content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def hex_to_64(hexstr):
"""Convert a hex string to a base64 string.
Keyword arguments:
hexstr -- the hex string we wish to convert
"""
B64CHARS = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
## internals
# bits contains the bits read off so far that don't make enou... | ca8c48bedf4ac776288a8faad06ec80c0289c11e | 32,488 |
def get_frozen_graph(graph_file):
"""Read Frozen Graph file from disk."""
with tf.gfile.FastGFile(graph_file, "rb") as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
return graph_def | e3a7bb3e1abf7eb09e6e11b325176eb95109e634 | 32,489 |
def wrap_functional_unit(dct):
"""Transform functional units for effective logging.
Turns ``Activity`` objects into their keys."""
data = []
for key, amount in dct.items():
if isinstance(key, int):
data.append({"id": key, "amount": amount})
else:
try:
... | 9c86b5c6c4f360e86f39e2bc59ce4a34804cd7fa | 32,490 |
def full_fuel_requirement(mass: int) -> int:
"""Complete fuel requirements for a single module."""
base_fuel = fuel_requirement(mass)
return base_fuel + sum(additional_fuel_requirements(base_fuel)) | 62c9d7e11afd0805d476216bdd113081285b10c4 | 32,492 |
def is_private(name):
"""Check whether a Python object is private based on its name."""
return name.startswith("_") | d04dfd84884bbc8c8be179c6bc5fc1371f426a78 | 32,493 |
import warnings
def get_suitable_output_file_name_for_current_output_format(output_file, output_format):
""" renames the name given for the output_file if the results for current_output format are returned compressed by default
and the name selected by the user does not contain the correct extension.
out... | 6925d721f06e52c8177c5e4f6404629043642cc4 | 32,494 |
def efficientnet_b1(
num_classes: int = 1000,
class_type: str = "single",
dropout: float = 0.2,
se_mod: bool = False,
) -> EfficientNet:
"""
EfficientNet B1 implementation; expected input shape is (B, 3, 240, 240)
:param num_classes: the number of classes to classify
:param class_type: ... | e713946ec937d0beb2069f7a273a311cad4b3305 | 32,495 |
def mark_user_authenticated(user, login):
"""
Modify a User so it knows it is logged in - checked via user.is_authenticated()
"""
setattr(user, ACTIVATED_LOGIN_KEY, login)
return user | dcd706204747c526c2128a49fcf24c7ef8e075bd | 32,496 |
def assignments(bmat, order=1, ntry=10):
"""Make assignments between rows and columns.
The objective is to have assigments following the following conditions:
- all association are allowed in bmat,
- each row is associated with a unique column,
- each column is associated with a unique row,
... | 5d183df6b538b13f53cf4a9ec18527525b5d0383 | 32,497 |
from operator import inv
def _tracemin_fiedler(L, X, normalized, tol, method):
"""Compute the Fiedler vector of L using the TraceMIN-Fiedler algorithm.
"""
n = X.shape[0]
if normalized:
# Form the normalized Laplacian matrix and determine the eigenvector of
# its nullspace.
e ... | 9b14aa1a8973134846bcf31dabe8bb27d70d36fd | 32,498 |
def default_char_class_join_with():
""" default join for char_class and combine types """
return '' | 9d8f15413f56202472f2e1257382babbaa444edc | 32,499 |
def infer_orf(pos1, pos2, corr_coeff=np.zeros(7)):
"""
Approximation of spatial correlations at seven angles, with borders at
30 degrees.
"""
if np.all(pos1 == pos2):
return 1.
else:
eta = np.arccos(np.dot(pos1, pos2))
idx = np.round( eta / np.pi * 180/30.).astype(int)
... | 9f624d42b39424ab14fefe68758403709661987f | 32,500 |
def draw_bs_reps_ind(data, func, size=1):
"""Draw bootstrap replicates, resampling indices"""
# Set up array of indices
inds = np.arange(len(data))
# Initialize replicates
bs_reps = np.empty(size)
# Generate replicates
for i in range(size):
bs_inds = np.random.choice(inds, size=le... | 39be61c2c7f3f1b67887c9f4a6159f63cc9f6c92 | 32,502 |
def get_committee_assignment(
state: BeaconState,
config: Eth2Config,
epoch: Epoch,
validator_index: ValidatorIndex,
) -> CommitteeAssignment:
"""
Return the ``CommitteeAssignment`` in the ``epoch`` for ``validator_index``.
``CommitteeAssignment.committee`` is the tuple array of validators i... | ad0661cb166c319fe7026199f0175de8939457ab | 32,503 |
def from_tfp(posterior, var_names=None, *, coords=None, dims=None):
"""Convert tfp data into an InferenceData object."""
return TfpConverter(
posterior=posterior, var_names=var_names, coords=coords, dims=dims
).to_inference_data() | b77b8fc6efbef07a3243026fa0baf40912be5950 | 32,504 |
def collection_file_fixture(config, filesystem):
"""Return a test CollectionFile instance"""
collection_name = 'test-collection'
file_name = 'index'
collection_file = CollectionFile(config, filesystem, collection_name, file_name)
collection_file.get_collection().get_path().mkdir(parents=True)
r... | f4c8aab35727cdc345a8cd173c7f4646a66e17dc | 32,505 |
def get_array_of_data():
"""Function helps to collect all filtered data in one array and it returns that"""
array_of_data = []
array_of_messages = gmail_get.get_bodies_of_messages()
for msg in array_of_messages:
if 'новый сотрудник' in msg:
message = get_data_from_text(msg)
... | 2990315722ee263922a119cba38c8e0d6e86675e | 32,506 |
def call_blade_functions (calls):
"""
Call a set of system functions for each blade in the rack. The results of the calls will be
aggregated together for each blade.
:param calls: A list of tuples containing the functions to call, the name of the parameter that
contains the blade ID, and a lis... | 30acf91d9346b9bcf090388a9d2a02b26b02ce36 | 32,507 |
from typing import Callable
from typing import Optional
def seglearn_wrapper(func: Callable, func_name: Optional[str] = None) -> FuncWrapper:
"""Wrapper enabling compatibility with seglearn functions.
As [seglearn feature-functions](https://github.com/dmbee/seglearn/blob/master/seglearn/feature_functions... | d13427f9c696c9ded8c412401b8879c4bbc66073 | 32,508 |
import scipy
def spline_fit(output_wave,input_wave,input_flux,required_resolution,input_ivar=None,order=3,max_resolution=None):
"""Performs spline fit of input_flux vs. input_wave and resamples at output_wave
Args:
output_wave : 1D array of output wavelength samples
input_wave : 1D array of i... | 2a42f6c85bace99bba7897be81ecd5a779373476 | 32,509 |
def park2_3_mf(z, x):
""" Computes the Park2_3 function. """
f = [z[0][0]/5000.0, z[1]/10.0]
return park2_3_z_x(f, x) | 801da280fd9287de6124c16a526f66d3526d054f | 32,510 |
def make_batch_sql(
table, datas, auto_update=False, update_columns=(), update_columns_value=()
):
"""
@summary: 生产批量的sql
---------
@param table:
@param datas: 表数据 [{...}]
@param auto_update: 使用的是replace into， 为完全覆盖已存在的数据
@param update_columns: 需要更新的列 默认全部，当指定值时，auto_update设置无效，当dupl... | 48c990994c226bc370c8c5a62694eae29ab8e6e5 | 32,511 |
import bot_config
import traceback
def get_dimensions():
"""Returns bot_config.py's get_attributes() dict."""
# Importing this administrator provided script could have side-effects on
# startup. That is why it is imported late.
try:
if _in_load_test_mode():
# Returns a minimal set of dimensions so i... | 7e8b2c29cf43ee46df77671370fb5c6a0030643a | 32,512 |
from pathlib import Path
def find_project_root(srcs):
"""Return a directory containing .git, .robocop or pyproject.toml.
That directory will be a common parent of all files and directories
passed in `srcs`.
If no directory in the tree contains a marker that would specify it's the
project root, the... | 87c2b40498879dccc8f5ec18c1b456390b845b44 | 32,513 |
def __virtual__():
"""
Return virtual name of the module.
:return: The virtual name of the module.
"""
if HAS_SQLI:
return __virtualname__
return False, "sqlite3 module is missing" | f40a769e6376e284ddc7ab805b094e056db78d9e | 32,514 |
def filter_contours(flist, contours, dist):
""" Filter out all visual cues with a eucl_dist(P/A ratio) smaller than .05
"""
n, fltr_cnts, bad_cnts = [], [], []
# loop over each frame to verify condition
for i in range(len(flist)):
fltr_areas = list(np.array(contours[i])[np.where(np.array(dis... | 4720bd1b1c860dfe45c067602672b042f060d571 | 32,515 |
def count_ents(phrase):
"""
Counts the number of Named Entities in a spaCy Doc/Span object.
:param phrase: the Doc/Span object from which to remove Named Entities.
:return: The number of Named Entities identified in the input object.
"""
named_entities = list(phrase.ents)
return len(named_en... | 7e592442ebaf504320a903c4084454ff73896595 | 32,516 |
def version_command(argv) -> CommandResult:
"""Show FlakeHell version.
"""
print('FlakeHell', colored(flakehell_version, 'green'))
print('Flake8 ', colored(flake8_version, 'green'))
print('For plugins versions use', colored('flakehell plugins', 'green'))
return ExitCode.OK, '' | bf541f6c049ed8c385200817912908d7f615bb17 | 32,517 |
import typing
def get_oldest_employees(count_employees: int) -> typing.List[typing.Tuple[str, str]]:
"""
Return a list of pairs in the form of (FirstName, LastName).
The list will consist of the `count` oldest employees from oldest to youngest.
:param count: Number of employees to return.
:type c... | 9b1518ddb936d40997a0f8c5bc8770b33956e5c2 | 32,518 |
def get_Q_UT_CL_d_t_i(L_CL_d_t_i, Q_T_CL_d_t_i):
"""冷房設備機器の未処理冷房潜熱負荷（MJ/h）(20b)を計算する
Args:
Q_max_CL_d_t_i(ndarray): 最大冷房潜熱出力
L_CL_d_t_i(ndarray): 冷房潜熱負荷
Q_T_CL_d_t_i: returns: 冷房設備機器の未処理冷房潜熱負荷（MJ/h）
Returns:
ndarray: 冷房設備機器の未処理冷房潜熱負荷（MJ/h）
"""
return L_CL_d_t_i - Q_T_CL_d_... | 4f46048e6df08d634153b176b241ac1caaae252f | 32,519 |
import re
def html_gscholar_to_json(soup):
"""
"""
# Scrape just PDF links
for pdf_link in soup.select('.gs_or_ggsm a'):
pdf_file_link = pdf_link['href']
print(pdf_file_link)
# JSON data will be collected here
data = []
# Container where all needed data is located
f... | cf7166650b9114e184896c10e17be4a32bc129a0 | 32,520 |
def csi_psroipooling(
cls_prob, roi, spatial_scale, output_dim, group_size, out_dtype, q_params, layer_name=""
):
"""Quantized psroipooling.
Parameters
----------
Returns
-------
result : relay.Expr
"""
return _make.CSIPSROIPooling(
cls_prob, roi, spatial_scale, output_dim, ... | 864dc29d469820f6ef09a006910aacaefce7c932 | 32,521 |
import logging
def short_links(link):
"""
Shortening a long url to a short link Byt.ly
: param link: long address
: return: string - short link Byt.ly
"""
url = 'https://api-ssl.bitly.com/v4/groups'
res = get(url=url, headers=head)
group = res.json()['groups'][0]['guid']
url = 'h... | 80b6803812933b0087d5c9d5cb1d3fb3e8f04be4 | 32,522 |
def parse_page_loaded(msg_type, target, logs, log_begin_idx):
"""
Parse WebViewPageLoadedEvent event logs
:params msg_type
:params target
:return: an instance of event.WebViewPageLoadedEvent
"""
assert len(logs) == 1
log_info = util.extract_info(logs[0])
plid, package = log_info['p... | 2721155f7b38c299100eb75cec2df1c18aaefd31 | 32,523 |
def suggest_mappings_by_content(resource, pathway_id):
"""Return list of top matches based on gene set similarity.
---
tags:
- mappings
parameters:
- name: resource
type: string
description: name of the database
required: true
... | 0dec7c0a2759a6aabb1bae5ab22973cd74b30e7f | 32,524 |
def animation(request):
"""
Controller for the streamflow animation page.
"""
context = {}
return render(request, 'sfpt/animationmap.html', context) | d42c4d0e7d51a772c115488636bf84701b9d5ee0 | 32,525 |
def kos_lookup_cmdr_embeds(session, cmdr_name, cmdr_pic=None):
"""
Look up the cmdr in the KOS db, if found return embeds that match (up to 3 closest).
Returns:
[embed, ...]: The discord.py embeds who match the cmdr_name.
[] : No matches in KOS db.
"""
if not cmdr_pic:
cmdr_... | 243f46a772e04874fd3a11c77c7ba6d3cdf439d0 | 32,526 |
def decode(s):
"""
Deserialize an MRS object from a SimpleMRS string.
"""
if hasattr(s, 'decode'):
s = s.decode('utf-8')
ms = next(_decode(s.splitlines()))
return ms | 11a5a914ab53d7de944637337b8f33315dacdb41 | 32,528 |
def fidimag_to_finitedifferencefield(sim):
"""
fidimag_to_finitedifferencefield(sim)
This function takes a Fidimag simulation object, and constructs a
Finite Difference Field object which has the magnetisation configuration
from the simulation at the last time step.
"""
cmin = np.array([sim... | b612127c457e4d8901a7bf7558210c3ea43a19c4 | 32,529 |
from typing import Tuple
def ERA_IrregularImgGrid(
lons: np.ndarray,
lats: np.ndarray,
bbox: Tuple[float, float, float, float] = None,
) -> CellGrid:
"""
Create a irregular grid from the passed coordinates.
"""
lons_gt_180 = np.where(lons > 180.0)
lons[lons_gt_180] = lons[lons_gt_180] ... | 461d98eaf7de17fa5b0fb510ce7c24698872e74e | 32,530 |
import inspect
def create_enforce_validation_serializer(serializer=None, **kwargs):
"""
Public function that creates a copy of a serializer which enforces ``must_validate_fields``.
The difference between this function and ``_create_enforce_validation_serializer``
is that this function can be used both... | 63f1e05148aa3a8190316898d4b111334bebf47b | 32,531 |
def read_FDF_cube(filename):
"""Read in a FDF/RMSF cube. Figures out which axis is Faraday depth and
puts it first (in numpy order) to accommodate the rest of the code.
Returns: (complex_cube, header,FD_axis)
"""
HDULst = pf.open(filename, "readonly", memmap=True)
head = HDULst[0].header.copy()
... | 25ab8de5ab75b7e6170a897e5bee4ec067a1c4d4 | 32,533 |
import torch
def bert_vector(text, tokenizer, model, args):
"""
BERT-based embedding.
:param text: original text to be embedded.
:param tokenizer: BERT tokenizer.
:param model: BERT model.
:param args: args.
:return: BERT embedded sentence.
"""
text = '[CLS] ' + text + ' [SEP]'
... | cbe2b74327d1e05761b922e4cc1f30cc399251ec | 32,534 |
from typing import List
from typing import Dict
def compute_benchmark_energies(molecule: tq.chemistry.Molecule,
benchmarks: List[str]) -> Dict:
"""
This uses psi4 to perforom the classical benchmarks.
"""
energy_benchmarks = {}
for method in ["hf", "mp2", "ccsd", "fc... | e8350a36c51418f6dd0cd2a571c43234577ec557 | 32,535 |
def fine_paid_message(message):
"""Returns true if the format of paid message is fine"""
return (len(message.mentions) > 0 or message.mention_everyone) and get_amount(message) is not None and message.channel.name == "expenses" and (message.content.split(" ")[0] == '!paid' or message.content.split(" ")[0] == '<@... | d545310d7606c818f9cc434db7b4caad25da9cab | 32,536 |
def print_qa(questions, answers_gt, answers_gt_original, answers_pred,
era, similarity=_dirac, path=''):
"""
In:
questions - list of questions
answers_gt - list of answers (after modifications like truncation)
answers_gt_original - list of answers (before modifications)
... | 523e474392c41971de1465ae15e1c12ac6b3d359 | 32,538 |
def compute_zhu(props,
zhu_kwargs):
"""
Compute the approximate Zhu-Nakamura hopping probabilities for
each geom in the dataset.
Args:
props (dict): dataset properties
zhu_kwargs (dict): dictionary with information about how
to calculate the hoppin... | 7ad687145e94b8a4b6eb6a3631783583d3cefdbd | 32,539 |
import html
def disaster_type_card():
"""
:return: A Div containing dashboard title & descriptions.
"""
return html.Div(
children=[
html.H6("Disaster Type"),
dcc.Dropdown(
options=[
... | 8e7ddfc88c075b035be591cd6a0ba6e068f444f8 | 32,540 |
def retrieve_context_topology_node_node_rule_group_inter_rule_group_risk_characteristic_risk_characteristic(uuid, node_uuid, node_rule_group_uuid, inter_rule_group_uuid): # noqa: E501
"""Retrieve risk-characteristic
Retrieve operation of resource: risk-characteristic # noqa: E501
:param uuid: ID of uuid
... | 73a2bcbae8cc023db6dd4378a93fb66c75d1ed11 | 32,541 |
import struct
def txt2domainname(input, canonical_form=False):
"""turn textual representation of a domain name into its wire format"""
if input == ".":
d = b'\x00'
else:
d = b""
for label in input.split('.'):
label = label.encode('ascii')
if canonical_form:
... | d5312ab1333810eaba6bac2f16e15441ea290dc9 | 32,542 |
def hstack(*args):
"""
Stacks images horizontally
If image depths are mismatched then converts grayscale images to bgr before stacking
"""
depths = [depth(im) for im in args]
gray = [d == 1 for d in depths]
if all(gray):
return np.hstack(args)
elif not all(gray):
return ... | 5e4a2278a9f5283446910d88053b52ee17e1cf6f | 32,545 |
def sample(x, n):
"""
Get n number of rows as a sample
"""
# import random
# print(random.sample(list(x.index), n))
return x.iloc[list(range(n))] | 3802f976f2a97a08945d8246093784c06fb07e67 | 32,546 |
def floor_div_mul(value, factor):
"""Fuction to get floor number."""
return (((value) // (factor))) *(factor) | 53adab5c9e0d9d5b27d36e2f77e1e7f0edd05585 | 32,547 |
def dup_div(f, g, K):
"""
Polynomial division with remainder in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ, QQ
>>> R, x = ring("x", ZZ)
>>> R.dup_div(x**2 + 1, 2*x - 4)
(0, x**2 + 1)
>>> R, x = ring("x", QQ)
>>> R.dup_div(x**2 + 1, 2*x - 4)
(1/2*x + ... | 01541d416a08613b1b400da1c6306fdce1ad29ff | 32,548 |
def append_Z_trace_vertical(path, new_point, height, ex, middle_layer=None, middle_taper=False):
"""Adds new_point to the path list plus TWO Z or S manhattan interesections.
Args:
path: list of tuples containing necessary info (pya.DPoint, layer, width)
new_point: tuple ((x, y) or pya.DPoint, la... | 17bce8bafd5c627d3e1d8b793e061816348fa086 | 32,549 |
from typing import List
def batch_ext(order: pd.Series, batch: pd.Series, classes: pd.Series,
class_list: List[str], ext: str) -> pd.Series:
"""
get minimum/maximum order of samples of classes in class_list. Auxiliary
function to be used with BatchChecker / FeatureCheckerBatchCorrection
... | eb48eee2392cb8c1db3691a38e9be97a243dc730 | 32,550 |
from typing import Tuple
import time
def chunk_push(params: dict | None = None) -> Tuple[bool | str, ...]:
"""
A helper function to push the data to database in chunks.
:param params: A dictionary that contains below structure.
{
"data_rowcount": data row count,
... | a65612d7ffbc83fa0bceb13a8d2c853aa79dcfeb | 32,551 |
def total_error_avgAx0(y_true, y_pred):
"""
"""
avgY = K.mean(y_true, axis=0, keepdims=True) # 0 is sample axis
return K.sum(K.square(y_true - avgY)) | 6fd12b66b689b4ff5b26ba6f0456927e902ec36b | 32,552 |
def var_aexp(compiler, node):
""" Variable compilation """
if node.context == 'assign':
gc = GC(compiler)
if compiler.environment.is_exist_local_var(node.name):
var = compiler.environment.get_local_var(node.name)
var_type = compiler.environment.get_local_var_runtime_type... | 003ad8a1db094516b9303e8769ceea48ef67a88b | 32,553 |
from .model_store import get_model_file
def resnet50_v1b(pretrained=False, root='~/.mxnet/models', ctx=cpu(0), **kwargs):
"""Constructs a ResNetV1b-50 model.
Parameters
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.mx... | 5357c998f5132b4121e0ec96f688177987139ff7 | 32,554 |
def _f_expl_5_cash_karp_adptv(x0, Y0, dx, *args, dYdx=None, econ=0.0001889568, eps=0.1, pgrow=-0.2, pshrink=-0.25, safety=0.9, **kwargs):
"""Explicit adaptive 5th-order Cash-Karp method
Parameters
----------
x0 : Intvar
Integration variable at beginning of scheme
Y0 : Field
Variable... | 3d50e50d2c11b1e274c6e1a88b79780132e140ae | 32,555 |
def issubset(list1, list2):
"""
Examples:
>>> issubset([], [65, 66, 67])
True
>>> issubset([65], [65, 66, 67])
True
>>> issubset([65, 66], [65, 66, 67])
True
>>> issubset([65, 67], [65, 66, 67])
False
"""
n = len(list1)
for startpos in range(len(list2) - n + 1):
... | 2f4acbba54b303b7041febbe485d8960baa6528f | 32,556 |
def make_start_and_end_images_with_words(start_words, end_words, perm: bool = False, repeat=1, size=150):
"""
Make two images from two sets of words.
:param start_words: Words to use for the first image.
:param end_words: Words to use for the second image
:param perm: Whether the words should be per... | 7ecb10eec8a447ffbc0f5f17f596dfc55e6e822b | 32,557 |
def bbox2corners(bbox):
"""
box parameters to four box corners
"""
x, y, w, h, _ = bbox.tolist()
xy_tl = [x - w/2, y - h/2]
xy_dl = [x - w/2, y + h/2]
xy_dr = [x + w/2, y + h/2]
xy_tr = [x + w/2, y - h/2]
return np.array([xy_tl, xy_dl, xy_dr, xy_tr]) | 50ac1dd1172c95b1edcf458e55759c01a593759c | 32,558 |
def clean_game_data_recent(df: pd.DataFrame, shift=False) -> dict:
"""Clean game data post mid-2018.
Follows a slightly different format than pre-2018 data.
"""
month_game_data = {}
game_type = "tables"
if shift == True: # APR_2021, MAY_2021 had no %diff, so we need to shift
add = 1
... | c2d5127b4f8b6d4e7caa03135ce257c5f6ac02a4 | 32,559 |
from typing import Dict
import re
def process_data(dataframe : pd.DataFrame,
label_to_id: Dict,
vocab : Dict = None,
vocab_size : int = 10_000,
max_tokens : int = 200,
max_token_size : int = 40) -> (tf.Tensor, tf.Tensor, dict, dict... | c30903af96f1157e08357daedacf67a146ed101c | 32,560 |
def tan_to_eq(xiDeg, etaDeg, ra0Deg, dec0Deg):
"""Convert tangential coordinates to equatorial (RA, Dec) in degrees."""
xi = xiDeg * np.pi / 180.
eta = etaDeg * np.pi / 180.
ra0 = ra0Deg * np.pi / 180.
dec0 = dec0Deg * np.pi / 180.
ra = np.arctan(xi / (np.cos(dec0) - eta * np.sin(dec0))) + ra0
... | a0e9bad863192dca391ae324f956562b092066c1 | 32,561 |
def type_from_tensors(tensors):
"""Builds a `tff.Type` from supplied tensors.
Args:
tensors: A nested structure of tensors.
Returns:
The nested TensorType structure.
"""
def _mapping_fn(x):
if not tf.is_tensor(x):
x = tf.convert_to_tensor(x)
return computation_types.TensorType(x.dtype... | 16821ca45a2000107069b992aac9a52638f2c5ea | 32,563 |
from typing import Any
def is_none_or_empty(obj: Any) -> bool:
"""Determine if object is None or empty
:param obj: object
:return: if object is None or empty
"""
return obj is None or len(obj) == 0 | a90245326e4c776ca1ee0066e965a4f656a20014 | 32,565 |
def create_python27_start_cmd(app_name,
login_ip, port, load_balancer_host, xmpp_ip):
""" Creates the start command to run the python application server.
Args:
app_name: The name of the application to run
login_ip: The public IP
port: The local port the application server will bind to
load_balanc... | 5eca494233ab5c38048cc583f564247167306594 | 32,566 |
from operator import and_
import types
import string
def create_query_constraint():
""" Create a constraint for a query WHERE clause """
op = oneOf("= < > >= <= != <>", caseless=True).setName("operator")
basic_constraint = (var + op + var_val).setResultsName("operator")
between = (
var + Suppr... | 92e3f2dcf87213126b70af7ae1dd302fc15b32e6 | 32,567 |
def reshape2D(x):
"""
Reshapes x from (batch, channels, H, W) to (batch, channels, H * W)
"""
return x.view(x.size(0), x.size(1), -1) | 29851e54bb816fb45184d3ea20e28d786270f662 | 32,568 |
from operator import add
from operator import mul
from operator import sub
def addNoise(s,x):
""" adds s percent random noise to reduce problems with zero traces """
xdif = max(x)-min(x)
n1,n2,n3 = s1.count,s2.count,s3.count
r = randfloat(n1,n2,n3)
x = add(mul(sub(r,0.5),s*xdif),x)
return x | a951f37fd48c4cf63d167189bd5674c4dc219245 | 32,569 |
def calc_cs_face_area(lon_b, lat_b, r_sphere = 6.375e6):
"""Calculate area of cubed-sphere grid cells on one face
Inputs must be in degrees. Edge arrays must be
shaped [N+1 x N+1]
"""
# Convert inputs to radians
lon_b_rad = lon_b * np.pi / 180.0
lat_b_rad = lat_b * np.pi / 180.0
... | fdc33180a49552e907d2bf683a7a829f4c1f6c47 | 32,570 |
def yices_new_param_record():
"""Creates a new param object, an opaque object that stores various search parameters and options that control the heuristics used by the solver."""
return libyices.yices_new_param_record() | b69bd915d1044703a5308ae1d4670e9905b7a180 | 32,571 |
def parse_multipart(input, boundary):
""" Parse multipart/form-data
Parse mime-encoded multipart/form-data into a
python dictionary. This function returns a tuple
consisting of post vars, and files.
Attributes:
input -- Input data to be parsed
boundary -- Field bou... | 0eef5559bf725654af6489e79c64e9ddc7658bf8 | 32,572 |
def get_fr_trj_ntrj(rslt, start, end, a_params):
"""Check whether event exhibits "blowup" behavior."""
# get spks during candidate replay event
spks_evt = rslt.spks[(start <= rslt.ts) & (rslt.ts < end), :]
# get mask over trj and non-trj PCs
pc_mask = rslt.ntwk.types_rcr == 'PC'
sgm_cu... | 7cb2f0262debba36789e4e230b4d26dd096cf950 | 32,573 |
from typing import Sequence
from typing import Any
def gapfilling(circuit: cirq.Circuit, placeholder: Sequence[Any]) -> cirq.Circuit:
"""
Fill single qubit gates according to placeholder on circuit
:param circuit:
:param placeholder:
:return:
"""
n_circuit = cirq.Circuit()
all_qubits ... | 23add843a8546bf9177da87c1bb7cb161fedc3cc | 32,574 |
import logging
def train_data_from_directory(train_path, val_path, target_size=(224, 224), batch_size=16,
rescale=1. / 255, rotation_range=20, width_shift_range=0.2,
height_shift_range=0.20, zoom_range=0.3, vertical_flip=True,
h... | d3f6906c5fb8e6eebabc1971a1430ac4d183cfeb | 32,575 |
def add_to_group(ctx, user, group):
"""Adds a user into a group.
Returns ``True`` if is just added (not already was there).
:rtype: bool
"""
result = ctx.sudo(f'adduser {user} {group}').stdout.strip()
return 'Adding' in result | abb7b432f4e4206a3509d1376adca4babb02e9f0 | 32,576 |
def ifft(X):
"""
Inverse FFT with normalization by N, so that x == ifft(fft(x)) within
round-off errors.
"""
N, x = len(X), fft(X, sign=1) # e^{j2\pi/N}
for i in range(N):
x[i] /= float(N)
return x | df388803e0a7ad91136ad174dee7d82521e60ce4 | 32,577 |
from typing import List
def _validate_fields(fields: List[_Field]
) -> List[mapry.validation.SchemaError]:
"""
Validate the correctness of the the corresponding C++ fields of a composite.
Notably, we validate that there are no duplicates and no reserved keywords
in the C++ field... | 49dfd85d473f4934b55539e7db6a707500ead547 | 32,578 |
def frames_collection(collection):
"""
returns a list of frames extracted from a collection of NAF files.
:param collection: collection of dictionaries with relevant info extracted from NAF files
:param collection: list
"""
collection_frames = []
for info_dict in collection:
for fra... | 6255a826d24bce0e26d40e7d1dbbd093c1e43a19 | 32,579 |
def execute(*cmd, **kwargs):
"""Convenience wrapper around oslo's execute() method."""
if 'run_as_root' in kwargs and 'root_helper' not in kwargs:
kwargs['root_helper'] = _get_root_helper()
return processutils.execute(*cmd, **kwargs) | 185c18c3c30305d302e8582b708e1f80069fb79a | 32,580 |
async def async_build_devices(hass, zha_gateway, config_entry, cluster_ids):
"""Build a zigpy device for each cluster id.
This will build devices for all cluster ids that exist in cluster_ids.
They get added to the network and then the sensor component is loaded
which will cause sensor entities to get ... | 5fb6900fe6bdd65f6ed68da6c51df7149679f36a | 32,581 |
import torch
def load_ckp(model, ckp_path, device, parallel=False, strict=True):
"""Load checkpoint
Args:
ckp_path (str): path to checkpoint
Returns:
int, int: current epoch, current iteration
"""
ckp = torch.load(ckp_path, map_location=device)
if parallel:
model.modu... | 4fe4e368d624583216add3eca62293d5d1539182 | 32,583 |
def show_branch_panel(
on_done,
local_branches_only=False,
remote_branches_only=False,
ignore_current_branch=False,
ask_remote_first=False,
local_branch=None,
selected_branch=None):
"""
Show a quick panel with branches. The callback `on_done(branch)` will
... | b458185b63281ab1da9d6b87047e3b8145c0d52b | 32,584 |
import torch
def map_str(string,char_encoding=default_char_encoding):
"""
Maps
"""
hold = torch.Tensor([char_encoding[x] for x in string])
hold = hold.long()
return hold | fd69d80d6bfa3fb7f55c17063f1878b3e9216526 | 32,585 |
def parse_section(section):
"""
Works out the component and section from the "Section" field.
Sections like `python` or `libdevel` are in main.
Sections with a prefix, separated with a forward-slash also show the
component.
It returns a list of strings in the form [component, section].
For ... | 06ab4f4ebb874e1a5b94c5e6736b4af4a137897f | 32,586 |
def tpm3_exon1_exon8_t_to_g():
"""Create test fixture for TPM3."""
params = {
"gene": "TPM3",
"chr": "NC_000001.11",
"start": 154192135,
"end": 154170399,
"exon_start": 1,
"exon_end": 8,
"exon_end_offset": 0,
"exon_start_offset": 0,
"transc... | 75075a328113cf0fe3639139c2f9170e96ae9a47 | 32,587 |
def ecg_rsp(ecg_rate, sampling_rate=1000, method="vangent2019"):
"""**ECG-Derived Respiration (EDR)**
Extract ECG-Derived Respiration (EDR), a proxy of a respiratory signal based on heart rate. *
Note that this implementation is far from being complete, as the information in the related
papers prevents... | d0964b33053edaf124933c762f40c1e403f7dfd7 | 32,588 |
def _get_version() -> str:
"""Returns the package version.
Adapted from:
https://github.com/deepmind/dm-haiku/blob/d4807e77b0b03c41467e24a247bed9d1897d336c/setup.py#L22
Returns:
Version number.
"""
path = '__init__.py'
version = '__version__'
with open(path) as fp:
for line in fp:
if lin... | 4811317fc7a22a11b4d074f41afebc7841577ad3 | 32,589 |
def find_misparsed_node(section_node, label, change, amended_labels):
""" Nodes can get misparsed in the sense that we don't always know where
they are in the tree. This uses label to find a candidate for a mis-parsed
node and creates an appropriate change. """
candidates = find_candidate(section_node,... | 2b6318160b8703dc963335029582f05dece42966 | 32,590 |
def degree_corrected_community_generative_model(num_nodes, class_prob,
bp_mu, bp_alpha, bp_beta,
node_theta,
burnin, end_time, n_cores=1, seed=None):
"""
Degree correct... | 7effbf8908ffe8e6b5f1df9ec7c7e52d0f1ce6cb | 32,591 |
from typing import List
from typing import Any
from typing import Generator
def neighborhood(
iterable: List[Any],
) -> Generator[Any, Any, Any]:
""" """
if not iterable:
return iterable
iterator = iter(iterable)
prev_item = None
current_item = next(iterator) # throws StopIteration i... | 4d07ee920e4861fce88658b1fc5ce719907ba897 | 32,592 |
def grafieken():
"""Deze functie maakt grafieken en plaatst ze in de template.
:return: de HTML pagina
"""
top_3_organismen_grafiek() # Functie die grafiek aanmaakt over de database
top_10_hoogste_scores() # Functie die grafiek aanmaakt over de database
return render_template('grafieken.html') | 04dfb1857f0095f135bf2484f738a5db3caf32ed | 32,593 |
import time
def path():
"""
传过来给定图片的路径即可，需要绝对路径
:return:
:rtype:
"""
jsonres = request.get_json()
#images是图片的路径
image_dir= jsonres.get('images', None)
#识别图片的路径
image_file_list = get_image_file_list(image_dir)
#把所有的图片的名字，bbox，识别结果放在一个tuple里面返回
images_result = []
for ... | c0b8f4f5df05b3153df24790c03e3904d3550f5a | 32,594 |
from operator import lt
def input_pipeline(filenames,
experiment_proto,
final_mbsz,
hps,
num_epochs=None,
num_threads=1):
"""Using Queues create an infinite stream of training minibatches.
Args:
filenames: list of ... | ea5d82b0105fc59201dd2f32b60c3560ad082270 | 32,595 |
def mAP(iou_threshold=0.5, threshold=0.01) -> CallbackProtocol:
"""Build a callback that computes mAP. All kwargs
passed to detector.mAP()"""
# pylint: disable=unused-argument
def callback(detector, summaries, data_dir):
return {
f"{split}_mAP": round(
np.nanmean(
... | 9802814db6a9c65648fd338c4b7dad43b60db25e | 32,596 |
from pathlib import Path
import time
def run_n_experiment(src_path, target_language='es', n_train=2000, n_to_copy=None, eval_tta=False,
n_test=3000,
do_baseline=True, tta_langs=('et',), **classif_kwargs):
"""Experiment on smaller version of IMBD with different augmentatio... | 52430b993954f8310e06e32466b927626dc8af3b | 32,597 |
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