content stringlengths 35 416k | sha1 stringlengths 40 40 | id int64 0 710k |
|---|---|---|
from typing import Dict
from datetime import datetime
def inject_now() -> Dict:
"""Inject current datetime into request context."""
return dict(request_datetime=datetime.now()) | e186d4b478a5da5bcdf83e2e34cd381de8d039be | 697,860 |
def _make_eof_producer(producer):
"""
Send a special EOF byte sequence to terminate the request.
Args:
producer (Callable[[str, socket.socket], None]):
Request producer.
Returns:
Callable[[str, socket.socket], None]:
Request producer that sends 'END-OF-FILE' at ... | 9c035b1f790cab96c9cffc91e6dcf8a13017a4cc | 697,861 |
def in_key_rd_dicts( key_rd_dict, key_rd_dicts ):
"""Return True if key_rd_dict is contained in the list of key_rd_dicts."""
k = key_rd_dict.keys()[ 0 ]
v = key_rd_dict[ k ]
for key_rd_dict in key_rd_dicts:
for key, val in key_rd_dict.items():
if key == k and val == v:
... | 04c691a1a78834c7d660ae3036e97ea0e78393de | 697,862 |
def medical_covered_by_1(responses, derived):
""" Return whether the children are covered under Claimant 1's plan """
if responses.get('medical_coverage_available', 'NO') == 'YES':
return 'My plan' in responses.get('whose_plan_is_coverage_under', '')
return False | a5116dbe07fa97e95a349acfe926b228a6829488 | 697,863 |
import re
def split_text(text, pattern=r";|。|；|,|，"):
"""split text by pattern
Args:
text (str): text
pattern (regexp, optional): expression. Defaults to r";|。|；|,|，".
Returns:
str: text split by pattern
Examples:
>>> s = String()
>>> text = "收快递的时候最怕收不到货，所以购... | 080b63c947f5b9aca749e2ec4981f64c09e2ad43 | 697,864 |
def mixedomatic(cls):
""" Mixed-in class decorator. """
classinit = cls.__dict__.get('__init__') # Possibly None.
# Define an __init__ function for the class.
def __init__(self, *args, **kwargs):
# Call the __init__ functions of all the bases.
for base in cls.__bases__:
bas... | 3891a748a5cd6ee5e31c1441a7645343c0862135 | 697,865 |
def sphere_sre(solution):
"""
Variant of the sphere function. Dimensions except the first 10 ones have limited impact on the function value.
"""
a = 0
bias = 0.2
x = solution.get_x()
x1 = x[:10]
x2 = x[10:]
value1 = sum([(i-bias)*(i-bias) for i in x1])
value2 = 1/len(x) * sum([(i... | 38987c77a6586a0bfab1d94cc4a1511e9418349f | 697,867 |
from typing import Union
import pytz
from datetime import datetime
def localnow(tz: Union[pytz.BaseTzInfo, str] = "US/Central") -> datetime:
""" Get the current datetime as a localized datetime object with timezone information
Keyword Arguments:
tz {Union[pytz.timezone, str]} -- localize datetime to ... | 3dd9132c4adebacf5d348ec34523584642f7140b | 697,868 |
def get_increment(msg_list):
"""
:param msg_list: list of on/off midi signals
:return: minimum time of all signals
"""
result = float('inf')
for msg in msg_list:
if msg.time != 0.0 and msg.time < result:
result = msg.time
return result | 5b41d4a26b91c6c98d191867f0a968b1a389ba2b | 697,869 |
import timeit
def tic():
""" Default timer
Example: t = tic()
... code
elapsed = toc(t)
print( '{0}: {1:.4f}ms'.format(message, elapsed) )
"""
global lastticstamp
t = timeit.default_timer()
lastticstamp = t
return t | 7b68cde350e931d9e8f479151ed3c142298a6366 | 697,870 |
from typing import List
import torch
from typing import Tuple
def collate_fn(batch: List[torch.Tensor]) -> Tuple[Tuple[torch.Tensor]]:
"""[summary]
Args:
batch (List[torch.Tensor]): [description]
Returns:
Tuple[Tuple[torch.Tensor]]: [description]
"""
return tuple(zip(*batch)) | 798d12485f5e1b258b2bd3fe7137bfe1fe352a1b | 697,871 |
import torch
def threshold_mask(weights, threshold):
"""Create a threshold mask for the provided parameter tensor using
magnitude thresholding.
Arguments:
weights: a parameter tensor which should be pruned.
threshold: the pruning threshold.
Returns:
prune_mask: The pruning mas... | 43ca3f018f047e2ac46a83c36c368798b69e104a | 697,874 |
def sigmoid(attrs, in_xlayers):
""" Return sigmoid registration information (shape) """
assert len(in_xlayers) == 1
shape = in_xlayers[0].shapes[:]
return {'shape': shape} | 5637c532ed9eda6ec14abac0cf5e360a47c7333b | 697,875 |
def get_answer(file_answer):
"""
"""
with open(file_answer, 'r') as f:
return [x.split(';')[0].rstrip() for x in f.readlines()] | 0acfa654a328a5d4ac3a7c5cd291577be52b707b | 697,876 |
def string_is_yes(string, default=None):
"""
Mapping of a given string to a boolean.
If it is empty or None (evaluates to False), and `default` is set, `default` is returned.
If the lowercase of the string is any of ['y', '1', 'yes', 'true', 'ja'], it will return `True`.
Else it will return `False`... | 68482f78f8d4464891f14c19953e1a4785fe0811 | 697,877 |
import argparse
def default_tool_argparser(description, example_parameters):
"""Create default parser for single tools.
"""
epilog = '\n'
for k, v in sorted(example_parameters.items()):
epilog += ' ' + k + '\n'
p = argparse.ArgumentParser(
description=description,
add_help... | 8a90854d432f134047d402ac9639790ac0c8a15e | 697,878 |
import os
def get_files_by_ext(dirname, *exts):
"""Returns list of paths to files with extensions in *exts.
- dirname - path to directory
- *exts - file extensions to filter on
"""
fnames = [f for f in os.listdir(dirname) if os.path.splitext(f)[-1] in exts]
return [os.path.join(dirname, f) fo... | 7b6179a448517bc8558bf9f87b128c3a79f37f48 | 697,879 |
def look_and_say(string):
"""
Expand a string of digits according to look-and-say process in the problem.
Keyword arguments:
string --- a string to be processed
"""
result = ""
last = ""
count = 0
for digit in string:
if digit != last:
if(count):
result += str(count) + last
l... | cd8fcce76302cdb1c9af10d9481559c1eb098e43 | 697,880 |
import torch
def rel_to_rect(bb, sz_norm=None):
"""Inverts the effect of rect_to_rel. See above."""
sz = torch.exp(bb[...,2:])
if sz_norm is None:
c = bb[...,:2] * sz
else:
c = bb[...,:2] * sz_norm
tl = c - 0.5 * sz
return torch.cat((tl, sz), dim=-1) | ed2c31d1add58b1d5af843159eab4fa20471f76d | 697,881 |
def arrays_avg(values_array, weights_array=None):
"""
Computes the mean of the elements of the array.
Parameters
----------
values_array : array.
The numbers used to calculate the mean.
weights_array : array, optional, default None.
Used to calculate the weighted average, indic... | 2f24da412c548c1da53338f2f66d57d18473f798 | 697,882 |
import argparse
def check_rate(arg):
"""confirm rate is in [0.25, 4.0] interval"""
rate = float(arg)
if not 0.25 <= rate <= 4.0:
msg = (
"TTS rate only supported for floats in the range 0.25 (slow) to "
"4.0 (fast). Default is 1.0."
)
raise argparse.ArgumentTypeError(msg)
... | 90919858dfd40319e60436b229652cef14a7b1ba | 697,883 |
import re
def identify_all_potential_shifts(mut_desc, chain_sequence,allowed_shifts):
"""
identify all potential shifts
"""
md_re=r'(?P<wt>[A-Z])(?P<pos>[0-9]+)(?P<mut>[A-Z\(\)]+)$'
saved_shifts=[]
for shift in allowed_shifts:
proposed_shift=shift
... | 4938a498ed696e590892f701a393d74e5d1786b9 | 697,884 |
def issue_dictionary_from(column, issue) -> dict:
"""Map issue to dictionary with field names."""
return {
"project column": column.name,
"issue title": issue.title,
"issue description": f"{issue.body}\n\n---\n\n{issue.html_url}",
"labels": ";".join(
f"'{label.name}'"... | eae9e6cdf7ea3d715ad2e1dc8c31672c8c53762e | 697,885 |
def age_bin(age, labels, bins):
""" Return a label for a given age and bin.
Argument notes:
age -- int
labels -- list of strings
bins -- list of tuples, with the first tuple value being
the inclusive lower limit, and the higher tuple
value being the exclusive upper lim... | 9caccc667b55f66824bcf8802161384590cc2a08 | 697,886 |
import argparse
def parse_arguments():
"""
Parses the command line arguments and returns the namespace with those
arguments.
:type return: Namespace object
:param return: The Namespace object containing the values of all supported
command-line arguments.
"""
arg_parse =... | 2b3a8b32d430417c18845e89ec096a8c0ac6365e | 697,887 |
def list_intersect(first, second):
"""
Returns elements found in first that are in second
:param first:
:param second:
:return:
"""
second = set(second)
return [item for item in first if item in second] | 74cf1fc791a57c299f7fcf2369c105d68bda772e | 697,888 |
def process_covid_csv_data(covid_csv_data: list) -> tuple:
"""Function takes a list of data from an argument called covid csv data,
and returns three variables; the number of cases in the last 7 days,
the current number of hospital cases and the cumulative number of deaths,
as contained in the given csv... | 1fd7937656d25072aaba9a0cbf0ab16919f91b38 | 697,889 |
import io
import base64
def image_file_to_b64(image_file: io.BytesIO) -> bytes:
"""
Encodes an image file as Base64.
To obtain the stringified Base64 version of the image,
you can convert the output like so:
````python
image_file_to_b64(my_image_file).decode()
````
Arguments:
... | 2606f21fca825ea22c06f6372576110c64dc511c | 697,890 |
def search_theme(plot):
"""
>>> search_theme(['get up', 'discussion'])
['loss', 'loss']
"""
plot = ['loss', 'loss']
return plot | 9eb2104ba2f31a0386eccb13a3b1ad15a74f7fe6 | 697,891 |
import json
def get_pretty_print(json_object):
""" print json """
return json.dumps(json_object, sort_keys=True, indent=4, separators=(',', ': ')) | 2539d3572c260e4b4fe2061d4e3f6112d7ee8dd5 | 697,892 |
def base41_encode(input):
"""Encode an array of bytes to a Base41 string.
input is the array of bytes to encode.
The encoded string is returned.
If input has an odd number of bytes, a TypeError is raised.
"""
rslt = ""
i = 0
while i + 1 < len(input):
x = input[i] + 256 * i... | 46ef331084a9932d8bd7ccf574dd9f5afa9face2 | 697,893 |
from typing import Dict
from typing import Tuple
def read_multiscale_params(cfg: Dict[str, dict]) -> Tuple[int, int]:
"""
Returns the multiscale parameters
:param cfg: configuration
:type cfg: dict
:return:
- num_scales: number of scales
- scale_factor: factor by which each coarse... | 8021cc90c4a4740854a92a7d56524d7037e01988 | 697,894 |
import time
def timeMS():
"""Gives a count of miliseconds from 1.1.1970.
Returns:
int: Miliseconds form 1.1.1970
"""
return round(time.time() * 1000) | c42a220499c528ecde869e2c74dc383a84c71ea4 | 697,897 |
from typing import Any
from typing import Dict
import os
def file_parser(file_path: str, key_col: int, key_type: Any, val_col: int, val_type: Any,
delimiter: str=',', rows_to_skip: int=0) -> Dict[Any, Any]:
"""Parses a text file and returns a data dictionary of the form d[key] = val
Args:
... | a37eb14d427fa51e386397aa183228946b2f3bd6 | 697,898 |
import torch
def predict(data_loader, encoder, dfc, device='cpu', encoder_type = 'vae'):
"""
Args:
data_loader:
encoder:
dfc:
device:
encoder_type:
Returns:
feature, label
"""
features = []
labels = []
encoder.eval()
dfc.eval()
wit... | 1369ebb5d24a14371da6af5765b741cff2d42d35 | 697,899 |
def get_image_type(data):
"""Return a tuple of (content type, extension) for the image data."""
if data[:2] == "\xff\xd8":
return ("image/jpeg", ".jpg")
return ("image/unknown", ".bin") | 1677cb375a7b405b8a229f1246bdb27ed36dc654 | 697,900 |
def parse_conjugations(group):
"""
Parse conjugations in a word group.
:param group: string of a word group
:return: list of parsed conjugations
"""
return list(
map(
lambda x: x.split('/')[0].strip(),
group.split(' – ')
)
) | 0a1eca118a1f194a51a889a0fe30fe72488d6ada | 697,901 |
import tempfile
import os
import subprocess
def make_csr_from_key(private_key):
"""Create a certificate signing request (CSR) from the given private
key.
"""
(csr_fd, csr_file) = tempfile.mkstemp()
os.close(csr_fd)
# Write private key to temporary file
(key_fd, key_file) = tempfile.mkstem... | 645b89f18d920481926d1988c75f9f9660905342 | 697,902 |
def read_thresholds(path):
"""
Read the p-value thresholds for each tumour type
"""
thresholds = {}
with open(path) as f:
for line in f:
line = line.strip()
line = line.split('\t')
tumour = line[0]
threshold = float(line[1])
thresh... | 2615cd3b38e4ce1d80baacd06cf955895f0984ee | 697,904 |
def _one_contains_other(s1, s2):
"""
Whether one set contains the other
"""
return min(len(s1), len(s2)) == len(s1 & s2) | f7313cc0cbee823e39c30da22455e228162555be | 697,905 |
import os
def write_mets(http_response, package_uuid, subdir):
"""Given a http response containing our METS data, create the path
we want to store our METS at, and then stream the response into a
file.
"""
mets_file = "METS.{}.xml".format(package_uuid)
download_file = os.path.join(subdir, mets... | f13236f7524486c7ad3be5fbcd07daedf4bf5bd4 | 697,906 |
def linear_regression_line(mb):
"""
Given the output of ``linear_regression()`` function, or provided with
a tuple of ``(m, b)``, where ``m`` is the slope and ``b`` is the intercept,
``inear_regression_line()`` returns a function that calculates y values
based on given x values.
Args:
m... | dbc61ffafe603e8e6ec21f87debc170e3b6eb289 | 697,907 |
def values(df, field, **kwargs):
"""
Return values from a specific field of the data frame within a given time extent
Args:
df (pd.DataFrame): The exported TAP tool data
field (str): The field representing the column name
Returns:
np.ndarray: An array of the time-specified valu... | 6416c18ba3891a133c9ed0d487ca4b82d7a5291d | 697,908 |
import os
def get_parent_dir(current_file):
"""Get the parth path"""
current_dir = os.path.dirname(current_file)
parent_dir = os.path.dirname(current_dir)
return parent_dir | f1fc33dc0fbd6b358b672d695cd0ad89f9bb9b3e | 697,909 |
import copy
def return_prim_graph (dag, innodes, outnodes):
""" remove input and output nodes from a graph """
G_primitive = copy.deepcopy(dag)
nonprims = innodes+outnodes
for node in nonprims:
if node in dag.nodes():
G_primitive.remove_node(node)
return G_primitive | e59fcfcb5796739cc940f6052e56aa5a4837fd47 | 697,910 |
import re
def convert_doctoc(html):
"""
Convert doctoc to confluence macro
:param html: html string
:return: modified html string
"""
toc_tag = '''<p>
<ac:structured-macro ac:name="toc">
<ac:parameter ac:name="printable">true</ac:parameter>
<ac:parameter ac:name="style">disc<... | b2a52126d6a234894dcf6f98f0d399c309587a7e | 697,911 |
def flip_case(phrase, to_swap):
"""Flip [to_swap] case each time it appears in phrase.
>>> flip_case('Aaaahhh', 'a')
'aAAAhhh'
>>> flip_case('Aaaahhh', 'A')
'aAAAhhh'
>>> flip_case('Aaaahhh', 'h')
'AaaaHHH'
"""
return ''.join(letter.lower() if letter.lower... | ab3a18249e882bb0e8fda35a903048a20bd667e6 | 697,912 |
def apply_class_label_replacement(X, Y, replacement_method):
"""
Replace class labels using the replacement method
:param X: data features
:type X: numpy.Array()
:param Y: data labels
:type Y: numpy.Array()
:param replacement_method: Method to update targets
:type replacement_method: me... | eac01d31ff63e39d8c203803ae14c08365ec20a5 | 697,913 |
import torch
def nt_xent_loss(out_1, out_2, temperature):
"""
Loss used in SimCLR
"""
out = torch.cat([out_1, out_2], dim=0)
n_samples = len(out)
# Full similarity matrix
cov = torch.mm(out, out.t().contiguous())
sim = torch.exp(cov / temperature)
# Negative similarity
mask =... | 6634e42f540835f5a45c4812e54455d0328b6ec2 | 697,914 |
def fromScopus(scopus_author):
"""Fetch all publications associated with Scopus author
Parameters
----------
scopus_author : AuthorRetrieval
Scopus author retrieval object (scopus.author_retrieval.AuthorRetrieval)
Returns
-------
bibs : list
List of Scopus search publi... | 88aeca0f28af9ca3256e77f6e77207ffb51cefa0 | 697,915 |
def W(H) -> int:
""" Default image width (equal to height) """
return H | 4b3fdaaba9f5100096ca1ebbc22442de21b34ad5 | 697,917 |
def org_commits_by_day(df_raw):
"""Returns all commits with a count and a date index by day"""
odf_day = df_raw.resample('D').sum()
return odf_day | bb003b8ce1a0a28e632cfc78ffa3483359259e49 | 697,918 |
def make_queue_name(mt_namespace, handler_name):
"""
Method for declare new queue name in channel. Depends on queue "type",
is it receive event or command.
:param mt_namespace: string with Mass Transit namespace
:param handler_name: string with queue time. MUST be 'command' or 'event'
:return: ... | f74a7be8bf46a56f760b087fe47c9eda58d9f51e | 697,919 |
import ipaddress
import sys
def calculate_ip_addressing(input_net, man_address, man_next_hop):
""" Calculate IP addressing (address, neighbor, default route) on the specified interface
This function is AFI agnostic, just feed it ipaddress objects.
:param input_net: the IPv4/IPv6 network to use
... | dec5d929049f34fe8135bff51f562615e9465838 | 697,920 |
def _fix_cookiecutter_jinja_var(value, replace='cookiecutter.'):
"""Remove 'cookiecutter.' string from 'cookiecutter.varname' jinja strings
Can be used to remove different substrings as well by passing a string
to the optional ``replace`` parameter.
:param value: The string value within which to repla... | fc04d36a368fe7dd8c21a8dd3abe46f60d4d3d5e | 697,921 |
import subprocess
def sync_call(*args, cwd, **kwargs):
"""Helper function which enforces cwd argument"""
return subprocess.call(*args, cwd=cwd, **kwargs) | 9e3670413d9a6c763a234f7d6e4bea36bfc439cb | 697,922 |
def flatten_dict(row, keys=[('title',),
('street', 'city', 'postalCode')]):
"""Flatten a dict by concatenating string values
of matching keys.
Args:
row (dict): Data to be flattened
Returns:
flat (str): Concatenated data.
"""
flat = '' # The output d... | b4bafb0ec19a19d4223d7e9a94e3b8630cad1066 | 697,923 |
import os
def program_installed(app):
"""
Check if the given app is installed in the users PATH
"""
path = os.environ['PATH']
paths = path.split(os.pathsep)
for dir in paths:
if os.path.isdir(dir):
if os.path.isfile(os.path.join(dir,app)):
return True
re... | 9783927deb266407e89c0e446759d049824f7897 | 697,924 |
def sam_flag_check(query, subject):
"""
Check two numbers, query (for filtering) in subject or not
convert to binary mode
q: 0000010 (2)
s: 1011011 (91)
q in s
range: 0 - 2048 (SAM flag)
"""
def to_bin(n):
return '{0:012b}'.format(n)
# convert to binary mode
q = to... | 939109ad1c1668327cb4af4fcada818cea4653f4 | 697,925 |
import string
def get_range_to_here_hashes(repo, start):
"""Return a list of strings corresponding to commits from 'start' to here.
The list begins with the revision closest to but not including 'start'.
Raise a ValueError if any of the returned values are not valid hexadecimal.
:repo: a callable su... | 41a8795f489d1646ba48366c791308a6d1435b3e | 697,926 |
import os
def get_all_lobster_files(directory, file_type='COOPCAR.lobster'):
""" Get all DOSCAR and CONTCAR file paths
Parameters
----------
directory : str
root directory to look for DOSCAR files
file_type : string
file type for which to search and return file path
... | a5be225108408b4812f42bf89df8d84f46334ce8 | 697,927 |
import re
def check_token(token):
""" Checks if the given token is a valid UUID."""
valid = re.compile(r"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-"
r"[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$")
return valid.match(token) | be675b2fa04aac96b006ab94d8c0f65d8c02132f | 697,929 |
from typing import List
def lshift(array: List) -> List:
"""
Example
-------
>>> lshift([0, 1, 2, 3, 4])
[1, 2, 3, 4, 0]
>>> lshift([0])
[0]
>>> lshift([])
[]
"""
return (array[1:] + [array[0]]) if len(array) > 1 else array | dbd9e23120eb136fb9beb02fda027174e75905da | 697,930 |
import requests
from bs4 import BeautifulSoup
def url_to_soup(url):
"""url -> soup"""
html = requests.get(url)
return BeautifulSoup(html.text, 'html.parser') | 8b3e6a67c2123ca134d581631321cb8a8daf132a | 697,931 |
def is_vowel(char):
"""Check if it is vowel."""
return char in ['a', 'e', 'i', 'o', 'u', 'A', 'E', 'I', 'O', 'U'] | 97f747d96e08cd15fe7a1b742b36f5ff6cc2f3fc | 697,932 |
def gs_block(men, women, pref, blocked):
"""
Gale-shapley algorithm, modified to exclude unacceptable matches
Inputs: men (list of men's names)
women (list of women's names)
pref (dictionary of preferences mapping names to list of preferred names in sorted order)
blocked ... | ea69e56604cac25d8f5c9d957157dbd2d9ad1b27 | 697,933 |
from typing import Iterable
from typing import List
def filter_wikipathways_files(file_names: Iterable[str]) -> List[str]:
"""Filter files that have not 'ttl' extension or not start with 'WP'."""
return [
file_name
for file_name in file_names
if file_name.startswith('WP') and file_name... | abac5be763309986b951d574a72c0f2652b2a981 | 697,934 |
def attr_dict(cls: type, data: dict):
"""
Removes keys from the passed dict ``data`` which don't exist on ``cls`` (thus would get rejected as kwargs),
then create and return an instance of ``cls``, passing the filtered data as keyword args.
Ensures that any keys in your dictionary which don't exist on ... | c764cda2ad772de8b239fe34d39ef3ac92e658e5 | 697,935 |
import glob
def _find_my_yamls(myc_folder, specific_files=None):
"""Load all .yaml files in a folder or a specific list of yaml files."""
selected_files = []
if specific_files:
yaml_list = specific_files.replace(" ", "").split(",")
all_files = [myc_folder + yaml for yaml in yaml_list]
... | badb9f2165470516c7dd9c5ba2a7e7c1c76d7913 | 697,936 |
from typing import List
def sbd_3_bitwise(ids: List):
"""
Solution: Use bitwise XOR on a single variable for each element.
Complexity:
Time: O(n)
Space: O(1)
"""
unique_id = 0
for item in ids:
unique_id ^= item
return unique_id | d964fe78b2d1cf8de9e4d1cc165ea03a38eb6387 | 697,937 |
def process_spatial(geo):
"""Process time range so it can be added to the dates metadata
Parameters
----------
geo : list
[minLon, maxLon, minLat, maxLat]
Returns
-------
polygon : dict(list(list))
Dictionary following GeoJSON polygon format
"""
polygon = { "type"... | 4ff7dea7d7dcefd5b6bfb1605dd50345fc379527 | 697,938 |
def normalized (string) :
"""Normalize a base32 encoded string."""
return string.upper ().replace ("-", "") | 1998b41d9a27c78b5519983a880a1aa573a6e4ea | 697,939 |
def list_bank_cards(account_id): # noqa: E501
"""Return all bank cards for an account
Return all cards for the specified account # noqa: E501
:param account_id: Id of account
:type account_id: str
:rtype: List[BankCard]
"""
return 'do some magic!' | 6268d6a3584fa38cda3ae2294daaebb736f695d0 | 697,940 |
def int32(x):
"""Force conversion of x to 32-bit signed integer"""
x = int(x)
maxint = int(2**31-1)
minint = int(-2**31)
if x > maxint: x = maxint
if x < minint: x = minint
return x | 854338b7fd748ba5ddbbbd8c697288c6331995c4 | 697,941 |
def video_no_found(error):
"""no such video exists"""
return {'message': 'video does not exist'}, 404 | ec4b3149e1c8f8c7d02e0ae7926cc41cc7e6ad29 | 697,942 |
def get_type(transaction):
"""
:return: the type of the transaction
"""
return transaction['type'] | 4f66830f7c1e3bdc5d6b2c4ccc5db493014b9e5f | 697,943 |
def find_max_str(smiles: str) -> str:
"""
General functionality to choose a multi-smiles string, containing the
longest string
"""
smiles = max(smiles.split("."), key=len)
return smiles | 8b3f495492e471c7aee5fa856745179ecb1e8f8f | 697,944 |
from typing import List
from typing import Any
from typing import Optional
import random
def _subsample_array(
arr: List[Any],
max_values: int,
can_modify_incoming_array: bool = True,
rand: Optional[random.Random] = None,
) -> List[Any]:
"""Shuffles the array and returns `max_values` number of ele... | 379d056fefbc7b4a828a56dd9999545683a46a30 | 697,945 |
def format_bytes(n):
"""Format bytes as text
Copied from dask to avoid dependency.
"""
if n > 1e15:
return "%0.2f PB" % (n / 1e15)
if n > 1e12:
return "%0.2f TB" % (n / 1e12)
if n > 1e9:
return "%0.2f GB" % (n / 1e9)
if n > 1e6:
return "%0.2f MB" % (n / 1e6)... | f82a135f7f5308a04bf53bd3b8d1a05ef5d96de0 | 697,946 |
import os
def pipe(cmd):
"""Runs a command in a subprocess.
cmd: string Unix command
Returns (res, stat), the output of the subprocess and the exit status.
"""
# Note: os.popen is deprecated
# now, which means we are supposed to stop using it and start using
# the subprocess module. But... | 4c31602dbe882422f2e9b107c379c1edf5096489 | 697,947 |
def semideviation(r):
"""
Returns the semi-deviation (Negative Deviation) of r ,
r must be a Series or DataFrame
"""
is_negative = r <0
return r [is_negative].std(ddof=0) | 78eb4092f2c7ed5439ef4ee44b5ddef898bd53fa | 697,948 |
def compute_several_statistics(X, Args):
""" A function to compute and stack the results of several statistics on data X.
Inputs:
* X = the data
* Args = list constitued of statistics_list and statistics_args
Outputs:
* a list correspond to the value of each stati... | 7cefa8a25ef22e85271a56339cfb43b796c74933 | 697,949 |
import os
def replace_file_name(filename: str, replace_with: str) -> str:
"""
Replace file name with a fixed string, preserving its extension.
Result would look like `<replace_with>.<extension>`
:param filename: str
:param replace_with: str
:return: str
"""
_, file_extension = os.path.... | 68caaf94ab921a862ba3b3f50735e5c96101aec8 | 697,950 |
def get_p_val(rank_table):
"""
Input:
"""
r = 1-rank_table["rank"]*1./(rank_table["out_of"]+1)
r.sort()
r.name = "p_value"
return r | 387b819f1a028e42bedd301e2324c0b25c159ca8 | 697,952 |
def _change_galician_cc_token_before_subtree(sentence, token):
"""Determine the token directly preceding a subtree in a sentence.
Args:
sentence (`Sentence`): The sentence.
token (`Token`): The root token of the subtree.
Returns:
str: The ID of the token directly preceding the root token and all of its dep... | 21eebf0ba9ec02af4a7c65e8631a95e83b68372e | 697,954 |
import torch
def get_jacobian(inputs, func, **kwargs):
"""
Return Jacobian matrix of size m x n
of a function f: R^n -> R^m
"""
size = inputs.size()
n = size[0]
# Input dim
if (len(size)) > 1:
dim_input = size[1]
else:
dim_input = 1
test = func(inputs, **kw... | 5ff764a11512ed3813956c7549562761b430092f | 697,955 |
def turn(p1, p2, p3):
"""
0 if the points are colinear
1 if the points define a left-turn
-1 if the points define a right-turn
"""
# Compute the z-coordinate of the vectorial product p1p2 x p2p3
z = (p2[0] - p1[0]) * (p3[1] - p1[1]) - (p2[1] - p1[1]) * (p3[0]- p1[0])
return 0 if z == 0 e... | 2b8dccbe0111d9cd655f4a6a8bc2131b73f3a3ee | 697,956 |
def find(node):
"""Find current canonical representative equivalent to node.
Adjust the parent pointer of each node along the way to the root
to point directly at the root for inverse-Ackerman-fast access.
"""
if node.parent is None:
return node
root = node
while root.parent is not ... | c9827af585c2bcd284640213bb92ae951659abf8 | 697,957 |
from typing import Optional
from pathlib import Path
from typing import Union
import logging
import os
def init_worker_env(
gobbli_dir: Optional[Path] = None, log_level: Union[int, str] = logging.WARNING
) -> logging.Logger:
"""
Initialize environment on a ray worker.
Args:
gobbli_dir: Used a... | 62309256e5430759ea70c2bfb649cecc58369b95 | 697,958 |
from os.path import join
def get_h5_file_name(cfg):
"""Return the HDF5 file name based on the configuration file"""
return join(cfg['output']['filepath'], f"{cfg['output']['fileprefix']}.{cfg['output']['type']}") | 70a6fef2198e3a5c70e4a176c1078c105dd38d04 | 697,959 |
def worker_number(worker_id):
"""Get the current worker number."""
id_as_str = "".join(ch for ch in worker_id if ch.isdigit())
if len(id_as_str) == 0:
return 0
return int(id_as_str) | 3cd6ca7e665fefda9427476e39de5ea23f843f72 | 697,960 |
import string
import re
def rm_non_textual_punct(dfcol):
""" Aggressively remove almost all punctuation (except .,?:;- ) """
text_punct = '.,?:;-' #this also removes + <> $ %
nontext_punct = [char for char in string.punctuation if char not in text_punct]
nontext_punct = re.escape(''.join(nontext_punct... | ff9dfc87ec0015b4a0d0ca5d83db3b116e476470 | 697,963 |
def get_reference_value_from_spec(openapi_spec: dict, reference_path: str) -> dict:
"""Follows the reference path passed in and returns the object at the end of the path
Args:
openapi_spec (dict): The openapi.json specification object
reference_path (str): a path formatted as "#/foo/bar/baz"
... | c32962a3b008825de4c5108d8d1a3ad5db179b17 | 697,964 |
def hide_keys(dictionary, keys_to_hide, new_value="xxx"):
"""
Return a copy of the given dictionary on which specified keys will be replaced by the new_value word (or 'xxx').
:param dictionary: a dictionary
:param keys_to_hide: keys to hide in the output dictionary
:param new_value: replacement str... | d6b8bc7958c637212899c048a9958ac3d2755894 | 697,965 |
def get_seq(_seq, _start, _end):
"""
:param _seq:
:param _start: !!! should be SSR start position on genome (begin from 1, not 0)
:param _end: !!! should be SSR end position on genome (begin from 1, not 0)
:return:
"""
if _start <= 200:
return _seq.seq[0: _end+200]
elif _end >= ... | c42db6e6a50fa46c30e948ac6f007d5c92e07708 | 697,967 |
import random
def active_sample(network, size, evaluate):
"""
Sample from affected genes as null model.
"""
sample = random.sample(network.nodes(), size)
subnet = network.subgraph(sample)
result = evaluate(subnet)
return result | d5f7ecf87e6b72b5930fe066e13fd593626fd352 | 697,968 |
def get_other_dims(da, dims_exclude):
"""
Returns all dimensions in provided dataset excluding dim_exclude
| Author: Dougie Squire
| Date: 22/04/2018
Parameters
----------
da : xarray DataArray
Array to retreive dimensions from
... | 506a8b7193ea95480c83e3d69a31774f77d4fbcc | 697,969 |
def standard_split(text, row_length):
"""text = abcdefghijklmnopqrstuvwxyz and row_length = 5
abcde
fghij
klmno
pqrst
uvwxy
z returns ['afkpuz', 'bglqv', 'chmrw', 'dinsx', 'ejoty']
"""
output = []
text_length = len(text)
# Takes output column by index in turn, taking e.g... | 3a4732433b58777dcf08529b98b90f890e680a29 | 697,970 |
def median(x):
"""Return the median of a list of values."""
m, r = divmod(len(x), 2)
if r:
return sorted(x)[m]
return sum(sorted(x)[m - 1:m + 1]) / 2 | 337584e40c61bd198496355e38f4a8d4da9310fa | 697,971 |
def _get_args(tp):
"""Backport of typing.get_args for Python 3.6"""
return getattr(tp, "__args__", ()) | f265cb6d8d85601d9ee6f20be8f78c8d9819c920 | 697,972 |
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