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def add_to_visited_places(x_curr: int, y_curr: int, visited_places: dict) -> dict: """ Visited placs[(x,y)] contains the number of visits that the cell (x,y). This updates the count to the current position (x_curr, y_curr) Args: x_curr: x coordinate of current position y_curr: ...
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from datetime import datetime def get_date() -> str: """Get the current date in order to properly name the recored log files Returns: str: The current date in: YY_MM_DD format """ return datetime.now().strftime('%Y_%m_%d')
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from typing import List def flatten(lst: List) -> list: """Reduce a nested list to a single flat list. >>> flatten(["A", [2, ["C"]], ["DE", (5, 6)]]) == ["A", 2, "C", "DE", 5, 6] True """ result = [] for item in lst: isiterable = False try: iter(item) i...
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import torch def distV(x:torch.Tensor) -> torch.Tensor: """Distance vectors of points. :param x: location Tensor of shape (n, 3) :returns: vector Tensor of shape (n, n, 3)""" n = x.shape[0] return x.view(1, n, 3) - x.view(n, 1, 3)
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def defvalkey(js, key, default=None, take_none=True): """ Returns js[key] if set, otherwise default. Note js[key] can be None. :param js: :param key: :param default: :param take_none: :return: """ if js is None: return default if key not in js: return default ...
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import re def add_accessions2(genomes: dict) -> dict: """ Some genomes have their assembly accession in the 'sourceName' field. Updates the the genome dict "assembly_accession" field for each genome found. """ re_acc = re.compile(r"GC[AF]_\d{9}\.\d+") for name in genomes: hit = re_acc...
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def fixture_use_real_aws(request): """Indicates whether the 'use actual AWS' option is on or off.""" return request.config.getoption("--use-real-aws-may-incur-charges")
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def make_window(x, y, xmin, ymin, windowsize): """ Create a window for writing a child tile to a parent output tif """ if x < xmin or y < ymin: raise ValueError("Indices can't be smaller than origin") row = (y - ymin) * windowsize col = (x - xmin) * windowsize return ( (...
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def first(sequence, condition=None): """ Returns the first item in a sequence that satisfies specified condition or raises error if no item found. Args: sequence: iterable Sequence of items to go through. condition: callable Condition to test. ...
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import copy def convert_results_to_list(results, deep_copy=True): """ Given a Whoosh results object, converts it to a list and returns that list. Useful, as the Whoosh results object does not permit reassignment of Hit objects. Note that if deep_copy is True, a deep copy of the list is returned. "...
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import math def simple_half_live(q, k, dt): """ Return the remaining quantity after biodegradation occuring during a time interval Parameters ---------- q : Amount k : Half life constant [1/s] dt : Time interval [s] """ return q*(1-math.e**(-k*dt))
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def reverse_downsample(self, ftimes, other_spatial, other_ftimes, **kwargs): """ Perform downsample_place the with the spatial data swapped. Calls other_spatial.downsample_place( other_ftimes, self, ftimes, **kwargs) See Also -------- downsample_place """ return other_spatial...
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def nsec_to_usec_round(DatetimeNanos) -> int: """Round nanoseconds to microseconds Timestamp in zipkin spans is int of microseconds. See: https://zipkin.io/pages/instrumenting.html """ inttimestamp = DatetimeNanos.timestamp() * 1e9 return int((inttimestamp + 500) // 10 ** 3)
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def count(text, pattern): """How many times the given pattern appears in the text""" i = 0 n = 0 while i <= len(text) - len(pattern): if text[i:i+len(pattern)] == pattern: n = n + 1 i = i + 1 return n
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import random def seed42(request): """A fixture that sets the random seed to 42, for consistency""" random.seed(42) return request
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def _is_password_valid(pw): """Returns `true` if password is strong enough for Firebase Auth.""" return len(pw) >= 6
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import string import secrets def get_alphanumeric_unique_tag(tag_length: int) -> str: """Generates a random alphanumeric string (a-z0-9) of a specified length""" if tag_length < 1: raise ValueError("Unique tag length should be 1 or greater.") use_chars = string.ascii_lowercase + string.digits ...
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def _parse_spectre_coefficients (hist_line): """ parse the coefficients from the spectre line Parameters ---------- hist_line : string "HISTORY 23: 7:2008 D1,2,3: 5.50348825884E+03 4.46070136915E-02 0.00000000000E+00" Returns ------- coefficients : list [5.503488258...
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def min_point(points, n_points): """ Return the index of the closest point to (0,0) :param points: tuple of list for each coordinate :param n_points: number of points :return: the index of the selected point in the list """ min_y_indexes = [0] min_y = points[1][0] # Find minimum y ...
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def commajoin(*items): """ Small helper function that joins all items by comma and maps types of items into strings. """ return ",".join(map(str, items))
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def _strip_path_prefix(path, prefix): """Strip a prefix from a path if it exists and any remaining prefix slashes Args: path: <string> prefix: <string> Returns: <string> """ if path.startswith(prefix): path = path[len(prefix):] if path.startswith("/"): pa...
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import functools def prod(factor): """ Equivalent to sum(list) with multiplication. Return the multiplication of all the elements in the list. """ return functools.reduce(lambda x, y: x*y, factor, 1)
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def add_computer (api, configuration, api_version, api_exception, hostname): """ Adds a computer to Deep Security Manager. :param api: The Deep Security API modules. :param configuration: Configuration object to pass to the api client. :param api_version: The version of the API to use. :param api_e...
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def fake_request(*responses): """ Creates a request function that returns the supplied responses, one at a time. Making a new request after the last response has been returned results in a StopIteration error. """ iterator = (response for response in responses) def request(method, url, **kwargs...
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def IsInTargetRange( target, error_ref, warning_percentage, error_percentage, value): """Test if a value falls into warning or error range around a target. Args: target: The target value. error_ref: The error reference as the base for warning/error percentage. warning_percentage: The percentage of ...
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def KeyValuePairMessagesToMap(key_value_pair_messages): """Transform a list of KeyValuePair message to a map. Args: key_value_pair_messages: a list of KeyValuePair message. Returns: a map with a string as key and a string as value """ return {msg.key: msg.value for msg in key_value_pair_messages}
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def forward_and_adapt(x, criterion, model, optimizer): """Forward and adapt model on batch of data. Measure entropy of the model prediction, take gradients, and update params. """ # forward outputs = model(x) # adapt loss = criterion(outputs) loss.backward() optimizer.step() opti...
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def rfc822_date(date): """Return date in RFC822 format For reference, the format (in CLDR notation) is: EEE, dd MMM yyyy HH:mm:ss Z With the caveat that the weekday (EEE) and month (MMM) are always in English. Example: Sat, 19 Sep 2015 14:53:07 +0100 For what it's worth, this ...
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def out_of_bounds(subject, start, end): """Check if the subject is completely outside of a given range""" return subject.start < start or subject.end > end
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import torch def pack(inputs, is_tensor=False): """Pack the inputs into tuple if they were a single tensor""" single = torch.is_tensor(inputs) outputs = (inputs, ) if single else inputs return (outputs, single) if is_tensor else outputs
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def convertMessagetoBinaryString(input): """convert ascii string or raw bytes (depending on if it is an ascii string) to string containing binary representation""" #take each character and pad to be 8 bits, add to output string and return entire string. output = "" if input.isascii(): input = in...
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def is_dialog_complete(handler_input): """ Checks whether the dialog is complete according to the dialog model :param handler_input: (HandlerInput) :return: (boolean) """ if not hasattr(handler_input.get_request(), "dialogState"): return False return handler_input.get_request().di...
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def search_string(text: str, pattern: str, starting_point: int = 0) -> int: """ Search a text for a pattern given a starting point Arguments: text - The text we're searching through pattern - The pattern we're searching for starting_point - The point in the strin...
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def apply_case(s, case): """Helper function that applies case to a string.""" if case.upper() == "UPPER": s = s.upper() elif case.upper() == "LOWER": s = s.lower() elif case.upper() == "CAPITALIZE": s = s.capitalize() elif case.upper() == "TITLE": s = " ".join([w.cap...
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def _value_sorter(feature_value): """Custom sorting function taking into account the structure of values. Given a feature value extracts its numeric portion, e.g. "18 ObligDoubleNeg" -> "18". Args: feature_value: (string) WALS feature value. Returns: An integer corresponding to the first portion ...
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def get_last_conv_layer(keras_model): """ Get last convolution layer name of keras model input: Keras model output: string of the name of the last convolution layer Make sure last convolution layer has "conv" in the name! """ layer_names=[layer.name for layer in keras_model.layers] layer_names.revers...
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def cheating_matrix(seating_chart): """ Calculate and return the probabilities of cheating for each position in a rxc grid :param seating_chart: A nested list representing a rxc grid :return: A nested list, the same size as seating_chart, with each element representing that position's cheati...
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def run(*args, initial=None): """Creates and runs the pipe calling functions in given sequence. Args: *args: functions to call in sequence initial: argument to the first function (pipe argument) Returns: result of the last function called """ data = initial for fun in ...
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def simple_hash(token: str, output_size: int) -> int: """ This runs a simple, deterministic hash function on the input token. This needs to be exactly duplicated in Java, and is very sensitive. In general, don't change this function. :param token: the token to hash :param output_size: the outpu...
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def has_fact_sheets(responses, derived): """ Return whether or not the user is submitting fact sheets """ return any([derived['show_fact_sheet_b'], derived['show_fact_sheet_c'], derived['show_fact_sheet_d'], derived['show_fact_sheet_e'], derived['show_fact_sheet_f'], ])
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def deleted_genes_to_reactions(model, genes): """ Convert a set of deleted genes to the respective deleted reactions. Arguments: model (CBModel): model genes (list): genes to delete Returns: list: list of deleted reactions """ if isinstance(genes, str): genes = [ge...
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def ensure_tuple(tuple_or_mixed, *, cls=tuple): """ If it's not a tuple, let's make a tuple of one item. Otherwise, not changed. :param tuple_or_mixed: :return: tuple """ if isinstance(tuple_or_mixed, cls): return tuple_or_mixed if tuple_or_mixed is None: return tuple...
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def df_div(df0, df1, axis=1): """Wrapper function to divide two Pandas data frames in a functional manner. Args: df0 (:obj:`pd.DataFrame`): First data frame. df1 (:obj:`pd.DataFrame`): Second data frame. axis (int): Axis; defaults to 1. Returns: The quotient from applyi...
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def _is_out_of_order(segmentation): """ Check if a given segmentation is out of order. Examples -------- >>> _is_out_of_order([[0, 1, 2, 3]]) False >>> _is_out_of_order([[0, 1], [2, 3]]) False >>> _is_out_of_order([[0, 1, 3], [2]]) True """ last_stroke = -1 for symbo...
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def convert_newlines(msg): """A routine that mimics Python's universal_newlines conversion.""" return msg.replace('\r\n', '\n').replace('\r', '\n')
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import math def is_square(x): """Returns True if x is a perfect square. Otherwise False. Examples -------- >>> is_square(1) True >>> is_square(-1) False >>> is_square(4) True """ try: return int(math.sqrt(x)) == math.sqrt(x) except ValueError: r...
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def pairs(seq): """Return a sequence in pairs. Arguments: seq (sequence): A sequence with an even number of elements. If the number is uneven, the last element will be ignored. Returns: A zip object with tuple pairs of elements. Example: >>> list(pairs(...
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import re def unixify_string(string): """ Sanitizes a string making it nice for unix by processing special characters. Removes: ()!? and spaces, Replaces with underscores: '/' and ' ' Parameters ---------- string : str the string to sanitize Returns ------- str ...
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import uuid def _create_uuid() -> uuid.UUID: """Creates a valid UUID 4. Returns: uuid.UUID: A UUID """ return uuid.uuid4()
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def null_processor(value): """Processor that does nothing, just returns the value""" return value
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def autotype_seq(entry): """Return value for autotype sequence Args: entry - dict Return: string """ return next((i.get('value') for i in entry['fields'] if i.get('name') == 'autotype'), "")
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import torch def new_arange(x, *size): """ Return a Tensor of `size` filled with a range function on the device of x. If size is empty, using the size of the variable x. """ if len(size) == 0: size = x.size() return torch.arange(size[-1], device=x.device).expand(*size).contiguous()
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import shutil def zipfile_make_archive(dirname, to=None, **kwargs): """ Thin layer over shutil.make_archive. Just defaults the to to the same name as the directory by default. :param dirname: (str) The directory name :param to: (str, default None) The file path to create the archi...
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def pegar_carta_index(lista_jogadores, jogador_da_vez, index_carta): """ -> Irá pegar o dicionário da carta através do índice da mesma na lista :param lista_jogadores: lista contendo os baralhos dos jogadores :param jogador_da_vez: jogador da vez :param index_carta: índice da carta que o usuário des...
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def _unique_combinations(model, ignore_pk=False): """ Returns an iterable of iterables to represent all the unique constraints defined on the model. For example given the following model definition: class ExampleModel(models.Model): username = models.CharField(unique=True) e...
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def _remove_trailing_chars(text: str) -> str: """ Removes trailing characters from the beginning or end of a string. """ chars = ['.', '@', '/', '&', '-', "'"] for char in chars: text = text.strip(char) return text
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import torch def compute_loss(inputs, outputs, criterion, edge_criterion): """Compute loss automatically based on what the model output dict contains. 'doc_logits' -> document-label CE loss 'para_logits' -> paragraph-label CE loss 'pare_edge_weights' -> additional edge CE loss """ if 'para_log...
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def CanonicalizeAddress(addr): """Strip angle brackes from email address iff not an empty address ("<>"). Args: addr: the email address to canonicalize (strip angle brackets from). Returns: The addr with leading and trailing angle brackets removed unless the address is "<>" (in which case the string...
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def merge_info(chr_list, pos_split, name_pos_split_list, no_chrom_list): """ Merges all lists created above to be used for DataFrame. Args: chr_list (list): the list with the chromosome info of product pos_split_list (list): the list with the split positions name_pos_split_list (list...
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from datetime import datetime def first_of_year(dte): """ Return the first day of the year for the specified date. Argument: dte - a date """ year = dte.year first = datetime(year, 1, 1) return first
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def get_mip_at_res(vol, resolution): """Find the mip that is at least a given resolution Args: vol (cloudvolume.CloudVoluem): CloudVolume object for desired precomputed volume resolution (int): Desired resolution in nanometers Returns: tuple: mip and resolution at that mip """ ...
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def array_to_grader(array, epsilon=1e-4): """Utility function to help preparing Coursera grading conditions descriptions. Args: array: iterable of numbers, the correct answers epslion: the generated expression will accept the answers with this absolute difference with provided values ...
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def _neighbor_keys_from_bond_keys(key, bnd_keys): """ Determine neighbor keys of an atom from the bond keys """ nkeys = [] for bnd_key in bnd_keys: if key in bnd_key: nkey, = bnd_key - {key} nkeys.append(nkey) return frozenset(nkeys)
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def LOS(arr): """The function is to find the maximum ordered subarray in a array Arguments: arr {int} -- It is a list of numbers Returns: arr {int} -- Returns the the maximum ordered subarray and Length """ n = len(arr) # Declare the list (array) for LIS and initialize LIS ...
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def get_url_without_trailing_slash(value): """ Function which strips a trailing slash from the provided url if one is present. :param value: URL to format. :type value: ``str`` :rtype: ``str`` """ result = value[:-1] if value.endswith("/") else value return result
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def oposto(a): """ Faz a negação do literal de acordo com os moldes do algoritmo. :param a: literal :return: negação do literal """ if a[0] == '~': aux = a[1:] else: aux = ''.join(['~', a]) return aux
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import pytz def getAwareTime(tt): """ Generates timezone aware timestamp from timezone unaware timestamp PARAMETERS ------------ :param tt: datatime timezome unaware timestamp RETURNS ------------ :return: datatime timezone aware timestamp ...
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def append_line(buf, linearr): """Append lines Args: buf (obj): Nvim buffer linearr (Array[string]): Line contents Returns: suc (bool): True if success """ for l in linearr: buf.append(l) return True
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def get_mac_addr_from_dbus_path(path): """Return the mac addres from a dev_XX_XX_XX_XX_XX_XX dbus path""" return path.split("/")[-1].replace("dev_", '').replace("_", ":")
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def is_biallelic(variant): """Returns True if variant has exactly one alternate allele.""" return len(variant.alternate_bases) == 1
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def equated_monthly_installments( principal: float, rate_per_annum: float, years_to_repay: int ) -> float: """ Formula for amortization amount per month: A = p * r * (1 + r)^n / ((1 + r)^n - 1) where p is the principal, r is the rate of interest per month and n is the number of payments >>>...
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def tag_function(entry): """ Default tag function Given a PDB report entry, generate a list of tags to apply to the entry when created in the database. This function can be overridden through the PDB_TAG_FUNCTION settings variable :param entry: :return: """ return [entry['diffrn_source....
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def give_pendant(character: str) -> str: """Returns the pendant to each character.""" if character == ')': return '(' if character == ']': return '[' if character == '}': return '{' if character == '>': return '<' raise ValueError(f"Unknown character '{character}' encountered.")
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import math def calc_node_distance(graph, node_1, node_2): """ Calculates distance between two nodes of graph, Requires node attribute 'position' as shapely Point, e.g. Point(10, 15.2) Parameters ----------- graph : nx.graph Graph object of networkx node_1 : int Node id of...
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def pad_base64(data): """ Pads a base64 encoded string Args: data (str): The base64 encoded string Returns: str: The padded base64 encoded string """ data = data.replace("-", "+").replace("_", "/") missing_padding = len(data) % 4 if missing_padding: data += "=...
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def predictions_for_df(df, inferrer): """Returns df with column that's the activations for each sequence. Args: df: DataFrame with columns 'sequence' and 'sequence_name'. inferrer: inferrer. Returns: pd.DataFrame with columns 'sequence_name', 'predicted_label', and 'predictions'. 'predictions' h...
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def encode_time(time): """ Converts a time string in HH:MM format into minutes """ time_list = time.split(":") if len(time_list) >= 2: return (int(time_list[0]) * 60) + int(time_list[1]) return 0
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def parse_lexicon(lex_file): """ Parse the lexicon file and return it in dictionary form. Args: lex_file (str): filename of lexicon file with structure '<word> <phone1> <phone2>...' eg. peppers p eh p er z Returns: lex (dict): dictionary mapping words to lis...
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def MultiplyTwoNumbers(a,b): """ multiplying two numbers input: a,b - two numbers output: returns multiplication """ c = a*b return c
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from pathlib import Path import pickle def load_trained_model(fname: str): """ Loads a saved ModelData object from file. Args: fname (str): Complete path to the file. Returns: A ModelData object containing the model, list of titles, list of authors, list of genres, list of summaries,...
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def get_visual(screen, desired_depth=32): """get_visual() returns the visual id of the screen @ some depth Returns an int (xcb_visualid_t) corresponding to the screen's visualid On failure it returns None. For an ARGB visual -> desired_depth=32 For a RGB visual -> desired_depth=24 If you ju...
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def _read_multi_smiles_from_file(filepath): """Read multiple SMILES strings from file""" smiles = [] with open(filepath) as input_file: for line in input_file: _smiles, _id = line.split() smiles.append(_smiles) return smiles
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def collatz(num): """ if n is even, n/2 if n is odd, 3n+1 """ newlist = [num] while num != 1: if num%2 == 0: num //= 2 elif num%2 == 1: num = 3*num + 1 newlist.append(num) return newlist
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async def valid_file_extension(file_extension: str) -> bool: """Return True if valid file-extension.""" if file_extension.lower() in ["ttl", "html", "png", "pdf"]: return True return False
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def euler(initial, tendency, h=1): """Integrate forward in time using Euler's method of numerical integration. initial + h*tendency Arguments --------- initial : float The initial state. tendency : float The rate of change in the initial state. Keyword arguments ------...
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def prevent_cache(response): """ Disable response caching for dashboard """ response.headers["Cache-Control"] = "no-cache, no-store, must-revalidate" return response
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import struct def _read_hkey(buff): """Reads from fobj and returns hkey (128 bites integer).""" a, b = struct.unpack('=QQ', buff) return (a << 64) | b
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def generateCSV(package_exports): """ Create a CSV file based on the exported data It expects to receive a list of objects with the following keys: - package - name - type """ csv_content = "" for package_export in package_exports: csv_content += "%s,%s,%s\n"%( ...
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def _image_name_from_key(agent_key: str) -> str: """Generate docker image name from an agent key. Args: agent_key: agent key in the form agent/organization/name. Returns: image_name: image name in the form : agent_organization_name. """ return agent_key.replace('/', '_').lower()
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def atom_in_core(atom, separated_cores): """ Checks if an atom is in any of the lists of atoms. """ for core in separated_cores: if atom in core: return True return False
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def timestamp(location): """Gets timestamp from the cur.txt associated with location.""" with open(f'{location}_cur.txt','r') as current_file: current_file.readline() return current_file.readline()
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import torch def predict_batch(model, x_batch, dynamics, fast_init): """ Compute the softmax prediction probabilities for a given data batch. Args: model: EnergyBasedModel x_batch: Batch of input tensors dynamics: Dictionary containing the keyword arguments for the rel...
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import logging def main(num: int) -> int: """Activity function performing a specific step in the chain Parameters ---------- num : int number whose value to increase by one Returns ------- int the input, plus one """ logging.info(f"Activity Triggered: {nu...
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import importlib def _import_class(cls: str): """Take a string FQP and return the imported class or identifier clas is of the form "package.module.klass". """ mod, name = cls.rsplit(".", maxsplit=1) module = importlib.import_module(mod) return getattr(module, name)
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def target_string_to_int(target_value): """ Convert a String-based into an Integer-based target value. """ if target_value == "Iris-setosa\n": return 0 elif target_value == "Iris-versicolor\n": return 1 else: return 2
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def f1 (p, r): """ Computes F1 Args: p (float): precision r (float): recall Returns: float: F1 """ try: return 2 * (p*r) / (p+r) except ZeroDivisionError: return 0
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import six def get_unicode_dicts(iterable): """ Iterates iterable and returns a list of dictionaries with keys and values converted to Unicode >>> gen = ({'0': None, 2: 'two', u'3': 0xc0ffee} for i in range(3)) >>> get_unicode_dicts(gen) [{u'2': u'two', u'0': None, u'3': u'12648430'}, {u'2':...
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def flat_clfs(params) -> dict: """Flatten the classifiers for easier access.""" flat = {} for clfs in params["classifiers"].values(): flat.update(clfs) return flat
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def auth_token(token): """ A token stored for a user. Format: token:[token] """ return f"token:{token}"
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def print_columns(objects, cols=3, gap=2): """ Print a list of items in rows and columns """ # if the list is empty, do nothing if not objects: return "" # make sure we have a string for each item in the list str_list = [str(x) for x in objects] # can't have more columns than items ...
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