content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def ConvertListToCSVString(csv_list):
"""Helper to convert a list to a csv string."""
return ','.join(str(s) for s in csv_list) | 547311ceac094211d47d0cc667d54b2a3e697f4e | 3,625,700 |
import os
def list_projects(verbose=True):
"""
Lists all projects that exist.
Args:
verbose: can be silent
"""
home_path, db_path, run_path, archive_path, disc = wrftamer_paths()
list_of_projects = [
name
for name in os.listdir(db_path)
if os.path.isdir(os.p... | b053193b6370b17ff69a16a6455a9697dc6bf0e4 | 3,625,701 |
def random_scale(img, min_size):
"""
min_size default: 640
正因为调用了这个函数，初始化成归一化的坐标就不用维护了
"""
h, w = img.shape[: 2]
if max(h, w) > 1280:
scale = 1280.0 / max(h, w)
img = cv2.resize(img, dsize=None, fx=scale, fy=scale)
h, w = img.shape[: 2]
random_scale = np.array([0.5, 1.0,... | 7a33d60f03c254c087c47d82ec8f12999037a5e4 | 3,625,702 |
def get_learn_performance(model):
""" For acquiring the sum total performance of a strategy"""
# get the list of agent
strategy = [a.strategy for a in model.schedule.agents]
# get the list of agent performances
scores = [a.score for a in model.schedule.agents]
# for each in that list, when stra... | 9515c1c9b11461dc8b26ffa627c7cd0e4e4e539c | 3,625,703 |
def min_distance_bottom_up(word1: str, word2: str) -> int:
"""
>>> min_distance_bottom_up("intention", "execution")
5
>>> min_distance_bottom_up("intention", "")
9
>>> min_distance_bottom_up("", "")
0
"""
m = len(word1)
n = len(word2)
dp = [[0 for _ in range(n + 1)] for _ in ... | 8cd87ffe877aa24d5b1fa36ce1d3b96efb7b4e1e | 3,625,704 |
def adjust_cell_formula(value, k):
""" Cell formula, i.e., if i=5, val=?(A11)+?(B12) -> val=A16+B17 """
if isinstance(value, str):
for i in range(value.count('?(')):
if value and '?(' in value and ')' in value:
i = value.index('?(')
j = value.index(')', i)
... | c95cd7a3e4667749c3aec502c33977ef93530a9e | 3,625,705 |
def insert_data(id: str, og: str, value: int):
"""
Insert data in db
Params:
id: short url(primary key)
og: original url
value: number of visit
returns:
True if successful else False
"""
query = f'''INSERT INTO URLS (ID, ORIGINAL, VISITS) VALUES ("{str(id)}", "{st... | 0fe1ff2679bee1353066f9c372a89e87193036ef | 3,625,706 |
def main(df):
"""
main function returs a clean data frame
Returns
-------
df_new : pandas data frame
clean data.
"""
df_new = data_cleaning(df)
return df_new | ce4bf4c8b184da27c801a29d32acdd9160b5c9c9 | 3,625,707 |
def lCQgCPevBZXs():
"""Package link to operation."""
pkg = Package("pkg")
return pkg.circles.long_operation.Bar | 7e204094d51a4344264ef22d0a22edf8da0dcccf | 3,625,708 |
def isExtended(lut):
""" Returns True if the lookup table has been extended with isExtended.
I.e. returns True if the last and second to last LUT entries are the same
"""
assertIsLut(lut)
return np.array_equal(lut[-1, :], lut[-2, :]) | ee00813f8b07697b3eb77935dc41c674deb102b3 | 3,625,709 |
import re
def exclude_regexps(regexps, suite):
"""Returns the tests whose id does not match with any of the regexps."""
if not regexps:
# No regexpes, no filtering
return suite
def matches_none_of(test):
# A test is kept if its id matches none of the 'excludes' regexps
tid... | 44e93679ef1ea40b7333794e284b8c9bef117ba4 | 3,625,710 |
import joblib
def _load_fcn(path, extension):
"""Actual loading function, which handles the cases specified in `load()`."""
if extension == "pt":
obj = to.load(path)
elif extension == "npy":
obj = np.load(path)
elif extension == "pkl":
obj = joblib.load(path)
else:
... | faddd58753fc3ed6c13fbe793223ec37c9531448 | 3,625,711 |
def tasks_mult_per_owner():
"""Several owners with several tasks each."""
return (
Task('Make a cookie', 'Raphael'),
Task('Use an emoji', 'Raphael'),
Task('Move to Berlin', 'Raphael'),
Task('Create', 'Michelle'),
Task('Inspire', 'Michelle'),
Task('Encourage', 'Mi... | fccf075a8b69301672ed9abfeb85a53254309ee9 | 3,625,712 |
def generate_systemd_scion_config(host, archive, with_sig_dummy_entry=False):
"""
Generate the configuration archive for the :host: in the given archive-writer
:param host: Host object
:param scionlab.util.archive.BaseArchiveWriter archive: output archive-writer
:returns: list of systemd units that ... | 90b8453d83fb93a03f17973febf1b633924be8c2 | 3,625,713 |
import json
def lascoverage(inputfile):
"""
Provide a file name with extension:
- las
- laz
...extract a tight polygon around the XY points in the file
and return a GeoJSON polygon
"""
# define a pipeline
metapipeline = {
"pipeline": [
{
"type":... | 08a2c2f85060552f0b181c6db20fcbbb06a39016 | 3,625,714 |
def get_renovations(ids, cache_time=5):
"""
Get stadium renovation by ID
Args:
ids: renovation ID(s). Can be a single string ID, comma separated string, or list.
cache_time: response cache lifetime in seconds, or `None` for infinite cache
"""
if isinstance(ids, list):
ids = ... | 0bbff09433a6e74f728960e7d9796ccfcfacbb47 | 3,625,715 |
def _simulate_delta_rule_2A(task_design,
alpha,
initial_value_learning,
alpha_pos=None,
alpha_neg=None):
"""Q learning (delta learning rule) for two alternative... | cb3fa709bea70d396cde0369bc70a68b8121c469 | 3,625,716 |
def get_sha3_calculator(input_bytes):
"""
Returns object that can be used to calculate sha3 hash
:param input_bytes: input bytes
:return: object that can calculate sha3 256 hash
"""
if input_bytes is None:
raise ValueError("Input is required")
return keccak.new(digest_bits=eth_comm... | 3fa938d02f988f6d7903fffea833a4634ca60d9e | 3,625,717 |
import ast
def Exec(content, global_scope, local_scope, filename='<unknown>'):
"""Safely execs a set of assignments. Mutates |local_scope|."""
node_or_string = ast.parse(content, filename=filename, mode='exec')
if isinstance(node_or_string, ast.Expression):
node_or_string = node_or_string.body
def _visit... | 4a7839072d31cba7326427b92471a5bd144a0028 | 3,625,718 |
def alerts():
"""
Endpoint to return and alerts we have
:returns result: dict with array of dicts containing alert data
"""
result = dict()
result['alerts'] = []
alert_list = Alert.query.all()
for alert in alert_list:
result['alerts'].append(alert.message)
return jsonify(re... | eede001e5b7a9d1898bb4ce476288c2bdf4cb531 | 3,625,719 |
def ff_multiplicative_inverse(a, modulus=0x11b):
"""
Based on extended Euclidean algorithm
>>> hex(ff_multiplicative_inverse(0x53))
'0xca'
"""
b = modulus
x0, x1 = 0, 1
while a:
(q, a), b = ff_divmod(b, a), a
x0, x1 = x1, x0 ^ ff_multiply(q, x1, modulus)
_, r = ff_divmod(x0, modulus)
return r | b6b863082ed9f341df7cbc099abda2d4c7e0f653 | 3,625,720 |
def list_own_groups(cm_id, caller_id):
"""
Method returns list of the groups caller is leader of.
@clmview_user
@response{list(dict)} dicts describing groups led by caller
"""
user = User.get(caller_id)
# returns all the groups where the user is the leader
return [g.dict for g in user... | 3bee791cc7f2dbd9cce72acfcd5d00afe5b7ba3b | 3,625,721 |
import copy
def _oned_intFunc(x,twodfunc,gfun,hfun,tol,args):
"""Internal function for bovy_dblquad"""
thisargs= copy.deepcopy(args)
thisargs.insert(0,x)
return integrate.romberg(twodfunc,gfun(x),hfun(x),args=thisargs,tol=tol) | 748fa35dbb2364b2c9cd8324356ac6f19f6ba320 | 3,625,722 |
def get_category(category_string, model=Category):
"""
Convert a string, including a path, and return the Category object
"""
model_class = get_cat_model(model)
category = str(category_string).strip("'\"")
category = category.strip('/')
cat_list = category.split('/')
if len(cat_list) ==... | 738be2115cd4b3cc7c3ad9aabbeda0ead9eab66a | 3,625,723 |
def genselect(arr, inds):
"""Select some elements along the inds.ndim-th axis of arr. Takes arr of
shape shape (a1, a2, …, am), and inds of shape (a1, a2, …, a(k-1), bk),
where k <= m. The elements of inds index into the kth axis of a, allowing
you to keep only a subset of "supercolumns" along a given a... | e763ab5981da44476807603082decdb494b268e4 | 3,625,724 |
def info(_: Request) -> Response:
"""
Definition of the /info endpoint, in accordance with SEP-0038.
See: https://github.com/stellar/stellar-protocol/blob/master/ecosystem/sep-0038.md#response
"""
info_data = {"assets": []}
for asset in Asset.objects.filter(sep38_enabled=True):
info_data... | 75314803d5b6b2d40f17a420efb4ae1a94cc0d68 | 3,625,725 |
def remove_nan(*args):
"""
*args: 1d arrays of the same length
"""
# Check input arrays have the same wavelegth
# ...
# Find bad pixels: nan, null or negative wavelengths
mask = []
mask = np.ones_like(args[0], dtype=bool)
for a in args:
for i in np.arange(len(a)):
... | 415f172ded154e12c9e0e0f5c6e282e98833ce07 | 3,625,726 |
def periodize_filter_fourier(h_f, nperiods=1, aggregation='sum'):
"""
Computes a periodization of a filter provided in the Fourier domain.
Parameters
----------
h_f : array_like
complex numpy array of shape (N*n_periods,)
n_periods: int, optional
Number of periods which should be... | f9a2845dcf40eedce9d46faba506f1c1358ce6a5 | 3,625,727 |
def bounding_box_crop(x,
bbox,
min_object_covered=0.1,
aspect_ratio_range=(0.75, 1.33),
area_range=(0.05, 1.0),
max_attempts=100):
"""Generates cropped_image using a one of the bboxes randomly distorted."""
... | d646e4fea765acecb29bed216b639d59b32209ba | 3,625,728 |
from sfepy.fem.probes import LineProbe
def gen_lines(problem):
"""
Define three line probes in axial directions.
Parameters
----------
problem : ProblemDefinition instance
The current ProblemDefinition instance.
Returns
-------
probes : list
The list of the probes... | 5b8ce8e3a39c99e9d0d357f4ae3dbaff86ee2f45 | 3,625,729 |
def authenticated_http_request(service_account, *args, **kwargs):
"""Sends an OAuth2-authenticated HTTP request.
Args:
service_account: Service account to use. For GCE, the name of the service
account, otherwise the path to the service account JSON file.
Raises:
AuthenticatedHttpRequestFailure
"... | c06637978dc23dd6e69bcf5cd087d4423d2726df | 3,625,730 |
import os
def load_config(config_path):
"""
load a config from the given path
"""
conf = os.path.expanduser(config_path)
if not os.path.exists(conf):
print("No config file at location: %s. Add --config to specify\
location or run from dir containing config.py." % conf)
... | 5e076c3de17df795665fe3ba51943659301a0ca4 | 3,625,731 |
def add_extra_columns(df, datatype='sim'):
""" Function to add to new columns to DataFrame that are commonly used
Parameters
----------
df : pandas.DataFrame
Input DataFrame
datatype : str, optional
Specify whether this is a DataFrame based on simulation or data
(default is ... | ee8fdd74132ed2d471b8393f61e26c51b18440d3 | 3,625,732 |
def _search(json_, query):
"""Search for matching packages.
:param json_: output json if True
:type json_: bool
:param query: The search term
:type query: str
:returns: Process status
:rtype: int
"""
if not query:
query = ''
config = util.get_config()
results = [ind... | 45e4fa71a5b5c77b40b89eff631491e0e369cf15 | 3,625,733 |
import base64
def decode_image(uri: str) -> np.array:
"""
Translates image from base64 string to numpy array.
"""
data = uri.split(",")[1]
data = BytesIO(base64.b64decode(data))
image = Image.open(data).convert("RGB")
return np.array(image) | 9a46dff14a7b6392cbe2b98f6658cbb759affd7f | 3,625,734 |
def solve_for_map(ds, m0, obs_mean, obs_std,
m_packer, obs_packer, mask3D, mds,
n_small=None,xdalike=None,dsim=None,dirs=None):
"""Solve for m_MAP
$m_{MAP} = m_0 + H^{-1}F^T R^{-1}(d - F m_0)$
Parameters
----------
ds : xarray Dataset
containing the EVD ... | 887f98d41c05bd64c906790c138b3e005c1ea26a | 3,625,735 |
def str_q2b(ustring, skip_cn_punc=False):
""" 全角转半角 """
return ''.join([q2b(uchar, skip_cn_punc) for uchar in ustring]) | f5db8276689fb62a434506f9f4fe4555d48c1173 | 3,625,736 |
def quick_sort(data):
"""To sort data as an increase order by divide and conquer method."""
def q_sort(left_index, right_index):
"""Do quicksort recursively."""
if right_index <= left_index:
return
# Sort sub partition.
part = partition(left_index, right_index)
... | e8c530b6da3f705b08279eb213d03bd54820f4a4 | 3,625,737 |
from datetime import datetime
import json
def monitor(event, context):
"""
This method looks for security groups and reports
any found groups to a json file in s3.
"""
groups = getAllSecurityGroups()
if len(groups) is 0:
logger.warning("no security groups found")
return
#... | 648c8bd478eae48677c1126f75c6fab3588375e7 | 3,625,738 |
def load_8_color_data(shot, frames=range(5,12), remove_edges=True, data=False, start_n = 13, end_n = 46, ignore=[22]):
"""
This function automatically loads data from the tree and passes it on to the load_8_color function. When loading data
this is generally the preferred method.
"""
MST_data = load... | 207b1516e8141a7f96af067157e8eb7a37a0fb82 | 3,625,739 |
import traceback
def error(mixed):
"""Show error page for HTTP and form errors.
:param mixed: String or actual catched exception.
"""
status = 400
trace = None
if isinstance(mixed, string_types):
page, error = mixed.split(':')
message = ERRORS[page][error]
else:
m... | ee4692fe362af93f68098192ff70bd838d5e7cb2 | 3,625,740 |
import os
def load_mnist(final = False, flatten = True):
"""
Load the MNIST data
:param final: If true, return the canonical test/train split. If false, split some validation data from the training
data and keep the test data hidden.
:param flatten:
:return:
"""
if not os.path.isfile('... | 682219013f0b4d9b60bbb90d58dd470e25571b7f | 3,625,741 |
def get_connection_params(config):
"""
Creates instances of DatasetParams, SystemParams, DatasetToSystemParams, and CollectionParams for connection
generation from config.
"""
dataset_params = DatasetParams(
dataset_count=config["dataset"]["dataset_count"],
dataset_env_count_map=proc... | 400369514000838af61eb8c5dc7040f2509ec761 | 3,625,742 |
def slope_id(csv_name):
"""
Extract an integer slope parameter from the filename.
:param csv_name: The name of a csv file of the form NWS-<SLP>-0.5.csv
:return: int(<SLP>)
"""
return int(csv_name.split("-")[1]) | 1ae34f1e5cc91fdc3aaff9a78e1ba26962475625 | 3,625,743 |
def full_path_to_points(path):
"""
Find the corners of the path
:param path: a list containing, a list of the x coordinates and a list of the y coordinates of the path
:return:a list containing, a list of the x coordinates and a list of the y coordinates of the corners of the path
"""
points_x =... | 7b740b136b232ab98fd7fe7d0f3ff129c69a14a7 | 3,625,744 |
import requests
def check_parent_login(username, dob):
"""Checks if user input for their credentials is correct
for parent's portal.
:param username: student's PID (format: XXXNameXXXX)
where X - integers
:type username: str
:param dob: User's Date of Birth
:type do... | 8817cd24a767f2a4deb71a7e0f5a122c7504146c | 3,625,745 |
import calendar
def within_duration(date: dt, start: dt, end: dt, is_break: bool, term: int) -> bool:
"""
Check if the date is within the current duration
If it is, print out the date as what week of the term or break it is
and return True
"""
if not start <= date <= end:
return False
... | c8198da050629d51ccc4c0b3e6d8f991105116c2 | 3,625,746 |
from joblib import delayed, Parallel
def joblib(function, argument_list, num_cores=None):
"""Apply a univariate function to a list of arguments in a parallel fashion.
Uses Joblib's delayed() function with a parallel executor that starts multiple
processes.
Args:
function: A callable object t... | 4a81738bf8dca1c570e34d2c39827bd052e746d7 | 3,625,747 |
def read_input(filename):
"""read input file and return list of raw intcodes."""
with open(args.input, "r") as infile:
raw_intcodes = infile.readlines()[0].strip().split(",")
return raw_intcodes | 3ff908d5552ff64e4d43b5a6454696ce1aa94b21 | 3,625,748 |
def marketYesterday(token="", version="stable", filter="", format="json"):
"""This returns previous day adjusted price data for whole market
https://iexcloud.io/docs/api/#previous-day-prices
Available after 4am ET Tue-Sat
Args:
token (str): Access token
version (str): API version
... | 701b9d9a6ab29dab7c61cf4f55e164b6b46d4651 | 3,625,749 |
def r2_glmnet(cv_out, y):
"""calculate r2 using the lambda_1se. This value is for the most regularized model whose mean squared error is
within one standard error of the minimal."""
# https://stackoverflow.com/questions/50610895/how-to-calculate-r-squared-value-for-lasso-regression-using-glmnet-in-r
be... | affc0b08207f7d8d14036953192687c17cfa8441 | 3,625,750 |
def shift_x(x, shift_amt):
"""
Shifts (registers) the raster plot x by shift_amt
"""
shifted = np.zeros_like(x)
for t in range(x.shape[1]):
col = x[:,t]
sh = shift_amt[t]
shifted[:,t] = shift(col, sh)
return shifted | 61acf0496b52bb34f3041e4ee1750eaa3eaebe9b | 3,625,751 |
def get_start_sig(line: dict, sched_line: m_sched.LineSchedule, i_stop):
"""select start signal from branching data and target signals of last stop"""
i_prev = (i_stop - 1) % len(line["stops"])
target_signals = list(line["routing"][i_prev].values())[0]["next"]
start_signal_str: str = target_signals[sch... | ddac473aef1b9f9b62434a9b1577519f4be6f784 | 3,625,752 |
def minbox(points):
"""Returns the minimal bounding box necessary to contain points
Args:
points (tuple, list, set): ((0,0), (40, 55), (66, 22))
Returns:
dict: {ulx, uly, lrx, lry}
Example:
>>> minbox((0, 0), (40, 55), (66,22))
{'ulx': 0, 'uly': 55, 'lrx': 66, 'lry': 0... | d8b11d40b52886f290d28f3434b17d2b9641c4fb | 3,625,753 |
import json
def update_workspace_acl(namespace, workspace, acl_updates, invite_users_not_found=False):
"""Update workspace access control list.
Args:
namespace (str): project to which workspace belongs
workspace (str): Workspace name
acl_updates (list(dict)): Acl updates as dicts with... | 05d5f0f259526e1c845a5c768c257188af3e4798 | 3,625,754 |
def resolve_cname(hostname):
"""Resolve a CNAME record to the original hostname.
This is required for AWS where the hostname of the RDS instance is part of
the signing request.
"""
try:
answers = dns.resolver.query(hostname, "CNAME")
for answer in answers:
if answer.rdt... | f7c090517531c18d103502600cb7c86c4869a494 | 3,625,755 |
from .nn import stack
import numpy
def eye(num_rows, num_columns=None, batch_shape=None, dtype='float32'):
"""
:alias_main: paddle.eye
:alias: paddle.eye,paddle.tensor.eye,paddle.tensor.creation.eye
:old_api: paddle.fluid.layers.eye
**eye**
This function constructs an identity tensor, or a batch of t... | 6254ee8fc44c3af847a15d02306482826a299e2c | 3,625,756 |
from typing import Tuple
def _IsRetriableHTTPError(ret_value: Tuple[httplib2.Response, Text]) -> bool:
"""Determines whether the given HTTP exception is retriable.
Args:
ret_value: The return Tuple returned from the request method.
Returns:
Whether the exception can be retried.
"""
retriable_http_... | f96364c741a9035029bc94dc681ffd4e869ba44f | 3,625,757 |
import csv
def write_csv(history, filename):
""" Write Letterboxd format CSV """
if history:
with open(filename, 'w', encoding='utf8') as fil:
writer = csv.DictWriter(fil, list(history[0].keys()))
writer.writeheader()
writer.writerows(history)
return True
... | 66ab2c9734c5d50b59d1aaff2dd62a4fffcfe0ec | 3,625,758 |
def apply_regression(df, w):
"""
Apply regression for different classifiers.
@param df pandas dataframe;
@param w dict[classifier: list of weights];
@return df with appended result.
"""
# get input
if 'state' in df.columns:
x = df.drop('state', axis=1).to_numpy(dtype='float64')
... | 1fb5fd9f4b297cd024e405dc5d9209213d28ff0d | 3,625,759 |
async def asset(request):
""" Browse a particular asset for which we have recorded readings and
return a readings with timestamps for the asset. The number of readings
return is defaulted to a small number (20), this may be changed by supplying
the query parameter ?limit=xx&skip=xx and it will not respe... | 2a42cc3f23259b57a51c170920fe998d4a7b7712 | 3,625,760 |
def get_geopandas_df(path):
"""
Creates geopandas dataframe from geeojson file
at "path" filepath
"""
open_json = open_geojson(path)
gdf = gpd.GeoDataFrame.from_features((open_json))
return gdf | d21d0285e9333385cd5b71b7c02702d3f41b49db | 3,625,761 |
from typing import Optional
def fabs(x: DNDarray, out: Optional[DNDarray] = None) -> DNDarray:
"""
Calculate the absolute value element-wise and return floating-point class:`~heat.core.dndarray.DNDarray`.
This function exists besides ``abs==absolute`` since it will be needed in case complex numbers will b... | 0e063ad4d691958b90dd877c138fed580b6a0e09 | 3,625,762 |
import sys
def parse_acc_table(infile):
"""Parsing tab-delim accession table (genome_name<tab>accession)
"""
if infile == '-':
inF = sys.stdin
else:
inF = open(infile)
tbl = []
for line in inF:
line = line.rstrip().split('\t')
tbl.append(line)
return tbl | 568aaeb0d6dd4158b1f6e6c59c709c9996948a69 | 3,625,763 |
def _parse_meme_motif(motif_line, f):
""" Parse the next meme motif from the file.
Parameters
----------
motif_line: string
the motif name line
f: file
the open file, which should be pointing to the line immediately after
the motif name line
Returns
-------
mot... | 79fccbbf07ef31277b8a2e6ecf5da1ea74a81e72 | 3,625,764 |
def get_lambda_cloud_watch_func_name(stackname, asg_name, instanceId):
"""
Generate the name of the cloud watch metrics as a function
of the ASG name and the instance id.
:param stackname:
:param asg_name:
:param instanceId:
:return: str
"""
name = asg_name + '-cwm-' + str(instan... | 893abaf60684cbf9d72774d6f5bb2c4351744290 | 3,625,765 |
def secondary_training_status_changed(current_job_description, prev_job_description):
"""Returns true if training job's secondary status message has changed.
Args:
current_job_description: Current job description, returned from DescribeTrainingJob call.
prev_job_description: Previous job descri... | b1d1a83cccb8cf84fa678345bcf7b3f6531aa2c5 | 3,625,766 |
import requests
def request_movie_info(movie):
"""
Request movie information.
:param movie: A movie object in Model.
:return: Request json or None
:type movie: Movie
"""
url = 'https://api.themoviedb.org/3/movie/' + str(movie.tmdb_id)
query = {
'api_key': TMDB_APIKEY,
... | 1957a09479150d064e3cfc38e402fe6ae4dec16b | 3,625,767 |
from typing import Callable
from typing import Any
from typing import Dict
from typing import Type
def event_source(
handler: Callable[[Any, LambdaContext], Any],
event: Dict[str, Any],
context: LambdaContext,
data_class: Type[DictWrapper],
):
"""Middleware to create an instance of the passed in e... | ddd4f4ab7445f9553b0bb744f3b8d569ebf2b17a | 3,625,768 |
import re
def get_placeholders(arg, check_duplicates=False):
"""
Get all the placeholders' names in order.
Use the regex below to locate all the opening ({{) and closing brackets (}}).
After that, extract "stuff" inside the brackets.
Args:
arg: The word which this function performs search... | 11364e0d897b87d79b588e5ffafe76d429f37f08 | 3,625,769 |
def string_concat(str1, str2):
"""Concatenates two strings."""
return str1 + str2 | 5b6d842fca2d3623d33341d9bba4e4a76ec29e15 | 3,625,770 |
from typing import Optional
def _determine_upstream_ids(
fid: str,
df: pd.DataFrame,
basin_field: str = None,
downstream_field: str = None,
basin_family: Optional[str] = None,
) -> pd.Series:
"""Return a list of upstream features by evaluating the downstream networks.
Parameters
-----... | 6be87a2a838842f8d7e54c8b686084824ef47f62 | 3,625,771 |
import glob
import sys
import os
import stat
def copy_binaries_and_libs(chroot, binarieslist, force_overwrite=0, be_verbose=0, check_libs=1, try_hardlink=1, allow_suid=0, retain_owner=0, try_glob_matching=0, handledfiles=[]):
"""copies a list of executables and their libraries to the chroot"""
if (chroot[-1] == '/'... | 87a5867b18199e71e2a1c27899dc24879e6c33fc | 3,625,772 |
def remove_spaces(input_text, main_rnd_generator=None, settings=None):
"""Removes spaces.
main_rnd_generator argument is listed only for compatibility purposes.
>>> remove_spaces("I love carrots")
'Ilovecarrots'
"""
return input_text.replace(" ", "") | a9ba3bcca4a4ff1610d52271562e053f25815618 | 3,625,773 |
def length_vector(vector):
"""
Calculates the norm of a vector.
"""
return np.linalg.norm(vector) | 029732f7bff27fcda65649378d6b7fc669aea410 | 3,625,774 |
import sys
def get_vrf(arg = None, opts = None, abort = False):
""" Returns VRF to work in
Returns a pynipap.VRF object representing the VRF we are working
in. If there is a VRF set globally, return this. If not, fetch the
VRF named 'arg'. If 'arg' is None, fetch the default_vrf
a... | f52b96af0eece3401e6da3b0478858fa6063e6d1 | 3,625,775 |
def init_calendar():
"""
init calendar.
The calendar initialization function is called to generate
the calendar id when the system starts.
:return: calendar id
"""
calendar_id = create_calendar()
if calendar_id is None:
raise Exception("init calendar failed.")
return calenda... | 0d4fb9c8a1211fb53bc26fa28e0f474a99795232 | 3,625,776 |
def get_db():
"""Opens a new database connection if there is none yet for the
current application context.
"""
#if not hasattr(g, 'sqlite_db'):
#g.sqlite_db = connect_db()
con = connect_db()
#return g.sqlite_db
return con | 1b09d2734a3c62bf6f17f2136924d2fbfb3d7d2c | 3,625,777 |
from typing import List
from typing import Counter
import heapq
def top_k_frequent_pq(nums: List[int], k: int) -> List[int]:
"""Given a list of numbers, return the the top k most frequent numbers.
Solved using priority queue approach.
Example:
nums: [1, 1, 1, 2, 2, 3], k=2
output: [1, 2]... | 4d30bd7e11a087be1a23f9db5c8af7f78c083a5f | 3,625,778 |
from typing import Optional
def get_db_instance(id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDBInstanceResult:
"""
Resource Type definition for AWS::Neptune::DBInstance
"""
__args__ = dict()
__args__['id'] = id
if opts is None:
... | 8267374486c3381fb4fee7fdf7531e0c96799820 | 3,625,779 |
def add(x, y):
"""Add 2 numbers together"""
return x+y | bdf809dee5716058a3df4c56d76ec6d9d2ec97c1 | 3,625,780 |
def create_engine(*args, **kwargs):
"""Create a new Engine instance.
The standard method of specifying the engine is via URL as the
first positional argument, to indicate the appropriate database
dialect and connection arguments, with additional keyword
arguments sent as options to the dialect and ... | 58884afb4cd2ae6179e40395d8942c5b7e451d44 | 3,625,781 |
import os
def init(): # pragma: no cover
# type: () -> AnnotatorConfig
"""Combines passed arguments to create Annotator config."""
parser = create_argparser()
args = parser.parse_args()
config = AnnotatorConfig(args.config, os.environ, vars(args))
return config | fcdedf45114895a564726915d148ffba7d7bbdc2 | 3,625,782 |
def splitData(X, Y=None, train_fraction=0.80):
"""
Split data into training and test data.
Parameters
----------
X : MxN numpy array of data to split
Y : Mx1 numpy array of associated target values
train_fraction : float, fraction of data used for training (default 80%)
Returns
---... | d5ce36bb663f138b924b9ce0173d464a067b2747 | 3,625,783 |
def wrap_cleverhans(model, attack_fn):
"""This should return (newmodel, (x,y,loss)) where newmodel has input connected x
"""
class Dummy(cleverhans.model.Model):
def __init__(self, model):
self.model = model
def predict(self, x):
return self.model(x)
def fpro... | 611999b88eefbe8e6887969e2790ffda4ef292f4 | 3,625,784 |
def monthFormat(month: int) -> str:
"""Formats a (zero-based) month number as a full month name, according to the current locale. For example: monthFormat(0) -> "January"."""
months = [
"January",
"February",
"March",
"April",
"May",
"June",
"July",
... | cb675f547d9beec0751d8252e99b5c025b8fd291 | 3,625,785 |
def test_postponed_resolution_error():
"""
This test checks that an unresolvable scopre provider induces an exception.
This is checked by using a scope provider which always returns a postponed
object.
"""
#################################
# META MODEL DEF
###############################... | c17d67364f3da6b0892cf2fe04c24e329f3d1732 | 3,625,786 |
from datetime import datetime
import decimal
def _jsonEncoder(obj):
""" Encodes C{decimal.Decimal} and C{datetime.datetime} objects. """
if isinstance(obj, datetime.datetime):
obj = datetime_util.convertToIso8601(obj)
elif isinstance(obj, decimal.Decimal):
decimalTuple = obj.as_tuple(... | 5b74cf4edc6a1a9eb30ec9c766329c1050d8b467 | 3,625,787 |
import torch
def optimization_step(A, Y, Z, beta, apply_cg, mode='prox_cg1'):
"""
Optimization step for several different modes:
- 'prox_exact' takes an exact proximal step
- 'prox_cgN' takes an approximate proximal step, generated by N conjugate gradient steps
- 'gradient' performs a ... | 0452c05dcdf2b5c61dc1a721e2b1365eb58acc41 | 3,625,788 |
from medimodule.Liver import LiverSegmentation
from typing import Optional
from typing import Tuple
import os
def AbdomenLiverSegmentation(
task: str,
weight: str,
image_path: str,
save_path: Optional[str] = None,
gpus: str = "-1"
) -> Tuple[np.array, np.array]:
"""
"""
Checker.check_... | 31f11910d993e292f7b5401011ed1931c148c703 | 3,625,789 |
def get_city_country_continent(city, country, continent):
"""Get id of city, country, and continent from database."""
if city is not None:
if City.objects.filter(name=city).count() == 0:
# Create new city object if not already in database
city = City(name=city)
city.s... | e5a3a3d0a68ba42f945f845f3a91d675bf3f84a6 | 3,625,790 |
import pyfits
def wcscopy( donor, recipient, dext=1, rext=1, verbose=False ):
""" Copy the WCS header keywords from the donor
fits file into the header of the recipient fits file.
dext and rext specify the fits extensions to use for
the donor and recipient, respectively.
"""
donfits = pyfits... | 82fd9eae1038f1e01ca51de6a8354f796d61ab9b | 3,625,791 |
from io import StringIO
import tempfile
import os
def PIL_decode_parts(parts):
"""Decode and assemble a bunch of images using PIL."""
tokens = set()
rows = []
max_image_size = options["Tokenizer", "max_image_size"]
for part in parts:
# See 'image_large_size_attribute' above - the provider ... | 516d563694d349ea9cbeaba0824a8b234cf12b7f | 3,625,792 |
def distance2line(line_start, line_end, point):
"""
Calculate distance from a line between the start and end to an arbitary point in space
:param line_start: array, position of the start of the line
:param line_end: array, position of the end of the line
:param point: array, arbitary position in sp... | e3bc1c318ae14f9d4af2db2622cd765217aec469 | 3,625,793 |
def create_linking_info(ctx, user_link_flags, files):
""" Creates CcLinkingInfo for the passed user link options and libraries.
Args:
ctx - rule context
user_link_flags - (list of strings) link optins, provided by user
files - (LibrariesToLink) provider with the library files
"""
... | fa536637dbfe81187f420f6ede32c13ad271521e | 3,625,794 |
def build_fnln_contact(individual_contact):
"""
Expected parameter format for individual_contact
('My Name', 'myname@gmail.com')
Sample output:
{'email': 'myname@gmail.com', 'name': 'My Name'}
"""
return {
"email": individual_contact[-1],
"name": individual_... | 54080191320cfeb425de0f765f10e29726405d0d | 3,625,795 |
def add_usdan_day(day_item):
"""
Unique ID for each day item is the time attr.
Assumes a day_item is in the form:
{
'time': <time>,
'breakfast':<meal_items>,
'lunch':<meal_items>,
'dinner':<meal_items>,
'brunch'...
}y
where <meal_items... | d162ed11accab4beae37db584fd0dbbf4bd7ac45 | 3,625,796 |
import numpy as np
def shortcut( sn ) :
""" For a given snana.SuperNova object sn,
quickly convert the posterior probabilities computed
using the 'mid' class fractions prior into the
posterior probabilities you get when adopting the
'galsnid' prior.
NOTE: we do not account for redshift... | adca461ca14c941e8f6a69193f796b78f5dc25dd | 3,625,797 |
def _create_device_profile(device, pv_type, iprofile_id):
"""Create a profile disk or partition, depending on the physical volume
type."""
device_profile = None
if pv_type == constants.PV_TYPE_DISK:
device_profile = _create_disk_profile(device, iprofile_id)
elif pv_type == constants.PV_T... | a4650905935b30aa1ca454f23eb4b0b4d1eb8b8d | 3,625,798 |
def initialize_with_zeros(dim):
"""
此函数为w创建一个维度为（dim，1）的0向量，并将b初始化为0。
参数：
dim - 我们想要的w矢量的大小（或者这种情况下的参数数量）
返回：
w - 维度为（dim，1）的初始化向量。
b - 初始化的标量（对应于偏差）
"""
w = np.zeros(shape = (dim,1))
b = 0
#使用断言来确保我要的数据是正确的
assert(w.shape == (dim,... | 7fb5dad91abab2f29066fffac8c2640f670c45fc | 3,625,799 |
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