content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import pyarrow as pa
def ST_IsValid(geos):
"""
Check if geometry is of valid geometry format.
:type geos: Series(dtype: object)
:param geos: Geometries in WKB form.
:rtype: Series(dtype: bool)
:return: True if geometry is valid.
:example:
>>> import pandas
>>> import arctern... | 466f29367dbdc7c09581f7bedda72fe729bdd73d | 32,000 |
import copy
import json
import logging
def import_email(assessment, campaign_number, template_smtp):
"""Import email from file."""
temp_template = Template(name=f"{assessment.id}-T{str(campaign_number)}")
temp_smtp = copy.deepcopy(template_smtp)
temp_smtp.name = f"{assessment.id}-SP-{campaign_number}"... | 7359ff21d159b0f5d7fce90fe58ae17ef785e271 | 32,001 |
import time
def get_framerate(has_already_started,
start_time,
frame_counter,
frame_rate,
frame_num=5,
decimal_round_num=2):
""" Returns current framerate of video based on
time elapsed in frame_num frames.
Works in... | 61db421be9e8d5a0e810a79875eac2b776be99ca | 32,002 |
def check_for_solve(grid):
""" checks if grid is full / filled"""
for x in range(9):
for y in range(9):
if grid[x][y] == 0:
return False
return True | 5fc4a8e7a2efaa016065fc0736aa5bdb7d4c92f8 | 32,003 |
def Sn(i, length):
"""Convert an int to a binary string."""
s = ''
while i != 0:
digit = i & 0xff
i >>= 8
s += chr(digit)
if len(s) > length:
raise Exception("Integer too big to fit")
while len(s) < length:
s += chr(0)
return s | 607c2b8e82379db091505d7422edc17ea121bc3f | 32,004 |
import os
def _get_config_file_schema():
"""
Return the path to the parameters file json schema.
"""
module_file = _decode_filesystem_path(__file__)
return os.path.join(os.path.dirname(module_file), "pystepsrc_schema.json") | 7a67cf8c5496d21dcff1b9e40c054e5961adab7f | 32,005 |
def parse_args():
"""Parse command line arguments"""
parser = ArgumentParser(
description='Print contents of a parsed config file',
formatter_class=ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
'pipeline', metavar='CONFIGFILE',
nargs='?',
default='settings... | 67462f2078ede7dfb9d9e0956b32f1eb09b2a747 | 32,006 |
import copy
def _normalize_annotation(annotation, tag_index):
"""
Normalize the annotation anchorStart and anchorEnd,
in the sense that we start to count the position
from the beginning of the sentence
and not from the beginning of the disambiguated page.
:param annotation: Annotation object
:param tag_inde... | a7da5810711ada97a2ddcc308be244233fe813be | 32,007 |
def read_lc(csvfile, comment='|'):
"""
Read a light curve csv file from gAperture.
:param csvfile: The name of the csv file to read.
:type csvfile: str
:param comment: The character used to denote a comment row.
:type comment: str
:returns: pandas DataFrame -- The contents of the csv fi... | 74e53cbfe902e9d23567569ec0f4c5ef5ef75baa | 32,008 |
def check_cutoffs(cutoffs):
"""Validates the cutoff
Parameters
----------
cutoffs : np.ndarray or pd.Index
Returns
----------
cutoffs (Sorted array)
Raises
----------
ValueError
If cutoffs is not a instance of np.array or pd.Index
If cutoffs array is empty.
... | db0a3a477b27883aa1d29486083cf3e6c993e021 | 32,009 |
def hook(images, augmenter, parents, default):
"""Determines which augmenters to apply to masks."""
return augmenter.__class__.__name__ in MASK_AUGMENTERS | 0e1e6589bc37d90b0ac8249e11dee54140efd86a | 32,010 |
def _get_videos(course, pagination_conf=None):
"""
Retrieves the list of videos from VAL corresponding to this course.
"""
videos, pagination_context = get_videos_for_course(
str(course.id),
VideoSortField.created,
SortDirection.desc,
pagination_conf
)
videos = li... | 21774a476424b8f68f67c368fb72343fb9cfd552 | 32,011 |
import torch
def sample_stacking_program(num_primitives, device, address_suffix="", fixed_num_blocks=False):
"""Samples blocks to stack from a set [0, ..., num_primitives - 1]
*without* replacement. The number of blocks is stochastic and
can be < num_primitives.
Args
num_primitives (int)
... | f5927edc11b2e20fcfb4b19b6ecddd92ba911841 | 32,012 |
def get_mmr_address(rn, m0m1):
"""Return address of an memory-mapped register and its size in bits.
"""
mmr_map = { 0b00 : 0xf0400,
0b01 : 0xf0500,
0b10 : 0xf0600,
0b11 : 0xf0700 }
address = mmr_map[m0m1] + (rn * 0x4)
size = get_register_size_by_addres... | 53b92051d7ac64f5e288a121dae7e764166c9d2e | 32,013 |
import sys
def with_translations(**columns):
"""Decorator that creates a translations table for the decorated model.
Creates a table mapped to a ``ModelTranslations`` class (given a
decorated model class ``Model``) containing the provided `**columns`,
with references to the :class:`.Language` and the... | 22928f878de1480bcd483b7313642969483c3dd8 | 32,014 |
def thread_map(func, data):
"""
http://code.activestate.com/recipes/577360-a-multithreaded-concurrent-version-of-map/
"""
#todo: this is disabled
return map(func, data)
N = len(data)
result = [None] * N
# wrapper to dispose the result in the right slot
def task_wrapper(i):
result[i] = func(data[i])
threa... | eec6efd698a71c63b0c1a7c0c0c4df1f21e3b62f | 32,015 |
import re
def number_of_a_char(element: Element):
"""
get number of linked char, for example, result of `<a href="#">hello</a>world` = 5
:param element:
:return: length
"""
if element is None:
return 0
text = ''.join(element.xpath('.//a//text()'))
text = re.sub(r'\s*', '', text... | 9d1394552b740844aadacc3fe3b2f802b698c18a | 32,016 |
def preprocessing_fn(batch):
"""
Standardize, then normalize sound clips
"""
processed_batch = []
for clip in batch:
signal = clip.astype(np.float64)
# Signal normalization
signal = signal / np.max(np.abs(signal))
# get pseudorandom chunk of fixed length (from SincN... | 25ce4a077027239126d02b62e93ca0a3bcb15b5e | 32,017 |
def elast_quad9(coord, params):
"""
Quadrilateral element with 9 nodes for classic elasticity
under plane-strain
Parameters
----------
coord : coord
Coordinates of the element.
params : list
List with material parameters in the following order:
[Young modulus, Poisso... | c27bae77ca54a3a370ccdac5b5550f73cb121d9a | 32,018 |
from typing import Union
from pathlib import Path
def peek(audio_file_path: Union[str, Path], output: str = "np"):
"""
Returns a tuple of audio data and its sampling rate
The audio data can be a numpy array or list
"""
data, sr = sf.read(audio_file_path, dtype="float32")
data = data.transpose(... | 30b47c77ab92cf0a544d84605204261c899f9e9a | 32,019 |
import click
def parse_rangelist(rli):
"""Parse a range list into a list of integers"""
try:
mylist = []
for nidrange in rli.split(","):
startstr, sep, endstr = nidrange.partition("-")
start = int(startstr, 0)
if sep:
end = int(endstr, 0)
... | 321496a1170b81d02b8378d687d8ce6d6295bff6 | 32,020 |
import os
def intersect_by_tf(emotion_dict):
""" Takes multiple emotion word lists and intersects them by their term frequency, leading to the emotional
difference between sets of any size.
Args:
emotion_dict: dict of summed up emotional scores based on the tf scores of the underlying words
... | f46a02b736a76bd3adcc1efaf7638452241567ce | 32,021 |
def transcript_segments(location_descriptors, gene_descriptors):
"""Provide possible transcript_segment input."""
return [
{
"transcript": "refseq:NM_152263.3",
"exon_start": 1,
"exon_start_offset": -9,
"exon_end": 8,
"exon_end_offset": 7,
... | 3ca9041ff278dcd19432b6d314b9c01de6be1983 | 32,022 |
def perform_data_filtering_q2(data):
"""
Takes the original DataFrame.
Returns the altered DataFrame necessary for Q2.
"""
# redoing the dataframe columns based on different values
df = data
diseased = df['num'] != 0
df['num'] = np.where(diseased, 'diseased', 'healthy')
males = df['s... | 2c8943bda66722b70a5dd25cb5a7c7473e40e67c | 32,023 |
def player_with_name_and_value(source):
"""
source: pn.widgets.DiscretePlayer()
target: consists of source player's name, value and player itself
With pn.widgets.DiscretePlayer, we don't get name and
value updates in textual form. This method is useful
in case we want name and continuous value ... | e7d415d798f9c6aefb203f861b08c9477dde32d7 | 32,024 |
def _cached_diff(expression, var):
"""
Derive expression with respect to a single variable.
:param expression: an expression to derive
:type expression: :class:`~sympy.Expr`
:param var: a variable
:type var: :class:`~sympy.Symbol`
:return: the derived expression
:type: :class:`~sympy.Ex... | 4a4206d327bee6f0c8168893e2bffbeaa23b9c14 | 32,025 |
def _get_mult_op_ ( klass1 , klass2 ) :
"""Get the proper multiplication operator
"""
t = klass1 , klass2
ops = _mult_ops_.get( t , None )
if ops : return ops ## RETURN
## try to load the operators
try :
ops = Ostap.Math.MultiplyOp ( klass1 , klass2 )
... | f7a000f697d4739894e1671e9cfeb23099e1ce4f | 32,026 |
def datetime_into_columns(df, column, weekday = False, hour_minutes = False, from_type = 'object'):
"""
The function converts a column with a date from either int64 or object type
into separate columns with day - month - year
user can choose to add weekday - hour - minutes columns
Keyword argument... | e6178b33f113ef1430d0d8df3fe9b6c53d200e1e | 32,027 |
def cis_codif_h1_moms(probe, starttime, endtime, sensitivity='high',
try_download=True):
"""
Load H+ moments from CIS instrument.
See https://caa.estec.esa.int/documents/UG/CAA_EST_UG_CIS_v35.pdf for more
information on the CIS data.
Parameters
----------
probe : stri... | e8f014196c2a634d406aaeb86a3130e6db59049f | 32,028 |
def readlines(file_path):
""" Read lines from fname, if the fname is loaded get the buffer."""
buffer = getbuffer(file_path)
if buffer and int(vim.eval('bufloaded(%d)' % buffer.number)):
return buffer
try:
with open(file_path, 'r') as fo:
# we are not decoding: since we hav... | a4f367a00f90095a17f9eaf29eb150e7a5176045 | 32,029 |
import random
from sys import path
def random_avg_subdir(myinput, dims = "", n = 20):
"""
Get the average of n faces chosen from different subdirectories of myinput.
You can also pass a list of directories into myinput instead of a string
representing the target directory
"""
results = []
if isinstan... | 83313fb7d31b0d07600dfc1424a2f94a37eca29c | 32,030 |
def convert_range_image_to_point_cloud(
frame, range_images, camera_projections, range_image_top_pose, ri_indexes=(0, 1)
):
"""Convert range images to point cloud. modified from
https://github.com/waymo-research/waymo-open-dataset/blob/master/waymo_open_dataset/utils/range_image_utils.py#L612
Args:
... | af6a6af4cfcde6f3b600ffe0add8a3a0b0870067 | 32,031 |
from typing import Dict
from typing import Tuple
def get_counts(circ: MyCircuit, n_shots: int, seed: int) -> Dict[Tuple[int, ...], int]:
"""Helper method for tests to summarise the shot table from the simulator
:param circ: The circuit to simulate
:type circ: MyCircuit
:param n_shots: The number of s... | e681fdc02e4cf7a637eac6f1e2096d9276b39cc6 | 32,032 |
def length(
inputs: tf.Tensor,
axis: int = -1,
keepdims: bool = False,
epsilon: float = 1e-10,
name: str = None
) -> tf.Tensor:
"""
Computes the vector length (2-norm) along specified ´axis´ of given Tensor ´inputs´.
Optionally an epsilon can be added to the squared n... | a548110ec2d8e3512e73805aea690f22c7d50fe3 | 32,033 |
def class_label_matrix(labels, img_sizes, num_classes):
""" Computes the class label matrix of the training data. """
# Class label matrix
Y = list()
# Modeling the object detection problem as a binary classification problem (none, detection)
if num_classes == 2:
print('Modeling as a bin... | 47efe5f8f76cac58d3afeaddb04d766ebdebf377 | 32,034 |
def default_lambda_consumer(env_id):
"""Create a default lambda consumer for the snapshot restore test."""
return st.consumer.LambdaConsumer(
metadata_provider=DictMetadataProvider(
CONFIG_DICT["measurements"],
SnapRestoreBaselinesProvider(env_id)
),
func=consume_... | ec7ec2ae6df4aaa7caf034537a5259b897755700 | 32,035 |
def thresholdPolyData(poly, attr, threshold, mode):
"""
Get the polydata after thresholding based on the input attribute
Args:
poly: vtk PolyData to apply threshold
atrr: attribute of the cell array
threshold: (min, max)
Returns:
output: resulted vtk PolyData
"""
... | e4717b971c238d9c3a63a902db7eb91e2c630340 | 32,036 |
def TCh_GetNum(*args):
"""
TCh_GetNum(char const & Ch) -> int
Parameters:
Ch: char const &
"""
return _snap.TCh_GetNum(*args) | 6caf9bcf71868604a6aedeceaba299a36a6bc62a | 32,037 |
def writeFGSSPostageStampRequestById(outfile, requestName, results, xsize, ysize, psRequestType = 'byid', optionMask = 2049, imageType = 'warp', psJobType = 'stamp', skycell = 'null', email = 'qub2@qub.ac.uk', camera = 'gpc1', coordMask = 2):
"""writeFGSSPostageStampRequestById.
Args:
outfile:
requ... | 636284d46cbaced8d0609afe988148cbc3111d32 | 32,038 |
def reduce_sequence(sequence, desired_length):
"""Reduces a sequence to the desired length by removing some of its elements uniformly."""
if len(sequence) < desired_length:
raise RuntimeError('Cannot reduce sequence to longer length.')
indexes = N.arange(desired_length) * len(sequence) / desired_len... | 25f104abc666e26821436a42f5cb71b99b41a86c | 32,039 |
def encode_label(text):
"""Encode text escapes for the static control and button labels
The ampersand (&) needs to be encoded as && for wx.StaticText
and wx.Button in order to keep it from signifying an accelerator.
"""
return text.replace("&", "&&") | b4402604f87f19dab9dbda4273798374ee1a38d8 | 32,040 |
def dash_table_from_data_frame(df: pd.DataFrame, *, id, **kwargs):
"""Returns a dash_table.DataTable that will render `df` in a simple HTML table."""
df_all_columns = df.reset_index()
return dash_table.DataTable(
id=id,
columns=[{"name": i, "id": i} for i in df_all_columns.columns],
... | 813bf054f33a4dc15dfcff300414f60fd9cf2973 | 32,041 |
from sys import exc_info
def _triple():
"""Return a (type, value, tb) triple."""
try:
one()
except IndexError:
return exc_info()
else:
raise AssertionError('We should have had an IndexError.') | 455826d91dfcb5e6f76b46e4f2631c03f4e55474 | 32,042 |
from warnings import filterwarnings
def calcRSI(df):
"""
Calculates RSI indicator
Read about RSI: https://www.investopedia.com/terms/r/rsi.asp
Args:
df : pandas.DataFrame()
dataframe of historical ticker data
Returns:
pandas.DataFrame()
dataframe of calcula... | 4c2c76159473bf8b23e24cb02af00841977c7cd3 | 32,043 |
import os
def sample_images2(imgs, model, path, idx=None,save=False):
"""Saves a generated sample from the test set"""
true_map = Variable(imgs['B'].type(Tensor))
save_image(true_map, os.path.join(path, 'test_results/gt', str(idx)) +'.jpg', normalize=True)
fake_B = model(Variable(imgs['A'].type(Tensor... | 2d03f7756aeed6cb4bb7106c7393a42bf7dc2ee4 | 32,044 |
def grep_annotations_multiple_files(files_list, regex, base_path, grep_type):
"""
:todo Refactor and remove the ugly type option
"""
annotations_list = []
for f in files_list:
annotations = []
if grep_type == "code":
annotations = grep_code_annotations(f, regex, base_path... | 434ed6f72026a62cd410d8b7d62b35a5e1fe5440 | 32,045 |
def test_c_py_compose_transforms_module():
"""
Test combining Python and C++ transforms
"""
ds.config.set_seed(0)
def test_config(arr, input_columns, output_cols, op_list):
data = ds.NumpySlicesDataset(arr, column_names=input_columns, shuffle=False)
data = data.map(operations=op_lis... | e51191a48cc79bcac8cfe41508dd9e539da4645c | 32,046 |
import struct
def add_header(input_array, codec, length, param):
"""Add the header to the appropriate array.
:param the encoded array to add the header to
:param the codec being used
:param the length of the decoded array
:param the parameter to add to the header
:return the prepended encoded ... | 228db86bb6eb9e3c7cc59cc48b67e443d46cc36d | 32,047 |
import torch
def jaccard_loss(logits, true, eps=1e-7):
"""Computes the Jaccard loss, a.k.a the IoU loss.
Note that PyTorch optimizers minimize a loss. In this
case, we would like to maximize the jaccard loss so we
return the negated jaccard loss.
Args:
true: a tensor of shape [B, H, W] or ... | 10e113294f67cbe88b61e90af51c6c6659ead805 | 32,048 |
def _get_positional_body(*args, **kwargs):
"""Verify args and kwargs are valid, and then return the positional body, if users passed it in."""
if len(args) > 1:
raise TypeError("There can only be one positional argument, which is the POST body of this request.")
if "options" in kwargs:
raise... | c777296ab9c0e95d0f4d7f88dfd4ae292bfc558f | 32,049 |
def resize_image_with_padding(im, new_dims, interp_order=1):
"""
Resize an image array with interpolation.
Parameters
----------
im : (H x W x K) ndarray
new_dims : (height, width) tuple of new dimensions.
interp_order : interpolation order, default is linear.
Returns
-------
i... | d39195cdd20db2a7cd6750c7a81b419a62f820f9 | 32,050 |
from typing import List
from typing import Dict
def _get_run_stats(calc_docs: List[Calculation]) -> Dict[str, RunStatistics]:
"""Get summary of runtime statistics for each calculation in this task."""
run_stats = {}
total = dict(
average_memory=0.0,
max_memory=0.0,
elapsed_time=0.0... | fb83c559ced3ca44eaee767d6dabf8c183779f7f | 32,051 |
import os
def naming_convention(file_dir, file_name):
"""Rename files with 8-character hash"""
long_hash = sha1sum(os.path.join(file_dir, file_name))
file_prefix, file_sufix = file_name.split('.')
new_name = '{file_prefix}-{short_hash}.{file_sufix}'.format(
file_prefix=file_prefix,
sho... | c150ce78ddfa6ac35e74421eb89979d3e069a585 | 32,052 |
def mvn_log_pdf(x, mean, covariance):
"""
This function calculates the log-likelihood of x for a multivariate normal distribution parameterised by the
provided mean and covariance.
:param x: The location(s) to evaluate the log-likelihood. Must be [B x D], where B is the batch size and D is the
dimen... | dc2b019ace6760a040d97045b50b552e937706fd | 32,053 |
def question_input (user_decision=None):
"""Obtains input from user on whether they want to scan barcodes or not.
Parameters
----------
user_decision: default is None, if passed in, will not ask user for input. string type.
Returns
-------
True if user input was 'yes'
False is... | afb7f3d4eef0795ad8c4ff7878e1469e07ec1875 | 32,054 |
def depth(d):
"""Check dictionary depth"""
if isinstance(d, dict):
return 1 + (max(map(depth, d.values())) if d else 0)
return 0 | 6fd72b255a5fba193612cfa249bf4d242b315be1 | 32,055 |
import logging
def validate_analysis_possible(f):
"""
Decorator that validates that the amount of information is
sufficient for attractor analysis.
:param f: function
:return: decorated function
"""
def f_decorated(*args, **kwargs):
db_conn, *_ = args
if db_conn.root.n_agg... | 9de0cbf2e18e47d14912ae3ebdff526a73f2c25d | 32,056 |
import struct
def get_short_chan_id(source: hex, dest: hex) -> bytes:
"""Return a short channel id (bytes) based on source and destination provided.
"""
channel = [
channel
for channel in config.rpc.listchannels(source=source)["channels"]
if channel["destination"] == dest
][0][... | 11e3bccf4fb120b05c9da118f3e05dfc02394a9e | 32,057 |
import logging
import os
def register_logging(app):
"""日志处理器"""
class RequestFormatter(logging.Formatter):
def format(self, record):
record.url = request.url
record.remote_addr = request.remote_addr
return super(RequestFormatter, self).format(record)
request_fo... | d657df03bffa1bcd3a0bcbee20389e654b9f863f | 32,058 |
def get_rel(href, method, rule):
"""Returns the `rel` of an endpoint (see `Returns` below).
If the rule is a common rule as specified in the utils.py file, then that rel is
returned.
If the current url is the same as the href for the current route, `self` is
returned.
Args:
href (str)... | e1e5af2baabec766f07460275d7525569439b40c | 32,059 |
def is_exist(self, connectivity):
"""Check the existence of a cell defined by a connectivity (vector of points indices).
The order of points indices does not matter.
Parameters
----------
self : CellMat
an CellMat object
connectivity : ndarray
an array of node tags
Returns
... | 59f111040ba158fa03e82400c1d3cb9dc1444601 | 32,060 |
from typing import Optional
from typing import cast
def get_current_identity_arn(boto3_session: Optional[boto3.Session] = None) -> str:
"""Get current user/role ARN.
Parameters
----------
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_... | 892ffdd35d8a31849f4a53b0048a5bf87be624ce | 32,061 |
import hmac
def proxy_signature_is_valid(request, secret):
"""
Return true if the calculated signature matches that present in the query string of the given request.
"""
# Allow skipping of validation with an explicit setting.
# If setting not present, skip if in debug mode by default.
skip_v... | 4050c736188b53e274a16d26c4f45d8ac1983785 | 32,062 |
def remove_whitespace(sentences):
"""
Clear out spaces and newlines
from the list of list of strings.
Arguments:
----------
sentences : list<list<str>>
Returns:
--------
list<list<str>> : same strings as input,
without spaces or newlines.
"""
return [[w.... | ed50124aec20feba037ea775490ede14457d6943 | 32,063 |
def generate_jwt(payload, expiry, secret=None):
"""
生成jwt
:param payload: dict 载荷
:param expiry: datetime 有效期
:param secret: 密钥
:return: jwt
"""
_payload = {'exp': expiry}
_payload.update(payload)
if not secret:
secret = current_app.config['JWT_SECRET']
token = jwt.... | aa4727b7d26a7f00b015cbaed9a977c5865eedca | 32,064 |
import json
import secrets
def authentication(uuid):
"""Allow a client to request/recieve an authentication key."""
if request.method == "POST":
with peewee_db.atomic():
if RestClient.get_or_none(RestClient.uuid == uuid):
return json.jsonify({"msg": "UUID already exits."}),... | ec984b03c17917b12eb7ed6034c28b40f42aac63 | 32,065 |
def one_sided_ema(xolds, yolds, low=None, high=None, n=512, decay_steps=1.,
low_counts_threshold=1e-8):
"""From openai.baselines.common.plot_util.py
perform one-sided (causal) EMA (exponential moving average)
smoothing and resampling to an even grid with n points.
Does not do extrapol... | 17f14cd7a775c347366f375dfecef6285dc55af7 | 32,066 |
def settings_value(setting_name):
"""Return value for a given setting variable.
{% settings_value "LANGUAGE_CODE" %}
"""
return getattr(settings, setting_name, "") | aab0b2f16f0fa66a1c4066382b0b96c6c2a15215 | 32,067 |
def mongo_stat(server, args_array, **kwargs):
"""Method: mongo_stat
Description: Function stub holder for mongo_perf.mongo_stat.
Arguments:
(input) server
(input) args_array
(input) **kwargs
class_cfg
"""
status = True
if server and args_array and kwar... | 45ae8fd66a1d0cae976959644837fae585d68e65 | 32,068 |
import pickle
def train_new_TFIDF(docs, save_as=None):
"""
Trains a new TFIDF model.\n
If a user abstract is given, it is used for the training.
Parameters
----------
docs : `[String]`. Documents to train on\n
save_as : `String`. Name to save model as.
Returns
-------
`TfidfV... | be520b62fa6f718eeb185e59fed5fe3edf8d7ea7 | 32,069 |
import math
def generate_sphere_points(n):
"""
Returns list of coordinates on a sphere using the Golden-
Section Spiral algorithm.
"""
points = []
inc = math.pi * (3 - math.sqrt(5))
offset = 2 / float(n)
for k in range(int(n)):
y = k * offset - 1 + (offset / 2)
r = math.sqrt(1 - y*y)
phi =... | 6349f001709c2d2958cc2bcdd9bfe9c70a79b8f9 | 32,070 |
def get_options():
"""
Purpose:
Parse CLI arguments for script
Args:
N/A
Return:
N/A
"""
parser = ArgumentParser(description="Produce to Kafka Topic")
required = parser.add_argument_group("Required Arguments")
optional = parser.add_argument_group("Optional Argume... | a6168fb549fff9b2634f4c55cc625b7e3e387fa7 | 32,071 |
def _estimate_log_gaussian_prob(X, means, precisions_chol, covariance_type):
"""Estimate the log Gaussian probability.
Parameters
----------
X : array-like of shape (n_samples, n_features)
means : array-like of shape (n_components, n_features)
precisions_chol : array-like
Cholesky decomp... | c8d50ca609dfd877463ae20c572ec1ab60960b21 | 32,072 |
def descendants(region_id, allowed_ids, rm: RegionMeta):
"""Get all filtered descendant IDs of a given region ID.
A descendant is only accepted if it's in ``allowed_ids`` or is a
leaf region.
This is mimicking Dimitri's algorithm, I'm not sure about why this must
be that way.
"""
all_desce... | b0d1a5b57c00335343e52fbfe6e73b47bbccda42 | 32,073 |
import json
def search_classification(request):
"""
Filters the classification by name.
"""
filters = json.loads(request.GET.get('filters', {}))
fields = filters.get('fields', [])
page = int_arg(request.GET.get('page', 1))
classifications = Classification.objects.get_queryset()
if 'n... | fd1b78a9169c3496ee0b5d286d03d81cf75473c9 | 32,074 |
import click
def get_zone_id(ctx, param, zone_name):
"""Return the id for a zone by name."""
del ctx #unused
del param #unused
cf = CloudFlare.CloudFlare()
zones = cf.zones.get(params={'name': zone_name})
if len(zones) != 1:
raise click.ClickException('Invalid zone name: {}'.format(zon... | 07ebf939fe08b9f146ddb871af97e59c88e9484d | 32,075 |
from typing import List
def solve(letters: List[str], dictionary: trie.Node) -> List[str]:
"""Finds all words that can be made using the given letters.
"""
center_letter = letters[0]
words = set()
queue = deque([letter for letter in letters])
while queue:
candidate = queue.popleft()
... | 8a1773c6c388b88cc4b208ca24d5c0b8249722d0 | 32,076 |
from datetime import datetime
def datetime_from_milliseconds_since_epoch(ms_since_epoch: int, timezone: datetime.timezone = None) -> datetime.datetime:
"""Converts milliseconds since epoch to a datetime object.
Arguments:
----------
ms_since_epoch {int} -- Number of milliseconds since epoch.
... | 95528da79c78ca9956d656067b5be623058b12e6 | 32,077 |
def input_file(path):
"""
Read common text file as a stream of (k, v) pairs where k is line number
and v is line text
:param path: path to the file to read
:return: lazy seq of pairs
"""
return zip(count(), __input_file(path)) | d1699863f790181bdbd5ea1abc08446e32909ffc | 32,078 |
def lik_constant(vec, rho, t, root=1, survival=1, p1=p1):
"""
Calculates the likelihood of a constant-rate birth-death process, conditioned
on the waiting times of a phylogenetic tree and degree of incomplete sampling.
Based off of the R function `TreePar::LikConstant` written by Tanja Stadler.
T.... | bfb74866eec3c6eedbd6536522403f08340d39d7 | 32,079 |
def window_bounds(
window: Window,
affine: Affine,
offset: str = 'center'
) -> tuple[float, float, float, float]:
"""Create bounds coordinates from a rasterio window
Parameters:
window: Window
affine: Affine
offset: str
Returns:
coordinate bounds (w, s, e, n)
... | 6d6dca039213b4f5ea85d9168172b5cb32ff1a1e | 32,080 |
import copy
def get_k8s_model(model_type, model_dict):
"""
Returns an instance of type specified model_type from an model instance or
represantative dictionary.
"""
model_dict = copy.deepcopy(model_dict)
if isinstance(model_dict, model_type):
return model_dict
elif isinstance(mode... | 217c517b53acb596eec51773f856ceaf15a93597 | 32,081 |
def merge_specs(specs_):
"""Merge TensorSpecs.
Args:
specs_: List of TensorSpecs to be merged.
Returns:
a TensorSpec: a merged TensorSpec.
"""
shape = specs_[0].shape
dtype = specs_[0].dtype
name = specs_[0].name
for spec in specs_[1:]:
assert shape[1:] == spec.shape[1:], "incompatible shap... | fb0c895847c477cc90eb3b495505fe436667fe1e | 32,082 |
def makeMapItem(pl_id):
""" Recupere les items d'un player sur la map (stand ou pub). Utilise les fonctions makeMapItemStand et Pub.
:param arg1: id du joueur
:type arg1: int
:return: collection des objets appartenant au joueur, avec leur position
:rtype: Collection d'objets Json
"""
mapItem = []
mapItem.a... | 5bb5745dc161d74b2bd832a213c55906bc5f358c | 32,083 |
def get_test_result_records(page_number, per_page, filters):
"""Get page with applied filters for uploaded test records.
:param page_number: The number of page.
:param per_page: The number of results for one page.
:param filters: (Dict) Filters that will be applied for records.
"""
return IMPL.... | 89fc8b6d441ec8830cdb16fccfa142eed39f6c6a | 32,084 |
def new_graph(**kwargs) -> Plot:
"""[summary]
:return: [description]
:rtype: Plot
"""
return GraphPlot(kwargs) | 0bdbe97f6d86ba7dcfe802b5d41cb2e61fbb0ea7 | 32,085 |
def _average_path_length(n_samples_leaf):
"""
Taken from sklearn implementation of isolation forest:
https://github.com/scikit-learn/scikit-learn/blob/fd237278e/sklearn/ensemble/_iforest.py#L480
For each given number of samples in the array n_samples_leaf, this calculates average path length of unsuccee... | d6434c4ed437e0f8bff9e5d9f25bfdc84ce8f82d | 32,086 |
import pkg_resources
def get_pkg_license(pkgname):
"""
Given a package reference (as from requirements.txt),
return license listed in package metadata.
NOTE: This function does no error checking and is for
demonstration purposes only.
"""
pkgs = pkg_resources.require(pkgname)
pkg = pkg... | 238f2b3d33de6bf8ebfcca8f61609a58357e6da1 | 32,087 |
def parse(date):
"""
convert date from different input formats:
Parameters
----------
date : STR
FLOAT (unix timestamp)
Python native datetime.date object
pandas datetime object
Returns
-------
datetime.date
"""
out = False
try... | e7de2f8198c177630dfd75980b25fe5e9a70e0a2 | 32,088 |
def check_table_exist(conn):
"""Check if a table exists.
We do not use IF EXISTS in creating the table so as to we will not create
hyper table twice when the table already exists.
Args:
conn (psycopg2.extensions.connection): The connection to PostgreSQL database.
Returns:
... | 0d9199464c0323f5258e4ca6638b5a5c6759b434 | 32,089 |
import traceback
def get_err_str(exception, message, trace=True):
"""Return an error string containing a message and exception details.
Args:
exception (obj): the exception object caught.
message (str): the base error message.
trace (bool): whether the traceback is included (default=T... | 0ede3de80fb1097b0537f90337cf11ffa1edecf7 | 32,090 |
def epoch_data(data, window_length = 2,overlap=0.5):
"""
Separates the data into equal sized windows
Input:
- data: data to seperate into windows
- window_length: length of the window in seconds
- overlap: overlap, float in [0,1), in percentage overlap of win... | ab15ea4927118ed36ccd9d161772de7457239374 | 32,091 |
def dailyUsagePer15minn(index_list, tank_data_list):
"""Process tank temperatures series to water usage series divided into 96 15 minutes intervals, where each
interval has value in liters equal to used normalized hot water(37deg of c).
:param index_list: list of indexes
:param tank_data_list: list of ... | 7699b4455376675312b2800896db4f75b37a1ada | 32,092 |
def is_valid(number):
"""Check if the number provided is a valid CAS RN."""
try:
return bool(validate(number))
except ValidationError:
return False | 7e05c8e05f779c6f06150d90ab34b18585dd4803 | 32,093 |
import torch
def get_kernel(kernel_type, input_dim, on_gpu=True, **kwargs):
"""
Initializes one of the following gpytorch kernels: RBF, Matern
Args:
kernel_type (str):
Kernel type ('RBF', Matern52', 'Spectral)
input_dim (int):
Number of input dimensions
... | f9660ba9ef16a816a2377ac90531e6d2705a0659 | 32,094 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other | 685ff34e14c26fcc408e5d4f9219483118bfd3c0 | 32,095 |
def down_sample(source, freq_vocab, replacement='', threshold=1e-3, min_freq=0, seed=None, name=None):
"""Randomly down-sample high frequency tokens in `source` with `replacement` value.
Args:
source: string `Tensor` or `RaggedTensor` or `SparseTensor` of any shape, items to be sampled.
freq_vo... | 2209bcc48356f4d11c9151a80ab85069c8b6ad5b | 32,096 |
import platform
import pickle
def load_pickle(f):
"""使用pickle加载文件"""
version = platform.python_version_tuple() # 取python版本号
if version[0] == '2':
return pickle.load(f) # pickle.load, 反序列化为python的数据类型
elif version[0] == '3':
return pickle.load(f, encoding='latin1')
raise ValueErro... | 33db0ba6dbd8b1d2b3eba57e63d4069d91fbcb0b | 32,097 |
def extract_hashtags(text_list):
"""Return a summary dictionary about hashtags in :attr:`text_list`
Get a summary of the number of hashtags, their frequency, the top
ones, and more.
:param list text_list: A list of text strings.
:returns summary: A dictionary with various stats about hashtags
... | 688824fbef72c961b48a6bdb001983c25b1e0cee | 32,098 |
def skipif_32bit(param):
"""
Skip parameters in a parametrize on 32bit systems. Specifically used
here to skip leaf_size parameters related to GH 23440.
"""
marks = pytest.mark.skipif(
compat.is_platform_32bit(), reason="GH 23440: int type mismatch on 32bit"
)
return pytest.param(par... | 575226d01867ae1f898fc821fe1d51de5eb630fb | 32,099 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.