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def collapse(intlist): """Collapse a list of int values of chars into the int they represent.""" f = '' for i in intlist: f += chr(i) return int(f)
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def _create_profile_for_host_communication(profile_name): """ Create a profile which allows traffic to and from the host. """ _log.info("Autocreating profile %s", profile_name) datastore.create_profile(profile_name) prof = datastore.get_profile(profile_name) host_net = str(_get_host_ip_net(...
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def file_is_dll_client( path_name): """ .. todo:: Document. """ file_is_dll_client_by_platform = { "darwin": file_is_dll_client_unix, "linux2": file_is_dll_client_unix, "win32": file_is_dll_client_win32 } return file_is_dll_client_by_platform[sys.platform...
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def _validate_environment_variable( ctx: click.core.Context, param: Union[click.core.Option, click.core.Parameter], value: Tuple[str], ) -> Dict[str, str]: """ Validate that environment variables are set as expected. """ # We "use" variables to satisfy linting tools. for _ in (param, ctx...
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def get_settings() -> Tuple[int, int]: """Gets some settings for the board.""" return board_size, num_ships
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def run_sunset(): """ Sends a tweet about the sunset and captures image """ tweet_sunset() return run_tweeter()
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def test_get_known_transcripts_specific_dataset(): """ Now make sure the correct transcript is returned when the dataset is specified. """ database = "scratch/filter/test.db" # Both datasets known = filt.get_known_transcripts(database, "toy", datasets =...
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def get_data(): """Get the population data.""" # Construct population pop = CosmicPopulation(n_srcs=SIZE, n_days=1, name='standard_candle') pop.set_dist(model='sfr', z_max=2.5, H_0=67.74, W_m=0.3089, W_v=0.6911) pop.set_dm_host(model='constant', value=100) pop.set_dm_igm(model='ioka', slope=1000...
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def dummy1_3857_tif(): """Fixture for dummy1_3857.tif""" return os.path.join(TESTDATA_DIR, "dummy1_3857.tif")
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def create_token(request): """Debug helper view. ========== ===================================================== Argument Value ========== ===================================================== timeout Number of seconds to keep token alive (default=6). url The url to ...
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def test_parse_source(): """ Ensure a tuple of two non-empty lists is returned """ with open('tests/names-generator.go', 'r') as go_source: source = go_source.read() parsed_source = _parse_source(source) assert type(parsed_source) == tuple assert type(parsed_source[0]) == list assert t...
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def tag_user(request, tag, username): """ Display all `tag` snippets of `username` user """ user = get_object_or_404(User, username=username) snippets = Snippet.objects.filter(author=user).filter( tags__name__in=[tag, ]).all() return render_to_response('tags/view.html', { 'tag': tag, ...
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def rmsfcalc(u, rmsfout, modus="calphas"): """ Calculation of Protein RMSF :param u: MDAnalysis universe :param rmsfout: File path to output file :param modus: Selection to align and calculation ("calphas" or "allatoms") :return: None """ calphas = u.select_atoms("protein and ...
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def extract_keywords(keywlist_handle): """extract_keywords(keywlist_handle) -> list of keywords Return the keywords from a keywlist.txt file. """ import warnings warnings.warn("Bio.SwissProt.KeyWList.extract_keywords is deprecated. Please use the function Bio.SwissProt.KeyWList.parse instead to pa...
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def automated_threshold_setting(image, mask_local_max): """Automatically set the optimal threshold to detect spots. In order to make the thresholding robust, it should be applied to a filtered image (bigfish.stack.log_filter for example). The optimal threshold is selected based on the spots distributio...
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def _get_raw_test_commands(name: str) -> List[str]: """テストケースのinclude解決を行っていない状態の生のコマンドを取得する Args: name (str): テストケース名 Raises: Exception: 取得に失敗した場合例外を送出します Returns: List[str]: テストコマンド配列 """ testcase = _get_testcase_object(name) return _convert_test_commands(testcas...
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def extract_params(func, standard_args): """Return WhyNot parameters for user-defined function. Performs error-checking to ensure parameters are disjoint from standard arguments and all arguments to the function are either standard arguments or parameters. Parameters ---------- func: f...
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def lark_to_float_value_node(tree: "Tree") -> "FloatValueNode": """ Creates and returns a FloatValueNode instance extracted from the parsing of the tree instance. :param tree: the Tree to parse in order to extract the proper node :type tree: Tree :return: a FloatValueNode instance extracted from...
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def confusion_matrix(pred, gt, thres=0.5): """Calculate the confusion matrix given a probablility threshold in (0,1). """ TP = np.sum((gt == 1) & (pred > thres)) FP = np.sum((gt == 0) & (pred > thres)) TN = np.sum((gt == 0) & (pred <= thres)) FN = np.sum((gt == 1) & (pred <= thres)) return (...
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def save_score_results(score, cfg, logger, verbose=None, config_name='None', current_step=0, time_stamp='time_step'): """Save scores. This method is used to store the normal/abnormal scores of frames which are used for the evaluation functions Args: score(list): The scores of all of the video...
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def data_path(filename: str) -> str: """Get full path to a file in the data folder. Args: filename (str): The data file's name. Returns: path (str): The full path to the file. """ return os.path.join(os.path.dirname(__file__), "data", filename)
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def do_heatmap(df): """ Make a bottom heatmap """ mask = np.zeros_like(df, dtype=np.bool) mask[np.triu_indices_from(mask)] = True cmap = sns.diverging_palette(220, 10, as_cmap=True) sns.heatmap(df.values.tolist(), yticklabels=df.columns, xticklabels=df.columns, vmin=-1, vmax=1, center=0, ...
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def docs2omop( docs: List[Doc], extensions: Optional[List[str]] = None, ) -> Tuple[pd.DataFrame, pd.DataFrame]: """ Transforms a list of spaCy docs to a pair of OMOP tables. Parameters ---------- docs : List[Doc] List of documents to transform. extensions : Optional[List[str]], ...
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def getWebVersion(d): """Get the version from the web of the catalog entry in d Use the page at the url specified in d['version']['url'], and the regular expression specified in d['version']['regex'] to find the latest version number of the passed package. The d['version']['regexpos']'th match of the ...
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def stdev_outliers_proxy(self, *args, **kwargs): """ Calls :meth:`.stdev_outliers` on each table in the TableSet. """ return self._proxy('stdev_outliers', *args, **kwargs)
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def load_cells(): """Load cell data. This cell dataset contains cell boundaries of mouse osteosarcoma (bone cancer) cells. The dlm8 cell line is derived from dunn and is more aggressive as a cancer. The cells have been treated with one of three treatments : control (no treatment), jasp (jasplakinol...
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def test_searchparam_type_date_period_ge(store: FHIRStore, index_resources): """Handle date search parameters on FHIR data type "period" The date format is the standard XML format, though other formats may be supported prefix ge: the range above the search value intersects (i.e. overlaps) with the r...
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def approve_story(story: str): """ Moves a story from the pending file to the story file. :param story: The story to approve. :return: """ pending_data = load_pending_list() story_to_approve = pending_data[story.lower()] del pending_data[story.lower()] update_pending_list(pending_da...
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def k_fold_cross_validation(X, k=None, randomize=False): """ Generates K (training, validation) pairs from the items in X. Each pair is a partition of X, where validation is an iterable of length len(X)/K. So each training iterable is of length (K-1)*len(X)/K. Parameters ---------- X :...
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def correlation_matrix( spark, idf, list_of_cols="all", drop_cols=[], stats_unique={}, print_impact=False ): """ :param spark: Spark Session :param idf: Input Dataframe :param list_of_cols: List of columns to analyse e.g., ["col1","col2"]. Alternatively, columns can be speci...
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def _model_variable_getter(getter, name, shape=None, dtype=None, initializer=None, regularizer=None, trainable=True, collections=None, caching_device=None, partitioner=None, rename=None, use_resource=None, **_): ...
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def password_check(value, user): """ Check that the password passes the following validation: Password is long enough (based on configuration setting) Password contains at least one digit Password contains at least one letter Password contains at least one uppercase character Password conta...
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def test_histogram_cli_no_datasets(output_path): """ Tests that the command line interface works correctly on the test dataset for histogram plots when the test dataset is passed in via command line. """ subprocess.run( [ "svl", # NOTE Don't need the template ...
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def copiar_dic(origen): """ Devuelve una copia nueva de ``origen`` con el menor estado compartido posible. Utiliza `fusionar_dics` debajo del capó, con un dict ``base`` vacío; consulte su documentación para obtener detalles sobre el comportamiento. .. versionadded:: 1.0 """ return fu...
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def get_all_users(conn): """Iterator that yields all IAM users, to simplify getting all users. The amazon interface presents a "next" token that has to be guarded. This makes that easier. However it doesn't present the returned object, only the list of user dicts Enables this sort of search: In [210]: r = get...
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def to_weight(df: pd.DataFrame, renorm=True): """ Converts molar quantities to mass quantities of the same order. E.g.: mol% --> mass% mol-ppm --> mass-ppm """ MWs = [pt.formula(c).mass for c in df.columns] if renorm: return renormalise(df.multiply(MWs)) else: return ...
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def sind(ang: ArrayLike) -> ArrayLike: """Return the sine of an angle specified in degrees. Parameters ---------- ang : float An angle, in degrees. """ return numpy.sin(numpy.radians(ang))
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def linscale(x, lb_in, ub_in, lb_out, ub_out): """linscale scales x according to the provided bounds. Parameters ---------- x : (N, x_dim) numpy array lb_in : scalar or 1D list of len x_dim or (1,) or (x_dim,) numpy array Returns ------- xs : (N, x_dim) numpy array """ lb_i...
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def sync_from(src, dest): """Synchronize a directory from Dropbox.""" return False
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def replypost(postnum): """ Reply to a post. Arguments: postnum: Post number to reply to. if postnum == "": ask for post number to reply to else: reply to global postum User input: Post number and/or post text. """ getme() global posttext posttext = '' if str(postnum) == "": postnu...
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async def get_view_config( name: str = Path(None, description="Name of the view"), token_jenkins_auth: TokenModel = Security( get_token_jenkins_auth ), ) -> str: """Retrieve view configuration""" ...
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def transcribe(seq: str) -> str: """ transcribes DNA to RNA by generating the complement sequence with T -> U replacement """ #stores the complement, RNA seq RNA_seq = "" #generate complement sequence #DNA->ACTG->A-><-T, C-><-G #T->U replacement keep_alpha_only = re.sub(r'[...
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def filter_timeline_actions(tim, **filters): """tim (dict) contains info for one TIM""" actions = tim['timeline'] for field, required_value in filters.items(): if field == 'time': # Times are given as closed intervals: either [0,134] or [135,150] acceptable_times = range(requ...
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def _make_n_rows(x, n, y=None): """ Multiplies or reduces the rows of x to get exactly *n* rows. """ if n < x.shape[0]: if y is None: return x[:n].copy() return x[:n].copy(), y[:n].copy() if len(x.shape) < 2: r = np.empty((n,), dtype=x.dtype) ...
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def calculate_match_unnormd_fft( params_h: Binary, params_d: Binary, fs, pad_low, pad_high, S_n=S_n_LISA ): """ Inner product of waveforms, maximized over Phi_c by taking absolute value and t_c using the fast Fourier transform. """ df = fs[1] - fs[0] wf_h = amp(fs, params_h) * jnp.exp(1j * P...
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def _force_merge(session, model, new_model): """Force merge an existing `model` with a `new_model` by copying the primary key values from `model` to `new_model` before calling ``session.merge(model)``. """ pk_cols = mapper_primary_key(model.__class__) for col in pk_cols: setattr(new_mod...
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def get_alignment(ra_difference, dec_difference): """ This function ... :param ra_difference: :param dec_difference: :return: """ ra_alignment = None dec_alignment = None if np.isclose(ra_difference, 1.0, atol=0.0001): # if RA increment is close to 1 with a positive x increment ...
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def three_to_one_with_mods(res: str) -> str: """ Converts three letter AA codes into 1 letter. Allows for modified residues. :param res: Three letter residue code str: :type res: str :return: 1-letter residue code :rtype: str """ return RESI_THREE_TO_1[res]
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def sent2features(sent, pos_lex=None, neg_lex=None): """ Converts a sentence (list of (word, pos_tag) tuples) into a list of feature dictionaries """ return [word2features(sent, i, pos_lex, neg_lex) for i in range(len(sent))]
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def ensure_virtualenv( python, numpy=True ): """Check/create virtualenv using our naming scheme""" expected_name = os.path.join( TEST_ENVS, python+['-nonum','-num'][bool(numpy)]) log.info( 'Ensuring %s', expected_name ) bin_path = os.path.join( expected_name, 'bin' ) if not os.path.exists( expected_...
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def effect_of_travel_range_on_afv_attractiveness(): """ Real Name: b'Effect of travel range on AFV Attractiveness' Original Eqn: b'AFV travel range/travel range max' Units: b'Dmnl' Limits: (None, None) Type: component b'' """ return afv_travel_range() / travel_range_max()
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def serialize_read(function_code: int, transaction_id: int, unit_address: int, first_address: int, count: int) -> str: """ Universal function for handling serialization of all read type messages. Args: function_code: Unique function code. transaction_id: Unique ID of the transaction. ...
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def plot_locally_connected_weights( weights: torch.Tensor, n_filters: int, kernel_size: Union[int, Tuple[int, int]], conv_size: Union[int, Tuple[int, int]], locations: torch.Tensor, input_sqrt: Union[int, Tuple[int, int]], wmin: float = 0.0, wmax: float = 1.0, im: Optional[AxesImage]...
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def clean(context, derived_data, caches, build, all): """Clean project & punic environment.""" logging.info("<cmd>Clean</cmd>") punic = context.obj with timeit('clean'): if build or all: logging.info('Erasing Carthage/Build directory') if punic.config.build_path.exists()...
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def draw_box_list(img_bgr, box_list, thickness=-1, color=None, is_overlap=True, is_arrow=False, is_text=True, is_show=False, is_new=False, save_name=None): """ 绘制矩形列表 """ if is_new: img_bgr = copy.deepcopy(img_bgr) n_box = len(box_list) if not color: color_list...
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def adjust_protons(formula, protons): """ @param formula: chemical formula as string @param protons: number of hydrogens to add/remove as intager @return: new formula as string """ if not protons: return (formula,"") protons = int(protons) Notes = "" #The whole function assum...
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def angsep(ra1,dec1,ra2,dec2): """Compute the angular separations between two points on a sphere Parameters: - ra1 - Right ascension of first position - dec1 - Declination of first position - ra2 - Right ascension of second position - dec2 - Declination of second position Note: All inp...
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def construct_schema_function_without_choices() -> Callable: """ Modifies model example and description if needed. Note that schema extra has to be a function, otherwise it's called to soon before all the relations are expanded. :return: callable that will be run by pydantic to modify the schema ...
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def is_cross_not_claimed(event_list, team): """Returns if event list has a cross-not-claimed Goalkeeper event; cross not successfully caught""" cnc = False for e in event_list[:1]: if e.type_id == 53: cnc = True return cnc
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def update_items(controller, async_add_entities, switches): """Update POE port state from the controller.""" new_switches = [] devices = controller.api.devices for client_id in controller.api.clients: if client_id in switches: LOGGER.debug("Updating UniFi switch %s (%s)", ...
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def _do_monte_carlo_run(pools, lulc_counts): """Do a single Monte Carlo run for carbon storage. Returns a dict with the results, keyed by scenario, and # including results for sequestration. """ # Sample carbon-per-grid-cell from the given normal distribution. # We sample this independently fo...
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def compute_partition(df): """Perform compute on a partition Partitions are perfectly aligned along 1 minute and the timestamp index is sorted. Below is a reasonably costly operation that aggregates data from each timestep. That dataframe would aggregate what the timestep had (i.e., measureme...
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def main(event , context): """Permite detectar las emociones de una imagen""" uri_base = event['bucket'] #Bucket donde esta la imagen pic = event['name'] #Nombre de la imagen a analizar result = emotion_detection.emo_detect(uri_base, pic) #Detectar emocion print("Emocion detectada: "+resul...
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def first_impressions_view(request): """First impressions view.""" auth = False try: auth = request.cookies['auth_tkt'] auth_tools = request.dbsession.query( MyModel ).filter(MyModel.category == 'admin').all() except KeyError: auth_tools = [] query = reque...
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def mysql_create_tables(): """ when using mysql database, this is the function that is used to create the tables in the database for the first time when you run the nettacker module. Args: None Returns: True if success otherwise False """ try: ...
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def get_camera_intrinsic_parameters(stub): """ Get camera intrinsic params from gprc detection server. """ request = detection_server_pb2.Empty() try: response = stub.GetCameraIntrinsicParameters(request) return response except grpc.RpcError as err: logger.error(err.details()) #p...
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def update_local_pool(online_pool) -> None: """ 更新本地卡池文件, 并备份原卡池 """ # 读取本地卡池 with open(local_pool_path, 'r', encoding='utf-8') as lf: local_pool = json.load(lf) # 备份本地卡池 logger.info(f'开始备份本地卡池') with open(local_pool_backup_path, 'w', encoding='utf-8') as backup: json.du...
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def remove_boot_record(boot_num): """Remove an EFI boot record with efibootmgr. :param boot_num: the number of the boot record """ utils.execute('efibootmgr', '-b', boot_num, '-B')
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def version_strategy(version: str) -> AwesomeVersionStrategy: """Return the version stragegy.""" if is_buildver(version): return AwesomeVersionStrategy.BUILDVER if is_calver(version): return AwesomeVersionStrategy.CALVER if is_semver(version): return AwesomeVersionStrategy.SEMVER...
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def get_name_from_path(path): """ Parses a directory in 'mgmt_<name> ' format into the camel case name used by ARM. The directory name should be in snake case. """ while path: path, item = os.path.split(path) if 'mgmt_' in item: return snake_to_camel(item.replace('mgmt_', '', 1))...
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def get_transcript_name(ids): """Get transcript name.""" return _search(transcript_name_re, ids)
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def rank_items(ratings, similarities): """ (アイテムのインデックス, 予測した評価値)のタプルリストをランキング(評価値の降順ソート)で返す """ ranking = [ ] for i, r in enumerate(ratings): if r != -1: continue ranking.append((i, predict_rating(ratings, i, similarities))) return sorted(ranking, key=lambda r: r[...
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def hex2(n, uppercase=True): """ Return 2 characters corresponding to the hexadecimal representation of `n`. :param n: 0 <= int < 256 :param uppercase: bool :return: str (length == 2) """ assert isinstance(n, int) assert 0 <= n < 256 assert isinstance(uppercase, bool), type(upperca...
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def test(ctx): """ Run the playbook :param ctx: context object :return: None """ os.chdir('tests/') test_case_list = glob.glob('*.py') for test_case in test_case_list: ctx.run( "ANSIBLE_PRIVATE_KEY_FILE={0} ANSIBLE_REMOTE_USER={1} pytest {2} -s -v --gherkin-terminal-r...
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async def async_remove_entry(hass, config_entry): """Handle removal of an entry.""" try: await hass.config_entries.async_forward_entry_unload(config_entry, PLATFORM) _LOGGER.info("Successfully removed sensor from the Deeds integration") except ValueError: pass
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def test_register_internal(plugin_manager): """Tests registration of internal flaskbb plugins.""" class A(object): pass a1, a2 = A(), A() plugin_manager.register(a1, "notinternal") plugin_manager.register(a2, "internal", internal=True) assert plugin_manager.is_registered(a2) out = ...
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def get_split_statistics(filepath): """ Computes the label frequency, amount of utterances and tokens for a preprocessed tsv file. """ label_freq = defaultdict(int) amount_tokens = 0 with open(filepath, 'r') as file: reader = csv.DictReader(file, delimiter='\t') for li...
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def test_complex_pattern_call(): """Ensure ComplexPattern calling (refinement) works as expected.""" Monomer('A', ['w', 'x'], {'x': ('e', 'f')}) Monomer('B', ['y', 'z'], {'z': ('g', 'h')}) cp = A(w=1, x='e') % B(y=1, z='g') r = {'x': 'f', 'z': 'h'} # refinement for complexpattern ok_(cp(**r)) ...
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def cast_int(value): """ Cast value to 32bit integer Usage: cast_int(1 << 31) == -1 (where as: 1 << 31 == 2147483648) """ value = value & 0xffffffff if value & 0x80000000: value = ~value + 1 & 0xffffffff return -value else: return value
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def dense_fast_decode( src_vocab_size, trg_vocab_size, max_in_len, n_layer, enc_n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, ...
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def fixed_rotation_objective(link,ref=None,local_axis=None,world_axis=None): """Convenience function for fixing the given link at its current orientation in space. If local_axis and world_axis are not provided, the entire link's orientation is constrained. If only local_axis is provided, the link...
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def chinese_cut(text): """ 进行中文分词 :param text: 中文数据 :return: 分词后的数据 """ return ' '.join(jieba.cut(text))
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def bottleneck_block_(inputs, filters, is_training, strides, use_projection=False, pruning_method='baseline', init_method='baseline', data_format='channels_first', ...
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def main(): """ Main function for the polynomial synthetic data experiment. """ ### Experiments with polynomials: _ = polynomial_experiment(scm_polynomial_thresholding_first, "./experiments/results/roc_polynomials_first.png") _ = polynomial_experiment(scm_polynomial_thresholding_second, "./experimen...
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def WaitForOperation(client, operation_ref, message): """Waits until the given operation finishes. Wait loop terminates when the operation's status becomes 'DONE'. Args: client: interface to the Cloud Updater API operation_ref: operation to poll message: message to be displayed by progress tracker ...
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def ifloordiv(): """//=: Inplace floor divide operator.""" class _Operand: def __init__(self): self.value = '' def __ifloordiv__(self, other): self.value = "int(val/{})".format(other) return self item = _Operand() item //= 2 return item.value
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def send_async_email(app, msg): """ Restore Flask's application context and send email via flask_mail's Mail instance. """ with app.app_context(): mail.send(msg)
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def search_custom_results(result_id): """ Search a result for predictions. request['maxPredictionSort'] - when true sort by max prediction request['all'] - include values in download request['page'] - which page of results to show request['perPage'] - items per page to show :param result_id:...
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def create_1_layer_ANN_classification( input_shape, num_hidden_nodes, num_classes, activation_function='relu' ): """ Creates a 1 layer classification ANN with the keras backend. Arguments: input_shape (int tuple): The shape of the input excluding batch. num_hidden_nodes (i...
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def unsqueeze(x, axis, name=None): """ :alias_main: paddle.unsqueeze :alias: paddle.unsqueeze, paddle.tensor.unsqueeze, paddle.tensor.manipulation.unsqueeze Insert single-dimensional entries to the shape of input Tensor ``x``. Takes one required argument axis, a dimension or list of dimensions that will ...
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def test_flow_affine(): """Test if Flow inheritance requirements are preserved. We'll run all Flow functions with the modules.AffineFlow flow. If flow.Flow has changed, AffineFlow should stop working. """ weight = torch.ones(1, 1) * 2 flow = AffineFlow(weight=weight) x = torch.ones(1, 1) ...
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def get_kills_info_player_match(player_id,match_id,prt=False): """ get ONE player in ONE match's kills information :param player_id: :param match_id: :param prt: :return: list of kill information """ info = get_player_info_match_id(player_id,match_id) info_kills = {} if('hero_kil...
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def update_args(args: Dict, inv_file: str, conf_file: str) -> Dict: """ Add inventory file and config file in the correct spots inside the arguments Args: args (Dict): controller args inv_file (str): inventory file conf_file (str): config file Returns: Dict: updated arg...
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def _add_vessel_class(df): """Creates 'Class' column based on vessel LOA ft.""" df.loc[:, "Class"] = "Panamax" post_row = (df.loc[:, "LOA ft"] > 965) post_loc = df.loc[post_row, :].index post_pan = df.index.isin(post_loc) df.loc[post_pan, "Class"] = "Post-Panamax" return df
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def async_generate_ptr_query(ip): """Generate a ptr query with the next random id.""" return message.make_query(ip.reverse_pointer, rdatatype.PTR)
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def masked_within_block_local_attention_1d(q, k, v, block_length=64, name=None): """Attention to the source and a neighborhood to the left within a block. The sequence is divided into blocks of length block_length. Attention for a given query position can only see memory positions less than or equal to the que...
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def catch_all(path): """ Repeats the request to the latest version of default service by replacing all occurrences of the hostname to the new_host defined above. The replacement happens for: - URL and URL query string - Headers, including cookie headers - The body, if we can decode it....
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def main(model_to_run, dataset_name, task, verbose=False): """ Takes model, dataset combination as input as well as classification or regression task and runs the respective model training and evaluation as well as calculating/averaging the metrics at the end. Sets the random state to 1 and n_fold for C...
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def bulk_process( debug = False, number_of_cycles_before_rate_analysis = 10, cell_ids = None, ): """ TEMPDOC first calls process_single_file then, calls process_cell_id """ if cell_ids is None: errors = list( map( lambda x: process_single_file(x, debug), ...
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def refresh_asset_cache(id, asset, action, remote_id=None): """ Perform asset cache add or update depending on action provided. """ try: if action == 'create': asset_cache_add(id, asset) elif action == 'update': update_asset_cache(id, asset, remote_id) else: ...
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