content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
async def create_cart_button() -> InlineKeyboardButton:
"""Makes cart button."""
return InlineKeyboardButton(
text=emojize('🛒 Корзина'),
callback_data='go_to_cart',
) | 964e6b1ab55bdcb36d6072ff650bff8ec9453ed9 | 61,424 |
def entities_or_platform(obj):
"""Get entities, or platform if no entities."""
entity_ids = get_entity_ids(obj)
if entity_ids:
return entity_ids
return [obj[const.CONF_PLATFORM]] | 4917d6241cd317de59b0c457fdd52036279adaa0 | 61,425 |
import torch
def simulate(
num_time_steps,
num_regions,
num_strains,
*,
num_transit_covariates=4,
overdispersion=0.5,
transit_rate=1e-2,
mutation_rate=1e-2,
initial_infected=10,
min_total_infected=1000,
max_total_infected=10000,
case_rate=0.25,
death_rate=0.03,
... | 19d76a43419a6a61daaf96992b504e53dc4ec441 | 61,426 |
def dnnlib_shadow_submit_convert_path(txt):
"""Not sure what this really does, so just a no-op."""
return txt | 9a883453edeb6171386dca221557eead8f9058b2 | 61,427 |
def security_group_set(port):
"""
Returns the security group set for a port.
A security group set is a comma-separated,
sorted list of security group ids
"""
# There are 36 chars to a uuid, and in the description fits 255 chars
security_groups = sorted(port['security_groups'])
num_group... | d55930f85219b31cf7b68c4b3136c4a3edfbf1a2 | 61,428 |
def getcompression():
"""
Returns default compression filter.
"""
return NX_COMPRESSION | 938a060d5cd771f14c64eb2094ff8c3816e1b897 | 61,431 |
from datetime import datetime
def get_duration_and_dead_ratio(file_name):
"""Takes a log filename and extracts the amount of wasted core hours.
:returns: A tuple containing the sim duration, percent of time lost, number of cores with valid times and the time lost for each core"""
with open(file_name) as f... | 0a6e335a892b248669662861daa0719424076677 | 61,432 |
def make_request(address):
"""
Set the lat_long field, if the appropriate fields are filled
"""
geolocator = Nominatim()
try:
location = geolocator.geocode(address)
lat_long = {"type": "Point",
"coordinates": [location.longitude, location.latitude]}
except (Ge... | 1a74fdf10a812c72f6eddf4f2fa5b0c9079d01d0 | 61,433 |
import re
def read_html(htmlfile):
"""
Reads the HTML file to a string.
Removes some potential trouble makers.
"""
with open(htmlfile, "r") as infile:
html = infile.read()
# Clean out some unnecessary stuff
html = re.sub("<div class=\"wp-about-author.*?</div>", "", html, re... | bb0f724792cd817464a8720199ce7c7035e6b0f1 | 61,434 |
def customise_org_office_controller(**attr):
"""
Customise org_office controller
- Marker fn
"""
current.s3db.configure("org_office",
marker_fn = org_office_marker_fn,
)
return attr | f0cbfd9eacf4dd8d560129a52ce99e9f7d24cba7 | 61,436 |
def fdr_bh(fdr, p_values):
"""
Benjamini-Hochberg false-discovery rate adjustment procedure.
pdfs.semanticscholar.org/af6e/9cd1652b40e219b45402313ec6f4b5b3d96b.pdf
Parameters
----------
fdr : float
False Discovery Rate (q*), proportion of significant results that are
actually f... | d41bff53a9a0df9a16b9163361041465be653ec6 | 61,437 |
import json
def get_new_username():
"""提示用户输入名户名"""
username = input("What is your name? ")
filename = 'username.json'
with open(filename, 'w') as file_object:
json.dump(username, file_object)
return username | 2d0f87131f551c135a229b48783886d533b81dd9 | 61,438 |
import re
def getCustomRead(alngt, compareList, readdic):
"""
Funtion which transforms an HTSeq alignment to a CustomRead class.
@type alngt: alignment
@param alngt: alignment from the sam file.
@type compareList: list
@param compareList: list which indicates differences between reference /... | 2c58db01d3a49a1753671b67ef448fc20238dfba | 61,439 |
import random
def set_new_cherry_pos(snake_lst):
"""
Sets new cherry position.
:param snake_lst: List, containing all snake instances present in the game. This is needed
to check that cherry will not be placed onto a snake.
:type snake_lst: list of Snake
"""
new_cherry_... | 2a495a4e70635dc4722344d62bd29c893f15c43a | 61,441 |
def edit_description(request, pk):
"""
Edit the description attached to an action
:param request: AJAX request
:param pk: Action ID
:return: AJAX response
"""
# Try to get the workflow first
workflow = get_workflow(request)
if not workflow:
return JsonResponse({'form_is_val... | b5897e8730cb5369866b832110016cc4c9a07d1e | 61,442 |
import json
def newBatch(batchName, seq, org, pam, skipAlign=False):
""" obtain a batch ID and write seq/org/pam to their files.
Return batchId, position string and a 100bp-extended seq, if possible.
"""
batchId = makeTempBase(seq, org, pam, batchName)
if skipAlign:
chrom, start, end, stra... | da2d0f87e0716d34bd0c8e062cf1078b277138b3 | 61,443 |
def testconf_dict(testgrid) -> dict:
"""Returns a mock of the contents expected in `config.yml`."""
# Copy the base config
testconf = deepcopy(CONFIG_BASE)
testconf["path"] = TEST_HEROGRID_PATH
return testconf | cd6e7f010a3b1c8658bc8837c36b42336a5abe85 | 61,444 |
def se_block(input_feature, name, ratio=8):
"""Contains the implementation of Squeeze-and-Excitation block.
As described in https://arxiv.org/abs/1709.01507.
"""
kernel_initializer = tf.contrib.layers.variance_scaling_initializer()
bias_initializer = tf.constant_initializer(value=0.0)
with tf.variable_sco... | 86bb1b205aa52e637097a0bc1ebc3482d87959a0 | 61,445 |
def showfiles(**args):
"""List of strings. All files modified, added, or removed by this
changeset.
"""
return showlist('file', args['ctx'].files(), **args) | 1d49591d32b7709a3704f272639dc6dca1237301 | 61,446 |
def vtk_version_ok(major, minor, build):
"""
Check the VTK version.
:param major: Major version.
:param minor: Minor version.
:param build: Build version.
:return: True if the requested VTK version is greater or equal to the actual VTK version.
"""
needed_version = 10000000000 * int(maj... | cb760ee01d143aa0be2da53210b60a433fa05320 | 61,447 |
def _parabola(data):
"""
Makes a parabola that fits the input data at the two endpoints.
Used in the beads calculation so that ``data - _parabola(data)`` is close
to 0 on the two endpoints, which gives better fits for beads.
Parameters
----------
data : array-like, shape (N,)
The d... | e40f42cbd79f69b33047c67d58332658ec0e643c | 61,448 |
def get_values_cont_x_no_numba(data_vector, no_of_evalupoints):
"""Get cut-off points for tree splitting for continuous variables.
No longer used; only kept if no_numba version would be needed
Parameters
----------
sorted_data : Numpy-1D array. Sorted vector
no_of_evalupoints : Int. c_dic... | 2b99d5274a8a9b432b47ff1dc20db88cad0d9338 | 61,449 |
def get_population():
"""Get a dummy population with minimal configuration."""
cfg = Config()
cfg.game.duration = 1 # Small duration
cfg.game.fps = 10 # Games of low accuracy but faster
cfg.genome.rnn_prob_gru_nr = 0
cfg.genome.rnn_prob_gru_nu = 0
cfg.genome.rnn_prob_gru = 0
cfg.genome... | 15604241ae2c29a0be21c781ccab53b299683c72 | 61,450 |
def adjacency_ba(tfr_dfs):
"""A stub transform function."""
return tfr_dfs | 53212b83e590cd83358a67e5b05cc4de67474107 | 61,451 |
def run_required(func):
"""A wrapper to check that the simulation has been run before a method can be executed"""
@wraps(func)
def _run_required(*args, **kwargs):
"""Check that the 'tso' attribute is not None"""
if args[0].tso_order1_ideal is None:
print("No simulation found! Ple... | 27fcfac0769e11eee34c203746e45342508fc01a | 61,452 |
def detect_hotdog(image_bytes):
""" Checks image for hotdog label using Amazon Rekoginition's object and scene detection deep learning feature.
Args:
image_bytes (bytes): Blob of image bytes.
Returns:
(boolean)
True if object and scene detection finds hotdog in blob of image bytes.... | 1edabb803bc4bf357c97593394e590a83a4de017 | 61,454 |
import time
def get_datetime():
"""Return the current datetime in a database compatible format"""
return time.strftime('%Y-%m-%d %H:%M:%S') | 804166ac7f56899733043871ea5ec9fcce474ee7 | 61,455 |
def im_detect_keypoints_aug(model, im, boxes):
"""Computes keypoint predictions with test-time augmentations.
Arguments:
model (DetectionModelHelper): the detection model to use
im (ndarray): BGR image to test
boxes (ndarray): R x 4 array of bounding boxes
Returns:
heatmaps... | d000adb64c3b921340d1b4d9aca5407ca34ca23d | 61,456 |
import numpy as np
import scipy
import torch
from torch.autograd import Variable
import sklearn
def get_data(audio, eeg, audio_unatt=None, idx_eeg=None, num_batch=None, idx_sample=None, num_context=1, num_predict=1, dct_params=None):
"""Select a sequence of audio, audio_unattnd, and eeg data
Reshape the ... | 3d684d4e2e984b8da6662a52a7746997c9a7d224 | 61,457 |
def parse_data_loader(dataloader_cfg, dataset):
"""
:param dataloader_cfg: config dict
:param dataset: torch.utils.data.Dataset
:return: torch.utils.data.DataLoader
"""
data_loader = DataLoader(
dataset,
batch_size=dataloader_cfg.get("batch-size"),
shuffle=dataloader_cfg.... | e600d9361333a66d2f1b4638cd14156039dc19f3 | 61,458 |
import wget
def read_first_line(file):
"""Gets the first line from a file.
Returns
-------
str
the first line text of the input file
"""
with open(file, 'rt',encoding="utf-8") as fd:
first_line = fd.readline()
f = open(file, 'r',encoding="utf-8") # 開啟並讀取檔案
lines =... | 20fa4bc413d22011180c02624f1edc5e7b094fbc | 61,459 |
def sort_key(doc):
"""helper function - sort by 'sider.side_effect.frequency' """
# take the first element from the document
default_value = -101
s = next(key_value(doc, "side_effect.frequency"))
n = str(next(key_value(doc, "side_effect.name")))
# if no element then return default value, name
... | 685b5d45be00c7157f507f9c43770082bdb56e69 | 61,460 |
def delete(**_):
"""Delete a virtual network.
:param ctx: The Cloudify ctx context.
:return: The status code of the REST request.
:rtype: int
"""
utils.validate_node_property(constants.VIRTUAL_NETWORK_KEY, ctx.node.properties)
utils.validate_node_property(constants.DELETABLE_KEY, ctx.node.p... | 5a61deb7da3493e40455d456af769742017ded24 | 61,461 |
def bSearch(arr, target, start=0, end=-1):
"""
-- BINARY SEARCH --
if target is not in arr, the opposite number of the
first number's index larger than target will return
"""
if not arr:
return None
if end == -1:
end = len(arr) - 1
if end < start:
raise Exception(... | f38413b6097df35c942faff2fa3c1850f6202f39 | 61,462 |
import inspect
def expand_lambda_function(lambda_func):
"""
Returns a lambda function after expansion.
"""
lambda_function = inspect.getsource(lambda_func).split(",")[1].strip()
if lambda_function.endswith(")"):
return lambda_function[:-1]
return lambda_function | 7076ce6bdee4077f6cbf665d686cd28c2420d67e | 61,463 |
def _softplus(x):
"""A nice softplus.
This is a monotonous function that is equivalent to x at +inf and
-1 / (3PI x^2) at -inf. To prove this, use two facts:
1. For negative x, atan(x) = -PI/2 - artan(1/x)
2. Near 0, atan(x) = x - x^3/3 + O(x^5)
From these two things, you can deduce that as x -> -inf:
... | 843a7b35405aa48589b3ae886ff94b632ad6d056 | 61,464 |
def utf8tounicode(arg):
"""Convert UTF8-encoded bytes to strings.
Only in Python 2. In Python 3 the errors are returned as strings.
"""
if PY2 and isinstance(arg, binary_type):
return arg.decode('utf-8')
return arg | ab69d98b088408e57e65d6886ee27b5393f86ad2 | 61,466 |
def get_bucket_usage(namespace, workspace):
"""Request google bucket usage for workspace.
Args:
namespace (str): project to which workspace belongs
workspace (str): Workspace name
Swagger:
https://api.firecloud.org/#!/Workspaces/getBucketUsage
"""
uri = "workspaces/{0}/{1}/... | ab059652e4c68f4538a6d97310eae92cf00efe73 | 61,467 |
def base2vectors(sbparams,cbparams,fbparams):
""" converts dictionary of base parameters to vector of parameters and then to pygom simulation parameters"""
global C_2s # scaling factor for c_2 (1000) to allow c_2 parameter to be same order of magnitude as other parameters
Exposure =sbparams['Exposure']
... | dbc277bac43bd04da09b8debb77556698e032a2f | 61,468 |
def inter_dists(sifts_result_i, sifts_result_j, structures=None,
atom_filter=None, intersect=False, output_prefix=None,
model=0, raise_missing=True):
"""
Compute inter-chain distances (between different entities)
in PDB file. Resulting distance map is typically not
symmet... | e6b809d0c4afe221b9e01729edb15f2147a1f32f | 61,469 |
def handle_400(e):
"""捕获abort(400)错误"""
rsp = {
'msg': 'Bad Request',
'err': 10
}
if isinstance(e.description, int):
rsp['err'] = e.description
if isinstance(e.description, dict):
rsp.update(e.description)
return jsonify(**rsp), 400 | 0e522eac390c211b1bed017631f6f62926fdcb5a | 61,470 |
def plugin_list(parser, options, args=None):
""" List github/external/built-in plugins. """
if args:
print_sub_help(parser, 'list')
return -1
# Requires Internet to access github.
if options.github: # pragma no cover
_list_github_plugins()
return 0
groups =... | 1c45126664d747403d172f22f641b0ca67862136 | 61,471 |
def dialog_open(starting_directory="", title="Open file", file_filter="All Files (*.*)"):
"""
Simple open dialog in Maya
Args:
starting_directory (unicode): Starting directory. (default: project root directory)
title (unicode): Dialog title. (default: "Open file")
file_filter (unicod... | db4f732c11e375ceebebc2f9ed546a59862e3c44 | 61,472 |
def get_messages():
"""
:return: all messages stored in database
"""
db = DataBase()
msgs = db.get_all_messages(MSG_LIMIT)
messages = remove_seconds_from_messages(msgs)
return jsonify(messages) | 04c5f052e8954204ead96f62bf96ef81ae80d4bf | 61,473 |
def key_matrix(rows, cols):
"""
first index is columns (so slightly backward from math)
:param rows:
:param cols:
:return:
"""
rv = [None] * cols
for i in range(0, cols):
rv[i] = key_vector(rows)
return rv | 9331c4a029df31c076e73809ac3ca892f662a791 | 61,474 |
def next_marker(xml_node, remaining_markers):
"""Try to determine the marker following the current xml_node. Remaining
markers is a list of other marks *within* the xml_node. May return
None"""
# More markers in this xml node
if remaining_markers:
return remaining_markers[0][0]
# Ch... | 4f9f28c14b24218ca46a07ffbf2cd5f292c76a2b | 61,475 |
def renumber_nodes(G, start=1):
"""Renumber nodes so that NeuronLand converter does not mess up.
Returns: (new_graph, node_map)
node_graph: a new DiGraph with the nodes numbered by bfs sequence.
node_map: dict mapping node number in G to that in node_graph
"""
ret = nx.DiGraph()
node_map... | 727d918882e398de70bdaa81517ac7b7dbad1915 | 61,476 |
def get_dict_from_params_str(params_str):
"""Get the dictionary of kv pairs in a string separated
by semi-colon."""
if params_str:
kvs = params_str.split(";")
params_dict = {}
for kv in kvs:
k, v = kv.strip().split("=")
params_dict[k] = eval(v)
return ... | 611f80b55c090ff5aa6afa78ee4b1b5db074cab0 | 61,477 |
def get_item_keyphrase_freq(keyphrase_freq,item):
"""
Get item's keyphrase frequency
"""
try:
count = keyphrase_freq[item].todense()
except:
count = keyphrase_freq[item]
return np.ravel(count/(np.sum(count)+0.001)) | ed91d3df2f4b112bd8e02d6f7bde245176639da3 | 61,478 |
def admin(func):
"""Require admin rights."""
def wrap(self, message, *args, **kwargs):
if message.source in self.session.admins:
return func(self, message, *args, **kwargs)
return message.dispatch("Sorry, you are not authorized to do that.")
wrap.__doc__ = func.__doc__
wrap.... | 78f8d0d3dab4b2c100ae51a4fd776f70b6fd3eda | 61,479 |
from datetime import datetime
def parse_timedelta(
delta,
min=None,
max=None,
min_included=True,
max_included=True,
):
"""
Parse time delta
"""
if isinstance(delta, str) and len(delta) > 0:
unit = delta[-1]
if unit in '0123456789':
unit = 's'
... | cb641166cb45eac781de13a20123c22990955edb | 61,480 |
def normalize(x_i):
"""
Normalize the vector
"""
min_i = tf.math.reduce_min(x_i)
max_i = tf.math.reduce_max(x_i)
x_i_normalized = (x_i - min_i) / (max_i - min_i)
return x_i_normalized | 2a3f9c98a5ae12b065259f67f5b7f1273f97ec84 | 61,481 |
def hmerge(dataset_left, dataset_right, on=None, left_on=None, right_on=None,
overwrite_text=False, from_set=None, merge_existing=None, verbose=True):
"""
Merge Quantipy datasets together using an index-wise identifer.
This function merges two Quantipy datasets (meta and data) together,
upda... | 34449f825742a6d84eefe1bfa25bfc55e6df4d20 | 61,482 |
def train_test_folds(features, labels_binary, cv_iterator, model_factory):
"""
Creates and trains an XGBoost model instance per fold from the feature matrix.
Train and test metrics are printed per fold.
The mean and std of the ROC AUC is printed at the end.
Returns all the trained models.
Argum... | 29fcd87eb1e36dbe81bdfba0e7d8d2e7a3df62ed | 61,483 |
def getSimScenarioFile(simId):
"""
Returns the path to sim's copy of the scenarios.xml file.
"""
return getSimXmlFile(simId, ScenarioFileName) | 4749ba1d4fde365d7be11b58c037b05342df5000 | 61,484 |
def bunchify(dict_tree):
"""
Traverses a dictionary tree and converts all sub-dictionaries to Bunch() objects.
"""
for k,v in dict_tree.iteritems():
if type(v) == type({}):
dict_tree[k] = bunchify(dict_tree[k])
return Bunch(dict_tree) | 3f7997f7b707ba0cf8099d06189b09f5b55df3c6 | 61,485 |
def bot(message):
"""Mocked instance of the bot"""
class Bot:
send_message = MagicMock()
return Bot() | d74c459bcbdc757017fb9ce34192875fc8d9721c | 61,486 |
from typing import Callable
from typing import Any
from typing import Optional
from typing import List
def run_simulation(
process: iterative_process.IterativeProcess,
client_selection_fn: Callable[[int], Any],
total_rounds: int,
file_checkpoint_manager: Optional[FileCheckpointManager] = None,
met... | 1913504613bda298cb099c9048b1a24ef63f5e51 | 61,487 |
import torch
def unique_first(x):
""" Torch function to get the first appearance unique items"""
unique, inverse = torch.unique(x, sorted=True, return_inverse=True)
perm = torch.arange(inverse.size(0), dtype=inverse.dtype, device=inverse.device)
inverse, perm = inverse.flip([0]), perm.flip([0])
pe... | f38fd73fddeec9a4ad220a40ae6c27cdc58097e3 | 61,488 |
def make_generator():
"""Creates a generator model that takes a 100-dimensional noise vector as a "seed", and outputs images
of size 28x28x1."""
model = Sequential()
model.add(Dense(1024, input_dim=100))
model.add(LeakyReLU())
model.add(Dense(128 * 7 * 7))
model.add(BatchNormalization())
... | 6cd56499c02500981a62f1ecb27f21506358488d | 61,489 |
from typing import List
def delete_policies(system_id: str, subject_type: str, subject_id: str, policy_ids: List[int]) -> None:
"""
删除权限
"""
url_path = "/api/v1/web/policies"
data = {"system_id": system_id, "subject_type": subject_type, "subject_id": subject_id, "ids": policy_ids}
permission_l... | a4827db7a4ebbd0470395c7d0240c333cd62d334 | 61,490 |
def WENOReconstruct( u_stencil, eps, p ):
"""WENO reconstruction. This reconstructs u_{i+1/2}
given cell averages \\bar{u}_i at each neighboring location.
See `High Order Weighted Essentially Nonoscillatory Schemes for
Convection Dominated Problems'.
Input
-----
u_stencil :
... | aa49be7b069f09c90c9b350d86575376eb5c9fbb | 61,491 |
def import_airfoil_polars(airfoil_polar_files):
"""This imports airfoil polars from a text file output from XFOIL or Airfoiltools.com
Assumptions:
Input airfoil polars file is obtained from XFOIL or from Airfoiltools.com
Source:
http://airfoiltools.com/
Inputs:
airfoil polar files ... | 1be5432bc5bbde5767c5591cbb06146f09547d90 | 61,492 |
from typing import List
def _get_representative_years(df_temp: pd.DataFrame, FS: pd.DataFrame) -> List[int]:
"""
Args:
df_temp(pd.DataFrame):
FS:
Returns:
List[int]: 月別の代表的な年
"""
df_threshold = pd.merge(df_temp, FS, on=['y', 'm'], suffixes=['_mean', '_fs']).sort_values(["m", ... | b0fb063fae3455dba28872575a87a8980f09b260 | 61,493 |
from toil.batchSystems.mesos.batchSystem import MesosBatchSystem
def loadBatchSystemClass(config):
"""
Returns a pair containing the concrete batch system class and a dictionary of keyword arguments to be passed to
the constructor of that class.
:param config: the current configuration
:param key... | c0e449fa0275b74559cf9a0bb8fa5b83fc034382 | 61,494 |
import warnings
def convert_feature_vector_to_time_series(feature_vector, sample_data):
""" Parse the feature name and reconstruct a time series object holding the equivalent data
In a feature vector object, a feature is determined by the feature
name and the feature value. When dealing with time do... | 1fd02054fb1d94bb2cf8fe38283b3bf0167dbbcd | 61,495 |
import inspect
def generate_cache_key(namespace, f, *args, **kwargs):
"""Generates a string key, based on a given function
as well as arguments to the returned function itself.
"""
argspec = inspect.getargspec(f)
has_self = bool(argspec[0]) and argspec[0][0] in ('self', 'cls')
if has_self:
... | b9f69980784560989d9c40426f091332f032eba9 | 61,497 |
def total_error(y_true, y_pred):
"""
I think this is simply the variance, but as a sum...
"""
return K.sum(K.square(y_true - K.mean(y_true))) | 5364239bf16be7603149d45f09663fd9a651f454 | 61,499 |
def hill_climbing(data_frame, et0=None, u=5, metric='bic', metric_params=None, chc=False, tw_bound_type='b', tw_bound=5, optimization_type='size', k_complex=0.1, cores=multiprocessing.cpu_count(), forbidden_parent=None):
"""Gets the adjacency matrix of the Bayesian network encoded by the elimination tree et
Ar... | 531f867d74982db34802daf39f82cea81219fc49 | 61,500 |
def get_dataloader(batch_size, image_size, data_dir='processed_celeba_small/'):
"""
Batch the neural network data using DataLoader
:param batch_size: The size of each batch; the number of images in a batch
:param img_size: The square size of the image data (x, y)
:param data_dir: Directory where ima... | ff4328fe649575850c79e3d84e98ddb8310dcb0b | 61,501 |
def get_sample_list(obj, args):
""" Try to get an attribute from an object.
Example: {% if block|getattr:"editable,True" %}
Beware that the default is always a string, if you want this
to return False, pass an empty second argument:
{% if block|getattr:"editable," %}
"""
args = args.split(... | 9f218a4b3bd306a796edbe7393fc8c1baa9bd29b | 61,502 |
def get_energy(vv, tt, chemical_potential, gbar=2.0, *args, **kwargs):
# type: (np.ndarray, np.ndarray, np.ndarray, float, list, dict) -> np.ndarray
"""Get IFG energy E in atomic units.
:param vv: Matrix of specific volumes in atomic units.
:param tt: Matrix of temperatures in atomic units.
:param ... | 78cfbb098f159be4b803a7aa33c94f92eb442229 | 61,503 |
def load_idx_cmds():
"""Load the cmds.h5 file, trying up to 3 times
It seems that one can occasionally get:
File "tables/hdf5extension.pyx", line 492, in tables.hdf5extension.File._g_new
tables.exceptions.HDF5ExtError: HDF5 error back trace
...
File "H5FDsec2.c", line 941, in H5FD_sec2_lock
u... | 0f1044e699d6eaf310663e3429c023634a436576 | 61,505 |
def objective_to_coeffs(objective_func, variables,
objective_type='minimize'):
"""Extracts variable coefficients from symbolic minimization objective
funtion.
Parameters
----------
objective_func: symbolic linear expression
variables: list of symbols
objective_type: ... | 0302f4a7789f9569340f70c33113cd26f7e42a20 | 61,506 |
def _stateless_uniform_orthogonal(shape, seed, gain=1.0,
dtype=tf.dtypes.float32):
"""Samples an orthogonal matrix from the uniform/Haar distribution."""
# The implementation of this function is essentially copied from
# tf.initializers.Orthogonal.
# Check the shape
if len(... | 31019a8c2cad11317d680898920efe2d86fe2704 | 61,509 |
def read_ssm_params(params, ssm):
"""Build dictionary from SSM keys in the form `ssm://{key}` to value in the
paramater store.
"""
result = ssm.get_parameters(Names=[s[len('ssm://'):] for s in params],
WithDecryption=True)
if result['InvalidParameters']:
raise... | dc4aa3272b8b371621074230bc2ce2b3cad1dd72 | 61,510 |
from typing import Tuple
def _split_resource(context: Context) -> Tuple[str, str, str]:
"""Splits a background event's resource into a CloudEvent service, resource, and subject."""
service = ""
resource = ""
if isinstance(context.resource, dict):
service = context.resource.get("service", "")
... | 5196f07516df20f1303745b70be77232e06d5c9a | 61,511 |
def packages_by_price(inf, sup, packages):
""" Retrieves all avaiable packages that are within a specified price threshold
:param: lowest value of price
:param: highest value of price
:param: list of packages
"""
lista = []
if inf: inf = str_to_float(inf)
else: inf = float(0)
if s... | d26ddd4f3a513b0cf9fc69cfbbc620195b95f13e | 61,512 |
def convert_example(example, tokenizer, is_test=False):
"""
Builds model inputs from a sequence for sequence classification tasks.
It use `jieba.cut` to tokenize text.
Args:
example(obj:`list[str]`): List of input data, containing text and label if it have label.
tokenizer(obj: paddlen... | e9c84c3a28bd6c03d4fb5deb82f012ecef5aae0e | 61,513 |
def aten_type_as(mapper, graph, node):
""" 构造转换Tensor类型的PaddleLayer。
TorchScript示例:
%57 : Tensor = aten::type_as(%56, %mask.1)
参数含义:
%57 (Tensor): 输出，改变类型后的Tensor。
%56 (Tensor): 需要改变类型的Tensor。
%mask.1 (Tensor): 转换成与该Tensor相一致的类型。
"""
scope_name = mapper.normalize... | 92c42927438d982f27aae1ec2173aa41d3912aff | 61,514 |
import re
def is_stable_version(version):
"""
A stable version has no letters in the final component, but only numbers.
Stable version example: 1.2, 1.3.4, 1.0.5
Not stable version: 1.2alpha, 1.3.4beta, 0.1.0rc1, 3.0.0dev
"""
if not isinstance(version, tuple):
version = version.split(... | 995dff30ff81908e0d5a00d88816d874e9bfd626 | 61,515 |
def generate_color_array(colors, opacities):
"""Generate RGB arrays each with opacity values that corresponds
to the frequency of the mutation present in each sample"""
co = np.zeros((len(colors), 4))
for i, (c, o) in enumerate(zip(colors, opacities)):
co[i, :3] = matplotlib.colors.to_rgb(c)
... | f5d13f148cf63f1599328c018d81d4be496bcc54 | 61,516 |
import click
def runner() -> click.testing.CliRunner:
"""Return a CLI console for testing"""
return click.testing.CliRunner() | 098c0fdf232eb57913459d446b5b36d582ce5737 | 61,517 |
import json
def login():
"""
Log in the user
"""
errors = None
try:
request_data = json.loads(request.data)
validate_dict_with_schema(request_data, "user/register/request")
user = User.check_user(
email=request_data["email"],
password=request_data["p... | df97c182c13faca2e48d4af0faa0fb3e164ed76c | 61,518 |
def mnx():
"""Path to xref reduced xref file."""
return join(dirname(__file__), "data", "chem_xref_seedset.tsv") | 46e49ce7df6cf285cc1f13336a72e3c78f9b733e | 61,519 |
def get_preferred_ca_repository():
"""Returns a singleton Secret repository instance."""
global _PREFERRED_CA_REPOSITORY
return _get_repository(_PREFERRED_CA_REPOSITORY,
PreferredCertificateAuthorityRepo) | c3bc5d5c1637b17bf859d3ba326f8aa35c9aac14 | 61,520 |
from datetime import datetime
def chart_grouping_as_date(value):
"""Transforms a string YYYYMM or YYYY in a date object"""
value = str(value)
for format in ('%Y', '%Y%m'):
try:
return datetime.strptime(str(value), format).date()
except ValueError:
pass | 92f80be0baea30944ebd90e1377dfa953f5fb7fa | 61,521 |
def _ncvar_to_dict(ncvar, lazydict=False):
""" Convert a NetCDF Dataset variable to a dictionary. """
# copy all attribute except for scaling parameters
d = dict((k, getattr(ncvar, k)) for k in ncvar.ncattrs()
if k not in ['scale_factor', 'add_offset'])
data_extractor = _NetCDFVariableDataE... | 2db5ac12bf06bf2f95cda89b2f6206f8b1813b06 | 61,523 |
def get_stream_credentials(username, password):
"""
Uses the `/user/uuid` endpoint.
takes a valid username and password as parameter.
It will return all the necessary credentials to use the API
and the upload endpoints.
e.g. username="bej48snvvthy", password=""
"""
endpoint = KICKFLIP_... | 17a98632f71fdeb502e14db3cc37c68069ae7621 | 61,524 |
import re
def desc(
operation: str = 'None'
):
"""
函数描述装饰器
自动添加请求属性配对
:return:
"""
def inner_method(f):
# 获取方法的参数名集合
# FullArgSpec(args=['test_arg1'], varargs=None, varkw=None, defaults=None, kwonlyargs=[], kwonlydefaults=None, annotations={})
full_arg_spec = g... | 644ab2db06c9d9028be54cab2b03054db56aa919 | 61,525 |
import requests
def run_ticket_validation(user_id, access_token, nonce):
"""
Validates Oculus session ticket.
Returns a unique ID for this player.
"""
token_check_url = 'https://graph.oculus.com/user_nonce_validate?access_token={access_token}&nonce={nonce}&user_id={user_id}'
url = token_check... | d8f5ca9d92681fe1f7ccd91fde08cada3a788f4d | 61,526 |
def impartial(f, *args, **kwargs):
"""
Acts just like Python's functools.partial, except that any arguments
to the returned function are ignored (making it 'impartial', get it?)
"""
def func(*_a, **_k):
return f(*args, **kwargs)
return func | ef512146057ae09546b6e7fac64c2496ac8f7d53 | 61,528 |
def convert_15_to_18(the15Id):
""" Convert Salesforce 15 Id to 18 Id
Arguments:
* the15Id - to be converted 15 Id
Return:
* 18 Id - converted 18 Id
"""
if not the15Id or len(the15Id) != 15: return the15Id
cmap = {
"00000": "A", "00001": "B", "00010": "C", "00011": "D", ... | 7a9ae31da7a5a84977ca1f4a1d02307d4be1e5fa | 61,529 |
def obs_seq(truth, obs_dim, obs_un, obs_op, seed):
"""This function takes the true state trajectory, and parameters, and returns an associated sequence of observations
"""
np.random.seed(seed)
[sys_dim, nanl] = np.shape(truth)
obs = np.zeros([obs_dim, nanl])
zero = np.zeros(obs_dim)
R = np.... | fc64bd73b2bfb519eadb1601271d8c76497b4bb0 | 61,530 |
import torch
import asyncio
async def webenv_slice(lock, state, indices, obs, act_len):
"""
Turns two PyTorch state tensors (pre-step and pre-output) (and what WebEnv received: observations and action lengths) into post-step state and lists of predictions and actions, asynchronously.
"""
# `obs` and `act_len`... | ffded703fbed40bf43713d62a798cbb6f5518c1e | 61,531 |
def bpow_const(a, f):
"""Broken power law with constant. This model assumes that there is a
break in the power spectrum at some given frequency. At high
frequencies the power spectrum is dominated by the constant background.
Parameters
----------
a : ndarray(5)
* a[0] : the natura... | a57c36c7965d1fe8ebfe8db937741ad6557ba911 | 61,532 |
def basic_encoding(x: pd.DataFrame, is_classification: bool):
""" Perform 'basic' encoding of categorical features.
Specifically, perform:
- Ordinal encoding for features with 2 or fewer unique values.
- One hot encoding for features with at most 10 unique values.
- Ordinal encoding for feat... | 1567d8a0170a32d4353cc777c90cdd1ccef69d86 | 61,533 |
def liked_products_view(request, **kwargs):
"""Return all the products liked by a given user"""
user_list = get_object_or_404(Like, user=request.user)
serializer = LikeSerializer(instance=user_list)
return Response(data=serializer.data) | 7024a91bf66980148a26976f1696a10bbe4a0726 | 61,535 |
def generate_header(build_type):
"""Return a C/C++ header for the given build type.
Args:
build_type: The build type definition to use.
Returns:
A string containing the C/C++ header file.
"""
return BUILD_TYPE_TEMPLATE.format(build_type=build_type) | 02fe6427fcfd23536c09d908593d0148e1a843cc | 61,536 |
def grid_dist(self,bmu_ind):
"""
som and bmu_ind
depending on the lattice "hexa" or "rect" we have different grid distance
functions.
bmu_ind is a number between 0 and number of nodes-1. depending on the map size
bmu_coord will be calculated and then distance matrix in the map will be returned
... | 60d3a1865bd750fe6c44aa16eedb4ecde504e855 | 61,537 |
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