content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _get_password(email):
"""
gets the password from the keychain
"""
return keyring.get_password('mspass', email) | c6deaf235bbfb5fadabc4dc31b667c58d0ede1fd | 80,519 |
import math
def millify(n):
"""
Return a human readable number.
"""
n = float(n)
millidx = max(
0,
min(
len(millnames) - 1,
int(math.floor(0 if n == 0 else math.log10(abs(n)) / 3)),
),
)
return '{:.0f}{}'.format(n / 10**(3 * millidx), millna... | 7ae535df908a71caa25dabc499eb17bba0707590 | 80,520 |
def load_token(token):
"""
Flask-Login token_loader callback.
The token_loader function asks this function to take the token that was
stored on the users computer process it to check if its valid and then
return a User Object if its valid or None if its not valid.
"""
# The Token itself was... | e4d5ced16d6f6cf68f030d5eacb337e3f1279361 | 80,521 |
def get_minutes_remain(minutes: int) -> int:
"""
Returns minutes remaining after converting to hours
:param minutes: Total minutes before converting to hours
:return: minutes after converting to hours
"""
return minutes % 60 | abf025a83804a03d2c41b88eaac35606a5eddc4c | 80,522 |
def critSC3(theta, z_c, jet_type='quark', alpha=alpha_fixed):
"""A soft-collinear piece of the critical, running
coupling radiator, as a function of theta.
Kicks in at low theta, theta < 2 MU_NP
"""
sc = (-(2.*alpha*beta_0)*np.log(2.*z_c)
* np.log(2.*MU_NP/theta)
/
(1.... | 1c9953b69b455b74d8fe87a137800e9bd535d48c | 80,523 |
from datetime import datetime
def last_x_days(days=5):
"""Return the last X days as string names YYMMDD in a list"""
dt = datetime.now()
dates = [dt + timedelta(days=-x) for x in xrange(1, days)] + [dt]
return [d.strftime("%y%m%d") for d in dates] | 85bcc05c4b20831df62684f53d201c8962497ad3 | 80,524 |
def get_primes(size, bit_size, count):
"""Generate a list of probably prime numbers with at least a constant
factor difference between the numbers.
Args:
size: polynomail modulus value.
bit_size: bit lengths of the prime no's to be generated.
count: No's of prime numbers required.
... | 9ac0d5d0e1c7a8341e632abdac6a2663da2a1435 | 80,525 |
def fmripop_save_imgdata(args, out_img, params_dict, output_tag=''):
"""
Saves the output 4D image
"""
# Output filename
output_filename, _ = args.niipath.split(".nii.gz")
# NOTE: this line is not general enough, but it'll do for now
output_tag = '_confounds-removed' + output_tag + '.nii.... | 2426c8a08740a0aa243091f5b62f60c1c0ab467e | 80,526 |
def measureBitsEntropy(const):
"""Use heuristics to measure the "entropy" of the given numeric value.
Args:
const (int): numeric constant to be measured
Return Value:
Overall "entropy" score of the given numeric constant
"""
# we only work on unsigned values
if const < 0:
... | 75ac80ea1afc1335949fc84e766757d81be23f10 | 80,527 |
def get_pubchemcompounds_of_user_entity_ids(cursor, unification_table, user_entity_ids):
"""
Get the pubchemcompounds using their BIANA user entity ids
"""
query_pubchemcompound = ("""SELECT PC.value
FROM externalEntityPubChemCompound PC, {} U
WHERE ... | 4085fc3620db3edfb926a4abc89fbe2e70f7b42c | 80,528 |
def diffheaders(t1, t2):
"""
Return the difference between the headers of the two tables as a pair of
sets. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar', 'baz'],
... ['a', 1, .3]]
>>> table2 = [['baz', 'bar', 'quux'],
... ['a', 1, .3]... | bb3d6cf8dac9c5ac05ba6d566e9f42ede2d0a029 | 80,529 |
def parse_slack_output(slack_rtm_output):
"""
The Slack Real Time Messaging API is an events firehose.
this parsing function returns None unless a message is
directed at the Bot, based on its ID.
"""
output_list = slack_rtm_output
if output_list and len(output_list) > 0:
... | bb5c0880933a9861adee4dcea9cd0fa2c632f6d7 | 80,530 |
def home(request):
"""
首页
"""
client = get_client_by_request(request)
inner_host_info = get_inner_host_info(request)
new_host_list = []
exist_host_list = []
update_host_list = []
for host in inner_host_info:
ip = host['ip']
os_type = host['os_type']
hostname =... | 6649677cfe3fbcee6460b7a2c4036155351d14e2 | 80,531 |
def _has_delta_prefix(name):
"""Check if name starts with any of two allowed delta prefixes."""
return name and (name.startswith(DeltaCounter.DELTA_PREFIX)
or name.startswith(DeltaCounter.ALT_DELTA_PREFIX)) | fecc2430e3cf4143a2c264dd2cc0e42c9d1bbd2c | 80,532 |
def get_Q_j(region, j):
"""断熱性能の区分jの熱損失係数 Q_j (W/m2K)
Args:
region(int):
j(int): 断熱性能の区分
Returns:
float: 断熱性能の区分jの熱損失係数 Q_j (W/m2K)
"""
return get_table_e_5()[j][region - 1] | 8792ab56b4390956fc32e8be6e690847452c9224 | 80,533 |
def format_text_to_tspans(text, keywordFormats):
"""
keywordFormats looks like this: {
'Stamina': {'style': "font-weight:bold", 'dx': '3.0' },
'Harm': {'style': "font-weight:bold", 'dx': '4.0' },
}
"""
allTspans = []
currentTspan = etree.fromstring('<tspan></tspan>')
for w... | c4a025b3ae7b38370f7d53823de86c12e19864af | 80,534 |
def rb_join_arg(li=[], identif="default", pos=0):
"""Construct url argument with identifier and li as list."""
if li == []:
return ""
if pos == 0:
letter = "?"
else:
letter = "&"
return "{letter}{ident}={arg}".format(letter=letter, ident=identif, arg=','.join(li)) | fefb80814ded2fd53ccf99c92a6ec9b538d85a28 | 80,535 |
def get_topics(bag):
"""
Get an alphabetical list of all the unique topics in the bag.
@return: sorted list of topics
@rtype: list of str
"""
return sorted(set([c.topic for c in bag._get_connections()])) | 863faf144cef064324bb0dff41a9ac70464837ee | 80,536 |
def has_elem(elem_ref):
"""
Has element?
:param elem_ref:
:return:
"""
if not is_elem_ref(elem_ref):
return False
elif elem_ref[0] == ElemRefObj:
return hasattr(elem_ref[1], elem_ref[2])
elif elem_ref[0] == ElemRefArr:
return elem_ref[2] in elem_ref[1] | a950e2315002e31fdba9faa8507f1ed3e06bb902 | 80,537 |
def get_vlan_brief_rpc(self, vlan_id=None, last_rcvd_vlan_id=None, api_timeout=''):
"""
This is an auto-generated method for the PySwitchLib.
**Supported Versions**:
* NOS: 6.0.2f, 7.2.0
* SLXOS: 17r.1.01a, 17r.2.00, 17s.1.02
**Instance Argument(s)**:
:type vlan_id: long
... | abf032824e9ba23fb1f2dd6f3d6b4e1a9362487c | 80,538 |
def run_python(env_prefix, args, cwd=None):
""" Execute a platform independent python command.
:param env_prefix:
Python executable prefix to use to run the command.
:param args:
Optional python arguments.
:param cwd:
The current working directory.
:return:
The re... | 7cdd731b08706cae6d4e7df83924aa7be35b6097 | 80,539 |
from typing import Optional
from typing import Union
def random_walk_timeseries(
mean: float = 0.0,
std: float = 1.0,
start: Optional[Union[pd.Timestamp, int]] = pd.Timestamp("2000-01-01"),
end: Optional[Union[pd.Timestamp, int]] = None,
length: Optional[int] = None,
freq: str = "D",
colum... | 79cec1decc5a8648d11d227c6e60e6389001f96d | 80,540 |
import itertools
def unroll_example(example, normalized_length=5500, labels=None):
"""Unroll one example and build labels for the unrolled example.
Unroll one example with shape (L, d) to a pd.Series with shape (L * d,)
Labels for the input example are an array with shape (d, ), e.g.:
['usr', 'sy... | 7aeccaa7a2dc80b467908ed4d139a4f8dc15d600 | 80,541 |
import requests
from bs4 import BeautifulSoup
def get_product_urls(page_lim=10):
""" Get urls of products from product listed web page """
urls = []
for i in range(page_lim):
url = 'http://www.cosme.net/item/item_id/1064/products/page/{0}'.format(i)
r = requests.get(url)
html = r.... | 2199c00a0e38280dd5bfdc84c583aaaf9897b316 | 80,542 |
from typing import Optional
def format_ipfs_cid(path: str) -> Optional[str]:
"""Format IPFS CID properly."""
if path.startswith('Qm'):
return path
elif path.startswith('ipfs://'):
return path.replace('ipfs://', '') | eca4a79bc2ba4151495831b51bbd50df68f73025 | 80,543 |
def standard_pars_x(x, A=A_def, p=p_def, r=r_def):
"""returns magnetic parameters based on value received from find_x"""
return 2 * A * r * x, A * x**p, (1 - x**p) / (r * x) | 4480ea14e242a3ad44176a23480606ece24e328e | 80,545 |
def obter_vetor(tab, vet):
"""
obter_vetor: tabuleiro x string -> tuplo de pecas
Esta funcao devolve todas as pecas da linha ou coluna especificada pelo
seu argumento.
"""
if vet in ('1', '2', '3'):
return tuple(tab[int(vet)-1])
else:
coluna_num = coluna_para_num(vet) - 1
... | 8689ae1dd1466b351012ebb3bd78269e46cbe5c3 | 80,546 |
def _constraints_from_gpu_info(info_str):
"""Parse the contents of a /proc/driver/nvidia/gpus/*/information to get the
gpu model type.
Args:
info_str (str): The contents of the file.
Returns:
(str) The full model name.
"""
if info_str is None:
return {}
lines = info_str... | f5064b9de8be4918e6fe17b6ba24433c7cd9230b | 80,547 |
import scipy
def reliability(data):
"""
Computes upper and lower boundaries of data reliability
:Args:
data (np.ndarray)
N samples x M features
:Returns:
(floor, ceiling)
"""
zdata = scipy.stats.zscore(data, axis=1)
# remove data with no variance in it
# se... | ff62687c99cb7b69c841d18bc752171e2c7d5222 | 80,548 |
import sqlite3
def get_1D_tiles(db_file, zoom, tile_x_pos, num_tiles=1):
"""
Retrieve a contiguous set of tiles from a db tile file.
Parameters
----------
db_file: str
The filename of the sqlite db file
zoom: int
The zoom level
tile_x_pos: int
The position of the f... | e9d3244720dc3e624a53870ba17fdae91c59d93b | 80,549 |
def turn_coherence(behaviors, n_steps):
"""
Computes the probability of keeping a turn direction, ignoring intervening stay and straight bouts
:param behaviors: Array of consecutive behaviors - 0-stay, 1-straight, 2-left, 3-right
:param n_steps: The number of steps over which to compute probalities
... | bb130662f9b46265902a8ace79f6fe87201f3b5f | 80,550 |
def get_transcript(uri):
"""
Get transcript for a audio WAVE file stored in GCS bucket
@param: uri - File location in the google cloud storage bucket
"""
# create speech client
client = speech.SpeechClient()
# actual audio file to recognize
audio = speech.RecognitionAudio(uri=uri)
... | 69f1feabceffc42f8fae9c2c0a6cf546cffe50ca | 80,551 |
def openUnicode(file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True,
opener=None):
"""
Unicode auto-detection by BOM.
:return: Returns open() with the correct encoding and with the missing first character, if it is BOM.
"""
detect = False
if "r" i... | c7af92a9acde80e5f1a14a304cb135b075b71d7b | 80,552 |
def meters_to_meters2d(meters: Meters) -> np.ndarray:
"""
Cast for meters to 2D meters. Will make the second dimension 0.
:param meters: The input, as meters.
:return: The raw value to use for the Meters2D instance.
"""
return np.append(meters.raw, 0) | b938a75d3aa52f85cbd2ed4666ad266509c4447e | 80,553 |
from typing import Tuple
from typing import Union
from typing import Iterable
def microservice_api_grpc_seldon_message(method: str = "predict", microservice_endpoint: str = "localhost:5000",
shape: Tuple = (1, 1),
data: object = None, p... | 69be6aa059c090becb1838a1e2c6c41684a94189 | 80,554 |
def calculate_level(score):
"""Get the level associated with a given score."""
return score//LINES_PER_LEVEL+1 | a09300433eff736b4423647c25e351a398bbaa89 | 80,555 |
def breadcrumb_url(parser, token):
"""
Same as breadcrumb
but instead of url context variable takes in all the
arguments URL tag takes.
{% breadcrumb "Title of breadcrumb" person_detail person.id %}
{% breadcrumb person.name person_detail person.id %}
"""
bits = token.split_cont... | d220fb2c29b5d6a2ecc25fa28128ac5358d34c6a | 80,556 |
def search(public_ip):
"""
Search for the ``public_ip`` in the ~/.ssh/known_hosts file,
returning any occurrences found.
"""
result = local("ssh-keygen -H -F {0}".format(public_ip), capture=True)
return bool(result) | 9d64e12a3c69558f050a7e5004581ec083cfbdbe | 80,557 |
def simulation(N=N,
G=None,
initial_infected_num=INITIAL_INFECTED_NUM,
prob_infect=PROB_INFECT,
incubation_duration_mean=INCUBATION_DURATION_MEAN,
incubation_duration_std=INCUBATION_DURATION_STD,
prob_asymptomatic=PROB_ASYMPTOMATI... | 86e82be91116dbf5961385fb8fba7ac47b8a7409 | 80,558 |
def import_sunpy_map():
"""
Import SunPy maps with directory importer.
"""
caption = "Select a directory containing SunPy Map files."
directory = pick_directory(caption)
wi = QtSunpyMapImporter(directory)
wi.exec_()
return wi.datasets | ab55c76f7e918d7f53ee79a23ec60ed5fcbc60fd | 80,559 |
def solve_EEC(self):
"""Compute the parameters dict for the analytical equivalent electrical circuit
cf "Influence of the Number of Pole Pairs on the Audible
Noise of Inverter-Fed Induction Motors: Radial
Force Waves and Mechanical Resonances"
I. P. Tsoumas, H. Tischmacher, B. Eichinger
Paramet... | 7b8069cf9174c05de277b1b1c625f9259271aa61 | 80,560 |
def downgrade(sql_connection, version):
"""
Downgrade the database's current migration level
:param sql_connection: sqlalchemy connection string
:param version: version to downgrade to
:retval version number
"""
db_version(sql_connection) # Ensure db is under migration control
repo_pat... | 6a3ffeaa87ca34fcdb1150bc0c1f590210a0a96b | 80,561 |
def insertion_sort(integers):
"""Iterate over the list of integers. With each iteration,
place the new element into its sorted position by shifting
over elements to the left of the pointer until the correct
location is found for the new element.
Sorts the list in place. O(n^2) running time, O(1) spa... | ee7aa8920406f7c74870e346e486f29486894df1 | 80,563 |
def generator(*, domain, name, version):
"""Decorator that registers a generator function to `ACTIVITY_FUNCTIONS`
"""
def function_wrapper(func):
identifier = '{}:{}:{}'.format(name, version, domain)
ACTIVITY_FUNCTIONS[identifier] = check_type_generator_output(func)
return function_wrap... | 45410bbe0c34c6a5761c23308d551b3bc3e89f02 | 80,564 |
def _load_file (filename, env):
"""_load_file()
Given a file name, and an environment, load the file, and
extend/modify the environment with information about the current
file to be processed."""
with (open(filename)) as fileobj:
text = fileobj.read()
env["filename"] = filename
env["... | f901d6295478b1bbbc8f1bf5b109e4fc0ec778aa | 80,565 |
import curses
def init_screen(args):
""" Set ncurses screen and returns the screen object """
screen = curses.initscr()
curses.curs_set(0)
curses.start_color()
curses.init_pair(1, 1, args.background)
curses.init_pair(2, 2, args.background)
curses.init_pair(3, 3, args.background)
curs... | e46a5a3bee5f498219fbbf2b8b4df50abffa07fe | 80,566 |
def get_settings():
"""
Returns some nice default settings for matplotlib to be used with `matplotlib.pyplot.rc_context`.
"""
return {'axes.labelsize': 32,
'xtick.major.size': 10,
'xtick.major.width': 1.5,
'xtick.labelsize': 24,
'ytick.major.size': 10,
... | 7864c0bcb3b7ab427f6046b3358ee81f70646dd5 | 80,568 |
def patron_pid_minter(record_uuid, data):
"""Dummy patron minter."""
return None | c4ab8008467d54326911634bb51335f3b86cc96e | 80,569 |
from javax.swing.event import UndoableEditListener
def addUndoableEditListener(target, listener, *args, **kwargs):
"""
Shortcut for addEventListener(target, UndoableEditListener,
'undoableEditHappened', listener).
"""
return addEventListener(target, UndoableEditListener,
... | 63bc28fb07f564fba4f59585723937a941f899f7 | 80,570 |
from typing import Optional
def doolittle(matrix: np.ndarray) -> Optional[np.ndarray]:
"""
Doolittle 法 LU 分解
:param matrix: 系数矩阵
:return: 分解后的矩阵，下半为 L，上半为 U
"""
row, col = matrix.shape
if row == col:
u = np.zeros((row, row))
# init
for j in range(0, row):
... | 64da71138127a3735e864e0822493ba5c5c6195d | 80,571 |
def plot_background(rgb_bg_data, title=None):
""" Plot the RGB backgrounds from `Background2d` objects.
Args:
rgb_bg_data (list[photutils.Background2D]): The RGB background data as
returned by calling `panoptes.utils.images.bayer.get_rgb_background`
with `return_separate=True`.
... | 18a68f396c717da2c30c1bd7f092eae08a4ff7cf | 80,572 |
def find_class_from_command_name(command_name):
"""Find the Python class for a specific command name.
Parameters:
command_name (str)
The command name, which should be used to find the class.
Returns (sublime_plugin.Command)
The python class, which belongs to the command name, o... | a43dee13bfa0987005c83d82962384eb921a0086 | 80,574 |
def get_dict_map(dict_code):
"""
获取字典映射
:param dict_code:
:return: dict
"""
if dict_code:
dicts = DictItem.query.filter_by(dict_code=dict_code, is_valid=IS_VALID_Y).all()
return {it.item_code: it.item_name for it in dicts}
else:
return {} | e0390f3126847b87951598db352c213cafbcfad1 | 80,575 |
from scipy.spatial import Voronoi
def VoronoiNeighbors(
tree, xy, k=100, **kd_kwds
):
"""
Return Neighbors on a Voronoi diagram (excuding xy)
Arguments
---------
tree : scipy.stats.cKDtree
must implement the query method and the data attribute.
xy : coordinates
dimensions(... | 3ac7e8201c9b1a650d603a18bd7dfb8859d982a1 | 80,576 |
def parse_poly(lines):
"""
Parse an Osmosis polygon filter file.
Accept a sequence of lines from a polygon file, return a django.contrib.gis.geos.MultiPolygon object.
Adapted Python 2 code from
http://wiki.openstreetmap.org/wiki/Osmosis/Polygon_Filter_File_Python_Parsing_Geodjango for ... | 7d99d30ae7e968f7f5500476ae310a77a4cd0646 | 80,579 |
def calc_weight(team_a,
team_b,
team_a_ind,
team_b_ind,
team_a_opt,
team_b_opt,
team_a_opt_ind,
team_b_opt_ind):
"""
Calculate the penalty for a given pairing
Args:
team_a - the firs... | 7b31b4e71b075f2fd32571e69b7c08a38834826e | 80,580 |
def printing(slab, I, Is, ea):
""" print output """
print "\nNumber of slabs to be Integrated: ", slab
print "Simpson's Integral value: ", Is
print "Analytic Integral value: ", I
print "Absolute error: ", ea
return 0 | b691d08dbe28a8271c035a977f250e6fb5700fdc | 80,582 |
import pickle
import random
def predict(day, sites, chimeres_day, geops_day, meteo_day, concentrations_day, model=None):
"""
day: day of the year (1-365)
sites : Dataframe with columns "idPolair","nom_station","coord_x_l93","coord_y_l93","X_lamb2","Y_lamb2", "LON" ,"LAT",
"Département","Zone_EPCI","typol... | a2db455385639095d8b049825ed2522ec7068277 | 80,583 |
def add_asset(data):
"""Create asset from provided data dictionary."""
client = _algod_client()
params = client.suggested_params()
unsigned_txn = AssetConfigTxn(
sp=params,
sender=data.get("creator"),
asset_name=data.get("name"),
unit_name=data.get("unit"),
total=... | 63543d5151b1830576a46023a3565c59d9530408 | 80,584 |
import timeit
def log_com(image):
"""Doing log compression and count the time for processing
Args:
image: input image data (should be ndarray)
returns:
img_str: image after log compression
time_process: time for doing the processing
"""
start = timeit.default_timer()
... | a1db7ec6d0f51e8b2515ca4f6138beb8ffd31c74 | 80,585 |
from typing import List
def _ext_oracle(
src: List[str],
ref: str,
sim_fn,
max_sent: int = 3,
max_len: int = -1,
threshold: int = -1,
):
"""
A functionality of generating the extractive oracle for
a sample in the summarization dataset
src: source documents
ref: reference s... | df8989c6d7d6103a6a212ea9cba4578f50a6beda | 80,586 |
def TrainingWeights(y, Pout, lev, weight_precip, weight_shallow):
"""Set up weights for training examples"""
wp = np.ones(y.shape[0])
ws = np.ones(y.shape[0])
if weight_precip:
wp = Pout + 1
if weight_shallow:
# 0.8 is near the level of maximum shallow convective activity
sha... | 4b0eaabd5c017972b524321f1f148960e79d4e33 | 80,587 |
def build_full_record_to(path_to_full_record_file):
"""structure of full record:
{commitID: {'build-time': time, files: {filename: {record}, filename: {record}}}}
"""
full_record = build_full_record()
if DO_PRINT_RECORDS:
f = open(path_to_full_record_file, 'w')
try:
f.wri... | cbde1306227d9e210a2f2a9a2d1c93ffc9522cee | 80,588 |
import random
def neighbor_test(nr_points, dim, bucket_size, radius):
"""Test all fixed radius neighbor search.
Test all fixed radius neighbor search using the
KD tree C module.
Arguments:
- nr_points: number of points used in test
- dim: dimension of coords
- bucket_size: nr of point... | 1542a40d9827dd5e40d92f86a233ec43dc58fb63 | 80,589 |
def send_source_data(appsrc_id, tensor, stream_name, stream_manager):
"""
Construct the input of the stream,
send inputs data to a specified stream based on streamName.
Returns:
bool: send data success or not
"""
tensor_package_list = MxpiDataType.MxpiTensorPackageList()
tensor_pack... | 879b48ee938d1b2bfc3092346094f9f991310e78 | 80,591 |
def population_counts(
boundaries: BoundariesLayer, population: PopulationLayer
) -> pd.Series:
"""Count population in each boundary.
Parameters
----------
boundaries : BoundariesLayer
Input boundaries vector layer.
population : PopulationLayer
Input population raster layer (pop... | 64f5a7b387524bf080d2ef8263b1b3e4585c9fb2 | 80,593 |
def solvationData(request, solute_adjlist, solvent=''):
"""
Returns an entry with the solute data for a given molecule
when the solute_adjlist is provided. If solvent is provided,
the interaction solvation quantities are also displayed.
The solvation data is estimated by RMG.
"""
#from rmgp... | 02fe79d860a2878e7265757207ec043a43e17d1c | 80,594 |
import json
def load_all_skillets(refresh=False) -> list:
"""
Returns a list of skillet dictionaries
:param refresh: Boolean flag whether to use the cache or force a cache refresh
:return: skillet dictionaries
"""
if refresh is False:
cached_skillets = cnc_utils.get_long_term_cached_va... | 7e79d4810241544019f45ce7533b18e05fb94803 | 80,595 |
def get_shorting_trading_value_and_volume_by_ticker(date: str, market: str, include: list) -> DataFrame:
"""[32001] 개별종목 공매도 거래
Args:
date (str): 조회 시작 일자 (YYYYMMDD)
market (str): 검색 시장 (KRX/KOSPI/KOSDAQ)
include (str): 증권 구분 (주식/ETF/ETN/ELW/신주인수권및증권/수익증권)
Returns:
Data... | c0bb66b69076c18404be306136eba6893ad82030 | 80,596 |
def merge_scored_dfs(scored_coding_df, scored_non_coding_df):
"""Merges the scored dataframes by changing some names around"""
# for every non-coding TransMap metric, copy it to the other name
for m in ['Coverage', 'Identity', 'Goodness']:
scored_non_coding_df['Aln' + m + '_mRNA'] = scored_non_codin... | 5e5d33edaf6e10bd5d927447b8d042e207cef594 | 80,597 |
from typing import List
def primary() -> List[str]:
"""Primary color scheme."""
return ["#00A58D", "#008A8B", "#9FCD91", "#09505D", "#00587C"] | 8527c8a649e554e077a57172dfb0d529fff4036a | 80,598 |
def cross_channel_normalization_bc01(bc01, alpha=1e-4, k=2, beta=0.75, n=5):
"""
BC01 format (batch, channels, rows, cols) version of Cross Channel Normalization.
See "ImageNet Classification with Deep Convolutional Neural Networks"
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton
NIPS 2012
... | 22172c5a799f402b7d355e556563ff6c26b47071 | 80,599 |
def draw_bbox(img_path: str, bbox: namedtuple, line_width=10):
""" Draw a bbox around the object.
:param str image_path: an image containing an object
:param namedtuple bbox: x0, y0, x1, y1
:param int line_width: a width of bbox side
:return draw: image object with bbox drawed.
"""
im ... | 62b8556301d2fc1186d50a1b72be9221f4072b32 | 80,600 |
import warnings
def pull_halo_output(h5file, clusterID, apertureID, dataset):
"""
Function to extract a dataset from a Bahamas snapshot output.
:param h5file: The h5py File object to extract the data from
:param clusterID: The number of cluster in the order imposed by FoF
:param apertureID: int(0-22) The index o... | d389af763c7dc7a3c6e54a1f61f4906c7fa4dc0e | 80,603 |
def rt_delta(maxdiff, precision=5):
# type: (float, int) -> float
"""Return the delta tolerance for the given retention time.
Keyword Arguments:
maxdiff -- maximum time difference between a feature edge and
an adjacent frame to be considered part of the same
... | ad04d4f0405544d1cf137b7b3c8aa25ac670365f | 80,604 |
from typing import List
def yara_rules_names(yara_rules_string: str) -> List[str]:
"""Get the name(s) of the given yara_rule(s)."""
yara_rules_data = yara_rules_parse(yara_rules_string)
all_rule_names = []
for rule in yara_rules_data:
if rule.get('rule_name'):
rule_name = rule['ru... | 6487f4a57b3b01028542aa86800ee8bee17aea0b | 80,605 |
import pkg_resources
import logging
def get_tango_server_class(device_name):
"""Build and return the Tango device class for DishMaster
:param device_name: str
The Tango device name
:return DishMaster: tango.server.Device
The Tango device class for dishmaster
"""
data_descr_files =... | 3f2dd05aba57b453da6f894f5ccd864890372c7f | 80,606 |
def check_converged(
new_transport: dict,
old_transport: dict,
properties: tuple[str, ...] = _CONVERGENCE_PROPERTIES,
tolerance: float = 0.1,
) -> bool:
"""
Check if all transport properties (averaged) are converged within the tol.
Parameters
----------
new_transport : dict
... | 45ec62bc180c924267892fb57ce836bb9d7cce68 | 80,607 |
def ratio_specials(s):
"""
Returns the ratio special characters to all characters in s.
The default special character list is "~`!@#$%^&*()_={}[]:>;',</?*-+"
:param s: Domain (string)
"""
return analyse.get_ratio_special_2ld(s) | 1fdd478e03742f3e5462893d65f9192826f8c4f0 | 80,608 |
from typing import List
def boxes_from_mask(mask: np.ndarray) -> List[np.ndarray]:
"""
Args:
mask: (1, h, w) 0~1
Returns:
"""
height, width = mask.shape[1:]
_, thresh = cv2.threshold((mask.transpose(1, 2, 0) * 255).astype(np.uint8), 127, 255, 0)
contours, _ = cv2.findContours(th... | 7b8a2efdc00247f045f82deabcb42653c291549a | 80,609 |
async def ensemble_forecast():
"""Execute ensemble forecast and represent as dataframe."""
# Assemble data used as input for simulations ######################################
timer_wfc = Timer(
text="Overall duration for preparing weather forecasts: {:.2f} seconds",
logger=logger.success,
... | 92daece08abac5e3a7007c7e7f630cc83354d815 | 80,610 |
def simple_impute(
adata: AnnData, var_names: list[str] | None = None, strategy: str = "mean", copy: bool = False
) -> AnnData:
"""Impute AnnData object using mean/median/most frequent imputation. This works for numerical data only.
Args:
adata: The AnnData object to use mean Imputation on
... | 24216bdb2aa50ad18afa0efed82384ab1be1c084 | 80,611 |
def positive_negative_basic_reward_function(causal_prefetch_item):
"""
Consistent positive reward based on something being used within 128 steps (1, -1) rewards
"""
if causal_prefetch_item is None:
return -1
return 1 | beaefcaebe806329d17ec8fa584e2a0f102b978c | 80,613 |
from typing import Union
def constant_schedule(
value: Union[float, int]
) -> base.Schedule:
"""Constructs a constant schedule.
Args:
value: value to be held constant throughout.
Returns:
schedule: A function that maps step counts to values.
"""
return lambda count: value | 8e20eb79a151b8dbeab914dc81aa71515a29aa5d | 80,614 |
def login():
"""
管理员登录页面
"""
form = LoginForm()
return render_template('/admin/login.html', form=form) | de8c69d658fcd6494967dde8678c37a85f0d66cf | 80,615 |
def create_template_dict(dbs):
""" Generate a Template which will be returned by Executor Classes """
return {db: {'keys': [], 'tables_not_found': []} for db in dbs} | 01dbd3733ec77fef0323eea35bc67064b19093c9 | 80,616 |
def header_case(s: str):
"""
Transform into a dash separated string of capitalized words.
Parameters
----------
s : str
Original string to transform.
Returns
-------
Transformed string.
"""
return _change_case(s, '-', str.capitalize) | d0ebceceac702b01c535d7ab0d6091df9f4e3ebf | 80,618 |
def _calc_height2area_ratio(lw, chain, ta=-1.0, tb=-1.0 ):
"""
We know the value of the full width half max line width in Hz that we have
in our data, and want to find the Ta and Tb values that yield this.
This function uses the minf_parabolic_info routine to optimze Ta and Tb
to values betwee... | 517d842d698bb705cfdd448b3f34261e736d051f | 80,619 |
def frame_multi_factory(buf, preface=False):
"""
Attempt to parse one or more Frame's out of buf
Args:
buf: string containing HTTP/2 frames. May have an incomplete frame at the
end.
preface: expect an HTTP/2 preface at the beginning of the buffer.
Returns:
[Frame]
int, ... | f80f42c07c1354af7b9100b342f2e36421074395 | 80,620 |
def is_camel_case(string):
"""
Checks if a string is formatted as camel case.
A string is considered camel case when:
- it starts with a lower case letter
- it's composed only by letters ([a-zA-Z]) and optionally numbers ([0-9])
- it contains both lowercase and uppercase letters or just lowercas... | ecd1f520bca8d4f6e1f54cb1dddea27db51eb302 | 80,621 |
def find_nearest_center(a, centers):
"""
return the nearest center
:param a: each pixel [r,g,b]
:param centers: a 9*3 R,G,B array
:return:
"""
mid_d = np.inf
r = 0
for i in range(len(centers)):
distance = np.linalg.norm(a - centers[i])
if distance < mid_d:
... | fd27bb3ce902d0c80d1c3b653375361c881be3e4 | 80,622 |
def NodalPlanes_Cast(*args):
"""
Cast(BaseObject o) -> NodalPlanes
NodalPlanes_Cast(Seiscomp::Core::BaseObjectPtr o) -> NodalPlanes
"""
return _DataModel.NodalPlanes_Cast(*args) | 7acaca0ff31257cb2a98fbaafd3e19fc76d983d7 | 80,623 |
import numpy
def write_gif(dataset, filename, fps=10, loop_times=0):
"""Write a NumPy array to GIF 89a format.
Or write a list of NumPy arrays to an animation (GIF 89a format).
- Positional arguments::
:param dataset: A NumPy arrayor list of arrays with shape
rgb x rows ... | cf22b9526681158f6bb111e0c7be44da6ccb13e8 | 80,624 |
def new_constant(name, py_conversion=None, default_value=None, validation=None,
widget_type=None,
str_conversion=None, base_class=Constant,
compute=None, query_compute=None):
"""new_constant(name: str,
py_conversion: callable,
... | 9d6e452e9e85a30f20264612e9912eb8ffc3d828 | 80,625 |
from pathlib import Path
def get_git_data():
"""Assemble some Git metadata."""
repo = Repo(Path(Path(__file__).resolve().parent.parent))
timestamp = repo.head.object.authored_datetime.isoformat()
timestamp = timestamp.split("+")[0].replace("T", " ")
repo_url = f"https://github.com/{GITHUB_REPO}"... | 670e883a986220a6cfb9bda0d3c35128ac49c2d8 | 80,626 |
from typing import Any
def create_model_group(
*,
db: Session = Depends(deps.get_db),
current_user: models.User = Depends(deps.get_current_active_user),
obj_in: schemas.ModelGroupCreate,
controller_client: ControllerClient = Depends(deps.get_controller_client),
) -> Any:
"""
Create model g... | e1c4d5c27e9fc8af0034dfc33186a9b9ba403e57 | 80,627 |
def doc2vec_vectorizer(vectorizer):
"""
Doc2vec interface for text similarity using Encoder model.
Parameters
----------
vectorizer : object
encoder interface object, BERT, XLNET.
should have `vectorize` method.
Returns
-------
result: malaya.similarity.VectorizerSimila... | 9f78f907229097be292a3ebeac335e2944a76da7 | 80,628 |
from typing import Union
from typing import Optional
def calc_terms_marg_probs(
phi: Union[ndarray, DataFrame],
word_id: Optional[int] = None) -> Union[ndarray, Series]:
"""Calculate marginal terms probabilities.
Parameters
----------
phi : Union[ndarray, DataFrame]
Words vs t... | b710a4b25b921b9d09804b4fd4c1e34b3257ecd6 | 80,629 |
def get_metadata(user, dataset_name):
"""Gets the metadata of the specific upload.
Checks datastore for an the latest entity that matches the name of the user
and dataset name.
Args:
user:
Name of the user that uploaded the file.
dataset_name:
Name of the dataset ... | da821288b70a72225578baa2492da746dde836f1 | 80,630 |
from typing import Mapping
from typing import Union
def _(
_data: TibbleGrouped,
_names_sep: str = None,
**cols: Mapping[str, Union[str, int]],
) -> TibbleGrouped:
"""Nesting grouped dataframe"""
if not cols:
cols = {
"data": regcall(setdiff, _data.columns, regcall(group_vars, ... | 17fcb0f53d410ed4615bb3b44a73e04640ffa234 | 80,631 |
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