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def read_query(name: str): """ Read in a query from a separate SQL file Retrieves a query from a separate SQL file and stores it as a string for later execution. Query files are stored in the utils/sql_queries directory Args: name: Name of the SQL file to retreive Returns: (str): ...
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import torch def FalseTensor(*size, device='cuda:0'): """ Returns a Tensor of type torch.uint8 containing only False values Parameters ---------- *size : int the shape of the tensor device : str the device to store the tensor to Returns ------- Tensor a ui...
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def quotewrap(item): """wrap item in double quotes and return it. item is a stringlike object""" return '"' + item + '"'
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def elide_list(line_list, max_num=10): """Takes a long list and limits it to a smaller number of elements, replacing intervening elements with '...'. For example:: elide_list([1,2,3,4,5,6], 4) gives:: [1, 2, 3, '...', 6] """ if len(line_list) > max_num: return...
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def msize(m): """ Checks whether the matrix is square and returns its size. Args: m (numpy.ndarray): the matrix to measure; Returns: An integer with the size. """ s = m.shape[0] if m.shape != (s, s): raise ValueError("Do not recognize the shape (must be a square matr...
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def dec2bin(num, width=0): """ >>> dec2bin(0, 8) '00000000' >>> dec2bin(57, 8) '00111001' >>> dec2bin(3, 10) '0000000011' >>> dec2bin(-23, 8) '11101001' >>> dec2bin(23, 8) '00010111' >>> dec2bin(256) '100000000' """ if num < 0: if not width: ...
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import torch def collate_train(batch): """ Collate function for preparing the training batch for DCL training. :param batch: The list containing outputs of the __get_item__() function. Length of the list is equal to the required batch size. :return: The batch containing images and labels for DCL ...
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def occurence_data(pat_df, column): """ Return value counts of given dataframe columns :param pat_df: Dataframe :param column: Column included in Dataframe :return: Series of value occurences """ return pat_df[column].value_counts()
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def get_rec_names(study_folder): """ Get list of keys of recordings. Read from the 'names.txt' file in study folder. Parameters ---------- study_folder: str The study folder. Returns ---------- rec_names: list LIst of names. """ with open(study_folder / 'na...
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import six import operator def inclusion_unlimited_args_kwargs(one, two='hi', *args, **kwargs): """Expected inclusion_unlimited_args_kwargs __doc__""" # Sort the dictionary by key to guarantee the order for testing. sorted_kwarg = sorted(six.iteritems(kwargs), key=operator.itemgetter(0)) return {"resu...
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def md_entry_same(entry_name, s1, s2): """Returns (s1 and s2 have the same value for entry_name?, message).""" s1_val = s1[entry_name] s2_val = s2[entry_name] return (s1_val == s2_val, "(" + entry_name + ") " + repr(s1_val) + ", " + repr(s2_val))
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def format_score(logpath, log, markup): """Turn a log file JSON into a pretty string.""" output = [] output.append('\nLog: ' + logpath) if log['unrecognized']: output.append('\nLog is unrecognized: {}'.format(log['unrecognized'])) else: if log['flagged']: output.append('\...
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def is_categorical(s, column=None): """Check if a pandas Series or a column in a DataFrame is categorical. s (pandas.Series or pandas.DataFrame): Series to check or dataframe with column to check. column (str): Column name. If a column name is given it is assumed that `s` is a `pandas.D...
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def create_datafile_url(base_url, identifier, is_filepid): """Creates URL of Datafile. Example - File ID: https://data.aussda.at/file.xhtml?persistentId=doi:10.11587/CCESLK/5RH5GK Parameters ---------- base_url : str Base URL of Dataverse instance identifier : str Identifie...
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def project_grad(g): """Project gradient onto tangent space of simplex.""" return g - g.sum() / g.size
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def IsGlobalTargetGrpcProxiesRef(target_grpc_proxy_ref): """Returns True if the target gRPC proxy reference is global.""" return target_grpc_proxy_ref.Collection() == 'compute.targetGrpcProxies'
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def interpretStatus(status, default_status="Idle"): """ Transform a integer globus status to either Wait, Idle, Running, Held, Completed or Removed """ if status == 5: return "Completed" elif status == 9: return "Removed" elif status == 1: return "Running" elif st...
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def conv_kwargs_helper(norm: bool, activation: bool): """ Helper to force disable normalization and activation in layers which have those by default Args: norm: en-/disable normalization layer activation: en-/disable activation layer Returns: dict: keyword arguments to pass...
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import math def rmsd(V, W): """ Calculate Root-mean-square deviation from two sets of vectors V and W. Parameters ---------- V : array (N,D) matrix, where N is points and D is dimension. W : array (N,D) matrix, where N is points and D is dimension. Returns ------- ...
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def med_min_2darray(a): """Takes in a list of lists of integers and returns the minimum value.""" return min(min(inner) for inner in a)
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def _cast_to_int(num, param_name): """Casts integer-like objects to int. Args: num: the number to be casted. param_name: the name of the parameter to be displayed in an error message. Returns: num as an int. Raises: TypeError: if num is not integer-like. """ try: # ...
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def prefix_by_topic(topic_str): """ Return a topic-based prefix to produce distinct output files. `+` in the topic is replaced with `ALL`. The last element, `#` is left out from the prefix. See https://digitransit.fi/en/developers/apis/4-realtime-api/vehicle-positions/#the-topic """ els = t...
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def split_by_two_strings(line, str1, str2): """Split the input line into three parts separated by two given strings.""" # Start of second part in the input string. i1 = line.index(str1) + len(str1) # End of second part in the input string. i2 = line.index(str2) # Now we know where the second p...
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def get_variant_prices_from_lines(lines): """Get's price of each individual item within the lines.""" return [ line.variant.get_price() for line in lines for item in range(line.quantity)]
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async def client_send(ctx, msg, embed=1): """Sends messages to Discord context. Easily makes messages 'embeded' if embed == 1""" try: msg = str(msg) if embed == 1: m = await ctx.send("```" + msg + "```") else: m = await ctx.send(msg) return m except: ...
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from typing import List def split_commits_data( commits_data: str, commits_sep: str = '\x1e', ) -> List[str]: """ Split data into individual commits using a separator. :param commits_data: the full data to be split :param commits_sep: the string which separates individual commits :return:...
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def create_prop_dictionary(properties_list): """ Creates a dictionary of all properties from the properties list :param properties_list: list of property objects :return: dictionary of property objects grouped by unique key (name, unit, condition name, condition unit, method and data type) """ ...
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def identity_transformation(data): """Default coder is no encoding/decoding""" return data
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from functools import reduce import operator def _vector_add(*vecs): """For any number of length-n vectors, pairwise add the entries, e.g. for x = (x_0, ..., x_{n-1}), y = (y_0, ..., y_{n-1}), xy = (x_0+y_0, x_1+y_1, ..., x_{n-1}+y{n-1}).""" assert(len(set(map(len, vecs))) == 1) return [reduce(ope...
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from typing import Tuple def participant_names(redcap_record: dict) -> Tuple[str, ...]: """ Extracts a tuple of names for the participant from the given *redcap_record*. """ if redcap_record['participant_first_name']: return (redcap_record['participant_first_name'], redcap_record['particip...
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def get_accounts_aws(self, filter=""): """Retrieves AWS account information from Polaris Args: filter (str): Search string to filter results Returns: dict: Details of AWS accounts in Polaris Raises: RequestException: If the query to Polaris returned an error """ try: ...
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def arg_type_to_string(arg_type) -> str: """ Converts the argument type to a string :param arg_type: :return: String representation of the argument type. Multiple return types are turned into a comma delimited list of type names """ union_params = ( getattr(arg_type, '_...
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def combine_biases(*masks): """Combine attention biases. Args: *masks: set of attention bias arguments to combine, some can be None. Returns: Combined mask, reduced by summation, returns None if no masks given. """ masks = [m for m in masks if m is not None] if not masks: return None assert ...
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from pathlib import Path def find_source_dir_from_file(filepath: Path): """Find the source directory of the Sphinx project.""" conf_file = Path("conf.py") source_dir = filepath.parent root = Path("/") while source_dir != root: path = source_dir / conf_file if path.exists(): ...
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import socket def localhost_has_free_port(port: int) -> bool: """Checks if the port is free on localhost. Args: port (int): The port which will be checked. Returns: bool: True if port is free, else False. """ sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) is_success ...
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import torch def generate_spatial_noise(size, device, *args, **kwargs): """ Generates a noise tensor. Currently uses torch.randn. """ # noise = generate_noise([size[0], *size[2:]], *args, **kwargs) # return noise.expand(size) return torch.randn(size, device=device)
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def get_first_child(node, type): """Return the first child of |node| that has type |type|.""" index = node.first_child_matching_class(type) return node[index]
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def add_normalized_column(df, column_name): """ Normalize a column and add it to the DataFrame. Parameters ---------- df: DataFrame Input DataFrame containing the column to normalize. column_name: string Name of the column to normalize. Returns ------- out: DataFram...
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def make_reverse_dict(in_dict, warn=True): """ Build a reverse dictionary from a cluster dictionary Parameters ---------- in_dict : dict(int:[int,]) A dictionary of clusters. Each cluster is a source index and the list of other source in the cluster. Returns ------- ou...
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def stations_highest_rel_level(stations, N): """For a list of MonitoringStaton objects (stations), returns a list of the N stations at which the water level, relative to the typical range, is highest""" #Filter list as to not include stations without relative water level new_stations = list(filter(lamb...
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def MeanAveragePrecision(predictions, retrieval_solution, max_predictions=100): """Computes mean average precision for retrieval prediction. Args: predictions: Dict mapping test image ID to a list of strings corresponding to index image IDs. retrieval_solution: Dict mapping test image ID to list of g...
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def safe_inserter(string, inserter): """Helper to insert a subject name into a string if %s is present Parameters ---------- string : str String to fill. inserter : str The string to put in ``string`` if ``'%s'`` is present. Returns ------- string : str The mod...
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def undulating(number): """ Returns True if number is undulating """ if number < 100: return False number = str(number) for idx in range(len(number)-2): if number[idx] != number[idx+2]: return False return True
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def parse_result_line(line): """Take a line consisting of a constituency name and vote count, party id pairs all separated by commas and return the constituency name and a list of results as a pair. The results list consists of vote-count party name pairs. To handle constituencies whose names include a...
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def is_ip_per_task(app): """ Return whether the application is using IP-per-task. :param app: The application to check. :return: True if using IP per task, False otherwise. """ return app.get('ipAddress') is not None
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def column(results): """ Get a list of values from a single-column ResultProxy. """ return [x for x, in results]
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def unflatten_dict(d, delimiter = "/"): """Creates a hierarchical dictionary by splitting the keys at delimiter.""" new_dict = {} for path, v in d.items(): current_dict = new_dict keys = path.split(delimiter) for key in keys[:-1]: if key not in current_dict: current_dict[key] = {} ...
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def parse_subnets(subnets): """ Parse the Subnets dict, checking it is in correct format. Raises errors if there is a format violation. Arguments: subnets : the subnets dict Returns: parsed_subnets : parsed Subnet dict """ if not isinstance(subnets, dict): raise Val...
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def _get_outside_corners(corners, board): """ Return the four corners of the board as a whole, as (up_left, up_right, down_right, down_left). """ xdim = board.n_cols ydim = board.n_rows if corners.shape[1] * corners.shape[0] != xdim * ydim: raise Exception( "Invalid numb...
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import importlib def import_object(obj): """Import an object from its qualified name.""" if isinstance(obj, str): package, name = obj.rsplit('.', 1) return getattr(importlib.import_module(package), name) return obj
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import re def snakeCasetoCamelCase(a_string): """assumes a_string is a string in snake_case returns a new string, representing a_string in camelCase""" pattern = "(\w)(_)(\w)" new_string = re.sub(pattern, r"\1\3", a_string) return new_string
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from re import findall def to_integer(given_input: str): """ Finds the number in a given input(should be a string with numbers) using regular expression. >>> to_integer('abc') 0 >>> to_integer('1') 1 >>> to_integer('abc123') '123' >>> to_integer('abc123abc') '123' >>> to_i...
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def _validate_scp_time(the_sicd): """ Validate the SCPTime. Parameters ---------- the_sicd : sarpy.io.complex.sicd_elements.SICD.SICDType Returns ------- bool """ if the_sicd.SCPCOA is None or the_sicd.SCPCOA.SCPTime is None or \ the_sicd.Grid is None or the_sicd.G...
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def directory_tree(tmp_path): """Create a test directory tree.""" # initialize p = tmp_path / "directory_tree" p.mkdir() p.joinpath("file1").write_text("123") p.joinpath("dir1").mkdir() p.joinpath("dir1/file2").write_text("456") p.joinpath("dir1/file3").write_text("789") return p
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def intstrtuple(s): """Get (int, string) tuple from int:str strings.""" parts = [p.strip() for p in s.split(":", 1)] if len(parts) == 2: return int(parts[0]), parts[1] else: return None, parts[0]
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def findSmallerInRight(string, start, end): """ Counts the number of caracters that are smaller than string[start] and are at the right of it. :param string: Input string. :param start: Integer corresponding to the index of the starting character. :param end: Integer correspo...
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def dict_is_song(info_dict): """Determine if a dictionary returned by youtube_dl is from a song (and not an album for example).""" if "full album" in info_dict["title"].lower(): return False if int(info_dict["duration"]) > 7200: return False return True
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def get_n_last_observations_from_trajectories(trajectories, n, ascending=True): """ Get n extremity observations from trajectories Parameters ---------- trajectories : dataframe a dataframe with a trajectory_id column that identify trajectory observations. (column trajectory_id and jd have ...
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def get_arg_to_class(class_names): """Constructs dictionary from argument to class names. # Arguments class_names: List of strings containing the class names. # Returns Dictionary mapping integer to class name. """ return dict(zip(list(range(len(class_names))), class_names))
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def has_encountered_output_source(context): """Return True if the current context has already encountered an @output_source directive.""" return 'output_source' in context
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def writeSeg(BCFILE, title, segID, planeNodeIDs): """write face segments to BC input file Args: BCFILE: file IO object title (str): header comment line segID (int): segment ID # planeNodeIDs (int): 2D array Returns: segID (inc +1) """ BCFILE.write('*SET_SEGMENT_TITLE...
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from typing import List def get_requires() -> List[str]: """ Get Requires: Returns a list of required packages. """ return [ 'Click', 'cupy', 'tqdm', 'appdirs' ]
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def github_repository_name(url): """ Get the repository name from a Github URL """ repo = url.rstrip("/") if repo.endswith(".git"): repo = repo[:-4] _, name = repo.rsplit("/", 1) return name
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def github_paginate(session, url): """Combines return from GitHub pagination :param session: requests client instance :param url: start url to get the data from. See https://developer.github.com/v3/#pagination """ result = [] while url: r = session.get(url) result.extend(r....
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def chunk(arr:list, size:int=1) -> list: """ This function takes a list and divides it into sublists of size equal to size. Args: arr ( list ) : list to split size ( int, optional ) : chunk size. Defaults to 1 Return: list : A new list containing the chunks of the original ...
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def split_rows(array:list, l:int=9) -> list: """ Transforms a 1D list into a list of lists with every list holding l elements. Error is raised if array has a length not divisible by l. """ if len(array) % l != 0: raise ValueError("split_rows(): Rows in list have different lengths") retu...
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def fixture_other_case() -> str: """Return the case id that differs from base fixture""" return "angrybird"
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import re def prune_protected(mailboxes, ns): """ Remove protected folders from a list of mailboxes Exchange has several protected folders that are used for non-mail purposes, but still appear in the list. Therefore, we want to exclude these folders to prevent reading non-mail items. Args: ...
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def remove_hetatm(filename_in, file_out, remove_all): """Remove HETATM and related lines. If remove_all is False, remove only element X which happens in many PDB entries but is not accepted by pointless, refmac, phaser, etc """ # we could instead zero occupancy of the atoms and replace X with Y ...
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def _urpc_test_func_2(buf): """! @brief u-RPC variable length data test function. @param buf A byte string buffer @return The same byte string repeated three times """ return buf*3
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import gzip def read_consanguineous_samples(path, cutoff=0.05): """ Read inbreeding coefficients from a TSV file at the specified path. Second column is sample id, 6th column is F coefficient. From PLINK: FID, IID, O(HOM), E(HOM), N(NM), F Additional columns may be present but will be ignored. ...
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def is_reserved_name(name): """Tests if name is reserved Names beginning with 'xml' are reserved for future standardization""" if name: return name[:3].lower() == 'xml' else: return False
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def prompt(message, values=None): """Prompt a message and return the user input. Set values to None for binary input ('y' or 'n'), to 0 for integer input, or to a list of possible inputs. """ if values is None: message += ' (y/n)' message += ' > ' while 1: ans = input(message) ...
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def parse_input(input_file): """ Processes the input with song titles. See above format. Returns a dict of mapping number -> [title1, title2, ...] """ tdb = {} disc_no = -1 with open(input_file) as fin: for line in fin: line = line.strip() if 'disc ' in l...
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def is_type(indexed_token, tag_type): """Tests if the given token was tagged with the given tag type.""" return indexed_token.has_key('tag') and (indexed_token['tag'] == tag_type)
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import re def get_root_url(the_line): """ Get the root URL from the line :param the_line: the line :return: either the root URL or None """ ret = re.search('https://[^/]*/[^/]*/', the_line) if ret: return ret.group(0) return None
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import six def _get_context(estimator=None): """Get context name for warning messages.""" if estimator is not None: if isinstance(estimator, six.string_types): estimator_name = estimator.lower() else: estimator_name = estimator.__class__.__name__.lower() estima...
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def strictly_equal(obj1: object, obj2: object) -> bool: """Checks if the objects are equal and are of the same type.""" return obj1 == obj2 and type(obj1) is type(obj2)
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def exception_redirect(new_exception_class, old_exception_class=Exception, logger=None): """ Decorator to replace a given exception to another Exception class, with optional exception logging. >>> >>> class MyException(Exception): ... pass >>> >>> @exception_redirect(MyException) .....
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def yubikey_get_yubikey_id(yubikey_otp): """ Returns the yubikey id based :param yubikey_otp: Yubikey OTP :type yubikey_otp: str :return: Yubikey ID :rtype: str """ yubikey_otp = str(yubikey_otp).strip() return yubikey_otp[:12]
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import torch def load_weights_from_path(model, path): """load weights from file Args: model (Net): Model instance path (str): Path to weights file Returns: Net: loaded model """ model.load_state_dict(torch.load(path)) return model
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def directory_current_user(request): """ Return the current user directory """ path = request.user.get_home_directory() try: if not request.fs.isdir(path): path = '/' except Exception: pass return path
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def create_dict_playlists_playlistids(p_list, pid_list): """ Create a dictionary of playlists and playlist ids """ playlists_and_playlist_ids = {} for i in range(len(p_list)): playlists_and_playlist_ids[p_list[i]] = pid_list[i] return playlists_and_playlist_ids
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import typing import types def is_iterable(obj: typing.Any) -> bool: """ >>> is_iterable([]) True >>> is_iterable(()) True >>> is_iterable([x for x in range(10)]) True >>> is_iterable((1, 2, 3)) True >>> g = (x for x in range(10)) >>> is_iterable(g) True >>> is_iter...
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def color565(red, green=0, blue=0): """ Convert red, green and blue values (0-255) into a 16-bit 565 encoding. """ try: red, green, blue = red # see if the first var is a tuple/list except TypeError: pass return (red & 0xf8) << 8 | (green & 0xfc) << 3 | blue >> 3
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from typing import Mapping def _flatten_dict(d, prefix=''): """ Convert a nested dict: {'a': {'b': 1}} -> {'a--b': 1} """ out = {} for k, v in d.items(): if isinstance(v, Mapping): out = {**out, **_flatten_dict(v, prefix=prefix + k + '--')} else: out[prefix...
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def mass(self): """get mass""" return self._mass
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def x_forwarded_ip(request): """ Returns the IP Address contained in the 'HTTP_X_FORWARDED_FOR' header, if present. Otherwise, `None`. Should handle properly configured proxy servers. """ ip_address_list = request.META.get('HTTP_X_FORWARDED_FOR') if ip_address_list: ip_address_list ...
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def float2String(input, ndigits=0): """ Round and converts the input, if int/float or list of, to a string. Parameters ---------- input: int/float or list of int/float ndigits: int number of decimals to round to Returns ------- output: string or list of strings dep...
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def remove_forbidden_keys(data): """Remove forbidden keys from data Args: data (list): A list of dictionaries, one per transactions Returns: list: A list of dictionariess, one per transaction, with forbidden keys removed """ # There are different forbidden keys based on the report...
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def RestoreListType(response, key_triggers=()): """Step (recursively) through a response object and restore list types that were overwritten by SOAPpy. Lists with only one element are converted by SOAPpy into a dictionary. This handler function restores the proper type. Args: response: dict Response data...
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def get_asset_url(release, quiet=False): """ get the assets url from the release information :return: the assets_url """ return release["assets_url"]
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def hour_of_day(datetime_col): """Returns the hour from a datetime column.""" return datetime_col.dt.hour
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def find_service_by_type(cluster, service_type): """ Finds and returns service of the given type @type cluster: ApiCluster @param cluster: The cluster whose services are checked @type service_type: str @param service_type: the service type to look for @return ApiService or None if not...
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def largest_factor(n): """Return the largest factor of n*n-1 that is smaller than n. >>> largest_factor(4) # n*n-1 is 15; factors are 1, 3, 5, 15 3 >>> largest_factor(9) # n*n-1 is 80; factors are 1, 2, 4, 5, 8, 10, ... 8 """ factor = n - 1 while factor > 0: if (n*n-1) % factor ...
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def add_required_cargo_fields(toml_3p): """Add required fields for a Cargo.toml to be parsed by `cargo tree`.""" toml_3p["package"] = { "name": "chromium", "version": "1.0.0", } return toml_3p
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import math def quat_to_euler(q): """returns yaw, pitch, roll at singularities (north and south pole), assumes roll = 0 """ # See http://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToEuler/ eps=1e-14 qw = q.w; qx = q.x; qy = q.z; qz = -q.y pitch_y = 2*qx*qy + 2...
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def describe(df): """Shorthand for df.describe() Args: df (`pandas.DataFrame`): The dataframe to describe Returns: summary: Series/DataFrame of summary statistics """ return df.describe()
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def ternary_expr(printer, ast): """Prints a ternary expression.""" cond_str = printer.ast_to_string(ast["left"]) # printer.ast_to_string(ast["cond"]) then_expr_str = printer.ast_to_string(ast["middle"]) # printer.ast_to_string(ast["thenExpr"]) else_expr_str = printer.ast_to_string(ast["right"]) # pri...
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def _combine_paths(path): """ Turn path list into edge list. :param path: List. A list of nodes representing a path. :returns: List. A list of edge tuples. """ edges = [] for i, node in enumerate(path[1:]): edges.append((path[i], node)) return edges
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