content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import List
def render(gs: game.VisibleGameState, actions: List[game.Action] = None) -> str:
"""
Pretty fuckin hacky...
"""
screen = [[" "] * WIDTH for _ in range(HEIGHT)]
# Talon:
talon_height_offset = 0
for i, card in enumerate(reversed(game.bitmask_to_cards(gs.talon))):
... | 5708fe2cb9d84f35c2ea38e3ec10acb79ed46a83 | 3,617,100 |
import logging
def evaluate_srnpdj(gt, pred, K=25):
"""
Parameters:
gt: np.array([N, ...])
ground truth array of binary labels (integers)
pred: np.array([, ...])
same shape as ground truth
Returns:
srnpdj_N6: np.array(shape=[N, 6])
for each paire... | 77db14c4a6e0bdecd2207e9955abfd8e33bb0724 | 3,617,101 |
from datetime import datetime
def ajax_delete():
"""
客户删除
:return:
"""
ajax_success_msg = AJAX_SUCCESS_MSG.copy()
ajax_failure_msg = AJAX_FAILURE_MSG.copy()
# 检查删除权限
if not permission_customer_section_del.can():
ext_msg = _('Permission Denied')
ajax_failure_msg['msg'] ... | e33cbab8db34739e970c2fe5651d49487245fc9b | 3,617,102 |
from typing import List
def compute_clustering_metrics(y_true: List, y_pred: List) -> List[float]:
"""
Computes ARI, NMI, goldInstance, sysInstance, goldClusterNum
and sysClusterNum between predicted and gold labels
Args:
y_true: Iterable, ground truth labels
y_pred: Iterable, labels ... | 289eb6d278aedd79bad83ed1140fb1656caad072 | 3,617,103 |
from bs4 import BeautifulSoup
import time
def _open_url(url: str):
"""Opens url, creates BeutifulSoup object and waits.
:param url: url to get
:type url: str
:return: BeautifulSoup object
"""
opener = build_opener()
opener.addheaders = [
('User-Agent', 'Mozilla/5.0 (Windows NT 10.... | 255b6aaabcfc3b1be2c284e3244067b2f03265bf | 3,617,104 |
def square(vx=1.0, vy=0, wz=0.8, t=16):
"""
Generate square trajectory, starting and ending at origin.
"""
time_points = range(t)
speed_points = (
# Get set
(0, 0, 0, 0),
# Walk forward and then turn left
(vx, 0, 0, 0),
(vx, 0, 0, 0),
(0, 0, 0, wz),
... | 7db4f1c13cb3055b45e96b0e85934df0c6aa0389 | 3,617,105 |
def crypto_adapter(adapter):
"""Modify an adapter to disable non-crypto symbols.
``crypto_adapter(adapter)(name, active, section)`` is like
``adapter(name, active, section)``, but unsets all X.509 and TLS symbols.
"""
def continuation(name, active, section):
if not include_in_crypto(name):
... | 6f1345d4266fc7a7f2391897170b08d29c57a729 | 3,617,106 |
from typing import Optional
from typing import List
from pathlib import Path
def get_ann_dir(
encoder_type: Encoder.Types,
code_lang: str,
query_langs: Optional[List[str]]=None,
run_id : Optional[str]=None
) -> Path:
"""
Returns the path to the .ann index files for a specif... | 8fa5b2a23cbc9dd436007299e239f39bb9e27050 | 3,617,107 |
from typing import Type
from typing import cast
def coerce(expr: Node, target_type: Type, source_type: Type, context: TypeInfo,
is_wrapper_class: bool = False, is_java: bool = False) -> Node:
"""Build an expression that coerces expr from source_type to target_type.
Return bare expr if the coercion... | 9687fccd5fddd216f2a96f21030da8e26f8ec3f3 | 3,617,108 |
def check_surrounded(string):
""" Check if the string as a whole is surrounded by brackets
:param string: The string to check.
:return: True if it is surrounded.
"""
length = len(string)
if length <= 1:
return False
counter = 0
for idx in range(length):
char = string[id... | 6855cadee02c32010ea98752a35ee6d929d53925 | 3,617,109 |
def make_message(name):
"""Constructs a welcoming message. Input: string, Output:string."""
message = "Good morning, %s! Nice to see you."%name
return message | ac5c9f845cd6779fa37758ec6b27b69dd325fb7d | 3,617,110 |
def format_time(sec: float) -> str:
"""Return formatted time in seconds."""
m, s = divmod(sec, 60)
h, m = divmod(m, 60)
return "%d h %d m %d s" % (h, m, s) | 5c825c7556c0e01d4344af8c35c0f005be69114c | 3,617,111 |
def file_path_pair(config, section):
"""Return input and output file paths for a config section."""
input_obj = config[section]['input']
if isinstance(input_obj, str):
input_path = get_file_path(config, input_obj)
else:
input_path = []
for path in input_obj:
input_pat... | eea94ae41595e18a11d30002a19aa3c5f7bb6f63 | 3,617,112 |
def get_name_candidates_from_email(parsed_text):
"""
Gets possible combination of names from the email address
:param parsed_text: (unicode string) parsed text from the resume.
:return: a list of possible combination of names.
"""
banned = ['the', 'and']
string_list = []
list_name_data =... | afa14780861d0e024c6f91c0d593ed0440e0bf1e | 3,617,113 |
def spot_price_difference():
"""返回 DOT 火币,币安,okex,抹茶,uniswap,heco交易所现货价格的最大价差
@@@
### description
> finished
### args
None
### return
status code: **200**
```json
[
{
"dex": "huobi",
"price": 100,
... | 2bc563cb9e80cf73a651a80938af34fe3c3f9267 | 3,617,114 |
def view_eco(key):
"""View existing eco."""
eco = ECO.get_by_key(key)
users = User.query.all()
projects = Project.query.all()
variables = {
'eco': eco,
'users': users,
'projects': projects
}
return render_template('eco/view_eco.html', **variables) | 578993b8549bd7f5f4c39e915b13ae4173afc8fb | 3,617,115 |
def fetch_accounts(clientCard):
"""
Function to return the accounts owned by the account holder that is linked to the bank card they
used to login into the website, and associated information.
Args:
clientCard (int): Bank card used for login
Returns:
accounts_modified (list): List w... | e38895073aaf4c3edad0551edc94dee259a6a1d7 | 3,617,116 |
def get_classifier_training_job_from_model(classifier_training_job_model):
"""Gets a classifier training job domain object from a classifier
training job model.
Args:
classifier_training_job_model: ClassifierTrainingJobModel. Classifier
training job instance in datastore.
Returns:
... | 4297df181b9fcb747bad2f5d839aad1787c84fac | 3,617,117 |
import requests
def makeModel(filenum=FILENUM):
"""
:param str file_num:
:return libsbml.Model:
"""
url = makeURL(filenum)
response = requests.get(url).content
document = tesbml.readSBMLFromString(response.decode("utf-8"))
return document.getModel() | 4a0a1c5021c138bc2f0fbddefcdd31e04b0b92ec | 3,617,118 |
import numpy.random
def random_sequences(num_seqs, average_length):
"""
@arg num_seqs: The number of sequences to return.
@arg average_length: The expected length of each sequence. (the lengths are actually distributed according to a Poisson distribution).
@return: A list of random sequences.
"""
... | c778a947faba9fcd651124fcf895f3e8a3a697a2 | 3,617,119 |
def tone3_to_tone(tone3):
"""将 :py:attr:`~pypinyin.Style.TONE3` 风格的拼音转换为
:py:attr:`~pypinyin.Style.TONE` 风格的拼音
:param tone3: :py:attr:`~pypinyin.Style.TONE3` 风格的拼音
:return: :py:attr:`~pypinyin.Style.TONE` 风格的拼音
Usage::
>>> from pypinyin.contrib.tone_convert import tone3_to_tone
>>> to... | 8facc123f5a8f381dc4166e326f919591dafd1e1 | 3,617,120 |
import io
def part1(stdin: io.TextIOWrapper, stderr: io.TextIOWrapper) -> int:
"""
Consider the validity of the nearby tickets you scanned. What is your
ticket scanning error rate?
"""
fields, tickets = parse(stdin)
groups = valid_groups(fields)
invalid_values = [
value
fo... | db8a7ce80df23ab5503b3ca37b181982d761f583 | 3,617,121 |
def image_update(client, image_id, values, purge_props=False):
"""
Set the given properties on an image and update it.
:raises NotFound if image does not exist.
"""
return client.image_update(values=values,
image_id=image_id,
purge_props... | ddd89c57cefa2972833ce87e382572406fbb811f | 3,617,122 |
def get_new_map(trace):
"""
Returns the new MAP model from exoplanet after sampling the posterior.
Parameters
----------
trace : arviz.data.inference_data.InferenceData
Information on the trace of all fitted parameters used in the model sampling, including the posterior values, log_likeliho... | 5fec674e4ba56c0163872357a40ed32d576c20f5 | 3,617,123 |
def encodeMorse(sequence: str) -> str:
"""
Encodes the given string to Morse Code
Morse code is case-insensitive and traditonally Capital Letters are used
Lower cases are converted to Upper cases
Every Character code is seperated by a single space between them
A space in the se... | 7fb6b631d894fe4d73d277d8a4374be581616b32 | 3,617,124 |
def brightness(image):
"""Change brightness of image randomly (maximum 30%)"""
hsv = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)
scale = 1.0 + np.random.uniform(-0.3, 0.3)
hsv[:,:,2] = hsv[:,:,2] * scale
return cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB) | 0f0463039992dc3d0087bbe066776af61eb889d3 | 3,617,125 |
def _parse_vertex_tuple(s):
"""Parse vertex indices in '/' separated form (like 'i/j/k', 'i//k' ...)."""
vt = [0, 0, 0]
for i, c in enumerate(s.split('/')):
if c:
vt[i] = int(c)
return tuple(vt) | e83182401b6443726660caf3688008f6209aed13 | 3,617,126 |
import random
def __create_clicks_for_statements(up_votes, statement_uid, users, is_up_vote):
"""
:param up_votes: Int
:param statement_uid: Statement.uid
:param users: {Users.nickname: User}
:return: [ClickedStatement]
:param is_up_vote: Boolean
"""
tmp_firstname = list(first_names)
... | 14a31bb3b594d92bc08322d6783828c92bce27f8 | 3,617,127 |
def get_pct_on_clutter_map_rhi(filename, polarization):
"""
get_pct_on_clutter_map_rhi grabs and returns clutter map point percentage occurrences and clutter map
masks from daily HSRHI clutter maps (in either H or H and V polarizations).
Parameters
----------
filename: str
full path... | 5cf4ea50b568744dfb39da615c1cdf1458f8d14b | 3,617,128 |
import torch
def tfidf_transform(tfidf_vectorizer, corpus_data, cuda0):
"""
Apply TFIDF transformation to test data.
Args:
vectorizer_train (object): trained tfidf vectorizer
newsgroups_test (ndarray): corpus of all documents from all categories in test set
Returns:... | 6f18b7114579412e1442b1c6220f34b7f643a2ab | 3,617,129 |
import os
def RunAllDir(dir_string, method, no_glob, param):
"""
Run 'method' on the pinballs in all directories which start with the string 'dir_string'.
Uses os.path.walk() to run the method on all pinballs in each directory (or directories).
@param dir_string string used to determine directories ... | 69d05be6288706cebc9c6babeb773555557e89c8 | 3,617,130 |
def or_(*args):
""" Trick operator precedence.
or_(foo < bar, bar < baz)
"""
value = DummyAttr()
for elem in args:
value |= elem
return value | 5e709f65fe2e03af2fe8e55e1638e8a012acc1c9 | 3,617,131 |
def plot_image(data=None, mode='imshow', backend='matplotlib', **kwargs):
""" Overall plotter function, converting kwarg-names to match chosen backend and redirecting
plotting task to one of the methods of backend-classes.
"""
if backend in ('matplotlib', 'plt'):
return MatplotlibPlotter.plot(da... | f2a4dd4a81aafb182aefd33ffd98667e154ad2d8 | 3,617,132 |
import tqdm
def project_to_ids_UNSC(Tokenizer, data, max_seq_length=512):
"""
Function to map data to indices in the albert vocabulary, as well as
adding special bert tokens such as [CLS] and [SEP]
Args:
Tokenizer (bert.tokenization.albert_tokenization.FullTokenizer):
tokenizer class ... | 159210068640e62bd3eb66acec3131dcf8d9b75e | 3,617,133 |
import os
import urllib
def download_pretrained_checkpoint(data_config: DatasetConfiguration, cache_folder: os.PathLike) -> str:
"""Utility function to download a pre-trained checkpoint from the original repository.
Parameters
----------
data_config : DatasetConfiguration
The configuration id... | 802b2330341e0c7de953d21b6ab70fcc4d0683ce | 3,617,134 |
def voigtMath(x, alpha, gamma):
"""
Function to return the Voigt line shape centered at cent with Lorentzian
component HWHM gamma and Gaussian component HWHM alpha.
Creates a Voigt line profile using the scipy.special.wofz, which returns
the value of the Faddeeva function.
WARNING
scipy.sp... | 623de058a893b79d857869f8a19bc0e3194b457a | 3,617,135 |
def get_installation_coordinates_google(dir_in, key_google, fn_out=None):
""" Gets installation coordinates using googlemaps api
:param dir_in: <string> path to directory with downlaoded installation data file
:param key_google: <string> google api key
:param fn_out: <string> name output file. If None, ... | 3f33fe2fb14fb3fba92d540c4b2d405a75e53426 | 3,617,136 |
def diag_dump(
enode, list='', daemon='', level='', file='',
_shell='vtysh',
_shell_args={
'matches': None,
'newline': True,
'timeout': None,
'connection': None
}
):
"""
Display diagnostics dump that supports diag-dump.
This function runs the following vtysh ... | 07a97e8e1dbb2a29b19b49c8b94c7e1fd2d5529f | 3,617,137 |
def randomizeCarVelocities(nCars, vMax):
"""This function takes integers nCars, and vMax. It then returns an array
of of random integers from 0 to vMax. The array is of length nCars.
No integers in the returned array are the same."""
carVelocities = []
for i in range(nCars):
randomVelocity =... | edd1d118d3b95560c4bcb85c266b63e0380c9b87 | 3,617,138 |
import time
import logging
def get_absl_log_prefix(record):
"""Returns the absl log prefix for the log record.
Args:
record: logging.LogRecord, the record to get prefix for.
"""
created_tuple = time.localtime(record.created)
created_microsecond = int(record.created % 1.0 * 1e6)
critical_prefix = ''
... | 623c6b8966424b8168686d05f5d65c1268a1d0e1 | 3,617,139 |
def delete_zcs_container(session, zcs_container_id, return_type=None,
**kwargs):
"""
Deletes a Zadara Container Services (ZCS) container. The container must
first be stopped. This action is irreversible.
:type session: zadarapy.session.Session
:param session: A valid zada... | 0eda96c2a07e5a0280584ba9cd323f6fa58e8190 | 3,617,140 |
def numStationsNotIgnored(observations):
""" Take a list of ObservedPoints and returns the number of stations that are actually to be used and
are not ignored in the solution.
Arguments:
observations: [list] A list of ObservedPoints objects.
Return:
[int] Number of stations that ... | 279f4075bc1fe155e4fa8b39758997c9748f06b8 | 3,617,141 |
import attr
from typing import Any
def _next_and_end(cls: "StateMirror") -> "StateMirror":
"""Add "Next" and "End" parameters to the class.
Also adds the "then()" and "end()" helper methods.
"""
def _validate_next(instance, attribute: attr.Attribute, value: Any):
if value is not None and inst... | 1bc7c87f0c9373c5a25866c05bbafb2e9b4d5518 | 3,617,142 |
def jf_mcma_lb(sample: np.ndarray, ref_size=None, c=None, delta=0.05, mode=None, mc_size=10000) -> float:
"""
A function calculates the lower bound using Monte-Carlo M_alpha method.
For more details, please check the paper:
"A New Confidence Interval for the Mean of a Bounded Random Variable"
... | 02791a7e22802cd50e20aa803b981111193cfd4f | 3,617,143 |
def parse_thumbnail_requirements(thumbnail_sizes):
""" Takes a list of dictionaries with "width", "height", and "method" keys
and creates a map from image media types to the thumbnail size, thumnailing
method, and thumbnail media type to precalculate
Args:
thumbnail_sizes(list): List of dicts w... | 07a1e6b5eac978aa59b7a676d8f5b932367599d5 | 3,617,144 |
def get_connected_regions_light(input_flow, strict=False):
"""
:param input_flow: the binary mask array, with shape [x, y, z], pid_id
:param strict: whether diagonal pixel is considered as adjacent.
:return: a dict, with key 1, 2, 3, ... (int), value is list of location: {1: [(x1, y1, z1), (x2, y2, z2),... | 58f89018e0933ac0aff29df83d1cb31f653ed70c | 3,617,145 |
def policy_decision():
"""Determines whether a request is allowed or not
Args:
The function uses HTTP request directly. These argument must be contained in the request:
thing_id (str): identification of the thing
thing_type (str): type of the thing
action (str): get,delete, or c... | 031446c3f212f7ecc5944ca040bc026f204fc9e3 | 3,617,146 |
def calc_num_nodes(np, ppn=1, threshold=0, name=None):
"""Calculate the number of required nodes with optional utilization check.
:param np:
Number of required processing units (e.g. CPUs, GPUs).
:param ppn:
Number of processing units available per node.
:param threshold:
(optio... | 950b72248b1e4f26f8d8e2ed4c2f6c26b0faa51b | 3,617,147 |
def get_status(req_sheet, row_num):
""" Accessor for JIRA Key
Args:
req_sheet: A variable holding an Excel Workbook sheet in memory.
row_num: A variable holding the row # of the data being accessed.
Returns:
A string value of the Notes
"""
return (req_sheet['G' + str(row_... | 3e1de0013bc0efc5824f5261ff4c0b278f486ea8 | 3,617,148 |
import torch
def validate(model, criterion, valset, iteration, batch_size, n_gpus,
collate_fn, distributed_run, rank):
"""Handles all the validation scoring and printing"""
model.eval()
with torch.no_grad():
val_sampler = DistributedSampler(valset) if distributed_run else None
... | a71192ee93901fb1c2f10c1d7cfcd12dfbd1dfbe | 3,617,149 |
def get_permissions(limit=None, offset=None):
"""Get permissions"""
session = current_app.appbuilder.get_session
total_entries = session.query(func.count(Permission.id)).scalar()
query = session.query(Permission)
actions = query.offset(offset).limit(limit).all()
return action_collection_schema.d... | 6fbb85696aaaafc2209d3e039f5d55c29ac726e3 | 3,617,150 |
from typing import List
import torch
def build_data_loader(
X: List[str],
y: List[List[str]],
batch_size: int,
tokenizer: BPETokenizer,
) -> torch.utils.data.DataLoader:
"""Build data loader.
Args:
X: list of textual data.
y: list of tags (TODO).
batch_... | 0952e9a3bcb3a171fcb97afbc8378998aff7b00b | 3,617,151 |
from typing import Union
from typing import Optional
def extract_wikipedia_id(url: Union[str, ParseResult, None]) -> Optional[str]:
""" extract Wikipedia ID from URL """
url = parse_url(url, ("en.wikipedia.org", "en.m.wikipedia.org"))
return (
unquote_plus(url.path[6:]) or None
if url and ... | 9388db4aefc4eb08338e9ed0c6619ba2e2afa365 | 3,617,152 |
def summation(num) -> int:
"""This function makes numbers summation."""
return sum(range(1, num + 1)) | 78983a3e60be914987fd1dc91d5097e1edb326da | 3,617,153 |
def SaveArrayWithGeo( array, src_filename, dst_filename, format ):
"""
SaveArrayWithGeo(): Saves an Array (array) with Georeferencing from another file (src_flnm), save it in file (dst_flnm) with format (format)
SaveArrayWithGeo( self, array, src_filename, dst_filename, format )
"""
#From warmerdam at p... Thu Ma... | 39191b446006c652860c054a627078d3038592a5 | 3,617,154 |
def get_mapshape_from_searchmap(hashtable):
"""Suppose keys have the form (x, y). We want max(x), max(y)
such that not necessarily the key (max(x), max(y)) exists
Args:
hashtable(dict): key-value pairs
Returns:
int, int: max values for the keys
"""
ks = hashtable.keys()
h = max([y... | cf5cb2051fc9254d70c60a71d2c7f9e378b0a39e | 3,617,155 |
def det(a, b):
"""
Calculate the determinent between two vectors
@param[a] One vector represented as [x,y]
@param[b] One vector represented as [x,y]
"""
return a[0] * b[1] - a[1] * b[0] | 61dfcbf421241ac9885643554bbf0c235f698098 | 3,617,156 |
import glob
def find_rar(path):
""" This function is designed to find the most appropriate file to use when extracting and/or
processing releases. This is designed for use with torrent clients and their various "on complete"
functionality.
This function will always return the largest file found under... | 6d1134a276352390d677f1d7fe63328e21498a2e | 3,617,157 |
def test_fft():
"""
Kymatio, (C) 2018-present. The Kymatio developers.
https://github.com/kymatio/kymatio/blob/master/kymatio/tests/scattering1d/
test_tensorflow_backend_1d.py
"""
if not got_tf:
return None if run_without_pytest else pytest.skip()
def coefficent(n):
return np... | 99d64eb78fd4642fe7b44e1749eb665db04436dd | 3,617,158 |
import re
def GetOSVersion():
"""Retrieve the current OS version from machine.
Returns:
os_version: string, like '10.9.5' or '10.10'.
Raises:
GmacpyutilException: command failed to execute.
GmacpyutilException: os_version does not match expected formatting.
"""
cmd = ['sw_vers', '-productVersio... | 2dad46642c448b32100c692de2d9c16051dbb46d | 3,617,159 |
def env_to_bool(environment_variable: str) -> bool:
""" Translate an environment variable to a boolean value, accounting for minor
variations (case, None vs. False, etc.)
"""
env_value = getenv(environment_variable)
return bool(env_value) and str(env_value).lower() not in ["false", "none"] | 69dc81884e900edd9b7849f927e8ea4387ed98a1 | 3,617,160 |
def make_var_with_poisson(infile, units, maskfile=None, gain=None, rdnoise=0.,
texp=None, origbkgd=0., epsilon=None, hext=0,
statcent=None, statsize=None, outfile=None,
outtype='var', outsnr=None, returnvar=True,
ver... | 1e5270fdef24d5a6d903ec64a487a2f80566d4b4 | 3,617,161 |
def dtype_limits(image, clip_negative=True):
"""Return intensity limits, i.e. (min, max) tuple, of the image's dtype.
Parameters
----------
image : ndarray
Input image.
clip_negative : bool
If True, clip the negative range (i.e. return 0 for min intensity)
even if the image ... | a75969f0f0f7664c05ef187050cb699ab3e81fdb | 3,617,162 |
def get_test_data(fname, as_file_obj=True, mode='rb'):
"""Access a file from MetPy's collection of test data."""
path = POOCH.fetch(fname)
# If we want a file object, open it, trying to guess whether this should be binary mode
# or not
if as_file_obj:
return open(path, mode)
return path | cfefdda29925e24da84f96ce2365fd042080d196 | 3,617,163 |
def runline(y, n, dn):
"""Perform local linear regression on a channel of EEG data.
A re-implementation of the ``runline`` function from the Chronux package
for MATLAB [1]_.
Parameters
----------
y : np.ndarray
A 1-D array of data from a single EEG channel.
n : int
Length o... | f1ab5b972004e838ee34f6e2bb1e43335eddd73e | 3,617,164 |
def ConsecutiveArrays(arr, step=1):
"""
Finds consecutive subarrays satisfying monotonic stepping with step in array.
Returns on each array element the island index (starting from 1).
:param list colors: colors to be included in the colormap
:param string name: name the colormap
:returns: f... | e9bb07ac1b3c3d527136b19bf9db8f2e5b33dd6c | 3,617,165 |
def normalize(X : np.ndarray, feature_axis = 1) -> np.ndarray:
"""
对数据进行归一化 \n
:param feature_axis: 各特征所在的维度 \n
feature_axis = 1 表示每列是不同的特征 \n
"""
if not feature_axis:
X = X.T
_sum = np.sum(X, axis = 0)
for j in range(len(_sum)):
if _sum[j] > 1e-100:
X[:, j] /= _sum[j]
else:
X[:, j] = 1 / X.s... | 47cd365d4a112d1cc2d014374bb7a1b24c8f425c | 3,617,166 |
import io
def table_to_image(
data: pd.DataFrame, titile: str = ""
) -> io.BytesIO:
"""Create image with rate table.
"""
dia = data.plot()
if titile:
ax.set_title(titile)
buffer = io.BytesIO()
img = dia.get_figure()
img.savefig(buffer)
buffer.seek(0)
return buffer | bd308fbd916cf6f3285c52403302c22d986b57c4 | 3,617,167 |
def update_item(id: str,
item_update: ItemUpdate = Body(
..., example=ItemFactory.updated_mock_item)):
"""
update an item
"""
item = item_service.get_item(id)
if not item:
raise HTTPException(status_code=404, detail="Item not found.")
return item_servi... | 60edc4b33eb7d1661e0c9e94e5cab0ba0f7dd91a | 3,617,168 |
from bs4 import BeautifulSoup
import requests
def fetch_events_ldi(base_url='https://ldi.upenn.edu'):
"""
Fetch events from Leonard & Davis Institute, https://ldi.upenn.edu
"""
events = []
page_soup = BeautifulSoup(requests.get(
urljoin(base_url, '/events')).content, 'html.parser')
tr... | 599bf4284ddc039c70daa4ae16b71456bb764e66 | 3,617,169 |
def splitdata_n_max(data, n_max):
""" split N into n_max - sized bins """
data = np.array(data).flatten()
N = len(data)
data_splited = []
for i in range(np.int64(np.ceil(N/n_max))):
start = i*n_max
stop = np.min([(i+1)*n_max, N])
data_splited.append(data[start:stop])
ret... | 9054ad90d632cc256e18ad90d0e02591cfc59ca3 | 3,617,170 |
def comments_search(posts,comments):
"""
:param posts1:Список со словарями, в которых данные публикаций
:param comments:Список со словарями, в которых данные комментариев
:return:Измененные список posts, с комментариями к постам с статусом sponsored
"""
for post in posts:
post['comms'] ... | e5d57854693de563b9a5beb7ca5f5e40b8d68d5a | 3,617,171 |
import torch
def update_weights(batch, batch_dic):
"""
Readjust weights so they sum to 1.
Args:
batch_dic (dict): Dictionary with extra conformer
information about the batch
batch (dict): Batch dictionary
Returns:
new_weights (torch.Tensor): renormalized weights
... | 90131e119e9d2cb849b79346fd2f5f86411f652b | 3,617,172 |
def scaled_dot_product_attention(q, k, v, mask):
"""Calculate the attention weights.
q, k, v must have matching leading dimensions.
k, v must have matching penultimate dimension, i.e.: seq_len_k = seq_len_v.
The mask has different shapes depending on its type(padding or look ahead)
but it must be br... | 2c239f141ac7aad901c2f2e597f228af4f0e4838 | 3,617,173 |
def get_client_lease_status_raw(client_row=None):
"""list the raw status of client leases."""
theRawLeaseStatus = u'UNKNOWN'
try:
# should probably move to config file
filepath = str("/var/lib/misc/dnsmasq.leases")
if (utils.xisfile(filepath) is True):
theRawLeaseStatus = utils.readFile(filepath)
except Ex... | ae139d824103ef2e96b0eb4f19814d8502c30fa1 | 3,617,174 |
def __edfdv__(fp, e, kv, dt):
"""
:param fp:
:param e:
:param kv:
:param dt:
:return:
"""
return np.exp(-1j * kv * dt * e[:, None]) * fp | 0ceff5470440e8fdc2d49b4b8d9824a3f5ccd660 | 3,617,175 |
def design_pts_from_ranges(ranges: np.ndarray,
thetas: np.ndarray):
"""
Args:
ranges (np.ndarray, shape=(C,), dtype=np.float32): range per camera ray
thetas (np.ndarray, shape=(C,), dtype=np.float32): in degrees and in increasing order in [-fov/2, fov/2]
... | 667c4afa9f8546caaabf8414ddc116f36d020a5d | 3,617,176 |
import inspect
def _dict_as_called(function, args, kwargs):
""" return a dict of all the args and kwargs as the keywords they would
be received in a real function call. It does not call function.
"""
names, args_name, kwargs_name, defaults = inspect.getargspec(function)
# assign basic args
... | e4d3ce1f1190b3a72d79235a6aa42ae0605d6737 | 3,617,177 |
import torch
def idcst2(x, expk0, expk1):
"""compute inverse discrete cosine-sine transformation
This is equivalent to idxct(idxst(x)^T)^T
"""
if x.is_cuda:
output = dct_cuda.idcst2(x.view([-1, x.size(-1)]), expk0, expk1)
else:
output = dct_cpp.idcst2(x.view([-1, x.size(-1)]), expk... | c5eacfc656a879d902e062d3fc0ff218616c0155 | 3,617,178 |
from typing import Any
def is_match(pattern: Any, expr: Expr) -> bool:
"""Returns whether or not an expression matches a pattern."""
if isinstance(pattern, Star):
raise ValueError('`Star` pattern must be inside of a sequence.')
for _ in matcher(pattern)(expr, {}, id_success):
return True
return False | 6bf59437256fdf260c38a06dad8ad0cc71ffb13c | 3,617,179 |
def add(a, b):
"""The add function.
Args:
a (Union[:class:`~taichi.lang.expr.Expr`, :class:`~taichi.lang.matrix.Matrix`]): A number or a matrix.
b (Union[:class:`~taichi.lang.expr.Expr`, :class:`~taichi.lang.matrix.Matrix`]): A number or a matrix.
Returns:
sum of `a` and `b`.
"... | 514592483910ee75730b2636e78c6b50a7b18125 | 3,617,180 |
import os
def export_file(isamAppliance, name, filepath, check_mode=False, force=False):
"""
Exporting a User Mapping CDAS file
"""
ret_obj = search(isamAppliance, name=name)
id = ret_obj['data']
if id == {}:
logger.info("User Mapping CDAS file '{0}' does not exists. Skipping expor... | 07e682e8e68f9fb52e86417b182466efd750b010 | 3,617,181 |
def create_authy_user(email, country_code, phone):
"""
Creates a user with the Authy API
:param email: email to be associated with the user.
Used by the API for account recovery
:param country_code: country code for the phone number
:param phone: national format phone number
:returns: ... | fb551badbe633bf839eee687c052806e093abcd6 | 3,617,182 |
import urllib
def check_remote_vcs():
"""
Check if the vcs-url is reachable.
Returns
-------
check_result: bool
Result for the remote vcs to check.
"""
try:
status = urllib.request.urlopen(VCS_SETTINGS['url']).getcode()
check_result = True if status == 200 else Fal... | 7c37a99d8630be680ba3ec28caefc2a3865afae9 | 3,617,183 |
import json
def jsonify(*args, **kwargs):
"""Improved json response factory"""
indent = None
status = kwargs.pop('_status', 200)
mime = kwargs.pop('_mime', 'application/json')
# Check for an argument passed, otherwise dict() the kwargs
data = args[0] if args else dict(kwargs)
# Format... | 49a5eb2d2df4ea8af62df8ae6e721b9c870d4c1b | 3,617,184 |
def pull_data_for_tickers(
tickers,
tiingo_api_key,
start_date=None,
end_date=None,
save_to='',
check_existing=True,
):
"""
Persist all the available data for each of the ticker in ticker_list
"""
n_tickers = len(tickers)
bar = progressbar.ProgressBar(
maxval=n_ticke... | 024e55db0be03375ecf8cc4fb9dcde9c5089c9ac | 3,617,185 |
def edmonds_karp(graph, source, destination):
"""Find maximum flow between two vertices in a weighted graph.
Args:
graph: Undirected or directed graph where every edge has property
'capacity' that indicates how many units may flow through it.
source: Source vertex.
destinati... | 80e1397004a676c6ef1673b66d90d6000724df7a | 3,617,186 |
import ast
def _get_all_names(tree):
"""
Return list of all words.
:param tree: _ast.Module object
:return: list with words
"""
return (node.id for node in ast.walk(tree) if isinstance(node, ast.Name)) | 2b7f39af8bbe0c253d0206bcc86a8a0d05c7686e | 3,617,187 |
import urllib
import os
import mimetypes
import logging
def download_image_link(link, dir_path, prefix = ''):
"""Use urllib to download asset
Args:
link (str):
dir_path (str):
prefix (str):
Returns:
bool
"""
print(f'download_image_link: from "{link}"')
... | 301b21361515a8b70de57bdac30e74cb3acd9a4c | 3,617,188 |
def rot_mat2rot_angle(rot_mat):
""" Return the angle corresponding to the given 2D rotation matrix."""
return np.arctan2(rot_mat[1, 0], rot_mat[0, 0]) | 770eb09b0124d5ca20cc08721e5cbd96a1df7785 | 3,617,189 |
def normalize(array):
"""
Normalize a 1d numpy array between [0,1]
Parameters
----------
array: ndarray
the array to normalize
Returns
-------
ndarray
the normalized array
"""
ptp = np.ptp(array)
if ptp != 0:
return (array - np.min(array)) / np.ptp(... | 96ebf4326938026191e857f1da8495dcae84c465 | 3,617,190 |
def heatmap(matrix, highlight_index=None, labels_left=None, labels_right=None, path=None):
"""
:param matrix: (n x n)
:param highlight_index: (n x 2)
:return:
"""
fig, ax = plt.subplots()
ax = sns.heatmap(matrix, ax=ax, linewidths=.5, cbar=False,
yticklabels=["%.1f" % l ... | ef1dbfff0791bed94b27f6f84542cb9c943a7628 | 3,617,191 |
import sys
import json
import traceback
def read_file_info(file, hdrnum, print_trace=None, content_mode="translated", content_type="simple",
outstream=sys.stdout, errstream=sys.stderr):
"""Read information from file
Parameters
----------
file : `str`
The file from which the... | fd674959c412bdca5d101cd902095cfface5f977 | 3,617,192 |
def get_dataset(config, key, *,
num_tasks):
""""Get dataset."""
if config.env.name == 'gym' or config.env.name == 'random':
return MDPDataset(config, key, num_tasks=num_tasks)
elif config.env.name == 'pw':
return DistributedSampleDataset(config, key, num_tasks=num_tasks)
else:
raise ... | c5597c81e6e4021601dbb87fac1adae21c92892f | 3,617,193 |
def km2_by_state(list_of_park_dicts):
"""
This function takes a list of national park data (e.g. the returned value from
<read_csv_file>), and returns a new dictionary that contains the summed
area (in kilometers squared) of national parks in each state. The output
dictionary should have the format:... | d513f4b46944964cd52ad3c751a4022606182704 | 3,617,194 |
def getRuleCount( lstRules, policy_name ):
"""
This function return the rule count for a given policy
indicated by policy_name
Parameters:
- IN : 1. List containing all the rules
2. Name of the policy
- Out: # of rules in the policy.
"""
count = 0
for x in lstRules:
if x.split(',')[0] == poli... | b4956b0a5af91f1834ee4d463414df2cc02c8796 | 3,617,195 |
def send_format(catfact):
"""
Format's the catfact into a the message to send content string
"""
return """
Thank you for subscribing to CatFacts™
Did you know:
```
{}```
Type "UNSUBSCRIBE" to unsubscribe from future catfacts.
""".format(catfact) | 208605f35db4505bb0037cae23088c89e6b1475f | 3,617,196 |
import sys
def setup_ssh(tn_conn):
"""Function to enable SSH on the device
:param tn_conn: the Telnet connection
:type tn_conn: class:Telnet
:return: 0 if the function succeeded, 1 if it failed, or 2 if there was an error.
:rtype: int
:raises ex: raises a runtime error
"""
rval = lu... | d32d8a2273e28afef0a8bbb665c54b32d58e84b4 | 3,617,197 |
def build_d_layer(flow, name, num_outputs=3):
"""
arXiv:1703.10593v1
d64
"""
with tf.variable_scope(name):
weights_initializer = tf.truncated_normal_initializer(stddev=0.02)
flow = tf.contrib.layers.convolution2d(
inputs=flow,
num_outputs=num_outputs,
... | 472a904141af6dde2ec762ccc0580e351a5920ca | 3,617,198 |
import logging
def drop_infreq_labels(seqs, labels):
"""Filter out infrequent labels."""
label_vocab, label_counts = np.unique(labels, return_counts=True)
is_dropped = {}
for i in xrange(len(label_vocab)):
logging.info('Found label %s, with count %d.', label_vocab[i],
label_counts[i])
... | 4f4567c03f84c92aab7d173c8d446eb857e361da | 3,617,199 |
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