFINITION_DIR')\\n if syntax_definition is not None:\\n add_syntax_definition(pdcmd, syntax_definition)\\n\\n pdcmd.append('--highlight-style')\\n highlight_style = highlight_style or os.environ.get('MD2PDF_HIGHLIGHT_STYLE')\\n if highlight_style is None:\\n pdcmd.append('pygments')\\n else:\\n check_highlight_style(highlight_style)\\n pdcmd.append(highlight_style)\\n\\n if not no_number_sections:\\n pdcmd.append('--number-sections')\\n\\n if no_titlepage:\\n pdcmd.set_m('titlepage', 'false')\\n\\n logo = logo or os.environ.get('MD2PDF_LOGO')\\n pdcmd.set_v('logo', logo)\\n\\n logo_width = logo_width or os.environ.get('MD2PDF_LOGO_WIDTH')\\n pdcmd.set_v('logo-width', logo_width)\\n\\n pdcmd.set_m('email', email)\\n\\n if not no_toc:\\n pdcmd.append('--toc')\\n\\n pdcmd.extend(mdfiles)\\n\\n if debug:\\n print(' '.join(pdcmd.pandoc))\\n\\n\\n pdcmd.run()\",\n \"def call(self, **kwargs):\\n # Get additional resources links\\n css = []\\n for path in (\\\"creative/vendor/bootstrap/css/bootstrap.min.css\\\",\\n \\\"creative/vendor/font-awesome/css/font-awesome.min.css\\\",\\n \\\"creative/vendor/magnific-popup/magnific-popup.css\\\",\\n \\\"creative/css/creative.css\\\"):\\n css.append(self._cw.data_url(path))\\n js = []\\n for path in (\\\"creative/vendor/jquery/jquery.min.js\\\",\\n \\\"creative/vendor/bootstrap/js/bootstrap.min.js\\\",\\n \\\"creative/vendor/scrollreveal/scrollreveal.min.js\\\",\\n \\\"creative/vendor/magnific-popup/jquery.magnific-popup.min.js\\\",\\n \\\"creative/js/creative.js\\\"):\\n js.append(self._cw.data_url(path))\\n\\n # Format template\\n template = self._cw.vreg.template_env.get_template(\\\"startup.jinja2\\\")\\n html = template.render(\\n header_url=self._cw.data_url(\\\"creative/img/neurospin.jpg\\\"),\\n login_url=self._cw.build_url(\\n \\\"login\\\", __message=u\\\"Please login with your account.\\\"),\\n contact_email=self._cw.vreg.config.get(\\n \\\"administrator-emails\\\", \\\"noreply@cea.fr\\\"),\\n css_url=css,\\n js_url=js)\\n self.w(html)\",\n \"def test_home_route_uses_right_templates(self):\\n response = self.client.get(\\\"/\\\")\\n self.assertTemplateUsed(response, \\\"layout.html\\\")\",\n \"def _GetTemplate(self):\\n# First read default template.\\n tmplt = self._LoadTemplate(c.preproc_template_default)\\n tmplt['proc'] = self.topdir\\n self.template_type = 'default'\\n\\n self.templates = []\\n if self.template_file is not None:\\n tmplt.update(self._LoadTemplate(self.template_file))\\n self.template_type = 'command-line'\\n self.templates.append(os.path.abspath(self.template_file))\\n found_template = True\\n else:\\n# Find a study specific template file.\\n study_template_file = self._FindTemplateFile('%s/..' % self.topdir)\\n if study_template_file is not None:\\n# Merge study template into default, study template has precedence.\\n if self.verbose:\\n print \\\"Using study template at \\\" + study_template_file\\n tmplt.update(self._LoadTemplate(study_template_file))\\n self.template_type = 'study-specific'\\n self.templates.append(os.path.abspath(study_template_file))\\n found_template = True\\n else:\\n found_template = False\\n# Now look for a subject-specific template file.\\n subject_template_file = self._FindTemplateFile('%s' % self.topdir)\\n if subject_template_file is not None:\\n# Merge subject template, subject template has precedence.\\n if self.verbose:\\n print \\\"Using subject-specific template at %s\\\" % \\\\\\n subject_template_file\\n tmplt.update(self._LoadTemplate(subject_template_file))\\n self.template_type = 'study-specific'\\n self.templates.append(os.path.abspath(subject_template_file))\\n found_template = True\\n\\n if not found_template:\\n raise RuntimeError('Could not find template file.')\\n\\n if tmplt.get('subject','same') == 'same':\\n# Default subdirectory is same as data directory.\\n tmplt['subject'] = self.topdir.split('/')[-1]\\n else:\\n if not isinstance(tmplt['subject'],str):\\n errstr = 'preprocess: Invalid subject number. Be sure to ' + \\\\\\n 'enclose the subject number item with double quotes.'\\n raise RuntimeError(errstr)\\n\\n# Keys that apply to all EPIs.\\n self.fsl_flip = tmplt.get('fsl_flip', False)\\n if self.fsl_flip:\\n self.flip_opts = '-LT'\\n else:\\n self.flip_opts = ''\\n\\n# Replace strings with python types.\\n for key in tmplt.keys():\\n if tmplt[key] == 'None':\\n tmplt[key] = None\\n elif key == 'True':\\n tmplt[key] = True\\n elif key == 'False':\\n tmplt[key] = False\\n return tmplt\",\n \"def preRunSetup(self):\\n self.logDesc(\\\"Pre Run Setup\\\")\\n #Check for current logged in user\\n self.verifyCurrentUser(userRole='Administrator', loginAsUser=True)\\n #Creates Sample Template if not exists\\n self.createSampleTemplate(templateName=self.templateName)\",\n \"def run(self):\\n self.render_templates()\\n self.create_docker_context()\\n self.build()\\n self.push()\",\n \"def test_correct_main_page_template(self):\\n response = self.client.get('/')\\n self.assertTemplateUsed(response, 'main.html')\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.80348116","0.7463657","0.7155762","0.7095249","0.6724418","0.6702859","0.6654424","0.6569718","0.6396812","0.63617265","0.63503236","0.63492066","0.63473433","0.632623","0.62927055","0.6273522","0.6273522","0.62619275","0.62587327","0.6243744","0.6218501","0.6202332","0.6196521","0.6168485","0.6168339","0.6071091","0.603533","0.6022544","0.60208964","0.5990569","0.59714913","0.5967179","0.596602","0.5952222","0.5948345","0.593558","0.5931946","0.59181243","0.5909545","0.59077156","0.5877181","0.587549","0.5867689","0.5849688","0.5822026","0.5810522","0.5806678","0.5800403","0.5790018","0.5787726","0.5783559","0.5774605","0.5759916","0.57517356","0.5747542","0.5743731","0.57405776","0.5726111","0.57183117","0.57183087","0.5717635","0.57117033","0.56840116","0.5673152","0.56668437","0.5663709","0.566319","0.566319","0.566179","0.56424814","0.56390667","0.56365484","0.5630227","0.5627188","0.56245506","0.5624311","0.5613757","0.56069565","0.5606687","0.5605846","0.56020355","0.55973685","0.55958587","0.55956286","0.5593314","0.5586029","0.5582688","0.55821866","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606","0.55783606"],"string":"[\n \"0.80348116\",\n \"0.7463657\",\n \"0.7155762\",\n \"0.7095249\",\n \"0.6724418\",\n \"0.6702859\",\n \"0.6654424\",\n \"0.6569718\",\n \"0.6396812\",\n \"0.63617265\",\n \"0.63503236\",\n \"0.63492066\",\n \"0.63473433\",\n \"0.632623\",\n \"0.62927055\",\n \"0.6273522\",\n \"0.6273522\",\n \"0.62619275\",\n \"0.62587327\",\n \"0.6243744\",\n \"0.6218501\",\n \"0.6202332\",\n \"0.6196521\",\n \"0.6168485\",\n \"0.6168339\",\n \"0.6071091\",\n \"0.603533\",\n \"0.6022544\",\n \"0.60208964\",\n \"0.5990569\",\n \"0.59714913\",\n \"0.5967179\",\n \"0.596602\",\n \"0.5952222\",\n \"0.5948345\",\n \"0.593558\",\n \"0.5931946\",\n \"0.59181243\",\n \"0.5909545\",\n \"0.59077156\",\n \"0.5877181\",\n \"0.587549\",\n \"0.5867689\",\n \"0.5849688\",\n \"0.5822026\",\n \"0.5810522\",\n \"0.5806678\",\n \"0.5800403\",\n \"0.5790018\",\n \"0.5787726\",\n \"0.5783559\",\n \"0.5774605\",\n \"0.5759916\",\n \"0.57517356\",\n \"0.5747542\",\n \"0.5743731\",\n \"0.57405776\",\n \"0.5726111\",\n \"0.57183117\",\n \"0.57183087\",\n \"0.5717635\",\n \"0.57117033\",\n \"0.56840116\",\n \"0.5673152\",\n \"0.56668437\",\n \"0.5663709\",\n \"0.566319\",\n \"0.566319\",\n \"0.566179\",\n \"0.56424814\",\n \"0.56390667\",\n \"0.56365484\",\n \"0.5630227\",\n \"0.5627188\",\n \"0.56245506\",\n \"0.5624311\",\n \"0.5613757\",\n \"0.56069565\",\n \"0.5606687\",\n \"0.5605846\",\n \"0.56020355\",\n \"0.55973685\",\n \"0.55958587\",\n \"0.55956286\",\n \"0.5593314\",\n \"0.5586029\",\n \"0.5582688\",\n \"0.55821866\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\",\n \"0.55783606\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5902942"},"document_rank":{"kind":"string","value":"40"}}},{"rowIdx":25682,"cells":{"query":{"kind":"string","value":"Mixin method. Not implemented in the base class."},"document":{"kind":"string","value":"def html(self, children, ordering):\n\n raise NotImplementedError"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __call__(self):\r\n raise NotImplementedError('override me')","def __call__(self):\n raise NotImplementedError","def __call__(self):\n raise NotImplementedError()","def __call__( self ):\n pass","def __call__(self, *args, **kwargs):\r\n raise NotImplementedError","def __call__(self, *args, **kwargs):\r\n raise NotImplementedError","def __call__(self, *args, **kwargs):\r\n raise NotImplementedError","def __call__(self):\n pass","def __call__(self):\n pass","def __call__(self, *args, **kwargs):\n raise NotImplementedError","def __call__(self, *args, **kwargs):\n raise NotImplementedError","def __call__(self, **kwargs):\n raise NotImplementedError","def __call__(self) -> None:","def override(self):\n return None","def __call__(self):\n\t\treturn","def extension (self):\n assert False, \"To be implemented by child\"","def base(self):\n raise NotImplementedError()","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # real signature unknown\n pass","def __subclasshook__(self, *args, **kwargs): # 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This should be called by the parent class's html method."},"document":{"kind":"string","value":"def _html(self, children, wide=False, additional=\"\", ordering='normal'):\n\n def sorter(r):\n\n \"\"\" provides a number to sort related in ascending length of description\"\"\"\n\n ans = len(r.description)\n if additional:\n for rr in r.monkey_additional:\n ans += len(rr)\n return ans\n\n # do we need the placeholder in the template for additional material?\n if additional == \"\":\n self.template = self.template.replace('XXX', \"\")\n self.wide_template = self.wide_template.replace('XX1', \"\")\n self.wide_template = self.wide_template.replace('XX2', \"\")\n\n if wide:\n\n if additional:\n a1 = additional.replace('r.monkey', 'r[0].monkey')\n a2 = additional.replace('r.monkey', 'r[1].monkey')\n self.wide_template = self.wide_template.replace('XX1',a1)\n self.wide_template = self.wide_template.replace('XX2',a2)\n\n # sort for similar lengths\n if ordering == 'normal':\n ordered = sorted(self.related, key=sorter)\n self.related = list(reversed(ordered))\n elif ordering == 'special':\n ordered = sorted(self.related[1:], key=sorter)\n self.related = [self.related[0], ordered[0]] + list(reversed(ordered[1:]))\n else:\n raise ValueError('html rendering with unexpected value of ordering %s' % ordering)\n pairs = zip(self.related[0::2], self.related[1::2])\n if len(pairs)*2 != len(self.related):\n pairs.append([self.related[-1], None])\n template = Template(self.wide_template)\n html = template.render(d=self.doc, related=pairs, mips=self.mips, children=children)\n else:\n if additional:\n self.template = self.template.replace('XXX',additional)\n template = Template(self.template)\n html = template.render(d=self.doc, related=self.related, mips=self.mips, children=children)\n return html"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def render(self):\r\n super().render()","def render(self):\n raise NotImplementedError","def render(self):\n raise NotImplementedError()","def __html__(self):\n return self.html","def render(self):\n pass","def render(self):\n pass","def render(self):\n pass","def render(self):\n pass","def render(self):\n pass","def render(self):\n pass","def render(self):\n raise RenderNotImplemented('Render function is not implemented.')","def _render(self) -> None:\n pass","def render_html(self):\n return self.template.render(content=self.content, **self.styles)","def _repr_html_(self) -> str:\n output_html = self.template_base.render(context=self.context)\n return output_html","def render(self, *args, **kwargs):\r\n raise NotImplementedError","def render(self):\n raise NotImplementedError(\"Renderer is an abstract class\")","def _repr_html_(self):\n return self.__repr__()","def _repr_html_(self):\n return self.__repr__()","def rawHTMLrendered(self):","def render(self):\n return self","def render(self):\n\n self.desert_image.render()\n self.cannon_image.render()\n self.play_button.render()\n self.escape_label.render()","def render(self):","def _render(self) -> str:\n html = self._template.render(self._transient_context)\n self._transient_context = None\n return html","def render(self, r):\n raise NotImplementedError","def _repr_html_(self):\n\n return self._repr__base(rich_output=True)","def _repr_html_(self):\n\n return self._repr__base(rich_output=True)","def __html__(self):\n return str(self)","def render(self):\n try:\n if self.permit():\n return self.renderer.render(self)\n except AttributeError:\n if self.renderer is None:\n raise NotImplementedError(\"Should have implemented a renderer for {0}\".format(self.name))\n else:\n raise\n return ''","def render(self) -> str:\n\n return \"\\n\".join(self.render_iter())","def render(self, value, context=None):\n if self.raw_html is not None:\n return format_html(self.raw_html)\n else:\n return ''","def render(self):\n self.rendered = self.value\n return self.rendered","def _repr_html_(self):\n return self.data.to_html()","def html(self, children, ordering):\n\n raise NotImplementedError","def html(self) -> SafeString:\n return format_html(self.__html__())","def html(self) -> SafeString:\n return format_html(self.__html__())","def render(self, mode='human'):\n pass # no use in this situation","def render(self, **kwargs) -> str:\n return self.renderable(**kwargs).render()","def display(self):\n\n # This will automatically choose the best representation among repr and repr_html\n\n display(self)","def display(self):\n\n # This will automatically choose the best representation among repr and repr_html\n\n display(self)","def render(self):\n if self.can_render():\n output = '<ul>'\n for item in self.items:\n output += \"<li>{0}</li>\".format(item)\n return output + '</ul>'\n return ''","def render(self, **kw):\r\n style = kw.get('style', c.render_style or 'html')\r\n return Wrapped.part_render(self, self.style, style = style, **kw)","def render(self):\n if not self.renderer:\n raise NoRendererError('Field %s has no renderer assigned.' %\n self.id)\n return self.renderer.render(self)","def render(self, mode='human'):\n\n pass","def _repr_html_(self):\n import jinja2 # noqa\n\n call_result = self._get_call_result()\n\n id_result = str(id(self) + np.random.random()).replace(\".\", \"rr\")\n\n params = {\n \"result\": self,\n \"id_result\": id_result,\n \"call_result\": call_result,\n \"json_result\": json.dumps(self.json_, indent=2),\n }\n return jinja2.Template(RESULT_HTML_TEMPLATE).render(**params)","def render(self):\n self._render_text = self.content.replace('\\n', '<br>') # deal with new line\n return render_str(\"post.html\", p = self)","def get_html(self):\r\n pass","def render(self):\n return render_to_string(\n self.template_name, self.get_context_data(), request=self.request\n )","def render(self, rstate):\n pass","def to_html(self):\n return self.serializer.render(self.formatter.formatMessage(self.oldmsg))","def render(self, mode='human'):","def render(self, *html, **opt):\n context = self.context\n # add request, response to context implicitly.\n context['request'] = self.request\n context['response'] = self.response\n if 'context' in opt:\n context.update(opt['context'])\n opt['context'] = context.dicts[0]\n cnt = self.get_controller()\n cnt.render(*html, **opt)","def dspyRender(self):\n pass","def as_html(self):\r\n template = get_template(self.template)\r\n request = build_request()\r\n return template.render(RequestContext(request, {'table': self}))","def render(self, session: Session) -> str:\n raise NotImplementedError()","def render(self):\n\n context = {\n 'model': self,\n 'hidden_fields': self.hidden_fields,\n 'css_prefix': self.css_prefix,\n }\n rendered = loader.render_to_string(self.template_path,\n dictionary=context)\n return rendered","def render(self, mode='human', close=False):\n raise NotImplementedError()","def render(self, name, value, attrs=None):\n raise NotImplementedError('subclasses of Widget must provide a render() method')","def to_html(self, content, request, **parameters):\n raise NotImplementedError","def render(self, renderer, right=False):\n pass # pragma: no cover","def __html__(self) -> str:\n components = [\n self.attributee_html,\n self.linked_title if self.title else 'untitled document',\n self.date.string if self.date else '',\n self.descriptive_phrase,\n f'archived in {self.collection}' if self.collection else '',\n ]\n return self.components_to_html(components)","def render_html(self, renderer, response_msg=''):\r\n # render ourself as a <span> + our content\r\n tree = etree.Element('span')\r\n\r\n # problem author can make this span display:inline\r\n if self.xml.get('inline', ''):\r\n tree.set('class', 'inline')\r\n\r\n for item in self.xml:\r\n # call provided procedure to do the rendering\r\n item_xhtml = renderer(item)\r\n if item_xhtml is not None:\r\n tree.append(item_xhtml)\r\n tree.tail = self.xml.tail\r\n\r\n # Add a <div> for the message at the end of the response\r\n if response_msg:\r\n tree.append(self._render_response_msg_html(response_msg))\r\n\r\n return tree","def html(self) -> str:\n return self._html","def render(self) -> str:\n with no_colors():\n self._render()\n return self.sio.getvalue()","def as_html(self): # pragma: no cover\n\n return render_to_string(\n self._meta.template,\n { \"table\": self } )","def render(self, mode='human', close=False):\n pass","def get_html(self):\r\n return self.system.render_template('lti.html', self.get_context())","def getHtml(self):\n return self.html","def to_html(self, data, options=None):\n from django.template.loader import render_to_string as render\n\n options = options or {}\n\n serialized = self.to_simple_html(data, options)\n return render(\"api/base.html\", {\"data\": serialized})","def render(self):\n\n self._render_text = self.content.replace('\\n', '<br>')\n return render_str('post_template.html', post=self, user=self.user)","def html(self):\n return self._html","def render(self):\n self._render_text = self.content.replace('\\n', '<br>')\n return TemplateFile.jinja_render_str(\"post.html\", p=self)","def unrendered(self) -> str:","def _repr_html_(self):\n return util.tree_html(self)","def html(self, **kwargs):\n # get bas context_data\n context_data = self.get_context_data(**kwargs)\n # setup the context object for it\n context = loader.Context(context_data)\n # render the template_source_body with current set of context\n body = loader.render_to_string(self.template_source_body, context)\n # add the rendered body to the underlying wrapper template\n context_data = self.get_context_data(body=body)\n # rerender it\n context = loader.Context(context_data)\n return self.template.render(context)","def _repr_html_(self):\n return self._frame._repr_html_()","def to_html(self, data=None, **kwargs) -> str:\n html = self.create_container()\n return html","def __repr__(self):\n #if self.parent: self.print_siblings()\n self.env.render()\n #self._print_children()\n return ''","def _repr_html_(self):\n return util.tree_sequence_html(self)","def __html__(self) -> str:\n components = [\n self.attributee_html,\n f'\"{self.linked_title}\"',\n self.date.string if self.date else '',\n ]\n return self.components_to_html(components)","def get_inner_html(self):\n\n pass","def get_html(self):\r\n context = self.get_context()\r\n html = self.system.render_template(\r\n '{0}/combined_open_ended.html'.format(self.TEMPLATE_DIR), context\r\n )\r\n return html","def __str__(self):\n t = Template(\n \"\"\"\n <h4>$title</h4>\n $imgs\n $footnotes\n <hr/>\"\"\")\n # Return result.\n return t.substitute({\n \"title\": self.title,\n \"imgs\": self.render_images(),\n \"footnotes\": self.render_footnotes()\n })","def render(self):\n self.increase_view_count()\n return render_to_string(self.template.template_file, {'advert':self})","def render(self, mode='human', close=False):\n pass","def render(self, axes=None):\n raise NotImplementedError()","def _repr_html_(self): # pragma: no cover\n return Utils.render_html('extent.html', extent=self)","def render(self, data, *args, **kwargs):\n pass # pragma: nocover","def _repr_html_(self):\n return \"<td><b>{0}</b></td><td>{1}</td>\".format(self.id, self.title)","def render(self, mode='human', close=False):\n return None","def __html__(self):\n if not self.hasArticle:\n return None\n\n if self.bbcode_is_active:\n return self._bbcodeAsHtml\n\n return self.html","def get_html(self):\r\n if self.debug == 'True':\r\n # Reset the user vote, for debugging only!\r\n self.user_voted = False\r\n if self.hints == {}:\r\n # Force self.hints to be written into the database. (When an xmodule is initialized,\r\n # fields are not added to the db until explicitly changed at least once.)\r\n self.hints = {}\r\n\r\n try:\r\n child = self.get_display_items()[0]\r\n out = child.render('student_view').content\r\n # The event listener uses the ajax url to find the child.\r\n child_id = child.id\r\n except IndexError:\r\n out = u\"Error in loading crowdsourced hinter - can't find child problem.\"\r\n child_id = ''\r\n\r\n # Wrap the module in a <section>. This lets us pass data attributes to the javascript.\r\n out += u'<section class=\"crowdsource-wrapper\" data-url=\"{ajax_url}\" data-child-id=\"{child_id}\"> </section>'.format(\r\n ajax_url=self.runtime.ajax_url,\r\n child_id=child_id\r\n )\r\n\r\n return out","def render(self):\n start_tag = format_html('<div {}>', mark_safe(' '.join(self.field_attrs)))\n output = [start_tag]\n for widget in self:\n output.append(force_text(widget))\n output.append('</div>')\n return mark_safe('\\n'.join(output))","def render(self):\n raise Exception(\"Abstract method\")","def render(self):\n self.env.render()","def render(self):\n breadcrumb_template = template.loader.get_template(self.template)\n extra_context = {\"breadcrumb\": self}\n return breadcrumb_template.render(extra_context, self.request)","def get_html(self):\r\n if self.template is None:\r\n raise NotImplementedError(\"no rendering template specified for class {0}\"\r\n .format(self.__class__))\r\n\r\n context = self._get_render_context()\r\n\r\n html = self.capa_system.render_template(self.template, context)\r\n\r\n try:\r\n output = etree.XML(html)\r\n except etree.XMLSyntaxError as ex:\r\n # If `html` contains attrs with no values, like `controls` in <audio controls src='smth'/>,\r\n # XML parser will raise exception, so wee fallback to html5parser, which will set empty \"\" values for such attrs.\r\n try:\r\n output = html5lib.parseFragment(html, treebuilder='lxml', namespaceHTMLElements=False)[0]\r\n except IndexError:\r\n raise ex\r\n\r\n return output","def show(self):\n import IPython.display\n disp = IPython.display.HTML(self.render())\n return IPython.display.display(disp, display_id=str(id(self)))","def show(self):\n\t\tself.html += '<head>\\n' + self.head + '</head>\\n<body>\\n' + self.body + '</body>\\n</html>'\n\n\t\treturn self.html","def html(self) -> str:\n if self._inner_element:\n return self.start_tag + self._inner_element.html + self.end_tag\n return super().html","def mj_render(self):\n self.render(mode='human')","def get_html(self):\n\n # these 3 will be used in class methods\n self.html_id = self.location.html_id()\n self.html_class = self.location.category\n self.configuration_json = self.build_configuration_json()\n params = {\n 'gst_html': self.substitute_controls(self.render),\n 'element_id': self.html_id,\n 'element_class': self.html_class,\n 'configuration_json': self.configuration_json\n }\n content = self.system.render_template(\n 'graphical_slider_tool.html', params)\n return content"],"string":"[\n \"def render(self):\\r\\n super().render()\",\n \"def render(self):\\n raise NotImplementedError\",\n \"def render(self):\\n raise NotImplementedError()\",\n \"def __html__(self):\\n return self.html\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n raise RenderNotImplemented('Render function is not implemented.')\",\n \"def _render(self) -> None:\\n pass\",\n \"def render_html(self):\\n return self.template.render(content=self.content, **self.styles)\",\n \"def _repr_html_(self) -> str:\\n output_html = self.template_base.render(context=self.context)\\n return output_html\",\n \"def render(self, *args, **kwargs):\\r\\n raise NotImplementedError\",\n \"def render(self):\\n raise NotImplementedError(\\\"Renderer is an abstract class\\\")\",\n \"def _repr_html_(self):\\n return self.__repr__()\",\n \"def _repr_html_(self):\\n return self.__repr__()\",\n \"def rawHTMLrendered(self):\",\n \"def render(self):\\n return self\",\n \"def render(self):\\n\\n self.desert_image.render()\\n self.cannon_image.render()\\n self.play_button.render()\\n self.escape_label.render()\",\n \"def render(self):\",\n \"def _render(self) -> str:\\n html = self._template.render(self._transient_context)\\n self._transient_context = None\\n return html\",\n \"def render(self, r):\\n raise NotImplementedError\",\n \"def _repr_html_(self):\\n\\n return self._repr__base(rich_output=True)\",\n \"def _repr_html_(self):\\n\\n return self._repr__base(rich_output=True)\",\n \"def __html__(self):\\n return str(self)\",\n \"def render(self):\\n try:\\n if self.permit():\\n return self.renderer.render(self)\\n except AttributeError:\\n if self.renderer is None:\\n raise NotImplementedError(\\\"Should have implemented a renderer for {0}\\\".format(self.name))\\n else:\\n raise\\n return ''\",\n \"def render(self) -> str:\\n\\n return \\\"\\\\n\\\".join(self.render_iter())\",\n \"def render(self, value, context=None):\\n if self.raw_html is not None:\\n return format_html(self.raw_html)\\n else:\\n return ''\",\n \"def render(self):\\n self.rendered = self.value\\n return self.rendered\",\n \"def _repr_html_(self):\\n return self.data.to_html()\",\n \"def html(self, children, ordering):\\n\\n raise NotImplementedError\",\n \"def html(self) -> SafeString:\\n return format_html(self.__html__())\",\n \"def html(self) -> SafeString:\\n return format_html(self.__html__())\",\n \"def render(self, mode='human'):\\n pass # no use in this situation\",\n \"def render(self, **kwargs) -> str:\\n return self.renderable(**kwargs).render()\",\n \"def display(self):\\n\\n # This will automatically choose the best representation among repr and repr_html\\n\\n display(self)\",\n \"def display(self):\\n\\n # This will automatically choose the best representation among repr and repr_html\\n\\n display(self)\",\n \"def render(self):\\n if self.can_render():\\n output = '<ul>'\\n for item in self.items:\\n output += \\\"<li>{0}</li>\\\".format(item)\\n return output + '</ul>'\\n return ''\",\n \"def render(self, **kw):\\r\\n style = kw.get('style', c.render_style or 'html')\\r\\n return Wrapped.part_render(self, self.style, style = style, **kw)\",\n \"def render(self):\\n if not self.renderer:\\n raise NoRendererError('Field %s has no renderer assigned.' %\\n self.id)\\n return self.renderer.render(self)\",\n \"def render(self, mode='human'):\\n\\n pass\",\n \"def _repr_html_(self):\\n import jinja2 # noqa\\n\\n call_result = self._get_call_result()\\n\\n id_result = str(id(self) + np.random.random()).replace(\\\".\\\", \\\"rr\\\")\\n\\n params = {\\n \\\"result\\\": self,\\n \\\"id_result\\\": id_result,\\n \\\"call_result\\\": call_result,\\n \\\"json_result\\\": json.dumps(self.json_, indent=2),\\n }\\n return jinja2.Template(RESULT_HTML_TEMPLATE).render(**params)\",\n \"def render(self):\\n self._render_text = self.content.replace('\\\\n', '<br>') # deal with new line\\n return render_str(\\\"post.html\\\", p = self)\",\n \"def get_html(self):\\r\\n pass\",\n \"def render(self):\\n return render_to_string(\\n self.template_name, self.get_context_data(), request=self.request\\n )\",\n \"def render(self, rstate):\\n pass\",\n \"def to_html(self):\\n return self.serializer.render(self.formatter.formatMessage(self.oldmsg))\",\n \"def render(self, mode='human'):\",\n \"def render(self, *html, **opt):\\n context = self.context\\n # add request, response to context implicitly.\\n context['request'] = self.request\\n context['response'] = self.response\\n if 'context' in opt:\\n context.update(opt['context'])\\n opt['context'] = context.dicts[0]\\n cnt = self.get_controller()\\n cnt.render(*html, **opt)\",\n \"def dspyRender(self):\\n pass\",\n \"def as_html(self):\\r\\n template = get_template(self.template)\\r\\n request = build_request()\\r\\n return template.render(RequestContext(request, {'table': self}))\",\n \"def render(self, session: Session) -> str:\\n raise NotImplementedError()\",\n \"def render(self):\\n\\n context = {\\n 'model': self,\\n 'hidden_fields': self.hidden_fields,\\n 'css_prefix': self.css_prefix,\\n }\\n rendered = loader.render_to_string(self.template_path,\\n dictionary=context)\\n return rendered\",\n \"def render(self, mode='human', close=False):\\n raise NotImplementedError()\",\n \"def render(self, name, value, attrs=None):\\n raise NotImplementedError('subclasses of Widget must provide a render() method')\",\n \"def to_html(self, content, request, **parameters):\\n raise NotImplementedError\",\n \"def render(self, renderer, right=False):\\n pass # pragma: no cover\",\n \"def __html__(self) -> str:\\n components = [\\n self.attributee_html,\\n self.linked_title if self.title else 'untitled document',\\n self.date.string if self.date else '',\\n self.descriptive_phrase,\\n f'archived in {self.collection}' if self.collection else '',\\n ]\\n return self.components_to_html(components)\",\n \"def render_html(self, renderer, response_msg=''):\\r\\n # render ourself as a <span> + our content\\r\\n tree = etree.Element('span')\\r\\n\\r\\n # problem author can make this span display:inline\\r\\n if self.xml.get('inline', ''):\\r\\n tree.set('class', 'inline')\\r\\n\\r\\n for item in self.xml:\\r\\n # call provided procedure to do the rendering\\r\\n item_xhtml = renderer(item)\\r\\n if item_xhtml is not None:\\r\\n tree.append(item_xhtml)\\r\\n tree.tail = self.xml.tail\\r\\n\\r\\n # Add a <div> for the message at the end of the response\\r\\n if response_msg:\\r\\n tree.append(self._render_response_msg_html(response_msg))\\r\\n\\r\\n return tree\",\n \"def html(self) -> str:\\n return self._html\",\n \"def render(self) -> str:\\n with no_colors():\\n self._render()\\n return self.sio.getvalue()\",\n \"def as_html(self): # pragma: no cover\\n\\n return render_to_string(\\n self._meta.template,\\n { \\\"table\\\": self } )\",\n \"def render(self, mode='human', close=False):\\n pass\",\n \"def get_html(self):\\r\\n return self.system.render_template('lti.html', self.get_context())\",\n \"def getHtml(self):\\n return self.html\",\n \"def to_html(self, data, options=None):\\n from django.template.loader import render_to_string as render\\n\\n options = options or {}\\n\\n serialized = self.to_simple_html(data, options)\\n return render(\\\"api/base.html\\\", {\\\"data\\\": serialized})\",\n \"def render(self):\\n\\n self._render_text = self.content.replace('\\\\n', '<br>')\\n return render_str('post_template.html', post=self, user=self.user)\",\n \"def html(self):\\n return self._html\",\n \"def render(self):\\n self._render_text = self.content.replace('\\\\n', '<br>')\\n return TemplateFile.jinja_render_str(\\\"post.html\\\", p=self)\",\n \"def unrendered(self) -> str:\",\n \"def _repr_html_(self):\\n return util.tree_html(self)\",\n \"def html(self, **kwargs):\\n # get bas context_data\\n context_data = self.get_context_data(**kwargs)\\n # setup the context object for it\\n context = loader.Context(context_data)\\n # render the template_source_body with current set of context\\n body = loader.render_to_string(self.template_source_body, context)\\n # add the rendered body to the underlying wrapper template\\n context_data = self.get_context_data(body=body)\\n # rerender it\\n context = loader.Context(context_data)\\n return self.template.render(context)\",\n \"def _repr_html_(self):\\n return self._frame._repr_html_()\",\n \"def to_html(self, data=None, **kwargs) -> str:\\n html = self.create_container()\\n return html\",\n \"def __repr__(self):\\n #if self.parent: self.print_siblings()\\n self.env.render()\\n #self._print_children()\\n return ''\",\n \"def _repr_html_(self):\\n return util.tree_sequence_html(self)\",\n \"def __html__(self) -> str:\\n components = [\\n self.attributee_html,\\n f'\\\"{self.linked_title}\\\"',\\n self.date.string if self.date else '',\\n ]\\n return self.components_to_html(components)\",\n \"def get_inner_html(self):\\n\\n pass\",\n \"def get_html(self):\\r\\n context = self.get_context()\\r\\n html = self.system.render_template(\\r\\n '{0}/combined_open_ended.html'.format(self.TEMPLATE_DIR), context\\r\\n )\\r\\n return html\",\n \"def __str__(self):\\n t = Template(\\n \\\"\\\"\\\"\\n <h4>$title</h4>\\n $imgs\\n $footnotes\\n <hr/>\\\"\\\"\\\")\\n # Return result.\\n return t.substitute({\\n \\\"title\\\": self.title,\\n \\\"imgs\\\": self.render_images(),\\n \\\"footnotes\\\": self.render_footnotes()\\n })\",\n \"def render(self):\\n self.increase_view_count()\\n return render_to_string(self.template.template_file, {'advert':self})\",\n \"def render(self, mode='human', close=False):\\n pass\",\n \"def render(self, axes=None):\\n raise NotImplementedError()\",\n \"def _repr_html_(self): # pragma: no cover\\n return Utils.render_html('extent.html', extent=self)\",\n \"def render(self, data, *args, **kwargs):\\n pass # pragma: nocover\",\n \"def _repr_html_(self):\\n return \\\"<td><b>{0}</b></td><td>{1}</td>\\\".format(self.id, self.title)\",\n \"def render(self, mode='human', close=False):\\n return None\",\n \"def __html__(self):\\n if not self.hasArticle:\\n return None\\n\\n if self.bbcode_is_active:\\n return self._bbcodeAsHtml\\n\\n return self.html\",\n \"def get_html(self):\\r\\n if self.debug == 'True':\\r\\n # Reset the user vote, for debugging only!\\r\\n self.user_voted = False\\r\\n if self.hints == {}:\\r\\n # Force self.hints to be written into the database. (When an xmodule is initialized,\\r\\n # fields are not added to the db until explicitly changed at least once.)\\r\\n self.hints = {}\\r\\n\\r\\n try:\\r\\n child = self.get_display_items()[0]\\r\\n out = child.render('student_view').content\\r\\n # The event listener uses the ajax url to find the child.\\r\\n child_id = child.id\\r\\n except IndexError:\\r\\n out = u\\\"Error in loading crowdsourced hinter - can't find child problem.\\\"\\r\\n child_id = ''\\r\\n\\r\\n # Wrap the module in a <section>. This lets us pass data attributes to the javascript.\\r\\n out += u'<section class=\\\"crowdsource-wrapper\\\" data-url=\\\"{ajax_url}\\\" data-child-id=\\\"{child_id}\\\"> </section>'.format(\\r\\n ajax_url=self.runtime.ajax_url,\\r\\n child_id=child_id\\r\\n )\\r\\n\\r\\n return out\",\n \"def render(self):\\n start_tag = format_html('<div {}>', mark_safe(' '.join(self.field_attrs)))\\n output = [start_tag]\\n for widget in self:\\n output.append(force_text(widget))\\n output.append('</div>')\\n return mark_safe('\\\\n'.join(output))\",\n \"def render(self):\\n raise Exception(\\\"Abstract method\\\")\",\n \"def render(self):\\n self.env.render()\",\n \"def render(self):\\n breadcrumb_template = template.loader.get_template(self.template)\\n extra_context = {\\\"breadcrumb\\\": self}\\n return breadcrumb_template.render(extra_context, self.request)\",\n \"def get_html(self):\\r\\n if self.template is None:\\r\\n raise NotImplementedError(\\\"no rendering template specified for class {0}\\\"\\r\\n .format(self.__class__))\\r\\n\\r\\n context = self._get_render_context()\\r\\n\\r\\n html = self.capa_system.render_template(self.template, context)\\r\\n\\r\\n try:\\r\\n output = etree.XML(html)\\r\\n except etree.XMLSyntaxError as ex:\\r\\n # If `html` contains attrs with no values, like `controls` in <audio controls src='smth'/>,\\r\\n # XML parser will raise exception, so wee fallback to html5parser, which will set empty \\\"\\\" values for such attrs.\\r\\n try:\\r\\n output = html5lib.parseFragment(html, treebuilder='lxml', namespaceHTMLElements=False)[0]\\r\\n except IndexError:\\r\\n raise ex\\r\\n\\r\\n return output\",\n \"def show(self):\\n import IPython.display\\n disp = IPython.display.HTML(self.render())\\n return IPython.display.display(disp, display_id=str(id(self)))\",\n \"def show(self):\\n\\t\\tself.html += '<head>\\\\n' + self.head + '</head>\\\\n<body>\\\\n' + self.body + '</body>\\\\n</html>'\\n\\n\\t\\treturn self.html\",\n \"def html(self) -> str:\\n if self._inner_element:\\n return self.start_tag + self._inner_element.html + self.end_tag\\n return super().html\",\n \"def mj_render(self):\\n self.render(mode='human')\",\n \"def get_html(self):\\n\\n # these 3 will be used in class methods\\n self.html_id = self.location.html_id()\\n self.html_class = self.location.category\\n self.configuration_json = self.build_configuration_json()\\n params = {\\n 'gst_html': self.substitute_controls(self.render),\\n 'element_id': self.html_id,\\n 'element_class': self.html_class,\\n 'configuration_json': self.configuration_json\\n }\\n content = self.system.render_template(\\n 'graphical_slider_tool.html', params)\\n return content\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.82992643","0.8107857","0.8076577","0.7906086","0.7878678","0.7878678","0.7878678","0.7878678","0.7878678","0.7878678","0.7871989","0.78110904","0.7726244","0.7694776","0.75172067","0.74649364","0.74395216","0.74395216","0.7385232","0.7338748","0.7338651","0.73338884","0.73315156","0.73112226","0.7299228","0.7299228","0.72697383","0.72684574","0.72134566","0.7199389","0.7181673","0.71490335","0.7059614","0.7053169","0.7053169","0.7053037","0.70390904","0.7009914","0.7009914","0.70052445","0.69989157","0.6973102","0.6951848","0.6940331","0.69383645","0.69188803","0.69110185","0.6878916","0.68678415","0.68528074","0.6842427","0.68083596","0.6795709","0.6768904","0.67597353","0.6757202","0.6741476","0.673424","0.6728001","0.670945","0.6693033","0.6690369","0.6656597","0.6652717","0.6648658","0.66437477","0.6641857","0.6639597","0.6623192","0.66228855","0.66040164","0.66023916","0.65919447","0.6563439","0.6560442","0.65542364","0.655405","0.6540761","0.6533031","0.6524813","0.6519679","0.6477135","0.6475631","0.64656407","0.6459226","0.6443188","0.6417036","0.641621","0.6407814","0.6405536","0.6404242","0.63876015","0.63846844","0.6382989","0.6379146","0.6376657","0.6372984","0.6371144","0.63633513","0.6361376","0.6354144"],"string":"[\n \"0.82992643\",\n \"0.8107857\",\n \"0.8076577\",\n \"0.7906086\",\n \"0.7878678\",\n \"0.7878678\",\n \"0.7878678\",\n \"0.7878678\",\n \"0.7878678\",\n \"0.7878678\",\n \"0.7871989\",\n \"0.78110904\",\n \"0.7726244\",\n \"0.7694776\",\n \"0.75172067\",\n \"0.74649364\",\n \"0.74395216\",\n \"0.74395216\",\n \"0.7385232\",\n \"0.7338748\",\n \"0.7338651\",\n \"0.73338884\",\n \"0.73315156\",\n \"0.73112226\",\n \"0.7299228\",\n \"0.7299228\",\n \"0.72697383\",\n \"0.72684574\",\n \"0.72134566\",\n \"0.7199389\",\n \"0.7181673\",\n \"0.71490335\",\n \"0.7059614\",\n \"0.7053169\",\n \"0.7053169\",\n \"0.7053037\",\n \"0.70390904\",\n \"0.7009914\",\n \"0.7009914\",\n \"0.70052445\",\n \"0.69989157\",\n \"0.6973102\",\n \"0.6951848\",\n \"0.6940331\",\n \"0.69383645\",\n \"0.69188803\",\n \"0.69110185\",\n \"0.6878916\",\n \"0.68678415\",\n \"0.68528074\",\n \"0.6842427\",\n \"0.68083596\",\n \"0.6795709\",\n \"0.6768904\",\n \"0.67597353\",\n \"0.6757202\",\n \"0.6741476\",\n \"0.673424\",\n \"0.6728001\",\n \"0.670945\",\n \"0.6693033\",\n \"0.6690369\",\n \"0.6656597\",\n \"0.6652717\",\n \"0.6648658\",\n \"0.66437477\",\n \"0.6641857\",\n \"0.6639597\",\n \"0.6623192\",\n \"0.66228855\",\n \"0.66040164\",\n \"0.66023916\",\n \"0.65919447\",\n \"0.6563439\",\n \"0.6560442\",\n \"0.65542364\",\n \"0.655405\",\n \"0.6540761\",\n \"0.6533031\",\n \"0.6524813\",\n \"0.6519679\",\n \"0.6477135\",\n \"0.6475631\",\n \"0.64656407\",\n \"0.6459226\",\n \"0.6443188\",\n \"0.6417036\",\n \"0.641621\",\n \"0.6407814\",\n \"0.6405536\",\n \"0.6404242\",\n \"0.63876015\",\n \"0.63846844\",\n \"0.6382989\",\n \"0.6379146\",\n \"0.6376657\",\n \"0.6372984\",\n \"0.6371144\",\n \"0.63633513\",\n \"0.6361376\",\n \"0.6354144\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":25684,"cells":{"query":{"kind":"string","value":"provides a number to sort related in ascending length of description"},"document":{"kind":"string","value":"def sorter(r):\n\n ans = len(r.description)\n if additional:\n for rr in r.monkey_additional:\n ans += len(rr)\n return ans"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def sort():\n return -1","def Order(self) -> int:","def _natural_sort_worksheet(x):\n l = re.findall(r\"\\d+$\", x.title)\n if l:\n return int(l[0])\n\n return -1","def _wiki_sort_key(doc):\n url = doc['url']\n return 1 if url.startswith('https://en.wikipedia') else -1","def bigSorting(unsorted):\n lookup = defaultdict(lambda: [])\n print(lookup)\n for num_string in unsorted:\n lookup[len(num_string)].append(num_string)\n\n results = []\n lengths = list(lookup.keys())\n lengths.sort()\n for length in lengths:\n x = lookup[length]\n x.sort()\n results = results + x\n print(results)\n return results","def sort_key(self):\n ...","def sort(self,desc):\n\tself.__sort(\"\",\"\",desc)","def sortkey(item):\n chrom, pos, ref, alt = item[0]\n if chrom.startswith('chr'):\n chrom = chrom[3:]\n if chrom.isdigit():\n chrom = int(chrom)\n return (chrom, pos, len(ref), len(alt))","def _status_sort(self):\n s = 0\n if self.status == 'failed':\n s += 10\n if self.image_status == 'diff':\n s += 3\n elif self.image_status == 'missing':\n s += 4\n if self.hash_status == 'diff':\n s += 1\n elif self.hash_status == 'missing':\n s += 5\n return f\"{s:02.0f}\"","def order(self):\n return self.n","def sortby(self):\n ...","def get_sort_field(self, kind, order, is_number):\n pass","def sortValue(self, data):\n storedText = data.get(self.name, '')\n try:\n return GenNumber(storedText).num\n except GenNumberError:\n return ''","def compare(self) -> int:","def sortValue(self, data):\n storedText = data.get(self.name, '')\n try:\n return int(UniqueIDFormat.formatRe.match(storedText).group(2))\n except AttributeError:\n return 0","def sort_format(src):\n src_list= src.split('-')\n res_list= []\n for elm in src_list:\n try:\n res_list.append('%05d' % int(elm))\n except:\n res_list.append(elm)\n res= '-'.join(res_list)\n return res","def get_longest_digit_count_desc(lst):\n rezultat = []\n for i in lst:\n if is_desc(i):\n rezultat.append(i)\n return rezultat","def sort_and_digitize(line):\n return int(''.join(sorted(str(line))))","def _trans_string(self, n):\r\n return \"%s %d\" % (self.desc, n+1)","def local_h( author, data ) :\n papers = papers_and_cites( author, data )\n papers.sort( lambda a,b : cmp(int(b[1]), int(a[1])) )\n i = 0\n while i < (len(papers)-1) and i < int(papers[i][1] ) :\n i = i + 1\n\n return (i+1, int(papers[i][1]) )","def get_sort_query(self, kind, order, is_number):\n pass","def get_word_len(self, length):\n\n sortedList = self.sortedList\n\n step = rd.randint(0, length) * round(time.time())\n print(step)\n\n n = rd.randint(0, len(sortedList) - 1)\n print(n)\n while len(sortedList[n]) != length:\n if len(sortedList[n]) > length:\n n += step\n else:\n n -= step\n if n < 0 or n > len(sortedList):\n n = rd.randint(0, len(sortedList) - 1)\n\n return sortedList[n]","def sort_1(l):\n pass","def humanSort(l): \n convert = lambda text: int(text) if text.isdigit() else text \n alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ] \n l.sort( key=alphanum_key )","def test_calc_sort_without_after_object(self):\n test_object = self.test.datum_type2\n actual = test_object._calc_sort_value(sort_base_length=3,\n increment=1,\n sort_prefix_parts=[test_object.datum_group.sort]\n )\n expected = 10101\n self.assertEqual(expected, actual)","def get_row_list_sorting_key(x):\n name, count = x\n if '_' not in name:\n return name\n s = name.split('_')\n end = s[-1]\n start = '_'.join(s[:-1])\n if utils.is_int(end):\n return (start, int(end))\n return name","def _get_field_sort_key(self, field):\n if not field.is_relation:\n return -1\n return 0 if field.many_to_many else 1","def countingSort(my_list, target):\r\n count = [0 for i in range(26)]\r\n position = [0 for i in range(26)]\r\n output = [0 for i in range(len(my_list))]\r\n if len(my_list) > 1:\r\n for i in range(len(my_list)):\r\n count[ord(my_list[i][0][target]) - 97] += 1\r\n position[0] = 0\r\n for i in range(1, len(position)):\r\n position[i] = position[i - 1] + count[i - 1]\r\n for i in range(len(my_list)):\r\n key = my_list[i][0]\r\n pos=0\r\n index = ord(my_list[i][0][target]) - 97\r\n if count[index] != 0:\r\n pos = position[index]\r\n position[index] += 1\r\n output[pos] = my_list[i]\r\n\r\n return output","def cmp_numcite( a, b ) :\n return cmp( int(b['Z9']), int(a['Z9']) )","def test_sorting(sort=selection_sort, num_items=20, max_value=50):\n # TODO: Repeat until all items are in sorted order\n # TODO: Take first unsorted item\n # TODO: Insert it in sorted order in front of items","def reversesort(self):\n ...","def get_row_list_sorting_key(x):\n name, count = x\n if '_' not in name:\n return name\n s = name.split('_')\n end = s[-1]\n start = '_'.join(s[:-1])\n if is_int(end):\n return (start, int(end))\n return name","def test_calc_sort_multiple_parts(self):\n test_object = self.test.datum_object1\n sort_parts = [test_object.datum_group.sort,\n test_object.datum_type.sort\n ]\n actual = self.test.datum_object1._calc_sort_value(sort_base_length=2,\n increment=1,\n sort_prefix_parts=sort_parts\n )\n expected = 101010010\n self.assertEqual(expected, actual)","def sort(n, integer=False):\n x = ''.join(sorted(str(n)))\n if integer:\n return(int(x))\n else:\n return(x)","def sort_order(self) -> int:\n return self._sort_order","def sort_order(self) -> int:\n return self._sort_order","def __cmp__(self, other):\n if self.length < other.length:\n return -1\n if self.length == other.length:\n return 0\n if self.length > other.length:\n return 1","def test_order(type_name):\n return len(type_name)","def test_calc_sort_prefix_reset(self):\n test_object = self.test.datum_type3\n sort_parts = [test_object.datum_group.sort,\n ]\n actual = test_object._calc_sort_value(sort_base_length=4,\n increment=1,\n sort_prefix_parts=sort_parts\n )\n expected = 201000\n self.assertEqual(expected, actual)","def _natural_sort_key(value):\n return map(try_int_cast, re.findall(r'(\\d+|\\D+)', value))","def test_calc_sort_with_after_object(self):\n test_object = self.test.datum_type2\n actual = test_object._calc_sort_value(after_object=self.test.datum_type1,\n sort_base_length=3,\n increment=1,\n sort_prefix_parts=[test_object.datum_group.sort]\n )\n expected = 10101\n self.assertEqual(expected, actual)","def sortby_num(tree, col, descending): # 重新排序 <-- 數字版\n # grab values to sort\n data = [(tree.set(child, col), child) \\\n for child in tree.get_children('')]\n\n # if the data to be sorted is numeric change to float\n #data = change_numeric(data)\n # now sort the data in place\n #data.sort(reverse=descending)\n # 數字的排法(但文字部分就無法排序)\n data.sort(key=lambda data: int(data[0]), reverse=descending)\n\n for ix, item in enumerate(data):\n tree.move(item[1], '', ix)\n\n # switch the heading so it will sort in the opposite direction\n tree.heading(col, command=lambda col=col: sortby_num(tree, col, \\\n int(not descending)))","def sort_duration(self):\n self.sort('duration')","def __len__(self):\r\n return len(self.__sorted_names)","def numerize():\n pass","def to_ordinal(self):\n return mod(self.number - 1 + 39 * (self.number - self.name), 260)","def norders(self):\n return 21","def dmc_order(self):\n return sorted(self.lookup_table, key=lambda clr: int(clr.id) if clr.id.isdigit() else 0)","def sorted(self): \n pass","def order(name: str):\n if name.startswith('pred'):\n split = name.split('_')\n if len(str(split[-2])) > 10: # New file format, -2 is hash\n return int(split[-3])\n return int(split[-2])\n split = name.split('_')\n x = split[-1].split('.')[0]\n return int(x)","def next_item_sort_order(self):\n from nano.models import InvoiceItem\n total = InvoiceItem.query.filter_by(invoice_id=self.id).count()\n return total+1","def sort_output_desc_asc(word_counts):\n\n # sort by item (-item[1] refers to reverse list of second item)\n sorted_items = sorted(word_counts.items(), key=lambda item: (-item[1], item[0]))\n \n for key, value in sorted_items:\n print \"{} {}\".format(value, key)","def human_sort(l):\n l.sort(key=alphanum_key)\n return l","def test_version_sorting(self):\n assert natsort(['1', '5', '10', '50']) == ['1', '5', '10', '50']","def nat_sort_key(val):\n split_val = _grouped_digits_re.split(str(val))\n for i in xrange(1, len(split_val), 2):\n split_val[i] = int(split_val[i])\n start = 1 if split_val[0] == '' else 0\n end = -1 if split_val[-1] == '' else None\n split_val = split_val[start:end]\n # _dbg(\"nat_sort_key: %r -> %r\", val, split_val)\n return split_val","def order(knl):\n return int(re.match(r\"k(\\d+)l\", knl).group(1))","def sort_numerical(paths):\n paths.sort(key=alphanum_key)\n return paths","def sort_0(l):\n l.sort()","def _run_pair_sorter(run_pair):\n run, other_run = run_pair\n\n return (len(run) + len(other_run), len(other_run))","def order_ideal(self, gens):","def _get_display_orders(self):\n if self.fake_orders < 1000:\n return self.fake_orders\n else:\n num500 = self.fake_orders / 500\n return \"%d+\" % (num500 * 500)","def fullcountSort(arr):\n sorted = [[] for i in range(100)]\n for i in range(int(len(arr) / 2)):\n sorted[int(arr[i][0])].append('-')\n for i in range(int(len(arr) / 2), len(arr)):\n sorted[int(arr[i][0])].append(arr[i][1])\n\n output = ''\n for item in sorted:\n if item == []:\n pass\n else:\n output = output + ' '.join(item) + ' '\n print(output)","def sortLength(self):\n return FeatureSet(sorted(self, key = lambda f: f.length()))","def min_lengths(cls, description):\n\n min_indexes = [s - 1 for s in partial_sums(description, colored=False)]\n return min_indexes","def sort_res(res_tim):\r\n i=0\r\n length=0\r\n for each in res_tim:\r\n mat=re.search(r'(\\d\\d:\\d\\d:\\d\\d)',each)\r\n if mat and i!=10:\r\n if i==0:\r\n hr=mat.group(1)\r\n i+=1\r\n elif i==10:\r\n break\r\n elif not mat.group(1)==hr:\r\n i+=1\r\n hr=mat.group(1)\r\n length+=1\r\n else:\r\n break\r\n return length,hr","def sortByIndex(self,_index,desc):\n\treturn self.sortByPostText(\"[%s]\"%_index,desc)","def index_sortable_title_IEntry(object, **kw):\n if object.__parent__.sorting == 'surname':\n # Assume title is a name, pull last word (surname) off and put it at\n # the start\n m = re.search('(.*) (.*)', object.title)\n if m:\n return \" \".join(m.groups()[::-1])\n # Sort by title\n return object.title","def main(str_text):\n\n frequencies = count_value(str_text)\n sorted_data = sort_dict(frequencies)\n\n return sorted_data","def human_sort( l ):\n convert = lambda text: int(text) if text.isdigit() else text\n alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ]\n alphanum_key = None\n try:\n l.sort( key=alphanum_key )\n except TypeError:\n l.sort()\n return l","def test_sort_fewer_than_n(self):\n e1 = Experience(rid=1, uid=3, experience=100)\n e2 = Experience(rid=1, uid=1, experience=89)\n e3 = Experience(rid=1, uid=12, experience=1343)\n db.session.add(e1)\n db.session.add(e2)\n db.session.add(e3)\n db.session.commit()\n list = top_n_in_order(1,5)\n self.assertEqual([(12, 1343), (3, 100), (1, 89)], list)","def _get_display_orders(self):\n query_set = SeriesEpisode.objects.filter(series=self.id)\n first_episode = query_set[0] if len(query_set) > 0 else None\n if first_episode:\n if first_episode.fake_orders < 1000:\n return first_episode.fake_orders\n else:\n num500 = first_episode.fake_orders / 500\n return \"%d+\" % (num500 * 500)\n else:\n return 20 # This is an arbitrary value","def _tab_order_sorter(app1, app2):\n app1_order = int(app1[\"taborder\"]) if \"taborder\" in app1 else sys.maxsize\n app2_order = int(app2[\"taborder\"]) if \"taborder\" in app2 else sys.maxsize\n return app1_order - app2_order","def sort_priors(self):\n return","def sort_width(sprite):\n return sprite.width","def shorten(strings, n):\n return sorted(strings, key=lambda x: x[n])","def descending_order(num: int) -> int:\n return int(''.join(sorted([x for x in str(num)], reverse=True)))","def reduce_sort_counts(self, type, word_counts):\n aux = 0\n for count, word in sorted(word_counts, reverse=True):\n if aux < 50: # Controls that we get only the 50 most common keywords\n aux = aux+1\n yield type, (int(count), word)","def _natural_key_sort(string_to_sort):\n return [int(s) if s.isdigit() else s for s in re.split(r'(\\d+)', string_to_sort)]","def _lexsort_depth(self) -> int:\n if self.sortorder is not None:\n return self.sortorder\n return _lexsort_depth(self.codes, self.nlevels)","def order(self):\n return self._order + 1","def reduce_sort_counts(self, type, word_counts):\n aux = 0\n for count, word in sorted(word_counts, reverse=True):\n if aux < 15: # Controls that we get only the 15 most common keywords\n aux = aux+1\n yield type, (int(count), word)","def sort_slide_names(l): \n convert = lambda text: int(text) if text.isdigit() else text \n alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key) ] \n return sorted(l, key = alphanum_key)","def sort_nicely(col):\n convert = lambda text: int(text) if text.isdigit() else text\n alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key[col])]\n return alphanum_key","def display_top_n_words(total_count__of_words, n): # Considering n=10 here as specified in the requirements\n return sorted(total_count__of_words.items(), key=lambda i: i[1], reverse=True)[:n]","def top_chars(phrase):\n list_string = phrase.split(\" \")\n phrase_without_spaces = \"\".join(list_string)\n\n letters_count = {}\n letters_count_list = []\n\n for letter in phrase_without_spaces:\n if letter in letters_count:\n letters_count[letter] += 1\n else:\n letters_count[letter] = 1\n\n for letter, count in letters_count.items():\n letters_count_list.append([letter, count])\n\n max_count = 0\n letters_with_highest_count = ['a']\n\n for letter_and_count in letters_count_list:\n if letter_and_count[1] > max_count:\n letters_with_highest_count[:] = letter_and_count[0]\n max_count = letter_and_count[1]\n elif letter_and_count[1] == max_count:\n letters_with_highest_count.append(letter_and_count[0])\n\n return sorted(letters_with_highest_count)\n\n\n \n\n\n\n \n\n\n\n return []","def sort_string(raw_str):","def smart_sort(item):\n try:\n return int(''.join(os.path.basename(item).split('.')[0:-1]))\n except (TypeError, ValueError, AttributeError):\n return item","def DLEN(self):","def task_property_sorter(property1: str, property2: str) -> int:\n v_1 = get_property_sort_index(property1)\n v_2 = get_property_sort_index(property2)\n return (v_1 > v_2) - (v_1 < v_2)","def __len__(self):\n return len(self._order)","def count_sort(v):\n \n biggest = v[0]\n\n\n for i in range (0, len(v)): #finds the biggest number in the list\n if v[i] > biggest:\n biggest = v[i]\n \n\n elements = [0] * (biggest+1) #A list where the entry at index i is the number of times i occurs in the list v\n \n\n for i in range(0,len(v)): \n\n elements[v[i]] += 1\n\n\n sorted_list = [0]*len(v) #Create the sorted list that will be returned\n \n counter = 0\n for i in range(0,len(elements)):\n for j in range(0,elements[i]):\n sorted_list[counter] = i\n counter += 1\n\n return sorted_list","def get_descr_short(self):\n desc_text = []\n stack = [(self._desc, 0)]\n while stack:\n dl, di = stack.pop()\n while di < len(dl):\n if dl[di] == 0:\n di += 1\n elif dl[di] > 0 and dl[di] < 100000:\n desc_text.append(\"%06d\" % dl[di])\n elif dl[di] >= 100000 and dl[di] < 200000:\n desc_text.append(\"%06d LOOP\" % dl[di])\n elif dl[di] >= 200000 and dl[di] < 300000:\n desc_text.append(\"%06d OPER\" % dl[di])\n elif dl[di] >= 300000 and dl[di] < 400000:\n desc_text.append(\"%06d SEQ\" % dl[di])\n di += 1\n return desc_text","def by_longest_length():\n# fill it out\n return sorted(STRING_LIST, key = lambda s: len(s), reverse=True)","def numerical_sort(self, value):\n numbers = re.compile(r'(\\d+)')\n parts = numbers.split(value)\n parts[1::2] = map(int, parts[1::2])\n return parts","def word_count_sort(word_count_list):\n\n for index in range(1, len(word_count_list)):\n # initialize pointers\n value = word_count_list[index] # starts at the tuple in index 1\n position = index - 1 # initialize to start at 0\n\n # move items to a higher index position while their value is less than the value at the next index\n # compare values in tuple[1] but swap entire tuple\n while position >= 0 and word_count_list[position][1] < value[1]:\n word_count_list[position + 1] = word_count_list[position] # swap the tuple at position into next index\n position -= 1 # decrement to fill lower index and break loop\n\n word_count_list[position + 1] = value # move higher number left one index\n\n return word_count_list","def sort_nicely(l):\r\n\tl.sort(key=alphanum_key)","def counting_sort(arr):\n # Given that numbers are integers in range 0 <= x < 100\n counts = [0 for _ in xrange(100)]\n for num in arr:\n counts[num] += 1\n sorted_arr = []\n for i in xrange(100):\n sorted_arr.extend([i] * counts[i])\n print \" \".join(map(str, sorted_arr))","def __file_sorter(self, filename: str) -> int:\n filename = filename.split('/')[-1]\n year = int(filename[-3:-1]) # extracts YY from ssssdddh.YYo\n day_info = filename[4:8] # extracts dddh from ssssdddh.YYo\n day_of_year = int(day_info[:3]) # ddd\n hour_block = day_info[-1] # h\n if hour_block.isdigit():\n return (year, day_of_year)\n return (year, day_of_year + ord(hour_block))","def ex41():\n with open('module41.in') as infile:\n lines = infile.readlines()\n\n lines.sort()\n\n with open('module41.out', 'w') as outfile:\n header = 'Total of {} names'.format(len(lines))\n outfile.writelines([header + os.linesep, ('-' * len(header)) + os.linesep])\n outfile.writelines(lines)","def display_count_longest_title():\n longest_title = reports.count_longest_title(filename)\n print(\n \"The longest title in {} has a {} characters\\n\".format(\n filename,\n longest_title))"],"string":"[\n \"def sort():\\n return -1\",\n \"def Order(self) -> int:\",\n \"def _natural_sort_worksheet(x):\\n l = re.findall(r\\\"\\\\d+$\\\", x.title)\\n if l:\\n return int(l[0])\\n\\n return -1\",\n \"def _wiki_sort_key(doc):\\n url = doc['url']\\n return 1 if url.startswith('https://en.wikipedia') else -1\",\n \"def bigSorting(unsorted):\\n lookup = defaultdict(lambda: [])\\n print(lookup)\\n for num_string in unsorted:\\n lookup[len(num_string)].append(num_string)\\n\\n results = []\\n lengths = list(lookup.keys())\\n lengths.sort()\\n for length in lengths:\\n x = lookup[length]\\n x.sort()\\n results = results + x\\n print(results)\\n return results\",\n \"def sort_key(self):\\n ...\",\n \"def sort(self,desc):\\n\\tself.__sort(\\\"\\\",\\\"\\\",desc)\",\n \"def sortkey(item):\\n chrom, pos, ref, alt = item[0]\\n if chrom.startswith('chr'):\\n chrom = chrom[3:]\\n if chrom.isdigit():\\n chrom = int(chrom)\\n return (chrom, pos, len(ref), len(alt))\",\n \"def _status_sort(self):\\n s = 0\\n if self.status == 'failed':\\n s += 10\\n if self.image_status == 'diff':\\n s += 3\\n elif self.image_status == 'missing':\\n s += 4\\n if self.hash_status == 'diff':\\n s += 1\\n elif self.hash_status == 'missing':\\n s += 5\\n return f\\\"{s:02.0f}\\\"\",\n \"def order(self):\\n return self.n\",\n \"def sortby(self):\\n ...\",\n \"def get_sort_field(self, kind, order, is_number):\\n pass\",\n \"def sortValue(self, data):\\n storedText = data.get(self.name, '')\\n try:\\n return GenNumber(storedText).num\\n except GenNumberError:\\n return ''\",\n \"def compare(self) -> int:\",\n \"def sortValue(self, data):\\n storedText = data.get(self.name, '')\\n try:\\n return int(UniqueIDFormat.formatRe.match(storedText).group(2))\\n except AttributeError:\\n return 0\",\n \"def sort_format(src):\\n src_list= src.split('-')\\n res_list= []\\n for elm in src_list:\\n try:\\n res_list.append('%05d' % int(elm))\\n except:\\n res_list.append(elm)\\n res= '-'.join(res_list)\\n return res\",\n \"def get_longest_digit_count_desc(lst):\\n rezultat = []\\n for i in lst:\\n if is_desc(i):\\n rezultat.append(i)\\n return rezultat\",\n \"def sort_and_digitize(line):\\n return int(''.join(sorted(str(line))))\",\n \"def _trans_string(self, n):\\r\\n return \\\"%s %d\\\" % (self.desc, n+1)\",\n \"def local_h( author, data ) :\\n papers = papers_and_cites( author, data )\\n papers.sort( lambda a,b : cmp(int(b[1]), int(a[1])) )\\n i = 0\\n while i < (len(papers)-1) and i < int(papers[i][1] ) :\\n i = i + 1\\n\\n return (i+1, int(papers[i][1]) )\",\n \"def get_sort_query(self, kind, order, is_number):\\n pass\",\n \"def get_word_len(self, length):\\n\\n sortedList = self.sortedList\\n\\n step = rd.randint(0, length) * round(time.time())\\n print(step)\\n\\n n = rd.randint(0, len(sortedList) - 1)\\n print(n)\\n while len(sortedList[n]) != length:\\n if len(sortedList[n]) > length:\\n n += step\\n else:\\n n -= step\\n if n < 0 or n > len(sortedList):\\n n = rd.randint(0, len(sortedList) - 1)\\n\\n return sortedList[n]\",\n \"def sort_1(l):\\n pass\",\n \"def humanSort(l): \\n convert = lambda text: int(text) if text.isdigit() else text \\n alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ] \\n l.sort( key=alphanum_key )\",\n \"def test_calc_sort_without_after_object(self):\\n test_object = self.test.datum_type2\\n actual = test_object._calc_sort_value(sort_base_length=3,\\n increment=1,\\n sort_prefix_parts=[test_object.datum_group.sort]\\n )\\n expected = 10101\\n self.assertEqual(expected, actual)\",\n \"def get_row_list_sorting_key(x):\\n name, count = x\\n if '_' not in name:\\n return name\\n s = name.split('_')\\n end = s[-1]\\n start = '_'.join(s[:-1])\\n if utils.is_int(end):\\n return (start, int(end))\\n return name\",\n \"def _get_field_sort_key(self, field):\\n if not field.is_relation:\\n return -1\\n return 0 if field.many_to_many else 1\",\n \"def countingSort(my_list, target):\\r\\n count = [0 for i in range(26)]\\r\\n position = [0 for i in range(26)]\\r\\n output = [0 for i in range(len(my_list))]\\r\\n if len(my_list) > 1:\\r\\n for i in range(len(my_list)):\\r\\n count[ord(my_list[i][0][target]) - 97] += 1\\r\\n position[0] = 0\\r\\n for i in range(1, len(position)):\\r\\n position[i] = position[i - 1] + count[i - 1]\\r\\n for i in range(len(my_list)):\\r\\n key = my_list[i][0]\\r\\n pos=0\\r\\n index = ord(my_list[i][0][target]) - 97\\r\\n if count[index] != 0:\\r\\n pos = position[index]\\r\\n position[index] += 1\\r\\n output[pos] = my_list[i]\\r\\n\\r\\n return output\",\n \"def cmp_numcite( a, b ) :\\n return cmp( int(b['Z9']), int(a['Z9']) )\",\n \"def test_sorting(sort=selection_sort, num_items=20, max_value=50):\\n # TODO: Repeat until all items are in sorted order\\n # TODO: Take first unsorted item\\n # TODO: Insert it in sorted order in front of items\",\n \"def reversesort(self):\\n ...\",\n \"def get_row_list_sorting_key(x):\\n name, count = x\\n if '_' not in name:\\n return name\\n s = name.split('_')\\n end = s[-1]\\n start = '_'.join(s[:-1])\\n if is_int(end):\\n return (start, int(end))\\n return name\",\n \"def test_calc_sort_multiple_parts(self):\\n test_object = self.test.datum_object1\\n sort_parts = [test_object.datum_group.sort,\\n test_object.datum_type.sort\\n ]\\n actual = self.test.datum_object1._calc_sort_value(sort_base_length=2,\\n increment=1,\\n sort_prefix_parts=sort_parts\\n )\\n expected = 101010010\\n self.assertEqual(expected, actual)\",\n \"def sort(n, integer=False):\\n x = ''.join(sorted(str(n)))\\n if integer:\\n return(int(x))\\n else:\\n return(x)\",\n \"def sort_order(self) -> int:\\n return self._sort_order\",\n \"def sort_order(self) -> int:\\n return self._sort_order\",\n \"def __cmp__(self, other):\\n if self.length < other.length:\\n return -1\\n if self.length == other.length:\\n return 0\\n if self.length > other.length:\\n return 1\",\n \"def test_order(type_name):\\n return len(type_name)\",\n \"def test_calc_sort_prefix_reset(self):\\n test_object = self.test.datum_type3\\n sort_parts = [test_object.datum_group.sort,\\n ]\\n actual = test_object._calc_sort_value(sort_base_length=4,\\n increment=1,\\n sort_prefix_parts=sort_parts\\n )\\n expected = 201000\\n self.assertEqual(expected, actual)\",\n \"def _natural_sort_key(value):\\n return map(try_int_cast, re.findall(r'(\\\\d+|\\\\D+)', value))\",\n \"def test_calc_sort_with_after_object(self):\\n test_object = self.test.datum_type2\\n actual = test_object._calc_sort_value(after_object=self.test.datum_type1,\\n sort_base_length=3,\\n increment=1,\\n sort_prefix_parts=[test_object.datum_group.sort]\\n )\\n expected = 10101\\n self.assertEqual(expected, actual)\",\n \"def sortby_num(tree, col, descending): # 重新排序 <-- 數字版\\n # grab values to sort\\n data = [(tree.set(child, col), child) \\\\\\n for child in tree.get_children('')]\\n\\n # if the data to be sorted is numeric change to float\\n #data = change_numeric(data)\\n # now sort the data in place\\n #data.sort(reverse=descending)\\n # 數字的排法(但文字部分就無法排序)\\n data.sort(key=lambda data: int(data[0]), reverse=descending)\\n\\n for ix, item in enumerate(data):\\n tree.move(item[1], '', ix)\\n\\n # switch the heading so it will sort in the opposite direction\\n tree.heading(col, command=lambda col=col: sortby_num(tree, col, \\\\\\n int(not descending)))\",\n \"def sort_duration(self):\\n self.sort('duration')\",\n \"def __len__(self):\\r\\n return len(self.__sorted_names)\",\n \"def numerize():\\n pass\",\n \"def to_ordinal(self):\\n return mod(self.number - 1 + 39 * (self.number - self.name), 260)\",\n \"def norders(self):\\n return 21\",\n \"def dmc_order(self):\\n return sorted(self.lookup_table, key=lambda clr: int(clr.id) if clr.id.isdigit() else 0)\",\n \"def sorted(self): \\n pass\",\n \"def order(name: str):\\n if name.startswith('pred'):\\n split = name.split('_')\\n if len(str(split[-2])) > 10: # New file format, -2 is hash\\n return int(split[-3])\\n return int(split[-2])\\n split = name.split('_')\\n x = split[-1].split('.')[0]\\n return int(x)\",\n \"def next_item_sort_order(self):\\n from nano.models import InvoiceItem\\n total = InvoiceItem.query.filter_by(invoice_id=self.id).count()\\n return total+1\",\n \"def sort_output_desc_asc(word_counts):\\n\\n # sort by item (-item[1] refers to reverse list of second item)\\n sorted_items = sorted(word_counts.items(), key=lambda item: (-item[1], item[0]))\\n \\n for key, value in sorted_items:\\n print \\\"{} {}\\\".format(value, key)\",\n \"def human_sort(l):\\n l.sort(key=alphanum_key)\\n return l\",\n \"def test_version_sorting(self):\\n assert natsort(['1', '5', '10', '50']) == ['1', '5', '10', '50']\",\n \"def nat_sort_key(val):\\n split_val = _grouped_digits_re.split(str(val))\\n for i in xrange(1, len(split_val), 2):\\n split_val[i] = int(split_val[i])\\n start = 1 if split_val[0] == '' else 0\\n end = -1 if split_val[-1] == '' else None\\n split_val = split_val[start:end]\\n # _dbg(\\\"nat_sort_key: %r -> %r\\\", val, split_val)\\n return split_val\",\n \"def order(knl):\\n return int(re.match(r\\\"k(\\\\d+)l\\\", knl).group(1))\",\n \"def sort_numerical(paths):\\n paths.sort(key=alphanum_key)\\n return paths\",\n \"def sort_0(l):\\n l.sort()\",\n \"def _run_pair_sorter(run_pair):\\n run, other_run = run_pair\\n\\n return (len(run) + len(other_run), len(other_run))\",\n \"def order_ideal(self, gens):\",\n \"def _get_display_orders(self):\\n if self.fake_orders < 1000:\\n return self.fake_orders\\n else:\\n num500 = self.fake_orders / 500\\n return \\\"%d+\\\" % (num500 * 500)\",\n \"def fullcountSort(arr):\\n sorted = [[] for i in range(100)]\\n for i in range(int(len(arr) / 2)):\\n sorted[int(arr[i][0])].append('-')\\n for i in range(int(len(arr) / 2), len(arr)):\\n sorted[int(arr[i][0])].append(arr[i][1])\\n\\n output = ''\\n for item in sorted:\\n if item == []:\\n pass\\n else:\\n output = output + ' '.join(item) + ' '\\n print(output)\",\n \"def sortLength(self):\\n return FeatureSet(sorted(self, key = lambda f: f.length()))\",\n \"def min_lengths(cls, description):\\n\\n min_indexes = [s - 1 for s in partial_sums(description, colored=False)]\\n return min_indexes\",\n \"def sort_res(res_tim):\\r\\n i=0\\r\\n length=0\\r\\n for each in res_tim:\\r\\n mat=re.search(r'(\\\\d\\\\d:\\\\d\\\\d:\\\\d\\\\d)',each)\\r\\n if mat and i!=10:\\r\\n if i==0:\\r\\n hr=mat.group(1)\\r\\n i+=1\\r\\n elif i==10:\\r\\n break\\r\\n elif not mat.group(1)==hr:\\r\\n i+=1\\r\\n hr=mat.group(1)\\r\\n length+=1\\r\\n else:\\r\\n break\\r\\n return length,hr\",\n \"def sortByIndex(self,_index,desc):\\n\\treturn self.sortByPostText(\\\"[%s]\\\"%_index,desc)\",\n \"def index_sortable_title_IEntry(object, **kw):\\n if object.__parent__.sorting == 'surname':\\n # Assume title is a name, pull last word (surname) off and put it at\\n # the start\\n m = re.search('(.*) (.*)', object.title)\\n if m:\\n return \\\" \\\".join(m.groups()[::-1])\\n # Sort by title\\n return object.title\",\n \"def main(str_text):\\n\\n frequencies = count_value(str_text)\\n sorted_data = sort_dict(frequencies)\\n\\n return sorted_data\",\n \"def human_sort( l ):\\n convert = lambda text: int(text) if text.isdigit() else text\\n alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ]\\n alphanum_key = None\\n try:\\n l.sort( key=alphanum_key )\\n except TypeError:\\n l.sort()\\n return l\",\n \"def test_sort_fewer_than_n(self):\\n e1 = Experience(rid=1, uid=3, experience=100)\\n e2 = Experience(rid=1, uid=1, experience=89)\\n e3 = Experience(rid=1, uid=12, experience=1343)\\n db.session.add(e1)\\n db.session.add(e2)\\n db.session.add(e3)\\n db.session.commit()\\n list = top_n_in_order(1,5)\\n self.assertEqual([(12, 1343), (3, 100), (1, 89)], list)\",\n \"def _get_display_orders(self):\\n query_set = SeriesEpisode.objects.filter(series=self.id)\\n first_episode = query_set[0] if len(query_set) > 0 else None\\n if first_episode:\\n if first_episode.fake_orders < 1000:\\n return first_episode.fake_orders\\n else:\\n num500 = first_episode.fake_orders / 500\\n return \\\"%d+\\\" % (num500 * 500)\\n else:\\n return 20 # This is an arbitrary value\",\n \"def _tab_order_sorter(app1, app2):\\n app1_order = int(app1[\\\"taborder\\\"]) if \\\"taborder\\\" in app1 else sys.maxsize\\n app2_order = int(app2[\\\"taborder\\\"]) if \\\"taborder\\\" in app2 else sys.maxsize\\n return app1_order - app2_order\",\n \"def sort_priors(self):\\n return\",\n \"def sort_width(sprite):\\n return sprite.width\",\n \"def shorten(strings, n):\\n return sorted(strings, key=lambda x: x[n])\",\n \"def descending_order(num: int) -> int:\\n return int(''.join(sorted([x for x in str(num)], reverse=True)))\",\n \"def reduce_sort_counts(self, type, word_counts):\\n aux = 0\\n for count, word in sorted(word_counts, reverse=True):\\n if aux < 50: # Controls that we get only the 50 most common keywords\\n aux = aux+1\\n yield type, (int(count), word)\",\n \"def _natural_key_sort(string_to_sort):\\n return [int(s) if s.isdigit() else s for s in re.split(r'(\\\\d+)', string_to_sort)]\",\n \"def _lexsort_depth(self) -> int:\\n if self.sortorder is not None:\\n return self.sortorder\\n return _lexsort_depth(self.codes, self.nlevels)\",\n \"def order(self):\\n return self._order + 1\",\n \"def reduce_sort_counts(self, type, word_counts):\\n aux = 0\\n for count, word in sorted(word_counts, reverse=True):\\n if aux < 15: # Controls that we get only the 15 most common keywords\\n aux = aux+1\\n yield type, (int(count), word)\",\n \"def sort_slide_names(l): \\n convert = lambda text: int(text) if text.isdigit() else text \\n alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key) ] \\n return sorted(l, key = alphanum_key)\",\n \"def sort_nicely(col):\\n convert = lambda text: int(text) if text.isdigit() else text\\n alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key[col])]\\n return alphanum_key\",\n \"def display_top_n_words(total_count__of_words, n): # Considering n=10 here as specified in the requirements\\n return sorted(total_count__of_words.items(), key=lambda i: i[1], reverse=True)[:n]\",\n \"def top_chars(phrase):\\n list_string = phrase.split(\\\" \\\")\\n phrase_without_spaces = \\\"\\\".join(list_string)\\n\\n letters_count = {}\\n letters_count_list = []\\n\\n for letter in phrase_without_spaces:\\n if letter in letters_count:\\n letters_count[letter] += 1\\n else:\\n letters_count[letter] = 1\\n\\n for letter, count in letters_count.items():\\n letters_count_list.append([letter, count])\\n\\n max_count = 0\\n letters_with_highest_count = ['a']\\n\\n for letter_and_count in letters_count_list:\\n if letter_and_count[1] > max_count:\\n letters_with_highest_count[:] = letter_and_count[0]\\n max_count = letter_and_count[1]\\n elif letter_and_count[1] == max_count:\\n letters_with_highest_count.append(letter_and_count[0])\\n\\n return sorted(letters_with_highest_count)\\n\\n\\n \\n\\n\\n\\n \\n\\n\\n\\n return []\",\n \"def sort_string(raw_str):\",\n \"def smart_sort(item):\\n try:\\n return int(''.join(os.path.basename(item).split('.')[0:-1]))\\n except (TypeError, ValueError, AttributeError):\\n return item\",\n \"def DLEN(self):\",\n \"def task_property_sorter(property1: str, property2: str) -> int:\\n v_1 = get_property_sort_index(property1)\\n v_2 = get_property_sort_index(property2)\\n return (v_1 > v_2) - (v_1 < v_2)\",\n \"def __len__(self):\\n return len(self._order)\",\n \"def count_sort(v):\\n \\n biggest = v[0]\\n\\n\\n for i in range (0, len(v)): #finds the biggest number in the list\\n if v[i] > biggest:\\n biggest = v[i]\\n \\n\\n elements = [0] * (biggest+1) #A list where the entry at index i is the number of times i occurs in the list v\\n \\n\\n for i in range(0,len(v)): \\n\\n elements[v[i]] += 1\\n\\n\\n sorted_list = [0]*len(v) #Create the sorted list that will be returned\\n \\n counter = 0\\n for i in range(0,len(elements)):\\n for j in range(0,elements[i]):\\n sorted_list[counter] = i\\n counter += 1\\n\\n return sorted_list\",\n \"def get_descr_short(self):\\n desc_text = []\\n stack = [(self._desc, 0)]\\n while stack:\\n dl, di = stack.pop()\\n while di < len(dl):\\n if dl[di] == 0:\\n di += 1\\n elif dl[di] > 0 and dl[di] < 100000:\\n desc_text.append(\\\"%06d\\\" % dl[di])\\n elif dl[di] >= 100000 and dl[di] < 200000:\\n desc_text.append(\\\"%06d LOOP\\\" % dl[di])\\n elif dl[di] >= 200000 and dl[di] < 300000:\\n desc_text.append(\\\"%06d OPER\\\" % dl[di])\\n elif dl[di] >= 300000 and dl[di] < 400000:\\n desc_text.append(\\\"%06d SEQ\\\" % dl[di])\\n di += 1\\n return desc_text\",\n \"def by_longest_length():\\n# fill it out\\n return sorted(STRING_LIST, key = lambda s: len(s), reverse=True)\",\n \"def numerical_sort(self, value):\\n numbers = re.compile(r'(\\\\d+)')\\n parts = numbers.split(value)\\n parts[1::2] = map(int, parts[1::2])\\n return parts\",\n \"def word_count_sort(word_count_list):\\n\\n for index in range(1, len(word_count_list)):\\n # initialize pointers\\n value = word_count_list[index] # starts at the tuple in index 1\\n position = index - 1 # initialize to start at 0\\n\\n # move items to a higher index position while their value is less than the value at the next index\\n # compare values in tuple[1] but swap entire tuple\\n while position >= 0 and word_count_list[position][1] < value[1]:\\n word_count_list[position + 1] = word_count_list[position] # swap the tuple at position into next index\\n position -= 1 # decrement to fill lower index and break loop\\n\\n word_count_list[position + 1] = value # move higher number left one index\\n\\n return word_count_list\",\n \"def sort_nicely(l):\\r\\n\\tl.sort(key=alphanum_key)\",\n \"def counting_sort(arr):\\n # Given that numbers are integers in range 0 <= x < 100\\n counts = [0 for _ in xrange(100)]\\n for num in arr:\\n counts[num] += 1\\n sorted_arr = []\\n for i in xrange(100):\\n sorted_arr.extend([i] * counts[i])\\n print \\\" \\\".join(map(str, sorted_arr))\",\n \"def __file_sorter(self, filename: str) -> int:\\n filename = filename.split('/')[-1]\\n year = int(filename[-3:-1]) # extracts YY from ssssdddh.YYo\\n day_info = filename[4:8] # extracts dddh from ssssdddh.YYo\\n day_of_year = int(day_info[:3]) # ddd\\n hour_block = day_info[-1] # h\\n if hour_block.isdigit():\\n return (year, day_of_year)\\n return (year, day_of_year + ord(hour_block))\",\n \"def ex41():\\n with open('module41.in') as infile:\\n lines = infile.readlines()\\n\\n lines.sort()\\n\\n with open('module41.out', 'w') as outfile:\\n header = 'Total of {} names'.format(len(lines))\\n outfile.writelines([header + os.linesep, ('-' * len(header)) + os.linesep])\\n outfile.writelines(lines)\",\n \"def display_count_longest_title():\\n longest_title = reports.count_longest_title(filename)\\n print(\\n \\\"The longest title in {} has a {} characters\\\\n\\\".format(\\n filename,\\n longest_title))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6401724","0.62728316","0.60654205","0.60012025","0.59754735","0.59544206","0.59370434","0.59157306","0.58810264","0.58680815","0.58301955","0.5825593","0.57766974","0.5709983","0.5653453","0.560097","0.5593121","0.555219","0.5539747","0.5538889","0.5534576","0.55307794","0.5512389","0.5501747","0.5498305","0.5471895","0.5465556","0.54616284","0.5441643","0.54373246","0.5432744","0.5430694","0.5399089","0.53864485","0.53857094","0.53857094","0.5369997","0.5368379","0.5367603","0.53655493","0.53609794","0.53423786","0.53407675","0.53396255","0.53376925","0.5336791","0.5332553","0.5309675","0.5297863","0.5296617","0.5290585","0.528964","0.5288361","0.52793586","0.5274856","0.5269018","0.52623683","0.5257306","0.5244098","0.52399683","0.5239573","0.5235955","0.5233495","0.52257866","0.52221286","0.52199334","0.5211668","0.5204462","0.5198348","0.51982975","0.5198159","0.5195735","0.51895654","0.5187998","0.5183245","0.5165672","0.51653296","0.51652336","0.5162983","0.51628155","0.5160168","0.51561314","0.5154035","0.5141189","0.5132303","0.511693","0.5108263","0.51081854","0.50986964","0.50953704","0.50929654","0.5086524","0.5083385","0.5082828","0.5078137","0.5070094","0.50652444","0.50602764","0.5057716","0.5057395"],"string":"[\n \"0.6401724\",\n \"0.62728316\",\n \"0.60654205\",\n \"0.60012025\",\n \"0.59754735\",\n \"0.59544206\",\n \"0.59370434\",\n \"0.59157306\",\n \"0.58810264\",\n \"0.58680815\",\n \"0.58301955\",\n \"0.5825593\",\n \"0.57766974\",\n \"0.5709983\",\n \"0.5653453\",\n \"0.560097\",\n \"0.5593121\",\n \"0.555219\",\n \"0.5539747\",\n \"0.5538889\",\n \"0.5534576\",\n \"0.55307794\",\n \"0.5512389\",\n \"0.5501747\",\n \"0.5498305\",\n \"0.5471895\",\n \"0.5465556\",\n \"0.54616284\",\n \"0.5441643\",\n \"0.54373246\",\n \"0.5432744\",\n \"0.5430694\",\n \"0.5399089\",\n \"0.53864485\",\n \"0.53857094\",\n \"0.53857094\",\n \"0.5369997\",\n \"0.5368379\",\n \"0.5367603\",\n \"0.53655493\",\n \"0.53609794\",\n \"0.53423786\",\n \"0.53407675\",\n \"0.53396255\",\n \"0.53376925\",\n \"0.5336791\",\n \"0.5332553\",\n \"0.5309675\",\n \"0.5297863\",\n \"0.5296617\",\n \"0.5290585\",\n \"0.528964\",\n \"0.5288361\",\n \"0.52793586\",\n \"0.5274856\",\n \"0.5269018\",\n \"0.52623683\",\n \"0.5257306\",\n \"0.5244098\",\n \"0.52399683\",\n \"0.5239573\",\n \"0.5235955\",\n \"0.5233495\",\n \"0.52257866\",\n \"0.52221286\",\n \"0.52199334\",\n \"0.5211668\",\n \"0.5204462\",\n \"0.5198348\",\n \"0.51982975\",\n \"0.5198159\",\n \"0.5195735\",\n \"0.51895654\",\n \"0.5187998\",\n \"0.5183245\",\n \"0.5165672\",\n \"0.51653296\",\n \"0.51652336\",\n \"0.5162983\",\n \"0.51628155\",\n \"0.5160168\",\n \"0.51561314\",\n \"0.5154035\",\n \"0.5141189\",\n \"0.5132303\",\n \"0.511693\",\n \"0.5108263\",\n \"0.51081854\",\n \"0.50986964\",\n \"0.50953704\",\n \"0.50929654\",\n \"0.5086524\",\n \"0.5083385\",\n \"0.5082828\",\n \"0.5078137\",\n \"0.5070094\",\n \"0.50652444\",\n \"0.50602764\",\n \"0.5057716\",\n \"0.5057395\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6969995"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":25685,"cells":{"query":{"kind":"string","value":"Render to PDF if desired, by first getting the HTML version."},"document":{"kind":"string","value":"def render(self, output_name, wide=False):\n\n html = self.html(wide)\n print 'You can ignore the GLib-Gobject errors (if they occur)'\n if wide:\n HTML(string=html).write_pdf(\n output_name, stylesheets=[CSS(string=esCSS.replace(\"8.8cm\", \"18cm\"))])\n else:\n HTML(string=html).write_pdf(\n output_name, stylesheets=[CSS(string=esCSS)])"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def render_as_pdf(self, width, height):\n pass","def get_raw_pdf(html_path, pdf_path, width='', height=''):\n debug = False\n if mg.EXPORT_IMAGES_DIAGNOSTIC: debug = True\n try:\n url = html_path.as_uri()\n cmd_make_pdf = 'cmd_make_pdf not successfully generated yet'\n \"\"\"\n Unless Linux, MUST be in report directory otherwise won't carry across\n internal links.\n\n Re: http://www.microsoft.com/resources/documentation/windows/xp/all/proddocs/en-us/ntcmds_shelloverview.mspx?mfr=true\n \"\"\"\n ## clear decks first so we can tell if image made or not\n try:\n os.remove(pdf_path)\n except Exception:\n pass\n rel_url = os.path.split(url)[1]\n cd_path = os.path.split(html_path)[0]\n if mg.PLATFORM == mg.WINDOWS: ## using Pyinstaller\n cmd_make_pdf = (\n f'cd \"{cd_path}\" && '\n f'\"{export_output.EXE_TMP}\\\\wkhtmltopdf.exe\" '\n f'{width} {height} \"{rel_url}\" \"{pdf_path}\"')\n elif mg.PLATFORM == mg.MAC:\n cmd_make_pdf = (\n f'cd \"{cd_path}\" && '\n f'\"{mg.MAC_FRAMEWORK_PATH}/wkhtmltopdf\" '\n f'{width} {height} \"{rel_url}\" \"{pdf_path}\"')\n elif mg.PLATFORM == mg.LINUX:\n cmd_make_pdf = f'wkhtmltopdf {width} {height} \"{url}\" \"{pdf_path}\"'\n else:\n raise Exception('Encountered an unexpected platform!')\n ## wkhtmltopdf uses stdout to actually output the PDF - a good feature but stuffs up reading stdout for message\n if debug: print(f'cmd_make_pdf: {cmd_make_pdf}')\n export_output.shellit(cmd_make_pdf)\n if not os.path.exists(pdf_path):\n raise Exception(\n f\"wkhtmltopdf didn't generate error but {pdf_path} not made \"\n f'nonetheless. cmd_make_pdf: {cmd_make_pdf}')\n if debug: print(f'Initial processing of {html_path} complete')\n except Exception as e:\n raise Exception(\n f'get_raw_pdf command failed: {cmd_make_pdf}. Orig error: {b.ue(e)}')\n return pdf_path","def make_pdf(self):\n source = self.get_page_source()\n if not source:\n self.errors.append('no_source')\n if not self.errors:\n self.generate_pdf_file(source)","def render_to_pdf(template_src, context_dict={}):\n template = get_template(template_src)\n html = template.render(context_dict)\n result = BytesIO()\n pdf = pisa.pisaDocument(BytesIO(html.encode(\"ISO-8859-1\")), result)\n if not pdf.err:\n return HttpResponse(result.getvalue(), content_type='application/pdf')\n return None","def get_pdf(self) -> io.BytesIO:\n return self._get_pdf(rendered_html=self.get_rendered_html())","def _produce_pdf_as_a_response(self, html):\n # Create a Django response object, and specify content_type as pdf\n response = HttpResponse(content_type='application/pdf')\n # Define that this is an attachment. \n response['Content-Disposition'] = 'attachment;'\n pisaStatus = pisa.CreatePDF(html, dest=response)\n \n return response","def to_pdf(self, wkhtmltopdf: str, f, output_file: Optional[str] = None):\n if output_file is None:\n output_file = \"-\"\n html = self(f)\n with tempfile.NamedTemporaryFile(\"wb\", suffix=\".html\") as fd:\n html.write(fd)\n fd.flush()\n res = subprocess.run([wkhtmltopdf, fd.name, output_file], stdin=subprocess.DEVNULL, capture_output=True)\n if res.returncode != 0:\n raise RuntimeError(\"%s exited with error %d: stderr: %s\", self.wkhtmltopdf, res.returncode, res.stderr)\n if output_file == \"-\":\n return res.stdout","def _pdf(self):\n # LOG: processing_type property\n self.set_property('processing_type', 'pdf')\n xmlDoc = PDFiD(self.src_path)\n oPDFiD = cPDFiD(xmlDoc, True)\n # TODO: are there other characteristics which should be dangerous?\n if oPDFiD.encrypt.count > 0:\n self.make_dangerous('encrypted pdf')\n if oPDFiD.js.count > 0 or oPDFiD.javascript.count > 0:\n self.make_dangerous('pdf with javascript')\n if oPDFiD.aa.count > 0 or oPDFiD.openaction.count > 0:\n self.make_dangerous('openaction')\n if oPDFiD.richmedia.count > 0:\n self.make_dangerous('flash')\n if oPDFiD.launch.count > 0:\n self.make_dangerous('launch')","def make_pdf(self, htmlbody, html_only=False):\n # wrap htmlbody with provided HTML template\n template = self.context.auto_template\n template = template.replace(u'${body}', htmlbody)\n if html_only:\n return template\n try:\n tempdir = tempfile.mkdtemp()\n # attachemnts saved. Let's save generated HTML\n fullpath = os.path.join(tempdir, 'issue.html')\n fp = open(fullpath, 'w')\n fp.write(template.encode('utf-8'))\n fp.close()\n # Run wkhtmltopdf and generate the PDF\n targetpath = os.path.join(tempdir, 'issue.pdf')\n result = subprocess.call([\"wkhtmltopdf\", '-q', 'file://%s' % fullpath, '%s' % targetpath])\n if result == 0:\n return open(targetpath, 'rb').read()\n else:\n return ''\n finally:\n shutil.rmtree(tempdir, ignore_errors=True)","def generate_pdf(pdf_data):\n\n html = HTML(string=pdf_data)\n f = html.write_pdf()\n\n return f","def render(path: str, params: dict):\n template = get_template(path)\n html = template.render(params)\n response = BytesIO()\n # is this file name a placeholder?\n #file = open('my.file.pdf', 'wb')\n pdf = pisa.pisaDocument(BytesIO(html.encode(\"UTF-8\")), response)\n #file.close()\n if not pdf.err:\n return HttpResponse(response.getvalue(), content_type='application/pdf')\n else:\n return HttpResponse(\"Error Rendering PDF\", status=400)","def _create_pdf(self, survey, response):\n pdf_transformer = PDFTransformer(survey, response)\n self._pdf, self._page_count = pdf_transformer.render_pages()\n return self._pdf","def render_pdf(\n template: Union[List[str], str],\n file_: IO,\n url_fetcher=django_url_fetcher,\n context: Optional[dict] = None,\n):\n context = context or {}\n\n if isinstance(template, str):\n template = [template]\n\n html = select_template(template).render(context)\n HTML(\n string=html,\n base_url=\"not-used://\",\n url_fetcher=url_fetcher,\n ).write_pdf(\n target=file_,\n )","def generate_pdf_flask_response(pdf_data):\n html = HTML(string=pdf_data)\n\n return render_pdf(html)","def preview():\r\n html = create_html_report()\r\n return html","def downlaod():\r\n filename = str(uuid.uuid4()) + '.pdf'\r\n filename = os.path.join('./output' , filename)\r\n\r\n config = pdfkit.configuration(wkhtmltopdf = PRG_Path)\r\n options = {\r\n 'page-size': 'Letter'\r\n ,'margin-top': '0.75in'\r\n ,'margin-right': '0.75in'\r\n ,'margin-bottom': '0.75in'\r\n ,'margin-left': '0.75in'\r\n ,'no-outline': None\r\n ,'encoding':'UTF-8'\r\n ,'enable-local-file-access':None\r\n ,'quiet': ''\r\n # ,'javascript-delay':2000000\r\n }\r\n\r\n\r\n html = create_html_report()\r\n pdf = pdfkit.from_string(input=html, output_path=filename,configuration=config, options=options)\r\n pdfDownload = open(filename,'rb').read()\r\n\r\n response: Response = Response (\r\n pdfDownload\r\n ,mimetype=\"application/pdf\"\r\n ,headers={\r\n \"Content-disposition\": \"attachment; filename=\" + filename\r\n ,\"Content-type\": \"application/force-download\"\r\n }\r\n )\r\n return response","def html(self):\n return self.report_format in ['pdf', 'html']","def render_pdf(self, target=None, zoom=1):\n return self._document.write_pdf(target=target, zoom=zoom)","def create_pdf(html, options):\n\n # TODO: we will change this path, or use an other library for converting PDF!\n # TODO: otherwise just say that wkhtmltopdf needs to be pre-installed (and how) and added to windows path\n path_wkthmltopdf = \"C:/Program Files/wkhtmltopdf/bin/wkhtmltopdf.exe\"\n config = pdfkit.configuration(wkhtmltopdf=path_wkthmltopdf)\n\n pdfkit.from_file(html, html.replace(\".html\", \".pdf\"), configuration=config, options=options)\n return html + \".pdf\"","def buildPDF(self):\n\n # TODO: get this working\n # TODO: make this configurable via a dialog\n os.chdir(self.file_path.parent)\n proc = subprocess.Popen(\n [\"make\", \"latexpdf\"],\n stdin=subprocess.PIPE,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT\n )\n proc.wait()\n for line in proc.stdout:\n print(\"stdout: \" + line.rstrip())","def render_to_response(self, context, **response_kwargs):\n\n response = HttpResponse(mimetype=self.mimetype)\n response['Content-Disposition'] = ('attachment; filename=%s.%s' %\n (context['filename'],\n self.extension))\n f = render_to_pdf(self.template_name, context)\n response.write(f)\n return response","def _compute_single_pdf(self, **kwargs):\n raise NotImplementedError","def __get_ticket_print(self, **kwargs):\n # TODO: выяснить используется ли pdf в принципе. В эл.регестратуре он никак не используется\n # TODO: pdf creator based on Flask templates and xhtml2pdf\n return \"\"","def generate_pdf(self):\n x = 100\n y = 100\n buffer = BytesIO()\n p = canvas.Canvas(buffer, pagesize=\"A4\")\n p.drawString(x, y, \"TO DO\")\n p.showPage()\n p.save()\n pdf = buffer.getvalue()\n buffer.close()\n return pdf","def generate_pdf(request):\n reg_no = request.user.username\n user = get_object_or_404(User, username=reg_no)\n user_profile = user.get_profile()\n user_application = user_profile.application\n np = user_application.np\n \n response = HttpResponse(mimetype='application/pdf')\n response['Content-Disposition'] = 'attachment; filename=JAM2012_Allottment.pdf'\n \n elements = []\n doc = SimpleDocTemplate(response)\n \n formatted_time = time.ctime()\n styles = getSampleStyleSheet()\n styles.add(ParagraphStyle(name='Justify', alignment=TA_JUSTIFY))\n \n ptext = '<font size=15>JAM 2012 - Admissions.</font>' \n elements.append(Paragraph(ptext, styles[\"Justify\"]))\n elements.append(Spacer(4, 20))\n \n ptext = '<font size=12>Registration Number: %s</font>' % reg_no \n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(1, 12))\n \n data = [] \n options = get_chosen_options(user) ##Put a check to show when the options chosen is empty\n \n if not(options):\n ptext = '<font size=12>No choices were selected.</font>' \n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(1, 12))\n doc.build(elements) \n return response \n \n ptext = '<font size=12>The choices selected by me are as follows: </font>' \n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(4, 30))\n \n counter = 1\n for opt in options:\n data.append([counter, opt.opt_code, opt.opt_location, opt.opt_name])\n counter = counter + 1\n \n t = Table(data)\n t.setStyle(TableStyle([('GRID',(0,0),(3,len(options)),1,colors.black),\n ('TEXTCOLOR',(0,0),(0,-1),colors.green)]))\n \n elements.append(t) \n \n elements.append(Spacer(4, 30))\n \n ptext = '<font size=12>I hereby declare that the order of preference given by me for my eligible programmes is final. </font>' \n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(4, 25))\n \n ptext = '<font size=12>Signature of the Candidate</font>' \n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(4, 20))\n \n ptext = '<font size=12>%s</font>' % formatted_time\n elements.append(Paragraph(ptext, styles[\"Normal\"]))\n elements.append(Spacer(1, 12))\n \n doc.build(elements)\n \n return response","def task_render_report():\n target = 'report.pdf'\n dep = 'report.md'\n return {\n 'file_dep': [dep],\n 'targets': [target],\n 'actions': [\n f\"pandoc -t latex -o {target} {dep}\"\n ],\n 'clean': True\n }","def form(request):\n\n font_config = FontConfiguration()\n # Use the BCSans font as the default.\n css = CSS(string='''\n @font-face {\n font-family: 'BCSans';\n font-style: normal;\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Regular.woff') format('woff');\n }\n @font-face {\n font-family: 'BCSans';\n font-style: italic;\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Italic.woff') format('woff');\n }\n @font-face {\n font-family: 'BCSans';\n font-weight: 700;\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Bold.woff') format('woff');\n }\n @font-face {\n font-family: 'BCSans';\n font-style: italic;\n font-weight: 700;\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-BoldItalic.woff') format('woff');\n }''', font_config=font_config)\n\n\n\n data = json.loads(request.body)\n name = request.GET['name']\n template = '{}.html'.format(name)\n\n template = get_template(template)\n html_content = template.render(data)\n\n pdf_content = render_pdf(html_content)\n\n response = HttpResponse(content_type='application/pdf')\n response['Content-Disposition'] = 'attachment; filename=\"report.pdf\"'\n\n response.write(pdf_content, stylesheet[css], font_config=font_config)\n\n return response","def test_render_pdf(self):\n charname = \"ChupStudent\"\n bad_char_name = \"Rumplestiltskin\" # pylint: disable=unused-variable\n config.OUTDIR = \".\"\n retval = -1\n expected_out_name = GAMEBASE + \"/Charsheets/\" + charname + \"_Charsheet.pdf\"\n retval = name_pdfs.render_pdf(charname, \"COS_Student_Adopted.tex\")\n self.assertEqual(retval, 0)\n self.assertTrue(\n Path.exists(Path(expected_out_name)),\n f\"Failed for expected output name {expected_out_name}\",\n )\n retval = -1\n for badname in self.bad_filenames:\n with self.subTest(badname=badname):\n try:\n retval = name_pdfs.render_pdf(charname, badname, draft=True)\n except TypeError:\n retval = 1\n except FileNotFoundError:\n retval = 1\n except subprocess.CalledProcessError:\n retval = 1\n else:\n self.fail()\n finally:\n self.assertNotEqual(retval, 0)","def download(texttitle):\n try:\n body = current_file.analysed_texts['Regular']\n rendered = render_template('pdf_template.html', title=texttitle, body=body)\n options = {'encoding': \"UTF-8\"}\n pdf = pdfkit.from_string(rendered, False, options=options)\n response = make_response(pdf)\n response.headers[\"Content-Type\"] = 'application/pdf'\n response.headers[\"Content-Disposition\"] = 'attachment; filename=output.pdf'\n\n return response\n except Exception as e:\n flash(\"Something went wrong, please try again\")\n return redirect(request.referrer)","def pdf_to_text(self, f):\n cmd = [\"pdftohtml\", \"-zoom\", \"1.35\", \"-xml\", \"-stdout\", f.name]\n code, stdout, stderr = self.shell(cmd)\n if code > 0:\n raise ValueError(stderr)\n return stdout.decode('utf-8')","def pdf():\n env.file_ext = \".pdf\"\n local(\"pandoc {input_files} -o {output_file}{file_ext} -H {preamble_file} --template {template_file} --bibliography={bib_file} --csl={csl_file} -V fontsize=12pt -V papersize=a4paper -V documentclass:report -N --latex-engine=xelatex\".format(**env))","def html2pdf(html_filename, output_filename=None, **options):\n\n if not output_filename:\n output_filename = newTempfile(suffix='.pdf')\n\n if not pdfreactor_available:\n raise RuntimeError(\"The external 'pdfreactor' converter isn't available\")\n\n cmd = '%s \"pdfreactor\" \"%s\" \"%s\"' % \\\n (execution_shell, html_filename, output_filename)\n \n status, output = runcmd(cmd)\n if status != 0:\n raise ConversionError('Error executing: %s' % cmd, output)\n return dict(output_filename=output_filename,\n status=status,\n output=output)","def make_pdf_from_raw_html(self, html, filename: str, options=None):\n return pdfkit.from_string(html, filename, configuration=self._get_pdfkit_config(), options=options)","def hs_document(self):\n doc_service = PDFKitService(html=self.html())\n return doc_service.pdf(template_name='engageletter.html')","def display_html_report():\n display(HTML('report_page.html'))","def template2pdf(template=None, **kwargs):\n str = render_to_string(template, kwargs)\n output = kwargs.get('output', False)\n ret = pdfkit.from_string(str, output, settings.WKHTMLTOPDF_OPTIONS or default_options)\n return (ret, str)","def generate_pdf_file(self, source):\n filename = self.generate_temp_filename()\n if not filename:\n self.errors.append('filename_generation_failed')\n return\n\n try:\n transform_module = getattr(transforms, self.pdf_generator)\n except AttributeError:\n self.errors.append('wrong_generator_configuration')\n return\n\n self.filename = filename\n url = self.context.absolute_url()\n\n print_css = (self.pdf_tool.always_print_css or\n self.context.portal_type in self.pdf_tool.print_css_types)\n\n # When the source is sent through Ajax, it's already encoded\n # as a utf-8 string. When using it without javascript, the\n # source comes from a view, which always returns unicode. In\n # that case we need to encode it.\n if isinstance(source, unicode):\n source = source.encode('utf-8')\n export_file, err = transform_module.html_to_pdf(\n source,\n self.tempdir,\n filename,\n url,\n print_css,\n self.get_extra_options())\n\n if err:\n self.errors.append('pdf_creation_failed')\n return\n\n self.pdf_tool.registerPDF(filename)\n self.pdf_file = export_file\n self.pdf_file.close()","def create_pdf(submission):\n # Get questions from sections\n fields = {}\n for section in submission.questions:\n for form in section[\"forms\"]:\n for field in form[\"fields\"]:\n fs = field.get(\"fields\", [field])\n for f in fs:\n fields[f[\"name\"]] = f\n\n # Pull out image and answers\n images = []\n docs = []\n answers = []\n for answer in submission.answers:\n answer, name = answer.get(\"answer\", \"\"), answer.get(\"name\", \"\")\n field = fields[name]\n if field[\"type\"] == \"FILE\":\n image_ids = []\n doc_ids = []\n for file in answer:\n if \"image\" in file:\n image_ids.append(file[\"id\"])\n elif \"file\" in file:\n doc_ids.append(file[\"id\"])\n\n if image_ids:\n images += [\n image_upload.image\n for image_upload in ImageUpload.objects.filter(\n pk__in=image_ids\n ).all()\n ]\n if doc_ids:\n docs += [\n file_upload.file\n for file_upload in FileUpload.objects.filter(pk__in=doc_ids).all()\n ]\n else:\n answers.append(\n {\n \"name\": name.lower().replace(\"_\", \" \").capitalize(),\n \"prompt\": field.get(\"prompt\", \"\"),\n \"answers\": answer if type(answer) is list else [answer],\n }\n )\n\n context = {\n \"submission\": submission,\n \"answers\": answers,\n \"images\": images,\n \"docs\": docs,\n }\n pdf_html_str = render_to_string(\"client-intake.html\", context=context)\n pdf_bytes = weasyprint.HTML(string=pdf_html_str).write_pdf()\n return pdf_bytes","def renderDocumentFromURL(self,url):\n in0=url\n in1=self.PDFreactorConfiguration.in1\n args = {\"in0\" : in0, \"in1\" : in1}\n \n self.resp = self.client.ROCall(\"renderDocumentFromURL\", args)\n return self.resp[\"pdf\"]","def renderDocumentFromContent(self,content):\n in0=content\n in1=self.PDFreactorConfiguration.in1\n args = {\"in0\" : in0, \"in1\" : in1}\n \n self.resp = self.client.ROCall(\"renderDocumentFromContent\",args)\n return self.resp[\"pdf\"]","def _produce_pdf_as_an_attachment(self, html, pdf_details):\n result = BytesIO()\n pisa.pisaDocument(BytesIO(html.encode(\"ISO-8859-1\")), result)\n return result.getvalue(), pdf_details","def generate_document(stats: dict, semester: str):\n filename = 'report_' + str(date.today()) + '.html'\n with open('raw_html.html', 'r') as f:\n string = f.read()\n string = string.format(semester,\n stats['faculty_with_usage'],\n stats['full_time'],\n stats['total_full_time'],\n round((stats['full_time'] / stats['total_full_time']) * 100, 1),\n stats['part_time'],\n stats['total_part_time'],\n round((stats['part_time'] / stats['total_part_time']) * 100, 1),\n stats['staff'],\n stats['courses_with_usage'],\n stats['total_courses'],\n round((stats['courses_with_usage'] / stats['total_courses']) * 100, 1),\n stats['specifics']['assignments'],\n stats['specifics']['grade'],\n stats['specifics']['graded'],\n stats['specifics']['discussion'])\n with open(filename, 'w') as f:\n f.write(string)\n pdf = weasyprint.HTML(filename).write_pdf()\n open(\"report_\" + str(date.today()) + \".pdf\", 'wb').write(pdf)","def response_pdf(self, filename):\n now = DateTime()\n nice_filename = '%s_%s' % (filename, now.strftime('%Y%m%d'))\n self.request.response.setHeader(\"Content-Type\", \"application/pdf\")\n self.request.response.setHeader(\"Content-Disposition\", \"attachment\")\n self.request.response.setHeader(\"filename\", nice_filename)\n self.request.response.setHeader('Last-Modified',\n DateTime.rfc822(DateTime()))\n self.request.response.setHeader(\"Cache-Control\", \"no-store\")\n self.request.response.setHeader(\"Pragma\", \"no-cache\")\n return open(filename, 'rb').read()","def get_text(self):\r\n if os.path.isfile(self.destination):\r\n pdf = self.read_from_text()\r\n else:\r\n pdf = self.convert_to_text\r\n self.save_text_to_file(pdf)\r\n return pdf","def generate_page_pdf(self, src, out, options=None):\n loger.info(\"start pdf creation\")\n with open(src, 'r') as f:\n print(pdfkit.from_file(f, out, options=self.__soft_cover_options if not options else\n \"Lol\"))\n loger.info(\"end pdf creation\")","def __call__(self, method):\n\n that = self\n \n @functools.wraps(method)\n def wrapper(self, *args, **kwargs):\n html = method(self, *args, **kwargs)\n\n out = cStringIO.StringIO()\n pdf = weasyprint.HTML(string = html).write_pdf(target = out)\n\n response = self.app.response_class()\n response.content_type = \"application/pdf\"\n #response.content_disposition = \"attachment; filename=\\\"...\\\"\"\n response.data = out.getvalue()\n return response\n \n return wrapper","def generate_pdf (tmp_folder, filename, pdf_page_size):\n\n shell_cmd = PDF_CONVERT_CMD.substitute(wkhtmltox_path=WKHTMLTOX_PATH, folder=tmp_folder, article_id=filename, page_size=pdf_page_size)\n proc = subprocess.Popen(shell_cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n stdout_value, stderr_value = proc.communicate()\n\n print u'\\n'.join(filter(None, [shell_cmd, stdout_value, stderr_value]))","def convert_to_text(self) -> str:\r\n import pdftotext\r\n with open(self.pdf_path, \"rb\") as f:\r\n pdf = pdftotext.PDF(f)\r\n pdf = \"\\n\\n\".join(pdf)\r\n return pdf","def _repr_html_(self) -> str:\n # Speical case inside Google Colab\n if \"google.colab\" in sys.modules:\n load_notebook(hide_banner=True)\n script, div, _ = notebook_content(self.to_render)\n return f\"{div}<script>{script}</script>\"\n\n # Windows forbids us open the file twice as the result bokeh cannot\n # write to the opened temporary file.\n with NamedTemporaryFile(suffix=\".html\", delete=False) as tmpf:\n pass\n\n save(\n self.to_render,\n filename=tmpf.name,\n resources=CDN,\n template=INLINE_TEMPLATE,\n title=\"DataPrep.EDA Report\",\n )\n with open(tmpf.name, \"r\") as f:\n output_html = f.read()\n\n # Delete the temporary file\n Path(tmpf.name).unlink()\n\n # Fix the bokeh: bokeh wrongly call the \"waiting for bokeh to load\" function\n # inside \"Bokeh.safely\", which causes Bokeh not found because\n # Bokeh is even not loaded!\n patched_html = output_html.replace(\n \"Bokeh.safely\",\n \"var __dataprep_bokeh_fix = (f) => document.Bokeh === undefined ? setTimeout(f, 1000) : f(); __dataprep_bokeh_fix\", # pylint: disable=line-too-long\n )\n # embed into report template created by us here\n return patched_html","def build_pdf_preview(self, file_path, cache_path, extension='.pdf'):\n\n # try:\n # os.mkdir(cache_path.format(d_id=document_id))\n # except OSError:\n # pass\n\n with open(file_path, 'rb') as odt:\n\n file_name = self.get_file_hash(file_path)\n\n if os.path.exists('{path}.pdf'.format(\n path=cache_path + file_name,\n )):\n result = open('{path}.pdf'.format(\n path=cache_path + file_name,\n ), 'rb')\n\n else:\n if os.path.exists(cache_path + file_name + '_flag'):\n time.sleep(2)\n self.build_pdf_preview(file_path, cache_path, extension)\n else:\n result = file_converter.office_to_pdf(odt, cache_path, file_name)\n\n with open(cache_path + file_name + extension, 'wb') as pdf:\n buffer = result.read(1024)\n while buffer:\n pdf.write(buffer)\n buffer = result.read(1024)","def convert_to_pdf(self, news_list):\n self.logger.info(\"Converting news to PDF...\")\n self.prepare_storage()\n self.process_news_list_with_images(news_list)\n content = self.generate_html_template(news_list)\n pdf = io.BytesIO()\n pisa.pisaDocument(content, pdf)\n self.write_to_file(pdf.getvalue())","def html_to_pdf(source_path: str, output_filename: str, delete_html=True):\n # open output file for writing (truncated binary)\n assert exists(source_path), \"The input file MUST exists!\"\n from_file(source_path, output_filename)\n if delete_html:\n remove(source_path)\n # return False on success and True on errors","def create_pdf(f,s1,s2='',s3=''):\n # does not need reportlab!\n if s1 == 'White Ballot': s1 = '\"'+'_'*10+'\"'\n cod = zlib.compress('BT /F1 16 Tf ET\\r\\nBT 300 270 Td (%s) Tj ET\\r\\nBT /F1 48 Tf ET\\r\\nBT 5 180 Td (%16s) Tj ET\\r\\nBT /F1 12 Tf ET\\r\\nBT 10 50 Td (%s) Tj ET'%(s3,s1,s2))\n open(f,'w').write(create_pdf.__doc__ + '/Length %d>>\\nstream\\n'%len(cod) + cod + 'endstream endobj\\ntrailer<</Root 4 0 R>>')","def convert_file_to_pdf(fileobj, outfilename=None,\n cmd_args=settings.WKHTML_DEFAULT_ARGS):\n log.debug(\"fileobj=%s\" % fileobj)\n log.debug(\"wkhtml args=%s\" % cmd_args)\n log.debug(\"outfile=%s\" % outfilename)\n if not outfilename:\n outfile, outfilename = tempfile.mkstemp(suffix='.pdf')\n log.debug(\"temp_pdf_file=%s\" % outfilename)\n os.close(outfile)\n else:\n outdirname = os.path.dirname(outfilename)\n log.debug(\"out_dir=%s\" % outdirname)\n if not os.path.exists(outdirname):\n os.makedirs(outdirname)\n tempfileobj, tempfilename = tempfile.mkstemp(suffix='.html')\n log.debug(\"temp_html_file=%s\" % tempfilename)\n tempfileobj = os.fdopen(tempfileobj, 'wb')\n log.debug(\"copying temp html\")\n shutil.copyfileobj(fileobj, tempfileobj)\n tempfileobj.close()\n cmd_args = cmd_args or []\n cmdline = [settings.WKHTML_PATH] + cmd_args + [tempfilename, outfilename]\n process = subprocess.Popen(cmdline,\n stdout=subprocess.PIPE,\n stderr=subprocess.PIPE)\n log.debug(\"running %s (%s)\" % (' '.join(cmdline),process))\n stdout, stderr = process.communicate()\n os.remove(tempfilename)\n if process.returncode > 0:\n raise ConvertError(stderr)\n return outfilename","def toPDF(Infos):\n\n\n #returnPDF = PDFDocument(\"output\")\n #returnPDF.Infos.get(\"name\")\n returnPDF = PDF(\"Courier\", Infos.get(\"name\"))\n if Infos.get('contact'):\n returnPDF.contact(Infos.get(\"contact\"))\n if Infos.get('Current position'):\n returnPDF.currentposition(Infos.get(\"Current position\"))\n if Infos.get('Education'):\n returnPDF.currentposition(Infos.get(\"Education\"))\n if Infos.get('Langue'):\n returnPDF.currentposition(Infos.get(\"Langue\"))\n returnPDF.output(\"result.pdf\", 'F')","def load_pdf(self, env=\"default\", debug=()):\n os.makedirs(\"txt\", exist_ok=True)\n if env is \"default\": # default python path\n call([executable,\n os.path.join(f\"{exec_prefix}\", \"Scripts\", \"pdf2txt.py\"),\n os.path.join(\"pdf\", f\"{self.pdf_filename}\"),\n os.path.join(f\"-otxt\", f\"{self.txt_filename}\")])\n if env is \"venv\": # virtual environment\n call([os.path.join(\"venv\", \"Scripts\", \"python.exe\"),\n os.path.join(\"venv\", \"Scripts\", \"pdf2txt.py\"),\n os.path.join(\"pdf\", f\"{self.pdf_filename}\"),\n os.path.join(f\"-otxt\", f\"{self.txt_filename}\")])\n with open(os.path.join(\"txt\", f\"{self.txt_filename}\"), \"r\", encoding=\"utf-8\") as file:\n self.paragraphs = [paragraph.rstrip('\\n') for paragraph in file]\n os.remove(os.path.join(\"txt\", f\"{self.txt_filename}\"))\n if debug:\n for counter, paragraph in enumerate(self.paragraphs):\n try:\n if int(debug[0]) < counter < int(debug[1]):\n print(counter, paragraph)\n except TypeError:\n print(\"Debug must be a (x,y) touple.\")","def pdf_manager(self):\n\n s3ocr_root = self.s3ocr_etree() # get element s3xml\n\n # define font size\n titlefontsize = 18\n sectionfontsize = 15\n regularfontsize = 13\n hintfontsize = 10\n \n # etree labels\n ITEXT = \"label\"\n HINT = \"comment\"\n TYPE = \"type\"\n HASOPTIONS = \"has_options\"\n LINES = \"lines\"\n BOXES = \"boxes\"\n\n #l10n\n l10n = self.l10n\n\n # get pdf title\n if self.pdftitle == None or self.pdftitle == \"\":\n try:\n pdftitle = self.manager.s3.crud_strings[\\\n self.tablename].subtitle_list.decode(\"utf-8\")\n except:\n pdftitle = self.resource.tablename\n else:\n pdftitle = self.pdftitle\n\n # prepare pdf\n form = Form()\n form.decorate()\n\n # set header\n form.canvas.setTitle(pdftitle) # set pdf meta title\n form.print_text([pdftitle,],\n fontsize=titlefontsize,\n style=\"center\") # set pdf header title\n\n form.print_text(\n [\n unicode(l10n.get(\"ocr_inst\").get(\"inst1\").decode(\"utf-8\")),\n unicode(l10n.get(\"ocr_inst\").get(\"inst2\").decode(\"utf-8\")),\n unicode(l10n.get(\"ocr_inst\").get(\"inst3\").decode(\"utf-8\"))\n ],\n fontsize=regularfontsize,\n gray=0)\n form.linespace(3)\n # printing the etree\n for eachresource in s3ocr_root:\n form.draw_line()\n form.print_text([\n eachresource.attrib.get(ITEXT,\n eachresource.attrib.get(\"name\"))\n ],\n fontsize=sectionfontsize)\n form.draw_line(nextline=1)\n form.linespace(12) # line spacing between each field\n for eachfield in eachresource.iterchildren():\n fieldlabel = eachfield.attrib.get(ITEXT)\n spacing = \" \" * 5\n fieldhint = self.__trim(eachfield.attrib.get(HINT))\n if fieldhint != \"\" and fieldhint != None:\n form.print_text([\"%s%s( %s )\" % \\\n (fieldlabel,\n spacing,\n fieldhint)],\n fontsize=regularfontsize)\n else:\n form.print_text([fieldlabel],\n fontsize=regularfontsize)\n\n if eachfield.attrib.get(\"readable\", \"False\") == \"True\" and \\\n eachfield.attrib.get(\"writable\", \"False\") == \"False\":\n # if it is a readonly field\n form.print_text(\n [eachfield.attrib.get(\"default\",\"No default Value\")],\n seek=10,\n )\n elif eachfield.attrib.get(HASOPTIONS) == \"True\":\n fieldtype = eachfield.attrib.get(TYPE)\n # if the field has to be shown with options\n if fieldtype == \"boolean\":\n form.nextline()\n form.resetx()\n bool_text = l10n.get(\"boolean\")\n form.print_text(\n [bool_text.get(\"yes\").decode(\"utf-8\")],\n continuetext=1,\n seek=3,\n )\n # TODO: Store positions\n form.draw_circle(\n boxes=1,\n continuetext=1,\n gray=0.9,\n seek=10,\n fontsize=12,\n )\n form.print_text(\n [bool_text.get(\"no\").decode(\"utf-8\")],\n continuetext=1,\n seek=10,\n )\n # TODO: Store positions\n form.draw_circle(\n boxes=1,\n continuetext=1,\n gray=0.9,\n seek=10,\n fontsize=12,\n )\n else:\n if fieldtype == \"multiselect\":\n option_hint = l10n.get(\"select\").get(\"multiselect\")\n else:\n option_hint = l10n.get(\"select\").get(\"singleselect\")\n form.print_text(\n [option_hint.decode(\"utf-8\")],\n fontsize=hintfontsize,\n gray=0.4,\n seek=3,\n )\n s3ocrselect = eachfield.getchildren()[0]\n form.nextline(regularfontsize)\n form.resetx() # move cursor to the front\n optionseek = 10\n # resting margin for options\n formmargin = form.marginsides\n form.marginsides = optionseek + formmargin\n for eachoption in s3ocrselect.iterchildren():\n form.print_text(\n [eachoption.text],\n continuetext=1,\n fontsize = regularfontsize,\n seek = 10,\n )\n # TODO: Store positions\n form.draw_circle(\n boxes=1,\n continuetext=1,\n gray=0.9,\n seek=10,\n fontsize=12,\n )\n # restoring orginal margin\n form.marginsides = formmargin\n \n else:\n # if it is a text field\n fieldtype = eachfield.attrib.get(TYPE)\n BOXES_TYPES = [\"string\", \"textbox\", \"integer\",\n \"double\", \"date\", \"datetime\",]\n if fieldtype in BOXES_TYPES:\n if fieldtype in [\"string\", \"textbox\"]:\n form.linespace(3)\n num_lines = int(eachfield.attrib.get(\"lines\",\n 1))\n for eachline in xrange(num_lines):\n # TODO: Store positions\n form.draw_check_boxes(\n completeline=1,\n gray=0.9,\n seek=3,\n )\n elif fieldtype in [\"integer\", \"double\"]:\n num_boxes = int(eachfield.attrib.get(\"boxes\",\n 9))\n form.linespace(3)\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = num_boxes,\n gray=0.9,\n seek=3,\n )\n elif fieldtype in [\"date\", \"datetime\"]:\n # print hint\n hinttext = \\\n l10n.get(\"datetime_hint\").get(fieldtype).decode(\"utf-8\")\n form.print_text(\n [hinttext],\n fontsize=hintfontsize,\n gray=0.4,\n seek=3,\n )\n form.linespace(8)\n datetime_continuetext = 0\n datetime_seek = 3\n if fieldtype == \"datetime\":\n datetime_continuetext = 1\n datetime_seek = 6\n #HH\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = 2,\n gray=0.9,\n seek = 3,\n )\n #MM\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = 2,\n gray=0.9,\n continuetext=1,\n seek = 4,\n )\n # DD\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = 2,\n gray=0.9,\n continuetext = datetime_continuetext,\n seek = datetime_seek,\n )\n # MM\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = 2,\n gray=0.9,\n continuetext=1,\n seek = 4,\n )\n # YYYY\n # TODO: Store positions\n form.draw_check_boxes(\n boxes = 4,\n gray=0.9,\n continuetext=1,\n seek = 4,\n )\n else:\n self.r.error(501, self.manager.PARSE_ERROR)\n print sys.stderr(\"%s :invalid field type: %s\" %\\\n (eachfield.attrib.get(\"name\"),\n fieldtype))\n return form.save()","def scrape (url, pdf_filename, pdf_page_size=PDF_PAGE_SIZE, folder=OUTPUT_FOLDER, clean_it=True):\n\n raw_html = get_url(url)\n if raw_html is None:\n print \"Sorry, could not read \", url\n else:\n filename_prefix, file_ext = os.path.splitext(pdf_filename)\n if clean_it:\n title = Document(raw_html).short_title()\n content = Document(raw_html).summary(html_partial=True)\n frame = HTML_FRAME.substitute(content=to_unicode(content),\n url=url,\n title=title)\n source = write_html_file(folder, os.extsep.join([filename_prefix, 'html']), frame)\n else:\n source = write_html_file(folder, os.extsep.join([filename_prefix, 'html']), raw_html)\n\n if source:\n generate_pdf (folder, filename_prefix, pdf_page_size)","def create_pdf(self):\n\n my_datetime = datetime.now()\n self.pdf_name = (\n self.pdf_name + \"_\" + my_datetime.strftime(\"%H%M_%d%m%Y\") + \".pdf\"\n )\n fig_width = aW * self.column_ratio[0]\n\n clm_width_meta = (aW * self.column_ratio[1]) / len(self.fields)\n\n c = canvas.Canvas(os.path.join(self.pdf_folder, self.pdf_name), pagesize=A4)\n\n for qc_run_id, fig_file in sorted(self._files.items()):\n (param_values, feature_values) = get_param_values(\n qc_run_id, self.db_name, return_meta_add_on=True\n )\n\n comment = self.subject + \"<br/>\"\n # c.saveState()\n title = \"Dataset \" + qc_run_id\n\n # Prepare header\n header = Paragraph(title, title_style)\n h_w, h_h = header.wrap(aW, aH)\n\n # Prepare image\n img = ImageReader(fig_file)\n im_width, im_height = img.getSize()\n aspect = im_height / float(im_width)\n fig_height = fig_width * aspect\n\n # Prepare metadata section\n\n meta_table = Table(\n param_values,\n colWidths=[clm_width_meta] * len(self.fields),\n hAlign=\"CENTER\",\n rowHeights=0.22 * inch,\n )\n meta_table.setStyle(\n TableStyle(\n [\n (\"FONT\", (0, 0), (-1, 0), \"Helvetica-Bold\"),\n (\"FONT\", (0, 1), (-1, -1), \"Helvetica\"),\n (\"LINEBELOW\", (0, 0), (1, 0), 0.08, colors.black),\n (\"SIZE\", (0, 0), (-1, -1), 8),\n (\"VALIGN\", (0, 0), (-1, -1), \"BOTTOM\"),\n # ('ALIGN', (0, 0), (-1, 0), 'CENTER'),\n (\"ALIGN\", (0, 0), (0, -1), \"LEFT\"),\n (\"ALIGN\", (1, 1), (1, -1), \"LEFT\"),\n (\"INNERGRID\", (0, 0), (-1, -1), 0.08, colors.beige),\n # ('BOX', (0,0), (-1,-1), 0.25, colors.grey),\n ]\n )\n )\n\n meta_width, meta_height = meta_table.wrap(aW - im_width, aH / 2)\n\n # Prepare comments header\n comments_header = Paragraph(\"Comments:\", title_style)\n avail_height = aH - fig_height - v_padding\n comm_h_width, comm_h_height = comments_header.wrap(\n im_width, avail_height # aW - meta_width,\n )\n # Prepare comments\n my_datetime = datetime.now()\n ts = \"Printed on \" + my_datetime.strftime(\"%c\")\n\n try:\n data_specific_comment = self.comments[int(qc_run_id)]\n comment += data_specific_comment + \"<br/>\"\n comment += self.comments[\"general\"] + \"<br/>\"\n\n comment += self.smalltalk + \"<br/>\"\n except Exception:\n logger.warning(\n \"Unable to summarize result of \" + \"dataset {}\".format(qc_run_id)\n )\n comment_ts = comment + ts\n comment_ts = textwrap.fill(comment_ts, 70)\n comment_ts = comment_ts.replace(\"\\n\", \"<br/>\")\n\n comments_p = Paragraph(comment_ts, body_style)\n\n avail_height = aH - fig_height - v_padding - comm_h_height\n\n comm_width, comm_height = comments_p.wrap(im_width, avail_height) # aW,\n\n line_widths = comments_p.getActualLineWidths0()\n number_of_lines = len(line_widths)\n if number_of_lines > 1:\n pass\n if number_of_lines == 1:\n min(line_widths)\n comm_width, comm_height = comments_p.wrap(im_width, avail_height)\n\n # Prepare features\n feat_table = Table(\n feature_values,\n colWidths=[clm_width_meta] * len(self.fields),\n hAlign=\"CENTER\",\n rowHeights=0.22 * inch,\n )\n feat_table.setStyle(\n TableStyle(\n [\n (\"FONT\", (0, 0), (-1, 0), \"Helvetica-Bold\"),\n (\"FONT\", (0, 1), (-1, -1), \"Helvetica\"),\n (\"LINEBELOW\", (0, 0), (1, 0), 0.08, colors.black),\n (\"SIZE\", (0, 0), (-1, -1), 8),\n (\"VALIGN\", (0, 0), (-1, -1), \"BOTTOM\"),\n # ('ALIGN', (0, 0), (-1, 0), 'CENTER'),\n (\"ALIGN\", (0, 0), (0, -1), \"LEFT\"),\n (\"ALIGN\", (1, 1), (1, -1), \"LEFT\"),\n (\"INNERGRID\", (0, 0), (-1, -1), 0.08, colors.beige),\n # ('BOX', (0,0), (-1,-1), 0.25, colors.grey),\n ]\n )\n )\n avail_height = aH - meta_height # fig_height - v_padding - comm_h_height\n avail_height -= comm_height\n feat_width, feat_height = feat_table.wrap(aW - im_width, avail_height)\n\n # Draw everyting on canvas\n\n header.drawOn(c, left_margin, aH - top_margin)\n\n c.drawImage(\n img,\n left_margin,\n aH - top_margin - fig_height - v_padding,\n width=fig_width * 1.1,\n height=fig_height * 1.1,\n mask=\"auto\",\n )\n\n meta_table.drawOn(\n c,\n left_margin + fig_width + h_padding,\n aH - meta_height - top_margin / 2, # - v_padding\n )\n\n comments_header.drawOn(\n c,\n left_margin,\n aH\n - top_margin\n - comm_h_height\n - fig_height\n - 2 * v_padding, # - add_on_height\n )\n\n comments_p.drawOn(\n c,\n left_margin,\n aH\n - top_margin\n - comm_h_height\n - comm_height\n - fig_height\n - 2 * v_padding\n - comm_h_height, # - add_on_height\n )\n\n feat_table.drawOn(\n c,\n left_margin + fig_width + h_padding,\n aH - meta_height - top_margin / 2 - feat_height - v_padding,\n # top_margin - fig_height - 2*v_padding - feat_height\n )\n\n # new page\n c.showPage()\n c.saveState()\n\n c.save()","def render(self, context):\n engine = Renderer()\n engine.environment.filters['format_date'] = format_date\n engine.environment.filters['format_datetime'] = format_datetime\n result = engine.render(self.template, **context)\n response = HttpResponse(\n content_type='application/vnd.oasis.opendocument.text; charset=UTF-8'\n )\n response['Content-Disposition'] = 'inline; filename=' + self.filename\n with tempfile.NamedTemporaryFile() as output:\n output.write(result)\n output.flush()\n output = open(output.name, 'rb')\n response.write(output.read())\n return response","def _generate_report(self):\n\n _LOG.info(\"Generating the HTML report.\")\n\n # Make sure the output directory exists.\n try:\n self.outdir.mkdir(parents=True, exist_ok=True)\n except OSError as err:\n raise Error(f\"failed to create directory '{self.outdir}': {err}\")\n\n raw_stats_paths, descr_paths = self._copy_raw_data()\n\n # Find the styles and templates paths.\n templdir = FSHelpers.search_for_app_data(\"wult\", Path(\"templates\"),\n pathdescr=\"HTML report Jinja2 templates\")\n csspath = FSHelpers.search_for_app_data(\"wult\", Path(\"css/style.css\"),\n pathdescr=\"HTML report CSS file\")\n\n # Copy the styles file to the output directory.\n dstpath = self.outdir.joinpath(\"style.css\")\n try:\n shutil.copyfile(csspath, dstpath)\n except OSError as err:\n raise Error(f\"failed to copy CSS file from '{csspath}' to '{dstpath}':\\n{err}\")\n\n # The summary table is only included into the main HTML page.\n sum_tbl = self._prepare_summary_table(raw_stats_paths, descr_paths)\n links_tbl = self._prepare_links_table()\n\n # Each column name gets its own HTML page.\n for colname, pinfos in self._pinfos.items():\n stats_tbl = self._prepare_stats_table(pinfos)\n\n # Render the template.\n jenv = Jinja2.build_jenv(templdir, trim_blocks=True, lstrip_blocks=True)\n jenv.globals[\"stats_tbl\"] = stats_tbl\n jenv.globals[\"pinfos\"] = pinfos\n jenv.globals[\"colname\"] = colname\n jenv.globals[\"title_descr\"] = self.title_descr\n jenv.globals[\"toolname\"] = self._refinfo[\"toolname\"]\n\n if sum_tbl:\n jenv.globals[\"sum_tbl\"] = sum_tbl\n jenv.globals[\"links_tbl\"] = links_tbl\n templfile = outfile = \"index.html\"\n sum_tbl = None\n else:\n templfile = \"metric.html\"\n outfile = links_tbl[colname][\"fname\"]\n\n Jinja2.render_template(jenv, Path(templfile), outfile=self.outdir.joinpath(outfile))","def pdf(self, identifier):\n return self.client.request_with_method(Methods.PDF % (self.name, identifier,))","def get_pdf(self, points=None):\n if points is not None:\n return self.parent.pdf(points)\n else:\n raise ValueError( 'Please digit an input for getPDF method')","def exportTable(self):\n\t\tself.pdf = \tself.dir + \"/application.pdf\"\n\t\tpdf = pisa.CreatePDF(\n\t\t\tfile(self.html, \"r\" ),\n\t\t\tfile(self.pdf, \"wb\")\n\t\t\t)","def getPDF(self):\n return self.pdfSample","def buildHTML(self):\n\n # TODO: make this configurable via a dialog\n os.chdir(self.file_path.parent)\n proc = subprocess.Popen(\n [\"make\", \"clean\"],\n stdin=subprocess.PIPE,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT\n )\n for line in proc.stdout:\n print(\"stdout: \" + str(line.rstrip(), encoding='utf8'))\n print('----------------')\n proc = subprocess.Popen(\n [\"make\", \"html\"],\n stdin=subprocess.PIPE,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT\n )\n proc.wait()\n for line in proc.stdout:\n print(\"stdout: \" + str(line.rstrip(), encoding='utf8'))\n\n # Load corresponding HTML file from newly-built Sphinx docs\n self.preview.load_html(self.output_html_path)","def proof_pdf(self):\n return self._proof_pdf","def create_pdf(request):\n\n contact_info = ContactDetails.objects.iterator()\n\n # Create a file-like buffer to receive PDF data.\n buffer = io.BytesIO()\n\n # Create the PDF object, using the buffer as its \"file.\"\n pdf_file = canvas.Canvas(buffer)\n\n # Draw things on the PDF. Here's where the PDF generation happens\n pdf_file.setTitle(\"Contact Infomation\")\n pdf_file.setFont(\"Helvetica-Bold\", 20, leading=None)\n pdf_file.setFillColorRGB(1,0,0)\n pdf_file.drawString( 60, 800, \"Stefanos Taramas Contact Information\")\n pdf_file.setFillColorRGB(0,0,0)\n pdf_file.setFont(\"Helvetica\", 15, leading=None)\n\n for index, item in enumerate(contact_info):\n line = str(index + 1) +\") \" + str(item.contact_name) + \": \" + str(item.contact_info)\n column = 50\n row = 750 - 15*index\n pdf_file.drawString(column, row, line)\n\n # Close the PDF object cleanly\n pdf_file.showPage()\n pdf_file.save()\n\n # FileResponse sets the Content-Disposition header so that browsers\n # present the option to save the file.\n buffer.seek(0)\n\n return FileResponse(buffer, as_attachment=True, filename='StefanosTaramasContactInfo.pdf')","def generate_pdf(file_path_or_url, data_type, filename):\n file_path = get_pdf_file_path(filename)\n if data_type == TYPE_FILE:\n try:\n HTML(filename=file_path_or_url).write_pdf(file_path)\n finally:\n default_storage.delete(file_path_or_url)\n else:\n HTML(file_path_or_url).write_pdf(file_path)\n return filename","def render_latex(self, latex_snippet, output_png_file, output_pdf_file):\n\t\ttmp_dir = tempfile.mkdtemp(prefix = \"mdx_latex_\")\n\t\ttex_file = os.path.join(tmp_dir, \"file.tex\")\n\t\tpdf_file = os.path.join(tmp_dir, \"file.pdf\")\n\t\t\n\t\ttry:\n\t\t\t# Generate the tex file\n\t\t\ttex = LaTeXBlockProcessor.LATEX_TEMPLATE.render(\n\t\t\t\tpreamble = self.preamble,\n\t\t\t\tdocument = latex_snippet,\n\t\t\t)\n\t\t\ttex_hash = hashlib.sha1(tex).hexdigest()\n\t\t\t\n\t\t\t# Check if anything needs to be done\n\t\t\ttry:\n\t\t\t\tpng_meta = self.get_png_metadata(output_png_file)\n\t\t\t\tif tex_hash == png_meta.get(\"tex_hash\", None):\n\t\t\t\t\t# Already got the latest version in the PNG, do nothing!\n\t\t\t\t\treturn\n\t\t\texcept IOError:\n\t\t\t\t# No file exists yet so we definately should build it\n\t\t\t\tpass\n\t\t\t\n\t\t\t\n\t\t\t# Store the tex in a file to be compiled\n\t\t\twith open(tex_file, \"w\") as f:\n\t\t\t\tf.write(tex)\n\t\t\t\n\t\t\t# Try and build the file\n\t\t\tfor build_num in range(LaTeXBlockProcessor.LATEX_BUILDS):\n\t\t\t\tp = Popen( [ \"pdflatex\"\n\t\t\t\t , \"-shell-escape\"\n\t\t\t\t , \"-halt-on-error\"\n\t\t\t\t , \"-output-directory\", tmp_dir\n\t\t\t\t , tex_file]\n\t\t\t\t , cwd = os.path.realpath(self.configs.get(\"input_path\", \"./\"))\n\t\t\t\t , stdin = None\n\t\t\t\t , stdout = sys.stderr\n\t\t\t\t , stderr = sys.stderr\n\t\t\t\t )\n\t\t\t\tif p.wait() != 0:\n\t\t\t\t\traise Exception(\"LaTeX Compilation Failed for:\\n%s\"%latex_snippet)\n\t\t\t\n\t\t\t# Make a copy of required\n\t\t\tif output_pdf_file is not None:\n\t\t\t\tshutil.copy(pdf_file, output_pdf_file)\n\t\t\t\n\t\t\t# Convert to PNG\n\t\t\tp = Popen( [\"convert\", \"-density\", \"440\", pdf_file, \"-resize\", \"25%\", output_png_file]\n\t\t\t , stdin = None\n\t\t\t , stdout = sys.stderr\n\t\t\t , stderr = sys.stderr\n\t\t\t )\n\t\t\tif p.wait() != 0:\n\t\t\t\traise Exception(\"Converting PDF to PNG failed for:\\n%s\"%latex_snippet)\n\t\t\t\n\t\t\t# Add the hash of the source to the metadata \n\t\t\tself.set_png_metadata(output_png_file, {\"tex_hash\":tex_hash})\n\t\t\t\n\t\tfinally:\n\t\t\tshutil.rmtree(tmp_dir)","def test_generate_pdf(self):\n with mock.patch.object(form_api.Client, 'wait') as wait_patched:\n template_id = 'tpl_000000000000000001' # str |\n\n response = self.client.generate_pdf(\n template_id, {\n 'data': {\n 'title': 'Test PDF',\n 'description': 'This PDF is great!'\n }\n })\n wait_patched.assert_called()\n self.assertEquals(response.status, 'success')\n submission = response.submission\n self.assertRegexpMatches(submission.id, '^sub_')\n self.assertEquals(submission.expired, False)\n self.assertEquals(submission.state, 'processed')","def print_report_pdf(self):\n self.ensure_one()\n return self.env.ref('eliterp_sale_reports.action_report_product_catalogue').report_action(self)","def render_html_with_data(self):\n self.logger.info('Builder {} prepares html data for {} file'.format(self.id, self.html_template_file()))\n return self \\\n .template_env.get_template(self.html_template_file()) \\\n .render(self.build_document().prepare_html_dict())","def createPDF(self, tex):\n for b in [TIMEOUT_BINARY, RUBBER_BINARY]:\n if not os.path.isfile(b):\n raise ValueError(\"Binary %s not available\" % b)\n\n self.explodeTeX(tex)\n\n p = subprocess.Popen(\n [\n TIMEOUT_BINARY, TIMEOUT,\n RUBBER_BINARY, '--inplace', '--ps', '-ops2pdf', '-Wall', '--maxerr=100', '--force',\n os.path.join(self.dir, 'exploded.tex'),\n ],\n stdin=subprocess.PIPE,\n stdout=subprocess.PIPE,\n stderr=subprocess.PIPE,\n )\n (processOut, processErr) = p.communicate(\"\")\n exitCode = p.wait()\n if exitCode != 0:\n return processOut + processErr + \"\\nCompilation of document failed!\"\n\n self._outputFile = os.path.join(self.dir, 'exploded.pdf')\n return processOut + processErr","def pdfReceiver(request, model=''):\n\n\tinput_str = ''\n\tinput_str += parsePOST(request)\n\t# packet = io.StringIO() # write to memory\n\tpacket = io.BytesIO()\n\n\ttry:\n\t\tpisa.CreatePDF(input_str, dest=packet)\n\texcept ValueError as error:\n\t\t# triggered from the elusive invalid color value issue:\n\t\tlogging.warning(\"elusive invalid color value, defaulting html background-color to FFFFFF\")\n\t\tpisa.CreatePDF(input_str, dest=packet, default_css=\"body{background-color:#FFFFFF;}\")\n\n\n\tjid = MetabolizerCalc().gen_jid() # create timestamp\n\tresponse = HttpResponse(packet.getvalue(), content_type='application/pdf')\n\tresponse['Content-Disposition'] = 'attachment; filename=' + model + '_' + jid + '.pdf'\n\tpacket.close() # todo: figure out why this doesn't solve the 'caching problem'\n\treturn response","def _render_as(self, extra_context={}, RESPONSE=None):\n import urlparse, re\n \n request = getattr(self, 'REQUEST', None)\n \n method = None\n if (extra_context.has_key('options') and\n extra_context['options'].has_key('method')):\n method = extra_context['options']['method']\n elif request.has_key('method'):\n method = request['method']\n \n if method not in self.render_methods:\n method = self.default_render_method\n \n transform_id = getattr(self, 'transform_%s' % method, '')\n transform_id = re.sub('\\s\\([^\\(]*?\\)$', '', transform_id)\n \n content_type = self.content_type_map.get(method, 'text/plain')\n\n # note we make sure we don't have a unicode object at the later steps,\n # because that causes all sorts of headaches with the XML parser later\n xml_rendered = self.pt_render(extra_context=extra_context).encode(self.char_encoding)\n \n if not transform_id or transform_id == self.unselected_transform:\n rendered = xml_rendered\n else:\n transform = getattr(self, transform_id, None)\n if not transform or transform.meta_type != 'XSLT Template':\n for obj in self._get_path_objs(self.transform_paths):\n transform = getattr(obj, transform_id, None)\n if transform and transform.meta_type == 'XSLT Template':\n break\n if not transform:\n raise TransformError, ('Transform %s did not exist' % \n transform_id)\n self.prune_cache()\n cached = self.retrieve_cache(transform, xml_rendered)\n if cached:\n rendered = cached\n else:\n rendered = transform.render_xml(xml_rendered, content_type)\n self.update_cache(transform, xml_rendered, rendered, 0)\n \n \n # set the base properly\n pathparts = list(urlparse.urlparse(self.absolute_url()))\n base = os.path.split(pathparts[2])[0]\n pathparts[2] = base\n base = urlparse.urlunparse(pathparts)\n \n RESPONSE.setBase(base)\n RESPONSE.setHeader('Content-Type', '%s; charset=%s' % (content_type,\n self.char_encoding))\n \n return rendered","def return_pdf(\n file_name: str,\n settings: config.Settings = Depends(get_settings),\n db: Session = Depends(get_db),\n token: str = Depends(oauth2_scheme),\n):\n logged_user = get_current_user(db, token)\n\n if not logged_user:\n raise HTTPException(403)\n\n if not (logged_user.is_staff or logged_user.is_superuser):\n results = read_results(db, cpf=logged_user.cpf, PDF_Filename=file_name)\n if not results:\n raise HTTPException(404)\n\n result_path = Path(settings.pdf_storage_path).joinpath(file_name)\n\n return FileResponse(str(result_path.absolute()), media_type=\"application/pdf\")","def get_html_report(self) -> str:\n template_contents = dict(\n vendor_bundle_js=self.vendor_bundle,\n app_bundle_js=self.app_bundle,\n # results\n results=self.results,\n # account metadata\n account_id=self.account_id,\n account_name=self.account_name,\n report_generated_time=str(self.report_generated_time),\n cloudsplaining_version=__version__,\n )\n template_path = os.path.dirname(__file__)\n env = Environment(loader=FileSystemLoader(template_path)) # nosec\n template = env.get_template(\"template.html\")\n return template.render(t=template_contents)","def render_pdf(\n self, input_file: str, render_target_dpi: int, page_number: int = 1\n ) -> Image:\n doc = pdfium.FPDF_LoadDocument(str(input_file), None)\n\n page = pdfium.FPDF_LoadPage(doc, page_number - 1)\n\n # Page dimensions are measured in points. One point is 1/72 inch (around 0.3528 mm).\n width = int(pdfium.FPDF_GetPageWidthF(page) + 0.5)\n height = int(pdfium.FPDF_GetPageHeightF(page) + 0.5)\n\n # Converting to page\n render_width = int(width / 72 * render_target_dpi)\n render_height = int(height / 72 * render_target_dpi)\n\n # render to bitmap\n bitmap = pdfium.FPDFBitmap_Create(render_width, render_height, 0)\n pdfium.FPDFBitmap_FillRect(\n bitmap, 0, 0, render_width, render_height, 0xFFFFFFFF\n )\n pdfium.FPDF_RenderPageBitmap(\n bitmap,\n page,\n 0,\n 0,\n render_width,\n render_height,\n 0,\n pdfium.FPDF_LCD_TEXT | pdfium.FPDF_ANNOT,\n )\n\n # retrieve data from bitmap\n buffer = pdfium.FPDFBitmap_GetBuffer(bitmap)\n buffer_ = ctypes.cast(\n buffer, ctypes.POINTER(ctypes.c_ubyte * (render_width * render_height * 4))\n )\n\n img = Image.frombuffer(\n \"RGBA\", (render_width, render_height), buffer_.contents, \"raw\", \"BGRA\", 0, 1\n )\n\n if bitmap is not None:\n pdfium.FPDFBitmap_Destroy(bitmap)\n pdfium.FPDF_ClosePage(page)\n\n pdfium.FPDF_CloseDocument(doc)\n\n return img","def create_report(self, output_filename=None, output_format='html', offline_js=False):\n\n # extra code to put in the <head> part of HTML\n extra_head_code = ''\n\n if output_format == 'html':\n\n # embed plotly.js in HTML (makes it bigger, but then doesn't require web connection)\n if offline_js:\n embed_chart = 'offline_embed_js_div'\n else:\n # otherwise put web link to plotly.js (but this means we need to download every time)\n embed_chart = 'offline_div'\n extra_head_code = '<head><script src=\"https://cdn.plot.ly/plotly-latest.min.js\"></script></head>'\n elif output_format == 'pdf':\n # for PDFs we need to create static PNGs of plotly charts\n embed_chart = 'offline_image_png_in_html'\n\n # get a list of the HTML to render\n elements_to_render = self._layout_computation_results_to_html(embed_chart)\n canvas = Canvas(elements_to_render=elements_to_render)\n\n # should we return a binary string containing the HTML/PDF (this can be displayed by a web server for example)\n # or later be written to disk\n return_binary = False\n\n # return a binary string, if we haven't specified a filename output\n if output_filename is None:\n return_binary = True\n\n # generate the HTML or PDF with chartpy's Canvas object\n if output_format == 'html':\n\n html, _ = canvas.generate_canvas(output_filename=output_filename, silent_display=True,\n canvas_plotter=self._canvas_plotter, page_title=self._title, render_pdf=False,\n return_html_binary=return_binary, extra_head_code=extra_head_code)\n\n return html\n elif output_format == 'pdf':\n _, pdf = canvas.generate_canvas(output_filename=output_filename, silent_display=True,\n canvas_plotter=self._canvas_plotter, page_title=self._title, render_pdf=True,\n return_pdf_binary=return_binary, extra_head_code=extra_head_code)\n\n return pdf\n else:\n raise Exception(\"Invalid output format selected\")","def save_news_in_pdf_file(news, path_to_pdf, logger, html_args=None):\n html_file = save_news_in_html_file(news, path_to_pdf, logger)\n path = os.path.join(path_to_pdf, 'rss_news.pdf')\n try:\n with open(path, 'wb') as pdf_file, open(html_file.name, 'r', encoding='utf-8') as html_file:\n logger.info('Creating pdf-file...')\n pisa.CreatePDF(src=html_file, dest=pdf_file)\n logger.info(\"Pdf-file is created successfully!\")\n if html_args is None:\n html_file.close()\n os.remove(html_file.name)\n logger.info(\"Temporary html-file was deleted\")\n return pdf_file\n except FileNotFoundError:\n raise SystemExit('Please, check the existing of file')","def process_pdf(path):\r\n str = \"\"\r\n try:\r\n pages = layout_scanner.get_pages(path) \r\n i = 0\r\n l = len(pages)\r\n while i < l: \r\n str += pages[i]\r\n i += 1\r\n except Exception, e:\r\n return g_error_template % e, \"\" \r\n \r\n return \"\", str","def create_web_bundle(filename, issue, **kwargs):\n pages = get_staging_pdf_files(**kwargs)\n if not pages:\n raise RuntimeWarning('No pages found')\n if len(pages) % 4 != 0:\n raise RuntimeError(f'Wrong number of pages {len(pages)}')\n\n optimized_pages = [convert_pdf_to_web(pdf) for pdf in pages]\n PS_DATEFORMAT = 'D: %Y%m%d%H%M%S' # used in pdf metadata\n output_file = Path(filename)\n pdfmark = output_file.parent / 'pdfmark' # pdf meta data\n pdfmark.write_text((\n f'[/Title (Universitas {issue.issue_name})'\n f'/CreationDate ({issue.publication_date:{PS_DATEFORMAT}})'\n f'/ModDate ({timezone.now():{PS_DATEFORMAT}})'\n '/Creator (Universitas)'\n '/Subject (Nyheter)'\n '/DOCINFO pdfmark'\n '['\n '/PageMode'\n '/UseThumbs' # do not show thumbs\n '/Page 1'\n '/View [/Fit]' # fit full page\n '/PageLayout'\n '/TwoColumnRight' # two column layout\n '/PageLabels'\n '<< /Nums [0 << /S /D /St 1 >>] >>' # fix page numbers\n '/DOCVIEW pdfmark'\n ))\n output_file.touch()\n args = [\n GHOSTSCRIPT,\n '-q',\n '-o',\n output_file,\n '-dBATCH',\n '-dNOPAUSE',\n '-dAutoRotatePages=/None',\n '-sDEVICE=pdfwrite',\n '-dCompressFonts=true',\n '-dSubsetFonts=true',\n '-dCompatibilityLevel=1.6',\n '-dDetectDuplicateImages=true',\n '-sDEVICE=pdfwrite',\n *optimized_pages,\n pdfmark,\n ]\n subprocess.run(map(str, args))\n pdfmark.unlink()\n return output_file","def html():\n env.file_ext = \".html\"\n local(\"pandoc {input_files} -o {output_file}{file_ext} --standalone --bibliography={bib_file} --csl={csl_file} --toc --number-sections\".format(**env))","def build(self, buffer=None) -> any:\n\n # init PDF\n if buffer:\n self.PDF = canvas.Canvas(buffer, pagesize=letter, bottomup=0)\n else:\n self.PDF = canvas.Canvas(self.buffer, pagesize=letter, bottomup=0)\n\n # run funcs\n\n self.add_title()\n self.draw_image()\n self.add_org_details()\n self.add_customer_details()\n self.draw_line(225)\n self.add_due_date()\n self.add_subscription()\n\n # save the pdf\n\n self.PDF.save()\n return self.PDF","def process(self, doc, is_):\n implementation = Implementation(self)\n implementation.process(doc, is_)\n return implementation.html","def __call__(self, method):\n\n that = self\n \n @functools.wraps(method)\n def wrapper(self, *args, **kwargs):\n html = method(self, *args, **kwargs)\n pdf = pisa.CreatePDF(html)\n\n response = self.app.response_class()\n response.content_type = \"application/pdf\"\n #response.content_disposition = \"attachment; filename=\\\"...\\\"\"\n response.data = pdf.dest.getvalue()\n return response\n \n return wrapper","def to_pdf(\n self,\n url: str,\n output: Union[None, str, Path] = None,\n ) -> Path:\n return asyncio.get_event_loop().run_until_complete(\n asyncio.wait_for(self._run(url, output), self.timeout) if self.timeout >= 0.01 else\n self._run(url, output)\n )","def should_see_pdf(self):\n return self.organization.has_a_pdf()","async def to_pdf(\n self,\n url: str,\n output: Union[None, str, Path] = None,\n ) -> Path:\n return await (asyncio.wait_for(self._run(url, output), self.timeout)\n if self.timeout >= 0.01 else self._run(url, output)\n )","def generate_pdf_report(release, spec, report_week):\n\n logging.info(u\" Generating the pdf report, give me a few minutes, please \"\n u\"...\")\n\n working_dir = spec.environment[u\"paths\"][u\"DIR[WORKING,SRC]\"]\n\n execute_command(f\"cd {working_dir} && mv -f index.pdf.template index.rst\")\n\n _convert_all_svg_to_pdf(spec.environment[u\"paths\"][u\"DIR[WORKING,SRC]\"])\n\n # Convert PyPLOT graphs in HTML format to PDF.\n convert_plots = u\"xvfb-run -a wkhtmltopdf {html} {pdf}\"\n plots = get_files(spec.environment[u\"paths\"][u\"DIR[STATIC,VPP]\"], u\"html\")\n plots.extend(\n get_files(spec.environment[u\"paths\"][u\"DIR[STATIC,DPDK]\"], u\"html\")\n )\n for plot in plots:\n file_name = f\"{plot.rsplit(u'.', 1)[0]}.pdf\"\n logging.info(f\"Converting {plot} to {file_name}\")\n execute_command(convert_plots.format(html=plot, pdf=file_name))\n\n # Generate the LaTeX documentation\n build_dir = spec.environment[u\"paths\"][u\"DIR[BUILD,LATEX]\"]\n cmd = PDF_BUILDER.format(\n release=release,\n date=datetime.datetime.utcnow().strftime(u'%Y-%m-%d %H:%M UTC'),\n working_dir=working_dir,\n build_dir=build_dir)\n execute_command(cmd)\n\n # Build pdf documentation\n archive_dir = spec.environment[u\"paths\"][u\"DIR[STATIC,ARCH]\"]\n cmds = [\n f'cd {build_dir} && '\n f'pdflatex -shell-escape -interaction nonstopmode csit.tex || true',\n f'cd {build_dir} && '\n f'pdflatex -interaction nonstopmode csit.tex || true',\n f'cd {build_dir} && '\n f'cp csit.pdf ../{archive_dir}/csit_{release}.{report_week}.pdf &&'\n f'cp csit.pdf ../{archive_dir}/csit_{release}.pdf'\n ]\n\n for cmd in cmds:\n execute_command(cmd)\n\n logging.info(u\" Done.\")","def gen_html_report(self, html_report_name=None, html_report_template=None):\n return render_html_report(\n self.summary,\n html_report_name,\n html_report_template\n )","def review_pdf_updated_eventhandler(obj, evt):\n if not obj.REQUEST.get(\"pdf_file\"):\n obj.update_generated_pdf()\n\n # Terrible hack, if this method gets called without a real\n # object, we assume that the caller wants htis to happen now\n interfaces.IReviewPDF(obj).generatePageImages(later=evt != None)","def print(self, request, items_to_print):\n if len(items_to_print) == 0:\n # No valid items provided, return an error message\n data = {\n 'error': _('No valid objects provided to template'),\n }\n\n return Response(data, status=400)\n\n outputs = []\n\n # In debug mode, generate single HTML output, rather than PDF\n debug_mode = common.models.InvenTreeSetting.get_setting('REPORT_DEBUG_MODE', cache=False)\n\n # Start with a default report name\n report_name = \"report.pdf\"\n\n try:\n # Merge one or more PDF files into a single download\n for item in items_to_print:\n report = self.get_object()\n report.object_to_print = item\n\n report_name = report.generate_filename(request)\n output = report.render(request)\n\n # Run report callback for each generated report\n self.report_callback(item, output, request)\n\n try:\n if debug_mode:\n outputs.append(report.render_as_string(request))\n else:\n outputs.append(output)\n except TemplateDoesNotExist as e:\n template = str(e)\n if not template:\n template = report.template\n\n return Response(\n {\n 'error': _(f\"Template file '{template}' is missing or does not exist\"),\n },\n status=400,\n )\n\n if not report_name.endswith('.pdf'):\n report_name += '.pdf'\n\n if debug_mode:\n \"\"\"Contatenate all rendered templates into a single HTML string, and return the string as a HTML response.\"\"\"\n\n html = \"\\n\".join(outputs)\n\n return HttpResponse(html)\n else:\n \"\"\"Concatenate all rendered pages into a single PDF object, and return the resulting document!\"\"\"\n\n pages = []\n\n try:\n for output in outputs:\n doc = output.get_document()\n for page in doc.pages:\n pages.append(page)\n\n pdf = outputs[0].get_document().copy(pages).write_pdf()\n\n except TemplateDoesNotExist as e:\n\n template = str(e)\n\n if not template:\n template = report.template\n\n return Response(\n {\n 'error': _(f\"Template file '{template}' is missing or does not exist\"),\n },\n status=400,\n )\n\n inline = common.models.InvenTreeUserSetting.get_setting('REPORT_INLINE', user=request.user, cache=False)\n\n return InvenTree.helpers.DownloadFile(\n pdf,\n report_name,\n content_type='application/pdf',\n inline=inline,\n )\n\n except Exception as exc:\n # Log the exception to the database\n log_error(request.path)\n\n # Re-throw the exception to the client as a DRF exception\n raise ValidationError({\n 'error': 'Report printing failed',\n 'detail': str(exc),\n 'path': request.path,\n })","def to_pdf(self, imageFileName, outFileName, fontname=\"Times-Roman\", fontsize=10, withVisibleOCRText=False, withVisibleImage=True, withVisibleBoundingBoxes=False):\n if self.hocr is None:\n # warn that no text will be embedded in the output PDF\n print \"Warning: No hOCR file specified. PDF will be image-only.\"\n \n im = Image.open(imageFileName)\n imwidthpx, imheightpx = im.size\n if 'dpi' in im.info:\n width = float(im.size[0])/im.info['dpi'][0]\n height = float(im.size[1])/im.info['dpi'][1]\n else:\n # we have to make a reasonable guess\n # set to None for now and try again using info from hOCR file\n width = height = None\n \n \n ocr_dpi = (300, 300) # a default, in case we can't find it\n \n # get dimensions of the OCR, which may not match the image\n if self.hocr is not None:\n for div in self.hocr.findall(\".//%sdiv\"%(self.xmlns)):\n if div.attrib['class'] == 'ocr_page':\n coords = self.element_coordinates(div)\n ocrwidth = coords[2]-coords[0]\n ocrheight = coords[3]-coords[1]\n if width is None:\n # no dpi info with the image\n # assume OCR was done at 300 dpi\n width = ocrwidth/300\n height = ocrheight/300\n ocr_dpi = (ocrwidth/width, ocrheight/height)\n break # there shouldn't be more than one, and if there is, we don't want it\n \n if width is None:\n # no dpi info with the image, and no help from the hOCR file either\n # this will probably end up looking awful, so issue a warning\n print \"Warning: DPI unavailable for image %s. Assuming 96 DPI.\"%(imageFileName)\n width = float(im.size[0])/96\n height = float(im.size[1])/96\n \n # create the PDF file\n pdf = Canvas(outFileName, pagesize=(width*inch, height*inch), pageCompression=1) # page size in points (1/72 in.)\n \n # put the image on the page, scaled to fill the page\n if withVisibleImage:\n pdf.drawInlineImage(im, 0, 0, width=width*inch, height=height*inch)\n \n if self.hocr is not None:\n for word in self.hocr.findall(\".//%sspan\"%(self.xmlns)):\n if word.attrib['class'] == 'ocr_word':\n coords = self.element_coordinates(word)\n content = self._get_element_text(word)\n if content.rstrip() == '':\n continue\n text = pdf.beginText()\n text.setFont(fontname, fontsize)\n if not withVisibleOCRText:\n #text.setTextRenderMode(0) # visible\n #else:\n text.setTextRenderMode(3) # invisible\n \n # set cursor to bottom left corner of line bbox (adjust for dpi)\n # Can't determine original text's baseline, but guess that ypg\n # roughly push it down by ~2/3 of line height. Correct for that.\n # PDF y coords increase going *up* the page, remember. Assume \"o\" is\n # round so width == line height.\n origin_y = (height*inch)-(float(coords[3])/ocr_dpi[1])*inch\n if re.search(r\"[gjpqy()]\", content):\n origin_y += pdf.stringWidth(\"o\") * 1/3\n if re.search(r\"[\\[\\]()]\", content):\n origin_y += pdf.stringWidth(\"o\") * 1/3.5\n elif re.search(r\"[,;]\", content):\n origin_y += pdf.stringWidth(\"o\") * 1/4\n text.setTextOrigin((float(coords[0])/ocr_dpi[0])*inch, origin_y)\n \n # scale the width of the text to fill the width of the line's bbox\n text.setHorizScale((((float(coords[2])/ocr_dpi[0]*inch)-(float(coords[0])/ocr_dpi[0]*inch))/pdf.stringWidth(content.rstrip(), fontname, fontsize))*100)\n \n # write the text to the page\n text.textLine(content.rstrip())\n pdf.drawText(text)\n \n # finish up the page and save it\n pdf.showPage()\n pdf.save()","def publish_pdf(\n self,\n filename: str | io.BytesIO,\n notes: str = None,\n open_file: bool = False,\n metadata: dict = None,\n bins: int = 10,\n logo: Path | str | None = None,\n ) -> None:\n plt.ioff()\n canvas = pdf.PylinacCanvas(\n filename, page_title=\"Picket Fence Analysis\", metadata=metadata, logo=logo\n )\n data = io.BytesIO()\n self.save_analyzed_image(data, leaf_error_subplot=True)\n canvas.add_image(data, location=(3, 5), dimensions=(15, 15))\n canvas.add_text(\n text=self.results(as_list=True), location=(1.5, 22), font_size=14\n )\n if notes is not None:\n canvas.add_text(text=\"Notes:\", location=(1, 5.5), font_size=14)\n canvas.add_text(text=notes, location=(1, 5))\n\n canvas.add_new_page()\n hist = io.BytesIO()\n self.save_histogram(hist, bins)\n canvas.add_image(hist, location=(3, 8), dimensions=(15, 15))\n canvas.finish()\n\n if open_file:\n webbrowser.open(filename)","def print_report_pdf(self):\n self.ensure_one()\n return self.env.ref('eliterp_sale_reports.action_report_product_sold').report_action(self)","def render(self):\n try:\n if self.permit():\n return self.renderer.render(self)\n except AttributeError:\n if self.renderer is None:\n raise NotImplementedError(\"Should have implemented a renderer for {0}\".format(self.name))\n else:\n raise\n return ''","def get_pdf(self, analysis_request):\n return self.get_last_attachment_pdf(analysis_request, \"Requisition\")","def get_search_pdf(self):\n current_app.logger.debug('Account {0} report type {1} setting up report data.'\n .format(self._account_id, self._report_key))\n data_copy = copy.deepcopy(self._report_data)\n # 1: Generate the search pdf with no TOC page numbers or total page count.\n data = self._setup_report_data()\n url = current_app.config.get('REPORT_SVC_URL') + SINGLE_URI\n current_app.logger.debug('Account {0} report type {1} calling report-api {2}.'\n .format(self._account_id, self._report_key, url))\n meta_data = report_utils.get_report_meta_data(self._report_key)\n files = report_utils.get_report_files(data, self._report_key)\n headers = Report.get_headers()\n response_reg = requests.post(url=url, headers=headers, data=meta_data, files=files)\n current_app.logger.debug('Account {0} report type {1} response status: {2}.'\n .format(self._account_id, self._report_key, response_reg.status_code))\n if response_reg.status_code != HTTPStatus.OK:\n content = ResourceErrorCodes.REPORT_ERR + ': ' + response_reg.content.decode('ascii')\n current_app.logger.error('Account {0} response status: {1} error: {2}.'\n .format(self._account_id, response_reg.status_code, content))\n return jsonify(message=content), response_reg.status_code, None\n # 2: Set TOC page numbers in report data from initial search pdf page numbering.\n self._report_data = report_utils.update_toc_page_numbers(data_copy, response_reg.content)\n # 3: Generate search report again with TOC page numbers and total page count.\n data_final = self._setup_report_data()\n current_app.logger.debug('Account {0} report type {1} calling report-api {2}.'\n .format(self._account_id, self._report_key, url))\n files = report_utils.get_report_files(data_final, self._report_key)\n current_app.logger.info('Search report regenerating with TOC page numbers set.')\n response = requests.post(url=url, headers=headers, data=meta_data, files=files)\n current_app.logger.info('Search report regeneration with TOC page numbers completed.')\n if response.status_code != HTTPStatus.OK:\n content = ResourceErrorCodes.REPORT_ERR + ': ' + response.content.decode('ascii')\n current_app.logger.error('Account {0} response status: {1} error: {2}.'\n .format(self._account_id, response.status_code, content))\n return jsonify(message=content), response.status_code, None\n return response.content, response.status_code, {'Content-Type': 'application/pdf'}"],"string":"[\n \"def render_as_pdf(self, width, height):\\n pass\",\n \"def get_raw_pdf(html_path, pdf_path, width='', height=''):\\n debug = False\\n if mg.EXPORT_IMAGES_DIAGNOSTIC: debug = True\\n try:\\n url = html_path.as_uri()\\n cmd_make_pdf = 'cmd_make_pdf not successfully generated yet'\\n \\\"\\\"\\\"\\n Unless Linux, MUST be in report directory otherwise won't carry across\\n internal links.\\n\\n Re: http://www.microsoft.com/resources/documentation/windows/xp/all/proddocs/en-us/ntcmds_shelloverview.mspx?mfr=true\\n \\\"\\\"\\\"\\n ## clear decks first so we can tell if image made or not\\n try:\\n os.remove(pdf_path)\\n except Exception:\\n pass\\n rel_url = os.path.split(url)[1]\\n cd_path = os.path.split(html_path)[0]\\n if mg.PLATFORM == mg.WINDOWS: ## using Pyinstaller\\n cmd_make_pdf = (\\n f'cd \\\"{cd_path}\\\" && '\\n f'\\\"{export_output.EXE_TMP}\\\\\\\\wkhtmltopdf.exe\\\" '\\n f'{width} {height} \\\"{rel_url}\\\" \\\"{pdf_path}\\\"')\\n elif mg.PLATFORM == mg.MAC:\\n cmd_make_pdf = (\\n f'cd \\\"{cd_path}\\\" && '\\n f'\\\"{mg.MAC_FRAMEWORK_PATH}/wkhtmltopdf\\\" '\\n f'{width} {height} \\\"{rel_url}\\\" \\\"{pdf_path}\\\"')\\n elif mg.PLATFORM == mg.LINUX:\\n cmd_make_pdf = f'wkhtmltopdf {width} {height} \\\"{url}\\\" \\\"{pdf_path}\\\"'\\n else:\\n raise Exception('Encountered an unexpected platform!')\\n ## wkhtmltopdf uses stdout to actually output the PDF - a good feature but stuffs up reading stdout for message\\n if debug: print(f'cmd_make_pdf: {cmd_make_pdf}')\\n export_output.shellit(cmd_make_pdf)\\n if not os.path.exists(pdf_path):\\n raise Exception(\\n f\\\"wkhtmltopdf didn't generate error but {pdf_path} not made \\\"\\n f'nonetheless. cmd_make_pdf: {cmd_make_pdf}')\\n if debug: print(f'Initial processing of {html_path} complete')\\n except Exception as e:\\n raise Exception(\\n f'get_raw_pdf command failed: {cmd_make_pdf}. Orig error: {b.ue(e)}')\\n return pdf_path\",\n \"def make_pdf(self):\\n source = self.get_page_source()\\n if not source:\\n self.errors.append('no_source')\\n if not self.errors:\\n self.generate_pdf_file(source)\",\n \"def render_to_pdf(template_src, context_dict={}):\\n template = get_template(template_src)\\n html = template.render(context_dict)\\n result = BytesIO()\\n pdf = pisa.pisaDocument(BytesIO(html.encode(\\\"ISO-8859-1\\\")), result)\\n if not pdf.err:\\n return HttpResponse(result.getvalue(), content_type='application/pdf')\\n return None\",\n \"def get_pdf(self) -> io.BytesIO:\\n return self._get_pdf(rendered_html=self.get_rendered_html())\",\n \"def _produce_pdf_as_a_response(self, html):\\n # Create a Django response object, and specify content_type as pdf\\n response = HttpResponse(content_type='application/pdf')\\n # Define that this is an attachment. \\n response['Content-Disposition'] = 'attachment;'\\n pisaStatus = pisa.CreatePDF(html, dest=response)\\n \\n return response\",\n \"def to_pdf(self, wkhtmltopdf: str, f, output_file: Optional[str] = None):\\n if output_file is None:\\n output_file = \\\"-\\\"\\n html = self(f)\\n with tempfile.NamedTemporaryFile(\\\"wb\\\", suffix=\\\".html\\\") as fd:\\n html.write(fd)\\n fd.flush()\\n res = subprocess.run([wkhtmltopdf, fd.name, output_file], stdin=subprocess.DEVNULL, capture_output=True)\\n if res.returncode != 0:\\n raise RuntimeError(\\\"%s exited with error %d: stderr: %s\\\", self.wkhtmltopdf, res.returncode, res.stderr)\\n if output_file == \\\"-\\\":\\n return res.stdout\",\n \"def _pdf(self):\\n # LOG: processing_type property\\n self.set_property('processing_type', 'pdf')\\n xmlDoc = PDFiD(self.src_path)\\n oPDFiD = cPDFiD(xmlDoc, True)\\n # TODO: are there other characteristics which should be dangerous?\\n if oPDFiD.encrypt.count > 0:\\n self.make_dangerous('encrypted pdf')\\n if oPDFiD.js.count > 0 or oPDFiD.javascript.count > 0:\\n self.make_dangerous('pdf with javascript')\\n if oPDFiD.aa.count > 0 or oPDFiD.openaction.count > 0:\\n self.make_dangerous('openaction')\\n if oPDFiD.richmedia.count > 0:\\n self.make_dangerous('flash')\\n if oPDFiD.launch.count > 0:\\n self.make_dangerous('launch')\",\n \"def make_pdf(self, htmlbody, html_only=False):\\n # wrap htmlbody with provided HTML template\\n template = self.context.auto_template\\n template = template.replace(u'${body}', htmlbody)\\n if html_only:\\n return template\\n try:\\n tempdir = tempfile.mkdtemp()\\n # attachemnts saved. Let's save generated HTML\\n fullpath = os.path.join(tempdir, 'issue.html')\\n fp = open(fullpath, 'w')\\n fp.write(template.encode('utf-8'))\\n fp.close()\\n # Run wkhtmltopdf and generate the PDF\\n targetpath = os.path.join(tempdir, 'issue.pdf')\\n result = subprocess.call([\\\"wkhtmltopdf\\\", '-q', 'file://%s' % fullpath, '%s' % targetpath])\\n if result == 0:\\n return open(targetpath, 'rb').read()\\n else:\\n return ''\\n finally:\\n shutil.rmtree(tempdir, ignore_errors=True)\",\n \"def generate_pdf(pdf_data):\\n\\n html = HTML(string=pdf_data)\\n f = html.write_pdf()\\n\\n return f\",\n \"def render(path: str, params: dict):\\n template = get_template(path)\\n html = template.render(params)\\n response = BytesIO()\\n # is this file name a placeholder?\\n #file = open('my.file.pdf', 'wb')\\n pdf = pisa.pisaDocument(BytesIO(html.encode(\\\"UTF-8\\\")), response)\\n #file.close()\\n if not pdf.err:\\n return HttpResponse(response.getvalue(), content_type='application/pdf')\\n else:\\n return HttpResponse(\\\"Error Rendering PDF\\\", status=400)\",\n \"def _create_pdf(self, survey, response):\\n pdf_transformer = PDFTransformer(survey, response)\\n self._pdf, self._page_count = pdf_transformer.render_pages()\\n return self._pdf\",\n \"def render_pdf(\\n template: Union[List[str], str],\\n file_: IO,\\n url_fetcher=django_url_fetcher,\\n context: Optional[dict] = None,\\n):\\n context = context or {}\\n\\n if isinstance(template, str):\\n template = [template]\\n\\n html = select_template(template).render(context)\\n HTML(\\n string=html,\\n base_url=\\\"not-used://\\\",\\n url_fetcher=url_fetcher,\\n ).write_pdf(\\n target=file_,\\n )\",\n \"def generate_pdf_flask_response(pdf_data):\\n html = HTML(string=pdf_data)\\n\\n return render_pdf(html)\",\n \"def preview():\\r\\n html = create_html_report()\\r\\n return html\",\n \"def downlaod():\\r\\n filename = str(uuid.uuid4()) + '.pdf'\\r\\n filename = os.path.join('./output' , filename)\\r\\n\\r\\n config = pdfkit.configuration(wkhtmltopdf = PRG_Path)\\r\\n options = {\\r\\n 'page-size': 'Letter'\\r\\n ,'margin-top': '0.75in'\\r\\n ,'margin-right': '0.75in'\\r\\n ,'margin-bottom': '0.75in'\\r\\n ,'margin-left': '0.75in'\\r\\n ,'no-outline': None\\r\\n ,'encoding':'UTF-8'\\r\\n ,'enable-local-file-access':None\\r\\n ,'quiet': ''\\r\\n # ,'javascript-delay':2000000\\r\\n }\\r\\n\\r\\n\\r\\n html = create_html_report()\\r\\n pdf = pdfkit.from_string(input=html, output_path=filename,configuration=config, options=options)\\r\\n pdfDownload = open(filename,'rb').read()\\r\\n\\r\\n response: Response = Response (\\r\\n pdfDownload\\r\\n ,mimetype=\\\"application/pdf\\\"\\r\\n ,headers={\\r\\n \\\"Content-disposition\\\": \\\"attachment; filename=\\\" + filename\\r\\n ,\\\"Content-type\\\": \\\"application/force-download\\\"\\r\\n }\\r\\n )\\r\\n return response\",\n \"def html(self):\\n return self.report_format in ['pdf', 'html']\",\n \"def render_pdf(self, target=None, zoom=1):\\n return self._document.write_pdf(target=target, zoom=zoom)\",\n \"def create_pdf(html, options):\\n\\n # TODO: we will change this path, or use an other library for converting PDF!\\n # TODO: otherwise just say that wkhtmltopdf needs to be pre-installed (and how) and added to windows path\\n path_wkthmltopdf = \\\"C:/Program Files/wkhtmltopdf/bin/wkhtmltopdf.exe\\\"\\n config = pdfkit.configuration(wkhtmltopdf=path_wkthmltopdf)\\n\\n pdfkit.from_file(html, html.replace(\\\".html\\\", \\\".pdf\\\"), configuration=config, options=options)\\n return html + \\\".pdf\\\"\",\n \"def buildPDF(self):\\n\\n # TODO: get this working\\n # TODO: make this configurable via a dialog\\n os.chdir(self.file_path.parent)\\n proc = subprocess.Popen(\\n [\\\"make\\\", \\\"latexpdf\\\"],\\n stdin=subprocess.PIPE,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT\\n )\\n proc.wait()\\n for line in proc.stdout:\\n print(\\\"stdout: \\\" + line.rstrip())\",\n \"def render_to_response(self, context, **response_kwargs):\\n\\n response = HttpResponse(mimetype=self.mimetype)\\n response['Content-Disposition'] = ('attachment; filename=%s.%s' %\\n (context['filename'],\\n self.extension))\\n f = render_to_pdf(self.template_name, context)\\n response.write(f)\\n return response\",\n \"def _compute_single_pdf(self, **kwargs):\\n raise NotImplementedError\",\n \"def __get_ticket_print(self, **kwargs):\\n # TODO: выяснить используется ли pdf в принципе. В эл.регестратуре он никак не используется\\n # TODO: pdf creator based on Flask templates and xhtml2pdf\\n return \\\"\\\"\",\n \"def generate_pdf(self):\\n x = 100\\n y = 100\\n buffer = BytesIO()\\n p = canvas.Canvas(buffer, pagesize=\\\"A4\\\")\\n p.drawString(x, y, \\\"TO DO\\\")\\n p.showPage()\\n p.save()\\n pdf = buffer.getvalue()\\n buffer.close()\\n return pdf\",\n \"def generate_pdf(request):\\n reg_no = request.user.username\\n user = get_object_or_404(User, username=reg_no)\\n user_profile = user.get_profile()\\n user_application = user_profile.application\\n np = user_application.np\\n \\n response = HttpResponse(mimetype='application/pdf')\\n response['Content-Disposition'] = 'attachment; filename=JAM2012_Allottment.pdf'\\n \\n elements = []\\n doc = SimpleDocTemplate(response)\\n \\n formatted_time = time.ctime()\\n styles = getSampleStyleSheet()\\n styles.add(ParagraphStyle(name='Justify', alignment=TA_JUSTIFY))\\n \\n ptext = '<font size=15>JAM 2012 - Admissions.</font>' \\n elements.append(Paragraph(ptext, styles[\\\"Justify\\\"]))\\n elements.append(Spacer(4, 20))\\n \\n ptext = '<font size=12>Registration Number: %s</font>' % reg_no \\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(1, 12))\\n \\n data = [] \\n options = get_chosen_options(user) ##Put a check to show when the options chosen is empty\\n \\n if not(options):\\n ptext = '<font size=12>No choices were selected.</font>' \\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(1, 12))\\n doc.build(elements) \\n return response \\n \\n ptext = '<font size=12>The choices selected by me are as follows: </font>' \\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(4, 30))\\n \\n counter = 1\\n for opt in options:\\n data.append([counter, opt.opt_code, opt.opt_location, opt.opt_name])\\n counter = counter + 1\\n \\n t = Table(data)\\n t.setStyle(TableStyle([('GRID',(0,0),(3,len(options)),1,colors.black),\\n ('TEXTCOLOR',(0,0),(0,-1),colors.green)]))\\n \\n elements.append(t) \\n \\n elements.append(Spacer(4, 30))\\n \\n ptext = '<font size=12>I hereby declare that the order of preference given by me for my eligible programmes is final. </font>' \\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(4, 25))\\n \\n ptext = '<font size=12>Signature of the Candidate</font>' \\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(4, 20))\\n \\n ptext = '<font size=12>%s</font>' % formatted_time\\n elements.append(Paragraph(ptext, styles[\\\"Normal\\\"]))\\n elements.append(Spacer(1, 12))\\n \\n doc.build(elements)\\n \\n return response\",\n \"def task_render_report():\\n target = 'report.pdf'\\n dep = 'report.md'\\n return {\\n 'file_dep': [dep],\\n 'targets': [target],\\n 'actions': [\\n f\\\"pandoc -t latex -o {target} {dep}\\\"\\n ],\\n 'clean': True\\n }\",\n \"def form(request):\\n\\n font_config = FontConfiguration()\\n # Use the BCSans font as the default.\\n css = CSS(string='''\\n @font-face {\\n font-family: 'BCSans';\\n font-style: normal;\\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Regular.woff') format('woff');\\n }\\n @font-face {\\n font-family: 'BCSans';\\n font-style: italic;\\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Italic.woff') format('woff');\\n }\\n @font-face {\\n font-family: 'BCSans';\\n font-weight: 700;\\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-Bold.woff') format('woff');\\n }\\n @font-face {\\n font-family: 'BCSans';\\n font-style: italic;\\n font-weight: 700;\\n src: url('https://cdn.jsdelivr.net/npm/@bcgov/bc-sans@1.0.1/fonts/BCSans-BoldItalic.woff') format('woff');\\n }''', font_config=font_config)\\n\\n\\n\\n data = json.loads(request.body)\\n name = request.GET['name']\\n template = '{}.html'.format(name)\\n\\n template = get_template(template)\\n html_content = template.render(data)\\n\\n pdf_content = render_pdf(html_content)\\n\\n response = HttpResponse(content_type='application/pdf')\\n response['Content-Disposition'] = 'attachment; filename=\\\"report.pdf\\\"'\\n\\n response.write(pdf_content, stylesheet[css], font_config=font_config)\\n\\n return response\",\n \"def test_render_pdf(self):\\n charname = \\\"ChupStudent\\\"\\n bad_char_name = \\\"Rumplestiltskin\\\" # pylint: disable=unused-variable\\n config.OUTDIR = \\\".\\\"\\n retval = -1\\n expected_out_name = GAMEBASE + \\\"/Charsheets/\\\" + charname + \\\"_Charsheet.pdf\\\"\\n retval = name_pdfs.render_pdf(charname, \\\"COS_Student_Adopted.tex\\\")\\n self.assertEqual(retval, 0)\\n self.assertTrue(\\n Path.exists(Path(expected_out_name)),\\n f\\\"Failed for expected output name {expected_out_name}\\\",\\n )\\n retval = -1\\n for badname in self.bad_filenames:\\n with self.subTest(badname=badname):\\n try:\\n retval = name_pdfs.render_pdf(charname, badname, draft=True)\\n except TypeError:\\n retval = 1\\n except FileNotFoundError:\\n retval = 1\\n except subprocess.CalledProcessError:\\n retval = 1\\n else:\\n self.fail()\\n finally:\\n self.assertNotEqual(retval, 0)\",\n \"def download(texttitle):\\n try:\\n body = current_file.analysed_texts['Regular']\\n rendered = render_template('pdf_template.html', title=texttitle, body=body)\\n options = {'encoding': \\\"UTF-8\\\"}\\n pdf = pdfkit.from_string(rendered, False, options=options)\\n response = make_response(pdf)\\n response.headers[\\\"Content-Type\\\"] = 'application/pdf'\\n response.headers[\\\"Content-Disposition\\\"] = 'attachment; filename=output.pdf'\\n\\n return response\\n except Exception as e:\\n flash(\\\"Something went wrong, please try again\\\")\\n return redirect(request.referrer)\",\n \"def pdf_to_text(self, f):\\n cmd = [\\\"pdftohtml\\\", \\\"-zoom\\\", \\\"1.35\\\", \\\"-xml\\\", \\\"-stdout\\\", f.name]\\n code, stdout, stderr = self.shell(cmd)\\n if code > 0:\\n raise ValueError(stderr)\\n return stdout.decode('utf-8')\",\n \"def pdf():\\n env.file_ext = \\\".pdf\\\"\\n local(\\\"pandoc {input_files} -o {output_file}{file_ext} -H {preamble_file} --template {template_file} --bibliography={bib_file} --csl={csl_file} -V fontsize=12pt -V papersize=a4paper -V documentclass:report -N --latex-engine=xelatex\\\".format(**env))\",\n \"def html2pdf(html_filename, output_filename=None, **options):\\n\\n if not output_filename:\\n output_filename = newTempfile(suffix='.pdf')\\n\\n if not pdfreactor_available:\\n raise RuntimeError(\\\"The external 'pdfreactor' converter isn't available\\\")\\n\\n cmd = '%s \\\"pdfreactor\\\" \\\"%s\\\" \\\"%s\\\"' % \\\\\\n (execution_shell, html_filename, output_filename)\\n \\n status, output = runcmd(cmd)\\n if status != 0:\\n raise ConversionError('Error executing: %s' % cmd, output)\\n return dict(output_filename=output_filename,\\n status=status,\\n output=output)\",\n \"def make_pdf_from_raw_html(self, html, filename: str, options=None):\\n return pdfkit.from_string(html, filename, configuration=self._get_pdfkit_config(), options=options)\",\n \"def hs_document(self):\\n doc_service = PDFKitService(html=self.html())\\n return doc_service.pdf(template_name='engageletter.html')\",\n \"def display_html_report():\\n display(HTML('report_page.html'))\",\n \"def template2pdf(template=None, **kwargs):\\n str = render_to_string(template, kwargs)\\n output = kwargs.get('output', False)\\n ret = pdfkit.from_string(str, output, settings.WKHTMLTOPDF_OPTIONS or default_options)\\n return (ret, str)\",\n \"def generate_pdf_file(self, source):\\n filename = self.generate_temp_filename()\\n if not filename:\\n self.errors.append('filename_generation_failed')\\n return\\n\\n try:\\n transform_module = getattr(transforms, self.pdf_generator)\\n except AttributeError:\\n self.errors.append('wrong_generator_configuration')\\n return\\n\\n self.filename = filename\\n url = self.context.absolute_url()\\n\\n print_css = (self.pdf_tool.always_print_css or\\n self.context.portal_type in self.pdf_tool.print_css_types)\\n\\n # When the source is sent through Ajax, it's already encoded\\n # as a utf-8 string. When using it without javascript, the\\n # source comes from a view, which always returns unicode. In\\n # that case we need to encode it.\\n if isinstance(source, unicode):\\n source = source.encode('utf-8')\\n export_file, err = transform_module.html_to_pdf(\\n source,\\n self.tempdir,\\n filename,\\n url,\\n print_css,\\n self.get_extra_options())\\n\\n if err:\\n self.errors.append('pdf_creation_failed')\\n return\\n\\n self.pdf_tool.registerPDF(filename)\\n self.pdf_file = export_file\\n self.pdf_file.close()\",\n \"def create_pdf(submission):\\n # Get questions from sections\\n fields = {}\\n for section in submission.questions:\\n for form in section[\\\"forms\\\"]:\\n for field in form[\\\"fields\\\"]:\\n fs = field.get(\\\"fields\\\", [field])\\n for f in fs:\\n fields[f[\\\"name\\\"]] = f\\n\\n # Pull out image and answers\\n images = []\\n docs = []\\n answers = []\\n for answer in submission.answers:\\n answer, name = answer.get(\\\"answer\\\", \\\"\\\"), answer.get(\\\"name\\\", \\\"\\\")\\n field = fields[name]\\n if field[\\\"type\\\"] == \\\"FILE\\\":\\n image_ids = []\\n doc_ids = []\\n for file in answer:\\n if \\\"image\\\" in file:\\n image_ids.append(file[\\\"id\\\"])\\n elif \\\"file\\\" in file:\\n doc_ids.append(file[\\\"id\\\"])\\n\\n if image_ids:\\n images += [\\n image_upload.image\\n for image_upload in ImageUpload.objects.filter(\\n pk__in=image_ids\\n ).all()\\n ]\\n if doc_ids:\\n docs += [\\n file_upload.file\\n for file_upload in FileUpload.objects.filter(pk__in=doc_ids).all()\\n ]\\n else:\\n answers.append(\\n {\\n \\\"name\\\": name.lower().replace(\\\"_\\\", \\\" \\\").capitalize(),\\n \\\"prompt\\\": field.get(\\\"prompt\\\", \\\"\\\"),\\n \\\"answers\\\": answer if type(answer) is list else [answer],\\n }\\n )\\n\\n context = {\\n \\\"submission\\\": submission,\\n \\\"answers\\\": answers,\\n \\\"images\\\": images,\\n \\\"docs\\\": docs,\\n }\\n pdf_html_str = render_to_string(\\\"client-intake.html\\\", context=context)\\n pdf_bytes = weasyprint.HTML(string=pdf_html_str).write_pdf()\\n return pdf_bytes\",\n \"def renderDocumentFromURL(self,url):\\n in0=url\\n in1=self.PDFreactorConfiguration.in1\\n args = {\\\"in0\\\" : in0, \\\"in1\\\" : in1}\\n \\n self.resp = self.client.ROCall(\\\"renderDocumentFromURL\\\", args)\\n return self.resp[\\\"pdf\\\"]\",\n \"def renderDocumentFromContent(self,content):\\n in0=content\\n in1=self.PDFreactorConfiguration.in1\\n args = {\\\"in0\\\" : in0, \\\"in1\\\" : in1}\\n \\n self.resp = self.client.ROCall(\\\"renderDocumentFromContent\\\",args)\\n return self.resp[\\\"pdf\\\"]\",\n \"def _produce_pdf_as_an_attachment(self, html, pdf_details):\\n result = BytesIO()\\n pisa.pisaDocument(BytesIO(html.encode(\\\"ISO-8859-1\\\")), result)\\n return result.getvalue(), pdf_details\",\n \"def generate_document(stats: dict, semester: str):\\n filename = 'report_' + str(date.today()) + '.html'\\n with open('raw_html.html', 'r') as f:\\n string = f.read()\\n string = string.format(semester,\\n stats['faculty_with_usage'],\\n stats['full_time'],\\n stats['total_full_time'],\\n round((stats['full_time'] / stats['total_full_time']) * 100, 1),\\n stats['part_time'],\\n stats['total_part_time'],\\n round((stats['part_time'] / stats['total_part_time']) * 100, 1),\\n stats['staff'],\\n stats['courses_with_usage'],\\n stats['total_courses'],\\n round((stats['courses_with_usage'] / stats['total_courses']) * 100, 1),\\n stats['specifics']['assignments'],\\n stats['specifics']['grade'],\\n stats['specifics']['graded'],\\n stats['specifics']['discussion'])\\n with open(filename, 'w') as f:\\n f.write(string)\\n pdf = weasyprint.HTML(filename).write_pdf()\\n open(\\\"report_\\\" + str(date.today()) + \\\".pdf\\\", 'wb').write(pdf)\",\n \"def response_pdf(self, filename):\\n now = DateTime()\\n nice_filename = '%s_%s' % (filename, now.strftime('%Y%m%d'))\\n self.request.response.setHeader(\\\"Content-Type\\\", \\\"application/pdf\\\")\\n self.request.response.setHeader(\\\"Content-Disposition\\\", \\\"attachment\\\")\\n self.request.response.setHeader(\\\"filename\\\", nice_filename)\\n self.request.response.setHeader('Last-Modified',\\n DateTime.rfc822(DateTime()))\\n self.request.response.setHeader(\\\"Cache-Control\\\", \\\"no-store\\\")\\n self.request.response.setHeader(\\\"Pragma\\\", \\\"no-cache\\\")\\n return open(filename, 'rb').read()\",\n \"def get_text(self):\\r\\n if os.path.isfile(self.destination):\\r\\n pdf = self.read_from_text()\\r\\n else:\\r\\n pdf = self.convert_to_text\\r\\n self.save_text_to_file(pdf)\\r\\n return pdf\",\n \"def generate_page_pdf(self, src, out, options=None):\\n loger.info(\\\"start pdf creation\\\")\\n with open(src, 'r') as f:\\n print(pdfkit.from_file(f, out, options=self.__soft_cover_options if not options else\\n \\\"Lol\\\"))\\n loger.info(\\\"end pdf creation\\\")\",\n \"def __call__(self, method):\\n\\n that = self\\n \\n @functools.wraps(method)\\n def wrapper(self, *args, **kwargs):\\n html = method(self, *args, **kwargs)\\n\\n out = cStringIO.StringIO()\\n pdf = weasyprint.HTML(string = html).write_pdf(target = out)\\n\\n response = self.app.response_class()\\n response.content_type = \\\"application/pdf\\\"\\n #response.content_disposition = \\\"attachment; filename=\\\\\\\"...\\\\\\\"\\\"\\n response.data = out.getvalue()\\n return response\\n \\n return wrapper\",\n \"def generate_pdf (tmp_folder, filename, pdf_page_size):\\n\\n shell_cmd = PDF_CONVERT_CMD.substitute(wkhtmltox_path=WKHTMLTOX_PATH, folder=tmp_folder, article_id=filename, page_size=pdf_page_size)\\n proc = subprocess.Popen(shell_cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n stdout_value, stderr_value = proc.communicate()\\n\\n print u'\\\\n'.join(filter(None, [shell_cmd, stdout_value, stderr_value]))\",\n \"def convert_to_text(self) -> str:\\r\\n import pdftotext\\r\\n with open(self.pdf_path, \\\"rb\\\") as f:\\r\\n pdf = pdftotext.PDF(f)\\r\\n pdf = \\\"\\\\n\\\\n\\\".join(pdf)\\r\\n return pdf\",\n \"def _repr_html_(self) -> str:\\n # Speical case inside Google Colab\\n if \\\"google.colab\\\" in sys.modules:\\n load_notebook(hide_banner=True)\\n script, div, _ = notebook_content(self.to_render)\\n return f\\\"{div}<script>{script}</script>\\\"\\n\\n # Windows forbids us open the file twice as the result bokeh cannot\\n # write to the opened temporary file.\\n with NamedTemporaryFile(suffix=\\\".html\\\", delete=False) as tmpf:\\n pass\\n\\n save(\\n self.to_render,\\n filename=tmpf.name,\\n resources=CDN,\\n template=INLINE_TEMPLATE,\\n title=\\\"DataPrep.EDA Report\\\",\\n )\\n with open(tmpf.name, \\\"r\\\") as f:\\n output_html = f.read()\\n\\n # Delete the temporary file\\n Path(tmpf.name).unlink()\\n\\n # Fix the bokeh: bokeh wrongly call the \\\"waiting for bokeh to load\\\" function\\n # inside \\\"Bokeh.safely\\\", which causes Bokeh not found because\\n # Bokeh is even not loaded!\\n patched_html = output_html.replace(\\n \\\"Bokeh.safely\\\",\\n \\\"var __dataprep_bokeh_fix = (f) => document.Bokeh === undefined ? setTimeout(f, 1000) : f(); __dataprep_bokeh_fix\\\", # pylint: disable=line-too-long\\n )\\n # embed into report template created by us here\\n return patched_html\",\n \"def build_pdf_preview(self, file_path, cache_path, extension='.pdf'):\\n\\n # try:\\n # os.mkdir(cache_path.format(d_id=document_id))\\n # except OSError:\\n # pass\\n\\n with open(file_path, 'rb') as odt:\\n\\n file_name = self.get_file_hash(file_path)\\n\\n if os.path.exists('{path}.pdf'.format(\\n path=cache_path + file_name,\\n )):\\n result = open('{path}.pdf'.format(\\n path=cache_path + file_name,\\n ), 'rb')\\n\\n else:\\n if os.path.exists(cache_path + file_name + '_flag'):\\n time.sleep(2)\\n self.build_pdf_preview(file_path, cache_path, extension)\\n else:\\n result = file_converter.office_to_pdf(odt, cache_path, file_name)\\n\\n with open(cache_path + file_name + extension, 'wb') as pdf:\\n buffer = result.read(1024)\\n while buffer:\\n pdf.write(buffer)\\n buffer = result.read(1024)\",\n \"def convert_to_pdf(self, news_list):\\n self.logger.info(\\\"Converting news to PDF...\\\")\\n self.prepare_storage()\\n self.process_news_list_with_images(news_list)\\n content = self.generate_html_template(news_list)\\n pdf = io.BytesIO()\\n pisa.pisaDocument(content, pdf)\\n self.write_to_file(pdf.getvalue())\",\n \"def html_to_pdf(source_path: str, output_filename: str, delete_html=True):\\n # open output file for writing (truncated binary)\\n assert exists(source_path), \\\"The input file MUST exists!\\\"\\n from_file(source_path, output_filename)\\n if delete_html:\\n remove(source_path)\\n # return False on success and True on errors\",\n \"def create_pdf(f,s1,s2='',s3=''):\\n # does not need reportlab!\\n if s1 == 'White Ballot': s1 = '\\\"'+'_'*10+'\\\"'\\n cod = zlib.compress('BT /F1 16 Tf ET\\\\r\\\\nBT 300 270 Td (%s) Tj ET\\\\r\\\\nBT /F1 48 Tf ET\\\\r\\\\nBT 5 180 Td (%16s) Tj ET\\\\r\\\\nBT /F1 12 Tf ET\\\\r\\\\nBT 10 50 Td (%s) Tj ET'%(s3,s1,s2))\\n open(f,'w').write(create_pdf.__doc__ + '/Length %d>>\\\\nstream\\\\n'%len(cod) + cod + 'endstream endobj\\\\ntrailer<</Root 4 0 R>>')\",\n \"def convert_file_to_pdf(fileobj, outfilename=None,\\n cmd_args=settings.WKHTML_DEFAULT_ARGS):\\n log.debug(\\\"fileobj=%s\\\" % fileobj)\\n log.debug(\\\"wkhtml args=%s\\\" % cmd_args)\\n log.debug(\\\"outfile=%s\\\" % outfilename)\\n if not outfilename:\\n outfile, outfilename = tempfile.mkstemp(suffix='.pdf')\\n log.debug(\\\"temp_pdf_file=%s\\\" % outfilename)\\n os.close(outfile)\\n else:\\n outdirname = os.path.dirname(outfilename)\\n log.debug(\\\"out_dir=%s\\\" % outdirname)\\n if not os.path.exists(outdirname):\\n os.makedirs(outdirname)\\n tempfileobj, tempfilename = tempfile.mkstemp(suffix='.html')\\n log.debug(\\\"temp_html_file=%s\\\" % tempfilename)\\n tempfileobj = os.fdopen(tempfileobj, 'wb')\\n log.debug(\\\"copying temp html\\\")\\n shutil.copyfileobj(fileobj, tempfileobj)\\n tempfileobj.close()\\n cmd_args = cmd_args or []\\n cmdline = [settings.WKHTML_PATH] + cmd_args + [tempfilename, outfilename]\\n process = subprocess.Popen(cmdline,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.PIPE)\\n log.debug(\\\"running %s (%s)\\\" % (' '.join(cmdline),process))\\n stdout, stderr = process.communicate()\\n os.remove(tempfilename)\\n if process.returncode > 0:\\n raise ConvertError(stderr)\\n return outfilename\",\n \"def toPDF(Infos):\\n\\n\\n #returnPDF = PDFDocument(\\\"output\\\")\\n #returnPDF.Infos.get(\\\"name\\\")\\n returnPDF = PDF(\\\"Courier\\\", Infos.get(\\\"name\\\"))\\n if Infos.get('contact'):\\n returnPDF.contact(Infos.get(\\\"contact\\\"))\\n if Infos.get('Current position'):\\n returnPDF.currentposition(Infos.get(\\\"Current position\\\"))\\n if Infos.get('Education'):\\n returnPDF.currentposition(Infos.get(\\\"Education\\\"))\\n if Infos.get('Langue'):\\n returnPDF.currentposition(Infos.get(\\\"Langue\\\"))\\n returnPDF.output(\\\"result.pdf\\\", 'F')\",\n \"def load_pdf(self, env=\\\"default\\\", debug=()):\\n os.makedirs(\\\"txt\\\", exist_ok=True)\\n if env is \\\"default\\\": # default python path\\n call([executable,\\n os.path.join(f\\\"{exec_prefix}\\\", \\\"Scripts\\\", \\\"pdf2txt.py\\\"),\\n os.path.join(\\\"pdf\\\", f\\\"{self.pdf_filename}\\\"),\\n os.path.join(f\\\"-otxt\\\", f\\\"{self.txt_filename}\\\")])\\n if env is \\\"venv\\\": # virtual environment\\n call([os.path.join(\\\"venv\\\", \\\"Scripts\\\", \\\"python.exe\\\"),\\n os.path.join(\\\"venv\\\", \\\"Scripts\\\", \\\"pdf2txt.py\\\"),\\n os.path.join(\\\"pdf\\\", f\\\"{self.pdf_filename}\\\"),\\n os.path.join(f\\\"-otxt\\\", f\\\"{self.txt_filename}\\\")])\\n with open(os.path.join(\\\"txt\\\", f\\\"{self.txt_filename}\\\"), \\\"r\\\", encoding=\\\"utf-8\\\") as file:\\n self.paragraphs = [paragraph.rstrip('\\\\n') for paragraph in file]\\n os.remove(os.path.join(\\\"txt\\\", f\\\"{self.txt_filename}\\\"))\\n if debug:\\n for counter, paragraph in enumerate(self.paragraphs):\\n try:\\n if int(debug[0]) < counter < int(debug[1]):\\n print(counter, paragraph)\\n except TypeError:\\n print(\\\"Debug must be a (x,y) touple.\\\")\",\n \"def pdf_manager(self):\\n\\n s3ocr_root = self.s3ocr_etree() # get element s3xml\\n\\n # define font size\\n titlefontsize = 18\\n sectionfontsize = 15\\n regularfontsize = 13\\n hintfontsize = 10\\n \\n # etree labels\\n ITEXT = \\\"label\\\"\\n HINT = \\\"comment\\\"\\n TYPE = \\\"type\\\"\\n HASOPTIONS = \\\"has_options\\\"\\n LINES = \\\"lines\\\"\\n BOXES = \\\"boxes\\\"\\n\\n #l10n\\n l10n = self.l10n\\n\\n # get pdf title\\n if self.pdftitle == None or self.pdftitle == \\\"\\\":\\n try:\\n pdftitle = self.manager.s3.crud_strings[\\\\\\n self.tablename].subtitle_list.decode(\\\"utf-8\\\")\\n except:\\n pdftitle = self.resource.tablename\\n else:\\n pdftitle = self.pdftitle\\n\\n # prepare pdf\\n form = Form()\\n form.decorate()\\n\\n # set header\\n form.canvas.setTitle(pdftitle) # set pdf meta title\\n form.print_text([pdftitle,],\\n fontsize=titlefontsize,\\n style=\\\"center\\\") # set pdf header title\\n\\n form.print_text(\\n [\\n unicode(l10n.get(\\\"ocr_inst\\\").get(\\\"inst1\\\").decode(\\\"utf-8\\\")),\\n unicode(l10n.get(\\\"ocr_inst\\\").get(\\\"inst2\\\").decode(\\\"utf-8\\\")),\\n unicode(l10n.get(\\\"ocr_inst\\\").get(\\\"inst3\\\").decode(\\\"utf-8\\\"))\\n ],\\n fontsize=regularfontsize,\\n gray=0)\\n form.linespace(3)\\n # printing the etree\\n for eachresource in s3ocr_root:\\n form.draw_line()\\n form.print_text([\\n eachresource.attrib.get(ITEXT,\\n eachresource.attrib.get(\\\"name\\\"))\\n ],\\n fontsize=sectionfontsize)\\n form.draw_line(nextline=1)\\n form.linespace(12) # line spacing between each field\\n for eachfield in eachresource.iterchildren():\\n fieldlabel = eachfield.attrib.get(ITEXT)\\n spacing = \\\" \\\" * 5\\n fieldhint = self.__trim(eachfield.attrib.get(HINT))\\n if fieldhint != \\\"\\\" and fieldhint != None:\\n form.print_text([\\\"%s%s( %s )\\\" % \\\\\\n (fieldlabel,\\n spacing,\\n fieldhint)],\\n fontsize=regularfontsize)\\n else:\\n form.print_text([fieldlabel],\\n fontsize=regularfontsize)\\n\\n if eachfield.attrib.get(\\\"readable\\\", \\\"False\\\") == \\\"True\\\" and \\\\\\n eachfield.attrib.get(\\\"writable\\\", \\\"False\\\") == \\\"False\\\":\\n # if it is a readonly field\\n form.print_text(\\n [eachfield.attrib.get(\\\"default\\\",\\\"No default Value\\\")],\\n seek=10,\\n )\\n elif eachfield.attrib.get(HASOPTIONS) == \\\"True\\\":\\n fieldtype = eachfield.attrib.get(TYPE)\\n # if the field has to be shown with options\\n if fieldtype == \\\"boolean\\\":\\n form.nextline()\\n form.resetx()\\n bool_text = l10n.get(\\\"boolean\\\")\\n form.print_text(\\n [bool_text.get(\\\"yes\\\").decode(\\\"utf-8\\\")],\\n continuetext=1,\\n seek=3,\\n )\\n # TODO: Store positions\\n form.draw_circle(\\n boxes=1,\\n continuetext=1,\\n gray=0.9,\\n seek=10,\\n fontsize=12,\\n )\\n form.print_text(\\n [bool_text.get(\\\"no\\\").decode(\\\"utf-8\\\")],\\n continuetext=1,\\n seek=10,\\n )\\n # TODO: Store positions\\n form.draw_circle(\\n boxes=1,\\n continuetext=1,\\n gray=0.9,\\n seek=10,\\n fontsize=12,\\n )\\n else:\\n if fieldtype == \\\"multiselect\\\":\\n option_hint = l10n.get(\\\"select\\\").get(\\\"multiselect\\\")\\n else:\\n option_hint = l10n.get(\\\"select\\\").get(\\\"singleselect\\\")\\n form.print_text(\\n [option_hint.decode(\\\"utf-8\\\")],\\n fontsize=hintfontsize,\\n gray=0.4,\\n seek=3,\\n )\\n s3ocrselect = eachfield.getchildren()[0]\\n form.nextline(regularfontsize)\\n form.resetx() # move cursor to the front\\n optionseek = 10\\n # resting margin for options\\n formmargin = form.marginsides\\n form.marginsides = optionseek + formmargin\\n for eachoption in s3ocrselect.iterchildren():\\n form.print_text(\\n [eachoption.text],\\n continuetext=1,\\n fontsize = regularfontsize,\\n seek = 10,\\n )\\n # TODO: Store positions\\n form.draw_circle(\\n boxes=1,\\n continuetext=1,\\n gray=0.9,\\n seek=10,\\n fontsize=12,\\n )\\n # restoring orginal margin\\n form.marginsides = formmargin\\n \\n else:\\n # if it is a text field\\n fieldtype = eachfield.attrib.get(TYPE)\\n BOXES_TYPES = [\\\"string\\\", \\\"textbox\\\", \\\"integer\\\",\\n \\\"double\\\", \\\"date\\\", \\\"datetime\\\",]\\n if fieldtype in BOXES_TYPES:\\n if fieldtype in [\\\"string\\\", \\\"textbox\\\"]:\\n form.linespace(3)\\n num_lines = int(eachfield.attrib.get(\\\"lines\\\",\\n 1))\\n for eachline in xrange(num_lines):\\n # TODO: Store positions\\n form.draw_check_boxes(\\n completeline=1,\\n gray=0.9,\\n seek=3,\\n )\\n elif fieldtype in [\\\"integer\\\", \\\"double\\\"]:\\n num_boxes = int(eachfield.attrib.get(\\\"boxes\\\",\\n 9))\\n form.linespace(3)\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = num_boxes,\\n gray=0.9,\\n seek=3,\\n )\\n elif fieldtype in [\\\"date\\\", \\\"datetime\\\"]:\\n # print hint\\n hinttext = \\\\\\n l10n.get(\\\"datetime_hint\\\").get(fieldtype).decode(\\\"utf-8\\\")\\n form.print_text(\\n [hinttext],\\n fontsize=hintfontsize,\\n gray=0.4,\\n seek=3,\\n )\\n form.linespace(8)\\n datetime_continuetext = 0\\n datetime_seek = 3\\n if fieldtype == \\\"datetime\\\":\\n datetime_continuetext = 1\\n datetime_seek = 6\\n #HH\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = 2,\\n gray=0.9,\\n seek = 3,\\n )\\n #MM\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = 2,\\n gray=0.9,\\n continuetext=1,\\n seek = 4,\\n )\\n # DD\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = 2,\\n gray=0.9,\\n continuetext = datetime_continuetext,\\n seek = datetime_seek,\\n )\\n # MM\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = 2,\\n gray=0.9,\\n continuetext=1,\\n seek = 4,\\n )\\n # YYYY\\n # TODO: Store positions\\n form.draw_check_boxes(\\n boxes = 4,\\n gray=0.9,\\n continuetext=1,\\n seek = 4,\\n )\\n else:\\n self.r.error(501, self.manager.PARSE_ERROR)\\n print sys.stderr(\\\"%s :invalid field type: %s\\\" %\\\\\\n (eachfield.attrib.get(\\\"name\\\"),\\n fieldtype))\\n return form.save()\",\n \"def scrape (url, pdf_filename, pdf_page_size=PDF_PAGE_SIZE, folder=OUTPUT_FOLDER, clean_it=True):\\n\\n raw_html = get_url(url)\\n if raw_html is None:\\n print \\\"Sorry, could not read \\\", url\\n else:\\n filename_prefix, file_ext = os.path.splitext(pdf_filename)\\n if clean_it:\\n title = Document(raw_html).short_title()\\n content = Document(raw_html).summary(html_partial=True)\\n frame = HTML_FRAME.substitute(content=to_unicode(content),\\n url=url,\\n title=title)\\n source = write_html_file(folder, os.extsep.join([filename_prefix, 'html']), frame)\\n else:\\n source = write_html_file(folder, os.extsep.join([filename_prefix, 'html']), raw_html)\\n\\n if source:\\n generate_pdf (folder, filename_prefix, pdf_page_size)\",\n \"def create_pdf(self):\\n\\n my_datetime = datetime.now()\\n self.pdf_name = (\\n self.pdf_name + \\\"_\\\" + my_datetime.strftime(\\\"%H%M_%d%m%Y\\\") + \\\".pdf\\\"\\n )\\n fig_width = aW * self.column_ratio[0]\\n\\n clm_width_meta = (aW * self.column_ratio[1]) / len(self.fields)\\n\\n c = canvas.Canvas(os.path.join(self.pdf_folder, self.pdf_name), pagesize=A4)\\n\\n for qc_run_id, fig_file in sorted(self._files.items()):\\n (param_values, feature_values) = get_param_values(\\n qc_run_id, self.db_name, return_meta_add_on=True\\n )\\n\\n comment = self.subject + \\\"<br/>\\\"\\n # c.saveState()\\n title = \\\"Dataset \\\" + qc_run_id\\n\\n # Prepare header\\n header = Paragraph(title, title_style)\\n h_w, h_h = header.wrap(aW, aH)\\n\\n # Prepare image\\n img = ImageReader(fig_file)\\n im_width, im_height = img.getSize()\\n aspect = im_height / float(im_width)\\n fig_height = fig_width * aspect\\n\\n # Prepare metadata section\\n\\n meta_table = Table(\\n param_values,\\n colWidths=[clm_width_meta] * len(self.fields),\\n hAlign=\\\"CENTER\\\",\\n rowHeights=0.22 * inch,\\n )\\n meta_table.setStyle(\\n TableStyle(\\n [\\n (\\\"FONT\\\", (0, 0), (-1, 0), \\\"Helvetica-Bold\\\"),\\n (\\\"FONT\\\", (0, 1), (-1, -1), \\\"Helvetica\\\"),\\n (\\\"LINEBELOW\\\", (0, 0), (1, 0), 0.08, colors.black),\\n (\\\"SIZE\\\", (0, 0), (-1, -1), 8),\\n (\\\"VALIGN\\\", (0, 0), (-1, -1), \\\"BOTTOM\\\"),\\n # ('ALIGN', (0, 0), (-1, 0), 'CENTER'),\\n (\\\"ALIGN\\\", (0, 0), (0, -1), \\\"LEFT\\\"),\\n (\\\"ALIGN\\\", (1, 1), (1, -1), \\\"LEFT\\\"),\\n (\\\"INNERGRID\\\", (0, 0), (-1, -1), 0.08, colors.beige),\\n # ('BOX', (0,0), (-1,-1), 0.25, colors.grey),\\n ]\\n )\\n )\\n\\n meta_width, meta_height = meta_table.wrap(aW - im_width, aH / 2)\\n\\n # Prepare comments header\\n comments_header = Paragraph(\\\"Comments:\\\", title_style)\\n avail_height = aH - fig_height - v_padding\\n comm_h_width, comm_h_height = comments_header.wrap(\\n im_width, avail_height # aW - meta_width,\\n )\\n # Prepare comments\\n my_datetime = datetime.now()\\n ts = \\\"Printed on \\\" + my_datetime.strftime(\\\"%c\\\")\\n\\n try:\\n data_specific_comment = self.comments[int(qc_run_id)]\\n comment += data_specific_comment + \\\"<br/>\\\"\\n comment += self.comments[\\\"general\\\"] + \\\"<br/>\\\"\\n\\n comment += self.smalltalk + \\\"<br/>\\\"\\n except Exception:\\n logger.warning(\\n \\\"Unable to summarize result of \\\" + \\\"dataset {}\\\".format(qc_run_id)\\n )\\n comment_ts = comment + ts\\n comment_ts = textwrap.fill(comment_ts, 70)\\n comment_ts = comment_ts.replace(\\\"\\\\n\\\", \\\"<br/>\\\")\\n\\n comments_p = Paragraph(comment_ts, body_style)\\n\\n avail_height = aH - fig_height - v_padding - comm_h_height\\n\\n comm_width, comm_height = comments_p.wrap(im_width, avail_height) # aW,\\n\\n line_widths = comments_p.getActualLineWidths0()\\n number_of_lines = len(line_widths)\\n if number_of_lines > 1:\\n pass\\n if number_of_lines == 1:\\n min(line_widths)\\n comm_width, comm_height = comments_p.wrap(im_width, avail_height)\\n\\n # Prepare features\\n feat_table = Table(\\n feature_values,\\n colWidths=[clm_width_meta] * len(self.fields),\\n hAlign=\\\"CENTER\\\",\\n rowHeights=0.22 * inch,\\n )\\n feat_table.setStyle(\\n TableStyle(\\n [\\n (\\\"FONT\\\", (0, 0), (-1, 0), \\\"Helvetica-Bold\\\"),\\n (\\\"FONT\\\", (0, 1), (-1, -1), \\\"Helvetica\\\"),\\n (\\\"LINEBELOW\\\", (0, 0), (1, 0), 0.08, colors.black),\\n (\\\"SIZE\\\", (0, 0), (-1, -1), 8),\\n (\\\"VALIGN\\\", (0, 0), (-1, -1), \\\"BOTTOM\\\"),\\n # ('ALIGN', (0, 0), (-1, 0), 'CENTER'),\\n (\\\"ALIGN\\\", (0, 0), (0, -1), \\\"LEFT\\\"),\\n (\\\"ALIGN\\\", (1, 1), (1, -1), \\\"LEFT\\\"),\\n (\\\"INNERGRID\\\", (0, 0), (-1, -1), 0.08, colors.beige),\\n # ('BOX', (0,0), (-1,-1), 0.25, colors.grey),\\n ]\\n )\\n )\\n avail_height = aH - meta_height # fig_height - v_padding - comm_h_height\\n avail_height -= comm_height\\n feat_width, feat_height = feat_table.wrap(aW - im_width, avail_height)\\n\\n # Draw everyting on canvas\\n\\n header.drawOn(c, left_margin, aH - top_margin)\\n\\n c.drawImage(\\n img,\\n left_margin,\\n aH - top_margin - fig_height - v_padding,\\n width=fig_width * 1.1,\\n height=fig_height * 1.1,\\n mask=\\\"auto\\\",\\n )\\n\\n meta_table.drawOn(\\n c,\\n left_margin + fig_width + h_padding,\\n aH - meta_height - top_margin / 2, # - v_padding\\n )\\n\\n comments_header.drawOn(\\n c,\\n left_margin,\\n aH\\n - top_margin\\n - comm_h_height\\n - fig_height\\n - 2 * v_padding, # - add_on_height\\n )\\n\\n comments_p.drawOn(\\n c,\\n left_margin,\\n aH\\n - top_margin\\n - comm_h_height\\n - comm_height\\n - fig_height\\n - 2 * v_padding\\n - comm_h_height, # - add_on_height\\n )\\n\\n feat_table.drawOn(\\n c,\\n left_margin + fig_width + h_padding,\\n aH - meta_height - top_margin / 2 - feat_height - v_padding,\\n # top_margin - fig_height - 2*v_padding - feat_height\\n )\\n\\n # new page\\n c.showPage()\\n c.saveState()\\n\\n c.save()\",\n \"def render(self, context):\\n engine = Renderer()\\n engine.environment.filters['format_date'] = format_date\\n engine.environment.filters['format_datetime'] = format_datetime\\n result = engine.render(self.template, **context)\\n response = HttpResponse(\\n content_type='application/vnd.oasis.opendocument.text; charset=UTF-8'\\n )\\n response['Content-Disposition'] = 'inline; filename=' + self.filename\\n with tempfile.NamedTemporaryFile() as output:\\n output.write(result)\\n output.flush()\\n output = open(output.name, 'rb')\\n response.write(output.read())\\n return response\",\n \"def _generate_report(self):\\n\\n _LOG.info(\\\"Generating the HTML report.\\\")\\n\\n # Make sure the output directory exists.\\n try:\\n self.outdir.mkdir(parents=True, exist_ok=True)\\n except OSError as err:\\n raise Error(f\\\"failed to create directory '{self.outdir}': {err}\\\")\\n\\n raw_stats_paths, descr_paths = self._copy_raw_data()\\n\\n # Find the styles and templates paths.\\n templdir = FSHelpers.search_for_app_data(\\\"wult\\\", Path(\\\"templates\\\"),\\n pathdescr=\\\"HTML report Jinja2 templates\\\")\\n csspath = FSHelpers.search_for_app_data(\\\"wult\\\", Path(\\\"css/style.css\\\"),\\n pathdescr=\\\"HTML report CSS file\\\")\\n\\n # Copy the styles file to the output directory.\\n dstpath = self.outdir.joinpath(\\\"style.css\\\")\\n try:\\n shutil.copyfile(csspath, dstpath)\\n except OSError as err:\\n raise Error(f\\\"failed to copy CSS file from '{csspath}' to '{dstpath}':\\\\n{err}\\\")\\n\\n # The summary table is only included into the main HTML page.\\n sum_tbl = self._prepare_summary_table(raw_stats_paths, descr_paths)\\n links_tbl = self._prepare_links_table()\\n\\n # Each column name gets its own HTML page.\\n for colname, pinfos in self._pinfos.items():\\n stats_tbl = self._prepare_stats_table(pinfos)\\n\\n # Render the template.\\n jenv = Jinja2.build_jenv(templdir, trim_blocks=True, lstrip_blocks=True)\\n jenv.globals[\\\"stats_tbl\\\"] = stats_tbl\\n jenv.globals[\\\"pinfos\\\"] = pinfos\\n jenv.globals[\\\"colname\\\"] = colname\\n jenv.globals[\\\"title_descr\\\"] = self.title_descr\\n jenv.globals[\\\"toolname\\\"] = self._refinfo[\\\"toolname\\\"]\\n\\n if sum_tbl:\\n jenv.globals[\\\"sum_tbl\\\"] = sum_tbl\\n jenv.globals[\\\"links_tbl\\\"] = links_tbl\\n templfile = outfile = \\\"index.html\\\"\\n sum_tbl = None\\n else:\\n templfile = \\\"metric.html\\\"\\n outfile = links_tbl[colname][\\\"fname\\\"]\\n\\n Jinja2.render_template(jenv, Path(templfile), outfile=self.outdir.joinpath(outfile))\",\n \"def pdf(self, identifier):\\n return self.client.request_with_method(Methods.PDF % (self.name, identifier,))\",\n \"def get_pdf(self, points=None):\\n if points is not None:\\n return self.parent.pdf(points)\\n else:\\n raise ValueError( 'Please digit an input for getPDF method')\",\n \"def exportTable(self):\\n\\t\\tself.pdf = \\tself.dir + \\\"/application.pdf\\\"\\n\\t\\tpdf = pisa.CreatePDF(\\n\\t\\t\\tfile(self.html, \\\"r\\\" ),\\n\\t\\t\\tfile(self.pdf, \\\"wb\\\")\\n\\t\\t\\t)\",\n \"def getPDF(self):\\n return self.pdfSample\",\n \"def buildHTML(self):\\n\\n # TODO: make this configurable via a dialog\\n os.chdir(self.file_path.parent)\\n proc = subprocess.Popen(\\n [\\\"make\\\", \\\"clean\\\"],\\n stdin=subprocess.PIPE,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT\\n )\\n for line in proc.stdout:\\n print(\\\"stdout: \\\" + str(line.rstrip(), encoding='utf8'))\\n print('----------------')\\n proc = subprocess.Popen(\\n [\\\"make\\\", \\\"html\\\"],\\n stdin=subprocess.PIPE,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT\\n )\\n proc.wait()\\n for line in proc.stdout:\\n print(\\\"stdout: \\\" + str(line.rstrip(), encoding='utf8'))\\n\\n # Load corresponding HTML file from newly-built Sphinx docs\\n self.preview.load_html(self.output_html_path)\",\n \"def proof_pdf(self):\\n return self._proof_pdf\",\n \"def create_pdf(request):\\n\\n contact_info = ContactDetails.objects.iterator()\\n\\n # Create a file-like buffer to receive PDF data.\\n buffer = io.BytesIO()\\n\\n # Create the PDF object, using the buffer as its \\\"file.\\\"\\n pdf_file = canvas.Canvas(buffer)\\n\\n # Draw things on the PDF. Here's where the PDF generation happens\\n pdf_file.setTitle(\\\"Contact Infomation\\\")\\n pdf_file.setFont(\\\"Helvetica-Bold\\\", 20, leading=None)\\n pdf_file.setFillColorRGB(1,0,0)\\n pdf_file.drawString( 60, 800, \\\"Stefanos Taramas Contact Information\\\")\\n pdf_file.setFillColorRGB(0,0,0)\\n pdf_file.setFont(\\\"Helvetica\\\", 15, leading=None)\\n\\n for index, item in enumerate(contact_info):\\n line = str(index + 1) +\\\") \\\" + str(item.contact_name) + \\\": \\\" + str(item.contact_info)\\n column = 50\\n row = 750 - 15*index\\n pdf_file.drawString(column, row, line)\\n\\n # Close the PDF object cleanly\\n pdf_file.showPage()\\n pdf_file.save()\\n\\n # FileResponse sets the Content-Disposition header so that browsers\\n # present the option to save the file.\\n buffer.seek(0)\\n\\n return FileResponse(buffer, as_attachment=True, filename='StefanosTaramasContactInfo.pdf')\",\n \"def generate_pdf(file_path_or_url, data_type, filename):\\n file_path = get_pdf_file_path(filename)\\n if data_type == TYPE_FILE:\\n try:\\n HTML(filename=file_path_or_url).write_pdf(file_path)\\n finally:\\n default_storage.delete(file_path_or_url)\\n else:\\n HTML(file_path_or_url).write_pdf(file_path)\\n return filename\",\n \"def render_latex(self, latex_snippet, output_png_file, output_pdf_file):\\n\\t\\ttmp_dir = tempfile.mkdtemp(prefix = \\\"mdx_latex_\\\")\\n\\t\\ttex_file = os.path.join(tmp_dir, \\\"file.tex\\\")\\n\\t\\tpdf_file = os.path.join(tmp_dir, \\\"file.pdf\\\")\\n\\t\\t\\n\\t\\ttry:\\n\\t\\t\\t# Generate the tex file\\n\\t\\t\\ttex = LaTeXBlockProcessor.LATEX_TEMPLATE.render(\\n\\t\\t\\t\\tpreamble = self.preamble,\\n\\t\\t\\t\\tdocument = latex_snippet,\\n\\t\\t\\t)\\n\\t\\t\\ttex_hash = hashlib.sha1(tex).hexdigest()\\n\\t\\t\\t\\n\\t\\t\\t# Check if anything needs to be done\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tpng_meta = self.get_png_metadata(output_png_file)\\n\\t\\t\\t\\tif tex_hash == png_meta.get(\\\"tex_hash\\\", None):\\n\\t\\t\\t\\t\\t# Already got the latest version in the PNG, do nothing!\\n\\t\\t\\t\\t\\treturn\\n\\t\\t\\texcept IOError:\\n\\t\\t\\t\\t# No file exists yet so we definately should build it\\n\\t\\t\\t\\tpass\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t# Store the tex in a file to be compiled\\n\\t\\t\\twith open(tex_file, \\\"w\\\") as f:\\n\\t\\t\\t\\tf.write(tex)\\n\\t\\t\\t\\n\\t\\t\\t# Try and build the file\\n\\t\\t\\tfor build_num in range(LaTeXBlockProcessor.LATEX_BUILDS):\\n\\t\\t\\t\\tp = Popen( [ \\\"pdflatex\\\"\\n\\t\\t\\t\\t , \\\"-shell-escape\\\"\\n\\t\\t\\t\\t , \\\"-halt-on-error\\\"\\n\\t\\t\\t\\t , \\\"-output-directory\\\", tmp_dir\\n\\t\\t\\t\\t , tex_file]\\n\\t\\t\\t\\t , cwd = os.path.realpath(self.configs.get(\\\"input_path\\\", \\\"./\\\"))\\n\\t\\t\\t\\t , stdin = None\\n\\t\\t\\t\\t , stdout = sys.stderr\\n\\t\\t\\t\\t , stderr = sys.stderr\\n\\t\\t\\t\\t )\\n\\t\\t\\t\\tif p.wait() != 0:\\n\\t\\t\\t\\t\\traise Exception(\\\"LaTeX Compilation Failed for:\\\\n%s\\\"%latex_snippet)\\n\\t\\t\\t\\n\\t\\t\\t# Make a copy of required\\n\\t\\t\\tif output_pdf_file is not None:\\n\\t\\t\\t\\tshutil.copy(pdf_file, output_pdf_file)\\n\\t\\t\\t\\n\\t\\t\\t# Convert to PNG\\n\\t\\t\\tp = Popen( [\\\"convert\\\", \\\"-density\\\", \\\"440\\\", pdf_file, \\\"-resize\\\", \\\"25%\\\", output_png_file]\\n\\t\\t\\t , stdin = None\\n\\t\\t\\t , stdout = sys.stderr\\n\\t\\t\\t , stderr = sys.stderr\\n\\t\\t\\t )\\n\\t\\t\\tif p.wait() != 0:\\n\\t\\t\\t\\traise Exception(\\\"Converting PDF to PNG failed for:\\\\n%s\\\"%latex_snippet)\\n\\t\\t\\t\\n\\t\\t\\t# Add the hash of the source to the metadata \\n\\t\\t\\tself.set_png_metadata(output_png_file, {\\\"tex_hash\\\":tex_hash})\\n\\t\\t\\t\\n\\t\\tfinally:\\n\\t\\t\\tshutil.rmtree(tmp_dir)\",\n \"def test_generate_pdf(self):\\n with mock.patch.object(form_api.Client, 'wait') as wait_patched:\\n template_id = 'tpl_000000000000000001' # str |\\n\\n response = self.client.generate_pdf(\\n template_id, {\\n 'data': {\\n 'title': 'Test PDF',\\n 'description': 'This PDF is great!'\\n }\\n })\\n wait_patched.assert_called()\\n self.assertEquals(response.status, 'success')\\n submission = response.submission\\n self.assertRegexpMatches(submission.id, '^sub_')\\n self.assertEquals(submission.expired, False)\\n self.assertEquals(submission.state, 'processed')\",\n \"def print_report_pdf(self):\\n self.ensure_one()\\n return self.env.ref('eliterp_sale_reports.action_report_product_catalogue').report_action(self)\",\n \"def render_html_with_data(self):\\n self.logger.info('Builder {} prepares html data for {} file'.format(self.id, self.html_template_file()))\\n return self \\\\\\n .template_env.get_template(self.html_template_file()) \\\\\\n .render(self.build_document().prepare_html_dict())\",\n \"def createPDF(self, tex):\\n for b in [TIMEOUT_BINARY, RUBBER_BINARY]:\\n if not os.path.isfile(b):\\n raise ValueError(\\\"Binary %s not available\\\" % b)\\n\\n self.explodeTeX(tex)\\n\\n p = subprocess.Popen(\\n [\\n TIMEOUT_BINARY, TIMEOUT,\\n RUBBER_BINARY, '--inplace', '--ps', '-ops2pdf', '-Wall', '--maxerr=100', '--force',\\n os.path.join(self.dir, 'exploded.tex'),\\n ],\\n stdin=subprocess.PIPE,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.PIPE,\\n )\\n (processOut, processErr) = p.communicate(\\\"\\\")\\n exitCode = p.wait()\\n if exitCode != 0:\\n return processOut + processErr + \\\"\\\\nCompilation of document failed!\\\"\\n\\n self._outputFile = os.path.join(self.dir, 'exploded.pdf')\\n return processOut + processErr\",\n \"def pdfReceiver(request, model=''):\\n\\n\\tinput_str = ''\\n\\tinput_str += parsePOST(request)\\n\\t# packet = io.StringIO() # write to memory\\n\\tpacket = io.BytesIO()\\n\\n\\ttry:\\n\\t\\tpisa.CreatePDF(input_str, dest=packet)\\n\\texcept ValueError as error:\\n\\t\\t# triggered from the elusive invalid color value issue:\\n\\t\\tlogging.warning(\\\"elusive invalid color value, defaulting html background-color to FFFFFF\\\")\\n\\t\\tpisa.CreatePDF(input_str, dest=packet, default_css=\\\"body{background-color:#FFFFFF;}\\\")\\n\\n\\n\\tjid = MetabolizerCalc().gen_jid() # create timestamp\\n\\tresponse = HttpResponse(packet.getvalue(), content_type='application/pdf')\\n\\tresponse['Content-Disposition'] = 'attachment; filename=' + model + '_' + jid + '.pdf'\\n\\tpacket.close() # todo: figure out why this doesn't solve the 'caching problem'\\n\\treturn response\",\n \"def _render_as(self, extra_context={}, RESPONSE=None):\\n import urlparse, re\\n \\n request = getattr(self, 'REQUEST', None)\\n \\n method = None\\n if (extra_context.has_key('options') and\\n extra_context['options'].has_key('method')):\\n method = extra_context['options']['method']\\n elif request.has_key('method'):\\n method = request['method']\\n \\n if method not in self.render_methods:\\n method = self.default_render_method\\n \\n transform_id = getattr(self, 'transform_%s' % method, '')\\n transform_id = re.sub('\\\\s\\\\([^\\\\(]*?\\\\)$', '', transform_id)\\n \\n content_type = self.content_type_map.get(method, 'text/plain')\\n\\n # note we make sure we don't have a unicode object at the later steps,\\n # because that causes all sorts of headaches with the XML parser later\\n xml_rendered = self.pt_render(extra_context=extra_context).encode(self.char_encoding)\\n \\n if not transform_id or transform_id == self.unselected_transform:\\n rendered = xml_rendered\\n else:\\n transform = getattr(self, transform_id, None)\\n if not transform or transform.meta_type != 'XSLT Template':\\n for obj in self._get_path_objs(self.transform_paths):\\n transform = getattr(obj, transform_id, None)\\n if transform and transform.meta_type == 'XSLT Template':\\n break\\n if not transform:\\n raise TransformError, ('Transform %s did not exist' % \\n transform_id)\\n self.prune_cache()\\n cached = self.retrieve_cache(transform, xml_rendered)\\n if cached:\\n rendered = cached\\n else:\\n rendered = transform.render_xml(xml_rendered, content_type)\\n self.update_cache(transform, xml_rendered, rendered, 0)\\n \\n \\n # set the base properly\\n pathparts = list(urlparse.urlparse(self.absolute_url()))\\n base = os.path.split(pathparts[2])[0]\\n pathparts[2] = base\\n base = urlparse.urlunparse(pathparts)\\n \\n RESPONSE.setBase(base)\\n RESPONSE.setHeader('Content-Type', '%s; charset=%s' % (content_type,\\n self.char_encoding))\\n \\n return rendered\",\n \"def return_pdf(\\n file_name: str,\\n settings: config.Settings = Depends(get_settings),\\n db: Session = Depends(get_db),\\n token: str = Depends(oauth2_scheme),\\n):\\n logged_user = get_current_user(db, token)\\n\\n if not logged_user:\\n raise HTTPException(403)\\n\\n if not (logged_user.is_staff or logged_user.is_superuser):\\n results = read_results(db, cpf=logged_user.cpf, PDF_Filename=file_name)\\n if not results:\\n raise HTTPException(404)\\n\\n result_path = Path(settings.pdf_storage_path).joinpath(file_name)\\n\\n return FileResponse(str(result_path.absolute()), media_type=\\\"application/pdf\\\")\",\n \"def get_html_report(self) -> str:\\n template_contents = dict(\\n vendor_bundle_js=self.vendor_bundle,\\n app_bundle_js=self.app_bundle,\\n # results\\n results=self.results,\\n # account metadata\\n account_id=self.account_id,\\n account_name=self.account_name,\\n report_generated_time=str(self.report_generated_time),\\n cloudsplaining_version=__version__,\\n )\\n template_path = os.path.dirname(__file__)\\n env = Environment(loader=FileSystemLoader(template_path)) # nosec\\n template = env.get_template(\\\"template.html\\\")\\n return template.render(t=template_contents)\",\n \"def render_pdf(\\n self, input_file: str, render_target_dpi: int, page_number: int = 1\\n ) -> Image:\\n doc = pdfium.FPDF_LoadDocument(str(input_file), None)\\n\\n page = pdfium.FPDF_LoadPage(doc, page_number - 1)\\n\\n # Page dimensions are measured in points. One point is 1/72 inch (around 0.3528 mm).\\n width = int(pdfium.FPDF_GetPageWidthF(page) + 0.5)\\n height = int(pdfium.FPDF_GetPageHeightF(page) + 0.5)\\n\\n # Converting to page\\n render_width = int(width / 72 * render_target_dpi)\\n render_height = int(height / 72 * render_target_dpi)\\n\\n # render to bitmap\\n bitmap = pdfium.FPDFBitmap_Create(render_width, render_height, 0)\\n pdfium.FPDFBitmap_FillRect(\\n bitmap, 0, 0, render_width, render_height, 0xFFFFFFFF\\n )\\n pdfium.FPDF_RenderPageBitmap(\\n bitmap,\\n page,\\n 0,\\n 0,\\n render_width,\\n render_height,\\n 0,\\n pdfium.FPDF_LCD_TEXT | pdfium.FPDF_ANNOT,\\n )\\n\\n # retrieve data from bitmap\\n buffer = pdfium.FPDFBitmap_GetBuffer(bitmap)\\n buffer_ = ctypes.cast(\\n buffer, ctypes.POINTER(ctypes.c_ubyte * (render_width * render_height * 4))\\n )\\n\\n img = Image.frombuffer(\\n \\\"RGBA\\\", (render_width, render_height), buffer_.contents, \\\"raw\\\", \\\"BGRA\\\", 0, 1\\n )\\n\\n if bitmap is not None:\\n pdfium.FPDFBitmap_Destroy(bitmap)\\n pdfium.FPDF_ClosePage(page)\\n\\n pdfium.FPDF_CloseDocument(doc)\\n\\n return img\",\n \"def create_report(self, output_filename=None, output_format='html', offline_js=False):\\n\\n # extra code to put in the <head> part of HTML\\n extra_head_code = ''\\n\\n if output_format == 'html':\\n\\n # embed plotly.js in HTML (makes it bigger, but then doesn't require web connection)\\n if offline_js:\\n embed_chart = 'offline_embed_js_div'\\n else:\\n # otherwise put web link to plotly.js (but this means we need to download every time)\\n embed_chart = 'offline_div'\\n extra_head_code = '<head><script src=\\\"https://cdn.plot.ly/plotly-latest.min.js\\\"></script></head>'\\n elif output_format == 'pdf':\\n # for PDFs we need to create static PNGs of plotly charts\\n embed_chart = 'offline_image_png_in_html'\\n\\n # get a list of the HTML to render\\n elements_to_render = self._layout_computation_results_to_html(embed_chart)\\n canvas = Canvas(elements_to_render=elements_to_render)\\n\\n # should we return a binary string containing the HTML/PDF (this can be displayed by a web server for example)\\n # or later be written to disk\\n return_binary = False\\n\\n # return a binary string, if we haven't specified a filename output\\n if output_filename is None:\\n return_binary = True\\n\\n # generate the HTML or PDF with chartpy's Canvas object\\n if output_format == 'html':\\n\\n html, _ = canvas.generate_canvas(output_filename=output_filename, silent_display=True,\\n canvas_plotter=self._canvas_plotter, page_title=self._title, render_pdf=False,\\n return_html_binary=return_binary, extra_head_code=extra_head_code)\\n\\n return html\\n elif output_format == 'pdf':\\n _, pdf = canvas.generate_canvas(output_filename=output_filename, silent_display=True,\\n canvas_plotter=self._canvas_plotter, page_title=self._title, render_pdf=True,\\n return_pdf_binary=return_binary, extra_head_code=extra_head_code)\\n\\n return pdf\\n else:\\n raise Exception(\\\"Invalid output format selected\\\")\",\n \"def save_news_in_pdf_file(news, path_to_pdf, logger, html_args=None):\\n html_file = save_news_in_html_file(news, path_to_pdf, logger)\\n path = os.path.join(path_to_pdf, 'rss_news.pdf')\\n try:\\n with open(path, 'wb') as pdf_file, open(html_file.name, 'r', encoding='utf-8') as html_file:\\n logger.info('Creating pdf-file...')\\n pisa.CreatePDF(src=html_file, dest=pdf_file)\\n logger.info(\\\"Pdf-file is created successfully!\\\")\\n if html_args is None:\\n html_file.close()\\n os.remove(html_file.name)\\n logger.info(\\\"Temporary html-file was deleted\\\")\\n return pdf_file\\n except FileNotFoundError:\\n raise SystemExit('Please, check the existing of file')\",\n \"def process_pdf(path):\\r\\n str = \\\"\\\"\\r\\n try:\\r\\n pages = layout_scanner.get_pages(path) \\r\\n i = 0\\r\\n l = len(pages)\\r\\n while i < l: \\r\\n str += pages[i]\\r\\n i += 1\\r\\n except Exception, e:\\r\\n return g_error_template % e, \\\"\\\" \\r\\n \\r\\n return \\\"\\\", str\",\n \"def create_web_bundle(filename, issue, **kwargs):\\n pages = get_staging_pdf_files(**kwargs)\\n if not pages:\\n raise RuntimeWarning('No pages found')\\n if len(pages) % 4 != 0:\\n raise RuntimeError(f'Wrong number of pages {len(pages)}')\\n\\n optimized_pages = [convert_pdf_to_web(pdf) for pdf in pages]\\n PS_DATEFORMAT = 'D: %Y%m%d%H%M%S' # used in pdf metadata\\n output_file = Path(filename)\\n pdfmark = output_file.parent / 'pdfmark' # pdf meta data\\n pdfmark.write_text((\\n f'[/Title (Universitas {issue.issue_name})'\\n f'/CreationDate ({issue.publication_date:{PS_DATEFORMAT}})'\\n f'/ModDate ({timezone.now():{PS_DATEFORMAT}})'\\n '/Creator (Universitas)'\\n '/Subject (Nyheter)'\\n '/DOCINFO pdfmark'\\n '['\\n '/PageMode'\\n '/UseThumbs' # do not show thumbs\\n '/Page 1'\\n '/View [/Fit]' # fit full page\\n '/PageLayout'\\n '/TwoColumnRight' # two column layout\\n '/PageLabels'\\n '<< /Nums [0 << /S /D /St 1 >>] >>' # fix page numbers\\n '/DOCVIEW pdfmark'\\n ))\\n output_file.touch()\\n args = [\\n GHOSTSCRIPT,\\n '-q',\\n '-o',\\n output_file,\\n '-dBATCH',\\n '-dNOPAUSE',\\n '-dAutoRotatePages=/None',\\n '-sDEVICE=pdfwrite',\\n '-dCompressFonts=true',\\n '-dSubsetFonts=true',\\n '-dCompatibilityLevel=1.6',\\n '-dDetectDuplicateImages=true',\\n '-sDEVICE=pdfwrite',\\n *optimized_pages,\\n pdfmark,\\n ]\\n subprocess.run(map(str, args))\\n pdfmark.unlink()\\n return output_file\",\n \"def html():\\n env.file_ext = \\\".html\\\"\\n local(\\\"pandoc {input_files} -o {output_file}{file_ext} --standalone --bibliography={bib_file} --csl={csl_file} --toc --number-sections\\\".format(**env))\",\n \"def build(self, buffer=None) -> any:\\n\\n # init PDF\\n if buffer:\\n self.PDF = canvas.Canvas(buffer, pagesize=letter, bottomup=0)\\n else:\\n self.PDF = canvas.Canvas(self.buffer, pagesize=letter, bottomup=0)\\n\\n # run funcs\\n\\n self.add_title()\\n self.draw_image()\\n self.add_org_details()\\n self.add_customer_details()\\n self.draw_line(225)\\n self.add_due_date()\\n self.add_subscription()\\n\\n # save the pdf\\n\\n self.PDF.save()\\n return self.PDF\",\n \"def process(self, doc, is_):\\n implementation = Implementation(self)\\n implementation.process(doc, is_)\\n return implementation.html\",\n \"def __call__(self, method):\\n\\n that = self\\n \\n @functools.wraps(method)\\n def wrapper(self, *args, **kwargs):\\n html = method(self, *args, **kwargs)\\n pdf = pisa.CreatePDF(html)\\n\\n response = self.app.response_class()\\n response.content_type = \\\"application/pdf\\\"\\n #response.content_disposition = \\\"attachment; filename=\\\\\\\"...\\\\\\\"\\\"\\n response.data = pdf.dest.getvalue()\\n return response\\n \\n return wrapper\",\n \"def to_pdf(\\n self,\\n url: str,\\n output: Union[None, str, Path] = None,\\n ) -> Path:\\n return asyncio.get_event_loop().run_until_complete(\\n asyncio.wait_for(self._run(url, output), self.timeout) if self.timeout >= 0.01 else\\n self._run(url, output)\\n )\",\n \"def should_see_pdf(self):\\n return self.organization.has_a_pdf()\",\n \"async def to_pdf(\\n self,\\n url: str,\\n output: Union[None, str, Path] = None,\\n ) -> Path:\\n return await (asyncio.wait_for(self._run(url, output), self.timeout)\\n if self.timeout >= 0.01 else self._run(url, output)\\n )\",\n \"def generate_pdf_report(release, spec, report_week):\\n\\n logging.info(u\\\" Generating the pdf report, give me a few minutes, please \\\"\\n u\\\"...\\\")\\n\\n working_dir = spec.environment[u\\\"paths\\\"][u\\\"DIR[WORKING,SRC]\\\"]\\n\\n execute_command(f\\\"cd {working_dir} && mv -f index.pdf.template index.rst\\\")\\n\\n _convert_all_svg_to_pdf(spec.environment[u\\\"paths\\\"][u\\\"DIR[WORKING,SRC]\\\"])\\n\\n # Convert PyPLOT graphs in HTML format to PDF.\\n convert_plots = u\\\"xvfb-run -a wkhtmltopdf {html} {pdf}\\\"\\n plots = get_files(spec.environment[u\\\"paths\\\"][u\\\"DIR[STATIC,VPP]\\\"], u\\\"html\\\")\\n plots.extend(\\n get_files(spec.environment[u\\\"paths\\\"][u\\\"DIR[STATIC,DPDK]\\\"], u\\\"html\\\")\\n )\\n for plot in plots:\\n file_name = f\\\"{plot.rsplit(u'.', 1)[0]}.pdf\\\"\\n logging.info(f\\\"Converting {plot} to {file_name}\\\")\\n execute_command(convert_plots.format(html=plot, pdf=file_name))\\n\\n # Generate the LaTeX documentation\\n build_dir = spec.environment[u\\\"paths\\\"][u\\\"DIR[BUILD,LATEX]\\\"]\\n cmd = PDF_BUILDER.format(\\n release=release,\\n date=datetime.datetime.utcnow().strftime(u'%Y-%m-%d %H:%M UTC'),\\n working_dir=working_dir,\\n build_dir=build_dir)\\n execute_command(cmd)\\n\\n # Build pdf documentation\\n archive_dir = spec.environment[u\\\"paths\\\"][u\\\"DIR[STATIC,ARCH]\\\"]\\n cmds = [\\n f'cd {build_dir} && '\\n f'pdflatex -shell-escape -interaction nonstopmode csit.tex || true',\\n f'cd {build_dir} && '\\n f'pdflatex -interaction nonstopmode csit.tex || true',\\n f'cd {build_dir} && '\\n f'cp csit.pdf ../{archive_dir}/csit_{release}.{report_week}.pdf &&'\\n f'cp csit.pdf ../{archive_dir}/csit_{release}.pdf'\\n ]\\n\\n for cmd in cmds:\\n execute_command(cmd)\\n\\n logging.info(u\\\" Done.\\\")\",\n \"def gen_html_report(self, html_report_name=None, html_report_template=None):\\n return render_html_report(\\n self.summary,\\n html_report_name,\\n html_report_template\\n )\",\n \"def review_pdf_updated_eventhandler(obj, evt):\\n if not obj.REQUEST.get(\\\"pdf_file\\\"):\\n obj.update_generated_pdf()\\n\\n # Terrible hack, if this method gets called without a real\\n # object, we assume that the caller wants htis to happen now\\n interfaces.IReviewPDF(obj).generatePageImages(later=evt != None)\",\n \"def print(self, request, items_to_print):\\n if len(items_to_print) == 0:\\n # No valid items provided, return an error message\\n data = {\\n 'error': _('No valid objects provided to template'),\\n }\\n\\n return Response(data, status=400)\\n\\n outputs = []\\n\\n # In debug mode, generate single HTML output, rather than PDF\\n debug_mode = common.models.InvenTreeSetting.get_setting('REPORT_DEBUG_MODE', cache=False)\\n\\n # Start with a default report name\\n report_name = \\\"report.pdf\\\"\\n\\n try:\\n # Merge one or more PDF files into a single download\\n for item in items_to_print:\\n report = self.get_object()\\n report.object_to_print = item\\n\\n report_name = report.generate_filename(request)\\n output = report.render(request)\\n\\n # Run report callback for each generated report\\n self.report_callback(item, output, request)\\n\\n try:\\n if debug_mode:\\n outputs.append(report.render_as_string(request))\\n else:\\n outputs.append(output)\\n except TemplateDoesNotExist as e:\\n template = str(e)\\n if not template:\\n template = report.template\\n\\n return Response(\\n {\\n 'error': _(f\\\"Template file '{template}' is missing or does not exist\\\"),\\n },\\n status=400,\\n )\\n\\n if not report_name.endswith('.pdf'):\\n report_name += '.pdf'\\n\\n if debug_mode:\\n \\\"\\\"\\\"Contatenate all rendered templates into a single HTML string, and return the string as a HTML response.\\\"\\\"\\\"\\n\\n html = \\\"\\\\n\\\".join(outputs)\\n\\n return HttpResponse(html)\\n else:\\n \\\"\\\"\\\"Concatenate all rendered pages into a single PDF object, and return the resulting document!\\\"\\\"\\\"\\n\\n pages = []\\n\\n try:\\n for output in outputs:\\n doc = output.get_document()\\n for page in doc.pages:\\n pages.append(page)\\n\\n pdf = outputs[0].get_document().copy(pages).write_pdf()\\n\\n except TemplateDoesNotExist as e:\\n\\n template = str(e)\\n\\n if not template:\\n template = report.template\\n\\n return Response(\\n {\\n 'error': _(f\\\"Template file '{template}' is missing or does not exist\\\"),\\n },\\n status=400,\\n )\\n\\n inline = common.models.InvenTreeUserSetting.get_setting('REPORT_INLINE', user=request.user, cache=False)\\n\\n return InvenTree.helpers.DownloadFile(\\n pdf,\\n report_name,\\n content_type='application/pdf',\\n inline=inline,\\n )\\n\\n except Exception as exc:\\n # Log the exception to the database\\n log_error(request.path)\\n\\n # Re-throw the exception to the client as a DRF exception\\n raise ValidationError({\\n 'error': 'Report printing failed',\\n 'detail': str(exc),\\n 'path': request.path,\\n })\",\n \"def to_pdf(self, imageFileName, outFileName, fontname=\\\"Times-Roman\\\", fontsize=10, withVisibleOCRText=False, withVisibleImage=True, withVisibleBoundingBoxes=False):\\n if self.hocr is None:\\n # warn that no text will be embedded in the output PDF\\n print \\\"Warning: No hOCR file specified. PDF will be image-only.\\\"\\n \\n im = Image.open(imageFileName)\\n imwidthpx, imheightpx = im.size\\n if 'dpi' in im.info:\\n width = float(im.size[0])/im.info['dpi'][0]\\n height = float(im.size[1])/im.info['dpi'][1]\\n else:\\n # we have to make a reasonable guess\\n # set to None for now and try again using info from hOCR file\\n width = height = None\\n \\n \\n ocr_dpi = (300, 300) # a default, in case we can't find it\\n \\n # get dimensions of the OCR, which may not match the image\\n if self.hocr is not None:\\n for div in self.hocr.findall(\\\".//%sdiv\\\"%(self.xmlns)):\\n if div.attrib['class'] == 'ocr_page':\\n coords = self.element_coordinates(div)\\n ocrwidth = coords[2]-coords[0]\\n ocrheight = coords[3]-coords[1]\\n if width is None:\\n # no dpi info with the image\\n # assume OCR was done at 300 dpi\\n width = ocrwidth/300\\n height = ocrheight/300\\n ocr_dpi = (ocrwidth/width, ocrheight/height)\\n break # there shouldn't be more than one, and if there is, we don't want it\\n \\n if width is None:\\n # no dpi info with the image, and no help from the hOCR file either\\n # this will probably end up looking awful, so issue a warning\\n print \\\"Warning: DPI unavailable for image %s. Assuming 96 DPI.\\\"%(imageFileName)\\n width = float(im.size[0])/96\\n height = float(im.size[1])/96\\n \\n # create the PDF file\\n pdf = Canvas(outFileName, pagesize=(width*inch, height*inch), pageCompression=1) # page size in points (1/72 in.)\\n \\n # put the image on the page, scaled to fill the page\\n if withVisibleImage:\\n pdf.drawInlineImage(im, 0, 0, width=width*inch, height=height*inch)\\n \\n if self.hocr is not None:\\n for word in self.hocr.findall(\\\".//%sspan\\\"%(self.xmlns)):\\n if word.attrib['class'] == 'ocr_word':\\n coords = self.element_coordinates(word)\\n content = self._get_element_text(word)\\n if content.rstrip() == '':\\n continue\\n text = pdf.beginText()\\n text.setFont(fontname, fontsize)\\n if not withVisibleOCRText:\\n #text.setTextRenderMode(0) # visible\\n #else:\\n text.setTextRenderMode(3) # invisible\\n \\n # set cursor to bottom left corner of line bbox (adjust for dpi)\\n # Can't determine original text's baseline, but guess that ypg\\n # roughly push it down by ~2/3 of line height. Correct for that.\\n # PDF y coords increase going *up* the page, remember. Assume \\\"o\\\" is\\n # round so width == line height.\\n origin_y = (height*inch)-(float(coords[3])/ocr_dpi[1])*inch\\n if re.search(r\\\"[gjpqy()]\\\", content):\\n origin_y += pdf.stringWidth(\\\"o\\\") * 1/3\\n if re.search(r\\\"[\\\\[\\\\]()]\\\", content):\\n origin_y += pdf.stringWidth(\\\"o\\\") * 1/3.5\\n elif re.search(r\\\"[,;]\\\", content):\\n origin_y += pdf.stringWidth(\\\"o\\\") * 1/4\\n text.setTextOrigin((float(coords[0])/ocr_dpi[0])*inch, origin_y)\\n \\n # scale the width of the text to fill the width of the line's bbox\\n text.setHorizScale((((float(coords[2])/ocr_dpi[0]*inch)-(float(coords[0])/ocr_dpi[0]*inch))/pdf.stringWidth(content.rstrip(), fontname, fontsize))*100)\\n \\n # write the text to the page\\n text.textLine(content.rstrip())\\n pdf.drawText(text)\\n \\n # finish up the page and save it\\n pdf.showPage()\\n pdf.save()\",\n \"def publish_pdf(\\n self,\\n filename: str | io.BytesIO,\\n notes: str = None,\\n open_file: bool = False,\\n metadata: dict = None,\\n bins: int = 10,\\n logo: Path | str | None = None,\\n ) -> None:\\n plt.ioff()\\n canvas = pdf.PylinacCanvas(\\n filename, page_title=\\\"Picket Fence Analysis\\\", metadata=metadata, logo=logo\\n )\\n data = io.BytesIO()\\n self.save_analyzed_image(data, leaf_error_subplot=True)\\n canvas.add_image(data, location=(3, 5), dimensions=(15, 15))\\n canvas.add_text(\\n text=self.results(as_list=True), location=(1.5, 22), font_size=14\\n )\\n if notes is not None:\\n canvas.add_text(text=\\\"Notes:\\\", location=(1, 5.5), font_size=14)\\n canvas.add_text(text=notes, location=(1, 5))\\n\\n canvas.add_new_page()\\n hist = io.BytesIO()\\n self.save_histogram(hist, bins)\\n canvas.add_image(hist, location=(3, 8), dimensions=(15, 15))\\n canvas.finish()\\n\\n if open_file:\\n webbrowser.open(filename)\",\n \"def print_report_pdf(self):\\n self.ensure_one()\\n return self.env.ref('eliterp_sale_reports.action_report_product_sold').report_action(self)\",\n \"def render(self):\\n try:\\n if self.permit():\\n return self.renderer.render(self)\\n except AttributeError:\\n if self.renderer is None:\\n raise NotImplementedError(\\\"Should have implemented a renderer for {0}\\\".format(self.name))\\n else:\\n raise\\n return ''\",\n \"def get_pdf(self, analysis_request):\\n return self.get_last_attachment_pdf(analysis_request, \\\"Requisition\\\")\",\n \"def get_search_pdf(self):\\n current_app.logger.debug('Account {0} report type {1} setting up report data.'\\n .format(self._account_id, self._report_key))\\n data_copy = copy.deepcopy(self._report_data)\\n # 1: Generate the search pdf with no TOC page numbers or total page count.\\n data = self._setup_report_data()\\n url = current_app.config.get('REPORT_SVC_URL') + SINGLE_URI\\n current_app.logger.debug('Account {0} report type {1} calling report-api {2}.'\\n .format(self._account_id, self._report_key, url))\\n meta_data = report_utils.get_report_meta_data(self._report_key)\\n files = report_utils.get_report_files(data, self._report_key)\\n headers = Report.get_headers()\\n response_reg = requests.post(url=url, headers=headers, data=meta_data, files=files)\\n current_app.logger.debug('Account {0} report type {1} response status: {2}.'\\n .format(self._account_id, self._report_key, response_reg.status_code))\\n if response_reg.status_code != HTTPStatus.OK:\\n content = ResourceErrorCodes.REPORT_ERR + ': ' + response_reg.content.decode('ascii')\\n current_app.logger.error('Account {0} response status: {1} error: {2}.'\\n .format(self._account_id, response_reg.status_code, content))\\n return jsonify(message=content), response_reg.status_code, None\\n # 2: Set TOC page numbers in report data from initial search pdf page numbering.\\n self._report_data = report_utils.update_toc_page_numbers(data_copy, response_reg.content)\\n # 3: Generate search report again with TOC page numbers and total page count.\\n data_final = self._setup_report_data()\\n current_app.logger.debug('Account {0} report type {1} calling report-api {2}.'\\n .format(self._account_id, self._report_key, url))\\n files = report_utils.get_report_files(data_final, self._report_key)\\n current_app.logger.info('Search report regenerating with TOC page numbers set.')\\n response = requests.post(url=url, headers=headers, data=meta_data, files=files)\\n current_app.logger.info('Search report regeneration with TOC page numbers completed.')\\n if response.status_code != HTTPStatus.OK:\\n content = ResourceErrorCodes.REPORT_ERR + ': ' + response.content.decode('ascii')\\n current_app.logger.error('Account {0} response status: {1} error: {2}.'\\n .format(self._account_id, response.status_code, content))\\n return jsonify(message=content), response.status_code, None\\n return response.content, response.status_code, {'Content-Type': 'application/pdf'}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.70788","0.6738788","0.6705874","0.6704703","0.66870785","0.666667","0.66463214","0.6614933","0.66001874","0.65993774","0.6502286","0.6423387","0.64061946","0.6362002","0.63022816","0.6281078","0.62789476","0.6275642","0.6163935","0.6161958","0.6047067","0.6017398","0.5986202","0.5967268","0.59592193","0.59336174","0.59218836","0.59120977","0.59081846","0.5904774","0.59047174","0.5898842","0.5834021","0.5765277","0.57384425","0.5733101","0.5707333","0.57039326","0.56830126","0.56745064","0.5666187","0.5661762","0.56403935","0.5622304","0.56051385","0.55863595","0.5578769","0.55348283","0.54980165","0.5495946","0.54930574","0.54868567","0.5454933","0.5450931","0.5429878","0.54275715","0.5424068","0.54103035","0.5408856","0.54004884","0.5399868","0.53968716","0.53949326","0.5384512","0.5382043","0.53677523","0.5362548","0.53490144","0.5339351","0.5337055","0.532647","0.5322439","0.5312475","0.5311881","0.52920306","0.52793807","0.52645266","0.52556753","0.5255293","0.52524024","0.52459323","0.5242675","0.5235446","0.5233675","0.5226275","0.522283","0.52136254","0.52064365","0.5205991","0.5203641","0.5178563","0.51750666","0.51717407","0.5141093","0.5137969","0.5125426","0.51170605","0.5112965","0.511178","0.51030004"],"string":"[\n \"0.70788\",\n \"0.6738788\",\n \"0.6705874\",\n \"0.6704703\",\n \"0.66870785\",\n \"0.666667\",\n \"0.66463214\",\n \"0.6614933\",\n \"0.66001874\",\n \"0.65993774\",\n \"0.6502286\",\n \"0.6423387\",\n \"0.64061946\",\n \"0.6362002\",\n \"0.63022816\",\n \"0.6281078\",\n \"0.62789476\",\n \"0.6275642\",\n \"0.6163935\",\n \"0.6161958\",\n \"0.6047067\",\n \"0.6017398\",\n \"0.5986202\",\n \"0.5967268\",\n \"0.59592193\",\n \"0.59336174\",\n \"0.59218836\",\n \"0.59120977\",\n \"0.59081846\",\n \"0.5904774\",\n \"0.59047174\",\n \"0.5898842\",\n \"0.5834021\",\n \"0.5765277\",\n \"0.57384425\",\n \"0.5733101\",\n \"0.5707333\",\n \"0.57039326\",\n \"0.56830126\",\n \"0.56745064\",\n \"0.5666187\",\n \"0.5661762\",\n \"0.56403935\",\n \"0.5622304\",\n \"0.56051385\",\n \"0.55863595\",\n \"0.5578769\",\n \"0.55348283\",\n \"0.54980165\",\n \"0.5495946\",\n \"0.54930574\",\n \"0.54868567\",\n \"0.5454933\",\n \"0.5450931\",\n \"0.5429878\",\n \"0.54275715\",\n \"0.5424068\",\n \"0.54103035\",\n \"0.5408856\",\n \"0.54004884\",\n \"0.5399868\",\n \"0.53968716\",\n \"0.53949326\",\n \"0.5384512\",\n \"0.5382043\",\n \"0.53677523\",\n \"0.5362548\",\n \"0.53490144\",\n \"0.5339351\",\n \"0.5337055\",\n \"0.532647\",\n \"0.5322439\",\n \"0.5312475\",\n \"0.5311881\",\n \"0.52920306\",\n \"0.52793807\",\n \"0.52645266\",\n \"0.52556753\",\n \"0.5255293\",\n \"0.52524024\",\n \"0.52459323\",\n \"0.5242675\",\n \"0.5235446\",\n \"0.5233675\",\n \"0.5226275\",\n \"0.522283\",\n \"0.52136254\",\n \"0.52064365\",\n \"0.5205991\",\n \"0.5203641\",\n \"0.5178563\",\n \"0.51750666\",\n \"0.51717407\",\n \"0.5141093\",\n \"0.5137969\",\n \"0.5125426\",\n \"0.51170605\",\n \"0.5112965\",\n \"0.511178\",\n \"0.51030004\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6588409"},"document_rank":{"kind":"string","value":"10"}}},{"rowIdx":25686,"cells":{"query":{"kind":"string","value":"Initialise with an experiment document"},"document":{"kind":"string","value":"def __init__(self, document):\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key == 'cim.2.designing.NumericalExperiment'\n self.doc = document\n\n # In most cases there is only one related mip.\n # Handle the edge case here rather than in template.\n mips = ''\n for m in document.related_mips:\n mips += m.name+', '\n self.mips = mips[:-2]\n\n self.related = []\n for r in self.doc.requirements:\n req = esd.retrieve(r.id)\n # Are there additional requirements?\n # If so, let's monkey patch their long names onto the linkage...\n # The other choice would be to have a requirements class WITH\n # it's own template.\n req.monkey_additional = []\n if req.additional_requirements:\n for rr in req.additional_requirements:\n rreq = esd.retrieve(rr.id)\n req.monkey_additional.append(rreq.long_name)\n self.related.append(req)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __init__(self, document):\n\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key == 'cim.2.designing.Project'\n self.doc = document\n\n # We will populate the \"mip\" variable with the mip era\n self.mips = 'CMIP6'\n\n self.related = []\n for r in self.doc.required_experiments:\n self.related.append(esd.retrieve(r.id))","def experiment_init(self):\n pass","def experiment_init(self):\n raise NotImplementedError(\"this needs to be implemented!\")","def setUp(self):\n super(SimpleDocumentTestCase, self).setUp()\n self.document = SimpleDocument()\n self.document.description = u\"body text\"\n self.document.title = u\"document title\"","def setUp(self):\n super(SimpleDocumentAnnotationTestCase, self).setUp()\n self.document = SimpleDocument()\n self.document.description = u\"body text\"\n self.document.title = u\"document title\"","def __init__(self, experiment_data):\n self._experiment_data = experiment_data","def create(init_document: 'Document') -> 'DocumentArray':","def test_init(self):\n ex = Experiment(note=\"Test\")\n self.assertEqual(ex.note, \"Test\")","def __init__(self, docs, **kargs): # [todo]\n self.cohort = kargs.get('cohort', None)\n self.nDoc = len(docs)\n\n return","def experiments_init(self):\n pass","def setUp(self):\n self.docCounter = 0","def Init(self, *args):\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)","def __init__(self, doc):\n\n self.doc = doc\n if self.doc.doi:\n self._populate()\n self.populated = True\n else:\n self.populated = False","def __init__(self, main_doc):\n\t\tif not isinstance(main_doc, Document):\n\t\t\traise TypeError('term must be of type Document')\n\t\tself.main_doc = main_doc\n\t\tself.env_docs = []","def init_doc(self):\n raise NotImplementedError()","def setUp(self):\n self._vocab = np.array([\"one\", \"two\", \"three\", \"four\",\n \"five\", \"six\", \"seven\", \"eight\", \"nine\"])\n self._embedding_dim = 2\n\n self._default_config = {\n \"vocab\": self._vocab,\n \"embedding_dim\": self._embedding_dim,\n \"position_encoding\": None\n }","def __init__(self, name, training_documents):\n self._name = name\n self._training_documents = training_documents","def __init__(self, run_id: str, doc: Dict, service: APIFactory):\n self.run_id = run_id\n self.file_id = doc['id']\n self.name = doc['name']\n self.title = doc.get('title', self.name)\n self.caption = doc.get('caption')\n self.format = doc.get('format', {})\n self.service = service","def build_document(self):\n pass","def __init__(self, doc=None, lda=None, max_doc_len=None, num_topics=None, gamma=None, lhood=None):\n self.doc = doc\n self.lda = lda\n self.gamma = gamma\n self.lhood = lhood\n if self.gamma is None:\n self.gamma = np.zeros(num_topics)\n if self.lhood is None:\n self.lhood = np.zeros(num_topics + 1)\n\n if max_doc_len is not None and num_topics is not None:\n self.phi = np.zeros((max_doc_len, num_topics))\n self.log_phi = np.zeros((max_doc_len, num_topics))\n\n # the following are class variables which are to be integrated during Document Influence Model\n\n self.doc_weight = None\n self.renormalized_doc_weight = None","def __init__(self, experiment, **kwargs):\n \n # retrieve which experiment to run\n experiment_function = getattr(self, experiment)\n\n if kwargs:\n kwargs['experiment']=experiment\n experiment_function(**kwargs)\n\n else:\n kwargs={'experiment':experiment}\n experiment_function(**kwargs)","def __init__(self):\n\n # Load embeddings index\n self.embeddings = self.load()\n self.console = Console()","def __init__(self, doc, target=None, stylesheet=\"\"):\n self.document = doc\n self.stylesheet = stylesheet\n self.target = target if target is not None else StringIO()","def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\n name=None, **kwargs):\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\n self.artDirection = artDirection\n self.path = path # Optional path to markdown file, if it has content.\n self.mdText = mdText # Optional markdown string.\n self.name = name or 'Untitled'\n self.startPage = startPage","def startDocument(self):\n pass","def startDocument(self):\n pass","def __init__(self, *args):\n this = _libsbml.new_SBMLDocument(*args)\n try: self.this.append(this)\n except: self.this = this","def document(self):\n ...","def initDocTagText(self):\n self.doc, self.tag, self.text = Doc().tagtext()","def start(self) -> None:\n\n self.doc = self.doc + r'''\n \\documentclass[\n 10pt, % Main document font size\n a4paper, % Paper type, use 'letterpaper' for US Letter paper\n ]{scrartcl}\n\n \\usepackage{graphicx}\n \\usepackage{epstopdf}\n \\usepackage{float}\n \\usepackage[scale=0.75]{geometry} % Reduce document margins\n \\usepackage{hyperref}\n \\usepackage{longtable}\n\n \\begin{document}\n\n \\title{Automatic Exploratory Data Analysis} % The article title\n\n \\subtitle{Study Case} % Uncomment to display a subtitle\n\n \\author{Jacob} % The article author(s) - author affiliations need to be specified in the AUTHOR AFFILIATIONS block\\\n\n \\maketitle % Print the title/author/date block\n\n \\newpage\n \\tableofcontents % Print the table of contents\n\n \\newpage\n \\listoffigures % Print the list of figures\n\n \\newpage\n \\listoftables % Print the list of tables\n '''","def new_document(self) -> nodes.document:\n document = super().new_document()\n document.__class__ = addnodes.document # replace the class with patched version\n\n # substitute transformer\n document.transformer = SphinxTransformer(document)\n document.transformer.set_environment(self.settings.env)\n\n # substitute reporter\n reporter = document.reporter\n document.reporter = LoggingReporter.from_reporter(reporter)\n\n return document","def __init__(self, doc_set):\n self.__doc_set = doc_set\n self.__preprocessor = InputPreprocessor(doc_set)","def __init__(self, documents_path):\n self.documents = []\n self.vocabulary = []\n self.likelihoods = []\n self.documents_path = documents_path\n self.term_doc_matrix = None \n self.document_topic_prob = None # P(z | d)\n self.topic_word_prob = None # P(w | z)\n self.topic_prob = None # P(z | d, w)\n\n self.number_of_documents = 0\n self.vocabulary_size = 0","def __init__(self, txt='', unicodeEncoding='utf-8'):\n # __document capture the document level structure\n # for each sentence and then put in the archives when the next sentence\n # is processed\n super(ConTextMarkup, self).__init__(__txt=None,\n __rawtxt=txt,\n __scope=None,\n __SCOPEUPDATED=False)\n self.__document = nx.DiGraph()\n self.__document.add_node(\"top\", category=\"document\")\n self.__VERBOSE = False\n self.__tagID = 0\n self.__unicodeEncoding = unicodeEncoding","def __init__(self, document_path):\n super(SaltXMIGraph, self).__init__()\n self.tree = etree.parse(document_path)\n self.doc_id = get_doc_id(self.tree)\n for i, node_element in enumerate(get_elements(self.tree, 'nodes')):\n node = create_class_instance(node_element, i, self.doc_id)\n self.add_node(i, node.__dict__)\n for i, edge_element in enumerate(get_elements(self.tree, 'edges')):\n edge = create_class_instance(edge_element, i, self.doc_id)\n self.add_edge(edge.source, edge.target, edge.__dict__)","def __init__(self, tutorial):\n self._tex = \"\"\n\n self.texPreamble(tutorial)\n self.texTutorialHeader(tutorial)\n\n for lecture in self.children(tutorial):\n self.texLectureHeader(lecture)\n\n for slide in self.children(lecture):\n self.texSlideHeader(slide)\n for section in slide.sections:\n self.texSlideSection(section)\n self.texSlideFooter(slide)\n\n self.texLectureFooter(lecture)\n\n self.texTutorialFooter(tutorial)\n self.texPostamble(tutorial)","def init():","def init(self, test_init_kwarg=None):\n\n logger.info(ackn_str)\n self.acknowledgements = ackn_str\n self.references = refs\n\n # Assign parameters for testing purposes\n self.new_thing = True\n self.test_init_kwarg = test_init_kwarg\n\n return","def __init__(self, args, n = 1):\n self.args = args\n self.n = n\n # The variable that holds a list of string representations of\n # randomly generated HTML documents\n self.doc_strings = []\n print_verbose(\n \"INFO : Generating random HTML documents...\",\n self.args.verbose,\n )\n # Generate a number of random HTML documents\n for i in range(self.n):\n self.doc_strings.append(self.generate_document())","def setUp(self):\n BuilderTestsMixin.setUp(self)\n self.builder = DocBuilder()\n self.howtoDir = FilePath(self.mktemp())\n self.howtoDir.createDirectory()\n self.templateFile = self.howtoDir.child(\"template.tpl\")\n self.templateFile.setContent(self.template)","def init(self) -> None:","def test_doc_init(self):\n expected = 'instantiates a new amenity'\n actual = Amenity.__init__.__doc__\n self.assertEqual(expected, actual)","def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\r\n pass","def __init__(self, cache_path=None, load=True):\n self.init(cache_path=cache_path, load=load)\n if not self.cache_path:\n return\n\n self.index = self.attributes['run_index']\n self.has_executed = False\n\n self.attrs = ExperimentAttributes(self.attributes)","def __init__(self, revisionNumber='', subject='', createdDateTime='', title='', category='', lastModifiedDateTime='', electronicAddress=None, status=None, ActivityRecords=None, docStatus=None, Measurements=None, *args, **kw_args):\n #: Revision number for this document.\n self.revisionNumber = revisionNumber\n\n #: Document subject.\n self.subject = subject\n\n #: Date and time that this document was created.\n self.createdDateTime = createdDateTime\n\n #: Document title.\n self.title = title\n\n #: Utility-specific categorisation of this document, according to their corporate standards, practices, and existing IT systems (e.g., for management of assets, maintenance, work, outage, customers, etc.).\n self.category = category\n\n #: Date and time this document was last modified. Documents may potentially be modified many times during their lifetime.\n self.lastModifiedDateTime = lastModifiedDateTime\n\n self.electronicAddress = electronicAddress\n\n self.status = status\n\n self._ActivityRecords = []\n self.ActivityRecords = [] if ActivityRecords is None else ActivityRecords\n\n self.docStatus = docStatus\n\n self._Measurements = []\n self.Measurements = [] if Measurements is None else Measurements\n\n super(Document, self).__init__(*args, **kw_args)","def __init__(self, document_path):\n self.tree = etree.parse(document_path)\n self.doc_id = get_doc_id(self.tree)\n for element_type in ('nodes', 'edges', 'layers'):\n self._extract_elements(self.tree, element_type)","def __init__(self, doc_root):\n self.doc_root = doc_root\n site = yaml_load('data/site.yaml')['site']\n self.site = site","def __init__(self, wf_ex):\n self.wf_ex = wf_ex\n self.wf_spec = spec_parser.get_workflow_spec(wf_ex.spec)","def __init__(self, num_docs, upper, lower, stemmer=True):\n\n # load data from json file\n self.num_docs = num_docs\n self.data = pd.read_json('data/arxiv-metadata-oai-snapshot.json', lines=True,\n nrows=self.num_docs)\n\n # create a list of list of documents from the abstracts, lowercase words, remove non-alphanumerical words\n self.stemmer = PorterStemmer() if stemmer == True else None\n self.docs = [self.preprocess(doc) for doc in self.data['abstract'].tolist()]\n\n # count occurrences per word and prune words that occur above some threshold\n self.counts = self.get_counts()\n self.prune(upper=upper, lower=lower)\n\n # obtain 'final' vocabulary, convert to integer ids.\n self.vocab = self.get_vocab()\n self.docs2ids()","def initialize_survey(self, **kwargs):","def put_init(self, title, num_dim, num_nodes, num_elem, num_elem_blk,\n num_node_sets, num_side_sets):\n self.dim = num_dim\n ierr = exolib.py_expini(self.exoid, title, num_dim, num_nodes,\n num_elem, num_elem_blk, num_node_sets,\n num_side_sets)\n if ierr:\n raise ExodusIIWriterError(\"Error initializing exodus output\")\n return","def __init__(self, exp_params, stamp_unique=True):\n self._main_thread = True\n self.params = copy.deepcopy(exp_params)\n self.params['class'] = self.__class__.__name__\n self._check_required_params()\n self.__check_exist_path()\n self.__create_folder(stamp_unique)\n set_experiment_logger(self.params['path_exp'], FILE_LOGS)\n # set stream logging to info level\n for lh in logging.getLogger().handlers:\n if isinstance(lh, logging.StreamHandler) and \\\n not isinstance(lh, logging.FileHandler):\n lh.setLevel(logging.INFO)\n logging.info('initialise experiment...')\n logging.info(string_dict(self.params, 'PARAMETERS:'))\n logging.info('COMPUTER: %r', computer_info())","def init(self):\n raise NotImplementedError","def init(self):\n raise NotImplementedError","def setup_parse(self, inputstring: str, document: nodes.document) -> None:\n self.inputstring = inputstring\n self.document = document","def __init__(self, *args):\n this = _libsbml.new_CompSBMLDocumentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def init(self) -> None:\n ...","def __init__(self, letter, name):\n\n import cdr\n from lxml import etree\n\n self.letter = letter\n path = \"/MiscellaneousDocument/MiscellaneousDocumentTitle\"\n query = f\"{path}/value eq {name}\"\n try:\n resp = cdr.search(\"guest\", query)\n except Exception as e:\n raise Exception(f\"failure loading misc doc {name!r}: {e}\")\n if not resp:\n raise Exception(f\"Miscellaneous document {name!r} not found\")\n self.docId = resp[0].docId\n try:\n doc = cdr.getDoc(\"guest\", self.docId, getObject=True)\n except Exception as e:\n raise Exception(f\"Retrieving {self.docId}: {e}\")\n self.root = etree.fromstring(doc.xml)","def __init__(self, template=site_template):\n self.template = template\n self.template_file = None\n if not os.path.exists(self.template):\n raise OpagMissingPrecondition, \"%s does not exist\" % self.template","def preproc_doc(document):\n\n # Each document is a list of lines\n tokenizer = tokenization.FullTokenizer(\n vocab_file=FLAGS.vocab_file, do_lower_case=FLAGS.do_lower_case)\n\n # set a random seed for reproducability\n # since this function is run in parallel, if we hardcode a seed, all\n # documents will have the same permutations. Instead we use the hash of the\n # first sentence as the seed so it is different for each document and it\n # is still reproducible.\n hash_object = hashlib.md5(document[0])\n rng = random.Random(int(hash_object.hexdigest(), 16) % (10**8))\n\n # Each document is composed of a list of sentences. We create paragraphs\n # by keeping together sentences on the same line and adding adjacent sentences\n # if there are fewer than 5 to form the paragraph.\n # The utility functions below expect the document to be split by paragraphs.\n list_of_paragraphs = []\n paragraph = []\n for line in document:\n line = tokenization.convert_to_unicode(line)\n line = line.replace(u\"\\u2018\", \"'\").replace(u\"\\u2019\", \"'\")\n sents = split_line_by_sentences(line)\n for sent in sents:\n tokens = tokenizer.tokenize(sent)\n if tokens:\n paragraph.append(tokens)\n if len(paragraph) > 5:\n list_of_paragraphs.append(paragraph)\n paragraph = []\n\n # In case of any empty paragraphs, remove them.\n list_of_paragraphs = [x for x in list_of_paragraphs if x]\n\n # Convert the list of paragraphs into TrainingInstance object\n # See preprocessing_utils.py for definition\n if FLAGS.format == FORMAT_BINARY:\n instances = create_instances_from_document(list_of_paragraphs,\n FLAGS.max_seq_length, rng)\n elif FLAGS.format == FORMAT_PARAGRAPH:\n instances = create_paragraph_order_from_document(list_of_paragraphs,\n FLAGS.max_seq_length, rng)\n\n # Convert token lists into ids and add any needed tokens and padding for BERT\n tf_examples = [\n convert_instance_to_tf_example(tokenizer, instance,\n FLAGS.max_seq_length)[0]\n for instance in instances\n ]\n\n # Serialize TFExample for writing to file.\n tf_examples = [example.SerializeToString() for example in tf_examples]\n\n return tf_examples","def __init__(self, *args):\n this = _libsbml.new_SBMLDocumentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def test_loading_document(self):","def __init__(self, morphit):\r\n self.MorphItFileName = morphit\r\n\r\n self.verbTags = ['VER', 'AUX', 'MOD', 'CAU', 'ASP']\r\n self.words = self.LoadWords()\r\n if not self.words:\r\n self.ReadMorphit()\r\n self.SaveWords()","def __init__(self, iReader):\n self.ireader = iReader\n self.num_of_doc = iReader.getNumberOfDocuments()","def __init__(self, setupName):\n\t\timport revitron\n\t\tself.options = revitron.DB.DWGExportOptions().GetPredefinedOptions(\n\t\t revitron.DOC,\n\t\t setupName\n\t\t)","def init():\n\n # Complete our stop words set.\n add_extra_words()\n\n model = read_model(MODEL_FILE)\n model_keys = list(model.keys())\n\n # Basic random.\n new_comment = generate_comment(model=model, order=2,\n number_of_sentences=2,\n initial_prefix=random.choice(model_keys))\n\n # Selective random.\n new_comment = generate_comment(model=model, order=2,\n number_of_sentences=2,\n initial_prefix=get_prefix(model_keys))\n\n # Context-aware.\n new_comment = generate_comment(model=model, order=2,\n number_of_sentences=2,\n initial_prefix=get_prefix_with_context(model, \"Agent_Phantom\"))\n\n print(new_comment)","def setUp(self):\n self.titulo_eleitoral = docbr.TituloEleitoral()","def __init__(self):\n # Initialise class attributes (visibility ease)\n self.__corpus__ = None\n self.__pron_det_pos_words__ = None\n self.__triples_corpus__ = None\n self.__entities_in_doc__ = None\n self.__wvmodel__ = None\n \n # For purpose of parsing relation triplets later\n # Load pretrained embedding model\n #plog('Loading pretrained word embeddings. This will take some time to load...')\n #self.__wvmodel__ = api.load('fasttext-wiki-news-subwords-300')\n #plog('Pretrained word embeddings loaded!')","def test_api_document_create_instructor(self):\n playlist = core_factories.PlaylistFactory()\n\n jwt_token = InstructorOrAdminLtiTokenFactory(playlist=playlist)\n\n self.assertEqual(MarkdownDocument.objects.count(), 0)\n\n response = self.client.post(\n \"/api/markdown-documents/\",\n {\n \"lti_id\": \"document_one\",\n \"playlist\": str(playlist.id),\n \"title\": \"Some document\",\n },\n HTTP_AUTHORIZATION=f\"Bearer {jwt_token}\",\n )\n\n self.assertEqual(MarkdownDocument.objects.count(), 1)\n self.assertEqual(response.status_code, 201)\n document = MarkdownDocument.objects.first()\n self.assertEqual(\n response.json(),\n {\n \"id\": str(document.id),\n \"images\": [],\n \"is_draft\": True,\n \"playlist\": {\n \"id\": str(playlist.id),\n \"lti_id\": playlist.lti_id,\n \"title\": playlist.title,\n },\n \"position\": 0,\n \"rendering_options\": {},\n \"translations\": [\n {\n \"content\": \"\",\n \"language_code\": \"en\",\n \"rendered_content\": \"\",\n \"title\": \"Some document\",\n }\n ],\n },\n )","def __init__(self, temboo_session):\n super(DownloadDocument, self).__init__(temboo_session, '/Library/Zoho/Writer/DownloadDocument')","def __init__(self, template_content, section_type):\n self.helpers = Documentation()\n self.template_content = template_content\n self.section_type = section_type\n self.stype = self.section_type\n self.children = []","def __init__(self, html, out_file):\n self.html = html\n self.out_file = out_file\n self.env = Environment(loader=PackageLoader('html2docx', 'templates'))\n self.template_names = {\n 'content_types': '[Content_Types].xml',\n 'apps': 'docProps/app.xml',\n 'core': 'docProps/core.xml',\n 'rels': '_rels/.rels',\n 'document': 'word/document.xml',\n 'fonts': 'word/fontTable.xml',\n 'document_rels': 'word/_rels/document.xml.rels',\n 'settings': 'word/settings.xml',\n 'styles': 'word/styles.xml',\n }\n self.document_state = []\n self.visited = set()","def prepareDocument(self):\n self.checkSyntaxDocument()","def __init__(self, run_config):\n print('Initializing logs...')\n log_root = run_config['log_root_path']\n self._save_iter = run_config['save_iter']\n self._best_epoch = False\n if run_config['resume_path']:\n # resume an old experiment\n self.log_dir = run_config['resume_path']\n if os.path.exists(os.path.join(log_root, self.log_dir)):\n self.log_path = os.path.join(log_root, self.log_dir)\n print(' Resuming experiment ' + self.log_dir)\n else:\n raise Exception('Experiment folder ' + self.log_dir + ' not found.')\n else:\n # start a new experiment\n if 'log_dir' not in run_config:\n self.log_dir = ''\n else:\n self.log_dir = run_config['log_dir']\n self.log_dir += strftime(\"%b_%d_%Y_%H_%M_%S\") + '/'\n self.log_path = os.path.join(log_root, self.log_dir)\n os.makedirs(self.log_path)\n os.system(\"rsync -au --include '*/' --include '*.py' --exclude '*' . \" + self.log_path + \"source\")\n os.makedirs(os.path.join(self.log_path, 'metrics'))\n os.makedirs(os.path.join(self.log_path, 'checkpoints'))\n self.epoch = 1\n print(' Starting experiment ' + self.log_dir)","def initialise(self):","def __init__(self, run):\n dict.__init__(self)\n self.read(run)","def setUp(self):\n self.new_article = Articles(\"Politico\",\"By Benjamin Din\", \"2024 GOP contenders collect cash\", \"Republicans who led efforts to overturn the election results in January did especially well, according to the latest quarterly FEC filings.\", \"https://www.politico.com/news/2021/04/15/2024-gop-cash-fec-482240\", \"https://static.politico.com/90/a6/2eff74ff4d69b7aee677b55ae6e2/gettyimages-1230713929.jpg\", \"2021-04-16T02:10:04Z\")","def __init__(self, template, file_path):\n self.navigator = Navigator()\n self.template = template\n self.file_path = file_path\n self.template_data = read_xml_get_json(template, ordered_dict=True)\n self.data = read_xml_get_json(file_path, ordered_dict=True)\n self.output = {\"status\": True, \"message\": \"\"}\n self.root = \"Testcase\"\n self.major = (\"Details\", \"Requirements\", \"Steps\")","def test_init_experiment(self):\n optimizer = \"RandomSearch\"\n name = \"test_init_experiment\"\n param_defs = {\n \"x\": MinMaxNumericParamDef(0, 1),\n \"name\": NominalParamDef([\"A\", \"B\", \"C\"])\n }\n minimization = True\n\n LAss = PrettyLabAssistant()\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\n\n exp_ass = LAss.exp_assistants[name]\n\n assert_equal(exp_ass.optimizer, optimizer)\n assert_is_none(exp_ass.optimizer_arguments, None)\n assert_equal(exp_ass.experiment.minimization_problem, minimization)\n with assert_raises(ValueError):\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)","def newExperiment(self):\n experiment = Experiment()\n newtitle = 'Untitled ' + self.getNextUntitled()\n experimentFrame = SequenceFrame(self, experiment, True, newtitle)\n experiment.setInteractionParameters(parentFrame=experimentFrame,\n graphManagerClass=StandardGraphManager)\n self.frames.append(experimentFrame)\n self.names.append(newtitle)\n log.info('Created experiment ' + newtitle)\n experimentFrame.Show()\n testFrame = tf.TestingFrame(experimentFrame, experiment)\n testFrame.Show()\n self.Show(False)","def __init__(self, document, builder):\n LaTeXTranslator.__init__(self, document, builder)\n self.elements[\"maketitle\"] = r\"\\maketitle\"\n self.elements[\"makeindex\"] = \"\"\n self.elements[\"printindex\"] = \"\"\n self.elements[\"tableofcontents\"] = \"\"\n self.elements[\"wrapperclass\"] = \"beamer\"\n self.elements[\"beamer_theme\"] = builder.config_options[\"beamer_theme\"]\n self.section_levels = [\n r\"\\begin{frame}\",\n r\"\\subsection\",\n r\"\\subsubsection\",\n ]\n self.elements[\"allowframebreaks\"] = \\\n builder.config_options[\"allowframebreaks\"]","def __init__(self, experiment_dir):\n self.experiment_dir = pathlib.Path(experiment_dir)\n\n parameters_data = parse_parameters(experiment_dir)\n self.__dict__ = {**self.__dict__, **parameters_data}","def __init__(self, contents: str) -> None:\n super().__init__(contents)","def setup_document(document_name=\"fSCAD-Preview\"):\n preview_doc = None\n saved_camera = None\n saved_units = None\n for document in app().documents:\n if document.name == document_name:\n preview_doc = document\n break\n if preview_doc is not None:\n preview_doc.activate()\n saved_camera = app().activeViewport.camera\n saved_units = design().fusionUnitsManager.distanceDisplayUnits\n preview_doc.close(False)\n\n preview_doc = app().documents.add(adsk.core.DocumentTypes.FusionDesignDocumentType)\n preview_doc.name = document_name\n preview_doc.activate()\n if saved_camera is not None:\n is_smooth_transition_bak = saved_camera.isSmoothTransition\n saved_camera.isSmoothTransition = False\n app().activeViewport.camera = saved_camera\n saved_camera.isSmoothTransition = is_smooth_transition_bak\n app().activeViewport.camera = saved_camera\n if saved_units is not None:\n design().fusionUnitsManager.distanceDisplayUnits = saved_units\n design().designType = adsk.fusion.DesignTypes.DirectDesignType","def setUp(self):\n self.m = m = random.randint(1, 100)\n self.n = n = random.randint(1, 100)\n self.sig = sig = Signature(\"name\", Dim(\"m\"), Dim(\"n\"),\n sData(\"A\", \"ldA * n\"), Ld(\"ldA\", \"m\"),\n dData(\"B\", \"ldB * m\"), Ld(\"ldB\", \"m\"),\n cData(\"C\", \"ldC * n\"), Ld(\"ldC\", \"n\"))\n self.ex = ex = Experiment()\n ex.calls = [sig(m, n, \"X\", None, \"Y\", None, \"Z\", None)]\n ex.infer_lds()\n self.i = Symbol(\"i\")\n self.j = Symbol(\"j\")","def __init__(self):\n self._create_options()\n self._create_sections()","def __init__(self, thesis, first=\"\", last='', major='CIS'):\r\n super().__init__(first, last, major)\r\n self.thesis = thesis","def __init__(self, html_contents):\n self.doc = html.document_fromstring(html_contents)","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def _problem_run_experiments_initialise(self):\n pass","def __init__(self, experiment, sigma_b, sigma_m, n_sigma):\n self.experiment = experiment\n self.sigma_b = sigma_b\n self.sigma_m = sigma_m\n self.n_sigma = n_sigma","def __init__(self, name):\n config = Config()\n super(TestTemplate, self).__init__(name)\n self.doc_dict = None\n func = getattr(self, name)\n self.get_test_doc(name, func.__doc__)\n # ASSIGN VALUES TO CONFIG\n config['name'] = self.doc_dict['name']\n logger.info(\"NAME: {}\".format(config['name']))\n config['title'] = self.doc_dict['title']\n logger.info(\"TITLE: {}\".format(config['title']))\n config['test'] = self.doc_dict['test']\n logger.info(\"TEST: {}\".format(config['test']))\n config['bug'] = self.doc_dict['bug']\n logger.info(\"BUG: {}\".format(config['bug']))","def __init__(self, spec):\n self.spec = spec"],"string":"[\n \"def __init__(self, document):\\n\\n self._settemplates(self.onecol, self.twocol)\\n assert document.type_key == 'cim.2.designing.Project'\\n self.doc = document\\n\\n # We will populate the \\\"mip\\\" variable with the mip era\\n self.mips = 'CMIP6'\\n\\n self.related = []\\n for r in self.doc.required_experiments:\\n self.related.append(esd.retrieve(r.id))\",\n \"def experiment_init(self):\\n pass\",\n \"def experiment_init(self):\\n raise NotImplementedError(\\\"this needs to be implemented!\\\")\",\n \"def setUp(self):\\n super(SimpleDocumentTestCase, self).setUp()\\n self.document = SimpleDocument()\\n self.document.description = u\\\"body text\\\"\\n self.document.title = u\\\"document title\\\"\",\n \"def setUp(self):\\n super(SimpleDocumentAnnotationTestCase, self).setUp()\\n self.document = SimpleDocument()\\n self.document.description = u\\\"body text\\\"\\n self.document.title = u\\\"document title\\\"\",\n \"def __init__(self, experiment_data):\\n self._experiment_data = experiment_data\",\n \"def create(init_document: 'Document') -> 'DocumentArray':\",\n \"def test_init(self):\\n ex = Experiment(note=\\\"Test\\\")\\n self.assertEqual(ex.note, \\\"Test\\\")\",\n \"def __init__(self, docs, **kargs): # [todo]\\n self.cohort = kargs.get('cohort', None)\\n self.nDoc = len(docs)\\n\\n return\",\n \"def experiments_init(self):\\n pass\",\n \"def setUp(self):\\n self.docCounter = 0\",\n \"def Init(self, *args):\\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)\",\n \"def __init__(self, doc):\\n\\n self.doc = doc\\n if self.doc.doi:\\n self._populate()\\n self.populated = True\\n else:\\n self.populated = False\",\n \"def __init__(self, main_doc):\\n\\t\\tif not isinstance(main_doc, Document):\\n\\t\\t\\traise TypeError('term must be of type Document')\\n\\t\\tself.main_doc = main_doc\\n\\t\\tself.env_docs = []\",\n \"def init_doc(self):\\n raise NotImplementedError()\",\n \"def setUp(self):\\n self._vocab = np.array([\\\"one\\\", \\\"two\\\", \\\"three\\\", \\\"four\\\",\\n \\\"five\\\", \\\"six\\\", \\\"seven\\\", \\\"eight\\\", \\\"nine\\\"])\\n self._embedding_dim = 2\\n\\n self._default_config = {\\n \\\"vocab\\\": self._vocab,\\n \\\"embedding_dim\\\": self._embedding_dim,\\n \\\"position_encoding\\\": None\\n }\",\n \"def __init__(self, name, training_documents):\\n self._name = name\\n self._training_documents = training_documents\",\n \"def __init__(self, run_id: str, doc: Dict, service: APIFactory):\\n self.run_id = run_id\\n self.file_id = doc['id']\\n self.name = doc['name']\\n self.title = doc.get('title', self.name)\\n self.caption = doc.get('caption')\\n self.format = doc.get('format', {})\\n self.service = service\",\n \"def build_document(self):\\n pass\",\n \"def __init__(self, doc=None, lda=None, max_doc_len=None, num_topics=None, gamma=None, lhood=None):\\n self.doc = doc\\n self.lda = lda\\n self.gamma = gamma\\n self.lhood = lhood\\n if self.gamma is None:\\n self.gamma = np.zeros(num_topics)\\n if self.lhood is None:\\n self.lhood = np.zeros(num_topics + 1)\\n\\n if max_doc_len is not None and num_topics is not None:\\n self.phi = np.zeros((max_doc_len, num_topics))\\n self.log_phi = np.zeros((max_doc_len, num_topics))\\n\\n # the following are class variables which are to be integrated during Document Influence Model\\n\\n self.doc_weight = None\\n self.renormalized_doc_weight = None\",\n \"def __init__(self, experiment, **kwargs):\\n \\n # retrieve which experiment to run\\n experiment_function = getattr(self, experiment)\\n\\n if kwargs:\\n kwargs['experiment']=experiment\\n experiment_function(**kwargs)\\n\\n else:\\n kwargs={'experiment':experiment}\\n experiment_function(**kwargs)\",\n \"def __init__(self):\\n\\n # Load embeddings index\\n self.embeddings = self.load()\\n self.console = Console()\",\n \"def __init__(self, doc, target=None, stylesheet=\\\"\\\"):\\n self.document = doc\\n self.stylesheet = stylesheet\\n self.target = target if target is not None else StringIO()\",\n \"def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\\n name=None, **kwargs):\\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\\n self.artDirection = artDirection\\n self.path = path # Optional path to markdown file, if it has content.\\n self.mdText = mdText # Optional markdown string.\\n self.name = name or 'Untitled'\\n self.startPage = startPage\",\n \"def startDocument(self):\\n pass\",\n \"def startDocument(self):\\n pass\",\n \"def __init__(self, *args):\\n this = _libsbml.new_SBMLDocument(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def document(self):\\n ...\",\n \"def initDocTagText(self):\\n self.doc, self.tag, self.text = Doc().tagtext()\",\n \"def start(self) -> None:\\n\\n self.doc = self.doc + r'''\\n \\\\documentclass[\\n 10pt, % Main document font size\\n a4paper, % Paper type, use 'letterpaper' for US Letter paper\\n ]{scrartcl}\\n\\n \\\\usepackage{graphicx}\\n \\\\usepackage{epstopdf}\\n \\\\usepackage{float}\\n \\\\usepackage[scale=0.75]{geometry} % Reduce document margins\\n \\\\usepackage{hyperref}\\n \\\\usepackage{longtable}\\n\\n \\\\begin{document}\\n\\n \\\\title{Automatic Exploratory Data Analysis} % The article title\\n\\n \\\\subtitle{Study Case} % Uncomment to display a subtitle\\n\\n \\\\author{Jacob} % The article author(s) - author affiliations need to be specified in the AUTHOR AFFILIATIONS block\\\\\\n\\n \\\\maketitle % Print the title/author/date block\\n\\n \\\\newpage\\n \\\\tableofcontents % Print the table of contents\\n\\n \\\\newpage\\n \\\\listoffigures % Print the list of figures\\n\\n \\\\newpage\\n \\\\listoftables % Print the list of tables\\n '''\",\n \"def new_document(self) -> nodes.document:\\n document = super().new_document()\\n document.__class__ = addnodes.document # replace the class with patched version\\n\\n # substitute transformer\\n document.transformer = SphinxTransformer(document)\\n document.transformer.set_environment(self.settings.env)\\n\\n # substitute reporter\\n reporter = document.reporter\\n document.reporter = LoggingReporter.from_reporter(reporter)\\n\\n return document\",\n \"def __init__(self, doc_set):\\n self.__doc_set = doc_set\\n self.__preprocessor = InputPreprocessor(doc_set)\",\n \"def __init__(self, documents_path):\\n self.documents = []\\n self.vocabulary = []\\n self.likelihoods = []\\n self.documents_path = documents_path\\n self.term_doc_matrix = None \\n self.document_topic_prob = None # P(z | d)\\n self.topic_word_prob = None # P(w | z)\\n self.topic_prob = None # P(z | d, w)\\n\\n self.number_of_documents = 0\\n self.vocabulary_size = 0\",\n \"def __init__(self, txt='', unicodeEncoding='utf-8'):\\n # __document capture the document level structure\\n # for each sentence and then put in the archives when the next sentence\\n # is processed\\n super(ConTextMarkup, self).__init__(__txt=None,\\n __rawtxt=txt,\\n __scope=None,\\n __SCOPEUPDATED=False)\\n self.__document = nx.DiGraph()\\n self.__document.add_node(\\\"top\\\", category=\\\"document\\\")\\n self.__VERBOSE = False\\n self.__tagID = 0\\n self.__unicodeEncoding = unicodeEncoding\",\n \"def __init__(self, document_path):\\n super(SaltXMIGraph, self).__init__()\\n self.tree = etree.parse(document_path)\\n self.doc_id = get_doc_id(self.tree)\\n for i, node_element in enumerate(get_elements(self.tree, 'nodes')):\\n node = create_class_instance(node_element, i, self.doc_id)\\n self.add_node(i, node.__dict__)\\n for i, edge_element in enumerate(get_elements(self.tree, 'edges')):\\n edge = create_class_instance(edge_element, i, self.doc_id)\\n self.add_edge(edge.source, edge.target, edge.__dict__)\",\n \"def __init__(self, tutorial):\\n self._tex = \\\"\\\"\\n\\n self.texPreamble(tutorial)\\n self.texTutorialHeader(tutorial)\\n\\n for lecture in self.children(tutorial):\\n self.texLectureHeader(lecture)\\n\\n for slide in self.children(lecture):\\n self.texSlideHeader(slide)\\n for section in slide.sections:\\n self.texSlideSection(section)\\n self.texSlideFooter(slide)\\n\\n self.texLectureFooter(lecture)\\n\\n self.texTutorialFooter(tutorial)\\n self.texPostamble(tutorial)\",\n \"def init():\",\n \"def init(self, test_init_kwarg=None):\\n\\n logger.info(ackn_str)\\n self.acknowledgements = ackn_str\\n self.references = refs\\n\\n # Assign parameters for testing purposes\\n self.new_thing = True\\n self.test_init_kwarg = test_init_kwarg\\n\\n return\",\n \"def __init__(self, args, n = 1):\\n self.args = args\\n self.n = n\\n # The variable that holds a list of string representations of\\n # randomly generated HTML documents\\n self.doc_strings = []\\n print_verbose(\\n \\\"INFO : Generating random HTML documents...\\\",\\n self.args.verbose,\\n )\\n # Generate a number of random HTML documents\\n for i in range(self.n):\\n self.doc_strings.append(self.generate_document())\",\n \"def setUp(self):\\n BuilderTestsMixin.setUp(self)\\n self.builder = DocBuilder()\\n self.howtoDir = FilePath(self.mktemp())\\n self.howtoDir.createDirectory()\\n self.templateFile = self.howtoDir.child(\\\"template.tpl\\\")\\n self.templateFile.setContent(self.template)\",\n \"def init(self) -> None:\",\n \"def test_doc_init(self):\\n expected = 'instantiates a new amenity'\\n actual = Amenity.__init__.__doc__\\n self.assertEqual(expected, actual)\",\n \"def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\\r\\n pass\",\n \"def __init__(self, cache_path=None, load=True):\\n self.init(cache_path=cache_path, load=load)\\n if not self.cache_path:\\n return\\n\\n self.index = self.attributes['run_index']\\n self.has_executed = False\\n\\n self.attrs = ExperimentAttributes(self.attributes)\",\n \"def __init__(self, revisionNumber='', subject='', createdDateTime='', title='', category='', lastModifiedDateTime='', electronicAddress=None, status=None, ActivityRecords=None, docStatus=None, Measurements=None, *args, **kw_args):\\n #: Revision number for this document.\\n self.revisionNumber = revisionNumber\\n\\n #: Document subject.\\n self.subject = subject\\n\\n #: Date and time that this document was created.\\n self.createdDateTime = createdDateTime\\n\\n #: Document title.\\n self.title = title\\n\\n #: Utility-specific categorisation of this document, according to their corporate standards, practices, and existing IT systems (e.g., for management of assets, maintenance, work, outage, customers, etc.).\\n self.category = category\\n\\n #: Date and time this document was last modified. Documents may potentially be modified many times during their lifetime.\\n self.lastModifiedDateTime = lastModifiedDateTime\\n\\n self.electronicAddress = electronicAddress\\n\\n self.status = status\\n\\n self._ActivityRecords = []\\n self.ActivityRecords = [] if ActivityRecords is None else ActivityRecords\\n\\n self.docStatus = docStatus\\n\\n self._Measurements = []\\n self.Measurements = [] if Measurements is None else Measurements\\n\\n super(Document, self).__init__(*args, **kw_args)\",\n \"def __init__(self, document_path):\\n self.tree = etree.parse(document_path)\\n self.doc_id = get_doc_id(self.tree)\\n for element_type in ('nodes', 'edges', 'layers'):\\n self._extract_elements(self.tree, element_type)\",\n \"def __init__(self, doc_root):\\n self.doc_root = doc_root\\n site = yaml_load('data/site.yaml')['site']\\n self.site = site\",\n \"def __init__(self, wf_ex):\\n self.wf_ex = wf_ex\\n self.wf_spec = spec_parser.get_workflow_spec(wf_ex.spec)\",\n \"def __init__(self, num_docs, upper, lower, stemmer=True):\\n\\n # load data from json file\\n self.num_docs = num_docs\\n self.data = pd.read_json('data/arxiv-metadata-oai-snapshot.json', lines=True,\\n nrows=self.num_docs)\\n\\n # create a list of list of documents from the abstracts, lowercase words, remove non-alphanumerical words\\n self.stemmer = PorterStemmer() if stemmer == True else None\\n self.docs = [self.preprocess(doc) for doc in self.data['abstract'].tolist()]\\n\\n # count occurrences per word and prune words that occur above some threshold\\n self.counts = self.get_counts()\\n self.prune(upper=upper, lower=lower)\\n\\n # obtain 'final' vocabulary, convert to integer ids.\\n self.vocab = self.get_vocab()\\n self.docs2ids()\",\n \"def initialize_survey(self, **kwargs):\",\n \"def put_init(self, title, num_dim, num_nodes, num_elem, num_elem_blk,\\n num_node_sets, num_side_sets):\\n self.dim = num_dim\\n ierr = exolib.py_expini(self.exoid, title, num_dim, num_nodes,\\n num_elem, num_elem_blk, num_node_sets,\\n num_side_sets)\\n if ierr:\\n raise ExodusIIWriterError(\\\"Error initializing exodus output\\\")\\n return\",\n \"def __init__(self, exp_params, stamp_unique=True):\\n self._main_thread = True\\n self.params = copy.deepcopy(exp_params)\\n self.params['class'] = self.__class__.__name__\\n self._check_required_params()\\n self.__check_exist_path()\\n self.__create_folder(stamp_unique)\\n set_experiment_logger(self.params['path_exp'], FILE_LOGS)\\n # set stream logging to info level\\n for lh in logging.getLogger().handlers:\\n if isinstance(lh, logging.StreamHandler) and \\\\\\n not isinstance(lh, logging.FileHandler):\\n lh.setLevel(logging.INFO)\\n logging.info('initialise experiment...')\\n logging.info(string_dict(self.params, 'PARAMETERS:'))\\n logging.info('COMPUTER: %r', computer_info())\",\n \"def init(self):\\n raise NotImplementedError\",\n \"def init(self):\\n raise NotImplementedError\",\n \"def setup_parse(self, inputstring: str, document: nodes.document) -> None:\\n self.inputstring = inputstring\\n self.document = document\",\n \"def __init__(self, *args):\\n this = _libsbml.new_CompSBMLDocumentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def init(self) -> None:\\n ...\",\n \"def __init__(self, letter, name):\\n\\n import cdr\\n from lxml import etree\\n\\n self.letter = letter\\n path = \\\"/MiscellaneousDocument/MiscellaneousDocumentTitle\\\"\\n query = f\\\"{path}/value eq {name}\\\"\\n try:\\n resp = cdr.search(\\\"guest\\\", query)\\n except Exception as e:\\n raise Exception(f\\\"failure loading misc doc {name!r}: {e}\\\")\\n if not resp:\\n raise Exception(f\\\"Miscellaneous document {name!r} not found\\\")\\n self.docId = resp[0].docId\\n try:\\n doc = cdr.getDoc(\\\"guest\\\", self.docId, getObject=True)\\n except Exception as e:\\n raise Exception(f\\\"Retrieving {self.docId}: {e}\\\")\\n self.root = etree.fromstring(doc.xml)\",\n \"def __init__(self, template=site_template):\\n self.template = template\\n self.template_file = None\\n if not os.path.exists(self.template):\\n raise OpagMissingPrecondition, \\\"%s does not exist\\\" % self.template\",\n \"def preproc_doc(document):\\n\\n # Each document is a list of lines\\n tokenizer = tokenization.FullTokenizer(\\n vocab_file=FLAGS.vocab_file, do_lower_case=FLAGS.do_lower_case)\\n\\n # set a random seed for reproducability\\n # since this function is run in parallel, if we hardcode a seed, all\\n # documents will have the same permutations. Instead we use the hash of the\\n # first sentence as the seed so it is different for each document and it\\n # is still reproducible.\\n hash_object = hashlib.md5(document[0])\\n rng = random.Random(int(hash_object.hexdigest(), 16) % (10**8))\\n\\n # Each document is composed of a list of sentences. We create paragraphs\\n # by keeping together sentences on the same line and adding adjacent sentences\\n # if there are fewer than 5 to form the paragraph.\\n # The utility functions below expect the document to be split by paragraphs.\\n list_of_paragraphs = []\\n paragraph = []\\n for line in document:\\n line = tokenization.convert_to_unicode(line)\\n line = line.replace(u\\\"\\\\u2018\\\", \\\"'\\\").replace(u\\\"\\\\u2019\\\", \\\"'\\\")\\n sents = split_line_by_sentences(line)\\n for sent in sents:\\n tokens = tokenizer.tokenize(sent)\\n if tokens:\\n paragraph.append(tokens)\\n if len(paragraph) > 5:\\n list_of_paragraphs.append(paragraph)\\n paragraph = []\\n\\n # In case of any empty paragraphs, remove them.\\n list_of_paragraphs = [x for x in list_of_paragraphs if x]\\n\\n # Convert the list of paragraphs into TrainingInstance object\\n # See preprocessing_utils.py for definition\\n if FLAGS.format == FORMAT_BINARY:\\n instances = create_instances_from_document(list_of_paragraphs,\\n FLAGS.max_seq_length, rng)\\n elif FLAGS.format == FORMAT_PARAGRAPH:\\n instances = create_paragraph_order_from_document(list_of_paragraphs,\\n FLAGS.max_seq_length, rng)\\n\\n # Convert token lists into ids and add any needed tokens and padding for BERT\\n tf_examples = [\\n convert_instance_to_tf_example(tokenizer, instance,\\n FLAGS.max_seq_length)[0]\\n for instance in instances\\n ]\\n\\n # Serialize TFExample for writing to file.\\n tf_examples = [example.SerializeToString() for example in tf_examples]\\n\\n return tf_examples\",\n \"def __init__(self, *args):\\n this = _libsbml.new_SBMLDocumentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def test_loading_document(self):\",\n \"def __init__(self, morphit):\\r\\n self.MorphItFileName = morphit\\r\\n\\r\\n self.verbTags = ['VER', 'AUX', 'MOD', 'CAU', 'ASP']\\r\\n self.words = self.LoadWords()\\r\\n if not self.words:\\r\\n self.ReadMorphit()\\r\\n self.SaveWords()\",\n \"def __init__(self, iReader):\\n self.ireader = iReader\\n self.num_of_doc = iReader.getNumberOfDocuments()\",\n \"def __init__(self, setupName):\\n\\t\\timport revitron\\n\\t\\tself.options = revitron.DB.DWGExportOptions().GetPredefinedOptions(\\n\\t\\t revitron.DOC,\\n\\t\\t setupName\\n\\t\\t)\",\n \"def init():\\n\\n # Complete our stop words set.\\n add_extra_words()\\n\\n model = read_model(MODEL_FILE)\\n model_keys = list(model.keys())\\n\\n # Basic random.\\n new_comment = generate_comment(model=model, order=2,\\n number_of_sentences=2,\\n initial_prefix=random.choice(model_keys))\\n\\n # Selective random.\\n new_comment = generate_comment(model=model, order=2,\\n number_of_sentences=2,\\n initial_prefix=get_prefix(model_keys))\\n\\n # Context-aware.\\n new_comment = generate_comment(model=model, order=2,\\n number_of_sentences=2,\\n initial_prefix=get_prefix_with_context(model, \\\"Agent_Phantom\\\"))\\n\\n print(new_comment)\",\n \"def setUp(self):\\n self.titulo_eleitoral = docbr.TituloEleitoral()\",\n \"def __init__(self):\\n # Initialise class attributes (visibility ease)\\n self.__corpus__ = None\\n self.__pron_det_pos_words__ = None\\n self.__triples_corpus__ = None\\n self.__entities_in_doc__ = None\\n self.__wvmodel__ = None\\n \\n # For purpose of parsing relation triplets later\\n # Load pretrained embedding model\\n #plog('Loading pretrained word embeddings. This will take some time to load...')\\n #self.__wvmodel__ = api.load('fasttext-wiki-news-subwords-300')\\n #plog('Pretrained word embeddings loaded!')\",\n \"def test_api_document_create_instructor(self):\\n playlist = core_factories.PlaylistFactory()\\n\\n jwt_token = InstructorOrAdminLtiTokenFactory(playlist=playlist)\\n\\n self.assertEqual(MarkdownDocument.objects.count(), 0)\\n\\n response = self.client.post(\\n \\\"/api/markdown-documents/\\\",\\n {\\n \\\"lti_id\\\": \\\"document_one\\\",\\n \\\"playlist\\\": str(playlist.id),\\n \\\"title\\\": \\\"Some document\\\",\\n },\\n HTTP_AUTHORIZATION=f\\\"Bearer {jwt_token}\\\",\\n )\\n\\n self.assertEqual(MarkdownDocument.objects.count(), 1)\\n self.assertEqual(response.status_code, 201)\\n document = MarkdownDocument.objects.first()\\n self.assertEqual(\\n response.json(),\\n {\\n \\\"id\\\": str(document.id),\\n \\\"images\\\": [],\\n \\\"is_draft\\\": True,\\n \\\"playlist\\\": {\\n \\\"id\\\": str(playlist.id),\\n \\\"lti_id\\\": playlist.lti_id,\\n \\\"title\\\": playlist.title,\\n },\\n \\\"position\\\": 0,\\n \\\"rendering_options\\\": {},\\n \\\"translations\\\": [\\n {\\n \\\"content\\\": \\\"\\\",\\n \\\"language_code\\\": \\\"en\\\",\\n \\\"rendered_content\\\": \\\"\\\",\\n \\\"title\\\": \\\"Some document\\\",\\n }\\n ],\\n },\\n )\",\n \"def __init__(self, temboo_session):\\n super(DownloadDocument, self).__init__(temboo_session, '/Library/Zoho/Writer/DownloadDocument')\",\n \"def __init__(self, template_content, section_type):\\n self.helpers = Documentation()\\n self.template_content = template_content\\n self.section_type = section_type\\n self.stype = self.section_type\\n self.children = []\",\n \"def __init__(self, html, out_file):\\n self.html = html\\n self.out_file = out_file\\n self.env = Environment(loader=PackageLoader('html2docx', 'templates'))\\n self.template_names = {\\n 'content_types': '[Content_Types].xml',\\n 'apps': 'docProps/app.xml',\\n 'core': 'docProps/core.xml',\\n 'rels': '_rels/.rels',\\n 'document': 'word/document.xml',\\n 'fonts': 'word/fontTable.xml',\\n 'document_rels': 'word/_rels/document.xml.rels',\\n 'settings': 'word/settings.xml',\\n 'styles': 'word/styles.xml',\\n }\\n self.document_state = []\\n self.visited = set()\",\n \"def prepareDocument(self):\\n self.checkSyntaxDocument()\",\n \"def __init__(self, run_config):\\n print('Initializing logs...')\\n log_root = run_config['log_root_path']\\n self._save_iter = run_config['save_iter']\\n self._best_epoch = False\\n if run_config['resume_path']:\\n # resume an old experiment\\n self.log_dir = run_config['resume_path']\\n if os.path.exists(os.path.join(log_root, self.log_dir)):\\n self.log_path = os.path.join(log_root, self.log_dir)\\n print(' Resuming experiment ' + self.log_dir)\\n else:\\n raise Exception('Experiment folder ' + self.log_dir + ' not found.')\\n else:\\n # start a new experiment\\n if 'log_dir' not in run_config:\\n self.log_dir = ''\\n else:\\n self.log_dir = run_config['log_dir']\\n self.log_dir += strftime(\\\"%b_%d_%Y_%H_%M_%S\\\") + '/'\\n self.log_path = os.path.join(log_root, self.log_dir)\\n os.makedirs(self.log_path)\\n os.system(\\\"rsync -au --include '*/' --include '*.py' --exclude '*' . \\\" + self.log_path + \\\"source\\\")\\n os.makedirs(os.path.join(self.log_path, 'metrics'))\\n os.makedirs(os.path.join(self.log_path, 'checkpoints'))\\n self.epoch = 1\\n print(' Starting experiment ' + self.log_dir)\",\n \"def initialise(self):\",\n \"def __init__(self, run):\\n dict.__init__(self)\\n self.read(run)\",\n \"def setUp(self):\\n self.new_article = Articles(\\\"Politico\\\",\\\"By Benjamin Din\\\", \\\"2024 GOP contenders collect cash\\\", \\\"Republicans who led efforts to overturn the election results in January did especially well, according to the latest quarterly FEC filings.\\\", \\\"https://www.politico.com/news/2021/04/15/2024-gop-cash-fec-482240\\\", \\\"https://static.politico.com/90/a6/2eff74ff4d69b7aee677b55ae6e2/gettyimages-1230713929.jpg\\\", \\\"2021-04-16T02:10:04Z\\\")\",\n \"def __init__(self, template, file_path):\\n self.navigator = Navigator()\\n self.template = template\\n self.file_path = file_path\\n self.template_data = read_xml_get_json(template, ordered_dict=True)\\n self.data = read_xml_get_json(file_path, ordered_dict=True)\\n self.output = {\\\"status\\\": True, \\\"message\\\": \\\"\\\"}\\n self.root = \\\"Testcase\\\"\\n self.major = (\\\"Details\\\", \\\"Requirements\\\", \\\"Steps\\\")\",\n \"def test_init_experiment(self):\\n optimizer = \\\"RandomSearch\\\"\\n name = \\\"test_init_experiment\\\"\\n param_defs = {\\n \\\"x\\\": MinMaxNumericParamDef(0, 1),\\n \\\"name\\\": NominalParamDef([\\\"A\\\", \\\"B\\\", \\\"C\\\"])\\n }\\n minimization = True\\n\\n LAss = PrettyLabAssistant()\\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\\n\\n exp_ass = LAss.exp_assistants[name]\\n\\n assert_equal(exp_ass.optimizer, optimizer)\\n assert_is_none(exp_ass.optimizer_arguments, None)\\n assert_equal(exp_ass.experiment.minimization_problem, minimization)\\n with assert_raises(ValueError):\\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\",\n \"def newExperiment(self):\\n experiment = Experiment()\\n newtitle = 'Untitled ' + self.getNextUntitled()\\n experimentFrame = SequenceFrame(self, experiment, True, newtitle)\\n experiment.setInteractionParameters(parentFrame=experimentFrame,\\n graphManagerClass=StandardGraphManager)\\n self.frames.append(experimentFrame)\\n self.names.append(newtitle)\\n log.info('Created experiment ' + newtitle)\\n experimentFrame.Show()\\n testFrame = tf.TestingFrame(experimentFrame, experiment)\\n testFrame.Show()\\n self.Show(False)\",\n \"def __init__(self, document, builder):\\n LaTeXTranslator.__init__(self, document, builder)\\n self.elements[\\\"maketitle\\\"] = r\\\"\\\\maketitle\\\"\\n self.elements[\\\"makeindex\\\"] = \\\"\\\"\\n self.elements[\\\"printindex\\\"] = \\\"\\\"\\n self.elements[\\\"tableofcontents\\\"] = \\\"\\\"\\n self.elements[\\\"wrapperclass\\\"] = \\\"beamer\\\"\\n self.elements[\\\"beamer_theme\\\"] = builder.config_options[\\\"beamer_theme\\\"]\\n self.section_levels = [\\n r\\\"\\\\begin{frame}\\\",\\n r\\\"\\\\subsection\\\",\\n r\\\"\\\\subsubsection\\\",\\n ]\\n self.elements[\\\"allowframebreaks\\\"] = \\\\\\n builder.config_options[\\\"allowframebreaks\\\"]\",\n \"def __init__(self, experiment_dir):\\n self.experiment_dir = pathlib.Path(experiment_dir)\\n\\n parameters_data = parse_parameters(experiment_dir)\\n self.__dict__ = {**self.__dict__, **parameters_data}\",\n \"def __init__(self, contents: str) -> None:\\n super().__init__(contents)\",\n \"def setup_document(document_name=\\\"fSCAD-Preview\\\"):\\n preview_doc = None\\n saved_camera = None\\n saved_units = None\\n for document in app().documents:\\n if document.name == document_name:\\n preview_doc = document\\n break\\n if preview_doc is not None:\\n preview_doc.activate()\\n saved_camera = app().activeViewport.camera\\n saved_units = design().fusionUnitsManager.distanceDisplayUnits\\n preview_doc.close(False)\\n\\n preview_doc = app().documents.add(adsk.core.DocumentTypes.FusionDesignDocumentType)\\n preview_doc.name = document_name\\n preview_doc.activate()\\n if saved_camera is not None:\\n is_smooth_transition_bak = saved_camera.isSmoothTransition\\n saved_camera.isSmoothTransition = False\\n app().activeViewport.camera = saved_camera\\n saved_camera.isSmoothTransition = is_smooth_transition_bak\\n app().activeViewport.camera = saved_camera\\n if saved_units is not None:\\n design().fusionUnitsManager.distanceDisplayUnits = saved_units\\n design().designType = adsk.fusion.DesignTypes.DirectDesignType\",\n \"def setUp(self):\\n self.m = m = random.randint(1, 100)\\n self.n = n = random.randint(1, 100)\\n self.sig = sig = Signature(\\\"name\\\", Dim(\\\"m\\\"), Dim(\\\"n\\\"),\\n sData(\\\"A\\\", \\\"ldA * n\\\"), Ld(\\\"ldA\\\", \\\"m\\\"),\\n dData(\\\"B\\\", \\\"ldB * m\\\"), Ld(\\\"ldB\\\", \\\"m\\\"),\\n cData(\\\"C\\\", \\\"ldC * n\\\"), Ld(\\\"ldC\\\", \\\"n\\\"))\\n self.ex = ex = Experiment()\\n ex.calls = [sig(m, n, \\\"X\\\", None, \\\"Y\\\", None, \\\"Z\\\", None)]\\n ex.infer_lds()\\n self.i = Symbol(\\\"i\\\")\\n self.j = Symbol(\\\"j\\\")\",\n \"def __init__(self):\\n self._create_options()\\n self._create_sections()\",\n \"def __init__(self, thesis, first=\\\"\\\", last='', major='CIS'):\\r\\n super().__init__(first, last, major)\\r\\n self.thesis = thesis\",\n \"def __init__(self, html_contents):\\n self.doc = html.document_fromstring(html_contents)\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def _problem_run_experiments_initialise(self):\\n pass\",\n \"def __init__(self, experiment, sigma_b, sigma_m, n_sigma):\\n self.experiment = experiment\\n self.sigma_b = sigma_b\\n self.sigma_m = sigma_m\\n self.n_sigma = n_sigma\",\n \"def __init__(self, name):\\n config = Config()\\n super(TestTemplate, self).__init__(name)\\n self.doc_dict = None\\n func = getattr(self, name)\\n self.get_test_doc(name, func.__doc__)\\n # ASSIGN VALUES TO CONFIG\\n config['name'] = self.doc_dict['name']\\n logger.info(\\\"NAME: {}\\\".format(config['name']))\\n config['title'] = self.doc_dict['title']\\n logger.info(\\\"TITLE: {}\\\".format(config['title']))\\n config['test'] = self.doc_dict['test']\\n logger.info(\\\"TEST: {}\\\".format(config['test']))\\n config['bug'] = self.doc_dict['bug']\\n logger.info(\\\"BUG: {}\\\".format(config['bug']))\",\n \"def __init__(self, spec):\\n self.spec = spec\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7011294","0.69498855","0.68237424","0.66328037","0.66267675","0.6497485","0.6457093","0.6423474","0.6372848","0.62703747","0.6235102","0.6179923","0.60615146","0.6018496","0.60152483","0.5986631","0.5941061","0.5928936","0.58815664","0.5872775","0.5864881","0.5856335","0.584796","0.58245957","0.58099353","0.58099353","0.57989323","0.5793716","0.5767949","0.57656074","0.5760162","0.5731764","0.5721819","0.57207465","0.5709247","0.5706665","0.56737494","0.5663276","0.5655255","0.56395453","0.5638274","0.56335837","0.56284404","0.56234854","0.56220394","0.5608867","0.5599396","0.55952334","0.5590271","0.55782574","0.5556524","0.5551689","0.5541906","0.5541906","0.55402756","0.5538479","0.55381864","0.55359864","0.5535587","0.55348265","0.55295426","0.552032","0.5517285","0.55115366","0.5509116","0.55037147","0.5503641","0.54981154","0.548952","0.54869413","0.5481898","0.5479683","0.5477753","0.5475804","0.5466662","0.5466537","0.545309","0.5452118","0.5448417","0.5447411","0.5442991","0.5441184","0.54379493","0.54377824","0.5433461","0.543092","0.5430673","0.5428436","0.54264206","0.54264206","0.54264206","0.54264206","0.54264206","0.54264206","0.54264206","0.54264206","0.5426258","0.5419783","0.54153264","0.54102564"],"string":"[\n \"0.7011294\",\n \"0.69498855\",\n \"0.68237424\",\n \"0.66328037\",\n \"0.66267675\",\n \"0.6497485\",\n \"0.6457093\",\n \"0.6423474\",\n \"0.6372848\",\n \"0.62703747\",\n \"0.6235102\",\n \"0.6179923\",\n \"0.60615146\",\n \"0.6018496\",\n \"0.60152483\",\n \"0.5986631\",\n \"0.5941061\",\n \"0.5928936\",\n \"0.58815664\",\n \"0.5872775\",\n \"0.5864881\",\n \"0.5856335\",\n \"0.584796\",\n \"0.58245957\",\n \"0.58099353\",\n \"0.58099353\",\n \"0.57989323\",\n \"0.5793716\",\n \"0.5767949\",\n \"0.57656074\",\n \"0.5760162\",\n \"0.5731764\",\n \"0.5721819\",\n \"0.57207465\",\n \"0.5709247\",\n \"0.5706665\",\n \"0.56737494\",\n \"0.5663276\",\n \"0.5655255\",\n \"0.56395453\",\n \"0.5638274\",\n \"0.56335837\",\n \"0.56284404\",\n \"0.56234854\",\n \"0.56220394\",\n \"0.5608867\",\n \"0.5599396\",\n \"0.55952334\",\n \"0.5590271\",\n \"0.55782574\",\n \"0.5556524\",\n \"0.5551689\",\n \"0.5541906\",\n \"0.5541906\",\n \"0.55402756\",\n \"0.5538479\",\n \"0.55381864\",\n \"0.55359864\",\n \"0.5535587\",\n \"0.55348265\",\n \"0.55295426\",\n \"0.552032\",\n \"0.5517285\",\n \"0.55115366\",\n \"0.5509116\",\n \"0.55037147\",\n \"0.5503641\",\n \"0.54981154\",\n \"0.548952\",\n \"0.54869413\",\n \"0.5481898\",\n \"0.5479683\",\n \"0.5477753\",\n \"0.5475804\",\n \"0.5466662\",\n \"0.5466537\",\n \"0.545309\",\n \"0.5452118\",\n \"0.5448417\",\n \"0.5447411\",\n \"0.5442991\",\n \"0.5441184\",\n \"0.54379493\",\n \"0.54377824\",\n \"0.5433461\",\n \"0.543092\",\n \"0.5430673\",\n \"0.5428436\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.54264206\",\n \"0.5426258\",\n \"0.5419783\",\n \"0.54153264\",\n \"0.54102564\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.67475593"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":25687,"cells":{"query":{"kind":"string","value":"Initialise with a MIP document"},"document":{"kind":"string","value":"def __init__(self, document):\n\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key == 'cim.2.designing.Project'\n self.doc = document\n\n # We will populate the \"mip\" variable with the mip era\n self.mips = 'CMIP6'\n\n self.related = []\n for r in self.doc.required_experiments:\n self.related.append(esd.retrieve(r.id))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __init__(self, doc):\n\n self.doc = doc\n if self.doc.doi:\n self._populate()\n self.populated = True\n else:\n self.populated = False","def __init__(self, document):\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key == 'cim.2.designing.NumericalExperiment'\n self.doc = document\n\n # In most cases there is only one related mip.\n # Handle the edge case here rather than in template.\n mips = ''\n for m in document.related_mips:\n mips += m.name+', '\n self.mips = mips[:-2]\n\n self.related = []\n for r in self.doc.requirements:\n req = esd.retrieve(r.id)\n # Are there additional requirements?\n # If so, let's monkey patch their long names onto the linkage...\n # The other choice would be to have a requirements class WITH\n # it's own template.\n req.monkey_additional = []\n if req.additional_requirements:\n for rr in req.additional_requirements:\n rreq = esd.retrieve(rr.id)\n req.monkey_additional.append(rreq.long_name)\n self.related.append(req)","def create(init_document: 'Document') -> 'DocumentArray':","def __init__(self, doc_set):\n self.__doc_set = doc_set\n self.__preprocessor = InputPreprocessor(doc_set)","def __init__(self):\n super(BlipDocument, self).__init__()\n self.annotations = Annotations()\n self.rotation = 0","def __init__(self, blip_data, context):\n super(OpBasedDocument, self).__init__(blip_data)\n self.__context = context","def __init__(self, doc, target=None, stylesheet=\"\"):\n self.document = doc\n self.stylesheet = stylesheet\n self.target = target if target is not None else StringIO()","def __init__(self, *args):\n this = _libsbml.new_SBMLDocument(*args)\n try: self.this.append(this)\n except: self.this = this","def __init__(self, *args):\n this = _libsbml.new_CompSBMLDocumentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def Init(self, *args):\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)","def __init__(self, txt='', unicodeEncoding='utf-8'):\n # __document capture the document level structure\n # for each sentence and then put in the archives when the next sentence\n # is processed\n super(ConTextMarkup, self).__init__(__txt=None,\n __rawtxt=txt,\n __scope=None,\n __SCOPEUPDATED=False)\n self.__document = nx.DiGraph()\n self.__document.add_node(\"top\", category=\"document\")\n self.__VERBOSE = False\n self.__tagID = 0\n self.__unicodeEncoding = unicodeEncoding","def __init__(self, template=site_template):\n self.template = template\n self.template_file = None\n if not os.path.exists(self.template):\n raise OpagMissingPrecondition, \"%s does not exist\" % self.template","def __init__(self, xdoc):\n \n self.xdoc = parse(xdoc)\n self.mapa = mapa.Mapa(self.xdoc)\n self.scrollx = 0\n self.scrolly = 0\n self.eventos = self.load_events()","def initialise(self):","def __init__(self,inp='INP.mcnp'):\n # Material dictionary for the moderator, light guide, and detector\n self.material = {'Moderator':None,'Detector':None,'LightGuide':None}\n self.material['Detector'] = {'name':'Detector','mt': 3, 'rho': 1.1,'matString':None} # detector\n self.material['LightGuide'] = {'name': 'PMMA','mt':10, 'rho':0.93} # PMMA\n self.material['Moderator'] = {'name':'HDPE','mt':456, 'rho': 0.93} # HPDE\n \n # Cell and Surface Inital Numbering\n self.CellStartNum = 600\n self.SurfaceStartNum = 600\n self.ZeroSurfaceNum = 500\n self.UniverseNum = 200\n self.surfGeo = None\n self.inp = inp\n self.name = 'OUT_'+self.inp.strip('.mcnp')+'.'\n self.setMaterial(0.1,'PS')","def __init__(self, docx, strict=False):\n self.strict = strict\n document_part = Package.open(docx).main_document_part\n if document_part.content_type != CONTENT_TYPE.WML_DOCUMENT_MAIN:\n tmpl = \"file '%s' is not a Word file, content type is '%s'\"\n raise ValueError(tmpl % (docx, document_part.content_type))\n super().__init__(document_part._element, document_part)","def __init__(self, *args):\n this = _libsbml.new_SBMLDocumentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def init(self) -> None:","def __init__(self, infile, runparser=True):\n super(FluoViewMosaic, self).__init__(infile)\n self.tree = self.validate_xml()\n self.mosaictrees = self.find_mosaictrees()\n if runparser:\n self.add_mosaics()","def __init__(self, ):\n super(MayaRefobjInterface, self).__init__()","def init(self):\n logger.info(mm_cnofs.ackn_str)\n self.acknowledgements = mm_cnofs.ackn_str\n self.references = '\\n'.join((mm_cnofs.refs['mission'],\n mm_cnofs.refs['vefi']))\n\n return","def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\n name=None, **kwargs):\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\n self.artDirection = artDirection\n self.path = path # Optional path to markdown file, if it has content.\n self.mdText = mdText # Optional markdown string.\n self.name = name or 'Untitled'\n self.startPage = startPage","def __init__(self):\n # Initialise class attributes (visibility ease)\n self.__corpus__ = None\n self.__pron_det_pos_words__ = None\n self.__triples_corpus__ = None\n self.__entities_in_doc__ = None\n self.__wvmodel__ = None\n \n # For purpose of parsing relation triplets later\n # Load pretrained embedding model\n #plog('Loading pretrained word embeddings. This will take some time to load...')\n #self.__wvmodel__ = api.load('fasttext-wiki-news-subwords-300')\n #plog('Pretrained word embeddings loaded!')","def __init__(self, model_pool):\n super(Template, self).__init__(model_pool)\n self.nlp_model = None","def init_doc(self):\n raise NotImplementedError()","def __init__(self, sourcefile, title=\"\", genre=\"classic\"):\n\n if self.__class__.__name__ != \"SentencePPT\":\n self._assert_class_variables()\n self._template = self.__class__._templates[genre]\n self._prs = Presentation(self._template)\n self._title = title\n self._sourcefile = sourcefile\n self._assert_content()\n else:\n raise TypeError(self.__class__.__doc__)","def __init__(self, morphit):\r\n self.MorphItFileName = morphit\r\n\r\n self.verbTags = ['VER', 'AUX', 'MOD', 'CAU', 'ASP']\r\n self.words = self.LoadWords()\r\n if not self.words:\r\n self.ReadMorphit()\r\n self.SaveWords()","def __init__(self, resource_path=None):\n\n (\n self.tokenized_document,\n self.stack,\n self.source_provider,\n self.__parse_properties,\n ) = (None, None, None, None)\n\n if not resource_path:\n resource_path = os.path.join(os.path.split(__file__)[0], \"resources\")\n InlineHelper.initialize(resource_path)","def __init__(self, reporoot, relnotesdir=None):\n self.reporoot = reporoot\n if relnotesdir is None:\n relnotesdir = defaults.RELEASE_NOTES_SUBDIR\n self.relnotesdir = relnotesdir\n # Initialize attributes from the defaults.\n self.override(**{o.name: o.default for o in _OPTIONS})\n\n self._contents = {}\n self._load_file()","def __init__(self):\n self._pronunciations = nltk.corpus.cmudict.dict()\n \"\"\"\n API Documentation for CMU dictionary corpus\n http://www.nltk.org/api/nltk.corpus.reader.html#module-nltk.corpus.reader.cmudict\n \"\"\"","def __init__(self, *args):\n this = _libsbml.new_MultiSBMLDocumentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def __init__(self, meta_type, document, data=None):\n\n self._meta_type = meta_type\n self._document = document\n self._data = data\n self.contentChanged = core.VSignal(self)","def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\r\n pass","def __init__(self, documents_path):\n self.documents = []\n self.vocabulary = []\n self.likelihoods = []\n self.documents_path = documents_path\n self.term_doc_matrix = None \n self.document_topic_prob = None # P(z | d)\n self.topic_word_prob = None # P(w | z)\n self.topic_prob = None # P(z | d, w)\n\n self.number_of_documents = 0\n self.vocabulary_size = 0","def startDocument(self):\n pass","def startDocument(self):\n pass","def init(self):\n raise NotImplementedError","def init(self):\n raise NotImplementedError","def document(self):\n ...","def _init(self):\n raise NotImplementedError","def __init__(self, source='cmip6'):\n\n self.source = source\n\n # We keep a dictionary of document sets so each call to getbyname does not need\n # to get the document set first, unless that document set has not previously been requested.\n\n self.documents = {}","def build_document(self):\n pass","def __init__(self, main_doc):\n\t\tif not isinstance(main_doc, Document):\n\t\t\traise TypeError('term must be of type Document')\n\t\tself.main_doc = main_doc\n\t\tself.env_docs = []","def setup_parse(self, inputstring: str, document: nodes.document) -> None:\n self.inputstring = inputstring\n self.document = document","def __init__(self, html, out_file):\n self.html = html\n self.out_file = out_file\n self.env = Environment(loader=PackageLoader('html2docx', 'templates'))\n self.template_names = {\n 'content_types': '[Content_Types].xml',\n 'apps': 'docProps/app.xml',\n 'core': 'docProps/core.xml',\n 'rels': '_rels/.rels',\n 'document': 'word/document.xml',\n 'fonts': 'word/fontTable.xml',\n 'document_rels': 'word/_rels/document.xml.rels',\n 'settings': 'word/settings.xml',\n 'styles': 'word/styles.xml',\n }\n self.document_state = []\n self.visited = set()","def __init__(self, output, encoding='utf-8'):\n document = XMLGenerator(output, encoding)\n document.startDocument()\n self._document = document\n self._output = output\n return","def init(self) -> None:\n ...","def __init__(self, iReader):\n self.ireader = iReader\n self.num_of_doc = iReader.getNumberOfDocuments()","def __init__(self):\n # simple header only necessary for this table of MIPs\n self.header = '<tr class=\"ename\"><td colspan=\"1\">{{d.name}} ({{mips}})</td></tr>'\n self.mips = 'core MIPS recorded by ES-DOC'\n self._settemplates(self.onecol, self.twocol)\n\n r = Repo()\n c = r.getbyname('CMIP6', 'mips')\n self.doc = c\n self.related = []\n\n # two properties to help the use of the resulting table in a paper\n self.reference_list = []\n # nocite list intended for cutting and pasting directly into a latex document!\n self.nocite = ''\n\n for m in c.sub_projects:\n mdoc = r.getbyname(m.name, 'mips')\n description = mdoc.long_name+' - '\n citations = []\n\n # for these purposees we only want the things with a doi\n # and we want only one, so we have to develop a heuristic to get the right one\n for ci in mdoc.citations:\n cidoc = esd.retrieve(ci.id)\n ref = Reference(cidoc)\n if ref.populated:\n citations.append(ref)\n citations.sort(key=lambda cc: cc.year)\n index = -1\n if len(citations) > 1:\n # start by getting the most recent\n year = citations[-1].year\n index = -1\n for i in range(len(citations)-1):\n if citations[i].year == year:\n if m.name in citations[i].text:\n # it's one of the most recent and it has the MIP name\n # in the document title.\n index = i\n description += citations[index].citestring\n self.reference_list.append(citations[index].text)\n self.nocite += '\\\\nocite{%s}\\n' % citations[index].citeguess\n\n # overwrite the real description for the purpose of this table\n mdoc.description = description\n self.related.append(mdoc)\n\n # want alphabetical order\n self.related.sort(key=lambda mm: mm.name)","def __init__(self, name, nlp):\n if not Doc.has_extension(\"flesch_kincaid_grade_level\"):\n Doc.set_extension(\"flesch_kincaid_grade_level\", getter=self.fk_grade)\n\n if not Doc.has_extension(\"flesch_kincaid_reading_ease\"):\n Doc.set_extension(\"flesch_kincaid_reading_ease\", getter=self.fk_ease)\n\n if not Doc.has_extension(\"dale_chall\"):\n Doc.set_extension(\"dale_chall\", getter=self.dale_chall)\n\n if not Doc.has_extension(\"smog\"):\n Doc.set_extension(\"smog\", getter=self.smog)\n\n if not Doc.has_extension(\"coleman_liau_index\"):\n Doc.set_extension(\"coleman_liau_index\", getter=self.coleman_liau)\n\n if not Doc.has_extension(\"automated_readability_index\"):\n Doc.set_extension(\"automated_readability_index\", getter=self.ari)\n\n if not Doc.has_extension(\"forcast\"):\n Doc.set_extension(\"forcast\", getter=self.forcast)\n\n if not Doc.has_extension(\"word_entropy\"):\n Doc.set_extension(\n \"word_entropy\", getter=lambda x: self.word_entropy(x, lemmatized=False)\n )\n\n if not Doc.has_extension(\"word_entropy_l\"):\n Doc.set_extension(\n \"word_entropy_l\", getter=lambda x: self.word_entropy(x, lemmatized=True)\n )\n\n if not Doc.has_extension(\"lix\"):\n Doc.set_extension(\"lix\", getter=self.lix)","def __init__(self,\n title=\"[CDR Form Letter]\",\n subject=None,\n template=None,\n pngName=\"dhhslogo.png\",\n author=\"cdr\",\n company=\"CIPS\",\n binImage=False,\n invitePara=\"\"):\n\n Document.__init__(self, title, author, company, subject)\n self.generator = \"CDR RTF Writer\"\n self.pngName = pngName # location of bitmap file for logo\n self.margL = 1080 # 3/4-inch left margin\n self.margR = 720 # 1/2-inch right margin\n self.margT = 1080 # 5/8-inch top margin\n self.margB = 1260 # 7/8-inch bottom margin\n self.fSize = 21 # 10.5-point default font size\n self.baskervilleFont = self.addFont(\"Baskerville Old Face\",\n \"roman\",\n \"Times New Roman\")\n self.__addLetterHead(binImage)\n if template:\n try:\n with open(template) as fp:\n body = fp.read()\n except Exception as e:\n raise Exception(\"loading %s: %s\" % (template, str(e)))\n if invitePara:\n replacement = \"@@MISCDOC:%s@@\" % invitePara\n body = body.replace(\"@@INVITATION@@\", replacement)\n pattern = re.compile(\"@@MISCDOC:(.*?)@@\")\n body = pattern.sub(lambda p: self.__loadMiscDoc(p), body)\n self.addRawContent(body)","def __init__(self, id, file=None):\n self.__name__ = id\n self.title = id\n self.id = id\n \n self._setPropValue('content_type', 'text/xml')\n\n self.setup_transformProperties()\n self.setup_schemaProperties()\n\n ZopePageTemplate.ZopePageTemplate.__init__(self, id)\n\n if hasattr(file, 'read'):\n self.write(file.read())","def build(self, text):\n self._xml4nlp = Element('xml4nlp')\n self._note = SubElement(self._xml4nlp, 'note')\n self._doc = SubElement(self._xml4nlp, 'doc')\n\n para = SubElement(self._doc, 'para')\n para.set(\"id\", \"0\")\n para.text = text\n\n self._clean_note()\n self.dom = self._xml4nlp","def init():","def __init__(self, document_path):\n self.tree = etree.parse(document_path)\n self.doc_id = get_doc_id(self.tree)\n for element_type in ('nodes', 'edges', 'layers'):\n self._extract_elements(self.tree, element_type)","def __init__(self, mdef, extinfo=None):\n raise NotImplementedError(\"EMFetcher abstract superclass\")","def memb_init(self):\n self.initialize()","def __init__(self, letter, name):\n\n import cdr\n from lxml import etree\n\n self.letter = letter\n path = \"/MiscellaneousDocument/MiscellaneousDocumentTitle\"\n query = f\"{path}/value eq {name}\"\n try:\n resp = cdr.search(\"guest\", query)\n except Exception as e:\n raise Exception(f\"failure loading misc doc {name!r}: {e}\")\n if not resp:\n raise Exception(f\"Miscellaneous document {name!r} not found\")\n self.docId = resp[0].docId\n try:\n doc = cdr.getDoc(\"guest\", self.docId, getObject=True)\n except Exception as e:\n raise Exception(f\"Retrieving {self.docId}: {e}\")\n self.root = etree.fromstring(doc.xml)","def __init__(self, proknow, requestor):\n self._proknow = proknow\n self._requestor = requestor","def __init__(self, document_name=None, id=None, p=None, rfid_presence=None, fdsid_list=None, necessary_lights=None, check_authenticity=None, uv_exp=None, authenticity_necessary_lights=None, local_vars_configuration=None): # noqa: E501 # noqa: E501\n if local_vars_configuration is None:\n local_vars_configuration = Configuration()\n self.local_vars_configuration = local_vars_configuration\n\n self._document_name = None\n self._id = None\n self._p = None\n self._rfid_presence = None\n self._fdsid_list = None\n self._necessary_lights = None\n self._check_authenticity = None\n self._uv_exp = None\n self._authenticity_necessary_lights = None\n self.discriminator = None\n\n if document_name is not None:\n self.document_name = document_name\n if id is not None:\n self.id = id\n if p is not None:\n self.p = p\n if rfid_presence is not None:\n self.rfid_presence = rfid_presence\n if fdsid_list is not None:\n self.fdsid_list = fdsid_list\n if necessary_lights is not None:\n self.necessary_lights = necessary_lights\n if check_authenticity is not None:\n self.check_authenticity = check_authenticity\n if uv_exp is not None:\n self.uv_exp = uv_exp\n if authenticity_necessary_lights is not None:\n self.authenticity_necessary_lights = authenticity_necessary_lights","def __init__(self, *args):\n _snap.Schema_swiginit(self, _snap.new_Schema(*args))","def init(self):","def init(self):","def __init__(self, invoice, buffer=None):\n self.invoice = invoice\n self.buffer = buffer","def do_setup_pocs(self, *arg):\n args, kwargs = string_to_params(*arg)\n simulator = kwargs.get('simulator', [])\n print_info(\"Simulator: {}\".format(simulator))\n\n try:\n self.pocs = POCS(simulator=simulator)\n self.pocs.initialize()\n except error.PanError as e:\n\n pass","def __init__(self):\n super().__init__(interface.Metadata, DEFAULT_PRIORITIES)","def __init__(self):\n # parse MSR data\n test_data, sent_dict, pair_dict = parse()\n # word mover model -- take long to load the model!\n wm_model = WMD()\n # copnvert the ID->String dict to ID-> token dict\n candidate_dict = wmd_utils.sent_dict_to_tok_dict(sent_dict)\n wm_model.evaluate_model(candidate_dict, pair_dict)","def __init__(self, ixs):\n ixs = sorted(list(set(ixs)))\n self.ixs = ixs\n self.all_ids = fc.load_keys('../data/keys.json')\n self.ids = set(itemgetter(*ixs)(self.all_ids))\n corpus_files = glob('../data/documents/*')\n corpus_files.sort(key=natural_keys)\n self.corpus_files = corpus_files\n\n self.dictionary = Dictionary.load('../data/corpus.dict')\n self.token2id = self.dictionary.token2id\n logging.info(\"loading docs to RAM\")\n self.docs_ram_dict = self.push_docs_to_ram()\n\n self.wv = Word2Vec.load('../data/w2v_200_5_w8').wv\n\n logging.info(\"loading qdr model\")\n self.qdr = qdr.QueryDocumentRelevance.load_from_file('../data/qdr_model.gz')\n\n logging.info(\"loading mpk data\")\n with open('../data/all_mpk.pkl', 'rb') as f:\n self.all_mpk = pickle.load(f)\n self.mpk = ft.MPK()\n logging.info('data is loaded')","def __init__(self, pageName):\n self.pageName = pageName\n self.updateFileData()\n self.template = pystache.parse(unicode(self.fileData, 'utf-8'))","def initialize(self):\n raise NotImplementedError","def initialize(self):\n raise NotImplementedError","def initialize(self):\n raise NotImplementedError","def __init__(self, run_id: str, doc: Dict, service: APIFactory):\n self.run_id = run_id\n self.file_id = doc['id']\n self.name = doc['name']\n self.title = doc.get('title', self.name)\n self.caption = doc.get('caption')\n self.format = doc.get('format', {})\n self.service = service","def __init__(self, data, context):\n super(OpBasedBlip, self).__init__(data, OpBasedDocument(data, context))\n self.__context = context","def __init__(self, number, title, paragraphs):\n self.number = number\n self.title = title\n self.paragraphs = []\n for paragraph_lines in paragraphs:\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\n self.paragraphs.append(new_pragraph)","def __init__(__self__,\n resource_name: str,\n args: Optional[NoteArgs] = None,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def __init__(self, content, template, **styles):\n self.content = content\n self.template = template\n self.styles = DEFAULT_DOCUMENT_STYLE.copy()\n # This is a rendered document ready to be painted on a cairo surface\n self._document = None # weasyprint.document.Document object\n self.compiled_html = None\n # Update the default styles and initialize self._document object\n self.update_style(**styles)","def __init__(self, doc_root):\n self.doc_root = doc_root\n site = yaml_load('data/site.yaml')['site']\n self.site = site","def __init__(self, footprint, mconf, name):\n logging.debug(\"%s entered __init__\" % name)\n self.image_id = mconf[\"image-id\"]\n self.networks = mconf[\"networks\"]\n self.ip_addresses = mconf[\"ip-addresses\"]\n self.flavor=mconf[\"flavor\"]\n self.machine_name = \"%s%s\" % (footprint.footprint_name, name)\n self.footprint = footprint","def __init__(self):\n\n self.prim_parser = parser.Parser()","def __init__(self):\n self.model = {'mol':[], 'nmol':0}\n self.template = {} \n self.config = {}\n self.config['tfile'] = 'gau-template-bsse.gjf'\n self.config['xyzfile'] = 'model.xyz'\n self.config['jobfile'] = 'gau.gjf'\n self.config['job_prefix'] = self.config['jobfile'].split(\".\")[0]\n self.config['incr'] = 1\n \n self.rd_cmd_stream()\n return","def initialize(self):","def initialize(self):","def initialize(self):","def initialize(self):","def init(pt, content):\n p = PTree()\n p.distribution = pt.distribution\n p.global_index = pt.global_index\n p.start_index = pt.start_index\n p.nb_segs = pt.nb_segs\n p.content = content\n return p","def __init__(self, author, title, text=\"\", haiku=\"False\"):\n self.author = author\n self.title = title\n self.text = text\n self.haiku = haiku\n self.name = self\n Poem.obj_created += 1","def __init__(self, metadata_folder='./'):\n self.metadata = self.load_metadata(metadata_folder)\n self.prefix = 'data/miap/images/'\n return","def __init__(self):\n super(MethodInfo, self).__init__()\n self.DocString = None","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n pass","def init(self):\n\n # Set the appropraite acknowledgements and references\n self.acknowledgements = mm_ace.acknowledgements()\n self.references = mm_ace.references(self.name)\n\n logger.info(self.acknowledgements)\n\n return","def __init__(self, page):\n self.raw_page = page\n self.page = etree.HTML(page)","def __initialize(self):\n\t\tself.matrix = [None] * self.size\n\t\tself.__get_log_values()\n\t\tfor row in range(self.size):\n\t\t\tself.matrix[row] = [None] * self.size\n\t\tmax_len = self.__get_max_length()\n\t\tdata = self.__get_data(self.text,max_len)\n\t\tmpoly = self.__get_mpoly(data)\n\t\tgpoly = self.__get_gploy()\n\t\tself.final_data = self.__get_final_data(mpoly,gpoly)\n\t\tself.__set_FIP(FP_num = 1)\n\t\tself.__set_FIP(FP_num = 2)\n\t\tself.__set_FIP(FP_num = 3)\n\t\tself.__set_AP()\n\t\tself.__fill_format_info_area()\n\t\tself.__set_TP()"],"string":"[\n \"def __init__(self, doc):\\n\\n self.doc = doc\\n if self.doc.doi:\\n self._populate()\\n self.populated = True\\n else:\\n self.populated = False\",\n \"def __init__(self, document):\\n self._settemplates(self.onecol, self.twocol)\\n assert document.type_key == 'cim.2.designing.NumericalExperiment'\\n self.doc = document\\n\\n # In most cases there is only one related mip.\\n # Handle the edge case here rather than in template.\\n mips = ''\\n for m in document.related_mips:\\n mips += m.name+', '\\n self.mips = mips[:-2]\\n\\n self.related = []\\n for r in self.doc.requirements:\\n req = esd.retrieve(r.id)\\n # Are there additional requirements?\\n # If so, let's monkey patch their long names onto the linkage...\\n # The other choice would be to have a requirements class WITH\\n # it's own template.\\n req.monkey_additional = []\\n if req.additional_requirements:\\n for rr in req.additional_requirements:\\n rreq = esd.retrieve(rr.id)\\n req.monkey_additional.append(rreq.long_name)\\n self.related.append(req)\",\n \"def create(init_document: 'Document') -> 'DocumentArray':\",\n \"def __init__(self, doc_set):\\n self.__doc_set = doc_set\\n self.__preprocessor = InputPreprocessor(doc_set)\",\n \"def __init__(self):\\n super(BlipDocument, self).__init__()\\n self.annotations = Annotations()\\n self.rotation = 0\",\n \"def __init__(self, blip_data, context):\\n super(OpBasedDocument, self).__init__(blip_data)\\n self.__context = context\",\n \"def __init__(self, doc, target=None, stylesheet=\\\"\\\"):\\n self.document = doc\\n self.stylesheet = stylesheet\\n self.target = target if target is not None else StringIO()\",\n \"def __init__(self, *args):\\n this = _libsbml.new_SBMLDocument(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def __init__(self, *args):\\n this = _libsbml.new_CompSBMLDocumentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def Init(self, *args):\\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)\",\n \"def __init__(self, txt='', unicodeEncoding='utf-8'):\\n # __document capture the document level structure\\n # for each sentence and then put in the archives when the next sentence\\n # is processed\\n super(ConTextMarkup, self).__init__(__txt=None,\\n __rawtxt=txt,\\n __scope=None,\\n __SCOPEUPDATED=False)\\n self.__document = nx.DiGraph()\\n self.__document.add_node(\\\"top\\\", category=\\\"document\\\")\\n self.__VERBOSE = False\\n self.__tagID = 0\\n self.__unicodeEncoding = unicodeEncoding\",\n \"def __init__(self, template=site_template):\\n self.template = template\\n self.template_file = None\\n if not os.path.exists(self.template):\\n raise OpagMissingPrecondition, \\\"%s does not exist\\\" % self.template\",\n \"def __init__(self, xdoc):\\n \\n self.xdoc = parse(xdoc)\\n self.mapa = mapa.Mapa(self.xdoc)\\n self.scrollx = 0\\n self.scrolly = 0\\n self.eventos = self.load_events()\",\n \"def initialise(self):\",\n \"def __init__(self,inp='INP.mcnp'):\\n # Material dictionary for the moderator, light guide, and detector\\n self.material = {'Moderator':None,'Detector':None,'LightGuide':None}\\n self.material['Detector'] = {'name':'Detector','mt': 3, 'rho': 1.1,'matString':None} # detector\\n self.material['LightGuide'] = {'name': 'PMMA','mt':10, 'rho':0.93} # PMMA\\n self.material['Moderator'] = {'name':'HDPE','mt':456, 'rho': 0.93} # HPDE\\n \\n # Cell and Surface Inital Numbering\\n self.CellStartNum = 600\\n self.SurfaceStartNum = 600\\n self.ZeroSurfaceNum = 500\\n self.UniverseNum = 200\\n self.surfGeo = None\\n self.inp = inp\\n self.name = 'OUT_'+self.inp.strip('.mcnp')+'.'\\n self.setMaterial(0.1,'PS')\",\n \"def __init__(self, docx, strict=False):\\n self.strict = strict\\n document_part = Package.open(docx).main_document_part\\n if document_part.content_type != CONTENT_TYPE.WML_DOCUMENT_MAIN:\\n tmpl = \\\"file '%s' is not a Word file, content type is '%s'\\\"\\n raise ValueError(tmpl % (docx, document_part.content_type))\\n super().__init__(document_part._element, document_part)\",\n \"def __init__(self, *args):\\n this = _libsbml.new_SBMLDocumentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def init(self) -> None:\",\n \"def __init__(self, infile, runparser=True):\\n super(FluoViewMosaic, self).__init__(infile)\\n self.tree = self.validate_xml()\\n self.mosaictrees = self.find_mosaictrees()\\n if runparser:\\n self.add_mosaics()\",\n \"def __init__(self, ):\\n super(MayaRefobjInterface, self).__init__()\",\n \"def init(self):\\n logger.info(mm_cnofs.ackn_str)\\n self.acknowledgements = mm_cnofs.ackn_str\\n self.references = '\\\\n'.join((mm_cnofs.refs['mission'],\\n mm_cnofs.refs['vefi']))\\n\\n return\",\n \"def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\\n name=None, **kwargs):\\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\\n self.artDirection = artDirection\\n self.path = path # Optional path to markdown file, if it has content.\\n self.mdText = mdText # Optional markdown string.\\n self.name = name or 'Untitled'\\n self.startPage = startPage\",\n \"def __init__(self):\\n # Initialise class attributes (visibility ease)\\n self.__corpus__ = None\\n self.__pron_det_pos_words__ = None\\n self.__triples_corpus__ = None\\n self.__entities_in_doc__ = None\\n self.__wvmodel__ = None\\n \\n # For purpose of parsing relation triplets later\\n # Load pretrained embedding model\\n #plog('Loading pretrained word embeddings. This will take some time to load...')\\n #self.__wvmodel__ = api.load('fasttext-wiki-news-subwords-300')\\n #plog('Pretrained word embeddings loaded!')\",\n \"def __init__(self, model_pool):\\n super(Template, self).__init__(model_pool)\\n self.nlp_model = None\",\n \"def init_doc(self):\\n raise NotImplementedError()\",\n \"def __init__(self, sourcefile, title=\\\"\\\", genre=\\\"classic\\\"):\\n\\n if self.__class__.__name__ != \\\"SentencePPT\\\":\\n self._assert_class_variables()\\n self._template = self.__class__._templates[genre]\\n self._prs = Presentation(self._template)\\n self._title = title\\n self._sourcefile = sourcefile\\n self._assert_content()\\n else:\\n raise TypeError(self.__class__.__doc__)\",\n \"def __init__(self, morphit):\\r\\n self.MorphItFileName = morphit\\r\\n\\r\\n self.verbTags = ['VER', 'AUX', 'MOD', 'CAU', 'ASP']\\r\\n self.words = self.LoadWords()\\r\\n if not self.words:\\r\\n self.ReadMorphit()\\r\\n self.SaveWords()\",\n \"def __init__(self, resource_path=None):\\n\\n (\\n self.tokenized_document,\\n self.stack,\\n self.source_provider,\\n self.__parse_properties,\\n ) = (None, None, None, None)\\n\\n if not resource_path:\\n resource_path = os.path.join(os.path.split(__file__)[0], \\\"resources\\\")\\n InlineHelper.initialize(resource_path)\",\n \"def __init__(self, reporoot, relnotesdir=None):\\n self.reporoot = reporoot\\n if relnotesdir is None:\\n relnotesdir = defaults.RELEASE_NOTES_SUBDIR\\n self.relnotesdir = relnotesdir\\n # Initialize attributes from the defaults.\\n self.override(**{o.name: o.default for o in _OPTIONS})\\n\\n self._contents = {}\\n self._load_file()\",\n \"def __init__(self):\\n self._pronunciations = nltk.corpus.cmudict.dict()\\n \\\"\\\"\\\"\\n API Documentation for CMU dictionary corpus\\n http://www.nltk.org/api/nltk.corpus.reader.html#module-nltk.corpus.reader.cmudict\\n \\\"\\\"\\\"\",\n \"def __init__(self, *args):\\n this = _libsbml.new_MultiSBMLDocumentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def __init__(self, meta_type, document, data=None):\\n\\n self._meta_type = meta_type\\n self._document = document\\n self._data = data\\n self.contentChanged = core.VSignal(self)\",\n \"def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\\r\\n pass\",\n \"def __init__(self, documents_path):\\n self.documents = []\\n self.vocabulary = []\\n self.likelihoods = []\\n self.documents_path = documents_path\\n self.term_doc_matrix = None \\n self.document_topic_prob = None # P(z | d)\\n self.topic_word_prob = None # P(w | z)\\n self.topic_prob = None # P(z | d, w)\\n\\n self.number_of_documents = 0\\n self.vocabulary_size = 0\",\n \"def startDocument(self):\\n pass\",\n \"def startDocument(self):\\n pass\",\n \"def init(self):\\n raise NotImplementedError\",\n \"def init(self):\\n raise NotImplementedError\",\n \"def document(self):\\n ...\",\n \"def _init(self):\\n raise NotImplementedError\",\n \"def __init__(self, source='cmip6'):\\n\\n self.source = source\\n\\n # We keep a dictionary of document sets so each call to getbyname does not need\\n # to get the document set first, unless that document set has not previously been requested.\\n\\n self.documents = {}\",\n \"def build_document(self):\\n pass\",\n \"def __init__(self, main_doc):\\n\\t\\tif not isinstance(main_doc, Document):\\n\\t\\t\\traise TypeError('term must be of type Document')\\n\\t\\tself.main_doc = main_doc\\n\\t\\tself.env_docs = []\",\n \"def setup_parse(self, inputstring: str, document: nodes.document) -> None:\\n self.inputstring = inputstring\\n self.document = document\",\n \"def __init__(self, html, out_file):\\n self.html = html\\n self.out_file = out_file\\n self.env = Environment(loader=PackageLoader('html2docx', 'templates'))\\n self.template_names = {\\n 'content_types': '[Content_Types].xml',\\n 'apps': 'docProps/app.xml',\\n 'core': 'docProps/core.xml',\\n 'rels': '_rels/.rels',\\n 'document': 'word/document.xml',\\n 'fonts': 'word/fontTable.xml',\\n 'document_rels': 'word/_rels/document.xml.rels',\\n 'settings': 'word/settings.xml',\\n 'styles': 'word/styles.xml',\\n }\\n self.document_state = []\\n self.visited = set()\",\n \"def __init__(self, output, encoding='utf-8'):\\n document = XMLGenerator(output, encoding)\\n document.startDocument()\\n self._document = document\\n self._output = output\\n return\",\n \"def init(self) -> None:\\n ...\",\n \"def __init__(self, iReader):\\n self.ireader = iReader\\n self.num_of_doc = iReader.getNumberOfDocuments()\",\n \"def __init__(self):\\n # simple header only necessary for this table of MIPs\\n self.header = '<tr class=\\\"ename\\\"><td colspan=\\\"1\\\">{{d.name}} ({{mips}})</td></tr>'\\n self.mips = 'core MIPS recorded by ES-DOC'\\n self._settemplates(self.onecol, self.twocol)\\n\\n r = Repo()\\n c = r.getbyname('CMIP6', 'mips')\\n self.doc = c\\n self.related = []\\n\\n # two properties to help the use of the resulting table in a paper\\n self.reference_list = []\\n # nocite list intended for cutting and pasting directly into a latex document!\\n self.nocite = ''\\n\\n for m in c.sub_projects:\\n mdoc = r.getbyname(m.name, 'mips')\\n description = mdoc.long_name+' - '\\n citations = []\\n\\n # for these purposees we only want the things with a doi\\n # and we want only one, so we have to develop a heuristic to get the right one\\n for ci in mdoc.citations:\\n cidoc = esd.retrieve(ci.id)\\n ref = Reference(cidoc)\\n if ref.populated:\\n citations.append(ref)\\n citations.sort(key=lambda cc: cc.year)\\n index = -1\\n if len(citations) > 1:\\n # start by getting the most recent\\n year = citations[-1].year\\n index = -1\\n for i in range(len(citations)-1):\\n if citations[i].year == year:\\n if m.name in citations[i].text:\\n # it's one of the most recent and it has the MIP name\\n # in the document title.\\n index = i\\n description += citations[index].citestring\\n self.reference_list.append(citations[index].text)\\n self.nocite += '\\\\\\\\nocite{%s}\\\\n' % citations[index].citeguess\\n\\n # overwrite the real description for the purpose of this table\\n mdoc.description = description\\n self.related.append(mdoc)\\n\\n # want alphabetical order\\n self.related.sort(key=lambda mm: mm.name)\",\n \"def __init__(self, name, nlp):\\n if not Doc.has_extension(\\\"flesch_kincaid_grade_level\\\"):\\n Doc.set_extension(\\\"flesch_kincaid_grade_level\\\", getter=self.fk_grade)\\n\\n if not Doc.has_extension(\\\"flesch_kincaid_reading_ease\\\"):\\n Doc.set_extension(\\\"flesch_kincaid_reading_ease\\\", getter=self.fk_ease)\\n\\n if not Doc.has_extension(\\\"dale_chall\\\"):\\n Doc.set_extension(\\\"dale_chall\\\", getter=self.dale_chall)\\n\\n if not Doc.has_extension(\\\"smog\\\"):\\n Doc.set_extension(\\\"smog\\\", getter=self.smog)\\n\\n if not Doc.has_extension(\\\"coleman_liau_index\\\"):\\n Doc.set_extension(\\\"coleman_liau_index\\\", getter=self.coleman_liau)\\n\\n if not Doc.has_extension(\\\"automated_readability_index\\\"):\\n Doc.set_extension(\\\"automated_readability_index\\\", getter=self.ari)\\n\\n if not Doc.has_extension(\\\"forcast\\\"):\\n Doc.set_extension(\\\"forcast\\\", getter=self.forcast)\\n\\n if not Doc.has_extension(\\\"word_entropy\\\"):\\n Doc.set_extension(\\n \\\"word_entropy\\\", getter=lambda x: self.word_entropy(x, lemmatized=False)\\n )\\n\\n if not Doc.has_extension(\\\"word_entropy_l\\\"):\\n Doc.set_extension(\\n \\\"word_entropy_l\\\", getter=lambda x: self.word_entropy(x, lemmatized=True)\\n )\\n\\n if not Doc.has_extension(\\\"lix\\\"):\\n Doc.set_extension(\\\"lix\\\", getter=self.lix)\",\n \"def __init__(self,\\n title=\\\"[CDR Form Letter]\\\",\\n subject=None,\\n template=None,\\n pngName=\\\"dhhslogo.png\\\",\\n author=\\\"cdr\\\",\\n company=\\\"CIPS\\\",\\n binImage=False,\\n invitePara=\\\"\\\"):\\n\\n Document.__init__(self, title, author, company, subject)\\n self.generator = \\\"CDR RTF Writer\\\"\\n self.pngName = pngName # location of bitmap file for logo\\n self.margL = 1080 # 3/4-inch left margin\\n self.margR = 720 # 1/2-inch right margin\\n self.margT = 1080 # 5/8-inch top margin\\n self.margB = 1260 # 7/8-inch bottom margin\\n self.fSize = 21 # 10.5-point default font size\\n self.baskervilleFont = self.addFont(\\\"Baskerville Old Face\\\",\\n \\\"roman\\\",\\n \\\"Times New Roman\\\")\\n self.__addLetterHead(binImage)\\n if template:\\n try:\\n with open(template) as fp:\\n body = fp.read()\\n except Exception as e:\\n raise Exception(\\\"loading %s: %s\\\" % (template, str(e)))\\n if invitePara:\\n replacement = \\\"@@MISCDOC:%s@@\\\" % invitePara\\n body = body.replace(\\\"@@INVITATION@@\\\", replacement)\\n pattern = re.compile(\\\"@@MISCDOC:(.*?)@@\\\")\\n body = pattern.sub(lambda p: self.__loadMiscDoc(p), body)\\n self.addRawContent(body)\",\n \"def __init__(self, id, file=None):\\n self.__name__ = id\\n self.title = id\\n self.id = id\\n \\n self._setPropValue('content_type', 'text/xml')\\n\\n self.setup_transformProperties()\\n self.setup_schemaProperties()\\n\\n ZopePageTemplate.ZopePageTemplate.__init__(self, id)\\n\\n if hasattr(file, 'read'):\\n self.write(file.read())\",\n \"def build(self, text):\\n self._xml4nlp = Element('xml4nlp')\\n self._note = SubElement(self._xml4nlp, 'note')\\n self._doc = SubElement(self._xml4nlp, 'doc')\\n\\n para = SubElement(self._doc, 'para')\\n para.set(\\\"id\\\", \\\"0\\\")\\n para.text = text\\n\\n self._clean_note()\\n self.dom = self._xml4nlp\",\n \"def init():\",\n \"def __init__(self, document_path):\\n self.tree = etree.parse(document_path)\\n self.doc_id = get_doc_id(self.tree)\\n for element_type in ('nodes', 'edges', 'layers'):\\n self._extract_elements(self.tree, element_type)\",\n \"def __init__(self, mdef, extinfo=None):\\n raise NotImplementedError(\\\"EMFetcher abstract superclass\\\")\",\n \"def memb_init(self):\\n self.initialize()\",\n \"def __init__(self, letter, name):\\n\\n import cdr\\n from lxml import etree\\n\\n self.letter = letter\\n path = \\\"/MiscellaneousDocument/MiscellaneousDocumentTitle\\\"\\n query = f\\\"{path}/value eq {name}\\\"\\n try:\\n resp = cdr.search(\\\"guest\\\", query)\\n except Exception as e:\\n raise Exception(f\\\"failure loading misc doc {name!r}: {e}\\\")\\n if not resp:\\n raise Exception(f\\\"Miscellaneous document {name!r} not found\\\")\\n self.docId = resp[0].docId\\n try:\\n doc = cdr.getDoc(\\\"guest\\\", self.docId, getObject=True)\\n except Exception as e:\\n raise Exception(f\\\"Retrieving {self.docId}: {e}\\\")\\n self.root = etree.fromstring(doc.xml)\",\n \"def __init__(self, proknow, requestor):\\n self._proknow = proknow\\n self._requestor = requestor\",\n \"def __init__(self, document_name=None, id=None, p=None, rfid_presence=None, fdsid_list=None, necessary_lights=None, check_authenticity=None, uv_exp=None, authenticity_necessary_lights=None, local_vars_configuration=None): # noqa: E501 # noqa: E501\\n if local_vars_configuration is None:\\n local_vars_configuration = Configuration()\\n self.local_vars_configuration = local_vars_configuration\\n\\n self._document_name = None\\n self._id = None\\n self._p = None\\n self._rfid_presence = None\\n self._fdsid_list = None\\n self._necessary_lights = None\\n self._check_authenticity = None\\n self._uv_exp = None\\n self._authenticity_necessary_lights = None\\n self.discriminator = None\\n\\n if document_name is not None:\\n self.document_name = document_name\\n if id is not None:\\n self.id = id\\n if p is not None:\\n self.p = p\\n if rfid_presence is not None:\\n self.rfid_presence = rfid_presence\\n if fdsid_list is not None:\\n self.fdsid_list = fdsid_list\\n if necessary_lights is not None:\\n self.necessary_lights = necessary_lights\\n if check_authenticity is not None:\\n self.check_authenticity = check_authenticity\\n if uv_exp is not None:\\n self.uv_exp = uv_exp\\n if authenticity_necessary_lights is not None:\\n self.authenticity_necessary_lights = authenticity_necessary_lights\",\n \"def __init__(self, *args):\\n _snap.Schema_swiginit(self, _snap.new_Schema(*args))\",\n \"def init(self):\",\n \"def init(self):\",\n \"def __init__(self, invoice, buffer=None):\\n self.invoice = invoice\\n self.buffer = buffer\",\n \"def do_setup_pocs(self, *arg):\\n args, kwargs = string_to_params(*arg)\\n simulator = kwargs.get('simulator', [])\\n print_info(\\\"Simulator: {}\\\".format(simulator))\\n\\n try:\\n self.pocs = POCS(simulator=simulator)\\n self.pocs.initialize()\\n except error.PanError as e:\\n\\n pass\",\n \"def __init__(self):\\n super().__init__(interface.Metadata, DEFAULT_PRIORITIES)\",\n \"def __init__(self):\\n # parse MSR data\\n test_data, sent_dict, pair_dict = parse()\\n # word mover model -- take long to load the model!\\n wm_model = WMD()\\n # copnvert the ID->String dict to ID-> token dict\\n candidate_dict = wmd_utils.sent_dict_to_tok_dict(sent_dict)\\n wm_model.evaluate_model(candidate_dict, pair_dict)\",\n \"def __init__(self, ixs):\\n ixs = sorted(list(set(ixs)))\\n self.ixs = ixs\\n self.all_ids = fc.load_keys('../data/keys.json')\\n self.ids = set(itemgetter(*ixs)(self.all_ids))\\n corpus_files = glob('../data/documents/*')\\n corpus_files.sort(key=natural_keys)\\n self.corpus_files = corpus_files\\n\\n self.dictionary = Dictionary.load('../data/corpus.dict')\\n self.token2id = self.dictionary.token2id\\n logging.info(\\\"loading docs to RAM\\\")\\n self.docs_ram_dict = self.push_docs_to_ram()\\n\\n self.wv = Word2Vec.load('../data/w2v_200_5_w8').wv\\n\\n logging.info(\\\"loading qdr model\\\")\\n self.qdr = qdr.QueryDocumentRelevance.load_from_file('../data/qdr_model.gz')\\n\\n logging.info(\\\"loading mpk data\\\")\\n with open('../data/all_mpk.pkl', 'rb') as f:\\n self.all_mpk = pickle.load(f)\\n self.mpk = ft.MPK()\\n logging.info('data is loaded')\",\n \"def __init__(self, pageName):\\n self.pageName = pageName\\n self.updateFileData()\\n self.template = pystache.parse(unicode(self.fileData, 'utf-8'))\",\n \"def initialize(self):\\n raise NotImplementedError\",\n \"def initialize(self):\\n raise NotImplementedError\",\n \"def initialize(self):\\n raise NotImplementedError\",\n \"def __init__(self, run_id: str, doc: Dict, service: APIFactory):\\n self.run_id = run_id\\n self.file_id = doc['id']\\n self.name = doc['name']\\n self.title = doc.get('title', self.name)\\n self.caption = doc.get('caption')\\n self.format = doc.get('format', {})\\n self.service = service\",\n \"def __init__(self, data, context):\\n super(OpBasedBlip, self).__init__(data, OpBasedDocument(data, context))\\n self.__context = context\",\n \"def __init__(self, number, title, paragraphs):\\n self.number = number\\n self.title = title\\n self.paragraphs = []\\n for paragraph_lines in paragraphs:\\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\\n self.paragraphs.append(new_pragraph)\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: Optional[NoteArgs] = None,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def __init__(self, content, template, **styles):\\n self.content = content\\n self.template = template\\n self.styles = DEFAULT_DOCUMENT_STYLE.copy()\\n # This is a rendered document ready to be painted on a cairo surface\\n self._document = None # weasyprint.document.Document object\\n self.compiled_html = None\\n # Update the default styles and initialize self._document object\\n self.update_style(**styles)\",\n \"def __init__(self, doc_root):\\n self.doc_root = doc_root\\n site = yaml_load('data/site.yaml')['site']\\n self.site = site\",\n \"def __init__(self, footprint, mconf, name):\\n logging.debug(\\\"%s entered __init__\\\" % name)\\n self.image_id = mconf[\\\"image-id\\\"]\\n self.networks = mconf[\\\"networks\\\"]\\n self.ip_addresses = mconf[\\\"ip-addresses\\\"]\\n self.flavor=mconf[\\\"flavor\\\"]\\n self.machine_name = \\\"%s%s\\\" % (footprint.footprint_name, name)\\n self.footprint = footprint\",\n \"def __init__(self):\\n\\n self.prim_parser = parser.Parser()\",\n \"def __init__(self):\\n self.model = {'mol':[], 'nmol':0}\\n self.template = {} \\n self.config = {}\\n self.config['tfile'] = 'gau-template-bsse.gjf'\\n self.config['xyzfile'] = 'model.xyz'\\n self.config['jobfile'] = 'gau.gjf'\\n self.config['job_prefix'] = self.config['jobfile'].split(\\\".\\\")[0]\\n self.config['incr'] = 1\\n \\n self.rd_cmd_stream()\\n return\",\n \"def initialize(self):\",\n \"def initialize(self):\",\n \"def initialize(self):\",\n \"def initialize(self):\",\n \"def init(pt, content):\\n p = PTree()\\n p.distribution = pt.distribution\\n p.global_index = pt.global_index\\n p.start_index = pt.start_index\\n p.nb_segs = pt.nb_segs\\n p.content = content\\n return p\",\n \"def __init__(self, author, title, text=\\\"\\\", haiku=\\\"False\\\"):\\n self.author = author\\n self.title = title\\n self.text = text\\n self.haiku = haiku\\n self.name = self\\n Poem.obj_created += 1\",\n \"def __init__(self, metadata_folder='./'):\\n self.metadata = self.load_metadata(metadata_folder)\\n self.prefix = 'data/miap/images/'\\n return\",\n \"def __init__(self):\\n super(MethodInfo, self).__init__()\\n self.DocString = None\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n pass\",\n \"def init(self):\\n\\n # Set the appropraite acknowledgements and references\\n self.acknowledgements = mm_ace.acknowledgements()\\n self.references = mm_ace.references(self.name)\\n\\n logger.info(self.acknowledgements)\\n\\n return\",\n \"def __init__(self, page):\\n self.raw_page = page\\n self.page = etree.HTML(page)\",\n \"def __initialize(self):\\n\\t\\tself.matrix = [None] * self.size\\n\\t\\tself.__get_log_values()\\n\\t\\tfor row in range(self.size):\\n\\t\\t\\tself.matrix[row] = [None] * self.size\\n\\t\\tmax_len = self.__get_max_length()\\n\\t\\tdata = self.__get_data(self.text,max_len)\\n\\t\\tmpoly = self.__get_mpoly(data)\\n\\t\\tgpoly = self.__get_gploy()\\n\\t\\tself.final_data = self.__get_final_data(mpoly,gpoly)\\n\\t\\tself.__set_FIP(FP_num = 1)\\n\\t\\tself.__set_FIP(FP_num = 2)\\n\\t\\tself.__set_FIP(FP_num = 3)\\n\\t\\tself.__set_AP()\\n\\t\\tself.__fill_format_info_area()\\n\\t\\tself.__set_TP()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6678455","0.6528227","0.61595803","0.6156851","0.6055568","0.5943074","0.5899902","0.58804005","0.5799892","0.5787662","0.5785426","0.57476616","0.5745662","0.5730278","0.5711061","0.57024944","0.57002866","0.56933963","0.56916255","0.5650309","0.5642371","0.56372166","0.563107","0.5619945","0.5611441","0.56067646","0.56033146","0.559048","0.55903476","0.5570163","0.5557836","0.5556373","0.554617","0.55449826","0.55357164","0.55357164","0.55320334","0.55320334","0.55281556","0.5526939","0.55269027","0.5525727","0.5516003","0.5514747","0.55105704","0.5509616","0.55053586","0.55053425","0.54964846","0.54957527","0.54942054","0.54937106","0.5485756","0.54805654","0.5478798","0.5478368","0.54721195","0.5471966","0.5471397","0.54637444","0.5459585","0.5454191","0.5454191","0.5419761","0.5413882","0.5408383","0.5405378","0.54044735","0.5403595","0.5403178","0.5403178","0.5403178","0.53884065","0.5386877","0.5382099","0.5376507","0.5372699","0.53704166","0.5370247","0.53672254","0.5363482","0.53560483","0.53560483","0.53560483","0.53560483","0.53533024","0.5349584","0.5348078","0.5346775","0.5344139","0.5344139","0.5344139","0.5344139","0.5344139","0.5344139","0.5344139","0.5344139","0.53382325","0.53330165","0.5332926"],"string":"[\n \"0.6678455\",\n \"0.6528227\",\n \"0.61595803\",\n \"0.6156851\",\n \"0.6055568\",\n \"0.5943074\",\n \"0.5899902\",\n \"0.58804005\",\n \"0.5799892\",\n \"0.5787662\",\n \"0.5785426\",\n \"0.57476616\",\n \"0.5745662\",\n \"0.5730278\",\n \"0.5711061\",\n \"0.57024944\",\n \"0.57002866\",\n \"0.56933963\",\n \"0.56916255\",\n \"0.5650309\",\n \"0.5642371\",\n \"0.56372166\",\n \"0.563107\",\n \"0.5619945\",\n \"0.5611441\",\n \"0.56067646\",\n \"0.56033146\",\n \"0.559048\",\n \"0.55903476\",\n \"0.5570163\",\n \"0.5557836\",\n \"0.5556373\",\n \"0.554617\",\n \"0.55449826\",\n \"0.55357164\",\n \"0.55357164\",\n \"0.55320334\",\n \"0.55320334\",\n \"0.55281556\",\n \"0.5526939\",\n \"0.55269027\",\n \"0.5525727\",\n \"0.5516003\",\n \"0.5514747\",\n \"0.55105704\",\n \"0.5509616\",\n \"0.55053586\",\n \"0.55053425\",\n \"0.54964846\",\n \"0.54957527\",\n \"0.54942054\",\n \"0.54937106\",\n \"0.5485756\",\n \"0.54805654\",\n \"0.5478798\",\n \"0.5478368\",\n \"0.54721195\",\n \"0.5471966\",\n \"0.5471397\",\n \"0.54637444\",\n \"0.5459585\",\n \"0.5454191\",\n \"0.5454191\",\n \"0.5419761\",\n \"0.5413882\",\n \"0.5408383\",\n \"0.5405378\",\n \"0.54044735\",\n \"0.5403595\",\n \"0.5403178\",\n \"0.5403178\",\n \"0.5403178\",\n \"0.53884065\",\n \"0.5386877\",\n \"0.5382099\",\n \"0.5376507\",\n \"0.5372699\",\n \"0.53704166\",\n \"0.5370247\",\n \"0.53672254\",\n \"0.5363482\",\n \"0.53560483\",\n \"0.53560483\",\n \"0.53560483\",\n \"0.53560483\",\n \"0.53533024\",\n \"0.5349584\",\n \"0.5348078\",\n \"0.5346775\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.5344139\",\n \"0.53382325\",\n \"0.53330165\",\n \"0.5332926\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7006556"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":25688,"cells":{"query":{"kind":"string","value":"Intialise with a pyesdoc citation document"},"document":{"kind":"string","value":"def __init__(self, doc):\n\n self.doc = doc\n if self.doc.doi:\n self._populate()\n self.populated = True\n else:\n self.populated = False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def make_citation(meta):\n pass","def init_doc(self):\n raise NotImplementedError()","def main(rc):\n with store_client(rc) as sclient:\n for doc in rc.documents:\n sclient.copydoc(doc)","def make_bibtex(self):\n\n\t\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, ","def create_citation(cit):\n if cit is not None:\n if cit['citation-type'] == \"BIBTEX\":\n return pybtex.database.parse_string(cit['citation-value'], \"bibtex\")\n return None","def __call__(self, doc):\n return doc","def fini_doc(self):\n raise NotImplementedError()","def dummy(doc):\r\n return doc","def to_citation(self, type):\n acs_authors = \"; \".join(self.format_authors(\"acs\"))\n # Some articles don't come with pages. :-(\n pages_with_endash = (self.pages.replace(\"-\", \"\\u2013\") if self.pages\n else \"\")\n # Actually, not using quote() generally gives results that work fine.\n # The only issue is that when using Markdown URLs with parentheses in\n # Jupyter notebooks, the conversion to HTML gets it wrong, thinking\n # that the URL ends at the first close parentheses in the URL. (In\n # the notebook itself, it is fine, only the conversion to HTML messes\n # up.) So we might as well escape them generally.\n doi_url = f\"https://doi.org/{urllib.parse.quote(self.doi)}\"\n\n # BibLaTeX\n if type in [\"bib\", \"b\"]:\n # Create (hopefully) unique identifier\n author_decoded = unidecode(self.authors[0][\"family\"])\n journal_initials = \"\".join(c for c in self.journal_short\n if c.isupper())\n ref_identifier = f\"{author_decoded}{self.year}{journal_initials}\"\n ref_identifier = \"\".join(ref_identifier.split()) # remove spaces\n # Author names in bib style\n author_names = \" and \".join(self.format_authors(\"bib\"))\n journal = self.journal_short.replace(\". \", \".\\\\ \")\n # Open and close braces\n # Truthfully we don't need this. However, including the doubled\n # curly braces in the f-string makes vim's indentation go crazy.\n open, close = \"{\", \"}\"\n # Make the citation\n s = (f\"@article{open}{ref_identifier},\\n\"\n f\" doi = {{{self.doi}}},\\n\"\n f\" author = {{{author_names}}},\\n\"\n f\" journal = {{{journal}}},\\n\"\n f\" title = {{{self.title}}},\\n\"\n f\" year = {{{self.year}}},\\n\")\n if self.volume is not None:\n s += f\" volume = {{{self.volume}}},\\n\"\n if self.issue is not None:\n s += f\" issue = {{{self.issue}}},\\n\"\n if self.pages is not None:\n s += f\" pages = {{{self.pages.replace('-', '--')}}},\\n\"\n s += close\n # Replace Unicode characters with their LaTeX equivalents\n for char in _g.unicodeLatexDict:\n s = s.replace(char, _g.unicodeLatexDict[char])\n return s\n\n # Just DOI\n if type in [\"doi\", \"d\"]:\n return self.doi\n\n # The rest all have a long vs short type.\n # Discern long vs short type\n long = False\n if type[0].upper() == type[0]:\n long = True\n type = type.lower()\n\n # reStructuredText\n if type in [\"rst\", \"r\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"*{self.volume}* ({self.issue}), \" if self.issue\n else f\"*{self.volume},* \")\n return (author_title\n + f\"*{self.journal_short}* **{self.year},** \"\n + vol_issue\n + f\"{pages_with_endash}. \"\n + f\"`DOI: {self.doi} <{doi_url}>`_\")\n\n # Markdown\n if type in [\"markdown\", \"m\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"*{self.volume}* ({self.issue}), \" if self.issue\n else f\"*{self.volume},* \")\n return (author_title\n + f\"*{self.journal_short}* **{self.year},** \"\n + vol_issue\n + f\"{pages_with_endash}. \"\n + f\"[DOI: {self.doi}]({doi_url})\")\n\n # Word\n elif type in [\"word\", \"w\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"{self.volume} ({self.issue}), \" if self.issue\n else f\"{self.volume}, \")\n return (author_title\n + f\"{self.journal_short} {self.year}, \"\n + vol_issue\n + f\"{pages_with_endash}.\")\n\n else:\n raise ValueError(\"Invalid citation type '{type}' given\")","def cppdoc(self, irc, msg, args, num, req):\n self.googleq('www.cplusplus.com/reference/', req, num, irc)","def documento():\r\n\tpass","def cite(silent=False):\n if silent is False:\n print(__cite__)\n else:\n return __bibtex__","def getCitations (self, doc, verbose = False):\r\n if verbose is True:\r\n print \"getting citations for document \" +str(doc) \r\n return self.citations[int(doc)]","def lispdoc(self, irc, msg, args, num, req):\n self.googleq('http://lispdoc.com/', req, num, irc)","def Init(self, *args):\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)","def __call__(self, doc: Doc) -> Doc:\n return doc","def __call__(self, doc: Doc) -> Doc:\n return doc","def pythondoc(self, irc, msg, args, num, req):\n self.googleq('http://docs.python.org/library/', req, num, irc)","def add_ref(doc_name, bib_name, keep_label=False, slides=False):\n bib_path = bib_name # os.path.join(static_path, \"tex\", bib_name)\n if not slides:\n keep_label = True\n with open(doc_name, \"r\") as f:\n _file = f.read()\n # find citations\n match = re.findall(r\"\\[@.*?\\]\", _file)\n references = []\n # print(match)\n for cit in match:\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\".html\", delete=True)\n tmp = tempfile.NamedTemporaryFile(suffix=\".md\", delete=True)\n with open(tmp.name, \"w\") as md_file:\n # Open the file for writing.\n md_file.write(cit)\n\n pandoc_command = [\n \"pandoc\",\n \"-C\",\n tmp.name,\n \"--bibliography\",\n bib_path,\n \"--csl\",\n \"./templates/my-csl.csl\",\n \"-o\",\n tmp_cite_html.name,\n ]\n if not slides:\n for tag in [\"--metadata\", \"link-citations=true\"]:\n pandoc_command.append(tag)\n output = subprocess.check_output(\n pandoc_command, stderr=subprocess.STDOUT\n ).decode(\"utf-8\")\n print(output.rstrip())\n tmp.close()\n with open(tmp_cite_html.name, \"r\") as cite_html:\n # Open the file for writing.\n cit_new = cite_html.read()\n # print(cit_new)\n if not keep_label:\n # remove first line\n cit_new = \"\\n\".join(cit_new.splitlines()[1:])\n else:\n lines = cit_new.splitlines()\n # remove the <p> tags\n lines[0] = lines[0][3:-4]\n cit_new = \"\\n\".join(lines)\n if slides:\n _file = _file.replace(cit, cit_new)\n else:\n _file = _file.replace(cit, lines[0])\n # collect the references\n references.append(\"<p>\")\n references.append(\"\\n\".join(lines))\n references.append(\"</p>\")\n # paste_refs_end()\n tmp_cite_html.close()\n if slides:\n with open(doc_name, \"w\") as f:\n f.write(_file)\n if not slides:\n if references == []:\n _file=clean_html_refs(_file)\n else:\n _file = _file.replace(\"<bibliography-placeholder>\", \"\\n\".join(references))\n with open(doc_name, \"w\") as f:\n f.write(_file)\n return","def javadoc(self, irc, msg, args, num, req):\n self.googleq('download.oracle.com/javase/6/docs/', req, num, irc)","def get_bibtex(self):\n url=\"http://www.biomedcentral.com/download/citation\"\n parameters={'citation':'on', \n 'result-selection':'THIS_PAGE',\n 'suplements': 'false',\n 'citationType':'BIBTEX_WITH_ABSTRACT',\n 'articleIdThisPage':self.article_ids\n }\n data=urllib.urlencode(parameters)\n self.bibtex=urllib2.urlopen(url,data)","def internal_citations(text, initial_label=None,\n require_marker=False, title=None):\n if not initial_label:\n initial_label = Label()\n citations = []\n\n def multiple_citations(matches, comment):\n \"\"\"i.e. head :: tail\"\"\"\n for match, start, end in matches:\n label = initial_label\n for submatch in chain([match.head], match.tail):\n cit = ParagraphCitation(\n submatch.pos[0], submatch.pos[1],\n match_to_label(submatch.tokens, label, comment=comment),\n full_start=start,\n full_end=end,\n in_clause=True)\n label = cit.label # update the label to keep context\n citations.append(cit)\n\n def single_citations(matches, comment):\n for match, start, end in matches:\n full_start = start\n if match.marker is not '':\n # Remove the marker from the beginning of the string\n start = match.marker.pos[1]\n citations.append(ParagraphCitation(\n start, end, match_to_label(match, initial_label,\n comment=comment),\n full_start=full_start))\n\n single_citations(grammar.marker_comment.scanString(text), True)\n\n multiple_citations(grammar.multiple_non_comments.scanString(text), False)\n multiple_citations(grammar.multiple_appendix_section.scanString(text),\n False)\n multiple_citations(grammar.multiple_comments.scanString(text), True)\n multiple_citations(grammar.multiple_appendices.scanString(text), False)\n multiple_citations(grammar.multiple_period_sections.scanString(text),\n False)\n\n single_citations(grammar.marker_appendix.scanString(text), False)\n single_citations(grammar.appendix_with_section.scanString(text), False)\n single_citations(grammar.marker_paragraph.scanString(text), False)\n single_citations(grammar.mps_paragraph.scanString(text), False)\n single_citations(grammar.m_section_paragraph.scanString(text), False)\n if not require_marker:\n single_citations(grammar.section_paragraph.scanString(text), False)\n single_citations(grammar.part_section_paragraph.scanString(text),\n False)\n multiple_citations(\n grammar.multiple_section_paragraphs.scanString(text), False)\n\n # Some appendix citations are... complex\n for match, start, end in grammar.appendix_with_part.scanString(text):\n full_start = start\n if match.marker is not '':\n start = match.marker.pos[1]\n label = filter(lambda l: l != '.', list(match)[3:])\n label = dict(zip(['p1', 'p2', 'p3'], label))\n citations.append(ParagraphCitation(\n start, end, initial_label.copy(\n appendix=match.appendix, appendix_section=match.a1,\n **label), full_start=full_start))\n\n # Internal citations can sometimes be in the form XX CFR YY.ZZ\n for match, start, end in grammar.internal_cfr_p.scanString(text):\n # Check if this is a reference to the CFR title and part we are parsing\n if match.cfr_title == title and match[1] == initial_label.to_list()[0]:\n full_start = start\n if match.marker is not '':\n # Remove the marker from the beginning of the string\n start = match.marker.pos[1]\n citations.append(ParagraphCitation(\n start, end, match_to_label(match, initial_label),\n full_start=full_start))\n else:\n continue\n\n # And sometimes there are several of them\n for match, start, end in grammar.multiple_cfr_p.scanString(text):\n label = initial_label\n if match.head.cfr_title == title:\n for submatch in chain([match.head], match.tail):\n if submatch.part == initial_label.to_list()[0]:\n cit = ParagraphCitation(\n submatch.pos[0], submatch.pos[1],\n match_to_label(submatch.tokens, label),\n full_start=start,\n full_end=end,\n in_clause=True)\n label = cit.label # update the label to keep context\n citations.append(cit)\n else:\n continue\n\n # Remove any sub-citations\n final_citations = []\n for cit in citations:\n if not any(cit in other for other in citations):\n final_citations.append(cit)\n\n return final_citations","def DocString():\n return","def main_docstring():","def test_doc_with_comments():\n doc = CoNLL.conll2doc(input_str=RUSSIAN_SAMPLE)\n check_russian_doc(doc)","def _populate(self):\n\n # Assume the first word is what we want, and we can find well formed years\n # This sucks, but will work for these ones.\n # Roll on bibtex for citations in the CIM.\n\n citation_detail = self.doc.citation_detail\n author = citation_detail.split(',')[0]\n match = '([^\\w])19|20\\d\\d([^\\w])*?'\n m = re.search(match, citation_detail)\n if m:\n year = m.group(0)\n else:\n year = None\n\n # one error in existing es-doc content to be fixed:\n if 'van Vuuren DP' in author:\n author = 'van Vuuren'\n print 'applying vv fix'\n\n self.year = int(year)\n\n # We assume that this table will have entries which ne\n\n # I use the first three letters of a an authors name, and for\n # three or more authors, EA, and then the year for my bibtex citation string\n self.citeguess = author[0:3] + 'EA' + year[2:]\n # This is what will appear in the table:\n self.citestring = '%s et al. (%s)' % (author, year)\n # Keep this for a reference list for checking against the eventual bibtex reference list.\n self.text = citation_detail","def docs():","def test_citations_and_toc_with_valid_defaults(self):\n\n pandoc_default_files = [\n os.path.join(\n TEST_DEFAULT_FILES_PATH,\n \"valid_defaults_with_toc_and_citations.yaml\",\n )\n ]\n\n settings = get_settings(\n PANDOC_DEFAULT_FILES=pandoc_default_files,\n FORMATTED_FIELDS=FORMATTED_FIELDS,\n )\n pandoc_reader = PandocReader(settings)\n\n source_path = os.path.join(\n TEST_CONTENT_PATH, \"valid_content_with_citation.md\"\n )\n output, metadata = pandoc_reader.read(source_path)\n self.maxDiff = None # pylint: disable=invalid-name\n\n self.assertEqual(\n (\n '<h2 id=\"string-theory\">String Theory</h2>\\n'\n \"<p>But this foundational principle of science has\"\n \" now been called into question by\"\n ' <a href=\"https://www.britannica.com/science/'\n 'string-theory\">String Theory</a>,'\n \" which is a relative newcomer to theoretical physics, but one\"\n \" that has captured the common imagination, judging by\"\n \" the popular explanations that abound on the Web\"\n ' <span class=\"citation\" data-cites=\"mann2019 wood2019'\n ' jones2020\">[1]–[3]</span>.'\n \" And whether string theory is or is not science, Popper\"\n \" notwithstanding, is an issue that is still up for debate\"\n \" <span\"\n ' class=\"citation\" data-cites=\"siegel2015 castelvecchi2016'\n ' alves2017 francis2019\">[4]–[7]</span>.</p>\\n'\n '<h1 class=\"unnumbered\" id=\"bibliography\">References</h1>\\n'\n '<div id=\"refs\" class=\"references csl-bib-body\"'\n ' role=\"doc-bibliography\">\\n'\n '<div id=\"ref-mann2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[1]'\n ' </div><div class=\"csl-right-inline\">A. Mann,'\n \" <span>“<span>What Is String Theory?</span>”</span>\"\n \" 20-Mar-2019. [Online].\"\n ' Available: <a href=\"https://www.livescience.com/'\n '65033-what-is-string-theory.html\">'\n \"https://www.livescience.com/\"\n \"65033-what-is-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-wood2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[2] </div>'\n '<div class=\"csl-right-inline\">'\n \"C. Wood, <span>“<span>What Is String Theory?</span>.\"\n \" Reference article:\"\n \" A simplified explanation and brief history of string\"\n \" theory,”</span> 11-Jul-2019.\"\n ' [Online]. Available: <a href=\"https://www.space.com/'\n '17594-string-theory.html\">'\n \"https://www.space.com/17594-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-jones2020\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[3]'\n ' </div><div class=\"csl-right-inline\">'\n 'A. Z. Jones, <span>“<span class=\"nocase\">The Basics of String'\n \" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\"\n ' <a href=\"https://www.thoughtco.com/'\n 'what-is-string-theory-2699363\">'\n \"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-siegel2015\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[4]'\n ' </div><div class=\"csl-right-inline\">'\n \"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\"\n \" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\"\n \" <a\"\n ' href=\"https://www.forbes.com/sites/'\n \"startswithabang/2015/12/23/\"\n 'why-string-theory-is-not-science/\">https://www.forbes.com/'\n \"sites/startswithabang/2015/12/23/\"\n \"why-string-theory-is-not-science/</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-castelvecchi2016\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[5]'\n ' </div><div class=\"csl-right-inline\">'\n 'D. Castelvecchi, <span>“<span class=\"nocase\">'\n \"Feuding physicists turn\"\n \" to philosophy for help</span>. String theory is at the\"\n \" heart of a debate over the integrity of the scientific\"\n \" method itself,”</span> 05-Jan-2016. [Online]. Available:\"\n ' <a href=\"https://www.nature.com/news/'\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\">'\n \"https://www.nature.com/news/\"\n \"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-alves2017\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[6] </div>'\n '<div class=\"csl-right-inline\">'\n 'R. A. Batista and J. Primack, <span>“<span class=\"nocase\">'\n \"Is String theory falsifiable?</span>. Can a theory that isn’t\"\n \" completely testable still be useful to physics?”</span>\"\n \" [Online].\"\n ' Available: <a href=\"https://metafact.io/factchecks/'\n '30-is-string-theory-falsifiable\">'\n \"https://metafact.io/factchecks/\"\n \"30-is-string-theory-falsifiable</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-francis2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[7]'\n ' </div><div class=\"csl-right-inline\">'\n 'M. R. Francis, <span>“<span class=\"nocase\">Falsifiability and'\n \" physics</span>. Can a theory that isn’t completely testable\"\n \" still be useful to physics?”</span> 23-Apr-2019.\"\n \" [Online]. Available:\"\n ' <a href=\"https://www.scientificamerican.com/'\n 'article/is-string-theory-science/\">'\n \"https://www.scientificamerican.com/article/is-\"\n \"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n \"</div>\\n\"\n ),\n output,\n )\n\n self.assertEqual(\"Valid Content With Citation\", str(metadata[\"title\"]))\n self.assertEqual(\"My Author\", str(metadata[\"author\"]))\n self.assertEqual(\"2020-10-16 00:00:00\", str(metadata[\"date\"]))\n self.assertEqual(\n (\n '<nav class=\"toc\" role=\"doc-toc\">\\n'\n \"<ul>\\n\"\n '<li><a href=\"#string-theory\">String Theory</a></li>\\n'\n '<li><a href=\"#bibliography\">References</a></li>\\n'\n \"</ul>\\n</nav>\\n\"\n ),\n str(metadata[\"toc\"]),\n )","def test_citations_and_toc(self):\n settings = get_settings(\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\"+citations\"],\n PANDOC_ARGS=PANDOC_ARGS\n + [\n \"--toc\",\n \"-C\",\n \"--csl=https://www.zotero.org/styles/ieee-with-url\",\n \"--metadata=link-citations:false\",\n \"--metadata=reference-section-title:References\",\n ],\n FORMATTED_FIELDS=FORMATTED_FIELDS,\n )\n\n pandoc_reader = PandocReader(settings)\n source_path = os.path.join(\n TEST_CONTENT_PATH, \"valid_content_with_citation.md\"\n )\n output, metadata = pandoc_reader.read(source_path)\n self.maxDiff = None\n\n self.assertEqual(\n (\n '<h2 id=\"string-theory\">String Theory</h2>\\n'\n \"<p>But this foundational principle of science has\"\n \" now been called into question by\"\n ' <a href=\"https://www.britannica.com/science/'\n 'string-theory\">String Theory</a>,'\n \" which is a relative newcomer to theoretical physics, but one\"\n \" that has captured the common imagination, judging by\"\n \" the popular explanations that abound on the Web\"\n ' <span class=\"citation\" data-cites=\"mann2019 wood2019'\n ' jones2020\">[1]–[3]</span>.'\n \" And whether string theory is or is not science, Popper\"\n \" notwithstanding, is an issue that is still up for debate\"\n \" <span\"\n ' class=\"citation\" data-cites=\"siegel2015 castelvecchi2016'\n ' alves2017 francis2019\">[4]–[7]</span>.</p>\\n'\n '<h1 class=\"unnumbered\" id=\"bibliography\">References</h1>\\n'\n '<div id=\"refs\" class=\"references csl-bib-body\"'\n ' role=\"doc-bibliography\">\\n'\n '<div id=\"ref-mann2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[1]'\n ' </div><div class=\"csl-right-inline\">A. Mann,'\n \" <span>“<span>What Is String Theory?</span>”</span>\"\n \" 20-Mar-2019. [Online].\"\n ' Available: <a href=\"https://www.livescience.com/'\n '65033-what-is-string-theory.html\">'\n \"https://www.livescience.com/\"\n \"65033-what-is-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-wood2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[2] </div>'\n '<div class=\"csl-right-inline\">'\n \"C. Wood, <span>“<span>What Is String Theory?</span>.\"\n \" Reference article:\"\n \" A simplified explanation and brief history of string\"\n \" theory,”</span> 11-Jul-2019.\"\n ' [Online]. Available: <a href=\"https://www.space.com/'\n '17594-string-theory.html\">'\n \"https://www.space.com/17594-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-jones2020\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[3]'\n ' </div><div class=\"csl-right-inline\">'\n 'A. Z. Jones, <span>“<span class=\"nocase\">The Basics of String'\n \" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\"\n ' <a href=\"https://www.thoughtco.com/'\n 'what-is-string-theory-2699363\">'\n \"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-siegel2015\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[4]'\n ' </div><div class=\"csl-right-inline\">'\n \"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\"\n \" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\"\n \" <a\"\n ' href=\"https://www.forbes.com/sites/'\n \"startswithabang/2015/12/23/\"\n 'why-string-theory-is-not-science/\">https://www.forbes.com/'\n \"sites/startswithabang/2015/12/23/\"\n \"why-string-theory-is-not-science/</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-castelvecchi2016\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[5]'\n ' </div><div class=\"csl-right-inline\">'\n 'D. Castelvecchi, <span>“<span class=\"nocase\">'\n \"Feuding physicists turn\"\n \" to philosophy for help</span>. String theory is at the\"\n \" heart of a debate over the integrity of the scientific\"\n \" method itself,”</span> 05-Jan-2016. [Online]. Available:\"\n ' <a href=\"https://www.nature.com/news/'\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\">'\n \"https://www.nature.com/news/\"\n \"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-alves2017\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[6] </div>'\n '<div class=\"csl-right-inline\">'\n 'R. A. Batista and J. Primack, <span>“<span class=\"nocase\">'\n \"Is String theory falsifiable?</span>. Can a theory that isn’t\"\n \" completely testable still be useful to physics?”</span>\"\n \" [Online].\"\n ' Available: <a href=\"https://metafact.io/factchecks/'\n '30-is-string-theory-falsifiable\">'\n \"https://metafact.io/factchecks/\"\n \"30-is-string-theory-falsifiable</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-francis2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[7]'\n ' </div><div class=\"csl-right-inline\">'\n 'M. R. Francis, <span>“<span class=\"nocase\">Falsifiability and'\n \" physics</span>. Can a theory that isn’t completely testable\"\n \" still be useful to physics?”</span> 23-Apr-2019.\"\n \" [Online]. Available:\"\n ' <a href=\"https://www.scientificamerican.com/'\n 'article/is-string-theory-science/\">'\n \"https://www.scientificamerican.com/article/is-\"\n \"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n \"</div>\\n\"\n ),\n output,\n )\n\n self.assertEqual(\"Valid Content With Citation\", str(metadata[\"title\"]))\n self.assertEqual(\"My Author\", str(metadata[\"author\"]))\n self.assertEqual(\"2020-10-16 00:00:00\", str(metadata[\"date\"]))\n self.assertEqual(\n (\n '<nav class=\"toc\" role=\"doc-toc\">\\n'\n \"<ul>\\n\"\n '<li><a href=\"#string-theory\">String Theory</a></li>\\n'\n '<li><a href=\"#bibliography\">References</a></li>\\n'\n \"</ul>\\n</nav>\\n\"\n ),\n str(metadata[\"toc\"]),\n )\n self.assertEqual(\n (\n \"<p>But this foundational principle of science has now been\"\n \" called into question by\"\n ' <a href=\"https://www.britannica.com/science/string-theory\">'\n \"String Theory</a>.</p>\\n\"\n ),\n str(metadata[\"summary\"]),\n )","def __call__(self, filename, manuscript=\"\", journal=\"\", author=[], \n publisher=\"\"):\n\n # check the parameters\n while len(author) < 4:\n author.append(\"\")\n\n doc = getDocument(filename)\n\n Story = []\n\n # Section 1\n Story.append(\n Paragraph(\n \"\"\"<seqreset id=\"main\" /><seq id=\"main\">. THIS Amendment hereby \n modifies and supplements the attached Publication Agreement \n concerning the following Article:\"\"\", styles['outer_style'])\n )\n\n journal_info_table = Table([\n [fillInRow(manuscript, \"(manuscript title)\", width=inch*5)],\n [fillInRow(journal, \"(journal name)\", width=inch*5)],\n ],\n )\n journal_info_table.hAlign = 'LEFT'\n Story.append(journal_info_table)\n\n # Section 2\n Story.append(\n Paragraph(\n \"\"\"<seq id=\"main\">. The parties to the Publication Agreement and\n to this Amendment are:\"\"\", styles['outer_style'])\n )\n\n journal_info_table = Table([\n [fillInRow(author[0], \"(corresponding author)\", width=inch*5)],\n [Paragraph(\"and\", styles['outer_style'])],\n [fillInRow(journal, \"(the Publisher)\", width=inch*5)],\n ],\n )\n journal_info_table.hAlign = 'LEFT'\n Story.append(journal_info_table)\n\n # Section 3\n Story.append(\n Paragraph(\n \"\"\"<seq id=\"main\">. The parties agree that wherever there is any\n conflict between the Amendment and the Publication Agreement, \n the provisions of this Amendment are paramount and the \n Publication Agreement shall be construed accordingly.\"\"\",\n styles['outer_style'])\n )\n\n # Section 4\n Story.append(\n Paragraph(\n \"\"\"<seq id=\"main\">. Notwithstanding any terms in the Publication\nAgreement to the contrary and in addition to the rights retained by Author \nor licensed by Published to Author in the Publication Agreement and any fair \nuse rights of Author, Author and Publisher agree that the Author shall also \nretain the following rights:\"\"\",\n styles['outer_style'])\n )\n\n # 4a\n Story.append(\n Paragraph(\n \"\"\"a. The Author shall, without limitation, have the non-exclusive right to use, reproduce, distribute, create derivative works including update, perform, and display publicly, the Article in electronic, digital or print form in connection with the Author's teaching, conference presentations, lectures, other scholarly works, and for all of Author's academic and professional activities. \"\"\",\n styles['inner_style'])\n )\n\n # 4b\n Story.append(\n Paragraph(\n \"\"\"b. Once the Article has been published by Publisher, the Author shall also have all the non-exclusive rights necessary to make, or to authorize others to make, the final published version of the Article available in digital form over the Internet, including but not limited to a website under the control of the Author or the Author's employer or through any digital repository, such as MIT's DSpace or the National Library of Medicine's PubMed Central database.\"\"\",\n styles['inner_style'])\n )\n\n #4c\n Story.append(\n Paragraph(\n \"\"\"c. The Author further retains all non-exclusive rights necessary to grant to the Author's employing institution the non-exclusive right to use, reproduce, distribute, display, publicly perform, and make copies of the work in electronic, digital or in print form in connection with teaching, digital repositories, conference presentations, lectures, other scholarly works, and all academic and professional activities conducted at the Author's employing institution. \"\"\",\n styles['inner_style'])\n )\n\n # Section 5\n Story.append(\n Paragraph(\n \"\"\"<seq id=\"main\" />. <b>Final Agreement.</b> This Amendment and the Publication Agreement, taken together, constitute the final agreement between the Author and the Publisher with respect to the publication of the Article and allocation of rights under copyright in the Article. Any modification of or additions to the terms of this Amendment or to the Publication Agreement must be in writing and executed by both Publisher and Author in order to be effective.\"\"\",\n styles['outer_style'])\n )\n\n # Signature\n journal_info_table = Table([\n [\"AUTHOR\", \" \", \"PUBLISHER\"],\n [fillInRow(\"\", \"(corresponding author on behalf of all authors)\"),\n \"\", fillInRow(\"\", \"\")],\n [fillInRow(\"\", \"Date\"),\n \"\",\n fillInRow(\"\", \"Date\")]\n ],\n colWidths=[inch*3, inch*.25, inch*3],\n )\n\n journal_info_table.hAlign = 'LEFT'\n Story.append(journal_info_table)\n\n # MIT Directive\n Story.append(\n Paragraph(\"<b>MIT Authors:</b>\", styles['outer_style'])\n )\n Story.append(\n Paragraph(\"Please fax a copy of the agreement to 617-253-8894. Direct any questions to amend-cip@mit.edu\",\n styles['inner_style'])\n )\n\n\n agreement = \"%s %s\" % (self.NAME, self.VERSION)\n doc.build(Story, \n onFirstPage=mit_pageInfo, onLaterPages=mit_pageInfo)","def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\r\n pass","def fill(self):\n if self.source == 'citations':\n url = self._scholarly.URLS(\"CITATIONPUB\").format(self.id_citations)\n soup = self._scholarly._get_soup(\n self._scholarly.URLS('HOST').format(url))\n self.bib['title'] = soup.find('div', id='gsc_vcd_title').text\n\n if soup.find('a', class_='gsc_vcd_title_link'):\n self.bib['url'] = soup.find(\n 'a', class_='gsc_vcd_title_link')['href']\n\n for item in soup.find_all('div', class_='gs_scl'):\n key = item.find(class_='gsc_vcd_field').text\n val = item.find(class_='gsc_vcd_value')\n if key == 'Authors':\n self.bib['author'] = ' and '.join(self.get_authorlist(val))\n elif key == 'Journal':\n self.bib['journal'] = val.text\n elif key == 'Volume':\n self.bib['volume'] = val.text\n elif key == 'Issue':\n self.bib['number'] = val.text\n elif key == 'Pages':\n self.bib['pages'] = val.text\n elif key == 'Publisher':\n self.bib['publisher'] = val.text\n elif key == 'Publication date':\n self.bib['year'] = arrow.get(val.text).year\n elif key == 'Description':\n if val.text[0:8].lower() == 'abstract':\n val = val.text[9:].strip()\n self.bib['abstract'] = val\n elif key == 'Total citations':\n self.id_scholarcitedby = re.findall(\n self._scholarly.URLS('SCHOLARPUBRE'), val.a['href'])[0]\n\n # number of citation per year\n years = [int(y.text) for y in soup.find_all(class_='gsc_vcd_g_t')]\n cites = [int(c.text) for c in soup.find_all(class_='gsc_vcd_g_al')]\n self.cites_per_year = dict(zip(years, cites))\n\n if soup.find('div', class_='gsc_vcd_title_ggi'):\n self.bib['eprint'] = soup.find(\n 'div', class_='gsc_vcd_title_ggi').a['href']\n self._filled = True\n\n elif self.source == 'scholar':\n self.bib['add_to_lib'] = self.url_add_sclib\n\n try:\n bibtex = self._scholarly._get_soup(self.url_scholarbib)\n bibtex = bibtex.find('pre').string\n self.bib.update(bibtexparser.loads(bibtex).entries[0])\n self.bib['author_count'] = str(\n len(self.bib['author'].split('and')))\n self.bib['age'] = str(\n int(date.today().year) - int(self.bib['year']))\n except:\n # did not find year\n pass\n\n self._filled = True\n return self","def doc(docid):\n\t\n\tdata = {'id':docid,\n\t\t\t'text':\"Some made up text for classification\"}\n\treturn _send(data)","def edit_document():","def document(self):\n ...","def test_citations_and_toc_2(self):\n settings = get_settings(\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\"+citations\"],\n PANDOC_ARGS=PANDOC_ARGS\n + [\n \"--table-of-contents\",\n \"--citeproc\",\n \"--csl=https://www.zotero.org/styles/ieee-with-url\",\n \"--metadata=link-citations:false\",\n \"--metadata=reference-section-title:References\",\n ],\n FORMATTED_FIELDS=FORMATTED_FIELDS,\n )\n\n pandoc_reader = PandocReader(settings)\n source_path = os.path.join(\n TEST_CONTENT_PATH, \"valid_content_with_citation.md\"\n )\n output, metadata = pandoc_reader.read(source_path)\n self.maxDiff = None\n\n self.assertEqual(\n (\n '<h2 id=\"string-theory\">String Theory</h2>\\n'\n \"<p>But this foundational principle of science has\"\n \" now been called into question by\"\n ' <a href=\"https://www.britannica.com/science/'\n 'string-theory\">String Theory</a>,'\n \" which is a relative newcomer to theoretical physics, but one\"\n \" that has captured the common imagination, judging by\"\n \" the popular explanations that abound on the Web\"\n ' <span class=\"citation\" data-cites=\"mann2019 wood2019'\n ' jones2020\">[1]–[3]</span>.'\n \" And whether string theory is or is not science, Popper\"\n \" notwithstanding, is an issue that is still up for debate\"\n \" <span\"\n ' class=\"citation\" data-cites=\"siegel2015 castelvecchi2016'\n ' alves2017 francis2019\">[4]–[7]</span>.</p>\\n'\n '<h1 class=\"unnumbered\" id=\"bibliography\">References</h1>\\n'\n '<div id=\"refs\" class=\"references csl-bib-body\"'\n ' role=\"doc-bibliography\">\\n'\n '<div id=\"ref-mann2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[1]'\n ' </div><div class=\"csl-right-inline\">A. Mann,'\n \" <span>“<span>What Is String Theory?</span>”</span>\"\n \" 20-Mar-2019. [Online].\"\n ' Available: <a href=\"https://www.livescience.com/'\n '65033-what-is-string-theory.html\">'\n \"https://www.livescience.com/\"\n \"65033-what-is-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-wood2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[2] </div>'\n '<div class=\"csl-right-inline\">'\n \"C. Wood, <span>“<span>What Is String Theory?</span>.\"\n \" Reference article:\"\n \" A simplified explanation and brief history of string\"\n \" theory,”</span> 11-Jul-2019.\"\n ' [Online]. Available: <a href=\"https://www.space.com/'\n '17594-string-theory.html\">'\n \"https://www.space.com/17594-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-jones2020\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[3]'\n ' </div><div class=\"csl-right-inline\">'\n 'A. Z. Jones, <span>“<span class=\"nocase\">The Basics of String'\n \" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\"\n ' <a href=\"https://www.thoughtco.com/'\n 'what-is-string-theory-2699363\">'\n \"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-siegel2015\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[4]'\n ' </div><div class=\"csl-right-inline\">'\n \"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\"\n \" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\"\n \" <a\"\n ' href=\"https://www.forbes.com/sites/'\n \"startswithabang/2015/12/23/\"\n 'why-string-theory-is-not-science/\">https://www.forbes.com/'\n \"sites/startswithabang/2015/12/23/\"\n \"why-string-theory-is-not-science/</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-castelvecchi2016\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[5]'\n ' </div><div class=\"csl-right-inline\">'\n 'D. Castelvecchi, <span>“<span class=\"nocase\">'\n \"Feuding physicists turn\"\n \" to philosophy for help</span>. String theory is at the\"\n \" heart of a debate over the integrity of the scientific\"\n \" method itself,”</span> 05-Jan-2016. [Online]. Available:\"\n ' <a href=\"https://www.nature.com/news/'\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\">'\n \"https://www.nature.com/news/\"\n \"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-alves2017\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[6] </div>'\n '<div class=\"csl-right-inline\">'\n 'R. A. Batista and J. Primack, <span>“<span class=\"nocase\">'\n \"Is String theory falsifiable?</span>. Can a theory that isn’t\"\n \" completely testable still be useful to physics?”</span>\"\n \" [Online].\"\n ' Available: <a href=\"https://metafact.io/factchecks/'\n '30-is-string-theory-falsifiable\">'\n \"https://metafact.io/factchecks/\"\n \"30-is-string-theory-falsifiable</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-francis2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[7]'\n ' </div><div class=\"csl-right-inline\">'\n 'M. R. Francis, <span>“<span class=\"nocase\">Falsifiability and'\n \" physics</span>. Can a theory that isn’t completely testable\"\n \" still be useful to physics?”</span> 23-Apr-2019.\"\n \" [Online]. Available:\"\n ' <a href=\"https://www.scientificamerican.com/'\n 'article/is-string-theory-science/\">'\n \"https://www.scientificamerican.com/article/is-\"\n \"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n \"</div>\\n\"\n ),\n output,\n )\n\n self.assertEqual(\"Valid Content With Citation\", str(metadata[\"title\"]))\n self.assertEqual(\"My Author\", str(metadata[\"author\"]))\n self.assertEqual(\"2020-10-16 00:00:00\", str(metadata[\"date\"]))\n self.assertEqual(\n (\n '<nav class=\"toc\" role=\"doc-toc\">\\n'\n \"<ul>\\n\"\n '<li><a href=\"#string-theory\">String Theory</a></li>\\n'\n '<li><a href=\"#bibliography\">References</a></li>\\n'\n \"</ul>\\n</nav>\\n\"\n ),\n str(metadata[\"toc\"]),\n )","def main():\n papers_with_references = add_references_to_papers(PAPERS_FILE, TEXT_DIR)\n citations = match_citations_with_papers(papers_with_references)\n insert_into_citation_table(citations)","def newThesisCitation(self, **attrlinks):\n return ThesisCitation(self, **attrlinks)","def beehive_make_doc(self):\n run_data = {\n u'tags':[u'doc'],\n u'local_package_path':self.local_package_path\n } \n self.ansible_playbook(u'docs', run_data, \n playbook=self.beehive_doc_playbook)","def cpp_docs(self, html):\n self._cppdocs = html\n return self","def doc_string():\n pass # pass does nothing","def getdoc(object):\r\n try:\r\n doc = object.__doc__\r\n except AttributeError:\r\n return None\r\n if not isinstance(doc, types.StringTypes):\r\n return None\r\n return cleandoc(doc)","def initDocTagText(self):\n self.doc, self.tag, self.text = Doc().tagtext()","def _initEditEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\r\n pass","def citeproc(style, reference_list):\n pass","def doc(caesar, input):\n name = input.group(1)\n name = name.lower()\n\n if caesar.doc.has_key(name): \n caesar.reply(caesar.doc[name][0])\n if caesar.doc[name][1]: \n caesar.say('e.g. ' + caesar.doc[name][1])","def create_from_document(doc: Dict[str, Any]) -> 'Publication':\n return Publication(\n name=doc['doc_name'],\n title=doc['doc_title'][:100],\n type=doc['doc_type'],\n number=doc['doc_num'],\n is_ignored=False,\n is_revoked=False\n )","def StartDoc(*args, **kwargs):\n return _gdi_.DC_StartDoc(*args, **kwargs)","def _copydoc():\n with open(app_config.TRANSCRIPT_HTML_PATH) as f:\n html = f.read()\n\n doc = CopyDoc(html)\n context = {\n 'doc': doc\n }\n\n return make_response(render_template('copydoc.html', **context))","def newBookCitation(self, **attrlinks):\n return BookCitation(self, **attrlinks)","def test_doc_representation(self):\n doc_str = \"# This is a comment\\n* One\\nText text\"\n doc = parser.parse(doc_str)\n\n self.assertEqual(str(doc), doc_str)\n\n doc_str = \"Text\\nMore text\\n\\n\\nSome empty lines and text\\n* HL\"\n doc = parser.parse(doc_str)\n\n self.assertEqual(str(doc), doc_str)\n\n doc_str = \"- List one\\n + Slist one\\n + Slist two\"\n doc = parser.parse(doc_str)\n\n self.assertEqual(str(doc), doc_str)","def contract(docid):\n return render_template('doc.html', docid=docid)","def chikin():\n return TexSoup(open(seed('samples/chikin.tex')))","def cite(self, arg=None):\n nums = self.selector.select_by_index(arg)\n if nums is None or not nums:\n self.visual.error(\"Need a selection to cite.\")\n return\n citation_id = \", \".join([self.reference_entry_id_list[n] for n in nums])\n citation = \"\\\\cite{{{}}}\".format(citation_id)\n # clipboard.copy(citation_id)\n clipboard.copy(citation)\n self.visual.message(\"Copied to clipboard: {}\".format(citation))","def newJournalCitation(self, **attrlinks):\n return JournalCitation(self, **attrlinks)","def triple_quote_docs():\n return","def __init__(self,\n title=\"[CDR Form Letter]\",\n subject=None,\n template=None,\n pngName=\"dhhslogo.png\",\n author=\"cdr\",\n company=\"CIPS\",\n binImage=False,\n invitePara=\"\"):\n\n Document.__init__(self, title, author, company, subject)\n self.generator = \"CDR RTF Writer\"\n self.pngName = pngName # location of bitmap file for logo\n self.margL = 1080 # 3/4-inch left margin\n self.margR = 720 # 1/2-inch right margin\n self.margT = 1080 # 5/8-inch top margin\n self.margB = 1260 # 7/8-inch bottom margin\n self.fSize = 21 # 10.5-point default font size\n self.baskervilleFont = self.addFont(\"Baskerville Old Face\",\n \"roman\",\n \"Times New Roman\")\n self.__addLetterHead(binImage)\n if template:\n try:\n with open(template) as fp:\n body = fp.read()\n except Exception as e:\n raise Exception(\"loading %s: %s\" % (template, str(e)))\n if invitePara:\n replacement = \"@@MISCDOC:%s@@\" % invitePara\n body = body.replace(\"@@INVITATION@@\", replacement)\n pattern = re.compile(\"@@MISCDOC:(.*?)@@\")\n body = pattern.sub(lambda p: self.__loadMiscDoc(p), body)\n self.addRawContent(body)","def _parse_docstring(doc):\n _cache_key = doc\n try:\n return _parse_docstring_cache[_cache_key]\n except KeyError:\n pass\n\n if doc is None:\n return _Doc('', '', {})\n\n # Convert Google- or Numpy-style docstrings to RST.\n # (Should do nothing if not in either style.)\n doc = str(GoogleDocstring(doc))\n doc = str(NumpyDocstring(doc))\n\n tree = publish_doctree(doc)\n\n class Visitor(NodeVisitor):\n optional = [\n 'document', 'docinfo',\n 'field_list', 'field_body',\n 'literal', 'problematic']\n\n def __init__(self, document):\n NodeVisitor.__init__(self, document)\n self.paragraphs = []\n self.start_lines = []\n self.params = defaultdict(dict)\n self._current_paragraph = None\n self._indent_iterator_stack = []\n self._indent_stack = []\n\n def _do_nothing(self, node):\n pass\n\n def visit_paragraph(self, node):\n self.start_lines.append(node.line)\n self._current_paragraph = []\n\n def depart_paragraph(self, node):\n text = ''.join(self._current_paragraph)\n text = ''.join(self._indent_stack) + text\n self._indent_stack = [\n ' ' * len(item) for item in self._indent_stack]\n text = text.replace('\\n', '\\n' + ''.join(self._indent_stack))\n self.paragraphs.append(text)\n self._current_paragraph = None\n\n def visit_Text(self, node):\n self._current_paragraph.append(node)\n\n depart_Text = _do_nothing\n\n def visit_emphasis(self, node):\n self._current_paragraph.append('\\033[3m') # *foo*: italic\n\n def visit_strong(self, node):\n self._current_paragraph.append('\\033[1m') # **foo**: bold\n\n def visit_title_reference(self, node):\n self._current_paragraph.append('\\033[4m') # `foo`: underlined\n\n def _depart_markup(self, node):\n self._current_paragraph.append('\\033[0m')\n\n depart_emphasis = depart_strong = depart_title_reference = \\\n _depart_markup\n\n def visit_literal_block(self, node):\n text, = node\n self.start_lines.append(node.line)\n self.paragraphs.append(re.sub('^|\\n', r'\\g<0> ', text)) # indent\n raise SkipNode\n\n def visit_bullet_list(self, node):\n self._indent_iterator_stack.append(\n (node['bullet'] + ' ' for _ in range(len(node))))\n\n def depart_bullet_list(self, node):\n self._indent_iterator_stack.pop()\n\n def visit_enumerated_list(self, node):\n enumtype = node['enumtype']\n fmt = {('(', ')'): 'parens',\n ('', ')'): 'rparen',\n ('', '.'): 'period'}[node['prefix'], node['suffix']]\n try:\n start = node['start']\n except KeyError:\n start = 1\n else:\n start = {\n 'arabic': int,\n 'loweralpha': lambda s: ord(s) - ord('a') + 1,\n 'upperalpha': lambda s: ord(s) - ord('A') + 1,\n 'lowerroman': lambda s: roman.fromRoman(s.upper()),\n 'upperroman': lambda s: roman.fromRoman(s),\n }[enumtype](start)\n enumerators = [Body(None).make_enumerator(i, enumtype, fmt)[0]\n for i in range(start, start + len(node))]\n width = max(map(len, enumerators))\n enumerators = [enum.ljust(width) for enum in enumerators]\n self._indent_iterator_stack.append(iter(enumerators))\n\n def depart_enumerated_list(self, node):\n self._indent_iterator_stack.pop()\n\n def visit_list_item(self, node):\n self._indent_stack.append(next(self._indent_iterator_stack[-1]))\n\n def depart_list_item(self, node):\n self._indent_stack.pop()\n\n def visit_field(self, node):\n field_name_node, field_body_node = node\n field_name, = field_name_node\n parts = field_name.split()\n if len(parts) == 2:\n doctype, name = parts\n elif len(parts) == 3:\n doctype, type_, name = parts\n if doctype not in _PARAM_TYPES:\n raise SkipNode\n if 'type' in self.params[name]:\n raise ValueError('type defined twice for {}'.format(name))\n self.params[name]['type'] = type_\n else:\n raise SkipNode\n if doctype in _PARAM_TYPES:\n doctype = 'param'\n if doctype in _TYPE_NAMES:\n doctype = 'type'\n if doctype in self.params[name]:\n raise ValueError('{} defined twice for {}'.format(doctype, name))\n visitor = Visitor(self.document)\n field_body_node.walkabout(visitor)\n self.params[name][doctype] = ''.join(visitor.paragraphs)\n raise SkipNode\n\n def visit_comment(self, node):\n raise SkipNode\n\n def visit_system_message(self, node):\n raise SkipNode\n\n visitor = Visitor(tree)\n tree.walkabout(visitor)\n\n tuples = {name: _Param(values.get('param'), values.get('type'))\n for name, values in visitor.params.items()}\n if visitor.paragraphs:\n text = []\n for start, paragraph, next_start in zip(\n visitor.start_lines,\n visitor.paragraphs,\n visitor.start_lines[1:] + [0]):\n text.append(paragraph)\n # We insert a space before each newline to prevent argparse\n # from stripping consecutive newlines down to just two\n # (http://bugs.python.org/issue31330).\n text.append(' \\n' * (next_start - start - paragraph.count('\\n')))\n parsed = _Doc('', ''.join(text), tuples)\n else:\n parsed = _Doc('', '', tuples)\n _parse_docstring_cache[_cache_key] = parsed\n return parsed","def prepareDocument(self):\n self.checkSyntaxDocument()","def build_document(self):\n pass","async def create_doc(self, *args, **kwargs):\n pass","def docstring_hack():\n pass","def __init__(self, doc_string: ast3.Expr, doc_type: Type) -> None:\n self._doc = doc_string\n self.value = doc_string.value.s.strip() # type: ignore\n desc = Tags.DESC.regex.search(self.value)\n ret = Tags.RETURN.regex.search(self.value)\n cc = Tags.CC.regex.search(self.value) # pylint: disable=invalid-name\n author = Tags.AUTHOR.regex.search(self.value)\n todo = Tags.TODO.regex.search(self.value)\n\n self.no_lint = bool(Tags.NO_LINT.regex.search(self.value))\n self.no_doc = bool(Tags.NO_DOC.regex.search(self.value))\n self.todo = todo[1] if todo else \"\"\n\n self.desc = desc[1] if desc else \"\"\n self.args = {\n x: y\n for x, y in Tags.ARG.regex.findall(self.value)\n if x not in DEFAULT_ARG_IGNORE\n }\n self.links = Tags.LINK.regex.findall(self.value)\n self.ret = ret[1] if ret else \"\"\n self.author = author[1] if author else \"\"\n self.cc = int(cc[1] if cc else -1) # pylint: disable=invalid-name\n\n self.notes = Tags.NOTE.regex.findall(self.value)\n self.warnings = Tags.WARN.regex.findall(self.value)","def documentation():\n return auto.html()","def portrayalCatalogueCitation(self) -> Sequence[Citation]:\n pass","def doc(obj):\n return Documentation.fromObject(obj).first","def inherits_doc():\n pass","def get_citation(self):\n etree = self.get_eml()\n try:\n citation_ipt = etree.find('./additionalMetadata/metadata/gbif/citation').text\n except AttributeError:\n citation_ipt = None\n if citation_ipt:\n now = datetime.datetime.now().date()\n pola3r = \"(Available: Polar 'Omics Links to Antarctic, Arctic and Alpine Research. Antarctic Biodiversity Portal. Scientific Committee for Antarctic Research. www.biodiversity.aq/pola3r. Accessed: {})\".format(\n now)\n citation = \"{} {}\".format(citation_ipt, pola3r)\n else:\n citation = None\n return citation","def getBibTeX(bibref,tag_suf,outFile):\n if bibref == '1988iras....1.....B':\n bibtex = ['>@article{1988iras....1.....B,\\n',\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\n',\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\n',\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\n',\n ' year=1988,\\n',\n ' volume = {1},\\n', \n ' month = jan,\\n', \n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\n'\n '}\\n']\n else:\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\n suf = '/exportcitation'\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\n \n bibtex = []\n for l in range(0, len(lines)):\n if 'export-textarea ' in str(lines[l]):\n bibtex.append(str(lines[l]))\n t = l+1\n \n while '</textarea>' not in str(lines[t+1]):\n bibtex.append(str(lines[t])) \n t += 1\n \n for item in bibtex:\n if 'author' in item.split('=')[0]:\n auth = item.split('=')[1].split(',')[0]\n for i in string.punctuation:\n auth = auth.replace(i, '')\n auth = auth.replace(' ', '')\n if 'year' in item.split('=')[0]:\n yr = item.split('=')[1].split(',')[0]\n yr = yr.replace(' ', '')\n \n try:\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\n'\n except UnboundLocalError as ule:\n print(bibtex)\n print('')\n print(ule)\n sys.exit()\n \n with open(outFile, 'a') as o:\n for item in bibtex:\n item = item.replace('"', '\"')\n item = item.replace(''', \"'\")\n item = item.replace('&', \"&\")\n o.write(item)\n o.write('\\n')\n \n return auth+yr+tag_suf","def with_docs(self):\r\n self._configurations.append('javadoc')\r\n return self","def test_doc():\n pass","def doc_begin(fdoc):\n fdoc.write(\n '\\\\documentclass{{hyperiondoc}}\\n'\n '\\n'\n '\\\\usepackage{{adjustbox}}\\n'\n '\\\\usepackage{{{0}}}\\n'\n '\\\\newfontfamily{{\\\\symbola}}{{Symbola}}\\n'\n '\\\\USymbolAllStyle{{\\\\symbola}}\\n'\n '\\n'\n '\\\\newcommand{{\\\\symboldemo}}[3]{{%\\n'\n ' \\\\noindent\\\\begin{{minipage}}[c]{{.1\\\\textwidth}}\\n'\n ' \\\\centering\\\\textlarger[2]{{#3}}\\n'\n ' \\\\end{{minipage}}%\\n'\n ' \\\\begin{{minipage}}{{.8\\\\textwidth}}\\n'\n ' $\\\\mathtt{{0x#1}}$\\\\\\\\[-0.4em]\\n'\n ' \\\\adjustbox{{max width=.9\\\\textwidth}}{{\\\\code{{\\\\bs #2}}}}\\n'\n ' \\\\end{{minipage}}\\\\\\\\[0.6em]\\n'\n '}}\\n'\n '\\n'\n '\\\\begin{{document}}\\n'\n .format(package_name('all'))\n )","def __init__(self,txt=u'',unicodeEncoding='utf-8',verbose=False,tagID=0):\n # __document capture the document level structure\n # for each sentence and then put in the archives when the next sentence\n # is processed\n super(ConTextMarkup,self).__init__(__txt=None,__rawTxt=txt,\n __SCOPEUPDATED=False,__VERBOSE=verbose,\n __tagID=tagID,\n __unicodeEncoding=unicodeEncoding)\n self.__cleanText()","def pubmed_citation(args=sys.argv[1:], out=sys.stdout):\n\n parser = argparse.ArgumentParser(\n description='Get a citation using a PubMed ID or PubMed URL')\n parser.add_argument('query', help='PubMed ID or PubMed URL')\n parser.add_argument(\n '-m', '--mini', action='store_true', help='get mini citation')\n parser.add_argument(\n '-e', '--email', action='store', help='set user email', default='')\n\n args = parser.parse_args(args=args)\n\n lookup = PubMedLookup(args.query, args.email)\n publication = Publication(lookup, resolve_doi=False)\n\n if args.mini:\n out.write(publication.cite_mini() + '\\n')\n else:\n out.write(publication.cite() + '\\n')","def doc(self):\n doc = self.get('doc')\n if doc:\n from .config import defaults\n return defaults.types.doc(doc)","def docx():\n env.file_ext = \".docx\"\n local(\"pandoc {input_files} -o {output_file}{file_ext} --bibliography={bib_file} --csl={csl_file} --toc\".format(**env))","def start(self) -> None:\n\n self.doc = self.doc + r'''\n \\documentclass[\n 10pt, % Main document font size\n a4paper, % Paper type, use 'letterpaper' for US Letter paper\n ]{scrartcl}\n\n \\usepackage{graphicx}\n \\usepackage{epstopdf}\n \\usepackage{float}\n \\usepackage[scale=0.75]{geometry} % Reduce document margins\n \\usepackage{hyperref}\n \\usepackage{longtable}\n\n \\begin{document}\n\n \\title{Automatic Exploratory Data Analysis} % The article title\n\n \\subtitle{Study Case} % Uncomment to display a subtitle\n\n \\author{Jacob} % The article author(s) - author affiliations need to be specified in the AUTHOR AFFILIATIONS block\\\n\n \\maketitle % Print the title/author/date block\n\n \\newpage\n \\tableofcontents % Print the table of contents\n\n \\newpage\n \\listoffigures % Print the list of figures\n\n \\newpage\n \\listoftables % Print the list of tables\n '''","def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\n name=None, **kwargs):\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\n self.artDirection = artDirection\n self.path = path # Optional path to markdown file, if it has content.\n self.mdText = mdText # Optional markdown string.\n self.name = name or 'Untitled'\n self.startPage = startPage","def __init__(self, txt='', unicodeEncoding='utf-8'):\n # __document capture the document level structure\n # for each sentence and then put in the archives when the next sentence\n # is processed\n super(ConTextMarkup, self).__init__(__txt=None,\n __rawtxt=txt,\n __scope=None,\n __SCOPEUPDATED=False)\n self.__document = nx.DiGraph()\n self.__document.add_node(\"top\", category=\"document\")\n self.__VERBOSE = False\n self.__tagID = 0\n self.__unicodeEncoding = unicodeEncoding","def make_doc(file, \n title, \n author, \n geometry_options = {\"margin\": \"1.15cm\"}, \n options=\"\"):\n \n # geometry_options = {\"tmargin\": \"1.5cm\", \"lmargin\": \"2.5cm\"},\n\n doc = Document(\n default_filepath = file.as_posix(),\n documentclass = 'article',\n document_options = ['12pt', 'titlepage' ] + options,\n fontenc = \"T1\",\n inputenc = ENCODING,\n font_size = \"normalsize\",\n lmodern = True,\n page_numbers = False,\n indent = False,\n geometry_options = geometry_options\n )\n doc.change_document_style(\"empty\")\n date = str(datetime.datetime.date(datetime.datetime.now()))\n comment(doc.preamble, \"Automatically generated by make on \" + date)\n\n doc.preamble.append(Command(\"usepackage\",\"graphicx\"))\n doc.preamble.append(Command(\"usepackage\",\"enumitem\"))\n doc.preamble.append(Command(\"usepackage\",\"url\"))\n doc.preamble.append(NoEscape(\"\\\\setcounter{secnumdepth}{0}\"))\n doc.preamble.append(Command(\"usepackage\",\"titlesec\"))\n doc.preamble.append(NoEscape(\"\\\\titlespacing\\\\section{0pt}{12pt}{12pt}\"))\n doc.preamble.append(NoEscape(\"\\\\titlespacing\\\\subsection{0pt}{12pt}{12pt}\"))\n doc.preamble.append(Command(\"title\", title.title()))\n doc.preamble.append(Command(\"author\", author.title()))\n doc.preamble.append(Command(\"date\", NoEscape(r'\\today')))\n doc.append(NoEscape(r'\\maketitle'))\n return doc","def write_citation_page(refdict: dict) -> None:\n with open(WEBOUT_PATH + init_data().cite_url, \"w\", encoding=\"utf-8\") as outfile:\n common_html_header(outfile, \"Fiddler Crab Website Citation\")\n outfile.write(\" <header id=\\\"\" + init_data().cite_url + \"\\\">\\n\")\n outfile.write(\" <h1>Citation Info</h1>\\n\")\n outfile.write(\" </header>\\n\")\n outfile.write(\"\\n\")\n outfile.write(\" <p>\\n\")\n outfile.write(\" Generally it is best to cite the primary literature, whenever possible. However, the \"\n \"following paper describes much of the data that is unique to this website:\\n\")\n outfile.write(\" </p>\\n\")\n outfile.write(\" <div class=\\\"reference_list\\\">\\n\")\n outfile.write(\" <ul>\\n\")\n ref = refdict[\"Rosenberg2014\"] # citation describing the database\n outfile.write(\" <li><a href=\\\"references/Rosenberg2014.html\\\">\" + ref.formatted_html + \"</a></li>\\n\")\n outfile.write(\" </ul>\\n\")\n outfile.write(\" </div>\\n\")\n outfile.write(\" <ul class=\\\"fa-ul\\\">\\n\")\n outfile.write(\" <li>\" + fetch_fa_glyph(\"list pdf\") +\n \"<a href=\\\"https://dx.plos.org/10.1371/journal.pone.0101704\\\">Read paper online at \"\n \"PLoS ONE</a></li>\\n\")\n outfile.write(\" <li>\" + fetch_fa_glyph(\"list github\") +\n \"<a href=\\\"https://github.com/msrosenberg/fiddlercrab.info\\\">Website data repository on \"\n \"GitHub</a></li>\\n\")\n outfile.write(\" </ul>\\n\")\n common_html_footer(outfile)","def read(self, source_path):\r\n from cStringIO import StringIO\r\n with pelican_open(source_path) as source:\r\n text = StringIO(source)\r\n content = StringIO()\r\n ad = AsciiDocAPI()\r\n\r\n options = self.settings['ASCIIDOC_OPTIONS']\r\n if isinstance(options, (str, unicode)):\r\n options = [m.strip() for m in options.split(',')]\r\n options = self.default_options + options\r\n for o in options:\r\n ad.options(*o.split())\r\n\r\n ad.execute(text, content, backend=\"html4\")\r\n content = content.getvalue()\r\n\r\n metadata = {}\r\n for name, value in ad.asciidoc.document.attributes.items():\r\n name = name.lower()\r\n metadata[name] = self.process_metadata(name, value)\r\n if 'doctitle' in metadata:\r\n metadata['title'] = metadata['doctitle']\r\n return content, metadata","def get_doc(self, dtype, identity):\n if dtype == 'pii':\n doc = FullDoc(sd_pii = identity)\n elif dtype == 'doi':\n doc= FullDoc(doi = identity)\n\n if doc.read(ElsClient(self.API_list[0])):\n pass\n else:\n print (\"Read document failed.\")\n\n return doc","def bibtex(self):\n return \"@comment{%(id)s: %(message)s}\" % \\\n {'id': self.id, 'message': self.message}","def onDocumentation(self):\n path = self.settings.path + 'doc\\\\report.pdf'\n os.startfile(path)","def process_citation(style, reference_list, citation):\n processed_citation = Element(\"span\", attrib={\"class\":\"citation\"})\n\n for reference in reference_list:\n citeref = SubElement(processed_citation, \"span\")\n for style_node in style.citation.layout:\n process_node(citeref, style_node, style.macros, reference) \n\n return(processed_citation)","def doc(update: Update, context: CallbackContext):\n language_code = update.effective_user.language_code\n args = context.args\n if_admin = database.get_user_attr('admin', user_id=update.effective_user.id)\n if len(args) > 2:\n text = get_text('quantity_error_doc_text', language_code).text()\n else:\n if len(args) == 0:\n text = get_text('doc_text', language_code).text({'command': consts.ALL, 'admin': if_admin})\n else:\n if args[0] not in consts.DOC_COMMANDS:\n text = get_text('wrong_command_error_doc_text', language_code).text()\n else:\n text = get_text('doc_text', language_code).text({'command': args[0], 'admin': if_admin})\n if not if_admin and args[0] == 'admin':\n text += get_text('doc_unavailable_text', language_code).text()\n cf.send_message(\n context=context,\n chat_id=update.effective_chat.id,\n text=text,\n )","def getdoc():\n\n\timport webnotes\n\tfrom webnotes.utils import cint\n\t\n\tform = webnotes.form_dict\n\tdoctype, docname = form.get('doctype'), form.get('name')\n\tprefix = cint(form.get('from_archive')) and 'arc' or 'tab'\n\n\tif not (doctype and docname):\n\t\traise Exception, 'doctype and name required!'\n\t\n\tdoclist = []\n\t# single\n\tdoclist = load_single_doc(doctype, docname, (form.get('user') or webnotes.session['user']), prefix)\n\t\n\t# load doctype along with the doc\n\tif form.get('getdoctype'):\n\t\timport webnotes.model.doctype\n\t\tdoclist += webnotes.model.doctype.get(doctype)\n\n\t# tag as archived\n\tif prefix == 'arc':\n\t\tdoclist[0].__archived=1\n\n\twebnotes.response['docs'] = doclist","def get_doc(self) -> str:\n if self.soup is not None:\n root = self.soup.contents[0]\n body = self.get_paragraph(root.find(\"abstract\", recursive=False))\n body += self.get_paragraph(root.find(\"discussion\", recursive=False))\n return body\n\n return self.doc","def __init__(self, doi='', reference=''):\n\n self.doi = doi\n self.reference = reference","def newConferenceCitation(self, **attrlinks):\n return ConferenceCitation(self, **attrlinks)","def get_documentation(self, *args, **dargs):\n pass","def generate_readme_url(self, dn):\n\n df_curation = dn.curation_dict\n\n # Preferred citation\n single_str_citation = df_curation['item']['citation']\n\n # handle period in author list. Assume no period in dataset title\n str_list = list([single_str_citation.split('):')[0] + '). '])\n str_list += [str_row + '.' for str_row in single_str_citation.split('):')[1].split('. ')]\n\n citation_list = [content for content in str_list[0:-2]]\n citation_list.append(f\"{str_list[-2]} {str_list[-1]}\")\n citation_list = ' <br> '.join(citation_list)\n\n # summary\n figshare_description = df_curation['item']['description']\n\n query_str_dict = {'article_id': dn.name_dict['article_id'],\n 'curation_id': dn.name_dict['curation_id'],\n 'title': dn.name_dict['title'],\n 'depositor_name': dn.name_dict['simplify_fullName'],\n 'preferred_citation': citation_list,\n 'license': df_curation['item']['license']['name'],\n 'summary': figshare_description}\n # doi\n if not df_curation['item']['doi']: # empty case\n query_str_dict['doi'] = f\"https://doi.org/10.25422/azu.data.{dn.name_dict['article_id']}\"\n else:\n query_str_dict['doi'] = f\"https://doi.org/{df_curation['item']['doi']}\"\n\n # links\n if not df_curation['item']['references']: # not empty case\n links = \" <br> \".join(df_curation['item']['references'])\n query_str_dict['links'] = links\n\n # query_str_encode = str(query_str_dict).encode('base64', 'strict')\n q_eed = base64.urlsafe_b64encode(json.dumps(query_str_dict).encode()).decode()\n\n full_url = f\"{self.dict['generate_url']}{self.readme_survey_id}?\" + \\\n 'Q_EED=' + q_eed\n\n return full_url","def test_docstring(self):\n self.assertIsNotNone(City.__doc__)","def __init__(self):\n self._pronunciations = nltk.corpus.cmudict.dict()\n \"\"\"\n API Documentation for CMU dictionary corpus\n http://www.nltk.org/api/nltk.corpus.reader.html#module-nltk.corpus.reader.cmudict\n \"\"\"","def convert(text):\n return NewDocument.from_rst(text).format()","def process(self, doc, is_):\n implementation = Implementation(self)\n implementation.process(doc, is_)\n return implementation.html","def doDocStrings(parentNode, srcNode):\n def makeDocElement(name, content):\n node = libxml2.newNode(name)\n node.addChild(libxml2.newText(content))\n return node\n \n autodoc = getAttr(srcNode, \"python_autodoc\")\n docstr = getAttr(srcNode, \"feature_docstring\")\n if autodoc:\n parentNode.addChild(makeDocElement(\"autodoc\", autodoc))\n if docstr:\n parentNode.addChild(makeDocElement(\"docstring\", docstr))","def add_doc(writer, entry):\n m = 0\n q_id = entry['Id']\n snippets = get_possible_snippets(q_id, False)\n for code, lang, ans_id in snippets:\n writer.add_document(question_id=q_id, answer_id=ans_id, code=return_unicode(code), language=return_unicode(lang))\n m += 1\n return m","def document(cls):\n header = cls.document_header()\n content = cls.document_content()\n index = cls.document_index()\n package = cls.package().name\n filename = inspect.getsourcefile(cls)\n try:\n lines = inspect.getsourcelines(cls)\n except IOError:\n lines = ([], 0)\n line = lines[1]+1\n return DocEntry(\n header, content, index=index,\n package=package, filename=filename, line=line)"],"string":"[\n \"def make_citation(meta):\\n pass\",\n \"def init_doc(self):\\n raise NotImplementedError()\",\n \"def main(rc):\\n with store_client(rc) as sclient:\\n for doc in rc.documents:\\n sclient.copydoc(doc)\",\n \"def make_bibtex(self):\\n\\n\\t\\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, \",\n \"def create_citation(cit):\\n if cit is not None:\\n if cit['citation-type'] == \\\"BIBTEX\\\":\\n return pybtex.database.parse_string(cit['citation-value'], \\\"bibtex\\\")\\n return None\",\n \"def __call__(self, doc):\\n return doc\",\n \"def fini_doc(self):\\n raise NotImplementedError()\",\n \"def dummy(doc):\\r\\n return doc\",\n \"def to_citation(self, type):\\n acs_authors = \\\"; \\\".join(self.format_authors(\\\"acs\\\"))\\n # Some articles don't come with pages. :-(\\n pages_with_endash = (self.pages.replace(\\\"-\\\", \\\"\\\\u2013\\\") if self.pages\\n else \\\"\\\")\\n # Actually, not using quote() generally gives results that work fine.\\n # The only issue is that when using Markdown URLs with parentheses in\\n # Jupyter notebooks, the conversion to HTML gets it wrong, thinking\\n # that the URL ends at the first close parentheses in the URL. (In\\n # the notebook itself, it is fine, only the conversion to HTML messes\\n # up.) So we might as well escape them generally.\\n doi_url = f\\\"https://doi.org/{urllib.parse.quote(self.doi)}\\\"\\n\\n # BibLaTeX\\n if type in [\\\"bib\\\", \\\"b\\\"]:\\n # Create (hopefully) unique identifier\\n author_decoded = unidecode(self.authors[0][\\\"family\\\"])\\n journal_initials = \\\"\\\".join(c for c in self.journal_short\\n if c.isupper())\\n ref_identifier = f\\\"{author_decoded}{self.year}{journal_initials}\\\"\\n ref_identifier = \\\"\\\".join(ref_identifier.split()) # remove spaces\\n # Author names in bib style\\n author_names = \\\" and \\\".join(self.format_authors(\\\"bib\\\"))\\n journal = self.journal_short.replace(\\\". \\\", \\\".\\\\\\\\ \\\")\\n # Open and close braces\\n # Truthfully we don't need this. However, including the doubled\\n # curly braces in the f-string makes vim's indentation go crazy.\\n open, close = \\\"{\\\", \\\"}\\\"\\n # Make the citation\\n s = (f\\\"@article{open}{ref_identifier},\\\\n\\\"\\n f\\\" doi = {{{self.doi}}},\\\\n\\\"\\n f\\\" author = {{{author_names}}},\\\\n\\\"\\n f\\\" journal = {{{journal}}},\\\\n\\\"\\n f\\\" title = {{{self.title}}},\\\\n\\\"\\n f\\\" year = {{{self.year}}},\\\\n\\\")\\n if self.volume is not None:\\n s += f\\\" volume = {{{self.volume}}},\\\\n\\\"\\n if self.issue is not None:\\n s += f\\\" issue = {{{self.issue}}},\\\\n\\\"\\n if self.pages is not None:\\n s += f\\\" pages = {{{self.pages.replace('-', '--')}}},\\\\n\\\"\\n s += close\\n # Replace Unicode characters with their LaTeX equivalents\\n for char in _g.unicodeLatexDict:\\n s = s.replace(char, _g.unicodeLatexDict[char])\\n return s\\n\\n # Just DOI\\n if type in [\\\"doi\\\", \\\"d\\\"]:\\n return self.doi\\n\\n # The rest all have a long vs short type.\\n # Discern long vs short type\\n long = False\\n if type[0].upper() == type[0]:\\n long = True\\n type = type.lower()\\n\\n # reStructuredText\\n if type in [\\\"rst\\\", \\\"r\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"*{self.volume}* ({self.issue}), \\\" if self.issue\\n else f\\\"*{self.volume},* \\\")\\n return (author_title\\n + f\\\"*{self.journal_short}* **{self.year},** \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}. \\\"\\n + f\\\"`DOI: {self.doi} <{doi_url}>`_\\\")\\n\\n # Markdown\\n if type in [\\\"markdown\\\", \\\"m\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"*{self.volume}* ({self.issue}), \\\" if self.issue\\n else f\\\"*{self.volume},* \\\")\\n return (author_title\\n + f\\\"*{self.journal_short}* **{self.year},** \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}. \\\"\\n + f\\\"[DOI: {self.doi}]({doi_url})\\\")\\n\\n # Word\\n elif type in [\\\"word\\\", \\\"w\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"{self.volume} ({self.issue}), \\\" if self.issue\\n else f\\\"{self.volume}, \\\")\\n return (author_title\\n + f\\\"{self.journal_short} {self.year}, \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}.\\\")\\n\\n else:\\n raise ValueError(\\\"Invalid citation type '{type}' given\\\")\",\n \"def cppdoc(self, irc, msg, args, num, req):\\n self.googleq('www.cplusplus.com/reference/', req, num, irc)\",\n \"def documento():\\r\\n\\tpass\",\n \"def cite(silent=False):\\n if silent is False:\\n print(__cite__)\\n else:\\n return __bibtex__\",\n \"def getCitations (self, doc, verbose = False):\\r\\n if verbose is True:\\r\\n print \\\"getting citations for document \\\" +str(doc) \\r\\n return self.citations[int(doc)]\",\n \"def lispdoc(self, irc, msg, args, num, req):\\n self.googleq('http://lispdoc.com/', req, num, irc)\",\n \"def Init(self, *args):\\n return _XCAFDoc.XCAFDoc_DocumentTool_Init(self, *args)\",\n \"def __call__(self, doc: Doc) -> Doc:\\n return doc\",\n \"def __call__(self, doc: Doc) -> Doc:\\n return doc\",\n \"def pythondoc(self, irc, msg, args, num, req):\\n self.googleq('http://docs.python.org/library/', req, num, irc)\",\n \"def add_ref(doc_name, bib_name, keep_label=False, slides=False):\\n bib_path = bib_name # os.path.join(static_path, \\\"tex\\\", bib_name)\\n if not slides:\\n keep_label = True\\n with open(doc_name, \\\"r\\\") as f:\\n _file = f.read()\\n # find citations\\n match = re.findall(r\\\"\\\\[@.*?\\\\]\\\", _file)\\n references = []\\n # print(match)\\n for cit in match:\\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\\\".html\\\", delete=True)\\n tmp = tempfile.NamedTemporaryFile(suffix=\\\".md\\\", delete=True)\\n with open(tmp.name, \\\"w\\\") as md_file:\\n # Open the file for writing.\\n md_file.write(cit)\\n\\n pandoc_command = [\\n \\\"pandoc\\\",\\n \\\"-C\\\",\\n tmp.name,\\n \\\"--bibliography\\\",\\n bib_path,\\n \\\"--csl\\\",\\n \\\"./templates/my-csl.csl\\\",\\n \\\"-o\\\",\\n tmp_cite_html.name,\\n ]\\n if not slides:\\n for tag in [\\\"--metadata\\\", \\\"link-citations=true\\\"]:\\n pandoc_command.append(tag)\\n output = subprocess.check_output(\\n pandoc_command, stderr=subprocess.STDOUT\\n ).decode(\\\"utf-8\\\")\\n print(output.rstrip())\\n tmp.close()\\n with open(tmp_cite_html.name, \\\"r\\\") as cite_html:\\n # Open the file for writing.\\n cit_new = cite_html.read()\\n # print(cit_new)\\n if not keep_label:\\n # remove first line\\n cit_new = \\\"\\\\n\\\".join(cit_new.splitlines()[1:])\\n else:\\n lines = cit_new.splitlines()\\n # remove the <p> tags\\n lines[0] = lines[0][3:-4]\\n cit_new = \\\"\\\\n\\\".join(lines)\\n if slides:\\n _file = _file.replace(cit, cit_new)\\n else:\\n _file = _file.replace(cit, lines[0])\\n # collect the references\\n references.append(\\\"<p>\\\")\\n references.append(\\\"\\\\n\\\".join(lines))\\n references.append(\\\"</p>\\\")\\n # paste_refs_end()\\n tmp_cite_html.close()\\n if slides:\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n if not slides:\\n if references == []:\\n _file=clean_html_refs(_file)\\n else:\\n _file = _file.replace(\\\"<bibliography-placeholder>\\\", \\\"\\\\n\\\".join(references))\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n return\",\n \"def javadoc(self, irc, msg, args, num, req):\\n self.googleq('download.oracle.com/javase/6/docs/', req, num, irc)\",\n \"def get_bibtex(self):\\n url=\\\"http://www.biomedcentral.com/download/citation\\\"\\n parameters={'citation':'on', \\n 'result-selection':'THIS_PAGE',\\n 'suplements': 'false',\\n 'citationType':'BIBTEX_WITH_ABSTRACT',\\n 'articleIdThisPage':self.article_ids\\n }\\n data=urllib.urlencode(parameters)\\n self.bibtex=urllib2.urlopen(url,data)\",\n \"def internal_citations(text, initial_label=None,\\n require_marker=False, title=None):\\n if not initial_label:\\n initial_label = Label()\\n citations = []\\n\\n def multiple_citations(matches, comment):\\n \\\"\\\"\\\"i.e. head :: tail\\\"\\\"\\\"\\n for match, start, end in matches:\\n label = initial_label\\n for submatch in chain([match.head], match.tail):\\n cit = ParagraphCitation(\\n submatch.pos[0], submatch.pos[1],\\n match_to_label(submatch.tokens, label, comment=comment),\\n full_start=start,\\n full_end=end,\\n in_clause=True)\\n label = cit.label # update the label to keep context\\n citations.append(cit)\\n\\n def single_citations(matches, comment):\\n for match, start, end in matches:\\n full_start = start\\n if match.marker is not '':\\n # Remove the marker from the beginning of the string\\n start = match.marker.pos[1]\\n citations.append(ParagraphCitation(\\n start, end, match_to_label(match, initial_label,\\n comment=comment),\\n full_start=full_start))\\n\\n single_citations(grammar.marker_comment.scanString(text), True)\\n\\n multiple_citations(grammar.multiple_non_comments.scanString(text), False)\\n multiple_citations(grammar.multiple_appendix_section.scanString(text),\\n False)\\n multiple_citations(grammar.multiple_comments.scanString(text), True)\\n multiple_citations(grammar.multiple_appendices.scanString(text), False)\\n multiple_citations(grammar.multiple_period_sections.scanString(text),\\n False)\\n\\n single_citations(grammar.marker_appendix.scanString(text), False)\\n single_citations(grammar.appendix_with_section.scanString(text), False)\\n single_citations(grammar.marker_paragraph.scanString(text), False)\\n single_citations(grammar.mps_paragraph.scanString(text), False)\\n single_citations(grammar.m_section_paragraph.scanString(text), False)\\n if not require_marker:\\n single_citations(grammar.section_paragraph.scanString(text), False)\\n single_citations(grammar.part_section_paragraph.scanString(text),\\n False)\\n multiple_citations(\\n grammar.multiple_section_paragraphs.scanString(text), False)\\n\\n # Some appendix citations are... complex\\n for match, start, end in grammar.appendix_with_part.scanString(text):\\n full_start = start\\n if match.marker is not '':\\n start = match.marker.pos[1]\\n label = filter(lambda l: l != '.', list(match)[3:])\\n label = dict(zip(['p1', 'p2', 'p3'], label))\\n citations.append(ParagraphCitation(\\n start, end, initial_label.copy(\\n appendix=match.appendix, appendix_section=match.a1,\\n **label), full_start=full_start))\\n\\n # Internal citations can sometimes be in the form XX CFR YY.ZZ\\n for match, start, end in grammar.internal_cfr_p.scanString(text):\\n # Check if this is a reference to the CFR title and part we are parsing\\n if match.cfr_title == title and match[1] == initial_label.to_list()[0]:\\n full_start = start\\n if match.marker is not '':\\n # Remove the marker from the beginning of the string\\n start = match.marker.pos[1]\\n citations.append(ParagraphCitation(\\n start, end, match_to_label(match, initial_label),\\n full_start=full_start))\\n else:\\n continue\\n\\n # And sometimes there are several of them\\n for match, start, end in grammar.multiple_cfr_p.scanString(text):\\n label = initial_label\\n if match.head.cfr_title == title:\\n for submatch in chain([match.head], match.tail):\\n if submatch.part == initial_label.to_list()[0]:\\n cit = ParagraphCitation(\\n submatch.pos[0], submatch.pos[1],\\n match_to_label(submatch.tokens, label),\\n full_start=start,\\n full_end=end,\\n in_clause=True)\\n label = cit.label # update the label to keep context\\n citations.append(cit)\\n else:\\n continue\\n\\n # Remove any sub-citations\\n final_citations = []\\n for cit in citations:\\n if not any(cit in other for other in citations):\\n final_citations.append(cit)\\n\\n return final_citations\",\n \"def DocString():\\n return\",\n \"def main_docstring():\",\n \"def test_doc_with_comments():\\n doc = CoNLL.conll2doc(input_str=RUSSIAN_SAMPLE)\\n check_russian_doc(doc)\",\n \"def _populate(self):\\n\\n # Assume the first word is what we want, and we can find well formed years\\n # This sucks, but will work for these ones.\\n # Roll on bibtex for citations in the CIM.\\n\\n citation_detail = self.doc.citation_detail\\n author = citation_detail.split(',')[0]\\n match = '([^\\\\w])19|20\\\\d\\\\d([^\\\\w])*?'\\n m = re.search(match, citation_detail)\\n if m:\\n year = m.group(0)\\n else:\\n year = None\\n\\n # one error in existing es-doc content to be fixed:\\n if 'van Vuuren DP' in author:\\n author = 'van Vuuren'\\n print 'applying vv fix'\\n\\n self.year = int(year)\\n\\n # We assume that this table will have entries which ne\\n\\n # I use the first three letters of a an authors name, and for\\n # three or more authors, EA, and then the year for my bibtex citation string\\n self.citeguess = author[0:3] + 'EA' + year[2:]\\n # This is what will appear in the table:\\n self.citestring = '%s et al. (%s)' % (author, year)\\n # Keep this for a reference list for checking against the eventual bibtex reference list.\\n self.text = citation_detail\",\n \"def docs():\",\n \"def test_citations_and_toc_with_valid_defaults(self):\\n\\n pandoc_default_files = [\\n os.path.join(\\n TEST_DEFAULT_FILES_PATH,\\n \\\"valid_defaults_with_toc_and_citations.yaml\\\",\\n )\\n ]\\n\\n settings = get_settings(\\n PANDOC_DEFAULT_FILES=pandoc_default_files,\\n FORMATTED_FIELDS=FORMATTED_FIELDS,\\n )\\n pandoc_reader = PandocReader(settings)\\n\\n source_path = os.path.join(\\n TEST_CONTENT_PATH, \\\"valid_content_with_citation.md\\\"\\n )\\n output, metadata = pandoc_reader.read(source_path)\\n self.maxDiff = None # pylint: disable=invalid-name\\n\\n self.assertEqual(\\n (\\n '<h2 id=\\\"string-theory\\\">String Theory</h2>\\\\n'\\n \\\"<p>But this foundational principle of science has\\\"\\n \\\" now been called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/'\\n 'string-theory\\\">String Theory</a>,'\\n \\\" which is a relative newcomer to theoretical physics, but one\\\"\\n \\\" that has captured the common imagination, judging by\\\"\\n \\\" the popular explanations that abound on the Web\\\"\\n ' <span class=\\\"citation\\\" data-cites=\\\"mann2019 wood2019'\\n ' jones2020\\\">[1]–[3]</span>.'\\n \\\" And whether string theory is or is not science, Popper\\\"\\n \\\" notwithstanding, is an issue that is still up for debate\\\"\\n \\\" <span\\\"\\n ' class=\\\"citation\\\" data-cites=\\\"siegel2015 castelvecchi2016'\\n ' alves2017 francis2019\\\">[4]–[7]</span>.</p>\\\\n'\\n '<h1 class=\\\"unnumbered\\\" id=\\\"bibliography\\\">References</h1>\\\\n'\\n '<div id=\\\"refs\\\" class=\\\"references csl-bib-body\\\"'\\n ' role=\\\"doc-bibliography\\\">\\\\n'\\n '<div id=\\\"ref-mann2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[1]'\\n ' </div><div class=\\\"csl-right-inline\\\">A. Mann,'\\n \\\" <span>“<span>What Is String Theory?</span>”</span>\\\"\\n \\\" 20-Mar-2019. [Online].\\\"\\n ' Available: <a href=\\\"https://www.livescience.com/'\\n '65033-what-is-string-theory.html\\\">'\\n \\\"https://www.livescience.com/\\\"\\n \\\"65033-what-is-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-wood2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[2] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n \\\"C. Wood, <span>“<span>What Is String Theory?</span>.\\\"\\n \\\" Reference article:\\\"\\n \\\" A simplified explanation and brief history of string\\\"\\n \\\" theory,”</span> 11-Jul-2019.\\\"\\n ' [Online]. Available: <a href=\\\"https://www.space.com/'\\n '17594-string-theory.html\\\">'\\n \\\"https://www.space.com/17594-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-jones2020\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[3]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'A. Z. Jones, <span>“<span class=\\\"nocase\\\">The Basics of String'\\n \\\" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.thoughtco.com/'\\n 'what-is-string-theory-2699363\\\">'\\n \\\"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-siegel2015\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[4]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n \\\"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\\\"\\n \\\" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\\\"\\n \\\" <a\\\"\\n ' href=\\\"https://www.forbes.com/sites/'\\n \\\"startswithabang/2015/12/23/\\\"\\n 'why-string-theory-is-not-science/\\\">https://www.forbes.com/'\\n \\\"sites/startswithabang/2015/12/23/\\\"\\n \\\"why-string-theory-is-not-science/</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-castelvecchi2016\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[5]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'D. Castelvecchi, <span>“<span class=\\\"nocase\\\">'\\n \\\"Feuding physicists turn\\\"\\n \\\" to philosophy for help</span>. String theory is at the\\\"\\n \\\" heart of a debate over the integrity of the scientific\\\"\\n \\\" method itself,”</span> 05-Jan-2016. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.nature.com/news/'\\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\\\">'\\n \\\"https://www.nature.com/news/\\\"\\n \\\"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-alves2017\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[6] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n 'R. A. Batista and J. Primack, <span>“<span class=\\\"nocase\\\">'\\n \\\"Is String theory falsifiable?</span>. Can a theory that isn’t\\\"\\n \\\" completely testable still be useful to physics?”</span>\\\"\\n \\\" [Online].\\\"\\n ' Available: <a href=\\\"https://metafact.io/factchecks/'\\n '30-is-string-theory-falsifiable\\\">'\\n \\\"https://metafact.io/factchecks/\\\"\\n \\\"30-is-string-theory-falsifiable</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-francis2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[7]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'M. R. Francis, <span>“<span class=\\\"nocase\\\">Falsifiability and'\\n \\\" physics</span>. Can a theory that isn’t completely testable\\\"\\n \\\" still be useful to physics?”</span> 23-Apr-2019.\\\"\\n \\\" [Online]. Available:\\\"\\n ' <a href=\\\"https://www.scientificamerican.com/'\\n 'article/is-string-theory-science/\\\">'\\n \\\"https://www.scientificamerican.com/article/is-\\\"\\n \\\"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n ),\\n output,\\n )\\n\\n self.assertEqual(\\\"Valid Content With Citation\\\", str(metadata[\\\"title\\\"]))\\n self.assertEqual(\\\"My Author\\\", str(metadata[\\\"author\\\"]))\\n self.assertEqual(\\\"2020-10-16 00:00:00\\\", str(metadata[\\\"date\\\"]))\\n self.assertEqual(\\n (\\n '<nav class=\\\"toc\\\" role=\\\"doc-toc\\\">\\\\n'\\n \\\"<ul>\\\\n\\\"\\n '<li><a href=\\\"#string-theory\\\">String Theory</a></li>\\\\n'\\n '<li><a href=\\\"#bibliography\\\">References</a></li>\\\\n'\\n \\\"</ul>\\\\n</nav>\\\\n\\\"\\n ),\\n str(metadata[\\\"toc\\\"]),\\n )\",\n \"def test_citations_and_toc(self):\\n settings = get_settings(\\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\\\"+citations\\\"],\\n PANDOC_ARGS=PANDOC_ARGS\\n + [\\n \\\"--toc\\\",\\n \\\"-C\\\",\\n \\\"--csl=https://www.zotero.org/styles/ieee-with-url\\\",\\n \\\"--metadata=link-citations:false\\\",\\n \\\"--metadata=reference-section-title:References\\\",\\n ],\\n FORMATTED_FIELDS=FORMATTED_FIELDS,\\n )\\n\\n pandoc_reader = PandocReader(settings)\\n source_path = os.path.join(\\n TEST_CONTENT_PATH, \\\"valid_content_with_citation.md\\\"\\n )\\n output, metadata = pandoc_reader.read(source_path)\\n self.maxDiff = None\\n\\n self.assertEqual(\\n (\\n '<h2 id=\\\"string-theory\\\">String Theory</h2>\\\\n'\\n \\\"<p>But this foundational principle of science has\\\"\\n \\\" now been called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/'\\n 'string-theory\\\">String Theory</a>,'\\n \\\" which is a relative newcomer to theoretical physics, but one\\\"\\n \\\" that has captured the common imagination, judging by\\\"\\n \\\" the popular explanations that abound on the Web\\\"\\n ' <span class=\\\"citation\\\" data-cites=\\\"mann2019 wood2019'\\n ' jones2020\\\">[1]–[3]</span>.'\\n \\\" And whether string theory is or is not science, Popper\\\"\\n \\\" notwithstanding, is an issue that is still up for debate\\\"\\n \\\" <span\\\"\\n ' class=\\\"citation\\\" data-cites=\\\"siegel2015 castelvecchi2016'\\n ' alves2017 francis2019\\\">[4]–[7]</span>.</p>\\\\n'\\n '<h1 class=\\\"unnumbered\\\" id=\\\"bibliography\\\">References</h1>\\\\n'\\n '<div id=\\\"refs\\\" class=\\\"references csl-bib-body\\\"'\\n ' role=\\\"doc-bibliography\\\">\\\\n'\\n '<div id=\\\"ref-mann2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[1]'\\n ' </div><div class=\\\"csl-right-inline\\\">A. Mann,'\\n \\\" <span>“<span>What Is String Theory?</span>”</span>\\\"\\n \\\" 20-Mar-2019. [Online].\\\"\\n ' Available: <a href=\\\"https://www.livescience.com/'\\n '65033-what-is-string-theory.html\\\">'\\n \\\"https://www.livescience.com/\\\"\\n \\\"65033-what-is-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-wood2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[2] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n \\\"C. Wood, <span>“<span>What Is String Theory?</span>.\\\"\\n \\\" Reference article:\\\"\\n \\\" A simplified explanation and brief history of string\\\"\\n \\\" theory,”</span> 11-Jul-2019.\\\"\\n ' [Online]. Available: <a href=\\\"https://www.space.com/'\\n '17594-string-theory.html\\\">'\\n \\\"https://www.space.com/17594-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-jones2020\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[3]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'A. Z. Jones, <span>“<span class=\\\"nocase\\\">The Basics of String'\\n \\\" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.thoughtco.com/'\\n 'what-is-string-theory-2699363\\\">'\\n \\\"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-siegel2015\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[4]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n \\\"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\\\"\\n \\\" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\\\"\\n \\\" <a\\\"\\n ' href=\\\"https://www.forbes.com/sites/'\\n \\\"startswithabang/2015/12/23/\\\"\\n 'why-string-theory-is-not-science/\\\">https://www.forbes.com/'\\n \\\"sites/startswithabang/2015/12/23/\\\"\\n \\\"why-string-theory-is-not-science/</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-castelvecchi2016\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[5]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'D. Castelvecchi, <span>“<span class=\\\"nocase\\\">'\\n \\\"Feuding physicists turn\\\"\\n \\\" to philosophy for help</span>. String theory is at the\\\"\\n \\\" heart of a debate over the integrity of the scientific\\\"\\n \\\" method itself,”</span> 05-Jan-2016. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.nature.com/news/'\\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\\\">'\\n \\\"https://www.nature.com/news/\\\"\\n \\\"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-alves2017\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[6] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n 'R. A. Batista and J. Primack, <span>“<span class=\\\"nocase\\\">'\\n \\\"Is String theory falsifiable?</span>. Can a theory that isn’t\\\"\\n \\\" completely testable still be useful to physics?”</span>\\\"\\n \\\" [Online].\\\"\\n ' Available: <a href=\\\"https://metafact.io/factchecks/'\\n '30-is-string-theory-falsifiable\\\">'\\n \\\"https://metafact.io/factchecks/\\\"\\n \\\"30-is-string-theory-falsifiable</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-francis2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[7]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'M. R. Francis, <span>“<span class=\\\"nocase\\\">Falsifiability and'\\n \\\" physics</span>. Can a theory that isn’t completely testable\\\"\\n \\\" still be useful to physics?”</span> 23-Apr-2019.\\\"\\n \\\" [Online]. Available:\\\"\\n ' <a href=\\\"https://www.scientificamerican.com/'\\n 'article/is-string-theory-science/\\\">'\\n \\\"https://www.scientificamerican.com/article/is-\\\"\\n \\\"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n ),\\n output,\\n )\\n\\n self.assertEqual(\\\"Valid Content With Citation\\\", str(metadata[\\\"title\\\"]))\\n self.assertEqual(\\\"My Author\\\", str(metadata[\\\"author\\\"]))\\n self.assertEqual(\\\"2020-10-16 00:00:00\\\", str(metadata[\\\"date\\\"]))\\n self.assertEqual(\\n (\\n '<nav class=\\\"toc\\\" role=\\\"doc-toc\\\">\\\\n'\\n \\\"<ul>\\\\n\\\"\\n '<li><a href=\\\"#string-theory\\\">String Theory</a></li>\\\\n'\\n '<li><a href=\\\"#bibliography\\\">References</a></li>\\\\n'\\n \\\"</ul>\\\\n</nav>\\\\n\\\"\\n ),\\n str(metadata[\\\"toc\\\"]),\\n )\\n self.assertEqual(\\n (\\n \\\"<p>But this foundational principle of science has now been\\\"\\n \\\" called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/string-theory\\\">'\\n \\\"String Theory</a>.</p>\\\\n\\\"\\n ),\\n str(metadata[\\\"summary\\\"]),\\n )\",\n \"def __call__(self, filename, manuscript=\\\"\\\", journal=\\\"\\\", author=[], \\n publisher=\\\"\\\"):\\n\\n # check the parameters\\n while len(author) < 4:\\n author.append(\\\"\\\")\\n\\n doc = getDocument(filename)\\n\\n Story = []\\n\\n # Section 1\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"<seqreset id=\\\"main\\\" /><seq id=\\\"main\\\">. THIS Amendment hereby \\n modifies and supplements the attached Publication Agreement \\n concerning the following Article:\\\"\\\"\\\", styles['outer_style'])\\n )\\n\\n journal_info_table = Table([\\n [fillInRow(manuscript, \\\"(manuscript title)\\\", width=inch*5)],\\n [fillInRow(journal, \\\"(journal name)\\\", width=inch*5)],\\n ],\\n )\\n journal_info_table.hAlign = 'LEFT'\\n Story.append(journal_info_table)\\n\\n # Section 2\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"<seq id=\\\"main\\\">. The parties to the Publication Agreement and\\n to this Amendment are:\\\"\\\"\\\", styles['outer_style'])\\n )\\n\\n journal_info_table = Table([\\n [fillInRow(author[0], \\\"(corresponding author)\\\", width=inch*5)],\\n [Paragraph(\\\"and\\\", styles['outer_style'])],\\n [fillInRow(journal, \\\"(the Publisher)\\\", width=inch*5)],\\n ],\\n )\\n journal_info_table.hAlign = 'LEFT'\\n Story.append(journal_info_table)\\n\\n # Section 3\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"<seq id=\\\"main\\\">. The parties agree that wherever there is any\\n conflict between the Amendment and the Publication Agreement, \\n the provisions of this Amendment are paramount and the \\n Publication Agreement shall be construed accordingly.\\\"\\\"\\\",\\n styles['outer_style'])\\n )\\n\\n # Section 4\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"<seq id=\\\"main\\\">. Notwithstanding any terms in the Publication\\nAgreement to the contrary and in addition to the rights retained by Author \\nor licensed by Published to Author in the Publication Agreement and any fair \\nuse rights of Author, Author and Publisher agree that the Author shall also \\nretain the following rights:\\\"\\\"\\\",\\n styles['outer_style'])\\n )\\n\\n # 4a\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"a. The Author shall, without limitation, have the non-exclusive right to use, reproduce, distribute, create derivative works including update, perform, and display publicly, the Article in electronic, digital or print form in connection with the Author's teaching, conference presentations, lectures, other scholarly works, and for all of Author's academic and professional activities. \\\"\\\"\\\",\\n styles['inner_style'])\\n )\\n\\n # 4b\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"b. Once the Article has been published by Publisher, the Author shall also have all the non-exclusive rights necessary to make, or to authorize others to make, the final published version of the Article available in digital form over the Internet, including but not limited to a website under the control of the Author or the Author's employer or through any digital repository, such as MIT's DSpace or the National Library of Medicine's PubMed Central database.\\\"\\\"\\\",\\n styles['inner_style'])\\n )\\n\\n #4c\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"c. The Author further retains all non-exclusive rights necessary to grant to the Author's employing institution the non-exclusive right to use, reproduce, distribute, display, publicly perform, and make copies of the work in electronic, digital or in print form in connection with teaching, digital repositories, conference presentations, lectures, other scholarly works, and all academic and professional activities conducted at the Author's employing institution. \\\"\\\"\\\",\\n styles['inner_style'])\\n )\\n\\n # Section 5\\n Story.append(\\n Paragraph(\\n \\\"\\\"\\\"<seq id=\\\"main\\\" />. <b>Final Agreement.</b> This Amendment and the Publication Agreement, taken together, constitute the final agreement between the Author and the Publisher with respect to the publication of the Article and allocation of rights under copyright in the Article. Any modification of or additions to the terms of this Amendment or to the Publication Agreement must be in writing and executed by both Publisher and Author in order to be effective.\\\"\\\"\\\",\\n styles['outer_style'])\\n )\\n\\n # Signature\\n journal_info_table = Table([\\n [\\\"AUTHOR\\\", \\\" \\\", \\\"PUBLISHER\\\"],\\n [fillInRow(\\\"\\\", \\\"(corresponding author on behalf of all authors)\\\"),\\n \\\"\\\", fillInRow(\\\"\\\", \\\"\\\")],\\n [fillInRow(\\\"\\\", \\\"Date\\\"),\\n \\\"\\\",\\n fillInRow(\\\"\\\", \\\"Date\\\")]\\n ],\\n colWidths=[inch*3, inch*.25, inch*3],\\n )\\n\\n journal_info_table.hAlign = 'LEFT'\\n Story.append(journal_info_table)\\n\\n # MIT Directive\\n Story.append(\\n Paragraph(\\\"<b>MIT Authors:</b>\\\", styles['outer_style'])\\n )\\n Story.append(\\n Paragraph(\\\"Please fax a copy of the agreement to 617-253-8894. Direct any questions to amend-cip@mit.edu\\\",\\n styles['inner_style'])\\n )\\n\\n\\n agreement = \\\"%s %s\\\" % (self.NAME, self.VERSION)\\n doc.build(Story, \\n onFirstPage=mit_pageInfo, onLaterPages=mit_pageInfo)\",\n \"def _initNewEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\\r\\n pass\",\n \"def fill(self):\\n if self.source == 'citations':\\n url = self._scholarly.URLS(\\\"CITATIONPUB\\\").format(self.id_citations)\\n soup = self._scholarly._get_soup(\\n self._scholarly.URLS('HOST').format(url))\\n self.bib['title'] = soup.find('div', id='gsc_vcd_title').text\\n\\n if soup.find('a', class_='gsc_vcd_title_link'):\\n self.bib['url'] = soup.find(\\n 'a', class_='gsc_vcd_title_link')['href']\\n\\n for item in soup.find_all('div', class_='gs_scl'):\\n key = item.find(class_='gsc_vcd_field').text\\n val = item.find(class_='gsc_vcd_value')\\n if key == 'Authors':\\n self.bib['author'] = ' and '.join(self.get_authorlist(val))\\n elif key == 'Journal':\\n self.bib['journal'] = val.text\\n elif key == 'Volume':\\n self.bib['volume'] = val.text\\n elif key == 'Issue':\\n self.bib['number'] = val.text\\n elif key == 'Pages':\\n self.bib['pages'] = val.text\\n elif key == 'Publisher':\\n self.bib['publisher'] = val.text\\n elif key == 'Publication date':\\n self.bib['year'] = arrow.get(val.text).year\\n elif key == 'Description':\\n if val.text[0:8].lower() == 'abstract':\\n val = val.text[9:].strip()\\n self.bib['abstract'] = val\\n elif key == 'Total citations':\\n self.id_scholarcitedby = re.findall(\\n self._scholarly.URLS('SCHOLARPUBRE'), val.a['href'])[0]\\n\\n # number of citation per year\\n years = [int(y.text) for y in soup.find_all(class_='gsc_vcd_g_t')]\\n cites = [int(c.text) for c in soup.find_all(class_='gsc_vcd_g_al')]\\n self.cites_per_year = dict(zip(years, cites))\\n\\n if soup.find('div', class_='gsc_vcd_title_ggi'):\\n self.bib['eprint'] = soup.find(\\n 'div', class_='gsc_vcd_title_ggi').a['href']\\n self._filled = True\\n\\n elif self.source == 'scholar':\\n self.bib['add_to_lib'] = self.url_add_sclib\\n\\n try:\\n bibtex = self._scholarly._get_soup(self.url_scholarbib)\\n bibtex = bibtex.find('pre').string\\n self.bib.update(bibtexparser.loads(bibtex).entries[0])\\n self.bib['author_count'] = str(\\n len(self.bib['author'].split('and')))\\n self.bib['age'] = str(\\n int(date.today().year) - int(self.bib['year']))\\n except:\\n # did not find year\\n pass\\n\\n self._filled = True\\n return self\",\n \"def doc(docid):\\n\\t\\n\\tdata = {'id':docid,\\n\\t\\t\\t'text':\\\"Some made up text for classification\\\"}\\n\\treturn _send(data)\",\n \"def edit_document():\",\n \"def document(self):\\n ...\",\n \"def test_citations_and_toc_2(self):\\n settings = get_settings(\\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\\\"+citations\\\"],\\n PANDOC_ARGS=PANDOC_ARGS\\n + [\\n \\\"--table-of-contents\\\",\\n \\\"--citeproc\\\",\\n \\\"--csl=https://www.zotero.org/styles/ieee-with-url\\\",\\n \\\"--metadata=link-citations:false\\\",\\n \\\"--metadata=reference-section-title:References\\\",\\n ],\\n FORMATTED_FIELDS=FORMATTED_FIELDS,\\n )\\n\\n pandoc_reader = PandocReader(settings)\\n source_path = os.path.join(\\n TEST_CONTENT_PATH, \\\"valid_content_with_citation.md\\\"\\n )\\n output, metadata = pandoc_reader.read(source_path)\\n self.maxDiff = None\\n\\n self.assertEqual(\\n (\\n '<h2 id=\\\"string-theory\\\">String Theory</h2>\\\\n'\\n \\\"<p>But this foundational principle of science has\\\"\\n \\\" now been called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/'\\n 'string-theory\\\">String Theory</a>,'\\n \\\" which is a relative newcomer to theoretical physics, but one\\\"\\n \\\" that has captured the common imagination, judging by\\\"\\n \\\" the popular explanations that abound on the Web\\\"\\n ' <span class=\\\"citation\\\" data-cites=\\\"mann2019 wood2019'\\n ' jones2020\\\">[1]–[3]</span>.'\\n \\\" And whether string theory is or is not science, Popper\\\"\\n \\\" notwithstanding, is an issue that is still up for debate\\\"\\n \\\" <span\\\"\\n ' class=\\\"citation\\\" data-cites=\\\"siegel2015 castelvecchi2016'\\n ' alves2017 francis2019\\\">[4]–[7]</span>.</p>\\\\n'\\n '<h1 class=\\\"unnumbered\\\" id=\\\"bibliography\\\">References</h1>\\\\n'\\n '<div id=\\\"refs\\\" class=\\\"references csl-bib-body\\\"'\\n ' role=\\\"doc-bibliography\\\">\\\\n'\\n '<div id=\\\"ref-mann2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[1]'\\n ' </div><div class=\\\"csl-right-inline\\\">A. Mann,'\\n \\\" <span>“<span>What Is String Theory?</span>”</span>\\\"\\n \\\" 20-Mar-2019. [Online].\\\"\\n ' Available: <a href=\\\"https://www.livescience.com/'\\n '65033-what-is-string-theory.html\\\">'\\n \\\"https://www.livescience.com/\\\"\\n \\\"65033-what-is-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-wood2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[2] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n \\\"C. Wood, <span>“<span>What Is String Theory?</span>.\\\"\\n \\\" Reference article:\\\"\\n \\\" A simplified explanation and brief history of string\\\"\\n \\\" theory,”</span> 11-Jul-2019.\\\"\\n ' [Online]. Available: <a href=\\\"https://www.space.com/'\\n '17594-string-theory.html\\\">'\\n \\\"https://www.space.com/17594-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-jones2020\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[3]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'A. Z. Jones, <span>“<span class=\\\"nocase\\\">The Basics of String'\\n \\\" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.thoughtco.com/'\\n 'what-is-string-theory-2699363\\\">'\\n \\\"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-siegel2015\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[4]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n \\\"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\\\"\\n \\\" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\\\"\\n \\\" <a\\\"\\n ' href=\\\"https://www.forbes.com/sites/'\\n \\\"startswithabang/2015/12/23/\\\"\\n 'why-string-theory-is-not-science/\\\">https://www.forbes.com/'\\n \\\"sites/startswithabang/2015/12/23/\\\"\\n \\\"why-string-theory-is-not-science/</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-castelvecchi2016\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[5]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'D. Castelvecchi, <span>“<span class=\\\"nocase\\\">'\\n \\\"Feuding physicists turn\\\"\\n \\\" to philosophy for help</span>. String theory is at the\\\"\\n \\\" heart of a debate over the integrity of the scientific\\\"\\n \\\" method itself,”</span> 05-Jan-2016. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.nature.com/news/'\\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\\\">'\\n \\\"https://www.nature.com/news/\\\"\\n \\\"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-alves2017\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[6] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n 'R. A. Batista and J. Primack, <span>“<span class=\\\"nocase\\\">'\\n \\\"Is String theory falsifiable?</span>. Can a theory that isn’t\\\"\\n \\\" completely testable still be useful to physics?”</span>\\\"\\n \\\" [Online].\\\"\\n ' Available: <a href=\\\"https://metafact.io/factchecks/'\\n '30-is-string-theory-falsifiable\\\">'\\n \\\"https://metafact.io/factchecks/\\\"\\n \\\"30-is-string-theory-falsifiable</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-francis2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[7]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'M. R. Francis, <span>“<span class=\\\"nocase\\\">Falsifiability and'\\n \\\" physics</span>. Can a theory that isn’t completely testable\\\"\\n \\\" still be useful to physics?”</span> 23-Apr-2019.\\\"\\n \\\" [Online]. Available:\\\"\\n ' <a href=\\\"https://www.scientificamerican.com/'\\n 'article/is-string-theory-science/\\\">'\\n \\\"https://www.scientificamerican.com/article/is-\\\"\\n \\\"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n ),\\n output,\\n )\\n\\n self.assertEqual(\\\"Valid Content With Citation\\\", str(metadata[\\\"title\\\"]))\\n self.assertEqual(\\\"My Author\\\", str(metadata[\\\"author\\\"]))\\n self.assertEqual(\\\"2020-10-16 00:00:00\\\", str(metadata[\\\"date\\\"]))\\n self.assertEqual(\\n (\\n '<nav class=\\\"toc\\\" role=\\\"doc-toc\\\">\\\\n'\\n \\\"<ul>\\\\n\\\"\\n '<li><a href=\\\"#string-theory\\\">String Theory</a></li>\\\\n'\\n '<li><a href=\\\"#bibliography\\\">References</a></li>\\\\n'\\n \\\"</ul>\\\\n</nav>\\\\n\\\"\\n ),\\n str(metadata[\\\"toc\\\"]),\\n )\",\n \"def main():\\n papers_with_references = add_references_to_papers(PAPERS_FILE, TEXT_DIR)\\n citations = match_citations_with_papers(papers_with_references)\\n insert_into_citation_table(citations)\",\n \"def newThesisCitation(self, **attrlinks):\\n return ThesisCitation(self, **attrlinks)\",\n \"def beehive_make_doc(self):\\n run_data = {\\n u'tags':[u'doc'],\\n u'local_package_path':self.local_package_path\\n } \\n self.ansible_playbook(u'docs', run_data, \\n playbook=self.beehive_doc_playbook)\",\n \"def cpp_docs(self, html):\\n self._cppdocs = html\\n return self\",\n \"def doc_string():\\n pass # pass does nothing\",\n \"def getdoc(object):\\r\\n try:\\r\\n doc = object.__doc__\\r\\n except AttributeError:\\r\\n return None\\r\\n if not isinstance(doc, types.StringTypes):\\r\\n return None\\r\\n return cleandoc(doc)\",\n \"def initDocTagText(self):\\n self.doc, self.tag, self.text = Doc().tagtext()\",\n \"def _initEditEntryDocument(self, atomDoc): #@UnusedVariable #$NON-NLS-1$\\r\\n pass\",\n \"def citeproc(style, reference_list):\\n pass\",\n \"def doc(caesar, input):\\n name = input.group(1)\\n name = name.lower()\\n\\n if caesar.doc.has_key(name): \\n caesar.reply(caesar.doc[name][0])\\n if caesar.doc[name][1]: \\n caesar.say('e.g. ' + caesar.doc[name][1])\",\n \"def create_from_document(doc: Dict[str, Any]) -> 'Publication':\\n return Publication(\\n name=doc['doc_name'],\\n title=doc['doc_title'][:100],\\n type=doc['doc_type'],\\n number=doc['doc_num'],\\n is_ignored=False,\\n is_revoked=False\\n )\",\n \"def StartDoc(*args, **kwargs):\\n return _gdi_.DC_StartDoc(*args, **kwargs)\",\n \"def _copydoc():\\n with open(app_config.TRANSCRIPT_HTML_PATH) as f:\\n html = f.read()\\n\\n doc = CopyDoc(html)\\n context = {\\n 'doc': doc\\n }\\n\\n return make_response(render_template('copydoc.html', **context))\",\n \"def newBookCitation(self, **attrlinks):\\n return BookCitation(self, **attrlinks)\",\n \"def test_doc_representation(self):\\n doc_str = \\\"# This is a comment\\\\n* One\\\\nText text\\\"\\n doc = parser.parse(doc_str)\\n\\n self.assertEqual(str(doc), doc_str)\\n\\n doc_str = \\\"Text\\\\nMore text\\\\n\\\\n\\\\nSome empty lines and text\\\\n* HL\\\"\\n doc = parser.parse(doc_str)\\n\\n self.assertEqual(str(doc), doc_str)\\n\\n doc_str = \\\"- List one\\\\n + Slist one\\\\n + Slist two\\\"\\n doc = parser.parse(doc_str)\\n\\n self.assertEqual(str(doc), doc_str)\",\n \"def contract(docid):\\n return render_template('doc.html', docid=docid)\",\n \"def chikin():\\n return TexSoup(open(seed('samples/chikin.tex')))\",\n \"def cite(self, arg=None):\\n nums = self.selector.select_by_index(arg)\\n if nums is None or not nums:\\n self.visual.error(\\\"Need a selection to cite.\\\")\\n return\\n citation_id = \\\", \\\".join([self.reference_entry_id_list[n] for n in nums])\\n citation = \\\"\\\\\\\\cite{{{}}}\\\".format(citation_id)\\n # clipboard.copy(citation_id)\\n clipboard.copy(citation)\\n self.visual.message(\\\"Copied to clipboard: {}\\\".format(citation))\",\n \"def newJournalCitation(self, **attrlinks):\\n return JournalCitation(self, **attrlinks)\",\n \"def triple_quote_docs():\\n return\",\n \"def __init__(self,\\n title=\\\"[CDR Form Letter]\\\",\\n subject=None,\\n template=None,\\n pngName=\\\"dhhslogo.png\\\",\\n author=\\\"cdr\\\",\\n company=\\\"CIPS\\\",\\n binImage=False,\\n invitePara=\\\"\\\"):\\n\\n Document.__init__(self, title, author, company, subject)\\n self.generator = \\\"CDR RTF Writer\\\"\\n self.pngName = pngName # location of bitmap file for logo\\n self.margL = 1080 # 3/4-inch left margin\\n self.margR = 720 # 1/2-inch right margin\\n self.margT = 1080 # 5/8-inch top margin\\n self.margB = 1260 # 7/8-inch bottom margin\\n self.fSize = 21 # 10.5-point default font size\\n self.baskervilleFont = self.addFont(\\\"Baskerville Old Face\\\",\\n \\\"roman\\\",\\n \\\"Times New Roman\\\")\\n self.__addLetterHead(binImage)\\n if template:\\n try:\\n with open(template) as fp:\\n body = fp.read()\\n except Exception as e:\\n raise Exception(\\\"loading %s: %s\\\" % (template, str(e)))\\n if invitePara:\\n replacement = \\\"@@MISCDOC:%s@@\\\" % invitePara\\n body = body.replace(\\\"@@INVITATION@@\\\", replacement)\\n pattern = re.compile(\\\"@@MISCDOC:(.*?)@@\\\")\\n body = pattern.sub(lambda p: self.__loadMiscDoc(p), body)\\n self.addRawContent(body)\",\n \"def _parse_docstring(doc):\\n _cache_key = doc\\n try:\\n return _parse_docstring_cache[_cache_key]\\n except KeyError:\\n pass\\n\\n if doc is None:\\n return _Doc('', '', {})\\n\\n # Convert Google- or Numpy-style docstrings to RST.\\n # (Should do nothing if not in either style.)\\n doc = str(GoogleDocstring(doc))\\n doc = str(NumpyDocstring(doc))\\n\\n tree = publish_doctree(doc)\\n\\n class Visitor(NodeVisitor):\\n optional = [\\n 'document', 'docinfo',\\n 'field_list', 'field_body',\\n 'literal', 'problematic']\\n\\n def __init__(self, document):\\n NodeVisitor.__init__(self, document)\\n self.paragraphs = []\\n self.start_lines = []\\n self.params = defaultdict(dict)\\n self._current_paragraph = None\\n self._indent_iterator_stack = []\\n self._indent_stack = []\\n\\n def _do_nothing(self, node):\\n pass\\n\\n def visit_paragraph(self, node):\\n self.start_lines.append(node.line)\\n self._current_paragraph = []\\n\\n def depart_paragraph(self, node):\\n text = ''.join(self._current_paragraph)\\n text = ''.join(self._indent_stack) + text\\n self._indent_stack = [\\n ' ' * len(item) for item in self._indent_stack]\\n text = text.replace('\\\\n', '\\\\n' + ''.join(self._indent_stack))\\n self.paragraphs.append(text)\\n self._current_paragraph = None\\n\\n def visit_Text(self, node):\\n self._current_paragraph.append(node)\\n\\n depart_Text = _do_nothing\\n\\n def visit_emphasis(self, node):\\n self._current_paragraph.append('\\\\033[3m') # *foo*: italic\\n\\n def visit_strong(self, node):\\n self._current_paragraph.append('\\\\033[1m') # **foo**: bold\\n\\n def visit_title_reference(self, node):\\n self._current_paragraph.append('\\\\033[4m') # `foo`: underlined\\n\\n def _depart_markup(self, node):\\n self._current_paragraph.append('\\\\033[0m')\\n\\n depart_emphasis = depart_strong = depart_title_reference = \\\\\\n _depart_markup\\n\\n def visit_literal_block(self, node):\\n text, = node\\n self.start_lines.append(node.line)\\n self.paragraphs.append(re.sub('^|\\\\n', r'\\\\g<0> ', text)) # indent\\n raise SkipNode\\n\\n def visit_bullet_list(self, node):\\n self._indent_iterator_stack.append(\\n (node['bullet'] + ' ' for _ in range(len(node))))\\n\\n def depart_bullet_list(self, node):\\n self._indent_iterator_stack.pop()\\n\\n def visit_enumerated_list(self, node):\\n enumtype = node['enumtype']\\n fmt = {('(', ')'): 'parens',\\n ('', ')'): 'rparen',\\n ('', '.'): 'period'}[node['prefix'], node['suffix']]\\n try:\\n start = node['start']\\n except KeyError:\\n start = 1\\n else:\\n start = {\\n 'arabic': int,\\n 'loweralpha': lambda s: ord(s) - ord('a') + 1,\\n 'upperalpha': lambda s: ord(s) - ord('A') + 1,\\n 'lowerroman': lambda s: roman.fromRoman(s.upper()),\\n 'upperroman': lambda s: roman.fromRoman(s),\\n }[enumtype](start)\\n enumerators = [Body(None).make_enumerator(i, enumtype, fmt)[0]\\n for i in range(start, start + len(node))]\\n width = max(map(len, enumerators))\\n enumerators = [enum.ljust(width) for enum in enumerators]\\n self._indent_iterator_stack.append(iter(enumerators))\\n\\n def depart_enumerated_list(self, node):\\n self._indent_iterator_stack.pop()\\n\\n def visit_list_item(self, node):\\n self._indent_stack.append(next(self._indent_iterator_stack[-1]))\\n\\n def depart_list_item(self, node):\\n self._indent_stack.pop()\\n\\n def visit_field(self, node):\\n field_name_node, field_body_node = node\\n field_name, = field_name_node\\n parts = field_name.split()\\n if len(parts) == 2:\\n doctype, name = parts\\n elif len(parts) == 3:\\n doctype, type_, name = parts\\n if doctype not in _PARAM_TYPES:\\n raise SkipNode\\n if 'type' in self.params[name]:\\n raise ValueError('type defined twice for {}'.format(name))\\n self.params[name]['type'] = type_\\n else:\\n raise SkipNode\\n if doctype in _PARAM_TYPES:\\n doctype = 'param'\\n if doctype in _TYPE_NAMES:\\n doctype = 'type'\\n if doctype in self.params[name]:\\n raise ValueError('{} defined twice for {}'.format(doctype, name))\\n visitor = Visitor(self.document)\\n field_body_node.walkabout(visitor)\\n self.params[name][doctype] = ''.join(visitor.paragraphs)\\n raise SkipNode\\n\\n def visit_comment(self, node):\\n raise SkipNode\\n\\n def visit_system_message(self, node):\\n raise SkipNode\\n\\n visitor = Visitor(tree)\\n tree.walkabout(visitor)\\n\\n tuples = {name: _Param(values.get('param'), values.get('type'))\\n for name, values in visitor.params.items()}\\n if visitor.paragraphs:\\n text = []\\n for start, paragraph, next_start in zip(\\n visitor.start_lines,\\n visitor.paragraphs,\\n visitor.start_lines[1:] + [0]):\\n text.append(paragraph)\\n # We insert a space before each newline to prevent argparse\\n # from stripping consecutive newlines down to just two\\n # (http://bugs.python.org/issue31330).\\n text.append(' \\\\n' * (next_start - start - paragraph.count('\\\\n')))\\n parsed = _Doc('', ''.join(text), tuples)\\n else:\\n parsed = _Doc('', '', tuples)\\n _parse_docstring_cache[_cache_key] = parsed\\n return parsed\",\n \"def prepareDocument(self):\\n self.checkSyntaxDocument()\",\n \"def build_document(self):\\n pass\",\n \"async def create_doc(self, *args, **kwargs):\\n pass\",\n \"def docstring_hack():\\n pass\",\n \"def __init__(self, doc_string: ast3.Expr, doc_type: Type) -> None:\\n self._doc = doc_string\\n self.value = doc_string.value.s.strip() # type: ignore\\n desc = Tags.DESC.regex.search(self.value)\\n ret = Tags.RETURN.regex.search(self.value)\\n cc = Tags.CC.regex.search(self.value) # pylint: disable=invalid-name\\n author = Tags.AUTHOR.regex.search(self.value)\\n todo = Tags.TODO.regex.search(self.value)\\n\\n self.no_lint = bool(Tags.NO_LINT.regex.search(self.value))\\n self.no_doc = bool(Tags.NO_DOC.regex.search(self.value))\\n self.todo = todo[1] if todo else \\\"\\\"\\n\\n self.desc = desc[1] if desc else \\\"\\\"\\n self.args = {\\n x: y\\n for x, y in Tags.ARG.regex.findall(self.value)\\n if x not in DEFAULT_ARG_IGNORE\\n }\\n self.links = Tags.LINK.regex.findall(self.value)\\n self.ret = ret[1] if ret else \\\"\\\"\\n self.author = author[1] if author else \\\"\\\"\\n self.cc = int(cc[1] if cc else -1) # pylint: disable=invalid-name\\n\\n self.notes = Tags.NOTE.regex.findall(self.value)\\n self.warnings = Tags.WARN.regex.findall(self.value)\",\n \"def documentation():\\n return auto.html()\",\n \"def portrayalCatalogueCitation(self) -> Sequence[Citation]:\\n pass\",\n \"def doc(obj):\\n return Documentation.fromObject(obj).first\",\n \"def inherits_doc():\\n pass\",\n \"def get_citation(self):\\n etree = self.get_eml()\\n try:\\n citation_ipt = etree.find('./additionalMetadata/metadata/gbif/citation').text\\n except AttributeError:\\n citation_ipt = None\\n if citation_ipt:\\n now = datetime.datetime.now().date()\\n pola3r = \\\"(Available: Polar 'Omics Links to Antarctic, Arctic and Alpine Research. Antarctic Biodiversity Portal. Scientific Committee for Antarctic Research. www.biodiversity.aq/pola3r. Accessed: {})\\\".format(\\n now)\\n citation = \\\"{} {}\\\".format(citation_ipt, pola3r)\\n else:\\n citation = None\\n return citation\",\n \"def getBibTeX(bibref,tag_suf,outFile):\\n if bibref == '1988iras....1.....B':\\n bibtex = ['>@article{1988iras....1.....B,\\\\n',\\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\\\n',\\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\\\n',\\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\\\n',\\n ' year=1988,\\\\n',\\n ' volume = {1},\\\\n', \\n ' month = jan,\\\\n', \\n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\\\n'\\n '}\\\\n']\\n else:\\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\\n suf = '/exportcitation'\\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\\n \\n bibtex = []\\n for l in range(0, len(lines)):\\n if 'export-textarea ' in str(lines[l]):\\n bibtex.append(str(lines[l]))\\n t = l+1\\n \\n while '</textarea>' not in str(lines[t+1]):\\n bibtex.append(str(lines[t])) \\n t += 1\\n \\n for item in bibtex:\\n if 'author' in item.split('=')[0]:\\n auth = item.split('=')[1].split(',')[0]\\n for i in string.punctuation:\\n auth = auth.replace(i, '')\\n auth = auth.replace(' ', '')\\n if 'year' in item.split('=')[0]:\\n yr = item.split('=')[1].split(',')[0]\\n yr = yr.replace(' ', '')\\n \\n try:\\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\\\n'\\n except UnboundLocalError as ule:\\n print(bibtex)\\n print('')\\n print(ule)\\n sys.exit()\\n \\n with open(outFile, 'a') as o:\\n for item in bibtex:\\n item = item.replace('"', '\\\"')\\n item = item.replace(''', \\\"'\\\")\\n item = item.replace('&', \\\"&\\\")\\n o.write(item)\\n o.write('\\\\n')\\n \\n return auth+yr+tag_suf\",\n \"def with_docs(self):\\r\\n self._configurations.append('javadoc')\\r\\n return self\",\n \"def test_doc():\\n pass\",\n \"def doc_begin(fdoc):\\n fdoc.write(\\n '\\\\\\\\documentclass{{hyperiondoc}}\\\\n'\\n '\\\\n'\\n '\\\\\\\\usepackage{{adjustbox}}\\\\n'\\n '\\\\\\\\usepackage{{{0}}}\\\\n'\\n '\\\\\\\\newfontfamily{{\\\\\\\\symbola}}{{Symbola}}\\\\n'\\n '\\\\\\\\USymbolAllStyle{{\\\\\\\\symbola}}\\\\n'\\n '\\\\n'\\n '\\\\\\\\newcommand{{\\\\\\\\symboldemo}}[3]{{%\\\\n'\\n ' \\\\\\\\noindent\\\\\\\\begin{{minipage}}[c]{{.1\\\\\\\\textwidth}}\\\\n'\\n ' \\\\\\\\centering\\\\\\\\textlarger[2]{{#3}}\\\\n'\\n ' \\\\\\\\end{{minipage}}%\\\\n'\\n ' \\\\\\\\begin{{minipage}}{{.8\\\\\\\\textwidth}}\\\\n'\\n ' $\\\\\\\\mathtt{{0x#1}}$\\\\\\\\\\\\\\\\[-0.4em]\\\\n'\\n ' \\\\\\\\adjustbox{{max width=.9\\\\\\\\textwidth}}{{\\\\\\\\code{{\\\\\\\\bs #2}}}}\\\\n'\\n ' \\\\\\\\end{{minipage}}\\\\\\\\\\\\\\\\[0.6em]\\\\n'\\n '}}\\\\n'\\n '\\\\n'\\n '\\\\\\\\begin{{document}}\\\\n'\\n .format(package_name('all'))\\n )\",\n \"def __init__(self,txt=u'',unicodeEncoding='utf-8',verbose=False,tagID=0):\\n # __document capture the document level structure\\n # for each sentence and then put in the archives when the next sentence\\n # is processed\\n super(ConTextMarkup,self).__init__(__txt=None,__rawTxt=txt,\\n __SCOPEUPDATED=False,__VERBOSE=verbose,\\n __tagID=tagID,\\n __unicodeEncoding=unicodeEncoding)\\n self.__cleanText()\",\n \"def pubmed_citation(args=sys.argv[1:], out=sys.stdout):\\n\\n parser = argparse.ArgumentParser(\\n description='Get a citation using a PubMed ID or PubMed URL')\\n parser.add_argument('query', help='PubMed ID or PubMed URL')\\n parser.add_argument(\\n '-m', '--mini', action='store_true', help='get mini citation')\\n parser.add_argument(\\n '-e', '--email', action='store', help='set user email', default='')\\n\\n args = parser.parse_args(args=args)\\n\\n lookup = PubMedLookup(args.query, args.email)\\n publication = Publication(lookup, resolve_doi=False)\\n\\n if args.mini:\\n out.write(publication.cite_mini() + '\\\\n')\\n else:\\n out.write(publication.cite() + '\\\\n')\",\n \"def doc(self):\\n doc = self.get('doc')\\n if doc:\\n from .config import defaults\\n return defaults.types.doc(doc)\",\n \"def docx():\\n env.file_ext = \\\".docx\\\"\\n local(\\\"pandoc {input_files} -o {output_file}{file_ext} --bibliography={bib_file} --csl={csl_file} --toc\\\".format(**env))\",\n \"def start(self) -> None:\\n\\n self.doc = self.doc + r'''\\n \\\\documentclass[\\n 10pt, % Main document font size\\n a4paper, % Paper type, use 'letterpaper' for US Letter paper\\n ]{scrartcl}\\n\\n \\\\usepackage{graphicx}\\n \\\\usepackage{epstopdf}\\n \\\\usepackage{float}\\n \\\\usepackage[scale=0.75]{geometry} % Reduce document margins\\n \\\\usepackage{hyperref}\\n \\\\usepackage{longtable}\\n\\n \\\\begin{document}\\n\\n \\\\title{Automatic Exploratory Data Analysis} % The article title\\n\\n \\\\subtitle{Study Case} % Uncomment to display a subtitle\\n\\n \\\\author{Jacob} % The article author(s) - author affiliations need to be specified in the AUTHOR AFFILIATIONS block\\\\\\n\\n \\\\maketitle % Print the title/author/date block\\n\\n \\\\newpage\\n \\\\tableofcontents % Print the table of contents\\n\\n \\\\newpage\\n \\\\listoffigures % Print the list of figures\\n\\n \\\\newpage\\n \\\\listoftables % Print the list of tables\\n '''\",\n \"def __init__(self, doc, artDirection, path=None, mdText=None, startPage=1,\\n name=None, **kwargs):\\n self.doc = doc # Reuired Document instance. Assummed to be initialized with size and styles.\\n self.artDirection = artDirection\\n self.path = path # Optional path to markdown file, if it has content.\\n self.mdText = mdText # Optional markdown string.\\n self.name = name or 'Untitled'\\n self.startPage = startPage\",\n \"def __init__(self, txt='', unicodeEncoding='utf-8'):\\n # __document capture the document level structure\\n # for each sentence and then put in the archives when the next sentence\\n # is processed\\n super(ConTextMarkup, self).__init__(__txt=None,\\n __rawtxt=txt,\\n __scope=None,\\n __SCOPEUPDATED=False)\\n self.__document = nx.DiGraph()\\n self.__document.add_node(\\\"top\\\", category=\\\"document\\\")\\n self.__VERBOSE = False\\n self.__tagID = 0\\n self.__unicodeEncoding = unicodeEncoding\",\n \"def make_doc(file, \\n title, \\n author, \\n geometry_options = {\\\"margin\\\": \\\"1.15cm\\\"}, \\n options=\\\"\\\"):\\n \\n # geometry_options = {\\\"tmargin\\\": \\\"1.5cm\\\", \\\"lmargin\\\": \\\"2.5cm\\\"},\\n\\n doc = Document(\\n default_filepath = file.as_posix(),\\n documentclass = 'article',\\n document_options = ['12pt', 'titlepage' ] + options,\\n fontenc = \\\"T1\\\",\\n inputenc = ENCODING,\\n font_size = \\\"normalsize\\\",\\n lmodern = True,\\n page_numbers = False,\\n indent = False,\\n geometry_options = geometry_options\\n )\\n doc.change_document_style(\\\"empty\\\")\\n date = str(datetime.datetime.date(datetime.datetime.now()))\\n comment(doc.preamble, \\\"Automatically generated by make on \\\" + date)\\n\\n doc.preamble.append(Command(\\\"usepackage\\\",\\\"graphicx\\\"))\\n doc.preamble.append(Command(\\\"usepackage\\\",\\\"enumitem\\\"))\\n doc.preamble.append(Command(\\\"usepackage\\\",\\\"url\\\"))\\n doc.preamble.append(NoEscape(\\\"\\\\\\\\setcounter{secnumdepth}{0}\\\"))\\n doc.preamble.append(Command(\\\"usepackage\\\",\\\"titlesec\\\"))\\n doc.preamble.append(NoEscape(\\\"\\\\\\\\titlespacing\\\\\\\\section{0pt}{12pt}{12pt}\\\"))\\n doc.preamble.append(NoEscape(\\\"\\\\\\\\titlespacing\\\\\\\\subsection{0pt}{12pt}{12pt}\\\"))\\n doc.preamble.append(Command(\\\"title\\\", title.title()))\\n doc.preamble.append(Command(\\\"author\\\", author.title()))\\n doc.preamble.append(Command(\\\"date\\\", NoEscape(r'\\\\today')))\\n doc.append(NoEscape(r'\\\\maketitle'))\\n return doc\",\n \"def write_citation_page(refdict: dict) -> None:\\n with open(WEBOUT_PATH + init_data().cite_url, \\\"w\\\", encoding=\\\"utf-8\\\") as outfile:\\n common_html_header(outfile, \\\"Fiddler Crab Website Citation\\\")\\n outfile.write(\\\" <header id=\\\\\\\"\\\" + init_data().cite_url + \\\"\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <h1>Citation Info</h1>\\\\n\\\")\\n outfile.write(\\\" </header>\\\\n\\\")\\n outfile.write(\\\"\\\\n\\\")\\n outfile.write(\\\" <p>\\\\n\\\")\\n outfile.write(\\\" Generally it is best to cite the primary literature, whenever possible. However, the \\\"\\n \\\"following paper describes much of the data that is unique to this website:\\\\n\\\")\\n outfile.write(\\\" </p>\\\\n\\\")\\n outfile.write(\\\" <div class=\\\\\\\"reference_list\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <ul>\\\\n\\\")\\n ref = refdict[\\\"Rosenberg2014\\\"] # citation describing the database\\n outfile.write(\\\" <li><a href=\\\\\\\"references/Rosenberg2014.html\\\\\\\">\\\" + ref.formatted_html + \\\"</a></li>\\\\n\\\")\\n outfile.write(\\\" </ul>\\\\n\\\")\\n outfile.write(\\\" </div>\\\\n\\\")\\n outfile.write(\\\" <ul class=\\\\\\\"fa-ul\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <li>\\\" + fetch_fa_glyph(\\\"list pdf\\\") +\\n \\\"<a href=\\\\\\\"https://dx.plos.org/10.1371/journal.pone.0101704\\\\\\\">Read paper online at \\\"\\n \\\"PLoS ONE</a></li>\\\\n\\\")\\n outfile.write(\\\" <li>\\\" + fetch_fa_glyph(\\\"list github\\\") +\\n \\\"<a href=\\\\\\\"https://github.com/msrosenberg/fiddlercrab.info\\\\\\\">Website data repository on \\\"\\n \\\"GitHub</a></li>\\\\n\\\")\\n outfile.write(\\\" </ul>\\\\n\\\")\\n common_html_footer(outfile)\",\n \"def read(self, source_path):\\r\\n from cStringIO import StringIO\\r\\n with pelican_open(source_path) as source:\\r\\n text = StringIO(source)\\r\\n content = StringIO()\\r\\n ad = AsciiDocAPI()\\r\\n\\r\\n options = self.settings['ASCIIDOC_OPTIONS']\\r\\n if isinstance(options, (str, unicode)):\\r\\n options = [m.strip() for m in options.split(',')]\\r\\n options = self.default_options + options\\r\\n for o in options:\\r\\n ad.options(*o.split())\\r\\n\\r\\n ad.execute(text, content, backend=\\\"html4\\\")\\r\\n content = content.getvalue()\\r\\n\\r\\n metadata = {}\\r\\n for name, value in ad.asciidoc.document.attributes.items():\\r\\n name = name.lower()\\r\\n metadata[name] = self.process_metadata(name, value)\\r\\n if 'doctitle' in metadata:\\r\\n metadata['title'] = metadata['doctitle']\\r\\n return content, metadata\",\n \"def get_doc(self, dtype, identity):\\n if dtype == 'pii':\\n doc = FullDoc(sd_pii = identity)\\n elif dtype == 'doi':\\n doc= FullDoc(doi = identity)\\n\\n if doc.read(ElsClient(self.API_list[0])):\\n pass\\n else:\\n print (\\\"Read document failed.\\\")\\n\\n return doc\",\n \"def bibtex(self):\\n return \\\"@comment{%(id)s: %(message)s}\\\" % \\\\\\n {'id': self.id, 'message': self.message}\",\n \"def onDocumentation(self):\\n path = self.settings.path + 'doc\\\\\\\\report.pdf'\\n os.startfile(path)\",\n \"def process_citation(style, reference_list, citation):\\n processed_citation = Element(\\\"span\\\", attrib={\\\"class\\\":\\\"citation\\\"})\\n\\n for reference in reference_list:\\n citeref = SubElement(processed_citation, \\\"span\\\")\\n for style_node in style.citation.layout:\\n process_node(citeref, style_node, style.macros, reference) \\n\\n return(processed_citation)\",\n \"def doc(update: Update, context: CallbackContext):\\n language_code = update.effective_user.language_code\\n args = context.args\\n if_admin = database.get_user_attr('admin', user_id=update.effective_user.id)\\n if len(args) > 2:\\n text = get_text('quantity_error_doc_text', language_code).text()\\n else:\\n if len(args) == 0:\\n text = get_text('doc_text', language_code).text({'command': consts.ALL, 'admin': if_admin})\\n else:\\n if args[0] not in consts.DOC_COMMANDS:\\n text = get_text('wrong_command_error_doc_text', language_code).text()\\n else:\\n text = get_text('doc_text', language_code).text({'command': args[0], 'admin': if_admin})\\n if not if_admin and args[0] == 'admin':\\n text += get_text('doc_unavailable_text', language_code).text()\\n cf.send_message(\\n context=context,\\n chat_id=update.effective_chat.id,\\n text=text,\\n )\",\n \"def getdoc():\\n\\n\\timport webnotes\\n\\tfrom webnotes.utils import cint\\n\\t\\n\\tform = webnotes.form_dict\\n\\tdoctype, docname = form.get('doctype'), form.get('name')\\n\\tprefix = cint(form.get('from_archive')) and 'arc' or 'tab'\\n\\n\\tif not (doctype and docname):\\n\\t\\traise Exception, 'doctype and name required!'\\n\\t\\n\\tdoclist = []\\n\\t# single\\n\\tdoclist = load_single_doc(doctype, docname, (form.get('user') or webnotes.session['user']), prefix)\\n\\t\\n\\t# load doctype along with the doc\\n\\tif form.get('getdoctype'):\\n\\t\\timport webnotes.model.doctype\\n\\t\\tdoclist += webnotes.model.doctype.get(doctype)\\n\\n\\t# tag as archived\\n\\tif prefix == 'arc':\\n\\t\\tdoclist[0].__archived=1\\n\\n\\twebnotes.response['docs'] = doclist\",\n \"def get_doc(self) -> str:\\n if self.soup is not None:\\n root = self.soup.contents[0]\\n body = self.get_paragraph(root.find(\\\"abstract\\\", recursive=False))\\n body += self.get_paragraph(root.find(\\\"discussion\\\", recursive=False))\\n return body\\n\\n return self.doc\",\n \"def __init__(self, doi='', reference=''):\\n\\n self.doi = doi\\n self.reference = reference\",\n \"def newConferenceCitation(self, **attrlinks):\\n return ConferenceCitation(self, **attrlinks)\",\n \"def get_documentation(self, *args, **dargs):\\n pass\",\n \"def generate_readme_url(self, dn):\\n\\n df_curation = dn.curation_dict\\n\\n # Preferred citation\\n single_str_citation = df_curation['item']['citation']\\n\\n # handle period in author list. Assume no period in dataset title\\n str_list = list([single_str_citation.split('):')[0] + '). '])\\n str_list += [str_row + '.' for str_row in single_str_citation.split('):')[1].split('. ')]\\n\\n citation_list = [content for content in str_list[0:-2]]\\n citation_list.append(f\\\"{str_list[-2]} {str_list[-1]}\\\")\\n citation_list = ' <br> '.join(citation_list)\\n\\n # summary\\n figshare_description = df_curation['item']['description']\\n\\n query_str_dict = {'article_id': dn.name_dict['article_id'],\\n 'curation_id': dn.name_dict['curation_id'],\\n 'title': dn.name_dict['title'],\\n 'depositor_name': dn.name_dict['simplify_fullName'],\\n 'preferred_citation': citation_list,\\n 'license': df_curation['item']['license']['name'],\\n 'summary': figshare_description}\\n # doi\\n if not df_curation['item']['doi']: # empty case\\n query_str_dict['doi'] = f\\\"https://doi.org/10.25422/azu.data.{dn.name_dict['article_id']}\\\"\\n else:\\n query_str_dict['doi'] = f\\\"https://doi.org/{df_curation['item']['doi']}\\\"\\n\\n # links\\n if not df_curation['item']['references']: # not empty case\\n links = \\\" <br> \\\".join(df_curation['item']['references'])\\n query_str_dict['links'] = links\\n\\n # query_str_encode = str(query_str_dict).encode('base64', 'strict')\\n q_eed = base64.urlsafe_b64encode(json.dumps(query_str_dict).encode()).decode()\\n\\n full_url = f\\\"{self.dict['generate_url']}{self.readme_survey_id}?\\\" + \\\\\\n 'Q_EED=' + q_eed\\n\\n return full_url\",\n \"def test_docstring(self):\\n self.assertIsNotNone(City.__doc__)\",\n \"def __init__(self):\\n self._pronunciations = nltk.corpus.cmudict.dict()\\n \\\"\\\"\\\"\\n API Documentation for CMU dictionary corpus\\n http://www.nltk.org/api/nltk.corpus.reader.html#module-nltk.corpus.reader.cmudict\\n \\\"\\\"\\\"\",\n \"def convert(text):\\n return NewDocument.from_rst(text).format()\",\n \"def process(self, doc, is_):\\n implementation = Implementation(self)\\n implementation.process(doc, is_)\\n return implementation.html\",\n \"def doDocStrings(parentNode, srcNode):\\n def makeDocElement(name, content):\\n node = libxml2.newNode(name)\\n node.addChild(libxml2.newText(content))\\n return node\\n \\n autodoc = getAttr(srcNode, \\\"python_autodoc\\\")\\n docstr = getAttr(srcNode, \\\"feature_docstring\\\")\\n if autodoc:\\n parentNode.addChild(makeDocElement(\\\"autodoc\\\", autodoc))\\n if docstr:\\n parentNode.addChild(makeDocElement(\\\"docstring\\\", docstr))\",\n \"def add_doc(writer, entry):\\n m = 0\\n q_id = entry['Id']\\n snippets = get_possible_snippets(q_id, False)\\n for code, lang, ans_id in snippets:\\n writer.add_document(question_id=q_id, answer_id=ans_id, code=return_unicode(code), language=return_unicode(lang))\\n m += 1\\n return m\",\n \"def document(cls):\\n header = cls.document_header()\\n content = cls.document_content()\\n index = cls.document_index()\\n package = cls.package().name\\n filename = inspect.getsourcefile(cls)\\n try:\\n lines = inspect.getsourcelines(cls)\\n except IOError:\\n lines = ([], 0)\\n line = lines[1]+1\\n return DocEntry(\\n header, content, index=index,\\n package=package, filename=filename, line=line)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6251723","0.61804336","0.61777425","0.6167132","0.6147496","0.610238","0.60910994","0.6082328","0.6082024","0.6033947","0.6022621","0.59620064","0.59356797","0.59301627","0.59235984","0.5893333","0.5893333","0.58614635","0.5857272","0.58394206","0.5837961","0.58084226","0.58046913","0.57456094","0.5733864","0.57287204","0.57216597","0.57182086","0.56775606","0.56647325","0.5622898","0.5618896","0.5615274","0.55920756","0.55897874","0.55863464","0.5576167","0.55744874","0.55418223","0.5533117","0.5514196","0.5478431","0.5452444","0.5450243","0.54257566","0.54153466","0.5393141","0.5391066","0.53884757","0.536399","0.5347513","0.5329013","0.53273654","0.53045726","0.52951694","0.528427","0.5274091","0.5270366","0.52694124","0.5263002","0.52601826","0.52502847","0.52466184","0.52461994","0.52429104","0.52413076","0.52266127","0.5226018","0.52173847","0.5212011","0.52112395","0.5206317","0.52045435","0.52039266","0.5202961","0.52012646","0.51905036","0.5188019","0.51739204","0.51626617","0.5162504","0.5157966","0.51393276","0.51351935","0.5123443","0.5122699","0.5121104","0.5117149","0.51130104","0.511265","0.51043785","0.50955886","0.5094647","0.5073166","0.5070926","0.50696754","0.50672257","0.50668037","0.50645053","0.50641114"],"string":"[\n \"0.6251723\",\n \"0.61804336\",\n \"0.61777425\",\n \"0.6167132\",\n \"0.6147496\",\n \"0.610238\",\n \"0.60910994\",\n \"0.6082328\",\n \"0.6082024\",\n \"0.6033947\",\n \"0.6022621\",\n \"0.59620064\",\n \"0.59356797\",\n \"0.59301627\",\n \"0.59235984\",\n \"0.5893333\",\n \"0.5893333\",\n \"0.58614635\",\n \"0.5857272\",\n \"0.58394206\",\n \"0.5837961\",\n \"0.58084226\",\n \"0.58046913\",\n \"0.57456094\",\n \"0.5733864\",\n \"0.57287204\",\n \"0.57216597\",\n \"0.57182086\",\n \"0.56775606\",\n \"0.56647325\",\n \"0.5622898\",\n \"0.5618896\",\n \"0.5615274\",\n \"0.55920756\",\n \"0.55897874\",\n \"0.55863464\",\n \"0.5576167\",\n \"0.55744874\",\n \"0.55418223\",\n \"0.5533117\",\n \"0.5514196\",\n \"0.5478431\",\n \"0.5452444\",\n \"0.5450243\",\n \"0.54257566\",\n \"0.54153466\",\n \"0.5393141\",\n \"0.5391066\",\n \"0.53884757\",\n \"0.536399\",\n \"0.5347513\",\n \"0.5329013\",\n \"0.53273654\",\n \"0.53045726\",\n \"0.52951694\",\n \"0.528427\",\n \"0.5274091\",\n \"0.5270366\",\n \"0.52694124\",\n \"0.5263002\",\n \"0.52601826\",\n \"0.52502847\",\n \"0.52466184\",\n \"0.52461994\",\n \"0.52429104\",\n \"0.52413076\",\n \"0.52266127\",\n \"0.5226018\",\n \"0.52173847\",\n \"0.5212011\",\n \"0.52112395\",\n \"0.5206317\",\n \"0.52045435\",\n \"0.52039266\",\n \"0.5202961\",\n \"0.52012646\",\n \"0.51905036\",\n \"0.5188019\",\n \"0.51739204\",\n \"0.51626617\",\n \"0.5162504\",\n \"0.5157966\",\n \"0.51393276\",\n \"0.51351935\",\n \"0.5123443\",\n \"0.5122699\",\n \"0.5121104\",\n \"0.5117149\",\n \"0.51130104\",\n \"0.511265\",\n \"0.51043785\",\n \"0.50955886\",\n \"0.5094647\",\n \"0.5073166\",\n \"0.5070926\",\n \"0.50696754\",\n \"0.50672257\",\n \"0.50668037\",\n \"0.50645053\",\n \"0.50641114\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6069784"},"document_rank":{"kind":"string","value":"9"}}},{"rowIdx":25689,"cells":{"query":{"kind":"string","value":"Want a citation string as opposed to a reference. That is, we want author (year), as opposed to author, title, journal, volume pages etc, they go in the bibliography."},"document":{"kind":"string","value":"def _populate(self):\n\n # Assume the first word is what we want, and we can find well formed years\n # This sucks, but will work for these ones.\n # Roll on bibtex for citations in the CIM.\n\n citation_detail = self.doc.citation_detail\n author = citation_detail.split(',')[0]\n match = '([^\\w])19|20\\d\\d([^\\w])*?'\n m = re.search(match, citation_detail)\n if m:\n year = m.group(0)\n else:\n year = None\n\n # one error in existing es-doc content to be fixed:\n if 'van Vuuren DP' in author:\n author = 'van Vuuren'\n print 'applying vv fix'\n\n self.year = int(year)\n\n # We assume that this table will have entries which ne\n\n # I use the first three letters of a an authors name, and for\n # three or more authors, EA, and then the year for my bibtex citation string\n self.citeguess = author[0:3] + 'EA' + year[2:]\n # This is what will appear in the table:\n self.citestring = '%s et al. (%s)' % (author, year)\n # Keep this for a reference list for checking against the eventual bibtex reference list.\n self.text = citation_detail"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def to_citation(self, type):\n acs_authors = \"; \".join(self.format_authors(\"acs\"))\n # Some articles don't come with pages. :-(\n pages_with_endash = (self.pages.replace(\"-\", \"\\u2013\") if self.pages\n else \"\")\n # Actually, not using quote() generally gives results that work fine.\n # The only issue is that when using Markdown URLs with parentheses in\n # Jupyter notebooks, the conversion to HTML gets it wrong, thinking\n # that the URL ends at the first close parentheses in the URL. (In\n # the notebook itself, it is fine, only the conversion to HTML messes\n # up.) So we might as well escape them generally.\n doi_url = f\"https://doi.org/{urllib.parse.quote(self.doi)}\"\n\n # BibLaTeX\n if type in [\"bib\", \"b\"]:\n # Create (hopefully) unique identifier\n author_decoded = unidecode(self.authors[0][\"family\"])\n journal_initials = \"\".join(c for c in self.journal_short\n if c.isupper())\n ref_identifier = f\"{author_decoded}{self.year}{journal_initials}\"\n ref_identifier = \"\".join(ref_identifier.split()) # remove spaces\n # Author names in bib style\n author_names = \" and \".join(self.format_authors(\"bib\"))\n journal = self.journal_short.replace(\". \", \".\\\\ \")\n # Open and close braces\n # Truthfully we don't need this. However, including the doubled\n # curly braces in the f-string makes vim's indentation go crazy.\n open, close = \"{\", \"}\"\n # Make the citation\n s = (f\"@article{open}{ref_identifier},\\n\"\n f\" doi = {{{self.doi}}},\\n\"\n f\" author = {{{author_names}}},\\n\"\n f\" journal = {{{journal}}},\\n\"\n f\" title = {{{self.title}}},\\n\"\n f\" year = {{{self.year}}},\\n\")\n if self.volume is not None:\n s += f\" volume = {{{self.volume}}},\\n\"\n if self.issue is not None:\n s += f\" issue = {{{self.issue}}},\\n\"\n if self.pages is not None:\n s += f\" pages = {{{self.pages.replace('-', '--')}}},\\n\"\n s += close\n # Replace Unicode characters with their LaTeX equivalents\n for char in _g.unicodeLatexDict:\n s = s.replace(char, _g.unicodeLatexDict[char])\n return s\n\n # Just DOI\n if type in [\"doi\", \"d\"]:\n return self.doi\n\n # The rest all have a long vs short type.\n # Discern long vs short type\n long = False\n if type[0].upper() == type[0]:\n long = True\n type = type.lower()\n\n # reStructuredText\n if type in [\"rst\", \"r\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"*{self.volume}* ({self.issue}), \" if self.issue\n else f\"*{self.volume},* \")\n return (author_title\n + f\"*{self.journal_short}* **{self.year},** \"\n + vol_issue\n + f\"{pages_with_endash}. \"\n + f\"`DOI: {self.doi} <{doi_url}>`_\")\n\n # Markdown\n if type in [\"markdown\", \"m\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"*{self.volume}* ({self.issue}), \" if self.issue\n else f\"*{self.volume},* \")\n return (author_title\n + f\"*{self.journal_short}* **{self.year},** \"\n + vol_issue\n + f\"{pages_with_endash}. \"\n + f\"[DOI: {self.doi}]({doi_url})\")\n\n # Word\n elif type in [\"word\", \"w\"]:\n author_title = f\"{acs_authors} {self.title}. \" if long else \"\"\n vol_issue = (f\"{self.volume} ({self.issue}), \" if self.issue\n else f\"{self.volume}, \")\n return (author_title\n + f\"{self.journal_short} {self.year}, \"\n + vol_issue\n + f\"{pages_with_endash}.\")\n\n else:\n raise ValueError(\"Invalid citation type '{type}' given\")","def make_citation(meta):\n pass","def citation_formatter(citation, title=False):\n # first we split the author-list\n citation_string = \"\"\n # the spaces around the and are required!\n for match in citation[\"author\"].split(\" and \"):\n last_name, first_names = match.split(\",\", 1)\n citation_string += last_name.strip() + \",\"\n for name in first_names.strip().split(' '):\n citation_string += \" \" + name.strip()[0]\n\n citation_string += \"; \"\n\n if \"journal\" in citation:\n citation_string += \" \" + citation[\"journal\"]\n\n citation_string += \" \" + citation[\"year\"]\n\n if \"doi\" in citation:\n citation_string += \"; \" + citation[\"doi\"]\n\n return citation_string","def cite(silent=False):\n if silent is False:\n print(__cite__)\n else:\n return __bibtex__","def create_citation(cit):\n if cit is not None:\n if cit['citation-type'] == \"BIBTEX\":\n return pybtex.database.parse_string(cit['citation-value'], \"bibtex\")\n return None","def make_bibtex(self):\n\n\t\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, ","def refine_author(c):\n c = strip_some_punct(c)\n c = strip_numbers(c)\n c = strip_all_unbalanced_parens(c)\n c = c.split()\n # this is hard to catch otherwise, unless we split the author vs copyright grammar in two\n if c[0].lower() == 'author':\n c = c[1:]\n c = u' '.join(c)\n return c.strip()","def process_bib_entry(\n cid, bibdatabase, bibnums, fallback_fmt=\"[{author_abbrev}, {year}]\"\n):\n entry = bibdatabase[cid]\n if cid not in bibnums:\n bibnums[cid] = len(bibnums) + 1\n\n if \"doi\" in entry:\n return r'<a href=\"https://doi.org/{doi}\">{text}</a>'.format(\n doi=entry[\"doi\"], text=bibnums[cid]\n )\n elif \"url\" in entry:\n return r'<a href=\"{url}\">{text}</a>'.format(url=entry[\"url\"], text=bibnums[cid])\n elif \"link\" in entry:\n return r'<a href=\"{url}\">{text}</a>'.format(\n url=entry[\"link\"], text=bibnums[cid]\n )\n else:\n return bibnums[cid]\n # add_abbreviated_author(entry)\n # split_date(entry)\n # return DefaultFormatter().format(fallback_fmt, **entry)","def _get_book(s):\n\n s = s.strip()\n if s == '': raise SyntaxError('The book identification string is empty')\n \n author = ''\n author_start = 0\n author_found = False \n for match in author_regex.finditer(s):\n author_found = True\n author_start = match.start()\n author = match.group(1).strip()\n \n if author_found:\n title = s[:author_start].strip()\n else:\n title = s\n # Sometimes titles have a byte order mark prepended. The Kindle behavior\n # changed in 2011 to stop doing this to entries in My Clippings.txt. \n # Ensure the title is consistent, strip this character if it exists.\n BOM = '\\ufeff'\n if title.startswith(BOM):\n title = title[1:] \n \n return title,author","def make_citation_authors(res):\n if \"author\" in res.keys():\n first_author = res['author'][0]['family'] + \", \" + res['author'][0]['given']\n last_author = res['author'][-1]['given'] + \" \" + res['author'][-1]['family']\n middle_authors = \", \".join(\" \".join([x['given'], x['family']]) for x in res['author'][1:-1])\n #assemble authors\n author_string = first_author\n author_string = author_string + \", \" + middle_authors if middle_authors != '' else author_string\n author_string = author_string + \", and \" + last_author if len(res['author']) > 1 else author_string\n \n author_string = author_string + \".\" if author_string[-1] != \".\" else author_string\n else:\n author_string = \"Unknown Authors\"\n\n return clean_txt(author_string.capitalize())","def get_bibtex(self):\n url=\"http://www.biomedcentral.com/download/citation\"\n parameters={'citation':'on', \n 'result-selection':'THIS_PAGE',\n 'suplements': 'false',\n 'citationType':'BIBTEX_WITH_ABSTRACT',\n 'articleIdThisPage':self.article_ids\n }\n data=urllib.urlencode(parameters)\n self.bibtex=urllib2.urlopen(url,data)","def format_bib_entry(e: BibDocument):\n if e.bibtex is not None:\n b = e.bibtex\n s = fix_string(b.get('title', b.get('ID', '?'))) + '\\n'\n s += format_author(b.get('author', b.get('editor', '?'))) + ' ' + b.get('year', '')\n if len(e.filepaths) > 0:\n s += ' [PDF]'\n return s\n else:\n return e.relpath()","def bibtex(self) -> str:\n a = BibDatabase()\n a.entries = [self.bib]\n return bibtexparser.dumps(a)","def get_citation(self):\n etree = self.get_eml()\n try:\n citation_ipt = etree.find('./additionalMetadata/metadata/gbif/citation').text\n except AttributeError:\n citation_ipt = None\n if citation_ipt:\n now = datetime.datetime.now().date()\n pola3r = \"(Available: Polar 'Omics Links to Antarctic, Arctic and Alpine Research. Antarctic Biodiversity Portal. Scientific Committee for Antarctic Research. www.biodiversity.aq/pola3r. Accessed: {})\".format(\n now)\n citation = \"{} {}\".format(citation_ipt, pola3r)\n else:\n citation = None\n return citation","def authorSign(g = None):\n if not g:\n return\n authors = g.find(\"Author\")\n ret = dict()\n for author in authors:\n ret[author['name']] = author['citation'].replace('\\n','').lower()\n return ret","def collect_citation_metadata(\n metadata: dict, references: List[pybtex.database.Entry]\n) -> dict:\n # Author list\n citation_authors = []\n for author_tier in [\"Core\", \"Developers\", \"Contributors\"]:\n for author in metadata[\"Authors\"][author_tier][\"List\"]:\n family_names, given_names = author[\"Name\"].split(\", \")\n citation_author = {\n \"family-names\": family_names,\n \"given-names\": given_names,\n }\n if \"Orcid\" in author:\n citation_author[\"orcid\"] = (\n \"https://orcid.org/\" + author[\"Orcid\"]\n )\n if \"Affiliations\" in author and len(author[\"Affiliations\"]) > 0:\n citation_author[\"affiliation\"] = \" and \".join(\n author[\"Affiliations\"]\n )\n citation_authors.append(citation_author)\n # References in CITATION.cff format\n citation_references = [to_cff_reference(entry) for entry in references]\n return {\n \"cff-version\": \"1.2.0\",\n \"message\": (\n \"Please cite SpECTRE in any publications that make use of its code\"\n \" or data. Cite the latest version that you use in your\"\n \" publication. The citation for this version is listed below.\"\n ),\n \"title\": metadata[\"Name\"],\n \"url\": metadata[\"Homepage\"],\n \"repository-code\": \"https://github.com/\" + metadata[\"GitHub\"],\n \"version\": metadata[\"Version\"],\n \"date-released\": metadata[\"PublicationDate\"],\n \"doi\": metadata[\"Doi\"],\n \"authors\": citation_authors,\n \"keywords\": metadata[\"Keywords\"],\n \"license\": metadata[\"License\"],\n \"references\": citation_references,\n }","def info(entry: BibItem) -> str:\n return \"{title}{author}{date}\".format(\n title=(\n \"Title: {}\\n\".format(re.sub(r\"[}{]\", \"\", entry[\"title\"]))\n if \"title\" in entry\n else \"\"\n ),\n author=(\n \"Author{plural}: {author}\\n\".format(\n plural=\"s\" if len(entry[\"author\"]) > 1 else \"\",\n author=\"; \".join(entry[\"author\"]),\n )\n if \"author\" in entry\n else \"\"\n ),\n date=(\n \"Year: {}\\n\".format(entry[\"date\"].split(\n \"-\")[0]) if \"date\" in entry else \"\"\n ),\n )","def getBibTeX(bibref,tag_suf,outFile):\n if bibref == '1988iras....1.....B':\n bibtex = ['>@article{1988iras....1.....B,\\n',\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\n',\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\n',\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\n',\n ' year=1988,\\n',\n ' volume = {1},\\n', \n ' month = jan,\\n', \n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\n'\n '}\\n']\n else:\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\n suf = '/exportcitation'\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\n \n bibtex = []\n for l in range(0, len(lines)):\n if 'export-textarea ' in str(lines[l]):\n bibtex.append(str(lines[l]))\n t = l+1\n \n while '</textarea>' not in str(lines[t+1]):\n bibtex.append(str(lines[t])) \n t += 1\n \n for item in bibtex:\n if 'author' in item.split('=')[0]:\n auth = item.split('=')[1].split(',')[0]\n for i in string.punctuation:\n auth = auth.replace(i, '')\n auth = auth.replace(' ', '')\n if 'year' in item.split('=')[0]:\n yr = item.split('=')[1].split(',')[0]\n yr = yr.replace(' ', '')\n \n try:\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\n'\n except UnboundLocalError as ule:\n print(bibtex)\n print('')\n print(ule)\n sys.exit()\n \n with open(outFile, 'a') as o:\n for item in bibtex:\n item = item.replace('"', '\"')\n item = item.replace(''', \"'\")\n item = item.replace('&', \"&\")\n o.write(item)\n o.write('\\n')\n \n return auth+yr+tag_suf","def bibtex(self):\n return \"@comment{%(id)s: %(message)s}\" % \\\n {'id': self.id, 'message': self.message}","def test_example():\n bib_database = bibtexparser.parse_string(\n bibtex_string,\n append_middleware=[\n SeparateCoAuthors(allow_inplace_modification=True),\n SplitNameParts(allow_inplace_modification=True),\n ],\n )\n\n new_bibtex_string = bibtexparser.write_string(\n bib_database,\n prepend_middleware=[\n MergeNameParts(allow_inplace_modification=True),\n MergeCoAuthors(allow_inplace_modification=True),\n ],\n )\n\n # Note: As defaults change, this assertion may need to be updated.\n assert (\n new_bibtex_string.strip()\n == dedent(\n \"\"\"\n @article{Muller2020,\n \\ttitle = {Some Paper Title},\n \\tauthor = {John Muller and Jane Doe},\n \\tjournal = {Nature Reviews Materials},\n \\tyear = {2019}\n }\n \n \n @comment{This is a comment.}\n \n \n @preamble{e = mc^2}\"\"\"\n ).strip()\n )","def __generate_author_string__(self, list_of_authors):\n author_string = \"\"\n return author_string.join(list_of_authors)","def get_bibtex_from_citation_file(package_name):\n package = importlib.import_module(package_name)\n cff_file = os.path.join(package.__path__[0], 'CITATION.cff')\n citation_file = os.path.join(package.__path__[0], 'CITATION')\n if os.path.exists(cff_file):\n with open(cff_file) as f:\n cffstr = f.read()\n citation = Citation(cffstr=cffstr)\n bibtex = citation.as_bibtex()\n elif os.path.exists(citation_file):\n with open(citation_file) as f:\n citestr = f.read()\n match = re.search(cite_tag_pattr, citestr)\n if match is None:\n raise ValueError('Could not find any BibTeX entries in CITATION file')\n for i_end in range(match.end(), len(citestr)):\n bibtex = citestr[match.start():i_end]\n if bibtex.count('{') == bibtex.count('}'):\n break\n else:\n raise ValueError('Mismatched braces in BibTeX entry in CITATION file')\n else:\n bibtex = None\n return bibtex","def to_citation(self, type):\n return self.to_article().to_citation(type)","def build_bibtex_entry(metadata: dict):\n # We truncate the author list in the BibTeX entry after 'Developers',\n # because not all journals are happy with printing an excessively long\n # author list, e.g. Phys. Rev. wants at most 15 authors. By truncating the\n # author list here, the user who copies the BibTeX entry doesn't have to\n # make the decision where to truncate.\n authors = [\n pybtex.database.Person(author[\"Name\"])\n for author in (\n metadata[\"Authors\"][\"Core\"][\"List\"]\n + metadata[\"Authors\"][\"Developers\"][\"List\"]\n )\n ] + [pybtex.database.Person(\"others\")]\n entry = pybtex.database.Entry(\n \"software\",\n persons=dict(author=authors),\n fields=dict(\n title=(\n r\"\\texttt{\"\n + metadata[\"Name\"]\n + \" v\"\n + metadata[\"Version\"]\n + \"}\"\n ),\n # The 'version' field is not used by revtex4-2, so we also put the\n # version in the title\n version=metadata[\"Version\"],\n publisher=\"Zenodo\",\n doi=metadata[\"Doi\"],\n url=metadata[\"Homepage\"],\n howpublished=(\n r\"\\href{https://doi.org/\"\n + metadata[\"Doi\"]\n + \"}{\"\n + metadata[\"Doi\"]\n + \"}\"\n ),\n license=metadata[\"License\"],\n year=str(metadata[\"PublicationDate\"].year),\n month=str(metadata[\"PublicationDate\"].month),\n ),\n )\n entry.key = \"spectrecode\"\n return entry","def list_publications(bib_format=\"dict\"):\n\n def get_bibtex(key, value):\n total_keys = [\n \"title\",\n \"journal\",\n \"volume\",\n \"issue\",\n \"number\",\n \"pages\",\n \"numpages\",\n \"year\",\n \"month\",\n \"publisher\",\n \"url\",\n \"doi\",\n \"issn\",\n ]\n bibtex_str = (\n \"@article{\"\n + key\n + \",\\n\"\n + \" author={\"\n + \" and \".join(value[\"author\"])\n + \"},\\n\"\n )\n for key in total_keys:\n if key in value.keys():\n bibtex_str += \" \" + key + \"={\" + value[key] + \"},\\n\"\n bibtex_str += \"}\\n\"\n return bibtex_str\n\n def get_apa(value):\n apa_str = \" & \".join(value[\"author\"])\n if \"year\" in value.keys():\n apa_str += \" (\" + value[\"year\"] + \"). \"\n if \"title\" in value.keys():\n apa_str += value[\"title\"] + \". \"\n if \"journal\" in value.keys():\n apa_str += value[\"journal\"] + \", \"\n if \"volume\" in value.keys():\n apa_str += value[\"volume\"] + \", \"\n if \"pages\" in value.keys():\n apa_str += value[\"pages\"] + \". \"\n if \"doi\" in value.keys():\n apa_str += \"doi: \" + value[\"doi\"] + \"\\n\"\n return apa_str\n\n publication_dict = s.publication_lst\n if bib_format.lower() == \"dict\":\n return publication_dict\n elif bib_format.lower() == \"bibtex\":\n total_str = \"\"\n for pub in publication_dict:\n for key, value in pub.items():\n total_str += get_bibtex(key, value)\n return total_str\n elif bib_format.lower() == \"apa\":\n total_str = \"\"\n for pub in publication_dict:\n for key, value in pub.items():\n total_str += get_apa(value)\n return total_str\n else:\n raise ValueError(\"Supported Bibformats are ['dict', 'bibtex', 'apa']\")","def _cookIdCore(self, ref, **kwargs):\n\n # AUTHORS\n namepart='nobody'\n if self._refHasAuthorNames(ref):\n lastnames = []\n for each in ref['authors']:\n if each.get('lastname', None):\n lastnames.append(each['lastname'])\n\n if len(lastnames) > 1:\n namepart = '%s' % ''.join([ lastname[0] for lastname in lastnames ])\n elif len(lastnames) == 1:\n namepart = lastnames[0][:3]\n else:\n pass\n\n # PUBLICATION YEAR\n if ref.get('publication_year', None):\n yearpart = str(ref['publication_year'])\n else:\n yearpart = \"1000\"\n\n return namepart + yearpart","def generateCopyrightStr(config, firstYear):\n copyrightStr = \"\"\n thisYear = str(datetime.date.today().year)\n\n if not firstYear or firstYear == thisYear:\n copyrightStr = \"©\" + thisYear + \" \" + \\\n config['rssAuthor'] + \". All rights reserved.\"\n else:\n copyrightStr = \"©\" + firstYear + \"—\" + thisYear + \" \" + \\\n config['rssAuthor'] + \". All rights reserved.\"\n\n return unicode(copyrightStr, 'utf-8')","def portrayalCatalogueCitation(self) -> Sequence[Citation]:\n pass","def get_bibtex_entry(doi, bibtext_cache={}, shortdoi_cache={}):\r\n bibtext = get_bibtext(doi, cache = bibtext_cache)\r\n if not bibtext:\r\n return None\r\n\r\n short_doi = shorten(doi, cache = shortdoi_cache)\r\n parser = BibTexParser()\r\n parser.ignore_nonstandard_types = False\r\n bibdb = bibtexparser.loads(bibtext, parser)\r\n entry, = bibdb.entries\r\n quoted_doi = urllib.request.quote(doi)\r\n entry['link'] = 'https://doi.org/{}'.format(quoted_doi)\r\n if 'author' in entry:\r\n entry['author'] = ' and '.join(entry['author'].rstrip(';').split('; '))\r\n entry['ID'] = short_doi[3:]\r\n return entry","def parse_citations(s: str):\n print(\"parse_citations(%s)\" % s)\n if pandas.isnull(s) or not s:\n return []\n terms = [e.strip() for e in s.split(\";\")]\n print(\"parse_citations: \" + str(terms))\n out = []\n for term in terms:\n if term.startswith(\"PMID\"):\n out.append({\"db\": \"PubMed\", \"id\": term})\n else:\n raise RuntimeError(\"Unknown citation format: \" + term)\n return out","def getAuthor(self):\n return self.bookAuthor","def get_clean_bib(bib):\n d = PyQuery(bib)\n div = d(\"div.csl-right-inline\").html()\n\n # zotero keeps the html escaped in the return value\n div = parser.unescape(div)\n\n return hyperlink_string(div)","def make_citation_key(res):\n year = str(make_year(res))\n\n try:\n last_names = [x['family'] for x in res['author']]\n except KeyError as e:\n last_names = [\"Unknown\"]\n if len(last_names) >= 3:\n key = last_names[0].capitalize() + \"ETAL\" + year\n else:\n key = \"\".join(last_names) + year\n\n return clean_txt(key.replace(\" \", \"\"))","def author(self) -> str:\n return pulumi.get(self, \"author\")","def bibtex_to_dict(text):\n def _format_person(person):\n von_last = ' '.join(person._prelast + person._last)\n jr = ' '.join(person._lineage)\n first = ' '.join(person._first + person._middle)\n return ' '.join(part for part in (first, von_last, jr) if part)\n\n parser = pybtex.database.input.bibtex.Parser()\n bib_data = parser.parse_stream(StringIO(text))\n\n plain_style = pybtex.style.formatting.plain.Style()\n plain_render = pybtex.backends.plaintext.Backend()\n formatted_entry = next(plain_style.format_entries(bib_data.entries.values()))\n\n # It is possible to parse out multiple BibTeX entries\n # in one go! But, I'm assuming that the metadata\n # contains information about only one publication.\n\n citekey = bib_data.entries.keys()[0]\n entry = bib_data.entries[citekey]\n meta = {\n 'citekey': citekey,\n 'type': entry.type,\n 'authors': [_format_person(person)\n for person in entry.persons['author']],\n 'cite_info': entry.fields,\n 'cite_bibtex': text,\n 'cite_plain': formatted_entry.text.render(plain_render),\n }\n\n # Get important stuff from cite_info\n extract = ('title', 'abstract', 'pdf', 'url', 'year', 'keywords',\n 'poster', 'presentation')\n for key in extract:\n if key in entry.fields:\n meta[key] = meta['cite_info'].pop(key)\n\n # Add editors to cite_info, if they exist\n if 'editor' in entry.persons:\n meta['cite_info']['editors'] = \", \" .join(\n [_format_person(person) for person in entry.persons['editor']])\n\n return meta","def newBookCitation(self, **attrlinks):\n return BookCitation(self, **attrlinks)","def getCitationFromIssue(issue):\n try:\n if \"\\nCitation: \" in issue[\"body\"]:\n citation = issue[\"body\"].split(\"\\nCitation: \")[1].split(\" \")[0]\n else:\n afterDOI = issue[\"body\"].split(\"DOI:\")[1]\n citation = afterDOI.split(\" \")[0]\n if citation == \"\":\n citation = afterDOI.split(\" \")[1]\n if \"\\r\\n\" in citation:\n citation = citation.split(\"\\r\\n\")[0]\n if citation.startswith(\"@\"):\n citation = citation[1:]\n return citation\n\n except:\n print(\n \"the citation could not be automatically extracted from the following issue: \\n\",\n issue[\"title\"])\n return \"unknown\"","def to_string(self):\n if self.__is_valid:\n return \"Author:\\n\\tName: %s\\n\\t%s\\n\\tLangId: %s\\n\\tPartNumber: %s\" % (\n self.__name, self.__build.to_string(), self.__lang_id, self.__part_number)\n else:\n return \"No Author info\"","def author(self):\n\t\tauthor = re.search(r\"([Ff]rom\\s)(.+) ([tT]\\s*o)([^,]+),\",self.raw_text()[:150])\n\t\treport = re.search(r\".*[Rr]eport of ([^,]+),\",self.raw_text()[:150])\n\t\torder = re.search(r\".*[Oo]rder of ([^,]+)[,.]* to\",self.raw_text()[:250])\n\t\torder2 = re.search(r\".*[Oo]rder of ([^,]+),\",self.raw_text()[:250])\n\t\tlogbook = re.search(r\".*[lL]og of ([^,]+)[,.]\",self.raw_text()[:250])\n\t\tif order:\n\t\t\torder = order.group(1)\n\t\t\treturn order\n\t\tif order2:\n\t\t\torder2 = order2.group(1)\n\t\t\treturn order2\n\t\tif logbook:\n\t\t\tlogbook = logbook.group(1)\n\t\t\treturn logbook\n\t\tif report:\n\t\t\treport = report.group(1)\n\t\t\treturn report\n\t\tif author: \t\n\t\t\tauthor = author.group(2) \n\t\t\tauthor = re.sub(r\"([^,]*),.*\",r\"\\1\",author)\t \n\t\t\treturn author\n\t\t\n\t\treturn \"Unknown\"","def isbn_lookup(isbn):\n base = \"https://www.googleapis.com/books/v1/volumes?q=isbn=\"\n# Unfortunately we can't use the superior \"with spam as eggs\" syntax here...\n search = urlopen(base + isbn + \"&prettyprint=false\")\n lines = search.read()\n search.close()\n for bool_pair in [(\"false\", \"False\"), (\"true\", \"True\")]:\n lines = lines.replace(*bool_pair)\n volume_info = literal_eval(lines)[\"items\"][0][\"volumeInfo\"]\n title = volume_info[\"title\"]\n authors = ', '.join(a for a in volume_info[\"authors\"])\n return \"Title:\\t\\t%s\\nAuthor(s):\\t%s\" % (title, authors)","def get_bibtex(package_name):\n full_path = os.path.join(_bib_path, '{0}.bib'.format(package_name.lower()))\n if not os.path.exists(full_path):\n raise ValueError('Bibtex not found for {0}! If you know it has a '\n 'citation, please consider adding it via pull request '\n ' to: https://github.com/adrn/makecite')\n\n with open(full_path, 'r') as f:\n bibtex = f.read()\n\n return bibtex","def getAuthors(self): #$NON-NLS-1$\r","def copyrightRecord(inputstring):\n \n return inputstring[19:24]","def author(name):\n print(\"Author:\", name)","def cite(self, arg=None):\n nums = self.selector.select_by_index(arg)\n if nums is None or not nums:\n self.visual.error(\"Need a selection to cite.\")\n return\n citation_id = \", \".join([self.reference_entry_id_list[n] for n in nums])\n citation = \"\\\\cite{{{}}}\".format(citation_id)\n # clipboard.copy(citation_id)\n clipboard.copy(citation)\n self.visual.message(\"Copied to clipboard: {}\".format(citation))","def getDOIFromCitation(citation):\n try:\n if \".org/\" in citation:\n DOI = citation.split(\".org/\")[1]\n elif citationContainsDOI(citation):\n DOI = citation.split(\"doi:\")[1]\n DOI = DOI.replace(\"]\", \"\")\n elif citation == \"unknown\":\n DOI = \"unknown\"\n else:\n DOI = citation\n # DOIs are case insensitive but lower-case seems to be preferred and is what's used by manubot\n DOI = DOI.lower()\n return DOI\n except:\n return \"unknown\"","def authors_string(self):\n all_authors = Author.objects.filter(book=self).order_by('last_name')\n return u', '.join([unicode(a) for a in all_authors])","def parse_bib_from_bibtex(filename):\n\tentry_regex = r'''\n\t\t\t(?msx) # flags: multi-line, dot-match-all, verbose\n\t\t\t^@\\w+\\{ # start of line, item type\n\t\t\t.*? # content, can span multiple lines, non-greedy\n\t\t\t^\\} # start of line, closing parens\n\t\t\t'''\n\tattr_regex = r'''\n\t\t\t(?ix) # flags: ignore-case, verbose\n\t\t\t\\s* # leading space\n\t\t\t%s # what to match: author, title, or year\n\t\t\t\\s*=\\s* # space and equals\n\t\t\t[{\\\"'] # opening parens\n\t\t\t(.*) # the actual author, title, or year\n\t\t\t[}\\\"'] # closing parens or quote\n\t\t\t\\,? # optional comma\n\t\t\t'''\n\tparse_func = make_parse_func(attr_regex % \"author\", attr_regex % \"title\", \n\t attr_regex % \"year\", \" and \")\n\treturn parse_bib(filename, entry_regex, parse_func)","def refine_copyright(c):\n c = strip_some_punct(c)\n c = fix_trailing_space_dot(c)\n c = strip_all_unbalanced_parens(c)\n # FIXME: this should be in the grammar, but is hard to get there right\n # these are often artifacts of markup\n c = c.replace('Copyright Copyright', 'Copyright')\n c = c.replace('Copyright copyright', 'Copyright')\n c = c.replace('copyright copyright', 'Copyright')\n c = c.replace('copyright Copyright', 'Copyright')\n c = c.replace('copyright\\'Copyright', 'Copyright')\n c = c.replace('copyright\"Copyright', 'Copyright')\n c = c.replace('copyright\\' Copyright', 'Copyright')\n c = c.replace('copyright\" Copyright', 'Copyright')\n s = c.split()\n\n # fix traliing garbage, captured by the grammar\n last_word = s[-1]\n if last_word.lower() in ('parts', 'any', '0', '1'):\n s = s[:-1]\n # this is hard to catch otherwise, unless we split the author\n # vs copyright grammar in two. Note that AUTHOR and Authors should be kept\n last_word = s[-1]\n if last_word.lower() == 'author' and last_word not in ('AUTHOR', 'AUTHORS', 'Authors',) :\n s = s[:-1]\n\n s = u' '.join(s)\n return s.strip()","def citationContainsDOI(citation):\n if citation.startswith(\"doi:\"):\n return True\n elif citation.startswith(\"@doi:\"):\n return True\n elif citation.startswith(\"[@doi\"):\n return True\n else:\n return False","def test_review_citation_wrt_canonical_uri(self):\n\n self.review_mono.doi = None\n self.issue_mono.setDoiRegistrationActive(False)\n self.review_jour.doi = None\n self.issue_jour.setDoiRegistrationActive(False)\n\n monograph_citation = self.review_mono.get_citation_string()\n self.assertEquals('<a href=\"http://nohost/plone' in monograph_citation, True)\n\n journal_citation = self.review_jour.get_citation_string()\n self.assertEquals('<a href=\"http://nohost/plone' in journal_citation, True)\n\n self.review_mono.canonical_uri = \"http://example.com\"\n monograph_citation = self.review_mono.get_citation_string()\n self.assertEquals('<a href=\"http://nohost/plone' in monograph_citation, False)\n\n self.review_jour.canonical_uri = \"http://example.com\"\n journal_citation = self.review_jour.get_citation_string()\n self.assertEquals('<a href=\"http://nohost/plone' in journal_citation, False)","def __str__(self):\n return '%s, %s: %s' % (self.first_author, self.year, self.title)","def __convert_authors(self, author_dict: dict) -> str:\n if \"author\" not in author_dict.keys():\n return str(author_dict)\n res = \"\"\n for i, _ in enumerate(author_dict['author']):\n if \"given-name\" in author_dict[\"author\"][i].keys() and \"surname\" in author_dict[\"author\"][i].keys():\n res += author_dict['author'][i][\"given-name\"] + \" \" + author_dict['author'][i][\"surname\"] + \", \"\n else:\n res += str(author_dict['author'][i])\n return res","def fill(self):\n if self.source == 'citations':\n url = self._scholarly.URLS(\"CITATIONPUB\").format(self.id_citations)\n soup = self._scholarly._get_soup(\n self._scholarly.URLS('HOST').format(url))\n self.bib['title'] = soup.find('div', id='gsc_vcd_title').text\n\n if soup.find('a', class_='gsc_vcd_title_link'):\n self.bib['url'] = soup.find(\n 'a', class_='gsc_vcd_title_link')['href']\n\n for item in soup.find_all('div', class_='gs_scl'):\n key = item.find(class_='gsc_vcd_field').text\n val = item.find(class_='gsc_vcd_value')\n if key == 'Authors':\n self.bib['author'] = ' and '.join(self.get_authorlist(val))\n elif key == 'Journal':\n self.bib['journal'] = val.text\n elif key == 'Volume':\n self.bib['volume'] = val.text\n elif key == 'Issue':\n self.bib['number'] = val.text\n elif key == 'Pages':\n self.bib['pages'] = val.text\n elif key == 'Publisher':\n self.bib['publisher'] = val.text\n elif key == 'Publication date':\n self.bib['year'] = arrow.get(val.text).year\n elif key == 'Description':\n if val.text[0:8].lower() == 'abstract':\n val = val.text[9:].strip()\n self.bib['abstract'] = val\n elif key == 'Total citations':\n self.id_scholarcitedby = re.findall(\n self._scholarly.URLS('SCHOLARPUBRE'), val.a['href'])[0]\n\n # number of citation per year\n years = [int(y.text) for y in soup.find_all(class_='gsc_vcd_g_t')]\n cites = [int(c.text) for c in soup.find_all(class_='gsc_vcd_g_al')]\n self.cites_per_year = dict(zip(years, cites))\n\n if soup.find('div', class_='gsc_vcd_title_ggi'):\n self.bib['eprint'] = soup.find(\n 'div', class_='gsc_vcd_title_ggi').a['href']\n self._filled = True\n\n elif self.source == 'scholar':\n self.bib['add_to_lib'] = self.url_add_sclib\n\n try:\n bibtex = self._scholarly._get_soup(self.url_scholarbib)\n bibtex = bibtex.find('pre').string\n self.bib.update(bibtexparser.loads(bibtex).entries[0])\n self.bib['author_count'] = str(\n len(self.bib['author'].split('and')))\n self.bib['age'] = str(\n int(date.today().year) - int(self.bib['year']))\n except:\n # did not find year\n pass\n\n self._filled = True\n return self","def get_bibtex_from_package(package_name, update_local=False):\n try:\n package = importlib.import_module(package_name)\n for attr in ['__bibtex__', '__citation__']:\n citation_info = getattr(package, attr, None)\n if citation_info:\n break\n except ImportError:\n warnings.warn(f\"{package_name} is not installed, cannot look for \"\n \"package provided BibTeX.\")\n return None\n\n if citation_info and update_local:\n path = os.path.join(_bib_path, '{0}.bib'.format(package_name))\n with open(path, 'w') as f:\n f.write(citation_info)\n\n return citation_info","def test_tax_court_citation_extractor(self):\n\n test_pairs = (\n (\n \"\"\" 1 UNITED STATES TAX COURT REPORT (2018)\n\n\n\n UNITED STATES TAX COURT\n\n\n\n BENTLEY COURT II LIMITED PARTNERSHIP, B.F. BENTLEY, INC., TAX\n MATTERS PARTNER, Petitioner v.\n COMMISSIONER OF INTERNAL REVENUE, Respondent\n\n\n\n Docket No. 5393-04. Filed May 31, 2006.\n\n\n\n Nancy Ortmeyer Kuhn, for petitioner.\n \"\"\",\n \"1 T.C. 2018\",\n ),\n (\n \"\"\" T.C. Memo. 2003-150\n\n\n\n UNITED STATES TAX COURT\n\n\n\n RIVER CITY RANCHES #1 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n RIVER CITY RANCHES #2 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n RIVER CITY RANCHES #3 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n\n\n \"\"\",\n \"2003 T.C. Memo. 150\",\n ),\n (\n \"\"\" T.C. Summary Opinion 2003-150\n\n\n\n UNITED STATES TAX COURT\n\n\n\n RIVER CITY RANCHES #1 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n RIVER CITY RANCHES #2 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n RIVER CITY RANCHES #3 LTD., LEON SHEPARD,\n TAX MATTERS PARTNER,\n\n\n \"\"\",\n \"2003 T.C. Summary Opinion 150\",\n ),\n (\n \"\"\"\n MICHAEL KEITH SHENK, PETITIONER v. COMMISSIONER\n OF INTERNAL REVENUE, RESPONDENT\n\n Docket No. 5706–12. Filed May 6, 2013.\n\n P was divorced from his wife, and their 2003 ‘‘Judgment of\n Absolute Divorce’’ provided that his ex-wife would have pri-\n mary residential custody of their three minor children. The\n judgment provided that the dependency exemption deductions\n for the three children would be divided between the two ex-\n spouses according to various conditions but did not provide\n that the ex-wife must execute in P’s favor a Form 8332,\n ‘‘Release of Claim to Exemption for Child of Divorced or Sepa-\n rated Parents’’. The children resided with P’s ex-wife for more\n than half of 2009, and P’s ex-wife did not execute in P’s favor\n any Form 8332 or equivalent document for any year. For 2009\n P timely filed a Federal income tax return on which he\n claimed dependency exemption deductions and the child tax\n credit for two of the children, consistent with his under-\n standing of the terms of the judgment, but he did not attach\n any Form 8332 to his return. He also claimed head-of-house-\n hold filing status. His ex-wife, the custodial parent, timely\n filed a Federal income tax return for 2009 on which she also\n\n 200\n\n\n\n\nVerDate Nov 24 2008 10:59 Jul 11, 2014 Jkt 372897 PO 20012 Frm 00001 Fmt 3857 Sfmt 3857 V:\\FILES\\BOUND VOL. WITHOUT CROP MARKS\\B.V.140\\SHENK JAMIE\n\f (200) SHENK v. COMMISSIONER 201\n\n\n claimed two dependency exemption deductions, so that one\n child was claimed on both parents’ returns. R allowed to P the\n dependency exemption deduction for one of the children but\n disallowed his claim for the dependency exemption deduction\n for the child who had also been claimed by the custodial\n parent. At trial P contended he is entitled to a dependency\n exemption deduction for all three children. Held: Since the\n custodial parent did not execute, and P could not and did not\n attach to his return, any Form 8332 or equivalent release, P\n is not entitled under I.R.C. sec. 152(e)(2)(A) to claim the\n dependency exemption deduction or the child tax credit. Held,\n further, where both the custodial parent and the noncustodial\n parent have claimed for the same year a dependency exemp-\n tion deduction for the same child, a declaration signed by the\n custodial parent after the period of limitations for assess-\n ments has expired as to the custodial parent could not qualify\n under I.R.C. sec. 152(e)(2)(A), and therefore there is no reason\n to grant P’s request to leave the record open so that he may\n obtain and proffer such a declaration. Held, further, P is not\n entitled to head-of-household filing status under I.R.C. sec.\n 2(b)(1) nor to the child tax credit under I.R.C. sec. 24.\n\n Michael Keith Shenk, for himself.\n Shari Salu, for respondent.\n GUSTAFSON, Judge: The Internal Revenue Service (IRS)\n determined a deficiency of $3,136 in the 2009 Federal income\n tax of petitioner Michael Keith Shenk. Mr. Shenk petitioned\n this Court, pursuant to section 6213(a), 1 for redetermination\n of the deficiency. After Mr. Shenk’s concession that he\n received but did not report $254 in dividend income, the\n issue for decision is whether Mr. Shenk is entitled to a\n dependency exemption deduction for one of his children\n under section 151(c), a child tax credit for that child under\n section 24(a), and head-of-household filing status under sec-\n tion 2(b)(1). On these issues, we hold for the IRS.\n FINDINGS OF FACT\n\n The judgment of divorce\n Mr. Shenk was married to Julie Phillips, and they have\n three minor children—M.S., W.S., and L.S. They divorced in\n 2003. The family court’s ‘‘Judgment of Absolute Divorce’’ pro-\n 1 Unless otherwise indicated, all citations of sections refer to the Internal\n\n Revenue Code (26 U.S.C.) in effect for the tax year at issue, and all cita-\n tions of Rules refer to the Tax Court Rules of Practice and Procedure.\n\n\n\n\nVerDate Nov 24 2008 10:59 Jul 11, 2014 Jkt 372897 PO 20012 Frm 00002 Fmt 3857 Sfmt 3857 V:\\FILES\\BOUND VOL. WITHOUT CROP MARKS\\B.V.140\\SHENK JAMIE\n\f 202 140 UNITED STATES TAX COURT REPORTS (200)\n\n\n vided: that Ms. Phillips was ‘‘awarded primary residential\n custody’’ of the parties’ three children; and that Mr. Shenk\n would be liable for child support payments; but that, as to\n dependency exemptions—\"\"\",\n \"140 T.C. 200\",\n ),\n )\n site = tax.Site()\n for q, a in test_pairs:\n results = site.extract_from_text(q)\n cite_string = \"%s %s %s\" % (\n results[\"Citation\"][\"volume\"],\n results[\"Citation\"][\"reporter\"],\n results[\"Citation\"][\"page\"],\n )\n\n self.assertEqual(cite_string, a)\n print \"✓\", cite_string","def author(self) -> pulumi.Output[Optional[str]]:\n return pulumi.get(self, \"author\")","def __init__(self, authorReference, authorString, text, time):\n self.authorReference = authorReference\n self.authorString = authorString\n self.text = text\n self.time = time","def pubmed_citation(args=sys.argv[1:], out=sys.stdout):\n\n parser = argparse.ArgumentParser(\n description='Get a citation using a PubMed ID or PubMed URL')\n parser.add_argument('query', help='PubMed ID or PubMed URL')\n parser.add_argument(\n '-m', '--mini', action='store_true', help='get mini citation')\n parser.add_argument(\n '-e', '--email', action='store', help='set user email', default='')\n\n args = parser.parse_args(args=args)\n\n lookup = PubMedLookup(args.query, args.email)\n publication = Publication(lookup, resolve_doi=False)\n\n if args.mini:\n out.write(publication.cite_mini() + '\\n')\n else:\n out.write(publication.cite() + '\\n')","def __str__(self):\n\n return super().__str__() + f'Author: {self.author}\\n'","def book_urn(author='%', title=\"%\", ddk=\"%\", subject=\"\", period=(1100, 2020), gender=\"\", limit=20 ):\n return get_urn({\n \"author\": author,\n \"title\":title,\n \"ddk\":ddk,\n \"subject\":subject,\n \"year\":period[0],\n 'next':period[1] - period[0],\n \"limit\":limit\n })","def newJournalCitation(self, **attrlinks):\n return JournalCitation(self, **attrlinks)","def author_name(text):\n tag = text.split()\n\n \"\"\"\n We take the beginning of the text since the\n author name will likely be there\n \"\"\"\n\n tag = tag[:100]\n author = []\n\n current_tag = 0\n \"\"\"\n We go through each word until we find the first instance\n of the word 'by' or 'author', which should mean the author\n will be written right after that.\n We save the first word after 'by' or 'author' since it should\n be the authors first name\n \"\"\"\n\n for word in tag:\n if (word.lower() == ('by') or\n word.lower() == ('author') or\n word.lower() == ('author:')):\n\n author.append(tag[current_tag+1].decode(encoding='UTF8',\n errors='ignore'))\n current_tag += 1\n tag = tag[current_tag+1:]\n break\n current_tag += 1\n\n \"\"\"\n We go through each word after the first name of the author\n until we find a word that is not capitalized. We assume that\n it marks the end of the author name.\n We then return a list of the author's name split up.\n \"\"\"\n current_tag = 0\n for word in tag:\n if tag[current_tag].lower() == 'this':\n break\n if tag[current_tag].istitle():\n author.append(tag[current_tag].decode(encoding='UTF8',\n errors='ignore'))\n current_tag += 1\n\n return author","def cv_list(self):\n\n mystr = \"\"\n for p in self.mypapers:\n mystr += f\"{p.title[0]}\\n\"\n if len(p.author) > 12:\n a = f\"{p.author[0]} et al. \"\n elif len(p.author) > 2:\n a = \", \".join(p.author[:-1]) + f\" & {p.author[-1]} \"\n elif len(p.author) == 2:\n a = f\"{p.author[0]} & {p.author[1]} \"\n else:\n a = f\"{p.author[0]} \"\n\n mystr += f\"{a}\"\n mystr += f\"{p.year}, {p.pub}\"\n if p.volume is not None:\n mystr += f\", {p.volume}\"\n if p.issue is not None:\n mystr += f\", {p.issue}\"\n if p.page is not None:\n mystr += f\", {p.page[0]}\"\n mystr += \"\\n\\n\"\n return mystr","def test_citations_and_toc(self):\n settings = get_settings(\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\"+citations\"],\n PANDOC_ARGS=PANDOC_ARGS\n + [\n \"--toc\",\n \"-C\",\n \"--csl=https://www.zotero.org/styles/ieee-with-url\",\n \"--metadata=link-citations:false\",\n \"--metadata=reference-section-title:References\",\n ],\n FORMATTED_FIELDS=FORMATTED_FIELDS,\n )\n\n pandoc_reader = PandocReader(settings)\n source_path = os.path.join(\n TEST_CONTENT_PATH, \"valid_content_with_citation.md\"\n )\n output, metadata = pandoc_reader.read(source_path)\n self.maxDiff = None\n\n self.assertEqual(\n (\n '<h2 id=\"string-theory\">String Theory</h2>\\n'\n \"<p>But this foundational principle of science has\"\n \" now been called into question by\"\n ' <a href=\"https://www.britannica.com/science/'\n 'string-theory\">String Theory</a>,'\n \" which is a relative newcomer to theoretical physics, but one\"\n \" that has captured the common imagination, judging by\"\n \" the popular explanations that abound on the Web\"\n ' <span class=\"citation\" data-cites=\"mann2019 wood2019'\n ' jones2020\">[1]–[3]</span>.'\n \" And whether string theory is or is not science, Popper\"\n \" notwithstanding, is an issue that is still up for debate\"\n \" <span\"\n ' class=\"citation\" data-cites=\"siegel2015 castelvecchi2016'\n ' alves2017 francis2019\">[4]–[7]</span>.</p>\\n'\n '<h1 class=\"unnumbered\" id=\"bibliography\">References</h1>\\n'\n '<div id=\"refs\" class=\"references csl-bib-body\"'\n ' role=\"doc-bibliography\">\\n'\n '<div id=\"ref-mann2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[1]'\n ' </div><div class=\"csl-right-inline\">A. Mann,'\n \" <span>“<span>What Is String Theory?</span>”</span>\"\n \" 20-Mar-2019. [Online].\"\n ' Available: <a href=\"https://www.livescience.com/'\n '65033-what-is-string-theory.html\">'\n \"https://www.livescience.com/\"\n \"65033-what-is-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-wood2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[2] </div>'\n '<div class=\"csl-right-inline\">'\n \"C. Wood, <span>“<span>What Is String Theory?</span>.\"\n \" Reference article:\"\n \" A simplified explanation and brief history of string\"\n \" theory,”</span> 11-Jul-2019.\"\n ' [Online]. Available: <a href=\"https://www.space.com/'\n '17594-string-theory.html\">'\n \"https://www.space.com/17594-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-jones2020\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[3]'\n ' </div><div class=\"csl-right-inline\">'\n 'A. Z. Jones, <span>“<span class=\"nocase\">The Basics of String'\n \" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\"\n ' <a href=\"https://www.thoughtco.com/'\n 'what-is-string-theory-2699363\">'\n \"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-siegel2015\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[4]'\n ' </div><div class=\"csl-right-inline\">'\n \"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\"\n \" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\"\n \" <a\"\n ' href=\"https://www.forbes.com/sites/'\n \"startswithabang/2015/12/23/\"\n 'why-string-theory-is-not-science/\">https://www.forbes.com/'\n \"sites/startswithabang/2015/12/23/\"\n \"why-string-theory-is-not-science/</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-castelvecchi2016\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[5]'\n ' </div><div class=\"csl-right-inline\">'\n 'D. Castelvecchi, <span>“<span class=\"nocase\">'\n \"Feuding physicists turn\"\n \" to philosophy for help</span>. String theory is at the\"\n \" heart of a debate over the integrity of the scientific\"\n \" method itself,”</span> 05-Jan-2016. [Online]. Available:\"\n ' <a href=\"https://www.nature.com/news/'\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\">'\n \"https://www.nature.com/news/\"\n \"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-alves2017\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[6] </div>'\n '<div class=\"csl-right-inline\">'\n 'R. A. Batista and J. Primack, <span>“<span class=\"nocase\">'\n \"Is String theory falsifiable?</span>. Can a theory that isn’t\"\n \" completely testable still be useful to physics?”</span>\"\n \" [Online].\"\n ' Available: <a href=\"https://metafact.io/factchecks/'\n '30-is-string-theory-falsifiable\">'\n \"https://metafact.io/factchecks/\"\n \"30-is-string-theory-falsifiable</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-francis2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[7]'\n ' </div><div class=\"csl-right-inline\">'\n 'M. R. Francis, <span>“<span class=\"nocase\">Falsifiability and'\n \" physics</span>. Can a theory that isn’t completely testable\"\n \" still be useful to physics?”</span> 23-Apr-2019.\"\n \" [Online]. Available:\"\n ' <a href=\"https://www.scientificamerican.com/'\n 'article/is-string-theory-science/\">'\n \"https://www.scientificamerican.com/article/is-\"\n \"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n \"</div>\\n\"\n ),\n output,\n )\n\n self.assertEqual(\"Valid Content With Citation\", str(metadata[\"title\"]))\n self.assertEqual(\"My Author\", str(metadata[\"author\"]))\n self.assertEqual(\"2020-10-16 00:00:00\", str(metadata[\"date\"]))\n self.assertEqual(\n (\n '<nav class=\"toc\" role=\"doc-toc\">\\n'\n \"<ul>\\n\"\n '<li><a href=\"#string-theory\">String Theory</a></li>\\n'\n '<li><a href=\"#bibliography\">References</a></li>\\n'\n \"</ul>\\n</nav>\\n\"\n ),\n str(metadata[\"toc\"]),\n )\n self.assertEqual(\n (\n \"<p>But this foundational principle of science has now been\"\n \" called into question by\"\n ' <a href=\"https://www.britannica.com/science/string-theory\">'\n \"String Theory</a>.</p>\\n\"\n ),\n str(metadata[\"summary\"]),\n )","def get_short_name(self):\n split = self.name.split(' - ')\n # author, year, and first couple of words of paper title\n return \"{} ({}), {}\".format(split[0], split[1], \" \".join(split[2].split(' ')[:3]))","def format_one_author(author, style):\n # Check If there's no given name.\n # We should probably try to handle the no family name case, but\n # I'm not sure when we will actually come across an example...\n if \"given\" not in author or author[\"given\"] == []:\n return author[\"family\"]\n # Otherwise...\n family_name = author[\"family\"]\n given_names = author[\"given\"]\n\n # deal with a pathological case, 10.1016/j.jmr.2018.02.009\n ns = given_names.split()\n for i, name in enumerate(ns):\n if i >= 1 and name.startswith('-'):\n this_name = ns.pop(i)\n ns[i - 1] += this_name\n given_names = \" \".join(ns)\n\n if style == \"display\":\n return (\"\".join(n[0] for n in re.split(r\"[\\s-]\", given_names))\n + \" \" + family_name)\n elif style == \"acs\":\n # \"Jean-Baptiste Simon\" -> [[\"Jean\", \"Baptiste\"], [\"Simon\"]]\n split_both = [name.split('-') for name in given_names.split()]\n # [[\"Jean\", \"Baptiste\"], [\"Simon\"]] -> \"J.-B. S\"\n joined_both = \". \".join([\".-\".join(n[0] for n in names)][0]\n for names in split_both)\n return (family_name + \", \" + joined_both + \".\")\n elif style == \"bib\":\n s = family_name + \", \" + given_names\n return s.replace(\". \", \".\\\\ \") # Must use control spaces\n elif style == \"full\":\n return given_names + \" \" + family_name\n # Otherwise, grumble.\n else:\n raise ValueError(f\"Invalid value '{style}' for style.\")","def newThesisCitation(self, **attrlinks):\n return ThesisCitation(self, **attrlinks)","def make_author_list(res):\n try:\n r = [\", \".join([clean_txt(x['family']).capitalize(), clean_txt(x['given']).capitalize()]) for x in res['author']]\n except KeyError as e:\n print(\"No 'author' key, using 'Unknown Author'. You should edit the markdown file to change the name and citationkey.\")\n r = [\"Unknown Authors\"]\n return r","def __str__(self):\n\t\treturn f'{self.body} - quote of {self.author}'","def scrape_author(self, author_name, min_len=0, max_len=9999):\n search = sc.search_author(author_name)\n author = next(search)\n sc.fill(author, sections=['publications'])\n print(author.keys())\n with open(\n 'loadings\\\\authors_papers\\\\{}.txt'.format(author_name),\n 'w',\n encoding='utf-8'\n ) as file:\n for counter, pubblication in enumerate(author['publications']):\n\n if len(pubblication['bib']['title']) < min_len \\\n or len(pubblication['bib']['title']) > max_len:\n continue\n file.write(pubblication['bib']['title'])\n file.write('\\n')\n counter += 1\n if counter > self.hard_limit:\n break","def fixAuthor(self, pageText):\n informationRegex = re.compile(\n r'\\|Author=Original uploader was '\n r'(?P<author>\\[\\[:\\w+:\\w+:\\w+\\|\\w+\\]\\] at \\[.+\\])')\n selfRegex = re.compile(\n r'{{self\\|author='\n r'(?P<author>\\[\\[:\\w+:\\w+:\\w+\\|\\w+\\]\\] at \\[.+\\])\\|')\n\n # Find the |Author=Original uploader was ....\n informationMatch = informationRegex.search(pageText)\n\n # Find the {{self|author=\n selfMatch = selfRegex.search(pageText)\n\n # Check if both are found and are equal\n if (informationMatch and selfMatch):\n if informationMatch.group('author') == selfMatch.group('author'):\n # Replace |Author=Original uploader was ... with |Author= ...\n pageText = informationRegex.sub(r'|Author=\\g<author>',\n pageText)\n return pageText","def internal_citations(text, initial_label=None,\n require_marker=False, title=None):\n if not initial_label:\n initial_label = Label()\n citations = []\n\n def multiple_citations(matches, comment):\n \"\"\"i.e. head :: tail\"\"\"\n for match, start, end in matches:\n label = initial_label\n for submatch in chain([match.head], match.tail):\n cit = ParagraphCitation(\n submatch.pos[0], submatch.pos[1],\n match_to_label(submatch.tokens, label, comment=comment),\n full_start=start,\n full_end=end,\n in_clause=True)\n label = cit.label # update the label to keep context\n citations.append(cit)\n\n def single_citations(matches, comment):\n for match, start, end in matches:\n full_start = start\n if match.marker is not '':\n # Remove the marker from the beginning of the string\n start = match.marker.pos[1]\n citations.append(ParagraphCitation(\n start, end, match_to_label(match, initial_label,\n comment=comment),\n full_start=full_start))\n\n single_citations(grammar.marker_comment.scanString(text), True)\n\n multiple_citations(grammar.multiple_non_comments.scanString(text), False)\n multiple_citations(grammar.multiple_appendix_section.scanString(text),\n False)\n multiple_citations(grammar.multiple_comments.scanString(text), True)\n multiple_citations(grammar.multiple_appendices.scanString(text), False)\n multiple_citations(grammar.multiple_period_sections.scanString(text),\n False)\n\n single_citations(grammar.marker_appendix.scanString(text), False)\n single_citations(grammar.appendix_with_section.scanString(text), False)\n single_citations(grammar.marker_paragraph.scanString(text), False)\n single_citations(grammar.mps_paragraph.scanString(text), False)\n single_citations(grammar.m_section_paragraph.scanString(text), False)\n if not require_marker:\n single_citations(grammar.section_paragraph.scanString(text), False)\n single_citations(grammar.part_section_paragraph.scanString(text),\n False)\n multiple_citations(\n grammar.multiple_section_paragraphs.scanString(text), False)\n\n # Some appendix citations are... complex\n for match, start, end in grammar.appendix_with_part.scanString(text):\n full_start = start\n if match.marker is not '':\n start = match.marker.pos[1]\n label = filter(lambda l: l != '.', list(match)[3:])\n label = dict(zip(['p1', 'p2', 'p3'], label))\n citations.append(ParagraphCitation(\n start, end, initial_label.copy(\n appendix=match.appendix, appendix_section=match.a1,\n **label), full_start=full_start))\n\n # Internal citations can sometimes be in the form XX CFR YY.ZZ\n for match, start, end in grammar.internal_cfr_p.scanString(text):\n # Check if this is a reference to the CFR title and part we are parsing\n if match.cfr_title == title and match[1] == initial_label.to_list()[0]:\n full_start = start\n if match.marker is not '':\n # Remove the marker from the beginning of the string\n start = match.marker.pos[1]\n citations.append(ParagraphCitation(\n start, end, match_to_label(match, initial_label),\n full_start=full_start))\n else:\n continue\n\n # And sometimes there are several of them\n for match, start, end in grammar.multiple_cfr_p.scanString(text):\n label = initial_label\n if match.head.cfr_title == title:\n for submatch in chain([match.head], match.tail):\n if submatch.part == initial_label.to_list()[0]:\n cit = ParagraphCitation(\n submatch.pos[0], submatch.pos[1],\n match_to_label(submatch.tokens, label),\n full_start=start,\n full_end=end,\n in_clause=True)\n label = cit.label # update the label to keep context\n citations.append(cit)\n else:\n continue\n\n # Remove any sub-citations\n final_citations = []\n for cit in citations:\n if not any(cit in other for other in citations):\n final_citations.append(cit)\n\n return final_citations","def _parse_mercurial_author(data, id_gen):\n angled = ur'(?P<author>.+?) <(?P<email>.+?)>'\n paren = ur'(?P<email>.+?) \\((?P<author>.+?)\\)'\n simple = ur'(?P<author>[^,]+)'\n author_list = []\n for regex in (angled, paren, simple):\n # Watch out for commas separating multiple names.\n regex += u'(,\\s*)?'\n for match in re.finditer(regex, data):\n # Watch out for suffixes like 'Jr.' when they are comma-separated\n # from the name and thus cause issues when *all* names are only\n # separated by commas.\n match_dict = match.groupdict()\n author = match_dict['author']\n if not author.partition(' ')[1] and author.endswith('.'):\n prev_author = author_list.pop()\n author = ', '.join([prev_author, author])\n if u'email' not in match_dict:\n email = ''\n else:\n email = match_dict['email']\n author_list.append((author, email))\n else:\n # If authors were found then stop searching as only expect one\n # style of author citation.\n if author_list:\n break\n author = Author(author_list[0])\n user = author.first_last\n email = author.email\n uid = id_gen[user]\n return (uid, user, email)","def author(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"author\")","def to_cff_reference(bib_entry: pybtex.database.Entry) -> dict:\n\n def _cff_transform(cff_field, bib_value):\n if cff_field == \"type\":\n if bib_value == \"inproceedings\":\n return \"article\"\n elif bib_value == \"incollection\":\n return \"article\"\n elif cff_field == \"publisher\":\n return {\"name\": bib_value}\n elif cff_field == \"month\":\n try:\n return int(bib_value)\n except ValueError:\n return {\n \"jan\": 1,\n \"feb\": 2,\n \"mar\": 3,\n \"apr\": 4,\n \"may\": 5,\n \"jun\": 6,\n \"jul\": 7,\n \"aug\": 8,\n \"sep\": 9,\n \"oct\": 10,\n \"nov\": 11,\n \"dec\": 12,\n }[bib_value[:3].lower()]\n return bib_value\n\n cff_reference = {\n \"type\": _cff_transform(cff_field=\"type\", bib_value=bib_entry.type),\n \"authors\": [\n to_cff_person(person) for person in bib_entry.persons[\"author\"]\n ],\n }\n # Map BibTeX to CFF fields. This is just a subset of the most relevant\n # fields.\n fields = {\n \"doi\": \"doi\",\n \"edition\": \"edition\",\n \"isbn\": \"isbn\",\n \"license\": \"license\",\n \"month\": \"month\",\n \"number\": \"number\",\n \"pages\": \"pages\",\n \"publisher\": \"publisher\",\n \"title\": \"title\",\n \"url\": \"url\",\n \"version\": \"version\",\n \"volume\": \"volume\",\n \"year\": \"year\",\n \"booktitle\": \"collection-title\",\n }\n for bibtex_field, value in bib_entry.fields.items():\n bibtex_field = bibtex_field.lower()\n if bibtex_field in fields:\n cff_field = fields[bibtex_field]\n cff_reference[cff_field] = _cff_transform(\n cff_field=cff_field, bib_value=value\n )\n return cff_reference","def generate_readme_url(self, dn):\n\n df_curation = dn.curation_dict\n\n # Preferred citation\n single_str_citation = df_curation['item']['citation']\n\n # handle period in author list. Assume no period in dataset title\n str_list = list([single_str_citation.split('):')[0] + '). '])\n str_list += [str_row + '.' for str_row in single_str_citation.split('):')[1].split('. ')]\n\n citation_list = [content for content in str_list[0:-2]]\n citation_list.append(f\"{str_list[-2]} {str_list[-1]}\")\n citation_list = ' <br> '.join(citation_list)\n\n # summary\n figshare_description = df_curation['item']['description']\n\n query_str_dict = {'article_id': dn.name_dict['article_id'],\n 'curation_id': dn.name_dict['curation_id'],\n 'title': dn.name_dict['title'],\n 'depositor_name': dn.name_dict['simplify_fullName'],\n 'preferred_citation': citation_list,\n 'license': df_curation['item']['license']['name'],\n 'summary': figshare_description}\n # doi\n if not df_curation['item']['doi']: # empty case\n query_str_dict['doi'] = f\"https://doi.org/10.25422/azu.data.{dn.name_dict['article_id']}\"\n else:\n query_str_dict['doi'] = f\"https://doi.org/{df_curation['item']['doi']}\"\n\n # links\n if not df_curation['item']['references']: # not empty case\n links = \" <br> \".join(df_curation['item']['references'])\n query_str_dict['links'] = links\n\n # query_str_encode = str(query_str_dict).encode('base64', 'strict')\n q_eed = base64.urlsafe_b64encode(json.dumps(query_str_dict).encode()).decode()\n\n full_url = f\"{self.dict['generate_url']}{self.readme_survey_id}?\" + \\\n 'Q_EED=' + q_eed\n\n return full_url","def _get_first_author(self):\n if not len(self.get_authors()):\n return ''\n return self.get_authors()[0]","def subject_info(intent, extra_info=[]):\n\n text = intent['inputTranscript'].lower()\n utterances = AS.load_file('sample_utterances.txt')\n\n # add \"book\" and \"books\" to every utterance\n for line in list(utterances):\n utterances.insert(0, line + \" book\")\n utterances.insert(0, line + \" books\")\n\n # tells how many characters needs to be dropped before the subject starts\n to_drop = 0\n\n for line in utterances:\n if text.startswith(line):\n to_drop = len(line)\n break\n\n # drops the characters and makes a list from the strings that are left\n text = text[to_drop:].strip()\n text_list = text.split(' ', len(text))\n\n subject_list = []\n keywords = [\"books\", \"book\", \"by\", \"published\", \"written\"]\n keyword = \"\"\n\n # Find out when the book name ends\n for word in text_list:\n if word not in keywords:\n subject_list.append(word)\n else:\n break\n\n subject = \" \".join(subject_list)\n\n # Get all the keywords in the middle, so they can be\n # all be dropped at once, eg written by, books by\n text_list = text_list[len(subject_list):]\n if text_list:\n word = text_list[0]\n while word in keywords:\n keyword += word + \" \"\n text_list = text_list[1:]\n if text_list:\n word = text_list[0]\n else:\n break\n\n # search for an author from the rest of the characters\n author_text = text[len(keyword):].strip()\n author = AS.search(author_text, False)\n if author is \"\":\n author = None\n\n # There might be old info in the extra_info (author), so \n # we need to clear it\n extra_info.clear()\n\n # add the author to extra info so it can be used in the Finna API call\n if author:\n extra_info += [\"author:\\\"\" + author + \"\\\"\"]\n elif intent['sessionAttributes'].get('author'):\n extra_info += [\n \"author:\\\"\" + intent['sessionAttributes']['author'] + \"\\\"\"\n ]\n\n # The Finna API call\n request = lookfor(term=subject, filter=extra_info)['json']\n\n return parse_subject(request, subject, {'author': author})","def citation(self, citation):\n\n self._citation = citation","def AuthorURLs(entry):\n a_URLs = ''\n for a in entry.getAuthors():\n url = a.get('homepage', ' ')\n a_URLs += \"%s and \" % url\n return a_URLs[:-5]","def add_ref(doc_name, bib_name, keep_label=False, slides=False):\n bib_path = bib_name # os.path.join(static_path, \"tex\", bib_name)\n if not slides:\n keep_label = True\n with open(doc_name, \"r\") as f:\n _file = f.read()\n # find citations\n match = re.findall(r\"\\[@.*?\\]\", _file)\n references = []\n # print(match)\n for cit in match:\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\".html\", delete=True)\n tmp = tempfile.NamedTemporaryFile(suffix=\".md\", delete=True)\n with open(tmp.name, \"w\") as md_file:\n # Open the file for writing.\n md_file.write(cit)\n\n pandoc_command = [\n \"pandoc\",\n \"-C\",\n tmp.name,\n \"--bibliography\",\n bib_path,\n \"--csl\",\n \"./templates/my-csl.csl\",\n \"-o\",\n tmp_cite_html.name,\n ]\n if not slides:\n for tag in [\"--metadata\", \"link-citations=true\"]:\n pandoc_command.append(tag)\n output = subprocess.check_output(\n pandoc_command, stderr=subprocess.STDOUT\n ).decode(\"utf-8\")\n print(output.rstrip())\n tmp.close()\n with open(tmp_cite_html.name, \"r\") as cite_html:\n # Open the file for writing.\n cit_new = cite_html.read()\n # print(cit_new)\n if not keep_label:\n # remove first line\n cit_new = \"\\n\".join(cit_new.splitlines()[1:])\n else:\n lines = cit_new.splitlines()\n # remove the <p> tags\n lines[0] = lines[0][3:-4]\n cit_new = \"\\n\".join(lines)\n if slides:\n _file = _file.replace(cit, cit_new)\n else:\n _file = _file.replace(cit, lines[0])\n # collect the references\n references.append(\"<p>\")\n references.append(\"\\n\".join(lines))\n references.append(\"</p>\")\n # paste_refs_end()\n tmp_cite_html.close()\n if slides:\n with open(doc_name, \"w\") as f:\n f.write(_file)\n if not slides:\n if references == []:\n _file=clean_html_refs(_file)\n else:\n _file = _file.replace(\"<bibliography-placeholder>\", \"\\n\".join(references))\n with open(doc_name, \"w\") as f:\n f.write(_file)\n return","def citeproc(style, reference_list):\n pass","def test_author_string(self):\n self.assertNotEqual(self.module.__author__, '???')","def fetch_arxiv_bibtex(fp, info=None):\n info = info if info else is_arxiv(fp)\n\n if info:\n cat, num = info\n\n # Successful. Now fetch the BiBTeX.\n page = urlopen('http://adsabs.harvard.edu/cgi-bin/bib_query?'\n 'arXiv:{}{}'.format(cat + '/' if cat else '',\n num)).read()\n soup = BeautifulSoup(page, 'html5lib')\n el = soup.find('a', text='Bibtex entry for this abstract', href=True)\n href = urlopen(el['href']).read().decode()\n\n # Skip until the first '@', which should mark the beginning of the\n # BiBTeX.\n return '@' + '@'.join(href.split('@')[1:])\n return None","def setAuthor(self,value):\n self.PDFreactorConfiguration.in1[\"author\"] = value","def catalogue(self, fix_author=True):\n response = requests.get(CATALOGUE_URL)\n\n flags = DOTALL | UNICODE\n tables = findall(r'<table.*?</table>', response.text, flags=flags)\n rows = findall(r'<tr.*?</tr>', tables[1], flags=flags)\n\n books = []\n for row in rows[1:]:\n elements = findall('<td.*?</td>', row, flags=flags)\n book_id, title = findall(r'/(.*?)/\">(.*?)<',\n elements[4], flags=flags)[0]\n try:\n author_id, author = findall(r'/authors/(.*?).html\">(.*?)<',\n elements[6], flags=flags)[0]\n except:\n author_id, author = '', ''\n if fix_author:\n # fix_author name collision. TODO\n author = globals()['fix_author'](author)\n book = {\n 'type': findall(r'alt=\"(.*?)\">', elements[0], flags=flags)[0],\n 'book_id': book_id,\n 'title': title,\n 'author_id': author_id,\n 'author': author,\n 'year': elements[8][15:-5],\n 'language': elements[10][-9:-7]\n }\n books.append(book)\n return DataFrame(books)","def parse_references(article):\n reference_list = []\n references = article.find(\"text\").find(\"div\", attrs={\"type\": \"references\"})\n references = references.find_all(\"biblstruct\") if references is not None else []\n reference_list = []\n for reference in references:\n title = reference.find(\"title\", attrs={\"level\": \"a\"})\n if title is None:\n title = reference.find(\"title\", attrs={\"level\": \"m\"})\n title = title.text if title is not None else \"\"\n journal = reference.find(\"title\", attrs={\"level\": \"j\"})\n journal = journal.text if journal is not None else \"\"\n if journal is \"\":\n journal = reference.find(\"publisher\")\n journal = journal.text if journal is not None else \"\"\n year = reference.find(\"date\")\n year = year.attrs.get(\"when\") if year is not None else \"\"\n authors = []\n for author in reference.find_all(\"author\"):\n firstname = author.find(\"forename\", {\"type\": \"first\"})\n firstname = firstname.text.strip() if firstname is not None else \"\"\n middlename = author.find(\"forename\", {\"type\": \"middle\"})\n middlename = middlename.text.strip() if middlename is not None else \"\"\n lastname = author.find(\"surname\")\n lastname = lastname.text.strip() if lastname is not None else \"\"\n if middlename is not \"\":\n authors.append(firstname + \" \" + middlename + \" \" + lastname)\n else:\n authors.append(firstname + \" \" + lastname)\n authors = \"; \".join(authors)\n reference_list.append(\n {\"title\": title, \"journal\": journal, \"year\": year, \"authors\": authors}\n )\n return reference_list","def __citation_correction(self, bs, ground_truth):\n bs_ref = bs.findNext('bibl')\n gt_ref = ground_truth.findNext('ref')\n while gt_ref is not None:\n if gt_ref.find('article-title') != bs_ref.title:\n pass\n gt_ref = gt_ref.findNext('ref')","def fix_errors_in_citation(citation):\n result = regex.sub(r\"\\s+\", \" \", citation)\n result = regex.sub(r\"§(?=\\d)\", \"§ \", result)\n result = regex.sub(r\",\\sbis\\s\", \" bis \", result)\n return result","def test_author_simple(self):\n invenio_search = 'author:\"ellis, j*\"'\n spires_search = 'find a ellis, j'\n self._compare_searches(invenio_search, spires_search)","def get_authors():\n authors = []\n authorfile = os.path.join('doc', 'authors.txt')\n with codecs.open(authorfile, 'r', 'utf-8') as f:\n for line in f:\n line = line.strip()\n if line and not line.startswith(u'#'):\n authors.append(line)\n return u\", \".join(authors)","def parsed2Bibtex(parsed):\n bibtex = '@'+parsed['ENTRYTYPE']+'{'+parsed['ID']+\",\\n\"\n\n for field in [i for i in sorted(parsed) if i not in ['ENTRYTYPE', 'ID']]:\n bibtex += \"\\t\"+field+\"={\"+parsed[field]+\"},\\n\"\n bibtex += \"}\\n\\n\"\n return bibtex","def sanitize_author(name, email):\n # deal with inconsistent email addresses/names in commits.\n # feel free to fill this method out.\n return name","def test_citations_and_toc_2(self):\n settings = get_settings(\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\"+citations\"],\n PANDOC_ARGS=PANDOC_ARGS\n + [\n \"--table-of-contents\",\n \"--citeproc\",\n \"--csl=https://www.zotero.org/styles/ieee-with-url\",\n \"--metadata=link-citations:false\",\n \"--metadata=reference-section-title:References\",\n ],\n FORMATTED_FIELDS=FORMATTED_FIELDS,\n )\n\n pandoc_reader = PandocReader(settings)\n source_path = os.path.join(\n TEST_CONTENT_PATH, \"valid_content_with_citation.md\"\n )\n output, metadata = pandoc_reader.read(source_path)\n self.maxDiff = None\n\n self.assertEqual(\n (\n '<h2 id=\"string-theory\">String Theory</h2>\\n'\n \"<p>But this foundational principle of science has\"\n \" now been called into question by\"\n ' <a href=\"https://www.britannica.com/science/'\n 'string-theory\">String Theory</a>,'\n \" which is a relative newcomer to theoretical physics, but one\"\n \" that has captured the common imagination, judging by\"\n \" the popular explanations that abound on the Web\"\n ' <span class=\"citation\" data-cites=\"mann2019 wood2019'\n ' jones2020\">[1]–[3]</span>.'\n \" And whether string theory is or is not science, Popper\"\n \" notwithstanding, is an issue that is still up for debate\"\n \" <span\"\n ' class=\"citation\" data-cites=\"siegel2015 castelvecchi2016'\n ' alves2017 francis2019\">[4]–[7]</span>.</p>\\n'\n '<h1 class=\"unnumbered\" id=\"bibliography\">References</h1>\\n'\n '<div id=\"refs\" class=\"references csl-bib-body\"'\n ' role=\"doc-bibliography\">\\n'\n '<div id=\"ref-mann2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[1]'\n ' </div><div class=\"csl-right-inline\">A. Mann,'\n \" <span>“<span>What Is String Theory?</span>”</span>\"\n \" 20-Mar-2019. [Online].\"\n ' Available: <a href=\"https://www.livescience.com/'\n '65033-what-is-string-theory.html\">'\n \"https://www.livescience.com/\"\n \"65033-what-is-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-wood2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[2] </div>'\n '<div class=\"csl-right-inline\">'\n \"C. Wood, <span>“<span>What Is String Theory?</span>.\"\n \" Reference article:\"\n \" A simplified explanation and brief history of string\"\n \" theory,”</span> 11-Jul-2019.\"\n ' [Online]. Available: <a href=\"https://www.space.com/'\n '17594-string-theory.html\">'\n \"https://www.space.com/17594-string-theory.html</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-jones2020\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[3]'\n ' </div><div class=\"csl-right-inline\">'\n 'A. Z. Jones, <span>“<span class=\"nocase\">The Basics of String'\n \" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\"\n ' <a href=\"https://www.thoughtco.com/'\n 'what-is-string-theory-2699363\">'\n \"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-siegel2015\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[4]'\n ' </div><div class=\"csl-right-inline\">'\n \"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\"\n \" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\"\n \" <a\"\n ' href=\"https://www.forbes.com/sites/'\n \"startswithabang/2015/12/23/\"\n 'why-string-theory-is-not-science/\">https://www.forbes.com/'\n \"sites/startswithabang/2015/12/23/\"\n \"why-string-theory-is-not-science/</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-castelvecchi2016\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[5]'\n ' </div><div class=\"csl-right-inline\">'\n 'D. Castelvecchi, <span>“<span class=\"nocase\">'\n \"Feuding physicists turn\"\n \" to philosophy for help</span>. String theory is at the\"\n \" heart of a debate over the integrity of the scientific\"\n \" method itself,”</span> 05-Jan-2016. [Online]. Available:\"\n ' <a href=\"https://www.nature.com/news/'\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\">'\n \"https://www.nature.com/news/\"\n \"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-alves2017\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[6] </div>'\n '<div class=\"csl-right-inline\">'\n 'R. A. Batista and J. Primack, <span>“<span class=\"nocase\">'\n \"Is String theory falsifiable?</span>. Can a theory that isn’t\"\n \" completely testable still be useful to physics?”</span>\"\n \" [Online].\"\n ' Available: <a href=\"https://metafact.io/factchecks/'\n '30-is-string-theory-falsifiable\">'\n \"https://metafact.io/factchecks/\"\n \"30-is-string-theory-falsifiable</a>.\"\n \" [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n '<div id=\"ref-francis2019\" class=\"csl-entry\"'\n ' role=\"doc-biblioentry\">\\n'\n '<div class=\"csl-left-margin\">[7]'\n ' </div><div class=\"csl-right-inline\">'\n 'M. R. Francis, <span>“<span class=\"nocase\">Falsifiability and'\n \" physics</span>. Can a theory that isn’t completely testable\"\n \" still be useful to physics?”</span> 23-Apr-2019.\"\n \" [Online]. Available:\"\n ' <a href=\"https://www.scientificamerican.com/'\n 'article/is-string-theory-science/\">'\n \"https://www.scientificamerican.com/article/is-\"\n \"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\n\"\n \"</div>\\n\"\n \"</div>\\n\"\n ),\n output,\n )\n\n self.assertEqual(\"Valid Content With Citation\", str(metadata[\"title\"]))\n self.assertEqual(\"My Author\", str(metadata[\"author\"]))\n self.assertEqual(\"2020-10-16 00:00:00\", str(metadata[\"date\"]))\n self.assertEqual(\n (\n '<nav class=\"toc\" role=\"doc-toc\">\\n'\n \"<ul>\\n\"\n '<li><a href=\"#string-theory\">String Theory</a></li>\\n'\n '<li><a href=\"#bibliography\">References</a></li>\\n'\n \"</ul>\\n</nav>\\n\"\n ),\n str(metadata[\"toc\"]),\n )","def _parse_email_bib_data(cls, bib_data):\n pub_title = None\n pub_year = None\n\n # Get author name(s)\n parsed_bib = bib_data.split(\" - \")\n m_author = _utils.clean_string(parsed_bib[0])\n\n # Split further to get year and author\n if len(parsed_bib) > 1:\n parsed_b2 = parsed_bib[1].split(',')\n\n if len(parsed_b2) == 2:\n pub_title = _utils.clean_string(parsed_b2[0])\n try:\n pub_year = int(_utils.clean_string(parsed_b2[1]))\n except ValueError:\n pub_year = None\n\n else:\n try:\n pub_year = int(_utils.clean_string(parsed_b2[0]))\n except ValueError:\n pub_year = None\n pub_title = _utils.clean_string(parsed_b2[0])\n\n return {\n 'author': m_author,\n 'pub_title': pub_title,\n 'pub_year': pub_year\n }","def write_citation_page(refdict: dict) -> None:\n with open(WEBOUT_PATH + init_data().cite_url, \"w\", encoding=\"utf-8\") as outfile:\n common_html_header(outfile, \"Fiddler Crab Website Citation\")\n outfile.write(\" <header id=\\\"\" + init_data().cite_url + \"\\\">\\n\")\n outfile.write(\" <h1>Citation Info</h1>\\n\")\n outfile.write(\" </header>\\n\")\n outfile.write(\"\\n\")\n outfile.write(\" <p>\\n\")\n outfile.write(\" Generally it is best to cite the primary literature, whenever possible. However, the \"\n \"following paper describes much of the data that is unique to this website:\\n\")\n outfile.write(\" </p>\\n\")\n outfile.write(\" <div class=\\\"reference_list\\\">\\n\")\n outfile.write(\" <ul>\\n\")\n ref = refdict[\"Rosenberg2014\"] # citation describing the database\n outfile.write(\" <li><a href=\\\"references/Rosenberg2014.html\\\">\" + ref.formatted_html + \"</a></li>\\n\")\n outfile.write(\" </ul>\\n\")\n outfile.write(\" </div>\\n\")\n outfile.write(\" <ul class=\\\"fa-ul\\\">\\n\")\n outfile.write(\" <li>\" + fetch_fa_glyph(\"list pdf\") +\n \"<a href=\\\"https://dx.plos.org/10.1371/journal.pone.0101704\\\">Read paper online at \"\n \"PLoS ONE</a></li>\\n\")\n outfile.write(\" <li>\" + fetch_fa_glyph(\"list github\") +\n \"<a href=\\\"https://github.com/msrosenberg/fiddlercrab.info\\\">Website data repository on \"\n \"GitHub</a></li>\\n\")\n outfile.write(\" </ul>\\n\")\n common_html_footer(outfile)","def store_name(author):\n with open(\"ref.txt\",\"a\") as fp:\n fp.write(str(reference)+\"\"+'\\n')","async def to_full_pdf_url(self, client_session=None):\n doi_url = \"https://doi.org/{}\".format(self.doi)\n publisher = None\n\n class _PublisherFound(Exception):\n pass\n # First item is the regex to match against.\n # Second item is the string to check the matched group for.\n publisherRegex = {\n 'wiley': [re.compile(r\"\"\"<meta name=[\"']citation_publisher[\"']\\s+content=[\"'](.+?)[\"']\\s*/?>\"\"\"),\n \"John Wiley\"],\n 'elsevier': [re.compile(r\"\"\"<input type=\"hidden\" name=\"redirectURL\" value=\"https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2F(.+?)%3Fvia%253Dihub\" id=\"redirectURL\"/>\"\"\"),\n \"\"],\n 'tandf': [re.compile(r\"\"\"<meta name=[\"']dc.Publisher[\"']\\s+content=[\"'](.+?)[\"']\\s*/?>\"\"\"),\n \"Taylor\"],\n 'annrev': [re.compile(r\"\"\"<meta name=[\"']dc.Publisher[\"']\\s+content=[\"'](.+?)[\"']\\s*/?>\"\"\"),\n \"Annual Reviews\"],\n 'rsc': [re.compile(r\"\"\"<meta content=[\"']https://pubs.rsc.org/en/content/articlepdf/(.+?)[\"']\\s+name=\"citation_pdf_url\"\\s*/>\"\"\"),\n \"\"],\n }\n publisherFmtStrings = {\n \"acs\": \"https://pubs.acs.org/doi/pdf/{}\",\n \"wiley\": \"https://onlinelibrary.wiley.com/doi/pdfdirect/{}\",\n \"elsevier\": \"https://www.sciencedirect.com/science/article/pii/{}/pdfft\",\n \"nature\": \"https://www.nature.com/articles/{}.pdf\",\n \"science\": \"https://science.sciencemag.org/content/sci/{}.full.pdf\",\n \"springer\": \"https://link.springer.com/content/pdf/{}.pdf\",\n \"tandf\": \"https://www.tandfonline.com/doi/pdf/{}\",\n \"annrev\": \"https://www.annualreviews.org/doi/pdf/{}\",\n \"rsc\": \"https://pubs.rsc.org/en/content/articlepdf/{}\",\n }\n\n # Create a new ClientSession if one wasn't provided\n if client_session is None:\n # Make sure we have a polite header, though.\n session = aiohttp.ClientSession(headers=_g.httpHeaders)\n else:\n session = client_session\n try:\n async with session.get(doi_url) as resp:\n # Shortcut for ACS, don't need to read content\n if any(\"pubs.acs.org\" in h\n for h in resp.headers.getall(\"Set-Cookie\", [])):\n publisher = \"acs\"\n identifier = self.doi\n raise _PublisherFound\n # Shortcut for Nature, don't need to read content\n elif any(\"www.nature.com\" in h\n for h in resp.headers.getall(\"X-Forwarded-Host\", [])):\n publisher = \"nature\"\n identifier = self.doi.split('/', maxsplit=1)[1]\n raise _PublisherFound\n # Shortcut for Science, don't need to read content.\n # Note that this doesn't work for Sci Advances\n elif any(\"science.sciencemag.org\" in h\n for h in resp.headers.getall(\"Link\", [])):\n publisher = \"science\"\n identifier = resp.headers[\"Link\"].split(\">\")[0].split(\"/content/\")[1]\n raise _PublisherFound\n # Shortcut for Springer\n elif any(\".springer.com\" in h\n for h in resp.headers.getall(\"Set-Cookie\", [])):\n publisher = \"springer\"\n identifier = self.doi\n raise _PublisherFound\n # Shortcut for Taylor and Francis\n elif any(\".tandfonline.com\" in h\n for h in resp.headers.getall(\"Set-Cookie\", [])):\n publisher = \"tandf\"\n identifier = self.doi\n raise _PublisherFound\n # Otherwise, start reading the content\n else:\n e = resp.get_encoding()\n async for line in resp.content:\n line = line.decode(e) # it's read as bytes\n # Search the line for every regex\n for pname, regexKeyword in publisherRegex.items():\n match = regexKeyword[0].search(line)\n if match and regexKeyword[1] in match.group(1):\n publisher = pname\n if publisher in [\"wiley\", \"tandf\", \"annrev\"]:\n identifier = self.doi\n elif publisher in [\"elsevier\"]:\n identifier = match.group(1)\n elif publisher in [\"rsc\"]:\n identifier = match.group(1)\n raise _PublisherFound\n except (aiohttp.client_exceptions.ContentTypeError,\n aiohttp.client_exceptions.InvalidURL,\n aiohttp.client_exceptions.ClientConnectorError):\n result = _error(f\"to_full_pdf_url: URL '{url_doi}' not accessible.\"\n f\" Do you have access to the full text?\")\n except _PublisherFound:\n result = publisherFmtStrings[publisher].format(identifier)\n else:\n result = _error(f\"to_full_pdf_url: could not find full text for \"\n f\"doi {self.doi}\")\n\n # Close the ClientSession if it was newly opened\n if client_session is None:\n await session.close()\n return result","def alt_authors(self, key, value):\n _authors = self.get(\"authors\", [])\n if _authors:\n for i, v in enumerate(force_list(value)):\n _authors[i].update({\"alternative_names\": clean_val(\"a\", v, str)})\n return _authors"],"string":"[\n \"def to_citation(self, type):\\n acs_authors = \\\"; \\\".join(self.format_authors(\\\"acs\\\"))\\n # Some articles don't come with pages. :-(\\n pages_with_endash = (self.pages.replace(\\\"-\\\", \\\"\\\\u2013\\\") if self.pages\\n else \\\"\\\")\\n # Actually, not using quote() generally gives results that work fine.\\n # The only issue is that when using Markdown URLs with parentheses in\\n # Jupyter notebooks, the conversion to HTML gets it wrong, thinking\\n # that the URL ends at the first close parentheses in the URL. (In\\n # the notebook itself, it is fine, only the conversion to HTML messes\\n # up.) So we might as well escape them generally.\\n doi_url = f\\\"https://doi.org/{urllib.parse.quote(self.doi)}\\\"\\n\\n # BibLaTeX\\n if type in [\\\"bib\\\", \\\"b\\\"]:\\n # Create (hopefully) unique identifier\\n author_decoded = unidecode(self.authors[0][\\\"family\\\"])\\n journal_initials = \\\"\\\".join(c for c in self.journal_short\\n if c.isupper())\\n ref_identifier = f\\\"{author_decoded}{self.year}{journal_initials}\\\"\\n ref_identifier = \\\"\\\".join(ref_identifier.split()) # remove spaces\\n # Author names in bib style\\n author_names = \\\" and \\\".join(self.format_authors(\\\"bib\\\"))\\n journal = self.journal_short.replace(\\\". \\\", \\\".\\\\\\\\ \\\")\\n # Open and close braces\\n # Truthfully we don't need this. However, including the doubled\\n # curly braces in the f-string makes vim's indentation go crazy.\\n open, close = \\\"{\\\", \\\"}\\\"\\n # Make the citation\\n s = (f\\\"@article{open}{ref_identifier},\\\\n\\\"\\n f\\\" doi = {{{self.doi}}},\\\\n\\\"\\n f\\\" author = {{{author_names}}},\\\\n\\\"\\n f\\\" journal = {{{journal}}},\\\\n\\\"\\n f\\\" title = {{{self.title}}},\\\\n\\\"\\n f\\\" year = {{{self.year}}},\\\\n\\\")\\n if self.volume is not None:\\n s += f\\\" volume = {{{self.volume}}},\\\\n\\\"\\n if self.issue is not None:\\n s += f\\\" issue = {{{self.issue}}},\\\\n\\\"\\n if self.pages is not None:\\n s += f\\\" pages = {{{self.pages.replace('-', '--')}}},\\\\n\\\"\\n s += close\\n # Replace Unicode characters with their LaTeX equivalents\\n for char in _g.unicodeLatexDict:\\n s = s.replace(char, _g.unicodeLatexDict[char])\\n return s\\n\\n # Just DOI\\n if type in [\\\"doi\\\", \\\"d\\\"]:\\n return self.doi\\n\\n # The rest all have a long vs short type.\\n # Discern long vs short type\\n long = False\\n if type[0].upper() == type[0]:\\n long = True\\n type = type.lower()\\n\\n # reStructuredText\\n if type in [\\\"rst\\\", \\\"r\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"*{self.volume}* ({self.issue}), \\\" if self.issue\\n else f\\\"*{self.volume},* \\\")\\n return (author_title\\n + f\\\"*{self.journal_short}* **{self.year},** \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}. \\\"\\n + f\\\"`DOI: {self.doi} <{doi_url}>`_\\\")\\n\\n # Markdown\\n if type in [\\\"markdown\\\", \\\"m\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"*{self.volume}* ({self.issue}), \\\" if self.issue\\n else f\\\"*{self.volume},* \\\")\\n return (author_title\\n + f\\\"*{self.journal_short}* **{self.year},** \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}. \\\"\\n + f\\\"[DOI: {self.doi}]({doi_url})\\\")\\n\\n # Word\\n elif type in [\\\"word\\\", \\\"w\\\"]:\\n author_title = f\\\"{acs_authors} {self.title}. \\\" if long else \\\"\\\"\\n vol_issue = (f\\\"{self.volume} ({self.issue}), \\\" if self.issue\\n else f\\\"{self.volume}, \\\")\\n return (author_title\\n + f\\\"{self.journal_short} {self.year}, \\\"\\n + vol_issue\\n + f\\\"{pages_with_endash}.\\\")\\n\\n else:\\n raise ValueError(\\\"Invalid citation type '{type}' given\\\")\",\n \"def make_citation(meta):\\n pass\",\n \"def citation_formatter(citation, title=False):\\n # first we split the author-list\\n citation_string = \\\"\\\"\\n # the spaces around the and are required!\\n for match in citation[\\\"author\\\"].split(\\\" and \\\"):\\n last_name, first_names = match.split(\\\",\\\", 1)\\n citation_string += last_name.strip() + \\\",\\\"\\n for name in first_names.strip().split(' '):\\n citation_string += \\\" \\\" + name.strip()[0]\\n\\n citation_string += \\\"; \\\"\\n\\n if \\\"journal\\\" in citation:\\n citation_string += \\\" \\\" + citation[\\\"journal\\\"]\\n\\n citation_string += \\\" \\\" + citation[\\\"year\\\"]\\n\\n if \\\"doi\\\" in citation:\\n citation_string += \\\"; \\\" + citation[\\\"doi\\\"]\\n\\n return citation_string\",\n \"def cite(silent=False):\\n if silent is False:\\n print(__cite__)\\n else:\\n return __bibtex__\",\n \"def create_citation(cit):\\n if cit is not None:\\n if cit['citation-type'] == \\\"BIBTEX\\\":\\n return pybtex.database.parse_string(cit['citation-value'], \\\"bibtex\\\")\\n return None\",\n \"def make_bibtex(self):\\n\\n\\t\\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, \",\n \"def refine_author(c):\\n c = strip_some_punct(c)\\n c = strip_numbers(c)\\n c = strip_all_unbalanced_parens(c)\\n c = c.split()\\n # this is hard to catch otherwise, unless we split the author vs copyright grammar in two\\n if c[0].lower() == 'author':\\n c = c[1:]\\n c = u' '.join(c)\\n return c.strip()\",\n \"def process_bib_entry(\\n cid, bibdatabase, bibnums, fallback_fmt=\\\"[{author_abbrev}, {year}]\\\"\\n):\\n entry = bibdatabase[cid]\\n if cid not in bibnums:\\n bibnums[cid] = len(bibnums) + 1\\n\\n if \\\"doi\\\" in entry:\\n return r'<a href=\\\"https://doi.org/{doi}\\\">{text}</a>'.format(\\n doi=entry[\\\"doi\\\"], text=bibnums[cid]\\n )\\n elif \\\"url\\\" in entry:\\n return r'<a href=\\\"{url}\\\">{text}</a>'.format(url=entry[\\\"url\\\"], text=bibnums[cid])\\n elif \\\"link\\\" in entry:\\n return r'<a href=\\\"{url}\\\">{text}</a>'.format(\\n url=entry[\\\"link\\\"], text=bibnums[cid]\\n )\\n else:\\n return bibnums[cid]\\n # add_abbreviated_author(entry)\\n # split_date(entry)\\n # return DefaultFormatter().format(fallback_fmt, **entry)\",\n \"def _get_book(s):\\n\\n s = s.strip()\\n if s == '': raise SyntaxError('The book identification string is empty')\\n \\n author = ''\\n author_start = 0\\n author_found = False \\n for match in author_regex.finditer(s):\\n author_found = True\\n author_start = match.start()\\n author = match.group(1).strip()\\n \\n if author_found:\\n title = s[:author_start].strip()\\n else:\\n title = s\\n # Sometimes titles have a byte order mark prepended. The Kindle behavior\\n # changed in 2011 to stop doing this to entries in My Clippings.txt. \\n # Ensure the title is consistent, strip this character if it exists.\\n BOM = '\\\\ufeff'\\n if title.startswith(BOM):\\n title = title[1:] \\n \\n return title,author\",\n \"def make_citation_authors(res):\\n if \\\"author\\\" in res.keys():\\n first_author = res['author'][0]['family'] + \\\", \\\" + res['author'][0]['given']\\n last_author = res['author'][-1]['given'] + \\\" \\\" + res['author'][-1]['family']\\n middle_authors = \\\", \\\".join(\\\" \\\".join([x['given'], x['family']]) for x in res['author'][1:-1])\\n #assemble authors\\n author_string = first_author\\n author_string = author_string + \\\", \\\" + middle_authors if middle_authors != '' else author_string\\n author_string = author_string + \\\", and \\\" + last_author if len(res['author']) > 1 else author_string\\n \\n author_string = author_string + \\\".\\\" if author_string[-1] != \\\".\\\" else author_string\\n else:\\n author_string = \\\"Unknown Authors\\\"\\n\\n return clean_txt(author_string.capitalize())\",\n \"def get_bibtex(self):\\n url=\\\"http://www.biomedcentral.com/download/citation\\\"\\n parameters={'citation':'on', \\n 'result-selection':'THIS_PAGE',\\n 'suplements': 'false',\\n 'citationType':'BIBTEX_WITH_ABSTRACT',\\n 'articleIdThisPage':self.article_ids\\n }\\n data=urllib.urlencode(parameters)\\n self.bibtex=urllib2.urlopen(url,data)\",\n \"def format_bib_entry(e: BibDocument):\\n if e.bibtex is not None:\\n b = e.bibtex\\n s = fix_string(b.get('title', b.get('ID', '?'))) + '\\\\n'\\n s += format_author(b.get('author', b.get('editor', '?'))) + ' ' + b.get('year', '')\\n if len(e.filepaths) > 0:\\n s += ' [PDF]'\\n return s\\n else:\\n return e.relpath()\",\n \"def bibtex(self) -> str:\\n a = BibDatabase()\\n a.entries = [self.bib]\\n return bibtexparser.dumps(a)\",\n \"def get_citation(self):\\n etree = self.get_eml()\\n try:\\n citation_ipt = etree.find('./additionalMetadata/metadata/gbif/citation').text\\n except AttributeError:\\n citation_ipt = None\\n if citation_ipt:\\n now = datetime.datetime.now().date()\\n pola3r = \\\"(Available: Polar 'Omics Links to Antarctic, Arctic and Alpine Research. Antarctic Biodiversity Portal. Scientific Committee for Antarctic Research. www.biodiversity.aq/pola3r. Accessed: {})\\\".format(\\n now)\\n citation = \\\"{} {}\\\".format(citation_ipt, pola3r)\\n else:\\n citation = None\\n return citation\",\n \"def authorSign(g = None):\\n if not g:\\n return\\n authors = g.find(\\\"Author\\\")\\n ret = dict()\\n for author in authors:\\n ret[author['name']] = author['citation'].replace('\\\\n','').lower()\\n return ret\",\n \"def collect_citation_metadata(\\n metadata: dict, references: List[pybtex.database.Entry]\\n) -> dict:\\n # Author list\\n citation_authors = []\\n for author_tier in [\\\"Core\\\", \\\"Developers\\\", \\\"Contributors\\\"]:\\n for author in metadata[\\\"Authors\\\"][author_tier][\\\"List\\\"]:\\n family_names, given_names = author[\\\"Name\\\"].split(\\\", \\\")\\n citation_author = {\\n \\\"family-names\\\": family_names,\\n \\\"given-names\\\": given_names,\\n }\\n if \\\"Orcid\\\" in author:\\n citation_author[\\\"orcid\\\"] = (\\n \\\"https://orcid.org/\\\" + author[\\\"Orcid\\\"]\\n )\\n if \\\"Affiliations\\\" in author and len(author[\\\"Affiliations\\\"]) > 0:\\n citation_author[\\\"affiliation\\\"] = \\\" and \\\".join(\\n author[\\\"Affiliations\\\"]\\n )\\n citation_authors.append(citation_author)\\n # References in CITATION.cff format\\n citation_references = [to_cff_reference(entry) for entry in references]\\n return {\\n \\\"cff-version\\\": \\\"1.2.0\\\",\\n \\\"message\\\": (\\n \\\"Please cite SpECTRE in any publications that make use of its code\\\"\\n \\\" or data. Cite the latest version that you use in your\\\"\\n \\\" publication. The citation for this version is listed below.\\\"\\n ),\\n \\\"title\\\": metadata[\\\"Name\\\"],\\n \\\"url\\\": metadata[\\\"Homepage\\\"],\\n \\\"repository-code\\\": \\\"https://github.com/\\\" + metadata[\\\"GitHub\\\"],\\n \\\"version\\\": metadata[\\\"Version\\\"],\\n \\\"date-released\\\": metadata[\\\"PublicationDate\\\"],\\n \\\"doi\\\": metadata[\\\"Doi\\\"],\\n \\\"authors\\\": citation_authors,\\n \\\"keywords\\\": metadata[\\\"Keywords\\\"],\\n \\\"license\\\": metadata[\\\"License\\\"],\\n \\\"references\\\": citation_references,\\n }\",\n \"def info(entry: BibItem) -> str:\\n return \\\"{title}{author}{date}\\\".format(\\n title=(\\n \\\"Title: {}\\\\n\\\".format(re.sub(r\\\"[}{]\\\", \\\"\\\", entry[\\\"title\\\"]))\\n if \\\"title\\\" in entry\\n else \\\"\\\"\\n ),\\n author=(\\n \\\"Author{plural}: {author}\\\\n\\\".format(\\n plural=\\\"s\\\" if len(entry[\\\"author\\\"]) > 1 else \\\"\\\",\\n author=\\\"; \\\".join(entry[\\\"author\\\"]),\\n )\\n if \\\"author\\\" in entry\\n else \\\"\\\"\\n ),\\n date=(\\n \\\"Year: {}\\\\n\\\".format(entry[\\\"date\\\"].split(\\n \\\"-\\\")[0]) if \\\"date\\\" in entry else \\\"\\\"\\n ),\\n )\",\n \"def getBibTeX(bibref,tag_suf,outFile):\\n if bibref == '1988iras....1.....B':\\n bibtex = ['>@article{1988iras....1.....B,\\\\n',\\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\\\n',\\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\\\n',\\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\\\n',\\n ' year=1988,\\\\n',\\n ' volume = {1},\\\\n', \\n ' month = jan,\\\\n', \\n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\\\n'\\n '}\\\\n']\\n else:\\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\\n suf = '/exportcitation'\\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\\n \\n bibtex = []\\n for l in range(0, len(lines)):\\n if 'export-textarea ' in str(lines[l]):\\n bibtex.append(str(lines[l]))\\n t = l+1\\n \\n while '</textarea>' not in str(lines[t+1]):\\n bibtex.append(str(lines[t])) \\n t += 1\\n \\n for item in bibtex:\\n if 'author' in item.split('=')[0]:\\n auth = item.split('=')[1].split(',')[0]\\n for i in string.punctuation:\\n auth = auth.replace(i, '')\\n auth = auth.replace(' ', '')\\n if 'year' in item.split('=')[0]:\\n yr = item.split('=')[1].split(',')[0]\\n yr = yr.replace(' ', '')\\n \\n try:\\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\\\n'\\n except UnboundLocalError as ule:\\n print(bibtex)\\n print('')\\n print(ule)\\n sys.exit()\\n \\n with open(outFile, 'a') as o:\\n for item in bibtex:\\n item = item.replace('"', '\\\"')\\n item = item.replace(''', \\\"'\\\")\\n item = item.replace('&', \\\"&\\\")\\n o.write(item)\\n o.write('\\\\n')\\n \\n return auth+yr+tag_suf\",\n \"def bibtex(self):\\n return \\\"@comment{%(id)s: %(message)s}\\\" % \\\\\\n {'id': self.id, 'message': self.message}\",\n \"def test_example():\\n bib_database = bibtexparser.parse_string(\\n bibtex_string,\\n append_middleware=[\\n SeparateCoAuthors(allow_inplace_modification=True),\\n SplitNameParts(allow_inplace_modification=True),\\n ],\\n )\\n\\n new_bibtex_string = bibtexparser.write_string(\\n bib_database,\\n prepend_middleware=[\\n MergeNameParts(allow_inplace_modification=True),\\n MergeCoAuthors(allow_inplace_modification=True),\\n ],\\n )\\n\\n # Note: As defaults change, this assertion may need to be updated.\\n assert (\\n new_bibtex_string.strip()\\n == dedent(\\n \\\"\\\"\\\"\\n @article{Muller2020,\\n \\\\ttitle = {Some Paper Title},\\n \\\\tauthor = {John Muller and Jane Doe},\\n \\\\tjournal = {Nature Reviews Materials},\\n \\\\tyear = {2019}\\n }\\n \\n \\n @comment{This is a comment.}\\n \\n \\n @preamble{e = mc^2}\\\"\\\"\\\"\\n ).strip()\\n )\",\n \"def __generate_author_string__(self, list_of_authors):\\n author_string = \\\"\\\"\\n return author_string.join(list_of_authors)\",\n \"def get_bibtex_from_citation_file(package_name):\\n package = importlib.import_module(package_name)\\n cff_file = os.path.join(package.__path__[0], 'CITATION.cff')\\n citation_file = os.path.join(package.__path__[0], 'CITATION')\\n if os.path.exists(cff_file):\\n with open(cff_file) as f:\\n cffstr = f.read()\\n citation = Citation(cffstr=cffstr)\\n bibtex = citation.as_bibtex()\\n elif os.path.exists(citation_file):\\n with open(citation_file) as f:\\n citestr = f.read()\\n match = re.search(cite_tag_pattr, citestr)\\n if match is None:\\n raise ValueError('Could not find any BibTeX entries in CITATION file')\\n for i_end in range(match.end(), len(citestr)):\\n bibtex = citestr[match.start():i_end]\\n if bibtex.count('{') == bibtex.count('}'):\\n break\\n else:\\n raise ValueError('Mismatched braces in BibTeX entry in CITATION file')\\n else:\\n bibtex = None\\n return bibtex\",\n \"def to_citation(self, type):\\n return self.to_article().to_citation(type)\",\n \"def build_bibtex_entry(metadata: dict):\\n # We truncate the author list in the BibTeX entry after 'Developers',\\n # because not all journals are happy with printing an excessively long\\n # author list, e.g. Phys. Rev. wants at most 15 authors. By truncating the\\n # author list here, the user who copies the BibTeX entry doesn't have to\\n # make the decision where to truncate.\\n authors = [\\n pybtex.database.Person(author[\\\"Name\\\"])\\n for author in (\\n metadata[\\\"Authors\\\"][\\\"Core\\\"][\\\"List\\\"]\\n + metadata[\\\"Authors\\\"][\\\"Developers\\\"][\\\"List\\\"]\\n )\\n ] + [pybtex.database.Person(\\\"others\\\")]\\n entry = pybtex.database.Entry(\\n \\\"software\\\",\\n persons=dict(author=authors),\\n fields=dict(\\n title=(\\n r\\\"\\\\texttt{\\\"\\n + metadata[\\\"Name\\\"]\\n + \\\" v\\\"\\n + metadata[\\\"Version\\\"]\\n + \\\"}\\\"\\n ),\\n # The 'version' field is not used by revtex4-2, so we also put the\\n # version in the title\\n version=metadata[\\\"Version\\\"],\\n publisher=\\\"Zenodo\\\",\\n doi=metadata[\\\"Doi\\\"],\\n url=metadata[\\\"Homepage\\\"],\\n howpublished=(\\n r\\\"\\\\href{https://doi.org/\\\"\\n + metadata[\\\"Doi\\\"]\\n + \\\"}{\\\"\\n + metadata[\\\"Doi\\\"]\\n + \\\"}\\\"\\n ),\\n license=metadata[\\\"License\\\"],\\n year=str(metadata[\\\"PublicationDate\\\"].year),\\n month=str(metadata[\\\"PublicationDate\\\"].month),\\n ),\\n )\\n entry.key = \\\"spectrecode\\\"\\n return entry\",\n \"def list_publications(bib_format=\\\"dict\\\"):\\n\\n def get_bibtex(key, value):\\n total_keys = [\\n \\\"title\\\",\\n \\\"journal\\\",\\n \\\"volume\\\",\\n \\\"issue\\\",\\n \\\"number\\\",\\n \\\"pages\\\",\\n \\\"numpages\\\",\\n \\\"year\\\",\\n \\\"month\\\",\\n \\\"publisher\\\",\\n \\\"url\\\",\\n \\\"doi\\\",\\n \\\"issn\\\",\\n ]\\n bibtex_str = (\\n \\\"@article{\\\"\\n + key\\n + \\\",\\\\n\\\"\\n + \\\" author={\\\"\\n + \\\" and \\\".join(value[\\\"author\\\"])\\n + \\\"},\\\\n\\\"\\n )\\n for key in total_keys:\\n if key in value.keys():\\n bibtex_str += \\\" \\\" + key + \\\"={\\\" + value[key] + \\\"},\\\\n\\\"\\n bibtex_str += \\\"}\\\\n\\\"\\n return bibtex_str\\n\\n def get_apa(value):\\n apa_str = \\\" & \\\".join(value[\\\"author\\\"])\\n if \\\"year\\\" in value.keys():\\n apa_str += \\\" (\\\" + value[\\\"year\\\"] + \\\"). \\\"\\n if \\\"title\\\" in value.keys():\\n apa_str += value[\\\"title\\\"] + \\\". \\\"\\n if \\\"journal\\\" in value.keys():\\n apa_str += value[\\\"journal\\\"] + \\\", \\\"\\n if \\\"volume\\\" in value.keys():\\n apa_str += value[\\\"volume\\\"] + \\\", \\\"\\n if \\\"pages\\\" in value.keys():\\n apa_str += value[\\\"pages\\\"] + \\\". \\\"\\n if \\\"doi\\\" in value.keys():\\n apa_str += \\\"doi: \\\" + value[\\\"doi\\\"] + \\\"\\\\n\\\"\\n return apa_str\\n\\n publication_dict = s.publication_lst\\n if bib_format.lower() == \\\"dict\\\":\\n return publication_dict\\n elif bib_format.lower() == \\\"bibtex\\\":\\n total_str = \\\"\\\"\\n for pub in publication_dict:\\n for key, value in pub.items():\\n total_str += get_bibtex(key, value)\\n return total_str\\n elif bib_format.lower() == \\\"apa\\\":\\n total_str = \\\"\\\"\\n for pub in publication_dict:\\n for key, value in pub.items():\\n total_str += get_apa(value)\\n return total_str\\n else:\\n raise ValueError(\\\"Supported Bibformats are ['dict', 'bibtex', 'apa']\\\")\",\n \"def _cookIdCore(self, ref, **kwargs):\\n\\n # AUTHORS\\n namepart='nobody'\\n if self._refHasAuthorNames(ref):\\n lastnames = []\\n for each in ref['authors']:\\n if each.get('lastname', None):\\n lastnames.append(each['lastname'])\\n\\n if len(lastnames) > 1:\\n namepart = '%s' % ''.join([ lastname[0] for lastname in lastnames ])\\n elif len(lastnames) == 1:\\n namepart = lastnames[0][:3]\\n else:\\n pass\\n\\n # PUBLICATION YEAR\\n if ref.get('publication_year', None):\\n yearpart = str(ref['publication_year'])\\n else:\\n yearpart = \\\"1000\\\"\\n\\n return namepart + yearpart\",\n \"def generateCopyrightStr(config, firstYear):\\n copyrightStr = \\\"\\\"\\n thisYear = str(datetime.date.today().year)\\n\\n if not firstYear or firstYear == thisYear:\\n copyrightStr = \\\"©\\\" + thisYear + \\\" \\\" + \\\\\\n config['rssAuthor'] + \\\". All rights reserved.\\\"\\n else:\\n copyrightStr = \\\"©\\\" + firstYear + \\\"—\\\" + thisYear + \\\" \\\" + \\\\\\n config['rssAuthor'] + \\\". All rights reserved.\\\"\\n\\n return unicode(copyrightStr, 'utf-8')\",\n \"def portrayalCatalogueCitation(self) -> Sequence[Citation]:\\n pass\",\n \"def get_bibtex_entry(doi, bibtext_cache={}, shortdoi_cache={}):\\r\\n bibtext = get_bibtext(doi, cache = bibtext_cache)\\r\\n if not bibtext:\\r\\n return None\\r\\n\\r\\n short_doi = shorten(doi, cache = shortdoi_cache)\\r\\n parser = BibTexParser()\\r\\n parser.ignore_nonstandard_types = False\\r\\n bibdb = bibtexparser.loads(bibtext, parser)\\r\\n entry, = bibdb.entries\\r\\n quoted_doi = urllib.request.quote(doi)\\r\\n entry['link'] = 'https://doi.org/{}'.format(quoted_doi)\\r\\n if 'author' in entry:\\r\\n entry['author'] = ' and '.join(entry['author'].rstrip(';').split('; '))\\r\\n entry['ID'] = short_doi[3:]\\r\\n return entry\",\n \"def parse_citations(s: str):\\n print(\\\"parse_citations(%s)\\\" % s)\\n if pandas.isnull(s) or not s:\\n return []\\n terms = [e.strip() for e in s.split(\\\";\\\")]\\n print(\\\"parse_citations: \\\" + str(terms))\\n out = []\\n for term in terms:\\n if term.startswith(\\\"PMID\\\"):\\n out.append({\\\"db\\\": \\\"PubMed\\\", \\\"id\\\": term})\\n else:\\n raise RuntimeError(\\\"Unknown citation format: \\\" + term)\\n return out\",\n \"def getAuthor(self):\\n return self.bookAuthor\",\n \"def get_clean_bib(bib):\\n d = PyQuery(bib)\\n div = d(\\\"div.csl-right-inline\\\").html()\\n\\n # zotero keeps the html escaped in the return value\\n div = parser.unescape(div)\\n\\n return hyperlink_string(div)\",\n \"def make_citation_key(res):\\n year = str(make_year(res))\\n\\n try:\\n last_names = [x['family'] for x in res['author']]\\n except KeyError as e:\\n last_names = [\\\"Unknown\\\"]\\n if len(last_names) >= 3:\\n key = last_names[0].capitalize() + \\\"ETAL\\\" + year\\n else:\\n key = \\\"\\\".join(last_names) + year\\n\\n return clean_txt(key.replace(\\\" \\\", \\\"\\\"))\",\n \"def author(self) -> str:\\n return pulumi.get(self, \\\"author\\\")\",\n \"def bibtex_to_dict(text):\\n def _format_person(person):\\n von_last = ' '.join(person._prelast + person._last)\\n jr = ' '.join(person._lineage)\\n first = ' '.join(person._first + person._middle)\\n return ' '.join(part for part in (first, von_last, jr) if part)\\n\\n parser = pybtex.database.input.bibtex.Parser()\\n bib_data = parser.parse_stream(StringIO(text))\\n\\n plain_style = pybtex.style.formatting.plain.Style()\\n plain_render = pybtex.backends.plaintext.Backend()\\n formatted_entry = next(plain_style.format_entries(bib_data.entries.values()))\\n\\n # It is possible to parse out multiple BibTeX entries\\n # in one go! But, I'm assuming that the metadata\\n # contains information about only one publication.\\n\\n citekey = bib_data.entries.keys()[0]\\n entry = bib_data.entries[citekey]\\n meta = {\\n 'citekey': citekey,\\n 'type': entry.type,\\n 'authors': [_format_person(person)\\n for person in entry.persons['author']],\\n 'cite_info': entry.fields,\\n 'cite_bibtex': text,\\n 'cite_plain': formatted_entry.text.render(plain_render),\\n }\\n\\n # Get important stuff from cite_info\\n extract = ('title', 'abstract', 'pdf', 'url', 'year', 'keywords',\\n 'poster', 'presentation')\\n for key in extract:\\n if key in entry.fields:\\n meta[key] = meta['cite_info'].pop(key)\\n\\n # Add editors to cite_info, if they exist\\n if 'editor' in entry.persons:\\n meta['cite_info']['editors'] = \\\", \\\" .join(\\n [_format_person(person) for person in entry.persons['editor']])\\n\\n return meta\",\n \"def newBookCitation(self, **attrlinks):\\n return BookCitation(self, **attrlinks)\",\n \"def getCitationFromIssue(issue):\\n try:\\n if \\\"\\\\nCitation: \\\" in issue[\\\"body\\\"]:\\n citation = issue[\\\"body\\\"].split(\\\"\\\\nCitation: \\\")[1].split(\\\" \\\")[0]\\n else:\\n afterDOI = issue[\\\"body\\\"].split(\\\"DOI:\\\")[1]\\n citation = afterDOI.split(\\\" \\\")[0]\\n if citation == \\\"\\\":\\n citation = afterDOI.split(\\\" \\\")[1]\\n if \\\"\\\\r\\\\n\\\" in citation:\\n citation = citation.split(\\\"\\\\r\\\\n\\\")[0]\\n if citation.startswith(\\\"@\\\"):\\n citation = citation[1:]\\n return citation\\n\\n except:\\n print(\\n \\\"the citation could not be automatically extracted from the following issue: \\\\n\\\",\\n issue[\\\"title\\\"])\\n return \\\"unknown\\\"\",\n \"def to_string(self):\\n if self.__is_valid:\\n return \\\"Author:\\\\n\\\\tName: %s\\\\n\\\\t%s\\\\n\\\\tLangId: %s\\\\n\\\\tPartNumber: %s\\\" % (\\n self.__name, self.__build.to_string(), self.__lang_id, self.__part_number)\\n else:\\n return \\\"No Author info\\\"\",\n \"def author(self):\\n\\t\\tauthor = re.search(r\\\"([Ff]rom\\\\s)(.+) ([tT]\\\\s*o)([^,]+),\\\",self.raw_text()[:150])\\n\\t\\treport = re.search(r\\\".*[Rr]eport of ([^,]+),\\\",self.raw_text()[:150])\\n\\t\\torder = re.search(r\\\".*[Oo]rder of ([^,]+)[,.]* to\\\",self.raw_text()[:250])\\n\\t\\torder2 = re.search(r\\\".*[Oo]rder of ([^,]+),\\\",self.raw_text()[:250])\\n\\t\\tlogbook = re.search(r\\\".*[lL]og of ([^,]+)[,.]\\\",self.raw_text()[:250])\\n\\t\\tif order:\\n\\t\\t\\torder = order.group(1)\\n\\t\\t\\treturn order\\n\\t\\tif order2:\\n\\t\\t\\torder2 = order2.group(1)\\n\\t\\t\\treturn order2\\n\\t\\tif logbook:\\n\\t\\t\\tlogbook = logbook.group(1)\\n\\t\\t\\treturn logbook\\n\\t\\tif report:\\n\\t\\t\\treport = report.group(1)\\n\\t\\t\\treturn report\\n\\t\\tif author: \\t\\n\\t\\t\\tauthor = author.group(2) \\n\\t\\t\\tauthor = re.sub(r\\\"([^,]*),.*\\\",r\\\"\\\\1\\\",author)\\t \\n\\t\\t\\treturn author\\n\\t\\t\\n\\t\\treturn \\\"Unknown\\\"\",\n \"def isbn_lookup(isbn):\\n base = \\\"https://www.googleapis.com/books/v1/volumes?q=isbn=\\\"\\n# Unfortunately we can't use the superior \\\"with spam as eggs\\\" syntax here...\\n search = urlopen(base + isbn + \\\"&prettyprint=false\\\")\\n lines = search.read()\\n search.close()\\n for bool_pair in [(\\\"false\\\", \\\"False\\\"), (\\\"true\\\", \\\"True\\\")]:\\n lines = lines.replace(*bool_pair)\\n volume_info = literal_eval(lines)[\\\"items\\\"][0][\\\"volumeInfo\\\"]\\n title = volume_info[\\\"title\\\"]\\n authors = ', '.join(a for a in volume_info[\\\"authors\\\"])\\n return \\\"Title:\\\\t\\\\t%s\\\\nAuthor(s):\\\\t%s\\\" % (title, authors)\",\n \"def get_bibtex(package_name):\\n full_path = os.path.join(_bib_path, '{0}.bib'.format(package_name.lower()))\\n if not os.path.exists(full_path):\\n raise ValueError('Bibtex not found for {0}! If you know it has a '\\n 'citation, please consider adding it via pull request '\\n ' to: https://github.com/adrn/makecite')\\n\\n with open(full_path, 'r') as f:\\n bibtex = f.read()\\n\\n return bibtex\",\n \"def getAuthors(self): #$NON-NLS-1$\\r\",\n \"def copyrightRecord(inputstring):\\n \\n return inputstring[19:24]\",\n \"def author(name):\\n print(\\\"Author:\\\", name)\",\n \"def cite(self, arg=None):\\n nums = self.selector.select_by_index(arg)\\n if nums is None or not nums:\\n self.visual.error(\\\"Need a selection to cite.\\\")\\n return\\n citation_id = \\\", \\\".join([self.reference_entry_id_list[n] for n in nums])\\n citation = \\\"\\\\\\\\cite{{{}}}\\\".format(citation_id)\\n # clipboard.copy(citation_id)\\n clipboard.copy(citation)\\n self.visual.message(\\\"Copied to clipboard: {}\\\".format(citation))\",\n \"def getDOIFromCitation(citation):\\n try:\\n if \\\".org/\\\" in citation:\\n DOI = citation.split(\\\".org/\\\")[1]\\n elif citationContainsDOI(citation):\\n DOI = citation.split(\\\"doi:\\\")[1]\\n DOI = DOI.replace(\\\"]\\\", \\\"\\\")\\n elif citation == \\\"unknown\\\":\\n DOI = \\\"unknown\\\"\\n else:\\n DOI = citation\\n # DOIs are case insensitive but lower-case seems to be preferred and is what's used by manubot\\n DOI = DOI.lower()\\n return DOI\\n except:\\n return \\\"unknown\\\"\",\n \"def authors_string(self):\\n all_authors = Author.objects.filter(book=self).order_by('last_name')\\n return u', '.join([unicode(a) for a in all_authors])\",\n \"def parse_bib_from_bibtex(filename):\\n\\tentry_regex = r'''\\n\\t\\t\\t(?msx) # flags: multi-line, dot-match-all, verbose\\n\\t\\t\\t^@\\\\w+\\\\{ # start of line, item type\\n\\t\\t\\t.*? # content, can span multiple lines, non-greedy\\n\\t\\t\\t^\\\\} # start of line, closing parens\\n\\t\\t\\t'''\\n\\tattr_regex = r'''\\n\\t\\t\\t(?ix) # flags: ignore-case, verbose\\n\\t\\t\\t\\\\s* # leading space\\n\\t\\t\\t%s # what to match: author, title, or year\\n\\t\\t\\t\\\\s*=\\\\s* # space and equals\\n\\t\\t\\t[{\\\\\\\"'] # opening parens\\n\\t\\t\\t(.*) # the actual author, title, or year\\n\\t\\t\\t[}\\\\\\\"'] # closing parens or quote\\n\\t\\t\\t\\\\,? # optional comma\\n\\t\\t\\t'''\\n\\tparse_func = make_parse_func(attr_regex % \\\"author\\\", attr_regex % \\\"title\\\", \\n\\t attr_regex % \\\"year\\\", \\\" and \\\")\\n\\treturn parse_bib(filename, entry_regex, parse_func)\",\n \"def refine_copyright(c):\\n c = strip_some_punct(c)\\n c = fix_trailing_space_dot(c)\\n c = strip_all_unbalanced_parens(c)\\n # FIXME: this should be in the grammar, but is hard to get there right\\n # these are often artifacts of markup\\n c = c.replace('Copyright Copyright', 'Copyright')\\n c = c.replace('Copyright copyright', 'Copyright')\\n c = c.replace('copyright copyright', 'Copyright')\\n c = c.replace('copyright Copyright', 'Copyright')\\n c = c.replace('copyright\\\\'Copyright', 'Copyright')\\n c = c.replace('copyright\\\"Copyright', 'Copyright')\\n c = c.replace('copyright\\\\' Copyright', 'Copyright')\\n c = c.replace('copyright\\\" Copyright', 'Copyright')\\n s = c.split()\\n\\n # fix traliing garbage, captured by the grammar\\n last_word = s[-1]\\n if last_word.lower() in ('parts', 'any', '0', '1'):\\n s = s[:-1]\\n # this is hard to catch otherwise, unless we split the author\\n # vs copyright grammar in two. Note that AUTHOR and Authors should be kept\\n last_word = s[-1]\\n if last_word.lower() == 'author' and last_word not in ('AUTHOR', 'AUTHORS', 'Authors',) :\\n s = s[:-1]\\n\\n s = u' '.join(s)\\n return s.strip()\",\n \"def citationContainsDOI(citation):\\n if citation.startswith(\\\"doi:\\\"):\\n return True\\n elif citation.startswith(\\\"@doi:\\\"):\\n return True\\n elif citation.startswith(\\\"[@doi\\\"):\\n return True\\n else:\\n return False\",\n \"def test_review_citation_wrt_canonical_uri(self):\\n\\n self.review_mono.doi = None\\n self.issue_mono.setDoiRegistrationActive(False)\\n self.review_jour.doi = None\\n self.issue_jour.setDoiRegistrationActive(False)\\n\\n monograph_citation = self.review_mono.get_citation_string()\\n self.assertEquals('<a href=\\\"http://nohost/plone' in monograph_citation, True)\\n\\n journal_citation = self.review_jour.get_citation_string()\\n self.assertEquals('<a href=\\\"http://nohost/plone' in journal_citation, True)\\n\\n self.review_mono.canonical_uri = \\\"http://example.com\\\"\\n monograph_citation = self.review_mono.get_citation_string()\\n self.assertEquals('<a href=\\\"http://nohost/plone' in monograph_citation, False)\\n\\n self.review_jour.canonical_uri = \\\"http://example.com\\\"\\n journal_citation = self.review_jour.get_citation_string()\\n self.assertEquals('<a href=\\\"http://nohost/plone' in journal_citation, False)\",\n \"def __str__(self):\\n return '%s, %s: %s' % (self.first_author, self.year, self.title)\",\n \"def __convert_authors(self, author_dict: dict) -> str:\\n if \\\"author\\\" not in author_dict.keys():\\n return str(author_dict)\\n res = \\\"\\\"\\n for i, _ in enumerate(author_dict['author']):\\n if \\\"given-name\\\" in author_dict[\\\"author\\\"][i].keys() and \\\"surname\\\" in author_dict[\\\"author\\\"][i].keys():\\n res += author_dict['author'][i][\\\"given-name\\\"] + \\\" \\\" + author_dict['author'][i][\\\"surname\\\"] + \\\", \\\"\\n else:\\n res += str(author_dict['author'][i])\\n return res\",\n \"def fill(self):\\n if self.source == 'citations':\\n url = self._scholarly.URLS(\\\"CITATIONPUB\\\").format(self.id_citations)\\n soup = self._scholarly._get_soup(\\n self._scholarly.URLS('HOST').format(url))\\n self.bib['title'] = soup.find('div', id='gsc_vcd_title').text\\n\\n if soup.find('a', class_='gsc_vcd_title_link'):\\n self.bib['url'] = soup.find(\\n 'a', class_='gsc_vcd_title_link')['href']\\n\\n for item in soup.find_all('div', class_='gs_scl'):\\n key = item.find(class_='gsc_vcd_field').text\\n val = item.find(class_='gsc_vcd_value')\\n if key == 'Authors':\\n self.bib['author'] = ' and '.join(self.get_authorlist(val))\\n elif key == 'Journal':\\n self.bib['journal'] = val.text\\n elif key == 'Volume':\\n self.bib['volume'] = val.text\\n elif key == 'Issue':\\n self.bib['number'] = val.text\\n elif key == 'Pages':\\n self.bib['pages'] = val.text\\n elif key == 'Publisher':\\n self.bib['publisher'] = val.text\\n elif key == 'Publication date':\\n self.bib['year'] = arrow.get(val.text).year\\n elif key == 'Description':\\n if val.text[0:8].lower() == 'abstract':\\n val = val.text[9:].strip()\\n self.bib['abstract'] = val\\n elif key == 'Total citations':\\n self.id_scholarcitedby = re.findall(\\n self._scholarly.URLS('SCHOLARPUBRE'), val.a['href'])[0]\\n\\n # number of citation per year\\n years = [int(y.text) for y in soup.find_all(class_='gsc_vcd_g_t')]\\n cites = [int(c.text) for c in soup.find_all(class_='gsc_vcd_g_al')]\\n self.cites_per_year = dict(zip(years, cites))\\n\\n if soup.find('div', class_='gsc_vcd_title_ggi'):\\n self.bib['eprint'] = soup.find(\\n 'div', class_='gsc_vcd_title_ggi').a['href']\\n self._filled = True\\n\\n elif self.source == 'scholar':\\n self.bib['add_to_lib'] = self.url_add_sclib\\n\\n try:\\n bibtex = self._scholarly._get_soup(self.url_scholarbib)\\n bibtex = bibtex.find('pre').string\\n self.bib.update(bibtexparser.loads(bibtex).entries[0])\\n self.bib['author_count'] = str(\\n len(self.bib['author'].split('and')))\\n self.bib['age'] = str(\\n int(date.today().year) - int(self.bib['year']))\\n except:\\n # did not find year\\n pass\\n\\n self._filled = True\\n return self\",\n \"def get_bibtex_from_package(package_name, update_local=False):\\n try:\\n package = importlib.import_module(package_name)\\n for attr in ['__bibtex__', '__citation__']:\\n citation_info = getattr(package, attr, None)\\n if citation_info:\\n break\\n except ImportError:\\n warnings.warn(f\\\"{package_name} is not installed, cannot look for \\\"\\n \\\"package provided BibTeX.\\\")\\n return None\\n\\n if citation_info and update_local:\\n path = os.path.join(_bib_path, '{0}.bib'.format(package_name))\\n with open(path, 'w') as f:\\n f.write(citation_info)\\n\\n return citation_info\",\n \"def test_tax_court_citation_extractor(self):\\n\\n test_pairs = (\\n (\\n \\\"\\\"\\\" 1 UNITED STATES TAX COURT REPORT (2018)\\n\\n\\n\\n UNITED STATES TAX COURT\\n\\n\\n\\n BENTLEY COURT II LIMITED PARTNERSHIP, B.F. BENTLEY, INC., TAX\\n MATTERS PARTNER, Petitioner v.\\n COMMISSIONER OF INTERNAL REVENUE, Respondent\\n\\n\\n\\n Docket No. 5393-04. Filed May 31, 2006.\\n\\n\\n\\n Nancy Ortmeyer Kuhn, for petitioner.\\n \\\"\\\"\\\",\\n \\\"1 T.C. 2018\\\",\\n ),\\n (\\n \\\"\\\"\\\" T.C. Memo. 2003-150\\n\\n\\n\\n UNITED STATES TAX COURT\\n\\n\\n\\n RIVER CITY RANCHES #1 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n RIVER CITY RANCHES #2 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n RIVER CITY RANCHES #3 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n\\n\\n \\\"\\\"\\\",\\n \\\"2003 T.C. Memo. 150\\\",\\n ),\\n (\\n \\\"\\\"\\\" T.C. Summary Opinion 2003-150\\n\\n\\n\\n UNITED STATES TAX COURT\\n\\n\\n\\n RIVER CITY RANCHES #1 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n RIVER CITY RANCHES #2 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n RIVER CITY RANCHES #3 LTD., LEON SHEPARD,\\n TAX MATTERS PARTNER,\\n\\n\\n \\\"\\\"\\\",\\n \\\"2003 T.C. Summary Opinion 150\\\",\\n ),\\n (\\n \\\"\\\"\\\"\\n MICHAEL KEITH SHENK, PETITIONER v. COMMISSIONER\\n OF INTERNAL REVENUE, RESPONDENT\\n\\n Docket No. 5706–12. Filed May 6, 2013.\\n\\n P was divorced from his wife, and their 2003 ‘‘Judgment of\\n Absolute Divorce’’ provided that his ex-wife would have pri-\\n mary residential custody of their three minor children. The\\n judgment provided that the dependency exemption deductions\\n for the three children would be divided between the two ex-\\n spouses according to various conditions but did not provide\\n that the ex-wife must execute in P’s favor a Form 8332,\\n ‘‘Release of Claim to Exemption for Child of Divorced or Sepa-\\n rated Parents’’. The children resided with P’s ex-wife for more\\n than half of 2009, and P’s ex-wife did not execute in P’s favor\\n any Form 8332 or equivalent document for any year. For 2009\\n P timely filed a Federal income tax return on which he\\n claimed dependency exemption deductions and the child tax\\n credit for two of the children, consistent with his under-\\n standing of the terms of the judgment, but he did not attach\\n any Form 8332 to his return. He also claimed head-of-house-\\n hold filing status. His ex-wife, the custodial parent, timely\\n filed a Federal income tax return for 2009 on which she also\\n\\n 200\\n\\n\\n\\n\\nVerDate Nov 24 2008 10:59 Jul 11, 2014 Jkt 372897 PO 20012 Frm 00001 Fmt 3857 Sfmt 3857 V:\\\\FILES\\\\BOUND VOL. WITHOUT CROP MARKS\\\\B.V.140\\\\SHENK JAMIE\\n\\f (200) SHENK v. COMMISSIONER 201\\n\\n\\n claimed two dependency exemption deductions, so that one\\n child was claimed on both parents’ returns. R allowed to P the\\n dependency exemption deduction for one of the children but\\n disallowed his claim for the dependency exemption deduction\\n for the child who had also been claimed by the custodial\\n parent. At trial P contended he is entitled to a dependency\\n exemption deduction for all three children. Held: Since the\\n custodial parent did not execute, and P could not and did not\\n attach to his return, any Form 8332 or equivalent release, P\\n is not entitled under I.R.C. sec. 152(e)(2)(A) to claim the\\n dependency exemption deduction or the child tax credit. Held,\\n further, where both the custodial parent and the noncustodial\\n parent have claimed for the same year a dependency exemp-\\n tion deduction for the same child, a declaration signed by the\\n custodial parent after the period of limitations for assess-\\n ments has expired as to the custodial parent could not qualify\\n under I.R.C. sec. 152(e)(2)(A), and therefore there is no reason\\n to grant P’s request to leave the record open so that he may\\n obtain and proffer such a declaration. Held, further, P is not\\n entitled to head-of-household filing status under I.R.C. sec.\\n 2(b)(1) nor to the child tax credit under I.R.C. sec. 24.\\n\\n Michael Keith Shenk, for himself.\\n Shari Salu, for respondent.\\n GUSTAFSON, Judge: The Internal Revenue Service (IRS)\\n determined a deficiency of $3,136 in the 2009 Federal income\\n tax of petitioner Michael Keith Shenk. Mr. Shenk petitioned\\n this Court, pursuant to section 6213(a), 1 for redetermination\\n of the deficiency. After Mr. Shenk’s concession that he\\n received but did not report $254 in dividend income, the\\n issue for decision is whether Mr. Shenk is entitled to a\\n dependency exemption deduction for one of his children\\n under section 151(c), a child tax credit for that child under\\n section 24(a), and head-of-household filing status under sec-\\n tion 2(b)(1). On these issues, we hold for the IRS.\\n FINDINGS OF FACT\\n\\n The judgment of divorce\\n Mr. Shenk was married to Julie Phillips, and they have\\n three minor children—M.S., W.S., and L.S. They divorced in\\n 2003. The family court’s ‘‘Judgment of Absolute Divorce’’ pro-\\n 1 Unless otherwise indicated, all citations of sections refer to the Internal\\n\\n Revenue Code (26 U.S.C.) in effect for the tax year at issue, and all cita-\\n tions of Rules refer to the Tax Court Rules of Practice and Procedure.\\n\\n\\n\\n\\nVerDate Nov 24 2008 10:59 Jul 11, 2014 Jkt 372897 PO 20012 Frm 00002 Fmt 3857 Sfmt 3857 V:\\\\FILES\\\\BOUND VOL. WITHOUT CROP MARKS\\\\B.V.140\\\\SHENK JAMIE\\n\\f 202 140 UNITED STATES TAX COURT REPORTS (200)\\n\\n\\n vided: that Ms. Phillips was ‘‘awarded primary residential\\n custody’’ of the parties’ three children; and that Mr. Shenk\\n would be liable for child support payments; but that, as to\\n dependency exemptions—\\\"\\\"\\\",\\n \\\"140 T.C. 200\\\",\\n ),\\n )\\n site = tax.Site()\\n for q, a in test_pairs:\\n results = site.extract_from_text(q)\\n cite_string = \\\"%s %s %s\\\" % (\\n results[\\\"Citation\\\"][\\\"volume\\\"],\\n results[\\\"Citation\\\"][\\\"reporter\\\"],\\n results[\\\"Citation\\\"][\\\"page\\\"],\\n )\\n\\n self.assertEqual(cite_string, a)\\n print \\\"✓\\\", cite_string\",\n \"def author(self) -> pulumi.Output[Optional[str]]:\\n return pulumi.get(self, \\\"author\\\")\",\n \"def __init__(self, authorReference, authorString, text, time):\\n self.authorReference = authorReference\\n self.authorString = authorString\\n self.text = text\\n self.time = time\",\n \"def pubmed_citation(args=sys.argv[1:], out=sys.stdout):\\n\\n parser = argparse.ArgumentParser(\\n description='Get a citation using a PubMed ID or PubMed URL')\\n parser.add_argument('query', help='PubMed ID or PubMed URL')\\n parser.add_argument(\\n '-m', '--mini', action='store_true', help='get mini citation')\\n parser.add_argument(\\n '-e', '--email', action='store', help='set user email', default='')\\n\\n args = parser.parse_args(args=args)\\n\\n lookup = PubMedLookup(args.query, args.email)\\n publication = Publication(lookup, resolve_doi=False)\\n\\n if args.mini:\\n out.write(publication.cite_mini() + '\\\\n')\\n else:\\n out.write(publication.cite() + '\\\\n')\",\n \"def __str__(self):\\n\\n return super().__str__() + f'Author: {self.author}\\\\n'\",\n \"def book_urn(author='%', title=\\\"%\\\", ddk=\\\"%\\\", subject=\\\"\\\", period=(1100, 2020), gender=\\\"\\\", limit=20 ):\\n return get_urn({\\n \\\"author\\\": author,\\n \\\"title\\\":title,\\n \\\"ddk\\\":ddk,\\n \\\"subject\\\":subject,\\n \\\"year\\\":period[0],\\n 'next':period[1] - period[0],\\n \\\"limit\\\":limit\\n })\",\n \"def newJournalCitation(self, **attrlinks):\\n return JournalCitation(self, **attrlinks)\",\n \"def author_name(text):\\n tag = text.split()\\n\\n \\\"\\\"\\\"\\n We take the beginning of the text since the\\n author name will likely be there\\n \\\"\\\"\\\"\\n\\n tag = tag[:100]\\n author = []\\n\\n current_tag = 0\\n \\\"\\\"\\\"\\n We go through each word until we find the first instance\\n of the word 'by' or 'author', which should mean the author\\n will be written right after that.\\n We save the first word after 'by' or 'author' since it should\\n be the authors first name\\n \\\"\\\"\\\"\\n\\n for word in tag:\\n if (word.lower() == ('by') or\\n word.lower() == ('author') or\\n word.lower() == ('author:')):\\n\\n author.append(tag[current_tag+1].decode(encoding='UTF8',\\n errors='ignore'))\\n current_tag += 1\\n tag = tag[current_tag+1:]\\n break\\n current_tag += 1\\n\\n \\\"\\\"\\\"\\n We go through each word after the first name of the author\\n until we find a word that is not capitalized. We assume that\\n it marks the end of the author name.\\n We then return a list of the author's name split up.\\n \\\"\\\"\\\"\\n current_tag = 0\\n for word in tag:\\n if tag[current_tag].lower() == 'this':\\n break\\n if tag[current_tag].istitle():\\n author.append(tag[current_tag].decode(encoding='UTF8',\\n errors='ignore'))\\n current_tag += 1\\n\\n return author\",\n \"def cv_list(self):\\n\\n mystr = \\\"\\\"\\n for p in self.mypapers:\\n mystr += f\\\"{p.title[0]}\\\\n\\\"\\n if len(p.author) > 12:\\n a = f\\\"{p.author[0]} et al. \\\"\\n elif len(p.author) > 2:\\n a = \\\", \\\".join(p.author[:-1]) + f\\\" & {p.author[-1]} \\\"\\n elif len(p.author) == 2:\\n a = f\\\"{p.author[0]} & {p.author[1]} \\\"\\n else:\\n a = f\\\"{p.author[0]} \\\"\\n\\n mystr += f\\\"{a}\\\"\\n mystr += f\\\"{p.year}, {p.pub}\\\"\\n if p.volume is not None:\\n mystr += f\\\", {p.volume}\\\"\\n if p.issue is not None:\\n mystr += f\\\", {p.issue}\\\"\\n if p.page is not None:\\n mystr += f\\\", {p.page[0]}\\\"\\n mystr += \\\"\\\\n\\\\n\\\"\\n return mystr\",\n \"def test_citations_and_toc(self):\\n settings = get_settings(\\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\\\"+citations\\\"],\\n PANDOC_ARGS=PANDOC_ARGS\\n + [\\n \\\"--toc\\\",\\n \\\"-C\\\",\\n \\\"--csl=https://www.zotero.org/styles/ieee-with-url\\\",\\n \\\"--metadata=link-citations:false\\\",\\n \\\"--metadata=reference-section-title:References\\\",\\n ],\\n FORMATTED_FIELDS=FORMATTED_FIELDS,\\n )\\n\\n pandoc_reader = PandocReader(settings)\\n source_path = os.path.join(\\n TEST_CONTENT_PATH, \\\"valid_content_with_citation.md\\\"\\n )\\n output, metadata = pandoc_reader.read(source_path)\\n self.maxDiff = None\\n\\n self.assertEqual(\\n (\\n '<h2 id=\\\"string-theory\\\">String Theory</h2>\\\\n'\\n \\\"<p>But this foundational principle of science has\\\"\\n \\\" now been called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/'\\n 'string-theory\\\">String Theory</a>,'\\n \\\" which is a relative newcomer to theoretical physics, but one\\\"\\n \\\" that has captured the common imagination, judging by\\\"\\n \\\" the popular explanations that abound on the Web\\\"\\n ' <span class=\\\"citation\\\" data-cites=\\\"mann2019 wood2019'\\n ' jones2020\\\">[1]–[3]</span>.'\\n \\\" And whether string theory is or is not science, Popper\\\"\\n \\\" notwithstanding, is an issue that is still up for debate\\\"\\n \\\" <span\\\"\\n ' class=\\\"citation\\\" data-cites=\\\"siegel2015 castelvecchi2016'\\n ' alves2017 francis2019\\\">[4]–[7]</span>.</p>\\\\n'\\n '<h1 class=\\\"unnumbered\\\" id=\\\"bibliography\\\">References</h1>\\\\n'\\n '<div id=\\\"refs\\\" class=\\\"references csl-bib-body\\\"'\\n ' role=\\\"doc-bibliography\\\">\\\\n'\\n '<div id=\\\"ref-mann2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[1]'\\n ' </div><div class=\\\"csl-right-inline\\\">A. Mann,'\\n \\\" <span>“<span>What Is String Theory?</span>”</span>\\\"\\n \\\" 20-Mar-2019. [Online].\\\"\\n ' Available: <a href=\\\"https://www.livescience.com/'\\n '65033-what-is-string-theory.html\\\">'\\n \\\"https://www.livescience.com/\\\"\\n \\\"65033-what-is-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-wood2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[2] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n \\\"C. Wood, <span>“<span>What Is String Theory?</span>.\\\"\\n \\\" Reference article:\\\"\\n \\\" A simplified explanation and brief history of string\\\"\\n \\\" theory,”</span> 11-Jul-2019.\\\"\\n ' [Online]. Available: <a href=\\\"https://www.space.com/'\\n '17594-string-theory.html\\\">'\\n \\\"https://www.space.com/17594-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-jones2020\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[3]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'A. Z. Jones, <span>“<span class=\\\"nocase\\\">The Basics of String'\\n \\\" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.thoughtco.com/'\\n 'what-is-string-theory-2699363\\\">'\\n \\\"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-siegel2015\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[4]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n \\\"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\\\"\\n \\\" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\\\"\\n \\\" <a\\\"\\n ' href=\\\"https://www.forbes.com/sites/'\\n \\\"startswithabang/2015/12/23/\\\"\\n 'why-string-theory-is-not-science/\\\">https://www.forbes.com/'\\n \\\"sites/startswithabang/2015/12/23/\\\"\\n \\\"why-string-theory-is-not-science/</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-castelvecchi2016\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[5]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'D. Castelvecchi, <span>“<span class=\\\"nocase\\\">'\\n \\\"Feuding physicists turn\\\"\\n \\\" to philosophy for help</span>. String theory is at the\\\"\\n \\\" heart of a debate over the integrity of the scientific\\\"\\n \\\" method itself,”</span> 05-Jan-2016. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.nature.com/news/'\\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\\\">'\\n \\\"https://www.nature.com/news/\\\"\\n \\\"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-alves2017\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[6] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n 'R. A. Batista and J. Primack, <span>“<span class=\\\"nocase\\\">'\\n \\\"Is String theory falsifiable?</span>. Can a theory that isn’t\\\"\\n \\\" completely testable still be useful to physics?”</span>\\\"\\n \\\" [Online].\\\"\\n ' Available: <a href=\\\"https://metafact.io/factchecks/'\\n '30-is-string-theory-falsifiable\\\">'\\n \\\"https://metafact.io/factchecks/\\\"\\n \\\"30-is-string-theory-falsifiable</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-francis2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[7]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'M. R. Francis, <span>“<span class=\\\"nocase\\\">Falsifiability and'\\n \\\" physics</span>. Can a theory that isn’t completely testable\\\"\\n \\\" still be useful to physics?”</span> 23-Apr-2019.\\\"\\n \\\" [Online]. Available:\\\"\\n ' <a href=\\\"https://www.scientificamerican.com/'\\n 'article/is-string-theory-science/\\\">'\\n \\\"https://www.scientificamerican.com/article/is-\\\"\\n \\\"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n ),\\n output,\\n )\\n\\n self.assertEqual(\\\"Valid Content With Citation\\\", str(metadata[\\\"title\\\"]))\\n self.assertEqual(\\\"My Author\\\", str(metadata[\\\"author\\\"]))\\n self.assertEqual(\\\"2020-10-16 00:00:00\\\", str(metadata[\\\"date\\\"]))\\n self.assertEqual(\\n (\\n '<nav class=\\\"toc\\\" role=\\\"doc-toc\\\">\\\\n'\\n \\\"<ul>\\\\n\\\"\\n '<li><a href=\\\"#string-theory\\\">String Theory</a></li>\\\\n'\\n '<li><a href=\\\"#bibliography\\\">References</a></li>\\\\n'\\n \\\"</ul>\\\\n</nav>\\\\n\\\"\\n ),\\n str(metadata[\\\"toc\\\"]),\\n )\\n self.assertEqual(\\n (\\n \\\"<p>But this foundational principle of science has now been\\\"\\n \\\" called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/string-theory\\\">'\\n \\\"String Theory</a>.</p>\\\\n\\\"\\n ),\\n str(metadata[\\\"summary\\\"]),\\n )\",\n \"def get_short_name(self):\\n split = self.name.split(' - ')\\n # author, year, and first couple of words of paper title\\n return \\\"{} ({}), {}\\\".format(split[0], split[1], \\\" \\\".join(split[2].split(' ')[:3]))\",\n \"def format_one_author(author, style):\\n # Check If there's no given name.\\n # We should probably try to handle the no family name case, but\\n # I'm not sure when we will actually come across an example...\\n if \\\"given\\\" not in author or author[\\\"given\\\"] == []:\\n return author[\\\"family\\\"]\\n # Otherwise...\\n family_name = author[\\\"family\\\"]\\n given_names = author[\\\"given\\\"]\\n\\n # deal with a pathological case, 10.1016/j.jmr.2018.02.009\\n ns = given_names.split()\\n for i, name in enumerate(ns):\\n if i >= 1 and name.startswith('-'):\\n this_name = ns.pop(i)\\n ns[i - 1] += this_name\\n given_names = \\\" \\\".join(ns)\\n\\n if style == \\\"display\\\":\\n return (\\\"\\\".join(n[0] for n in re.split(r\\\"[\\\\s-]\\\", given_names))\\n + \\\" \\\" + family_name)\\n elif style == \\\"acs\\\":\\n # \\\"Jean-Baptiste Simon\\\" -> [[\\\"Jean\\\", \\\"Baptiste\\\"], [\\\"Simon\\\"]]\\n split_both = [name.split('-') for name in given_names.split()]\\n # [[\\\"Jean\\\", \\\"Baptiste\\\"], [\\\"Simon\\\"]] -> \\\"J.-B. S\\\"\\n joined_both = \\\". \\\".join([\\\".-\\\".join(n[0] for n in names)][0]\\n for names in split_both)\\n return (family_name + \\\", \\\" + joined_both + \\\".\\\")\\n elif style == \\\"bib\\\":\\n s = family_name + \\\", \\\" + given_names\\n return s.replace(\\\". \\\", \\\".\\\\\\\\ \\\") # Must use control spaces\\n elif style == \\\"full\\\":\\n return given_names + \\\" \\\" + family_name\\n # Otherwise, grumble.\\n else:\\n raise ValueError(f\\\"Invalid value '{style}' for style.\\\")\",\n \"def newThesisCitation(self, **attrlinks):\\n return ThesisCitation(self, **attrlinks)\",\n \"def make_author_list(res):\\n try:\\n r = [\\\", \\\".join([clean_txt(x['family']).capitalize(), clean_txt(x['given']).capitalize()]) for x in res['author']]\\n except KeyError as e:\\n print(\\\"No 'author' key, using 'Unknown Author'. You should edit the markdown file to change the name and citationkey.\\\")\\n r = [\\\"Unknown Authors\\\"]\\n return r\",\n \"def __str__(self):\\n\\t\\treturn f'{self.body} - quote of {self.author}'\",\n \"def scrape_author(self, author_name, min_len=0, max_len=9999):\\n search = sc.search_author(author_name)\\n author = next(search)\\n sc.fill(author, sections=['publications'])\\n print(author.keys())\\n with open(\\n 'loadings\\\\\\\\authors_papers\\\\\\\\{}.txt'.format(author_name),\\n 'w',\\n encoding='utf-8'\\n ) as file:\\n for counter, pubblication in enumerate(author['publications']):\\n\\n if len(pubblication['bib']['title']) < min_len \\\\\\n or len(pubblication['bib']['title']) > max_len:\\n continue\\n file.write(pubblication['bib']['title'])\\n file.write('\\\\n')\\n counter += 1\\n if counter > self.hard_limit:\\n break\",\n \"def fixAuthor(self, pageText):\\n informationRegex = re.compile(\\n r'\\\\|Author=Original uploader was '\\n r'(?P<author>\\\\[\\\\[:\\\\w+:\\\\w+:\\\\w+\\\\|\\\\w+\\\\]\\\\] at \\\\[.+\\\\])')\\n selfRegex = re.compile(\\n r'{{self\\\\|author='\\n r'(?P<author>\\\\[\\\\[:\\\\w+:\\\\w+:\\\\w+\\\\|\\\\w+\\\\]\\\\] at \\\\[.+\\\\])\\\\|')\\n\\n # Find the |Author=Original uploader was ....\\n informationMatch = informationRegex.search(pageText)\\n\\n # Find the {{self|author=\\n selfMatch = selfRegex.search(pageText)\\n\\n # Check if both are found and are equal\\n if (informationMatch and selfMatch):\\n if informationMatch.group('author') == selfMatch.group('author'):\\n # Replace |Author=Original uploader was ... with |Author= ...\\n pageText = informationRegex.sub(r'|Author=\\\\g<author>',\\n pageText)\\n return pageText\",\n \"def internal_citations(text, initial_label=None,\\n require_marker=False, title=None):\\n if not initial_label:\\n initial_label = Label()\\n citations = []\\n\\n def multiple_citations(matches, comment):\\n \\\"\\\"\\\"i.e. head :: tail\\\"\\\"\\\"\\n for match, start, end in matches:\\n label = initial_label\\n for submatch in chain([match.head], match.tail):\\n cit = ParagraphCitation(\\n submatch.pos[0], submatch.pos[1],\\n match_to_label(submatch.tokens, label, comment=comment),\\n full_start=start,\\n full_end=end,\\n in_clause=True)\\n label = cit.label # update the label to keep context\\n citations.append(cit)\\n\\n def single_citations(matches, comment):\\n for match, start, end in matches:\\n full_start = start\\n if match.marker is not '':\\n # Remove the marker from the beginning of the string\\n start = match.marker.pos[1]\\n citations.append(ParagraphCitation(\\n start, end, match_to_label(match, initial_label,\\n comment=comment),\\n full_start=full_start))\\n\\n single_citations(grammar.marker_comment.scanString(text), True)\\n\\n multiple_citations(grammar.multiple_non_comments.scanString(text), False)\\n multiple_citations(grammar.multiple_appendix_section.scanString(text),\\n False)\\n multiple_citations(grammar.multiple_comments.scanString(text), True)\\n multiple_citations(grammar.multiple_appendices.scanString(text), False)\\n multiple_citations(grammar.multiple_period_sections.scanString(text),\\n False)\\n\\n single_citations(grammar.marker_appendix.scanString(text), False)\\n single_citations(grammar.appendix_with_section.scanString(text), False)\\n single_citations(grammar.marker_paragraph.scanString(text), False)\\n single_citations(grammar.mps_paragraph.scanString(text), False)\\n single_citations(grammar.m_section_paragraph.scanString(text), False)\\n if not require_marker:\\n single_citations(grammar.section_paragraph.scanString(text), False)\\n single_citations(grammar.part_section_paragraph.scanString(text),\\n False)\\n multiple_citations(\\n grammar.multiple_section_paragraphs.scanString(text), False)\\n\\n # Some appendix citations are... complex\\n for match, start, end in grammar.appendix_with_part.scanString(text):\\n full_start = start\\n if match.marker is not '':\\n start = match.marker.pos[1]\\n label = filter(lambda l: l != '.', list(match)[3:])\\n label = dict(zip(['p1', 'p2', 'p3'], label))\\n citations.append(ParagraphCitation(\\n start, end, initial_label.copy(\\n appendix=match.appendix, appendix_section=match.a1,\\n **label), full_start=full_start))\\n\\n # Internal citations can sometimes be in the form XX CFR YY.ZZ\\n for match, start, end in grammar.internal_cfr_p.scanString(text):\\n # Check if this is a reference to the CFR title and part we are parsing\\n if match.cfr_title == title and match[1] == initial_label.to_list()[0]:\\n full_start = start\\n if match.marker is not '':\\n # Remove the marker from the beginning of the string\\n start = match.marker.pos[1]\\n citations.append(ParagraphCitation(\\n start, end, match_to_label(match, initial_label),\\n full_start=full_start))\\n else:\\n continue\\n\\n # And sometimes there are several of them\\n for match, start, end in grammar.multiple_cfr_p.scanString(text):\\n label = initial_label\\n if match.head.cfr_title == title:\\n for submatch in chain([match.head], match.tail):\\n if submatch.part == initial_label.to_list()[0]:\\n cit = ParagraphCitation(\\n submatch.pos[0], submatch.pos[1],\\n match_to_label(submatch.tokens, label),\\n full_start=start,\\n full_end=end,\\n in_clause=True)\\n label = cit.label # update the label to keep context\\n citations.append(cit)\\n else:\\n continue\\n\\n # Remove any sub-citations\\n final_citations = []\\n for cit in citations:\\n if not any(cit in other for other in citations):\\n final_citations.append(cit)\\n\\n return final_citations\",\n \"def _parse_mercurial_author(data, id_gen):\\n angled = ur'(?P<author>.+?) <(?P<email>.+?)>'\\n paren = ur'(?P<email>.+?) \\\\((?P<author>.+?)\\\\)'\\n simple = ur'(?P<author>[^,]+)'\\n author_list = []\\n for regex in (angled, paren, simple):\\n # Watch out for commas separating multiple names.\\n regex += u'(,\\\\s*)?'\\n for match in re.finditer(regex, data):\\n # Watch out for suffixes like 'Jr.' when they are comma-separated\\n # from the name and thus cause issues when *all* names are only\\n # separated by commas.\\n match_dict = match.groupdict()\\n author = match_dict['author']\\n if not author.partition(' ')[1] and author.endswith('.'):\\n prev_author = author_list.pop()\\n author = ', '.join([prev_author, author])\\n if u'email' not in match_dict:\\n email = ''\\n else:\\n email = match_dict['email']\\n author_list.append((author, email))\\n else:\\n # If authors were found then stop searching as only expect one\\n # style of author citation.\\n if author_list:\\n break\\n author = Author(author_list[0])\\n user = author.first_last\\n email = author.email\\n uid = id_gen[user]\\n return (uid, user, email)\",\n \"def author(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"author\\\")\",\n \"def to_cff_reference(bib_entry: pybtex.database.Entry) -> dict:\\n\\n def _cff_transform(cff_field, bib_value):\\n if cff_field == \\\"type\\\":\\n if bib_value == \\\"inproceedings\\\":\\n return \\\"article\\\"\\n elif bib_value == \\\"incollection\\\":\\n return \\\"article\\\"\\n elif cff_field == \\\"publisher\\\":\\n return {\\\"name\\\": bib_value}\\n elif cff_field == \\\"month\\\":\\n try:\\n return int(bib_value)\\n except ValueError:\\n return {\\n \\\"jan\\\": 1,\\n \\\"feb\\\": 2,\\n \\\"mar\\\": 3,\\n \\\"apr\\\": 4,\\n \\\"may\\\": 5,\\n \\\"jun\\\": 6,\\n \\\"jul\\\": 7,\\n \\\"aug\\\": 8,\\n \\\"sep\\\": 9,\\n \\\"oct\\\": 10,\\n \\\"nov\\\": 11,\\n \\\"dec\\\": 12,\\n }[bib_value[:3].lower()]\\n return bib_value\\n\\n cff_reference = {\\n \\\"type\\\": _cff_transform(cff_field=\\\"type\\\", bib_value=bib_entry.type),\\n \\\"authors\\\": [\\n to_cff_person(person) for person in bib_entry.persons[\\\"author\\\"]\\n ],\\n }\\n # Map BibTeX to CFF fields. This is just a subset of the most relevant\\n # fields.\\n fields = {\\n \\\"doi\\\": \\\"doi\\\",\\n \\\"edition\\\": \\\"edition\\\",\\n \\\"isbn\\\": \\\"isbn\\\",\\n \\\"license\\\": \\\"license\\\",\\n \\\"month\\\": \\\"month\\\",\\n \\\"number\\\": \\\"number\\\",\\n \\\"pages\\\": \\\"pages\\\",\\n \\\"publisher\\\": \\\"publisher\\\",\\n \\\"title\\\": \\\"title\\\",\\n \\\"url\\\": \\\"url\\\",\\n \\\"version\\\": \\\"version\\\",\\n \\\"volume\\\": \\\"volume\\\",\\n \\\"year\\\": \\\"year\\\",\\n \\\"booktitle\\\": \\\"collection-title\\\",\\n }\\n for bibtex_field, value in bib_entry.fields.items():\\n bibtex_field = bibtex_field.lower()\\n if bibtex_field in fields:\\n cff_field = fields[bibtex_field]\\n cff_reference[cff_field] = _cff_transform(\\n cff_field=cff_field, bib_value=value\\n )\\n return cff_reference\",\n \"def generate_readme_url(self, dn):\\n\\n df_curation = dn.curation_dict\\n\\n # Preferred citation\\n single_str_citation = df_curation['item']['citation']\\n\\n # handle period in author list. Assume no period in dataset title\\n str_list = list([single_str_citation.split('):')[0] + '). '])\\n str_list += [str_row + '.' for str_row in single_str_citation.split('):')[1].split('. ')]\\n\\n citation_list = [content for content in str_list[0:-2]]\\n citation_list.append(f\\\"{str_list[-2]} {str_list[-1]}\\\")\\n citation_list = ' <br> '.join(citation_list)\\n\\n # summary\\n figshare_description = df_curation['item']['description']\\n\\n query_str_dict = {'article_id': dn.name_dict['article_id'],\\n 'curation_id': dn.name_dict['curation_id'],\\n 'title': dn.name_dict['title'],\\n 'depositor_name': dn.name_dict['simplify_fullName'],\\n 'preferred_citation': citation_list,\\n 'license': df_curation['item']['license']['name'],\\n 'summary': figshare_description}\\n # doi\\n if not df_curation['item']['doi']: # empty case\\n query_str_dict['doi'] = f\\\"https://doi.org/10.25422/azu.data.{dn.name_dict['article_id']}\\\"\\n else:\\n query_str_dict['doi'] = f\\\"https://doi.org/{df_curation['item']['doi']}\\\"\\n\\n # links\\n if not df_curation['item']['references']: # not empty case\\n links = \\\" <br> \\\".join(df_curation['item']['references'])\\n query_str_dict['links'] = links\\n\\n # query_str_encode = str(query_str_dict).encode('base64', 'strict')\\n q_eed = base64.urlsafe_b64encode(json.dumps(query_str_dict).encode()).decode()\\n\\n full_url = f\\\"{self.dict['generate_url']}{self.readme_survey_id}?\\\" + \\\\\\n 'Q_EED=' + q_eed\\n\\n return full_url\",\n \"def _get_first_author(self):\\n if not len(self.get_authors()):\\n return ''\\n return self.get_authors()[0]\",\n \"def subject_info(intent, extra_info=[]):\\n\\n text = intent['inputTranscript'].lower()\\n utterances = AS.load_file('sample_utterances.txt')\\n\\n # add \\\"book\\\" and \\\"books\\\" to every utterance\\n for line in list(utterances):\\n utterances.insert(0, line + \\\" book\\\")\\n utterances.insert(0, line + \\\" books\\\")\\n\\n # tells how many characters needs to be dropped before the subject starts\\n to_drop = 0\\n\\n for line in utterances:\\n if text.startswith(line):\\n to_drop = len(line)\\n break\\n\\n # drops the characters and makes a list from the strings that are left\\n text = text[to_drop:].strip()\\n text_list = text.split(' ', len(text))\\n\\n subject_list = []\\n keywords = [\\\"books\\\", \\\"book\\\", \\\"by\\\", \\\"published\\\", \\\"written\\\"]\\n keyword = \\\"\\\"\\n\\n # Find out when the book name ends\\n for word in text_list:\\n if word not in keywords:\\n subject_list.append(word)\\n else:\\n break\\n\\n subject = \\\" \\\".join(subject_list)\\n\\n # Get all the keywords in the middle, so they can be\\n # all be dropped at once, eg written by, books by\\n text_list = text_list[len(subject_list):]\\n if text_list:\\n word = text_list[0]\\n while word in keywords:\\n keyword += word + \\\" \\\"\\n text_list = text_list[1:]\\n if text_list:\\n word = text_list[0]\\n else:\\n break\\n\\n # search for an author from the rest of the characters\\n author_text = text[len(keyword):].strip()\\n author = AS.search(author_text, False)\\n if author is \\\"\\\":\\n author = None\\n\\n # There might be old info in the extra_info (author), so \\n # we need to clear it\\n extra_info.clear()\\n\\n # add the author to extra info so it can be used in the Finna API call\\n if author:\\n extra_info += [\\\"author:\\\\\\\"\\\" + author + \\\"\\\\\\\"\\\"]\\n elif intent['sessionAttributes'].get('author'):\\n extra_info += [\\n \\\"author:\\\\\\\"\\\" + intent['sessionAttributes']['author'] + \\\"\\\\\\\"\\\"\\n ]\\n\\n # The Finna API call\\n request = lookfor(term=subject, filter=extra_info)['json']\\n\\n return parse_subject(request, subject, {'author': author})\",\n \"def citation(self, citation):\\n\\n self._citation = citation\",\n \"def AuthorURLs(entry):\\n a_URLs = ''\\n for a in entry.getAuthors():\\n url = a.get('homepage', ' ')\\n a_URLs += \\\"%s and \\\" % url\\n return a_URLs[:-5]\",\n \"def add_ref(doc_name, bib_name, keep_label=False, slides=False):\\n bib_path = bib_name # os.path.join(static_path, \\\"tex\\\", bib_name)\\n if not slides:\\n keep_label = True\\n with open(doc_name, \\\"r\\\") as f:\\n _file = f.read()\\n # find citations\\n match = re.findall(r\\\"\\\\[@.*?\\\\]\\\", _file)\\n references = []\\n # print(match)\\n for cit in match:\\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\\\".html\\\", delete=True)\\n tmp = tempfile.NamedTemporaryFile(suffix=\\\".md\\\", delete=True)\\n with open(tmp.name, \\\"w\\\") as md_file:\\n # Open the file for writing.\\n md_file.write(cit)\\n\\n pandoc_command = [\\n \\\"pandoc\\\",\\n \\\"-C\\\",\\n tmp.name,\\n \\\"--bibliography\\\",\\n bib_path,\\n \\\"--csl\\\",\\n \\\"./templates/my-csl.csl\\\",\\n \\\"-o\\\",\\n tmp_cite_html.name,\\n ]\\n if not slides:\\n for tag in [\\\"--metadata\\\", \\\"link-citations=true\\\"]:\\n pandoc_command.append(tag)\\n output = subprocess.check_output(\\n pandoc_command, stderr=subprocess.STDOUT\\n ).decode(\\\"utf-8\\\")\\n print(output.rstrip())\\n tmp.close()\\n with open(tmp_cite_html.name, \\\"r\\\") as cite_html:\\n # Open the file for writing.\\n cit_new = cite_html.read()\\n # print(cit_new)\\n if not keep_label:\\n # remove first line\\n cit_new = \\\"\\\\n\\\".join(cit_new.splitlines()[1:])\\n else:\\n lines = cit_new.splitlines()\\n # remove the <p> tags\\n lines[0] = lines[0][3:-4]\\n cit_new = \\\"\\\\n\\\".join(lines)\\n if slides:\\n _file = _file.replace(cit, cit_new)\\n else:\\n _file = _file.replace(cit, lines[0])\\n # collect the references\\n references.append(\\\"<p>\\\")\\n references.append(\\\"\\\\n\\\".join(lines))\\n references.append(\\\"</p>\\\")\\n # paste_refs_end()\\n tmp_cite_html.close()\\n if slides:\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n if not slides:\\n if references == []:\\n _file=clean_html_refs(_file)\\n else:\\n _file = _file.replace(\\\"<bibliography-placeholder>\\\", \\\"\\\\n\\\".join(references))\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n return\",\n \"def citeproc(style, reference_list):\\n pass\",\n \"def test_author_string(self):\\n self.assertNotEqual(self.module.__author__, '???')\",\n \"def fetch_arxiv_bibtex(fp, info=None):\\n info = info if info else is_arxiv(fp)\\n\\n if info:\\n cat, num = info\\n\\n # Successful. Now fetch the BiBTeX.\\n page = urlopen('http://adsabs.harvard.edu/cgi-bin/bib_query?'\\n 'arXiv:{}{}'.format(cat + '/' if cat else '',\\n num)).read()\\n soup = BeautifulSoup(page, 'html5lib')\\n el = soup.find('a', text='Bibtex entry for this abstract', href=True)\\n href = urlopen(el['href']).read().decode()\\n\\n # Skip until the first '@', which should mark the beginning of the\\n # BiBTeX.\\n return '@' + '@'.join(href.split('@')[1:])\\n return None\",\n \"def setAuthor(self,value):\\n self.PDFreactorConfiguration.in1[\\\"author\\\"] = value\",\n \"def catalogue(self, fix_author=True):\\n response = requests.get(CATALOGUE_URL)\\n\\n flags = DOTALL | UNICODE\\n tables = findall(r'<table.*?</table>', response.text, flags=flags)\\n rows = findall(r'<tr.*?</tr>', tables[1], flags=flags)\\n\\n books = []\\n for row in rows[1:]:\\n elements = findall('<td.*?</td>', row, flags=flags)\\n book_id, title = findall(r'/(.*?)/\\\">(.*?)<',\\n elements[4], flags=flags)[0]\\n try:\\n author_id, author = findall(r'/authors/(.*?).html\\\">(.*?)<',\\n elements[6], flags=flags)[0]\\n except:\\n author_id, author = '', ''\\n if fix_author:\\n # fix_author name collision. TODO\\n author = globals()['fix_author'](author)\\n book = {\\n 'type': findall(r'alt=\\\"(.*?)\\\">', elements[0], flags=flags)[0],\\n 'book_id': book_id,\\n 'title': title,\\n 'author_id': author_id,\\n 'author': author,\\n 'year': elements[8][15:-5],\\n 'language': elements[10][-9:-7]\\n }\\n books.append(book)\\n return DataFrame(books)\",\n \"def parse_references(article):\\n reference_list = []\\n references = article.find(\\\"text\\\").find(\\\"div\\\", attrs={\\\"type\\\": \\\"references\\\"})\\n references = references.find_all(\\\"biblstruct\\\") if references is not None else []\\n reference_list = []\\n for reference in references:\\n title = reference.find(\\\"title\\\", attrs={\\\"level\\\": \\\"a\\\"})\\n if title is None:\\n title = reference.find(\\\"title\\\", attrs={\\\"level\\\": \\\"m\\\"})\\n title = title.text if title is not None else \\\"\\\"\\n journal = reference.find(\\\"title\\\", attrs={\\\"level\\\": \\\"j\\\"})\\n journal = journal.text if journal is not None else \\\"\\\"\\n if journal is \\\"\\\":\\n journal = reference.find(\\\"publisher\\\")\\n journal = journal.text if journal is not None else \\\"\\\"\\n year = reference.find(\\\"date\\\")\\n year = year.attrs.get(\\\"when\\\") if year is not None else \\\"\\\"\\n authors = []\\n for author in reference.find_all(\\\"author\\\"):\\n firstname = author.find(\\\"forename\\\", {\\\"type\\\": \\\"first\\\"})\\n firstname = firstname.text.strip() if firstname is not None else \\\"\\\"\\n middlename = author.find(\\\"forename\\\", {\\\"type\\\": \\\"middle\\\"})\\n middlename = middlename.text.strip() if middlename is not None else \\\"\\\"\\n lastname = author.find(\\\"surname\\\")\\n lastname = lastname.text.strip() if lastname is not None else \\\"\\\"\\n if middlename is not \\\"\\\":\\n authors.append(firstname + \\\" \\\" + middlename + \\\" \\\" + lastname)\\n else:\\n authors.append(firstname + \\\" \\\" + lastname)\\n authors = \\\"; \\\".join(authors)\\n reference_list.append(\\n {\\\"title\\\": title, \\\"journal\\\": journal, \\\"year\\\": year, \\\"authors\\\": authors}\\n )\\n return reference_list\",\n \"def __citation_correction(self, bs, ground_truth):\\n bs_ref = bs.findNext('bibl')\\n gt_ref = ground_truth.findNext('ref')\\n while gt_ref is not None:\\n if gt_ref.find('article-title') != bs_ref.title:\\n pass\\n gt_ref = gt_ref.findNext('ref')\",\n \"def fix_errors_in_citation(citation):\\n result = regex.sub(r\\\"\\\\s+\\\", \\\" \\\", citation)\\n result = regex.sub(r\\\"§(?=\\\\d)\\\", \\\"§ \\\", result)\\n result = regex.sub(r\\\",\\\\sbis\\\\s\\\", \\\" bis \\\", result)\\n return result\",\n \"def test_author_simple(self):\\n invenio_search = 'author:\\\"ellis, j*\\\"'\\n spires_search = 'find a ellis, j'\\n self._compare_searches(invenio_search, spires_search)\",\n \"def get_authors():\\n authors = []\\n authorfile = os.path.join('doc', 'authors.txt')\\n with codecs.open(authorfile, 'r', 'utf-8') as f:\\n for line in f:\\n line = line.strip()\\n if line and not line.startswith(u'#'):\\n authors.append(line)\\n return u\\\", \\\".join(authors)\",\n \"def parsed2Bibtex(parsed):\\n bibtex = '@'+parsed['ENTRYTYPE']+'{'+parsed['ID']+\\\",\\\\n\\\"\\n\\n for field in [i for i in sorted(parsed) if i not in ['ENTRYTYPE', 'ID']]:\\n bibtex += \\\"\\\\t\\\"+field+\\\"={\\\"+parsed[field]+\\\"},\\\\n\\\"\\n bibtex += \\\"}\\\\n\\\\n\\\"\\n return bibtex\",\n \"def sanitize_author(name, email):\\n # deal with inconsistent email addresses/names in commits.\\n # feel free to fill this method out.\\n return name\",\n \"def test_citations_and_toc_2(self):\\n settings = get_settings(\\n PANDOC_EXTENSIONS=PANDOC_EXTENSIONS + [\\\"+citations\\\"],\\n PANDOC_ARGS=PANDOC_ARGS\\n + [\\n \\\"--table-of-contents\\\",\\n \\\"--citeproc\\\",\\n \\\"--csl=https://www.zotero.org/styles/ieee-with-url\\\",\\n \\\"--metadata=link-citations:false\\\",\\n \\\"--metadata=reference-section-title:References\\\",\\n ],\\n FORMATTED_FIELDS=FORMATTED_FIELDS,\\n )\\n\\n pandoc_reader = PandocReader(settings)\\n source_path = os.path.join(\\n TEST_CONTENT_PATH, \\\"valid_content_with_citation.md\\\"\\n )\\n output, metadata = pandoc_reader.read(source_path)\\n self.maxDiff = None\\n\\n self.assertEqual(\\n (\\n '<h2 id=\\\"string-theory\\\">String Theory</h2>\\\\n'\\n \\\"<p>But this foundational principle of science has\\\"\\n \\\" now been called into question by\\\"\\n ' <a href=\\\"https://www.britannica.com/science/'\\n 'string-theory\\\">String Theory</a>,'\\n \\\" which is a relative newcomer to theoretical physics, but one\\\"\\n \\\" that has captured the common imagination, judging by\\\"\\n \\\" the popular explanations that abound on the Web\\\"\\n ' <span class=\\\"citation\\\" data-cites=\\\"mann2019 wood2019'\\n ' jones2020\\\">[1]–[3]</span>.'\\n \\\" And whether string theory is or is not science, Popper\\\"\\n \\\" notwithstanding, is an issue that is still up for debate\\\"\\n \\\" <span\\\"\\n ' class=\\\"citation\\\" data-cites=\\\"siegel2015 castelvecchi2016'\\n ' alves2017 francis2019\\\">[4]–[7]</span>.</p>\\\\n'\\n '<h1 class=\\\"unnumbered\\\" id=\\\"bibliography\\\">References</h1>\\\\n'\\n '<div id=\\\"refs\\\" class=\\\"references csl-bib-body\\\"'\\n ' role=\\\"doc-bibliography\\\">\\\\n'\\n '<div id=\\\"ref-mann2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[1]'\\n ' </div><div class=\\\"csl-right-inline\\\">A. Mann,'\\n \\\" <span>“<span>What Is String Theory?</span>”</span>\\\"\\n \\\" 20-Mar-2019. [Online].\\\"\\n ' Available: <a href=\\\"https://www.livescience.com/'\\n '65033-what-is-string-theory.html\\\">'\\n \\\"https://www.livescience.com/\\\"\\n \\\"65033-what-is-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-wood2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[2] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n \\\"C. Wood, <span>“<span>What Is String Theory?</span>.\\\"\\n \\\" Reference article:\\\"\\n \\\" A simplified explanation and brief history of string\\\"\\n \\\" theory,”</span> 11-Jul-2019.\\\"\\n ' [Online]. Available: <a href=\\\"https://www.space.com/'\\n '17594-string-theory.html\\\">'\\n \\\"https://www.space.com/17594-string-theory.html</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-jones2020\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[3]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'A. Z. Jones, <span>“<span class=\\\"nocase\\\">The Basics of String'\\n \\\" Theory</span>,”</span> 02-Mar-2019. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.thoughtco.com/'\\n 'what-is-string-theory-2699363\\\">'\\n \\\"https://www.thoughtco.com/what-is-string-theory-2699363</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-siegel2015\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[4]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n \\\"E. Siegel, <span>“<span>Why String Theory Is Not A Scientific\\\"\\n \\\" Theory</span>,”</span> 23-Dec-2015. [Online]. Available:\\\"\\n \\\" <a\\\"\\n ' href=\\\"https://www.forbes.com/sites/'\\n \\\"startswithabang/2015/12/23/\\\"\\n 'why-string-theory-is-not-science/\\\">https://www.forbes.com/'\\n \\\"sites/startswithabang/2015/12/23/\\\"\\n \\\"why-string-theory-is-not-science/</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-castelvecchi2016\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[5]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'D. Castelvecchi, <span>“<span class=\\\"nocase\\\">'\\n \\\"Feuding physicists turn\\\"\\n \\\" to philosophy for help</span>. String theory is at the\\\"\\n \\\" heart of a debate over the integrity of the scientific\\\"\\n \\\" method itself,”</span> 05-Jan-2016. [Online]. Available:\\\"\\n ' <a href=\\\"https://www.nature.com/news/'\\n 'feuding-physicists-turn-to-philosophy-for-help-1.19076\\\">'\\n \\\"https://www.nature.com/news/\\\"\\n \\\"feuding-physicists-turn-to-philosophy-for-help-1.19076</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-alves2017\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[6] </div>'\\n '<div class=\\\"csl-right-inline\\\">'\\n 'R. A. Batista and J. Primack, <span>“<span class=\\\"nocase\\\">'\\n \\\"Is String theory falsifiable?</span>. Can a theory that isn’t\\\"\\n \\\" completely testable still be useful to physics?”</span>\\\"\\n \\\" [Online].\\\"\\n ' Available: <a href=\\\"https://metafact.io/factchecks/'\\n '30-is-string-theory-falsifiable\\\">'\\n \\\"https://metafact.io/factchecks/\\\"\\n \\\"30-is-string-theory-falsifiable</a>.\\\"\\n \\\" [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n '<div id=\\\"ref-francis2019\\\" class=\\\"csl-entry\\\"'\\n ' role=\\\"doc-biblioentry\\\">\\\\n'\\n '<div class=\\\"csl-left-margin\\\">[7]'\\n ' </div><div class=\\\"csl-right-inline\\\">'\\n 'M. R. Francis, <span>“<span class=\\\"nocase\\\">Falsifiability and'\\n \\\" physics</span>. Can a theory that isn’t completely testable\\\"\\n \\\" still be useful to physics?”</span> 23-Apr-2019.\\\"\\n \\\" [Online]. Available:\\\"\\n ' <a href=\\\"https://www.scientificamerican.com/'\\n 'article/is-string-theory-science/\\\">'\\n \\\"https://www.scientificamerican.com/article/is-\\\"\\n \\\"string-theory-science/</a>. [Accessed: 12-Nov-2020]</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n \\\"</div>\\\\n\\\"\\n ),\\n output,\\n )\\n\\n self.assertEqual(\\\"Valid Content With Citation\\\", str(metadata[\\\"title\\\"]))\\n self.assertEqual(\\\"My Author\\\", str(metadata[\\\"author\\\"]))\\n self.assertEqual(\\\"2020-10-16 00:00:00\\\", str(metadata[\\\"date\\\"]))\\n self.assertEqual(\\n (\\n '<nav class=\\\"toc\\\" role=\\\"doc-toc\\\">\\\\n'\\n \\\"<ul>\\\\n\\\"\\n '<li><a href=\\\"#string-theory\\\">String Theory</a></li>\\\\n'\\n '<li><a href=\\\"#bibliography\\\">References</a></li>\\\\n'\\n \\\"</ul>\\\\n</nav>\\\\n\\\"\\n ),\\n str(metadata[\\\"toc\\\"]),\\n )\",\n \"def _parse_email_bib_data(cls, bib_data):\\n pub_title = None\\n pub_year = None\\n\\n # Get author name(s)\\n parsed_bib = bib_data.split(\\\" - \\\")\\n m_author = _utils.clean_string(parsed_bib[0])\\n\\n # Split further to get year and author\\n if len(parsed_bib) > 1:\\n parsed_b2 = parsed_bib[1].split(',')\\n\\n if len(parsed_b2) == 2:\\n pub_title = _utils.clean_string(parsed_b2[0])\\n try:\\n pub_year = int(_utils.clean_string(parsed_b2[1]))\\n except ValueError:\\n pub_year = None\\n\\n else:\\n try:\\n pub_year = int(_utils.clean_string(parsed_b2[0]))\\n except ValueError:\\n pub_year = None\\n pub_title = _utils.clean_string(parsed_b2[0])\\n\\n return {\\n 'author': m_author,\\n 'pub_title': pub_title,\\n 'pub_year': pub_year\\n }\",\n \"def write_citation_page(refdict: dict) -> None:\\n with open(WEBOUT_PATH + init_data().cite_url, \\\"w\\\", encoding=\\\"utf-8\\\") as outfile:\\n common_html_header(outfile, \\\"Fiddler Crab Website Citation\\\")\\n outfile.write(\\\" <header id=\\\\\\\"\\\" + init_data().cite_url + \\\"\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <h1>Citation Info</h1>\\\\n\\\")\\n outfile.write(\\\" </header>\\\\n\\\")\\n outfile.write(\\\"\\\\n\\\")\\n outfile.write(\\\" <p>\\\\n\\\")\\n outfile.write(\\\" Generally it is best to cite the primary literature, whenever possible. However, the \\\"\\n \\\"following paper describes much of the data that is unique to this website:\\\\n\\\")\\n outfile.write(\\\" </p>\\\\n\\\")\\n outfile.write(\\\" <div class=\\\\\\\"reference_list\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <ul>\\\\n\\\")\\n ref = refdict[\\\"Rosenberg2014\\\"] # citation describing the database\\n outfile.write(\\\" <li><a href=\\\\\\\"references/Rosenberg2014.html\\\\\\\">\\\" + ref.formatted_html + \\\"</a></li>\\\\n\\\")\\n outfile.write(\\\" </ul>\\\\n\\\")\\n outfile.write(\\\" </div>\\\\n\\\")\\n outfile.write(\\\" <ul class=\\\\\\\"fa-ul\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <li>\\\" + fetch_fa_glyph(\\\"list pdf\\\") +\\n \\\"<a href=\\\\\\\"https://dx.plos.org/10.1371/journal.pone.0101704\\\\\\\">Read paper online at \\\"\\n \\\"PLoS ONE</a></li>\\\\n\\\")\\n outfile.write(\\\" <li>\\\" + fetch_fa_glyph(\\\"list github\\\") +\\n \\\"<a href=\\\\\\\"https://github.com/msrosenberg/fiddlercrab.info\\\\\\\">Website data repository on \\\"\\n \\\"GitHub</a></li>\\\\n\\\")\\n outfile.write(\\\" </ul>\\\\n\\\")\\n common_html_footer(outfile)\",\n \"def store_name(author):\\n with open(\\\"ref.txt\\\",\\\"a\\\") as fp:\\n fp.write(str(reference)+\\\"\\\"+'\\\\n')\",\n \"async def to_full_pdf_url(self, client_session=None):\\n doi_url = \\\"https://doi.org/{}\\\".format(self.doi)\\n publisher = None\\n\\n class _PublisherFound(Exception):\\n pass\\n # First item is the regex to match against.\\n # Second item is the string to check the matched group for.\\n publisherRegex = {\\n 'wiley': [re.compile(r\\\"\\\"\\\"<meta name=[\\\"']citation_publisher[\\\"']\\\\s+content=[\\\"'](.+?)[\\\"']\\\\s*/?>\\\"\\\"\\\"),\\n \\\"John Wiley\\\"],\\n 'elsevier': [re.compile(r\\\"\\\"\\\"<input type=\\\"hidden\\\" name=\\\"redirectURL\\\" value=\\\"https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2F(.+?)%3Fvia%253Dihub\\\" id=\\\"redirectURL\\\"/>\\\"\\\"\\\"),\\n \\\"\\\"],\\n 'tandf': [re.compile(r\\\"\\\"\\\"<meta name=[\\\"']dc.Publisher[\\\"']\\\\s+content=[\\\"'](.+?)[\\\"']\\\\s*/?>\\\"\\\"\\\"),\\n \\\"Taylor\\\"],\\n 'annrev': [re.compile(r\\\"\\\"\\\"<meta name=[\\\"']dc.Publisher[\\\"']\\\\s+content=[\\\"'](.+?)[\\\"']\\\\s*/?>\\\"\\\"\\\"),\\n \\\"Annual Reviews\\\"],\\n 'rsc': [re.compile(r\\\"\\\"\\\"<meta content=[\\\"']https://pubs.rsc.org/en/content/articlepdf/(.+?)[\\\"']\\\\s+name=\\\"citation_pdf_url\\\"\\\\s*/>\\\"\\\"\\\"),\\n \\\"\\\"],\\n }\\n publisherFmtStrings = {\\n \\\"acs\\\": \\\"https://pubs.acs.org/doi/pdf/{}\\\",\\n \\\"wiley\\\": \\\"https://onlinelibrary.wiley.com/doi/pdfdirect/{}\\\",\\n \\\"elsevier\\\": \\\"https://www.sciencedirect.com/science/article/pii/{}/pdfft\\\",\\n \\\"nature\\\": \\\"https://www.nature.com/articles/{}.pdf\\\",\\n \\\"science\\\": \\\"https://science.sciencemag.org/content/sci/{}.full.pdf\\\",\\n \\\"springer\\\": \\\"https://link.springer.com/content/pdf/{}.pdf\\\",\\n \\\"tandf\\\": \\\"https://www.tandfonline.com/doi/pdf/{}\\\",\\n \\\"annrev\\\": \\\"https://www.annualreviews.org/doi/pdf/{}\\\",\\n \\\"rsc\\\": \\\"https://pubs.rsc.org/en/content/articlepdf/{}\\\",\\n }\\n\\n # Create a new ClientSession if one wasn't provided\\n if client_session is None:\\n # Make sure we have a polite header, though.\\n session = aiohttp.ClientSession(headers=_g.httpHeaders)\\n else:\\n session = client_session\\n try:\\n async with session.get(doi_url) as resp:\\n # Shortcut for ACS, don't need to read content\\n if any(\\\"pubs.acs.org\\\" in h\\n for h in resp.headers.getall(\\\"Set-Cookie\\\", [])):\\n publisher = \\\"acs\\\"\\n identifier = self.doi\\n raise _PublisherFound\\n # Shortcut for Nature, don't need to read content\\n elif any(\\\"www.nature.com\\\" in h\\n for h in resp.headers.getall(\\\"X-Forwarded-Host\\\", [])):\\n publisher = \\\"nature\\\"\\n identifier = self.doi.split('/', maxsplit=1)[1]\\n raise _PublisherFound\\n # Shortcut for Science, don't need to read content.\\n # Note that this doesn't work for Sci Advances\\n elif any(\\\"science.sciencemag.org\\\" in h\\n for h in resp.headers.getall(\\\"Link\\\", [])):\\n publisher = \\\"science\\\"\\n identifier = resp.headers[\\\"Link\\\"].split(\\\">\\\")[0].split(\\\"/content/\\\")[1]\\n raise _PublisherFound\\n # Shortcut for Springer\\n elif any(\\\".springer.com\\\" in h\\n for h in resp.headers.getall(\\\"Set-Cookie\\\", [])):\\n publisher = \\\"springer\\\"\\n identifier = self.doi\\n raise _PublisherFound\\n # Shortcut for Taylor and Francis\\n elif any(\\\".tandfonline.com\\\" in h\\n for h in resp.headers.getall(\\\"Set-Cookie\\\", [])):\\n publisher = \\\"tandf\\\"\\n identifier = self.doi\\n raise _PublisherFound\\n # Otherwise, start reading the content\\n else:\\n e = resp.get_encoding()\\n async for line in resp.content:\\n line = line.decode(e) # it's read as bytes\\n # Search the line for every regex\\n for pname, regexKeyword in publisherRegex.items():\\n match = regexKeyword[0].search(line)\\n if match and regexKeyword[1] in match.group(1):\\n publisher = pname\\n if publisher in [\\\"wiley\\\", \\\"tandf\\\", \\\"annrev\\\"]:\\n identifier = self.doi\\n elif publisher in [\\\"elsevier\\\"]:\\n identifier = match.group(1)\\n elif publisher in [\\\"rsc\\\"]:\\n identifier = match.group(1)\\n raise _PublisherFound\\n except (aiohttp.client_exceptions.ContentTypeError,\\n aiohttp.client_exceptions.InvalidURL,\\n aiohttp.client_exceptions.ClientConnectorError):\\n result = _error(f\\\"to_full_pdf_url: URL '{url_doi}' not accessible.\\\"\\n f\\\" Do you have access to the full text?\\\")\\n except _PublisherFound:\\n result = publisherFmtStrings[publisher].format(identifier)\\n else:\\n result = _error(f\\\"to_full_pdf_url: could not find full text for \\\"\\n f\\\"doi {self.doi}\\\")\\n\\n # Close the ClientSession if it was newly opened\\n if client_session is None:\\n await session.close()\\n return result\",\n \"def alt_authors(self, key, value):\\n _authors = self.get(\\\"authors\\\", [])\\n if _authors:\\n for i, v in enumerate(force_list(value)):\\n _authors[i].update({\\\"alternative_names\\\": clean_val(\\\"a\\\", v, str)})\\n return _authors\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.728667","0.68427366","0.68227404","0.66083246","0.65711814","0.6367512","0.6355733","0.6156344","0.61316967","0.6123189","0.6094504","0.6091088","0.60479695","0.5990289","0.59520656","0.5934677","0.5889932","0.5889375","0.58619887","0.5843337","0.5815948","0.5809036","0.57780355","0.5751395","0.57281494","0.5726748","0.5709306","0.57038987","0.5696522","0.566002","0.56414557","0.5640532","0.5588431","0.55863297","0.5585568","0.55845046","0.5557143","0.5553916","0.55260295","0.55088896","0.54953915","0.54743165","0.546861","0.5448022","0.54137415","0.54126513","0.54058903","0.5389149","0.5367965","0.53614885","0.53541064","0.53425205","0.5329973","0.5317503","0.53008324","0.529575","0.52791953","0.527471","0.52685434","0.52618897","0.5248913","0.522704","0.521995","0.52171654","0.52116156","0.5210228","0.5205485","0.5199473","0.51916","0.5181915","0.5179998","0.51755846","0.51746386","0.5171904","0.51582605","0.51496536","0.5143424","0.5141007","0.51358837","0.51357615","0.51346517","0.5125666","0.51197636","0.51185876","0.5116117","0.5113173","0.50997955","0.50898314","0.50845087","0.5080514","0.50754654","0.50749075","0.50749004","0.50740147","0.5071052","0.50653476","0.50511277","0.5047865","0.5046557","0.504653"],"string":"[\n \"0.728667\",\n \"0.68427366\",\n \"0.68227404\",\n \"0.66083246\",\n \"0.65711814\",\n \"0.6367512\",\n \"0.6355733\",\n \"0.6156344\",\n \"0.61316967\",\n \"0.6123189\",\n \"0.6094504\",\n \"0.6091088\",\n \"0.60479695\",\n \"0.5990289\",\n \"0.59520656\",\n \"0.5934677\",\n \"0.5889932\",\n \"0.5889375\",\n \"0.58619887\",\n \"0.5843337\",\n \"0.5815948\",\n \"0.5809036\",\n \"0.57780355\",\n \"0.5751395\",\n \"0.57281494\",\n \"0.5726748\",\n \"0.5709306\",\n \"0.57038987\",\n \"0.5696522\",\n \"0.566002\",\n \"0.56414557\",\n \"0.5640532\",\n \"0.5588431\",\n \"0.55863297\",\n \"0.5585568\",\n \"0.55845046\",\n \"0.5557143\",\n \"0.5553916\",\n \"0.55260295\",\n \"0.55088896\",\n \"0.54953915\",\n \"0.54743165\",\n \"0.546861\",\n \"0.5448022\",\n \"0.54137415\",\n \"0.54126513\",\n \"0.54058903\",\n \"0.5389149\",\n \"0.5367965\",\n \"0.53614885\",\n \"0.53541064\",\n \"0.53425205\",\n \"0.5329973\",\n \"0.5317503\",\n \"0.53008324\",\n \"0.529575\",\n \"0.52791953\",\n \"0.527471\",\n \"0.52685434\",\n \"0.52618897\",\n \"0.5248913\",\n \"0.522704\",\n \"0.521995\",\n \"0.52171654\",\n \"0.52116156\",\n \"0.5210228\",\n \"0.5205485\",\n \"0.5199473\",\n \"0.51916\",\n \"0.5181915\",\n \"0.5179998\",\n \"0.51755846\",\n \"0.51746386\",\n \"0.5171904\",\n \"0.51582605\",\n \"0.51496536\",\n \"0.5143424\",\n \"0.5141007\",\n \"0.51358837\",\n \"0.51357615\",\n \"0.51346517\",\n \"0.5125666\",\n \"0.51197636\",\n \"0.51185876\",\n \"0.5116117\",\n \"0.5113173\",\n \"0.50997955\",\n \"0.50898314\",\n \"0.50845087\",\n \"0.5080514\",\n \"0.50754654\",\n \"0.50749075\",\n \"0.50749004\",\n \"0.50740147\",\n \"0.5071052\",\n \"0.50653476\",\n \"0.50511277\",\n \"0.5047865\",\n \"0.5046557\",\n \"0.504653\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5731608"},"document_rank":{"kind":"string","value":"24"}}},{"rowIdx":25690,"cells":{"query":{"kind":"string","value":"Load the CMIP6 experiment description."},"document":{"kind":"string","value":"def __init__(self):\n # simple header only necessary for this table of MIPs\n self.header = '<tr class=\"ename\"><td colspan=\"1\">{{d.name}} ({{mips}})</td></tr>'\n self.mips = 'core MIPS recorded by ES-DOC'\n self._settemplates(self.onecol, self.twocol)\n\n r = Repo()\n c = r.getbyname('CMIP6', 'mips')\n self.doc = c\n self.related = []\n\n # two properties to help the use of the resulting table in a paper\n self.reference_list = []\n # nocite list intended for cutting and pasting directly into a latex document!\n self.nocite = ''\n\n for m in c.sub_projects:\n mdoc = r.getbyname(m.name, 'mips')\n description = mdoc.long_name+' - '\n citations = []\n\n # for these purposees we only want the things with a doi\n # and we want only one, so we have to develop a heuristic to get the right one\n for ci in mdoc.citations:\n cidoc = esd.retrieve(ci.id)\n ref = Reference(cidoc)\n if ref.populated:\n citations.append(ref)\n citations.sort(key=lambda cc: cc.year)\n index = -1\n if len(citations) > 1:\n # start by getting the most recent\n year = citations[-1].year\n index = -1\n for i in range(len(citations)-1):\n if citations[i].year == year:\n if m.name in citations[i].text:\n # it's one of the most recent and it has the MIP name\n # in the document title.\n index = i\n description += citations[index].citestring\n self.reference_list.append(citations[index].text)\n self.nocite += '\\\\nocite{%s}\\n' % citations[index].citeguess\n\n # overwrite the real description for the purpose of this table\n mdoc.description = description\n self.related.append(mdoc)\n\n # want alphabetical order\n self.related.sort(key=lambda mm: mm.name)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def testCMIP6(self):\n\n c = CMIP6()\n c.render(self.testoutput[3])\n for r in c.reference_list:\n print r\n print c.nocite","def test_load_from_v6(self) -> None:\n self.save_new_valid_exploration(\n 'Exp1', 'user@example.com', end_state_name='End')\n collection = collection_domain.Collection.from_yaml(\n 'cid', self.YAML_CONTENT_V6)\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)","def load_sas_desc_file(input_data):\n # parse description file\n i94_desc_path = os.path.join(input_data, 'I94_SAS_Labels_Descriptions.SAS')\n with open(i94_desc_path) as f:\n lines = f.readlines()\n i94_desc_string = ''.join(lines)\n i94_desc_string = i94_desc_string.replace('\\n', '')\n i94_desc_string = i94_desc_string.replace('\\t', '')\n logging.info('SAS description file successfully processed')\n return i94_desc_string","def loadTutorialSuit():\n loader.loadModelNode(\"phase_3.5/models/char/suitC-mod\")\n loadDialog(1)","def load_interface_details(self):\n for line in self.ShowInterfacePerInt:\n if line.find('Description:') >= 0:\n self.InterfaceDescription = line.replace('Description:', '')\n elif line.find('packets input') >= 0:\n self.PacketsInput = int(line.split()[0])\n elif line.find('packets output') >= 0:\n self.PacketsOutput = int(line.split()[0])\n elif line.find('line protocol') >= 0:\n self.LineProtocol = line\n elif line.find('Last clearing of') >= 0:\n self.LastClearing = line.split()[-1]\n\n for line in self.ShowInterfaceSwitchportPerInt:\n if line.find('Administrative Mode:') >= 0:\n self.AdministrativeMode = line[20:].strip()\n elif line.find('Access Mode VLAN:') >= 0:\n self.AccessModeVlan = line.split()[3]\n elif line.find('Voice VLAN:') >= 0:\n self.VoiceVlan = line.split()[2]\n\n for line in self.ShowInterfaceCapabilitiesPerInt:\n if line.find('Type:') >= 0:\n self.Type = line.split(\":\")[1].strip()","def get_description(self):\n return self.bot_data_file[\"description\"]","def _load_robot_description(self):\n name = \"robot_description\" # self._widget.robot_description_edit.text()\n self._robot_description_xml_root = None\n try:\n xml = rospy.get_param(name)\n self._robot_description_xml_root = ET.fromstring(xml)\n except KeyError as e:\n rospy.logerr(\n \"Failed to get robot description from param %s : %s\" % (name, e))\n return\n except:\n raise","def load_eli5(self, opt):\n dp = opt['datapath']\n dt = opt['datatype'].split(':')[0]\n eli_path = \"eli5/processed_data/selected_15_1/explainlikeimfive_\"\n fname = os.path.join(dp, eli_path + dt + \".json\")\n if not PathManager.exists(fname):\n raise FileNotFoundError(\n f\"{fname} not found. Please follow the instructions found at \"\n \"https://github.com/facebookresearch/ParlAI/tree/main/parlai/tasks/eli5/README.md\"\n \" to construct the dataset.\"\n )\n opt['datafile'] = fname\n with PathManager.open(fname) as json_file:\n data = json.load(json_file)\n ds = []\n for d in data:\n if self.opt['knowledge']:\n text = d['document'] + \"\\n\" + d['question']\n else:\n text = d['question']\n act = {\n 'id': 'eli5',\n 'text': text,\n 'labels': [d['answer']],\n 'episode_done': True,\n }\n ds.append(act)\n return ds","def description(self):\n if self._description is None:\n self._load()\n return self._description","def update_experiment_description(self, experiment_id, description):\n return self.dbclient.update_by_id(Tables.EXPERIMENTS, experiment_id, {\n ExperimentAttr.DESC: description\n })","def load_description():\n with open('description.txt') as description:\n return [line.strip() for line in description]","def load(self):\n self.data = NSPSpecIO().read(self.path)","def load_experiment(self):\n load_dir = select_dir(os.getcwd())\n if load_dir is not None:\n if os.path.isfile(os.path.join(load_dir, 'conf', 'config')):\n self.load_main(load_dir)\n else:\n msg_window('missing conf/config file, not experiment directory')\n return\n\n if self.t is None:\n self.t = Tabs(self)\n self.vbox.addWidget(self.t)\n self.t.clear_configs()\n self.t.load_conf(load_dir)\n\n self.set_experiment(True)\n else:\n msg_window('please select valid conf directory')","def load(self, path):\n with open(path, 'rb') as fp:\n me = pickle.load(fp)\n self.exp = me[\"exp\"] # type: Experiment\n with suppress_errors(\"output root directory may have changed\"):\n self.mru_exp_root = self.exp.root\n self.chdir()\n self.imdb = self.exp.imdb\n self.exp_df = me[\"exp_df\"]\n with suppress_errors(\"caffenet may no longer exist\"):\n self.caffenet = self.exp.caffenet\n with suppress_errors(\"caffemodel may no longer exist\"):\n self.caffemodel = self.exp.caffemodel\n with suppress_errors(\"data directory may have changed\"):\n self.mru_exp_data = self.exp.data\n self.lbl_exp_data.setText(self.mru_exp_data)\n self.edt_caffemodel.setText(self.caffemodel)\n self.edt_caffenet.setText(self.caffenet)\n self.lbl_exp_data.setText(self.mru_exp_data)\n if self.exp_df is not None:\n model = PandasModel(self.exp_df)\n self.table_imdb.setModel(model)\n self.table_imdb.show()\n # Update the status label\n self.lbl_last_status.setText(str(self.exp))","def get_description():\n desc = dict()\n desc[\"cache\"] = 3600\n desc[\"data\"] = True\n desc[\n \"description\"\n ] = \"\"\"This plot is not meant for interactive use, but a backend for\n SPS plots.\n \"\"\"\n desc[\"arguments\"] = [\n dict(\n type=\"text\",\n name=\"pid\",\n default=\"202012300005-KDVN-WWUS83-SPSDVN\",\n label=\"IEM generated up to 35 char product identifier:\",\n ),\n dict(\n type=\"int\",\n default=0,\n name=\"segnum\",\n label=\"Product Segment Number (starts at 0):\",\n ),\n ]\n return desc","def test_load_experiment(self):\n exp = Experiment(self.epath,\n normalization='ch0',\n auto_alignment=False)\n self.assertTrue(isinstance(exp, Experiment))","def load_demo():\n\tprint(\"\"\"\n\tBreast Cancer Wisconsin dataset. It contains a total of 569 samples of tumor and malignant cells. \n\tData labeled 1 corresponds to malignant cells, while data labeled 0 corresponds to benign cells. \n\tThe 30 characteristics contain real values obtained from images of cell nuclei. For more information:\n\n\t\t\thttp://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic)\n\n\n\tThe returned value is a dictionary where 'x_data' are the predictor variables, 'y_data' the class \n\tlabels and 'features' the name of the characteristics.\n\t\"\"\")\n\tpath = '/'.join(os.path.abspath(pywinEA.__file__).split('/')[:-1])\n\t\n\tdata = pd.read_csv(path+'/dataset/data/BreastCancerWisconsin.csv', index_col=0)\n\tx_data = data.iloc[:, 1:].values\n\ty_data = data.iloc[:, 0].values\n\tfeatures = data.columns[1:].values\n\n\t# Transform labels\n\ty_data[np.where(y_data == 'M')] = 1\n\ty_data[np.where(y_data == 'B')] = 0\n\ty_data = y_data.astype(int)\n\n\treturn {'x_data': x_data, 'y_data': y_data, 'features': features}","def load_description(path_dir=PATH_ROOT, filename=\"DOCS.md\"):\n with open(os.path.join(path_dir, filename)) as f:\n long_description = f.read()\n return long_description","def set_description(self, data):\n self._description = self._uni(data)","def load_training_data(s3: str = \"s3://epam-hack4med-dataset\") -> pd.DataFrame:\n # Load labels\n df_labels = pd.read_csv(f\"{s3}/CRACoV-ETYKIETY.csv\")\n df_labels[id_cols] = df_labels[id_cols].astype(int)\n df_labels = df_labels.set_index(id_cols)\n labels = df_labels[[basic_target]]\n idx = labels.index\n\n # Load hospital admission file (PRZYJECIE)\n df_admission = pd.read_csv(f\"{s3}/CRACoV-PRZYJECIE.csv\")\n binary_adm_vars = [x for x in basic_adm_vars if df_admission[x].isin([\"Tak\", \"Nie\"]).any()]\n other_adm_vars = [x for x in basic_adm_vars if x not in binary_adm_vars]\n adm = df_admission.copy()\n adm = adm[id_cols + binary_adm_vars + other_adm_vars]\n adm = adm.set_index(id_cols).reindex(idx)\n \n # Load biochem analyses\n biochem_raw = pd.read_csv(f\"{s3}/CRACoV-BIOCHEMIA.csv\", parse_dates=['DATA_WYK']).sort_values('DATA_WYK')\n biochem = (\n biochem_raw.loc[biochem_raw.KOD.isin(basic_bio_codes)]\n .pivot_table(index=['LP.', 'ID_LAB'], columns='KOD', values='WYNIK', aggfunc='first')\n .reindex(idx)\n )\n # Merge it all together\n Xy_raw = pd.concat([labels, adm, biochem], axis='columns')\n return Xy_raw","def refresh_description(self):\n # AIN\n code_ain = (self.CODE >> 12) & 0b0111\n # DICT_AIN = [[0, 1], [0, 3], [1, 3], [2, 3], [0, 4], [1, 4], [2, 4], [3, 4]]\n ind_p, ind_n = DICT_AIN[code_ain]\n self.AINP = \"AIN\" + str(ind_p)\n self.AINN = \"AIN\" + str(ind_n)\n if (ind_n == 4): self.AINN = \"GND\"\n\n # FSR\n code_fsr = (self.CODE >> 9) & 0b0000111\n # DICT_FSR = [\"6.144V\", \"4.096V\", \"2.048V\", \"1.024V\", \"0.512V\", \"0.256V\"]\n self.FSR = DICT_FSR[code_fsr]\n\n # MODE\n\n # rate\n code_rate = (self.CODE >> 5) & 0b00000000111\n # DICT_RATE = [\"8 SPS\", \"16 SPS\", \"32 SPS\", \"64 SPS\", \"128 SPS\", \"250 SPS\", \"475 SPS\", \"860 SPS\"]\n self.RATE = DICT_RATE[code_rate]","def set_description(self, desc: str) -> None:\n self.metadata.data[\"description\"] = desc","def loadExample(self, exID):\r\n return \"\"","def load(self):\n basePath = './examples/'\n file = \"print8.ls8\"\n # file = \"mult.ls8\"\n # file = \"stack.ls8\"\n # file = \"call.ls8\"\n file = \"sctest.ls8\"\n if len(sys.argv) > 1:\n file = sys.argv[1]\n address = 0\n\n with open(basePath + file, \"r\") as f:\n for line in f:\n line = line.split(\"#\")\n\n try:\n v = int(line[0], 2)\n except ValueError:\n continue\n # print(v)\n self.ram[address] = v\n address += 1","def _load_molecule(self):\n self.pymol = pybel.readstring(self.input_format, self.file_dic['input'])","def gmcp_setup_data(self):\n yield \"Core.Supports.Debug\", 20\n yield \"Core.Supports.Set\", [ \"MG.char 1\", \"MG.room 1\", \"comm.channel 1\" ]","def load_problem_definition():\n # TODO this should be expanded to include all definitions\n with open(Path(\"config.yml\")) as file:\n CONFIG = yaml.full_load(file)\n\n problem_definition_config = CONFIG[\"problem_definition\"]\n\n num_days = problem_definition_config[\"num_days\"]\n hotel_index = problem_definition_config[\"hotel_index\"]\n\n problem_definition = {\"num_days\": num_days, \"hotel_index\": hotel_index}\n\n return problem_definition","def load_qc(self):\n rejectval = self.config.getint('profiles', 'qcreject') \n self.qc = self.read_var(self.qcvar)\n self.qc = self.qc.astype('unicode')\n self.qc[self.qc == '1'] = 1\n self.qc[np.logical_or(self.qc=='4', self.qc == '0')] = 0\n self.qc = self.qc.astype(bool)\n self.test_shape(self.qcvar, self.qc.shape, 2)","def test_description(self):\n\n for desc in TEST_DESCS:\n self.colorspace.setDescription(desc)\n self.assertEqual(desc, self.colorspace.getDescription())","def load_metadata_from_desc_file(self, desc_file, partition='train',\n max_duration=10.0):\n logger.info('Reading description file: {} for partition: {}'\n .format(desc_file, partition))\n audio_paths, durations, texts, arpabets = [], [], [], []\n with open(desc_file) as json_line_file:\n for line_num, json_line in enumerate(json_line_file):\n try:\n spec = json.loads(json_line)\n if float(spec['duration']) > max_duration:\n continue\n audio_paths.append(spec['key'])\n durations.append(float(spec['duration']))\n texts.append(spec['text'])\n if self.use_arpabets:\n arpabets.append(spec['arpabet'])\n except Exception as e:\n # Change to (KeyError, ValueError) or\n # (KeyError,json.decoder.JSONDecodeError), depending on\n # json module version\n logger.warn('Error reading line #{}: {}'\n .format(line_num, json_line))\n logger.warn(str(e))\n\n if not self.use_arpabets:\n arpabets = [''] * len(audio_paths)\n\n if partition == 'train':\n self.train_audio_paths = audio_paths\n self.train_durations = durations\n self.train_texts = texts\n self.train_arpabets = arpabets\n elif partition == 'validation':\n self.val_audio_paths = audio_paths\n self.val_durations = durations\n self.val_texts = texts\n self.val_arpabets = arpabets\n elif partition == 'test':\n self.test_audio_paths = audio_paths\n self.test_durations = durations\n self.test_texts = texts\n self.test_arpabets = arpabets\n else:\n raise Exception(\"Invalid partition to load metadata. \"\n \"Must be train/validation/test\")","def load_mpeg7():\n # List of image file names\n dataset_directory = os.path.join(root_directory,'MPEG7')\n filenames = os.listdir(dataset_directory)\n filenames.sort()\n\n # List of numpy array; each row is a Image of the dataset\n data = []\n\n # Numpy array of labels associated to each class of image\n target = np.empty([len(filenames), ])\n\n previous_label = ''\n class_num = -1\n index = 0\n\n for index, filename in enumerate(filenames):\n data.append(Bitmap(io.imread(os.path.join(dataset_directory, filename))))\n file_label = filename.split('-')[0]\n\n if(previous_label != file_label):\n previous_label = file_label\n class_num += 1\n target[index] = class_num\n else:\n target[index] = class_num\n\n return {'bitmaps': data, 'targets': target}","def load_mc(filename):\n global simulator\n if simulator is None:\n print \"program is not started\"\n else:\n simulator.load_mc(filename)","def load_dataset(self, folder: str):\n # just in case the user forgot to add a / to the end of his path\n if folder[-1] != \"/\":\n folder += \"/\"\n\n files = os.listdir(folder)\n description_file = [name for name in files if name.__contains__(\"description\")]\n instance_files = sorted([name for name in files if name.__contains__(\"instance\")])\n\n # make sure only one description file exists\n assert len(description_file) == 1\n\n description = None\n description_file = description_file[0]\n with open(folder + description_file, \"rb\") as file:\n description = pickle.load(file)\n\n dataset = []\n for instance_file in instance_files:\n with open(folder + instance_file, \"rb\") as file:\n dataset.append(pickle.load(file))\n\n # test if everything is alright (tests the easy parameters for every instance)\n assert len(dataset) == description[\"num_instances\"]\n for instance in dataset:\n assert len(instance) == description[\"num_end_cells\"]\n\n return dataset, description","def test_import(self):\r\n descriptor = self.get_dummy_course(START)","def test_answerfile_ipv6(tmpdir):\n\n _test_answerfile(tmpdir, \"cgcs_config.ipv6\")","def get_description(self):\n try:\n long_desc = self.__data[\"descriptions\"][\"MM - \" + self.__name][\"text\"].replace(\"<p>\", \"\").split('</p>')[0]\n return long_desc\n except:\n return None","def load_experiment(file_name: str):\n exp = Experiment2P()\n # initialize the lazy-load objects with empty lists\n exp.tail_data = []\n exp.replaced_tail_frames = []\n exp.laser_data = []\n exp.all_c = []\n exp.all_dff = []\n exp.func_stacks = []\n with h5py.File(file_name, 'r') as dfile:\n exp.version = dfile[\"version\"][()] # in future allows for version specific loading\n try:\n if exp.version == b\"unstable\" or exp.version == \"unstable\":\n warnings.warn(\"Experiment file was created with development version of analysis code. Trying to \"\n \"load as version 1\")\n elif int(exp.version) > 2:\n raise IOError(f\"File version {exp.version} is larger than highest recognized version '2'\")\n except ValueError:\n raise IOError(f\"File version {exp.version} not recognized\")\n # load general experiment data\n n_planes = dfile[\"n_planes\"][()] # inferrred property of class but used here for loading plane data\n exp.experiment_name = dfile[\"experiment_name\"][()]\n exp.original_path = dfile[\"original_path\"][()]\n exp.scope_name = dfile[\"scope_name\"][()]\n exp.comment = dfile[\"comment\"][()]\n exp.tail_frame_rate = dfile[\"tail_frame_rate\"][()]\n # load singular parameter dictionary\n exp.info_data = exp._load_dictionary(\"info_data\", dfile)\n # load tail-data modification flag if this is version 2\n if int(exp.version) > 1:\n exp.tail_data_augmented = dfile[\"tail_data_augmented\"][()]\n # load per-plane data\n for i in range(n_planes):\n plane_group = dfile[str(i)]\n exp.scanner_data.append(exp._load_dictionary(\"scanner_data\", plane_group))\n exp.tail_data.append(plane_group[\"tail_data\"][()])\n exp.projections.append(plane_group[\"projection\"][()])\n if \"func_stack\" in plane_group:\n exp.func_stacks.append(plane_group[\"func_stack\"][()])\n if \"anat_projection\" in plane_group: # test if this experiment was dual-channel\n exp.anat_projections.append(plane_group[\"anat_projection\"][()])\n if \"tail_data\" in plane_group: # test if this experiment had tail data (for all planes)\n exp.tail_data.append(plane_group[\"tail_data\"][()])\n exp.bout_data.append(plane_group[\"bout_data\"][()])\n exp.tail_frame_times.append(plane_group[\"tail_frame_time\"][()])\n if int(exp.version) > 1 and \"replaced_tail_frames\" in plane_group:\n exp.replaced_tail_frames.append(plane_group[\"replaced_tail_frames\"][()])\n if \"laser_data\" in plane_group: # test if this experiment had laser data\n exp.laser_data.append(plane_group[\"laser_data\"][()])\n exp.all_c.append(plane_group[\"C\"][()])\n exp.all_dff.append(plane_group[\"dff\"][()])\n exp.all_centroids.append(plane_group[\"centroids\"][()])\n exp.all_sizes.append(plane_group[\"sizes\"][()])\n exp.all_spatial.append(plane_group[\"spatial\"][()])\n ps = plane_group[\"mcorr_dict\"][()]\n exp.mcorr_dicts.append(json.loads(ps))\n ps = plane_group[\"cnmf_extract_dict\"][()]\n exp.cnmf_extract_dicts.append(json.loads(ps))\n ps = plane_group[\"cnmf_val_dict\"][()]\n exp.cnmf_val_dicts.append(json.loads(ps))\n exp.populated = True\n return exp","def processDescrString(self):\n\t\tself.descrString = self._getVal(4, 1)","def help_load(self):\n print(LOAD)","def set_desc(self, annonce):\n d = annonce.find_element_by_class_name('prdtBILDesc.jsPrdtBILLink')\n self.desc = d.text.splitlines()","def get_protocol_init_data(self):\n\t\tcontents = self.archive.read_file('replay.initData')\n\t\treturn self.protocol.decode_replay_initdata(contents)","def load(cls, labpath: str) -> None:\n raise NotImplementedError","def load_inst(self):\n self.sanity_check()\n\n fname_pub_auth_all = ''.join([self.config.dir_data, '/',\n self.config.fname_pub_auth_all, '_',\n self.config.experiment_id, '.pk'])\n fname_pub_auth_top = ''.join([self.config.dir_data, '/',\n self.config.fname_pub_auth_top, '_',\n self.config.experiment_id, '.pk'])\n fname_pub_inst_all = ''.join([self.config.dir_data, '/',\n self.config.fname_pub_inst_all, '_',\n self.config.experiment_id, '.pk'])\n fname_pub_inst_top = ''.join([self.config.dir_data, '/',\n self.config.fname_pub_inst_top, '_',\n self.config.experiment_id, '.pk'])\n self.pub_auth_all = pickle.load(open(fname_pub_auth_all, 'rb'))\n self.pub_auth_top = pickle.load(open(fname_pub_auth_top, 'rb'))\n self.pub_inst_all = pickle.load(open(fname_pub_inst_all, 'rb'))\n self.pub_inst_top = pickle.load(open(fname_pub_inst_top, 'rb'))\n\n fname_pub_history = ''.join([self.config.dir_data, '/history_',\n self.config.experiment_id, '.pk'])\n self.history = pickle.load(open(fname_pub_history, 'rb'))\n\n fname_pub_staff = ''.join([self.config.dir_data, '/staff_',\n self.config.experiment_id, '.pk'])\n self.staff = pickle.load(open(fname_pub_staff, 'rb'))","def part_6():\n\n raise NotImplementedError","def config_section_data():\n config_data = u\"\"\"[feeds]\n# comma separated section names. ex. sqlserver_feed,file_feed\nfeed_names=<your feeds>\nreload=true\n# use reload_types to limit the types of objects when reload=true.\n# Ex: incident,task,note,artifact,attachment,<data_table_api_name>\nreload_types=\n# set to true if ElasticSearch errors occur during reload=true\nreload_query_api_method=false\n\n# feed_data is the default message destination that will be listened to\nqueue=feed_data\n\n# set to true if attachment data should be part of payload send to plugins\ninclude_attachment_data=false\n# if necessary, specify the supported workspace (by label, case sensitive) and the list of feeds associated with it\n# ex: 'Default Workspace': ['sqlserver_feed'], 'workspace A': ['kafka_feed', 'resilient_feed']\nworkspaces=\n\"\"\"\n return config_data","def test_load_from_v5(self) -> None:\n self.save_new_valid_exploration(\n 'Exp1', 'user@example.com', end_state_name='End')\n collection = collection_domain.Collection.from_yaml(\n 'cid', self.YAML_CONTENT_V5)\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)","def load():\r\n\r\n data = dict()\r\n global IMAGES_FILE_PATH\r\n chdir(IMAGES_FILE_PATH)\r\n try:\r\n with open('Descriptions_File.txt', 'r') as f:\r\n reader = csv.DictReader(f, delimiter=',')\r\n for row in reader:\r\n url = row['url']\r\n data[url] = row['description']\r\n f.close()\r\n except Exception: # If no Descriptions found\r\n return data\r\n return data","def get_club_description(club):\n elts = get_elements_with_class(club, 'em', '')\n if len(elts) < 1:\n return ''\n return elts[0].text\n\n return ''","def get_model_description() -> Dict[str, Any]:\n\n desc_file = os.path.join(os.path.dirname(__file__), \"model_files\", \"description.yaml\")\n if not os.path.exists(desc_file):\n raise FileNotFoundError(f\"File not found - {desc_file}\")\n else:\n with open(desc_file, \"r\") as f:\n desc = yaml.safe_load(f.read())\n if desc is None:\n raise RuntimeError(f\"Error parsing {desc_file}\")\n return desc","def __init__(self, inputfolder, gpu_id=0, model=None):\n CaffeLoader.__init__(self, inputfolder, gpu_id=gpu_id)\n logger.info('loading deploy.prototxt from %s' % inputfolder)\n if model:\n self.setModel(model)\n if self.caffemodel and self.protofile:\n self.net = caffe.Net(self.protofile, caffe.TEST)\n else:\n logger.error('Cannot find prototxt or caffemodel file')\n sys.exit(0)","def init_from_file(self):\n self.src.load('start.00') \n self.oe1.load('start.01')\n #self.det.load('start.02')\n print('NOTE: variables loaded from start.00/start.01 files')","def get_description(self):\n des = self.soup.find('div', id = 'zh-topic-desc').find('div', class_ = 'zm-editable-content')\n if des:\n return des.get_text(strip = True).encode(CODE)\n return None","def test_fif6(self):\n # TODO this should be ideally in setUpClass, but then we hit a bug\n # with VppIpRoute incorrectly reporting it's present when it's not\n # so we need to manually remove the vpp config, thus we cannot have\n # it shared for multiple test cases\n self.tun_ip6 = \"1002::1\"\n\n self.gre6 = VppGreInterface(self, self.src_if.local_ip6, self.tun_ip6)\n self.gre6.add_vpp_config()\n self.gre6.admin_up()\n self.gre6.config_ip6()\n\n self.vapi.ip_reassembly_enable_disable(\n sw_if_index=self.gre6.sw_if_index, enable_ip6=True\n )\n\n self.route6 = VppIpRoute(\n self,\n self.tun_ip6,\n 128,\n [VppRoutePath(self.src_if.remote_ip6, self.src_if.sw_if_index)],\n )\n self.route6.add_vpp_config()\n\n self.reset_packet_infos()\n for i in range(test_packet_count):\n info = self.create_packet_info(self.src_if, self.dst_if)\n payload = self.info_to_payload(info)\n # Ethernet header here is only for size calculation, thus it\n # doesn't matter how it's initialized. This is to ensure that\n # reassembled packet is not > 9000 bytes, so that it's not dropped\n p = (\n Ether()\n / IPv6(src=self.src_if.remote_ip6, dst=self.dst_if.remote_ip6)\n / UDP(sport=1234, dport=5678)\n / Raw(payload)\n )\n size = self.packet_sizes[(i // 2) % len(self.packet_sizes)]\n self.extend_packet(p, size, self.padding)\n info.data = p[IPv6] # use only IPv6 part, without ethernet header\n\n fragments = [\n x\n for _, i in self._packet_infos.items()\n for x in fragment_rfc8200(i.data, i.index, 400)\n ]\n\n encapped_fragments = [\n Ether(dst=self.src_if.local_mac, src=self.src_if.remote_mac)\n / IPv6(src=self.tun_ip6, dst=self.src_if.local_ip6)\n / GRE()\n / p\n for p in fragments\n ]\n\n fragmented_encapped_fragments = [\n x\n for p in encapped_fragments\n for x in (\n fragment_rfc8200(\n p, 2 * len(self._packet_infos) + p[IPv6ExtHdrFragment].id, 200\n )\n if IPv6ExtHdrFragment in p\n else [p]\n )\n ]\n\n self.src_if.add_stream(fragmented_encapped_fragments)\n\n self.pg_enable_capture(self.pg_interfaces)\n self.pg_start()\n\n self.src_if.assert_nothing_captured()\n packets = self.dst_if.get_capture(len(self._packet_infos))\n self.verify_capture(packets, IPv6)\n\n # TODO remove gre vpp config by hand until VppIpRoute gets fixed\n # so that it's query_vpp_config() works as it should\n self.gre6.remove_vpp_config()","def descr(self):\n return self.recipe.get(\"descr\", \"no description\")","def load_crawl():\n\n\tmodule_path = dirname(__file__)\n\twith open(join(module_path, 'data', 'train2.csv')) as csv_file:\n\t\tdata_file = csv.reader(csv_file)\n\t\ttemp = next(data_file)\n\t\tglobal n_samples\n\t\tn_samples = int(temp[0])\n\t\tglobal n_features\n\t\tn_features = int(temp[1])\n\t\tprint \"n samples \" + str((n_samples))\n\t\tprint \"n_features\" + str((n_features))\n\t\ttarget_names = np.array(temp[2:4])\n\t\tdata = np.empty((n_samples, n_features))\n\t\ttarget = np.empty((n_samples,), dtype=np.int)\n\n\t\tfor count, value in enumerate(data_file):\n\t\t\tdata[count] = np.asarray(value[:-1], dtype=np.float)\n\t\t\ttarget[count] = np.asarray(value[-1], dtype=np.int)\n\t\t\t#print \"data is \" + str(data[count])\n\t\t\t#print \"target is \" + str(target[count])\n\t\tprint \"Number of target records is \" + str(len(target))\n\t#with open(join(module_path, 'descr', 'train.rst')) as rst_file:\n\t#\tfdescr = rst_file.read()\n\n\treturn Bunch(data=data, target=target,\n\t\t\t target_names=target_names,\n\t\t\t DESCR=None,\n\t\t\t feature_names = ['evalCount', 'setInterval', 'setTimeout', 'link', \n\t\t\t\t\t\t\t 'search', 'exec','escape', 'unescape', 'ratio', \n\t\t\t\t\t\t\t 'emtropyAvg', 'entropyScript', 'longStrings', \n\t\t\t\t\t\t\t 'maxEntropy', 'stringAvg', 'maxLength', 'longVarFunc', \n\t\t\t\t\t\t\t 'stringAssignments', 'stringModFuncsCount', 'eventFuncsCount', \n\t\t\t\t\t\t\t 'domModFuncsCounter', 'suspStrings', 'whiteSpaceRatio', \n\t\t\t\t\t\t\t 'hexaStrings', 'maxNonPrintableCharactersinString', 'lineAvg', \n\t\t\t\t\t\t\t 'iframeCount', 'malTagCount', 'jsLength'])","def test_get_description(self):\n description = get_description(self.work_data[\"description\"])\n expected = \"First in the Old Kingdom/Abhorsen series.\"\n self.assertEqual(description, expected)","def load_epicsLive(self, instrument=None, **kwargs):\n# if 'instrument' in kwargs:\n# instrument = kwargs.get('instrument')\n# self.instrument = instrument\n if not instrument:\n instrument = self.instrument\n\n self.ioc = psioc.IOC(instrument=self.instrument)\n if self.instrument in ['cxi', 'mfx', 'xcs', 'mec']:\n self.ioc.load_cfg('xrt')\n \n print 'Loading EpicsSets for', instrument\n self.epicsLive = lcls_devices.EpicsSets(instrument=instrument, **kwargs)\n self.update_epicsLive()","def load_explainer(self):\n explainer_path = os.path.join(self.model_path, \"explainer.dill\")\n csv_path = os.path.join(self.model_path, self.__csv_path)\n if os.path.isfile(explainer_path):\n with open(explainer_path, \"rb\") as f:\n self.__explainer = dill.load(f)\n elif os.path.isfile(csv_path):\n print(\"[WARN] Making new explainer!\")\n self.__explainer = make_explainer(\n pd.read_csv(csv_path),\n self.FEATURES\n )\n with open(explainer_path, \"wb\") as f:\n dill.dump(self.__explainer, f)\n else:\n print(\"[WARN] Explainer not found!\")","def data_description(hf, var):\n desc = hf['/output/data/%s' % var].attrs['description']\n if type(desc) != str:\n desc = desc.decode('UTF-8')\n\n if desc:\n return desc\n return var","def load_caffe_model(self):\n print(\"Loading caffe model used for detecting a human_blob.\")\n\n # Use cv2.dnn function to read the caffe model used for detecting faces and set preferable target.\n # self.detector = cv2.dnn.readNetFromCaffe(os.path.join(\n # os.path.dirname(os.path.realpath(__file__)),\n # prototxt_path),\n # os.path.join(\n # os.path.dirname(os.path.realpath(__file__)),\n # human_model_path))\n self.detector = cv2.dnn.readNetFromCaffe(prototxt=\"human_detection_model/MobileNetSSD_deploy.prototxt.txt\",\n caffeModel=\"human_detection_model/MobileNetSSD_deploy.caffemodel\")\n self.detector.setPreferableTarget(Rescue_PI.preferable_target)","def description(self, description) :\n\t\ttry :\n\t\t\tself._description = description\n\t\texcept Exception as e:\n\t\t\traise e","def define_description(self):\n self._description = 'NODDI-based processing of DWI datasets.'","def load(f, model, nper=1, ext_unit_dict=None):\r\n\r\n if model.verbose:\r\n sys.stdout.write('loading bas6 package file...\\n')\r\n\r\n if not hasattr(f, 'read'):\r\n filename = f\r\n f = open(filename, 'r')\r\n\r\n if model.nrow_ncol_nlay_nper != (0, 0, 0, 0):\r\n nrow, ncol, nlay, nper = model.nrow_ncol_nlay_nper\r\n\r\n t = f.readline().strip()\r\n maxrivr = int(t[0])\r\n irivcb = int(t[1])\r\n\r\n stress_period_data = mflist_reader(f, Modflow88Riv, nper)\r\n\r\n return Modflow88Riv(model, irivcb, stress_period_data)","def load(self):\n super().load()\n for channel in range(self.n_channels):\n c_str = 'Channel_{0:02d}'.format(channel)\n if c_str not in self:\n log.info(f'{c_str} not found in config yaml, adding it now with defaults')\n self.set(c_str, {'amplitude': 1.5, 'dc_offset': 0.0}, save_config=True)\n\n val = self.get(c_str)\n self.amplitude(channel, val['amplitude'])\n self.offset(channel, val['dc_offset'])\n self._set_register(0, self.get('clock_delay', 1000)//100 + self._seq_length//100 - 1)","def load_config(self):\n with h5py.File(iop.fields, 'r') as hf:\n # fields = hf.get('data')[:]\n config = hf.get('config')[:]\n return config","def load(self):\n raise NotImplementedError","def load(self):\n raise NotImplementedError","def load(extended=False):\n\n _fetch_large()\n if extended:\n return _load(cache_experiment_extended, _parse_experiment)\n else:\n return _load(cache_experiment, _parse_experiment)","def description(self):\n return self.marmite_tree['description']","def load(self):\n\n logging.info(\"Loading the `BeagleSummaryCatalogue` file: \" + self.file_name)\n\n name = getPathForData(self.file_name)\n self.hdulist = fits.open(name)","def load_data(self) -> None:","def load(self):\n self.classifier = joblib.load(\"data/models/repeatsfinder/repeatsfinder.joblib\")","def _read_opt_mpl(self, code, *, desc):\n _type = self._read_opt_type(code)\n _size = self._read_unpack(1)\n if _size < 2:\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\n _smvr = self._read_binary(1)\n _seqn = self._read_unpack(1)\n\n opt = dict(\n desc=desc,\n type=_type,\n length=_size + 2,\n seed_len=_IPv6_Opts_SEED.get(int(_smvr[:2], base=2)),\n flags=dict(\n max=bool(int(_smvr[2], base=2)),\n verification=bool(int(_smvr[3], base=2)),\n ),\n seq=_seqn,\n )\n\n _kind = _smvr[:2]\n if _kind == '00':\n if _size != 2:\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\n elif _kind == '01':\n if _size != 4:\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\n opt['seed_id'] = self._read_unpack(2)\n elif _kind == '10':\n if _size != 10:\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\n opt['seed_id'] = self._read_unpack(8)\n elif _kind == '11':\n if _size != 18:\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\n opt['seed_id'] = self._read_unpack(16)\n else:\n opt['seed_id'] = self._read_unpack(_size-2)\n\n _plen = _size - opt['seed_len']\n if _plen:\n self._read_fileng(_plen)\n\n return opt","async def description(ctx, bot: typing.Union[discord.Member, discord.User]):\n data = await make_request(\"https://www.motiondevelopment.top/api/v1.2/bots/\", bot.id)\n if not bot.bot:\n return await r(ctx, \"Not a bot.\")\n\n if len(data[\"Big_desc\"]) > 2000:\n desc = data[\"Big_desc\"][:2000] + \\\n f\"...\\n[View original page for full description](https://www.motiondevelopment.top/bots/{bot.id})\"\n else:\n desc = data[\"Big_desc\"]\n await em(ctx, embed=discord.Embed(color=0xfecdea, description=desc))","def description(self):\r\n if \"description\" in self.data:\r\n return self.data[\"description\"]\r\n return None","def createExpCfg(expCfgPathAndName):\n\n print (\"Loading experiment config file: \" + expCfgPathAndName)\n \n from os import path\n filePath = path.dirname(path.abspath(expCfgPathAndName))\n\n # This is where the parser is called.\n expCfg = ConfigObj(expCfgPathAndName, configspec=filePath + '/expCfgSpec.ini', raise_errors = False, file_error = False)\n\n validator = Validator()\n expCfgOK = expCfg.validate(validator)\n if expCfgOK == True:\n print (\"Experiment config file parsed correctly\")\n else:\n print ('Experiment config file validation failed!')\n res = expCfg.validate(validator, preserve_errors=True)\n for entry in flatten_errors(expCfg, res):\n # 1each entry is a tuple\n section_list, key, error = entry\n if key is not None:\n section_list.append(key)\n else:\n section_list.append('[missing section]')\n section_string = ', '.join(section_list)\n if error == False:\n error = 'Missing value or section.'\n print (section_string, ' = ', error)\n sys.exit(1)\n if expCfg.has_key('_LOAD_'):\n for ld in expCfg['_LOAD_']['loadList']:\n print ('Loading: ' + ld + ' as ' + expCfg['_LOAD_'][ld]['cfgFile'])\n curCfg = ConfigObj(expCfg['_LOAD_'][ld]['cfgFile'], configspec = expCfg['_LOAD_'][ld]['cfgSpec'], raise_errors = True, file_error = True)\n validator = Validator()\n expCfgOK = curCfg.validate(validator)\n if expCfgOK == True:\n print (\"Experiment config file parsed correctly\")\n else:\n print ('Experiment config file validation failed!')\n res = curCfg.validate(validator, preserve_errors=True)\n for entry in flatten_errors(curCfg, res):\n # each entry is a tuple\n section_list, key, error = entry\n if key is not None:\n section_list.append(key)\n else:\n section_list.append('[missing section]')\n section_string = ', '.join(section_list)\n if error == False:\n error = 'Missing value or section.'\n print (section_string, ' = ', error)\n sys.exit(1)\n expCfg.merge(curCfg)\n\n return expCfg","def _load_metadata(self):\n\n cub_dir = self.root / \"CUB_200_2011\"\n images_list: Dict[int, List] = OrderedDict()\n\n with open(str(cub_dir / \"train_test_split.txt\")) as csv_file:\n csv_reader = csv.reader(csv_file, delimiter=\" \")\n for row in csv_reader:\n img_id = int(row[0])\n is_train_instance = int(row[1]) == 1\n if is_train_instance == self.train:\n images_list[img_id] = []\n\n with open(str(cub_dir / \"images.txt\")) as csv_file:\n csv_reader = csv.reader(csv_file, delimiter=\" \")\n for row in csv_reader:\n img_id = int(row[0])\n if img_id in images_list:\n images_list[img_id].append(row[1])\n\n with open(str(cub_dir / \"image_class_labels.txt\")) as csv_file:\n csv_reader = csv.reader(csv_file, delimiter=\" \")\n for row in csv_reader:\n img_id = int(row[0])\n if img_id in images_list:\n # CUB starts counting classes from 1 ...\n images_list[img_id].append(int(row[1]) - 1)\n\n with open(str(cub_dir / \"bounding_boxes.txt\")) as csv_file:\n csv_reader = csv.reader(csv_file, delimiter=\" \")\n for row in csv_reader:\n img_id = int(row[0])\n if img_id in images_list:\n box_cub = [int(float(x)) for x in row[1:]]\n box_avl = [box_cub[1], box_cub[0], box_cub[3], box_cub[2]]\n # PathsDataset accepts (top, left, height, width)\n images_list[img_id].append(box_avl)\n\n images_tuples = []\n for _, img_tuple in images_list.items():\n images_tuples.append(tuple(img_tuple))\n self._images = images_tuples # type: ignore\n\n # Integrity check\n for row_check in self._images:\n filepath = self.root / CUB200.images_folder / row_check[0]\n if not filepath.is_file():\n if self.verbose:\n print(\"[CUB200] Error checking integrity of:\", filepath)\n return False\n\n return True","def load_crawl():\n\n\tmodule_path = dirname(__file__)\n\twith open(sys.argv[1]) as csv_file:\n\t\tdata_file = csv.reader(csv_file)\n\t\ttemp = next(data_file)\n\t\tn_samples = int(temp[0])\n\t\tn_features = int(temp[1])\n\t\ttarget_names = np.array(temp[2:4])\n\t\tdata = np.empty((n_samples, n_features))\n\t\ttarget = np.empty((n_samples,), dtype=np.int)\n\n\t\tfor count, value in enumerate(data_file):\n\t\t\tif len(value)<28:\n\t\t\t\tcontinue\n\t\t\ttry:\n\t\t\t\tdata[count] = np.asarray(value[:28], dtype=np.float)\n\t\t\t\ttarget[count] = np.asarray(value[28], dtype=np.int)\t\n\t\t\texcept:\n\t\t\t\tcontinue\n\t\t\t#print \"data is \" + str(data[count])\n\t\t\t#print \"target is \" + str(target[count])\n\n\twith open(join(module_path, 'descr', 'crawl.rst')) as rst_file:\n\t\tfdescr = rst_file.read()\n\n\treturn Bunch(data=data, target=target,\n\t\t\t target_names=target_names,\n\t\t\t DESCR=fdescr,\n\t\t\t feature_names = ['evalCount', 'setInterval', 'setTimeout', 'link', \n\t\t\t\t\t\t\t 'search', 'exec','escape', 'unescape', 'ratio', \n\t\t\t\t\t\t\t 'emtropyAvg', 'entropyScript', 'longStrings', \n\t\t\t\t\t\t\t 'maxEntropy', 'stringAvg', 'maxLength', 'longVarFunc', \n\t\t\t\t\t\t\t 'stringAssignments', 'stringModFuncsCount', 'eventFuncsCount', \n\t\t\t\t\t\t\t 'domModFuncsCounter', 'suspStrings', 'whiteSpaceRatio', \n\t\t\t\t\t\t\t 'hexaStrings', 'maxNonPrintableCharactersinString', 'lineAvg', \n\t\t\t\t\t\t\t 'iframeCount', 'malTagCount', 'jsLength'])","def run_example_udpv6():\n config = {\n 'server_address': '10.8.254.65',\n 'wan_port': Device(interface='nontrunk-1',\n mac='00:ff:1f:00:00:01',\n iptype=6, slaac=True),\n 'cpe_port': Device(interface='trunk-1-19',\n iptype=6, dhcp=True,\n nat=True),\n 'traffic_profile': UdpTrafficProfile(interframegap=1000000, # ns\n frame_size=508 # bytes\n ),\n 'number_of_downstream_flows': 2,\n 'number_of_upstream_flows': 1,\n 'traffic_duration': datetime.timedelta(seconds=3)\n }\n\n with Example(**config) as example:\n results = example.run()\n return results","def test_description(self):\n self.assertEqual(\n \"Description.\",\n DescribedModel.parse_obj({\"name\": \"Name\", \"description\": \"Description\"}).description,\n )","def parse_description(self, in_str):\n in_str = self.parse_tags(in_str)\n self.description = self.parse_metadata(in_str)","def get_description(self):\n\t\treturn call_sdk_function('PrlVmCfg_GetDescription', self.handle)","def set_description(self, descr):\n self._current_test_descr = descr","def workbench_scenarios():\n return [\n (\"Oppia Embedding\",\n \"\"\"<vertical_demo>\n <oppia oppiaid=\"0\" src=\"https://www.oppia.org\" width=\"700\" />\n </vertical_demo>\n \"\"\"),\n ]","def Description(self, default=None):\n return self.data.get('description', default)","def Description(self, default=None):\n return self.data.get('description', default)","def read_uef_details(chunks):\n\n\tpos, chunk = find_next_chunk(chunks, 0, [0x0])\n\n\tif pos == None:\n\n\t\toriginator = 'Unknown'\n\n\telif chunk[1] == '':\n\n\t\toriginator = 'Unknown'\n\telse:\n\t\toriginator = chunk[1]\n\n\tpos, chunk = find_next_chunk(chunks, 0, [0x5])\n\n\tif pos == None:\n\n\t\tmachine, keyboard = 'Unknown', 'Unknown'\n\n\telse:\n\n\t\tmachines = ('BBC Model A', 'Electron', 'BBC Model B', 'BBC Master')\n\t\tkeyboards = ('Any layout', 'Physical layout', 'Remapped')\n\n\t\tmachine = ord(chunk[1][0]) & 0x0f\n\t\tkeyboard = (ord(chunk[1][0]) & 0xf0) >> 4\n\n\t\tif machine < len(machines):\n\t\t\tmachine = machines[machine]\n\t\telse:\n\t\t\tmachine = 'Unknown'\n\n\t\tif keyboard < len(keyboards):\n\t\t\tkeyboard = keyboards[keyboard]\n\t\telse:\n\t\t\tkeyboard = 'Unknown'\n\n\tpos, chunk = find_next_chunk(chunks, 0, [0xff00])\n\n\tif pos == None:\n\n\t\temulator = 'Unknown'\n\n\telif chunk[1] == '':\n\n\t\temulator = 'Unknown'\n\telse:\n\t\temulator = chunk[1]\n\n\n\t# Remove trailing null bytes\n\twhile originator[-1] == '\\000':\n\n\t\toriginator = originator[:-1]\n\n\twhile emulator[-1] == '\\000':\n\n\t\temulator = emulator[:-1]\n\n\tfeatures = ''\n\tif find_next_chunk(chunks, 0, [0x1])[0] != None:\n\t\tfeatures = features + '\\n' + 'Instructions'\n\tif find_next_chunk(chunks, 0, [0x2])[0] != None:\n\t\tfeatures = features + '\\n' + 'Credits'\n\tif find_next_chunk(chunks, 0, [0x3])[0] != None:\n\t\tfeatures = features + '\\n' + 'Inlay'\n\n\treturn originator, machine, keyboard, emulator, features","def test_entry_6(self):\n row = self.dataset.iloc[6]\n self.assertEqual('./cnn/stories/d312173b8c95cc6c206a32cc0acd8a92c1e272d5.story',\n row.story_id)\n self.assertEqual(\"Who is hiring ?\", row.question)\n self.assertEqual('334:345|292:297,372:379|4045:4079|301:324', row.answer_char_ranges)\n self.assertEqual(0, row.is_answer_absent)\n self.assertEqual('0.0', row.is_question_bad)\n self.assertEqual(\n '25,43,71,94,109,120,131,158,168,188,208,222,260,288,327,332,348,369,378,409,417,428,478,504,541,606,623,636,662,682,689,695,712,732,752,778,808,818,852,883,898,927,956,975,999,1020,1051,1069,1080,1092',\n row.sentence_starts)\n self.assertEqual('56:59', row.answer_token_ranges)\n self.assertEqual(\"CNN affiliates report on where job seekers are\", row.story_text[:46])\n self.assertEqual([\"the federal government\"], _get_answers(row))","def new_experiment_from_h5file(self, name, file_path, description=''):\n new_exp = {\n ExperimentAttr.NAME: name,\n ExperimentAttr.SAVED_MODEL_LOC: file_path,\n ExperimentAttr.DESC: description\n }\n\n return self.dbclient.insert(Tables.EXPERIMENTS, new_exp).inserted_id","def description(self):\n return self._data.get('description')","def loadInception(self):\r\n\r\n self.reqsize = self.confs[\"Classifier\"][\"ImageSize\"]\r\n\r\n with open(self.confs[\"Classifier\"][\"NetworkPath\"] + self.confs[\"Classifier\"][\"InceptionGraph\"], mode='rb') as f:\r\n ncsGraphFile = f.read()\r\n\r\n self.allocateGraph(ncsGraphFile)\r\n\r\n with open(self.confs[\"Classifier\"][\"DatasetDir\"] + \"/\" + self.confs[\"Classifier\"][\"Classes\"], 'r') as f:\r\n for line in f:\r\n cat = line.split('\\n')[0]\r\n if cat != 'classes':\r\n self.classes.append(cat)\r\n f.close()\r\n\r\n self.Helpers.logger.info(\"Inception loaded successfully.\")","def load_run_summary(self):\n vrun_attrs = {}\n print 'Loading summary of {:} runs for {:} from SQL database'.format( \\\n len(self.runs),self.exp)\n print 'Estimate loading time ~{:} sec'.format(len(self.runs)/4)\n for run in range(1,self.runs[-1]['num']+1):\n run_attr = experiment_info.run_attributes(self.instrument,self.exp,run)\n for a in run_attr:\n if a['name'] not in vrun_attrs:\n vrun_attrs[a['name']] = {'class': a['class'], 'desc': a['descr'], \n 'type': a['type'], 'val': \n [None for i in range(1,run)]} \n vrun_attrs[a['name']]['val'].append(a['val'])\n self.run_summary = vrun_attrs","def description(self, new_description):\n self.set_description(new_description, self._xml)\n self._description = self._read_description(self._xml)","def _load_experiment(\n experiment_name: str, decoder: Decoder, reduced_state: bool = False\n) -> Experiment:\n # Convert SQA to user-facing class outside of session scope to avoid timeouts\n return decoder.experiment_from_sqa(\n experiment_sqa=_get_experiment_sqa_reduced_state(\n experiment_name=experiment_name, decoder=decoder\n )\n if reduced_state\n else _get_experiment_sqa(experiment_name=experiment_name, decoder=decoder),\n reduced_state=reduced_state,\n )","def load_cci9():\n cci9 = pd.read_csv(pkg_resources.resource_filename(__name__,'cci2015.csv'),skiprows=1)\n cci9.columns = [i.strip('\\'') for i in cci9.columns]\n \n for col in cci9.columns:\n cci9.loc[:,col] = cci9[col].str.strip('\\'')\n cci9 = cci9.replace(r'^\\s*$', np.nan, regex=True)\n cci9.columns=[i.replace('CATEGORY DESCRIPTION','CHRONIC') for i in cci9.columns]\n\n dict_bodysystem=[\n ('1' ,'Infectious and parasitic disease'),\n ('2' ,'Neoplasms'),\n ('3' ,'Endocrine, nutritional, and metabolic diseases and immunity disorders'),\n ('4' ,'Diseases of blood and blood-forming organs'),\n ('5' ,'Mental disorders'),\n ('6' ,'Diseases of the nervous system and sense organs'),\n ('7' ,'Diseases of the circulatory system'),\n ('8' ,'Diseases of the respiratory system'),\n ('9' ,'Diseases of the digestive system'),\n ('10','Diseases of the genitourinary system'),\n ('11','Complications of pregnancy, childbirth, and the puerperium'),\n ('12','Diseases of the skin and subcutaneous tissue'),\n ('13','Diseases of the musculoskeletal system'),\n ('14','Congenital anomalies'),\n ('15','Certain conditions originating in the perinatal period'),\n ('16','Symptoms, signs, and ill-defined conditions'),\n ('17','Injury and poisoning'),\n ('18','Factors influencing health status and contact with health service'),\n ]\n \n cci9 = cci9.merge(pd.DataFrame(dict_bodysystem,columns=['BODY SYSTEM','BODY SYSTEM DESCRIPTION']),how='left',on='BODY SYSTEM')\n \n cci9.loc[:,'ICD-9-CM CODE'] = cci9['ICD-9-CM CODE'].str.replace(' ','')\n \n return cci9","def experiment_init(self):\n pass","def test_update_flow_classifier_description(self):\n resource = 'flow_classifier'\n cmd = fc.FlowClassifierUpdate(test_cli20.MyApp(sys.stdout), None)\n myid = 'myid'\n args = [myid, '--description', 'flow_classifier1', '--description',\n 'flow_classifier2']\n updatefields = {'description': 'flow_classifier2'}\n self._test_update_resource(resource, cmd, myid, args, updatefields)","def load_data(self):","def load_info():\n data = np.loadtxt(\"u_sol_meta.txt\", dtype=int)\n return data","def description(path='election-manifest.json'):\n from electionguard.manifest import Manifest\n with open(path, 'r') as manifest:\n string_representation = manifest.read()\n return Manifest.from_json(string_representation)","def load(self):\n pass"],"string":"[\n \"def testCMIP6(self):\\n\\n c = CMIP6()\\n c.render(self.testoutput[3])\\n for r in c.reference_list:\\n print r\\n print c.nocite\",\n \"def test_load_from_v6(self) -> None:\\n self.save_new_valid_exploration(\\n 'Exp1', 'user@example.com', end_state_name='End')\\n collection = collection_domain.Collection.from_yaml(\\n 'cid', self.YAML_CONTENT_V6)\\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)\",\n \"def load_sas_desc_file(input_data):\\n # parse description file\\n i94_desc_path = os.path.join(input_data, 'I94_SAS_Labels_Descriptions.SAS')\\n with open(i94_desc_path) as f:\\n lines = f.readlines()\\n i94_desc_string = ''.join(lines)\\n i94_desc_string = i94_desc_string.replace('\\\\n', '')\\n i94_desc_string = i94_desc_string.replace('\\\\t', '')\\n logging.info('SAS description file successfully processed')\\n return i94_desc_string\",\n \"def loadTutorialSuit():\\n loader.loadModelNode(\\\"phase_3.5/models/char/suitC-mod\\\")\\n loadDialog(1)\",\n \"def load_interface_details(self):\\n for line in self.ShowInterfacePerInt:\\n if line.find('Description:') >= 0:\\n self.InterfaceDescription = line.replace('Description:', '')\\n elif line.find('packets input') >= 0:\\n self.PacketsInput = int(line.split()[0])\\n elif line.find('packets output') >= 0:\\n self.PacketsOutput = int(line.split()[0])\\n elif line.find('line protocol') >= 0:\\n self.LineProtocol = line\\n elif line.find('Last clearing of') >= 0:\\n self.LastClearing = line.split()[-1]\\n\\n for line in self.ShowInterfaceSwitchportPerInt:\\n if line.find('Administrative Mode:') >= 0:\\n self.AdministrativeMode = line[20:].strip()\\n elif line.find('Access Mode VLAN:') >= 0:\\n self.AccessModeVlan = line.split()[3]\\n elif line.find('Voice VLAN:') >= 0:\\n self.VoiceVlan = line.split()[2]\\n\\n for line in self.ShowInterfaceCapabilitiesPerInt:\\n if line.find('Type:') >= 0:\\n self.Type = line.split(\\\":\\\")[1].strip()\",\n \"def get_description(self):\\n return self.bot_data_file[\\\"description\\\"]\",\n \"def _load_robot_description(self):\\n name = \\\"robot_description\\\" # self._widget.robot_description_edit.text()\\n self._robot_description_xml_root = None\\n try:\\n xml = rospy.get_param(name)\\n self._robot_description_xml_root = ET.fromstring(xml)\\n except KeyError as e:\\n rospy.logerr(\\n \\\"Failed to get robot description from param %s : %s\\\" % (name, e))\\n return\\n except:\\n raise\",\n \"def load_eli5(self, opt):\\n dp = opt['datapath']\\n dt = opt['datatype'].split(':')[0]\\n eli_path = \\\"eli5/processed_data/selected_15_1/explainlikeimfive_\\\"\\n fname = os.path.join(dp, eli_path + dt + \\\".json\\\")\\n if not PathManager.exists(fname):\\n raise FileNotFoundError(\\n f\\\"{fname} not found. Please follow the instructions found at \\\"\\n \\\"https://github.com/facebookresearch/ParlAI/tree/main/parlai/tasks/eli5/README.md\\\"\\n \\\" to construct the dataset.\\\"\\n )\\n opt['datafile'] = fname\\n with PathManager.open(fname) as json_file:\\n data = json.load(json_file)\\n ds = []\\n for d in data:\\n if self.opt['knowledge']:\\n text = d['document'] + \\\"\\\\n\\\" + d['question']\\n else:\\n text = d['question']\\n act = {\\n 'id': 'eli5',\\n 'text': text,\\n 'labels': [d['answer']],\\n 'episode_done': True,\\n }\\n ds.append(act)\\n return ds\",\n \"def description(self):\\n if self._description is None:\\n self._load()\\n return self._description\",\n \"def update_experiment_description(self, experiment_id, description):\\n return self.dbclient.update_by_id(Tables.EXPERIMENTS, experiment_id, {\\n ExperimentAttr.DESC: description\\n })\",\n \"def load_description():\\n with open('description.txt') as description:\\n return [line.strip() for line in description]\",\n \"def load(self):\\n self.data = NSPSpecIO().read(self.path)\",\n \"def load_experiment(self):\\n load_dir = select_dir(os.getcwd())\\n if load_dir is not None:\\n if os.path.isfile(os.path.join(load_dir, 'conf', 'config')):\\n self.load_main(load_dir)\\n else:\\n msg_window('missing conf/config file, not experiment directory')\\n return\\n\\n if self.t is None:\\n self.t = Tabs(self)\\n self.vbox.addWidget(self.t)\\n self.t.clear_configs()\\n self.t.load_conf(load_dir)\\n\\n self.set_experiment(True)\\n else:\\n msg_window('please select valid conf directory')\",\n \"def load(self, path):\\n with open(path, 'rb') as fp:\\n me = pickle.load(fp)\\n self.exp = me[\\\"exp\\\"] # type: Experiment\\n with suppress_errors(\\\"output root directory may have changed\\\"):\\n self.mru_exp_root = self.exp.root\\n self.chdir()\\n self.imdb = self.exp.imdb\\n self.exp_df = me[\\\"exp_df\\\"]\\n with suppress_errors(\\\"caffenet may no longer exist\\\"):\\n self.caffenet = self.exp.caffenet\\n with suppress_errors(\\\"caffemodel may no longer exist\\\"):\\n self.caffemodel = self.exp.caffemodel\\n with suppress_errors(\\\"data directory may have changed\\\"):\\n self.mru_exp_data = self.exp.data\\n self.lbl_exp_data.setText(self.mru_exp_data)\\n self.edt_caffemodel.setText(self.caffemodel)\\n self.edt_caffenet.setText(self.caffenet)\\n self.lbl_exp_data.setText(self.mru_exp_data)\\n if self.exp_df is not None:\\n model = PandasModel(self.exp_df)\\n self.table_imdb.setModel(model)\\n self.table_imdb.show()\\n # Update the status label\\n self.lbl_last_status.setText(str(self.exp))\",\n \"def get_description():\\n desc = dict()\\n desc[\\\"cache\\\"] = 3600\\n desc[\\\"data\\\"] = True\\n desc[\\n \\\"description\\\"\\n ] = \\\"\\\"\\\"This plot is not meant for interactive use, but a backend for\\n SPS plots.\\n \\\"\\\"\\\"\\n desc[\\\"arguments\\\"] = [\\n dict(\\n type=\\\"text\\\",\\n name=\\\"pid\\\",\\n default=\\\"202012300005-KDVN-WWUS83-SPSDVN\\\",\\n label=\\\"IEM generated up to 35 char product identifier:\\\",\\n ),\\n dict(\\n type=\\\"int\\\",\\n default=0,\\n name=\\\"segnum\\\",\\n label=\\\"Product Segment Number (starts at 0):\\\",\\n ),\\n ]\\n return desc\",\n \"def test_load_experiment(self):\\n exp = Experiment(self.epath,\\n normalization='ch0',\\n auto_alignment=False)\\n self.assertTrue(isinstance(exp, Experiment))\",\n \"def load_demo():\\n\\tprint(\\\"\\\"\\\"\\n\\tBreast Cancer Wisconsin dataset. It contains a total of 569 samples of tumor and malignant cells. \\n\\tData labeled 1 corresponds to malignant cells, while data labeled 0 corresponds to benign cells. \\n\\tThe 30 characteristics contain real values obtained from images of cell nuclei. For more information:\\n\\n\\t\\t\\thttp://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic)\\n\\n\\n\\tThe returned value is a dictionary where 'x_data' are the predictor variables, 'y_data' the class \\n\\tlabels and 'features' the name of the characteristics.\\n\\t\\\"\\\"\\\")\\n\\tpath = '/'.join(os.path.abspath(pywinEA.__file__).split('/')[:-1])\\n\\t\\n\\tdata = pd.read_csv(path+'/dataset/data/BreastCancerWisconsin.csv', index_col=0)\\n\\tx_data = data.iloc[:, 1:].values\\n\\ty_data = data.iloc[:, 0].values\\n\\tfeatures = data.columns[1:].values\\n\\n\\t# Transform labels\\n\\ty_data[np.where(y_data == 'M')] = 1\\n\\ty_data[np.where(y_data == 'B')] = 0\\n\\ty_data = y_data.astype(int)\\n\\n\\treturn {'x_data': x_data, 'y_data': y_data, 'features': features}\",\n \"def load_description(path_dir=PATH_ROOT, filename=\\\"DOCS.md\\\"):\\n with open(os.path.join(path_dir, filename)) as f:\\n long_description = f.read()\\n return long_description\",\n \"def set_description(self, data):\\n self._description = self._uni(data)\",\n \"def load_training_data(s3: str = \\\"s3://epam-hack4med-dataset\\\") -> pd.DataFrame:\\n # Load labels\\n df_labels = pd.read_csv(f\\\"{s3}/CRACoV-ETYKIETY.csv\\\")\\n df_labels[id_cols] = df_labels[id_cols].astype(int)\\n df_labels = df_labels.set_index(id_cols)\\n labels = df_labels[[basic_target]]\\n idx = labels.index\\n\\n # Load hospital admission file (PRZYJECIE)\\n df_admission = pd.read_csv(f\\\"{s3}/CRACoV-PRZYJECIE.csv\\\")\\n binary_adm_vars = [x for x in basic_adm_vars if df_admission[x].isin([\\\"Tak\\\", \\\"Nie\\\"]).any()]\\n other_adm_vars = [x for x in basic_adm_vars if x not in binary_adm_vars]\\n adm = df_admission.copy()\\n adm = adm[id_cols + binary_adm_vars + other_adm_vars]\\n adm = adm.set_index(id_cols).reindex(idx)\\n \\n # Load biochem analyses\\n biochem_raw = pd.read_csv(f\\\"{s3}/CRACoV-BIOCHEMIA.csv\\\", parse_dates=['DATA_WYK']).sort_values('DATA_WYK')\\n biochem = (\\n biochem_raw.loc[biochem_raw.KOD.isin(basic_bio_codes)]\\n .pivot_table(index=['LP.', 'ID_LAB'], columns='KOD', values='WYNIK', aggfunc='first')\\n .reindex(idx)\\n )\\n # Merge it all together\\n Xy_raw = pd.concat([labels, adm, biochem], axis='columns')\\n return Xy_raw\",\n \"def refresh_description(self):\\n # AIN\\n code_ain = (self.CODE >> 12) & 0b0111\\n # DICT_AIN = [[0, 1], [0, 3], [1, 3], [2, 3], [0, 4], [1, 4], [2, 4], [3, 4]]\\n ind_p, ind_n = DICT_AIN[code_ain]\\n self.AINP = \\\"AIN\\\" + str(ind_p)\\n self.AINN = \\\"AIN\\\" + str(ind_n)\\n if (ind_n == 4): self.AINN = \\\"GND\\\"\\n\\n # FSR\\n code_fsr = (self.CODE >> 9) & 0b0000111\\n # DICT_FSR = [\\\"6.144V\\\", \\\"4.096V\\\", \\\"2.048V\\\", \\\"1.024V\\\", \\\"0.512V\\\", \\\"0.256V\\\"]\\n self.FSR = DICT_FSR[code_fsr]\\n\\n # MODE\\n\\n # rate\\n code_rate = (self.CODE >> 5) & 0b00000000111\\n # DICT_RATE = [\\\"8 SPS\\\", \\\"16 SPS\\\", \\\"32 SPS\\\", \\\"64 SPS\\\", \\\"128 SPS\\\", \\\"250 SPS\\\", \\\"475 SPS\\\", \\\"860 SPS\\\"]\\n self.RATE = DICT_RATE[code_rate]\",\n \"def set_description(self, desc: str) -> None:\\n self.metadata.data[\\\"description\\\"] = desc\",\n \"def loadExample(self, exID):\\r\\n return \\\"\\\"\",\n \"def load(self):\\n basePath = './examples/'\\n file = \\\"print8.ls8\\\"\\n # file = \\\"mult.ls8\\\"\\n # file = \\\"stack.ls8\\\"\\n # file = \\\"call.ls8\\\"\\n file = \\\"sctest.ls8\\\"\\n if len(sys.argv) > 1:\\n file = sys.argv[1]\\n address = 0\\n\\n with open(basePath + file, \\\"r\\\") as f:\\n for line in f:\\n line = line.split(\\\"#\\\")\\n\\n try:\\n v = int(line[0], 2)\\n except ValueError:\\n continue\\n # print(v)\\n self.ram[address] = v\\n address += 1\",\n \"def _load_molecule(self):\\n self.pymol = pybel.readstring(self.input_format, self.file_dic['input'])\",\n \"def gmcp_setup_data(self):\\n yield \\\"Core.Supports.Debug\\\", 20\\n yield \\\"Core.Supports.Set\\\", [ \\\"MG.char 1\\\", \\\"MG.room 1\\\", \\\"comm.channel 1\\\" ]\",\n \"def load_problem_definition():\\n # TODO this should be expanded to include all definitions\\n with open(Path(\\\"config.yml\\\")) as file:\\n CONFIG = yaml.full_load(file)\\n\\n problem_definition_config = CONFIG[\\\"problem_definition\\\"]\\n\\n num_days = problem_definition_config[\\\"num_days\\\"]\\n hotel_index = problem_definition_config[\\\"hotel_index\\\"]\\n\\n problem_definition = {\\\"num_days\\\": num_days, \\\"hotel_index\\\": hotel_index}\\n\\n return problem_definition\",\n \"def load_qc(self):\\n rejectval = self.config.getint('profiles', 'qcreject') \\n self.qc = self.read_var(self.qcvar)\\n self.qc = self.qc.astype('unicode')\\n self.qc[self.qc == '1'] = 1\\n self.qc[np.logical_or(self.qc=='4', self.qc == '0')] = 0\\n self.qc = self.qc.astype(bool)\\n self.test_shape(self.qcvar, self.qc.shape, 2)\",\n \"def test_description(self):\\n\\n for desc in TEST_DESCS:\\n self.colorspace.setDescription(desc)\\n self.assertEqual(desc, self.colorspace.getDescription())\",\n \"def load_metadata_from_desc_file(self, desc_file, partition='train',\\n max_duration=10.0):\\n logger.info('Reading description file: {} for partition: {}'\\n .format(desc_file, partition))\\n audio_paths, durations, texts, arpabets = [], [], [], []\\n with open(desc_file) as json_line_file:\\n for line_num, json_line in enumerate(json_line_file):\\n try:\\n spec = json.loads(json_line)\\n if float(spec['duration']) > max_duration:\\n continue\\n audio_paths.append(spec['key'])\\n durations.append(float(spec['duration']))\\n texts.append(spec['text'])\\n if self.use_arpabets:\\n arpabets.append(spec['arpabet'])\\n except Exception as e:\\n # Change to (KeyError, ValueError) or\\n # (KeyError,json.decoder.JSONDecodeError), depending on\\n # json module version\\n logger.warn('Error reading line #{}: {}'\\n .format(line_num, json_line))\\n logger.warn(str(e))\\n\\n if not self.use_arpabets:\\n arpabets = [''] * len(audio_paths)\\n\\n if partition == 'train':\\n self.train_audio_paths = audio_paths\\n self.train_durations = durations\\n self.train_texts = texts\\n self.train_arpabets = arpabets\\n elif partition == 'validation':\\n self.val_audio_paths = audio_paths\\n self.val_durations = durations\\n self.val_texts = texts\\n self.val_arpabets = arpabets\\n elif partition == 'test':\\n self.test_audio_paths = audio_paths\\n self.test_durations = durations\\n self.test_texts = texts\\n self.test_arpabets = arpabets\\n else:\\n raise Exception(\\\"Invalid partition to load metadata. \\\"\\n \\\"Must be train/validation/test\\\")\",\n \"def load_mpeg7():\\n # List of image file names\\n dataset_directory = os.path.join(root_directory,'MPEG7')\\n filenames = os.listdir(dataset_directory)\\n filenames.sort()\\n\\n # List of numpy array; each row is a Image of the dataset\\n data = []\\n\\n # Numpy array of labels associated to each class of image\\n target = np.empty([len(filenames), ])\\n\\n previous_label = ''\\n class_num = -1\\n index = 0\\n\\n for index, filename in enumerate(filenames):\\n data.append(Bitmap(io.imread(os.path.join(dataset_directory, filename))))\\n file_label = filename.split('-')[0]\\n\\n if(previous_label != file_label):\\n previous_label = file_label\\n class_num += 1\\n target[index] = class_num\\n else:\\n target[index] = class_num\\n\\n return {'bitmaps': data, 'targets': target}\",\n \"def load_mc(filename):\\n global simulator\\n if simulator is None:\\n print \\\"program is not started\\\"\\n else:\\n simulator.load_mc(filename)\",\n \"def load_dataset(self, folder: str):\\n # just in case the user forgot to add a / to the end of his path\\n if folder[-1] != \\\"/\\\":\\n folder += \\\"/\\\"\\n\\n files = os.listdir(folder)\\n description_file = [name for name in files if name.__contains__(\\\"description\\\")]\\n instance_files = sorted([name for name in files if name.__contains__(\\\"instance\\\")])\\n\\n # make sure only one description file exists\\n assert len(description_file) == 1\\n\\n description = None\\n description_file = description_file[0]\\n with open(folder + description_file, \\\"rb\\\") as file:\\n description = pickle.load(file)\\n\\n dataset = []\\n for instance_file in instance_files:\\n with open(folder + instance_file, \\\"rb\\\") as file:\\n dataset.append(pickle.load(file))\\n\\n # test if everything is alright (tests the easy parameters for every instance)\\n assert len(dataset) == description[\\\"num_instances\\\"]\\n for instance in dataset:\\n assert len(instance) == description[\\\"num_end_cells\\\"]\\n\\n return dataset, description\",\n \"def test_import(self):\\r\\n descriptor = self.get_dummy_course(START)\",\n \"def test_answerfile_ipv6(tmpdir):\\n\\n _test_answerfile(tmpdir, \\\"cgcs_config.ipv6\\\")\",\n \"def get_description(self):\\n try:\\n long_desc = self.__data[\\\"descriptions\\\"][\\\"MM - \\\" + self.__name][\\\"text\\\"].replace(\\\"<p>\\\", \\\"\\\").split('</p>')[0]\\n return long_desc\\n except:\\n return None\",\n \"def load_experiment(file_name: str):\\n exp = Experiment2P()\\n # initialize the lazy-load objects with empty lists\\n exp.tail_data = []\\n exp.replaced_tail_frames = []\\n exp.laser_data = []\\n exp.all_c = []\\n exp.all_dff = []\\n exp.func_stacks = []\\n with h5py.File(file_name, 'r') as dfile:\\n exp.version = dfile[\\\"version\\\"][()] # in future allows for version specific loading\\n try:\\n if exp.version == b\\\"unstable\\\" or exp.version == \\\"unstable\\\":\\n warnings.warn(\\\"Experiment file was created with development version of analysis code. Trying to \\\"\\n \\\"load as version 1\\\")\\n elif int(exp.version) > 2:\\n raise IOError(f\\\"File version {exp.version} is larger than highest recognized version '2'\\\")\\n except ValueError:\\n raise IOError(f\\\"File version {exp.version} not recognized\\\")\\n # load general experiment data\\n n_planes = dfile[\\\"n_planes\\\"][()] # inferrred property of class but used here for loading plane data\\n exp.experiment_name = dfile[\\\"experiment_name\\\"][()]\\n exp.original_path = dfile[\\\"original_path\\\"][()]\\n exp.scope_name = dfile[\\\"scope_name\\\"][()]\\n exp.comment = dfile[\\\"comment\\\"][()]\\n exp.tail_frame_rate = dfile[\\\"tail_frame_rate\\\"][()]\\n # load singular parameter dictionary\\n exp.info_data = exp._load_dictionary(\\\"info_data\\\", dfile)\\n # load tail-data modification flag if this is version 2\\n if int(exp.version) > 1:\\n exp.tail_data_augmented = dfile[\\\"tail_data_augmented\\\"][()]\\n # load per-plane data\\n for i in range(n_planes):\\n plane_group = dfile[str(i)]\\n exp.scanner_data.append(exp._load_dictionary(\\\"scanner_data\\\", plane_group))\\n exp.tail_data.append(plane_group[\\\"tail_data\\\"][()])\\n exp.projections.append(plane_group[\\\"projection\\\"][()])\\n if \\\"func_stack\\\" in plane_group:\\n exp.func_stacks.append(plane_group[\\\"func_stack\\\"][()])\\n if \\\"anat_projection\\\" in plane_group: # test if this experiment was dual-channel\\n exp.anat_projections.append(plane_group[\\\"anat_projection\\\"][()])\\n if \\\"tail_data\\\" in plane_group: # test if this experiment had tail data (for all planes)\\n exp.tail_data.append(plane_group[\\\"tail_data\\\"][()])\\n exp.bout_data.append(plane_group[\\\"bout_data\\\"][()])\\n exp.tail_frame_times.append(plane_group[\\\"tail_frame_time\\\"][()])\\n if int(exp.version) > 1 and \\\"replaced_tail_frames\\\" in plane_group:\\n exp.replaced_tail_frames.append(plane_group[\\\"replaced_tail_frames\\\"][()])\\n if \\\"laser_data\\\" in plane_group: # test if this experiment had laser data\\n exp.laser_data.append(plane_group[\\\"laser_data\\\"][()])\\n exp.all_c.append(plane_group[\\\"C\\\"][()])\\n exp.all_dff.append(plane_group[\\\"dff\\\"][()])\\n exp.all_centroids.append(plane_group[\\\"centroids\\\"][()])\\n exp.all_sizes.append(plane_group[\\\"sizes\\\"][()])\\n exp.all_spatial.append(plane_group[\\\"spatial\\\"][()])\\n ps = plane_group[\\\"mcorr_dict\\\"][()]\\n exp.mcorr_dicts.append(json.loads(ps))\\n ps = plane_group[\\\"cnmf_extract_dict\\\"][()]\\n exp.cnmf_extract_dicts.append(json.loads(ps))\\n ps = plane_group[\\\"cnmf_val_dict\\\"][()]\\n exp.cnmf_val_dicts.append(json.loads(ps))\\n exp.populated = True\\n return exp\",\n \"def processDescrString(self):\\n\\t\\tself.descrString = self._getVal(4, 1)\",\n \"def help_load(self):\\n print(LOAD)\",\n \"def set_desc(self, annonce):\\n d = annonce.find_element_by_class_name('prdtBILDesc.jsPrdtBILLink')\\n self.desc = d.text.splitlines()\",\n \"def get_protocol_init_data(self):\\n\\t\\tcontents = self.archive.read_file('replay.initData')\\n\\t\\treturn self.protocol.decode_replay_initdata(contents)\",\n \"def load(cls, labpath: str) -> None:\\n raise NotImplementedError\",\n \"def load_inst(self):\\n self.sanity_check()\\n\\n fname_pub_auth_all = ''.join([self.config.dir_data, '/',\\n self.config.fname_pub_auth_all, '_',\\n self.config.experiment_id, '.pk'])\\n fname_pub_auth_top = ''.join([self.config.dir_data, '/',\\n self.config.fname_pub_auth_top, '_',\\n self.config.experiment_id, '.pk'])\\n fname_pub_inst_all = ''.join([self.config.dir_data, '/',\\n self.config.fname_pub_inst_all, '_',\\n self.config.experiment_id, '.pk'])\\n fname_pub_inst_top = ''.join([self.config.dir_data, '/',\\n self.config.fname_pub_inst_top, '_',\\n self.config.experiment_id, '.pk'])\\n self.pub_auth_all = pickle.load(open(fname_pub_auth_all, 'rb'))\\n self.pub_auth_top = pickle.load(open(fname_pub_auth_top, 'rb'))\\n self.pub_inst_all = pickle.load(open(fname_pub_inst_all, 'rb'))\\n self.pub_inst_top = pickle.load(open(fname_pub_inst_top, 'rb'))\\n\\n fname_pub_history = ''.join([self.config.dir_data, '/history_',\\n self.config.experiment_id, '.pk'])\\n self.history = pickle.load(open(fname_pub_history, 'rb'))\\n\\n fname_pub_staff = ''.join([self.config.dir_data, '/staff_',\\n self.config.experiment_id, '.pk'])\\n self.staff = pickle.load(open(fname_pub_staff, 'rb'))\",\n \"def part_6():\\n\\n raise NotImplementedError\",\n \"def config_section_data():\\n config_data = u\\\"\\\"\\\"[feeds]\\n# comma separated section names. ex. sqlserver_feed,file_feed\\nfeed_names=<your feeds>\\nreload=true\\n# use reload_types to limit the types of objects when reload=true.\\n# Ex: incident,task,note,artifact,attachment,<data_table_api_name>\\nreload_types=\\n# set to true if ElasticSearch errors occur during reload=true\\nreload_query_api_method=false\\n\\n# feed_data is the default message destination that will be listened to\\nqueue=feed_data\\n\\n# set to true if attachment data should be part of payload send to plugins\\ninclude_attachment_data=false\\n# if necessary, specify the supported workspace (by label, case sensitive) and the list of feeds associated with it\\n# ex: 'Default Workspace': ['sqlserver_feed'], 'workspace A': ['kafka_feed', 'resilient_feed']\\nworkspaces=\\n\\\"\\\"\\\"\\n return config_data\",\n \"def test_load_from_v5(self) -> None:\\n self.save_new_valid_exploration(\\n 'Exp1', 'user@example.com', end_state_name='End')\\n collection = collection_domain.Collection.from_yaml(\\n 'cid', self.YAML_CONTENT_V5)\\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)\",\n \"def load():\\r\\n\\r\\n data = dict()\\r\\n global IMAGES_FILE_PATH\\r\\n chdir(IMAGES_FILE_PATH)\\r\\n try:\\r\\n with open('Descriptions_File.txt', 'r') as f:\\r\\n reader = csv.DictReader(f, delimiter=',')\\r\\n for row in reader:\\r\\n url = row['url']\\r\\n data[url] = row['description']\\r\\n f.close()\\r\\n except Exception: # If no Descriptions found\\r\\n return data\\r\\n return data\",\n \"def get_club_description(club):\\n elts = get_elements_with_class(club, 'em', '')\\n if len(elts) < 1:\\n return ''\\n return elts[0].text\\n\\n return ''\",\n \"def get_model_description() -> Dict[str, Any]:\\n\\n desc_file = os.path.join(os.path.dirname(__file__), \\\"model_files\\\", \\\"description.yaml\\\")\\n if not os.path.exists(desc_file):\\n raise FileNotFoundError(f\\\"File not found - {desc_file}\\\")\\n else:\\n with open(desc_file, \\\"r\\\") as f:\\n desc = yaml.safe_load(f.read())\\n if desc is None:\\n raise RuntimeError(f\\\"Error parsing {desc_file}\\\")\\n return desc\",\n \"def __init__(self, inputfolder, gpu_id=0, model=None):\\n CaffeLoader.__init__(self, inputfolder, gpu_id=gpu_id)\\n logger.info('loading deploy.prototxt from %s' % inputfolder)\\n if model:\\n self.setModel(model)\\n if self.caffemodel and self.protofile:\\n self.net = caffe.Net(self.protofile, caffe.TEST)\\n else:\\n logger.error('Cannot find prototxt or caffemodel file')\\n sys.exit(0)\",\n \"def init_from_file(self):\\n self.src.load('start.00') \\n self.oe1.load('start.01')\\n #self.det.load('start.02')\\n print('NOTE: variables loaded from start.00/start.01 files')\",\n \"def get_description(self):\\n des = self.soup.find('div', id = 'zh-topic-desc').find('div', class_ = 'zm-editable-content')\\n if des:\\n return des.get_text(strip = True).encode(CODE)\\n return None\",\n \"def test_fif6(self):\\n # TODO this should be ideally in setUpClass, but then we hit a bug\\n # with VppIpRoute incorrectly reporting it's present when it's not\\n # so we need to manually remove the vpp config, thus we cannot have\\n # it shared for multiple test cases\\n self.tun_ip6 = \\\"1002::1\\\"\\n\\n self.gre6 = VppGreInterface(self, self.src_if.local_ip6, self.tun_ip6)\\n self.gre6.add_vpp_config()\\n self.gre6.admin_up()\\n self.gre6.config_ip6()\\n\\n self.vapi.ip_reassembly_enable_disable(\\n sw_if_index=self.gre6.sw_if_index, enable_ip6=True\\n )\\n\\n self.route6 = VppIpRoute(\\n self,\\n self.tun_ip6,\\n 128,\\n [VppRoutePath(self.src_if.remote_ip6, self.src_if.sw_if_index)],\\n )\\n self.route6.add_vpp_config()\\n\\n self.reset_packet_infos()\\n for i in range(test_packet_count):\\n info = self.create_packet_info(self.src_if, self.dst_if)\\n payload = self.info_to_payload(info)\\n # Ethernet header here is only for size calculation, thus it\\n # doesn't matter how it's initialized. This is to ensure that\\n # reassembled packet is not > 9000 bytes, so that it's not dropped\\n p = (\\n Ether()\\n / IPv6(src=self.src_if.remote_ip6, dst=self.dst_if.remote_ip6)\\n / UDP(sport=1234, dport=5678)\\n / Raw(payload)\\n )\\n size = self.packet_sizes[(i // 2) % len(self.packet_sizes)]\\n self.extend_packet(p, size, self.padding)\\n info.data = p[IPv6] # use only IPv6 part, without ethernet header\\n\\n fragments = [\\n x\\n for _, i in self._packet_infos.items()\\n for x in fragment_rfc8200(i.data, i.index, 400)\\n ]\\n\\n encapped_fragments = [\\n Ether(dst=self.src_if.local_mac, src=self.src_if.remote_mac)\\n / IPv6(src=self.tun_ip6, dst=self.src_if.local_ip6)\\n / GRE()\\n / p\\n for p in fragments\\n ]\\n\\n fragmented_encapped_fragments = [\\n x\\n for p in encapped_fragments\\n for x in (\\n fragment_rfc8200(\\n p, 2 * len(self._packet_infos) + p[IPv6ExtHdrFragment].id, 200\\n )\\n if IPv6ExtHdrFragment in p\\n else [p]\\n )\\n ]\\n\\n self.src_if.add_stream(fragmented_encapped_fragments)\\n\\n self.pg_enable_capture(self.pg_interfaces)\\n self.pg_start()\\n\\n self.src_if.assert_nothing_captured()\\n packets = self.dst_if.get_capture(len(self._packet_infos))\\n self.verify_capture(packets, IPv6)\\n\\n # TODO remove gre vpp config by hand until VppIpRoute gets fixed\\n # so that it's query_vpp_config() works as it should\\n self.gre6.remove_vpp_config()\",\n \"def descr(self):\\n return self.recipe.get(\\\"descr\\\", \\\"no description\\\")\",\n \"def load_crawl():\\n\\n\\tmodule_path = dirname(__file__)\\n\\twith open(join(module_path, 'data', 'train2.csv')) as csv_file:\\n\\t\\tdata_file = csv.reader(csv_file)\\n\\t\\ttemp = next(data_file)\\n\\t\\tglobal n_samples\\n\\t\\tn_samples = int(temp[0])\\n\\t\\tglobal n_features\\n\\t\\tn_features = int(temp[1])\\n\\t\\tprint \\\"n samples \\\" + str((n_samples))\\n\\t\\tprint \\\"n_features\\\" + str((n_features))\\n\\t\\ttarget_names = np.array(temp[2:4])\\n\\t\\tdata = np.empty((n_samples, n_features))\\n\\t\\ttarget = np.empty((n_samples,), dtype=np.int)\\n\\n\\t\\tfor count, value in enumerate(data_file):\\n\\t\\t\\tdata[count] = np.asarray(value[:-1], dtype=np.float)\\n\\t\\t\\ttarget[count] = np.asarray(value[-1], dtype=np.int)\\n\\t\\t\\t#print \\\"data is \\\" + str(data[count])\\n\\t\\t\\t#print \\\"target is \\\" + str(target[count])\\n\\t\\tprint \\\"Number of target records is \\\" + str(len(target))\\n\\t#with open(join(module_path, 'descr', 'train.rst')) as rst_file:\\n\\t#\\tfdescr = rst_file.read()\\n\\n\\treturn Bunch(data=data, target=target,\\n\\t\\t\\t target_names=target_names,\\n\\t\\t\\t DESCR=None,\\n\\t\\t\\t feature_names = ['evalCount', 'setInterval', 'setTimeout', 'link', \\n\\t\\t\\t\\t\\t\\t\\t 'search', 'exec','escape', 'unescape', 'ratio', \\n\\t\\t\\t\\t\\t\\t\\t 'emtropyAvg', 'entropyScript', 'longStrings', \\n\\t\\t\\t\\t\\t\\t\\t 'maxEntropy', 'stringAvg', 'maxLength', 'longVarFunc', \\n\\t\\t\\t\\t\\t\\t\\t 'stringAssignments', 'stringModFuncsCount', 'eventFuncsCount', \\n\\t\\t\\t\\t\\t\\t\\t 'domModFuncsCounter', 'suspStrings', 'whiteSpaceRatio', \\n\\t\\t\\t\\t\\t\\t\\t 'hexaStrings', 'maxNonPrintableCharactersinString', 'lineAvg', \\n\\t\\t\\t\\t\\t\\t\\t 'iframeCount', 'malTagCount', 'jsLength'])\",\n \"def test_get_description(self):\\n description = get_description(self.work_data[\\\"description\\\"])\\n expected = \\\"First in the Old Kingdom/Abhorsen series.\\\"\\n self.assertEqual(description, expected)\",\n \"def load_epicsLive(self, instrument=None, **kwargs):\\n# if 'instrument' in kwargs:\\n# instrument = kwargs.get('instrument')\\n# self.instrument = instrument\\n if not instrument:\\n instrument = self.instrument\\n\\n self.ioc = psioc.IOC(instrument=self.instrument)\\n if self.instrument in ['cxi', 'mfx', 'xcs', 'mec']:\\n self.ioc.load_cfg('xrt')\\n \\n print 'Loading EpicsSets for', instrument\\n self.epicsLive = lcls_devices.EpicsSets(instrument=instrument, **kwargs)\\n self.update_epicsLive()\",\n \"def load_explainer(self):\\n explainer_path = os.path.join(self.model_path, \\\"explainer.dill\\\")\\n csv_path = os.path.join(self.model_path, self.__csv_path)\\n if os.path.isfile(explainer_path):\\n with open(explainer_path, \\\"rb\\\") as f:\\n self.__explainer = dill.load(f)\\n elif os.path.isfile(csv_path):\\n print(\\\"[WARN] Making new explainer!\\\")\\n self.__explainer = make_explainer(\\n pd.read_csv(csv_path),\\n self.FEATURES\\n )\\n with open(explainer_path, \\\"wb\\\") as f:\\n dill.dump(self.__explainer, f)\\n else:\\n print(\\\"[WARN] Explainer not found!\\\")\",\n \"def data_description(hf, var):\\n desc = hf['/output/data/%s' % var].attrs['description']\\n if type(desc) != str:\\n desc = desc.decode('UTF-8')\\n\\n if desc:\\n return desc\\n return var\",\n \"def load_caffe_model(self):\\n print(\\\"Loading caffe model used for detecting a human_blob.\\\")\\n\\n # Use cv2.dnn function to read the caffe model used for detecting faces and set preferable target.\\n # self.detector = cv2.dnn.readNetFromCaffe(os.path.join(\\n # os.path.dirname(os.path.realpath(__file__)),\\n # prototxt_path),\\n # os.path.join(\\n # os.path.dirname(os.path.realpath(__file__)),\\n # human_model_path))\\n self.detector = cv2.dnn.readNetFromCaffe(prototxt=\\\"human_detection_model/MobileNetSSD_deploy.prototxt.txt\\\",\\n caffeModel=\\\"human_detection_model/MobileNetSSD_deploy.caffemodel\\\")\\n self.detector.setPreferableTarget(Rescue_PI.preferable_target)\",\n \"def description(self, description) :\\n\\t\\ttry :\\n\\t\\t\\tself._description = description\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def define_description(self):\\n self._description = 'NODDI-based processing of DWI datasets.'\",\n \"def load(f, model, nper=1, ext_unit_dict=None):\\r\\n\\r\\n if model.verbose:\\r\\n sys.stdout.write('loading bas6 package file...\\\\n')\\r\\n\\r\\n if not hasattr(f, 'read'):\\r\\n filename = f\\r\\n f = open(filename, 'r')\\r\\n\\r\\n if model.nrow_ncol_nlay_nper != (0, 0, 0, 0):\\r\\n nrow, ncol, nlay, nper = model.nrow_ncol_nlay_nper\\r\\n\\r\\n t = f.readline().strip()\\r\\n maxrivr = int(t[0])\\r\\n irivcb = int(t[1])\\r\\n\\r\\n stress_period_data = mflist_reader(f, Modflow88Riv, nper)\\r\\n\\r\\n return Modflow88Riv(model, irivcb, stress_period_data)\",\n \"def load(self):\\n super().load()\\n for channel in range(self.n_channels):\\n c_str = 'Channel_{0:02d}'.format(channel)\\n if c_str not in self:\\n log.info(f'{c_str} not found in config yaml, adding it now with defaults')\\n self.set(c_str, {'amplitude': 1.5, 'dc_offset': 0.0}, save_config=True)\\n\\n val = self.get(c_str)\\n self.amplitude(channel, val['amplitude'])\\n self.offset(channel, val['dc_offset'])\\n self._set_register(0, self.get('clock_delay', 1000)//100 + self._seq_length//100 - 1)\",\n \"def load_config(self):\\n with h5py.File(iop.fields, 'r') as hf:\\n # fields = hf.get('data')[:]\\n config = hf.get('config')[:]\\n return config\",\n \"def load(self):\\n raise NotImplementedError\",\n \"def load(self):\\n raise NotImplementedError\",\n \"def load(extended=False):\\n\\n _fetch_large()\\n if extended:\\n return _load(cache_experiment_extended, _parse_experiment)\\n else:\\n return _load(cache_experiment, _parse_experiment)\",\n \"def description(self):\\n return self.marmite_tree['description']\",\n \"def load(self):\\n\\n logging.info(\\\"Loading the `BeagleSummaryCatalogue` file: \\\" + self.file_name)\\n\\n name = getPathForData(self.file_name)\\n self.hdulist = fits.open(name)\",\n \"def load_data(self) -> None:\",\n \"def load(self):\\n self.classifier = joblib.load(\\\"data/models/repeatsfinder/repeatsfinder.joblib\\\")\",\n \"def _read_opt_mpl(self, code, *, desc):\\n _type = self._read_opt_type(code)\\n _size = self._read_unpack(1)\\n if _size < 2:\\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\\n _smvr = self._read_binary(1)\\n _seqn = self._read_unpack(1)\\n\\n opt = dict(\\n desc=desc,\\n type=_type,\\n length=_size + 2,\\n seed_len=_IPv6_Opts_SEED.get(int(_smvr[:2], base=2)),\\n flags=dict(\\n max=bool(int(_smvr[2], base=2)),\\n verification=bool(int(_smvr[3], base=2)),\\n ),\\n seq=_seqn,\\n )\\n\\n _kind = _smvr[:2]\\n if _kind == '00':\\n if _size != 2:\\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\\n elif _kind == '01':\\n if _size != 4:\\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\\n opt['seed_id'] = self._read_unpack(2)\\n elif _kind == '10':\\n if _size != 10:\\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\\n opt['seed_id'] = self._read_unpack(8)\\n elif _kind == '11':\\n if _size != 18:\\n raise ProtocolError(f'{self.alias}: [OptNo {code}] invalid format')\\n opt['seed_id'] = self._read_unpack(16)\\n else:\\n opt['seed_id'] = self._read_unpack(_size-2)\\n\\n _plen = _size - opt['seed_len']\\n if _plen:\\n self._read_fileng(_plen)\\n\\n return opt\",\n \"async def description(ctx, bot: typing.Union[discord.Member, discord.User]):\\n data = await make_request(\\\"https://www.motiondevelopment.top/api/v1.2/bots/\\\", bot.id)\\n if not bot.bot:\\n return await r(ctx, \\\"Not a bot.\\\")\\n\\n if len(data[\\\"Big_desc\\\"]) > 2000:\\n desc = data[\\\"Big_desc\\\"][:2000] + \\\\\\n f\\\"...\\\\n[View original page for full description](https://www.motiondevelopment.top/bots/{bot.id})\\\"\\n else:\\n desc = data[\\\"Big_desc\\\"]\\n await em(ctx, embed=discord.Embed(color=0xfecdea, description=desc))\",\n \"def description(self):\\r\\n if \\\"description\\\" in self.data:\\r\\n return self.data[\\\"description\\\"]\\r\\n return None\",\n \"def createExpCfg(expCfgPathAndName):\\n\\n print (\\\"Loading experiment config file: \\\" + expCfgPathAndName)\\n \\n from os import path\\n filePath = path.dirname(path.abspath(expCfgPathAndName))\\n\\n # This is where the parser is called.\\n expCfg = ConfigObj(expCfgPathAndName, configspec=filePath + '/expCfgSpec.ini', raise_errors = False, file_error = False)\\n\\n validator = Validator()\\n expCfgOK = expCfg.validate(validator)\\n if expCfgOK == True:\\n print (\\\"Experiment config file parsed correctly\\\")\\n else:\\n print ('Experiment config file validation failed!')\\n res = expCfg.validate(validator, preserve_errors=True)\\n for entry in flatten_errors(expCfg, res):\\n # 1each entry is a tuple\\n section_list, key, error = entry\\n if key is not None:\\n section_list.append(key)\\n else:\\n section_list.append('[missing section]')\\n section_string = ', '.join(section_list)\\n if error == False:\\n error = 'Missing value or section.'\\n print (section_string, ' = ', error)\\n sys.exit(1)\\n if expCfg.has_key('_LOAD_'):\\n for ld in expCfg['_LOAD_']['loadList']:\\n print ('Loading: ' + ld + ' as ' + expCfg['_LOAD_'][ld]['cfgFile'])\\n curCfg = ConfigObj(expCfg['_LOAD_'][ld]['cfgFile'], configspec = expCfg['_LOAD_'][ld]['cfgSpec'], raise_errors = True, file_error = True)\\n validator = Validator()\\n expCfgOK = curCfg.validate(validator)\\n if expCfgOK == True:\\n print (\\\"Experiment config file parsed correctly\\\")\\n else:\\n print ('Experiment config file validation failed!')\\n res = curCfg.validate(validator, preserve_errors=True)\\n for entry in flatten_errors(curCfg, res):\\n # each entry is a tuple\\n section_list, key, error = entry\\n if key is not None:\\n section_list.append(key)\\n else:\\n section_list.append('[missing section]')\\n section_string = ', '.join(section_list)\\n if error == False:\\n error = 'Missing value or section.'\\n print (section_string, ' = ', error)\\n sys.exit(1)\\n expCfg.merge(curCfg)\\n\\n return expCfg\",\n \"def _load_metadata(self):\\n\\n cub_dir = self.root / \\\"CUB_200_2011\\\"\\n images_list: Dict[int, List] = OrderedDict()\\n\\n with open(str(cub_dir / \\\"train_test_split.txt\\\")) as csv_file:\\n csv_reader = csv.reader(csv_file, delimiter=\\\" \\\")\\n for row in csv_reader:\\n img_id = int(row[0])\\n is_train_instance = int(row[1]) == 1\\n if is_train_instance == self.train:\\n images_list[img_id] = []\\n\\n with open(str(cub_dir / \\\"images.txt\\\")) as csv_file:\\n csv_reader = csv.reader(csv_file, delimiter=\\\" \\\")\\n for row in csv_reader:\\n img_id = int(row[0])\\n if img_id in images_list:\\n images_list[img_id].append(row[1])\\n\\n with open(str(cub_dir / \\\"image_class_labels.txt\\\")) as csv_file:\\n csv_reader = csv.reader(csv_file, delimiter=\\\" \\\")\\n for row in csv_reader:\\n img_id = int(row[0])\\n if img_id in images_list:\\n # CUB starts counting classes from 1 ...\\n images_list[img_id].append(int(row[1]) - 1)\\n\\n with open(str(cub_dir / \\\"bounding_boxes.txt\\\")) as csv_file:\\n csv_reader = csv.reader(csv_file, delimiter=\\\" \\\")\\n for row in csv_reader:\\n img_id = int(row[0])\\n if img_id in images_list:\\n box_cub = [int(float(x)) for x in row[1:]]\\n box_avl = [box_cub[1], box_cub[0], box_cub[3], box_cub[2]]\\n # PathsDataset accepts (top, left, height, width)\\n images_list[img_id].append(box_avl)\\n\\n images_tuples = []\\n for _, img_tuple in images_list.items():\\n images_tuples.append(tuple(img_tuple))\\n self._images = images_tuples # type: ignore\\n\\n # Integrity check\\n for row_check in self._images:\\n filepath = self.root / CUB200.images_folder / row_check[0]\\n if not filepath.is_file():\\n if self.verbose:\\n print(\\\"[CUB200] Error checking integrity of:\\\", filepath)\\n return False\\n\\n return True\",\n \"def load_crawl():\\n\\n\\tmodule_path = dirname(__file__)\\n\\twith open(sys.argv[1]) as csv_file:\\n\\t\\tdata_file = csv.reader(csv_file)\\n\\t\\ttemp = next(data_file)\\n\\t\\tn_samples = int(temp[0])\\n\\t\\tn_features = int(temp[1])\\n\\t\\ttarget_names = np.array(temp[2:4])\\n\\t\\tdata = np.empty((n_samples, n_features))\\n\\t\\ttarget = np.empty((n_samples,), dtype=np.int)\\n\\n\\t\\tfor count, value in enumerate(data_file):\\n\\t\\t\\tif len(value)<28:\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tdata[count] = np.asarray(value[:28], dtype=np.float)\\n\\t\\t\\t\\ttarget[count] = np.asarray(value[28], dtype=np.int)\\t\\n\\t\\t\\texcept:\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\t#print \\\"data is \\\" + str(data[count])\\n\\t\\t\\t#print \\\"target is \\\" + str(target[count])\\n\\n\\twith open(join(module_path, 'descr', 'crawl.rst')) as rst_file:\\n\\t\\tfdescr = rst_file.read()\\n\\n\\treturn Bunch(data=data, target=target,\\n\\t\\t\\t target_names=target_names,\\n\\t\\t\\t DESCR=fdescr,\\n\\t\\t\\t feature_names = ['evalCount', 'setInterval', 'setTimeout', 'link', \\n\\t\\t\\t\\t\\t\\t\\t 'search', 'exec','escape', 'unescape', 'ratio', \\n\\t\\t\\t\\t\\t\\t\\t 'emtropyAvg', 'entropyScript', 'longStrings', \\n\\t\\t\\t\\t\\t\\t\\t 'maxEntropy', 'stringAvg', 'maxLength', 'longVarFunc', \\n\\t\\t\\t\\t\\t\\t\\t 'stringAssignments', 'stringModFuncsCount', 'eventFuncsCount', \\n\\t\\t\\t\\t\\t\\t\\t 'domModFuncsCounter', 'suspStrings', 'whiteSpaceRatio', \\n\\t\\t\\t\\t\\t\\t\\t 'hexaStrings', 'maxNonPrintableCharactersinString', 'lineAvg', \\n\\t\\t\\t\\t\\t\\t\\t 'iframeCount', 'malTagCount', 'jsLength'])\",\n \"def run_example_udpv6():\\n config = {\\n 'server_address': '10.8.254.65',\\n 'wan_port': Device(interface='nontrunk-1',\\n mac='00:ff:1f:00:00:01',\\n iptype=6, slaac=True),\\n 'cpe_port': Device(interface='trunk-1-19',\\n iptype=6, dhcp=True,\\n nat=True),\\n 'traffic_profile': UdpTrafficProfile(interframegap=1000000, # ns\\n frame_size=508 # bytes\\n ),\\n 'number_of_downstream_flows': 2,\\n 'number_of_upstream_flows': 1,\\n 'traffic_duration': datetime.timedelta(seconds=3)\\n }\\n\\n with Example(**config) as example:\\n results = example.run()\\n return results\",\n \"def test_description(self):\\n self.assertEqual(\\n \\\"Description.\\\",\\n DescribedModel.parse_obj({\\\"name\\\": \\\"Name\\\", \\\"description\\\": \\\"Description\\\"}).description,\\n )\",\n \"def parse_description(self, in_str):\\n in_str = self.parse_tags(in_str)\\n self.description = self.parse_metadata(in_str)\",\n \"def get_description(self):\\n\\t\\treturn call_sdk_function('PrlVmCfg_GetDescription', self.handle)\",\n \"def set_description(self, descr):\\n self._current_test_descr = descr\",\n \"def workbench_scenarios():\\n return [\\n (\\\"Oppia Embedding\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <oppia oppiaid=\\\"0\\\" src=\\\"https://www.oppia.org\\\" width=\\\"700\\\" />\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def Description(self, default=None):\\n return self.data.get('description', default)\",\n \"def Description(self, default=None):\\n return self.data.get('description', default)\",\n \"def read_uef_details(chunks):\\n\\n\\tpos, chunk = find_next_chunk(chunks, 0, [0x0])\\n\\n\\tif pos == None:\\n\\n\\t\\toriginator = 'Unknown'\\n\\n\\telif chunk[1] == '':\\n\\n\\t\\toriginator = 'Unknown'\\n\\telse:\\n\\t\\toriginator = chunk[1]\\n\\n\\tpos, chunk = find_next_chunk(chunks, 0, [0x5])\\n\\n\\tif pos == None:\\n\\n\\t\\tmachine, keyboard = 'Unknown', 'Unknown'\\n\\n\\telse:\\n\\n\\t\\tmachines = ('BBC Model A', 'Electron', 'BBC Model B', 'BBC Master')\\n\\t\\tkeyboards = ('Any layout', 'Physical layout', 'Remapped')\\n\\n\\t\\tmachine = ord(chunk[1][0]) & 0x0f\\n\\t\\tkeyboard = (ord(chunk[1][0]) & 0xf0) >> 4\\n\\n\\t\\tif machine < len(machines):\\n\\t\\t\\tmachine = machines[machine]\\n\\t\\telse:\\n\\t\\t\\tmachine = 'Unknown'\\n\\n\\t\\tif keyboard < len(keyboards):\\n\\t\\t\\tkeyboard = keyboards[keyboard]\\n\\t\\telse:\\n\\t\\t\\tkeyboard = 'Unknown'\\n\\n\\tpos, chunk = find_next_chunk(chunks, 0, [0xff00])\\n\\n\\tif pos == None:\\n\\n\\t\\temulator = 'Unknown'\\n\\n\\telif chunk[1] == '':\\n\\n\\t\\temulator = 'Unknown'\\n\\telse:\\n\\t\\temulator = chunk[1]\\n\\n\\n\\t# Remove trailing null bytes\\n\\twhile originator[-1] == '\\\\000':\\n\\n\\t\\toriginator = originator[:-1]\\n\\n\\twhile emulator[-1] == '\\\\000':\\n\\n\\t\\temulator = emulator[:-1]\\n\\n\\tfeatures = ''\\n\\tif find_next_chunk(chunks, 0, [0x1])[0] != None:\\n\\t\\tfeatures = features + '\\\\n' + 'Instructions'\\n\\tif find_next_chunk(chunks, 0, [0x2])[0] != None:\\n\\t\\tfeatures = features + '\\\\n' + 'Credits'\\n\\tif find_next_chunk(chunks, 0, [0x3])[0] != None:\\n\\t\\tfeatures = features + '\\\\n' + 'Inlay'\\n\\n\\treturn originator, machine, keyboard, emulator, features\",\n \"def test_entry_6(self):\\n row = self.dataset.iloc[6]\\n self.assertEqual('./cnn/stories/d312173b8c95cc6c206a32cc0acd8a92c1e272d5.story',\\n row.story_id)\\n self.assertEqual(\\\"Who is hiring ?\\\", row.question)\\n self.assertEqual('334:345|292:297,372:379|4045:4079|301:324', row.answer_char_ranges)\\n self.assertEqual(0, row.is_answer_absent)\\n self.assertEqual('0.0', row.is_question_bad)\\n self.assertEqual(\\n '25,43,71,94,109,120,131,158,168,188,208,222,260,288,327,332,348,369,378,409,417,428,478,504,541,606,623,636,662,682,689,695,712,732,752,778,808,818,852,883,898,927,956,975,999,1020,1051,1069,1080,1092',\\n row.sentence_starts)\\n self.assertEqual('56:59', row.answer_token_ranges)\\n self.assertEqual(\\\"CNN affiliates report on where job seekers are\\\", row.story_text[:46])\\n self.assertEqual([\\\"the federal government\\\"], _get_answers(row))\",\n \"def new_experiment_from_h5file(self, name, file_path, description=''):\\n new_exp = {\\n ExperimentAttr.NAME: name,\\n ExperimentAttr.SAVED_MODEL_LOC: file_path,\\n ExperimentAttr.DESC: description\\n }\\n\\n return self.dbclient.insert(Tables.EXPERIMENTS, new_exp).inserted_id\",\n \"def description(self):\\n return self._data.get('description')\",\n \"def loadInception(self):\\r\\n\\r\\n self.reqsize = self.confs[\\\"Classifier\\\"][\\\"ImageSize\\\"]\\r\\n\\r\\n with open(self.confs[\\\"Classifier\\\"][\\\"NetworkPath\\\"] + self.confs[\\\"Classifier\\\"][\\\"InceptionGraph\\\"], mode='rb') as f:\\r\\n ncsGraphFile = f.read()\\r\\n\\r\\n self.allocateGraph(ncsGraphFile)\\r\\n\\r\\n with open(self.confs[\\\"Classifier\\\"][\\\"DatasetDir\\\"] + \\\"/\\\" + self.confs[\\\"Classifier\\\"][\\\"Classes\\\"], 'r') as f:\\r\\n for line in f:\\r\\n cat = line.split('\\\\n')[0]\\r\\n if cat != 'classes':\\r\\n self.classes.append(cat)\\r\\n f.close()\\r\\n\\r\\n self.Helpers.logger.info(\\\"Inception loaded successfully.\\\")\",\n \"def load_run_summary(self):\\n vrun_attrs = {}\\n print 'Loading summary of {:} runs for {:} from SQL database'.format( \\\\\\n len(self.runs),self.exp)\\n print 'Estimate loading time ~{:} sec'.format(len(self.runs)/4)\\n for run in range(1,self.runs[-1]['num']+1):\\n run_attr = experiment_info.run_attributes(self.instrument,self.exp,run)\\n for a in run_attr:\\n if a['name'] not in vrun_attrs:\\n vrun_attrs[a['name']] = {'class': a['class'], 'desc': a['descr'], \\n 'type': a['type'], 'val': \\n [None for i in range(1,run)]} \\n vrun_attrs[a['name']]['val'].append(a['val'])\\n self.run_summary = vrun_attrs\",\n \"def description(self, new_description):\\n self.set_description(new_description, self._xml)\\n self._description = self._read_description(self._xml)\",\n \"def _load_experiment(\\n experiment_name: str, decoder: Decoder, reduced_state: bool = False\\n) -> Experiment:\\n # Convert SQA to user-facing class outside of session scope to avoid timeouts\\n return decoder.experiment_from_sqa(\\n experiment_sqa=_get_experiment_sqa_reduced_state(\\n experiment_name=experiment_name, decoder=decoder\\n )\\n if reduced_state\\n else _get_experiment_sqa(experiment_name=experiment_name, decoder=decoder),\\n reduced_state=reduced_state,\\n )\",\n \"def load_cci9():\\n cci9 = pd.read_csv(pkg_resources.resource_filename(__name__,'cci2015.csv'),skiprows=1)\\n cci9.columns = [i.strip('\\\\'') for i in cci9.columns]\\n \\n for col in cci9.columns:\\n cci9.loc[:,col] = cci9[col].str.strip('\\\\'')\\n cci9 = cci9.replace(r'^\\\\s*$', np.nan, regex=True)\\n cci9.columns=[i.replace('CATEGORY DESCRIPTION','CHRONIC') for i in cci9.columns]\\n\\n dict_bodysystem=[\\n ('1' ,'Infectious and parasitic disease'),\\n ('2' ,'Neoplasms'),\\n ('3' ,'Endocrine, nutritional, and metabolic diseases and immunity disorders'),\\n ('4' ,'Diseases of blood and blood-forming organs'),\\n ('5' ,'Mental disorders'),\\n ('6' ,'Diseases of the nervous system and sense organs'),\\n ('7' ,'Diseases of the circulatory system'),\\n ('8' ,'Diseases of the respiratory system'),\\n ('9' ,'Diseases of the digestive system'),\\n ('10','Diseases of the genitourinary system'),\\n ('11','Complications of pregnancy, childbirth, and the puerperium'),\\n ('12','Diseases of the skin and subcutaneous tissue'),\\n ('13','Diseases of the musculoskeletal system'),\\n ('14','Congenital anomalies'),\\n ('15','Certain conditions originating in the perinatal period'),\\n ('16','Symptoms, signs, and ill-defined conditions'),\\n ('17','Injury and poisoning'),\\n ('18','Factors influencing health status and contact with health service'),\\n ]\\n \\n cci9 = cci9.merge(pd.DataFrame(dict_bodysystem,columns=['BODY SYSTEM','BODY SYSTEM DESCRIPTION']),how='left',on='BODY SYSTEM')\\n \\n cci9.loc[:,'ICD-9-CM CODE'] = cci9['ICD-9-CM CODE'].str.replace(' ','')\\n \\n return cci9\",\n \"def experiment_init(self):\\n pass\",\n \"def test_update_flow_classifier_description(self):\\n resource = 'flow_classifier'\\n cmd = fc.FlowClassifierUpdate(test_cli20.MyApp(sys.stdout), None)\\n myid = 'myid'\\n args = [myid, '--description', 'flow_classifier1', '--description',\\n 'flow_classifier2']\\n updatefields = {'description': 'flow_classifier2'}\\n self._test_update_resource(resource, cmd, myid, args, updatefields)\",\n \"def load_data(self):\",\n \"def load_info():\\n data = np.loadtxt(\\\"u_sol_meta.txt\\\", dtype=int)\\n return data\",\n \"def description(path='election-manifest.json'):\\n from electionguard.manifest import Manifest\\n with open(path, 'r') as manifest:\\n string_representation = manifest.read()\\n return Manifest.from_json(string_representation)\",\n \"def load(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.58439624","0.56758475","0.5097717","0.5092497","0.50313264","0.5024391","0.5001988","0.4999472","0.497601","0.49601525","0.4910506","0.48574418","0.48146957","0.47966567","0.47924876","0.47363088","0.47330913","0.4709552","0.47017694","0.4664248","0.46575555","0.46489972","0.4641186","0.46410248","0.46276212","0.46232912","0.46230397","0.46152207","0.46111974","0.46091282","0.45967644","0.4587036","0.45739588","0.45733","0.45672375","0.45522615","0.45468715","0.45391193","0.4536989","0.45329273","0.45320144","0.45277247","0.45275685","0.45246765","0.45220876","0.45211437","0.4515025","0.45147774","0.45085663","0.4508082","0.4506297","0.44993183","0.44984257","0.44838628","0.44832656","0.44817388","0.44745007","0.44722715","0.44709456","0.4467234","0.44671288","0.44632724","0.44571748","0.44546467","0.4441074","0.44396007","0.44396007","0.4437033","0.44357315","0.44354847","0.44333005","0.44314024","0.44261953","0.44249746","0.4418556","0.44156355","0.44017294","0.4401208","0.4398759","0.4394142","0.43903753","0.438952","0.43886796","0.43881792","0.43872708","0.43872708","0.43861234","0.43843335","0.43784818","0.43769827","0.43753985","0.43752226","0.43727404","0.43707833","0.43636373","0.43608382","0.43598005","0.43585056","0.4356381","0.43535846","0.43516862"],"string":"[\n \"0.58439624\",\n \"0.56758475\",\n \"0.5097717\",\n \"0.5092497\",\n \"0.50313264\",\n \"0.5024391\",\n \"0.5001988\",\n \"0.4999472\",\n \"0.497601\",\n \"0.49601525\",\n \"0.4910506\",\n \"0.48574418\",\n \"0.48146957\",\n \"0.47966567\",\n \"0.47924876\",\n \"0.47363088\",\n \"0.47330913\",\n \"0.4709552\",\n \"0.47017694\",\n \"0.4664248\",\n \"0.46575555\",\n \"0.46489972\",\n \"0.4641186\",\n \"0.46410248\",\n \"0.46276212\",\n \"0.46232912\",\n \"0.46230397\",\n \"0.46152207\",\n \"0.46111974\",\n \"0.46091282\",\n \"0.45967644\",\n \"0.4587036\",\n \"0.45739588\",\n \"0.45733\",\n \"0.45672375\",\n \"0.45522615\",\n \"0.45468715\",\n \"0.45391193\",\n \"0.4536989\",\n \"0.45329273\",\n \"0.45320144\",\n \"0.45277247\",\n \"0.45275685\",\n \"0.45246765\",\n \"0.45220876\",\n \"0.45211437\",\n \"0.4515025\",\n \"0.45147774\",\n \"0.45085663\",\n \"0.4508082\",\n \"0.4506297\",\n \"0.44993183\",\n \"0.44984257\",\n \"0.44838628\",\n \"0.44832656\",\n \"0.44817388\",\n \"0.44745007\",\n \"0.44722715\",\n \"0.44709456\",\n \"0.4467234\",\n \"0.44671288\",\n \"0.44632724\",\n \"0.44571748\",\n \"0.44546467\",\n \"0.4441074\",\n \"0.44396007\",\n \"0.44396007\",\n \"0.4437033\",\n \"0.44357315\",\n \"0.44354847\",\n \"0.44333005\",\n \"0.44314024\",\n \"0.44261953\",\n \"0.44249746\",\n \"0.4418556\",\n \"0.44156355\",\n \"0.44017294\",\n \"0.4401208\",\n \"0.4398759\",\n \"0.4394142\",\n \"0.43903753\",\n \"0.438952\",\n \"0.43886796\",\n \"0.43881792\",\n \"0.43872708\",\n \"0.43872708\",\n \"0.43861234\",\n \"0.43843335\",\n \"0.43784818\",\n \"0.43769827\",\n \"0.43753985\",\n \"0.43752226\",\n \"0.43727404\",\n \"0.43707833\",\n \"0.43636373\",\n \"0.43608382\",\n \"0.43598005\",\n \"0.43585056\",\n \"0.4356381\",\n \"0.43535846\",\n \"0.43516862\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":25691,"cells":{"query":{"kind":"string","value":"make sure the html output works"},"document":{"kind":"string","value":"def testHTML(self):\n\n html = self.E.html()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_html_output(self):\n pass","def test_error_html_using_patch(self):\n pass","def test_prep_fields_called_html_output(self):\n pass","def get_html(self):\r\n pass","def rawHTMLrendered(self):","def __html__(self):\n return self.html","def test_error_html_using_put(self):\n pass","def test_error_html_using_get(self):\n pass","def test_error_html_using_post(self):\n pass","def test_home_page_returns_correct_html(self):\n request = HttpRequest()\n response = home_page(request)\n self.assertIn(\n b'<h1>42 Coffee Cups Test Assignment</h1>',\n response.content)","def test_error_html_using_head(self):\n pass","def get_html(self):\r\n return u'This is supposed to be test html.'","def assert_studio_view_valid_html(block, html):\r\n pass","def test_html_structure(self):\n self.assertContains(self.response, '<form', 1)\n self.assertContains(self.response, '<input', 3)\n #3 pois são 2 filefield mais o csrf\n self.assertContains(self.response, 'type=\"file\"', 1)\n self.assertContains(self.response, 'type=\"submit\"', 1)","def test_error_html_using_options(self):\n pass","def convert_html():\n return","def html(input):\n output=atpic.cleaner_alex.clean(input)\n return output","def test_home_page_returns_correct_html(self):\n\n request = HttpRequest()\n response = home_view(request)\n html = response.content.decode('utf8')\n self.assertTrue(html.startswith('<!doctype html>'))\n self.assertIn('<title>home</title>', html)\n self.assertTrue(html.endswith('</html>'))","def test_public_unit_page_html(self):\r\n html = self.get_page_html(self.vertical)\r\n self.validate_html_for_add_buttons(html)","def assert_student_view_valid_html(block, html):\r\n pass","def test_gethtml_multiple(self):\r\n mock_module = VerticalWithModulesFactory.create()\r\n out_html = mock_module.render('student_view').content\r\n self.assertTrue('Test numerical problem.' in out_html)\r\n self.assertTrue('Another test numerical problem.' in out_html)","def test_get_root_html(self):\n pass","def has_html_gui(self):\r\n return True","def test_lessthan(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text_lessthan_noencd), self.text_lessthan_encode)","def test_get_root_html2(self):\n pass","def test_gettesttools_html(self):\n pass","def plain(self):\n return not self.html","def assert_studio_view_invalid_html(block, html):\r\n assert False, \"studio_view should produce valid html\"","def test_html_repr():\n repr_html = grid._repr_html_()\n assert repr_html is not None","def initFormat(self):\n self.html = True","def initFormat(self):\n self.html = True","def test_get_html(self):\r\n _html = self.peer_grading.get_html()","def assert_student_view_invalid_html(block, html):\r\n assert False, \"student_view should produce valid html\"","def print_html(html):\n display(HTML(html))","def test_get_root_html1(self):\n pass","def printContent(self):\n if self.content != \"Failed to find HTML template.\":\n print self.content","def test_render_to_html_valid_variables(self):\n marker = \"TEMPLATESTRINGINVALID\"\n settings.TEMPLATE_STRING_IF_INVALID = marker\n\n issue = Issue.objects.create(newsletter=self.newsletter,\n pub_date=datetime.date.today())\n html = issue.render_to_html(\n html_template_name='bulletin/api/test/html_template.html')\n\n self.assertEqual(html.find(marker), -1)","def test_render_student_view(self):\r\n html = self.module_system.render(self.vertical, 'student_view', {}).content\r\n self.assertIn(self.test_html_1, html)\r\n self.assertIn(self.test_html_2, html)","def test_combined(self):\r\n test_input = u\"{}\\n{}\\n{}\\n\\n{}{}\\n{}\".format(self.link_text,\r\n self.text,\r\n self.script_dirty,\r\n self.embed_dirty,\r\n self.text_lessthan_noencd,\r\n self.img_dirty)\r\n test_output = u\"{}<br/>{}<br/>{}<br/><br/>{}{}<br/>{}\".format(self.link_atag,\r\n self.text,\r\n self.script_clean,\r\n self.embed_clean,\r\n self.text_lessthan_encode,\r\n self.img_clean)\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(test_input), test_output)","def test_text(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text), self.text)","def test_export_html(self):\r\n resp = self.client.get_html(self.url)\r\n self.assertEquals(resp.status_code, 200)\r\n self.assertContains(resp, \"Export My Course Content\")","def test_script(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.script_dirty), self.script_clean)","def get_html_string(self, **kwargs):\n ...","def test_get_html(self):\r\n context = self.mod.get_html()\r\n for key in ['display_name', 'instructions_html', 'sourceUrl', 'typeSource', 'poster', 'annotation_storage']:\r\n self.assertIn(key, context)","def output_to_html(string_data):\n raise NotImplementedError(\"This function is not yet Implemented!\")","def publish_html(self, readyhtml):\n with open(self.outfile,'w') as f_out:\n f_out.writelines(readyhtml)","def template(self):\n output=file(self.src, 'w').write\n output(\"\"\"%s\n<html>\n<head>\n<title>CHANGE ME</title>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=iso-8859-15\">\n<link rel=\"STYLESHEET\" href=\"%s\" type=\"text/css\">\n</head>\n<body>\n\n<!--it-->\n <p>\n Pagina non disponibile in questa lingua!\n <FORM><INPUT TYPE=\"button\" VALUE=\"Indietro\" onClick=\"history.go(-1);return true;\"> </FORM>\n </p>\n<!--/it-->\n\n<!--en-->\n <p>\n Page not available in this language!\n <FORM><INPUT TYPE=\"button\" VALUE=\"Back\" onClick=\"history.go(-1);return true;\"> </FORM>\n </p>\n<!--/en-->\n\n</body>\n</html>\n\"\"\" % (self.doctype, self.css))","def test_library_page_preview_html(self):\n # Add some content to library.\n self._add_simple_content_block()\n self.validate_preview_html(self.library, self.container_view, can_reorder=False, can_move=False)","def is_html(self):\r\n return self.__content_type == html_ctype","def test_content_is_correct(self):\n why_page = self.client.get(\"/why/\")\n self.assertTemplateUsed(why_page, \"home/why.html\")\n why_page_template_output = render_to_response(\"home/why.html\", {\"active\": \"why\"}).content\n self.assertEqual(why_page.content, why_page_template_output)","def mk_htmls(self):\n\n domain_link_list = self.scrape_domain_int_links()\n html_fail_rate = float(self.failed_retrieving_html_counter / len(domain_link_list))\n print \"mk_htmls SUCCES RATE %r\" % html_fail_rate\n if html_fail_rate < (float(0.1)):\n # driving links, to collect htmls from web and create htmls with removed img elements\n for ind in range(len(domain_link_list)):\n page_file_name = \"page_\" + str(ind + 1) + \".html\" # gen file names for html file of page on site\n active_page_link = domain_link_list[ind]\n if \";;;\" in active_page_link: # separator problems hedging\n self.links_contain_seprator.append([active_page_link, page_file_name])\n print \"LINK CONTAINS SEPARATOR, CAN NOT ADD TO PAGE LIST, WILL RUIN DATASYSTEM, WILL BE ADDED TO SEPARATE FILE\"\n else:\n BS_object = self.retrieve_html(active_page_link, self.domain_folder_name, self.html_folder_name, page_file_name)\n self.page_list.append([active_page_link, page_file_name])\n self.bs_object_dict[active_page_link] = BS_object\n # if no \";;;\" separator found in link, then write as usual\n if len(self.links_contain_seprator) > 0:\n c_m.l_of_l_write(self.links_contain_seprator, self.main_path, self.domain_folder_name, self.link_contains_separator)\n else:\n c_m.l_of_l_write(self.page_list, self.main_path, self.domain_folder_name, self.page_list_f_name)\n return self.bs_object_dict\n else:\n return False","def test_get_html(self):\r\n context = self.mod.get_html()\r\n for key in ['display_name', 'tag', 'source', 'instructions_html', 'content_html', 'annotation_storage', 'token']:\r\n self.assertIn(key, context)","def test_homepage_html(self):\n\n request = HttpRequest()\n engine = import_module(settings.SESSION_ENGINE)\n request.session = engine.SessionStore()\n response = product_all(request)\n html = response.content.decode(\"utf8\")\n self.assertInHTML(\"<title>Book Store</title>\", html)\n self.assertEqual(response.status_code, 200)","def test_get_services_html(self):\n pass","def test_display_html_tag_prompt(self):\r\n self.context['tag_prompt'] = \"<p>Unescaped <b>HTML</b></p>\"\r\n xml = self.render_to_xml(self.context)\r\n\r\n # Because the HTML is unescaped, we should be able to\r\n # descend to the <b> tag\r\n xpath = \"//div[@class='block']/p/b\"\r\n self.assert_has_text(xml, xpath, 'HTML')","def test_get_problem_html_error(self):\r\n module = CapaFactory.create()\r\n\r\n # Save the original problem so we can compare it later\r\n original_problem = module.lcp\r\n\r\n # Simulate throwing an exception when the capa problem\r\n # is asked to render itself as HTML\r\n module.lcp.get_html = Mock(side_effect=Exception(\"Test\"))\r\n\r\n # Stub out the get_test_system rendering function\r\n module.system.render_template = Mock(return_value=\"<div>Test Template HTML</div>\")\r\n\r\n # Turn off DEBUG\r\n module.system.DEBUG = False\r\n\r\n # Try to render the module with DEBUG turned off\r\n html = module.get_problem_html()\r\n\r\n self.assertTrue(html is not None)\r\n\r\n # Check the rendering context\r\n render_args, _ = module.system.render_template.call_args\r\n context = render_args[1]\r\n self.assertTrue(\"error\" in context['problem']['html'])\r\n\r\n # Expect that the module has created a new dummy problem with the error\r\n self.assertNotEqual(original_problem, module.lcp)","def test_homepage_render(self):\n\n result = self.client.get(\"/\")\n self.assertIn(\"<h1 class=\\\"title\\\">Bark Park!</h1>\", result.data)","def test_html(self):\n tags = (\n ('<form', 1),\n # Csrf, first_name, last_name, email, superuser, username and password\n ('<input', 7),\n ('type=\"text\"', 3),\n ('type=\"password\"', 1),\n ('type=\"checkbox\"', 1),\n ('type=\"email\"', 1),\n ('type=\"submit\"', 1),\n )\n for text, count in tags:\n with self.subTest():\n self.assertContains(self.response, text, count)","def test_embed(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.embed_dirty), self.embed_clean)","def display_html_report():\n display(HTML('report_page.html'))","def test_html(self):\n tags = (('<input', 3),\n ('<span', 1),\n ('<button', 1))\n\n for text, count in tags:\n with self.subTest():\n self.assertContains(self.resp, text, count)","def HTMLResponse():\n\n\thtml = \t\"<html><head><title>MA MAURO ESISTE?</title><style type='text/css'>body{width:30%}</style></head><body><pre>\"\n\thtml += \" _ __<br>\"\n\thtml += \" (_) / /<br>\"\n\thtml += \" ______ __ ____ ____ / /____<br>\"\n\thtml += \" / ___/ / _ \\\\/ _ \\\\/ / _ \\\\<br>\"\n\thtml += \" / / / / /_) / /_) / / ____/<br>\"\n\thtml += \"/__/ /__/ .___/ .___/__/ \\\\_____/<br>\"\n\thtml += \" / / / /<br>\"\n\thtml += \" /__/ /__/<br>\"\n\thtml += \"<b>PYTHON > ALL VERSION</b><br><br>\"\n\thtml += \"<marquee style='white-space:pre;'><br>\"\n\thtml += \" .. o .<br>\"\n\thtml += \" o.o o . o<br>\"\n\thtml += \" oo...<br>\"\n\thtml += \" __[]__<br>\"\n\thtml += \" phwr--> _\\\\:D/_/o_o_o_|__ <span style=\\\"font-family: 'Comic Sans MS'; font-size: 8pt;\\\">u wot m8</span><br>\"\n\thtml += \" \\\\\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"/<br>\"\n\thtml += \" \\\\ . .. .. . /<br>\"\n\thtml += \"^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>\"\n\thtml += \"</marquee><br><strike>reverse engineering a protocol impossible to reverse engineer since always</strike><br>we are actually reverse engineering bancho successfully. for the third time.</pre></body></html>\"\n\treturn html","def test_error_html_using_delete(self):\n pass","def test_get_html(self):\r\n context = self.mod.get_html()\r\n for key in ['display_name', 'instructions_html', 'annotation_storage', 'token', 'tag', 'openseadragonjson']:\r\n self.assertIn(key, context)","def test_html(self):\n \n tags = (('<form',1),\n ('<input',6),\n ('type=\"text\"',3),\n ('type=\"email\"',1),\n ('type=\"submit\"',1))\n \n for text, count in tags:\n with self.subTest():\n self.assertContains(self.resp, text, count)","def handle_problem_html_error(self, err):\r\n log.exception(err.message)\r\n\r\n # TODO (vshnayder): another switch on DEBUG.\r\n if self.runtime.DEBUG:\r\n msg = (\r\n u'[courseware.capa.capa_module] <font size=\"+1\" color=\"red\">'\r\n u'Failed to generate HTML for problem {url}</font>'.format(\r\n url=cgi.escape(self.location.to_deprecated_string()))\r\n )\r\n msg += u'<p>Error:</p><p><pre>{msg}</pre></p>'.format(msg=cgi.escape(err.message))\r\n msg += u'<p><pre>{tb}</pre></p>'.format(tb=cgi.escape(traceback.format_exc()))\r\n html = msg\r\n\r\n else:\r\n # We're in non-debug mode, and possibly even in production. We want\r\n # to avoid bricking of problem as much as possible\r\n\r\n # Presumably, student submission has corrupted LoncapaProblem HTML.\r\n # First, pull down all student answers\r\n student_answers = self.lcp.student_answers\r\n answer_ids = student_answers.keys()\r\n\r\n # Some inputtypes, such as dynamath, have additional \"hidden\" state that\r\n # is not exposed to the student. Keep those hidden\r\n # TODO: Use regex, e.g. 'dynamath' is suffix at end of answer_id\r\n hidden_state_keywords = ['dynamath']\r\n for answer_id in answer_ids:\r\n for hidden_state_keyword in hidden_state_keywords:\r\n if answer_id.find(hidden_state_keyword) >= 0:\r\n student_answers.pop(answer_id)\r\n\r\n # Next, generate a fresh LoncapaProblem\r\n self.lcp = self.new_lcp(None)\r\n self.set_state_from_lcp()\r\n\r\n # Prepend a scary warning to the student\r\n _ = self.runtime.service(self, \"i18n\").ugettext\r\n warning_msg = _(\"Warning: The problem has been reset to its initial state!\")\r\n warning = '<div class=\"capa_reset\"> <h2> ' + warning_msg + '</h2>'\r\n\r\n # Translators: Following this message, there will be a bulleted list of items.\r\n warning_msg = _(\"The problem's state was corrupted by an invalid submission. The submission consisted of:\")\r\n warning += warning_msg + '<ul>'\r\n\r\n for student_answer in student_answers.values():\r\n if student_answer != '':\r\n warning += '<li>' + cgi.escape(student_answer) + '</li>'\r\n\r\n warning_msg = _('If this error persists, please contact the course staff.')\r\n warning += '</ul>' + warning_msg + '</div>'\r\n\r\n html = warning\r\n try:\r\n html += self.lcp.get_html()\r\n except Exception: # pylint: disable=broad-except\r\n # Couldn't do it. Give up.\r\n log.exception(\"Unable to generate html from LoncapaProblem\")\r\n raise\r\n\r\n return html","def index_html(self,REQUEST): \n return self.posting_html(self,REQUEST)","def is_html(self):\n return self.__content_type == html_ctype","def get_html(self):\r\n raise NotImplementedError(\r\n \"get_html() must be provided by specific modules - not present in {0}\"\r\n .format(self.__class__))","def test_gethtml(self):\r\n mock_module = CHModuleFactory.create()\r\n\r\n def fake_get_display_items():\r\n \"\"\"\r\n A mock of get_display_items\r\n \"\"\"\r\n return [FakeChild()]\r\n mock_module.get_display_items = fake_get_display_items\r\n out_html = mock_module.render('student_view').content\r\n self.assertTrue('This is supposed to be test html.' in out_html)\r\n self.assertTrue('i4x://this/is/a/fake/id' in out_html)","def unrendered(self) -> str:","def test_get_root_html3(self):\n pass","def outputHtml(s):\n htmlFile.write(s + \"\\n\")","def html(self):\n return self.report_format in ['pdf', 'html']","def test__markHTML_simpleHTML1(self):\n self._degrotesque._restoreDefaultElementsToSkip()\n assert(self._degrotesque._markHTML(\"Hallo <b>Mama!</b>\")==\"000000111000001111\")","def test_render_html_no_layout(self):\n assets = Asset.objects.select_subclasses()\n # Create a section without specifying layout \n section = create_section(title=\"Test Section1\", story=self.story)\n # Associate assets with the section without specifying a container\n SectionAsset.objects.create(section=section, asset=assets[0])\n SectionAsset.objects.create(section=section, asset=assets[1])\n html = section.render_html()\n self.assertIn(assets[0].title, html)\n self.assertIn(assets[1].title, html)","def output_html(self, path):\n if path is None:\n return\n import os\n fout = codecs.open(os.path.abspath(path), 'w', encoding='utf-8')\n fout.write('<html><body><table>')\n for data in self.datas:\n fout.write('<tr><td>%s</td><td>%s</td><td>%s</td></tr>' % (data['url'], data['title'], data['summary']))\n self.datas.remove(data)\n fout.write('</table></body></html>')\n fout.close()","def test_blank_problem(self):\r\n xml_str = \"<problem> </problem>\"\r\n\r\n # Create the problem\r\n problem = new_loncapa_problem(xml_str)\r\n\r\n # Render the HTML\r\n rendered_html = etree.XML(problem.get_html())\r\n # expect that we made it here without blowing up\r","def test_insert_content(self):\n self.request.path = \"/non_ascii_request/\"\n response = self.panel.process_request(self.request)\n # ensure the panel does not have content yet.\n self.assertNotIn(\"nôt åscíì\", self.panel.content)\n self.panel.generate_stats(self.request, response)\n # ensure the panel renders correctly.\n content = self.panel.content\n self.assertIn(\"nôt åscíì\", content)\n self.assertValidHTML(content)","def test_sample(self):\n response = self.tester.get('/sample-household/',\n content_type='html/text')\n self.assertEqual(response.status_code, 200)","def test_clean_storytranslation_html(self):\n unclean_summary = (\"<p>This is the first paragraph</p>\"\n \"<script src=\\\"/static/js/fake.js\\\"></script>\")\n unclean_call = (\"<blockquote>Quote in call</blockquote>\"\n \"<iframe src=\\\"/fake/\\\"></iframe>\")\n story = create_story(title=\"Test Story\", summary=unclean_summary,\n call_to_action=unclean_call, status='draft')\n story.save()\n story = Story.objects.get(story_id=story.story_id)\n # Test that the invalid tags aren't in the saved field values.\n # Right now, we don't care whether the tags were escaped or removed\n self.assertNotIn(\"<script\", story.summary)\n self.assertNotIn(\"<iframe\", story.call_to_action)","def test_img(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.img_dirty), self.img_clean)","def test_create_form_with_malformed_html(self):\n with pytest.raises(ValidationError):\n SurveyForm.create('badform', '<input name=\"oops\" /><<<>')","def test_content_is_correct(self):\n home_page = self.client.get(\"/\")\n self.assertTemplateUsed(home_page, \"home/home.html\")\n home_page_template_output = render_to_response(\"home/home.html\", {\"active\": \"home\"}).content\n self.assertEqual(home_page.content, home_page_template_output)","def __html__(self, file_path:str):\n raise NotImplementedError","def view_html_page():\n\n return render_template(\"moby.html\")","def writeHTMLbody(appurl, numberOfCompletedFiles, stoppedState, componentList, dayStart, dayEnd):\n html = u'''\\\n<html>\n <head></head>\n <body>\n <p>Kære Operatør</p>\n <p>\n Her en rapport over hvordan det er gået med opsamling af YouSee\n TV i det seneste døgn. Informationerne i denne mail er alle trukket fra\n <a href=\"%(url)s\">Ingest Monitor websiden</a> som du også selv kan klikke rundt på.\n </p><p>\n Døgnet startede i går klokken %(start)s og varede indtil i dag klokken %(end)s.\n </p>\n <p>\n''' % {'url': appurl, 'start': dayStart, 'end': dayEnd}\n\n html += '<hr>'\n html += u'<p>I det seneste døgn blev der med succes blevet behandlet ' + str(numberOfCompletedFiles) + ' filer.</p>'\n\n if len(componentList) > 0:\n # add a list of files still in progress BUT previously were in a FAILED state\n # grouped by the component\n html += u'<h3>Filer som tidligere fejlede men som stadig er under behandling eller er blevet genstartet.</h3>'\n html += u'<p>'\n for component in componentList:\n html += u'<h4>Følgende filer fejlede i ' + component[0] + ' komponenten:</h4>'\n\t newList = set([e['entity']['name'] for e in component[1]])\n for e in newList:\n html += u'<a href=\"'\\\n + getDetailUrl(appurl, e)\\\n + '\">'\\\n + e\\\n + '</a><br>\\n'\n html += u'</p>'\n else:\n html += u'<p>Ingen filer under behandling har en fejlstatus.</p>'\n\n html += '<hr>'\n if len(stoppedState) > 0:\n # add a list of failed files to the report.\n html += u'<h3>Filer der er markeret som værende stoppet og som kun bliver genstartet ved manuel indgriben:</h3>'\n html += u'<p>'\n for e in stoppedState:\n html += u'<a href=\"' + getDetailUrl(appurl, e['entity']['name']) + '\">'\\\n + e['entity']['name']\\\n + u'</a><br>\\n'\n html += u'</p>'\n else:\n html += u'<p>Ingen filer er markeret som stoppet.</p>'\n\n # end the html part of the report\n html += u'''\\\n </ul>\n </p>\n </body>\n</html>\n'''\n return html","def test_html_documentation(self):\n app = Sphinx(\n self.source_dir,\n self.config_dir,\n self.output_dir,\n self.doctree_dir,\n buildername='html',\n warningiserror=True,\n )\n app.build(force_all=self.all_files)","def get_html( self, prefix=\"\" ):\n raise TypeError( \"Abstract Method\" )","def test_dose_check_generation(self):\n response = self.client.get('/dose_check/V117108T/Insertion%201/Pre%20Ins%201/', follow=True)\n self.assertEqual(response.status_code, 200)\n self.assertTemplateUsed(response, 'myapp/dose_check.html')\n # with open(r\"myapp\\\\tests\\\\test_dose_check_page.html\", 'r') as myfile:\n # test_html_data=myfile.read()\n # self.assertEqual(response.content.decode(\"utf-8\"),test_html_data)","def command_show(problem):\r\n print problem.get_html()","def test_killhtml():\r\n test_cases = (\r\n ('Just Text', 'Just Text'),\r\n ('<p>One</p><p>Two</p>', 'One Two'),\r\n ('<p>One</p> \\n <p>Two</p>', 'One Two'),\r\n ('<p>One</p>\\n<p>Two</p>', 'One Two'),\r\n ('Some Text<p>then tag</p>', 'Some Text then tag'),\r\n ('<p>Some Text</p>then no tag.', 'Some Text then no tag.'),\r\n ('Entities & <hr/>', 'Entities & <hr/>'),\r\n ('<p>Unknown tags: <asdf>qwerty</asdf>', 'Unknown tags: qwerty'),\r\n )\r\n for input_text, expected_output in test_cases:\r\n yield is_equal, killhtml(input_text), expected_output","def generate_html(self):\n html_text_1 = \"\"\"\n <div class=\"concept\">\n\n \t\t<div class=\"concept-title\">\n\n \t\t\t\t\"\"\" + self.title\n\n html_text_2 = \"\"\"\n \t\t</div>\n\n \t\t<div class=\"concept-description\">\n\n\t\t <p>\n\t\t\t\n \t\t \t\t\"\"\" + self.description + \"\"\" \n \n </p>\"\"\"\n\n html_text_3 = '''\n\n \t\t</div>\n\n </div>'''\n\n return html_text_1 + html_text_2 + html_text_3","def _render(self) -> None:\n pass","def test__markHTML_simpleHTML3(self):\n self._degrotesque._restoreDefaultElementsToSkip()\n assert(self._degrotesque._markHTML(\"a<b>a</b>\")==\"011101111\")","def _build_html():\n\n # Build twice until getnikola/nikola#1032 is fixed.\n local('nikola build && nikola build')\n\n ## Remove all the source files, we only want the output!\n local('ls | grep -v output | xargs rm -rf')\n with settings(warn_only=True):\n local('mv output/* output/.* .')","def test__markHTML_simpleHTML2(self):\n self._degrotesque._restoreDefaultElementsToSkip()\n assert(self._degrotesque._markHTML(\"a<b></b>\")==\"01111111\")","def test_custom_decorator_displaytex_no_malformed(self):\n self.assertEqual(\n DOM.render(\n DOM.create_element(\n ashley_render_children,\n {\n \"block\": {\n \"key\": \"a215p\",\n \"text\": \"\",\n \"type\": \"atomic\",\n \"data\": {\"type\": \"TEXBLOCK\"},\n }\n },\n )\n ),\n '<span class=\"ashley-latex-display\"></span>',\n )","def render(self):\n pass","def render(self):\n pass"],"string":"[\n \"def test_html_output(self):\\n pass\",\n \"def test_error_html_using_patch(self):\\n pass\",\n \"def test_prep_fields_called_html_output(self):\\n pass\",\n \"def get_html(self):\\r\\n pass\",\n \"def rawHTMLrendered(self):\",\n \"def __html__(self):\\n return self.html\",\n \"def test_error_html_using_put(self):\\n pass\",\n \"def test_error_html_using_get(self):\\n pass\",\n \"def test_error_html_using_post(self):\\n pass\",\n \"def test_home_page_returns_correct_html(self):\\n request = HttpRequest()\\n response = home_page(request)\\n self.assertIn(\\n b'<h1>42 Coffee Cups Test Assignment</h1>',\\n response.content)\",\n \"def test_error_html_using_head(self):\\n pass\",\n \"def get_html(self):\\r\\n return u'This is supposed to be test html.'\",\n \"def assert_studio_view_valid_html(block, html):\\r\\n pass\",\n \"def test_html_structure(self):\\n self.assertContains(self.response, '<form', 1)\\n self.assertContains(self.response, '<input', 3)\\n #3 pois são 2 filefield mais o csrf\\n self.assertContains(self.response, 'type=\\\"file\\\"', 1)\\n self.assertContains(self.response, 'type=\\\"submit\\\"', 1)\",\n \"def test_error_html_using_options(self):\\n pass\",\n \"def convert_html():\\n return\",\n \"def html(input):\\n output=atpic.cleaner_alex.clean(input)\\n return output\",\n \"def test_home_page_returns_correct_html(self):\\n\\n request = HttpRequest()\\n response = home_view(request)\\n html = response.content.decode('utf8')\\n self.assertTrue(html.startswith('<!doctype html>'))\\n self.assertIn('<title>home</title>', html)\\n self.assertTrue(html.endswith('</html>'))\",\n \"def test_public_unit_page_html(self):\\r\\n html = self.get_page_html(self.vertical)\\r\\n self.validate_html_for_add_buttons(html)\",\n \"def assert_student_view_valid_html(block, html):\\r\\n pass\",\n \"def test_gethtml_multiple(self):\\r\\n mock_module = VerticalWithModulesFactory.create()\\r\\n out_html = mock_module.render('student_view').content\\r\\n self.assertTrue('Test numerical problem.' in out_html)\\r\\n self.assertTrue('Another test numerical problem.' in out_html)\",\n \"def test_get_root_html(self):\\n pass\",\n \"def has_html_gui(self):\\r\\n return True\",\n \"def test_lessthan(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text_lessthan_noencd), self.text_lessthan_encode)\",\n \"def test_get_root_html2(self):\\n pass\",\n \"def test_gettesttools_html(self):\\n pass\",\n \"def plain(self):\\n return not self.html\",\n \"def assert_studio_view_invalid_html(block, html):\\r\\n assert False, \\\"studio_view should produce valid html\\\"\",\n \"def test_html_repr():\\n repr_html = grid._repr_html_()\\n assert repr_html is not None\",\n \"def initFormat(self):\\n self.html = True\",\n \"def initFormat(self):\\n self.html = True\",\n \"def test_get_html(self):\\r\\n _html = self.peer_grading.get_html()\",\n \"def assert_student_view_invalid_html(block, html):\\r\\n assert False, \\\"student_view should produce valid html\\\"\",\n \"def print_html(html):\\n display(HTML(html))\",\n \"def test_get_root_html1(self):\\n pass\",\n \"def printContent(self):\\n if self.content != \\\"Failed to find HTML template.\\\":\\n print self.content\",\n \"def test_render_to_html_valid_variables(self):\\n marker = \\\"TEMPLATESTRINGINVALID\\\"\\n settings.TEMPLATE_STRING_IF_INVALID = marker\\n\\n issue = Issue.objects.create(newsletter=self.newsletter,\\n pub_date=datetime.date.today())\\n html = issue.render_to_html(\\n html_template_name='bulletin/api/test/html_template.html')\\n\\n self.assertEqual(html.find(marker), -1)\",\n \"def test_render_student_view(self):\\r\\n html = self.module_system.render(self.vertical, 'student_view', {}).content\\r\\n self.assertIn(self.test_html_1, html)\\r\\n self.assertIn(self.test_html_2, html)\",\n \"def test_combined(self):\\r\\n test_input = u\\\"{}\\\\n{}\\\\n{}\\\\n\\\\n{}{}\\\\n{}\\\".format(self.link_text,\\r\\n self.text,\\r\\n self.script_dirty,\\r\\n self.embed_dirty,\\r\\n self.text_lessthan_noencd,\\r\\n self.img_dirty)\\r\\n test_output = u\\\"{}<br/>{}<br/>{}<br/><br/>{}{}<br/>{}\\\".format(self.link_atag,\\r\\n self.text,\\r\\n self.script_clean,\\r\\n self.embed_clean,\\r\\n self.text_lessthan_encode,\\r\\n self.img_clean)\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(test_input), test_output)\",\n \"def test_text(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text), self.text)\",\n \"def test_export_html(self):\\r\\n resp = self.client.get_html(self.url)\\r\\n self.assertEquals(resp.status_code, 200)\\r\\n self.assertContains(resp, \\\"Export My Course Content\\\")\",\n \"def test_script(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.script_dirty), self.script_clean)\",\n \"def get_html_string(self, **kwargs):\\n ...\",\n \"def test_get_html(self):\\r\\n context = self.mod.get_html()\\r\\n for key in ['display_name', 'instructions_html', 'sourceUrl', 'typeSource', 'poster', 'annotation_storage']:\\r\\n self.assertIn(key, context)\",\n \"def output_to_html(string_data):\\n raise NotImplementedError(\\\"This function is not yet Implemented!\\\")\",\n \"def publish_html(self, readyhtml):\\n with open(self.outfile,'w') as f_out:\\n f_out.writelines(readyhtml)\",\n \"def template(self):\\n output=file(self.src, 'w').write\\n output(\\\"\\\"\\\"%s\\n<html>\\n<head>\\n<title>CHANGE ME</title>\\n<meta http-equiv=\\\"Content-Type\\\" content=\\\"text/html; charset=iso-8859-15\\\">\\n<link rel=\\\"STYLESHEET\\\" href=\\\"%s\\\" type=\\\"text/css\\\">\\n</head>\\n<body>\\n\\n<!--it-->\\n <p>\\n Pagina non disponibile in questa lingua!\\n <FORM><INPUT TYPE=\\\"button\\\" VALUE=\\\"Indietro\\\" onClick=\\\"history.go(-1);return true;\\\"> </FORM>\\n </p>\\n<!--/it-->\\n\\n<!--en-->\\n <p>\\n Page not available in this language!\\n <FORM><INPUT TYPE=\\\"button\\\" VALUE=\\\"Back\\\" onClick=\\\"history.go(-1);return true;\\\"> </FORM>\\n </p>\\n<!--/en-->\\n\\n</body>\\n</html>\\n\\\"\\\"\\\" % (self.doctype, self.css))\",\n \"def test_library_page_preview_html(self):\\n # Add some content to library.\\n self._add_simple_content_block()\\n self.validate_preview_html(self.library, self.container_view, can_reorder=False, can_move=False)\",\n \"def is_html(self):\\r\\n return self.__content_type == html_ctype\",\n \"def test_content_is_correct(self):\\n why_page = self.client.get(\\\"/why/\\\")\\n self.assertTemplateUsed(why_page, \\\"home/why.html\\\")\\n why_page_template_output = render_to_response(\\\"home/why.html\\\", {\\\"active\\\": \\\"why\\\"}).content\\n self.assertEqual(why_page.content, why_page_template_output)\",\n \"def mk_htmls(self):\\n\\n domain_link_list = self.scrape_domain_int_links()\\n html_fail_rate = float(self.failed_retrieving_html_counter / len(domain_link_list))\\n print \\\"mk_htmls SUCCES RATE %r\\\" % html_fail_rate\\n if html_fail_rate < (float(0.1)):\\n # driving links, to collect htmls from web and create htmls with removed img elements\\n for ind in range(len(domain_link_list)):\\n page_file_name = \\\"page_\\\" + str(ind + 1) + \\\".html\\\" # gen file names for html file of page on site\\n active_page_link = domain_link_list[ind]\\n if \\\";;;\\\" in active_page_link: # separator problems hedging\\n self.links_contain_seprator.append([active_page_link, page_file_name])\\n print \\\"LINK CONTAINS SEPARATOR, CAN NOT ADD TO PAGE LIST, WILL RUIN DATASYSTEM, WILL BE ADDED TO SEPARATE FILE\\\"\\n else:\\n BS_object = self.retrieve_html(active_page_link, self.domain_folder_name, self.html_folder_name, page_file_name)\\n self.page_list.append([active_page_link, page_file_name])\\n self.bs_object_dict[active_page_link] = BS_object\\n # if no \\\";;;\\\" separator found in link, then write as usual\\n if len(self.links_contain_seprator) > 0:\\n c_m.l_of_l_write(self.links_contain_seprator, self.main_path, self.domain_folder_name, self.link_contains_separator)\\n else:\\n c_m.l_of_l_write(self.page_list, self.main_path, self.domain_folder_name, self.page_list_f_name)\\n return self.bs_object_dict\\n else:\\n return False\",\n \"def test_get_html(self):\\r\\n context = self.mod.get_html()\\r\\n for key in ['display_name', 'tag', 'source', 'instructions_html', 'content_html', 'annotation_storage', 'token']:\\r\\n self.assertIn(key, context)\",\n \"def test_homepage_html(self):\\n\\n request = HttpRequest()\\n engine = import_module(settings.SESSION_ENGINE)\\n request.session = engine.SessionStore()\\n response = product_all(request)\\n html = response.content.decode(\\\"utf8\\\")\\n self.assertInHTML(\\\"<title>Book Store</title>\\\", html)\\n self.assertEqual(response.status_code, 200)\",\n \"def test_get_services_html(self):\\n pass\",\n \"def test_display_html_tag_prompt(self):\\r\\n self.context['tag_prompt'] = \\\"<p>Unescaped <b>HTML</b></p>\\\"\\r\\n xml = self.render_to_xml(self.context)\\r\\n\\r\\n # Because the HTML is unescaped, we should be able to\\r\\n # descend to the <b> tag\\r\\n xpath = \\\"//div[@class='block']/p/b\\\"\\r\\n self.assert_has_text(xml, xpath, 'HTML')\",\n \"def test_get_problem_html_error(self):\\r\\n module = CapaFactory.create()\\r\\n\\r\\n # Save the original problem so we can compare it later\\r\\n original_problem = module.lcp\\r\\n\\r\\n # Simulate throwing an exception when the capa problem\\r\\n # is asked to render itself as HTML\\r\\n module.lcp.get_html = Mock(side_effect=Exception(\\\"Test\\\"))\\r\\n\\r\\n # Stub out the get_test_system rendering function\\r\\n module.system.render_template = Mock(return_value=\\\"<div>Test Template HTML</div>\\\")\\r\\n\\r\\n # Turn off DEBUG\\r\\n module.system.DEBUG = False\\r\\n\\r\\n # Try to render the module with DEBUG turned off\\r\\n html = module.get_problem_html()\\r\\n\\r\\n self.assertTrue(html is not None)\\r\\n\\r\\n # Check the rendering context\\r\\n render_args, _ = module.system.render_template.call_args\\r\\n context = render_args[1]\\r\\n self.assertTrue(\\\"error\\\" in context['problem']['html'])\\r\\n\\r\\n # Expect that the module has created a new dummy problem with the error\\r\\n self.assertNotEqual(original_problem, module.lcp)\",\n \"def test_homepage_render(self):\\n\\n result = self.client.get(\\\"/\\\")\\n self.assertIn(\\\"<h1 class=\\\\\\\"title\\\\\\\">Bark Park!</h1>\\\", result.data)\",\n \"def test_html(self):\\n tags = (\\n ('<form', 1),\\n # Csrf, first_name, last_name, email, superuser, username and password\\n ('<input', 7),\\n ('type=\\\"text\\\"', 3),\\n ('type=\\\"password\\\"', 1),\\n ('type=\\\"checkbox\\\"', 1),\\n ('type=\\\"email\\\"', 1),\\n ('type=\\\"submit\\\"', 1),\\n )\\n for text, count in tags:\\n with self.subTest():\\n self.assertContains(self.response, text, count)\",\n \"def test_embed(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.embed_dirty), self.embed_clean)\",\n \"def display_html_report():\\n display(HTML('report_page.html'))\",\n \"def test_html(self):\\n tags = (('<input', 3),\\n ('<span', 1),\\n ('<button', 1))\\n\\n for text, count in tags:\\n with self.subTest():\\n self.assertContains(self.resp, text, count)\",\n \"def HTMLResponse():\\n\\n\\thtml = \\t\\\"<html><head><title>MA MAURO ESISTE?</title><style type='text/css'>body{width:30%}</style></head><body><pre>\\\"\\n\\thtml += \\\" _ __<br>\\\"\\n\\thtml += \\\" (_) / /<br>\\\"\\n\\thtml += \\\" ______ __ ____ ____ / /____<br>\\\"\\n\\thtml += \\\" / ___/ / _ \\\\\\\\/ _ \\\\\\\\/ / _ \\\\\\\\<br>\\\"\\n\\thtml += \\\" / / / / /_) / /_) / / ____/<br>\\\"\\n\\thtml += \\\"/__/ /__/ .___/ .___/__/ \\\\\\\\_____/<br>\\\"\\n\\thtml += \\\" / / / /<br>\\\"\\n\\thtml += \\\" /__/ /__/<br>\\\"\\n\\thtml += \\\"<b>PYTHON > ALL VERSION</b><br><br>\\\"\\n\\thtml += \\\"<marquee style='white-space:pre;'><br>\\\"\\n\\thtml += \\\" .. o .<br>\\\"\\n\\thtml += \\\" o.o o . o<br>\\\"\\n\\thtml += \\\" oo...<br>\\\"\\n\\thtml += \\\" __[]__<br>\\\"\\n\\thtml += \\\" phwr--> _\\\\\\\\:D/_/o_o_o_|__ <span style=\\\\\\\"font-family: 'Comic Sans MS'; font-size: 8pt;\\\\\\\">u wot m8</span><br>\\\"\\n\\thtml += \\\" \\\\\\\\\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"\\\\\\\"/<br>\\\"\\n\\thtml += \\\" \\\\\\\\ . .. .. . /<br>\\\"\\n\\thtml += \\\"^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>\\\"\\n\\thtml += \\\"</marquee><br><strike>reverse engineering a protocol impossible to reverse engineer since always</strike><br>we are actually reverse engineering bancho successfully. for the third time.</pre></body></html>\\\"\\n\\treturn html\",\n \"def test_error_html_using_delete(self):\\n pass\",\n \"def test_get_html(self):\\r\\n context = self.mod.get_html()\\r\\n for key in ['display_name', 'instructions_html', 'annotation_storage', 'token', 'tag', 'openseadragonjson']:\\r\\n self.assertIn(key, context)\",\n \"def test_html(self):\\n \\n tags = (('<form',1),\\n ('<input',6),\\n ('type=\\\"text\\\"',3),\\n ('type=\\\"email\\\"',1),\\n ('type=\\\"submit\\\"',1))\\n \\n for text, count in tags:\\n with self.subTest():\\n self.assertContains(self.resp, text, count)\",\n \"def handle_problem_html_error(self, err):\\r\\n log.exception(err.message)\\r\\n\\r\\n # TODO (vshnayder): another switch on DEBUG.\\r\\n if self.runtime.DEBUG:\\r\\n msg = (\\r\\n u'[courseware.capa.capa_module] <font size=\\\"+1\\\" color=\\\"red\\\">'\\r\\n u'Failed to generate HTML for problem {url}</font>'.format(\\r\\n url=cgi.escape(self.location.to_deprecated_string()))\\r\\n )\\r\\n msg += u'<p>Error:</p><p><pre>{msg}</pre></p>'.format(msg=cgi.escape(err.message))\\r\\n msg += u'<p><pre>{tb}</pre></p>'.format(tb=cgi.escape(traceback.format_exc()))\\r\\n html = msg\\r\\n\\r\\n else:\\r\\n # We're in non-debug mode, and possibly even in production. We want\\r\\n # to avoid bricking of problem as much as possible\\r\\n\\r\\n # Presumably, student submission has corrupted LoncapaProblem HTML.\\r\\n # First, pull down all student answers\\r\\n student_answers = self.lcp.student_answers\\r\\n answer_ids = student_answers.keys()\\r\\n\\r\\n # Some inputtypes, such as dynamath, have additional \\\"hidden\\\" state that\\r\\n # is not exposed to the student. Keep those hidden\\r\\n # TODO: Use regex, e.g. 'dynamath' is suffix at end of answer_id\\r\\n hidden_state_keywords = ['dynamath']\\r\\n for answer_id in answer_ids:\\r\\n for hidden_state_keyword in hidden_state_keywords:\\r\\n if answer_id.find(hidden_state_keyword) >= 0:\\r\\n student_answers.pop(answer_id)\\r\\n\\r\\n # Next, generate a fresh LoncapaProblem\\r\\n self.lcp = self.new_lcp(None)\\r\\n self.set_state_from_lcp()\\r\\n\\r\\n # Prepend a scary warning to the student\\r\\n _ = self.runtime.service(self, \\\"i18n\\\").ugettext\\r\\n warning_msg = _(\\\"Warning: The problem has been reset to its initial state!\\\")\\r\\n warning = '<div class=\\\"capa_reset\\\"> <h2> ' + warning_msg + '</h2>'\\r\\n\\r\\n # Translators: Following this message, there will be a bulleted list of items.\\r\\n warning_msg = _(\\\"The problem's state was corrupted by an invalid submission. The submission consisted of:\\\")\\r\\n warning += warning_msg + '<ul>'\\r\\n\\r\\n for student_answer in student_answers.values():\\r\\n if student_answer != '':\\r\\n warning += '<li>' + cgi.escape(student_answer) + '</li>'\\r\\n\\r\\n warning_msg = _('If this error persists, please contact the course staff.')\\r\\n warning += '</ul>' + warning_msg + '</div>'\\r\\n\\r\\n html = warning\\r\\n try:\\r\\n html += self.lcp.get_html()\\r\\n except Exception: # pylint: disable=broad-except\\r\\n # Couldn't do it. Give up.\\r\\n log.exception(\\\"Unable to generate html from LoncapaProblem\\\")\\r\\n raise\\r\\n\\r\\n return html\",\n \"def index_html(self,REQUEST): \\n return self.posting_html(self,REQUEST)\",\n \"def is_html(self):\\n return self.__content_type == html_ctype\",\n \"def get_html(self):\\r\\n raise NotImplementedError(\\r\\n \\\"get_html() must be provided by specific modules - not present in {0}\\\"\\r\\n .format(self.__class__))\",\n \"def test_gethtml(self):\\r\\n mock_module = CHModuleFactory.create()\\r\\n\\r\\n def fake_get_display_items():\\r\\n \\\"\\\"\\\"\\r\\n A mock of get_display_items\\r\\n \\\"\\\"\\\"\\r\\n return [FakeChild()]\\r\\n mock_module.get_display_items = fake_get_display_items\\r\\n out_html = mock_module.render('student_view').content\\r\\n self.assertTrue('This is supposed to be test html.' in out_html)\\r\\n self.assertTrue('i4x://this/is/a/fake/id' in out_html)\",\n \"def unrendered(self) -> str:\",\n \"def test_get_root_html3(self):\\n pass\",\n \"def outputHtml(s):\\n htmlFile.write(s + \\\"\\\\n\\\")\",\n \"def html(self):\\n return self.report_format in ['pdf', 'html']\",\n \"def test__markHTML_simpleHTML1(self):\\n self._degrotesque._restoreDefaultElementsToSkip()\\n assert(self._degrotesque._markHTML(\\\"Hallo <b>Mama!</b>\\\")==\\\"000000111000001111\\\")\",\n \"def test_render_html_no_layout(self):\\n assets = Asset.objects.select_subclasses()\\n # Create a section without specifying layout \\n section = create_section(title=\\\"Test Section1\\\", story=self.story)\\n # Associate assets with the section without specifying a container\\n SectionAsset.objects.create(section=section, asset=assets[0])\\n SectionAsset.objects.create(section=section, asset=assets[1])\\n html = section.render_html()\\n self.assertIn(assets[0].title, html)\\n self.assertIn(assets[1].title, html)\",\n \"def output_html(self, path):\\n if path is None:\\n return\\n import os\\n fout = codecs.open(os.path.abspath(path), 'w', encoding='utf-8')\\n fout.write('<html><body><table>')\\n for data in self.datas:\\n fout.write('<tr><td>%s</td><td>%s</td><td>%s</td></tr>' % (data['url'], data['title'], data['summary']))\\n self.datas.remove(data)\\n fout.write('</table></body></html>')\\n fout.close()\",\n \"def test_blank_problem(self):\\r\\n xml_str = \\\"<problem> </problem>\\\"\\r\\n\\r\\n # Create the problem\\r\\n problem = new_loncapa_problem(xml_str)\\r\\n\\r\\n # Render the HTML\\r\\n rendered_html = etree.XML(problem.get_html())\\r\\n # expect that we made it here without blowing up\\r\",\n \"def test_insert_content(self):\\n self.request.path = \\\"/non_ascii_request/\\\"\\n response = self.panel.process_request(self.request)\\n # ensure the panel does not have content yet.\\n self.assertNotIn(\\\"nôt åscíì\\\", self.panel.content)\\n self.panel.generate_stats(self.request, response)\\n # ensure the panel renders correctly.\\n content = self.panel.content\\n self.assertIn(\\\"nôt åscíì\\\", content)\\n self.assertValidHTML(content)\",\n \"def test_sample(self):\\n response = self.tester.get('/sample-household/',\\n content_type='html/text')\\n self.assertEqual(response.status_code, 200)\",\n \"def test_clean_storytranslation_html(self):\\n unclean_summary = (\\\"<p>This is the first paragraph</p>\\\"\\n \\\"<script src=\\\\\\\"/static/js/fake.js\\\\\\\"></script>\\\")\\n unclean_call = (\\\"<blockquote>Quote in call</blockquote>\\\"\\n \\\"<iframe src=\\\\\\\"/fake/\\\\\\\"></iframe>\\\")\\n story = create_story(title=\\\"Test Story\\\", summary=unclean_summary,\\n call_to_action=unclean_call, status='draft')\\n story.save()\\n story = Story.objects.get(story_id=story.story_id)\\n # Test that the invalid tags aren't in the saved field values.\\n # Right now, we don't care whether the tags were escaped or removed\\n self.assertNotIn(\\\"<script\\\", story.summary)\\n self.assertNotIn(\\\"<iframe\\\", story.call_to_action)\",\n \"def test_img(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.img_dirty), self.img_clean)\",\n \"def test_create_form_with_malformed_html(self):\\n with pytest.raises(ValidationError):\\n SurveyForm.create('badform', '<input name=\\\"oops\\\" /><<<>')\",\n \"def test_content_is_correct(self):\\n home_page = self.client.get(\\\"/\\\")\\n self.assertTemplateUsed(home_page, \\\"home/home.html\\\")\\n home_page_template_output = render_to_response(\\\"home/home.html\\\", {\\\"active\\\": \\\"home\\\"}).content\\n self.assertEqual(home_page.content, home_page_template_output)\",\n \"def __html__(self, file_path:str):\\n raise NotImplementedError\",\n \"def view_html_page():\\n\\n return render_template(\\\"moby.html\\\")\",\n \"def writeHTMLbody(appurl, numberOfCompletedFiles, stoppedState, componentList, dayStart, dayEnd):\\n html = u'''\\\\\\n<html>\\n <head></head>\\n <body>\\n <p>Kære Operatør</p>\\n <p>\\n Her en rapport over hvordan det er gået med opsamling af YouSee\\n TV i det seneste døgn. Informationerne i denne mail er alle trukket fra\\n <a href=\\\"%(url)s\\\">Ingest Monitor websiden</a> som du også selv kan klikke rundt på.\\n </p><p>\\n Døgnet startede i går klokken %(start)s og varede indtil i dag klokken %(end)s.\\n </p>\\n <p>\\n''' % {'url': appurl, 'start': dayStart, 'end': dayEnd}\\n\\n html += '<hr>'\\n html += u'<p>I det seneste døgn blev der med succes blevet behandlet ' + str(numberOfCompletedFiles) + ' filer.</p>'\\n\\n if len(componentList) > 0:\\n # add a list of files still in progress BUT previously were in a FAILED state\\n # grouped by the component\\n html += u'<h3>Filer som tidligere fejlede men som stadig er under behandling eller er blevet genstartet.</h3>'\\n html += u'<p>'\\n for component in componentList:\\n html += u'<h4>Følgende filer fejlede i ' + component[0] + ' komponenten:</h4>'\\n\\t newList = set([e['entity']['name'] for e in component[1]])\\n for e in newList:\\n html += u'<a href=\\\"'\\\\\\n + getDetailUrl(appurl, e)\\\\\\n + '\\\">'\\\\\\n + e\\\\\\n + '</a><br>\\\\n'\\n html += u'</p>'\\n else:\\n html += u'<p>Ingen filer under behandling har en fejlstatus.</p>'\\n\\n html += '<hr>'\\n if len(stoppedState) > 0:\\n # add a list of failed files to the report.\\n html += u'<h3>Filer der er markeret som værende stoppet og som kun bliver genstartet ved manuel indgriben:</h3>'\\n html += u'<p>'\\n for e in stoppedState:\\n html += u'<a href=\\\"' + getDetailUrl(appurl, e['entity']['name']) + '\\\">'\\\\\\n + e['entity']['name']\\\\\\n + u'</a><br>\\\\n'\\n html += u'</p>'\\n else:\\n html += u'<p>Ingen filer er markeret som stoppet.</p>'\\n\\n # end the html part of the report\\n html += u'''\\\\\\n </ul>\\n </p>\\n </body>\\n</html>\\n'''\\n return html\",\n \"def test_html_documentation(self):\\n app = Sphinx(\\n self.source_dir,\\n self.config_dir,\\n self.output_dir,\\n self.doctree_dir,\\n buildername='html',\\n warningiserror=True,\\n )\\n app.build(force_all=self.all_files)\",\n \"def get_html( self, prefix=\\\"\\\" ):\\n raise TypeError( \\\"Abstract Method\\\" )\",\n \"def test_dose_check_generation(self):\\n response = self.client.get('/dose_check/V117108T/Insertion%201/Pre%20Ins%201/', follow=True)\\n self.assertEqual(response.status_code, 200)\\n self.assertTemplateUsed(response, 'myapp/dose_check.html')\\n # with open(r\\\"myapp\\\\\\\\tests\\\\\\\\test_dose_check_page.html\\\", 'r') as myfile:\\n # test_html_data=myfile.read()\\n # self.assertEqual(response.content.decode(\\\"utf-8\\\"),test_html_data)\",\n \"def command_show(problem):\\r\\n print problem.get_html()\",\n \"def test_killhtml():\\r\\n test_cases = (\\r\\n ('Just Text', 'Just Text'),\\r\\n ('<p>One</p><p>Two</p>', 'One Two'),\\r\\n ('<p>One</p> \\\\n <p>Two</p>', 'One Two'),\\r\\n ('<p>One</p>\\\\n<p>Two</p>', 'One Two'),\\r\\n ('Some Text<p>then tag</p>', 'Some Text then tag'),\\r\\n ('<p>Some Text</p>then no tag.', 'Some Text then no tag.'),\\r\\n ('Entities & <hr/>', 'Entities & <hr/>'),\\r\\n ('<p>Unknown tags: <asdf>qwerty</asdf>', 'Unknown tags: qwerty'),\\r\\n )\\r\\n for input_text, expected_output in test_cases:\\r\\n yield is_equal, killhtml(input_text), expected_output\",\n \"def generate_html(self):\\n html_text_1 = \\\"\\\"\\\"\\n <div class=\\\"concept\\\">\\n\\n \\t\\t<div class=\\\"concept-title\\\">\\n\\n \\t\\t\\t\\t\\\"\\\"\\\" + self.title\\n\\n html_text_2 = \\\"\\\"\\\"\\n \\t\\t</div>\\n\\n \\t\\t<div class=\\\"concept-description\\\">\\n\\n\\t\\t <p>\\n\\t\\t\\t\\n \\t\\t \\t\\t\\\"\\\"\\\" + self.description + \\\"\\\"\\\" \\n \\n </p>\\\"\\\"\\\"\\n\\n html_text_3 = '''\\n\\n \\t\\t</div>\\n\\n </div>'''\\n\\n return html_text_1 + html_text_2 + html_text_3\",\n \"def _render(self) -> None:\\n pass\",\n \"def test__markHTML_simpleHTML3(self):\\n self._degrotesque._restoreDefaultElementsToSkip()\\n assert(self._degrotesque._markHTML(\\\"a<b>a</b>\\\")==\\\"011101111\\\")\",\n \"def _build_html():\\n\\n # Build twice until getnikola/nikola#1032 is fixed.\\n local('nikola build && nikola build')\\n\\n ## Remove all the source files, we only want the output!\\n local('ls | grep -v output | xargs rm -rf')\\n with settings(warn_only=True):\\n local('mv output/* output/.* .')\",\n \"def test__markHTML_simpleHTML2(self):\\n self._degrotesque._restoreDefaultElementsToSkip()\\n assert(self._degrotesque._markHTML(\\\"a<b></b>\\\")==\\\"01111111\\\")\",\n \"def test_custom_decorator_displaytex_no_malformed(self):\\n self.assertEqual(\\n DOM.render(\\n DOM.create_element(\\n ashley_render_children,\\n {\\n \\\"block\\\": {\\n \\\"key\\\": \\\"a215p\\\",\\n \\\"text\\\": \\\"\\\",\\n \\\"type\\\": \\\"atomic\\\",\\n \\\"data\\\": {\\\"type\\\": \\\"TEXBLOCK\\\"},\\n }\\n },\\n )\\n ),\\n '<span class=\\\"ashley-latex-display\\\"></span>',\\n )\",\n \"def render(self):\\n pass\",\n \"def render(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.84040964","0.69680446","0.6919716","0.687463","0.6762656","0.67169726","0.66983867","0.65646785","0.6555906","0.6548506","0.6533556","0.65294725","0.6498341","0.6488538","0.6470183","0.64627945","0.6459197","0.64506996","0.64353263","0.64152896","0.6384148","0.6376362","0.6356995","0.6349154","0.6324273","0.63223004","0.62979436","0.62601465","0.6223759","0.62206346","0.62206346","0.62116694","0.6206625","0.6200237","0.61863965","0.6176208","0.6173827","0.6165572","0.61483514","0.6144378","0.61341083","0.6117066","0.6075064","0.60746247","0.60706425","0.60626096","0.60151434","0.6002572","0.6000473","0.600019","0.5980019","0.5977449","0.5964231","0.5938515","0.59313285","0.5931243","0.5931135","0.5910505","0.5908319","0.5905898","0.5905308","0.5902721","0.5893352","0.588193","0.5877549","0.5875712","0.5869657","0.5866848","0.5865133","0.5862726","0.58453625","0.58395493","0.58359855","0.5832939","0.58323896","0.5825359","0.5823092","0.58188534","0.57989454","0.57753915","0.57742095","0.5772788","0.57515216","0.57484585","0.5741911","0.5740759","0.5725261","0.57220614","0.5720989","0.57164514","0.5706776","0.5700829","0.5699454","0.5691286","0.568411","0.56661665","0.5662389","0.56612414","0.56512076","0.56512076"],"string":"[\n \"0.84040964\",\n \"0.69680446\",\n \"0.6919716\",\n \"0.687463\",\n \"0.6762656\",\n \"0.67169726\",\n \"0.66983867\",\n \"0.65646785\",\n \"0.6555906\",\n \"0.6548506\",\n \"0.6533556\",\n \"0.65294725\",\n \"0.6498341\",\n \"0.6488538\",\n \"0.6470183\",\n \"0.64627945\",\n \"0.6459197\",\n \"0.64506996\",\n \"0.64353263\",\n \"0.64152896\",\n \"0.6384148\",\n \"0.6376362\",\n \"0.6356995\",\n \"0.6349154\",\n \"0.6324273\",\n \"0.63223004\",\n \"0.62979436\",\n \"0.62601465\",\n \"0.6223759\",\n \"0.62206346\",\n \"0.62206346\",\n \"0.62116694\",\n \"0.6206625\",\n \"0.6200237\",\n \"0.61863965\",\n \"0.6176208\",\n \"0.6173827\",\n \"0.6165572\",\n \"0.61483514\",\n \"0.6144378\",\n \"0.61341083\",\n \"0.6117066\",\n \"0.6075064\",\n \"0.60746247\",\n \"0.60706425\",\n \"0.60626096\",\n \"0.60151434\",\n \"0.6002572\",\n \"0.6000473\",\n \"0.600019\",\n \"0.5980019\",\n \"0.5977449\",\n \"0.5964231\",\n \"0.5938515\",\n \"0.59313285\",\n \"0.5931243\",\n \"0.5931135\",\n \"0.5910505\",\n \"0.5908319\",\n \"0.5905898\",\n \"0.5905308\",\n \"0.5902721\",\n \"0.5893352\",\n \"0.588193\",\n \"0.5877549\",\n \"0.5875712\",\n \"0.5869657\",\n \"0.5866848\",\n \"0.5865133\",\n \"0.5862726\",\n \"0.58453625\",\n \"0.58395493\",\n \"0.58359855\",\n \"0.5832939\",\n \"0.58323896\",\n \"0.5825359\",\n \"0.5823092\",\n \"0.58188534\",\n \"0.57989454\",\n \"0.57753915\",\n \"0.57742095\",\n \"0.5772788\",\n \"0.57515216\",\n \"0.57484585\",\n \"0.5741911\",\n \"0.5740759\",\n \"0.5725261\",\n \"0.57220614\",\n \"0.5720989\",\n \"0.57164514\",\n \"0.5706776\",\n \"0.5700829\",\n \"0.5699454\",\n \"0.5691286\",\n \"0.568411\",\n \"0.56661665\",\n \"0.5662389\",\n \"0.56612414\",\n \"0.56512076\",\n \"0.56512076\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7505332"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":25692,"cells":{"query":{"kind":"string","value":"double column mip table"},"document":{"kind":"string","value":"def testDoubleMIP(self):\n\n self.M.render(self.testoutput[2], wide=True)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def columns(self):\n \n pass","def with_column(self, label, values):\n \n \n \n # self.column_labels.append(label)\n # for i in range(len(self.rows)):\n # self.rows[i].append(values[i]) \n \n new_label = []\n new_rows = []\n for x in self.column_labels:\n new_label.append(x)\n new_label.append(label)\n \n for i in range(len(self.rows)):\n new_row = []\n new_row += self.rows[i]\n # for i in range(len(b)): \n new_row.append(values[i])\n new_rows.append(new_row)\n \n \n new_Table = T88ble(new_rows, new_label)\n\n return new_Table","def prepare_table(self):\n i = 0\n for item in ['DN[-]', 'd_out[mm]', 'tl_trub[mm]', 'roztec_trub[mm]', 'delka[mm]', 'roztec_prep[mm]', 'vyska_prep[mm]']:\n self.table.insertColumn(i)\n self.table.setHorizontalHeaderItem(i, QTableWidgetItem(item))\n i += 1\n for item in ['tl_prep[mm]','pocet_prep[-]', 'pocet_trub[-]', 'TP[m/s]', 'MZP[m/s]', 'vykon [W]',\n 'tlak_ztraty[Pa]', 'hmotnost[kg]']:\n self.table.insertColumn(i)\n self.table.setHorizontalHeaderItem(i, QTableWidgetItem(item))\n i += 1","def multiplicationTable(size=10,line_space=7):\n for column in range(1,size+1):\n row = ''\n for i in range(1, 11):\n if i*column > 9:\n row += str(i*column) + ' '*( (line_space+1) - len(str(i*column)) )\n continue\n row += str(i*column)+ ' '*line_space\n print(row)","def create_numbers_table():\n work_tuples = parse_columns()\n print('\\n\\n\\n ----- Tableau récapitulatif -----')\n print('-----------------------')\n for ii in work_tuples:\n line = '|'\n for ij in ii:\n line += ' ij |'\n print(line)\n print('-----------------------')","def multtable(n):\n for i in range(1, n+1):\n for j in range(1, n+1):\n print(i * j, end=' ')\n print()","def generate_table(self, rows):\n ...","def mult_tab(self):\n raise NotImplementedError","def make_tables(self):\n r = np.zeros((self.size*self.size, 4))\n p = np.zeros((self.size*self.size, 4, self.size*self.size))\n directions = np.array([[1, -1, 0, 0], [0, 0, -1, 1]])\n for x in range(self.size):\n for y in range(self.size):\n for a in range(4):\n i = x*self.size + y\n r[i, a] = self.reward((x, y))\n if (x, y) == (self.size-1, self.size-1) or \\\n (x, y) == (self.mid, self.mid):\n p[i, a, 0] = 1\n else:\n for d in range(4):\n dx, dy = directions[:, d]\n x_ = max(0, min(self.size-1, x+dx))\n y_ = max(0, min(self.size-1, y+dy))\n j = x_*self.size + y_\n if self.noise is not None:\n p[i, a, j] += 0.3 * self.noise[x, y, a, d] + 0.7 * int(a == d)\n else:\n p[i, a, j] += int(a == d)\n return r, p","def tiles(self, nums, row = 1, spaces = 0):\r\n # We add the (\" \" * 5) to align the rows\r\n # with odd number of values\r\n separator = (\"+---+\" + (\" \" * 5)) * row\r\n space = (\" \" * 5) * spaces\r\n\r\n tile = space + separator + space + \"\\n\"\r\n \r\n tile += space\r\n for i in nums:\r\n # We add the (\" \" * 5) to align the rows\r\n # with odd number of values\r\n tile += f\"| {i} |\" + (\" \" * 5)\r\n tile += space + \"\\n\"\r\n \r\n tile += space + separator + space + \"\\n\"\r\n \r\n return tile","def dyntable(self):\n table = ANSITable(\n Column(\"j\", colalign=\">\", headalign=\"^\"),\n Column(\"m\", colalign=\"<\", headalign=\"^\"),\n Column(\"r\", colalign=\"<\", headalign=\"^\"),\n Column(\"I\", colalign=\"<\", headalign=\"^\"),\n Column(\"Jm\", colalign=\"<\", headalign=\"^\"),\n Column(\"B\", colalign=\"<\", headalign=\"^\"),\n Column(\"Tc\", colalign=\"<\", headalign=\"^\"),\n Column(\"G\", colalign=\"<\", headalign=\"^\"), border=\"thin\")\n\n for j, link in enumerate(self):\n table.row(link.name, *link._dyn2list())\n return str(table)","def table_for_mi(n11, n10, n01, n00, feature, w=15):\r\n\r\n table = '|{}|{}|{}|'.format(''.center(w), feature.center(\r\n w), 'No \"{}\"'.format(feature).center(w))\r\n table += '\\n|' + '-' * w\r\n table += '|' + '-' * w\r\n table += '|' + '-' * w\r\n table += '|'\r\n\r\n table += '\\n|{}|{}|{}|'.format('y(=1)'.center(w),\r\n '{}'.format(n11).center(w), '{}'.format(n10).center(w))\r\n table += '\\n|{}|{}|{}|'.format('y(=0)'.center(w),\r\n '{}'.format(n01).center(w), '{}'.format(n00).center(w))\r\n\r\n return table","def get_cols_dummy():","def _init_pagoda_clses(self):\n a = []; b = [] #IGNORE:C0321\n c = []; d = [] #IGNORE:C0321\n row_selector = ((a, b), (c, d))\n for cell in self.compact:\n row_selector[cell.y % 2][cell.x % 2].append(cell)\n cell.pvalue = cell.y % 2 + 1 + cell.x % 2 \n return a, b, c, d","def twenty_four_cell(self):\n verts = []\n q12 = QQ(1)/2\n base = [q12,q12,q12,q12]\n for i in range(2):\n for j in range(2):\n for k in range(2):\n for l in range(2):\n verts.append([x for x in base])\n base[3] = base[3]*(-1)\n base[2] = base[2]*(-1)\n base[1] = base[1]*(-1)\n base[0] = base[0]*(-1)\n verts = verts + permutations([0,0,0,1])\n verts = verts + permutations([0,0,0,-1])\n return Polyhedron(vertices = verts)","def prepare_table(table):\n n = len(table)\n for i, row in enumerate(table):\n assert len(row) == n, f\"len(row) = {len(row)} != {n} = n\"\n for j, _ in enumerate(row):\n if i == j:\n table[i][i] = 0.0\n elif i > j:\n table[i][j] = 1 - table[j][i]\n return table","def transpose():","def timingColumns(self, results):\n \n pass","def zernike_Double_Index(nlevels):\n \n\t \n if not (nlevels>=0):\n print('Input parameter nlevels must be >= 0')\n raise AssertionError()\n \n if (nlevels == 0):\n \n m = 0\n n = 0\n \n return n, m\n \n else:\n \n # ++++ Defining layout for row number n and colunmn number m ++++++++\n\n row_n = nlevels+1\n col_m = 2*nlevels +1\n x = np.arange(row_n)\n y = np.arange(-(col_m-1)//2, (col_m+1)//2,1)\n Q = [(i,j) for i in x for j in y]\n #\n\n\n nm_index = []\n \n top = (col_m + 1)/2\n leftside = row_n*col_m - col_m + 1\n rightside = row_n*col_m \n\n k1 = 0; k2 = 0\n\n for i in xrange(top,row_n*col_m+1, 2*col_m):\n\n nm_index.append(Q[i-1])\n s1 = i + col_m + 1\n s2 = i + col_m - 1 \n jj1 = k1\n jj2 = k2\n\n\n while (s2 <= leftside): \n\n nm_index.append(Q[s2-1])\n s2 +=col_m - 1\n jj1 += 1\n jj2 -= 1\n\n leftside +=2\n\n jj1 = k1\n jj2 = k2\n\n while (s1 <= rightside): \n\n # \n nm_index.append(Q[s1-1])\n s1 +=col_m + 1\n jj1 += 1\n jj2 += 1\n\n rightside -=2\n k1 = 0; k2 += 2\n\n n = np.array(nm_index)[:,0]\n m = np.array(nm_index)[:,1]\n\n return n, m","def row_times_column(m1, row, m2, column):\n\n pass","def table(nb, max):\n\ti = 0\n\twhile i < max:\n\t\tprint(i + 1, \"*\", nb, \"=\", (i + 1) * nb)\n\t\ti += 1","def multiply_trtr_diagram(data):\n\n names = data.index.names\n data = pd.concat([ data.xs('rere', level=2), \\\n data.xs('reim', level=2) + data.xs('imre', level=2)], \\\n keys=['re', 'im']).reorder_levels([1,2,0]).\\\n sort_index(level=[0,1])\n data.index.names = names\n return data","def __repr__(self):\n return '<widths: {}, subtable: {}>'.format(self.widths, self.subtable)","def collect_columns():\n return ((x, y) for x in range(72) for y in range(x + 9, 81, 9))","def multi_table(a, b):\n for i in range(1, int(b) + 1):\n print(f'{a} * {i} = {a*i}')","def _gen_table_rows(self):\n row_labels = self._get_padded_row_labels()\n column_labels = self._get_padded_column_labels()\n for row in zip(*column_labels):\n yield ''.join('<td>%s</td>' % c for c in row)\n for label, row_string in zip(row_labels, HeatMap._gen_table_rows(self)):\n yield ''.join('<td>%s</td>' % c for c in label) + row_string","def tab(data, column) :\r\n\r\n table = {}\r\n \r\n for i in data :\r\n if i[column] not in table :\r\n # add it to tab\r\n table[i[column]] = 1 \r\n else:\r\n # add tabulation\r\n table[i[column]] += 1\r\n\r\n #place the cursor back at 0\r\n \r\n return table","def create_w_tbl(index: int, entries: int) -> List[float]:\n min_w = StackupTestHelper.index_to_min_width_fn(index)\n return list(map(lambda x: min_w*x, range(1, 4 * entries + 1, 4)))","def extractSubTable(self,**dico):\n #\n if not len(dico):\n return self.copy()\n elif len(dico)>1:\n msg='only one argument allowed.'\n raise msg\n #\n cle=list(dico.keys())[0]\n val=dico[cle]\n cle=cle.lower()\n if cle=='withvaluesincolumn':\n model,numeroColonne=val[0],val[1]\n listTypeCheck(model,[IntType,FloatType])\n model=[float(x) for x in model]\n verifyType(numeroColonne,[StringType,\\\n IntType,FloatType])\n tttitres=self.getColumnNames()\n ttunits = self.getColumnUnits()\n if type(numeroColonne) is StringType:\n for tit in tttitres:\n if tit==numeroColonne:\n numCol=tttitres.index(tit)\n pass\n pass\n pass\n else:\n if numeroColonne>=len(tttitres):\n msg='The table does not have\\n'\n msg+='that number of columns : %s'%numeroColonne\n raise msg\n numCol=numeroColonne\n pass\n if len(val)==3:\n eps=val[2]\n pass\n else:\n eps=1.e-15\n pass\n new=DataTable(self.getName(),tttitres,ttunits)\n nlig=self.getNbRows()\n ip=0\n comp=[float(x) for x in self.getColumn(numCol)]\n for ip in range(len(model)):\n for i in range(len(comp)):\n value=comp[i]\n if ip==1 and i==len(comp)-1:\n pass\n if areClose(value,model[ip],eps,'rel'):\n new.addRow(self.getRow(i))\n pass\n if ip==len(model):\n break\n pass\n pass\n pass \n else:\n valeurs=toList(val)\n tttitres=self.getColumnNames()\n ttunits = self.getColumnUnits()\n for st in ['row','column']:\n if st=='row':nn=self.getNbRows()\n if st=='column':nn=self.getNbColumns()\n if cle.find(st)>=0:\n cleOk=st\n pass\n if cle==st:\n if len(valeurs) != 1:\n raise Exception(\" list length problem within the extractSubTable function\")\n if cle=='from'+st: valeurs=valeurs[valeurs[0]:nn-1]\n if cle=='to'+st: valeurs=valeurs[0:valeurs[0]]\n if cle.find('name')>=0:\n newv=[]\n for v in valeurs:\n for tit in tttitres:\n if tit==v:\n newv.append(tttitres.index(tit))\n break\n pass\n pass\n valeurs=newv\n pass\n pass\n if cleOk=='row':\n newtitres=tttitres\n newunits = ttunits\n pass\n if cleOk=='column':\n newtitres=[]\n newunits = []\n for i in valeurs:\n newtitres.append(tttitres[i])\n if len(ttunits): newunits.append(ttunits[i])\n pass\n pass\n new=DataTable(self.getName(),newtitres,newunits)\n for i in valeurs:\n if cleOk=='row':\n liste=self.getRow(i)\n new.addRow(liste)\n pass\n if cleOk=='column':\n liste=self.getColumn(i)\n new.addColumnValues(liste)\n pass\n pass\n pass\n return new","def derMatrix(Bulk_Operators, Bdy_Operators, Bulk_second, s=1):\n\t\tMatrix = []\n\t\tfor i in range(1, M_max + 1):\n\t\t\t\trow = []\n\t\t\t\tfor Bulk_Op in Bulk_Operators:\n\t\t\t\t\t\ttable_call = N*table1.table[0, i].subs({\"Delta\":Bulk_Op, \"Delta_12\":delta_12, \"Xi\":1.00})\n\t\t\t\t\t\trow.append(table_call)\n\t\t\t\tfor index in range(len(Bulk_second)):\n\t\t\t\t\t\trow.append(0*table1.table[0,0])\n\t\t\t\tfor Bdy_Op in Bdy_Operators:\n\t\t\t\t\tif Bdy_Op == 2.0:\n\t\t\t\t\t\t\tprint(\"here\")\n\t\t\t\t\t\t\ttable_call = (N-1)*table1.table[1, i].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\t\t\telse:\n\t\t\t\t\t\ttable_call = table1.table[1, i].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\t\t\trow.append(table_call)\n\t\t\t\tXi = symbols('Xi')\n\t\t\t\tif s == 1:\n\t\t\t\t\t\tlast_expr = Xi**((delta_1 + delta_2)/2)\n\t\t\t\t\t\tlast_elem = diff(last_expr, Xi, i).subs({\"Xi\":1.00}).evalf()\n\t\t\t\t\t\trow.append(last_elem)\n\t\t\t\tMatrix.append(row)\n\t\t\t\trow2 = []\n\t\t\t\tfor index in range(len(Bulk_Operators)):\n\t\t\t\t\t\trow2.append(0*table1.table[0,0])\n\t\t\t\tfor Bulk_Op in Bulk_second:\n\t\t\t\t\t\ttable_call = table1.table[0, i].subs({\"Delta\":Bulk_Op, \"Delta_12\":delta_12, \"Xi\":1.00})\n\t\t\t\t\t\trow2.append(table_call)\n\t\t\t\tfor Bdy_Op in Bdy_Operators:\n\t\t\t\t\t\tif Bdy_Op == 2.0:\n\t\t\t\t\t\t\tprint(\"here\")\n\t\t\t\t\t\t\ttable_call = -1*table1.table[1, i].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\ttable_call = table1.table[1, i].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\t\t\t\trow2.append(table_call)\n\t\t\t\tXi = symbols('Xi')\n\t\t\t\tif s == 1:\n\t\t\t\t\t\tlast_expr = Xi**((delta_1 + delta_2)/2)\n\t\t\t\t\t\tlast_elem = diff(last_expr, Xi, i).subs({\"Xi\":1.00}).evalf()\n\t\t\t\t\t\trow2.append(last_elem)\n\t\t\t\tMatrix.append(row2)\t\t\n\t\treturn np.array(Matrix)","def _settemplates(self, onecol, twocol):\n\n self.template = \"\"\"\n <table class=\"f\"><tbody>\n %s\n %s\n </tbody></table>\n \"\"\" % (self.header, onecol)\n\n # This is suitable for two column width.\n self.wide_template = \"\"\"\n <table class=\"f\"><tbody>\n %s\n %s\n </tbody></table>\n \"\"\" % (self.header.replace(\"1\", \"2\"), twocol)","def times_table_6x6(x):\n assert x > 12 == False, \"The highest value of input is 12\"\n layout = \"\"\n index = 0\n while x > index:\n layout += \"{%s:>4}\" % index\n index += 1\n\n for i in range(1, x + 1):\n print(\n layout.format(\n i * 1,\n i * 2,\n i * 3,\n i * 4,\n i * 5,\n i * 6,\n i * 7,\n i * 8,\n i * 9,\n i * 10,\n i * 11,\n i * 12,\n )\n )","def table(self):\n return self.t","def multtable(n):\n for i in range(1,n+1):\n for x in range(1, n+1):\n result = print(i * x, end =' ')\n print ()\n return result","def __str__(self):\n table_string = ''\n values = [x * y for x in range(1, self.x + 1)\n for y in range(1, self.y + 1)\n ]\n for value in range(1, len(values) + 1):\n if value % self.x == 0:\n table_string += f'{values[value - 1]}\\n'\n else:\n table_string += f'{values[value - 1]} | '\n return table_string","def six_hundred_cell(self):\n verts = []\n q12 = QQ(1)/2\n base = [q12,q12,q12,q12]\n for i in range(2):\n for j in range(2):\n for k in range(2):\n for l in range(2):\n verts.append([x for x in base])\n base[3] = base[3]*(-1)\n base[2] = base[2]*(-1)\n base[1] = base[1]*(-1)\n base[0] = base[0]*(-1)\n for x in permutations([0,0,0,1]):\n verts.append(x)\n for x in permutations([0,0,0,-1]):\n verts.append(x)\n g = QQ(1618033)/1000000 # Golden ratio approximation\n verts = verts + [i([q12,g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([q12,g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([q12,-g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([q12,-g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([-q12,g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([-q12,g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([-q12,-g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\n verts = verts + [i([-q12,-g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\n return Polyhedron(vertices = verts)","def start_table(self):\n self.col_widths = []\n self.result = \"\"","def get_table(self):\n result_table = [row[:] for row in self.table] # Clone the result table\n\n # Htmlise all columns containing images\n for col_num in self.image_column_nums():\n for row_num in range(1, len(result_table)):\n result_table[row_num][col_num] = self.htmlise(result_table[row_num][col_num])\n\n # Append images\n for ((col,row), image_list) in self.images.items():\n for image in image_list:\n try:\n result_table[row][col] += \"<br>\" + image\n except IndexError:\n pass # Testing must have aborted so discard image\n\n return result_table","def test_collected_columns_as_table_two_col_from_two(self):\n col_double, allow_colspan = True, True # as_type == 'table'\n col_args = ('span', False, {})\n names, multi_field_row = ('first', 'billing_address_1'), True\n row = {name: self.form.fields[name] for name in names}\n col_count = 2\n expected = [self.form.collect_col_data(name, self.form.fields[name], *col_args) for name in names]\n for ea in expected:\n if multi_field_row:\n ea['css_classes'] = ' '.join(['nowrap', ea['css_classes']])\n ea['html_head_attr'] = ' class=\"nowrap\"'\n val = ea.pop('css_classes', '')\n val = ' class=\"%s\"' % val if val else ''\n if not multi_field_row and col_count > 1:\n val = val + ' colspan=\"{}\"'.format(2 * col_count - 1)\n ea['html_col_attr'] = val\n col_settings = (multi_field_row, col_count, col_double, allow_colspan)\n actual = self.form.collect_columns(row, col_settings, *col_args)\n\n self.assertEqual(len(expected), len(actual))\n for expect, got in zip(expected, actual):\n self.assertEqual(len(expect), len(got))\n self.assertListEqual(list(expect.keys()), list(got.keys()))\n self.assertListEqual(list(expect.values()), list(got.values()))\n self.assertEqual(expected, actual)","def fill_table(self, data):\r\n if len(data) > 0:\r\n if isinstance(data, np.ndarray):\r\n data = data.tolist()\r\n data_rows = len(data)\r\n data_columns = len(data[0])\r\n if data_columns > 0:\r\n self.setRowCount(data_rows)\r\n # We hide the imag part of the complex impedance\r\n self.setColumnCount(data_columns - 1)\r\n for r in range(0, data_rows):\r\n # Update real columns\r\n for c, realc in [(0, 0), (1, 1), (3, 4)]:\r\n item = QTableWidgetItem() \r\n item.setText(str(data[r][realc])) \r\n self.setItem(r, c, item)\r\n # Earth resistance has a hidden column which can have an imaginary number\r\n if data[r][3] != 0.0:\r\n # show complex impedance\r\n item = QTableWidgetItem() \r\n item.setText(str(np.complex(data[r][2], data[r][3])))\r\n self.setItem(r, 2, item)\r\n else:\r\n # show real impedance\r\n item = QTableWidgetItem()\r\n item.setText(str(data[r][2])) \r\n self.setItem(r, 2, item)\r\n # Last Column is a QComboBox to select phasing\r\n phasing = QComboBox()\r\n phasing.addItems([\"Normal\",\"120 degree shift\", \"240 degree shift\"])\r\n phasing.setCurrentIndex(np.real(data[r][5]))\r\n phasing.currentIndexChanged.connect(self.phasing_signal(phasing, r, 5))\r\n self.setCellWidget(r, 4, phasing)","def print_table(n):\n \n numbers = list(range(1, n + 1))\n\n #处理第一行\n s = ''\n for i in numbers:\n s = s + '\\t' + str(i)\n print(s)\n\n for i in numbers:\n s = str(i)\n for j in numbers:\n s = s + '\\t' + str(i * j)\n print(s)","def table(self, doc, level, output):\n output('<table border=\"1\" cellpadding=\"2\">\\n')\n for row in doc.getRows()[0]:\n output(\"<tr>\\n\")\n for column in row.getColumns()[0]:\n str = ('<%s colspan=\"%s\" align=\"%s\" valign=\"%s\">'\n % (column.getType(),\n column.getSpan(),\n column.getAlign(),\n column.getValign()))\n output(str)\n for c in column.getChildNodes():\n getattr(self, self.element_types[c.getNodeName()]\n )(c, level, output)\n output(\"</\" + column.getType() + \">\\n\")\n output(\"</tr>\\n\")\n output(\"</table>\\n\")","def print_table(self):\n print(\"%-12s%-12s%-12s%-12s%-12s\" % (\"index\",\"balance\",\"payment\",\"interest\",\"amortization\"))\n print(\"-------------------------------------------------------------\")\n for i in self.table[\"index\"]:\n print(\"%-12i%-12i%-12i%-12i%-12i\" % (self.table[\"index\"][i],self.table[\"balance\"][i]\\\n ,self.table[\"payment\"][i],self.table[\"interest\"][i],\\\n self.table[\"amortization\"][i]))","def create_pairwise_metric_table(\n row_list: Set[Text],\n column_list: Set[Text],\n name_value_map: Dict[Text, float],\n same_match_value\n) -> Text:\n table_template = template.TABLE_TEMPLATE\n\n headers = ['​'] + list(column_list)\n header_string = \"|\".join(headers)\n header_separator = \"|\".join([\":-----:\" for i in range(len(headers))])\n\n table_content = []\n\n for row_name in row_list:\n # row header is in BOLD\n row_values = [template.BOLD.format(content=row_name.strip())]\n for col_name in column_list:\n # same_match_value is used when row_name == column_name\n if row_name == col_name:\n value = same_match_value\n else:\n value = name_value_map[row_name + '-' + col_name]\n\n # if the same_match_value is string, simply append it\n if isinstance(value, str):\n row_values.append(same_match_value)\n else:\n row_values.append(formatting.numeric_formatting(value))\n\n table_content.append(\"|\".join(row_values))\n\n table_content_string = \"\\n\".join(table_content)\n\n return table_template.format(\n header=header_string,\n header_separator=header_separator,\n table_content=table_content_string\n )","def __call__(self, i, j):\n return _table.Table___call__(self, i, j)","def print_table(table, title_list):\n\n # your goes code\n cols = len(title_list)\n\n \n\n table.insert(0,title_list)\n\n for sublist in range(len(table)):\n if cols != len(table[sublist]):\n print('dataset does not match number of cols')\n quit()\n\n max_lenghts = []\n maxi = -1\n for sub_elem in range(cols): \n maxi = -1 \n for sublist in range(len(table)):\n if len(table[sublist][sub_elem]) > maxi:\n maxi = len(table[sublist][sub_elem])\n max_lenghts.append(maxi)\n \n\n \n\n sub_elem = 0\n \n for sublist in range(len(table)):\n if sublist == 0:\n while sub_elem < len(table[0]):\n \n if sub_elem == len(table[0])- 1:\n print('\\033[1;37;41m| {:^25} |'.format(table[sublist][sub_elem]), end =\"\")\n else:\n print('\\033[1;37;41m| {:^25} '.format(table[sublist][sub_elem]), end =\"\")\n sub_elem += 1\n \n print('\\033[0;32;48m\\n') \n sub_elem = 0 \n else:\n while sub_elem < len(table[0]):\n \n if sub_elem == len(table[0])- 1:\n print('\\033[0;37;44m| {:^25} |'.format(table[sublist][sub_elem]), end =\"\")\n else:\n print('\\033[0;37;44m| {:^25} '.format(table[sublist][sub_elem]), end =\"\")\n sub_elem += 1\n \n print('\\033[0;32;48m\\n') \n sub_elem = 0 \n print('\\033[0;37;48m\\n')\n table.pop(0)","def print_grid2(y, z):\n for i in range(y):\n prow(z, y)\n for i in range(z):\n pcolumn(z*2, y)\n prow(z, y)","def matrix_table(matrix):\r\n result =\"<table id='matrix_result'>\"\r\n for line in range(len(matrix)):\r\n result += \"<tr>\"\r\n for column in range(len(matrix)):\r\n result += \"<td>\" + str(matrix[line][column]) + \"</td>\"\r\n result += \"</tr>\"\r\n result += \"</table>\"\r\n return result","def select(self, labels):\n indexs = []\n \n for i in range(len(labels)):\n indexs.append(self.column_labels.index(labels[i]))\n new_rows = []\n for x in self.rows:\n new_row = []\n for index in indexs:\n new_row.append(x[index])\n new_rows.append(new_row)\n\n\n\n new_Table = T88ble(new_rows, labels)\n\n return new_Table","def table(self, L, R, n):\n s = \"\"\n for x in np.linspace(L, R, n):\n y = self(x)\n s += \"%12g %12g\\n\" % (x, y)\n return s","def cell_edges(self):","def _gen_table_style_lines(self):\n yield '.heatmap {border: none; border-collapse: collapse; border-spacing: 0}'\n yield '.heatmap td {padding: 0; margin: 0; font-family: monospace;}'","def transpose(self) -> None:\n ...","def rosterRowData(self):","def get_colspecs(self):\n width = 80\n\n total_width = 0.0\n # first see if we get too wide.\n for node in self._col_specs:\n colwidth = float(node['colwidth']+1) / width\n total_width += colwidth\n self._col_width = []\n self._rowspan = []\n # donot make it full linewidth\n factor = 0.93\n if total_width > 1.0:\n factor /= total_width\n bar = self.get_vertical_bar()\n latex_table_spec = \"\"\n for node in self._col_specs:\n colwidth = factor * float(node['colwidth']+1) / width\n self._col_width.append(colwidth+0.005)\n self._rowspan.append(0)\n latex_table_spec += \"%sp{%.2f\\\\locallinewidth}\" % (bar,colwidth+0.005)\n return latex_table_spec+bar","def table(self, L, R, n):\n s =''\n import numpy as np\n for x in np.linspace(L, R, n):\n y = self(x)\n s += '%12g %12g\\n' % (x, y)\n return s","def make_space_table(space):\n columns = dragon[\"%s\" % space].reset_index().columns\n return DataTable(\n id=\"%s_table\" % space,\n columns=[{\"name\": i, \"id\": \"%s\" % i} for i in columns],\n data=get_table_data(space, []),\n style_header={\n \"transform\": \"translate(0px, 0px) rotate(-0.0deg)\",\n \"max-width\": \"20px\",\n \"backgroundColor\": \"transparent\",\n },\n )","def table(self, L, R, n):\n s = \"\"\n import numpy as np\n for x in np.linspace(L, R, n):\n y = self(x)\n s += \"%12g %12g\\n\" %(x,y)\n return s","def process_ipet_table(table, repres, add_ind=False, swap=False):\n # split rowspan cells from the tables body to enable js datatable\n table_rows = [e for e in table.find(\".//tbody\").iter() if e.tag == \"tr\" or e.tag == \"th\"]\n groupcount = 1\n oldtext = \"\"\n for row in table_rows:\n cellcount = 0\n for cell in row.iter():\n if add_ind and cellcount == 1 and cell.tag == \"th\" and cell.text != oldtext:\n cell.text = \"{:0>2d}. {}\".format(groupcount, cell.text)\n oldtext = cell.text\n groupcount = groupcount + 1\n rowspan = cell.get(\"rowspan\")\n if rowspan is not None:\n del cell.attrib[\"rowspan\"]\n nextrow = row\n for i in range(int(rowspan) - 1):\n nextrow = nextrow.getnext()\n newcell = html.fromstring(html.tostring(cell))\n nextrow.insert(cellcount - 1, newcell)\n cellcount = cellcount + 1\n\n # render to string and make the dataTable fit the width\n htmltable = html.tostring(table).decode(\"utf-8\")\n # replace ids and so on\n htmltable = replace_in_str(htmltable, repres)\n htmltable = htmltable.replace(\"nan\", NONE_DISPLAY)\n return htmltable","def displayPokedex(pokedex):\n for col1,col2 in zip(pokedex[::2],pokedex[1::2]):\n\t print(col1+\",\",col2+\",\")","def print_table(table):\n rest = table[1:]\n fmt = \"%-28s %-9s %-16s %s\"\n for row in rest:\n print(fmt % tuple(row))","def nktable(nmax, kmax, sort = \"value\"):\n number_of_columns = nmax\n firstline = r\"\\begin{tabular}{\"\n secondline = r\"&\\multicolumn{\"+str(nmax)+ r\"}{|c}{Scheibenzahl $n$}\\\\\"\n i = 0\n while i < number_of_columns:\n i += 1\n if i == 1:\n firstline += \"c|\"\n firstline += \"c\"\n firstline += \"}\"\n hline = r\"\\hline\"\n lines = [firstline]\n lines.append(secondline)\n line = r\"$k\\downarrow$\"\n for n in range(1,nmax+1):\n line += \"&\"+str(n)\n\n for k in range(3,kmax+1):\n line += r\"\\\\\"\n lines.append(line)\n if k == 3:\n lines.append(hline)\n line = str(k)\n for n in range(1,nmax+1):\n if sort == \"value\":\n line += \"&\"+str(M(n,k))\n elif sort == \"increment\":\n line += \"&\"+str(2**t_(n,k))\n elif sort == \"possibilities\":\n line += \"&\"+str(upsilon(n,k))\n elif sort == \"totalpossibilities\":\n line += \"&\"+str(totalpossibilities(n,k))\n elif sort == \"adjustedpossibilities\":\n line += \"&\"+str(adjustedUpsilon(n,k))\n elif sort == \"bfadjustedpossibilities\":\n line += \"&\"+str(bruteforceadjustedUpsilon(n,k))\n\n lines.append(line)\n lines.append(r\"\\end{tabular}\")\n return lines","def cols(self, col):\n self.col += col","def _modify_columns(self, cols, X, y=None):","def T(self):\n # TODO - your code here\n transpose = []\n for col in range(self.w):\n new_row = []\n for row in range(self.h):\n new_row.append(self.g[row][col])\n transpose.append(new_row)\n return Matrix(transpose)\n # TODO - your code here","def get_table_df(df):\n # --------------------------------------------------------------------------\n # Start\n # --------------------------------------------------------------------------\n indf = df.copy()\n tabzeros = {i:'0' for i in ['-','*']}\n pctzeros = {i:'0' for i in ['*','**']}\n combzeros = {i:'0' for i in ['-','*','**']}\n # --------------------------------------------------------------------------\n # Drop the empty columns and rows\n # --------------------------------------------------------------------------\n # indf.dropna(axis=0,how='all',inplace=True)\n indf.dropna(axis=1,how='all',inplace=True)\n indf.fillna('',inplace=True)\n # --------------------------------------------------------------------------\n # Grab the first column\n # --------------------------------------------------------------------------\n cols = indf.columns.to_list()\n indxcol = indf[cols[0]].to_list()\n # --------------------------------------------------------------------------\n # Figure out where the pieces of the table are\n # --------------------------------------------------------------------------\n title = [0,1]\n banner = []\n table = []\n inheader = True\n inbanner = False\n intable = False\n # --------------------------------------------------------------------------\n # Go through and figure out where everything starts and stops\n # --------------------------------------------------------------------------\n for i,val in enumerate(indxcol):\n # ----------------------------------------------------------------------\n # Find the start of the information\n # ----------------------------------------------------------------------\n if inheader:\n bskip = True\n for cell in indf.iloc[i,:].values.tolist():\n if cell != '':\n bskip = False\n break\n if bskip:\n continue\n if val != '' or val is not np.nan:\n instart = False\n inheader = True\n # ----------------------------------------------------------------------\n # In the header\n # ----------------------------------------------------------------------\n if inheader:\n if val == '' or val is np.nan:\n inbanner = True\n inheader = False\n # ----------------------------------------------------------------------\n # In the banner\n # ----------------------------------------------------------------------\n if inbanner:\n bskip = True\n # ------------------------------------------------------------------\n # In the case that we have an entire row that is empty, skip.\n # This should handle empty rows after the header\n # ------------------------------------------------------------------\n for cell in indf.iloc[i,:].values.tolist():\n if cell != '':\n bskip = False\n break\n if bskip:\n continue\n if val != '':\n inbanner = False\n intable = True\n else:\n banner.append(i)\n # ----------------------------------------------------------------------\n # In the table\n # ----------------------------------------------------------------------\n if intable:\n table.append(i)\n # ------------------------------------------------------------------\n # Exit if we've reached the bottom\n # ------------------------------------------------------------------\n if 'Statistics' in str(val):\n break\n if 'Table ' in str(val):\n table = table[:-2]\n # --------------------------------------------------------------------------\n # Break the dataframe apart\n # --------------------------------------------------------------------------\n bandf = indf.iloc[banner[0]:banner[-1]+1].copy()\n tabdf = indf.iloc[table[0]:table[-2]].copy()\n # --------------------------------------------------------------------------\n # Create the column index setup\n # --------------------------------------------------------------------------\n banmat = bandf.iloc[:,1:].values.tolist()\n for row in banmat:\n for i in range(len(row)):\n if row[i] == '':\n row[i] = row[i-1]\n # --------------------------------------------------------------------------\n # Set up the tuples for the columns\n # --------------------------------------------------------------------------\n colnames = []\n for i in range(len(banmat[0])):\n colnames.append(tuple([row[i] for row in banmat]))\n multi_col = pd.MultiIndex.from_tuples(colnames)\n # --------------------------------------------------------------------------\n # Create the final using the information above\n # --------------------------------------------------------------------------\n tabindx = tabdf[cols[0]].to_list()\n for i,val in enumerate(tabindx):\n if val == '':\n tabindx[i] = currval\n else:\n currval = val\n # --------------------------------------------------------------------------\n # Set the index\n # --------------------------------------------------------------------------\n # setindx = pd.MultiIndex.from_tuples(tabindx)\n tabdf.index = [str(i) for i in tabindx]\n del tabdf[cols[0]]\n # --------------------------------------------------------------------------\n # Set the columns\n # --------------------------------------------------------------------------\n tabdf.columns = multi_col\n # --------------------------------------------------------------------------\n # Go through the rows and add a typing tag\n # --------------------------------------------------------------------------\n typecol = []\n for idx, row in tabdf.iterrows():\n # ----------------------------------------------------------------------\n # Default to a count row\n # ----------------------------------------------------------------------\n thistype = 'count'\n # ----------------------------------------------------------------------\n # If the entire row is empty, it's a stat row\n # ----------------------------------------------------------------------\n bstat = True\n for val in row:\n if val != '':\n bstat = False\n break\n if bstat:\n thistype = 'stat'\n # ----------------------------------------------------------------------\n # Go through the values and guess at the type\n # ----------------------------------------------------------------------\n for val in row:\n # ------------------------------------------------------------------\n # Skip if empty since it doesn't tell us anything\n # ------------------------------------------------------------------\n if val == '':\n continue\n # ------------------------------------------------------------------\n # If it has any of the following keys, skip\n # ------------------------------------------------------------------\n if val in tabzeros:\n continue\n # ------------------------------------------------------------------\n # If it is one of the zeros for pcts, mark\n # ------------------------------------------------------------------\n if val in pctzeros:\n thistype = 'pct'\n break\n # ------------------------------------------------------------------\n # If we are able to cast as float and the value is less than 1, pct\n # ------------------------------------------------------------------\n try:\n floatval = float(val)\n if floatval < 1:\n thistype = 'pct'\n break\n # ------------------------------------------------------------------\n # If it breaks, we are in a stat row\n # ------------------------------------------------------------------\n except:\n thistype = 'stat'\n break\n typecol.append(thistype)\n tabdf['type'] = typecol\n # --------------------------------------------------------------------------\n # Split the table into multiple tables (count, pct, stat)\n # --------------------------------------------------------------------------\n tmpmask = tabdf[('type')] == 'count'\n countdf = tabdf.loc[tmpmask].copy()\n tmpmask = tabdf[('type')] == 'stat'\n statdf = tabdf.loc[tmpmask].copy()\n tmpmask = tabdf[('type')] == 'pct'\n pctdf = tabdf.loc[tmpmask].copy()\n # --------------------------------------------------------------------------\n # Create the base, unweighted base, and effective base dataframes\n # --------------------------------------------------------------------------\n # --------------------------------------------------------------------------\n # Base df\n # --------------------------------------------------------------------------\n basedf = tabdf.copy()\n baserow = None\n for idx,row in basedf.iterrows():\n if (idx.lower()[:4] == 'base' and 'unweighted' not in idx.lower() and 'effective' not in idx.lower()) and row[('type')].to_list()[0] == 'count':\n baserow = row\n for col,val in row.items():\n if baserow is None:\n usebase = np.nan\n else:\n usebase = baserow[col]\n basedf.loc[idx,col] = usebase\n basedf = basedf[~basedf.index.duplicated(keep='first')]\n # --------------------------------------------------------------------------\n # Unweighted df\n # --------------------------------------------------------------------------\n unwbdf = tabdf.copy()\n baserow = None\n for idx,row in unwbdf.iterrows():\n if ('unweighted' in idx.lower()) and row[('type')].to_list()[0] == 'count':\n baserow = row\n for col,val in row.items():\n if baserow is None:\n usebase = np.nan\n else:\n usebase = baserow[col]\n unwbdf.loc[idx,col] = usebase\n unwbdf = unwbdf[~unwbdf.index.duplicated(keep='first')]\n # --------------------------------------------------------------------------\n # Effective df\n # --------------------------------------------------------------------------\n effbdf = tabdf.copy()\n baserow = None\n for idx,row in effbdf.iterrows():\n if ('effective' in idx.lower()) and row[('type')].to_list()[0] == 'count':\n baserow = row\n for col,val in row.items():\n if baserow is None:\n usebase = np.nan\n else:\n usebase = baserow[col]\n effbdf.loc[idx,col] = usebase\n effbdf = effbdf[~effbdf.index.duplicated(keep='first')]\n # --------------------------------------------------------------------------\n # Clean up the statdf in case there are bases\n # --------------------------------------------------------------------------\n rmlist = []\n for idx in statdf.index:\n if str(idx).lower()[:4] == 'base':\n rmlist.append(idx)\n if 'unweighted' in str(idx).lower():\n rmlist.append(idx)\n if 'effective' in str(idx).lower():\n rmlist.append(idx)\n statdf.drop(rmlist,inplace=True)\n # --------------------------------------------------------------------------\n # Drop the type column\n # --------------------------------------------------------------------------\n del countdf[('type')]\n del statdf[('type')]\n del pctdf[('type')]\n del basedf[('type')]\n del unwbdf[('type')]\n del effbdf[('type')]\n # --------------------------------------------------------------------------\n # Set the column types appropriately for the count and pct dataframes\n # --------------------------------------------------------------------------\n for col in countdf.columns:\n countdf.loc[:,col] = countdf[col].copy().replace(tabzeros).astype(float)\n for col in pctdf.columns:\n pctdf.loc[:,col] = pctdf[col].copy().replace(combzeros).astype(float)\n # --------------------------------------------------------------------------\n # If any of the dataframes are empty, replace with None\n # --------------------------------------------------------------------------\n if countdf.empty:\n countdf = None\n if statdf.empty:\n statdf = None\n if pctdf.empty:\n pctdf = None\n # --------------------------------------------------------------------------\n # If there is a statdf that is not none, drop the last row of the multiindex\n # --------------------------------------------------------------------------\n if statdf is not None:\n if countdf is not None:\n countdf.columns = countdf.columns.droplevel(-1)\n if pctdf is not None:\n pctdf.columns = pctdf.columns.droplevel(-1)\n if basedf is not None:\n basedf.columns = basedf.columns.droplevel(-1)\n if unwbdf is not None:\n unwbdf.columns = unwbdf.columns.droplevel(-1)\n if effbdf is not None:\n effbdf.columns = effbdf.columns.droplevel(-1)\n # --------------------------------------------------------------------------\n # Finish\n # --------------------------------------------------------------------------\n out = {}\n out['count'] = countdf\n out['pct'] = pctdf\n out['stat'] = statdf\n out['base'] = basedf\n out['unwb'] = unwbdf\n out['effb'] = effbdf\n return out","def _rotate_cw(self, table):\n return [ [ table[1][0], table[0][0] ],\n [table[1][1], table[0][1] ] ]","def transpose(self):\n pass","def make_table(m, n):\n return np.array([[0] * n for _ in range(m)], dtype=float)","def visit_table(self, sytable):\n def index(sytable):\n try:\n return sytable.get_column(self.input_index)\n except:\n return np.arange(sytable.number_of_rows())\n\n def slices_using_group_array(group_array):\n \"\"\"Return the slices to split by.\n A group array is made of strictly increasing group identifiers.\n\n >>> slices_using_group_array(np.array([0, 0, 0, 1, 1, 2, 3, 3, 3]))\n [(0, 3), (3, 5), (5, 6), (6, 9)]\n \"\"\"\n unique_elements = np.unique(group_array)\n slices = []\n for unique_element in unique_elements:\n indexes = np.flatnonzero(group_array == unique_element)\n low, high = (indexes[0], indexes[-1] + 1)\n slices.append((unique_element, slice(low, high)))\n return slices\n\n def indices_using_group_array(group_array):\n \"\"\"\n Return list of index lists, ordered by first occurance of value.\n \"\"\"\n unique_elements = np.unique(group_array)\n indices = []\n for unique_element in unique_elements:\n indices.append((unique_element,\n np.flatnonzero(group_array == unique_element)))\n return indices\n\n columns = sytable.columns()\n # Perform the split and append the new tables to output.\n slice_indices = indices_using_group_array(index(sytable))\n column_attrs = {}\n\n for unique_element, slice_index in slice_indices:\n # Sets of all columns except for the INDEX columns.\n result = type(sytable)(sytable.container_type)\n self.output_list.append((unique_element, result))\n\n for column in columns:\n array = sytable.get_column(column)[slice_index]\n if self.remove_fill and len(array):\n kind = array.dtype.kind\n if kind in ['S', 'U']:\n if np.all(array == ''):\n continue\n else:\n if not len(array) or np.isnan(np.min(array)):\n continue\n\n result.set_column(column, array)\n if column in column_attrs:\n attrs = column_attrs[column]\n else:\n attrs = dict(\n sytable.get_column_attributes(column).get())\n column_attrs[column] = attrs\n result.get_column_attributes(column).set(attrs)","def markdown_row(self, ncol, which):\n if which == 'C':\n dat = self.C\n elif which == 'c':\n dat = self.d1\n elif which == 'f':\n dat = self.d2\n line = '|%d|' % (self.N*2)\n for i in range(1,self.N+1):\n line = line + ' $%s$ |' % (dat[i])\n for i in range(1,ncol - self.N+1):\n line = line + ' |'\n line = line + '\\n'\n return line","def construct_table(self):\n table_str = self.header_row\n row_lbls, col_lbls = self.get_idxvals()\n for r,rlbl in enumerate(row_lbls):\n row_data = [self.data[rlbl,clbl] for clbl in col_lbls]\n table_str += self.construct_row(r, row_data)\n \n return table_str","def __init__(self, grid, column_id, column_span=1):\n super(GraphVisualizerConnectedcolumn, self).__init__(\n grid, column_id, column_span\n )\n\n for i in range(column_span):\n self._grid.setColumnStretch(self._column_id + i, 1)","def dctColUels(pdct, j):\n return _dctmcc.dctColUels(pdct, j)","def _generate_tabular(lookup_table, interpolation='linear', points_unit=u.pix, **kwargs):\n if not isinstance(lookup_table, u.Quantity):\n raise TypeError(\"lookup_table must be a Quantity.\") # pragma: no cover\n\n ndim = lookup_table.ndim\n TabularND = tabular_model(ndim, name=f\"Tabular{ndim}D\")\n\n # The integer location is at the centre of the pixel.\n points = [(np.arange(size) - 0) * points_unit for size in lookup_table.shape]\n if len(points) == 1:\n points = points[0]\n\n kwargs = {\n 'bounds_error': False,\n 'fill_value': np.nan,\n 'method': interpolation,\n **kwargs\n }\n\n t = TabularND(points, lookup_table, **kwargs)\n\n # TODO: Remove this when there is a new gWCS release\n # Work around https://github.com/spacetelescope/gwcs/pull/331\n t.bounding_box = None\n\n return t","def test_collected_columns_as_table_one_col_from_one(self):\n col_double, allow_colspan = True, True # as_type == 'table'\n col_args = ('span', False, {})\n name, multi_field_row = 'first', False\n names = [name]\n row = {name: self.form.fields[name]}\n col_count = 1\n expected = [self.form.collect_col_data(name, self.form.fields[name], *col_args) for name in names]\n for ea in expected:\n if multi_field_row:\n ea['css_classes'] = ' '.join(['nowrap', ea['css_classes']])\n ea['html_head_attr'] = ' class=\"nowrap\"'\n val = ea.pop('css_classes', '')\n val = ' class=\"%s\"' % val if val else ''\n if not multi_field_row and col_count > 1:\n val = val + ' colspan=\"{}\"'.format(2 * col_count - 1)\n ea['html_col_attr'] = val\n col_settings = (multi_field_row, col_count, col_double, allow_colspan)\n actual = self.form.collect_columns(row, col_settings, *col_args)\n\n self.assertEqual(len(expected), len(actual))\n for expect, got in zip(expected, actual):\n self.assertEqual(len(expect), len(got))\n self.assertListEqual(list(expect.keys()), list(got.keys()))\n self.assertListEqual(list(expect.values()), list(got.values()))\n self.assertEqual(expected, actual)","def slice(self, i, j, n, m):\n return Table(rows=[list.__getitem__(self, i)[j:j+m] for i in range(i, i+n)])","def show_from_database(self, table_model):\n arr = [4, 1]\n # TODO","def colWithTile(self, pos):\n\n\n return self.colWithBox(pos, [2.0,2.0,2.0])","def make_table(m, n):\n return [[0] * n for _ in range(m)]","def for_reverse_triange():\r\n\r\n for row in range(6,0,-1):\r\n print(' '*(6-row), '* '*row)","def tiles(rxs):\n\n lo = math.inf\n hi = -math.inf\n\n for rx in rxs:\n lo = min(lo, rx[\"has\"][0])\n hi = max(hi, rx[\"has\"][len(rx[\"has\"]) - 1])\n\n for rx in rxs:\n t, u = rx['has'], []\n\n def of(x, most):\n return int(max(1, min(most, x)))\n\n def at(x):\n return t[of(len(t)*x//1, len(t))]\n\n def pos(x):\n return math.floor(of(40*(x-lo)/(hi-lo+1E-32)//1, 40))\n\n for _ in range(globals.the[\"width\"] + 1):\n u.append(\" \")\n\n for i in range(pos(at(.1)), pos(at(.3)) + 1):\n u[i] = \"-\"\n\n for i in range(pos(at(.7)), pos(at(.9)) + 1):\n u[i] = \"-\"\n\n u[globals.the[\"width\"] // 2] = \"|\"\n u[pos(at(.5))] = \"*\"\n\n rx[\"show\"] = \"\".join(u) + \" {\" + globals.the[\"Fmt\"].format(at(.1))\n\n for x in [at(.3), at(.5), at(.7), at(.9)]:\n rx[\"show\"] += \", \" + globals.the[\"Fmt\"].format(x)\n\n rx[\"show\"] += \" }\"\n\n return rxs","def __tbl_synthese(table_1_restant, table_terme_supl, nbr):\n table_synthese = [0 for i in range(len(table_1_restant))]\n msq1 = (1 << nbr)- 1\n cpt = 0\n pteur = 1\n for ter1, msq in table_terme_supl:\n for index, ter in enumerate(table_1_restant):\n if (ter1 & (msq ^ msq1)) == (ter & (msq ^ msq1)):\n table_synthese[index] |= pteur\n pteur <<= 1\n cpt += 1\n return table_synthese, cpt","def print_column():\n print('+----+----+----+----+')","def print_column():\n print('+----+----+')","def initTableView(self):\r\n # productive\r\n profprint()\r\n if self.table == None:\r\n # self.keys = (\"#\")\r\n # self.keys = (\"#\",\"Round\" ,\"Reliability\")\r\n self.keys = (\"#\")\r\n self.labelStats = {}\r\n self.labelStats['Labels'] = []\r\n self.items = []\r\n if self.model == None:\r\n self.model = qt.QStandardItemModel()\r\n self.model.setColumnCount(5)\r\n self.model.setHeaderData(0, 1, \"\")\r\n self.model.setHeaderData(1, 1, \"#\")\r\n # self.model.setHeaderData(2,1,\"R.\")\r\n # self.model.setHeaderData(3,1,\"Reliability\")\r\n self.model.setHeaderData(2, 1, \"Display\")\r\n self.model.setHeaderData(3, 1, \"Reformat\")\r\n self.model.setHeaderData(4, 1, \"Comments\")\r\n # self.model.setStrechLastSection(True)\r\n if self.view == None:\r\n self.view = qt.QTableView()\r\n self.view.setMinimumHeight(300)\r\n self.view.sortingEnabled = True\r\n self.view.verticalHeader().visible = False\r\n self.view.horizontalHeader().setStretchLastSection(True)\r\n\r\n # col = 1\r\n # for k in self.keys:\r\n # # self.view.setColumnWidth(col,15*len(k))\r\n # # self.model.setHeaderData(col,1,k)\r\n # col += 1\r\n self.view.setModel(self.model)\r\n self.view.setColumnWidth(0, 18)\r\n self.view.setColumnWidth(1, 58)\r\n self.view.setColumnWidth(2, 58)\r\n self.table = 1\r\n self.row = 0\r\n self.col = 0\r\n slicer.modules.NeedleFinderWidget.analysisGroupBoxLayout.addRow(self.view)","def cols(self):\n\n return []","def column_pack(plateau, num_col, debut, sens):\n if check_room(plateau, num_col, debut) == False or (sens != 1 and sens != 0): # si plateau n est pas valide ou sens != 1 et 0\n return \"Erreur !\"\n if sens == 1:\n i = debut # tasser a partie de i\n while i < 3:\n set_value(plateau, i, num_col, get_value(plateau, i+1, num_col)) # remplacer la valeur avec la valeur suivant\n i += 1\n set_value(plateau, i, num_col, 0)\n else:\n i = debut\n while i > 0:\n set_value(plateau, i, num_col, get_value(plateau, i-1, num_col)) # remplacer la valeur avec la valeur precedente\n i -= 1\n set_value(plateau, i, num_col, 0)","def get_formatted_table(images):\n header = ['CEE (Windows)']\n table = columned_table(header, [images])\n return table","def _permutate(self, table, block):\n return list(map(lambda x: block[x], table))","def print_table(table_2D, title_list):\n \n max_length = [] # max length of item for each column\n\n # BELOW VAR NEEDS TO BE FIXED, GOT RID OFF\n # without this correction table horizontal lines displays unevenly\n length_correction = 2 \n\n # count max length of all elements in a table, so we can print all details in neat columns\n for row in table_2D:\n column = 0\n\n for item in row:\n item = str(item)\n\n try:\n if len(item) > max_length[column]:\n max_length[column] = len(item)\n column += 1\n # expand table if needed\n except IndexError:\n max_length.append(0)\n if len(item) > max_length[column]:\n max_length[column] = len(item)\n column += 1\n\n title_index = \"No\"\n\n # print titles, while keeping columns straight\n titles = side_sign + \" \" + title_index + separator_sign\n for i in range(len(title_list)):\n # count length of all titles, to check if they are longer than entries\n if len(title_list[i]) > max_length[i]:\n max_length[i] = len(title_list[i])\n\n titles += title_list[i] + fill(str(title_list[i]), max_length[i]) + separator_sign\n\n print(\"\\n\\t/\" + fill(\"\", len(titles.strip())-length_correction, sourrounding_sign) + \"\\\\\") # print top line\n print(\"\\t\" + titles)\n print(\"\\t\" + side_sign + fill(\"\", len(titles.strip())-length_correction, sourrounding_sign) + side_sign) # print line below titles\n\n table_content = \"\"\n # print all game details, while keeping columns straight\n for row in range(len(table_2D)):\n table_content += \"\\t\" + side_sign + \" \" + str(row+1) + fill(str(row+1), max(len(str(row+1)), len(title_index))) + separator_sign\n for item in range(len(table_2D[row])):\n table_content += str(table_2D[row][item]) + fill(str(table_2D[row][item]), max_length[item]) + separator_sign\n table_content += \"\\n\"\n\n print(table_content, end=\"\")\n print(\"\\t\\\\\" + fill(\"\", len(titles.strip())-length_correction, sourrounding_sign) + \"/\")","def mostrar_tablero(mtx, n):\n # Cabecera de Columnas\n fila = \"/ |\"\n for i in range(n):\n fila = fila + \" \" + chr(65+i)\n print fila\n print \"-\"*(2*n+3)\n # Cabecera de Filas\n for i in range(n):\n fila = str(i+1)\n if i < 9 : fila += \" |\"\n else:\n fila+=\"|\"\n for e in range(n):\n fila = fila+\" \"+mtx[i][e]\n print fila\n fila = \"\"\n # Nueva linea\n print \"\"","def col_diag(self):\n rows = self._row_type_2d()\n for i, m in iter_items(self.col_totals):\n rows[i][i] = m\n return self.__class__(rows=rows)","def inhomoCoeffs(Bulk_Operators, Bdy_Operators, Bulk_second, s=1):\n\t\tRow = []\n\t\tfor Bulk_Op in Bulk_Operators:\n\t\t\t\ttable_call = table1.table[0, 0].subs({\"Delta\":Bulk_Op, \"Delta_12\":delta_12, \"Xi\":1.00})\n\t\t\t\tRow.append(table_call)\n\t\tfor index in range(len(Bulk_second)):\n\t\t\t\tRow.append(0*table1.table[0,0])\n\t\tfor Bdy_Op in Bdy_Operators:\n\t\t\tif Bdy_Op == 2.0:\n\t\t\t\ttable_call = (N-1)*table1.table[1, 0].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\telse:\n\t\t\t\ttable_call = table1.table[1, 0].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\tRow.append(table_call)\n\t\tif s==1:\n\t\t\tXi = symbols('Xi')\n\t\t\tlast_expr = Xi**((delta_1 + delta_2)/2)\n\t\t\tlast_elem = last_expr.subs({\"Xi\":1.00}).evalf()\n\t\t\tRow.append(last_elem)\n\t\tRow2 = []\n\t\tfor index in range(len(Bulk_Operators)):\n\t\t\t\tRow2.append(0*table1.table[0,0])\n\t\tfor Bulk_Op in Bulk_second:\n\t\t\t\ttable_call = table1.table[0, 0].subs({\"Delta\":Bulk_Op, \"Delta_12\":delta_12, \"Xi\":1.00})\n\t\t\t\tRow2.append(table_call)\n\t\tfor Bdy_Op in Bdy_Operators:\n\t\t\tif Bdy_Op == 2.0:\n\t\t\t\ttable_call = -1*table1.table[1,0].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\telse:\n\t\t\t\ttable_call = table1.table[1,0].subs({\"Delta\":Bdy_Op, \"Xi\":1.00})\n\t\t\tRow2.append(table_call)\n\t\tif s==1:\n\t\t\tXi = symbols('Xi')\n\t\t\tlast_expr = Xi**((delta_1 + delta_2)/2)\n\t\t\tlast_elem = last_expr.subs({\"Xi\":1.00}).evalf()\n\t\t\tRow2.append(last_elem)\n\t\t\t\n\t\treturn np.array(Row), np.array(Row2)","def unstructured_grid(self, X, Y, Z):\r\n uX = []\r\n uY = []\r\n uZ = []\r\n l = self.size[0] * self.size[1]\r\n self.Grid = vtk.vtkUnstructuredGrid()\r\n for k in range(self.size[2]):\r\n n = 0\r\n for j in range(self.size[1]):\r\n for i in range(self.size[0]):\r\n # SW-B\r\n swb = 8 * k * l + 4 * l + 2 * self.size[0] * (j + 1) + 2 * n\r\n uX.append(X[swb])\r\n uY.append(Y[swb])\r\n uZ.append(Z[swb])\r\n # SE-B\r\n seb = 8 * k * l + 4 * l + 2 * self.size[0] * (j + 1) + 2 * n + 1\r\n uX.append(X[seb])\r\n uY.append(Y[seb])\r\n uZ.append(Z[seb])\r\n # NE-B\r\n neb = 8 * k * l + 4 * l + 2 * self.size[0] * j + 2 * n + 1\r\n uX.append(X[neb])\r\n uY.append(Y[neb])\r\n uZ.append(Z[neb])\r\n # NW-B\r\n nwb = 8 * k * l + 4 * l + 2 * self.size[0] * j + 2 * n\r\n uX.append(X[nwb])\r\n uY.append(Y[nwb])\r\n uZ.append(Z[nwb])\r\n # SW-T\r\n swt = 8 * k * l + 2 * self.size[0] * (j + 1) + 2 * n\r\n uX.append(X[swt])\r\n uY.append(Y[swt])\r\n uZ.append(Z[swt])\r\n # SE-T\r\n sett = 8 * k * l + 2 * self.size[0] * (j + 1) + 2 * n + 1\r\n uX.append(X[sett])\r\n uY.append(Y[sett])\r\n uZ.append(Z[sett])\r\n # NE-T\r\n net = 8 * k * l + 2 * self.size[0] * j + 2 * n + 1\r\n uX.append(X[net])\r\n uY.append(Y[net])\r\n uZ.append(Z[net])\r\n # NW-T\r\n nwt = 8 * k * l + 2 * self.size[0] * j + 2 * n\r\n uX.append(X[nwt])\r\n uY.append(Y[nwt])\r\n uZ.append(Z[nwt])\r\n\r\n n += 1\r\n\r\n # Set points\r\n points = vtk.vtkPoints()\r\n points.SetNumberOfPoints(2 * self.size[0] * 2 * self.size[1] * 2 * self.size[2])\r\n for i in range(len(uX)):\r\n points.SetPoint(i, [uX[i], uY[i], uZ[i]])\r\n self.Grid.SetPoints(points)\r\n\r\n # Set cells\r\n cells = vtk.vtkCellArray()\r\n cell = vtk.vtkHexahedron()\r\n for i in range(len(uX)):\r\n if i > 0 and i % 8 == 0:\r\n cells.InsertNextCell(cell)\r\n cell.GetPointIds().SetId(i % 8, i)\r\n cells.InsertNextCell(cell)\r\n\r\n self.Grid.SetCells(cell.GetCellType(), cells)","def mono_table():\n return Table(\n {\n \"obs_id\": [1, 1, 1, 1, 1, 2],\n \"event_id\": [1, 1, 1, 2, 2, 1],\n \"tel_id\": [1, 2, 3, 5, 7, 1],\n \"hillas_intensity\": [1, 2, 0, 1, 5, 9],\n \"hillas_width\": [0.1, 0.2, 0.1, 0.1, 0.2, 0.1] * u.deg,\n \"hillas_length\": 3 * ([0.1, 0.2, 0.1, 0.1, 0.2, 0.1] * u.deg),\n \"dummy_tel_energy\": [1, 10, 4, 0.5, 0.7, 1] * u.TeV,\n \"dummy_tel_is_valid\": [\n True,\n True,\n True,\n True,\n False,\n False,\n ],\n \"classifier_tel_prediction\": [1, 0, 0.5, 0, 0.6, 1],\n \"classifier_tel_is_valid\": [\n True,\n True,\n False,\n True,\n True,\n True,\n ],\n \"disp_tel_alt\": [58.5, 58, 62.5, 72, 74.5, 81] * u.deg,\n \"disp_tel_az\": [12.5, 15, 13, 21, 20, 14.5] * u.deg,\n \"disp_tel_is_valid\": [\n True,\n False,\n True,\n True,\n True,\n True,\n ],\n }\n )","def lap_mat(self):","def initTableView(self):\n #productive\n profprint()\n if self.table==None:\n # self.keys = (\"#\")\n # self.keys = (\"#\",\"Round\" ,\"Reliability\")\n self.keys = (\"#\")\n self.labelStats = {}\n self.labelStats['Labels'] = []\n self.items = []\n if self.model==None:\n self.model = qt.QStandardItemModel()\n self.model.setColumnCount(5)\n self.model.setHeaderData(0,1,\"\")\n self.model.setHeaderData(1,1,\"#\")\n # self.model.setHeaderData(2,1,\"R.\")\n # self.model.setHeaderData(3,1,\"Reliability\")\n self.model.setHeaderData(2,1,\"Display\")\n self.model.setHeaderData(3,1,\"Reformat\")\n self.model.setHeaderData(4,1,\"Comments\")\n # self.model.setStrechLastSection(True)\n if self.view == None:\n self.view = qt.QTableView()\n self.view.setMinimumHeight(300)\n self.view.sortingEnabled = True\n self.view.verticalHeader().visible = False\n self.view.horizontalHeader().setStretchLastSection(True)\n\n # col = 1\n # for k in self.keys:\n # # self.view.setColumnWidth(col,15*len(k))\n # # self.model.setHeaderData(col,1,k)\n # col += 1 \n self.view.setModel(self.model)\n self.view.setColumnWidth(0,18)\n self.view.setColumnWidth(1,58)\n self.view.setColumnWidth(2,58)\n self.table = 1\n self.row=0\n self.col=0\n slicer.modules.NeedleFinderWidget.analysisGroupBoxLayout.addRow(self.view)","def get_tabular_layour_string(n_cols):\n token = '@{}c@{}|'\n layout = '|'\n for _ in range(n_cols + 1):\n layout += token\n return layout","def amult(self,coef):\n new_name = self.getName() + '_' + str(coef)\n newDataTable = DataTable(new_name)\n newDataTable.setColumnUnits(self.getColumnUnits())\n col_names= self.getColumnNames()\n # Copy the first column as it\n newDataTable.addColumn(col_names[0],self.getColumn(0))\n for i in range(1,len(col_names)):\n c = self.getColumn(i)*coef\n newDataTable.addColumn(col_names[i],c)\n pass\n return newDataTable"],"string":"[\n \"def columns(self):\\n \\n pass\",\n \"def with_column(self, label, values):\\n \\n \\n \\n # self.column_labels.append(label)\\n # for i in range(len(self.rows)):\\n # self.rows[i].append(values[i]) \\n \\n new_label = []\\n new_rows = []\\n for x in self.column_labels:\\n new_label.append(x)\\n new_label.append(label)\\n \\n for i in range(len(self.rows)):\\n new_row = []\\n new_row += self.rows[i]\\n # for i in range(len(b)): \\n new_row.append(values[i])\\n new_rows.append(new_row)\\n \\n \\n new_Table = T88ble(new_rows, new_label)\\n\\n return new_Table\",\n \"def prepare_table(self):\\n i = 0\\n for item in ['DN[-]', 'd_out[mm]', 'tl_trub[mm]', 'roztec_trub[mm]', 'delka[mm]', 'roztec_prep[mm]', 'vyska_prep[mm]']:\\n self.table.insertColumn(i)\\n self.table.setHorizontalHeaderItem(i, QTableWidgetItem(item))\\n i += 1\\n for item in ['tl_prep[mm]','pocet_prep[-]', 'pocet_trub[-]', 'TP[m/s]', 'MZP[m/s]', 'vykon [W]',\\n 'tlak_ztraty[Pa]', 'hmotnost[kg]']:\\n self.table.insertColumn(i)\\n self.table.setHorizontalHeaderItem(i, QTableWidgetItem(item))\\n i += 1\",\n \"def multiplicationTable(size=10,line_space=7):\\n for column in range(1,size+1):\\n row = ''\\n for i in range(1, 11):\\n if i*column > 9:\\n row += str(i*column) + ' '*( (line_space+1) - len(str(i*column)) )\\n continue\\n row += str(i*column)+ ' '*line_space\\n print(row)\",\n \"def create_numbers_table():\\n work_tuples = parse_columns()\\n print('\\\\n\\\\n\\\\n ----- Tableau récapitulatif -----')\\n print('-----------------------')\\n for ii in work_tuples:\\n line = '|'\\n for ij in ii:\\n line += ' ij |'\\n print(line)\\n print('-----------------------')\",\n \"def multtable(n):\\n for i in range(1, n+1):\\n for j in range(1, n+1):\\n print(i * j, end=' ')\\n print()\",\n \"def generate_table(self, rows):\\n ...\",\n \"def mult_tab(self):\\n raise NotImplementedError\",\n \"def make_tables(self):\\n r = np.zeros((self.size*self.size, 4))\\n p = np.zeros((self.size*self.size, 4, self.size*self.size))\\n directions = np.array([[1, -1, 0, 0], [0, 0, -1, 1]])\\n for x in range(self.size):\\n for y in range(self.size):\\n for a in range(4):\\n i = x*self.size + y\\n r[i, a] = self.reward((x, y))\\n if (x, y) == (self.size-1, self.size-1) or \\\\\\n (x, y) == (self.mid, self.mid):\\n p[i, a, 0] = 1\\n else:\\n for d in range(4):\\n dx, dy = directions[:, d]\\n x_ = max(0, min(self.size-1, x+dx))\\n y_ = max(0, min(self.size-1, y+dy))\\n j = x_*self.size + y_\\n if self.noise is not None:\\n p[i, a, j] += 0.3 * self.noise[x, y, a, d] + 0.7 * int(a == d)\\n else:\\n p[i, a, j] += int(a == d)\\n return r, p\",\n \"def tiles(self, nums, row = 1, spaces = 0):\\r\\n # We add the (\\\" \\\" * 5) to align the rows\\r\\n # with odd number of values\\r\\n separator = (\\\"+---+\\\" + (\\\" \\\" * 5)) * row\\r\\n space = (\\\" \\\" * 5) * spaces\\r\\n\\r\\n tile = space + separator + space + \\\"\\\\n\\\"\\r\\n \\r\\n tile += space\\r\\n for i in nums:\\r\\n # We add the (\\\" \\\" * 5) to align the rows\\r\\n # with odd number of values\\r\\n tile += f\\\"| {i} |\\\" + (\\\" \\\" * 5)\\r\\n tile += space + \\\"\\\\n\\\"\\r\\n \\r\\n tile += space + separator + space + \\\"\\\\n\\\"\\r\\n \\r\\n return tile\",\n \"def dyntable(self):\\n table = ANSITable(\\n Column(\\\"j\\\", colalign=\\\">\\\", headalign=\\\"^\\\"),\\n Column(\\\"m\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"r\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"I\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"Jm\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"B\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"Tc\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"),\\n Column(\\\"G\\\", colalign=\\\"<\\\", headalign=\\\"^\\\"), border=\\\"thin\\\")\\n\\n for j, link in enumerate(self):\\n table.row(link.name, *link._dyn2list())\\n return str(table)\",\n \"def table_for_mi(n11, n10, n01, n00, feature, w=15):\\r\\n\\r\\n table = '|{}|{}|{}|'.format(''.center(w), feature.center(\\r\\n w), 'No \\\"{}\\\"'.format(feature).center(w))\\r\\n table += '\\\\n|' + '-' * w\\r\\n table += '|' + '-' * w\\r\\n table += '|' + '-' * w\\r\\n table += '|'\\r\\n\\r\\n table += '\\\\n|{}|{}|{}|'.format('y(=1)'.center(w),\\r\\n '{}'.format(n11).center(w), '{}'.format(n10).center(w))\\r\\n table += '\\\\n|{}|{}|{}|'.format('y(=0)'.center(w),\\r\\n '{}'.format(n01).center(w), '{}'.format(n00).center(w))\\r\\n\\r\\n return table\",\n \"def get_cols_dummy():\",\n \"def _init_pagoda_clses(self):\\n a = []; b = [] #IGNORE:C0321\\n c = []; d = [] #IGNORE:C0321\\n row_selector = ((a, b), (c, d))\\n for cell in self.compact:\\n row_selector[cell.y % 2][cell.x % 2].append(cell)\\n cell.pvalue = cell.y % 2 + 1 + cell.x % 2 \\n return a, b, c, d\",\n \"def twenty_four_cell(self):\\n verts = []\\n q12 = QQ(1)/2\\n base = [q12,q12,q12,q12]\\n for i in range(2):\\n for j in range(2):\\n for k in range(2):\\n for l in range(2):\\n verts.append([x for x in base])\\n base[3] = base[3]*(-1)\\n base[2] = base[2]*(-1)\\n base[1] = base[1]*(-1)\\n base[0] = base[0]*(-1)\\n verts = verts + permutations([0,0,0,1])\\n verts = verts + permutations([0,0,0,-1])\\n return Polyhedron(vertices = verts)\",\n \"def prepare_table(table):\\n n = len(table)\\n for i, row in enumerate(table):\\n assert len(row) == n, f\\\"len(row) = {len(row)} != {n} = n\\\"\\n for j, _ in enumerate(row):\\n if i == j:\\n table[i][i] = 0.0\\n elif i > j:\\n table[i][j] = 1 - table[j][i]\\n return table\",\n \"def transpose():\",\n \"def timingColumns(self, results):\\n \\n pass\",\n \"def zernike_Double_Index(nlevels):\\n \\n\\t \\n if not (nlevels>=0):\\n print('Input parameter nlevels must be >= 0')\\n raise AssertionError()\\n \\n if (nlevels == 0):\\n \\n m = 0\\n n = 0\\n \\n return n, m\\n \\n else:\\n \\n # ++++ Defining layout for row number n and colunmn number m ++++++++\\n\\n row_n = nlevels+1\\n col_m = 2*nlevels +1\\n x = np.arange(row_n)\\n y = np.arange(-(col_m-1)//2, (col_m+1)//2,1)\\n Q = [(i,j) for i in x for j in y]\\n #\\n\\n\\n nm_index = []\\n \\n top = (col_m + 1)/2\\n leftside = row_n*col_m - col_m + 1\\n rightside = row_n*col_m \\n\\n k1 = 0; k2 = 0\\n\\n for i in xrange(top,row_n*col_m+1, 2*col_m):\\n\\n nm_index.append(Q[i-1])\\n s1 = i + col_m + 1\\n s2 = i + col_m - 1 \\n jj1 = k1\\n jj2 = k2\\n\\n\\n while (s2 <= leftside): \\n\\n nm_index.append(Q[s2-1])\\n s2 +=col_m - 1\\n jj1 += 1\\n jj2 -= 1\\n\\n leftside +=2\\n\\n jj1 = k1\\n jj2 = k2\\n\\n while (s1 <= rightside): \\n\\n # \\n nm_index.append(Q[s1-1])\\n s1 +=col_m + 1\\n jj1 += 1\\n jj2 += 1\\n\\n rightside -=2\\n k1 = 0; k2 += 2\\n\\n n = np.array(nm_index)[:,0]\\n m = np.array(nm_index)[:,1]\\n\\n return n, m\",\n \"def row_times_column(m1, row, m2, column):\\n\\n pass\",\n \"def table(nb, max):\\n\\ti = 0\\n\\twhile i < max:\\n\\t\\tprint(i + 1, \\\"*\\\", nb, \\\"=\\\", (i + 1) * nb)\\n\\t\\ti += 1\",\n \"def multiply_trtr_diagram(data):\\n\\n names = data.index.names\\n data = pd.concat([ data.xs('rere', level=2), \\\\\\n data.xs('reim', level=2) + data.xs('imre', level=2)], \\\\\\n keys=['re', 'im']).reorder_levels([1,2,0]).\\\\\\n sort_index(level=[0,1])\\n data.index.names = names\\n return data\",\n \"def __repr__(self):\\n return '<widths: {}, subtable: {}>'.format(self.widths, self.subtable)\",\n \"def collect_columns():\\n return ((x, y) for x in range(72) for y in range(x + 9, 81, 9))\",\n \"def multi_table(a, b):\\n for i in range(1, int(b) + 1):\\n print(f'{a} * {i} = {a*i}')\",\n \"def _gen_table_rows(self):\\n row_labels = self._get_padded_row_labels()\\n column_labels = self._get_padded_column_labels()\\n for row in zip(*column_labels):\\n yield ''.join('<td>%s</td>' % c for c in row)\\n for label, row_string in zip(row_labels, HeatMap._gen_table_rows(self)):\\n yield ''.join('<td>%s</td>' % c for c in label) + row_string\",\n \"def tab(data, column) :\\r\\n\\r\\n table = {}\\r\\n \\r\\n for i in data :\\r\\n if i[column] not in table :\\r\\n # add it to tab\\r\\n table[i[column]] = 1 \\r\\n else:\\r\\n # add tabulation\\r\\n table[i[column]] += 1\\r\\n\\r\\n #place the cursor back at 0\\r\\n \\r\\n return table\",\n \"def create_w_tbl(index: int, entries: int) -> List[float]:\\n min_w = StackupTestHelper.index_to_min_width_fn(index)\\n return list(map(lambda x: min_w*x, range(1, 4 * entries + 1, 4)))\",\n \"def extractSubTable(self,**dico):\\n #\\n if not len(dico):\\n return self.copy()\\n elif len(dico)>1:\\n msg='only one argument allowed.'\\n raise msg\\n #\\n cle=list(dico.keys())[0]\\n val=dico[cle]\\n cle=cle.lower()\\n if cle=='withvaluesincolumn':\\n model,numeroColonne=val[0],val[1]\\n listTypeCheck(model,[IntType,FloatType])\\n model=[float(x) for x in model]\\n verifyType(numeroColonne,[StringType,\\\\\\n IntType,FloatType])\\n tttitres=self.getColumnNames()\\n ttunits = self.getColumnUnits()\\n if type(numeroColonne) is StringType:\\n for tit in tttitres:\\n if tit==numeroColonne:\\n numCol=tttitres.index(tit)\\n pass\\n pass\\n pass\\n else:\\n if numeroColonne>=len(tttitres):\\n msg='The table does not have\\\\n'\\n msg+='that number of columns : %s'%numeroColonne\\n raise msg\\n numCol=numeroColonne\\n pass\\n if len(val)==3:\\n eps=val[2]\\n pass\\n else:\\n eps=1.e-15\\n pass\\n new=DataTable(self.getName(),tttitres,ttunits)\\n nlig=self.getNbRows()\\n ip=0\\n comp=[float(x) for x in self.getColumn(numCol)]\\n for ip in range(len(model)):\\n for i in range(len(comp)):\\n value=comp[i]\\n if ip==1 and i==len(comp)-1:\\n pass\\n if areClose(value,model[ip],eps,'rel'):\\n new.addRow(self.getRow(i))\\n pass\\n if ip==len(model):\\n break\\n pass\\n pass\\n pass \\n else:\\n valeurs=toList(val)\\n tttitres=self.getColumnNames()\\n ttunits = self.getColumnUnits()\\n for st in ['row','column']:\\n if st=='row':nn=self.getNbRows()\\n if st=='column':nn=self.getNbColumns()\\n if cle.find(st)>=0:\\n cleOk=st\\n pass\\n if cle==st:\\n if len(valeurs) != 1:\\n raise Exception(\\\" list length problem within the extractSubTable function\\\")\\n if cle=='from'+st: valeurs=valeurs[valeurs[0]:nn-1]\\n if cle=='to'+st: valeurs=valeurs[0:valeurs[0]]\\n if cle.find('name')>=0:\\n newv=[]\\n for v in valeurs:\\n for tit in tttitres:\\n if tit==v:\\n newv.append(tttitres.index(tit))\\n break\\n pass\\n pass\\n valeurs=newv\\n pass\\n pass\\n if cleOk=='row':\\n newtitres=tttitres\\n newunits = ttunits\\n pass\\n if cleOk=='column':\\n newtitres=[]\\n newunits = []\\n for i in valeurs:\\n newtitres.append(tttitres[i])\\n if len(ttunits): newunits.append(ttunits[i])\\n pass\\n pass\\n new=DataTable(self.getName(),newtitres,newunits)\\n for i in valeurs:\\n if cleOk=='row':\\n liste=self.getRow(i)\\n new.addRow(liste)\\n pass\\n if cleOk=='column':\\n liste=self.getColumn(i)\\n new.addColumnValues(liste)\\n pass\\n pass\\n pass\\n return new\",\n \"def derMatrix(Bulk_Operators, Bdy_Operators, Bulk_second, s=1):\\n\\t\\tMatrix = []\\n\\t\\tfor i in range(1, M_max + 1):\\n\\t\\t\\t\\trow = []\\n\\t\\t\\t\\tfor Bulk_Op in Bulk_Operators:\\n\\t\\t\\t\\t\\t\\ttable_call = N*table1.table[0, i].subs({\\\"Delta\\\":Bulk_Op, \\\"Delta_12\\\":delta_12, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\t\\trow.append(table_call)\\n\\t\\t\\t\\tfor index in range(len(Bulk_second)):\\n\\t\\t\\t\\t\\t\\trow.append(0*table1.table[0,0])\\n\\t\\t\\t\\tfor Bdy_Op in Bdy_Operators:\\n\\t\\t\\t\\t\\tif Bdy_Op == 2.0:\\n\\t\\t\\t\\t\\t\\t\\tprint(\\\"here\\\")\\n\\t\\t\\t\\t\\t\\t\\ttable_call = (N-1)*table1.table[1, i].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\ttable_call = table1.table[1, i].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\trow.append(table_call)\\n\\t\\t\\t\\tXi = symbols('Xi')\\n\\t\\t\\t\\tif s == 1:\\n\\t\\t\\t\\t\\t\\tlast_expr = Xi**((delta_1 + delta_2)/2)\\n\\t\\t\\t\\t\\t\\tlast_elem = diff(last_expr, Xi, i).subs({\\\"Xi\\\":1.00}).evalf()\\n\\t\\t\\t\\t\\t\\trow.append(last_elem)\\n\\t\\t\\t\\tMatrix.append(row)\\n\\t\\t\\t\\trow2 = []\\n\\t\\t\\t\\tfor index in range(len(Bulk_Operators)):\\n\\t\\t\\t\\t\\t\\trow2.append(0*table1.table[0,0])\\n\\t\\t\\t\\tfor Bulk_Op in Bulk_second:\\n\\t\\t\\t\\t\\t\\ttable_call = table1.table[0, i].subs({\\\"Delta\\\":Bulk_Op, \\\"Delta_12\\\":delta_12, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\t\\trow2.append(table_call)\\n\\t\\t\\t\\tfor Bdy_Op in Bdy_Operators:\\n\\t\\t\\t\\t\\t\\tif Bdy_Op == 2.0:\\n\\t\\t\\t\\t\\t\\t\\tprint(\\\"here\\\")\\n\\t\\t\\t\\t\\t\\t\\ttable_call = -1*table1.table[1, i].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\t\\ttable_call = table1.table[1, i].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\t\\t\\trow2.append(table_call)\\n\\t\\t\\t\\tXi = symbols('Xi')\\n\\t\\t\\t\\tif s == 1:\\n\\t\\t\\t\\t\\t\\tlast_expr = Xi**((delta_1 + delta_2)/2)\\n\\t\\t\\t\\t\\t\\tlast_elem = diff(last_expr, Xi, i).subs({\\\"Xi\\\":1.00}).evalf()\\n\\t\\t\\t\\t\\t\\trow2.append(last_elem)\\n\\t\\t\\t\\tMatrix.append(row2)\\t\\t\\n\\t\\treturn np.array(Matrix)\",\n \"def _settemplates(self, onecol, twocol):\\n\\n self.template = \\\"\\\"\\\"\\n <table class=\\\"f\\\"><tbody>\\n %s\\n %s\\n </tbody></table>\\n \\\"\\\"\\\" % (self.header, onecol)\\n\\n # This is suitable for two column width.\\n self.wide_template = \\\"\\\"\\\"\\n <table class=\\\"f\\\"><tbody>\\n %s\\n %s\\n </tbody></table>\\n \\\"\\\"\\\" % (self.header.replace(\\\"1\\\", \\\"2\\\"), twocol)\",\n \"def times_table_6x6(x):\\n assert x > 12 == False, \\\"The highest value of input is 12\\\"\\n layout = \\\"\\\"\\n index = 0\\n while x > index:\\n layout += \\\"{%s:>4}\\\" % index\\n index += 1\\n\\n for i in range(1, x + 1):\\n print(\\n layout.format(\\n i * 1,\\n i * 2,\\n i * 3,\\n i * 4,\\n i * 5,\\n i * 6,\\n i * 7,\\n i * 8,\\n i * 9,\\n i * 10,\\n i * 11,\\n i * 12,\\n )\\n )\",\n \"def table(self):\\n return self.t\",\n \"def multtable(n):\\n for i in range(1,n+1):\\n for x in range(1, n+1):\\n result = print(i * x, end =' ')\\n print ()\\n return result\",\n \"def __str__(self):\\n table_string = ''\\n values = [x * y for x in range(1, self.x + 1)\\n for y in range(1, self.y + 1)\\n ]\\n for value in range(1, len(values) + 1):\\n if value % self.x == 0:\\n table_string += f'{values[value - 1]}\\\\n'\\n else:\\n table_string += f'{values[value - 1]} | '\\n return table_string\",\n \"def six_hundred_cell(self):\\n verts = []\\n q12 = QQ(1)/2\\n base = [q12,q12,q12,q12]\\n for i in range(2):\\n for j in range(2):\\n for k in range(2):\\n for l in range(2):\\n verts.append([x for x in base])\\n base[3] = base[3]*(-1)\\n base[2] = base[2]*(-1)\\n base[1] = base[1]*(-1)\\n base[0] = base[0]*(-1)\\n for x in permutations([0,0,0,1]):\\n verts.append(x)\\n for x in permutations([0,0,0,-1]):\\n verts.append(x)\\n g = QQ(1618033)/1000000 # Golden ratio approximation\\n verts = verts + [i([q12,g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([q12,g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([q12,-g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([q12,-g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([-q12,g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([-q12,g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([-q12,-g/2,1/(g*2),0]) for i in AlternatingGroup(4)]\\n verts = verts + [i([-q12,-g/2,-1/(g*2),0]) for i in AlternatingGroup(4)]\\n return Polyhedron(vertices = verts)\",\n \"def start_table(self):\\n self.col_widths = []\\n self.result = \\\"\\\"\",\n \"def get_table(self):\\n result_table = [row[:] for row in self.table] # Clone the result table\\n\\n # Htmlise all columns containing images\\n for col_num in self.image_column_nums():\\n for row_num in range(1, len(result_table)):\\n result_table[row_num][col_num] = self.htmlise(result_table[row_num][col_num])\\n\\n # Append images\\n for ((col,row), image_list) in self.images.items():\\n for image in image_list:\\n try:\\n result_table[row][col] += \\\"<br>\\\" + image\\n except IndexError:\\n pass # Testing must have aborted so discard image\\n\\n return result_table\",\n \"def test_collected_columns_as_table_two_col_from_two(self):\\n col_double, allow_colspan = True, True # as_type == 'table'\\n col_args = ('span', False, {})\\n names, multi_field_row = ('first', 'billing_address_1'), True\\n row = {name: self.form.fields[name] for name in names}\\n col_count = 2\\n expected = [self.form.collect_col_data(name, self.form.fields[name], *col_args) for name in names]\\n for ea in expected:\\n if multi_field_row:\\n ea['css_classes'] = ' '.join(['nowrap', ea['css_classes']])\\n ea['html_head_attr'] = ' class=\\\"nowrap\\\"'\\n val = ea.pop('css_classes', '')\\n val = ' class=\\\"%s\\\"' % val if val else ''\\n if not multi_field_row and col_count > 1:\\n val = val + ' colspan=\\\"{}\\\"'.format(2 * col_count - 1)\\n ea['html_col_attr'] = val\\n col_settings = (multi_field_row, col_count, col_double, allow_colspan)\\n actual = self.form.collect_columns(row, col_settings, *col_args)\\n\\n self.assertEqual(len(expected), len(actual))\\n for expect, got in zip(expected, actual):\\n self.assertEqual(len(expect), len(got))\\n self.assertListEqual(list(expect.keys()), list(got.keys()))\\n self.assertListEqual(list(expect.values()), list(got.values()))\\n self.assertEqual(expected, actual)\",\n \"def fill_table(self, data):\\r\\n if len(data) > 0:\\r\\n if isinstance(data, np.ndarray):\\r\\n data = data.tolist()\\r\\n data_rows = len(data)\\r\\n data_columns = len(data[0])\\r\\n if data_columns > 0:\\r\\n self.setRowCount(data_rows)\\r\\n # We hide the imag part of the complex impedance\\r\\n self.setColumnCount(data_columns - 1)\\r\\n for r in range(0, data_rows):\\r\\n # Update real columns\\r\\n for c, realc in [(0, 0), (1, 1), (3, 4)]:\\r\\n item = QTableWidgetItem() \\r\\n item.setText(str(data[r][realc])) \\r\\n self.setItem(r, c, item)\\r\\n # Earth resistance has a hidden column which can have an imaginary number\\r\\n if data[r][3] != 0.0:\\r\\n # show complex impedance\\r\\n item = QTableWidgetItem() \\r\\n item.setText(str(np.complex(data[r][2], data[r][3])))\\r\\n self.setItem(r, 2, item)\\r\\n else:\\r\\n # show real impedance\\r\\n item = QTableWidgetItem()\\r\\n item.setText(str(data[r][2])) \\r\\n self.setItem(r, 2, item)\\r\\n # Last Column is a QComboBox to select phasing\\r\\n phasing = QComboBox()\\r\\n phasing.addItems([\\\"Normal\\\",\\\"120 degree shift\\\", \\\"240 degree shift\\\"])\\r\\n phasing.setCurrentIndex(np.real(data[r][5]))\\r\\n phasing.currentIndexChanged.connect(self.phasing_signal(phasing, r, 5))\\r\\n self.setCellWidget(r, 4, phasing)\",\n \"def print_table(n):\\n \\n numbers = list(range(1, n + 1))\\n\\n #处理第一行\\n s = ''\\n for i in numbers:\\n s = s + '\\\\t' + str(i)\\n print(s)\\n\\n for i in numbers:\\n s = str(i)\\n for j in numbers:\\n s = s + '\\\\t' + str(i * j)\\n print(s)\",\n \"def table(self, doc, level, output):\\n output('<table border=\\\"1\\\" cellpadding=\\\"2\\\">\\\\n')\\n for row in doc.getRows()[0]:\\n output(\\\"<tr>\\\\n\\\")\\n for column in row.getColumns()[0]:\\n str = ('<%s colspan=\\\"%s\\\" align=\\\"%s\\\" valign=\\\"%s\\\">'\\n % (column.getType(),\\n column.getSpan(),\\n column.getAlign(),\\n column.getValign()))\\n output(str)\\n for c in column.getChildNodes():\\n getattr(self, self.element_types[c.getNodeName()]\\n )(c, level, output)\\n output(\\\"</\\\" + column.getType() + \\\">\\\\n\\\")\\n output(\\\"</tr>\\\\n\\\")\\n output(\\\"</table>\\\\n\\\")\",\n \"def print_table(self):\\n print(\\\"%-12s%-12s%-12s%-12s%-12s\\\" % (\\\"index\\\",\\\"balance\\\",\\\"payment\\\",\\\"interest\\\",\\\"amortization\\\"))\\n print(\\\"-------------------------------------------------------------\\\")\\n for i in self.table[\\\"index\\\"]:\\n print(\\\"%-12i%-12i%-12i%-12i%-12i\\\" % (self.table[\\\"index\\\"][i],self.table[\\\"balance\\\"][i]\\\\\\n ,self.table[\\\"payment\\\"][i],self.table[\\\"interest\\\"][i],\\\\\\n self.table[\\\"amortization\\\"][i]))\",\n \"def create_pairwise_metric_table(\\n row_list: Set[Text],\\n column_list: Set[Text],\\n name_value_map: Dict[Text, float],\\n same_match_value\\n) -> Text:\\n table_template = template.TABLE_TEMPLATE\\n\\n headers = ['​'] + list(column_list)\\n header_string = \\\"|\\\".join(headers)\\n header_separator = \\\"|\\\".join([\\\":-----:\\\" for i in range(len(headers))])\\n\\n table_content = []\\n\\n for row_name in row_list:\\n # row header is in BOLD\\n row_values = [template.BOLD.format(content=row_name.strip())]\\n for col_name in column_list:\\n # same_match_value is used when row_name == column_name\\n if row_name == col_name:\\n value = same_match_value\\n else:\\n value = name_value_map[row_name + '-' + col_name]\\n\\n # if the same_match_value is string, simply append it\\n if isinstance(value, str):\\n row_values.append(same_match_value)\\n else:\\n row_values.append(formatting.numeric_formatting(value))\\n\\n table_content.append(\\\"|\\\".join(row_values))\\n\\n table_content_string = \\\"\\\\n\\\".join(table_content)\\n\\n return table_template.format(\\n header=header_string,\\n header_separator=header_separator,\\n table_content=table_content_string\\n )\",\n \"def __call__(self, i, j):\\n return _table.Table___call__(self, i, j)\",\n \"def print_table(table, title_list):\\n\\n # your goes code\\n cols = len(title_list)\\n\\n \\n\\n table.insert(0,title_list)\\n\\n for sublist in range(len(table)):\\n if cols != len(table[sublist]):\\n print('dataset does not match number of cols')\\n quit()\\n\\n max_lenghts = []\\n maxi = -1\\n for sub_elem in range(cols): \\n maxi = -1 \\n for sublist in range(len(table)):\\n if len(table[sublist][sub_elem]) > maxi:\\n maxi = len(table[sublist][sub_elem])\\n max_lenghts.append(maxi)\\n \\n\\n \\n\\n sub_elem = 0\\n \\n for sublist in range(len(table)):\\n if sublist == 0:\\n while sub_elem < len(table[0]):\\n \\n if sub_elem == len(table[0])- 1:\\n print('\\\\033[1;37;41m| {:^25} |'.format(table[sublist][sub_elem]), end =\\\"\\\")\\n else:\\n print('\\\\033[1;37;41m| {:^25} '.format(table[sublist][sub_elem]), end =\\\"\\\")\\n sub_elem += 1\\n \\n print('\\\\033[0;32;48m\\\\n') \\n sub_elem = 0 \\n else:\\n while sub_elem < len(table[0]):\\n \\n if sub_elem == len(table[0])- 1:\\n print('\\\\033[0;37;44m| {:^25} |'.format(table[sublist][sub_elem]), end =\\\"\\\")\\n else:\\n print('\\\\033[0;37;44m| {:^25} '.format(table[sublist][sub_elem]), end =\\\"\\\")\\n sub_elem += 1\\n \\n print('\\\\033[0;32;48m\\\\n') \\n sub_elem = 0 \\n print('\\\\033[0;37;48m\\\\n')\\n table.pop(0)\",\n \"def print_grid2(y, z):\\n for i in range(y):\\n prow(z, y)\\n for i in range(z):\\n pcolumn(z*2, y)\\n prow(z, y)\",\n \"def matrix_table(matrix):\\r\\n result =\\\"<table id='matrix_result'>\\\"\\r\\n for line in range(len(matrix)):\\r\\n result += \\\"<tr>\\\"\\r\\n for column in range(len(matrix)):\\r\\n result += \\\"<td>\\\" + str(matrix[line][column]) + \\\"</td>\\\"\\r\\n result += \\\"</tr>\\\"\\r\\n result += \\\"</table>\\\"\\r\\n return result\",\n \"def select(self, labels):\\n indexs = []\\n \\n for i in range(len(labels)):\\n indexs.append(self.column_labels.index(labels[i]))\\n new_rows = []\\n for x in self.rows:\\n new_row = []\\n for index in indexs:\\n new_row.append(x[index])\\n new_rows.append(new_row)\\n\\n\\n\\n new_Table = T88ble(new_rows, labels)\\n\\n return new_Table\",\n \"def table(self, L, R, n):\\n s = \\\"\\\"\\n for x in np.linspace(L, R, n):\\n y = self(x)\\n s += \\\"%12g %12g\\\\n\\\" % (x, y)\\n return s\",\n \"def cell_edges(self):\",\n \"def _gen_table_style_lines(self):\\n yield '.heatmap {border: none; border-collapse: collapse; border-spacing: 0}'\\n yield '.heatmap td {padding: 0; margin: 0; font-family: monospace;}'\",\n \"def transpose(self) -> None:\\n ...\",\n \"def rosterRowData(self):\",\n \"def get_colspecs(self):\\n width = 80\\n\\n total_width = 0.0\\n # first see if we get too wide.\\n for node in self._col_specs:\\n colwidth = float(node['colwidth']+1) / width\\n total_width += colwidth\\n self._col_width = []\\n self._rowspan = []\\n # donot make it full linewidth\\n factor = 0.93\\n if total_width > 1.0:\\n factor /= total_width\\n bar = self.get_vertical_bar()\\n latex_table_spec = \\\"\\\"\\n for node in self._col_specs:\\n colwidth = factor * float(node['colwidth']+1) / width\\n self._col_width.append(colwidth+0.005)\\n self._rowspan.append(0)\\n latex_table_spec += \\\"%sp{%.2f\\\\\\\\locallinewidth}\\\" % (bar,colwidth+0.005)\\n return latex_table_spec+bar\",\n \"def table(self, L, R, n):\\n s =''\\n import numpy as np\\n for x in np.linspace(L, R, n):\\n y = self(x)\\n s += '%12g %12g\\\\n' % (x, y)\\n return s\",\n \"def make_space_table(space):\\n columns = dragon[\\\"%s\\\" % space].reset_index().columns\\n return DataTable(\\n id=\\\"%s_table\\\" % space,\\n columns=[{\\\"name\\\": i, \\\"id\\\": \\\"%s\\\" % i} for i in columns],\\n data=get_table_data(space, []),\\n style_header={\\n \\\"transform\\\": \\\"translate(0px, 0px) rotate(-0.0deg)\\\",\\n \\\"max-width\\\": \\\"20px\\\",\\n \\\"backgroundColor\\\": \\\"transparent\\\",\\n },\\n )\",\n \"def table(self, L, R, n):\\n s = \\\"\\\"\\n import numpy as np\\n for x in np.linspace(L, R, n):\\n y = self(x)\\n s += \\\"%12g %12g\\\\n\\\" %(x,y)\\n return s\",\n \"def process_ipet_table(table, repres, add_ind=False, swap=False):\\n # split rowspan cells from the tables body to enable js datatable\\n table_rows = [e for e in table.find(\\\".//tbody\\\").iter() if e.tag == \\\"tr\\\" or e.tag == \\\"th\\\"]\\n groupcount = 1\\n oldtext = \\\"\\\"\\n for row in table_rows:\\n cellcount = 0\\n for cell in row.iter():\\n if add_ind and cellcount == 1 and cell.tag == \\\"th\\\" and cell.text != oldtext:\\n cell.text = \\\"{:0>2d}. {}\\\".format(groupcount, cell.text)\\n oldtext = cell.text\\n groupcount = groupcount + 1\\n rowspan = cell.get(\\\"rowspan\\\")\\n if rowspan is not None:\\n del cell.attrib[\\\"rowspan\\\"]\\n nextrow = row\\n for i in range(int(rowspan) - 1):\\n nextrow = nextrow.getnext()\\n newcell = html.fromstring(html.tostring(cell))\\n nextrow.insert(cellcount - 1, newcell)\\n cellcount = cellcount + 1\\n\\n # render to string and make the dataTable fit the width\\n htmltable = html.tostring(table).decode(\\\"utf-8\\\")\\n # replace ids and so on\\n htmltable = replace_in_str(htmltable, repres)\\n htmltable = htmltable.replace(\\\"nan\\\", NONE_DISPLAY)\\n return htmltable\",\n \"def displayPokedex(pokedex):\\n for col1,col2 in zip(pokedex[::2],pokedex[1::2]):\\n\\t print(col1+\\\",\\\",col2+\\\",\\\")\",\n \"def print_table(table):\\n rest = table[1:]\\n fmt = \\\"%-28s %-9s %-16s %s\\\"\\n for row in rest:\\n print(fmt % tuple(row))\",\n \"def nktable(nmax, kmax, sort = \\\"value\\\"):\\n number_of_columns = nmax\\n firstline = r\\\"\\\\begin{tabular}{\\\"\\n secondline = r\\\"&\\\\multicolumn{\\\"+str(nmax)+ r\\\"}{|c}{Scheibenzahl $n$}\\\\\\\\\\\"\\n i = 0\\n while i < number_of_columns:\\n i += 1\\n if i == 1:\\n firstline += \\\"c|\\\"\\n firstline += \\\"c\\\"\\n firstline += \\\"}\\\"\\n hline = r\\\"\\\\hline\\\"\\n lines = [firstline]\\n lines.append(secondline)\\n line = r\\\"$k\\\\downarrow$\\\"\\n for n in range(1,nmax+1):\\n line += \\\"&\\\"+str(n)\\n\\n for k in range(3,kmax+1):\\n line += r\\\"\\\\\\\\\\\"\\n lines.append(line)\\n if k == 3:\\n lines.append(hline)\\n line = str(k)\\n for n in range(1,nmax+1):\\n if sort == \\\"value\\\":\\n line += \\\"&\\\"+str(M(n,k))\\n elif sort == \\\"increment\\\":\\n line += \\\"&\\\"+str(2**t_(n,k))\\n elif sort == \\\"possibilities\\\":\\n line += \\\"&\\\"+str(upsilon(n,k))\\n elif sort == \\\"totalpossibilities\\\":\\n line += \\\"&\\\"+str(totalpossibilities(n,k))\\n elif sort == \\\"adjustedpossibilities\\\":\\n line += \\\"&\\\"+str(adjustedUpsilon(n,k))\\n elif sort == \\\"bfadjustedpossibilities\\\":\\n line += \\\"&\\\"+str(bruteforceadjustedUpsilon(n,k))\\n\\n lines.append(line)\\n lines.append(r\\\"\\\\end{tabular}\\\")\\n return lines\",\n \"def cols(self, col):\\n self.col += col\",\n \"def _modify_columns(self, cols, X, y=None):\",\n \"def T(self):\\n # TODO - your code here\\n transpose = []\\n for col in range(self.w):\\n new_row = []\\n for row in range(self.h):\\n new_row.append(self.g[row][col])\\n transpose.append(new_row)\\n return Matrix(transpose)\\n # TODO - your code here\",\n \"def get_table_df(df):\\n # --------------------------------------------------------------------------\\n # Start\\n # --------------------------------------------------------------------------\\n indf = df.copy()\\n tabzeros = {i:'0' for i in ['-','*']}\\n pctzeros = {i:'0' for i in ['*','**']}\\n combzeros = {i:'0' for i in ['-','*','**']}\\n # --------------------------------------------------------------------------\\n # Drop the empty columns and rows\\n # --------------------------------------------------------------------------\\n # indf.dropna(axis=0,how='all',inplace=True)\\n indf.dropna(axis=1,how='all',inplace=True)\\n indf.fillna('',inplace=True)\\n # --------------------------------------------------------------------------\\n # Grab the first column\\n # --------------------------------------------------------------------------\\n cols = indf.columns.to_list()\\n indxcol = indf[cols[0]].to_list()\\n # --------------------------------------------------------------------------\\n # Figure out where the pieces of the table are\\n # --------------------------------------------------------------------------\\n title = [0,1]\\n banner = []\\n table = []\\n inheader = True\\n inbanner = False\\n intable = False\\n # --------------------------------------------------------------------------\\n # Go through and figure out where everything starts and stops\\n # --------------------------------------------------------------------------\\n for i,val in enumerate(indxcol):\\n # ----------------------------------------------------------------------\\n # Find the start of the information\\n # ----------------------------------------------------------------------\\n if inheader:\\n bskip = True\\n for cell in indf.iloc[i,:].values.tolist():\\n if cell != '':\\n bskip = False\\n break\\n if bskip:\\n continue\\n if val != '' or val is not np.nan:\\n instart = False\\n inheader = True\\n # ----------------------------------------------------------------------\\n # In the header\\n # ----------------------------------------------------------------------\\n if inheader:\\n if val == '' or val is np.nan:\\n inbanner = True\\n inheader = False\\n # ----------------------------------------------------------------------\\n # In the banner\\n # ----------------------------------------------------------------------\\n if inbanner:\\n bskip = True\\n # ------------------------------------------------------------------\\n # In the case that we have an entire row that is empty, skip.\\n # This should handle empty rows after the header\\n # ------------------------------------------------------------------\\n for cell in indf.iloc[i,:].values.tolist():\\n if cell != '':\\n bskip = False\\n break\\n if bskip:\\n continue\\n if val != '':\\n inbanner = False\\n intable = True\\n else:\\n banner.append(i)\\n # ----------------------------------------------------------------------\\n # In the table\\n # ----------------------------------------------------------------------\\n if intable:\\n table.append(i)\\n # ------------------------------------------------------------------\\n # Exit if we've reached the bottom\\n # ------------------------------------------------------------------\\n if 'Statistics' in str(val):\\n break\\n if 'Table ' in str(val):\\n table = table[:-2]\\n # --------------------------------------------------------------------------\\n # Break the dataframe apart\\n # --------------------------------------------------------------------------\\n bandf = indf.iloc[banner[0]:banner[-1]+1].copy()\\n tabdf = indf.iloc[table[0]:table[-2]].copy()\\n # --------------------------------------------------------------------------\\n # Create the column index setup\\n # --------------------------------------------------------------------------\\n banmat = bandf.iloc[:,1:].values.tolist()\\n for row in banmat:\\n for i in range(len(row)):\\n if row[i] == '':\\n row[i] = row[i-1]\\n # --------------------------------------------------------------------------\\n # Set up the tuples for the columns\\n # --------------------------------------------------------------------------\\n colnames = []\\n for i in range(len(banmat[0])):\\n colnames.append(tuple([row[i] for row in banmat]))\\n multi_col = pd.MultiIndex.from_tuples(colnames)\\n # --------------------------------------------------------------------------\\n # Create the final using the information above\\n # --------------------------------------------------------------------------\\n tabindx = tabdf[cols[0]].to_list()\\n for i,val in enumerate(tabindx):\\n if val == '':\\n tabindx[i] = currval\\n else:\\n currval = val\\n # --------------------------------------------------------------------------\\n # Set the index\\n # --------------------------------------------------------------------------\\n # setindx = pd.MultiIndex.from_tuples(tabindx)\\n tabdf.index = [str(i) for i in tabindx]\\n del tabdf[cols[0]]\\n # --------------------------------------------------------------------------\\n # Set the columns\\n # --------------------------------------------------------------------------\\n tabdf.columns = multi_col\\n # --------------------------------------------------------------------------\\n # Go through the rows and add a typing tag\\n # --------------------------------------------------------------------------\\n typecol = []\\n for idx, row in tabdf.iterrows():\\n # ----------------------------------------------------------------------\\n # Default to a count row\\n # ----------------------------------------------------------------------\\n thistype = 'count'\\n # ----------------------------------------------------------------------\\n # If the entire row is empty, it's a stat row\\n # ----------------------------------------------------------------------\\n bstat = True\\n for val in row:\\n if val != '':\\n bstat = False\\n break\\n if bstat:\\n thistype = 'stat'\\n # ----------------------------------------------------------------------\\n # Go through the values and guess at the type\\n # ----------------------------------------------------------------------\\n for val in row:\\n # ------------------------------------------------------------------\\n # Skip if empty since it doesn't tell us anything\\n # ------------------------------------------------------------------\\n if val == '':\\n continue\\n # ------------------------------------------------------------------\\n # If it has any of the following keys, skip\\n # ------------------------------------------------------------------\\n if val in tabzeros:\\n continue\\n # ------------------------------------------------------------------\\n # If it is one of the zeros for pcts, mark\\n # ------------------------------------------------------------------\\n if val in pctzeros:\\n thistype = 'pct'\\n break\\n # ------------------------------------------------------------------\\n # If we are able to cast as float and the value is less than 1, pct\\n # ------------------------------------------------------------------\\n try:\\n floatval = float(val)\\n if floatval < 1:\\n thistype = 'pct'\\n break\\n # ------------------------------------------------------------------\\n # If it breaks, we are in a stat row\\n # ------------------------------------------------------------------\\n except:\\n thistype = 'stat'\\n break\\n typecol.append(thistype)\\n tabdf['type'] = typecol\\n # --------------------------------------------------------------------------\\n # Split the table into multiple tables (count, pct, stat)\\n # --------------------------------------------------------------------------\\n tmpmask = tabdf[('type')] == 'count'\\n countdf = tabdf.loc[tmpmask].copy()\\n tmpmask = tabdf[('type')] == 'stat'\\n statdf = tabdf.loc[tmpmask].copy()\\n tmpmask = tabdf[('type')] == 'pct'\\n pctdf = tabdf.loc[tmpmask].copy()\\n # --------------------------------------------------------------------------\\n # Create the base, unweighted base, and effective base dataframes\\n # --------------------------------------------------------------------------\\n # --------------------------------------------------------------------------\\n # Base df\\n # --------------------------------------------------------------------------\\n basedf = tabdf.copy()\\n baserow = None\\n for idx,row in basedf.iterrows():\\n if (idx.lower()[:4] == 'base' and 'unweighted' not in idx.lower() and 'effective' not in idx.lower()) and row[('type')].to_list()[0] == 'count':\\n baserow = row\\n for col,val in row.items():\\n if baserow is None:\\n usebase = np.nan\\n else:\\n usebase = baserow[col]\\n basedf.loc[idx,col] = usebase\\n basedf = basedf[~basedf.index.duplicated(keep='first')]\\n # --------------------------------------------------------------------------\\n # Unweighted df\\n # --------------------------------------------------------------------------\\n unwbdf = tabdf.copy()\\n baserow = None\\n for idx,row in unwbdf.iterrows():\\n if ('unweighted' in idx.lower()) and row[('type')].to_list()[0] == 'count':\\n baserow = row\\n for col,val in row.items():\\n if baserow is None:\\n usebase = np.nan\\n else:\\n usebase = baserow[col]\\n unwbdf.loc[idx,col] = usebase\\n unwbdf = unwbdf[~unwbdf.index.duplicated(keep='first')]\\n # --------------------------------------------------------------------------\\n # Effective df\\n # --------------------------------------------------------------------------\\n effbdf = tabdf.copy()\\n baserow = None\\n for idx,row in effbdf.iterrows():\\n if ('effective' in idx.lower()) and row[('type')].to_list()[0] == 'count':\\n baserow = row\\n for col,val in row.items():\\n if baserow is None:\\n usebase = np.nan\\n else:\\n usebase = baserow[col]\\n effbdf.loc[idx,col] = usebase\\n effbdf = effbdf[~effbdf.index.duplicated(keep='first')]\\n # --------------------------------------------------------------------------\\n # Clean up the statdf in case there are bases\\n # --------------------------------------------------------------------------\\n rmlist = []\\n for idx in statdf.index:\\n if str(idx).lower()[:4] == 'base':\\n rmlist.append(idx)\\n if 'unweighted' in str(idx).lower():\\n rmlist.append(idx)\\n if 'effective' in str(idx).lower():\\n rmlist.append(idx)\\n statdf.drop(rmlist,inplace=True)\\n # --------------------------------------------------------------------------\\n # Drop the type column\\n # --------------------------------------------------------------------------\\n del countdf[('type')]\\n del statdf[('type')]\\n del pctdf[('type')]\\n del basedf[('type')]\\n del unwbdf[('type')]\\n del effbdf[('type')]\\n # --------------------------------------------------------------------------\\n # Set the column types appropriately for the count and pct dataframes\\n # --------------------------------------------------------------------------\\n for col in countdf.columns:\\n countdf.loc[:,col] = countdf[col].copy().replace(tabzeros).astype(float)\\n for col in pctdf.columns:\\n pctdf.loc[:,col] = pctdf[col].copy().replace(combzeros).astype(float)\\n # --------------------------------------------------------------------------\\n # If any of the dataframes are empty, replace with None\\n # --------------------------------------------------------------------------\\n if countdf.empty:\\n countdf = None\\n if statdf.empty:\\n statdf = None\\n if pctdf.empty:\\n pctdf = None\\n # --------------------------------------------------------------------------\\n # If there is a statdf that is not none, drop the last row of the multiindex\\n # --------------------------------------------------------------------------\\n if statdf is not None:\\n if countdf is not None:\\n countdf.columns = countdf.columns.droplevel(-1)\\n if pctdf is not None:\\n pctdf.columns = pctdf.columns.droplevel(-1)\\n if basedf is not None:\\n basedf.columns = basedf.columns.droplevel(-1)\\n if unwbdf is not None:\\n unwbdf.columns = unwbdf.columns.droplevel(-1)\\n if effbdf is not None:\\n effbdf.columns = effbdf.columns.droplevel(-1)\\n # --------------------------------------------------------------------------\\n # Finish\\n # --------------------------------------------------------------------------\\n out = {}\\n out['count'] = countdf\\n out['pct'] = pctdf\\n out['stat'] = statdf\\n out['base'] = basedf\\n out['unwb'] = unwbdf\\n out['effb'] = effbdf\\n return out\",\n \"def _rotate_cw(self, table):\\n return [ [ table[1][0], table[0][0] ],\\n [table[1][1], table[0][1] ] ]\",\n \"def transpose(self):\\n pass\",\n \"def make_table(m, n):\\n return np.array([[0] * n for _ in range(m)], dtype=float)\",\n \"def visit_table(self, sytable):\\n def index(sytable):\\n try:\\n return sytable.get_column(self.input_index)\\n except:\\n return np.arange(sytable.number_of_rows())\\n\\n def slices_using_group_array(group_array):\\n \\\"\\\"\\\"Return the slices to split by.\\n A group array is made of strictly increasing group identifiers.\\n\\n >>> slices_using_group_array(np.array([0, 0, 0, 1, 1, 2, 3, 3, 3]))\\n [(0, 3), (3, 5), (5, 6), (6, 9)]\\n \\\"\\\"\\\"\\n unique_elements = np.unique(group_array)\\n slices = []\\n for unique_element in unique_elements:\\n indexes = np.flatnonzero(group_array == unique_element)\\n low, high = (indexes[0], indexes[-1] + 1)\\n slices.append((unique_element, slice(low, high)))\\n return slices\\n\\n def indices_using_group_array(group_array):\\n \\\"\\\"\\\"\\n Return list of index lists, ordered by first occurance of value.\\n \\\"\\\"\\\"\\n unique_elements = np.unique(group_array)\\n indices = []\\n for unique_element in unique_elements:\\n indices.append((unique_element,\\n np.flatnonzero(group_array == unique_element)))\\n return indices\\n\\n columns = sytable.columns()\\n # Perform the split and append the new tables to output.\\n slice_indices = indices_using_group_array(index(sytable))\\n column_attrs = {}\\n\\n for unique_element, slice_index in slice_indices:\\n # Sets of all columns except for the INDEX columns.\\n result = type(sytable)(sytable.container_type)\\n self.output_list.append((unique_element, result))\\n\\n for column in columns:\\n array = sytable.get_column(column)[slice_index]\\n if self.remove_fill and len(array):\\n kind = array.dtype.kind\\n if kind in ['S', 'U']:\\n if np.all(array == ''):\\n continue\\n else:\\n if not len(array) or np.isnan(np.min(array)):\\n continue\\n\\n result.set_column(column, array)\\n if column in column_attrs:\\n attrs = column_attrs[column]\\n else:\\n attrs = dict(\\n sytable.get_column_attributes(column).get())\\n column_attrs[column] = attrs\\n result.get_column_attributes(column).set(attrs)\",\n \"def markdown_row(self, ncol, which):\\n if which == 'C':\\n dat = self.C\\n elif which == 'c':\\n dat = self.d1\\n elif which == 'f':\\n dat = self.d2\\n line = '|%d|' % (self.N*2)\\n for i in range(1,self.N+1):\\n line = line + ' $%s$ |' % (dat[i])\\n for i in range(1,ncol - self.N+1):\\n line = line + ' |'\\n line = line + '\\\\n'\\n return line\",\n \"def construct_table(self):\\n table_str = self.header_row\\n row_lbls, col_lbls = self.get_idxvals()\\n for r,rlbl in enumerate(row_lbls):\\n row_data = [self.data[rlbl,clbl] for clbl in col_lbls]\\n table_str += self.construct_row(r, row_data)\\n \\n return table_str\",\n \"def __init__(self, grid, column_id, column_span=1):\\n super(GraphVisualizerConnectedcolumn, self).__init__(\\n grid, column_id, column_span\\n )\\n\\n for i in range(column_span):\\n self._grid.setColumnStretch(self._column_id + i, 1)\",\n \"def dctColUels(pdct, j):\\n return _dctmcc.dctColUels(pdct, j)\",\n \"def _generate_tabular(lookup_table, interpolation='linear', points_unit=u.pix, **kwargs):\\n if not isinstance(lookup_table, u.Quantity):\\n raise TypeError(\\\"lookup_table must be a Quantity.\\\") # pragma: no cover\\n\\n ndim = lookup_table.ndim\\n TabularND = tabular_model(ndim, name=f\\\"Tabular{ndim}D\\\")\\n\\n # The integer location is at the centre of the pixel.\\n points = [(np.arange(size) - 0) * points_unit for size in lookup_table.shape]\\n if len(points) == 1:\\n points = points[0]\\n\\n kwargs = {\\n 'bounds_error': False,\\n 'fill_value': np.nan,\\n 'method': interpolation,\\n **kwargs\\n }\\n\\n t = TabularND(points, lookup_table, **kwargs)\\n\\n # TODO: Remove this when there is a new gWCS release\\n # Work around https://github.com/spacetelescope/gwcs/pull/331\\n t.bounding_box = None\\n\\n return t\",\n \"def test_collected_columns_as_table_one_col_from_one(self):\\n col_double, allow_colspan = True, True # as_type == 'table'\\n col_args = ('span', False, {})\\n name, multi_field_row = 'first', False\\n names = [name]\\n row = {name: self.form.fields[name]}\\n col_count = 1\\n expected = [self.form.collect_col_data(name, self.form.fields[name], *col_args) for name in names]\\n for ea in expected:\\n if multi_field_row:\\n ea['css_classes'] = ' '.join(['nowrap', ea['css_classes']])\\n ea['html_head_attr'] = ' class=\\\"nowrap\\\"'\\n val = ea.pop('css_classes', '')\\n val = ' class=\\\"%s\\\"' % val if val else ''\\n if not multi_field_row and col_count > 1:\\n val = val + ' colspan=\\\"{}\\\"'.format(2 * col_count - 1)\\n ea['html_col_attr'] = val\\n col_settings = (multi_field_row, col_count, col_double, allow_colspan)\\n actual = self.form.collect_columns(row, col_settings, *col_args)\\n\\n self.assertEqual(len(expected), len(actual))\\n for expect, got in zip(expected, actual):\\n self.assertEqual(len(expect), len(got))\\n self.assertListEqual(list(expect.keys()), list(got.keys()))\\n self.assertListEqual(list(expect.values()), list(got.values()))\\n self.assertEqual(expected, actual)\",\n \"def slice(self, i, j, n, m):\\n return Table(rows=[list.__getitem__(self, i)[j:j+m] for i in range(i, i+n)])\",\n \"def show_from_database(self, table_model):\\n arr = [4, 1]\\n # TODO\",\n \"def colWithTile(self, pos):\\n\\n\\n return self.colWithBox(pos, [2.0,2.0,2.0])\",\n \"def make_table(m, n):\\n return [[0] * n for _ in range(m)]\",\n \"def for_reverse_triange():\\r\\n\\r\\n for row in range(6,0,-1):\\r\\n print(' '*(6-row), '* '*row)\",\n \"def tiles(rxs):\\n\\n lo = math.inf\\n hi = -math.inf\\n\\n for rx in rxs:\\n lo = min(lo, rx[\\\"has\\\"][0])\\n hi = max(hi, rx[\\\"has\\\"][len(rx[\\\"has\\\"]) - 1])\\n\\n for rx in rxs:\\n t, u = rx['has'], []\\n\\n def of(x, most):\\n return int(max(1, min(most, x)))\\n\\n def at(x):\\n return t[of(len(t)*x//1, len(t))]\\n\\n def pos(x):\\n return math.floor(of(40*(x-lo)/(hi-lo+1E-32)//1, 40))\\n\\n for _ in range(globals.the[\\\"width\\\"] + 1):\\n u.append(\\\" \\\")\\n\\n for i in range(pos(at(.1)), pos(at(.3)) + 1):\\n u[i] = \\\"-\\\"\\n\\n for i in range(pos(at(.7)), pos(at(.9)) + 1):\\n u[i] = \\\"-\\\"\\n\\n u[globals.the[\\\"width\\\"] // 2] = \\\"|\\\"\\n u[pos(at(.5))] = \\\"*\\\"\\n\\n rx[\\\"show\\\"] = \\\"\\\".join(u) + \\\" {\\\" + globals.the[\\\"Fmt\\\"].format(at(.1))\\n\\n for x in [at(.3), at(.5), at(.7), at(.9)]:\\n rx[\\\"show\\\"] += \\\", \\\" + globals.the[\\\"Fmt\\\"].format(x)\\n\\n rx[\\\"show\\\"] += \\\" }\\\"\\n\\n return rxs\",\n \"def __tbl_synthese(table_1_restant, table_terme_supl, nbr):\\n table_synthese = [0 for i in range(len(table_1_restant))]\\n msq1 = (1 << nbr)- 1\\n cpt = 0\\n pteur = 1\\n for ter1, msq in table_terme_supl:\\n for index, ter in enumerate(table_1_restant):\\n if (ter1 & (msq ^ msq1)) == (ter & (msq ^ msq1)):\\n table_synthese[index] |= pteur\\n pteur <<= 1\\n cpt += 1\\n return table_synthese, cpt\",\n \"def print_column():\\n print('+----+----+----+----+')\",\n \"def print_column():\\n print('+----+----+')\",\n \"def initTableView(self):\\r\\n # productive\\r\\n profprint()\\r\\n if self.table == None:\\r\\n # self.keys = (\\\"#\\\")\\r\\n # self.keys = (\\\"#\\\",\\\"Round\\\" ,\\\"Reliability\\\")\\r\\n self.keys = (\\\"#\\\")\\r\\n self.labelStats = {}\\r\\n self.labelStats['Labels'] = []\\r\\n self.items = []\\r\\n if self.model == None:\\r\\n self.model = qt.QStandardItemModel()\\r\\n self.model.setColumnCount(5)\\r\\n self.model.setHeaderData(0, 1, \\\"\\\")\\r\\n self.model.setHeaderData(1, 1, \\\"#\\\")\\r\\n # self.model.setHeaderData(2,1,\\\"R.\\\")\\r\\n # self.model.setHeaderData(3,1,\\\"Reliability\\\")\\r\\n self.model.setHeaderData(2, 1, \\\"Display\\\")\\r\\n self.model.setHeaderData(3, 1, \\\"Reformat\\\")\\r\\n self.model.setHeaderData(4, 1, \\\"Comments\\\")\\r\\n # self.model.setStrechLastSection(True)\\r\\n if self.view == None:\\r\\n self.view = qt.QTableView()\\r\\n self.view.setMinimumHeight(300)\\r\\n self.view.sortingEnabled = True\\r\\n self.view.verticalHeader().visible = False\\r\\n self.view.horizontalHeader().setStretchLastSection(True)\\r\\n\\r\\n # col = 1\\r\\n # for k in self.keys:\\r\\n # # self.view.setColumnWidth(col,15*len(k))\\r\\n # # self.model.setHeaderData(col,1,k)\\r\\n # col += 1\\r\\n self.view.setModel(self.model)\\r\\n self.view.setColumnWidth(0, 18)\\r\\n self.view.setColumnWidth(1, 58)\\r\\n self.view.setColumnWidth(2, 58)\\r\\n self.table = 1\\r\\n self.row = 0\\r\\n self.col = 0\\r\\n slicer.modules.NeedleFinderWidget.analysisGroupBoxLayout.addRow(self.view)\",\n \"def cols(self):\\n\\n return []\",\n \"def column_pack(plateau, num_col, debut, sens):\\n if check_room(plateau, num_col, debut) == False or (sens != 1 and sens != 0): # si plateau n est pas valide ou sens != 1 et 0\\n return \\\"Erreur !\\\"\\n if sens == 1:\\n i = debut # tasser a partie de i\\n while i < 3:\\n set_value(plateau, i, num_col, get_value(plateau, i+1, num_col)) # remplacer la valeur avec la valeur suivant\\n i += 1\\n set_value(plateau, i, num_col, 0)\\n else:\\n i = debut\\n while i > 0:\\n set_value(plateau, i, num_col, get_value(plateau, i-1, num_col)) # remplacer la valeur avec la valeur precedente\\n i -= 1\\n set_value(plateau, i, num_col, 0)\",\n \"def get_formatted_table(images):\\n header = ['CEE (Windows)']\\n table = columned_table(header, [images])\\n return table\",\n \"def _permutate(self, table, block):\\n return list(map(lambda x: block[x], table))\",\n \"def print_table(table_2D, title_list):\\n \\n max_length = [] # max length of item for each column\\n\\n # BELOW VAR NEEDS TO BE FIXED, GOT RID OFF\\n # without this correction table horizontal lines displays unevenly\\n length_correction = 2 \\n\\n # count max length of all elements in a table, so we can print all details in neat columns\\n for row in table_2D:\\n column = 0\\n\\n for item in row:\\n item = str(item)\\n\\n try:\\n if len(item) > max_length[column]:\\n max_length[column] = len(item)\\n column += 1\\n # expand table if needed\\n except IndexError:\\n max_length.append(0)\\n if len(item) > max_length[column]:\\n max_length[column] = len(item)\\n column += 1\\n\\n title_index = \\\"No\\\"\\n\\n # print titles, while keeping columns straight\\n titles = side_sign + \\\" \\\" + title_index + separator_sign\\n for i in range(len(title_list)):\\n # count length of all titles, to check if they are longer than entries\\n if len(title_list[i]) > max_length[i]:\\n max_length[i] = len(title_list[i])\\n\\n titles += title_list[i] + fill(str(title_list[i]), max_length[i]) + separator_sign\\n\\n print(\\\"\\\\n\\\\t/\\\" + fill(\\\"\\\", len(titles.strip())-length_correction, sourrounding_sign) + \\\"\\\\\\\\\\\") # print top line\\n print(\\\"\\\\t\\\" + titles)\\n print(\\\"\\\\t\\\" + side_sign + fill(\\\"\\\", len(titles.strip())-length_correction, sourrounding_sign) + side_sign) # print line below titles\\n\\n table_content = \\\"\\\"\\n # print all game details, while keeping columns straight\\n for row in range(len(table_2D)):\\n table_content += \\\"\\\\t\\\" + side_sign + \\\" \\\" + str(row+1) + fill(str(row+1), max(len(str(row+1)), len(title_index))) + separator_sign\\n for item in range(len(table_2D[row])):\\n table_content += str(table_2D[row][item]) + fill(str(table_2D[row][item]), max_length[item]) + separator_sign\\n table_content += \\\"\\\\n\\\"\\n\\n print(table_content, end=\\\"\\\")\\n print(\\\"\\\\t\\\\\\\\\\\" + fill(\\\"\\\", len(titles.strip())-length_correction, sourrounding_sign) + \\\"/\\\")\",\n \"def mostrar_tablero(mtx, n):\\n # Cabecera de Columnas\\n fila = \\\"/ |\\\"\\n for i in range(n):\\n fila = fila + \\\" \\\" + chr(65+i)\\n print fila\\n print \\\"-\\\"*(2*n+3)\\n # Cabecera de Filas\\n for i in range(n):\\n fila = str(i+1)\\n if i < 9 : fila += \\\" |\\\"\\n else:\\n fila+=\\\"|\\\"\\n for e in range(n):\\n fila = fila+\\\" \\\"+mtx[i][e]\\n print fila\\n fila = \\\"\\\"\\n # Nueva linea\\n print \\\"\\\"\",\n \"def col_diag(self):\\n rows = self._row_type_2d()\\n for i, m in iter_items(self.col_totals):\\n rows[i][i] = m\\n return self.__class__(rows=rows)\",\n \"def inhomoCoeffs(Bulk_Operators, Bdy_Operators, Bulk_second, s=1):\\n\\t\\tRow = []\\n\\t\\tfor Bulk_Op in Bulk_Operators:\\n\\t\\t\\t\\ttable_call = table1.table[0, 0].subs({\\\"Delta\\\":Bulk_Op, \\\"Delta_12\\\":delta_12, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\tRow.append(table_call)\\n\\t\\tfor index in range(len(Bulk_second)):\\n\\t\\t\\t\\tRow.append(0*table1.table[0,0])\\n\\t\\tfor Bdy_Op in Bdy_Operators:\\n\\t\\t\\tif Bdy_Op == 2.0:\\n\\t\\t\\t\\ttable_call = (N-1)*table1.table[1, 0].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\telse:\\n\\t\\t\\t\\ttable_call = table1.table[1, 0].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\tRow.append(table_call)\\n\\t\\tif s==1:\\n\\t\\t\\tXi = symbols('Xi')\\n\\t\\t\\tlast_expr = Xi**((delta_1 + delta_2)/2)\\n\\t\\t\\tlast_elem = last_expr.subs({\\\"Xi\\\":1.00}).evalf()\\n\\t\\t\\tRow.append(last_elem)\\n\\t\\tRow2 = []\\n\\t\\tfor index in range(len(Bulk_Operators)):\\n\\t\\t\\t\\tRow2.append(0*table1.table[0,0])\\n\\t\\tfor Bulk_Op in Bulk_second:\\n\\t\\t\\t\\ttable_call = table1.table[0, 0].subs({\\\"Delta\\\":Bulk_Op, \\\"Delta_12\\\":delta_12, \\\"Xi\\\":1.00})\\n\\t\\t\\t\\tRow2.append(table_call)\\n\\t\\tfor Bdy_Op in Bdy_Operators:\\n\\t\\t\\tif Bdy_Op == 2.0:\\n\\t\\t\\t\\ttable_call = -1*table1.table[1,0].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\telse:\\n\\t\\t\\t\\ttable_call = table1.table[1,0].subs({\\\"Delta\\\":Bdy_Op, \\\"Xi\\\":1.00})\\n\\t\\t\\tRow2.append(table_call)\\n\\t\\tif s==1:\\n\\t\\t\\tXi = symbols('Xi')\\n\\t\\t\\tlast_expr = Xi**((delta_1 + delta_2)/2)\\n\\t\\t\\tlast_elem = last_expr.subs({\\\"Xi\\\":1.00}).evalf()\\n\\t\\t\\tRow2.append(last_elem)\\n\\t\\t\\t\\n\\t\\treturn np.array(Row), np.array(Row2)\",\n \"def unstructured_grid(self, X, Y, Z):\\r\\n uX = []\\r\\n uY = []\\r\\n uZ = []\\r\\n l = self.size[0] * self.size[1]\\r\\n self.Grid = vtk.vtkUnstructuredGrid()\\r\\n for k in range(self.size[2]):\\r\\n n = 0\\r\\n for j in range(self.size[1]):\\r\\n for i in range(self.size[0]):\\r\\n # SW-B\\r\\n swb = 8 * k * l + 4 * l + 2 * self.size[0] * (j + 1) + 2 * n\\r\\n uX.append(X[swb])\\r\\n uY.append(Y[swb])\\r\\n uZ.append(Z[swb])\\r\\n # SE-B\\r\\n seb = 8 * k * l + 4 * l + 2 * self.size[0] * (j + 1) + 2 * n + 1\\r\\n uX.append(X[seb])\\r\\n uY.append(Y[seb])\\r\\n uZ.append(Z[seb])\\r\\n # NE-B\\r\\n neb = 8 * k * l + 4 * l + 2 * self.size[0] * j + 2 * n + 1\\r\\n uX.append(X[neb])\\r\\n uY.append(Y[neb])\\r\\n uZ.append(Z[neb])\\r\\n # NW-B\\r\\n nwb = 8 * k * l + 4 * l + 2 * self.size[0] * j + 2 * n\\r\\n uX.append(X[nwb])\\r\\n uY.append(Y[nwb])\\r\\n uZ.append(Z[nwb])\\r\\n # SW-T\\r\\n swt = 8 * k * l + 2 * self.size[0] * (j + 1) + 2 * n\\r\\n uX.append(X[swt])\\r\\n uY.append(Y[swt])\\r\\n uZ.append(Z[swt])\\r\\n # SE-T\\r\\n sett = 8 * k * l + 2 * self.size[0] * (j + 1) + 2 * n + 1\\r\\n uX.append(X[sett])\\r\\n uY.append(Y[sett])\\r\\n uZ.append(Z[sett])\\r\\n # NE-T\\r\\n net = 8 * k * l + 2 * self.size[0] * j + 2 * n + 1\\r\\n uX.append(X[net])\\r\\n uY.append(Y[net])\\r\\n uZ.append(Z[net])\\r\\n # NW-T\\r\\n nwt = 8 * k * l + 2 * self.size[0] * j + 2 * n\\r\\n uX.append(X[nwt])\\r\\n uY.append(Y[nwt])\\r\\n uZ.append(Z[nwt])\\r\\n\\r\\n n += 1\\r\\n\\r\\n # Set points\\r\\n points = vtk.vtkPoints()\\r\\n points.SetNumberOfPoints(2 * self.size[0] * 2 * self.size[1] * 2 * self.size[2])\\r\\n for i in range(len(uX)):\\r\\n points.SetPoint(i, [uX[i], uY[i], uZ[i]])\\r\\n self.Grid.SetPoints(points)\\r\\n\\r\\n # Set cells\\r\\n cells = vtk.vtkCellArray()\\r\\n cell = vtk.vtkHexahedron()\\r\\n for i in range(len(uX)):\\r\\n if i > 0 and i % 8 == 0:\\r\\n cells.InsertNextCell(cell)\\r\\n cell.GetPointIds().SetId(i % 8, i)\\r\\n cells.InsertNextCell(cell)\\r\\n\\r\\n self.Grid.SetCells(cell.GetCellType(), cells)\",\n \"def mono_table():\\n return Table(\\n {\\n \\\"obs_id\\\": [1, 1, 1, 1, 1, 2],\\n \\\"event_id\\\": [1, 1, 1, 2, 2, 1],\\n \\\"tel_id\\\": [1, 2, 3, 5, 7, 1],\\n \\\"hillas_intensity\\\": [1, 2, 0, 1, 5, 9],\\n \\\"hillas_width\\\": [0.1, 0.2, 0.1, 0.1, 0.2, 0.1] * u.deg,\\n \\\"hillas_length\\\": 3 * ([0.1, 0.2, 0.1, 0.1, 0.2, 0.1] * u.deg),\\n \\\"dummy_tel_energy\\\": [1, 10, 4, 0.5, 0.7, 1] * u.TeV,\\n \\\"dummy_tel_is_valid\\\": [\\n True,\\n True,\\n True,\\n True,\\n False,\\n False,\\n ],\\n \\\"classifier_tel_prediction\\\": [1, 0, 0.5, 0, 0.6, 1],\\n \\\"classifier_tel_is_valid\\\": [\\n True,\\n True,\\n False,\\n True,\\n True,\\n True,\\n ],\\n \\\"disp_tel_alt\\\": [58.5, 58, 62.5, 72, 74.5, 81] * u.deg,\\n \\\"disp_tel_az\\\": [12.5, 15, 13, 21, 20, 14.5] * u.deg,\\n \\\"disp_tel_is_valid\\\": [\\n True,\\n False,\\n True,\\n True,\\n True,\\n True,\\n ],\\n }\\n )\",\n \"def lap_mat(self):\",\n \"def initTableView(self):\\n #productive\\n profprint()\\n if self.table==None:\\n # self.keys = (\\\"#\\\")\\n # self.keys = (\\\"#\\\",\\\"Round\\\" ,\\\"Reliability\\\")\\n self.keys = (\\\"#\\\")\\n self.labelStats = {}\\n self.labelStats['Labels'] = []\\n self.items = []\\n if self.model==None:\\n self.model = qt.QStandardItemModel()\\n self.model.setColumnCount(5)\\n self.model.setHeaderData(0,1,\\\"\\\")\\n self.model.setHeaderData(1,1,\\\"#\\\")\\n # self.model.setHeaderData(2,1,\\\"R.\\\")\\n # self.model.setHeaderData(3,1,\\\"Reliability\\\")\\n self.model.setHeaderData(2,1,\\\"Display\\\")\\n self.model.setHeaderData(3,1,\\\"Reformat\\\")\\n self.model.setHeaderData(4,1,\\\"Comments\\\")\\n # self.model.setStrechLastSection(True)\\n if self.view == None:\\n self.view = qt.QTableView()\\n self.view.setMinimumHeight(300)\\n self.view.sortingEnabled = True\\n self.view.verticalHeader().visible = False\\n self.view.horizontalHeader().setStretchLastSection(True)\\n\\n # col = 1\\n # for k in self.keys:\\n # # self.view.setColumnWidth(col,15*len(k))\\n # # self.model.setHeaderData(col,1,k)\\n # col += 1 \\n self.view.setModel(self.model)\\n self.view.setColumnWidth(0,18)\\n self.view.setColumnWidth(1,58)\\n self.view.setColumnWidth(2,58)\\n self.table = 1\\n self.row=0\\n self.col=0\\n slicer.modules.NeedleFinderWidget.analysisGroupBoxLayout.addRow(self.view)\",\n \"def get_tabular_layour_string(n_cols):\\n token = '@{}c@{}|'\\n layout = '|'\\n for _ in range(n_cols + 1):\\n layout += token\\n return layout\",\n \"def amult(self,coef):\\n new_name = self.getName() + '_' + str(coef)\\n newDataTable = DataTable(new_name)\\n newDataTable.setColumnUnits(self.getColumnUnits())\\n col_names= self.getColumnNames()\\n # Copy the first column as it\\n newDataTable.addColumn(col_names[0],self.getColumn(0))\\n for i in range(1,len(col_names)):\\n c = self.getColumn(i)*coef\\n newDataTable.addColumn(col_names[i],c)\\n pass\\n return newDataTable\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6182871","0.58670676","0.5789016","0.5669425","0.56620336","0.5656002","0.56398475","0.5629267","0.5606348","0.5552602","0.55167204","0.54714936","0.53963476","0.53924036","0.53915703","0.5390585","0.53538346","0.5328843","0.53097725","0.5293032","0.528918","0.5288747","0.5270954","0.5262167","0.5252663","0.5238994","0.5234037","0.52316225","0.5230155","0.52255136","0.52147865","0.5204373","0.5198956","0.5195855","0.51862204","0.518308","0.51719636","0.5169572","0.5169208","0.5162633","0.51611537","0.51515436","0.5147613","0.51266336","0.51202804","0.51189125","0.51183575","0.51062465","0.5102825","0.5099594","0.5096831","0.50890726","0.5084115","0.5072703","0.5067372","0.5061979","0.50599056","0.50519496","0.5051603","0.5048291","0.5047575","0.5046909","0.5046246","0.5041347","0.50391746","0.5038401","0.5033048","0.5027464","0.50239635","0.50234294","0.50222164","0.50134104","0.50118667","0.50107664","0.4991457","0.4989978","0.4987826","0.4987203","0.4982064","0.4973749","0.49669147","0.49623019","0.4961299","0.49610797","0.4957872","0.49573866","0.49570832","0.49547487","0.49536812","0.49523956","0.49478483","0.49446014","0.4943603","0.49415666","0.49390066","0.49359712","0.49338678","0.49338177","0.49313682","0.49309662"],"string":"[\n \"0.6182871\",\n \"0.58670676\",\n \"0.5789016\",\n \"0.5669425\",\n \"0.56620336\",\n \"0.5656002\",\n \"0.56398475\",\n \"0.5629267\",\n \"0.5606348\",\n \"0.5552602\",\n \"0.55167204\",\n \"0.54714936\",\n \"0.53963476\",\n \"0.53924036\",\n \"0.53915703\",\n \"0.5390585\",\n \"0.53538346\",\n \"0.5328843\",\n \"0.53097725\",\n \"0.5293032\",\n \"0.528918\",\n \"0.5288747\",\n \"0.5270954\",\n \"0.5262167\",\n \"0.5252663\",\n \"0.5238994\",\n \"0.5234037\",\n \"0.52316225\",\n \"0.5230155\",\n \"0.52255136\",\n \"0.52147865\",\n \"0.5204373\",\n \"0.5198956\",\n \"0.5195855\",\n \"0.51862204\",\n \"0.518308\",\n \"0.51719636\",\n \"0.5169572\",\n \"0.5169208\",\n \"0.5162633\",\n \"0.51611537\",\n \"0.51515436\",\n \"0.5147613\",\n \"0.51266336\",\n \"0.51202804\",\n \"0.51189125\",\n \"0.51183575\",\n \"0.51062465\",\n \"0.5102825\",\n \"0.5099594\",\n \"0.5096831\",\n \"0.50890726\",\n \"0.5084115\",\n \"0.5072703\",\n \"0.5067372\",\n \"0.5061979\",\n \"0.50599056\",\n \"0.50519496\",\n \"0.5051603\",\n \"0.5048291\",\n \"0.5047575\",\n \"0.5046909\",\n \"0.5046246\",\n \"0.5041347\",\n \"0.50391746\",\n \"0.5038401\",\n \"0.5033048\",\n \"0.5027464\",\n \"0.50239635\",\n \"0.50234294\",\n \"0.50222164\",\n \"0.50134104\",\n \"0.50118667\",\n \"0.50107664\",\n \"0.4991457\",\n \"0.4989978\",\n \"0.4987826\",\n \"0.4987203\",\n \"0.4982064\",\n \"0.4973749\",\n \"0.49669147\",\n \"0.49623019\",\n \"0.4961299\",\n \"0.49610797\",\n \"0.4957872\",\n \"0.49573866\",\n \"0.49570832\",\n \"0.49547487\",\n \"0.49536812\",\n \"0.49523956\",\n \"0.49478483\",\n \"0.49446014\",\n \"0.4943603\",\n \"0.49415666\",\n \"0.49390066\",\n \"0.49359712\",\n \"0.49338678\",\n \"0.49338177\",\n \"0.49313682\",\n \"0.49309662\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5124593"},"document_rank":{"kind":"string","value":"44"}}},{"rowIdx":25693,"cells":{"query":{"kind":"string","value":"Create a table which names each of the CMIP experiments, adds references for each, and outputs the strings necessary for bibtex to put the references in the reference list."},"document":{"kind":"string","value":"def testCMIP6(self):\n\n c = CMIP6()\n c.render(self.testoutput[3])\n for r in c.reference_list:\n print r\n print c.nocite"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __init__(self):\n # simple header only necessary for this table of MIPs\n self.header = '<tr class=\"ename\"><td colspan=\"1\">{{d.name}} ({{mips}})</td></tr>'\n self.mips = 'core MIPS recorded by ES-DOC'\n self._settemplates(self.onecol, self.twocol)\n\n r = Repo()\n c = r.getbyname('CMIP6', 'mips')\n self.doc = c\n self.related = []\n\n # two properties to help the use of the resulting table in a paper\n self.reference_list = []\n # nocite list intended for cutting and pasting directly into a latex document!\n self.nocite = ''\n\n for m in c.sub_projects:\n mdoc = r.getbyname(m.name, 'mips')\n description = mdoc.long_name+' - '\n citations = []\n\n # for these purposees we only want the things with a doi\n # and we want only one, so we have to develop a heuristic to get the right one\n for ci in mdoc.citations:\n cidoc = esd.retrieve(ci.id)\n ref = Reference(cidoc)\n if ref.populated:\n citations.append(ref)\n citations.sort(key=lambda cc: cc.year)\n index = -1\n if len(citations) > 1:\n # start by getting the most recent\n year = citations[-1].year\n index = -1\n for i in range(len(citations)-1):\n if citations[i].year == year:\n if m.name in citations[i].text:\n # it's one of the most recent and it has the MIP name\n # in the document title.\n index = i\n description += citations[index].citestring\n self.reference_list.append(citations[index].text)\n self.nocite += '\\\\nocite{%s}\\n' % citations[index].citeguess\n\n # overwrite the real description for the purpose of this table\n mdoc.description = description\n self.related.append(mdoc)\n\n # want alphabetical order\n self.related.sort(key=lambda mm: mm.name)","def main():\n papers_with_references = add_references_to_papers(PAPERS_FILE, TEXT_DIR)\n citations = match_citations_with_papers(papers_with_references)\n insert_into_citation_table(citations)","def output_name_table(outfile: TextIO, do_print: bool, is_name: bool, itemlist: list, unique_set: set,\n notecnt: int, comcnt: int, refdict: dict, name_table: dict, point_locations: dict) -> None:\n\n def create_location_sublink(x: str) -> str:\n \"\"\"\n create a link to location pages, preserving [] info when applicable\n \"\"\"\n tmpname = strip_location_subtext(x)\n if tmpname in point_locations:\n loc = point_locations[tmpname]\n tmpstr = create_location_link(loc, tmpname, do_print, path=\"../locations/\")\n if tmpname != x:\n tmpstr += x[len(tmpname):]\n tmpstr = tmpstr.replace(\"<!>\", fetch_fa_glyph(\"bad location\"))\n # tmpstr = tmpstr.replace(\"<?>\", fetch_fa_glyph(\"questionable id\"))\n tmpstr = tmpstr.replace(\"<?>\", \"\").strip()\n else:\n tmpstr = x\n return tmpstr\n\n # ---main part of loop---\n first_name = True\n ncols = 5\n if notecnt > 0:\n ncols += 1\n if comcnt > 0:\n ncols += 1\n\n for n in itemlist:\n outfile.write(\" <tr>\\n\")\n if is_name:\n nref = n.cite_key\n else:\n nref = n.name\n if nref in unique_set:\n if first_name:\n first_name = False\n else:\n outfile.write(\" <td class=\\\"rowspacer\\\" colspan=\\\"\" + str(ncols) + \"\\\"> </td>\\n\")\n outfile.write(\" </tr>\\n\")\n outfile.write(\" <tr>\\n\")\n\n if nref == \".\":\n outfile.write(\" <td> </td>\\n\")\n elif is_name: # output citation\n crossref = refdict[nref]\n outfile.write(\" <td><a href=\\\"\" + rel_link_prefix(do_print, \"../references/\") +\n crossref.cite_key + \".html\\\">\" + crossref.citation + \"</a></td>\\n\")\n else: # output species name\n outfile.write(\" <td><a href=\\\"\" + rel_link_prefix(do_print, \"../names/\") +\n name_to_filename(nref) + \".html\\\">\" + format_name_string(nref) + \"</a></td>\\n\")\n\n # common names\n if comcnt > 0:\n if n.common == \".\":\n outfile.write(\" <td> </td>\\n\")\n else:\n outfile.write(\" <td>\" + n.common + \"</td>\\n\")\n outfile.write(\" <td>\" + n.where + \"</td>\\n\")\n unique_set -= {nref}\n else:\n outfile.write(\" <td> </td>\\n\")\n if comcnt > 0:\n outfile.write(\" <td> </td>\\n\")\n outfile.write(\" <td> </td>\\n\")\n\n # applies to...\n if n.context == \"location\":\n outstr = create_location_sublink(n.application)\n outfile.write(\" <td>\" + fetch_fa_glyph(\"location\") + \"location: \" + outstr + \"</td>\\n\")\n elif n.context == \"citation\":\n if n.application in refdict:\n crossref = refdict[n.application]\n if n.application in name_table:\n nstr = n.cite_n\n if nstr == \"0\":\n outfile.write(\" <td>\" + fetch_fa_glyph(\"citation\") + \"citation: \"\n \"<a href=\\\"\" + rel_link_prefix(do_print, \"../references/\") + crossref.cite_key +\n \".html\\\">\" + crossref.citation + \"</a></td>\\n\")\n else:\n if \".\" in nstr:\n try:\n extraref = \" [\" + name_table[n.application][nstr][1] + \"]\"\n refname = name_table[n.application][nstr][0]\n except LookupError:\n if is_name: # only print errors on one pass\n report_error(\"Error in citation: \" + n.cite_key + \" cites\" + nstr +\n \" in \" + n.application)\n extraref = \"\"\n refname = \"\"\n else:\n extraref = \"\" \n try:\n refname = name_table[n.application][int(nstr)]\n except ValueError:\n report_error(\"Citation \" + n.cite_key + \" tried to cite \" + n.application +\n \" #\" + nstr)\n refname = \"\"\n outfile.write(\" <td>\" + fetch_fa_glyph(\"citation\") + \"citation: \"\n \"<a href=\\\"\" + rel_link_prefix(do_print, \"../references/\") + crossref.cite_key +\n \".html\\\">\" + crossref.citation + \"</a> → \" + format_name_string(refname) +\n extraref + \"</td>\\n\")\n else:\n outfile.write(\" <td>\" + fetch_fa_glyph(\"citation\") + \"citation: \"\n \"<a href=\\\"\" + rel_link_prefix(do_print, \"../references/\") + crossref.cite_key +\n \".html\\\">\" + crossref.citation + \"</a></td>\\n\")\n else:\n outfile.write(\" <td>\" + fetch_fa_glyph(\"citation\") + \"citation: \" + n.application +\n \"</td>\\n\")\n if is_name and not do_print: # only print on one pass\n report_error(\"Citation not in DB: \" + n.cite_key + \" cites \" + n.application)\n elif n.context == \"specimen\":\n if n.application == \"?\":\n outfile.write(\" <td>\" + fetch_fa_glyph(\"specimen\") + \"specimen: unknown locality</td>\\n\")\n else:\n outstr = create_location_sublink(n.application)\n outfile.write(\" <td>\" + fetch_fa_glyph(\"specimen\") + \"specimen: \" + outstr + \"</td>\\n\")\n elif n.context == \"sequence\":\n if n.application == \"?\":\n outfile.write(\" <td>\" + fetch_fa_glyph(\"sequence\") + \"sequence: unknown locality</td>\\n\")\n else:\n outstr = create_location_sublink(n.application)\n outfile.write(\" <td>\" + fetch_fa_glyph(\"sequence\") + \"sequence: \" + outstr + \"</td>\\n\")\n\n elif n.context == \"unpublished\":\n outfile.write(\" <td>unpublished name <em class=\\\"species\\\">\" +\n n.application + \"</em></td>\\n\")\n else: # \"n/a\"\n outfile.write(\" <td> </td>\\n\")\n\n # accepted species name\n if n.actual == \"?\":\n outfile.write(\" <td>?</td>\\n\")\n elif n.actual in {\".\", \"=\"}:\n outfile.write(\" <td>TBD</td>\\n\")\n elif n.actual == \"n/a\":\n outfile.write(\" <td> </td>\\n\") \n elif n.actual.startswith(\">\"):\n outfile.write(\" <td><em class=\\\"species\\\">\" + n.actual[1:] + \"</em></td>\\n\")\n elif n.actual.startswith(\"#\"):\n t_rank, t_name = n.actual[1:].split(\"#\")\n outfile.write(\" <td>\" + create_taxon_link(t_rank, t_name, do_print, path=\"../\") + \"</td>\\n\")\n else:\n s = find_species_by_name(n.actual)\n if \"<?>\" in n.application:\n glyphstr = \" \" + fetch_fa_glyph(\"questionable id\")\n else:\n glyphstr = \"\"\n outfile.write(\" <td><a href=\\\"\" + rel_link_prefix(do_print, \"../\") + \"u_\" + n.actual +\n \".html\\\"><em class=\\\"species\\\">\" + s.binomial() + \"</em></a>\" + glyphstr + \"</td>\\n\")\n\n # source of accepted species\n if n.source == \".\": # currently not listed\n outfile.write(\" <td> </td>\\n\")\n elif n.source == \"<\": # original name retained\n outfile.write(\" <td>\" + fetch_fa_glyph(\"original\") + \"Original</td>\\n\")\n elif n.source == \"=\": # automatically computer\n outfile.write(\" <td>\" + fetch_fa_glyph(\"computed\") + \"Computed</td>\\n\")\n else:\n if \";\" in n.source:\n source_list = n.source.split(\";\")\n else:\n source_list = [n.source]\n source_strs = []\n for source in source_list:\n if source in refdict: # another reference\n crossref = refdict[source]\n source_strs.append(\"<a href=\\\"\" + rel_link_prefix(do_print, \"../references/\") +\n crossref.cite_key + \".html\\\">\" + crossref.citation + \"</a>\")\n else: # should start with a >\n tmpsource = source[1:]\n tmpsource = tmpsource.replace(\"MSR:\", \"\")\n tmpsource = tmpsource.replace(\"/\", \"/<br />\")\n tmpsource = tmpsource.replace(\"geography\", fetch_fa_glyph(\"geography\") + \"Geography\")\n tmpsource = tmpsource.replace(\"synonymy\", fetch_fa_glyph(\"synonymy\") + \"Synonymy\")\n source_strs.append(tmpsource)\n outfile.write(\" <td>\" + \", \".join(source_strs) + \"</td>\\n\")\n\n # notes\n if notecnt > 0:\n if n.name_note == \".\":\n outfile.write(\" <td> </td>\\n\")\n else:\n outfile.write(\" <td>\" + replace_species_in_string(n.name_note) + \"</td>\\n\")\n outfile.write(\" </tr>\\n\")\n outfile.write(\" </table>\\n\")","def add_ref_tag(basicSeqs):\r\n\r\n formattedBasicSeqs=list(basicSeqs) \r\n for record in formattedBasicSeqs:\r\n record.id=record.id+'_Ref'\r\n record.name=record.name+'_Ref'\r\n record.description=record.description+'_Ref'\r\n return formattedBasicSeqs","def cite_report(self):\n\n num_cites = np.sum(np.array([q.citation_count for q in self.mypapers]))\n print(\"number of citations = \", num_cites)\n\n for n, p in enumerate(self.mypapers):\n clean_tags = re.compile(\"<.*?>\")\n title = re.sub(clean_tags, \"\", p.title[0])\n tt = textwrap.wrap(title, 60)\n print(f\"{n+1:3} | {p.citation_count:4} {tt[0]}\")\n if len(tt) > 1:\n for line in tt[1:]:\n print(\"{:3} | {:4} {}\".format(\"\", \"\", line))\n print(\"{:3} | {:4} {}\".format(\"\", \"\", \"\"))","def add_ref(doc_name, bib_name, keep_label=False, slides=False):\n bib_path = bib_name # os.path.join(static_path, \"tex\", bib_name)\n if not slides:\n keep_label = True\n with open(doc_name, \"r\") as f:\n _file = f.read()\n # find citations\n match = re.findall(r\"\\[@.*?\\]\", _file)\n references = []\n # print(match)\n for cit in match:\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\".html\", delete=True)\n tmp = tempfile.NamedTemporaryFile(suffix=\".md\", delete=True)\n with open(tmp.name, \"w\") as md_file:\n # Open the file for writing.\n md_file.write(cit)\n\n pandoc_command = [\n \"pandoc\",\n \"-C\",\n tmp.name,\n \"--bibliography\",\n bib_path,\n \"--csl\",\n \"./templates/my-csl.csl\",\n \"-o\",\n tmp_cite_html.name,\n ]\n if not slides:\n for tag in [\"--metadata\", \"link-citations=true\"]:\n pandoc_command.append(tag)\n output = subprocess.check_output(\n pandoc_command, stderr=subprocess.STDOUT\n ).decode(\"utf-8\")\n print(output.rstrip())\n tmp.close()\n with open(tmp_cite_html.name, \"r\") as cite_html:\n # Open the file for writing.\n cit_new = cite_html.read()\n # print(cit_new)\n if not keep_label:\n # remove first line\n cit_new = \"\\n\".join(cit_new.splitlines()[1:])\n else:\n lines = cit_new.splitlines()\n # remove the <p> tags\n lines[0] = lines[0][3:-4]\n cit_new = \"\\n\".join(lines)\n if slides:\n _file = _file.replace(cit, cit_new)\n else:\n _file = _file.replace(cit, lines[0])\n # collect the references\n references.append(\"<p>\")\n references.append(\"\\n\".join(lines))\n references.append(\"</p>\")\n # paste_refs_end()\n tmp_cite_html.close()\n if slides:\n with open(doc_name, \"w\") as f:\n f.write(_file)\n if not slides:\n if references == []:\n _file=clean_html_refs(_file)\n else:\n _file = _file.replace(\"<bibliography-placeholder>\", \"\\n\".join(references))\n with open(doc_name, \"w\") as f:\n f.write(_file)\n return","def formatJointTableForLaTeX(joints):\n (varList, atoms, probs) = joints\n cols = len(varList) + len (probs[0][1])\n with open(\"table1.tex\",\"w\") as out:\n out.write (\"\\\\begin{tabular}{|\" + \"|\".join([\"c\"]*(cols-2))+\"||c|c|}\\n\")\n out.write (\"\\\\hline\\n\")\n # Table header\n out.write (\" & \".join(varList) + \" & \" + \" & \".join([a for a in atoms]) + \" & Joint $p$ & ln~$p$ \\\\\\\\ \\\\hline\\n\")\n # Table rows\n logps = []\n for (grounding, probs) in probs:\n out.write (\" & \".join([val for (var, val) in grounding.varList]) + \" & \" +\n \" & \".join([str(n.val)+\" ({:.1f})\".format(p) for (n,p) in probs[:-2]]) +\n \" & {:.2f}\".format(probs[-2]) + \" & {:.2f}\".format(probs[-1]) + \"\\\\\\\\\\n\")\n logps.append(probs[-1])\n # A line to indicate there are further entries in the DB\n out.write(\" & \".join([\"\\ldots\"]*cols) + \"\\\\\\\\\\n\")\n # Close environment\n out.write (\"\\\\hline\\n\\\\end{tabular}\\n\")\n\n with open(\"tab1plogp.tex\",\"w\") as plogp:\n plogp.write(\"\\\\newcommand{\\\\pseudologp}{\"+\"{:.2f}\".format(sum(logps)/len(logps))+\"}\\n\")","def insert_into_citation_table(citations):\n cursor = connection.cursor()\n cursor.execute(\n 'DROP TABLE IF EXISTS Citations;'\n 'CREATE TABLE Citations(sourcePaperId INT, targetPaperId INT, citationId INT NOT NULL AUTO_INCREMENT PRIMARY KEY);'\n )\n cursor.close()\n i = 0\n\n for citation in citations:\n print i\n i+=1\n cursor = connection.cursor()\n cursor.execute(\n 'INSERT INTO Citations (sourcePaperId, targetPaperId) VALUES '\n '((SELECT PaperId FROM Papers WHERE DOI = %s),(SELECT PaperId FROM Papers WHERE DOI = %s));'\n ,[citation['source'].encode('UTF-8'),citation['target'].encode('UTF-8')])\n cursor.close()","def main():\n ref_seq = {}\n ent_spe_sero = {}\n tag_dict = {\"Contigs_with_VP1\":\"contigs\", \"P1_sequences\":\"p1\",\n \"VP1_sequences\":\"vp1\", \"5UTR_sequences\":\"5utr\", \"3D_sequences\":\"3d\"}\n args = get_arguments()\n # Load query elements\n print(\"Load resume file\")\n (query_dict, classify_list,\n classify_specie_list, serotype_list) = get_query(args.resume_file,\n args.tag,\n args.incomplete)\n print(\"{} descriptions loaded\".format(len(query_dict)))\n # Load specie association\n if args.ent_serotype_file and args.template_seq_file:\n # Load enterovirus serotype\n print(\"Load enterovirus serotype association\")\n ent_spe_sero = load_spe_sero(args.ent_serotype_file)\n # Load template sequence\n print(\"Load template sequence\")\n ref_seq = get_template_sequence(args.template_seq_file, ent_spe_sero)\n # Grab query sequence in the database\n print(\"Load database sequence\")\n sequence_data = get_sequence(query_dict, args.fasta_file)\n print(\"{} sequences loaded\".format(len(sequence_data)))\n # Write the new fasta file\n print(\"Write the new fasta\")\n write_sequence(args.results, sequence_data, query_dict, classify_list,\n tag_dict[args.tag], ref_seq, ent_spe_sero)\n #print(save_association)\n print(\"Write the itol label\")\n write_itol_label(args.itol_dir, sequence_data, query_dict, classify_list,\n tag_dict[args.tag])\n print(\"Write the itol tree color\")\n write_itol_tree_color(args.itol_dir, sequence_data, query_dict, classify_specie_list, serotype_list,\n tag_dict[args.tag])\n print(\"Done\")","def compute_species_from_citation_linking(citelist: list) -> None:\n # for i, cite in enumerate(tqdm(citelist)):\n unrecorded_xrefs = []\n recorded_refs = set()\n for i, cite in enumerate(citelist):\n recorded_refs.add(cite.cite_key)\n if cite.actual == \"=\":\n cname = \"\"\n crossnames = collections.Counter()\n for j in range(i): # only look at entries up to the current one\n tmp = citelist[j]\n if (tmp.cite_key == cite.application) and match_num_ref(tmp.name_key, cite.cite_n):\n cname = tmp.name\n crossnames.update([tmp.actual])\n if len(crossnames) == 0:\n unrecorded_xrefs.append([cite.cite_key, cite.application, cite.name_key, cite.cite_n])\n elif len(crossnames) == 1:\n cite.actual = list(crossnames.keys())[0]\n else:\n # find name(s) with largest count\n mcnt = max(crossnames.values())\n keylist = []\n for key in crossnames:\n if crossnames[key] == mcnt:\n keylist.append(key)\n\n if len(keylist) == 1:\n cite.actual = keylist[0]\n else:\n cite_name = cite.name.lower()\n while cite_name.find(\" \") > -1:\n cite_name = cite_name[cite_name.find(\" \")+1:]\n while cname.find(\" \") > -1:\n cname = cname[cname.find(\" \")+1:]\n\n if cite_name in keylist:\n cite.actual = cite_name\n elif cname in keylist:\n cite.actual = cname\n else:\n cite.actual = keylist[0]\n\n if cite.name_note == \".\":\n cite.name_note = \"in part\"\n else:\n cite.name_note = \"in part; \" + cite.name_note\n\n for x in unrecorded_xrefs:\n if x[1] in recorded_refs:\n report_error(\"Reference {} ({}) does not appear until after citation from {} ({})\".format(x[1], x[3],\n x[0], x[2]))","def references(name, tag):\n\n gen_refs = \"\\n\".join([''.join([\"J. Bartels, The technique of scaling \",\n \"indices K and Q of geomagnetic activity, \",\n \"Ann. Intern. Geophys. Year 4, 215-226, \",\n \"1957.\"]),\n ''.join([\"J. Bartels,The geomagnetic measures for \",\n \"the time-variations of solar corpuscular \",\n \"radiation, described for use in \",\n \"correlation studies in other geophysical \",\n \"fields, Ann. Intern. Geophys. Year 4, \",\n \"227-236, 1957.\"]),\n ''.join([\"P.N. Mayaud, Derivation, Meaning and Use \",\n \"of Geomagnetic Indices, Geophysical \",\n \"Monograph 22, Am. Geophys. Union, \",\n \"Washington D.C., 1980.\"]),\n ''.join([\"G.K. Rangarajan, Indices of magnetic \",\n \"activity, in Geomagnetism, edited by I.A. \",\n \"Jacobs, Academic, San Diego, 1989.\"]),\n ''.join([\"M. Menvielle and A. Berthelier, The \",\n \"K-derived planetary indices: description \",\n \"and availability, Rev. Geophys. 29, 3, \",\n \"415-432, 1991.\"])])\n refs = {'kp': {'': gen_refs, 'forecast': gen_refs, 'recent': gen_refs}}\n\n return refs[name][tag]","def references_list( self, theWeaver ):\n return [ (c.name, c.seq) \n for c in theWeaver.reference_style.chunkReferencedBy( self ) ]","def extract_references(text, preprocessor, model):\n has_reference_section, reference_section, non_reference_section = preprocess_reference_text(text)\n reference_text = reference_section if has_reference_section else non_reference_section\n fragment = preprocessor(reference_text)\n out = model(fragment.idx).argmax(dim=2).cpu().numpy()\n\n buffer = ''\n found_citations = []\n in_citation = False\n for char, pred in zip(fragment.text, out[0, :]):\n if pred == 2:\n in_citation = True\n if pred == 3:\n in_citation = False\n if pred in [2, 3]:\n if buffer:\n found_citations.append(buffer)\n buffer = char\n elif pred == 1:\n buffer += char\n elif pred == 0:\n if in_citation:\n buffer += char\n else:\n if buffer:\n found_citations.append(buffer)\n buffer = ''\n return found_citations","def _populate(self):\n\n # Assume the first word is what we want, and we can find well formed years\n # This sucks, but will work for these ones.\n # Roll on bibtex for citations in the CIM.\n\n citation_detail = self.doc.citation_detail\n author = citation_detail.split(',')[0]\n match = '([^\\w])19|20\\d\\d([^\\w])*?'\n m = re.search(match, citation_detail)\n if m:\n year = m.group(0)\n else:\n year = None\n\n # one error in existing es-doc content to be fixed:\n if 'van Vuuren DP' in author:\n author = 'van Vuuren'\n print 'applying vv fix'\n\n self.year = int(year)\n\n # We assume that this table will have entries which ne\n\n # I use the first three letters of a an authors name, and for\n # three or more authors, EA, and then the year for my bibtex citation string\n self.citeguess = author[0:3] + 'EA' + year[2:]\n # This is what will appear in the table:\n self.citestring = '%s et al. (%s)' % (author, year)\n # Keep this for a reference list for checking against the eventual bibtex reference list.\n self.text = citation_detail","def _showStringXrefs(self):\n\n # Retrieve some config values\n show_misc.entropy = self.config.calculate_misc.entropy\n show_unique_s = self.config.display_unique_strings\n\n self._console_output(\"Calculating string references...\")\n\n self.ba.calculate_strings_list()\n s_ref_list = self.ba.get_string_references()\n\n # Found any references at all?\n nrows = len(s_ref_list)\n if not nrows:\n self._console_output(\"[!] No string references found\", err = True)\n return\n\n if show_misc.entropy:\n self.table.setColumnCount(3)\n self.table.setHorizontalHeaderLabels((\"Address\", \"String\", \"misc.entropy\"))\n\n else:\n self.table.setColumnCount(2)\n self.table.setHorizontalHeaderLabels((\"Address\", \"String\"))\n\n self.table_label.setText(\"String references in current function\")\n self.table.clearContents()\n self.table.setRowCount(0)\n\n # Fill the table\n displayed_strings = []\n\n idx = 0\n for (addr, s) in s_ref_list:\n if show_unique_s and s in displayed_strings:\n continue\n\n displayed_strings.append(s)\n\n self.table.insertRow(idx)\n addr_item = QTableWidgetItem(\"%08x\" % addr)\n addr_item.setFlags(addr_item.flags() ^ QtCore.Qt.ItemIsEditable)\n string_item = QTableWidgetItem(\"%s\" % s)\n string_item.setFlags(string_item.flags() ^ QtCore.Qt.ItemIsEditable)\n\n self.table.setItem(idx, 0, addr_item)\n self.table.setItem(idx, 1, string_item)\n\n if show_misc.entropy:\n misc.entropy_item = cw.NumQTableWidgetItem(\"%.4f\" % misc.entropy(s))\n self.table.setItem(idx, 2, misc.entropy_item)\n\n idx += 1","def enrich_textrefs(self, db):\n tr_list = db.select_all(db.TextRef,\n db.TextContent.text_ref_id == db.TextRef.id,\n db.TextContent.source == self.my_source,\n db.TextRef.manuscript_id.is_(None))\n file_list = self.ftp.get_csv_as_dict('filelist.csv', header=0)\n pmcid_mid_dict = {entry['PMCID']: entry['MID'] for entry in file_list}\n pmid_mid_dict = {entry['PMID']: entry['MID'] for entry in file_list\n if entry['PMID'] is not '0'}\n for tr in tr_list:\n if tr.pmcid is not None:\n tr.manuscript_id = pmcid_mid_dict[tr.pmcid]\n elif tr.pmid is not None and tr.pmid in pmid_mid_dict.keys():\n tr.manuscript_id = pmid_mid_dict[tr.pmid]\n db.commit(\"Could not update text refs with manuscript ids.\")\n return","def populate_crossreference_dictionary(self):\n master_crossreference_dictionary = dict()\n\n # If additional crossreferences need to be used to find interactors, they can be added here.\n # Use the crossreference prefix as the dictionary name.\n # Also add a regex entry to the resolve_identifier function.\n master_crossreference_dictionary['UniProtKB'] = dict()\n master_crossreference_dictionary['ENSEMBL'] = dict()\n master_crossreference_dictionary['NCBI_Gene'] = dict()\n master_crossreference_dictionary['RefSeq'] = dict()\n\n for key in master_crossreference_dictionary:\n self.logger.info('Querying for %s cross references.', key)\n with Neo4jHelper().run_single_parameter_query(self.query_xrefs, key) as result:\n for record in result:\n cross_ref_record = None\n # Modify the cross reference ID to match the PSI MITAB format if necessary.\n # So far, this is just converting 'NCBI_Gene' to 'entrez gene/locuslink'.\n if record['cr.globalCrossRefId'].startswith('NCBI_Gene'):\n cross_ref_record_split = record['cr.globalCrossRefId'].split(':')[1]\n cross_ref_record = 'entrez gene/locuslink:' + cross_ref_record_split\n else:\n cross_ref_record = record['cr.globalCrossRefId']\n\n # The crossreference dictionary is a list of genes\n # linked to a single crossreference.\n # Append the gene if the crossref dict entry exists.\n # Otherwise, create a list and append the entry.\n if cross_ref_record.lower() in master_crossreference_dictionary[key]:\n master_crossreference_dictionary[key][cross_ref_record.lower()].append(record['g.primaryKey'])\n else:\n master_crossreference_dictionary[key][cross_ref_record.lower()] = []\n master_crossreference_dictionary[key][cross_ref_record.lower()].append(record['g.primaryKey'])\n\n # The ids in PSI-MITAB files are lower case, hence the .lower() used above.\n\n return master_crossreference_dictionary","def table_of_cores():\n return (\n '### Magnetic core library '\n f'(from [{LIBRARY_PATH}]({LIBRARY_PATH}))\\n' +\n 'Variable `cores[\\'<some key\\']` can be used for adding the cores ' +\n 'below to the design parameters.\\n\\n' +\n format_markdown_table(\n ['key', 'permeability $ \\\\mu $', '$ A_e $', '$ l_e $', '$ V_e $',\n '$ B_{sat} $', 'note'],\n [\n [key, str(round(c.mu, 2)), str(round(c.A_e, 2)),\n str(round(c.l_e, 2)), str(round(c.V_e, 2)),\n str(c.B_sat), str(c.note)]\n for key, c in cores.items()\n ]\n ))","def get_references(cls, pmids):\n\n references = cls.query.filter(cls.pmid.in_(pmids)).all()\n citations = {}\n\n for reference in references:\n citation_text = reference.authors + \". (\" + str(\n reference.year) + \"). \" + reference.title + \" \" + reference.journal + \".\"\n citations[reference.pmid] = citation_text\n\n return citations","def create_output(self, bib):\n for b in bib:\n if isinstance(b, ReferenceErrorInfo):\n self.error_count += 1\n if self.args.comments:\n self.output.append(b.bibtex())\n if not self.args.quiet:\n self.messages.append(str(b))\n else:\n self.output.append(b.bibtex())","def add_references_to_papers(infile, dir):\n papers = json.load(open(infile))\n for paper in papers:\n for file in os.listdir(dir):\n if file.split(\".txt\")[0] == paper['doi']: # Must find the correct file to parse\n filename = TEXT_DIR+file\n refs =extract_references_from_txt(filename) #Uses the text files to find references\n paper['references']=refs\n return papers","def _export_reference_representations(self):\n\n self.logger.msg1(\"Saving reference representations\")\n general_refset, _ = get_refsets(self.dbpath)\n general_refset.save(self.rootpath+\"-references\", \"phenotype\")","def CreateGeneModels(genes_cmpt, transcripts_cmpt, exons_cmpt, utr3_cmpt, utr5_cmpt, cds_cmpt):\n gene_counter, gene_models = 1, []\n for gene_entry in genes_cmpt: ## Figure out the genes and transcripts associated feature \n if gene_entry in transcripts_cmpt:\n gene=init_gene() \n gene['id']=gene_counter\n gene['name']=gene_entry[1]\n gene['chr']=genes_cmpt[gene_entry]['chr']\n gene['source']=genes_cmpt[gene_entry]['source']\n gene['start']=genes_cmpt[gene_entry]['start']\n gene['stop']=genes_cmpt[gene_entry]['stop']\n gene['strand']=genes_cmpt[gene_entry]['strand']\n if not gene['strand'] in ['+', '-']:\n gene['strand']='.' # Strand info not known replaced with a dot symbol instead of None, ?, . etc.\n if len(transcripts_cmpt[gene_entry])>1:\n gene['is_alt_spliced'] = 1\n gene['is_alt'] = 1\n\t gtype=[]\n for tids in transcripts_cmpt[gene_entry]: ## transcript section related tags \n gene['transcripts'].append(tids['ID'])\n\t\tgtype.append(tids['type'])\n exon_cod, utr5_cod, utr3_cod, cds_cod = [], [], [], []\n if (gene['chr'], tids['ID']) in exons_cmpt:\n exon_cod = [[feat_exon['start'], feat_exon['stop']] for feat_exon in exons_cmpt[(gene['chr'], tids['ID'])]]\n if (gene['chr'], tids['ID']) in utr5_cmpt:\n utr5_cod = [[feat_utr5['start'], feat_utr5['stop']] for feat_utr5 in utr5_cmpt[(gene['chr'], tids['ID'])]]\n if (gene['chr'], tids['ID']) in utr3_cmpt:\n utr3_cod = [[feat_utr3['start'], feat_utr3['stop']] for feat_utr3 in utr3_cmpt[(gene['chr'], tids['ID'])]]\n if (gene['chr'], tids['ID']) in cds_cmpt:\n cds_cod = [[feat_cds['start'], feat_cds['stop']] for feat_cds in cds_cmpt[(gene['chr'], tids['ID'])]]\n if len(exon_cod) == 0: ## build exon coordinates from UTR3, UTR5 and CDS\n if cds_cod != []:\n exon_cod=createExon(gene['strand'], utr5_cod, cds_cod, utr3_cod) \n\n if gene['strand']=='-': ## general order to coordinates\n if len(exon_cod) >1:\n if exon_cod[0][0] > exon_cod[-1][0]:\n exon_cod.reverse()\n if len(cds_cod) >1:\n if cds_cod[0][0] > cds_cod[-1][0]: \n cds_cod.reverse()\n if len(utr3_cod) >1:\n if utr3_cod[0][0] > utr3_cod[-1][0]: \n utr3_cod.reverse()\n if len(utr5_cod) >1:\n if utr5_cod[0][0] > utr5_cod[-1][0]:\n utr5_cod.reverse()\n\n tis, cdsStop, tss, cleave = [], [], [], [] ## speacial sited in the gene region \n if cds_cod != []:\n if gene['strand'] == '+':\n tis = [cds_cod[0][0]]\n cdsStop = [cds_cod[-1][1]-3]\n elif gene['strand'] == '-':\n tis = [cds_cod[-1][1]]\n cdsStop = [cds_cod[0][0]+3]\n if utr5_cod != []:\n if gene['strand'] == '+':\n tss = [utr5_cod[0][0]]\n elif gene['strand'] == '-':\n tss = [utr5_cod[-1][1]]\n if utr3_cod != []:\n if gene['strand'] == '+':\n cleave = [utr3_cod[-1][1]]\n elif gene['strand'] == '-':\n cleave = [utr3_cod[0][0]]\n\n cds_status, exon_status, utr_status = 0, 0, 0 ## status of the complete elements of the gene\n if cds_cod != []: ## adding phase to the CDS region \n cds_cod_phase = addCDSphase(gene['strand'], cds_cod)\n cds_status = 1\n gene['cds_exons'].append(cds_cod_phase)\n\n if exon_cod != []: \n exon_status = 1\n if utr5_cod != [] or utr3_cod != []: \n utr_status = 1\n if cds_status != 0 and exon_status != 0 and utr_status != 0:\n gene['transcript_status'].append(1)\n else:\n gene['transcript_status'].append(0)\n\n if exon_cod: ## final check point for a valid gene model \n gene['exons'].append(exon_cod)\n gene['utr3_exons'].append(utr3_cod)\n gene['utr5_exons'].append(utr5_cod)\n gene['tis'].append(tis)\n gene['cdsStop'].append(cdsStop)\n gene['tss'].append(tss)\n gene['cleave'].append(cleave) \n\t \n\t gtype=list(set(gtype)) ## different types \n gene['gene_info']=dict(ID=gene_entry[1],\n\t\t\t\tSource=genes_cmpt[gene_entry]['source'],\n\t\t\t\tType=gtype)\n gene=FeatureValueFormat(gene) ## get prepare for MAT writing \n gene_counter+=1\n gene_models.append(gene)\n return gene_models","def make_bibtex(self):\n\n\t\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, ","def perf2latex(latex_fn, all_perf, metrics_name, slice_v, cam_v):\n slice_num = slice_v.shape[0]\n\n f = open('%s'%latex_fn, 'w')\n f.write(\"\\\\documentclass{article}\\n\")\n f.write(\"\\\\usepackage[utf8]{inputenc}\\n\")\n f.write(\"\\\\usepackage{booktabs} \\n\")\n f.write(\"\\\\usepackage[]{float}\\n\")\n f.write(\"\\\\usepackage[margin=1.2in]{geometry}\\n\")\n f.write(\"\\\\begin{document}\\n\\n\")\n\n for m_name in metrics_name:\n print(m_name)\n f.write('\\\\begin{table}[tbh]\\n')\n f.write('\\\\begin{center}\\n')\n f.write('\\\\begin{tabular}{|*{%d}{c|}}\\n'%(slice_num + 1))\n f.write('\\\\hline\\n')\n f.write(' Survey')\n #for slice_idx, slice_id in enumerate(slice_cam_id[:-1]):\n for j, (slice_id, cam_id) in enumerate(zip(slice_v, cam_v)):\n f.write(' & %d\\_c%d'%(slice_id, cam_id))\n f.write(' \\\\\\\\ \\n')\n f.write('\\\\hline\\n')\n\n m = all_perf[m_name]\n print(m.shape)\n survey_num = m.shape[0]\n for i in range(survey_num):\n f.write('%d'%(i))\n for j in range(slice_num):\n f.write(' & %.3f'%m[i,j])\n f.write(' \\\\\\\\ \\n')\n\n f.write('\\\\hline\\n')\n f.write('\\\\end{tabular}\\n')\n f.write('\\\\end{center}\\n')\n f.write('\\\\caption{Metric: %s}\\n'%(m_name))\n f.write('\\\\end{table}\\n\\n\\n')\n\n f.write('\\\\end{document}\\n')\n print('\\\\end{document}\\n')\n \n f.close()","def collect_citation_metadata(\n metadata: dict, references: List[pybtex.database.Entry]\n) -> dict:\n # Author list\n citation_authors = []\n for author_tier in [\"Core\", \"Developers\", \"Contributors\"]:\n for author in metadata[\"Authors\"][author_tier][\"List\"]:\n family_names, given_names = author[\"Name\"].split(\", \")\n citation_author = {\n \"family-names\": family_names,\n \"given-names\": given_names,\n }\n if \"Orcid\" in author:\n citation_author[\"orcid\"] = (\n \"https://orcid.org/\" + author[\"Orcid\"]\n )\n if \"Affiliations\" in author and len(author[\"Affiliations\"]) > 0:\n citation_author[\"affiliation\"] = \" and \".join(\n author[\"Affiliations\"]\n )\n citation_authors.append(citation_author)\n # References in CITATION.cff format\n citation_references = [to_cff_reference(entry) for entry in references]\n return {\n \"cff-version\": \"1.2.0\",\n \"message\": (\n \"Please cite SpECTRE in any publications that make use of its code\"\n \" or data. Cite the latest version that you use in your\"\n \" publication. The citation for this version is listed below.\"\n ),\n \"title\": metadata[\"Name\"],\n \"url\": metadata[\"Homepage\"],\n \"repository-code\": \"https://github.com/\" + metadata[\"GitHub\"],\n \"version\": metadata[\"Version\"],\n \"date-released\": metadata[\"PublicationDate\"],\n \"doi\": metadata[\"Doi\"],\n \"authors\": citation_authors,\n \"keywords\": metadata[\"Keywords\"],\n \"license\": metadata[\"License\"],\n \"references\": citation_references,\n }","def column_creator(path):\n if not os.path.exists(path+'tables'):\n os.makedirs(path+'tables')\n\n\n # Sequences\n if os.path.exists(path+'SEQ.txt'):\n with open(os.path.join(path+'SEQ.txt')) as f1, open(os.path.join(path+'tables/sequences_table.txt'), 'a') as f2:\n c = Counter(x.strip() for x in f1)\n for x in c:\n f2.write(\"%s\\t%s\\n\" % (x, str(c[x])))\n f1.close()\n f2.close()\n\n # Modifications\n if os.path.exists(path + 'modifications.txt'):\n\n with open(os.path.join(path+'modifications.txt')) as f1, open(os.path.join(path+'tables/modifications_table.txt'), 'a') as f2:\n c = Counter(x.strip() for x in f1)\n for x in c:\n f2.write(\"%s\\t%s\\n\" % (x, str(c[x])))\n f1.close()\n f2.close()\n\n # Spectrum identify:\n if os.path.exists(path + 'spectrum_identify.txt'):\n\n with open(os.path.join(path+'spectrum_identify.txt')) as f1, open(path+'tables/spectrum_ide_table.txt', 'a') as f3:\n lines1 = f1.read().count('\\n')\n f3.write(\"%s\\n%s\\n\" % (\"Spectrum Number\",lines1))\n f1.close()\n f3.close()\n\n if os.path.exists(path + 'spectrum_unidentify.txt'):\n with open(os.path.join(path+'spectrum_unidentify.txt')) as f2, open(path+'tables/spectrum_unide_table.txt', 'a') as f3:\n lines2 = f2.read().count('\\n')\n f3.write(\"%s\\n%s\\n\" % (\"Spectrum Number\",lines2))\n f2.close()\n f3.close()\n\n if os.path.exists(path+'taxonomy_identify.txt'):\n # Taxonomy ide:\n with open(os.path.join(path+'taxonomy_identify.txt')) as f1, open(os.path.join(path+'tables/taxonomy_ide_table.txt'), 'a') as f2:\n c = Counter(x.strip() for x in f1)\n for x in c:\n f2.write(\"%s\\t%s\\n\" % (x, str(c[x])))\n f1.close()\n f2.close()\n\n\n if os.path.exists(path + 'taxonomy_unidentify.txt'):\n # Taxonomy unide:\n with open(os.path.join(path+'taxonomy_unidentify.txt')) as f1, open(os.path.join(path+'tables/taxonomy_unide_table.txt'), 'a') as f2:\n c = Counter(x.strip() for x in f1)\n for x in c:\n f2.write(\"%s\\t%s\\n\" % (x, str(c[x])))\n f1.close()\n f2.close()","def main(argv):\n if len(argv) == 0 or argv == None:\n print(HELP_TXT)\n sys.exit(2)\n try:\n opts, args = getopt.getopt(argv,\"dhmb:\",[\"debug\", \"help\", \"markdown\", \"biblio=\"])\n except getopt.GetoptError:\n print(HELP_TXT)\n sys.exit(2)\n\n testing = False\n markdown = False\n bibtex_filename = \"library.bib\"\n \n for opt, arg in opts:\n if opt in ('-h', '--help'):\n print(HELP_TXT)\n sys.exit()\n elif opt in ('-d', '--debug'):\n testing = True\n print(\"Fetching of DOI and printing metadata, but not adding to bibtex or creating markdown.\")\n elif opt in ('-b', '--biblio'):\n bibtex_filename = arg\n elif opt in ('-m', '--markdown'):\n markdown = True\n print(\"Writing entry to bibtex file but not creating a markdown file.\")\n\n if len(args) == 0:\n print(\"Error: At least one DOI must be provided.\")\n sys.exit(2)\n\n for doi in args:\n #Get the metadata from crossref.org\n res = doi2json(doi)\n \n #extract\n meta = extract_metadata(res)\n \n #check if reference exists\n citation_found = True\n letters = list(string.ascii_lowercase)\n try:\n with open(bibtex_filename, 'r') as fobj:\n text = fobj.read().strip()\n tmp_key = meta['citationkey']\n for letter in letters:\n if tmp_key in text:\n tmp_key = meta['citationkey'] + letter\n else:\n meta['citationkey'] = tmp_key\n break\n except FileNotFoundError:\n pass\n\n #Then write if not testing\n if testing:\n print(\"DOI RESULTS:\")\n for k,v in res.items():\n if type(v) is list:\n print(k + ': ' + str(v) + '\\n')\n else:\n print(k + ': \"' + str(v) + '\"\\n')\n print(\"PARSED METADATA:\")\n for k,v in meta.items():\n if type(v) is list:\n print(k + ': ' + str(v) + '\\n')\n else:\n print(k + ': \"' + str(v) + '\"\\n')\n else:\n if not os.path.isfile(bibtex_filename):\n print(\"Bibtex file {} does not exist, creating it.\".format(bibtex_filename))\n\n #Add the metadata to the bibtex reference\n with open(bibtex_filename, \"a+\") as f:\n s = \",\".join([\n \"\\n@article{\" + meta['citationkey'],\n \"\\nauthor = {\" + \" and \".join(meta['authors']) + \"}\",\n \"\\ndoi = {\" + meta['doi'] + \"}\",\n \"\\nissn = {\" + meta['issn'] + \"}\",\n \"\\njournal = {\" + meta['container'] + \"}\",\n \"\\npublisher = {\" + meta['publisher'] + \"}\",\n \"\\nnumber = {\" + meta['issue'] + \"}\",\n \"\\npages = {\" + meta['pages'] + \"}\",\n \"\\ntitle = {\" + meta['source-title'] + \"}\",\n \"\\nurl = {\" + meta['link'] + \"}\",\n \"\\nvolume = {\" + meta['volume'] + \"}\",\n \"\\nyear = {\" + meta['year'] + \"}\\n}\\n\\n\"\n ])\n f.write(s)\n \n print(\"reference {} from {} added to {}!\\n\".format(meta['citationkey'], meta['container'], bibtex_filename))\n \n # create the markdown notes file\n if markdown:\n subject_dir = re.sub(r'\\([^)]*\\)', '', meta['subjects'][0]).strip().lower().replace(\" \", \"_\").replace(\",\",\"\")\n md_dir = \"/\".join([HOME_DIR, REPO_DIR, MD_DIR, subject_dir])\n os.mkdir(md_dir) if os.path.isdir(md_dir) == False else None\n filename = \"/\".join([md_dir, meta['citationkey'] + \".md\"])\n with open(filename, \"w\") as f:\n f.write(\"---\\nlayout: mathpost\\n\")\n for k,v in meta.items():\n try:\n if type(v) is list:\n f.write(k + ': ' + str(v) + '\\n')\n else:\n f.write(k + ': \"' + str(v) + '\"\\n')\n except UnicodeEncodeError as e:\n print(\"Unicode Error. Some character(s) may be wrong.\")\n print(meta.keys())\n print(repr(k) + \": \" + repr(v))\n print(e)\n \n f.write(\"---\\n\\n\")\n citation = \"**Citation:** \" \\\n + meta['citation-authors'] + ' \"' \\\n + meta['source-title'] + '\". ' \\\n + '*' + meta['container'] + '*'\n citation = citation + \" \" + meta['volume'] if meta['volume'] != '' else citation\n citation = citation + \", no. \" + meta['issue'] if meta['issue'] != '' else citation\n citation = citation + \" (\" + meta['year'] + \")\" if meta['year'] != '' else citation\n citation = citation + \": \" + meta['pages'] if meta['pages'] != '' else citation\n \n f.write(citation + \". [[Paper link](\" + meta['link'] + \")]\")\n \n #add the reference to the \"reading_list.md\" file\n with open(\"/\".join([HOME_DIR, REPO_DIR, MD_DIR, \"reading_list.md\"]), \"a\") as f:\n f.write(\"* [ ] **\" + meta['citationkey'] \\\n + \"**: (\" \\\n + re.sub(r'\\([^)]*\\)', '', meta['subjects'][0]).strip() \\\n + \") \" + meta['link'] + \"\\n\")\n \n print(\"reference {} added in {}!\\n\".format(meta['citationkey'], md_dir))","def run(self):\n env = cast(\"BuildEnvironment\", self.state.document.settings.env)\n foot_old_refs = env.temp_data.setdefault(\"bibtex_foot_old_refs\", set())\n foot_new_refs = env.temp_data.setdefault(\"bibtex_foot_new_refs\", set())\n footbibliography_count = env.temp_data[\"bibtex_footbibliography_count\"] = (\n env.temp_data.get(\"bibtex_footbibliography_count\", 0) + 1\n )\n if not foot_new_refs:\n return []\n else:\n foot_old_refs |= foot_new_refs\n foot_new_refs.clear()\n # bibliography stored in env.temp_data[\"bibtex_foot_bibliography\"]\n foot_domain = cast(\"BibtexFootDomain\", env.get_domain(\"footcite\"))\n foot_bibliography, env.temp_data[\"bibtex_foot_bibliography\"] = (\n env.temp_data[\"bibtex_foot_bibliography\"],\n foot_domain.bibliography_header.deepcopy(),\n )\n domain = cast(\"BibtexDomain\", env.get_domain(\"cite\"))\n for bibfile in domain.bibdata.bibfiles:\n env.note_dependency(bibfile)\n foot_bibliography[\"ids\"] += _make_ids(\n docname=env.docname,\n lineno=self.lineno,\n ids=set(self.state.document.ids.keys()),\n raw_id=env.app.config.bibtex_footbibliography_id.format(\n footbibliography_count=footbibliography_count\n ),\n )\n self.state.document.note_explicit_target(\n foot_bibliography, foot_bibliography\n )\n return [foot_bibliography]","def formula_list_html(header, model, tables_html):\n page = 'ms1_test_files'\n #epa template header\n html = render_to_string('01epa_drupal_header.html', {\n 'SITE_SKIN': os.environ['SITE_SKIN'],\n 'TITLE': u\"\\u00FCbertool\"\n })\n html += render_to_string('02epa_drupal_header_bluestripe_onesidebar.html', {})\n html += render_to_string('epa_drupal_section_title_nta.html', {})\n\n #main body\n html += render_to_string('06ubertext_start_index_drupal.html', {\n 'TITLE': header + ' References',\n 'TEXT_PARAGRAPH': tables_html\n })\n html += render_to_string('07ubertext_end_drupal.html', {})\n html += links_left.ordered_list(model, page)\n\n #css and scripts\n html += render_to_string('09epa_drupal_pram_css.html', {})\n html += render_to_string('09epa_drupal_pram_scripts.html', {})\n #html += render_to_string('09epa_drupal_pram_scripts.html', {})\n\n #epa template footer\n html += render_to_string('10epa_drupal_footer.html', {})\n return html","def composeWorkplaceOntology():\n\n import ossPyFuncs \n import pandas as pd\n \n #mysql query to extract full table from government organizations\n #certian table columns feature capital letters which cases uproblems\n postgreSql_selectQuery=\"SELECT * FROM us_gov_manual.us_govman_2019 ;\"\n #pass querry and obtain table\n govTable=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\n\n #mysql query to obtain academic instutions\n postgreSql_selectQuery=\"SELECT institution FROM hipolabs.universities ;\"\n #pass querry and obtain table\n univTable=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\n \n postgreSql_selectQuery=\"SELECT company FROM forbes.fortune2018_us1000;\"\n businesses1=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\n \n postgreSql_selectQuery=\"SELECT company FROM forbes.fortune2019_us1000;\"\n businesses2=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\n \n postgreSql_selectQuery=\"SELECT company FROM forbes.fortune2020_global2000;\"\n businesses3=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\n\n #combine theinsitutions into a vector\n combinedSeries=[govTable['AgencyName'],univTable['institution'],businesses1['company'],businesses2['company'],businesses3['company']]\n #turn the multi item vector into a single series\n fullWordbank=pd.concat(combinedSeries)\n #turn that series into a pd dataframe\n wordbankTable=pd.DataFrame(fullWordbank.unique())\n\n return wordbankTable","def make_table_declarations(ibs):\n # available tables\n TABLENAME_LIST = [\n IMAGE_TABLE,\n ANNOTATION_TABLE,\n # NAME_TABLE,\n IMAGESET_TABLE,\n IMAGE_GRID,\n THUMB_TABLE,\n NAMES_TREE,\n ]\n\n # table nice names\n TABLE_NICE = {\n IMAGE_TABLE: 'Image Table',\n ANNOTATION_TABLE: 'Annotations Table',\n NAME_TABLE: 'Name Table',\n QRES_TABLE: 'Query Results Table',\n IMAGESET_TABLE: 'ImageSet Table',\n IMAGE_GRID: 'Thumbnail Grid',\n THUMB_TABLE: 'Thumbnail Table',\n NAMES_TREE: 'Tree of Names',\n }\n\n # COLUMN DEFINITIONS\n # the columns each wbia table has,\n TABLE_COLNAMES = {\n IMAGE_TABLE: [\n 'gid',\n 'thumb',\n # 'nAids',\n 'img_gname',\n # 'ext',\n 'reviewed', # detection reviewed flag is not fullyused\n 'datetime',\n 'gps',\n 'orientation',\n 'party_tag',\n 'contributor_tag',\n # 'gdconf',\n 'imgnotes',\n 'image_uuid',\n ],\n # debug with\n # --noannottbl\n # --nonametree\n # even just aid seems to be very slow\n ANNOTATION_TABLE: [\n # 'annotation_uuid',\n 'aid',\n 'thumb',\n 'annot_gname',\n 'name',\n 'exemplar',\n 'species', # <put back in\n 'viewpoint',\n 'quality_text',\n 'age_min',\n 'age_max',\n 'sex_text',\n # 'rdconf',\n # 'nGt', # ## <put back in\n 'imagesettext_names',\n 'annotnotes', # ## <put back in\n 'tag_text', # < Hack should have actual tag structure\n # 'annot_visual_uuid',\n # 'nFeats',\n # 'bbox',\n # 'theta',\n # 'verts',\n # 'num_verts',\n ],\n NAME_TABLE: ['nid', 'name', 'nAids', 'namenotes'],\n QRES_TABLE: ['rank', 'score', 'name', 'aid'],\n IMAGESET_TABLE: [\n 'imagesettext',\n 'nImgs',\n # 'num_imgs_reviewed',\n # 'num_annotmatch_reviewed',\n # 'imageset_end_datetime',\n # 'imageset_processed_flag',\n # 'imageset_shipped_flag',\n 'imgsetid',\n ],\n NAMES_TREE: [\n 'name',\n 'nAids',\n 'thumb',\n 'nid',\n # 'exemplar',\n # 'nExAids',\n 'aid',\n # 'annot_gname',\n # 'quality_text',\n # 'age_min',\n # 'age_max',\n # 'sex_text',\n # 'imagesettext_names',\n # 'datetime',\n # 'max_hourdiff',\n # 'max_speed',\n # 'has_split',\n # 'namenotes',\n ],\n IMAGE_GRID: ['thumb'],\n # TEST TABLE\n THUMB_TABLE: ['img_gname', 'thumb'],\n }\n\n # dynamicly defined headers\n if not const.SIMPLIFY_INTERFACE:\n from wbia.control import accessor_decors\n\n if accessor_decors.API_CACHE:\n # Too slow without api cache\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\n ['percent_annotmatch_reviewed_str', 'percent_names_with_exemplar_str']\n )\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\n [\n # 'percent_imgs_reviewed_str',\n 'imageset_start_datetime',\n # 'imageset_end_datetime',\n 'imageset_duration',\n 'imageset_notes',\n ]\n )\n\n if ibs.cfg.other_cfg.show_shipped_imagesets:\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\n ['imageset_processed_flag', 'imageset_shipped_flag']\n )\n\n # THUMB_TABLE : ['thumb' 'thumb' 'thumb' 'thumb'],\n # NAMES_TREE : {('name' 'nid' 'nAids') : ['aid' 'bbox' 'thumb']}\n\n TABLE_TREE_LEVELS = {\n NAMES_TREE: {\n 'name': 0,\n 'namenotes': 0,\n 'nid': 0,\n 'nAids': 0,\n 'nExAids': 0,\n 'sex_text': 0,\n 'exemplar': 1,\n 'thumb': 1,\n 'viewpoint': 1,\n 'quality_text': 1,\n 'age_min': 1,\n 'age_max': 1,\n 'imagesettext_names': 1,\n 'aid': 1,\n 'annot_gname': 1,\n 'datetime': 1,\n 'max_hourdiff': 0,\n 'max_speed': 0,\n 'has_split': 0,\n },\n }\n\n # the columns which are editable\n TABLE_EDITSET = {\n IMAGE_TABLE: {'reviewed', 'imgnotes', 'gps'},\n ANNOTATION_TABLE: {\n 'name',\n 'species',\n 'annotnotes',\n 'exemplar',\n 'viewpoint',\n 'quality_text',\n 'age_min',\n 'age_max',\n 'sex_text',\n 'tag_text',\n },\n NAME_TABLE: {'name', 'namenotes'},\n QRES_TABLE: {'name'},\n IMAGESET_TABLE: {\n 'imagesettext',\n 'imageset_shipped_flag',\n 'imageset_processed_flag',\n },\n IMAGE_GRID: set(),\n THUMB_TABLE: set(),\n NAMES_TREE: {\n 'exemplar',\n 'name',\n 'namenotes',\n 'viewpoint',\n 'quality_text',\n 'age_min',\n 'age_max',\n 'sex_text',\n },\n }\n\n if const.SIMPLIFY_INTERFACE:\n TABLE_EDITSET[NAMES_TREE].remove('name')\n\n TABLE_HIDDEN_LIST = {\n # IMAGE_TABLE : [False, True, False, False, False, True, False, False, False, False, False],\n # ANNOTATION_TABLE : [False, False, False, False, False, False, False, True, True, True, True, True, True],\n # NAMES_TREE : [False, False, False, False, False, False],\n # NAME_TABLE : [False, False, False, False],\n }\n\n TABLE_STRIPE_LIST = {\n IMAGE_GRID: 9,\n }\n\n # Define the valid columns a table could have\n COL_DEF = dict(\n [\n ('annot_visual_uuid', (str, 'Annot Visual UUID')),\n ('image_uuid', (str, 'Image UUID')),\n ('gid', (int, 'Image ID')),\n ('aid', (int, 'Annotation ID')),\n ('nid', (int, 'Name ID')),\n ('imgsetid', (int, 'ImageSet ID')),\n ('nAids', (int, '#Annots')),\n ('nExAids', (int, '#Exemplars')),\n ('nGt', (int, '#GT')),\n ('nImgs', (int, '#Imgs')),\n ('nFeats', (int, '#Features')),\n ('quality_text', (str, 'Quality')),\n ('imagesettext_names', (str, 'ImageSet Names')),\n ('age_min', (int, 'Age (min)')),\n ('age_max', (int, 'Age (max)')),\n ('sex_text', (str, 'Sex')),\n ('rank', (str, 'Rank')), # needs to be a string for !Query\n ('unixtime', (float, 'unixtime')),\n ('species', (str, 'Species')),\n ('viewpoint', (str, 'Viewpoint')),\n ('img_gname', (str, 'Image Name')),\n ('annot_gname', (str, 'Source Image')),\n ('gdconf', (str, 'Detection Confidence')),\n ('rdconf', (float, 'Detection Confidence')),\n ('name', (str, 'Name')),\n ('annotnotes', (str, 'Annot Notes')),\n ('namenotes', (str, 'Name Notes')),\n ('imgnotes', (str, 'Image Notes')),\n ('match_name', (str, 'Matching Name')),\n ('bbox', (str, 'BBOX (x, y, w, h))')), # Non editables are safe as strs\n ('num_verts', (int, 'NumVerts')),\n ('verts', (str, 'Verts')),\n ('score', (str, 'Confidence')),\n ('theta', (str, 'Theta')),\n ('reviewed', (bool, 'Detection Reviewed')),\n ('exemplar', (bool, 'Is Exemplar')),\n ('imagesettext', (str, 'ImageSet')),\n ('datetime', (str, 'Date / Time')),\n ('ext', (str, 'EXT')),\n ('thumb', ('PIXMAP', 'Thumb')),\n ('gps', (str, 'GPS')),\n ('orientation', (str, 'Orientation')),\n ('imageset_processed_flag', (bool, 'Processed')),\n ('imageset_shipped_flag', (bool, 'Commited')),\n ('imageset_start_datetime', (str, 'Start Time')),\n ('imageset_end_datetime', (str, 'End Time')),\n ('imageset_duration', (str, 'Duration')),\n ('imageset_notes', (str, 'Notes')),\n ('party_tag', (str, 'Party')),\n ('contributor_tag', (str, 'Contributor')),\n ('percent_imgs_reviewed_str', (str, '%Imgs Reviewed')),\n ('percent_annotmatch_reviewed_str', (str, '%Queried')),\n ('num_imgs_reviewed', (str, '#Imgs Reviewed')),\n ('num_annotmatch_reviewed', (str, '#Matches Reviewed')),\n ('percent_names_with_exemplar_str', (str, '%Names with Exemplar')),\n ('max_speed', (float, 'Max Speed km/h')),\n ('has_split', (float, 'Needs Split')),\n ('max_hourdiff', (float, 'Max Hour Diff')),\n ('tag_text', (str, 'Tags')),\n ]\n )\n\n declare_tup = (\n TABLENAME_LIST,\n TABLE_NICE,\n TABLE_COLNAMES,\n TABLE_TREE_LEVELS,\n TABLE_EDITSET,\n TABLE_HIDDEN_LIST,\n TABLE_STRIPE_LIST,\n COL_DEF,\n )\n return declare_tup","def make_crossref_metadata(dataset: ObservatoryDataset) -> List[Dict]:\n\n records = []\n\n for paper in dataset.papers:\n # Create funders\n funders = []\n for funder in paper.funders:\n funders.append({\"name\": funder.name, \"DOI\": funder.doi, \"award\": None, \"doi_asserted_by\": None})\n\n # Add Crossref record\n records.append(\n {\n \"type\": paper.type,\n \"title\": [paper.title],\n \"DOI\": paper.doi,\n \"is_referenced_by_count\": len(paper.cited_by),\n \"issued\": {\n \"date_parts\": [paper.published_date.year, paper.published_date.month, paper.published_date.day]\n },\n \"funder\": funders,\n \"publisher\": paper.publisher.name,\n }\n )\n\n return records","def write_the_table(what):\n global count_row\n count_row += 1\n\n if what.get('rank') == 0:\n background_blue.append(count_row)\n\n struct = what.get('structure')\n link = what.get('link')\n exams_1 = what.get('exams_1')\n exams_2 = what.get('exams_2')\n exams_empty = [['', '', '', '', '', '', '', '', '', '', '', '']] \\\n if self.training.session_type != '1' else \\\n [['', '', '', '', '', '']]\n\n def formated(number):\n \"\"\"\n Remove trailing 0\n \"\"\"\n frac, whole = modf(number)\n if frac == 0:\n return int(whole)\n return str(number).rstrip('0')\n\n def write_exams(list_1, list_2):\n exam_table = []\n for ex_1, ex_2 in itertools.zip_longest(list_1, list_2):\n ex_1_table = [\n formated(ex_1.coefficient) if ex_1 is not None else '',\n [\n Paragraph(filter_content(ex_1.label) if ex_1 else '',\n self.styles['SmallNormal']),\n Paragraph(\n \"<para textColor=grey>\" + filter_content(ex_1.additionnal_info) \\\n if ex_1 and ex_1.additionnal_info \\\n else \"\" + \"</para\\>\",\n self.styles['SmallNormal'])\n ],\n ex_1.type_exam if ex_1 is not None else '',\n ex_1.text_duration if ex_1 is not None else '',\n '' if ex_1 is None \\\n else ex_1.convocation if not training_is_ccct \\\n else ex_1.get_type_ccct_display(),\n ex_1.eliminatory_grade if ex_1 is not None else '',\n ex_1.threshold_session_2 if ex_1 is not None else '',\n ]\n\n ex_2_table = [\n formated(ex_2.coefficient) if ex_2 is not None else '',\n [Paragraph(filter_content(ex_2.label) if ex_2 is not None else '', self.styles[\n 'SmallNormal']), Paragraph(\"<para textColor=grey\\\n >\" + ex_2.additionnal_info + \"</para\\\n >\" if ex_2.additionnal_info is not None else \"\",\n self.styles['SmallNormal'])],\n ex_2.type_exam if ex_2 is not None else '',\n ex_2.text_duration if ex_2 is not None else '',\n ex_2.eliminatory_grade if ex_2 is not None else '',\n ] if ex_2 is not None else ['', '', '', '', '']\n if self.training.session_type != '1':\n ex_1_table.extend(ex_2_table)\n else:\n ex_1_table.pop()\n exam_table.append(ex_1_table)\n exam_table = exam_table if len(exam_table) > 0 else exams_empty\n if exam_table == exams_empty:\n # TODO: calculate empty space to set rowHeights in order to\n # avoid blank in table\n pass\n inner_table = Table(\n exam_table, colWidths=width_exams, rowHeights=None)\n inner_table.setStyle(TableStyle(\n [('INNERGRID', (0, 0), (-1, -1), 0.1, colors.black),\n ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),\n ('ALIGN', (0, 0), (-1, -1), 'CENTER'),\n ('FONTSIZE', (0, 0), (-1, -1), 8),\n # ('LEFTPADDING', (0, 0), (-1, -1), 0),\n # ('RIGHTPADDING', (0, 0), (-1, -1), 0),\n ('BOTTOMPADDING', (0, 0), (-1, -1), 0),\n ('TOPPADDING', (0, 0), (-1, -1), 0),\n ]))\n return inner_table\n\n ref_scol = struct.ref_si_scol if struct.ref_si_scol else \"\" # FIX bug with rof data\n ref_data = (\n Paragraph(struct.ROF_ref, self.styles['CenterSmall']),\n Paragraph(ref_scol, self.styles['CenterSmall'])\n ) if self.reference == 'both' \\\n else Paragraph(struct.ROF_ref, self.styles['CenterSmall']) if self.reference == 'with_rof' \\\n else Paragraph(ref_scol, self.styles['CenterSmall']) if self.reference == 'with_si' \\\n else Paragraph('', self.styles['CenterSmall'])\n\n object_line = [\n Paragraph(\n \"<para leftIndent=%s>%s</para> \" % (what.get('rank')*10, filter_content(struct.label)),\n self.styles['SmallBold'] if what.get('rank') == 0 \\\n or what.get('structure').nature == 'UE' \\\n else self.styles['SmallNormal']\n ),\n Paragraph(\n struct.get_respens_name if not struct.external_name \\\n else struct.external_name,\n self.styles['CenterSmall'] if not struct.external_name else \\\n self.styles['CenterSmallItalic']\n ),\n [ref_data],\n '30' if self.training.degree_type.ROF_code in self.training_types_for_which_to_display_30_ects\\\n and struct.nature == 'SE'\\\n else struct.ECTS_credit if struct.ECTS_credit else '-',\n formated(link.coefficient) if link.coefficient else '',\n link.eliminatory_grade,\n write_exams(exams_1, exams_2)\n ]\n if self.respforms:\n if self.reference == 'without':\n object_line.pop(2)\n else:\n object_line.pop(1)\n if self.reference == 'without':\n object_line.pop(1)\n\n big_table.append(object_line)\n\n for e in what.get('children'):\n write_the_table(e)","def ref_analyzer(citation_informations, initialresult, initial_citationlist,\n initial_referencelist,config, updated_rec_list ):\n function = \"\"\n try:\n function = config.get(\"rank_method\", \"function\")\n except:\n register_exception(prefix=\"cfg section [rank_method] has no attr function\", alert_admin=True)\n return {}\n\n pubrefntag = \"\"\n try:\n pubrefntag = config.get(function, \"reference_via_report_number\")\n except:\n register_exception(prefix=\"cfg section \"+function+\" has no attr reference_via_report_number\", alert_admin=True)\n return {}\n\n pubreftag = \"\"\n try:\n pubreftag = config.get(function, \"reference_via_pubinfo\")\n except:\n register_exception(prefix=\"cfg section \"+function+\" has no attr reference_via_pubinfo\", alert_admin=True)\n return {}\n\n #pubrefntag is often 999C5r, pubreftag 999C5s\n if task_get_task_param('verbose') >= 9:\n write_message(\"pubrefntag \"+pubrefntag)\n write_message(\"pubreftag \"+pubreftag)\n\n citation_list = initial_citationlist\n reference_list = initial_referencelist\n result = initialresult\n d_reports_numbers = citation_informations[0] #dict of recid -> institute_give_publ_id\n d_references_report_numbers = citation_informations[1] #dict of recid -> ['astro-ph/xyz'..]\n d_references_s = citation_informations[2]\n #dict of recid -> publication_infos_in_its_bibliography\n d_records_s = citation_informations[3] #recid -> its publication inf\n t1 = os.times()[4]\n\n write_message(\"Phase 0: temporarily remove changed records from citation dictionaries; they will be filled later\")\n for somerecid in updated_rec_list:\n try:\n del citation_list[somerecid]\n except KeyError:\n pass\n try:\n del reference_list[somerecid]\n except KeyError:\n pass\n\n write_message(\"Phase 1: d_references_report_numbers\")\n #d_references_report_numbers: e.g 8 -> ([astro-ph/9889],[hep-ph/768])\n #meaning: rec 8 contains these in bibliography\n\n done = 0\n numrecs = len(d_references_report_numbers)\n for thisrecid, refnumbers in d_references_report_numbers.iteritems():\n if (done % 1000 == 0):\n mesg = \"d_references_report_numbers done \"+str(done)+\" of \"+str(numrecs)\n write_message(mesg)\n task_update_progress(mesg)\n task_sleep_now_if_required()\n done = done+1\n\n for refnumber in refnumbers:\n if refnumber:\n p = refnumber\n f = 'reportnumber'\n #sanitise p\n p.replace(\"\\n\",'')\n #search for \"hep-th/5644654 or such\" in existing records\n rec_ids = get_recids_matching_query(p, f)\n\n if len(rec_ids) > 1:\n msg = \"Whoops: record '%d' report number value '%s' \" \\\n \"matches many records; taking only the first one. %s\" % \\\n (thisrecid, p, repr(rec_ids))\n write_message(msg, stream=sys.stderr)\n try:\n raise ValueError(msg)\n except ValueError:\n register_exception(alert_admin=True)\n\n if rec_ids and rec_ids[0]:\n write_citer_cited(thisrecid, rec_ids[0])\n remove_from_missing(p)\n if not result.has_key(rec_ids[0]):\n result[rec_ids[0]] = 0\n # Citation list should have rec_ids[0] but check anyway\n if not citation_list.has_key(rec_ids[0]):\n citation_list[rec_ids[0]] = []\n #append unless this key already has the item\n if not thisrecid in citation_list[rec_ids[0]]:\n citation_list[rec_ids[0]].append(thisrecid)\n #and update result\n result[rec_ids[0]] += 1\n\n if not reference_list.has_key(thisrecid):\n reference_list[thisrecid] = []\n if not rec_ids[0] in reference_list[thisrecid]:\n reference_list[thisrecid].append(rec_ids[0])\n else:\n #the reference we wanted was not found among our records.\n #put the reference in the \"missing\".. however, it will look\n #bad.. gfhgf/1254312, so get the corresponding 999C5s (full ref) too\n #This should really be done in the next loop d_references_s\n #but the 999C5s fields are not yet normalized\n\n #rectext = print_record(thisrecid, format='hm', ot=pubreftag[:-1])\n rectext = \"\" # print_record() call disabled to speed things up\n lines = rectext.split(\"\\n\")\n rpart = p #to be used..\n for l in lines:\n if (l.find(p) > 0): #the gfhgf/1254312 was found.. get the s-part of it\n st = l.find('$s')\n if (st > 0):\n end = l.find('$', st)\n if (end == st):\n end = len(l)\n rpart = l[st+2:end]\n insert_into_missing(thisrecid, rpart)\n\n mesg = \"d_references_report_numbers done fully\"\n write_message(mesg)\n task_update_progress(mesg)\n\n t2 = os.times()[4]\n\n #try to find references based on 999C5s, like Phys.Rev.Lett. 53 (1986) 2285\n write_message(\"Phase 2: d_references_s\")\n done = 0\n numrecs = len(d_references_s)\n for thisrecid, refss in d_references_s.iteritems():\n if (done % 1000 == 0):\n mesg = \"d_references_s done \"+str(done)+\" of \"+str(numrecs)\n write_message(mesg)\n task_update_progress(mesg)\n task_sleep_now_if_required()\n\n done = done+1\n\n for refs in refss:\n if refs:\n p = refs\n #remove the latter page number if it is like 67-74\n matches = re.compile(\"(.*)(-\\d+$)\").findall(p)\n if matches and matches[0]:\n p = matches[0][0]\n\n # check reference value to see whether it is well formed:\n if not re_CFG_JOURNAL_PUBINFO_STANDARD_FORM_REGEXP_CHECK.match(p):\n msg = \"Whoops, record '%d' reference value '%s' \" \\\n \"is not well formed; skipping it.\" % (thisrecid, p)\n write_message(msg, stream=sys.stderr)\n try:\n raise ValueError(msg)\n except ValueError:\n register_exception(alert_admin=True)\n continue # skip this ill-formed value\n\n # look for reference value:\n rec_id = None\n try:\n rec_ids = list(search_unit(p, 'journal') - INTBITSET_OF_DELETED_RECORDS)\n except:\n rec_ids = None\n if len(rec_ids) > 1:\n msg = \"Whoops, record '%d' reference value '%s' \" \\\n \"matches many records; taking only the first one. %s\" % \\\n (thisrecid, p, repr(rec_ids))\n write_message(msg, stream=sys.stderr)\n try:\n raise ValueError(msg)\n except ValueError:\n register_exception(alert_admin=True)\n\n if rec_ids and rec_ids[0]:\n write_message(\"These match searching \"+p+\" in journal: \"+repr(rec_ids), verbose=9)\n #the refered publication is in our collection, remove\n #from missing\n remove_from_missing(p)\n else:\n #it was not found so add in missing\n insert_into_missing(thisrecid, p)\n #check citation and reference for this..\n if rec_ids and rec_ids[0]:\n #the above should always hold\n if not result.has_key(rec_ids[0]):\n result[rec_ids[0]] = 0\n if not citation_list.has_key(rec_ids[0]):\n citation_list[rec_ids[0]] = []\n if not thisrecid in citation_list[rec_ids[0]]:\n citation_list[rec_ids[0]].append(thisrecid) #append actual list\n result[rec_ids[0]] += 1 #add count for this..\n\n #update reference_list accordingly\n if not reference_list.has_key(thisrecid):\n reference_list[thisrecid] = []\n if not rec_ids[0] in reference_list[thisrecid]:\n reference_list[thisrecid].append(rec_ids[0])\n mesg = \"d_references_s done fully\"\n write_message(mesg)\n task_update_progress(mesg)\n\n t3 = os.times()[4]\n done = 0\n numrecs = len(d_reports_numbers)\n write_message(\"Phase 3: d_reports_numbers\")\n\n #search for stuff like CERN-TH-4859/87 in list of refs\n for thisrecid, reportcodes in d_reports_numbers.iteritems():\n if (done % 1000 == 0):\n mesg = \"d_report_numbers done \"+str(done)+\" of \"+str(numrecs)\n write_message(mesg)\n task_update_progress(mesg)\n done = done+1\n\n for reportcode in reportcodes:\n if reportcode:\n rec_ids = []\n try:\n rec_ids = get_recids_matching_query(reportcode, pubrefntag)\n except:\n rec_ids = []\n\n if rec_ids:\n for recid in rec_ids:\n #normal checks..\n if not citation_list.has_key(thisrecid):\n citation_list[thisrecid] = []\n if not reference_list.has_key(recid):\n reference_list[recid] = []\n if not result.has_key(thisrecid):\n result[thisrecid] = 0\n\n #normal updates\n if not recid in citation_list[thisrecid]:\n result[thisrecid] += 1\n citation_list[thisrecid].append(recid)\n if not thisrecid in reference_list[recid]:\n reference_list[recid].append(thisrecid)\n\n mesg = \"d_report_numbers done fully\"\n write_message(mesg)\n task_update_progress(mesg)\n\n #find this record's pubinfo in other records' bibliography\n write_message(\"Phase 4: d_records_s\")\n done = 0\n numrecs = len(d_records_s)\n t4 = os.times()[4]\n for thisrecid, recs in d_records_s.iteritems():\n if (done % 1000 == 0):\n mesg = \"d_records_s done \"+str(done)+\" of \"+str(numrecs)\n write_message(mesg)\n task_update_progress(mesg)\n done = done+1\n p = recs.replace(\"\\\"\",\"\")\n #search the publication string like Phys. Lett., B 482 (2000) 417 in 999C5s\n rec_ids = list(search_unit(f=pubreftag, p=p, m='a') - INTBITSET_OF_DELETED_RECORDS)\n write_message(\"These records match \"+p+\" in \"+pubreftag+\" : \"+str(rec_ids), verbose=9)\n if rec_ids:\n for rec_id in rec_ids:\n #normal checks\n if not result.has_key(thisrecid):\n result[thisrecid] = 0\n if not citation_list.has_key(thisrecid):\n citation_list[thisrecid] = []\n if not reference_list.has_key(rec_id):\n reference_list[rec_id] = []\n\n if not rec_id in citation_list[thisrecid]:\n result[thisrecid] += 1\n citation_list[thisrecid].append(rec_id)\n if not thisrecid in reference_list[rec_id]:\n reference_list[rec_id].append(thisrecid)\n\n mesg = \"d_records_s done fully\"\n write_message(mesg)\n task_update_progress(mesg)\n\n write_message(\"Phase 5: reverse lists\")\n\n #remove empty lists in citation and reference\n keys = citation_list.keys()\n for k in keys:\n if not citation_list[k]:\n del citation_list[k]\n\n keys = reference_list.keys()\n for k in keys:\n if not reference_list[k]:\n del reference_list[k]\n\n write_message(\"Phase 6: self-citations\")\n selfdic = {}\n #get the initial self citation dict\n initial_self_dict = get_cit_dict(\"selfcitdict\")\n selfdic = initial_self_dict\n #add new records to selfdic\n acit = task_get_option(\"author-citations\")\n if not acit:\n write_message(\"Self cite processing disabled. Use -A option to enable it.\")\n else:\n write_message(\"self cite and author citations enabled\")\n selfdic = get_self_citations(updated_rec_list, citation_list,\n initial_self_dict, config)\n #selfdic consists of\n #key k -> list of values [v1,v2,..]\n #where k is a record with author A and k cites v1,v2.. and A appears in v1,v2..\n\n #create a reverse \"x cited by y\" self cit dict\n selfcitedbydic = {}\n for k in selfdic.keys():\n vlist = selfdic[k]\n for v in vlist:\n if selfcitedbydic.has_key(v):\n tmplist = selfcitedbydic[v]\n if not k in tmplist:\n tmplist.append(k)\n else:\n tmplist = [k]\n selfcitedbydic[v] = tmplist\n\n write_message(\"Getting author citations\")\n\n #get author citations for records in updated_rec_list\n initial_author_dict = get_initial_author_dict()\n authorcitdic = initial_author_dict\n acit = task_get_option(\"author-citations\")\n if not acit:\n print \"Author cites disabled. Use -A option to enable it.\"\n else:\n write_message(\"author citations enabled\")\n authorcitdic = get_author_citations(updated_rec_list, citation_list,\n initial_author_dict, config)\n\n\n if task_get_task_param('verbose') >= 3:\n #print only X first to prevent flood\n tmpdict = {}\n tmp = citation_list.keys()[0:10]\n for t in tmp:\n tmpdict[t] = citation_list[t]\n write_message(\"citation_list (x is cited by y): \"+str(tmpdict))\n write_message(\"size: \"+str(len(citation_list.keys())))\n tmp = reference_list.keys()[0:10]\n tmpdict = {}\n for t in tmp:\n tmpdict[t] = reference_list[t]\n write_message(\"reference_list (x cites y): \"+str(tmpdict))\n write_message(\"size: \"+str(len(reference_list.keys())))\n tmp = selfcitedbydic.keys()[0:10]\n tmpdict = {}\n for t in tmp:\n tmpdict[t] = selfcitedbydic[t]\n mesg = \"selfcitedbydic (x is cited by y and one of the authors of x same as y's):\"\n mesg += str(tmpdict)\n write_message(mesg)\n write_message(\"size: \"+str(len(selfcitedbydic.keys())))\n tmp = selfdic.keys()[0:100]\n tmpdict = {}\n for t in tmp:\n tmpdict[t] = selfdic[t]\n mesg = \"selfdic (x cites y and one of the authors of x same as y's): \"+str(tmpdict)\n write_message(mesg)\n write_message(\"size: \"+str(len(selfdic.keys())))\n tmp = authorcitdic.keys()[0:10]\n tmpdict = {}\n for t in tmp:\n tmpdict[t] = authorcitdic[t]\n write_message(\"authorcitdic (author is cited in recs): \"+str(tmpdict))\n write_message(\"size: \"+str(len(authorcitdic.keys())))\n insert_cit_ref_list_intodb(citation_list, reference_list,\n selfcitedbydic, selfdic, authorcitdic)\n\n t5 = os.times()[4]\n\n write_message(\"Execution time for analyzing the citation information generating the dictionary:\")\n write_message(\"... checking ref number: %.2f sec\" % (t2-t1))\n write_message(\"... checking ref ypvt: %.2f sec\" % (t3-t2))\n write_message(\"... checking rec number: %.2f sec\" % (t4-t3))\n write_message(\"... checking rec ypvt: %.2f sec\" % (t5-t4))\n write_message(\"... total time of ref_analyze: %.2f sec\" % (t5-t1))\n\n return result","def get_examples_table_data(technique, reference_list, next_reference_number):\n\n # Creating map to avoid repeating the code 3 times\n examples_map = [\n { 'example_type': config.tools_using_technique }, \n { 'example_type': config.malware_using_technique },\n { 'example_type': config.groups_using_technique }\n ]\n\n example_data = []\n\n # Get malware or tools used by group\n for examples in examples_map:\n if examples['example_type'].get(technique.get('id')):\n for example in examples['example_type'][technique['id']]:\n\n attack_id = util.get_attack_id(example['object'])\n\n # Only add example data if the attack id is found \n if attack_id:\n row = {}\n\n row['id'] = attack_id\n\n if attack_id.startswith('S'):\n row['path'] = \"software\"\n else:\n row['path'] = \"groups\"\n\n row['name'] = example['object']['name']\n\n if example['relationship'].get('description'):\n # Get filtered description\n row['descr'] = util.get_filtered_description(reference_list, next_reference_number, example)\n\n example_data.append(row)\n \n if example_data:\n example_data = sorted(example_data, key=lambda k: k['name'].lower())\n return example_data","def cv_list(self):\n\n mystr = \"\"\n for p in self.mypapers:\n mystr += f\"{p.title[0]}\\n\"\n if len(p.author) > 12:\n a = f\"{p.author[0]} et al. \"\n elif len(p.author) > 2:\n a = \", \".join(p.author[:-1]) + f\" & {p.author[-1]} \"\n elif len(p.author) == 2:\n a = f\"{p.author[0]} & {p.author[1]} \"\n else:\n a = f\"{p.author[0]} \"\n\n mystr += f\"{a}\"\n mystr += f\"{p.year}, {p.pub}\"\n if p.volume is not None:\n mystr += f\", {p.volume}\"\n if p.issue is not None:\n mystr += f\", {p.issue}\"\n if p.page is not None:\n mystr += f\", {p.page[0]}\"\n mystr += \"\\n\\n\"\n return mystr","def ref_to_link(txt):\n text = txt.group(1) # because it was a match in a regular expression\n\n thecite, everythingelse = first_bracketed_string(text)\n thecite = thecite[1:-1] # strip curly brackets\n thecite = thecite.replace(\"\\\\\",\"\") # \\href --> href\n\n refs = thecite.split(\",\")\n ans = \"\"\n\n # print \"refs\",refs\n\n for ref in refs:\n ref = ref.strip() # because \\cite{A, B, C,D} can have spaces\n this_link = \"\"\n if ref.startswith(\"href\"):\n the_link = re.sub(r\".*{([^}]+)}{.*\", r\"\\1\", ref)\n click_on = re.sub(r\".*}{([^}]+)}\\s*\", r\"\\1\", ref)\n this_link = '{{ LINK_EXT(\"' + click_on + '\",\"' + the_link + '\") | safe}}'\n elif ref.startswith(\"doi\"):\n ref = ref.replace(\":\",\"\") # could be doi:: or doi: or doi\n the_doi = ref[3:] # remove the \"doi\"\n this_link = '{{ LINK_EXT(\"' + the_doi + '\",\"https://doi.org/' + the_doi + '\")| safe }}'\n elif ref.lower().startswith(\"mr\"):\n ref = ref.replace(\":\",\"\")\n the_mr = ref[2:] # remove the \"MR\"\n this_link = '{{ LINK_EXT(\"' + 'MR:' + the_mr + '\", '\n this_link += '\"http://www.ams.org/mathscinet/search/publdoc.html?pg1=MR&s1='\n this_link += the_mr + '\") | safe}}'\n elif ref.lower().startswith(\"arxiv\"):\n ref = ref.replace(\":\",\"\")\n the_arx = ref[5:] # remove the \"arXiv\"\n this_link = '{{ LINK_EXT(\"' + 'arXiv:' + the_arx + '\", '\n this_link += '\"http://arxiv.org/abs/'\n this_link += the_arx + '\")| safe}}'\n\n\n if this_link:\n if ans:\n ans += \", \"\n ans += this_link\n\n return '[' + ans + ']' + everythingelse","def generate_latex_table(dictionary,filename,location=\".\"):\n if type(filename) != str:\n raise TypeError('filename should be string')\n if type(dictionary) != dict:\n raise TypeError('dictionary should be dictionary')\n\n head_code = \"\"\"\\\\documentclass{article}\n%In the preamble section include the arabtex and utf8 packages\n\\\\usepackage{arabtex}\n\\\\usepackage{utf8}\n\\\\usepackage{longtable}\n\\\\usepackage{color, colortbl}\n\\\\usepackage{supertabular}\n\\\\usepackage{multicol}\n\\\\usepackage{geometry}\n\\\\geometry{left=.1in, right=.1in, top=.1in, bottom=.1in}\n\n\\\\begin{document}\n\\\\begin{multicols}{6}\n\\\\setcode{utf8}\n\n\\\\begin{center}\"\"\"\n\n tail_code = \"\"\"\\\\end{center}\n\\\\end{multicols}\n\\\\end{document}\"\"\"\n\n begin_table = \"\"\"\\\\begin{tabular}{ P{2cm} P{1cm}}\n\\\\textbf{words} & \\\\textbf{\\\\#} \\\\\\\\\n\\\\hline\n\\\\\\\\[0.01cm]\"\"\"\n end_table= \"\"\"\\\\end{tabular}\"\"\"\n rows_num = 40\n if location != '.':\n filename = location +\"/\"+ filename\n\n try:\n file = open(filename+'.tex', 'w', encoding='utf8')\n file.write(head_code+'\\n')\n n= int(len(dictionary)/rows_num)\n words = [(\"\\\\<\"+word+\"> & \"+str(frequancy)+' \\\\\\\\ \\n') for word, frequancy in dictionary.items()]\n start=0\n end=rows_num\n new_words = []\n for i in range(n):\n new_words = new_words+ [begin_table+'\\n'] +words[start:end] +[end_table+\" \\n\"]\n start=end\n end+=rows_num\n remain_words = len(dictionary) - rows_num*n\n if remain_words > 0:\n new_words += [begin_table+\" \\n\"]+ words[-1*remain_words:]+[end_table+\" \\n\"]\n for word in new_words:\n file.write(word)\n file.write(tail_code)\n file.close()\n return True\n except:\n return False","def write_contigs(self, refs):\n\n contigs_group = self.f.create_group('contigs')\n\n for ref_name, ref in refs:\n contig = contigs_group.create_group(ref_name)\n contig.attrs['name'] = ref_name\n contig.attrs['seq'] = ref\n contig.attrs['len'] = len(ref)","def cpi_data():\n\n\n cpi_workbook = xlrd.open_workbook(\n 'corruption_perception_index.xlsx')\n cpi_sheet = cpi_workbook.sheets()[0]\n\n\n cpi_title_rows = zip(cpi_sheet.row_values(1), cpi_sheet.row_values(2))\n cpi_titles = [t[0] + ' ' + t[1] for t in cpi_title_rows]\n cpi_titles = [t.strip() for t in cpi_titles]\n cpi_rows = [cpi_sheet.row_values(r) for r in range(3, cpi_sheet.nrows)]\n\n\n cpi_types = get_types(cpi_sheet.row(3))\n cpi_titles[0] = cpi_titles[0] + ' Duplicate'\n cpi_table = get_table(cpi_rows, cpi_types, cpi_titles)\n\n return cpi_table","def index_labtests(cnxdict, engine, labtestlist):\n for currtbl in labtestlist:\n currtbl = currtbl.replace(' ', '_')\n mycnx = connect_to_mysql_db_prod('caisismysql')\n mycnx['sql'] = \"\"\"\n ALTER TABLE `caisis`.`{0}`\n CHANGE COLUMN `LabTestId` `LabTestId` BIGINT(20) NOT NULL ,\n ADD PRIMARY KEY (`LabTestId`);\n ALTER TABLE `caisis`.`{0}`\n ADD INDEX `patientid` (`PatientId` ASC);\n ALTER TABLE `caisis`.`{0}`\n ADD INDEX `labdate` (`LabDate` ASC);\n ALTER TABLE `caisis`.`{0}`\n ADD FULLTEXT INDEX `labtest` (`LabTest` ASC);\n \"\"\".format(currtbl)\n dosqlexecute(mycnx)","def __citationsFromFile(file):\n\n # Tokens for parsing\n titleToken = '#*'\n indexToken = '#index'\n citationToken = '#%'\n\n # Predicates for error checking\n noneNone = lambda *items: all([item is not None for item in items])\n allNone = lambda *items: all([item is None for item in items])\n\n # Next entry data\n title = None\n index = None\n citations = []\n\n # Basic stats\n withCitations = 0\n withoutCitations = 0\n totalPapers = 0\n\n for line in file:\n line = line.strip()\n\n # Parse entry, enforcing that data appears in title -> index -> citations order\n if line.startswith(titleToken):\n assert allNone(title, index) and len(citations) == 0\n title = line[len(titleToken):].strip('.')\n\n elif line.startswith(indexToken):\n assert noneNone(title) and allNone(index) and len(citations) == 0\n index = int(line[len(indexToken):])\n\n elif line.startswith(citationToken):\n assert noneNone(title, index)\n newCitationId = int(line[len(citationToken):])\n assert newCitationId >= 0\n citations.append(newCitationId)\n\n elif len(line) == 0:\n totalPapers += 1\n\n # Yield this entry if it has any citations,\n if noneNone(title, index):\n if len(citations) > 0:\n withCitations += 1\n yield title, index, citations\n else:\n withoutCitations += 1\n\n title = None\n index = None\n citations = []\n\n # Output some basic statistics about papers with/without citations\n withCitationsPercent = 100.0 * (float(withCitations) / totalPapers)\n withoutCitationsPercent = 100.0 * (float(withoutCitations) / totalPapers)\n print \"\\n\\nTotal Papers: %d\" % totalPapers\n print \" With References: %d (%2.2f%%)\\n Without References: %d (%2.2f%%)\" % (\n withCitations, withCitationsPercent, withoutCitations, withoutCitationsPercent\n )","def file_creator(title_list):\n for file_name in title_list: #title names are retrieved out of genID.txt\n with open (\"nuc_variant_calls/\"+file_name.strip()+\".var\",'w') as x:\n x.write(\"Feature type\\tAlignment length\\tIdentical nucleotides\\tIndel count\\n\") #Table headers.","def table_maker():\r\n try:\r\n off_copy = off.copy()\r\n man_copy = man.copy()\r\n exe_copy = exe.copy()\r\n ceo_copy = ceo.copy()\r\n list_of_lists = [off_copy, man_copy, exe_copy, ceo_copy]\r\n\r\n for i in list_of_lists:\r\n for j in i:\r\n if type(j) == str:\r\n continue\r\n else:\r\n raise ValueError('All elements must be strings')\r\n\r\n row_num = max(len(off_copy), len(man_copy),\r\n len(exe_copy), len(ceo_copy))\r\n for i in list_of_lists:\r\n if len(i) != row_num:\r\n diff = row_num - len(i)\r\n for j in range(diff):\r\n i.append('')\r\n\r\n t = PrettyTable(\r\n ['Office Workers', 'Managers', 'Executives', 'CEO'])\r\n for i in range(row_num):\r\n t.add_row([off_copy[i], man_copy[i], exe_copy[i], ceo_copy[i]])\r\n\r\n with open('Employee Table.txt', 'w') as f:\r\n f.write(str(t))\r\n\r\n except FileNotFoundError:\r\n print(\"Error: No file entered\")","def create_tables():\n inf(\"Creating tables\")\n \n pinners = Table('pinners', metadata,\n Column('pinner_id', Integer, primary_key=True),\n Column('name', String(40)),\n Column('email', String(40))\n )\n pinners.create()\n \n contents = Table('contents', metadata,\n Column('content_id', Integer, primary_key=True),\n Column('url', String(80)),\n Column('display_status', String(20)), # good, objectionable, copyright\n Column('pinner_id', Integer, ForeignKey('pinners.pinner_id'))\n )\n contents.create()\n\n reviewers = Table('reviewers', metadata,\n Column('reviewer_id', Integer, primary_key=True),\n Column('name', String(40)),\n Column('email', String(40))\n )\n reviewers.create()\n\n complaints = Table('complaints', metadata,\n Column('complaint_id', Integer, primary_key=True),\n Column('complaint_timestamp', DateTime), # when the complaint was filed\n Column('complaint_type', String(80)), # objectionable, copyright\n Column('process_status', String(20)), # complaint, review, done\n Column('display_status', String(20)), # good, objectionable, copyright\n Column('review_timestamp', DateTime), # when the compliant was resolved\n Column('pinner_id', Integer, ForeignKey('pinners.pinner_id')),\n Column('reviewer_id', Integer, ForeignKey('reviewers.reviewer_id')),\n Column('content_id', Integer, ForeignKey('contents.content_id'))\n )\n complaints.create()\n \n # could create a table of \"near by\" images and/or near by features and \n # include these in the review","def tables(args):\n\n config_file = args.setupfn\n conf_base = os.path.basename(config_file).split('.')[0]\n statfile = os.path.join(args.outputdir,\n \"{}_radvel.stat\".format(conf_base))\n status = load_status(statfile)\n\n assert status.getboolean('mcmc', 'run'), \\\n \"Must run MCMC before making tables\"\n\n P, post = radvel.utils.initialize_posterior(config_file)\n post = radvel.posterior.load(status.get('fit', 'postfile'))\n chains = pd.read_csv(status.get('mcmc', 'chainfile'))\n minafactor = status.get('mcmc', 'minafactor')\n maxarchange = status.get('mcmc', 'maxarchange')\n maxgr = status.get('mcmc', 'maxgr')\n mintz = status.get('mcmc', 'mintz')\n if 'derive' in status.sections() and status.getboolean('derive', 'run'):\n dchains = pd.read_csv(status.get('derive', 'chainfile'))\n chains = chains.join(dchains, rsuffix='_derived')\n derived = True\n else:\n derived = False\n report = radvel.report.RadvelReport(P, post, chains, minafactor, maxarchange, maxgr, mintz, derived=derived)\n tabletex = radvel.report.TexTable(report)\n attrdict = {'priors': 'tab_prior_summary', 'rv': 'tab_rv',\n 'params': 'tab_params', 'derived': 'tab_derived',\n 'crit': 'tab_crit'}\n for tabtype in args.type:\n print(\"Generating LaTeX code for {} table\".format(tabtype))\n\n if tabtype == 'ic_compare':\n assert status.has_option('ic_compare', 'ic'), \\\n \"Must run Information Criteria comparison before making comparison tables\"\n\n compstats = eval(status.get('ic_compare', 'ic'))\n report = radvel.report.RadvelReport(\n P, post, chains, minafactor, maxarchange, maxgr, mintz, compstats=compstats\n )\n tabletex = radvel.report.TexTable(report)\n tex = tabletex.tab_comparison()\n elif tabtype == 'rv':\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title, max_lines=None)\n elif tabtype == 'crit':\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title)\n else:\n if tabtype == 'derived':\n assert status.has_option('derive', 'run'), \\\n \"Must run `radvel derive` before making derived parameter table\"\n assert tabtype in attrdict, 'Invalid Table Type %s ' % tabtype\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title)\n\n saveto = os.path.join(\n args.outputdir, '{}_{}.tex'.format(conf_base, tabtype)\n )\n with open(saveto, 'w+') as f:\n f.write(tex)\n\n savestate = {'{}_tex'.format(tabtype): os.path.relpath(saveto)}\n save_status(statfile, 'table', savestate)","def input_models():\n return [\n PDBFile(\n Path(golden_data, \"protdna_complex_1.pdb\"),\n path=golden_data,\n score=42.0,\n restr_fname=Path(golden_data, \"example_ambig_1.tbl\")\n ),\n PDBFile(\n Path(golden_data, \"protdna_complex_2.pdb\"),\n path=golden_data,\n score=28.0,\n restr_fname=Path(golden_data, \"example_ambig_2.tbl\")\n )]","def combine_list_allformats(\n reference_genome_list, new_ref_genome_label, project):\n rg_dataset_list = []\n for ref_genome in reference_genome_list:\n rg_dataset_tup = None\n for dataset_type in [\n Dataset.TYPE.REFERENCE_GENOME_GENBANK,\n Dataset.TYPE.REFERENCE_GENOME_FASTA]:\n filter_result = ref_genome.dataset_set.filter(type=dataset_type)\n if len(filter_result):\n rg_dataset_tup = (ref_genome, filter_result[0])\n break\n if (not rg_dataset_tup or\n not os.path.exists(rg_dataset_tup[1].get_absolute_location())):\n return {\n 'is_success': False,\n 'error_msg': 'All reference genomes must have an associated \\\n FASTA or Genbank dataset'\n }\n else:\n rg_dataset_list.append(rg_dataset_tup)\n assert len(rg_dataset_list) == len(reference_genome_list)\n\n # Read the datasets into Biopython SeqRecord objects.\n rg_seqrecord_list = []\n seqrecord_ids = []\n seqrecord_descriptions = []\n for rg, dataset in rg_dataset_list:\n with open(dataset.get_absolute_location()) as input_fh:\n for record in SeqIO.parse(\n input_fh, DATASET_TO_SEQIO_FORMAT[dataset.type]):\n rg_seqrecord_list.append((rg, record))\n seqrecord_ids.append('_'.join([\n remove_whitespace(rg.label)[:7],\n remove_whitespace(record.id)[:8]]))\n seqrecord_descriptions.append(record.description)\n\n # Create a new ReferenceGenome.\n new_ref_genome = ReferenceGenome.objects.create(\n project=project,\n label=new_ref_genome_label)\n\n # If ReferenceGenome label and Chromosome id are the same, there will be\n # duplicate seqrecord_ids: resolve by including numeric prefix in id\n seq_record_list = []\n MAX_LOCUS_NAME_LEN = 16\n unique_id_len = len(str(len(seqrecord_ids)))\n label_len = (MAX_LOCUS_NAME_LEN - 2 - unique_id_len) / 2\n for i, seqrecord_id in enumerate(seqrecord_ids):\n rg, seqrecord = rg_seqrecord_list[i]\n\n if seqrecord_ids.count(seqrecord_id) == 1:\n unique_seqrecord_id = seqrecord_id\n else:\n unique_seqrecord_id = '_'.join([\n str(i),\n remove_whitespace(rg.label)[:label_len],\n remove_whitespace(seqrecord.id)[:label_len]])\n\n seqrecord.seq.alphabet = ambiguous_dna\n seqrecord.name = unique_seqrecord_id\n seqrecord.id = unique_seqrecord_id\n\n if seqrecord_descriptions.count(seqrecord.description) > 1:\n seqrecord.description = ' '.join([\n seqrecord.description,\n 'from Reference Genome:', rg.label])\n\n seq_record_list.append(seqrecord)\n Chromosome.objects.create(\n reference_genome=new_ref_genome,\n label=seqrecord.id,\n seqrecord_id=seqrecord.id,\n num_bases=len(seqrecord))\n\n # Generate a filename from the label with non-alphanumeric characters\n # replaced by underscores.\n filename_prefix = generate_safe_filename_prefix_from_label(\n new_ref_genome_label)\n does_list_include_genbank = (\n Dataset.TYPE.REFERENCE_GENOME_GENBANK in\n [rg_dataset_tup[1].type for rg_dataset_tup in rg_dataset_list])\n\n if does_list_include_genbank:\n filename = filename_prefix + '.gb'\n else:\n filename = filename_prefix + '.fa'\n new_file_dest = os.path.join(new_ref_genome.get_model_data_dir(), filename)\n\n # Write the result.\n if does_list_include_genbank:\n ref_genome_dataset_type = Dataset.TYPE.REFERENCE_GENOME_GENBANK\n else:\n ref_genome_dataset_type = Dataset.TYPE.REFERENCE_GENOME_FASTA\n output_file_format = DATASET_TO_SEQIO_FORMAT[ref_genome_dataset_type]\n\n with open(new_file_dest, 'w') as output_fh:\n SeqIO.write(seq_record_list, output_fh, output_file_format)\n\n # Create a dataset which will point to the file. This step must happen\n # after writing the file because a signal will be triggered which requires\n # the Genbank to exist already.\n add_dataset_to_entity(\n new_ref_genome, ref_genome_dataset_type, ref_genome_dataset_type,\n new_file_dest)\n\n return {\n 'is_success': True,\n 'new_reference_genome': new_ref_genome\n }","def fetch(id_list):\n database = 'pmc' if 'PMC' in id_list[0][0] else 'pubmed'\n print(database)\n for sublist in id_list:\n with Entrez.efetch(db=database, id=','.join(sublist),\n retmode='xml') as handle:\n records = Entrez.read(handle)\n\n write_csv_file(records, output_file)","def make_doi_table(dataset: ObservatoryDataset) -> List[Dict]:\n\n records = []\n for paper in dataset.papers:\n # Doi, events and grids\n doi = paper.doi.upper()\n events = make_doi_events(doi, paper.events)\n\n # Affiliations: institutions, countries, regions, subregion, funders, journals, publishers\n institutions = make_doi_institutions(paper.authors)\n countries = make_doi_countries(paper.authors)\n regions = make_doi_regions(paper.authors)\n subregions = make_doi_subregions(paper.authors)\n funders = make_doi_funders(paper.funders)\n journals = make_doi_journals(paper.in_unpaywall, paper.journal)\n publishers = make_doi_publishers(paper.publisher)\n\n # Make final record\n records.append(\n {\n \"doi\": doi,\n \"crossref\": {\n \"type\": paper.type,\n \"title\": paper.title,\n \"published_year\": paper.published_date.year,\n \"published_month\": paper.published_date.month,\n \"published_year_month\": f\"{paper.published_date.year}-{paper.published_date.month}\",\n \"funder\": [{\"name\": funder.name, \"DOI\": funder.doi} for funder in paper.funders],\n },\n \"unpaywall\": {},\n \"unpaywall_history\": {},\n \"open_citations\": {},\n \"events\": events,\n \"affiliations\": {\n \"doi\": doi,\n \"institutions\": institutions,\n \"countries\": countries,\n \"subregions\": subregions,\n \"regions\": regions,\n \"groupings\": [],\n \"funders\": funders,\n \"authors\": [],\n \"journals\": journals,\n \"publishers\": publishers,\n },\n }\n )\n\n # Sort to match with sorted results\n records.sort(key=lambda r: r[\"doi\"])\n\n return records","def fetchReferences(self, dataRef, exposure):\n skyMap = dataRef.get(self.dataPrefix + \"skyMap\", immediate=True)\n tractInfo = skyMap[dataRef.dataId[\"tract\"]]\n patch = tuple(int(v) for v in dataRef.dataId[\"patch\"].split(\",\"))\n patchInfo = tractInfo.getPatchInfo(patch)\n references = lsst.afw.table.SourceCatalog(self.references.schema)\n references.extend(self.references.fetchInPatches(dataRef, patchList=[patchInfo]))\n return references","def generate_pr_table(start_ref, end_ref):\r\n header = \"|| Merged By || Author || Title || PR || JIRA || Verified? ||\"\r\n pr_link = \"[#{num}|https://github.com/edx/edx-platform/pull/{num}]\"\r\n user_link = \"[@{user}|https://github.com/{user}]\"\r\n rows = [header]\r\n prbe = prs_by_email(start_ref, end_ref)\r\n for email, pull_requests in prbe.items():\r\n for i, pull_request in enumerate(pull_requests):\r\n try:\r\n pr_info = get_pr_info(pull_request)\r\n title = pr_info[\"title\"] or \"\"\r\n body = pr_info[\"body\"] or \"\"\r\n author = pr_info[\"user\"][\"login\"]\r\n except requests.exceptions.RequestException as e:\r\n message = (\r\n \"Warning: could not fetch data for #{num}: \"\r\n \"{message}\".format(num=pull_request, message=e.message)\r\n )\r\n print(colorize(\"red\", message), file=sys.stderr)\r\n title = \"?\"\r\n body = \"?\"\r\n author = \"\"\r\n rows.append(\"| {merged_by} | {author} | {title} | {pull_request} | {jira} | {verified} |\".format(\r\n merged_by=email if i == 0 else \"\",\r\n author=user_link.format(user=author) if author else \"\",\r\n title=title.replace(\"|\", \"\\|\"),\r\n pull_request=pr_link.format(num=pull_request),\r\n jira=\", \".join(parse_ticket_references(body)),\r\n verified=\"\",\r\n ))\r\n return \"\\n\".join(rows)","def make_reference(self):\r\n d = dict([(\"M\", 1000),\r\n (\"CM\", 800),\r\n (\"D\", 500),\r\n (\"CD\", 300),\r\n (\"C\", 100),\r\n (\"XC\", 80),\r\n (\"L\", 50),\r\n (\"XL\", 30),\r\n (\"X\", 10),\r\n (\"IX\", 8),\r\n (\"V\", 5),\r\n (\"IV\", 3),\r\n (\"I\", 1),])\r\n return d","def doit():\n myp = MyPapers()\n cites = Cites(myp.mypapers)\n #cites.cite_report()\n cites.compare_and_update()","def get_references(input, verbose=False):\n\n # TODO: Make this a class reference parser\n\n # *** These tags are mobile-site specific\n\n # When we don't have proper access rights, this is present in the html\n GUEST_TAG_TUPLE = (\"li\", {\"id\": \"menuGuest\"})\n\n # Entries are \"li\" tags with classes of the form:\n # article-reference-article\n # article-reference-other-ref\n REFERENCE_TAG_TUPLE = (\"li\", {\"class\": re.compile('article-reference-*')})\n\n # This is the URL to the page that contains the document info, including\n # reference material\n BASE_URL = _SD_URL + '/science/article/pii/'\n\n # This URL was found first via Fiddler, then via closer inspection of the script\n # 'article_catalyst.js' under sciencedirect.com/mobile/js in the function\n # resolveReferences\n REF_RESOLVER_URL = _SD_URL + '/science/referenceResolution/ajaxRefResol'\n\n # Return the BeautifulSoup result, the requests session, and the requests response\n if _is_url(input):\n pii = _extract_pii(input)\n else:\n pii = input\n\n sess = requests.Session()\n\n if verbose:\n print('Requesting main page for pii: %s' % pii)\n resp = sess.get(BASE_URL + pii, cookies={'Site': 'Mobile'})\n\n # Step 2 - Get the reference tags\n\n soup = BeautifulSoup(resp.text)\n\n reference_section = soup.find(\"ol\", {\"class\": \"article-references\"})\n\n if reference_section is None:\n # Then we might be a guest. In other words, we might not have sufficient\n # privileges to access the data we want. Generally this is protected via\n # IP mask. When I'm working from home I need to VPN into work so\n # that I can access the data :/\n print(\"reference_section is None\")\n temp = soup.find(*GUEST_TAG_TUPLE)\n if temp is None:\n # We might have no references ... (Doubtful)\n raise ParseException(\"References were not found ..., code error likely\")\n else:\n raise InsufficientCredentialsException(\n \"Insufficient access rights to get referencs, requires certain IP addresses (e.g. university based IP)\")\n\n ref_tags = reference_section.find_all(*REFERENCE_TAG_TUPLE)\n\n n_refs = len(ref_tags)\n\n if n_refs == 0:\n return None\n\n # Step 3 - Resolve reference links\n # --------------------------------------------------------------------------\n # The returned html code contains javascript which returns more information\n # about each reference, such as:\n #\n # - links to the full text\n # - DOI \n\n\n # Step 3.1 - Make the request for the information\n # --------------------------------------------------------------------------\n # We need the eid of the current entry, it is of the form:\n #\n # SDM.pm.eid = \"1-s2.0-0006899387903726\"\n #\n # * I think this entry gets deleted after the requests so it may not be\n # visible if looking for it in Chrome. \n match = re.search('SDM\\.pm\\.eid\\s*=\\s*\"([^\"]+)\"', resp.text)\n #eid = match.group(1)\n\n # This list comes from the resolveReferences function in article_catalyst.js\n payload = {\n '_pii': pii,\n '_refCnt': n_refs,\n '_docType': 'article', # yikes, this might change ...\n '_refRangeStart': '1',\n '_refRangeCount': str(n_refs)} # This is normally in sets of 20's ...\n # I'm not sure if it is important to limit this. The browser then\n # makes a request fromr 1 count 20, 21 count 20, 41 count 20 etc,\n # It always goes by 20 even if there aren't 20 left\n\n if verbose:\n print('Requesting reference links')\n r2 = sess.get(REF_RESOLVER_URL, params=payload)\n\n # Step 3.2 - Parse the returned information into single entries\n # --------------------------------------------------------------------------\n # This could probably be optimized in terms of execution time. We basically\n # get back a single script tag. Inside is some sort of hash map for links\n # for each reference.\n #\n # The script tag is of the form:\n # myMap['bibsbref11']['refHtml']= \"<some html stuffs>\"; \n # myMap['bibsbref11']['absUrl']= \"http://www.sciencedirect.com/science/absref/sd/0018506X7790068X\";\n # etc.\n #\n # - Each entry is quite long.\n # - Normally contains html\n # - can be empty i.e. myMap['bibsbref11']['refHtml'] = \"\";\n # - the refHtml is quite interesting\n # - the absolute url is not always present (and currently not parsed)\n more_soup = BeautifulSoup(r2.text)\n script_tag = more_soup.find('script')\n\n # We unquote the script text as it is transmitted with characters escaped\n # and we want the parsed data to contain the non-escaped text\n #\n # We might eventually want to move this to being after the regular expression ...\n script_text = urllib_unquote(script_tag.text)\n\n ref_match_result = re.findall(\"myMap\\['bibsbref(\\d+)'\\]\\['refHtml'\\]=\\s?\" + '\"([^\"]*)\";', script_text)\n # Tokens:\n # 0 - the # from bibsbref#\n # 1 - the html content from the 'refHtml' entry\n # \n # NOTE: We don't really use the #, so we might remove the () around\n # \\d+ which would shift the index from 1 to 0\n if verbose:\n print('Creating reference objects')\n\n if len(ref_match_result) > 0:\n zipped = zip(ref_tags, ref_match_result, range(n_refs))\n ref_objects = [ScienceDirectRef(ref_tag, ref_link_info[1], ref_id) for\n ref_tag, ref_link_info, ref_id in zipped]\n else:\n zipped = zip(ref_tags, range(n_refs))\n ref_objects = [ScienceDirectRef(ref_tag, ref_id) for\n ref_tag, ref_id in zipped]\n\n # Step 4:\n # --------------------------------------------------------------------------\n # TODO: Improve documentation for this step\n\n if verbose:\n print('Retrieving Scopus Counts')\n\n ref_scopus_eids = [] # The Scopus IDs of the references to resolve\n # but with a particular formatting ...\n ref_count = 0 # Number of references we haven't resolved\n\n ref_count_list = []\n # NOTE: Browser requests these in the reverse order ...\n for ref_id, ref in enumerate(ref_objects):\n\n if ref._data_sceid is not None:\n ref_scopus_eids.append(ref._data_sceid + ',' + str(ref_id + 1) + '~')\n ref_count += 1\n\n # If we've got enough, then update the counts\n # The 20 may be arbitrary but it was what was used in original JS\n if ref_count > 20:\n ref_count_list += _update_counts(sess, ref_scopus_eids, REF_RESOLVER_URL)\n ref_count = 0\n ref_scopus_eids = []\n\n # Get any remaining reference counts\n if ref_count != 0:\n ref_count_list += _update_counts(sess, ref_scopus_eids, REF_RESOLVER_URL)\n\n # Take the raw data and set the citation count for each object\n for ref_tuple in ref_count_list:\n ref_id = int(ref_tuple[0]) - 1\n ref_count = int(ref_tuple[1])\n ref_objects[ref_id].scopus_cite_count = ref_count\n\n # All done!\n # ---------\n return ref_objects","async def create_tables():\n text_create_citizens_table = queries.CREATE_CITIZENS\n text_create_relative_table = queries.CREATE_RELATIVES\n text_create_consts_table = queries.CREATE_CONSTS\n text_insert_base_import_id = queries.INSERT_IMPORT_ID_0\n text_create_index_citizens = queries.CREATE_INDEX_CITIZENS\n text_create_index_relatives = queries.CREATE_INDEX_RELATIVES\n\n queries_list = [text_create_citizens_table, text_create_relative_table,\n text_create_consts_table, text_insert_base_import_id,\n text_create_index_citizens,text_create_index_relatives]\n\n connection = await sql.connect()\n async with connection.transaction():\n for query in queries_list:\n await sql.execute_query(connection, query)\n await sql.close(connection)","def build_latex(file_list):\n eingabe=[]\n anhang_count=0\n anhaenge=[]\n anhaenge_file=[]\n for file in file_list:\n x=load_file(file)[1]\n eingabe.append(\"\\section{%s}\" %(x[2]))\n eingabe.append(\"\\subsection{Infos}\")\n eingabe.append(\"\\\\begin{tabularx}{\\linewidth}{@{}lX}\")\n eingabe.append(r\"\\textbf{Datum} & %s\\\\\" %(x[0]))\n eingabe.append(r\"\\textbf{Gremium} & %s\\\\\" %(x[1]))\n eingabe.append(r\"\\textbf{Anatrag/Beschluss wurde} & %s\\\\\" %(x[9]))\n x[11]=x[11].replace(\" \",\"\")\n kw=x[11].split(\",\")\n for i in range(0,len(kw)):\n if i==0:\n eingabe.append(r\"\\textbf{Keyword:} & %s\\\\\" %(kw[i]))\n else:\n eingabe.append(r\" & %s\\\\\" %(kw[i]))\n eingabe.append(\"\\end{tabularx}\")\n eingabe.append(\"\\\\begin{tabularx}{\\linewidth}{@{}XXX}\")\n eingabe.append(r\"\\textbf{Abstimmungsergebniss:}&&\\\\\")\n eingabe.append(r\"Zustimmung & Ablehnung & Enthaltungen \\\\\")\n eingabe.append(r\"{} & {} & {} \\\\\".format(x[6],x[7],x[8]))\n eingabe.append(\"\\end{tabularx}\")\n eingabe.append(\"\\subsection{Antrags/Beschlusstext}\")\n line_text=len(eingabe)\n eingabe.append(x[3])\n eingabe.append(\"\\subsection{Begründung}\")\n eingabe.append(x[4])\n if x[23]==\"Ja\" and x[24]!=\"\":\n delta=7\n anzahl=int((len(x)-23)/delta)\n if anzahl==1:\n eingabe.append(\"\\subsection{Änderungsantrag}\")\n eingabe.append(\"\\subsubsection*{Vorschlag}\")\n eingabe.append(x[24])\n eingabe.append(\"\\subsubsection*{Begründung}\")\n eingabe.append(x[25]+\"\\\\vspace{1.5ex} \\\\\\\\\")\n eingabe.append(\"\\\\begin{tabularx}{\\linewidth}{@{}XXX}\")\n eingabe.append(r\"\\textbf{Abstimmungsergebniss:}&&\\\\\")\n eingabe.append(r\"Zustimmung & Ablehnung & Enthaltungen \\\\\")\n eingabe.append(r\"{} & {} & {} \\\\\".format(x[26],x[27],x[28]))\n eingabe.append(r\"\\multicolumn{2}{@{}l}{\\textbf{Änderungsantrag wurde:}} & %s \\\\\" %(x[29]))\n eingabe.append(\"\\\\end{tabularx}\")\n else:\n eingabe.append(\"\\subsection{Änderungsanträge}\")\n for i in range(0,anzahl):\n eingabe.append(\"\\subsubsection{Änderungsvorschlag %s}\" %(i+1))\n eingabe.append(\"\\\\paragraph*{Vorschlag}\")\n eingabe.append(x[24+(delta*i)])\n eingabe.append(\"\\\\paragraph*{Begründung}\")\n eingabe.append(x[25+(delta*i)]+\"\\\\vspace{1.5ex} \\\\\\\\\")\n eingabe.append(\"\\\\begin{tabularx}{\\linewidth}{@{}XXX}\")\n eingabe.append(r\"\\textbf{Abstimmungsergebniss:}&&\\\\\")\n eingabe.append(r\"Zustimmung & Ablehnung & Enthaltungen \\\\\")\n eingabe.append(r\"{} & {} & {} \\\\\".format(x[26+(delta*i)],x[27+(delta*i)],x[28+(delta*i)]))\n eingabe.append(r\"\\multicolumn{2}{@{}l}{\\textbf{Änderungsantrag wurde:}} & %s \\\\\" %(x[29+(delta*i)]))\n eingabe.append(\"\\\\end{tabularx}\")\n if x[10]!=\"\":\n anhang=x[10].split(\",\")\n bennenung=x[11].split(\",\")\n eingabe[line_text]=eingabe[line_text]+\"\\\\\\\\ \\n Dieser Antrag enthält %s Anhänge: \" %(len(anhang))\n for i in range(0,len(anhang)):\n anhang_count=anhang_count+1\n anhaenge.append(\"\\section{%s - %s} \\label{An:%s}\" % (x[2],bennenung[i],str(anhang_count)))\n anhaenge.append(\"\\includepdf[pages=-]{%s}\" %(anhang[i]))\n anhaenge_file.append(anhang[i])\n if i!=len(anhang)-1:\n eingabe[line_text]=eingabe[line_text]+\"\\\\nameref{An:%s}, \" % (str(anhang_count))\n else:\n eingabe[line_text]=eingabe[line_text]+\"\\\\nameref{An:%s} \" % (str(anhang_count)) \n \n eingabe.append(\"\\\\newpage\") \n eingabe.append(\"\\\\appendix\") \n eingabe.append(\"\\\\pagenumbering{Roman}\") \n ausgabe=\"\"\n for i in range(0,len(eingabe)):\n ausgabe=ausgabe+eingabe[i]+\"\\n\"\n \n for i in range(0,len(anhaenge)):\n ausgabe=ausgabe+anhaenge[i]+\"\\n\"\n \n return ausgabe,anhaenge_file","def write_to_latex(codelist, unwanted_courses):\n # TODO: investigate a way to add large amounts of text outside of the\n # function\n abstract01 = \"I created this document to practice parsing html and using\\\n tools like Beautiful Soup which I've previously had little experience\\\n in. As a result, it's not perfect.\\\\newline\\\n It is also a slightly condensed all-in-one-place look at a selection\\\n of courses that are available for fourth year computer science\\\n students at the University of Glasgow. For the purposes of clarity I\\\n have removed several courses from this selection. The following\\\n courses have been omitted:\"\n abstract02 = \"For more insight into the project, to report issues or to\\\n inspect the code, have a look at the GitHub:\\\n \\\\url{https://github.com/IS0metric/course-ripper}\"\n unincluded = create_not_included_list(unwanted_courses)\n with open('courses.tex', 'w') as f:\n # TODO Try and move all this to a separate function?\n # TODO: Check if it's more efficient to write a single, massive string\n # to file\n f.write('\\\\documentclass{hitec}\\n')\n f.write('\\\\usepackage[document]{ragged2e}\\n')\n f.write('\\\\usepackage{url}\\n')\n f.write('\\\\usepackage{hyperref}\\n')\n f.write('\\\\setcounter{tocdepth}{4}\\n')\n f.write('\\\\begin{document}\\n')\n f.write('\\\\title{Fourth Year (2016-17) Courses}\\n')\n f.write('\\\\author{Jack Parkinson}\\n')\n f.write('\\\\date{August 2016}\\n')\n f.write('\\\\maketitle\\n')\n f.write('\\\\abstract{' + abstract01 + unincluded + abstract02 + '}\\n')\n f.write('\\\\newpage\\n\\n')\n f.write('\\\\tableofcontents\\n')\n f.write('\\\\newpage\\n\\n')\n # TODO: Look into alternatives to the three lists\n all_courses = []\n sem1_courses = []\n sem2_courses = []\n for code in codelist:\n course = bsoup(get_coursepage(code))\n if course['offered']['value'] == 'Runs Throughout Semesters 1 and 2':\n all_courses.append(course)\n elif \"1\" in course['offered']['value']:\n sem1_courses.append(course)\n elif \"2\" in course['offered']['value']:\n sem2_courses.append(course)\n f.write('\\\\section{Semester 1 and 2 Courses}\\n\\n')\n for course in all_courses:\n f.write(latex_course(course))\n f.write('\\\\section{Semester 1 Only Courses}\\n\\n')\n for course in sem1_courses:\n f.write(latex_course(course))\n f.write('\\\\section{Semester 2 Only Courses}\\n\\n')\n for course in sem2_courses:\n f.write(latex_course(course))\n f.write('\\\\end{document}')\n return None","def write_reference_page(outfile: TextIO, do_print: bool, ref: TMB_Classes.ReferenceClass, citelist: list,\n refdict: dict, name_table: dict, point_locations: dict) -> None:\n if do_print:\n start_page_division(outfile, \"ref_page\")\n else:\n common_html_header(outfile, ref.citation, indexpath=\"../\")\n outfile.write(\" <header id=\\\"\" + ref.cite_key + \".html\\\">\\n\")\n outfile.write(\" <h2 class=\\\"nobookmark\\\">\" + ref.formatted_html + \"</h2>\\n\")\n if not do_print:\n outfile.write(\" <nav>\\n\")\n outfile.write(\" <ul>\\n\")\n outfile.write(\" <li><a href=\\\"../\" + init_data().ref_url +\n \"\\\">\" + fetch_fa_glyph(\"index\") + \"Full Reference List</a></li>\\n\")\n outfile.write(\" </ul>\\n\")\n outfile.write(\" </nav>\\n\")\n outfile.write(\" </header>\\n\")\n outfile.write(\"\\n\")\n # find names for this citation\n names = []\n cites_to = []\n for c in citelist:\n if c.cite_key == ref.cite_key:\n names.append(c)\n if c.application == ref.cite_key:\n cites_to.append(c)\n started_note = False\n comcnt = 0\n notecnt = 0\n uniquenames = set()\n for n in names:\n if n.general_note != \".\":\n if not started_note:\n outfile.write(\" <p>\\n\")\n started_note = True\n outfile.write(\" \" + replace_species_in_string(n.general_note) + \"\\n\")\n if n.common != \".\":\n comcnt += 1\n if n.name_note != \".\":\n notecnt += 1\n uniquenames |= {n.name}\n if started_note:\n outfile.write(\" </p>\\n\")\n\n if ref.language != \"\":\n outfile.write(\"<p><strong>Language:</strong> \" + format_language(ref.language) + \"</p>\\n\")\n if ref.doi is not None:\n outfile.write(\"<p><strong>Online:</strong> \")\n if ref.doi.startswith(\"10\"):\n outfile.write(\"<img src=\\\"../images/DOI_logo.svg\\\" style=\\\"height: 1em; vertical-align: middle\\\" \"\n \"alt=\\\"DOI\\\"> \")\n outfile.write(\"<a href=\\\"https://doi.org/{0}\\\">https://doi.org/{0}</a></p>\\n\".format(ref.doi))\n else:\n outfile.write(\"{0}</p>\\n\".format(ref.doi))\n\n # write name table\n outfile.write(\" <h3 class=\\\"nobookmark\\\">Names Appearing in this Publication</h3>\\n\")\n if len(names) > 0:\n outfile.write(\" <table class=\\\"citetable\\\">\\n\")\n outfile.write(\" <tr>\\n\")\n outfile.write(\" <th class=\\\"name_col\\\">Name Used</th>\\n\")\n if comcnt > 0:\n outfile.write(\" <th class=\\\"common_col\\\">Common Name(s)</th>\\n\")\n outfile.write(\" <th class=\\\"where_col\\\">Where</th>\\n\")\n outfile.write(\" <th class=\\\"applied_col\\\">Applied to...</th>\\n\")\n outfile.write(\" <th class=\\\"accepted_col\\\">Accepted Name</th>\\n\")\n outfile.write(\" <th class=\\\"source_col\\\">Source of Accepted</th>\\n\")\n if notecnt > 0:\n outfile.write(\" <th class=\\\"notes_col\\\">Note(s)</th>\\n\")\n outfile.write(\" </tr>\\n\")\n names.sort()\n output_name_table(outfile, do_print, False, names, uniquenames, notecnt, comcnt, refdict, name_table,\n point_locations)\n else:\n outfile.write(\" <p>\\n\")\n outfile.write(\" Data not yet available.\\n\")\n outfile.write(\" </p>\\n\")\n\n if len(cites_to) > 0:\n outfile.write(\" <h3 class=\\\"nobookmark\\\">This Publication is Cited By</h3>\\n\")\n outfile.write(\" <p>\\n\")\n cs = set()\n for c in cites_to:\n if c.cite_key in refdict:\n crossref = refdict[c.cite_key]\n cs |= {\"<a href=\\\"\" + rel_link_prefix(do_print) + crossref.cite_key +\n \".html\\\">\" + crossref.citation + \"</a>\"}\n else:\n cs |= {c.cite_key}\n cl = []\n for x in cs:\n cl.append(x)\n cl.sort()\n outfile.write(\" \" + \", \".join(cl) + \"\\n\")\n outfile.write(\" </p>\\n\")\n\n if do_print:\n end_page_division(outfile)\n else:\n common_html_footer(outfile, indexpath=\"../\")","def label_data(data_dir):\n # Reads in the metadata matrices (i.e., paper by metadata matrix)\n metadata_dir = os.path.join(data_dir, 'metadata/')\n filenames = sorted(glob(os.path.join(metadata_dir, 'Karina*.csv')))\n\n converter = {'Paradigm Class': 'ParadigmClass',\n 'Behavioral Domain': 'BehavioralDomain',\n 'Diagnosis': 'Diagnosis',\n 'Stimulus Modality': 'StimModality',\n 'Stimulus Type': 'StimType',\n 'Response Modality': 'RespModality',\n 'Response Type': 'RespType',\n 'Instructions': 'Instruction'}\n\n columns = converter.keys()\n\n # Cycles through all columns and all metadata files and concatenates everything\n metadata_dfs = [pd.read_csv(file_, dtype=str)[['PubMed ID'] + converter.keys()] for file_ in filenames]\n metadata_df = pd.concat(metadata_dfs, ignore_index=True)\n\n # Transforms to table format and sorts the metadata matrices\n all_labels = []\n for column in converter.keys():\n dimension = converter[column]\n dim_labels = get_label_parents(metadata_df, column, dimension)\n all_labels += dim_labels\n\n all_labels = [label_con.get(label, label) for label in all_labels]\n all_labels = [label for label in all_labels if label != 'DROP']\n all_labels = sorted(list(set(all_labels)))\n\n # Get list of annotated papers with associated files\n metadata_df = metadata_df[metadata_df['PubMed ID'].str.contains('^\\d+$')].reset_index()\n list_of_pmids = metadata_df['PubMed ID'].unique().tolist()\n\n column_names = ['pmid'] + all_labels\n label_df = pd.DataFrame(columns=column_names, data=np.zeros((len(list_of_pmids), len(column_names))))\n label_df['pmid'] = list_of_pmids\n\n # This generates a binary matrix of pmids by all labels.\n for row in metadata_df.index:\n pmid = metadata_df['PubMed ID'].iloc[row]\n\n # Only label papers with associated files.\n if pmid in list_of_pmids:\n for column in columns:\n exp_labels = metadata_df[column].iloc[row]\n if pd.notnull(exp_labels):\n exp_labels = exp_labels.split('| ')\n exp_labels = ['{0}.{1}'.format(converter[column], clean_str(label)) for label in exp_labels]\n for label in exp_labels:\n corr_label = label_con.get(label, label)\n for out_column in label_df.columns:\n # Count each label toward itself and its parents.\n if corr_label.startswith(out_column):\n out_row = label_df.loc[label_df['pmid']==pmid].index[0]\n label_df[out_column].iloc[out_row] = 1\n\n # Save DataFrames.\n count_df = label_df.sum().to_frame()\n label_df = label_df.astype(int).astype(str)\n out_file = os.path.join(data_dir, 'labels/fiu_labels.csv')\n label_df.to_csv(out_file, index=False)\n\n count_file = os.path.join(data_dir, 'labels/label_counts.csv')\n count_df = count_df.ix[1:]\n count_df.index.name = 'Label'\n count_df.columns = ['Count']\n count_df.to_csv(count_file, index=True)","def calculate_name_index_data(refdict: dict, citelist: list, specific_names: list) -> Tuple[list, dict, dict, dict,\n dict, dict, dict, dict,\n dict, dict]:\n name_table = create_name_table(citelist)\n unique_names = list()\n nameset = set()\n # total_binomial_year_cnts = {}\n total_binomial_year_cnts = collections.Counter()\n for c in citelist:\n if c.name != \".\":\n clean = clean_name(c.name)\n if not clean.lower() in nameset:\n nameset |= {clean.lower()}\n unique_names.append(clean)\n y = refdict[c.cite_key].year()\n if y is not None:\n total_binomial_year_cnts.update([y])\n # if y in total_binomial_year_cnts:\n # total_binomial_year_cnts[y] += 1\n # else:\n # total_binomial_year_cnts[y] = 1\n unique_names.sort(key=lambda s: s.lower())\n\n # identify genera used per paper\n genera_per_paper = {}\n for c in citelist:\n if c.name != \".\":\n if c.cite_key not in genera_per_paper:\n genera_per_paper[c.cite_key] = set()\n genera_set = genera_per_paper[c.cite_key]\n genera_set |= {extract_genus(clean_name(c.name))}\n genus_cnts = {}\n for c in genera_per_paper:\n y = refdict[c].year()\n if y is not None:\n if init_data().start_year <= y <= init_data().current_year:\n genera_set = genera_per_paper[c]\n for genus in genera_set:\n genus = clean_genus(genus)\n if genus != \"\":\n genus_cnts.setdefault(genus, {y: 0 for y in range(init_data().start_year,\n init_data().current_year + 1)})[y] += 1\n # if genus not in genus_cnts:\n # genus_cnts[genus] = {y: 0 for y in range(init_data().start_year,\n # init_data().current_year + 1)}\n # gcnts = genus_cnts[genus]\n # gcnts[y] += 1\n\n binomial_usage_cnts_by_year = {}\n binomial_location_applications = {}\n binomial_usage_cnts = {}\n for name in unique_names:\n binomial_usage_cnts_by_year[name], tmptotal = calculate_binomial_yearly_cnts(name, refdict, citelist)\n if tmptotal > 0:\n binomial_usage_cnts[name] = tmptotal\n binomial_location_applications[name] = calculate_binomial_locations(name, citelist)\n\n # specific_year_cnts = {}\n specific_year_cnts = collections.Counter()\n specific_usage_cnts_by_year = {}\n specific_location_applications = {}\n specific_usage_cnts = {}\n for name in specific_names:\n (specific_usage_cnts_by_year[name.name],\n tmptotal) = calculate_specific_name_yearly_cnts(name, unique_names, binomial_usage_cnts_by_year)\n if tmptotal > 0:\n specific_usage_cnts[name.name] = tmptotal\n specific_location_applications[name] = calculate_specific_locations(name, unique_names,\n binomial_location_applications)\n tmpkey = name.priority_source\n if tmpkey != \".\":\n y = refdict[tmpkey].year()\n if y is not None:\n specific_year_cnts.update([y])\n # if y in specific_year_cnts:\n # specific_year_cnts[y] += 1\n # else:\n # specific_year_cnts[y] = 1\n return (unique_names, binomial_usage_cnts_by_year, specific_usage_cnts_by_year, genus_cnts,\n total_binomial_year_cnts, name_table, specific_location_applications, binomial_location_applications,\n binomial_usage_cnts, specific_usage_cnts)","def create_lookup_tables(text):\n vocab = set(text.split())\n vocab_to_int = copy.copy(CODES)\n\n for v_i, v in enumerate(vocab, len(CODES)):\n vocab_to_int[v] = v_i\n\n int_to_vocab = {v_i: v for v, v_i in vocab_to_int.items()}\n\n return vocab_to_int, int_to_vocab","def create_numbers_table():\n work_tuples = parse_columns()\n print('\\n\\n\\n ----- Tableau récapitulatif -----')\n print('-----------------------')\n for ii in work_tuples:\n line = '|'\n for ij in ii:\n line += ' ij |'\n print(line)\n print('-----------------------')","def parse_corenlp_coref_xml_doc(input_dir = 'CoreNLP_coref_anno/dev'):\n\n\tmentions = []\n\tfor file in os.listdir(input_dir):\n\t\ttree = ET.parse(input_dir + '/' + file)\n\t\tdocument = tree.getroot()[0]\n\t\t# sentences_node = document.find('sentences')\n\n\t\t# for sentence in enumerate(sentences_node):\n\t\t# \ts_num = sentence.attribs['id']\n\t\t# \tsentence_text = \" \".join([token.word for token in sentence.find('tokens')])\n\t\t# \tsentences[s_num] = sentence_text\n\n\t\tcoref_node = document.find('coreference')\n\t\t\n\t\tfor coref_id, coref_chain in enumerate(coref_node):\n\t\t\tfor mention in cluster:\n\t\t\t\tsent_num = int(mention[0].text)\n\t\t\t\tstart = int(mention[1].text)-1\n\t\t\t\tend = int(mention[2].text)-1\n\t\t\t\ttext = mention[4].text\n\t\t\t\tmentions.append({\"filename\":file, \"s_num\":sent_num,\"EP\":\"E\", \"indices\":range(start, end),\"coref\":coref_id+1})\n\n\tmentions.sort(key=lambda x:(x[\"filename\"],x[\"s_num\"],x[\"indices\"][0]))\n\twith open('coref_output.txt', 'w') as out_file:\n\t\tout_file.write(\"file\\tsentence\\tentity(E) or predicate(P)\\t coref chain\\tindices\\t\\n\")\n\t\tout_file.write(\"\\n\".join([e[\"filename\"]+\"\\t\"+str(e[\"s_num\"])+\"\\t\"+e[\"EP\"]+\"\\t\"+str(e[\"coref\"])+\"\\t\"+str(e[\"indices\"])[1:-1] for e in mentions]))","def data_connections():\r\n section = document.add_section()\r\n new_width, new_height = section.page_height, section.page_width\r\n section.orientation = WD_ORIENT.LANDSCAPE\r\n section.page_width = 10058400\r\n section.page_height = 7772400\r\n document.add_heading('Data connections', level=1)\r\n connections = get_qlik_sense.get_dataconnections()\r\n num_of_connections = len(connections)\r\n table = document.add_table(rows=num_of_connections+1, cols=3)\r\n table.style = 'Grid Table 1 Light Accent 1'\r\n row = table.rows[0]\r\n row.cells[0].text = 'name'\r\n row.cells[1].text = 'connection string'\r\n row.cells[2].text = 'type'\r\n for connection in range(num_of_connections):\r\n row = table.rows[connection+1]\r\n row.cells[0].text = str(connections[connection][0])\r\n row.cells[1].text = str(connections[connection][1])\r\n row.cells[2].text = str(connections[connection][2])\r\n document.add_page_break()","def get_citation_informations(recid_list, config):\n begin_time = os.times()[4]\n d_reports_numbers = {} #dict of recid -> institute-given-report-code\n d_references_report_numbers = {} #dict of recid -> ['astro-ph/xyz']\n d_references_s = {} #dict of recid -> list_of_the_entries_of_this_recs_bibliography\n d_records_s = {} #dict of recid -> this_records_publication_info\n citation_informations = []\n\n write_message(\"config function \"+config.get(\"rank_method\", \"function\"), verbose=9)\n function = \"\"\n try:\n function = config.get(\"rank_method\", \"function\")\n except:\n register_exception(prefix=\"cfg section [rank_method] has no attribute called function\", alert_admin=True)\n #we cannot continue\n return [ {}, {}, {}, {} ]\n record_pri_number_tag = \"\"\n try:\n record_pri_number_tag = config.get(function, \"primary_report_number\")\n except:\n register_exception(prefix=\"cfg section \"+function+\" has no attribute primary_report_number\", alert_admin=True)\n return [ {}, {}, {}, {} ]\n record_add_number_tag = \"\"\n try:\n record_add_number_tag = config.get(config.get(\"rank_method\", \"function\"),\n \"additional_report_number\")\n except:\n register_exception(prefix=\"config error. cfg section \"+function+\" has no attribute additional_report_number\", alert_admin=True)\n return [ {}, {}, {}, {} ]\n\n reference_number_tag = \"\"\n try:\n reference_number_tag = config.get(config.get(\"rank_method\", \"function\"),\n \"reference_via_report_number\")\n except:\n register_exception(prefix=\"config error. cfg section \"+function+\" has no attribute reference_via_report_number\", alert_admin=True)\n return [ {}, {}, {}, {} ]\n\n reference_tag = \"\"\n try:\n reference_tag = config.get(config.get(\"rank_method\", \"function\"),\n \"reference_via_pubinfo\")\n except:\n register_exception(prefix=\"config error. cfg section \"+function+\" has no attribute reference_via_pubinfo\", alert_admin=True)\n return [ {}, {}, {}, {} ]\n\n p_record_pri_number_tag = tagify(parse_tag(record_pri_number_tag))\n #037a: contains (often) the \"hep-ph/0501084\" tag of THIS record\n p_record_add_number_tag = tagify(parse_tag(record_add_number_tag))\n #088a: additional short identifier for the record\n p_reference_number_tag = tagify(parse_tag(reference_number_tag))\n #999C5r. this is in the reference list, refers to other records. Looks like: hep-ph/0408002\n p_reference_tag = tagify(parse_tag(reference_tag))\n #999C5s. A standardized way of writing a reference in the reference list. Like: Nucl. Phys. B 710 (2000) 371\n #fields needed to construct the pubinfo for this record\n publication_pages_tag = \"\"\n publication_year_tag = \"\"\n publication_journal_tag = \"\"\n publication_volume_tag = \"\"\n publication_format_string = \"p v (y) c\"\n try:\n tag = config.get(function, \"pubinfo_journal_page\")\n publication_pages_tag = tagify(parse_tag(tag))\n tag = config.get(function, \"pubinfo_journal_year\")\n publication_year_tag = tagify(parse_tag(tag))\n tag = config.get(function, \"pubinfo_journal_title\")\n publication_journal_tag = tagify(parse_tag(tag))\n tag = config.get(function, \"pubinfo_journal_volume\")\n publication_volume_tag = tagify(parse_tag(tag))\n publication_format_string = config.get(function, \"pubinfo_journal_format\")\n except:\n pass\n\n #print values for tags for debugging\n if task_get_task_param('verbose') >= 9:\n write_message(\"tag values\")\n write_message(\"p_record_pri_number_tag \"+str(p_record_pri_number_tag))\n write_message(\"p_reference_tag \"+str(p_reference_tag))\n write_message(\"publication_journal_tag \"+str(publication_journal_tag))\n write_message(\"publication_format_string is \"+publication_format_string)\n done = 0 #for status reporting\n numrecs = len(recid_list)\n\n # perform quick check to see if there are some records with\n # reference tags, because otherwise get.cit.inf would be slow even\n # if there is nothing to index:\n if run_sql(\"SELECT value FROM bib%sx WHERE tag=%%s LIMIT 1\" % p_reference_tag[0:2],\n (p_reference_tag,)) or \\\n run_sql(\"SELECT value FROM bib%sx WHERE tag=%%s LIMIT 1\" % p_reference_number_tag[0:2],\n (p_reference_number_tag,)):\n for recid in recid_list:\n if (done % 10 == 0):\n task_sleep_now_if_required()\n #in fact we can sleep any time here\n\n if (done % 1000 == 0):\n mesg = \"get cit.inf done \"+str(done)+\" of \"+str(numrecs)\n write_message(mesg)\n task_update_progress(mesg)\n done = done+1\n\n if recid in INTBITSET_OF_DELETED_RECORDS:\n # do not treat this record since it was deleted; we\n # skip it like this in case it was only soft-deleted\n # e.g. via bibedit (i.e. when collection tag 980 is\n # DELETED but other tags like report number or journal\n # publication info remained the same, so the calls to\n # get_fieldvalues() below would return old values)\n continue\n\n pri_report_numbers = get_fieldvalues(recid, p_record_pri_number_tag)\n add_report_numbers = get_fieldvalues(recid, p_record_add_number_tag)\n reference_report_numbers = get_fieldvalues(recid, p_reference_number_tag)\n references_s = get_fieldvalues(recid, p_reference_tag)\n\n l_report_numbers = pri_report_numbers\n l_report_numbers.extend(add_report_numbers)\n d_reports_numbers[recid] = l_report_numbers\n\n if reference_report_numbers:\n write_message(str(recid)+\"'s report number values \"+str(l_report_numbers), verbose=9)\n d_references_report_numbers[recid] = reference_report_numbers\n\n references_s = get_fieldvalues(recid, p_reference_tag)\n if references_s:\n write_message(str(recid)+\"'s \"+str(p_reference_tag)+\" values \"+str(references_s), verbose=9)\n d_references_s[recid] = references_s\n\n #get a combination of\n #journal vol (year) pages\n if publication_pages_tag and publication_journal_tag and \\\n publication_volume_tag and publication_year_tag and publication_format_string:\n tagsvalues = {} #we store the tags and their values here\n #like c->444 y->1999 p->\"journal of foo\",v->20\n tagsvalues[\"p\"] = \"\"\n tagsvalues[\"y\"] = \"\"\n tagsvalues[\"c\"] = \"\"\n tagsvalues[\"v\"] = \"\"\n tmp = get_fieldvalues(recid, publication_journal_tag)\n if tmp:\n tagsvalues[\"p\"] = tmp[0]\n tmp = get_fieldvalues(recid, publication_volume_tag)\n if tmp:\n tagsvalues[\"v\"] = tmp[0]\n tmp = get_fieldvalues(recid, publication_year_tag)\n if tmp:\n tagsvalues[\"y\"] = tmp[0]\n tmp = get_fieldvalues(recid, publication_pages_tag)\n if tmp:\n #if the page numbers have \"x-y\" take just x\n pages = tmp[0]\n hpos = pages.find(\"-\")\n if hpos > 0:\n pages = pages[:hpos]\n tagsvalues[\"c\"] = pages\n #format the publ infostring according to the format\n publ = \"\"\n ok = 1\n for i in range (0, len(publication_format_string)):\n current = publication_format_string[i]\n #these are supported\n if current == \"p\" or current == \"c\" or current == \"v\" \\\n or current == \"y\":\n if tagsvalues[current]:\n #add the value in the string\n publ += tagsvalues[current]\n else:\n ok = 0\n break #it was needed and not found\n else:\n publ += current #just add the character in the format string\n if ok:\n write_message(\"d_records_s (publication info) for \"+str(recid)+\" is \"+publ, verbose=9)\n d_records_s[recid] = publ\n else:\n mesg = \"Warning: there are no records with tag values for \"\n mesg += p_reference_number_tag+\" or \"+p_reference_tag+\". Nothing to do.\"\n write_message(mesg)\n\n mesg = \"get cit.inf done fully\"\n write_message(mesg)\n task_update_progress(mesg)\n\n citation_informations.append(d_reports_numbers)\n citation_informations.append(d_references_report_numbers)\n citation_informations.append(d_references_s)\n citation_informations.append(d_records_s)\n end_time = os.times()[4]\n write_message(\"Execution time for generating citation info from record: %.2f sec\" % \\\n (end_time - begin_time))\n return citation_informations","def lookup(subjects, target):\n\n # regex stuff\n p = re.compile(\"<.*>.* - (.*)</TD>\")\n url = \"https://wl11gp.neu.edu/udcprod8/bwckctlg.p_disp_course_detail?cat_term_in=201630&subj_code_in={0}&crse_numb_in={1}\"\n\n # Get progress bar ready.\n toolbar_width = len(subjects)\n sys.stdout.write(\"[%s]\" % (\" \" * toolbar_width))\n sys.stdout.flush()\n sys.stdout.write(\"\\b\" * (toolbar_width+1)) # return to start of line, after '['\n\n # file I/o\n out = open(target, \"w\")\n\n for subject in subjects:\n for course_num in subjects[subject]:\n page = urllib.urlopen(url.format(subject, course_num)).read()\n match = p.findall(page)\n if match:\n out.write(subject + course_num + \": \" + match[0] + '\\n')\n sys.stdout.write(\"-\")\n sys.stdout.flush()\n\n sys.stdout.write(\"\\n\")","def reference_multi():\n content = textwrap.dedent(\"\"\"\n ; Some line before the first molecule.\n ; Just because.\n\n [ molecule ]\n dummy_0\n\n [ atoms ]\n 0 X1 A\n 1 X2 B\n\n ; Some mess between two molecules.\n\n [ molecule ]\n ; A comment just after the molecule section.\n dummy_1\n\n [ atoms ]\n 0 X2 C\n 1 X3 D\n \"\"\").split('\\n')\n reference = {'universal': {'martini22': {\n 'dummy_0': (\n {(0, 'X1'): [(0, 'A')], (0, 'X2'): [(0, 'B')]},\n {(0, 'A'): {(0, 'X1'): 1.0}, (0, 'B'): {(0, 'X2'): 1.0}},\n [],\n ),\n 'dummy_1': (\n {(0, 'X2'): [(0, 'C')], (0, 'X3'): [(0, 'D')]},\n {(0, 'C'): {(0, 'X2'): 1.0}, (0, 'D'): {(0, 'X3'): 1.0}},\n [],\n ),\n }}}\n return content, reference","def populateReference(self, reference_data_folder=None):\n if reference_data_folder is None:\n reference_data_folder = os.path.join(\"..\", \"default_data\")\n\n files = os.listdir(reference_data_folder)\n\n reference_tables = []\n # Create reference table list\n with self.session_scope() as session:\n self.setupTabletypeMap()\n reference_table_objects = self.metaClasses[TableTypes.REFERENCE]\n for object in list(reference_table_objects):\n reference_tables.append(object.__tablename__)\n\n reference_files = [file for file in files if os.path.splitext(file)[0] in reference_tables]\n for file in reference_files:\n # split file into filename and extension\n table_name, _ = os.path.splitext(file)\n possible_method = 'addTo' + table_name\n method_to_call = getattr(self, possible_method, None)\n if method_to_call:\n with open(os.path.join(reference_data_folder, file), 'r') as f:\n reader = csv.reader(f)\n # skip header\n _ = next(reader)\n with self.session_scope() as session:\n for row in reader:\n # this solves error of add functions which take one\n # value instead of list of strings\n if len(row) == 1:\n method_to_call(row[0])\n else:\n method_to_call(*row)\n else:\n print(f\"Method({possible_method}) not found!\")","def create_tables (cls, env=os.environ):\n\n cur = cls.pri_table_read_cursor (env=env)\n cur.execute ('SPECIALCASE gettablelist')\n ret = cur.fetchall ()\n \n existingtables = set ([x[0].lower() for x in ret])\n\n for tabname in (set (cls.table_desc.keys ()) - existingtables):\n sql, lsd = cls.table_desc[tabname]\n epls, desls, sqlprefix = lsd.get_create_labeling (savels=True)\n\n conn = get_labeled_conn (epls, desls)\n cur = conn.cursor ()\n cur.execute (sql)\n conn.close ()\n lsd.pop_labelset ()\n\n \n import psycopg2\n for sql in cls.sql_createindex:\n conn = get_labeled_conn ()\n cur = conn.cursor ()\n # XXX It would be better to check which indices exist as we do for tables.\n try:\n cur.execute (sql)\n except psycopg2.ProgrammingError, e: \n pass\n conn.close ()","def load_data(data_links_list=(\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\n '/raw_data/raw_data.csv',\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\n '/raw_data/sample_meta_info.tsv')):\n\n # Reading data sets from the links provided.\n df1 = pd.read_csv(data_links_list[0],\n error_bad_lines=False)\n df2 = pd.read_csv(data_links_list[1],\n sep='\\t')\n df2 = df2.set_index(df2['project'])\n # fill the Nas id df1 as \". Makes the groupbys behave better.\n df1.fillna('', inplace=True)\n # repleace 'genus' = 'other' with an empty string to be consistent.\n df1.replace(to_replace='other', value='', inplace=True)\n # Removing duplicate columns.\n del df2['project']\n del df2['ID']\n df1 = df1.set_index(df1['project'])\n # Removing duplicate column.\n del df1['project']\n # Joining the two datasets.\n df = df1.join(df2)\n # Uniformity in non-capitalization of column names.\n df.rename(columns={'Kingdom': 'kingdom', 'Phylum': 'phylum',\n 'Class': 'class', 'Order': 'order',\n 'Family': 'family', 'Genus': 'genus',\n 'Length': 'length'}, inplace=True)\n df.index.names = ['sampleID']\n # Rearranging columns so that abundance is the last column.\n df = df[['kingdom',\t'phylum', 'class', 'order',\n 'family', 'genus', 'length', 'oxygen',\n 'replicate', 'week', 'abundance']]\n assert isinstance(df, pd.DataFrame)\n return df","def co_table():\n\n connection = MongoClient(\n \"mongodb://anshuman264:VJkCopXqbK5smqf0@cluster0-shard-00-00-ouybv.mongodb.net:27017,\"\n \"cluster0-shard-00-01-ouybv.mongodb.net:27017,\"\n \"cluster0-shard-00-02-ouybv.mongodb.net:27017/co_table?ssl=true&replicaSet=Cluster0-shard-0&authSource\"\n \"=admin\")\n\n collection = connection[DBS_NAME][COLLECTION_NAME]\n co_occurrences = collection.find_one()\n co_occurrences = todict(co_occurrences)\n co_list = list(co_occurrences.items())\n co_list = sorted(co_list, key=itemgetter(1), reverse=True)\n print(co_list)\n labels = ['Word', 'Co-Occurrence']\n\n df = pd.DataFrame.from_records(co_list, columns=labels)\n connection.close()\n\n return render_template(\"analysis.html\", tables=[df.to_html()], titles=['na', 'of Research Articles'])","def make_M3LDF_tables(conn, csv_input_dir, Description_Vegetation, DB_LDF):\n\n print(\"Creating M3LDF DB tables from: %s\\n\" % csv_input_dir)\n csv_Canopy_Position_adjust = pd.read_csv(csv_input_dir + 'Canopy_Position_adjust.csv')\n csv_Description_Class = pd.read_csv(csv_input_dir + 'Description_Class.csv')\n csv_Description_Vegetation = pd.read_csv(csv_input_dir + Description_Vegetation)\n csv_Description_Compounds = pd.read_csv(csv_input_dir + 'Description_Compounds.csv')\n csv_Description_References = pd.read_csv(csv_input_dir + 'Description_References.csv')\n csv_DB_LDF = pd.read_csv(csv_input_dir + DB_LDF)\n\n csv_Canopy_Position_adjust.to_sql(\"Canopy Position adjust\", conn, flavor='sqlite', if_exists='replace')\n print(\"'Canopy Position adjust' Table Loaded from: %s\" % csv_input_dir + 'Canopy_Position_adjust.csv')\n\n csv_Description_Class.to_sql(\"Description Class\", conn, flavor='sqlite', if_exists='replace')\n print(\"'Description Class' Table Loaded from: %s\" % csv_input_dir + 'Description_Class.csv')\n\n csv_Description_Vegetation.to_sql(\"Description Vegetation\", conn, flavor='sqlite', if_exists='replace')\n print(\"'Description Vegetation' Table Loaded from: %s\" % csv_input_dir + Description_Vegetation)\n\n csv_Description_Compounds.to_sql(\"Description Compounds\", conn, flavor='sqlite', if_exists='replace')\n print(\"'Description Compounds' Table Loaded from: %s\" % csv_input_dir + 'Description_Compounds.csv')\n\n csv_Description_References.to_sql(\"Description References\", conn, flavor='sqlite', if_exists='replace')\n print(\"'Description References' Table Loaded from: %s\" % csv_input_dir + 'Description_References.csv')\n\n csv_DB_LDF.to_sql(\"DB LDF\", conn, flavor='sqlite', if_exists='replace')\n print(\"'DB LDF' Table Loaded from: %s\" % csv_input_dir + DB_LDF)","def create_table(build_list):\n # extract list of files:\n all_files = build_list.split(',')\n\n output_file = os.getcwd() + \"/fpkm_table.tbl\"\n verbalise(\"B\", \"saving built table to file \", output_file)\n\n awk_cmd = \"\"\"awk '!($10~/FPKM/){\\\n gene_sample[$1,FILENAME]=$9;\\\n samples[FILENAME]=1;genes[$1]=1}\\\n END{printf \"%s\\t\", \"genes\";\\\n for(g in genes){printf \"%s\\t\", g};print \"\";\\\n for(s in samples){printf \"%s\\t\",s;\\\n for(g in genes){printf \"%s\\t\", gene_sample[g,s]};\\\n print \"\"}}' \"\"\"\n\n full_cmd = awk_cmd + \" \".join(all_files) + \">\" + str(output_file)\n\n # build table:\n os.system(full_cmd)\n\n # shorten filenames within table for easier reading!\n #output\n\n return output_file","def main():\n files = init.file_list\n citations = load_citations.load_files(files)\n citations_a = citations[0]\n citations_b = citations[1]\n\n common_citations, num_common = compare_citations.common_citations(citations_a, citations_b)\n save_citations.save_citations(common_citations)","def generate_ref_sheet(output_path):\r\n #header of reference sheet\r\n ref_out = Path(output_path)\r\n reference_elements=[]\r\n title = Paragraph('Validation Reference Sheet', style=styles['title'])\r\n reference_elements.append(title)\r\n\r\n #creating table with properties of metric scores\r\n metric_ref = (['Metrics Reference Table','','',''],\r\n ['Name', 'Attribute','Range','Perfect Score'],\r\n ['Percent Correct','Accuracy','0 to 1', '1'],\r\n ['Bias','Bias','0 to infinity','1'],\r\n ['Hit Rate','Discrimination','0 to 1','1'],\r\n ['False Alarm Rate','Discrimination','0 to 1', '0'],\r\n ['Frequency of Misses','Discrimination','0 to 1','0'],\r\n ['Probability of Correct Negatives','Discrimination',\r\n '0 to 1','1'],\r\n ['Frequency of Hits','Reliability and Resolution',\r\n '0 to 1','1'],\r\n ['False Alarm Ratio','Reliability and Resolution',\r\n '0 to 1','1'],\r\n ['Detection Failure Ratio','Reliability and Resolution',\r\n '0 to 1','0'],\r\n ['Frequency of Correct Negatives',\r\n 'Reliability and Resolution','0 to 1','1'],\r\n ['Threat Score','Accuracy','0 to 1','1'],\r\n ['Odds Ratio','Accuracy','0 to infinity','infinity'],\r\n ['Skill Scores','','',''],\r\n ['True Skill Score','','-1 to 1','1'],\r\n ['Heidke Skill Score','','-1 to 1','1'],\r\n ['Odds Ratio Skill Score','','-1 to 1','1'],\r\n ['Relative Operating Characteristic Skill Score (RSS)','',\r\n '0 to 1','1'],\r\n ['Mean Percentage Error','','-infinity to infinity','0'],\r\n ['Mean Absolute Percentage Error','','0 to infinity','0'])\r\n\r\n metric_ref_table=Table(metric_ref)\r\n metric_ref_table.setStyle(TableStyle([('BACKGROUND',(0,2),(3,13),\r\n colors.lightgrey),\r\n ('BACKGROUND',(0,15),(3,20),\r\n colors.lightgrey),\r\n ('GRID',(0,1),(3,20),0.25,\r\n colors.black),\r\n ('SPAN',(0,0),(3,0)),\r\n ('SPAN',(0,14),(3,14)),\r\n ('SPAN',(0,15),(1,15)),\r\n ('SPAN',(0,16),(1,16)),\r\n ('SPAN',(0,17),(1,17)),\r\n ('SPAN',(0,18),(1,18)),\r\n ('SPAN',(0,19),(1,19)),\r\n ('SPAN',(0,20),(1,20))]))\r\n\r\n #writing report\r\n reference_elements.append(metric_ref_table)\r\n\r\n reference = SimpleDocTemplate(str(ref_out / 'validation_reference.pdf'),\r\n pagesize=letter)\r\n reference.build(reference_elements)","def create_reference(filename):\n contigs = {}\n with open(filename, \"r\") as f:\n header = \"\"\n seq = \"\"\n for line in f:\n if line[0] == \">\":\n if header:\n contigs[header] = seq\n header = line[1:].rstrip()\n seq = \"\"\n else:\n seq += line.rstrip()\n\n return contigs","def generate_commit_table(start_ref, end_ref):\r\n header = \"|| Author || Summary || Commit || JIRA || Verified? ||\"\r\n commit_link = \"[commit|https://github.com/edx/edx-platform/commit/{sha}]\"\r\n rows = [header]\r\n commits = get_commits_not_in_prs(start_ref, end_ref)\r\n for commit in commits:\r\n rows.append(\"| {author} | {summary} | {commit} | {jira} | {verified} |\".format(\r\n author=commit.author.email,\r\n summary=commit.summary.replace(\"|\", \"\\|\"),\r\n commit=commit_link.format(sha=commit.hexsha),\r\n jira=\", \".join(parse_ticket_references(commit.message)),\r\n verified=\"\",\r\n ))\r\n return \"\\n\".join(rows)","def getBibTeX(bibref,tag_suf,outFile):\n if bibref == '1988iras....1.....B':\n bibtex = ['>@article{1988iras....1.....B,\\n',\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\n',\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\n',\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\n',\n ' year=1988,\\n',\n ' volume = {1},\\n', \n ' month = jan,\\n', \n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\n'\n '}\\n']\n else:\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\n suf = '/exportcitation'\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\n \n bibtex = []\n for l in range(0, len(lines)):\n if 'export-textarea ' in str(lines[l]):\n bibtex.append(str(lines[l]))\n t = l+1\n \n while '</textarea>' not in str(lines[t+1]):\n bibtex.append(str(lines[t])) \n t += 1\n \n for item in bibtex:\n if 'author' in item.split('=')[0]:\n auth = item.split('=')[1].split(',')[0]\n for i in string.punctuation:\n auth = auth.replace(i, '')\n auth = auth.replace(' ', '')\n if 'year' in item.split('=')[0]:\n yr = item.split('=')[1].split(',')[0]\n yr = yr.replace(' ', '')\n \n try:\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\n'\n except UnboundLocalError as ule:\n print(bibtex)\n print('')\n print(ule)\n sys.exit()\n \n with open(outFile, 'a') as o:\n for item in bibtex:\n item = item.replace('"', '\"')\n item = item.replace(''', \"'\")\n item = item.replace('&', \"&\")\n o.write(item)\n o.write('\\n')\n \n return auth+yr+tag_suf","def print_output(data,alignments,file):\n print(\"######################################################################\")\n print(\"Task 1 : IBM model 1 and EM algorithm implementation ,with corpus @\",file)\n print(\"######################################################################\")\n\n for i in range(len(data)):\n print(\"English Sentence : \",data[i][\"en\"])\n print(\"Foreign Sentence : \",data[i][\"fr\"])\n print(\"Alignment : \",alignments[i])\n print(\"----------------------------------------------------------------------\")","def make_table(ranked_means):\n fp = open(\"table.tex\", \"w\")\n fp.write(\"\"\"\\\\begin{tabular}{|l|c||l|c|}\n \\\\hline\n \\\\multicolumn{2}{|c||}{Slowest} & \\\\multicolumn{2}{|c|}{Fastest} \\\\\\\\ \\\\hline\n Feature & Rate & Feature & Rate \\\\\\\\ \\\\hline\n\"\"\")\n top_10 = ranked_means[0:10]\n bottom_10 = ranked_means[-10:]\n for ((f_rate, f_name),(s_rate,s_name)) in zip(top_10, bottom_10):\n f_name = f_name.split(\":\")[-1]\n f_name = f_name.rsplit(\" \", 1)[0] if f_name.endswith(\"(V)\") else f_name\n s_name = s_name.split(\":\")[-1]\n s_name = s_name.rsplit(\" \", 1)[0] if s_name.endswith(\"(V)\") else s_name\n fp.write(\" %s & %.2f & %s & %.2f \\\\\\\\ \\n\" % \\\n (f_name, f_rate, s_name, s_rate))\n fp.write(\"\\\\hline\\n\")\n fp.write(\"\\\\end{tabular}\\n\")\n fp.close()\n\n fp = open(\"supp_meaning_table.tex\", \"w\")\n fp.write(\"\"\"\\\\begin{tabular}{|l|c||l|c||l|c||l|c|}\n \\\\hline\n Meaning & Category & Meaning & Category & Meaning & Category & Meaning & Category\\\\\\\\ \\\\hline\n\n\"\"\")\n feature_names = [f.split(\":\")[-1] for (r,f) in ranked_means]\n feature_names.sort(key=lambda s: s.lower())\n col1 = feature_names[0:25]\n col2 = feature_names[25:50]\n col3 = feature_names[50:75]\n col4 = feature_names[75:]\n for a,b,c,d in zip(col1,col2,col3,col4):\n x,y,z,w = [get_meaning_category(i) or \"Excluded\" for i in (a,b,c,d)]\n # Lop off (V)s (we needed them above for get_meaning_category to work)\n a,b,c,d = [f.rsplit(\" \", 1)[0] if f.endswith(\"(V)\") else f for f in (a,b,c,d)]\n fp.write(\"%s & %s & %s & %s & %s & %s & %s & %s\\\\\\\\ \\n\" % (a, x, b, y, c, z, d, w))\n fp.write(\"\\\\hline\\n\")\n fp.write(\"\\\\end{tabular}\\n\")\n fp.close()","def populate_db():\n stdout.write('Emptying the tables...\\n')\n empty_tables()\n stdout.write('Populating Language records...\\n')\n populate_language()\n stdout.write('Populating Lemma, Wordform, and Definition records...\\n')\n populate_lexical()\n stdout.write('Populating ProperName records...\\n')\n populate_proper_names()","def create_database_and_add_model(models,database):\n conn =sqlite3.connect(database)\n for model in models:\n mod_tab_name = model.replace('-','_')\n sql_create_projects_table = \"\"\" CREATE TABLE IF NOT EXISTS %s (\n case_var text NOT NULL PRIMARY KEY,\n model_case text NOT NULL,\n var text NOT NULL,\n case_name text NOT NULL,\n original_var_name text,\n units text ,\n units_original text,\n lev_is_dim integer NOT NULL,\n is_computed_var integer,\n path_computed_data text,\n pressure_coordinate_path text\n ); \"\"\"%(mod_tab_name)\n\n # create a database connection\n if conn is not None:\n # create projects table\n create_table(conn, sql_create_projects_table)\n else:\n print(\"Error! cannot create the database connection.\")\n conn.close()\n return","def insert_mbifields(config,doctype,inst):\n\t\n\tdocname = get_docname_from_schema(doctype,config)\n\tfieldtext = '<table width=\"100%\" bgcolor=\"#99CC00\" align=\"center\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\"><tr><td align=\"left\"><br /><b>Modify a docname bibliographic information:</b><br /><br /><span style=\"color: red;\">*</span>Reference Number: '\n\tfieldtext = fieldtext.replace(\"docname\",docname)\n\tfieldlevel = \"O\"\n\taction = \"MBI\"\n\tpagenum = \"1\"\n\tfieldname = \"rn\"\n\tfieldshortdesc = fieldname.replace(\"hgf_\",\"\")\n\tfieldcheck = \"\"\n\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\t\n\t\n\t## hgf_change\n\tselect_box = '<select visibility=\"hidden\" name=\"mod_%s[]\" size=\"1\"><option value=\"Select:\">Please click continue:</option></select>' %doctype #fake selectbox\n\telname = \"mod_\" + doctype\n\telmarccode = \"\"\n\teltype = \"S\"\n\telsize = \"\"\n\telrows = \"\"\n\telcols = \"\"\n\telmaxlength = \"\"\n\telval = \"\"\n\telfidesc = select_box # select box for modification form\n\telmodifytext = \"\"\n\tinsert_element_details(elname, elmarccode, eltype, elsize, elrows, elcols, elmaxlength, elval, elfidesc, elmodifytext) # inserrt into sbmFIELDDESCR\n\t\n\t\n\tfieldtext = ''\n\tfieldlevel = \"O\"\n\taction = \"MBI\"\n\tpagenum = \"1\"\n\tfieldname = elname\n\tfieldshortdesc = elname.replace(\"hgf_\",\"\")\n\tfieldcheck = \"\"\n\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\t\n\t\n\t#mbi_end \n\tfieldtext = '<br /><br /></td></tr></table><br />'\n\tfieldlevel = \"O\"\n\taction = \"MBI\"\n\tpagenum = \"1\"\n\tfieldname = \"mbi_end\"\n\tfieldshortdesc = fieldname.replace(\"hgf_\",\"\")\n\tfieldcheck = \"\"\n\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\t","def main():\n args = get_args()\n str_arg = args.arg\n int_arg = args.int\n flag_arg = args.flag\n #pos_arg = args.positional\n\n #read and open the annotations file\n intpro_dict = {}\n with open('InterPro_entry_list.tsv') as csvfile:\n reader = csv.DictReader(csvfile, delimiter='\\t')\n for row in reader:\n intpro_dict[row['ENTRY_AC']] = row['ENTRY_NAME']\n\n with open('model_topics.txt', 'r') as file:\n model_topics = file.read().replace('\\n', '')\n\n model_topics = re.sub(\"'\", \"\", model_topics)\n model_topics = re.sub(\"\\[\", \"\", model_topics)\n model_topics = re.sub(\"\\]\", \"\", model_topics)\n\n mtl = model_topics.split('), ')\n\n with open('output_topics.tsv' ,'w') as f:\n print('Topic\\tModel_coefficient\\tInterpro_ID\\tInterPro_ENTRY_NAME', file=f)\n for list in mtl:\n topic = list[1]\n split_list = list.split()\n id_re = re.compile('IPR\\d{3}')\n c_words = []\n for w in split_list:\n match = id_re.search(w)\n if match:\n c_words.append(w)\n c_words = [re.sub('\"', '', i) for i in c_words]\n for w in c_words:\n re.sub('\\)', '', w)\n coef, intpro = w.split('*')\n intpro = intpro[:9]\n\n if intpro in intpro_dict.keys():\n label = intpro_dict[intpro]\n else:\n label = ''\n\n print('{}\\t{}\\t{}\\t{}'.format(topic,coef,intpro,label), file=f)","def _create_lookup_tables(self, text):\n word_counts = Counter(text)\n sorted_words = sorted(word_counts, key=word_counts.get, reverse=True)\n vocab_to_int = {word: ii for ii, word in enumerate(sorted_words)}\n int_to_vocab = {ii: word for ii, word in enumerate(sorted_words)}\n return (vocab_to_int, int_to_vocab)","def fill_table(model_list, field_list, foreign_field_list):\n out = ''\n for model in model_list:\n out += '<tr>'\n for field in field_list:\n out += '<td>' + str(model[field]) + '</td>'\n # for field in foreign_field_list:\n # attr = model[field]\n # if attr is not None:\n # out += '<td>' + '<a href=\" + attr + \"><div style=\"height:100%;width:100%\">' + ', '.join([str(i.pk) for i in attr.all()]) + '</td>'\n out += '</tr>'\n return mark_safe(out)","def associate_related_footnotes(apps, schema_editor):\n\n User = apps.get_model(\"auth\", \"User\")\n Annotation = apps.get_model(\"annotations\", \"Annotation\")\n ContentType = apps.get_model(\"contenttypes\", \"ContentType\")\n Document = apps.get_model(\"corpus\", \"Document\")\n Footnote = apps.get_model(\"footnotes\", \"Footnote\")\n Source = apps.get_model(\"footnotes\", \"Source\")\n LogEntry = apps.get_model(\"admin\", \"LogEntry\")\n\n DIGITAL_EDITION = \"X\"\n\n # much of this code adapted from signal handlers and static methods\n document_contenttype = ContentType.objects.get_for_model(Document)\n\n annotations = Annotation.objects.all()\n for annotation in annotations:\n # resolve URIs to Source and Document IDs (without using static methods)\n manifest_uri = (\n annotation.content.get(\"target\", {})\n .get(\"source\", {})\n .get(\"partOf\", {})\n .get(\"id\")\n )\n source_uri = annotation.content.get(\"dc:source\")\n source_id = int(source_uri.split(\"/\")[-2])\n try:\n document_id = document_id_from_manifest_uri(manifest_uri)\n except Resolver404:\n continue\n try:\n # try to get a DIGITAL_EDITION footnote for this source and document\n footnote = Footnote.objects.get(\n doc_relation__contains=DIGITAL_EDITION,\n source__pk=source_id,\n content_type=document_contenttype,\n object_id=document_id,\n )\n except Footnote.DoesNotExist:\n # create the DIGITAL_EDITION footnote\n source = Source.objects.get(pk=source_id)\n footnote = Footnote.objects.create(\n source=source,\n doc_relation=[DIGITAL_EDITION],\n object_id=document_id,\n content_type=document_contenttype,\n )\n LogEntry.objects.log_action(\n user_id=User.objects.get(username=settings.SCRIPT_USERNAME).id,\n content_type_id=ContentType.objects.get_for_model(Footnote).pk,\n object_id=footnote.pk,\n object_repr=str(footnote),\n action_flag=ADDITION,\n change_message=\"Footnote automatically created via annotation migration.\",\n )\n\n # instantiate the FK relation\n annotation.footnote = footnote\n\n # remove the existing manifest and source URIs from annotation content field\n del annotation.content[\"dc:source\"]\n del annotation.content[\"target\"][\"source\"][\"partOf\"]\n\n # save all FK relations and content fields\n Annotation.objects.bulk_update(annotations, [\"content\", \"footnote\"])","def populate_db(database, annot_name, chrom_genes, chrom_transcripts, edges, genome_build):\n # Connecting to the database file\n conn = sqlite3.connect(database)\n c = conn.cursor()\n\n for chromosome in chrom_genes.keys():\n start_time = time.time()\n print(chromosome)\n genes = chrom_genes[chromosome]\n transcripts = chrom_transcripts[chromosome] \n\n gene_id_map = add_genes(c, genes, annot_name)\n add_transcripts(c, transcripts, annot_name, gene_id_map, genome_build)\n\n conn.commit()\n end_time = time.time()\n print(\"It took {} to process chromosome\".format(hms_string(end_time - start_time)))\n conn.close()\n \n return","def build_index(self):\r\n date_time('Building indexes in citations table')\r\n self.cursor.execute('DROP INDEX IF EXISTS IDX_citations ;')\r\n self.cursor.execute('CREATE INDEX IDX_citations ON citations (citation);')\r\n self.conn.commit()\r\n gc.collect()","def _get_references_data(wit_path):\n\n with open(os.path.join(wit_path, '.wit', 'references.txt'), 'r') as data:\n info = {'None': 'None'}\n info.update({'HEAD': data.readline().split('=')[-1].strip('\\n')})\n info.update({'master': data.readline().split('=')[-1].strip('\\n')})\n for row in data.readlines():\n name, commit_id = row.split('=')\n info.update({name.strip('\\n'): commit_id.strip('\\n')})\n\n return info","def start_cfm_jobs(file_dir, db, spec_type, job_template=None,\n job_comp_number=100, max_mass=1500):\n if not os.path.exists(file_dir):\n os.mkdir(file_dir)\n os.chdir(file_dir)\n\n out_file = open(db.name + \"_1.txt\", \"w\")\n i = 1\n j = 1\n inchi_set = set()\n if spec_type == 'pos':\n search = {\"_id\": {\"$regex\": \"^C\"}, \"Mass\": {\"$lt\": max_mass},\n \"Charge\": 0, \"Pos_CFM_spectra\": {\"$exists\": 0}}\n elif spec_type == 'neg':\n search = {\"_id\": {\"$regex\": \"^C\"}, \"Mass\": {\"$lt\": max_mass},\n \"Charge\": 0, \"Neg_CFM_spectra\": {\"$exists\": 0}}\n elif spec_type == 'ei':\n search = {\"_id\": {\"$regex\": \"^C\"}, \"Mass\": {\"$lt\": max_mass},\n \"Charge\": 0, \"EI_CFM_spectra\": {\"$exists\": 0}}\n else:\n raise ValueError('invalid spectrum spec_type')\n\n for compound in db.compounds.find(search, {\"SMILES\": 1, \"Inchikey\": 1}):\n con_block = compound['Inchikey'].split('-')[0]\n if con_block not in inchi_set:\n out_file.write(\"%s %s\\n\" % (con_block, compound['SMILES']))\n i += 1\n inchi_set.add(con_block)\n if not i % job_comp_number:\n out_file.close()\n j += 1\n out_file = open(db_name + \"_\" + str(j) + \".txt\", 'w')\n out_file.close()\n\n if job_template:\n # for Quest?\n # fetch the information from the job template\n try:\n infile = open(job_template)\n except IOError:\n sys.exit(\"Job template file not found\")\n temp_data = infile.readlines()\n infile.close()\n\n for comp_file in os.listdir(\".\"):\n if \".txt\" not in comp_file:\n continue\n job_data = deepcopy(temp_data)\n # edit the job template data for the specific job\n job_data[1] = \"#$ -e logs/cfm_%s.err\\n\" % (comp_file.strip('.txt'))\n job_data[2] = \"#$ -o logs/cfm_%s.log\\n\" % (comp_file.strip('.txt'))\n new_file = file_dir + \"/\" + comp_file.strip()\n job_data[11] = job_data[11].replace(\"{smile_file}\", new_file)\n\n # write the specific job file\n job_file = \"cfm_%s.job\" % comp_file.strip('.txt')\n outfile = open(job_file, 'w')\n outfile.writelines(job_data)\n outfile.close()\n rc = call([\"qsub\", job_file], shell=True)\n if not rc:\n os.remove(job_file)","def _intermediary_to_markdown(tables, relationships):\n t = '\\n'.join(t.to_markdown() for t in tables)\n r = '\\n'.join(r.to_markdown() for r in relationships)\n return '{}\\n{}'.format(t, r)","def __init__(self, fastaRecords, modelFile, modelIterations=-1):\n\n self.pre = 10\n self.post = 4\n\n self.pad = 30\n self.base4 = 4 ** np.array(range(self.pre + self.post + 1))\n\n self.refDict = {}\n self.refLengthDict = {}\n\n for contig in fastaRecords:\n if contig.cmph5ID is None:\n # This contig has no mapped reads -- skip it\n continue\n\n rawSeq = contig.sequence[:]\n refSeq = np.fromstring(rawSeq, dtype=byte)\n\n # Store the reference length\n self.refLengthDict[contig.cmph5ID] = len(rawSeq)\n\n # Make a shared array\n sa = SharedArray(dtype='B', shape=len(rawSeq) + self.pad * 2)\n saWrap = sa.getNumpyWrapper()\n\n # Lut Codes convert Ns to As so that we don't put Ns into the Gbm Model\n # Seq Codes leaves Ns as Ns for getting reference snippets out\n innerLutCodes = lutCodeMap[refSeq]\n innerSeqCodes = seqCodeMap[refSeq]\n innerCodes = np.bitwise_or(innerLutCodes, np.left_shift(innerSeqCodes, 4))\n\n saWrap[self.pad:(len(rawSeq) + self.pad)] = innerCodes\n\n # Padding codes -- the lut array is padded with 0s the sequence array is padded with N's (4)\n outerCodes = np.left_shift(np.ones(self.pad, dtype=uint8) * 4, 4)\n saWrap[0:self.pad] = outerCodes\n saWrap[(len(rawSeq) + self.pad):(len(rawSeq) + 2 * self.pad)] = outerCodes\n\n self.refDict[contig.cmph5ID] = sa\n\n # No correction factor for IPDs everything is normalized to 1\n self.meanIpd = 1\n\n # Find and open the ipd model file\n self.lutPath = modelFile\n if os.path.exists(self.lutPath):\n h5File = h5py.File(self.lutPath, mode='r')\n\n gbmModelGroup = h5File[\"/AllMods_GbmModel\"]\n self.gbmModel = GbmContextModel(gbmModelGroup, modelIterations)\n\n # We always use the model -- no more LUTS\n self.predictIpdFunc = self.predictIpdFuncModel\n self.predictManyIpdFunc = self.predictManyIpdFuncModel\n else:\n logging.info(\"Couldn't find model file: %s\" % self.lutPath)","def compute_applied_name_contexts(citelist: list) -> None:\n for i, cite in enumerate(citelist):\n if (cite.context == \"specimen\") or (cite.context == \"location\") or (cite.context == \"sequence\"):\n cite.applied_cites = {cite}\n elif cite.context == \"citation\":\n for j in range(i): # only look at entries up to the current one\n tmp = citelist[j]\n if (tmp.cite_key == cite.application) and match_num_ref(tmp.name_key, cite.cite_n):\n if (tmp.context == \"specimen\") or (tmp.context == \"location\") or (tmp.context == \"sequence\"):\n cite.applied_cites |= {tmp}\n if len(cite.applied_cites) == 0:\n cite.applied_cites = None\n\n # for testing purposes only\n # if cite.applied_cites is None:\n # print(cite.cite_key, cite.name_key, cite.context, \"No application\")\n # else:\n # for c in cite.applied_cites:\n # print(cite.cite_key, cite.name_key, cite.context, c.cite_key, c.name_key, c.context)\n # input()","def feature_table(chr_id, source, orient, genes, transcripts, cds, exons, unk):\n for gname, ginfo in genes.items():\n line = [str(chr_id), \n 'gbk_to_gff',\n ginfo[3],\n str(ginfo[0]),\n str(ginfo[1]),\n '.',\n ginfo[2],\n '.',\n 'ID='+str(gname)+';Name='+str(gname)+';Note='+ginfo[-1]]\n print '\\t'.join(line) \n ## construct the transcript line is not defined in the original file \n t_line = [str(chr_id), 'gbk_to_gff', source, 0, 1, '.', ginfo[2], '.'] \n\n if not transcripts:\n t_line.append('ID=Transcript:'+str(gname)+';Parent='+str(gname))\n\n if exons: ## get the entire transcript region from the defined feature\n t_line[3] = str(exons[gname][0][0])\n t_line[4] = str(exons[gname][0][-1])\n elif cds:\n t_line[3] = str(cds[gname][0][0])\n t_line[4] = str(cds[gname][0][-1])\n print '\\t'.join(t_line) \n\n if exons:\n exon_line_print(t_line, exons[gname], 'Transcript:'+str(gname), 'exon')\n\n if cds:\n exon_line_print(t_line, cds[gname], 'Transcript:'+str(gname), 'CDS')\n if not exons:\n exon_line_print(t_line, cds[gname], 'Transcript:'+str(gname), 'exon')\n\n else: ## transcript is defined \n for idx in transcripts[gname]: \n t_line[2] = idx[3]\n t_line[3] = str(idx[0])\n t_line[4] = str(idx[1])\n t_line.append('ID='+str(idx[2])+';Parent='+str(gname))\n print '\\t'.join(t_line) \n \n ## feature line print call \n if exons:\n exon_line_print(t_line, exons[gname], str(idx[2]), 'exon')\n if cds:\n exon_line_print(t_line, cds[gname], str(idx[2]), 'CDS')\n if not exons:\n exon_line_print(t_line, cds[gname], str(idx[2]), 'exon')\n\n if len(genes) == 0: ## feature entry with fragment information \n \n line = [str(chr_id), 'gbk_to_gff', source, 0, 1, '.', orient, '.'] \n fStart = fStop = None \n\n for eid, ex in cds.items(): \n fStart = ex[0][0] \n fStop = ex[0][-1]\n\n for eid, ex in exons.items(): \n fStart = ex[0][0] \n fStop = ex[0][-1]\n\n if fStart or fStart:\n\n line[2] = 'gene'\n line[3] = str(fStart)\n line[4] = str(fStop)\n line.append('ID=Unknown_Gene_' + str(unk) + ';Name=Unknown_Gene_' + str(unk))\n print \"\\t\".join(line)\n\n if not cds:\n line[2] = 'transcript'\n else:\n line[2] = 'mRNA'\n line[8] = 'ID=Unknown_Transcript_' + str(unk) + ';Parent=Unknown_Gene_' + str(unk)\n print \"\\t\".join(line)\n \n if exons:\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'exon')\n \n if cds:\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'CDS')\n if not exons:\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'exon')\n \n unk +=1 \n\n return unk","def _prepare_links_table(self):\n\n links_tbl = OrderedDict()\n for colname in itertools.islice(self._pinfos, 1, None):\n links_tbl[colname] = {}\n links_tbl[colname][\"name\"] = f\"{colname}\"\n fname = colname.replace(\"%\", \"_pcnt\") + \".html\"\n links_tbl[colname][\"fname\"] = fname\n links_tbl[colname][\"hlink\"] = f\"<a href=\\\"{fname}\\\">{colname}</a>\"\n\n return links_tbl","def writeIssnTables(outDir, pubIds, pubToIssn, issnOverwrite):\n outFhDict = {}\n\n # prep the lookup table\n pubIdToDescs = {}\n for pubDesc, pubId in pubIds.iteritems():\n pubIdToDescs.setdefault(pubId, []).append(pubDesc)\n\n # outDir has to be identical to the pubId from pubConf\n pubId = basename(outDir)\n\n issnOutFname = join(outDir, ISSNTAB)\n\n if not isdir(outDir):\n logging.info(\"Creating dir %s\" % outDir)\n os.makedirs(outDir)\n\n # lookup Issns for publisher description\n # write default ISSNs\n logging.info(\"Writing to %s\" % issnOutFname)\n if issnOutFname not in outFhDict:\n outFh = open(issnOutFname, \"w\")\n outFh.write(\"issn\\tjournal\\tstartYear\\tendYear\\tpublisher\\n\")\n outFhDict[issnOutFname] = outFh\n else:\n outFh = outFhDict[issnOutFname]\n\n # now output ISSNs\n issnCount = 0\n for pubDesc in pubIdToDescs[pubId]:\n logging.debug(\"Found %d issns for publisher %s\" % (len(pubToIssn[pubDesc]), pubId))\n for issn, title in pubToIssn[pubDesc]:\n logging.info(\"Title: %s, print ISSN %s\" % (title, issn))\n if issn==\"\":\n continue\n line = \"%(issn)s\\t%(title)s\\t0\\t0\\t%(pubDesc)s\\n\" % locals()\n # some journal names contain unicode, we just strip it here\n outFh.write(unidecode.unidecode(line))\n issnCount+=1\n\n # add manual ISSNs\n for issn, startYear, endYear in issnOverwrite.get(pubId, []):\n outFh.write(\"%s\\t%d\\t%d\\t%s\\n\" % (issn, startYear, endYear, pubName))\n issnCount+=1\n logging.info(\"Wrote %d ISSNs\" % issnCount)","def write_latex_table(machine, all_benchs, summary, diff, skipped, tex_file, num_splits,\n with_preamble=False, longtable=False, diff_vms=[]):\n\n num_benchmarks = len(all_benchs)\n all_vms = sorted(summary.keys())\n num_vms = len(summary)\n\n # decide how to lay out the splits\n num_vms_rounded = int(math.ceil(num_vms / float(num_splits)) * num_splits)\n vms_per_split = int(num_vms_rounded / float(num_splits))\n splits = [[] for x in xrange(num_splits)]\n vm_num = 0\n split_idx = 0\n for vm_idx in xrange(num_vms_rounded):\n if vm_idx < len(all_vms):\n vm = all_vms[vm_idx]\n else:\n vm = None\n splits[split_idx].append(vm)\n vm_num += 1\n if vm_num % vms_per_split == 0:\n split_idx += 1\n\n with open(tex_file, 'w') as fp:\n if with_preamble:\n fp.write(preamble(TITLE))\n if diff_vms:\n fp.write('\\\\centering{%%\\n\\\\Large{\\\\textbf{%s vs. %s}}%%\\n}\\n\\\\\\\\\\n~\\\\\\\\\\n\\n'\n % (diff_vms[0], diff_vms[1]))\n legends = get_latex_symbol_map() + ' \\\\\\\\ ' + legend()\n fp.write('\\\\centering %s' % legends)\n fp.write('\\n\\n\\n')\n if not longtable:\n fp.write('\\\\begin{landscape}\\n')\n fp.write('\\\\begin{table*}[hptb]\\n')\n fp.write('\\\\vspace{.8cm}\\n')\n fp.write('\\\\begin{adjustbox}{totalheight=12.4cm}\\n')\n # Emit table header.\n heads1 = TABLE_HEADINGS_START1 + '&'.join([TABLE_HEADINGS1] * num_splits)\n heads2 = TABLE_HEADINGS_START2 + '&'.join([TABLE_HEADINGS2] * num_splits)\n heads = '%s\\\\\\\\%s' % (heads1, heads2)\n if longtable:\n fp.write(start_longtable(TABLE_FORMAT, heads))\n else:\n fp.write(start_table(TABLE_FORMAT, heads))\n split_row_idx = 0\n for row_vms in zip(*splits):\n bench_idx = 0\n skipped_before = [b for (b, v) in skipped[SKIPPED_BEFORE] if v == row_vms[0]]\n skipped_after = [b for (b, v) in skipped[SKIPPED_AFTER] if v == row_vms[0]]\n for bench in sorted(all_benchs + skipped_before + skipped_after):\n row = []\n for vm in row_vms:\n if vm is None:\n continue # no more results\n try:\n this_summary = summary[vm][bench]\n except KeyError:\n if bench in skipped_before or bench in skipped_after:\n classification = '\\\\emph{Skipped}'\n else:\n classification = ''\n last_cpt = BLANK_CELL\n time_steady = BLANK_CELL\n last_mean = BLANK_CELL\n steady_iter_var = BLANK_CELL\n steady_time_var = BLANK_CELL\n else:\n if vm in diff and bench in diff[vm]:\n classification = colour_tex_cell(diff[vm][bench][CLASSIFICATIONS], this_summary['style'])\n last_cpt = colour_tex_cell(diff[vm][bench][STEADY_ITER], this_summary['last_cpt'])\n steady_iter_var = colour_tex_cell(diff[vm][bench][STEADY_ITER_VAR], this_summary['steady_iter_var'])\n time_steady = colour_tex_cell(diff[vm][bench][STEADY_ITER], this_summary['time_to_steady_state'])\n last_mean = colour_tex_cell(diff[vm][bench][STEADY_STATE_TIME], this_summary['last_mean'])\n steady_time_var = colour_tex_cell(diff[vm][bench][STEADY_STATE_TIME_VAR], this_summary['steady_time_var'])\n else:\n classification = this_summary['style']\n last_cpt = this_summary['last_cpt']\n steady_iter_var = this_summary['steady_iter_var']\n time_steady = this_summary['time_to_steady_state']\n last_mean = this_summary['last_mean']\n steady_time_var = this_summary['steady_time_var']\n classification = '\\\\multicolumn{1}{l}{%s}' % classification\n if classification == STYLE_SYMBOLS['flat']:\n last_cpt = BLANK_CELL\n time_steady = BLANK_CELL\n if last_cpt == '':\n last_cpt = BLANK_CELL\n if time_steady == '':\n time_steady = BLANK_CELL\n if last_mean == '':\n last_mean = BLANK_CELL\n\n if bench_idx == 0:\n if num_benchmarks == 10:\n fudge = 4\n elif num_benchmarks == 12:\n fudge = 5\n else:\n fudge = 0\n vm_cell = '\\\\multirow{%s}{*}{\\\\rotatebox[origin=c]{90}{%s}}' \\\n % (num_benchmarks + fudge, vm)\n else:\n vm_cell = ''\n row_add = [BLANK_CELL, vm_cell, classification, last_cpt,\n steady_iter_var, time_steady, last_mean, steady_time_var]\n if not row: # First bench in this row, needs the vm column.\n if vm in diff and bench in diff[vm]:\n bname = colour_tex_cell(diff[vm][bench][INTERSECTION], bench)\n else:\n bname = bench\n row.insert(0, escape(bname))\n row.extend(row_add)\n vm_idx += 1\n fp.write('&'.join(row))\n # Only -ve space row if not next to a midrule\n if not longtable and bench_idx < num_vms - 1:\n fp.write('\\\\\\\\[-3pt] \\n')\n else:\n fp.write('\\\\\\\\ \\n')\n bench_idx += 1\n if split_row_idx < vms_per_split - 1:\n if longtable:\n fp.write('\\\\hline\\n')\n else:\n fp.write('\\\\midrule\\n')\n split_row_idx += 1\n if longtable:\n fp.write(end_longtable())\n else:\n fp.write(end_table())\n if with_preamble:\n if not longtable:\n fp.write('\\\\end{adjustbox}\\n')\n fp.write('\\\\end{table*}\\n')\n fp.write('\\\\end{landscape}\\n')\n fp.write(end_document())","def create_convergence_table(initial_condition, flux):\n\n group_path = initial_condition + \"/\" + flux \n \n error_norms = error_norms_data(*group_path.split(\"/\"))\n\n# Return a formatted string containing convergence information for the given grid resolution \n def convergence_row(k): \n return \"{k:^3} {M:^10} {h:^15.10f} {sup_norm:^15.10f} {sup_norm_rate:^5.2f} {one_norm:^15.10f} {one_norm_rate:^5.2f} {two_norm:^15.10f} {two_norm_rate:^5.2f}\".format(**convergence_table_row_data(k, error_norms))\n\n# Formatted string containing the text of the header of the table\n header = \"{k:^3} {M:^10} {h:^15} {sup_norm:^15} {sup_norm_rate:^5} {one_norm:^15} {one_norm_rate:^5} {two_norm:^15} {two_norm_rate:^5}\".format(**convergence_table_header_data)\n\n# Formatted string containing the attributes of the computation\n closing = \"Speed: {a_text:>12} {a} \\nCFL Number: sigma = {CFL} \\nOutput Time: {T_text:>6} {T}\".format(\n a_text = \"a =\",\n T_text = \"T =\",\n **computation_attributes(*group_path.split(\"/\"))\n )\n\n# Write the table to a text file \n output_text_table_file = open(html_path + \"convergence_tables/\" + group_path.replace(\"/\", \"_\") + \".txt\", \"w\") \n output_text_table_file.write(header + \"\\n\\n\")\n for k in range(7, 17):\n output_text_table_file.write(convergence_row(k) + \"\\n\")\n output_text_table_file.write(\"\\n\" + closing)"],"string":"[\n \"def __init__(self):\\n # simple header only necessary for this table of MIPs\\n self.header = '<tr class=\\\"ename\\\"><td colspan=\\\"1\\\">{{d.name}} ({{mips}})</td></tr>'\\n self.mips = 'core MIPS recorded by ES-DOC'\\n self._settemplates(self.onecol, self.twocol)\\n\\n r = Repo()\\n c = r.getbyname('CMIP6', 'mips')\\n self.doc = c\\n self.related = []\\n\\n # two properties to help the use of the resulting table in a paper\\n self.reference_list = []\\n # nocite list intended for cutting and pasting directly into a latex document!\\n self.nocite = ''\\n\\n for m in c.sub_projects:\\n mdoc = r.getbyname(m.name, 'mips')\\n description = mdoc.long_name+' - '\\n citations = []\\n\\n # for these purposees we only want the things with a doi\\n # and we want only one, so we have to develop a heuristic to get the right one\\n for ci in mdoc.citations:\\n cidoc = esd.retrieve(ci.id)\\n ref = Reference(cidoc)\\n if ref.populated:\\n citations.append(ref)\\n citations.sort(key=lambda cc: cc.year)\\n index = -1\\n if len(citations) > 1:\\n # start by getting the most recent\\n year = citations[-1].year\\n index = -1\\n for i in range(len(citations)-1):\\n if citations[i].year == year:\\n if m.name in citations[i].text:\\n # it's one of the most recent and it has the MIP name\\n # in the document title.\\n index = i\\n description += citations[index].citestring\\n self.reference_list.append(citations[index].text)\\n self.nocite += '\\\\\\\\nocite{%s}\\\\n' % citations[index].citeguess\\n\\n # overwrite the real description for the purpose of this table\\n mdoc.description = description\\n self.related.append(mdoc)\\n\\n # want alphabetical order\\n self.related.sort(key=lambda mm: mm.name)\",\n \"def main():\\n papers_with_references = add_references_to_papers(PAPERS_FILE, TEXT_DIR)\\n citations = match_citations_with_papers(papers_with_references)\\n insert_into_citation_table(citations)\",\n \"def output_name_table(outfile: TextIO, do_print: bool, is_name: bool, itemlist: list, unique_set: set,\\n notecnt: int, comcnt: int, refdict: dict, name_table: dict, point_locations: dict) -> None:\\n\\n def create_location_sublink(x: str) -> str:\\n \\\"\\\"\\\"\\n create a link to location pages, preserving [] info when applicable\\n \\\"\\\"\\\"\\n tmpname = strip_location_subtext(x)\\n if tmpname in point_locations:\\n loc = point_locations[tmpname]\\n tmpstr = create_location_link(loc, tmpname, do_print, path=\\\"../locations/\\\")\\n if tmpname != x:\\n tmpstr += x[len(tmpname):]\\n tmpstr = tmpstr.replace(\\\"<!>\\\", fetch_fa_glyph(\\\"bad location\\\"))\\n # tmpstr = tmpstr.replace(\\\"<?>\\\", fetch_fa_glyph(\\\"questionable id\\\"))\\n tmpstr = tmpstr.replace(\\\"<?>\\\", \\\"\\\").strip()\\n else:\\n tmpstr = x\\n return tmpstr\\n\\n # ---main part of loop---\\n first_name = True\\n ncols = 5\\n if notecnt > 0:\\n ncols += 1\\n if comcnt > 0:\\n ncols += 1\\n\\n for n in itemlist:\\n outfile.write(\\\" <tr>\\\\n\\\")\\n if is_name:\\n nref = n.cite_key\\n else:\\n nref = n.name\\n if nref in unique_set:\\n if first_name:\\n first_name = False\\n else:\\n outfile.write(\\\" <td class=\\\\\\\"rowspacer\\\\\\\" colspan=\\\\\\\"\\\" + str(ncols) + \\\"\\\\\\\"> </td>\\\\n\\\")\\n outfile.write(\\\" </tr>\\\\n\\\")\\n outfile.write(\\\" <tr>\\\\n\\\")\\n\\n if nref == \\\".\\\":\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n elif is_name: # output citation\\n crossref = refdict[nref]\\n outfile.write(\\\" <td><a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../references/\\\") +\\n crossref.cite_key + \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a></td>\\\\n\\\")\\n else: # output species name\\n outfile.write(\\\" <td><a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../names/\\\") +\\n name_to_filename(nref) + \\\".html\\\\\\\">\\\" + format_name_string(nref) + \\\"</a></td>\\\\n\\\")\\n\\n # common names\\n if comcnt > 0:\\n if n.common == \\\".\\\":\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n else:\\n outfile.write(\\\" <td>\\\" + n.common + \\\"</td>\\\\n\\\")\\n outfile.write(\\\" <td>\\\" + n.where + \\\"</td>\\\\n\\\")\\n unique_set -= {nref}\\n else:\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n if comcnt > 0:\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n\\n # applies to...\\n if n.context == \\\"location\\\":\\n outstr = create_location_sublink(n.application)\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"location\\\") + \\\"location: \\\" + outstr + \\\"</td>\\\\n\\\")\\n elif n.context == \\\"citation\\\":\\n if n.application in refdict:\\n crossref = refdict[n.application]\\n if n.application in name_table:\\n nstr = n.cite_n\\n if nstr == \\\"0\\\":\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"citation\\\") + \\\"citation: \\\"\\n \\\"<a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../references/\\\") + crossref.cite_key +\\n \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a></td>\\\\n\\\")\\n else:\\n if \\\".\\\" in nstr:\\n try:\\n extraref = \\\" [\\\" + name_table[n.application][nstr][1] + \\\"]\\\"\\n refname = name_table[n.application][nstr][0]\\n except LookupError:\\n if is_name: # only print errors on one pass\\n report_error(\\\"Error in citation: \\\" + n.cite_key + \\\" cites\\\" + nstr +\\n \\\" in \\\" + n.application)\\n extraref = \\\"\\\"\\n refname = \\\"\\\"\\n else:\\n extraref = \\\"\\\" \\n try:\\n refname = name_table[n.application][int(nstr)]\\n except ValueError:\\n report_error(\\\"Citation \\\" + n.cite_key + \\\" tried to cite \\\" + n.application +\\n \\\" #\\\" + nstr)\\n refname = \\\"\\\"\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"citation\\\") + \\\"citation: \\\"\\n \\\"<a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../references/\\\") + crossref.cite_key +\\n \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a> → \\\" + format_name_string(refname) +\\n extraref + \\\"</td>\\\\n\\\")\\n else:\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"citation\\\") + \\\"citation: \\\"\\n \\\"<a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../references/\\\") + crossref.cite_key +\\n \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a></td>\\\\n\\\")\\n else:\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"citation\\\") + \\\"citation: \\\" + n.application +\\n \\\"</td>\\\\n\\\")\\n if is_name and not do_print: # only print on one pass\\n report_error(\\\"Citation not in DB: \\\" + n.cite_key + \\\" cites \\\" + n.application)\\n elif n.context == \\\"specimen\\\":\\n if n.application == \\\"?\\\":\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"specimen\\\") + \\\"specimen: unknown locality</td>\\\\n\\\")\\n else:\\n outstr = create_location_sublink(n.application)\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"specimen\\\") + \\\"specimen: \\\" + outstr + \\\"</td>\\\\n\\\")\\n elif n.context == \\\"sequence\\\":\\n if n.application == \\\"?\\\":\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"sequence\\\") + \\\"sequence: unknown locality</td>\\\\n\\\")\\n else:\\n outstr = create_location_sublink(n.application)\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"sequence\\\") + \\\"sequence: \\\" + outstr + \\\"</td>\\\\n\\\")\\n\\n elif n.context == \\\"unpublished\\\":\\n outfile.write(\\\" <td>unpublished name <em class=\\\\\\\"species\\\\\\\">\\\" +\\n n.application + \\\"</em></td>\\\\n\\\")\\n else: # \\\"n/a\\\"\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n\\n # accepted species name\\n if n.actual == \\\"?\\\":\\n outfile.write(\\\" <td>?</td>\\\\n\\\")\\n elif n.actual in {\\\".\\\", \\\"=\\\"}:\\n outfile.write(\\\" <td>TBD</td>\\\\n\\\")\\n elif n.actual == \\\"n/a\\\":\\n outfile.write(\\\" <td> </td>\\\\n\\\") \\n elif n.actual.startswith(\\\">\\\"):\\n outfile.write(\\\" <td><em class=\\\\\\\"species\\\\\\\">\\\" + n.actual[1:] + \\\"</em></td>\\\\n\\\")\\n elif n.actual.startswith(\\\"#\\\"):\\n t_rank, t_name = n.actual[1:].split(\\\"#\\\")\\n outfile.write(\\\" <td>\\\" + create_taxon_link(t_rank, t_name, do_print, path=\\\"../\\\") + \\\"</td>\\\\n\\\")\\n else:\\n s = find_species_by_name(n.actual)\\n if \\\"<?>\\\" in n.application:\\n glyphstr = \\\" \\\" + fetch_fa_glyph(\\\"questionable id\\\")\\n else:\\n glyphstr = \\\"\\\"\\n outfile.write(\\\" <td><a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../\\\") + \\\"u_\\\" + n.actual +\\n \\\".html\\\\\\\"><em class=\\\\\\\"species\\\\\\\">\\\" + s.binomial() + \\\"</em></a>\\\" + glyphstr + \\\"</td>\\\\n\\\")\\n\\n # source of accepted species\\n if n.source == \\\".\\\": # currently not listed\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n elif n.source == \\\"<\\\": # original name retained\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"original\\\") + \\\"Original</td>\\\\n\\\")\\n elif n.source == \\\"=\\\": # automatically computer\\n outfile.write(\\\" <td>\\\" + fetch_fa_glyph(\\\"computed\\\") + \\\"Computed</td>\\\\n\\\")\\n else:\\n if \\\";\\\" in n.source:\\n source_list = n.source.split(\\\";\\\")\\n else:\\n source_list = [n.source]\\n source_strs = []\\n for source in source_list:\\n if source in refdict: # another reference\\n crossref = refdict[source]\\n source_strs.append(\\\"<a href=\\\\\\\"\\\" + rel_link_prefix(do_print, \\\"../references/\\\") +\\n crossref.cite_key + \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a>\\\")\\n else: # should start with a >\\n tmpsource = source[1:]\\n tmpsource = tmpsource.replace(\\\"MSR:\\\", \\\"\\\")\\n tmpsource = tmpsource.replace(\\\"/\\\", \\\"/<br />\\\")\\n tmpsource = tmpsource.replace(\\\"geography\\\", fetch_fa_glyph(\\\"geography\\\") + \\\"Geography\\\")\\n tmpsource = tmpsource.replace(\\\"synonymy\\\", fetch_fa_glyph(\\\"synonymy\\\") + \\\"Synonymy\\\")\\n source_strs.append(tmpsource)\\n outfile.write(\\\" <td>\\\" + \\\", \\\".join(source_strs) + \\\"</td>\\\\n\\\")\\n\\n # notes\\n if notecnt > 0:\\n if n.name_note == \\\".\\\":\\n outfile.write(\\\" <td> </td>\\\\n\\\")\\n else:\\n outfile.write(\\\" <td>\\\" + replace_species_in_string(n.name_note) + \\\"</td>\\\\n\\\")\\n outfile.write(\\\" </tr>\\\\n\\\")\\n outfile.write(\\\" </table>\\\\n\\\")\",\n \"def add_ref_tag(basicSeqs):\\r\\n\\r\\n formattedBasicSeqs=list(basicSeqs) \\r\\n for record in formattedBasicSeqs:\\r\\n record.id=record.id+'_Ref'\\r\\n record.name=record.name+'_Ref'\\r\\n record.description=record.description+'_Ref'\\r\\n return formattedBasicSeqs\",\n \"def cite_report(self):\\n\\n num_cites = np.sum(np.array([q.citation_count for q in self.mypapers]))\\n print(\\\"number of citations = \\\", num_cites)\\n\\n for n, p in enumerate(self.mypapers):\\n clean_tags = re.compile(\\\"<.*?>\\\")\\n title = re.sub(clean_tags, \\\"\\\", p.title[0])\\n tt = textwrap.wrap(title, 60)\\n print(f\\\"{n+1:3} | {p.citation_count:4} {tt[0]}\\\")\\n if len(tt) > 1:\\n for line in tt[1:]:\\n print(\\\"{:3} | {:4} {}\\\".format(\\\"\\\", \\\"\\\", line))\\n print(\\\"{:3} | {:4} {}\\\".format(\\\"\\\", \\\"\\\", \\\"\\\"))\",\n \"def add_ref(doc_name, bib_name, keep_label=False, slides=False):\\n bib_path = bib_name # os.path.join(static_path, \\\"tex\\\", bib_name)\\n if not slides:\\n keep_label = True\\n with open(doc_name, \\\"r\\\") as f:\\n _file = f.read()\\n # find citations\\n match = re.findall(r\\\"\\\\[@.*?\\\\]\\\", _file)\\n references = []\\n # print(match)\\n for cit in match:\\n tmp_cite_html = tempfile.NamedTemporaryFile(suffix=\\\".html\\\", delete=True)\\n tmp = tempfile.NamedTemporaryFile(suffix=\\\".md\\\", delete=True)\\n with open(tmp.name, \\\"w\\\") as md_file:\\n # Open the file for writing.\\n md_file.write(cit)\\n\\n pandoc_command = [\\n \\\"pandoc\\\",\\n \\\"-C\\\",\\n tmp.name,\\n \\\"--bibliography\\\",\\n bib_path,\\n \\\"--csl\\\",\\n \\\"./templates/my-csl.csl\\\",\\n \\\"-o\\\",\\n tmp_cite_html.name,\\n ]\\n if not slides:\\n for tag in [\\\"--metadata\\\", \\\"link-citations=true\\\"]:\\n pandoc_command.append(tag)\\n output = subprocess.check_output(\\n pandoc_command, stderr=subprocess.STDOUT\\n ).decode(\\\"utf-8\\\")\\n print(output.rstrip())\\n tmp.close()\\n with open(tmp_cite_html.name, \\\"r\\\") as cite_html:\\n # Open the file for writing.\\n cit_new = cite_html.read()\\n # print(cit_new)\\n if not keep_label:\\n # remove first line\\n cit_new = \\\"\\\\n\\\".join(cit_new.splitlines()[1:])\\n else:\\n lines = cit_new.splitlines()\\n # remove the <p> tags\\n lines[0] = lines[0][3:-4]\\n cit_new = \\\"\\\\n\\\".join(lines)\\n if slides:\\n _file = _file.replace(cit, cit_new)\\n else:\\n _file = _file.replace(cit, lines[0])\\n # collect the references\\n references.append(\\\"<p>\\\")\\n references.append(\\\"\\\\n\\\".join(lines))\\n references.append(\\\"</p>\\\")\\n # paste_refs_end()\\n tmp_cite_html.close()\\n if slides:\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n if not slides:\\n if references == []:\\n _file=clean_html_refs(_file)\\n else:\\n _file = _file.replace(\\\"<bibliography-placeholder>\\\", \\\"\\\\n\\\".join(references))\\n with open(doc_name, \\\"w\\\") as f:\\n f.write(_file)\\n return\",\n \"def formatJointTableForLaTeX(joints):\\n (varList, atoms, probs) = joints\\n cols = len(varList) + len (probs[0][1])\\n with open(\\\"table1.tex\\\",\\\"w\\\") as out:\\n out.write (\\\"\\\\\\\\begin{tabular}{|\\\" + \\\"|\\\".join([\\\"c\\\"]*(cols-2))+\\\"||c|c|}\\\\n\\\")\\n out.write (\\\"\\\\\\\\hline\\\\n\\\")\\n # Table header\\n out.write (\\\" & \\\".join(varList) + \\\" & \\\" + \\\" & \\\".join([a for a in atoms]) + \\\" & Joint $p$ & ln~$p$ \\\\\\\\\\\\\\\\ \\\\\\\\hline\\\\n\\\")\\n # Table rows\\n logps = []\\n for (grounding, probs) in probs:\\n out.write (\\\" & \\\".join([val for (var, val) in grounding.varList]) + \\\" & \\\" +\\n \\\" & \\\".join([str(n.val)+\\\" ({:.1f})\\\".format(p) for (n,p) in probs[:-2]]) +\\n \\\" & {:.2f}\\\".format(probs[-2]) + \\\" & {:.2f}\\\".format(probs[-1]) + \\\"\\\\\\\\\\\\\\\\\\\\n\\\")\\n logps.append(probs[-1])\\n # A line to indicate there are further entries in the DB\\n out.write(\\\" & \\\".join([\\\"\\\\ldots\\\"]*cols) + \\\"\\\\\\\\\\\\\\\\\\\\n\\\")\\n # Close environment\\n out.write (\\\"\\\\\\\\hline\\\\n\\\\\\\\end{tabular}\\\\n\\\")\\n\\n with open(\\\"tab1plogp.tex\\\",\\\"w\\\") as plogp:\\n plogp.write(\\\"\\\\\\\\newcommand{\\\\\\\\pseudologp}{\\\"+\\\"{:.2f}\\\".format(sum(logps)/len(logps))+\\\"}\\\\n\\\")\",\n \"def insert_into_citation_table(citations):\\n cursor = connection.cursor()\\n cursor.execute(\\n 'DROP TABLE IF EXISTS Citations;'\\n 'CREATE TABLE Citations(sourcePaperId INT, targetPaperId INT, citationId INT NOT NULL AUTO_INCREMENT PRIMARY KEY);'\\n )\\n cursor.close()\\n i = 0\\n\\n for citation in citations:\\n print i\\n i+=1\\n cursor = connection.cursor()\\n cursor.execute(\\n 'INSERT INTO Citations (sourcePaperId, targetPaperId) VALUES '\\n '((SELECT PaperId FROM Papers WHERE DOI = %s),(SELECT PaperId FROM Papers WHERE DOI = %s));'\\n ,[citation['source'].encode('UTF-8'),citation['target'].encode('UTF-8')])\\n cursor.close()\",\n \"def main():\\n ref_seq = {}\\n ent_spe_sero = {}\\n tag_dict = {\\\"Contigs_with_VP1\\\":\\\"contigs\\\", \\\"P1_sequences\\\":\\\"p1\\\",\\n \\\"VP1_sequences\\\":\\\"vp1\\\", \\\"5UTR_sequences\\\":\\\"5utr\\\", \\\"3D_sequences\\\":\\\"3d\\\"}\\n args = get_arguments()\\n # Load query elements\\n print(\\\"Load resume file\\\")\\n (query_dict, classify_list,\\n classify_specie_list, serotype_list) = get_query(args.resume_file,\\n args.tag,\\n args.incomplete)\\n print(\\\"{} descriptions loaded\\\".format(len(query_dict)))\\n # Load specie association\\n if args.ent_serotype_file and args.template_seq_file:\\n # Load enterovirus serotype\\n print(\\\"Load enterovirus serotype association\\\")\\n ent_spe_sero = load_spe_sero(args.ent_serotype_file)\\n # Load template sequence\\n print(\\\"Load template sequence\\\")\\n ref_seq = get_template_sequence(args.template_seq_file, ent_spe_sero)\\n # Grab query sequence in the database\\n print(\\\"Load database sequence\\\")\\n sequence_data = get_sequence(query_dict, args.fasta_file)\\n print(\\\"{} sequences loaded\\\".format(len(sequence_data)))\\n # Write the new fasta file\\n print(\\\"Write the new fasta\\\")\\n write_sequence(args.results, sequence_data, query_dict, classify_list,\\n tag_dict[args.tag], ref_seq, ent_spe_sero)\\n #print(save_association)\\n print(\\\"Write the itol label\\\")\\n write_itol_label(args.itol_dir, sequence_data, query_dict, classify_list,\\n tag_dict[args.tag])\\n print(\\\"Write the itol tree color\\\")\\n write_itol_tree_color(args.itol_dir, sequence_data, query_dict, classify_specie_list, serotype_list,\\n tag_dict[args.tag])\\n print(\\\"Done\\\")\",\n \"def compute_species_from_citation_linking(citelist: list) -> None:\\n # for i, cite in enumerate(tqdm(citelist)):\\n unrecorded_xrefs = []\\n recorded_refs = set()\\n for i, cite in enumerate(citelist):\\n recorded_refs.add(cite.cite_key)\\n if cite.actual == \\\"=\\\":\\n cname = \\\"\\\"\\n crossnames = collections.Counter()\\n for j in range(i): # only look at entries up to the current one\\n tmp = citelist[j]\\n if (tmp.cite_key == cite.application) and match_num_ref(tmp.name_key, cite.cite_n):\\n cname = tmp.name\\n crossnames.update([tmp.actual])\\n if len(crossnames) == 0:\\n unrecorded_xrefs.append([cite.cite_key, cite.application, cite.name_key, cite.cite_n])\\n elif len(crossnames) == 1:\\n cite.actual = list(crossnames.keys())[0]\\n else:\\n # find name(s) with largest count\\n mcnt = max(crossnames.values())\\n keylist = []\\n for key in crossnames:\\n if crossnames[key] == mcnt:\\n keylist.append(key)\\n\\n if len(keylist) == 1:\\n cite.actual = keylist[0]\\n else:\\n cite_name = cite.name.lower()\\n while cite_name.find(\\\" \\\") > -1:\\n cite_name = cite_name[cite_name.find(\\\" \\\")+1:]\\n while cname.find(\\\" \\\") > -1:\\n cname = cname[cname.find(\\\" \\\")+1:]\\n\\n if cite_name in keylist:\\n cite.actual = cite_name\\n elif cname in keylist:\\n cite.actual = cname\\n else:\\n cite.actual = keylist[0]\\n\\n if cite.name_note == \\\".\\\":\\n cite.name_note = \\\"in part\\\"\\n else:\\n cite.name_note = \\\"in part; \\\" + cite.name_note\\n\\n for x in unrecorded_xrefs:\\n if x[1] in recorded_refs:\\n report_error(\\\"Reference {} ({}) does not appear until after citation from {} ({})\\\".format(x[1], x[3],\\n x[0], x[2]))\",\n \"def references(name, tag):\\n\\n gen_refs = \\\"\\\\n\\\".join([''.join([\\\"J. Bartels, The technique of scaling \\\",\\n \\\"indices K and Q of geomagnetic activity, \\\",\\n \\\"Ann. Intern. Geophys. Year 4, 215-226, \\\",\\n \\\"1957.\\\"]),\\n ''.join([\\\"J. Bartels,The geomagnetic measures for \\\",\\n \\\"the time-variations of solar corpuscular \\\",\\n \\\"radiation, described for use in \\\",\\n \\\"correlation studies in other geophysical \\\",\\n \\\"fields, Ann. Intern. Geophys. Year 4, \\\",\\n \\\"227-236, 1957.\\\"]),\\n ''.join([\\\"P.N. Mayaud, Derivation, Meaning and Use \\\",\\n \\\"of Geomagnetic Indices, Geophysical \\\",\\n \\\"Monograph 22, Am. Geophys. Union, \\\",\\n \\\"Washington D.C., 1980.\\\"]),\\n ''.join([\\\"G.K. Rangarajan, Indices of magnetic \\\",\\n \\\"activity, in Geomagnetism, edited by I.A. \\\",\\n \\\"Jacobs, Academic, San Diego, 1989.\\\"]),\\n ''.join([\\\"M. Menvielle and A. Berthelier, The \\\",\\n \\\"K-derived planetary indices: description \\\",\\n \\\"and availability, Rev. Geophys. 29, 3, \\\",\\n \\\"415-432, 1991.\\\"])])\\n refs = {'kp': {'': gen_refs, 'forecast': gen_refs, 'recent': gen_refs}}\\n\\n return refs[name][tag]\",\n \"def references_list( self, theWeaver ):\\n return [ (c.name, c.seq) \\n for c in theWeaver.reference_style.chunkReferencedBy( self ) ]\",\n \"def extract_references(text, preprocessor, model):\\n has_reference_section, reference_section, non_reference_section = preprocess_reference_text(text)\\n reference_text = reference_section if has_reference_section else non_reference_section\\n fragment = preprocessor(reference_text)\\n out = model(fragment.idx).argmax(dim=2).cpu().numpy()\\n\\n buffer = ''\\n found_citations = []\\n in_citation = False\\n for char, pred in zip(fragment.text, out[0, :]):\\n if pred == 2:\\n in_citation = True\\n if pred == 3:\\n in_citation = False\\n if pred in [2, 3]:\\n if buffer:\\n found_citations.append(buffer)\\n buffer = char\\n elif pred == 1:\\n buffer += char\\n elif pred == 0:\\n if in_citation:\\n buffer += char\\n else:\\n if buffer:\\n found_citations.append(buffer)\\n buffer = ''\\n return found_citations\",\n \"def _populate(self):\\n\\n # Assume the first word is what we want, and we can find well formed years\\n # This sucks, but will work for these ones.\\n # Roll on bibtex for citations in the CIM.\\n\\n citation_detail = self.doc.citation_detail\\n author = citation_detail.split(',')[0]\\n match = '([^\\\\w])19|20\\\\d\\\\d([^\\\\w])*?'\\n m = re.search(match, citation_detail)\\n if m:\\n year = m.group(0)\\n else:\\n year = None\\n\\n # one error in existing es-doc content to be fixed:\\n if 'van Vuuren DP' in author:\\n author = 'van Vuuren'\\n print 'applying vv fix'\\n\\n self.year = int(year)\\n\\n # We assume that this table will have entries which ne\\n\\n # I use the first three letters of a an authors name, and for\\n # three or more authors, EA, and then the year for my bibtex citation string\\n self.citeguess = author[0:3] + 'EA' + year[2:]\\n # This is what will appear in the table:\\n self.citestring = '%s et al. (%s)' % (author, year)\\n # Keep this for a reference list for checking against the eventual bibtex reference list.\\n self.text = citation_detail\",\n \"def _showStringXrefs(self):\\n\\n # Retrieve some config values\\n show_misc.entropy = self.config.calculate_misc.entropy\\n show_unique_s = self.config.display_unique_strings\\n\\n self._console_output(\\\"Calculating string references...\\\")\\n\\n self.ba.calculate_strings_list()\\n s_ref_list = self.ba.get_string_references()\\n\\n # Found any references at all?\\n nrows = len(s_ref_list)\\n if not nrows:\\n self._console_output(\\\"[!] No string references found\\\", err = True)\\n return\\n\\n if show_misc.entropy:\\n self.table.setColumnCount(3)\\n self.table.setHorizontalHeaderLabels((\\\"Address\\\", \\\"String\\\", \\\"misc.entropy\\\"))\\n\\n else:\\n self.table.setColumnCount(2)\\n self.table.setHorizontalHeaderLabels((\\\"Address\\\", \\\"String\\\"))\\n\\n self.table_label.setText(\\\"String references in current function\\\")\\n self.table.clearContents()\\n self.table.setRowCount(0)\\n\\n # Fill the table\\n displayed_strings = []\\n\\n idx = 0\\n for (addr, s) in s_ref_list:\\n if show_unique_s and s in displayed_strings:\\n continue\\n\\n displayed_strings.append(s)\\n\\n self.table.insertRow(idx)\\n addr_item = QTableWidgetItem(\\\"%08x\\\" % addr)\\n addr_item.setFlags(addr_item.flags() ^ QtCore.Qt.ItemIsEditable)\\n string_item = QTableWidgetItem(\\\"%s\\\" % s)\\n string_item.setFlags(string_item.flags() ^ QtCore.Qt.ItemIsEditable)\\n\\n self.table.setItem(idx, 0, addr_item)\\n self.table.setItem(idx, 1, string_item)\\n\\n if show_misc.entropy:\\n misc.entropy_item = cw.NumQTableWidgetItem(\\\"%.4f\\\" % misc.entropy(s))\\n self.table.setItem(idx, 2, misc.entropy_item)\\n\\n idx += 1\",\n \"def enrich_textrefs(self, db):\\n tr_list = db.select_all(db.TextRef,\\n db.TextContent.text_ref_id == db.TextRef.id,\\n db.TextContent.source == self.my_source,\\n db.TextRef.manuscript_id.is_(None))\\n file_list = self.ftp.get_csv_as_dict('filelist.csv', header=0)\\n pmcid_mid_dict = {entry['PMCID']: entry['MID'] for entry in file_list}\\n pmid_mid_dict = {entry['PMID']: entry['MID'] for entry in file_list\\n if entry['PMID'] is not '0'}\\n for tr in tr_list:\\n if tr.pmcid is not None:\\n tr.manuscript_id = pmcid_mid_dict[tr.pmcid]\\n elif tr.pmid is not None and tr.pmid in pmid_mid_dict.keys():\\n tr.manuscript_id = pmid_mid_dict[tr.pmid]\\n db.commit(\\\"Could not update text refs with manuscript ids.\\\")\\n return\",\n \"def populate_crossreference_dictionary(self):\\n master_crossreference_dictionary = dict()\\n\\n # If additional crossreferences need to be used to find interactors, they can be added here.\\n # Use the crossreference prefix as the dictionary name.\\n # Also add a regex entry to the resolve_identifier function.\\n master_crossreference_dictionary['UniProtKB'] = dict()\\n master_crossreference_dictionary['ENSEMBL'] = dict()\\n master_crossreference_dictionary['NCBI_Gene'] = dict()\\n master_crossreference_dictionary['RefSeq'] = dict()\\n\\n for key in master_crossreference_dictionary:\\n self.logger.info('Querying for %s cross references.', key)\\n with Neo4jHelper().run_single_parameter_query(self.query_xrefs, key) as result:\\n for record in result:\\n cross_ref_record = None\\n # Modify the cross reference ID to match the PSI MITAB format if necessary.\\n # So far, this is just converting 'NCBI_Gene' to 'entrez gene/locuslink'.\\n if record['cr.globalCrossRefId'].startswith('NCBI_Gene'):\\n cross_ref_record_split = record['cr.globalCrossRefId'].split(':')[1]\\n cross_ref_record = 'entrez gene/locuslink:' + cross_ref_record_split\\n else:\\n cross_ref_record = record['cr.globalCrossRefId']\\n\\n # The crossreference dictionary is a list of genes\\n # linked to a single crossreference.\\n # Append the gene if the crossref dict entry exists.\\n # Otherwise, create a list and append the entry.\\n if cross_ref_record.lower() in master_crossreference_dictionary[key]:\\n master_crossreference_dictionary[key][cross_ref_record.lower()].append(record['g.primaryKey'])\\n else:\\n master_crossreference_dictionary[key][cross_ref_record.lower()] = []\\n master_crossreference_dictionary[key][cross_ref_record.lower()].append(record['g.primaryKey'])\\n\\n # The ids in PSI-MITAB files are lower case, hence the .lower() used above.\\n\\n return master_crossreference_dictionary\",\n \"def table_of_cores():\\n return (\\n '### Magnetic core library '\\n f'(from [{LIBRARY_PATH}]({LIBRARY_PATH}))\\\\n' +\\n 'Variable `cores[\\\\'<some key\\\\']` can be used for adding the cores ' +\\n 'below to the design parameters.\\\\n\\\\n' +\\n format_markdown_table(\\n ['key', 'permeability $ \\\\\\\\mu $', '$ A_e $', '$ l_e $', '$ V_e $',\\n '$ B_{sat} $', 'note'],\\n [\\n [key, str(round(c.mu, 2)), str(round(c.A_e, 2)),\\n str(round(c.l_e, 2)), str(round(c.V_e, 2)),\\n str(c.B_sat), str(c.note)]\\n for key, c in cores.items()\\n ]\\n ))\",\n \"def get_references(cls, pmids):\\n\\n references = cls.query.filter(cls.pmid.in_(pmids)).all()\\n citations = {}\\n\\n for reference in references:\\n citation_text = reference.authors + \\\". (\\\" + str(\\n reference.year) + \\\"). \\\" + reference.title + \\\" \\\" + reference.journal + \\\".\\\"\\n citations[reference.pmid] = citation_text\\n\\n return citations\",\n \"def create_output(self, bib):\\n for b in bib:\\n if isinstance(b, ReferenceErrorInfo):\\n self.error_count += 1\\n if self.args.comments:\\n self.output.append(b.bibtex())\\n if not self.args.quiet:\\n self.messages.append(str(b))\\n else:\\n self.output.append(b.bibtex())\",\n \"def add_references_to_papers(infile, dir):\\n papers = json.load(open(infile))\\n for paper in papers:\\n for file in os.listdir(dir):\\n if file.split(\\\".txt\\\")[0] == paper['doi']: # Must find the correct file to parse\\n filename = TEXT_DIR+file\\n refs =extract_references_from_txt(filename) #Uses the text files to find references\\n paper['references']=refs\\n return papers\",\n \"def _export_reference_representations(self):\\n\\n self.logger.msg1(\\\"Saving reference representations\\\")\\n general_refset, _ = get_refsets(self.dbpath)\\n general_refset.save(self.rootpath+\\\"-references\\\", \\\"phenotype\\\")\",\n \"def CreateGeneModels(genes_cmpt, transcripts_cmpt, exons_cmpt, utr3_cmpt, utr5_cmpt, cds_cmpt):\\n gene_counter, gene_models = 1, []\\n for gene_entry in genes_cmpt: ## Figure out the genes and transcripts associated feature \\n if gene_entry in transcripts_cmpt:\\n gene=init_gene() \\n gene['id']=gene_counter\\n gene['name']=gene_entry[1]\\n gene['chr']=genes_cmpt[gene_entry]['chr']\\n gene['source']=genes_cmpt[gene_entry]['source']\\n gene['start']=genes_cmpt[gene_entry]['start']\\n gene['stop']=genes_cmpt[gene_entry]['stop']\\n gene['strand']=genes_cmpt[gene_entry]['strand']\\n if not gene['strand'] in ['+', '-']:\\n gene['strand']='.' # Strand info not known replaced with a dot symbol instead of None, ?, . etc.\\n if len(transcripts_cmpt[gene_entry])>1:\\n gene['is_alt_spliced'] = 1\\n gene['is_alt'] = 1\\n\\t gtype=[]\\n for tids in transcripts_cmpt[gene_entry]: ## transcript section related tags \\n gene['transcripts'].append(tids['ID'])\\n\\t\\tgtype.append(tids['type'])\\n exon_cod, utr5_cod, utr3_cod, cds_cod = [], [], [], []\\n if (gene['chr'], tids['ID']) in exons_cmpt:\\n exon_cod = [[feat_exon['start'], feat_exon['stop']] for feat_exon in exons_cmpt[(gene['chr'], tids['ID'])]]\\n if (gene['chr'], tids['ID']) in utr5_cmpt:\\n utr5_cod = [[feat_utr5['start'], feat_utr5['stop']] for feat_utr5 in utr5_cmpt[(gene['chr'], tids['ID'])]]\\n if (gene['chr'], tids['ID']) in utr3_cmpt:\\n utr3_cod = [[feat_utr3['start'], feat_utr3['stop']] for feat_utr3 in utr3_cmpt[(gene['chr'], tids['ID'])]]\\n if (gene['chr'], tids['ID']) in cds_cmpt:\\n cds_cod = [[feat_cds['start'], feat_cds['stop']] for feat_cds in cds_cmpt[(gene['chr'], tids['ID'])]]\\n if len(exon_cod) == 0: ## build exon coordinates from UTR3, UTR5 and CDS\\n if cds_cod != []:\\n exon_cod=createExon(gene['strand'], utr5_cod, cds_cod, utr3_cod) \\n\\n if gene['strand']=='-': ## general order to coordinates\\n if len(exon_cod) >1:\\n if exon_cod[0][0] > exon_cod[-1][0]:\\n exon_cod.reverse()\\n if len(cds_cod) >1:\\n if cds_cod[0][0] > cds_cod[-1][0]: \\n cds_cod.reverse()\\n if len(utr3_cod) >1:\\n if utr3_cod[0][0] > utr3_cod[-1][0]: \\n utr3_cod.reverse()\\n if len(utr5_cod) >1:\\n if utr5_cod[0][0] > utr5_cod[-1][0]:\\n utr5_cod.reverse()\\n\\n tis, cdsStop, tss, cleave = [], [], [], [] ## speacial sited in the gene region \\n if cds_cod != []:\\n if gene['strand'] == '+':\\n tis = [cds_cod[0][0]]\\n cdsStop = [cds_cod[-1][1]-3]\\n elif gene['strand'] == '-':\\n tis = [cds_cod[-1][1]]\\n cdsStop = [cds_cod[0][0]+3]\\n if utr5_cod != []:\\n if gene['strand'] == '+':\\n tss = [utr5_cod[0][0]]\\n elif gene['strand'] == '-':\\n tss = [utr5_cod[-1][1]]\\n if utr3_cod != []:\\n if gene['strand'] == '+':\\n cleave = [utr3_cod[-1][1]]\\n elif gene['strand'] == '-':\\n cleave = [utr3_cod[0][0]]\\n\\n cds_status, exon_status, utr_status = 0, 0, 0 ## status of the complete elements of the gene\\n if cds_cod != []: ## adding phase to the CDS region \\n cds_cod_phase = addCDSphase(gene['strand'], cds_cod)\\n cds_status = 1\\n gene['cds_exons'].append(cds_cod_phase)\\n\\n if exon_cod != []: \\n exon_status = 1\\n if utr5_cod != [] or utr3_cod != []: \\n utr_status = 1\\n if cds_status != 0 and exon_status != 0 and utr_status != 0:\\n gene['transcript_status'].append(1)\\n else:\\n gene['transcript_status'].append(0)\\n\\n if exon_cod: ## final check point for a valid gene model \\n gene['exons'].append(exon_cod)\\n gene['utr3_exons'].append(utr3_cod)\\n gene['utr5_exons'].append(utr5_cod)\\n gene['tis'].append(tis)\\n gene['cdsStop'].append(cdsStop)\\n gene['tss'].append(tss)\\n gene['cleave'].append(cleave) \\n\\t \\n\\t gtype=list(set(gtype)) ## different types \\n gene['gene_info']=dict(ID=gene_entry[1],\\n\\t\\t\\t\\tSource=genes_cmpt[gene_entry]['source'],\\n\\t\\t\\t\\tType=gtype)\\n gene=FeatureValueFormat(gene) ## get prepare for MAT writing \\n gene_counter+=1\\n gene_models.append(gene)\\n return gene_models\",\n \"def make_bibtex(self):\\n\\n\\t\\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi, \",\n \"def perf2latex(latex_fn, all_perf, metrics_name, slice_v, cam_v):\\n slice_num = slice_v.shape[0]\\n\\n f = open('%s'%latex_fn, 'w')\\n f.write(\\\"\\\\\\\\documentclass{article}\\\\n\\\")\\n f.write(\\\"\\\\\\\\usepackage[utf8]{inputenc}\\\\n\\\")\\n f.write(\\\"\\\\\\\\usepackage{booktabs} \\\\n\\\")\\n f.write(\\\"\\\\\\\\usepackage[]{float}\\\\n\\\")\\n f.write(\\\"\\\\\\\\usepackage[margin=1.2in]{geometry}\\\\n\\\")\\n f.write(\\\"\\\\\\\\begin{document}\\\\n\\\\n\\\")\\n\\n for m_name in metrics_name:\\n print(m_name)\\n f.write('\\\\\\\\begin{table}[tbh]\\\\n')\\n f.write('\\\\\\\\begin{center}\\\\n')\\n f.write('\\\\\\\\begin{tabular}{|*{%d}{c|}}\\\\n'%(slice_num + 1))\\n f.write('\\\\\\\\hline\\\\n')\\n f.write(' Survey')\\n #for slice_idx, slice_id in enumerate(slice_cam_id[:-1]):\\n for j, (slice_id, cam_id) in enumerate(zip(slice_v, cam_v)):\\n f.write(' & %d\\\\_c%d'%(slice_id, cam_id))\\n f.write(' \\\\\\\\\\\\\\\\ \\\\n')\\n f.write('\\\\\\\\hline\\\\n')\\n\\n m = all_perf[m_name]\\n print(m.shape)\\n survey_num = m.shape[0]\\n for i in range(survey_num):\\n f.write('%d'%(i))\\n for j in range(slice_num):\\n f.write(' & %.3f'%m[i,j])\\n f.write(' \\\\\\\\\\\\\\\\ \\\\n')\\n\\n f.write('\\\\\\\\hline\\\\n')\\n f.write('\\\\\\\\end{tabular}\\\\n')\\n f.write('\\\\\\\\end{center}\\\\n')\\n f.write('\\\\\\\\caption{Metric: %s}\\\\n'%(m_name))\\n f.write('\\\\\\\\end{table}\\\\n\\\\n\\\\n')\\n\\n f.write('\\\\\\\\end{document}\\\\n')\\n print('\\\\\\\\end{document}\\\\n')\\n \\n f.close()\",\n \"def collect_citation_metadata(\\n metadata: dict, references: List[pybtex.database.Entry]\\n) -> dict:\\n # Author list\\n citation_authors = []\\n for author_tier in [\\\"Core\\\", \\\"Developers\\\", \\\"Contributors\\\"]:\\n for author in metadata[\\\"Authors\\\"][author_tier][\\\"List\\\"]:\\n family_names, given_names = author[\\\"Name\\\"].split(\\\", \\\")\\n citation_author = {\\n \\\"family-names\\\": family_names,\\n \\\"given-names\\\": given_names,\\n }\\n if \\\"Orcid\\\" in author:\\n citation_author[\\\"orcid\\\"] = (\\n \\\"https://orcid.org/\\\" + author[\\\"Orcid\\\"]\\n )\\n if \\\"Affiliations\\\" in author and len(author[\\\"Affiliations\\\"]) > 0:\\n citation_author[\\\"affiliation\\\"] = \\\" and \\\".join(\\n author[\\\"Affiliations\\\"]\\n )\\n citation_authors.append(citation_author)\\n # References in CITATION.cff format\\n citation_references = [to_cff_reference(entry) for entry in references]\\n return {\\n \\\"cff-version\\\": \\\"1.2.0\\\",\\n \\\"message\\\": (\\n \\\"Please cite SpECTRE in any publications that make use of its code\\\"\\n \\\" or data. Cite the latest version that you use in your\\\"\\n \\\" publication. The citation for this version is listed below.\\\"\\n ),\\n \\\"title\\\": metadata[\\\"Name\\\"],\\n \\\"url\\\": metadata[\\\"Homepage\\\"],\\n \\\"repository-code\\\": \\\"https://github.com/\\\" + metadata[\\\"GitHub\\\"],\\n \\\"version\\\": metadata[\\\"Version\\\"],\\n \\\"date-released\\\": metadata[\\\"PublicationDate\\\"],\\n \\\"doi\\\": metadata[\\\"Doi\\\"],\\n \\\"authors\\\": citation_authors,\\n \\\"keywords\\\": metadata[\\\"Keywords\\\"],\\n \\\"license\\\": metadata[\\\"License\\\"],\\n \\\"references\\\": citation_references,\\n }\",\n \"def column_creator(path):\\n if not os.path.exists(path+'tables'):\\n os.makedirs(path+'tables')\\n\\n\\n # Sequences\\n if os.path.exists(path+'SEQ.txt'):\\n with open(os.path.join(path+'SEQ.txt')) as f1, open(os.path.join(path+'tables/sequences_table.txt'), 'a') as f2:\\n c = Counter(x.strip() for x in f1)\\n for x in c:\\n f2.write(\\\"%s\\\\t%s\\\\n\\\" % (x, str(c[x])))\\n f1.close()\\n f2.close()\\n\\n # Modifications\\n if os.path.exists(path + 'modifications.txt'):\\n\\n with open(os.path.join(path+'modifications.txt')) as f1, open(os.path.join(path+'tables/modifications_table.txt'), 'a') as f2:\\n c = Counter(x.strip() for x in f1)\\n for x in c:\\n f2.write(\\\"%s\\\\t%s\\\\n\\\" % (x, str(c[x])))\\n f1.close()\\n f2.close()\\n\\n # Spectrum identify:\\n if os.path.exists(path + 'spectrum_identify.txt'):\\n\\n with open(os.path.join(path+'spectrum_identify.txt')) as f1, open(path+'tables/spectrum_ide_table.txt', 'a') as f3:\\n lines1 = f1.read().count('\\\\n')\\n f3.write(\\\"%s\\\\n%s\\\\n\\\" % (\\\"Spectrum Number\\\",lines1))\\n f1.close()\\n f3.close()\\n\\n if os.path.exists(path + 'spectrum_unidentify.txt'):\\n with open(os.path.join(path+'spectrum_unidentify.txt')) as f2, open(path+'tables/spectrum_unide_table.txt', 'a') as f3:\\n lines2 = f2.read().count('\\\\n')\\n f3.write(\\\"%s\\\\n%s\\\\n\\\" % (\\\"Spectrum Number\\\",lines2))\\n f2.close()\\n f3.close()\\n\\n if os.path.exists(path+'taxonomy_identify.txt'):\\n # Taxonomy ide:\\n with open(os.path.join(path+'taxonomy_identify.txt')) as f1, open(os.path.join(path+'tables/taxonomy_ide_table.txt'), 'a') as f2:\\n c = Counter(x.strip() for x in f1)\\n for x in c:\\n f2.write(\\\"%s\\\\t%s\\\\n\\\" % (x, str(c[x])))\\n f1.close()\\n f2.close()\\n\\n\\n if os.path.exists(path + 'taxonomy_unidentify.txt'):\\n # Taxonomy unide:\\n with open(os.path.join(path+'taxonomy_unidentify.txt')) as f1, open(os.path.join(path+'tables/taxonomy_unide_table.txt'), 'a') as f2:\\n c = Counter(x.strip() for x in f1)\\n for x in c:\\n f2.write(\\\"%s\\\\t%s\\\\n\\\" % (x, str(c[x])))\\n f1.close()\\n f2.close()\",\n \"def main(argv):\\n if len(argv) == 0 or argv == None:\\n print(HELP_TXT)\\n sys.exit(2)\\n try:\\n opts, args = getopt.getopt(argv,\\\"dhmb:\\\",[\\\"debug\\\", \\\"help\\\", \\\"markdown\\\", \\\"biblio=\\\"])\\n except getopt.GetoptError:\\n print(HELP_TXT)\\n sys.exit(2)\\n\\n testing = False\\n markdown = False\\n bibtex_filename = \\\"library.bib\\\"\\n \\n for opt, arg in opts:\\n if opt in ('-h', '--help'):\\n print(HELP_TXT)\\n sys.exit()\\n elif opt in ('-d', '--debug'):\\n testing = True\\n print(\\\"Fetching of DOI and printing metadata, but not adding to bibtex or creating markdown.\\\")\\n elif opt in ('-b', '--biblio'):\\n bibtex_filename = arg\\n elif opt in ('-m', '--markdown'):\\n markdown = True\\n print(\\\"Writing entry to bibtex file but not creating a markdown file.\\\")\\n\\n if len(args) == 0:\\n print(\\\"Error: At least one DOI must be provided.\\\")\\n sys.exit(2)\\n\\n for doi in args:\\n #Get the metadata from crossref.org\\n res = doi2json(doi)\\n \\n #extract\\n meta = extract_metadata(res)\\n \\n #check if reference exists\\n citation_found = True\\n letters = list(string.ascii_lowercase)\\n try:\\n with open(bibtex_filename, 'r') as fobj:\\n text = fobj.read().strip()\\n tmp_key = meta['citationkey']\\n for letter in letters:\\n if tmp_key in text:\\n tmp_key = meta['citationkey'] + letter\\n else:\\n meta['citationkey'] = tmp_key\\n break\\n except FileNotFoundError:\\n pass\\n\\n #Then write if not testing\\n if testing:\\n print(\\\"DOI RESULTS:\\\")\\n for k,v in res.items():\\n if type(v) is list:\\n print(k + ': ' + str(v) + '\\\\n')\\n else:\\n print(k + ': \\\"' + str(v) + '\\\"\\\\n')\\n print(\\\"PARSED METADATA:\\\")\\n for k,v in meta.items():\\n if type(v) is list:\\n print(k + ': ' + str(v) + '\\\\n')\\n else:\\n print(k + ': \\\"' + str(v) + '\\\"\\\\n')\\n else:\\n if not os.path.isfile(bibtex_filename):\\n print(\\\"Bibtex file {} does not exist, creating it.\\\".format(bibtex_filename))\\n\\n #Add the metadata to the bibtex reference\\n with open(bibtex_filename, \\\"a+\\\") as f:\\n s = \\\",\\\".join([\\n \\\"\\\\n@article{\\\" + meta['citationkey'],\\n \\\"\\\\nauthor = {\\\" + \\\" and \\\".join(meta['authors']) + \\\"}\\\",\\n \\\"\\\\ndoi = {\\\" + meta['doi'] + \\\"}\\\",\\n \\\"\\\\nissn = {\\\" + meta['issn'] + \\\"}\\\",\\n \\\"\\\\njournal = {\\\" + meta['container'] + \\\"}\\\",\\n \\\"\\\\npublisher = {\\\" + meta['publisher'] + \\\"}\\\",\\n \\\"\\\\nnumber = {\\\" + meta['issue'] + \\\"}\\\",\\n \\\"\\\\npages = {\\\" + meta['pages'] + \\\"}\\\",\\n \\\"\\\\ntitle = {\\\" + meta['source-title'] + \\\"}\\\",\\n \\\"\\\\nurl = {\\\" + meta['link'] + \\\"}\\\",\\n \\\"\\\\nvolume = {\\\" + meta['volume'] + \\\"}\\\",\\n \\\"\\\\nyear = {\\\" + meta['year'] + \\\"}\\\\n}\\\\n\\\\n\\\"\\n ])\\n f.write(s)\\n \\n print(\\\"reference {} from {} added to {}!\\\\n\\\".format(meta['citationkey'], meta['container'], bibtex_filename))\\n \\n # create the markdown notes file\\n if markdown:\\n subject_dir = re.sub(r'\\\\([^)]*\\\\)', '', meta['subjects'][0]).strip().lower().replace(\\\" \\\", \\\"_\\\").replace(\\\",\\\",\\\"\\\")\\n md_dir = \\\"/\\\".join([HOME_DIR, REPO_DIR, MD_DIR, subject_dir])\\n os.mkdir(md_dir) if os.path.isdir(md_dir) == False else None\\n filename = \\\"/\\\".join([md_dir, meta['citationkey'] + \\\".md\\\"])\\n with open(filename, \\\"w\\\") as f:\\n f.write(\\\"---\\\\nlayout: mathpost\\\\n\\\")\\n for k,v in meta.items():\\n try:\\n if type(v) is list:\\n f.write(k + ': ' + str(v) + '\\\\n')\\n else:\\n f.write(k + ': \\\"' + str(v) + '\\\"\\\\n')\\n except UnicodeEncodeError as e:\\n print(\\\"Unicode Error. Some character(s) may be wrong.\\\")\\n print(meta.keys())\\n print(repr(k) + \\\": \\\" + repr(v))\\n print(e)\\n \\n f.write(\\\"---\\\\n\\\\n\\\")\\n citation = \\\"**Citation:** \\\" \\\\\\n + meta['citation-authors'] + ' \\\"' \\\\\\n + meta['source-title'] + '\\\". ' \\\\\\n + '*' + meta['container'] + '*'\\n citation = citation + \\\" \\\" + meta['volume'] if meta['volume'] != '' else citation\\n citation = citation + \\\", no. \\\" + meta['issue'] if meta['issue'] != '' else citation\\n citation = citation + \\\" (\\\" + meta['year'] + \\\")\\\" if meta['year'] != '' else citation\\n citation = citation + \\\": \\\" + meta['pages'] if meta['pages'] != '' else citation\\n \\n f.write(citation + \\\". [[Paper link](\\\" + meta['link'] + \\\")]\\\")\\n \\n #add the reference to the \\\"reading_list.md\\\" file\\n with open(\\\"/\\\".join([HOME_DIR, REPO_DIR, MD_DIR, \\\"reading_list.md\\\"]), \\\"a\\\") as f:\\n f.write(\\\"* [ ] **\\\" + meta['citationkey'] \\\\\\n + \\\"**: (\\\" \\\\\\n + re.sub(r'\\\\([^)]*\\\\)', '', meta['subjects'][0]).strip() \\\\\\n + \\\") \\\" + meta['link'] + \\\"\\\\n\\\")\\n \\n print(\\\"reference {} added in {}!\\\\n\\\".format(meta['citationkey'], md_dir))\",\n \"def run(self):\\n env = cast(\\\"BuildEnvironment\\\", self.state.document.settings.env)\\n foot_old_refs = env.temp_data.setdefault(\\\"bibtex_foot_old_refs\\\", set())\\n foot_new_refs = env.temp_data.setdefault(\\\"bibtex_foot_new_refs\\\", set())\\n footbibliography_count = env.temp_data[\\\"bibtex_footbibliography_count\\\"] = (\\n env.temp_data.get(\\\"bibtex_footbibliography_count\\\", 0) + 1\\n )\\n if not foot_new_refs:\\n return []\\n else:\\n foot_old_refs |= foot_new_refs\\n foot_new_refs.clear()\\n # bibliography stored in env.temp_data[\\\"bibtex_foot_bibliography\\\"]\\n foot_domain = cast(\\\"BibtexFootDomain\\\", env.get_domain(\\\"footcite\\\"))\\n foot_bibliography, env.temp_data[\\\"bibtex_foot_bibliography\\\"] = (\\n env.temp_data[\\\"bibtex_foot_bibliography\\\"],\\n foot_domain.bibliography_header.deepcopy(),\\n )\\n domain = cast(\\\"BibtexDomain\\\", env.get_domain(\\\"cite\\\"))\\n for bibfile in domain.bibdata.bibfiles:\\n env.note_dependency(bibfile)\\n foot_bibliography[\\\"ids\\\"] += _make_ids(\\n docname=env.docname,\\n lineno=self.lineno,\\n ids=set(self.state.document.ids.keys()),\\n raw_id=env.app.config.bibtex_footbibliography_id.format(\\n footbibliography_count=footbibliography_count\\n ),\\n )\\n self.state.document.note_explicit_target(\\n foot_bibliography, foot_bibliography\\n )\\n return [foot_bibliography]\",\n \"def formula_list_html(header, model, tables_html):\\n page = 'ms1_test_files'\\n #epa template header\\n html = render_to_string('01epa_drupal_header.html', {\\n 'SITE_SKIN': os.environ['SITE_SKIN'],\\n 'TITLE': u\\\"\\\\u00FCbertool\\\"\\n })\\n html += render_to_string('02epa_drupal_header_bluestripe_onesidebar.html', {})\\n html += render_to_string('epa_drupal_section_title_nta.html', {})\\n\\n #main body\\n html += render_to_string('06ubertext_start_index_drupal.html', {\\n 'TITLE': header + ' References',\\n 'TEXT_PARAGRAPH': tables_html\\n })\\n html += render_to_string('07ubertext_end_drupal.html', {})\\n html += links_left.ordered_list(model, page)\\n\\n #css and scripts\\n html += render_to_string('09epa_drupal_pram_css.html', {})\\n html += render_to_string('09epa_drupal_pram_scripts.html', {})\\n #html += render_to_string('09epa_drupal_pram_scripts.html', {})\\n\\n #epa template footer\\n html += render_to_string('10epa_drupal_footer.html', {})\\n return html\",\n \"def composeWorkplaceOntology():\\n\\n import ossPyFuncs \\n import pandas as pd\\n \\n #mysql query to extract full table from government organizations\\n #certian table columns feature capital letters which cases uproblems\\n postgreSql_selectQuery=\\\"SELECT * FROM us_gov_manual.us_govman_2019 ;\\\"\\n #pass querry and obtain table\\n govTable=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\\n\\n #mysql query to obtain academic instutions\\n postgreSql_selectQuery=\\\"SELECT institution FROM hipolabs.universities ;\\\"\\n #pass querry and obtain table\\n univTable=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\\n \\n postgreSql_selectQuery=\\\"SELECT company FROM forbes.fortune2018_us1000;\\\"\\n businesses1=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\\n \\n postgreSql_selectQuery=\\\"SELECT company FROM forbes.fortune2019_us1000;\\\"\\n businesses2=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\\n \\n postgreSql_selectQuery=\\\"SELECT company FROM forbes.fortune2020_global2000;\\\"\\n businesses3=ossPyFuncs.queryToPDTable(postgreSql_selectQuery)\\n\\n #combine theinsitutions into a vector\\n combinedSeries=[govTable['AgencyName'],univTable['institution'],businesses1['company'],businesses2['company'],businesses3['company']]\\n #turn the multi item vector into a single series\\n fullWordbank=pd.concat(combinedSeries)\\n #turn that series into a pd dataframe\\n wordbankTable=pd.DataFrame(fullWordbank.unique())\\n\\n return wordbankTable\",\n \"def make_table_declarations(ibs):\\n # available tables\\n TABLENAME_LIST = [\\n IMAGE_TABLE,\\n ANNOTATION_TABLE,\\n # NAME_TABLE,\\n IMAGESET_TABLE,\\n IMAGE_GRID,\\n THUMB_TABLE,\\n NAMES_TREE,\\n ]\\n\\n # table nice names\\n TABLE_NICE = {\\n IMAGE_TABLE: 'Image Table',\\n ANNOTATION_TABLE: 'Annotations Table',\\n NAME_TABLE: 'Name Table',\\n QRES_TABLE: 'Query Results Table',\\n IMAGESET_TABLE: 'ImageSet Table',\\n IMAGE_GRID: 'Thumbnail Grid',\\n THUMB_TABLE: 'Thumbnail Table',\\n NAMES_TREE: 'Tree of Names',\\n }\\n\\n # COLUMN DEFINITIONS\\n # the columns each wbia table has,\\n TABLE_COLNAMES = {\\n IMAGE_TABLE: [\\n 'gid',\\n 'thumb',\\n # 'nAids',\\n 'img_gname',\\n # 'ext',\\n 'reviewed', # detection reviewed flag is not fullyused\\n 'datetime',\\n 'gps',\\n 'orientation',\\n 'party_tag',\\n 'contributor_tag',\\n # 'gdconf',\\n 'imgnotes',\\n 'image_uuid',\\n ],\\n # debug with\\n # --noannottbl\\n # --nonametree\\n # even just aid seems to be very slow\\n ANNOTATION_TABLE: [\\n # 'annotation_uuid',\\n 'aid',\\n 'thumb',\\n 'annot_gname',\\n 'name',\\n 'exemplar',\\n 'species', # <put back in\\n 'viewpoint',\\n 'quality_text',\\n 'age_min',\\n 'age_max',\\n 'sex_text',\\n # 'rdconf',\\n # 'nGt', # ## <put back in\\n 'imagesettext_names',\\n 'annotnotes', # ## <put back in\\n 'tag_text', # < Hack should have actual tag structure\\n # 'annot_visual_uuid',\\n # 'nFeats',\\n # 'bbox',\\n # 'theta',\\n # 'verts',\\n # 'num_verts',\\n ],\\n NAME_TABLE: ['nid', 'name', 'nAids', 'namenotes'],\\n QRES_TABLE: ['rank', 'score', 'name', 'aid'],\\n IMAGESET_TABLE: [\\n 'imagesettext',\\n 'nImgs',\\n # 'num_imgs_reviewed',\\n # 'num_annotmatch_reviewed',\\n # 'imageset_end_datetime',\\n # 'imageset_processed_flag',\\n # 'imageset_shipped_flag',\\n 'imgsetid',\\n ],\\n NAMES_TREE: [\\n 'name',\\n 'nAids',\\n 'thumb',\\n 'nid',\\n # 'exemplar',\\n # 'nExAids',\\n 'aid',\\n # 'annot_gname',\\n # 'quality_text',\\n # 'age_min',\\n # 'age_max',\\n # 'sex_text',\\n # 'imagesettext_names',\\n # 'datetime',\\n # 'max_hourdiff',\\n # 'max_speed',\\n # 'has_split',\\n # 'namenotes',\\n ],\\n IMAGE_GRID: ['thumb'],\\n # TEST TABLE\\n THUMB_TABLE: ['img_gname', 'thumb'],\\n }\\n\\n # dynamicly defined headers\\n if not const.SIMPLIFY_INTERFACE:\\n from wbia.control import accessor_decors\\n\\n if accessor_decors.API_CACHE:\\n # Too slow without api cache\\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\\n ['percent_annotmatch_reviewed_str', 'percent_names_with_exemplar_str']\\n )\\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\\n [\\n # 'percent_imgs_reviewed_str',\\n 'imageset_start_datetime',\\n # 'imageset_end_datetime',\\n 'imageset_duration',\\n 'imageset_notes',\\n ]\\n )\\n\\n if ibs.cfg.other_cfg.show_shipped_imagesets:\\n TABLE_COLNAMES[IMAGESET_TABLE].extend(\\n ['imageset_processed_flag', 'imageset_shipped_flag']\\n )\\n\\n # THUMB_TABLE : ['thumb' 'thumb' 'thumb' 'thumb'],\\n # NAMES_TREE : {('name' 'nid' 'nAids') : ['aid' 'bbox' 'thumb']}\\n\\n TABLE_TREE_LEVELS = {\\n NAMES_TREE: {\\n 'name': 0,\\n 'namenotes': 0,\\n 'nid': 0,\\n 'nAids': 0,\\n 'nExAids': 0,\\n 'sex_text': 0,\\n 'exemplar': 1,\\n 'thumb': 1,\\n 'viewpoint': 1,\\n 'quality_text': 1,\\n 'age_min': 1,\\n 'age_max': 1,\\n 'imagesettext_names': 1,\\n 'aid': 1,\\n 'annot_gname': 1,\\n 'datetime': 1,\\n 'max_hourdiff': 0,\\n 'max_speed': 0,\\n 'has_split': 0,\\n },\\n }\\n\\n # the columns which are editable\\n TABLE_EDITSET = {\\n IMAGE_TABLE: {'reviewed', 'imgnotes', 'gps'},\\n ANNOTATION_TABLE: {\\n 'name',\\n 'species',\\n 'annotnotes',\\n 'exemplar',\\n 'viewpoint',\\n 'quality_text',\\n 'age_min',\\n 'age_max',\\n 'sex_text',\\n 'tag_text',\\n },\\n NAME_TABLE: {'name', 'namenotes'},\\n QRES_TABLE: {'name'},\\n IMAGESET_TABLE: {\\n 'imagesettext',\\n 'imageset_shipped_flag',\\n 'imageset_processed_flag',\\n },\\n IMAGE_GRID: set(),\\n THUMB_TABLE: set(),\\n NAMES_TREE: {\\n 'exemplar',\\n 'name',\\n 'namenotes',\\n 'viewpoint',\\n 'quality_text',\\n 'age_min',\\n 'age_max',\\n 'sex_text',\\n },\\n }\\n\\n if const.SIMPLIFY_INTERFACE:\\n TABLE_EDITSET[NAMES_TREE].remove('name')\\n\\n TABLE_HIDDEN_LIST = {\\n # IMAGE_TABLE : [False, True, False, False, False, True, False, False, False, False, False],\\n # ANNOTATION_TABLE : [False, False, False, False, False, False, False, True, True, True, True, True, True],\\n # NAMES_TREE : [False, False, False, False, False, False],\\n # NAME_TABLE : [False, False, False, False],\\n }\\n\\n TABLE_STRIPE_LIST = {\\n IMAGE_GRID: 9,\\n }\\n\\n # Define the valid columns a table could have\\n COL_DEF = dict(\\n [\\n ('annot_visual_uuid', (str, 'Annot Visual UUID')),\\n ('image_uuid', (str, 'Image UUID')),\\n ('gid', (int, 'Image ID')),\\n ('aid', (int, 'Annotation ID')),\\n ('nid', (int, 'Name ID')),\\n ('imgsetid', (int, 'ImageSet ID')),\\n ('nAids', (int, '#Annots')),\\n ('nExAids', (int, '#Exemplars')),\\n ('nGt', (int, '#GT')),\\n ('nImgs', (int, '#Imgs')),\\n ('nFeats', (int, '#Features')),\\n ('quality_text', (str, 'Quality')),\\n ('imagesettext_names', (str, 'ImageSet Names')),\\n ('age_min', (int, 'Age (min)')),\\n ('age_max', (int, 'Age (max)')),\\n ('sex_text', (str, 'Sex')),\\n ('rank', (str, 'Rank')), # needs to be a string for !Query\\n ('unixtime', (float, 'unixtime')),\\n ('species', (str, 'Species')),\\n ('viewpoint', (str, 'Viewpoint')),\\n ('img_gname', (str, 'Image Name')),\\n ('annot_gname', (str, 'Source Image')),\\n ('gdconf', (str, 'Detection Confidence')),\\n ('rdconf', (float, 'Detection Confidence')),\\n ('name', (str, 'Name')),\\n ('annotnotes', (str, 'Annot Notes')),\\n ('namenotes', (str, 'Name Notes')),\\n ('imgnotes', (str, 'Image Notes')),\\n ('match_name', (str, 'Matching Name')),\\n ('bbox', (str, 'BBOX (x, y, w, h))')), # Non editables are safe as strs\\n ('num_verts', (int, 'NumVerts')),\\n ('verts', (str, 'Verts')),\\n ('score', (str, 'Confidence')),\\n ('theta', (str, 'Theta')),\\n ('reviewed', (bool, 'Detection Reviewed')),\\n ('exemplar', (bool, 'Is Exemplar')),\\n ('imagesettext', (str, 'ImageSet')),\\n ('datetime', (str, 'Date / Time')),\\n ('ext', (str, 'EXT')),\\n ('thumb', ('PIXMAP', 'Thumb')),\\n ('gps', (str, 'GPS')),\\n ('orientation', (str, 'Orientation')),\\n ('imageset_processed_flag', (bool, 'Processed')),\\n ('imageset_shipped_flag', (bool, 'Commited')),\\n ('imageset_start_datetime', (str, 'Start Time')),\\n ('imageset_end_datetime', (str, 'End Time')),\\n ('imageset_duration', (str, 'Duration')),\\n ('imageset_notes', (str, 'Notes')),\\n ('party_tag', (str, 'Party')),\\n ('contributor_tag', (str, 'Contributor')),\\n ('percent_imgs_reviewed_str', (str, '%Imgs Reviewed')),\\n ('percent_annotmatch_reviewed_str', (str, '%Queried')),\\n ('num_imgs_reviewed', (str, '#Imgs Reviewed')),\\n ('num_annotmatch_reviewed', (str, '#Matches Reviewed')),\\n ('percent_names_with_exemplar_str', (str, '%Names with Exemplar')),\\n ('max_speed', (float, 'Max Speed km/h')),\\n ('has_split', (float, 'Needs Split')),\\n ('max_hourdiff', (float, 'Max Hour Diff')),\\n ('tag_text', (str, 'Tags')),\\n ]\\n )\\n\\n declare_tup = (\\n TABLENAME_LIST,\\n TABLE_NICE,\\n TABLE_COLNAMES,\\n TABLE_TREE_LEVELS,\\n TABLE_EDITSET,\\n TABLE_HIDDEN_LIST,\\n TABLE_STRIPE_LIST,\\n COL_DEF,\\n )\\n return declare_tup\",\n \"def make_crossref_metadata(dataset: ObservatoryDataset) -> List[Dict]:\\n\\n records = []\\n\\n for paper in dataset.papers:\\n # Create funders\\n funders = []\\n for funder in paper.funders:\\n funders.append({\\\"name\\\": funder.name, \\\"DOI\\\": funder.doi, \\\"award\\\": None, \\\"doi_asserted_by\\\": None})\\n\\n # Add Crossref record\\n records.append(\\n {\\n \\\"type\\\": paper.type,\\n \\\"title\\\": [paper.title],\\n \\\"DOI\\\": paper.doi,\\n \\\"is_referenced_by_count\\\": len(paper.cited_by),\\n \\\"issued\\\": {\\n \\\"date_parts\\\": [paper.published_date.year, paper.published_date.month, paper.published_date.day]\\n },\\n \\\"funder\\\": funders,\\n \\\"publisher\\\": paper.publisher.name,\\n }\\n )\\n\\n return records\",\n \"def write_the_table(what):\\n global count_row\\n count_row += 1\\n\\n if what.get('rank') == 0:\\n background_blue.append(count_row)\\n\\n struct = what.get('structure')\\n link = what.get('link')\\n exams_1 = what.get('exams_1')\\n exams_2 = what.get('exams_2')\\n exams_empty = [['', '', '', '', '', '', '', '', '', '', '', '']] \\\\\\n if self.training.session_type != '1' else \\\\\\n [['', '', '', '', '', '']]\\n\\n def formated(number):\\n \\\"\\\"\\\"\\n Remove trailing 0\\n \\\"\\\"\\\"\\n frac, whole = modf(number)\\n if frac == 0:\\n return int(whole)\\n return str(number).rstrip('0')\\n\\n def write_exams(list_1, list_2):\\n exam_table = []\\n for ex_1, ex_2 in itertools.zip_longest(list_1, list_2):\\n ex_1_table = [\\n formated(ex_1.coefficient) if ex_1 is not None else '',\\n [\\n Paragraph(filter_content(ex_1.label) if ex_1 else '',\\n self.styles['SmallNormal']),\\n Paragraph(\\n \\\"<para textColor=grey>\\\" + filter_content(ex_1.additionnal_info) \\\\\\n if ex_1 and ex_1.additionnal_info \\\\\\n else \\\"\\\" + \\\"</para\\\\>\\\",\\n self.styles['SmallNormal'])\\n ],\\n ex_1.type_exam if ex_1 is not None else '',\\n ex_1.text_duration if ex_1 is not None else '',\\n '' if ex_1 is None \\\\\\n else ex_1.convocation if not training_is_ccct \\\\\\n else ex_1.get_type_ccct_display(),\\n ex_1.eliminatory_grade if ex_1 is not None else '',\\n ex_1.threshold_session_2 if ex_1 is not None else '',\\n ]\\n\\n ex_2_table = [\\n formated(ex_2.coefficient) if ex_2 is not None else '',\\n [Paragraph(filter_content(ex_2.label) if ex_2 is not None else '', self.styles[\\n 'SmallNormal']), Paragraph(\\\"<para textColor=grey\\\\\\n >\\\" + ex_2.additionnal_info + \\\"</para\\\\\\n >\\\" if ex_2.additionnal_info is not None else \\\"\\\",\\n self.styles['SmallNormal'])],\\n ex_2.type_exam if ex_2 is not None else '',\\n ex_2.text_duration if ex_2 is not None else '',\\n ex_2.eliminatory_grade if ex_2 is not None else '',\\n ] if ex_2 is not None else ['', '', '', '', '']\\n if self.training.session_type != '1':\\n ex_1_table.extend(ex_2_table)\\n else:\\n ex_1_table.pop()\\n exam_table.append(ex_1_table)\\n exam_table = exam_table if len(exam_table) > 0 else exams_empty\\n if exam_table == exams_empty:\\n # TODO: calculate empty space to set rowHeights in order to\\n # avoid blank in table\\n pass\\n inner_table = Table(\\n exam_table, colWidths=width_exams, rowHeights=None)\\n inner_table.setStyle(TableStyle(\\n [('INNERGRID', (0, 0), (-1, -1), 0.1, colors.black),\\n ('VALIGN', (0, 0), (-1, -1), 'MIDDLE'),\\n ('ALIGN', (0, 0), (-1, -1), 'CENTER'),\\n ('FONTSIZE', (0, 0), (-1, -1), 8),\\n # ('LEFTPADDING', (0, 0), (-1, -1), 0),\\n # ('RIGHTPADDING', (0, 0), (-1, -1), 0),\\n ('BOTTOMPADDING', (0, 0), (-1, -1), 0),\\n ('TOPPADDING', (0, 0), (-1, -1), 0),\\n ]))\\n return inner_table\\n\\n ref_scol = struct.ref_si_scol if struct.ref_si_scol else \\\"\\\" # FIX bug with rof data\\n ref_data = (\\n Paragraph(struct.ROF_ref, self.styles['CenterSmall']),\\n Paragraph(ref_scol, self.styles['CenterSmall'])\\n ) if self.reference == 'both' \\\\\\n else Paragraph(struct.ROF_ref, self.styles['CenterSmall']) if self.reference == 'with_rof' \\\\\\n else Paragraph(ref_scol, self.styles['CenterSmall']) if self.reference == 'with_si' \\\\\\n else Paragraph('', self.styles['CenterSmall'])\\n\\n object_line = [\\n Paragraph(\\n \\\"<para leftIndent=%s>%s</para> \\\" % (what.get('rank')*10, filter_content(struct.label)),\\n self.styles['SmallBold'] if what.get('rank') == 0 \\\\\\n or what.get('structure').nature == 'UE' \\\\\\n else self.styles['SmallNormal']\\n ),\\n Paragraph(\\n struct.get_respens_name if not struct.external_name \\\\\\n else struct.external_name,\\n self.styles['CenterSmall'] if not struct.external_name else \\\\\\n self.styles['CenterSmallItalic']\\n ),\\n [ref_data],\\n '30' if self.training.degree_type.ROF_code in self.training_types_for_which_to_display_30_ects\\\\\\n and struct.nature == 'SE'\\\\\\n else struct.ECTS_credit if struct.ECTS_credit else '-',\\n formated(link.coefficient) if link.coefficient else '',\\n link.eliminatory_grade,\\n write_exams(exams_1, exams_2)\\n ]\\n if self.respforms:\\n if self.reference == 'without':\\n object_line.pop(2)\\n else:\\n object_line.pop(1)\\n if self.reference == 'without':\\n object_line.pop(1)\\n\\n big_table.append(object_line)\\n\\n for e in what.get('children'):\\n write_the_table(e)\",\n \"def ref_analyzer(citation_informations, initialresult, initial_citationlist,\\n initial_referencelist,config, updated_rec_list ):\\n function = \\\"\\\"\\n try:\\n function = config.get(\\\"rank_method\\\", \\\"function\\\")\\n except:\\n register_exception(prefix=\\\"cfg section [rank_method] has no attr function\\\", alert_admin=True)\\n return {}\\n\\n pubrefntag = \\\"\\\"\\n try:\\n pubrefntag = config.get(function, \\\"reference_via_report_number\\\")\\n except:\\n register_exception(prefix=\\\"cfg section \\\"+function+\\\" has no attr reference_via_report_number\\\", alert_admin=True)\\n return {}\\n\\n pubreftag = \\\"\\\"\\n try:\\n pubreftag = config.get(function, \\\"reference_via_pubinfo\\\")\\n except:\\n register_exception(prefix=\\\"cfg section \\\"+function+\\\" has no attr reference_via_pubinfo\\\", alert_admin=True)\\n return {}\\n\\n #pubrefntag is often 999C5r, pubreftag 999C5s\\n if task_get_task_param('verbose') >= 9:\\n write_message(\\\"pubrefntag \\\"+pubrefntag)\\n write_message(\\\"pubreftag \\\"+pubreftag)\\n\\n citation_list = initial_citationlist\\n reference_list = initial_referencelist\\n result = initialresult\\n d_reports_numbers = citation_informations[0] #dict of recid -> institute_give_publ_id\\n d_references_report_numbers = citation_informations[1] #dict of recid -> ['astro-ph/xyz'..]\\n d_references_s = citation_informations[2]\\n #dict of recid -> publication_infos_in_its_bibliography\\n d_records_s = citation_informations[3] #recid -> its publication inf\\n t1 = os.times()[4]\\n\\n write_message(\\\"Phase 0: temporarily remove changed records from citation dictionaries; they will be filled later\\\")\\n for somerecid in updated_rec_list:\\n try:\\n del citation_list[somerecid]\\n except KeyError:\\n pass\\n try:\\n del reference_list[somerecid]\\n except KeyError:\\n pass\\n\\n write_message(\\\"Phase 1: d_references_report_numbers\\\")\\n #d_references_report_numbers: e.g 8 -> ([astro-ph/9889],[hep-ph/768])\\n #meaning: rec 8 contains these in bibliography\\n\\n done = 0\\n numrecs = len(d_references_report_numbers)\\n for thisrecid, refnumbers in d_references_report_numbers.iteritems():\\n if (done % 1000 == 0):\\n mesg = \\\"d_references_report_numbers done \\\"+str(done)+\\\" of \\\"+str(numrecs)\\n write_message(mesg)\\n task_update_progress(mesg)\\n task_sleep_now_if_required()\\n done = done+1\\n\\n for refnumber in refnumbers:\\n if refnumber:\\n p = refnumber\\n f = 'reportnumber'\\n #sanitise p\\n p.replace(\\\"\\\\n\\\",'')\\n #search for \\\"hep-th/5644654 or such\\\" in existing records\\n rec_ids = get_recids_matching_query(p, f)\\n\\n if len(rec_ids) > 1:\\n msg = \\\"Whoops: record '%d' report number value '%s' \\\" \\\\\\n \\\"matches many records; taking only the first one. %s\\\" % \\\\\\n (thisrecid, p, repr(rec_ids))\\n write_message(msg, stream=sys.stderr)\\n try:\\n raise ValueError(msg)\\n except ValueError:\\n register_exception(alert_admin=True)\\n\\n if rec_ids and rec_ids[0]:\\n write_citer_cited(thisrecid, rec_ids[0])\\n remove_from_missing(p)\\n if not result.has_key(rec_ids[0]):\\n result[rec_ids[0]] = 0\\n # Citation list should have rec_ids[0] but check anyway\\n if not citation_list.has_key(rec_ids[0]):\\n citation_list[rec_ids[0]] = []\\n #append unless this key already has the item\\n if not thisrecid in citation_list[rec_ids[0]]:\\n citation_list[rec_ids[0]].append(thisrecid)\\n #and update result\\n result[rec_ids[0]] += 1\\n\\n if not reference_list.has_key(thisrecid):\\n reference_list[thisrecid] = []\\n if not rec_ids[0] in reference_list[thisrecid]:\\n reference_list[thisrecid].append(rec_ids[0])\\n else:\\n #the reference we wanted was not found among our records.\\n #put the reference in the \\\"missing\\\".. however, it will look\\n #bad.. gfhgf/1254312, so get the corresponding 999C5s (full ref) too\\n #This should really be done in the next loop d_references_s\\n #but the 999C5s fields are not yet normalized\\n\\n #rectext = print_record(thisrecid, format='hm', ot=pubreftag[:-1])\\n rectext = \\\"\\\" # print_record() call disabled to speed things up\\n lines = rectext.split(\\\"\\\\n\\\")\\n rpart = p #to be used..\\n for l in lines:\\n if (l.find(p) > 0): #the gfhgf/1254312 was found.. get the s-part of it\\n st = l.find('$s')\\n if (st > 0):\\n end = l.find('$', st)\\n if (end == st):\\n end = len(l)\\n rpart = l[st+2:end]\\n insert_into_missing(thisrecid, rpart)\\n\\n mesg = \\\"d_references_report_numbers done fully\\\"\\n write_message(mesg)\\n task_update_progress(mesg)\\n\\n t2 = os.times()[4]\\n\\n #try to find references based on 999C5s, like Phys.Rev.Lett. 53 (1986) 2285\\n write_message(\\\"Phase 2: d_references_s\\\")\\n done = 0\\n numrecs = len(d_references_s)\\n for thisrecid, refss in d_references_s.iteritems():\\n if (done % 1000 == 0):\\n mesg = \\\"d_references_s done \\\"+str(done)+\\\" of \\\"+str(numrecs)\\n write_message(mesg)\\n task_update_progress(mesg)\\n task_sleep_now_if_required()\\n\\n done = done+1\\n\\n for refs in refss:\\n if refs:\\n p = refs\\n #remove the latter page number if it is like 67-74\\n matches = re.compile(\\\"(.*)(-\\\\d+$)\\\").findall(p)\\n if matches and matches[0]:\\n p = matches[0][0]\\n\\n # check reference value to see whether it is well formed:\\n if not re_CFG_JOURNAL_PUBINFO_STANDARD_FORM_REGEXP_CHECK.match(p):\\n msg = \\\"Whoops, record '%d' reference value '%s' \\\" \\\\\\n \\\"is not well formed; skipping it.\\\" % (thisrecid, p)\\n write_message(msg, stream=sys.stderr)\\n try:\\n raise ValueError(msg)\\n except ValueError:\\n register_exception(alert_admin=True)\\n continue # skip this ill-formed value\\n\\n # look for reference value:\\n rec_id = None\\n try:\\n rec_ids = list(search_unit(p, 'journal') - INTBITSET_OF_DELETED_RECORDS)\\n except:\\n rec_ids = None\\n if len(rec_ids) > 1:\\n msg = \\\"Whoops, record '%d' reference value '%s' \\\" \\\\\\n \\\"matches many records; taking only the first one. %s\\\" % \\\\\\n (thisrecid, p, repr(rec_ids))\\n write_message(msg, stream=sys.stderr)\\n try:\\n raise ValueError(msg)\\n except ValueError:\\n register_exception(alert_admin=True)\\n\\n if rec_ids and rec_ids[0]:\\n write_message(\\\"These match searching \\\"+p+\\\" in journal: \\\"+repr(rec_ids), verbose=9)\\n #the refered publication is in our collection, remove\\n #from missing\\n remove_from_missing(p)\\n else:\\n #it was not found so add in missing\\n insert_into_missing(thisrecid, p)\\n #check citation and reference for this..\\n if rec_ids and rec_ids[0]:\\n #the above should always hold\\n if not result.has_key(rec_ids[0]):\\n result[rec_ids[0]] = 0\\n if not citation_list.has_key(rec_ids[0]):\\n citation_list[rec_ids[0]] = []\\n if not thisrecid in citation_list[rec_ids[0]]:\\n citation_list[rec_ids[0]].append(thisrecid) #append actual list\\n result[rec_ids[0]] += 1 #add count for this..\\n\\n #update reference_list accordingly\\n if not reference_list.has_key(thisrecid):\\n reference_list[thisrecid] = []\\n if not rec_ids[0] in reference_list[thisrecid]:\\n reference_list[thisrecid].append(rec_ids[0])\\n mesg = \\\"d_references_s done fully\\\"\\n write_message(mesg)\\n task_update_progress(mesg)\\n\\n t3 = os.times()[4]\\n done = 0\\n numrecs = len(d_reports_numbers)\\n write_message(\\\"Phase 3: d_reports_numbers\\\")\\n\\n #search for stuff like CERN-TH-4859/87 in list of refs\\n for thisrecid, reportcodes in d_reports_numbers.iteritems():\\n if (done % 1000 == 0):\\n mesg = \\\"d_report_numbers done \\\"+str(done)+\\\" of \\\"+str(numrecs)\\n write_message(mesg)\\n task_update_progress(mesg)\\n done = done+1\\n\\n for reportcode in reportcodes:\\n if reportcode:\\n rec_ids = []\\n try:\\n rec_ids = get_recids_matching_query(reportcode, pubrefntag)\\n except:\\n rec_ids = []\\n\\n if rec_ids:\\n for recid in rec_ids:\\n #normal checks..\\n if not citation_list.has_key(thisrecid):\\n citation_list[thisrecid] = []\\n if not reference_list.has_key(recid):\\n reference_list[recid] = []\\n if not result.has_key(thisrecid):\\n result[thisrecid] = 0\\n\\n #normal updates\\n if not recid in citation_list[thisrecid]:\\n result[thisrecid] += 1\\n citation_list[thisrecid].append(recid)\\n if not thisrecid in reference_list[recid]:\\n reference_list[recid].append(thisrecid)\\n\\n mesg = \\\"d_report_numbers done fully\\\"\\n write_message(mesg)\\n task_update_progress(mesg)\\n\\n #find this record's pubinfo in other records' bibliography\\n write_message(\\\"Phase 4: d_records_s\\\")\\n done = 0\\n numrecs = len(d_records_s)\\n t4 = os.times()[4]\\n for thisrecid, recs in d_records_s.iteritems():\\n if (done % 1000 == 0):\\n mesg = \\\"d_records_s done \\\"+str(done)+\\\" of \\\"+str(numrecs)\\n write_message(mesg)\\n task_update_progress(mesg)\\n done = done+1\\n p = recs.replace(\\\"\\\\\\\"\\\",\\\"\\\")\\n #search the publication string like Phys. Lett., B 482 (2000) 417 in 999C5s\\n rec_ids = list(search_unit(f=pubreftag, p=p, m='a') - INTBITSET_OF_DELETED_RECORDS)\\n write_message(\\\"These records match \\\"+p+\\\" in \\\"+pubreftag+\\\" : \\\"+str(rec_ids), verbose=9)\\n if rec_ids:\\n for rec_id in rec_ids:\\n #normal checks\\n if not result.has_key(thisrecid):\\n result[thisrecid] = 0\\n if not citation_list.has_key(thisrecid):\\n citation_list[thisrecid] = []\\n if not reference_list.has_key(rec_id):\\n reference_list[rec_id] = []\\n\\n if not rec_id in citation_list[thisrecid]:\\n result[thisrecid] += 1\\n citation_list[thisrecid].append(rec_id)\\n if not thisrecid in reference_list[rec_id]:\\n reference_list[rec_id].append(thisrecid)\\n\\n mesg = \\\"d_records_s done fully\\\"\\n write_message(mesg)\\n task_update_progress(mesg)\\n\\n write_message(\\\"Phase 5: reverse lists\\\")\\n\\n #remove empty lists in citation and reference\\n keys = citation_list.keys()\\n for k in keys:\\n if not citation_list[k]:\\n del citation_list[k]\\n\\n keys = reference_list.keys()\\n for k in keys:\\n if not reference_list[k]:\\n del reference_list[k]\\n\\n write_message(\\\"Phase 6: self-citations\\\")\\n selfdic = {}\\n #get the initial self citation dict\\n initial_self_dict = get_cit_dict(\\\"selfcitdict\\\")\\n selfdic = initial_self_dict\\n #add new records to selfdic\\n acit = task_get_option(\\\"author-citations\\\")\\n if not acit:\\n write_message(\\\"Self cite processing disabled. Use -A option to enable it.\\\")\\n else:\\n write_message(\\\"self cite and author citations enabled\\\")\\n selfdic = get_self_citations(updated_rec_list, citation_list,\\n initial_self_dict, config)\\n #selfdic consists of\\n #key k -> list of values [v1,v2,..]\\n #where k is a record with author A and k cites v1,v2.. and A appears in v1,v2..\\n\\n #create a reverse \\\"x cited by y\\\" self cit dict\\n selfcitedbydic = {}\\n for k in selfdic.keys():\\n vlist = selfdic[k]\\n for v in vlist:\\n if selfcitedbydic.has_key(v):\\n tmplist = selfcitedbydic[v]\\n if not k in tmplist:\\n tmplist.append(k)\\n else:\\n tmplist = [k]\\n selfcitedbydic[v] = tmplist\\n\\n write_message(\\\"Getting author citations\\\")\\n\\n #get author citations for records in updated_rec_list\\n initial_author_dict = get_initial_author_dict()\\n authorcitdic = initial_author_dict\\n acit = task_get_option(\\\"author-citations\\\")\\n if not acit:\\n print \\\"Author cites disabled. Use -A option to enable it.\\\"\\n else:\\n write_message(\\\"author citations enabled\\\")\\n authorcitdic = get_author_citations(updated_rec_list, citation_list,\\n initial_author_dict, config)\\n\\n\\n if task_get_task_param('verbose') >= 3:\\n #print only X first to prevent flood\\n tmpdict = {}\\n tmp = citation_list.keys()[0:10]\\n for t in tmp:\\n tmpdict[t] = citation_list[t]\\n write_message(\\\"citation_list (x is cited by y): \\\"+str(tmpdict))\\n write_message(\\\"size: \\\"+str(len(citation_list.keys())))\\n tmp = reference_list.keys()[0:10]\\n tmpdict = {}\\n for t in tmp:\\n tmpdict[t] = reference_list[t]\\n write_message(\\\"reference_list (x cites y): \\\"+str(tmpdict))\\n write_message(\\\"size: \\\"+str(len(reference_list.keys())))\\n tmp = selfcitedbydic.keys()[0:10]\\n tmpdict = {}\\n for t in tmp:\\n tmpdict[t] = selfcitedbydic[t]\\n mesg = \\\"selfcitedbydic (x is cited by y and one of the authors of x same as y's):\\\"\\n mesg += str(tmpdict)\\n write_message(mesg)\\n write_message(\\\"size: \\\"+str(len(selfcitedbydic.keys())))\\n tmp = selfdic.keys()[0:100]\\n tmpdict = {}\\n for t in tmp:\\n tmpdict[t] = selfdic[t]\\n mesg = \\\"selfdic (x cites y and one of the authors of x same as y's): \\\"+str(tmpdict)\\n write_message(mesg)\\n write_message(\\\"size: \\\"+str(len(selfdic.keys())))\\n tmp = authorcitdic.keys()[0:10]\\n tmpdict = {}\\n for t in tmp:\\n tmpdict[t] = authorcitdic[t]\\n write_message(\\\"authorcitdic (author is cited in recs): \\\"+str(tmpdict))\\n write_message(\\\"size: \\\"+str(len(authorcitdic.keys())))\\n insert_cit_ref_list_intodb(citation_list, reference_list,\\n selfcitedbydic, selfdic, authorcitdic)\\n\\n t5 = os.times()[4]\\n\\n write_message(\\\"Execution time for analyzing the citation information generating the dictionary:\\\")\\n write_message(\\\"... checking ref number: %.2f sec\\\" % (t2-t1))\\n write_message(\\\"... checking ref ypvt: %.2f sec\\\" % (t3-t2))\\n write_message(\\\"... checking rec number: %.2f sec\\\" % (t4-t3))\\n write_message(\\\"... checking rec ypvt: %.2f sec\\\" % (t5-t4))\\n write_message(\\\"... total time of ref_analyze: %.2f sec\\\" % (t5-t1))\\n\\n return result\",\n \"def get_examples_table_data(technique, reference_list, next_reference_number):\\n\\n # Creating map to avoid repeating the code 3 times\\n examples_map = [\\n { 'example_type': config.tools_using_technique }, \\n { 'example_type': config.malware_using_technique },\\n { 'example_type': config.groups_using_technique }\\n ]\\n\\n example_data = []\\n\\n # Get malware or tools used by group\\n for examples in examples_map:\\n if examples['example_type'].get(technique.get('id')):\\n for example in examples['example_type'][technique['id']]:\\n\\n attack_id = util.get_attack_id(example['object'])\\n\\n # Only add example data if the attack id is found \\n if attack_id:\\n row = {}\\n\\n row['id'] = attack_id\\n\\n if attack_id.startswith('S'):\\n row['path'] = \\\"software\\\"\\n else:\\n row['path'] = \\\"groups\\\"\\n\\n row['name'] = example['object']['name']\\n\\n if example['relationship'].get('description'):\\n # Get filtered description\\n row['descr'] = util.get_filtered_description(reference_list, next_reference_number, example)\\n\\n example_data.append(row)\\n \\n if example_data:\\n example_data = sorted(example_data, key=lambda k: k['name'].lower())\\n return example_data\",\n \"def cv_list(self):\\n\\n mystr = \\\"\\\"\\n for p in self.mypapers:\\n mystr += f\\\"{p.title[0]}\\\\n\\\"\\n if len(p.author) > 12:\\n a = f\\\"{p.author[0]} et al. \\\"\\n elif len(p.author) > 2:\\n a = \\\", \\\".join(p.author[:-1]) + f\\\" & {p.author[-1]} \\\"\\n elif len(p.author) == 2:\\n a = f\\\"{p.author[0]} & {p.author[1]} \\\"\\n else:\\n a = f\\\"{p.author[0]} \\\"\\n\\n mystr += f\\\"{a}\\\"\\n mystr += f\\\"{p.year}, {p.pub}\\\"\\n if p.volume is not None:\\n mystr += f\\\", {p.volume}\\\"\\n if p.issue is not None:\\n mystr += f\\\", {p.issue}\\\"\\n if p.page is not None:\\n mystr += f\\\", {p.page[0]}\\\"\\n mystr += \\\"\\\\n\\\\n\\\"\\n return mystr\",\n \"def ref_to_link(txt):\\n text = txt.group(1) # because it was a match in a regular expression\\n\\n thecite, everythingelse = first_bracketed_string(text)\\n thecite = thecite[1:-1] # strip curly brackets\\n thecite = thecite.replace(\\\"\\\\\\\\\\\",\\\"\\\") # \\\\href --> href\\n\\n refs = thecite.split(\\\",\\\")\\n ans = \\\"\\\"\\n\\n # print \\\"refs\\\",refs\\n\\n for ref in refs:\\n ref = ref.strip() # because \\\\cite{A, B, C,D} can have spaces\\n this_link = \\\"\\\"\\n if ref.startswith(\\\"href\\\"):\\n the_link = re.sub(r\\\".*{([^}]+)}{.*\\\", r\\\"\\\\1\\\", ref)\\n click_on = re.sub(r\\\".*}{([^}]+)}\\\\s*\\\", r\\\"\\\\1\\\", ref)\\n this_link = '{{ LINK_EXT(\\\"' + click_on + '\\\",\\\"' + the_link + '\\\") | safe}}'\\n elif ref.startswith(\\\"doi\\\"):\\n ref = ref.replace(\\\":\\\",\\\"\\\") # could be doi:: or doi: or doi\\n the_doi = ref[3:] # remove the \\\"doi\\\"\\n this_link = '{{ LINK_EXT(\\\"' + the_doi + '\\\",\\\"https://doi.org/' + the_doi + '\\\")| safe }}'\\n elif ref.lower().startswith(\\\"mr\\\"):\\n ref = ref.replace(\\\":\\\",\\\"\\\")\\n the_mr = ref[2:] # remove the \\\"MR\\\"\\n this_link = '{{ LINK_EXT(\\\"' + 'MR:' + the_mr + '\\\", '\\n this_link += '\\\"http://www.ams.org/mathscinet/search/publdoc.html?pg1=MR&s1='\\n this_link += the_mr + '\\\") | safe}}'\\n elif ref.lower().startswith(\\\"arxiv\\\"):\\n ref = ref.replace(\\\":\\\",\\\"\\\")\\n the_arx = ref[5:] # remove the \\\"arXiv\\\"\\n this_link = '{{ LINK_EXT(\\\"' + 'arXiv:' + the_arx + '\\\", '\\n this_link += '\\\"http://arxiv.org/abs/'\\n this_link += the_arx + '\\\")| safe}}'\\n\\n\\n if this_link:\\n if ans:\\n ans += \\\", \\\"\\n ans += this_link\\n\\n return '[' + ans + ']' + everythingelse\",\n \"def generate_latex_table(dictionary,filename,location=\\\".\\\"):\\n if type(filename) != str:\\n raise TypeError('filename should be string')\\n if type(dictionary) != dict:\\n raise TypeError('dictionary should be dictionary')\\n\\n head_code = \\\"\\\"\\\"\\\\\\\\documentclass{article}\\n%In the preamble section include the arabtex and utf8 packages\\n\\\\\\\\usepackage{arabtex}\\n\\\\\\\\usepackage{utf8}\\n\\\\\\\\usepackage{longtable}\\n\\\\\\\\usepackage{color, colortbl}\\n\\\\\\\\usepackage{supertabular}\\n\\\\\\\\usepackage{multicol}\\n\\\\\\\\usepackage{geometry}\\n\\\\\\\\geometry{left=.1in, right=.1in, top=.1in, bottom=.1in}\\n\\n\\\\\\\\begin{document}\\n\\\\\\\\begin{multicols}{6}\\n\\\\\\\\setcode{utf8}\\n\\n\\\\\\\\begin{center}\\\"\\\"\\\"\\n\\n tail_code = \\\"\\\"\\\"\\\\\\\\end{center}\\n\\\\\\\\end{multicols}\\n\\\\\\\\end{document}\\\"\\\"\\\"\\n\\n begin_table = \\\"\\\"\\\"\\\\\\\\begin{tabular}{ P{2cm} P{1cm}}\\n\\\\\\\\textbf{words} & \\\\\\\\textbf{\\\\\\\\#} \\\\\\\\\\\\\\\\\\n\\\\\\\\hline\\n\\\\\\\\\\\\\\\\[0.01cm]\\\"\\\"\\\"\\n end_table= \\\"\\\"\\\"\\\\\\\\end{tabular}\\\"\\\"\\\"\\n rows_num = 40\\n if location != '.':\\n filename = location +\\\"/\\\"+ filename\\n\\n try:\\n file = open(filename+'.tex', 'w', encoding='utf8')\\n file.write(head_code+'\\\\n')\\n n= int(len(dictionary)/rows_num)\\n words = [(\\\"\\\\\\\\<\\\"+word+\\\"> & \\\"+str(frequancy)+' \\\\\\\\\\\\\\\\ \\\\n') for word, frequancy in dictionary.items()]\\n start=0\\n end=rows_num\\n new_words = []\\n for i in range(n):\\n new_words = new_words+ [begin_table+'\\\\n'] +words[start:end] +[end_table+\\\" \\\\n\\\"]\\n start=end\\n end+=rows_num\\n remain_words = len(dictionary) - rows_num*n\\n if remain_words > 0:\\n new_words += [begin_table+\\\" \\\\n\\\"]+ words[-1*remain_words:]+[end_table+\\\" \\\\n\\\"]\\n for word in new_words:\\n file.write(word)\\n file.write(tail_code)\\n file.close()\\n return True\\n except:\\n return False\",\n \"def write_contigs(self, refs):\\n\\n contigs_group = self.f.create_group('contigs')\\n\\n for ref_name, ref in refs:\\n contig = contigs_group.create_group(ref_name)\\n contig.attrs['name'] = ref_name\\n contig.attrs['seq'] = ref\\n contig.attrs['len'] = len(ref)\",\n \"def cpi_data():\\n\\n\\n cpi_workbook = xlrd.open_workbook(\\n 'corruption_perception_index.xlsx')\\n cpi_sheet = cpi_workbook.sheets()[0]\\n\\n\\n cpi_title_rows = zip(cpi_sheet.row_values(1), cpi_sheet.row_values(2))\\n cpi_titles = [t[0] + ' ' + t[1] for t in cpi_title_rows]\\n cpi_titles = [t.strip() for t in cpi_titles]\\n cpi_rows = [cpi_sheet.row_values(r) for r in range(3, cpi_sheet.nrows)]\\n\\n\\n cpi_types = get_types(cpi_sheet.row(3))\\n cpi_titles[0] = cpi_titles[0] + ' Duplicate'\\n cpi_table = get_table(cpi_rows, cpi_types, cpi_titles)\\n\\n return cpi_table\",\n \"def index_labtests(cnxdict, engine, labtestlist):\\n for currtbl in labtestlist:\\n currtbl = currtbl.replace(' ', '_')\\n mycnx = connect_to_mysql_db_prod('caisismysql')\\n mycnx['sql'] = \\\"\\\"\\\"\\n ALTER TABLE `caisis`.`{0}`\\n CHANGE COLUMN `LabTestId` `LabTestId` BIGINT(20) NOT NULL ,\\n ADD PRIMARY KEY (`LabTestId`);\\n ALTER TABLE `caisis`.`{0}`\\n ADD INDEX `patientid` (`PatientId` ASC);\\n ALTER TABLE `caisis`.`{0}`\\n ADD INDEX `labdate` (`LabDate` ASC);\\n ALTER TABLE `caisis`.`{0}`\\n ADD FULLTEXT INDEX `labtest` (`LabTest` ASC);\\n \\\"\\\"\\\".format(currtbl)\\n dosqlexecute(mycnx)\",\n \"def __citationsFromFile(file):\\n\\n # Tokens for parsing\\n titleToken = '#*'\\n indexToken = '#index'\\n citationToken = '#%'\\n\\n # Predicates for error checking\\n noneNone = lambda *items: all([item is not None for item in items])\\n allNone = lambda *items: all([item is None for item in items])\\n\\n # Next entry data\\n title = None\\n index = None\\n citations = []\\n\\n # Basic stats\\n withCitations = 0\\n withoutCitations = 0\\n totalPapers = 0\\n\\n for line in file:\\n line = line.strip()\\n\\n # Parse entry, enforcing that data appears in title -> index -> citations order\\n if line.startswith(titleToken):\\n assert allNone(title, index) and len(citations) == 0\\n title = line[len(titleToken):].strip('.')\\n\\n elif line.startswith(indexToken):\\n assert noneNone(title) and allNone(index) and len(citations) == 0\\n index = int(line[len(indexToken):])\\n\\n elif line.startswith(citationToken):\\n assert noneNone(title, index)\\n newCitationId = int(line[len(citationToken):])\\n assert newCitationId >= 0\\n citations.append(newCitationId)\\n\\n elif len(line) == 0:\\n totalPapers += 1\\n\\n # Yield this entry if it has any citations,\\n if noneNone(title, index):\\n if len(citations) > 0:\\n withCitations += 1\\n yield title, index, citations\\n else:\\n withoutCitations += 1\\n\\n title = None\\n index = None\\n citations = []\\n\\n # Output some basic statistics about papers with/without citations\\n withCitationsPercent = 100.0 * (float(withCitations) / totalPapers)\\n withoutCitationsPercent = 100.0 * (float(withoutCitations) / totalPapers)\\n print \\\"\\\\n\\\\nTotal Papers: %d\\\" % totalPapers\\n print \\\" With References: %d (%2.2f%%)\\\\n Without References: %d (%2.2f%%)\\\" % (\\n withCitations, withCitationsPercent, withoutCitations, withoutCitationsPercent\\n )\",\n \"def file_creator(title_list):\\n for file_name in title_list: #title names are retrieved out of genID.txt\\n with open (\\\"nuc_variant_calls/\\\"+file_name.strip()+\\\".var\\\",'w') as x:\\n x.write(\\\"Feature type\\\\tAlignment length\\\\tIdentical nucleotides\\\\tIndel count\\\\n\\\") #Table headers.\",\n \"def table_maker():\\r\\n try:\\r\\n off_copy = off.copy()\\r\\n man_copy = man.copy()\\r\\n exe_copy = exe.copy()\\r\\n ceo_copy = ceo.copy()\\r\\n list_of_lists = [off_copy, man_copy, exe_copy, ceo_copy]\\r\\n\\r\\n for i in list_of_lists:\\r\\n for j in i:\\r\\n if type(j) == str:\\r\\n continue\\r\\n else:\\r\\n raise ValueError('All elements must be strings')\\r\\n\\r\\n row_num = max(len(off_copy), len(man_copy),\\r\\n len(exe_copy), len(ceo_copy))\\r\\n for i in list_of_lists:\\r\\n if len(i) != row_num:\\r\\n diff = row_num - len(i)\\r\\n for j in range(diff):\\r\\n i.append('')\\r\\n\\r\\n t = PrettyTable(\\r\\n ['Office Workers', 'Managers', 'Executives', 'CEO'])\\r\\n for i in range(row_num):\\r\\n t.add_row([off_copy[i], man_copy[i], exe_copy[i], ceo_copy[i]])\\r\\n\\r\\n with open('Employee Table.txt', 'w') as f:\\r\\n f.write(str(t))\\r\\n\\r\\n except FileNotFoundError:\\r\\n print(\\\"Error: No file entered\\\")\",\n \"def create_tables():\\n inf(\\\"Creating tables\\\")\\n \\n pinners = Table('pinners', metadata,\\n Column('pinner_id', Integer, primary_key=True),\\n Column('name', String(40)),\\n Column('email', String(40))\\n )\\n pinners.create()\\n \\n contents = Table('contents', metadata,\\n Column('content_id', Integer, primary_key=True),\\n Column('url', String(80)),\\n Column('display_status', String(20)), # good, objectionable, copyright\\n Column('pinner_id', Integer, ForeignKey('pinners.pinner_id'))\\n )\\n contents.create()\\n\\n reviewers = Table('reviewers', metadata,\\n Column('reviewer_id', Integer, primary_key=True),\\n Column('name', String(40)),\\n Column('email', String(40))\\n )\\n reviewers.create()\\n\\n complaints = Table('complaints', metadata,\\n Column('complaint_id', Integer, primary_key=True),\\n Column('complaint_timestamp', DateTime), # when the complaint was filed\\n Column('complaint_type', String(80)), # objectionable, copyright\\n Column('process_status', String(20)), # complaint, review, done\\n Column('display_status', String(20)), # good, objectionable, copyright\\n Column('review_timestamp', DateTime), # when the compliant was resolved\\n Column('pinner_id', Integer, ForeignKey('pinners.pinner_id')),\\n Column('reviewer_id', Integer, ForeignKey('reviewers.reviewer_id')),\\n Column('content_id', Integer, ForeignKey('contents.content_id'))\\n )\\n complaints.create()\\n \\n # could create a table of \\\"near by\\\" images and/or near by features and \\n # include these in the review\",\n \"def tables(args):\\n\\n config_file = args.setupfn\\n conf_base = os.path.basename(config_file).split('.')[0]\\n statfile = os.path.join(args.outputdir,\\n \\\"{}_radvel.stat\\\".format(conf_base))\\n status = load_status(statfile)\\n\\n assert status.getboolean('mcmc', 'run'), \\\\\\n \\\"Must run MCMC before making tables\\\"\\n\\n P, post = radvel.utils.initialize_posterior(config_file)\\n post = radvel.posterior.load(status.get('fit', 'postfile'))\\n chains = pd.read_csv(status.get('mcmc', 'chainfile'))\\n minafactor = status.get('mcmc', 'minafactor')\\n maxarchange = status.get('mcmc', 'maxarchange')\\n maxgr = status.get('mcmc', 'maxgr')\\n mintz = status.get('mcmc', 'mintz')\\n if 'derive' in status.sections() and status.getboolean('derive', 'run'):\\n dchains = pd.read_csv(status.get('derive', 'chainfile'))\\n chains = chains.join(dchains, rsuffix='_derived')\\n derived = True\\n else:\\n derived = False\\n report = radvel.report.RadvelReport(P, post, chains, minafactor, maxarchange, maxgr, mintz, derived=derived)\\n tabletex = radvel.report.TexTable(report)\\n attrdict = {'priors': 'tab_prior_summary', 'rv': 'tab_rv',\\n 'params': 'tab_params', 'derived': 'tab_derived',\\n 'crit': 'tab_crit'}\\n for tabtype in args.type:\\n print(\\\"Generating LaTeX code for {} table\\\".format(tabtype))\\n\\n if tabtype == 'ic_compare':\\n assert status.has_option('ic_compare', 'ic'), \\\\\\n \\\"Must run Information Criteria comparison before making comparison tables\\\"\\n\\n compstats = eval(status.get('ic_compare', 'ic'))\\n report = radvel.report.RadvelReport(\\n P, post, chains, minafactor, maxarchange, maxgr, mintz, compstats=compstats\\n )\\n tabletex = radvel.report.TexTable(report)\\n tex = tabletex.tab_comparison()\\n elif tabtype == 'rv':\\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title, max_lines=None)\\n elif tabtype == 'crit':\\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title)\\n else:\\n if tabtype == 'derived':\\n assert status.has_option('derive', 'run'), \\\\\\n \\\"Must run `radvel derive` before making derived parameter table\\\"\\n assert tabtype in attrdict, 'Invalid Table Type %s ' % tabtype\\n tex = getattr(tabletex, attrdict[tabtype])(name_in_title=args.name_in_title)\\n\\n saveto = os.path.join(\\n args.outputdir, '{}_{}.tex'.format(conf_base, tabtype)\\n )\\n with open(saveto, 'w+') as f:\\n f.write(tex)\\n\\n savestate = {'{}_tex'.format(tabtype): os.path.relpath(saveto)}\\n save_status(statfile, 'table', savestate)\",\n \"def input_models():\\n return [\\n PDBFile(\\n Path(golden_data, \\\"protdna_complex_1.pdb\\\"),\\n path=golden_data,\\n score=42.0,\\n restr_fname=Path(golden_data, \\\"example_ambig_1.tbl\\\")\\n ),\\n PDBFile(\\n Path(golden_data, \\\"protdna_complex_2.pdb\\\"),\\n path=golden_data,\\n score=28.0,\\n restr_fname=Path(golden_data, \\\"example_ambig_2.tbl\\\")\\n )]\",\n \"def combine_list_allformats(\\n reference_genome_list, new_ref_genome_label, project):\\n rg_dataset_list = []\\n for ref_genome in reference_genome_list:\\n rg_dataset_tup = None\\n for dataset_type in [\\n Dataset.TYPE.REFERENCE_GENOME_GENBANK,\\n Dataset.TYPE.REFERENCE_GENOME_FASTA]:\\n filter_result = ref_genome.dataset_set.filter(type=dataset_type)\\n if len(filter_result):\\n rg_dataset_tup = (ref_genome, filter_result[0])\\n break\\n if (not rg_dataset_tup or\\n not os.path.exists(rg_dataset_tup[1].get_absolute_location())):\\n return {\\n 'is_success': False,\\n 'error_msg': 'All reference genomes must have an associated \\\\\\n FASTA or Genbank dataset'\\n }\\n else:\\n rg_dataset_list.append(rg_dataset_tup)\\n assert len(rg_dataset_list) == len(reference_genome_list)\\n\\n # Read the datasets into Biopython SeqRecord objects.\\n rg_seqrecord_list = []\\n seqrecord_ids = []\\n seqrecord_descriptions = []\\n for rg, dataset in rg_dataset_list:\\n with open(dataset.get_absolute_location()) as input_fh:\\n for record in SeqIO.parse(\\n input_fh, DATASET_TO_SEQIO_FORMAT[dataset.type]):\\n rg_seqrecord_list.append((rg, record))\\n seqrecord_ids.append('_'.join([\\n remove_whitespace(rg.label)[:7],\\n remove_whitespace(record.id)[:8]]))\\n seqrecord_descriptions.append(record.description)\\n\\n # Create a new ReferenceGenome.\\n new_ref_genome = ReferenceGenome.objects.create(\\n project=project,\\n label=new_ref_genome_label)\\n\\n # If ReferenceGenome label and Chromosome id are the same, there will be\\n # duplicate seqrecord_ids: resolve by including numeric prefix in id\\n seq_record_list = []\\n MAX_LOCUS_NAME_LEN = 16\\n unique_id_len = len(str(len(seqrecord_ids)))\\n label_len = (MAX_LOCUS_NAME_LEN - 2 - unique_id_len) / 2\\n for i, seqrecord_id in enumerate(seqrecord_ids):\\n rg, seqrecord = rg_seqrecord_list[i]\\n\\n if seqrecord_ids.count(seqrecord_id) == 1:\\n unique_seqrecord_id = seqrecord_id\\n else:\\n unique_seqrecord_id = '_'.join([\\n str(i),\\n remove_whitespace(rg.label)[:label_len],\\n remove_whitespace(seqrecord.id)[:label_len]])\\n\\n seqrecord.seq.alphabet = ambiguous_dna\\n seqrecord.name = unique_seqrecord_id\\n seqrecord.id = unique_seqrecord_id\\n\\n if seqrecord_descriptions.count(seqrecord.description) > 1:\\n seqrecord.description = ' '.join([\\n seqrecord.description,\\n 'from Reference Genome:', rg.label])\\n\\n seq_record_list.append(seqrecord)\\n Chromosome.objects.create(\\n reference_genome=new_ref_genome,\\n label=seqrecord.id,\\n seqrecord_id=seqrecord.id,\\n num_bases=len(seqrecord))\\n\\n # Generate a filename from the label with non-alphanumeric characters\\n # replaced by underscores.\\n filename_prefix = generate_safe_filename_prefix_from_label(\\n new_ref_genome_label)\\n does_list_include_genbank = (\\n Dataset.TYPE.REFERENCE_GENOME_GENBANK in\\n [rg_dataset_tup[1].type for rg_dataset_tup in rg_dataset_list])\\n\\n if does_list_include_genbank:\\n filename = filename_prefix + '.gb'\\n else:\\n filename = filename_prefix + '.fa'\\n new_file_dest = os.path.join(new_ref_genome.get_model_data_dir(), filename)\\n\\n # Write the result.\\n if does_list_include_genbank:\\n ref_genome_dataset_type = Dataset.TYPE.REFERENCE_GENOME_GENBANK\\n else:\\n ref_genome_dataset_type = Dataset.TYPE.REFERENCE_GENOME_FASTA\\n output_file_format = DATASET_TO_SEQIO_FORMAT[ref_genome_dataset_type]\\n\\n with open(new_file_dest, 'w') as output_fh:\\n SeqIO.write(seq_record_list, output_fh, output_file_format)\\n\\n # Create a dataset which will point to the file. This step must happen\\n # after writing the file because a signal will be triggered which requires\\n # the Genbank to exist already.\\n add_dataset_to_entity(\\n new_ref_genome, ref_genome_dataset_type, ref_genome_dataset_type,\\n new_file_dest)\\n\\n return {\\n 'is_success': True,\\n 'new_reference_genome': new_ref_genome\\n }\",\n \"def fetch(id_list):\\n database = 'pmc' if 'PMC' in id_list[0][0] else 'pubmed'\\n print(database)\\n for sublist in id_list:\\n with Entrez.efetch(db=database, id=','.join(sublist),\\n retmode='xml') as handle:\\n records = Entrez.read(handle)\\n\\n write_csv_file(records, output_file)\",\n \"def make_doi_table(dataset: ObservatoryDataset) -> List[Dict]:\\n\\n records = []\\n for paper in dataset.papers:\\n # Doi, events and grids\\n doi = paper.doi.upper()\\n events = make_doi_events(doi, paper.events)\\n\\n # Affiliations: institutions, countries, regions, subregion, funders, journals, publishers\\n institutions = make_doi_institutions(paper.authors)\\n countries = make_doi_countries(paper.authors)\\n regions = make_doi_regions(paper.authors)\\n subregions = make_doi_subregions(paper.authors)\\n funders = make_doi_funders(paper.funders)\\n journals = make_doi_journals(paper.in_unpaywall, paper.journal)\\n publishers = make_doi_publishers(paper.publisher)\\n\\n # Make final record\\n records.append(\\n {\\n \\\"doi\\\": doi,\\n \\\"crossref\\\": {\\n \\\"type\\\": paper.type,\\n \\\"title\\\": paper.title,\\n \\\"published_year\\\": paper.published_date.year,\\n \\\"published_month\\\": paper.published_date.month,\\n \\\"published_year_month\\\": f\\\"{paper.published_date.year}-{paper.published_date.month}\\\",\\n \\\"funder\\\": [{\\\"name\\\": funder.name, \\\"DOI\\\": funder.doi} for funder in paper.funders],\\n },\\n \\\"unpaywall\\\": {},\\n \\\"unpaywall_history\\\": {},\\n \\\"open_citations\\\": {},\\n \\\"events\\\": events,\\n \\\"affiliations\\\": {\\n \\\"doi\\\": doi,\\n \\\"institutions\\\": institutions,\\n \\\"countries\\\": countries,\\n \\\"subregions\\\": subregions,\\n \\\"regions\\\": regions,\\n \\\"groupings\\\": [],\\n \\\"funders\\\": funders,\\n \\\"authors\\\": [],\\n \\\"journals\\\": journals,\\n \\\"publishers\\\": publishers,\\n },\\n }\\n )\\n\\n # Sort to match with sorted results\\n records.sort(key=lambda r: r[\\\"doi\\\"])\\n\\n return records\",\n \"def fetchReferences(self, dataRef, exposure):\\n skyMap = dataRef.get(self.dataPrefix + \\\"skyMap\\\", immediate=True)\\n tractInfo = skyMap[dataRef.dataId[\\\"tract\\\"]]\\n patch = tuple(int(v) for v in dataRef.dataId[\\\"patch\\\"].split(\\\",\\\"))\\n patchInfo = tractInfo.getPatchInfo(patch)\\n references = lsst.afw.table.SourceCatalog(self.references.schema)\\n references.extend(self.references.fetchInPatches(dataRef, patchList=[patchInfo]))\\n return references\",\n \"def generate_pr_table(start_ref, end_ref):\\r\\n header = \\\"|| Merged By || Author || Title || PR || JIRA || Verified? ||\\\"\\r\\n pr_link = \\\"[#{num}|https://github.com/edx/edx-platform/pull/{num}]\\\"\\r\\n user_link = \\\"[@{user}|https://github.com/{user}]\\\"\\r\\n rows = [header]\\r\\n prbe = prs_by_email(start_ref, end_ref)\\r\\n for email, pull_requests in prbe.items():\\r\\n for i, pull_request in enumerate(pull_requests):\\r\\n try:\\r\\n pr_info = get_pr_info(pull_request)\\r\\n title = pr_info[\\\"title\\\"] or \\\"\\\"\\r\\n body = pr_info[\\\"body\\\"] or \\\"\\\"\\r\\n author = pr_info[\\\"user\\\"][\\\"login\\\"]\\r\\n except requests.exceptions.RequestException as e:\\r\\n message = (\\r\\n \\\"Warning: could not fetch data for #{num}: \\\"\\r\\n \\\"{message}\\\".format(num=pull_request, message=e.message)\\r\\n )\\r\\n print(colorize(\\\"red\\\", message), file=sys.stderr)\\r\\n title = \\\"?\\\"\\r\\n body = \\\"?\\\"\\r\\n author = \\\"\\\"\\r\\n rows.append(\\\"| {merged_by} | {author} | {title} | {pull_request} | {jira} | {verified} |\\\".format(\\r\\n merged_by=email if i == 0 else \\\"\\\",\\r\\n author=user_link.format(user=author) if author else \\\"\\\",\\r\\n title=title.replace(\\\"|\\\", \\\"\\\\|\\\"),\\r\\n pull_request=pr_link.format(num=pull_request),\\r\\n jira=\\\", \\\".join(parse_ticket_references(body)),\\r\\n verified=\\\"\\\",\\r\\n ))\\r\\n return \\\"\\\\n\\\".join(rows)\",\n \"def make_reference(self):\\r\\n d = dict([(\\\"M\\\", 1000),\\r\\n (\\\"CM\\\", 800),\\r\\n (\\\"D\\\", 500),\\r\\n (\\\"CD\\\", 300),\\r\\n (\\\"C\\\", 100),\\r\\n (\\\"XC\\\", 80),\\r\\n (\\\"L\\\", 50),\\r\\n (\\\"XL\\\", 30),\\r\\n (\\\"X\\\", 10),\\r\\n (\\\"IX\\\", 8),\\r\\n (\\\"V\\\", 5),\\r\\n (\\\"IV\\\", 3),\\r\\n (\\\"I\\\", 1),])\\r\\n return d\",\n \"def doit():\\n myp = MyPapers()\\n cites = Cites(myp.mypapers)\\n #cites.cite_report()\\n cites.compare_and_update()\",\n \"def get_references(input, verbose=False):\\n\\n # TODO: Make this a class reference parser\\n\\n # *** These tags are mobile-site specific\\n\\n # When we don't have proper access rights, this is present in the html\\n GUEST_TAG_TUPLE = (\\\"li\\\", {\\\"id\\\": \\\"menuGuest\\\"})\\n\\n # Entries are \\\"li\\\" tags with classes of the form:\\n # article-reference-article\\n # article-reference-other-ref\\n REFERENCE_TAG_TUPLE = (\\\"li\\\", {\\\"class\\\": re.compile('article-reference-*')})\\n\\n # This is the URL to the page that contains the document info, including\\n # reference material\\n BASE_URL = _SD_URL + '/science/article/pii/'\\n\\n # This URL was found first via Fiddler, then via closer inspection of the script\\n # 'article_catalyst.js' under sciencedirect.com/mobile/js in the function\\n # resolveReferences\\n REF_RESOLVER_URL = _SD_URL + '/science/referenceResolution/ajaxRefResol'\\n\\n # Return the BeautifulSoup result, the requests session, and the requests response\\n if _is_url(input):\\n pii = _extract_pii(input)\\n else:\\n pii = input\\n\\n sess = requests.Session()\\n\\n if verbose:\\n print('Requesting main page for pii: %s' % pii)\\n resp = sess.get(BASE_URL + pii, cookies={'Site': 'Mobile'})\\n\\n # Step 2 - Get the reference tags\\n\\n soup = BeautifulSoup(resp.text)\\n\\n reference_section = soup.find(\\\"ol\\\", {\\\"class\\\": \\\"article-references\\\"})\\n\\n if reference_section is None:\\n # Then we might be a guest. In other words, we might not have sufficient\\n # privileges to access the data we want. Generally this is protected via\\n # IP mask. When I'm working from home I need to VPN into work so\\n # that I can access the data :/\\n print(\\\"reference_section is None\\\")\\n temp = soup.find(*GUEST_TAG_TUPLE)\\n if temp is None:\\n # We might have no references ... (Doubtful)\\n raise ParseException(\\\"References were not found ..., code error likely\\\")\\n else:\\n raise InsufficientCredentialsException(\\n \\\"Insufficient access rights to get referencs, requires certain IP addresses (e.g. university based IP)\\\")\\n\\n ref_tags = reference_section.find_all(*REFERENCE_TAG_TUPLE)\\n\\n n_refs = len(ref_tags)\\n\\n if n_refs == 0:\\n return None\\n\\n # Step 3 - Resolve reference links\\n # --------------------------------------------------------------------------\\n # The returned html code contains javascript which returns more information\\n # about each reference, such as:\\n #\\n # - links to the full text\\n # - DOI \\n\\n\\n # Step 3.1 - Make the request for the information\\n # --------------------------------------------------------------------------\\n # We need the eid of the current entry, it is of the form:\\n #\\n # SDM.pm.eid = \\\"1-s2.0-0006899387903726\\\"\\n #\\n # * I think this entry gets deleted after the requests so it may not be\\n # visible if looking for it in Chrome. \\n match = re.search('SDM\\\\.pm\\\\.eid\\\\s*=\\\\s*\\\"([^\\\"]+)\\\"', resp.text)\\n #eid = match.group(1)\\n\\n # This list comes from the resolveReferences function in article_catalyst.js\\n payload = {\\n '_pii': pii,\\n '_refCnt': n_refs,\\n '_docType': 'article', # yikes, this might change ...\\n '_refRangeStart': '1',\\n '_refRangeCount': str(n_refs)} # This is normally in sets of 20's ...\\n # I'm not sure if it is important to limit this. The browser then\\n # makes a request fromr 1 count 20, 21 count 20, 41 count 20 etc,\\n # It always goes by 20 even if there aren't 20 left\\n\\n if verbose:\\n print('Requesting reference links')\\n r2 = sess.get(REF_RESOLVER_URL, params=payload)\\n\\n # Step 3.2 - Parse the returned information into single entries\\n # --------------------------------------------------------------------------\\n # This could probably be optimized in terms of execution time. We basically\\n # get back a single script tag. Inside is some sort of hash map for links\\n # for each reference.\\n #\\n # The script tag is of the form:\\n # myMap['bibsbref11']['refHtml']= \\\"<some html stuffs>\\\"; \\n # myMap['bibsbref11']['absUrl']= \\\"http://www.sciencedirect.com/science/absref/sd/0018506X7790068X\\\";\\n # etc.\\n #\\n # - Each entry is quite long.\\n # - Normally contains html\\n # - can be empty i.e. myMap['bibsbref11']['refHtml'] = \\\"\\\";\\n # - the refHtml is quite interesting\\n # - the absolute url is not always present (and currently not parsed)\\n more_soup = BeautifulSoup(r2.text)\\n script_tag = more_soup.find('script')\\n\\n # We unquote the script text as it is transmitted with characters escaped\\n # and we want the parsed data to contain the non-escaped text\\n #\\n # We might eventually want to move this to being after the regular expression ...\\n script_text = urllib_unquote(script_tag.text)\\n\\n ref_match_result = re.findall(\\\"myMap\\\\['bibsbref(\\\\d+)'\\\\]\\\\['refHtml'\\\\]=\\\\s?\\\" + '\\\"([^\\\"]*)\\\";', script_text)\\n # Tokens:\\n # 0 - the # from bibsbref#\\n # 1 - the html content from the 'refHtml' entry\\n # \\n # NOTE: We don't really use the #, so we might remove the () around\\n # \\\\d+ which would shift the index from 1 to 0\\n if verbose:\\n print('Creating reference objects')\\n\\n if len(ref_match_result) > 0:\\n zipped = zip(ref_tags, ref_match_result, range(n_refs))\\n ref_objects = [ScienceDirectRef(ref_tag, ref_link_info[1], ref_id) for\\n ref_tag, ref_link_info, ref_id in zipped]\\n else:\\n zipped = zip(ref_tags, range(n_refs))\\n ref_objects = [ScienceDirectRef(ref_tag, ref_id) for\\n ref_tag, ref_id in zipped]\\n\\n # Step 4:\\n # --------------------------------------------------------------------------\\n # TODO: Improve documentation for this step\\n\\n if verbose:\\n print('Retrieving Scopus Counts')\\n\\n ref_scopus_eids = [] # The Scopus IDs of the references to resolve\\n # but with a particular formatting ...\\n ref_count = 0 # Number of references we haven't resolved\\n\\n ref_count_list = []\\n # NOTE: Browser requests these in the reverse order ...\\n for ref_id, ref in enumerate(ref_objects):\\n\\n if ref._data_sceid is not None:\\n ref_scopus_eids.append(ref._data_sceid + ',' + str(ref_id + 1) + '~')\\n ref_count += 1\\n\\n # If we've got enough, then update the counts\\n # The 20 may be arbitrary but it was what was used in original JS\\n if ref_count > 20:\\n ref_count_list += _update_counts(sess, ref_scopus_eids, REF_RESOLVER_URL)\\n ref_count = 0\\n ref_scopus_eids = []\\n\\n # Get any remaining reference counts\\n if ref_count != 0:\\n ref_count_list += _update_counts(sess, ref_scopus_eids, REF_RESOLVER_URL)\\n\\n # Take the raw data and set the citation count for each object\\n for ref_tuple in ref_count_list:\\n ref_id = int(ref_tuple[0]) - 1\\n ref_count = int(ref_tuple[1])\\n ref_objects[ref_id].scopus_cite_count = ref_count\\n\\n # All done!\\n # ---------\\n return ref_objects\",\n \"async def create_tables():\\n text_create_citizens_table = queries.CREATE_CITIZENS\\n text_create_relative_table = queries.CREATE_RELATIVES\\n text_create_consts_table = queries.CREATE_CONSTS\\n text_insert_base_import_id = queries.INSERT_IMPORT_ID_0\\n text_create_index_citizens = queries.CREATE_INDEX_CITIZENS\\n text_create_index_relatives = queries.CREATE_INDEX_RELATIVES\\n\\n queries_list = [text_create_citizens_table, text_create_relative_table,\\n text_create_consts_table, text_insert_base_import_id,\\n text_create_index_citizens,text_create_index_relatives]\\n\\n connection = await sql.connect()\\n async with connection.transaction():\\n for query in queries_list:\\n await sql.execute_query(connection, query)\\n await sql.close(connection)\",\n \"def build_latex(file_list):\\n eingabe=[]\\n anhang_count=0\\n anhaenge=[]\\n anhaenge_file=[]\\n for file in file_list:\\n x=load_file(file)[1]\\n eingabe.append(\\\"\\\\section{%s}\\\" %(x[2]))\\n eingabe.append(\\\"\\\\subsection{Infos}\\\")\\n eingabe.append(\\\"\\\\\\\\begin{tabularx}{\\\\linewidth}{@{}lX}\\\")\\n eingabe.append(r\\\"\\\\textbf{Datum} & %s\\\\\\\\\\\" %(x[0]))\\n eingabe.append(r\\\"\\\\textbf{Gremium} & %s\\\\\\\\\\\" %(x[1]))\\n eingabe.append(r\\\"\\\\textbf{Anatrag/Beschluss wurde} & %s\\\\\\\\\\\" %(x[9]))\\n x[11]=x[11].replace(\\\" \\\",\\\"\\\")\\n kw=x[11].split(\\\",\\\")\\n for i in range(0,len(kw)):\\n if i==0:\\n eingabe.append(r\\\"\\\\textbf{Keyword:} & %s\\\\\\\\\\\" %(kw[i]))\\n else:\\n eingabe.append(r\\\" & %s\\\\\\\\\\\" %(kw[i]))\\n eingabe.append(\\\"\\\\end{tabularx}\\\")\\n eingabe.append(\\\"\\\\\\\\begin{tabularx}{\\\\linewidth}{@{}XXX}\\\")\\n eingabe.append(r\\\"\\\\textbf{Abstimmungsergebniss:}&&\\\\\\\\\\\")\\n eingabe.append(r\\\"Zustimmung & Ablehnung & Enthaltungen \\\\\\\\\\\")\\n eingabe.append(r\\\"{} & {} & {} \\\\\\\\\\\".format(x[6],x[7],x[8]))\\n eingabe.append(\\\"\\\\end{tabularx}\\\")\\n eingabe.append(\\\"\\\\subsection{Antrags/Beschlusstext}\\\")\\n line_text=len(eingabe)\\n eingabe.append(x[3])\\n eingabe.append(\\\"\\\\subsection{Begründung}\\\")\\n eingabe.append(x[4])\\n if x[23]==\\\"Ja\\\" and x[24]!=\\\"\\\":\\n delta=7\\n anzahl=int((len(x)-23)/delta)\\n if anzahl==1:\\n eingabe.append(\\\"\\\\subsection{Änderungsantrag}\\\")\\n eingabe.append(\\\"\\\\subsubsection*{Vorschlag}\\\")\\n eingabe.append(x[24])\\n eingabe.append(\\\"\\\\subsubsection*{Begründung}\\\")\\n eingabe.append(x[25]+\\\"\\\\\\\\vspace{1.5ex} \\\\\\\\\\\\\\\\\\\")\\n eingabe.append(\\\"\\\\\\\\begin{tabularx}{\\\\linewidth}{@{}XXX}\\\")\\n eingabe.append(r\\\"\\\\textbf{Abstimmungsergebniss:}&&\\\\\\\\\\\")\\n eingabe.append(r\\\"Zustimmung & Ablehnung & Enthaltungen \\\\\\\\\\\")\\n eingabe.append(r\\\"{} & {} & {} \\\\\\\\\\\".format(x[26],x[27],x[28]))\\n eingabe.append(r\\\"\\\\multicolumn{2}{@{}l}{\\\\textbf{Änderungsantrag wurde:}} & %s \\\\\\\\\\\" %(x[29]))\\n eingabe.append(\\\"\\\\\\\\end{tabularx}\\\")\\n else:\\n eingabe.append(\\\"\\\\subsection{Änderungsanträge}\\\")\\n for i in range(0,anzahl):\\n eingabe.append(\\\"\\\\subsubsection{Änderungsvorschlag %s}\\\" %(i+1))\\n eingabe.append(\\\"\\\\\\\\paragraph*{Vorschlag}\\\")\\n eingabe.append(x[24+(delta*i)])\\n eingabe.append(\\\"\\\\\\\\paragraph*{Begründung}\\\")\\n eingabe.append(x[25+(delta*i)]+\\\"\\\\\\\\vspace{1.5ex} \\\\\\\\\\\\\\\\\\\")\\n eingabe.append(\\\"\\\\\\\\begin{tabularx}{\\\\linewidth}{@{}XXX}\\\")\\n eingabe.append(r\\\"\\\\textbf{Abstimmungsergebniss:}&&\\\\\\\\\\\")\\n eingabe.append(r\\\"Zustimmung & Ablehnung & Enthaltungen \\\\\\\\\\\")\\n eingabe.append(r\\\"{} & {} & {} \\\\\\\\\\\".format(x[26+(delta*i)],x[27+(delta*i)],x[28+(delta*i)]))\\n eingabe.append(r\\\"\\\\multicolumn{2}{@{}l}{\\\\textbf{Änderungsantrag wurde:}} & %s \\\\\\\\\\\" %(x[29+(delta*i)]))\\n eingabe.append(\\\"\\\\\\\\end{tabularx}\\\")\\n if x[10]!=\\\"\\\":\\n anhang=x[10].split(\\\",\\\")\\n bennenung=x[11].split(\\\",\\\")\\n eingabe[line_text]=eingabe[line_text]+\\\"\\\\\\\\\\\\\\\\ \\\\n Dieser Antrag enthält %s Anhänge: \\\" %(len(anhang))\\n for i in range(0,len(anhang)):\\n anhang_count=anhang_count+1\\n anhaenge.append(\\\"\\\\section{%s - %s} \\\\label{An:%s}\\\" % (x[2],bennenung[i],str(anhang_count)))\\n anhaenge.append(\\\"\\\\includepdf[pages=-]{%s}\\\" %(anhang[i]))\\n anhaenge_file.append(anhang[i])\\n if i!=len(anhang)-1:\\n eingabe[line_text]=eingabe[line_text]+\\\"\\\\\\\\nameref{An:%s}, \\\" % (str(anhang_count))\\n else:\\n eingabe[line_text]=eingabe[line_text]+\\\"\\\\\\\\nameref{An:%s} \\\" % (str(anhang_count)) \\n \\n eingabe.append(\\\"\\\\\\\\newpage\\\") \\n eingabe.append(\\\"\\\\\\\\appendix\\\") \\n eingabe.append(\\\"\\\\\\\\pagenumbering{Roman}\\\") \\n ausgabe=\\\"\\\"\\n for i in range(0,len(eingabe)):\\n ausgabe=ausgabe+eingabe[i]+\\\"\\\\n\\\"\\n \\n for i in range(0,len(anhaenge)):\\n ausgabe=ausgabe+anhaenge[i]+\\\"\\\\n\\\"\\n \\n return ausgabe,anhaenge_file\",\n \"def write_to_latex(codelist, unwanted_courses):\\n # TODO: investigate a way to add large amounts of text outside of the\\n # function\\n abstract01 = \\\"I created this document to practice parsing html and using\\\\\\n tools like Beautiful Soup which I've previously had little experience\\\\\\n in. As a result, it's not perfect.\\\\\\\\newline\\\\\\n It is also a slightly condensed all-in-one-place look at a selection\\\\\\n of courses that are available for fourth year computer science\\\\\\n students at the University of Glasgow. For the purposes of clarity I\\\\\\n have removed several courses from this selection. The following\\\\\\n courses have been omitted:\\\"\\n abstract02 = \\\"For more insight into the project, to report issues or to\\\\\\n inspect the code, have a look at the GitHub:\\\\\\n \\\\\\\\url{https://github.com/IS0metric/course-ripper}\\\"\\n unincluded = create_not_included_list(unwanted_courses)\\n with open('courses.tex', 'w') as f:\\n # TODO Try and move all this to a separate function?\\n # TODO: Check if it's more efficient to write a single, massive string\\n # to file\\n f.write('\\\\\\\\documentclass{hitec}\\\\n')\\n f.write('\\\\\\\\usepackage[document]{ragged2e}\\\\n')\\n f.write('\\\\\\\\usepackage{url}\\\\n')\\n f.write('\\\\\\\\usepackage{hyperref}\\\\n')\\n f.write('\\\\\\\\setcounter{tocdepth}{4}\\\\n')\\n f.write('\\\\\\\\begin{document}\\\\n')\\n f.write('\\\\\\\\title{Fourth Year (2016-17) Courses}\\\\n')\\n f.write('\\\\\\\\author{Jack Parkinson}\\\\n')\\n f.write('\\\\\\\\date{August 2016}\\\\n')\\n f.write('\\\\\\\\maketitle\\\\n')\\n f.write('\\\\\\\\abstract{' + abstract01 + unincluded + abstract02 + '}\\\\n')\\n f.write('\\\\\\\\newpage\\\\n\\\\n')\\n f.write('\\\\\\\\tableofcontents\\\\n')\\n f.write('\\\\\\\\newpage\\\\n\\\\n')\\n # TODO: Look into alternatives to the three lists\\n all_courses = []\\n sem1_courses = []\\n sem2_courses = []\\n for code in codelist:\\n course = bsoup(get_coursepage(code))\\n if course['offered']['value'] == 'Runs Throughout Semesters 1 and 2':\\n all_courses.append(course)\\n elif \\\"1\\\" in course['offered']['value']:\\n sem1_courses.append(course)\\n elif \\\"2\\\" in course['offered']['value']:\\n sem2_courses.append(course)\\n f.write('\\\\\\\\section{Semester 1 and 2 Courses}\\\\n\\\\n')\\n for course in all_courses:\\n f.write(latex_course(course))\\n f.write('\\\\\\\\section{Semester 1 Only Courses}\\\\n\\\\n')\\n for course in sem1_courses:\\n f.write(latex_course(course))\\n f.write('\\\\\\\\section{Semester 2 Only Courses}\\\\n\\\\n')\\n for course in sem2_courses:\\n f.write(latex_course(course))\\n f.write('\\\\\\\\end{document}')\\n return None\",\n \"def write_reference_page(outfile: TextIO, do_print: bool, ref: TMB_Classes.ReferenceClass, citelist: list,\\n refdict: dict, name_table: dict, point_locations: dict) -> None:\\n if do_print:\\n start_page_division(outfile, \\\"ref_page\\\")\\n else:\\n common_html_header(outfile, ref.citation, indexpath=\\\"../\\\")\\n outfile.write(\\\" <header id=\\\\\\\"\\\" + ref.cite_key + \\\".html\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <h2 class=\\\\\\\"nobookmark\\\\\\\">\\\" + ref.formatted_html + \\\"</h2>\\\\n\\\")\\n if not do_print:\\n outfile.write(\\\" <nav>\\\\n\\\")\\n outfile.write(\\\" <ul>\\\\n\\\")\\n outfile.write(\\\" <li><a href=\\\\\\\"../\\\" + init_data().ref_url +\\n \\\"\\\\\\\">\\\" + fetch_fa_glyph(\\\"index\\\") + \\\"Full Reference List</a></li>\\\\n\\\")\\n outfile.write(\\\" </ul>\\\\n\\\")\\n outfile.write(\\\" </nav>\\\\n\\\")\\n outfile.write(\\\" </header>\\\\n\\\")\\n outfile.write(\\\"\\\\n\\\")\\n # find names for this citation\\n names = []\\n cites_to = []\\n for c in citelist:\\n if c.cite_key == ref.cite_key:\\n names.append(c)\\n if c.application == ref.cite_key:\\n cites_to.append(c)\\n started_note = False\\n comcnt = 0\\n notecnt = 0\\n uniquenames = set()\\n for n in names:\\n if n.general_note != \\\".\\\":\\n if not started_note:\\n outfile.write(\\\" <p>\\\\n\\\")\\n started_note = True\\n outfile.write(\\\" \\\" + replace_species_in_string(n.general_note) + \\\"\\\\n\\\")\\n if n.common != \\\".\\\":\\n comcnt += 1\\n if n.name_note != \\\".\\\":\\n notecnt += 1\\n uniquenames |= {n.name}\\n if started_note:\\n outfile.write(\\\" </p>\\\\n\\\")\\n\\n if ref.language != \\\"\\\":\\n outfile.write(\\\"<p><strong>Language:</strong> \\\" + format_language(ref.language) + \\\"</p>\\\\n\\\")\\n if ref.doi is not None:\\n outfile.write(\\\"<p><strong>Online:</strong> \\\")\\n if ref.doi.startswith(\\\"10\\\"):\\n outfile.write(\\\"<img src=\\\\\\\"../images/DOI_logo.svg\\\\\\\" style=\\\\\\\"height: 1em; vertical-align: middle\\\\\\\" \\\"\\n \\\"alt=\\\\\\\"DOI\\\\\\\"> \\\")\\n outfile.write(\\\"<a href=\\\\\\\"https://doi.org/{0}\\\\\\\">https://doi.org/{0}</a></p>\\\\n\\\".format(ref.doi))\\n else:\\n outfile.write(\\\"{0}</p>\\\\n\\\".format(ref.doi))\\n\\n # write name table\\n outfile.write(\\\" <h3 class=\\\\\\\"nobookmark\\\\\\\">Names Appearing in this Publication</h3>\\\\n\\\")\\n if len(names) > 0:\\n outfile.write(\\\" <table class=\\\\\\\"citetable\\\\\\\">\\\\n\\\")\\n outfile.write(\\\" <tr>\\\\n\\\")\\n outfile.write(\\\" <th class=\\\\\\\"name_col\\\\\\\">Name Used</th>\\\\n\\\")\\n if comcnt > 0:\\n outfile.write(\\\" <th class=\\\\\\\"common_col\\\\\\\">Common Name(s)</th>\\\\n\\\")\\n outfile.write(\\\" <th class=\\\\\\\"where_col\\\\\\\">Where</th>\\\\n\\\")\\n outfile.write(\\\" <th class=\\\\\\\"applied_col\\\\\\\">Applied to...</th>\\\\n\\\")\\n outfile.write(\\\" <th class=\\\\\\\"accepted_col\\\\\\\">Accepted Name</th>\\\\n\\\")\\n outfile.write(\\\" <th class=\\\\\\\"source_col\\\\\\\">Source of Accepted</th>\\\\n\\\")\\n if notecnt > 0:\\n outfile.write(\\\" <th class=\\\\\\\"notes_col\\\\\\\">Note(s)</th>\\\\n\\\")\\n outfile.write(\\\" </tr>\\\\n\\\")\\n names.sort()\\n output_name_table(outfile, do_print, False, names, uniquenames, notecnt, comcnt, refdict, name_table,\\n point_locations)\\n else:\\n outfile.write(\\\" <p>\\\\n\\\")\\n outfile.write(\\\" Data not yet available.\\\\n\\\")\\n outfile.write(\\\" </p>\\\\n\\\")\\n\\n if len(cites_to) > 0:\\n outfile.write(\\\" <h3 class=\\\\\\\"nobookmark\\\\\\\">This Publication is Cited By</h3>\\\\n\\\")\\n outfile.write(\\\" <p>\\\\n\\\")\\n cs = set()\\n for c in cites_to:\\n if c.cite_key in refdict:\\n crossref = refdict[c.cite_key]\\n cs |= {\\\"<a href=\\\\\\\"\\\" + rel_link_prefix(do_print) + crossref.cite_key +\\n \\\".html\\\\\\\">\\\" + crossref.citation + \\\"</a>\\\"}\\n else:\\n cs |= {c.cite_key}\\n cl = []\\n for x in cs:\\n cl.append(x)\\n cl.sort()\\n outfile.write(\\\" \\\" + \\\", \\\".join(cl) + \\\"\\\\n\\\")\\n outfile.write(\\\" </p>\\\\n\\\")\\n\\n if do_print:\\n end_page_division(outfile)\\n else:\\n common_html_footer(outfile, indexpath=\\\"../\\\")\",\n \"def label_data(data_dir):\\n # Reads in the metadata matrices (i.e., paper by metadata matrix)\\n metadata_dir = os.path.join(data_dir, 'metadata/')\\n filenames = sorted(glob(os.path.join(metadata_dir, 'Karina*.csv')))\\n\\n converter = {'Paradigm Class': 'ParadigmClass',\\n 'Behavioral Domain': 'BehavioralDomain',\\n 'Diagnosis': 'Diagnosis',\\n 'Stimulus Modality': 'StimModality',\\n 'Stimulus Type': 'StimType',\\n 'Response Modality': 'RespModality',\\n 'Response Type': 'RespType',\\n 'Instructions': 'Instruction'}\\n\\n columns = converter.keys()\\n\\n # Cycles through all columns and all metadata files and concatenates everything\\n metadata_dfs = [pd.read_csv(file_, dtype=str)[['PubMed ID'] + converter.keys()] for file_ in filenames]\\n metadata_df = pd.concat(metadata_dfs, ignore_index=True)\\n\\n # Transforms to table format and sorts the metadata matrices\\n all_labels = []\\n for column in converter.keys():\\n dimension = converter[column]\\n dim_labels = get_label_parents(metadata_df, column, dimension)\\n all_labels += dim_labels\\n\\n all_labels = [label_con.get(label, label) for label in all_labels]\\n all_labels = [label for label in all_labels if label != 'DROP']\\n all_labels = sorted(list(set(all_labels)))\\n\\n # Get list of annotated papers with associated files\\n metadata_df = metadata_df[metadata_df['PubMed ID'].str.contains('^\\\\d+$')].reset_index()\\n list_of_pmids = metadata_df['PubMed ID'].unique().tolist()\\n\\n column_names = ['pmid'] + all_labels\\n label_df = pd.DataFrame(columns=column_names, data=np.zeros((len(list_of_pmids), len(column_names))))\\n label_df['pmid'] = list_of_pmids\\n\\n # This generates a binary matrix of pmids by all labels.\\n for row in metadata_df.index:\\n pmid = metadata_df['PubMed ID'].iloc[row]\\n\\n # Only label papers with associated files.\\n if pmid in list_of_pmids:\\n for column in columns:\\n exp_labels = metadata_df[column].iloc[row]\\n if pd.notnull(exp_labels):\\n exp_labels = exp_labels.split('| ')\\n exp_labels = ['{0}.{1}'.format(converter[column], clean_str(label)) for label in exp_labels]\\n for label in exp_labels:\\n corr_label = label_con.get(label, label)\\n for out_column in label_df.columns:\\n # Count each label toward itself and its parents.\\n if corr_label.startswith(out_column):\\n out_row = label_df.loc[label_df['pmid']==pmid].index[0]\\n label_df[out_column].iloc[out_row] = 1\\n\\n # Save DataFrames.\\n count_df = label_df.sum().to_frame()\\n label_df = label_df.astype(int).astype(str)\\n out_file = os.path.join(data_dir, 'labels/fiu_labels.csv')\\n label_df.to_csv(out_file, index=False)\\n\\n count_file = os.path.join(data_dir, 'labels/label_counts.csv')\\n count_df = count_df.ix[1:]\\n count_df.index.name = 'Label'\\n count_df.columns = ['Count']\\n count_df.to_csv(count_file, index=True)\",\n \"def calculate_name_index_data(refdict: dict, citelist: list, specific_names: list) -> Tuple[list, dict, dict, dict,\\n dict, dict, dict, dict,\\n dict, dict]:\\n name_table = create_name_table(citelist)\\n unique_names = list()\\n nameset = set()\\n # total_binomial_year_cnts = {}\\n total_binomial_year_cnts = collections.Counter()\\n for c in citelist:\\n if c.name != \\\".\\\":\\n clean = clean_name(c.name)\\n if not clean.lower() in nameset:\\n nameset |= {clean.lower()}\\n unique_names.append(clean)\\n y = refdict[c.cite_key].year()\\n if y is not None:\\n total_binomial_year_cnts.update([y])\\n # if y in total_binomial_year_cnts:\\n # total_binomial_year_cnts[y] += 1\\n # else:\\n # total_binomial_year_cnts[y] = 1\\n unique_names.sort(key=lambda s: s.lower())\\n\\n # identify genera used per paper\\n genera_per_paper = {}\\n for c in citelist:\\n if c.name != \\\".\\\":\\n if c.cite_key not in genera_per_paper:\\n genera_per_paper[c.cite_key] = set()\\n genera_set = genera_per_paper[c.cite_key]\\n genera_set |= {extract_genus(clean_name(c.name))}\\n genus_cnts = {}\\n for c in genera_per_paper:\\n y = refdict[c].year()\\n if y is not None:\\n if init_data().start_year <= y <= init_data().current_year:\\n genera_set = genera_per_paper[c]\\n for genus in genera_set:\\n genus = clean_genus(genus)\\n if genus != \\\"\\\":\\n genus_cnts.setdefault(genus, {y: 0 for y in range(init_data().start_year,\\n init_data().current_year + 1)})[y] += 1\\n # if genus not in genus_cnts:\\n # genus_cnts[genus] = {y: 0 for y in range(init_data().start_year,\\n # init_data().current_year + 1)}\\n # gcnts = genus_cnts[genus]\\n # gcnts[y] += 1\\n\\n binomial_usage_cnts_by_year = {}\\n binomial_location_applications = {}\\n binomial_usage_cnts = {}\\n for name in unique_names:\\n binomial_usage_cnts_by_year[name], tmptotal = calculate_binomial_yearly_cnts(name, refdict, citelist)\\n if tmptotal > 0:\\n binomial_usage_cnts[name] = tmptotal\\n binomial_location_applications[name] = calculate_binomial_locations(name, citelist)\\n\\n # specific_year_cnts = {}\\n specific_year_cnts = collections.Counter()\\n specific_usage_cnts_by_year = {}\\n specific_location_applications = {}\\n specific_usage_cnts = {}\\n for name in specific_names:\\n (specific_usage_cnts_by_year[name.name],\\n tmptotal) = calculate_specific_name_yearly_cnts(name, unique_names, binomial_usage_cnts_by_year)\\n if tmptotal > 0:\\n specific_usage_cnts[name.name] = tmptotal\\n specific_location_applications[name] = calculate_specific_locations(name, unique_names,\\n binomial_location_applications)\\n tmpkey = name.priority_source\\n if tmpkey != \\\".\\\":\\n y = refdict[tmpkey].year()\\n if y is not None:\\n specific_year_cnts.update([y])\\n # if y in specific_year_cnts:\\n # specific_year_cnts[y] += 1\\n # else:\\n # specific_year_cnts[y] = 1\\n return (unique_names, binomial_usage_cnts_by_year, specific_usage_cnts_by_year, genus_cnts,\\n total_binomial_year_cnts, name_table, specific_location_applications, binomial_location_applications,\\n binomial_usage_cnts, specific_usage_cnts)\",\n \"def create_lookup_tables(text):\\n vocab = set(text.split())\\n vocab_to_int = copy.copy(CODES)\\n\\n for v_i, v in enumerate(vocab, len(CODES)):\\n vocab_to_int[v] = v_i\\n\\n int_to_vocab = {v_i: v for v, v_i in vocab_to_int.items()}\\n\\n return vocab_to_int, int_to_vocab\",\n \"def create_numbers_table():\\n work_tuples = parse_columns()\\n print('\\\\n\\\\n\\\\n ----- Tableau récapitulatif -----')\\n print('-----------------------')\\n for ii in work_tuples:\\n line = '|'\\n for ij in ii:\\n line += ' ij |'\\n print(line)\\n print('-----------------------')\",\n \"def parse_corenlp_coref_xml_doc(input_dir = 'CoreNLP_coref_anno/dev'):\\n\\n\\tmentions = []\\n\\tfor file in os.listdir(input_dir):\\n\\t\\ttree = ET.parse(input_dir + '/' + file)\\n\\t\\tdocument = tree.getroot()[0]\\n\\t\\t# sentences_node = document.find('sentences')\\n\\n\\t\\t# for sentence in enumerate(sentences_node):\\n\\t\\t# \\ts_num = sentence.attribs['id']\\n\\t\\t# \\tsentence_text = \\\" \\\".join([token.word for token in sentence.find('tokens')])\\n\\t\\t# \\tsentences[s_num] = sentence_text\\n\\n\\t\\tcoref_node = document.find('coreference')\\n\\t\\t\\n\\t\\tfor coref_id, coref_chain in enumerate(coref_node):\\n\\t\\t\\tfor mention in cluster:\\n\\t\\t\\t\\tsent_num = int(mention[0].text)\\n\\t\\t\\t\\tstart = int(mention[1].text)-1\\n\\t\\t\\t\\tend = int(mention[2].text)-1\\n\\t\\t\\t\\ttext = mention[4].text\\n\\t\\t\\t\\tmentions.append({\\\"filename\\\":file, \\\"s_num\\\":sent_num,\\\"EP\\\":\\\"E\\\", \\\"indices\\\":range(start, end),\\\"coref\\\":coref_id+1})\\n\\n\\tmentions.sort(key=lambda x:(x[\\\"filename\\\"],x[\\\"s_num\\\"],x[\\\"indices\\\"][0]))\\n\\twith open('coref_output.txt', 'w') as out_file:\\n\\t\\tout_file.write(\\\"file\\\\tsentence\\\\tentity(E) or predicate(P)\\\\t coref chain\\\\tindices\\\\t\\\\n\\\")\\n\\t\\tout_file.write(\\\"\\\\n\\\".join([e[\\\"filename\\\"]+\\\"\\\\t\\\"+str(e[\\\"s_num\\\"])+\\\"\\\\t\\\"+e[\\\"EP\\\"]+\\\"\\\\t\\\"+str(e[\\\"coref\\\"])+\\\"\\\\t\\\"+str(e[\\\"indices\\\"])[1:-1] for e in mentions]))\",\n \"def data_connections():\\r\\n section = document.add_section()\\r\\n new_width, new_height = section.page_height, section.page_width\\r\\n section.orientation = WD_ORIENT.LANDSCAPE\\r\\n section.page_width = 10058400\\r\\n section.page_height = 7772400\\r\\n document.add_heading('Data connections', level=1)\\r\\n connections = get_qlik_sense.get_dataconnections()\\r\\n num_of_connections = len(connections)\\r\\n table = document.add_table(rows=num_of_connections+1, cols=3)\\r\\n table.style = 'Grid Table 1 Light Accent 1'\\r\\n row = table.rows[0]\\r\\n row.cells[0].text = 'name'\\r\\n row.cells[1].text = 'connection string'\\r\\n row.cells[2].text = 'type'\\r\\n for connection in range(num_of_connections):\\r\\n row = table.rows[connection+1]\\r\\n row.cells[0].text = str(connections[connection][0])\\r\\n row.cells[1].text = str(connections[connection][1])\\r\\n row.cells[2].text = str(connections[connection][2])\\r\\n document.add_page_break()\",\n \"def get_citation_informations(recid_list, config):\\n begin_time = os.times()[4]\\n d_reports_numbers = {} #dict of recid -> institute-given-report-code\\n d_references_report_numbers = {} #dict of recid -> ['astro-ph/xyz']\\n d_references_s = {} #dict of recid -> list_of_the_entries_of_this_recs_bibliography\\n d_records_s = {} #dict of recid -> this_records_publication_info\\n citation_informations = []\\n\\n write_message(\\\"config function \\\"+config.get(\\\"rank_method\\\", \\\"function\\\"), verbose=9)\\n function = \\\"\\\"\\n try:\\n function = config.get(\\\"rank_method\\\", \\\"function\\\")\\n except:\\n register_exception(prefix=\\\"cfg section [rank_method] has no attribute called function\\\", alert_admin=True)\\n #we cannot continue\\n return [ {}, {}, {}, {} ]\\n record_pri_number_tag = \\\"\\\"\\n try:\\n record_pri_number_tag = config.get(function, \\\"primary_report_number\\\")\\n except:\\n register_exception(prefix=\\\"cfg section \\\"+function+\\\" has no attribute primary_report_number\\\", alert_admin=True)\\n return [ {}, {}, {}, {} ]\\n record_add_number_tag = \\\"\\\"\\n try:\\n record_add_number_tag = config.get(config.get(\\\"rank_method\\\", \\\"function\\\"),\\n \\\"additional_report_number\\\")\\n except:\\n register_exception(prefix=\\\"config error. cfg section \\\"+function+\\\" has no attribute additional_report_number\\\", alert_admin=True)\\n return [ {}, {}, {}, {} ]\\n\\n reference_number_tag = \\\"\\\"\\n try:\\n reference_number_tag = config.get(config.get(\\\"rank_method\\\", \\\"function\\\"),\\n \\\"reference_via_report_number\\\")\\n except:\\n register_exception(prefix=\\\"config error. cfg section \\\"+function+\\\" has no attribute reference_via_report_number\\\", alert_admin=True)\\n return [ {}, {}, {}, {} ]\\n\\n reference_tag = \\\"\\\"\\n try:\\n reference_tag = config.get(config.get(\\\"rank_method\\\", \\\"function\\\"),\\n \\\"reference_via_pubinfo\\\")\\n except:\\n register_exception(prefix=\\\"config error. cfg section \\\"+function+\\\" has no attribute reference_via_pubinfo\\\", alert_admin=True)\\n return [ {}, {}, {}, {} ]\\n\\n p_record_pri_number_tag = tagify(parse_tag(record_pri_number_tag))\\n #037a: contains (often) the \\\"hep-ph/0501084\\\" tag of THIS record\\n p_record_add_number_tag = tagify(parse_tag(record_add_number_tag))\\n #088a: additional short identifier for the record\\n p_reference_number_tag = tagify(parse_tag(reference_number_tag))\\n #999C5r. this is in the reference list, refers to other records. Looks like: hep-ph/0408002\\n p_reference_tag = tagify(parse_tag(reference_tag))\\n #999C5s. A standardized way of writing a reference in the reference list. Like: Nucl. Phys. B 710 (2000) 371\\n #fields needed to construct the pubinfo for this record\\n publication_pages_tag = \\\"\\\"\\n publication_year_tag = \\\"\\\"\\n publication_journal_tag = \\\"\\\"\\n publication_volume_tag = \\\"\\\"\\n publication_format_string = \\\"p v (y) c\\\"\\n try:\\n tag = config.get(function, \\\"pubinfo_journal_page\\\")\\n publication_pages_tag = tagify(parse_tag(tag))\\n tag = config.get(function, \\\"pubinfo_journal_year\\\")\\n publication_year_tag = tagify(parse_tag(tag))\\n tag = config.get(function, \\\"pubinfo_journal_title\\\")\\n publication_journal_tag = tagify(parse_tag(tag))\\n tag = config.get(function, \\\"pubinfo_journal_volume\\\")\\n publication_volume_tag = tagify(parse_tag(tag))\\n publication_format_string = config.get(function, \\\"pubinfo_journal_format\\\")\\n except:\\n pass\\n\\n #print values for tags for debugging\\n if task_get_task_param('verbose') >= 9:\\n write_message(\\\"tag values\\\")\\n write_message(\\\"p_record_pri_number_tag \\\"+str(p_record_pri_number_tag))\\n write_message(\\\"p_reference_tag \\\"+str(p_reference_tag))\\n write_message(\\\"publication_journal_tag \\\"+str(publication_journal_tag))\\n write_message(\\\"publication_format_string is \\\"+publication_format_string)\\n done = 0 #for status reporting\\n numrecs = len(recid_list)\\n\\n # perform quick check to see if there are some records with\\n # reference tags, because otherwise get.cit.inf would be slow even\\n # if there is nothing to index:\\n if run_sql(\\\"SELECT value FROM bib%sx WHERE tag=%%s LIMIT 1\\\" % p_reference_tag[0:2],\\n (p_reference_tag,)) or \\\\\\n run_sql(\\\"SELECT value FROM bib%sx WHERE tag=%%s LIMIT 1\\\" % p_reference_number_tag[0:2],\\n (p_reference_number_tag,)):\\n for recid in recid_list:\\n if (done % 10 == 0):\\n task_sleep_now_if_required()\\n #in fact we can sleep any time here\\n\\n if (done % 1000 == 0):\\n mesg = \\\"get cit.inf done \\\"+str(done)+\\\" of \\\"+str(numrecs)\\n write_message(mesg)\\n task_update_progress(mesg)\\n done = done+1\\n\\n if recid in INTBITSET_OF_DELETED_RECORDS:\\n # do not treat this record since it was deleted; we\\n # skip it like this in case it was only soft-deleted\\n # e.g. via bibedit (i.e. when collection tag 980 is\\n # DELETED but other tags like report number or journal\\n # publication info remained the same, so the calls to\\n # get_fieldvalues() below would return old values)\\n continue\\n\\n pri_report_numbers = get_fieldvalues(recid, p_record_pri_number_tag)\\n add_report_numbers = get_fieldvalues(recid, p_record_add_number_tag)\\n reference_report_numbers = get_fieldvalues(recid, p_reference_number_tag)\\n references_s = get_fieldvalues(recid, p_reference_tag)\\n\\n l_report_numbers = pri_report_numbers\\n l_report_numbers.extend(add_report_numbers)\\n d_reports_numbers[recid] = l_report_numbers\\n\\n if reference_report_numbers:\\n write_message(str(recid)+\\\"'s report number values \\\"+str(l_report_numbers), verbose=9)\\n d_references_report_numbers[recid] = reference_report_numbers\\n\\n references_s = get_fieldvalues(recid, p_reference_tag)\\n if references_s:\\n write_message(str(recid)+\\\"'s \\\"+str(p_reference_tag)+\\\" values \\\"+str(references_s), verbose=9)\\n d_references_s[recid] = references_s\\n\\n #get a combination of\\n #journal vol (year) pages\\n if publication_pages_tag and publication_journal_tag and \\\\\\n publication_volume_tag and publication_year_tag and publication_format_string:\\n tagsvalues = {} #we store the tags and their values here\\n #like c->444 y->1999 p->\\\"journal of foo\\\",v->20\\n tagsvalues[\\\"p\\\"] = \\\"\\\"\\n tagsvalues[\\\"y\\\"] = \\\"\\\"\\n tagsvalues[\\\"c\\\"] = \\\"\\\"\\n tagsvalues[\\\"v\\\"] = \\\"\\\"\\n tmp = get_fieldvalues(recid, publication_journal_tag)\\n if tmp:\\n tagsvalues[\\\"p\\\"] = tmp[0]\\n tmp = get_fieldvalues(recid, publication_volume_tag)\\n if tmp:\\n tagsvalues[\\\"v\\\"] = tmp[0]\\n tmp = get_fieldvalues(recid, publication_year_tag)\\n if tmp:\\n tagsvalues[\\\"y\\\"] = tmp[0]\\n tmp = get_fieldvalues(recid, publication_pages_tag)\\n if tmp:\\n #if the page numbers have \\\"x-y\\\" take just x\\n pages = tmp[0]\\n hpos = pages.find(\\\"-\\\")\\n if hpos > 0:\\n pages = pages[:hpos]\\n tagsvalues[\\\"c\\\"] = pages\\n #format the publ infostring according to the format\\n publ = \\\"\\\"\\n ok = 1\\n for i in range (0, len(publication_format_string)):\\n current = publication_format_string[i]\\n #these are supported\\n if current == \\\"p\\\" or current == \\\"c\\\" or current == \\\"v\\\" \\\\\\n or current == \\\"y\\\":\\n if tagsvalues[current]:\\n #add the value in the string\\n publ += tagsvalues[current]\\n else:\\n ok = 0\\n break #it was needed and not found\\n else:\\n publ += current #just add the character in the format string\\n if ok:\\n write_message(\\\"d_records_s (publication info) for \\\"+str(recid)+\\\" is \\\"+publ, verbose=9)\\n d_records_s[recid] = publ\\n else:\\n mesg = \\\"Warning: there are no records with tag values for \\\"\\n mesg += p_reference_number_tag+\\\" or \\\"+p_reference_tag+\\\". Nothing to do.\\\"\\n write_message(mesg)\\n\\n mesg = \\\"get cit.inf done fully\\\"\\n write_message(mesg)\\n task_update_progress(mesg)\\n\\n citation_informations.append(d_reports_numbers)\\n citation_informations.append(d_references_report_numbers)\\n citation_informations.append(d_references_s)\\n citation_informations.append(d_records_s)\\n end_time = os.times()[4]\\n write_message(\\\"Execution time for generating citation info from record: %.2f sec\\\" % \\\\\\n (end_time - begin_time))\\n return citation_informations\",\n \"def lookup(subjects, target):\\n\\n # regex stuff\\n p = re.compile(\\\"<.*>.* - (.*)</TD>\\\")\\n url = \\\"https://wl11gp.neu.edu/udcprod8/bwckctlg.p_disp_course_detail?cat_term_in=201630&subj_code_in={0}&crse_numb_in={1}\\\"\\n\\n # Get progress bar ready.\\n toolbar_width = len(subjects)\\n sys.stdout.write(\\\"[%s]\\\" % (\\\" \\\" * toolbar_width))\\n sys.stdout.flush()\\n sys.stdout.write(\\\"\\\\b\\\" * (toolbar_width+1)) # return to start of line, after '['\\n\\n # file I/o\\n out = open(target, \\\"w\\\")\\n\\n for subject in subjects:\\n for course_num in subjects[subject]:\\n page = urllib.urlopen(url.format(subject, course_num)).read()\\n match = p.findall(page)\\n if match:\\n out.write(subject + course_num + \\\": \\\" + match[0] + '\\\\n')\\n sys.stdout.write(\\\"-\\\")\\n sys.stdout.flush()\\n\\n sys.stdout.write(\\\"\\\\n\\\")\",\n \"def reference_multi():\\n content = textwrap.dedent(\\\"\\\"\\\"\\n ; Some line before the first molecule.\\n ; Just because.\\n\\n [ molecule ]\\n dummy_0\\n\\n [ atoms ]\\n 0 X1 A\\n 1 X2 B\\n\\n ; Some mess between two molecules.\\n\\n [ molecule ]\\n ; A comment just after the molecule section.\\n dummy_1\\n\\n [ atoms ]\\n 0 X2 C\\n 1 X3 D\\n \\\"\\\"\\\").split('\\\\n')\\n reference = {'universal': {'martini22': {\\n 'dummy_0': (\\n {(0, 'X1'): [(0, 'A')], (0, 'X2'): [(0, 'B')]},\\n {(0, 'A'): {(0, 'X1'): 1.0}, (0, 'B'): {(0, 'X2'): 1.0}},\\n [],\\n ),\\n 'dummy_1': (\\n {(0, 'X2'): [(0, 'C')], (0, 'X3'): [(0, 'D')]},\\n {(0, 'C'): {(0, 'X2'): 1.0}, (0, 'D'): {(0, 'X3'): 1.0}},\\n [],\\n ),\\n }}}\\n return content, reference\",\n \"def populateReference(self, reference_data_folder=None):\\n if reference_data_folder is None:\\n reference_data_folder = os.path.join(\\\"..\\\", \\\"default_data\\\")\\n\\n files = os.listdir(reference_data_folder)\\n\\n reference_tables = []\\n # Create reference table list\\n with self.session_scope() as session:\\n self.setupTabletypeMap()\\n reference_table_objects = self.metaClasses[TableTypes.REFERENCE]\\n for object in list(reference_table_objects):\\n reference_tables.append(object.__tablename__)\\n\\n reference_files = [file for file in files if os.path.splitext(file)[0] in reference_tables]\\n for file in reference_files:\\n # split file into filename and extension\\n table_name, _ = os.path.splitext(file)\\n possible_method = 'addTo' + table_name\\n method_to_call = getattr(self, possible_method, None)\\n if method_to_call:\\n with open(os.path.join(reference_data_folder, file), 'r') as f:\\n reader = csv.reader(f)\\n # skip header\\n _ = next(reader)\\n with self.session_scope() as session:\\n for row in reader:\\n # this solves error of add functions which take one\\n # value instead of list of strings\\n if len(row) == 1:\\n method_to_call(row[0])\\n else:\\n method_to_call(*row)\\n else:\\n print(f\\\"Method({possible_method}) not found!\\\")\",\n \"def create_tables (cls, env=os.environ):\\n\\n cur = cls.pri_table_read_cursor (env=env)\\n cur.execute ('SPECIALCASE gettablelist')\\n ret = cur.fetchall ()\\n \\n existingtables = set ([x[0].lower() for x in ret])\\n\\n for tabname in (set (cls.table_desc.keys ()) - existingtables):\\n sql, lsd = cls.table_desc[tabname]\\n epls, desls, sqlprefix = lsd.get_create_labeling (savels=True)\\n\\n conn = get_labeled_conn (epls, desls)\\n cur = conn.cursor ()\\n cur.execute (sql)\\n conn.close ()\\n lsd.pop_labelset ()\\n\\n \\n import psycopg2\\n for sql in cls.sql_createindex:\\n conn = get_labeled_conn ()\\n cur = conn.cursor ()\\n # XXX It would be better to check which indices exist as we do for tables.\\n try:\\n cur.execute (sql)\\n except psycopg2.ProgrammingError, e: \\n pass\\n conn.close ()\",\n \"def load_data(data_links_list=(\\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\\n '/raw_data/raw_data.csv',\\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\\n '/raw_data/sample_meta_info.tsv')):\\n\\n # Reading data sets from the links provided.\\n df1 = pd.read_csv(data_links_list[0],\\n error_bad_lines=False)\\n df2 = pd.read_csv(data_links_list[1],\\n sep='\\\\t')\\n df2 = df2.set_index(df2['project'])\\n # fill the Nas id df1 as \\\". Makes the groupbys behave better.\\n df1.fillna('', inplace=True)\\n # repleace 'genus' = 'other' with an empty string to be consistent.\\n df1.replace(to_replace='other', value='', inplace=True)\\n # Removing duplicate columns.\\n del df2['project']\\n del df2['ID']\\n df1 = df1.set_index(df1['project'])\\n # Removing duplicate column.\\n del df1['project']\\n # Joining the two datasets.\\n df = df1.join(df2)\\n # Uniformity in non-capitalization of column names.\\n df.rename(columns={'Kingdom': 'kingdom', 'Phylum': 'phylum',\\n 'Class': 'class', 'Order': 'order',\\n 'Family': 'family', 'Genus': 'genus',\\n 'Length': 'length'}, inplace=True)\\n df.index.names = ['sampleID']\\n # Rearranging columns so that abundance is the last column.\\n df = df[['kingdom',\\t'phylum', 'class', 'order',\\n 'family', 'genus', 'length', 'oxygen',\\n 'replicate', 'week', 'abundance']]\\n assert isinstance(df, pd.DataFrame)\\n return df\",\n \"def co_table():\\n\\n connection = MongoClient(\\n \\\"mongodb://anshuman264:VJkCopXqbK5smqf0@cluster0-shard-00-00-ouybv.mongodb.net:27017,\\\"\\n \\\"cluster0-shard-00-01-ouybv.mongodb.net:27017,\\\"\\n \\\"cluster0-shard-00-02-ouybv.mongodb.net:27017/co_table?ssl=true&replicaSet=Cluster0-shard-0&authSource\\\"\\n \\\"=admin\\\")\\n\\n collection = connection[DBS_NAME][COLLECTION_NAME]\\n co_occurrences = collection.find_one()\\n co_occurrences = todict(co_occurrences)\\n co_list = list(co_occurrences.items())\\n co_list = sorted(co_list, key=itemgetter(1), reverse=True)\\n print(co_list)\\n labels = ['Word', 'Co-Occurrence']\\n\\n df = pd.DataFrame.from_records(co_list, columns=labels)\\n connection.close()\\n\\n return render_template(\\\"analysis.html\\\", tables=[df.to_html()], titles=['na', 'of Research Articles'])\",\n \"def make_M3LDF_tables(conn, csv_input_dir, Description_Vegetation, DB_LDF):\\n\\n print(\\\"Creating M3LDF DB tables from: %s\\\\n\\\" % csv_input_dir)\\n csv_Canopy_Position_adjust = pd.read_csv(csv_input_dir + 'Canopy_Position_adjust.csv')\\n csv_Description_Class = pd.read_csv(csv_input_dir + 'Description_Class.csv')\\n csv_Description_Vegetation = pd.read_csv(csv_input_dir + Description_Vegetation)\\n csv_Description_Compounds = pd.read_csv(csv_input_dir + 'Description_Compounds.csv')\\n csv_Description_References = pd.read_csv(csv_input_dir + 'Description_References.csv')\\n csv_DB_LDF = pd.read_csv(csv_input_dir + DB_LDF)\\n\\n csv_Canopy_Position_adjust.to_sql(\\\"Canopy Position adjust\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'Canopy Position adjust' Table Loaded from: %s\\\" % csv_input_dir + 'Canopy_Position_adjust.csv')\\n\\n csv_Description_Class.to_sql(\\\"Description Class\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'Description Class' Table Loaded from: %s\\\" % csv_input_dir + 'Description_Class.csv')\\n\\n csv_Description_Vegetation.to_sql(\\\"Description Vegetation\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'Description Vegetation' Table Loaded from: %s\\\" % csv_input_dir + Description_Vegetation)\\n\\n csv_Description_Compounds.to_sql(\\\"Description Compounds\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'Description Compounds' Table Loaded from: %s\\\" % csv_input_dir + 'Description_Compounds.csv')\\n\\n csv_Description_References.to_sql(\\\"Description References\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'Description References' Table Loaded from: %s\\\" % csv_input_dir + 'Description_References.csv')\\n\\n csv_DB_LDF.to_sql(\\\"DB LDF\\\", conn, flavor='sqlite', if_exists='replace')\\n print(\\\"'DB LDF' Table Loaded from: %s\\\" % csv_input_dir + DB_LDF)\",\n \"def create_table(build_list):\\n # extract list of files:\\n all_files = build_list.split(',')\\n\\n output_file = os.getcwd() + \\\"/fpkm_table.tbl\\\"\\n verbalise(\\\"B\\\", \\\"saving built table to file \\\", output_file)\\n\\n awk_cmd = \\\"\\\"\\\"awk '!($10~/FPKM/){\\\\\\n gene_sample[$1,FILENAME]=$9;\\\\\\n samples[FILENAME]=1;genes[$1]=1}\\\\\\n END{printf \\\"%s\\\\t\\\", \\\"genes\\\";\\\\\\n for(g in genes){printf \\\"%s\\\\t\\\", g};print \\\"\\\";\\\\\\n for(s in samples){printf \\\"%s\\\\t\\\",s;\\\\\\n for(g in genes){printf \\\"%s\\\\t\\\", gene_sample[g,s]};\\\\\\n print \\\"\\\"}}' \\\"\\\"\\\"\\n\\n full_cmd = awk_cmd + \\\" \\\".join(all_files) + \\\">\\\" + str(output_file)\\n\\n # build table:\\n os.system(full_cmd)\\n\\n # shorten filenames within table for easier reading!\\n #output\\n\\n return output_file\",\n \"def main():\\n files = init.file_list\\n citations = load_citations.load_files(files)\\n citations_a = citations[0]\\n citations_b = citations[1]\\n\\n common_citations, num_common = compare_citations.common_citations(citations_a, citations_b)\\n save_citations.save_citations(common_citations)\",\n \"def generate_ref_sheet(output_path):\\r\\n #header of reference sheet\\r\\n ref_out = Path(output_path)\\r\\n reference_elements=[]\\r\\n title = Paragraph('Validation Reference Sheet', style=styles['title'])\\r\\n reference_elements.append(title)\\r\\n\\r\\n #creating table with properties of metric scores\\r\\n metric_ref = (['Metrics Reference Table','','',''],\\r\\n ['Name', 'Attribute','Range','Perfect Score'],\\r\\n ['Percent Correct','Accuracy','0 to 1', '1'],\\r\\n ['Bias','Bias','0 to infinity','1'],\\r\\n ['Hit Rate','Discrimination','0 to 1','1'],\\r\\n ['False Alarm Rate','Discrimination','0 to 1', '0'],\\r\\n ['Frequency of Misses','Discrimination','0 to 1','0'],\\r\\n ['Probability of Correct Negatives','Discrimination',\\r\\n '0 to 1','1'],\\r\\n ['Frequency of Hits','Reliability and Resolution',\\r\\n '0 to 1','1'],\\r\\n ['False Alarm Ratio','Reliability and Resolution',\\r\\n '0 to 1','1'],\\r\\n ['Detection Failure Ratio','Reliability and Resolution',\\r\\n '0 to 1','0'],\\r\\n ['Frequency of Correct Negatives',\\r\\n 'Reliability and Resolution','0 to 1','1'],\\r\\n ['Threat Score','Accuracy','0 to 1','1'],\\r\\n ['Odds Ratio','Accuracy','0 to infinity','infinity'],\\r\\n ['Skill Scores','','',''],\\r\\n ['True Skill Score','','-1 to 1','1'],\\r\\n ['Heidke Skill Score','','-1 to 1','1'],\\r\\n ['Odds Ratio Skill Score','','-1 to 1','1'],\\r\\n ['Relative Operating Characteristic Skill Score (RSS)','',\\r\\n '0 to 1','1'],\\r\\n ['Mean Percentage Error','','-infinity to infinity','0'],\\r\\n ['Mean Absolute Percentage Error','','0 to infinity','0'])\\r\\n\\r\\n metric_ref_table=Table(metric_ref)\\r\\n metric_ref_table.setStyle(TableStyle([('BACKGROUND',(0,2),(3,13),\\r\\n colors.lightgrey),\\r\\n ('BACKGROUND',(0,15),(3,20),\\r\\n colors.lightgrey),\\r\\n ('GRID',(0,1),(3,20),0.25,\\r\\n colors.black),\\r\\n ('SPAN',(0,0),(3,0)),\\r\\n ('SPAN',(0,14),(3,14)),\\r\\n ('SPAN',(0,15),(1,15)),\\r\\n ('SPAN',(0,16),(1,16)),\\r\\n ('SPAN',(0,17),(1,17)),\\r\\n ('SPAN',(0,18),(1,18)),\\r\\n ('SPAN',(0,19),(1,19)),\\r\\n ('SPAN',(0,20),(1,20))]))\\r\\n\\r\\n #writing report\\r\\n reference_elements.append(metric_ref_table)\\r\\n\\r\\n reference = SimpleDocTemplate(str(ref_out / 'validation_reference.pdf'),\\r\\n pagesize=letter)\\r\\n reference.build(reference_elements)\",\n \"def create_reference(filename):\\n contigs = {}\\n with open(filename, \\\"r\\\") as f:\\n header = \\\"\\\"\\n seq = \\\"\\\"\\n for line in f:\\n if line[0] == \\\">\\\":\\n if header:\\n contigs[header] = seq\\n header = line[1:].rstrip()\\n seq = \\\"\\\"\\n else:\\n seq += line.rstrip()\\n\\n return contigs\",\n \"def generate_commit_table(start_ref, end_ref):\\r\\n header = \\\"|| Author || Summary || Commit || JIRA || Verified? ||\\\"\\r\\n commit_link = \\\"[commit|https://github.com/edx/edx-platform/commit/{sha}]\\\"\\r\\n rows = [header]\\r\\n commits = get_commits_not_in_prs(start_ref, end_ref)\\r\\n for commit in commits:\\r\\n rows.append(\\\"| {author} | {summary} | {commit} | {jira} | {verified} |\\\".format(\\r\\n author=commit.author.email,\\r\\n summary=commit.summary.replace(\\\"|\\\", \\\"\\\\|\\\"),\\r\\n commit=commit_link.format(sha=commit.hexsha),\\r\\n jira=\\\", \\\".join(parse_ticket_references(commit.message)),\\r\\n verified=\\\"\\\",\\r\\n ))\\r\\n return \\\"\\\\n\\\".join(rows)\",\n \"def getBibTeX(bibref,tag_suf,outFile):\\n if bibref == '1988iras....1.....B':\\n bibtex = ['>@article{1988iras....1.....B,\\\\n',\\n ' title={Infrared astronomical satellite (IRAS) catalogs and atlases. Volume 1: Explanatory supplement},\\\\n',\\n ' keywords = {All Sky Photography, Catalogs, Indexes (Documentation), Infrared Astronomy Satellite, Cosmology, Galaxies, Star Formation, Stellar Evolution, Astrophysics},\\\\n',\\n ' author={Beichman, CA and Neugebauer, G and Habing, HJ and Clegg, PE and Chester, Thomas J},\\\\n',\\n ' year=1988,\\\\n',\\n ' volume = {1},\\\\n', \\n ' month = jan,\\\\n', \\n ' adsurl = {https://ui.adsabs.harvard.edu/abs/1988iras....1.....B},\\\\n'\\n '}\\\\n']\\n else:\\n baseURL = 'https://ui.adsabs.harvard.edu/abs/'\\n suf = '/exportcitation'\\n lines = urllib.request.urlopen(baseURL+bibref+suf).readlines()\\n lines = [l.decode('utf-8') for l in lines] # remove additional webpage encoding\\n \\n bibtex = []\\n for l in range(0, len(lines)):\\n if 'export-textarea ' in str(lines[l]):\\n bibtex.append(str(lines[l]))\\n t = l+1\\n \\n while '</textarea>' not in str(lines[t+1]):\\n bibtex.append(str(lines[t])) \\n t += 1\\n \\n for item in bibtex:\\n if 'author' in item.split('=')[0]:\\n auth = item.split('=')[1].split(',')[0]\\n for i in string.punctuation:\\n auth = auth.replace(i, '')\\n auth = auth.replace(' ', '')\\n if 'year' in item.split('=')[0]:\\n yr = item.split('=')[1].split(',')[0]\\n yr = yr.replace(' ', '')\\n \\n try:\\n bibtex[0] = bibtex[0].split('>')[1].split('{')[0]+'{'+auth+yr+tag_suf+',\\\\n'\\n except UnboundLocalError as ule:\\n print(bibtex)\\n print('')\\n print(ule)\\n sys.exit()\\n \\n with open(outFile, 'a') as o:\\n for item in bibtex:\\n item = item.replace('"', '\\\"')\\n item = item.replace(''', \\\"'\\\")\\n item = item.replace('&', \\\"&\\\")\\n o.write(item)\\n o.write('\\\\n')\\n \\n return auth+yr+tag_suf\",\n \"def print_output(data,alignments,file):\\n print(\\\"######################################################################\\\")\\n print(\\\"Task 1 : IBM model 1 and EM algorithm implementation ,with corpus @\\\",file)\\n print(\\\"######################################################################\\\")\\n\\n for i in range(len(data)):\\n print(\\\"English Sentence : \\\",data[i][\\\"en\\\"])\\n print(\\\"Foreign Sentence : \\\",data[i][\\\"fr\\\"])\\n print(\\\"Alignment : \\\",alignments[i])\\n print(\\\"----------------------------------------------------------------------\\\")\",\n \"def make_table(ranked_means):\\n fp = open(\\\"table.tex\\\", \\\"w\\\")\\n fp.write(\\\"\\\"\\\"\\\\\\\\begin{tabular}{|l|c||l|c|}\\n \\\\\\\\hline\\n \\\\\\\\multicolumn{2}{|c||}{Slowest} & \\\\\\\\multicolumn{2}{|c|}{Fastest} \\\\\\\\\\\\\\\\ \\\\\\\\hline\\n Feature & Rate & Feature & Rate \\\\\\\\\\\\\\\\ \\\\\\\\hline\\n\\\"\\\"\\\")\\n top_10 = ranked_means[0:10]\\n bottom_10 = ranked_means[-10:]\\n for ((f_rate, f_name),(s_rate,s_name)) in zip(top_10, bottom_10):\\n f_name = f_name.split(\\\":\\\")[-1]\\n f_name = f_name.rsplit(\\\" \\\", 1)[0] if f_name.endswith(\\\"(V)\\\") else f_name\\n s_name = s_name.split(\\\":\\\")[-1]\\n s_name = s_name.rsplit(\\\" \\\", 1)[0] if s_name.endswith(\\\"(V)\\\") else s_name\\n fp.write(\\\" %s & %.2f & %s & %.2f \\\\\\\\\\\\\\\\ \\\\n\\\" % \\\\\\n (f_name, f_rate, s_name, s_rate))\\n fp.write(\\\"\\\\\\\\hline\\\\n\\\")\\n fp.write(\\\"\\\\\\\\end{tabular}\\\\n\\\")\\n fp.close()\\n\\n fp = open(\\\"supp_meaning_table.tex\\\", \\\"w\\\")\\n fp.write(\\\"\\\"\\\"\\\\\\\\begin{tabular}{|l|c||l|c||l|c||l|c|}\\n \\\\\\\\hline\\n Meaning & Category & Meaning & Category & Meaning & Category & Meaning & Category\\\\\\\\\\\\\\\\ \\\\\\\\hline\\n\\n\\\"\\\"\\\")\\n feature_names = [f.split(\\\":\\\")[-1] for (r,f) in ranked_means]\\n feature_names.sort(key=lambda s: s.lower())\\n col1 = feature_names[0:25]\\n col2 = feature_names[25:50]\\n col3 = feature_names[50:75]\\n col4 = feature_names[75:]\\n for a,b,c,d in zip(col1,col2,col3,col4):\\n x,y,z,w = [get_meaning_category(i) or \\\"Excluded\\\" for i in (a,b,c,d)]\\n # Lop off (V)s (we needed them above for get_meaning_category to work)\\n a,b,c,d = [f.rsplit(\\\" \\\", 1)[0] if f.endswith(\\\"(V)\\\") else f for f in (a,b,c,d)]\\n fp.write(\\\"%s & %s & %s & %s & %s & %s & %s & %s\\\\\\\\\\\\\\\\ \\\\n\\\" % (a, x, b, y, c, z, d, w))\\n fp.write(\\\"\\\\\\\\hline\\\\n\\\")\\n fp.write(\\\"\\\\\\\\end{tabular}\\\\n\\\")\\n fp.close()\",\n \"def populate_db():\\n stdout.write('Emptying the tables...\\\\n')\\n empty_tables()\\n stdout.write('Populating Language records...\\\\n')\\n populate_language()\\n stdout.write('Populating Lemma, Wordform, and Definition records...\\\\n')\\n populate_lexical()\\n stdout.write('Populating ProperName records...\\\\n')\\n populate_proper_names()\",\n \"def create_database_and_add_model(models,database):\\n conn =sqlite3.connect(database)\\n for model in models:\\n mod_tab_name = model.replace('-','_')\\n sql_create_projects_table = \\\"\\\"\\\" CREATE TABLE IF NOT EXISTS %s (\\n case_var text NOT NULL PRIMARY KEY,\\n model_case text NOT NULL,\\n var text NOT NULL,\\n case_name text NOT NULL,\\n original_var_name text,\\n units text ,\\n units_original text,\\n lev_is_dim integer NOT NULL,\\n is_computed_var integer,\\n path_computed_data text,\\n pressure_coordinate_path text\\n ); \\\"\\\"\\\"%(mod_tab_name)\\n\\n # create a database connection\\n if conn is not None:\\n # create projects table\\n create_table(conn, sql_create_projects_table)\\n else:\\n print(\\\"Error! cannot create the database connection.\\\")\\n conn.close()\\n return\",\n \"def insert_mbifields(config,doctype,inst):\\n\\t\\n\\tdocname = get_docname_from_schema(doctype,config)\\n\\tfieldtext = '<table width=\\\"100%\\\" bgcolor=\\\"#99CC00\\\" align=\\\"center\\\" cellspacing=\\\"2\\\" cellpadding=\\\"2\\\" border=\\\"1\\\"><tr><td align=\\\"left\\\"><br /><b>Modify a docname bibliographic information:</b><br /><br /><span style=\\\"color: red;\\\">*</span>Reference Number: '\\n\\tfieldtext = fieldtext.replace(\\\"docname\\\",docname)\\n\\tfieldlevel = \\\"O\\\"\\n\\taction = \\\"MBI\\\"\\n\\tpagenum = \\\"1\\\"\\n\\tfieldname = \\\"rn\\\"\\n\\tfieldshortdesc = fieldname.replace(\\\"hgf_\\\",\\\"\\\")\\n\\tfieldcheck = \\\"\\\"\\n\\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\\t\\n\\t\\n\\t## hgf_change\\n\\tselect_box = '<select visibility=\\\"hidden\\\" name=\\\"mod_%s[]\\\" size=\\\"1\\\"><option value=\\\"Select:\\\">Please click continue:</option></select>' %doctype #fake selectbox\\n\\telname = \\\"mod_\\\" + doctype\\n\\telmarccode = \\\"\\\"\\n\\teltype = \\\"S\\\"\\n\\telsize = \\\"\\\"\\n\\telrows = \\\"\\\"\\n\\telcols = \\\"\\\"\\n\\telmaxlength = \\\"\\\"\\n\\telval = \\\"\\\"\\n\\telfidesc = select_box # select box for modification form\\n\\telmodifytext = \\\"\\\"\\n\\tinsert_element_details(elname, elmarccode, eltype, elsize, elrows, elcols, elmaxlength, elval, elfidesc, elmodifytext) # inserrt into sbmFIELDDESCR\\n\\t\\n\\t\\n\\tfieldtext = ''\\n\\tfieldlevel = \\\"O\\\"\\n\\taction = \\\"MBI\\\"\\n\\tpagenum = \\\"1\\\"\\n\\tfieldname = elname\\n\\tfieldshortdesc = elname.replace(\\\"hgf_\\\",\\\"\\\")\\n\\tfieldcheck = \\\"\\\"\\n\\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\\t\\n\\t\\n\\t#mbi_end \\n\\tfieldtext = '<br /><br /></td></tr></table><br />'\\n\\tfieldlevel = \\\"O\\\"\\n\\taction = \\\"MBI\\\"\\n\\tpagenum = \\\"1\\\"\\n\\tfieldname = \\\"mbi_end\\\"\\n\\tfieldshortdesc = fieldname.replace(\\\"hgf_\\\",\\\"\\\")\\n\\tfieldcheck = \\\"\\\"\\n\\tinsert_field_onto_submissionpage(doctype, action, pagenum, fieldname, fieldtext, fieldlevel, fieldshortdesc, fieldcheck) #insert into sbmFIELD\\t\",\n \"def main():\\n args = get_args()\\n str_arg = args.arg\\n int_arg = args.int\\n flag_arg = args.flag\\n #pos_arg = args.positional\\n\\n #read and open the annotations file\\n intpro_dict = {}\\n with open('InterPro_entry_list.tsv') as csvfile:\\n reader = csv.DictReader(csvfile, delimiter='\\\\t')\\n for row in reader:\\n intpro_dict[row['ENTRY_AC']] = row['ENTRY_NAME']\\n\\n with open('model_topics.txt', 'r') as file:\\n model_topics = file.read().replace('\\\\n', '')\\n\\n model_topics = re.sub(\\\"'\\\", \\\"\\\", model_topics)\\n model_topics = re.sub(\\\"\\\\[\\\", \\\"\\\", model_topics)\\n model_topics = re.sub(\\\"\\\\]\\\", \\\"\\\", model_topics)\\n\\n mtl = model_topics.split('), ')\\n\\n with open('output_topics.tsv' ,'w') as f:\\n print('Topic\\\\tModel_coefficient\\\\tInterpro_ID\\\\tInterPro_ENTRY_NAME', file=f)\\n for list in mtl:\\n topic = list[1]\\n split_list = list.split()\\n id_re = re.compile('IPR\\\\d{3}')\\n c_words = []\\n for w in split_list:\\n match = id_re.search(w)\\n if match:\\n c_words.append(w)\\n c_words = [re.sub('\\\"', '', i) for i in c_words]\\n for w in c_words:\\n re.sub('\\\\)', '', w)\\n coef, intpro = w.split('*')\\n intpro = intpro[:9]\\n\\n if intpro in intpro_dict.keys():\\n label = intpro_dict[intpro]\\n else:\\n label = ''\\n\\n print('{}\\\\t{}\\\\t{}\\\\t{}'.format(topic,coef,intpro,label), file=f)\",\n \"def _create_lookup_tables(self, text):\\n word_counts = Counter(text)\\n sorted_words = sorted(word_counts, key=word_counts.get, reverse=True)\\n vocab_to_int = {word: ii for ii, word in enumerate(sorted_words)}\\n int_to_vocab = {ii: word for ii, word in enumerate(sorted_words)}\\n return (vocab_to_int, int_to_vocab)\",\n \"def fill_table(model_list, field_list, foreign_field_list):\\n out = ''\\n for model in model_list:\\n out += '<tr>'\\n for field in field_list:\\n out += '<td>' + str(model[field]) + '</td>'\\n # for field in foreign_field_list:\\n # attr = model[field]\\n # if attr is not None:\\n # out += '<td>' + '<a href=\\\" + attr + \\\"><div style=\\\"height:100%;width:100%\\\">' + ', '.join([str(i.pk) for i in attr.all()]) + '</td>'\\n out += '</tr>'\\n return mark_safe(out)\",\n \"def associate_related_footnotes(apps, schema_editor):\\n\\n User = apps.get_model(\\\"auth\\\", \\\"User\\\")\\n Annotation = apps.get_model(\\\"annotations\\\", \\\"Annotation\\\")\\n ContentType = apps.get_model(\\\"contenttypes\\\", \\\"ContentType\\\")\\n Document = apps.get_model(\\\"corpus\\\", \\\"Document\\\")\\n Footnote = apps.get_model(\\\"footnotes\\\", \\\"Footnote\\\")\\n Source = apps.get_model(\\\"footnotes\\\", \\\"Source\\\")\\n LogEntry = apps.get_model(\\\"admin\\\", \\\"LogEntry\\\")\\n\\n DIGITAL_EDITION = \\\"X\\\"\\n\\n # much of this code adapted from signal handlers and static methods\\n document_contenttype = ContentType.objects.get_for_model(Document)\\n\\n annotations = Annotation.objects.all()\\n for annotation in annotations:\\n # resolve URIs to Source and Document IDs (without using static methods)\\n manifest_uri = (\\n annotation.content.get(\\\"target\\\", {})\\n .get(\\\"source\\\", {})\\n .get(\\\"partOf\\\", {})\\n .get(\\\"id\\\")\\n )\\n source_uri = annotation.content.get(\\\"dc:source\\\")\\n source_id = int(source_uri.split(\\\"/\\\")[-2])\\n try:\\n document_id = document_id_from_manifest_uri(manifest_uri)\\n except Resolver404:\\n continue\\n try:\\n # try to get a DIGITAL_EDITION footnote for this source and document\\n footnote = Footnote.objects.get(\\n doc_relation__contains=DIGITAL_EDITION,\\n source__pk=source_id,\\n content_type=document_contenttype,\\n object_id=document_id,\\n )\\n except Footnote.DoesNotExist:\\n # create the DIGITAL_EDITION footnote\\n source = Source.objects.get(pk=source_id)\\n footnote = Footnote.objects.create(\\n source=source,\\n doc_relation=[DIGITAL_EDITION],\\n object_id=document_id,\\n content_type=document_contenttype,\\n )\\n LogEntry.objects.log_action(\\n user_id=User.objects.get(username=settings.SCRIPT_USERNAME).id,\\n content_type_id=ContentType.objects.get_for_model(Footnote).pk,\\n object_id=footnote.pk,\\n object_repr=str(footnote),\\n action_flag=ADDITION,\\n change_message=\\\"Footnote automatically created via annotation migration.\\\",\\n )\\n\\n # instantiate the FK relation\\n annotation.footnote = footnote\\n\\n # remove the existing manifest and source URIs from annotation content field\\n del annotation.content[\\\"dc:source\\\"]\\n del annotation.content[\\\"target\\\"][\\\"source\\\"][\\\"partOf\\\"]\\n\\n # save all FK relations and content fields\\n Annotation.objects.bulk_update(annotations, [\\\"content\\\", \\\"footnote\\\"])\",\n \"def populate_db(database, annot_name, chrom_genes, chrom_transcripts, edges, genome_build):\\n # Connecting to the database file\\n conn = sqlite3.connect(database)\\n c = conn.cursor()\\n\\n for chromosome in chrom_genes.keys():\\n start_time = time.time()\\n print(chromosome)\\n genes = chrom_genes[chromosome]\\n transcripts = chrom_transcripts[chromosome] \\n\\n gene_id_map = add_genes(c, genes, annot_name)\\n add_transcripts(c, transcripts, annot_name, gene_id_map, genome_build)\\n\\n conn.commit()\\n end_time = time.time()\\n print(\\\"It took {} to process chromosome\\\".format(hms_string(end_time - start_time)))\\n conn.close()\\n \\n return\",\n \"def build_index(self):\\r\\n date_time('Building indexes in citations table')\\r\\n self.cursor.execute('DROP INDEX IF EXISTS IDX_citations ;')\\r\\n self.cursor.execute('CREATE INDEX IDX_citations ON citations (citation);')\\r\\n self.conn.commit()\\r\\n gc.collect()\",\n \"def _get_references_data(wit_path):\\n\\n with open(os.path.join(wit_path, '.wit', 'references.txt'), 'r') as data:\\n info = {'None': 'None'}\\n info.update({'HEAD': data.readline().split('=')[-1].strip('\\\\n')})\\n info.update({'master': data.readline().split('=')[-1].strip('\\\\n')})\\n for row in data.readlines():\\n name, commit_id = row.split('=')\\n info.update({name.strip('\\\\n'): commit_id.strip('\\\\n')})\\n\\n return info\",\n \"def start_cfm_jobs(file_dir, db, spec_type, job_template=None,\\n job_comp_number=100, max_mass=1500):\\n if not os.path.exists(file_dir):\\n os.mkdir(file_dir)\\n os.chdir(file_dir)\\n\\n out_file = open(db.name + \\\"_1.txt\\\", \\\"w\\\")\\n i = 1\\n j = 1\\n inchi_set = set()\\n if spec_type == 'pos':\\n search = {\\\"_id\\\": {\\\"$regex\\\": \\\"^C\\\"}, \\\"Mass\\\": {\\\"$lt\\\": max_mass},\\n \\\"Charge\\\": 0, \\\"Pos_CFM_spectra\\\": {\\\"$exists\\\": 0}}\\n elif spec_type == 'neg':\\n search = {\\\"_id\\\": {\\\"$regex\\\": \\\"^C\\\"}, \\\"Mass\\\": {\\\"$lt\\\": max_mass},\\n \\\"Charge\\\": 0, \\\"Neg_CFM_spectra\\\": {\\\"$exists\\\": 0}}\\n elif spec_type == 'ei':\\n search = {\\\"_id\\\": {\\\"$regex\\\": \\\"^C\\\"}, \\\"Mass\\\": {\\\"$lt\\\": max_mass},\\n \\\"Charge\\\": 0, \\\"EI_CFM_spectra\\\": {\\\"$exists\\\": 0}}\\n else:\\n raise ValueError('invalid spectrum spec_type')\\n\\n for compound in db.compounds.find(search, {\\\"SMILES\\\": 1, \\\"Inchikey\\\": 1}):\\n con_block = compound['Inchikey'].split('-')[0]\\n if con_block not in inchi_set:\\n out_file.write(\\\"%s %s\\\\n\\\" % (con_block, compound['SMILES']))\\n i += 1\\n inchi_set.add(con_block)\\n if not i % job_comp_number:\\n out_file.close()\\n j += 1\\n out_file = open(db_name + \\\"_\\\" + str(j) + \\\".txt\\\", 'w')\\n out_file.close()\\n\\n if job_template:\\n # for Quest?\\n # fetch the information from the job template\\n try:\\n infile = open(job_template)\\n except IOError:\\n sys.exit(\\\"Job template file not found\\\")\\n temp_data = infile.readlines()\\n infile.close()\\n\\n for comp_file in os.listdir(\\\".\\\"):\\n if \\\".txt\\\" not in comp_file:\\n continue\\n job_data = deepcopy(temp_data)\\n # edit the job template data for the specific job\\n job_data[1] = \\\"#$ -e logs/cfm_%s.err\\\\n\\\" % (comp_file.strip('.txt'))\\n job_data[2] = \\\"#$ -o logs/cfm_%s.log\\\\n\\\" % (comp_file.strip('.txt'))\\n new_file = file_dir + \\\"/\\\" + comp_file.strip()\\n job_data[11] = job_data[11].replace(\\\"{smile_file}\\\", new_file)\\n\\n # write the specific job file\\n job_file = \\\"cfm_%s.job\\\" % comp_file.strip('.txt')\\n outfile = open(job_file, 'w')\\n outfile.writelines(job_data)\\n outfile.close()\\n rc = call([\\\"qsub\\\", job_file], shell=True)\\n if not rc:\\n os.remove(job_file)\",\n \"def _intermediary_to_markdown(tables, relationships):\\n t = '\\\\n'.join(t.to_markdown() for t in tables)\\n r = '\\\\n'.join(r.to_markdown() for r in relationships)\\n return '{}\\\\n{}'.format(t, r)\",\n \"def __init__(self, fastaRecords, modelFile, modelIterations=-1):\\n\\n self.pre = 10\\n self.post = 4\\n\\n self.pad = 30\\n self.base4 = 4 ** np.array(range(self.pre + self.post + 1))\\n\\n self.refDict = {}\\n self.refLengthDict = {}\\n\\n for contig in fastaRecords:\\n if contig.cmph5ID is None:\\n # This contig has no mapped reads -- skip it\\n continue\\n\\n rawSeq = contig.sequence[:]\\n refSeq = np.fromstring(rawSeq, dtype=byte)\\n\\n # Store the reference length\\n self.refLengthDict[contig.cmph5ID] = len(rawSeq)\\n\\n # Make a shared array\\n sa = SharedArray(dtype='B', shape=len(rawSeq) + self.pad * 2)\\n saWrap = sa.getNumpyWrapper()\\n\\n # Lut Codes convert Ns to As so that we don't put Ns into the Gbm Model\\n # Seq Codes leaves Ns as Ns for getting reference snippets out\\n innerLutCodes = lutCodeMap[refSeq]\\n innerSeqCodes = seqCodeMap[refSeq]\\n innerCodes = np.bitwise_or(innerLutCodes, np.left_shift(innerSeqCodes, 4))\\n\\n saWrap[self.pad:(len(rawSeq) + self.pad)] = innerCodes\\n\\n # Padding codes -- the lut array is padded with 0s the sequence array is padded with N's (4)\\n outerCodes = np.left_shift(np.ones(self.pad, dtype=uint8) * 4, 4)\\n saWrap[0:self.pad] = outerCodes\\n saWrap[(len(rawSeq) + self.pad):(len(rawSeq) + 2 * self.pad)] = outerCodes\\n\\n self.refDict[contig.cmph5ID] = sa\\n\\n # No correction factor for IPDs everything is normalized to 1\\n self.meanIpd = 1\\n\\n # Find and open the ipd model file\\n self.lutPath = modelFile\\n if os.path.exists(self.lutPath):\\n h5File = h5py.File(self.lutPath, mode='r')\\n\\n gbmModelGroup = h5File[\\\"/AllMods_GbmModel\\\"]\\n self.gbmModel = GbmContextModel(gbmModelGroup, modelIterations)\\n\\n # We always use the model -- no more LUTS\\n self.predictIpdFunc = self.predictIpdFuncModel\\n self.predictManyIpdFunc = self.predictManyIpdFuncModel\\n else:\\n logging.info(\\\"Couldn't find model file: %s\\\" % self.lutPath)\",\n \"def compute_applied_name_contexts(citelist: list) -> None:\\n for i, cite in enumerate(citelist):\\n if (cite.context == \\\"specimen\\\") or (cite.context == \\\"location\\\") or (cite.context == \\\"sequence\\\"):\\n cite.applied_cites = {cite}\\n elif cite.context == \\\"citation\\\":\\n for j in range(i): # only look at entries up to the current one\\n tmp = citelist[j]\\n if (tmp.cite_key == cite.application) and match_num_ref(tmp.name_key, cite.cite_n):\\n if (tmp.context == \\\"specimen\\\") or (tmp.context == \\\"location\\\") or (tmp.context == \\\"sequence\\\"):\\n cite.applied_cites |= {tmp}\\n if len(cite.applied_cites) == 0:\\n cite.applied_cites = None\\n\\n # for testing purposes only\\n # if cite.applied_cites is None:\\n # print(cite.cite_key, cite.name_key, cite.context, \\\"No application\\\")\\n # else:\\n # for c in cite.applied_cites:\\n # print(cite.cite_key, cite.name_key, cite.context, c.cite_key, c.name_key, c.context)\\n # input()\",\n \"def feature_table(chr_id, source, orient, genes, transcripts, cds, exons, unk):\\n for gname, ginfo in genes.items():\\n line = [str(chr_id), \\n 'gbk_to_gff',\\n ginfo[3],\\n str(ginfo[0]),\\n str(ginfo[1]),\\n '.',\\n ginfo[2],\\n '.',\\n 'ID='+str(gname)+';Name='+str(gname)+';Note='+ginfo[-1]]\\n print '\\\\t'.join(line) \\n ## construct the transcript line is not defined in the original file \\n t_line = [str(chr_id), 'gbk_to_gff', source, 0, 1, '.', ginfo[2], '.'] \\n\\n if not transcripts:\\n t_line.append('ID=Transcript:'+str(gname)+';Parent='+str(gname))\\n\\n if exons: ## get the entire transcript region from the defined feature\\n t_line[3] = str(exons[gname][0][0])\\n t_line[4] = str(exons[gname][0][-1])\\n elif cds:\\n t_line[3] = str(cds[gname][0][0])\\n t_line[4] = str(cds[gname][0][-1])\\n print '\\\\t'.join(t_line) \\n\\n if exons:\\n exon_line_print(t_line, exons[gname], 'Transcript:'+str(gname), 'exon')\\n\\n if cds:\\n exon_line_print(t_line, cds[gname], 'Transcript:'+str(gname), 'CDS')\\n if not exons:\\n exon_line_print(t_line, cds[gname], 'Transcript:'+str(gname), 'exon')\\n\\n else: ## transcript is defined \\n for idx in transcripts[gname]: \\n t_line[2] = idx[3]\\n t_line[3] = str(idx[0])\\n t_line[4] = str(idx[1])\\n t_line.append('ID='+str(idx[2])+';Parent='+str(gname))\\n print '\\\\t'.join(t_line) \\n \\n ## feature line print call \\n if exons:\\n exon_line_print(t_line, exons[gname], str(idx[2]), 'exon')\\n if cds:\\n exon_line_print(t_line, cds[gname], str(idx[2]), 'CDS')\\n if not exons:\\n exon_line_print(t_line, cds[gname], str(idx[2]), 'exon')\\n\\n if len(genes) == 0: ## feature entry with fragment information \\n \\n line = [str(chr_id), 'gbk_to_gff', source, 0, 1, '.', orient, '.'] \\n fStart = fStop = None \\n\\n for eid, ex in cds.items(): \\n fStart = ex[0][0] \\n fStop = ex[0][-1]\\n\\n for eid, ex in exons.items(): \\n fStart = ex[0][0] \\n fStop = ex[0][-1]\\n\\n if fStart or fStart:\\n\\n line[2] = 'gene'\\n line[3] = str(fStart)\\n line[4] = str(fStop)\\n line.append('ID=Unknown_Gene_' + str(unk) + ';Name=Unknown_Gene_' + str(unk))\\n print \\\"\\\\t\\\".join(line)\\n\\n if not cds:\\n line[2] = 'transcript'\\n else:\\n line[2] = 'mRNA'\\n line[8] = 'ID=Unknown_Transcript_' + str(unk) + ';Parent=Unknown_Gene_' + str(unk)\\n print \\\"\\\\t\\\".join(line)\\n \\n if exons:\\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'exon')\\n \\n if cds:\\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'CDS')\\n if not exons:\\n exon_line_print(line, cds[None], 'Unknown_Transcript_' + str(unk), 'exon')\\n \\n unk +=1 \\n\\n return unk\",\n \"def _prepare_links_table(self):\\n\\n links_tbl = OrderedDict()\\n for colname in itertools.islice(self._pinfos, 1, None):\\n links_tbl[colname] = {}\\n links_tbl[colname][\\\"name\\\"] = f\\\"{colname}\\\"\\n fname = colname.replace(\\\"%\\\", \\\"_pcnt\\\") + \\\".html\\\"\\n links_tbl[colname][\\\"fname\\\"] = fname\\n links_tbl[colname][\\\"hlink\\\"] = f\\\"<a href=\\\\\\\"{fname}\\\\\\\">{colname}</a>\\\"\\n\\n return links_tbl\",\n \"def writeIssnTables(outDir, pubIds, pubToIssn, issnOverwrite):\\n outFhDict = {}\\n\\n # prep the lookup table\\n pubIdToDescs = {}\\n for pubDesc, pubId in pubIds.iteritems():\\n pubIdToDescs.setdefault(pubId, []).append(pubDesc)\\n\\n # outDir has to be identical to the pubId from pubConf\\n pubId = basename(outDir)\\n\\n issnOutFname = join(outDir, ISSNTAB)\\n\\n if not isdir(outDir):\\n logging.info(\\\"Creating dir %s\\\" % outDir)\\n os.makedirs(outDir)\\n\\n # lookup Issns for publisher description\\n # write default ISSNs\\n logging.info(\\\"Writing to %s\\\" % issnOutFname)\\n if issnOutFname not in outFhDict:\\n outFh = open(issnOutFname, \\\"w\\\")\\n outFh.write(\\\"issn\\\\tjournal\\\\tstartYear\\\\tendYear\\\\tpublisher\\\\n\\\")\\n outFhDict[issnOutFname] = outFh\\n else:\\n outFh = outFhDict[issnOutFname]\\n\\n # now output ISSNs\\n issnCount = 0\\n for pubDesc in pubIdToDescs[pubId]:\\n logging.debug(\\\"Found %d issns for publisher %s\\\" % (len(pubToIssn[pubDesc]), pubId))\\n for issn, title in pubToIssn[pubDesc]:\\n logging.info(\\\"Title: %s, print ISSN %s\\\" % (title, issn))\\n if issn==\\\"\\\":\\n continue\\n line = \\\"%(issn)s\\\\t%(title)s\\\\t0\\\\t0\\\\t%(pubDesc)s\\\\n\\\" % locals()\\n # some journal names contain unicode, we just strip it here\\n outFh.write(unidecode.unidecode(line))\\n issnCount+=1\\n\\n # add manual ISSNs\\n for issn, startYear, endYear in issnOverwrite.get(pubId, []):\\n outFh.write(\\\"%s\\\\t%d\\\\t%d\\\\t%s\\\\n\\\" % (issn, startYear, endYear, pubName))\\n issnCount+=1\\n logging.info(\\\"Wrote %d ISSNs\\\" % issnCount)\",\n \"def write_latex_table(machine, all_benchs, summary, diff, skipped, tex_file, num_splits,\\n with_preamble=False, longtable=False, diff_vms=[]):\\n\\n num_benchmarks = len(all_benchs)\\n all_vms = sorted(summary.keys())\\n num_vms = len(summary)\\n\\n # decide how to lay out the splits\\n num_vms_rounded = int(math.ceil(num_vms / float(num_splits)) * num_splits)\\n vms_per_split = int(num_vms_rounded / float(num_splits))\\n splits = [[] for x in xrange(num_splits)]\\n vm_num = 0\\n split_idx = 0\\n for vm_idx in xrange(num_vms_rounded):\\n if vm_idx < len(all_vms):\\n vm = all_vms[vm_idx]\\n else:\\n vm = None\\n splits[split_idx].append(vm)\\n vm_num += 1\\n if vm_num % vms_per_split == 0:\\n split_idx += 1\\n\\n with open(tex_file, 'w') as fp:\\n if with_preamble:\\n fp.write(preamble(TITLE))\\n if diff_vms:\\n fp.write('\\\\\\\\centering{%%\\\\n\\\\\\\\Large{\\\\\\\\textbf{%s vs. %s}}%%\\\\n}\\\\n\\\\\\\\\\\\\\\\\\\\n~\\\\\\\\\\\\\\\\\\\\n\\\\n'\\n % (diff_vms[0], diff_vms[1]))\\n legends = get_latex_symbol_map() + ' \\\\\\\\\\\\\\\\ ' + legend()\\n fp.write('\\\\\\\\centering %s' % legends)\\n fp.write('\\\\n\\\\n\\\\n')\\n if not longtable:\\n fp.write('\\\\\\\\begin{landscape}\\\\n')\\n fp.write('\\\\\\\\begin{table*}[hptb]\\\\n')\\n fp.write('\\\\\\\\vspace{.8cm}\\\\n')\\n fp.write('\\\\\\\\begin{adjustbox}{totalheight=12.4cm}\\\\n')\\n # Emit table header.\\n heads1 = TABLE_HEADINGS_START1 + '&'.join([TABLE_HEADINGS1] * num_splits)\\n heads2 = TABLE_HEADINGS_START2 + '&'.join([TABLE_HEADINGS2] * num_splits)\\n heads = '%s\\\\\\\\\\\\\\\\%s' % (heads1, heads2)\\n if longtable:\\n fp.write(start_longtable(TABLE_FORMAT, heads))\\n else:\\n fp.write(start_table(TABLE_FORMAT, heads))\\n split_row_idx = 0\\n for row_vms in zip(*splits):\\n bench_idx = 0\\n skipped_before = [b for (b, v) in skipped[SKIPPED_BEFORE] if v == row_vms[0]]\\n skipped_after = [b for (b, v) in skipped[SKIPPED_AFTER] if v == row_vms[0]]\\n for bench in sorted(all_benchs + skipped_before + skipped_after):\\n row = []\\n for vm in row_vms:\\n if vm is None:\\n continue # no more results\\n try:\\n this_summary = summary[vm][bench]\\n except KeyError:\\n if bench in skipped_before or bench in skipped_after:\\n classification = '\\\\\\\\emph{Skipped}'\\n else:\\n classification = ''\\n last_cpt = BLANK_CELL\\n time_steady = BLANK_CELL\\n last_mean = BLANK_CELL\\n steady_iter_var = BLANK_CELL\\n steady_time_var = BLANK_CELL\\n else:\\n if vm in diff and bench in diff[vm]:\\n classification = colour_tex_cell(diff[vm][bench][CLASSIFICATIONS], this_summary['style'])\\n last_cpt = colour_tex_cell(diff[vm][bench][STEADY_ITER], this_summary['last_cpt'])\\n steady_iter_var = colour_tex_cell(diff[vm][bench][STEADY_ITER_VAR], this_summary['steady_iter_var'])\\n time_steady = colour_tex_cell(diff[vm][bench][STEADY_ITER], this_summary['time_to_steady_state'])\\n last_mean = colour_tex_cell(diff[vm][bench][STEADY_STATE_TIME], this_summary['last_mean'])\\n steady_time_var = colour_tex_cell(diff[vm][bench][STEADY_STATE_TIME_VAR], this_summary['steady_time_var'])\\n else:\\n classification = this_summary['style']\\n last_cpt = this_summary['last_cpt']\\n steady_iter_var = this_summary['steady_iter_var']\\n time_steady = this_summary['time_to_steady_state']\\n last_mean = this_summary['last_mean']\\n steady_time_var = this_summary['steady_time_var']\\n classification = '\\\\\\\\multicolumn{1}{l}{%s}' % classification\\n if classification == STYLE_SYMBOLS['flat']:\\n last_cpt = BLANK_CELL\\n time_steady = BLANK_CELL\\n if last_cpt == '':\\n last_cpt = BLANK_CELL\\n if time_steady == '':\\n time_steady = BLANK_CELL\\n if last_mean == '':\\n last_mean = BLANK_CELL\\n\\n if bench_idx == 0:\\n if num_benchmarks == 10:\\n fudge = 4\\n elif num_benchmarks == 12:\\n fudge = 5\\n else:\\n fudge = 0\\n vm_cell = '\\\\\\\\multirow{%s}{*}{\\\\\\\\rotatebox[origin=c]{90}{%s}}' \\\\\\n % (num_benchmarks + fudge, vm)\\n else:\\n vm_cell = ''\\n row_add = [BLANK_CELL, vm_cell, classification, last_cpt,\\n steady_iter_var, time_steady, last_mean, steady_time_var]\\n if not row: # First bench in this row, needs the vm column.\\n if vm in diff and bench in diff[vm]:\\n bname = colour_tex_cell(diff[vm][bench][INTERSECTION], bench)\\n else:\\n bname = bench\\n row.insert(0, escape(bname))\\n row.extend(row_add)\\n vm_idx += 1\\n fp.write('&'.join(row))\\n # Only -ve space row if not next to a midrule\\n if not longtable and bench_idx < num_vms - 1:\\n fp.write('\\\\\\\\\\\\\\\\[-3pt] \\\\n')\\n else:\\n fp.write('\\\\\\\\\\\\\\\\ \\\\n')\\n bench_idx += 1\\n if split_row_idx < vms_per_split - 1:\\n if longtable:\\n fp.write('\\\\\\\\hline\\\\n')\\n else:\\n fp.write('\\\\\\\\midrule\\\\n')\\n split_row_idx += 1\\n if longtable:\\n fp.write(end_longtable())\\n else:\\n fp.write(end_table())\\n if with_preamble:\\n if not longtable:\\n fp.write('\\\\\\\\end{adjustbox}\\\\n')\\n fp.write('\\\\\\\\end{table*}\\\\n')\\n fp.write('\\\\\\\\end{landscape}\\\\n')\\n fp.write(end_document())\",\n \"def create_convergence_table(initial_condition, flux):\\n\\n group_path = initial_condition + \\\"/\\\" + flux \\n \\n error_norms = error_norms_data(*group_path.split(\\\"/\\\"))\\n\\n# Return a formatted string containing convergence information for the given grid resolution \\n def convergence_row(k): \\n return \\\"{k:^3} {M:^10} {h:^15.10f} {sup_norm:^15.10f} {sup_norm_rate:^5.2f} {one_norm:^15.10f} {one_norm_rate:^5.2f} {two_norm:^15.10f} {two_norm_rate:^5.2f}\\\".format(**convergence_table_row_data(k, error_norms))\\n\\n# Formatted string containing the text of the header of the table\\n header = \\\"{k:^3} {M:^10} {h:^15} {sup_norm:^15} {sup_norm_rate:^5} {one_norm:^15} {one_norm_rate:^5} {two_norm:^15} {two_norm_rate:^5}\\\".format(**convergence_table_header_data)\\n\\n# Formatted string containing the attributes of the computation\\n closing = \\\"Speed: {a_text:>12} {a} \\\\nCFL Number: sigma = {CFL} \\\\nOutput Time: {T_text:>6} {T}\\\".format(\\n a_text = \\\"a =\\\",\\n T_text = \\\"T =\\\",\\n **computation_attributes(*group_path.split(\\\"/\\\"))\\n )\\n\\n# Write the table to a text file \\n output_text_table_file = open(html_path + \\\"convergence_tables/\\\" + group_path.replace(\\\"/\\\", \\\"_\\\") + \\\".txt\\\", \\\"w\\\") \\n output_text_table_file.write(header + \\\"\\\\n\\\\n\\\")\\n for k in range(7, 17):\\n output_text_table_file.write(convergence_row(k) + \\\"\\\\n\\\")\\n output_text_table_file.write(\\\"\\\\n\\\" + closing)\"\n]","isConversational":false},"negative_scores":{"kind":"list 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purposes, we do not remove the outputs, which is why this is NOtearDown. If you really want to use this for unit tests, rename to tearDown."},"document":{"kind":"string","value":"def NOtearDown(self):\n\n for f in self.testoutput:\n if os.path.exists(f):\n os.remove(f)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def tearDown(self):\n print('Calling \\'tearDown\\'')","def tearDown(self):\n self.logger.info(\"tearDown begin\")\n self.logger.info(\"tearDown end\\n\")","def tearDown(self):\n pass\n # teardown called after each test\n # e.g. maybe write test results to some text file","def tearDown(self) -> None:\n pass","def tearDown(self) -> None:\n pass","def tearDown(self) -> None:\n pass","def tearDown(self):\n if not self.test_manager.leave_output:\n shutil.rmtree(self.directory)","def tearDown(self):\n\t\tprint(\"end test\")\n\t\tpass","def XXtearDown(self):\n print(\"FooTest:tearDown_:begin\")\n ## do something...\n print(\"FooTest:tearDown_:end\")","def XXtearDown(self):\n print(\"FooTest:tearDown_:begin\")\n ## do something...\n print(\"FooTest:tearDown_:end\")","def tearDown(self):\n pass #because we dont have anything to tearDown.","def tearDown(self) :\n pass","def tearDown(self) :\n pass","def tearDown(self) :\n pass","def tearDown(self):\n print('tearDown method\\n')","def tearDown(self):\n \n return","def tearDown(self):\n\t\tpass","def tearDown(self):\r\n testing.tearDown()","def tearDown(self):\n print 'unittest.tearDown()'\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass","def tearDown(self):\n pass"],"string":"[\n \"def tearDown(self):\\n print('Calling \\\\'tearDown\\\\'')\",\n \"def tearDown(self):\\n self.logger.info(\\\"tearDown begin\\\")\\n self.logger.info(\\\"tearDown end\\\\n\\\")\",\n \"def tearDown(self):\\n pass\\n # teardown called after each test\\n # e.g. maybe write test results to some text file\",\n \"def tearDown(self) -> None:\\n pass\",\n \"def tearDown(self) -> None:\\n pass\",\n \"def tearDown(self) -> None:\\n pass\",\n \"def tearDown(self):\\n if not self.test_manager.leave_output:\\n shutil.rmtree(self.directory)\",\n \"def tearDown(self):\\n\\t\\tprint(\\\"end test\\\")\\n\\t\\tpass\",\n \"def XXtearDown(self):\\n print(\\\"FooTest:tearDown_:begin\\\")\\n ## do something...\\n print(\\\"FooTest:tearDown_:end\\\")\",\n \"def XXtearDown(self):\\n print(\\\"FooTest:tearDown_:begin\\\")\\n ## do something...\\n print(\\\"FooTest:tearDown_:end\\\")\",\n \"def tearDown(self):\\n pass #because we dont have anything to tearDown.\",\n \"def tearDown(self) :\\n pass\",\n \"def tearDown(self) :\\n pass\",\n \"def tearDown(self) :\\n pass\",\n \"def tearDown(self):\\n print('tearDown method\\\\n')\",\n \"def tearDown(self):\\n \\n return\",\n \"def tearDown(self):\\n\\t\\tpass\",\n \"def tearDown(self):\\r\\n testing.tearDown()\",\n \"def tearDown(self):\\n print 'unittest.tearDown()'\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n 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pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\",\n \"def tearDown(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list 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replicate of 1D data."},"document":{"kind":"string","value":"def bootstrap_replicate_1d(data, func):\r\n bs_sample = np.random.choice(data, len(data))\r\n return func(bs_sample)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def bootstrap_replicate_1d(data, func):\n bs_sample = np.random.choice(data, len(data))\n return func(bs_sample)","def bootstrap_replicate_1d(data, func):\n bs_sample = np.random.choice(data, len(data))\n\n return func(bs_sample)","def bootstrap(X):\n return X[np.random.choice(list(range(X.shape[0])), size=X.shape[0]), :]","def standard_bootstrap(dataset):\n randseed=np.random.randint(0,10000)\n np.random.seed(randseed)\n \n n = dataset.shape[0]\n b = np.random.randint(0, high=n-1, size=n)\n return dataset[b]","def bootstrap_sample(data):\n return [random.choice(data) for _ in data]","def bootstrap(data):\r\n size = int(len(data))\r\n train = resample(data, n_samples=size, replace=True)\r\n test = data.drop(train.index) \r\n return train[encoded_features], train[target], test[encoded_features], test[target]","def bootstrap(data,func,nboot):\n\n n = len(data)\n resamples = np.array([[random.choice(data) for i in range(n)]\n for j in range(nboot)])\n return np.apply_along_axis(func, 1, resamples)","def bootstrap_data(self):\n for i in range(self.bootstraps):\n df_i = self.training_df.groupby(\n self.random_effect, group_keys=False\n ).apply(\n lambda x: x.sample(len(x), replace=True)\n )\n self.models.append(self.convert(df=df_i))","def _get_bootstrap_sample(x, y, num_reps):\r\n combined = array(list(x) + list(y))\r\n total_obs = len(combined)\r\n num_x = len(x)\r\n for i in range(num_reps):\r\n # sampling with replacement\r\n indices = randint(0, total_obs, total_obs)\r\n sampled = combined.take(indices)\r\n # split into the two populations\r\n sampled_x = sampled[:num_x]\r\n sampled_y = sampled[num_x:]\r\n yield sampled_x, sampled_y","def dataset_augmentation(data_start, bootstrapping = 1, epurate = 1, shuffle = True):\n data = data_start\n for ii in range(bootstrapping):\n data = data.append(data_start.apply(bootstrap_sample, axis=1), ignore_index=True)\n\n#Bugged version that weirdly works well....\n# for ii in range(bootstrapping):\n # data = data.append(bootstrap_sample(data_start), ignore_index=True)\n\n for ii in range(epurate):\n data = data.append(data_start.apply(epurate_sample, axis=1), ignore_index=True)\n\n # Shuffling (Important)\n if shuffle == True:\n data = data.sample(frac=1)\n return data","def bootstrap_resample(labels):\n idxs = np.arange(len(labels))\n num_labels = max(labels) + 1\n bootstrap_idxs = np.zeros_like(idxs)\n ptr = 0\n for i in range(num_labels):\n strat = idxs[labels == i]\n bootstrap_idxs[ptr:ptr + len(strat)] = np.random.choice(strat, len(strat), replace=True)\n ptr += len(strat)\n return bootstrap_idxs","def bs_replicate(data, func=np.mean):\n bs_sample = np.random.choice(data, replace=True, size=len(data))\n return func(bs_sample)","def get_bootstraps(self):\n col_range = range(self.response.shape[1])\n random_state = np.random.RandomState(seed=self.random_seed)\n return random_state.choice(col_range, size=(self.num_bootstraps, self.response.shape[1])).tolist()","def bootstrap_sample_from_data(data, weights=None, seed=0):\n # Set up the random number generator\n RNG = np.random.default_rng(seed)\n N = data.shape[0]\n\n # Set up weights\n if weights is not None:\n cutoffs = np.cumsum(weights)\n else:\n cutoffs = np.linspace(0, 1, N)\n\n # Draw random indices\n indices = np.searchsorted(cutoffs, RNG.uniform(size=N))\n\n # Create a bootstrapped sample\n new_data = deepcopy(data[indices,])\n return new_data","def bootstrap_sample_generator_1D(samples: Union[NumpyFloatArray, NumpyIntArray]):\n n_samples = samples.shape[0]\n\n while True:\n _indices = np.random.randint(0, high=n_samples, size=n_samples)\n\n yield samples[_indices]","def boot_matrix(z, B):\n\n n = len(z) # sample size\n idz = np.random.randint(0, n, size=(B, n)) # indices to pick for all boostrap samples\n return z[idz]","def bootstrap_resample(X, n=None):\r\n if n == None:\r\n n = len(X)\r\n \r\n resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)\r\n X_resample = X[resample_i]\r\n return X_resample","def boot_matrix(z, B):\n z = np.array(z).flatten()\n n = len(z) # sample size\n idz = np.random.randint(0, n, size=(B, n)) # indices to pick for all boostrap samples\n return z[idz]","def genBootstrapData(fullData, dirName=\"bootstrap_data/\", ti=None, tf=None, n=1, blockLen=7):\n # If initial (final) time not given, apply block bootstrap to whole data set\n if ti == None:\n ti = 0\n if tf == None:\n tf = fullData.shape[0]\n\n # Reset seed\n np.random.seed()\n\n bsSets = []\n\n for i in range(0, n):\n bsSet = fullData.copy()\n\n # Loop over the sensors\n for sensor in range(fullData.shape[1]):\n # Loop over the blocks\n for tStart in range(ti, tf, blockLen):\n # Resample only the non-nan datapoints\n # TODO: is this a valid way of doing this???\n oldBlockNonNans = bsSet[tStart:tStart+blockLen, sensor].copy()\n oldBlockNonNans = oldBlockNonNans[np.isfinite(oldBlockNonNans)]\n\n for t in range(tStart, min(tStart + blockLen, fullData.shape[0])):\n if not np.isnan(bsSet[t, sensor]):\n bsSet[t, sensor] = np.random.choice(oldBlockNonNans, 1, replace=False)\n\n bsSets.append(bsSet)\n\n # Save the dataset\n np.savetxt(dirName + \"/blockLen=%i_%i.csv\"%(blockLen, i), bsSet, delimiter=\" \", fmt=\"%f\")\n\n return bsSets","def compute_bootstrapped_sample(X_table, y_table):\n n = len(X_table)\n X_sample = []\n y_sample = []\n for _ in range(n):\n rand_index = random.randrange(0, n)\n X_sample.append(X_table[rand_index])\n y_sample.append(y_table[rand_index])\n return X_sample, y_sample","def bootstrap_data_array(data, H, R, permute=None):\n\n if permute is None:\n permute = randint(data.shape[-1], size=data.shape[-1])\n assert R.shape == H.shape\n assert len(permute) == R.shape[-1]\n R = R[permute]\n data = dot(data, (H+R).T)\n return data","def bootstrap(items, choices, repeats):\n for i in range(repeats):\n yield sample(items, choices, replace=True)","def generate_bootstrap_samples(num_samples, test_universe, test_set_sizes):\n for sample_idx, sample_size in zip(range(num_samples), cycle(test_set_sizes)):\n yield random.sample(test_universe, sample_size)","def bootstrap_array(f_values, values, bootstraps=1000):\n x = np.array(values)\n x_bs = x[np.random.randint(x.size, size=(bootstraps, x.size))]\n return np.array(map(f_values, x_bs))","def bootstrap_resample(X, n=None):\r\n if n == None:\r\n n = len(X)\r\n\r\n resample_i = N.floor(N.random.rand(n)*len(X)).astype(int)\r\n X_resample = X[resample_i]\r\n return X_resample","def bootstrap( M ):\n tot_ct_per_ob = M.sum(axis = 0)\n zero_list = []\n for i in range(len(tot_ct_per_ob)):\n if tot_ct_per_ob[i] <= 0:\n zero_list.append(i)\n M = np.delete(M, zero_list, 1)\n new_M = np.zeros(M.shape)\n tot_ct_per_ob = M.sum(axis = 0)\n for i in range(len(M)):\n for j in range(len(M[0])):\n new_M[i][j] = M[i][j]/tot_ct_per_ob[j]\n new_M = np.transpose(new_M)\n bootstrap = []\n for i in range(len(tot_ct_per_ob)):\n rnd_vec = np.random.multinomial(tot_ct_per_ob[i], new_M[i])\n bootstrap.append(rnd_vec)\n \n bootstrap = np.transpose(np.asarray(bootstrap)) \n return bootstrap","def make_repeatable():\n random.seed(1234)\n np.random.seed(1234)","def bootstrap_resample(self, X, n=None):\n if n == None:\n n = len(X)\n\n resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)\n X_resample = X.iloc[resample_i, :]\n return X_resample","def draw_bootstrap_pairs(x, y, func, size=1):\n\n # Set up array of indices to sample from: inds\n inds = np.arange(len(x))\n\n # Initialize replicates: bs_replicates\n bs_replicates = np.empty(size)\n\n # Generate replicates\n for i in range(size):\n bs_inds = np.random.choice(inds, len(inds))\n bs_x, bs_y = x[bs_inds], y[bs_inds]\n bs_replicates[i] = func(bs_x, bs_y)\n\n return bs_replicates","def eg_pre():\n\n print(\"\\teg3\")\n\n d = 1\n\n for _ in range(10):\n t1 = []\n t2 = []\n\n for _ in range(32):\n t1.append(utils.gaussian(10, 1))\n t2.append(utils.gaussian(d * 10, 1))\n\n print(\"\", \"\", d, d < 1.1, stats.bootstrap(\n t1, t2), stats.bootstrap(t1, t1), sep=\"\\t\")\n\n d = round(d + .05, 2)","def test_Pad3D19():\n input_shape = (1, 2, 3)\n pad = [1, 2]\n mode = \"replicate\"\n res = [[[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6], [4, 5, 6]]]\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\n obj.run(res=res, padding=pad, mode=mode, data_format=\"NLC\", data=data)","def asrepeats(self):\n w_int = np.floor(self.weights).astype(int)\n return np.repeat(self.data, w_int, axis=0)","def bootstrap(data, iterations=10000):\n\n boot_mean = []\n\n for n in range(0, iterations):\n\n boot = resample(data, replace=True, n_samples=None,\n random_state=None)\n\n boot_mean.append(np.mean(boot))\n\n final_mean = np.mean(boot_mean)\n\n final_std = np.std(boot_mean, dtype=np.float64)\n\n return final_mean, final_std","def test_Pad3D17():\n input_shape = (1, 2, 3)\n pad = [2, 1]\n mode = \"replicate\"\n res = [[[1, 1, 1, 2, 3, 3], [4, 4, 4, 5, 6, 6]]]\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\n obj.run(res=res, padding=pad, mode=mode, data=data, data_format=\"NCL\")","def bootstrap(h0, h1, f, B=10000):\n t_star = np.zeros(B)\n m = len(h0)\n n = len(h1)\n all_h = np.concatenate([h0, h1])\n for b_id in range(B):\n b_data = np.random.choice(all_h, size=m + n, replace=True)\n t_star[b_id] = f(b_data[:m], b_data[m:])\n return t_star","def bootstrap(df, nclass, if_new=False):\n ori_size = Counter(df.label)\n logger.info(f'class info before resampling: {ori_size.values()}')\n ori_size_list = list(ori_size.values())\n\n if if_new:\n df_new = pd.DataFrame(data=None, columns=df.columns)\n target_size = min(ori_size_list)\n else:\n target_size = max(ori_size_list)\n df_new = df.copy()\n\n for i in range(nclass):\n name = list(ori_size.keys())[i]\n name_index = np.array(df[df.label == name].index)\n if target_size < ori_size_list[i]:\n sample_size = target_size\n elif target_size > ori_size_list[i]:\n sample_size = target_size - ori_size_list[i]\n else:\n if if_new:\n sample_size = target_size\n else:\n sample_size = 0\n\n np.random.seed(i)\n boostrap_sample = np.random.randint(0, ori_size_list[i], sample_size)\n df_new = df_new.append(df.iloc[name_index[boostrap_sample]], ignore_index=True)\n logger.info(f'class info after resampling: {Counter(df_new.label).values()}')\n return df_new","def bootstrap_group(nsubj, ngroups):\n groupsize = nsubj\n samples = [(groupsize * np.random.rand(groupsize)).astype(np.int_)\n for i in range(ngroups)]\n return samples","def bootstrap(x, iter=int(1E6), return_samples=False):\n\n \n means = np.empty(iter) \n dfs = []\n for i in tqdm(range(iter), desc='Performing bootstrap sampling'):\n resamp = np.random.choice(x, size=len(x), replace=True)\n means[i] = resamp.mean()\n\n if return_samples:\n _df = pd.DataFrame([])\n _df['value'] = resamp\n _df['iter'] = i + 1\n dfs.append(_df)\n\n # Compute confidence intervals of the means.\n mean_val = means.mean()\n bounds_ci = {'99%': (0.5, 99.5), '95%': (2.5, 97.5), '90%': (5, 95),\n '75%': (12.5, 87.5), '50%': (25, 75), '25%': (37.5, 62.5),\n '10%': (45, 55), '5%': (47.5, 52.5), '1%': (49.5, 50.5)} \n cis = {} \n for k, v in bounds_ci.items():\n bounds = np.percentile(means, v)\n cis[k] = bounds\n\n statistics['original_data'] = x\n statistics['resampled_means'] = means\n statistics['mean_value'] = mean_val\n statistics['confidence_intervals'] = cis\n\n if return_samples:\n _df = pd.concat(dfs, sort=False)\n return [statistics, _df]\n else:\n return statistics","def draw_bs_reps(data, func, reps=1):\n bs_replicates = np.empty(reps)\n for i in range(reps):\n bs = np.random.choice(data, replace=True, size=len(data))\n bs_replicates[i] = np.mean(bs)\n return func(bs_replicates)","def generate(self):\n self.lst=[]\n for i in range(8):\n self.mat= random.sample(range(100),8)\n self.lst.append(self.mat)\n return self.lst","def joint_bootstrap(m_list, axis=0, n=None, replace=True):\n size = m_list[0].shape[axis]\n if n is None:\n n = size\n idx = np.random.choice(size, n, replace=replace)\n return [np.take(m, idx, axis=axis) for m in m_list]","def predict(self, data):\n return self.output.repeat(data.size(0), 1)","def initial_population(datapoints_nr, population_size):\n\n # row = members\n population = np.empty(shape=(population_size, datapoints_nr))\n\n for member in range(population_size):\n # each member consist of the indices from 0 to datapoints_nr-1 and is\n # some random assignment between them\n population[member] = random.sample(range(datapoints_nr), datapoints_nr)\n\n return population.astype(int)","def generate_rand():\n n_cols = 5\n n_rows = 100\n n_class = 10\n trial_x = np.random.rand(n_rows, n_cols)\n trial_y = np.random.random_integers(1, n_class, size = (n_rows, 1))\n\n # Append response to data\n trial_data = np.append(trial_x, trial_y, 1)\n return trial_data, n_class, n_cols","def generate_data(self,seed):\n X, y = make_classification( n_samples = 250, random_state = seed )\n # Add bias term\n X = np.concatenate( ( np.ones( ( 250, 1 ) ), X ), axis = 1 )\n self.X_train, self.X_test, self.y_train, self.y_test = train_test_split( \n X, y, test_size = 50, random_state = seed )","def Repeat(dataset, count=None):\n return dataset.repeat(count=count)","def shuffle_1d_nb(a, seed=None):\n if seed is not None:\n np.random.seed(seed)\n return np.random.permutation(a)","def test_bootstrap_array_shape():\n test_array = np.zeros((3, 4))\n test_axis = 1\n nboot = 5\n new_array = utils.bootstrap_array(test_array, nboot=nboot, axis=test_axis)\n shape = (3, 4, 5)\n assert shape == new_array.shape","def _make_boot_index(elements, niter):\n return numpy.random.randint(low=0, high=elements, size=(niter, elements))","def generate_dataset():\n num_list = 10\n return [generate_list() for _ in range(num_list)]","def bootstrap_data_voxel(data, H, R, permute=None):\n if permute is None:\n permute = randint(data.shape[-1], size=data.shape[-1])\n r = dot(data, R.T)\n r = r[permute]\n d = dot(data, H.T) + r\n return d","def _seed_population(self):\n return [self._generate_weights() for x in range(self.population_size)]","def bootstrap_two_sample_diff_in_proportions(p_group_1_count, p_group_1_sample_size, p_group_2_count, p_group_2_sample_size, p_size=1, p_alpha=.05):\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n original_group_1_proportion = p_group_1_count / p_group_1_sample_size \n original_group_2_proportion = p_group_2_count / p_group_2_sample_size \n \n original_proportion_diff = original_group_1_proportion - original_group_2_proportion\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ \n # Create an array of zeros and ones with the same proportions as group_1\n\n arr_1 = np.array([0] * (p_group_1_sample_size - p_group_1_count) + [1] * p_group_1_count)\n\n np.random.shuffle(arr_1)\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ \n # Create an array of zeros and ones with the same proportions as group_2\n\n arr_2 = np.array([0] * (p_group_2_sample_size - p_group_2_count) + [1] * p_group_2_count)\n\n np.random.shuffle(arr_2)\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n # Initialize array of replicates: \n bs_replicates = np.empty(p_size)\n\n # Generate replicates\n for i in range(p_size):\n\n # Generate bootstrap sample for arr_1 and arr_2 \n bs_sample_arr_1 = np.random.choice(arr_1, len(arr_1))\n bs_sample_arr_2 = np.random.choice(arr_2, len(arr_2))\n \n # Get the proportions on the bootstrap samples \n bs_sample_arr_1_proportion = np.sum(bs_sample_arr_1) / len(bs_sample_arr_1)\n bs_sample_arr_2_proportion = np.sum(bs_sample_arr_2) / len(bs_sample_arr_2)\n\n # Add the diff of those proportions to the bs_replicates array:\n bs_replicates[i] = bs_sample_arr_1_proportion - bs_sample_arr_2_proportion\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n # Get the bootstrap mean and standard error\n bs_mean = np.mean(bs_replicates)\n bs_std = np.std(bs_replicates)\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n # Get the confidence interval\n lower_critical_value, upper_critical_value = get_two_tailed_critical_values(p_alpha = p_alpha)\n\n ci_lower, ci_upper = np.percentile(bs_replicates, [lower_critical_value*100, upper_critical_value*100])\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n Result = namedtuple(\n 'Result', [\n 'original_group_1_proportion', \n 'original_group_2_proportion', \n 'original_proportion_diff', \n 'bs_mean', \n 'bs_std', \n 'ci_lower',\n 'ci_upper',\n 'bs_replicates'\n ]\n )\n\n result = Result(\n original_group_1_proportion,\n original_group_2_proportion,\n original_proportion_diff,\n bs_mean,\n bs_std,\n ci_lower,\n ci_upper,\n bs_replicates\n )\n\n return result\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~","def eg_bootmu():\n\n a = []\n b = []\n\n for _ in range(100):\n a.append(utils.gaussian(10, 1))\n\n print(\"\", \"mu\", \"sd\", \"cliffs\", \"boot\", \"both\", sep=\"\\t\")\n print(\"\", \"--\", \"--\", \"------\", \"----\", \"----\", sep=\"\\t\")\n\n for mu in range(100, 111):\n b = []\n\n for _ in range(100):\n b.append(utils.gaussian(mu / 10, 1))\n\n cl = utils.cliffsDelta(a, b)\n bs = stats.bootstrap(a, b)\n\n print(\"\", mu / 10, 1, cl, bs, cl and bs, sep=\"\\t\")","def stationary_bootstrap(data,B,w):\n (t,k) = data.shape\n assert k == 1, 'DATA must be a column vector'\n assert t>=2, 'DATA must have at least 2 observations.'\n assert w >= 0, 'Average block length W must be a positive scalar.'\n assert (isinstance(B,int)) and(B >= 0), 'Number of bootstrap samples B must be a \\\n positive scalar integer'\n \n # Probability of new block\n p=1/w\n \n #Set up the bsdata and indices\n indices = np.zeros((t,B))\n indices[0,:] = np.ceil(t*np.random.rand(1,B))\n \n # Set up random numbers\n select=np.random.rand(t,B) < p\n indices[select] = np.ceil(np.random.rand(1,np.sum(select))*t).flatten()\n \n \n for i in range(1,t):\n # Determine whether we stay (rand>p) or move to a new starting value\n indices[i,~select[i,:]] = indices[i-1,~select[i,:]]\n # Make sure indices don't go out of bound\n indices[indices>t-1] = indices[indices>t-1]-t-1\n # Indices need to be integers\n indices = indices.astype(int)\n # Sample data\n bsdata=data[indices]\n # Get rid of extra dimension that comes from sampling\n bsdata = bsdata.reshape((t,B))\n \n return bsdata, indices","def WeightInitializer():\n return np.random.uniform(-1, 1)","def block_replicate(data, block_size, conserve_sum=True):\n data, block_size = _process_block_inputs(data, block_size)\n for i in range(data.ndim):\n data = np.repeat(data, block_size[i], axis=i)\n\n if conserve_sum:\n # in-place division can fail due to dtype casting rule\n data = data / np.prod(block_size)\n\n return data","def bootstrapping(datasample):\r\n \r\n datasample=df_to_array(datasample)\r\n \r\n boots_indexs=np.random.randint(len(datasample),size=(1,len(datasample)))\r\n \r\n whole_indexs=list(range(len(datasample)))\r\n \r\n missing_indexs=np.array(list(set(whole_indexs).difference(set(list(boots_indexs[0])))))\r\n \r\n \r\n return boots_indexs,missing_indexs","def bootstrap_sample_generator_2D(samples: Union[NumpyFloatArray, NumpyIntArray]):\n n_samples = samples.shape[0]\n\n num_cols = samples.shape[1]\n cols = np.arange(num_cols)\n\n while True:\n # generate indices to pick N values from f_A, f_B and f_C_i\n _indices = np.random.randint(0, high=n_samples, size=samples.shape)\n\n yield samples[_indices, cols]","def bootstrap_mean(x, n=100):\n out = []\n\n for i in range(n):\n idx = pd.Series(np.arange(len(x))).sample(frac=1.0, replace=True).values\n out.append(x[idx].mean(0))\n outm = np.stack(out)\n return outm.mean(0), outm.std(0)","def deterministic_samples_dim_1(self,\n X,\n simplices):\n return X[simplices[:, 0]]","def static(seq: List[int]):\n return Data._create_dataset(seq, pad=True)","def draw_bs_reps_mle(mle_fun, data, args=(), size=1, n_jobs=1, progress_bar=False):\n # Just call the original function if n_jobs is 1 (no parallelization)\n if n_jobs == 1:\n return _draw_bs_reps_mle(\n mle_fun, data, args=args, size=size, progress_bar=progress_bar)\n\n # Set up sizes of bootstrap replicates for each core, making sure we\n # get all of them, even if sizes % n_jobs != 0\n sizes = [size // n_jobs for _ in range(n_jobs)]\n sizes[-1] += size - sum(sizes)\n\n # Build arguments\n arg_iterable = [(mle_fun, data, args, s, progress_bar, None) for s in sizes]\n\n with multiprocess.Pool(n_jobs) as pool:\n result = pool.starmap(_draw_bs_reps_mle, arg_iterable)\n\n return np.concatenate(result)","def bootstrap_sample_generator_3D(samples: Union[NumpyFloatArray, NumpyIntArray]):\n n_samples = samples.shape[1]\n array_shape = samples.shape[1:]\n num_cols = samples.shape[2]\n cols = np.arange(num_cols)\n\n while True:\n _indices = np.random.randint(0, high=n_samples, size=array_shape)\n\n yield samples[:, _indices, cols]","def generate_model (d):\n return np.random.rand (d+1, 1)","def warmUpExercise():\n\n return np.identity(5)","def replicate(self, count):\n return map(lambda x: x.clone(),[self]*count)","def initialize(self):\n N=self.N\n M=[]\n a=random.rand(self.d,1,self.D)\n M.append(a)\n for i in range(1,N-1):\n a=random.rand(self.d,self.D,self.D)\n M.append(a)\n a=random.rand(self.d,self.D,1)\n M.append(a)\n return M","def compute_bootstrapped_diff(x0, x1, is_paired, effect_size,\n resamples=5000, random_seed=12345):\n \n from . import effsize as __es\n import numpy as np\n from numpy.random import PCG64, RandomState\n \n # rng = RandomState(default_rng(random_seed))\n rng = RandomState(PCG64(random_seed))\n\n out = np.repeat(np.nan, resamples)\n x0_len = len(x0)\n x1_len = len(x1)\n \n for i in range(int(resamples)):\n \n if is_paired:\n if x0_len != x1_len:\n raise ValueError(\"The two arrays do not have the same length.\")\n random_idx = rng.choice(x0_len, x0_len, replace=True)\n x0_sample = x0[random_idx]\n x1_sample = x1[random_idx]\n else:\n x0_sample = rng.choice(x0, x0_len, replace=True)\n x1_sample = rng.choice(x1, x1_len, replace=True)\n \n out[i] = __es.two_group_difference(x0_sample, x1_sample,\n is_paired, effect_size)\n \n # check whether there are any infinities in the bootstrap,\n # which likely indicates the sample sizes are too small as\n # the computation of Cohen's d and Hedges' g necessitated \n # a division by zero.\n # Added in v0.2.6.\n \n # num_infinities = len(out[np.isinf(out)])\n # print(num_infinities)\n # if num_infinities > 0:\n # warn_msg = \"There are {} bootstraps that are not defined. \"\\\n # \"This is likely due to smaple sample sizes. \"\\\n # \"The values in a bootstrap for a group will be more likely \"\\\n # \"to be all equal, with a resulting variance of zero. \"\\\n # \"The computation of Cohen's d and Hedges' g will therefore \"\\\n # \"involved a division by zero. \"\n # warnings.warn(warn_msg.format(num_infinities), category=\"UserWarning\")\n \n return out","def draw_bs_sample(data):\n return np.random.choice(data, size=len(data))","def _generate_clones(self, data: list[Dict[str, Any]]) -> list[_Clone]:\n return [_Clone(clone) for clone in data or []]","def bootstrap(m, axis=0, n=None, replace=True, return_holdout=False):\n if n is None:\n n = m.shape[axis]\n idx = np.random.choice(m.shape[axis], n, replace=replace)\n bootstrap = np.take(m, idx, axis=axis)\n if return_holdout:\n ran = np.arange(m.shape[axis])\n holdout_idx = ran[np.array([x not in idx for x in ran])]\n holdout = np.take(m, holdout_idx, axis=axis)\n return bootstrap, holdout\n else:\n return bootstrap","def sample(self):\n return self(np.random.randn(self.num_xi)).reshape(self.X.shape)","def random_init(self, shape):\n return np.random.randn(shape[0],shape[1])*0.01","def build_toy_dataset(N):\n pi = np.array([0.4, 0.6])\n mus = [[1, 1], [-1, -1]]\n stds = [[0.1, 0.1], [0.1, 0.1]]\n x = np.zeros((N, 2), dtype=np.float32)\n\n for n in range(N):\n k = np.argmax(np.random.multinomial(1, pi))\n x[n, :] = np.random.multivariate_normal(mus[k], np.diag(stds[k]))\n\n return x","def generate_samples(self, n_samples):","def generate_samples(self, n_samples):","def bootstrap(self, X_list, n_sampling):\n if len(X_list) < 2:\n raise ValueError('X_list must be a list containing at least two items')\n\n n_features = check_array(X_list[0]).shape[1]\n X_list_ = []\n for X in X_list:\n X_ = check_array(X)\n if X_.shape[1] != n_features:\n raise ValueError('X_list must be a list with the same number of features')\n X_list_.append(X_)\n X_list = np.array(X_list_)\n\n if isinstance(n_sampling, (numbers.Integral, np.integer)):\n if not 0 < n_sampling:\n raise ValueError('n_sampling must be an integer greater than 0.')\n else:\n raise ValueError('n_sampling must be an integer greater than 0.')\n\n # Bootstrapping\n adjacency_matrices_list = [[] for _ in range(X_list.shape[0])]\n for _ in range(n_sampling):\n resampled_X_list = [resample(X) for X in X_list]\n model = self.fit(resampled_X_list)\n for i, am in enumerate(model.adjacency_matrices_):\n adjacency_matrices_list[i].append(am)\n\n result_list = []\n for adjacency_matrices in adjacency_matrices_list:\n result_list.append(BootstrapResult(adjacency_matrices))\n\n return result_list","def init_batch(self, src):\n batch, bos = src.size(1), self.src_dict.get_bos()\n return src.data.new(1, batch).fill_(bos)","def vec_repeat_at_start(x, p):\n n = x.shape[0]\n indices = (jnp.arange(p) + n - p) % n\n padding = x[indices]\n return jnp.concatenate((padding, x))","def rand(self, x):\r\n return np.random.random(1)[0]","def generatePattern(numCols=100, minOnes=21, maxOnes=25):\n assert minOnes < maxOnes\n assert maxOnes < numCols\n\n nOnes = random.randint(minOnes, maxOnes)\n ind = random.sample(xrange(numCols), nOnes)\n x = numpy.zeros(numCols, dtype='float32')\n x[ind] = 1\n\n return x","def test_Pad3D16():\n input_shape = (1, 2, 3)\n pad = [1, 2]\n mode = \"replicate\"\n res = [[[1, 1, 2, 3, 3, 3], [4, 4, 5, 6, 6, 6]]]\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\n obj.base(res=res, padding=pad, mode=mode, data=data, data_format=\"NCL\")","def resample(self):\n self.X = np.random.uniform(-1, 1, (100, 2))\n self.generate_y()\n self.phi = None\n self.K = 0\n self.centers = None\n self.cluster_sizes = None\n self.g = None\n self.gamma = None","def dice(data, size):\n\treturn data.reshape((data.shape[0] // size, size))","def bootstrap():\n Bootstrap()","def bootstrap_sample_binomial(k, n, B):\n\n vec = np.zeros(n) # Original sample created as a vector\n vec[0:k] = 1 # 1 == success\n y = np.zeros(B) # Bootstrap statistics of # success\n \n for k in range(B):\n y[k] = np.sum(np.random.choice(vec,n)) # default is with replacement\n\n return y","def create_beams(x):\n return tf.repeat(x, self.num_beams, axis=0)","def pad_examples(x, desired_batch_size):\n batch_pad = desired_batch_size - x.shape[0]\n tile_dims = [1] * len(x.shape)\n tile_dims[0] = batch_pad\n return np.concatenate([x, np.tile(x[-1], tile_dims)], axis=0)","def some_simple_data(length=1000000):\n data = list(range(length))\n random.shuffle(data)\n return data","def warm_up_exercise():\n A = np.eye(5)\n return A","def generate_all_samples(self):\n\n n_samples, n_dimensions, V = self.n_samples, self.n_dimensions, self.V\n sample_all = np.zeros([n_samples, n_dimensions])\n\n X = int(0)\n for j in range(1, n_samples):\n X ^= V[self.index_of_least_significant_zero_bit(j - 1)]\n sample_all[j][:] = [float(x / math.pow(2, self.scale)) for x in X]\n return sample_all","def _train(self):\n return np.zeros(1, 10)","def network_bootstrap(self, args):\n pass","def SampleReplicate(\r\n data: Iterable,\r\n factor: int,\r\n lazy: bool = True,\r\n workers: int = 1,\r\n buffer_len: int = 3,\r\n *arg: List,\r\n **kwargs: Dict\r\n) -> Union[SampleReplicateAbstract, DataAbstract, np.ndarray, list]:\r\n if lazy:\r\n return SampleReplicateAbstract(data, factor, *arg, **kwargs)\r\n else:\r\n # ToDo: replace by a list and np equivalent\r\n return DataAbstract(\r\n SampleReplicateAbstract(data, factor, *arg, **kwargs),\r\n workers=workers,\r\n buffer_len=buffer_len,\r\n )[:]","def construct_random_initial(self):\n x = np.random.random((self._crv_size, self._bound))\n return x","def seqBootstrap(indM, sLength=None):\n if sLength is None:\n sLength = indM.shape[1]\n phi = []\n while len(phi) < sLength:\n avgU = pd.Series(dtype=\"float64\")\n for i in indM:\n indM_ = indM[phi + [i]]\n avgU.loc[i] = getAvgUniqueness(indM_).iloc[-1]\n prob = avgU / avgU.sum()\n phi += [np.random.choice(indM.columns, p=prob)]\n return phi","def duplicate_data(rng):\n N = 10\n keys = [str(1) for _ in range(1,N)]\n return zip(keys,\n [1 for _ in range(1,N)],\n [rng.random(128) for _ in range(N)],\n [random.choice([range(1,N),None]) for _ in range(N)])","def generate_matrix(size) -> np.ndarray:\n np.random.seed(1)\n return np.random.rand(size, size) - 0.5","def test_Pad3D23():\n input_shape = (1, 2, 3)\n # pad = np.array([1, 2]).astype('int32')\n pad = [1, 2]\n mode = \"replicate\"\n res = [[[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6], [4, 5, 6]]]\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\n obj.run(res=res, padding=pad, mode=mode, data_format=\"NLC\", data=data)"],"string":"[\n \"def bootstrap_replicate_1d(data, func):\\n bs_sample = np.random.choice(data, len(data))\\n return func(bs_sample)\",\n \"def bootstrap_replicate_1d(data, func):\\n bs_sample = np.random.choice(data, len(data))\\n\\n return func(bs_sample)\",\n \"def bootstrap(X):\\n return X[np.random.choice(list(range(X.shape[0])), size=X.shape[0]), :]\",\n \"def standard_bootstrap(dataset):\\n randseed=np.random.randint(0,10000)\\n np.random.seed(randseed)\\n \\n n = dataset.shape[0]\\n b = np.random.randint(0, high=n-1, size=n)\\n return dataset[b]\",\n \"def bootstrap_sample(data):\\n return [random.choice(data) for _ in data]\",\n \"def bootstrap(data):\\r\\n size = int(len(data))\\r\\n train = resample(data, n_samples=size, replace=True)\\r\\n test = data.drop(train.index) \\r\\n return train[encoded_features], train[target], test[encoded_features], test[target]\",\n \"def bootstrap(data,func,nboot):\\n\\n n = len(data)\\n resamples = np.array([[random.choice(data) for i in range(n)]\\n for j in range(nboot)])\\n return np.apply_along_axis(func, 1, resamples)\",\n \"def bootstrap_data(self):\\n for i in range(self.bootstraps):\\n df_i = self.training_df.groupby(\\n self.random_effect, group_keys=False\\n ).apply(\\n lambda x: x.sample(len(x), replace=True)\\n )\\n self.models.append(self.convert(df=df_i))\",\n \"def _get_bootstrap_sample(x, y, num_reps):\\r\\n combined = array(list(x) + list(y))\\r\\n total_obs = len(combined)\\r\\n num_x = len(x)\\r\\n for i in range(num_reps):\\r\\n # sampling with replacement\\r\\n indices = randint(0, total_obs, total_obs)\\r\\n sampled = combined.take(indices)\\r\\n # split into the two populations\\r\\n sampled_x = sampled[:num_x]\\r\\n sampled_y = sampled[num_x:]\\r\\n yield sampled_x, sampled_y\",\n \"def dataset_augmentation(data_start, bootstrapping = 1, epurate = 1, shuffle = True):\\n data = data_start\\n for ii in range(bootstrapping):\\n data = data.append(data_start.apply(bootstrap_sample, axis=1), ignore_index=True)\\n\\n#Bugged version that weirdly works well....\\n# for ii in range(bootstrapping):\\n # data = data.append(bootstrap_sample(data_start), ignore_index=True)\\n\\n for ii in range(epurate):\\n data = data.append(data_start.apply(epurate_sample, axis=1), ignore_index=True)\\n\\n # Shuffling (Important)\\n if shuffle == True:\\n data = data.sample(frac=1)\\n return data\",\n \"def bootstrap_resample(labels):\\n idxs = np.arange(len(labels))\\n num_labels = max(labels) + 1\\n bootstrap_idxs = np.zeros_like(idxs)\\n ptr = 0\\n for i in range(num_labels):\\n strat = idxs[labels == i]\\n bootstrap_idxs[ptr:ptr + len(strat)] = np.random.choice(strat, len(strat), replace=True)\\n ptr += len(strat)\\n return bootstrap_idxs\",\n \"def bs_replicate(data, func=np.mean):\\n bs_sample = np.random.choice(data, replace=True, size=len(data))\\n return func(bs_sample)\",\n \"def get_bootstraps(self):\\n col_range = range(self.response.shape[1])\\n random_state = np.random.RandomState(seed=self.random_seed)\\n return random_state.choice(col_range, size=(self.num_bootstraps, self.response.shape[1])).tolist()\",\n \"def bootstrap_sample_from_data(data, weights=None, seed=0):\\n # Set up the random number generator\\n RNG = np.random.default_rng(seed)\\n N = data.shape[0]\\n\\n # Set up weights\\n if weights is not None:\\n cutoffs = np.cumsum(weights)\\n else:\\n cutoffs = np.linspace(0, 1, N)\\n\\n # Draw random indices\\n indices = np.searchsorted(cutoffs, RNG.uniform(size=N))\\n\\n # Create a bootstrapped sample\\n new_data = deepcopy(data[indices,])\\n return new_data\",\n \"def bootstrap_sample_generator_1D(samples: Union[NumpyFloatArray, NumpyIntArray]):\\n n_samples = samples.shape[0]\\n\\n while True:\\n _indices = np.random.randint(0, high=n_samples, size=n_samples)\\n\\n yield samples[_indices]\",\n \"def boot_matrix(z, B):\\n\\n n = len(z) # sample size\\n idz = np.random.randint(0, n, size=(B, n)) # indices to pick for all boostrap samples\\n return z[idz]\",\n \"def bootstrap_resample(X, n=None):\\r\\n if n == None:\\r\\n n = len(X)\\r\\n \\r\\n resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)\\r\\n X_resample = X[resample_i]\\r\\n return X_resample\",\n \"def boot_matrix(z, B):\\n z = np.array(z).flatten()\\n n = len(z) # sample size\\n idz = np.random.randint(0, n, size=(B, n)) # indices to pick for all boostrap samples\\n return z[idz]\",\n \"def genBootstrapData(fullData, dirName=\\\"bootstrap_data/\\\", ti=None, tf=None, n=1, blockLen=7):\\n # If initial (final) time not given, apply block bootstrap to whole data set\\n if ti == None:\\n ti = 0\\n if tf == None:\\n tf = fullData.shape[0]\\n\\n # Reset seed\\n np.random.seed()\\n\\n bsSets = []\\n\\n for i in range(0, n):\\n bsSet = fullData.copy()\\n\\n # Loop over the sensors\\n for sensor in range(fullData.shape[1]):\\n # Loop over the blocks\\n for tStart in range(ti, tf, blockLen):\\n # Resample only the non-nan datapoints\\n # TODO: is this a valid way of doing this???\\n oldBlockNonNans = bsSet[tStart:tStart+blockLen, sensor].copy()\\n oldBlockNonNans = oldBlockNonNans[np.isfinite(oldBlockNonNans)]\\n\\n for t in range(tStart, min(tStart + blockLen, fullData.shape[0])):\\n if not np.isnan(bsSet[t, sensor]):\\n bsSet[t, sensor] = np.random.choice(oldBlockNonNans, 1, replace=False)\\n\\n bsSets.append(bsSet)\\n\\n # Save the dataset\\n np.savetxt(dirName + \\\"/blockLen=%i_%i.csv\\\"%(blockLen, i), bsSet, delimiter=\\\" \\\", fmt=\\\"%f\\\")\\n\\n return bsSets\",\n \"def compute_bootstrapped_sample(X_table, y_table):\\n n = len(X_table)\\n X_sample = []\\n y_sample = []\\n for _ in range(n):\\n rand_index = random.randrange(0, n)\\n X_sample.append(X_table[rand_index])\\n y_sample.append(y_table[rand_index])\\n return X_sample, y_sample\",\n \"def bootstrap_data_array(data, H, R, permute=None):\\n\\n if permute is None:\\n permute = randint(data.shape[-1], size=data.shape[-1])\\n assert R.shape == H.shape\\n assert len(permute) == R.shape[-1]\\n R = R[permute]\\n data = dot(data, (H+R).T)\\n return data\",\n \"def bootstrap(items, choices, repeats):\\n for i in range(repeats):\\n yield sample(items, choices, replace=True)\",\n \"def generate_bootstrap_samples(num_samples, test_universe, test_set_sizes):\\n for sample_idx, sample_size in zip(range(num_samples), cycle(test_set_sizes)):\\n yield random.sample(test_universe, sample_size)\",\n \"def bootstrap_array(f_values, values, bootstraps=1000):\\n x = np.array(values)\\n x_bs = x[np.random.randint(x.size, size=(bootstraps, x.size))]\\n return np.array(map(f_values, x_bs))\",\n \"def bootstrap_resample(X, n=None):\\r\\n if n == None:\\r\\n n = len(X)\\r\\n\\r\\n resample_i = N.floor(N.random.rand(n)*len(X)).astype(int)\\r\\n X_resample = X[resample_i]\\r\\n return X_resample\",\n \"def bootstrap( M ):\\n tot_ct_per_ob = M.sum(axis = 0)\\n zero_list = []\\n for i in range(len(tot_ct_per_ob)):\\n if tot_ct_per_ob[i] <= 0:\\n zero_list.append(i)\\n M = np.delete(M, zero_list, 1)\\n new_M = np.zeros(M.shape)\\n tot_ct_per_ob = M.sum(axis = 0)\\n for i in range(len(M)):\\n for j in range(len(M[0])):\\n new_M[i][j] = M[i][j]/tot_ct_per_ob[j]\\n new_M = np.transpose(new_M)\\n bootstrap = []\\n for i in range(len(tot_ct_per_ob)):\\n rnd_vec = np.random.multinomial(tot_ct_per_ob[i], new_M[i])\\n bootstrap.append(rnd_vec)\\n \\n bootstrap = np.transpose(np.asarray(bootstrap)) \\n return bootstrap\",\n \"def make_repeatable():\\n random.seed(1234)\\n np.random.seed(1234)\",\n \"def bootstrap_resample(self, X, n=None):\\n if n == None:\\n n = len(X)\\n\\n resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)\\n X_resample = X.iloc[resample_i, :]\\n return X_resample\",\n \"def draw_bootstrap_pairs(x, y, func, size=1):\\n\\n # Set up array of indices to sample from: inds\\n inds = np.arange(len(x))\\n\\n # Initialize replicates: bs_replicates\\n bs_replicates = np.empty(size)\\n\\n # Generate replicates\\n for i in range(size):\\n bs_inds = np.random.choice(inds, len(inds))\\n bs_x, bs_y = x[bs_inds], y[bs_inds]\\n bs_replicates[i] = func(bs_x, bs_y)\\n\\n return bs_replicates\",\n \"def eg_pre():\\n\\n print(\\\"\\\\teg3\\\")\\n\\n d = 1\\n\\n for _ in range(10):\\n t1 = []\\n t2 = []\\n\\n for _ in range(32):\\n t1.append(utils.gaussian(10, 1))\\n t2.append(utils.gaussian(d * 10, 1))\\n\\n print(\\\"\\\", \\\"\\\", d, d < 1.1, stats.bootstrap(\\n t1, t2), stats.bootstrap(t1, t1), sep=\\\"\\\\t\\\")\\n\\n d = round(d + .05, 2)\",\n \"def test_Pad3D19():\\n input_shape = (1, 2, 3)\\n pad = [1, 2]\\n mode = \\\"replicate\\\"\\n res = [[[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6], [4, 5, 6]]]\\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\\n obj.run(res=res, padding=pad, mode=mode, data_format=\\\"NLC\\\", data=data)\",\n \"def asrepeats(self):\\n w_int = np.floor(self.weights).astype(int)\\n return np.repeat(self.data, w_int, axis=0)\",\n \"def bootstrap(data, iterations=10000):\\n\\n boot_mean = []\\n\\n for n in range(0, iterations):\\n\\n boot = resample(data, replace=True, n_samples=None,\\n random_state=None)\\n\\n boot_mean.append(np.mean(boot))\\n\\n final_mean = np.mean(boot_mean)\\n\\n final_std = np.std(boot_mean, dtype=np.float64)\\n\\n return final_mean, final_std\",\n \"def test_Pad3D17():\\n input_shape = (1, 2, 3)\\n pad = [2, 1]\\n mode = \\\"replicate\\\"\\n res = [[[1, 1, 1, 2, 3, 3], [4, 4, 4, 5, 6, 6]]]\\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\\n obj.run(res=res, padding=pad, mode=mode, data=data, data_format=\\\"NCL\\\")\",\n \"def bootstrap(h0, h1, f, B=10000):\\n t_star = np.zeros(B)\\n m = len(h0)\\n n = len(h1)\\n all_h = np.concatenate([h0, h1])\\n for b_id in range(B):\\n b_data = np.random.choice(all_h, size=m + n, replace=True)\\n t_star[b_id] = f(b_data[:m], b_data[m:])\\n return t_star\",\n \"def bootstrap(df, nclass, if_new=False):\\n ori_size = Counter(df.label)\\n logger.info(f'class info before resampling: {ori_size.values()}')\\n ori_size_list = list(ori_size.values())\\n\\n if if_new:\\n df_new = pd.DataFrame(data=None, columns=df.columns)\\n target_size = min(ori_size_list)\\n else:\\n target_size = max(ori_size_list)\\n df_new = df.copy()\\n\\n for i in range(nclass):\\n name = list(ori_size.keys())[i]\\n name_index = np.array(df[df.label == name].index)\\n if target_size < ori_size_list[i]:\\n sample_size = target_size\\n elif target_size > ori_size_list[i]:\\n sample_size = target_size - ori_size_list[i]\\n else:\\n if if_new:\\n sample_size = target_size\\n else:\\n sample_size = 0\\n\\n np.random.seed(i)\\n boostrap_sample = np.random.randint(0, ori_size_list[i], sample_size)\\n df_new = df_new.append(df.iloc[name_index[boostrap_sample]], ignore_index=True)\\n logger.info(f'class info after resampling: {Counter(df_new.label).values()}')\\n return df_new\",\n \"def bootstrap_group(nsubj, ngroups):\\n groupsize = nsubj\\n samples = [(groupsize * np.random.rand(groupsize)).astype(np.int_)\\n for i in range(ngroups)]\\n return samples\",\n \"def bootstrap(x, iter=int(1E6), return_samples=False):\\n\\n \\n means = np.empty(iter) \\n dfs = []\\n for i in tqdm(range(iter), desc='Performing bootstrap sampling'):\\n resamp = np.random.choice(x, size=len(x), replace=True)\\n means[i] = resamp.mean()\\n\\n if return_samples:\\n _df = pd.DataFrame([])\\n _df['value'] = resamp\\n _df['iter'] = i + 1\\n dfs.append(_df)\\n\\n # Compute confidence intervals of the means.\\n mean_val = means.mean()\\n bounds_ci = {'99%': (0.5, 99.5), '95%': (2.5, 97.5), '90%': (5, 95),\\n '75%': (12.5, 87.5), '50%': (25, 75), '25%': (37.5, 62.5),\\n '10%': (45, 55), '5%': (47.5, 52.5), '1%': (49.5, 50.5)} \\n cis = {} \\n for k, v in bounds_ci.items():\\n bounds = np.percentile(means, v)\\n cis[k] = bounds\\n\\n statistics['original_data'] = x\\n statistics['resampled_means'] = means\\n statistics['mean_value'] = mean_val\\n statistics['confidence_intervals'] = cis\\n\\n if return_samples:\\n _df = pd.concat(dfs, sort=False)\\n return [statistics, _df]\\n else:\\n return statistics\",\n \"def draw_bs_reps(data, func, reps=1):\\n bs_replicates = np.empty(reps)\\n for i in range(reps):\\n bs = np.random.choice(data, replace=True, size=len(data))\\n bs_replicates[i] = np.mean(bs)\\n return func(bs_replicates)\",\n \"def generate(self):\\n self.lst=[]\\n for i in range(8):\\n self.mat= random.sample(range(100),8)\\n self.lst.append(self.mat)\\n return self.lst\",\n \"def joint_bootstrap(m_list, axis=0, n=None, replace=True):\\n size = m_list[0].shape[axis]\\n if n is None:\\n n = size\\n idx = np.random.choice(size, n, replace=replace)\\n return [np.take(m, idx, axis=axis) for m in m_list]\",\n \"def predict(self, data):\\n return self.output.repeat(data.size(0), 1)\",\n \"def initial_population(datapoints_nr, population_size):\\n\\n # row = members\\n population = np.empty(shape=(population_size, datapoints_nr))\\n\\n for member in range(population_size):\\n # each member consist of the indices from 0 to datapoints_nr-1 and is\\n # some random assignment between them\\n population[member] = random.sample(range(datapoints_nr), datapoints_nr)\\n\\n return population.astype(int)\",\n \"def generate_rand():\\n n_cols = 5\\n n_rows = 100\\n n_class = 10\\n trial_x = np.random.rand(n_rows, n_cols)\\n trial_y = np.random.random_integers(1, n_class, size = (n_rows, 1))\\n\\n # Append response to data\\n trial_data = np.append(trial_x, trial_y, 1)\\n return trial_data, n_class, n_cols\",\n \"def generate_data(self,seed):\\n X, y = make_classification( n_samples = 250, random_state = seed )\\n # Add bias term\\n X = np.concatenate( ( np.ones( ( 250, 1 ) ), X ), axis = 1 )\\n self.X_train, self.X_test, self.y_train, self.y_test = train_test_split( \\n X, y, test_size = 50, random_state = seed )\",\n \"def Repeat(dataset, count=None):\\n return dataset.repeat(count=count)\",\n \"def shuffle_1d_nb(a, seed=None):\\n if seed is not None:\\n np.random.seed(seed)\\n return np.random.permutation(a)\",\n \"def test_bootstrap_array_shape():\\n test_array = np.zeros((3, 4))\\n test_axis = 1\\n nboot = 5\\n new_array = utils.bootstrap_array(test_array, nboot=nboot, axis=test_axis)\\n shape = (3, 4, 5)\\n assert shape == new_array.shape\",\n \"def _make_boot_index(elements, niter):\\n return numpy.random.randint(low=0, high=elements, size=(niter, elements))\",\n \"def generate_dataset():\\n num_list = 10\\n return [generate_list() for _ in range(num_list)]\",\n \"def bootstrap_data_voxel(data, H, R, permute=None):\\n if permute is None:\\n permute = randint(data.shape[-1], size=data.shape[-1])\\n r = dot(data, R.T)\\n r = r[permute]\\n d = dot(data, H.T) + r\\n return d\",\n \"def _seed_population(self):\\n return [self._generate_weights() for x in range(self.population_size)]\",\n \"def bootstrap_two_sample_diff_in_proportions(p_group_1_count, p_group_1_sample_size, p_group_2_count, p_group_2_sample_size, p_size=1, p_alpha=.05):\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n original_group_1_proportion = p_group_1_count / p_group_1_sample_size \\n original_group_2_proportion = p_group_2_count / p_group_2_sample_size \\n \\n original_proportion_diff = original_group_1_proportion - original_group_2_proportion\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ \\n # Create an array of zeros and ones with the same proportions as group_1\\n\\n arr_1 = np.array([0] * (p_group_1_sample_size - p_group_1_count) + [1] * p_group_1_count)\\n\\n np.random.shuffle(arr_1)\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ \\n # Create an array of zeros and ones with the same proportions as group_2\\n\\n arr_2 = np.array([0] * (p_group_2_sample_size - p_group_2_count) + [1] * p_group_2_count)\\n\\n np.random.shuffle(arr_2)\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n # Initialize array of replicates: \\n bs_replicates = np.empty(p_size)\\n\\n # Generate replicates\\n for i in range(p_size):\\n\\n # Generate bootstrap sample for arr_1 and arr_2 \\n bs_sample_arr_1 = np.random.choice(arr_1, len(arr_1))\\n bs_sample_arr_2 = np.random.choice(arr_2, len(arr_2))\\n \\n # Get the proportions on the bootstrap samples \\n bs_sample_arr_1_proportion = np.sum(bs_sample_arr_1) / len(bs_sample_arr_1)\\n bs_sample_arr_2_proportion = np.sum(bs_sample_arr_2) / len(bs_sample_arr_2)\\n\\n # Add the diff of those proportions to the bs_replicates array:\\n bs_replicates[i] = bs_sample_arr_1_proportion - bs_sample_arr_2_proportion\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n # Get the bootstrap mean and standard error\\n bs_mean = np.mean(bs_replicates)\\n bs_std = np.std(bs_replicates)\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n # Get the confidence interval\\n lower_critical_value, upper_critical_value = get_two_tailed_critical_values(p_alpha = p_alpha)\\n\\n ci_lower, ci_upper = np.percentile(bs_replicates, [lower_critical_value*100, upper_critical_value*100])\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\\n\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n Result = namedtuple(\\n 'Result', [\\n 'original_group_1_proportion', \\n 'original_group_2_proportion', \\n 'original_proportion_diff', \\n 'bs_mean', \\n 'bs_std', \\n 'ci_lower',\\n 'ci_upper',\\n 'bs_replicates'\\n ]\\n )\\n\\n result = Result(\\n original_group_1_proportion,\\n original_group_2_proportion,\\n original_proportion_diff,\\n bs_mean,\\n bs_std,\\n ci_lower,\\n ci_upper,\\n bs_replicates\\n )\\n\\n return result\\n # -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\",\n \"def eg_bootmu():\\n\\n a = []\\n b = []\\n\\n for _ in range(100):\\n a.append(utils.gaussian(10, 1))\\n\\n print(\\\"\\\", \\\"mu\\\", \\\"sd\\\", \\\"cliffs\\\", \\\"boot\\\", \\\"both\\\", sep=\\\"\\\\t\\\")\\n print(\\\"\\\", \\\"--\\\", \\\"--\\\", \\\"------\\\", \\\"----\\\", \\\"----\\\", sep=\\\"\\\\t\\\")\\n\\n for mu in range(100, 111):\\n b = []\\n\\n for _ in range(100):\\n b.append(utils.gaussian(mu / 10, 1))\\n\\n cl = utils.cliffsDelta(a, b)\\n bs = stats.bootstrap(a, b)\\n\\n print(\\\"\\\", mu / 10, 1, cl, bs, cl and bs, sep=\\\"\\\\t\\\")\",\n \"def stationary_bootstrap(data,B,w):\\n (t,k) = data.shape\\n assert k == 1, 'DATA must be a column vector'\\n assert t>=2, 'DATA must have at least 2 observations.'\\n assert w >= 0, 'Average block length W must be a positive scalar.'\\n assert (isinstance(B,int)) and(B >= 0), 'Number of bootstrap samples B must be a \\\\\\n positive scalar integer'\\n \\n # Probability of new block\\n p=1/w\\n \\n #Set up the bsdata and indices\\n indices = np.zeros((t,B))\\n indices[0,:] = np.ceil(t*np.random.rand(1,B))\\n \\n # Set up random numbers\\n select=np.random.rand(t,B) < p\\n indices[select] = np.ceil(np.random.rand(1,np.sum(select))*t).flatten()\\n \\n \\n for i in range(1,t):\\n # Determine whether we stay (rand>p) or move to a new starting value\\n indices[i,~select[i,:]] = indices[i-1,~select[i,:]]\\n # Make sure indices don't go out of bound\\n indices[indices>t-1] = indices[indices>t-1]-t-1\\n # Indices need to be integers\\n indices = indices.astype(int)\\n # Sample data\\n bsdata=data[indices]\\n # Get rid of extra dimension that comes from sampling\\n bsdata = bsdata.reshape((t,B))\\n \\n return bsdata, indices\",\n \"def WeightInitializer():\\n return np.random.uniform(-1, 1)\",\n \"def block_replicate(data, block_size, conserve_sum=True):\\n data, block_size = _process_block_inputs(data, block_size)\\n for i in range(data.ndim):\\n data = np.repeat(data, block_size[i], axis=i)\\n\\n if conserve_sum:\\n # in-place division can fail due to dtype casting rule\\n data = data / np.prod(block_size)\\n\\n return data\",\n \"def bootstrapping(datasample):\\r\\n \\r\\n datasample=df_to_array(datasample)\\r\\n \\r\\n boots_indexs=np.random.randint(len(datasample),size=(1,len(datasample)))\\r\\n \\r\\n whole_indexs=list(range(len(datasample)))\\r\\n \\r\\n missing_indexs=np.array(list(set(whole_indexs).difference(set(list(boots_indexs[0])))))\\r\\n \\r\\n \\r\\n return boots_indexs,missing_indexs\",\n \"def bootstrap_sample_generator_2D(samples: Union[NumpyFloatArray, NumpyIntArray]):\\n n_samples = samples.shape[0]\\n\\n num_cols = samples.shape[1]\\n cols = np.arange(num_cols)\\n\\n while True:\\n # generate indices to pick N values from f_A, f_B and f_C_i\\n _indices = np.random.randint(0, high=n_samples, size=samples.shape)\\n\\n yield samples[_indices, cols]\",\n \"def bootstrap_mean(x, n=100):\\n out = []\\n\\n for i in range(n):\\n idx = pd.Series(np.arange(len(x))).sample(frac=1.0, replace=True).values\\n out.append(x[idx].mean(0))\\n outm = np.stack(out)\\n return outm.mean(0), outm.std(0)\",\n \"def deterministic_samples_dim_1(self,\\n X,\\n simplices):\\n return X[simplices[:, 0]]\",\n \"def static(seq: List[int]):\\n return Data._create_dataset(seq, pad=True)\",\n \"def draw_bs_reps_mle(mle_fun, data, args=(), size=1, n_jobs=1, progress_bar=False):\\n # Just call the original function if n_jobs is 1 (no parallelization)\\n if n_jobs == 1:\\n return _draw_bs_reps_mle(\\n mle_fun, data, args=args, size=size, progress_bar=progress_bar)\\n\\n # Set up sizes of bootstrap replicates for each core, making sure we\\n # get all of them, even if sizes % n_jobs != 0\\n sizes = [size // n_jobs for _ in range(n_jobs)]\\n sizes[-1] += size - sum(sizes)\\n\\n # Build arguments\\n arg_iterable = [(mle_fun, data, args, s, progress_bar, None) for s in sizes]\\n\\n with multiprocess.Pool(n_jobs) as pool:\\n result = pool.starmap(_draw_bs_reps_mle, arg_iterable)\\n\\n return np.concatenate(result)\",\n \"def bootstrap_sample_generator_3D(samples: Union[NumpyFloatArray, NumpyIntArray]):\\n n_samples = samples.shape[1]\\n array_shape = samples.shape[1:]\\n num_cols = samples.shape[2]\\n cols = np.arange(num_cols)\\n\\n while True:\\n _indices = np.random.randint(0, high=n_samples, size=array_shape)\\n\\n yield samples[:, _indices, cols]\",\n \"def generate_model (d):\\n return np.random.rand (d+1, 1)\",\n \"def warmUpExercise():\\n\\n return np.identity(5)\",\n \"def replicate(self, count):\\n return map(lambda x: x.clone(),[self]*count)\",\n \"def initialize(self):\\n N=self.N\\n M=[]\\n a=random.rand(self.d,1,self.D)\\n M.append(a)\\n for i in range(1,N-1):\\n a=random.rand(self.d,self.D,self.D)\\n M.append(a)\\n a=random.rand(self.d,self.D,1)\\n M.append(a)\\n return M\",\n \"def compute_bootstrapped_diff(x0, x1, is_paired, effect_size,\\n resamples=5000, random_seed=12345):\\n \\n from . import effsize as __es\\n import numpy as np\\n from numpy.random import PCG64, RandomState\\n \\n # rng = RandomState(default_rng(random_seed))\\n rng = RandomState(PCG64(random_seed))\\n\\n out = np.repeat(np.nan, resamples)\\n x0_len = len(x0)\\n x1_len = len(x1)\\n \\n for i in range(int(resamples)):\\n \\n if is_paired:\\n if x0_len != x1_len:\\n raise ValueError(\\\"The two arrays do not have the same length.\\\")\\n random_idx = rng.choice(x0_len, x0_len, replace=True)\\n x0_sample = x0[random_idx]\\n x1_sample = x1[random_idx]\\n else:\\n x0_sample = rng.choice(x0, x0_len, replace=True)\\n x1_sample = rng.choice(x1, x1_len, replace=True)\\n \\n out[i] = __es.two_group_difference(x0_sample, x1_sample,\\n is_paired, effect_size)\\n \\n # check whether there are any infinities in the bootstrap,\\n # which likely indicates the sample sizes are too small as\\n # the computation of Cohen's d and Hedges' g necessitated \\n # a division by zero.\\n # Added in v0.2.6.\\n \\n # num_infinities = len(out[np.isinf(out)])\\n # print(num_infinities)\\n # if num_infinities > 0:\\n # warn_msg = \\\"There are {} bootstraps that are not defined. \\\"\\\\\\n # \\\"This is likely due to smaple sample sizes. \\\"\\\\\\n # \\\"The values in a bootstrap for a group will be more likely \\\"\\\\\\n # \\\"to be all equal, with a resulting variance of zero. \\\"\\\\\\n # \\\"The computation of Cohen's d and Hedges' g will therefore \\\"\\\\\\n # \\\"involved a division by zero. \\\"\\n # warnings.warn(warn_msg.format(num_infinities), category=\\\"UserWarning\\\")\\n \\n return out\",\n \"def draw_bs_sample(data):\\n return np.random.choice(data, size=len(data))\",\n \"def _generate_clones(self, data: list[Dict[str, Any]]) -> list[_Clone]:\\n return [_Clone(clone) for clone in data or []]\",\n \"def bootstrap(m, axis=0, n=None, replace=True, return_holdout=False):\\n if n is None:\\n n = m.shape[axis]\\n idx = np.random.choice(m.shape[axis], n, replace=replace)\\n bootstrap = np.take(m, idx, axis=axis)\\n if return_holdout:\\n ran = np.arange(m.shape[axis])\\n holdout_idx = ran[np.array([x not in idx for x in ran])]\\n holdout = np.take(m, holdout_idx, axis=axis)\\n return bootstrap, holdout\\n else:\\n return bootstrap\",\n \"def sample(self):\\n return self(np.random.randn(self.num_xi)).reshape(self.X.shape)\",\n \"def random_init(self, shape):\\n return np.random.randn(shape[0],shape[1])*0.01\",\n \"def build_toy_dataset(N):\\n pi = np.array([0.4, 0.6])\\n mus = [[1, 1], [-1, -1]]\\n stds = [[0.1, 0.1], [0.1, 0.1]]\\n x = np.zeros((N, 2), dtype=np.float32)\\n\\n for n in range(N):\\n k = np.argmax(np.random.multinomial(1, pi))\\n x[n, :] = np.random.multivariate_normal(mus[k], np.diag(stds[k]))\\n\\n return x\",\n \"def generate_samples(self, n_samples):\",\n \"def generate_samples(self, n_samples):\",\n \"def bootstrap(self, X_list, n_sampling):\\n if len(X_list) < 2:\\n raise ValueError('X_list must be a list containing at least two items')\\n\\n n_features = check_array(X_list[0]).shape[1]\\n X_list_ = []\\n for X in X_list:\\n X_ = check_array(X)\\n if X_.shape[1] != n_features:\\n raise ValueError('X_list must be a list with the same number of features')\\n X_list_.append(X_)\\n X_list = np.array(X_list_)\\n\\n if isinstance(n_sampling, (numbers.Integral, np.integer)):\\n if not 0 < n_sampling:\\n raise ValueError('n_sampling must be an integer greater than 0.')\\n else:\\n raise ValueError('n_sampling must be an integer greater than 0.')\\n\\n # Bootstrapping\\n adjacency_matrices_list = [[] for _ in range(X_list.shape[0])]\\n for _ in range(n_sampling):\\n resampled_X_list = [resample(X) for X in X_list]\\n model = self.fit(resampled_X_list)\\n for i, am in enumerate(model.adjacency_matrices_):\\n adjacency_matrices_list[i].append(am)\\n\\n result_list = []\\n for adjacency_matrices in adjacency_matrices_list:\\n result_list.append(BootstrapResult(adjacency_matrices))\\n\\n return result_list\",\n \"def init_batch(self, src):\\n batch, bos = src.size(1), self.src_dict.get_bos()\\n return src.data.new(1, batch).fill_(bos)\",\n \"def vec_repeat_at_start(x, p):\\n n = x.shape[0]\\n indices = (jnp.arange(p) + n - p) % n\\n padding = x[indices]\\n return jnp.concatenate((padding, x))\",\n \"def rand(self, x):\\r\\n return np.random.random(1)[0]\",\n \"def generatePattern(numCols=100, minOnes=21, maxOnes=25):\\n assert minOnes < maxOnes\\n assert maxOnes < numCols\\n\\n nOnes = random.randint(minOnes, maxOnes)\\n ind = random.sample(xrange(numCols), nOnes)\\n x = numpy.zeros(numCols, dtype='float32')\\n x[ind] = 1\\n\\n return x\",\n \"def test_Pad3D16():\\n input_shape = (1, 2, 3)\\n pad = [1, 2]\\n mode = \\\"replicate\\\"\\n res = [[[1, 1, 2, 3, 3, 3], [4, 4, 5, 6, 6, 6]]]\\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\\n obj.base(res=res, padding=pad, mode=mode, data=data, data_format=\\\"NCL\\\")\",\n \"def resample(self):\\n self.X = np.random.uniform(-1, 1, (100, 2))\\n self.generate_y()\\n self.phi = None\\n self.K = 0\\n self.centers = None\\n self.cluster_sizes = None\\n self.g = None\\n self.gamma = None\",\n \"def dice(data, size):\\n\\treturn data.reshape((data.shape[0] // size, size))\",\n \"def bootstrap():\\n Bootstrap()\",\n \"def bootstrap_sample_binomial(k, n, B):\\n\\n vec = np.zeros(n) # Original sample created as a vector\\n vec[0:k] = 1 # 1 == success\\n y = np.zeros(B) # Bootstrap statistics of # success\\n \\n for k in range(B):\\n y[k] = np.sum(np.random.choice(vec,n)) # default is with replacement\\n\\n return y\",\n \"def create_beams(x):\\n return tf.repeat(x, self.num_beams, axis=0)\",\n \"def pad_examples(x, desired_batch_size):\\n batch_pad = desired_batch_size - x.shape[0]\\n tile_dims = [1] * len(x.shape)\\n tile_dims[0] = batch_pad\\n return np.concatenate([x, np.tile(x[-1], tile_dims)], axis=0)\",\n \"def some_simple_data(length=1000000):\\n data = list(range(length))\\n random.shuffle(data)\\n return data\",\n \"def warm_up_exercise():\\n A = np.eye(5)\\n return A\",\n \"def generate_all_samples(self):\\n\\n n_samples, n_dimensions, V = self.n_samples, self.n_dimensions, self.V\\n sample_all = np.zeros([n_samples, n_dimensions])\\n\\n X = int(0)\\n for j in range(1, n_samples):\\n X ^= V[self.index_of_least_significant_zero_bit(j - 1)]\\n sample_all[j][:] = [float(x / math.pow(2, self.scale)) for x in X]\\n return sample_all\",\n \"def _train(self):\\n return np.zeros(1, 10)\",\n \"def network_bootstrap(self, args):\\n pass\",\n \"def SampleReplicate(\\r\\n data: Iterable,\\r\\n factor: int,\\r\\n lazy: bool = True,\\r\\n workers: int = 1,\\r\\n buffer_len: int = 3,\\r\\n *arg: List,\\r\\n **kwargs: Dict\\r\\n) -> Union[SampleReplicateAbstract, DataAbstract, np.ndarray, list]:\\r\\n if lazy:\\r\\n return SampleReplicateAbstract(data, factor, *arg, **kwargs)\\r\\n else:\\r\\n # ToDo: replace by a list and np equivalent\\r\\n return DataAbstract(\\r\\n SampleReplicateAbstract(data, factor, *arg, **kwargs),\\r\\n workers=workers,\\r\\n buffer_len=buffer_len,\\r\\n )[:]\",\n \"def construct_random_initial(self):\\n x = np.random.random((self._crv_size, self._bound))\\n return x\",\n \"def seqBootstrap(indM, sLength=None):\\n if sLength is None:\\n sLength = indM.shape[1]\\n phi = []\\n while len(phi) < sLength:\\n avgU = pd.Series(dtype=\\\"float64\\\")\\n for i in indM:\\n indM_ = indM[phi + [i]]\\n avgU.loc[i] = getAvgUniqueness(indM_).iloc[-1]\\n prob = avgU / avgU.sum()\\n phi += [np.random.choice(indM.columns, p=prob)]\\n return phi\",\n \"def duplicate_data(rng):\\n N = 10\\n keys = [str(1) for _ in range(1,N)]\\n return zip(keys,\\n [1 for _ in range(1,N)],\\n [rng.random(128) for _ in range(N)],\\n [random.choice([range(1,N),None]) for _ in range(N)])\",\n \"def generate_matrix(size) -> np.ndarray:\\n np.random.seed(1)\\n return np.random.rand(size, size) - 0.5\",\n \"def test_Pad3D23():\\n input_shape = (1, 2, 3)\\n # pad = np.array([1, 2]).astype('int32')\\n pad = [1, 2]\\n mode = \\\"replicate\\\"\\n res = [[[1, 2, 3], [1, 2, 3], [4, 5, 6], [4, 5, 6], [4, 5, 6]]]\\n data = np.arange(np.prod(input_shape)).reshape(input_shape) + 1\\n obj.run(res=res, padding=pad, mode=mode, data_format=\\\"NLC\\\", data=data)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7789665","0.77793765","0.740078","0.7145126","0.6915617","0.676676","0.65354204","0.6499645","0.6398692","0.62889034","0.62032557","0.6193025","0.6095193","0.601948","0.5998936","0.58984625","0.5879488","0.58694214","0.5786773","0.5758723","0.5742155","0.57388103","0.5737552","0.5737403","0.56797403","0.5634709","0.5575294","0.557007","0.55336916","0.5503485","0.55015635","0.5490317","0.5466333","0.5436162","0.5428693","0.5420956","0.5413498","0.5401016","0.5398818","0.5392786","0.5383632","0.537286","0.53682005","0.5358771","0.53564507","0.53498226","0.5346811","0.53305167","0.53231895","0.53093857","0.52935773","0.5282692","0.5269428","0.5265371","0.525872","0.5241343","0.52350014","0.52285963","0.52230173","0.5217313","0.5212418","0.52119994","0.5208926","0.52047086","0.5180896","0.5165503","0.5157534","0.5152809","0.5140773","0.5137539","0.51342744","0.5132646","0.51226926","0.510364","0.51021177","0.5098216","0.5098216","0.50953954","0.50922716","0.5089881","0.5085033","0.50813544","0.5078329","0.5075822","0.5072182","0.50716156","0.505836","0.50581676","0.50510406","0.50440925","0.50404197","0.5028255","0.50266","0.50245404","0.50244576","0.5022561","0.50221485","0.50123644","0.50087416","0.500868"],"string":"[\n \"0.7789665\",\n \"0.77793765\",\n \"0.740078\",\n \"0.7145126\",\n \"0.6915617\",\n \"0.676676\",\n \"0.65354204\",\n \"0.6499645\",\n \"0.6398692\",\n \"0.62889034\",\n \"0.62032557\",\n \"0.6193025\",\n \"0.6095193\",\n \"0.601948\",\n \"0.5998936\",\n \"0.58984625\",\n \"0.5879488\",\n \"0.58694214\",\n \"0.5786773\",\n \"0.5758723\",\n \"0.5742155\",\n \"0.57388103\",\n \"0.5737552\",\n \"0.5737403\",\n \"0.56797403\",\n \"0.5634709\",\n \"0.5575294\",\n \"0.557007\",\n \"0.55336916\",\n \"0.5503485\",\n \"0.55015635\",\n \"0.5490317\",\n \"0.5466333\",\n \"0.5436162\",\n \"0.5428693\",\n \"0.5420956\",\n \"0.5413498\",\n \"0.5401016\",\n \"0.5398818\",\n \"0.5392786\",\n \"0.5383632\",\n \"0.537286\",\n \"0.53682005\",\n \"0.5358771\",\n \"0.53564507\",\n \"0.53498226\",\n \"0.5346811\",\n \"0.53305167\",\n \"0.53231895\",\n \"0.53093857\",\n \"0.52935773\",\n \"0.5282692\",\n \"0.5269428\",\n \"0.5265371\",\n \"0.525872\",\n \"0.5241343\",\n \"0.52350014\",\n \"0.52285963\",\n \"0.52230173\",\n \"0.5217313\",\n \"0.5212418\",\n \"0.52119994\",\n \"0.5208926\",\n \"0.52047086\",\n \"0.5180896\",\n \"0.5165503\",\n \"0.5157534\",\n \"0.5152809\",\n \"0.5140773\",\n \"0.5137539\",\n \"0.51342744\",\n \"0.5132646\",\n \"0.51226926\",\n \"0.510364\",\n \"0.51021177\",\n \"0.5098216\",\n \"0.5098216\",\n \"0.50953954\",\n \"0.50922716\",\n \"0.5089881\",\n \"0.5085033\",\n \"0.50813544\",\n \"0.5078329\",\n \"0.5075822\",\n \"0.5072182\",\n \"0.50716156\",\n \"0.505836\",\n \"0.50581676\",\n \"0.50510406\",\n \"0.50440925\",\n \"0.50404197\",\n \"0.5028255\",\n \"0.50266\",\n \"0.50245404\",\n \"0.50244576\",\n \"0.5022561\",\n \"0.50221485\",\n \"0.50123644\",\n \"0.50087416\",\n \"0.500868\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.78276443"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":25696,"cells":{"query":{"kind":"string","value":"Actualiza los canvas, los pinta en esta ventana, y lleva a cabo el flip para mostrar los cambios"},"document":{"kind":"string","value":"def display(self):\n\t\tfor c in self.canvas.values():\n\t\t\tc.update()\n\t\t\tself.superficie.blit(c.superficie, c.origen)\n\t\tpygame.display.flip()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def loop(self, frame):\n self.root = frame\n self.drawUI()\n cv2.imshow('Fotopasca', self.root)","def renderizar(self):\n\t\t# Limpiar la pantalla\n\t\tglClear(GL_COLOR_BUFFER_BIT)\n\t\t# Renderizar la escena\n\t\tself.escena.renderizar()\n\t\t# Renderizar los buffers a la pantalla\n\t\tpygame.display.flip()","def cambiar_escena(self, escena):\n\t\t# Reemplazo directo\n\t\tself.escena = escena\n\t\t# Reiniciar la ventana con el tamaño de la nueva escena\n\t\tprint(\"Iniciando nuevo contexto OpenGL...\")\n\t\tv_ancho, v_alto = escena.tam\n\t\topciones = OPENGL | DOUBLEBUF\n\t\tif escena.pant_compl:\n\t\t\topciones |= FULLSCREEN\n\t\tpygame.display.set_mode((v_ancho, v_alto), opciones)\n\t\t# Título por defecto de la ventana\n\t\tpygame.display.set_caption(escena.nombre)\n\t\t# Reiniciar OpenGL\n\t\tself.gl_ini(v_ancho, v_alto)\n\t\t# Darle los datos del núcleo a la ventana\n\t\tself.escena.nucleo = self\n\t\tself.escena.eventos = self.mapa_eve\n\t\tglClearColor(*escena.color)\n\t\t# Ejecutar la lógica inicial de la escena\n\t\tprint(\"Iniciando escena...\")\n\t\tself.escena.logica_ini()","def draw(self, screen):","def on_draw(self):\n # Clearing the buffers\n self.clear()\n self.set3d()\n # Makes it so color can be added\n glColor3d(1, 1, 1)\n\n self.push(self.player.pos, self.player.rot)\n self.model.draw()\n glPopMatrix()\n self.model.process_queue_slowly()\n\n # Draws the crosshairs on the screen\n self.set2d()\n self.draw_position_label()\n self.draw_reticle()","def _draw(self):\r\n \r\n if self.active:\r\n self.surface = self.activeSurface # Set active surface to be displayed.\r\n else:\r\n self.surface = self.passiveSurface # Set passive surface to be displayed.\r","def before_flip(self):\n from klibs.KLGraphics import blit\n\n if P.show_gaze_dot and self.el.recording:\n try:\n blit(self.tracker_dot, 5, self.el.gaze())\n except RuntimeError:\n pass","def draw(self):\n\n self.squares.draw(self.screen)\n if not self.hide_grid:\n self.draw_grid()\n self.fleas.draw(self.screen)\n pygame.display.flip()","def update(self):\n # Desplazar izquierda/derecha\n self.rect.x += self.cambio_x\n global COL\n COL = False\n # Hemos chocado contra la pared despues de esta actualizacion?\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False)\n for bloque in lista_impactos_bloques:\n #Si nos estamos desplazando hacia la derecha, hacemos que nuestro lado derecho sea el lado izquierdo del objeto que hemos tocado-\n if self.cambio_x > 0:\n self.rect.right = bloque.rect.left\n else:\n # En caso contrario, si nos desplazamos hacia la izquierda, hacemos lo opuesto.\n self.rect.left = bloque.rect.right\n COL = True\n \n # Desplazar arriba/izquierda\n self.rect.y += self.cambio_y\n \n # Comprobamos si hemos chocado contra algo\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False) \n for bloque in lista_impactos_bloques:\n \n # Reseteamos nuestra posicion basandonos en la parte superior/inferior del objeto.\n if self.cambio_y > 0:\n self.rect.bottom = bloque.rect.top \n else:\n self.rect.top = bloque.rect.bottom \n COL = True","def _drawOnCanvas(self):\n self.canvas=np.ones(self.canvas.shape,dtype=np.uint8)*255\n for key in self.elements:\n graphElement=self.elements[key]\n graphElement.draw(self.canvas)\n self.sync=True","def creditos():\n playSegundaria()\n img_creditos = pygame.image.load(\"imagenes/creditos.jpg\")\n screen.blit(img_creditos, (0,0))\n pygame.display.update()\n time.sleep(8)\n run()","def preGameScreen(self) -> None:\n\n # load all images\n # created with: https://de.flamingtext.com/Free-Logo-Designs/\n logo = Image(Configuration.windowWidth / 2 - 750 / 2, Configuration.windowHeight / 4 - 120 / 2, (750, 120),\n \"PongLogo.png\", pathToImage=\"images/Pong/\")\n keys_player_one = Image(Configuration.windowWidth / 4 - 150, Configuration.windowHeight * 3 / 4 - 50,\n (300, 100),\n \"AandD.png\", pathToImage=\"images/Pong/\")\n keys_player_two = Image(Configuration.windowWidth * 3 / 4 - 150, Configuration.windowHeight * 3 / 4 - 50,\n (300, 100),\n \"ArrowLeftRight.png\", pathToImage=\"images/Pong/\")\n\n # draw text and images\n self.surface.fill(Colors.Black)\n self.drawImageOnSurface(logo)\n self.drawImageOnSurface(keys_player_one)\n if not self.hasComputerPlayer: # only draw the control of the second player, if he isn´t a computer player\n self.drawImageOnSurface(keys_player_two)\n self.drawTextOnSurface(\"First player that reaches 1000 points wins!\",\n (Configuration.windowWidth / 2, Configuration.windowHeight / 2), Colors.ByteGreen,\n font=self.font)\n\n self.drawTextOnSurface(\"Controls\",\n (Configuration.windowWidth / 2, Configuration.windowHeight * 3 / 4), Colors.ByteGreen,\n font=self.font)\n\n super().updateScreen() # display images on screen\n\n logger.info(\"Displaying prescreen animation\")\n\n sleep(4) # wait for seconds","def pysweep_before_finish_init(self):\n self.displaycanvas = DisplayCanvas(self.pysweep.master, self.boardsize, self.lcounterlength, self.rcounterlength, self.images)\n self.displaycanvas.pack()\n\n self.pysweep.master.update_idletasks()\n self.displaycanvas.update_idletasks()\n # enode = self.arbitrary()\n # print('DisplayCanvas:', enode)","def draw(self, canvas):\n canvas.delete(\"all\")\n width = canvas.winfo_reqwidth()\n height = canvas.winfo_reqheight()\n\n image = ImageTk.PhotoImage(self.image())\n canvas.create_image(width/2, height/2, image=image)\n canvas.img = image","def draw(self):\n self.game.screen.blit(self.image, self.game.off(self.pos))","def reDraw(self):\n self.canvasIGetDrawnOn.delete(self.spriteOnCanvas)\n self.spriteImage = ImageTk.PhotoImage(self.spriteImageFile.rotate(self.faceHeading, expand=True))\n self.spriteOnCanvas=self.canvasIGetDrawnOn.create_image(self.xPos,self.yPos,image=self.spriteImage)","def draw(self):\n ui.clear()\n ui.draw_board(self)\n ui.output_buffer()","def draw(self): \n pygame.event.clear()\n self.window = ocempgui.widgets.Box(GG.utils.SCREEN_SZ[0], GG.utils.SCREEN_SZ[1])\n self.paintScreen()\n self.paintAvatar()\n self.paintTags()\n self.paintCustomizeZone()\n self.paintButtons()\n self.window.zOrder = 90000\n self.window.depth = 2\n return self.window","def main(self):\n update = self.update\n draw = self.draw\n screen = self.screen\n flip = pg.display.update\n clock = time.time\n frame_length = (1. / self.fps)\n time_since_draw = 0\n last_update = clock()\n fps_timer = 0\n frames = 0\n\n while not self.done:\n clock_tick = clock() - last_update\n last_update = clock()\n time_since_draw += clock_tick\n update(clock_tick)\n if time_since_draw >= frame_length:\n time_since_draw -= frame_length\n draw(screen)\n flip()\n frames += 1\n\n fps_timer, frames = self.handle_fps(clock_tick, fps_timer, frames)\n time.sleep(.01)","def draw():","def actualise_fenetre(self,plateau,fenetre,joueur,info,bouton,etape_texte):\n\n self.affiche_plateau(plateau,fenetre)\n liste_im_joueur = [pygame.image.load(\"joueur\"+str(i)+\".png\").convert_alpha() for i in range(1,5)]\n for i in range (4) :\n x_joueur = 60\n y_joueur = 60\n liste_im_joueur[i] = pygame.transform.scale(liste_im_joueur[i], (int(x_joueur),int(y_joueur)))\n\n for i in range(len(plateau.dico_joueurs)) :\n fenetre.blit(liste_im_joueur[i],(1030,320+i*80))\n fenetre.blit(police_small.render(str(plateau.dico_joueurs[i].nom) + \" : \",False,pygame.Color(\"#000000\")),(800,340+i*75))\n fenetre.blit(police1.render(\"Score : \"+str(plateau.dico_joueurs[i].points),False,pygame.Color(\"#000000\")),(800,340+i*75+15))\n fenetre.blit(police1.render(\"Ordre de mission : \"+str(sorted(plateau.dico_joueurs[i].fantome_target)),False,pygame.Color(\"#000000\")),(800,340+i*75+30))\n fenetre.blit(police1.render(\"Jokers restants : \"+str(plateau.dico_joueurs[i].nb_joker),False,pygame.Color(\"#000000\")),(800,340+i*75+45))\n \n #test texte pour afficher le joueur qui joue\n if self.turn == True :\n fenetre.blit(police.render(\"C'est à vous de jouer\",False,pygame.Color(0,0,0)),(800,240))\n else:\n fenetre.blit(police.render(\"C'est le tour de votre adversaire\",False,pygame.Color(0,0,0)),(800,240))\n \n #affichage du message d'erreur\n for i in range(len(info)) : \n fenetre.blit(police.render(info[i],False,pygame.Color(\"#000000\")),(760,180+i*20))\n \n fenetre.blit(police.render(etape_texte,False,pygame.Color(\"#000000\")),(760,160))\n \n \n bouton.draw(fenetre)\n \n pygame.display.flip()","def on_draw(self):\n arcade.start_render()","def draw(self):\n self.write_image()\n self.update()","def on_draw(self):\n # draw everything","def ventanaprincipal():\r\n titulo_principal=pygame.image.load(\"../recursor/Imagenes juegos/parejas_1.png\")\r\n ventana.blit(titulo_principal, (405,0))\r\n logo_plaython=pygame.image.load(\"../recursor/Imagenes juegos/plaython.png\")#Cargamos la imagen del logo\r\n imagen_decoracion=pygame.image.load(\"../recursor/Imagenes juegos/imagenpc.png\")\r\n imagen_decoracion = pygame.transform.scale(imagen_decoracion, (210, 210))\r\n ventana.blit(logo_plaython, (900, 180))\r\n ventana.blit(imagen_decoracion,(100,240))\r\n titulo_plaython = pygame.image.load(\"../recursor/Imagenes juegos/TITULOPLAYTHON.png\")\r\n titulo_plaython = pygame.transform.scale(titulo_plaython, (240, 150))\r\n ventana.blit(titulo_plaython, (505, 550))","def draw(self, p):\r\n self.active = True\r\n surface = pygame.surfarray.make_surface(p)\r\n self.screen.blit(surface, (0, 0))\r\n pygame.display.flip()\r\n return","def pre_draw(self):","def drawBoard(self):\r\n self.outer.draw(self.surface)\r\n self.background.draw(self.surface)\r\n for point in self.points:\r\n point.draw(self.surface)\r\n point.drawCheckers(self.surface)\r\n self.dice.draw(self.surface)\r\n self.message.draw(self.surface)\r\n self.checkerBox.draw(self.surface)\r\n self.checkerBox.drawCheckers(self.surface)\r\n for bar in self.bar:\r\n bar.draw(self.surface)\r\n bar.drawCheckers(self.surface)\r\n pygame.display.flip()","def draw(self):\r\n self.screen.blit(self.image, self.image.get_rect())","def show(self):\n if self.video:\n self.video.write(self.img)\n cv2.imshow('Simpy', self.img)\n cv2.waitKey(1000 // self.fps)","def draw(self, canvas, pos):\r\n for card in self.deck:\r\n canvas.draw_image(\r\n card_back, CARD_BACK_CENTER,\r\n CARD_BACK_SIZE, pos, CARD_BACK_SIZE)","def drawGeneration(self,screen):\n screen.blit(self.genSurface,(0,0))","def __init__ (self, id_s = \"unknown\",rept = 1,tipo = 1, width = 800, height = 600, fps = 30):\n pygame.init()\n pygame.display.set_caption(\"VIP: BCI\")\n self.tipo = tipo \n self.width = width\n self.height = height\n self.id_s = str(id_s)\n self.rept = int(rept)\n self.dimensions = (self.width, self.height)\n #self.screen = pygame.display.set_mode(self.dimensions, pygame.DOUBLEBUF)\n self.screen = pygame.display.set_mode(self.dimensions, pygame.FULLSCREEN)\n self.imagenR= pygame.image.load(\"R1.png\").convert()\n self.imagenL= pygame.image.load(\"R2.png\").convert()\n self.background = pygame.Surface(self.screen.get_size()).convert()\n self.screen.fill((255,255,255))#Fondo blanco\n self.clock = pygame.time.Clock()\n self.fps = fps\n self.playtime = 0.0\n self.font = pygame.font.SysFont('mono', 40, bold=True)\n size_screen= self.screen.get_size();\n self.x_center = size_screen[0]/2.0 - 210\n self.y_center = size_screen[1]/2.0 - 210","def finish_render():\n get_window().static_display = True\n get_window().flip_count = 0\n get_window().flip()","def draw(self):\n i = 0\n self.window.fill((60,50,20))\n for i in range(len(self.board)):\n for j in range(len(self.board[i])):\n pygame.draw.rect(self.window, ((i+j)%2*255, (i+j)%2*255, (i+j)%2*255), (20+j*100, 20+i*100, 100, 100))\n if self.board[i][j] != 0:\n if self.board[i][j].player == 0:\n color = (200, 0, 0)\n else:\n color = (0, 0, 200)\n if self.board[i][j].direction == 0:\n pygame.draw.ellipse(self.window, color, (30+j*100, 40+i*100, 80, 60))\n elif self.board[i][j].direction == 1:\n pygame.draw.ellipse(self.window, color, (40+j*100, 30+i*100, 60, 80))\n if self.board[i][j].master:\n if self.board[i][j].direction == 0:\n pygame.draw.ellipse(self.window, (255,255,0), (40+j*100, 50+i*100, 60, 40))\n pygame.draw.ellipse(self.window, color, (45+j*100, 55+i*100, 50, 30))\n elif self.board[i][j].direction == 1:\n pygame.draw.ellipse(self.window, (255,255,0), (50+j*100, 40+i*100, 40, 60))\n pygame.draw.ellipse(self.window, color, (55+j*100, 45+i*100, 30, 50))\n \n if self.selected != None:\n pygame.draw.rect(self.window, (200, 200, 0), (20+self.selected[1]*100, 20+self.selected[0]*100, 100, 100), 5)\n pygame.display.flip()","def display_win_view(screen):\n\n pygame.time.Clock().tick(30)\n screen.blit(pygame.image.load('resources//pictures//winb.jpg').convert(), (0, 0))\n pygame.display.flip()","def __draw_game(self) -> None:\n self.__draw_window()\n self.pipes.draw(self.win)\n self.player.draw(self.win)\n pygame.display.update()","def draw_me(self):\r\n\t\tself.image.fill((100, 200, 100))\r\n\t\tif self.active: pg.draw.rect(self.image, (100, 100, 200), self.frame, 3) #if active => draw frame around selected entity width 3\r\n\t\tself.display_surface.blit(self.image, self.rect)","def mostrar(imagenObj,x,y):\n gameDisplay.blit(imagenObj,(x,y))","def draw(self):\r\n self.screen.fill(self.color_bg) \r\n for t in self.thumbs: t.draw(self.screen) \r\n pygame.display.flip()\r\n self.clock.tick(60)","def draw(self):\n self.screen.blit(self.image, self.rect)","def events(self):\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n self.context.open = False\n if event.type == KEYDOWN:\n\n if event.key == K_ESCAPE:\n self.context.open = False\n if event.key == K_SPACE or event.key == K_MENU or event.key == K_q:\n self.setMode((self.mode + 1) % 3)\n if event.key == K_0:\n self.show_polynomial = not(self.show_polynomial)\n if event.key == K_1:\n self.show_image = not(self.show_image)\n if event.key == K_2:\n self.show_drawing = not(self.show_drawing)\n if event.key == K_3:\n self.show_display = not(self.show_display)\n if event.key == K_4:\n self.show_vectors = not(self.show_vectors)\n if event.key == K_5:\n self.show_circles = not(self.show_circles)\n if event.key == K_6:\n self.show_sample = not(self.show_sample)\n if event.key == K_r:\n self.reset()\n if event.key == K_z:\n self.drawing = self.drawing[:-1]\n self.updateSample()\n if event.key == K_s:\n self.save() # Save the coefficients and the graphs\n if event.key == K_d:\n self.saveCoefficients()\n if event.key == K_a:\n # Save a picture the screen\n self.screenshot(self.directory)\n if event.key == K_p:\n self.pause = not(self.pause)\n if event.key == K_f:\n self.context.switch()\n if event.key == K_c:\n self.show_camera = not(self.show_camera)\n if self.show_camera:\n self.context.camera.buildCapture()\n else:\n self.context.camera.destroy()\n if event.type == pygame.MOUSEBUTTONDOWN:\n if (event.button == 1) and (self.mode == 0):\n self.place()\n self.updateSample()\n if event.button == 4:\n self.context.draw.plane.zoom([1.1, 1.1])\n if event.button == 5:\n self.context.draw.plane.zoom([0.9, 0.9])\n\n if event.type == VIDEORESIZE:\n self.context.screen = pygame.display.set_mode(\n (event.w, event.h), RESIZABLE)","def on_draw(self):\n arcade.start_render()\n background()\n self.player_sprite.draw()","def video_loop(self):\n\n _, img = self.vs.read()\n img = imutils.resize(img, width=self.width)\n image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n image = Image.fromarray(image)\n image = ImageTk.PhotoImage(image)\n self.frame.configure(image=image)\n self.frame.photo = image\n\n self.top.after(self.fps, self.video_loop)","def draw(self):\n self.screen.blit(self.image, (self.x_pos1, self.y_pos))\n self.screen.blit(self.image, (self.x_pos2, self.y_pos))","def draw(self):","def draw(self):\n self.screen.fill((0,51,102))\n # get the new drawables\n self.drawables = (self.game_model.get_background_drawables()\n + self.game_model.get_plane_drawables()\n + self.game_model.get_bullet_drawables()\n + self.game_model.get_enemy_drawables())\n for d in self.drawables:\n rect = d.get_rect()\n surf = d.get_surface()\n surf.set_colorkey((255,255,255))\n self.screen.blit(surf, rect)","def draw(self):\r\n\r\n self.screen.fill((0,0,0))\r\n self.sprite_group.draw(self.screen)\r\n pygame.display.flip()","def draw(self, win):\n img = self.tower_imgs\n win.blit(img, (self.x - img.get_width() // 2, self.y - img.get_height() // 2))\n\n if self.selected:\n self.menu.draw(win)","def _update_screen(self):\n self.screen.fill((250,250,250))\n self.rocket.blitme()\n pygame.display.flip()","def prepareForDraw(self, obj_path, camera_path, frame_context, old_data):\n pass","def __init__(self, master=None):\n super().__init__(master)\n self.masterframe = Frame(self.master)\n self.masterframe.pack()\n self.grid = Grid(3)\n self.canvasSize = 100\n self.mX = 0\n self.mY = 0\n self.working = True\n # True is Player 1 and False is Player 2\n self.turn = True\n self.createCanvas()","def initial_draw(self):\n self.player.take_card(self.deck)\n self.dealer.take_card(self.deck)\n self.player.take_card(self.deck)\n self.dealer.put_face_down(self.deck)","def JUEGOPAREJAS():\r\n cuadrados=[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]\r\n ##############Primeramente, definimos los cuadrados de nuestra pizarra##############\r\n Cuadrado1=Rect(420,140,100,100)\r\n Cuadrado2=Rect(520,140,100,100)\r\n Cuadrado3=Rect(620,140,100,100)\r\n Cuadrado4=Rect(720,140,100,100)\r\n Cuadrado5=Rect(420,240,100,100)\r\n Cuadrado6=Rect(520,240,100,100)\r\n Cuadrado7=Rect(620,240,100,100)\r\n Cuadrado8=Rect(720,240,100,100)\r\n Cuadrado9=Rect(420,340,100,100)\r\n Cuadrado10=Rect(520,340,100,100)\r\n Cuadrado11=Rect(620,340,100,100)\r\n Cuadrado12=Rect(720,340,100,100)\r\n Cuadrado13=Rect(420,440,100,100)\r\n Cuadrado14=Rect(520,440,100,100)\r\n Cuadrado15=Rect(620,440,100,100)\r\n Cuadrado16=Rect(720,440,100,100)\r\n\r\n Totalcuadrados=(Cuadrado1,Cuadrado2,Cuadrado3,Cuadrado4,Cuadrado5,Cuadrado6,Cuadrado7,Cuadrado8,Cuadrado9,Cuadrado10,Cuadrado11,Cuadrado12,Cuadrado13,Cuadrado14,Cuadrado15,Cuadrado16)\r\n listafiguras=[]\r\n def ventanaprincipal():\r\n \"\"\"\"\r\n Esta funcion, genera la ventana principal de nuestro juego de parejas. Contiene\r\n cada uno de los titulos e imagenes del juego.\r\n :return None\r\n \"\"\"\r\n titulo_principal=pygame.image.load(\"../recursor/Imagenes juegos/parejas_1.png\")\r\n ventana.blit(titulo_principal, (405,0))\r\n logo_plaython=pygame.image.load(\"../recursor/Imagenes juegos/plaython.png\")#Cargamos la imagen del logo\r\n imagen_decoracion=pygame.image.load(\"../recursor/Imagenes juegos/imagenpc.png\")\r\n imagen_decoracion = pygame.transform.scale(imagen_decoracion, (210, 210))\r\n ventana.blit(logo_plaython, (900, 180))\r\n ventana.blit(imagen_decoracion,(100,240))\r\n titulo_plaython = pygame.image.load(\"../recursor/Imagenes juegos/TITULOPLAYTHON.png\")\r\n titulo_plaython = pygame.transform.scale(titulo_plaython, (240, 150))\r\n ventana.blit(titulo_plaython, (505, 550))\r\n\r\n def dibujarcirculos(x,color):\r\n \"\"\"\r\n Esta funcion, dibuja cada uno de las figuras de forma circular del juego en base a su generacion aleatoria.\r\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\r\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\r\n :return None\r\n \"\"\"\r\n if x==1:\r\n pygame.draw.circle(ventana,color,(470,190),30)\r\n elif x==2:\r\n pygame.draw.circle(ventana,color,(570,190),30)\r\n elif x==3:\r\n pygame.draw.circle(ventana,color,(670,190),30)\r\n elif x==4:\r\n pygame.draw.circle(ventana,color,(770,190),30)\r\n elif x==5:\r\n pygame.draw.circle(ventana,color,(470,290),30)\r\n elif x==6:\r\n pygame.draw.circle(ventana,color,(570,290),30)\r\n elif x==7:\r\n pygame.draw.circle(ventana,color,(670,290),30)\r\n elif x==8:\r\n pygame.draw.circle(ventana,color,(770,290),30)\r\n elif x==9:\r\n pygame.draw.circle(ventana,color,(470,390),30)\r\n elif x==10:\r\n pygame.draw.circle(ventana,color,(570,390),30)\r\n elif x==11:\r\n pygame.draw.circle(ventana,color,(670,390),30)\r\n elif x==12:\r\n pygame.draw.circle(ventana,color,(770,390),30)\r\n elif x==13:\r\n pygame.draw.circle(ventana,color,(470,490),30)\r\n elif x==14:\r\n pygame.draw.circle(ventana,color,(570,490),30)\r\n elif x==15:\r\n pygame.draw.circle(ventana,color,(670,490),30)\r\n elif x==16:\r\n pygame.draw.circle(ventana,color,(770,490),30)\r\n\r\n def dibujarcuadrados(x,color):\r\n \"\"\"\r\n Esta funcion, dibuja cada uno de las figuras de forma cuadrada del juego en base a su generacion aleatoria.\r\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\r\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\r\n :return None\r\n \"\"\"\r\n if x==1:\r\n pygame.draw.rect(ventana,color,Rect(440,160,60,60))\r\n elif x==2:\r\n pygame.draw.rect(ventana,color,Rect(540,160,60,60))\r\n elif x==3:\r\n pygame.draw.rect(ventana,color,Rect(640,160,60,60))\r\n elif x==4:\r\n pygame.draw.rect(ventana,color,Rect(740,160,60,60))\r\n elif x==5:\r\n pygame.draw.rect(ventana,color,Rect(440,260,60,60))\r\n elif x==6:\r\n pygame.draw.rect(ventana,color,Rect(540,260,60,60))\r\n elif x==7:\r\n pygame.draw.rect(ventana,color,Rect(640,260,60,60))\r\n elif x==8:\r\n pygame.draw.rect(ventana,color,Rect(740,260,60,60))\r\n elif x==9:\r\n pygame.draw.rect(ventana,color,Rect(440,360,60,60))\r\n elif x==10:\r\n pygame.draw.rect(ventana,color,Rect(540,360,60,60))\r\n elif x==11:\r\n pygame.draw.rect(ventana,color,Rect(640,360,60,60))\r\n elif x==12:\r\n pygame.draw.rect(ventana,color,Rect(740,360,60,60))\r\n elif x==13:\r\n pygame.draw.rect(ventana,color,Rect(440,460,60,60))\r\n elif x==14:\r\n pygame.draw.rect(ventana,color,Rect(540,460,60,60))\r\n elif x==15:\r\n pygame.draw.rect(ventana,color,Rect(640,460,60,60))\r\n elif x==16:\r\n pygame.draw.rect(ventana,color,Rect(740,460,60,60))\r\n\r\n def dibujardiamantes(x,color):\r\n \"\"\"\r\n Esta funcion, dibuja cada uno de las figuras de forma de diamante del juego en base a su generacion aleatoria.\r\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\r\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\r\n :return None\r\n \"\"\"\r\n if x==1:\r\n pygame.draw.polygon(ventana,color,( (430,190),(470,160),(510,190),(470,220)))\r\n elif x==2:\r\n pygame.draw.polygon(ventana,color,( (530,190),(570,160),(610,190),(570,220) ))\r\n elif x==3:\r\n pygame.draw.polygon(ventana,color,( (630,190),(670,160),(710,190),(670,220) ))\r\n elif x==4:\r\n pygame.draw.polygon(ventana,color,( (730,190),(770,160),(810,190),(770,220) ))\r\n elif x==5:\r\n pygame.draw.polygon(ventana,color,( (430,290),(470,260),(510,290),(470,320) ))\r\n elif x==6:\r\n pygame.draw.polygon(ventana,color,( (530,290),(570,260),(610,290),(570,320) ))\r\n elif x==7:\r\n pygame.draw.polygon(ventana,color,( (630,290),(670,260),(710,290),(670,320) ))\r\n elif x==8:\r\n pygame.draw.polygon(ventana,color,( (730,290),(770,260),(810,290),(770,320) ))\r\n elif x==9:\r\n pygame.draw.polygon(ventana,color,( (430,390),(470,360),(510,390),(470,420) ))\r\n elif x==10:\r\n pygame.draw.polygon(ventana,color,( (530,390),(570,360),(610,390),(570,420) ))\r\n elif x==11:\r\n pygame.draw.polygon(ventana,color,( (630,390),(670,360),(710,390),(670,420) ))\r\n elif x==12:\r\n pygame.draw.polygon(ventana,color,( (730,390),(770,360),(810,390),(770,420) ))\r\n elif x==13:\r\n pygame.draw.polygon(ventana,color,( (430,490),(470,460),(510,490),(470,520) ))\r\n elif x==14:\r\n pygame.draw.polygon(ventana,color,( (530,490),(570,460),(610,490),(570,520) ))\r\n elif x==15:\r\n pygame.draw.polygon(ventana,color,( (630,490),(670,460),(710,490),(670,520) ))\r\n elif x==16:\r\n pygame.draw.polygon(ventana,color,( (730,490),(770,460),(810,490),(770,520) ))\r\n def dibujartriangulos(x,color):\r\n \"\"\"\r\n Esta funcion, dibuja cada uno de las figuras de forma triangular del juego en base a su generacion aleatoria.\r\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\r\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\r\n :return None\r\n \"\"\"\r\n if x==1:\r\n pygame.draw.polygon(ventana,color,( (430,160),(510,160),(470,220) ))\r\n elif x==2:\r\n pygame.draw.polygon(ventana,color,( (530,160),(610,160),(570,220) ))\r\n elif x==3:\r\n pygame.draw.polygon(ventana,color,( (630,160),(710,160),(670,220) ))\r\n elif x==4:\r\n pygame.draw.polygon(ventana,color,( (730,160),(810,160),(770,220) ))\r\n elif x==5:\r\n pygame.draw.polygon(ventana,color,( (430,260),(510,260),(470,320)))\r\n elif x==6:\r\n pygame.draw.polygon(ventana,color,( (530,260),(610,260),(570,320) ))\r\n elif x==7:\r\n pygame.draw.polygon(ventana,color,( (630,260),(710,260),(670,320) ))\r\n elif x==8:\r\n pygame.draw.polygon(ventana,color,( (730,260),(810,260),(770,320) ))\r\n elif x==9:\r\n pygame.draw.polygon(ventana,color,( (430,360),(510,360),(470,420) ))\r\n elif x==10:\r\n pygame.draw.polygon(ventana,color,( (530,360),(610,360),(570,420) ))\r\n elif x==11:\r\n pygame.draw.polygon(ventana,color,( (630,360),(710,360),(670,420) ))\r\n elif x==12:\r\n pygame.draw.polygon(ventana,color,( (730,360),(810,360),(770,420) ))\r\n elif x==13:\r\n pygame.draw.polygon(ventana,color,( (430,460),(510,460),(470,520) ))\r\n elif x==14:\r\n pygame.draw.polygon(ventana,color,( (530,460),(610,460),(570,520) ))\r\n elif x==15:\r\n pygame.draw.polygon(ventana,color,( (630,460),(710,460),(670,520) ))\r\n elif x==16:\r\n pygame.draw.polygon(ventana,color,( (730,460),(810,460),(770,520) ))\r\n\r\n def iniciarjuego():\r\n \"\"\"\"\r\n Esta funcion, crea cuatro figuras de cada una de las posibles, dos de ellas con diferente color de las otras dos.\r\n \"\"\"\r\n for i in range(4):\r\n if i == 1 or i == 0:\r\n color = (250,208,120,98)\r\n else:\r\n color = (159, 250, 120,98)\r\n x = random.choice(cuadrados)\r\n listafiguras.append(x)\r\n dibujarcuadrados(x, color)\r\n cuadrados.remove(x)\r\n\r\n for i in range(4):\r\n if i == 0 or i == 1:\r\n color = (195, 139, 255,100)\r\n else:\r\n color = (250, 242, 120,98)\r\n x = random.choice(cuadrados)\r\n listafiguras.append(x)\r\n dibujarcirculos(x, color)\r\n cuadrados.remove(x)\r\n\r\n for i in range(4):\r\n if i == 0 or i == 1:\r\n color = (250, 145, 137,98)\r\n else:\r\n color = (126, 139, 250,98)\r\n x = random.choice(cuadrados)\r\n listafiguras.append(x)\r\n dibujartriangulos(x, color)\r\n cuadrados.remove(x)\r\n\r\n for i in range(4):\r\n if i == 0 or i == 1:\r\n color = (176, 255, 237,100)\r\n else:\r\n color = (255, 176, 228,100)\r\n x = random.choice(cuadrados)\r\n listafiguras.append(x)\r\n dibujardiamantes(x, color)\r\n cuadrados.remove(x)\r\n\r\n def mostrar(posicion_del_mouse):\r\n \"\"\"\r\n Esta funcion muestra segun la casilla que clickee el jugador.\r\n :param tuple posicion_del_mouse: Este parametro representa segun clickee el jugador (posicion en x y y).\r\n \"\"\"\r\n numerodecuadrado = numerocuadrado(posicion_del_mouse)\r\n ubicaciondelcuadrado=ubicacion_cuadrado(posicion_del_mouse)\r\n if ubicaciondelcuadrado==0 or ubicaciondelcuadrado==1:\r\n color = (250,208,120,98)\r\n dibujarcuadrados(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==2 or ubicaciondelcuadrado==3:\r\n color = (159, 250, 120,98)\r\n dibujarcuadrados(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==4 or ubicaciondelcuadrado==5:\r\n color = (195, 139, 255,100)\r\n dibujarcirculos(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==6 or ubicaciondelcuadrado==7:\r\n color = (250, 242, 120,98)\r\n dibujarcirculos(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==8 or ubicaciondelcuadrado==9:\r\n color = (250, 145, 137,98)\r\n dibujartriangulos(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==10 or ubicaciondelcuadrado==11:\r\n color = (126, 139, 250,98)\r\n dibujartriangulos(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==12 or ubicaciondelcuadrado==13:\r\n color = (176, 255, 237,100)\r\n dibujardiamantes(numerodecuadrado,color)\r\n elif ubicaciondelcuadrado==14 or ubicaciondelcuadrado==15:\r\n color = (255, 176, 228,100)\r\n dibujardiamantes(numerodecuadrado,color)\r\n\r\n def esconderfichas(posicion_del_mouse):\r\n \"\"\"\"\r\n Esta funcion, esconde las fichas, si la seleccion del usuario no es la correcta.\r\n :param tuple posicion_del_mouse: :param tuple primeraeleccion: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\r\n \"\"\"\r\n numerodecuadrado=numerocuadrado(posicion_del_mouse)\r\n for j in range(16):\r\n if numerodecuadrado==j+1:\r\n pygame.draw.rect(ventana,(135,206,250),Totalcuadrados[j].inflate(-10,-10))\r\n\r\n def encontrarparejas(primeraeleccion,segundaeleccion):\r\n \"\"\"\r\n Esta funcion determina si se encontro una pareja.\r\n :param tuple primeraeleccion: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\r\n :param tuple segundaeleccion: Representa la segunda posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\r\n Retorna un booleano\r\n \"\"\"\r\n x=ubicacion_cuadrado(primeraeleccion)\r\n y=ubicacion_cuadrado(segundaeleccion)\r\n if (x==0 and y==1 or x==1 and y==0)\\\r\n or (x == 2 and y == 3 or x == 3 and y == 2) \\\r\n or (x == 4 and y == 5 or x == 5 and y == 4)\\\r\n or (x == 6 and y == 7 or x == 7 and y == 6)\\\r\n or (x == 8 and y == 9 or x == 9 and y == 8) \\\r\n or (x==10 and y==11 or x==11 and y==10)\\\r\n or (x==12 and y==13 or x==13 and y==12)\\\r\n or (x==14 and y==15 or x==15 and y==14):\r\n return True\r\n\r\n def ubicacion_cuadrado(posicion_del_mouse):\r\n \"\"\"\r\n Esta funcion, retorna la figura que se encuentra en determinado indice segun se clickee.\r\n :param tuple posicion_del_mouse: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\r\n Retorna la figura de determinado indice\r\n \"\"\"\r\n for j in range(16):\r\n if Totalcuadrados[j].collidepoint(posicion_del_mouse):\r\n return listafiguras.index(j+1)\r\n\r\n def dibujartablero():\r\n \"\"\"\"\r\n Esta funcion, dibuja los cuadrados que hacen nuestro tablero.\r\n :return None\r\n \"\"\"\r\n ventana.fill((135,206,250)) #colocamos el color de fondo de nuestra pantalla\r\n for j in range(16): #iteramos entre los cuadrados ya diseñados, eligiendo parametros como el color y el grueso de sus lineas.\r\n pygame.draw.rect(ventana,(255,255,255),Totalcuadrados[j],10)\r\n\r\n def numerocuadrado(posicion_del_mouse):\r\n \"\"\"\r\n Esta funcion, retorna el indice de determinado cuadrado segun se clickee.\r\n :param tuple posicion_del_mouse: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\r\n Retorna el indice de terminada posicion\r\n \"\"\"\r\n\r\n for j in range(16):\r\n if Totalcuadrados[j].collidepoint(posicion_del_mouse):\r\n return j+1\r\n\r\n def main():\r\n \"\"\"\"\r\n Funcion proncipal del juego.\r\n :return None\r\n \"\"\"\r\n pygame.init()\r\n global ventana\r\n ventana= pygame.display.set_mode((1280,700))\r\n ventana.fill((135,206,250))\r\n pygame.display.set_caption('Encuentra las parejas')\r\n logo = pygame.image.load(\"../recursor/icono.ico\")\r\n pygame.display.set_icon(logo)\r\n pygame.display.update()\r\n dibujartablero()\r\n iniciarjuego()\r\n titulo_principal=pygame.image.load(\"../recursor/Imagenes juegos/parejas_2.png\")\r\n ventana.blit(titulo_principal, (405,0))\r\n pygame.display.update()\r\n pygame.time.wait(3000)\r\n dibujartablero()\r\n ventanaprincipal()\r\n pygame.display.update()\r\n prueba=0\r\n eleccioncorrecta=[]\r\n while True:\r\n for event in pygame.event.get():\r\n if event.type==QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n elif event.type==pygame.MOUSEBUTTONUP:\r\n posicion_del_mouse=pygame.mouse.get_pos()\r\n mostrar(posicion_del_mouse)\r\n pygame.display.update()\r\n if prueba==0:\r\n primeraeleccion=posicion_del_mouse\r\n if numerocuadrado(primeraeleccion) in eleccioncorrecta:\r\n prueba=0\r\n else:\r\n prueba=1\r\n else:\r\n segundaeleccion=posicion_del_mouse\r\n if numerocuadrado(segundaeleccion) in eleccioncorrecta:\r\n prueba=1\r\n else:\r\n prueba=0\r\n if not (numerocuadrado(primeraeleccion) in eleccioncorrecta) and not numerocuadrado(segundaeleccion) in eleccioncorrecta:\r\n if encontrarparejas(primeraeleccion,segundaeleccion):\r\n eleccioncorrecta.append(numerocuadrado(primeraeleccion))\r\n eleccioncorrecta.append(numerocuadrado(segundaeleccion))\r\n else:\r\n pygame.time.wait(1000)\r\n esconderfichas(primeraeleccion)\r\n esconderfichas(segundaeleccion)\r\n pygame.display.update()\r\n\r\n if len(eleccioncorrecta)==16:\r\n ganador=pygame.image.load('../recursor/Imagenes juegos/Ganadorgg0000.png')\r\n ventana.blit(ganador,(420, 140))\r\n pygame.display.update()\r\n time.sleep(4)\r\n pygame.quit()\r\n break\r\n\r\n main()","def draw(self):\n self.screen.fill(BACKGROUND_COLOR)\n self.cannon.draw(self.screen)\n self.objects.draw(self.screen)","def draw():\n screen.fill((0, 0, 0))\n alien.draw()","def save_file(camera, frame):\n save = input(\"Would you like to save your drawing? Enter yes or no \")\n if save == \"yes\" or save == \"y\" or save == \"ye\" or save == \"yes \": # accounting for typos\n name = input(\"What would you like to name your masterpiece? \")\n filename = 'images/' + name + '.png'\n cv2.imwrite(filename, cv2.flip(frame,1)) # saves the image as the last frame\n camera.release()\n pygame.quit()\n\n # reopen saved picture to display for user\n img = cv2.imread(filename, 1)\n b,g,r = cv2.split(img) # get b,g,r\n rgb_img = cv2.merge([r,g,b]) # convert from bgr colorspace to rgb\n crop_img = rgb_img[36:450, 0:600] # crop out the colorbar\n cv2.imshow(filename, crop_img)\n cv2.imwrite(filename, crop_img)\n cv2.waitKey(10000)\n cv2.destroyAllWindows()\n camera.release()\n pygame.quit() # cleanup the camera and close any open windows\n else:\n print(\"Thank you for trying CVPaint!\")\n pygame.quit()\n camera.release()\n cv2.destroyAllWindows()","def update(self):\n\n surface = pygame.Surface(CARD_SIZE, pygame.SRCALPHA)\n card_filename = f\"assets/sprites/cardBack.png\"\n card_image = pygame.image.load(card_filename).convert_alpha()\n surface.blit(card_image, (0, 0))\n self.image = surface\n self.rect = self.image.get_rect()","def draw(self):\n self.bufferX = (self.appWidth/2) - self.viewX\n self.bufferY = (self.appHeight/2) - self.viewY\n anwp.sl.engine.clear()\n anwp.sl.engine.drawImage(0, 0, self.appWidth, self.appHeight, self.backgroundImage)\n self.drawWarpLines()\n \n # render engine\n anwp.sl.engine.render()\n self.drawSystemInfo()\n self.drawWarpGateInfo()\n self.drawWarpTradeInfo()","def setup_draw(self):\n pass","def redraw(self):\n self.vispy_viewer.canvas.update()","def __display(self):\n self.__rotate_model()\n self.__generate_shadows()\n self.__generate_model()\n\n glutSwapBuffers()\n if self.__callback is not None:\n self.__callback()","def _blit_images(self):\n self.screen.blit(self.dial, (self.dialPos))\n self.screen.blit(self.rotatedImage, self.rotatedImageRectangle)","def new_canvas(self):\n libtcod.console_clear(self.console)","def draw_card(dealer,player):\n # hidden_img = Image(img_path+\"back.png\")\n depth = 100\n x0,y0 = 100,100\n x1,y1 = 100,300\n ix = 30\n\n bj_board.clear()\n for card in dealer:\n if card.state:\n card.image.moveTo(x0, y0)\n card.image.setDepth(depth)\n bj_board.add(card.image)\n else:\n img = Image(img_path+\"Back.png\")\n img.moveTo(x0, y0)\n img.setDepth(depth)\n bj_board.add(img)\n x0 += ix\n \n for card in player:\n if card.state:\n card.image.moveTo(x1, y1)\n card.image.setDepth(depth)\n bj_board.add(card.image)\n else:\n img = Image(img_path+\"back.png\")\n img.moveTo(x1, y1)\n img.setDepth(depth)\n bj_board.add(img)\n x1 += ix","def on_show_view(self):\n self.setup()\n arcade.set_background_color(arcade.color.BLACK)\n arcade.set_viewport(0, constants.SCREEN_WIDTH - 1, 0, constants.SCREEN_HEIGHT - 1)","def draw_how_to(self):\n howto = pygame.image.load(res.IMG_HOW_TO)\n self.screen.blit(howto, (0, 0))","def update_frame(self):\n if self.should_reset_camera:\n self.ren.ResetCamera()\n self.should_reset_camera = False\n self.interactor.Render()\n app.processEvents()","def update_frame(self):\n if self.should_reset_camera:\n self.ren.ResetCamera()\n self.should_reset_camera = False\n self.interactor.Render()\n app.processEvents()","def update_display(self):\n self.lick_plot_0.setData(self.k+self.T,self.buffer[:,1]) \n self.lick_plot_1.setData(self.k+self.T,self.buffer[:,2]) \n self.breathing_plot.setData(self.k+self.T,self.buffer[:,0]) \n \n if self.settings.movie_on.value():\n self.camera_image.setImage(self.camera.read())\n if self.settings.save_movie.value():\n self.camera.write()\n \n #print(self.buffer_h5.size)","def draw(self, surface):\n\n\t\tsurface.blit(self.image, self.rect.topleft)","def redraw(self):\n x2, y2 = [[] for i in range(len(self.x))], \\\n [[] for i in range(len(self.x))]\n game_point = [random.randint(1, 100),\n random.randint(1, 100)]\n for i in range(self.generations):\n x2, y2, game_point = self.move(x2, y2, game_point)\n for i in range(10): # Czyszczenie starych wykresow\n self.plots[i].set_xdata([])\n self.plots[i].set_ydata([])\n self.plots2[i].set_xdata([])\n self.plots2[i].set_ydata([])\n for i in range(len(self.x)): # Nowe dane wykresow\n self.plots[i].set_xdata(self.x[i])\n self.plots[i].set_ydata(self.y[i])\n self.plots2[i].set_xdata(x2[i])\n self.plots2[i].set_ydata(y2[i])\n self.fig.canvas.draw_idle()","def draw(self):\n\t\tpass","def move(self):\n \n self.rect.move_ip(0,self.speed) # Funcion para mover el enemigo especificando la velocidad xy\n \n if (self.rect.top > SCREEN_HEIGHT): # Condicion cuando llega a la parte inferior y no colisiono con el jugador\n del self.surf #Libera memoria\n del self.rect\n self.randomNumber = random.choice([70,64,32]) # Su tamaño se asigna nuevamente\n self.size = (self.randomNumber,self.randomNumber) #Se genera su tamaño como un cuadrado de lado aleatorio\n self.surf = pygame.Surface(self.size) #Se genera la superficie que aparecera la pantalla\n self.surf.fill(RED)\n self.rect = self.surf.get_rect(center = (random.randint(40,SCREEN_WIDTH-40),0))# me da info de las coordenadas de surf\n if(self.randomNumber == 32):\n self.surf = self.imagen\n elif(self.randomNumber ==64):\n self.surf = self.imagen2\n elif self.randomNumber ==70 :\n self.surf = self.imagen3","def update_drawer_img(self):\n self.drawer = aggdraw.Draw(self.img)\n self.drawer.settransform(self.coordspace_transform)","def draw(self):\n pass","def draw(self):\n pass","def draw(self):\n pass","def draw(self):\n pass","def updateScreen(self) -> None:\n\n # fill game display black\n self.surface.fill(Colors.Black)\n\n # draw players and ball\n self.drawImageOnSurface(self.player_one)\n self.drawImageOnSurface(self.player_two)\n self.drawImageOnSurface(self.ball)\n\n # draw all the spacer images\n for image in self.spacers:\n self.drawImageOnSurface(image)\n\n # draw scores and format the scores in byte representation\n self.drawTextOnSurface(format(self._score[0], \"04b\"),\n (Configuration.windowWidth / 4, Configuration.windowHeight / 2), Colors.ByteGreen,\n font=self.font)\n self.drawTextOnSurface(format(self._score[1], \"04b\"),\n (3 * Configuration.windowWidth / 4, Configuration.windowHeight / 2), Colors.ByteGreen,\n font=self.font)\n\n super().updateScreen() # call the parent method to update the screen","def update_deck_display(self):\n self.deck_surface.fill(CLEARCOLOUR)\n self.deck_surface.blit(self.background, (0, 0))\n if not self.is_empty():\n cards_to_draw = self.cards\n if self.draw_from_last:\n cards_to_draw = reversed(cards_to_draw)\n\n for i, card in enumerate(cards_to_draw):\n selected = (i == self.selected_card)\n image_to_draw = card.image\n\n if self.deck_reveal == DeckReveal.HIDE_ALL:\n image_to_draw = card.backimage\n\n if self.flip:\n image_to_draw = pygame.transform.flip(image_to_draw, self.vert_orientation,\n not self.vert_orientation)\n\n self.deck_surface.blit(image_to_draw, (card.x - selected * card.x * 0.5 *\n (-1)**self.flip * self.vert_orientation,\n card.y - selected * card.y * 0.5 *\n (-1)**self.flip * (not self.vert_orientation)))","def create_canvas(self):\n self.canvas = tk.Canvas(\n self,\n bd=-2,\n height=self.controller.GAME_HEIGHT,\n width=self.controller.GAME_WIDTH)\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)","def create_canvas(self):\n self.canvas = tk.Canvas(\n self,\n bd=-2,\n height=self.controller.GAME_HEIGHT,\n width=self.controller.GAME_WIDTH)\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)","def create_canvas(self):\n self.canvas = tk.Canvas(\n self,\n bd=-2,\n height=self.controller.GAME_HEIGHT,\n width=self.controller.GAME_WIDTH)\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)","def update_current_image(self):\n\n rect = (0, 0, self.variables.canvas_width, self.variables.canvas_height)\n if self.variables.canvas_image_object is not None:\n self.variables.canvas_image_object.update_canvas_display_image_from_canvas_rect(rect)\n self.set_image_from_numpy_array(self.variables.canvas_image_object.display_image)\n self.update()","def draw(self, surface):\r\n if self.visible:\r\n surface.blit(self.image, (self.x, self.y))","def _drawFrame(self):\n\n self._clearScreen()\n \n for object in Object.Objects:\n self._drawObject(object)\n\n for entity in Entity.Entities:\n self._drawObject(entity)\n\n self._drawObject(Game.Player)","def flip(self):","def main():\r\n pygame.init()\r\n global ventana\r\n ventana= pygame.display.set_mode((1280,700))\r\n ventana.fill((135,206,250))\r\n pygame.display.set_caption('Encuentra las parejas')\r\n logo = pygame.image.load(\"../recursor/icono.ico\")\r\n pygame.display.set_icon(logo)\r\n pygame.display.update()\r\n dibujartablero()\r\n iniciarjuego()\r\n titulo_principal=pygame.image.load(\"../recursor/Imagenes juegos/parejas_2.png\")\r\n ventana.blit(titulo_principal, (405,0))\r\n pygame.display.update()\r\n pygame.time.wait(3000)\r\n dibujartablero()\r\n ventanaprincipal()\r\n pygame.display.update()\r\n prueba=0\r\n eleccioncorrecta=[]\r\n while True:\r\n for event in pygame.event.get():\r\n if event.type==QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n elif event.type==pygame.MOUSEBUTTONUP:\r\n posicion_del_mouse=pygame.mouse.get_pos()\r\n mostrar(posicion_del_mouse)\r\n pygame.display.update()\r\n if prueba==0:\r\n primeraeleccion=posicion_del_mouse\r\n if numerocuadrado(primeraeleccion) in eleccioncorrecta:\r\n prueba=0\r\n else:\r\n prueba=1\r\n else:\r\n segundaeleccion=posicion_del_mouse\r\n if numerocuadrado(segundaeleccion) in eleccioncorrecta:\r\n prueba=1\r\n else:\r\n prueba=0\r\n if not (numerocuadrado(primeraeleccion) in eleccioncorrecta) and not numerocuadrado(segundaeleccion) in eleccioncorrecta:\r\n if encontrarparejas(primeraeleccion,segundaeleccion):\r\n eleccioncorrecta.append(numerocuadrado(primeraeleccion))\r\n eleccioncorrecta.append(numerocuadrado(segundaeleccion))\r\n else:\r\n pygame.time.wait(1000)\r\n esconderfichas(primeraeleccion)\r\n esconderfichas(segundaeleccion)\r\n pygame.display.update()\r\n\r\n if len(eleccioncorrecta)==16:\r\n ganador=pygame.image.load('../recursor/Imagenes juegos/Ganadorgg0000.png')\r\n ventana.blit(ganador,(420, 140))\r\n pygame.display.update()\r\n time.sleep(4)\r\n pygame.quit()\r\n break","def draw_pavement():\n\n roberto.penup()\n roberto.goto(-345, -100)\n roberto.pendown()\n roberto.begin_fill()\n for i in range(4): # this loop draws a big black rectangle that is positioned at the bottom part of the screen\n roberto.forward(684)\n roberto.right(90)\n roberto.end_fill()","def punched(self):\n if not self.dizzy:\n self.dizzy= 1\n self.original= self.image","def viewUpdate(self):\n # Update Capture\n imgtk = self.model.capture\n self.updateImage(self.view.lmain, imgtk)\n # Update Stitch \n imgtk = self.model.stitch\n self.updateImage(self.view.rmain, imgtk)\n self.view.dist.set(self.model.dist)","def set_mode(self, size, buffered=True, *args, **kwargs):\n self.canvas = Canvas(size, buffered)\n env.set_env('canvas', self.canvas)\n self.frame = Window.getDocumentRoot()\n env.set_env('frame', self.frame)\n panel = SimplePanel(Widget=self.canvas)\n RootPanel().add(panel)\n self.panel = panel\n self.vpanel = None\n self.textbox = None\n self.textarea = None\n self.Textbox = Textbox\n self.Textarea = Textarea\n self.surface = self.canvas.surface\n self.surface._display = self\n self._surface_rect = self.surface.get_rect()\n if not self.canvas._bufferedimage:\n self.flip = lambda: None\n self.update = lambda *arg: None\n return self.surface","def setBlackFrame(self):\r\n frame = ImageTk.PhotoImage(Image.fromarray(np.array([[0]*self.w]*self.h)))\r\n self.player.config(image=frame)\r\n self.player.image = frame","def draw(self, win, player, displayList, enemyHitboxList, mapWidth, mapHeight):\n cameraX = player.rect.left + (player.rect.width // 2) - (SCREEN_WIDTH // 2)\n cameraY = player.rect.top + (player.rect.height // 2) - (SCREEN_HEIGHT // 2)\n\n # On centre la camera tant que le joueurs n'atteind pas les bords\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\n self.x = cameraX\n\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\n self.y = cameraY\n\n # Calcul de l'X du joueur en fonction s'il est en haut, bas ou entre les 2\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\n playerX = (SCREEN_WIDTH // 2) - (player.rect.width // 2)\n else:\n # Si le joueur est a droite\"\"\"\n if cameraX >= mapWidth - SCREEN_WIDTH:\n self.x = mapWidth - SCREEN_WIDTH\n playerX = player.rect.left - mapWidth + SCREEN_WIDTH\n # Si le joueur est a gauche\"\"\"\n else:\n self.x = 0\n playerX = player.rect.left\n\n\n # Calcul de l'Y du joueur en fonction s'il est a gauche, droite ou entre les 2\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\n playerY = (SCREEN_HEIGHT // 2) - (player.rect.height // 2)\n else:\n # Si le joueur est en dessous\n if cameraY >= mapHeight - SCREEN_HEIGHT:\n self.y = mapHeight - SCREEN_HEIGHT\n playerY = player.rect.top - mapHeight + SCREEN_HEIGHT\n # Si le joueur est au dessus \n else:\n self.y = 0\n playerY = player.rect.top\n\n for element in displayList:\n element.draw(win,element.rect.left - self.x,element.rect.top - self.y)\n #for elem in enemyHitboxList:\n #pg.draw.rect(win, (200, 200, 200), pg.Rect(elem.left - self.x,elem.top - self.y, elem.width, elem.height))\n player.draw(win, playerX, playerY)","def __init__(self, screen_width:int, screen_height:int, screen, sensitivity:int, max_fps:int, debug:bool):\n\n #Call the superclass init method\n super().__init__(screen_width, screen_height, screen, State(102), sensitivity, max_fps, 0.1, debug)\n\n #Commander brief image\n self.bg = ImageObject(300, 285, 600, 570, StoryTemplate.sprites['commander_brief'], debug)\n\n #Image of figure head (To be replaced with the actual image)\n self.marco = ImageObject(300, 215, 217, 217, StoryTemplate.sprites['yuckerberg'], debug)\n self.marco.scale(217,217)\n\n #Image of the commander\n self.commander = ImageObject(300, 210, 217, 217, StoryTemplate.sprites['silloette_commander'], debug)\n self.commander.scale(217,217)\n\n #Textbox\n self.tb = ImageObject(300, 685, 600, 230, StoryTemplate.sprites['textbox'], debug)","def _update_screen(self):\n self.screen.fill(self.settings.bg_color)\n self.sideways_ship.blitme()\n for bullet in self.bullets.sprites():\n bullet.draw_bullet()\n self.aliens.draw(self.screen)\n pygame.display.flip()","def main(winstyle = 0):\n pygame.init()\n # Try to init the sound\n if pygame.mixer and not pygame.mixer.get_init():\n print ('Error, no hay sonido')\n pygame.mixer = None\n \n # Set the screen mode\n winstyle = RESIZABLE # FULLSCREEN for fullscreen\n bestColorDepth = pygame.display.mode_ok(SCREENRECT.size, winstyle, 32)\n screen = pygame.display.set_mode(SCREENRECT.size, winstyle, bestColorDepth)\n \n # Load the images of the Sprite classes\n Player.images = assembleSprite('rubia.gif', (42,60), (4,2))\n Fairy.images = assembleSprites((40,40), (3,1), 'hadaDO.gif', 'hadaRE.gif', 'hadaMI.gif', 'hadaFA.gif', 'hadaSOL.gif', 'hadaLA.gif', 'hadaSI.gif')\n Step.images = load_images('pent_flores.gif', 'pent1.gif', 'pent2.gif', 'pent3.gif', 'pent4.gif', 'pent5.gif', 'pent6.gif')\n StepMove.images = [load_image('pent1_mover.gif')]\n Block.images = load_images('bloque_pent1.gif', 'bloque_pent2.gif', 'bloque_pent3.gif', 'bloque_pent4.gif', 'bloque_pent5.gif')\n Note.images = load_images('do.gif', 're.gif', 'mi.gif', 'fa.gif', 'sol.gif', 'la.gif', 'si.gif')\n Score.notesImages = load_images('do2.gif', 're2.gif', 'mi2.gif', 'fa2.gif', 'sol2.gif', 'la2.gif', 'si2.gif', 'borde.gif')\n Shot.images = load_images('do2.gif', 're2.gif', 'mi2.gif', 'fa2.gif', 'sol2.gif', 'la2.gif', 'si2.gif', 'ruido.gif')\n \n \n # Create the visualization window\n pygame.display.set_icon(load_image('icon.gif'))\n pygame.display.set_caption('Lost Sound')\n \n # Greate the background\n bgdImage = load_image('background.bmp')\n background = pygame.Surface(screen.get_size())\n background = background.convert()\n background.blit(bgdImage, (0, 0))\n\n screen.blit(background, (0,0))\n pygame.display.flip()\n \n # Load the sound\n if pygame.mixer:\n sounds = load_sounds('do.wav', 're.wav', 'mi.wav', 'fa.wav', 'sol.wav', 'la.wav', 'si.wav', 'ruido.wav')\n dead_sound = load_sound('morir.wav')\n dead_sound.set_volume(0.5)\n for s in sounds:\n s.set_volume(0.8)\n sounds[7].set_volume(0.2)\n\n # Load the music \n if pygame.mixer:\n file = os.path.join(main_dir, 'data', 'I_Talk_to_the_Rain.mp3')\n pygame.mixer.music.load(file)\n pygame.mixer.music.set_volume(0.8)\n pygame.mixer.music.play(-1) # Makes the music sound a number of times. -1 infinite\n \n # Init the sprites Groups\n fairies = pygame.sprite.Group()\n steps = pygame.sprite.Group()\n stepsM = pygame.sprite.Group()\n blocks = pygame.sprite.Group()\n notes = pygame.sprite.Group()\n shots = pygame.sprite.Group()\n all = pygame.sprite.Group()\n \n # Assign Sprites to the Groups\n Player.containers = all\n Fairy.containers = fairies, all\n Step.containers = steps, all\n StepMove.containers = stepsM, all\n Block.containers = blocks, all\n Note.containers = notes, all\n Shot.containers = shots, all\n Score.containers = all\n ScoreF.containers = all\n Help.containers = all\n \n # Variables needed\n clock = pygame.time.Clock()\n SELECTED_NOTE = -1\n SCORE = 0\n\n # Init the Sprites\n player = Player(PLAYER_SPEEDX,FLOORRECT)\n PLAYER_POS = player.rect.left\n\n Note(0,(500, 100),PLAYER_POS,SCREEN_SPEED)\n Note(1,(2350, 150),PLAYER_POS,SCREEN_SPEED)\n Note(2,(4000, 10),PLAYER_POS,SCREEN_SPEED)\n Note(3,(6450, 120),PLAYER_POS,SCREEN_SPEED)\n Note(4,(7250, 20),PLAYER_POS,SCREEN_SPEED)\n Note(5,(8700, 30),PLAYER_POS,SCREEN_SPEED)\n Note(6,(10150, 200),PLAYER_POS,SCREEN_SPEED)\n \n Step(0,(400,350),PLAYER_POS,SCREEN_SPEED)\n Step(3,(2400,350),PLAYER_POS,SCREEN_SPEED)\n Step(2,(3500,350),PLAYER_POS,SCREEN_SPEED)\n Step(4,(4250,250),PLAYER_POS,SCREEN_SPEED)\n Step(1,(4850,200),PLAYER_POS,SCREEN_SPEED)\n Step(5,(5670,350),PLAYER_POS,SCREEN_SPEED)\n Step(6,(6450,200),PLAYER_POS,SCREEN_SPEED)\n Step(3,(6950,200),PLAYER_POS,SCREEN_SPEED)\n Step(2,(7550,300),PLAYER_POS,SCREEN_SPEED)\n Step(1,(9150,200),PLAYER_POS,SCREEN_SPEED)\n Step(2,(10500,200),PLAYER_POS,SCREEN_SPEED)\n Step(3,(11200,350),PLAYER_POS,SCREEN_SPEED)\n\n StepMove(0,(8600,400),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\n \n Block(0,(2200, 50),PLAYER_POS,SCREEN_SPEED)\n Block(2,(6350, 0),PLAYER_POS,SCREEN_SPEED)\n\n Fairy(0,(1100, 200),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\n for j in range(1200,10300,150):\n i = random.randrange(0,7)\n k = random.randrange(j,j+150)\n l = random.randrange(200,450)\n appear = random.choice((0,1))\n if appear:\n Fairy(i,(k, l),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\n \n score = Score((20,50),SCREEN_SPEED)\n scoreF = ScoreF()\n if pygame.font:\n all.add(scoreF)\n \n help = Help(PLAYER_POS,SCREEN_SPEED)\n \n while player.alive():\n # Set the fps\n timePassed = clock.tick(50)\n\n # Check if the player wants to quit and get the key pressed\n for event in pygame.event.get():\n if event.type == QUIT or \\\n (event.type == KEYDOWN and event.key == K_ESCAPE):\n return\n keystate = pygame.key.get_pressed()\n \n # Clear the Sprites from the screen\n all.clear(screen, background)\n SELECTED_NOTE = player.selectedNote\n\n # updated all the Sprites status\n all.update()\n \n # Read the inputs and update the status variables\n directionX = keystate[K_RIGHT] - keystate[K_LEFT]\n jumpState = keystate[K_UP]\n firing = keystate[K_SPACE]\n noteUP = keystate[K_d]\n noteDOWN = keystate[K_s]\n\n if (noteUP or noteDOWN) and not player.changing:\n player.changing = 1\n player.selectNote(noteUP,noteDOWN)\n elif (not noteUP and not noteDOWN) and player.changing:\n player.changing = 0\n \n if not player.reloading and firing and len(shots) < MAX_SHOTS:\n Shot(player.gunPos(), player.facingX, player.selectedNote, SCREENRECT)\n sounds[player.selectedNote].play()\n player.reloading = firing \n\n # Create the effect of the player jump\n if not player.jumping and jumpState:\n player.setJumpBase(player.rect.bottom)\n player.jumping = 1\n player.setSpeed(player.speedX,player.jumpSpeed)\n else:\n if player.jumping and (player.jumpBase <= player.rect.bottom):\n player.jumping = 0\n elif player.jumping and player.climbed:\n player.setJumpBase(player.rect.bottom)\n player.jumping = 0\n elif player.jumping and player.climbedB:\n player.setJumpBase(player.rect.bottom)\n player.jumping = 0\n\n # Update the player and move it\n player.setSpeed(PLAYER_SPEEDX,player.speedY)\n player.gravity(0,0.05)\n player.move(directionX,timePassed)\n\n # Create the effect of movement in the screen\n directionX = -directionX\n # If the player has reached the end and has all the notes, the screen freezes\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20):\n pass\n elif (player.rect.left == FLOORRECT.left or player.rect.right == FLOORRECT.right) and PLAYER_POS >= END_LVL:\n if PLAYER_POS <= BEGIN_LVL:\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\n elif PLAYER_POS >= BEGIN_LVL and directionX == -1:\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\n elif PLAYER_POS <= END_LVL and directionX == 1:\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\n\n # Update the player position for the other Sprites\n for note in notes:\n note.updatePlayerPos(PLAYER_POS)\n for fairy in fairies:\n fairy.updatePlayerPos(PLAYER_POS)\n for step in steps:\n step.updatePlayerPos(PLAYER_POS)\n for step in stepsM:\n step.updatePlayerPos(PLAYER_POS)\n for block in blocks:\n block.updatePlayerPos(PLAYER_POS)\n help.updatePlayerPos(PLAYER_POS)\n\n # Check collisions between the obstacles and the player\n player.climbed = 0 \n for step in pygame.sprite.spritecollide(player, steps, 0):\n if step.rect.top <= player.rect.bottom and step.rect.bottom <> player.rect.bottom and step.rect.centery > player.rect.bottom:\n player.setSpeed(player.speedX,0)\n player.position((0,-1))\n player.climbed = 1\n\n player.climbedB = 0 \n for step in pygame.sprite.spritecollide(player, stepsM, 0):\n if step.rect.top <= player.rect.bottom and step.rect.bottom <> player.rect.bottom and step.rect.centery > player.rect.bottom:\n player.setSpeed(player.speedX,0)\n player.position((0,5*step.facingY))\n player.climbedB = 1\n \n for block in pygame.sprite.spritecollide(player, blocks, 0):\n if block.rect.left <= player.rect.right:\n player.setSpeed(0,player.speedY)\n player.position((-11,0))\n\n # Check collisions with the notes\n for note in pygame.sprite.spritecollide(player, notes, 0):\n # Hacer un sonido\n id = note.kill()\n player.insertNote(id)\n score.addNote(id)\n scoreF.addPoints(100)\n\n # Check collisions between the blocks and the shots\n for shot, block in pygame.sprite.groupcollide(shots, blocks, 1, 0).items():\n if block[0].id == shot.id:\n block[0].kill()\n\n for shot, step in pygame.sprite.groupcollide(shots, stepsM, 1, 0).items():\n if step[0].id == shot.id:\n step[0].activate()\n \n # Check collisions with the fairies\n for fairy in pygame.sprite.spritecollide(player, fairies, 1):\n dead_sound.play()\n player.kill()\n\n # Check collisions between the fairies and the shots\n for shot, fairy in pygame.sprite.groupcollide(shots, fairies, 1, 0).items():\n if fairy[0].id == shot.id:\n fairy[0].kill()\n dead_sound.play()\n scoreF.addPoints(10)\n else:\n fairy[0].lives = fairy[0].lives-1\n if fairy[0].lives == 0:\n dead_sound.play()\n scoreF.addPoints(1)\n \n background.blit(bgdImage, (PLAYER_POS,0))\n screen.blit(background, (0,0))\n\n # Check if the player has reached the end and has all the notes\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20):\n result = game_end(scoreF.getScore())\n result[1].center = screen.get_rect().center\n screen.blit(result[0], result[1])\n \n # Draw the updated Sprites\n dirty = all.draw(screen)\n pygame.display.flip()\n\n # Check if the end has ended\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20): \n pygame.time.wait(3000)\n return\n \n # Stop the music and quit\n if pygame.mixer:\n pygame.mixer.music.stop()\n pygame.time.wait(1000)\n pygame.quit()","def Draw(self):\n\t\tGameImage.Draw(self, self.coords)","def on_show(self): \n arcade.set_background_color(arcade.color.BLACK)"],"string":"[\n \"def loop(self, frame):\\n self.root = frame\\n self.drawUI()\\n cv2.imshow('Fotopasca', self.root)\",\n \"def renderizar(self):\\n\\t\\t# Limpiar la pantalla\\n\\t\\tglClear(GL_COLOR_BUFFER_BIT)\\n\\t\\t# Renderizar la escena\\n\\t\\tself.escena.renderizar()\\n\\t\\t# Renderizar los buffers a la pantalla\\n\\t\\tpygame.display.flip()\",\n \"def cambiar_escena(self, escena):\\n\\t\\t# Reemplazo directo\\n\\t\\tself.escena = escena\\n\\t\\t# Reiniciar la ventana con el tamaño de la nueva escena\\n\\t\\tprint(\\\"Iniciando nuevo contexto OpenGL...\\\")\\n\\t\\tv_ancho, v_alto = escena.tam\\n\\t\\topciones = OPENGL | DOUBLEBUF\\n\\t\\tif escena.pant_compl:\\n\\t\\t\\topciones |= FULLSCREEN\\n\\t\\tpygame.display.set_mode((v_ancho, v_alto), opciones)\\n\\t\\t# Título por defecto de la ventana\\n\\t\\tpygame.display.set_caption(escena.nombre)\\n\\t\\t# Reiniciar OpenGL\\n\\t\\tself.gl_ini(v_ancho, v_alto)\\n\\t\\t# Darle los datos del núcleo a la ventana\\n\\t\\tself.escena.nucleo = self\\n\\t\\tself.escena.eventos = self.mapa_eve\\n\\t\\tglClearColor(*escena.color)\\n\\t\\t# Ejecutar la lógica inicial de la escena\\n\\t\\tprint(\\\"Iniciando escena...\\\")\\n\\t\\tself.escena.logica_ini()\",\n \"def draw(self, screen):\",\n \"def on_draw(self):\\n # Clearing the buffers\\n self.clear()\\n self.set3d()\\n # Makes it so color can be added\\n glColor3d(1, 1, 1)\\n\\n self.push(self.player.pos, self.player.rot)\\n self.model.draw()\\n glPopMatrix()\\n self.model.process_queue_slowly()\\n\\n # Draws the crosshairs on the screen\\n self.set2d()\\n self.draw_position_label()\\n self.draw_reticle()\",\n \"def _draw(self):\\r\\n \\r\\n if self.active:\\r\\n self.surface = self.activeSurface # Set active surface to be displayed.\\r\\n else:\\r\\n self.surface = self.passiveSurface # Set passive surface to be displayed.\\r\",\n \"def before_flip(self):\\n from klibs.KLGraphics import blit\\n\\n if P.show_gaze_dot and self.el.recording:\\n try:\\n blit(self.tracker_dot, 5, self.el.gaze())\\n except RuntimeError:\\n pass\",\n \"def draw(self):\\n\\n self.squares.draw(self.screen)\\n if not self.hide_grid:\\n self.draw_grid()\\n self.fleas.draw(self.screen)\\n pygame.display.flip()\",\n \"def update(self):\\n # Desplazar izquierda/derecha\\n self.rect.x += self.cambio_x\\n global COL\\n COL = False\\n # Hemos chocado contra la pared despues de esta actualizacion?\\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False)\\n for bloque in lista_impactos_bloques:\\n #Si nos estamos desplazando hacia la derecha, hacemos que nuestro lado derecho sea el lado izquierdo del objeto que hemos tocado-\\n if self.cambio_x > 0:\\n self.rect.right = bloque.rect.left\\n else:\\n # En caso contrario, si nos desplazamos hacia la izquierda, hacemos lo opuesto.\\n self.rect.left = bloque.rect.right\\n COL = True\\n \\n # Desplazar arriba/izquierda\\n self.rect.y += self.cambio_y\\n \\n # Comprobamos si hemos chocado contra algo\\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False) \\n for bloque in lista_impactos_bloques:\\n \\n # Reseteamos nuestra posicion basandonos en la parte superior/inferior del objeto.\\n if self.cambio_y > 0:\\n self.rect.bottom = bloque.rect.top \\n else:\\n self.rect.top = bloque.rect.bottom \\n COL = True\",\n \"def _drawOnCanvas(self):\\n self.canvas=np.ones(self.canvas.shape,dtype=np.uint8)*255\\n for key in self.elements:\\n graphElement=self.elements[key]\\n graphElement.draw(self.canvas)\\n self.sync=True\",\n \"def creditos():\\n playSegundaria()\\n img_creditos = pygame.image.load(\\\"imagenes/creditos.jpg\\\")\\n screen.blit(img_creditos, (0,0))\\n pygame.display.update()\\n time.sleep(8)\\n run()\",\n \"def preGameScreen(self) -> None:\\n\\n # load all images\\n # created with: https://de.flamingtext.com/Free-Logo-Designs/\\n logo = Image(Configuration.windowWidth / 2 - 750 / 2, Configuration.windowHeight / 4 - 120 / 2, (750, 120),\\n \\\"PongLogo.png\\\", pathToImage=\\\"images/Pong/\\\")\\n keys_player_one = Image(Configuration.windowWidth / 4 - 150, Configuration.windowHeight * 3 / 4 - 50,\\n (300, 100),\\n \\\"AandD.png\\\", pathToImage=\\\"images/Pong/\\\")\\n keys_player_two = Image(Configuration.windowWidth * 3 / 4 - 150, Configuration.windowHeight * 3 / 4 - 50,\\n (300, 100),\\n \\\"ArrowLeftRight.png\\\", pathToImage=\\\"images/Pong/\\\")\\n\\n # draw text and images\\n self.surface.fill(Colors.Black)\\n self.drawImageOnSurface(logo)\\n self.drawImageOnSurface(keys_player_one)\\n if not self.hasComputerPlayer: # only draw the control of the second player, if he isn´t a computer player\\n self.drawImageOnSurface(keys_player_two)\\n self.drawTextOnSurface(\\\"First player that reaches 1000 points wins!\\\",\\n (Configuration.windowWidth / 2, Configuration.windowHeight / 2), Colors.ByteGreen,\\n font=self.font)\\n\\n self.drawTextOnSurface(\\\"Controls\\\",\\n (Configuration.windowWidth / 2, Configuration.windowHeight * 3 / 4), Colors.ByteGreen,\\n font=self.font)\\n\\n super().updateScreen() # display images on screen\\n\\n logger.info(\\\"Displaying prescreen animation\\\")\\n\\n sleep(4) # wait for seconds\",\n \"def pysweep_before_finish_init(self):\\n self.displaycanvas = DisplayCanvas(self.pysweep.master, self.boardsize, self.lcounterlength, self.rcounterlength, self.images)\\n self.displaycanvas.pack()\\n\\n self.pysweep.master.update_idletasks()\\n self.displaycanvas.update_idletasks()\\n # enode = self.arbitrary()\\n # print('DisplayCanvas:', enode)\",\n \"def draw(self, canvas):\\n canvas.delete(\\\"all\\\")\\n width = canvas.winfo_reqwidth()\\n height = canvas.winfo_reqheight()\\n\\n image = ImageTk.PhotoImage(self.image())\\n canvas.create_image(width/2, height/2, image=image)\\n canvas.img = image\",\n \"def draw(self):\\n self.game.screen.blit(self.image, self.game.off(self.pos))\",\n \"def reDraw(self):\\n self.canvasIGetDrawnOn.delete(self.spriteOnCanvas)\\n self.spriteImage = ImageTk.PhotoImage(self.spriteImageFile.rotate(self.faceHeading, expand=True))\\n self.spriteOnCanvas=self.canvasIGetDrawnOn.create_image(self.xPos,self.yPos,image=self.spriteImage)\",\n \"def draw(self):\\n ui.clear()\\n ui.draw_board(self)\\n ui.output_buffer()\",\n \"def draw(self): \\n pygame.event.clear()\\n self.window = ocempgui.widgets.Box(GG.utils.SCREEN_SZ[0], GG.utils.SCREEN_SZ[1])\\n self.paintScreen()\\n self.paintAvatar()\\n self.paintTags()\\n self.paintCustomizeZone()\\n self.paintButtons()\\n self.window.zOrder = 90000\\n self.window.depth = 2\\n return self.window\",\n \"def main(self):\\n update = self.update\\n draw = self.draw\\n screen = self.screen\\n flip = pg.display.update\\n clock = time.time\\n frame_length = (1. / self.fps)\\n time_since_draw = 0\\n last_update = clock()\\n fps_timer = 0\\n frames = 0\\n\\n while not self.done:\\n clock_tick = clock() - last_update\\n last_update = clock()\\n time_since_draw += clock_tick\\n update(clock_tick)\\n if time_since_draw >= frame_length:\\n time_since_draw -= frame_length\\n draw(screen)\\n flip()\\n frames += 1\\n\\n fps_timer, frames = self.handle_fps(clock_tick, fps_timer, frames)\\n time.sleep(.01)\",\n \"def draw():\",\n \"def actualise_fenetre(self,plateau,fenetre,joueur,info,bouton,etape_texte):\\n\\n self.affiche_plateau(plateau,fenetre)\\n liste_im_joueur = [pygame.image.load(\\\"joueur\\\"+str(i)+\\\".png\\\").convert_alpha() for i in range(1,5)]\\n for i in range (4) :\\n x_joueur = 60\\n y_joueur = 60\\n liste_im_joueur[i] = pygame.transform.scale(liste_im_joueur[i], (int(x_joueur),int(y_joueur)))\\n\\n for i in range(len(plateau.dico_joueurs)) :\\n fenetre.blit(liste_im_joueur[i],(1030,320+i*80))\\n fenetre.blit(police_small.render(str(plateau.dico_joueurs[i].nom) + \\\" : \\\",False,pygame.Color(\\\"#000000\\\")),(800,340+i*75))\\n fenetre.blit(police1.render(\\\"Score : \\\"+str(plateau.dico_joueurs[i].points),False,pygame.Color(\\\"#000000\\\")),(800,340+i*75+15))\\n fenetre.blit(police1.render(\\\"Ordre de mission : \\\"+str(sorted(plateau.dico_joueurs[i].fantome_target)),False,pygame.Color(\\\"#000000\\\")),(800,340+i*75+30))\\n fenetre.blit(police1.render(\\\"Jokers restants : \\\"+str(plateau.dico_joueurs[i].nb_joker),False,pygame.Color(\\\"#000000\\\")),(800,340+i*75+45))\\n \\n #test texte pour afficher le joueur qui joue\\n if self.turn == True :\\n fenetre.blit(police.render(\\\"C'est à vous de jouer\\\",False,pygame.Color(0,0,0)),(800,240))\\n else:\\n fenetre.blit(police.render(\\\"C'est le tour de votre adversaire\\\",False,pygame.Color(0,0,0)),(800,240))\\n \\n #affichage du message d'erreur\\n for i in range(len(info)) : \\n fenetre.blit(police.render(info[i],False,pygame.Color(\\\"#000000\\\")),(760,180+i*20))\\n \\n fenetre.blit(police.render(etape_texte,False,pygame.Color(\\\"#000000\\\")),(760,160))\\n \\n \\n bouton.draw(fenetre)\\n \\n pygame.display.flip()\",\n \"def on_draw(self):\\n arcade.start_render()\",\n \"def draw(self):\\n self.write_image()\\n self.update()\",\n \"def on_draw(self):\\n # draw everything\",\n \"def ventanaprincipal():\\r\\n titulo_principal=pygame.image.load(\\\"../recursor/Imagenes juegos/parejas_1.png\\\")\\r\\n ventana.blit(titulo_principal, (405,0))\\r\\n logo_plaython=pygame.image.load(\\\"../recursor/Imagenes juegos/plaython.png\\\")#Cargamos la imagen del logo\\r\\n imagen_decoracion=pygame.image.load(\\\"../recursor/Imagenes juegos/imagenpc.png\\\")\\r\\n imagen_decoracion = pygame.transform.scale(imagen_decoracion, (210, 210))\\r\\n ventana.blit(logo_plaython, (900, 180))\\r\\n ventana.blit(imagen_decoracion,(100,240))\\r\\n titulo_plaython = pygame.image.load(\\\"../recursor/Imagenes juegos/TITULOPLAYTHON.png\\\")\\r\\n titulo_plaython = pygame.transform.scale(titulo_plaython, (240, 150))\\r\\n ventana.blit(titulo_plaython, (505, 550))\",\n \"def draw(self, p):\\r\\n self.active = True\\r\\n surface = pygame.surfarray.make_surface(p)\\r\\n self.screen.blit(surface, (0, 0))\\r\\n pygame.display.flip()\\r\\n return\",\n \"def pre_draw(self):\",\n \"def drawBoard(self):\\r\\n self.outer.draw(self.surface)\\r\\n self.background.draw(self.surface)\\r\\n for point in self.points:\\r\\n point.draw(self.surface)\\r\\n point.drawCheckers(self.surface)\\r\\n self.dice.draw(self.surface)\\r\\n self.message.draw(self.surface)\\r\\n self.checkerBox.draw(self.surface)\\r\\n self.checkerBox.drawCheckers(self.surface)\\r\\n for bar in self.bar:\\r\\n bar.draw(self.surface)\\r\\n bar.drawCheckers(self.surface)\\r\\n pygame.display.flip()\",\n \"def draw(self):\\r\\n self.screen.blit(self.image, self.image.get_rect())\",\n \"def show(self):\\n if self.video:\\n self.video.write(self.img)\\n cv2.imshow('Simpy', self.img)\\n cv2.waitKey(1000 // self.fps)\",\n \"def draw(self, canvas, pos):\\r\\n for card in self.deck:\\r\\n canvas.draw_image(\\r\\n card_back, CARD_BACK_CENTER,\\r\\n CARD_BACK_SIZE, pos, CARD_BACK_SIZE)\",\n \"def drawGeneration(self,screen):\\n screen.blit(self.genSurface,(0,0))\",\n \"def __init__ (self, id_s = \\\"unknown\\\",rept = 1,tipo = 1, width = 800, height = 600, fps = 30):\\n pygame.init()\\n pygame.display.set_caption(\\\"VIP: BCI\\\")\\n self.tipo = tipo \\n self.width = width\\n self.height = height\\n self.id_s = str(id_s)\\n self.rept = int(rept)\\n self.dimensions = (self.width, self.height)\\n #self.screen = pygame.display.set_mode(self.dimensions, pygame.DOUBLEBUF)\\n self.screen = pygame.display.set_mode(self.dimensions, pygame.FULLSCREEN)\\n self.imagenR= pygame.image.load(\\\"R1.png\\\").convert()\\n self.imagenL= pygame.image.load(\\\"R2.png\\\").convert()\\n self.background = pygame.Surface(self.screen.get_size()).convert()\\n self.screen.fill((255,255,255))#Fondo blanco\\n self.clock = pygame.time.Clock()\\n self.fps = fps\\n self.playtime = 0.0\\n self.font = pygame.font.SysFont('mono', 40, bold=True)\\n size_screen= self.screen.get_size();\\n self.x_center = size_screen[0]/2.0 - 210\\n self.y_center = size_screen[1]/2.0 - 210\",\n \"def finish_render():\\n get_window().static_display = True\\n get_window().flip_count = 0\\n get_window().flip()\",\n \"def draw(self):\\n i = 0\\n self.window.fill((60,50,20))\\n for i in range(len(self.board)):\\n for j in range(len(self.board[i])):\\n pygame.draw.rect(self.window, ((i+j)%2*255, (i+j)%2*255, (i+j)%2*255), (20+j*100, 20+i*100, 100, 100))\\n if self.board[i][j] != 0:\\n if self.board[i][j].player == 0:\\n color = (200, 0, 0)\\n else:\\n color = (0, 0, 200)\\n if self.board[i][j].direction == 0:\\n pygame.draw.ellipse(self.window, color, (30+j*100, 40+i*100, 80, 60))\\n elif self.board[i][j].direction == 1:\\n pygame.draw.ellipse(self.window, color, (40+j*100, 30+i*100, 60, 80))\\n if self.board[i][j].master:\\n if self.board[i][j].direction == 0:\\n pygame.draw.ellipse(self.window, (255,255,0), (40+j*100, 50+i*100, 60, 40))\\n pygame.draw.ellipse(self.window, color, (45+j*100, 55+i*100, 50, 30))\\n elif self.board[i][j].direction == 1:\\n pygame.draw.ellipse(self.window, (255,255,0), (50+j*100, 40+i*100, 40, 60))\\n pygame.draw.ellipse(self.window, color, (55+j*100, 45+i*100, 30, 50))\\n \\n if self.selected != None:\\n pygame.draw.rect(self.window, (200, 200, 0), (20+self.selected[1]*100, 20+self.selected[0]*100, 100, 100), 5)\\n pygame.display.flip()\",\n \"def display_win_view(screen):\\n\\n pygame.time.Clock().tick(30)\\n screen.blit(pygame.image.load('resources//pictures//winb.jpg').convert(), (0, 0))\\n pygame.display.flip()\",\n \"def __draw_game(self) -> None:\\n self.__draw_window()\\n self.pipes.draw(self.win)\\n self.player.draw(self.win)\\n pygame.display.update()\",\n \"def draw_me(self):\\r\\n\\t\\tself.image.fill((100, 200, 100))\\r\\n\\t\\tif self.active: pg.draw.rect(self.image, (100, 100, 200), self.frame, 3) #if active => draw frame around selected entity width 3\\r\\n\\t\\tself.display_surface.blit(self.image, self.rect)\",\n \"def mostrar(imagenObj,x,y):\\n gameDisplay.blit(imagenObj,(x,y))\",\n \"def draw(self):\\r\\n self.screen.fill(self.color_bg) \\r\\n for t in self.thumbs: t.draw(self.screen) \\r\\n pygame.display.flip()\\r\\n self.clock.tick(60)\",\n \"def draw(self):\\n self.screen.blit(self.image, self.rect)\",\n \"def events(self):\\n for event in pygame.event.get():\\n if event.type == pygame.QUIT:\\n self.context.open = False\\n if event.type == KEYDOWN:\\n\\n if event.key == K_ESCAPE:\\n self.context.open = False\\n if event.key == K_SPACE or event.key == K_MENU or event.key == K_q:\\n self.setMode((self.mode + 1) % 3)\\n if event.key == K_0:\\n self.show_polynomial = not(self.show_polynomial)\\n if event.key == K_1:\\n self.show_image = not(self.show_image)\\n if event.key == K_2:\\n self.show_drawing = not(self.show_drawing)\\n if event.key == K_3:\\n self.show_display = not(self.show_display)\\n if event.key == K_4:\\n self.show_vectors = not(self.show_vectors)\\n if event.key == K_5:\\n self.show_circles = not(self.show_circles)\\n if event.key == K_6:\\n self.show_sample = not(self.show_sample)\\n if event.key == K_r:\\n self.reset()\\n if event.key == K_z:\\n self.drawing = self.drawing[:-1]\\n self.updateSample()\\n if event.key == K_s:\\n self.save() # Save the coefficients and the graphs\\n if event.key == K_d:\\n self.saveCoefficients()\\n if event.key == K_a:\\n # Save a picture the screen\\n self.screenshot(self.directory)\\n if event.key == K_p:\\n self.pause = not(self.pause)\\n if event.key == K_f:\\n self.context.switch()\\n if event.key == K_c:\\n self.show_camera = not(self.show_camera)\\n if self.show_camera:\\n self.context.camera.buildCapture()\\n else:\\n self.context.camera.destroy()\\n if event.type == pygame.MOUSEBUTTONDOWN:\\n if (event.button == 1) and (self.mode == 0):\\n self.place()\\n self.updateSample()\\n if event.button == 4:\\n self.context.draw.plane.zoom([1.1, 1.1])\\n if event.button == 5:\\n self.context.draw.plane.zoom([0.9, 0.9])\\n\\n if event.type == VIDEORESIZE:\\n self.context.screen = pygame.display.set_mode(\\n (event.w, event.h), RESIZABLE)\",\n \"def on_draw(self):\\n arcade.start_render()\\n background()\\n self.player_sprite.draw()\",\n \"def video_loop(self):\\n\\n _, img = self.vs.read()\\n img = imutils.resize(img, width=self.width)\\n image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\\n image = Image.fromarray(image)\\n image = ImageTk.PhotoImage(image)\\n self.frame.configure(image=image)\\n self.frame.photo = image\\n\\n self.top.after(self.fps, self.video_loop)\",\n \"def draw(self):\\n self.screen.blit(self.image, (self.x_pos1, self.y_pos))\\n self.screen.blit(self.image, (self.x_pos2, self.y_pos))\",\n \"def draw(self):\",\n \"def draw(self):\\n self.screen.fill((0,51,102))\\n # get the new drawables\\n self.drawables = (self.game_model.get_background_drawables()\\n + self.game_model.get_plane_drawables()\\n + self.game_model.get_bullet_drawables()\\n + self.game_model.get_enemy_drawables())\\n for d in self.drawables:\\n rect = d.get_rect()\\n surf = d.get_surface()\\n surf.set_colorkey((255,255,255))\\n self.screen.blit(surf, rect)\",\n \"def draw(self):\\r\\n\\r\\n self.screen.fill((0,0,0))\\r\\n self.sprite_group.draw(self.screen)\\r\\n pygame.display.flip()\",\n \"def draw(self, win):\\n img = self.tower_imgs\\n win.blit(img, (self.x - img.get_width() // 2, self.y - img.get_height() // 2))\\n\\n if self.selected:\\n self.menu.draw(win)\",\n \"def _update_screen(self):\\n self.screen.fill((250,250,250))\\n self.rocket.blitme()\\n pygame.display.flip()\",\n \"def prepareForDraw(self, obj_path, camera_path, frame_context, old_data):\\n pass\",\n \"def __init__(self, master=None):\\n super().__init__(master)\\n self.masterframe = Frame(self.master)\\n self.masterframe.pack()\\n self.grid = Grid(3)\\n self.canvasSize = 100\\n self.mX = 0\\n self.mY = 0\\n self.working = True\\n # True is Player 1 and False is Player 2\\n self.turn = True\\n self.createCanvas()\",\n \"def initial_draw(self):\\n self.player.take_card(self.deck)\\n self.dealer.take_card(self.deck)\\n self.player.take_card(self.deck)\\n self.dealer.put_face_down(self.deck)\",\n \"def JUEGOPAREJAS():\\r\\n cuadrados=[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]\\r\\n ##############Primeramente, definimos los cuadrados de nuestra pizarra##############\\r\\n Cuadrado1=Rect(420,140,100,100)\\r\\n Cuadrado2=Rect(520,140,100,100)\\r\\n Cuadrado3=Rect(620,140,100,100)\\r\\n Cuadrado4=Rect(720,140,100,100)\\r\\n Cuadrado5=Rect(420,240,100,100)\\r\\n Cuadrado6=Rect(520,240,100,100)\\r\\n Cuadrado7=Rect(620,240,100,100)\\r\\n Cuadrado8=Rect(720,240,100,100)\\r\\n Cuadrado9=Rect(420,340,100,100)\\r\\n Cuadrado10=Rect(520,340,100,100)\\r\\n Cuadrado11=Rect(620,340,100,100)\\r\\n Cuadrado12=Rect(720,340,100,100)\\r\\n Cuadrado13=Rect(420,440,100,100)\\r\\n Cuadrado14=Rect(520,440,100,100)\\r\\n Cuadrado15=Rect(620,440,100,100)\\r\\n Cuadrado16=Rect(720,440,100,100)\\r\\n\\r\\n Totalcuadrados=(Cuadrado1,Cuadrado2,Cuadrado3,Cuadrado4,Cuadrado5,Cuadrado6,Cuadrado7,Cuadrado8,Cuadrado9,Cuadrado10,Cuadrado11,Cuadrado12,Cuadrado13,Cuadrado14,Cuadrado15,Cuadrado16)\\r\\n listafiguras=[]\\r\\n def ventanaprincipal():\\r\\n \\\"\\\"\\\"\\\"\\r\\n Esta funcion, genera la ventana principal de nuestro juego de parejas. Contiene\\r\\n cada uno de los titulos e imagenes del juego.\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n titulo_principal=pygame.image.load(\\\"../recursor/Imagenes juegos/parejas_1.png\\\")\\r\\n ventana.blit(titulo_principal, (405,0))\\r\\n logo_plaython=pygame.image.load(\\\"../recursor/Imagenes juegos/plaython.png\\\")#Cargamos la imagen del logo\\r\\n imagen_decoracion=pygame.image.load(\\\"../recursor/Imagenes juegos/imagenpc.png\\\")\\r\\n imagen_decoracion = pygame.transform.scale(imagen_decoracion, (210, 210))\\r\\n ventana.blit(logo_plaython, (900, 180))\\r\\n ventana.blit(imagen_decoracion,(100,240))\\r\\n titulo_plaython = pygame.image.load(\\\"../recursor/Imagenes juegos/TITULOPLAYTHON.png\\\")\\r\\n titulo_plaython = pygame.transform.scale(titulo_plaython, (240, 150))\\r\\n ventana.blit(titulo_plaython, (505, 550))\\r\\n\\r\\n def dibujarcirculos(x,color):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, dibuja cada uno de las figuras de forma circular del juego en base a su generacion aleatoria.\\r\\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\\r\\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n if x==1:\\r\\n pygame.draw.circle(ventana,color,(470,190),30)\\r\\n elif x==2:\\r\\n pygame.draw.circle(ventana,color,(570,190),30)\\r\\n elif x==3:\\r\\n pygame.draw.circle(ventana,color,(670,190),30)\\r\\n elif x==4:\\r\\n pygame.draw.circle(ventana,color,(770,190),30)\\r\\n elif x==5:\\r\\n pygame.draw.circle(ventana,color,(470,290),30)\\r\\n elif x==6:\\r\\n pygame.draw.circle(ventana,color,(570,290),30)\\r\\n elif x==7:\\r\\n pygame.draw.circle(ventana,color,(670,290),30)\\r\\n elif x==8:\\r\\n pygame.draw.circle(ventana,color,(770,290),30)\\r\\n elif x==9:\\r\\n pygame.draw.circle(ventana,color,(470,390),30)\\r\\n elif x==10:\\r\\n pygame.draw.circle(ventana,color,(570,390),30)\\r\\n elif x==11:\\r\\n pygame.draw.circle(ventana,color,(670,390),30)\\r\\n elif x==12:\\r\\n pygame.draw.circle(ventana,color,(770,390),30)\\r\\n elif x==13:\\r\\n pygame.draw.circle(ventana,color,(470,490),30)\\r\\n elif x==14:\\r\\n pygame.draw.circle(ventana,color,(570,490),30)\\r\\n elif x==15:\\r\\n pygame.draw.circle(ventana,color,(670,490),30)\\r\\n elif x==16:\\r\\n pygame.draw.circle(ventana,color,(770,490),30)\\r\\n\\r\\n def dibujarcuadrados(x,color):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, dibuja cada uno de las figuras de forma cuadrada del juego en base a su generacion aleatoria.\\r\\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\\r\\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n if x==1:\\r\\n pygame.draw.rect(ventana,color,Rect(440,160,60,60))\\r\\n elif x==2:\\r\\n pygame.draw.rect(ventana,color,Rect(540,160,60,60))\\r\\n elif x==3:\\r\\n pygame.draw.rect(ventana,color,Rect(640,160,60,60))\\r\\n elif x==4:\\r\\n pygame.draw.rect(ventana,color,Rect(740,160,60,60))\\r\\n elif x==5:\\r\\n pygame.draw.rect(ventana,color,Rect(440,260,60,60))\\r\\n elif x==6:\\r\\n pygame.draw.rect(ventana,color,Rect(540,260,60,60))\\r\\n elif x==7:\\r\\n pygame.draw.rect(ventana,color,Rect(640,260,60,60))\\r\\n elif x==8:\\r\\n pygame.draw.rect(ventana,color,Rect(740,260,60,60))\\r\\n elif x==9:\\r\\n pygame.draw.rect(ventana,color,Rect(440,360,60,60))\\r\\n elif x==10:\\r\\n pygame.draw.rect(ventana,color,Rect(540,360,60,60))\\r\\n elif x==11:\\r\\n pygame.draw.rect(ventana,color,Rect(640,360,60,60))\\r\\n elif x==12:\\r\\n pygame.draw.rect(ventana,color,Rect(740,360,60,60))\\r\\n elif x==13:\\r\\n pygame.draw.rect(ventana,color,Rect(440,460,60,60))\\r\\n elif x==14:\\r\\n pygame.draw.rect(ventana,color,Rect(540,460,60,60))\\r\\n elif x==15:\\r\\n pygame.draw.rect(ventana,color,Rect(640,460,60,60))\\r\\n elif x==16:\\r\\n pygame.draw.rect(ventana,color,Rect(740,460,60,60))\\r\\n\\r\\n def dibujardiamantes(x,color):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, dibuja cada uno de las figuras de forma de diamante del juego en base a su generacion aleatoria.\\r\\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\\r\\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n if x==1:\\r\\n pygame.draw.polygon(ventana,color,( (430,190),(470,160),(510,190),(470,220)))\\r\\n elif x==2:\\r\\n pygame.draw.polygon(ventana,color,( (530,190),(570,160),(610,190),(570,220) ))\\r\\n elif x==3:\\r\\n pygame.draw.polygon(ventana,color,( (630,190),(670,160),(710,190),(670,220) ))\\r\\n elif x==4:\\r\\n pygame.draw.polygon(ventana,color,( (730,190),(770,160),(810,190),(770,220) ))\\r\\n elif x==5:\\r\\n pygame.draw.polygon(ventana,color,( (430,290),(470,260),(510,290),(470,320) ))\\r\\n elif x==6:\\r\\n pygame.draw.polygon(ventana,color,( (530,290),(570,260),(610,290),(570,320) ))\\r\\n elif x==7:\\r\\n pygame.draw.polygon(ventana,color,( (630,290),(670,260),(710,290),(670,320) ))\\r\\n elif x==8:\\r\\n pygame.draw.polygon(ventana,color,( (730,290),(770,260),(810,290),(770,320) ))\\r\\n elif x==9:\\r\\n pygame.draw.polygon(ventana,color,( (430,390),(470,360),(510,390),(470,420) ))\\r\\n elif x==10:\\r\\n pygame.draw.polygon(ventana,color,( (530,390),(570,360),(610,390),(570,420) ))\\r\\n elif x==11:\\r\\n pygame.draw.polygon(ventana,color,( (630,390),(670,360),(710,390),(670,420) ))\\r\\n elif x==12:\\r\\n pygame.draw.polygon(ventana,color,( (730,390),(770,360),(810,390),(770,420) ))\\r\\n elif x==13:\\r\\n pygame.draw.polygon(ventana,color,( (430,490),(470,460),(510,490),(470,520) ))\\r\\n elif x==14:\\r\\n pygame.draw.polygon(ventana,color,( (530,490),(570,460),(610,490),(570,520) ))\\r\\n elif x==15:\\r\\n pygame.draw.polygon(ventana,color,( (630,490),(670,460),(710,490),(670,520) ))\\r\\n elif x==16:\\r\\n pygame.draw.polygon(ventana,color,( (730,490),(770,460),(810,490),(770,520) ))\\r\\n def dibujartriangulos(x,color):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, dibuja cada uno de las figuras de forma triangular del juego en base a su generacion aleatoria.\\r\\n :param int x: Representa la casilla elegida, y en base a este valor, se dibuja un cuadrado en determinado lugar\\r\\n :param tuple color: Representa un color determinado, el cual se encuentra escrito en base a sus valores RGB\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n if x==1:\\r\\n pygame.draw.polygon(ventana,color,( (430,160),(510,160),(470,220) ))\\r\\n elif x==2:\\r\\n pygame.draw.polygon(ventana,color,( (530,160),(610,160),(570,220) ))\\r\\n elif x==3:\\r\\n pygame.draw.polygon(ventana,color,( (630,160),(710,160),(670,220) ))\\r\\n elif x==4:\\r\\n pygame.draw.polygon(ventana,color,( (730,160),(810,160),(770,220) ))\\r\\n elif x==5:\\r\\n pygame.draw.polygon(ventana,color,( (430,260),(510,260),(470,320)))\\r\\n elif x==6:\\r\\n pygame.draw.polygon(ventana,color,( (530,260),(610,260),(570,320) ))\\r\\n elif x==7:\\r\\n pygame.draw.polygon(ventana,color,( (630,260),(710,260),(670,320) ))\\r\\n elif x==8:\\r\\n pygame.draw.polygon(ventana,color,( (730,260),(810,260),(770,320) ))\\r\\n elif x==9:\\r\\n pygame.draw.polygon(ventana,color,( (430,360),(510,360),(470,420) ))\\r\\n elif x==10:\\r\\n pygame.draw.polygon(ventana,color,( (530,360),(610,360),(570,420) ))\\r\\n elif x==11:\\r\\n pygame.draw.polygon(ventana,color,( (630,360),(710,360),(670,420) ))\\r\\n elif x==12:\\r\\n pygame.draw.polygon(ventana,color,( (730,360),(810,360),(770,420) ))\\r\\n elif x==13:\\r\\n pygame.draw.polygon(ventana,color,( (430,460),(510,460),(470,520) ))\\r\\n elif x==14:\\r\\n pygame.draw.polygon(ventana,color,( (530,460),(610,460),(570,520) ))\\r\\n elif x==15:\\r\\n pygame.draw.polygon(ventana,color,( (630,460),(710,460),(670,520) ))\\r\\n elif x==16:\\r\\n pygame.draw.polygon(ventana,color,( (730,460),(810,460),(770,520) ))\\r\\n\\r\\n def iniciarjuego():\\r\\n \\\"\\\"\\\"\\\"\\r\\n Esta funcion, crea cuatro figuras de cada una de las posibles, dos de ellas con diferente color de las otras dos.\\r\\n \\\"\\\"\\\"\\r\\n for i in range(4):\\r\\n if i == 1 or i == 0:\\r\\n color = (250,208,120,98)\\r\\n else:\\r\\n color = (159, 250, 120,98)\\r\\n x = random.choice(cuadrados)\\r\\n listafiguras.append(x)\\r\\n dibujarcuadrados(x, color)\\r\\n cuadrados.remove(x)\\r\\n\\r\\n for i in range(4):\\r\\n if i == 0 or i == 1:\\r\\n color = (195, 139, 255,100)\\r\\n else:\\r\\n color = (250, 242, 120,98)\\r\\n x = random.choice(cuadrados)\\r\\n listafiguras.append(x)\\r\\n dibujarcirculos(x, color)\\r\\n cuadrados.remove(x)\\r\\n\\r\\n for i in range(4):\\r\\n if i == 0 or i == 1:\\r\\n color = (250, 145, 137,98)\\r\\n else:\\r\\n color = (126, 139, 250,98)\\r\\n x = random.choice(cuadrados)\\r\\n listafiguras.append(x)\\r\\n dibujartriangulos(x, color)\\r\\n cuadrados.remove(x)\\r\\n\\r\\n for i in range(4):\\r\\n if i == 0 or i == 1:\\r\\n color = (176, 255, 237,100)\\r\\n else:\\r\\n color = (255, 176, 228,100)\\r\\n x = random.choice(cuadrados)\\r\\n listafiguras.append(x)\\r\\n dibujardiamantes(x, color)\\r\\n cuadrados.remove(x)\\r\\n\\r\\n def mostrar(posicion_del_mouse):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion muestra segun la casilla que clickee el jugador.\\r\\n :param tuple posicion_del_mouse: Este parametro representa segun clickee el jugador (posicion en x y y).\\r\\n \\\"\\\"\\\"\\r\\n numerodecuadrado = numerocuadrado(posicion_del_mouse)\\r\\n ubicaciondelcuadrado=ubicacion_cuadrado(posicion_del_mouse)\\r\\n if ubicaciondelcuadrado==0 or ubicaciondelcuadrado==1:\\r\\n color = (250,208,120,98)\\r\\n dibujarcuadrados(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==2 or ubicaciondelcuadrado==3:\\r\\n color = (159, 250, 120,98)\\r\\n dibujarcuadrados(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==4 or ubicaciondelcuadrado==5:\\r\\n color = (195, 139, 255,100)\\r\\n dibujarcirculos(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==6 or ubicaciondelcuadrado==7:\\r\\n color = (250, 242, 120,98)\\r\\n dibujarcirculos(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==8 or ubicaciondelcuadrado==9:\\r\\n color = (250, 145, 137,98)\\r\\n dibujartriangulos(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==10 or ubicaciondelcuadrado==11:\\r\\n color = (126, 139, 250,98)\\r\\n dibujartriangulos(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==12 or ubicaciondelcuadrado==13:\\r\\n color = (176, 255, 237,100)\\r\\n dibujardiamantes(numerodecuadrado,color)\\r\\n elif ubicaciondelcuadrado==14 or ubicaciondelcuadrado==15:\\r\\n color = (255, 176, 228,100)\\r\\n dibujardiamantes(numerodecuadrado,color)\\r\\n\\r\\n def esconderfichas(posicion_del_mouse):\\r\\n \\\"\\\"\\\"\\\"\\r\\n Esta funcion, esconde las fichas, si la seleccion del usuario no es la correcta.\\r\\n :param tuple posicion_del_mouse: :param tuple primeraeleccion: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\\r\\n \\\"\\\"\\\"\\r\\n numerodecuadrado=numerocuadrado(posicion_del_mouse)\\r\\n for j in range(16):\\r\\n if numerodecuadrado==j+1:\\r\\n pygame.draw.rect(ventana,(135,206,250),Totalcuadrados[j].inflate(-10,-10))\\r\\n\\r\\n def encontrarparejas(primeraeleccion,segundaeleccion):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion determina si se encontro una pareja.\\r\\n :param tuple primeraeleccion: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\\r\\n :param tuple segundaeleccion: Representa la segunda posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\\r\\n Retorna un booleano\\r\\n \\\"\\\"\\\"\\r\\n x=ubicacion_cuadrado(primeraeleccion)\\r\\n y=ubicacion_cuadrado(segundaeleccion)\\r\\n if (x==0 and y==1 or x==1 and y==0)\\\\\\r\\n or (x == 2 and y == 3 or x == 3 and y == 2) \\\\\\r\\n or (x == 4 and y == 5 or x == 5 and y == 4)\\\\\\r\\n or (x == 6 and y == 7 or x == 7 and y == 6)\\\\\\r\\n or (x == 8 and y == 9 or x == 9 and y == 8) \\\\\\r\\n or (x==10 and y==11 or x==11 and y==10)\\\\\\r\\n or (x==12 and y==13 or x==13 and y==12)\\\\\\r\\n or (x==14 and y==15 or x==15 and y==14):\\r\\n return True\\r\\n\\r\\n def ubicacion_cuadrado(posicion_del_mouse):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, retorna la figura que se encuentra en determinado indice segun se clickee.\\r\\n :param tuple posicion_del_mouse: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\\r\\n Retorna la figura de determinado indice\\r\\n \\\"\\\"\\\"\\r\\n for j in range(16):\\r\\n if Totalcuadrados[j].collidepoint(posicion_del_mouse):\\r\\n return listafiguras.index(j+1)\\r\\n\\r\\n def dibujartablero():\\r\\n \\\"\\\"\\\"\\\"\\r\\n Esta funcion, dibuja los cuadrados que hacen nuestro tablero.\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n ventana.fill((135,206,250)) #colocamos el color de fondo de nuestra pantalla\\r\\n for j in range(16): #iteramos entre los cuadrados ya diseñados, eligiendo parametros como el color y el grueso de sus lineas.\\r\\n pygame.draw.rect(ventana,(255,255,255),Totalcuadrados[j],10)\\r\\n\\r\\n def numerocuadrado(posicion_del_mouse):\\r\\n \\\"\\\"\\\"\\r\\n Esta funcion, retorna el indice de determinado cuadrado segun se clickee.\\r\\n :param tuple posicion_del_mouse: Representa la posicion de donde clickeo el jugador (tanto en el ejex como en el eje y).\\r\\n Retorna el indice de terminada posicion\\r\\n \\\"\\\"\\\"\\r\\n\\r\\n for j in range(16):\\r\\n if Totalcuadrados[j].collidepoint(posicion_del_mouse):\\r\\n return j+1\\r\\n\\r\\n def main():\\r\\n \\\"\\\"\\\"\\\"\\r\\n Funcion proncipal del juego.\\r\\n :return None\\r\\n \\\"\\\"\\\"\\r\\n pygame.init()\\r\\n global ventana\\r\\n ventana= pygame.display.set_mode((1280,700))\\r\\n ventana.fill((135,206,250))\\r\\n pygame.display.set_caption('Encuentra las parejas')\\r\\n logo = pygame.image.load(\\\"../recursor/icono.ico\\\")\\r\\n pygame.display.set_icon(logo)\\r\\n pygame.display.update()\\r\\n dibujartablero()\\r\\n iniciarjuego()\\r\\n titulo_principal=pygame.image.load(\\\"../recursor/Imagenes juegos/parejas_2.png\\\")\\r\\n ventana.blit(titulo_principal, (405,0))\\r\\n pygame.display.update()\\r\\n pygame.time.wait(3000)\\r\\n dibujartablero()\\r\\n ventanaprincipal()\\r\\n pygame.display.update()\\r\\n prueba=0\\r\\n eleccioncorrecta=[]\\r\\n while True:\\r\\n for event in pygame.event.get():\\r\\n if event.type==QUIT:\\r\\n pygame.quit()\\r\\n sys.exit()\\r\\n elif event.type==pygame.MOUSEBUTTONUP:\\r\\n posicion_del_mouse=pygame.mouse.get_pos()\\r\\n mostrar(posicion_del_mouse)\\r\\n pygame.display.update()\\r\\n if prueba==0:\\r\\n primeraeleccion=posicion_del_mouse\\r\\n if numerocuadrado(primeraeleccion) in eleccioncorrecta:\\r\\n prueba=0\\r\\n else:\\r\\n prueba=1\\r\\n else:\\r\\n segundaeleccion=posicion_del_mouse\\r\\n if numerocuadrado(segundaeleccion) in eleccioncorrecta:\\r\\n prueba=1\\r\\n else:\\r\\n prueba=0\\r\\n if not (numerocuadrado(primeraeleccion) in eleccioncorrecta) and not numerocuadrado(segundaeleccion) in eleccioncorrecta:\\r\\n if encontrarparejas(primeraeleccion,segundaeleccion):\\r\\n eleccioncorrecta.append(numerocuadrado(primeraeleccion))\\r\\n eleccioncorrecta.append(numerocuadrado(segundaeleccion))\\r\\n else:\\r\\n pygame.time.wait(1000)\\r\\n esconderfichas(primeraeleccion)\\r\\n esconderfichas(segundaeleccion)\\r\\n pygame.display.update()\\r\\n\\r\\n if len(eleccioncorrecta)==16:\\r\\n ganador=pygame.image.load('../recursor/Imagenes juegos/Ganadorgg0000.png')\\r\\n ventana.blit(ganador,(420, 140))\\r\\n pygame.display.update()\\r\\n time.sleep(4)\\r\\n pygame.quit()\\r\\n break\\r\\n\\r\\n main()\",\n \"def draw(self):\\n self.screen.fill(BACKGROUND_COLOR)\\n self.cannon.draw(self.screen)\\n self.objects.draw(self.screen)\",\n \"def draw():\\n screen.fill((0, 0, 0))\\n alien.draw()\",\n \"def save_file(camera, frame):\\n save = input(\\\"Would you like to save your drawing? Enter yes or no \\\")\\n if save == \\\"yes\\\" or save == \\\"y\\\" or save == \\\"ye\\\" or save == \\\"yes \\\": # accounting for typos\\n name = input(\\\"What would you like to name your masterpiece? \\\")\\n filename = 'images/' + name + '.png'\\n cv2.imwrite(filename, cv2.flip(frame,1)) # saves the image as the last frame\\n camera.release()\\n pygame.quit()\\n\\n # reopen saved picture to display for user\\n img = cv2.imread(filename, 1)\\n b,g,r = cv2.split(img) # get b,g,r\\n rgb_img = cv2.merge([r,g,b]) # convert from bgr colorspace to rgb\\n crop_img = rgb_img[36:450, 0:600] # crop out the colorbar\\n cv2.imshow(filename, crop_img)\\n cv2.imwrite(filename, crop_img)\\n cv2.waitKey(10000)\\n cv2.destroyAllWindows()\\n camera.release()\\n pygame.quit() # cleanup the camera and close any open windows\\n else:\\n print(\\\"Thank you for trying CVPaint!\\\")\\n pygame.quit()\\n camera.release()\\n cv2.destroyAllWindows()\",\n \"def update(self):\\n\\n surface = pygame.Surface(CARD_SIZE, pygame.SRCALPHA)\\n card_filename = f\\\"assets/sprites/cardBack.png\\\"\\n card_image = pygame.image.load(card_filename).convert_alpha()\\n surface.blit(card_image, (0, 0))\\n self.image = surface\\n self.rect = self.image.get_rect()\",\n \"def draw(self):\\n self.bufferX = (self.appWidth/2) - self.viewX\\n self.bufferY = (self.appHeight/2) - self.viewY\\n anwp.sl.engine.clear()\\n anwp.sl.engine.drawImage(0, 0, self.appWidth, self.appHeight, self.backgroundImage)\\n self.drawWarpLines()\\n \\n # render engine\\n anwp.sl.engine.render()\\n self.drawSystemInfo()\\n self.drawWarpGateInfo()\\n self.drawWarpTradeInfo()\",\n \"def setup_draw(self):\\n pass\",\n \"def redraw(self):\\n self.vispy_viewer.canvas.update()\",\n \"def __display(self):\\n self.__rotate_model()\\n self.__generate_shadows()\\n self.__generate_model()\\n\\n glutSwapBuffers()\\n if self.__callback is not None:\\n self.__callback()\",\n \"def _blit_images(self):\\n self.screen.blit(self.dial, (self.dialPos))\\n self.screen.blit(self.rotatedImage, self.rotatedImageRectangle)\",\n \"def new_canvas(self):\\n libtcod.console_clear(self.console)\",\n \"def draw_card(dealer,player):\\n # hidden_img = Image(img_path+\\\"back.png\\\")\\n depth = 100\\n x0,y0 = 100,100\\n x1,y1 = 100,300\\n ix = 30\\n\\n bj_board.clear()\\n for card in dealer:\\n if card.state:\\n card.image.moveTo(x0, y0)\\n card.image.setDepth(depth)\\n bj_board.add(card.image)\\n else:\\n img = Image(img_path+\\\"Back.png\\\")\\n img.moveTo(x0, y0)\\n img.setDepth(depth)\\n bj_board.add(img)\\n x0 += ix\\n \\n for card in player:\\n if card.state:\\n card.image.moveTo(x1, y1)\\n card.image.setDepth(depth)\\n bj_board.add(card.image)\\n else:\\n img = Image(img_path+\\\"back.png\\\")\\n img.moveTo(x1, y1)\\n img.setDepth(depth)\\n bj_board.add(img)\\n x1 += ix\",\n \"def on_show_view(self):\\n self.setup()\\n arcade.set_background_color(arcade.color.BLACK)\\n arcade.set_viewport(0, constants.SCREEN_WIDTH - 1, 0, constants.SCREEN_HEIGHT - 1)\",\n \"def draw_how_to(self):\\n howto = pygame.image.load(res.IMG_HOW_TO)\\n self.screen.blit(howto, (0, 0))\",\n \"def update_frame(self):\\n if self.should_reset_camera:\\n self.ren.ResetCamera()\\n self.should_reset_camera = False\\n self.interactor.Render()\\n app.processEvents()\",\n \"def update_frame(self):\\n if self.should_reset_camera:\\n self.ren.ResetCamera()\\n self.should_reset_camera = False\\n self.interactor.Render()\\n app.processEvents()\",\n \"def update_display(self):\\n self.lick_plot_0.setData(self.k+self.T,self.buffer[:,1]) \\n self.lick_plot_1.setData(self.k+self.T,self.buffer[:,2]) \\n self.breathing_plot.setData(self.k+self.T,self.buffer[:,0]) \\n \\n if self.settings.movie_on.value():\\n self.camera_image.setImage(self.camera.read())\\n if self.settings.save_movie.value():\\n self.camera.write()\\n \\n #print(self.buffer_h5.size)\",\n \"def draw(self, surface):\\n\\n\\t\\tsurface.blit(self.image, self.rect.topleft)\",\n \"def redraw(self):\\n x2, y2 = [[] for i in range(len(self.x))], \\\\\\n [[] for i in range(len(self.x))]\\n game_point = [random.randint(1, 100),\\n random.randint(1, 100)]\\n for i in range(self.generations):\\n x2, y2, game_point = self.move(x2, y2, game_point)\\n for i in range(10): # Czyszczenie starych wykresow\\n self.plots[i].set_xdata([])\\n self.plots[i].set_ydata([])\\n self.plots2[i].set_xdata([])\\n self.plots2[i].set_ydata([])\\n for i in range(len(self.x)): # Nowe dane wykresow\\n self.plots[i].set_xdata(self.x[i])\\n self.plots[i].set_ydata(self.y[i])\\n self.plots2[i].set_xdata(x2[i])\\n self.plots2[i].set_ydata(y2[i])\\n self.fig.canvas.draw_idle()\",\n \"def draw(self):\\n\\t\\tpass\",\n \"def move(self):\\n \\n self.rect.move_ip(0,self.speed) # Funcion para mover el enemigo especificando la velocidad xy\\n \\n if (self.rect.top > SCREEN_HEIGHT): # Condicion cuando llega a la parte inferior y no colisiono con el jugador\\n del self.surf #Libera memoria\\n del self.rect\\n self.randomNumber = random.choice([70,64,32]) # Su tamaño se asigna nuevamente\\n self.size = (self.randomNumber,self.randomNumber) #Se genera su tamaño como un cuadrado de lado aleatorio\\n self.surf = pygame.Surface(self.size) #Se genera la superficie que aparecera la pantalla\\n self.surf.fill(RED)\\n self.rect = self.surf.get_rect(center = (random.randint(40,SCREEN_WIDTH-40),0))# me da info de las coordenadas de surf\\n if(self.randomNumber == 32):\\n self.surf = self.imagen\\n elif(self.randomNumber ==64):\\n self.surf = self.imagen2\\n elif self.randomNumber ==70 :\\n self.surf = self.imagen3\",\n \"def update_drawer_img(self):\\n self.drawer = aggdraw.Draw(self.img)\\n self.drawer.settransform(self.coordspace_transform)\",\n \"def draw(self):\\n pass\",\n \"def draw(self):\\n pass\",\n \"def draw(self):\\n pass\",\n \"def draw(self):\\n pass\",\n \"def updateScreen(self) -> None:\\n\\n # fill game display black\\n self.surface.fill(Colors.Black)\\n\\n # draw players and ball\\n self.drawImageOnSurface(self.player_one)\\n self.drawImageOnSurface(self.player_two)\\n self.drawImageOnSurface(self.ball)\\n\\n # draw all the spacer images\\n for image in self.spacers:\\n self.drawImageOnSurface(image)\\n\\n # draw scores and format the scores in byte representation\\n self.drawTextOnSurface(format(self._score[0], \\\"04b\\\"),\\n (Configuration.windowWidth / 4, Configuration.windowHeight / 2), Colors.ByteGreen,\\n font=self.font)\\n self.drawTextOnSurface(format(self._score[1], \\\"04b\\\"),\\n (3 * Configuration.windowWidth / 4, Configuration.windowHeight / 2), Colors.ByteGreen,\\n font=self.font)\\n\\n super().updateScreen() # call the parent method to update the screen\",\n \"def update_deck_display(self):\\n self.deck_surface.fill(CLEARCOLOUR)\\n self.deck_surface.blit(self.background, (0, 0))\\n if not self.is_empty():\\n cards_to_draw = self.cards\\n if self.draw_from_last:\\n cards_to_draw = reversed(cards_to_draw)\\n\\n for i, card in enumerate(cards_to_draw):\\n selected = (i == self.selected_card)\\n image_to_draw = card.image\\n\\n if self.deck_reveal == DeckReveal.HIDE_ALL:\\n image_to_draw = card.backimage\\n\\n if self.flip:\\n image_to_draw = pygame.transform.flip(image_to_draw, self.vert_orientation,\\n not self.vert_orientation)\\n\\n self.deck_surface.blit(image_to_draw, (card.x - selected * card.x * 0.5 *\\n (-1)**self.flip * self.vert_orientation,\\n card.y - selected * card.y * 0.5 *\\n (-1)**self.flip * (not self.vert_orientation)))\",\n \"def create_canvas(self):\\n self.canvas = tk.Canvas(\\n self,\\n bd=-2,\\n height=self.controller.GAME_HEIGHT,\\n width=self.controller.GAME_WIDTH)\\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)\",\n \"def create_canvas(self):\\n self.canvas = tk.Canvas(\\n self,\\n bd=-2,\\n height=self.controller.GAME_HEIGHT,\\n width=self.controller.GAME_WIDTH)\\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)\",\n \"def create_canvas(self):\\n self.canvas = tk.Canvas(\\n self,\\n bd=-2,\\n height=self.controller.GAME_HEIGHT,\\n width=self.controller.GAME_WIDTH)\\n self.canvas.pack(expand=tk.YES, fill=tk.BOTH)\",\n \"def update_current_image(self):\\n\\n rect = (0, 0, self.variables.canvas_width, self.variables.canvas_height)\\n if self.variables.canvas_image_object is not None:\\n self.variables.canvas_image_object.update_canvas_display_image_from_canvas_rect(rect)\\n self.set_image_from_numpy_array(self.variables.canvas_image_object.display_image)\\n self.update()\",\n \"def draw(self, surface):\\r\\n if self.visible:\\r\\n surface.blit(self.image, (self.x, self.y))\",\n \"def _drawFrame(self):\\n\\n self._clearScreen()\\n \\n for object in Object.Objects:\\n self._drawObject(object)\\n\\n for entity in Entity.Entities:\\n self._drawObject(entity)\\n\\n self._drawObject(Game.Player)\",\n \"def flip(self):\",\n \"def main():\\r\\n pygame.init()\\r\\n global ventana\\r\\n ventana= pygame.display.set_mode((1280,700))\\r\\n ventana.fill((135,206,250))\\r\\n pygame.display.set_caption('Encuentra las parejas')\\r\\n logo = pygame.image.load(\\\"../recursor/icono.ico\\\")\\r\\n pygame.display.set_icon(logo)\\r\\n pygame.display.update()\\r\\n dibujartablero()\\r\\n iniciarjuego()\\r\\n titulo_principal=pygame.image.load(\\\"../recursor/Imagenes juegos/parejas_2.png\\\")\\r\\n ventana.blit(titulo_principal, (405,0))\\r\\n pygame.display.update()\\r\\n pygame.time.wait(3000)\\r\\n dibujartablero()\\r\\n ventanaprincipal()\\r\\n pygame.display.update()\\r\\n prueba=0\\r\\n eleccioncorrecta=[]\\r\\n while True:\\r\\n for event in pygame.event.get():\\r\\n if event.type==QUIT:\\r\\n pygame.quit()\\r\\n sys.exit()\\r\\n elif event.type==pygame.MOUSEBUTTONUP:\\r\\n posicion_del_mouse=pygame.mouse.get_pos()\\r\\n mostrar(posicion_del_mouse)\\r\\n pygame.display.update()\\r\\n if prueba==0:\\r\\n primeraeleccion=posicion_del_mouse\\r\\n if numerocuadrado(primeraeleccion) in eleccioncorrecta:\\r\\n prueba=0\\r\\n else:\\r\\n prueba=1\\r\\n else:\\r\\n segundaeleccion=posicion_del_mouse\\r\\n if numerocuadrado(segundaeleccion) in eleccioncorrecta:\\r\\n prueba=1\\r\\n else:\\r\\n prueba=0\\r\\n if not (numerocuadrado(primeraeleccion) in eleccioncorrecta) and not numerocuadrado(segundaeleccion) in eleccioncorrecta:\\r\\n if encontrarparejas(primeraeleccion,segundaeleccion):\\r\\n eleccioncorrecta.append(numerocuadrado(primeraeleccion))\\r\\n eleccioncorrecta.append(numerocuadrado(segundaeleccion))\\r\\n else:\\r\\n pygame.time.wait(1000)\\r\\n esconderfichas(primeraeleccion)\\r\\n esconderfichas(segundaeleccion)\\r\\n pygame.display.update()\\r\\n\\r\\n if len(eleccioncorrecta)==16:\\r\\n ganador=pygame.image.load('../recursor/Imagenes juegos/Ganadorgg0000.png')\\r\\n ventana.blit(ganador,(420, 140))\\r\\n pygame.display.update()\\r\\n time.sleep(4)\\r\\n pygame.quit()\\r\\n break\",\n \"def draw_pavement():\\n\\n roberto.penup()\\n roberto.goto(-345, -100)\\n roberto.pendown()\\n roberto.begin_fill()\\n for i in range(4): # this loop draws a big black rectangle that is positioned at the bottom part of the screen\\n roberto.forward(684)\\n roberto.right(90)\\n roberto.end_fill()\",\n \"def punched(self):\\n if not self.dizzy:\\n self.dizzy= 1\\n self.original= self.image\",\n \"def viewUpdate(self):\\n # Update Capture\\n imgtk = self.model.capture\\n self.updateImage(self.view.lmain, imgtk)\\n # Update Stitch \\n imgtk = self.model.stitch\\n self.updateImage(self.view.rmain, imgtk)\\n self.view.dist.set(self.model.dist)\",\n \"def set_mode(self, size, buffered=True, *args, **kwargs):\\n self.canvas = Canvas(size, buffered)\\n env.set_env('canvas', self.canvas)\\n self.frame = Window.getDocumentRoot()\\n env.set_env('frame', self.frame)\\n panel = SimplePanel(Widget=self.canvas)\\n RootPanel().add(panel)\\n self.panel = panel\\n self.vpanel = None\\n self.textbox = None\\n self.textarea = None\\n self.Textbox = Textbox\\n self.Textarea = Textarea\\n self.surface = self.canvas.surface\\n self.surface._display = self\\n self._surface_rect = self.surface.get_rect()\\n if not self.canvas._bufferedimage:\\n self.flip = lambda: None\\n self.update = lambda *arg: None\\n return self.surface\",\n \"def setBlackFrame(self):\\r\\n frame = ImageTk.PhotoImage(Image.fromarray(np.array([[0]*self.w]*self.h)))\\r\\n self.player.config(image=frame)\\r\\n self.player.image = frame\",\n \"def draw(self, win, player, displayList, enemyHitboxList, mapWidth, mapHeight):\\n cameraX = player.rect.left + (player.rect.width // 2) - (SCREEN_WIDTH // 2)\\n cameraY = player.rect.top + (player.rect.height // 2) - (SCREEN_HEIGHT // 2)\\n\\n # On centre la camera tant que le joueurs n'atteind pas les bords\\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\\n self.x = cameraX\\n\\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\\n self.y = cameraY\\n\\n # Calcul de l'X du joueur en fonction s'il est en haut, bas ou entre les 2\\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\\n playerX = (SCREEN_WIDTH // 2) - (player.rect.width // 2)\\n else:\\n # Si le joueur est a droite\\\"\\\"\\\"\\n if cameraX >= mapWidth - SCREEN_WIDTH:\\n self.x = mapWidth - SCREEN_WIDTH\\n playerX = player.rect.left - mapWidth + SCREEN_WIDTH\\n # Si le joueur est a gauche\\\"\\\"\\\"\\n else:\\n self.x = 0\\n playerX = player.rect.left\\n\\n\\n # Calcul de l'Y du joueur en fonction s'il est a gauche, droite ou entre les 2\\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\\n playerY = (SCREEN_HEIGHT // 2) - (player.rect.height // 2)\\n else:\\n # Si le joueur est en dessous\\n if cameraY >= mapHeight - SCREEN_HEIGHT:\\n self.y = mapHeight - SCREEN_HEIGHT\\n playerY = player.rect.top - mapHeight + SCREEN_HEIGHT\\n # Si le joueur est au dessus \\n else:\\n self.y = 0\\n playerY = player.rect.top\\n\\n for element in displayList:\\n element.draw(win,element.rect.left - self.x,element.rect.top - self.y)\\n #for elem in enemyHitboxList:\\n #pg.draw.rect(win, (200, 200, 200), pg.Rect(elem.left - self.x,elem.top - self.y, elem.width, elem.height))\\n player.draw(win, playerX, playerY)\",\n \"def __init__(self, screen_width:int, screen_height:int, screen, sensitivity:int, max_fps:int, debug:bool):\\n\\n #Call the superclass init method\\n super().__init__(screen_width, screen_height, screen, State(102), sensitivity, max_fps, 0.1, debug)\\n\\n #Commander brief image\\n self.bg = ImageObject(300, 285, 600, 570, StoryTemplate.sprites['commander_brief'], debug)\\n\\n #Image of figure head (To be replaced with the actual image)\\n self.marco = ImageObject(300, 215, 217, 217, StoryTemplate.sprites['yuckerberg'], debug)\\n self.marco.scale(217,217)\\n\\n #Image of the commander\\n self.commander = ImageObject(300, 210, 217, 217, StoryTemplate.sprites['silloette_commander'], debug)\\n self.commander.scale(217,217)\\n\\n #Textbox\\n self.tb = ImageObject(300, 685, 600, 230, StoryTemplate.sprites['textbox'], debug)\",\n \"def _update_screen(self):\\n self.screen.fill(self.settings.bg_color)\\n self.sideways_ship.blitme()\\n for bullet in self.bullets.sprites():\\n bullet.draw_bullet()\\n self.aliens.draw(self.screen)\\n pygame.display.flip()\",\n \"def main(winstyle = 0):\\n pygame.init()\\n # Try to init the sound\\n if pygame.mixer and not pygame.mixer.get_init():\\n print ('Error, no hay sonido')\\n pygame.mixer = None\\n \\n # Set the screen mode\\n winstyle = RESIZABLE # FULLSCREEN for fullscreen\\n bestColorDepth = pygame.display.mode_ok(SCREENRECT.size, winstyle, 32)\\n screen = pygame.display.set_mode(SCREENRECT.size, winstyle, bestColorDepth)\\n \\n # Load the images of the Sprite classes\\n Player.images = assembleSprite('rubia.gif', (42,60), (4,2))\\n Fairy.images = assembleSprites((40,40), (3,1), 'hadaDO.gif', 'hadaRE.gif', 'hadaMI.gif', 'hadaFA.gif', 'hadaSOL.gif', 'hadaLA.gif', 'hadaSI.gif')\\n Step.images = load_images('pent_flores.gif', 'pent1.gif', 'pent2.gif', 'pent3.gif', 'pent4.gif', 'pent5.gif', 'pent6.gif')\\n StepMove.images = [load_image('pent1_mover.gif')]\\n Block.images = load_images('bloque_pent1.gif', 'bloque_pent2.gif', 'bloque_pent3.gif', 'bloque_pent4.gif', 'bloque_pent5.gif')\\n Note.images = load_images('do.gif', 're.gif', 'mi.gif', 'fa.gif', 'sol.gif', 'la.gif', 'si.gif')\\n Score.notesImages = load_images('do2.gif', 're2.gif', 'mi2.gif', 'fa2.gif', 'sol2.gif', 'la2.gif', 'si2.gif', 'borde.gif')\\n Shot.images = load_images('do2.gif', 're2.gif', 'mi2.gif', 'fa2.gif', 'sol2.gif', 'la2.gif', 'si2.gif', 'ruido.gif')\\n \\n \\n # Create the visualization window\\n pygame.display.set_icon(load_image('icon.gif'))\\n pygame.display.set_caption('Lost Sound')\\n \\n # Greate the background\\n bgdImage = load_image('background.bmp')\\n background = pygame.Surface(screen.get_size())\\n background = background.convert()\\n background.blit(bgdImage, (0, 0))\\n\\n screen.blit(background, (0,0))\\n pygame.display.flip()\\n \\n # Load the sound\\n if pygame.mixer:\\n sounds = load_sounds('do.wav', 're.wav', 'mi.wav', 'fa.wav', 'sol.wav', 'la.wav', 'si.wav', 'ruido.wav')\\n dead_sound = load_sound('morir.wav')\\n dead_sound.set_volume(0.5)\\n for s in sounds:\\n s.set_volume(0.8)\\n sounds[7].set_volume(0.2)\\n\\n # Load the music \\n if pygame.mixer:\\n file = os.path.join(main_dir, 'data', 'I_Talk_to_the_Rain.mp3')\\n pygame.mixer.music.load(file)\\n pygame.mixer.music.set_volume(0.8)\\n pygame.mixer.music.play(-1) # Makes the music sound a number of times. -1 infinite\\n \\n # Init the sprites Groups\\n fairies = pygame.sprite.Group()\\n steps = pygame.sprite.Group()\\n stepsM = pygame.sprite.Group()\\n blocks = pygame.sprite.Group()\\n notes = pygame.sprite.Group()\\n shots = pygame.sprite.Group()\\n all = pygame.sprite.Group()\\n \\n # Assign Sprites to the Groups\\n Player.containers = all\\n Fairy.containers = fairies, all\\n Step.containers = steps, all\\n StepMove.containers = stepsM, all\\n Block.containers = blocks, all\\n Note.containers = notes, all\\n Shot.containers = shots, all\\n Score.containers = all\\n ScoreF.containers = all\\n Help.containers = all\\n \\n # Variables needed\\n clock = pygame.time.Clock()\\n SELECTED_NOTE = -1\\n SCORE = 0\\n\\n # Init the Sprites\\n player = Player(PLAYER_SPEEDX,FLOORRECT)\\n PLAYER_POS = player.rect.left\\n\\n Note(0,(500, 100),PLAYER_POS,SCREEN_SPEED)\\n Note(1,(2350, 150),PLAYER_POS,SCREEN_SPEED)\\n Note(2,(4000, 10),PLAYER_POS,SCREEN_SPEED)\\n Note(3,(6450, 120),PLAYER_POS,SCREEN_SPEED)\\n Note(4,(7250, 20),PLAYER_POS,SCREEN_SPEED)\\n Note(5,(8700, 30),PLAYER_POS,SCREEN_SPEED)\\n Note(6,(10150, 200),PLAYER_POS,SCREEN_SPEED)\\n \\n Step(0,(400,350),PLAYER_POS,SCREEN_SPEED)\\n Step(3,(2400,350),PLAYER_POS,SCREEN_SPEED)\\n Step(2,(3500,350),PLAYER_POS,SCREEN_SPEED)\\n Step(4,(4250,250),PLAYER_POS,SCREEN_SPEED)\\n Step(1,(4850,200),PLAYER_POS,SCREEN_SPEED)\\n Step(5,(5670,350),PLAYER_POS,SCREEN_SPEED)\\n Step(6,(6450,200),PLAYER_POS,SCREEN_SPEED)\\n Step(3,(6950,200),PLAYER_POS,SCREEN_SPEED)\\n Step(2,(7550,300),PLAYER_POS,SCREEN_SPEED)\\n Step(1,(9150,200),PLAYER_POS,SCREEN_SPEED)\\n Step(2,(10500,200),PLAYER_POS,SCREEN_SPEED)\\n Step(3,(11200,350),PLAYER_POS,SCREEN_SPEED)\\n\\n StepMove(0,(8600,400),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\\n \\n Block(0,(2200, 50),PLAYER_POS,SCREEN_SPEED)\\n Block(2,(6350, 0),PLAYER_POS,SCREEN_SPEED)\\n\\n Fairy(0,(1100, 200),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\\n for j in range(1200,10300,150):\\n i = random.randrange(0,7)\\n k = random.randrange(j,j+150)\\n l = random.randrange(200,450)\\n appear = random.choice((0,1))\\n if appear:\\n Fairy(i,(k, l),PLAYER_POS,SCREENRECT,SCREEN_SPEED)\\n \\n score = Score((20,50),SCREEN_SPEED)\\n scoreF = ScoreF()\\n if pygame.font:\\n all.add(scoreF)\\n \\n help = Help(PLAYER_POS,SCREEN_SPEED)\\n \\n while player.alive():\\n # Set the fps\\n timePassed = clock.tick(50)\\n\\n # Check if the player wants to quit and get the key pressed\\n for event in pygame.event.get():\\n if event.type == QUIT or \\\\\\n (event.type == KEYDOWN and event.key == K_ESCAPE):\\n return\\n keystate = pygame.key.get_pressed()\\n \\n # Clear the Sprites from the screen\\n all.clear(screen, background)\\n SELECTED_NOTE = player.selectedNote\\n\\n # updated all the Sprites status\\n all.update()\\n \\n # Read the inputs and update the status variables\\n directionX = keystate[K_RIGHT] - keystate[K_LEFT]\\n jumpState = keystate[K_UP]\\n firing = keystate[K_SPACE]\\n noteUP = keystate[K_d]\\n noteDOWN = keystate[K_s]\\n\\n if (noteUP or noteDOWN) and not player.changing:\\n player.changing = 1\\n player.selectNote(noteUP,noteDOWN)\\n elif (not noteUP and not noteDOWN) and player.changing:\\n player.changing = 0\\n \\n if not player.reloading and firing and len(shots) < MAX_SHOTS:\\n Shot(player.gunPos(), player.facingX, player.selectedNote, SCREENRECT)\\n sounds[player.selectedNote].play()\\n player.reloading = firing \\n\\n # Create the effect of the player jump\\n if not player.jumping and jumpState:\\n player.setJumpBase(player.rect.bottom)\\n player.jumping = 1\\n player.setSpeed(player.speedX,player.jumpSpeed)\\n else:\\n if player.jumping and (player.jumpBase <= player.rect.bottom):\\n player.jumping = 0\\n elif player.jumping and player.climbed:\\n player.setJumpBase(player.rect.bottom)\\n player.jumping = 0\\n elif player.jumping and player.climbedB:\\n player.setJumpBase(player.rect.bottom)\\n player.jumping = 0\\n\\n # Update the player and move it\\n player.setSpeed(PLAYER_SPEEDX,player.speedY)\\n player.gravity(0,0.05)\\n player.move(directionX,timePassed)\\n\\n # Create the effect of movement in the screen\\n directionX = -directionX\\n # If the player has reached the end and has all the notes, the screen freezes\\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20):\\n pass\\n elif (player.rect.left == FLOORRECT.left or player.rect.right == FLOORRECT.right) and PLAYER_POS >= END_LVL:\\n if PLAYER_POS <= BEGIN_LVL:\\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\\n elif PLAYER_POS >= BEGIN_LVL and directionX == -1:\\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\\n elif PLAYER_POS <= END_LVL and directionX == 1:\\n PLAYER_POS = PLAYER_POS+SCREEN_SPEED*directionX\\n\\n # Update the player position for the other Sprites\\n for note in notes:\\n note.updatePlayerPos(PLAYER_POS)\\n for fairy in fairies:\\n fairy.updatePlayerPos(PLAYER_POS)\\n for step in steps:\\n step.updatePlayerPos(PLAYER_POS)\\n for step in stepsM:\\n step.updatePlayerPos(PLAYER_POS)\\n for block in blocks:\\n block.updatePlayerPos(PLAYER_POS)\\n help.updatePlayerPos(PLAYER_POS)\\n\\n # Check collisions between the obstacles and the player\\n player.climbed = 0 \\n for step in pygame.sprite.spritecollide(player, steps, 0):\\n if step.rect.top <= player.rect.bottom and step.rect.bottom <> player.rect.bottom and step.rect.centery > player.rect.bottom:\\n player.setSpeed(player.speedX,0)\\n player.position((0,-1))\\n player.climbed = 1\\n\\n player.climbedB = 0 \\n for step in pygame.sprite.spritecollide(player, stepsM, 0):\\n if step.rect.top <= player.rect.bottom and step.rect.bottom <> player.rect.bottom and step.rect.centery > player.rect.bottom:\\n player.setSpeed(player.speedX,0)\\n player.position((0,5*step.facingY))\\n player.climbedB = 1\\n \\n for block in pygame.sprite.spritecollide(player, blocks, 0):\\n if block.rect.left <= player.rect.right:\\n player.setSpeed(0,player.speedY)\\n player.position((-11,0))\\n\\n # Check collisions with the notes\\n for note in pygame.sprite.spritecollide(player, notes, 0):\\n # Hacer un sonido\\n id = note.kill()\\n player.insertNote(id)\\n score.addNote(id)\\n scoreF.addPoints(100)\\n\\n # Check collisions between the blocks and the shots\\n for shot, block in pygame.sprite.groupcollide(shots, blocks, 1, 0).items():\\n if block[0].id == shot.id:\\n block[0].kill()\\n\\n for shot, step in pygame.sprite.groupcollide(shots, stepsM, 1, 0).items():\\n if step[0].id == shot.id:\\n step[0].activate()\\n \\n # Check collisions with the fairies\\n for fairy in pygame.sprite.spritecollide(player, fairies, 1):\\n dead_sound.play()\\n player.kill()\\n\\n # Check collisions between the fairies and the shots\\n for shot, fairy in pygame.sprite.groupcollide(shots, fairies, 1, 0).items():\\n if fairy[0].id == shot.id:\\n fairy[0].kill()\\n dead_sound.play()\\n scoreF.addPoints(10)\\n else:\\n fairy[0].lives = fairy[0].lives-1\\n if fairy[0].lives == 0:\\n dead_sound.play()\\n scoreF.addPoints(1)\\n \\n background.blit(bgdImage, (PLAYER_POS,0))\\n screen.blit(background, (0,0))\\n\\n # Check if the player has reached the end and has all the notes\\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20):\\n result = game_end(scoreF.getScore())\\n result[1].center = screen.get_rect().center\\n screen.blit(result[0], result[1])\\n \\n # Draw the updated Sprites\\n dirty = all.draw(screen)\\n pygame.display.flip()\\n\\n # Check if the end has ended\\n if (player.gameEnded() == 1) and (PLAYER_POS <= END_LVL+20): \\n pygame.time.wait(3000)\\n return\\n \\n # Stop the music and quit\\n if pygame.mixer:\\n pygame.mixer.music.stop()\\n pygame.time.wait(1000)\\n pygame.quit()\",\n \"def Draw(self):\\n\\t\\tGameImage.Draw(self, self.coords)\",\n \"def on_show(self): \\n arcade.set_background_color(arcade.color.BLACK)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6508464","0.6444371","0.6252179","0.62192374","0.6206115","0.6204564","0.6166355","0.61551905","0.6130094","0.60961246","0.6088001","0.60873604","0.6068308","0.6057062","0.60507476","0.6043697","0.60300726","0.60265714","0.60210216","0.6011016","0.6006273","0.5990426","0.5981349","0.5977395","0.59744024","0.59697944","0.5960354","0.5955739","0.59447724","0.5932965","0.59240544","0.59150034","0.5911577","0.58615124","0.58570933","0.5846052","0.5842635","0.5840647","0.5834738","0.58279425","0.5826095","0.5824585","0.58228","0.5819891","0.5818073","0.58009124","0.5795956","0.57863146","0.5781552","0.57810074","0.5773792","0.57664645","0.57635635","0.57622933","0.576203","0.5756704","0.57553977","0.57534575","0.5741136","0.5739982","0.5735467","0.5735094","0.57247967","0.57221395","0.5715575","0.5708053","0.56948227","0.56922483","0.56922483","0.5690574","0.5686617","0.5674517","0.56712526","0.56618536","0.565478","0.56520706","0.56520706","0.56520706","0.56520706","0.5640172","0.5639731","0.56387866","0.56387866","0.56387866","0.56337595","0.5623961","0.5618065","0.5618005","0.56154555","0.5614718","0.56143886","0.5611809","0.5607629","0.56021774","0.56006145","0.5595717","0.55943996","0.5594043","0.55902237","0.5589885"],"string":"[\n \"0.6508464\",\n \"0.6444371\",\n \"0.6252179\",\n \"0.62192374\",\n \"0.6206115\",\n \"0.6204564\",\n \"0.6166355\",\n \"0.61551905\",\n \"0.6130094\",\n \"0.60961246\",\n \"0.6088001\",\n \"0.60873604\",\n \"0.6068308\",\n \"0.6057062\",\n \"0.60507476\",\n \"0.6043697\",\n \"0.60300726\",\n \"0.60265714\",\n \"0.60210216\",\n \"0.6011016\",\n \"0.6006273\",\n \"0.5990426\",\n \"0.5981349\",\n \"0.5977395\",\n \"0.59744024\",\n \"0.59697944\",\n \"0.5960354\",\n \"0.5955739\",\n \"0.59447724\",\n \"0.5932965\",\n \"0.59240544\",\n \"0.59150034\",\n \"0.5911577\",\n \"0.58615124\",\n \"0.58570933\",\n \"0.5846052\",\n \"0.5842635\",\n \"0.5840647\",\n \"0.5834738\",\n \"0.58279425\",\n \"0.5826095\",\n \"0.5824585\",\n \"0.58228\",\n \"0.5819891\",\n \"0.5818073\",\n \"0.58009124\",\n \"0.5795956\",\n \"0.57863146\",\n \"0.5781552\",\n \"0.57810074\",\n \"0.5773792\",\n \"0.57664645\",\n \"0.57635635\",\n \"0.57622933\",\n \"0.576203\",\n \"0.5756704\",\n \"0.57553977\",\n \"0.57534575\",\n \"0.5741136\",\n \"0.5739982\",\n \"0.5735467\",\n \"0.5735094\",\n \"0.57247967\",\n \"0.57221395\",\n \"0.5715575\",\n \"0.5708053\",\n \"0.56948227\",\n \"0.56922483\",\n \"0.56922483\",\n \"0.5690574\",\n \"0.5686617\",\n \"0.5674517\",\n \"0.56712526\",\n \"0.56618536\",\n \"0.565478\",\n \"0.56520706\",\n \"0.56520706\",\n \"0.56520706\",\n \"0.56520706\",\n \"0.5640172\",\n \"0.5639731\",\n \"0.56387866\",\n \"0.56387866\",\n \"0.56387866\",\n \"0.56337595\",\n \"0.5623961\",\n \"0.5618065\",\n \"0.5618005\",\n \"0.56154555\",\n \"0.5614718\",\n \"0.56143886\",\n \"0.5611809\",\n \"0.5607629\",\n \"0.56021774\",\n \"0.56006145\",\n \"0.5595717\",\n \"0.55943996\",\n \"0.5594043\",\n \"0.55902237\",\n \"0.5589885\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.71416545"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":25697,"cells":{"query":{"kind":"string","value":"Setup injections Note that the actual injected current is proportional to dt of the clock So, you need to use the same dt for stimulation as for the model Strangely, the pulse gen in compartment_net refers to firstdelay, etc."},"document":{"kind":"string","value":"def setupinj(model, delay,width,neuron_pop):\n pg = moose.PulseGen('pulse')\n pg.firstDelay = delay\n pg.firstWidth = width\n pg.secondDelay = 1e9\n for ntype in neuron_pop.keys():\n for num, name in enumerate(neuron_pop[ntype]):\n injectcomp=moose.element(name +'/'+model.param_cond.NAME_SOMA)\n print(\"INJECT:\", name, injectcomp.path)\n moose.connect(pg, 'output', injectcomp, 'injectMsg')\n return pg"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def setup(timestep=None, min_delay=None, max_delay=None, **kwargs):\n global controller\n\n logger.info(\"PACMAN103 (c) 2014 APT Group, University of Manchester\")\n logger.info(\" Release version 2014.4.1 - April 2014\")\n # Raise an exception if no SpiNNaker machine is specified\n if kwargs.has_key(\"machine\"):\n machine_name = kwargs.get(\"machine\")\n logger.warn(\"The machine name from kwargs is overriding the machine \"\n \"name defined in the pacman.cfg file\")\n elif conf.config.has_option(\"Machine\", \"machineName\"):\n machine_name = conf.config.get(\"Machine\", \"machineName\")\n else:\n raise Exception(\"A SpiNNaker machine must be specified in pacman.cfg.\")\n if machine_name == 'None':\n raise Exception(\"A SpiNNaker machine must be specified in pacman.cfg.\")\n\n reload_time = None\n if conf.config.has_option(\"Execute\", \"reload_date\"):\n reload_time = conf.config.get(\"Execute\", \"reload_date\")\n if reload_time != 'None':\n logger.warn(\"The reload parameter was set, therefore not recompiling\")\n else:\n reload_time = None\n\n #deal with params allowed via the setup optimals\n if timestep is not None:\n timestep *= 1000 # convert into ms from microseconds\n conf.config.set(\"Machine\", \"machineTimeStep\", timestep)\n else:\n timestep = conf.config.get(\"Machine\", \"machineTimeStep\")\n if min_delay is not None and float(min_delay * 1000) < 1.0 * timestep:\n raise exceptions.ConfigurationException(\"Pacman does not support min \"\n \"delays below {} ms with the current \"\n \"machine time step\".format(1.0 * timestep))\n\n natively_supported_delay_for_models = MAX_SUPPORTED_DELAY_TICS\n delay_extention_max_supported_delay = MAX_DELAY_BLOCKS * MAX_TIMER_TICS_SUPPORTED_PER_BLOCK\n\n max_delay_tics_supported = \\\n natively_supported_delay_for_models + delay_extention_max_supported_delay\n\n if max_delay is not None and float(max_delay * 1000) > max_delay_tics_supported * timestep:\n raise exceptions.ConfigurationException(\"Pacman does not support max delays \"\n \"above {} ms with the current machine \"\n \"time step\".format(0.144 * timestep))\n if min_delay is not None:\n conf.config.add_section(\"Model\")\n conf.config.set(\"Model\", \"min_delay\", (min_delay * 1000) / timestep)\n\n if max_delay is not None:\n if not conf.config.has_section(\"Model\"):\n conf.config.add_section(\"Model\")\n conf.config.set(\"Model\", \"max_delay\", (max_delay * 1000) / timestep)\n\n time_scale_factor = None\n if (conf.config.has_option(\"Machine\", \"timeScaleFactor\") and\n conf.config.get(\"Machine\", \"timeScaleFactor\") != \"None\"):\n time_scale_factor = conf.config.getint(\"Machine\", \"timeScaleFactor\")\n if timestep * time_scale_factor < 1000:\n logger.warn(\"the combination of machine time step and the machine \"\n \"time scale factor results in a real timer tic that is \"\n \"currently not reliably supported by the spinnaker \"\n \"machine.\")\n else:\n time_scale_factor = max(1, math.ceil(1000.0 / float(timestep)))\n if time_scale_factor > 1:\n logger.warn(\"A timestep was entered that has forced pacman103 to \"\n \"automatically slow the simulation down from real time \"\n \"by a factor of {}. To remove this automatic behaviour\"\n \", please enter a timescaleFactor value in \"\n \"your .pacman.cfg\".format(time_scale_factor))\n\n\n\n\n \n # Create a new Controller to run PyNN:\n controller = control.Controller(sys.modules[__name__],\n machine_name, reload_time=reload_time)\n # Set the app ID:\n appID = conf.config.getint(\"Machine\", \"appID\")\n controller.dao.app_id = appID\n logger.info(\"Setting appID to %d.\" % appID)\n # Set the machine time step for the simulation:\n machineTimeStep = conf.config.getint(\"Machine\", \"machineTimeStep\")\n controller.dao.machineTimeStep = machineTimeStep\n logger.info(\"Setting machine time step to %d micro-seconds.\" % machineTimeStep)\n controller.dao.time_scale_factor = time_scale_factor\n logger.info(\"Setting time scale factor to %d.\" % time_scale_factor)\n # Set boolean variable writeTextSpecs in DAO if we are required to:\n writeTextSpecs = False\n if conf.config.getboolean(\"Reports\", \"reportsEnabled\"):\n writeTextSpecs = conf.config.getboolean(\"Reports\", \"writeTextSpecs\")\n controller.dao.writeTextSpecs = writeTextSpecs\n\n if conf.config.has_option(\"Recording\", \"send_live_spikes\"):\n if conf.config.getboolean(\"Recording\", \"send_live_spikes\") == True:\n port = None\n if conf.config.has_option(\"Recording\", \"live_spike_port\"):\n port = conf.config.getint(\"Recording\", \"live_spike_port\")\n hostname = \"localhost\"\n if conf.config.has_option(\"Recording\", \"live_spike_host\"):\n hostname = conf.config.get(\"Recording\", \"live_spike_host\")\n tag = None\n if conf.config.has_option(\"Recording\", \"live_spike_tag\"):\n tag = conf.config.getint(\"Recording\", \"live_spike_tag\")\n if tag == None:\n raise exceptions.PacmanException(\"Target tag for live spikes \"\n \"has not been set\")\n\n # Set up the forwarding so that monitored spikes are sent to the\n # requested location\n controller.set_tag_output(tag, port, hostname, 10)\n #takes the same port for the visualiser if being used\n if conf.config.getboolean(\"Visualiser\", \"enable\") and \\\n conf.config.getboolean(\"Visualiser\", \"have_board\"):\n controller.set_visulaiser_port(port)\n \n # Create special AppMonitor vertex, to receive spikes for immediate \n # transfer to host:\n monitorVertex = AppMonitor()\n \n # Add the special vertex to the list of vertices:\n controller.add_vertex(monitorVertex)\n \n # Get track of this special vertex as it will be used as a target\n # for recorded spikes:\n global appMonitorVertex\n appMonitorVertex = monitorVertex\n\n # PyNN API says something must be returned, \n # so we return something useful: our controller instance\n return controller","def __init__(self,n,\n d=3,\n maxn=125,\n controllers=[],\n xmax=XMAX,\n ymax=YMAX,\n zmax=ZMAX,\n vmax=VMAX,\n simbox=None,\n mass=1.0,\n rinit=None,\n source=None,\n side=(5,5,5),\n integrator='rk4',\n spacing=0.1):\n self.n = n\n self.dim = d\n self.maxn = maxn\n self.dt = 0.0\n self.steps = 0\n\n # Basic mechanical properties\n if not simbox:\n self.box = box.MirrorBox(p=self,xmax=xmax,ymax=ymax,zmax=zmax)\n else:\n self.box = simbox\n \n # Select integrator\n integrator_mapping = {'euler':euler,\n 'ieuler':imp_euler,\n 'rk4':rk4}\n\n self.step = integrator_mapping[integrator]\n\n # Start with a random configuration\n self.r = self.box.xmax * np.random.random([self.maxn,self.dim])\n self.m = np.zeros(self.maxn,dtype=float)\n self.v = vmax * (np.random.random([self.maxn,self.dim]) - 0.5)\n self.rdot = np.zeros(self.r.shape)\n self.vdot = np.zeros(self.v.shape)\n self.mdot = np.zeros(self.m.shape)\n\n if rinit == 'grid':\n self.r[0:n,:] = configuration.grid3d(n,side,(xmax/2.,ymax/2.,zmax/2.)\n ,spacing=spacing)\n elif rinit == 'fcc':\n self.r[0:n,:] = configuration.fcc3d(n,side,(xmax/2.,ymax/2.,zmax/2.)\n ,spacing=spacing)\n elif rinit == 'load':\n # Load the configuration from a target.\n # Today the target is hard-coded\n source = os.environ.get('SPDATA') + '/' + source #nanobox_eq_2.nc'\n read_step(source,self,step='last')\n # Make some assumptions about the source file.\n\n # Initialise values\n #self.r[0:self.n]=configuration.grid3d(self.n,5,5,(20,20,20),spacing=0.8)\n self.m[:] = mass \n self.colour = 1.0,0.0,0.0 \n\n # State vectors to pass to numerical integrators\n n_variables = 7\n self.x = np.zeros([n_variables,self.maxn])\n self.xdot = np.zeros([n_variables,self.maxn])\n\n self.nlists = []\n self.forces = []\n\n self.controllers = controllers\n for controller in self.controllers:\n controller.bind_particles(self)\n\n \"\"\" Variables for measuring performance. \"\"\"\n self.timing = {}\n self.timing['force time'] = -1\n self.timing['deriv time'] = -1\n self.timing['pairsep time'] = -1\n self.timing['update time'] = -1\n self.timing['integrate time'] = -1","def startup(self):\n # Initializing the cycle data (cd) dictionary\n self.cd[\"started_up\"] = False\n self.cd[\"peak_pressure\"] = 0\n self.cd[\"tidal_volume\"] = 0\n self.cd[\"inhale_duration\"] = 0\n self.cd[\"exhale_duration\"] = 0\n self.cd[\"IE_ratio\"] = 1\n self.cd[\"PEEP\"] = 0\n\n to = 2 # Timeout\n startup_cycles = 0\n limit = 20\n # If the piston position is unknown\n last_cycle = time.time()\n while not self.piston.piston_at_bottom and not self.piston.piston_at_top:\n if self.pst_dir == 1:\n self.piston.pst_up()\n if time.time() - last_cycle > to:\n self.pst_dir = 0\n startup_cycles += 1\n last_cycle = time.time()\n else:\n self.piston.pst_down()\n if time.time() - last_cycle > to:\n self.pst_dir = 1\n startup_cycles += 1\n last_cycle = time.time()\n if startup_cycles >= limit:\n print(\"There is a problem at startup, check compressed air\")\n print(f\"Tried to startup for {startup_cycles} cycles\")\n # Breaks the loop so that the controller doesn't start\n self.signal_startup_error.emit(True)\n return\n while not self.piston.piston_at_top:\n self.piston.pst_up()\n self.piston.stop()\n\n print(f\"startup_cycles: {startup_cycles}\")\n self.cd[\"started_up\"] = True\n self.signal_cycle_data.emit(self.cd)\n # Duration of the first tare of the system\n tare_duration = 5.0\n time.sleep(tare_duration)\n self.signal_get_tare.emit(tare_duration)\n # Waits a little bit just to make sure that the respirator isn't working when the controller \n # is called\n time.sleep(0.5)\n self.piston_control()","def setup_ssem(self):\n \n groundBox = box_polygon_shape(-20,-500,1,1) # A tiny box that just acts as the ground body for everything else\n groundBody = self.world.CreateStaticBody(shapes=groundBox)\n self.memory_sender_y = -500\n self.groundBody = groundBody\n # Initial charge for main injector\n self.ball_bearing_block(0,190,cols=16)\n self.add_static_polygon([ (0,20), (100,0), (100,5), (0,25)], -132, 220)\n self.add_static_polygon([ (0,0), (3,0), (3,20), (0,20)], -132, 240)\n self.injector_cranks = []\n self.parts.main_injector_raiser = self.injector(-32,150, groundBody, injector_crank_array=self.injector_cranks)\n\n (self.parts.memory_selector_holdoff, self.parts.memory_follower_holdoff) = self.memory_module(0,0, groundBody)\n self.upper_regenerators = []\n self.parts.accumulator_diverter_lever = self.diverter_set(0,130, groundBody, slope_x=-240, slope_y=180, return_weight=10) # Diverter 1. Splits to subtractor reader.\n\n self.parts.discard_lever_2 = self.diverter_set(-5,-30, groundBody, discard=470) # Diverter 2a. Discard reader-pulse data.\n self.parts.upper_regen_control = self.regenerator(-5,-65, groundBody, self.upper_regenerators) # Regenerator 1. For regenning anything read from memory.\n self.parts.ip_diverter_lever = self.diverter_set(-5,-95, groundBody, slope_x=320, slope_y=170, start_at=3, return_weight=5) # Diverter 1. Splits to instruction counter.\n self.parts.diverter_3 = self.diverter_set(-10,-158, groundBody, slope_x=200, slope_y=310) # Diverter 3; splits to instruction reg/PC\n \n # PC injector\n pc_injector_x = 230\n pc_injector_y = -290\n self.pc_injector_cranks = [] \n self.parts.pc_injector_raiser = self.injector(pc_injector_x,pc_injector_y, groundBody, injector_crank_array=self.pc_injector_cranks, columns=5)\n # Initial charge for PC injector\n self.ball_bearing_block(250,-240,cols=8)\n\n\n sub_pos_x = -15\n sub_pos_y = -220\n self.parts.accumulator_reset_lever = self.subtractor(sub_pos_x,sub_pos_y, groundBody, discard_bands=True, toggle_joint_array=self.accumulator_toggles, comparison_output=True)\n self.dropper = self.slow_drop_unit(groundBody, sub_pos_x-18, sub_pos_y+40)\n\n # The 'skip lever' - the large balance arm which injects one\n # into the program counter when comparison (CMP) succeeds\n skip_lever_x = sub_pos_x - 200\n skip_lever_y = sub_pos_y - 200\n a = fixtureDef(shape=polygonShape(vertices=[(-50,-32), (0,-30), (0,-25), (-50,-30)]), filter=filters[0], density=1.0)\n b = fixtureDef(shape=box_polygon_shape(0,-30,5,30), filter=filters[0], density=1.0)\n c = fixtureDef(shape=box_polygon_shape(-30,-30,5,30), filter=filters[0], density=1.0)\n d = fixtureDef(shape=box_polygon_shape(0,0,300,5), filter=filters[2], density=1.0)\n e = fixtureDef(shape=box_polygon_shape(285,-15,15,15), filter=filters[2], density=2.10)\n f = fixtureDef(shape=box_polygon_shape(150,-50,5,50), filter=filters[0], density=1.0)\n skip_lever=self.add_multifixture([a,b,d,e,f], skip_lever_x, skip_lever_y)\n skip_lever.attachment_point = (150,-50)\n skip_lever.origin = (skip_lever_x,skip_lever_y)\n\n self.revolving_joint(groundBody, skip_lever, (skip_lever_x+150, skip_lever_y+2.5), friction=0)\n self.add_static_polygon(polygonShape(vertices=box_vertices(0, 0, 10,10)), skip_lever_x+270, skip_lever_y-15, filter=filters[2])\n self.parts.cmp_injector = self.horizontal_injector(skip_lever_x-48,skip_lever_y+257, groundBody)\n self.ball_bearing_block(skip_lever_x-30,skip_lever_y+280,cols=1)\n self.add_static_polygon(polygonShape(vertices=[(0,0), (20,0), (0,20)]), skip_lever_x-30,skip_lever_y+230)\n \n self.lower_regenerators = []\n self.parts.lower_regen_control = self.regenerator(-203,-400, groundBody, self.lower_regenerators)\n #Program counter\n self.parts.pc_reset_lever = self.subtractor(400,-320, groundBody, lines=5, toggle_joint_array=self.ip_toggles, is_actually_adder=True)\n # Thing that adds one ball bearing to the PC\n pc_incrementer_x = 457\n pc_incrementer = self.horizontal_injector(pc_incrementer_x,-240, groundBody)\n # Overspill loose ball bearings from the PC incrementer to the PC reader\n overspill_width = pc_incrementer_x - pc_injector_x - 125\n self.add_static_polygon([ (0, 0), (overspill_width,15), (overspill_width,20), (0,5) ], pc_injector_x+125,pc_injector_y+65)\n\n # Block to stop right-side overspill on incrementer\n self.add_static_polygon([ (0, 0), (5,0), (5,20), (0,20) ], pc_incrementer_x+27,-240+40)\n\n\n self.ball_bearing_block(457+20,-250+30,cols=1)\n self.distance_joint(skip_lever, pc_incrementer)\n\n self.connect_regenerators()\n\n # Large collection plates at the bottom\n self.add_static_polygon([ (-300,-600),(700,-550), (700,-610), (-300,-610)])\n self.add_static_polygon([ (600,-610),(700,-610), (850,-400), (800,-400)])\n self.add_static_polygon([ (-500,-400),(-450,-400), (-310,-610), (-400,-610)])\n\n # Instruction decoder ROM\n self.rom_followers = []\n self.rom_selectors = []\n (self.parts.instruction_selector_holdoff, self.parts.instruction_follower_holdoff) = self.add_row_decoder(200, 0, groundBody, self.rom_followers, self.rom_selectors)\n self.labels.append((\"Instruction decoder\", 400,0,0))\n\n self.add_instruction_cranks(groundBody, 550, 140)\n self.parts.sender_eject = self.memory_sender(198,self.memory_sender_y, groundBody)\n self.connect_memory()\n\n # A guard which stops waste data from the subtractor falling into the instruction register\n self.add_static_polygon([ (0,0), (120,120), (120,123), (0,3)], 120, self.memory_sender_y-10)\n\n # Add one final transfer band to move everything back into band 0\n self.transfer_bands.append((-550+10, -550, [ (-300,800)], 1))","def setup(self, tau1=None, tau2=None, template_tmax=None, dt=None, \n delay=0.0, sign=1, eventstartthr=None, risepower=4., min_event_amplitude=2.0):\n assert sign in [-1, 1]\n self.sign = sign\n self.taus = [tau1, tau2]\n self.dt = dt\n self.template_tmax = template_tmax\n self.idelay = int(delay/dt) # points delay in template with zeros\n self.template = None # reset the template if needed.\n self.eventstartthr = eventstartthr\n self.risepower = risepower\n self.min_event_amplitude = min_event_amplitude","def setup(self):\n\n self._enable_torque(self._reg.TORQUE_ENABLE)\n self.change_operating_mode(self._reg.MODE_EXT_POSI)\n # set to max velocity\n self.change_veloity(self._default_velocity)","def prepare_experiment(assumptions):\n print(\"\\nGenerate species parameters\")\n np.random.seed(assumptions['seed']) \n params = MakeParams(assumptions) \n if assumptions[\"selected_function\"] == \"f5_invader_suppression\":\n print(\"\\nDraw invader feature\")\n params = create_invader(params, assumptions)\n print(params[\"c\"])\n \n print(\"\\nDraw per-capita function and cost\")\n f1_species_smooth, f1_species_rugged, f2_species_smooth, f2_species_rugged = draw_species_function(assumptions)\n params.update({\"f1_species_smooth\": f1_species_smooth, \"f1_species_rugged\": f1_species_rugged, \"f2_species_smooth\": f2_species_smooth, \"f2_species_rugged\": f2_species_rugged})\n gi = draw_species_cost(f1_species_smooth, assumptions)\n params.update({\"g\": gi})\n \n print(\"\\nConstruct plate\")\n np.random.seed(assumptions['seed']) \n plate = make_plate(assumptions,params)\n \n print(\"\\nAdd community function to plate\")\n plate = add_community_function(plate, assumptions, params)\n \n if not pd.isnull(assumptions[\"overwrite_plate\"]) :\n print(\"\\nUpdating the initial plate composition by overwrite_plate\")\n plate = overwrite_plate(plate, assumptions)\n \n print(\"\\nPrepare Protocol\")\n #Extract Protocol from protocol database\n algorithms = make_algorithms(assumptions)\n params_algorithm = algorithms[algorithms['algorithm_name'] == assumptions['protocol']]\n \n #Params_simulation by default contains all assumptions not stored in params.\n params_simulation = dict((k, assumptions[k]) for k in assumptions.keys() if k not in params.keys())\n \n return params, params_simulation , params_algorithm, plate","def setup(self, tau1=None, tau2=None, template_tmax=0.05, dt=None, \n delay=0.0, sign=1, eventstartthr=None, risepower=4.0, min_event_amplitude=2.0):\n assert sign in [-1, 1]\n self.sign = sign\n self.taus = [tau1, tau2]\n self.dt = dt\n self.template_tmax = template_tmax\n self.idelay = int(delay/dt) # points delay in template with zeros\n self.template = None # reset the template if needed.\n self.eventstartthr = eventstartthr\n self.risepower = risepower\n self.min_event_amplitude = min_event_amplitude","def setup(env, channel, interT, station, mean):\r\n network = Network(env, channel)\r\n system = System(env, network, station, mean)\r\n transmitList = []\r\n \r\n while True:\r\n system.stations","def __init__(self,\n setup,\n host=None,\n dof=6,\n control_type='position',\n derivative_type='none',\n target_type='position',\n reset_type='random',\n reward_type='linear',\n deriv_action_max=10,\n first_deriv_max=10, # used only with second derivative control\n vel_penalty=0,\n obs_history=1,\n actuation_sync_period=1,\n episode_length_time=None,\n episode_length_step=None,\n rllab_box = False,\n servoj_t=ur_utils.COMMANDS['SERVOJ']['default']['t'],\n servoj_gain=ur_utils.COMMANDS['SERVOJ']['default']['gain'],\n speedj_a=ur_utils.COMMANDS['SPEEDJ']['default']['a'],\n speedj_t_min=ur_utils.COMMANDS['SPEEDJ']['default']['t_min'],\n movej_t=2, # used for resetting\n accel_max=None,\n speed_max=None,\n dt=0.008,\n delay=0.0, # to simulate extra delay in the system\n **kwargs):\n\n\n # Check that the task parameters chosen are implemented in this class\n assert dof in [2, 6]\n assert control_type in ['position', 'velocity', 'acceleration']\n assert derivative_type in ['none', 'first', 'second']\n assert target_type in ['position', 'angle']\n assert reset_type in ['random', 'zero', 'none']\n assert actuation_sync_period >= 0\n\n if episode_length_step is not None:\n assert episode_length_time is None\n self._episode_length_step = episode_length_step\n self._episode_length_time = episode_length_step * dt\n elif episode_length_time is not None:\n assert episode_length_step is None\n self._episode_length_time = episode_length_time\n self._episode_length_step = int(episode_length_time / dt)\n else:\n #TODO: should we allow a continuous behaviour case here, with no episodes?\n print(\"episode_length_time or episode_length_step needs to be set\")\n raise AssertionError\n\n # Task Parameters\n self._host = setups[setup]['host'] if host is None else host\n self._obs_history = obs_history\n self._dof = dof\n self._control_type = control_type\n self._derivative_type = derivative_type\n self._target_type = target_type\n self._reset_type = reset_type\n self._reward_type = reward_type\n self._vel_penalty = vel_penalty # weight of the velocity penalty\n self._deriv_action_max = deriv_action_max\n self._first_deriv_max = first_deriv_max\n self._speedj_a = speedj_a\n self._delay = delay\n self.return_point = None\n if accel_max==None:\n accel_max = setups[setup]['accel_max']\n if speed_max==None:\n speed_max = setups[setup]['speed_max']\n if self._dof == 6:\n self._joint_indices = [0, 1, 2, 3, 4, 5]\n self._end_effector_indices = [0, 1, 2]\n elif self._dof == 2:\n self._joint_indices = [1, 2]\n self._end_effector_indices = [1, 2]\n\n # Arm/Control/Safety Parameters\n self._end_effector_low = setups[setup]['end_effector_low']\n self._end_effector_high = setups[setup]['end_effector_high']\n self._angles_low = setups[setup]['angles_low'][self._joint_indices]\n self._angles_high = setups[setup]['angles_high'][self._joint_indices]\n self._speed_low = -np.ones(self._dof) * speed_max\n self._speed_high = np.ones(self._dof) * speed_max\n self._accel_low = -np.ones(self._dof) * accel_max\n self._accel_high = np.ones(self._dof) * accel_max\n\n self._box_bound_buffer = setups[setup]['box_bound_buffer']\n self._angle_bound_buffer = setups[setup]['angle_bound_buffer']\n self._q_ref = setups[setup]['q_ref']\n self._ik_params = setups[setup]['ik_params']\n\n # State Variables\n self._q_ = np.zeros((self._obs_history, self._dof))\n self._qd_ = np.zeros((self._obs_history, self._dof))\n\n self._episode_steps = 0\n\n self._pstop_time_ = None\n self._pstop_times_ = []\n self._safety_mode_ = ur_utils.SafetyModes.NONE\n self._max_pstop = 10\n self._max_pstop_window = 600\n self._clear_pstop_after = 2\n self._x_target_ = np.frombuffer(Array('f', 3).get_obj(), dtype='float32')\n self._x_ = np.frombuffer(Array('f', 3).get_obj(), dtype='float32')\n self._reward_ = Value('d', 0.0)\n\n if self._target_type == 'position':\n if self._dof == 2:\n self._target_ = np.zeros((2))\n self._target_low = self._end_effector_low[self._end_effector_indices]\n self._target_high = self._end_effector_high[self._end_effector_indices]\n elif self._dof == 6:\n self._target_ = np.zeros((3))\n self._target_low = self._end_effector_low\n self._target_high = self._end_effector_high\n elif self._target_type == 'angle':\n self._target_ = np.zeros((self._dof))\n self._target_low = self._angles_low\n self._target_high = self._angles_high\n\n # Set up action and observation space\n\n if self._derivative_type== 'second' or self._derivative_type== 'first':\n self._action_low = -np.ones(self._dof) * self._deriv_action_max\n self._action_high = np.ones(self._dof) * self._deriv_action_max\n else: # derivative_type=='none'\n if self._control_type == 'position':\n self._action_low = self._angles_low\n self._action_high = self._angles_high\n elif self._control_type == 'velocity':\n self._action_low = self._speed_low\n self._action_high = self._speed_high\n elif self._control_type == 'acceleration':\n self._action_low = self._accel_low\n self._action_high = self._accel_high\n\n # TODO: is there a nicer way to do this?\n if rllab_box:\n from rllab.spaces import Box as RlBox # use this for rllab TRPO\n Box = RlBox\n else:\n from gym.spaces import Box as GymBox # use this for baselines algos\n Box = GymBox\n\n self._observation_space = Box(\n low=np.array(\n list(self._angles_low * self._obs_history) # q_actual\n + list(-np.ones(self._dof * self._obs_history)) # qd_actual\n + list(self._target_low) # target\n + list(-self._action_low) # previous action in cont space\n ),\n high=np.array(\n list(self._angles_high * self._obs_history) # q_actual\n + list(np.ones(self._dof * self._obs_history)) # qd_actual\n + list(self._target_high) # target\n + list(self._action_high) # previous action in cont space\n )\n )\n\n\n self._action_space = Box(low=self._action_low, high=self._action_high)\n\n if rllab_box:\n from rllab.envs.env_spec import EnvSpec\n self._spec = EnvSpec(self.observation_space, self.action_space)\n\n # Only used with second derivative control\n self._first_deriv_ = np.zeros(len(self.action_space.low))\n\n # Communicator Parameters\n communicator_setups = {'UR5':\n {\n 'num_sensor_packets': obs_history,\n\n 'kwargs': {'host': self._host,\n 'actuation_sync_period': actuation_sync_period,\n 'buffer_len': obs_history + SharedBuffer.DEFAULT_BUFFER_LEN,\n }\n }\n }\n if self._delay > 0:\n from senseact.devices.ur.ur_communicator_delay import URCommunicator\n communicator_setups['UR5']['kwargs']['delay'] = self._delay\n else:\n from senseact.devices.ur.ur_communicator import URCommunicator\n communicator_setups['UR5']['Communicator'] = URCommunicator\n\n super(ReacherEnv, self).__init__(communicator_setups=communicator_setups,\n action_dim=len(self.action_space.low),\n observation_dim=len(self.observation_space.low),\n dt=dt,\n **kwargs)\n\n # The last action\n self._action_ = self._rand_obj_.uniform(self._action_low, self._action_high)\n\n # Defining packet structure for quickly building actions\n self._reset_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\n self._reset_packet[0] = ur_utils.COMMANDS['MOVEJ']['id']\n self._reset_packet[1:1 + 6] = self._q_ref\n self._reset_packet[-2] = movej_t\n\n self._servoj_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\n self._servoj_packet[0] = ur_utils.COMMANDS['SERVOJ']['id']\n self._servoj_packet[1:1 + 6] = self._q_ref\n self._servoj_packet[-3] = servoj_t\n self._servoj_packet[-1] = servoj_gain\n\n self._speedj_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\n self._speedj_packet[0] = ur_utils.COMMANDS['SPEEDJ']['id']\n self._speedj_packet[1:1 + 6] = np.zeros((6,))\n self._speedj_packet[-2] = speedj_a\n self._speedj_packet[-1] = speedj_t_min\n\n self._stopj_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\n self._stopj_packet[0] = ur_utils.COMMANDS['STOPJ']['id']\n self._stopj_packet[1] = 2.0\n\n # Tell the arm to do nothing (overwritting previous command)\n self._nothing_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\n\n self._pstop_unlock_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\n self._pstop_unlock_packet[0] = ur_utils.COMMANDS['UNLOCK_PSTOP']['id']\n\n\n # self.info['reward_dist'] = 0\n # self.info['reward_vel'] = 0","def setup(self, tau1=None, tau2=None, template_tmax=None, dt=None, \n delay=0.0, sign=1, eventstartthr=None, risepower=4., min_event_amplitude=2.0):\n assert sign in [-1, 1] # must be selective, positive or negative events only\n self.sign = sign\n self.taus = [tau1, tau2]\n self.dt = 1/20000.\n self.template_tmax = template_tmax\n self.idelay = int(delay/dt) # points delay in template with zeros\n self.template = None # reset the template if needed.\n self.eventstartthr = eventstartthr\n self.risepower = risepower\n self.min_event_amplitude = min_event_amplitude","def set_up_model(dt, model, update = False):\n \n start_scope()\n \n ##### Update model parameters (should be done, if original parameters have been changed)\n if update:\n ##### Structure of ANF\n # terminal = 0\n # internode = 1\n # node = 2\n # presomatic region = 3\n # Soma = 4\n # postsomatic region = 5\n model.structure = np.array(list(np.tile([2] + np.tile([1],model.nof_segments_internodes).tolist(),model.nof_internodes)) + [2])\n model.nof_comps = len(model.structure)\n \n ##### compartment lengths\n # initialize\n model.compartment_lengths = np.zeros_like(structure)*um\n # length internodes\n model.compartment_lengths[model.structure == 1] = model.length_internodes / model.nof_segments_internodes\n # length nodes\n model.compartment_lengths[model.structure == 2] = model.length_nodes\n # total length neuron\n model.length_neuron = sum(model.compartment_lengths)\n \n ##### Compartment diameters\n # initialize\n model.compartment_diameters = np.zeros(model.nof_comps+1)*um\n # same diameter for whole fiber\n model.compartment_diameters[:] = model.diameter_fiber\n \n ##### conductivity of leakage channels\n model.g_L = model.g_L_node/model.surface_aria_node\n\n ##### Surface arias\n # lateral surfaces\n m = [np.sqrt(abs(model.compartment_diameters[i+1] - model.compartment_diameters[i])**2 + model.compartment_lengths[i]**2)\n for i in range(0,model.nof_comps)]\n # total surfaces\n model.A_surface = [(model.compartment_diameters[i+1] + model.compartment_diameters[i])*np.pi*m[i]*0.5\n for i in range(0,model.nof_comps)]\n \n ##### Compartment middle point distances (needed for plots)\n model.distance_comps_middle[0] = 0.5*model.compartment_lengths[0]\n model.distance_comps_middle = np.zeros_like(model.compartment_lengths)\n for ii in range(0,model.nof_comps-1):\n model.distance_comps_middle[ii+1] = 0.5* model.compartment_lengths[ii] + 0.5* model.compartment_lengths[ii+1]\n \n ##### Capacities\n # initialize\n model.c_m = np.zeros_like(model.structure)*uF/cm**2\n # nodes\n model.c_m[model.structure == 2] = model.c_m_node/model.surface_aria_node\n # internodes\n model.c_m[structure == 1] = model.c_m_layer/(1+model.nof_myelin_layers)\n \n ##### Condactivities internodes\n # initialize\n model.g_m = np.zeros_like(model.structure)*msiemens/cm**2\n # internodes\n model.g_m[model.structure == 1] = model.g_m_layer/(1+model.nof_myelin_layers)\n \n ##### Axoplasmatic resistances\n model.compartment_center_diameters = np.zeros(model.nof_comps)*um\n model.compartment_center_diameters = (model.compartment_diameters[0:-1] + model.compartment_diameters[1:]) / 2\n model.R_a = (model.compartment_lengths*model.rho_in) / ((model.compartment_center_diameters*0.5)**2*np.pi)\n \n ##### Noise term\n model.gamma_Na_vector = np.zeros(model.nof_comps)*psiemens\n model.gamma_Na_vector[model.structure == 2] = model.gamma_Na\n model.noise_term = np.sqrt(model.A_surface*model.gamma_Na_vector*model.rho_Na)\n \n ##### Compartments to plot\n # get indexes of all compartments that are not segmented\n model.indexes_comps = np.where(model.structure == 2)[0]\n # calculate middle compartments of internodes\n model.middle_comps_internodes = np.ceil(model.indexes_comps[:-1] + model.nof_segments_internodes/2).astype(int)\n # create array with all compartments to plot\n model.comps_to_plot = np.sort(np.append(model.indexes_comps, model.middle_comps_internodes))\n \n ##### initialize defaultclock\n defaultclock.dt = dt\n\n ##### define morphology\n morpho = Section(n = model.nof_comps,\n length = model.compartment_lengths,\n diameter = model.compartment_diameters)\n \n ##### define neuron\n neuron = SpatialNeuron(morphology = morpho,\n model = model.eqs,\n Cm = model.c_m,\n Ri = model.rho_in,\n method=\"exponential_euler\")\n \n ##### initial values\n neuron.v = model.V_res\n neuron.m = model.m_init\n neuron.h = model.h_init\n neuron.n = model.n_init\n \n ##### Set parameter values of differential equations\n # conductances nodes\n neuron.gamma_Na = model.gamma_Na\n neuron.gamma_K = model.gamma_K\n neuron.g_L = model.g_L\n \n # conductances internodes\n neuron.g_myelin = model.g_m\n neuron.gamma_Na[np.asarray(np.where(model.structure == 1))] = 0*psiemens\n neuron.gamma_K[np.asarray(np.where(model.structure == 1))] = 0*psiemens\n neuron.g_L[np.asarray(np.where(model.structure == 1))] = 0*msiemens/cm**2\n \n # conductances peripheral terminal\n neuron.gamma_Na[np.where(model.structure == 0)[0]] = model.gamma_Na_terminal\n neuron.gamma_K[np.where(model.structure == 0)[0]] = model.gamma_K_terminal\n neuron.g_L[np.where(model.structure == 0)[0]] = model.g_L_terminal\n \n # conductances soma\n neuron.gamma_Na[index_soma] = 0*psiemens\n neuron.gamma_K[index_soma] = 0*psiemens\n neuron.g_L[index_soma] = 0*msiemens/cm**2\n \n # Nernst potential for leakage current\n neuron.E_Leak = model.E_L\n neuron.E_Leak[np.where(model.structure == 0)[0]] = E_L_terminal\n \n # other parameters\n neuron.V_res = model.V_res\n neuron.T_celsius = model.T_celsius\n neuron.E_Na = model.E_Na\n neuron.E_K = model.E_K\n neuron.rho_Na = model.rho_Na\n neuron.rho_K = model.rho_K\n \n return neuron, model","def get_observations(self):\n joint_states = self.joints_state\n self.force = self.wrench_stamped.wrench.force\n self.torque = self.wrench_stamped.wrench.torque\n self.static_taxel = self.tactile_static.taxels\n# dynamic_taxel= tactile_dynamic\n\n# print(\"[force]\", self.force.x, self.force.y, self.force.z)\n# print(\"[torque]\", self.torque.x, self.torque.y, self.torque.z)\n shp_joint_ang = joint_states.position[0]\n shl_joint_ang = joint_states.position[1]\n elb_joint_ang = joint_states.position[2]\n wr1_joint_ang = joint_states.position[3]\n wr2_joint_ang = joint_states.position[4]\n wr3_joint_ang = joint_states.position[5]\n\n shp_joint_vel = joint_states.velocity[0]\n shl_joint_vel = joint_states.velocity[1]\n elb_joint_vel = joint_states.velocity[2]\n wr1_joint_vel = joint_states.velocity[3]\n wr2_joint_vel = joint_states.velocity[4]\n wr3_joint_vel = joint_states.velocity[5]\n\n q = [shp_joint_ang, shl_joint_ang, elb_joint_ang, wr1_joint_ang, wr2_joint_ang, wr3_joint_ang]\n# print(\"q(observation):\", q)\n eef_x, eef_y, eef_z = self.get_xyz(q)\n self.end_effector = self.get_xyz(q)\n eef_x_ini, eef_y_ini, eef_z_ini = self.get_xyz(self.init_joint_pose2) \n\n delta_image_r, delta_image_l = self.get_image()\n self.cnn_image_r = agent.update_cnn(delta_image_r)\n self.cnn_image_l = agent.update_cnn(delta_image_l)\n self.cnn_image_r_list = self.cnn_image_r.tolist()\n self.cnn_image_l_list = self.cnn_image_l.tolist()\n print(\"r_list\", self.cnn_image_r_list)\n print(\"l_list\", self.cnn_image_l_list)\n\n observation = []\n# rospy.logdebug(\"List of Observations==>\"+str(self.observations))\n for obs_name in self.observations:\n if obs_name == \"shp_joint_ang\":\n observation.append((shp_joint_ang - self.init_joint_pose2[0]) * self.joint_n)\n elif obs_name == \"shl_joint_ang\":\n observation.append((shl_joint_ang - self.init_joint_pose2[1]) * self.joint_n)\n elif obs_name == \"elb_joint_ang\":\n observation.append((elb_joint_ang - self.init_joint_pose2[2]) * self.joint_n)\n elif obs_name == \"wr1_joint_ang\":\n observation.append((wr1_joint_ang - self.init_joint_pose2[3]) * self.joint_n)\n elif obs_name == \"wr2_joint_ang\":\n observation.append((wr2_joint_ang - self.init_joint_pose2[4]) * self.joint_n)\n elif obs_name == \"wr3_joint_ang\":\n observation.append((wr3_joint_ang - self.init_joint_pose2[5]) * self.joint_n)\n elif obs_name == \"shp_joint_vel\":\n observation.append(shp_joint_vel)\n elif obs_name == \"shl_joint_vel\":\n observation.append(shl_joint_vel)\n elif obs_name == \"elb_joint_vel\":\n observation.append(elb_joint_vel)\n elif obs_name == \"wr1_joint_vel\":\n observation.append(wr1_joint_vel)\n elif obs_name == \"wr2_joint_vel\":\n observation.append(wr2_joint_vel)\n elif obs_name == \"wr3_joint_vel\":\n observation.append(wr3_joint_vel)\n elif obs_name == \"eef_x\":\n observation.append((eef_x - eef_x_ini) * self.eef_n)\n elif obs_name == \"eef_y\":\n observation.append((eef_y - eef_y_ini) * self.eef_n)\n elif obs_name == \"eef_z\":\n observation.append((eef_z - eef_z_ini) * self.eef_n)\n elif obs_name == \"force_x\":\n observation.append((self.force.x - self.force_ini.x) / self.force_limit1 * self.force_n)\n elif obs_name == \"force_y\":\n observation.append((self.force.y - self.force_ini.y) / self.force_limit1 * self.force_n)\n elif obs_name == \"force_z\":\n observation.append((self.force.z - self.force_ini.z) / self.force_limit1 * self.force_n)\n elif obs_name == \"torque_x\":\n observation.append((self.torque.x - self.torque_ini.x) / self.torque_limit1 * self.torque_n)\n elif obs_name == \"torque_y\":\n observation.append((self.torque.y - self.torque_ini.y) / self.torque_limit1 * self.torque_n)\n elif obs_name == \"torque_z\":\n observation.append((self.torque.z - self.torque_ini.z) / self.torque_limit1 * self.torque_n)\n elif obs_name == \"image_cnn\":\n for x in range(0, 10):\n observation.append(self.cnn_image_r_list[0][x])\n# print(\"r_list\", self.cnn_image_r_list[0][x])\n for x in range(0, 10):\n observation.append(self.cnn_image_l_list[0][x])\n# print(\"l_list\", self.cnn_image_l_list[0][x])\n elif obs_name == \"static_taxel\":\n for x in range(0, 28):\n observation.append((self.static_taxel[0].values[x] - self.static_taxel_ini[0].values[x]) * self.taxel_n)\n for x in range(0, 28):\n observation.append((self.static_taxel[1].values[x] - self.static_taxel_ini[1].values[x]) * self.taxel_n)\n# elif obs_name == \"dynamic_taxel\":\n# observation.append(dynamic_taxel[0].values) * self.taxel_n\n# observation.append(dynamic_taxel[1].values) * self.taxel_n\n else:\n raise NameError('Observation Asked does not exist=='+str(obs_name))\n\n print(\"observation\", list(map(round, observation, [3]*len(observation))))\n# print(\"observation\", observation)\n\n return observation","def simulate(initstate, t, timestep=forward, drive=donothing, bounds = [0.97, 0.97, 0.97, 0.97], saveinterval=10, beta=0.281105, eps=0.013, gamma=0.0880, mu=0.3, nu=0, dudt_x = dudt, dvdt_x = dvdt, dndt_x = dndt, grav=True, cori=True, advx=True, advy=True, attn=True): # gives surface height array of the system after evert dt\n bounds = np.asarray(bounds, dtype=np.float32)\n h, n, u, v, f, dx, dy, dt = [initstate[k] for k in ('h', 'n', 'u', 'v', 'lat', 'dx', 'dy', 'dt')]\n \n f = np.float32(((2*2*np.pi*np.sin(f*np.pi/180))/(24*3600))[:,np.newaxis])\n \n \n du0 = np.zeros_like(u)\n dv0 = np.zeros_like(v)\n dn0 = np.zeros_like(n)\n \n \n dndt_x(h, n, u, v, dx, dy, dn0)\n dn = (dn0, np.copy(dn0), np.copy(dn0))\n \n dudt_x(h, n, f, u, v, dx, dy, du0)\n du = (du0, np.copy(du0), np.copy(du0), np.copy(du0))\n \n dvdt_x(h, n, f, u, v, dx, dy, dv0)\n dv = (dv0, np.copy(dv0), np.copy(dv0), np.copy(dv0))\n \n nu = (dx+dy)/1000\n \n mmax = np.max(np.abs(n))\n landthresh = 1.5*np.max(n) # threshhold for when sea ends and land begins\n itrs = int(np.ceil(t/dt))\n saveinterval = np.int(saveinterval//dt)\n assert (dt >= 0), 'negative dt!' # dont try if timstep is zero or negative\n \n ntt = np.zeros((np.int(np.ceil(itrs/saveinterval)),)+n.shape, dtype=np.float32)\n maxn = np.zeros(n.shape, dtype=n.dtype) # max height in that area\n \n coastx = np.less(h, landthresh) # where the reflective condition is enforced on the coast\n \n print('simulating...')\n try:\n for itr in range(itrs):# iterate for the given number of iterations\n if itr%saveinterval == 0:\n ntt[np.int(itr/saveinterval),:,:] = n\n print(np.argmax( ntt[np.int(itr/saveinterval),:,:],axis=0)[5])\n \n \n maxn = np.max((n, maxn), axis=0) # record new maxes if they are greater than previous records \n \n # pushes n, u, v one step into the future\n n,u,v, du, dv, dn = timestep(h, n, u, v, f, dt, dx, dy, du, dv, dn, beta=beta, eps=eps, gamma=gamma, mu=mu, nu=nu, dudt_x=dudt_x, dvdt_x=dvdt_x, dndt_x=dndt_x, grav=grav, cori=cori, advx=advx, advy=advy, attn=attn)\n\n land(h, n, u, v, coastx) # how to handle land/coast\n border(n, u, v, 15, bounds) \n drive(h, n, u, v, f, dt, dx, dy, nu, coastx, bounds, mu, itr)\n print('simulation complete')\n except Exception as e:\n print('timestep: ', itr)\n raise e\n return ntt, maxn#, minn, timemax # return surface height through time and maximum heights","def setup(env, NUM_TRACKS, landtime, t_inter):\n # Create the airport\n airport = Airport(env, NUM_TRACKS, landtime)\n\n # Create 4 initial planes\n for i in range(1):\n env.process(plane(env, 'Aviao %d' % i, airport))\n\n # Create more planes while the simulation is running\n while True:\n yield env.timeout(random.randint(t_inter-2, t_inter+2))\n# yield env.timeout(random.expovariate(1.0 / t_inter))\n i += 1\n env.process(plane(env, 'Aviao %d' % i, airport))","def Inject(self,injector):\n # Inject constant source of wind mass & energy (as pure KE)\n dt = integrator.Integrator().dt\n injector.AddMass(self._massloss*dt)\n injector.AddKE(self._lum*dt)\n integrator.Integrator().CourantLimiter(self._vcourant)","def __init__(self,\n debug=False,\n urdf_version=None,\n control_time_step=0.005,\n action_repeat=5,\n control_latency=0,\n pd_latency=0,\n on_rack=False,\n motor_kp=1.0,\n motor_kd=0.02,\n render=False,\n num_steps_to_log=2000,\n env_randomizer=None,\n log_path=None,\n signal_type='ik',\n target_position=None,\n backwards=None,\n gait_type='trot',\n terrain_type='plane',\n terrain_id='plane',\n mark='base',\n ):\n self.phase = 0\n\n self._gait_type = gait_type \n # for observation space bounding \n self.max_speed = 1.0\n self.min_speed = 0.5 # change back to 0.2 for OLD TD3 model evaluation\n \n self.min_side_speed = 0.0\n self.max_side_speed = 0.0\n\n self.speed = np.random.uniform(self.min_speed, self.max_speed)\n self.side_speed = np.random.uniform(self.min_side_speed, self.max_side_speed)\n self.speed_des = [self.speed, self.side_speed]\n\n # Initialization variables for periodic reward sum composition\n self.theta_FL = phase_constants.PHASE_VALS[self._gait_type]['front_left']\n self.theta_FR = phase_constants.PHASE_VALS[self._gait_type]['front_right']\n self.theta_RL = phase_constants.PHASE_VALS[self._gait_type]['rear_left']\n self.theta_RR = phase_constants.PHASE_VALS[self._gait_type]['rear_right']\n\n self.min_swing_ratio = 0.6\n self.max_swing_ratio = 0.8\n self.ratio = np.random.uniform(self.min_swing_ratio, self.max_swing_ratio)\n\n super(rexPeriodicRewardEnv,\n self).__init__(urdf_version=urdf_version,\n accurate_motor_model_enabled=True,\n motor_overheat_protection=False,\n motor_kp=motor_kp,\n motor_kd=motor_kd,\n remove_default_joint_damping=False,\n control_latency=control_latency,\n pd_latency=pd_latency,\n on_rack=on_rack,\n render=render,\n num_steps_to_log=num_steps_to_log,\n env_randomizer=env_randomizer,\n log_path=log_path,\n control_time_step=control_time_step,\n action_repeat=action_repeat,\n target_position=target_position,\n signal_type=signal_type,\n backwards=backwards,\n debug=debug,\n terrain_id=terrain_id,\n terrain_type=terrain_type,\n mark=mark,\n ratio=self.ratio,\n forward_reward_cap=5\n )\n\n self.height_des = 0.206 # this is init standing height for rex\n\n self.cycle_complete = 0\n self.cycle_len = 1000 # this is L\n \n # vonmises variables\n self.kappa = phase_constants.VON_MISES_KAPPA\n\n rex_joints = p.getNumJoints(bodyUniqueId=self.rex.quadruped)\n link_name_to_ID = {}\n for i in range(rex_joints):\n name = p.getJointInfo(self.rex.quadruped, i)[12].decode('UTF-8')\n link_name_to_ID[name] = i\n\n self.link_name_to_ID = link_name_to_ID\n self.toe_pos_last = { 'front_left_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['front_left_toe_link'])[0],\n 'front_right_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['front_right_toe_link'])[0],\n 'rear_left_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['rear_left_toe_link'])[0],\n 'rear_right_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['rear_right_toe_link'])[0]\n\n } \n\n print('Using Periodic Reward Composition Rex Environment')","def main():\n geom = dde.geometry.TimeDomain(0, 3)\n y0 = initial_condition()\n for i in range(0,C)\n # ic3 = dde.IC(geom, lambda X: 27, boundary, component=5)\n data = dde.data.PDE(\n geom,\n SLE_DL,\n [ic1, ic2, ic3, observe_y0, observe_y1, observe_y2],\n num_domain=400,\n num_boundary=2,\n anchors=observe_t,\n )","def init_servos():\n for i in range(0, 7):\n kit.servo[i].actuation_range = 180\n kit.servo[i].set_pulse_width_range(450, 2550)","def Inject(self,injector):\r\n\r\n # Calculate the star's current age\r\n integrator = weltgeist.integrator.Integrator()\r\n t = integrator.time\r\n dt = integrator.dt\r\n age = t-self._tbirth\r\n Teff = 0.0\r\n star = self._star\r\n\r\n # If it's been born, start the tracks\r\n if age > 0.0:\r\n if self._wind:\r\n # Get mass loss and energy from winds\r\n ml0 = star.WindMassLoss(age)\r\n lum0 = star.WindLuminosity(age)\r\n massloss = 0.5*(ml0+star.WindMassLoss(age+dt))*dt\r\n energy = 0.5*(lum0+star.WindLuminosity(age+dt))*dt\r\n # Add mass FIRST since KE needs to be added elastically\r\n injector.AddMass(massloss)\r\n # Add energy to grid as kinetic energy\r\n injector.AddKE(energy)\r\n # Add some thermal energy to account for star's temperature\r\n Teff = 0.5*(star.Teff(age)+star.Teff(age+dt))\r\n TE = 1.5 * wunits.kB * massloss/(wunits.mH/wunits.X)*Teff\r\n injector.AddTE(TE)\r\n # Set the Courant condition\r\n vwind = np.sqrt(2.0*lum0/ml0)\r\n integrator.CourantLimiter(vwind)\r\n if self._radiation:\r\n # Get radiation properties for ionising and non-ionising UV\r\n Lionising = 0.5*(star.LIonising(age)+star.LIonising(age+dt))\r\n Lnonionising = 0.5*(star.LNonIonising(age)+star.LNonIonising(age+dt))\r\n Eionising = 0.5*(star.EPhoton(age)+star.EPhoton(age+dt)) \r\n Teff = 0.5*(star.Teff(age)+star.Teff(age+dt)) \r\n Tion = weltgeist.radiation.IonisedGasTemperature(Teff, self._metal)\r\n injector.AddPhotons(Lionising, Lnonionising, Eionising, Tion)","def _setup_simulation(self\n ) -> None:\n pass","def simulationTwoDrugsDelayedTreatment():\n\n # TODO","def set_up_and_parameterise_experiment(self):\n # Update experiment using capacity\n capacity = self._parameter_values[\"Nominal cell capacity [A.h]\"]\n for op_conds in self.experiment.operating_conditions_steps:\n if op_conds.type == \"C-rate\":\n op_conds.type = \"current\"\n op_conds.value = op_conds.value * capacity\n\n # Update terminations\n termination = op_conds.termination\n for term in termination:\n term_type = term[\"type\"]\n if term_type == \"C-rate\":\n # Change type to current\n term[\"type\"] = \"current\"\n # Scale C-rate with capacity to obtain current\n term[\"value\"] = term[\"value\"] * capacity\n\n # Add time to the experiment times\n dt = op_conds.duration\n if dt is None:\n if op_conds.type == \"current\":\n # Current control: max simulation time: 3h / C-rate\n Crate = op_conds.value / capacity\n dt = 3 / abs(Crate) * 3600 # seconds\n else:\n # max simulation time: 1 day\n dt = 24 * 3600 # seconds\n op_conds.duration = dt\n\n # Set up model for experiment\n self.set_up_and_parameterise_model_for_experiment()","def simulation(self, pvmod=True):\r\n \r\n self.Real.Ppv2ac_out, self.Real.Ppv2bat_in, self.Real.Ppv2bat_in0, self.Real.Pbat2ac_out, self.Real.Pbat2ac_out0, self.Real.Ppvbs, self.Real.Pbat, self.Real.soc, self.Real.soc0 = batmod_dc(\r\n self.d, self.dt, self.Real.soc0, self.Real.soc, self.Real.Pr, self.Real.Prpv, self.Real.Ppv, self.Real.Ppv2bat_in0, self.Real.Ppv2bat_in,\r\n self.Real.Pbat2ac_out0, self.Real.Pbat2ac_out, self.Real.Ppv2ac_out, self.Real.Ppvbs, self.Real.Pbat)\r\n\r\n self.Ideal.Pbat, self.Ideal.soc, self.Ideal.soc0 = batmod_dc_ideal(self.d, self.dt, self.Ideal.soc0, self.Ideal.soc, self.Ideal.Pr, self.Ideal.Pbat)\r\n\r\n # Define missing parameters\r\n self.Real.Ppv2ac = self.Real.Ppv2ac_out # AC output power of the PV2AC conversion pathway\r\n self.Real.Ppv2bat = self.Real.Ppv2bat_in # DC input power of the PV2BAT conversion pathway\r\n\r\n self.Ideal.Ppvbs = self.Ideal.Ppv - np.maximum(0, self.Ideal.Pbat) - (np.minimum(0, self.Ideal.Pbat)) # Realized AC power of the PV-battery system\r\n self.Ideal.Ppv2ac = self.Ideal.Ppv - np.maximum(0, self.Ideal.Pbat) # AC output power of the PV2AC conversion pathway\r\n self.Ideal.Ppv2bat = np.maximum(0, self.Ideal.Pbat) # DC input power of the PV2BAT conversion pathway\r\n\r\n print()","def run(self):\n\n # initializing random network activity\n s_rand_T = np.zeros((self.T, self.N_rand))\n p_rand_T = np.zeros((self.T, self.N_rand))\n r_rand_T = np.zeros((self.T, self.N_rand))\n\n s_rand_T[0, :] = np.random.uniform(low=0, high=0.01, size=(self.N_rand))\n\n # initializing sensory networks\n s_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\n p_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\n r_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\n s_sens_T[0, :] = np.random.uniform(low=0, high=0.01, size=(self.N_sensory_nets * self.N_sensory))\n\n # extend input to be T timesteps and only nonzero for 100 ts\n s_ext_T = np.broadcast_to(self.s_ext, (self.T, self.N_sensory * self.N_sensory_nets)).copy()\n # stimulus is presented for 100 ms\n stim_T = int(200/self.rand_net.dt)\n s_ext_T[:100] = 0\n s_ext_T[100+stim_T:] = 0\n # s_ext_T *= 0\n\n for t in range(1, self.T):\n if (t + 1) % 100 == 0:\n print(f'step {t} of {self.T}')\n s_sens_prev = s_sens_T[t - 1]\n s_rand_prev = s_rand_T[t - 1]\n p_rand_prev = p_rand_T[t - 1]\n s_ext = s_ext_T[t - 1]\n step = self.forward(s_ext=s_ext, s_rand_prev=s_rand_prev, s_sens_prev=s_sens_prev, p_rand_prev=p_rand_prev)\n s_sens_T[t] = step['s_sens']\n p_sens_T[t] = step['p_sens']\n r_sens_T[t] = step['r_sens']\n s_rand_T[t] = step['s_rand']\n r_rand_T[t] = step['r_rand']\n p_rand_T[t] = step['p_rand']\n\n p_sens_T = p_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\n s_ext_T = s_ext_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\n r_sens_T = r_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\n s_sens_T = s_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\n\n return dict(\n n_sensory=self.N_sensory,\n n_rand=self.N_rand,\n mus=self.mus,\n sigma=self.sigma,\n s_ext=s_ext_T,\n s_sens=s_sens_T,\n r_sens=r_sens_T,\n p_sens=p_sens_T,\n s_rand=s_rand_T,\n r_rand=r_rand_T,\n p_rand=p_rand_T\n )","def setup_simulation(self, **kwargs):\n\n self.distance = self.config[\"site\"][\"distance\"]\n self.num_substations = self.config[\"num_substations\"]\n\n self.initialize_substructure_production()\n self.initialize_installation_vessel()","def __init__(self, services, config):\n #pytau.setNode(1)\n #timer = pytau.profileTimer(\"component.__init__\", \"\", str(os.getpid()))\n #pytau.start(timer)\n self.component_id = None\n self.invocation_q = None\n self.services = weakref.proxy(services)\n self.config = config\n self.start_time=0.0\n self.sys_exit = None\n for i in config.keys():\n try:\n setattr(self, i, config[i])\n except Exception, e:\n print 'Error setting Component parameter : ', i, ' - ', e\n #pytau.stop(timer)\n raise\n\n #pytau.stop(timer)","def __init__(self, n): # this is equivalent to starting a random one\n self.n = n\n # From table S1 in the supplemental materials\n # each c parameters is [body,limb]\n self.cv0 = [0.3, 0.0]\n self.cv1 = [0.2, 0.2]\n self.cR0 = [0.196,0.131]\n self.cR1 = [0.065,0.131]\n #[[dbodylow,dbodyhigh],[dlimblow,dlimbhigh]]\n self.d_params = [[1,5],[1,3]]\n # which oscillators are limb oscillators and which ones are body oscillators is pretty constant\n n_body = n - 4\n self.osc_class = [0 if i < n_body else 1 for i in range(self.n)] # 0 for body oscillator, 1 for limb oscillator\n # list of keys that can be mutated during evolution\n self.evolvables = ['w', 'phi', 'a', 'gsl', 'gsh', 'gb1', 'gb2', 'theta', 'ampl', 'ampl_dot']\n self.scalars = set(['gsl', 'gsh', 'gb1', 'gb2'])\n self.nonzeros = set([int(i) for i in \"8 160 29 181 50 202 71 223 92 244 113 265 134 286 155 307 1 20 22 41 43 62 64 83 85 104 106 125 127 146 169 188 190 209 211 230 232 251 253 272 274 293 295 314 320 321 322 323 364 365 366 367 348 349 350 351 392 393 394 395 338 376 337 356 359 397 379 398\".split(\" \")])\n self.shapes = {'w':n*n,\n 'phi':n*n,\n 'a':n,\n 'theta':n,\n 'ampl':n,\n 'ampl_dot':n}\n self.sizes = {'w':n*n,\n 'phi':n*n,\n 'a':n,\n 'theta':n,\n 'ampl':n,\n 'ampl_dot':n}","def set_up_orbit_correctors(ps_beg, delay, id_slice1, ds_slice, zplot, id_slices, U_core, lambdaref):\n SXSS = Chicane(3.2716, 0.362, 0.830399, delay[0])\n HXSS = Chicane(3.2, 0.3636, 0.5828, delay[1])\n\n OC2 = [CORR08, D1_SXSS, SXSS, D2_SXSS, QUAD09, CORR09]\n OC3 = [CORR15, D1_HXSS, HXSS, D2_HXSS, QUAD16, CORR16]\n\n ps_end1 = beam_transportation(ps_beg, U_core[0])\n\n # ps_end1 is a 4-by-N array. N is the number of macro-particles. It is the full\n # 4D phase space distribution at the end of the first undulator section.\n\n # The id of the slice on the axis in the second undulator section\n on_axis_id_U2 = int(id_slice1+delay[0]/ds_slice+ (8*110)*lambdaref/ds_slice) # The last part is slippage\n\n print(on_axis_id_U2)\n\n ps_end_slice1 = beam_property_along_s(ps_end1, id_slices)[0:4, :]\n ps_on_axis_2 = np.ravel(ps_end_slice1[:, on_axis_id_U2])\n\n # print(ps_on_axis_2)\n\n OC2_optimized = analyze_orbit_corrector(OC2[0], OC2[-1], OC2[1:-1], ps_on_axis_2)\n print(OC2_optimized)\n CORR08_new = Orbit_Corrector(OC2[0].length, OC2_optimized[0], OC2_optimized[2])\n CORR09_new = Orbit_Corrector(OC2[-1].length, OC2_optimized[1], OC2_optimized[3])\n\n # The whole U2 with optimized orbit correctors\n U2_new = [CORR08_new] + OC2[1:-1] + [CORR09_new] + U_core[1]\n ps_end2 = beam_transportation(ps_end1, U2_new)\n\n # ps_end2 is a 4-by-N array. N is the number of macro-particles. It is the full\n # 4D phase space distribution at the end of the second undulator section.\n\n # The id of the slice on the axis in the third undulator section\n on_axis_id_U3 = int(id_slice1+(delay[0]+delay[1])/ds_slice +(14*110*lambdaref)/ds_slice) # The last term is the slipage\n\n print(on_axis_id_U3)\n\n ps_end_slice2 = beam_property_along_s(ps_end2, id_slices)[0:4, :]\n ps_on_axis_3 = np.ravel(ps_end_slice2[ :, on_axis_id_U3])\n\n # print(ps_on_axis_3)\n\n OC3_optimized = analyze_orbit_corrector(OC3[0], OC3[-1], OC3[1:-1], ps_on_axis_3)\n print(OC3_optimized)\n CORR15_new = Orbit_Corrector(OC3[0].length, OC3_optimized[0], OC3_optimized[2])\n CORR16_new = Orbit_Corrector(OC3[-1].length, OC3_optimized[1], OC3_optimized[3])\n\n U3_new = [CORR15_new] + OC3[1:-1] + [CORR16_new] + U_core[2]\n\n Undulator_Beamline = U_core[0]+U2_new+U3_new\n\n return Undulator_Beamline","def Inject(self,injector):\n dt = integrator.Integrator().dt\n injector.AddPhotons(self._QH*dt)","def setup(self):\n super().setup()\n\n # prepare scratch directory\n unix.mkdir(PATH.ORTHO)\n\n # get data file names from solver\n solver = sys.modules['seisflows_solver']\n\n nevt = PAR.NEVT # number of encoded sources\n ntpss = PAR.NTPSS # number of timesteps after steady state\n dt = PAR.DT # total number of timesteps\n nrec = PAR.NREC # number of stations\n # ntrace = len(solver.data_filenames)\n freq_min = float(PAR.FREQ_MIN) # minimium frequency of interest\n freq_max = float(PAR.FREQ_MAX) # maximium frequency of interest\n \n #create a mask on relevant frequencies\n freq_full = fftfreq(ntpss, dt) # full frequency compunent\n freq_thresh = 1 / (ntpss * dt) / 200 # threshold for frequency alignment\n freq_idx = np.squeeze(np.where((freq_min <= (freq_full)) & ((freq_full) < freq_max - freq_thresh))) # frequency band of interest\n freq = freq_full[freq_idx] # index of frequencies within the frequency band\n nfreq = len(freq_idx) # number of frequency within the frequency band\n print('Number of frequencies considered: ' +str(nfreq)+' / '+str(len(freq_full)))\n\n # converts time data to Fourier domain\n sff_obs = np.zeros((nfreq, nevt), dtype=complex) # fourier transform of observed source time function\n ft_obs = np.zeros((nfreq, nevt, nrec), dtype=complex) # TODO ntrace fourier transform of observed seismogram\n\n for isrc in range(nevt):\n source_name = solver.source_names_all[isrc] # name of source\n stf_file = solver.stf_files_all[isrc] # name of source file\n with open(stf_file) as f:\n lines = f.readlines()\n stf_obs = []\n for line in lines:\n stf_obs.append(float(line.split()[1]))\n\n sff_obs[:, isrc] = fft(stf_obs, n=ntpss)[freq_idx]\n # for itrace in range(ntrace):\n # trace = self.reader(PATH.DATA + '/' + source_name, solver.data_filenames[itrace])\n # for irec in range(nrec):\n # ft_obs[:, isrc, irec, itrace] = fft(trace[irec].data, n=ntpss)[freq_idx]\n for irec in range(nrec):\n trace = self.reader(PATH.DATA + '/' + source_name, solver.data_filenames[0])\n ft_obs[:, isrc, irec] = fft(trace[irec].data, n=ntpss)[freq_idx]\n \n self.save('freq_idx', freq_idx)\n self.save('freq', freq)\n self.save('sff_obs', sff_obs)\n self.save('ft_obs', ft_obs)","def test_config():\n import yaml\n import astropy.units as u\n from tqdm import tqdm\n # Need these for `eval` below\n from numpy import array\n\n # Same test suite as used in test_imsim above.\n # This time, we just use this for the det names.\n with open(DATA_DIR / \"wcs_466749.yaml\", 'r') as f:\n wcss = yaml.safe_load(f)\n\n cmds = {}\n with open(DATA_DIR / \"phosim_cat_466749.txt\", 'r') as f:\n for line in f:\n k, v = line.split()\n try:\n v = int(v)\n except ValueError:\n try:\n v = float(v)\n except ValueError:\n pass\n cmds[k] = v\n\n # Values below (and others) from phosim_cat_466749.txt\n rc = cmds['rightascension']\n dc = cmds['declination']\n boresight = galsim.CelestialCoord(\n rc*galsim.degrees,\n dc*galsim.degrees\n )\n obstime = Time(cmds['mjd'], format='mjd', scale='utc')\n obstime -= 15*u.s\n band = \"ugrizy\"[cmds['filter']]\n wavelength_dict = dict(\n u=365.49,\n g=480.03,\n r=622.20,\n i=754.06,\n z=868.21,\n y=991.66\n )\n wavelength = wavelength_dict[band]\n camera = imsim.get_camera()\n\n rotTelPos = cmds['rottelpos'] * galsim.degrees\n telescope = imsim.load_telescope(f\"LSST_{band}.yaml\", rotTelPos=rotTelPos)\n # Non-default values.\n temperature = 293.\n pressure = 69.0\n H2O_pressure = 2.0\n\n factory = imsim.BatoidWCSFactory(\n boresight, obstime, telescope, wavelength,\n camera,\n temperature=temperature,\n pressure=pressure,\n H2O_pressure=H2O_pressure\n )\n\n config = {\n 'input': {\n 'telescope': {\n 'file_name':f\"LSST_{band}.yaml\",\n 'rotTelPos': rotTelPos\n }\n },\n 'image': {\n 'wcs': {\n 'type': 'Batoid',\n 'boresight': boresight,\n 'camera': 'LsstCam',\n 'obstime': obstime,\n 'wavelength': wavelength,\n 'temperature': temperature,\n 'pressure': pressure,\n 'H2O_pressure': H2O_pressure,\n 'order': 2,\n }\n }\n }\n\n rng = np.random.default_rng(1234)\n for k in tqdm(wcss.keys()):\n name = k[18:25].replace('-', '_')\n det = camera[name]\n\n wcs1 = factory.getWCS(det, order=2)\n config['image']['wcs']['det_name'] = name\n galsim.config.RemoveCurrent(config['image']['wcs'])\n galsim.config.ProcessInput(config)\n wcs2 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n\n # Test points\n xs = rng.uniform(0, 4000, 100)\n ys = rng.uniform(0, 4000, 100)\n ra1, dec1 = wcs1.xyToradec(xs, ys, units='radians')\n ra2, dec2 = wcs2.xyToradec(xs, ys, units='radians')\n np.testing.assert_allclose(ra1, ra2)\n np.testing.assert_allclose(dec1, dec2)\n\n # Test == when identical\n galsim.config.RemoveCurrent(config['image']['wcs'])\n wcs3 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n assert wcs3 == wcs2\n\n # Test that pressure and temperature matter.\n config['image']['wcs']['temperature'] = 250\n galsim.config.RemoveCurrent(config['image']['wcs'])\n wcs4 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n assert wcs4 != wcs2\n\n config['image']['wcs']['temperature'] = temperature\n config['image']['wcs']['pressure'] = 55\n galsim.config.RemoveCurrent(config['image']['wcs'])\n wcs5 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n assert wcs5 != wcs2\n\n config['image']['wcs']['pressure'] = pressure\n config['image']['wcs']['H2O_pressure'] = 10\n galsim.config.RemoveCurrent(config['image']['wcs'])\n wcs6 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n assert wcs6 != wcs2\n\n # Test defaults\n del config['image']['wcs']['temperature']\n del config['image']['wcs']['pressure']\n del config['image']['wcs']['H2O_pressure']\n galsim.config.RemoveCurrent(config['image']['wcs'])\n config = galsim.config.CleanConfig(config)\n galsim.config.ProcessInput(config)\n wcs7 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n default_pressure = 101.325 * (1-2.25577e-5*2715)**5.25588\n wcs7a = imsim.BatoidWCSFactory(\n boresight, obstime, telescope, wavelength, camera,\n temperature=280,\n pressure=default_pressure,\n H2O_pressure=1.0,\n ).getWCS(det, order=2)\n assert wcs7 == wcs7a\n\n # Default wavelength from bandpass\n del config['image']['wcs']['wavelength']\n config['bandpass'] = imsim.RubinBandpass('r')\n galsim.config.RemoveCurrent(config['image']['wcs'])\n config = galsim.config.CleanConfig(config)\n galsim.config.ProcessInput(config)\n wcs8 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n wcs8a = imsim.BatoidWCSFactory(\n boresight, obstime, telescope,\n wavelength=config['bandpass'].effective_wavelength,\n camera=camera,\n temperature=280,\n pressure=default_pressure,\n H2O_pressure=1.0,\n ).getWCS(det, order=2)\n assert wcs8 == wcs8a\n\n del config['bandpass']\n config['image']['bandpass'] = {\n 'type': 'RubinBandpass',\n 'band' : 'r',\n }\n galsim.config.RemoveCurrent(config['image']['wcs'])\n config = galsim.config.CleanConfig(config)\n galsim.config.ProcessInput(config)\n wcs8b = galsim.config.BuildWCS(config['image'], 'wcs', config)\n assert wcs8b == wcs8a\n\n # Obstime can be a string\n print('obstime = ',obstime.to_value('iso'), type(obstime.to_value('iso')))\n config['image']['wcs']['obstime'] = obstime.to_value('iso')\n # Doesn't quite roundtrip perfectly. But within a millisecond.\n obstime = Time(obstime.to_value('iso'), scale='tai')\n print('obstime => ',obstime)\n galsim.config.RemoveCurrent(config['image']['wcs'])\n config = galsim.config.CleanConfig(config)\n galsim.config.ProcessInput(config)\n wcs9 = galsim.config.BuildWCS(config['image'], 'wcs', config)\n wcs9a = imsim.BatoidWCSFactory(\n boresight, obstime, telescope,\n wavelength=config['bandpass'].effective_wavelength,\n camera=camera,\n temperature=280,\n pressure=default_pressure,\n H2O_pressure=1.0,\n ).getWCS(det, order=2)\n assert wcs9 == wcs9a","def initialise_variables(n_action, n_pc):\n y_action_neurons = np.zeros((n_action,1))\n \n n_neurons = n_pc+n_action\n \n epsp_rise = np.zeros((n_neurons, n_action))\n epsp_decay = np.zeros((n_neurons, n_action))\n epsp_tot = np.zeros((n_neurons, n_action))\n \n action_firing_rate = np.zeros((n_action,1))\n action_firing_rise = np.zeros((n_action,1))\n action_firing_decay = np.zeros((n_action,1))\n \n canc = np.ones((1, n_action))\n \n last_post_spike = np.zeros((n_action,1)) - 1000 # last spike time of postsynaptic neuron \n trace_pre_post = np.zeros((n_action, n_pc))\n trace_post_pre = np.zeros((n_action, n_pc))\n trace_tot = np.zeros((n_action, n_pc))\n eligibility_trace = np.zeros((n_action, n_pc))\n \n return y_action_neurons, canc, \\\n epsp_rise, epsp_decay, epsp_tot, \\\n action_firing_rate, action_firing_decay, action_firing_rise, \\\n last_post_spike, trace_pre_post, trace_post_pre, trace_tot, eligibility_trace","def setup_pwn(name,pwndata,phase, free_radius=5, tempdir=None, emin=1.0e2, emax=1.0e5,maxroi=10,model=None,**kwargs):\n sources=yaml.load(open(pwndata))\n\n catalog_name=sources[name]['catalog']\n ltcube=sources[name]['ltcube']\n pulsar_position=SkyDir(*sources[name]['dir'])\n ft2=sources[name]['ft2']\n ft1=sources[name]['ft1']\n\n # in case no list was passed\n if len(phase)==2 and isinstance(phase[0],numbers.Real) and \\\n isinstance(phase[1],numbers.Real):\n\n # write in case phase wraps around.\n if phase[0]>phase[1]:\n phase=[[phase[0],1.0],[0.0,phase[1]]]\n else:\n phase = [phase] \n\n phase_factor=get_phase_factor(phase)\n print \"phase\"\n print phase\n print \"phase_factor=%.2f\"%phase_factor\n\n catalog=FermiCatalog(e(\"$FERMI/catalogs/gll_psc_v02.fit\"),free_radius=free_radius)\n catalog_source=[i for i in catalog.get_sources(SkyDir(),180) if i.name==catalog_name][0]\n\n center=catalog_source.skydir\n\n if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')\n\n binfile=j(tempdir,'binned_phased.fits')\n\n # apply phase cut to ft1 file\n phased_ft1 = j(tempdir,'ft1_phased.fits')\n phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase)\n\n # create a temporary ltcube scaled by the phase factor\n# phased_ltcube=j(tempdir,'phased_ltcube.fits')\n# phase_ltcube(ltcube,phased_ltcube, phase=phase)\n phased_ltcube=ltcube\n from uw.like.pointspec import DataSpecification\n data_specification = DataSpecification(\n ft1files = phased_ft1,\n ft2files = ft2,\n ltcube = phased_ltcube,\n binfile = binfile)\n\n spectral_analysis = SpectralAnalysis(data_specification,\n binsperdec = 4,\n emin = 100,\n emax = 100000,\n irf = \"P6_V3_DIFFUSE\",\n roi_dir = center,\n maxROI = maxroi,\n minROI = maxroi)\n\n if model == None :\n roi=spectral_analysis.roi(\n roi_dir=center,\n diffuse_sources=get_default_diffuse(diffdir=e(\"$FERMI/diffuse\"),\n gfile=\"gll_iem_v02.fit\",\n ifile=\"isotropic_iem_v02.txt\"),\n catalogs = catalog,\n phase_factor = 1.0,\n fit_emin = [emin,emin],\n fit_emax = [emax,emax],\n **kwargs)\n else :\n roi=spectral_analysis.roi(\n roi_dir=center,\n xmlfile = model,\n phase_factor =1.0,\n fit_emin = [emin,emin],\n fit_emax = [emax,emax],\n **kwargs)\n\n print \"---------------------Energy range--------------------\"\n \n print \"emin=\"+str(roi.bands[0].emin)+\"\\n\"\n print \"emax=\"+str(roi.bands[len(roi.bands)-1].emax)+\"\\n\"\n \n\n # keep overall flux of catalog source,\n # but change the starting index to 2.\n roi.modify(which=catalog_name, name=name, index=2, \n keep_old_flux=True)\n\n return roi","def __init__(self, config):\n self.config = config\n self.observation_space = spaces.Box(\n low=np.array([-15, -15, -15, -15, -15]),\n high=np.array([15, 15, 15, 15, 15])\n )\n self.action_space = spaces.Box(\n low=np.array([0, 0]),\n high=np.array([15, 5])\n )\n if config[\"backend\"] == \"EH\":\n self.params = {\n \"a_1\": 1,\n \"b_1\": 3,\n \"c_1\": 1,\n \"d_1\": 5,\n \"I_ext1\": 3.1,\n \"m\": 0,\n \"a_2\": 6,\n \"tau_2\": 10,\n \"I_ext2\": .45,\n \"gamma\": .01,\n \"r\": .00035,\n \"s\": 4,\n \"x0\": -1.6,\n }\n self.sim = EHSim()\n else:\n self.params = {\n \"x0\": -1.6,\n \"y0\": 1,\n \"tau0\": 2857,\n \"tau1\": 1,\n \"tau2\": 10,\n \"I_rst1\": 3.1,\n \"I_rst2\": .45,\n \"gamma\": .01,\n }\n self.sim = JSim()\n self.x1 = 0\n self.y1 = -5\n self.z = 5.5\n self.x2 = 0\n self.y2 = 0\n self.frame = 0\n self.curr_stim = []\n self.reset()\n self.history = list()","def sequencePreparation(self):\n #Calculation of the number of frames in function of the duration + LED list for the acquisition\n if self.seqMode == \"rgbMode\":\n self._rgbSequenceInit()\n elif self.seqMode == 'rbMode':\n self._rbSequenceInit()\n else:\n print('Please select a valid mode of led sequence initialization')\n #Sending nb of frames to initialize the progress bar\n if type(self.nbFrames) == int:\n self.nbFramesSig.emit(self.nbFrames)\n\n print('acquisition Side : ', self.expRatio)\n #Saving the configuration of the experiment file (.json)\n self.savePath = cfgFileSaving(self.experimentName,\n self.nbFrames,\n self.duration,\n self.expRatio,\n self.acquMode,\n self.seqMode,\n self.rgbLedRatio,\n self.greenFrameInterval,\n round(1/self.cycleTime,2), #framerate\n self.folderPath,\n self.colorMode,\n self.mmc,\n 'Zyla') #WARNING > modulabilty (there is a way to get device label but it's not so easy)\n\n #initialization of the acquisition saving files : .tif (frames) and .txt (metadata)\n (self.tiffWriterList, self.textFile) = filesInit( self.savePath,\n self.experimentName,\n self.nbFrames,\n self.maxFrames)\n #send all informations to each LED driver\n self.arduinoSync()","def load_params(self, event):\n \n self.robot_type = rospy.get_param(\"robot_type\" , 'pendulum' )\n self.robot_config = rospy.get_param(\"robot_config\", 'wrist-only' )\n self.robot_ctl = rospy.get_param(\"controller\", 'RfixCTC' )\n self.fixed_mode = rospy.get_param(\"fixed_mode\", 1 )\n \n \n ###############################################\n # Load robot model for the right configuration\n if self.robot_config == 'wrist-only':\n self.R = Proto.SingleRevoluteDSDM()\n \n elif self.robot_config == 'dual-plane' :\n self.R = Proto.TwoPlanarSerialDSDM()\n \n else:\n self.R = None\n \n ###############################################\n # Load controller\n if self.robot_ctl == 'RfixCTC' :\n self.Ctl = RminCTC.RfixComputedTorqueController( self.R , self.fixed_mode )\n \n elif self.robot_ctl == 'RminCTC' :\n self.Ctl = RminCTC.RminComputedTorqueController( self.R )\n \n elif self.robot_ctl == 'RfixSLD' :\n self.Ctl = RminCTC.RfixSlidingModeController( self.R , self.fixed_mode )\n \n elif self.robot_ctl == 'RminSLD' :\n self.Ctl = RminCTC.RminSlidingModeController( self.R )\n \n elif self.robot_ctl == 'RollCTC' :\n self.Ctl = RollCTC.RolloutComputedTorqueController( self.R )\n \n elif self.robot_ctl == 'RollSLD' :\n self.Ctl = RollCTC.RolloutSlidingModeController( self.R )\n \n else:\n self.Ctl = None\n \n \n if self.robot_config == 'wrist-only':\n self.Ctl.n_gears = rospy.get_param(\"n_gears\", 2 )\n self.x_d = np.array( rospy.get_param(\"goal\", [0,0] ) )\n \n elif self.robot_config == 'dual-plane' :\n self.Ctl.n_gears = rospy.get_param(\"n_gears\", 4 )\n self.x_d = np.array( rospy.get_param(\"goal\", [0.0,0.0,0.0,0.0] ) )\n #self.x_d = np.array( [-3.14 , 0 , 0 , 0] )\n \n # Gen ctl params\n self.Ctl.hysteresis = rospy.get_param(\"hysteresis\", True )\n self.Ctl.min_delay = rospy.get_param(\"min_delay\", 0.5 )\n \n self.Ctl.w0 = rospy.get_param(\"w0\", 1 )\n self.Ctl.zeta = rospy.get_param(\"zeta\", 0.7 )\n \n self.Ctl.lam = rospy.get_param(\"lam\", 1 )\n self.Ctl.nab = rospy.get_param(\"nab\", 1 )\n self.Ctl.D = rospy.get_param(\"D\", 0 )\n \n self.Ctl.horizon = rospy.get_param(\"horizon\", 0.5 )\n self.Ctl.sim_dt = rospy.get_param(\"sim_dt\", 0.1 )\n \n self.Ctl.domain_check = rospy.get_param(\"domain_check\", False )\n \n # Base policy param for roll \n if self.robot_ctl == 'RollCTC' :\n self.Ctl.FixCtl.lam = self.Ctl.lam\n \n elif self.robot_ctl == 'RollSLD' :\n self.Ctl.FixCtl.lam = self.Ctl.lam \n self.Ctl.FixCtl.nab = self.Ctl.nab \n self.Ctl.FixCtl.D = self.Ctl.D","def sweep_timing(dir_out,box,channel,width,delay,scope,min_volt=None):\n print '____________________________'\n print width\n\n #fixed options\n height = 16383 \n fibre_delay = 0\n trigger_delay = 0\n pulse_number = 11100 \n #first select the correct channel and provide settings\n logical_channel = (box-1)*8 + channel\n \n sc.select_channel(logical_channel)\n sc.set_pulse_width(width)\n sc.set_pulse_height(16383)\n sc.set_pulse_number(pulse_number)\n sc.set_pulse_delay(delay)\n sc.set_fibre_delay(fibre_delay)\n sc.set_trigger_delay(trigger_delay)\n \n # first, run a single acquisition with a forced trigger, effectively to clear the waveform\n scope._connection.send(\"trigger:state ready\")\n time.sleep(0.1)\n scope._connection.send(\"trigger force\")\n time.sleep(0.1)\n\n # Get pin read\n time.sleep(0.1)\n sc.fire_sequence() # previously fire_sequence!\n #wait for the sequence to end\n tsleep = pulse_number * (delay*1e-3 + 210e-6)\n time.sleep(tsleep) #add the offset in\n sc.stop()\n\n # File system stuff\n check_dir(\"%s/raw_data/\" % (dir_out))\n directory = check_dir(\"%s/raw_data/Channel_%02d/\" % (dir_out,logical_channel))\n channels = [1,4]\n fnames = []\n fnames.append(\"%sPMTPulseWidth%05d\" % (directory,width))\n fnames.append(\"%sTriggerPulseWidth%05d\" % (directory,width))\n \n # Check scope\n ck = find_and_set_scope_y_scale(1,height,width,delay,scope,scaleGuess=min_volt)\n scope.set_edge_trigger(1.4, 4 , falling=False) # Rising edge trigger \n if ck == True:\n print \"Saving raw files to: %s and %s\" % (fnames[0],fnames[1])\n sc.fire_continuous()\n time.sleep(0.2)\n save_ck = save_scopeTraces_Multiple(fnames, scope, channels, 100)\n sc.stop()\n time.sleep(5)\n if save_ck == True:\n # Calc and return params\n xPMT,yPMT = calc.readPickleChannel(fnames[0], 1)\n xTrigger,yTrigger = calc.readPickleChannel(fnames[1], 1)\n meanJitter, JitterDev, JitterErrorOnMean = calc.calcJitter(xTrigger,yTrigger,xPMT,yPMT)\n return meanJitter, JitterErrorOnMean","def setUp(self):\n shape = RNG.integers(5, 50)\n periods = self.periods = RNG.normal() * 3\n freq = periods / shape\n amp = RNG.normal()\n offset = RNG.normal()\n phase = (RNG.normal() - 1 / 2) * 5 / 3 * np.pi\n p_gt = self.p_gt = (amp, freq, phase, offset)\n x = self.x = np.arange(shape)\n self.data = sine(x, *p_gt)","def __init__(self, **kwargs):\n\n # mod_path = os.path.join(os.path.dirname(a.__file__), 'BindingPMF.py')\n # print \"\"\"###########\n # # AlGDock #\n # ###########\n # Molecular docking with adaptively scaled alchemical interaction grids\n #\n # in {0}\n # last modified {1}\n # \"\"\".format(mod_path, time.ctime(os.path.getmtime(mod_path)))\n\n from AlGDock.argument_parser import SimulationArguments\n self.args = SimulationArguments(**kwargs)\n\n from AlGDock.simulation_data import SimulationData\n self.data = {}\n self.data['BC'] = SimulationData(self.args.dir['BC'], 'BC', \\\n self.args.params['CD']['pose'])\n self.data['CD'] = SimulationData(self.args.dir['CD'], 'CD', \\\n self.args.params['CD']['pose'])\n\n if not 'max_time' in kwargs.keys():\n kwargs['max_time'] = None\n if not 'run_type' in kwargs.keys():\n kwargs['run_type'] = None\n\n from AlGDock.logger import Logger\n self.log = Logger(self.args, \\\n max_time=kwargs['max_time'], run_type=kwargs['run_type'])\n\n self.T_HIGH = self.args.params['BC']['T_HIGH']\n self.T_TARGET = self.args.params['BC']['T_TARGET']\n\n self._setup()\n\n print '\\n*** Simulation parameters and constants ***'\n for p in ['BC', 'CD']:\n print '\\nfor %s:' % p\n print dictionary_tools.dict_view(self.args.params[p])[:-1]\n\n self.run(kwargs['run_type'])","def __init__(self, initScript = None): \n super(IdealPump, self).__init__(initScript)\n\n self.balance = Balance.Balance(Balance.MOLE_BALANCE | Balance.ENERGY_BALANCE)\n self.lastPIn = None\n self.lastPOut = None\n \n inPort = self.CreatePort(MAT|IN, IN_PORT)\n outPort = self.CreatePort(MAT|OUT, OUT_PORT)\n\n dpPort = self.CreatePort(SIG, DELTAP_PORT)\n dpPort.SetSignalType(DELTAP_VAR) \n \n qPort = self.CreatePort(ENE|IN, IN_PORT + 'Q')\n self.balance.AddInput((inPort, qPort))\n self.balance.AddOutput(outPort)\n\n self.SetParameterValue(ISENTROPIC_PAR, 1)","def __init__( self, interp, comm, dt, ptcl, v, p_nz, time,\n ux_m=0., uy_m=0., uz_m=0., ux_th=0., uy_th=0., uz_th=0.,\n gamma_boost=None ) :\n # Check that the boundaries are open\n if ((comm.rank == comm.size-1) and (comm.right_proc is not None)) \\\n or ((comm.rank == 0) and (comm.left_proc is not None)):\n raise ValueError('The simulation is using a moving window, but '\n 'the boundaries are periodic.\\n Please select open '\n 'boundaries when initializing the Simulation object.')\n\n # Momenta parameters\n self.ux_m = ux_m\n self.uy_m = uy_m\n self.uz_m = uz_m\n self.ux_th = ux_th\n self.uy_th = uy_th\n self.uz_th = uz_th\n\n # When running the simulation in boosted frame, convert the arguments\n if gamma_boost is not None:\n boost = BoostConverter( gamma_boost )\n self.uz_m, = boost.longitudinal_momentum([ self.uz_m ])\n\n # Attach moving window speed and period\n self.v = v\n\n # Get the positions of the global physical domain\n zmin_global_domain, zmax_global_domain = comm.get_zmin_zmax(\n local=False, with_damp=False, with_guard=False )\n\n # Attach reference position of moving window (only for the first proc)\n # (Determines by how many cells the window should be moved)\n if comm.rank == 0:\n self.zmin = zmin_global_domain\n\n # Attach injection position and speed (only for the last proc)\n if comm.rank == comm.size-1:\n self.v_end_plasma = \\\n c * self.uz_m / np.sqrt(1 + ux_m**2 + uy_m**2 + self.uz_m**2)\n # Initialize plasma *ahead* of the right *physical* boundary of\n # the box so, after `exchange_period` iterations\n # (without adding new plasma), there will still be plasma\n # inside the physical domain. ( +3 takes into account that 3 more\n # cells need to be filled w.r.t the left edge of the physical box\n # such that the last cell inside the box is always correct for\n # 1st and 3rd order shape factor particles after the moving window\n # shifted by exchange_period cells. )\n self.z_inject = zmax_global_domain + 3*comm.dz + \\\n comm.exchange_period * (v-self.v_end_plasma) * dt\n # Try to detect the position of the end of the plasma:\n # Find the maximal position of the particles which are\n # continously injected.\n self.z_end_plasma = None\n for species in ptcl:\n if species.continuous_injection and species.Ntot != 0:\n # Add half of the spacing between particles (the injection\n # function itself will add a half-spacing again)\n self.z_end_plasma = species.z.max() + 0.5*comm.dz/p_nz\n break\n # Default value in the absence of continuously-injected particles\n if self.z_end_plasma is None:\n self.z_end_plasma = zmax_global_domain\n self.nz_inject = 0\n self.p_nz = p_nz\n\n # Attach time of last move\n self.t_last_move = time - dt","def setup_simulation(system, pdb, integrator):\n #platform = Platform.getPlatformByName('CPU')\n platform = Platform.getPlatformByName('OpenCL')\n prop = {'OpenCLPrecision':'single'}\n \n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\n simulation.context.setPositions(pdb.positions)\n simulation.minimizeEnergy()\n simulation.context.setVelocitiesToTemperature(310*kelvin)\n print('Created simulation')\n return simulation","def simulationDelayedTreatment():\n\n delays = [300, 150, 75, 0]\n colors = [\"r\", \"b\", \"g\", \"y\"]\n nbrSim = 500\n \n patient = Patient(getViruses(100, 0.1, 0.05, {\"guttagonol\":False}, 0.05), 1000)\n \n for iter in range(len(delays)):\n print \"Simulation with \", delays[iter], \"delay\"\n totalPopulation = []\n for sim in range(0, nbrSim):\n for i in range (0, delays[iter]):\n patient.update()\n\n patient.addPrescription(\"guttagonol\")\n \n for i in range (0, 150):\n patient.update()\n \n totalPopulation.append(patient.update())\n \n histPopulation(totalPopulation, \"Delay: \" + str(delays[iter]), colors[iter])\n\n pylab.legend()\n pylab.show()","def setup(self):\n insts = []\n for i in range(5):\n insts.append(pysat.Instrument('pysat', 'testing',\n clean_level='clean'))\n self.testC = pysat.Constellation(instruments=insts)\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\n self.testC.bounds = self.bounds\n self.testI.bounds = self.bounds\n\n # Define variables for 1D testing\n self.one_d_vars = ['dummy1', 'dummy2', 'dummy3']\n self.unequal_one_d_vars = []\n\n return","def __init__(self, max_simsecs=30, net=None, noise_sd=0.01, quick=0):\n Sim.__init__(self, max_simsecs, noise_sd, quick)\n log.debug('init PoleBalance sim')\n self.network = net\n\n CART_POSITION = (0, 0, 2)\n POLE_POSITION = (0, 0, 3+(5.0/2))\n CART_SIZE = (8, 8, 2)\n POLE_SIZE = (1, 1, 5)\n HINGE_POSITION = (0, 0, 3)\n CART_MASS = 10\n POLE_MASS = 0.5\n self.MAXF = 1000\n\n self.INIT_U = [] # initial force, eg [10000]\n\n self.cart_geom = ode.GeomBox(self.space, CART_SIZE)\n self.geoms.append(self.cart_geom)\n self.cart_body = ode.Body(self.world)\n self.cart_body.setPosition(CART_POSITION)\n cart_mass = ode.Mass()\n cart_mass.setBoxTotal(CART_MASS, CART_SIZE[0], CART_SIZE[1], CART_SIZE[2])\n self.cart_body.setMass(cart_mass)\n self.cart_geom.setBody(self.cart_body)\n\n self.pole_geom = ode.GeomBox(self.space, POLE_SIZE)\n self.geoms.append(self.pole_geom)\n self.pole_body = ode.Body(self.world)\n self.pole_body.setPosition(POLE_POSITION)\n pole_mass = ode.Mass()\n pole_mass.setBoxTotal(POLE_MASS, POLE_SIZE[0], POLE_SIZE[1], POLE_SIZE[2])\n self.pole_body.setMass(pole_mass)\n self.pole_geom.setBody(self.pole_body)\n\n self.cart_geom.setCategoryBits(long(0))\n self.pole_geom.setCategoryBits(long(0))\n\n # joint 0 - slide along 1D\n self.slider_joint = ode.SliderJoint(self.world)\n self.joints.append(self.slider_joint)\n self.slider_joint.attach(self.cart_body, ode.environment)\n self.slider_joint.setAxis((1, 0, 0))\n self.slider_joint.setParam(ode.ParamLoStop, -5)\n self.slider_joint.setParam(ode.ParamHiStop, 5)\n\n # joint 1 - hinge between the two boxes\n self.hinge_joint = ode.HingeJoint(self.world)\n self.joints.append(self.hinge_joint)\n self.hinge_joint.attach(self.cart_body, self.pole_body)\n self.hinge_joint.setAnchor(HINGE_POSITION)\n self.hinge_joint.setAxis((0, 1, 0))\n\n self.last_hit = 0.0\n self.init_u_count = 0\n self.regular_random_force = 1\n self.lqr = None\n self.controlForce = 0\n self.randomForce = 0\n self.force_urge = 0","def __setup_parameters__(self):\r\n self.M=self.N+1\r\n self.u=1+self.pu\r\n self.d=1-self.pd\r\n self.qu=(math.exp((self.r-self.div)*self.dt)-self.d)/(self.u-self.d)\r\n self.qd=1-self.qu","def setup_simulation(system, pdb, integrator):\n #platform = Platform.getPlatformByName('CPU')\n platform = Platform.getPlatformByName('OpenCL')\n prop = {'OpenCLPrecision':'single'}\n\n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\n simulation.context.setPositions(pdb.positions)\n simulation.minimizeEnergy()\n simulation.context.setVelocitiesToTemperature(300*kelvin)\n print('Created simulation')\n return simulation","def setup(self):\n\n warnings.simplefilter(\"always\", DeprecationWarning)\n\n orbit_info = {'index': 'slt', 'kind': 'lt'}\n self.tinst = pysat.Instrument('pysat', 'testing', orbit_info=orbit_info)\n self.tinst.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 2))\n\n self.warn_msgs = []\n self.war = \"\"\n return","def robotInit(self):\n\n #Initialize Networktables\n self.sd = NetworkTables.getTable('SmartDashboard')\n\n \n #Set up motors to drive robot\n self.M2 = wpilib.VictorSP(2)\n self.M3 = wpilib.VictorSP(3)\n #self.M2.setInverted(True)\n #self.M3.setInverted(True)\n self.left = wpilib.SpeedControllerGroup(self.M2,self.M3)\n \n self.M0 = wpilib.VictorSP(0)\n self.M1 = wpilib.VictorSP(1)\n self.right = wpilib.SpeedControllerGroup(self.M0,self.M1)\n self.drive = wpilib.drive.DifferentialDrive(self.left, self.right)\n \n \n self.stick = wpilib.Joystick(1)\n self.timer = wpilib.Timer()\n #Camera\n wpilib.CameraServer.launch()\n #Servo\n self.SV1 = wpilib.Servo(9)\n self.SV2 = wpilib.Servo(8) \n #Dashboard\n NetworkTables.initialize(server='10.61.62.2')\n #Switches\n self.SW0 = wpilib.DigitalInput(0)\n self.SW1 = wpilib.DigitalInput(1)\n #Elevator\n self.E = wpilib.VictorSP(5)\n self.prepareCubeFlag = 0\n self.grabCubeFlag = 0\n self.deliverCubeFlag = 0\n self.adjustLeftFlag=0\n self.adjustRightFlag=0\n self.driveFlag=0\n #Gyro\n self.gyro = wpilib.ADXRS450_Gyro(0)\n self.gyro.reset()\n #All possible autonomous routines in a sendable chooser\n '''\n self.chooser = wpilib.SendableChooser()\n self.chooser.addDefault(\"None\", '4')\n self.chooser.addObject(\"left-LeftScale\", '1')\n self.chooser.addObject(\"Middle-LeftScale\", '2')\n self.chooser.addObject(\"Right-LeftScale\", '3')\n self.chooser.addObject(\"Left-RightScale\", '5')\n '''\n #wpilib.SmartDashboard.putData('Choice', self.chooser)\n #Encoders\n self.EC1 = wpilib.Encoder(2,3)\n self.EC2 = wpilib.Encoder(4,5)\n self.EC1.reset()\n self.EC2.reset()","def __init__ (self, sys='NULL',usett=False,usepcav=False,debug=False):\n if sys == 'XPP': # set up xpp system\n print('starting XPP')\n self.delay = 0.1 # 1 second delay\n pvname = 'XPP:TIMETOOL:TTALL' # time tool array name\n matlab_start = 20 # first matlab pv\n matlab_prefix = 'LAS:FS3:VIT:matlab:' # start of matlab names\n stagename = 'XPP:LAS:MMN:16' # delay stage for time tool\n ipmname = 'XPP:SB2:BMMON:SUM' # intensity profile monitor PV\n\n elif sys == 'CXI': # set up cxi system\n print('starting CXI')\n self.delay = 0.1 # 1 second delay\n pvname = 'CXI:TIMETOOL:TTALL' # time tool array name\n matlab_start = 20 # first matlab pv\n matlab_prefix = 'LAS:FS5:VIT:matlab:' # start of matlab names\n stagename = 'CXI:LAS:MMN:04' # delay stage for time tool\n ipmname = 'CXI:DG2:BMMON:SUM' # intensity profile monitor PV\n \n elif sys == 'XCS': # set up xcs system\n print('starting XCS')\n self.delay = 0.1 # 1 second delay\n pvname = 'XCS:TIMETOOL:TTALL' # time tool array name\n matlab_start = 20 # first matlab pv\n matlab_prefix = 'LAS:FS4:VIT:matlab:' # start of matlab names\n stagename = 'XCS:LAS:MMN:01' # delay stage for time tool\n ipmname = 'XCS:SB2:BMMON:SUM' # intensity profile monitor PV\n\n else:\n print(sys + ' not found, exiting')\n exit()\n \n self.usett = usett\n self.usepcav = usepcav\n self.debug = debug\n if usett:\n print(\"Using time tool drift compensation\")\n if usepcav:\n print(\"Using phase cavity drift compensation\")\n if debug:\n print(\"..running in debug mode\")\n pcavpv=['SIOC:UNDH:PT01:0:TIME0','SIOC:UNDH:PT01:0:TIME1'] # PVs for the output time for the two FEH,NC Linac cavities\n \n self.ttpv = Pv(pvname)\n self.ttpv.connect(timeout=1.0) # connect to pv\n self.stagepv = Pv(stagename)\n self.stagepv.connect(timeout=1.0)\n self.ipmpv = Pv(ipmname)\n self.ipmpv.connect(timeout=1.0)\n self.pcava=Pv(pcavpv[0])\n self.pcava.connect(timeout=1.0)\n self.pcavb=Pv(pcavpv[1])\n self.pcavb.connect(timeout=1.0)\n self.matlab_pv = dict() # will hold list of pvs\n self.values = dict() # will hold the numbers from the time tool\n self.pcavdata = dict() # will hold values from the phase cavities\n self.pcavbuffer = deque()\n # for n in range(0,60):\n # self.pcavbuffer.append(0.0)\n self.dccalc = 0\n self.pcavcalc=0\n self.limits = dict() # will hold limits from matlab pvs\n self.old_values = dict() # will hold the old values read from matlab\n self.nm = ['watchdog', 'pix', 'fs', 'amp', 'amp_second', 'ref', 'FWHM', 'Stage', 'ipm','dcsignal','pcavcomp'] #list of internal names\n for n in range(0,self.nm.__len__+1): # loop over pvs to create\n base = matlab_prefix + str(n+matlab_start) # base pv name\n self.matlab_pv[self.nm[n]] = [Pv(base), Pv(base+'.LOW'), Pv(base+'.HIGH'), Pv(base+'.DESC')] # pv with normal, low and high\n for x in range(0,4):\n self.matlab_pv[self.nm[n]][x].connect(timeout=1.0) # connnect to all the various PVs. \n for x in range(0,3):\n self.matlab_pv[self.nm[n]][x].get(ctrl=True, timeout=1.0)\n self.matlab_pv[self.nm[n]][3].put(value = self.nm[n], timeout = 1.0)\n self.W = watchdog.watchdog(self.matlab_pv[self.nm[0]][0]) # initialize watcdog ","def trial_prep(self):\n pass","def dynamics(self,eta,nu,u_actual,u_control,sampleTime): \n \n # Current velocities\n u_c = self.V_c * math.cos(self.beta_c - eta[5]) # current surge velocity\n v_c = self.V_c * math.sin(self.beta_c - eta[5]) # current sway velocity \n \n nu_c = np.array([u_c,v_c,0,0,0,0],float) # current velocity vector\n nu_r = nu - nu_c # relative velocity vector\n \n U_r = math.sqrt( nu_r[0]**2 + nu_r[1]**2 ) # relative speed\n \n # Rudder command and actual rudder angle\n delta_c = u_control[0]\n delta = u_actual[0]\n \n # Rudder forces and moment (Fossen 2021, Chapter 9.5.1)\n b = 0.7 * self.T # rudder height\n AR = b**2 / self.Lambda # aspect ratio: Lamdba = b**2/AR \n CN = 6.13 * self.Lambda / ( self.Lambda + 2.25 ) # normal coefficient\n t_R = 1 - 0.28 * self.Cb - 0.55\n a_H = 0.4\n x_R = -0.45 * self.L\n x_H = -1.0 * self.L\n\n Xdd = -0.5 * ( 1 - t_R ) * self.rho * U_r**2 * AR * CN\n Yd = -0.25 * ( 1 + a_H ) * self.rho * U_r**2 * AR * CN \n Nd = -0.25 * ( x_R + a_H * x_H ) * self.rho * U_r**2 * AR * CN \n \n # Control forces and moment\n delta_R = -delta # physical rudder angle (rad)\n T = self.tau_X # thrust (N)\n t_deduction = 0.1 # thrust deduction number\n tau1 = ( 1 - t_deduction ) * T - Xdd * math.sin( delta_R )**2 \n tau2 = -Yd * math.sin( 2 * delta_R ) \n tau6 = -Nd * math.sin( 2 * delta_R ) \n tau = np.array( [ tau1, tau2, tau6 ],float) \n \n # Linear maneuvering model\n T_surge = self.L # approx. time constant in surge (s)\n xg = 0 # approx. x-coordinate, CG (m) \n \n # 3-DOF ship model\n [M,N] = clarke83(U_r,self.L, self.B, self.T,self.Cb,self.R66,xg,T_surge)\n Minv = np.linalg.inv(M)\n nu3 = np.array( [ nu_r[0], nu_r[1], nu_r[5] ]) \n nu3_dot = np.matmul( Minv, tau - np.matmul(N,nu3) ) \n \n # 6-DOF ship model\n nu_dot = np.array( [ nu3_dot[0],nu3_dot[1],0,0,0,nu3_dot[2] ]) \n\n # Rudder angle saturation\n if ( abs(delta) >= self.deltaMax * math.pi / 180 ):\n delta = np.sign(delta) * self.deltaMax * math.pi / 180\n \n # Rudder dynamics\n delta_dot = (delta_c - delta) / self.T_delta \n\n # Forward Euler integration [k+1]\n nu = nu + sampleTime * nu_dot\n delta = delta + sampleTime * delta_dot\n\n u_actual = np.array([delta],float) \n\n return nu, u_actual","def __init__(self, t=0.01):\r\n\r\n\t\tself.t = float(t)\r\n\t\t\r\n\t\t#Control constants\r\n\t\t#Altitude\r\n\t\t#P\r\n\t\tkp1=3\r\n\t\t#PID\r\n\t\tkp2=6\r\n\t\tki2=0\r\n\t\tkd2=2.5\r\n\t\t#PID\r\n\t\tkp3=0.75\r\n\t\tki3=1.5\r\n\t\tkd3=0\r\n\t\t\r\n\t\t#Pitch\r\n\t\t#P\r\n\t\tkp1_theta=4.5\r\n\t\t#PID\r\n\t\tkp2_theta=0.15\r\n\t\tki2_theta=0.1\r\n\t\tkd2_theta=0.004\r\n\t\t\r\n\t\t#Roll\r\n\t\t#P\r\n\t\tkp1_phi=4.5\r\n\t\t#PID\r\n\t\tkp2_phi=0.15\r\n\t\tki2_phi=0.1\r\n\t\tkd2_phi=0.004\r\n\t\t\r\n\t\t#Yaw\r\n\t\t#P\r\n\t\tkp1_psi=10\r\n\t\t#PID\r\n\t\tkp2_psi=0.2\r\n\t\tki2_psi=0.02\r\n\t\tkd2_psi=0\r\n\t\t\r\n\t\t#Control\r\n\t\timax1=10\r\n\t\tt_max1=200\r\n\t\timax2=10\r\n\t\tt_max2=120\r\n\t\t\r\n\t\t#Constrains\r\n\t\trate_imax = 50\r\n\t\tac_imax = 40\r\n\t\tt_min = 800\r\n\t\tt_max = 1500\r\n\t\t\r\n\t\t#Goals\r\n\t\tself.target_z=3\r\n\t\tself.target_theta=0\r\n\t\tself.target_phi=0\r\n\t\tself.target_psi=0\r\n\r\n\t\t#Initial Conditions\r\n\t\tself.w=[1000, 1000, 1000, 1000]\r\n\t\t#self.ev = [0, 0, 1, 0, 0, 0, 0, 0, -9.81, 0.4, -0.2, 1, 0.1, -0.1, 0.2, 0.01, -0.01, 0.02]\r\n\t\tself.ev = [0, 0, 0, 0, 0, 0, 0, 0, -9.81, 0, 0, 0, 0, 0, 0, 0, 0, 0]\r\n\r\n\t\t#Create controllers\r\n\t\tself.altitudeController = control.controlAlt (self.t, kp1, kp2, ki2, kd2, kp3, ki3, kd3, rate_imax, ac_imax,t_min,t_max)\r\n\t\tself.thetaController = control.controlAngle (self.t, kp1_theta, kp2_theta, ki2_theta, kd2_theta, imax1, t_max1)\r\n\t\tself.phiController = control.controlAngle (self.t, kp1_phi, kp2_phi, ki2_phi, kd2_phi, imax1, t_max1)\r\n\t\tself.psiController = control.controlAngle (self.t, kp1_psi, kp2_psi, ki2_psi, kd2_psi, imax2, t_max2)","def run_loop_measurement(t=0.5, name='test', loops=4, pump_t=180, total_t=600, jump_x=10):\n\n incident_angles = [0.1, 0.4]\n waxs_arc = [20, 0]\n user = \"TP\"\n\n condition = (\n ( -1 < waxs.arc.position )\n and ( waxs.arc.position < 1 )\n and (waxs_arc[0] == 20)\n )\n\n if condition:\n waxs_arc = waxs_arc[::-1]\n \n ranges = { 0.1 : [-16, 16, 33],\n 0.4 : [-25, 25, 51],\n }\n\n try:\n ai0 = RE.md['ai_0']\n except:\n yield from bp.count([])\n ai0 = db[-1].start['ai_0']\n print('Failed to acces RE.md')\n print(f'\\n\\nSample flat at theta = {ai0}')\n \n proposal_id('2023_2', '311564_Pettersson')\n #det_exposure_time(t, t)\n \n t_initial = time.time()\n\n for i in range(loops):\n t_start = time.time()\n print('Cycle number',i+1,'started at', (t_start - t_initial)/60)\n\n # Wait initial time for pumping to finish\n print(f'Start pumping now, going to wait for {pump_t} s\\n')\n while (time.time() - t_start) < pump_t:\n print(f'Pumping time: {(time.time() - t_start):.1f} s')\n yield from bps.sleep(10)\n\n # Go over SAXS and WAXS\n t_measurement = ( time.time() - t_initial ) / 60\n for wa in waxs_arc:\n yield from bps.mv(waxs, wa)\n dets = [pil900KW] if waxs.arc.position < 15 else [pil1M, pil900KW]\n\n for ai in incident_angles:\n yield from bps.mv(piezo.th, ai0 + ai)\n yield from bps.mvr(piezo.x, - jump_x)\n\n t2 = 2 * t if ai == 0.4 else t\n det_exposure_time(t2, t2)\n\n try:\n y_range = ranges[ai]\n except:\n y_range = [-10, 10, 11]\n \n sample_name = f'{name}{get_scan_md()}_time{t_measurement:.1f}_ai{ai}'\n sample_id(user_name=user, sample_name=sample_name)\n print(f\"\\n\\n\\n\\t=== Sample: {sample_name} ===\")\n yield from bp.rel_scan(dets, piezo.y, *y_range, md=dict(ai=ai))\n \n yield from bps.mv(waxs, waxs_arc[0],\n piezo.th, ai0)\n\n # Wait until the total loop time passes\n if i + 1 < loops:\n print(f'Waiting for the loop to last {total_t} s in total\\n')\n sleep_count = 0\n while (time.time() - t_start) < total_t:\n sleep_count += 1\n if (sleep_count % 10 == 0):\n print(f'Total time: {(time.time() - t_start):.1f} s')\n yield from bps.sleep(1)\n\n sample_id(user_name=\"test\", sample_name=\"test\")\n det_exposure_time(0.5, 0.5)","def _setup(self) -> None:\n # Call base implementation\n super()._setup()\n\n # Configure the low-level integrator\n engine_options = self.simulator.engine.get_options()\n engine_options[\"stepper\"][\"iterMax\"] = 0\n engine_options[\"stepper\"][\"dtMax\"] = min(0.02, self.step_dt)\n engine_options[\"stepper\"][\"logInternalStepperSteps\"] = False\n\n # Set maximum computation time for single internal integration steps\n if self.debug:\n engine_options[\"stepper\"][\"timeout\"] = 0.0\n else:\n engine_options[\"stepper\"][\"timeout\"] = 2.0\n\n # Enable logging of geometries in debug mode\n if self.debug:\n engine_options[\"telemetry\"][\"isPersistent\"] = True\n\n # Update engine options\n self.simulator.engine.set_options(engine_options)\n\n # Set robot in neutral configuration\n qpos = self._neutral()\n framesForwardKinematics(\n self.robot.pinocchio_model, self.robot.pinocchio_data, qpos)","def simulationDelayedTreatment(numTrials):\n\n delays = [300,150,75,0]\n results = [[],[],[],[]]\n for place in range(0, 4):\n for trial in range(numTrials):\n viruses = []\n for num in range(100):\n viruses.append(ResistantVirus(0.1,0.05, {'guttagonol': False}, 0.005))\n patient = TreatedPatient(viruses, 1000)\n for delay in range(delays[place]):\n patient.update()\n patient.addPrescription(\"guttagonol\") \n for l in range(150):\n patient.update()\n results[place].append(patient.getTotalPop())\n pylab.hist(results[0])\n pylab.hist(results[1])\n pylab.hist(results[2])\n pylab.hist(results[3])\n pylab.show()\n for x in range(0, 10):","def scenario2(sim):\n n = 83\n t_start = 25.0\n duration = 100.0\n t_stop = 150.0\n tau_m = 20.0\n v_thresh = 10.0\n cm = 1.0\n cell_params = {\"tau_m\": tau_m, \"v_rest\": 0.0, \"v_reset\": 0.0,\n \"tau_refrac\": 100.0, \"v_thresh\": v_thresh, \"cm\": cm}\n I0 = (v_thresh * cm) / tau_m\n sim.setup(timestep=0.01, min_delay=0.1, spike_precision=\"off_grid\")\n neurons = sim.Population(n, sim.IF_curr_exp(**cell_params))\n neurons.initialize(v=0.0)\n I = numpy.arange(I0, I0 + 1.0, 1.0 / n)\n currents = [sim.DCSource(start=t_start, stop=t_start + duration, amplitude=amp)\n for amp in I]\n for j, (neuron, current) in enumerate(zip(neurons, currents)):\n if j % 2 == 0: # these should\n neuron.inject(current) # be entirely\n else: # equivalent\n current.inject_into([neuron])\n neurons.record(['spikes', 'v'])\n\n sim.run(t_stop)\n\n spiketrains = neurons.get_data().segments[0].spiketrains\n assert_equal(len(spiketrains), n)\n assert_equal(len(spiketrains[0]), 0) # first cell does not fire\n assert_equal(len(spiketrains[1]), 1) # other cells fire once\n assert_equal(len(spiketrains[-1]), 1) # other cells fire once\n expected_spike_times = t_start + tau_m * numpy.log(I * tau_m / (I * tau_m - v_thresh * cm))\n a = spike_times = [numpy.array(st)[0] for st in spiketrains[1:]]\n b = expected_spike_times[1:]\n max_error = abs((a - b) / b).max()\n print(\"max error =\", max_error)\n assert max_error < 0.005, max_error\n sim.end()\n return a, b, spike_times","def setup_simulation(system, pdb, integrator):\n #platform = Platform.getPlatformByName('CPU')\n platform = Platform.getPlatformByName('OpenCL')\n prop = {'OpenCLPrecision':'single'}\n \n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\n simulation.context.setPositions(pdb.positions)\n simulation.minimizeEnergy(100)\n simulation.context.setVelocitiesToTemperature(310*kelvin)\n print('Created simulation')\n return simulation","def __init__(self,files_atte,files_emis,states,lifetime):\n self.files_atte = files_atte #!\n self.files_emis = files_emis #!\n self.beam_emis = [] #!\n self.beam_atte = [] #!\n print('The wavelength assumes an hydrogen atom')\n self.n_low = states[0] #!\n self.n_high = states[1] #!\n self.E0 = -13.6\n self.lifetime = lifetime\n self.read_adas()\n\n # compute the interpolant\n self.atte_tck_dens = [] #!\n self.emis_tck_dens = [] #!\n self.atte_tck_temp = [] #!\n self.emis_tck_temp = [] #!\n for i in range(len(self.beam_atte)):\n # get data\n ldensities = np.log(self.get_list_density('atte',i))\n lbeams = np.log(self.get_list_beams('atte',i))\n coef_dens = self.get_coef_density('atte',i)\n lbeams, ldens = np.meshgrid(lbeams, ldensities)\n \n # interpolation over beam and density\n self.atte_tck_dens.append(interpolate.bisplrep(\n lbeams,ldens,coef_dens,kx=1,ky=1))\n \n # get data for the interpolation in temperature\n T = np.log(self.get_list_temperature('atte',i))\n coef_T = self.get_coef_T('atte',i)\n Tref = np.log(self.get_Tref('atte',i))\n index = abs((Tref-T)/Tref) < 1e-4\n \n #interpolation over the temperature\n self.atte_tck_temp.append(interpolate.splrep(\n T,coef_T/coef_T[index],k=1))\n\n for i in range(len(self.beam_emis)):\n # get data\n ldensities = np.log(self.get_list_density('emis',i))\n lbeams = np.log(self.get_list_beams('emis',i))\n coef_dens = self.get_coef_density('emis',i)\n lbeams, ldens = np.meshgrid(lbeams, ldensities)\n \n # interpolation over beam and density\n self.emis_tck_dens.append(interpolate.bisplrep(\n lbeams,ldens,coef_dens,kx=1,ky=1))\n\n # Get data for the interpolation in temperature\n T = np.log(self.get_list_temperature('emis',i))\n coef_T = self.get_coef_T('emis',i)\n Tref = np.log(self.get_Tref('emis',i))\n index = abs((Tref-T)/Tref) < 1e-4\n \n #interpolation over the temperature\n self.emis_tck_temp.append(interpolate.splrep(\n T,coef_T/coef_T[index],k=1))","def getActpolSim(iterationNum = 0, patch = 'deep5', \n season = 's13', \\\n array = 'pa1', \\\n psa = None,\\\n noiseDictFile = 'templateInputsMr3c.dict', \\\n noiseDictFilePath = os.path.join(os.path.dirname(os.path.abspath(__file__)),'../inputParams/'), \\\n signalDictFile = 'signal.dict',\\\n signalDictFilePath = os.path.join(os.path.dirname(os.path.abspath(__file__)),'../inputParams/'),\\\n verbose = True,\\\n simType = 'noise',\n cmbSet = 0,\n doBeam = True, applyWindow = True, noiseDiagsOnly = False, cmbMaptype = 'LensedCMB', splitWanted = None,\n applyModulation = True):\n #update the last one to True if possible\n\n\n#FIXME: get rid of absolute pathnames\n\n nDict = flipperDict.flipperDict()\n nDict.read_from_file(noiseDictFilePath + '/' + noiseDictFile)\n\n sDict = flipperDict.flipperDict()\n sDict.read_from_file(signalDictFilePath + '/' + signalDictFile)\n \n if psa == None: #psa stands for patch, season, \n psa = '%s_%s_%s' %(patch, season, array)\n\n\n #Figure out what frequencies correspond to this array, using the function defined above.\n psaFreqs = freqsInPsas(psa, nDict['freqsInArrays'])\n\n\n #unroll psa names (normally stored as a nested list of lists)\n psaList = [item for sublist in nDict['psaList'] for item in sublist]\n\n\n if psa not in psaList:\n raise ValueError('psa %s not found in psaList; options are ' % (psa ), psaList)\n\n\n noiseSeed = (cmbSet, psaList.index(psa), noiseSeedInd * 4 + (0 if splitWanted is None else splitWanted), iterationNum)\n\n #load up one sample map, just to get the shape and wcs info. Do this for \"I\" at one frequency\n sampleMap = enmap.read_map(os.path.join(os.path.dirname(os.path.abspath(__file__)))+\"/\"+nDict['dataMapDir'] + 'totalWeightMap' \\\n + 'I' + '_' + psa + '_' + psaFreqs[0] + '_fromenlib.fits') \n\n\n #Note! Foreground seed is the same for every sky patch, season, and frequency!\n #This is because they are used to generate fullsky alm's\n foregroundSeed = (cmbSet, 0, fgSeedInd, iterationNum)\n\n\n\n if simType == 'noise':\n\n return getActpolNoiseSim(noiseSeed = noiseSeed, \\\n psa = psa, \\\n noisePsdDir = os.path.dirname(os.path.abspath(__file__))+\"/\"+nDict['dataMapDir'],\n freqs = psaFreqs, \n verbose = verbose,\n noiseDiagsOnly = noiseDiagsOnly,\n splitWanted = splitWanted)\n\n elif simType == 'cmb' or simType == 'foregrounds':\n \n\n return getActpolCmbFgSim(beamfileDict = sDict['beamNames'],\n shape = sampleMap.shape, wcs = sampleMap.wcs,\n iterationNum = iterationNum,\n cmbDir = os.path.dirname(os.path.abspath(__file__))+\"/\"+sDict['cmbDir'],\n freqs = psaFreqs,\n psa = psa,\n cmbSet = cmbSet, \n doBeam = doBeam, applyWindow = applyWindow,\n verbose = verbose, cmbMaptype = cmbMaptype, foregroundSeed = foregroundSeed,\n simType = simType, foregroundPowerFile = sDict['foregroundPowerFile'],\n applyModulation = applyModulation)\n\n\n else:\n raise ValueError(\"bad input\")","def ptc_acquisition(self, explow=0.1, exphigh=2, expdelta=0.1, laserchannel = 2, lasercurrent=45.0):\n\n #\n self.laser.select(laserchannel)\n self.laser.setCurrent(laserchannel, lasercurrent)\n self.laser.enable()\n\n #self.powerup_CCD()\n self.reb.set_testtype('PTC')\n\n #self.DKD.setup_current_measurements(DKD_range)\n self.PhD.setup_current_measurements(2e-8)\n\n # Create the logging summary file\n summaryfile = os.path.join(eodir, 'summary.log')\n f = open(summaryfile, 'a')\n\n print >>f, \"# power\\t exposure time\\t file name\"\n\n effpow = self.laser.getPower(laserchannel)\n # First take bias frames\n self.log(\"Taking bias\")\n m = self.execute_reb_sequence('ClearBias', 0, 20, True )\n #to have only useful channels:\n fname = \"%s_ptc_bias_%s.fits\" % (serno, self.reb.reb.imgtag)\n i = self.conv_to_fits(channels=validamps)\n # to save FITS HDU with headers\n self.save_to_fits(i, m, fitsname=os.path.join(eodir, fname))\n\n print >>f, effpow, 0, fname\n\n for t in np.arange(explow, exphigh+expdelta, expdelta):\n # pair of flats\n for numpair in [1, 2]:\n effpow = self.laser.getPower(laserchannel)\n m = self.execute_reb_sequence('Acquisition', t)\n #to have only useful channels:\n fname = \"%s_ptc_flat%d_%05d_%s.fits\" % (serno, numpair, int(t*100), self.reb.reb.imgtag)\n i = self.conv_to_fits(channels=validamps)\n # to save FITS HDU with headers\n self.save_to_fits(i, m, fitsname=os.path.join(eodir, fname))\n\n print >>f, effpow, t, fname\n\n f.close()\n\n # Shutting down (not the lamp by default)\n self.laser.disable()\n #self.shutdown_CCD()\n # p = self.reb.start_waiting_sequence()","def setparams (w=None, delay=None, tau=None, low=None, high=None):\n global firststep\n for n in nclist: \n if w is not None: n.weight[0] = w if useHHCell else -w # neg wts are needed for ArtCell (neg driving force for HHCell)\n if delay is not None: n.delay=delay\n if firststep or (low and high): # only set this up using defaults the 1st time\n firststep = False \n if low is not None: low, high = 10, 11\n for ce,ran,start in zip(cells, np.random.uniform(low, high, ncells), np.random.uniform(0, 30, ncells)): \n if useHHCell:\n ce.stim.amp = ran\n ce.stim.delay = start\n else: \n ce.pp.invl = ran\n if tau is not None: ce.tau = tau","def setup(env, num_machines, washtime, t_inter):\n # Create the CarWashMachine\n WashMachine = CarWashMachine(env, num_machines, washtime)\n\n # Create 4 initial cars\n for i in range(4):\n env.process(car(env, 'Car %d' % i, WashMachine))\n\n # Create more cars while the simulation is running\n while True:\n yield env.timeout(random.randint(t_inter - 2, t_inter + 2))\n i += 1\n env.process(car(env, 'Car %d' % i, WashMachine))","def setup_tacs_problems(self, comm):\n # Overwrite default check values\n if self.dtype == complex:\n self.rtol = 1e-8\n self.atol = 1e-3\n self.dh = 1e-50\n else:\n self.rtol = 1e-1\n self.atol = 1e-4\n self.dh = 1e-5\n\n # Instantiate FEA Assembler\n fea_assembler = pytacs.pyTACS(bdf_file, comm)\n\n # Set up constitutive objects and elements\n fea_assembler.initialize()\n\n # set transient problem options\n transientOptions = {\"timeIntegrator\": \"DIRK\", \"integrationOrder\": DIRK_order}\n\n # get some problem info\n n_vpn = fea_assembler.getVarsPerNode()\n\n # Create coarse load-specified transient problem\n coarse_prob = fea_assembler.createTransientProblem(\n name=\"load_coarse\",\n tInit=0.0,\n tFinal=1.0,\n numSteps=8,\n options=transientOptions,\n )\n # Create fine load-specified transient problem\n fine_prob = fea_assembler.createTransientProblem(\n name=\"load_fine\",\n tInit=0.0,\n tFinal=1.0,\n numSteps=32,\n options=transientOptions,\n )\n load_probs = [coarse_prob, fine_prob]\n\n for prob in load_probs:\n forces = np.zeros(n_vpn)\n ns = prob.getNumTimeSteps()\n for k in range(ns + 1):\n t_array = prob.getTimeStages(k)\n for s, t in enumerate(t_array):\n f = f_mag * t**5\n forces[2] = f # applied to z-direction\n prob.addLoadToNodes(\n timeStep=k,\n timeStage=s,\n nodeIDs=21,\n F=forces,\n nastranOrdering=True,\n )\n\n for problem in load_probs:\n problem.addFunction(\"mass\", functions.StructuralMass)\n problem.addFunction(\n \"ks_disp\",\n functions.KSDisplacement,\n direction=[0.0, 0.0, 100.0],\n ftype=\"discrete\",\n )\n\n return load_probs, fea_assembler","def autonomousInit(self):\n '''\n self.cumulativeTime=0\n self.totalTime=0\n self.dataSet=[[-0.5,0,1,-1.0],[0.3,0.4,1,1.0],[-0.5,0,1,-1.0]]\n for i in self.dataSet:\n self.totalTime+=i[2]\n self.intervals = 0\n self.currentTime = 0\n for i in range(0,len(self.dataSet)):\n self.dataSet[i].append([self.currentTime,self.currentTime+self.dataSet[i][2]])\n self.currentTime+=self.dataSet[i][2]\n for i in self.dataSet:\n if i[3]==1.0:\n i.append(\"Forward\")\n if i[3]==-1.0:\n i.append(\"Backward\")\n \n self.timer.reset()\n self.timer.start()\n '''\n self.timer.reset()\n self.timer.start()\n\n #self.auto = self.chooser.getSelected()\n self.auto = 6\n self.autoState = 0\n #self.auto = 1\n\n self.EC1.reset()\n \n\n #self.auto = self.chooser.getSelected()","async def prepare_measuring(self):\n # close MDV,\n # fill the constant tank, start the measurement pumps.\n self.valves[MEASURING_DRAIN_VALVE].close()\n await self.tanks[CONSTANT_TANK].fill(keep_source_active=True)\n self.pumps[PUMP_MEASURING_TANK].stop()\n self.scale.start()\n\n self._state = self.PREPARING_MEASUREMENT","def __init__(self) -> None:\n self.simulation = None\n self.update_time = 0.1\n self.time = None\n self.config = None","def _init_system(*args):\n __set_time_elements(args[0], args[1])\n __set_control_elements(args[0], args[2], args[3])\n __set_sensor_elements(args[0], args[4], args[5], args[6], args[7])","def __init__(self):\n # set vars\n self.__deamon = True\n _tacho_pin = 'GPIO_PZ0'\n self._pow_pin = 'CAM_AF_EN'\n self._mist_pin = 'SPI2_MOSI'\n _pwm_pin = 'LCD_BL_PW'\n self._pwm_obj = None\n self._pump_pin = 'DAP4_DIN'\n self._sens_level_mist = 'UART2_CTS'\n self._sens_level_tank = 'DAP4_FS'\n self._sleep_pin = 'SPI2_SCK'\n self.__pow = 0\n self.__hum = 0\n self.__hum_temp = 100\n self.__sens_temp = 100\n self.__t = time.time()\n self.__rpm = 0\n\n # init everything\n GPIO.setmode(GPIO.TEGRA_SOC)\n GPIO.setup(self._pow_pin, GPIO.OUT)\n GPIO.setup(self._mist_pin, GPIO.OUT)\n GPIO.setup(self._pump_pin, GPIO.OUT)\n GPIO.setup(_tacho_pin, GPIO.IN)\n GPIO.setup(self._sens_level_mist, GPIO.IN)\n GPIO.setup(self._sens_level_tank, GPIO.IN)\n GPIO.setup(self._sleep_pin, GPIO.IN)\n GPIO.add_event_detect(_tacho_pin, GPIO.FALLING, self.__fan_int)\n GPIO.add_event_detect(self._sens_level_tank,\n GPIO.BOTH, self.__tank)\n GPIO.add_event_detect(self._sleep_pin, GPIO.FALLING, self.__Sleep)\n self._tah = temps.Temp()\n self._led = LED()\n self.kit = ServoKit(channels=16)\n self.kit.servo[7].actuation_range = 180\n self.kit.servo[8].actuation_range = 20\n self._pwm_obj = GPIO.PWM(_pwm_pin, 1000)\n self.__mist_thread = threading.Thread(target=self.__mist_deamon)\n self.__pow_thread = threading.Thread(target=self.__pow_deamon)\n self.__pump_thread = threading.Thread(target=self.__pump_deamon)\n self.__mist_thread.start()\n self.__pow_thread.start()\n self.__pump_thread.start()\n self._pwm_obj.start(0)\n self._led.reset_error()","def __init__(self, robot: SmartBot, dt: float):\n super(Ideal, self).__init__(robot, dt)","def setdelay(self):\n delay=self.inputdelay.getEntry()\n cmd=\"setDelay(\"+self.board+','+self.inpedge+','+delay+')'\n self.vb.io.execute(cmd,log=\"out\",applout=\"<>\")","def evaluateIFsetup(ants=0, timerange=3.4, deltat=0.1,\n verbose=False, iniAtten=0) :\n antlist = makeAntList(ants)\n for a in antlist:\n if a < 16:\n print \"SZA antennas only can be used - exiting\"\n return\n tpMP = \"Ifmod.ifTotalPower\"\n attenMP = \"Ifmod.totalAtten\"\n currentPos = \"AMBIENT\"\n print \"Inserting ambient load into beam\"\n rtn = amb(ants)\n pos1ants = rtn.ready\n mplist = []\n for a in pos1ants:\n prefix = \"Sza%d.\" %(a-15)\n mplist.append([prefix+tpMP, prefix+attenMP])\n #print mplist\n if len(rtn.notready) != 0:\n print \"Ambient load not inserted for ants:\", rtn.notready\n if iniAtten != None :\n print \"Setting IF atten to %.1f\" %iniAtten\n antennaIFatten(iniAtten, 1, invalidateTsys=False, \n ants=antlist)\n wait(tmo=2.0)\n t0=time.time()\n antennaIFpower(0.3, ants)\n t1 = time.time()\n cmdtime = t1-t0\n results = []\n times = []\n nsamps = int(round(timerange/deltat))\n for i in range(nsamps):\n sleep(deltat)\n dt=time.time()-t1\n times.append(dt)\n results.append(queryMpValues(mplist))\n #print results\n print \"Command time = %.3f seconds\" %cmdtime\n for j in range(len(pos1ants)):\n aname = \"Sza%d\" %(pos1ants[j]-15)\n if verbose: print \"======== %s ========\" %aname\n for i in range(nsamps):\n r = results[i][j]\n st = \"%s: %4.1f %6.3f %4.1f\" %(aname,times[i],r[0],r[1])\n if verbose: print st\n print \"\\n==== Inferred timing & final atten =====\"\n for j in range(len(pos1ants)):\n aname = \"Sza%d\" %(pos1ants[j]-15)\n finalAtten = results[nsamps-1][j][1]\n timing = times[nsamps-1]\n for i in range(nsamps):\n index = nsamps-1-i\n atten = results[index][j][1]\n if atten != finalAtten: break\n timing = times[index]\n st = \" %s: %4.1f %4.1f\" %(aname,timing, finalAtten)\n print st\n \n #print \"Moving ambient load out of the beam\"\n pos2ants = sky(ants).ready\n # Wait for two seconds to get final psys reading\n wait(tmo=2.0)\n skyants = pos2ants\n complete = []\n for a in pos1ants :\n if (pos2ants.count(a) > 0) : complete.append(a)\n return complete","def init_devices(timeStep):\r\n\r\n robot = Robot()\r\n \r\n # Obtener dispositivos correspondientes a las ruedas.\r\n leftWheel = robot.getDevice('left wheel motor')\r\n rightWheel = robot.getDevice('right wheel motor')\r\n # Utilizamos velocidad, establecemos posición a infinito.\r\n leftWheel.setPosition(float('inf'))\r\n rightWheel.setPosition(float('inf')) \r\n leftWheel.setVelocity(0)\r\n rightWheel.setVelocity(0)\r\n\r\n # Obtener y activar el dispositivo de la cámara \r\n camera = robot.getDevice('camera')\r\n camera.enable(timeStep*10)\r\n\r\n\r\n #activar sensores ultrasónicos\r\n ultrasonic_sensors = []\r\n i = 0\r\n for sensor in ultrasonic_sensors_names: \r\n ultrasonic_sensors = ultrasonic_sensors + [robot.getDevice(sensor)]\r\n ultrasonic_sensors[i].enable(timeStep)\r\n i = i + 1\r\n print(ultrasonic_sensors_names)\r\n\r\n #activar sensores infrarojos\r\n infrared_sensors = []\r\n i = 0\r\n for sensor in infrared_sensors_names: \r\n infrared_sensors = infrared_sensors + [robot.getDevice(sensor)]\r\n infrared_sensors[i].enable(timeStep)\r\n i = i + 1\r\n \r\n return robot, camera, leftWheel, rightWheel , infrared_sensors, ultrasonic_sensors","def simulation(self):\r\n \r\n self.Real.Pbat, self.Real.Pbs, self.Real.soc, self.Real.soc0, self.Real.Pbs0 = batmod_ac(\r\n self.d, self.dt, self.Real.soc0, self.Real.soc, self.Real.Pr, self.Real.Pbs0, self.Real.Pbs, self.Real.Pbat)\r\n \r\n self.Ideal.Pbs, self.Ideal.Pbat, self.Ideal.soc0, self.Ideal.soc = batmod_ac_ideal(\r\n self.d, self.dt, self.Ideal.soc0, self.Ideal.soc, self.Ideal.Pr, self.Ideal.Pbat)","def eulers_spring(dt=.05,p=1,s0=1,v0=0,t0=0,damp=0,plotit = True,trials = 1000):\n \n delta_t = dt\n \n\n s = np.zeros([trials+1])\n v = np.zeros([trials+1])\n t = np.zeros([trials+1])\n s[0] = s0\n v[0] = v0\n t[0] = t0\n \n for i in range(trials):\n s[i + 1] = updater(s[i],v[i], delta_t)\n v[i + 1] = updater(v[i],acceleration(p,s[i],v=v[i],damp=damp),delta_t)\n t[i + 1] = updater(t[i],1,delta_t)\n \n #s[i + 1] = s[i] + v[i] *delta_t #non functional implementation I saw online\n #v[i + 1] = v[i] + -p*s[i] * delta_t\n #t[i + 1] = t[i] + delta_t\n \n if plotit == True:\n plt.plot(t,s)\n plt.plot(t,v)\n plt.show()","def __init__(self, encut, magmom, ldaul, Uparam, Jparam, name=\"DFTCL_settings\"):\n\n cl_settings = {\"ISPIN\": 2, \"MAGMOM\": magmom, \"SAXIS\": None, \"LSORBIT\": None, \"LNONCOLLINEAR\": None}\n dftu_settings = {\"LDAU\": \".TRUE.\", \"LDAUU\": Uparam, \"LDATYPE\": 2, \"LDAUL\": ldaul, \"LDAUJ\": Jparam , \"LMAXMIMX\": 4}\n InputParameters.__init__(self, name=name, magnetic_settings=cl_settings, hubbard_settings=dftu_settings)\n self.update_electronic_settings(\"encut\", encut)","def setup(self):\n GPIO.setwarnings(False)\n GPIO.setmode(GPIO.BCM)\n GPIO.setup(self.Motor_A_EN, GPIO.OUT)\n GPIO.setup(self.Motor_B_EN, GPIO.OUT)\n GPIO.setup(self.Motor_A_Pin1, GPIO.OUT)\n GPIO.setup(self.Motor_A_Pin2, GPIO.OUT)\n GPIO.setup(self.Motor_B_Pin1, GPIO.OUT)\n GPIO.setup(self.Motor_B_Pin2, GPIO.OUT)\n self.motorStop() # Avoids automatic motor rotation after initialization\n try: # Try is used here to avoid errors due to repeated setting of PWM\n self.pwm_A = GPIO.PWM(self.Motor_A_EN, 1000)\n self.pwm_B = GPIO.PWM(self.Motor_B_EN, 1000)\n except:\n pass","def _setup_simulation_from_parameters(self):\n for param_name, modifier in self.modifiers:\n modifier(getattr(self.parameters, param_name))","def init_motors(self):\n # self.maxVelocity = 576# -> 5 m/s\n # self.maxTorque = 30\n\n # motor init\n for m in self.motors:\n m.setPosition(float('inf'))\n m.setVelocity(1.)\n\n # Propeller PID control params tunned with Ziegler–Nichols PID\n K_u = 150.\n T_u = 342.857 / 1000. # ms\n # no overshoot\n params_roll = {'P': K_u / 5., 'I': (2. / 5.) * K_u / T_u,\n 'D': K_u * T_u / 15., 'sp': 0.}\n self.rollPID = PID(params_roll['P'], params_roll['I'],\n params_roll['D'], setpoint=params_roll['sp'],\n output_limits=(-2., 2.), sample_time=self.deltaT)\n\n K_u = 150.\n T_u = 682.66 / 1000. # ms\n # no overshoot\n params_pitch = {'P': K_u/5.,\n 'I': (2. / 5.) * K_u / T_u,\n 'D': K_u*T_u/15.,\n 'sp': 0.}\n self.pitchPID = PID(params_pitch['P'], params_pitch['I'],\n params_pitch['D'], setpoint=params_pitch['sp'],\n output_limits=(-2., 2.), sample_time=self.deltaT)\n K_u = 20.\n T_u = 1621.33 / 1000. # ms\n # PD\n params_yaw = {'P': 0.8 * K_u,\n 'I': 0.,\n 'D': K_u * T_u / 10.,\n 'sp': self.target_yaw}\n self.yawPID = PID(params_yaw['P'], params_yaw['I'], params_yaw['D'],\n setpoint=params_yaw['sp'], output_limits=(-2., 2.),\n sample_time=self.deltaT, error_map=pi_clip)\n\n K_u = 20.\n T_u = 2668.8 / 1000. # ms\n # PD\n params_vert = {'P': 0.8 * K_u,\n 'I': 0.,\n 'D': K_u * T_u / 10.,\n 'sp': self.target_altitude}\n self.vertPID = PID(params_vert['P'], params_vert['I'],\n params_vert['D'], setpoint=params_vert['sp'],\n output_limits=(-5., 5.), sample_time=self.deltaT)\n\n return True","def simulate_1Dsystem(inps, mdps, method, potfunc, bcs, filetitle,\n makeplot, plot_freq, make_movie, ebound):\n\n steps = inps[0]\n dt = inps[1]\n x0 = inps[2]\n T = inps[3]\n m = inps[4]\n xmin = inps[5]\n xmax = inps[6]\n xinc = inps[7]\n kb = inps[13]\n winit = mdps[0]\n delta = mdps[1]\n hfreq = mdps[2]\n DT = mdps[3]\n w = np.array([0.0])\n bcs = bcs[0]\n dimension = potfunc.dimension\n if (make_movie == 'True'):\n if os.path.exists(filetitle+\"_movies\"):\n os.rmdir(filetitle+\"_movies\")\n os.mkdir(filetitle+\"_movies\")\n frame = 0\n os.chdir(filetitle+\"_movies\")\n\n gamma = inps[12] # Friction factor\n beta = 1 / T / (kb) # units of 1/kcal\n\n xlong = np.arange(xmin, xmax+xinc, xinc)\n coords = np.empty(int(steps))\n E = np.empty(int(steps))\n history = np.array([0.0])\n dep_count = 0\n time = np.array([0.0])\n walkerpot = np.array([0.0])\n\n pot_base = potfunc.get_potential(xlong)\n bias = np.zeros_like(pot_base)\n iv = potfunc.get_potential(x0)\n coords[0] = x0\n if makeplot == 'True':\n plt.plot(xlong, pot_base, '-b')\n plt.plot(x0, iv, 'ro', markersize=10)\n plt.axis([xmin, xmax, ebound[0],\n ebound[1]])\n plt.xlabel(\"CV(s)\")\n plt.ylabel(\"F\")\n plt.draw()\n plt.pause(0.0001)\n\n v0 = np.random.normal(0, 1, 1)\n T1 = m*v0**2/kb\n vscaled = v0 * (T/T1)**(0.5)\n p = vscaled * m\n # is_periodic = selected_bc(iv, selected_pot(x0)[1], coords[0])[4]\n\n FES = np.zeros_like(xlong)\n icount = np.zeros_like(xlong)\n\n E[0] = 0.5*p**2/m + iv\n\n info = ('Parameters: \\n' + 'Number of steps: ' + str(steps) + '\\n' +\n 'Initial x coordinate ' + str(x0) + '\\n' + 'Temperature ' +\n str(T) + '\\n' + 'Timestep ' + str(dt) + '\\n' +\n ' Initial Hill Height ' + str(winit) + '\\n' +\n 'Hill Width ' + str(delta) + '\\n' +\n 'Deposition Frequency (steps)' + str(hfreq) + '\\n' +\n 'Well Temperature ' + str(DT) + '\\n' + 'Gaussian ' + str(gamma) +\n '\\n' + 'Potential ' + str(potfunc))\n i = 0\n\n while i < steps - 1:\n\n if (method == \"Infrequent WT MetaD\"):\n (triggered, path) = potfunc.get_triggered(coords[i])\n\n if triggered is True:\n totaltime = time[i]\n teff = lf.calc_teff(walkerpot, beta, dt)\n for xc in range(0, xlong.size):\n bias[xc] = bias[xc]+lf.calc_biased_pot(xlong[xc],\n history[dep_count:],\n w[dep_count:],\n delta, dimension)\n [bins, FES] = lf.calc_FES_1D(coords, bias, xlong, method,\n beta, T, DT)\n\n init_center_point = int((x0 - np.min(bins))/(bins[1]-bins[0]))\n end_center_point = int((coords[i] - np.min(bins)) /\n (bins[1]-bins[0]))\n\n rare_E = FES[end_center_point]\n initial_E = FES[init_center_point]\n for a in range(-100, 100):\n if (end_center_point + a <= FES.size and\n end_center_point + a > 0):\n other_rare_E = FES[end_center_point + a]\n other_initial_E = FES[init_center_point + a]\n if other_rare_E > rare_E:\n rare_E = other_rare_E\n if other_initial_E < initial_E:\n initial_E = other_initial_E\n barrier = rare_E - initial_E\n\n return (totaltime, teff, info, path, barrier)\n\n if sp.mod(i, hfreq) == 0 and i > 0:\n if(i == hfreq):\n history[0] = coords[i]\n w[0] = winit\n if bcs.type == 'Periodic':\n history = bcs.add_depositions(coords[i], history)\n w = np.append(w, winit)\n w = np.append(w, winit)\n else:\n\n if method == 'Metadynamics':\n history = np.append(history, coords[i])\n w = np.append(w, winit)\n if bcs.type == 'Periodic':\n (history) = bcs.add_depositions(coords[i], history)\n w = np.append(w, winit)\n w = np.append(w, winit)\n elif (method == 'Well-Tempered Metadynamics' or\n method == \"Infrequent WT MetaD\"):\n VR = lf.calc_biased_pot(coords[i], history, w, delta,\n dimension)\n history = np.append(history, coords[i])\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\n if bcs.type == 'Periodic':\n (history) = bcs.add_depositions(coords[i], history)\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\n [pnew, vnew, newcoord, bcbias] = lf.integrate_step(coords[i], history,\n w, delta, DT,\n potfunc, bcs, p, m,\n dt, gamma, beta,\n dimension)\n p = pnew\n\n coords[i+1] = newcoord\n E[i+1] = 0.5 * p**2/m + vnew\n\n time = np.append(time, dt*(i+1))\n\n walkerpot = np.append(walkerpot, lf.calc_biased_pot(coords[i+1],\n history, w, delta,\n dimension)+bcbias)\n if method != \"Infrequent WT MetaD\":\n [FES, icount] = recreate_1DFES(FES, icount, coords[i+1],\n xinc, xmin, xmax, E[i+1])\n if makeplot == 'True' and sp.mod(i, plot_freq) == 0:\n\n for xc in range(0, xlong.size):\n\n bias[xc] = bias[xc] + lf.calc_biased_pot(xlong[xc],\n history[dep_count:],\n w[dep_count:],\n delta, dimension)\n walkv = vnew + lf.calc_biased_pot(coords[i+1], history, w, delta,\n dimension)\n # pdb.set_trace()\n\n dep_count = len(history)\n if len(history) == 1:\n dep_count = dep_count-1\n\n plt.clf()\n plt.plot(xlong, bias+pot_base, '-r')\n plt.plot(xlong, pot_base, '-b')\n plt.plot(coords[i+1], walkv, 'ro', markersize=10)\n plt.axis([xmin, xmax, ebound[0],\n ebound[1]])\n plt.xlabel(\"CV(s)\")\n plt.ylabel(\"F\")\n plt.draw()\n plt.pause(0.0001)\n if (make_movie == 'True'):\n filename = \"movieframe\" + str(frame)\n plt.savefig(filename + '.png', bbox_inches='tight')\n frame = frame + 1\n i = i + 1\n\n if(method != \"Infrequent WT MetaD\"):\n if dep_count < len(history):\n #pdb.set_trace()\n for xc in range(0, xlong.size):\n bias[xc] = bias[xc] + lf.calc_biased_pot(xlong[xc],\n history[dep_count:],\n w[dep_count:], delta, dimension)\n\n FES = lf.calc_FES_1D(coords, bias,\n xlong, method, beta, T, DT)\n rmsds = lf.calc_rmsd(FES[1], beta, pot_base)\n\n return (coords, E, FES, rmsds, info)\n\n elif(method == \"Infrequent WT MetaD\"):\n teff = 0\n info = info + 'NO RARE EVENT'\n totaltime = 0\n path = 'NULL'\n barrier = 0\n return (totaltime, teff, info, path, barrier)","def init_paramters(self):\r\n carb_bg_ratio = 5.0\r\n time_to_breakdown = 45.0\r\n insulin_bg_ratio = 50.0\r\n time_to_peak = 45.0\r\n basal_rate = 0.0\r\n digestion_speed = 1.0\r\n activation_speed = 1.0\r\n\r\n # set state to initial\r\n self.S = [self.carb_bg_ratio, self.time_to_breakdown,\r\n self.insulin_bg_ratio, self.time_to_peak,\r\n self.basal_rate, self.digestion_speed,\r\n self.activation_speed]","def init_for_run(self, stimulus):\n # Initialize training traces\n max_steps = self.settings['maxSteps']\n self.vars['S_trace'] = torch.zeros((max_steps, self.nSym, 1))\n self.vars['prev_s'] = torch.tensor(\n [float('inf')]) * torch.ones((self.nSym, 1))\n self.vars['Harmony_trace'] = torch.zeros(max_steps)\n self.vars['speed_trace'] = torch.zeros(max_steps)\n self.vars['ema_trace'] = torch.zeros(max_steps)\n self.vars['lambda_trace'] = torch.zeros(max_steps)\n self.vars['temp_trace'] = torch.zeros(max_steps)\n self.vars['TP_trace'] = list()\n self.vars['TPnum_trace'] = torch.zeros(max_steps)\n self.vars['TP_h_trace'] = torch.zeros(max_steps)\n self.vars['TP_dist_trace'] = torch.zeros(max_steps)\n self.vars['maxHarmony'] = torch.empty(\n self.grammar.nF, self.grammar.nR, self.nStimuli, self.settings['epochs']) # check this size\n\n # Create the representations for the stimulus\n stimulus = fortran_reshape(\n stimulus, (torch.numel(stimulus), 1)).double()\n #stimulus = stimulus.reshape((torch.numel(stimulus), 1)).double()\n # TPR representation of the external input\n self.inpS = self.TP.matmul(stimulus)\n #self.inpC = self.TP.T.matmul(self.inpS)\n self.inpC = self.toConceptual(self.inpS)\n\n # ----------- ALTERNATIVE ---------------------\n # Let's try the matrix version : TPR = Fillers * Bind * Roles\n #self.inpS = self.F.matmul(stimulus).matmul(self.R)\n #self.inpC = self.inpS @ torch.pinverse(self.R)\n # Reshape to make it suitable for MM.\n #self.inpC = self.inpC.reshape((self.inpC.numel(), 1))\n #self.inpS = self.inpS.reshape((self.inpS.numel(), 1))\n # ----------- END ALTERNATIVE ---------------------\n\n self.inpS = self.inpS.double()\n self.inpC = self.inpC.double()\n\n # Initialize state\n self.initial_state = self.settings['initStateMean'] + torch.normal(0.5, .2,\n (self.grammar.nF, self.grammar.nR)) * self.settings[\"initStateStdev\"]\n self.initial_state = self.initial_state.double()\n self.state = self.toNeural(self.initial_state)\n self.stateC = self.toConceptual(self.state)\n\n # Set Lambda and Temperature\n self.vars['T'] = self.vars['TInit']\n self.vars['lambda'] = self.vars['lambdaInit']\n self.vars['step'] = 0","def setUp(self):\n self.iv1 = Interval(1, 10)\n self.iv2 = Interval(5, 15)\n self.iv1_r = Interval(10, 1)\n self.iv2_r = Interval(15, 5)\n self.iv3 = Interval(3, 8)\n self.iv4 = Interval(11, 20)","def setup(cls):\n cls.logger = logging.getLogger('ModelTestLogger')\n cls.logger.setLevel(logging.DEBUG)\n\n s1 = model.Subject('subject1')\n s2 = model.Subject('subject2')\n\n cls.experiment = model.Experiment()\n cls.experiment.put_subject(s1)\n cls.experiment.put_subject(s2)\n\n setup1 = model.Setup(cls.experiment)\n modality1 = model.Modality(setup1, 20, 'emg')\n modality2 = model.Modality(setup1, 5, 'kin')\n\n model.Channel(modality1, 'brachoradialis')\n model.Channel(modality1, 'musculus sterno clavicularis')\n model.Channel(modality1, 'musculus rhombideus')\n model.Channel(modality1, 'musculus lattisimus')\n\n model.Channel(modality2, 'Pos-X')\n model.Channel(modality2, 'Pos-Y')\n model.Channel(modality2, 'Pos-Z')\n\n session1 = model.Session(cls.experiment, setup1, s1, 'session1')\n arr = np.column_stack((\n np.tile(\n np.concatenate((\n np.arange(0., 1., 0.1),\n np.arange(1., 0., -0.1)\n )),\n 10\n ),\n np.tile(\n np.concatenate((\n np.arange(10),\n np.arange(10, 0, -1)\n )),\n 10\n ),\n np.tile(\n np.concatenate((\n np.arange(0.0, 0.1, 0.01),\n np.arange(0.1, 0.0, -0.01)\n )),\n 10\n ),\n np.tile(\n np.concatenate((\n np.arange(0.5, 1.5, 0.1),\n np.arange(1.5, 0.5, -0.1)\n )),\n 10\n ),\n ))\n recording1 = model.Recording(session1, modality1, data=arr,\n identifier='emg_recording1')\n\n arr2 = np.column_stack((\n np.sum(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1),\n np.prod(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1),\n np.square(np.sum(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1))\n ))\n recording2 = model.Recording(session1, modality2, data=arr2,\n identifier='kin_recording1')\n for i in range(5):\n model.Trial(recording1, i * 2, 2)\n model.Trial(recording2, i * 2, 2)\n\n session2 = model.Session(cls.experiment, setup1, s2, 'session2')\n arr = np.add(arr, np.random.randn(*arr.shape))\n recording1 = model.Recording(session2, modality1, data=arr,\n identifier='emg_recording2')\n arr2 = np.column_stack((\n np.sin(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1))),\n np.cos(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1))),\n np.tan(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1)))\n ))\n recording2 = model.Recording(session2, modality2, data=arr2,\n identifier='kin_recording2')\n for i in range(5):\n model.Trial(recording1, i * 2, 2)\n model.Trial(recording2, i * 2, 2)","def set_IPlay3(self, stimulus, t, amp = None):\n \n if self.do_run:\n \n for m in self.tvecs:\n #m.destroy()\n del m \n del self.tvecs\n \n for m in self.ivecs:\n #m.destroy()\n del m \n del self.ivecs\n \n for m in self.plays:\n #m.destroy()\n del m \n del self.plays\n \n self.tvecs = []\n self.ivecs = []\n self.plays = []\n \n for j in self.a_celltype:\n \n if amp is None:\n amp0 = 0\n else:\n amp0 = amp[j]\n \n tvec = h.Vector(t/ms)\n self.tvecs.append(tvec) # add to list\n \n for i, gid in enumerate(self.gidlist[j]): # for every cell in the gidlist \n \n if isinstance(self.factor_celltype[j], ( int, long ) ): \n ivec = h.Vector(self.factor_celltype[j]*(stimulus*amp0)/nA) \n else:\n np.random.seed(gid*40)\n rnd.seed(gid*40)\n if self.factor_celltype[j][1] > 0:\n f = np.random.normal(self.factor_celltype[j][0], self.factor_celltype[j][1], 1).clip(min=0)\n else:\n f = self.factor_celltype[j][0] \n if self.factor_celltype[j][2] > 0: # add inverted input with 50% probability, in future versions this will indicate the propability for -1 and 1\n f = rnd.sample([-1,1],1)[0] * f\n if self.id == 0: print \"- inverted input with 50% probability:\", f \n if self.id == 0: print \"- randomize play stimulus height\" \n ivec = h.Vector(f*(stimulus*amp0)/nA)\n \n self.ivecs.append(ivec) # add to list \n \n #fluctuating current\n play = h.IClamp(self.cells[j][i].soma(0.5))\n play.delay = 0\n play.dur = 1e9\n ivec.play(play._ref_amp, tvec, 1)\n \n self.plays.append(play) # add to list\n \n if self.id == 0: print \"set_IPlay3 finished.\"","def run(config, tim=None):\n import common_lib\n import dr_lib\n import DST\n \n if tim is not None:\n tim.getTime(False)\n old_time = tim.getOldTime()\n\n if config.data is None:\n raise RuntimeError(\"Need to pass a data filename to the driver \"\\\n +\"script.\")\n\n # Read in geometry if one is provided\n if config.inst_geom is not None:\n if config.verbose:\n print \"Reading in instrument geometry file\"\n \n inst_geom_dst = DST.getInstance(\"application/x-NxsGeom\",\n config.inst_geom)\n else:\n inst_geom_dst = None\n\n config.so_axis = \"time_of_flight\"\n\n # Steps 1-3: Produce a scaled summed dark current dataset\n dc_som = dr_lib.scaled_summed_data(config.dkcur, config,\n dataset_type=\"dark_current\",\n timer=tim)\n\n # Perform Steps 3-6 on black can data\n if config.bcan is not None:\n b_som1 = dr_lib.calibrate_dgs_data(config.bcan, config, dc_som,\n dataset_type=\"black_can\",\n inst_geom_dst=inst_geom_dst,\n tib_const=config.tib_const,\n cwp=config.cwp_bcan,\n timer=tim)\n else:\n b_som1 = None\n\n # Perform Steps 3-6 on empty can data \n if config.ecan is not None:\n e_som1 = dr_lib.calibrate_dgs_data(config.ecan, config, dc_som,\n dataset_type=\"empty_can\",\n inst_geom_dst=inst_geom_dst,\n tib_const=config.tib_const,\n cwp=config.cwp_ecan,\n timer=tim)\n else:\n e_som1 = None\n\n # Perform Steps 3-6 on normalization data\n n_som1 = dr_lib.calibrate_dgs_data(config.data, config, dc_som,\n dataset_type=\"normalization\",\n inst_geom_dst=inst_geom_dst,\n tib_const=config.tib_const,\n cwp=config.cwp_data,\n timer=tim)\n\n # Perform Steps 7-16 on normalization data\n if config.norm_trans_coeff is None:\n norm_trans_coeff = None\n else:\n norm_trans_coeff = config.norm_trans_coeff.toValErrTuple()\n\n # Determine if we need to rebin the empty or black can data\n if config.ecan is not None and e_som1 is not None:\n ecan_cwp = True\n else:\n ecan_cwp = False\n\n if config.bcan is not None and b_som1 is not None:\n bcan_cwp = True\n else:\n bcan_cwp = False \n\n cwp_used = ecan_cwp or bcan_cwp\n\n n_som2 = dr_lib.process_dgs_data(n_som1, config, b_som1, e_som1,\n norm_trans_coeff,\n dataset_type=\"normalization\",\n cwp_used=cwp_used,\n timer=tim)\n \n del n_som1, b_som1, e_som1\n\n # Step 17: Integrate normalization spectra\n if config.verbose:\n print \"Integrating normalization spectra\"\n\n if tim is not None:\n tim.getTime(False)\n\n if config.norm_int_range is None:\n start_val = float(\"inf\")\n end_val = float(\"inf\")\n else:\n if not config.wb_norm:\n # Translate energy transfer to final energy\n ef_start = config.initial_energy.getValue() - \\\n config.norm_int_range[0]\n ef_end = config.initial_energy.getValue() - \\\n config.norm_int_range[1]\n # Convert final energy to final wavelength\n start_val = common_lib.energy_to_wavelength((ef_start, 0.0))[0]\n end_val = common_lib.energy_to_wavelength((ef_end, 0.0))[0]\n else:\n start_val = config.norm_int_range[0]\n end_val = config.norm_int_range[1]\n \n n_som3 = dr_lib.integrate_spectra(n_som2, start=start_val,\n end=end_val, width=True)\n\n del n_som2\n \n if tim is not None:\n tim.getTime(msg=\"After integrating normalization spectra \")\n\n file_comment = \"Normalization Integration range: %0.3fA, %0.3fA\" \\\n % (start_val, end_val)\n \n hlr_utils.write_file(config.output, \"text/num-info\", n_som3,\n output_ext=\"norm\",\n data_ext=config.ext_replacement,\n path_replacement=config.path_replacement,\n verbose=config.verbose,\n message=\"normalization values\",\n comments=[file_comment],\n tag=\"Integral\", units=\"counts\") \n \n if tim is not None:\n tim.getTime(False)\n\n if config.verbose:\n print \"Making mask file\"\n\n # Make mask file from threshold\n dr_lib.filter_normalization(n_som3, config.lo_threshold,\n config.hi_threshold, config)\n\n if tim is not None:\n tim.getTime(msg=\"After making mask file \")\n\n # Write out RMD file\n n_som3.attr_list[\"config\"] = config\n\n hlr_utils.write_file(config.output, \"text/rmd\", n_som3,\n output_ext=\"rmd\",\n data_ext=config.ext_replacement, \n path_replacement=config.path_replacement,\n verbose=config.verbose,\n message=\"metadata\")\n \n if tim is not None:\n tim.setOldTime(old_time)\n tim.getTime(msg=\"Total Running Time\")","def shooterPrep(oe0, oef, A, B, dt, scInfo, dynInfo, time, shooter, plot, body, grav, srp, thirdbod):\n\n # Normalizing based off dt1 and mu = 1\n shooterInfo = {} # dictionary for shooter functions\n shooterInfo['abtol'] = 1e-12\n shooterInfo['reltol'] = 1e-12\n shooterInfo['m0'] = scInfo['m0'] # kg, spacecraft mass\n t_norm = np.copy(dt) # s, time of first burn\n r_norm = (dynInfo['mu_host']*t_norm**2)**(1/3) # m\n shooterInfo['mu_host'] = dynInfo ['mu_host']/r_norm**3*t_norm**2\n\n # State\n meoe0_norm = af.oe2meoe(oe0)\n meoe0_norm[0] /= r_norm # m\n meoef_norm = af.oe2meoe(oef)\n meoef_norm[0] /= r_norm # m\n\n # Time\n shooterInfo['t0'] = dynInfo['t0']/t_norm # s\n dt_norm = np.copy(dt)/t_norm # s\n shooterInfo['manTime'] = np.sum(dt)/t_norm # s\n\n # BLT parameters\n A_norm = np.copy(A) # -\n B_norm = np.copy(B)*t_norm # 1/s\n\n # Constants\n if grav == False and srp == False and thirdbod == False:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host,)\n\n elif grav == True and srp == False and thirdbod == False:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n w_host = dynInfo['w_host']*t_norm # rad/s\n degree = dynInfo['degree'] # -\n order = dynInfo['order'] # -\n theta_gst = dynInfo['theta_gst'] # rad\n gc = dynInfo['gc'] # -\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, degree, order, theta_gst, gc, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, degree, order, theta_gst, gc)\n\n elif grav == False and srp == True and thirdbod == False:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_srp_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_srp_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n d_3B = dynInfo['d_3B']/r_norm # m\n r_3B = dynInfo['r_3B']/r_norm # m\n Cr = scInfo['Cr'] # -\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\n c = con.c/r_norm*t_norm # m/s\n AU = con.AU*1e3/r_norm # m\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, d_3B, r_3B, Cr, a2m, srp_flux, c, AU, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, d_3B, r_3B, Cr, a2m, srp_flux, c, AU)\n\n elif grav == False and srp == False and thirdbod == True:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_3bod_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_3bod_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\n d_3B = dynInfo['d_3B']/r_norm # m\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, mu_3B, d_3B, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, mu_3B, d_3B)\n\n elif grav == True and srp == True and thirdbod == False:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_srp_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_srp_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n w_host = dynInfo['w_host']*t_norm # rad/s\n d_3B = dynInfo['d_3B']/r_norm # m\n r_3B = dynInfo['r_3B']/r_norm # m\n degree = dynInfo['degree'] # -\n order = dynInfo['order'] # -\n theta_gst = dynInfo['theta_gst'] # rad\n gc = dynInfo['gc'] # -\n Cr = scInfo['Cr'] # -\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\n c = con.c/r_norm*t_norm # m/s\n AU = con.AU*1e3/r_norm # m\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU)\n\n elif grav == True and srp == False and thirdbod == True:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_3bod_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_3bod_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n w_host = dynInfo['w_host']*t_norm # rad/s\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\n d_3B = dynInfo['d_3B']/r_norm # m\n degree = dynInfo['degree'] # -\n order = dynInfo['order'] # -\n theta_gst = dynInfo['theta_gst'] # rad\n gc = dynInfo['gc'] # -\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, mu_3B, d_3B, degree, order, theta_gst, gc, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, mu_3B, d_3B, degree, order, theta_gst, gc)\n\n elif grav == False and srp == True and thirdbod == True:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_srp_3bod_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_srp_3bod_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\n d_3B = dynInfo['d_3B']/r_norm # m\n r_3B = dynInfo['r_3B']/r_norm # m\n Cr = scInfo['Cr'] # -\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\n c = con.c/r_norm*t_norm # m/s\n AU = con.AU*1e3/r_norm # m\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, mu_3B, d_3B, r_3B, Cr, a2m, srp_flux, c, AU, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, mu_3B, d_3B, r_3B, Cr, a2m, srp_flux, c, AU)\n\n elif grav == True and srp == True and thirdbod == True:\n # Dynamic Files\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_srp_3bod_blt_meoe \n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_srp_3bod_coast_meoe\n\n # Necessary Constants\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\n r_host = dynInfo['r_host']/r_norm # m\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\n w_host = dynInfo['w_host']*t_norm # rad/s\n d_3B = dynInfo['d_3B']/r_norm # m\n r_3B = dynInfo['r_3B']/r_norm # m\n degree = dynInfo['degree'] # -\n order = dynInfo['order'] # -\n theta_gst = dynInfo['theta_gst'] # rad\n gc = dynInfo['gc'] # -\n Cr = scInfo['Cr'] # -\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\n c = con.c/r_norm*t_norm # m/s\n AU = con.AU*1e3/r_norm # m\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\n isp = scInfo['isp']/t_norm # s\n\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, mu_3B, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU, g0, T, isp)\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, mu_3B, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU)\n\n return meoe0_norm, meoef_norm, A_norm, B_norm, dt_norm, shooterInfo, r_norm, t_norm","def Inject(self,injector):\n\n # Check that the table is set up\n # NOTE: Make sure singlestarLocation is set before you get here\n self._TableSetup()\n\n # Calculate the star's current age\n t = integrator.Integrator().time\n dt = integrator.Integrator().dt\n age = t-self._tbirth\n if age > 0.0:\n if self._wind:\n # Get energy and mass to inject\n energy, massloss = singlestar.star_winds(self._mass,age,dt)\n # Add mass FIRST since KE needs to be added elastically\n injector.AddMass(massloss)\n # Add energy to grid as kinetic energy\n injector.AddKE(energy)\n # Add some thermal energy to account for star's temperature\n # TODO: Add star's actual temperature\n Tstar = 40000.0 # K\n TE = 1.5 * units.kB * massloss/(units.mH/units.X)*Tstar\n injector.AddTE(TE)\n # Set the Courant condition\n ecourant, mcourant = singlestar.star_winds(self._mass,age,1.0)\n vwind = np.sqrt(2.0*ecourant/mcourant)\n integrator.Integrator().CourantLimiter(vwind)\n if self._radiation:\n #DO RAD\n nphotons = singlestar.star_radiation(self._mass,age,dt)\n # NOTE !!! ASSUMES 5 RADIATION BINS!!!\n # 1 = IR, 2 = optical+FUV, 3 = H-ionising, \n # 4 = HeI->HeII, 5 = HeII->HeIII and up\n nuv = np.sum(nphotons[2:5])\n injector.AddPhotons(nuv)","def __init__(self):\n super(Config, self).__init__()\n self.run_control[\"output_dir\"] = os.getcwd()+\"/output/arctan_baseline/single_turn_injection/tracking\"\n ring_tof = 1149.185123\n field_files = glob.glob(\"output/arctan_baseline/bump_quest_v9/find_bump_r_*_theta_90/find_bump_parameters_001.out\")\n substitutions = config.get_baseline_substitution(0.22, ring_tof)\n substitutions = self.ramp_fields(\n substitutions,\n field_files,\n [i for i, f in enumerate(field_files)],\n ring_tof,\n will_step = False\n )\n self.substitution_list = [substitutions] # used for plotting unperturbed CO\n\n self.run_control[\"find_closed_orbits_4d\"] = False\n self.run_control[\"find_da\"] = False\n self.run_control[\"find_bump_parameters\"] = False\n self.run_control[\"track_bump\"] = False\n self.run_control[\"track_beam\"] = True\n self.find_closed_orbits[\"subs_overrides\"][\"__n_turns__\"] = 0.11\n self.find_closed_orbits[\"subs_overrides\"][\"__do_bump__\"] = False\n self.find_closed_orbits[\"final_subs_overrides\"].update(substitutions)\n self.find_closed_orbits[\"max_iterations\"] = 0\n self.find_closed_orbits[\"do_minuit\"] = True\n self.find_closed_orbits[\"minuit_iterations\"] = 10 \n self.find_closed_orbits[\"us_cell\"] = 0\n self.find_closed_orbits[\"ds_cell\"] = 1\n\n self.find_da = {\n \"run_dir\":\"tmp/find_da/\",\n \"probe_files\":\"RINGPROBE01.h5\",\n \"subs_overrides\":{\"__n_turns__\":101.1, \"__do_magnet_field_maps__\":\"False\", \"__step_size__\":0.01},\n \"get_output_file\":\"get_da\",\n \"scan_output_file\":\"scan_da\",\n \"row_list\":None,\n \"scan_x_list\":[],\n \"scan_y_list\":[],\n \"x_seed\":1.,\n \"y_seed\":1.,\n \"min_delta\":0.9,\n \"max_delta\":1000.,\n \"required_n_hits\":100,\n \"dt_tolerance\":0.5, # fraction of closed orbit dt\n \"max_iterations\":15,\n \"decoupled\":True,\n }\n\n max_amp = 0.01\n self.track_beam_dummy = {\n \"run_dir\":\"tmp/track_beam/\",\n \"save_dir\":\"track_beam\",\n \"print_events\":[0, 1, -1],\n \"settings\":[{\n \"name\":\"forwards\",\n \"direction\":\"forwards\",\n \"probe_files\":\"RINGPROBE01.h5\", \n \"beam\":{\n \"type\":\"beam_gen\",\n \"closed_orbit_file\":\"closed_orbits_cache\",\n \"eigen_emittances\":[[0, 0]]*3,#+[[max_amp, max_amp]],\n \"n_per_dimension\":2,\n \"variables\":[\"x\",\"x'\",\"y\",\"y'\"],\n \"amplitude_dist\":\"uniform\", #\"grid\", # \n \"phase_dist\":\"uniform\", #\"grid\", # \n \"max_amplitude_4d\":max_amp, # amplitude_dist != grid\n \"energy\":3.0,\n },\n \"subs_overrides\":{\n \"__n_turns__\":45.1,\n \"__hdf5__\":\"True\",\n \"__do_magnet_field_maps__\":\"False\",\n \"__do_bump__\":\"True\",\n \"__step_size__\":0.01\n },\n },],\n }\n\n T0 = ring_tof\n self.track_beam = {\n \"run_dir\":\"tmp/track_beam/\",\n \"save_dir\":\"track_beam_rf_on_2\",\n \"print_events\":[i for i in range(1)],\n \"variables\":[\"x\", \"x'\", \"y\", \"y'\", \"t\", \"energy\"],\n \"settings\":[{\n \"name\":\"grid\",\n \"direction\":\"forwards\",\n \"probe_files\":\"RINGPROBE01.h5\", \n \"beam\":{\n \"type\":\"grid\",\n \"energy\":3.0,\n \"start\":[4357.646683446333, 0.0, -116.7090485272821, 0.0, 0.0, 941.272],\n \"stop\":[4357.646683446333, 0.0, -116.7090485272821, 0.0, T0, 941.272],\n \"nsteps\":[1, 1, 1, 1, 4+1, 1],\n },\n \"subs_overrides\":{\n \"__n_turns__\":100.1,\n \"__hdf5__\":True,\n \"__do_magnet_field_maps__\":False,\n \"__do_bump__\":True,\n \"__do_rf__\":True,\n \"__do_foil__\":False,\n \"__step_size__\":0.01\n },\n },],\n }","def test_single_ended_trans_att_synthetic():\n from dtscalibration import DataStore\n\n cable_len = 100.0\n nt = 50\n nx = 200\n time = np.arange(nt)\n x = np.linspace(0.0, cable_len, nx)\n ts_cold = np.ones(nt) * 4.0\n ts_warm = np.ones(nt) * 20.0\n ts_ambient = np.ones(nt) * 12\n ts_valid = np.ones(nt) * 16\n\n C_p = 15246\n C_m = 2400.0\n dalpha_r = 0.0005284\n dalpha_m = 0.0004961\n dalpha_p = 0.0005607\n gamma = 482.6\n cold_mask1 = np.logical_and(x > 0.125 * cable_len, x < 0.25 * cable_len)\n cold_mask2 = np.logical_and(x > 0.625 * cable_len, x < 0.75 * cable_len)\n warm_mask1 = np.logical_and(x > 0.75 * cable_len, x < 0.875 * cable_len)\n warm_mask2 = np.logical_and(x > 0.25 * cable_len, x < 0.375 * cable_len)\n valid_mask = np.logical_and(x > 0.40 * cable_len, x < 0.50 * cable_len)\n temp_real = np.ones((len(x), nt)) * 12 + 273.15\n temp_real[cold_mask1 + cold_mask2] = ts_cold + 273.15\n temp_real[warm_mask1 + warm_mask2] = ts_warm + 273.15\n temp_real[valid_mask] = ts_valid + 273.15\n\n st = (\n C_p\n * np.exp(-dalpha_r * x[:, None])\n * np.exp(-dalpha_p * x[:, None])\n * np.exp(gamma / temp_real)\n / (np.exp(gamma / temp_real) - 1)\n )\n ast = (\n C_m\n * np.exp(-dalpha_r * x[:, None])\n * np.exp(-dalpha_m * x[:, None])\n / (np.exp(gamma / temp_real) - 1)\n )\n\n # Add attenuation\n tr_att = np.random.rand(nt) * 0.2 + 0.8\n st[int(x.size * 0.4) :] *= tr_att\n tr_att2 = np.random.rand(nt) * 0.2 + 0.8\n st[int(x.size * 0.6) :] *= tr_att2\n\n ds = DataStore(\n {\n \"st\": ([\"x\", \"time\"], st),\n \"ast\": ([\"x\", \"time\"], ast),\n \"userAcquisitionTimeFW\": ([\"time\"], np.ones(nt)),\n \"cold\": ([\"time\"], ts_cold),\n \"warm\": ([\"time\"], ts_warm),\n \"ambient\": ([\"time\"], ts_ambient),\n },\n coords={\"x\": x, \"time\": time},\n attrs={\"isDoubleEnded\": \"0\"},\n )\n\n sections = {\n \"ambient\": [slice(0.52 * cable_len, 0.58 * cable_len)],\n \"cold\": [\n slice(0.125 * cable_len, 0.25 * cable_len),\n slice(0.65 * cable_len, 0.70 * cable_len),\n ],\n \"warm\": [slice(0.25 * cable_len, 0.375 * cable_len)],\n }\n\n ds_test = ds.copy(deep=True)\n\n # WLS\n ds_test.calibration_single_ended(\n sections=sections,\n st_var=1.0,\n ast_var=1.0,\n method=\"wls\",\n trans_att=[40, 60],\n solver=\"sparse\",\n )\n\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\n )\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\n )\n\n # test `trans_att` related functions\n # Clear out old results\n ds_test.set_trans_att([])\n\n assert ds_test.trans_att.size == 0, \"clear out trans_att config\"\n\n del_keys = []\n for k, v in ds_test.data_vars.items():\n if \"trans_att\" in v.dims:\n del_keys.append(k)\n\n assert len(del_keys) == 0, \"clear out trans_att config\"\n\n ds_test.calibration_single_ended(\n sections=sections,\n st_var=1.0,\n ast_var=1.0,\n method=\"wls\",\n trans_att=[40, 60],\n solver=\"sparse\",\n )\n\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\n )\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\n )\n\n ds_test = ds.copy(deep=True)\n\n # Test fixing gamma + transient att.\n ds_test.calibration_single_ended(\n sections=sections,\n st_var=1.0,\n ast_var=1.0,\n method=\"wls\",\n fix_gamma=(482.6, 0),\n trans_att=[40, 60],\n solver=\"sparse\",\n )\n\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=10)\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\n )\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\n )\n\n ds_test = ds.copy(deep=True)\n\n # Test fixing alpha + transient att.\n ds_test.calibration_single_ended(\n sections=sections,\n st_var=1.0,\n ast_var=1.0,\n method=\"wls\",\n fix_dalpha=(6.46e-05, 0),\n trans_att=[40, 60],\n solver=\"sparse\",\n )\n\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\n )\n assert_almost_equal_verbose(\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\n )","def setups():\n setups = []\n\n # If you run this in detailed mode, you need to set --t8 to 1e8\n kotani2017_F2 = dict()\n kotani2017_F2['name'] = 'kotani2017_F2'\n kotani2017_F2['piltemplate'] = kotani2017_F2_pil\n kotani2017_F2['pilparams'] = [None]\n kotani2017_F2['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\n kotani2017_F2['simulation'] = [\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=1'),\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=0.5'),\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=0.05')]\n kotani2017_F2['reporter'] = 'D'\n kotani2017_F2['exp_results'] = [(7733, 7.42), (11333, 6.18), (25533, 1.40)]\n setups.append(kotani2017_F2)\n\n\n\n # If you run this in detailed mode, you need to set --t8 to 1e8\n kotani2017_F3 = dict()\n kotani2017_F3['name'] = 'kotani2017_F3'\n kotani2017_F3['piltemplate'] = kotani2017_F3_pil\n kotani2017_F3['pilparams'] = [None]\n kotani2017_F3['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\n kotani2017_F3['simulation'] = [\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.1'),\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.01'),\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.001')]\n kotani2017_F3['reporter'] = 'D'\n kotani2017_F3['exp_results'] = [(21220, 7.72), (64203, 3.12), (86996, 0.69)]\n setups.append(kotani2017_F3)\n\n # If you run this in detailed mode, you need to set --t8 to 1e8\n kotani2017_F4 = dict()\n kotani2017_F4['name'] = 'kotani2017_F4'\n kotani2017_F4['piltemplate'] = kotani2017_F4_pil\n kotani2017_F4['pilparams'] = [None]\n kotani2017_F4['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\n kotani2017_F4['simulation'] = [\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.1'),\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.01'),\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.001'),\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0')]\n kotani2017_F4['reporter'] = 'D'\n kotani2017_F4['exp_results'] = [(6815, 6.06), (9004, 4.78), (10278, 4.03), (10795, 3.73)]\n setups.append(kotani2017_F4)\n\n return setups","def __init__(self,b,u,v,hbls_old,hbbl_old,Kv_old,Kt_old,srflx,sustr,svstr,f,grid_dict,tstep_mode,dt):\n \n # INPUTS FROM TTTW SYSTEM\n self.b = b #buoyancy field: [Ly,N]\n self.u = u # x-component of velocity [Ly,N]\n self.v = v # y-component of velocity [Ly+1,N]\n self.hbls_old = hbls_old #boundary layer depth from previous time step [Ly]\n self.hbbl_old = hbbl_old # bottom boundary layer depth from previous time step [Ly]\n self.Kv_old = Kv_old # momentum mixing coefficeint from previous time step [Ly,N+1]\n self.Kt_old = Kt_old # tracer mixing coefficient from previous time step [Ly,N+1]\n self.srflx = srflx #solar heat flux [Ly] (degC * (m/s))\n self.sustr = sustr # x-component surface wind stress [Ly] (N/m^2) \n self.svstr = svstr # y-component surface wind stress [Ly+1] (N/m^2)\n self.grid_dict = grid_dict #gridded data\n self.f = f #coriolis parameter\n # KPP-SPECIFIC VARIABLES \n self.hbls = np.zeros([self.b.shape[0]])\n self.hbbl = np.zeros([self.b.shape[0]])\n self.ustar = []\n self.bvf = [] \n self.kmo = []\n self.C_h_MO = []\n self.kbl = []\n self.Cr = [] \n self.Fc = []\n self.ghat = [] #NONLOCAL TERM: TO BE USED IN TIME STEPPING\n self.tstep_mode = tstep_mode# if in time steppign mode, turn on HBL_RATE_LIMIT\n self.dt = dt","async def setup_comp(opp):\n opp.config.units = IMPERIAL_SYSTEM\n assert await async_setup_component(\n opp, water_heater.DOMAIN, {\"water_heater\": {\"platform\": \"demo\"}}\n )\n await opp.async_block_till_done()","def piston_control(self):\n # At the beginning it is necessary to set some variables\n t_last = 0 # time of the last cycle\n inhale_end = time.time() - 1 # End of the last inhale\n self.cd[\"exhale_duration\"] = 1\n self.cd[\"inhale_duration\"] = 1\n #now = time.time()\n VCV_stage = 0\n PCV_stage = 0\n PSV_stage = 0\n emergency_contained = False\n\n # Gets the current volume and pressure before starting the cycles. If this doesn't work and \n # takes too long, there is probably some problem with the sensors\n t_P, P = (None, None)\n t_V, V = (None, None)\n P_V_t_limit = 5\n first_P_V = time.time()\n while P == None and V == None:\n if not self.prs.empty():\n t_P, P = self.prs.get()\n if not self.vol.empty():\n t_V, V = self.vol.get()\n if time.time() - first_P_V > P_V_t_limit:\n print(\"Took too long to receive new values of P or V from the queues\")\n # TODO Raise exception, error or return in this condition\n\n while True:\n # Gets the newest data and empties que queues. If there was no data, uses the values of \n # pressure or volume that it already has\n if not self.prs.empty():\n t_P, P = self.prs.get()\n while not self.prs.empty(): # Emptying the queue, only the most recent info is used\n dump = self.prs.get()\n\n if not self.vol.empty():\n t_V, V = self.vol.get()\n while not self.vol.empty(): # Emptying the queue, only the most recent info is used\n dump = self.vol.get()\n\n # TODO Needs to be obtained from the interface or defined in a configuration by the user\n T_inh_max = 60. / self.gui[\"VCV_frequency_spb\"].value() / 2\n\n if self.mode == 1: # 'VCV'\n \"\"\"\n This mode has 3 stages:\n 0 - Wait\n 1 - Inhale\n 2 - Exhale\n \"\"\"\n period = 60. / self.gui[\"VCV_frequency_spb\"].value()\n T_inh_max = period / 2\n if VCV_stage == 0: \n self.piston.stop()\n # If it's time for a new cycle, volume and pressure are within limits\n if (time.time() - t_last > period\n and V < self.gui[\"VCV_volume_spb\"].value()\n and P < self.gui[\"VCV_pressure_max_spb\"].value()):\n VCV_stage = 1\n inhale_start = time.time()\n # It is possible to calculate how long the last exhale took\n self.cd[\"exhale_duration\"] = inhale_start - inhale_end\n\n if VCV_stage == 1:\n # Checks if the current pressure is above P_max\n if P >= self.gui[\"VCV_pressure_max_spb\"].value():\n print(\"Pressure is too high during VCV cycle!\")\n self.piston.stop()\n # Checks if it reached the maximum inhale t\n elif time.time() - inhale_start >= T_inh_max:\n print(f\"VCV cycle is too long: {time.time() - inhale_start:.2f} s\")\n self.piston.stop()\n VCV_stage = 2\n inhale_end = time.time()\n # Checks whether the piston reached the bottom\n # TODO Define what happens in this case\n elif self.piston.piston_at_bottom:\n print(\"Reached max piston travel\")\n self.piston.stop()\n VCV_stage = 2\n inhale_end = time.time()\n # Checks if the current volume is above target\n # TODO Implement margin in options\n elif V >= self.gui[\"VCV_volume_spb\"].value() * 0.9:\n print(\"Reached target volume\")\n self.piston.stop()\n VCV_stage = 2 \n inhale_end = time.time()\n # if none of the previous limitations occured, may move the piston\n else:\n self.piston.pst_down()\n\n if VCV_stage == 2:\n # While the piston still hasn't reached the top\n # TODO Put timeout in piston raise time\n if not self.piston.piston_at_top and time.time() - t_last > period:\n self.piston.pst_up()\n else:\n self.piston.stop()\n VCV_stage = 0\n # Saves the last inhale start time to calculate when a new one should start\n t_last = inhale_start\n # It is possible to calculate how long the last inhale took\n self.cd[\"inhale_duration\"] = inhale_end - inhale_start\n\n elif self.mode == 2: # 'PCV'\n \"\"\"\n This mode has 3 stages:\n 0 - Wait\n 1 - Inhale\n 2 - Exhale\n \"\"\" \n period = 60. / self.gui[\"PCV_frequency_spb\"].value()\n T_inh_max = period / 2\n if PCV_stage == 0: \n self.piston.stop()\n # If it's time for a new cycle, volume and pressure are within limits\n if (time.time() - t_last > period\n and V < self.gui[\"PCV_volume_max_spb\"].value()\n and P < self.gui[\"PCV_pressure_spb\"].value()):\n PCV_stage = 1\n inhale_start = time.time()\n # It is possible to calculate how long the last exhale took\n self.cd[\"exhale_duration\"] = inhale_start - inhale_end\n\n if PCV_stage == 1:\n # Checks if the current volume is above max\n if V >= self.gui[\"PCV_volume_max_spb\"].value():\n print(\"Volume is too high during PCV cycle!\")\n self.piston.stop()\n # Checks if it reached the maximum inhale t\n elif time.time() - inhale_start >= T_inh_max:\n print(f\"PCV cycle is too long: {time.time() - inhale_start:.2f} s\")\n self.piston.stop()\n PCV_stage = 2\n inhale_end = time.time()\n # Checks whether the piston reached the bottom\n elif self.piston.piston_at_bottom:\n print(\"Reached max piston travel\")\n self.piston.stop()\n PCV_stage = 2\n inhale_end = time.time()\n # Checks if the current pressure is above target\n elif P >= self.gui[\"PCV_pressure_spb\"].value():\n print(\"Reached target pressure\")\n self.piston.stop()\n PCV_stage = 2 \n inhale_end = time.time()\n # if none of the previous limitations occured, may move the piston\n else:\n self.piston.pst_down()\n\n if PCV_stage == 2:\n # While the piston still hasn't reached the top\n if not self.piston.piston_at_top and time.time() - t_last > period:\n self.piston.pst_up()\n else:\n self.piston.stop()\n PCV_stage = 0\n # Saves the last inhale start time to calculate when a new one should start\n t_last = inhale_start\n # It is possible to calculate how long the last inhale took\n self.cd[\"inhale_duration\"] = inhale_end - inhale_start\n\n elif self.mode == 3: # 'PSV'\n \"\"\"\n This mode has 3 stages:\n 0 - Wait for inhale, P < threshold\n 1 - Inhale\n 2 - Exhale\n \"\"\"\n if PSV_stage == 0:\n self.piston.stop()\n # If the pressure is below the threshold, time to inhale\n if P < self.gui[\"PSV_sensitivity_spb\"].value():\n PSV_stage = 1\n inhale_start = time.time()\n # It is possible to calculate how long the last exhale took\n self.cd[\"exhale_duration\"] = inhale_start - inhale_end\n\n if PSV_stage == 1:\n # Checks if the current pressure is close to P_target\n if P >= self.gui[\"PSV_pressure_spb\"].value():\n print(\"Pressure reached target.\")\n self.piston.stop()\n PSV_stage = 2\n inhale_end = time.time()\n elif self.piston.piston_at_bottom:\n print(\"Reached max piston travel.\")\n self.piston.stop()\n PSV_stage = 2\n inhale_end = time.time()\n # if none of the previous limitations occured, may move the piston\n else:\n self.piston.pst_down()\n \n if PSV_stage == 2:\n # While the piston still hasn't reached the top\n if not self.piston.piston_at_top:\n self.piston.pst_up()\n else:\n self.piston.stop()\n PSV_stage = 0\n # Saves the last inhale start time to calculate when a new one should start\n t_last = inhale_start\n # It is possible to calculate how long the last inhale took\n self.cd[\"inhale_duration\"] = inhale_end - inhale_start\n\n # Emergency mode\n elif self.mode == 4: # 'Emergency'\n if not emergency_contained:\n self.piston.emergency()\n emergency_contained = True\n else:\n self.piston.stop()\n\n\n else: # Stop\n self.piston.stop()\n\n # Finds the indexes of data from the last cycle for flow and pressure\n # i_flw = np.where(time.time() - self.flw_data[0, :] < last_cycle_dur)[0]\n # i_prs = np.where(time.time() - self.prs_data[0, :] < last_cycle_dur)[0]\n \n # Sends the maximum pressure and volume in the last cycle to the interface\n self.cd[\"IE_ratio\"] = self.cd[\"exhale_duration\"] / self.cd[\"inhale_duration\"]\n # Saving the data for the GUI update\n # self.cd[\"peak_pressure\"] = peak_prs\n # self.cd[\"tidal_volume\"] = peak_vol\n self.signal_cycle_data.emit(self.cd)\n\n time.sleep(0.05)","def __init__(\n self,\n model_domain: ModelDomain,\n dt: Union[float, timedelta],\n rnday: Union[float, timedelta],\n ihfskip: int = None,\n dramp: Union[float, timedelta] = None,\n start_date: datetime = None,\n ibc: Union[Stratification, int, str] = Stratification.BAROTROPIC,\n drampbc: Union[float, timedelta] = None,\n stations: Stations = None,\n nspool: Union[int, timedelta] = None,\n nhot_write: Union[int, timedelta, bool] = None,\n server_config: ServerConfig = None,\n combine_hotstart: Union[str, os.PathLike] = None,\n cutoff_depth: float = 50.,\n **surface_outputs\n ):\n # init param.nml\n self._param = Param(model_domain, dt, rnday, dramp, start_date, ibc,\n drampbc, nspool, ihfskip, nhot_write, stations,\n **surface_outputs)\n\n # init bctides.in\n self._bctides = Bctides(model_domain, self.param,\n cutoff_depth=cutoff_depth)\n\n # init atmospheric data.\n self._nws = model_domain.nws\n\n # init hydrology data\n self._hydrology = model_domain.hydrology\n\n # init hotstart file\n self._combine_hotstart = combine_hotstart\n\n # init Makefile drivers\n self._makefile = MakefileDriver(server_config=server_config)","def __init__(self, para, ini_cond):\n\n # grid\n self.z = np.linspace(0, para['grid']['zmax'], para['grid']['Nlayers']) # grid [m] above ground\n self.dz = self.z[1] - self.z[0] # gridsize [m]\n self.ones = np.ones(len(self.z)) # dummy\n self.zref = para['zref'] # height of forcing data [m]\n \n # moss properties\n self.hc = para['hc'] # canopy height (m)\n self.lad = para['lad'] # shoot-area density (m2m-3)\n self.LAI = sum(self.lad*self.dz)\n \n self.canopy_nodes = np.where(self.lad > 0)[0]\n \n # hydraulic\n self.porosity = para['hydraulic']['porosity']\n self.pF = para['hydraulic']['pF']\n self.Ksat = para['hydraulic']['Ksat']\n self.freezing_curve = para['hydraulic']['freezing_curve']\n \n # radiation\n self.albedo = para['radiation'] # 'PAR', 'NIR'\n self.emissivity = para['radiation']['emissivity']\n self.clump = para['radiation']['clumping']\n self.leaf_angle = para['radiation']['leaf_angle']\n \n #self.radiation = para['radiation']\n \n # compute non-dimensional flow velocity Un = U/ust and momentum diffusivity\n Utop = ini_cond['Utop'] # U/ust at zref\n Ubot = 0.0 # no-slip\n self.Sc = para['Schmidt_nr']\n _, self.Un, self.Kmn, _ = closure_model_U_moss(self.z, self.lad, self.hc, Utop, Ubot) \n \n self.U = None\n self.Ks = None\n self.length_scale = para['length_scale']\n \n self.Switch_WMA = False\n \n # initial states\n self.T = ini_cond['T']\n self.Wtot = ini_cond['Wtot']\n self.Wliq, self.Wice, _ = frozen_water(self.T, self.Wot, fp=self.freezing_curve, To=0.0)\n self.h = water_retention(self.pF, theta=self.Wliq)","def setup(self):\n insts = []\n for i in range(2):\n r_date = dt.datetime(2009, 1, i + 1)\n insts.append(pysat.Instrument('pysat', 'testing',\n clean_level='clean',\n root_date=r_date))\n self.testC = pysat.Constellation(instruments=insts)\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\n self.testC.bounds = self.bounds\n self.testI.bounds = self.bounds\n\n # Define variables for 1D testing. A more limited set that only\n # depends upon 'mlt'. Other variables also include longitude, which\n # can differ between instruments when only binning by 'mlt'.\n self.one_d_vars = ['dummy1']\n self.unequal_one_d_vars = ['dummy2', 'dummy3']\n\n return","def setup(instname):\n global reducer, inst_name,van_mass,bleed_switch,rate,pixels\n # debugging (allows to reload changed DirectEnergyConversion package from Mantid)\n\n if instname=='MAR' or instname=='mar':\n print 'setup mari'\n inst_name='MAR'\n reducer = DRC.setup_reducer('MARI')\n bleed_switch=False\n rate=0.0\n pixels=0\n elif instname=='MER' or instname=='mer':\n print 'setup merlin'\n inst_name='MER'\n reducer = DRC.setup_reducer('MERLIN')\n bleed_switch=True\n rate=0.01\n pixels=80\n elif instname=='MAP' or instname=='map':\n print 'setup maps'\n inst_name='MAP'\n reducer = DRC.setup_reducer('MAPS')\n bleed_switch=False\n rate=0.0\n pixels=0.0\n elif instname=='LET' or instname=='let':\n print 'setup let'\n inst_name='LET'\n reducer = DRC.setup_reducer('LET')\n bleed_switch=True\n rate=0.01\n pixels=80\n elif instname=='ARCS' or instname=='arcs':\n print 'setup Arcs'\n inst_name='ARC'\n reducer = DRC.setup_reducer('ARCS')\n bleed_switch=False\n rate=0.01\n pixels=80\n elif instname=='SEQ' or instname=='seq':\n print 'setup Sequoia'\n inst_name='SEQ'\n reducer = DRC.setup_reducer('SEQUOIA')\n bleed_switch=False\n rate=0.01\n pixels=80\n elif instname=='CNCS' or instname=='cncs':\n print 'setup cncs'\n inst_name='SEQ'\n reducer = DRC.setup_reducer('CNCS')\n bleed_switch=False\n rate=0.01\n pixels=80\n elif instname=='HYSPEC' or instname=='hyspec':\n print 'setup hyspec'\n inst_name='SEQ'\n reducer = DRC.setup_reducer('HYSPEC')\n bleed_switch=False\n rate=0.01\n pixels=80\n else:\n print 'Instrument name not defined'\n return \n van_mass=reducer.get_default_parameter('vanadium-mass')","def main():\n \n # Particle in SHO - c.f. Mocz & Succi (2015) Fig. 2\n # parameters\n n = 100 # number of particles\n dt = 0.02 # timestep\n nt = 100 # number of timesteps\n nt_setup = 400 # number of timesteps to set up simulation\n n_out = 25 # plot solution every nout steps\n b = 4 # velocity damping for acquiring initial condition\n m = 1/n # mass of SPH particle ( m * n = 1 normalizes |wavefunction|^2 to 1)\n h = 40/n # smoothing length\n t = 0. # time\n\n # plot potential\n xx = np.linspace(-4.0, 4.0, num=400)\n xx = np.reshape(xx,(xx.size,1))\n fig = plt.plot(xx, 0.5*xx**2, linewidth=5, color=[0.7, 0.7, 0.9])\n \n # initialize\n x = np.linspace(-3.0, 3.0, num=n)\n x = np.reshape(x,(n,1))\n u = np.zeros((n,1))\n \n rho = density( x, m, h )\n P = pressure( x, rho, m, h )\n a = acceleration( x, u, m, rho, P, b, h )\n\n # get v at t=-0.5*dt for the leap frog integrator using Euler's method\n u_mhalf = u - 0.5 * dt * a\n\n # main loop (time evolution)\n for i in np.arange(-nt_setup, nt): # negative time (t<0, i<0) is used to set up initial conditions\n\n # leap frog\n u_phalf = u_mhalf + a*dt\n x = x + u_phalf*dt\n u = 0.5*(u_mhalf+u_phalf)\n u_mhalf = u_phalf\n if (i >= 0):\n t = t + dt\n print(\"%.2f\" % t)\n \n if (i == -1 ): # switch off damping before t=0\n u = np.zeros((n,1)) + 1.0\n u_mhalf = u\n b = 0 # switch off damping at time t=0\n \n # update densities, pressures, accelerations\n rho = density( x, m, h )\n P = pressure( x, rho, m, h )\n a = acceleration( x, u, m, rho, P, b, h)\n \n # plot solution every n_out steps\n if( (i >= 0) and (i % n_out) == 0 ):\n xx = np.linspace(-4.0, 4.0, num=400)\n xx = np.reshape(xx,(xx.size,1))\n rr = probeDensity(x, m, h, xx)\n rr_exact = 1./np.sqrt(np.pi) * np.exp(-(xx-np.sin(t))**2/2.)**2\n fig = plt.plot(xx, rr_exact, linewidth=2, color=[.6, .6, .6])\n fig = plt.plot(xx, rr, linewidth=2, color=[1.*i/nt, 0, 1.-1.*i/nt], label='$t='+\"%.2f\" % t +'$')\n # plot the t<0 damping process for fun\n if( i==-nt_setup or i==-nt_setup*3/4 or i==-nt_setup/2 ):\n xx = np.linspace(-4.0, 4.0, num=400)\n xx = np.reshape(xx,(xx.size,1))\n rr = probeDensity(x, m, h, xx)\n fig = plt.plot(xx, rr, linewidth=1, color=[0.9, 0.9, 0.9])\n \n plt.legend()\n plt.xlabel('$x$')\n plt.ylabel('$|\\psi|^2$')\n plt.axis([-2, 4, 0, 0.8])\n plt.savefig('solution.pdf', aspect = 'normal', bbox_inches='tight', pad_inches = 0)\n plt.close()"],"string":"[\n \"def setup(timestep=None, min_delay=None, max_delay=None, **kwargs):\\n global controller\\n\\n logger.info(\\\"PACMAN103 (c) 2014 APT Group, University of Manchester\\\")\\n logger.info(\\\" Release version 2014.4.1 - April 2014\\\")\\n # Raise an exception if no SpiNNaker machine is specified\\n if kwargs.has_key(\\\"machine\\\"):\\n machine_name = kwargs.get(\\\"machine\\\")\\n logger.warn(\\\"The machine name from kwargs is overriding the machine \\\"\\n \\\"name defined in the pacman.cfg file\\\")\\n elif conf.config.has_option(\\\"Machine\\\", \\\"machineName\\\"):\\n machine_name = conf.config.get(\\\"Machine\\\", \\\"machineName\\\")\\n else:\\n raise Exception(\\\"A SpiNNaker machine must be specified in pacman.cfg.\\\")\\n if machine_name == 'None':\\n raise Exception(\\\"A SpiNNaker machine must be specified in pacman.cfg.\\\")\\n\\n reload_time = None\\n if conf.config.has_option(\\\"Execute\\\", \\\"reload_date\\\"):\\n reload_time = conf.config.get(\\\"Execute\\\", \\\"reload_date\\\")\\n if reload_time != 'None':\\n logger.warn(\\\"The reload parameter was set, therefore not recompiling\\\")\\n else:\\n reload_time = None\\n\\n #deal with params allowed via the setup optimals\\n if timestep is not None:\\n timestep *= 1000 # convert into ms from microseconds\\n conf.config.set(\\\"Machine\\\", \\\"machineTimeStep\\\", timestep)\\n else:\\n timestep = conf.config.get(\\\"Machine\\\", \\\"machineTimeStep\\\")\\n if min_delay is not None and float(min_delay * 1000) < 1.0 * timestep:\\n raise exceptions.ConfigurationException(\\\"Pacman does not support min \\\"\\n \\\"delays below {} ms with the current \\\"\\n \\\"machine time step\\\".format(1.0 * timestep))\\n\\n natively_supported_delay_for_models = MAX_SUPPORTED_DELAY_TICS\\n delay_extention_max_supported_delay = MAX_DELAY_BLOCKS * MAX_TIMER_TICS_SUPPORTED_PER_BLOCK\\n\\n max_delay_tics_supported = \\\\\\n natively_supported_delay_for_models + delay_extention_max_supported_delay\\n\\n if max_delay is not None and float(max_delay * 1000) > max_delay_tics_supported * timestep:\\n raise exceptions.ConfigurationException(\\\"Pacman does not support max delays \\\"\\n \\\"above {} ms with the current machine \\\"\\n \\\"time step\\\".format(0.144 * timestep))\\n if min_delay is not None:\\n conf.config.add_section(\\\"Model\\\")\\n conf.config.set(\\\"Model\\\", \\\"min_delay\\\", (min_delay * 1000) / timestep)\\n\\n if max_delay is not None:\\n if not conf.config.has_section(\\\"Model\\\"):\\n conf.config.add_section(\\\"Model\\\")\\n conf.config.set(\\\"Model\\\", \\\"max_delay\\\", (max_delay * 1000) / timestep)\\n\\n time_scale_factor = None\\n if (conf.config.has_option(\\\"Machine\\\", \\\"timeScaleFactor\\\") and\\n conf.config.get(\\\"Machine\\\", \\\"timeScaleFactor\\\") != \\\"None\\\"):\\n time_scale_factor = conf.config.getint(\\\"Machine\\\", \\\"timeScaleFactor\\\")\\n if timestep * time_scale_factor < 1000:\\n logger.warn(\\\"the combination of machine time step and the machine \\\"\\n \\\"time scale factor results in a real timer tic that is \\\"\\n \\\"currently not reliably supported by the spinnaker \\\"\\n \\\"machine.\\\")\\n else:\\n time_scale_factor = max(1, math.ceil(1000.0 / float(timestep)))\\n if time_scale_factor > 1:\\n logger.warn(\\\"A timestep was entered that has forced pacman103 to \\\"\\n \\\"automatically slow the simulation down from real time \\\"\\n \\\"by a factor of {}. To remove this automatic behaviour\\\"\\n \\\", please enter a timescaleFactor value in \\\"\\n \\\"your .pacman.cfg\\\".format(time_scale_factor))\\n\\n\\n\\n\\n \\n # Create a new Controller to run PyNN:\\n controller = control.Controller(sys.modules[__name__],\\n machine_name, reload_time=reload_time)\\n # Set the app ID:\\n appID = conf.config.getint(\\\"Machine\\\", \\\"appID\\\")\\n controller.dao.app_id = appID\\n logger.info(\\\"Setting appID to %d.\\\" % appID)\\n # Set the machine time step for the simulation:\\n machineTimeStep = conf.config.getint(\\\"Machine\\\", \\\"machineTimeStep\\\")\\n controller.dao.machineTimeStep = machineTimeStep\\n logger.info(\\\"Setting machine time step to %d micro-seconds.\\\" % machineTimeStep)\\n controller.dao.time_scale_factor = time_scale_factor\\n logger.info(\\\"Setting time scale factor to %d.\\\" % time_scale_factor)\\n # Set boolean variable writeTextSpecs in DAO if we are required to:\\n writeTextSpecs = False\\n if conf.config.getboolean(\\\"Reports\\\", \\\"reportsEnabled\\\"):\\n writeTextSpecs = conf.config.getboolean(\\\"Reports\\\", \\\"writeTextSpecs\\\")\\n controller.dao.writeTextSpecs = writeTextSpecs\\n\\n if conf.config.has_option(\\\"Recording\\\", \\\"send_live_spikes\\\"):\\n if conf.config.getboolean(\\\"Recording\\\", \\\"send_live_spikes\\\") == True:\\n port = None\\n if conf.config.has_option(\\\"Recording\\\", \\\"live_spike_port\\\"):\\n port = conf.config.getint(\\\"Recording\\\", \\\"live_spike_port\\\")\\n hostname = \\\"localhost\\\"\\n if conf.config.has_option(\\\"Recording\\\", \\\"live_spike_host\\\"):\\n hostname = conf.config.get(\\\"Recording\\\", \\\"live_spike_host\\\")\\n tag = None\\n if conf.config.has_option(\\\"Recording\\\", \\\"live_spike_tag\\\"):\\n tag = conf.config.getint(\\\"Recording\\\", \\\"live_spike_tag\\\")\\n if tag == None:\\n raise exceptions.PacmanException(\\\"Target tag for live spikes \\\"\\n \\\"has not been set\\\")\\n\\n # Set up the forwarding so that monitored spikes are sent to the\\n # requested location\\n controller.set_tag_output(tag, port, hostname, 10)\\n #takes the same port for the visualiser if being used\\n if conf.config.getboolean(\\\"Visualiser\\\", \\\"enable\\\") and \\\\\\n conf.config.getboolean(\\\"Visualiser\\\", \\\"have_board\\\"):\\n controller.set_visulaiser_port(port)\\n \\n # Create special AppMonitor vertex, to receive spikes for immediate \\n # transfer to host:\\n monitorVertex = AppMonitor()\\n \\n # Add the special vertex to the list of vertices:\\n controller.add_vertex(monitorVertex)\\n \\n # Get track of this special vertex as it will be used as a target\\n # for recorded spikes:\\n global appMonitorVertex\\n appMonitorVertex = monitorVertex\\n\\n # PyNN API says something must be returned, \\n # so we return something useful: our controller instance\\n return controller\",\n \"def __init__(self,n,\\n d=3,\\n maxn=125,\\n controllers=[],\\n xmax=XMAX,\\n ymax=YMAX,\\n zmax=ZMAX,\\n vmax=VMAX,\\n simbox=None,\\n mass=1.0,\\n rinit=None,\\n source=None,\\n side=(5,5,5),\\n integrator='rk4',\\n spacing=0.1):\\n self.n = n\\n self.dim = d\\n self.maxn = maxn\\n self.dt = 0.0\\n self.steps = 0\\n\\n # Basic mechanical properties\\n if not simbox:\\n self.box = box.MirrorBox(p=self,xmax=xmax,ymax=ymax,zmax=zmax)\\n else:\\n self.box = simbox\\n \\n # Select integrator\\n integrator_mapping = {'euler':euler,\\n 'ieuler':imp_euler,\\n 'rk4':rk4}\\n\\n self.step = integrator_mapping[integrator]\\n\\n # Start with a random configuration\\n self.r = self.box.xmax * np.random.random([self.maxn,self.dim])\\n self.m = np.zeros(self.maxn,dtype=float)\\n self.v = vmax * (np.random.random([self.maxn,self.dim]) - 0.5)\\n self.rdot = np.zeros(self.r.shape)\\n self.vdot = np.zeros(self.v.shape)\\n self.mdot = np.zeros(self.m.shape)\\n\\n if rinit == 'grid':\\n self.r[0:n,:] = configuration.grid3d(n,side,(xmax/2.,ymax/2.,zmax/2.)\\n ,spacing=spacing)\\n elif rinit == 'fcc':\\n self.r[0:n,:] = configuration.fcc3d(n,side,(xmax/2.,ymax/2.,zmax/2.)\\n ,spacing=spacing)\\n elif rinit == 'load':\\n # Load the configuration from a target.\\n # Today the target is hard-coded\\n source = os.environ.get('SPDATA') + '/' + source #nanobox_eq_2.nc'\\n read_step(source,self,step='last')\\n # Make some assumptions about the source file.\\n\\n # Initialise values\\n #self.r[0:self.n]=configuration.grid3d(self.n,5,5,(20,20,20),spacing=0.8)\\n self.m[:] = mass \\n self.colour = 1.0,0.0,0.0 \\n\\n # State vectors to pass to numerical integrators\\n n_variables = 7\\n self.x = np.zeros([n_variables,self.maxn])\\n self.xdot = np.zeros([n_variables,self.maxn])\\n\\n self.nlists = []\\n self.forces = []\\n\\n self.controllers = controllers\\n for controller in self.controllers:\\n controller.bind_particles(self)\\n\\n \\\"\\\"\\\" Variables for measuring performance. \\\"\\\"\\\"\\n self.timing = {}\\n self.timing['force time'] = -1\\n self.timing['deriv time'] = -1\\n self.timing['pairsep time'] = -1\\n self.timing['update time'] = -1\\n self.timing['integrate time'] = -1\",\n \"def startup(self):\\n # Initializing the cycle data (cd) dictionary\\n self.cd[\\\"started_up\\\"] = False\\n self.cd[\\\"peak_pressure\\\"] = 0\\n self.cd[\\\"tidal_volume\\\"] = 0\\n self.cd[\\\"inhale_duration\\\"] = 0\\n self.cd[\\\"exhale_duration\\\"] = 0\\n self.cd[\\\"IE_ratio\\\"] = 1\\n self.cd[\\\"PEEP\\\"] = 0\\n\\n to = 2 # Timeout\\n startup_cycles = 0\\n limit = 20\\n # If the piston position is unknown\\n last_cycle = time.time()\\n while not self.piston.piston_at_bottom and not self.piston.piston_at_top:\\n if self.pst_dir == 1:\\n self.piston.pst_up()\\n if time.time() - last_cycle > to:\\n self.pst_dir = 0\\n startup_cycles += 1\\n last_cycle = time.time()\\n else:\\n self.piston.pst_down()\\n if time.time() - last_cycle > to:\\n self.pst_dir = 1\\n startup_cycles += 1\\n last_cycle = time.time()\\n if startup_cycles >= limit:\\n print(\\\"There is a problem at startup, check compressed air\\\")\\n print(f\\\"Tried to startup for {startup_cycles} cycles\\\")\\n # Breaks the loop so that the controller doesn't start\\n self.signal_startup_error.emit(True)\\n return\\n while not self.piston.piston_at_top:\\n self.piston.pst_up()\\n self.piston.stop()\\n\\n print(f\\\"startup_cycles: {startup_cycles}\\\")\\n self.cd[\\\"started_up\\\"] = True\\n self.signal_cycle_data.emit(self.cd)\\n # Duration of the first tare of the system\\n tare_duration = 5.0\\n time.sleep(tare_duration)\\n self.signal_get_tare.emit(tare_duration)\\n # Waits a little bit just to make sure that the respirator isn't working when the controller \\n # is called\\n time.sleep(0.5)\\n self.piston_control()\",\n \"def setup_ssem(self):\\n \\n groundBox = box_polygon_shape(-20,-500,1,1) # A tiny box that just acts as the ground body for everything else\\n groundBody = self.world.CreateStaticBody(shapes=groundBox)\\n self.memory_sender_y = -500\\n self.groundBody = groundBody\\n # Initial charge for main injector\\n self.ball_bearing_block(0,190,cols=16)\\n self.add_static_polygon([ (0,20), (100,0), (100,5), (0,25)], -132, 220)\\n self.add_static_polygon([ (0,0), (3,0), (3,20), (0,20)], -132, 240)\\n self.injector_cranks = []\\n self.parts.main_injector_raiser = self.injector(-32,150, groundBody, injector_crank_array=self.injector_cranks)\\n\\n (self.parts.memory_selector_holdoff, self.parts.memory_follower_holdoff) = self.memory_module(0,0, groundBody)\\n self.upper_regenerators = []\\n self.parts.accumulator_diverter_lever = self.diverter_set(0,130, groundBody, slope_x=-240, slope_y=180, return_weight=10) # Diverter 1. Splits to subtractor reader.\\n\\n self.parts.discard_lever_2 = self.diverter_set(-5,-30, groundBody, discard=470) # Diverter 2a. Discard reader-pulse data.\\n self.parts.upper_regen_control = self.regenerator(-5,-65, groundBody, self.upper_regenerators) # Regenerator 1. For regenning anything read from memory.\\n self.parts.ip_diverter_lever = self.diverter_set(-5,-95, groundBody, slope_x=320, slope_y=170, start_at=3, return_weight=5) # Diverter 1. Splits to instruction counter.\\n self.parts.diverter_3 = self.diverter_set(-10,-158, groundBody, slope_x=200, slope_y=310) # Diverter 3; splits to instruction reg/PC\\n \\n # PC injector\\n pc_injector_x = 230\\n pc_injector_y = -290\\n self.pc_injector_cranks = [] \\n self.parts.pc_injector_raiser = self.injector(pc_injector_x,pc_injector_y, groundBody, injector_crank_array=self.pc_injector_cranks, columns=5)\\n # Initial charge for PC injector\\n self.ball_bearing_block(250,-240,cols=8)\\n\\n\\n sub_pos_x = -15\\n sub_pos_y = -220\\n self.parts.accumulator_reset_lever = self.subtractor(sub_pos_x,sub_pos_y, groundBody, discard_bands=True, toggle_joint_array=self.accumulator_toggles, comparison_output=True)\\n self.dropper = self.slow_drop_unit(groundBody, sub_pos_x-18, sub_pos_y+40)\\n\\n # The 'skip lever' - the large balance arm which injects one\\n # into the program counter when comparison (CMP) succeeds\\n skip_lever_x = sub_pos_x - 200\\n skip_lever_y = sub_pos_y - 200\\n a = fixtureDef(shape=polygonShape(vertices=[(-50,-32), (0,-30), (0,-25), (-50,-30)]), filter=filters[0], density=1.0)\\n b = fixtureDef(shape=box_polygon_shape(0,-30,5,30), filter=filters[0], density=1.0)\\n c = fixtureDef(shape=box_polygon_shape(-30,-30,5,30), filter=filters[0], density=1.0)\\n d = fixtureDef(shape=box_polygon_shape(0,0,300,5), filter=filters[2], density=1.0)\\n e = fixtureDef(shape=box_polygon_shape(285,-15,15,15), filter=filters[2], density=2.10)\\n f = fixtureDef(shape=box_polygon_shape(150,-50,5,50), filter=filters[0], density=1.0)\\n skip_lever=self.add_multifixture([a,b,d,e,f], skip_lever_x, skip_lever_y)\\n skip_lever.attachment_point = (150,-50)\\n skip_lever.origin = (skip_lever_x,skip_lever_y)\\n\\n self.revolving_joint(groundBody, skip_lever, (skip_lever_x+150, skip_lever_y+2.5), friction=0)\\n self.add_static_polygon(polygonShape(vertices=box_vertices(0, 0, 10,10)), skip_lever_x+270, skip_lever_y-15, filter=filters[2])\\n self.parts.cmp_injector = self.horizontal_injector(skip_lever_x-48,skip_lever_y+257, groundBody)\\n self.ball_bearing_block(skip_lever_x-30,skip_lever_y+280,cols=1)\\n self.add_static_polygon(polygonShape(vertices=[(0,0), (20,0), (0,20)]), skip_lever_x-30,skip_lever_y+230)\\n \\n self.lower_regenerators = []\\n self.parts.lower_regen_control = self.regenerator(-203,-400, groundBody, self.lower_regenerators)\\n #Program counter\\n self.parts.pc_reset_lever = self.subtractor(400,-320, groundBody, lines=5, toggle_joint_array=self.ip_toggles, is_actually_adder=True)\\n # Thing that adds one ball bearing to the PC\\n pc_incrementer_x = 457\\n pc_incrementer = self.horizontal_injector(pc_incrementer_x,-240, groundBody)\\n # Overspill loose ball bearings from the PC incrementer to the PC reader\\n overspill_width = pc_incrementer_x - pc_injector_x - 125\\n self.add_static_polygon([ (0, 0), (overspill_width,15), (overspill_width,20), (0,5) ], pc_injector_x+125,pc_injector_y+65)\\n\\n # Block to stop right-side overspill on incrementer\\n self.add_static_polygon([ (0, 0), (5,0), (5,20), (0,20) ], pc_incrementer_x+27,-240+40)\\n\\n\\n self.ball_bearing_block(457+20,-250+30,cols=1)\\n self.distance_joint(skip_lever, pc_incrementer)\\n\\n self.connect_regenerators()\\n\\n # Large collection plates at the bottom\\n self.add_static_polygon([ (-300,-600),(700,-550), (700,-610), (-300,-610)])\\n self.add_static_polygon([ (600,-610),(700,-610), (850,-400), (800,-400)])\\n self.add_static_polygon([ (-500,-400),(-450,-400), (-310,-610), (-400,-610)])\\n\\n # Instruction decoder ROM\\n self.rom_followers = []\\n self.rom_selectors = []\\n (self.parts.instruction_selector_holdoff, self.parts.instruction_follower_holdoff) = self.add_row_decoder(200, 0, groundBody, self.rom_followers, self.rom_selectors)\\n self.labels.append((\\\"Instruction decoder\\\", 400,0,0))\\n\\n self.add_instruction_cranks(groundBody, 550, 140)\\n self.parts.sender_eject = self.memory_sender(198,self.memory_sender_y, groundBody)\\n self.connect_memory()\\n\\n # A guard which stops waste data from the subtractor falling into the instruction register\\n self.add_static_polygon([ (0,0), (120,120), (120,123), (0,3)], 120, self.memory_sender_y-10)\\n\\n # Add one final transfer band to move everything back into band 0\\n self.transfer_bands.append((-550+10, -550, [ (-300,800)], 1))\",\n \"def setup(self, tau1=None, tau2=None, template_tmax=None, dt=None, \\n delay=0.0, sign=1, eventstartthr=None, risepower=4., min_event_amplitude=2.0):\\n assert sign in [-1, 1]\\n self.sign = sign\\n self.taus = [tau1, tau2]\\n self.dt = dt\\n self.template_tmax = template_tmax\\n self.idelay = int(delay/dt) # points delay in template with zeros\\n self.template = None # reset the template if needed.\\n self.eventstartthr = eventstartthr\\n self.risepower = risepower\\n self.min_event_amplitude = min_event_amplitude\",\n \"def setup(self):\\n\\n self._enable_torque(self._reg.TORQUE_ENABLE)\\n self.change_operating_mode(self._reg.MODE_EXT_POSI)\\n # set to max velocity\\n self.change_veloity(self._default_velocity)\",\n \"def prepare_experiment(assumptions):\\n print(\\\"\\\\nGenerate species parameters\\\")\\n np.random.seed(assumptions['seed']) \\n params = MakeParams(assumptions) \\n if assumptions[\\\"selected_function\\\"] == \\\"f5_invader_suppression\\\":\\n print(\\\"\\\\nDraw invader feature\\\")\\n params = create_invader(params, assumptions)\\n print(params[\\\"c\\\"])\\n \\n print(\\\"\\\\nDraw per-capita function and cost\\\")\\n f1_species_smooth, f1_species_rugged, f2_species_smooth, f2_species_rugged = draw_species_function(assumptions)\\n params.update({\\\"f1_species_smooth\\\": f1_species_smooth, \\\"f1_species_rugged\\\": f1_species_rugged, \\\"f2_species_smooth\\\": f2_species_smooth, \\\"f2_species_rugged\\\": f2_species_rugged})\\n gi = draw_species_cost(f1_species_smooth, assumptions)\\n params.update({\\\"g\\\": gi})\\n \\n print(\\\"\\\\nConstruct plate\\\")\\n np.random.seed(assumptions['seed']) \\n plate = make_plate(assumptions,params)\\n \\n print(\\\"\\\\nAdd community function to plate\\\")\\n plate = add_community_function(plate, assumptions, params)\\n \\n if not pd.isnull(assumptions[\\\"overwrite_plate\\\"]) :\\n print(\\\"\\\\nUpdating the initial plate composition by overwrite_plate\\\")\\n plate = overwrite_plate(plate, assumptions)\\n \\n print(\\\"\\\\nPrepare Protocol\\\")\\n #Extract Protocol from protocol database\\n algorithms = make_algorithms(assumptions)\\n params_algorithm = algorithms[algorithms['algorithm_name'] == assumptions['protocol']]\\n \\n #Params_simulation by default contains all assumptions not stored in params.\\n params_simulation = dict((k, assumptions[k]) for k in assumptions.keys() if k not in params.keys())\\n \\n return params, params_simulation , params_algorithm, plate\",\n \"def setup(self, tau1=None, tau2=None, template_tmax=0.05, dt=None, \\n delay=0.0, sign=1, eventstartthr=None, risepower=4.0, min_event_amplitude=2.0):\\n assert sign in [-1, 1]\\n self.sign = sign\\n self.taus = [tau1, tau2]\\n self.dt = dt\\n self.template_tmax = template_tmax\\n self.idelay = int(delay/dt) # points delay in template with zeros\\n self.template = None # reset the template if needed.\\n self.eventstartthr = eventstartthr\\n self.risepower = risepower\\n self.min_event_amplitude = min_event_amplitude\",\n \"def setup(env, channel, interT, station, mean):\\r\\n network = Network(env, channel)\\r\\n system = System(env, network, station, mean)\\r\\n transmitList = []\\r\\n \\r\\n while True:\\r\\n system.stations\",\n \"def __init__(self,\\n setup,\\n host=None,\\n dof=6,\\n control_type='position',\\n derivative_type='none',\\n target_type='position',\\n reset_type='random',\\n reward_type='linear',\\n deriv_action_max=10,\\n first_deriv_max=10, # used only with second derivative control\\n vel_penalty=0,\\n obs_history=1,\\n actuation_sync_period=1,\\n episode_length_time=None,\\n episode_length_step=None,\\n rllab_box = False,\\n servoj_t=ur_utils.COMMANDS['SERVOJ']['default']['t'],\\n servoj_gain=ur_utils.COMMANDS['SERVOJ']['default']['gain'],\\n speedj_a=ur_utils.COMMANDS['SPEEDJ']['default']['a'],\\n speedj_t_min=ur_utils.COMMANDS['SPEEDJ']['default']['t_min'],\\n movej_t=2, # used for resetting\\n accel_max=None,\\n speed_max=None,\\n dt=0.008,\\n delay=0.0, # to simulate extra delay in the system\\n **kwargs):\\n\\n\\n # Check that the task parameters chosen are implemented in this class\\n assert dof in [2, 6]\\n assert control_type in ['position', 'velocity', 'acceleration']\\n assert derivative_type in ['none', 'first', 'second']\\n assert target_type in ['position', 'angle']\\n assert reset_type in ['random', 'zero', 'none']\\n assert actuation_sync_period >= 0\\n\\n if episode_length_step is not None:\\n assert episode_length_time is None\\n self._episode_length_step = episode_length_step\\n self._episode_length_time = episode_length_step * dt\\n elif episode_length_time is not None:\\n assert episode_length_step is None\\n self._episode_length_time = episode_length_time\\n self._episode_length_step = int(episode_length_time / dt)\\n else:\\n #TODO: should we allow a continuous behaviour case here, with no episodes?\\n print(\\\"episode_length_time or episode_length_step needs to be set\\\")\\n raise AssertionError\\n\\n # Task Parameters\\n self._host = setups[setup]['host'] if host is None else host\\n self._obs_history = obs_history\\n self._dof = dof\\n self._control_type = control_type\\n self._derivative_type = derivative_type\\n self._target_type = target_type\\n self._reset_type = reset_type\\n self._reward_type = reward_type\\n self._vel_penalty = vel_penalty # weight of the velocity penalty\\n self._deriv_action_max = deriv_action_max\\n self._first_deriv_max = first_deriv_max\\n self._speedj_a = speedj_a\\n self._delay = delay\\n self.return_point = None\\n if accel_max==None:\\n accel_max = setups[setup]['accel_max']\\n if speed_max==None:\\n speed_max = setups[setup]['speed_max']\\n if self._dof == 6:\\n self._joint_indices = [0, 1, 2, 3, 4, 5]\\n self._end_effector_indices = [0, 1, 2]\\n elif self._dof == 2:\\n self._joint_indices = [1, 2]\\n self._end_effector_indices = [1, 2]\\n\\n # Arm/Control/Safety Parameters\\n self._end_effector_low = setups[setup]['end_effector_low']\\n self._end_effector_high = setups[setup]['end_effector_high']\\n self._angles_low = setups[setup]['angles_low'][self._joint_indices]\\n self._angles_high = setups[setup]['angles_high'][self._joint_indices]\\n self._speed_low = -np.ones(self._dof) * speed_max\\n self._speed_high = np.ones(self._dof) * speed_max\\n self._accel_low = -np.ones(self._dof) * accel_max\\n self._accel_high = np.ones(self._dof) * accel_max\\n\\n self._box_bound_buffer = setups[setup]['box_bound_buffer']\\n self._angle_bound_buffer = setups[setup]['angle_bound_buffer']\\n self._q_ref = setups[setup]['q_ref']\\n self._ik_params = setups[setup]['ik_params']\\n\\n # State Variables\\n self._q_ = np.zeros((self._obs_history, self._dof))\\n self._qd_ = np.zeros((self._obs_history, self._dof))\\n\\n self._episode_steps = 0\\n\\n self._pstop_time_ = None\\n self._pstop_times_ = []\\n self._safety_mode_ = ur_utils.SafetyModes.NONE\\n self._max_pstop = 10\\n self._max_pstop_window = 600\\n self._clear_pstop_after = 2\\n self._x_target_ = np.frombuffer(Array('f', 3).get_obj(), dtype='float32')\\n self._x_ = np.frombuffer(Array('f', 3).get_obj(), dtype='float32')\\n self._reward_ = Value('d', 0.0)\\n\\n if self._target_type == 'position':\\n if self._dof == 2:\\n self._target_ = np.zeros((2))\\n self._target_low = self._end_effector_low[self._end_effector_indices]\\n self._target_high = self._end_effector_high[self._end_effector_indices]\\n elif self._dof == 6:\\n self._target_ = np.zeros((3))\\n self._target_low = self._end_effector_low\\n self._target_high = self._end_effector_high\\n elif self._target_type == 'angle':\\n self._target_ = np.zeros((self._dof))\\n self._target_low = self._angles_low\\n self._target_high = self._angles_high\\n\\n # Set up action and observation space\\n\\n if self._derivative_type== 'second' or self._derivative_type== 'first':\\n self._action_low = -np.ones(self._dof) * self._deriv_action_max\\n self._action_high = np.ones(self._dof) * self._deriv_action_max\\n else: # derivative_type=='none'\\n if self._control_type == 'position':\\n self._action_low = self._angles_low\\n self._action_high = self._angles_high\\n elif self._control_type == 'velocity':\\n self._action_low = self._speed_low\\n self._action_high = self._speed_high\\n elif self._control_type == 'acceleration':\\n self._action_low = self._accel_low\\n self._action_high = self._accel_high\\n\\n # TODO: is there a nicer way to do this?\\n if rllab_box:\\n from rllab.spaces import Box as RlBox # use this for rllab TRPO\\n Box = RlBox\\n else:\\n from gym.spaces import Box as GymBox # use this for baselines algos\\n Box = GymBox\\n\\n self._observation_space = Box(\\n low=np.array(\\n list(self._angles_low * self._obs_history) # q_actual\\n + list(-np.ones(self._dof * self._obs_history)) # qd_actual\\n + list(self._target_low) # target\\n + list(-self._action_low) # previous action in cont space\\n ),\\n high=np.array(\\n list(self._angles_high * self._obs_history) # q_actual\\n + list(np.ones(self._dof * self._obs_history)) # qd_actual\\n + list(self._target_high) # target\\n + list(self._action_high) # previous action in cont space\\n )\\n )\\n\\n\\n self._action_space = Box(low=self._action_low, high=self._action_high)\\n\\n if rllab_box:\\n from rllab.envs.env_spec import EnvSpec\\n self._spec = EnvSpec(self.observation_space, self.action_space)\\n\\n # Only used with second derivative control\\n self._first_deriv_ = np.zeros(len(self.action_space.low))\\n\\n # Communicator Parameters\\n communicator_setups = {'UR5':\\n {\\n 'num_sensor_packets': obs_history,\\n\\n 'kwargs': {'host': self._host,\\n 'actuation_sync_period': actuation_sync_period,\\n 'buffer_len': obs_history + SharedBuffer.DEFAULT_BUFFER_LEN,\\n }\\n }\\n }\\n if self._delay > 0:\\n from senseact.devices.ur.ur_communicator_delay import URCommunicator\\n communicator_setups['UR5']['kwargs']['delay'] = self._delay\\n else:\\n from senseact.devices.ur.ur_communicator import URCommunicator\\n communicator_setups['UR5']['Communicator'] = URCommunicator\\n\\n super(ReacherEnv, self).__init__(communicator_setups=communicator_setups,\\n action_dim=len(self.action_space.low),\\n observation_dim=len(self.observation_space.low),\\n dt=dt,\\n **kwargs)\\n\\n # The last action\\n self._action_ = self._rand_obj_.uniform(self._action_low, self._action_high)\\n\\n # Defining packet structure for quickly building actions\\n self._reset_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\\n self._reset_packet[0] = ur_utils.COMMANDS['MOVEJ']['id']\\n self._reset_packet[1:1 + 6] = self._q_ref\\n self._reset_packet[-2] = movej_t\\n\\n self._servoj_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\\n self._servoj_packet[0] = ur_utils.COMMANDS['SERVOJ']['id']\\n self._servoj_packet[1:1 + 6] = self._q_ref\\n self._servoj_packet[-3] = servoj_t\\n self._servoj_packet[-1] = servoj_gain\\n\\n self._speedj_packet = np.ones(self._actuator_comms['UR5'].actuator_buffer.array_len) * ur_utils.USE_DEFAULT\\n self._speedj_packet[0] = ur_utils.COMMANDS['SPEEDJ']['id']\\n self._speedj_packet[1:1 + 6] = np.zeros((6,))\\n self._speedj_packet[-2] = speedj_a\\n self._speedj_packet[-1] = speedj_t_min\\n\\n self._stopj_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\\n self._stopj_packet[0] = ur_utils.COMMANDS['STOPJ']['id']\\n self._stopj_packet[1] = 2.0\\n\\n # Tell the arm to do nothing (overwritting previous command)\\n self._nothing_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\\n\\n self._pstop_unlock_packet = np.zeros(self._actuator_comms['UR5'].actuator_buffer.array_len)\\n self._pstop_unlock_packet[0] = ur_utils.COMMANDS['UNLOCK_PSTOP']['id']\\n\\n\\n # self.info['reward_dist'] = 0\\n # self.info['reward_vel'] = 0\",\n \"def setup(self, tau1=None, tau2=None, template_tmax=None, dt=None, \\n delay=0.0, sign=1, eventstartthr=None, risepower=4., min_event_amplitude=2.0):\\n assert sign in [-1, 1] # must be selective, positive or negative events only\\n self.sign = sign\\n self.taus = [tau1, tau2]\\n self.dt = 1/20000.\\n self.template_tmax = template_tmax\\n self.idelay = int(delay/dt) # points delay in template with zeros\\n self.template = None # reset the template if needed.\\n self.eventstartthr = eventstartthr\\n self.risepower = risepower\\n self.min_event_amplitude = min_event_amplitude\",\n \"def set_up_model(dt, model, update = False):\\n \\n start_scope()\\n \\n ##### Update model parameters (should be done, if original parameters have been changed)\\n if update:\\n ##### Structure of ANF\\n # terminal = 0\\n # internode = 1\\n # node = 2\\n # presomatic region = 3\\n # Soma = 4\\n # postsomatic region = 5\\n model.structure = np.array(list(np.tile([2] + np.tile([1],model.nof_segments_internodes).tolist(),model.nof_internodes)) + [2])\\n model.nof_comps = len(model.structure)\\n \\n ##### compartment lengths\\n # initialize\\n model.compartment_lengths = np.zeros_like(structure)*um\\n # length internodes\\n model.compartment_lengths[model.structure == 1] = model.length_internodes / model.nof_segments_internodes\\n # length nodes\\n model.compartment_lengths[model.structure == 2] = model.length_nodes\\n # total length neuron\\n model.length_neuron = sum(model.compartment_lengths)\\n \\n ##### Compartment diameters\\n # initialize\\n model.compartment_diameters = np.zeros(model.nof_comps+1)*um\\n # same diameter for whole fiber\\n model.compartment_diameters[:] = model.diameter_fiber\\n \\n ##### conductivity of leakage channels\\n model.g_L = model.g_L_node/model.surface_aria_node\\n\\n ##### Surface arias\\n # lateral surfaces\\n m = [np.sqrt(abs(model.compartment_diameters[i+1] - model.compartment_diameters[i])**2 + model.compartment_lengths[i]**2)\\n for i in range(0,model.nof_comps)]\\n # total surfaces\\n model.A_surface = [(model.compartment_diameters[i+1] + model.compartment_diameters[i])*np.pi*m[i]*0.5\\n for i in range(0,model.nof_comps)]\\n \\n ##### Compartment middle point distances (needed for plots)\\n model.distance_comps_middle[0] = 0.5*model.compartment_lengths[0]\\n model.distance_comps_middle = np.zeros_like(model.compartment_lengths)\\n for ii in range(0,model.nof_comps-1):\\n model.distance_comps_middle[ii+1] = 0.5* model.compartment_lengths[ii] + 0.5* model.compartment_lengths[ii+1]\\n \\n ##### Capacities\\n # initialize\\n model.c_m = np.zeros_like(model.structure)*uF/cm**2\\n # nodes\\n model.c_m[model.structure == 2] = model.c_m_node/model.surface_aria_node\\n # internodes\\n model.c_m[structure == 1] = model.c_m_layer/(1+model.nof_myelin_layers)\\n \\n ##### Condactivities internodes\\n # initialize\\n model.g_m = np.zeros_like(model.structure)*msiemens/cm**2\\n # internodes\\n model.g_m[model.structure == 1] = model.g_m_layer/(1+model.nof_myelin_layers)\\n \\n ##### Axoplasmatic resistances\\n model.compartment_center_diameters = np.zeros(model.nof_comps)*um\\n model.compartment_center_diameters = (model.compartment_diameters[0:-1] + model.compartment_diameters[1:]) / 2\\n model.R_a = (model.compartment_lengths*model.rho_in) / ((model.compartment_center_diameters*0.5)**2*np.pi)\\n \\n ##### Noise term\\n model.gamma_Na_vector = np.zeros(model.nof_comps)*psiemens\\n model.gamma_Na_vector[model.structure == 2] = model.gamma_Na\\n model.noise_term = np.sqrt(model.A_surface*model.gamma_Na_vector*model.rho_Na)\\n \\n ##### Compartments to plot\\n # get indexes of all compartments that are not segmented\\n model.indexes_comps = np.where(model.structure == 2)[0]\\n # calculate middle compartments of internodes\\n model.middle_comps_internodes = np.ceil(model.indexes_comps[:-1] + model.nof_segments_internodes/2).astype(int)\\n # create array with all compartments to plot\\n model.comps_to_plot = np.sort(np.append(model.indexes_comps, model.middle_comps_internodes))\\n \\n ##### initialize defaultclock\\n defaultclock.dt = dt\\n\\n ##### define morphology\\n morpho = Section(n = model.nof_comps,\\n length = model.compartment_lengths,\\n diameter = model.compartment_diameters)\\n \\n ##### define neuron\\n neuron = SpatialNeuron(morphology = morpho,\\n model = model.eqs,\\n Cm = model.c_m,\\n Ri = model.rho_in,\\n method=\\\"exponential_euler\\\")\\n \\n ##### initial values\\n neuron.v = model.V_res\\n neuron.m = model.m_init\\n neuron.h = model.h_init\\n neuron.n = model.n_init\\n \\n ##### Set parameter values of differential equations\\n # conductances nodes\\n neuron.gamma_Na = model.gamma_Na\\n neuron.gamma_K = model.gamma_K\\n neuron.g_L = model.g_L\\n \\n # conductances internodes\\n neuron.g_myelin = model.g_m\\n neuron.gamma_Na[np.asarray(np.where(model.structure == 1))] = 0*psiemens\\n neuron.gamma_K[np.asarray(np.where(model.structure == 1))] = 0*psiemens\\n neuron.g_L[np.asarray(np.where(model.structure == 1))] = 0*msiemens/cm**2\\n \\n # conductances peripheral terminal\\n neuron.gamma_Na[np.where(model.structure == 0)[0]] = model.gamma_Na_terminal\\n neuron.gamma_K[np.where(model.structure == 0)[0]] = model.gamma_K_terminal\\n neuron.g_L[np.where(model.structure == 0)[0]] = model.g_L_terminal\\n \\n # conductances soma\\n neuron.gamma_Na[index_soma] = 0*psiemens\\n neuron.gamma_K[index_soma] = 0*psiemens\\n neuron.g_L[index_soma] = 0*msiemens/cm**2\\n \\n # Nernst potential for leakage current\\n neuron.E_Leak = model.E_L\\n neuron.E_Leak[np.where(model.structure == 0)[0]] = E_L_terminal\\n \\n # other parameters\\n neuron.V_res = model.V_res\\n neuron.T_celsius = model.T_celsius\\n neuron.E_Na = model.E_Na\\n neuron.E_K = model.E_K\\n neuron.rho_Na = model.rho_Na\\n neuron.rho_K = model.rho_K\\n \\n return neuron, model\",\n \"def get_observations(self):\\n joint_states = self.joints_state\\n self.force = self.wrench_stamped.wrench.force\\n self.torque = self.wrench_stamped.wrench.torque\\n self.static_taxel = self.tactile_static.taxels\\n# dynamic_taxel= tactile_dynamic\\n\\n# print(\\\"[force]\\\", self.force.x, self.force.y, self.force.z)\\n# print(\\\"[torque]\\\", self.torque.x, self.torque.y, self.torque.z)\\n shp_joint_ang = joint_states.position[0]\\n shl_joint_ang = joint_states.position[1]\\n elb_joint_ang = joint_states.position[2]\\n wr1_joint_ang = joint_states.position[3]\\n wr2_joint_ang = joint_states.position[4]\\n wr3_joint_ang = joint_states.position[5]\\n\\n shp_joint_vel = joint_states.velocity[0]\\n shl_joint_vel = joint_states.velocity[1]\\n elb_joint_vel = joint_states.velocity[2]\\n wr1_joint_vel = joint_states.velocity[3]\\n wr2_joint_vel = joint_states.velocity[4]\\n wr3_joint_vel = joint_states.velocity[5]\\n\\n q = [shp_joint_ang, shl_joint_ang, elb_joint_ang, wr1_joint_ang, wr2_joint_ang, wr3_joint_ang]\\n# print(\\\"q(observation):\\\", q)\\n eef_x, eef_y, eef_z = self.get_xyz(q)\\n self.end_effector = self.get_xyz(q)\\n eef_x_ini, eef_y_ini, eef_z_ini = self.get_xyz(self.init_joint_pose2) \\n\\n delta_image_r, delta_image_l = self.get_image()\\n self.cnn_image_r = agent.update_cnn(delta_image_r)\\n self.cnn_image_l = agent.update_cnn(delta_image_l)\\n self.cnn_image_r_list = self.cnn_image_r.tolist()\\n self.cnn_image_l_list = self.cnn_image_l.tolist()\\n print(\\\"r_list\\\", self.cnn_image_r_list)\\n print(\\\"l_list\\\", self.cnn_image_l_list)\\n\\n observation = []\\n# rospy.logdebug(\\\"List of Observations==>\\\"+str(self.observations))\\n for obs_name in self.observations:\\n if obs_name == \\\"shp_joint_ang\\\":\\n observation.append((shp_joint_ang - self.init_joint_pose2[0]) * self.joint_n)\\n elif obs_name == \\\"shl_joint_ang\\\":\\n observation.append((shl_joint_ang - self.init_joint_pose2[1]) * self.joint_n)\\n elif obs_name == \\\"elb_joint_ang\\\":\\n observation.append((elb_joint_ang - self.init_joint_pose2[2]) * self.joint_n)\\n elif obs_name == \\\"wr1_joint_ang\\\":\\n observation.append((wr1_joint_ang - self.init_joint_pose2[3]) * self.joint_n)\\n elif obs_name == \\\"wr2_joint_ang\\\":\\n observation.append((wr2_joint_ang - self.init_joint_pose2[4]) * self.joint_n)\\n elif obs_name == \\\"wr3_joint_ang\\\":\\n observation.append((wr3_joint_ang - self.init_joint_pose2[5]) * self.joint_n)\\n elif obs_name == \\\"shp_joint_vel\\\":\\n observation.append(shp_joint_vel)\\n elif obs_name == \\\"shl_joint_vel\\\":\\n observation.append(shl_joint_vel)\\n elif obs_name == \\\"elb_joint_vel\\\":\\n observation.append(elb_joint_vel)\\n elif obs_name == \\\"wr1_joint_vel\\\":\\n observation.append(wr1_joint_vel)\\n elif obs_name == \\\"wr2_joint_vel\\\":\\n observation.append(wr2_joint_vel)\\n elif obs_name == \\\"wr3_joint_vel\\\":\\n observation.append(wr3_joint_vel)\\n elif obs_name == \\\"eef_x\\\":\\n observation.append((eef_x - eef_x_ini) * self.eef_n)\\n elif obs_name == \\\"eef_y\\\":\\n observation.append((eef_y - eef_y_ini) * self.eef_n)\\n elif obs_name == \\\"eef_z\\\":\\n observation.append((eef_z - eef_z_ini) * self.eef_n)\\n elif obs_name == \\\"force_x\\\":\\n observation.append((self.force.x - self.force_ini.x) / self.force_limit1 * self.force_n)\\n elif obs_name == \\\"force_y\\\":\\n observation.append((self.force.y - self.force_ini.y) / self.force_limit1 * self.force_n)\\n elif obs_name == \\\"force_z\\\":\\n observation.append((self.force.z - self.force_ini.z) / self.force_limit1 * self.force_n)\\n elif obs_name == \\\"torque_x\\\":\\n observation.append((self.torque.x - self.torque_ini.x) / self.torque_limit1 * self.torque_n)\\n elif obs_name == \\\"torque_y\\\":\\n observation.append((self.torque.y - self.torque_ini.y) / self.torque_limit1 * self.torque_n)\\n elif obs_name == \\\"torque_z\\\":\\n observation.append((self.torque.z - self.torque_ini.z) / self.torque_limit1 * self.torque_n)\\n elif obs_name == \\\"image_cnn\\\":\\n for x in range(0, 10):\\n observation.append(self.cnn_image_r_list[0][x])\\n# print(\\\"r_list\\\", self.cnn_image_r_list[0][x])\\n for x in range(0, 10):\\n observation.append(self.cnn_image_l_list[0][x])\\n# print(\\\"l_list\\\", self.cnn_image_l_list[0][x])\\n elif obs_name == \\\"static_taxel\\\":\\n for x in range(0, 28):\\n observation.append((self.static_taxel[0].values[x] - self.static_taxel_ini[0].values[x]) * self.taxel_n)\\n for x in range(0, 28):\\n observation.append((self.static_taxel[1].values[x] - self.static_taxel_ini[1].values[x]) * self.taxel_n)\\n# elif obs_name == \\\"dynamic_taxel\\\":\\n# observation.append(dynamic_taxel[0].values) * self.taxel_n\\n# observation.append(dynamic_taxel[1].values) * self.taxel_n\\n else:\\n raise NameError('Observation Asked does not exist=='+str(obs_name))\\n\\n print(\\\"observation\\\", list(map(round, observation, [3]*len(observation))))\\n# print(\\\"observation\\\", observation)\\n\\n return observation\",\n \"def simulate(initstate, t, timestep=forward, drive=donothing, bounds = [0.97, 0.97, 0.97, 0.97], saveinterval=10, beta=0.281105, eps=0.013, gamma=0.0880, mu=0.3, nu=0, dudt_x = dudt, dvdt_x = dvdt, dndt_x = dndt, grav=True, cori=True, advx=True, advy=True, attn=True): # gives surface height array of the system after evert dt\\n bounds = np.asarray(bounds, dtype=np.float32)\\n h, n, u, v, f, dx, dy, dt = [initstate[k] for k in ('h', 'n', 'u', 'v', 'lat', 'dx', 'dy', 'dt')]\\n \\n f = np.float32(((2*2*np.pi*np.sin(f*np.pi/180))/(24*3600))[:,np.newaxis])\\n \\n \\n du0 = np.zeros_like(u)\\n dv0 = np.zeros_like(v)\\n dn0 = np.zeros_like(n)\\n \\n \\n dndt_x(h, n, u, v, dx, dy, dn0)\\n dn = (dn0, np.copy(dn0), np.copy(dn0))\\n \\n dudt_x(h, n, f, u, v, dx, dy, du0)\\n du = (du0, np.copy(du0), np.copy(du0), np.copy(du0))\\n \\n dvdt_x(h, n, f, u, v, dx, dy, dv0)\\n dv = (dv0, np.copy(dv0), np.copy(dv0), np.copy(dv0))\\n \\n nu = (dx+dy)/1000\\n \\n mmax = np.max(np.abs(n))\\n landthresh = 1.5*np.max(n) # threshhold for when sea ends and land begins\\n itrs = int(np.ceil(t/dt))\\n saveinterval = np.int(saveinterval//dt)\\n assert (dt >= 0), 'negative dt!' # dont try if timstep is zero or negative\\n \\n ntt = np.zeros((np.int(np.ceil(itrs/saveinterval)),)+n.shape, dtype=np.float32)\\n maxn = np.zeros(n.shape, dtype=n.dtype) # max height in that area\\n \\n coastx = np.less(h, landthresh) # where the reflective condition is enforced on the coast\\n \\n print('simulating...')\\n try:\\n for itr in range(itrs):# iterate for the given number of iterations\\n if itr%saveinterval == 0:\\n ntt[np.int(itr/saveinterval),:,:] = n\\n print(np.argmax( ntt[np.int(itr/saveinterval),:,:],axis=0)[5])\\n \\n \\n maxn = np.max((n, maxn), axis=0) # record new maxes if they are greater than previous records \\n \\n # pushes n, u, v one step into the future\\n n,u,v, du, dv, dn = timestep(h, n, u, v, f, dt, dx, dy, du, dv, dn, beta=beta, eps=eps, gamma=gamma, mu=mu, nu=nu, dudt_x=dudt_x, dvdt_x=dvdt_x, dndt_x=dndt_x, grav=grav, cori=cori, advx=advx, advy=advy, attn=attn)\\n\\n land(h, n, u, v, coastx) # how to handle land/coast\\n border(n, u, v, 15, bounds) \\n drive(h, n, u, v, f, dt, dx, dy, nu, coastx, bounds, mu, itr)\\n print('simulation complete')\\n except Exception as e:\\n print('timestep: ', itr)\\n raise e\\n return ntt, maxn#, minn, timemax # return surface height through time and maximum heights\",\n \"def setup(env, NUM_TRACKS, landtime, t_inter):\\n # Create the airport\\n airport = Airport(env, NUM_TRACKS, landtime)\\n\\n # Create 4 initial planes\\n for i in range(1):\\n env.process(plane(env, 'Aviao %d' % i, airport))\\n\\n # Create more planes while the simulation is running\\n while True:\\n yield env.timeout(random.randint(t_inter-2, t_inter+2))\\n# yield env.timeout(random.expovariate(1.0 / t_inter))\\n i += 1\\n env.process(plane(env, 'Aviao %d' % i, airport))\",\n \"def Inject(self,injector):\\n # Inject constant source of wind mass & energy (as pure KE)\\n dt = integrator.Integrator().dt\\n injector.AddMass(self._massloss*dt)\\n injector.AddKE(self._lum*dt)\\n integrator.Integrator().CourantLimiter(self._vcourant)\",\n \"def __init__(self,\\n debug=False,\\n urdf_version=None,\\n control_time_step=0.005,\\n action_repeat=5,\\n control_latency=0,\\n pd_latency=0,\\n on_rack=False,\\n motor_kp=1.0,\\n motor_kd=0.02,\\n render=False,\\n num_steps_to_log=2000,\\n env_randomizer=None,\\n log_path=None,\\n signal_type='ik',\\n target_position=None,\\n backwards=None,\\n gait_type='trot',\\n terrain_type='plane',\\n terrain_id='plane',\\n mark='base',\\n ):\\n self.phase = 0\\n\\n self._gait_type = gait_type \\n # for observation space bounding \\n self.max_speed = 1.0\\n self.min_speed = 0.5 # change back to 0.2 for OLD TD3 model evaluation\\n \\n self.min_side_speed = 0.0\\n self.max_side_speed = 0.0\\n\\n self.speed = np.random.uniform(self.min_speed, self.max_speed)\\n self.side_speed = np.random.uniform(self.min_side_speed, self.max_side_speed)\\n self.speed_des = [self.speed, self.side_speed]\\n\\n # Initialization variables for periodic reward sum composition\\n self.theta_FL = phase_constants.PHASE_VALS[self._gait_type]['front_left']\\n self.theta_FR = phase_constants.PHASE_VALS[self._gait_type]['front_right']\\n self.theta_RL = phase_constants.PHASE_VALS[self._gait_type]['rear_left']\\n self.theta_RR = phase_constants.PHASE_VALS[self._gait_type]['rear_right']\\n\\n self.min_swing_ratio = 0.6\\n self.max_swing_ratio = 0.8\\n self.ratio = np.random.uniform(self.min_swing_ratio, self.max_swing_ratio)\\n\\n super(rexPeriodicRewardEnv,\\n self).__init__(urdf_version=urdf_version,\\n accurate_motor_model_enabled=True,\\n motor_overheat_protection=False,\\n motor_kp=motor_kp,\\n motor_kd=motor_kd,\\n remove_default_joint_damping=False,\\n control_latency=control_latency,\\n pd_latency=pd_latency,\\n on_rack=on_rack,\\n render=render,\\n num_steps_to_log=num_steps_to_log,\\n env_randomizer=env_randomizer,\\n log_path=log_path,\\n control_time_step=control_time_step,\\n action_repeat=action_repeat,\\n target_position=target_position,\\n signal_type=signal_type,\\n backwards=backwards,\\n debug=debug,\\n terrain_id=terrain_id,\\n terrain_type=terrain_type,\\n mark=mark,\\n ratio=self.ratio,\\n forward_reward_cap=5\\n )\\n\\n self.height_des = 0.206 # this is init standing height for rex\\n\\n self.cycle_complete = 0\\n self.cycle_len = 1000 # this is L\\n \\n # vonmises variables\\n self.kappa = phase_constants.VON_MISES_KAPPA\\n\\n rex_joints = p.getNumJoints(bodyUniqueId=self.rex.quadruped)\\n link_name_to_ID = {}\\n for i in range(rex_joints):\\n name = p.getJointInfo(self.rex.quadruped, i)[12].decode('UTF-8')\\n link_name_to_ID[name] = i\\n\\n self.link_name_to_ID = link_name_to_ID\\n self.toe_pos_last = { 'front_left_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['front_left_toe_link'])[0],\\n 'front_right_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['front_right_toe_link'])[0],\\n 'rear_left_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['rear_left_toe_link'])[0],\\n 'rear_right_toe_pos' : p.getLinkState(self.rex.quadruped, self.link_name_to_ID['rear_right_toe_link'])[0]\\n\\n } \\n\\n print('Using Periodic Reward Composition Rex Environment')\",\n \"def main():\\n geom = dde.geometry.TimeDomain(0, 3)\\n y0 = initial_condition()\\n for i in range(0,C)\\n # ic3 = dde.IC(geom, lambda X: 27, boundary, component=5)\\n data = dde.data.PDE(\\n geom,\\n SLE_DL,\\n [ic1, ic2, ic3, observe_y0, observe_y1, observe_y2],\\n num_domain=400,\\n num_boundary=2,\\n anchors=observe_t,\\n )\",\n \"def init_servos():\\n for i in range(0, 7):\\n kit.servo[i].actuation_range = 180\\n kit.servo[i].set_pulse_width_range(450, 2550)\",\n \"def Inject(self,injector):\\r\\n\\r\\n # Calculate the star's current age\\r\\n integrator = weltgeist.integrator.Integrator()\\r\\n t = integrator.time\\r\\n dt = integrator.dt\\r\\n age = t-self._tbirth\\r\\n Teff = 0.0\\r\\n star = self._star\\r\\n\\r\\n # If it's been born, start the tracks\\r\\n if age > 0.0:\\r\\n if self._wind:\\r\\n # Get mass loss and energy from winds\\r\\n ml0 = star.WindMassLoss(age)\\r\\n lum0 = star.WindLuminosity(age)\\r\\n massloss = 0.5*(ml0+star.WindMassLoss(age+dt))*dt\\r\\n energy = 0.5*(lum0+star.WindLuminosity(age+dt))*dt\\r\\n # Add mass FIRST since KE needs to be added elastically\\r\\n injector.AddMass(massloss)\\r\\n # Add energy to grid as kinetic energy\\r\\n injector.AddKE(energy)\\r\\n # Add some thermal energy to account for star's temperature\\r\\n Teff = 0.5*(star.Teff(age)+star.Teff(age+dt))\\r\\n TE = 1.5 * wunits.kB * massloss/(wunits.mH/wunits.X)*Teff\\r\\n injector.AddTE(TE)\\r\\n # Set the Courant condition\\r\\n vwind = np.sqrt(2.0*lum0/ml0)\\r\\n integrator.CourantLimiter(vwind)\\r\\n if self._radiation:\\r\\n # Get radiation properties for ionising and non-ionising UV\\r\\n Lionising = 0.5*(star.LIonising(age)+star.LIonising(age+dt))\\r\\n Lnonionising = 0.5*(star.LNonIonising(age)+star.LNonIonising(age+dt))\\r\\n Eionising = 0.5*(star.EPhoton(age)+star.EPhoton(age+dt)) \\r\\n Teff = 0.5*(star.Teff(age)+star.Teff(age+dt)) \\r\\n Tion = weltgeist.radiation.IonisedGasTemperature(Teff, self._metal)\\r\\n injector.AddPhotons(Lionising, Lnonionising, Eionising, Tion)\",\n \"def _setup_simulation(self\\n ) -> None:\\n pass\",\n \"def simulationTwoDrugsDelayedTreatment():\\n\\n # TODO\",\n \"def set_up_and_parameterise_experiment(self):\\n # Update experiment using capacity\\n capacity = self._parameter_values[\\\"Nominal cell capacity [A.h]\\\"]\\n for op_conds in self.experiment.operating_conditions_steps:\\n if op_conds.type == \\\"C-rate\\\":\\n op_conds.type = \\\"current\\\"\\n op_conds.value = op_conds.value * capacity\\n\\n # Update terminations\\n termination = op_conds.termination\\n for term in termination:\\n term_type = term[\\\"type\\\"]\\n if term_type == \\\"C-rate\\\":\\n # Change type to current\\n term[\\\"type\\\"] = \\\"current\\\"\\n # Scale C-rate with capacity to obtain current\\n term[\\\"value\\\"] = term[\\\"value\\\"] * capacity\\n\\n # Add time to the experiment times\\n dt = op_conds.duration\\n if dt is None:\\n if op_conds.type == \\\"current\\\":\\n # Current control: max simulation time: 3h / C-rate\\n Crate = op_conds.value / capacity\\n dt = 3 / abs(Crate) * 3600 # seconds\\n else:\\n # max simulation time: 1 day\\n dt = 24 * 3600 # seconds\\n op_conds.duration = dt\\n\\n # Set up model for experiment\\n self.set_up_and_parameterise_model_for_experiment()\",\n \"def simulation(self, pvmod=True):\\r\\n \\r\\n self.Real.Ppv2ac_out, self.Real.Ppv2bat_in, self.Real.Ppv2bat_in0, self.Real.Pbat2ac_out, self.Real.Pbat2ac_out0, self.Real.Ppvbs, self.Real.Pbat, self.Real.soc, self.Real.soc0 = batmod_dc(\\r\\n self.d, self.dt, self.Real.soc0, self.Real.soc, self.Real.Pr, self.Real.Prpv, self.Real.Ppv, self.Real.Ppv2bat_in0, self.Real.Ppv2bat_in,\\r\\n self.Real.Pbat2ac_out0, self.Real.Pbat2ac_out, self.Real.Ppv2ac_out, self.Real.Ppvbs, self.Real.Pbat)\\r\\n\\r\\n self.Ideal.Pbat, self.Ideal.soc, self.Ideal.soc0 = batmod_dc_ideal(self.d, self.dt, self.Ideal.soc0, self.Ideal.soc, self.Ideal.Pr, self.Ideal.Pbat)\\r\\n\\r\\n # Define missing parameters\\r\\n self.Real.Ppv2ac = self.Real.Ppv2ac_out # AC output power of the PV2AC conversion pathway\\r\\n self.Real.Ppv2bat = self.Real.Ppv2bat_in # DC input power of the PV2BAT conversion pathway\\r\\n\\r\\n self.Ideal.Ppvbs = self.Ideal.Ppv - np.maximum(0, self.Ideal.Pbat) - (np.minimum(0, self.Ideal.Pbat)) # Realized AC power of the PV-battery system\\r\\n self.Ideal.Ppv2ac = self.Ideal.Ppv - np.maximum(0, self.Ideal.Pbat) # AC output power of the PV2AC conversion pathway\\r\\n self.Ideal.Ppv2bat = np.maximum(0, self.Ideal.Pbat) # DC input power of the PV2BAT conversion pathway\\r\\n\\r\\n print()\",\n \"def run(self):\\n\\n # initializing random network activity\\n s_rand_T = np.zeros((self.T, self.N_rand))\\n p_rand_T = np.zeros((self.T, self.N_rand))\\n r_rand_T = np.zeros((self.T, self.N_rand))\\n\\n s_rand_T[0, :] = np.random.uniform(low=0, high=0.01, size=(self.N_rand))\\n\\n # initializing sensory networks\\n s_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\\n p_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\\n r_sens_T = np.zeros((self.T, self.N_sensory_nets * self.N_sensory))\\n s_sens_T[0, :] = np.random.uniform(low=0, high=0.01, size=(self.N_sensory_nets * self.N_sensory))\\n\\n # extend input to be T timesteps and only nonzero for 100 ts\\n s_ext_T = np.broadcast_to(self.s_ext, (self.T, self.N_sensory * self.N_sensory_nets)).copy()\\n # stimulus is presented for 100 ms\\n stim_T = int(200/self.rand_net.dt)\\n s_ext_T[:100] = 0\\n s_ext_T[100+stim_T:] = 0\\n # s_ext_T *= 0\\n\\n for t in range(1, self.T):\\n if (t + 1) % 100 == 0:\\n print(f'step {t} of {self.T}')\\n s_sens_prev = s_sens_T[t - 1]\\n s_rand_prev = s_rand_T[t - 1]\\n p_rand_prev = p_rand_T[t - 1]\\n s_ext = s_ext_T[t - 1]\\n step = self.forward(s_ext=s_ext, s_rand_prev=s_rand_prev, s_sens_prev=s_sens_prev, p_rand_prev=p_rand_prev)\\n s_sens_T[t] = step['s_sens']\\n p_sens_T[t] = step['p_sens']\\n r_sens_T[t] = step['r_sens']\\n s_rand_T[t] = step['s_rand']\\n r_rand_T[t] = step['r_rand']\\n p_rand_T[t] = step['p_rand']\\n\\n p_sens_T = p_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\\n s_ext_T = s_ext_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\\n r_sens_T = r_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\\n s_sens_T = s_sens_T.reshape(self.T, self.N_sensory_nets, self.N_sensory)\\n\\n return dict(\\n n_sensory=self.N_sensory,\\n n_rand=self.N_rand,\\n mus=self.mus,\\n sigma=self.sigma,\\n s_ext=s_ext_T,\\n s_sens=s_sens_T,\\n r_sens=r_sens_T,\\n p_sens=p_sens_T,\\n s_rand=s_rand_T,\\n r_rand=r_rand_T,\\n p_rand=p_rand_T\\n )\",\n \"def setup_simulation(self, **kwargs):\\n\\n self.distance = self.config[\\\"site\\\"][\\\"distance\\\"]\\n self.num_substations = self.config[\\\"num_substations\\\"]\\n\\n self.initialize_substructure_production()\\n self.initialize_installation_vessel()\",\n \"def __init__(self, services, config):\\n #pytau.setNode(1)\\n #timer = pytau.profileTimer(\\\"component.__init__\\\", \\\"\\\", str(os.getpid()))\\n #pytau.start(timer)\\n self.component_id = None\\n self.invocation_q = None\\n self.services = weakref.proxy(services)\\n self.config = config\\n self.start_time=0.0\\n self.sys_exit = None\\n for i in config.keys():\\n try:\\n setattr(self, i, config[i])\\n except Exception, e:\\n print 'Error setting Component parameter : ', i, ' - ', e\\n #pytau.stop(timer)\\n raise\\n\\n #pytau.stop(timer)\",\n \"def __init__(self, n): # this is equivalent to starting a random one\\n self.n = n\\n # From table S1 in the supplemental materials\\n # each c parameters is [body,limb]\\n self.cv0 = [0.3, 0.0]\\n self.cv1 = [0.2, 0.2]\\n self.cR0 = [0.196,0.131]\\n self.cR1 = [0.065,0.131]\\n #[[dbodylow,dbodyhigh],[dlimblow,dlimbhigh]]\\n self.d_params = [[1,5],[1,3]]\\n # which oscillators are limb oscillators and which ones are body oscillators is pretty constant\\n n_body = n - 4\\n self.osc_class = [0 if i < n_body else 1 for i in range(self.n)] # 0 for body oscillator, 1 for limb oscillator\\n # list of keys that can be mutated during evolution\\n self.evolvables = ['w', 'phi', 'a', 'gsl', 'gsh', 'gb1', 'gb2', 'theta', 'ampl', 'ampl_dot']\\n self.scalars = set(['gsl', 'gsh', 'gb1', 'gb2'])\\n self.nonzeros = set([int(i) for i in \\\"8 160 29 181 50 202 71 223 92 244 113 265 134 286 155 307 1 20 22 41 43 62 64 83 85 104 106 125 127 146 169 188 190 209 211 230 232 251 253 272 274 293 295 314 320 321 322 323 364 365 366 367 348 349 350 351 392 393 394 395 338 376 337 356 359 397 379 398\\\".split(\\\" \\\")])\\n self.shapes = {'w':n*n,\\n 'phi':n*n,\\n 'a':n,\\n 'theta':n,\\n 'ampl':n,\\n 'ampl_dot':n}\\n self.sizes = {'w':n*n,\\n 'phi':n*n,\\n 'a':n,\\n 'theta':n,\\n 'ampl':n,\\n 'ampl_dot':n}\",\n \"def set_up_orbit_correctors(ps_beg, delay, id_slice1, ds_slice, zplot, id_slices, U_core, lambdaref):\\n SXSS = Chicane(3.2716, 0.362, 0.830399, delay[0])\\n HXSS = Chicane(3.2, 0.3636, 0.5828, delay[1])\\n\\n OC2 = [CORR08, D1_SXSS, SXSS, D2_SXSS, QUAD09, CORR09]\\n OC3 = [CORR15, D1_HXSS, HXSS, D2_HXSS, QUAD16, CORR16]\\n\\n ps_end1 = beam_transportation(ps_beg, U_core[0])\\n\\n # ps_end1 is a 4-by-N array. N is the number of macro-particles. It is the full\\n # 4D phase space distribution at the end of the first undulator section.\\n\\n # The id of the slice on the axis in the second undulator section\\n on_axis_id_U2 = int(id_slice1+delay[0]/ds_slice+ (8*110)*lambdaref/ds_slice) # The last part is slippage\\n\\n print(on_axis_id_U2)\\n\\n ps_end_slice1 = beam_property_along_s(ps_end1, id_slices)[0:4, :]\\n ps_on_axis_2 = np.ravel(ps_end_slice1[:, on_axis_id_U2])\\n\\n # print(ps_on_axis_2)\\n\\n OC2_optimized = analyze_orbit_corrector(OC2[0], OC2[-1], OC2[1:-1], ps_on_axis_2)\\n print(OC2_optimized)\\n CORR08_new = Orbit_Corrector(OC2[0].length, OC2_optimized[0], OC2_optimized[2])\\n CORR09_new = Orbit_Corrector(OC2[-1].length, OC2_optimized[1], OC2_optimized[3])\\n\\n # The whole U2 with optimized orbit correctors\\n U2_new = [CORR08_new] + OC2[1:-1] + [CORR09_new] + U_core[1]\\n ps_end2 = beam_transportation(ps_end1, U2_new)\\n\\n # ps_end2 is a 4-by-N array. N is the number of macro-particles. It is the full\\n # 4D phase space distribution at the end of the second undulator section.\\n\\n # The id of the slice on the axis in the third undulator section\\n on_axis_id_U3 = int(id_slice1+(delay[0]+delay[1])/ds_slice +(14*110*lambdaref)/ds_slice) # The last term is the slipage\\n\\n print(on_axis_id_U3)\\n\\n ps_end_slice2 = beam_property_along_s(ps_end2, id_slices)[0:4, :]\\n ps_on_axis_3 = np.ravel(ps_end_slice2[ :, on_axis_id_U3])\\n\\n # print(ps_on_axis_3)\\n\\n OC3_optimized = analyze_orbit_corrector(OC3[0], OC3[-1], OC3[1:-1], ps_on_axis_3)\\n print(OC3_optimized)\\n CORR15_new = Orbit_Corrector(OC3[0].length, OC3_optimized[0], OC3_optimized[2])\\n CORR16_new = Orbit_Corrector(OC3[-1].length, OC3_optimized[1], OC3_optimized[3])\\n\\n U3_new = [CORR15_new] + OC3[1:-1] + [CORR16_new] + U_core[2]\\n\\n Undulator_Beamline = U_core[0]+U2_new+U3_new\\n\\n return Undulator_Beamline\",\n \"def Inject(self,injector):\\n dt = integrator.Integrator().dt\\n injector.AddPhotons(self._QH*dt)\",\n \"def setup(self):\\n super().setup()\\n\\n # prepare scratch directory\\n unix.mkdir(PATH.ORTHO)\\n\\n # get data file names from solver\\n solver = sys.modules['seisflows_solver']\\n\\n nevt = PAR.NEVT # number of encoded sources\\n ntpss = PAR.NTPSS # number of timesteps after steady state\\n dt = PAR.DT # total number of timesteps\\n nrec = PAR.NREC # number of stations\\n # ntrace = len(solver.data_filenames)\\n freq_min = float(PAR.FREQ_MIN) # minimium frequency of interest\\n freq_max = float(PAR.FREQ_MAX) # maximium frequency of interest\\n \\n #create a mask on relevant frequencies\\n freq_full = fftfreq(ntpss, dt) # full frequency compunent\\n freq_thresh = 1 / (ntpss * dt) / 200 # threshold for frequency alignment\\n freq_idx = np.squeeze(np.where((freq_min <= (freq_full)) & ((freq_full) < freq_max - freq_thresh))) # frequency band of interest\\n freq = freq_full[freq_idx] # index of frequencies within the frequency band\\n nfreq = len(freq_idx) # number of frequency within the frequency band\\n print('Number of frequencies considered: ' +str(nfreq)+' / '+str(len(freq_full)))\\n\\n # converts time data to Fourier domain\\n sff_obs = np.zeros((nfreq, nevt), dtype=complex) # fourier transform of observed source time function\\n ft_obs = np.zeros((nfreq, nevt, nrec), dtype=complex) # TODO ntrace fourier transform of observed seismogram\\n\\n for isrc in range(nevt):\\n source_name = solver.source_names_all[isrc] # name of source\\n stf_file = solver.stf_files_all[isrc] # name of source file\\n with open(stf_file) as f:\\n lines = f.readlines()\\n stf_obs = []\\n for line in lines:\\n stf_obs.append(float(line.split()[1]))\\n\\n sff_obs[:, isrc] = fft(stf_obs, n=ntpss)[freq_idx]\\n # for itrace in range(ntrace):\\n # trace = self.reader(PATH.DATA + '/' + source_name, solver.data_filenames[itrace])\\n # for irec in range(nrec):\\n # ft_obs[:, isrc, irec, itrace] = fft(trace[irec].data, n=ntpss)[freq_idx]\\n for irec in range(nrec):\\n trace = self.reader(PATH.DATA + '/' + source_name, solver.data_filenames[0])\\n ft_obs[:, isrc, irec] = fft(trace[irec].data, n=ntpss)[freq_idx]\\n \\n self.save('freq_idx', freq_idx)\\n self.save('freq', freq)\\n self.save('sff_obs', sff_obs)\\n self.save('ft_obs', ft_obs)\",\n \"def test_config():\\n import yaml\\n import astropy.units as u\\n from tqdm import tqdm\\n # Need these for `eval` below\\n from numpy import array\\n\\n # Same test suite as used in test_imsim above.\\n # This time, we just use this for the det names.\\n with open(DATA_DIR / \\\"wcs_466749.yaml\\\", 'r') as f:\\n wcss = yaml.safe_load(f)\\n\\n cmds = {}\\n with open(DATA_DIR / \\\"phosim_cat_466749.txt\\\", 'r') as f:\\n for line in f:\\n k, v = line.split()\\n try:\\n v = int(v)\\n except ValueError:\\n try:\\n v = float(v)\\n except ValueError:\\n pass\\n cmds[k] = v\\n\\n # Values below (and others) from phosim_cat_466749.txt\\n rc = cmds['rightascension']\\n dc = cmds['declination']\\n boresight = galsim.CelestialCoord(\\n rc*galsim.degrees,\\n dc*galsim.degrees\\n )\\n obstime = Time(cmds['mjd'], format='mjd', scale='utc')\\n obstime -= 15*u.s\\n band = \\\"ugrizy\\\"[cmds['filter']]\\n wavelength_dict = dict(\\n u=365.49,\\n g=480.03,\\n r=622.20,\\n i=754.06,\\n z=868.21,\\n y=991.66\\n )\\n wavelength = wavelength_dict[band]\\n camera = imsim.get_camera()\\n\\n rotTelPos = cmds['rottelpos'] * galsim.degrees\\n telescope = imsim.load_telescope(f\\\"LSST_{band}.yaml\\\", rotTelPos=rotTelPos)\\n # Non-default values.\\n temperature = 293.\\n pressure = 69.0\\n H2O_pressure = 2.0\\n\\n factory = imsim.BatoidWCSFactory(\\n boresight, obstime, telescope, wavelength,\\n camera,\\n temperature=temperature,\\n pressure=pressure,\\n H2O_pressure=H2O_pressure\\n )\\n\\n config = {\\n 'input': {\\n 'telescope': {\\n 'file_name':f\\\"LSST_{band}.yaml\\\",\\n 'rotTelPos': rotTelPos\\n }\\n },\\n 'image': {\\n 'wcs': {\\n 'type': 'Batoid',\\n 'boresight': boresight,\\n 'camera': 'LsstCam',\\n 'obstime': obstime,\\n 'wavelength': wavelength,\\n 'temperature': temperature,\\n 'pressure': pressure,\\n 'H2O_pressure': H2O_pressure,\\n 'order': 2,\\n }\\n }\\n }\\n\\n rng = np.random.default_rng(1234)\\n for k in tqdm(wcss.keys()):\\n name = k[18:25].replace('-', '_')\\n det = camera[name]\\n\\n wcs1 = factory.getWCS(det, order=2)\\n config['image']['wcs']['det_name'] = name\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n galsim.config.ProcessInput(config)\\n wcs2 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n\\n # Test points\\n xs = rng.uniform(0, 4000, 100)\\n ys = rng.uniform(0, 4000, 100)\\n ra1, dec1 = wcs1.xyToradec(xs, ys, units='radians')\\n ra2, dec2 = wcs2.xyToradec(xs, ys, units='radians')\\n np.testing.assert_allclose(ra1, ra2)\\n np.testing.assert_allclose(dec1, dec2)\\n\\n # Test == when identical\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n wcs3 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n assert wcs3 == wcs2\\n\\n # Test that pressure and temperature matter.\\n config['image']['wcs']['temperature'] = 250\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n wcs4 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n assert wcs4 != wcs2\\n\\n config['image']['wcs']['temperature'] = temperature\\n config['image']['wcs']['pressure'] = 55\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n wcs5 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n assert wcs5 != wcs2\\n\\n config['image']['wcs']['pressure'] = pressure\\n config['image']['wcs']['H2O_pressure'] = 10\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n wcs6 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n assert wcs6 != wcs2\\n\\n # Test defaults\\n del config['image']['wcs']['temperature']\\n del config['image']['wcs']['pressure']\\n del config['image']['wcs']['H2O_pressure']\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n config = galsim.config.CleanConfig(config)\\n galsim.config.ProcessInput(config)\\n wcs7 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n default_pressure = 101.325 * (1-2.25577e-5*2715)**5.25588\\n wcs7a = imsim.BatoidWCSFactory(\\n boresight, obstime, telescope, wavelength, camera,\\n temperature=280,\\n pressure=default_pressure,\\n H2O_pressure=1.0,\\n ).getWCS(det, order=2)\\n assert wcs7 == wcs7a\\n\\n # Default wavelength from bandpass\\n del config['image']['wcs']['wavelength']\\n config['bandpass'] = imsim.RubinBandpass('r')\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n config = galsim.config.CleanConfig(config)\\n galsim.config.ProcessInput(config)\\n wcs8 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n wcs8a = imsim.BatoidWCSFactory(\\n boresight, obstime, telescope,\\n wavelength=config['bandpass'].effective_wavelength,\\n camera=camera,\\n temperature=280,\\n pressure=default_pressure,\\n H2O_pressure=1.0,\\n ).getWCS(det, order=2)\\n assert wcs8 == wcs8a\\n\\n del config['bandpass']\\n config['image']['bandpass'] = {\\n 'type': 'RubinBandpass',\\n 'band' : 'r',\\n }\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n config = galsim.config.CleanConfig(config)\\n galsim.config.ProcessInput(config)\\n wcs8b = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n assert wcs8b == wcs8a\\n\\n # Obstime can be a string\\n print('obstime = ',obstime.to_value('iso'), type(obstime.to_value('iso')))\\n config['image']['wcs']['obstime'] = obstime.to_value('iso')\\n # Doesn't quite roundtrip perfectly. But within a millisecond.\\n obstime = Time(obstime.to_value('iso'), scale='tai')\\n print('obstime => ',obstime)\\n galsim.config.RemoveCurrent(config['image']['wcs'])\\n config = galsim.config.CleanConfig(config)\\n galsim.config.ProcessInput(config)\\n wcs9 = galsim.config.BuildWCS(config['image'], 'wcs', config)\\n wcs9a = imsim.BatoidWCSFactory(\\n boresight, obstime, telescope,\\n wavelength=config['bandpass'].effective_wavelength,\\n camera=camera,\\n temperature=280,\\n pressure=default_pressure,\\n H2O_pressure=1.0,\\n ).getWCS(det, order=2)\\n assert wcs9 == wcs9a\",\n \"def initialise_variables(n_action, n_pc):\\n y_action_neurons = np.zeros((n_action,1))\\n \\n n_neurons = n_pc+n_action\\n \\n epsp_rise = np.zeros((n_neurons, n_action))\\n epsp_decay = np.zeros((n_neurons, n_action))\\n epsp_tot = np.zeros((n_neurons, n_action))\\n \\n action_firing_rate = np.zeros((n_action,1))\\n action_firing_rise = np.zeros((n_action,1))\\n action_firing_decay = np.zeros((n_action,1))\\n \\n canc = np.ones((1, n_action))\\n \\n last_post_spike = np.zeros((n_action,1)) - 1000 # last spike time of postsynaptic neuron \\n trace_pre_post = np.zeros((n_action, n_pc))\\n trace_post_pre = np.zeros((n_action, n_pc))\\n trace_tot = np.zeros((n_action, n_pc))\\n eligibility_trace = np.zeros((n_action, n_pc))\\n \\n return y_action_neurons, canc, \\\\\\n epsp_rise, epsp_decay, epsp_tot, \\\\\\n action_firing_rate, action_firing_decay, action_firing_rise, \\\\\\n last_post_spike, trace_pre_post, trace_post_pre, trace_tot, eligibility_trace\",\n \"def setup_pwn(name,pwndata,phase, free_radius=5, tempdir=None, emin=1.0e2, emax=1.0e5,maxroi=10,model=None,**kwargs):\\n sources=yaml.load(open(pwndata))\\n\\n catalog_name=sources[name]['catalog']\\n ltcube=sources[name]['ltcube']\\n pulsar_position=SkyDir(*sources[name]['dir'])\\n ft2=sources[name]['ft2']\\n ft1=sources[name]['ft1']\\n\\n # in case no list was passed\\n if len(phase)==2 and isinstance(phase[0],numbers.Real) and \\\\\\n isinstance(phase[1],numbers.Real):\\n\\n # write in case phase wraps around.\\n if phase[0]>phase[1]:\\n phase=[[phase[0],1.0],[0.0,phase[1]]]\\n else:\\n phase = [phase] \\n\\n phase_factor=get_phase_factor(phase)\\n print \\\"phase\\\"\\n print phase\\n print \\\"phase_factor=%.2f\\\"%phase_factor\\n\\n catalog=FermiCatalog(e(\\\"$FERMI/catalogs/gll_psc_v02.fit\\\"),free_radius=free_radius)\\n catalog_source=[i for i in catalog.get_sources(SkyDir(),180) if i.name==catalog_name][0]\\n\\n center=catalog_source.skydir\\n\\n if tempdir is None: tempdir=mkdtemp(prefix='/scratch/')\\n\\n binfile=j(tempdir,'binned_phased.fits')\\n\\n # apply phase cut to ft1 file\\n phased_ft1 = j(tempdir,'ft1_phased.fits')\\n phasetools.phase_cut(ft1,phased_ft1,phaseranges=phase)\\n\\n # create a temporary ltcube scaled by the phase factor\\n# phased_ltcube=j(tempdir,'phased_ltcube.fits')\\n# phase_ltcube(ltcube,phased_ltcube, phase=phase)\\n phased_ltcube=ltcube\\n from uw.like.pointspec import DataSpecification\\n data_specification = DataSpecification(\\n ft1files = phased_ft1,\\n ft2files = ft2,\\n ltcube = phased_ltcube,\\n binfile = binfile)\\n\\n spectral_analysis = SpectralAnalysis(data_specification,\\n binsperdec = 4,\\n emin = 100,\\n emax = 100000,\\n irf = \\\"P6_V3_DIFFUSE\\\",\\n roi_dir = center,\\n maxROI = maxroi,\\n minROI = maxroi)\\n\\n if model == None :\\n roi=spectral_analysis.roi(\\n roi_dir=center,\\n diffuse_sources=get_default_diffuse(diffdir=e(\\\"$FERMI/diffuse\\\"),\\n gfile=\\\"gll_iem_v02.fit\\\",\\n ifile=\\\"isotropic_iem_v02.txt\\\"),\\n catalogs = catalog,\\n phase_factor = 1.0,\\n fit_emin = [emin,emin],\\n fit_emax = [emax,emax],\\n **kwargs)\\n else :\\n roi=spectral_analysis.roi(\\n roi_dir=center,\\n xmlfile = model,\\n phase_factor =1.0,\\n fit_emin = [emin,emin],\\n fit_emax = [emax,emax],\\n **kwargs)\\n\\n print \\\"---------------------Energy range--------------------\\\"\\n \\n print \\\"emin=\\\"+str(roi.bands[0].emin)+\\\"\\\\n\\\"\\n print \\\"emax=\\\"+str(roi.bands[len(roi.bands)-1].emax)+\\\"\\\\n\\\"\\n \\n\\n # keep overall flux of catalog source,\\n # but change the starting index to 2.\\n roi.modify(which=catalog_name, name=name, index=2, \\n keep_old_flux=True)\\n\\n return roi\",\n \"def __init__(self, config):\\n self.config = config\\n self.observation_space = spaces.Box(\\n low=np.array([-15, -15, -15, -15, -15]),\\n high=np.array([15, 15, 15, 15, 15])\\n )\\n self.action_space = spaces.Box(\\n low=np.array([0, 0]),\\n high=np.array([15, 5])\\n )\\n if config[\\\"backend\\\"] == \\\"EH\\\":\\n self.params = {\\n \\\"a_1\\\": 1,\\n \\\"b_1\\\": 3,\\n \\\"c_1\\\": 1,\\n \\\"d_1\\\": 5,\\n \\\"I_ext1\\\": 3.1,\\n \\\"m\\\": 0,\\n \\\"a_2\\\": 6,\\n \\\"tau_2\\\": 10,\\n \\\"I_ext2\\\": .45,\\n \\\"gamma\\\": .01,\\n \\\"r\\\": .00035,\\n \\\"s\\\": 4,\\n \\\"x0\\\": -1.6,\\n }\\n self.sim = EHSim()\\n else:\\n self.params = {\\n \\\"x0\\\": -1.6,\\n \\\"y0\\\": 1,\\n \\\"tau0\\\": 2857,\\n \\\"tau1\\\": 1,\\n \\\"tau2\\\": 10,\\n \\\"I_rst1\\\": 3.1,\\n \\\"I_rst2\\\": .45,\\n \\\"gamma\\\": .01,\\n }\\n self.sim = JSim()\\n self.x1 = 0\\n self.y1 = -5\\n self.z = 5.5\\n self.x2 = 0\\n self.y2 = 0\\n self.frame = 0\\n self.curr_stim = []\\n self.reset()\\n self.history = list()\",\n \"def sequencePreparation(self):\\n #Calculation of the number of frames in function of the duration + LED list for the acquisition\\n if self.seqMode == \\\"rgbMode\\\":\\n self._rgbSequenceInit()\\n elif self.seqMode == 'rbMode':\\n self._rbSequenceInit()\\n else:\\n print('Please select a valid mode of led sequence initialization')\\n #Sending nb of frames to initialize the progress bar\\n if type(self.nbFrames) == int:\\n self.nbFramesSig.emit(self.nbFrames)\\n\\n print('acquisition Side : ', self.expRatio)\\n #Saving the configuration of the experiment file (.json)\\n self.savePath = cfgFileSaving(self.experimentName,\\n self.nbFrames,\\n self.duration,\\n self.expRatio,\\n self.acquMode,\\n self.seqMode,\\n self.rgbLedRatio,\\n self.greenFrameInterval,\\n round(1/self.cycleTime,2), #framerate\\n self.folderPath,\\n self.colorMode,\\n self.mmc,\\n 'Zyla') #WARNING > modulabilty (there is a way to get device label but it's not so easy)\\n\\n #initialization of the acquisition saving files : .tif (frames) and .txt (metadata)\\n (self.tiffWriterList, self.textFile) = filesInit( self.savePath,\\n self.experimentName,\\n self.nbFrames,\\n self.maxFrames)\\n #send all informations to each LED driver\\n self.arduinoSync()\",\n \"def load_params(self, event):\\n \\n self.robot_type = rospy.get_param(\\\"robot_type\\\" , 'pendulum' )\\n self.robot_config = rospy.get_param(\\\"robot_config\\\", 'wrist-only' )\\n self.robot_ctl = rospy.get_param(\\\"controller\\\", 'RfixCTC' )\\n self.fixed_mode = rospy.get_param(\\\"fixed_mode\\\", 1 )\\n \\n \\n ###############################################\\n # Load robot model for the right configuration\\n if self.robot_config == 'wrist-only':\\n self.R = Proto.SingleRevoluteDSDM()\\n \\n elif self.robot_config == 'dual-plane' :\\n self.R = Proto.TwoPlanarSerialDSDM()\\n \\n else:\\n self.R = None\\n \\n ###############################################\\n # Load controller\\n if self.robot_ctl == 'RfixCTC' :\\n self.Ctl = RminCTC.RfixComputedTorqueController( self.R , self.fixed_mode )\\n \\n elif self.robot_ctl == 'RminCTC' :\\n self.Ctl = RminCTC.RminComputedTorqueController( self.R )\\n \\n elif self.robot_ctl == 'RfixSLD' :\\n self.Ctl = RminCTC.RfixSlidingModeController( self.R , self.fixed_mode )\\n \\n elif self.robot_ctl == 'RminSLD' :\\n self.Ctl = RminCTC.RminSlidingModeController( self.R )\\n \\n elif self.robot_ctl == 'RollCTC' :\\n self.Ctl = RollCTC.RolloutComputedTorqueController( self.R )\\n \\n elif self.robot_ctl == 'RollSLD' :\\n self.Ctl = RollCTC.RolloutSlidingModeController( self.R )\\n \\n else:\\n self.Ctl = None\\n \\n \\n if self.robot_config == 'wrist-only':\\n self.Ctl.n_gears = rospy.get_param(\\\"n_gears\\\", 2 )\\n self.x_d = np.array( rospy.get_param(\\\"goal\\\", [0,0] ) )\\n \\n elif self.robot_config == 'dual-plane' :\\n self.Ctl.n_gears = rospy.get_param(\\\"n_gears\\\", 4 )\\n self.x_d = np.array( rospy.get_param(\\\"goal\\\", [0.0,0.0,0.0,0.0] ) )\\n #self.x_d = np.array( [-3.14 , 0 , 0 , 0] )\\n \\n # Gen ctl params\\n self.Ctl.hysteresis = rospy.get_param(\\\"hysteresis\\\", True )\\n self.Ctl.min_delay = rospy.get_param(\\\"min_delay\\\", 0.5 )\\n \\n self.Ctl.w0 = rospy.get_param(\\\"w0\\\", 1 )\\n self.Ctl.zeta = rospy.get_param(\\\"zeta\\\", 0.7 )\\n \\n self.Ctl.lam = rospy.get_param(\\\"lam\\\", 1 )\\n self.Ctl.nab = rospy.get_param(\\\"nab\\\", 1 )\\n self.Ctl.D = rospy.get_param(\\\"D\\\", 0 )\\n \\n self.Ctl.horizon = rospy.get_param(\\\"horizon\\\", 0.5 )\\n self.Ctl.sim_dt = rospy.get_param(\\\"sim_dt\\\", 0.1 )\\n \\n self.Ctl.domain_check = rospy.get_param(\\\"domain_check\\\", False )\\n \\n # Base policy param for roll \\n if self.robot_ctl == 'RollCTC' :\\n self.Ctl.FixCtl.lam = self.Ctl.lam\\n \\n elif self.robot_ctl == 'RollSLD' :\\n self.Ctl.FixCtl.lam = self.Ctl.lam \\n self.Ctl.FixCtl.nab = self.Ctl.nab \\n self.Ctl.FixCtl.D = self.Ctl.D\",\n \"def sweep_timing(dir_out,box,channel,width,delay,scope,min_volt=None):\\n print '____________________________'\\n print width\\n\\n #fixed options\\n height = 16383 \\n fibre_delay = 0\\n trigger_delay = 0\\n pulse_number = 11100 \\n #first select the correct channel and provide settings\\n logical_channel = (box-1)*8 + channel\\n \\n sc.select_channel(logical_channel)\\n sc.set_pulse_width(width)\\n sc.set_pulse_height(16383)\\n sc.set_pulse_number(pulse_number)\\n sc.set_pulse_delay(delay)\\n sc.set_fibre_delay(fibre_delay)\\n sc.set_trigger_delay(trigger_delay)\\n \\n # first, run a single acquisition with a forced trigger, effectively to clear the waveform\\n scope._connection.send(\\\"trigger:state ready\\\")\\n time.sleep(0.1)\\n scope._connection.send(\\\"trigger force\\\")\\n time.sleep(0.1)\\n\\n # Get pin read\\n time.sleep(0.1)\\n sc.fire_sequence() # previously fire_sequence!\\n #wait for the sequence to end\\n tsleep = pulse_number * (delay*1e-3 + 210e-6)\\n time.sleep(tsleep) #add the offset in\\n sc.stop()\\n\\n # File system stuff\\n check_dir(\\\"%s/raw_data/\\\" % (dir_out))\\n directory = check_dir(\\\"%s/raw_data/Channel_%02d/\\\" % (dir_out,logical_channel))\\n channels = [1,4]\\n fnames = []\\n fnames.append(\\\"%sPMTPulseWidth%05d\\\" % (directory,width))\\n fnames.append(\\\"%sTriggerPulseWidth%05d\\\" % (directory,width))\\n \\n # Check scope\\n ck = find_and_set_scope_y_scale(1,height,width,delay,scope,scaleGuess=min_volt)\\n scope.set_edge_trigger(1.4, 4 , falling=False) # Rising edge trigger \\n if ck == True:\\n print \\\"Saving raw files to: %s and %s\\\" % (fnames[0],fnames[1])\\n sc.fire_continuous()\\n time.sleep(0.2)\\n save_ck = save_scopeTraces_Multiple(fnames, scope, channels, 100)\\n sc.stop()\\n time.sleep(5)\\n if save_ck == True:\\n # Calc and return params\\n xPMT,yPMT = calc.readPickleChannel(fnames[0], 1)\\n xTrigger,yTrigger = calc.readPickleChannel(fnames[1], 1)\\n meanJitter, JitterDev, JitterErrorOnMean = calc.calcJitter(xTrigger,yTrigger,xPMT,yPMT)\\n return meanJitter, JitterErrorOnMean\",\n \"def setUp(self):\\n shape = RNG.integers(5, 50)\\n periods = self.periods = RNG.normal() * 3\\n freq = periods / shape\\n amp = RNG.normal()\\n offset = RNG.normal()\\n phase = (RNG.normal() - 1 / 2) * 5 / 3 * np.pi\\n p_gt = self.p_gt = (amp, freq, phase, offset)\\n x = self.x = np.arange(shape)\\n self.data = sine(x, *p_gt)\",\n \"def __init__(self, **kwargs):\\n\\n # mod_path = os.path.join(os.path.dirname(a.__file__), 'BindingPMF.py')\\n # print \\\"\\\"\\\"###########\\n # # AlGDock #\\n # ###########\\n # Molecular docking with adaptively scaled alchemical interaction grids\\n #\\n # in {0}\\n # last modified {1}\\n # \\\"\\\"\\\".format(mod_path, time.ctime(os.path.getmtime(mod_path)))\\n\\n from AlGDock.argument_parser import SimulationArguments\\n self.args = SimulationArguments(**kwargs)\\n\\n from AlGDock.simulation_data import SimulationData\\n self.data = {}\\n self.data['BC'] = SimulationData(self.args.dir['BC'], 'BC', \\\\\\n self.args.params['CD']['pose'])\\n self.data['CD'] = SimulationData(self.args.dir['CD'], 'CD', \\\\\\n self.args.params['CD']['pose'])\\n\\n if not 'max_time' in kwargs.keys():\\n kwargs['max_time'] = None\\n if not 'run_type' in kwargs.keys():\\n kwargs['run_type'] = None\\n\\n from AlGDock.logger import Logger\\n self.log = Logger(self.args, \\\\\\n max_time=kwargs['max_time'], run_type=kwargs['run_type'])\\n\\n self.T_HIGH = self.args.params['BC']['T_HIGH']\\n self.T_TARGET = self.args.params['BC']['T_TARGET']\\n\\n self._setup()\\n\\n print '\\\\n*** Simulation parameters and constants ***'\\n for p in ['BC', 'CD']:\\n print '\\\\nfor %s:' % p\\n print dictionary_tools.dict_view(self.args.params[p])[:-1]\\n\\n self.run(kwargs['run_type'])\",\n \"def __init__(self, initScript = None): \\n super(IdealPump, self).__init__(initScript)\\n\\n self.balance = Balance.Balance(Balance.MOLE_BALANCE | Balance.ENERGY_BALANCE)\\n self.lastPIn = None\\n self.lastPOut = None\\n \\n inPort = self.CreatePort(MAT|IN, IN_PORT)\\n outPort = self.CreatePort(MAT|OUT, OUT_PORT)\\n\\n dpPort = self.CreatePort(SIG, DELTAP_PORT)\\n dpPort.SetSignalType(DELTAP_VAR) \\n \\n qPort = self.CreatePort(ENE|IN, IN_PORT + 'Q')\\n self.balance.AddInput((inPort, qPort))\\n self.balance.AddOutput(outPort)\\n\\n self.SetParameterValue(ISENTROPIC_PAR, 1)\",\n \"def __init__( self, interp, comm, dt, ptcl, v, p_nz, time,\\n ux_m=0., uy_m=0., uz_m=0., ux_th=0., uy_th=0., uz_th=0.,\\n gamma_boost=None ) :\\n # Check that the boundaries are open\\n if ((comm.rank == comm.size-1) and (comm.right_proc is not None)) \\\\\\n or ((comm.rank == 0) and (comm.left_proc is not None)):\\n raise ValueError('The simulation is using a moving window, but '\\n 'the boundaries are periodic.\\\\n Please select open '\\n 'boundaries when initializing the Simulation object.')\\n\\n # Momenta parameters\\n self.ux_m = ux_m\\n self.uy_m = uy_m\\n self.uz_m = uz_m\\n self.ux_th = ux_th\\n self.uy_th = uy_th\\n self.uz_th = uz_th\\n\\n # When running the simulation in boosted frame, convert the arguments\\n if gamma_boost is not None:\\n boost = BoostConverter( gamma_boost )\\n self.uz_m, = boost.longitudinal_momentum([ self.uz_m ])\\n\\n # Attach moving window speed and period\\n self.v = v\\n\\n # Get the positions of the global physical domain\\n zmin_global_domain, zmax_global_domain = comm.get_zmin_zmax(\\n local=False, with_damp=False, with_guard=False )\\n\\n # Attach reference position of moving window (only for the first proc)\\n # (Determines by how many cells the window should be moved)\\n if comm.rank == 0:\\n self.zmin = zmin_global_domain\\n\\n # Attach injection position and speed (only for the last proc)\\n if comm.rank == comm.size-1:\\n self.v_end_plasma = \\\\\\n c * self.uz_m / np.sqrt(1 + ux_m**2 + uy_m**2 + self.uz_m**2)\\n # Initialize plasma *ahead* of the right *physical* boundary of\\n # the box so, after `exchange_period` iterations\\n # (without adding new plasma), there will still be plasma\\n # inside the physical domain. ( +3 takes into account that 3 more\\n # cells need to be filled w.r.t the left edge of the physical box\\n # such that the last cell inside the box is always correct for\\n # 1st and 3rd order shape factor particles after the moving window\\n # shifted by exchange_period cells. )\\n self.z_inject = zmax_global_domain + 3*comm.dz + \\\\\\n comm.exchange_period * (v-self.v_end_plasma) * dt\\n # Try to detect the position of the end of the plasma:\\n # Find the maximal position of the particles which are\\n # continously injected.\\n self.z_end_plasma = None\\n for species in ptcl:\\n if species.continuous_injection and species.Ntot != 0:\\n # Add half of the spacing between particles (the injection\\n # function itself will add a half-spacing again)\\n self.z_end_plasma = species.z.max() + 0.5*comm.dz/p_nz\\n break\\n # Default value in the absence of continuously-injected particles\\n if self.z_end_plasma is None:\\n self.z_end_plasma = zmax_global_domain\\n self.nz_inject = 0\\n self.p_nz = p_nz\\n\\n # Attach time of last move\\n self.t_last_move = time - dt\",\n \"def setup_simulation(system, pdb, integrator):\\n #platform = Platform.getPlatformByName('CPU')\\n platform = Platform.getPlatformByName('OpenCL')\\n prop = {'OpenCLPrecision':'single'}\\n \\n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\\n simulation.context.setPositions(pdb.positions)\\n simulation.minimizeEnergy()\\n simulation.context.setVelocitiesToTemperature(310*kelvin)\\n print('Created simulation')\\n return simulation\",\n \"def simulationDelayedTreatment():\\n\\n delays = [300, 150, 75, 0]\\n colors = [\\\"r\\\", \\\"b\\\", \\\"g\\\", \\\"y\\\"]\\n nbrSim = 500\\n \\n patient = Patient(getViruses(100, 0.1, 0.05, {\\\"guttagonol\\\":False}, 0.05), 1000)\\n \\n for iter in range(len(delays)):\\n print \\\"Simulation with \\\", delays[iter], \\\"delay\\\"\\n totalPopulation = []\\n for sim in range(0, nbrSim):\\n for i in range (0, delays[iter]):\\n patient.update()\\n\\n patient.addPrescription(\\\"guttagonol\\\")\\n \\n for i in range (0, 150):\\n patient.update()\\n \\n totalPopulation.append(patient.update())\\n \\n histPopulation(totalPopulation, \\\"Delay: \\\" + str(delays[iter]), colors[iter])\\n\\n pylab.legend()\\n pylab.show()\",\n \"def setup(self):\\n insts = []\\n for i in range(5):\\n insts.append(pysat.Instrument('pysat', 'testing',\\n clean_level='clean'))\\n self.testC = pysat.Constellation(instruments=insts)\\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n\\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\\n self.testC.bounds = self.bounds\\n self.testI.bounds = self.bounds\\n\\n # Define variables for 1D testing\\n self.one_d_vars = ['dummy1', 'dummy2', 'dummy3']\\n self.unequal_one_d_vars = []\\n\\n return\",\n \"def __init__(self, max_simsecs=30, net=None, noise_sd=0.01, quick=0):\\n Sim.__init__(self, max_simsecs, noise_sd, quick)\\n log.debug('init PoleBalance sim')\\n self.network = net\\n\\n CART_POSITION = (0, 0, 2)\\n POLE_POSITION = (0, 0, 3+(5.0/2))\\n CART_SIZE = (8, 8, 2)\\n POLE_SIZE = (1, 1, 5)\\n HINGE_POSITION = (0, 0, 3)\\n CART_MASS = 10\\n POLE_MASS = 0.5\\n self.MAXF = 1000\\n\\n self.INIT_U = [] # initial force, eg [10000]\\n\\n self.cart_geom = ode.GeomBox(self.space, CART_SIZE)\\n self.geoms.append(self.cart_geom)\\n self.cart_body = ode.Body(self.world)\\n self.cart_body.setPosition(CART_POSITION)\\n cart_mass = ode.Mass()\\n cart_mass.setBoxTotal(CART_MASS, CART_SIZE[0], CART_SIZE[1], CART_SIZE[2])\\n self.cart_body.setMass(cart_mass)\\n self.cart_geom.setBody(self.cart_body)\\n\\n self.pole_geom = ode.GeomBox(self.space, POLE_SIZE)\\n self.geoms.append(self.pole_geom)\\n self.pole_body = ode.Body(self.world)\\n self.pole_body.setPosition(POLE_POSITION)\\n pole_mass = ode.Mass()\\n pole_mass.setBoxTotal(POLE_MASS, POLE_SIZE[0], POLE_SIZE[1], POLE_SIZE[2])\\n self.pole_body.setMass(pole_mass)\\n self.pole_geom.setBody(self.pole_body)\\n\\n self.cart_geom.setCategoryBits(long(0))\\n self.pole_geom.setCategoryBits(long(0))\\n\\n # joint 0 - slide along 1D\\n self.slider_joint = ode.SliderJoint(self.world)\\n self.joints.append(self.slider_joint)\\n self.slider_joint.attach(self.cart_body, ode.environment)\\n self.slider_joint.setAxis((1, 0, 0))\\n self.slider_joint.setParam(ode.ParamLoStop, -5)\\n self.slider_joint.setParam(ode.ParamHiStop, 5)\\n\\n # joint 1 - hinge between the two boxes\\n self.hinge_joint = ode.HingeJoint(self.world)\\n self.joints.append(self.hinge_joint)\\n self.hinge_joint.attach(self.cart_body, self.pole_body)\\n self.hinge_joint.setAnchor(HINGE_POSITION)\\n self.hinge_joint.setAxis((0, 1, 0))\\n\\n self.last_hit = 0.0\\n self.init_u_count = 0\\n self.regular_random_force = 1\\n self.lqr = None\\n self.controlForce = 0\\n self.randomForce = 0\\n self.force_urge = 0\",\n \"def __setup_parameters__(self):\\r\\n self.M=self.N+1\\r\\n self.u=1+self.pu\\r\\n self.d=1-self.pd\\r\\n self.qu=(math.exp((self.r-self.div)*self.dt)-self.d)/(self.u-self.d)\\r\\n self.qd=1-self.qu\",\n \"def setup_simulation(system, pdb, integrator):\\n #platform = Platform.getPlatformByName('CPU')\\n platform = Platform.getPlatformByName('OpenCL')\\n prop = {'OpenCLPrecision':'single'}\\n\\n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\\n simulation.context.setPositions(pdb.positions)\\n simulation.minimizeEnergy()\\n simulation.context.setVelocitiesToTemperature(300*kelvin)\\n print('Created simulation')\\n return simulation\",\n \"def setup(self):\\n\\n warnings.simplefilter(\\\"always\\\", DeprecationWarning)\\n\\n orbit_info = {'index': 'slt', 'kind': 'lt'}\\n self.tinst = pysat.Instrument('pysat', 'testing', orbit_info=orbit_info)\\n self.tinst.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 2))\\n\\n self.warn_msgs = []\\n self.war = \\\"\\\"\\n return\",\n \"def robotInit(self):\\n\\n #Initialize Networktables\\n self.sd = NetworkTables.getTable('SmartDashboard')\\n\\n \\n #Set up motors to drive robot\\n self.M2 = wpilib.VictorSP(2)\\n self.M3 = wpilib.VictorSP(3)\\n #self.M2.setInverted(True)\\n #self.M3.setInverted(True)\\n self.left = wpilib.SpeedControllerGroup(self.M2,self.M3)\\n \\n self.M0 = wpilib.VictorSP(0)\\n self.M1 = wpilib.VictorSP(1)\\n self.right = wpilib.SpeedControllerGroup(self.M0,self.M1)\\n self.drive = wpilib.drive.DifferentialDrive(self.left, self.right)\\n \\n \\n self.stick = wpilib.Joystick(1)\\n self.timer = wpilib.Timer()\\n #Camera\\n wpilib.CameraServer.launch()\\n #Servo\\n self.SV1 = wpilib.Servo(9)\\n self.SV2 = wpilib.Servo(8) \\n #Dashboard\\n NetworkTables.initialize(server='10.61.62.2')\\n #Switches\\n self.SW0 = wpilib.DigitalInput(0)\\n self.SW1 = wpilib.DigitalInput(1)\\n #Elevator\\n self.E = wpilib.VictorSP(5)\\n self.prepareCubeFlag = 0\\n self.grabCubeFlag = 0\\n self.deliverCubeFlag = 0\\n self.adjustLeftFlag=0\\n self.adjustRightFlag=0\\n self.driveFlag=0\\n #Gyro\\n self.gyro = wpilib.ADXRS450_Gyro(0)\\n self.gyro.reset()\\n #All possible autonomous routines in a sendable chooser\\n '''\\n self.chooser = wpilib.SendableChooser()\\n self.chooser.addDefault(\\\"None\\\", '4')\\n self.chooser.addObject(\\\"left-LeftScale\\\", '1')\\n self.chooser.addObject(\\\"Middle-LeftScale\\\", '2')\\n self.chooser.addObject(\\\"Right-LeftScale\\\", '3')\\n self.chooser.addObject(\\\"Left-RightScale\\\", '5')\\n '''\\n #wpilib.SmartDashboard.putData('Choice', self.chooser)\\n #Encoders\\n self.EC1 = wpilib.Encoder(2,3)\\n self.EC2 = wpilib.Encoder(4,5)\\n self.EC1.reset()\\n self.EC2.reset()\",\n \"def __init__ (self, sys='NULL',usett=False,usepcav=False,debug=False):\\n if sys == 'XPP': # set up xpp system\\n print('starting XPP')\\n self.delay = 0.1 # 1 second delay\\n pvname = 'XPP:TIMETOOL:TTALL' # time tool array name\\n matlab_start = 20 # first matlab pv\\n matlab_prefix = 'LAS:FS3:VIT:matlab:' # start of matlab names\\n stagename = 'XPP:LAS:MMN:16' # delay stage for time tool\\n ipmname = 'XPP:SB2:BMMON:SUM' # intensity profile monitor PV\\n\\n elif sys == 'CXI': # set up cxi system\\n print('starting CXI')\\n self.delay = 0.1 # 1 second delay\\n pvname = 'CXI:TIMETOOL:TTALL' # time tool array name\\n matlab_start = 20 # first matlab pv\\n matlab_prefix = 'LAS:FS5:VIT:matlab:' # start of matlab names\\n stagename = 'CXI:LAS:MMN:04' # delay stage for time tool\\n ipmname = 'CXI:DG2:BMMON:SUM' # intensity profile monitor PV\\n \\n elif sys == 'XCS': # set up xcs system\\n print('starting XCS')\\n self.delay = 0.1 # 1 second delay\\n pvname = 'XCS:TIMETOOL:TTALL' # time tool array name\\n matlab_start = 20 # first matlab pv\\n matlab_prefix = 'LAS:FS4:VIT:matlab:' # start of matlab names\\n stagename = 'XCS:LAS:MMN:01' # delay stage for time tool\\n ipmname = 'XCS:SB2:BMMON:SUM' # intensity profile monitor PV\\n\\n else:\\n print(sys + ' not found, exiting')\\n exit()\\n \\n self.usett = usett\\n self.usepcav = usepcav\\n self.debug = debug\\n if usett:\\n print(\\\"Using time tool drift compensation\\\")\\n if usepcav:\\n print(\\\"Using phase cavity drift compensation\\\")\\n if debug:\\n print(\\\"..running in debug mode\\\")\\n pcavpv=['SIOC:UNDH:PT01:0:TIME0','SIOC:UNDH:PT01:0:TIME1'] # PVs for the output time for the two FEH,NC Linac cavities\\n \\n self.ttpv = Pv(pvname)\\n self.ttpv.connect(timeout=1.0) # connect to pv\\n self.stagepv = Pv(stagename)\\n self.stagepv.connect(timeout=1.0)\\n self.ipmpv = Pv(ipmname)\\n self.ipmpv.connect(timeout=1.0)\\n self.pcava=Pv(pcavpv[0])\\n self.pcava.connect(timeout=1.0)\\n self.pcavb=Pv(pcavpv[1])\\n self.pcavb.connect(timeout=1.0)\\n self.matlab_pv = dict() # will hold list of pvs\\n self.values = dict() # will hold the numbers from the time tool\\n self.pcavdata = dict() # will hold values from the phase cavities\\n self.pcavbuffer = deque()\\n # for n in range(0,60):\\n # self.pcavbuffer.append(0.0)\\n self.dccalc = 0\\n self.pcavcalc=0\\n self.limits = dict() # will hold limits from matlab pvs\\n self.old_values = dict() # will hold the old values read from matlab\\n self.nm = ['watchdog', 'pix', 'fs', 'amp', 'amp_second', 'ref', 'FWHM', 'Stage', 'ipm','dcsignal','pcavcomp'] #list of internal names\\n for n in range(0,self.nm.__len__+1): # loop over pvs to create\\n base = matlab_prefix + str(n+matlab_start) # base pv name\\n self.matlab_pv[self.nm[n]] = [Pv(base), Pv(base+'.LOW'), Pv(base+'.HIGH'), Pv(base+'.DESC')] # pv with normal, low and high\\n for x in range(0,4):\\n self.matlab_pv[self.nm[n]][x].connect(timeout=1.0) # connnect to all the various PVs. \\n for x in range(0,3):\\n self.matlab_pv[self.nm[n]][x].get(ctrl=True, timeout=1.0)\\n self.matlab_pv[self.nm[n]][3].put(value = self.nm[n], timeout = 1.0)\\n self.W = watchdog.watchdog(self.matlab_pv[self.nm[0]][0]) # initialize watcdog \",\n \"def trial_prep(self):\\n pass\",\n \"def dynamics(self,eta,nu,u_actual,u_control,sampleTime): \\n \\n # Current velocities\\n u_c = self.V_c * math.cos(self.beta_c - eta[5]) # current surge velocity\\n v_c = self.V_c * math.sin(self.beta_c - eta[5]) # current sway velocity \\n \\n nu_c = np.array([u_c,v_c,0,0,0,0],float) # current velocity vector\\n nu_r = nu - nu_c # relative velocity vector\\n \\n U_r = math.sqrt( nu_r[0]**2 + nu_r[1]**2 ) # relative speed\\n \\n # Rudder command and actual rudder angle\\n delta_c = u_control[0]\\n delta = u_actual[0]\\n \\n # Rudder forces and moment (Fossen 2021, Chapter 9.5.1)\\n b = 0.7 * self.T # rudder height\\n AR = b**2 / self.Lambda # aspect ratio: Lamdba = b**2/AR \\n CN = 6.13 * self.Lambda / ( self.Lambda + 2.25 ) # normal coefficient\\n t_R = 1 - 0.28 * self.Cb - 0.55\\n a_H = 0.4\\n x_R = -0.45 * self.L\\n x_H = -1.0 * self.L\\n\\n Xdd = -0.5 * ( 1 - t_R ) * self.rho * U_r**2 * AR * CN\\n Yd = -0.25 * ( 1 + a_H ) * self.rho * U_r**2 * AR * CN \\n Nd = -0.25 * ( x_R + a_H * x_H ) * self.rho * U_r**2 * AR * CN \\n \\n # Control forces and moment\\n delta_R = -delta # physical rudder angle (rad)\\n T = self.tau_X # thrust (N)\\n t_deduction = 0.1 # thrust deduction number\\n tau1 = ( 1 - t_deduction ) * T - Xdd * math.sin( delta_R )**2 \\n tau2 = -Yd * math.sin( 2 * delta_R ) \\n tau6 = -Nd * math.sin( 2 * delta_R ) \\n tau = np.array( [ tau1, tau2, tau6 ],float) \\n \\n # Linear maneuvering model\\n T_surge = self.L # approx. time constant in surge (s)\\n xg = 0 # approx. x-coordinate, CG (m) \\n \\n # 3-DOF ship model\\n [M,N] = clarke83(U_r,self.L, self.B, self.T,self.Cb,self.R66,xg,T_surge)\\n Minv = np.linalg.inv(M)\\n nu3 = np.array( [ nu_r[0], nu_r[1], nu_r[5] ]) \\n nu3_dot = np.matmul( Minv, tau - np.matmul(N,nu3) ) \\n \\n # 6-DOF ship model\\n nu_dot = np.array( [ nu3_dot[0],nu3_dot[1],0,0,0,nu3_dot[2] ]) \\n\\n # Rudder angle saturation\\n if ( abs(delta) >= self.deltaMax * math.pi / 180 ):\\n delta = np.sign(delta) * self.deltaMax * math.pi / 180\\n \\n # Rudder dynamics\\n delta_dot = (delta_c - delta) / self.T_delta \\n\\n # Forward Euler integration [k+1]\\n nu = nu + sampleTime * nu_dot\\n delta = delta + sampleTime * delta_dot\\n\\n u_actual = np.array([delta],float) \\n\\n return nu, u_actual\",\n \"def __init__(self, t=0.01):\\r\\n\\r\\n\\t\\tself.t = float(t)\\r\\n\\t\\t\\r\\n\\t\\t#Control constants\\r\\n\\t\\t#Altitude\\r\\n\\t\\t#P\\r\\n\\t\\tkp1=3\\r\\n\\t\\t#PID\\r\\n\\t\\tkp2=6\\r\\n\\t\\tki2=0\\r\\n\\t\\tkd2=2.5\\r\\n\\t\\t#PID\\r\\n\\t\\tkp3=0.75\\r\\n\\t\\tki3=1.5\\r\\n\\t\\tkd3=0\\r\\n\\t\\t\\r\\n\\t\\t#Pitch\\r\\n\\t\\t#P\\r\\n\\t\\tkp1_theta=4.5\\r\\n\\t\\t#PID\\r\\n\\t\\tkp2_theta=0.15\\r\\n\\t\\tki2_theta=0.1\\r\\n\\t\\tkd2_theta=0.004\\r\\n\\t\\t\\r\\n\\t\\t#Roll\\r\\n\\t\\t#P\\r\\n\\t\\tkp1_phi=4.5\\r\\n\\t\\t#PID\\r\\n\\t\\tkp2_phi=0.15\\r\\n\\t\\tki2_phi=0.1\\r\\n\\t\\tkd2_phi=0.004\\r\\n\\t\\t\\r\\n\\t\\t#Yaw\\r\\n\\t\\t#P\\r\\n\\t\\tkp1_psi=10\\r\\n\\t\\t#PID\\r\\n\\t\\tkp2_psi=0.2\\r\\n\\t\\tki2_psi=0.02\\r\\n\\t\\tkd2_psi=0\\r\\n\\t\\t\\r\\n\\t\\t#Control\\r\\n\\t\\timax1=10\\r\\n\\t\\tt_max1=200\\r\\n\\t\\timax2=10\\r\\n\\t\\tt_max2=120\\r\\n\\t\\t\\r\\n\\t\\t#Constrains\\r\\n\\t\\trate_imax = 50\\r\\n\\t\\tac_imax = 40\\r\\n\\t\\tt_min = 800\\r\\n\\t\\tt_max = 1500\\r\\n\\t\\t\\r\\n\\t\\t#Goals\\r\\n\\t\\tself.target_z=3\\r\\n\\t\\tself.target_theta=0\\r\\n\\t\\tself.target_phi=0\\r\\n\\t\\tself.target_psi=0\\r\\n\\r\\n\\t\\t#Initial Conditions\\r\\n\\t\\tself.w=[1000, 1000, 1000, 1000]\\r\\n\\t\\t#self.ev = [0, 0, 1, 0, 0, 0, 0, 0, -9.81, 0.4, -0.2, 1, 0.1, -0.1, 0.2, 0.01, -0.01, 0.02]\\r\\n\\t\\tself.ev = [0, 0, 0, 0, 0, 0, 0, 0, -9.81, 0, 0, 0, 0, 0, 0, 0, 0, 0]\\r\\n\\r\\n\\t\\t#Create controllers\\r\\n\\t\\tself.altitudeController = control.controlAlt (self.t, kp1, kp2, ki2, kd2, kp3, ki3, kd3, rate_imax, ac_imax,t_min,t_max)\\r\\n\\t\\tself.thetaController = control.controlAngle (self.t, kp1_theta, kp2_theta, ki2_theta, kd2_theta, imax1, t_max1)\\r\\n\\t\\tself.phiController = control.controlAngle (self.t, kp1_phi, kp2_phi, ki2_phi, kd2_phi, imax1, t_max1)\\r\\n\\t\\tself.psiController = control.controlAngle (self.t, kp1_psi, kp2_psi, ki2_psi, kd2_psi, imax2, t_max2)\",\n \"def run_loop_measurement(t=0.5, name='test', loops=4, pump_t=180, total_t=600, jump_x=10):\\n\\n incident_angles = [0.1, 0.4]\\n waxs_arc = [20, 0]\\n user = \\\"TP\\\"\\n\\n condition = (\\n ( -1 < waxs.arc.position )\\n and ( waxs.arc.position < 1 )\\n and (waxs_arc[0] == 20)\\n )\\n\\n if condition:\\n waxs_arc = waxs_arc[::-1]\\n \\n ranges = { 0.1 : [-16, 16, 33],\\n 0.4 : [-25, 25, 51],\\n }\\n\\n try:\\n ai0 = RE.md['ai_0']\\n except:\\n yield from bp.count([])\\n ai0 = db[-1].start['ai_0']\\n print('Failed to acces RE.md')\\n print(f'\\\\n\\\\nSample flat at theta = {ai0}')\\n \\n proposal_id('2023_2', '311564_Pettersson')\\n #det_exposure_time(t, t)\\n \\n t_initial = time.time()\\n\\n for i in range(loops):\\n t_start = time.time()\\n print('Cycle number',i+1,'started at', (t_start - t_initial)/60)\\n\\n # Wait initial time for pumping to finish\\n print(f'Start pumping now, going to wait for {pump_t} s\\\\n')\\n while (time.time() - t_start) < pump_t:\\n print(f'Pumping time: {(time.time() - t_start):.1f} s')\\n yield from bps.sleep(10)\\n\\n # Go over SAXS and WAXS\\n t_measurement = ( time.time() - t_initial ) / 60\\n for wa in waxs_arc:\\n yield from bps.mv(waxs, wa)\\n dets = [pil900KW] if waxs.arc.position < 15 else [pil1M, pil900KW]\\n\\n for ai in incident_angles:\\n yield from bps.mv(piezo.th, ai0 + ai)\\n yield from bps.mvr(piezo.x, - jump_x)\\n\\n t2 = 2 * t if ai == 0.4 else t\\n det_exposure_time(t2, t2)\\n\\n try:\\n y_range = ranges[ai]\\n except:\\n y_range = [-10, 10, 11]\\n \\n sample_name = f'{name}{get_scan_md()}_time{t_measurement:.1f}_ai{ai}'\\n sample_id(user_name=user, sample_name=sample_name)\\n print(f\\\"\\\\n\\\\n\\\\n\\\\t=== Sample: {sample_name} ===\\\")\\n yield from bp.rel_scan(dets, piezo.y, *y_range, md=dict(ai=ai))\\n \\n yield from bps.mv(waxs, waxs_arc[0],\\n piezo.th, ai0)\\n\\n # Wait until the total loop time passes\\n if i + 1 < loops:\\n print(f'Waiting for the loop to last {total_t} s in total\\\\n')\\n sleep_count = 0\\n while (time.time() - t_start) < total_t:\\n sleep_count += 1\\n if (sleep_count % 10 == 0):\\n print(f'Total time: {(time.time() - t_start):.1f} s')\\n yield from bps.sleep(1)\\n\\n sample_id(user_name=\\\"test\\\", sample_name=\\\"test\\\")\\n det_exposure_time(0.5, 0.5)\",\n \"def _setup(self) -> None:\\n # Call base implementation\\n super()._setup()\\n\\n # Configure the low-level integrator\\n engine_options = self.simulator.engine.get_options()\\n engine_options[\\\"stepper\\\"][\\\"iterMax\\\"] = 0\\n engine_options[\\\"stepper\\\"][\\\"dtMax\\\"] = min(0.02, self.step_dt)\\n engine_options[\\\"stepper\\\"][\\\"logInternalStepperSteps\\\"] = False\\n\\n # Set maximum computation time for single internal integration steps\\n if self.debug:\\n engine_options[\\\"stepper\\\"][\\\"timeout\\\"] = 0.0\\n else:\\n engine_options[\\\"stepper\\\"][\\\"timeout\\\"] = 2.0\\n\\n # Enable logging of geometries in debug mode\\n if self.debug:\\n engine_options[\\\"telemetry\\\"][\\\"isPersistent\\\"] = True\\n\\n # Update engine options\\n self.simulator.engine.set_options(engine_options)\\n\\n # Set robot in neutral configuration\\n qpos = self._neutral()\\n framesForwardKinematics(\\n self.robot.pinocchio_model, self.robot.pinocchio_data, qpos)\",\n \"def simulationDelayedTreatment(numTrials):\\n\\n delays = [300,150,75,0]\\n results = [[],[],[],[]]\\n for place in range(0, 4):\\n for trial in range(numTrials):\\n viruses = []\\n for num in range(100):\\n viruses.append(ResistantVirus(0.1,0.05, {'guttagonol': False}, 0.005))\\n patient = TreatedPatient(viruses, 1000)\\n for delay in range(delays[place]):\\n patient.update()\\n patient.addPrescription(\\\"guttagonol\\\") \\n for l in range(150):\\n patient.update()\\n results[place].append(patient.getTotalPop())\\n pylab.hist(results[0])\\n pylab.hist(results[1])\\n pylab.hist(results[2])\\n pylab.hist(results[3])\\n pylab.show()\\n for x in range(0, 10):\",\n \"def scenario2(sim):\\n n = 83\\n t_start = 25.0\\n duration = 100.0\\n t_stop = 150.0\\n tau_m = 20.0\\n v_thresh = 10.0\\n cm = 1.0\\n cell_params = {\\\"tau_m\\\": tau_m, \\\"v_rest\\\": 0.0, \\\"v_reset\\\": 0.0,\\n \\\"tau_refrac\\\": 100.0, \\\"v_thresh\\\": v_thresh, \\\"cm\\\": cm}\\n I0 = (v_thresh * cm) / tau_m\\n sim.setup(timestep=0.01, min_delay=0.1, spike_precision=\\\"off_grid\\\")\\n neurons = sim.Population(n, sim.IF_curr_exp(**cell_params))\\n neurons.initialize(v=0.0)\\n I = numpy.arange(I0, I0 + 1.0, 1.0 / n)\\n currents = [sim.DCSource(start=t_start, stop=t_start + duration, amplitude=amp)\\n for amp in I]\\n for j, (neuron, current) in enumerate(zip(neurons, currents)):\\n if j % 2 == 0: # these should\\n neuron.inject(current) # be entirely\\n else: # equivalent\\n current.inject_into([neuron])\\n neurons.record(['spikes', 'v'])\\n\\n sim.run(t_stop)\\n\\n spiketrains = neurons.get_data().segments[0].spiketrains\\n assert_equal(len(spiketrains), n)\\n assert_equal(len(spiketrains[0]), 0) # first cell does not fire\\n assert_equal(len(spiketrains[1]), 1) # other cells fire once\\n assert_equal(len(spiketrains[-1]), 1) # other cells fire once\\n expected_spike_times = t_start + tau_m * numpy.log(I * tau_m / (I * tau_m - v_thresh * cm))\\n a = spike_times = [numpy.array(st)[0] for st in spiketrains[1:]]\\n b = expected_spike_times[1:]\\n max_error = abs((a - b) / b).max()\\n print(\\\"max error =\\\", max_error)\\n assert max_error < 0.005, max_error\\n sim.end()\\n return a, b, spike_times\",\n \"def setup_simulation(system, pdb, integrator):\\n #platform = Platform.getPlatformByName('CPU')\\n platform = Platform.getPlatformByName('OpenCL')\\n prop = {'OpenCLPrecision':'single'}\\n \\n simulation = Simulation(pdb.topology, system, integrator, platform, prop)\\n simulation.context.setPositions(pdb.positions)\\n simulation.minimizeEnergy(100)\\n simulation.context.setVelocitiesToTemperature(310*kelvin)\\n print('Created simulation')\\n return simulation\",\n \"def __init__(self,files_atte,files_emis,states,lifetime):\\n self.files_atte = files_atte #!\\n self.files_emis = files_emis #!\\n self.beam_emis = [] #!\\n self.beam_atte = [] #!\\n print('The wavelength assumes an hydrogen atom')\\n self.n_low = states[0] #!\\n self.n_high = states[1] #!\\n self.E0 = -13.6\\n self.lifetime = lifetime\\n self.read_adas()\\n\\n # compute the interpolant\\n self.atte_tck_dens = [] #!\\n self.emis_tck_dens = [] #!\\n self.atte_tck_temp = [] #!\\n self.emis_tck_temp = [] #!\\n for i in range(len(self.beam_atte)):\\n # get data\\n ldensities = np.log(self.get_list_density('atte',i))\\n lbeams = np.log(self.get_list_beams('atte',i))\\n coef_dens = self.get_coef_density('atte',i)\\n lbeams, ldens = np.meshgrid(lbeams, ldensities)\\n \\n # interpolation over beam and density\\n self.atte_tck_dens.append(interpolate.bisplrep(\\n lbeams,ldens,coef_dens,kx=1,ky=1))\\n \\n # get data for the interpolation in temperature\\n T = np.log(self.get_list_temperature('atte',i))\\n coef_T = self.get_coef_T('atte',i)\\n Tref = np.log(self.get_Tref('atte',i))\\n index = abs((Tref-T)/Tref) < 1e-4\\n \\n #interpolation over the temperature\\n self.atte_tck_temp.append(interpolate.splrep(\\n T,coef_T/coef_T[index],k=1))\\n\\n for i in range(len(self.beam_emis)):\\n # get data\\n ldensities = np.log(self.get_list_density('emis',i))\\n lbeams = np.log(self.get_list_beams('emis',i))\\n coef_dens = self.get_coef_density('emis',i)\\n lbeams, ldens = np.meshgrid(lbeams, ldensities)\\n \\n # interpolation over beam and density\\n self.emis_tck_dens.append(interpolate.bisplrep(\\n lbeams,ldens,coef_dens,kx=1,ky=1))\\n\\n # Get data for the interpolation in temperature\\n T = np.log(self.get_list_temperature('emis',i))\\n coef_T = self.get_coef_T('emis',i)\\n Tref = np.log(self.get_Tref('emis',i))\\n index = abs((Tref-T)/Tref) < 1e-4\\n \\n #interpolation over the temperature\\n self.emis_tck_temp.append(interpolate.splrep(\\n T,coef_T/coef_T[index],k=1))\",\n \"def getActpolSim(iterationNum = 0, patch = 'deep5', \\n season = 's13', \\\\\\n array = 'pa1', \\\\\\n psa = None,\\\\\\n noiseDictFile = 'templateInputsMr3c.dict', \\\\\\n noiseDictFilePath = os.path.join(os.path.dirname(os.path.abspath(__file__)),'../inputParams/'), \\\\\\n signalDictFile = 'signal.dict',\\\\\\n signalDictFilePath = os.path.join(os.path.dirname(os.path.abspath(__file__)),'../inputParams/'),\\\\\\n verbose = True,\\\\\\n simType = 'noise',\\n cmbSet = 0,\\n doBeam = True, applyWindow = True, noiseDiagsOnly = False, cmbMaptype = 'LensedCMB', splitWanted = None,\\n applyModulation = True):\\n #update the last one to True if possible\\n\\n\\n#FIXME: get rid of absolute pathnames\\n\\n nDict = flipperDict.flipperDict()\\n nDict.read_from_file(noiseDictFilePath + '/' + noiseDictFile)\\n\\n sDict = flipperDict.flipperDict()\\n sDict.read_from_file(signalDictFilePath + '/' + signalDictFile)\\n \\n if psa == None: #psa stands for patch, season, \\n psa = '%s_%s_%s' %(patch, season, array)\\n\\n\\n #Figure out what frequencies correspond to this array, using the function defined above.\\n psaFreqs = freqsInPsas(psa, nDict['freqsInArrays'])\\n\\n\\n #unroll psa names (normally stored as a nested list of lists)\\n psaList = [item for sublist in nDict['psaList'] for item in sublist]\\n\\n\\n if psa not in psaList:\\n raise ValueError('psa %s not found in psaList; options are ' % (psa ), psaList)\\n\\n\\n noiseSeed = (cmbSet, psaList.index(psa), noiseSeedInd * 4 + (0 if splitWanted is None else splitWanted), iterationNum)\\n\\n #load up one sample map, just to get the shape and wcs info. Do this for \\\"I\\\" at one frequency\\n sampleMap = enmap.read_map(os.path.join(os.path.dirname(os.path.abspath(__file__)))+\\\"/\\\"+nDict['dataMapDir'] + 'totalWeightMap' \\\\\\n + 'I' + '_' + psa + '_' + psaFreqs[0] + '_fromenlib.fits') \\n\\n\\n #Note! Foreground seed is the same for every sky patch, season, and frequency!\\n #This is because they are used to generate fullsky alm's\\n foregroundSeed = (cmbSet, 0, fgSeedInd, iterationNum)\\n\\n\\n\\n if simType == 'noise':\\n\\n return getActpolNoiseSim(noiseSeed = noiseSeed, \\\\\\n psa = psa, \\\\\\n noisePsdDir = os.path.dirname(os.path.abspath(__file__))+\\\"/\\\"+nDict['dataMapDir'],\\n freqs = psaFreqs, \\n verbose = verbose,\\n noiseDiagsOnly = noiseDiagsOnly,\\n splitWanted = splitWanted)\\n\\n elif simType == 'cmb' or simType == 'foregrounds':\\n \\n\\n return getActpolCmbFgSim(beamfileDict = sDict['beamNames'],\\n shape = sampleMap.shape, wcs = sampleMap.wcs,\\n iterationNum = iterationNum,\\n cmbDir = os.path.dirname(os.path.abspath(__file__))+\\\"/\\\"+sDict['cmbDir'],\\n freqs = psaFreqs,\\n psa = psa,\\n cmbSet = cmbSet, \\n doBeam = doBeam, applyWindow = applyWindow,\\n verbose = verbose, cmbMaptype = cmbMaptype, foregroundSeed = foregroundSeed,\\n simType = simType, foregroundPowerFile = sDict['foregroundPowerFile'],\\n applyModulation = applyModulation)\\n\\n\\n else:\\n raise ValueError(\\\"bad input\\\")\",\n \"def ptc_acquisition(self, explow=0.1, exphigh=2, expdelta=0.1, laserchannel = 2, lasercurrent=45.0):\\n\\n #\\n self.laser.select(laserchannel)\\n self.laser.setCurrent(laserchannel, lasercurrent)\\n self.laser.enable()\\n\\n #self.powerup_CCD()\\n self.reb.set_testtype('PTC')\\n\\n #self.DKD.setup_current_measurements(DKD_range)\\n self.PhD.setup_current_measurements(2e-8)\\n\\n # Create the logging summary file\\n summaryfile = os.path.join(eodir, 'summary.log')\\n f = open(summaryfile, 'a')\\n\\n print >>f, \\\"# power\\\\t exposure time\\\\t file name\\\"\\n\\n effpow = self.laser.getPower(laserchannel)\\n # First take bias frames\\n self.log(\\\"Taking bias\\\")\\n m = self.execute_reb_sequence('ClearBias', 0, 20, True )\\n #to have only useful channels:\\n fname = \\\"%s_ptc_bias_%s.fits\\\" % (serno, self.reb.reb.imgtag)\\n i = self.conv_to_fits(channels=validamps)\\n # to save FITS HDU with headers\\n self.save_to_fits(i, m, fitsname=os.path.join(eodir, fname))\\n\\n print >>f, effpow, 0, fname\\n\\n for t in np.arange(explow, exphigh+expdelta, expdelta):\\n # pair of flats\\n for numpair in [1, 2]:\\n effpow = self.laser.getPower(laserchannel)\\n m = self.execute_reb_sequence('Acquisition', t)\\n #to have only useful channels:\\n fname = \\\"%s_ptc_flat%d_%05d_%s.fits\\\" % (serno, numpair, int(t*100), self.reb.reb.imgtag)\\n i = self.conv_to_fits(channels=validamps)\\n # to save FITS HDU with headers\\n self.save_to_fits(i, m, fitsname=os.path.join(eodir, fname))\\n\\n print >>f, effpow, t, fname\\n\\n f.close()\\n\\n # Shutting down (not the lamp by default)\\n self.laser.disable()\\n #self.shutdown_CCD()\\n # p = self.reb.start_waiting_sequence()\",\n \"def setparams (w=None, delay=None, tau=None, low=None, high=None):\\n global firststep\\n for n in nclist: \\n if w is not None: n.weight[0] = w if useHHCell else -w # neg wts are needed for ArtCell (neg driving force for HHCell)\\n if delay is not None: n.delay=delay\\n if firststep or (low and high): # only set this up using defaults the 1st time\\n firststep = False \\n if low is not None: low, high = 10, 11\\n for ce,ran,start in zip(cells, np.random.uniform(low, high, ncells), np.random.uniform(0, 30, ncells)): \\n if useHHCell:\\n ce.stim.amp = ran\\n ce.stim.delay = start\\n else: \\n ce.pp.invl = ran\\n if tau is not None: ce.tau = tau\",\n \"def setup(env, num_machines, washtime, t_inter):\\n # Create the CarWashMachine\\n WashMachine = CarWashMachine(env, num_machines, washtime)\\n\\n # Create 4 initial cars\\n for i in range(4):\\n env.process(car(env, 'Car %d' % i, WashMachine))\\n\\n # Create more cars while the simulation is running\\n while True:\\n yield env.timeout(random.randint(t_inter - 2, t_inter + 2))\\n i += 1\\n env.process(car(env, 'Car %d' % i, WashMachine))\",\n \"def setup_tacs_problems(self, comm):\\n # Overwrite default check values\\n if self.dtype == complex:\\n self.rtol = 1e-8\\n self.atol = 1e-3\\n self.dh = 1e-50\\n else:\\n self.rtol = 1e-1\\n self.atol = 1e-4\\n self.dh = 1e-5\\n\\n # Instantiate FEA Assembler\\n fea_assembler = pytacs.pyTACS(bdf_file, comm)\\n\\n # Set up constitutive objects and elements\\n fea_assembler.initialize()\\n\\n # set transient problem options\\n transientOptions = {\\\"timeIntegrator\\\": \\\"DIRK\\\", \\\"integrationOrder\\\": DIRK_order}\\n\\n # get some problem info\\n n_vpn = fea_assembler.getVarsPerNode()\\n\\n # Create coarse load-specified transient problem\\n coarse_prob = fea_assembler.createTransientProblem(\\n name=\\\"load_coarse\\\",\\n tInit=0.0,\\n tFinal=1.0,\\n numSteps=8,\\n options=transientOptions,\\n )\\n # Create fine load-specified transient problem\\n fine_prob = fea_assembler.createTransientProblem(\\n name=\\\"load_fine\\\",\\n tInit=0.0,\\n tFinal=1.0,\\n numSteps=32,\\n options=transientOptions,\\n )\\n load_probs = [coarse_prob, fine_prob]\\n\\n for prob in load_probs:\\n forces = np.zeros(n_vpn)\\n ns = prob.getNumTimeSteps()\\n for k in range(ns + 1):\\n t_array = prob.getTimeStages(k)\\n for s, t in enumerate(t_array):\\n f = f_mag * t**5\\n forces[2] = f # applied to z-direction\\n prob.addLoadToNodes(\\n timeStep=k,\\n timeStage=s,\\n nodeIDs=21,\\n F=forces,\\n nastranOrdering=True,\\n )\\n\\n for problem in load_probs:\\n problem.addFunction(\\\"mass\\\", functions.StructuralMass)\\n problem.addFunction(\\n \\\"ks_disp\\\",\\n functions.KSDisplacement,\\n direction=[0.0, 0.0, 100.0],\\n ftype=\\\"discrete\\\",\\n )\\n\\n return load_probs, fea_assembler\",\n \"def autonomousInit(self):\\n '''\\n self.cumulativeTime=0\\n self.totalTime=0\\n self.dataSet=[[-0.5,0,1,-1.0],[0.3,0.4,1,1.0],[-0.5,0,1,-1.0]]\\n for i in self.dataSet:\\n self.totalTime+=i[2]\\n self.intervals = 0\\n self.currentTime = 0\\n for i in range(0,len(self.dataSet)):\\n self.dataSet[i].append([self.currentTime,self.currentTime+self.dataSet[i][2]])\\n self.currentTime+=self.dataSet[i][2]\\n for i in self.dataSet:\\n if i[3]==1.0:\\n i.append(\\\"Forward\\\")\\n if i[3]==-1.0:\\n i.append(\\\"Backward\\\")\\n \\n self.timer.reset()\\n self.timer.start()\\n '''\\n self.timer.reset()\\n self.timer.start()\\n\\n #self.auto = self.chooser.getSelected()\\n self.auto = 6\\n self.autoState = 0\\n #self.auto = 1\\n\\n self.EC1.reset()\\n \\n\\n #self.auto = self.chooser.getSelected()\",\n \"async def prepare_measuring(self):\\n # close MDV,\\n # fill the constant tank, start the measurement pumps.\\n self.valves[MEASURING_DRAIN_VALVE].close()\\n await self.tanks[CONSTANT_TANK].fill(keep_source_active=True)\\n self.pumps[PUMP_MEASURING_TANK].stop()\\n self.scale.start()\\n\\n self._state = self.PREPARING_MEASUREMENT\",\n \"def __init__(self) -> None:\\n self.simulation = None\\n self.update_time = 0.1\\n self.time = None\\n self.config = None\",\n \"def _init_system(*args):\\n __set_time_elements(args[0], args[1])\\n __set_control_elements(args[0], args[2], args[3])\\n __set_sensor_elements(args[0], args[4], args[5], args[6], args[7])\",\n \"def __init__(self):\\n # set vars\\n self.__deamon = True\\n _tacho_pin = 'GPIO_PZ0'\\n self._pow_pin = 'CAM_AF_EN'\\n self._mist_pin = 'SPI2_MOSI'\\n _pwm_pin = 'LCD_BL_PW'\\n self._pwm_obj = None\\n self._pump_pin = 'DAP4_DIN'\\n self._sens_level_mist = 'UART2_CTS'\\n self._sens_level_tank = 'DAP4_FS'\\n self._sleep_pin = 'SPI2_SCK'\\n self.__pow = 0\\n self.__hum = 0\\n self.__hum_temp = 100\\n self.__sens_temp = 100\\n self.__t = time.time()\\n self.__rpm = 0\\n\\n # init everything\\n GPIO.setmode(GPIO.TEGRA_SOC)\\n GPIO.setup(self._pow_pin, GPIO.OUT)\\n GPIO.setup(self._mist_pin, GPIO.OUT)\\n GPIO.setup(self._pump_pin, GPIO.OUT)\\n GPIO.setup(_tacho_pin, GPIO.IN)\\n GPIO.setup(self._sens_level_mist, GPIO.IN)\\n GPIO.setup(self._sens_level_tank, GPIO.IN)\\n GPIO.setup(self._sleep_pin, GPIO.IN)\\n GPIO.add_event_detect(_tacho_pin, GPIO.FALLING, self.__fan_int)\\n GPIO.add_event_detect(self._sens_level_tank,\\n GPIO.BOTH, self.__tank)\\n GPIO.add_event_detect(self._sleep_pin, GPIO.FALLING, self.__Sleep)\\n self._tah = temps.Temp()\\n self._led = LED()\\n self.kit = ServoKit(channels=16)\\n self.kit.servo[7].actuation_range = 180\\n self.kit.servo[8].actuation_range = 20\\n self._pwm_obj = GPIO.PWM(_pwm_pin, 1000)\\n self.__mist_thread = threading.Thread(target=self.__mist_deamon)\\n self.__pow_thread = threading.Thread(target=self.__pow_deamon)\\n self.__pump_thread = threading.Thread(target=self.__pump_deamon)\\n self.__mist_thread.start()\\n self.__pow_thread.start()\\n self.__pump_thread.start()\\n self._pwm_obj.start(0)\\n self._led.reset_error()\",\n \"def __init__(self, robot: SmartBot, dt: float):\\n super(Ideal, self).__init__(robot, dt)\",\n \"def setdelay(self):\\n delay=self.inputdelay.getEntry()\\n cmd=\\\"setDelay(\\\"+self.board+','+self.inpedge+','+delay+')'\\n self.vb.io.execute(cmd,log=\\\"out\\\",applout=\\\"<>\\\")\",\n \"def evaluateIFsetup(ants=0, timerange=3.4, deltat=0.1,\\n verbose=False, iniAtten=0) :\\n antlist = makeAntList(ants)\\n for a in antlist:\\n if a < 16:\\n print \\\"SZA antennas only can be used - exiting\\\"\\n return\\n tpMP = \\\"Ifmod.ifTotalPower\\\"\\n attenMP = \\\"Ifmod.totalAtten\\\"\\n currentPos = \\\"AMBIENT\\\"\\n print \\\"Inserting ambient load into beam\\\"\\n rtn = amb(ants)\\n pos1ants = rtn.ready\\n mplist = []\\n for a in pos1ants:\\n prefix = \\\"Sza%d.\\\" %(a-15)\\n mplist.append([prefix+tpMP, prefix+attenMP])\\n #print mplist\\n if len(rtn.notready) != 0:\\n print \\\"Ambient load not inserted for ants:\\\", rtn.notready\\n if iniAtten != None :\\n print \\\"Setting IF atten to %.1f\\\" %iniAtten\\n antennaIFatten(iniAtten, 1, invalidateTsys=False, \\n ants=antlist)\\n wait(tmo=2.0)\\n t0=time.time()\\n antennaIFpower(0.3, ants)\\n t1 = time.time()\\n cmdtime = t1-t0\\n results = []\\n times = []\\n nsamps = int(round(timerange/deltat))\\n for i in range(nsamps):\\n sleep(deltat)\\n dt=time.time()-t1\\n times.append(dt)\\n results.append(queryMpValues(mplist))\\n #print results\\n print \\\"Command time = %.3f seconds\\\" %cmdtime\\n for j in range(len(pos1ants)):\\n aname = \\\"Sza%d\\\" %(pos1ants[j]-15)\\n if verbose: print \\\"======== %s ========\\\" %aname\\n for i in range(nsamps):\\n r = results[i][j]\\n st = \\\"%s: %4.1f %6.3f %4.1f\\\" %(aname,times[i],r[0],r[1])\\n if verbose: print st\\n print \\\"\\\\n==== Inferred timing & final atten =====\\\"\\n for j in range(len(pos1ants)):\\n aname = \\\"Sza%d\\\" %(pos1ants[j]-15)\\n finalAtten = results[nsamps-1][j][1]\\n timing = times[nsamps-1]\\n for i in range(nsamps):\\n index = nsamps-1-i\\n atten = results[index][j][1]\\n if atten != finalAtten: break\\n timing = times[index]\\n st = \\\" %s: %4.1f %4.1f\\\" %(aname,timing, finalAtten)\\n print st\\n \\n #print \\\"Moving ambient load out of the beam\\\"\\n pos2ants = sky(ants).ready\\n # Wait for two seconds to get final psys reading\\n wait(tmo=2.0)\\n skyants = pos2ants\\n complete = []\\n for a in pos1ants :\\n if (pos2ants.count(a) > 0) : complete.append(a)\\n return complete\",\n \"def init_devices(timeStep):\\r\\n\\r\\n robot = Robot()\\r\\n \\r\\n # Obtener dispositivos correspondientes a las ruedas.\\r\\n leftWheel = robot.getDevice('left wheel motor')\\r\\n rightWheel = robot.getDevice('right wheel motor')\\r\\n # Utilizamos velocidad, establecemos posición a infinito.\\r\\n leftWheel.setPosition(float('inf'))\\r\\n rightWheel.setPosition(float('inf')) \\r\\n leftWheel.setVelocity(0)\\r\\n rightWheel.setVelocity(0)\\r\\n\\r\\n # Obtener y activar el dispositivo de la cámara \\r\\n camera = robot.getDevice('camera')\\r\\n camera.enable(timeStep*10)\\r\\n\\r\\n\\r\\n #activar sensores ultrasónicos\\r\\n ultrasonic_sensors = []\\r\\n i = 0\\r\\n for sensor in ultrasonic_sensors_names: \\r\\n ultrasonic_sensors = ultrasonic_sensors + [robot.getDevice(sensor)]\\r\\n ultrasonic_sensors[i].enable(timeStep)\\r\\n i = i + 1\\r\\n print(ultrasonic_sensors_names)\\r\\n\\r\\n #activar sensores infrarojos\\r\\n infrared_sensors = []\\r\\n i = 0\\r\\n for sensor in infrared_sensors_names: \\r\\n infrared_sensors = infrared_sensors + [robot.getDevice(sensor)]\\r\\n infrared_sensors[i].enable(timeStep)\\r\\n i = i + 1\\r\\n \\r\\n return robot, camera, leftWheel, rightWheel , infrared_sensors, ultrasonic_sensors\",\n \"def simulation(self):\\r\\n \\r\\n self.Real.Pbat, self.Real.Pbs, self.Real.soc, self.Real.soc0, self.Real.Pbs0 = batmod_ac(\\r\\n self.d, self.dt, self.Real.soc0, self.Real.soc, self.Real.Pr, self.Real.Pbs0, self.Real.Pbs, self.Real.Pbat)\\r\\n \\r\\n self.Ideal.Pbs, self.Ideal.Pbat, self.Ideal.soc0, self.Ideal.soc = batmod_ac_ideal(\\r\\n self.d, self.dt, self.Ideal.soc0, self.Ideal.soc, self.Ideal.Pr, self.Ideal.Pbat)\",\n \"def eulers_spring(dt=.05,p=1,s0=1,v0=0,t0=0,damp=0,plotit = True,trials = 1000):\\n \\n delta_t = dt\\n \\n\\n s = np.zeros([trials+1])\\n v = np.zeros([trials+1])\\n t = np.zeros([trials+1])\\n s[0] = s0\\n v[0] = v0\\n t[0] = t0\\n \\n for i in range(trials):\\n s[i + 1] = updater(s[i],v[i], delta_t)\\n v[i + 1] = updater(v[i],acceleration(p,s[i],v=v[i],damp=damp),delta_t)\\n t[i + 1] = updater(t[i],1,delta_t)\\n \\n #s[i + 1] = s[i] + v[i] *delta_t #non functional implementation I saw online\\n #v[i + 1] = v[i] + -p*s[i] * delta_t\\n #t[i + 1] = t[i] + delta_t\\n \\n if plotit == True:\\n plt.plot(t,s)\\n plt.plot(t,v)\\n plt.show()\",\n \"def __init__(self, encut, magmom, ldaul, Uparam, Jparam, name=\\\"DFTCL_settings\\\"):\\n\\n cl_settings = {\\\"ISPIN\\\": 2, \\\"MAGMOM\\\": magmom, \\\"SAXIS\\\": None, \\\"LSORBIT\\\": None, \\\"LNONCOLLINEAR\\\": None}\\n dftu_settings = {\\\"LDAU\\\": \\\".TRUE.\\\", \\\"LDAUU\\\": Uparam, \\\"LDATYPE\\\": 2, \\\"LDAUL\\\": ldaul, \\\"LDAUJ\\\": Jparam , \\\"LMAXMIMX\\\": 4}\\n InputParameters.__init__(self, name=name, magnetic_settings=cl_settings, hubbard_settings=dftu_settings)\\n self.update_electronic_settings(\\\"encut\\\", encut)\",\n \"def setup(self):\\n GPIO.setwarnings(False)\\n GPIO.setmode(GPIO.BCM)\\n GPIO.setup(self.Motor_A_EN, GPIO.OUT)\\n GPIO.setup(self.Motor_B_EN, GPIO.OUT)\\n GPIO.setup(self.Motor_A_Pin1, GPIO.OUT)\\n GPIO.setup(self.Motor_A_Pin2, GPIO.OUT)\\n GPIO.setup(self.Motor_B_Pin1, GPIO.OUT)\\n GPIO.setup(self.Motor_B_Pin2, GPIO.OUT)\\n self.motorStop() # Avoids automatic motor rotation after initialization\\n try: # Try is used here to avoid errors due to repeated setting of PWM\\n self.pwm_A = GPIO.PWM(self.Motor_A_EN, 1000)\\n self.pwm_B = GPIO.PWM(self.Motor_B_EN, 1000)\\n except:\\n pass\",\n \"def _setup_simulation_from_parameters(self):\\n for param_name, modifier in self.modifiers:\\n modifier(getattr(self.parameters, param_name))\",\n \"def init_motors(self):\\n # self.maxVelocity = 576# -> 5 m/s\\n # self.maxTorque = 30\\n\\n # motor init\\n for m in self.motors:\\n m.setPosition(float('inf'))\\n m.setVelocity(1.)\\n\\n # Propeller PID control params tunned with Ziegler–Nichols PID\\n K_u = 150.\\n T_u = 342.857 / 1000. # ms\\n # no overshoot\\n params_roll = {'P': K_u / 5., 'I': (2. / 5.) * K_u / T_u,\\n 'D': K_u * T_u / 15., 'sp': 0.}\\n self.rollPID = PID(params_roll['P'], params_roll['I'],\\n params_roll['D'], setpoint=params_roll['sp'],\\n output_limits=(-2., 2.), sample_time=self.deltaT)\\n\\n K_u = 150.\\n T_u = 682.66 / 1000. # ms\\n # no overshoot\\n params_pitch = {'P': K_u/5.,\\n 'I': (2. / 5.) * K_u / T_u,\\n 'D': K_u*T_u/15.,\\n 'sp': 0.}\\n self.pitchPID = PID(params_pitch['P'], params_pitch['I'],\\n params_pitch['D'], setpoint=params_pitch['sp'],\\n output_limits=(-2., 2.), sample_time=self.deltaT)\\n K_u = 20.\\n T_u = 1621.33 / 1000. # ms\\n # PD\\n params_yaw = {'P': 0.8 * K_u,\\n 'I': 0.,\\n 'D': K_u * T_u / 10.,\\n 'sp': self.target_yaw}\\n self.yawPID = PID(params_yaw['P'], params_yaw['I'], params_yaw['D'],\\n setpoint=params_yaw['sp'], output_limits=(-2., 2.),\\n sample_time=self.deltaT, error_map=pi_clip)\\n\\n K_u = 20.\\n T_u = 2668.8 / 1000. # ms\\n # PD\\n params_vert = {'P': 0.8 * K_u,\\n 'I': 0.,\\n 'D': K_u * T_u / 10.,\\n 'sp': self.target_altitude}\\n self.vertPID = PID(params_vert['P'], params_vert['I'],\\n params_vert['D'], setpoint=params_vert['sp'],\\n output_limits=(-5., 5.), sample_time=self.deltaT)\\n\\n return True\",\n \"def simulate_1Dsystem(inps, mdps, method, potfunc, bcs, filetitle,\\n makeplot, plot_freq, make_movie, ebound):\\n\\n steps = inps[0]\\n dt = inps[1]\\n x0 = inps[2]\\n T = inps[3]\\n m = inps[4]\\n xmin = inps[5]\\n xmax = inps[6]\\n xinc = inps[7]\\n kb = inps[13]\\n winit = mdps[0]\\n delta = mdps[1]\\n hfreq = mdps[2]\\n DT = mdps[3]\\n w = np.array([0.0])\\n bcs = bcs[0]\\n dimension = potfunc.dimension\\n if (make_movie == 'True'):\\n if os.path.exists(filetitle+\\\"_movies\\\"):\\n os.rmdir(filetitle+\\\"_movies\\\")\\n os.mkdir(filetitle+\\\"_movies\\\")\\n frame = 0\\n os.chdir(filetitle+\\\"_movies\\\")\\n\\n gamma = inps[12] # Friction factor\\n beta = 1 / T / (kb) # units of 1/kcal\\n\\n xlong = np.arange(xmin, xmax+xinc, xinc)\\n coords = np.empty(int(steps))\\n E = np.empty(int(steps))\\n history = np.array([0.0])\\n dep_count = 0\\n time = np.array([0.0])\\n walkerpot = np.array([0.0])\\n\\n pot_base = potfunc.get_potential(xlong)\\n bias = np.zeros_like(pot_base)\\n iv = potfunc.get_potential(x0)\\n coords[0] = x0\\n if makeplot == 'True':\\n plt.plot(xlong, pot_base, '-b')\\n plt.plot(x0, iv, 'ro', markersize=10)\\n plt.axis([xmin, xmax, ebound[0],\\n ebound[1]])\\n plt.xlabel(\\\"CV(s)\\\")\\n plt.ylabel(\\\"F\\\")\\n plt.draw()\\n plt.pause(0.0001)\\n\\n v0 = np.random.normal(0, 1, 1)\\n T1 = m*v0**2/kb\\n vscaled = v0 * (T/T1)**(0.5)\\n p = vscaled * m\\n # is_periodic = selected_bc(iv, selected_pot(x0)[1], coords[0])[4]\\n\\n FES = np.zeros_like(xlong)\\n icount = np.zeros_like(xlong)\\n\\n E[0] = 0.5*p**2/m + iv\\n\\n info = ('Parameters: \\\\n' + 'Number of steps: ' + str(steps) + '\\\\n' +\\n 'Initial x coordinate ' + str(x0) + '\\\\n' + 'Temperature ' +\\n str(T) + '\\\\n' + 'Timestep ' + str(dt) + '\\\\n' +\\n ' Initial Hill Height ' + str(winit) + '\\\\n' +\\n 'Hill Width ' + str(delta) + '\\\\n' +\\n 'Deposition Frequency (steps)' + str(hfreq) + '\\\\n' +\\n 'Well Temperature ' + str(DT) + '\\\\n' + 'Gaussian ' + str(gamma) +\\n '\\\\n' + 'Potential ' + str(potfunc))\\n i = 0\\n\\n while i < steps - 1:\\n\\n if (method == \\\"Infrequent WT MetaD\\\"):\\n (triggered, path) = potfunc.get_triggered(coords[i])\\n\\n if triggered is True:\\n totaltime = time[i]\\n teff = lf.calc_teff(walkerpot, beta, dt)\\n for xc in range(0, xlong.size):\\n bias[xc] = bias[xc]+lf.calc_biased_pot(xlong[xc],\\n history[dep_count:],\\n w[dep_count:],\\n delta, dimension)\\n [bins, FES] = lf.calc_FES_1D(coords, bias, xlong, method,\\n beta, T, DT)\\n\\n init_center_point = int((x0 - np.min(bins))/(bins[1]-bins[0]))\\n end_center_point = int((coords[i] - np.min(bins)) /\\n (bins[1]-bins[0]))\\n\\n rare_E = FES[end_center_point]\\n initial_E = FES[init_center_point]\\n for a in range(-100, 100):\\n if (end_center_point + a <= FES.size and\\n end_center_point + a > 0):\\n other_rare_E = FES[end_center_point + a]\\n other_initial_E = FES[init_center_point + a]\\n if other_rare_E > rare_E:\\n rare_E = other_rare_E\\n if other_initial_E < initial_E:\\n initial_E = other_initial_E\\n barrier = rare_E - initial_E\\n\\n return (totaltime, teff, info, path, barrier)\\n\\n if sp.mod(i, hfreq) == 0 and i > 0:\\n if(i == hfreq):\\n history[0] = coords[i]\\n w[0] = winit\\n if bcs.type == 'Periodic':\\n history = bcs.add_depositions(coords[i], history)\\n w = np.append(w, winit)\\n w = np.append(w, winit)\\n else:\\n\\n if method == 'Metadynamics':\\n history = np.append(history, coords[i])\\n w = np.append(w, winit)\\n if bcs.type == 'Periodic':\\n (history) = bcs.add_depositions(coords[i], history)\\n w = np.append(w, winit)\\n w = np.append(w, winit)\\n elif (method == 'Well-Tempered Metadynamics' or\\n method == \\\"Infrequent WT MetaD\\\"):\\n VR = lf.calc_biased_pot(coords[i], history, w, delta,\\n dimension)\\n history = np.append(history, coords[i])\\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\\n if bcs.type == 'Periodic':\\n (history) = bcs.add_depositions(coords[i], history)\\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\\n w = np.append(w, winit * np.exp(-VR / (kb*DT)))\\n [pnew, vnew, newcoord, bcbias] = lf.integrate_step(coords[i], history,\\n w, delta, DT,\\n potfunc, bcs, p, m,\\n dt, gamma, beta,\\n dimension)\\n p = pnew\\n\\n coords[i+1] = newcoord\\n E[i+1] = 0.5 * p**2/m + vnew\\n\\n time = np.append(time, dt*(i+1))\\n\\n walkerpot = np.append(walkerpot, lf.calc_biased_pot(coords[i+1],\\n history, w, delta,\\n dimension)+bcbias)\\n if method != \\\"Infrequent WT MetaD\\\":\\n [FES, icount] = recreate_1DFES(FES, icount, coords[i+1],\\n xinc, xmin, xmax, E[i+1])\\n if makeplot == 'True' and sp.mod(i, plot_freq) == 0:\\n\\n for xc in range(0, xlong.size):\\n\\n bias[xc] = bias[xc] + lf.calc_biased_pot(xlong[xc],\\n history[dep_count:],\\n w[dep_count:],\\n delta, dimension)\\n walkv = vnew + lf.calc_biased_pot(coords[i+1], history, w, delta,\\n dimension)\\n # pdb.set_trace()\\n\\n dep_count = len(history)\\n if len(history) == 1:\\n dep_count = dep_count-1\\n\\n plt.clf()\\n plt.plot(xlong, bias+pot_base, '-r')\\n plt.plot(xlong, pot_base, '-b')\\n plt.plot(coords[i+1], walkv, 'ro', markersize=10)\\n plt.axis([xmin, xmax, ebound[0],\\n ebound[1]])\\n plt.xlabel(\\\"CV(s)\\\")\\n plt.ylabel(\\\"F\\\")\\n plt.draw()\\n plt.pause(0.0001)\\n if (make_movie == 'True'):\\n filename = \\\"movieframe\\\" + str(frame)\\n plt.savefig(filename + '.png', bbox_inches='tight')\\n frame = frame + 1\\n i = i + 1\\n\\n if(method != \\\"Infrequent WT MetaD\\\"):\\n if dep_count < len(history):\\n #pdb.set_trace()\\n for xc in range(0, xlong.size):\\n bias[xc] = bias[xc] + lf.calc_biased_pot(xlong[xc],\\n history[dep_count:],\\n w[dep_count:], delta, dimension)\\n\\n FES = lf.calc_FES_1D(coords, bias,\\n xlong, method, beta, T, DT)\\n rmsds = lf.calc_rmsd(FES[1], beta, pot_base)\\n\\n return (coords, E, FES, rmsds, info)\\n\\n elif(method == \\\"Infrequent WT MetaD\\\"):\\n teff = 0\\n info = info + 'NO RARE EVENT'\\n totaltime = 0\\n path = 'NULL'\\n barrier = 0\\n return (totaltime, teff, info, path, barrier)\",\n \"def init_paramters(self):\\r\\n carb_bg_ratio = 5.0\\r\\n time_to_breakdown = 45.0\\r\\n insulin_bg_ratio = 50.0\\r\\n time_to_peak = 45.0\\r\\n basal_rate = 0.0\\r\\n digestion_speed = 1.0\\r\\n activation_speed = 1.0\\r\\n\\r\\n # set state to initial\\r\\n self.S = [self.carb_bg_ratio, self.time_to_breakdown,\\r\\n self.insulin_bg_ratio, self.time_to_peak,\\r\\n self.basal_rate, self.digestion_speed,\\r\\n self.activation_speed]\",\n \"def init_for_run(self, stimulus):\\n # Initialize training traces\\n max_steps = self.settings['maxSteps']\\n self.vars['S_trace'] = torch.zeros((max_steps, self.nSym, 1))\\n self.vars['prev_s'] = torch.tensor(\\n [float('inf')]) * torch.ones((self.nSym, 1))\\n self.vars['Harmony_trace'] = torch.zeros(max_steps)\\n self.vars['speed_trace'] = torch.zeros(max_steps)\\n self.vars['ema_trace'] = torch.zeros(max_steps)\\n self.vars['lambda_trace'] = torch.zeros(max_steps)\\n self.vars['temp_trace'] = torch.zeros(max_steps)\\n self.vars['TP_trace'] = list()\\n self.vars['TPnum_trace'] = torch.zeros(max_steps)\\n self.vars['TP_h_trace'] = torch.zeros(max_steps)\\n self.vars['TP_dist_trace'] = torch.zeros(max_steps)\\n self.vars['maxHarmony'] = torch.empty(\\n self.grammar.nF, self.grammar.nR, self.nStimuli, self.settings['epochs']) # check this size\\n\\n # Create the representations for the stimulus\\n stimulus = fortran_reshape(\\n stimulus, (torch.numel(stimulus), 1)).double()\\n #stimulus = stimulus.reshape((torch.numel(stimulus), 1)).double()\\n # TPR representation of the external input\\n self.inpS = self.TP.matmul(stimulus)\\n #self.inpC = self.TP.T.matmul(self.inpS)\\n self.inpC = self.toConceptual(self.inpS)\\n\\n # ----------- ALTERNATIVE ---------------------\\n # Let's try the matrix version : TPR = Fillers * Bind * Roles\\n #self.inpS = self.F.matmul(stimulus).matmul(self.R)\\n #self.inpC = self.inpS @ torch.pinverse(self.R)\\n # Reshape to make it suitable for MM.\\n #self.inpC = self.inpC.reshape((self.inpC.numel(), 1))\\n #self.inpS = self.inpS.reshape((self.inpS.numel(), 1))\\n # ----------- END ALTERNATIVE ---------------------\\n\\n self.inpS = self.inpS.double()\\n self.inpC = self.inpC.double()\\n\\n # Initialize state\\n self.initial_state = self.settings['initStateMean'] + torch.normal(0.5, .2,\\n (self.grammar.nF, self.grammar.nR)) * self.settings[\\\"initStateStdev\\\"]\\n self.initial_state = self.initial_state.double()\\n self.state = self.toNeural(self.initial_state)\\n self.stateC = self.toConceptual(self.state)\\n\\n # Set Lambda and Temperature\\n self.vars['T'] = self.vars['TInit']\\n self.vars['lambda'] = self.vars['lambdaInit']\\n self.vars['step'] = 0\",\n \"def setUp(self):\\n self.iv1 = Interval(1, 10)\\n self.iv2 = Interval(5, 15)\\n self.iv1_r = Interval(10, 1)\\n self.iv2_r = Interval(15, 5)\\n self.iv3 = Interval(3, 8)\\n self.iv4 = Interval(11, 20)\",\n \"def setup(cls):\\n cls.logger = logging.getLogger('ModelTestLogger')\\n cls.logger.setLevel(logging.DEBUG)\\n\\n s1 = model.Subject('subject1')\\n s2 = model.Subject('subject2')\\n\\n cls.experiment = model.Experiment()\\n cls.experiment.put_subject(s1)\\n cls.experiment.put_subject(s2)\\n\\n setup1 = model.Setup(cls.experiment)\\n modality1 = model.Modality(setup1, 20, 'emg')\\n modality2 = model.Modality(setup1, 5, 'kin')\\n\\n model.Channel(modality1, 'brachoradialis')\\n model.Channel(modality1, 'musculus sterno clavicularis')\\n model.Channel(modality1, 'musculus rhombideus')\\n model.Channel(modality1, 'musculus lattisimus')\\n\\n model.Channel(modality2, 'Pos-X')\\n model.Channel(modality2, 'Pos-Y')\\n model.Channel(modality2, 'Pos-Z')\\n\\n session1 = model.Session(cls.experiment, setup1, s1, 'session1')\\n arr = np.column_stack((\\n np.tile(\\n np.concatenate((\\n np.arange(0., 1., 0.1),\\n np.arange(1., 0., -0.1)\\n )),\\n 10\\n ),\\n np.tile(\\n np.concatenate((\\n np.arange(10),\\n np.arange(10, 0, -1)\\n )),\\n 10\\n ),\\n np.tile(\\n np.concatenate((\\n np.arange(0.0, 0.1, 0.01),\\n np.arange(0.1, 0.0, -0.01)\\n )),\\n 10\\n ),\\n np.tile(\\n np.concatenate((\\n np.arange(0.5, 1.5, 0.1),\\n np.arange(1.5, 0.5, -0.1)\\n )),\\n 10\\n ),\\n ))\\n recording1 = model.Recording(session1, modality1, data=arr,\\n identifier='emg_recording1')\\n\\n arr2 = np.column_stack((\\n np.sum(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1),\\n np.prod(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1),\\n np.square(np.sum(np.mean(arr.reshape(-1, 4, 4), axis=1), axis=1))\\n ))\\n recording2 = model.Recording(session1, modality2, data=arr2,\\n identifier='kin_recording1')\\n for i in range(5):\\n model.Trial(recording1, i * 2, 2)\\n model.Trial(recording2, i * 2, 2)\\n\\n session2 = model.Session(cls.experiment, setup1, s2, 'session2')\\n arr = np.add(arr, np.random.randn(*arr.shape))\\n recording1 = model.Recording(session2, modality1, data=arr,\\n identifier='emg_recording2')\\n arr2 = np.column_stack((\\n np.sin(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1))),\\n np.cos(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1))),\\n np.tan(np.mean(np.sum(arr.reshape(-1, 4, 4), axis=1)))\\n ))\\n recording2 = model.Recording(session2, modality2, data=arr2,\\n identifier='kin_recording2')\\n for i in range(5):\\n model.Trial(recording1, i * 2, 2)\\n model.Trial(recording2, i * 2, 2)\",\n \"def set_IPlay3(self, stimulus, t, amp = None):\\n \\n if self.do_run:\\n \\n for m in self.tvecs:\\n #m.destroy()\\n del m \\n del self.tvecs\\n \\n for m in self.ivecs:\\n #m.destroy()\\n del m \\n del self.ivecs\\n \\n for m in self.plays:\\n #m.destroy()\\n del m \\n del self.plays\\n \\n self.tvecs = []\\n self.ivecs = []\\n self.plays = []\\n \\n for j in self.a_celltype:\\n \\n if amp is None:\\n amp0 = 0\\n else:\\n amp0 = amp[j]\\n \\n tvec = h.Vector(t/ms)\\n self.tvecs.append(tvec) # add to list\\n \\n for i, gid in enumerate(self.gidlist[j]): # for every cell in the gidlist \\n \\n if isinstance(self.factor_celltype[j], ( int, long ) ): \\n ivec = h.Vector(self.factor_celltype[j]*(stimulus*amp0)/nA) \\n else:\\n np.random.seed(gid*40)\\n rnd.seed(gid*40)\\n if self.factor_celltype[j][1] > 0:\\n f = np.random.normal(self.factor_celltype[j][0], self.factor_celltype[j][1], 1).clip(min=0)\\n else:\\n f = self.factor_celltype[j][0] \\n if self.factor_celltype[j][2] > 0: # add inverted input with 50% probability, in future versions this will indicate the propability for -1 and 1\\n f = rnd.sample([-1,1],1)[0] * f\\n if self.id == 0: print \\\"- inverted input with 50% probability:\\\", f \\n if self.id == 0: print \\\"- randomize play stimulus height\\\" \\n ivec = h.Vector(f*(stimulus*amp0)/nA)\\n \\n self.ivecs.append(ivec) # add to list \\n \\n #fluctuating current\\n play = h.IClamp(self.cells[j][i].soma(0.5))\\n play.delay = 0\\n play.dur = 1e9\\n ivec.play(play._ref_amp, tvec, 1)\\n \\n self.plays.append(play) # add to list\\n \\n if self.id == 0: print \\\"set_IPlay3 finished.\\\"\",\n \"def run(config, tim=None):\\n import common_lib\\n import dr_lib\\n import DST\\n \\n if tim is not None:\\n tim.getTime(False)\\n old_time = tim.getOldTime()\\n\\n if config.data is None:\\n raise RuntimeError(\\\"Need to pass a data filename to the driver \\\"\\\\\\n +\\\"script.\\\")\\n\\n # Read in geometry if one is provided\\n if config.inst_geom is not None:\\n if config.verbose:\\n print \\\"Reading in instrument geometry file\\\"\\n \\n inst_geom_dst = DST.getInstance(\\\"application/x-NxsGeom\\\",\\n config.inst_geom)\\n else:\\n inst_geom_dst = None\\n\\n config.so_axis = \\\"time_of_flight\\\"\\n\\n # Steps 1-3: Produce a scaled summed dark current dataset\\n dc_som = dr_lib.scaled_summed_data(config.dkcur, config,\\n dataset_type=\\\"dark_current\\\",\\n timer=tim)\\n\\n # Perform Steps 3-6 on black can data\\n if config.bcan is not None:\\n b_som1 = dr_lib.calibrate_dgs_data(config.bcan, config, dc_som,\\n dataset_type=\\\"black_can\\\",\\n inst_geom_dst=inst_geom_dst,\\n tib_const=config.tib_const,\\n cwp=config.cwp_bcan,\\n timer=tim)\\n else:\\n b_som1 = None\\n\\n # Perform Steps 3-6 on empty can data \\n if config.ecan is not None:\\n e_som1 = dr_lib.calibrate_dgs_data(config.ecan, config, dc_som,\\n dataset_type=\\\"empty_can\\\",\\n inst_geom_dst=inst_geom_dst,\\n tib_const=config.tib_const,\\n cwp=config.cwp_ecan,\\n timer=tim)\\n else:\\n e_som1 = None\\n\\n # Perform Steps 3-6 on normalization data\\n n_som1 = dr_lib.calibrate_dgs_data(config.data, config, dc_som,\\n dataset_type=\\\"normalization\\\",\\n inst_geom_dst=inst_geom_dst,\\n tib_const=config.tib_const,\\n cwp=config.cwp_data,\\n timer=tim)\\n\\n # Perform Steps 7-16 on normalization data\\n if config.norm_trans_coeff is None:\\n norm_trans_coeff = None\\n else:\\n norm_trans_coeff = config.norm_trans_coeff.toValErrTuple()\\n\\n # Determine if we need to rebin the empty or black can data\\n if config.ecan is not None and e_som1 is not None:\\n ecan_cwp = True\\n else:\\n ecan_cwp = False\\n\\n if config.bcan is not None and b_som1 is not None:\\n bcan_cwp = True\\n else:\\n bcan_cwp = False \\n\\n cwp_used = ecan_cwp or bcan_cwp\\n\\n n_som2 = dr_lib.process_dgs_data(n_som1, config, b_som1, e_som1,\\n norm_trans_coeff,\\n dataset_type=\\\"normalization\\\",\\n cwp_used=cwp_used,\\n timer=tim)\\n \\n del n_som1, b_som1, e_som1\\n\\n # Step 17: Integrate normalization spectra\\n if config.verbose:\\n print \\\"Integrating normalization spectra\\\"\\n\\n if tim is not None:\\n tim.getTime(False)\\n\\n if config.norm_int_range is None:\\n start_val = float(\\\"inf\\\")\\n end_val = float(\\\"inf\\\")\\n else:\\n if not config.wb_norm:\\n # Translate energy transfer to final energy\\n ef_start = config.initial_energy.getValue() - \\\\\\n config.norm_int_range[0]\\n ef_end = config.initial_energy.getValue() - \\\\\\n config.norm_int_range[1]\\n # Convert final energy to final wavelength\\n start_val = common_lib.energy_to_wavelength((ef_start, 0.0))[0]\\n end_val = common_lib.energy_to_wavelength((ef_end, 0.0))[0]\\n else:\\n start_val = config.norm_int_range[0]\\n end_val = config.norm_int_range[1]\\n \\n n_som3 = dr_lib.integrate_spectra(n_som2, start=start_val,\\n end=end_val, width=True)\\n\\n del n_som2\\n \\n if tim is not None:\\n tim.getTime(msg=\\\"After integrating normalization spectra \\\")\\n\\n file_comment = \\\"Normalization Integration range: %0.3fA, %0.3fA\\\" \\\\\\n % (start_val, end_val)\\n \\n hlr_utils.write_file(config.output, \\\"text/num-info\\\", n_som3,\\n output_ext=\\\"norm\\\",\\n data_ext=config.ext_replacement,\\n path_replacement=config.path_replacement,\\n verbose=config.verbose,\\n message=\\\"normalization values\\\",\\n comments=[file_comment],\\n tag=\\\"Integral\\\", units=\\\"counts\\\") \\n \\n if tim is not None:\\n tim.getTime(False)\\n\\n if config.verbose:\\n print \\\"Making mask file\\\"\\n\\n # Make mask file from threshold\\n dr_lib.filter_normalization(n_som3, config.lo_threshold,\\n config.hi_threshold, config)\\n\\n if tim is not None:\\n tim.getTime(msg=\\\"After making mask file \\\")\\n\\n # Write out RMD file\\n n_som3.attr_list[\\\"config\\\"] = config\\n\\n hlr_utils.write_file(config.output, \\\"text/rmd\\\", n_som3,\\n output_ext=\\\"rmd\\\",\\n data_ext=config.ext_replacement, \\n path_replacement=config.path_replacement,\\n verbose=config.verbose,\\n message=\\\"metadata\\\")\\n \\n if tim is not None:\\n tim.setOldTime(old_time)\\n tim.getTime(msg=\\\"Total Running Time\\\")\",\n \"def shooterPrep(oe0, oef, A, B, dt, scInfo, dynInfo, time, shooter, plot, body, grav, srp, thirdbod):\\n\\n # Normalizing based off dt1 and mu = 1\\n shooterInfo = {} # dictionary for shooter functions\\n shooterInfo['abtol'] = 1e-12\\n shooterInfo['reltol'] = 1e-12\\n shooterInfo['m0'] = scInfo['m0'] # kg, spacecraft mass\\n t_norm = np.copy(dt) # s, time of first burn\\n r_norm = (dynInfo['mu_host']*t_norm**2)**(1/3) # m\\n shooterInfo['mu_host'] = dynInfo ['mu_host']/r_norm**3*t_norm**2\\n\\n # State\\n meoe0_norm = af.oe2meoe(oe0)\\n meoe0_norm[0] /= r_norm # m\\n meoef_norm = af.oe2meoe(oef)\\n meoef_norm[0] /= r_norm # m\\n\\n # Time\\n shooterInfo['t0'] = dynInfo['t0']/t_norm # s\\n dt_norm = np.copy(dt)/t_norm # s\\n shooterInfo['manTime'] = np.sum(dt)/t_norm # s\\n\\n # BLT parameters\\n A_norm = np.copy(A) # -\\n B_norm = np.copy(B)*t_norm # 1/s\\n\\n # Constants\\n if grav == False and srp == False and thirdbod == False:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host,)\\n\\n elif grav == True and srp == False and thirdbod == False:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n w_host = dynInfo['w_host']*t_norm # rad/s\\n degree = dynInfo['degree'] # -\\n order = dynInfo['order'] # -\\n theta_gst = dynInfo['theta_gst'] # rad\\n gc = dynInfo['gc'] # -\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, degree, order, theta_gst, gc, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, degree, order, theta_gst, gc)\\n\\n elif grav == False and srp == True and thirdbod == False:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_srp_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_srp_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n d_3B = dynInfo['d_3B']/r_norm # m\\n r_3B = dynInfo['r_3B']/r_norm # m\\n Cr = scInfo['Cr'] # -\\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\\n c = con.c/r_norm*t_norm # m/s\\n AU = con.AU*1e3/r_norm # m\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, d_3B, r_3B, Cr, a2m, srp_flux, c, AU, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, d_3B, r_3B, Cr, a2m, srp_flux, c, AU)\\n\\n elif grav == False and srp == False and thirdbod == True:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_3bod_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_3bod_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\\n d_3B = dynInfo['d_3B']/r_norm # m\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, mu_3B, d_3B, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, mu_3B, d_3B)\\n\\n elif grav == True and srp == True and thirdbod == False:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_srp_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_srp_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n w_host = dynInfo['w_host']*t_norm # rad/s\\n d_3B = dynInfo['d_3B']/r_norm # m\\n r_3B = dynInfo['r_3B']/r_norm # m\\n degree = dynInfo['degree'] # -\\n order = dynInfo['order'] # -\\n theta_gst = dynInfo['theta_gst'] # rad\\n gc = dynInfo['gc'] # -\\n Cr = scInfo['Cr'] # -\\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\\n c = con.c/r_norm*t_norm # m/s\\n AU = con.AU*1e3/r_norm # m\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU)\\n\\n elif grav == True and srp == False and thirdbod == True:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_3bod_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_3bod_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n w_host = dynInfo['w_host']*t_norm # rad/s\\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\\n d_3B = dynInfo['d_3B']/r_norm # m\\n degree = dynInfo['degree'] # -\\n order = dynInfo['order'] # -\\n theta_gst = dynInfo['theta_gst'] # rad\\n gc = dynInfo['gc'] # -\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, mu_3B, d_3B, degree, order, theta_gst, gc, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, mu_3B, d_3B, degree, order, theta_gst, gc)\\n\\n elif grav == False and srp == True and thirdbod == True:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_srp_3bod_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_srp_3bod_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\\n d_3B = dynInfo['d_3B']/r_norm # m\\n r_3B = dynInfo['r_3B']/r_norm # m\\n Cr = scInfo['Cr'] # -\\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\\n c = con.c/r_norm*t_norm # m/s\\n AU = con.AU*1e3/r_norm # m\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, mu_3B, d_3B, r_3B, Cr, a2m, srp_flux, c, AU, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, mu_3B, d_3B, r_3B, Cr, a2m, srp_flux, c, AU)\\n\\n elif grav == True and srp == True and thirdbod == True:\\n # Dynamic Files\\n shooterInfo['ode_burn'] = dyn.ode_2bod_grav_srp_3bod_blt_meoe \\n shooterInfo['ode_coast'] = dyn.ode_2bod_grav_srp_3bod_coast_meoe\\n\\n # Necessary Constants\\n mu_host = dynInfo['mu_host']/r_norm**3*t_norm**2 # m3/s2\\n r_host = dynInfo['r_host']/r_norm # m\\n mu_3B = dynInfo['mu_3B']/r_norm**3*t_norm**2 # m3/s2\\n w_host = dynInfo['w_host']*t_norm # rad/s\\n d_3B = dynInfo['d_3B']/r_norm # m\\n r_3B = dynInfo['r_3B']/r_norm # m\\n degree = dynInfo['degree'] # -\\n order = dynInfo['order'] # -\\n theta_gst = dynInfo['theta_gst'] # rad\\n gc = dynInfo['gc'] # -\\n Cr = scInfo['Cr'] # -\\n a2m = scInfo['a2m']/r_norm/r_norm # m2/kg\\n srp_flux = con.srp_flux*t_norm**3 # kg/s3\\n c = con.c/r_norm*t_norm # m/s\\n AU = con.AU*1e3/r_norm # m\\n g0 = con.g0/r_norm*t_norm*t_norm # m/s2\\n T = scInfo['T']/r_norm*t_norm*t_norm # (kg)m/s2\\n isp = scInfo['isp']/t_norm # s\\n\\n shooterInfo['extras_burn'] = (mu_host, r_host, w_host, mu_3B, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU, g0, T, isp)\\n shooterInfo['extras_coast'] = (mu_host, r_host, w_host, mu_3B, d_3B, r_3B, degree, order, theta_gst, gc, Cr, a2m, srp_flux, c, AU)\\n\\n return meoe0_norm, meoef_norm, A_norm, B_norm, dt_norm, shooterInfo, r_norm, t_norm\",\n \"def Inject(self,injector):\\n\\n # Check that the table is set up\\n # NOTE: Make sure singlestarLocation is set before you get here\\n self._TableSetup()\\n\\n # Calculate the star's current age\\n t = integrator.Integrator().time\\n dt = integrator.Integrator().dt\\n age = t-self._tbirth\\n if age > 0.0:\\n if self._wind:\\n # Get energy and mass to inject\\n energy, massloss = singlestar.star_winds(self._mass,age,dt)\\n # Add mass FIRST since KE needs to be added elastically\\n injector.AddMass(massloss)\\n # Add energy to grid as kinetic energy\\n injector.AddKE(energy)\\n # Add some thermal energy to account for star's temperature\\n # TODO: Add star's actual temperature\\n Tstar = 40000.0 # K\\n TE = 1.5 * units.kB * massloss/(units.mH/units.X)*Tstar\\n injector.AddTE(TE)\\n # Set the Courant condition\\n ecourant, mcourant = singlestar.star_winds(self._mass,age,1.0)\\n vwind = np.sqrt(2.0*ecourant/mcourant)\\n integrator.Integrator().CourantLimiter(vwind)\\n if self._radiation:\\n #DO RAD\\n nphotons = singlestar.star_radiation(self._mass,age,dt)\\n # NOTE !!! ASSUMES 5 RADIATION BINS!!!\\n # 1 = IR, 2 = optical+FUV, 3 = H-ionising, \\n # 4 = HeI->HeII, 5 = HeII->HeIII and up\\n nuv = np.sum(nphotons[2:5])\\n injector.AddPhotons(nuv)\",\n \"def __init__(self):\\n super(Config, self).__init__()\\n self.run_control[\\\"output_dir\\\"] = os.getcwd()+\\\"/output/arctan_baseline/single_turn_injection/tracking\\\"\\n ring_tof = 1149.185123\\n field_files = glob.glob(\\\"output/arctan_baseline/bump_quest_v9/find_bump_r_*_theta_90/find_bump_parameters_001.out\\\")\\n substitutions = config.get_baseline_substitution(0.22, ring_tof)\\n substitutions = self.ramp_fields(\\n substitutions,\\n field_files,\\n [i for i, f in enumerate(field_files)],\\n ring_tof,\\n will_step = False\\n )\\n self.substitution_list = [substitutions] # used for plotting unperturbed CO\\n\\n self.run_control[\\\"find_closed_orbits_4d\\\"] = False\\n self.run_control[\\\"find_da\\\"] = False\\n self.run_control[\\\"find_bump_parameters\\\"] = False\\n self.run_control[\\\"track_bump\\\"] = False\\n self.run_control[\\\"track_beam\\\"] = True\\n self.find_closed_orbits[\\\"subs_overrides\\\"][\\\"__n_turns__\\\"] = 0.11\\n self.find_closed_orbits[\\\"subs_overrides\\\"][\\\"__do_bump__\\\"] = False\\n self.find_closed_orbits[\\\"final_subs_overrides\\\"].update(substitutions)\\n self.find_closed_orbits[\\\"max_iterations\\\"] = 0\\n self.find_closed_orbits[\\\"do_minuit\\\"] = True\\n self.find_closed_orbits[\\\"minuit_iterations\\\"] = 10 \\n self.find_closed_orbits[\\\"us_cell\\\"] = 0\\n self.find_closed_orbits[\\\"ds_cell\\\"] = 1\\n\\n self.find_da = {\\n \\\"run_dir\\\":\\\"tmp/find_da/\\\",\\n \\\"probe_files\\\":\\\"RINGPROBE01.h5\\\",\\n \\\"subs_overrides\\\":{\\\"__n_turns__\\\":101.1, \\\"__do_magnet_field_maps__\\\":\\\"False\\\", \\\"__step_size__\\\":0.01},\\n \\\"get_output_file\\\":\\\"get_da\\\",\\n \\\"scan_output_file\\\":\\\"scan_da\\\",\\n \\\"row_list\\\":None,\\n \\\"scan_x_list\\\":[],\\n \\\"scan_y_list\\\":[],\\n \\\"x_seed\\\":1.,\\n \\\"y_seed\\\":1.,\\n \\\"min_delta\\\":0.9,\\n \\\"max_delta\\\":1000.,\\n \\\"required_n_hits\\\":100,\\n \\\"dt_tolerance\\\":0.5, # fraction of closed orbit dt\\n \\\"max_iterations\\\":15,\\n \\\"decoupled\\\":True,\\n }\\n\\n max_amp = 0.01\\n self.track_beam_dummy = {\\n \\\"run_dir\\\":\\\"tmp/track_beam/\\\",\\n \\\"save_dir\\\":\\\"track_beam\\\",\\n \\\"print_events\\\":[0, 1, -1],\\n \\\"settings\\\":[{\\n \\\"name\\\":\\\"forwards\\\",\\n \\\"direction\\\":\\\"forwards\\\",\\n \\\"probe_files\\\":\\\"RINGPROBE01.h5\\\", \\n \\\"beam\\\":{\\n \\\"type\\\":\\\"beam_gen\\\",\\n \\\"closed_orbit_file\\\":\\\"closed_orbits_cache\\\",\\n \\\"eigen_emittances\\\":[[0, 0]]*3,#+[[max_amp, max_amp]],\\n \\\"n_per_dimension\\\":2,\\n \\\"variables\\\":[\\\"x\\\",\\\"x'\\\",\\\"y\\\",\\\"y'\\\"],\\n \\\"amplitude_dist\\\":\\\"uniform\\\", #\\\"grid\\\", # \\n \\\"phase_dist\\\":\\\"uniform\\\", #\\\"grid\\\", # \\n \\\"max_amplitude_4d\\\":max_amp, # amplitude_dist != grid\\n \\\"energy\\\":3.0,\\n },\\n \\\"subs_overrides\\\":{\\n \\\"__n_turns__\\\":45.1,\\n \\\"__hdf5__\\\":\\\"True\\\",\\n \\\"__do_magnet_field_maps__\\\":\\\"False\\\",\\n \\\"__do_bump__\\\":\\\"True\\\",\\n \\\"__step_size__\\\":0.01\\n },\\n },],\\n }\\n\\n T0 = ring_tof\\n self.track_beam = {\\n \\\"run_dir\\\":\\\"tmp/track_beam/\\\",\\n \\\"save_dir\\\":\\\"track_beam_rf_on_2\\\",\\n \\\"print_events\\\":[i for i in range(1)],\\n \\\"variables\\\":[\\\"x\\\", \\\"x'\\\", \\\"y\\\", \\\"y'\\\", \\\"t\\\", \\\"energy\\\"],\\n \\\"settings\\\":[{\\n \\\"name\\\":\\\"grid\\\",\\n \\\"direction\\\":\\\"forwards\\\",\\n \\\"probe_files\\\":\\\"RINGPROBE01.h5\\\", \\n \\\"beam\\\":{\\n \\\"type\\\":\\\"grid\\\",\\n \\\"energy\\\":3.0,\\n \\\"start\\\":[4357.646683446333, 0.0, -116.7090485272821, 0.0, 0.0, 941.272],\\n \\\"stop\\\":[4357.646683446333, 0.0, -116.7090485272821, 0.0, T0, 941.272],\\n \\\"nsteps\\\":[1, 1, 1, 1, 4+1, 1],\\n },\\n \\\"subs_overrides\\\":{\\n \\\"__n_turns__\\\":100.1,\\n \\\"__hdf5__\\\":True,\\n \\\"__do_magnet_field_maps__\\\":False,\\n \\\"__do_bump__\\\":True,\\n \\\"__do_rf__\\\":True,\\n \\\"__do_foil__\\\":False,\\n \\\"__step_size__\\\":0.01\\n },\\n },],\\n }\",\n \"def test_single_ended_trans_att_synthetic():\\n from dtscalibration import DataStore\\n\\n cable_len = 100.0\\n nt = 50\\n nx = 200\\n time = np.arange(nt)\\n x = np.linspace(0.0, cable_len, nx)\\n ts_cold = np.ones(nt) * 4.0\\n ts_warm = np.ones(nt) * 20.0\\n ts_ambient = np.ones(nt) * 12\\n ts_valid = np.ones(nt) * 16\\n\\n C_p = 15246\\n C_m = 2400.0\\n dalpha_r = 0.0005284\\n dalpha_m = 0.0004961\\n dalpha_p = 0.0005607\\n gamma = 482.6\\n cold_mask1 = np.logical_and(x > 0.125 * cable_len, x < 0.25 * cable_len)\\n cold_mask2 = np.logical_and(x > 0.625 * cable_len, x < 0.75 * cable_len)\\n warm_mask1 = np.logical_and(x > 0.75 * cable_len, x < 0.875 * cable_len)\\n warm_mask2 = np.logical_and(x > 0.25 * cable_len, x < 0.375 * cable_len)\\n valid_mask = np.logical_and(x > 0.40 * cable_len, x < 0.50 * cable_len)\\n temp_real = np.ones((len(x), nt)) * 12 + 273.15\\n temp_real[cold_mask1 + cold_mask2] = ts_cold + 273.15\\n temp_real[warm_mask1 + warm_mask2] = ts_warm + 273.15\\n temp_real[valid_mask] = ts_valid + 273.15\\n\\n st = (\\n C_p\\n * np.exp(-dalpha_r * x[:, None])\\n * np.exp(-dalpha_p * x[:, None])\\n * np.exp(gamma / temp_real)\\n / (np.exp(gamma / temp_real) - 1)\\n )\\n ast = (\\n C_m\\n * np.exp(-dalpha_r * x[:, None])\\n * np.exp(-dalpha_m * x[:, None])\\n / (np.exp(gamma / temp_real) - 1)\\n )\\n\\n # Add attenuation\\n tr_att = np.random.rand(nt) * 0.2 + 0.8\\n st[int(x.size * 0.4) :] *= tr_att\\n tr_att2 = np.random.rand(nt) * 0.2 + 0.8\\n st[int(x.size * 0.6) :] *= tr_att2\\n\\n ds = DataStore(\\n {\\n \\\"st\\\": ([\\\"x\\\", \\\"time\\\"], st),\\n \\\"ast\\\": ([\\\"x\\\", \\\"time\\\"], ast),\\n \\\"userAcquisitionTimeFW\\\": ([\\\"time\\\"], np.ones(nt)),\\n \\\"cold\\\": ([\\\"time\\\"], ts_cold),\\n \\\"warm\\\": ([\\\"time\\\"], ts_warm),\\n \\\"ambient\\\": ([\\\"time\\\"], ts_ambient),\\n },\\n coords={\\\"x\\\": x, \\\"time\\\": time},\\n attrs={\\\"isDoubleEnded\\\": \\\"0\\\"},\\n )\\n\\n sections = {\\n \\\"ambient\\\": [slice(0.52 * cable_len, 0.58 * cable_len)],\\n \\\"cold\\\": [\\n slice(0.125 * cable_len, 0.25 * cable_len),\\n slice(0.65 * cable_len, 0.70 * cable_len),\\n ],\\n \\\"warm\\\": [slice(0.25 * cable_len, 0.375 * cable_len)],\\n }\\n\\n ds_test = ds.copy(deep=True)\\n\\n # WLS\\n ds_test.calibration_single_ended(\\n sections=sections,\\n st_var=1.0,\\n ast_var=1.0,\\n method=\\\"wls\\\",\\n trans_att=[40, 60],\\n solver=\\\"sparse\\\",\\n )\\n\\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\\n )\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\\n )\\n\\n # test `trans_att` related functions\\n # Clear out old results\\n ds_test.set_trans_att([])\\n\\n assert ds_test.trans_att.size == 0, \\\"clear out trans_att config\\\"\\n\\n del_keys = []\\n for k, v in ds_test.data_vars.items():\\n if \\\"trans_att\\\" in v.dims:\\n del_keys.append(k)\\n\\n assert len(del_keys) == 0, \\\"clear out trans_att config\\\"\\n\\n ds_test.calibration_single_ended(\\n sections=sections,\\n st_var=1.0,\\n ast_var=1.0,\\n method=\\\"wls\\\",\\n trans_att=[40, 60],\\n solver=\\\"sparse\\\",\\n )\\n\\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\\n )\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\\n )\\n\\n ds_test = ds.copy(deep=True)\\n\\n # Test fixing gamma + transient att.\\n ds_test.calibration_single_ended(\\n sections=sections,\\n st_var=1.0,\\n ast_var=1.0,\\n method=\\\"wls\\\",\\n fix_gamma=(482.6, 0),\\n trans_att=[40, 60],\\n solver=\\\"sparse\\\",\\n )\\n\\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=10)\\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\\n )\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\\n )\\n\\n ds_test = ds.copy(deep=True)\\n\\n # Test fixing alpha + transient att.\\n ds_test.calibration_single_ended(\\n sections=sections,\\n st_var=1.0,\\n ast_var=1.0,\\n method=\\\"wls\\\",\\n fix_dalpha=(6.46e-05, 0),\\n trans_att=[40, 60],\\n solver=\\\"sparse\\\",\\n )\\n\\n assert_almost_equal_verbose(ds_test.gamma.values, gamma, decimal=8)\\n assert_almost_equal_verbose(ds_test.tmpf.values, temp_real - 273.15, decimal=8)\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=0).talpha_fw, -np.log(tr_att), decimal=8\\n )\\n assert_almost_equal_verbose(\\n ds_test.isel(trans_att=1).talpha_fw, -np.log(tr_att2), decimal=8\\n )\",\n \"def setups():\\n setups = []\\n\\n # If you run this in detailed mode, you need to set --t8 to 1e8\\n kotani2017_F2 = dict()\\n kotani2017_F2['name'] = 'kotani2017_F2'\\n kotani2017_F2['piltemplate'] = kotani2017_F2_pil\\n kotani2017_F2['pilparams'] = [None]\\n kotani2017_F2['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\\n kotani2017_F2['simulation'] = [\\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=1'),\\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=0.5'),\\n ('pilsimulator', '--nxy', '--atol', '1e-13', '--rtol', '1e-13', '--mxstep', '10000', '--t8', '36000', '--p0', 'S1=10', 'S2=10', 'R=20', 'C1=0.05')]\\n kotani2017_F2['reporter'] = 'D'\\n kotani2017_F2['exp_results'] = [(7733, 7.42), (11333, 6.18), (25533, 1.40)]\\n setups.append(kotani2017_F2)\\n\\n\\n\\n # If you run this in detailed mode, you need to set --t8 to 1e8\\n kotani2017_F3 = dict()\\n kotani2017_F3['name'] = 'kotani2017_F3'\\n kotani2017_F3['piltemplate'] = kotani2017_F3_pil\\n kotani2017_F3['pilparams'] = [None]\\n kotani2017_F3['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\\n kotani2017_F3['simulation'] = [\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.1'),\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.01'),\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S1=10', 'S2=10', 'S3=10', 'S4=10', 'R=20', 'C1=0.001')]\\n kotani2017_F3['reporter'] = 'D'\\n kotani2017_F3['exp_results'] = [(21220, 7.72), (64203, 3.12), (86996, 0.69)]\\n setups.append(kotani2017_F3)\\n\\n # If you run this in detailed mode, you need to set --t8 to 1e8\\n kotani2017_F4 = dict()\\n kotani2017_F4['name'] = 'kotani2017_F4'\\n kotani2017_F4['piltemplate'] = kotani2017_F4_pil\\n kotani2017_F4['pilparams'] = [None]\\n kotani2017_F4['pepperargs'] = {'condensed': True, 'conc': 'nM', 'release_cutoff': 10}\\n kotani2017_F4['simulation'] = [\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.1'),\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.01'),\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0.001'),\\n ('pilsimulator', '--nxy', '--atol', '1e-10', '--rtol', '1e-10', '--mxstep', '10000', '--t8', '360000', '--p0', 'S5au=10', 'S6au=10', 'R=20', 'C1x=0')]\\n kotani2017_F4['reporter'] = 'D'\\n kotani2017_F4['exp_results'] = [(6815, 6.06), (9004, 4.78), (10278, 4.03), (10795, 3.73)]\\n setups.append(kotani2017_F4)\\n\\n return setups\",\n \"def __init__(self,b,u,v,hbls_old,hbbl_old,Kv_old,Kt_old,srflx,sustr,svstr,f,grid_dict,tstep_mode,dt):\\n \\n # INPUTS FROM TTTW SYSTEM\\n self.b = b #buoyancy field: [Ly,N]\\n self.u = u # x-component of velocity [Ly,N]\\n self.v = v # y-component of velocity [Ly+1,N]\\n self.hbls_old = hbls_old #boundary layer depth from previous time step [Ly]\\n self.hbbl_old = hbbl_old # bottom boundary layer depth from previous time step [Ly]\\n self.Kv_old = Kv_old # momentum mixing coefficeint from previous time step [Ly,N+1]\\n self.Kt_old = Kt_old # tracer mixing coefficient from previous time step [Ly,N+1]\\n self.srflx = srflx #solar heat flux [Ly] (degC * (m/s))\\n self.sustr = sustr # x-component surface wind stress [Ly] (N/m^2) \\n self.svstr = svstr # y-component surface wind stress [Ly+1] (N/m^2)\\n self.grid_dict = grid_dict #gridded data\\n self.f = f #coriolis parameter\\n # KPP-SPECIFIC VARIABLES \\n self.hbls = np.zeros([self.b.shape[0]])\\n self.hbbl = np.zeros([self.b.shape[0]])\\n self.ustar = []\\n self.bvf = [] \\n self.kmo = []\\n self.C_h_MO = []\\n self.kbl = []\\n self.Cr = [] \\n self.Fc = []\\n self.ghat = [] #NONLOCAL TERM: TO BE USED IN TIME STEPPING\\n self.tstep_mode = tstep_mode# if in time steppign mode, turn on HBL_RATE_LIMIT\\n self.dt = dt\",\n \"async def setup_comp(opp):\\n opp.config.units = IMPERIAL_SYSTEM\\n assert await async_setup_component(\\n opp, water_heater.DOMAIN, {\\\"water_heater\\\": {\\\"platform\\\": \\\"demo\\\"}}\\n )\\n await opp.async_block_till_done()\",\n \"def piston_control(self):\\n # At the beginning it is necessary to set some variables\\n t_last = 0 # time of the last cycle\\n inhale_end = time.time() - 1 # End of the last inhale\\n self.cd[\\\"exhale_duration\\\"] = 1\\n self.cd[\\\"inhale_duration\\\"] = 1\\n #now = time.time()\\n VCV_stage = 0\\n PCV_stage = 0\\n PSV_stage = 0\\n emergency_contained = False\\n\\n # Gets the current volume and pressure before starting the cycles. If this doesn't work and \\n # takes too long, there is probably some problem with the sensors\\n t_P, P = (None, None)\\n t_V, V = (None, None)\\n P_V_t_limit = 5\\n first_P_V = time.time()\\n while P == None and V == None:\\n if not self.prs.empty():\\n t_P, P = self.prs.get()\\n if not self.vol.empty():\\n t_V, V = self.vol.get()\\n if time.time() - first_P_V > P_V_t_limit:\\n print(\\\"Took too long to receive new values of P or V from the queues\\\")\\n # TODO Raise exception, error or return in this condition\\n\\n while True:\\n # Gets the newest data and empties que queues. If there was no data, uses the values of \\n # pressure or volume that it already has\\n if not self.prs.empty():\\n t_P, P = self.prs.get()\\n while not self.prs.empty(): # Emptying the queue, only the most recent info is used\\n dump = self.prs.get()\\n\\n if not self.vol.empty():\\n t_V, V = self.vol.get()\\n while not self.vol.empty(): # Emptying the queue, only the most recent info is used\\n dump = self.vol.get()\\n\\n # TODO Needs to be obtained from the interface or defined in a configuration by the user\\n T_inh_max = 60. / self.gui[\\\"VCV_frequency_spb\\\"].value() / 2\\n\\n if self.mode == 1: # 'VCV'\\n \\\"\\\"\\\"\\n This mode has 3 stages:\\n 0 - Wait\\n 1 - Inhale\\n 2 - Exhale\\n \\\"\\\"\\\"\\n period = 60. / self.gui[\\\"VCV_frequency_spb\\\"].value()\\n T_inh_max = period / 2\\n if VCV_stage == 0: \\n self.piston.stop()\\n # If it's time for a new cycle, volume and pressure are within limits\\n if (time.time() - t_last > period\\n and V < self.gui[\\\"VCV_volume_spb\\\"].value()\\n and P < self.gui[\\\"VCV_pressure_max_spb\\\"].value()):\\n VCV_stage = 1\\n inhale_start = time.time()\\n # It is possible to calculate how long the last exhale took\\n self.cd[\\\"exhale_duration\\\"] = inhale_start - inhale_end\\n\\n if VCV_stage == 1:\\n # Checks if the current pressure is above P_max\\n if P >= self.gui[\\\"VCV_pressure_max_spb\\\"].value():\\n print(\\\"Pressure is too high during VCV cycle!\\\")\\n self.piston.stop()\\n # Checks if it reached the maximum inhale t\\n elif time.time() - inhale_start >= T_inh_max:\\n print(f\\\"VCV cycle is too long: {time.time() - inhale_start:.2f} s\\\")\\n self.piston.stop()\\n VCV_stage = 2\\n inhale_end = time.time()\\n # Checks whether the piston reached the bottom\\n # TODO Define what happens in this case\\n elif self.piston.piston_at_bottom:\\n print(\\\"Reached max piston travel\\\")\\n self.piston.stop()\\n VCV_stage = 2\\n inhale_end = time.time()\\n # Checks if the current volume is above target\\n # TODO Implement margin in options\\n elif V >= self.gui[\\\"VCV_volume_spb\\\"].value() * 0.9:\\n print(\\\"Reached target volume\\\")\\n self.piston.stop()\\n VCV_stage = 2 \\n inhale_end = time.time()\\n # if none of the previous limitations occured, may move the piston\\n else:\\n self.piston.pst_down()\\n\\n if VCV_stage == 2:\\n # While the piston still hasn't reached the top\\n # TODO Put timeout in piston raise time\\n if not self.piston.piston_at_top and time.time() - t_last > period:\\n self.piston.pst_up()\\n else:\\n self.piston.stop()\\n VCV_stage = 0\\n # Saves the last inhale start time to calculate when a new one should start\\n t_last = inhale_start\\n # It is possible to calculate how long the last inhale took\\n self.cd[\\\"inhale_duration\\\"] = inhale_end - inhale_start\\n\\n elif self.mode == 2: # 'PCV'\\n \\\"\\\"\\\"\\n This mode has 3 stages:\\n 0 - Wait\\n 1 - Inhale\\n 2 - Exhale\\n \\\"\\\"\\\" \\n period = 60. / self.gui[\\\"PCV_frequency_spb\\\"].value()\\n T_inh_max = period / 2\\n if PCV_stage == 0: \\n self.piston.stop()\\n # If it's time for a new cycle, volume and pressure are within limits\\n if (time.time() - t_last > period\\n and V < self.gui[\\\"PCV_volume_max_spb\\\"].value()\\n and P < self.gui[\\\"PCV_pressure_spb\\\"].value()):\\n PCV_stage = 1\\n inhale_start = time.time()\\n # It is possible to calculate how long the last exhale took\\n self.cd[\\\"exhale_duration\\\"] = inhale_start - inhale_end\\n\\n if PCV_stage == 1:\\n # Checks if the current volume is above max\\n if V >= self.gui[\\\"PCV_volume_max_spb\\\"].value():\\n print(\\\"Volume is too high during PCV cycle!\\\")\\n self.piston.stop()\\n # Checks if it reached the maximum inhale t\\n elif time.time() - inhale_start >= T_inh_max:\\n print(f\\\"PCV cycle is too long: {time.time() - inhale_start:.2f} s\\\")\\n self.piston.stop()\\n PCV_stage = 2\\n inhale_end = time.time()\\n # Checks whether the piston reached the bottom\\n elif self.piston.piston_at_bottom:\\n print(\\\"Reached max piston travel\\\")\\n self.piston.stop()\\n PCV_stage = 2\\n inhale_end = time.time()\\n # Checks if the current pressure is above target\\n elif P >= self.gui[\\\"PCV_pressure_spb\\\"].value():\\n print(\\\"Reached target pressure\\\")\\n self.piston.stop()\\n PCV_stage = 2 \\n inhale_end = time.time()\\n # if none of the previous limitations occured, may move the piston\\n else:\\n self.piston.pst_down()\\n\\n if PCV_stage == 2:\\n # While the piston still hasn't reached the top\\n if not self.piston.piston_at_top and time.time() - t_last > period:\\n self.piston.pst_up()\\n else:\\n self.piston.stop()\\n PCV_stage = 0\\n # Saves the last inhale start time to calculate when a new one should start\\n t_last = inhale_start\\n # It is possible to calculate how long the last inhale took\\n self.cd[\\\"inhale_duration\\\"] = inhale_end - inhale_start\\n\\n elif self.mode == 3: # 'PSV'\\n \\\"\\\"\\\"\\n This mode has 3 stages:\\n 0 - Wait for inhale, P < threshold\\n 1 - Inhale\\n 2 - Exhale\\n \\\"\\\"\\\"\\n if PSV_stage == 0:\\n self.piston.stop()\\n # If the pressure is below the threshold, time to inhale\\n if P < self.gui[\\\"PSV_sensitivity_spb\\\"].value():\\n PSV_stage = 1\\n inhale_start = time.time()\\n # It is possible to calculate how long the last exhale took\\n self.cd[\\\"exhale_duration\\\"] = inhale_start - inhale_end\\n\\n if PSV_stage == 1:\\n # Checks if the current pressure is close to P_target\\n if P >= self.gui[\\\"PSV_pressure_spb\\\"].value():\\n print(\\\"Pressure reached target.\\\")\\n self.piston.stop()\\n PSV_stage = 2\\n inhale_end = time.time()\\n elif self.piston.piston_at_bottom:\\n print(\\\"Reached max piston travel.\\\")\\n self.piston.stop()\\n PSV_stage = 2\\n inhale_end = time.time()\\n # if none of the previous limitations occured, may move the piston\\n else:\\n self.piston.pst_down()\\n \\n if PSV_stage == 2:\\n # While the piston still hasn't reached the top\\n if not self.piston.piston_at_top:\\n self.piston.pst_up()\\n else:\\n self.piston.stop()\\n PSV_stage = 0\\n # Saves the last inhale start time to calculate when a new one should start\\n t_last = inhale_start\\n # It is possible to calculate how long the last inhale took\\n self.cd[\\\"inhale_duration\\\"] = inhale_end - inhale_start\\n\\n # Emergency mode\\n elif self.mode == 4: # 'Emergency'\\n if not emergency_contained:\\n self.piston.emergency()\\n emergency_contained = True\\n else:\\n self.piston.stop()\\n\\n\\n else: # Stop\\n self.piston.stop()\\n\\n # Finds the indexes of data from the last cycle for flow and pressure\\n # i_flw = np.where(time.time() - self.flw_data[0, :] < last_cycle_dur)[0]\\n # i_prs = np.where(time.time() - self.prs_data[0, :] < last_cycle_dur)[0]\\n \\n # Sends the maximum pressure and volume in the last cycle to the interface\\n self.cd[\\\"IE_ratio\\\"] = self.cd[\\\"exhale_duration\\\"] / self.cd[\\\"inhale_duration\\\"]\\n # Saving the data for the GUI update\\n # self.cd[\\\"peak_pressure\\\"] = peak_prs\\n # self.cd[\\\"tidal_volume\\\"] = peak_vol\\n self.signal_cycle_data.emit(self.cd)\\n\\n time.sleep(0.05)\",\n \"def __init__(\\n self,\\n model_domain: ModelDomain,\\n dt: Union[float, timedelta],\\n rnday: Union[float, timedelta],\\n ihfskip: int = None,\\n dramp: Union[float, timedelta] = None,\\n start_date: datetime = None,\\n ibc: Union[Stratification, int, str] = Stratification.BAROTROPIC,\\n drampbc: Union[float, timedelta] = None,\\n stations: Stations = None,\\n nspool: Union[int, timedelta] = None,\\n nhot_write: Union[int, timedelta, bool] = None,\\n server_config: ServerConfig = None,\\n combine_hotstart: Union[str, os.PathLike] = None,\\n cutoff_depth: float = 50.,\\n **surface_outputs\\n ):\\n # init param.nml\\n self._param = Param(model_domain, dt, rnday, dramp, start_date, ibc,\\n drampbc, nspool, ihfskip, nhot_write, stations,\\n **surface_outputs)\\n\\n # init bctides.in\\n self._bctides = Bctides(model_domain, self.param,\\n cutoff_depth=cutoff_depth)\\n\\n # init atmospheric data.\\n self._nws = model_domain.nws\\n\\n # init hydrology data\\n self._hydrology = model_domain.hydrology\\n\\n # init hotstart file\\n self._combine_hotstart = combine_hotstart\\n\\n # init Makefile drivers\\n self._makefile = MakefileDriver(server_config=server_config)\",\n \"def __init__(self, para, ini_cond):\\n\\n # grid\\n self.z = np.linspace(0, para['grid']['zmax'], para['grid']['Nlayers']) # grid [m] above ground\\n self.dz = self.z[1] - self.z[0] # gridsize [m]\\n self.ones = np.ones(len(self.z)) # dummy\\n self.zref = para['zref'] # height of forcing data [m]\\n \\n # moss properties\\n self.hc = para['hc'] # canopy height (m)\\n self.lad = para['lad'] # shoot-area density (m2m-3)\\n self.LAI = sum(self.lad*self.dz)\\n \\n self.canopy_nodes = np.where(self.lad > 0)[0]\\n \\n # hydraulic\\n self.porosity = para['hydraulic']['porosity']\\n self.pF = para['hydraulic']['pF']\\n self.Ksat = para['hydraulic']['Ksat']\\n self.freezing_curve = para['hydraulic']['freezing_curve']\\n \\n # radiation\\n self.albedo = para['radiation'] # 'PAR', 'NIR'\\n self.emissivity = para['radiation']['emissivity']\\n self.clump = para['radiation']['clumping']\\n self.leaf_angle = para['radiation']['leaf_angle']\\n \\n #self.radiation = para['radiation']\\n \\n # compute non-dimensional flow velocity Un = U/ust and momentum diffusivity\\n Utop = ini_cond['Utop'] # U/ust at zref\\n Ubot = 0.0 # no-slip\\n self.Sc = para['Schmidt_nr']\\n _, self.Un, self.Kmn, _ = closure_model_U_moss(self.z, self.lad, self.hc, Utop, Ubot) \\n \\n self.U = None\\n self.Ks = None\\n self.length_scale = para['length_scale']\\n \\n self.Switch_WMA = False\\n \\n # initial states\\n self.T = ini_cond['T']\\n self.Wtot = ini_cond['Wtot']\\n self.Wliq, self.Wice, _ = frozen_water(self.T, self.Wot, fp=self.freezing_curve, To=0.0)\\n self.h = water_retention(self.pF, theta=self.Wliq)\",\n \"def setup(self):\\n insts = []\\n for i in range(2):\\n r_date = dt.datetime(2009, 1, i + 1)\\n insts.append(pysat.Instrument('pysat', 'testing',\\n clean_level='clean',\\n root_date=r_date))\\n self.testC = pysat.Constellation(instruments=insts)\\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n\\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\\n self.testC.bounds = self.bounds\\n self.testI.bounds = self.bounds\\n\\n # Define variables for 1D testing. A more limited set that only\\n # depends upon 'mlt'. Other variables also include longitude, which\\n # can differ between instruments when only binning by 'mlt'.\\n self.one_d_vars = ['dummy1']\\n self.unequal_one_d_vars = ['dummy2', 'dummy3']\\n\\n return\",\n \"def setup(instname):\\n global reducer, inst_name,van_mass,bleed_switch,rate,pixels\\n # debugging (allows to reload changed DirectEnergyConversion package from Mantid)\\n\\n if instname=='MAR' or instname=='mar':\\n print 'setup mari'\\n inst_name='MAR'\\n reducer = DRC.setup_reducer('MARI')\\n bleed_switch=False\\n rate=0.0\\n pixels=0\\n elif instname=='MER' or instname=='mer':\\n print 'setup merlin'\\n inst_name='MER'\\n reducer = DRC.setup_reducer('MERLIN')\\n bleed_switch=True\\n rate=0.01\\n pixels=80\\n elif instname=='MAP' or instname=='map':\\n print 'setup maps'\\n inst_name='MAP'\\n reducer = DRC.setup_reducer('MAPS')\\n bleed_switch=False\\n rate=0.0\\n pixels=0.0\\n elif instname=='LET' or instname=='let':\\n print 'setup let'\\n inst_name='LET'\\n reducer = DRC.setup_reducer('LET')\\n bleed_switch=True\\n rate=0.01\\n pixels=80\\n elif instname=='ARCS' or instname=='arcs':\\n print 'setup Arcs'\\n inst_name='ARC'\\n reducer = DRC.setup_reducer('ARCS')\\n bleed_switch=False\\n rate=0.01\\n pixels=80\\n elif instname=='SEQ' or instname=='seq':\\n print 'setup Sequoia'\\n inst_name='SEQ'\\n reducer = DRC.setup_reducer('SEQUOIA')\\n bleed_switch=False\\n rate=0.01\\n pixels=80\\n elif instname=='CNCS' or instname=='cncs':\\n print 'setup cncs'\\n inst_name='SEQ'\\n reducer = DRC.setup_reducer('CNCS')\\n bleed_switch=False\\n rate=0.01\\n pixels=80\\n elif instname=='HYSPEC' or instname=='hyspec':\\n print 'setup hyspec'\\n inst_name='SEQ'\\n reducer = DRC.setup_reducer('HYSPEC')\\n bleed_switch=False\\n rate=0.01\\n pixels=80\\n else:\\n print 'Instrument name not defined'\\n return \\n van_mass=reducer.get_default_parameter('vanadium-mass')\",\n \"def main():\\n \\n # Particle in SHO - c.f. Mocz & Succi (2015) Fig. 2\\n # parameters\\n n = 100 # number of particles\\n dt = 0.02 # timestep\\n nt = 100 # number of timesteps\\n nt_setup = 400 # number of timesteps to set up simulation\\n n_out = 25 # plot solution every nout steps\\n b = 4 # velocity damping for acquiring initial condition\\n m = 1/n # mass of SPH particle ( m * n = 1 normalizes |wavefunction|^2 to 1)\\n h = 40/n # smoothing length\\n t = 0. # time\\n\\n # plot potential\\n xx = np.linspace(-4.0, 4.0, num=400)\\n xx = np.reshape(xx,(xx.size,1))\\n fig = plt.plot(xx, 0.5*xx**2, linewidth=5, color=[0.7, 0.7, 0.9])\\n \\n # initialize\\n x = np.linspace(-3.0, 3.0, num=n)\\n x = np.reshape(x,(n,1))\\n u = np.zeros((n,1))\\n \\n rho = density( x, m, h )\\n P = pressure( x, rho, m, h )\\n a = acceleration( x, u, m, rho, P, b, h )\\n\\n # get v at t=-0.5*dt for the leap frog integrator using Euler's method\\n u_mhalf = u - 0.5 * dt * a\\n\\n # main loop (time evolution)\\n for i in np.arange(-nt_setup, nt): # negative time (t<0, i<0) is used to set up initial conditions\\n\\n # leap frog\\n u_phalf = u_mhalf + a*dt\\n x = x + u_phalf*dt\\n u = 0.5*(u_mhalf+u_phalf)\\n u_mhalf = u_phalf\\n if (i >= 0):\\n t = t + dt\\n print(\\\"%.2f\\\" % t)\\n \\n if (i == -1 ): # switch off damping before t=0\\n u = np.zeros((n,1)) + 1.0\\n u_mhalf = u\\n b = 0 # switch off damping at time t=0\\n \\n # update densities, pressures, accelerations\\n rho = density( x, m, h )\\n P = pressure( x, rho, m, h )\\n a = acceleration( x, u, m, rho, P, b, h)\\n \\n # plot solution every n_out steps\\n if( (i >= 0) and (i % n_out) == 0 ):\\n xx = np.linspace(-4.0, 4.0, num=400)\\n xx = np.reshape(xx,(xx.size,1))\\n rr = probeDensity(x, m, h, xx)\\n rr_exact = 1./np.sqrt(np.pi) * np.exp(-(xx-np.sin(t))**2/2.)**2\\n fig = plt.plot(xx, rr_exact, linewidth=2, color=[.6, .6, .6])\\n fig = plt.plot(xx, rr, linewidth=2, color=[1.*i/nt, 0, 1.-1.*i/nt], label='$t='+\\\"%.2f\\\" % t +'$')\\n # plot the t<0 damping process for fun\\n if( i==-nt_setup or i==-nt_setup*3/4 or i==-nt_setup/2 ):\\n xx = np.linspace(-4.0, 4.0, num=400)\\n xx = np.reshape(xx,(xx.size,1))\\n rr = probeDensity(x, m, h, xx)\\n fig = plt.plot(xx, rr, linewidth=1, color=[0.9, 0.9, 0.9])\\n \\n plt.legend()\\n plt.xlabel('$x$')\\n plt.ylabel('$|\\\\psi|^2$')\\n plt.axis([-2, 4, 0, 0.8])\\n plt.savefig('solution.pdf', aspect = 'normal', bbox_inches='tight', pad_inches = 0)\\n plt.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.60317343","0.5933767","0.59041595","0.5831756","0.57520694","0.57439333","0.5739036","0.57341063","0.5705485","0.5683423","0.5623893","0.5612428","0.5607956","0.5603607","0.5600375","0.5599384","0.55948526","0.55602384","0.5559706","0.55517477","0.55408883","0.55262274","0.5508686","0.5468752","0.54408324","0.54368925","0.54319364","0.54122734","0.54115576","0.5409604","0.5398396","0.53945565","0.53737617","0.5358529","0.5330032","0.5328408","0.531331","0.53128254","0.53107005","0.5303784","0.5296832","0.52950275","0.52945447","0.52942073","0.529262","0.5291261","0.52889144","0.5278041","0.5276476","0.52753854","0.5274474","0.5270778","0.525647","0.52539855","0.5253417","0.52514726","0.52509576","0.5249904","0.5247865","0.5237114","0.5233042","0.52324843","0.52301985","0.52295846","0.5229179","0.52208906","0.52207553","0.52116334","0.52083695","0.51827216","0.5178896","0.517743","0.5177254","0.5175278","0.51712346","0.5166207","0.5163092","0.51610786","0.51554334","0.51549524","0.51517826","0.5150743","0.51500887","0.514172","0.5141178","0.5139866","0.5138744","0.513511","0.5127747","0.5125037","0.512122","0.51195395","0.51177406","0.51132137","0.51116216","0.51076424","0.5103322","0.5101923","0.5092009","0.50881803"],"string":"[\n \"0.60317343\",\n \"0.5933767\",\n \"0.59041595\",\n \"0.5831756\",\n \"0.57520694\",\n \"0.57439333\",\n \"0.5739036\",\n \"0.57341063\",\n \"0.5705485\",\n \"0.5683423\",\n \"0.5623893\",\n \"0.5612428\",\n \"0.5607956\",\n \"0.5603607\",\n \"0.5600375\",\n \"0.5599384\",\n \"0.55948526\",\n \"0.55602384\",\n \"0.5559706\",\n \"0.55517477\",\n \"0.55408883\",\n \"0.55262274\",\n \"0.5508686\",\n \"0.5468752\",\n \"0.54408324\",\n \"0.54368925\",\n \"0.54319364\",\n \"0.54122734\",\n \"0.54115576\",\n \"0.5409604\",\n \"0.5398396\",\n \"0.53945565\",\n \"0.53737617\",\n \"0.5358529\",\n \"0.5330032\",\n \"0.5328408\",\n \"0.531331\",\n \"0.53128254\",\n \"0.53107005\",\n \"0.5303784\",\n \"0.5296832\",\n \"0.52950275\",\n \"0.52945447\",\n \"0.52942073\",\n \"0.529262\",\n \"0.5291261\",\n \"0.52889144\",\n \"0.5278041\",\n \"0.5276476\",\n \"0.52753854\",\n \"0.5274474\",\n \"0.5270778\",\n \"0.525647\",\n \"0.52539855\",\n \"0.5253417\",\n \"0.52514726\",\n \"0.52509576\",\n \"0.5249904\",\n \"0.5247865\",\n \"0.5237114\",\n \"0.5233042\",\n \"0.52324843\",\n \"0.52301985\",\n \"0.52295846\",\n \"0.5229179\",\n \"0.52208906\",\n \"0.52207553\",\n \"0.52116334\",\n \"0.52083695\",\n \"0.51827216\",\n \"0.5178896\",\n \"0.517743\",\n \"0.5177254\",\n \"0.5175278\",\n \"0.51712346\",\n \"0.5166207\",\n \"0.5163092\",\n \"0.51610786\",\n \"0.51554334\",\n \"0.51549524\",\n \"0.51517826\",\n \"0.5150743\",\n \"0.51500887\",\n \"0.514172\",\n \"0.5141178\",\n \"0.5139866\",\n \"0.5138744\",\n \"0.513511\",\n \"0.5127747\",\n \"0.5125037\",\n \"0.512122\",\n \"0.51195395\",\n \"0.51177406\",\n \"0.51132137\",\n \"0.51116216\",\n \"0.51076424\",\n \"0.5103322\",\n \"0.5101923\",\n \"0.5092009\",\n \"0.50881803\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.611647"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":25698,"cells":{"query":{"kind":"string","value":"This is a mocked integration function to mimic scipy.integrate.quad. It doesn't do anything other than return some value in the correct format."},"document":{"kind":"string","value":"def quad(*args, **kwargs):\n return (42, 0.001)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def sp_integrate_1D ( func , xmin , xmax , *args , **kwargs ) : \n from scipy import integrate\n ##\n result = integrate.quad ( func , xmin , xmax , *args , **kwargs )\n return result[0]","def integrate_fun(fun: Callable, low_b: float, upp_b: float) -> float:\n return integrate.quad(fun, low_b, upp_b)[0]","def integrate(self, t):","def sp_integrate_2D ( func ,\n xmin , xmax ,\n ymin , ymax , *args , **kwargs ) :\n from scipy import integrate\n ##\n result = integrate.dblquad ( func ,\n ymin ,\n ymax ,\n lambda x : xmin ,\n lambda x : xmax , \n *args , **kwargs )\n return result[0]","def integrate(f, inf_lim, sup_lim):\n function = get_function_from_text(f)\n return sp_integrate.quad(function, inf_lim, sup_lim)[0]","def _quad_function(order, *args, **kws):\n params = parameters_spec.copy()\n params.update(kws)\n return quad_function(order, *args, **params)","def integrate(self, *args, **kwargs):\n from sympy.integrals.integrals import integrate\n return integrate(self, *args, **kwargs)","def integrate(x, y, xmin, xmax):\n indexes = get_interval(x, xmin, xmax)\n integral = np.trapz(y[indexes], x[indexes])\n\n return integral","def integrate(self,lower,upper,method=True,n=100,jac=None,**kwargs):\n\n #TODO?: vectorize when needed\n\n import scipy.integrate as itg\n if method is True:\n method=self.defaultIntMethod\n\n e,d=None,None\n\n ps=tuple(self.parvals)\n if jac:\n def f(x,*pars):\n return jac(x,*pars)*self.f(x,*pars)\n else:\n f=self.f\n\n if method=='quad':\n res=itg.quad(f,lower,upper,args=ps,full_output=1,**kwargs)\n if len(res) == 4:\n v,e,d,m = res\n from warnings import warn\n warn('Integration message: %s'%m)\n #use these for 2d and 3d\n #elif method=='dblquad':\n # raise NotImplementedError\n #elif method=='tplquad':\n # raise NotImplementedError\n elif method=='fixed_quad':\n res=itg.fixed_quad(f,lower,upper,ps,5 if n is None else n,**kwargs)\n elif method=='quadrature':\n res=itg.quadrature(f,lower,upper,ps,**kwargs)\n elif method=='romberg':\n res=itg.romberg(f,lower,upper,ps,**kwargs)\n else: #sampled techniques\n if n is None:\n n=100\n if np.isscalar(n):\n x=np.linspace(lower,upper,n)\n else:\n x=np.array(n)\n y=f(x,*ps)\n if method=='trapz':\n res=itg.trapz(y,x,**kwargs)\n elif method=='cumtrapz':\n res=itg.cumtrapz(y,x,**kwargs)\n elif method=='simps':\n res=itg.simps(y,x,**kwargs)\n elif method=='romb':\n res=itg.simps(y,np.convolve(x,[1,-1],mode='same').mean(),**kwargs)\n else:\n raise ValueError('unrecognized integration method')\n\n\n self.lastintegrate = res\n return res if np.isscalar(res) else res[0]","def integrate(func, a, b, tol=1e-8):\n left_pts = []\n result = integ(func, a, b, tol, 0, left_pts)\n\n return result, left_pts","def integrate_f_from0(b):\n integral, err = scipy.integrate.quad(f, 0, b)\n return integral","def integrate(self, x, dx):\n return self.State.integrate(x, dx)","def integrate(f, delta):\r\n I = np.sum(f)\r\n I -= (f[0] + f[-1])/2\r\n I *= delta\r\n return I","def quad(func, a, b, args=()):\n\tx_units = a.units\n\tf_units = func(.5*(a+b)).units\n\n\tI, abserr = sciquad(\n\t\tlambda x : func(x*x_units).to(f_units).magnitude,\n\t\ta.magnitude, b.to(x_units).magnitude,\n\t\targs)\n\n\treturn I*x_units*f_units, abserr*x_units*f_units","def integrate(self):\n raise MethodImplementationError(self, 'integrate')","def integrate_quantity(self, q, mask=None, layer=None):\n if type(q) == str:\n qarr = self.get_scalar_quantity(q)\n else:\n qarr = q\n if layer is not None:\n l = self.layers[layer]\n z_vals = self.Z[l.get_slice(self.Z)]\n qarr = qarr[l.get_slice(self.Z)]\n if mask is not None and len(mask.shape) == 3:\n mask = mask[l.get_slice(self.Z)]\n else:\n z_vals = self.Z\n if mask is not None:\n qarr = qarr*mask\n z_integral = intg.trapz(qarr, x=z_vals, axis=0)\n x_integral = intg.trapz(z_integral, x=self.X, axis=0)\n y_integral = intg.trapz(x_integral, x=self.Y, axis=0)\n return y_integral","def integrate(self, x, dx):\n raise NotImplementedError(\"Not implemented yet.\")","def test_quad1():\n xi = np.array([-1., 0., 2.])\n yi = np.array([ 1., -1., 7.])\n c = quad_interp(xi,yi)\n c_true = np.array([-1., 0., 2.])\n print(\"c = \", c)\n print(\"c_true = \", c_true)\n # test that all elements have small error:\n assert np.allclose(c, c_true), \\\n \"Incorrect result, c = %s, Expected: c = %s\" % (c,c_true)","def test_integrate_fixme(self):\n ans_photlam = 12.39167258 * (u.ph / (u.cm * u.cm * u.s))\n assert_quantity_allclose(\n self.sp.integrate(integration_type='analytical'), ans_photlam)","def integrate(f, m=1, j=0):\n return f.per(dmp_integrate_in(f.rep, m, j, f.lev, f.dom))","def integrate_function():\n def midpoint_integration(f, a, b, n=100):\n h = (b - a)/float(n)\n I = 0\n for i in range(n):\n I += f(a + i*h + 0.5*h)\n return h*I\n\n\n f_formula = sys.argv[1]\n a = eval(sys.argv[2])\n b = eval(sys.argv[3])\n if len (sys.argv) >= 5:\n n = int(sys.arvg[4])\n else:\n n = 200\n\n from scitools.StringFunction import StringFunction\n f = StringFunction(f_formula) # turn formula into f(x) func.\n\n \"\"\"\n >>> g = StringFunction('A*exp(-a*t)*sin(omega*x)',\n independent_variable='t',\n A=1, a=0.1, omega=pi, x=0.5)\n >>> g.set_parameters(omega=0.1)\n >>> g.set_parameters(omega=0.1, A=5, x=0)\n >>> g(0)\n 0.0\n >>> g(pi)\n 2.8382392288852166e-15\n \"\"\"\n\n I = midpoint_integration(f, a, b, n)\n print(\"Integral of {:s} on [{:g}, {:g}] with n ={:d}: {:g}\" \\\n .format(f_formula, a, b, n, I))","def test_integrate_wontfix(self):\n ans_flam = 8.8608168e-09 * (u.erg / (u.cm * u.cm * u.s))\n assert_quantity_allclose(\n self.sp.integrate(wavelengths=self.w, flux_unit='flam',\n integration_type='analytical'), ans_flam)","def integrate(self, *args, **kws):\n gap_handling = kws.get('gap_handling', 'error')\n wbin = Spectrum._groom_integration_ranges(*args)\n\n # check for gap overlap\n # sometimes small numerical errors cause trouble, so compare to size\n # of pixels\n if self.any_gap_overalp(wbin):\n if gap_handling == 'error':\n raise ValueError('Some of the integration ranges cover gaps '\n 'in the spectrum.')\n elif gap_handling == 'zero':\n pass\n else:\n raise ValueError('gap_handling parameter not recognized')\n\n wunit = wbin.unit\n Fs, Es = [], []\n for spec in self.spectra:\n wrange = spec.wbins[[0, -1]].to(wunit).value\n xbins = utils.rangeset_intersect(wbin.value, [wrange])\n if len(xbins) > 0:\n F, E = spec.integrate(xbins*wunit)\n else:\n Funit = spec.y.unit*wunit\n F = 0*Funit\n E = None if spec.e is None else 0*Funit\n Fs.append(F); Es.append(E)\n\n F = sum(Fs)\n if any(E is None for E in Es):\n E = None\n else:\n E = _np.sqrt(sum([E**2 for E in Es]))\n return F, E","def integral(self, dmax, dmin=0):\r\n # more expressive\r\n #return integrate.quad(lambda r: 2*np.pi*r*self(r), dmin, dmax)[0]\r\n return self.bpsf.integral(dmax, dmin)","def solve_integral(integrand, y):\n solnarr = np.empty(len(y))\n for i in range(len(y)):\n yy = y[i]\n soln = quad(integrand, 0, np.inf, args=(yy))\n solnarr[i] = soln[0]\n return solnarr","def integrate(self, x, dx):\n nq, nv, nx, ndx = self.model.nq, self.model.nv, self.nx, self.ndx\n assert (x.shape == (nx, ) and dx.shape == (ndx, ))\n q = x[:nq]\n v = x[-nv:]\n dq = dx[:nv]\n dv = dx[-nv:]\n qn = pinocchio.integrate(self.model, a2m(q), a2m(dq))\n return np.concatenate([qn.flat, v + dv])","def integrate(self, x1, dx):\n return x1 + dx","def integralFunction(xa, ya, xb, yb):\n return psi(xb, yb) - psi(xa, ya)","def test_integrate_spectrum():\n e1 = Quantity(1, \"TeV\")\n e2 = Quantity(10, \"TeV\")\n einf = Quantity(1e10, \"TeV\")\n e = Quantity(1, \"TeV\")\n g = 2.3\n I = Quantity(1e-12, \"cm-2 s-1\")\n\n ref = power_law_energy_flux(I=I, g=g, e=e, e1=e1, e2=e2)\n norm = power_law_flux(I=I, g=g, e=e, e1=e1, e2=einf)\n f = lambda x: x * power_law_evaluate(x, norm, g, e)\n val = integrate_spectrum(f, e1, e2)\n assert_quantity_allclose(val, ref)\n\n # Test quantity handling\n e2_ = Quantity(1e4, \"GeV\")\n val_ = integrate_spectrum(f, e1, e2_)\n assert_quantity_allclose(val, val_)","def integrate_base(self, t):\n\n return self.__integrate_base(t)","def quad(self, y, z=None, method=\"sptrapz\"):\n return self.rsphere * self.dlam * np.sum(self.quad_meridional(y, z, method))","def eo_numerical(th):\n res = integrate.dblquad(gaussian_func_2dim_extra, th, np.inf, lambda x: th, lambda x: np.inf)\n return res[0]","def quadTo(self, *__args): # real signature unknown; restored from __doc__ with multiple overloads\r\n pass","def calc_quad(self,mw,A0,A1,A2): \n return (A0 + A1 * mw + A2 * mw**2)","def integrate(u, j, h):\n y = u[j]\n return (h/2.)*((y[0]+y[-1]) + 2*sum(y[1:-1]))","def test_quad_grid_volume_integration(self):\n r = 1\n R = 10\n vol = 2 * (np.pi**2) * (r**2) * R\n\n inputs = {\n \"L\": 1,\n \"M\": 1,\n \"N\": 0,\n \"NFP\": 1,\n \"Psi\": 1.0,\n \"pressure\": np.array([[0, 0]]),\n \"iota\": np.array([[0, 0]]),\n \"surface\": np.array([[0, 0, 0, R, 0], [0, 1, 0, r, 0], [0, -1, 0, 0, -r]]),\n \"spectral_indexing\": \"ansi\",\n \"bdry_mode\": \"lcfs\",\n \"node_pattern\": \"quad\",\n }\n\n eq = Equilibrium(**inputs)\n grid = QuadratureGrid(L=eq.L, M=eq.M, N=eq.N, NFP=eq.NFP)\n g = eq.compute(\"sqrt(g)\", grid=grid)\n vol_quad = np.sum(np.abs(g[\"sqrt(g)\"]) * grid.weights)\n\n np.testing.assert_allclose(vol, vol_quad)","def test_functions():\n\n isGood = True\n\n # Test the trapezoidal integration function\n trapz = integrate_trapz(f, 0, 1, N=1000)[0]\n if abs(trapz - 1/3) > 0.00001:\n print(\"WARNING: integrate_trapz() failed the test.\")\n isGood = False\n\n # Test the simpson integration function\n simps = integrate_simpson(f, 0, 1, N=1000)[0]\n if abs(simps - 1 / 3) > 1e-12:\n print(\"WARNING: integrate_simpson() failed the test.\")\n isGood = False\n\n # Test the adaptive trapezoidal integration function\n trapz = integrate_trapz_adaptive(f, 0, 1, 1e-12)[0]\n if abs(trapz - 1 / 3) > 1e-12:\n print(\"WARNING: integrate_trapz_adaptive() failed the test.\")\n isGood = False\n\n # Test the adaptive simpson integration function\n simps = integrate_simpson_adaptive(f, 0, 1, 1e-12)[0]\n if abs(simps - 1 / 3) > 1e-12:\n print(\"WARNING: integrate_simpson_adaptive() failed the test.\")\n isGood = False\n\n # Test the 1D Monte Carlo integration function\n monte = integrate_monte_carlo(f, 0, 1, 1000000)\n if abs(monte - 1 / 3) > 0.01:\n print(\"WARNING: integrate_monte_carlo() failed the test.\")\n print(\"NOTE: There is a small probability of random failure with this method.\")\n print(\"Run the test a few more times.\")\n isGood = False\n\n # Test the multi-dimensional Monte Carlo integration function\n monte = integrate_monte_carlo_nd(g, 3, [[-1, 1], [-1, 1], [-1, 1]], N=100000)\n if abs(monte - (4/3)*np.pi) > 0.1:\n print(\"WARNING: integrate_monte_carlo_nd() failed the test.\")\n print(\"NOTE: There is a small probability of random failure with this method.\")\n print(\"Run the test a few more times.\")\n isGood = False\n\n if isGood is True:\n print(\"Module is good.\")","def integral(\n self,\n start: XValue[T],\n stop: XValue[T],\n transform: Callable[[XValueDiff[T]], float] = lambda x: cast(float, x),\n ) -> float:\n return self.integrals(start, stop, (stop - start), transform).values()[0]","def integrateCartesian(self,xl,xu,yl,yu,**kwargs):\n import scipy.integrate as itg\n\n oldcoordsys = self.incoordsys\n try:\n self.incoordsys = 'cartesian'\n f = lambda y,x:self((x,y))\n\n res = itg.dblquad(f,xl,xu,lambda y:yl,lambda y:yu,**kwargs)\n finally:\n self.incoordsys = oldcoordsys\n\n self.lastintegrate = res\n return res[0]","def complex_integral(self,func,a,b):\r\n \r\n import scipy\r\n from scipy import array\r\n \r\n def quad_routine(func, a, b, x_list, w_list):\r\n c_1 = (b-a)/2.0\r\n c_2 = (b+a)/2.0\r\n eval_points = map(lambda x: c_1*x+c_2, x_list)\r\n func_evals = list(map(func, eval_points)) # Python 3: make a list here\r\n return c_1 * sum(array(func_evals) * array(w_list))\r\n \r\n def quad_gauss_7(func, a, b):\r\n x_gauss = [-0.949107912342759, -0.741531185599394, -0.405845151377397, 0, 0.405845151377397, 0.741531185599394, 0.949107912342759]\r\n w_gauss = array([0.129484966168870, 0.279705391489277, 0.381830050505119, 0.417959183673469, 0.381830050505119, 0.279705391489277,0.129484966168870])\r\n return quad_routine(func,a,b,x_gauss, w_gauss)\r\n \r\n def quad_kronrod_15(func, a, b):\r\n x_kr = [-0.991455371120813,-0.949107912342759, -0.864864423359769, -0.741531185599394, -0.586087235467691,-0.405845151377397, -0.207784955007898, 0.0, 0.207784955007898,0.405845151377397, 0.586087235467691, 0.741531185599394, 0.864864423359769, 0.949107912342759, 0.991455371120813]\r\n w_kr = [0.022935322010529, 0.063092092629979, 0.104790010322250, 0.140653259715525, 0.169004726639267, 0.190350578064785, 0.204432940075298, 0.209482141084728, 0.204432940075298, 0.190350578064785, 0.169004726639267, 0.140653259715525, 0.104790010322250, 0.063092092629979, 0.022935322010529]\r\n return quad_routine(func,a,b,x_kr, w_kr)\r\n \r\n class Memorize: # Python 3: no need to inherit from object\r\n def __init__(self, func):\r\n self.func = func\r\n self.eval_points = {}\r\n def __call__(self, *args):\r\n if args not in self.eval_points:\r\n self.eval_points[args] = self.func(*args)\r\n return self.eval_points[args]\r\n \r\n def quad(func,a,b):\r\n ''' Output is the 15 point estimate; and the estimated error '''\r\n func = Memorize(func) # Memorize function to skip repeated function calls.\r\n g7 = quad_gauss_7(func,a,b)\r\n k15 = quad_kronrod_15(func,a,b)\r\n # I don't have much faith in this error estimate taken from wikipedia\r\n # without incorporating how it should scale with changing limits\r\n return [k15, (200*scipy.absolute(g7-k15))**1.5]\r\n \r\n return quad(func,a,b)","def complex_integral(self,func,a,b):\r\n \r\n import scipy\r\n from scipy import array\r\n \r\n def quad_routine(func, a, b, x_list, w_list):\r\n c_1 = (b-a)/2.0\r\n c_2 = (b+a)/2.0\r\n eval_points = map(lambda x: c_1*x+c_2, x_list)\r\n func_evals = list(map(func, eval_points)) # Python 3: make a list here\r\n return c_1 * sum(array(func_evals) * array(w_list))\r\n \r\n def quad_gauss_7(func, a, b):\r\n x_gauss = [-0.949107912342759, -0.741531185599394, -0.405845151377397, 0, 0.405845151377397, 0.741531185599394, 0.949107912342759]\r\n w_gauss = array([0.129484966168870, 0.279705391489277, 0.381830050505119, 0.417959183673469, 0.381830050505119, 0.279705391489277,0.129484966168870])\r\n return quad_routine(func,a,b,x_gauss, w_gauss)\r\n \r\n def quad_kronrod_15(func, a, b):\r\n x_kr = [-0.991455371120813,-0.949107912342759, -0.864864423359769, -0.741531185599394, -0.586087235467691,-0.405845151377397, -0.207784955007898, 0.0, 0.207784955007898,0.405845151377397, 0.586087235467691, 0.741531185599394, 0.864864423359769, 0.949107912342759, 0.991455371120813]\r\n w_kr = [0.022935322010529, 0.063092092629979, 0.104790010322250, 0.140653259715525, 0.169004726639267, 0.190350578064785, 0.204432940075298, 0.209482141084728, 0.204432940075298, 0.190350578064785, 0.169004726639267, 0.140653259715525, 0.104790010322250, 0.063092092629979, 0.022935322010529]\r\n return quad_routine(func,a,b,x_kr, w_kr)\r\n \r\n class Memorize: # Python 3: no need to inherit from object\r\n def __init__(self, func):\r\n self.func = func\r\n self.eval_points = {}\r\n def __call__(self, *args):\r\n if args not in self.eval_points:\r\n self.eval_points[args] = self.func(*args)\r\n return self.eval_points[args]\r\n \r\n def quad(func,a,b):\r\n ''' Output is the 15 point estimate; and the estimated error '''\r\n func = Memorize(func) # Memorize function to skip repeated function calls.\r\n g7 = quad_gauss_7(func,a,b)\r\n k15 = quad_kronrod_15(func,a,b)\r\n # I don't have much faith in this error estimate taken from wikipedia\r\n # without incorporating how it should scale with changing limits\r\n return [k15, (200*scipy.absolute(g7-k15))**1.5]\r\n \r\n return quad(func,a,b)","def vert_integrate(self, u, d='up', Q='self'):\n s = \"::: vertically integrating function :::\"\n print_text(s, cls=self)\n\n if type(Q) != FunctionSpace:\n Q = self.Q\n ff = self.ff\n phi = TestFunction(Q)\n v = TrialFunction(Q)\n bcs = []\n # integral is zero on bed (ff = 3,5) \n if d == 'up':\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_B_GND)) # grounded\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_B_FLT)) # shelves\n a = v.dx(2) * phi * dx\n # integral is zero on surface (ff = 2,6) \n elif d == 'down':\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_S_GND)) # grounded\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_S_FLT)) # shelves\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_U_GND)) # grounded\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_U_FLT)) # shelves\n a = -v.dx(2) * phi * dx\n L = u * phi * dx\n name = 'value integrated %s' % d \n v = Function(Q, name=name)\n solve(a == L, v, bcs, annotate=False)\n print_min_max(u, 'vertically integrated function', cls=self)\n return v","def quad_interp(x,y,xi) :\n f = interp1d(x,y,kind='quadratic')\n yi = f(xi)\n \n return yi","def integral ( self, xmin , xmax , ymin , ymax , nevents = True ) :\n if self.xminmax() :\n xmn , xmx = self.xminmax()\n xmin = max ( xmin , xmn )\n xmax = min ( xmax , xmx )\n\n if self.yminmax() : \n ymn , ymx = self.yminmax() \n ymin = max ( ymin , ymn )\n ymax = min ( ymax , ymx )\n\n value , todo = 0 , True \n \n ## 1) make a try to use analytical integral (could be fast)\n if self.tricks :\n try:\n if hasattr ( self.pdf , 'setPars' ) : self.pdf.setPars() \n fun = self.pdf.function()\n value , todo = fun.integral ( xmin , xmax , ymin , ymax ) , False \n except:\n pass\n\n ## use numerical integration \n from ostap.math.integral import integral2 as _integral2\n\n extended = self.pdf.canBeExtended() or isinstance ( self.pdf , ROOT.RooAddPdf )\n\n if todo and extended : value = _integral2 ( self , xmin , xmax , ymin , ymax )\n elif todo :\n \n ## use unormalized PDF here to speed up the integration \n ifun = lambda x, y : self ( x , y , error = False , normalized = False )\n value = _integral2 ( ifun , xmin , xmax , ymin , ymax )\n norm = self.pdf.getNorm ( self.vars )\n value /= norm\n\n if nevents and self.pdf.mustBeExtended () :\n evts = self.pdf.expectedEvents( self.vars )\n if evts <= 0 or iszero ( evts ) :\n self.warning ( \"integral: expectedEvents is %s\" % evts )\n value *= evts \n\n return value","def integrate(self, start, end):\n return self.foldl_time(start, end, 0,\n lambda v, time, lvl: v + time * lvl)","def complex_quadrature(func, a, b, **kwargs):\n\n def real_func(x):\n return scipy.real(func(x))\n\n def imag_func(x):\n return scipy.imag(func(x))\n\n real_integral = quad(real_func, a, b, **kwargs)\n imag_integral = quad(imag_func, a, b, **kwargs)\n return (real_integral[0] + 1j * imag_integral[0], real_integral[1:], imag_integral[1:])","def _test_integrate(self, integrator: BaseTsdfIntegrator) -> None:\n integrator.integrate(points=self.points, extrinsic=self.pose)","def integrate(x, power):\n if power == -1:\n return log(abs(x))\n else:\n return float(pow(x, power+1)) / (power+1.)","def test_get_quad_square_all_float(self):\n result = get_quadrilateral_type(2.4, 2.4, 2.4, 2.4, 90, 90, 90, 90)\n self.assertEqual(result, 'square')","def sp_integrate_1D_ ( pdf , xmin , xmax , *args , **kwargs ) :\n if hasattr ( pdf , 'setPars' ) : pdf.setPars() \n func = pdf.function()\n return func.sp_integrate_1D ( xmin , xmax , *args , **kwargs )","def scipy_integrate(func, X0, args, N=0):\n V0 = 0.7 # we fix the volatge initial condition\n t_span = [0.0, args.h * N]\n t_sim = np.linspace(0.0, args.h * N, N+1)\n sol = solve_ivp(func, t_span, [X0[0], X0[1], X0[2], X0[3], V0], method=args.method, t_eval=t_sim.reshape(-1,))\n y_test = sol.y\n t_sim = t_sim.reshape(-1, 1)\n return t_sim[1:,:], y_test[:, 1:]","def mc_integrate1d(f, a, b, N=10000):\n #use the approximation formula with a translate and scale of unit interval\n points = (b-a)*np.random.rand(N)+a\n y = f(points)\n return (b-a)*sum(y)/N","def integrate(self, *args):\n wbin = Spectrum._groom_integration_ranges(*args)\n try:\n wbin.to(self.w.unit)\n except AttributeError as xxx_todo_changeme:\n _u.UnitConversionError = xxx_todo_changeme\n raise ValueError('Input must be astropy quantity with units '\n 'convertable to that of spectrum.')\n if _np.any(wbin < self.wbins[0]) or _np.any(wbin > self.wbins[-1]):\n raise ValueError('Integration range is beyond spectrum range.')\n dw = _np.diff(wbin, 1).squeeze()\n newspec = self.rebin(wbin.ravel())\n flux_dens = newspec.y[::2]\n fluxes = flux_dens*dw\n flux = _np.sum(fluxes)\n if self.e is None:\n error = None\n else:\n err_dens = newspec.e[::2]\n errs = err_dens*dw\n error = utils.quadsum(errs)\n return flux, error","def test_quad_flush_ind(self):","def integrate(self, *w):\n # deal with subspectrums if necessary\n if not w:\n spectrum = self.spectrum\n interp = self.interp\n else:\n assert len(w) >= 2 and w[0] < w[\n 1], 'Error: Too few wavelengths or start wavelength is not shorter than the longest wavelength.'\n spectrum = self.sub_spectrum(w[0], w[1])\n # TODO: Decide if to use quad and interp1d obj for integration or not. trapz is faster & close in result\n # interp = interpolate.interp1d(spectrum[:, 0], spectrum[:, 1])\n # get the total number of discrete wavelengths as a bin limit\n # bin_limit = len(spectrum[:, 0])\n # integrate the power\n # power_f = integrate.quad(interp, spectrum[0, 0], spectrum[-1, 0], full_output=1, limit=bin_limit)\n power_f = integrate.trapz(spectrum[:, 1], spectrum[:, 0])\n return power_f # Units Watts/meters^2","def _integrate(self, integrator, dt, tf, post_step_callback):\n t = 0.0\n while t < tf:\n integrator.step(t, dt)\n post_step_callback(t+dt)\n t += dt","def integrate(self, X_0, t_vec, rel_tol, abs_tol, params):\n return None","def integrate_trapz_adaptive(f, lower, upper, accuracy=1e-8, detailed=False):\n a = lower # Lower limit of integration\n b = upper # Upper limit of integration\n Tol = accuracy # Error tolerance\n error = 1 # Error needs to be initialized as something\n N = 1 # Start with 1 trapezoid\n\n # I0 is the approximation with a single trapezoid\n I0 = (f(a) + f(b))*(b-a)*0.5\n\n # Do you want detailed results?\n if detailed is True:\n print(\"N = \", N, \", I = \", I0, sep=\"\")\n\n while error > Tol: # Repeat until the error is less than the error tolerance\n\n N *= 2 # Double the slices each iteration\n w = (b - a)/N # Width of each trapezoid\n\n I = 0.5*I0\n for i in range(1, N, 2):\n I += f(a + i*w)*w\n\n error = abs(I - I0)/3\n\n I0 = I\n\n # Do you want detailed results?\n if detailed is True:\n print(\"N = \", N, \", I = \", I, \", Error = \", error, sep=\"\")\n\n return I, N, error","def integrate(self, units=True, e_weight=0):\n int = logsimps(lambda e: e**e_weight*self(e, units=False), self.emin, self.emax, sed_config.PER_DECADE)\n return int*(u.erg**(e_weight+1)*self.units() if units else 1)","def _oned_intFunc(x,twodfunc,gfun,hfun,tol,args):\n thisargs= copy.deepcopy(args)\n thisargs.insert(0,x)\n return integrate.romberg(twodfunc,gfun(x),hfun(x),args=thisargs,tol=tol)","def quad(f, a, b):\n\tS, D = (b+a)/2.0, (b-a)/2.0\n\tdef rescaled_f(x):\n\t\treturn f(x*D + S)*D\n\treturn sum(w * rescaled_f(p) for w, p in zip(quad_weights, quad_points))","def integrate_using_univariate_gauss_legendre_quadrature_unbounded(\n integrand, lb, ub, nquad_samples, atol=1e-8, rtol=1e-8,\n interval_size=2, max_steps=1000, verbose=0, adaptive=True,\n soft_error=False, tabulated_quad_rules=None):\n if interval_size <= 0:\n raise ValueError(\"Interval size must be positive\")\n\n if np.isfinite(lb) and np.isfinite(ub):\n partial_lb, partial_ub = lb, ub\n elif np.isfinite(lb) and not np.isfinite(ub):\n partial_lb, partial_ub = lb, lb+interval_size\n elif not np.isfinite(lb) and np.isfinite(ub):\n partial_lb, partial_ub = ub-interval_size, ub\n else:\n partial_lb, partial_ub = -interval_size/2, interval_size/2\n\n result = __integrate_using_univariate_gauss_legendre_quadrature_bounded(\n integrand, partial_lb, partial_ub, nquad_samples, rtol,\n atol, verbose-1, adaptive, tabulated_quad_rules)\n\n step = 0\n partial_result = np.inf\n plb, pub = partial_lb-interval_size, partial_lb\n while (np.any(np.absolute(partial_result) >= rtol*np.absolute(result)+atol)\n and (plb >= lb) and step < max_steps):\n partial_result = \\\n __integrate_using_univariate_gauss_legendre_quadrature_bounded(\n integrand, plb, pub, nquad_samples, rtol, atol,\n verbose-1, adaptive, tabulated_quad_rules)\n result += partial_result\n pub = plb\n plb -= interval_size\n step += 1\n if verbose > 1:\n print('Left', step, result, partial_result, plb, pub,\n interval_size)\n if verbose > 0:\n if step >= max_steps:\n msg = \"Early termination when computing left integral\"\n msg += f\"max_steps {max_steps} reached\"\n if soft_error is True:\n warn(msg, UserWarning)\n else:\n raise RuntimeError(msg)\n if np.all(np.abs(partial_result) < rtol*np.absolute(result)+atol):\n msg = f'Tolerance {atol} {rtol} for left integral reached in '\n msg += f'{step} iterations'\n print(msg)\n\n step = 0\n partial_result = np.inf\n plb, pub = partial_ub, partial_ub+interval_size\n while (np.any(np.absolute(partial_result) >= rtol*np.absolute(result)+atol)\n and (pub <= ub) and step < max_steps):\n partial_result = \\\n __integrate_using_univariate_gauss_legendre_quadrature_bounded(\n integrand, plb, pub, nquad_samples, rtol, atol,\n verbose-1, adaptive, tabulated_quad_rules)\n result += partial_result\n plb = pub\n pub += interval_size\n step += 1\n if verbose > 1:\n print('Right', step, result, partial_result, plb, pub,\n interval_size)\n if verbose > 0:\n if step >= max_steps:\n msg = \"Early termination when computing right integral. \"\n msg += f\"max_steps {max_steps} reached\"\n if soft_error is True:\n warn(msg, UserWarning)\n else:\n raise RuntimeError(msg)\n if np.all(np.abs(partial_result) < rtol*np.absolute(result)+atol):\n msg = f'Tolerance {atol} {rtol} for right integral reached in '\n msg += f'{step} iterations'\n print(msg)\n # print(partial_result, plb, pub)\n\n return result","def test_get_quad_angover_all_float(self):\n result = get_quadrilateral_type(2, 2, 2, 2, 180.1, .1, 180.1, .1)\n self.assertEqual(result, 'invalid')","def integrand(x, n):\n return jn(n, x)","def integrateCircular(self,outr,inr=0,theta=(0,2*pi),**kwargs):\n import scipy.integrate as itg\n oldcoordsys = self.incoordsys\n try:\n self.incoordsys = 'polar'\n f = lambda th,r:r*self((r,th))\n\n res = itg.dblquad(f,inr,outr,lambda y:theta[0],lambda y:theta[1],**kwargs)\n finally:\n self.incoordsys = oldcoordsys\n\n self.lastintegrate = res\n return res[0]","def intsolve(func, value, start=None, stop=None, maxit=1000):\n from scipy import inf\n from scipy.integrate import quad\n from warnings import warn\n if start is None:\n start = -inf\n if stop is None:\n stop = inf\n lower_bound = start\n upper_bound = stop\n it = 0\n while it < maxit:\n it += 1\n if upper_bound == inf:\n if lower_bound == -inf:\n test_bound = 0\n elif lower_bound < 1.0:\n test_bound = 1.0\n else:\n test_bound = lower_bound * 2\n else:\n if lower_bound == -inf:\n if upper_bound > -1.0:\n test_bound = -1.0\n else:\n test_bound = upper_bound * 2\n else:\n test_bound = (lower_bound + upper_bound) / 2.0\n (test_value, err) = quad(func, start, test_bound)\n if abs(value - test_value) <= err:\n break\n elif value < test_value:\n upper_bound = test_bound\n else:\n lower_bound = test_bound\n\n if abs(value - test_value) > err:\n warn('Difference between desired value and actual is ' +\n str(abs(value - test_value)) +\n ', greater than integral error ' +\n str(err), UserWarning, stacklevel=2)\n return test_bound","def integrate(self, x0, t0, tend, N):\n raise NotImplementedError","def field_line_integrate(\n r0, z0, phis, field, params={}, rtol=1e-8, atol=1e-8, maxstep=1000\n):\n r0, z0, phis = map(jnp.asarray, (r0, z0, phis))\n assert r0.shape == z0.shape, \"r0 and z0 must have the same shape\"\n rshape = r0.shape\n r0 = r0.flatten()\n z0 = z0.flatten()\n x0 = jnp.array([r0, phis[0] * jnp.ones_like(r0), z0]).T\n\n @jit\n def odefun(rpz, s):\n rpz = rpz.reshape((3, -1)).T\n r = rpz[:, 0]\n br, bp, bz = field.compute_magnetic_field(rpz, params, basis=\"rpz\").T\n return jnp.array(\n [r * br / bp * jnp.sign(bp), jnp.sign(bp), r * bz / bp * jnp.sign(bp)]\n ).squeeze()\n\n intfun = lambda x: odeint(odefun, x, phis, rtol=rtol, atol=atol, mxstep=maxstep)\n x = jnp.vectorize(intfun, signature=\"(k)->(n,k)\")(x0)\n r = x[:, :, 0].T.reshape((len(phis), *rshape))\n z = x[:, :, 2].T.reshape((len(phis), *rshape))\n return r, z","def integrate(self, q: Variable, p: Variable, n_steps: int, eps: float, forward, method=\"leapfrog\"):\n _isin(method, Hamiltonian.integrate_methods)\n # Again, casting hyperparameters to tf.Tensor is crucial here. Otherwise, leapfrog will retrace at each\n # change of arguments.\n # Also necessary to cast for avoiding compatibility issues; even if float64 by default with the tf.constant(...)\n # constructor\n eps = tf.constant(eps, dtype='float32')\n\n params = dict(q=q, p=p,\n n_steps=tf.constant(n_steps),\n eps=eps,\n forward=tf.constant(forward),\n grad_func_q=self.grad_potential,\n grad_func_p=self.grad_kinetic)\n if method == \"leapfrog\":\n return _leapfrog_integration(**params)\n elif method == \"euler\":\n return _euler_integration(**params)","def test_wrapped_call(self, config: HandlerConfig) -> None:\n # Arrange.\n # Create a mock Unit to convert.\n mock_unit = mock.Mock(spec=MyUnit)\n\n # Act.\n # Try converting it.\n converted = config.handler(mock_unit)\n\n # Assert.\n # It should have made sure all the units were correct.\n config.mock_from_unit.assert_called_once_with(mock_unit)\n\n input_unit = config.mock_from_unit.return_value\n config.mock_function.assert_called_once_with(input_unit)\n\n raw_output = config.mock_function.return_value\n config.mock_to_unit.assert_called_once_with(raw_output)\n\n assert converted == config.mock_to_unit.return_value","def get_integral_over_times(start, stop, rate):\n return integrate.quad(get_townsend_pi, start, stop, args=(rate))","def _G(xi, B):\n try:\n import scipy.integrate\n except:\n raise ImportError(' [PHIDL] To run the microstrip functions you '\n 'need scipy, please install it with '\n '`pip install scipy`')\n return B/sinh(B)*scipy.integrate.quad(_G_integrand, 0, xi, args = (B))[0]","def integrate_axis_py(obj, **kwargs):\n\n # import the helper functions\n import hlr_utils\n\n # set up for working through data\n o_descr = hlr_utils.get_descr(obj)\n\n if o_descr == \"number\" or o_descr == \"list\":\n raise RuntimeError(\"Must provide a SOM of a SO to the function.\")\n # Go on\n else:\n pass\n\n # Check for starting bin\n try:\n start = kwargs[\"start\"]\n except KeyError:\n start = 0\n\n # Check for ending bin\n try: \n end = kwargs[\"end\"]\n if end != -1:\n end += 1\n else:\n pass\n except KeyError:\n end = -1\n\n # Check for axis keyword argument\n try:\n axis = kwargs[\"axis\"]\n except KeyError:\n axis = \"y\"\n \n # Check for axis_pos keyword argument\n try:\n axis_pos = kwargs[\"axis_pos\"]\n except KeyError:\n axis_pos = 0\n\n # Check for avg keyword argument\n try:\n avg = kwargs[\"avg\"]\n except KeyError:\n avg = False\n\n # Check for width keyword argument\n try:\n width = kwargs[\"width\"]\n except KeyError:\n width = False \n\n # Check for width_pos keyword argument\n try:\n width_pos = kwargs[\"width_pos\"]\n except KeyError:\n width_pos = 0 \n \n integration = float(0)\n integration_error2 = float(0)\n\n import itertools\n if width:\n import utils\n\n bad_values = [\"nan\", \"inf\", \"-inf\"]\n\n for i in xrange(hlr_utils.get_length(obj)): \n counter = 0 \n\n value = hlr_utils.get_value(obj, i, o_descr, axis, axis_pos)\n error = hlr_utils.get_err2(obj, i, o_descr, axis, axis_pos)\n\n if end == -1:\n value = value[start:]\n error = error[start:]\n else:\n value = value[start:end]\n error = error[start:end]\n \n if not width:\n for val, err2 in itertools.izip(value, error):\n if str(val) in bad_values or str(err2) in bad_values:\n continue\n else:\n integration += val\n integration_error2 += err2\n counter += 1\n else:\n if axis == \"y\":\n x_axis = hlr_utils.get_value(obj, i, o_descr, \"x\", width_pos)\n x_err2 = hlr_utils.get_err2(obj, i, o_descr, \"x\", width_pos)\n elif axis == \"x\":\n raise RuntimeError(\"Cannot use width flag with x-axis \"\\\n +\"integration\")\n\n bin_widths = utils.calc_bin_widths(x_axis, x_err2)\n\n for val, err2, delta in itertools.izip(value, error,\n bin_widths[0]):\n if str(val) in bad_values or str(err2) in bad_values:\n continue\n else:\n integration += (delta * val)\n integration_error2 += (delta * delta * err2)\n counter += 1\n \n if avg:\n return (integration / float(counter),\n integration_error2 / float(counter))\n else:\n return (integration, integration_error2)","def piecewise_integrate(x, y, a, b):\n assert x[0] == a\n assert x[-1] <= b\n output = 0.\n num_x = len(x)\n if x[-1] == b:\n for idx in range(num_x - 1):\n output += y[idx] * (x[idx+1] - x[idx])\n else:\n for idx in range(num_x):\n if idx < num_x - 1:\n output += y[idx] * (x[idx+1] - x[idx])\n else:\n output += y[idx] * (b - x[idx])\n return output","def integrate(self,u,x,Dt,t,bc):\n time=t[0]\n i=1\n result=interfaces.State()\n result.x=scipy.zeros((len(x),len(t)),scipy.float64)\n result.x[:,0]=x\n s=list(scipy.shape(u))\n s.append(len(t))\n result.u=scipy.zeros(s,scipy.float64)\n result.u[:,:,0]=u\n result.time=t\n \n while not scipy.allclose(time,t[-1],rtol=1e-8,atol=1e-10):\n k1=self.estimator.estimate(u,time,x,bc)\n\t k2=self.estimator.estimate(u+0.5*Dt*k1,time+0.5*Dt,x,bc)\n\t k3=self.estimator.estimate(u+0.5*Dt*k2,time+0.5*Dt,x,bc)\n\t k4=self.estimator.estimate(u+Dt*k3,time+Dt,x,bc)\n\t u=u+Dt*(1./6.*k1+1./3.*k2+1./3.*k3+1./6.*k4)\n time=time+Dt\n\t if scipy.allclose(time,t[i],rtol=1e-8,atol=1e-10):\n \tresult.x[:,i]=x\n result.u[:,:,i]=u\n \ti+=1\n return result","def integrate(f, a, b, args=(), minintervals=1, limit=200, tol=1e-10):\n fv = np.vectorize(f)\n\n intervals = []\n\n limits = np.linspace(a, b, minintervals+1)\n for left, right in zip(limits[:-1], limits[1:]):\n I, err = integrate_gausskronrod(fv, left, right, args)\n bisect.insort(intervals, (err, left, right, I))\n\n while True:\n Itotal = sum([x[3] for x in intervals])\n err2 = sum([x[0]**2 for x in intervals])\n err = sqrt(err2)\n\n if abs(err/Itotal) < tol:\n return Itotal, err\n\n # no convergence\n if len(intervals) >= limit:\n return False # better to raise an exception\n\n err, left, right, I = intervals.pop()\n\n # split integral\n mid = left+(right-left)/2\n\n # calculate integrals and errors, replace one item in the list and\n # append the other item to the end of the list\n I, err = integrate_gausskronrod(fv, left, mid, args)\n bisect.insort(intervals, (err, left, mid, I))\n I, err = integrate_gausskronrod(fv, mid, right, args)\n bisect.insort(intervals, (err, mid, right, I))","def trapz(x, modify_endpoints=False):\n integral = (\n x[1:] + x[:-1]\n ) / 2\n if modify_endpoints:\n integral[0] = integral[0] + x[0] * 0.5\n integral[-1] = integral[-1] + x[-1] * 0.5\n\n return integral","def integrate_simpson_adaptive(f, lower, upper, accuracy=1e-15, detailed=False):\n a = lower # Lower limit of integration\n b = upper # Upper limit of integration\n Tol = accuracy # Error tolerance\n error = 1.0 # Error needs to be initialized as something\n N = 1 # Start with 1 slice\n\n # I0 is the approximation with a single slice\n I0 = ((b-a)/6) * (f(a) + 4 * f((b - a)/2) + f(b)) # Area of first and last slice\n\n # Do you want detailed results?\n if detailed is True:\n print(\"N = \", N, \", I = \", I0, sep=\"\")\n\n while error > Tol:\n\n N *= 2\n w = (b - a) / N # Width of each slice\n\n I = 0.5 * I0\n for i in range(1, N, 2):\n I += -f(a + w * i) * w / 3\n for i in range(0, N):\n I += (2 / 3) * f(a + w * (i + 1 / 2)) * w\n\n error = abs(I - I0)/15\n\n I0 = I\n\n # Do you want detailed results?\n if detailed is True:\n print(\"N = \", N, \", I = \", I, \", Error = \", error, sep=\"\")\n\n return I, N, error","def integrate(equ):\n if \"x\" in equ:\n return polynomial_equation(equ)\n else:\n return constant_equation(equ)","def compute_integrals(self):\n\n integrals = self.dat.data.reshape(-1, self.nvdofs).T.dot(self.cell_volumes)\n integrals_lift = Function(self._function_space)\n integrals_lift.dat.data[:] = np.tile(integrals,(self.nhdofs,))\n\n return integrals_lift","def integrate_dphi_phi(self, i, j):\n def func(x):\n return self.shape_function_deriv(i, x) * self.shape_function(j, x)\n i, err = quadrature(func, -1, 1)\n return i","def integrate_highest_dimension(self, field, dx = 1):\n axis_num = field.ndim - 1\n integrated_field = np.trapz(field, dx = dx, axis = axis_num)\n \n return integrated_field","def do_math_double(cls, quad, type):\n\t\tdata1 = cls.get_address_value(quad.left_operand)\n\t\tdata2 = cls.get_address_value(quad.right_operand)\n\t\tval = 0.0\n\t\tif(type == \"pow\"):\n\t\t\tval = math.pow(data1, data2)\n\n\t\tcls.set_address_value(quad.result, val)","def integrate(self, t):\n t0 = self.t0\n if t-t0 <= self.max_step_size:\n self.y0 = self.y0 + (t-t0)*self.f(t0,self.y0) \n \n else :\n n = (t-t0) / self.max_step_size\n dt = (t-t0)/int(n+1)\n \n while t0 < t :\n self.y0 = self.y0 + dt*self.f(t0,self.y0)\n t0 += dt\n \n return self.y0","def Integrator_1(t_vec, x0):\n\tx = np.zeros((len(t_vec), x0.shape[0], N_max)) # set up the array of x values\n\t\n\tfor N in range(1, N_max+1):\n\t\tx[0, :, N-1] = x0.reshape(2)\n\t\tfor i in range(1,len(t_vec)):\n\t\t\tx[i,:,N-1] = (f_step(0, t_vec[i], N) @ x0).reshape(2)\n\t\t\tif (i*100) % (len(t_vec)-1) == 0:\n\t\t\t\tprint(\"\\r\" + \"integrated {:.0%}\".format(i/(len(t_vec)-1)), end='')\n\t\t\n\t\tprint(' done order ', N)\n\t\t\n\treturn x","def integrate_simpson(f, lower, upper, N=1000):\n a = lower # Lower integration limit\n b = upper # Upper integration limit\n w = (b - a) / N # Width of each trapezoid\n\n if N % 2 != 0:\n N += 1\n print(\"Number of slices was odd so 1 was added to N.\")\n\n I = (1 / 3) * f(a) * w + (1 / 3) * f(b) * w # Area of first and last trapezoids\n\n for i in range(1, N, 2): # Odd terms\n I += f(a + i * w) * w * (4 / 3)\n\n for i in range(2, N, 2): # Even terms\n I += f(a + i * w) * w * (2 / 3)\n\n return I, N","def integrate(l_tr_val, ind_bs):\n\n phi1max = 360. # max phi1 angle (deg) for integration domain\n phimax = 90. # max phi angle (deg) for integration domain\n phi2max = 60. # max phi2 angle (deg) for integration domain\n inc = 3. # degree increment for euler angle generation\n l_tr_cal = 8 # truncation level in the l index for the GSH\n\n indxvec = gsh.gsh_basis_info()\n N_L_cal = np.sum(indxvec[:, 0] <= l_tr_cal)\n N_L_val = np.sum(indxvec[:, 0] <= l_tr_val)\n N_L = np.max([N_L_cal, N_L_val])\n\n euler, n_tot = euler_grid_center(inc, phi1max, phimax, phi2max)\n\n \"\"\"Generate X\"\"\"\n X = gsh.gsh_eval(euler, np.arange(N_L))/(2*indxvec[:N_L, 0]+1)\n\n \"\"\"Generate Y (test function)\"\"\"\n\n np.random.seed(141)\n\n normvec = (2*indxvec[:N_L, 0]+1)**3\n bval = (np.random.normal(scale=1.0, size=N_L_cal)**3)/normvec\n\n Y = np.zeros(n_tot, dtype='complex128')\n for ii in xrange(N_L_cal):\n Y += bval[ii]*X[:, ii]\n\n Y = Y.real\n\n \"\"\"Perform the integration for the GSH coefficients\"\"\"\n coef = np.zeros(N_L_val, dtype='complex128')\n\n # domain_eul_sz is the integration domain in radians\n domain_sz = phi1max*phimax*phi2max*(np.pi/180.)**3\n # full_eul_sz is the size of euler space in radians\n full_sz = (2*np.pi)*(np.pi)*(2*np.pi)\n eul_frac = domain_sz/full_sz\n fzsz = 1./(eul_frac*8.*np.pi**2)\n bsz = domain_sz/n_tot\n\n for ii in xrange(N_L_val):\n\n l = indxvec[ii, 0]\n tmp = (2*l+1)*np.sum(Y*X[:, ii].conj()*np.sin(euler[:, 1]))*bsz*fzsz\n coef[ii] = tmp\n\n \"\"\"check accuracy of GSH representation\"\"\"\n\n Y_gsh = np.zeros(n_tot, dtype='complex128')\n for ii in xrange(N_L_val):\n Y_gsh += coef[ii]*X[:, ii]\n\n Y_gsh = Y_gsh.real\n\n error_gsh = np.abs(Y_gsh - Y)\n\n print \"\\nGSH basis representation errors\"\n print \"mean error: %s\" % np.mean(error_gsh)\n print \"std of error: %s\" % np.std(error_gsh)\n print \"max error: %s\" % np.max(error_gsh)\n\n \"\"\"Perform the integration for the indicator basis coefficients\"\"\"\n n_p1_ind = phi1max/ind_bs\n n_P_ind = phimax/ind_bs\n n_p2_ind = phi2max/ind_bs\n\n ysum = np.zeros((n_p1_ind, n_P_ind, n_p2_ind))\n ycount = np.zeros((n_p1_ind, n_P_ind, n_p2_ind))\n\n N_ind = ysum.size\n\n ind_bs_r = ind_bs*np.pi/180.\n\n for ii in xrange(np.int64(n_tot)):\n eset = np.int64(np.floor(euler[ii, :]/ind_bs_r))\n ysum[eset[0], eset[1], eset[2]] += Y[ii]\n ycount[eset[0], eset[1], eset[2]] += 1\n\n y_integrate = ysum/ycount\n del ysum, ycount\n\n Y_ind = np.zeros(n_tot, dtype='float64')\n\n for ii in xrange(np.int64(n_tot)):\n eset = np.int64(np.floor(euler[ii, :]/ind_bs_r))\n Y_ind[ii] = y_integrate[eset[0], eset[1], eset[2]]\n del y_integrate\n\n \"\"\"check accuracy of indicator function representation\"\"\"\n\n error_ind = np.abs(Y_ind - Y)\n\n print \"\\nindicator basis representation errors\"\n print \"mean error: %s\" % np.mean(error_ind)\n print \"std of error: %s\" % np.std(error_ind)\n print \"max error: %s\" % np.max(error_ind)\n\n \"\"\" Plot the regression results \"\"\"\n\n phi2_u = np.unique(euler[:, 2])\n\n ang_sel = euler[:, 2] == phi2_u[np.int64(len(phi2_u)/2.)]\n\n plt.figure(figsize=[8, 8])\n\n vmin = np.min([Y, Y_gsh, Y_ind])\n vmax = np.max([Y, Y_gsh, Y_ind])\n\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\n Y[ang_sel], inc)\n\n plt.subplot(311)\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\n vmin=vmin, vmax=vmax,\n extent=[0, 2*np.pi, 0, np.pi/2.])\n plt.colorbar(ax)\n plt.title(\"Reference ODF slice\")\n plt.xlabel(\"$\\phi1$\")\n plt.ylabel(\"$\\Phi$\")\n\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\n Y_gsh[ang_sel], inc)\n\n plt.subplot(312)\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\n vmin=vmin, vmax=vmax,\n extent=[0, 2*np.pi, 0, np.pi/2.])\n plt.colorbar(ax)\n plt.title(\"ODF slice with %s GSH bases\" % N_L_val)\n plt.xlabel(\"$\\phi1$\")\n plt.ylabel(\"$\\Phi$\")\n\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\n Y_ind[ang_sel], inc)\n\n plt.subplot(313)\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\n vmin=vmin, vmax=vmax,\n extent=[0, 2*np.pi, 0, np.pi/2.])\n plt.colorbar(ax)\n plt.title(\"ODF slice with %s indicator bases\" % N_ind)\n plt.xlabel(\"$\\phi1$\")\n plt.ylabel(\"$\\Phi$\")\n\n plt.show()","def test_get_quad_under_all_float(self):\n result = get_quadrilateral_type(2, 2, 2, 2, 179.9, .1, 179.9, .1)\n self.assertEqual(result, 'rhombus')","def integral( self ):\n integral = 0.0\n for i in range( 1, self.GetN() ):\n previousPoint = ( ROOT.Double(), ROOT.Double() )\n thisPoint = ( ROOT.Double(), ROOT.Double() )\n self.GetPoint( i-1, previousPoint[0], previousPoint[1] )\n self.GetPoint( i, thisPoint[0], thisPoint[1] )\n \n integral += (thisPoint[0]-previousPoint[0]) * (thisPoint[1]+previousPoint[1])/2.0\n return integral","def integrate_range(self, lower, upper):\n if upper>self.upper:\n upper=self.upper\n if lower<self.lower:\n lower = self.lower\n\n i_l = int(np.floor((lower-self.lower)/self._dx))\n i_u = int(np.floor((upper-self.lower)/self._dx))\n #print \"i_l \",i_l,\" i_u \",i_u\n total = 0.0\n for i in range(i_l,i_u):\n total+= self.y[i]*self._dx\n return total","def _integrate_malmquist(self, malm_pars, q0, q1):\n return np.sum([p/(i+1.0)*(q1**(i+1.0) - q0**(i+1.0)) for i, p in enumerate(malm_pars)])","def add_quad(a, b):\n s = np.sqrt(np.square(a) + np.square(b))\n return s","def fpga_moving_integrator(samples, integration, math_round=False, extra_bits=0):\n sreg = deque(np.zeros(integration))\n result = []\n acc = 0\n for sample in samples:\n acc += sample - sreg.pop()\n sreg.appendleft(sample)\n if math_round:\n value = int(round(acc/integration*2**extra_bits))/2**extra_bits\n else:\n value = int(np.floor(acc/integration*2**extra_bits))/2**extra_bits\n result.append(value)\n return result","def test_hermite_integral(dimensions, specification, size, naive_specification):\n integral = lambda n, w: w.T @ (n ** 2).prod(axis=1)\n nodes, weights = Integration(specification, size, seed=0)._build(dimensions)\n simulated = integral(nodes, weights)\n np.testing.assert_allclose(simulated, 1, rtol=0, atol=0.01)\n if naive_specification:\n naive = integral(*Integration(naive_specification, 10 * weights.size, seed=0)._build(dimensions))\n np.testing.assert_array_less(np.linalg.norm(simulated - 1), np.linalg.norm(naive - 1))","def test_float64(self):\r\n start, stop, step = dscalars('start', 'stop', 'step')\r\n out = arange(start, stop, step)\r\n f = function([start, stop, step], out)\r\n\r\n assert out.dtype == start.type.dtype\r\n arg_vals = [(0, 5, 1), (2, 11, 4), (-5, 1.1, 1.2), (1.3, 2,\r\n -2.1), (10, 2, 2)]\r\n for arg_v in arg_vals:\r\n start_v, stop_v, step_v = arg_v\r\n start_v_, stop_v_, step_v_ = numpy.asarray(arg_v,\r\n dtype=start.type.dtype)\r\n f_val = f(start_v_, stop_v_, step_v_)\r\n if config.cast_policy == 'custom':\r\n expected_val = numpy.arange(start_v, stop_v, step_v,\r\n dtype=start.type.dtype)\r\n elif config.cast_policy in ('numpy', 'numpy+floatX'):\r\n expected_val = numpy.arange(start_v_, stop_v_, step_v_)\r\n else:\r\n raise NotImplementedError(config.cast_policy)\r\n assert numpy.all(f_val == expected_val)","def _integrand(u1,\n dens_lum, sigma_lum, q_lum,\n dens_pot, sigma_pot, q_pot,\n x1, y1, inc, beta, tensor):\n dens_lum = dens_lum[:, None, None]\n sigma_lum = sigma_lum[:, None, None]\n q_lum = q_lum[:, None, None]\n beta = beta[:, None, None]\n\n dens_pot = dens_pot[None, :, None]\n sigma_pot = sigma_pot[None, :, None]\n q_pot = q_pot[None, :, None]\n\n u = u1[None, None, :]\n\n kani = 1./(1 - beta) # Anisotropy ratio b = (sig_R/sig_z)**2\n ci = np.cos(inc)\n si = np.sin(inc)\n si2 = si**2\n ci2 = ci**2\n x2 = x1**2\n y2 = y1**2\n u2 = u**2\n\n s2_lum = sigma_lum**2\n q2_lum = q_lum**2\n e2_lum = 1 - q2_lum\n s2q2_lum = s2_lum*q2_lum\n\n s2_pot = sigma_pot**2\n e2_pot = 1 - q_pot**2\n\n # Double summation over (j, k) of eq.(28) for all values of integration variable u.\n # The triple loop in (j, k, u) is replaced by broadcast Numpy array operations.\n # The j-index refers to the Gaussians describing the total mass,\n # from which the potential is derived, while the k-index is used\n # for the MGE components describing the galaxy stellar luminosity.\n\n e2u2_pot = e2_pot*u2\n a = 0.5*(u2/s2_pot + 1/s2_lum) # equation (29) in C08\n b = 0.5*(e2u2_pot*u2/(s2_pot*(1 - e2u2_pot)) + e2_lum/s2q2_lum) # equation (30) in C08\n c = e2_pot - s2q2_lum/s2_pot # equation (22) in C08\n d = 1 - kani*q2_lum - ((1 - kani)*c + e2_pot*kani)*u2 # equation (23) in C08\n e = a + b*ci2\n if tensor == 'xx':\n f = kani*s2q2_lum + d*((y1*ci*(a+b)/e)**2 + si2/(2*e)) # equation (4) in C12\n elif tensor == 'yy':\n f = s2q2_lum*(si2 + kani*ci2) + d*x2*ci2 # equation (5) in C12\n elif tensor == 'zz':\n f = s2q2_lum*(ci2 + kani*si2) + d*x2*si2 # z' LOS equation (28) in C08\n elif tensor == 'xy':\n f = -d*np.abs(x1*y1)*ci2*(a+b)/e # equation (6) in C12\n elif tensor == 'xz':\n f = d*np.abs(x1*y1)*si*ci*(a+b)/e # equation (7) in C12\n elif tensor == 'yz':\n f = si*ci*(s2q2_lum*(1 - kani) - d*x2) # equation (8) in C12\n else:\n raise RuntimeError('Incorrect TENSOR string')\n\n # arr has the dimensions (q_lum.size, q_pot.size, u.size)\n\n arr = q_pot*dens_pot*dens_lum*u2*f*np.exp(-a*(x2 + y2*(a + b)/e)) \\\n / ((1. - c*u2)*np.sqrt((1. - e2u2_pot)*e))\n\n G = 0.00430237 # (km/s)^2 pc/Msun [6.674e-11 SI units (CODATA-10)]\n\n return 4*np.pi**1.5*G*np.sum(arr, axis=(0, 1))","def integrate_spectrum(func, xmin, xmax, ndecade=100, intervals=False):\n is_quantity = False\n if isinstance(xmin, Quantity):\n unit = xmin.unit\n xmin = xmin.value\n xmax = xmax.value\n is_quantity = True\n\n if np.isscalar(xmin):\n logmin = np.log10(xmin)\n logmax = np.log10(xmax)\n n = (logmax - logmin) * ndecade\n x = np.logspace(logmin, logmax, n)\n else:\n x = np.append(xmin, xmax[-1])\n\n if is_quantity:\n x = x * unit\n\n y = func(x)\n\n val = _trapz_loglog(y, x, intervals=intervals)\n\n return val","def integrate_trapz(f, lower, upper, N=1000):\n a = lower # Lower integration limit\n b = upper # Upper integration limit\n w = (b - a) / N # Width of each trapezoid\n\n # Area of first and last trapezoids\n I = 0.5 * f(a) * w + 0.5 * f(b) * w\n\n # Area of rest of trapezoids\n for i in range(1, N):\n I += f(a + i * w) * w\n\n return I, N","def integrate(self, lmin, lmax, z, band=1):\n\n if not hasattr(self, 'lummean'):\n self.magmean = np.array([(self.magbins[i]+self.magbins[i+1])/2\n for i in range(len(self.magbins)-1)])\n if not hasattr(self, 'zmean'):\n self.zmean = np.array([(self.zbins[i]+self.zbins[i+1])/2\n for i in range(len(self.zbins)-1)])\n\n if not hasattr(self, 'integ_spline'):\n self.mv_spline = RectBivariateSpline(self.magmean, self.zmean,\n self.luminosity_function[:,band,:])\n\n uvspl = lambda l : self.mv_spline(l, z)\n\n n = quad(uvspl, lmin, lmax)\n\n return n[0]","def integral(self, pars = None):\n if pars is None:\n pars = self.pars_fit\n return .5 * np.sqrt(2.*np.pi) * pars[0] * (pars[2] + pars[3])"],"string":"[\n \"def sp_integrate_1D ( func , xmin , xmax , *args , **kwargs ) : \\n from scipy import integrate\\n ##\\n result = integrate.quad ( func , xmin , xmax , *args , **kwargs )\\n return result[0]\",\n \"def integrate_fun(fun: Callable, low_b: float, upp_b: float) -> float:\\n return integrate.quad(fun, low_b, upp_b)[0]\",\n \"def integrate(self, t):\",\n \"def sp_integrate_2D ( func ,\\n xmin , xmax ,\\n ymin , ymax , *args , **kwargs ) :\\n from scipy import integrate\\n ##\\n result = integrate.dblquad ( func ,\\n ymin ,\\n ymax ,\\n lambda x : xmin ,\\n lambda x : xmax , \\n *args , **kwargs )\\n return result[0]\",\n \"def integrate(f, inf_lim, sup_lim):\\n function = get_function_from_text(f)\\n return sp_integrate.quad(function, inf_lim, sup_lim)[0]\",\n \"def _quad_function(order, *args, **kws):\\n params = parameters_spec.copy()\\n params.update(kws)\\n return quad_function(order, *args, **params)\",\n \"def integrate(self, *args, **kwargs):\\n from sympy.integrals.integrals import integrate\\n return integrate(self, *args, **kwargs)\",\n \"def integrate(x, y, xmin, xmax):\\n indexes = get_interval(x, xmin, xmax)\\n integral = np.trapz(y[indexes], x[indexes])\\n\\n return integral\",\n \"def integrate(self,lower,upper,method=True,n=100,jac=None,**kwargs):\\n\\n #TODO?: vectorize when needed\\n\\n import scipy.integrate as itg\\n if method is True:\\n method=self.defaultIntMethod\\n\\n e,d=None,None\\n\\n ps=tuple(self.parvals)\\n if jac:\\n def f(x,*pars):\\n return jac(x,*pars)*self.f(x,*pars)\\n else:\\n f=self.f\\n\\n if method=='quad':\\n res=itg.quad(f,lower,upper,args=ps,full_output=1,**kwargs)\\n if len(res) == 4:\\n v,e,d,m = res\\n from warnings import warn\\n warn('Integration message: %s'%m)\\n #use these for 2d and 3d\\n #elif method=='dblquad':\\n # raise NotImplementedError\\n #elif method=='tplquad':\\n # raise NotImplementedError\\n elif method=='fixed_quad':\\n res=itg.fixed_quad(f,lower,upper,ps,5 if n is None else n,**kwargs)\\n elif method=='quadrature':\\n res=itg.quadrature(f,lower,upper,ps,**kwargs)\\n elif method=='romberg':\\n res=itg.romberg(f,lower,upper,ps,**kwargs)\\n else: #sampled techniques\\n if n is None:\\n n=100\\n if np.isscalar(n):\\n x=np.linspace(lower,upper,n)\\n else:\\n x=np.array(n)\\n y=f(x,*ps)\\n if method=='trapz':\\n res=itg.trapz(y,x,**kwargs)\\n elif method=='cumtrapz':\\n res=itg.cumtrapz(y,x,**kwargs)\\n elif method=='simps':\\n res=itg.simps(y,x,**kwargs)\\n elif method=='romb':\\n res=itg.simps(y,np.convolve(x,[1,-1],mode='same').mean(),**kwargs)\\n else:\\n raise ValueError('unrecognized integration method')\\n\\n\\n self.lastintegrate = res\\n return res if np.isscalar(res) else res[0]\",\n \"def integrate(func, a, b, tol=1e-8):\\n left_pts = []\\n result = integ(func, a, b, tol, 0, left_pts)\\n\\n return result, left_pts\",\n \"def integrate_f_from0(b):\\n integral, err = scipy.integrate.quad(f, 0, b)\\n return integral\",\n \"def integrate(self, x, dx):\\n return self.State.integrate(x, dx)\",\n \"def integrate(f, delta):\\r\\n I = np.sum(f)\\r\\n I -= (f[0] + f[-1])/2\\r\\n I *= delta\\r\\n return I\",\n \"def quad(func, a, b, args=()):\\n\\tx_units = a.units\\n\\tf_units = func(.5*(a+b)).units\\n\\n\\tI, abserr = sciquad(\\n\\t\\tlambda x : func(x*x_units).to(f_units).magnitude,\\n\\t\\ta.magnitude, b.to(x_units).magnitude,\\n\\t\\targs)\\n\\n\\treturn I*x_units*f_units, abserr*x_units*f_units\",\n \"def integrate(self):\\n raise MethodImplementationError(self, 'integrate')\",\n \"def integrate_quantity(self, q, mask=None, layer=None):\\n if type(q) == str:\\n qarr = self.get_scalar_quantity(q)\\n else:\\n qarr = q\\n if layer is not None:\\n l = self.layers[layer]\\n z_vals = self.Z[l.get_slice(self.Z)]\\n qarr = qarr[l.get_slice(self.Z)]\\n if mask is not None and len(mask.shape) == 3:\\n mask = mask[l.get_slice(self.Z)]\\n else:\\n z_vals = self.Z\\n if mask is not None:\\n qarr = qarr*mask\\n z_integral = intg.trapz(qarr, x=z_vals, axis=0)\\n x_integral = intg.trapz(z_integral, x=self.X, axis=0)\\n y_integral = intg.trapz(x_integral, x=self.Y, axis=0)\\n return y_integral\",\n \"def integrate(self, x, dx):\\n raise NotImplementedError(\\\"Not implemented yet.\\\")\",\n \"def test_quad1():\\n xi = np.array([-1., 0., 2.])\\n yi = np.array([ 1., -1., 7.])\\n c = quad_interp(xi,yi)\\n c_true = np.array([-1., 0., 2.])\\n print(\\\"c = \\\", c)\\n print(\\\"c_true = \\\", c_true)\\n # test that all elements have small error:\\n assert np.allclose(c, c_true), \\\\\\n \\\"Incorrect result, c = %s, Expected: c = %s\\\" % (c,c_true)\",\n \"def test_integrate_fixme(self):\\n ans_photlam = 12.39167258 * (u.ph / (u.cm * u.cm * u.s))\\n assert_quantity_allclose(\\n self.sp.integrate(integration_type='analytical'), ans_photlam)\",\n \"def integrate(f, m=1, j=0):\\n return f.per(dmp_integrate_in(f.rep, m, j, f.lev, f.dom))\",\n \"def integrate_function():\\n def midpoint_integration(f, a, b, n=100):\\n h = (b - a)/float(n)\\n I = 0\\n for i in range(n):\\n I += f(a + i*h + 0.5*h)\\n return h*I\\n\\n\\n f_formula = sys.argv[1]\\n a = eval(sys.argv[2])\\n b = eval(sys.argv[3])\\n if len (sys.argv) >= 5:\\n n = int(sys.arvg[4])\\n else:\\n n = 200\\n\\n from scitools.StringFunction import StringFunction\\n f = StringFunction(f_formula) # turn formula into f(x) func.\\n\\n \\\"\\\"\\\"\\n >>> g = StringFunction('A*exp(-a*t)*sin(omega*x)',\\n independent_variable='t',\\n A=1, a=0.1, omega=pi, x=0.5)\\n >>> g.set_parameters(omega=0.1)\\n >>> g.set_parameters(omega=0.1, A=5, x=0)\\n >>> g(0)\\n 0.0\\n >>> g(pi)\\n 2.8382392288852166e-15\\n \\\"\\\"\\\"\\n\\n I = midpoint_integration(f, a, b, n)\\n print(\\\"Integral of {:s} on [{:g}, {:g}] with n ={:d}: {:g}\\\" \\\\\\n .format(f_formula, a, b, n, I))\",\n \"def test_integrate_wontfix(self):\\n ans_flam = 8.8608168e-09 * (u.erg / (u.cm * u.cm * u.s))\\n assert_quantity_allclose(\\n self.sp.integrate(wavelengths=self.w, flux_unit='flam',\\n integration_type='analytical'), ans_flam)\",\n \"def integrate(self, *args, **kws):\\n gap_handling = kws.get('gap_handling', 'error')\\n wbin = Spectrum._groom_integration_ranges(*args)\\n\\n # check for gap overlap\\n # sometimes small numerical errors cause trouble, so compare to size\\n # of pixels\\n if self.any_gap_overalp(wbin):\\n if gap_handling == 'error':\\n raise ValueError('Some of the integration ranges cover gaps '\\n 'in the spectrum.')\\n elif gap_handling == 'zero':\\n pass\\n else:\\n raise ValueError('gap_handling parameter not recognized')\\n\\n wunit = wbin.unit\\n Fs, Es = [], []\\n for spec in self.spectra:\\n wrange = spec.wbins[[0, -1]].to(wunit).value\\n xbins = utils.rangeset_intersect(wbin.value, [wrange])\\n if len(xbins) > 0:\\n F, E = spec.integrate(xbins*wunit)\\n else:\\n Funit = spec.y.unit*wunit\\n F = 0*Funit\\n E = None if spec.e is None else 0*Funit\\n Fs.append(F); Es.append(E)\\n\\n F = sum(Fs)\\n if any(E is None for E in Es):\\n E = None\\n else:\\n E = _np.sqrt(sum([E**2 for E in Es]))\\n return F, E\",\n \"def integral(self, dmax, dmin=0):\\r\\n # more expressive\\r\\n #return integrate.quad(lambda r: 2*np.pi*r*self(r), dmin, dmax)[0]\\r\\n return self.bpsf.integral(dmax, dmin)\",\n \"def solve_integral(integrand, y):\\n solnarr = np.empty(len(y))\\n for i in range(len(y)):\\n yy = y[i]\\n soln = quad(integrand, 0, np.inf, args=(yy))\\n solnarr[i] = soln[0]\\n return solnarr\",\n \"def integrate(self, x, dx):\\n nq, nv, nx, ndx = self.model.nq, self.model.nv, self.nx, self.ndx\\n assert (x.shape == (nx, ) and dx.shape == (ndx, ))\\n q = x[:nq]\\n v = x[-nv:]\\n dq = dx[:nv]\\n dv = dx[-nv:]\\n qn = pinocchio.integrate(self.model, a2m(q), a2m(dq))\\n return np.concatenate([qn.flat, v + dv])\",\n \"def integrate(self, x1, dx):\\n return x1 + dx\",\n \"def integralFunction(xa, ya, xb, yb):\\n return psi(xb, yb) - psi(xa, ya)\",\n \"def test_integrate_spectrum():\\n e1 = Quantity(1, \\\"TeV\\\")\\n e2 = Quantity(10, \\\"TeV\\\")\\n einf = Quantity(1e10, \\\"TeV\\\")\\n e = Quantity(1, \\\"TeV\\\")\\n g = 2.3\\n I = Quantity(1e-12, \\\"cm-2 s-1\\\")\\n\\n ref = power_law_energy_flux(I=I, g=g, e=e, e1=e1, e2=e2)\\n norm = power_law_flux(I=I, g=g, e=e, e1=e1, e2=einf)\\n f = lambda x: x * power_law_evaluate(x, norm, g, e)\\n val = integrate_spectrum(f, e1, e2)\\n assert_quantity_allclose(val, ref)\\n\\n # Test quantity handling\\n e2_ = Quantity(1e4, \\\"GeV\\\")\\n val_ = integrate_spectrum(f, e1, e2_)\\n assert_quantity_allclose(val, val_)\",\n \"def integrate_base(self, t):\\n\\n return self.__integrate_base(t)\",\n \"def quad(self, y, z=None, method=\\\"sptrapz\\\"):\\n return self.rsphere * self.dlam * np.sum(self.quad_meridional(y, z, method))\",\n \"def eo_numerical(th):\\n res = integrate.dblquad(gaussian_func_2dim_extra, th, np.inf, lambda x: th, lambda x: np.inf)\\n return res[0]\",\n \"def quadTo(self, *__args): # real signature unknown; restored from __doc__ with multiple overloads\\r\\n pass\",\n \"def calc_quad(self,mw,A0,A1,A2): \\n return (A0 + A1 * mw + A2 * mw**2)\",\n \"def integrate(u, j, h):\\n y = u[j]\\n return (h/2.)*((y[0]+y[-1]) + 2*sum(y[1:-1]))\",\n \"def test_quad_grid_volume_integration(self):\\n r = 1\\n R = 10\\n vol = 2 * (np.pi**2) * (r**2) * R\\n\\n inputs = {\\n \\\"L\\\": 1,\\n \\\"M\\\": 1,\\n \\\"N\\\": 0,\\n \\\"NFP\\\": 1,\\n \\\"Psi\\\": 1.0,\\n \\\"pressure\\\": np.array([[0, 0]]),\\n \\\"iota\\\": np.array([[0, 0]]),\\n \\\"surface\\\": np.array([[0, 0, 0, R, 0], [0, 1, 0, r, 0], [0, -1, 0, 0, -r]]),\\n \\\"spectral_indexing\\\": \\\"ansi\\\",\\n \\\"bdry_mode\\\": \\\"lcfs\\\",\\n \\\"node_pattern\\\": \\\"quad\\\",\\n }\\n\\n eq = Equilibrium(**inputs)\\n grid = QuadratureGrid(L=eq.L, M=eq.M, N=eq.N, NFP=eq.NFP)\\n g = eq.compute(\\\"sqrt(g)\\\", grid=grid)\\n vol_quad = np.sum(np.abs(g[\\\"sqrt(g)\\\"]) * grid.weights)\\n\\n np.testing.assert_allclose(vol, vol_quad)\",\n \"def test_functions():\\n\\n isGood = True\\n\\n # Test the trapezoidal integration function\\n trapz = integrate_trapz(f, 0, 1, N=1000)[0]\\n if abs(trapz - 1/3) > 0.00001:\\n print(\\\"WARNING: integrate_trapz() failed the test.\\\")\\n isGood = False\\n\\n # Test the simpson integration function\\n simps = integrate_simpson(f, 0, 1, N=1000)[0]\\n if abs(simps - 1 / 3) > 1e-12:\\n print(\\\"WARNING: integrate_simpson() failed the test.\\\")\\n isGood = False\\n\\n # Test the adaptive trapezoidal integration function\\n trapz = integrate_trapz_adaptive(f, 0, 1, 1e-12)[0]\\n if abs(trapz - 1 / 3) > 1e-12:\\n print(\\\"WARNING: integrate_trapz_adaptive() failed the test.\\\")\\n isGood = False\\n\\n # Test the adaptive simpson integration function\\n simps = integrate_simpson_adaptive(f, 0, 1, 1e-12)[0]\\n if abs(simps - 1 / 3) > 1e-12:\\n print(\\\"WARNING: integrate_simpson_adaptive() failed the test.\\\")\\n isGood = False\\n\\n # Test the 1D Monte Carlo integration function\\n monte = integrate_monte_carlo(f, 0, 1, 1000000)\\n if abs(monte - 1 / 3) > 0.01:\\n print(\\\"WARNING: integrate_monte_carlo() failed the test.\\\")\\n print(\\\"NOTE: There is a small probability of random failure with this method.\\\")\\n print(\\\"Run the test a few more times.\\\")\\n isGood = False\\n\\n # Test the multi-dimensional Monte Carlo integration function\\n monte = integrate_monte_carlo_nd(g, 3, [[-1, 1], [-1, 1], [-1, 1]], N=100000)\\n if abs(monte - (4/3)*np.pi) > 0.1:\\n print(\\\"WARNING: integrate_monte_carlo_nd() failed the test.\\\")\\n print(\\\"NOTE: There is a small probability of random failure with this method.\\\")\\n print(\\\"Run the test a few more times.\\\")\\n isGood = False\\n\\n if isGood is True:\\n print(\\\"Module is good.\\\")\",\n \"def integral(\\n self,\\n start: XValue[T],\\n stop: XValue[T],\\n transform: Callable[[XValueDiff[T]], float] = lambda x: cast(float, x),\\n ) -> float:\\n return self.integrals(start, stop, (stop - start), transform).values()[0]\",\n \"def integrateCartesian(self,xl,xu,yl,yu,**kwargs):\\n import scipy.integrate as itg\\n\\n oldcoordsys = self.incoordsys\\n try:\\n self.incoordsys = 'cartesian'\\n f = lambda y,x:self((x,y))\\n\\n res = itg.dblquad(f,xl,xu,lambda y:yl,lambda y:yu,**kwargs)\\n finally:\\n self.incoordsys = oldcoordsys\\n\\n self.lastintegrate = res\\n return res[0]\",\n \"def complex_integral(self,func,a,b):\\r\\n \\r\\n import scipy\\r\\n from scipy import array\\r\\n \\r\\n def quad_routine(func, a, b, x_list, w_list):\\r\\n c_1 = (b-a)/2.0\\r\\n c_2 = (b+a)/2.0\\r\\n eval_points = map(lambda x: c_1*x+c_2, x_list)\\r\\n func_evals = list(map(func, eval_points)) # Python 3: make a list here\\r\\n return c_1 * sum(array(func_evals) * array(w_list))\\r\\n \\r\\n def quad_gauss_7(func, a, b):\\r\\n x_gauss = [-0.949107912342759, -0.741531185599394, -0.405845151377397, 0, 0.405845151377397, 0.741531185599394, 0.949107912342759]\\r\\n w_gauss = array([0.129484966168870, 0.279705391489277, 0.381830050505119, 0.417959183673469, 0.381830050505119, 0.279705391489277,0.129484966168870])\\r\\n return quad_routine(func,a,b,x_gauss, w_gauss)\\r\\n \\r\\n def quad_kronrod_15(func, a, b):\\r\\n x_kr = [-0.991455371120813,-0.949107912342759, -0.864864423359769, -0.741531185599394, -0.586087235467691,-0.405845151377397, -0.207784955007898, 0.0, 0.207784955007898,0.405845151377397, 0.586087235467691, 0.741531185599394, 0.864864423359769, 0.949107912342759, 0.991455371120813]\\r\\n w_kr = [0.022935322010529, 0.063092092629979, 0.104790010322250, 0.140653259715525, 0.169004726639267, 0.190350578064785, 0.204432940075298, 0.209482141084728, 0.204432940075298, 0.190350578064785, 0.169004726639267, 0.140653259715525, 0.104790010322250, 0.063092092629979, 0.022935322010529]\\r\\n return quad_routine(func,a,b,x_kr, w_kr)\\r\\n \\r\\n class Memorize: # Python 3: no need to inherit from object\\r\\n def __init__(self, func):\\r\\n self.func = func\\r\\n self.eval_points = {}\\r\\n def __call__(self, *args):\\r\\n if args not in self.eval_points:\\r\\n self.eval_points[args] = self.func(*args)\\r\\n return self.eval_points[args]\\r\\n \\r\\n def quad(func,a,b):\\r\\n ''' Output is the 15 point estimate; and the estimated error '''\\r\\n func = Memorize(func) # Memorize function to skip repeated function calls.\\r\\n g7 = quad_gauss_7(func,a,b)\\r\\n k15 = quad_kronrod_15(func,a,b)\\r\\n # I don't have much faith in this error estimate taken from wikipedia\\r\\n # without incorporating how it should scale with changing limits\\r\\n return [k15, (200*scipy.absolute(g7-k15))**1.5]\\r\\n \\r\\n return quad(func,a,b)\",\n \"def complex_integral(self,func,a,b):\\r\\n \\r\\n import scipy\\r\\n from scipy import array\\r\\n \\r\\n def quad_routine(func, a, b, x_list, w_list):\\r\\n c_1 = (b-a)/2.0\\r\\n c_2 = (b+a)/2.0\\r\\n eval_points = map(lambda x: c_1*x+c_2, x_list)\\r\\n func_evals = list(map(func, eval_points)) # Python 3: make a list here\\r\\n return c_1 * sum(array(func_evals) * array(w_list))\\r\\n \\r\\n def quad_gauss_7(func, a, b):\\r\\n x_gauss = [-0.949107912342759, -0.741531185599394, -0.405845151377397, 0, 0.405845151377397, 0.741531185599394, 0.949107912342759]\\r\\n w_gauss = array([0.129484966168870, 0.279705391489277, 0.381830050505119, 0.417959183673469, 0.381830050505119, 0.279705391489277,0.129484966168870])\\r\\n return quad_routine(func,a,b,x_gauss, w_gauss)\\r\\n \\r\\n def quad_kronrod_15(func, a, b):\\r\\n x_kr = [-0.991455371120813,-0.949107912342759, -0.864864423359769, -0.741531185599394, -0.586087235467691,-0.405845151377397, -0.207784955007898, 0.0, 0.207784955007898,0.405845151377397, 0.586087235467691, 0.741531185599394, 0.864864423359769, 0.949107912342759, 0.991455371120813]\\r\\n w_kr = [0.022935322010529, 0.063092092629979, 0.104790010322250, 0.140653259715525, 0.169004726639267, 0.190350578064785, 0.204432940075298, 0.209482141084728, 0.204432940075298, 0.190350578064785, 0.169004726639267, 0.140653259715525, 0.104790010322250, 0.063092092629979, 0.022935322010529]\\r\\n return quad_routine(func,a,b,x_kr, w_kr)\\r\\n \\r\\n class Memorize: # Python 3: no need to inherit from object\\r\\n def __init__(self, func):\\r\\n self.func = func\\r\\n self.eval_points = {}\\r\\n def __call__(self, *args):\\r\\n if args not in self.eval_points:\\r\\n self.eval_points[args] = self.func(*args)\\r\\n return self.eval_points[args]\\r\\n \\r\\n def quad(func,a,b):\\r\\n ''' Output is the 15 point estimate; and the estimated error '''\\r\\n func = Memorize(func) # Memorize function to skip repeated function calls.\\r\\n g7 = quad_gauss_7(func,a,b)\\r\\n k15 = quad_kronrod_15(func,a,b)\\r\\n # I don't have much faith in this error estimate taken from wikipedia\\r\\n # without incorporating how it should scale with changing limits\\r\\n return [k15, (200*scipy.absolute(g7-k15))**1.5]\\r\\n \\r\\n return quad(func,a,b)\",\n \"def vert_integrate(self, u, d='up', Q='self'):\\n s = \\\"::: vertically integrating function :::\\\"\\n print_text(s, cls=self)\\n\\n if type(Q) != FunctionSpace:\\n Q = self.Q\\n ff = self.ff\\n phi = TestFunction(Q)\\n v = TrialFunction(Q)\\n bcs = []\\n # integral is zero on bed (ff = 3,5) \\n if d == 'up':\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_B_GND)) # grounded\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_B_FLT)) # shelves\\n a = v.dx(2) * phi * dx\\n # integral is zero on surface (ff = 2,6) \\n elif d == 'down':\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_S_GND)) # grounded\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_S_FLT)) # shelves\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_U_GND)) # grounded\\n bcs.append(DirichletBC(Q, 0.0, ff, self.GAMMA_U_FLT)) # shelves\\n a = -v.dx(2) * phi * dx\\n L = u * phi * dx\\n name = 'value integrated %s' % d \\n v = Function(Q, name=name)\\n solve(a == L, v, bcs, annotate=False)\\n print_min_max(u, 'vertically integrated function', cls=self)\\n return v\",\n \"def quad_interp(x,y,xi) :\\n f = interp1d(x,y,kind='quadratic')\\n yi = f(xi)\\n \\n return yi\",\n \"def integral ( self, xmin , xmax , ymin , ymax , nevents = True ) :\\n if self.xminmax() :\\n xmn , xmx = self.xminmax()\\n xmin = max ( xmin , xmn )\\n xmax = min ( xmax , xmx )\\n\\n if self.yminmax() : \\n ymn , ymx = self.yminmax() \\n ymin = max ( ymin , ymn )\\n ymax = min ( ymax , ymx )\\n\\n value , todo = 0 , True \\n \\n ## 1) make a try to use analytical integral (could be fast)\\n if self.tricks :\\n try:\\n if hasattr ( self.pdf , 'setPars' ) : self.pdf.setPars() \\n fun = self.pdf.function()\\n value , todo = fun.integral ( xmin , xmax , ymin , ymax ) , False \\n except:\\n pass\\n\\n ## use numerical integration \\n from ostap.math.integral import integral2 as _integral2\\n\\n extended = self.pdf.canBeExtended() or isinstance ( self.pdf , ROOT.RooAddPdf )\\n\\n if todo and extended : value = _integral2 ( self , xmin , xmax , ymin , ymax )\\n elif todo :\\n \\n ## use unormalized PDF here to speed up the integration \\n ifun = lambda x, y : self ( x , y , error = False , normalized = False )\\n value = _integral2 ( ifun , xmin , xmax , ymin , ymax )\\n norm = self.pdf.getNorm ( self.vars )\\n value /= norm\\n\\n if nevents and self.pdf.mustBeExtended () :\\n evts = self.pdf.expectedEvents( self.vars )\\n if evts <= 0 or iszero ( evts ) :\\n self.warning ( \\\"integral: expectedEvents is %s\\\" % evts )\\n value *= evts \\n\\n return value\",\n \"def integrate(self, start, end):\\n return self.foldl_time(start, end, 0,\\n lambda v, time, lvl: v + time * lvl)\",\n \"def complex_quadrature(func, a, b, **kwargs):\\n\\n def real_func(x):\\n return scipy.real(func(x))\\n\\n def imag_func(x):\\n return scipy.imag(func(x))\\n\\n real_integral = quad(real_func, a, b, **kwargs)\\n imag_integral = quad(imag_func, a, b, **kwargs)\\n return (real_integral[0] + 1j * imag_integral[0], real_integral[1:], imag_integral[1:])\",\n \"def _test_integrate(self, integrator: BaseTsdfIntegrator) -> None:\\n integrator.integrate(points=self.points, extrinsic=self.pose)\",\n \"def integrate(x, power):\\n if power == -1:\\n return log(abs(x))\\n else:\\n return float(pow(x, power+1)) / (power+1.)\",\n \"def test_get_quad_square_all_float(self):\\n result = get_quadrilateral_type(2.4, 2.4, 2.4, 2.4, 90, 90, 90, 90)\\n self.assertEqual(result, 'square')\",\n \"def sp_integrate_1D_ ( pdf , xmin , xmax , *args , **kwargs ) :\\n if hasattr ( pdf , 'setPars' ) : pdf.setPars() \\n func = pdf.function()\\n return func.sp_integrate_1D ( xmin , xmax , *args , **kwargs )\",\n \"def scipy_integrate(func, X0, args, N=0):\\n V0 = 0.7 # we fix the volatge initial condition\\n t_span = [0.0, args.h * N]\\n t_sim = np.linspace(0.0, args.h * N, N+1)\\n sol = solve_ivp(func, t_span, [X0[0], X0[1], X0[2], X0[3], V0], method=args.method, t_eval=t_sim.reshape(-1,))\\n y_test = sol.y\\n t_sim = t_sim.reshape(-1, 1)\\n return t_sim[1:,:], y_test[:, 1:]\",\n \"def mc_integrate1d(f, a, b, N=10000):\\n #use the approximation formula with a translate and scale of unit interval\\n points = (b-a)*np.random.rand(N)+a\\n y = f(points)\\n return (b-a)*sum(y)/N\",\n \"def integrate(self, *args):\\n wbin = Spectrum._groom_integration_ranges(*args)\\n try:\\n wbin.to(self.w.unit)\\n except AttributeError as xxx_todo_changeme:\\n _u.UnitConversionError = xxx_todo_changeme\\n raise ValueError('Input must be astropy quantity with units '\\n 'convertable to that of spectrum.')\\n if _np.any(wbin < self.wbins[0]) or _np.any(wbin > self.wbins[-1]):\\n raise ValueError('Integration range is beyond spectrum range.')\\n dw = _np.diff(wbin, 1).squeeze()\\n newspec = self.rebin(wbin.ravel())\\n flux_dens = newspec.y[::2]\\n fluxes = flux_dens*dw\\n flux = _np.sum(fluxes)\\n if self.e is None:\\n error = None\\n else:\\n err_dens = newspec.e[::2]\\n errs = err_dens*dw\\n error = utils.quadsum(errs)\\n return flux, error\",\n \"def test_quad_flush_ind(self):\",\n \"def integrate(self, *w):\\n # deal with subspectrums if necessary\\n if not w:\\n spectrum = self.spectrum\\n interp = self.interp\\n else:\\n assert len(w) >= 2 and w[0] < w[\\n 1], 'Error: Too few wavelengths or start wavelength is not shorter than the longest wavelength.'\\n spectrum = self.sub_spectrum(w[0], w[1])\\n # TODO: Decide if to use quad and interp1d obj for integration or not. trapz is faster & close in result\\n # interp = interpolate.interp1d(spectrum[:, 0], spectrum[:, 1])\\n # get the total number of discrete wavelengths as a bin limit\\n # bin_limit = len(spectrum[:, 0])\\n # integrate the power\\n # power_f = integrate.quad(interp, spectrum[0, 0], spectrum[-1, 0], full_output=1, limit=bin_limit)\\n power_f = integrate.trapz(spectrum[:, 1], spectrum[:, 0])\\n return power_f # Units Watts/meters^2\",\n \"def _integrate(self, integrator, dt, tf, post_step_callback):\\n t = 0.0\\n while t < tf:\\n integrator.step(t, dt)\\n post_step_callback(t+dt)\\n t += dt\",\n \"def integrate(self, X_0, t_vec, rel_tol, abs_tol, params):\\n return None\",\n \"def integrate_trapz_adaptive(f, lower, upper, accuracy=1e-8, detailed=False):\\n a = lower # Lower limit of integration\\n b = upper # Upper limit of integration\\n Tol = accuracy # Error tolerance\\n error = 1 # Error needs to be initialized as something\\n N = 1 # Start with 1 trapezoid\\n\\n # I0 is the approximation with a single trapezoid\\n I0 = (f(a) + f(b))*(b-a)*0.5\\n\\n # Do you want detailed results?\\n if detailed is True:\\n print(\\\"N = \\\", N, \\\", I = \\\", I0, sep=\\\"\\\")\\n\\n while error > Tol: # Repeat until the error is less than the error tolerance\\n\\n N *= 2 # Double the slices each iteration\\n w = (b - a)/N # Width of each trapezoid\\n\\n I = 0.5*I0\\n for i in range(1, N, 2):\\n I += f(a + i*w)*w\\n\\n error = abs(I - I0)/3\\n\\n I0 = I\\n\\n # Do you want detailed results?\\n if detailed is True:\\n print(\\\"N = \\\", N, \\\", I = \\\", I, \\\", Error = \\\", error, sep=\\\"\\\")\\n\\n return I, N, error\",\n \"def integrate(self, units=True, e_weight=0):\\n int = logsimps(lambda e: e**e_weight*self(e, units=False), self.emin, self.emax, sed_config.PER_DECADE)\\n return int*(u.erg**(e_weight+1)*self.units() if units else 1)\",\n \"def _oned_intFunc(x,twodfunc,gfun,hfun,tol,args):\\n thisargs= copy.deepcopy(args)\\n thisargs.insert(0,x)\\n return integrate.romberg(twodfunc,gfun(x),hfun(x),args=thisargs,tol=tol)\",\n \"def quad(f, a, b):\\n\\tS, D = (b+a)/2.0, (b-a)/2.0\\n\\tdef rescaled_f(x):\\n\\t\\treturn f(x*D + S)*D\\n\\treturn sum(w * rescaled_f(p) for w, p in zip(quad_weights, quad_points))\",\n \"def integrate_using_univariate_gauss_legendre_quadrature_unbounded(\\n integrand, lb, ub, nquad_samples, atol=1e-8, rtol=1e-8,\\n interval_size=2, max_steps=1000, verbose=0, adaptive=True,\\n soft_error=False, tabulated_quad_rules=None):\\n if interval_size <= 0:\\n raise ValueError(\\\"Interval size must be positive\\\")\\n\\n if np.isfinite(lb) and np.isfinite(ub):\\n partial_lb, partial_ub = lb, ub\\n elif np.isfinite(lb) and not np.isfinite(ub):\\n partial_lb, partial_ub = lb, lb+interval_size\\n elif not np.isfinite(lb) and np.isfinite(ub):\\n partial_lb, partial_ub = ub-interval_size, ub\\n else:\\n partial_lb, partial_ub = -interval_size/2, interval_size/2\\n\\n result = __integrate_using_univariate_gauss_legendre_quadrature_bounded(\\n integrand, partial_lb, partial_ub, nquad_samples, rtol,\\n atol, verbose-1, adaptive, tabulated_quad_rules)\\n\\n step = 0\\n partial_result = np.inf\\n plb, pub = partial_lb-interval_size, partial_lb\\n while (np.any(np.absolute(partial_result) >= rtol*np.absolute(result)+atol)\\n and (plb >= lb) and step < max_steps):\\n partial_result = \\\\\\n __integrate_using_univariate_gauss_legendre_quadrature_bounded(\\n integrand, plb, pub, nquad_samples, rtol, atol,\\n verbose-1, adaptive, tabulated_quad_rules)\\n result += partial_result\\n pub = plb\\n plb -= interval_size\\n step += 1\\n if verbose > 1:\\n print('Left', step, result, partial_result, plb, pub,\\n interval_size)\\n if verbose > 0:\\n if step >= max_steps:\\n msg = \\\"Early termination when computing left integral\\\"\\n msg += f\\\"max_steps {max_steps} reached\\\"\\n if soft_error is True:\\n warn(msg, UserWarning)\\n else:\\n raise RuntimeError(msg)\\n if np.all(np.abs(partial_result) < rtol*np.absolute(result)+atol):\\n msg = f'Tolerance {atol} {rtol} for left integral reached in '\\n msg += f'{step} iterations'\\n print(msg)\\n\\n step = 0\\n partial_result = np.inf\\n plb, pub = partial_ub, partial_ub+interval_size\\n while (np.any(np.absolute(partial_result) >= rtol*np.absolute(result)+atol)\\n and (pub <= ub) and step < max_steps):\\n partial_result = \\\\\\n __integrate_using_univariate_gauss_legendre_quadrature_bounded(\\n integrand, plb, pub, nquad_samples, rtol, atol,\\n verbose-1, adaptive, tabulated_quad_rules)\\n result += partial_result\\n plb = pub\\n pub += interval_size\\n step += 1\\n if verbose > 1:\\n print('Right', step, result, partial_result, plb, pub,\\n interval_size)\\n if verbose > 0:\\n if step >= max_steps:\\n msg = \\\"Early termination when computing right integral. \\\"\\n msg += f\\\"max_steps {max_steps} reached\\\"\\n if soft_error is True:\\n warn(msg, UserWarning)\\n else:\\n raise RuntimeError(msg)\\n if np.all(np.abs(partial_result) < rtol*np.absolute(result)+atol):\\n msg = f'Tolerance {atol} {rtol} for right integral reached in '\\n msg += f'{step} iterations'\\n print(msg)\\n # print(partial_result, plb, pub)\\n\\n return result\",\n \"def test_get_quad_angover_all_float(self):\\n result = get_quadrilateral_type(2, 2, 2, 2, 180.1, .1, 180.1, .1)\\n self.assertEqual(result, 'invalid')\",\n \"def integrand(x, n):\\n return jn(n, x)\",\n \"def integrateCircular(self,outr,inr=0,theta=(0,2*pi),**kwargs):\\n import scipy.integrate as itg\\n oldcoordsys = self.incoordsys\\n try:\\n self.incoordsys = 'polar'\\n f = lambda th,r:r*self((r,th))\\n\\n res = itg.dblquad(f,inr,outr,lambda y:theta[0],lambda y:theta[1],**kwargs)\\n finally:\\n self.incoordsys = oldcoordsys\\n\\n self.lastintegrate = res\\n return res[0]\",\n \"def intsolve(func, value, start=None, stop=None, maxit=1000):\\n from scipy import inf\\n from scipy.integrate import quad\\n from warnings import warn\\n if start is None:\\n start = -inf\\n if stop is None:\\n stop = inf\\n lower_bound = start\\n upper_bound = stop\\n it = 0\\n while it < maxit:\\n it += 1\\n if upper_bound == inf:\\n if lower_bound == -inf:\\n test_bound = 0\\n elif lower_bound < 1.0:\\n test_bound = 1.0\\n else:\\n test_bound = lower_bound * 2\\n else:\\n if lower_bound == -inf:\\n if upper_bound > -1.0:\\n test_bound = -1.0\\n else:\\n test_bound = upper_bound * 2\\n else:\\n test_bound = (lower_bound + upper_bound) / 2.0\\n (test_value, err) = quad(func, start, test_bound)\\n if abs(value - test_value) <= err:\\n break\\n elif value < test_value:\\n upper_bound = test_bound\\n else:\\n lower_bound = test_bound\\n\\n if abs(value - test_value) > err:\\n warn('Difference between desired value and actual is ' +\\n str(abs(value - test_value)) +\\n ', greater than integral error ' +\\n str(err), UserWarning, stacklevel=2)\\n return test_bound\",\n \"def integrate(self, x0, t0, tend, N):\\n raise NotImplementedError\",\n \"def field_line_integrate(\\n r0, z0, phis, field, params={}, rtol=1e-8, atol=1e-8, maxstep=1000\\n):\\n r0, z0, phis = map(jnp.asarray, (r0, z0, phis))\\n assert r0.shape == z0.shape, \\\"r0 and z0 must have the same shape\\\"\\n rshape = r0.shape\\n r0 = r0.flatten()\\n z0 = z0.flatten()\\n x0 = jnp.array([r0, phis[0] * jnp.ones_like(r0), z0]).T\\n\\n @jit\\n def odefun(rpz, s):\\n rpz = rpz.reshape((3, -1)).T\\n r = rpz[:, 0]\\n br, bp, bz = field.compute_magnetic_field(rpz, params, basis=\\\"rpz\\\").T\\n return jnp.array(\\n [r * br / bp * jnp.sign(bp), jnp.sign(bp), r * bz / bp * jnp.sign(bp)]\\n ).squeeze()\\n\\n intfun = lambda x: odeint(odefun, x, phis, rtol=rtol, atol=atol, mxstep=maxstep)\\n x = jnp.vectorize(intfun, signature=\\\"(k)->(n,k)\\\")(x0)\\n r = x[:, :, 0].T.reshape((len(phis), *rshape))\\n z = x[:, :, 2].T.reshape((len(phis), *rshape))\\n return r, z\",\n \"def integrate(self, q: Variable, p: Variable, n_steps: int, eps: float, forward, method=\\\"leapfrog\\\"):\\n _isin(method, Hamiltonian.integrate_methods)\\n # Again, casting hyperparameters to tf.Tensor is crucial here. Otherwise, leapfrog will retrace at each\\n # change of arguments.\\n # Also necessary to cast for avoiding compatibility issues; even if float64 by default with the tf.constant(...)\\n # constructor\\n eps = tf.constant(eps, dtype='float32')\\n\\n params = dict(q=q, p=p,\\n n_steps=tf.constant(n_steps),\\n eps=eps,\\n forward=tf.constant(forward),\\n grad_func_q=self.grad_potential,\\n grad_func_p=self.grad_kinetic)\\n if method == \\\"leapfrog\\\":\\n return _leapfrog_integration(**params)\\n elif method == \\\"euler\\\":\\n return _euler_integration(**params)\",\n \"def test_wrapped_call(self, config: HandlerConfig) -> None:\\n # Arrange.\\n # Create a mock Unit to convert.\\n mock_unit = mock.Mock(spec=MyUnit)\\n\\n # Act.\\n # Try converting it.\\n converted = config.handler(mock_unit)\\n\\n # Assert.\\n # It should have made sure all the units were correct.\\n config.mock_from_unit.assert_called_once_with(mock_unit)\\n\\n input_unit = config.mock_from_unit.return_value\\n config.mock_function.assert_called_once_with(input_unit)\\n\\n raw_output = config.mock_function.return_value\\n config.mock_to_unit.assert_called_once_with(raw_output)\\n\\n assert converted == config.mock_to_unit.return_value\",\n \"def get_integral_over_times(start, stop, rate):\\n return integrate.quad(get_townsend_pi, start, stop, args=(rate))\",\n \"def _G(xi, B):\\n try:\\n import scipy.integrate\\n except:\\n raise ImportError(' [PHIDL] To run the microstrip functions you '\\n 'need scipy, please install it with '\\n '`pip install scipy`')\\n return B/sinh(B)*scipy.integrate.quad(_G_integrand, 0, xi, args = (B))[0]\",\n \"def integrate_axis_py(obj, **kwargs):\\n\\n # import the helper functions\\n import hlr_utils\\n\\n # set up for working through data\\n o_descr = hlr_utils.get_descr(obj)\\n\\n if o_descr == \\\"number\\\" or o_descr == \\\"list\\\":\\n raise RuntimeError(\\\"Must provide a SOM of a SO to the function.\\\")\\n # Go on\\n else:\\n pass\\n\\n # Check for starting bin\\n try:\\n start = kwargs[\\\"start\\\"]\\n except KeyError:\\n start = 0\\n\\n # Check for ending bin\\n try: \\n end = kwargs[\\\"end\\\"]\\n if end != -1:\\n end += 1\\n else:\\n pass\\n except KeyError:\\n end = -1\\n\\n # Check for axis keyword argument\\n try:\\n axis = kwargs[\\\"axis\\\"]\\n except KeyError:\\n axis = \\\"y\\\"\\n \\n # Check for axis_pos keyword argument\\n try:\\n axis_pos = kwargs[\\\"axis_pos\\\"]\\n except KeyError:\\n axis_pos = 0\\n\\n # Check for avg keyword argument\\n try:\\n avg = kwargs[\\\"avg\\\"]\\n except KeyError:\\n avg = False\\n\\n # Check for width keyword argument\\n try:\\n width = kwargs[\\\"width\\\"]\\n except KeyError:\\n width = False \\n\\n # Check for width_pos keyword argument\\n try:\\n width_pos = kwargs[\\\"width_pos\\\"]\\n except KeyError:\\n width_pos = 0 \\n \\n integration = float(0)\\n integration_error2 = float(0)\\n\\n import itertools\\n if width:\\n import utils\\n\\n bad_values = [\\\"nan\\\", \\\"inf\\\", \\\"-inf\\\"]\\n\\n for i in xrange(hlr_utils.get_length(obj)): \\n counter = 0 \\n\\n value = hlr_utils.get_value(obj, i, o_descr, axis, axis_pos)\\n error = hlr_utils.get_err2(obj, i, o_descr, axis, axis_pos)\\n\\n if end == -1:\\n value = value[start:]\\n error = error[start:]\\n else:\\n value = value[start:end]\\n error = error[start:end]\\n \\n if not width:\\n for val, err2 in itertools.izip(value, error):\\n if str(val) in bad_values or str(err2) in bad_values:\\n continue\\n else:\\n integration += val\\n integration_error2 += err2\\n counter += 1\\n else:\\n if axis == \\\"y\\\":\\n x_axis = hlr_utils.get_value(obj, i, o_descr, \\\"x\\\", width_pos)\\n x_err2 = hlr_utils.get_err2(obj, i, o_descr, \\\"x\\\", width_pos)\\n elif axis == \\\"x\\\":\\n raise RuntimeError(\\\"Cannot use width flag with x-axis \\\"\\\\\\n +\\\"integration\\\")\\n\\n bin_widths = utils.calc_bin_widths(x_axis, x_err2)\\n\\n for val, err2, delta in itertools.izip(value, error,\\n bin_widths[0]):\\n if str(val) in bad_values or str(err2) in bad_values:\\n continue\\n else:\\n integration += (delta * val)\\n integration_error2 += (delta * delta * err2)\\n counter += 1\\n \\n if avg:\\n return (integration / float(counter),\\n integration_error2 / float(counter))\\n else:\\n return (integration, integration_error2)\",\n \"def piecewise_integrate(x, y, a, b):\\n assert x[0] == a\\n assert x[-1] <= b\\n output = 0.\\n num_x = len(x)\\n if x[-1] == b:\\n for idx in range(num_x - 1):\\n output += y[idx] * (x[idx+1] - x[idx])\\n else:\\n for idx in range(num_x):\\n if idx < num_x - 1:\\n output += y[idx] * (x[idx+1] - x[idx])\\n else:\\n output += y[idx] * (b - x[idx])\\n return output\",\n \"def integrate(self,u,x,Dt,t,bc):\\n time=t[0]\\n i=1\\n result=interfaces.State()\\n result.x=scipy.zeros((len(x),len(t)),scipy.float64)\\n result.x[:,0]=x\\n s=list(scipy.shape(u))\\n s.append(len(t))\\n result.u=scipy.zeros(s,scipy.float64)\\n result.u[:,:,0]=u\\n result.time=t\\n \\n while not scipy.allclose(time,t[-1],rtol=1e-8,atol=1e-10):\\n k1=self.estimator.estimate(u,time,x,bc)\\n\\t k2=self.estimator.estimate(u+0.5*Dt*k1,time+0.5*Dt,x,bc)\\n\\t k3=self.estimator.estimate(u+0.5*Dt*k2,time+0.5*Dt,x,bc)\\n\\t k4=self.estimator.estimate(u+Dt*k3,time+Dt,x,bc)\\n\\t u=u+Dt*(1./6.*k1+1./3.*k2+1./3.*k3+1./6.*k4)\\n time=time+Dt\\n\\t if scipy.allclose(time,t[i],rtol=1e-8,atol=1e-10):\\n \\tresult.x[:,i]=x\\n result.u[:,:,i]=u\\n \\ti+=1\\n return result\",\n \"def integrate(f, a, b, args=(), minintervals=1, limit=200, tol=1e-10):\\n fv = np.vectorize(f)\\n\\n intervals = []\\n\\n limits = np.linspace(a, b, minintervals+1)\\n for left, right in zip(limits[:-1], limits[1:]):\\n I, err = integrate_gausskronrod(fv, left, right, args)\\n bisect.insort(intervals, (err, left, right, I))\\n\\n while True:\\n Itotal = sum([x[3] for x in intervals])\\n err2 = sum([x[0]**2 for x in intervals])\\n err = sqrt(err2)\\n\\n if abs(err/Itotal) < tol:\\n return Itotal, err\\n\\n # no convergence\\n if len(intervals) >= limit:\\n return False # better to raise an exception\\n\\n err, left, right, I = intervals.pop()\\n\\n # split integral\\n mid = left+(right-left)/2\\n\\n # calculate integrals and errors, replace one item in the list and\\n # append the other item to the end of the list\\n I, err = integrate_gausskronrod(fv, left, mid, args)\\n bisect.insort(intervals, (err, left, mid, I))\\n I, err = integrate_gausskronrod(fv, mid, right, args)\\n bisect.insort(intervals, (err, mid, right, I))\",\n \"def trapz(x, modify_endpoints=False):\\n integral = (\\n x[1:] + x[:-1]\\n ) / 2\\n if modify_endpoints:\\n integral[0] = integral[0] + x[0] * 0.5\\n integral[-1] = integral[-1] + x[-1] * 0.5\\n\\n return integral\",\n \"def integrate_simpson_adaptive(f, lower, upper, accuracy=1e-15, detailed=False):\\n a = lower # Lower limit of integration\\n b = upper # Upper limit of integration\\n Tol = accuracy # Error tolerance\\n error = 1.0 # Error needs to be initialized as something\\n N = 1 # Start with 1 slice\\n\\n # I0 is the approximation with a single slice\\n I0 = ((b-a)/6) * (f(a) + 4 * f((b - a)/2) + f(b)) # Area of first and last slice\\n\\n # Do you want detailed results?\\n if detailed is True:\\n print(\\\"N = \\\", N, \\\", I = \\\", I0, sep=\\\"\\\")\\n\\n while error > Tol:\\n\\n N *= 2\\n w = (b - a) / N # Width of each slice\\n\\n I = 0.5 * I0\\n for i in range(1, N, 2):\\n I += -f(a + w * i) * w / 3\\n for i in range(0, N):\\n I += (2 / 3) * f(a + w * (i + 1 / 2)) * w\\n\\n error = abs(I - I0)/15\\n\\n I0 = I\\n\\n # Do you want detailed results?\\n if detailed is True:\\n print(\\\"N = \\\", N, \\\", I = \\\", I, \\\", Error = \\\", error, sep=\\\"\\\")\\n\\n return I, N, error\",\n \"def integrate(equ):\\n if \\\"x\\\" in equ:\\n return polynomial_equation(equ)\\n else:\\n return constant_equation(equ)\",\n \"def compute_integrals(self):\\n\\n integrals = self.dat.data.reshape(-1, self.nvdofs).T.dot(self.cell_volumes)\\n integrals_lift = Function(self._function_space)\\n integrals_lift.dat.data[:] = np.tile(integrals,(self.nhdofs,))\\n\\n return integrals_lift\",\n \"def integrate_dphi_phi(self, i, j):\\n def func(x):\\n return self.shape_function_deriv(i, x) * self.shape_function(j, x)\\n i, err = quadrature(func, -1, 1)\\n return i\",\n \"def integrate_highest_dimension(self, field, dx = 1):\\n axis_num = field.ndim - 1\\n integrated_field = np.trapz(field, dx = dx, axis = axis_num)\\n \\n return integrated_field\",\n \"def do_math_double(cls, quad, type):\\n\\t\\tdata1 = cls.get_address_value(quad.left_operand)\\n\\t\\tdata2 = cls.get_address_value(quad.right_operand)\\n\\t\\tval = 0.0\\n\\t\\tif(type == \\\"pow\\\"):\\n\\t\\t\\tval = math.pow(data1, data2)\\n\\n\\t\\tcls.set_address_value(quad.result, val)\",\n \"def integrate(self, t):\\n t0 = self.t0\\n if t-t0 <= self.max_step_size:\\n self.y0 = self.y0 + (t-t0)*self.f(t0,self.y0) \\n \\n else :\\n n = (t-t0) / self.max_step_size\\n dt = (t-t0)/int(n+1)\\n \\n while t0 < t :\\n self.y0 = self.y0 + dt*self.f(t0,self.y0)\\n t0 += dt\\n \\n return self.y0\",\n \"def Integrator_1(t_vec, x0):\\n\\tx = np.zeros((len(t_vec), x0.shape[0], N_max)) # set up the array of x values\\n\\t\\n\\tfor N in range(1, N_max+1):\\n\\t\\tx[0, :, N-1] = x0.reshape(2)\\n\\t\\tfor i in range(1,len(t_vec)):\\n\\t\\t\\tx[i,:,N-1] = (f_step(0, t_vec[i], N) @ x0).reshape(2)\\n\\t\\t\\tif (i*100) % (len(t_vec)-1) == 0:\\n\\t\\t\\t\\tprint(\\\"\\\\r\\\" + \\\"integrated {:.0%}\\\".format(i/(len(t_vec)-1)), end='')\\n\\t\\t\\n\\t\\tprint(' done order ', N)\\n\\t\\t\\n\\treturn x\",\n \"def integrate_simpson(f, lower, upper, N=1000):\\n a = lower # Lower integration limit\\n b = upper # Upper integration limit\\n w = (b - a) / N # Width of each trapezoid\\n\\n if N % 2 != 0:\\n N += 1\\n print(\\\"Number of slices was odd so 1 was added to N.\\\")\\n\\n I = (1 / 3) * f(a) * w + (1 / 3) * f(b) * w # Area of first and last trapezoids\\n\\n for i in range(1, N, 2): # Odd terms\\n I += f(a + i * w) * w * (4 / 3)\\n\\n for i in range(2, N, 2): # Even terms\\n I += f(a + i * w) * w * (2 / 3)\\n\\n return I, N\",\n \"def integrate(l_tr_val, ind_bs):\\n\\n phi1max = 360. # max phi1 angle (deg) for integration domain\\n phimax = 90. # max phi angle (deg) for integration domain\\n phi2max = 60. # max phi2 angle (deg) for integration domain\\n inc = 3. # degree increment for euler angle generation\\n l_tr_cal = 8 # truncation level in the l index for the GSH\\n\\n indxvec = gsh.gsh_basis_info()\\n N_L_cal = np.sum(indxvec[:, 0] <= l_tr_cal)\\n N_L_val = np.sum(indxvec[:, 0] <= l_tr_val)\\n N_L = np.max([N_L_cal, N_L_val])\\n\\n euler, n_tot = euler_grid_center(inc, phi1max, phimax, phi2max)\\n\\n \\\"\\\"\\\"Generate X\\\"\\\"\\\"\\n X = gsh.gsh_eval(euler, np.arange(N_L))/(2*indxvec[:N_L, 0]+1)\\n\\n \\\"\\\"\\\"Generate Y (test function)\\\"\\\"\\\"\\n\\n np.random.seed(141)\\n\\n normvec = (2*indxvec[:N_L, 0]+1)**3\\n bval = (np.random.normal(scale=1.0, size=N_L_cal)**3)/normvec\\n\\n Y = np.zeros(n_tot, dtype='complex128')\\n for ii in xrange(N_L_cal):\\n Y += bval[ii]*X[:, ii]\\n\\n Y = Y.real\\n\\n \\\"\\\"\\\"Perform the integration for the GSH coefficients\\\"\\\"\\\"\\n coef = np.zeros(N_L_val, dtype='complex128')\\n\\n # domain_eul_sz is the integration domain in radians\\n domain_sz = phi1max*phimax*phi2max*(np.pi/180.)**3\\n # full_eul_sz is the size of euler space in radians\\n full_sz = (2*np.pi)*(np.pi)*(2*np.pi)\\n eul_frac = domain_sz/full_sz\\n fzsz = 1./(eul_frac*8.*np.pi**2)\\n bsz = domain_sz/n_tot\\n\\n for ii in xrange(N_L_val):\\n\\n l = indxvec[ii, 0]\\n tmp = (2*l+1)*np.sum(Y*X[:, ii].conj()*np.sin(euler[:, 1]))*bsz*fzsz\\n coef[ii] = tmp\\n\\n \\\"\\\"\\\"check accuracy of GSH representation\\\"\\\"\\\"\\n\\n Y_gsh = np.zeros(n_tot, dtype='complex128')\\n for ii in xrange(N_L_val):\\n Y_gsh += coef[ii]*X[:, ii]\\n\\n Y_gsh = Y_gsh.real\\n\\n error_gsh = np.abs(Y_gsh - Y)\\n\\n print \\\"\\\\nGSH basis representation errors\\\"\\n print \\\"mean error: %s\\\" % np.mean(error_gsh)\\n print \\\"std of error: %s\\\" % np.std(error_gsh)\\n print \\\"max error: %s\\\" % np.max(error_gsh)\\n\\n \\\"\\\"\\\"Perform the integration for the indicator basis coefficients\\\"\\\"\\\"\\n n_p1_ind = phi1max/ind_bs\\n n_P_ind = phimax/ind_bs\\n n_p2_ind = phi2max/ind_bs\\n\\n ysum = np.zeros((n_p1_ind, n_P_ind, n_p2_ind))\\n ycount = np.zeros((n_p1_ind, n_P_ind, n_p2_ind))\\n\\n N_ind = ysum.size\\n\\n ind_bs_r = ind_bs*np.pi/180.\\n\\n for ii in xrange(np.int64(n_tot)):\\n eset = np.int64(np.floor(euler[ii, :]/ind_bs_r))\\n ysum[eset[0], eset[1], eset[2]] += Y[ii]\\n ycount[eset[0], eset[1], eset[2]] += 1\\n\\n y_integrate = ysum/ycount\\n del ysum, ycount\\n\\n Y_ind = np.zeros(n_tot, dtype='float64')\\n\\n for ii in xrange(np.int64(n_tot)):\\n eset = np.int64(np.floor(euler[ii, :]/ind_bs_r))\\n Y_ind[ii] = y_integrate[eset[0], eset[1], eset[2]]\\n del y_integrate\\n\\n \\\"\\\"\\\"check accuracy of indicator function representation\\\"\\\"\\\"\\n\\n error_ind = np.abs(Y_ind - Y)\\n\\n print \\\"\\\\nindicator basis representation errors\\\"\\n print \\\"mean error: %s\\\" % np.mean(error_ind)\\n print \\\"std of error: %s\\\" % np.std(error_ind)\\n print \\\"max error: %s\\\" % np.max(error_ind)\\n\\n \\\"\\\"\\\" Plot the regression results \\\"\\\"\\\"\\n\\n phi2_u = np.unique(euler[:, 2])\\n\\n ang_sel = euler[:, 2] == phi2_u[np.int64(len(phi2_u)/2.)]\\n\\n plt.figure(figsize=[8, 8])\\n\\n vmin = np.min([Y, Y_gsh, Y_ind])\\n vmax = np.max([Y, Y_gsh, Y_ind])\\n\\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\\n Y[ang_sel], inc)\\n\\n plt.subplot(311)\\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\\n vmin=vmin, vmax=vmax,\\n extent=[0, 2*np.pi, 0, np.pi/2.])\\n plt.colorbar(ax)\\n plt.title(\\\"Reference ODF slice\\\")\\n plt.xlabel(\\\"$\\\\phi1$\\\")\\n plt.ylabel(\\\"$\\\\Phi$\\\")\\n\\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\\n Y_gsh[ang_sel], inc)\\n\\n plt.subplot(312)\\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\\n vmin=vmin, vmax=vmax,\\n extent=[0, 2*np.pi, 0, np.pi/2.])\\n plt.colorbar(ax)\\n plt.title(\\\"ODF slice with %s GSH bases\\\" % N_L_val)\\n plt.xlabel(\\\"$\\\\phi1$\\\")\\n plt.ylabel(\\\"$\\\\Phi$\\\")\\n\\n x1, x2, z = pre_surf(euler[ang_sel, 0], euler[ang_sel, 1],\\n Y_ind[ang_sel], inc)\\n\\n plt.subplot(313)\\n ax = plt.imshow(z.T, interpolation='none', cmap='magma',\\n vmin=vmin, vmax=vmax,\\n extent=[0, 2*np.pi, 0, np.pi/2.])\\n plt.colorbar(ax)\\n plt.title(\\\"ODF slice with %s indicator bases\\\" % N_ind)\\n plt.xlabel(\\\"$\\\\phi1$\\\")\\n plt.ylabel(\\\"$\\\\Phi$\\\")\\n\\n plt.show()\",\n \"def test_get_quad_under_all_float(self):\\n result = get_quadrilateral_type(2, 2, 2, 2, 179.9, .1, 179.9, .1)\\n self.assertEqual(result, 'rhombus')\",\n \"def integral( self ):\\n integral = 0.0\\n for i in range( 1, self.GetN() ):\\n previousPoint = ( ROOT.Double(), ROOT.Double() )\\n thisPoint = ( ROOT.Double(), ROOT.Double() )\\n self.GetPoint( i-1, previousPoint[0], previousPoint[1] )\\n self.GetPoint( i, thisPoint[0], thisPoint[1] )\\n \\n integral += (thisPoint[0]-previousPoint[0]) * (thisPoint[1]+previousPoint[1])/2.0\\n return integral\",\n \"def integrate_range(self, lower, upper):\\n if upper>self.upper:\\n upper=self.upper\\n if lower<self.lower:\\n lower = self.lower\\n\\n i_l = int(np.floor((lower-self.lower)/self._dx))\\n i_u = int(np.floor((upper-self.lower)/self._dx))\\n #print \\\"i_l \\\",i_l,\\\" i_u \\\",i_u\\n total = 0.0\\n for i in range(i_l,i_u):\\n total+= self.y[i]*self._dx\\n return total\",\n \"def _integrate_malmquist(self, malm_pars, q0, q1):\\n return np.sum([p/(i+1.0)*(q1**(i+1.0) - q0**(i+1.0)) for i, p in enumerate(malm_pars)])\",\n \"def add_quad(a, b):\\n s = np.sqrt(np.square(a) + np.square(b))\\n return s\",\n \"def fpga_moving_integrator(samples, integration, math_round=False, extra_bits=0):\\n sreg = deque(np.zeros(integration))\\n result = []\\n acc = 0\\n for sample in samples:\\n acc += sample - sreg.pop()\\n sreg.appendleft(sample)\\n if math_round:\\n value = int(round(acc/integration*2**extra_bits))/2**extra_bits\\n else:\\n value = int(np.floor(acc/integration*2**extra_bits))/2**extra_bits\\n result.append(value)\\n return result\",\n \"def test_hermite_integral(dimensions, specification, size, naive_specification):\\n integral = lambda n, w: w.T @ (n ** 2).prod(axis=1)\\n nodes, weights = Integration(specification, size, seed=0)._build(dimensions)\\n simulated = integral(nodes, weights)\\n np.testing.assert_allclose(simulated, 1, rtol=0, atol=0.01)\\n if naive_specification:\\n naive = integral(*Integration(naive_specification, 10 * weights.size, seed=0)._build(dimensions))\\n np.testing.assert_array_less(np.linalg.norm(simulated - 1), np.linalg.norm(naive - 1))\",\n \"def test_float64(self):\\r\\n start, stop, step = dscalars('start', 'stop', 'step')\\r\\n out = arange(start, stop, step)\\r\\n f = function([start, stop, step], out)\\r\\n\\r\\n assert out.dtype == start.type.dtype\\r\\n arg_vals = [(0, 5, 1), (2, 11, 4), (-5, 1.1, 1.2), (1.3, 2,\\r\\n -2.1), (10, 2, 2)]\\r\\n for arg_v in arg_vals:\\r\\n start_v, stop_v, step_v = arg_v\\r\\n start_v_, stop_v_, step_v_ = numpy.asarray(arg_v,\\r\\n dtype=start.type.dtype)\\r\\n f_val = f(start_v_, stop_v_, step_v_)\\r\\n if config.cast_policy == 'custom':\\r\\n expected_val = numpy.arange(start_v, stop_v, step_v,\\r\\n dtype=start.type.dtype)\\r\\n elif config.cast_policy in ('numpy', 'numpy+floatX'):\\r\\n expected_val = numpy.arange(start_v_, stop_v_, step_v_)\\r\\n else:\\r\\n raise NotImplementedError(config.cast_policy)\\r\\n assert numpy.all(f_val == expected_val)\",\n \"def _integrand(u1,\\n dens_lum, sigma_lum, q_lum,\\n dens_pot, sigma_pot, q_pot,\\n x1, y1, inc, beta, tensor):\\n dens_lum = dens_lum[:, None, None]\\n sigma_lum = sigma_lum[:, None, None]\\n q_lum = q_lum[:, None, None]\\n beta = beta[:, None, None]\\n\\n dens_pot = dens_pot[None, :, None]\\n sigma_pot = sigma_pot[None, :, None]\\n q_pot = q_pot[None, :, None]\\n\\n u = u1[None, None, :]\\n\\n kani = 1./(1 - beta) # Anisotropy ratio b = (sig_R/sig_z)**2\\n ci = np.cos(inc)\\n si = np.sin(inc)\\n si2 = si**2\\n ci2 = ci**2\\n x2 = x1**2\\n y2 = y1**2\\n u2 = u**2\\n\\n s2_lum = sigma_lum**2\\n q2_lum = q_lum**2\\n e2_lum = 1 - q2_lum\\n s2q2_lum = s2_lum*q2_lum\\n\\n s2_pot = sigma_pot**2\\n e2_pot = 1 - q_pot**2\\n\\n # Double summation over (j, k) of eq.(28) for all values of integration variable u.\\n # The triple loop in (j, k, u) is replaced by broadcast Numpy array operations.\\n # The j-index refers to the Gaussians describing the total mass,\\n # from which the potential is derived, while the k-index is used\\n # for the MGE components describing the galaxy stellar luminosity.\\n\\n e2u2_pot = e2_pot*u2\\n a = 0.5*(u2/s2_pot + 1/s2_lum) # equation (29) in C08\\n b = 0.5*(e2u2_pot*u2/(s2_pot*(1 - e2u2_pot)) + e2_lum/s2q2_lum) # equation (30) in C08\\n c = e2_pot - s2q2_lum/s2_pot # equation (22) in C08\\n d = 1 - kani*q2_lum - ((1 - kani)*c + e2_pot*kani)*u2 # equation (23) in C08\\n e = a + b*ci2\\n if tensor == 'xx':\\n f = kani*s2q2_lum + d*((y1*ci*(a+b)/e)**2 + si2/(2*e)) # equation (4) in C12\\n elif tensor == 'yy':\\n f = s2q2_lum*(si2 + kani*ci2) + d*x2*ci2 # equation (5) in C12\\n elif tensor == 'zz':\\n f = s2q2_lum*(ci2 + kani*si2) + d*x2*si2 # z' LOS equation (28) in C08\\n elif tensor == 'xy':\\n f = -d*np.abs(x1*y1)*ci2*(a+b)/e # equation (6) in C12\\n elif tensor == 'xz':\\n f = d*np.abs(x1*y1)*si*ci*(a+b)/e # equation (7) in C12\\n elif tensor == 'yz':\\n f = si*ci*(s2q2_lum*(1 - kani) - d*x2) # equation (8) in C12\\n else:\\n raise RuntimeError('Incorrect TENSOR string')\\n\\n # arr has the dimensions (q_lum.size, q_pot.size, u.size)\\n\\n arr = q_pot*dens_pot*dens_lum*u2*f*np.exp(-a*(x2 + y2*(a + b)/e)) \\\\\\n / ((1. - c*u2)*np.sqrt((1. - e2u2_pot)*e))\\n\\n G = 0.00430237 # (km/s)^2 pc/Msun [6.674e-11 SI units (CODATA-10)]\\n\\n return 4*np.pi**1.5*G*np.sum(arr, axis=(0, 1))\",\n \"def integrate_spectrum(func, xmin, xmax, ndecade=100, intervals=False):\\n is_quantity = False\\n if isinstance(xmin, Quantity):\\n unit = xmin.unit\\n xmin = xmin.value\\n xmax = xmax.value\\n is_quantity = True\\n\\n if np.isscalar(xmin):\\n logmin = np.log10(xmin)\\n logmax = np.log10(xmax)\\n n = (logmax - logmin) * ndecade\\n x = np.logspace(logmin, logmax, n)\\n else:\\n x = np.append(xmin, xmax[-1])\\n\\n if is_quantity:\\n x = x * unit\\n\\n y = func(x)\\n\\n val = _trapz_loglog(y, x, intervals=intervals)\\n\\n return val\",\n \"def integrate_trapz(f, lower, upper, N=1000):\\n a = lower # Lower integration limit\\n b = upper # Upper integration limit\\n w = (b - a) / N # Width of each trapezoid\\n\\n # Area of first and last trapezoids\\n I = 0.5 * f(a) * w + 0.5 * f(b) * w\\n\\n # Area of rest of trapezoids\\n for i in range(1, N):\\n I += f(a + i * w) * w\\n\\n return I, N\",\n \"def integrate(self, lmin, lmax, z, band=1):\\n\\n if not hasattr(self, 'lummean'):\\n self.magmean = np.array([(self.magbins[i]+self.magbins[i+1])/2\\n for i in range(len(self.magbins)-1)])\\n if not hasattr(self, 'zmean'):\\n self.zmean = np.array([(self.zbins[i]+self.zbins[i+1])/2\\n for i in range(len(self.zbins)-1)])\\n\\n if not hasattr(self, 'integ_spline'):\\n self.mv_spline = RectBivariateSpline(self.magmean, self.zmean,\\n self.luminosity_function[:,band,:])\\n\\n uvspl = lambda l : self.mv_spline(l, z)\\n\\n n = quad(uvspl, lmin, lmax)\\n\\n return n[0]\",\n \"def integral(self, pars = None):\\n if pars is None:\\n pars = self.pars_fit\\n return .5 * np.sqrt(2.*np.pi) * pars[0] * (pars[2] + pars[3])\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.5149811\",\n \"0.51459557\",\n \"0.5132584\",\n \"0.5131349\",\n \"0.51298445\",\n \"0.51284605\",\n \"0.5124338\",\n \"0.5118985\",\n \"0.5110952\",\n \"0.50949764\",\n \"0.5094253\",\n \"0.5087884\",\n \"0.5083161\",\n \"0.50768125\",\n \"0.5072326\",\n \"0.50534576\",\n \"0.504804\",\n \"0.50476575\",\n \"0.5040012\",\n \"0.5031167\",\n \"0.50181854\",\n \"0.50177675\",\n \"0.50051194\",\n \"0.49995515\",\n \"0.49792108\",\n \"0.4965449\",\n \"0.49635094\",\n \"0.49625453\",\n \"0.49612108\",\n \"0.49581492\",\n \"0.49562025\",\n \"0.49435624\",\n \"0.49385142\",\n \"0.49210832\",\n \"0.49102265\",\n \"0.49045956\",\n \"0.48989594\",\n \"0.48962423\",\n \"0.48958513\",\n \"0.48953345\",\n \"0.48906755\",\n \"0.48823014\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5866004"},"document_rank":{"kind":"string","value":"11"}}},{"rowIdx":25699,"cells":{"query":{"kind":"string","value":"Runs the unit tests without test coverage."},"document":{"kind":"string","value":"def test():\n nose.run()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _run_ci_test():\n _run_install(False)\n _run_coverage_html(False)\n _run_typecheck_xml(False)\n _run_lint(True)","def main():\n import coverage\n import nose\n import os\n from shutil import rmtree\n rmtree('./covhtml', ignore_errors=True)\n try:\n os.remove('./.coverage')\n except Exception,e:\n pass\n\n # run nose in its own process because the .coverage file isn't written\n # until the process terminates and we need to read it\n nose.run()","def runTest(self):\n unittest.main()\n ChoreTest.clean_up()","def runTests(self):\n \n pass","def RunUnitTests():\n if FLAGS.test_targets:\n tests = FLAGS.test_targets\n else:\n tests = shell_interfaces.GetStdout(\n 'bazel query kind(\"cc_test\", ...)').split()\n\n # Run coverage, joining all data into one file.\n subprocess.check_call(['bazel', 'coverage', '--instrument_test_targets',\n '--experimental_cc_coverage',\n '--combined_report=lcov',\n ('--coverage_report_generator=@bazel_tools//tools/tes'\n 't/CoverageOutputGenerator/java/com/google/devtools/'\n 'coverageoutputgenerator:Main')] + tests)","def run(self):\n if self.all:\n cmd = self.apply_options(self.test_all_cmd)\n self.call_and_exit(cmd)\n else:\n cmds = (self.apply_options(self.unit_test_cmd, (\"coverage\",)),)\n if self.coverage:\n cmds += (self.apply_options(self.coverage_cmd),)\n self.call_in_sequence(cmds)","def main():\n run_test_all()","def test():\n with lcd(BASEDIR):\n local('virtenv/bin/coverage run runtests.py -v2')\n local('virtenv/bin/coverage report -m')","def run(self):\n cmd = 'coverage run setup.py test && coverage report -m'\n check_call(cmd, shell=True)","def run_tests():\n testfiles = ['tests.test_overall']\n exclude = ['__init__.py', 'test_overall.py']\n for t in glob(pjoin('tests', '*.py')):\n if True not in [t.endswith(ex) for ex in exclude]:\n if basename(t).startswith('test_'):\n testfiles.append('tests.%s' % splitext(basename(t))[0])\n\n suites = []\n for file in testfiles:\n __import__(file)\n suites.append(sys.modules[file].suite)\n\n tests = unittest.TestSuite(suites)\n runner = unittest.TextTestRunner(verbosity=2)\n\n # Disable logging output\n logging.basicConfig(level=100)\n logging.disable(100)\n\n result = runner.run(tests)\n return result","def __main() :\n launchTests()","def test_dummy_test():\n pass","def unitary_test():","def test_single_test_case():\n pass","def tests():\n api.local('nosetests')","def run_tests(self):\n raise NotImplementedError","def runtests(ctx):\n run('pytest -s tests', pty=pty_available)\n run('flake8 --ignore E265,E266,E501 --exclude src, lib', pty=pty_available)","def spec_tests():\n pass","def runalltests():\n doctest.testmod()","def run_all_unit_tests(cls):\n suites_list = []\n for test_class in cls.TESTS:\n suite = unittest.TestLoader().loadTestsFromTestCase(test_class)\n suites_list.append(suite)\n result = unittest.TextTestRunner().run(unittest.TestSuite(suites_list))\n if not result.wasSuccessful() or result.errors:\n raise Exception(result)","def main():\n fix_sys_path()\n result = unittest.TextTestRunner(verbosity=2).run(createTestSuite())\n\n if result.testsRun != EXPECTED_TEST_COUNT:\n raise Exception(\n 'Expected %s tests to be run, not %s.' % (EXPECTED_TEST_COUNT, result.testsRun))\n\n if len(result.errors) != 0 or len(result.failures) != 0:\n raise Exception(\n \"Functional test suite failed: %s errors, %s failures of %s tests run.\" % (\n len(result.errors), len(result.failures), result.testsRun))","def test():\n import unittest\n\n tests = unittest.TestLoader().discover(\"tests\")\n unittest.TextTestRunner(verbosity=2).run(tests)","def _run_ci_integration_test():\n _run_install(False)\n _run_integration_tests_on_github(False)","def runTest(self):\n\t\tself.setUp()\n\t\tself.test_postopProgramming1()","def runtests():\n #- Load all TestCase classes from desistar/test/test_*.py\n tests = desistar_test_suite()\n #- Run them\n unittest.TextTestRunner(verbosity=2).run(tests)","def run_tests(self):\n import nose\n from pocketlint.formatcheck import main as pocket_main\n\n nose_args = ['nosetests']\n if self.verbose:\n nose_args.append('-v')\n else:\n nose_args.append('-q')\n\n module = self.test_suite\n if self.test_module:\n module = self.test_module\n\n nose_args.extend([\n '--with-coverage',\n '--cover-package=' + module,\n '--cover-erase',\n '--cover-test',\n module.replace('.', '/'),\n ])\n\n pocket_args = [\n 'README.rst',\n 'release-notes.rst',\n 'setup.py',\n ]\n for root, dirs, files in os.walk('chevah/keycert', topdown=False):\n for name in files:\n pocket_args.append(os.path.join(root, name))\n\n nose_code = nose.run(argv=nose_args)\n if nose_code:\n nose_code = 0\n else:\n nose_code = 1\n\n pocket_code = pocket_main(pocket_args)\n if not pocket_code:\n print('Linter OK')\n\n coverage_args = [\n 'report',\n '--include=chevah/keycert/tests/*',\n '--fail-under=100',\n ]\n covergate_code = load_entry_point(\n 'coverage', 'console_scripts', 'coverage')(argv=coverage_args)\n if not covergate_code:\n print('Tests coverage OK')\n\n sys.exit(pocket_code or nose_code or covergate_code)","def tests():","def test(coverage):\n print('success')\n pass","def runAll():\n\n loader = unittest.TestLoader()\n test_dir = pkg_resources.resource_filename('frvcpy.test','.')\n suite = loader.discover(test_dir)\n\n runner = unittest.TextTestRunner(verbosity=2)\n runner.run(suite)","def run_main(): # pragma: no cover\n RunTestsCLI.run()","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def run_tests(self):\n\n # log\n self.logger.debug('\\n\\nExecute test methods:\\n-----------------------------')\n\n # test methods start here\n # ------------------------------------------------------------------\n # ------------------------------------------------------------------\n\n # dummy_method\n self.dummy_method()\n\n # ------------------------------------------------------------------\n # ------------------------------------------------------------------\n # test methods end here\n\n # log\n self.logger.debug('\\n\\n-----------------------------\\nFinished test methods.')","def run_all_tests(self) -> None:\n self.run_trt_precision_tests()\n logging.info(\"Check analysis result at: %s\", self._output_dir)","def test():\r\n import unittest\r\n tests=unittest.TestLoader().discover('tests')\r\n unittest.TextTestRunner(verbosity=2).run(tests)","def run_tests(virtual_env):\n signal.signal(signal.SIGINT, signal.SIG_IGN)\n args = [\n 'python',\n 'setup.py',\n 'nosetests',\n '--with-coverage',\n '--with-xunit',\n ]\n subprocess.call(args, cwd=abspath(join(HOLLAND_ROOT, 'holland-core')), env=virtual_env)\n subprocess.call(['coverage', 'xml'], cwd=abspath(join(HOLLAND_ROOT, 'holland-core')), env=virtual_env)\n for plugin_dir in open(join(HOLLAND_ROOT, 'plugins', 'ACTIVE')):\n plugin_dir = plugin_dir.rstrip()\n plugin_path = join(HOLLAND_ROOT, 'plugins', plugin_dir)\n subprocess.call(args, cwd=plugin_path, env=virtual_env)\n subprocess.call(['coverage', 'xml'], cwd=plugin_path, env=virtual_env)\n for addon_dir in open(join(HOLLAND_ROOT, 'addons', 'ACTIVE')):\n addon_dir = addon_dir.rstrip()\n addon_path = join(HOLLAND_ROOT, 'addons', addon_dir)\n subprocess.call(args, cwd=addon_path, env=virtual_env)\n subprocess.call(['coverage', 'xml'], cwd=plugin_path, env=virtual_env)\n #return subprocess.call(args, env=virtual_env)","def test():\n import unittest\n tests = unittest \n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\r\n import unittest\r\n tests = unittest.TestLoader().discover('tests')\r\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\r\n import unittest\r\n tests = unittest.TestLoader().discover('tests')\r\n unittest.TextTestRunner(verbosity=2).run(tests)","def runTest(self):\n self.setUp()\n self.test_ProstateReporting1()","def test():\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def runtest(self):","def run_tests():\n test_command = \"pytest -s \" + os.path.join(root_path, \"cases\", \"test_cases.py::TestCases::test_cases\") + \" --html=\" + os.path.join(root_path, \"reports\", \"qa_testing_report.html\")\n\n subprocess.run(test_command, shell=True)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n\n tests = unittest.TestLoader().discover(\"tests\")\n unittest.TextTestRunner(verbosity=2).run(tests)","def test():\n import unittest\n\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)","def coverage():\n print(\"Coverage tests always re-run\")\n with safe_cd(SRC):\n my_env = config_pythonpath()\n # You will need something like this in pytest.ini\n # By default, pytest is VERY restrictive in the file names it will match.\n #\n # [pytest]\n # DJANGO_SETTINGS_MODULE = core.settings\n # python_files = tests.py test_*.py *_tests.py test*_*.py *_test*.py\n if not os.path.exists(\"pytest.ini\") and IS_DJANGO:\n print(\n \"pytest.ini MUST exist for Django test detection or too few tests are found.\"\n )\n exit(-1)\n return\n\n my_env = config_pythonpath()\n command = \"{0} py.test {1} --cov={2} --cov-report html:coverage --cov-fail-under 55 --verbose\".format(\n PIPENV, \"test\", PROJECT_NAME\n )\n execute_with_environment(command, my_env)","def runTest(self):\r\n self.setUp()","def runTest(self):\n self.setUp()\n self.test_NeuroPath1()","def test():\n for cmd in [\n \"pytest --verbose --cov pike/ --cov-report term --cov-report html tests/\",\n ]:\n _run_in_venv(shlex.split(cmd))\n for linter in [[\"black\", \"--check\"], [\"flake8\"], [\"isort\", \"--check\"]]:\n _run_in_venv(linter + TEST_FILES)\n\n _run_in_venv(\n [\"mypy\", \"pike/\", \"tests/\", \"setup.py\", \"pikefile.py\", \"--show-error-codes\"]\n )\n _run_in_venv([\"mypy\", \"examples/\"])\n _run_in_venv([\"bandit\", \"-r\", \"pike/\"])","def test():\n import unittest\n tests = unittest.TestLoader().discover(tests)\n unittest.TextTestRunner(verbosity=2).run(tests)","def run_test_coverage(self, build=False):\n\n # print('Running unit tests for package %s' % package)\n if self.is_metapackage:\n self.out = 'This is a metapackage'\n return 0\n\n if not self.has_test:\n self.out = 'No tests defined on CMakeLists.txt'\n return 0\n\n if build:\n self.build_for_coverage() \n\n # Capture initial zero coverage data\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --directory build --zerocounters')\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --capture --initial --directory build/' + self.name + ' --output-file build/lcov.base')\n\n # Run tests with coverage flags\n extra_parms = '--no-deps --cmake-args -DCMAKE_CXX_FLAGS=\"-g -O0 -Wall -fprofile-arcs -ftest-coverage\" -DCMAKE_EXE_LINKER_FLAGS=\"-fprofile-arcs -ftest-coverage\"'\n cmd = ['catkin', 'run_tests', self.name]\n cmd.extend(shlex.split(extra_parms))\n\n process = subprocess.Popen(cmd,\n stdout=subprocess.PIPE, \n stderr=subprocess.PIPE,\n universal_newlines=True)\n\n self.out , self.err = process.communicate()\n\n self.setSummary(self.get_test_summary())\n self.setExecutionStatus(process.returncode)\n\n if process.returncode != 0:\n return process.returncode\n\n # Capture coverage data after running tests\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --no-checksum --directory build/' + self.name + ' --capture --output-file build/lcov.info')\n\n # Add baseline counters\n out, err = self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --add-tracefile build/lcov.base --add-tracefile build/lcov.info --output-file build/lcov.total')\n\n # Remove coverage data for a particular set of files from the tracefile\n out, err = self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --remove build/lcov.total /usr* /opt* */test/* */CMakeFiles/* */build/* --output-file build/lcov.total.cleaned')\n \n # Extract line coverage from output\n if 'lines......:' in out:\n self.coverage = float(out.split('lines......: ')[1].split('%')[0])\n else:\n self.coverage = 0\n\n return 0","def test_nothing(self):","def test_dummy():","def unittest():\n from a6test import test_all\n test_all()","def _run_local_tests(self, *args, **kwargs):\n pass","def main():\n vunit = vunit_pkg.VUnit.from_argv()\n vunit = map_sources(vunit)\n run_tests(vunit)","def startTestRun(self, event):\n self.prof = cProfile.Profile()\n event.executeTests = self.prof.runcall","def runTest(self):\n self.setUp()\n self.test_FiberDistance1()","def runAllTests():\n\tttr = unittest.TextTestRunner(verbosity=3).run(suite())\n\tnTests = ttr.testsRun + len(ttr.skipped)\n\tprint(\"Report:\")\n\tprint(\"\\t\" + str(len(ttr.failures)) + \"/\" + str(nTests) + \" failed\")\n\tprint(\"\\t\" + str(len(ttr.errors)) + \"/\" + str(nTests) + \" errors\")\n\tprint(\"\\t\" + str(len(ttr.skipped)) + \"/\" + str(nTests) + \" skipped\")","def test(coverage=False):\n COV = True\n if COV:\n import coverage\n cov = coverage.coverage(branch=True, include='app/*')\n cov.start()\n\n import unittest\n # tests = unittest.TestLoader().discover('testing_tests')\n tests = unittest.TestLoader().discover('tests')\n\n unittest.TextTestRunner(verbosity=2).run(tests)\n if COV:\n cov.stop()\n cov.save()\n print('Coverage Summary:')\n cov.report()\n basedir = os.path.abspath(os.path.dirname(__file__))\n covdir = os.path.join(basedir, 'tmp/coverage')\n cov.html_report(directory=covdir)\n print('HTML version: file://%s/index.html' % covdir)\n cov.erase()","def test(cline):\n print(\"Running unit tests.\")\n cline.run(\"TF_CPP_MIN_LOG_LEVEL=3 python3 -m unittest\")","def tests(context):\n black(context)\n isort(context)\n flake8(context)\n pylint(context)\n yamllint(context)\n pydocstyle(context)\n bandit(context)\n pytest(context)\n\n print(\"All tests have passed!\")","def run_all_tests():\n remove_dbs()\n run_training_tests()\n run_custom_training_tests()\n run_training_save_tests()\n run_validation_tests()\n run_feature_extraction_tests()","def test():\n import unittest\n import tests\n tests = unittest.TestLoader().discover('tests', pattern='*tests.py')\n unittest.TextTestRunner(verbosity=2).run(tests)","def coverage(ctx):\n ctx.run(\"coverage run --source {PROJECT_NAME} -m pytest\".format(PROJECT_NAME=PROJECT_NAME))\n ctx.run(\"coverage report -m\")\n ctx.run(\"coverage html\")","def collectTests(self, global_ctx):\n pass","def run_tests(self):\n # Charm does not defer hooks so that test is not included.\n # Trigger a package change which requires a restart\n self.run_package_change_test(\n 'ovn-central',\n 'ovn-central')","def run_tests():\n \n test_constructor_positive()\n test_constructor_negative()\n test_game_move_positive()\n test_game_move_negative()\n test_game_move_edge()\n print(\"Congratulations ! You passed all the game test cases.\")","def main():\n try:\n unittest.main(testLoader=BetterLoader(), defaultTest='suite')\n except Exception:\n import sys\n import traceback\n traceback.print_exc()\n sys.exit(1)","def task_coverage():\n return {\n 'actions': ['py.test --cov nikola --cov-report term-missing tests/'],\n 'verbosity': 2,\n }","def actionRunUnitTests():\n UnitTestRunner.init()\n \n for target in Settings.targets:\n for platform in Settings.targetPlatforms:\n for cpu in Settings.targetCPUs:\n for configuration in Settings.targetConfigurations:\n if not Summary.checkIfActionFailed(ACTION_BUILD, target, platform, cpu, configuration):\n Logger.printStartActionMessage('Running unit tests for ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration, ColoredFormatter.YELLOW)\n result = UnitTestRunner.run(target, platform, cpu, configuration)\n Summary.addSummary(ACTION_RUN_UNITTESTS, target, platform, cpu, configuration, result, UnitTestRunner.executionTime)\n if result != NO_ERROR:\n Logger.printEndActionMessage('Failed to execute unit tests!')\n else:\n Logger.printEndActionMessage('Executed all unit tests')","def run_test(self):\n raise NotImplementedError","def main():\n unittest.main(exit=False, verbosity=2)\n return 0","def runTest(self):\n self.setUp()\n self.test_Analytics1()","def cov():\n tests = unittest.TestLoader().discover('project/tests')\n result = unittest.TextTestRunner(verbosity=2).run(tests)\n if result.wasSuccessful():\n COV.stop()\n COV.save()\n print('Coverage Summary:')\n COV.report()\n COV.html_report()\n COV.erase()\n return 0\n return 1","def runTest(self):\n self.setUp()\n self.test_FiducialTransform1()","def cov():\n cov = coverage.coverage(branch=True, include='project/*')\n cov.start()\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)\n cov.stop()\n cov.save()\n print('Coverage Summary:')\n cov.report()\n basedir = os.path.abspath(os.path.dirname(__file__))\n covdir = os.path.join(basedir, 'tmp/coverage')\n cov.html_report(directory=covdir)\n print('HTML version: file://%s/index.html' % covdir)\n cov.erase()","def main():\n run_test_summary1a()\n run_test_summary1c()\n run_test_summary1c()","def test_basic_execution(self):","def cov():\n cov = coverage.coverage(\n branch=True,\n include='project/*',\n omit=\"*/__init__.py\"\n )\n cov.start()\n tests = unittest.TestLoader().discover('tests')\n unittest.TextTestRunner(verbosity=2).run(tests)\n cov.stop()\n cov.save()\n print 'Coverage Summary:'\n cov.report()\n basedir = os.path.abspath(os.path.dirname(__file__))\n covdir = os.path.join(basedir, 'tmp/coverage')\n cov.html_report(directory=covdir)\n print('HTML version: file://%s/index.html' % covdir)\n cov.erase()","def runTest(self):\n self.setUp()\n self.test_SegmentDicom1()","def run():\n\tsubsuite_list = []\n\tfor _, modname, _ in pkgutil.iter_modules(test.__path__):\n\t\tif modname.startswith(\"test_\"):\n\t\t\tmodule = importlib.import_module('test.' + modname)\n\t\t\tsubsuite = unittest.TestLoader().loadTestsFromModule(module)\n\t\t\tsubsuite_list.append(subsuite)\n\tsuite = unittest.TestSuite(subsuite_list)\n\n\tprint(\"Testing:\\n\")\n\tunittest.TextTestRunner(verbosity=2).run(suite)","def test_script(self) -> None:\n main()","def test():\n tests = unittest.TestLoader().discover('project/tests', pattern='test*.py')\n result = unittest.TextTestRunner(verbosity=2).run(tests)\n if result.wasSuccessful():\n return 0\n sys.exit(result)","def test_all_no_class(self):"],"string":"[\n \"def _run_ci_test():\\n _run_install(False)\\n _run_coverage_html(False)\\n _run_typecheck_xml(False)\\n _run_lint(True)\",\n \"def main():\\n import coverage\\n import nose\\n import os\\n from shutil import rmtree\\n rmtree('./covhtml', ignore_errors=True)\\n try:\\n os.remove('./.coverage')\\n except Exception,e:\\n pass\\n\\n # run nose in its own process because the .coverage file isn't written\\n # until the process terminates and we need to read it\\n nose.run()\",\n \"def runTest(self):\\n unittest.main()\\n ChoreTest.clean_up()\",\n \"def runTests(self):\\n \\n pass\",\n \"def RunUnitTests():\\n if FLAGS.test_targets:\\n tests = FLAGS.test_targets\\n else:\\n tests = shell_interfaces.GetStdout(\\n 'bazel query kind(\\\"cc_test\\\", ...)').split()\\n\\n # Run coverage, joining all data into one file.\\n subprocess.check_call(['bazel', 'coverage', '--instrument_test_targets',\\n '--experimental_cc_coverage',\\n '--combined_report=lcov',\\n ('--coverage_report_generator=@bazel_tools//tools/tes'\\n 't/CoverageOutputGenerator/java/com/google/devtools/'\\n 'coverageoutputgenerator:Main')] + tests)\",\n \"def run(self):\\n if self.all:\\n cmd = self.apply_options(self.test_all_cmd)\\n self.call_and_exit(cmd)\\n else:\\n cmds = (self.apply_options(self.unit_test_cmd, (\\\"coverage\\\",)),)\\n if self.coverage:\\n cmds += (self.apply_options(self.coverage_cmd),)\\n self.call_in_sequence(cmds)\",\n \"def main():\\n run_test_all()\",\n \"def test():\\n with lcd(BASEDIR):\\n local('virtenv/bin/coverage run runtests.py -v2')\\n local('virtenv/bin/coverage report -m')\",\n \"def run(self):\\n cmd = 'coverage run setup.py test && coverage report -m'\\n check_call(cmd, shell=True)\",\n \"def run_tests():\\n testfiles = ['tests.test_overall']\\n exclude = ['__init__.py', 'test_overall.py']\\n for t in glob(pjoin('tests', '*.py')):\\n if True not in [t.endswith(ex) for ex in exclude]:\\n if basename(t).startswith('test_'):\\n testfiles.append('tests.%s' % splitext(basename(t))[0])\\n\\n suites = []\\n for file in testfiles:\\n __import__(file)\\n suites.append(sys.modules[file].suite)\\n\\n tests = unittest.TestSuite(suites)\\n runner = unittest.TextTestRunner(verbosity=2)\\n\\n # Disable logging output\\n logging.basicConfig(level=100)\\n logging.disable(100)\\n\\n result = runner.run(tests)\\n return result\",\n \"def __main() :\\n launchTests()\",\n \"def test_dummy_test():\\n pass\",\n \"def unitary_test():\",\n \"def test_single_test_case():\\n pass\",\n \"def tests():\\n api.local('nosetests')\",\n \"def run_tests(self):\\n raise NotImplementedError\",\n \"def runtests(ctx):\\n run('pytest -s tests', pty=pty_available)\\n run('flake8 --ignore E265,E266,E501 --exclude src, lib', pty=pty_available)\",\n \"def spec_tests():\\n pass\",\n \"def runalltests():\\n doctest.testmod()\",\n \"def run_all_unit_tests(cls):\\n suites_list = []\\n for test_class in cls.TESTS:\\n suite = unittest.TestLoader().loadTestsFromTestCase(test_class)\\n suites_list.append(suite)\\n result = unittest.TextTestRunner().run(unittest.TestSuite(suites_list))\\n if not result.wasSuccessful() or result.errors:\\n raise Exception(result)\",\n \"def main():\\n fix_sys_path()\\n result = unittest.TextTestRunner(verbosity=2).run(createTestSuite())\\n\\n if result.testsRun != EXPECTED_TEST_COUNT:\\n raise Exception(\\n 'Expected %s tests to be run, not %s.' % (EXPECTED_TEST_COUNT, result.testsRun))\\n\\n if len(result.errors) != 0 or len(result.failures) != 0:\\n raise Exception(\\n \\\"Functional test suite failed: %s errors, %s failures of %s tests run.\\\" % (\\n len(result.errors), len(result.failures), result.testsRun))\",\n \"def test():\\n import unittest\\n\\n tests = unittest.TestLoader().discover(\\\"tests\\\")\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def _run_ci_integration_test():\\n _run_install(False)\\n _run_integration_tests_on_github(False)\",\n \"def runTest(self):\\n\\t\\tself.setUp()\\n\\t\\tself.test_postopProgramming1()\",\n \"def runtests():\\n #- Load all TestCase classes from desistar/test/test_*.py\\n tests = desistar_test_suite()\\n #- Run them\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def run_tests(self):\\n import nose\\n from pocketlint.formatcheck import main as pocket_main\\n\\n nose_args = ['nosetests']\\n if self.verbose:\\n nose_args.append('-v')\\n else:\\n nose_args.append('-q')\\n\\n module = self.test_suite\\n if self.test_module:\\n module = self.test_module\\n\\n nose_args.extend([\\n '--with-coverage',\\n '--cover-package=' + module,\\n '--cover-erase',\\n '--cover-test',\\n module.replace('.', '/'),\\n ])\\n\\n pocket_args = [\\n 'README.rst',\\n 'release-notes.rst',\\n 'setup.py',\\n ]\\n for root, dirs, files in os.walk('chevah/keycert', topdown=False):\\n for name in files:\\n pocket_args.append(os.path.join(root, name))\\n\\n nose_code = nose.run(argv=nose_args)\\n if nose_code:\\n nose_code = 0\\n else:\\n nose_code = 1\\n\\n pocket_code = pocket_main(pocket_args)\\n if not pocket_code:\\n print('Linter OK')\\n\\n coverage_args = [\\n 'report',\\n '--include=chevah/keycert/tests/*',\\n '--fail-under=100',\\n ]\\n covergate_code = load_entry_point(\\n 'coverage', 'console_scripts', 'coverage')(argv=coverage_args)\\n if not covergate_code:\\n print('Tests coverage OK')\\n\\n sys.exit(pocket_code or nose_code or covergate_code)\",\n \"def tests():\",\n \"def test(coverage):\\n print('success')\\n pass\",\n \"def runAll():\\n\\n loader = unittest.TestLoader()\\n test_dir = pkg_resources.resource_filename('frvcpy.test','.')\\n suite = loader.discover(test_dir)\\n\\n runner = unittest.TextTestRunner(verbosity=2)\\n runner.run(suite)\",\n \"def run_main(): # pragma: no cover\\n RunTestsCLI.run()\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def run_tests(self):\\n\\n # log\\n self.logger.debug('\\\\n\\\\nExecute test methods:\\\\n-----------------------------')\\n\\n # test methods start here\\n # ------------------------------------------------------------------\\n # ------------------------------------------------------------------\\n\\n # dummy_method\\n self.dummy_method()\\n\\n # ------------------------------------------------------------------\\n # ------------------------------------------------------------------\\n # test methods end here\\n\\n # log\\n self.logger.debug('\\\\n\\\\n-----------------------------\\\\nFinished test methods.')\",\n \"def run_all_tests(self) -> None:\\n self.run_trt_precision_tests()\\n logging.info(\\\"Check analysis result at: %s\\\", self._output_dir)\",\n \"def test():\\r\\n import unittest\\r\\n tests=unittest.TestLoader().discover('tests')\\r\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def run_tests(virtual_env):\\n signal.signal(signal.SIGINT, signal.SIG_IGN)\\n args = [\\n 'python',\\n 'setup.py',\\n 'nosetests',\\n '--with-coverage',\\n '--with-xunit',\\n ]\\n subprocess.call(args, cwd=abspath(join(HOLLAND_ROOT, 'holland-core')), env=virtual_env)\\n subprocess.call(['coverage', 'xml'], cwd=abspath(join(HOLLAND_ROOT, 'holland-core')), env=virtual_env)\\n for plugin_dir in open(join(HOLLAND_ROOT, 'plugins', 'ACTIVE')):\\n plugin_dir = plugin_dir.rstrip()\\n plugin_path = join(HOLLAND_ROOT, 'plugins', plugin_dir)\\n subprocess.call(args, cwd=plugin_path, env=virtual_env)\\n subprocess.call(['coverage', 'xml'], cwd=plugin_path, env=virtual_env)\\n for addon_dir in open(join(HOLLAND_ROOT, 'addons', 'ACTIVE')):\\n addon_dir = addon_dir.rstrip()\\n addon_path = join(HOLLAND_ROOT, 'addons', addon_dir)\\n subprocess.call(args, cwd=addon_path, env=virtual_env)\\n subprocess.call(['coverage', 'xml'], cwd=plugin_path, env=virtual_env)\\n #return subprocess.call(args, env=virtual_env)\",\n \"def test():\\n import unittest\\n tests = unittest \\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\r\\n import unittest\\r\\n tests = unittest.TestLoader().discover('tests')\\r\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\r\\n import unittest\\r\\n tests = unittest.TestLoader().discover('tests')\\r\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def runTest(self):\\n self.setUp()\\n self.test_ProstateReporting1()\",\n \"def test():\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def runtest(self):\",\n \"def run_tests():\\n test_command = \\\"pytest -s \\\" + os.path.join(root_path, \\\"cases\\\", \\\"test_cases.py::TestCases::test_cases\\\") + \\\" --html=\\\" + os.path.join(root_path, \\\"reports\\\", \\\"qa_testing_report.html\\\")\\n\\n subprocess.run(test_command, shell=True)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n\\n tests = unittest.TestLoader().discover(\\\"tests\\\")\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def test():\\n import unittest\\n\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def coverage():\\n print(\\\"Coverage tests always re-run\\\")\\n with safe_cd(SRC):\\n my_env = config_pythonpath()\\n # You will need something like this in pytest.ini\\n # By default, pytest is VERY restrictive in the file names it will match.\\n #\\n # [pytest]\\n # DJANGO_SETTINGS_MODULE = core.settings\\n # python_files = tests.py test_*.py *_tests.py test*_*.py *_test*.py\\n if not os.path.exists(\\\"pytest.ini\\\") and IS_DJANGO:\\n print(\\n \\\"pytest.ini MUST exist for Django test detection or too few tests are found.\\\"\\n )\\n exit(-1)\\n return\\n\\n my_env = config_pythonpath()\\n command = \\\"{0} py.test {1} --cov={2} --cov-report html:coverage --cov-fail-under 55 --verbose\\\".format(\\n PIPENV, \\\"test\\\", PROJECT_NAME\\n )\\n execute_with_environment(command, my_env)\",\n \"def runTest(self):\\r\\n self.setUp()\",\n \"def runTest(self):\\n self.setUp()\\n self.test_NeuroPath1()\",\n \"def test():\\n for cmd in [\\n \\\"pytest --verbose --cov pike/ --cov-report term --cov-report html tests/\\\",\\n ]:\\n _run_in_venv(shlex.split(cmd))\\n for linter in [[\\\"black\\\", \\\"--check\\\"], [\\\"flake8\\\"], [\\\"isort\\\", \\\"--check\\\"]]:\\n _run_in_venv(linter + TEST_FILES)\\n\\n _run_in_venv(\\n [\\\"mypy\\\", \\\"pike/\\\", \\\"tests/\\\", \\\"setup.py\\\", \\\"pikefile.py\\\", \\\"--show-error-codes\\\"]\\n )\\n _run_in_venv([\\\"mypy\\\", \\\"examples/\\\"])\\n _run_in_venv([\\\"bandit\\\", \\\"-r\\\", \\\"pike/\\\"])\",\n \"def test():\\n import unittest\\n tests = unittest.TestLoader().discover(tests)\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def run_test_coverage(self, build=False):\\n\\n # print('Running unit tests for package %s' % package)\\n if self.is_metapackage:\\n self.out = 'This is a metapackage'\\n return 0\\n\\n if not self.has_test:\\n self.out = 'No tests defined on CMakeLists.txt'\\n return 0\\n\\n if build:\\n self.build_for_coverage() \\n\\n # Capture initial zero coverage data\\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --directory build --zerocounters')\\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --capture --initial --directory build/' + self.name + ' --output-file build/lcov.base')\\n\\n # Run tests with coverage flags\\n extra_parms = '--no-deps --cmake-args -DCMAKE_CXX_FLAGS=\\\"-g -O0 -Wall -fprofile-arcs -ftest-coverage\\\" -DCMAKE_EXE_LINKER_FLAGS=\\\"-fprofile-arcs -ftest-coverage\\\"'\\n cmd = ['catkin', 'run_tests', self.name]\\n cmd.extend(shlex.split(extra_parms))\\n\\n process = subprocess.Popen(cmd,\\n stdout=subprocess.PIPE, \\n stderr=subprocess.PIPE,\\n universal_newlines=True)\\n\\n self.out , self.err = process.communicate()\\n\\n self.setSummary(self.get_test_summary())\\n self.setExecutionStatus(process.returncode)\\n\\n if process.returncode != 0:\\n return process.returncode\\n\\n # Capture coverage data after running tests\\n self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --no-checksum --directory build/' + self.name + ' --capture --output-file build/lcov.info')\\n\\n # Add baseline counters\\n out, err = self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --add-tracefile build/lcov.base --add-tracefile build/lcov.info --output-file build/lcov.total')\\n\\n # Remove coverage data for a particular set of files from the tracefile\\n out, err = self.run_lcov_cmd('--rc lcov_branch_coverage=' + self.use_branch_coverage + ' --remove build/lcov.total /usr* /opt* */test/* */CMakeFiles/* */build/* --output-file build/lcov.total.cleaned')\\n \\n # Extract line coverage from output\\n if 'lines......:' in out:\\n self.coverage = float(out.split('lines......: ')[1].split('%')[0])\\n else:\\n self.coverage = 0\\n\\n return 0\",\n \"def test_nothing(self):\",\n \"def test_dummy():\",\n \"def unittest():\\n from a6test import test_all\\n test_all()\",\n \"def _run_local_tests(self, *args, **kwargs):\\n pass\",\n \"def main():\\n vunit = vunit_pkg.VUnit.from_argv()\\n vunit = map_sources(vunit)\\n run_tests(vunit)\",\n \"def startTestRun(self, event):\\n self.prof = cProfile.Profile()\\n event.executeTests = self.prof.runcall\",\n \"def runTest(self):\\n self.setUp()\\n self.test_FiberDistance1()\",\n \"def runAllTests():\\n\\tttr = unittest.TextTestRunner(verbosity=3).run(suite())\\n\\tnTests = ttr.testsRun + len(ttr.skipped)\\n\\tprint(\\\"Report:\\\")\\n\\tprint(\\\"\\\\t\\\" + str(len(ttr.failures)) + \\\"/\\\" + str(nTests) + \\\" failed\\\")\\n\\tprint(\\\"\\\\t\\\" + str(len(ttr.errors)) + \\\"/\\\" + str(nTests) + \\\" errors\\\")\\n\\tprint(\\\"\\\\t\\\" + str(len(ttr.skipped)) + \\\"/\\\" + str(nTests) + \\\" skipped\\\")\",\n \"def test(coverage=False):\\n COV = True\\n if COV:\\n import coverage\\n cov = coverage.coverage(branch=True, include='app/*')\\n cov.start()\\n\\n import unittest\\n # tests = unittest.TestLoader().discover('testing_tests')\\n tests = unittest.TestLoader().discover('tests')\\n\\n unittest.TextTestRunner(verbosity=2).run(tests)\\n if COV:\\n cov.stop()\\n cov.save()\\n print('Coverage Summary:')\\n cov.report()\\n basedir = os.path.abspath(os.path.dirname(__file__))\\n covdir = os.path.join(basedir, 'tmp/coverage')\\n cov.html_report(directory=covdir)\\n print('HTML version: file://%s/index.html' % covdir)\\n cov.erase()\",\n \"def test(cline):\\n print(\\\"Running unit tests.\\\")\\n cline.run(\\\"TF_CPP_MIN_LOG_LEVEL=3 python3 -m unittest\\\")\",\n \"def tests(context):\\n black(context)\\n isort(context)\\n flake8(context)\\n pylint(context)\\n yamllint(context)\\n pydocstyle(context)\\n bandit(context)\\n pytest(context)\\n\\n print(\\\"All tests have passed!\\\")\",\n \"def run_all_tests():\\n remove_dbs()\\n run_training_tests()\\n run_custom_training_tests()\\n run_training_save_tests()\\n run_validation_tests()\\n run_feature_extraction_tests()\",\n \"def test():\\n import unittest\\n import tests\\n tests = unittest.TestLoader().discover('tests', pattern='*tests.py')\\n unittest.TextTestRunner(verbosity=2).run(tests)\",\n \"def coverage(ctx):\\n ctx.run(\\\"coverage run --source {PROJECT_NAME} -m pytest\\\".format(PROJECT_NAME=PROJECT_NAME))\\n ctx.run(\\\"coverage report -m\\\")\\n ctx.run(\\\"coverage html\\\")\",\n \"def collectTests(self, global_ctx):\\n pass\",\n \"def run_tests(self):\\n # Charm does not defer hooks so that test is not included.\\n # Trigger a package change which requires a restart\\n self.run_package_change_test(\\n 'ovn-central',\\n 'ovn-central')\",\n \"def run_tests():\\n \\n test_constructor_positive()\\n test_constructor_negative()\\n test_game_move_positive()\\n test_game_move_negative()\\n test_game_move_edge()\\n print(\\\"Congratulations ! You passed all the game test cases.\\\")\",\n \"def main():\\n try:\\n unittest.main(testLoader=BetterLoader(), defaultTest='suite')\\n except Exception:\\n import sys\\n import traceback\\n traceback.print_exc()\\n sys.exit(1)\",\n \"def task_coverage():\\n return {\\n 'actions': ['py.test --cov nikola --cov-report term-missing tests/'],\\n 'verbosity': 2,\\n }\",\n \"def actionRunUnitTests():\\n UnitTestRunner.init()\\n \\n for target in Settings.targets:\\n for platform in Settings.targetPlatforms:\\n for cpu in Settings.targetCPUs:\\n for configuration in Settings.targetConfigurations:\\n if not Summary.checkIfActionFailed(ACTION_BUILD, target, platform, cpu, configuration):\\n Logger.printStartActionMessage('Running unit tests for ' + target + ' ' + platform + ' ' + cpu + ' ' + configuration, ColoredFormatter.YELLOW)\\n result = UnitTestRunner.run(target, platform, cpu, configuration)\\n Summary.addSummary(ACTION_RUN_UNITTESTS, target, platform, cpu, configuration, result, UnitTestRunner.executionTime)\\n if result != NO_ERROR:\\n Logger.printEndActionMessage('Failed to execute unit tests!')\\n else:\\n Logger.printEndActionMessage('Executed all unit tests')\",\n \"def run_test(self):\\n raise NotImplementedError\",\n \"def main():\\n unittest.main(exit=False, verbosity=2)\\n return 0\",\n \"def runTest(self):\\n self.setUp()\\n self.test_Analytics1()\",\n \"def cov():\\n tests = unittest.TestLoader().discover('project/tests')\\n result = unittest.TextTestRunner(verbosity=2).run(tests)\\n if result.wasSuccessful():\\n COV.stop()\\n COV.save()\\n print('Coverage Summary:')\\n COV.report()\\n COV.html_report()\\n COV.erase()\\n return 0\\n return 1\",\n \"def runTest(self):\\n self.setUp()\\n self.test_FiducialTransform1()\",\n \"def cov():\\n cov = coverage.coverage(branch=True, include='project/*')\\n cov.start()\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\\n cov.stop()\\n cov.save()\\n print('Coverage Summary:')\\n cov.report()\\n basedir = os.path.abspath(os.path.dirname(__file__))\\n covdir = os.path.join(basedir, 'tmp/coverage')\\n cov.html_report(directory=covdir)\\n print('HTML version: file://%s/index.html' % covdir)\\n cov.erase()\",\n \"def main():\\n run_test_summary1a()\\n run_test_summary1c()\\n run_test_summary1c()\",\n \"def test_basic_execution(self):\",\n \"def cov():\\n cov = coverage.coverage(\\n branch=True,\\n include='project/*',\\n omit=\\\"*/__init__.py\\\"\\n )\\n cov.start()\\n tests = unittest.TestLoader().discover('tests')\\n unittest.TextTestRunner(verbosity=2).run(tests)\\n cov.stop()\\n cov.save()\\n print 'Coverage Summary:'\\n cov.report()\\n basedir = os.path.abspath(os.path.dirname(__file__))\\n covdir = os.path.join(basedir, 'tmp/coverage')\\n cov.html_report(directory=covdir)\\n print('HTML version: file://%s/index.html' % covdir)\\n cov.erase()\",\n \"def runTest(self):\\n self.setUp()\\n self.test_SegmentDicom1()\",\n \"def run():\\n\\tsubsuite_list = []\\n\\tfor _, modname, _ in pkgutil.iter_modules(test.__path__):\\n\\t\\tif modname.startswith(\\\"test_\\\"):\\n\\t\\t\\tmodule = importlib.import_module('test.' + modname)\\n\\t\\t\\tsubsuite = unittest.TestLoader().loadTestsFromModule(module)\\n\\t\\t\\tsubsuite_list.append(subsuite)\\n\\tsuite = unittest.TestSuite(subsuite_list)\\n\\n\\tprint(\\\"Testing:\\\\n\\\")\\n\\tunittest.TextTestRunner(verbosity=2).run(suite)\",\n \"def test_script(self) -> None:\\n main()\",\n \"def test():\\n tests = unittest.TestLoader().discover('project/tests', pattern='test*.py')\\n result = unittest.TextTestRunner(verbosity=2).run(tests)\\n if result.wasSuccessful():\\n return 0\\n sys.exit(result)\",\n \"def test_all_no_class(self):\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7740198","0.7395665","0.73899317","0.73077023","0.7184236","0.71184987","0.7116021","0.7049126","0.695683","0.6951264","0.6858743","0.682145","0.6820713","0.6819008","0.6809791","0.67945355","0.6780462","0.6749489","0.671787","0.6669164","0.66648895","0.66419506","0.663322","0.6627821","0.6617628","0.66106844","0.66097254","0.6583377","0.65735316","0.65563804","0.6552433","0.6549086","0.65327287","0.652728","0.651633","0.650739","0.6502367","0.6502367","0.64956135","0.6489306","0.6489306","0.6489306","0.6489248","0.64619476","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.64542","0.6454192","0.6453797","0.6445205","0.6442094","0.64406633","0.64386016","0.6429521","0.6421117","0.6417108","0.6409513","0.6398091","0.6391008","0.6389989","0.63870597","0.63816077","0.6380179","0.63757944","0.6371951","0.63498116","0.63433075","0.6342515","0.634239","0.63381493","0.63336605","0.6323768","0.63147837","0.63058037","0.6304162","0.630137","0.6294818","0.62875044","0.62819076","0.62689775","0.62682","0.62675077","0.6246566","0.6244128","0.6243914","0.6243798","0.62375784","0.6233122","0.6194239"],"string":"[\n \"0.7740198\",\n \"0.7395665\",\n \"0.73899317\",\n \"0.73077023\",\n \"0.7184236\",\n \"0.71184987\",\n \"0.7116021\",\n \"0.7049126\",\n \"0.695683\",\n \"0.6951264\",\n \"0.6858743\",\n \"0.682145\",\n \"0.6820713\",\n \"0.6819008\",\n \"0.6809791\",\n \"0.67945355\",\n \"0.6780462\",\n \"0.6749489\",\n \"0.671787\",\n \"0.6669164\",\n \"0.66648895\",\n \"0.66419506\",\n \"0.663322\",\n \"0.6627821\",\n \"0.6617628\",\n \"0.66106844\",\n \"0.66097254\",\n \"0.6583377\",\n \"0.65735316\",\n \"0.65563804\",\n \"0.6552433\",\n \"0.6549086\",\n \"0.65327287\",\n \"0.652728\",\n \"0.651633\",\n \"0.650739\",\n \"0.6502367\",\n \"0.6502367\",\n \"0.64956135\",\n \"0.6489306\",\n \"0.6489306\",\n \"0.6489306\",\n \"0.6489248\",\n \"0.64619476\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.64542\",\n \"0.6454192\",\n \"0.6453797\",\n \"0.6445205\",\n \"0.6442094\",\n \"0.64406633\",\n \"0.64386016\",\n \"0.6429521\",\n \"0.6421117\",\n \"0.6417108\",\n \"0.6409513\",\n \"0.6398091\",\n \"0.6391008\",\n \"0.6389989\",\n \"0.63870597\",\n \"0.63816077\",\n \"0.6380179\",\n \"0.63757944\",\n \"0.6371951\",\n \"0.63498116\",\n \"0.63433075\",\n \"0.6342515\",\n \"0.634239\",\n \"0.63381493\",\n \"0.63336605\",\n \"0.6323768\",\n \"0.63147837\",\n \"0.63058037\",\n \"0.6304162\",\n \"0.630137\",\n \"0.6294818\",\n \"0.62875044\",\n \"0.62819076\",\n \"0.62689775\",\n \"0.62682\",\n \"0.62675077\",\n \"0.6246566\",\n \"0.6244128\",\n \"0.6243914\",\n \"0.6243798\",\n \"0.62375784\",\n \"0.6233122\",\n \"0.6194239\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6756857"},"document_rank":{"kind":"string","value":"17"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":256,"numItemsPerPage":100,"numTotalItems":95772,"offset":25600,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sInJlcG9JZHMiOlsiNjc1Mzc2ODJkMmE2Mjg0NzVhMWJmZmNkIl0sImlhdCI6MTc5MTEzNTA1MywianRpIjoiM2Y1MDRjNmUtNDBlMy00ZGEzLWJjNTgtODIyMTE2YjNjYTNmIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3OTExMzg2NTMsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.GCbv89GhP_abosr417K5OXHL4ubKZYTCjJtW3A-mNGERH18ZuM4x_-uQDbjGevWyFvfre4GATfBKYzIMUWDNDQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Post a stop transaction | def on_post(self, req, resp):
USER_IDTAG = req.media.get('idTag')
METERVALUE_STOP = req.media.get('meterValue')
VICINITY_OID = req.media.get('vicinityOid')
CONTRACT_ADDRESS = 'address'
print("Stopping TX for idTag {} with meter value {}".format(USER_IDTAG, METERVALUE_STOP))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exit_transaction():\n _state.transactions = max(get_transactions() - 1, 0)",
"def endTransaction(self, transactionID: int) -> None:\n ...",
"def abort_transaction(self) -> None:\n pass",
"def stop(self):\n self.auto_commit_interval = None",
"def tpc_abort(self, transaction):\n ... | [
"0.6699632",
"0.66263175",
"0.6615936",
"0.65986675",
"0.6569888",
"0.65262157",
"0.649279",
"0.63895684",
"0.63655126",
"0.63429636",
"0.63281006",
"0.6308372",
"0.6287366",
"0.624233",
"0.6233434",
"0.62268543",
"0.621473",
"0.621473",
"0.61691254",
"0.61691254",
"0.6169125... | 0.0 | -1 |
To load the descriptor settings from the config file,only HOG is supported | def load_descriptor(settings):
return {
'hog': descriptors.HogDescriptor.from_config_file(settings['hog']),
}.get(settings['train']['descriptor'], 'hog') # Default to HOG for invalid input | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_config(self):\n pass",
"def config():",
"def config():",
"def read_config(self, config_filename):",
"def loadConfig(self):\r\n self.config.read(self.CONFIG_FILE)\r\n try:\r\n assert \"Settings\" in self.config\r\n except AssertionError:\r\n print(\... | [
"0.64163566",
"0.60806596",
"0.60806596",
"0.5885641",
"0.58768445",
"0.58304346",
"0.58304346",
"0.582294",
"0.57977813",
"0.5787138",
"0.5759142",
"0.57564086",
"0.57534146",
"0.5717577",
"0.5700591",
"0.56643593",
"0.56641626",
"0.563442",
"0.56303775",
"0.5625049",
"0.562... | 0.7915412 | 0 |
Generator which yields all files in the given directories with any of the EXTENSIONS. | def get_files(dirs):
for dir in dirs:
for root, _, files in os.walk(dir):
for file in files:
path = Path(os.path.join(root, file))
if path.suffix in EXTENSIONS:
yield path | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_files_in_dir(dir, ext):\n import os\n\n for root, dirs, files in os.walk(dir):\n for file in files:\n if file.split('.')[1].lower() == ext.lower() or not ext:\n file_full_path = os.path.join(root, file)\n yield file_full_path",
"def search_images(\n ... | [
"0.7361726",
"0.7168468",
"0.70106226",
"0.6978779",
"0.69671875",
"0.6956483",
"0.69562167",
"0.69542754",
"0.6939163",
"0.68995976",
"0.68970984",
"0.683653",
"0.68256193",
"0.6820684",
"0.67836255",
"0.67363906",
"0.67210203",
"0.6719789",
"0.6704543",
"0.67027146",
"0.669... | 0.8138541 | 0 |
assumed called after can_place_piece | def place_piece(cfg, b, m, n, piece):
for mm, nn in threats_gen_for[piece](cfg, m, n):
mark_if_empty(cfg, b, mm, nn, ':')
b[board_idx(cfg, m, n)] = piece
cfg[piece] = cfg[piece] - 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_comp_place_piece():\n board = Board(640, 640, 8)\n black_piece = GamePiece(0, 0, BLACK, 0)\n white_piece = GamePiece(0, 0, WHITE, 0)\n board.start_game()\n\n board.game_pieces[3][3] = None\n board.game_pieces[3][4] = None\n board.game_pieces[4][3] = None\n board.game_pieces[4][4] =... | [
"0.72498935",
"0.7119869",
"0.7078613",
"0.69797564",
"0.66100985",
"0.6450406",
"0.63937426",
"0.63600475",
"0.6337117",
"0.6296665",
"0.627747",
"0.6170568",
"0.6148269",
"0.6143879",
"0.61077535",
"0.6037338",
"0.6025112",
"0.6015202",
"0.6011923",
"0.60070294",
"0.5972882... | 0.6223171 | 11 |
Set the hash preprocessors of the state and the action, in order to make them hashable. | def _initialize_hash(self):
# action
if isinstance(self.env.action_space, gym.spaces.Discrete):
self._hash_action = lambda x: x
elif isinstance(self.env.action_space, gym.spaces.Box):
if self.__class__.__name__ == "MCTS":
raise Exception("Cannot run vanil... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init_hash_state(self) -> None:\n self.hash_states = [hashlib.sha1()]",
"def __setstate__(self, state):\n self.__dict__ = dict(state)\n self._init_compiled()",
"def hash_functions(self):\n pass",
"def _state_actions(self) -> dict:\n return {}",
"def state_encod_arch2(s... | [
"0.57571864",
"0.5435478",
"0.54035085",
"0.52372074",
"0.518619",
"0.5141052",
"0.5130122",
"0.50220853",
"0.5004999",
"0.49558762",
"0.4926324",
"0.49014458",
"0.48990655",
"0.48768932",
"0.48673987",
"0.48605478",
"0.48585635",
"0.4834343",
"0.48277575",
"0.48239538",
"0.4... | 0.5770757 | 0 |
Return the decision node of drawn by the select outcome function. If it's a new node, it gets appended to the random node. Else returns the decsion node already stored in the random node. | def update_decision_node(self, decision_node, random_node, hash_preprocess):
if hash_preprocess(decision_node.state) not in random_node.children.keys():
decision_node.father = random_node
random_node.add_children(decision_node, hash_preprocess)
else:
decision_node = ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def select_outcome(self, env, random_node):\n new_state_index, r, done, _ = env.step(random_node.action)\n return DecisionNode(state=new_state_index, father=random_node, is_final=done), r",
"def choose_node(self, choices, scores):\n total = sum(scores)\n cumdist = list(itertools.accum... | [
"0.710089",
"0.6310771",
"0.62979186",
"0.61296755",
"0.60056055",
"0.566461",
"0.56139195",
"0.5580124",
"0.55776966",
"0.5576547",
"0.55047697",
"0.54978997",
"0.54622674",
"0.5436584",
"0.54286194",
"0.5427209",
"0.5420681",
"0.54089963",
"0.5405846",
"0.5405593",
"0.53766... | 0.5864453 | 5 |
Explores the current tree with the UCB principle until we reach an unvisited node where the reward is obtained with random rollouts. | def grow_tree(self):
decision_node = self.root
internal_env = copy.copy(self.env)
while (not decision_node.is_final) and decision_node.visits > 1:
a = self.select(decision_node)
new_random_node = decision_node.next_random_node(a, self._hash_action)
(new_d... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def UCT(rootstate, itermax, verbose=False):\n\n rootnode = Node(state=rootstate)\n\n for i in range(itermax):\n node = rootnode\n state = rootstate.Clone()\n\n # Select\n while node.untriedMoves == [] and node.childNodes != []: # node is fully expanded and non-terminal\n ... | [
"0.6164046",
"0.61358875",
"0.6106919",
"0.6031748",
"0.60115874",
"0.595056",
"0.59471905",
"0.59269196",
"0.58961433",
"0.58696514",
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"0.5783845",
"0.5782573",
"0.57748175",
"0.5721878",
"0.57213783",
"0.5706393",
"0.5656... | 0.6590161 | 0 |
Evaluates a DecionNode playing until an terminal node using the rollotPolicy | def evaluate(self, env):
max_iter = 100
R = 0
done = False
iter = 0
while ((not done) and (iter < max_iter)):
iter += 1
a = env.action_space.sample()
s, r, done, _ = env.step(a)
R += r
return R | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def q_learning_episode(self, policy):\n state = self.env.reset(self.agent_start_pos)\n done = False\n\n while not done:\n action = policy(state, self.q_values)\n next_cell = self.env.move(self.env.agent_position, action)\n s_next, rew, done, _ = self.env.step(n... | [
"0.55386966",
"0.5254755",
"0.52383435",
"0.52076405",
"0.5176333",
"0.51604325",
"0.5145268",
"0.5110981",
"0.5029525",
"0.5023521",
"0.5023521",
"0.50121635",
"0.5000631",
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"0.4981898",
"0.49673364",
"0.49540222",
"0.49504992",
"0.49406677",
"0.49151736",
"0.491... | 0.0 | -1 |
Given a RandomNode returns a DecisionNode | def select_outcome(self, env, random_node):
new_state_index, r, done, _ = env.step(random_node.action)
return DecisionNode(state=new_state_index, father=random_node, is_final=done), r | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_random_node(self):\n if random.randint(0, 100) > self.goal_sample_rate:\n random_node = self.Node(\n random.uniform(self.min_rand, self.max_rand),\n random.uniform(self.min_rand, self.max_rand),\n )\n else: # goal point sampling\n ... | [
"0.6875797",
"0.6506942",
"0.636228",
"0.632881",
"0.6185813",
"0.6153899",
"0.6089393",
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"0.5892125",
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"0.56049466",
"0.5597951",
"0.5591621",
"0.5579573",
"0.5573688",
"0.557171",
"0... | 0.7110679 | 0 |
Selects the action to play from the current decision node | def select(self, x):
if x.visits <= 2:
x.children = {a: RandomNode(a, father=x) for a in range(self.env.action_space.n)}
def scoring(k):
if x.children[k].visits > 0:
return x.children[k].cumulative_reward/x.children[k].visits + \
self.K*np.sqr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ChooseAction(self):\n self.lastAction = None\n self.lastState = None\n if(self.attention is None or self.attention == \"\"): return\n # find best action for the currently attended node\n actions = list(self.vi.Q[self.states.index(self.attention)])\n actionIndex = actions.i... | [
"0.74682564",
"0.7420793",
"0.7184482",
"0.7134516",
"0.7029573",
"0.69586843",
"0.6921828",
"0.691864",
"0.6875106",
"0.6863868",
"0.68618166",
"0.6847336",
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"0.67138106",
"0.6693452",
"0.6592016",
"0.65595233",
"0.6557133",
"0.6526618",
"0.65131426"... | 0.0 | -1 |
At the end of the simulations returns the most visited action | def best_action(self):
number_of_visits_children = [node.visits for node in self.root.children.values()]
index_best_action = np.argmax(number_of_visits_children)
a = list(self.root.children.values())[index_best_action].action
return a | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def select_action(self) -> int:\n # simulation loop\n for i in range(self.iterations):\n self.__simulate(self.root, self.iterations)\n\n # action choice\n max_q = 0\n best_action = 0\n for action in actions:\n new_node = self.root.children[action]\n ... | [
"0.70127183",
"0.687149",
"0.6863603",
"0.67862076",
"0.6771671",
"0.6724781",
"0.670188",
"0.66465",
"0.66390723",
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"0.6597186",
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"0.65311867",
"0.6512796",
"0.6509938",
"0.6498248",
"0.64976394",
"0.6495535",
... | 0.7107038 | 0 |
Expand the tree and return the bet action | def learn(self, Nsim, progress_bar=False):
if progress_bar:
iterations = tqdm(range(Nsim))
else:
iterations = range(Nsim)
for _ in iterations:
self.grow_tree() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def expand(node):\n if not node.is_leaf():\n return\n\n # build children\n is_done = []\n for action in constants.Action:\n child_node = node.copy()\n agents_obs = node.game_env.get_observations()\n\n # Combine current observation with the agent's memory of the game\n ... | [
"0.71309716",
"0.6870978",
"0.6248184",
"0.6238105",
"0.61890656",
"0.61695313",
"0.61247694",
"0.6108605",
"0.60646635",
"0.60078114",
"0.59485406",
"0.58924407",
"0.5844102",
"0.5844102",
"0.5844102",
"0.5844102",
"0.58059675",
"0.5793563",
"0.5791642",
"0.5724908",
"0.5716... | 0.0 | -1 |
If the env is determonostic we can salvage most of the tree structure. Advances the tree in the action taken if found in the tree nodes. | def forward(self, action, new_state):
if self._hash_action(action) in self.root.children.keys():
rnd_node = self.root.children[self._hash_action(action)]
if len(rnd_node.children) > 1:
self.root = DecisionNode(state=new_state, is_root=True)
else:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clean():\n new_tree = None",
"def reset_tree(self):\n self.root = None\n self.action = None\n self.dist_probability = None",
"def tree_removeDeadBranches():\n nonlocal d_tree\n d_tree = { k : v for k, v in d_tree.items() if v}\n # By creating a new b... | [
"0.66061085",
"0.6231232",
"0.6116748",
"0.60997236",
"0.60270435",
"0.5866573",
"0.5859067",
"0.58203506",
"0.57578725",
"0.56961167",
"0.56451476",
"0.55916977",
"0.5587942",
"0.5561475",
"0.55515796",
"0.5533417",
"0.5515334",
"0.5514626",
"0.5477468",
"0.54768384",
"0.547... | 0.54636896 | 21 |
Collects the data and parameters to save. | def _collect_data(self):
data = {
"K": self.K,
"root": self.root
}
return data | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def saveData(self):\n pass",
"def save_data(self):\n pass",
"def make_save(self):\n\t\tsave = {}\n\t\tsave['p'] = self.p\n\t\tsave['injail'] = self.injail.copy()\n\t\tsave['tile'] = self.tile.copy()\n\t\tsave['bal'] = self.bal.copy()\n\t\tsave['goojf'] = self.goojf.copy()\n\t\tsave['isalive'] = s... | [
"0.79443794",
"0.7918926",
"0.72642434",
"0.6999899",
"0.6981673",
"0.69450337",
"0.69021773",
"0.6835701",
"0.6794337",
"0.67396384",
"0.6688276",
"0.66301215",
"0.6612951",
"0.65625846",
"0.65606374",
"0.653039",
"0.652962",
"0.6527134",
"0.6516258",
"0.64973986",
"0.649706... | 0.0 | -1 |
Saves the tree structure as a pkl. | def save(self, path=None):
data = self._collect_data()
name = np.random.choice(['a', 'b', 'c', 'd', 'e', 'f']+list(map(str, range(0, 10))), size=8)
if path is None:
path = './logs/'+"".join(name)+'_'
with open(path, "wb") as f:
cloudpickle.dump(data, f)
p... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self, path):\n with open(path, 'wb') as f:\n pkl.dump(self, f)",
"def _save_tree(tree, tree_path):\n try:\n with open(tree_path, 'wb') as f:\n pickle.dump(tree, f)\n except Exception as e:\n logger.warning('Could not save tree to {}: {... | [
"0.6902854",
"0.6814618",
"0.6799568",
"0.67856103",
"0.6687682",
"0.6494133",
"0.6403352",
"0.6380208",
"0.62340564",
"0.62287766",
"0.61716175",
"0.614781",
"0.6124842",
"0.60752356",
"0.6000558",
"0.5963424",
"0.5955345",
"0.5908942",
"0.5908559",
"0.5869761",
"0.5800398",... | 0.0 | -1 |
Return the best action accoring to the maximum visits principle. | def act(self):
action = self.best_action()
return action | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def best_action(self):\n\n number_of_visits_children = [node.visits for node in self.root.children.values()]\n index_best_action = np.argmax(number_of_visits_children)\n\n a = list(self.root.children.values())[index_best_action].action\n return a",
"def _best_action(self, state):\n ... | [
"0.7849317",
"0.7557292",
"0.7380547",
"0.72836643",
"0.7183584",
"0.7147923",
"0.71446735",
"0.7056981",
"0.7048105",
"0.69948894",
"0.6994605",
"0.69541126",
"0.69461155",
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"0.69361454",
"0.69264233",
"0.69251484",
"0.6905916",
"0.6904357",
"0.6896602",
"0.68432... | 0.69599766 | 11 |
Builds a DAG of Steps from a SQL expression so that it's easier to execute in an engine. | def from_expression(
cls, expression: exp.Expression, ctes: t.Optional[t.Dict[str, Step]] = None
) -> Step:
ctes = ctes or {}
expression = expression.unnest()
with_ = expression.args.get("with")
# CTEs break the mold of scope and introduce themselves to all in the context.
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plan_step_to_expr(atom: clingo.Symbol) -> str:\n # The predicate and its arguments are double-quoted. Simply extract them\n matches = re.findall(r'\\\"(.+?)\\\"', str(atom))\n predicate = matches[0]\n args = f'({\",\".join(matches[1:])})' if matches[1:] else ''\n return predicate + args",
"def... | [
"0.5711968",
"0.5664347",
"0.538123",
"0.52660775",
"0.52169806",
"0.51955956",
"0.51791394",
"0.5158939",
"0.51581794",
"0.51150316",
"0.51042306",
"0.5073506",
"0.50646734",
"0.505281",
"0.5020296",
"0.49805304",
"0.49764872",
"0.4972279",
"0.49443945",
"0.49404278",
"0.493... | 0.6603545 | 0 |
This is used for debugging and will not return the tree in a pretty way, only the info about this node will be returned | def __repr__(self):
return (f'Heuristic: {self.heuristic}\n'\
f'Ancestors: {self.ancestors}\n'\
f'Result: {self.result}\n'\
f'Attributes: {self.attributes}\n'\
f'Split Attribute: {self.split_attr}\n'\
f'Has children: {self.val0 != N... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def print_tree(self):\n return \"\"",
"def print_tree(self):\n\t\tprint(self.__print_tree('', True, ''))",
"def __repr__(self):\n return show_tree(self, lambda node: node.name,\n lambda node: node.children)",
"def print_tree(self):\n print(_Node.__print_tree(self)... | [
"0.8037728",
"0.79554933",
"0.76366156",
"0.75786775",
"0.7553154",
"0.7531516",
"0.7483125",
"0.74414235",
"0.73703814",
"0.7342984",
"0.7342984",
"0.7313995",
"0.7260545",
"0.7253631",
"0.72212666",
"0.71999764",
"0.7148193",
"0.7119914",
"0.71159977",
"0.7104752",
"0.70868... | 0.0 | -1 |
This will continue splitting the tree until every leaf node is pure and the training data is perfectly characterized by the decision tree | def train(self):
max_tuple = self.max_gain()
# If that gain is 0 then every node should be a pure leaf (hopefully) and you can stop
while max_tuple.gain != 0:
max_tuple.node.split(max_tuple.attribute)
max_tuple = self.max_gain() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def decision_tree(original_training_data,call_depth):\n\n ''' Checking the stopping criterion. If yes then it returns the majority class (Muffin or CupCake) '''\n if check_if_stopping_criterion_is_met(original_training_data.values) or call_depth > 10:\n majority = classification(original_training_data... | [
"0.736419",
"0.6879376",
"0.68064624",
"0.66134644",
"0.65553546",
"0.6515525",
"0.6498684",
"0.6492946",
"0.6436828",
"0.6393142",
"0.6376377",
"0.6344093",
"0.63422775",
"0.62961286",
"0.62934136",
"0.62801987",
"0.62608254",
"0.6223276",
"0.61976653",
"0.6194716",
"0.61382... | 0.7007727 | 1 |
If the node has children it will return the (node, attribute, gain) tuple of the child with the highest gain If the node does not have children and is not pure it will return the (node, attribute, gain) tuple with itself as the node and the highest heuristic score of splitting on any of its attributes as the gain If th... | def max_gain(self):
if self.val1:
val1_gain_tuple, val0_gain_tuple = self.val1.max_gain(), self.val0.max_gain()
if val1_gain_tuple.gain > val0_gain_tuple.gain:
return val1_gain_tuple
else:
return val0_gain_tuple
elif self.attributes:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def select_child(self, node):\n ucb_values = []\n for action, child in node.children.items():\n if node.state.player_turn == 1:\n if child.n_visits == 0:\n ucb_max = float('inf')\n else:\n ucb_max = self.calculate_ucb_max... | [
"0.64669144",
"0.63168865",
"0.6179859",
"0.6137272",
"0.6127355",
"0.6071936",
"0.6051509",
"0.6038578",
"0.60306424",
"0.5946005",
"0.59143674",
"0.5897368",
"0.5833015",
"0.5821131",
"0.5816206",
"0.58110994",
"0.5801434",
"0.57993925",
"0.57883",
"0.5769697",
"0.57651377"... | 0.6359626 | 1 |
This splits a node on the attribute "attribute" | def split(self, attribute):
if attribute not in self.attributes:
raise KeyError('Attribute not present in node')
self.split_attr = attribute
# list() is used to make a copy of the list instead of pointing to the same list
child_attributes = list(self.attribu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def splitAttribute(self, atr, divider=0.5):\n big, lit = DecisionTree(None, self.atr), DecisionTree(None, self.atr)\n for d in self:\n if d[atr] > divider: big.append(d)\n else: lit.append(d)\n return lit, big",
"def split_by_attribute(dbsession, group, attr):\n valu... | [
"0.5715175",
"0.5710266",
"0.5545711",
"0.55031914",
"0.55031914",
"0.5446711",
"0.5446711",
"0.54354566",
"0.5370533",
"0.53344154",
"0.5330768",
"0.5245361",
"0.52420187",
"0.5240586",
"0.5158735",
"0.5151447",
"0.5148021",
"0.5079045",
"0.50706065",
"0.50669575",
"0.506043... | 0.77221286 | 0 |
If the sample is pure, returns class, else returns None | def purity_test(self):
mean = filter_data(self.data,self.ancestors)['Class'].mean()
if mean == 0:
return 0
elif mean == 1:
return 1
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_returns_class(self):\n assert type is simple_class().__class__",
"def sample(self):\r\n raise NotImplementedError",
"def sample(self, sample_id: str):\n\n class LimsSample:\n \"\"\" A mock class for a sample coming from LIMS. It only needs a comment \"\"\"\n\n de... | [
"0.66925657",
"0.61924195",
"0.6062284",
"0.6007603",
"0.5844515",
"0.58352",
"0.5829622",
"0.5829622",
"0.580038",
"0.57619864",
"0.57172626",
"0.5700162",
"0.56975627",
"0.5693888",
"0.56934226",
"0.56467",
"0.5638737",
"0.563829",
"0.55490357",
"0.5489884",
"0.54813504",
... | 0.5173868 | 37 |
This will return the information gain that you get from splitting a node with that has the data "data" on the attribute "attribute" | def entropy_gain(node,attribute):
data_subset1 = filter_data(node.data,node.ancestors)
data_counts = list(Counter(data_subset1['Class']).values())
base_entropy = entropy(data_counts,base=2)
num_values = len(data_subset1)
entropy_sum = 0
for value in [0,1]:
data_subset2 = filter_data... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getSplitAttr(self, data, attributes):\n splitAttrIndex = 0\n lengthAttr = len(attributes)\n del self.infoGain[:]\n index = 0\n while index < lengthAttr:\n self.infoGain.append(self.getInfoGain(data, index))\n index += 1\n\n for gain in self.infoGa... | [
"0.6657157",
"0.63218254",
"0.61898667",
"0.6106076",
"0.60014737",
"0.5843759",
"0.56900775",
"0.5589873",
"0.55893284",
"0.5522103",
"0.54951817",
"0.54832",
"0.54067916",
"0.5388961",
"0.53631663",
"0.53464425",
"0.53424656",
"0.53007346",
"0.5284335",
"0.527781",
"0.52702... | 0.5414344 | 12 |
This will return the information gain that you get from splitting a node with that has the data "data" on the attribute "attribute" | def impurity_gain(node, attribute):
data_subset1 = filter_data(node.data,node.ancestors)
data_counts = list(Counter(data_subset1['Class']).values())
base_impurity = impurity(data_counts)
num_values = len(data_subset1)
impurity_sum = 0
for value in [0,1]:
data_subset2 = filter_data(n... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getSplitAttr(self, data, attributes):\n splitAttrIndex = 0\n lengthAttr = len(attributes)\n del self.infoGain[:]\n index = 0\n while index < lengthAttr:\n self.infoGain.append(self.getInfoGain(data, index))\n index += 1\n\n for gain in self.infoGa... | [
"0.66578203",
"0.6325501",
"0.6186457",
"0.6108713",
"0.6002287",
"0.5846265",
"0.5691551",
"0.559086",
"0.5583705",
"0.5522734",
"0.54993653",
"0.54846495",
"0.5415968",
"0.5407902",
"0.53898907",
"0.5364955",
"0.5345286",
"0.5343627",
"0.5299366",
"0.52865124",
"0.5280009",... | 0.51550907 | 28 |
This filters the training data according to the ancestors of this node so that only a subset of the training data is considered for calculations like entropy | def filter_data(data,filters):
final_filter = pd.Series(np.array([True] * data.shape[0]))
for attribute, value in filters:
final_filter &= data[attribute] == value
return data[final_filter] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def filter_nodes(self, node_filter, parent=None):\n if self.data is None:\n return None\n\n if parent is None:\n return self.data.xpath(node_filter)\n else:\n return parent.xpath(node_filter)",
"def __filterEdges(self):",
"def get_filtered_pedigree_with_sam... | [
"0.5749394",
"0.57379466",
"0.56971365",
"0.5644228",
"0.56307316",
"0.5488976",
"0.5440608",
"0.542651",
"0.5393545",
"0.5392112",
"0.5351504",
"0.5328558",
"0.5202672",
"0.520047",
"0.51837265",
"0.517472",
"0.5142696",
"0.513255",
"0.51286936",
"0.5114975",
"0.51093954",
... | 0.0 | -1 |
sort and retrieve top rows of df | def get_top_recipes(df, sort_params=None, count=10):
if not sort_params:
logging.warning("Column names to soty by are not defined.")
return df
return df.sort_values(sort_params["names"],
ascending=sort_params["order"]).head(count) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def select_topn(df, top_n=25):\n assert df.columns.str.contains(\"ranking\").any(), \"select_topn failed. Missing 'ranking' column.\"\n \n # top-n by ranking\n topn_idx = df.groupby(\"ranking\").value_normalized.nlargest(top_n).droplevel(0).index\n \n return df.loc[topn_idx, : ]",
"def analyse_... | [
"0.68262124",
"0.6588031",
"0.6443308",
"0.6321405",
"0.6281697",
"0.62319",
"0.6184617",
"0.6135005",
"0.6129716",
"0.6061375",
"0.6024057",
"0.60073507",
"0.59771293",
"0.59485084",
"0.5929012",
"0.5920936",
"0.5898448",
"0.5891113",
"0.5877641",
"0.5877335",
"0.5831138",
... | 0.6937662 | 0 |
1. parse the json object and extract name, headline, prepTime, ratingsCount, favoritesCount, nutrition and export to a csv file 2. retrieve top 10 recipes based on ratingsCount, favoritesCount and export to a csv file | def read_recipes(year, week):
# read config file
cp = ConfigParser()
cp.read("config.ini")
# load menu data
fname_json = cp["other"]["json_out_fname"]
if not os.path.exists(fname_json):
logging.error("JSON file not found.")
return
with open(fname_json) as f:
m... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getTopMovies(endpoint, date, count=10):\n\n try:\n response = urlreq.urlopen(endpoint.format(date))\n soup = BeautifulSoup(response.read(), \"html.parser\")\n table = soup.find('table', border=\"0\", cellpadding=\"5\", cellspacing=\"1\")\n tdata = []\n\n for i, r... | [
"0.5909842",
"0.57680744",
"0.5694507",
"0.56098086",
"0.5597891",
"0.556882",
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"0.550861",
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"0.54270613",
"0.54165226",
"0.54148346",
"0.5412836",
"0.5410096",
"0.53659177",
"0.5352422"... | 0.6317173 | 0 |
Sanity check that the tests have been set up correctly. | def setUp(self):
assert COMMANDS.keys() == EXPCT_RESULTS.keys()
self.tests = []
self.test_numbers = deque(sorted(COMMANDS.keys())) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tests():",
"def setUp(self):\n\n app.testing = True\n self.app = app.test_client()\n\n self.valid_question = {\n \"title\" : \"tests\",\n \"question\": \"How do I refactor tests with database?\"\n }\n\n self.invalid_question = {\n \"title\" ... | [
"0.7378789",
"0.72924495",
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"0.7285571",
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"0.71835464",
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"0.7178741",
"0.7178741",
"0.7178741",
"0.7178741",
"0.7178741",
"0.7178741"... | 0.0 | -1 |
Check whether the test has passed by comparing its stdout to what is expected. | def check_test(self, test):
(stdout, stderr) = (out.decode('ascii').strip()
for out in test.process.communicate())
self.assertEqual(stderr, "")
self.assertEqual(stdout, EXPCT_RESULTS[test.number],
"Test {} failed".format(test.number))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_stdout(self, expected: str):\n assert self._std_out is not None, f\"You first need to `execute` the program before checking stdout!\"\n self._test.assertEqual(self._std_out.strip(), expected.strip())",
"def testStdoutAndStderr(self):\n with self.OutputCapturer():\n print('foo')\n ... | [
"0.80546683",
"0.7428795",
"0.7355473",
"0.717167",
"0.7111023",
"0.7000859",
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"0.66335154",
"0.66038454",
"0.6588386",
"0.65542763",
"0.65454364",
"0.6543559... | 0.78012776 | 1 |
Start the next test. | def start_next_test(self):
next_test_num = self.test_numbers.popleft()
self.tests.append(
self.TEST(
process=Popen(COMMANDS[next_test_num],
stdout=PIPE,
stderr=PIPE),
number=next_test_num)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def startTestRun(self):",
"def startTest(self, test):\n self._timer = time()",
"def test_run_started(self):",
"def startTestRun(self, test):\n self.runTime= time.time()\n self.logger.debug(\"\\nBeginning ForceBalance test suite at %s\\n\" % time.strftime('%x %X %Z'))",
"def startTest(a... | [
"0.7740946",
"0.71101433",
"0.7070812",
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"0.6931316",
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"0.66558033",
"0.6652603",
"0.6652206",
"0.66263163",
"0.6597661",
"0.6591751",
"0.6574502",... | 0.8345263 | 0 |
Poll tests for completion. When one finishes, start another one if there are more to run. Stop when all are finished. | def poll_tests(self):
for i, test in enumerate(self.tests):
if test.process.poll() is not None:
self.check_test(test)
self.tests.pop(i)
if self.test_numbers:
self.start_next_test() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _wait_for_all_operations_done(self):\n while self._test_names_to_processes:\n time.sleep(10)\n running_test_names = list(self._test_names_to_processes.keys())\n for test_name in running_test_names:\n running_proc = self._test_names_to_processes.get(test_name)\n return_code = run... | [
"0.73554826",
"0.674941",
"0.65526724",
"0.6549344",
"0.6529588",
"0.64772254",
"0.64764065",
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"0.6316884",
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"0.6168625",
"0.6148079",
"0.6129336",
"0.60931456",
"0.609054",
"0.6083866",... | 0.7962783 | 0 |
Parse the tests to be run. These may be given as a single number, a commaseperated list or two numbers seperated by a dash. | def parse_tests(tests_input):
if '-' in tests_input:
limits = tests_input.partition('-')
tests = list(range(int(limits[0]), int(limits[2]) + 1))
else:
tests = [int(t) for t in tests_input.split(',')]
return tests | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_parser():\n return parser(\"Testing\", \"Use this from a test\", \"\")",
"def test_multiple_series(self):\n assert parse_command('test{{A,B}}{{1,2}}') == [\n ('testA1', {}), ('testA2', {}), ('testB1', {}), ('testB2', {})]",
"def parse(lines):\n num_tests = int(lines.next())\n ... | [
"0.64865124",
"0.64598006",
"0.64436996",
"0.624886",
"0.62173283",
"0.61449796",
"0.61414963",
"0.61308944",
"0.6120973",
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"0.59605867",
"0.59500784",
"0.5947035",
"0.59386694",
"0.5920873",
"0.59173906",
"0.5... | 0.7508628 | 0 |
Description The neighbor matching procedure of edge coarsening used in | def _neighbor_matching(
graph_idx, num_nodes, edge_weights=None, relabel_idx=True
):
edge_weight_capi = nd.NULL["int64"]
if edge_weights is not None:
edge_weight_capi = F.zerocopy_to_dgl_ndarray(edge_weights)
node_label = F.full_1d(
num_nodes,
-1,
getattr(F, graph_idx.dty... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _connect_neighbours(self):\n for prev in self.unvisited:\n for next in self.unvisited:\n if (next[0] == prev[0] and next[1] == prev[1] + 1) or (next[0] == prev[0] + 1 and next[1] == prev[1]):\n self.graph.addEdge((prev, next))\n self.visite... | [
"0.6153587",
"0.6068474",
"0.6067164",
"0.6052014",
"0.59956855",
"0.59085745",
"0.58968294",
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"0.5831831",
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"0.5721212",
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"0.5695957",
"0.5694912",
"0.5684748",
"0.56846213",
"0.5665716",
"0.5652258",
"0.5650964"... | 0.556528 | 30 |
Orchestrator class, get all args, compare if exist any aggregation tag and set the right class To add more aggregator, create a class using IAgregation abstract class and register on mapp variable. Design Pattern Chain of Responsability | def __init__(self, args):
self._mapp = {
'top_ips': ATopIps,
'request_rate': ARequests,
'top_sources': ATopSources
}
self.active = False
self.ag = self.setup(args) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup(self, args):\n for key, ags in self._mapp.items():\n arg = args.get(key)\n\n if arg: #if exist, turn aggregator actived and create a new instance a new aggregator class\n self.active = True\n return ags(arg)",
"def __init__(self, aggregator: a... | [
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"0.55537397",
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"0.5222265",
"0.5210367",
"0.52063924",
"0.5206035",
"0.5178624",
"0.5167367... | 0.54321074 | 8 |
Find which aggregator will be use, accordly cli args | def setup(self, args):
for key, ags in self._mapp.items():
arg = args.get(key)
if arg: #if exist, turn aggregator actived and create a new instance a new aggregator class
self.active = True
return ags(arg) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def aggregator_name(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"aggregator_name\")",
"def aggregator_name(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"aggregator_name\")",
"def main():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--process_qu... | [
"0.623255",
"0.60802627",
"0.5820678",
"0.5737905",
"0.57234126",
"0.57187593",
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"0.53977966",
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"0.5323734",
"0.5302474",
"0.52866167",
"0.5259916",
"0.52444696",
"0.52374387",
"0.52364... | 0.6193614 | 1 |
Used by Crawler class, append a line on instance of aggregator setuped. | def append(self, line):
self.ag.append(line) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def do_add_node(self, line=''):\n self.fibbing.add_node()",
"def add(self, line):\n self.body.append(line)",
"def connectionMade(self):\n self.output = DelayedStartupLineLogger()\n self.output.makeConnection(self.transport)\n self.output.tag = self.name",
"def _augment_pipe... | [
"0.56161034",
"0.5413999",
"0.5366023",
"0.5317709",
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"0.52674985",
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"0.51818913",
"0.5181332",
"0.5165727",
"0.51442534",
"0.5141288",
"0.5126... | 0.6032251 | 0 |
Return the result accordly each aggregator | def out(self):
return self.ag.output() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def aggregate_results(self):\n\n raise NotImplementedError",
"def getResults():",
"def get_results_from_aggregation_sources(self, context):",
"def _get_aggregated_results(self):\n gradients = self.gradients\n client_traj_infos = flatten_lists(self.client_traj_infos)\n client_opt_i... | [
"0.7283095",
"0.66016525",
"0.6454805",
"0.6355541",
"0.62754244",
"0.62277496",
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"0.59026664",
"0.58947885",
"0.5873596",
"0.58522385",
"0.58376825",
"0.58325... | 0.0 | -1 |
Start command to start bot on Telegram. = information about the bot = the user info. | def start(self, bot, update):
start_text = "This is the bot!"
bot.send_message(chat_id=update.message.chat_id, text=start_text) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def command_start(self, bot, update):\n\n msg = (\"Hi! I'm @MylesBot, a Telegram bot made by @MylesB about \"\n \"@MylesB.\")\n\n self.send_message(bot, update, msg)",
"def start(bot, update, session, chat, user):\n if chat.is_maintenance:\n call_tg_func(update.message.chat,... | [
"0.72836596",
"0.72188544",
"0.7043724",
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"0.66286534",
"0.66097116",
"0.6591849",
"0.65889055",
"0.6547758",
"0.6530... | 0.7057546 | 2 |
Echo the user message. | def echo(self, bot, update):
# print(update)
update.message.reply_text(update.message.text) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def showMessage(self, message):\r\n print message",
"def do_echo(self, message):\r\n\t\tself.trace(f'Echo: {message}!')",
"def say(self, message):\r\n print message",
"def echo(self, msg=None):\n return msg",
"def Echo(self, message):\n logging.info('Echoing %s', message)\n retur... | [
"0.76790404",
"0.76771134",
"0.76046246",
"0.7395257",
"0.72742033",
"0.72385746",
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"0.70086247",
"0.6957034",
"0.6957034",
"0.6937433",
"0.6937433",
"0.6937433"... | 0.6567033 | 51 |
Release module to pypi | def release_pypi():
local('python setup.py clean sdist register upload') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def publish():\n fab.local(\"env/bin/python setup.py sdist\")\n tar_filename = fab.local(\n \"env/bin/python setup.py --fullname\", capture=True\n )\n dist_filename = \"dist/{}.tar.gz\".format(tar_filename)\n fab.put(dist_filename, PYREPO_DIR)",
"def upload():\n sh('python setup.py regis... | [
"0.67773676",
"0.6478244",
"0.63994586",
"0.6243652",
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"0.5860913",
"0.5859919",
"0.58371365",
"0.58328044",
"0.5812867",
"0.57... | 0.77637976 | 0 |
Subprocess call for command that return non zero exit code... | def _subexec(command):
lcwd = fabric.state.env.get('lcwd', None) or None #sets lcwd to None if it bools to false as well
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=lcwd)
out, err = process.communicate()
print "command : %s " % command
print "... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(cmd, shell=False, cwd=None):\n try:\n out = check_output(cmd, shell=shell, cwd=cwd, stderr=STDOUT)\n except CalledProcessError as ex:\n return ex.returncode, ex.output\n else:\n return 0, out",
"def run(cmd):\n print ' '.join(cmd)\n try:\n check_call(cmd)\n e... | [
"0.7782048",
"0.76977396",
"0.7639604",
"0.7635583",
"0.75630707",
"0.75365514",
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"0.72279525",
"0.72127426",
"0.7181438",
"0.71659833",
"0.7133339... | 0.67369956 | 66 |
Pylint and PEP8 QA report generator We use subprocess instead local because pylint and pep8 don't return a zero exit code. This behaviour is incompatible with fabric... | def release_qa():
lines = StringIO.StringIO(local('find . -name "*.py"', capture=True))
for line in lines.readlines():
print "PYLINT CHECK"
print "-----------------------"
pyfile = os.path.normpath(line).replace("\n","").replace("\r","")
reportfilename = pyfile.replace(".... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def lint(to_lint):\n exit_code = 0\n for linter, options in (('pyflakes', []), ('pep8', pep8_options)):\n try:\n output = local[linter](*(options + to_lint))\n except commands.ProcessExecutionError as e:\n output = e.stdout\n\n if output:\n exit_code = 1\... | [
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"0.60457647",
"0.60411966",
"0.6017067",
"0.5966548",
"0.5959962",
"0.5957931",
"0.5918821",
"0.5904913",
"0.5893862",
"0.58845... | 0.7032081 | 0 |
installs and configures a fresh DIRAC UI (VO specific) | def install_ui():
# pick which VO I want to test, default gridpp
print "Which VO do you want to test (default: gridpp) ?"
user_VO = raw_input("Your choices are: gridpp, lz, lsst, solidexperiment.org, skatelescope.eu: ") \
or "gridpp"
if user_VO not in ["gridpp", "lz", "lsst", "solidexperiment.org", "skate... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bootstrap():\n validate_configurator_version()\n\n # put new mkinitcpio.conf in place\n run(\"mv /etc/mkinitcpio.conf.pacnew /etc/mkinitcpio.conf\")\n sed(\"/etc/mkinitcpio.conf\",\n 'MODULES=\"\"',\n 'MODULES=\"xen-blkfront xen-fbfront xen-kbdfront xen-netfront xen-pcifront xenbus_pr... | [
"0.603138",
"0.58798337",
"0.5784808",
"0.5766571",
"0.57437",
"0.5734021",
"0.5714146",
"0.56864846",
"0.5641124",
"0.5625011",
"0.56127167",
"0.56086886",
"0.5601726",
"0.55902636",
"0.55759335",
"0.55585897",
"0.55564934",
"0.55510265",
"0.5542947",
"0.5528047",
"0.5500627... | 0.7038603 | 0 |
Create a new installable package. | def __init__(self, pkg_info, remote_files, install_mgr):
_check_pkg_info(pkg_info, self._MANDATORY_KEYS)
_add_pkg_info_defaults(pkg_info)
self.pkg_info = pkg_info
self.remote_files = remote_files
self.install_mgr = install_mgr | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_package(self, **kwargs):\n results = self.api.action.package_create(**kwargs)\n self.get_ckan_metadata(True)\n return results",
"def makePackage(self, destination, packageName):\r\n packageFolder = os.path.join(destination, packageName)\r\n MakePyDir().makePyDir(pack... | [
"0.7582697",
"0.73307925",
"0.7132005",
"0.7014748",
"0.6922174",
"0.69100004",
"0.6891954",
"0.68648934",
"0.6862199",
"0.679142",
"0.6751084",
"0.67348325",
"0.66702074",
"0.6627358",
"0.6554115",
"0.6535373",
"0.6498029",
"0.6456046",
"0.6427742",
"0.6420937",
"0.6355059",... | 0.0 | -1 |
Create a new installed package. pkg_info same as pkg_info for installable package but adds the | def __init__(self, pkg_info):
_check_pkg_info(pkg_info, self._MANDATORY_KEYS)
_add_pkg_info_defaults(pkg_info)
self.pkg_info = pkg_info | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_package ( self, package_info, addition_control, **pkg_add_kw ):\n return self._get_package_dir ( package_info ['name'] ).add_package (\n package_info, addition_control, **pkg_add_kw\n )",
"def create_package(self, **kwargs):\n results = self.api.action.package_create(**kwargs)\n ... | [
"0.664372",
"0.6378287",
"0.6274833",
"0.6235504",
"0.62233025",
"0.62112504",
"0.61472887",
"0.6116683",
"0.6106578",
"0.6072149",
"0.6033826",
"0.6025865",
"0.60145664",
"0.6013302",
"0.60074437",
"0.5996898",
"0.5982463",
"0.59394276",
"0.59046775",
"0.5891099",
"0.5850441... | 0.57937473 | 27 |
Called before anything else, i.e. just after installer controller creation. Return value is ignored. | def pre_installation(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepareController(self):\n pass",
"def preRunSetup(self):\n self.logDesc(\"Pre Run Setup\") \n self.verifyCurrentUser(userRole='Administrator', loginAsUser=True)",
"def preRunSetup(self):\n self.logDesc(\"Pre Run Setup\") \n self.verifyCurrentUser(userRole='Ad... | [
"0.69888854",
"0.6657627",
"0.6657627",
"0.65865713",
"0.64082533",
"0.6388744",
"0.6384215",
"0.6347374",
"0.63209623",
"0.6310592",
"0.6240077",
"0.62371147",
"0.62121433",
"0.6202042",
"0.619813",
"0.61480397",
"0.61330086",
"0.6025088",
"0.6025088",
"0.60231227",
"0.60074... | 0.71761113 | 0 |
Return a list of package IDs from the given list of package IDs. Every returned package ID must be in the installable package storage. | def preprocess_raw_pkg_ids(self, raw_pkg_ids):
return raw_pkg_ids | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_packages(self, package_ids):\n return [self.get_package(package_id) for package_id in package_ids]",
"def list_package_ids(self):\n raise NotImplementedError",
"def get_all_package_ids(self):\n return self._package_cache.keys()",
"def BuildIdsPaths(package_paths):\n\n build_ids_... | [
"0.7364979",
"0.7235984",
"0.6563376",
"0.6440611",
"0.63969654",
"0.61363554",
"0.59568906",
"0.59266436",
"0.5838303",
"0.57976454",
"0.57939595",
"0.5681225",
"0.56639105",
"0.56542856",
"0.5640473",
"0.5615153",
"0.5544031",
"0.5539764",
"0.5531911",
"0.55237174",
"0.5521... | 0.62428546 | 5 |
Return a list of package from the given list of packages. | def preprocess_raw_pkgs(self, raw_installable_pkgs):
for installable_pkg in raw_installable_pkgs:
installable_pkg.pkg_info['explicit_install'] = True
return raw_installable_pkgs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_packages_list(packages: list = [], **kwargs) -> list:\n\n response = ca_client.list_packages(\n domain=domain,\n domainOwner=domain_owner,\n repository=repository,\n format=lang_format,\n **kwargs\n )\n if \"nextToken\" in response:\n packages = get_packag... | [
"0.75616795",
"0.745376",
"0.7141492",
"0.69627184",
"0.6918363",
"0.689751",
"0.6887808",
"0.68198246",
"0.6819392",
"0.66968155",
"0.6656828",
"0.66327983",
"0.6632158",
"0.6531161",
"0.6528741",
"0.65256906",
"0.6519611",
"0.65063256",
"0.6493329",
"0.6492118",
"0.6467504"... | 0.0 | -1 |
Return a list of remote file from the given list of remote files. | def preprocess_raw_remote_files(self, raw_remote_files):
return [xfile for xfile in raw_remote_files if not xfile.exists()] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_files(target_files, config):\n out = []\n find_fn = _find_file(config)\n for fname_in in target_files.keys():\n if isinstance(fname_in, (list, tuple)):\n fnames = fname_in\n else:\n fnames = fname_in.split(\";\")\n for fname in fnames:\n remote... | [
"0.7237889",
"0.6767547",
"0.66274375",
"0.65912855",
"0.65586805",
"0.6552874",
"0.6420708",
"0.6325109",
"0.6185326",
"0.616658",
"0.6161692",
"0.61429477",
"0.6124814",
"0.61134636",
"0.6096036",
"0.6086759",
"0.60865915",
"0.60829717",
"0.6061942",
"0.60608625",
"0.603315... | 0.67033446 | 2 |
Called before any files have downloaded. | def pre_download(self, remote_files):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def download_and_prepare(self):\n self._download_and_prepare()",
"def download_files(self):",
"def pre_download(self):\n while not os.path.exists(self.file_path):\n time.sleep(1)\n\n if self.downloader.file_size != 0:\n # Waits %1 of the total download\n percen... | [
"0.72078025",
"0.6953876",
"0.6938813",
"0.6892764",
"0.6278536",
"0.60983944",
"0.60776293",
"0.59928954",
"0.59894645",
"0.59894645",
"0.59813267",
"0.5980656",
"0.5966963",
"0.59472805",
"0.5930741",
"0.59225214",
"0.58397645",
"0.58169204",
"0.57641727",
"0.57575905",
"0.... | 0.80088097 | 0 |
Called to download the next file. | def download_file(self, remote_file):
remote_file.download() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def next_file(self):\n raise NotImplementedError()",
"def download_files(self):",
"def setNextFile(self):\n\n if (self.nReadBlocks >= self.processingHeaderObj.dataBlocksPerFile):\n self.nReadFiles=self.nReadFiles+1\n if self.nReadFiles > self.nTotalReadFiles:\n ... | [
"0.7292811",
"0.7247551",
"0.67648876",
"0.6716271",
"0.66955405",
"0.6679946",
"0.66258854",
"0.6596123",
"0.6596123",
"0.65185505",
"0.65049696",
"0.6477158",
"0.6471547",
"0.64661497",
"0.64401084",
"0.642619",
"0.6409882",
"0.6366054",
"0.63562936",
"0.635614",
"0.6333223... | 0.58904463 | 62 |
Called after every files have been downloaded. | def post_download(self, remote_files):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def download_finish(self, cloud_file):",
"def pre_download(self, remote_files):\n pass",
"def download_files(self):",
"def _finalize(self):\n if self.url and self.url.startswith('file://'):\n self.parse_external_files(self.url[7:])\n Media._finalize(self)",
"def download_fil... | [
"0.6957989",
"0.6865277",
"0.68242747",
"0.64642113",
"0.64255536",
"0.64033055",
"0.62918645",
"0.62449217",
"0.62424684",
"0.62129873",
"0.62109494",
"0.62088096",
"0.6166017",
"0.616356",
"0.6145047",
"0.6114954",
"0.6033107",
"0.6015093",
"0.59706825",
"0.5961392",
"0.594... | 0.7216123 | 0 |
Called before the installation of any pkg. | def pre_install(self, installable_pkgs):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pre_install_pkg(self, installable_pkg):\n pass",
"def pre_installation(self):\n pass",
"def post_install(self, installable_pkgs):\n pass",
"def post_install_pkg(self, installable_pkg):\n pass",
"def _install(self):\n\n pass",
"def do_post_install(self, context):\n ... | [
"0.87274486",
"0.8490351",
"0.78138494",
"0.76809055",
"0.7401921",
"0.7185641",
"0.7014699",
"0.7007921",
"0.68065137",
"0.6684582",
"0.6648925",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6534111",
"0.65294236",
"0.6491212",
"0.6484541",
"0.64816105... | 0.86834514 | 1 |
Called before the installation of the given installable pkg. | def pre_install_pkg(self, installable_pkg):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pre_install(self, installable_pkgs):\n pass",
"def post_install_pkg(self, installable_pkg):\n pass",
"def post_install(self, installable_pkgs):\n pass",
"def pre_installation(self):\n pass",
"def setPkgRequired(self, *args):\n return _libsbml.SBMLDocument_setPkgRequir... | [
"0.803951",
"0.79661417",
"0.72544426",
"0.7061348",
"0.6615395",
"0.645456",
"0.63259906",
"0.62912256",
"0.6285924",
"0.62740517",
"0.625301",
"0.62484384",
"0.6227197",
"0.6225595",
"0.6215587",
"0.6126311",
"0.6083534",
"0.60764074",
"0.5963906",
"0.59445024",
"0.5924112"... | 0.89542097 | 0 |
Called after the successful installation of the given installable pkg. | def post_install_pkg(self, installable_pkg):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post_install(self, installable_pkgs):\n pass",
"def pre_install_pkg(self, installable_pkg):\n pass",
"def do_post_install(self, context):\n pass",
"def notify_add_package(self, pkg):\n ver_key = (pkg.category, pkg.package)\n s = set(self.versions.get(ver_key, ()))\n ... | [
"0.7332126",
"0.69622064",
"0.6393076",
"0.60962796",
"0.5933556",
"0.58876604",
"0.58322257",
"0.58148694",
"0.5752",
"0.554155",
"0.5408007",
"0.5398204",
"0.53647107",
"0.5351951",
"0.5319673",
"0.52867943",
"0.5283457",
"0.52370936",
"0.5234688",
"0.5212532",
"0.52116287"... | 0.8569286 | 0 |
Called after the successful installation of all pkg. | def post_install(self, installable_pkgs):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post_install_pkg(self, installable_pkg):\n pass",
"def do_post_install(self, context):\n pass",
"def post_installation(self, exc_value):\n pass",
"def pre_install(self, installable_pkgs):\n pass",
"def pre_install_pkg(self, installable_pkg):\n pass",
"def _install(s... | [
"0.83991206",
"0.7399972",
"0.7169786",
"0.69973654",
"0.6994343",
"0.6681931",
"0.657458",
"0.6570379",
"0.65510577",
"0.64301735",
"0.6408434",
"0.63056946",
"0.6250174",
"0.6222582",
"0.61908776",
"0.61649483",
"0.6062687",
"0.6025747",
"0.6022049",
"0.599792",
"0.5966197"... | 0.8408907 | 0 |
Called after anything else (will be called if pre_installation returned successfully) exc_value is None if no error, else the exception value | def post_installation(self, exc_value):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exc_handler(self, exc_type, exc, *args) -> None:\n self.exception = exc\n self.exit_code = 1",
"def on_failure(self, exc: BaseException) -> None:",
"def postcondition(self, result, exc_info, *args, **kwargs):\n pass",
"def pre_setup(self) -> None:\n if self.__setup_done:\n ... | [
"0.62841517",
"0.62787837",
"0.6137501",
"0.5973818",
"0.5940887",
"0.58668447",
"0.58472353",
"0.5836734",
"0.5826562",
"0.5807436",
"0.5798474",
"0.57931894",
"0.57608753",
"0.5755618",
"0.5744285",
"0.57340395",
"0.57157147",
"0.5701963",
"0.5669499",
"0.566829",
"0.564802... | 0.8339836 | 0 |
Return the list of tuple (installed pkg, installable pkg) to upgrade from the list of (installed pkg, installable pkg) tuple that have a different version than their installable counterpart. | def preprocess_raw_upgrade_list(self, raw_upgrade_list):
# By default, upgrade all package that are not in sync, which is
# not what you want to do for more evolved package management
return raw_upgrade_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compare_package_lists(manifest, installed):\n\n uninstalled = [x for x in manifest if x not in installed]\n\n # == comm -23\n also_installed = [x for x in installed if x not in manifest]\n\n # 'easiest' solution\n # print \"apt-get remove -y %s\" % (' '.join(uninstalled))\n # print \"apt-get ... | [
"0.65186965",
"0.6409755",
"0.62714106",
"0.62447596",
"0.6222031",
"0.6134092",
"0.6092698",
"0.60819024",
"0.60146976",
"0.5998767",
"0.59756505",
"0.5935078",
"0.5915402",
"0.5899426",
"0.58644897",
"0.5856976",
"0.5855966",
"0.58493674",
"0.58337134",
"0.5801425",
"0.5791... | 0.54904187 | 45 |
From the list of known to be upgraded pkgs, return a list of tuple (installed_pkg, [], [])) such that both list doesn't contains the pkg of the installed pkg. Also, if a new package to install is found in more than in one list, it will be discard in the later list. | def preprocess_upgrade_list(self, upgrade_list):
return [(ed_pkg, able_pkg, [], []) for (ed_pkg, able_pkg) in upgrade_list] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_installed_packages() -> List['Package']:\n repo_packages_names = set(expac(\"-S\", ['n'], []))\n\n # packages the user wants to install from aur\n aur_names = packages_from_other_sources()[0]\n repo_packages_names -= aur_names\n\n installed_packages_names = set(expac(\"-Q... | [
"0.68577033",
"0.66643363",
"0.63001037",
"0.6242023",
"0.6221818",
"0.61724806",
"0.611967",
"0.6084042",
"0.608403",
"0.60733235",
"0.60682243",
"0.6050123",
"0.6046999",
"0.60445344",
"0.60400933",
"0.599542",
"0.59662074",
"0.5938913",
"0.5904515",
"0.5884107",
"0.5870722... | 0.7349749 | 0 |
Called before the installation of any pkg. | def pre_upgrade(self, upgrade_specs):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pre_install_pkg(self, installable_pkg):\n pass",
"def pre_install(self, installable_pkgs):\n pass",
"def pre_installation(self):\n pass",
"def post_install(self, installable_pkgs):\n pass",
"def post_install_pkg(self, installable_pkg):\n pass",
"def _install(self):\... | [
"0.87274486",
"0.86834514",
"0.8490351",
"0.78138494",
"0.76809055",
"0.7401921",
"0.7185641",
"0.7014699",
"0.7007921",
"0.68065137",
"0.6684582",
"0.6648925",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6547911",
"0.6534111",
"0.65294236",
"0.6491212",
"0.6484541... | 0.0 | -1 |
Builds the Tensorflow graph. | def _build_model(self):
# Placeholders for our input
# Our input are MEMORY_LENGTH frames of shape 5, 5 each
self.X_pl = tf.placeholder(shape=[None, 5, 5, MEMORY_LENGTH], dtype=tf.uint8, name="X")
# The TD target value
self.y_pl = tf.placeholder(shape=[None], dtype=tf.float32, n... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_tf_graph(self):\n raise NotImplementedError",
"def build_graph(self):\n\t\tself._create_placeholders()\n\t\tself._create_embedding()\n\t\tself._create_recurrent_layers()\n\t\tself._create_de_embedding()\n\t\tself._create_loss()\n\t\tself._create_optimizer()\n\t\tself._create_summaries()",
"def bui... | [
"0.8258779",
"0.8072614",
"0.8026864",
"0.7975154",
"0.7965664",
"0.7960153",
"0.79411334",
"0.7920188",
"0.79135257",
"0.7908656",
"0.7888244",
"0.78879184",
"0.78817815",
"0.7828711",
"0.7801996",
"0.77979594",
"0.77831817",
"0.7782756",
"0.77774066",
"0.7767193",
"0.776609... | 0.6579968 | 79 |
Copies the model parameters of one estimator to another. | def copy_model_parameters(sess, estimator1, estimator2):
e1_params = [t for t in tf.trainable_variables() if t.name.startswith(estimator1.scope)]
e1_params = sorted(e1_params, key=lambda v: v.name)
e2_params = [t for t in tf.trainable_variables() if t.name.startswith(estimator2.scope)]
e2_params = sorte... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def copy_para(from_model, to_model):\n for i, j in zip(from_model.trainable_weights, to_model.trainable_weights):\n j.assign(i)",
"def sync_parameters(self, model: nn.Module) -> None:\n # before ema, copy weights from orig\n avg_param = (\n itertools.chain(self.... | [
"0.6655023",
"0.6186064",
"0.6186064",
"0.61854655",
"0.6052574",
"0.60511726",
"0.60407877",
"0.5963009",
"0.5963009",
"0.59216297",
"0.59045017",
"0.58989644",
"0.589293",
"0.58706653",
"0.5860739",
"0.58496034",
"0.58299047",
"0.58268255",
"0.5764856",
"0.57535136",
"0.574... | 0.7852629 | 1 |
Creates an epsilongreedy policy based on a given Qfunction approximator and epsilon. | def make_epsilon_greedy_policy(estimator, nA):
def policy_fn(sess, observation, epsilon):
A = np.ones(nA, dtype=float) * epsilon / nA
q_values = estimator.predict(sess, np.expand_dims(observation, 0))[0]
print(f'q_values: {q_values}')
best_action = np.argmax(q_values)
A[best_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def createEpsilonGreedyPolicy(Q, epsilon, num_actions):\n\n def policyFunction(state):\n Action_probabilities = np.ones(num_actions,\n dtype=float) * epsilon / num_actions\n\n best_action = np.argmax(Q[state])\n Action_probabilities[best_action] += (1.0... | [
"0.78010213",
"0.7771446",
"0.7609632",
"0.7590617",
"0.75758374",
"0.75702316",
"0.7455431",
"0.7435255",
"0.72975755",
"0.70651025",
"0.7052984",
"0.6743078",
"0.6650919",
"0.65363425",
"0.6319062",
"0.62520564",
"0.62376964",
"0.6202657",
"0.61382174",
"0.6107149",
"0.6052... | 0.7177619 | 9 |
QLearning algorithm for offpolicy TD control using Function Approximation. Finds the optimal greedy policy while following an epsilongreedy policy. | def empathic_deep_q_learning(sess,
env,
q_estimator,
target_estimator,
empathic_estimator,
num_episodes,
replay_memory_size=500000,
replay_memory_init_size=50000,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def policies(self, QTable, epsilon, state, next_states, action_to_do): # Inspiration from https://www.geeksforgeeks.org/q-learning-in-python/?fbclid=IwAR1UXR88IuJBhhTakjxNq_gcf3nCmJB0puuoA46J8mZnEan_qx9hhoFzhK8\r\n num_actions = 5 # 5 actions-value, [moved_out, into_goal, send_opp_home, send_self_home, move... | [
"0.77068037",
"0.6990565",
"0.69714993",
"0.6962928",
"0.69604427",
"0.6906738",
"0.6886918",
"0.6791934",
"0.6698574",
"0.6691974",
"0.66405153",
"0.65949064",
"0.65601516",
"0.6510425",
"0.64388055",
"0.6399038",
"0.6367646",
"0.63593113",
"0.63479406",
"0.6339692",
"0.6325... | 0.0 | -1 |
trim nonlinear aircraft with angle of attack and elevator. | def trim_alpha_de_nonlinear(speed, altitude, gamma, n=1, tol=1e-1):
def obj(x):
out = x[2]
return out
def alpha_stab(x):
u = array([0, x[1], 0, x[2]])
x = array([speed * cos(x[0]), 0, speed * sin(x[0]), 0, x[0] + deg2rad(gamma), 0, 0, 0, 0, 0, 0, altitude])
x_dot = mode... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def coll_trim(th):\n lam = TipLoss(lamInit, th)\n AoA = th - lam / r\n dCL, dCD = PolarLookup(AoA)\n dCT = 0.5 * solDist * (dCL*np.cos(lam/r)-dCD*np.sin(lam/r))* r ** 2\n # dCT = 0.5 * solDist * dCL * r ** 2\n CT = np.trapz(dCT, r)\n\n return CT, dCT, dCL, dCD, lam,... | [
"0.57309926",
"0.5562074",
"0.54877454",
"0.53574204",
"0.53017944",
"0.52877146",
"0.522877",
"0.52124757",
"0.51419944",
"0.51196784",
"0.51184297",
"0.50799096",
"0.50414336",
"0.49780405",
"0.49701124",
"0.49640945",
"0.49638167",
"0.49542117",
"0.49492422",
"0.49434245",
... | 0.48222995 | 28 |
LSTM input Generates a tensor that corresponds an LSTM input sequence from a two dimensional table (rows = samples, columns = variables) | def generate_lstm_input_sequence(
input_tensor: Tensor,
seq_len: int,
window_shift_step_size: int
):
num_iterations = (seq_len // window_shift_step_size)
num_vars = input_tensor.shape[1]
tensor_list = []
for i in range(num_iterations):
# calculate how much the window has to be shifte... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def LSTM(inputs, dim, seq_len, name):\r\n with tf.name_scope(name) as scope:\r\n cell = tf.contrib.rnn.LSTMCell(num_units=dim)\r\n hidden_states, cell_states = tf.nn.dynamic_rnn(cell, inputs=inputs, sequence_length=seq_len, dtype=tf.float32, scope=name)\r\n\r\n return hidden_states, cell_states... | [
"0.671775",
"0.6443419",
"0.63130444",
"0.6284584",
"0.62595385",
"0.6248711",
"0.61987054",
"0.61636215",
"0.6117673",
"0.6102052",
"0.6073893",
"0.6053332",
"0.60326666",
"0.5990912",
"0.5978899",
"0.59719133",
"0.5913929",
"0.58949786",
"0.58881134",
"0.5882032",
"0.587783... | 0.66498864 | 1 |
Gets the maximum sequence bounds of non idle time Machines shows default values at the beginning and end of the operations; this functions returns the ids of the longest sequence that is not operating with the default values. Note that you cannot just remove all default values, essentially because order matters and the... | def get_id_bounds(
values: Tensor,
default_value: float
):
# get all values that are not default ones
default_value_idx = (values == default_value).nonzero()[:, 0]
# get the longest sequence without interruption
# to do this, get the difference of the above ids
diff = default_value_idx[1:] -... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def return_loose_bounds(maxlum=None):\n return[(None,None), (10**-6, None), (2., 350),\n (None, -10**-6), (None, None)]",
"def longest_sequence(start=1, end=1000000):\n\n max_length = 0\n max_start_value = 0\n\n # generate sequence for each value\n for i in range(start, end):\n cu... | [
"0.5749199",
"0.5637835",
"0.5553669",
"0.5540054",
"0.5517348",
"0.54871017",
"0.547557",
"0.5464125",
"0.54230356",
"0.53948283",
"0.53876203",
"0.53298086",
"0.5300341",
"0.52418303",
"0.5241372",
"0.52193195",
"0.5216842",
"0.52015424",
"0.520039",
"0.51883274",
"0.516819... | 0.7332722 | 0 |
Pad sequences that are too short | def padding_tensor(sequences, max_length=1000000):
# get the number of sequences
num = len(sequences)
# get the maximum length (clip too long sequences)
max_len = min(max([s.shape[0] for s in sequences]), max_length)
# define new output dimensions
out_dims = (num, max_len, *sequences[0].shape[1:... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pad(seq, n):\n return",
"def _pad_shorter(sequence: str) -> str:\n return sequence.ljust(3, \"X\")",
"def pad_to_max_length(self, sequence):\n sequence = sequence[:self.max_seq_length]\n n = len(sequence)\n #return sequence + ['[PAD]'] * (self.max_seq_length - n)\n ret... | [
"0.8076515",
"0.79440534",
"0.78587586",
"0.76918006",
"0.76324975",
"0.747446",
"0.7422067",
"0.7331402",
"0.7119049",
"0.70603657",
"0.69992334",
"0.6998201",
"0.698124",
"0.6966674",
"0.6966566",
"0.69475687",
"0.68809956",
"0.6873199",
"0.6871419",
"0.68637884",
"0.685601... | 0.6648124 | 33 |
Ensure that sequence is a numeric array. | def ensure_numeric(A, typecode=None):
if isinstance(A, basestring):
msg = 'Sorry, cannot handle strings in ensure_numeric()'
raise Exception(msg)
if typecode is None:
if isinstance(A, numpy.ndarray):
return A
else:
return numpy.array(A)
else:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_number_sequence(self, seq, n):\n if seq is None:\n return np.zeros(n)\n if len(seq) is n:\n try:\n l = [float(e) for e in seq]\n except ValueError:\n raise ValueError(\"One or more elements in sequence <\" + repr(seq) + \"> ... | [
"0.7163305",
"0.7004887",
"0.6348093",
"0.6331678",
"0.62893003",
"0.6272969",
"0.62521833",
"0.6226475",
"0.6204775",
"0.6202429",
"0.6157295",
"0.6149922",
"0.6109198",
"0.6074564",
"0.6060793",
"0.60362536",
"0.60159546",
"0.5984151",
"0.5964977",
"0.59511167",
"0.5949249"... | 0.69070625 | 2 |
Cumulative Normal Distribution Function Input | def cdf(x, mu=0, sigma=1, kind='normal'):
msg = 'Argument "kind" must be either normal or lognormal'
if kind not in ['normal', 'lognormal']:
raise RuntimeError(msg)
if kind == 'lognormal':
return cdf(numpy.log(x), mu=mu, sigma=sigma, kind='normal')
arg = (x - mu) / (sigma * numpy.sqrt... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def normal_cdf(x: torch.Tensor) -> torch.Tensor:\n return torch.distributions.Normal(0, 1.0).cdf(x)",
"def cumulative_normal_distribution(z):\n from math import exp\n\n b1 = +0.319381530\n b2 = -0.356563782\n b3 = +1.781477937\n b4 = -1.821255978\n b5 = +1.330274429\n p = +0.2316419\n ... | [
"0.78193784",
"0.7713642",
"0.74481666",
"0.73976594",
"0.7385765",
"0.7318204",
"0.7032038",
"0.6768214",
"0.6707595",
"0.67005926",
"0.6619152",
"0.65774465",
"0.65379506",
"0.65120757",
"0.64703155",
"0.64342105",
"0.64087766",
"0.63950425",
"0.63945556",
"0.6386111",
"0.6... | 0.5889642 | 80 |
Creates a list of strings indicating available devices to test on. Checks for CUDA devices, primarily. Assumes CPU is always available. | def get_test_devices():
# Assumption: CPU is always available
devices = ['cpu']
if torch.cuda.is_available():
devices.append('cuda')
return devices | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_test_devices():\n devices = [\"cpu\"]\n if torch.cuda.is_available():\n devices.append(\"cuda\")\n return devices",
"def get_available_devices():\n executable_path = os.path.join(os.path.dirname(__file__), 'build')\n try:\n num_devices = int(subprocess.check_output(\n ... | [
"0.79648924",
"0.779924",
"0.74314016",
"0.742399",
"0.72089636",
"0.7203299",
"0.7203299",
"0.71994233",
"0.71461236",
"0.71363676",
"0.7131888",
"0.7081655",
"0.69478077",
"0.6909545",
"0.6909545",
"0.68895745",
"0.6862883",
"0.6847569",
"0.6778976",
"0.67201084",
"0.671292... | 0.8175212 | 0 |
Defines the basic properties of the dataset reader. | def __init__(self, language, dataset_name):
self._language = language
self._dataset_name = dataset_name
# TODO: Maybe the paths should be passed as parameters or read from a configuration file.
self._trainset_path = "data/raw/{}/{}_Train.tsv".format(language.lower(), dataset_name)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def readProperties(self):\r\n print('not yet implemented')",
"def __init__(self, resource, read_header=True, dialect=None, encoding=None,\r\n detect_header=False, sample_size=200, skip_rows=None,\r\n empty_as_null=True,fields=None, **reader_args):\r\n self.read_heade... | [
"0.59841424",
"0.5928963",
"0.5784238",
"0.57840806",
"0.57327986",
"0.57229203",
"0.57107365",
"0.5557109",
"0.5537866",
"0.5524832",
"0.54842496",
"0.5471898",
"0.5462397",
"0.5455518",
"0.5455518",
"0.5455518",
"0.54534966",
"0.5443496",
"0.54328513",
"0.54135853",
"0.5410... | 0.0 | -1 |
list. Getter method for the training set. | def train_set(self):
if self._trainset is None: # loads the data to memory once and when requested.
trainset_raw = self.read_dataset(self._trainset_path)
trainset_spacy = self.read_spacy_pickle(self._trainset_spacy_path)
if trainset_raw is None and trainset_spacy is None:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def training_set(self):\n return self._training_set",
"def getTrainSet(self):\r\n return self.fTrainData",
"def get_train_examples(self):\n raise NotImplementedError()",
"def getTrainingData(self):\n raise NotImplementedError",
"def ytrain(self,)->list:",
"def train_data(self)... | [
"0.7853087",
"0.7833995",
"0.7162848",
"0.7011273",
"0.69807905",
"0.68640167",
"0.6779734",
"0.67625207",
"0.67128795",
"0.6642267",
"0.66175365",
"0.6588874",
"0.65435916",
"0.6489735",
"0.64823407",
"0.64677966",
"0.64677536",
"0.64677536",
"0.64677536",
"0.64677536",
"0.6... | 0.63743335 | 26 |
list. Getter method for the development set. | def dev_set(self):
if self._devset is None: # loads the data to memory once and when requested.
devset_raw = self.read_dataset(self._devset_path)
devset_spacy = self.read_spacy_pickle(self._devset_spacy_path)
if devset_raw is None and devset_spacy is None:
# ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getList(self):\n\treturn self.list",
"def getList(self):\n pass",
"def list(self):\n return self._get_list()",
"def getList(self):",
"def getList(self):",
"def getList(self):\n return self.list",
"def _list(self):\n raise NotImplementedError",
"def getList(self):\n ... | [
"0.73627645",
"0.71417344",
"0.71412355",
"0.70894736",
"0.70894736",
"0.70750684",
"0.7051862",
"0.6963677",
"0.68805003",
"0.68201923",
"0.66853786",
"0.665861",
"0.665861",
"0.65717626",
"0.65602267",
"0.65473986",
"0.6545399",
"0.65362054",
"0.65142536",
"0.6490376",
"0.6... | 0.0 | -1 |
list. Getter method for the test set. | def test_set(self):
if self._testset is None: # loads the data to memory once and when requested.
testset_raw = self.read_dataset(self._testset_path)
testset_spacy = self.read_spacy_pickle(self._testset_spacy_path)
self._testset = pd.concat([testset_raw, testset_spacy], axis... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getTestSet(self):\r\n return self.fTestData",
"def test_list(self):\n pass",
"def test_list(self):\n pass",
"def test_get_list(self):\n pass",
"def test_setlist(self):\n self.assertEqual(self.show.setlist, [])",
"def getList(self):",
"def getList(self):",
"def _... | [
"0.7663302",
"0.75377935",
"0.75377935",
"0.74939066",
"0.7442792",
"0.7260937",
"0.7260937",
"0.7233362",
"0.71777934",
"0.7144615",
"0.708761",
"0.7086548",
"0.7085815",
"0.69690573",
"0.6968609",
"0.68739635",
"0.68606836",
"0.68267024",
"0.6802899",
"0.6769468",
"0.675869... | 0.0 | -1 |
Read the dataset file. | def read_dataset(self, file_path):
try:
with open(file_path, encoding="utf-8") as file:
fieldnames = ['hit_id', 'sentence', 'start_offset', 'end_offset', 'target_word', 'native_annots',
'nonnative_annots', 'native_complex', 'nonnative_complex', 'gold_lab... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def open_file(path):\n input_file = os.path.join(path)\n with open(input_file) as f:\n dataset = f.read()\n return dataset",
"def read_data(self, file_path):\n raise NotImplementedError('should be overridden with specific data reader')",
"def read_data_file(self, file_name: str = \"\") -... | [
"0.7127761",
"0.7097751",
"0.6955917",
"0.69546825",
"0.6948491",
"0.691113",
"0.691113",
"0.68785495",
"0.68783164",
"0.6860642",
"0.6858185",
"0.681202",
"0.6805915",
"0.6805572",
"0.68029416",
"0.6799209",
"0.67829126",
"0.6773895",
"0.6773895",
"0.6763192",
"0.674889",
... | 0.6905276 | 7 |
Read the pickled spacy objects | def read_spacy_pickle(self, file_path):
vocab = self.nlp.vocab
try:
file = open(file_path, "rb")
# putting the spacy doc in a single-item list to avoid pandas splitting it up
spacy_objects = [[Doc(vocab).from_bytes(x)] for x in pickle.load(file)]
file.cl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_dictionary():\n # model = 'en_core_web_sm'\n # model = 'en_core_web_md'\n # model = 'en_core_web_lg'\n model = 'en' # Using 'en' instead of 'en_core_web_md', as the latter has many words without vector data. Check!\n print(\"Starting to read the model:\", model)\n # nlp = spacy.cli.down... | [
"0.60844487",
"0.60844284",
"0.59511757",
"0.59002733",
"0.587763",
"0.5824237",
"0.5801722",
"0.5801091",
"0.57834816",
"0.57699907",
"0.5766996",
"0.57638127",
"0.57596767",
"0.57547075",
"0.5739896",
"0.5739467",
"0.57228065",
"0.57223886",
"0.57158464",
"0.5714373",
"0.57... | 0.67977774 | 0 |
Creates an Experiment with totaly artificial data. Experiment has one setup with two modalities, EMG and kin. EMG has four channels, KIN has three channels. Two sessions are "recorded" for two different subjects. All EMG recordings have sampling rate of 20Hz, all KIN recordings sampling rate of 5Hz. | def setup(cls):
cls.logger = logging.getLogger('ModelTestLogger')
cls.logger.setLevel(logging.DEBUG)
s1 = model.Subject('subject1')
s2 = model.Subject('subject2')
cls.experiment = model.Experiment()
cls.experiment.put_subject(s1)
cls.experiment.put_subject(s2)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_exp2(args):\n\n # load data.\n SC = np.load(args.SC)\n sc_lbls = np.load(args.sc_lbls)\n c_lbls = np.load(args.c_lbls)\n b_lbls = np.load(args.b_lbls)\n\n # compute dimensions.\n n = args.n\n m = SC.shape[0]\n k = c_lbls.shape[0]\n l = SC.shape[1]\n t = args.t\n q = a... | [
"0.62235945",
"0.6049082",
"0.6045395",
"0.5995295",
"0.5993515",
"0.5865029",
"0.5863797",
"0.579151",
"0.5732537",
"0.57056975",
"0.56597024",
"0.56380254",
"0.56178087",
"0.56018513",
"0.55858195",
"0.5584628",
"0.5583475",
"0.55769795",
"0.5555405",
"0.55462915",
"0.55410... | 0.7082174 | 0 |
Initialise with repository of choice, default is CMIP6 | def __init__(self, source='cmip6'):
self.source = source
# We keep a dictionary of document sets so each call to getbyname does not need
# to get the document set first, unless that document set has not previously been requested.
self.documents = {} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, repository):\n self.__repo = repository",
"def repo_init(self, repo_id, numpkgs, islocal=False):\n self.send(repo_id, 'repo_init', numpkgs, islocal)",
"def repo_init(_request):\n python = models.Repository.query(models.Repository.name == 'Python').get()\n if python is None:\n... | [
"0.6699109",
"0.64469814",
"0.6162112",
"0.6121241",
"0.6062029",
"0.60173815",
"0.5958106",
"0.59234595",
"0.58981305",
"0.5851899",
"0.5851416",
"0.58101404",
"0.57702166",
"0.5729564",
"0.57086456",
"0.5697416",
"0.5675124",
"0.565054",
"0.5635948",
"0.5585092",
"0.5546062... | 0.0 | -1 |
Get a particular document, given knowledge of it's name and document type | def getbyname(self, name, doctype='experiment'):
if doctype not in self.documents:
self.documents[doctype] = esd.search(self.source, doctype)
return self.documents[doctype].load_document(name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_document_by_name(label, doc_type):\n return Documents.query.filter_by(type=doc_type, label=label).first()",
"def get_document(name):\n document = [d for d in documents if d.name == name]\n if len(document) > 0:\n return document[0]",
"def get_named_document(self, entity, name):\n ... | [
"0.8119024",
"0.7807013",
"0.7141701",
"0.71329045",
"0.6930829",
"0.69083655",
"0.68151665",
"0.6775295",
"0.67580533",
"0.66710275",
"0.666382",
"0.66597706",
"0.6616618",
"0.65856236",
"0.6542822",
"0.652078",
"0.64975977",
"0.6474223",
"0.64734006",
"0.64587903",
"0.64214... | 0.67501426 | 9 |
Get a particular document when you know it's id | def getbyid(self, id):
return esd.retrieve(id) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_document_by_id(document_id):\n return Documents.query.filter_by(id=document_id).first()",
"def get_document(self, docid):\n raise NotImplementedError",
"def obj_get(self, request=None, **kwargs):\n return Document(self.get_collection(request).find_one({\n \"_id\": Object... | [
"0.8036257",
"0.78460073",
"0.7527839",
"0.74206144",
"0.72871727",
"0.72503227",
"0.72271115",
"0.7211136",
"0.7207188",
"0.7205287",
"0.7191581",
"0.716146",
"0.71606684",
"0.71544635",
"0.71252185",
"0.7115029",
"0.7100616",
"0.706832",
"0.70278084",
"0.7019712",
"0.696564... | 0.0 | -1 |
Set up the templates | def _settemplates(self, onecol, twocol):
self.template = """
<table class="f"><tbody>
%s
%s
</tbody></table>
""" % (self.header, onecol)
# This is suitable for two column width.
self.wide_template = """
<table class="f"><tbody>
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_templates(self):\n self.libs[\"template\"] = (\"#libs/templates/include\", None, \"\")\n self[\"CPPPATH\"].append(\"#libs/templates/include\")",
"def setUp(self):\n print \"Setting Up: %s\" % self.id()\n # render the template\n g.render_template(self.template_file,\n ... | [
"0.80348116",
"0.7463657",
"0.7155762",
"0.7095249",
"0.6724418",
"0.6702859",
"0.6654424",
"0.6569718",
"0.6396812",
"0.63617265",
"0.63503236",
"0.63492066",
"0.63473433",
"0.632623",
"0.62927055",
"0.6273522",
"0.6273522",
"0.62619275",
"0.62587327",
"0.6243744",
"0.621850... | 0.5902942 | 40 |
Mixin method. Not implemented in the base class. | def html(self, children, ordering):
raise NotImplementedError | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __call__(self):\r\n raise NotImplementedError('override me')",
"def __call__(self):\n raise NotImplementedError",
"def __call__(self):\n raise NotImplementedError()",
"def __call__( self ):\n pass",
"def __call__(self, *args, **kwargs):\r\n raise NotImplementedError",... | [
"0.789931",
"0.77198046",
"0.7548892",
"0.71948624",
"0.71636724",
"0.71636724",
"0.71636724",
"0.7158493",
"0.7158493",
"0.71576095",
"0.71576095",
"0.7091741",
"0.7085437",
"0.7035599",
"0.7027999",
"0.70000744",
"0.6968931",
"0.6883279",
"0.6883279",
"0.6883279",
"0.688327... | 0.0 | -1 |
Render to html. This should be called by the parent class's html method. | def _html(self, children, wide=False, additional="", ordering='normal'):
def sorter(r):
""" provides a number to sort related in ascending length of description"""
ans = len(r.description)
if additional:
for rr in r.monkey_additional:
an... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def render(self):\r\n super().render()",
"def render(self):\n raise NotImplementedError",
"def render(self):\n raise NotImplementedError()",
"def __html__(self):\n return self.html",
"def render(self):\n pass",
"def render(self):\n pass",
"def render(self):\n ... | [
"0.82992643",
"0.8107857",
"0.8076577",
"0.7906086",
"0.7878678",
"0.7878678",
"0.7878678",
"0.7878678",
"0.7878678",
"0.7878678",
"0.7871989",
"0.78110904",
"0.7726244",
"0.7694776",
"0.75172067",
"0.74649364",
"0.74395216",
"0.74395216",
"0.7385232",
"0.7338748",
"0.7338651... | 0.0 | -1 |
provides a number to sort related in ascending length of description | def sorter(r):
ans = len(r.description)
if additional:
for rr in r.monkey_additional:
ans += len(rr)
return ans | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sort():\n return -1",
"def Order(self) -> int:",
"def _natural_sort_worksheet(x):\n l = re.findall(r\"\\d+$\", x.title)\n if l:\n return int(l[0])\n\n return -1",
"def _wiki_sort_key(doc):\n url = doc['url']\n return 1 if url.startswith('https://en.wikipedia') else -1... | [
"0.6401724",
"0.62728316",
"0.60654205",
"0.60012025",
"0.59754735",
"0.59544206",
"0.59370434",
"0.59157306",
"0.58810264",
"0.58680815",
"0.58301955",
"0.5825593",
"0.57766974",
"0.5709983",
"0.5653453",
"0.560097",
"0.5593121",
"0.555219",
"0.5539747",
"0.5538889",
"0.5534... | 0.6969995 | 0 |
Render to PDF if desired, by first getting the HTML version. | def render(self, output_name, wide=False):
html = self.html(wide)
print 'You can ignore the GLib-Gobject errors (if they occur)'
if wide:
HTML(string=html).write_pdf(
output_name, stylesheets=[CSS(string=esCSS.replace("8.8cm", "18cm"))])
else:
HTM... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def render_as_pdf(self, width, height):\n pass",
"def get_raw_pdf(html_path, pdf_path, width='', height=''):\n debug = False\n if mg.EXPORT_IMAGES_DIAGNOSTIC: debug = True\n try:\n url = html_path.as_uri()\n cmd_make_pdf = 'cmd_make_pdf not successfully generated yet'\n \"\"\... | [
"0.70788",
"0.6738788",
"0.6705874",
"0.6704703",
"0.66870785",
"0.666667",
"0.66463214",
"0.6614933",
"0.66001874",
"0.65993774",
"0.6502286",
"0.6423387",
"0.64061946",
"0.6362002",
"0.63022816",
"0.6281078",
"0.62789476",
"0.6275642",
"0.6163935",
"0.6161958",
"0.6047067",... | 0.6588409 | 10 |
Initialise with an experiment document | def __init__(self, document):
self._settemplates(self.onecol, self.twocol)
assert document.type_key == 'cim.2.designing.NumericalExperiment'
self.doc = document
# In most cases there is only one related mip.
# Handle the edge case here rather than in template.
mips = ''
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, document):\n\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key == 'cim.2.designing.Project'\n self.doc = document\n\n # We will populate the \"mip\" variable with the mip era\n self.mips = 'CMIP6'\n\n self.related = []\n fo... | [
"0.7011294",
"0.69498855",
"0.68237424",
"0.66328037",
"0.66267675",
"0.6497485",
"0.6457093",
"0.6423474",
"0.6372848",
"0.62703747",
"0.6235102",
"0.6179923",
"0.60615146",
"0.6018496",
"0.60152483",
"0.5986631",
"0.5941061",
"0.5928936",
"0.58815664",
"0.5872775",
"0.58648... | 0.67475593 | 3 |
Initialise with a MIP document | def __init__(self, document):
self._settemplates(self.onecol, self.twocol)
assert document.type_key == 'cim.2.designing.Project'
self.doc = document
# We will populate the "mip" variable with the mip era
self.mips = 'CMIP6'
self.related = []
for r in self.doc.r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, doc):\n\n self.doc = doc\n if self.doc.doi:\n self._populate()\n self.populated = True\n else:\n self.populated = False",
"def __init__(self, document):\n self._settemplates(self.onecol, self.twocol)\n assert document.type_key... | [
"0.6678455",
"0.6528227",
"0.61595803",
"0.6156851",
"0.6055568",
"0.5943074",
"0.5899902",
"0.58804005",
"0.5799892",
"0.5787662",
"0.5785426",
"0.57476616",
"0.5745662",
"0.5730278",
"0.5711061",
"0.57024944",
"0.57002866",
"0.56933963",
"0.56916255",
"0.5650309",
"0.564237... | 0.7006556 | 0 |
Intialise with a pyesdoc citation document | def __init__(self, doc):
self.doc = doc
if self.doc.doi:
self._populate()
self.populated = True
else:
self.populated = False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_citation(meta):\n pass",
"def init_doc(self):\n raise NotImplementedError()",
"def main(rc):\n with store_client(rc) as sclient:\n for doc in rc.documents:\n sclient.copydoc(doc)",
"def make_bibtex(self):\n\n\t\t# bib = requests.request('GET', 'http://dx.doi.org/' + self.doi... | [
"0.6251723",
"0.61804336",
"0.61777425",
"0.6167132",
"0.6147496",
"0.610238",
"0.60910994",
"0.6082328",
"0.6082024",
"0.6033947",
"0.6022621",
"0.59620064",
"0.59356797",
"0.59301627",
"0.59235984",
"0.5893333",
"0.5893333",
"0.58614635",
"0.5857272",
"0.58394206",
"0.58379... | 0.6069784 | 9 |
Want a citation string as opposed to a reference. That is, we want author (year), as opposed to author, title, journal, volume pages etc, they go in the bibliography. | def _populate(self):
# Assume the first word is what we want, and we can find well formed years
# This sucks, but will work for these ones.
# Roll on bibtex for citations in the CIM.
citation_detail = self.doc.citation_detail
author = citation_detail.split(',')[0]
match... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_citation(self, type):\n acs_authors = \"; \".join(self.format_authors(\"acs\"))\n # Some articles don't come with pages. :-(\n pages_with_endash = (self.pages.replace(\"-\", \"\\u2013\") if self.pages\n else \"\")\n # Actually, not using quote() genera... | [
"0.728667",
"0.68427366",
"0.68227404",
"0.66083246",
"0.65711814",
"0.6367512",
"0.6355733",
"0.6156344",
"0.61316967",
"0.6123189",
"0.6094504",
"0.6091088",
"0.60479695",
"0.5990289",
"0.59520656",
"0.5934677",
"0.5889932",
"0.5889375",
"0.58619887",
"0.5843337",
"0.581594... | 0.5731608 | 24 |
Load the CMIP6 experiment description. | def __init__(self):
# simple header only necessary for this table of MIPs
self.header = '<tr class="ename"><td colspan="1">{{d.name}} ({{mips}})</td></tr>'
self.mips = 'core MIPS recorded by ES-DOC'
self._settemplates(self.onecol, self.twocol)
r = Repo()
c = r.getbyname(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def testCMIP6(self):\n\n c = CMIP6()\n c.render(self.testoutput[3])\n for r in c.reference_list:\n print r\n print c.nocite",
"def test_load_from_v6(self) -> None:\n self.save_new_valid_exploration(\n 'Exp1', 'user@example.com', end_state_name='End')\n ... | [
"0.58439624",
"0.56758475",
"0.5097717",
"0.5092497",
"0.50313264",
"0.5024391",
"0.5001988",
"0.4999472",
"0.497601",
"0.49601525",
"0.4910506",
"0.48574418",
"0.48146957",
"0.47966567",
"0.47924876",
"0.47363088",
"0.47330913",
"0.4709552",
"0.47017694",
"0.4664248",
"0.465... | 0.0 | -1 |
make sure the html output works | def testHTML(self):
html = self.E.html() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_html_output(self):\n pass",
"def test_error_html_using_patch(self):\n pass",
"def test_prep_fields_called_html_output(self):\n pass",
"def get_html(self):\r\n pass",
"def rawHTMLrendered(self):",
"def __html__(self):\n return self.html",
"def test_error_html_... | [
"0.84040964",
"0.69680446",
"0.6919716",
"0.687463",
"0.6762656",
"0.67169726",
"0.66983867",
"0.65646785",
"0.6555906",
"0.6548506",
"0.6533556",
"0.65294725",
"0.6498341",
"0.6488538",
"0.6470183",
"0.64627945",
"0.6459197",
"0.64506996",
"0.64353263",
"0.64152896",
"0.6384... | 0.7505332 | 1 |
double column mip table | def testDoubleMIP(self):
self.M.render(self.testoutput[2], wide=True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def columns(self):\n \n pass",
"def with_column(self, label, values):\n \n \n \n # self.column_labels.append(label)\n # for i in range(len(self.rows)):\n # self.rows[i].append(values[i]) \n \n new_label = []\n new_rows = []\n ... | [
"0.6182871",
"0.58670676",
"0.5789016",
"0.5669425",
"0.56620336",
"0.5656002",
"0.56398475",
"0.5629267",
"0.5606348",
"0.5552602",
"0.55167204",
"0.54714936",
"0.53963476",
"0.53924036",
"0.53915703",
"0.5390585",
"0.53538346",
"0.5328843",
"0.53097725",
"0.5293032",
"0.528... | 0.5124593 | 44 |
Create a table which names each of the CMIP experiments, adds references for each, and outputs the strings necessary for bibtex to put the references in the reference list. | def testCMIP6(self):
c = CMIP6()
c.render(self.testoutput[3])
for r in c.reference_list:
print r
print c.nocite | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n # simple header only necessary for this table of MIPs\n self.header = '<tr class=\"ename\"><td colspan=\"1\">{{d.name}} ({{mips}})</td></tr>'\n self.mips = 'core MIPS recorded by ES-DOC'\n self._settemplates(self.onecol, self.twocol)\n\n r = Repo()\n ... | [
"0.648065",
"0.5882049",
"0.5557056",
"0.52493566",
"0.52067536",
"0.51254106",
"0.51068753",
"0.50777084",
"0.5076734",
"0.5042223",
"0.50285196",
"0.5026917",
"0.4994443",
"0.49744835",
"0.49690348",
"0.49572152",
"0.4908166",
"0.49010965",
"0.48995394",
"0.48971975",
"0.48... | 0.0 | -1 |
For example purposes, we do not remove the outputs, which is why this is NOtearDown. If you really want to use this for unit tests, rename to tearDown. | def NOtearDown(self):
for f in self.testoutput:
if os.path.exists(f):
os.remove(f) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tearDown(self):\n print('Calling \\'tearDown\\'')",
"def tearDown(self):\n self.logger.info(\"tearDown begin\")\n self.logger.info(\"tearDown end\\n\")",
"def tearDown(self):\n pass\n # teardown called after each test\n # e.g. maybe write test results to some text ... | [
"0.80834854",
"0.7997705",
"0.7978577",
"0.7940476",
"0.7940476",
"0.7940476",
"0.78952134",
"0.78137136",
"0.77655464",
"0.77655464",
"0.77423745",
"0.7723258",
"0.7723258",
"0.7723258",
"0.7717584",
"0.7717088",
"0.77133566",
"0.7675167",
"0.76713866",
"0.76457465",
"0.7645... | 0.80674917 | 1 |
Generate bootstrap replicate of 1D data. | def bootstrap_replicate_1d(data, func):
bs_sample = np.random.choice(data, len(data))
return func(bs_sample) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bootstrap_replicate_1d(data, func):\n bs_sample = np.random.choice(data, len(data))\n return func(bs_sample)",
"def bootstrap_replicate_1d(data, func):\n bs_sample = np.random.choice(data, len(data))\n\n return func(bs_sample)",
"def bootstrap(X):\n return X[np.random.choice(list(range(X.sha... | [
"0.7789665",
"0.77793765",
"0.740078",
"0.7145126",
"0.6915617",
"0.676676",
"0.65354204",
"0.6499645",
"0.6398692",
"0.62889034",
"0.62032557",
"0.6193025",
"0.6095193",
"0.601948",
"0.5998936",
"0.58984625",
"0.5879488",
"0.58694214",
"0.5786773",
"0.5758723",
"0.5742155",
... | 0.78276443 | 0 |
Actualiza los canvas, los pinta en esta ventana, y lleva a cabo el flip para mostrar los cambios | def display(self):
for c in self.canvas.values():
c.update()
self.superficie.blit(c.superficie, c.origen)
pygame.display.flip() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def loop(self, frame):\n self.root = frame\n self.drawUI()\n cv2.imshow('Fotopasca', self.root)",
"def renderizar(self):\n\t\t# Limpiar la pantalla\n\t\tglClear(GL_COLOR_BUFFER_BIT)\n\t\t# Renderizar la escena\n\t\tself.escena.renderizar()\n\t\t# Renderizar los buffers a la pantalla\n\t\tpyg... | [
"0.6508464",
"0.6444371",
"0.6252179",
"0.62192374",
"0.6206115",
"0.6204564",
"0.6166355",
"0.61551905",
"0.6130094",
"0.60961246",
"0.6088001",
"0.60873604",
"0.6068308",
"0.6057062",
"0.60507476",
"0.6043697",
"0.60300726",
"0.60265714",
"0.60210216",
"0.6011016",
"0.60062... | 0.71416545 | 0 |
Setup injections Note that the actual injected current is proportional to dt of the clock So, you need to use the same dt for stimulation as for the model Strangely, the pulse gen in compartment_net refers to firstdelay, etc. | def setupinj(model, delay,width,neuron_pop):
pg = moose.PulseGen('pulse')
pg.firstDelay = delay
pg.firstWidth = width
pg.secondDelay = 1e9
for ntype in neuron_pop.keys():
for num, name in enumerate(neuron_pop[ntype]):
injectcomp=moose.element(name +'/'+model.param_cond.NAME_SOMA)... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup(timestep=None, min_delay=None, max_delay=None, **kwargs):\n global controller\n\n logger.info(\"PACMAN103 (c) 2014 APT Group, University of Manchester\")\n logger.info(\" Release version 2014.4.1 - April 2014\")\n # Raise an exception if no SpiNNaker machine is specified\n ... | [
"0.60317343",
"0.5933767",
"0.59041595",
"0.5831756",
"0.57520694",
"0.57439333",
"0.5739036",
"0.57341063",
"0.5705485",
"0.5683423",
"0.5623893",
"0.5612428",
"0.5607956",
"0.5603607",
"0.5600375",
"0.5599384",
"0.55948526",
"0.55602384",
"0.5559706",
"0.55517477",
"0.55408... | 0.611647 | 0 |
This is a mocked integration function to mimic scipy.integrate.quad. It doesn't do anything other than return some value in the correct format. | def quad(*args, **kwargs):
return (42, 0.001) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sp_integrate_1D ( func , xmin , xmax , *args , **kwargs ) : \n from scipy import integrate\n ##\n result = integrate.quad ( func , xmin , xmax , *args , **kwargs )\n return result[0]",
"def integrate_fun(fun: Callable, low_b: float, upp_b: float) -> float:\n return integrate.quad(fun, low_b... | [
"0.7110071",
"0.66581416",
"0.6405214",
"0.6365771",
"0.6297045",
"0.6241524",
"0.6084706",
"0.5989712",
"0.59154487",
"0.5907231",
"0.59036356",
"0.58382195",
"0.58156836",
"0.5791033",
"0.5787734",
"0.575591",
"0.57527786",
"0.5731111",
"0.560053",
"0.5583005",
"0.55691606"... | 0.5866004 | 11 |
Runs the unit tests without test coverage. | def test():
nose.run() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _run_ci_test():\n _run_install(False)\n _run_coverage_html(False)\n _run_typecheck_xml(False)\n _run_lint(True)",
"def main():\n import coverage\n import nose\n import os\n from shutil import rmtree\n rmtree('./covhtml', ignore_errors=True)\n try:\n os.remove('./.coverage... | [
"0.7740198",
"0.7395665",
"0.73899317",
"0.73077023",
"0.7184236",
"0.71184987",
"0.7116021",
"0.7049126",
"0.695683",
"0.6951264",
"0.6858743",
"0.682145",
"0.6820713",
"0.6819008",
"0.6809791",
"0.67945355",
"0.6780462",
"0.6749489",
"0.671787",
"0.6669164",
"0.66648895",
... | 0.6756857 | 17 |
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