content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def map_vocabulary(docs, vocabulary):
"""
Maps sentencs and labels to vectors based on a vocabulary.
"""
mapped = np.array([[vocabulary[word] for word in doc] for doc in docs])
return mapped | b5b39aeac6306709a4b4ac10a29d40a2006d57ff | 3,638,331 |
def mobilenetv3_large_minimal_100(pretrained=False, **kwargs):
""" MobileNet V3 Large (Minimalistic) 1.0 """
# NOTE for train set drop_rate=0.2
model = _gen_mobilenet_v3('mobilenetv3_large_minimal_100', 1.0, pretrained=pretrained, **kwargs)
return model | 717a67b1ab7cb0ad7a6c8d40ea4b0b29108eff94 | 3,638,332 |
def get_identity(user, identity_uuid):
"""
Given the (request) user and an identity uuid,
return None or an Active Identity
"""
try:
identity_list = get_identity_list(user)
if not identity_list:
raise CoreIdentity.DoesNotExist(
"No identities found for use... | 800e47d8782fc5e71e97192f76713032eade9441 | 3,638,333 |
def same_strange_looking_function(param1, callback_fn):
"""
This function is documented, but the function is identical to some_strange_looking_function
and should result in the same hash
"""
tail = param1[-1]
# return the callback value from the tail of param whatever that is
return callback... | 438becf6803e6b25a200a34e18eb648aaa4b6fbb | 3,638,334 |
def __extractFunction(text, jsDoc, classConstructor):
"""
Extracts a function depending of its pattern:
'function declaration':
function <name>(<parameters>) {
<realization>
}[;]
'named function expression':
<variable> = function <name>(<... | 992604ccd1e56da6706cf2e4ec2955c2c9ecfa7e | 3,638,336 |
def vocabulary_size(tokens):
"""Returns the vocabulary size count defined as the number of alphabetic
characters as defined by the Python str.isalpha method. This is a
case-sensitive count. `tokens` is a list of token strings."""
vocab_list = set(token for token in tokens if token.isalpha())
return ... | 5e26e1be98a3e82737277458758f0fd65a64fe8f | 3,638,337 |
from typing import Dict
from typing import Any
from typing import Optional
from typing import Tuple
def max_iteration_for_analysis(query: Dict[str, Any],
db: cosem_db.MongoCosemDB,
check_evals_complete: bool = False,
conv_it:... | b5d0bebd2af634ac72f8bc318276d0f7c03114f2 | 3,638,338 |
def getMatirces(Dynamics, Cost):
"""
This functions takes the dynamics class as input and outputs the required
matrices and cvxpy.variables to turn the covariance steering problem into a
finite dimensional optimization problem.
"""
Alist = Dynamics.Alist
Blist = Dynamics.Blist
Dlist = Dy... | 50de11ba3f3d1528f7ff577861613b96f8e35254 | 3,638,339 |
def get_transit_boundary_indices(time, transit_size):
""" Determines transit boundaries from sorted time of transit cut out
:param time (1D np.array) sorted times of transit cut out
:param transit_size (float) size of the transit crop window in days
:returns tuple:
[0... | cd3775d72690eb4539e0434b0ac7f715d14374a6 | 3,638,340 |
def decode_gbe_string(s):
"""This helper function turns gbe output strings into dataframes"""
columns, df = s.replace('","',';').replace('"','').split('\n')
df = pd.DataFrame([column.split(',') for column in df.split(';')][:-1]).transpose().ffill().iloc[:-1]
df.columns = [c.replace('tr_','') for c in co... | 0a2d262b2653f736ef8ae7c7ed4b969faf80e9bf | 3,638,342 |
import re
def get_scihub_namespaces(xml):
"""Take an xml string and return a dict of namespace prefixes to
namespaces mapping."""
nss = {}
matches = re.findall(r'\s+xmlns:?(\w*?)\s*=\s*[\'"](.*?)[\'"]', xml.decode('utf-8'))
for match in matches:
prefix = match[0]; ns = match[1]
... | b1d5a32d7583a655c59fa5175bdd133899bf6223 | 3,638,343 |
def valid_verify_email(form, email):
"""
Returns true if "email" is equal the first email
"""
try:
if(form.email.data!=form.email_verify.data):
raise ValidationError('Email address is not the same')
if models.Account.pull_by_email(form.email.data) is not None:
pri... | 16073bb559e06759632323289f49e127bb9f8cb1 | 3,638,344 |
def _computePolyVal(poly, value):
"""
Evaluates a polynomial at a specific value.
:param poly: a list of polynomial coefficients, (first item = highest degree to last item = constant term).
:param value: number used to evaluate poly
:return: a number, the evaluation of poly with value
"""
#return numpy.polyval... | 0377ba0757439409824b89b207485a99f804cb41 | 3,638,345 |
from io import StringIO
def fix_e26(source):
"""Format block comments."""
if '#' not in source:
# Optimization.
return source
string_line_numbers = multiline_string_lines(source,
include_docstrings=True)
fixed_lines = []
sio = Strin... | ec569e442c2244421afa94cc8316478c55377220 | 3,638,346 |
def graph_distance(tree, node1, node2=None):
""" Return shortest distance from node1 to node2,
or just update all node.distance shortest to node1 """
for node in tree.nodes():
node.distance = inf
node.back = None # node backwards towards node1
fringe = Queue([node1])
while fri... | 0764d2a687933631d592e1b6d40ceec8d629036c | 3,638,347 |
def trunicos(b):
"""Return a unit-distance embedding of the truncated icosahedron graph."""
p0 = star_radius(5)*root(1,20,1)
p1 = p0 + root(1,20,1)
p2 = mpc(b, 0.5)
p3 = cu(p2, p1)
p4 = cu(p3, p1*root(1,5,-1))
p5 = cu(p4, p2*root(1,5,-1))
return (symmetrise((p0, p1, p2, p3, p4, p5), "D5"... | 018112497882a6f0a572cf2c1c222cdf36ca95e9 | 3,638,348 |
import torch
def histogram2d(
x1: torch.Tensor, x2: torch.Tensor, bins: torch.Tensor, bandwidth: torch.Tensor, epsilon: float = 1e-10
) -> torch.Tensor:
"""Function that estimates the 2d histogram of the input tensor.
The calculation uses kernel density estimation which requires a bandwidth (smoothing) p... | 5e360f1e9350a29664e3beb1d0cc6ba3024647b9 | 3,638,349 |
import json
def webhooks_v2(request):
"""
Handles all known webhooks from stripe, and calls signals.
Plug in as you need.
"""
if request.method != "POST":
return HttpResponse("Invalid Request.", status=400)
event_json = json.loads(request.body)
event_key = event_json['type'].repla... | afa86e189c417a147ae05fa46e89d985207c403b | 3,638,350 |
def nth(iterable, n, default=None):
"""
Returns the nth item or a default value
:param iterable: The iterable to retrieve the item from
:param n: index of the item to retrieve. Must be >= 0
:param default: the value to return if the index isn't valid
:return: the nth item, or the default value i... | 9f0eb8a31d8b4499d8538f6aefc9dba8231b27e0 | 3,638,351 |
import types
def _dict_items(typingctx, d):
"""Get dictionary iterator for .items()"""
resty = types.DictItemsIterableType(d)
sig = resty(d)
codegen = _iterator_codegen(resty)
return sig, codegen | 6435320c6ba490b85c3ef4c065f55cef0d7d2c8e | 3,638,352 |
def odd_desc(count):
"""
Replace ___ with a single call to range to return a list of descending odd numbers ending with 1
For e.g if count = 2, return a list of 2 odds [3,1]. See the test below if it is not clear
"""
return list(reversed(range(1,count*2,2))) | 2f90095c5b25f8ac33f3bb86d3f46e67932bc78a | 3,638,353 |
def retrieval_score(test_ratings: pd.DataFrame,
recommender,
remove_known_pos: bool = False,
metric: str = 'mrr') -> float:
"""
Mean Average Precision / Mean Reciprocal Rank of first relevant item @ N
"""
N = recommender.N
user_scores = []
... | c7167eef0195496ea460dcbe63926028c430433e | 3,638,354 |
def test_dump_load_keras_model_with_dict(tmpdir, save_and_load):
"""Test whether tensorflow ser/de-ser work for models returning dictionaries"""
class DummyModel(tf.keras.Model):
def __init__(self):
super().__init__()
def _random_method(self):
pass
def call(sel... | 5fcaf73e5a0b138a04091573782a2c03f4459f15 | 3,638,355 |
def stemmer_middle_high_german(text_l, rem_umlauts=True, exceptions=exc_dict):
"""text_l: text in string format
rem_umlauts: choose whether to remove umlauts from string
exceptions: hard-coded dictionary for the cases the algorithm fails"""
# Normalize text
text_l = normalize_middle_high_german(
... | 608ec49ad36ee5ae7ad41fe4eab5d9f7c65eb609 | 3,638,356 |
def test_queue_trials(start_connected_emptyhead_cluster):
"""Tests explicit oversubscription for autoscaling.
Tune oversubscribes a trial when `queue_trials=True`, but
does not block other trials from running.
"""
cluster = start_connected_emptyhead_cluster
runner = TrialRunner()
def creat... | fed9fe1458db15f871ccd4afff942c0d022a9b8a | 3,638,357 |
def get_bboxes(outputs, proposals, num_proposals, num_classes,
im_shape, im_scale, max_per_image=100, thresh=0.001, nms_thresh=0.4):
"""
Returns bounding boxes for detected objects, organized by class.
Transforms the proposals from the region proposal network to bounding box predictions
... | 09e5eb94f35672e77980c89e71fcb9ed6b460ab4 | 3,638,358 |
def air_transport_per_year_by_country(country):
"""Returns the number of passenger carried per year of the given country."""
cur = get_db().execute('SELECT Year, Value FROM Indicators WHERE CountryCode="{}" AND IndicatorCode="IS.AIR.PSGR"'.format(country))
air_transport = cur.fetchall()
cur.close()
... | 4ca85c537c5bc7ccda332af977f1252b14672235 | 3,638,359 |
def outside_range(number, min_range, max_range):
"""
Returns True if `number` is between `min_range` and `max_range` exclusive.
"""
return number < min_range or number > max_range | dc3889fbabb74db38b8558537413ebc5bc613d05 | 3,638,360 |
import re
def is_string_constant(node):
"""Checks whether the :code:`node` is a string constant."""
return is_leaf(node) and re.match('^\"[^\"]*\"$', node) is not None | 5a62c513bc856571e62c40b9d14bdefb67be4c79 | 3,638,361 |
from typing import List
def is_list_type(t) -> bool:
"""
Return True if ``t`` is ``List`` python type
"""
# print(t, getattr(t, '__origin__', None) is list)
return t == list or is_pa_type(t, pa.types.is_list) or (
hasattr(t, '__origin__') and t.__origin__ in (list, List)
) or (
... | 7da1ea98dccc4341a6db7a3e13e9f9bd278bd984 | 3,638,362 |
from datetime import datetime
def get_measure_of_money_supply():
""" 从 Sina 获取 中国货币供应量数据。
Returns: 返回获取到的数据表。数据从1978.1开始。
Examples:
.. code-block:: python
>>> from finance_datareader_py.sina import get_measure_of_money_supply
>>> df = get_measure_of_money_supply()
... | 304cf05be6a226e7da46ec16e36a6632f02848c5 | 3,638,363 |
def make_inverter_path(wire, inverted):
""" Create site pip path through an inverter. """
if inverted:
return [('site_pip', '{}INV'.format(wire), '{}_B'.format(wire)),
('inverter', '{}INV'.format(wire))]
else:
return [('site_pip', '{}INV'.format(wire), wire)] | 066c4bbad0f65fec587b12fc7a2947246401b877 | 3,638,365 |
def constant(t, length):
""" ezgal.sfhs.constant( ages, length )
Burst of constant starformation from t=0 to t=length """
if type(t) == type(np.array([])):
sfr = np.zeros(t.size)
m = t <= length
if m.sum(): sfr[m] = 1.0
return sfr
else:
return 0.0 if t > length el... | bfbc32042512465c7fecc50d976b369ac8e2c9fe | 3,638,367 |
def model_setup_fn(attrs):
"""Generate the setup function for models."""
model = load_model(attrs['type'], attrs['data'])
def func(self):
self.model = model
self.type = attrs['type']
self.data = attrs['data']
self.network_type = attrs['network_type']
self.dto = attr... | 4f0ffa9e1de3f60edef847faf319f3c5a4bef28d | 3,638,368 |
def _mkdir(space, dirname, mode=0777, recursive=False, w_ctx=None):
""" mkdir - Makes directory """
mode = 0x7FFFFFFF & mode
if not _valid_fname(dirname):
space.ec.warn("mkdir() expects parameter 1 to "
"be a valid path, string given")
return space.w_False
if not ... | c16b5e0100c50e300fcf9268383f20b1cb5c11b5 | 3,638,369 |
import decimal
def prepare_fixed_decimal(data, schema):
"""Converts decimal.Decimal to fixed length bytes array"""
if not isinstance(data, decimal.Decimal):
return data
scale = schema.get('scale', 0)
size = schema['size']
# based on https://github.com/apache/avro/pull/82/
sign, digit... | 5dc5ae8355842e175e1fa83394a63b37c04bdade | 3,638,370 |
from typing import Any
def device_traits() -> dict[str, Any]:
"""Fixture that sets default traits used for devices."""
return {"sdm.devices.traits.Info": {"customName": "My Sensor"}} | 1ccaeac4a716706915654d24270c24dac0210977 | 3,638,371 |
def calculate_equivalent_diameter(areas):
"""Calculate the equivalent diameters of a list or numpy array of areas.
:param areas: List or numpy array of areas.
:return: List of equivalent diameters.
"""
areas = np.asarray(areas)
diameters = np.sqrt(4 * areas / np.pi)
return diameters.tolis... | a353883cf148819d9f298167e73acd60b89720e5 | 3,638,373 |
def truncation_error(stencil: list, deriv: int, interval: str = DEFAULT_INTERVAL):
"""
derive the leading-order of error term
in the finite difference equation based on the given stencil.
Args:
stencil (list of int): relative point numbers
used for discretization.
deriv (int... | e3b8d312d551ed88ead3690b285659d56865e6e0 | 3,638,374 |
def cmd_renderurl(cfg, command, argv):
"""Renders a single url of your blog to stdout."""
parser = build_parser('%prog renderurl [options] <url> [<url>...]')
parser.add_option('--headers',
action='store_true', dest='headers', default=False,
help='Option that caus... | 2073c71c459357c0b6a9661596cad34196fd6c24 | 3,638,376 |
def combine_expressions(expressions, relation='AND', licensing=Licensing()):
"""
Return a combined license expression string with relation, given a list of
license expressions strings.
For example:
>>> a = 'mit'
>>> b = 'gpl'
>>> combine_expressions([a, b])
'mit AND gpl'
>>> assert ... | 8955522546a8b803caf0b1c6a3c6e8752cb35a19 | 3,638,377 |
import sqlite3
def get_prof_details(prof_id):
"""
Returns the details of the professor in same order as DB.
"""
cursor = sqlite3.connect('./db.sqlite3').cursor()
cursor.execute("SELECT * FROM professor WHERE prof_id = ?;", (prof_id))
return cursor.fetchone() | 668652474009abdda36d3e97fb5d30074f0a2755 | 3,638,379 |
def available_help(mod, ending="_command"):
"""Returns the dochelp from all functions in this module that have _command
at the end."""
help_text = []
for key in mod.__dict__:
if key.endswith(ending):
name = key.split(ending)[0]
help_text.append(name + ":\n" + mod.__dict__... | 9afa1525c016aa74dd4b3eb91851890da3590524 | 3,638,382 |
from functools import reduce
import operator
def __s_polynomial(g, h):
"""
Computes the S-polynomial of g, h. The S-polynomial is a polynomial built explicitly so that the leading terms
cancel when combining g and h linearly.
"""
deg_g = __multidegree(g)
deg_h = __multidegree(h)
max_deg =... | 49aa5b5b1dbebde1309aaa9fd2cb5947a010709f | 3,638,383 |
def generate_map_chunk(size_x: int, size_y: int, biome_type: str, x_offset: int = 0, y_offset: int = 0):
"""
Function responsible for generating map chunk in specified or random biome type,
map chunk is basically a rectangular part of a map;
generated array is basically nested list representing ... | 42863b7058bfce23b1123c14db562483254bdc21 | 3,638,384 |
def test_process_cycle(zs2_file_name, verbose=True):
"""This is a test to check if util output changed
in an incompatible manner. A zs2 file is read, converted to XML,
and back-converted to a raw datastream."""
if verbose:
print('Decoding %s...' % zs2_file_name)
data_stream = _parser.l... | 6417362a9bdaa4086865f0b8fc510dda186534f7 | 3,638,386 |
def get_dev_risk(weight, error):
"""
:param weight: shape [N, 1], the importance weight for N source samples in the validation set
:param error: shape [N, 1], the error value for each source sample in the validation set
(typically 0 for correct classification and 1 for wrong classification)
"""
... | 7278a8827dd48c341d9f294a3fed3a8b2e3c71ae | 3,638,387 |
import torch
def skewness_fn(x, dim=1):
"""Calculates skewness of data "x" along dimension "dim"."""
std, mean = torch.std_mean(x, dim)
n = torch.Tensor([x.shape[dim]]).to(x.device)
eps = 1e-6 # for stability
sample_bias_adjustment = torch.sqrt(n * (n - 1)) / (n - 2)
skewness = sample_bias_a... | ae0bdea16c1461a2e407ed57279557bc8c7f56de | 3,638,388 |
import random
def encrypt(message):
""" Self-developed encryption method that uses base conversion """
base = random.randint(3, 9)
number_list = []
for i in message:
number_list.append(keys.index(i)+1)
converted_number_list = []
for i in number_list:
converted_number_list.appen... | 967d45341fb8a5ec87f946ba6fc0a603f491485e | 3,638,389 |
def get_signature_algorithm(algorithm_type_string):
"""convert a string into a key_type (TFTF_SIGNATURE_TYPE_xxx)
returns a numeric key_type, or raises an exception if invalid
"""
try:
return TFTF_SIGNATURE_ALGORITHMS[algorithm_type_string]
except:
raise ValueError("Unknown algorith... | 41ca226dc7e6c1c0f8d5b8592803d6555630902c | 3,638,390 |
def corrgroups60(display=False):
""" A simulated dataset with tight correlations among distinct groups of features.
"""
# set a constant seed
old_seed = np.random.seed()
np.random.seed(0)
# generate dataset with known correlation
N = 1000
M = 60
# set one coefficent from each grou... | 5a80116890ff262a164f48421871107c4cdaf8a6 | 3,638,392 |
def alpha_nu_gao08(profile, **kwargs):
"""log normal distribution of alpha about the
alpha--peak height relation from Gao+2008"""
z = kwargs["z"]
alpha = kwargs["alpha"]
# scatter in dex
if "sigma_alpha" in kwargs:
sigma_alpha = kwargs["sigma_alpha"]
else:
# take scatter fr... | 393fdc6c87d4bf61fc367e7f9033bac24b9d6cea | 3,638,393 |
import base64
def get_feed_entries(helper, name, stats):
"""Pulls the indicators from the minemeld feed."""
feed_url = helper.get_arg('feed_url')
feed_creds = helper.get_arg('credentials')
feed_headers = {}
# If auth is specified, add it as a header.
if feed_creds is not None:
auth = '... | e881eebaaa9c31bc8d0abdd8b8f4aaeb9efcffe6 | 3,638,394 |
def get_skeleton_definition(character):
"""
Returns skeleton definition of the given character
:param character: str, HIK character name
:return: dict
"""
hik_bones = dict()
hik_count = maya.cmds.hikGetNodeCount()
for i in range(hik_count):
bone = get_skeleton_node(character, i)... | f76d4613f3a8adec649ea689d049ccff2966783c | 3,638,395 |
def get_f_a_st(
fuel="C3H8",
oxidizer="O2:1 N2:3.76",
mech="gri30.cti"
):
"""
Calculate the stoichiometric fuel/air ratio of an undiluted mixture using
Cantera. Calculates using only x_fuel to allow for compound oxidizer
(e.g. air)
Parameters
----------
fuel : str
... | ecd711d8a1d5499e47ccbedebfb5641aec7c7a8b | 3,638,396 |
def get_parser_args(args=None):
"""
Transform args (``None``, ``str``, ``list``, ``dict``) to parser-compatible (list of strings) args.
Parameters
----------
args : string, list, dict, default=None
Arguments. If dict, '--' are added in front and there should not be positional arguments.
... | 41b607a6ebf12526efcd38469192b398419327bf | 3,638,397 |
def parse_time_to_min(time):
"""Convert a duration to an integer in minutes.
Example
-------
>>> parse_time_to_min("2m 30s")
2.5
"""
if " " in time:
return sum([parse_time_to_min(t) for t in time.split(" ")])
time = time.strip()
for unit, value in time_units.items():
... | 6bf9656694ba4787bf9fd3e7c269d9c84e3ed143 | 3,638,398 |
def relate_stream_island(stream_layer, island_layer):
"""
Return the streams inside or delimiting islands.
The topology is defined by DE-9IM matrices.
:param stream_layer: the layer of the river network
:stream_layer type: QgisVectorLayer object (lines)
:param island_layer: the layer of the... | 1d6c90349808f6364cc8b1461b09a0c31df6d9d3 | 3,638,399 |
def stringify_array(v,
maxDepth=None,
maxItems=-1,
maxStrlen=-1):
"""
Convert a dict to a string representation.
Parameters:
d(dict) : the data dict to convert
maxDepth (int|None): if > 0, then ellipsise structures deeper than th... | 17bf5008c7a263c102f0fa03fdcc708c0fcc9a0f | 3,638,400 |
import pickle
def rpickle(picke_file, state=None):
"""
Save the state of the gps file treated
"""
logger.warning('Running rpickle ...')
results = []
if picke_file.isfile():
with open(picke_file, 'rb') as read_pickle:
results += pickle.load(read_pickle)
# print results
... | a3f0cc46d6992032d008053e679ec75c64805141 | 3,638,401 |
def should_print(test_function):
"""should_print is a helper for testing code that uses print
For example, if you had a function like this:
```python
def hello(name):
print('Hello,', name)
```
You might want to test that it prints "Hello, Nate" if you give it the
name "Nate". To d... | 16a1f675d3dced411fe5a6ffdc566db61ca7890f | 3,638,403 |
def produce_segmentation(indices: list[list[int]], wav_name: str) -> list[dict]:
"""produces the segmentation yaml content from the indices of the probabilistic_dac
Args:
indices (list[list[int]]): output of the probabilistic_dac function
wav_name (str): the name of the wav file (with the .wav ... | cd8267e90f5e69589325a4e261d3f8136b36cc53 | 3,638,405 |
def trac_get_tracs_for_object(obj, user=None, trac_type=None):
"""
Returns tracs for a specific object.
"""
content_type = ContentType.objects.get_for_model(type(obj))
qs = Trac.objects.filter(content_type=content_type, object_id=obj.pk)
if user:
qs = qs.filter(user=user)
if trac_typ... | 9617fc5e417e40fb27bfe90b2f87434902cdb70b | 3,638,406 |
def size_from_ftp(ftp, url):
"""Get size of a file on an FTP server.
Parameters
----------
ftp : FTP
An open ftplib FTP session.
url : str
File URL.
Returns
-------
int
Size in bytes.
"""
url = urlparse(url)
return ftp.size(url.path) | 50d21fa95669a9863b32de3a67eda78de713fe7c | 3,638,407 |
def set_name_line(hole_lines, name):
"""Define the label of each line of the hole
Parameters
----------
hole_lines: list
a list of line object of the slot
name: str
the name to give to the line
Returns
-------
hole_lines: list
List of line object with label
... | a57667f269dac62d39fa127b2a4bcd438a8a989b | 3,638,408 |
import torch
def dist_to_boxes(points, boxes):
"""
Calculates combined distance for each point to all boxes
:param points: (N, 3)
:param boxes: (N, 7) [x, y, z, h, w, l, ry]
:return: distances_array: (M) torch.Tensor of [(N), (N), ...] distances
"""
distances_array = torch.Tensor([])
b... | b3305ec8a4c8d5e0d5cf520e9e22d2c5377fe1de | 3,638,409 |
def blackwhite2D(data,xsize=None,ysize=None,show=1):
"""blackwhite2D(data,xsize=None,ysize=None,show=1)) - display list or array data as black white image
default popup window with (300x300) pixels
"""
if type(data) == type([]):
data = array(data)
w,h = data.shape[1],data.shape[0]
... | 78a76fab9f3eb989697b695c8d7b82c877f8dc9a | 3,638,411 |
def contains_digit(s):
"""Find all files that contain a number and store their patterns.
"""
isdigit = str.isdigit
return any(map(isdigit, s)) | 941bcee8b6fbca6a60a8845f88a3b5765e3711bb | 3,638,412 |
def to_signed(dtype):
"""
Return dtype that can hold data of passed dtype but is signed.
Raise ValueError if no such dtype exists.
Parameters
----------
dtype : `numpy.dtype`
dtype whose values the new dtype needs to be able to represent.
Returns
-------
`numpy.dtype`
"... | 7be15d324eef6f9686a5866a92ad365a67949424 | 3,638,413 |
def listen_for_wakeword():
"""Continuously detecting the appeareance of wakeword from the audio stream. Higher priority than the listen() function.
Returns:
(bool): return True if detected wakeword, False otherwise.
"""
gotWakeWord = core.listen_for_wakeword()
return gotWakeWord | 49f600ed303fb9bea11cb9247653c66272fc5491 | 3,638,414 |
from scipy.stats import kurtosis
def kurtosis(x,y):
"""
Calculate kurtosis of the probability
distribution of the forecast error if
an observation and forecast vector are given.
Both vectors must have same length, so pairs of
elements with same index are compared.
Description:
Ku... | b4242f58db8a48dbe9bec03ec641ae78858c28f7 | 3,638,416 |
def preprocess_text(sentence):
"""Handle some weird edge cases in parsing, like 'i' needing to be capitalized
to be correctly identified as a pronoun"""
cleaned = []
words = sentence.split(' ')
for w in words:
if w == 'i':
w = 'I'
if w == "i'm":
w = "I'm"
... | 4e1d69eaf0adc1ede6bc67563e499602e320e76b | 3,638,417 |
def csr_scale_rows(*args):
"""
csr_scale_rows(npy_int32 const n_row, npy_int32 const n_col, npy_int32 const [] Ap, npy_int32 const [] Aj,
npy_bool_wrapper [] Ax, npy_bool_wrapper const [] Xx)
csr_scale_rows(npy_int32 const n_row, npy_int32 const n_col, npy_int32 const [] Ap, npy_int32 const [] Aj,
... | 887f6c51d297649232d6fd297380c551dbb47008 | 3,638,420 |
def complexity_hjorth(signal):
"""**Hjorth's Complexity and Parameters**
Hjorth Parameters are indicators of statistical properties initially introduced by Hjorth
(1970) to describe the general characteristics of an EEG trace in a few quantitative terms, but
which can applied to any time series. The pa... | af5b5fb8925055da4cf48facadd1bed257e40f76 | 3,638,422 |
import pandas
def load_gecko():
"""
target variable is column "A375 Percent rank"
"""
data_nonessential = pandas.read_excel(settings.pj(settings.offtarget_data_dir, 'GeCKOv2_Non_essentials_Achilles_A375_complete.xls')) #(4697, 31)
data_all_A375 = pandas.read_csv(settings.pj(settings.offtarget_data... | 31c2db07261fb1b242f4c52808c3b7e6312b1e54 | 3,638,423 |
def get_sample_eclat(name):
"""Read a tweet sample from a sample file and return it in a format eclat
can process.
"""
sampleFile = open(name)
X = []
Y = []
line = sampleFile.readline()
while line != '':
row = line.split()
Y.append(int(row[0]))
x = []
... | dd5daa2cd19b087c4b59379b8d3b2c2ea9ec27de | 3,638,424 |
from datetime import datetime
def submission_storage_path(instance, filename):
"""
Function DocString
"""
string = '/'.join(['submissions', instance.submission_user.user_nick, str(instance.submission_question.question_level), str(instance.submission_question.question_level_id)])
string += '/'+... | 587785869da8906234bb572e9d635a892dc3270b | 3,638,425 |
def distance_to_center(n):
"""Return Manhattan distance to center of spiral of length <n>."""
dist = distances_to_center()
for _ in range(n - 1):
next(dist)
return next(dist) | 1301d0370a3f3dca72fb003073522376fd0790c0 | 3,638,426 |
from typing import List
from typing import Mapping
from typing import Any
from typing import Optional
import inspect
async def _assert_preconditions_async(preconditions: List[List[Contract]],
resolved_kwargs: Mapping[str, Any]) -> Optional[BaseException]:
"""Assert that the p... | d89c355ed56e350a619e1d7324c8341bb74f827c | 3,638,428 |
import re
def moveGeneratorFromStrList (betaStringList, string_mode = True):
""" generate the final output of move sequence as a list of dictionary.
Input :
['F5-LH', 'F5-RH', 'E8-LH', 'H10-RH', 'E13-LH', 'I14-RH', 'E15-LH', 'G18-RH']
Length of the list: how many moves in this climb to the target... | c2905fffd9d1873c79239199027697e5c6162731 | 3,638,429 |
from datetime import datetime
def generateVtBar(row):
"""生成K线"""
bar = VtBarData()
symbol, exchange = row['symbol'].split('.')
bar.symbol = symbol
bar.exchange = exchangeMapReverse[exchange]
if bar.exchange in ['SSE', 'SZSE']:
bar.vtSymbol = '.'.join([bar.symbol, bar.exc... | 5beecf78f932c8e1bf76c680157ecd29fbdf9567 | 3,638,430 |
import sqlite3
def index_with_links():
"""post request that the form link uses
"""
db = sqlite3.connect('link_shortner.db')
c = db.cursor()
link = request.forms.get('link')
generated_id = gen_id()
#row = db.execute('SELECT * from links where link_id=?', generate_id).fetchone()
c.execut... | 38e4ee6e63bacbc55a40533759c06b836a050e56 | 3,638,431 |
def divide_blend(img_x: np.ndarray, img_y: np.ndarray) -> np.ndarray:
"""
Blend image x and y in 'divide' mode
:param img_x: input grayscale image on top
:param img_y: input grayscale image at bottom
:return:
"""
result = np.zeros_like(img_x, np.float_)
height, width = img_x.shape
f... | 27207b209c871a794162ee5b2932344a185668e7 | 3,638,433 |
def init_wavefunction(n_sites,bond_dim,**kwargs):
"""
A function that initializes the coefficients of a wavefunction for L sites (from 0 to L-1) and arranges
them in a tensor of dimension n_0 x n_1 x ... x n_L for L sites. SVD
is applied to this tensor iteratively to obtain the matrix product state.
... | 8f1a4d456945d9a345f560ee3d87dadbf353e7d3 | 3,638,435 |
def num_channels_to_num_groups(num_channels):
"""Returns number of groups to use in a GroupNorm layer with a given number
of channels. Note that these choices are hyperparameters.
Args:
num_channels (int): Number of channels.
"""
if num_channels < 8:
return 1
if num_channels < 3... | e2095fba2b1b9cdada72d354ddcd781d99e4aa48 | 3,638,436 |
def response_message(status, message, status_code):
"""
method to handle response messages
"""
return jsonify({
"status": status,
"message": message
}), status_code | e9dd25f237f264835d507af01a71ef9c826bf28d | 3,638,437 |
def glDrawBuffers( baseOperation, n=None, bufs=None ):
"""glDrawBuffers( bufs ) -> bufs
Wrapper will calculate n from dims of bufs if only
one argument is provided...
"""
if bufs is None:
bufs = n
n = None
bufs = arrays.GLenumArray.asArray( bufs )
if n is None:
n = a... | ef5a83ea633138d4cb18d8d2d20736d8c1942bc0 | 3,638,438 |
def compare_rendered(obj1, obj2):
"""
Return True/False if the normalized rendered version of
two folium map objects are the equal or not.
"""
return normalize(obj1) == normalize(obj2) | b7debf048ea41b882003283b6e3b94d257f0e0fa | 3,638,439 |
async def _get_device_client_adapter(settings_object):
"""
get a device client adapter for the given settings object
"""
if not settings_object.device_id and not settings_object.id_scope:
return None
adapter = adapters.create_adapter(settings_object.adapter_address, "device_client")
ad... | 411b52a4e916d55b46933afbfa4e8513243b4397 | 3,638,440 |
def is_reserved(word):
"""
Determines if word is reserved
:param word: String representing the variable
:return: True if word is reserved and False otherwise
"""
lorw = ['define','define-struct']
return word in lorw | 0b0e3706bcafe36fc52e6384617223078a141fb2 | 3,638,441 |
def verify_figure_hash(name, figure=None):
"""
Verifies whether a figure has the same hash as the named hash in the current hash library.
If the hash library does not contain the specified name, the hash is added to the library.
Parameters
----------
name : string
The identifier for the... | 09ee240c9efbeddd4a0f33401d80b918175a579e | 3,638,442 |
def x_span_contains_y(x_spans, y_spans):
"""
Return whether all elements of y_spans are contained by some elements of x_spans
:param x_spans:
:type x_spans:
:param y_spans:
:type y_spans:
"""
for i, j in y_spans:
match_found = False
for m, n in x_spans:
i... | c366a5a5543e2fe9f6325cd3d31eccffb921693c | 3,638,443 |
import time
def log(fn):
"""
logging decorator for the for the REST method calls. Gets all important information
about the request and response, takes the time to complete the calls and writes it
to the logs.
"""
def wrapped(self, *args):
try:
start = time()
ret... | 8efcfcf043c220565092971749a12876a55641dc | 3,638,445 |
def deal_line(text_str1, text_str2, para_bound=None):
"""行合并和段落拆分"""
global result_text
text_str2 = text_str2.strip()
len_text_str2 = len(text_str2)
if len_text_str2 > 3 and len(set(text_str2)) == 1: # 处理 ***** 这类分割线
st = list(set(text_str2))[0]
# new_file.write(' ' + st * 24 +... | b984cefd842071fed3359ac36f8bae46e916e956 | 3,638,446 |
def resized_image(image: np.ndarray, max_size: int) -> np.ndarray:
"""Resize image to feature_process_size."""
h, w = image.shape[:2]
size = max(w, h)
if 0 < max_size < size:
dsize = w * max_size // size, h * max_size // size
return cv2.resize(image, dsize=dsize, interpolation=cv2.INTER_... | a32f0639b8b59cef8817861d123b5c304b7c243c | 3,638,447 |
def load_folder_list(args, ndict):
"""
Args:
dict : "name_run" -> path
"""
l = []
for p in ndict:
print("loading %s" % p)
l.append(load_pickle_to_dataframe(args, p))
d = pd.concat(l)
d = d.sort_values("name_run")
print("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... | bd434fd93b3cb06a18d40edc48f8119442e7f0ff | 3,638,448 |
def charge_initial():
"""
Not currently in use, parking spot id gets passed in and it carries over
and passes it into the stripe charge view.
"""
spot_id = int(request.args.get('id'))
spot = AddressEntry.query.get(spot_id)
return render_template('users/charge_initial.html', key=stripe_keys['... | f971b5c69954ce2026d2c4b08d6877c9f7da6067 | 3,638,449 |
import csv
def read_csv_from_file(file):
"""
Reads the CSV data from the open file handle and returns a list of dicts.
Assumes the CSV data includes a header row and uses that header row as
fieldnames in the dict. The following fields are required and are
case-sensitive:
- ``artist``
... | 89cfce0be6270076230051a6e852d1add3f4dcaf | 3,638,450 |
def identify_denonavr_receivers():
"""
Identify DenonAVR using SSDP and SCPD queries.
Returns a list of dictionaries which includes all discovered Denon AVR
devices with keys "host", "modelName", "friendlyName", "presentationURL".
"""
# Sending SSDP broadcast message to get devices
devices ... | 712cba308d150ec179a390c27ae6931595cdffa9 | 3,638,452 |
def get_index_settings(index):
"""Returns ES settings for this index"""
return (get_es().indices.get_settings(index=index)
.get(index, {}).get('settings', {})) | 6d5d13bc30fdf8db666206bb07c3310394f3ff44 | 3,638,453 |
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