content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import re
def block2dict(block: list, kind: str = None, sequence: int = -1) -> dict:
"""Takes a text block from a SerialEM .nav file and converts it into a
dictionary."""
patt_split = re.compile(r'\s?=\s?')
d = {}
for item in block:
key, value = re.split(patt_split, item)
try:
... | 7169d95d88e6e68d7f5716a5d50b629030ae8783 | 43,528 |
def plurality(l):
"""
Take the most common label from all labels with the same rev_id.
"""
s = l.groupby(l.index).apply(lambda x:x.value_counts().index[0])
s.name = 'y'
return s | 4e363648e79b5e9049aca2de56fd343c1efe1b93 | 43,529 |
import uuid
def trace_using(logger):
"""Decorator factory to trace callables.
Args:
logger: The logger to use for tracing
Returns:
The decorator, which takes a function and decorates it.
"""
def real_decorator(func):
"""Decorate a callable to report args, kwargs and ret... | 51b6dacfd36b52dde7a3bdf3b3c939b51adb2eb2 | 43,530 |
def lowpass_filter(data: FLOATS_TYPE,
sampling_freq_hz: float,
cutoff_freq_hz: float,
numtaps: int) -> FLOATS_TYPE:
"""
Apply a low-pass filter to the data.
Args:
data: time series of the data
sampling_freq_hz: sampling frequency :mat... | 4bb15468e3a26d15c0184c1094e07b3675aa321c | 43,531 |
def uncollect_if_test_explainer(**kwargs):
"""
This function is used to skip combinations of explainers
and classifiers that do not make sense. This is achieved
by using the hooks in conftest.py. Such functions should
be passed to the @pytest.mark.uncollect_if decorator as
the func argument. The... | cca68a9ff3656fcfa0181c84554f920b5beee0fc | 43,532 |
def electric_field(relative_permittivity, relative_permeability, frequency, current, length, r, theta):
"""
Calculate the electric far field for the Hertzian dipole.
:param relative_permittivity: The relative permittivity.
:param relative_permeability: The relative permeability.
:param frequency: Th... | 9e154f9c7110027b1e67f991b59d04df259d7c46 | 43,534 |
def get_messages_per_week(msgs):
"""Gets lists of messages for each calendar week between the first and the last message.
Args:
msgs (list of Mymessage objects): Messages.
Returns:
A dictionary such as:
{
week (datetime.date): list of messages within this week
... | 43ade76498c38d9977e6baddd8c651abc03e6ee7 | 43,535 |
def _handle_text_outputs(snippet: dict, results: str) -> dict:
"""
Parse the results string as a text blob into a single variable.
- name: system_info
path: /api/?type=op&cmd=<show><system><info></info></system></show>&key={{ api_key }}
output_type: text
outputs:
- name: system_in... | 693a3e5cba6d72d09b2adb3745abb4fcf07f92d3 | 43,536 |
def make_uuid():
"""generate uuids even on Python 2.4 which has no 'uuid'"""
return _uuids.pop(0) | 596702b0eed0c6f7563e25c0fd6f33756d8811ae | 43,538 |
from datetime import datetime
def _to_iso_format(traintime: datetime) -> str:
"""Return isoformatted utc time."""
return dt.as_utc(traintime).isoformat() | 04b0c7f8695bcec1de3a759d46f54a4b3a890a4c | 43,539 |
from datetime import datetime
def parse_timestamp(datetime_repr: str) -> datetime:
"""Construct a datetime object from a string."""
return datetime.strptime(datetime_repr, '%b %d %Y %I:%M%p') | ddacf877c55466354559f751eac633b5bcd7313c | 43,540 |
def proxy_request(request, **kwargs):
""" generic view to proxy a request.
Args:
destination: string, the proxied url
prefix: string, the prrefix behind we proxy the path
headers: dict, custom HTTP headers
no_redirect: boolean, False by default, do not redirect to "/"
... | 539e1bd2e70e49435ec6272888193943076d0129 | 43,541 |
def image_stabilisation_proj(
image: xpArray, axis: int = 0, projection_type: str = "max-min", **kwargs
) -> SequenceRegistrationModel:
"""
Computes a sequence stabilisation model for an image sequence indexed along a specified axis.
Instead of running a full nD registration, this uses projections inste... | 86e04bdcb529bbe3abbec42b4334b280f6404f4f | 43,542 |
def get_LOR_colors(LOR_list, min_max=(-2, 2)):
"""Use Log Odds Ratios list to create color map for allele columns
"""
cmap = cm.coolwarm
if min_max!=False:
norm = Normalize(vmin=min_max[0], vmax=min_max[1])
else:
bnd_Val = max(abs(min(LOR_list)), abs(max(LOR_list)))
print("mi... | 6b6f6c35bf38ce70a5f9a1f17600a332d99d0459 | 43,543 |
from typing import Tuple
def _shard(split: Split, shard_index: int, num_shards: int) -> Tuple[int, int]:
"""Returns [start, end) for the given shard index."""
assert shard_index < num_shards
arange = np.arange(split.num_examples)
shard_range = np.array_split(arange, num_shards)[shard_index]
start,... | ffb6410e0e806f3a91e7959e047bdc93f51d8ce9 | 43,544 |
def refractive_index(h_gp):
"""average atmospheric refractive index"""
delta = 2.93e-4
rho = atmosphere(h_gp)
n = 1. + delta * (rho / RHO0)
return n | 75dd302a50ff56abc9a93f3a815435b681b564c3 | 43,545 |
import random
def randvec(n):
"""
Given the number of vertices n returns a random 2^n x 1 basis vector
Parameters
----------
n : integer
Number of bits in string which represents the number of verticies
in graph.
Returns
-------
v : ndarray
A random 2... | 2c97e7907bd6972bb791a60142f95e26001d960b | 43,546 |
def assemble_result_str(ref_snp, alt_snp, flanking_5, flanking_3):
"""
(str, str, str, str) -> str
ref_snp : str
DESCRIPTION: 1 character (A, T, G or C), the reference SNP.
alt_snp : str
DESCRIPTION: 1 character (A, T, G or C), the variant SNP.
flanking_5 : str
DESCRIPTI... | bc0b43464124d0d19f4bfc5646730a1f951a5ced | 43,547 |
def encrypt_blob(raw_data, public_key) -> bytes:
"""Return RSA + AES encrypted byte data from raw data input.
:ivar raw_data: Bytes rsa + aes data.
:raw_data raw_data: bytes
:ivar public_key: urlsafe base64encoded rsa public key string value.
:public_key public_key: string"""
decrypted_bytes = b... | f9a1f592014cb02b0d11c39d665ab1cba1dea490 | 43,548 |
import requests
def get_api_data(session, url, date_time):
"""Get the JSON-formatted response from the AMM API for the desired
date-time.
"""
session = session or requests.Session()
return session.get(url, params={"dt": date_time.format("DD/MM/YYYY")}).json() | ff44be4a958c4f05cc5bd562854059c552f693e1 | 43,549 |
def validate_cnpj(doc):
"""Basic function to validate the CNPJ number for serializer field
Args:
doc (str): The CNPJ number, accepts with or without characters
Raises:
ValidationError: CNPJ inválido!
Returns:
doc: The CNPJ number
"""
if not cnpj(doc):
raise Val... | e1cc1b4c0287efb02c80fccb2ae3c9dc15d1b5ea | 43,551 |
def make_trefoil(size=100, noise=0.0, a=2, b=2, c=3, **kwargs):
"""Generate synthetic trefoil dataset.
Params
-----
:size = int (default = 1000)
- the number of data points to use
"""
# generate trefoil
phi = np.linspace(0, 2*np.pi, size)
x = np.sin(phi) + a*np.sin(a*phi)
y = n... | ed75bde74997dd29d599d1cffe3900f882c33f90 | 43,552 |
def _makeOperator(operatorInput, expectedShape):
"""Takes a dense numpy array or a sparse matrix or
a function and makes an operator performing matrix * blockvector
products.
Examples
--------
>>> A = _makeOperator( arrayA, (n, n) )
>>> vectorB = A( vectorX )
"""
if operatorInput i... | df6246eabfae83b11c77570ffc091dac9166f447 | 43,553 |
def search(state, goal_state):
"""Iterative deepening depth-first"""
depth = 0
def dls(node):
if node.is_goal(goal_state):
return node
if node.depth < depth:
node.expand()
for child in node.children:
result = dls(child)
if ... | f29c8d2abeb3f4f98bb2b37da880ed815c94aead | 43,554 |
from rasterio._io import window_union
def union(*windows):
"""Union windows and return the outermost extent they cover.
Parameters
----------
windows: list-like of window objects
((row_start, row_stop), (col_start, col_stop))
Returns
-------
((row_start, row_stop), (col_start, co... | 5a0b331e9b6eb923c553e6e4aef3cf590b9d0792 | 43,555 |
from typing import Mapping
def create_remote_executor(
channel: GRPCChannel,
cardinalities: Mapping[placements.PlacementLiteral, int],
) -> _executor_bindings.Executor:
"""Constructs a RemoteExecutor proxying service on `channel`."""
uri_cardinalities = data_conversions.convert_cardinalities_dict_to_strin... | 264d2a02547fb1bae7e7b35a5d3136a03f3488df | 43,556 |
def complex_abs(data):
"""
Compute the absolute value of a complex valued stacked input array.
Args:
data (numpy.array): A complex valued array with real and
imaginary parts stacked,where the size of the final dimension should be
2.
Returns:
numpy.array: Absolute value of data
"""
... | 70d4a9691e6a4697dec4a3a6778bb4bd2ae7f50d | 43,557 |
def _build_batch_norm_params(batch_norm, is_training):
"""Build a dictionary of batch_norm params from config.
Args:
batch_norm: hyperparams_pb2.ConvHyperparams.batch_norm proto.
is_training: Whether the models is in training mode.
Returns:
A dictionary containing batch_norm parameters.
"""
batc... | 892cf0891c5738e89f98f95c900d2e70dc99974d | 43,558 |
def search_abstracts(search_terms, reldate):
"""
:arg list search_terms:
:arg int reldate:
:returns object:
"""
query = '"{}"'.format('" OR "'.join(search_terms))
return Entrez.read(Entrez.esearch(
db='pubmed', term=query, reldate=reldate, datetype='pdat',
usehistory='y')) | 5a4b47ba6c0f51a91fae218168ca5e9edf04d566 | 43,560 |
def tokenize(string: str) -> [str]:
"""Tokenize a string.
:param string: [description]
:type string: str
"""
return string.split(" ") | dfc2d11e0445a6b2f867660f101e7ade7823d8ed | 43,561 |
from datetime import datetime
import html
import requests
def get_liste_match(nb_jour):
"""
Fonction permettant de chercher les matchs qui vont avoir lieu entre aujourd'hui et un horizon en paramètre.
:param nb_jour: Le nombre de jour à parcourir
:return: Un dictionnaire contenant pour chaque date la ... | 57f754484e3bed11f9e4abe3fa2b220a481911f2 | 43,562 |
def setBvar(value):
"""If `value` is a dict returns a generic_json object, otherwise it returns the value
- - - - -
**Args**:
- `value` (any type): value to assing
**Returns**
- `generic_json` if value is a dict, otherwise it returns the value
"""
if type(value) == dict:
retur... | c9832f81f8d9fc2ab4fc1b3f1cfb5a698b6181a4 | 43,563 |
def convex_attributes(variables):
"""Returns a list of the (constraint-generating) convex attributes present
among the variables.
"""
return attributes_present(variables, CONVEX_ATTRIBUTES) | d46605e5a5240271cbfb94732182c387f166a4c6 | 43,564 |
def LMStep4InitializePyBrainNetworkForLearning(fNetwork):
"""
This function realize Learning mode step:
4. Initialize empty PyBrain network for learning or reading network configuration from file.
fNetwork is a PyBrain format neural network, created at 1st step.
Function returns True if all operatio... | 7d5721447e63bbf2d3982c4ed36e86604006b3e5 | 43,565 |
def is_installed(service):
"""Check whether the Snips service `service` is installed.
Args:
service (str): The Snips service to check.
Returns:
bool: True if the service is installed; False otherwise.
Example:
>>> is_installed('snips-nlu')
True
.. versionadded:: ... | d892d12095a458fd90f7822d86bfad57f2c3bba8 | 43,566 |
def trunc(s, length):
"""Truncate a string to a given length.
The string is truncated by cutting off the last (length-4) characters
and replacing them with ' ...'
"""
if s and len(s) > length:
return s[:length - 4] + ' ...'
return s or '' | ea6d1702d709ac7d94cc2bcb2e945da71009c0fe | 43,567 |
def user_preference_form_builder(instance, preferences=[], **kwargs):
"""
A shortcut :py:func:`preference_form_builder(UserPreferenceForm, preferences, **kwargs)`
:param user: a :py:class:`django.contrib.auth.models.User` instance
"""
return preference_form_builder(
UserPreferenceForm,
... | a53b3e0f6bfef2b7ad80c522786223a7a9e52c50 | 43,568 |
def get_parser(subparsers, parent=None):
""" "Define and return a subparser for the tune subcommand."""
parser = subparsers.add_parser(
"tune",
description="Tune model using the ML on MCU flow.",
parents=[parent] if parent else [],
add_help=(parent is None),
)
parser.set_... | cc351315ab5852d3cbad00cc3784f260018c8a6a | 43,569 |
from re import M
def find_prime(bits: int) -> int:
"""Returns a prime number with the specified amount of bits."""
p = random_odd(bits)
while True:
# if p is not coprime with M then it isn't prime.
if gcd(p, M) != 1:
p += 2
continue
if miller_rabin(p, 10):
... | 7a10c8346986dc037bde486ef61b4f056170c84d | 43,570 |
import operator
def sort_values(values: list[tuple]) -> list[tuple]:
"""Returns a list of tuples sorted by x value (the value at index 0 of the inner tuple."""
return sorted(values, key=operator.itemgetter(0)) | f172f68418988d4e01dcc406de8ec467abfe7aa8 | 43,571 |
def calc_rank(age, is_veteran=False, has_disability=False):
"""
Calculate a participant's rank. A higher number is higher ranked (top of the list).
(i.e., Reverse this when sorting.)
Change this function to change the ranking algorithm.
The code in the comments below is a ranking system based ... | 2c3ab7446ac12e634ffe47b0e57e2232908b12b9 | 43,572 |
def say(text: str) -> str:
"""Return an ASCII art skeleton with a speech bubble
Args:
text: What to put in the speech bubble
>>> print(say("Hello")[1:28])
-------
( Hello )
-------
"""
template = Template(template_path.read_text())
return template.render(text=text) | 42222ac2a54c7d15da9366327937b0f24a0e6cb6 | 43,573 |
def jwtauth(handler_class):
"""
Class decorator to check for authorization
"""
# pylint: disable=W0613
def wrap_execute(handler_execute):
def require_auth(handler, kwargs):
auth = handler.request.headers.get('Authorization')
token_validation_res = validate_toke... | 3b66460a4d41883beb9efe32b86a66f9f8c79726 | 43,575 |
def js_prerelease(command):
"""decorator for building minified js/css prior to another command"""
class DecoratedCommand(command):
def run(self):
print('inner runnn.....')
try:
self.distribution.run_command('jsdeps')
except Exception as e:
... | 5856d5765383415f2c994bf0d10b921b38f23f98 | 43,576 |
from typing import Sequence
def is_sequence(obj):
"""Check if `obj` is a sequence, but not a string or bytes."""
return isinstance(obj, Sequence) and not BinaryClass.is_valid_type(obj) | ec25a6bc25c1feeacb460ea14d788369b718c0f4 | 43,577 |
def is_user_stasised(nick):
"""Checks if a user is in stasis. Returns a tuple of two items.
First parameter is True or False, and tells if the user is in stasis.
If the first parameter is False, the second will always be None.
If the first parameter is True, the second is an integer of the amount
o... | f61f4bf5554a046724d1c5cc0eedcd9323b3d46c | 43,579 |
def expose(class_method):
"""
Decorator which exposes given method into interface
:param class_method: method to expose
:return: given method with modifications
"""
class_method.is_exposed = True
return class_method | ee234bd7535f29c39fc80643997b89aeb3c0f533 | 43,580 |
def merge_length_list(lists):
"""
Merge the list that demonstrates the word length
"""
res_list = []
for l in lists:
if len(res_list) < len(l):
res_list[len(res_list):] = [0] * (len(l)-len(res_list))
for length, num in enumerate(l):
res_list[length] += num
... | 564742fd7e0a7f3a0a8535a1f02c343d193a69ac | 43,581 |
def func(pseudo_state, a1, a2, b1, b2, c1, c2, d1, d2):
"""
quadratic fit function for the Bellman value at given pseudo-state
:param pseudo_state: list(float) - list of the four state variables for a given state
:param a1, a2, ... d2: float - parameters of the quadratic fit function
"""
sum = a1*pseudo_state[0... | 6478219704999dc4cfcbc915126d919e15fe3043 | 43,582 |
async def fav_(request:Request,user_id:int=None,authorization: str = Header(None),info : dict=Depends(is_valid_token),insert:str=None,delete:str=None,toggle:str=None):
"""gallerys endpoint"""
token_user_id=int(info['id'])
token_user_secret=info["secret"]
username=None
if user_id:
resp=await ... | 0d308b266cf1bdff6f1e716ab187adaf9906984f | 43,583 |
def intersection(box1, box2):
"""
Args:
box1: bounding box
box2: bounding box
Returns:
float: the area that intersects the two boxes
"""
y_min1, x_min1, y_max1, x_max1 = box1
y_min2, x_min2, y_max2, x_max2 = box2
min_ymax = min(y_max1, y_max2)
max_ymin = max(y_mi... | 71746d93ead54aa5b36e7e6a5eb40e757711bef5 | 43,584 |
import json
def make_json_buffer(json_obj):
"""Returns a file-like object containing json_obj serialized to JSON
>>> f = make_json_buffer([1, 2, 3, True, {u'distance': 4.5}])
>>> f.read()
'[1, 2, 3, true, {"distance": 4.5}]'
"""
return make_string_buffer(json.dumps(json_obj)) | 41d1306722583a302a440cfb5d79e923c5e04615 | 43,585 |
import re
def remove_emoji(string):
"""
Remove emoticons from a text string and
return a cleaned string
"""
emoji_pattern = re.compile("["
u"\U0001F600-\U0001F64F" # emoticons
u"\U0001F300-\U0001F5FF" # symbols & pictographs
... | 436b71c2a9c36621b659630d5eb3b141800025bb | 43,586 |
def delete_project():
"""
删除项目
:return:
"""
data = request.get_json()
project_id = data["project_id"]
project = Project.objects.filter(id=project_id).first_or_404()
project.delete()
devices = Device.objects.filter(project_id=project_id).get_or_404()
for device in devices:
... | 41fc3a09f65518e6bc63b6c95e52c01550bb9c52 | 43,587 |
def verify_proof(request: VerifyProofRequest) -> bool:
"""Verifies the proof
Args:
request: Request for the proof verification operation
Return:
True if verification was successful, False if not
"""
handle = bbs_verify_proof.bbs_verify_proof_context_init()
bbs_verify_proof.bbs_v... | a8fa27924df8004e0ba86294e9d402fadbaf08bf | 43,588 |
def _wrapAngle360(lon):
"""wrap angle to [0, 360[."""
lon = np.array(lon)
return np.mod(lon, 360) | 501a0004f7162369acea5db145e079f5de86275a | 43,589 |
async def purge_all(ctx, amount, *args, **kwargs):
"""
Removes messages in given channel
Args:
ctx:
amount:
*args:
**kwargs:
Returns:
"""
channel = ctx.channel
num = int(amount) + 1 # call is additional
if num >= 1:
def check_true(m):
... | bfb806b37ce5400ed08c5d8ea3693761bdb21e9a | 43,590 |
def extended_5_3_predict(t, power_anaerobic_alactic, power_anaerobic_decay,
cp, tau_delay, cp_delay, cp_decay, cp_decay_delay, tau):
"""
Credits to Damien Grauser. Source:
https://github.com/GoldenCheetah/GoldenCheetah/blob/master/src/Metrics/ExtendedCriticalPower.cpp
"""
model ... | 0b73eb9c4bde57cef9612418b30792d3091d191a | 43,591 |
def tuplesums(tuplelist):
# type: (List[Tuple[int, int]]) -> Tuple[int, ...]
"""[(a, b), (c, d), (e, f)] -> [sum(a, c, e), sum(b, d, f)]
"""
return tuple(sum(x) for x in zip(*tuplelist)) | 7367bb63789218b4ce4beb4f164ebbba5daed14c | 43,592 |
def remove_emoji(data: str) -> str:
"""Remove the emoji from the 'data' string."""
return demoji.replace(data) | 270d280152d79eb8b9c98361e34aa48df9c20944 | 43,593 |
def get_header_value(header_list, key):
# type: (List[Tuple[str, str]], str) -> List[str]
"""Filter the header_list with provided key value.
This method is used to parse through the header list obtained from the
SMAPI response header object and retrieve list of specific tuple objects
with keys like... | 8cdd0630b5539c6229135a53ec4eb1add35fd1be | 43,596 |
def data_by_variable(datalines, variable):
"""
This function takes in a list of datalines and returns
a new list of datalines for a specified variable.
Parameters:
-----------
datalines : list
This is a list of datalines output by Temoa.
variable : string
This is the variabl... | 93c87625c9fce159424819a3fcfedeaa0fffd8b1 | 43,597 |
import torch
def compute_gradient_penalty(D, real_samples, fake_samples, opt):
"""Calculates the gradient penalty loss for WGAN GP"""
# Random weight term for interpolation between real and fake samples
alpha = torch.tensor(np.random.random((real_samples.size(0), 1, 1, 1))).float()
if opt.cuda:
... | 3996eaf7c2600be1b8184e39d4c5108ac4deccb3 | 43,598 |
import glob
def remove_skipped_echo_direct_transfer(df, fn):
"""Remove wells that were reported as skipped in the Echo protocol (xml).
This functions works with Echo direct transfer protocols.
Function supports using wildcards in the filename, the first file will be used.
Returns a new dataframe witho... | a8ef266ad859fe1118c21f5d46925d86314b60e8 | 43,599 |
def log_access(request, location=None, reason=None):
"""
Checkin form used by LNL members when accessing a storage location (contact tracing)
:param location: The name of the location (must match a location that contains equipment)
:param reason: Should be set to "OUT" if user is checking out of a loca... | 401b08bd1bd736551aac33dc5855e250e88d4944 | 43,600 |
import array
import logging
def oep(atoms,orbs,energy_func,grad_func=None,**kwargs):
"""oep - Form the optimized effective potential for a given energy expression
oep(atoms,orbs,energy_func,grad_func=None,**kwargs)
atoms A Molecule object containing a list of the atoms
orbs A matrix of ... | a6036f391aa0b3435550abcfcf69d70044477267 | 43,602 |
from jeepney.bindgen import code_from_xml # type: ignore[import]
from typing import Generator
def generate(conn: znc.Socket, save_path: str) -> Generator[None, None, str]:
"""Dump latest Signal interface description to file.
See ``jeepney.bindgen.generate``.
"""
message = yield from send_dbus_messa... | 863037b02f8133972d8238e0099b4d9eaa4baa48 | 43,603 |
import copy
import torch
def deepfool(image, net, device, num_classes=10, overshoot=0.02, max_iter=50):
"""
:param image: 输入图像：1x1x28x28
:param net: network
:device: cuda or cpu
:param num_classes: num_classes (limits the number of classes to test against, by default = 10)
:par... | db92768fda05fe8e37856082e4e353bc7184b304 | 43,604 |
def preprocess_cost_reward(data, ind_trace, steps_per_epoch, window=1):
"""Preprocess the given cost and the given reward and return
the mean, mean+std and mean-std values as metrics. This function
requires data from a single trace (execution). EVolution with respect
to the number of epochs.
"""
... | a89d477900e9dd1ff858baaff30c7d93b71edc22 | 43,605 |
def is_valid_url(string: str) -> bool:
"""Returns boolean describing if the provided string is a url"""
result = urlparse(string)
return all((result.scheme, result.netloc)) | a111a1ac4d4821d5baa00f3053f808f3ffdff5d6 | 43,606 |
def MLP(
input_shape,
output_size,
loss,
optimizer,
hidden_layers=[32, 16, 8],
dropout=0.0,
activation="linear",
out_activation="linear",
):
"""Multi Layer Perceptron.
Args:
input_shape (tuple): Shape of the input data
output_size (int): Number of neurons of the ... | 0db53ded4d0e7ac87f2ddb296bffdacec586c285 | 43,608 |
def _get_crm_resource_v1(credentials):
"""
Instantiates a Google Compute Resource Manager v1 resource object to call the Resource Manager API.
See https://cloud.google.com/resource-manager/reference/rest/.
:param credentials: The GoogleCredentials object
:return: A CRM v1 resource object
"""
... | adc1f2576404e67f95262711ab1089ca80ed5153 | 43,609 |
def line_intersection(lines, lines2, abs_tolerance = 1e-14, full_output = False):
"""
Generic Line to line intersection function
:param lines: The first set of lines, with shape [n_lines, 2, 2] where lines[i, 0, :] is the first point of the ith line
:type line: np.ndarray
:param lines2: Th... | d68d07499da2bbd0e8532862abf1181fc86ab800 | 43,610 |
import re
def get_tag_name(tag):
"""
Get the name field of a tag:
{#x:name_field:t}
Parameters
----------
tag: str
Returns
-------
name: str
"""
name = re.findall(NAME_REGEX, tag)[0]
return name | 976891bfe6e4a286f1b47f0a1fcd0cf061ac7101 | 43,611 |
from typing import Dict
from typing import Callable
def snap_array_registry(
file_pointer: h5py.File, data_source: str, name_map: Dict[str, str] = None,
) -> Dict[str, Callable]:
"""Generate snap array registry.
Parameters
----------
file_pointer
The h5py file pointer to the snap file.
... | 21bf78ebc33c9d213c49f360fa2f05a22a11bf7a | 43,612 |
import inspect
def get_storage(dictionary, index=None):
"""Get a unique storage point within a class method.
Parameters
----------
dictionary : dict
A dictionary used for storage.
index : hashable
An index under which to load the element. Needs to be hashable.
This is usef... | 199aa57fc9b04a0d4ec64b0357b31ec2877e2b03 | 43,613 |
def sample_hyperparameters():
"""
Yield possible hyperparameter choices.
"""
return {
"no_components": np.random.randint(5, 64),
"learning_schedule": np.random.choice(["adagrad", "adadelta"]),
"loss": np.random.choice(["bpr", "warp", "warp-kos"]),
"learning_rate": np.ran... | 89100422e66312450b8c0ab2232fdd69ea9efebe | 43,614 |
def waypoint_sampling(X, n_waypoints=100):
"""
Min-max sampling of waypoints in a two dimensional embedding.
:param X:
:param n_waypoints:
:return:
"""
# store waypoints and initiate distances
wps = []
N = X.shape[0]
dists = np.zeros((N, n_waypoints))
# random sampling of f... | a2fa30d90c94d6a9323b6f73ff0711315719267b | 43,615 |
import threading
def threadpool_waited_join(thread_object, timeout):
"""
Call threadpool.join() with timeout. If join completed return True, otherwise False
Notice: This function creates another daemon thread and kills it, use with care.
:param thread_object: Thread to join
:param float timeout: ... | a1f143775684aecca85c02c26879e8ec546938a9 | 43,616 |
from typing import Union
def get_relevant_terms(
phi: Union[ndarray, DataFrame],
topic: int,
lambda_: float = 0.6) -> Series:
"""Select relevant terms.
Parameters
----------
phi : Union[np.ndarray, DataFrame]
Words vs topics matrix (phi).
topic : int
Topic ... | e7266c9258cd7b36b2ec976ab41bfece8b1d9a03 | 43,617 |
import posixpath
import re
def GetCudaToolkitVersion(vm):
"""Get the CUDA toolkit version on the vm, based on nvcc.
Args:
vm: the virtual machine to query
Returns:
A string containing the active CUDA toolkit version,
None if nvcc could not be found
Raises:
NvccParseOutputError: On can not p... | e3f18651e4865b40012e53d6762b8297fab76295 | 43,618 |
def divided_by_sentences(abstract):
"""Divides abstracts by sentences
:param abstract:load
:return: list of sentences of the abstract
"""
nlp_l = English()
nlp_l.add_pipe(nlp_l.create_pipe('sentencizer'))
doc = nlp_l(abstract)
sentences = [sent.string.strip() for sent in doc.sents]
... | 360f21f0d4a5caa2c906b4691503a99a2f8a885b | 43,619 |
def write_submission_pool(outputs, args, dataset,
conf_thresh=0.1,
horizontal_flip=False,
max_workers=20):
"""
For accelerating filter image
:param outputs:
:param args:
:param dataset:
:param conf_thresh:
:param horizontal_flip:... | 2fbe04fef67bc52c49840ba176837a6f1ff22ff0 | 43,621 |
def transform_one(transformer, X=None, y=None):
"""Transform the data using one estimator."""
def prepare_df(out):
"""Convert to df and set correct column names and order."""
use_cols = inc or [c for c in X.columns if c not in exc]
# Convert to pandas and assign proper column names
... | c2f7a177bc6a547419c38bfa0a8ca62dbe2f748c | 43,622 |
def calculateHeaders(tokens: list, rawHeaders: tuple) -> tuple:
"""
Takes sanitised, tokenised URCL code and the rawHeaders.
Calculates the new optimised header values, then returns them.
"""
BITS = rawHeaders[0]
bitsOperator = rawHeaders[1]
MINREG = 0
MINHEAP = rawHeaders[3]
... | 472eeb4397d68e232b66517064f91e5688c33e3c | 43,623 |
import toml
import logging
def from_file():
"""try to load the configuration from file"""
try:
return toml.load(Config.get_path_to_conf())
except FileNotFoundError:
logging.info(f"Configuration file '{Config.get_path_to_conf()}' not found.") | 4a833987e563fdc52fabb861f84f89dbf889bf92 | 43,624 |
def synthetic_data(w, b, num_examples):
"""
y = Xw + b + noise
"""
X = tf.zeros((num_examples, w.shape[0]))
X += tf.random.normal(shape=X.shape)
y = tf.matmul(X, tf.reshape(w, (-1, 1))) + b
y += tf.random.normal(shape=y.shape, stddev=0.01)
y = tf.reshape(y, (-1, 1))
return X, y | e861c9af287108f1f08c491142093ad10bcd5a8f | 43,625 |
def weg(m) -> str:
"""capture multiple "weg"s"""
return m | 2be9b16a4969d04f1322c22b07ffd98318fa05fb | 43,626 |
from typing import Iterable
def cossin(X, p=None, q=None, separate=False,
swap_sign=False, compute_u=True, compute_vh=True):
"""
Compute the cosine-sine (CS) decomposition of an orthogonal/unitary matrix.
X is an ``(m, m)`` orthogonal/unitary matrix, partitioned as the following
where uppe... | 2350d8b65a470346631d2d657f900c899c6b3bec | 43,627 |
def getBlankBoard():
"""Create a new, blank tic tac toe board."""
board = {} # The board is represented as a Python dictionary.
for space in ALL_SPACES:
board[space] = BLANK # All spaces start as blank.
return board | 1db53045128b6ae246d9be6ef52d443aa9d8e7a1 | 43,628 |
def isopycnal_arr(arrin,target_density,pd,interp=None):
"""
Returns the value of an input array along an isopycnal.
"""
if target_density < 100:
target_density += 1000
if not interp:
i0 = isopycnal_mask(target_density,pd)
if len(arrin.shape) > 1:
i1,i2 = np.indi... | 51bdd3dbb5c410178bc2581bb14a0f48230c559f | 43,629 |
def forecast(model, predict_data, seq_len=50, forward=10, stride=1):
"""Step through the out-of-sample data and make predictions.
Args:
model (keras.Model): Trained model.
predict_data (numpy.array): Out-of-sample data.
seq_len (int): Sequence length.
forward (int): Forward.
stride (int): Step size.
Retu... | d1e520f2008d0ef74b17c1c91f5e8d8bdba26bbf | 43,630 |
def _run_on_failure_decorator(method, *args, **kwargs):
"""
A decorator to run when the tests fail
:param method: the method to run
:param args: the tuple arguments to pass to the method
:param kwargs: the dict arguments to pass to the method
:return: runs the method on failure, raises exception... | fbc6a273da852eeecb269dd89b851b6965b48a9a | 43,631 |
def get_xy_arrs(m_size, ant_rad):
"""Finds the x/y position of each pixel in the image-space
Returns arrays that contain the x-distances and y-distances of every
pixel in the model.
Parameters
----------
m_size : int
The number of pixels along one dimension of the model
ant_rad : f... | 6ce7b6aed1a4d1e3535ef57dfc2f5dac976b99f0 | 43,633 |
import json
def build_data(known_languages):
"""Build primary objects edge_struct and nodes from graph_base."""
with (SRC_DATA / 'graph_base.json').open() as base_fh:
primary_data = json.load(base_fh)
edge_struct = {}
for relation_type, edges in primary_data['edges'].items():
edge_str... | a3af7ae5aaf45e5a52d97f45a4fb126daee52439 | 43,635 |
def PrepareSipCollection(adornedRuleset):
"""
Takes adorned ruleset and returns an RDF dataset
formed from the sips associated with each adorned
rule as named graphs. Also returns a mapping from
the head predicates of each rule to the rules that match
it - for efficient retrieval later
"""
... | dde70f55c559e01ca2c050a56b3903a2658958bc | 43,636 |
def negate_q(a: ElementModQ) -> ElementModQ:
"""
Computes (Q - a) mod q.
"""
return ElementModQ(_Q_gmp - a.elem, make_formula("negate_q", a)) | 39d9e845adf52e41a6d4ff063aac0116be8e7c52 | 43,637 |
def candidate_synsets(lemma, pos):
"""
Used to restrict our attention only to synsets from the entire probability distribution over the output layer
:param lemma:
:param pos:
:return: list(Candidate synsets) or lemma if nothing in Wordnet
"""
pos_dict = {"ADJ": wn.ADJ, "ADV": wn.ADV, "NOUN":... | f7f5f02765a0c93b499a706c4d1d30ea7bdb8632 | 43,638 |
from unittest.mock import patch
def start_session(username="user", password="password", enterprise="enterprise", api_url="https://vsd:8443", version="3.2", api_prefix="api"):
""" Log in and fetch api key """
session = NURESTTestSession(username=username, password=password, enterprise=enterprise, api_url=api_... | b82a0ea396084e9fdbc11c93926f08b77ed6d2b3 | 43,639 |
def nodes_or_number(which_args):
"""PORTED FROM NETWORKX
Decorator to allow number of nodes or container of nodes.
Parameters
----------
which_args : int or sequence of ints
Location of the node arguments in args. Even if the argument is a
named positional argument (with a default va... | 3166c80d6bd5c2faaee16d70b919eda412f4d33a | 43,640 |
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