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def parabole(x, a, b, c) : """ Fonction parabolique du type y = a*x**2 + b*x + c Paramètres : x (liste ou tableau Numpy) : abscisses. a (float) : b (float) : c (float) : Retourne : Valeur de la fonction (float ou tableau Numpy) """ return a*x**2+b*x+c
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import re def _find_special_id(txt: str, pattern: str, split_str: str) -> list: """Creates an accession ID from starting characters in `pattern` and digits following `split_str` in `txt`. Args: txt (str): Text to search for ID pattern (str): Pattern containing at the start the character p...
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def is_cyclic(x, y): """Are these four-digit numbers cyclic?""" # We can safely truncate to int as x and y come from the polygonal funcs. return str(int(x))[2:] == str(int(y))[:2]
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import math def binomial(n, k): """Computes the binomial coefficient "n over k". """ if k == n: return 1 if k == 1: return n if k > n: return 0 return math.factorial(n) // ( math.factorial(k) * math.factorial(n - k) )
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from typing import Iterator import re def allints(s: str) -> Iterator[int]: """ Returns a list of all of the integers in the string. """ return map(lambda m: int(m.group(0)), re.finditer(r"-?\d+", s))
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import re def _read_ssim_values(content): """Parse FFMpeg output to find SSIM statistics""" result = {} stats_re = re.compile(r"^\[.*\] SSIM (?P<stats>.*)$") for line in content.splitlines(): match = stats_re.match(line) if match: for stat in match.group("stats").split(): ...
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import pickle def save_pickle(obj, filename): """ Serializes a given object Parameters: ----------- obj : object filename : string """ return pickle.dump(obj, open(filename, 'wb'))
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def basic_stats(db): """Collect basic statistics to be fed to output functions""" rps = len(list(db['rp'].keys())) users = len(list(db['users'].keys())) logins = db['logins'] return {"rps": rps, "users": users, "logins": logins}
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def readable_timedelta(days): """Print the number of weeks and days in a number of days.""" #to get the number of weeks we use integer division weeks = days // 7 #to get the number of days that remain we use %, the modulus operator remainder = days % 7 return "{} week(s) and {} day(s).".format(w...
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def get_dimension(geometry): """Gets the dimension of a Fiona-like geometry element.""" coordinates = geometry["coordinates"] type_ = geometry["type"] if type_ in ('Point',): return len(coordinates) elif type_ in ('LineString', 'MultiPoint'): return len(coordinates[0]) elif type_...
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import unicodedata def is_unicode_letter(character): """Return True if character is a Unicode letter""" if ord(character) > 127: return unicodedata.category(character)[0] == 'L' return False
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from typing import Optional from typing import Tuple def wrap_slice( start: Optional[int], stop: Optional[int], step: Optional[int], length: Optional[int], ) -> Tuple[int, int, int]: """Wraps slice indices into a window. Arguments: start (int): :attr:`slice.start` index, o...
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def _extract_open_mpi(version_buffer_str): """ Parses the typical OpenMPI library version message, eg: Open MPI v4.0.1, package: Open MPI Distribution, ident: 4.0.1, repo rev: v4.0.1, Mar 26, 2019 """ return version_buffer_str.split("v", 1)[1].split(",", 1)[0]
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def zfsr32(val, n): """zero fill shift right for 32 bit integers""" return (val >> n) if val >= 0 else ((val + 4294967296) >> n)
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import struct def Bbytes(b): """ Return bytes representation of boolean """ return struct.pack("?", b)
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import string def is_alnum(a_string, okchars=None): """ Checks if the *a_string* contains alnum characters (i.e like string.alnum) but allows you to also include specific characters which you want to allow. Returns false if a character in *a_string* is not alphanumeric and not one of *okchars* """...
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def filter_query_by_project(q, project_safe, context): """Filters a query to the context's project Returns the updated query, Adds filter to limit project to the context's project for non-admin users. For admin users, the query is returned unmodified. :param query: query to apply filters to ...
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def binary_search(lst, item): """ Perform binary search on a sorted list. Return the index of the element if it is in the list, otherwise return -1. """ low = 0 high = len(lst) - 1 while low < high: middle = (high+low)/2 current = lst[middle] if current == item: ...
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def xy(v0x=2.0, v0y=5.0, t=0.6): """Computes horizontal and vertical positions at time t""" g = 9.81 # acceleration of gravity return v0x*t, v0y*t - 0.5*g*t**2
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import struct import socket def maxIpaddr(ipaddr, netmask): """ Takes a quad dot format IP address string and makes it the largest valid value still in the same subnet. Returns: Max quad dot IP string or None if error """ try: val = struct.unpack("!I", socket.inet_aton...
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def as_tuple(range_): """Returns a Python tuple (reference_name, start, end).""" return range_.reference_name, range_.start, range_.end
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import hashlib def computeFileChecksum(algo, filePath): """Compute digest of ``filePath`` using ``algo``. Supported hashing algorithms are SHA256, SHA512, and MD5. It internally reads the file by chunk of 8192 bytes. :raises ValueError: if algo is unknown. :raises IOError: if filePath does not e...
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def get_util_info(service, curr_util, config): """ Fetches the current utilization along with high and low thresholds defined in config file. Args: service: name of the service curr_util: the current utilization data of all services config: config file Returns: Dictionary ...
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def evaluate_apartment(area: float, distance_to_underground: int) -> float: """Estimate price of an apartment.""" price = 200000 * area - 1000 * distance_to_underground return price
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from typing import Counter def predict_license_expression(license_matches): """ Return the best-effort predicted license expression given a list of LicenseMatch objects. """ unknown_expressions = ['unknown', 'warranty-disclaimer'] license_expressions = ( license_match.license_expr...
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def set(bit): """Set the specifeid bit (1-indexed) eg. set(8) == 0x80""" return 1 << (bit - 1)
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def strcmp(s1, s2): """Compare two strings respecting german umlauts.""" chars = "AaÄäBbCcDdEeFfGgHhIiJjKkLlMmNnOoÖöPpQqRrSsßTtUuÜüVvWwXxYyZz" lng = min(len(s1), len(s2)) for i in range(lng): d = chars.find(s1[i]) - chars.find(s2[i]); if d != 0: return d return len(s1) - ...
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import torch from typing import Union from typing import Iterable def clamp_norm( x: torch.Tensor, maxnorm: float, p: Union[str, int] = 'fro', dim: Union[None, int, Iterable[int]] = None, eps: float = 1.0e-08, ) -> torch.Tensor: """Ensure that a tensor's norm does not exceeds some threshold. ...
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import re def extract(regularE : str, init : str, stop : str, string : str): """ regularE: RE to catch string init: First string to replace stop: Last string to replace string: String to apply the RE With a regular expression and init and stop to replace,...
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from typing import List from typing import Optional from typing import Mapping def resolver(parameters: List[str], defaults: Optional[Mapping]=None): """ Creates a function that resolves its positional and keyword arguments against a list of parameters, returning a mapping from parameter to argument ...
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def str_xor(a, b): """ (string, string) -> string xor two strings(a and b) of different lengths >>> str_xor("string", "integer") '\x1a\x1a\x06\x0c\t\x02' >>> str_xor("hello", "world") '\x1f\n\x1e\x00\x0b' >>> str_xor("foo", "bar!") '\x04\x0e\x1d' >>> str_xor("AI", " ") 'ai...
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def _LoadPathmap(pathmap_path): """Load the pathmap of obfuscated resource paths. Returns: A dict mapping from obfuscated paths to original paths or an empty dict if passed a None |pathmap_path|. """ if pathmap_path is None: return {} pathmap = {} with open(pathmap_path, 'r') as f: for ...
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def conta_palavras(frase): """ Recebe uma palavra e retorna um dicionário em que a chave é uma palavra e seu valor a quantidade de vezes que essa palavra está presente na frase """ d = {} for palavra in frase.lower().split(): if palavra in d: d[palavra] += 1 else: ...
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def groupID_callback(x): """ image_name = 1_1-1256_1264_2461_2455-12003110450161(_1).jpg big_image_name = 12003110450161 """ img_path = x['info']['image_path'] big_img_name = img_path.split('.')[-2] big_img_name = big_img_name.split('-')[-1].split('_')[0] return big_img_name
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def get_at_content(sequence): """Return content of AT in sequence, as float between 0 and 1, inclusive. """ sequence = sequence.upper() a_content = sequence.count('A') t_content = sequence.count('T') return round((a_content+t_content)/len(sequence), 2)
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async def amount_to_secs(amount: tuple) -> int: """Resolves one unit to total seconds. Args: amount (``int``, ``str``): Tuple where str is the unit. Returns: ``int``: Total seconds of the unit on success. Example: >>> await amount_to_secs(("1", "m")) ...
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def normalize_loss_dict(losses, weight=1, inplace=True): """Normalize all losses in a dict. Parameters ---------- losses : dict Accumulated dictionary of losses/metrics weight : float, default=1 Sum of weights across all batches inplace : bool, default=True Modify the di...
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def _xpath_eval(xmlschema, xpath, namespaces): """ Wrapper around the xpath calls in this module. Used for caching the results :param xmlschema: xmltree representing the schema :param xpath: str, xpath expression to evaluate :param namespaces: dictionary with the defined namespaces """ ...
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def max_contig_sum(L): """ L, a list of integers, at least one positive Returns the maximum sum of a contiguous subsequence in L """ ############# This is getting the biggest powerset of L # def powerset(s): # x = len(s) # masks = [1 << i for i in range(x)] # for i in range(1 << x)...
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def _varied_parameters(parameters, varied, names): """ Help function for identifying parameters that are varied (or fixed) in experiments. (Not used anymore in this module.) ========== =========================================================== names names of parameters. parameters valu...
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def gc_at_decompress(gcat): """ Decompress GT/AC content - inverse function of gc_at_compress(gc, at). Parameters ---------- gcat : numpy.ndarray Array contains compressed GC/AT content. Returns ------- gc : list of int Binned GC content (100bp bins). at : list of i...
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def combine_duplicate_businesses(businesses): """ Averages ratings of the same business from different sources :param businesses: Full list of businesses :returns: Filtered list with combined sources """ seen_addresses = set() filtered_list = [] for business in businesses: if b...
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def binary_search(array: list[int], item: int) -> int: """ Search an item in an array. binary_search ============= The `binary_search` function takes an sorted array and an item. If the item is in the array, the function returns its position or index. Parameters ---------- array: list[int] ...
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def prepare_source_valid_lengths(F, valid_length, query_data, num_heads: int): """ Returns an int32 valid length tensor of shape (batch * num_heads, query_length) to be used in the softmax operation in DotAttentionCell with the length argument. Due to broadcast_like, dtypes of valid_length and query_dat...
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def get_hand(indices, game_lines): """Return a subset of the game between the supplied indices.""" hand_start_index, hand_end_index = indices return game_lines[hand_start_index : hand_end_index + 1]
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import re def tamper(payload, **kwargs): """ Prepends (inline) comment before parentheses (e.g. ( -> /**/() Tested against: * Microsoft SQL Server * MySQL * Oracle * PostgreSQL Notes: * Useful to bypass web application firewalls that block usage of f...
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import configparser def configparser_config(filename): """Return configparser config object from a filename""" config = configparser.ConfigParser() config.read(filename) return config
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def prediction_output_partial(output): """ Function that given the predicted labels, updates the labels to fit intended data output format. Specifically, corrects predicted answer spans that start with a 2, to instead start with a 1 Input: array of labels Output: array of corrected labels "...
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def create_np_dtype(py_obj, h_group, name, **kwargs): """ dumps an numpy dtype object to h5py file Parameters ---------- py_obj (numpy.dtype): python object to dump; should be a numpy dtype, e.g. numpy.float16 h_group (h5.File.group): group to dump data into. name (str): ...
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def stringify(value): """ Escapes a string to be usable as cell content of a CSV formatted data. """ stringified = '' if value is None else str(value) if ',' in stringified: stringified = stringified.replace('"', '""') stringified = f'"{stringified}"' return stringified
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def sql_comment(comment: str) -> str: """ Transforms a single- or multi-line string into an ANSI SQL comment, prefixed by ``--``. """ """Using -- as a comment marker is ANSI SQL.""" if not comment: return "" return "\n".join(f"-- {x}" for x in comment.splitlines())
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def requires_2fa(response): """Determine whether a response requires us to prompt the user for 2FA.""" if ( response.status_code == 401 and "X-GitHub-OTP" in response.headers and "required" in response.headers["X-GitHub-OTP"] ): return True return False
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import torch def lossFunctionKLD(mu, logvar): """Compute KL divergence loss. Parameters ---------- mu: Tensor Latent space mean of encoder distribution. logvar: Tensor Latent space log variance of encoder distribution. """ kl_error = -0.5 * torch.sum(1 + logvar - mu.pow(2) ...
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from typing import Sequence def vector_sub(u: Sequence[int], v: Sequence[int]) -> Sequence[int]: """Returns the difference (u - v) of equal-length vectors u and v.""" return [u[i] - v[i] for i in range(len(u))]
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def read_fasta(filename): """ Returns the sequences from a fasta file. :param filename: filename of the fasta file :type filename: str :return: list """ sequences = [] with open(filename) as file: for i, line in enumerate(file): if i % 2 == 0: pass ...
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import re def scrape_console_capturing(html): """ Scrapes system capturing percentage from Console page HTML """ # Capturing percentage examples: # <span class="status"><label>Capturing</label>66.7%</span> # <span class="status"><label>Capturing</label>100%</span> capturing_regex = r'Capturing\D+(...
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def lcm(a: int, b: int) -> int: """Return a LCM (Lowest Common Multiple) of given two integers >>> lcm(3, 10) 30 >>> lcm(42, 63) 126 >>> lcm(40, 80) 80 >>> lcm(-20, 30) 60 """ g = min(abs(a), abs(b)) while g >= 1: if a % g == 0 and b % g == 0: break ...
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def set_environ(env_holder: dict, overwrite: bool): """Return lambda to set environ. Use setdefault unless overwrite is specified. """ if overwrite: return lambda k, v: env_holder.update({k: str(v)}) return lambda k, v: env_holder.setdefault(k, str(v))
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import re def countRotated(text): """Counts the number of ocurrences of '\w\n' in text. Args: text (string): text that is going to be processed. Returns: int: number of ocurrences """ return len(re.findall(r'\w\n', text))
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import json def LoadNotebook(filename): """Read a IPython notebook (.ipynb). Reads the file and parses it as JSON. Args: filename: The path to the .ipynb file. Returns: A parsed JSON object (dictionary). """ with open(filename) as f: return json.load(f)
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def are_features_consistent(train_df, test_df, dependent_variables=None): """Verifies that features in training and test sets are consistent Training set and test set should have the same features/columns, except for the dependent variables train_dr: pd.DataFrame training dataset test_df: pd.Dat...
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from operator import truediv def distances_from_average(test_list): """Return a list of distances to the average in absolute terms.""" avg = truediv(sum(test_list), len(test_list)) return [round(float((v - avg) * - 1), 2) for v in test_list]
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import re def get_confidence(s) -> int: """ Using the input string (for x_wconf), parse out the confidence value and return the confidence (100 - confidence) """ conf_rgx = r'''(?<=x_wconf )([0-9]+)''' match = re.search(conf_rgx, s.get('title')) return 100 - int(match.group(0)) if match el...
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def format_test_id(test_id) -> str: """Format numeric to 0-padded string""" return f"{test_id:0>5}"
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def format_datestamp(datestamp): """Format datestamp to an OAI-PMH compliant format. Parameters ---------- datestamp: datetime.datetime A datestamp. Return ------ str: Formatted datestamp. """ return datestamp.strftime('%Y-%m-%dT%H:%M:%SZ')
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import torch def sgn(x): """PyTorch sign function""" return torch.sign(x)
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def diff_renorm(image): """Maps image back into [0,1]. Useful for visualising differences""" scale = 0.5/image.abs().max() image = image*scale image += 0.5 return image
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def _is_ethernet(port_data): """Return whether ifIndex port_data belongs to an Ethernet port. Args: port_data: Data dict related to the port Returns: valid: True if valid ethernet port """ # Initialize key variables valid = False # Process ifType if 'ifType' in port_d...
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async def resolve_delete_user(_root, info, id): """Resolver function for deleting a user object""" user = await info.context["registry"].get(id) await info.context["registry"].delete(user.id) return True
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def count_null(column=None, index=None): """ Get total number of null values in a DplyFrame, one or more rows of DplyFrame, or one or more columns of DplyFrame :param column: one column name or one list of column names of a DplyFrame :param index: one row name or one list of row names of a DplyF...
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def find_span_binsearch(degree, knot_vector, num_ctrlpts, knot, **kwargs): """ Finds the span of the knot over the input knot vector using binary search. Implementation of Algorithm A2.1 from The NURBS Book by Piegl & Tiller. The NURBS Book states that the knot span index always starts from zero, i.e. for...
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def slide_elements(conn, item_id, group_list=None): """Retrieve a list of elements from the HTK annotation response. Each element in this list corresponds to a polygon. Optionally, ask for elements that belong to a specific group or list of groups. """ # Pull down the annotation objects annotat...
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def fitness_func(individual): """Evaluate the fitness of an individual using hamming distance to [1,1, ... , 1]. returns value within [0,1] """ # ideal vector target = [1] * len(individual) # hamming distance to ideal vector distance = sum([abs(x - y) for (x,y) in zip(individual, target)])...
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def matrix(rows,columns,val): """ Bulds a matrix of size rows x columns, with val values in cells NOTE: Does not checks negative values Parameters ---------- rows(int) : The number of rows of the matrix columns(int) : The number of columns of the matrix val(int) : The value in every cel...
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import requests import time def elements_json_overpass(overpass_query): """ This function gets the response of the Overpass API according to a query. It returns a json. It must be used when the overpy can not get specific elements from API response. Example: bound limits of a way from Open Str...
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import torch def complex_mult(data1, data2, dim=-1): """ Element-wise complex matrix multiplication X^T Y :param data1 -> torch.Tensor: :param data2 -> torch.Tensor: :param dim -> int: dimension that represents the complex values """ assert data1.size(dim) == 2 assert data2.size(dim)...
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def hide_axis(ax, axis='x', axislabel=True, ticklabels=True, ticks=False, hide_everything=False): """ Hide axis features on an axes instance, including axis label, tick labels, tick marks themselves and everything. Careful: hiding the ticks will also hide grid lines if a grid is on! Para...
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def convert_time(timestamp): """ Convert time stamp to total hours, minutes and seconds """ hrs = int(timestamp // 3600) if hrs < 10: hrs = "{0:02d}".format(hrs) mins = "{0:02d}".format((int(timestamp % 3600) // 60)) secs = "{0:02d}".format((int(timestamp % 3600) % 60)) return hrs, mins,...
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def redirect(url: str, perm: bool = True) -> bytes: """Send a 3x (redirect) response. :param url: The URL to redirect to. :param perm: Whether this is a permanent redirect. :return: Bytes to be sent to the client. """ code = 31 if perm else 30 return f'{code} {url}\r\n'.encode()
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import re def _slugify_resource_name(name): """Slugify resource name """ return re.sub(r'[^a-zA-Z0-9_]', '_', name)
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import torch def distance_to_reference_trajectory(pred_centroid: torch.Tensor, ref_traj: torch.Tensor) -> torch.Tensor: """ Computes the distance from the predicted centroid to the closest waypoint in the reference trajectory. :param pred_centroid: predicted centroid tensor, size: [batch_size, 2] :type p...
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def _divide_bundles(bundles): """Take each subsegment inside a bundle and put it in its own bundle, copying the bundle metadata.""" divided = [] for bund in bundles: for t in bund['times']: new_bund = bund.copy() new_bund['times'] = [t] divided.append(new_bun...
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def calculate_buy_and_hold_perc(df): """Uses the first closing price and closing price to determine the return percentage if the strategy was simply buy and hold. """ first_close = df.iloc[0].close last_close = df.iloc[-1].close buy_and_hold_perc = (1 - (first_close / last_close)) * 100 ret...
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from typing import Any from typing import Type def _is_measurement_device(instrument_handle: Any, class_type: Type) -> bool: """ Returns True if the instrument handle is of the given type, else False. This function checks whether the given handle is of the correct instrument type. All error's are...
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def equals_auto_tol(x: float, y: float, precision: float = 1e-6) -> bool: """ Returns true if two numbers are equals using a default tolerance of 1e-6 about the smaller one. """ return abs(x - y) < min(x, y) * precision;
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def add_lists(*lists): """Add two lists together without numpy For example, given lists: [1, 2] [3, 4] The result is: [4, 6] Lists are sliced to prevent mutation. """ lists = (l[:] for l in lists) return list(map(sum, zip(*lists)))
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def author(entry): """ Convert author field to list """ if 'author' in entry: entry['author'] = [name for name in entry['author'].replace('\n', ' ').split(' and ') if name.strip()] return entry
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import math def poisson(lam, n, highest_k): """Generates probability of n or more cognates assuming Poisson distribution. Args: lam: The mean of the Poisson n: true cognates highest_k: bottom of range to generate Returns: area under the Poisson distribution for k >= n, or 0 if underflow. """ tr...
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def normalize_whitespace(text): """ Remove redundant whitespace from a string. """ text = text.replace('"', '').replace("'", '') return ' '.join(text.split())
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def dump_param(val): """dump a query param value""" return str(val)
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def bypass_csrf_protection(f): """ Decorator that allows a route to bypass the need for a CSRF nonce on POST requests. This should be considered beta and may change in future versions. :param f: A function that needs to bypass CSRF protection :return: Returns a function with the _bypass_csrf attri...
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def find_sort_symbol(list_names): """ :param list_names: список имен :return: первый символ имени, реже всего встречающийся в списке """ # инициализация пустого словаря dict_First_sym_of_names dict_First_sym_of_names = {} #print(type(dict_First_sym_of_names),dict_First_sym_of_names) # ог...
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def misclassification_percentage(y_true, y_pred): """ Returns misclassification percentage ( misclassified_examples / total_examples * 100.0) """ misclassified_examples = list(y_true == y_pred).count(False) * 1. total_examples = y_true.shape[0] return (misclassified_examples / total_examples) * 100.0
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def genericGetContent(path): """ Retrieve the data from a given file path. """ # We are not currently willing to use a with-statement here, for backwards # compatibility. fp = path.open() try: return fp.read() finally: fp.close()
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import configparser def get_details(field, detail): """ Config parser Reads config.ini file, returns data from an appropriate field and detail """ config = configparser.ConfigParser() config.read("config.ini") return config[field][detail]
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def unique_chains(buss_obj, location): """Counts the unique number of chains in the given location""" # storing for unique ids seen_id = set() # dict for chain and number of stores of that chain chains = {} for buss in buss_obj: if location == buss.location: # eleminating the...
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def parse_join_type(join_type: str) -> str: """Parse and normalize join type string. The normalization will lower the string, remove all space and ``_``, and then map to the limited options. Here are the options after normalization: ``inner``, ``cross``, ``left_semi``, ``left_anti``, ``left_outer``...
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from datetime import datetime def pretty_time(x: float) -> datetime: """Return a datetime object from unix timestamp.""" return datetime.fromtimestamp(x)
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def get_driver_readiness(config: dict) -> str: """Get the code_readiness config setting.""" return config.get("code_readiness", "Release")
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from typing import Optional def safe_language_tag(name: Optional[str]) -> str: """Convert language names to tags that are safe to use for identifiers and file names. Args: name: Name to convert to a safe name. Can be `None`. Returns: A safe string to use for identifiers and file names. ...
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