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def sort_kv_pairs_by_value(d): """Turn a dict into a list of key-value pairs, sorted by value.""" return [ (k, v) for v, k in sorted([(v, k) for k, v in d.items()], reverse=True) ]
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def check_length(min_length: int, max_length: int, mode: str = 'and', *args) -> bool: """ check items length is between min_length and max_length :param min_length: minimum length :param max_length: maximum length :param mode: check mode, 'and': all...
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def check_processed_data(df,col_list,na_action): """ Checks if provided dataframe consists of required columns and no missing values """ check_passed = True # Check columns df_cols = df.columns if set(df_cols) != set(col_list): check_passed = False print('Column names mismatched...
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def _determine_levels(index): """Determine the correct levels argument to groupby.""" if isinstance(index, (tuple, list)) and len(index) > 1: return list(range(len(index))) else: return 0
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def format_val(v): """Takes in float and formats as str with 1 decimal place :v: float :returns: str """ return '{:.1f}%'.format(v)
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import re def you_to_yall(text: str) -> str: """Convert all you's to y'all.""" pattern = r'\b(y)(ou)\b' return re.sub(pattern, r"\1'all", text, flags=re.IGNORECASE)
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def to_aws_tags(tags): """ When you assign tags to an AWS resource, you have to use the form [{"key": "KEY1", "value": "VALUE1"}, {"key": "KEY2", "value": "VALUE2"}, ...] This function converts a Python-style dict() into these tags. """ return [ {"key": key, "valu...
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def get_game_player(game_state): """Get the game player whose turn it is to play.""" num_players = len(game_state.game_players) for game_player in game_state.game_players: if game_state.turn_number % num_players == game_player.turn_order: return game_player return None
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import re def get_headers_pairs_list(filename, verbose=False): """ Read data for clustering from a given file. Data format: <email_number> <header>. Clusters are separated with a blank line. :param filename: file with input data for clustering. :param verbose: Whether to be verbose. Default ...
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from pathlib import Path def _run_jlab_string(talktorials_dst_dir): """ Print command for starting JupyterLab from workspace folder. Parameters ---------- talktorials_dst_dir : str or pathlib.Path Path to directory containing the talktorial folders. """ talktorials_dst_dir = Path...
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def get_table_type(filename): """ Accepted filenames: device-<device_id>.csv, user.csv, session-<time_iso>.csv, trials-<time_iso>-Block_<n>.csv :param filename: name of uploaded file. :type filename: str :return: Name of table type. :rtype: str|None """ basename, ext = f...
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def make_download_filename(genome, args, response_format): """ Make filename that will explain to the user what the predictions are for :param genome: str: which version of the genome we are pulling data from :param args: SearchArgs: argument used for search :param response_format: str file extensio...
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def change(csq): """ >>> change("missense|TMEM240|ENST00000378733|protein_coding|-|170P>170L|1470752G>A") ('170P', '170L', True) >>> change('synonymous|AGRN|ENST00000379370|protein_coding|+|268A|976629C>T') ('268A', '268A', False) """ parts = csq.split("|") if len(parts) < 7: ret...
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def with_coordinates(pw_in_path, positions_type, atom_symbols, atom_positions): """Return a string giving a new input file, which is the same as the one at `pw_in_path` except that the ATOMIC_POSITIONS block is replaced by the one specified by the other parameters of this function. `positions_type`, `a...
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def calculate_factor_initial_size(n, key): """ Calculate different initial embedding sizes by a chosen factor. :param n: Number of nodes in the graph :param key: The factor- for example if key==10, the sizes will be n/10, n/100, n/100, .... the minimum is 100 nodes in the initial embedding :retu...
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def is_iterable(value): """ Verifies the value is an is_iterable :param value: value to identify if iterable or not. """ try: iterable_obj = iter(value) return True except TypeError as te: return False
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def rw_normalize(A): """ Random walk normalization: computes D^⁼1 * A. Parameters ---------- A: torch.Tensor The matrix to normalize. Returns ------- A_norm: torch.FloatTensor The normalized adjacency matrix. """ degs = A.sum(dim=1) degs[degs == 0] = 1 r...
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import logging def _get_areas(params, feature_names): """Returns mapping between areas and constituent feature types.""" areas = {} for feature_id in range(len(params)): feature_info = params[feature_id] feature = feature_info["ID"] area = feature_info["Area"] if area not in areas: areas[a...
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def transform_seed_objects(objects): """Map seed objects to state format.""" return {obj['instance_id']: { 'initial_player_number': obj['player_number'], 'initial_object_id': obj['object_id'], 'initial_class_id': obj['class_id'], 'created': 0, 'created_x': obj['x'], ...
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from pathlib import Path def getFileAbsolutePath(rel_path): """ Retorna o caminho absoluto de um arquivo a partir de seu caminho relativo no projeto :param rel_path: :return: absolute_path """ data_folder = Path("PythoWebScraper/src") file_to_open = data_folder / rel_path return file_...
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def directive_exists(name, line): """ Checks if directive exists in the line, but it is not commented out. :param str name: name of directive :param str line: line of file """ return line.lstrip().startswith(name)
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def entrypoint(label): """ If a class if going to be registered with setuptools as an entrypoint it must have the label it will be registered under associated with it via this decorator. This decorator sets the ENTRY_POINT_ORIG_LABEL and ENTRY_POINT_LABEL class proprieties to the same value, la...
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def hide_empty(value, prefix=', '): """Return a string with optional prefix if value is non-empty""" value = str(value) return prefix + value if value else ''
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def as_dict_with_keys(obj, keys): """ Convert SQLAlchemy model to list of dictionary with provided keys. """ return [dict((a, b) for (a, b) in zip(keys, item)) for item in obj]
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def sdate_from_datetime(datetime_object, format='%y-%m-%d'): """ Converts a datetime object to SDATE string. """ return datetime_object.strftime(format)
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def arrays_shape(*arrays): """Returns the shape of the first array that is not None. Parameters ---------- arrays : ndarray Arrays. Returns ------- tuple of int Shape. """ for array in arrays: if array is not None: shape = array.shape ...
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def cone(toplexes, subcomplex, coneVertex="*"): """Construct the cone over a subcomplex. The cone vertex can be renamed if desired. The resulting complex is homotopy equivalent to the quotient by the subcomplex.""" return toplexes + [spx + [coneVertex] for spx in subcomplex]
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def bipartite_sets(bg): """Return two nodes sets of a bipartite graph. Parameters: ----------- bg: nx.Graph Bipartite graph to operate on. """ top = set(n for n, d in bg.nodes(data=True) if d['bipartite']==0) bottom = set(bg) - top return (top, bottom)
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def _merge_block(internal_transactions, transactions, whitelist): """ Merge responses with trace and chain transactions. Remove non-whitelisted fields Parameters ---------- internal_transactions : list List of trace transactions transactions : list List of chain transactions ...
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def remove_virtual_slot_cmd(lpar_id, slot_num): """ Generate HMC command to remove virtual slot. :param lpar_id: LPAR id :param slot_num: virtual adapter slot number :returns: A HMC command to remove the virtual slot. """ return ("chhwres -r virtualio --rsubtype eth -o r -s %(slot)s " ...
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import json def dict_to_bytestring(dictionary): """Converts a python dict to json formatted bytestring""" return json.dumps(dictionary).encode("utf8")
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def _merge_candidate_name(src, dest): """Returns the formatted name of a merge candidate branch.""" return f"xxx-merge-candidate--{src}--{dest}"
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def decorator_with_args(decorator_to_enhance): """ This is decorator for decorator. It allows any decorator to get additional arguments """ def decorator_maker(*args, **kwargs): def decorator_wrapper(func): return decorator_to_enhance(func, *args, **kwargs) return decorator_...
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import re def find_subtype(meta_dict): """Find subtype from dictionary of sequence metadata. Args: `meta_dict` (dict) dictionary of metadata downloaded from genbank Returns: `subtype` (str) RSV subtype as one letter string, 'A' or 'B'. """ subtype = '' if '...
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from typing import Sequence from typing import Type from typing import Union def unique_fast( seq: Sequence, *, ret_type: Type[Union[list, tuple]] = list ) -> Sequence: """Fastest order-preserving method for (hashable) uniques in Python >= 3.6. Notes ----- Values of seq must be hashable! See...
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def getHeaders(lst, filterOne, filterTwo): """ Find indexes of desired values. Gets a list and finds index for values which exist either in filter one or filter two. Parameters: lst (list): Main list which includes the values. filterOne (list): A list containing values to find indexes of in the main list...
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def top(Q): """Inspects the top of the queue""" if Q: return Q[0] raise ValueError('PLF ERROR: empty queue')
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def move_items_back(garbages): """ Moves the items/garbage backwards according to the speed the background is moving. Args: garbages(list): A list containing the garbage rects Returns: garbages(list): A list containing the garbage rects """ for garbage_rect in garbages: # Loop...
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import re def _mask_pattern(dirty: str): """ Masks out known sensitive data from string. Parameters ---------- dirty : str Input that may contain sensitive information. Returns ------- str Output with any known sensitive information masked out. """ # DB credenti...
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def __remove_duplicate_chars(string_input, string_replace): """ Remove duplicate chars from a string. """ while (string_replace * 2) in string_input: string_input = \ string_input.replace((string_replace * 2), string_replace) return string_input
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def format_birthday_for_database(p_birthday_of_contact_month, p_birthday_of_contact_day, p_birthday_of_contact_year): """Takes an input of contact's birthday month, day, and year and creates a string to insert into the contacts database.""" formated_birthday_string = p_birthday_of_contact_month + "/" + p_birthd...
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import math def normal_distribution(x: float) -> float: """ 標準正規分布 f(x) = (1/sqrt(2pi))exp(-x^2/2) """ # 係数 coefficient = 1 / math.sqrt(2 * math.pi) # 指数 exponent = math.exp(-(x ** 2) / 2) # 標準正規分布 return coefficient * exponent
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def str_format(s, *args, **kwargs): """Return a formatted version of S, using substitutions from args and kwargs. (Roughly matches the functionality of str.format but ensures compatibility with Python 2.5) """ args = list(args) x = 0 while x < len(s): # Skip non-start token characters...
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def read_float(field: str) -> float: """Read a float.""" return float(field) if field != "" else float('nan')
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def make_word(parts, sub, i): """Replace a syllable in a list of words, and return the joined word.""" j = 0 for part in parts: for k in range(len(part)): if i == j: part[k] = sub return ' '.join(''.join(p for p in part) for part in parts) j +=...
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def reverse_complement(string): """Returns the reverse complement strand for a given DNA sequence""" return(string[::-1].translate(str.maketrans('ATGC','TACG')))
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def _parse_seq(seq): """Get a primary sequence and its length (without gaps)""" return seq, len(seq.replace('-', ''))
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def reverse_digit(x): """ Reverses the digits of an integer. Parameters ---------- x : int Digit to be reversed. Returns ------- rev_x : int `x` with it's digits reversed. """ # Initialisations if x < 0: neg = True else: neg ...
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def hammingDistance(str1, str2): """ Returns the number of `i`th characters in `str1` that don't match the `i`th character in `str2`. Args --- `str1 : string` The first string `str2 : string` The second string Returns --- `differences : int` The differences between `str1` and `str2` ...
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from typing import OrderedDict def _order_dict(d): """Convert dict to sorted OrderedDict""" if isinstance(d, dict): d = [(k, v) for k, v in d.items()] d = sorted(d, key=lambda x: x[0]) return OrderedDict(d) elif isinstance(d, OrderedDict): return d else: raise E...
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def clean_toc(toc: str) -> str: """Each line in `toc` has 6 unnecessary spaces, so get rid of them""" lines = toc.splitlines() return "\n".join(line[6:] for line in lines)
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import pickle def pickle_load(file_path): """ data = pickle_load(file_path) Load data from a pickle dump file inputs: file_path: str, path of the pickle file output: data: python object """ with open(file_path, 'rb') as file_ptr: data = pickle.load(file_ptr) r...
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def versiontuple(v): """Return the version as a tuple for easy comparison.""" return tuple(int(x) for x in v.split("."))
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import re def find_checksum(s): """Accepts a manifest-style filename and returns the embedded checksum string, or None if no such string could be found.""" m = re.search(r"\b([a-z0-9]{32})\b", s, flags=re.IGNORECASE) md5 = m.group(1).lower() if m else None return md5
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def get_expts(context, expts): """Takes an expts list and returns a space separated list of expts.""" return '"' + ' '.join([expt['name'] for expt in expts]) + '"'
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def create_filename(last_element): """ For a given file, returns its name without the extension. :param last_element: str, file name :return: str, file name without extension """ return last_element[:-4]
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def simplify_numpy_dtype(dtype): """Given a numpy dtype, write out the type as string Args: dtype (numpy.dtype): Type Returns: (string) name as a simple string """ kind = dtype.kind if kind == "b": return "boolean" elif kind == "i" or kind == "u": return "in...
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def OpenFace(openface_features, PID, EXP): """ Tidy up OpenFace features in pandas data.frame to be stored in sqlite database: - Participant and experiment identifiers are added as columns - Underscores in column names are removed, because sqlite does not like underscores in column names. ...
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import copy def deep_merge_dict(base, priority): """Recursively merges the two given dicts into a single dict. Treating base as the the initial point of the resulting merged dict, and considering the nested dictionaries as trees, they are merged os: 1. Every path to every leaf in priority would be re...
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def _get_span(s, pattern): """Return the span of the first group that matches the pattern.""" i, j = -1, -1 match = pattern.match(s) if not match: return i, j for group_name in pattern.groupindex: i, j = match.span(group_name) if (i, j) != (-1, -1): return i, j ...
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from pathlib import Path def guess_format(path): """Guess file format identifier from it's suffix. Default to DICOM.""" path = Path(path) if path.is_file(): suffixes = [x.lower() for x in path.suffixes] if suffixes[-1] in ['.h5', '.txt', '.zip']: return suffixes[-1][1:] ...
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def get_samples(profileDict): """ Returns the samples only for the metrics (i.e. does not return any information from the activity timeline) """ return profileDict["samples"]["metrics"]
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def dobro(n): """ Dobrar número :param n: número a ser dobrado :return: resultado """ n = float(n) n += n return n
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def aoi_from_experiment_to_cairo(aoi): """Transform aoi from exp coordinates to cairo coordinates.""" width = round(aoi[1]-aoi[0], 2) height = round(aoi[3]-aoi[2], 2) return([aoi[0], aoi[2], width, height])
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def palindromic(d): """Gets a palindromic number made from a product of two d-digit numbers""" # Get the upper limit of d digits, e.g 3 digits is 999 a = 10 ** d - 1 b = a # Get the lower limit of d digits, e.g. 3 digits is 100 limit = 10 ** (d - 1) for x in range(a, limit - 1, -1): ...
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def markup(pre, string): """ By Adam O'Hern for Mechanical Color Returns a formatting string for modo treeview objects. Requires a prefix (usually "c" or "f" for colors and fonts respectively), followed by a string. Colors are done with "\03(c:color)", where "color" is a string representing a ...
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from bs4 import BeautifulSoup def get_person_speech_pair(file_name): """ XML parser to get the person_ids from given XML file Args: file_name(str): file name Returns: person_id_speech_pair(dict): Dict[person_id(int) -> speech(str)] """ person_id_speech_dict = dict() with op...
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def _pad_keys_tabular(data, sort): """Pad only the key fields in data (i.e. the strs) in a tabular way, such that they all take the same amount of characters Args: data: list of tuples. The first member of the tuple must be str, the rest can be anything. Returns: list with the strs padded with space cha...
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import bz2 import base64 def passx_decode(passx): """decode the obfuscated plain text password, returns plain text password""" return bz2.decompress(base64.b64decode(passx.encode("ascii"))).decode("ascii")
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def checksum_file(summer, path): """ Calculates the checksum of the file 'path' using the provided hashlib digest implementation. Returns the hex form of the digest. """ with open(path, "rb") as f: # Read the file in 4KB chunks until EOF. while True: chunk = f.read(4096) if not chunk: ...
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def camel_case(value): """Convert an identifier to CamelCase""" return "".join(ele.title() for ele in value.split("_"))
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def format_directory_path(path: str) -> str: """Replaces windows style path seperators to forward-slashes and adds another slash to the end of the string. """ if path == ".": return path formatted_path = path.replace('\\', '/') if formatted_path[-1] is not '/': formatted_path += ...
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def get_metagen_search_body(self): """ Get the MetaGenSearchView view body. Attributes ---------- measure: str the genomic measure label. gene: str the gene name. Returns ------- html: str the MetaGenSearchView view body. """ # Get parameters measure...
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def _toCamelCase(string): """Convert a snake case string (PyTorch) to camel case (PopART)""" words = string.split("_") return words[0] + "".join(w.capitalize() for w in words[1:])
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def pulse(x): """Return the pulse fn of the input.""" return 2*(x % 1 < .5) -1
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def index_singleton_clusters(clusters): """Replace cluster labels of -1 with ascending integers larger than the maximum cluster index. """ clusters = clusters.copy() filt = clusters == -1 n = clusters.max() clusters[filt] = range(n, n + len(filt)) return clusters
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def scaled_up_roi(roi, scale: int, shape=None): """ Compute ROI for a scaled up image. Given a crop region in the original image compute equivalent crop in the upsampled image. :param roi: ROI in the original image :param scale: integer scale to get scaled up image :return: ROI in the scaled u...
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def test_depends(func): """Decorator to prevent a test being executed in individual mode""" def invalid(self, test): if self.test_individual: test.description = "Invalid" return test.DISABLED("This test cannot be performed individually") else: return func(self...
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def fix_month(bib_str: str) -> str: """Fixes the string formatting in a bibtex entry""" return ( bib_str.replace("{Jan}", "jan") .replace("{jan}", "jan") .replace("{Feb}", "feb") .replace("{feb}", "feb") .replace("{Mar}", "mar") .replace("{mar}", "mar") .r...
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def pad(text: str, width: int, align: str = '<', fill: str = ' '): """ pad the string with `fill` to length of `width` :param text: text to pad :param width: expected length :param align: left: <, center: ^, right: > :param fill: char to fill the padding :return: """ assert align in ...
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import torch def create_input(shape): """Create a random input tensor.""" return torch.rand(shape).float()
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def add_data_to_list(twitter_return): """ Extract the data from the twitter_return dictionary and place in a list """ twitter_dict = twitter_return ['response_dict'] # Grab the twitter data twitter_data_list=twitter_dict['data'] return twitter_data_list
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from typing import Dict def get_noise_range_pcts(db_range_exps: dict, length: float) -> Dict[int, float]: """Calculates percentages of aggregated exposures to different noise levels of total length. Note: Noise levels exceeding 70 dB are aggregated and as well as noise levels lower than 50 dB. Re...
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def calc_n_max_vehicle(n2v_g_vmax, v_max): """Calc `n_max3` of Annex 2-2.g from `v_max` (Annex 2-2.i). """ return n2v_g_vmax * v_max
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def get_filepath_wo_ext(file_spec): """ Get file path without extension Parameters ---------- file_spec : DataStruct The function use attributes output_dir and fname_wo_ext for construct file path Returns ------- out : str Constructed file path """ return file_...
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def amplitude(data): """ Calculates the amplitude of a data list. """ n = len(data) if (n == 0) : amplitude = None else : min_value = min(data) max_value = max(data) amplitude = (max_value + min_value) / 2.0 return amplitude
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def ranks_from_scores(scores): """Return the ordering of the scores""" return sorted(range(len(scores)), key=lambda i: scores[i], reverse=True)
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import struct def unpack_word(str, big_endian=False): """ Unpacks a 32-bit word from binary data. """ endian = ">" if big_endian else "<" return struct.unpack("%sL" % endian, str)[0]
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import ast def parse_source(source, path=None): """Parse python source into an AST.""" path = "<unknown>" if path is None else path return ast.parse(source, filename=path)
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def is_hit(x, y): """Return wheter given coords hit a circular target of r=1.""" return x*x + y*y <= 1
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def set_fpn_weights(training_model, inference_model, verbose=False): """ Set feature pyramid network (FPN) weights from training to inference graph Args: training_model: MaskRCNN training graph, tf.keras.Model inference_model: MaskRCNN inference graph, tf.keras.Model verbose: ...
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def navamsa_from_long(longitude): """Calculates the navamsa-sign in which given longitude falls 0 = Aries, 1 = Taurus, ..., 11 = Pisces """ one_pada = (360 / (12 * 9)) # There are also 108 navamsas one_sign = 12 * one_pada # = 40 degrees exactly signs_elapsed = longitude / one_sign fraction_left = sig...
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def compare_connexion(conn1, conn2): """See if two connexions are the same. Because the :class:`connexion` could store the two components in different orders, or have different instances of the same component object, direct comparison may fail. This function explicitly compares both possible combina...
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def without_end_slash(url): """Makes sure there is no end slash at the end of a url.""" return url.rstrip("/")
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from stat import S_ISDIR def list_remote_files(con, directory): """ List the files and folders in a remote directory using an active SFTPClient from Paramiko :param con: SFTPClient, an active connection to an SFTP server :param directory: string, the directory to search :return: (generator, generator), the files...
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def distinct_count(daskDf, columnName): """Counts distint number of values in Dask dataframe Keyword arguments: daskDf -- Dask dataframe columnName -- Column name Return: return -- Distinct number of values """ return daskDf[columnName].drop_duplicates().size
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from typing import OrderedDict def save_chain(config, chain): """ Encode a chain of operation classes as json. :param config: dictionary with settings. :param chain: OrderedDict of operation class lists. :return: string-encoded version of the above. """ di = OrderedDict() di['__config__'] = config for k...
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def db_connection_string(dbconf): # type: (dict) -> str """ Constructs a database connection string from the passed configuration object. """ user = dbconf["user"] password = dbconf["password"] db_name = "traffic_ops" if dbconf["type"] == "Pg" else dbconf["type"] hostname = dbconf["hostname"] port = dbconf["por...
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def normalize_units( df, unitsmap, targetunit, paramcol="parameter", rescol="res", unitcol="units", napolicy="ignore", ): """ Normalize units of measure in a dataframe. Parameters ---------- df : pandas.DataFrame Dataframe contained results and units of measure d...
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from typing import List from typing import Dict from typing import Any def format_sents_for_output(sents: List[str], doc_id: str) -> Dict[str, Dict[str, Any]]: """ Transform a list of sentences into a dict of format: { "sent_id": {"text": "sentence text", "label": []} } """ ...
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