content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import List
import collections
import heapq
def findCheapestPrice(self, n: int, flights: List[List[int]], src: int, dst: int, K: int) -> int:
"""
>>> Dijkstra's Algorithm Variation
The differences are:
1. Also track the number of stops so far;
2. Now since ... | 27a06b0ebce16e3b2389ce28d9a6548bfd1bdf8c | 3,608,900 |
def get_row_col(i, axes):
"""Get the ith element of axes
"""
if isinstance(axes, np.ndarray):
# it contains subplots
if len(axes.shape) == 1:
return axes[i]
elif len(axes.shape) == 2:
nrow = axes.shape[0]
ncol = axes.shape[1]
row_i = i ... | 20c3af7e27072225699d61e16ed7968850205a28 | 3,608,901 |
from typing import Match
from typing import Optional
from typing import Union
async def rise_score_data(payload: dict, match: Match, nickname: Optional[str] = None) -> Union[MessageSegment, str]:
"""
上分数据
- `payload` : 传递给查分器的数据
- `match` : 正则结果
- `nickname` : 用户昵称
"""
dx_ra_lowest = 999
... | b6d6bba6b75779aafcd0ce8cc530c0e086ff43da | 3,608,902 |
from ecdsa import numbertheory, ellipticcurve, util
import base64
def verify_message(address, signature, message):
""" See http://www.secg.org/download/aid-780/sec1-v2.pdf for the math """
curve = curve_secp256k1
G = generator_secp256k1
order = G.order()
# extract r,s from signature
sig = base... | d4d37d5aa93cb2e02ae956204bcb850e14bb649a | 3,608,903 |
from typing import Iterable
from re import T
from typing import Tuple
def grouped(iterable: Iterable[T], n=2) -> Iterable[Tuple[T, ...]]:
"""s -> (s0,s1,s2,...sn-1), (sn,sn+1,sn+2,...s2n-1), ..."""
return zip(*[iter(iterable)] * n) | 38caab13c4e26cb504e3155765316da9235e2a3a | 3,608,904 |
import requests
import json
def get_cards_done(board_id, app_key, user_token, board_name):
"""Fetches and returns the number of cards in the Trello list under the passed name"""
# Constructing GET request to get all lists on the board
url = "https://api.trello.com/1/boards/%s/lists?cards=all&key=%s&token... | e957313ac72fdfc3b1499a09496bece614ba7a6f | 3,608,905 |
import numpy
def w_conj_kernel_fn(kernel_fn):
"""Wrap a kernel function for which we know that
kernel_fn(w) = conj(kernel_fn(-w))
Such that we only evaluate the function for positive w. This is
benificial when the underlying kernel function does caching, as it
improves the cache hit rate.
... | c5ba5bb741e9e696a94535c4373e84268a7ab95d | 3,608,906 |
def loadWorld(worldName, store):
"""
Load an imaginary world from a file.
The specified file should be a Python file defining a global callable named
C{world}, taking an axiom L{Store} object and returning an
L{ImaginaryWorld}. This world (and its attendant L{Store}) should contain
only a sing... | 801c98b5be82e9d5c9ca19db9adbe3078f500674 | 3,608,907 |
def _cosine_dist(u, v, w=None):
"""
:purpose:
Computes the cosine similarity between two 1D arrays
Unlike scipy's cosine distance, this returns similarity, which is 1 - distance
:params:
u, v : input arrays, both of shape (n,)
w : weights at each index of u and v. array of shape (n,)... | d4252f6d79e4b1254bf79d1933ef123ff8fadc16 | 3,608,908 |
import matplotlib.pyplot as plt
from pathlib import Path
def save_fig(fig, dest=None, close=True, **savefig_kw):
"""
Saves a figure and, optionally, closes it.
The way in which the destination path is specified differs from the
one used by :meth:`~matplotlib.figure.Figure.savefig`. Moreover, if
t... | c4d23a378a461f4e4dbd4a4e982d31be505b30b2 | 3,608,909 |
import torch
def full(*args, **kwargs):
"""
In ``treetensor``, you can use ``ones`` to create a tree of tensors with the same value.
Example::
>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.full((2, 3), 2.3) # the same as torch.full((2, 3), 2.3)
tensor... | 8c6df708b76a799c27a45979e9a43b3d3678ac8d | 3,608,910 |
def funnel(base, test):
"""Tests string against the base string to determine if it can be constructed
by removing one character from the base string
str, str -> bool
>>> funnel("leave", "eave")
True
>>> funnel("eave", "leave")
False
"""
return test in get_shortened_string_list(base) | 03e0b0e223ed9c1fabdf4411eb3ea3a938917d08 | 3,608,911 |
from bs4 import BeautifulSoup
from typing import Dict
from typing import List
def extract_back_matter_from_tei_xml(
sp: BeautifulSoup,
bib_dict: Dict,
ref_dict: Dict,
cleanup_bracket: bool
) -> List[Dict]:
"""
Parse back matter from soup
:param sp:
:param bib_dict:
... | 7f830bcd4588a29281ea96e90fdba5d00f4c75c4 | 3,608,912 |
def kearsley_rotation(reference_sites, other_sites):
"""
Kearsley, S.K. (1989). Acta Cryst. A45, 208-210.
On the orthogonal transformation used for structural comparison
Added by Peter H. Zwart, Nov 3rd, 2006.
Converted to C++ by Gabor Bunkoczi, Apr 2008.
"""
return matrix.sqr(superpose_kearsley_rotation... | 2833704e69a380d1c91c2448cb39a37e49bdb941 | 3,608,913 |
def lc_virus(playing_field):
"""
From https://leetcode.com/contest/weekly-contest-63/problems/contain-virus/
A virus is spreading rapidly, and your task is to quarantine the infected area by installing walls.
The world is modeled as a 2-D array of cells, where 0 represents uninfected cells, and 1 repre... | fb3991a8c19d7cbc3599231fd7fa6a9bf0c5b7e0 | 3,608,914 |
import math
def tan(x):
"""Get tan(x)"""
return math.tan(x) | 112b52faee2f08262515086fe59b2ff978001200 | 3,608,915 |
def gelu_ad_custom(head, in_data, target="cce"):
"""
Automatic differentiation of gelu with customize function.
In order to achieve higher precision, we could also self-define tanh part differentiate with simplify calculation.
"""
dtype = in_data.dtype
const1 = akg.tvm.const(0.044715, dtype)
... | aec594eed9954e79cf16a36a4e50911c9a7991f1 | 3,608,916 |
def ParticleFactory(variables, name="SamplingParticle", BaseClass=parcels.JITParticle):
"""Create a Particle class that samples the specified variables.
The variables that should be sampled will be prepended by ``var_`` as
class attributes, in case there are any namespace clashes with existing
variable... | 5c09acf1cc4a1ce3a3fdad7cbaf026cb5533a467 | 3,608,917 |
def piece_placed(x, y, player, board):
"""This function determines the piece played.
It takes the coordinates of the piece, the player number, and the board.
The pieces are zeros or ones and the function returns the piece on the board based on the number."""
if player == 0:
board[x][y] = 1
e... | ffcd46e11c3e5b0704ed66d6010dfc227106c752 | 3,608,918 |
def get_max_unsecured_debt_ratio(income):
"""Return the maximum unsecured-debt-to-income ratio, based on income."""
if not isinstance(income, (int, float)):
raise TypeError("Expected a real number.")
# Below this income, you should not have any unsecured debt.
min_income = 40000
if income <... | ffff63807842197e2f60ebfd29b54ecf895f6279 | 3,608,919 |
import glob
import shutil
def merger():
""" Function to combine all results csv into a single file. """
#import csv files from folders
path = r'C:/Users/luxon/OneDrive/Research/McQuade/Projects/NSF/OKN/phase1/Work/ml-hte-results-20200207' # Adam's tablet. will vary by OS, computer
# path = r'C:/Use... | 8b96d569cef54636cc009df797061b45c31c264b | 3,608,920 |
def calc_other_bias(probs):
"""
:param probs: list of negative log likelihoods for a corpus
:return: gender bias in corpus
"""
bias = 0
for idx in range(0, len(probs), 16):
bias -= probs[idx + 1] + probs[idx + 3] + probs[idx + 5] + probs[idx + 7]
bias += probs[idx + 8] + probs[id... | 2ceb6788e22277192475218db6e3175f259dc9ba | 3,608,921 |
def pubkey_to_merkletree(key, hashfunction, salt, prefix=""):
"""Convert a full signing-key pubkey into a merkletree dictionary"""
drval = dict()
part1 = key[0]
part2 = key[1]
if len(key) > 2:
breakpoint = int(len(key)/2)
part1, dpart1 = pubkey_to_merkletree(key[:breakpoint], hashfun... | 50e5283a7189aa0202e93201d70f7343719f1f13 | 3,608,922 |
import os
def images_data_set(data_set, args, session_file):
"""Adding images information when the data_set contains the images
directory.
"""
try:
args.images_dir = None
args.images_file = None
if os.path.isdir(data_set):
# When data_set is a directory, we assume ... | 4612e8946b37bbe2b52ae7756a5cfa6294039db4 | 3,608,923 |
def generate_test_case(num_nodes=500, num_edges=1000, num_communities=5,
connecting_strength_among_communities=0.01, random_state=None):
"""
:param num_nodes: int
:param num_edges: int
:param num_communities: int
:param connecting_strength_among_communities: float
:param r... | 417f4bf0a4c2089796dcdd2de749225c86bdb7b0 | 3,608,924 |
def deprocess_image(x):
"""normalize tensor: center on 0., ensure std is 0.1"""
x -= x.mean()
x /= (x.std() + K.epsilon())
x *= 0.1
# clip to [0, 1]
x += 0.5
x = np.clip(x, 0, 1)
# convert to RGB array
x *= 255
if K.image_data_format() == 'channels_first':
x = x.transpo... | 3ecf94411855e3a212fc0ebe2b60ff76bf30efd3 | 3,608,925 |
def DFFN_3tower_5depth(x_dict, dropout, reuse, is_training, n_classes):
"""Three towers. Each depth 5.
This is the train_paviaU network when input is 23.
20 steps/second.
94.5% on PaviaU 2%, lr 5e-5, within 10k
"""
with tf.variable_scope('DFFN', reuse=reuse):
x = x_dict['s... | 9945092ba2c983b218c0c8d9351aaede6f807a80 | 3,608,926 |
def build_list_all_request(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
"""List scan rulesets in Data catalog.
See https://aka.ms/azsdk/python/protocol/quickstart for how to incorporate this request builder into your code flow.
:return: Returns an :class:`~azure.purview.scanning.core.res... | 4b2cbf297ec89855f794bd0bb9046f525f23a7fa | 3,608,927 |
from typing import Any
import json
def is_jsonable(x: Any):
"""
Check if an object is json serializable.
Source: https://stackoverflow.com/a/53112659
"""
try:
json.dumps(x)
return True
except (TypeError, OverflowError):
return False | 3735de8bd1940d84c185142c0a4387366d7cd9c2 | 3,608,928 |
def plot_cumvar_pca(data,title):
"""Plots the cumulative variance explained by PCA for different
number of components"""
fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(10,8))
pca = PCA().fit(data)
axes[0,0].plot(np.cumsum(pca.explained_variance_ratio_),'bx',alpha=0.6)
axes[0,1].plot(np.cumsu... | e2e6758af3bc203df76f12d60be0b83ad8163036 | 3,608,929 |
def add_number_of_different_roles(dev_type: str) -> int:
"""
INPUT
dev_type - dev_type answer (separeted by ';')
OUTPUT
numeric value - number of different dev types
"""
try:
return len(dev_type.split(';'))
except:
return 0 | 78872b9101b128cc107a0194fc85b353f1d2f836 | 3,608,930 |
import time
def try_models(models, X_train, y_train, preprocessor):
""" Fits different regression models on the given
dataset and evaluates the mean absolute error.
Parameters
----------
models : dict
Dictionary of various regression models to try.
X_train : DataFrame
Traini... | 4d7c1acd19ef425ebb7185cb805ddf805af55619 | 3,608,931 |
def FormatCommentWithAnnotations(comment, type_name=''):
"""Format a comment string with additional RST for annotations.
Args:
comment: comment string.
type_name: optional, 'message' or 'enum' may be specified for additional
message/enum specific annotations.
Returns:
A string with additional ... | accf33ab834e9aeada2c3edfbd83427935e5e130 | 3,608,932 |
def _todict(matobj):
"""
A recursive function which constructs from matobjects nested dictionaries.
"""
dict = {}
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
if isinstance(elem, spio.matlab.mio5_params.mat_struct):
dict[strg] = _todict(elem)
else:... | cc5c594cecdb88183b36ce4be5b8c01424847936 | 3,608,933 |
def create_network_with_bn():
"""Creates a network contains both QConv2D and QDepthwiseConv2D layers."""
xi = Input((28, 28, 1))
x = Conv2D(32, (3, 3))(xi)
x = BatchNormalization()(x)
x = Activation("relu")(x)
x = DepthwiseConv2D((3, 3), activation="relu")(x)
x = BatchNormalization()(x)
x = Activation(... | 22a167a15326cc6d8830c6498402b45c91587c02 | 3,608,934 |
def GetBigQueryTableID(tag):
"""Returns the ID of the BigQuery table associated with tag. This ID is
appended at the end of the table name.
"""
# BigQuery table names can contain only alpha numeric characters and
# underscores.
return ''.join(c for c in tag if c.isalnum() or c == '_') | 0fe659fd3c7ca3df5f061289dad5635841146901 | 3,608,935 |
import os
def _dst_path(config, entry):
"""Construct output path for entry."""
return os.path.join(config["dst"], entry["slug"], MAIN_DST_FILE) | 0b13cd7257e6fc3e92c5c533de7781d6b435e28d | 3,608,936 |
import timeit
from typing import DefaultDict
def dnscl_rpz(ip_address: str) -> str:
"""Return RPZ names queried by a client IP address.
Args:
ip_address (str): IP address to search.
Returns:
str: Search results found.
"""
start_time = timeit.default_timer()
rpz_dict: Default... | 0916933d64f5fca1145f3c1d31bbc6e8ae82c139 | 3,608,937 |
def rf_local_unequal_int(tile_col, scalar):
"""Return a Tile with values equal 1 if the cell is not equal to a scalar, otherwise 0"""
return _apply_scalar_to_tile('rf_local_unequal_int', tile_col, scalar) | ca9200dd94b786ae258ec2f91dca9934f280dd01 | 3,608,938 |
def get_process_list(node: Node):
"""Analyse the process description and return the Actinia process chain and the name of the processing result
:param node: The process node
:return: (output_objects, actinia_process_list)
"""
input_objects, process_list = check_node_parents(node=node)
output_o... | e14ecb3d43c1329cf707a21bb11c933e84875712 | 3,608,939 |
def run_text(query_string):
"""Run a query that should only return string contents."""
contents, types, result = run(query_string)
assert types is None
assert result is None
return contents | 6201bdde6a5fb42603b3d9a7e67629bb368dfc72 | 3,608,940 |
def Value_getNullValue():
"""Value_getNullValue() -> Value"""
return _yarp.Value_getNullValue() | efae2c7810f2ae277e10d68c0e6640e7d760982b | 3,608,941 |
def transform_landmark(landmark, t):
"""
Function applies transformation t to a single landmark represented by its coordinates in space.
It first creates poly data from its positions and then applies given transformation.
:param landmark: (x, y, z) coordinates of landmark to be transformed
:param t... | f058ba9060ba1e7f718c8c9d87e7cf332592ce27 | 3,608,942 |
import requests
def find_location(location):
"""
Takes a location as a string, and returns a dict of data
:param location: string
:return: dict
"""
params = {"address": location, "key": dev_key}
if bias:
params['region'] = bias
json = requests.get(geocode_api, params=params).j... | 44381de26b3db10e00b0f03be2a5b2da14dcf812 | 3,608,943 |
import token
import time
def sign_url_path(url, secret_key, expire_in=None, digest=None):
# type: (str, bytes, int, Callable) -> str
"""
Sign a URL (excluding the domain and scheme).
:param url: URL to sign
:param secret_key: Secret key
:param expire_in: Expiry time.
:param digest: Specif... | 946d0ae6d704d5a6b9da8517f1b37563471761cb | 3,608,944 |
from typing import Dict
from typing import List
def get_label_colour_map() -> Dict[str, str]:
"""converts a comma seperated list of organizations/repositories into a list
of tuples.
"""
def _preproc(label_colour: str) -> List[str]:
return label_colour.lower().split(sep="/")
return {
... | 440092d8f31fab679761453ec7abc8fb37b5f5d8 | 3,608,945 |
def log_modulo(a, b, m):
"""Computes discrete logarithm i.e.
finds x such that a^x = b (mod m)
Uses Shanks algorithms which takes O(sqrt(m)) time
"""
# find x in form x = np - q for some (n, p)
# => a^x = b ~ a^np = a^q * b
a, b = a % m, b % m
n = isqrt(m) + 1
# compute all a^q * b
... | 6f2c2afd9858ba7d3baaaa2e871cc336396d2042 | 3,608,946 |
import os
def temp_video_path():
"""
Defines default video path to write to for testing.
"""
return os.path.join(robomimic.__path__[0], "../tests/", "tmp.mp4") | 724af72e70f87de3c3fdfd985e7240243853726c | 3,608,947 |
def _linear_transform(src, dst):
""" Parameters of a linear transform from range specifications """
(s0, s1), (d0,d1) = src, dst
w = (d1 - d0) / (s1 - s0)
b = d0 - w*s0
return w, b | 7f55a2617721fdefcc724bcb8ce9f880d7bcd846 | 3,608,948 |
def feature_within_s(annolayer, list_of_s):
"""Extracts all <annolayer> from all sentence-elements in list_of_s;
returns a flat list of <annolayer>-elements;
"""
list_of_lists_of_feature = [s.findall('.//' + annolayer) for s in list_of_s]
list_of_feature = [element for sublist in list_of_lists_of_fe... | df6ed3603381a4b8d2ea12fc483fa37ea3068372 | 3,608,949 |
def _permute_facets(facets, ori, ori_map):
"""
Return a copy of `facets` array with vertices sorted lexicographically.
"""
assert_((in1d(nm.unique(ori), ori_map.keys())).all())
permuted_facets = facets.copy()
for key, ori_map in ori_map.iteritems():
perm = ori_map[1]
ip = nm.wh... | 0e09ad2b7555be8e77e564266e3920e5413d851e | 3,608,950 |
def showname(keyvalue):
"""filter koji za neku od prosledjenih kljuceva vraca vrednost"""
key_dict ={'P':'Accepted','C': 'Created','Z': 'Closed','O': 'On Wait'}
return key_dict[keyvalue] | 59453d5e0dd31696b99d01c8b927297adddec10c | 3,608,951 |
def findDomainRanges(r,r_surf_index,W,oldMiddleRange):
"""
Because the islands grow and shrink, the location of the boundaries are in
constant flux. This code figures out the boundaries and returns the
indices associates with all three regions.
"""
innerBCIndex=findNearest(r,r[r_surf_index]-W/2)
if innerB... | db213209e4bed1daf9d3e18ceb8f0e30db5d875e | 3,608,952 |
def create_taperedvia(AR, dr, Nseg):
"""Return the areas and view factor of a rectangular trench, where
the vertical wall is divided into identical sections.
Parameters
----------
AR : float
Aspect ratio, defined as the width to top diameter ratio
dr : Float
Ratio between the bo... | 408077ec50272236da497b93ec897213ae6b30eb | 3,608,953 |
import torchvision
import torch
def get_train_val_loaders(train_dir,
collate_fn,
height,
width,
no_data_augmentation=False,
max_trainset_size=np.infty,
seed=0,
... | 675be081fa34ad2c282674dbb59a9e81cb36581d | 3,608,954 |
def adjust_learning_rate(optimizer, epoch, gammas, schedule):
"""Sets the learning rate to the initial LR decayed by 10 at 600 and 900 epochs"""
lr = args.lr_
assert len(gammas) == len(schedule), "length of gammas and schedule should be equal"
for (gamma, step) in zip(gammas, schedule):
if (epoc... | 5fb413f4403aa9606758134929f684d2dd03a621 | 3,608,955 |
def get_organizations_from_ckan(portal_url, verify_ssl=False,
requests_timeout=REQUESTS_TIMEOUT):
"""Toma la url de un portal y devuelve su árbol de organizaciones.
Args:
portal_url (str): La URL del portal CKAN de origen.
verify_ssl(bool)... | fd280b3106d84b66c893877657f5ec0b3b2dc635 | 3,608,956 |
def processPostMessage(post_message, status_type):
"""
Check if the message is >500 characters
If it is, shorten it to 500 characters
Ouput: a tuple of strings: read_more (empty if not shortened), post text
"""
if len(post_message) > 500:
post_message = post_message[:500]
last_sp... | 2d21ec04ef863b57f95bb4b8256f2195559e6f8e | 3,608,957 |
def linkHasRel(link_attrs, target_rel):
"""Does this link have target_rel as a relationship?"""
# XXX: TESTME
rel_attr = link_attrs.get('rel')
return rel_attr and relMatches(rel_attr, target_rel) | f2a264dbb922d7c2c5318e9564744334f994454e | 3,608,958 |
def _focus_measurement_3d(image, neighborhood_size):
"""Helmli and Scherer’s mean method used as a focus metric.
Parameters
----------
image : np.ndarray, np.uint8
A 3-d tensor with shape (z, y, x).
neighborhood_size : int
The size of the square used to define the neighborhood of ea... | f830fc867177fdc4232938da03e433a2a5aa9d0a | 3,608,959 |
from mmdet.models import SSDHead
def get_ssd_head_model():
"""SSDHead Config."""
test_cfg = mmcv.Config(
dict(
nms_pre=1000,
nms=dict(type='nms', iou_threshold=0.45),
min_bbox_size=0,
score_thr=0.02,
max_per_img=200))
model = SSDHead(
... | d46ea93f0245be1636f0f10497154724c9564f3c | 3,608,960 |
def save_gan_images(generator, epoch, examples=100, dim=(10, 10), figsize=(10, 10)):
"""
Generate a sample of examples.
"""
noise = get_noise(examples)
generated_images = generator.predict(noise)
generated_images = generated_images.reshape(examples, 28, 28)
plt.figure(figsize=figsize)
f... | 2ad954a072e85247990204061566f9bbf6238094 | 3,608,961 |
import datasets
def load(dataset_info: datasets.DatasetInfo) -> testbed_base.TestbedProblem:
"""Load a regression problem from a real dataset specified by config."""
num_enn_samples = 1000 # We set it to the number we use for our testbed
train_data, test_data = load_dataset(name=dataset_info.dataset_name)
d... | de7700759da4aa8b18fc87f8d663720fd3fc4962 | 3,608,962 |
def calc_blue(historys):
"""
{
1: [0.16, 0.16, 0.15, ...],
2: [0.16, 0.16, 0.22, ...],
...
12: [0.16, 0.16, 0.3, ...],
}
"""
blues = [history['result']['blue'] for history in historys]
result = dict()
for num in range(1,13): #12选2
# result.setdefault(n... | 44e391adc8db7c85ecd45c533ce0e12485866113 | 3,608,963 |
def get_transition_analysis_matrices(odf_order, angle_max,
angle_weight="flat", angle_weighting_power=1.):
"""
Convenience function that creates and returns all the necessary matrices
for iodf1 and iodf2
Parameters:
-----------
odf_order: "odf4", "odf6", "odf8" or "odf1... | aab9fa68b11e2f47acb32507e3e72422fdaea1b0 | 3,608,964 |
def condition_match(row, condition):
"""Return whether a condition matches a row
:param row An OVSDB Row
:param condition A 3-tuple containing (column, operation, match)
"""
col, op, match = condition
val = get_column_value(row, col)
matched = True
# TODO(twilson) Implement othe... | 49bdf006fc47e5eda628798033b9eabeb0551034 | 3,608,965 |
def expected_wait_time_random_arrival(xdata,wdata,headway,
nsims = 5000000, ntrips=3,
q_half=None):
"""
Given R-Vector xdata representing instances and R-Vector wdata
representing weighted probabilities of those instances (need not
add ... | ee1369516d3ee13e48c1b185fdab5b0b4278e6fc | 3,608,966 |
def main(global_config, **settings):
"""
Returns a Pyramid WSGI application. Apart from the clld boilerplate, it
orders the home sub-navigation and registers the get_map_marker hook.
"""
config = Configurator(settings=settings)
config.include('clld.web.app')
config.registry.settings['home_c... | 71c845c2b6d190cfc7ac1845ddc7f3152c838ebd | 3,608,967 |
import yaml
def open_yaml(yfile):
"""
This function opens file with YAML configuration.
:param yfile: Name of file.
:return: Python object ( nested lists / dicts ).
"""
with open(yfile, 'r') as stream:
yamlobj = yaml.load(stream)
return yamlobj | 0a76866a8430cd917518fe620fa7c346cdca7edb | 3,608,968 |
def get_instance_path(index_instance):
"""
Return a platform formated filesytem path corresponding to an
index instance
"""
names = []
for ancestor in index_instance.get_ancestors():
names.append(ancestor.value)
names.append(index_instance.value)
return assemble_path_from_list(... | 5144a9f6bf9b88b36bec6d6c556448a2450b788c | 3,608,969 |
def download_media_suite(request, domain, app_id):
"""
See Application.create_media_suite
"""
if not request.app.copy_of:
request.app.set_media_versions(None)
return HttpResponse(
request.app.create_media_suite()
) | bbbefb1eb20a404811baf70d42b389b74301e869 | 3,608,970 |
def current_token() -> object:
"""Return a backend specific token object that can be used to get back to the event loop."""
return get_asynclib().current_token() | d456fef0117d64ce51050171dfb4ae82f8dba45c | 3,608,971 |
import base64
def _derive_sha256_key(passwd):
"""Derive a base64 encoded urlsafe digest from password.
Using the given password, an irreversible hash is derived using
cryptography algorithm. To make use of this for Fernet encryption,
it is transformed to base64 encoded urlsafe digest.
:param str... | 4e92a76dca0f99ee0f38d5ba922762396da51d91 | 3,608,972 |
def runAllTces(tceFile,sector,outfile):
"""
Run for all TCEs
"""
df=p.read_csv(tceFile,comment='#')
for index,row in df[37:38].iterrows():
clip = runOneDv(sector,row.ticid,row.planetNumber)
text,header = outputInfo(clip)
#Write out decision
with open(ou... | c1474d79041b904d36fc4a4c2e2b3c90258a00fc | 3,608,973 |
def data_for_keys(data_dict, data_keys):
"""
Return a dict with data for requested keys, or empty strings if missing.
"""
return {x: data_dict[x] if x in data_dict else '' for x in data_keys} | b844ae2dba804e179e7e8dd08166f392a90e7f7a | 3,608,974 |
def new_uniformly_random_array_list(low, high, shapes):
"""
This function returns a list whose kth entry is an array with shape=
shapes[k] and with entries selected uniformly at random from
the interval [low, high].
Parameters
----------
low : float
high : float
shapes : list[tuples... | 5e4d1a9d2ed1a5e367ef14a6b6941a5429bd6edf | 3,608,975 |
def distinct_values_bt(bin_tree):
"""Find distinct values in a binary tree."""
distinct = {}
result = []
def _walk(node=None):
if node is None:
return
if node.left is not None:
_walk(node.left)
if distinct.get(node.val):
distinct[node.val] =... | 8d84d57559a0c813e7ac12199680172a9b591be9 | 3,608,976 |
import subprocess
def runshell(cmd):
""" Run a shell command. if fails, raise an exception. """
p = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
if p.returncode != 0:
err = "Subprocess: \"{0}\" failed, std err = {1}".format(str(cmd), str(p.stderr))
raise RuntimeError... | d5a617cec03fe70d601f496f9f62b6c30fcdbd1e | 3,608,977 |
def create_filename_template(request):
"""creates a new FilenameTemplate
"""
logged_in_user = get_logged_in_user(request)
# get parameters
name = request.params.get('name')
target_entity_type = request.params.get('target_entity_type')
path = request.params.get('path')
filename = request... | 5cdf50e32ce3b26c86735c8e93aafea880f6ab91 | 3,608,978 |
def custom_slugify(data, suffix=True, offset=15):
"""
Using django util methods create a slug.
Append a random string at the end of the slug if necessary for making it unique
"""
# slugify the source_field passed to the function
new_slug = slugify(data)[:offset]
if suffix:
# get a ... | f4119e3fd6c3e2089376a93cc8dc360983b428f6 | 3,608,979 |
def filter_output(filter_callbacks, kwargs, obj, missing_ok=False):
"""Filter ouput.
For each key in filter_callbacks, if it exists in kwargs,
kwargs[key] tells what we need to filter. If the call of
filter_callbacks[key] returns False, it tells the obj should be
filtered out of output.
"""
... | cd9f6b1b68b0155a8f00986ae4619ffd4119dabf | 3,608,980 |
def fix_iobtag(iob, DESC_DECISION):
""" This is specific to the BBN Corpus; the reason some of the entity
labels are being modified:
1) Errors in the original labeling, or
2) Not enough labels of the given category
The parameter DESC_DECISION can be 'keep', 'merge' or 'remove', which
determine... | 2743e7d36c7d8153a7cf6694a69e9a212219ae8f | 3,608,981 |
from typing import List
def get_answered_questions(question_list: List[List[bytes]]) -> list:
"""Dont let the type hint confuse you, problem of not using classes.
It takes the result of get_question_list(file_list)
Returns a list of questions that are answered.
"""
t = []
for q in quest... | d485b374721f445ab62853eaa67de65bd2a893e2 | 3,608,982 |
import gettext
def profile_update():
"""
用户信息更新
:return:
"""
gender = request.argget.all('gender', 'secret')
birthday = request.argget.all('birthday')
homepage = request.argget.all('homepage')
address = json_to_pyseq(request.argget.all('address', {}))
info = request.argget.all('inf... | e7fa3fe06c2fd7f76cf4f39f71001af3630dc308 | 3,608,983 |
def keywords_volume_query_id(request, keywd, query_id, format=None):
"""
Retrieve related queries
"""
ip_address = request.META['REMOTE_ADDR']
if valid_ip(ip_address) is False:
return Response("Not authorised client IP", status=status.HTTP_401_UNAUTHORIZED)
print "in view:" + str(keywd... | e94514c5cf58ff31c22205ad4c96f5caeb943212 | 3,608,984 |
def drafts(request):
"""
The function is used to get all the files created by user(employee).
It gets all files created by user by filtering file(table) object by user i.e, uploader.
It displays user and file details of a file(table) of filetracking(model) in the
template of 'Saved f... | d9993ba1c69c5abfc52e14096759bad0a51868b4 | 3,608,985 |
from typing import Union
def _data_period(index) -> Union[pd.Timedelta, Number]:
"""Return data index period as pd.Timedelta"""
values = pd.Series(index[-100:])
return values.diff().dropna().median() | 87d00003072dd364efee89c3f1b6d4a3843211b0 | 3,608,986 |
def chain_callbacks(f):
"""Decorate to mimic the promise pattern via an yield expression.
Decorator function to make a wrapper which executes functions
yielded by the given generator in order.
"""
@wraps(f)
def wrapper(*args, **kwargs):
chain = f(*args, **kwargs)
try:
... | 616914636a806c5e92ffbc5b79b3b97f20d03490 | 3,608,987 |
import json
def well_known_did (mode) :
""" did:web
https://w3c-ccg.github.io/did-method-web/
https://identity.foundation/.well-known/resources/did-configuration/#LinkedDomains
"""
address = mode.owner_talao
# secp256k
pvk = privatekey.get_key(address, 'private_key', mode)
key = helpe... | 15610de05d529b4721790c8e2dd89c93cb64d8ce | 3,608,988 |
def generate_blobimage(shape, blobs):
"""function to generate blob images from an image shape and blob
coordinates and sigmas
:param shape:shape of image to generate
:param blobs: array with blob coordinates and sigma in last column"""
img = np.zeros(shape, dtype=np.float)
if blobs is None:
... | 2e046e53163058dbda3cb2df490cbe1ef1a7433e | 3,608,989 |
def _update_or_delete(host, ipaddr, secure=False, logger=None, _delete=False):
"""
common code shared by the 2 update/delete views
:param host: host object
:param ipaddr: ip addr (v4 or v6)
:param secure: True if we use TLS/https
:param logger: a logger object
:param _delete: True for delet... | 1011c455d0d3ca6e484a29e9b9147333f687ff76 | 3,608,990 |
def split_data_list(list_data, num_split):
""" list_data: list of data items
returning: list with num_split elements,
each as a list of data items
"""
num_data_all = len(list_data)
num_per_worker = num_data_all // num_split
print("num_data_all: %d" % num_data_all... | 7282d1ae89f830d5b48fa73ea3d355cd63344f5c | 3,608,991 |
import re
def _find_breakpoint(line, break_pattern=', ', nmax=80):
""" determine where to break the line """
line = _remove_comment(line)
locs = [m.start() for m in re.finditer(break_pattern, line)]
if len(locs) > 0:
break_loc = locs[np.where(
np.asarray(locs) < (nmax - len(break_p... | 553dfe3a088fb16b5abb52ace1078b18917904ae | 3,608,992 |
import argparse
def get_input_args():
"""
Retrieves and parses the command line arguments created and defined using
the argparse module. This function returns these arguments as an
ArgumentParser object.
3 command line arguments are created:
dir - Path to the pet image files(default- 'pet_... | 7ab44bbbd2163c96eb337beff4fd2eb5e2a0ffba | 3,608,993 |
def patch_set_approved(patch_set):
"""Return True if the patchset has been approved.
:param dict patch_set: De-serialized dict of a gerrit change
:return: True if one of the patchset reviews approved it.
:rtype: bool
"""
approvals = patch_set.get('approvals', [])
for review in approvals:
... | af7e56be45e537be9308f0031fe3923425afd48c | 3,608,994 |
def _load_one_df(date):
"""Helper function for load_merged_summary in multiproc pool."""
# print(f'({date}) ', end='', flush=True)
print('.', end='', flush=True)
return load_casus_summary(date).reset_index() | 8ad388d312359a6e77439d90d1189d5a47f424cd | 3,608,995 |
import torch
def mean_tour_len_edges(x_edges_values, y_pred_edges):
"""
Computes mean tour length for given batch prediction as edge adjacency matrices (for PyTorch tensors).
Args:
x_edges_values: Edge values (distance) matrix (batch_size, num_nodes, num_nodes)
y_pred_edges: Edge predicti... | dc15b22fb6625ef7c8fcf4e518a617dd0a109c55 | 3,608,996 |
import os
def get_files_with_ext(path, str_ext, flag_walk=False):
""" get files with filename ending with str_ext, in directory: path
"""
list_all = []
if flag_walk:
# 列出目录下，以及各级子目录下，所有目录和文件
for (root, dirs, files) in os.walk(path):
for filename in files:
... | 1a8ade0b5efead0b6260430145e601d98f6fa057 | 3,608,997 |
import requests
import time
import re
def nrel_bcl_api_request(data):
"""Send a request to the Building Component Library API via HTTP GET and
return the JSON response.
Args:
data (dict or OrderedDict): key-value pairs of parameters to post to the
API
Returns:
dict: the j... | e0a32ce733f97dda0302a14b160af2eefb5f565d | 3,608,998 |
import shutil
def install(
kernel_spec_manager=None,
user=False,
kernel_name=KERNEL_NAME,
display_name=None,
prefix=None,
):
"""Install the Picky kernelspec for Jupyter
Parameters
----------
kernel_spec_manager: KernelSpecManager [optional]
A KernelSpecManager to ... | 7360f8b23f4b2ee8b005b3e3bb6e5de1fd88fb9d | 3,608,999 |
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