content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def sin_potential2(z):
"""Modified sin potential."""
z = tf.transpose(z)
logterm1 = tf.math.exp(-0.5 * ((z[1] - w1(z)) / 0.4) ** 2)
logterm2 = tf.math.exp(-0.5 * ((z[1] - w1(z) + w3(z)) / 0.35) ** 2)
term3 = 0.1 * tf.math.abs(z[0])
output = -1. * tf.math.log(logterm1 + logterm2) + term3
ret... | 843f4ca43ab2f2e464d8759cae8a1504b32992d8 | 3,598,364 |
def map_crystal_to_sim(CRYS_PDB, SIM_PDB):
"""
Map resid of crystallographic water to resid of corresponding simulation water
"""
crys_molid = molecule.load('pdb', CRYS_PDB)
sim_molid = molecule.load('pdb', SIM_PDB)
# align_crys_to_sim_structures(crys_molid, sim_molid)
# coordinate_selection = "noh and wate... | 23989ed343b23dcc3a38120536bec36b81829206 | 3,598,365 |
def export_estimator_savedmodel(estimator,
export_dir_base,
serving_input_receiver_fn,
assets_extra=None,
as_text=False,
checkpoint_path=None,
... | 161b0773c76550e62643454e932eb6c4755f7b1e | 3,598,366 |
def fetch_w(*, wid):
"""Get all the files on a workspace"""
workspace = Workspace.get_or_404(wid)
if not ReadWorkspacePermission(wid).can():
raise APIException(status=codes.forbidden,
title='Forbidden',
detail='You are not authorized to read met... | 7bb42d77c1d8a9111bcb9c648b1e1c4ed21b5922 | 3,598,367 |
def _extract_lr(labels_in, dat_type):
"""Pull out the L/R information from ROI label.
Parameters
----------
labels_in : list of str
ROI labels.
dat_type : {'anat', 'elec'}
Whether ROI label comes from anat or elec data.
Returns
-------
labels : list of str
Clean... | 0dd503dbc37bab9fec6b389a22b6561f725a6757 | 3,598,368 |
def _parse_raw_day(fragment):
"""
Taking all the info we need from the object
Args:
fragment: 'BeautifulSoup' objects contains day info ('div' with class 'col-md-6')
Returns:
tuple: (str, str, list): Tuple contains date, day and list of the lessons
"""
header = fragment.find_n... | 0b236022889bffc2dbfa9479015dfa1545a2b4c0 | 3,598,369 |
import glob
import platform
def get_targetNames2(target, inputFolder):
"""
-> return the list of center or the list of date
occuring in patient file present in data folder
-> target is a string, could be:
- center
- date
- disease
"""
listOfPatientFiles = glob.glob(str(inputFolder)+"/*.csv")
listOfCente... | 00945dd882fb28ed5b60f0f65371fada64ed45ac | 3,598,370 |
import logging
def list_to_dataframe(file_list):
"""
Convert a list of ctf files, that are named in the the standard format 'year_month_day_hours' to a pandas dataframe
Args:
file_list (list): a list of files
Returns:
pd.DataFrame: Pandas DataFrame containing a list of files
"""
... | c33851e88c6ee6681ca727cbb880416733fcdfc4 | 3,598,372 |
def pull_courses():
"""Retrieve list of JSON objects describing all the courses."""
# return query_endpoint('courses')
return query_endpoint('accounts/1/courses') | aa362dd8888f6fdea33afa4fa60e849aa92ad651 | 3,598,373 |
def ev_annot_freq(bootstrap_rng=None):
"""Compute binned frequencies of event boundary annotations
Parameters
----------
bootstrap_ng : Generator (from numpy.random.default_rng())
If provided, bootstrap resample event annotations
Returns
-------
ndarray
Proportion of raters... | 37d265c751dddbf6dfd3c8bd3780da5a860adb66 | 3,598,374 |
import torch
def collect_samples(
rand_init,
queue,
env,
policy,
custom_reward,
mean_action,
render,
running_state,
min_batch_size,
):
"""Helper function - Collect batch of action and log depends on the batch size
Args:
rand_init: random initialization for reproduc... | 1a7da3a571f7ea7bb2ed739a4ddaaa1f98ee3664 | 3,598,375 |
def frame_id_unpack(frame_id):
"""Unpack given frame id and return a tuple of priority, reserved,
data page, PDU format, PDU specific and source address.
"""
try:
packed = bitstruct.pack('u29', frame_id)
except bitstruct.Error:
raise Error(
'Expected a frame id 0..0x1ff... | 12e860863e6f9036a9bbf050bb2d7c4c1afd0ee1 | 3,598,376 |
import random
import time
import json
def fetch_job_states():
"""
dummy function returning random dictionaries
with job names and job states for the purpose of
simulating the actual long running tasks
:return:
"""
job1 = [{'job_name': 'job1', 'job_state': 'running'},
{'job_name... | d872edb4ada47a59b0137ba45e3a0611ff99b0a8 | 3,598,377 |
from datetime import datetime
def generate_download_signed_url_v4(bucket_name, blob_name, sa_name):
"""Generates a v4 signed URL for downloading a blob.
Note that this method requires a service account key file. You can not use
this if you are using Application Default Credentials from Google Compute
... | b742354de82ffe266ced5555b23c582031411373 | 3,598,378 |
import tokenize
def simple_lesk(gloss: str, word: str):
"""":returns the sense most suited to the given word as per the Simple LESK Algorithm"""
# converting everything to lowercase
gloss = gloss.lower()
word = word.lower()
# obtaining tokens from the gloss
gloss_tokens = tokenize(gloss, wor... | 3fc717c83f0293d077392294fbed2a3e4aba0c42 | 3,598,379 |
from typing import Optional
def check_change_full_name(
user_profile: UserProfile, full_name_raw: str, acting_user: Optional[UserProfile]
) -> str:
"""Verifies that the user's proposed full name is valid. The caller
is responsible for checking check permissions. Returns the new
full name, which may ... | c1806233263024d8c6b18e079829e2ee0c0005c4 | 3,598,380 |
def get_course_exam_all(course_id, prev_years=False):
""" Return a summary of information about all current exams in the course
{id, course, name, description, start, duration, end, type}
"""
assert isinstance(course_id, int)
assert isinstance(prev_years, bool)
if prev_years:
key = "... | b9822bbd4e060d1eae7ea72a98053e526d023d8c | 3,598,381 |
import jinja2
def render_template(template_file, template_vars, searchpath="./templates/"):
"""
Render a jinja2 template
"""
templateLoader = jinja2.FileSystemLoader(searchpath=searchpath)
template_env = jinja2.Environment(loader=templateLoader)
template = template_env.get_template(template_fi... | d15f5d6e120a22ee5735dbf5b1f8c324a5cae861 | 3,598,382 |
def getAxes():
""" Get each of the axes over which the data is measured. """
df = load_file("atyeo_covid")
df = df.filter(regex='SampleID|Ig|Fc|SNA|RCA', axis=1)
axes = df.filter(regex='Ig|Fc|SNA|RCA', axis=1)
axes = axes.columns.str.split(" ", expand = True)
subject = df['SampleID']
subje... | 5e2abcbd7458978378faa5865268c5721afd4645 | 3,598,383 |
def summarize_power(power_summary, sim_num, test, colors):
"""Generates a dataframe describing a power calculation run
Please note, this function is primarily designed for use with the
simulation notebooks.
Parameters
----------
power_summary : dict
A dictionary summarizing the power s... | 46c5d051193d2c87d1a1301f8c06217b5c33551e | 3,598,384 |
def head(r, t, h0, Q, delz, K, S):
"""
Compute the head around a pumping well according to the THEIS model.
Source: SHEMAT-Book Clauser2003, section 2.6.1, p.57.
Parameters
----------
r : float
Distance from well [m]
t : float
time [s]
h0 : float
Undisturbed he... | 7409211ddff0905ce4b07cad2176ef87609e4aee | 3,598,385 |
def pagerank_weighted(graph, damping=0.85):
"""Get dictionary of `graph` nodes and its ranks.
Parameters
----------
graph : :class:`~gensim.summarization.graph.Graph`
Given graph.
damping : float
Damping parameter, optional
Returns
-------
dict
Nodes of `graph` ... | 4a6ee1c6ea3c402e84b5a3e246a66ff004e96aab | 3,598,387 |
def crate_data_for_linear_regression_weighted(initial_proj_nodes, dict_intial_projections, dict_enode_enode_in,
dict_enode_enode_out, dim, G):
"""
In order to find the best parameters to calculate a node's vector, we perform linear regression. In this function
w... | 8858589d1f8a6eea6d9036126d83b4b3ea1e6f90 | 3,598,388 |
from typing import Any
from typing import List
def search_commands(*args: Any) -> List[Any]:
"""Pass find_commands function from C."""
return actually_calls(args, find_commands) | f8471e6160ba2cd37f2ae99240f4db7f00a9bb86 | 3,598,389 |
def subtract(x, y):
"""Subtract two objects and return the result
>>> from methods import subtract
>>> subtract(2, 1)
1
"""
return x - y | 00fd9bff041879b372ab7b0d8aa536e3aecb8378 | 3,598,390 |
def query_for_user(user):
"""Queries for information about user from the database.
:param user: Object User to query for.
:return: Data about the user.
"""
database = connect_to_cloudsql()
cursor = database.cursor()
cursor.execute("SELECT * FROM Users WHERE username='" + user.username + "'"... | 4b17b111efd9e4bc230fbcd9ff22637ce014b1f1 | 3,598,391 |
def RunDistributed(module_name,
package_root,
num_ps,
num_workers,
start_port,
user_args=None):
"""Create a cluster configuration and start processes for the cluster.
Args:
module_name: str. Python module to use as t... | edab626aa6b09a1bb039da2d3db051e9d578859d | 3,598,392 |
from operator import add
from operator import concat
def normalA(x, p, filters, scope=None):
"""Normal cell for NASNet-A (Fig. 4 in the paper)"""
p = adjust(p, x, filters)
h = relu(x)
h = conv(h, filters, 1, scope='1x1')
x1 = add(sconv(h, filters, 3, scope='left1'), h, name='add1')
x2 = add(... | 23908563b584db0fa66b4b24da3f050c2be45406 | 3,598,394 |
def DEFAULT_THRESHOLDING(phenotype):
"""
Threshold function for a phenotype
for each gene, >0 becomes 1 and <0 becomes -1
"""
# verification, sign declaration, return thresholded phenotype
assert(phenotype.shape == (DEFAULT_GENE_NUMBER, 1))
def sign(x): return (1 if x > 0 else (-1 if x < 0 e... | bca278e17c96668f260fbfad004619c24881f5f0 | 3,598,395 |
def dict_sort(dictionary: dict) -> list:
"""Takes in a dictionary with integer values and outputs a list of the keys sorted by their associated values in descending order."""
return list(reversed(sorted(dictionary, key=dictionary.__getitem__))) | 330e6033a9e511341e5d9216a385b366a09eed9c | 3,598,396 |
import re
def get_citation_form(attributes):
""" Compute the citation form of a pronominal mention.
Args:
attributes (dict(str, object)): Attributes of the mention, must contain
the key "tokens".
Returns:
str: The citation form of the pronoun, one of "i", "you", "he", "she",
... | 2e02063ae0694e7ce76e3be8ce111d9550de7697 | 3,598,397 |
def SINH(df):
"""
函数名：SINH
名称：双曲正弦函数，三角函数
python API
real=SINH(close)
:return:
"""
close = df['close']
return talib.SINH(close) | b40dd33fd7a41f5219dfb84631695435da4241a6 | 3,598,398 |
def completion_formatter_factory(subsec_precision=2):
"""
Formatter factory
Parameters
----------
subsec_precision : int (Default : 2)
The number of decimal digits for the second in the time formatting
Return
------
:func:`completion_formatter`
"""
def completion_format... | 91d3c28e59f78a5addf04247d35d2bd84dfefef9 | 3,598,399 |
def _design_knockoff_equi(exog):
"""
Construct an equivariant design matrix for knockoff analysis.
Follows the 'equi-correlated knockoff approach of equation 2.4 in
Barber and Candes.
Constructs a pair of design matrices exogs, exogn such that exogs
is a scaled/centered version of the input ma... | 149252ad76664ded9f3ed344d54b8026ac3e4da0 | 3,598,400 |
def parse_int(value) -> int:
"""
this function is used to parse data from the DB into an integer.
because a lot of the cells can be empty, we get None as the return type. This function makes sure we
get 0 if the value is None or empty
!!! IMPORTANT !!!
This is to be added to values where we wou... | 066e0a93436697bb31b91743faf851a752dd0e87 | 3,598,401 |
def converted_size(path, estimate=False):
"""Get size of converted raw image.
The size of image converted to raw format can be growing up to the virtual
size of the image.
:param path: path to the image file.
:param estimate: Whether to estimate the size by scaling the
original size
:r... | 0357c63dc64d25dff71f970227946b480f52df6a | 3,598,403 |
def asap(handlers, *, body, **kwargs):
""" Execute one handler at a time, skip on failure, try the next one, retry after the full cycle. """
retryfn = lambda handler: get_retry_count(body=body, handler=handler)
return sorted(handlers, key=retryfn)[:1] | 82d956b0527ee5796669c9ec7a04cfc7a3feaba7 | 3,598,405 |
def distance_by_lowtemp():
"""
"""
q = text(
"""
select date(start_date) as start_date,
avg(W.day_temp_min) as low_temp,
sum(R.distance) as distance
from rides R join ride_weather W on W.ride_id = R.id
group by date(start_date)
... | 483bf254a4948709a834a2351d048d43a4ad0aaf | 3,598,406 |
def bitpos_from_mask(mask, lsb_pos=0, increment=1):
"""
Turn a decimal value (bitmask) into a list of indices where each
index value corresponds to the bit position of a bit that was set (1)
in the mask. What numbers are assigned to the bit positions is controlled
by lsb_pos and increment, as explai... | d7938258c0f2dc523720bc82a48ecba1c2342223 | 3,598,407 |
def cli_arguments():
"""Retrieve all CLI arguments provided by user."""
# First of all, we need to specify all command line flags that are
# recognized by this tool.
parser = ArgumentParser()
parser.add_argument(
"-c",
"--count",
dest="count",
default... | c2b5a1da7b1a23ef9edd47cbb904909b39ef6c63 | 3,598,408 |
def moving_average(list):
"""
list의 평균을 return한다.
input:
list
return:
average(float)
"""
mysum = 0
for i in range(0, len(list)):
mysum = mysum + list[i]
return mysum / len(list) | d5602113e74a7ef0f0027ec5f6964b72680c3499 | 3,598,409 |
def pixelwise_predictor(feat,
nc=3,
n_layers=1,
n_layerwise_steps=0,
skip_feat=None,
reuse=False,
is_training=True):
"""Predicts texture images and probilistic masks.
Args... | a700668bb7f513fc0ee59c5da2e656346ef8fb98 | 3,598,411 |
def _data_aug_fn(image, ground_truth, hin, win, hout, wout, hnei, wnei, parts, limbs, data_format="channels_first"):
"""Data augmentation function."""
#restore data
ground_truth = cPickle.loads(ground_truth.numpy())
image=image.numpy()
annos = ground_truth["kpt"]
mask = ground_truth["mask"]
... | 98f587ce6282ebcaf999a0945286ffc71b187c20 | 3,598,412 |
import numpy
def _rolling_ball(tile, ball_radius: int, light_background: bool):
""" Applies the rolling-ball algorithm to a single tile.
Args:
tile: A tile, usually from an ome.tif file.
ball_radius: The radius of the ball to use for calculating the background.
light_background: Wheth... | e629d51b6607c0113cc27427775a72449cad0f39 | 3,598,413 |
def quality_threshold(sample, cutoff=5, PBC=False, net_height=0, net_width=0):
""" Run the complete clustering algorithm in one go and returns the clustered indices as a list.
Args:
sample (array): The input dataset
cutoff (float, optional): The clustering cutoff distance.
... | bc9fd5def494431e6e58ecf2cfb9ea5691bffa14 | 3,598,414 |
def setup_metadata_controller():
""" Load metadata controller based on spell_type
"""
if app.metadata.spell_type == consts.spell_types.SNAP:
return _setup_snap_metadata_controller()
# This is the typical default for now
return _setup_juju_metadata_controller() | 59757cade58bd4134106a908272cbf1822d76933 | 3,598,415 |
from datetime import datetime
def create_question(question_text, days):
"""
Creates a question with the given 'question_text' and published the
given number of 'days' offset to now (negative for questions published
in the past, positive for questions that have yet to be published).
"""
time = timezone.now() + d... | c541eb40f68eb9dd3b54eb1d8f96bc84f8a79269 | 3,598,416 |
def url_compose(camera):
""" Compose URL string for the camera """
# rtsp://88.204.57.242:5533/user=admin&password=******&channel=1&stream=1.sdp?
url: str = f'rtsp://{camera.ip_addr}:{camera.port}/user={camera.login}&password={camera.password}&channel=1&stream=0.sdp?'
return url | 62bf81b993e95a4c5ed7ca8362220cf16102c877 | 3,598,417 |
def pt2gen(t_arr, K, T, y0 = 0):
""" generate y(t) of PT2 for t in t_arr
Args:
t_arr (list(float)): time array
K (float): gain
T (float): time-constant
Returns:
list(float): y(t) for t in t_arr
"""
return [pt2(t, K, T) + y0 for t in t_arr] | ae29779f491669f5f56dbafb209da6b1664014bc | 3,598,418 |
def _select_deep(v, field, depth, record):
"""
field = {"name":name, "value":["attribute", "path"]}
r[field.name]=v[field.value], BUT WE MUST DEAL WITH POSSIBLE LIST IN field.value PATH
"""
if hasattr(field.value, "__call__"):
try:
record[field.name] = field.value(wrap(v))
... | 27580452cd7d5e17172d817a8f1a407518c00fda | 3,598,419 |
def filter_constant(vars):
"""Create T/F index for data with variance vars, F if variance constant.
"""
return vars != 0 | 57da83f60c42445903e8fd1442c60f7fd4e16bc6 | 3,598,420 |
import logging
def _project_duals_op_for_layer(layer, dual_var_list):
"""Returns op that updates duals for a single layer."""
# Dual variable may not be required.
if layer.dual_shape() is None:
project_op = tf.no_op()
else:
try:
project_op = layer.project_duals_op(dual_var_list[-1])
except (... | bfb3e11dd5caf6128f4f24d8e93678b4bed3f71c | 3,598,421 |
def recent_blog_posts(author=None, limit=10, offset=0, asc=False, before=None):
"""
Get user's recent posts/recommendations
"""
if author and isinstance(author, (int, long)):
author = User(author)
if author and author.id != env.user.id:
if author.get_profile('private') and not autho... | 4a70c3be2ddd03c3550645b1ed00ddaa6550ead3 | 3,598,423 |
def optimal_amiRNA(dna_sequence):
"""
Id any seqs of 21 nt with T at nucleotide 1 and A or T at nucleotide 10
Input is the target (not the complement)
optimal_RNAs --> [(amiRNA,*amiRNA)]
"""
dna_sequence.upper()
dna_sequence = complement(dna_sequence)
pos = 0
optimal_amiRNAs=[]
... | f900b92f96108e37e82f09e220631feeba480ace | 3,598,425 |
import functools
def input_function(is_train, embeddings):
"""An input function satisfying the tf.estimator API."""
# A dataset with keys `question`, `context`, `answer_start`, and `answer_end`.
dataset = nq_long_dataset.get_dataset(is_train)
dataset = dataset.map(
functools.partial(
preproce... | 6ebb0fdfd3e54c6a142aff2373785e43b3315dfd | 3,598,426 |
def calculate_proportion_dict(data, relevant_keys, percent=False, floor=0., underscore=True):
"""
General method to calculate proportions from absolute values provided as dictionaries.
Args:
data: Dictionary containing the absolute values
relevant_keys: The keys of data from which proportio... | 0c11cdb2d5efa73ee9bb8fa4e05cd55e0e3197cd | 3,598,427 |
from plyfile import PlyData, PlyElement
def loadCloudPLY(path):
"""
Loads a PLY file from the specified path.
"""
try:
except:
assert False, "Please install plyfile (pip install plyfile) to load PLY."
# look for/load header file if one exists
header, data = matchHeader(path)
... | c0460843d8efdfc8eeb00526e900a150a2e23985 | 3,598,428 |
def GetClientIdFlag():
"""Anthos auth token client-id flag, specifies the ClientID is the id for OIDC client application."""
return base.Argument(
'--client-id',
required=False,
help='ClientID is the id for OIDC client application.') | 019f23808cdc20a25775ca5d4516ec6a9b4ecf3d | 3,598,429 |
def get_first_package_name(name):
"""
Returns first package name.
From `a.b.c` it returns `a`.
:param str name: Full module name
:return: First package name.
:rtype: str
"""
return name.split(".")[0] | 814b175356ef715af46f788dc9eac7e776884b30 | 3,598,430 |
def get_schlagworte_sorted(schlagworte):
""" uebersetzt die gestemmten Schlagwoerter in die ursruenglichen Schlagwoerter """
items = []
for schlagwort in schlagworte.all():
items.append(get_schlagwort_by_stem(schlagwort))
items.sort()
return items | a8df8e52821689aec70da56b258dcc299dc8a7f0 | 3,598,431 |
def _parse_url_work_relation(response):
""" response is
{'resource': 'https://imslp.org/wiki/7_Bagatelles,_Op.33_(Beethoven,_Ludwig_van)',
'relations': [{'source-credit': '',
'target-credit': '',
'type-id': '0cc8527e-ea40-40dd-b144-3b7588e759bf',
'type': 'download for free',
'end': None,
'direct... | 4e36330be029846bc44c235dafb20e6dc9c5f58f | 3,598,432 |
def run():
"""Entrypoint function."""
logger.info("Scheduled scan for newer versions started")
print("Scheduled scan for newer versions started")
read_packages()
get_repos()
get_version_data(REPO_DATA, PACKAGE_DATA, NEW_VERSION_DATA, VERSION_DATA)
get_version_data(REPO_DATA, TRANSITIVE_PACKA... | b24a69ef0609ba08ed5b52d204eaafdf73b62034 | 3,598,433 |
def get_edge_mask(poly, mask):
"""
Generate edge mask
"""
cv2.polylines(mask, [poly], True, [1])
return mask | 481b91c8ea289df2cd388a93299e6cc94d6ef384 | 3,598,434 |
def merge_dicts(dict_args):
"""
Given any number of dicts, shallow copy and merge into a new dict,
precedence goes to key value pairs in latter dicts.
"""
result = {}
for dictionary in dict_args:
result.update(dictionary)
return result | bdd006b0a9ba641d1608bbf793953610de06f04c | 3,598,435 |
def _checkXmlStructure(data):
"""
@summary: checks the structure of the xml to check if it is valid xml
@param data: can be an xml string
"""
try:
d = minidom.parseString(data)
d = str(d.toxml())
return None
except Exception as e:
return str(e) | 0462e375a3e45cc4da3ba9cc6e41597e7477587c | 3,598,436 |
import urllib
def embed_mp3(music_file, meta_tags):
"""Embed metadata to MP3 files."""
# EasyID3 is fun to use ;)
audiofile = EasyID3(music_file)
audiofile['artist'] = meta_tags['artists'][0]['name']
audiofile['albumartist'] = meta_tags['artists'][0]['name']
audiofile['album'] = meta_tags['alb... | 76e8f9643ebdc9f7a90d0d78fc4a9987b82d5f19 | 3,598,437 |
def isint(value):
""" To check if any variable can be converted to integer """
try:
int(value)
return True
except ValueError:
return False | 9c8b3e4abe11e8c23fb6d28b92637ec885093f28 | 3,598,438 |
def test_np_print_2():
"""
Feature: JIT Fallback
Description: Support print.
Expectation: No exception.
"""
class PrintNet(nn.Cell):
def construct(self):
x = np.array([1, 2, 3, 4, 5])
print("x: ", x)
return Tensor(x)
net = PrintNet()
res = net... | 075d70848ece95d314167014d0730b12f9967996 | 3,598,440 |
def hkcancor_to_ud(tag: str = None):
"""Map a part-of-speech tag from HKCanCor to Universal Dependencies.
HKCanCor uses a part-of-speech tagset of over 100 tags (46 of which
are described at http://compling.hss.ntu.edu.sg/hkcancor/).
For applications that would benefit from a less granular part-of-spee... | 56624cb18f6684f317f7caaa04f884bdf149282b | 3,598,441 |
def to_array(x):
"""Convert the input to a numpy array"""
if isinstance(x, pd.Series):
return x.values
return np.asarray(x) | 77196a44a6580ebbfc1667c46c4edc8e9525c365 | 3,598,442 |
def example_two_by_two_data():
"""load santa clara data to test two by two ei and plots"""
sc_data = data.Datasets.Santa_Clara.to_dataframe()
group_fractions = np.array(sc_data["pct_e_asian_vote"])
votes_fractions = np.array(sc_data["pct_for_hardy2"])
precinct_pops = np.array(sc_data["total2"])
... | 33d99d6b3804b77eab1486347d9f84943899f462 | 3,598,443 |
def is_russian(token):
"""
Returns true if the token contains only russian characters or punctuation, otherwise false.
"""
return any([c in RUS_ALPHABET_SET for c in token]) | db880efa5de5a028c220ea075c925c02244099e9 | 3,598,445 |
def check(client: Client, args: Namespace) -> bool:
"""Checks whether the specified conditions are met."""
stats = client.stats(full=True)
if args.max_players is not None and stats.num_players > args.may_players:
return False
if args.min_players is not None and stats.num_players < args.min_pl... | c129a5023359e5461cd214b0c713603bc8c066c6 | 3,598,446 |
def get_languages(*args, **kwargs):
"""
Wraps tesserocr.get_languages() with a fixed path parameter.
"""
return get_languages_(*args, path=get_tessdata_path(), **kwargs) | 077903b485d112b0de09fe959398fa57f87975c4 | 3,598,447 |
def adjust_contrast_log(arr, gain):
"""
Adjust image contrast by scaling pixels to ``255*gain*log_2(1+v/255)``.
Supported dtypes
----------------
* ``uint8``: yes; fully tested (1) (2) (3)
* ``uint16``: yes; tested (2) (3)
* ``uint32``: no; tested (2) (3) (8)
* ``uint64... | 5fd52969c2c2222f9d9ae20f2a2c42fcefe6582e | 3,598,448 |
def largest_odd_factor(var_arr):
"""
Function that computes the larges odd factors of an array of integers
Parameters
-----------------
var_arr: numpy.array
Array of integers whose largest odd factors needs to be computed
Returns
------------
odd_d: numpy.array
Array of... | 408e94c6223dec5e529d69181a8f187b017fe5b6 | 3,598,449 |
def update_step(loss, config, clip_gradient=1., scope='optimizer'):
"""Computation of gradients and application of weight updates
Optimizer can be supplied via config file, e.g. as
"optimizer_params": {"learning_rate": 1e-3},
"optimizer": "'AdamOptimizer'"
Parameters
-------
loss : tensor
... | 797d90163efc1ea21f8f7526a7ff022d4bcabff6 | 3,598,450 |
def set_ecr_repository_tags(ecr_repository_arn, resource_tags):
"""Applies a list of passed resource tags to the AWS ECR repository.
Args:
ecr_repository_arn: ECR repository identifier/ARN
resource_tags: a list of key:string,value:string resource tag dictionaries
Returns:
Returns T... | 3c49d7d1871ff46f84b64488329270da0f9d1445 | 3,598,452 |
import base64
import gzip
def decode_base64_gzip_to_bytes(base64_gzip_data: str) -> bytes:
"""Decode Base64 GZIP into bytes."""
with BytesIO() as compressed_file:
compressed_file.write(base64.b64decode(base64_gzip_data))
compressed_file.seek(0)
with gzip.GzipFile(fileobj=compressed_fi... | a06b315281c1aae8e87e2d6bc5c403929012b534 | 3,598,453 |
import logging
def download_script(script):
"""Download a script"""
logging.info('[ROUTER]: Download script '+script)
try:
script = ScriptService.get_script(script, current_identity)
return send_from_directory(directory=SETTINGS.get('SCRIPTS_FS'), filename=script.slug + '.tar.gz')
exce... | 345097cda32d80863771485c5045f3f7b9544ad3 | 3,598,454 |
import toml
import yaml
import json
def mock_settings_file(request, monkeypatch, tmpdir, file_extension):
"""Temporarily write a settings file and return the filepath and the expected settings outcome."""
ext = file_extension
p = tmpdir.mkdir("sub").join("settings" + ext)
expected_result = {"testgrou... | 4899ebbc9efbe31a931387d4a09dcb8c727eaf8d | 3,598,456 |
def MathSolution(N):
"""Use sum of squares formula and sum of integers formula for O(1) solution"""
sumOfSquares = N * (N+1) * (2*N + 1) // 6
squareOfSum = pow((N + 1) * N // 2, 2)
diff = squareOfSum - sumOfSquares
print("Math solution: ", diff)
return diff | d30046150d95c3217bc446fc3c8e5f3a985f6c51 | 3,598,458 |
from typing import List
def extract_urls_with_indices(text: str, extract_urls_without_protocol: bool = True) -> List[dict]:
"""
Extract valid URLs present in ``text`` along with their Unicode code point indices.
>>> extract_urls_with_indices('http://twitter.com/これは日本語です。example.com中国語')
[
{
... | 1cc646a678a82512fed3cf984c698dffae8e1752 | 3,598,459 |
def error_handler(func):
"""Contain handler for json and error exception. Accept only one value (not tuple) and should be a dict/list
Arguments:
func {[type]} -- [description]
Returns:
[type] -- [description]
"""
@wraps(func)
def wrapper(*args, **kwargs):
try:
... | 4d3dae44f42d31abc722104e8130132330ce00f1 | 3,598,460 |
import re
def searchWalmart(query):
"""
The searchWalmart function scrapes walmart.com
Parameters: query- search query for the product,
currency- currency type entered by the user
Returns a list of items available on walmart.com that match the product entered by the user
"""
qu... | 01180517570d5ef7abc1b937cc3b1077bf22fed1 | 3,598,461 |
def get_months_range(start_date, end_date, keep_day=False):
"""
Returns a list of all months that are within start_date and end_date.
Useful when we need to fill up missing months in a QuerySet where there
were no results in that month and fill up those months with the value `0`.
"""
start_date ... | ac755beb085b8d696471bf316b1fe8d4479946e8 | 3,598,462 |
def integrator_interval(x, k):
"""
Compute the interval of an integrator system: dx = -k*x
:param x: state interval
:param k: gain interval, must be positive
:return: interval for dx
"""
if x[0] >= 0:
interval_gain = np.flip(-k, 0)
elif x[1] <= 0:
interval_gain = -k
... | 0f6c3667ffff4e78d777a0b6e2220713ad0623e6 | 3,598,463 |
import requests
def get_page(link):
"""
this thing takes a link and shoves back some html shit
"""
r = requests.get(link)
r.raise_for_status()
return r.content | 913b96c8670e7d91da92aa00d53582d7eae33dbe | 3,598,464 |
from typing import Iterable
def _build_correction_str(iterator: Iterable) -> str:
""" Creates madx commands (assignments) to run for correction"""
last_type = ''
text = ''
for corr in iterator:
if not _types_almost_equal(corr.type, last_type):
text += f"\n!! {_nice_type(corr.type)}... | d460d1e265619235a71b815b98d8ac4d1200bbbd | 3,598,465 |
def _start_daemon_and_get_client(wallet_name):
"""
Starts a daemon and create a client
"""
electrum_dir = _create_electrum_dir()
# check if running already
process_name = j.sal.process.getProcessByPort(RPC_PORT)
if process_name and 'electrum' in process_name:
print("Electrum daemon i... | 1e3005adb5f554363dba97101a649d9005548d2c | 3,598,467 |
from typing import Union
from typing import Tuple
def nonzero(x: Union[ivy.Array, ivy.NativeArray]) -> Tuple[ivy.Array]:
"""Returns the indices of the array elements which are non-zero.
Parameters
----------
x
input array. Must have a positive rank. If `x` is zero-dimensional, the function
... | 627780d21c18c9a3c862341428202dd1587b60af | 3,598,468 |
import signal
import asyncio
def cli_coro(
signals=(signal.SIGHUP, signal.SIGTERM, signal.SIGINT),
shutdown_func=None,
):
"""Decorator function that allows defining coroutines with click."""
def decorator_cli_coro(f):
@wraps(f)
def wrapper(*args, **kwargs):
loop = asyncio.... | b79b07071bd4c751805ced879fe354c5a45c78eb | 3,598,470 |
def replicate_idx(head):
"""Return a list of indices representing replicate groups"""
h = head
g = h.groupby(['Sample Name', 'Measurement day'])
idx = [i[1].index for i in g]
return(idx) | ac5b80de8d15ef283185b0e93d495516695aa936 | 3,598,471 |
def get_plugin_instance(api_client, id, *args, **kwargs): # noqa: E501
"""get_plugin_instance # noqa: E501
Get running plugin instance # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> response = await api.... | ca74093c8fc963a7555a570b18b15f1bf7190ac0 | 3,598,472 |
def str2ascii(string: str) -> list:
"""Convert a string to a list of ascii-codes"""
return [ord(i) for i in string] | a938b0c585e78a455721e9d17e8915b0769a025f | 3,598,473 |
def rgbToHexColor(r, g, b):
"""Convert r, g, b to #RRGGBB."""
return f'#{int(r):02X}{int(g):02X}{int(b):02X}' | 5cff9abc67c235a4f0fdf258ea555f018d80d1ad | 3,598,474 |
import pathlib
def within_dev_env():
""" detect whether we are within an ASMR dev environment. """
return pathlib.Path('/.ASMR_DEV_ENV').exists() | 86430b29846435b03460b2676d41cea0ba4063e4 | 3,598,475 |
def numeric_to_traj(vals, trajname, coordnames, indepvar=None, indepvarname='t',
indepdomain=None, all_types_float=True, discrete=True,
event_times=None, event_vals=None):
"""Utility function to convert one or more numeric type to a Trajectory.
Option to make the trajecto... | 7241d75179a923873fe9439fd08bc068a4dee262 | 3,598,476 |
def find_nearest(array, value):
"""Gets the nearest element of array to a value."""
array = np.asarray(array)
idx = np.nanargmin((np.abs(array - value)))
return array[idx] | 6b216d10c85a4f9b378f807d42cc3507814fac6e | 3,598,477 |
def red(url):
"""Redirects user from short_url to long_url
:Parameters:
- 'url': Short URL used to query for and redirect to long URL
On GET: Grabs URL Mapping from database and routes accordinly
"""
if request.method == 'GET':
url_map = URLMap.query.filter_by(short_url=url).first()
... | 75da6d78bfd754b1a3c8779e40b960fb903252c3 | 3,598,478 |
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