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def _escape(input_string: str) -> str: """ Adopted from https://github.com/titan550/bcpy/blob/master/bcpy/format_file_builder.py#L25 """ return ( input_string.replace('"', '\\"') .replace("'", "\\'") .replace("\r", "\\r") .replace("\n", "\\n") )
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def make_word_class_dict(word_info): """ 根据数据库查询结果,构造词-类字典 :param word_info: 数据库中记录 :return: 根据查询结果建立的词-类字典 """ word_class_dict = {} for entry in word_info: word = entry[1] word_class = entry[5] # 第五列为词语的类别字段 word_class_dict[word] = word_class return word_class_...
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import re def baselineNumber (Title): """Extract the processing baseline number from the given product title.""" return re.sub(r".+_N(\d{4})_.+", r"\1", Title)
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import html def html_unescape(text: str) -> str: """ convert HTML content to readable 1. unescape html 2. remove some empty code Args: text: Returns: """ text = html.unescape(text).strip() text = text.replace("\xa0", "") return text
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def _charlson(): """ Wrapper function for charlson comorbidity dictionary """ return { 'Myocardial infarction':{ 10:['I21.x', 'I22.x', 'I25.2'], 9:[ '410.x', '412.x'], 'Original':1, 'Quan11':0, }, 'Congestive heart failure':{ ...
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def _is_expecting_event(event_recv_list): """ check for more event is expected in event list Args: event_recv_list: list of events Returns: result: True if more events are expected. False if not. """ for state in event_recv_list: if state is False: return True ...
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def get_orders_dict(orders): """Form a dictionary of current order buys and sells """ list_orders = list(orders) orders_dict = {} orders_dict["sells"] = [] orders_dict["buys"] = [] for order in list_orders: if order["side"] == "sell": temp_price = round(float(order["price...
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def data_gen(list_length): """ >>> data_gen(3) {'numbers_list': [0, 1, 2]} >>> data_gen(7) {'numbers_list': [0, 1, 2, 3, 4, 5, 6]} """ numbers_list = [number for number in range(list_length)] return {"numbers_list" : numbers_list}
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import re def get_offer_total_floors(html_parser, default_value=''): """ This method returns the maximal number of floors in the building. :param html_parser: a BeautifulSoup object :rtype: string :return: The maximal floor number """ # searching dom for floor data floor_raw_data = ht...
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import functools def request(req=None, method=None, requires_response=True): """Call function req and then emit its results to the LSP server.""" if req is None: return functools.partial(request, method=method, requires_response=requires_response) @functools.wraps...
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from typing import Counter def word_lookup(words: list, rand_string: str): """ This function takes the list of words that can be used for the game and the random string of consonants and vowels as arguments. The function then iterates through every word in the list. A list is created from the rand...
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def rreplace(s, old, new, occurrence): """This function performs a search-and-replace on a string for a given number of occurrences, but works from the back to the front. :param s: string to manipulate :param old: substring to search for :param new: substring to replace with :param occurrence: ...
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import requests def get_all_episodes(cfg, series_id): """ Request all episodes within a series. :param series_id: Unique identifier for series :param cfg: Opencast configuration :return: List of pair of eventIds and titles for episodes """ url = cfg['uri'] + "/api/events" params = {"f...
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def default_sid_function(id, rsid): """ The default function for turning a Bgen (SNP) id and rsid into a :attr:`pysnptools.distreader.DistReader.sid`. If the Bgen rsid is '' or '0', the sid will be the (SNP) id. Otherwise, the sid will be 'ID,RSID' >>> default_sid_function('SNP1','rs102343') ...
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def filter_BF_matches(matches: list, threshold=45) -> list: """ filter matches list and keep the best matches according to threshold :param matches: a list of matches :param threshold: threshold filtering :return: matches_tmp: list of the best matches """ matches_tmp = [] sorted_matches ...
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def get_school_total_funding(school_id, aug_school_info): """ Gets (total) funding associated with a school. Args: district_id (str): NCES ID of target school (e.g. '010000500889'). aug_school_info (pandas.DataFrame): Target augmented school information (as formatted by `auxil...
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def _convert_key_and_value(key, value): """Helper function to convert the provided key and value pair (from a dictionary) to a string. Args: key (str): The key in the dictionary. value: The value for this key. Returns: str: The provided key value pair as a string. """ upda...
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def max_value_bits(b): """ Get maximum (unsigned) value of a given integer bit size variable. Parameters ---------- b : int Number of bits (binary values) that are used to describe a putative variable. Returns ------- max_value : int Maximum value that putative variable...
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def aligned_output(cols, indent, tab_size=4): """ Pretty printing function to output tabular data containing multiple columns of text, left-aligned. The first column is aligned at an indentation of "indent". Each successive column is aligned on a suitable multiple of the "tab_size" with spaces ...
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def max_path_sum_in_triangle(triangle): """ Finds the maximum sum path in a triangle(tree) and returns it :param triangle: :return: maximum sum path in the given tree :rtype: int """ length = len(triangle) for _ in range(length - 1): a = triangle[-1] b = triangle[-2] ...
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import re def remove_blank(text): """ Args: text (str): input text, contains blank between zh and en, zh and zh, en and en Returns: str: text without blank between zh and en, zh and zh, but keep en and en Examples: >>> text = "比如 Convolutional Neural Network,CNN 对应中 文是卷 积神 经网络...
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def last_of_list(the_list): """Return the last item of the provided list.""" if len(the_list) == 0: return None return the_list[len(the_list) - 1]
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import torch def get_mean_std(loader): """Calculate mean and standard deviation of the dataset Args: loader (instance): torch instance for data loader Returns: tensor: mean and std of data """ channel_sum, channel_squared_sum, num_batches = 0,0,0 for img,_ in loader: ...
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from typing import Tuple def get_sweep_time_ascii( data: str, sweep_b: Tuple[int, int], time_b: Tuple[int, int] ) -> Tuple[int, int]: """Get sweep and time from a given ASCII string. :param data: ASCII string :param sweep_b: Boundaries of sweep :param time_b: Boundaries of time :return: swee...
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def getFrameLength(socketFile, boundary, skipLines): """Get frame length from stream""" line = socketFile.readline() # Find boundary while len(line) > 0 and line.count(boundary) == 0: line = socketFile.readline() length = 0 # Read in chunk headers while len(line) > 0 and line.strip()...
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def bubbles_from_fixed_threshold(data, threshold=0, upper_lim=True): """ @ Giri at al. (2018a) It is a method to identify regions of interest in noisy images. The method uses a fixed threshold. Parameters ---------- data : ndarray The brightness temperature or ionization fraction cube. threshold : floa...
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def coords_deplacees(c, direction): """ Permet d'avoir les nouveaux coordonnées du gardien :param c: liste avec les coordonnées du gardien :param direction: direction du placement du gardien :return: liste avec les nouveaux coordonnées du gardien """ if direction == 'haut': c[0] -= ...
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import re def lower_case_all_tags(s): """ Change all the tags to lower-case """ return re.sub(r'(<.*?>)', lambda pat: pat.group(1).lower(), s, flags=re.IGNORECASE)
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import binascii def unpack(packet): """ unpack a packet into its hex """ return binascii.unhexlify(packet)
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import argparse import pathlib def get_parser(): """Returns an argument parser.""" parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( '--out', required=True, type=pathlib.Path, help='file to output diff result') parser.add_argument( '--cpp', required=Tru...
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def check(file1, file2): """Compare file1 and file2. Ignore leading and trailing whitespaces of the file""" with open(file1) as f1: test_output = f1.read() with open(file2) as f2: ref_output = f2.read() #p = subprocess.run(['diff', file1,file2], stdout=subprocess.PIPE) #print(p....
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def trim_lcs(lcs : dict, cut_requirement : int = 0) -> dict : """ Remove epochs from a lightcurve that occur before object discovery, which is defined as the first mjd with SNR >= 3.0. Args: lcs (dict): dictionary from a lightcurve file cut_requirement (int, default=0): cut number to re...
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def format_data_types(s): """ apply the correct data type to each value in the list created from a comma separated sting "s" x1: PDB ID (string) x2: Macro molecule overlaps (int) x3: Symmetry overlaps (int) x4: All overlaps (int) x5: Macro molecule overlaps per 1000 atoms (float) x6: Symmetry overlap...
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def prep_first_file(ds, chan): """ Take the dataset for chan and drop spurious variables and rename the main variables """ drop_vars = ( "nominal_satellite_subpoint_lat", "nominal_satellite_subpoint_lon", "nominal_satellite_height", "geospatial_lat_lon_extent", ...
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import math def choose(n,k): """Standard Choose function. :param n: The total sample size. :type n: int :param k: The number of elements you're choosing. :type k: int :return: n choose k :rtype: int """ return (math.factorial(n)/(math.factorial(k)*math.factorial(n-k)))
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import re def sanitize_target(target: str = "") -> str: """ Format target, allow only numeric character e.g. - "012345678901234" => "012345678901234" - "080-123-4567" => "0801234567" - "1-1111-11111-11-1" => "1111111111111" - "+66-89-123-4567" => "66891234567" :param target: :return: ...
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import numpy import math def analytic(x): """ analytic solution """ return numpy.cos(math.pi*x/2) + 2.0*numpy.sin(math.pi*x/2) - 1.0
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def create_label_dict(signal_labels, backgr_labels, discard_labels): """ Create label dictionary, following the convetion: * signal_labels are mapped to 1,2,3,... * backgr_labels are mapped to 0 * discard_labels are mapped to -1 Args: signal_labels: list, or...
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import os import re def list_image_dir(directory, ext='jpg|jpeg|bmp|png|ppm'): """ 列出目录下的所有图片的路径 :param directory: :param ext: :return: """ return [os.path.join(root, f) for root, _, files in os.walk(directory) for f in files if re.match(r'([\w]+\.(?:' + ext + '))',...
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def search_event_using_event_name(df): """ Search event using event name :df : dataframe :return : dataframe """ event_name = input("Please enter the event name to be searched : ") event_name = df[df["event_type"] == f"{event_name}"] print(event_name["name"]) return df
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import json def fix_mgame_str(mgame): """Create info for handling a data game""" return json.dumps(mgame.to_json())
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def checkread(stream, n): """Read exactly *n* bytes from *stream*. A ParseError is raised if less than *n* bytes are available. """ data = stream.read(n) if len(data) < n: raise ValueError("unexpected end of file") return data
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from typing import Optional import torch def check_nans_(x, warn: Optional[str] = None, value: float = 0): """Mask out all non-finite values + warn if `warn is not None`""" msk = torch.isfinite(x) if warn is not None: if ~(msk.all()): print(f'WARNING: NaNs in {warn}') x.masked_fill...
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def get_element_text(element): """Builds the element text by iterating through child elements. Parameters ---------- element: lxml.Element The element for which to build text. Returns ------- text: str The inner text of the element. """ text = ''.join(element.iterte...
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def _sum_counters(*counters_list): """Combine many maps from group to counter to amount.""" result = {} for counters in counters_list: for group, counter_to_amount in counters.items(): for counter, amount in counter_to_amount.items(): result.setdefault(group, {}) ...
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def solution(A, target): # O(N) """ Similar to src.arrays.two_sum, find all the combinations that can be added up to reach a given target. Given that all values are unique. >>> solution([1, 2, 3, 4, 5], 5) 2 >>> solution([3, 4, 5, 6], 9) 2 """ ...
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def exponential_ease_in_out(p): """Modeled after the piecewise exponential y = (1/2)2^(10(2x - 1)) ; [0,0.5) y = -(1/2)*2^(-10(2x - 1))) + 1 ; [0.5,1] """ if p == 0.0 or p == 1.0: return p if p < 0.5: return 0.5 * pow(2, (20 * p) - 10) else: return -0.5 * pow...
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import re def extract_urls(tweets, exclude_pattern): """Extract urls from twitter data.""" extracted_urls = [] twitter_pattern = r'(http[s]*://)(twitter.com)[\D\d]+' for tweet in tweets: temp = set() if tweet.get("retweeted_status"): for url in tweet["retweeted_status"]['e...
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from bs4 import BeautifulSoup import requests import re def get_new_vacancies(tag='machinelearning'): """returns list of new vacancies which are up to date""" def extract_text(obj): """Extraxt text from html code""" ans = [] for i in obj: for ii in i: ...
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import inspect def issetdescriptor(object): """Return true if the object is a method descriptor with setters. But not if ismethod() or isclass() or isfunction() are true. """ if inspect.isclass(object) or inspect.ismethod(object) or inspect.isfunction(object): # mutual exclusion retur...
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def _trim_data(data, max_rows, max_columns=None): """Prints a warning and returns trimmed data if necessary.""" # If the number of columns per row exceeds the max, we need to trim each row. if max_columns is not None and len(data) and len(data[0]) > max_columns: for i, _ in enumerate(data): data[i] = d...
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def unique_2d_list(list_: list): """ Only keep those lists inside the big list which are unique. Args: list_: list of list where second dimension can contain duplicates Returns: """ return list(map(lambda x: list(x), set(map(lambda x: tuple(x), list_))))
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import sys def ask_confirm(question, default_yes): """Ask the user a yes/no question. This only looks at the first character of the response, and is case-insensitive. Takes: question (str): The question to ask the user. Include a question mark. default_yes (bo...
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def calculate_total_clones(haplotypes): """ # ======================================================================== CALCULATE TOTAL CLONES PURPOSE ------- Calculates the total number of clones accross multiple haplotypes. Note that there may be multiple clones associated with each hap...
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def xor_bytes(a, b): """Returns a byte array with the values from XOR'ing each byte of the input arrays.""" if len(a) != len(b): raise ValueError("Both byte arrays must be the same length.") return bytes([a[i] ^ b[i] for i in range(len(a))])
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def _is_numeric(obj): """Return True if obj is a number, otherwise False. >>> _is_numeric(2.5) True >>> _is_numeric('spam') False """ try: obj + 0 except TypeError: return False else: return True
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def run_migration(connection, queries): """ Apply a migration to the SQL server """ # Execute query with connection.cursor() as cursorMig: cursorMig.execute(queries) connection.commit() return True
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def _get_arg_parser_delete(parser): """ Parses arguments given at the command line :return: Namespace object built from attributes parsed from command line. """ parser.add_argument( "-i", "--index", type=str, required=True, help=f"index to delete", ) return parser
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def identity(x): """ 恒等関数 Args: x(np.array): 入力値 Returns: 入力値と同じ配列 """ return x
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def has_divisor(n): """Dado un entero n >= 0, devuelve None si es primo, o el menor divisor encontrado si no""" factor = 2 # para iterar en los posibles divisores que iremos comprobando max_factor = int(round(n ** 0.5)) salto = 1 while factor <= max_factor: if n % factor == 0: ...
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def get_books_by_year(args, books): """ Get books published between two year arguments :param args: args object containing all arguments :param books: A list of book objects read from csv file :return: A list of book objects published between two year arguments """ if not args.year: ...
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def rivers_by_station_number(stations, N): """Builds and returns a list of the N rivers with the greatest number of stations (as a tuple: river name, number of stations) In the case where there are multiple rivers with the same number of stations as the Nth station, these are also included. """ rivers =...
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import os def get_tldr_root(): """ Get the path of local tldr repository for environment variable TLDR_ROOT. """ # If this script is running from tldr/scripts, the parent's parent is the root f = os.path.normpath(__file__) if f.endswith("tldr/scripts/set-more-info-link.py"): return os...
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def GetGLGetTypeConversion(result_type, value_type, value): """Makes a gl compatible type conversion string for accessing state variables. Useful when accessing state variables through glGetXXX calls. glGet documetation (for example, the manual pages): [...] If glGetIntegerv is called, [...] most floating-p...
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def list_to_csv(row): """ Takes a list and converts it to a comma separated string. """ format_string = ",".join(["{}"] * len(row)) return format_string.format(*row)
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import torch def collate_fn(batch): """ function needed for data loaders """ feature_list, protein_seq_list, label_list = [], [], [] for _features, _protein_seq, _label in batch: #print(type(_features), type(_protein_seq), type(_label)) feature_list.append(_features) protei...
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def get_deformation_field_scales(reg_params): """ Calculates the scaling of the deformation field from real space to voxels :param reg_params: :return: """ x_scale = 1000 / float(reg_params.atlas_x_pix_size) y_scale = 1000 / float(reg_params.atlas_y_pix_size) z_scale = 1000 / float(r...
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def add_link(s): """ if `s` is a url, then adds anchor tags for html representation in ipynb. """ if s.startswith('http'): a = '<a href="{0}" target="_blank">'.format(s) a += s a += '</a>' return a
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def GenerateCompareBuildsLink(build_ids, siblings): """Return the URL to compare siblings for this build. Args: build_ids: list of CIDB id for the builds. siblings: boolean indicating whether sibling builds should be included. Returns: The fully formed URL. """ params = ['buildIds=%s' % ','.join...
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from functools import reduce def compute_fitness(tree, features, data): """ Computes a normalized MAE on the predictions made by one tree. """ predicted = [tree.predict(feat) for feat in features] difference = [abs(predicted[i] - data[i]) for i in range(len(data))] mae = reduce(lambda a,b: a+b...
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import os import time def _cache_load_base(save_fn, load_fn, filepath, preprocess_fn, *args, **kwargs): """ Args: save_fn (callable): save dataset function load_fn (callable): load dataset function filepath (str): filepath to cache dataset preprocess_...
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import requests def get_displayable_tracks_metadata(authorization_header,track_ids): """ get the relevant metadata for the tracks that will be displayed on the page Args: authorization_header (dict): valid authorization header track_ids (list): list of track_ids to get data for Retur...
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def int_to_bool(value): """Turn integer into boolean.""" if value is None or value == 0: return False else: return True
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def apply(func, bound_args): """Function to properly apply a function with the arguments we have""" return func(*bound_args.args, **bound_args.kwargs)
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def deep_merge(base, changes): """ Create a copy of ``base`` dict and recursively merges the ``changes`` dict. Returns merged dict. :type base: dict :param base: The base dictionary for the merge :type changes: dict :param changes: The dictionary to merge into the base one :return: The...
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def arctanh(x): """ [Definition] x的反双曲正切函数 [Category] 反双曲函数 domain of definition: (-1, 1) """ return 'arctanh(%s)' %x
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from typing import Optional def admin_obj_url(obj: Optional[object], route: str = "", base_url: str = "") -> str: """ Returns admin URL to object. If object is standard model with default route name, the function can deduct the route name as in "admin:<app>_<class-lowercase>_change". :param obj: Objec...
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def contains_subsets(iter_of_sets): """ Checks whether a collection of sets contains any sets which are subsets of another set in the collection """ for si in iter_of_sets: for sj in iter_of_sets: if si != sj and set(sj).issubset(si): return True return F...
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def parse_owner(this_sample_id, owner): """ Extract name and contact from owner :param this_sample_id: :param owner: :return: """ name = "" email = "" for child in owner: if "Name" == child.tag and child.text: name = child.text elif "Contact" == child.ta...
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import re def href_html2tex(link): """Converts html links to Latex links""" link = link.replace("\n", "^%") matcher = r'<a href=[\'"]?([^\'" >]+)[\'"]?.*?>(<\w+>)*([^<>"]+).*?</a>' texfmt = r"\\href{\1}{\\textcolor{heading}{\\textbf{\3}}}" output = re.sub(matcher, texfmt, link) return output.r...
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def evaluate(data): """ Cost function evaluation parameters: - average_total_time - average_total_queue_time - average_utility_rate (inverse relationship) """ average_total_time = sum(v[10] - v[0] for v in data.values()) / len(data.values()) average_t...
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import numpy def generate_regular_ngon_vertices(n: int, radius: float) -> numpy.ndarray: """Generate the vertices of a regular N-gon centered at zero.""" angles = (numpy.arange(n, dtype=float) * 2 * numpy.pi / n).reshape(-1, 1) return radius * numpy.hstack([numpy.cos(angles), numpy.sin(angles)])
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def list_formatter(values): """ Return string with comma separated values :param values: Value to check """ return u', '.join(values)
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import random import string def random_numeric_token(length): """Generates a random string of a given length, suitable for typing on a numeric keypad. """ return ''.join(random.choice(string.digits) for i in range(length))
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def tensor_to_string_list(tensor): """Convert a tensor to a list of strings representing its value""" scalar_list = tensor.squeeze().numpy().tolist() return ["%.5f" % scalar for scalar in scalar_list]
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def eval_if_exist_else_none(name, global_symbol_table): """ Args: name([str]): Expression passed into `eval`. local_symbol_table(dict): Specified from `globals()`. DO NOT use `locals()`, because all STATIC_CONVERT_VAR_SHAPE_SUFFIX vars is ...
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def to_brackets(field_name, format_spec): """Return PEP 3101 format string with field name and format specification. """ if format_spec: format_spec = ':' + format_spec return '{' + field_name + format_spec + '}' return '{' + field_name + '}'
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import glob import os def find_osx_sdks(): """ Finds installed osx sdks, returns dict mapping version to file system path """ res = {} sdks = glob.glob("/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX*.sdk") for sdk in sdks: sdk_base = os.path...
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def line_2d(p1=(), p2=()): """ :param p1: Coordinates of first point :param p2: Coordinates of second point :return: Slope, intersection """ try: m = (p2[1] - p1[1]) / (p2[0] - p1[0]) b = p1[1] - m * p1[0] return [m, b] except ZeroDivisionError: if p2[1] == p1...
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import os import gc def software_details(): """ returns software details """ try: lists=[] for value in os.uname(): lists.append(value) sw_data={'sysname':lists[0],'nodename':lists[1],'release':lists[2],'version':lists[3],'machine':lists[4]} return sw_data ...
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def loweRatio(matches, kp1, kp2, LOWE_RATIO=0.7): """Reduce list of keypoints to likeliest matches using Lowe's Ratio test. [Reference] David G. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. IJCV 2004""" # Store all the good matches as per Lowe's ratio test good = [] pts1...
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import random def direction(): """Return a random direction as a tuple in the form: ( x-direction, y-direction)""" x = random.randint(-1, 1) y = random.randint(-1, 1) if (x, y) != (0, 0): return x, y return direction()
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def clear_exceptions(estimates_output, param_dict): """Clears exceptions column of estimates_output df for all models that are going to be run (this is needed because the str defining exceptions get concatenated) """ estimates_output = estimates_output.copy() for code in param_dict.keys(...
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def bud_function(input_branch, output_branch, callable, args=[], kwargs={}): """callable(input_branch, *args, **kwargs) -> output_branch""" def bud(manager): return {output_branch:callable(manager[input_branch], *args, **kwargs)} return bud
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def dtype_is_supported(dtype): """Check if data type is supported by BNNS backend""" return dtype in ("", "float32")
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def concat_fields(one, two, sep): """ (str, str, str) -> str Function concat two multiline strings """ line = "" s_one, s_two = one.split("\n"), two.split("\n") for i in range(len(s_one)): line += (s_one[i]+sep+s_two[i]+"\n") return line
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import torch def decode_arr_to_seq(arr, idx2vocab): """Taken from OGB repo""" eos_idx_list = torch.nonzero(arr == len(idx2vocab) - 1) if len(eos_idx_list) > 0: clippted_arr = arr[: torch.min(eos_idx_list)] # find the smallest __EOS__ else: clippted_arr = arr return list(map(lamb...
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import re def _get_valid_filter_terms(filter_terms, colnames): """Removes any filter terms referencing non-existent columns Parameters ---------- filter_terms A list of terms formatted so as to be used in the `where` argument of :func:`pd.read_hdf`. colnames : A list of co...
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def chunk_size(value): """Calculate nice value for chunk size.""" return round(value / 1000 + 0.5) * 1000
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def dekker( t: float, x1: float, y1: float, x2: float, y2: float, x3: float, y3: float, x4: float, y4: float, ) -> float: """ Estimates the root using Dekker's method. Uses a secant line from (x2, y2) to either (x1, y1) or (x3, y3), depending on which point is closes...
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