content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import random
def get_random_string(length=12,
allowed_chars='abcdefghijklmnopqrstuvwxyz'
'ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789'):
"""
Returns a securely generated random string.
The default length of 12 with the a-z, A-Z, 0-9 character set return... | 7e113513331a94170948763e15d2de4415eeb0a0 | 3,616,800 |
import os
import sys
def load_cfg(cfg_path):
"""Load config file"""
# Remove a (possible) trailing file-extension from the config path
# (importlib doesn't want it)
cfg_path = os.path.splitext(cfg_path)[0]
try:
sys.path.append(os.path.dirname(os.path.realpath(cfg_path)))
cfg = impo... | 89835b566cf155b9c0523b9fff27a083661dbad1 | 3,616,801 |
def chunk_average(epochs):
"""
Because the number of trials is hugee, ~ 5000, I don't have the patience to
wait for the process and the cluster does not have the memory to process
such a huge dataset, so I will average every 10 trials to boost the
signal-to-noise ratio and decrease the number of t... | 377da889f56902cd8db00cd4e610c4936511ad3f | 3,616,802 |
def getField(statefile, fieldname):
""" Get field from MITgcm netCDF output
statefile : string with /path/to/state.0000000000.t001.nc
fieldname : string with the variable name as written on the netCDF file ('Temp', 'S','Eta', etc.)"""
StateOut = Dataset(statefile)
Fld = StateOut.variables[fieldname][:... | 808c302ac0a2daae3d5c11009391bb8bee4fab0c | 3,616,803 |
from typing import List
def get_stations_with_n_docks(num: int, stations: List['Station']) -> List[int]:
"""Return a list containing the station ids for the stations in
stations that have at least num docks available, in the same order
as they appear in stations.
Precondition: num >= 0
>>> get_s... | 9e9f1b265dc7721a031369bc996363a5e71629ac | 3,616,804 |
def apply_corrections(fluxes, filters, pd_corrections):
"""Apply pd correctionst to the fluxes by fitler."""
return np.array([flux*pd_corrections.get(filt, 1)
for flux, filt in zip(fluxes, filters)]) | 1d049fe5187e6c38b1b65ea0e9898e68a97a6178 | 3,616,805 |
import os
import pickle
import json
import warnings
def read_sim_file(file_path):
"""Read a sim file.
Parameters
----------
file_path : str
Path of the file.
Returns
-------
str, dict, pandas.DataFrame
The name, the header and the lcs of the simulation.
"""
file_... | 8ca0e4d673a7b81e7a60766715b6fd8e50b4d5c0 | 3,616,806 |
import feedparser # type: ignore
def get_posts_details(rss=None):
"""
Take link of mrss feed as argument
"""
if rss is not None:
# import the library only when url for feed is passed
# parsing partner feed
partner_feed = partner_feed = feedparser.parse(rss)
# getting lists of partner entries vi... | eee63b49ab4cf7c1746b752cb0a436b18fb7201e | 3,616,807 |
import json
def _is_json(data):
"""
Test, if a data set can be expressed as JSON.
"""
try:
json.dumps(data, cls=BlenderEncoder)
return True
except:
print_console('DEBUG', 'Failed to json.dumps custom properties')
return False | 54453b4e6dafc7d8002206c902d131cee13cec73 | 3,616,808 |
def better_repr(v, version):
"""Work around Python's unorthogonal and unhelpful repr() for primitive float
and complex."""
if isinstance(v, float):
# float values 'nan' and 'inf' are not directly
# representable in Python before Python 3.5. In Python 3.5
# it is accessible via a libr... | 30872965790d810d9600819fc2501769d4c61389 | 3,616,809 |
def XYZ2Shp(filecsv, t_srs="EPSG:4326", fileout=None):
"""
XYZ2Shp
"""
driver = ogr.GetDriverByName('ESRI Shapefile')
fileout = forceext(filecsv, "shp") if not fileout else fileout
remove(fileout)
layername = juststem(fileout)
print layername
dataset = driver.CreateDataSource(fileout... | 5b4c03c34863d1d5ee82bf2f7fbcca8fce4221ad | 3,616,810 |
import copy
def __transform_dataframe_to_event_stream_new(dataframe, stream_post_processing=False, compress=False):
"""
Transforms a dataframe to an event stream
Parameters
------------------
dataframe
Pandas dataframe
stream_post_processing
Boolean value that enables the post... | 98ca6190434cb68732ee2b554279722b252b1abb | 3,616,811 |
def backward_selection(g, n_, k_=None):
"""For details, see here.
Parameters
----------
g : function
n_ : int
k_ : int, optional
Returns
-------
s_star_bwd : list, shape(k_, 1:k_)
"""
if k_ is None:
k_ = n_
# Step 0: Initialize
s_star_backw... | cc384b6c6fca68b51d0806c498b0a7328edd2ebd | 3,616,812 |
def auc_score(y_true, y_pred):
"""Gets the auc score of labels and predictions.
Parameters
----------
y_true : torch.tensor
The true labels.
y_pred : torch.tensor
The prediction.
Returns
-------
numpy.ndarray
The auc score.
"""
y_true, y_pred = prepare... | 8e37e1ad60b1593f61d80c88b1fb6f65e5148e9f | 3,616,813 |
def _get_node_names():
"""
returns the list of nodes in the cluster
:return: the list of nodes in the cluster
:rtype: list[str]
"""
nodes = _get_nodes()
node_list = []
for n in nodes:
node_list.append(n['name'])
return node_list | 96a323e6da30c6247d7e53d7306a7d7003f25fb1 | 3,616,814 |
import collections
def defaultdict():
"""defaultdict(...): Dictionary with a value for missing keys."""
kart = collections.defaultdict(lambda: 'unknown')
kart['speed'] = 66
return "kart specs are {}".format(''.join(
'{} -> {}'.format(key, kart[key]) for key in ('speed', 'sound'))) | 71f00871b2280ce09581aa90e4645aa0424bf2de | 3,616,815 |
def execute_cast_datetime_to_integer(op, data, type, **kwargs):
"""Cast datetimes to integers"""
return pd.Timestamp(data).value | 5448a341adaae6fe58769ef43c5d0da5322aabfd | 3,616,816 |
def ferret_result_limits(efid):
"""
Abstract axis limits for the shapefile_writeval PyEF
"""
return ( (1, 1), None, None, None, None, None, ) | 9e1ef0f1ee1a0126c47e4fa46cbb5c1ee6ed52fb | 3,616,817 |
import warnings
def containment(lower_forecast, upper_forecast, actual):
"""Expects two, 2-D numpy arrays of forecast_length * n series.
Returns a 1-D array of results in len n series
Args:
actual (numpy.array): known true values
forecast (numpy.array): predicted values
"""
with ... | 7692a31337705cf5fafc9f3efb664be41e7678b7 | 3,616,818 |
def _normalize_newlines(text: str) -> str:
"""Normalizes the newlines in a string to use \n (instead of \r or \r\n).
:param text: the text to normalize the newlines in
:return: the text with the newlines normalized
"""
return "\n".join(text.splitlines()) | 6b53b42e8cec72a8e63ec0065776f47de2fba835 | 3,616,819 |
def getAxlib(libPath=None):
"""Return the handle to the axon library (CLibrary instance).
If libPath is specified, then it must give the location of the AxMultiClampMsg.dll
file that should be loaded. Otherwise, a predefined set of paths will be searched.
Note: if you want to specify the DLL file usin... | 365cd4a57036cc936b27030c2c07bec36c48a171 | 3,616,820 |
def create_stanford_article_level_model(rnn_type, embedding_matrix, sentence_size, hidden_size, dense_size, trainable=False, use_dropout=True, dropout=0.5):
"""
Create RNN model
:param rnn_type:
:param hidden_size:
:param dense_size:
:return:
"""
# Model
model = Sequential()
# E... | e611441a5c8c14ce23425bba03fb1078be13debc | 3,616,821 |
import requests, json
def backdoor(request, userid=None, view=None, list=None):
"""Provide simple client interface in Django backend."""
if not userid:
user = None # perhaps there is no user yet
username = request.GET.get('user', 'test001') # default: test001
originname = request.GE... | 10b89eb502aaefde4970c4fbc8c19d041f1d22bf | 3,616,822 |
def read_words(f, count=100, encoding="utf-8"):
"""Reads the given number of words from the specified open file."""
result = []
while len(result) < count:
line = wrapped_readline(f, encoding=encoding).strip()
words = [w.strip() for w in line.split(" ")]
# remove empty words
w... | 2d6d2a5cd086e1ccdb4ba3035f660597e098e62b | 3,616,823 |
def create_tvshow_tiles_content(tvshows):
""" The HTML content for this section of the page
"""
content = ''
for tvshow in tvshows:
# Extract the youtube ID from the url
youtube_id_match = re.search(r'(?<=v=)[^&#]+', tvshow.trailer_youtube_url)
youtube_id_match = youtube_id_match... | 9bfe36740497f70e37ad525cb0fefe06180ea419 | 3,616,824 |
def pick_from_greatests(dictionary, wobble):
"""
Picks the left- or rightmost positions of the greatests list in a window
determined by the wobble size. Whether the left or the rightmost positions
are desired can be set by the user, and the list is ordered accordingly.
"""
previous = -100
is... | 52685877620ab7f58a27eb6997ec25f3b499e3a4 | 3,616,825 |
from typing import Iterable
import os
def resolve_sources(directory: str, sources: Sources) -> Iterable[str]:
"""
Returns an iterable of absolute paths to the files specified by the sources
object. Files are not guaranteed to exist.
"""
filesystem = get_filesystem()
result = {os.path.j... | 831383b42a658287a4f555c27f1eddcde6399794 | 3,616,826 |
def replace_layer(model, layer_name, replace_fn):
"""Replace single layer in a (possibly nested) torch.nn.Module using `replace_fn`.
Given a module `model` and a layer specified by `layer_name` replace the layer using
`new_layer = replace_fn(old_layer)`. Here `layer_name` is a list of strings, each string
... | 2e0ee082d6ab8b48979aa49e303a0e12583812b7 | 3,616,827 |
def create_html_output(json_docs):
"""Create html output for the playbook by converting the docs to markdown and then converting to html."""
markdown_docs = create_markdown_output(json_docs)
return markdown.markdown(markdown_docs) | 0c59d85a06a9d8c842eaee16ec5b50dd5a7507b4 | 3,616,828 |
def has_name_pf(name_p, ignore_case=True):
"""
Predicate factory, returns true if the element name matches the pred parameter
* **name_p**: something that can be converted into a string compare predicate
* **ignore_case**: should the comparison be case sensitive (default: ignore case)
* **return**:... | 0392820f5ec7f0540f0eb4f0fbff1f9bf00bd28f | 3,616,829 |
def genInvSBox( SBox ):
"""
genInvSBox - generates inverse of an SBox.
Args:
SBox: The SBox to generate the inverse.
Returns:
The inverse SBox.
"""
InvSBox = [0]*0x100
for i in range(0x100):
InvSBox[ SBox[i] ] = i
return InvSBox | 8ddf7e338e914f6cb6c309dc25705601326160c0 | 3,616,830 |
def get_unassigned(values:dict, unassigned:dict):
"""
Select Unassigned Variable
It uses minimum remaining values MRV and degree as heuristics
returns a tuple of:
unassigned key and a list of the possible values
e.g. ('a1', [1, 2, 3, 4, 5, 6, 7, 8, 9])
"""
values_sort = dict() # em... | 32ff78f7a6443bfbf4406c420ba87e254e88d5c3 | 3,616,831 |
def countvec():
"""
对文本进行特征值化
:return: None
"""
# 实例化CountVectorizer
vector = CountVectorizer()
# 调用fit_transform输入并转换数据
# res = vector.fit_transform(["life is short,i like python","life is too long, i dislike python"])
res = vector.fit_transform(["人生苦短，我喜欢python","人生漫长，不用python"])... | c0756a9a072296e6d78001deb55d51cc9de5bf15 | 3,616,832 |
def get_auth_token_ssh(account, signature, appid, ip=None):
"""
Authenticate a Rucio account temporarily via SSH key exchange.
The token lifetime is 1 hour.
:param account: Account identifier as a string.
:param signature: Response to challenge token signed with SSH private key as a base64 encoded... | 5ca3b104b0b84bfdbd0df16e349325835970667f | 3,616,833 |
def is_superset_of(value, superset):
"""Check if a variable is a superset."""
return set(value) <= set(superset) | 8b40089430dedef72566e93eb551b35001ec2e96 | 3,616,834 |
import requests
def _poll_for_status(client_id, device_code):
"""Polls API to see if user entered the device code
This is the second step of the Device Flow. Returns an access token, and
also writes the token to a file in the user's home directory.
"""
header = {"Content-Type": "application/json... | 698e21be730a767f604a8be07d73799d8658f028 | 3,616,835 |
from datetime import datetime
def datetime_to_year(dt: datetime) -> float:
"""
Convert a DateTime instance to decimal year
For example, 1/7/2010 would be approximately 2010.5
:param dt: The datetime instance to convert
:return: Equivalent decimal year
"""
# By Luke Davis from https://st... | 5f4ae29d57d13a344e70016ab59dbc0a619db4d8 | 3,616,836 |
import struct
def read_track(chunk):
"""Retuns a list of midi events and tempo change events"""
# Deviations: The running status should be reset on non midi events, but
# some files contain meta events inbetween.
# Offset and time signature are not used.
tempos = []
events = []
deltasum... | 74340ef030a7325e904df2402d9c862371f57e32 | 3,616,837 |
def are_adjacent_empty(positions, seats):
"""Check if all seats from the positions are not OCCUPIED."""
return all(
seat != OCCUPIED
for seat in get_seats(positions, seats)
) | 9c14377a658ffd2d6ba04780fd2f407e1d338feb | 3,616,838 |
def one_component_ejecta_relation(time, redshift, mass_1, mass_2,
lambda_1, lambda_2, kappa, **kwargs):
"""
Assumes no velocity projection in the ejecta velocity ejecta relation
:param time: observer frame time in days
:param redshift: redshift
:param mass_1: mass ... | 8a4317b0fa7e33e269c4a17e74b711755a5d452b | 3,616,839 |
import json
def uhs500_msg_parsed() -> Message:
"""Expected :class:`~tslumd.messages.Message` object
matching data from :func:`uhs500_msg_bytes`
"""
data = json.loads(MESSAGE_JSON.read_text())
data['scontrol'] = b''
displays = []
for disp in data['displays']:
for key in ['rh_tally'... | 15a45da5809d29184456959adffbdbbef311c33b | 3,616,840 |
from typing import List
def brute_force_matchings(graph: Graph, partial_matchings: List[Matching]) -> List[Matching]:
"""Recursive algorithm for brute force maximum matching search"""
if len(graph.get_edges()) == 0:
return partial_matchings
updated_matchings = []
for edge in graph.get_edges():... | 3f2bb71a70f2883821b48d69b1128a8f795f9242 | 3,616,841 |
def status_check(request):
"""
JSON response for health checks.
"""
# because the argument is framework we will ignore
# pylint: disable=unused-argument
resp = {'status': 'up'}
return JsonResponse(resp) | ead0070f454b3233a9f3deb3092feae19de19c5f | 3,616,842 |
def ek_R56Q(cell):
"""
Returns the R56Q reversal potential (in mV) for the given integer index
``cell``.
"""
reversal_potentials = {
1: -96.0,
2: -95.0,
3: -90.5,
4: -94.5,
5: -94.5,
6: -101.0
}
return reversal_potentials[cell] | a61d33426e4c14147677c29b8e37381981f0d1db | 3,616,843 |
def _get_schema(cur: pyodbc.Cursor, table_name: str):
"""Get schema and table name - returned as tuple
"""
t_spl = table_name.split(".")
if len(t_spl) > 1:
return t_spl[0], ".".join(t_spl[1:])
else:
return _get_default_schema(cur), table_name | 84f25b43f1f1c0707725c2ec64540f1f1348e427 | 3,616,844 |
def poincare_tiling(p, q, nlayers, center):
"""
produce poincare regular tiling
p : number of edges per face
q : number of faces meeting at a vertex
nlayers : number of layers or rings of faces
"""
max_faces = count_faces(p, q, nlayers)
edges_out = []
verts_out = []
faces_out =... | cce0fb8f5f0d12e8fbdb524129e960ce1705f974 | 3,616,845 |
def magenta_on_white(string, *funcs, **additional):
"""Text color - magenta on background color - white. (see sgr_combiner())."""
return sgr_combiner(string, ansi.MAGENTA, *funcs, attributes=(ansi.BG_WHITE,)) | 53c230bc90442749c5d372f2a50ebf5154e6d90c | 3,616,846 |
import six
import re
def build(directory, name):
"""
Build an image using a Dockerfile at a specific path using the full name to
tag the resulting image.
Arguments:
directory (str): The directory containing the Dockerfile for the
distribution.
name (str): The full name of ... | f5699d7ca0ce4f8d5e7de7ded4e2f30d29a70dc5 | 3,616,847 |
import sys
def command_validate(opts):
"""Check a .zs file for errors or data corruption.
Usage:
zs validate [-j PARALLELISM] [--] <zs_file>
Arguments:
<zs_file> Path or URL pointing to a .zs file. An argument beginning with
the four characters "http" will be treated as a URL.
Options:
-j P... | f990a3a1964de1ae7f8d9b84d79ecb4ba604e88f | 3,616,848 |
def deriv_activation_func(func_type, z):
"""
Implements the different kind of derivated activation functions including:
line - linear function
sigm - sigmoidal
tanh - hyperbolic tangent
ptanh - smothly hyperbolic tangent
relu - Rectfied
step - Heavside (binary ste... | 1d18fe4df9ca7ef63f381581f466450355d20607 | 3,616,849 |
def createStringMacroseismicHeader(header):
"""
Function that creates NordicMacroseismic list with values being strings
:param str header: string from where the data is parsed from
:return: NordicMacroseismic object with list of values parsed from header
"""
nordic_macroseismic = [None]*22
... | 2d651e77ed0abc56116178afbab01cdb35088d18 | 3,616,850 |
def code_search(ea, val):
"""Search forward for the next occurance of val. Return None if no match."""
res = idc.FindBinary(ea, idc.SEARCH_DOWN, val)
if res == idaapi.BADADDR:
return None
else:
return res | 14b1ca9156bd081c289e78d3145ed7cb947f79c9 | 3,616,851 |
def buffer_input(data, buffer, input_data):
"""Repeats last search with 'input_data' as regexp."""
try:
cmd_grep_stop(buffer, input_data)
except:
return WEECHAT_RC_OK
if input_data in ('q', 'Q'):
weechat.buffer_close(buffer)
return weechat.WEECHAT_RC_OK
global search... | 51999ff6ed463b0033cc3e3ab19951199b4d7945 | 3,616,852 |
def read_input_files(input_file: str) -> list[Seat]:
"""
Extracts a list of valid passwords from the input file.
"""
with open(input_file) as input_fobj:
seats = [Seat.from_binary_partition(line.strip()) for line in input_fobj]
return seats | d56c78c330be9189e83dcb1cbb3baf690d806529 | 3,616,853 |
import re
import json
def mediapackage_channel_mediapackage_endpoint_ddb_items():
"""
Identify and format MediaPackage channel to MediaPackage endpoint connections for cache storage.
"""
items = []
package_key = re.compile("^(.+)Package$")
try:
# get mediapackage channels
media... | da94679df115fda6fc2dbb30e739b921f681afd4 | 3,616,854 |
def reinsert_star(seq, gapped_seq):
"""
Reinserts '*' at end of gapped alignment to make finding the end of
the aligned portion more accurate
"""
length = len(seq)
count = 0
for i in range(len(gapped_seq)):
if gapped_seq[i] == seq[count] and count == 0:
start = i
... | f4ef9428f023d655f43ca50582d3af61bddfe27e | 3,616,855 |
def _functional_groups_stable(geo, thy_save_fs, mod_thy_info):
""" look for functional group attachments that could cause
molecule instabilities
"""
# Initialize empty set of product graphs
prd_gras = ()
# Check for instability causing functional groups
gra = automol.geom.graph(geo)
... | 6f826ccf1f551f775b5bb61b8e5157e73724363a | 3,616,856 |
from typing import Callable
from typing import List
def get_table_reader() -> Callable[[Engine, Table], List[dict]]:
"""
When syncing from a relational database, currently MySQL or Postgres, the database has only a single concept of
state, that is the current state. We simply capture this state by readin... | d7d5c6349da5a779f1d8495b0851ef42fbf1fe00 | 3,616,857 |
def scene_to_raster(scene):
"""Convert scene to a integer array height x width containing color codes.
"""
pixels = simulator_bindings.render(serialize(scene))
return np.array(pixels).reshape((scene.height, scene.width)) | f4db88f58398228e58cca9dbf0662b3c0ecd89c8 | 3,616,858 |
import os
def _GetGitOrigin(path):
"""Returns the URL of the 'origin' remote for the git repo in |path|. Returns
None if the 'origin' remote doesn't exist. Raises an IOError if |path| doesn't
exist or is not a git repo.
"""
section = None
for line in open(os.path.join(path, '.git', 'config'), 'rb'):
m... | 633a6361e26d8d803b92ddef7aca1537b1241168 | 3,616,859 |
def gtk_menu_position(event, *args):
"""
Create a menu at the given location for an event. This function is meant to
be used as the *func* parameter for the :py:meth:`Gtk.Menu.popup` method.
The *event* object must be passed in as the first parameter, which can be
accomplished using :py:func:`functools.partial`.
... | 2670b4c2b3f5d7ad7fa74a836ec1b918a724c436 | 3,616,860 |
def mm2cm(v):
"""
Converts value from mm to cm
Parameters
----------
v: value
input value, mm
returns:
value in cm
"""
if np.isnan(v):
raise ValueError("mm2cm", "Not a number")
return v * 0.1 | 302377993307dbaa6011281b96a71d969c692579 | 3,616,861 |
import torch
def ssim(x, y):
"""Calculate ssim value of x (3D) in respect to y (3D).
:param x: preprocessed predicted tensor (3D)
:type x: torch.Tensor
:param y: preprocessed groundtruth tensor (3D)
:type y: torch.Tensor
"""
# pre-computation
C1 = (0.01 * 255) ** 2
C2 = (0.03 * 25... | e94d4565f694ecdc8f7e72f692861b9982e66b11 | 3,616,862 |
import math
def draw_star (im, yc, xc, radius, npoints, inner_radius=None,
v=max_image_value, fast=False, fill=False):
"""
Draw an npoints-pointed star of radius r centred at (yc, xc).
Arguments:
im image upon which the text is to be written (modified)
yc y-va... | 75193ebb73be3ab5f7c59d28fcacca9ceb5bf45f | 3,616,863 |
from typing import Any
import websockets
import json
async def songdb(timeout: int = config.TIMEOUT) -> Any:
"""
返回 ``song_id`` - 歌名(en|jp) 的字典表
"""
async with websockets.connect(config.ESTERTION_URI, timeout=timeout) as ws:
await ws.send('constants')
r = await ws.recv()
await ... | ecd751de2ad1940a7623b46bcf86d1edb16e62b0 | 3,616,864 |
def imagenet_resnet_v2_generator(block_fn, layers, num_classes, data_format=None):
"""Generator for ImageNet ResNet v2 models.
Args:
block_fn: The block to use within the model, either `building_block` or
`bottleneck_block`.
layers: A length-4 array denoting the number of blocks to include in each
... | 8d5f7ff0c19b6aa8ae88a1954759b26406c16603 | 3,616,865 |
import re
def get_api_url(request_object, production=False):
""" Get api URL and PORT
Usefull to handle https and similar
unfiltering what is changed from nginx and container network configuration
Warning: it works only if called inside a Flask endpoint
"""
api_url = request_object.url_root... | b8c9850e8379f1d49c717ecf11a2b135c2eeb88c | 3,616,866 |
from typing import List
from typing import Dict
def get_group_of_dependent_blocks(blocks: List[BuildingBlock]) -> Dict[int, int]:
"""
Building blocks can be categorized into groups. Blocks that follow each other in the graph
(that is, they are connected by one edge) belong to the same group.
:param: ... | 042b69f9b224c0451a4b81e8567151c837fe5301 | 3,616,867 |
def eval_data(dataset):
"""
Given a dataset as input returns the loss and accuracy.
"""
# If dataset.num_examples is not divisible by BATCH_SIZE
# the remainder will be discarded.
# Ex: If BATCH_SIZE is 64 and training set has 55000 examples
# steps_per_epoch = 55000 // 64 = 859
# num_ex... | cfcba534913936ba66bb0cd7002e7400383cd42b | 3,616,868 |
def list_blobs(bucket_name):
"""Lists all the blobs in the bucket."""
# bucket_name = "your-bucket-name"
storage_client = storage.Client()
# Note: Client.list_blobs requires at least package version 1.17.0.
blobs = storage_client.list_blobs(bucket_name)
return [i.name for i in blobs]
# for... | fe6e4e9d9b5ff73e43c1079d3b0a1decfcf9fafe | 3,616,869 |
def valid_header(header: BlockHeader, difficulty: int) -> bool:
"""Check if block hash matches header data."""
h = hash.hash(header['timestamp'] +
header['previous_hash'] +
header['nonce'] +
header['merkle_root'])
return (header['this_hash'] == h and
... | 8b457ec85d25bd965f27c2e55bd5078597d24395 | 3,616,870 |
def poisson_gamma(data, sum_w, sum_w2, a=1, b=0):
"""
Log-likelihood based on the poisson-gamma mixture. This is a Poisson likelihood using a Gamma prior.
This implementation is based on the implementation of Austin Schneider (aschneider@icecube.wisc.edu)
-- Input variables --
data = data histogram
... | f4d71aca26e262b127baa62526f8a6d85a6a11ea | 3,616,871 |
def a_coreProperties():
"""Syntactic sugar to construct a CT_CorePropertiesBuilder instance"""
return CT_CorePropertiesBuilder() | 4088d48518988df15daa883c310bbfb3ad1ec59b | 3,616,872 |
import copy
def model_builder(features,
labels,
mode,
params,
config,
output_type=ModelBuilderOutputType.MODEL_FN_OPS):
"""Multi-machine batch gradient descent tree model.
Args:
features: `Tensor` or `dict` of `Tensor` ... | 144432534e21074d6f9f87a00962fa8e0845e2f1 | 3,616,873 |
def dmax_curve_z(tddose, shot_y, shot_z):
"""
Return dmax Z curve for a shot
Parameters
----------
tddose: 3ddose object
contains dose and boundaries, possible symmetrized
shot_y: float
Y shot position, mm
shot_z: float
Z shot position, mm
returns: tuple of a... | d557e59a896a88dac9a572e6f35793cae7207dae | 3,616,874 |
import os
import json
def get_erc20_tokens() -> pd.DataFrame:
"""Helper method that loads ~1500 most traded erc20 token.
[Source: json file]
Returns
-------
pd.DataFrame
ERC20 tokens with address, symbol and name
"""
file_path = os.path.join(
os.path.dirname(os.path.abspat... | bb73ffaeaceca1f41381e93bb2118b45d9c87627 | 3,616,875 |
def _2samp_rotate(sim, x, y, p, degree=90, pow_type="samp"):
"""Generate an independence simulation, rotate it to produce another."""
angle = np.radians(degree)
data = np.hstack([x, y])
same_shape = [
"joint_normal",
"logarithmic",
"sin_four_pi",
"sin_sixteen_pi",
... | f0c4a7f5e4e72327359ca51962e554690b0e8e7a | 3,616,876 |
import re
def _sort_nd2_files(files):
"""
The script used on the Nikon scopes is not handling > 100 file names
correctly and is generating a pattern like:
ESN_2021_01_08_00_jsp116_00_P_009.nd2
ESN_2021_01_08_00_jsp116_00_P_010.nd2
ESN_2021_01_08_00_jsp116_00_P_0100.nd2
ESN_... | 17a034323412174beab3fd9cfb23e315a26d4d5a | 3,616,877 |
def trending_up(df: pd.Series, period: int) -> pd.Series:
"""returns boolean Series if the inputs Series is trending up over last n periods.
:param df: data
:param period: range
:return: result Series
"""
return pd.Series(df.diff(period) > 0, name="trending_up {}".format(period)) | 187dbee151d927828d1d17c02ebbb3bb079f6c0d | 3,616,878 |
def get_maxtarget(pairs):
"""
This method looks at a set of (before_label, after_label) tuples.
There are a few informative statistics from this set.
- proportion of changed labels: P(before_label != after_label)
- maximum proportional class gain: max_i(P(before_label != after_label AND after_l... | 6c1bbaa5630f455e2e10169fdcd84f9cb01eb4c6 | 3,616,879 |
def _get_formats(region=None):
"""Return the formats for the region."""
if region:
region = _clean_region(region)
if region not in _number_formats_per_region:
raise InvalidComponent()
return [_number_formats_per_region[region]]
return _number_formats_per_region.values() | f4962a46f1786bbc97a5991b5749e993efaac814 | 3,616,880 |
def jsonCatalog():
"""
The function that returns a JSON format output that contains
all database data. Including all categories and all items.
"""
output = {}
# Get all the categories from the database
categories = session.query(CatalogCategory).all()
for category in categories:
... | c7e22fa205bf648b5e6d830946317d6cf73afce1 | 3,616,881 |
import types
def argmax(values: np.ndarray) -> types.Action:
"""Argmax with random tie-breaking."""
check_numerics(values)
max_value = np.max(values)
return np.int32(np.random.choice(np.flatnonzero(values == max_value))) | 9cf697e375c1e4ba8d4e8605344bf03955cf272b | 3,616,882 |
def html_parser():
"""
Create an HTML5 parser.
"""
return HTMLParser(strict=True) | 0521cc74ae64d592d436a563cafb698fec1d8a69 | 3,616,883 |
from sys import path
from sys import stderr
def main() -> int:
"""Entry point function."""
argument_parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter)
argument_parser.add_argument("INPUT")
argument_parser.add_argument("-o", "--output", default="a.dbg")
argument_parser.add_argu... | 009fcda438b054aa8786340860449dc565562560 | 3,616,884 |
def _crop_shape(shape):
"""Calculates a new, smaller shape after cropping.
Args:
shape: A shape.
Returns:
A shape.
"""
return [int(CROP_RATIO * shape[0]), int(CROP_RATIO * shape[1]), shape[2]] | 6e329aa2f37638994d772926b826ed4cc9702e80 | 3,616,885 |
def app_context():
"""Get app context for tests
:return:
"""
return app.app_context() | ebb9160362c73876631745c9b66ed5d03a84e313 | 3,616,886 |
import scipy
def fit_linear_least_squares(X, y, weights=None):
"""Fit linear model
Returns
-------
coefs : array
XXinv : array
Inverse of (X*transpose(X)), or None if system is not full rank
"""
num_coefs = np.size(X,1)
if weights is not None:
rtw = np.diag(np.sqrt(wei... | bd193b6e6b6a130782af2e9803a0d4f5636d7c4e | 3,616,887 |
def dmp_rem(f, g, u, K):
"""
Returns polynomial remainder in ``K[X]``.
**Examples**
>>> from sympy.polys.domains import ZZ, QQ
>>> from sympy.polys.densearith import dmp_rem
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_rem(f, g, 1, ZZ)
[[1], [1, 0], []]
... | 8c03d5d2e5e110c0a323ba1997a4ad2ab1882231 | 3,616,888 |
import os
def post_process_slides_output(file, pdf, python, slides, exc=True,
nblinks=None, fLOG=None,
notebook_replacements=None):
"""
Processes a :epkg:`HTML` file generated from the conversion of a notebook.
@param file ... | 507a2af99e349bbd156dc19a5e848df3adf2e838 | 3,616,889 |
def find_data(*args):
"""find_data(ea_t ea, int sflag) -> ea_t"""
return _idaapi.find_data(*args) | 7181f508d09e980c1d8d13b76e6a570eca1a66f1 | 3,616,890 |
import array
def a_starify(search_map: array):
"""Beings an a-star search through the input numpy array.
:param search_map: Input numpy array.
:return:
"""
end_point = (search_map.shape[1] - 1, search_map.shape[0] - 1)
start_node = Node(0, 0, None, 0, end_point[0], end_point[1])
heap = []... | d025f333402a574ef7916c83a30583dd9c750b4f | 3,616,891 |
from bs4 import BeautifulSoup
def parse_search_article_result(html):
"""
解析一页搜索结果中所有的微信文章条目，包括文章标题、摘要、时间、文章来源
:param html:
:return:list
"""
soup = BeautifulSoup(html, 'html.parser')
ul = soup.find('ul', attrs={'class': 'news-list'})
res = list()
for li in ul.find_all('li'):
... | ce293b1e78b174a5343417e40cf5285f9cd46464 | 3,616,892 |
def generate_ground_image(height,
width,
focal,
principal_point,
camera_rotation_matrix,
camera_translation_vector,
ground_color=(0.43, 0.43, 0.8)):
"""Generate a... | 31ff3b82132e7bf56b0a1347c78b8ea9223833bc | 3,616,893 |
import codecs
def get_config(p):
"""Reads a config file.
:return: dict of ('section.option', value) pairs.
"""
cfg = {}
parser = ConfigParser()
parser.readfp(codecs.open(p, encoding='utf8'))
for section in parser.sections():
for option in parser.options(section):
typ... | 983ff3363e0b0f6d0e2d7f9f516d484849718d56 | 3,616,894 |
def process_key(key):
"""
返回32 bytes 的key
"""
if not isinstance(key, bytes):
key = bytes(key, encoding='utf-8')
if len(key) >= 32:
return key[:32]
return pad(key, 32) | 39fcab8fe8bb18014307d86432b3bc22c40107bf | 3,616,895 |
def dobro(valor=0, formatc=False):
"""
-> Dá o dobro de um valor.
Parâmetros opcionais
:param valor: Valor que será dobrado.
:param formatc: Booleano que indica se a formatação no valor será feita
:return: Valor dobrado com a formatação ou não.
"""
res = valor * 2
return res if not f... | dcb79b83a8e347d2fa77d1ee65756f9eedf3c301 | 3,616,896 |
def _suppression_polynomial(halo_mass, z, log_half_mode_mass, c_scale, c_power):
"""
:param halo_mass: halo mass
:param z: halo redshift
:param log_half_mode_mass: log10 of half-mode mass
:param c_scale: the scale where the relation turns over
:param c_power: the steepness of the turnover
... | e0d72ae6c092ff01864cfb74d18143b070f075c9 | 3,616,897 |
import networkx as nx
import warnings
def patch_nx():
"""Temporary fix for NX's watts_strogatz routine, which has a bug in versions 1.1-1.3
"""
# Quick test to see if we get the broken version
g = nx.watts_strogatz_graph(2, 0, 0)
if g.number_of_nodes() != 2:
# Buggy version detected. C... | 26c2a567a27b2111f23e05b6036bbae0d623fd30 | 3,616,898 |
import torch
def KLDiv_loss(x, y):
"""Wrapper for PyTorch's KLDivLoss function"""
x_log = x.log()
return torch.nn.functional.kl_div(x_log, y) | e288c3e60fab90a30693b6d5856bd2964f421599 | 3,616,899 |
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