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def make_costate_rates(ham, states, costate_names, derivative_fn): """Make costates.""" costates = [SymVar({'name': lam, 'eom':derivative_fn(-1*(ham), s)}) for s, lam in zip(states, costate_names)] return costates
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def test_store_status_called_without_args(): """Tests that `store_status` calls the callback function without args.""" # Given build_results = create_dummy_build_result() mock_status_callback = MagicMock() # When build_results.store_status(mock_status_callback) # Then mock_status_callb...
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def projection(): """ RESTful CRUD controller """ if deployment_settings.get_security_map() and not s3_has_role("MapAdmin"): unauthorised() tablename = module + "_" + resourcename table = db[tablename] # CRUD Strings ADD_PROJECTION = T("Add Projection") LIST_PROJECTIONS = T("List...
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def parse_segments(segments_str): """ Parse segments stored as a string. :param vertices: "v1,v2,v3,..." :param return: [(v1,v2), (v3, v4), (v5, v6), ... ] """ s = [int(t) for t in segments_str.split(',')] return zip(s[::2], s[1::2])
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def print_attack_results(attack_name: str, attack_results: AttackResult): """ Takes the attack name and the attack result object and prints the results to the console. """ print( f'{attack_name}: \n ' + f'\tRecall: {attack_results.recall:.4f} \t Precision: {attack_results.precision:.4f} ' + ...
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def GetFirstWord(buff, sep=None):#{{{ """ Get the first word string delimited by the supplied separator """ try: return buff.split(sep, 1)[0] except IndexError: return ""
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def setup_periodic_tasks(sender, **kwargs): """ Creates periodic tasks after celery is initialized :param sender: Celery app """ sender.add_periodic_task(30.0, test_domains, name='Every 30s check domains')
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def reset(): """ Resets the visited status of matrix and the operators in the generated AST. """ for m in matrix.visited: m.visited = False matrix.visited = [] matrix.ml = MLContext(matrix.sc) matrix.dml = [] matrix.script = pydml('')
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def modify_bboxs_to_keypoints(json_src, pad_frac=0.1, plot=False): """Goes through any unidentified bboxs, and modifies them to be the bounding box of the joints, + padding. pad_frac is a frac of avg(img height, img width)""" img_dir = r"E:\IIB Project Data\Training data sets\Dogs\youtube_clips_1\output_frames" w...
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def test_np_list_td_corr(): """ correlation: comparing TLS emission corr. (np-list td format) """ # both H and c_ops are time-dependent # calculate emission zero-delay second order correlation, g2[0], for TLS # with following parameters: # gamma = 1, omega = 2, tp = 0.5 # Then: g2(0)...
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def get_table(id: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetTableResult: """ Resource Type definition for AWS::DynamoDB::Table """ __args__ = dict() __args__['id'] = id if opts is None: opts = pulumi.InvokeOptions() if opts.versio...
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def load_perezfornos2012(shuffle=False, subjects=None, figures=None, random_state=0): """Load data from [PerezFornos2012]_ Load the brightness associated with joystick position data described in [PerezFornos2012]_. Datapoints were extracted from Figures 3-7 of the paper. ...
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def add_actor_batch(asset_list): """ Add an actor to the level for each entry in the asset_list each value in the List has to be an `ObjectInfo` instance. """ msg = 'AddActorBatch' for obj_info in asset_list: line = object_info_to_string(obj_info) msg = msg + "\n" + line _lg.debu...
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def filter_tests(tests: Set[str], exclude_tests: List[str]) -> Set[str]: """ Exclude tests which have been denylisted. :param tests: Set of tests to filter. :param exclude_tests: Tests to filter out. :return: Set of tests with exclude_tests filtered out. """ tests = {test for test in tests ...
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def setup_Component_with_parameters(): """ Sets up a Component with parameters and all options used. """ comp = setup_Component_all_keywords() comp._unfreeze() # Need to set up attribute parameters comp.new_par1 = 1.5 comp.new_par2 = 3 comp.new_par3 = None comp.this_par = "test...
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def dpuSetTaskPriority(task, priority): """ Set the priority of one DPU task. Priority range is 0 to 15, 0 has the highest priority. The priority of the task when it was created defaults to 15. """ return pyc_libn2cube.pyc_dpuSetTaskPriority(task, c_int(priority))
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def find_std(arr): """ This function determines the standard deviation of the given array. Args: arr = numpy array for which the standard deviation and means are to be determined Returns: std = standard deviation of the given array mean = mean value of the given array Usage...
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def host(context): """ Bootstrap a machine to be an Ansible target host. :param context: Click context """ context.obj.run_playbook(playbook_relative_path='bootstrap/host', )
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def process(frame: np.ndarray, mask: np.ndarray = None, hsv: np.ndarray = None, *, lower=(20, 100, 100), upper=(35, 255, 255), min_area_prop=1/64, focal_length=208.5): """Find cubes using our vision algorithm. Args ---- frame: the image to process mask: optional array to sto...
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async def key(client, message, **kwargs): """Store your Challonge API key Look for it here: https://challonge.com/settings/developer Optional Argument: key -- the Challonge API key """ if kwargs.get('key') and len(kwargs.get('key')) % 8 != 0: await client.send_message(message.author, '❌ ...
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def required_daemons(instance): """ Return which daemon types are required by the instance """ daemons = [DaemonType.SENSOR] if isinstance(instance.scheduler, DagsterDaemonScheduler): daemons.append(DaemonType.SCHEDULER) if isinstance(instance.run_coordinator, QueuedRunCoordinator): ...
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def get_matching_s3_objects(bucket, prefix="", suffix=""): """ Generate objects in an S3 bucket. Parameters ---------- bucket : str Name of the s3 bucket. prefix : str, optional Only fetch objects whose key starts with this prefix, by default '' suffix : str, optional ...
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def SplitDictOfTensors(t_dict, num_splits): """Splits tensors in `t_dict` evenly into `num_splits` along the 1st dimenion. Args: t_dict: A dictionary of tensors. Each tensor's 1st dimension is the same size. num_splits: A python integer. Returns: A list of dictionaries of tensors, num elements...
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def add_gradient_noise(t, stddev=1e-3, name=None): """ Adds gradient noise as described in http://arxiv.org/abs/1511.06807 [2]. The input Tensor `t` should be a gradient. The output will be `t` + gaussian noise. 0.001 was said to be a good fixed value for memory networks [2]. """ with tf.name_scope(values...
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def _read_csv( reader, header=True, skiprows=0, numeric=True, columns=None, index=None, index_col=None, ): """ Reads a file in as a DataFrame. :param reader: A file handle or filename. :param headers: True if headers are on the first line of data, false otherwise. :param...
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def find_entering_variable( tableau: npt.NDArray, pivot_row_index: int, non_basic_variables: set ) -> Any: """ Finds the non-basic variable which becomes basic after pivoting Parameters ---------- tableau : array A tableau corresponding to a vertex of a Polytope. pivot_row_index : i...
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def activity_final(self): """Find or create a final node in a Activity Note that while UML allows multiple final nodes, use of this routine assumes a single is sufficient. :return: FinalNode for Activity """ final = [a for a in self.nodes if isinstance(a, FinalNode)] if not final: self....
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def contar_caracteres(s): """ FUNÇÃO QUE CONTA OS CARACTERES DE UMA STRING :param s: string a ser contada """ num_of_caracteres = {} for caracter in s: num_of_caracteres[caracter] = (num_of_caracteres.get(caracter, 0) + 1) return num_of_caracteres
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def batch_and_learn(i, lock=threading.Lock()): """Thread target for the learning process.""" global step, stats timings = Timings() while step < args.total_steps: timings.reset() batch, agent_state = get_batch( args, free_queue, full_queue, ...
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def parse_symmetric_morlet_single_scale_parameters( parameter_map ): """ Parses parameters for the single scale, symmetric Morlet wavelet generator. Takes a dictionary of (key, string value)'s and casts the values to the types expected by get_symmetric_morlet_single_scale_transform(). The following...
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def test_get_new_command(): """ Replace the Alt+Space character by a simple space """ assert get_new_command(Command(u"ps -ef | grep foo", "")) == "ps -ef | grep foo"
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def keep_protein_class(data: Union[pd.DataFrame, PandasTextFileReader, Iterator], protein_data: pd.DataFrame, classes: Optional[Union[dict, List[dict]]] = [{'l2': 'Kinase'}, {'l5': 'Adenosine receptor'}], generic_regex: bool = False): """Keep only the data matching desi...
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def load_embeddings(env_config): """Attempt to loads user and movie embeddings from a json or pickle file. Args: env_config: `EnvConfig` class from movie_lens_simulator.py Returns: embedding_dict containing embeddings for movies and users """ path = env_config.embeddings_path embedding_dict = load...
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def reset_db(ctx: click.Context, yes: bool) -> None: """ Wipes all user-created data and resets the database back to its freshly initialized state. """ config = ctx.obj["CONFIG"] if yes: are_you_sure = "y" else: echo_red( "This will drop all data from the Fides databa...
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def find_one_file(directory, pattern): """ Use :func:`find_files()` to find a file and make sure a single file is matched. :param directory: The pathname of the directory to be searched (a string). :param pattern: The filename pattern to match (a string). :returns: The matched pathname (a string). ...
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def image_hosting(): """ 图床 """ # from app.util import file_list_qiniu # imgs = file_list_qiniu() page = request.args.get('page',1, type=int) imgs = Picture.query.order_by(Picture.id.desc()). \ paginate(page, per_page=20, error_out=False) return render_template('admin/image_hosti...
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def get_domain_ip(domain): """ Get the IP for the domain. Any IP that responded is good enough. """ if domain.canonical.ip is not None: return domain.canonical.ip if domain.https.ip is not None: return domain.https.ip if domain.httpswww.ip is not None: return domain.http...
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def shutdown(exit_code=0) -> None: """ Safely close down the ingress application. :param exit_code: raise a system exit with the provided exit code. Defaults to 0. """ LOG.info('Shutting Down.') get_singleton_instance(tweepy.Stream).disconnect() sys.exit(exit_code)
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def create_frame(i): """Helper function to create snapshot objects.""" snap = gsd.hoomd.Snapshot() snap.configuration.step = i + 1 return snap
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def BPR_Loss(positive : torch.Tensor, negative : torch.Tensor) -> torch.Tensor: """ Given postive and negative examples, compute Bayesian Personalized ranking loss """ distances = positive - negative loss = - torch.sum(torch.log(torch.sigmoid(distances)), 0, keepdim=True) return loss
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def _add_line_rectangle_ellipse(layer, event, data, shape_type): """Helper function for adding a a line, rectangle or ellipse.""" # on press # Start drawing rectangle / ellipse / line layer.add(data, shape_type=shape_type) layer.selected_data = {layer.nshapes - 1} layer._value = (layer.nshapes ...
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def gen_segment(curr_img, curr_predictor, try_bools = [False, False], out_trk = None): """Apply different methods (see try_bools) iteratively to try to segment a single shot (non-ALC) image. Because image source is not a mosaic, extent jittering (zooming in and out) is ...
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def test_tips(): """Test module tips.py by downloading tips.csv and testing shape of extracted data has 244 rows and 7 columns """ test_path = tempfile.mkdtemp() x_train, metadata = tips(test_path) try: assert x_train.shape == (244, 7) except: shutil.rmtree(test_path) raise()
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async def test_relays_stop(control_motors_relays, hass, lcn_connection): """Test the relays cover stops.""" states = [MotorStateModifier.NOCHANGE] * 4 states[0] = MotorStateModifier.STOP state = hass.states.get("cover.cover_relays") state.state = STATE_CLOSING # command failed control_moto...
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def query(url): """Send the query url and return the DOM Exception is raised if there is errors""" u = urllib.FancyURLopener(HTTP_PROXY) usock = u.open(url) dom = minidom.parse(usock) usock.close() errors = dom.getElementsByTagName('Error') if errors: e = buildException(errors) raise e return dom
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def expandFilename(filename): """Get the actual file name. Parameters ---------- filename: str A file or directory name. Returns ------- full_file_name: str The real directory name. """ fname = filename done = False count = 0 while not done: tem...
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def reshape_img(image): """ Reshape an image into the form (height, width, channels). :param image (np.array): Loaded image :return: reshaped (np.array): Reshaped image """ img = [] for i in range(3): img_c = np.reshape(image[channel * i:channel * (i + 1)], (image_size, image_size)...
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def clear(): """ Clear all captured images in main code folder. """ files = os.listdir() for file in files: if 'snap' in file: os.remove(file) print('Trash files are clear')
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def test_svd_threshold(): """ Test SVD threshold option of BDCSVD """ with pytest.raises( ValueError, match="The svd_threshold option is available only for non-sparse solvers.", ): # 1D Lattice g = nk.graph.Hypercube(length=20, n_dim=1, pbc=True) # Hilbert sp...
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def RetArquivo(dir: str= '.', prefix_data:bool= True, radical_arquivo:str= 'arq', dig_serial: int= 5, extensao: str= 'dat', incArq: int= 0, ) -> str: """ Gerar nomes de arquivos, com prefixo ...
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def set_levels(lst_all, lst_chiln, lng_level): """Top down recursive setting of nesting levels""" lng_next = lng_level + 1 for id_child in lst_chiln: dct_child = lst_all[id_child] dct_child[ATT_LEVEL] = lng_level lst_next = dct_child[ATT_CHILN] if lst_next: set_levels(lst_all, lst_next, lng_next) return...
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def check_proplist(path, exp_out): """Verify that property list on PATH has a value of EXP_OUT""" props = svntest.tree.get_props([path]).get(path, {}) if props != exp_out: logger.warn("Expected properties: %s", exp_out) logger.warn("Actual properties: %s", props) raise svntest.Failure
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def ThreadPlugin(): """ :return: thread plugin class """ from tests.test_plugins.threads_plugin import ThreadPlugin return ThreadPlugin
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def get_distance(pos_1, pos_2): """Get the distance between two point Args: pos_1, pos_2: Coordinate tuples for both points. """ x1, y1 = pos_1 x2, y2 = pos_2 dx = x1 - x2 dy = y1 - y2 return math.hypot(dx, dy)
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def jsonContentCategories(): """ Parses the Google Cloud content categories from a local txt file and returns a nested dictionary (ugly, but effective). Returns: Dictionary -- Nested dictionary of content categories. """ f = open("google_content_categories.txt", "r") catArr = [] fo...
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def makeFigure(): """ Makes figure 5. """ # Get list of axis objects ax, f = getSetup((10, 10), (4, 3)) figureMaker(ax, *commonAnalyze(list_of_populations, 2), num_lineages=num_lineages) subplotLabel(ax) return f
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def test_is_not_empty_failure(): """ validate_files.py: Run is_not_empty() with bad inputs :raises ValidationException: always, if test is working """ a = [] assert v.is_not_empty(a)
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def preprocess_finance(decompressed_path, X_path, y_path): """Preprocess the Finance dataset for a Lasso problem. Normalization performed: - X with only columns with >= 3 non zero elements, norm-1 columns, and a constant column to fit intercept - y centered and set to std equal to 1 """ n...
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def illust(illustration, directory, allow_duplicates, track): """Download an illustration by URL or ID.""" try: download_image( Client().fetch_illustration(illustration), directory=(Path(directory or Config()["pixi"]["download_directory"])), allow_duplicate=allow_dupl...
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def gauss2D_FIT(xy, x0, y0, sigma_x, sigma_y): """Version of gauss2D used for fitting (1 x_data input (xy) and flattened output). Returns the value of a gaussian at a 2D set of points for the given standard deviation with maximum normalized to 1. The Gaussian axes are assumed to be 90 degrees from e...
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def insert_many(sql, *args): """ 执行SQL语句 :param sql: insert的SQL语句,可含? :param args: insert的SQL语句所对应的值 :return: 最后插入行的主键ID """ return _insert(sql, True, *args)
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def _sub_matches_cl(subs, state_expr, state): """ Checks whether any of the substitutions in subs will be applied to state_expr Arguments: subs: substitutions in tuple format state_expr: target symbolic expressions in which substitutions will be applied state: target symboli...
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def get_full_json(job_id: str = None, textract_api: Textract_API = Textract_API.DETECT, boto3_textract_client=None, job_done_polling_interval=1) -> dict: """returns full json for call, even when response is chunked""" logger.debug(f"get_full_json: job_id: {j...
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def get_time_from_filename(file_name, date_extraction_pattern, date_pattern): """ @param file_name name of the file @param date_extraction_pattern regular expression describing how the date is represented in the filename @param date_pattern """ file_str = os.path.basename(file_name) matches ...
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def calc_sense_prob(x, S): """ This function calculates the probabilities for x (can be a lemma or a key) from S (can be a Semantic Class or a Wordnet Synset) """ if isinstance(S, Semantic_Class): pass elif isinstance(S, nltk.corpus.reader.wordnet.Synset): if isinsta...
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def find_fxn(tu, fxn, call_graph): """ Looks up the dictionary associated with the function. :param tu: The translation unit in which to look for locals functions :param fxn: The function name :param call_graph: a object used to store information about each function :return: the dictionary for t...
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def _prepare_embeddings(h, m): """ Combine FCN outputs with segmentation masks to build a batch of mask-pooled hidden vectors. Represents the calculation of h_{m} in the first equation in Henaff et al's paper :h: batch of embeddings; (N,w,h,d) :m: batch of NORMALIZED segmentation tensors; ...
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def estimate_mode_width(distribution): """Estimate mode and width-at-half-maximum for a 1D distribution. Parameters ---------- distribution : array of int or float The input distribution. ``plt.plot(distribution)`` should look like a histogram. Returns ------- mode : int ...
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def agent_hostname_by_id(agent_id): """Given a agent_id provides the agent ip""" for agent in __get_all_agents(): if agent['id'] == agent_id: return agent['hostname'] return None
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def detect_person(gcs_uri="gs://YOUR_BUCKET_ID/path/to/your/video.mp4"): """Detects people in a video.""" client = videointelligence.VideoIntelligenceServiceClient() # Configure the request config = videointelligence.types.PersonDetectionConfig( include_bounding_boxes=True, inc...
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def parse_tile_name(name: str): """ Parse the tile """ match = reTILE.match(name) if match is None: return None groups = match.groupdict() # type: Dict[str, Any] groups['tile'] = int(groups['tile']) return groups
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def save_format(file): """Return 'mat' or 'py' based on file name extension.""" ext = os.path.splitext(file)[1] return ext[-(len(ext) - 1):]
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def test_metrics_aggerrs(monkeypatch): """Mock response to test metrics while aggregating errors.""" df = pd.DataFrame(dict(x=[1, 2, 3, 4], y=[1, 2, 3, 4])) mock_predict = lambda *x, **y: df.x.rename("y") # perfect response class Model(Normal): dv = "y" features = dict(x=dict(transform...
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def query_object_elasticsearch(query_string, item_type="tor"): """Return a dict of Elasticsearch results.""" # make an http request to elasticsearch #pool = urllib3.HTTPSConnectionPool(settings.ELASTICSEARCH_HOST, # settings.ELASTICSEARCH_PORT, # assert_fingerprint=settings.ELASTICSEAR...
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def article_to_frequency(article: str) -> List[int]: """Convert an article or article description to a list of numbers. :param article: The article or article description :return: A list of numbers corresponding to the words """ numbers: List[int] = [0] * len(common_words) article_words = artic...
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def test_actual_results_itakura_parallelogram(params, arr_desired): """Test that the actual results are the expected ones.""" arr_actual = itakura_parallelogram(**params) np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0.)
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def track_requests(fn): """ Decorator to log 21 sell request data. Args: fn: function to wrap """ @wraps(fn) def decorator(*args, **kwargs): service_name = os.environ["SERVICE"] url = request.url host = request.headers["Host"] endpoint = url.strip("https:/...
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def Date(default=None, validator=None, repr=False, eq=True, order=True, # NOQA converter=None, label=None, help=None,): # NOQA """ A date attribute. It always serializes to an ISO date string. Behavior is TBD and for now this is exactly a string. """ return String( default=defau...
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def compute_confuse_matrix_batch(y_targetlabel_list,y_logits_array,label_dict,name='default'): """ compute confuse matrix for a batch :param y_targetlabel_list: a list; each element is a mulit-hot,e.g. [1,0,0,1,...] :param y_logits_array: a 2-d array. [batch_size,num_class] :param label_dict:{label:...
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def test_get_account_short_name_replaces_spaces_with_underscores(): """It replaces spaces in account short names with underscores.""" pacioli = Pacioli(config_file="tests/resources/sample_config.yml") name = pacioli.get_account_short_name("Assets:Longterm:Real Estate") assert name == "real_estate"
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def jsonify_item(category_id, item_id): """Return an item information of a category in JSON""" try: item = db.session.query(Item).filter_by( category_id=category_id, id=item_id).one() return jsonify(Item=item.serialize) except Exception as e: abort(404)
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def parse(source: Union[str, bytes], fnam: str = None, errors: Errors = None, pyversion: Tuple[int, int] = defaults.PYTHON3_VERSION, custom_typing_module: str = None) -> MypyFile: """Parse a source file, without doing any semantic analysis. Return the parse tree. If errors is not provided, ...
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def check_AP_raw(abf,n=10): """X""" timePoints=get_AP_timepoints(abf)[:n] #first 10 if len(timePoints)==0: return swhlab.plot.new(abf,True,title="AP shape (n=%d)"%n,xlabel="ms") Ys=abf.get_data_around(timePoints,padding=.2) Xs=(np.arange(len(Ys[0]))-len(Ys[0])/2)*1000/abf.rate for i ...
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def encode_multipart_formdata(fields, files): #http://code.activestate.com/recipes/146306/ """ fields is a sequence of (name, value) elements for regular form fields. files is a sequence of (name, filename, value) elements for data to be uploaded as files Return (content_type, body) ready for httplib.HTTP instance...
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def test_get_chan_type(chan: str, expected: Union[str, None]) -> None: """Test to_resistics_chan""" from resistics.common import get_chan_type if expected is None: with pytest.raises(ValueError): get_chan_type(chan) return assert get_chan_type(chan) == expected
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def ParseMaxRevision(revision_list): """Returns the max revision from a list of url@revision string.""" revision_re = re.compile(r'.*@(\d+)') def RevisionKey(revision): return revision_re.match(revision).group(1) max_revision = max(revision_list.split(), key=RevisionKey) return max_revision.rpartition('...
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def get_resolv_conf_namservers() -> List[str]: """Return list of namserver IPs in /etc/resolv.conf.""" result = [] with open("/etc/resolv.conf") as f: for line in f: parts = line.lower().split() if len(parts) >= 2 and parts[0] == 'nameserver': result.append(pa...
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def get_sfcwind_6() -> None: """Get the CMIP6 surface wind from the figure data.""" # wsp = can_coords(return_figure_ds("5d")["wnspClim"]) wsp = can_coords(xr.open_dataarray(os.path.join(CMIP6_CLIM60_PATH, "wsp.nc"))) print(wsp.max()) print(wsp.min()) wsp = wsp.where(wsp < 20).fillna(20) # w...
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def import_gloss_csv(request): """ Check which objects exist and which not. Then show the user a list of glosses that will be added if user confirms. Store the glosses to be added into sessions. """ glosses_new = [] glosses_exists = [] # Make sure that the session variables are flushed befor...
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def _showvid(video_name, from_frame = 0): """ HELPER FUNCTION Navigate through video frame by frame from a certain frame. :param video_name: videopath :param from_frame: show vid from this frame :return: nothing """ cap = cv2.VideoCapture(str(video_name)) cap.set(1, from_frame) ...
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def transfer_cnn_weights(model, source_path, split, selection="best_balanced_accuracy", cnn_index=None): """ Set the weights of the model according to the CNN at source path. :param model: (Module) the model which must be initialized :param source_path: (str) path to the source task experiment :para...
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def TweetColecting(list_of_kw, startdate, enddate, exclude, outfile): """ Function to parse tweets between period of time based on included/excluded keywords. Tweet Manager has been modified to fixed the error of stopping halfway due to time limit exceed Current info retrieved including: - id - text (with emojies...
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def vis_timeslices(vis: Visibility, timeslice='auto') -> int: """ Calculate number of time slices in a visibility :param vis: Visibility :param timeslice: 'auto' or float (seconds) :return: Number of slices """ assert isinstance(vis, Visibility) or isinstance(vis, BlockVisibility), vis tim...
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def alexnet_metapoison(widths=[16, 32, 32, 64, 64], in_channels=3, num_classes=10, batchnorm=False): """AlexNet variant as used in MetaPoison.""" def convblock(width_in, width_out): if batchnorm: bn = torch.nn.BatchNorm2d(width_out) else: bn = torch.nn.Identity() ...
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def test_wrong_negated_complex_conditions( code, template, assert_errors, parse_ast_tree, default_options, ): """Testing complex conditions with nagated ``if`` condition.""" tree = parse_ast_tree(template.format(code)) visitor = IfStatementVisitor(default_options, tree=tree) visitor...
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def find_paths_with_suid_sgid(root_path): """Finds all paths/files which have an suid/sgid bit enabled. Starting with the root_path, this will recursively find all paths which have an suid or sgid bit set. """ cmd = ['find', root_path, '-perm', '-4000', '-o', '-perm', '-2000', '-type', '...
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def checksum(message): """ Calculate the GDB server protocol checksum of the message. The GDB server protocol uses a simple modulo 256 sum. """ check = 0 for c in message: check += ord(c) return check % 256
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def sds_bmm_torch(s_t1, d_t2): """ bmm (Batch Matrix Matrix) for sparse x dense -> sparse. This function doesn't support gradient. And sparse tensors cannot accept gradient due to the limitation of torch implementation. with s_t1.shape = (b, x, s), d_t2.shape = (b, s, y), the output shape is (b, x, y) ...
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def calc_fires(mappability_filename, cooler_filenames, bin_size, neighborhood_region, perc_threshold=.25, avg_mappability_threshold=0.9): """Perform FIREcaller algorithm. Parameters: ---------- mappability_filename : str Path to mappability file cooler_filenames : str List of paths ...
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def chown(): """Sets proper permissions""" sudo('chown -R www-data:www-data %s' % PROJECT_ROOT)
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