content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def camelcase(key_name):
"""Convert snake-case to camel-case."""
parts = iter(key_name.split('_'))
return next(parts) + ''.join(i.title() for i in parts) | 078adb6b7b014bf3b0a7dffb00f1ff321951f275 | 27,300 |
def calculate_sigmoid(alpha_value = 1, TDE = 0, sigma=.1):
"""
SOFTMAX VBDE: f(s, a, \sigma) = \frac{2e^{-|\alpha TDE| / \sigma}}{1-e^{-|\alpha TDE|/\sigma}}
:return:
"""
temp = np.exp(-np.abs(alpha_value *TDE + 1e-16) / sigma)
return 2*temp / (1-temp) | d030447197531a850c43d5c86b17aae698c806ff | 27,301 |
def getprop(obj, string):
"""
Par exemple 'position.x'
:param string:
:return:
"""
tab = string.split('.')
curr_val = obj
for str in tab:
curr_val = getattr(curr_val, str)
return curr_val | c82f869395129a8b69d1a89cde97ce36fe5affd9 | 27,302 |
import argparse
def get_options():
"""Parses options."""
parser = argparse.ArgumentParser(
description="Dynamic inventory for Decapod.")
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument(
"-l", "--list",
help="List all inventory.",
action="... | c4efc1978dfb735e6e08060400d3752357e924a0 | 27,303 |
def extend(vals, inds, shape):
""" Makes an array of shape `shape` where indices `inds` have vales `vals`
"""
z = np.zeros(shape, dtype=vals.dtype)
z[inds] = vals
return z | fddcf709779ce139f1645e4292690fed6e0378f6 | 27,304 |
def check_model(model_name, model, model_type):
"""
Check the type of input `model` .
Args:
model_name (str): Name of model.
model (Object): Model object.
model_type (Class): Class of model.
Returns:
Object, if the type of `model` is `model_type`, return `model` itself.... | b6bd8b25cc2ea91e328ec5e17fd88f3f6e676e67 | 27,305 |
import os
def load_score_map(input_prefix, day, epsilon=0.000000001, excluded_indices=None, restricted_indices=None):
"""TODO: The centrality maps were pre-sorted in decreasing order???"""
score_file_path = input_prefix + '_%i.csv' % day
if not os.path.exists(score_file_path):
raise IOError("File ... | 7596f68644ce0c4d56becedd26aad450e5590276 | 27,306 |
def compute_tnacs( hvib ):
"""
Computes the time-averaged nonadiabatic couplings for a given hvib.
hvib ( list of list of matrices ): The vibronic hamiltonian for all timesteps
returns: a matrix of time-averaged nonadiabatic couplings between all electronic states
in meV
"""
nst... | 87a30d408a2a9a14fd4987edba66a47b95d4a0fe | 27,307 |
import async_timeout
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Set up config entry."""
session = aiohttp_client.async_get_clientsession(hass)
hass.data.setdefault(DOMAIN, {})
printer = SyncThru(
entry.data[CONF_URL], session, connection_mode=ConnectionMo... | 4dbecb1a63b228b689461f764c8e679c3a52f545 | 27,308 |
def center_binned_stats(*args, **kwargs):
"""
Same as scipy.stats.binned_statistic, but returns
the bin centers (matching length of `statistic`)
instead of the binedges.
See docs.scipy.org/doc/scipy/reference/generated/scipy.stats.binned_statistic.html
"""
stat, binedges, binnumber = bi... | adb762d874a19b4af09a49a2ad30b1b33d314be8 | 27,309 |
def create_account():
"""
Handles the user signing up to create an account
Redirects them to the log in page with a message after if successful
"""
signUpForm = forms.RegisterFormFactory()
if signUpForm.validate_on_submit():
netid,name,duke_email,phone_number,affiliation,password=extrac... | 321bcf6c779c6aa8857b9c4d054c18c5f611c5ad | 27,310 |
from art.classifiers import BlackBoxClassifier
from art.utils import to_categorical
import os
import json
def get_classifier_bb(defences=None):
"""
Standard BlackBox classifier for unit testing
:return: BlackBoxClassifier
"""
# define blackbox classifier
def predict(x):
with open(os.... | 8a2c3d47296450544c3f7ed69b9e4316f85ca591 | 27,311 |
import warnings
def tracks(track):
"""
Check if the submitted RGTs are valid
Arguments
---------
track: ICESat-2 reference ground track (RGT)
"""
#-- string length of RGTs in granules
track_length = 4
#-- total number of ICESat-2 satellite RGTs is 1387
all_tracks = [str(tr + 1... | 306b213fc040dbaabf515dfeff7efe45db656549 | 27,312 |
def submit_spark_job(project_id, region, cluster_name, job_id_output_path,
main_jar_file_uri=None, main_class=None, args=[], spark_job={}, job={},
wait_interval=30):
"""Submits a Cloud Dataproc job for running Apache Spark applications on YARN.
Args:
project_id (str): Required. The ID of t... | 86494a8af89a93507d40c334a84ee279cc5f7250 | 27,313 |
import sys
def load_pickle(f):
"""load pickle file and generate dictionary
:param f: absolute filepath to CSC library pickle files
:return: dictionary object (Pandas)
"""
with open(f, 'rb') as infile:
pickle_dataframe = pl.load(infile,encoding='latin1')
try:
pickle_d... | 09b28ce3981d41381a632c888e2f331c2733ba84 | 27,314 |
def get_filter_ids(id_query):
"""Parses the `id` filter paramter from the url query.
"""
if id_query is None:
return None
filter_ids = id_query.split(',')
for filter_id in filter_ids:
validate_id(filter_id)
return filter_ids | 08582368e4487c602160af42dbc6ffcd10c97075 | 27,315 |
import random
def random_sampling(predictions, number):
"""
This method will return us the next values that we need to labelise
for our training with a random prioritisation
Args:
predictions : A matrix of probabilities with all the predictions
for t... | 22a1b13122bdf5c1b95d2b039458d27a62544f6d | 27,316 |
def natsort_key_icase(s: str) -> str:
"""Split string to numeric and non-numeric fragments."""
return natsort_key(s.lower()) | ae8bbbec4a7889c2737fbe10e62c69215398faf7 | 27,317 |
def model_fn_builder(bert_config, init_checkpoint, learning_rate,
num_train_steps, num_warmup_steps, use_tpu,
use_one_hot_embeddings):
"""Returns `model_fn` closure for TPUEstimator."""
def model_fn(features, labels, mode, params): # pylint: disable=unused-argument
""... | 84a66d5e10032c5e6fffbbf0069e2e674f8ca8f8 | 27,318 |
def datetime_to_gps_format(t):
"""
Converts from a datetime to week number and time of week format.
NOTE: This does NOT convert between utc and gps time. The result
will still be in gps time (so will be off by some number of
leap seconds).
Parameters
----------
t : np.datetime64, pd.Ti... | 66dfdb09534f3b425f50d0710c68819e067c89a4 | 27,319 |
def view(jinja_environment: Environment, name: str, *args, **kwargs):
"""
Returns a Response object with HTML obtained from synchronous rendering.
Use this when `enable_async` is set to False when calling `use_templates`.
"""
return get_response(
render_template(
jinja_environme... | 864c7106db19cc15cb37132c7755652b500f3ef2 | 27,320 |
from typing import List
import collections
def create_preprocess_fn(
vocab: List[str],
num_oov_buckets: int,
client_batch_size: int,
client_epochs_per_round: int,
max_sequence_length: int,
max_elements_per_client: int,
max_shuffle_buffer_size: int = 10000) -> tff.Computation:
"""Creates ... | 1a7d114de3d979da4556123b185a00ca810b3f82 | 27,321 |
def get_slope_aspect(dem, get_aspect=True):
"""
Return the instantaneous slope and aspect (if get_aspect) for dem.
Both values derived using NumPy's gradient method by methods from:
Ritter, Paul. "A vector-based slope and aspect generation algorithm."
Photogrammetric Engineering and Remote Sensing... | 261ea3dbd114dc706f2b1f388741961bd7eb0360 | 27,322 |
def get_element_parts(
original_list: list, splitter_character: str, split_index: int
) -> list:
"""
Split all elements of the passed list on the passed splitter_character.
Return the element at the passed index.
Parameters
----------
original_list : list
List of strings to be spli... | 8c663fd64ebb1b2c53a64a17f7d63e842b457652 | 27,323 |
from typing import Union
import os
import csv
import requests
import json
def download(tickers: list, start: Union[str, int] = None, end: Union[str, int] = None, interval: str = "1d") -> dict:
"""
Download historical data for tickers in the list.
Parameters
----------
tickers: list
Ticker... | f775f45ab6136773f5c9859531ef96eb73f9e337 | 27,324 |
def logsumexp_masked(a, mask):
"""Returns row-wise masked log sum exp of a.
Uses the following trick for numeric stability:
log(sum(exp(x))) == log(sum(exp(x - max(x)))) + max(x)
Args:
a: 2D tensor.
mask: 2D tensor.
"""
mask = tf.cast(mask, a.dtype)
a_max = tf.math.reduce_max(a * mask, axis=1, k... | 86102b153e7ce912678a6381b38cb3a5168de3c8 | 27,325 |
def mutaprop_class(display_name, gui_id=None, gui_major_version=0,
gui_minor_version=0):
""" Class-level decorator. It is required for classes whose instances should
be visible for the Mutaprop UI manager.
:param display_name: Class name/description to be accessible by the UI API.
... | 4aee47a88ec5f20263decb12eb64340dd0bf296f | 27,326 |
def preprocess2(data: list, max_length: int, test_data: bool):
"""
입력을 받아서 딥러닝 모델이 학습 가능한 포맷으로 변경하는 함수입니다.
기본 제공 알고리즘은 char2vec이며, 기본 모델이 MLP이기 때문에, 입력 값의 크기를 모두 고정한 벡터를 리턴합니다.
문자열의 길이가 고정값보다 길면 긴 부분을 제거하고, 짧으면 0으로 채웁니다.
:param data: 문자열 리스트 ([문자열1, 문자열2, ...])
:param max_length: 문자열의 최대 길이
... | 61810a385c935796f1d4f6e57c5f602cb0fa6f33 | 27,327 |
def create_inference_metadata(object_type, boundary_image, boundary_world):
"""
Create a metadata of **each** detected object
:param object_type: Type of the object | int
:param boundary: Boundary of the object in GCS - shape: 2(x, y) x points | np.array
:return: JSON object of each detected object ... | b13f1ad4abc22f3eaca2c81c56ab9cb0eae80aa9 | 27,328 |
def noauth_filter_factory(global_conf, forged_roles):
"""Create a NoAuth paste deploy filter
:param forged_roles: A space seperated list for roles to forge on requests
"""
forged_roles = forged_roles.split()
def filter(app):
return NoAuthFilter(app, forged_roles)
return filter | 5a18d581616c6b4ae54b5d9c30095dd8734ed2e7 | 27,329 |
from typing import Tuple
from typing import Dict
def parse_line_protocol_stat_key(key: str) -> Tuple[str, Dict[str, str]]:
"""Parseline protocolish key to stat prefix and key.
Examples:
SNMP_WORKER;hostname=abc.com,worker=snmp-mti
will become:
("SNMP_WORKER", {"hostname": "abc.com", "... | a6806f7dd67fb2a4734caca94bff3d974923f4b2 | 27,330 |
def negative_log_partial_likelihood(censor, risk):
"""Return the negative log-partial likelihood of the prediction
y_true contains the survival time
risk is the risk output from the neural network
censor is the vector of inputs that are censored
regularization is the regularization constant (not use... | e42a7cf32fd191efb91806ecf51fd7bf279595c6 | 27,331 |
import math
def approx_equal(x, y, tol=1e-12, rel=1e-7):
"""approx_equal(x, y [, tol [, rel]]) => True|False
Return True if numbers x and y are approximately equal, to within some
margin of error, otherwise return False. Numbers which compare equal
will also compare approximately equal.
x is app... | 45285d62e6fb3da403f3efd15b1f67df92cd345c | 27,332 |
import os
def get_deleted_filename(absolute):
"""
Returns the name of the deleted file referenced by the AUFS whiteout file at the given path or
None if the file path does not reference a whiteout file.
"""
filename = os.path.basename(absolute)
if not filename.startswith(AUFS_WHITEOUT):
... | 14936fa55bbb1733bf2d481772e9fe96c5291a55 | 27,333 |
import json
def get_latest_enabled_scripts():
"""The ``/scripts/latest/enabled`` endpoint requires authentication.
It is used to get latest enabled scripts for all services submitted
by all teams including master/organizer where the team id will be
Null.
The JSON response is:
{
... | 4430eaf9c7a0d0a82f5977850e46221e8b5998fe | 27,334 |
def hanning(shape, dtype=np.float, device=backend.cpu_device):
"""Create multi-dimensional hanning window.
Args:
shape (tuple of ints): Output shape.
dtype (Dtype): Output data-type.
device (Device): Output device.
Returns:
array: hanning filter.
"""
device = backe... | 2192b4e75ceb52560865219553d27acd56bf4ef4 | 27,335 |
from typing import Union
def bitwise_and(x1: Union[ivy.Array, ivy.NativeArray], x2: Union[ivy.Array, ivy.NativeArray]) -> ivy.Array:
"""
Computes the bitwise AND of the underlying binary representation of each element x1_i of the input array x1 with
the respective element x2_i of the input array x2.
... | 662a706ba79e5f67958c78752197eff4c2a0a298 | 27,336 |
import os
def init_database(use_mysql=False, dbname="sbs"):
"""
initialize database
if use_mysql is true, use environment variables to set it up
otherwise default to sqlite
"""
#engine = create_engine('sqlite:///:memory:', echo=False)
# "mysql+mysqldb://{user}:{password}@{host}:{port}/{dbn... | 9f4ecd5c375333ef717acf6f521001854138b2d2 | 27,337 |
def add_without_punctuation(line, punctuation):
"""Returns the line cleaned of punctuation.
Param:
line (unicode)
Returns:
False if there are not any punctuation
Corrected line
"""
cleaned_line = line.translate(str.maketrans('', '', punctuation))
if line != cleaned_line... | 20dafde21efad966f8ea1be0da928594e2ee5cc4 | 27,338 |
from typing import Callable
def there_is_zero(
f: Callable[[float], float], head: float, tail: float, subint: int
) -> bool:
"""
Checks if the function has a zero in [head, tail], looking at subint
subintervals
"""
length = tail - head
step = length / subint
t = head
a = f(head)
... | dd80c55d4be5fed2e3100672ea63862014b0f8cc | 27,339 |
def target_distribution_gen(name, parameter1, parameter2):
""" parameter1 is usually a parameter of distribution (not always relevant). parameter2 is usually noise."""
if name=="Fritz-visibility":
""" parameter2 is the visibility"""
ids = np.zeros((4,4,4)).astype(str)
p = np.zeros((4,4,... | 475ee931c64f1e0bb0f6a6494aeacb25283adb9f | 27,340 |
def module_code(
sexpr,
name: str = "<unknown>",
filename: str = "<unknown>",
lineno: int = 1,
doc: str = "",
):
"""Create a module's code object from given metadata and s-expression.
"""
module_builder = Builder(
ScopeSolver.outermost(), [], SharedState(doc, lineno, filename)
... | b1baf9ab8355fadd15c6763c569399aca62b9994 | 27,341 |
def acknowledgements():
"""Provides acknowlegements for the JRO instruments and experiments
Returns
-------
ackn : str
String providing acknowledgement text for studies using JRO data
"""
ackn = ' '.join(["The Jicamarca Radio Observatory is a facility of the",
"Ins... | 013727319d43baaec57461995af8a683b5f02278 | 27,342 |
def list_vmachines(vdc):
"""
Returns:
list: vmachines info
"""
return vdc.to_dict()["vmachines"] | b3ce74c5b6f7d6d9f109a884f0c050ffae840e70 | 27,343 |
def reflection_matrix(v):
"""
The reflection transformation about a plane with normal vector `v`.
"""
n = len(v)
v = np.array(v)[np.newaxis]
return np.eye(n) - 2 * np.dot(v.T, v) | 0b56f21e95162720e4856ac2ee995570c0231d4f | 27,344 |
import logging
def log_level(level):
""" Setup the root logger for the script """
return {
'DEBUG': logging.DEBUG,
'INFO': logging.INFO,
'WARNING': logging.WARNING,
'ERROR': logging.ERROR,
'CRITICAL': logging.CRITICAL,
}.get(level, logging.INFO) | 97af634f195c1ccaef52e3db0e29caaa50554e31 | 27,345 |
def is_valid_furl_or_file(furl_or_file):
"""Validate a FURL or a FURL file.
If ``furl_or_file`` looks like a file, we simply make sure its directory
exists and that it has a ``.furl`` file extension. We don't try to see
if the FURL file exists or to read its contents. This is useful for
cases wher... | 452617b469006ec5bf4d341af2163dc3b4f69bf7 | 27,346 |
import random
def stride(input_data, input_labels):
"""
Takes an input waterfall visibility with labels and strides across frequency,
producing (Nchan - 64)/S new waterfalls to be folded.
"""
spw_hw = 32 # spectral window half width
nchans = 1024
fold = nchans / (2 * spw_hw)
sample_sp... | f490df82e65356443d6fe8a951a0ad282ca1c2af | 27,347 |
import os
def abspaths(paths):
"""
an wrapper function of os.path.abspath to process mutliple paths.
"""
return [os.path.abspath(p) for p in paths] | ae3591a11ee152a0ca2eb342644749c669c8d78e | 27,348 |
import DominantSparseEigenAD.Lanczos as lanczos
import torch
def chiF_sparseAD(model, k):
"""
Compute chi_F using the DominantSparseSymeig primitive, where the matrix
to be diagonalized is "sparse" and represented as a function.
"""
lanczos.setDominantSparseSymeig(model.H, model.Hadjoint_to_g... | acb820da75218dd37d805867ed246ca9ec2efad2 | 27,349 |
def sum_digits(y):
"""Sum all the digits of y.
>>> sum_digits(10) # 1 + 0 = 1
1
>>> sum_digits(4224) # 4 + 2 + 2 + 4 = 12
12
>>> sum_digits(1234567890)
45
>>> a = sum_digits(123) # make sure that you are using return rather than print
>>> a
6
"""
"*** YOUR CODE HERE ***"... | 5300e5bdbb058c4cc8d4a57155b114eab31b1935 | 27,350 |
import scipy
def leastsq(error_func, x0, *args, **options):
"""Find the parameters that yield the best fit for the data.
`x0` can be a sequence, array, Series, or Params
Positional arguments are passed along to `error_func`.
Keyword arguments are passed to `scipy.optimize.leastsq`
error_func: ... | d949358016ddab5d650ca1bab5c98e4ae124c153 | 27,351 |
def atomic_token_partition(value):
"""Partition given value on a token that appears resolvable(contains no
sub tokens). Returns in a tuple: (before_token, token, after_token).
Returned token includes token syntax. If no tokens are found, returned
tuple contains None in all values.
:param value: tex... | 1a4b0b952dcaa65c6f04d066685a609f1bd03669 | 27,352 |
def add_color_bar(img, space, cv):
"""
args:
img: (ndarray) in [img_rows, img_cols, channels], dtype as unit8
space: (int) pixels of space
cv: (int) color value in [0, 255]
return:
tmp_img: (ndarray) processed img
"""
assert len(img.shape) == 3, "img should be 3D"
... | a08fc1eac525dd4156add949bc4cf706ee1ea299 | 27,353 |
import json
def get_cli_body_ssh(command, response, module):
"""Get response for when transport=cli. This is kind of a hack and mainly
needed because these modules were originally written for NX-API. And
not every command supports "| json" when using cli/ssh. As such, we assume
if | json returns an... | 7d65bd1d19a837b5e78d0e1d834f2a00f4815cdb | 27,354 |
def zero_at(pos, size=8):
"""
Create a size-bit int which only has one '0' bit at specific position.
:param int pos: Position of '0' bit.
:param int size: Length of value by bit.
:rtype: int
"""
assert 0 <= pos < size
return 2**size - 2**(size - pos - 1) - 1 | 7ebdcc1ac9db4ad934108f67a751b336b4f18011 | 27,355 |
def get_authz_token(request, user=None, access_token=None):
"""Construct AuthzToken instance from session; refresh token if needed."""
if access_token is not None:
return _create_authz_token(request, user=user, access_token=access_token)
elif is_request_access_token(request):
return _create_... | 84a7f06085877b51181cadaf29da4dc0611c636b | 27,356 |
import torch
def get_bert_model():
"""
Load uncased HuggingFace model.
"""
bert_model = torch.hub.load('huggingface/pytorch-transformers',
'model',
'bert-base-uncased')
return bert_model | 51b49255fe4b1291d538251c8c199bd570fb1a31 | 27,357 |
import bio_utils.bio as bio
import tqdm
def get_bitseq_estimates(
config,
isoform_strategy,
bitseq_id_field='transcript_id',
strings_to_remove=['.cds-only', '.merged']):
""" Load the bitseq abundance estimates into a single long data frame.
Parameters
----------
config... | 93738faf48d82c6989411c3034271da1224490b0 | 27,358 |
from pathlib import Path
def na_layout(na_layout_path: Path) -> ParadigmLayout:
"""
Returns the parsed NA layout.
"""
with na_layout_path.open(encoding="UTF-8") as layout_file:
return ParadigmLayout.load(layout_file) | 35e8405b5e17ab4da917d48ef89779c7d081791e | 27,359 |
def mean_allcnnc():
"""The all convolution layer implementation of torch.mean()."""
# TODO implement pre forward hook to adapt to arbitary image size for other data sets than cifar100
return nn.Sequential(
nn.AvgPool2d(kernel_size=(6, 6)),
flatten()
) | f607750c5a05eba77999f54b8ed59f2af2ea1d12 | 27,360 |
def load_atomic_data_for_training(in_file, categories, tokenizer, max_input_length, max_output_length):
"""
Loads an ATOMIC dataset file and
:param in_file: CSV ATOMIC file
:param categories: ATOMIC category list
:param tokenizer: LM tokenizer
:return: a list of tuples
"""
examples = loa... | e47916d61dae92bdbe3cc8ccf8a06299878f1814 | 27,361 |
def md5s_loaded(func):
"""Decorator which automatically calls load_md5s."""
def newfunc(self, *args, **kwargs):
if self.md5_map == None:
self.load_md5s()
return func(self, *args, **kwargs)
return newfunc | 9eba943b939c484280b6dca79cf79fc04337f0ab | 27,362 |
def is_dap_message(message: str) -> bool:
"""Checks if a message contains information about some neighbour DAP."""
if "DAP" in message:
return True
return False | 01294888ab5cac7560fb7c58669f14573e0c1acd | 27,363 |
import random
def PhotoMetricDistortion(
img,
brightness_delta=32,
contrast_range=(0.5, 1.5),
saturation_range=(0.5, 1.5),
hue_delta=18):
"""Apply photometric distortion to image sequentially, every dictprocessation
is applied with a probability of 0.5. The position of ... | 04b371ec269d1ea52e7689726fe63b158bb53e11 | 27,364 |
from typing import Optional
import functools
def sharded_adafactor(
learning_rate_fn: optax.Schedule,
weight_decay: Optional[float] = None,
layerwise_adaptation: bool = False,
decay_method: str = '',
decay_adam: float = 0.,
decay_pow: float = 0.,
beta1: float = 0.,
clipping_threshold: ... | 1b90507a8fa78e9d13a0f030e7a11cac25aee524 | 27,365 |
def make_game():
"""Builds and returns an Apprehend game."""
return ascii_art.ascii_art_to_game(
GAME_ART, what_lies_beneath=' ',
sprites={'P': PlayerSprite, 'b': BallSprite},
update_schedule=['b', 'P'],nb_action=2) | 9e6b1ead4ec65083ffe00c5e8708bd174c7eaf79 | 27,366 |
import psutil
import os
import sys
def get_system_memory():
"""Return the total amount of system memory in bytes.
Returns:
The total amount of system memory in bytes.
"""
# Try to accurately figure out the memory limit if we are in a docker
# container. Note that this file is not specific... | a9bcde327495cf48a471c42855fc62f39e68fa5b | 27,367 |
from typing import Any
from typing import Tuple
def process_makefile(
data: Any,
specification: Any,
path: Tuple[str, ...] = (),
apply_defaults: bool = True,
) -> Any:
"""Validates a makefile and applies defaults to missing keys.
Note that that default values are deep-copied before being set.... | 6d4d114b59c22c36414a3c4e0f232dc7782802f1 | 27,368 |
def load_fashion(n_data=70000):
"""Fetches the fashion MNIST dataset and returns its desired subset.
Args:
n_data (int, optional): The size of the wanted subset. Defaults to 70000.
Returns:
tuple: The dataset, the labels of elements, the names of categories and the name of the dataset.
... | ed09938ad8c776f11029f6eaecb4f5a01cbf2fed | 27,369 |
from matplotlib.animation import Animation
import os
import re
def matplotlib_scraper_multi(block, block_vars, gallery_conf, **kwargs):
"""Scrape Matplotlib images, but with both high and low-def...
Parameters
----------
block : tuple
A tuple containing the (label, content, line_number) of th... | d1684402ba359653dc8d77cd57e189cb9592d9b2 | 27,370 |
def add_countdown_ago(date, event, events_dates_per_event):
"""
Given a date and an even,
compute the number of days since the previous occurence of this events within events_dates_per_event
"""
countdown = []
for special_date in events_dates_per_event[event]:
date_count_down = (special_... | 3ced21ad6b53007e8777d245dee4fb84f83a3086 | 27,371 |
import json
import sys
def get_groups_from_json(json_definitions):
"""Return a dict of tango.Group objects matching the JSON definitions.
Extracts the definitions of groups of devices and builds up matching
tango.Group objects. Some minimal validation is done - if the definition
contains nothing the... | 8d1f741448764236705a06d72d960f6e3b160c41 | 27,372 |
def _get_indexed_role(dep):
"""Return the function (governor/dependent) and role
based on the dependency relation type."""
gram_relation = dep['@type'][0:5]
if gram_relation in ["conj", "conj_"]:
return (-1, 'conj')
(function, role) = _relation_map[gram_relation]
return (_iminus_one... | 46edb717174f4267414604c362c22134265ceca4 | 27,373 |
def aug_op_mul_col(aug_input: Tensor, mul: float) -> Tensor:
"""
multiply each pixel
:param aug_input: the tensor to augment
:param mul: the multiplication factor
:return: the augmented tensor
"""
input_tensor = aug_input * mul
input_tensor = aug_op_clip(input_tensor, clip=(0, 1))
re... | 42e7d1596a7417ca7d981573ffaac9dccff49490 | 27,374 |
import math
def example3(path: str):
"""Planetary orbit"""
print(f"\n{Col.TITL}{' Example 3 ':-^79}{Col.RES}\n")
if not path:
path = "qr_data/ex3.txt"
file = open(path, "r")
ls = file.readlines()
# Read input data from `file`
m = int(ls[0].replace("\n", ""))
data = np.zeros((m... | aebe5d23d3d1080ce6795ba6e292ee4d973360a5 | 27,375 |
def drones_byDroneId_patch(droneId):
"""
Update the information on a specific drone
It is handler for PATCH /drones/<droneId>
"""
return handlers.drones_byDroneId_patchHandler(droneId) | 93f66abc182ff4df3b3ad06bb8cdd38d19ab8e01 | 27,376 |
def load_drop_columns(df, targets, file):
"""
Loads a dataframe with only a subset of the columns
TODO: we probably need to delete this because this exists:
df = pd.read_csv('data.csv', skipinitialspace=True, usecols=fields)
#https://stackoverflow.com/questions/26063231/read-specific-columns-with-pa... | c9218bbf22ae1429f5f7134e1e53fd85fd9d422e | 27,377 |
def get_categories(categories_file):
""" Group categories by image
"""
# map each category id to its name
id_to_category = {}
for category in categories_file['categories']:
id_to_category[category['id']] = category['name']
image_categories = {}
for category in categories_file['annot... | 10377ea688c2e33195f137cc9470cadd6eb2b9e7 | 27,378 |
from typing import Callable
from datetime import datetime
def get_profit_forecast(code: str,
getter: Callable[[str], pd.DataFrame] = rdb.get_profit_forecast):
""" 获取分析师的盈利预期
"""
today = datetime.datetime.now().strftime('%Y-%m-%d')
return getter(today).loc[code].to_dict() | 1e2499eb785e1e4e50b6d82a2c3a4eea7b297a0d | 27,379 |
import functools
def checkpoint_wrapper(module: nn.Module, offload_to_cpu: bool = False) -> nn.Module:
"""
A friendlier wrapper for performing activation checkpointing.
Compared to the PyTorch version, this version:
- wraps an nn.Module, so that all subsequent calls will use checkpointing
- handl... | 63d8f20265d2ade29e35ad5ae38b85e5a7f5f8af | 27,380 |
def get_L_star_CS_d_t_i(L_CS_d_t_i, Q_star_trs_prt_d_t_i, region):
"""(9-2)(9-2)(9-3)
Args:
L_CS_t_i: 日付dの時刻tにおける暖冷房区画iの1時間当たりの冷房顕熱負荷（MJ/h）
Q_star_trs_prt_d_t_i: 日付dの時刻tにおける暖冷房区画iの1時間当たりの熱損失を含む負荷バランス時の非居室への熱移動（MJ/h）
region: 地域区分
L_CS_d_t_i: returns: 日付dの時刻tにおける暖冷房区画iの1時間当たりの熱損失を含む負荷バランス... | 2d679123b10d4c5206253a9a7a4aadfb14fc77da | 27,381 |
def delete(isamAppliance, name, check_mode=False, force=False):
"""
Delete an Authentication Mechanism
"""
ret_obj = search(isamAppliance, name, check_mode=check_mode, force=force)
mech_id = ret_obj['data']
if mech_id == {}:
logger.info("Authentication Mechanism {0} not found, skipping ... | 4deb3c1362010d59abc39868f0b5fef8b4ddaa2f | 27,382 |
def point_to_line_cluster_distance(point, line_cluster):
"""
Distance between a single point and a cluster of lines
"""
return val_point_to_line_cluster_distance(point.value, np.array([l.value for l in line_cluster])) | 082ba543895e6bf25d013df6d94954de93468754 | 27,383 |
import time
def str_time_prop(start, end, date_format, prop):
"""Get a time at a proportion of a range of two formatted times.
start and end should be strings specifying times formated in the
given format (strftime-style), giving an interval [start, end].
prop specifies how a proportion of the interv... | 6ce9a7ec5afd41df43ce029ed7391150f42b8d8a | 27,384 |
def parse_fields(flds):
"""Parse Data Dictionary XML Fields
Arguments:
flds -- XML document element for fields
"""
fields_dict = dict()
for elem in flds:
elem_tag = str(elem.tag).strip()
if elem_tag.lower() != FIELD_TAG.lower():
raise ValueError(elem_tag + " elem... | c3057f2dc3ff525564589024ec75a58bab0a3331 | 27,385 |
import json
def analyse_json_data(input_file_path):
"""
:type input_file_path: str
:rtype: InputData
:raise FileNotFoundError
"""
data = InputData()
try:
with open(input_file_path, 'r') as input_file:
json_data = json.load(input_file)
except FileNotFoundError as e:... | fe4eef01d2fe14f920a1bf64687410ef9d8e13d9 | 27,386 |
import math
def process_datastore_tweets(project, dataset, pipeline_options):
"""Creates a pipeline that reads tweets from Cloud Datastore from the last
N days. The pipeline finds the top most-used words, the top most-tweeted
URLs, ranks word co-occurrences by an 'interestingness' metric (similar to
on tf* id... | db60b67d85f2d703e8cf46f5d89d56d8c9cfcbed | 27,387 |
def unpack_uid(uid):
"""
Convert packed PFile UID to standard DICOM UID.
Parameters
----------
uid : str
packed PFile UID as a string
Returns
-------
uid : str
unpacked PFile UID as string
"""
return ''.join([str(i-1) if i < 11 else '.' for pair in [(ord(c) >> 4... | cb131f3df386c40382cf70ddee5125f901de5fa8 | 27,388 |
def command(name=None):
"""A decorator to register a subcommand with the global `Subcommands` instance.
"""
def decorator(f):
_commands.append((name, f))
return f
return decorator | 89dd62a97ce6af317dbb2d33273fa215d740deab | 27,389 |
def agse_convert(invec, swdata, insys='gse'):
"""Convert between GSE and aberrated GSE
Using common definiton, e.g., Schwartz 1998
(S.J. Schwartz, "Shock and Discontinuity Normals, Mach Numbers, and Related Parameters",
In: Analysis Methods for Multi-Spacecraft Data, Eds.: G. Paschmann and P. Daly,
... | 3d5d77565187e9242104d8b25260b86458109701 | 27,390 |
import numpy as np
def parse_geom_text_output(out_lines, input_dict=None):
"""
Parse output of .geom file
:param out_lines: a list of lines from the readline function
:param input_dict: not in use at the moment
:return parsed_data: key, value of the trajectories of cell, atoms,
force etc
... | a01ba11130d91aa2211563322384e772dfe7ad1a | 27,391 |
def evalKnapsackBalanced(individual):
"""
Variant of the original weight-value knapsack problem with added third object being minimizing weight difference between items.
"""
weight, value = evalKnapsack(individual)
balance = 0.0
for a,b in zip(individual, list(individual)[1:]):
balance +... | 2037e6b33d4cd8c76496b8fbb866febbf355aaac | 27,392 |
import os
def read_links(ls):
"""Returns list of objects with source and target"""
return list(map(lambda el: {"source": el, "target": os.readlink(el)}, ls)) | 9768106043c706ed37b90de9289325f0574096db | 27,393 |
def complexify_module(lines_in):
"""
Complexify a module by separating its derived types, functions, and subroutines
and passing them through a line complexification function.
Parameters
----------
lines_in : list of string
List of strings source code for one module to be complexified
... | dfa30e883c2addeb1e3e5ac0c84be4f7d7834277 | 27,394 |
from datetime import datetime
import pytz
def utc_right_now():
"""
Returns a datetime object reflecting the time in UTC as of when this function was called.
"""
return datetime.datetime.now(tz=pytz.utc).replace(tzinfo=None) | 870eff5c5f744b8d3e84a21f00adc48bae088221 | 27,395 |
def process_img_border(img_array, polygon_pts, border=6):
"""Process Raw Data into
Args:
img_array (numpy array): numpy representation of image.
polygon_pts (array): corners of the building polygon.
Returns:
numpy array: .
"""
heigh... | 7ad98cc9e66e34849a534a42e3d78062e1b779c4 | 27,396 |
from typing import Dict
from typing import Any
def async_flow_poll(destination: Text, batch_id: Text) -> Dict[Text, Any]:
"""Repeatedly checks on the status of the batch, and returns
the result after the processing has been completed.
Args:
destination (Text): This is the destination parsed
... | e0816d6c7bb2f841a5878f55781329844d5b4ce9 | 27,397 |
from typing import Optional
from typing import Mapping
def get_connection(arn: Optional[str] = None,
tags: Optional[Mapping[str, str]] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetConnectionResult:
"""
Provides details about CodeStar Connection.
... | 76494278cfd1ec4adf3ecd90d8f5536f545a814f | 27,398 |
from typing import Counter
def generate_samples(n_samples, func, *args, **kwargs):
"""Call a function a bunch of times and count the results.
Args:
n_samples: Number of time to call the function.
func: The function results are counted from.
*args
**args: The arguments to pass ... | 625c2bf6713420e26704d2c2842504343be09434 | 27,399 |
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