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def datetime_to_ds_nodash(dt): """Convert a Python datetime object to a string with the format YYYYMMDD""" return dt.strftime('%Y%m%d')
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def init_model_with_data(model_obj, data_dict): """instantiate the generated tfp model object with data Parameters ---------- model_obj : tfd.Distribution an un-instantiated model object data_dict : dict data for the model Returns ------- tfd.Distribution ...
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def quintic_easein(pos): """ Easing function for animations: Quintic Ease In """ return pos * pos * pos * pos * pos
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def _format_exception(exception): """Formats the exception into a string.""" exception_type = type(exception).__name__ exception_message = str(exception) if exception_message: return "{}: {}".format(exception_type, exception_message) else: return exception_type
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def query_attr_where(params, table_ref=True): """ Construct where conditions when building neighbors query Create portion of WHERE clauses for weeding out NULL-valued geometries Input: dict of params: {'subquery': ..., 'numerator': 'data1', 'denominator': ...
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def round_nearest(value, multiple_of): """round to `multiple_of` value. based on: https://stackoverflow.com/a/28425782/574981 """ return round(value / multiple_of) * multiple_of
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import json def get_connection_string(credential_path): """Converts credentials JSON to a connection string.""" with open(credential_path) as file_ptr: credential_dict = json.load(file_ptr) connection_string = credential_dict['connection_string'] full_connection_string = connection_string.f...
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def sextodec(xyz, delimiter=None): """Decimal value from numbers in sexagesimal system. The input value can be either a floating point number or a string such as "hh mm ss.ss" or "dd mm ss.ss". Delimiters other than " " can be specified using the keyword ``delimiter``. """ divisors = [1, 60.0, 3600...
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def from_db(x): """ Convert from decibels to original units. Inputs: - x [float]: Input data (dB) Outputs: - y [float]: Output data """ return 10**(0.1*x)
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def index(seq): """ Build an index for a sequence of items. Assumes that the items in the sequence are unique. @param seq the sequence to index @returns a dictionary from item to position in the sequence """ return dict((k,v) for (v,k) in enumerate(seq))
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def calc_variables(df, var_list): """Calculate area-weighted values for variables. Formula: x_pre=A_intersect1 / A_pre * x_bg1 + A_intersect2 / A_pre * x_bg2 Args: df (DataFrame): the dataframe containing census spatially merged with precincts var_list (list): names of variables to calcul...
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import requests def request_ct(url): """Performs a get request that provides a (somewhat) useful error message.""" try: response = requests.get(url) except: raise IOError( "Couldn't retrieve the data, check your search expression or try again later." ) else: ...
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def replace_spaces(text): """ Replace spaces with a dash. """ if not isinstance(text, str): return text return text.replace(" ", "-")
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def log_format_metadata(metadata): """Return a string representation of the metadata formatted for log output. """ return ", ".join("{}={}".format(k, v) for k, v in metadata.items())
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import math def shubert04(ind): """Shubert04 function defined as: $$ f(x) = \sum_{i=1}^n \sum_{j=1}^5 j cos((j+1)x_i) + j $$ with a search domain of $-10 < x_i < 10, 1 \leq i \leq n$. """ return sum(( sum((-j * math.cos((j+1) * ind[i] + j) for j in range(1, 6))) for i in range(len(ind)))),
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def safe_sum(v1, v2): """Sum two integers (string type) accounting for the possibility that one or both is missing; returns an integer.""" if v1: if v2: return int(v1) + int(v2) else: return int(v1) if v2: return int(v2) return 0
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def render_services(args, df): """ replace service number with service name, for common services""" for col in ['srcport', 'dstport']: df[col][df[col] == '22'] = 'ssh' df[col][df[col] == '23'] = 'telnet' df[col][df[col] == '53'] = 'domain' df[col][df[col] == '80'] = 'http' ...
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def tuple_add(tuple_a: tuple, tuple_b: tuple) -> tuple: """Return the result of the addition of two tuples.""" return tuple(map(lambda x, y: x + y, tuple_a, tuple_b)) # Source: https://stackoverflow.com/questions/497885/python-element-wise-tuple-operations-like-sum
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def signal_percent_to_dbm(percent: int) -> int: """ arbitrary conversion factor from Windows WiFi signal % to dBm assumes signal percents map to dBm like: * 100% is -30 dBm * 0% is -100 dBm Parameters ---------- percent: int signal strength as percent 0..100 Returns --...
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def fibonacci(n): """ This is the original function, it will be used to compare execution times. """ if n <= 1: return n return fibonacci(n - 1) + fibonacci(n - 2)
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def find_by_name(name, items): """ Find the object with the specified name attribute. :param name: str: name to look for :param items: [object]: list of objects to look for :return: first item matching name or None if not found """ for item in items: if item.name == name: ...
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def disc(x): """ Returns 'x' rounded to the nearest integer. """ return int(round(x))
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def _read_filepath(source: str) -> str: """ Read file contents """ with open(source, 'r', encoding='utf-8') as infile: contents = infile.read() return contents
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def is_podcast_series_id(item_id): """Validate if ID is in the format of a Google Music series ID.""" return len(item_id) == 27 and item_id.startswith('I')
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import torch def format_abstract_tensile(cycles, predictions): """ Format abstracted tensile test data, where only the yield strength and ultimate tensile strength are available. This method relies on the input cycles being: * 0: in the elastic regime * 1: for the first 1/2 of the remaining t...
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def get_set_vertices_u_0(g_or_n): """Get indexes for the belief vector:" 0: capture 1,...n: vertices""" if isinstance(g_or_n, int): n = g_or_n else: n = len(g_or_n.vs) V = list(range(1, n + 1)) V_ext = [0] + V return V_ext
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def instance_dist(novel, word): """ Takes in a particular word, returns a list of distances between each instance of that word in the novel. >>> from gender_novels import novel >>> summary = "Hester was her convicted of adultery. " >>> summary += "which made her very sad, and then her Arthur was als...
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def define_constants_for_fixed_srht_with_momentum(n, d, m): """ As defined in Jonathan Lacotte, Mert Pilanci, Optimal Randomized First-Order Methods for Least-Squares Problems (https://arxiv.org/abs/2002.09488) Args: n: Number of rows of data matrix d: Number of columns of data matrix ...
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def _get_action_profile(x, indptr): """ Obtain a tuple of mixed actions from a flattened action profile. Parameters ---------- x : array_like(float, ndim=1) Array of flattened mixed action profile of length equal to n_0 + ... + n_N-1, where `out[indptr[i]:indptr[i+1]]` contains play...
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def fromSI(value: str) -> float: """converts from SI unit values to metric Args: value (str): a value in SI units, e.g. 1.3u Returns: float: the value in metric units. """ return float(value.replace("u", "e-6"))
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def _get_jsonld_property(jsonld, property, default=None): """Return property value from expanded JSON-LD data.""" value = jsonld.get(property) if not value: return default if isinstance(value, list) and len(value) == 1 and isinstance(value[0], dict) and "@value" in value[0]: value = valu...
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def dfa_word_acceptance(dfa: dict, word: list) -> bool: """ Checks if a given **word** is accepted by a DFA, returning True/false. The word w is accepted by a DFA if DFA has an accepting run on w. Since A is deterministic, :math:`w ∈ L(A)` if and only if :math:`ρ(s_0 , w) ∈ F` . :param dict df...
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def avseth_gassmann(ksat1, kf1, kf2, kmin, phi): """ Applies the Gassmann equation. Args: ksat1 (float): Ksat1. kf1 (float): Kfluid1. kf2 (float): Kfluid2. kmin (float): Kmineral. phi (float): Porosity. Returns: float: Ksat2. """ s = ksat1 / (km...
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import re def snakify(name: str, *, sep: str = '_', _re_upper=re.compile(r'([A-Z])')) -> str: """Lowercase ``name`` adding ``sep`` before in-word-uppercase letters. >>> snakify('CamelCase') 'camel_case' """ return (name[:1] + _re_upper.sub(rf'{sep}\1', name[1:])).lower()
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def model_values(model): """Get the values out of a Z3 model. """ return { d.name(): model[d] for d in model.decls() }
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def add_suffix(string,suffix): """if suffix, appends suffix to string with underscore. otherwise return it unchanged.""" if suffix is None: return string else: return "{}_{}".format(string, suffix)
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import torch def _collate_fn(batch): """ Custom collate function to manually specify how samples are batched from the DataLoader. See https://pytorch.org/tutorials/beginner/data_loading_tutorial.html#iterating-through-the-dataset for an introduction. In particular, the batch represents a collection of ...
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def findTerm(ont,name): """ Searches an ontology for a specific term name and returns the first hit Args: ont (pronto Ontology): Ontology to search name (str): Search query Returns: pronto Ontology: Term that matched name or None if not found """ for term in ont: if term.name == name: return term re...
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from typing import Union from pathlib import Path def find_file(path="~", file="LabRecorderCLI.exe") -> Union[Path, None]: """find a file recursively args ---- path:str the root folder file:str the file name returns ------- filepath: Union[Path, None] ...
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def make_strategy_id(strategy): """ Return a string that will identify a strategy - just concatenate the numbers of transfers per gameweek. """ strat_id = ",".join([str(nt) for nt in strategy[0].values()]) return strat_id
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import torch def focal_loss(input, target, reduction='mean', beta=0.5, gamma=2., eps=1e-7, **kwargs): """ Focal loss, see arXiv:1708.02002 input: [B, 1, H, W] tensor that contains predictions to compare target: [B, 1, H,...
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import torch def create_xyz_tensor(sl): """ Return an 32 x 32 x 32 x 3 tensor where each len 3 inner tensor is the xyz coordinates of that position """ incr_t = torch.arange(sl, dtype=torch.float64) z = incr_t.expand(sl, sl, sl).unsqueeze(3) y = incr_t.unsqueeze(1).expand(sl, sl, sl).unsqu...
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def _build_rtw88_config(rtw88_config): """Builds the wifi configuration for the rtw88 driver. Args: rtw88_config: Rtw88Config config. Returns: wifi configuration for the rtw88 driver. """ result = {} def power_chain(power): return { 'limit-2g': power.limit_2g, 'limit-5g-1': po...
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import re def get_process_id_and_name(header): """Get process id from header.""" m_process_num = re.match(r'(.*)[(]\s*(\d+)[)]', header) if not m_process_num: return None return int(m_process_num.group(2)), m_process_num.group(1).strip()
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def get_n_control_ts(model): """Get number of timesteps in the model's control variable""" return len(model.wells.event_dates)
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def allow(whitelist): """ Decorates a handler to filter all except a whitelist of commands The decorated handler will only be called if message.command is in the whitelist: @allow(['A', 'B']) def handle_only_a_and_b(client, message): pass Single-item whitelists may be ...
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def stats_file_values(pop_size, gene_number, generation_number, diversity, viability_ratios, viability_ratios_db): """Return a dict usable with csv.DictWriter for stats file""" values = { 'popsize': pop_size, 'genenumber': gene_number, 'generationnumber':generation_number, ...
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def selection_sort_counting(A): """ Instrumented Selection Sort to return #swaps, #compares. """ N = len(A) num_swap = num_compare = 0 for i in range(N - 1): min_index = i for j in range(i + 1, N): num_compare += 1 if A[j] < A[min_index]: m...
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def to_fahrenheit(temp): """ Converts a temperature in celsius to fahrenheit. """ return (temp * 1.8) + 32
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import re def regression_test_almost_match_file_names(old_fname, new_fname): """Checks whether the two file names match (if the files match up to name_i*.ext, it counts as if they match) """ if old_fname == new_fname: return True if '_i' in old_fname: if re.sub('_i[0-9]*', '', old...
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def site_client(client, site): """Returns a client tied to a specific site.""" client.config['default_site'] = site['id'] client.default_site = site['id'] return client
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def time_frog_jumps(other_side_position: int, leaf_positions: list) -> int: """ Returns the earliest time that a frog can jump to the other side of the river. Uses a Set to store unique values from leaf_positions[]. When the size equals to other_side_position, means the leaves have covered all position...
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from typing import Tuple def calc_pad_value(src_value: int, dst_value: int) -> Tuple[int, int]: """ Calculate a padding values for a pair of source and destination numbers. Parameters: ---------- src_value : int Source number. dst_value : int Destination num...
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import re def parse_line(line): """ parse model.js line-by-line using voodoo-regexp: '{title: "Bungeejumper", url: "modellen/Bungeejumper.xml"},\n' => ["Bungeejumper", "modellen/Bungeejumper.xml"] [\"|'] --> match " or ' (.[^'|\"]*) --> group: match anything except " or ' [\"|'] ...
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async def readyz(): """ Readyz endpoint. """ return {"status": "ready"}
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def IoU(boxA, boxB): """ Computes the Intersection over Union (IoU) metric, given two bounding boxes. Input: "boxA": bounding box A "boxB": bounding box B Output: "score": IoU score """ # Compute the intersection points of the two BBs xLeft = max(boxA[0], boxB[0]) yLeft ...
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def is_transition(allele1, allele2): """Is the pair of single bp alleles a transition? Args: allele1: A string of the first allele, must be 1 bp in length. allele2: A string of the second allele, must be 1 bp in length. Returns: True if allele1/allele2 are a transition SNP. Raises: ValueError...
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def example_choices(field, arg=3): """ Returns a number (default: 3) of example choices for a ChoiceFiled (useful for CSV import forms). """ examples = [] if hasattr(field, 'queryset'): choices = [(obj.pk, getattr(obj, field.to_field_name)) for obj in field.queryset[:arg + 1]] else: ...
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def f1(x): """ A simple quadratic function. """ y = x**2 - 3.*x + 5. return y
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def arithmetic_sum_n(a_1, d, n): """Calculate the sum of an arithmetic series. Parameters: a_1 The first element of the series d The difference between elements n The number of elements in the series to sum Return: The sum of n numbers in the arithmetic seri...
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def apply_text_replacements(path, text, text_replacements): """ If path appears in text_replacements, replace each old value with new value in order. """ if path in text_replacements: for old_val, new_val in text_replacements[path]: text = text.replace(old_val, new_val) retur...
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import re def humanish(remote_url): """Get the humanish part of a remote git url equivalent of the following multiexpression sed search and replace: sed -e 's|/$||' -e 's|:*/*\.git$||' -e 's|.*[/:]||g' https://stackoverflow.com/questions/13839879/how-to-determine-the-humanish-part-of-a-git-repos...
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def is_shared_to(video: dict) -> bool: """ Checks if a video was shared to an account. Returns True if it was shared to another account, False otherwise. """ shared = video.get('sharing') if shared and shared.get('to_external_acct'): return True return False
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def input_data_task_id(conf): # type: (dict) -> str """Retrieve input data task id :param dict conf: configuration object :rtype: str :return: task id """ return conf['task_id']
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from typing import Any from typing import List def listify(collection: Any) -> List: """ Takes a given collection and returns a list of the elements, handling strings correctly Parameters ---------- collection: tuple, set, str Any type of collection or string Returns ------- ...
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def normalize_strides( strides ): """Normalize strides of the same format. Args: strides: An integer or pair of integers. Returns: A pair of integers. Raises: ValueError: Input strides is neither an integer nor a pair of integers. """ if isinstance(strides, (list, tuple)) and len(strides)...
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def realign_shifted_streams(tokens, durations, F0s, shifts): """ Durations are shifted by 1, F0 by 2 >>> tokens = ["<s>", "t1", "t2", "t3", "</s>", "x", "x"] >>> durations = ["<0>", "<0>", "d1", "d2", "d3", "<0>", "x"] >>> F0s = ["<0>", "<0>", "<0>", "f1", "f2", "f3", "<0>"] >>> shifts = [1,...
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def ssv(words): """Convert a words list into space separated values""" line = "" for w in words: if len(line) != 0: line += ' ' line += w return line
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def get_region_filename(region, subregion): """Returns the filename needed to download/manage PBF files. Parameters ---------------------- region : str subregion : str Returns ---------------------- filename : str """ base_name = '{}-latest.osm.pbf' if subregion is None: ...
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from typing import Dict from typing import Any def is_aromatic(n: str, d: Dict[str, Any]) -> bool: """Adds indicator of aromaticity of the atom to the node data. :param n: Node name, this is unused and only included for compatibility with the other functions. :type n: str :param d: Node data :typ...
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from typing import OrderedDict def get_data_types(data): """ returns a dictionary with column names and their respective data types :param pandas.DataFrame data: a dataframe :rtype: dict[str,str] """ dtypes = data.dtypes return OrderedDict(zip(dtypes.index, dtypes.astype(str)))
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def _bool_to_str(val): """ Convert Python bool to string 'true' or 'false'. Note we cannot use the standard conversion to str, as Python uses 'True' and 'False', whereas C++ uses 'true' and 'false'. """ return 'true' if val else 'false'
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import time def timestamp2date(timestamp): """ 时间戳转换为日期 Parameters ---------- timestamp: int or str 用户账号 Returns ------- datetime: 转换好的日期:年-月-日 时:分:秒 """ time_array = time.localtime(int(timestamp)) datetime = time.strftime("%Y-%m-%d %H:%M:%S", time_array) ...
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def __data_to_string(write_data): """ Converts data array to string.""" return "".join(["{:08b}".format(data) for data in write_data])
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import codecs def open_enc(fn, utf16): """ Open a file for reading with either the standard built-in open() or the open in the codecs module for reading UTF-16 encoded files. :param fn: Name of the file to open :param utf16: Boolean flag to specify a UTF-16 file """ if utf16: retu...
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from pathlib import Path def account_exists(account_id='jodel_account'): """Checks whether an account has already been created.""" if Path('./' + account_id + '.pkl').is_file(): return True else: return False
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import zlib def crc32File(filename, skip=0): """Computes the CRC-32 of the contents of filename, optionally skipping a certain number of bytes at the beginning of the file. """ with open(filename, 'rb') as stream: discard = stream.read(skip) return zlib.crc32(stream.read()) & 0xfffffff...
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def sanitize_package_name(name): """ Sanitize package name Args: name (str): package name. Returns: str: sanitized package name. """ return name.replace("+", "plus").strip(" ")
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def json_get(item, path, default=None): """ Return the path of the field in a dict. Arguments: item (dict): The object where we want to put a field. path (unicode): The path separated with dots to the field. default: default value if path not found. Return: The value. ...
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from typing import List def common_words(sentence1: List[str], sentence2: List[str]) -> List[str]: """ Input: Two sentences - each is a list of words in case insensitive ways. Output: those common words appearing in both sentences. Capital and lowercase words are treated as the same word. ...
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def lng180(lng): """Returns a longitude in degrees between {-180, 180] given a longitude in degrees.""" newlng = float(lng) if lng <= -180: return lng + 360 if newlng > 180: return lng - 360 return lng
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from datetime import datetime def _calc_elapsed(start, fmt=True): """Returns hours, minutes, seconds; formats to {H}h, {m} min., {s}s if fmt""" elapsed = datetime.now() - start hours, remainder = divmod(elapsed.total_seconds(), 3600) minutes, seconds = divmod(remainder, 60) if fmt: ...
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def divide_by(value, arg): """ Returns the result of the division of value with arg. """ result = 0 try: result = value / arg except: # error in division pass return result
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def dropout_mask(x, sz, dropout): """ Applies a dropout mask whose size is determined by passed argument 'sz'. Args: x (nn.Variable): A torch Variable object sz (tuple(int, int, int)): The expected size of the new tensor dropout (float): The dropout fraction to apply This method use...
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import torch def nms(boxes, scores, overlap=0.7): """Apply non-maximum suppression at test time to avoid detecting too many overlapping bounding boxes for a given object. Args: scores: (N) FloatTensor boxes: (N, 4) FloatTensor overlap: (float) The overlap thresh for suppressing unn...
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import inspect def is_generator(obj): """ Return True if ``obj`` is a generator """ return inspect.isgeneratorfunction(obj) or inspect.isgenerator(obj)
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import codecs def decode_text_part(part): """Extract the payload from a text/plain mime part as a unicode string""" txt = part.get_payload(decode=True) charset = part.get_content_charset('latin1') # Make sure the charset is supported and fallback to 'ascii' if not try: codecs.lookup(charse...
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def calcite(piezometer=None): """ Data base for calcite piezometers. It returns the material parameter, the exponent parameter and a warn with the "average" grain size measure to be use. Parameter --------- piezometer : string or None the piezometric relation References ---------- ...
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import re def _without_nbt_style(s: str) -> str: """ Given a full string with NBT styling, return the string without coloring and recomb symbols. :param s: The given string. :return: The given string without NBT styling. """ return re.sub('§ka|§.', '', s).strip()
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import random def randbytes(length: int) -> bytes: """ Generate a random bytes object. :param length: Length of the random bytes object. :return: Random bytes object. """ return bytes(random.getrandbits(8) for _ in range(length))
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def MoveStr2List(mv: str) -> list: """ param: mv: str [x_src, y_src, x_dst, y_dst] return: mv_list: List-> [int: x_src, y_src, x_dst, y_dst] """ mv_list = [] if mv != " ": mv_list = list(map(int, mv[1:-1].split(","))) return mv_list
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from pathlib import Path def sorted_glob(p: Path, pattern="*"): """ return sorted filenames for matched files. """ names = [x.name for x in p.glob(pattern)] names.sort() return names
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import torch def generate_linear_data(n=1000): """ Generates an example dataset that can be seperated linearly Output: inputs : nx2 dimension FloatTensor targets : nx1 dimension LongTensor with range [0,1] """ torch.manual_seed(123) inputs = torch.rand(n,2) targets = torch.s...
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def nonstandard(cls): """ Testcase decorator that marks the test as being non-standard. These tests are not automatically added to the "standard" group. """ cls._nonstandard = True return cls
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import torch def quadratic_bezier(params: torch.Tensor, t: torch.Tensor) -> torch.Tensor: """Evaluate a batch of quadratic bezier curves at different points. Args: params: torch.Tensor of size [batch, 3, D]. Each batch item is interpreted as four points corresponding to the start point, the fir...
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def OR_AND_product_fuzzy(Z_n, U_d): """ Compute probability of emitting a zero for fuzzy vectors under OR-AND logic. """ out = 1 for l in range(Z_n.shape[0]): out *= 1 - Z_n[l] * U_d[l] return 1 - out
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def get_log_params(prog: str, cfg: dict, def_logfile: str) -> tuple: """Get the log file, level and size for the given program from config The logfile is supposed to be defined by a variable called logfile within the hierarchy of the config dictionary. Thus, the poller log file will be {'poller': {'log...
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def has_view_restrictions(page): """Returns True if the page has view restrictions set up, False otherwise.""" return page.view_restrictions.count() > 0
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def drop_prefix(s, pattern): """ Remove prefix pattern of a string. :param s: string :param pattern: string pattern """ if s.startswith(pattern): return s[len(pattern):] return s
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def getAPNTopicFromX509(x509): """ Given an L{X509} certificate, extract the UID value portion of the subject, which in this context is used for the associated APN topic. @param x509: the certificate @type x509: L{X509} @return: C{str} topic, or empty string if value is not found """ s...
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