content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def get_ground_weather_one_place(dir_path):
""" 1地点の地上気象データを取得する
Args:
dir_path(string) : ディレクトリパス
Returns:
DataFrame : ファイルの読込結果
"""
# 地上気象データのファイル一覧取得
file_paths = read_csv.get_file_paths(dir_path)
# 気象データを読み込み、DataFrameに格納する
ground_df = None
... | b25c6008c1f1cf9760c16dc10fd44dee8e62ad55 | 5,200 |
def trash_description(spl, garbage, keyword, description="description_1"):
"""description_1 OR description_2"""
relocate = spl[spl[description].str.contains(keyword, na=False, regex=True)]
spl = spl[~spl[description].str.contains(keyword, na=False, regex=True)]
garbage = pd.concat([garbage, relocate], i... | 16a1512ddaf914bd5ebcd00f2dcdfa11d59ec73c | 5,201 |
import random
def prepositionalPhrase():
"""Builds and returns a prepositional phrase."""
return random.choice(prepositions) + " " + nounPhrase() | 33a6f1111f752c160ef90eedde4bf56b79b1100a | 5,202 |
def check_possible_dtype(df):
"""Guess dtypes for each column in a dataframe, where dataframe must contains only string values.
Raise an exception if dataframe contains non-string values.
:param df: a DataFrame whose all values must be strings.
"""
column = []
int_cnt = []
dec_cnt = []
... | 0e9759959af04fbf1bb9db3672f6a188afe7f6ab | 5,203 |
from typing import List
def filter_objects_avoiding_duplicated(objects: List[Object],
max_distance: int = 20) -> List[Object]:
"""Filtra los objetos evitando aquellas posibles que sean detecciones múltiples.
El fundamento del algoritmo es que si se detectan dos objetos ... | 042fee5df94dc1c72fb53635577c8006c57f73f9 | 5,204 |
import os
def splitall(path):
"""
Credit goes to Trent Mick
SOURCE:
https://www.oreilly.com/library/view/python-cookbook/0596001673/ch04s16.html
"""
allparts = []
while 1:
parts = os.path.split(path)
if parts[0] == path: # sentinel for absolute paths
allparts.i... | 3d25bdfab5fd74d59e67100c864c950a2aaaa78b | 5,205 |
import os
def netstat():
"""
Return list of all connections.
Return list of TCP listenning connections and UDP connections.
All localhost connections are filtered out.
This script must run as root in order to be able to obtain PID values
of all processes. For more information see:
https:... | 04884bd091438956012c1524671a1ffdfddc4c6f | 5,206 |
def print_hdr(soup, hdr, file = None):
"""
:param soup: [bs4.BeautifulSoup] document context
:param hdr: [dict] header node to process
:param file: [stream] I/O stream to print to
:return: [stream] pass on the I/O stream so descent continues
"""
tag = hdr['tag']
tag_id = tag['id']
in... | 2c6fd613a5c6ddb5ec842fb7cee845d1a8771ccd | 5,207 |
from unittest.mock import Mock
def __empty_2():
""" Empty used as parent of cube_2 """
obj = Mock()
obj.name = 'empty_2'
obj.mode = 'OBJECT'
obj.to_mesh.return_value = None
obj.matrix_world = Matrix.Identity(4)
obj.visible_get.return_value = False
obj.hide_viewport = True
obj.hide_... | 024614d7967da5da6d6629167a20eda4188e812f | 5,208 |
import argparse
def parse_args(args):
"""Parse command line parameters
Args:
args ([str]): command line parameters as list of strings
Returns:
:obj:`argparse.Namespace`: command line parameters namespace
"""
parser = argparse.ArgumentParser(
description="A scaffolding program... | 8217e73fe219e18a8a7c8d0560fba95c5c3458df | 5,209 |
def get_gradient(bf_data: np.ndarray, smooth=10):
"""
Removes first dimension,
Computes gradient of the image,
applies gaussian filter
Returns SegmentedImage object
"""
data = strip_dimensions(bf_data)
gradient = get_2d_gradient(data)
smoothed_gradient = gaussian_filter(gradient, smo... | 864b3bc118d08099c56657b2f2883e20de5c663e | 5,210 |
def sum_seq(seq):
""" Lambda wrapper for sum. """
return K.sum(seq, axis=1, keepdims=False) | e2bf342f6cda9bda50dc15814c7808a42e8a9925 | 5,211 |
def split_by_time(files_rad):
"""Separate a list of files by their timestamp"""
out = {}
if type(files_rad) == dict:
for k in files_rad.keys():
out[k] = _split_by_time(files_rad[k])
else:
out = _split_by_time(files_rad)
return out | 9a77b3db2e21c27198337b1a1852494bca5acefb | 5,212 |
def make_general_csv_rows(general_csv_dict):
"""
Method for make list of metrics from general metrics dict.
Rows using in general metrics writer
:param general_csv_dict: dict with all metrics
:type general_csv_dict: dict
:return: all metrics as rows
:rtype: list
"""
rows = []
f... | 45ca165d312b39cd0b7088e0bcbfb402a92e7e2b | 5,213 |
def build_hstwcs(crval1, crval2, crpix1, crpix2, naxis1, naxis2, pscale, orientat):
""" Create an HSTWCS object for a default instrument without distortion
based on user provided parameter values.
"""
wcsout = wcsutil.HSTWCS()
wcsout.wcs.crval = np.array([crval1,crval2])
wcsout.wcs.crpix = n... | 0247a8dc7e6aa083db50f21d82676216583be206 | 5,214 |
def build_regressor_for_ranking_positive_class(dataset, features, regression_target=TARGET_COLUMN):
"""This function builds a regressor based exclusively on positive class'
examples present in the dataset
"""
if regression_target in features:
print('The target for the regression task cannot be one of the f... | 1312751425f79c1e4fec09f705f0ea551e2a60b3 | 5,215 |
def get_speakable_timestamp(timestamp):
"""Return a 'speakable' timestamp, e.g. 8am, noon, 9pm, etc."""
speakable = f"{timestamp.strftime('%I').lstrip('0')} {timestamp.strftime('%p')}"
if speakable == '12 PM':
return 'noon'
elif speakable == '12 AM':
return 'midnight'
return speakab... | 0b724686ebd5d3152d9017dc456d2945c78be0ee | 5,216 |
def createColor(red: int, green: int, blue: int) -> tuple:
"""
Create color
Parameters:
red -> 0-255
green -> 0-255
blue -> 0-255
"""
return tuple(
max(min(red, 255), 0),
max(min(green, 255), 0),
max(min(blue, 255), 0)
) | 3e8ee43e9d458668f4312f9fd75050b5875036d7 | 5,217 |
from typing import List
def export_nodeclass_list(node_classes: List[NodeClass]) -> str:
"""Writes the Node data as a XML string. Does not write
to a file -- use ``with open(output_file) as out_stream:`` etc.
"""
# This is the data string, the rest is formalities
node_classes_string = '\n'.join([s... | f50638e9b3a7ab2f1df6e49703b9ed3e39916f9d | 5,218 |
import time
def recognition(request):
"""
style transform service
"""
if request.method == 'POST':
name = ''
predicitons = ''
try:
# load image
now = time.localtime()
img = request.FILES['image']
image_name = '{}{}{}{}{}o... | d8de5ab5c33e6ca0c2ac5afbec81c402f7151187 | 5,219 |
def url(s):
"""Validate url input"""
u = urlparse(s)
if u.scheme not in ["http", "https"]:
raise ValueError(s)
return u.geturl() | 82683af4ad6fb35b6d74409a9a429c4dfd81a723 | 5,220 |
import pickle
def getGPLCs(df, savepath='./',plotpath='./', bands='ugrizY', ts='0000000', fn='GPSet'):
"""Short summary.
Parameters
----------
df : type
Description of parameter `df`.
savepath : type
Description of parameter `savepath`.
plotpath : type
Description of p... | 755dec48771ae17c058565ef88087d6ec6a78aec | 5,221 |
import torch
def _featurize(inputs,model):
"""
Helper function used to featurize exemplars before feeding into
buffer.
"""
with torch.no_grad():
# Forward pass
outputs = model(*inputs).detach() #Featurize raw exem
return outputs | 191fd1b362f38309a35618284fcf3f1910a06bd6 | 5,222 |
def ligth_condition(img, args):
"""
Change ligthning condition in the image
Inputs:
img: Image to change ligthning
args: Dictionary with "gamma" argument
Return:
Image with ligthning values changed
"""
invGamma = 1.0 / args["gamma"]
table = np.array([((i / 255.0) ** i... | dc5273a1df8e13292147b00be45452a7ccf4a197 | 5,223 |
import numpy as np
from sklearn.metrics import mean_squared_error
def calc_RMSE(varx,vary,lats,lons,weight):
"""
Calculates root mean square weighted average
Parameters
----------
varx : 2d array
vary : 2d array
lons : 1d array of latitude
weigh... | 150d08e0790f3a8ce59a2054cdc042ff6cdc2969 | 5,224 |
def sample(internal_nodes, alpha=0.5, beta=0.5, only_tree=False):
""" Generates a junction tree with order internal nodes with the junction tree expander.
Args:
internal_nodes (int): number of nodes in the underlying graph
alpha (float): parameter for the subtree kernel
beta (float): pa... | d0cc00e7ad96491147149aa4be396af970a9f68f | 5,225 |
def _get_version_tuple():
"""
version as a tuple
"""
return major, minor, revision | 1d82390224de07964dce7c4e7fd3e32595b189a0 | 5,226 |
def _fit_seasonal_model_with_gibbs_sampling(observed_time_series,
seasonal_structure,
num_warmup_steps=50,
num_results=100,
seed=None):
"""Bui... | c13d4df3eca25f1a53ed27cd94e5f2b4b102013c | 5,227 |
def deskew(data, angle, dx, dz, rotate=True, return_resolution=True, out=None):
"""
Args:
data (ndarray): 3-D array to apply deskew
angle (float): angle between the objective and coverslip, in degree
dx (float): X resolution
dz (float): Z resolution
rotate (bool, optional... | a39ff1d48777c266e83358e272b6ba7d6d7ce894 | 5,228 |
import os
import tqdm
def process_data(path,stage = 'train'):
"""
train
test
sample_submission
"""
# loading the data
df = pd.read_csv(os.path.join(path,f'{stage}.csv'))
MASK = -1 # fill NA with -1
T_HIST = 10 # time history, last 10 games
# for cols "date", change to datatime
for col in df.filter(regex=... | ff6542c8a4f7366c2a1b612d7b41e3aa539e34a4 | 5,229 |
import pandas as pd
import numpy as np
def rm_standard_dev(var,window):
"""
Smoothed standard deviation
"""
print('\n\n-----------STARTED: Rolling std!\n\n')
rollingstd = np.empty((var.shape))
for ens in range(var.shape[0]):
for i in range(var.shape[2]):
for j in ... | d37cfa3c756f8fc062a28ac078e4e16557282951 | 5,230 |
import os
def load_letter(folder, min_num_images):
"""Load the data for a single letter label."""
image_files = os.listdir(folder)
dataset = np.ndarray(shape=(len(image_files), image_size, image_size),
dtype=np.float32)
image_index = 0
print(folder)
for image in os.listdir(folder)... | 30324858e8481b348f004dfbc39bf790cd0ca930 | 5,231 |
def visualizeTimeSeriesCategorization(dataName, saveDir, numberOfLagsToDraw=3, autocorrelationBased=True):
"""Visualize time series classification.
Parameters:
dataName: str
Data name, e.g. "myData_1"
saveDir: str
Path of directories pointing to data storage
... | b2fcac2179e3a689ee73e13519e2f4ad77c59037 | 5,232 |
from typing import Dict
def refund(payment_information: Dict, connection_params) -> Dict:
"""Refund a payment using the culqi client.
But it first check if the given payment instance is supported
by the gateway.
It first retrieve a `charge` transaction to retrieve the
payment id to refund. And r... | 75dff392c0748a1408eb801ad78ef65be988026c | 5,233 |
import argparse
import os
def get_args():
"""Get command-line arguments"""
parser = argparse.ArgumentParser(
description='Howler',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('text',
metavar='str',
help='Inpu... | 906e38ad510016068ca7d431c681b4680ee56f5d | 5,234 |
import torch
from typing import Tuple
def _ssim_map(
X: torch.Tensor,
Y: torch.Tensor,
data_range: float,
win: torch.Tensor,
K: Tuple[float, float] = (0.01, 0.03),
scales: Tuple[float, float, float] = (1, 1, 1),
gradient_based: bool = False,
) -> Tuple[torch.Tensor, torch.Tensor]:
"""
... | 3a1d34497228bb95d0bc295475fb0df38220107b | 5,235 |
import numbers
def check_random_state(seed):
"""Turn `seed` into a `np.random.RandomState` instance.
Parameters
----------
seed : {None, int, `numpy.random.Generator`,
`numpy.random.RandomState`}, optional
If `seed` is None (or `np.random`), the `numpy.random.RandomState`
s... | 57390806329776c77977a27e18e78fdad298fef9 | 5,236 |
def power3_sum_2method():
"""
Input:
nothing, it have everything it needs.
Output:
sum: summ of all numbers which is power of 3
and fit in between 0 and upper bound == 1000000
"""
k = 0
sum = 0
while True:
a = 3**k
k += 1
if a < 1000000:
s... | b86bfaeb2418e183a78054d2a4b76c58d58be388 | 5,237 |
def bitwise_right_shift(rasters, extent_type="FirstOf", cellsize_type="FirstOf", astype=None):
"""
The BitwiseRightShift operation
The arguments for this function are as follows:
:param rasters: array of rasters. If a scalar is needed for the operation, the scalar can be a double or string
:param ... | 8d07a60a514466ee4aa0b15b0b442fb71b3347ed | 5,238 |
import re
def strip_comments(line):
"""Strips comments from a line and return None if the line is empty
or else the contents of line with leading and trailing spaces removed
and all other whitespace collapsed"""
commentIndex = line.find('//')
if commentIndex is -1:
commentIndex = len(line... | 09579031294d7b5787c97fa81807fa5ecfe12329 | 5,239 |
import logging
def fft_pxscale(header,wave):
"""Compute conversion scale from telescope space to sky space.
Parameters
----------
ima : array
2D Telescope pupil model.
Returns
-------
fftscale : float
The frequency scale in sky space.
Exam... | 6935bdefe96aec771704a79952cfc25ffb55e8bb | 5,240 |
def parse_git_submodules(gitmodules_data):
"""Parse a .gitmodules file to extract a { name -> url } map from it."""
result = {}
# NOTE: configparser.ConfigParser() doesn't seem to like the file
# (i.e. read_string() always returns None), so do the parsing
# manually here.
section_nam... | 78d01ec70b68164189a2ea775c6084e256116d0a | 5,241 |
import pathlib
from typing import Dict
import json
def get_model_cases(dir_path: pathlib.Path) -> Dict[str, Dict[str, str]]:
"""
Returns the Zen model case for each test if it exists.
:param dir_path: The path to the directory containing the DIFFERENCES directory.
"""
model_cases = defaultdict(di... | d35b4cf59cf9b99a6aeb9e05e0af3ee342b11f3b | 5,242 |
def _format_date(event):
"""Returns formated date json object for event"""
old_date = event["date"]
term = event["term"]
dates = old_date.split("-")
if len(dates) == 1:
is_range = False
else:
is_range = True
is_range = (len(dates) > 1)
if is_range:
start_date =... | aa8bf9a41fe30b664920e895cdc31d6993a408b2 | 5,243 |
def fetch(bibcode, filename=None, replace=None):
"""
Attempt to fetch a PDF file from ADS. If successful, then
add it into the database. If the fetch succeeds but the bibcode is
not in th database, download file to current folder.
Parameters
----------
bibcode: String
ADS bibcode ... | 7d264df3f0eab896a9cb4858e7b19e2590d8142b | 5,244 |
def crop_multi(x, wrg, hrg, is_random=False, row_index=0, col_index=1):
"""Randomly or centrally crop multiple images.
Parameters
----------
x : list of numpy.array
List of images with dimension of [n_images, row, col, channel] (default).
others : args
See ``tl.prepro.crop``.
R... | 61593029455a880d5309e8343cf4f6d1049f598f | 5,245 |
def value_loss_given_predictions(value_prediction,
rewards,
reward_mask,
gamma,
epsilon,
value_prediction_old=None):
"""Computes the value loss given the... | 5896dd57e1e9d05eb71e5b31aab4071b61d0fdbf | 5,246 |
def build_pkt(pkt):
"""Build and return a packet and eth type from a dict."""
def serialize(layers):
"""Concatenate packet layers and serialize."""
result = packet.Packet()
for layer in reversed(layers):
result.add_protocol(layer)
result.serialize()
return re... | afd84446d3bb545b03b9d4c42d80f096b6665342 | 5,247 |
def make_file_prefix(run, component_name):
"""
Compose the run number and component name into string prefix
to use with filenames.
"""
return "{}_{}".format(component_name, run) | 73ef37d75d9e187ee49ee058958c3b8701185585 | 5,248 |
def identifier_needs_escaping(text):
"""
Slightly slow, but absolutely correct determination if a given symbol _must_ be escaped.
Necessary when you might be generating column names that could be a reserved keyword.
>>> identifier_needs_escaping("my_column")
False
>>> identifier_needs_escaping(... | 265f7acd1e92a954758f44eb03247b0b935d6d4d | 5,249 |
from typing import Dict
def initialize_lock_and_key_ciphers() -> Dict[str, VigenereCipher]:
"""[summary]
Returns:
Dict[VigenereCipher]: [description]"""
ciphers = {}
with open(CIPHER_RESOURCE, "r") as cipher_resource_file:
cipher_data = load(cipher_resource_file, Loader=FullLoader)
... | 1c0a27b36b4c0524b77dcb5c44a3bc840797b226 | 5,250 |
def add_service():
"""
Used to register a new service
"""
form = ServiceForm()
if form.validate_on_submit():
try:
srv = Services()
srv.populate_from_form(form)
srv.authentication.value = {"db":request.form.get('authdb'),"user":request.form.get('authuser'... | 56ce52c293d42710a9d4d5ac57b21f5ba1c0c0ac | 5,251 |
def f_columnas_pips(datos):
"""
Parameters
----------
datos : pandas.DataFrame : df con información de transacciones ejecutadas en Oanda,
después de haber ejecutado f_columnas_tiempos
Returns
-------
datos : pandas.DataFrame : df modificado
Debugging
... | 5d6d47d23dbe16f3619b7e1264d30e91a9acd8ce | 5,252 |
def parse_resolution(resolution):
"""
return: width, height, resolution
"""
resolution = resolution.strip()
splits = resolution.split(',')
return int(splits[0]), int(splits[1]), int(splits[2]) | de937e440c4540d11cedd868e3f4a046baa99f22 | 5,253 |
def link_cube(cube, locale, provider=None, namespace=None,
ignore_missing=False):
"""Links dimensions to the `cube` in the `context` object. The `context`
object should implement a function `dimension(name, locale, namespace,
provider)`. Modifies cube in place, returns the cube.
"""
# ... | 09062ff3fd9dcfeeac7a746557c7f5384e4560a6 | 5,254 |
import argparse
def _parser() -> argparse.Namespace:
"""Take care of all the argparse stuff.
:returns: the args
"""
# parser = GooeyParser(description='Remove : from data files')
parser = argparse.ArgumentParser(description='Combines Nods using ')
parser.add_argument('listspectra', help='List... | 3edcefc24898d15fd67925729590710a4f0d1fb5 | 5,255 |
import inspect
def get_arguments(func):
"""Returns list of arguments this function has."""
if hasattr(func, '__code__'):
# Regular function.
return inspect.getargspec(func).args
elif hasattr(func, '__call__'):
# Callable object.
print(func)
return _get_arguments(fun... | f93133f20c819c590c30e25b6c339c07732daebe | 5,256 |
def _check(isamAppliance, name):
"""
Check if suffix exists
"""
ret_obj = get(isamAppliance)
check_value, warnings = False, ret_obj['warnings']
if warnings == []:
for suffix in ret_obj['data']:
if suffix['name'] == name:
logger.info("Suffix found in embedded ... | be2a6226ebdccb92ec3361df79e50165a22d6981 | 5,257 |
def check_listening_address(address: str) -> bool:
"""Check entered ip address for validity."""
if address == 'localhost':
return True
return address in get_local_addresses() | eaa5cecfee4e8be2947150a537213f4159ee6baf | 5,258 |
import base64
def multibase_b64decode(data):
"""
Follow forge's base64 urlsafe encode convention to decode string
Args:
data(string): encoded string
Returns: bytes
Examples:
>>> multibase_b64decode('aGVsbG8')
b'hello'
"""
if isinstance(data, str):
data =... | fdbc0f937e33d7994737a3a515973598cac3debd | 5,259 |
from typing import List
def parse_ordering_params(param: List[str]) -> List[str]:
"""
Ignores the request to sort by "ord".
Returns a sorting order based on the params and includes "readable_id"
sorting in passed params if the sorting request contains title
otherwise, it returns the requested orde... | a6a5f4665515a292ad2367945a6b8407000d656a | 5,260 |
def file_senzing_rabbitmq():
"""#!/usr/bin/env bash
# --- Functions ---------------------------------------------------------------
function up {
echo -ne "\033[2K${CONTAINER_NAME} status: starting...\r"
mkdir -p ${RABBITMQ_DIR}
chmod 777 ${RABBITMQ_DIR}
if [ "${CONTAINER_VERSION}" == "latest" ]... | 95396425074096d17561b20cd197e77f1d550476 | 5,261 |
def mse(predictions, targets):
"""Calculate MSE: (Mean squared error)
"""
return ((predictions - targets) ** 2).mean() | 79d87a3422d4d24201cae86ee861614c83f6770f | 5,262 |
def export1d(hist):
"""Export a 1-dimensional `Hist` object to uproot
This allows one to write a coffea histogram into a ROOT file, via uproot.
Parameters
----------
hist : Hist
A 1-dimensional histogram object
Returns
-------
out
A ``uproot_methods.cla... | ffe09495a268c68d26f9861e6d732649f2f74497 | 5,263 |
def filter_words(w_map, emb_array, ck_filenames):
""" delete word in w_map but not in the current corpus """
vocab = set()
for filename in ck_filenames:
for line in open(filename, 'r'):
if not (line.isspace() or (len(line) > 10 and line[0:10] == '-DOCSTART-')):
line = lin... | efdef92093acf25c992dba86da25a4118ba728ec | 5,264 |
def get_cache_template(sources, grids, geopackage, table_name="tiles"):
"""
Returns the cache template which is "controlled" settings for the application.
The intent is to allow the user to configure certain things but impose specific behavior.
:param sources: A name for the source
:param grids: sp... | dc83a155d28e0b39f12a7dc7142b61a4bf27512b | 5,265 |
from datetime import datetime
def plotter(fdict):
""" Go """
pgconn = get_dbconn('coop')
ccursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
ctx = get_autoplot_context(fdict, get_description())
station = ctx['station']
lagmonths = ctx['lag']
months = ctx['months']
month ... | 0f41a53336f2bf65805adaf83a8f3f17c006e161 | 5,266 |
def _action_spec():
"""Returns the action spec."""
paddle_action_spec = dm_env_rpc_pb2.TensorSpec(
dtype=dm_env_rpc_pb2.INT8, name=_ACTION_PADDLE)
tensor_spec_utils.set_bounds(
paddle_action_spec,
minimum=np.min(_VALID_ACTIONS),
maximum=np.max(_VALID_ACTIONS))
return {1: paddle_action_sp... | 130b7b2fe9f56d925d4ec1206eb3fb2752fee716 | 5,267 |
def stdin(sys_stdin):
"""
Imports standard input.
"""
inputs = [x.strip("[]\n") for x in sys_stdin]
a = [int(x) for x in inputs[0].split(",")]
x = int(inputs[1][0])
return a, x | 4c34e1bc80da31c6c7aff0d71a0c65f6fc01ed00 | 5,268 |
def _row_key(row):
"""
:param row: a normalized row from STATEMENT_METRICS_QUERY
:return: a tuple uniquely identifying this row
"""
return row['database_name'], row['user_name'], row['query_signature'], row['query_hash'], row['query_plan_hash'] | 2984e0e0b5fcc4e51a26af188e51fe65c52077a2 | 5,269 |
from io import StringIO
def get (url, user_agent=UA, referrer=None):
"""Make a GET request of the url using pycurl and return the data
(which is None if unsuccessful)"""
data = None
databuffer = StringIO()
curl = pycurl.Curl()
curl.setopt(pycurl.URL, url)
curl.setopt(pycurl.FOLLOWLOCATIO... | e18de239a598be249d81c2a15486a66af763bc85 | 5,270 |
def detect_callec(tree):
"""Collect names of escape continuations from call_ec invocations in tree.
Currently supported and unsupported cases::
# use as decorator, supported
@call_ec
def result(ec): # <-- we grab name "ec" from here
...
# use directly on a literal... | 1980c2abd9d5b995a47eab381eb595eb71ced595 | 5,271 |
from typing import List
from typing import Tuple
from typing import Any
def apply_filters(
stream: StreamMeta, filters: List[Tuple[str, str]], config: Any
) -> StreamMeta:
"""Apply enabled filters ordered by priority on item"""
filter_pool = get_filter_pool(filters, config)
for filter_instance in fil... | 2ff50b5d31e84ba69afe694b4beb4116dbc5fc55 | 5,272 |
def threading_d(func):
"""
A decorator to run function in background on thread
Args:
func:``function``
Function with args
Return:
background_thread: ``Thread``
"""
@wraps(func)
def wrapper(*args, **kwags):
background_thread = Thread(target=func, args=(*args,))
ba... | ff4d86ded189737d68d4cdc98c0e9ba9f1a28664 | 5,273 |
def create_anchors_3d_stride(
feature_size,
sizes=[1.6, 3.9, 1.56],
anchor_strides=[0.4, 0.4, 0.0],
anchor_offsets=[0.2, -39.8, -1.78],
rotations=[0, np.pi / 2],
velocities=[],
dtype=np.float32,
):
"""
Args:
feature_size: list [D, H, W](zyx)
sizes: [N, 3] list of list... | 6834d20f44196f5dad19d1917a673196334adf9f | 5,274 |
import hashlib
def sha1_file(filename):
"""
Return the hex string representation of the SHA1 checksum of the filename
"""
s = hashlib.sha1()
with open(filename, "rb") as f:
for line in f:
s.update(line)
return s.hexdigest() | b993ac9f025d69124962905f87b1968617bb33f5 | 5,275 |
def unit_parameters(_bb_spine_db_export: dict, _grid_name: str, _node_name: str, _unit_name: str, _time_index,
_alternative='Base', _eff_level=1, _p_unit=False,
_node_name_if_output=None, _node_name_if_input=None
):
"""
:param _bb_spine_db_export:
... | 698770193d23c8decb240132c462860cd59ef77b | 5,276 |
def read_from_file(file_path):
"""
Read a file and return a list with all the lines in the file
"""
file_in_list = []
with open(file_path, 'r') as f:
for line in f.readlines():
file_in_list.append(line)
return file_in_list | 5fef3a3f50528c1a9786451666ae7e43be282bf9 | 5,277 |
def count(predicate, iterable):
"""
Iterate over iterable, pass the value to the predicate predicate and
return the number of times the predicate returns value considered True.
@param predicate: Predicate function.
@param iterable: Iterable containing the elements to count.
@return: The number o... | 1a2d9a05203f32a6f1a8349b6e31d14cb1b82b71 | 5,278 |
def get_object_from_path(path):
"""
:param path:
dot seperated path. Assumes last item is the object and first part is module
path(str) -
example:
cls = get_object_from_path("a.module.somewhere.MyClass")
you can create a path like this:
class_path = "{0}.{1}".format... | e722b040486288d53fe4a357d81ddec8dfc9820e | 5,279 |
def _get_collection_memcache_key(collection_id, version=None):
"""Returns a memcache key for the collection.
Args:
collection_id: str. ID of the collection.
version: int. Schema version of the collection.
Returns:
str. The memcache key of the collection.
"""
if version:
... | cc054d726d1d2642701803a816e214eed4d9663d | 5,280 |
def biKmeans(dataSet, k, distMeas=calcEuclideanDistance):
"""
二分K-均值算法
:param dataSet:
:param k:
:param distMeas:
:return:
"""
m = np.shape(dataSet)[0]
clusterAssment = np.mat(np.zeros((m, 2)))
centroid0 = np.mean(dataSet, axis=0).tolist()[0]
centList = [centroid0] # create... | 1421dfa95c44e046bd7d729ad343e98eb83bbbcd | 5,281 |
import glob
import os
import logging
def get(directory):
"""Prepare df and gdf with solar atlas tiled data."""
files_list = glob.glob(os.path.join(directory, "*", "*.csv"))
data = []
for file in files_list:
logging.info(file)
tiles = pd.read_csv(file, header=None)
tiles.columns... | 69a32931930ffc5793f84faa09c3aa4b09688b42 | 5,282 |
def cleanup(args, repo):
"""Clean up undeployed pods."""
if args.keep < 0:
raise ValueError('negative keep: %d' % args.keep)
def _is_enabled_or_started(pod):
for instance in pod.iter_instances():
if scripts.systemctl_is_enabled(instance.unit_name):
return True
... | b015c1dbfeb3ad50218afaadfe198123ff2ab6df | 5,283 |
from typing import Dict
def optimizer_builder(
config: Dict):
"""
Instantiate an optimizer.
:param config:
:return:
"""
# --- argument checking
if not isinstance(config, dict):
raise ValueError("config must be a dictionary")
# --- read configuration
decay_rate = c... | 2194408d74d4f03bc54371b98b12c8dbe85fb585 | 5,284 |
def psi(z: float, a: float, b: float) -> float:
"""Penalty function with uniformly bounded derivative (Eq. 20)
Args:
z: Relative distance
a: Cohesion strength
b: Separation strength
"""
c = np.abs(a - b) / (2 * np.sqrt(a * b))
return ((a + b) / 2) * (np.sqrt(1 + (z + c) ** 2)... | df88e57d80a32d95367f30ce52af84308349387a | 5,285 |
def caselessSort(alist):
"""Return a sorted copy of a list. If there are only strings
in the list, it will not consider case.
"""
try:
return sorted(alist, key=lambda a: (a.lower(), a))
except TypeError:
return sorted(alist) | 7558a57e28255817c71846da84230ced49553bb6 | 5,286 |
def EnableRing(serialPort):
""" Enable the ISU to listen for SBD Ring Alerts. When SBD Ring Alert indication is enabled, the 9602 asserts the RI line and issues the unsolicited result
code SBDRING when an SBD Ring Alert is received. """
... | 7036610523802f659c7a69ae192f1009401a6ac3 | 5,287 |
def render(template, **context):
"""Render the given template.
:param template: The template file name or string to render.
:param **context: Context keyword-arguments.
"""
class Undefined(BaseUndefined):
def _fail_with_undefined_error(self, *args, **kwargs):
try:
... | 6680f163e1b89424e88b1a3046784083cdbb6520 | 5,288 |
import re
from io import StringIO
import os
import json
def read(pth, format=None, encoding=None, cols=None, **kwargs):
"""Returns the contents of a file into a string or format-dependent data
type (with special handling for json and csv files).
The format will either be inferred from the file extension ... | 58f1b53b7ece08bc0da44dbd709e107e0ae46dbf | 5,289 |
def audio(src: str) -> str:
""" Insert audio tag
The tag is currently not supported by Nuance, please use `audio_player` kit:
docs/use_kits_and_actions.md
:param src:
:return:
"""
return f'<audio src="{src}"/>' | f9396d5f82eeca27089de41187fd7d5e967cc9cf | 5,290 |
import os
def read(*rnames):
"""
Read content of a file. We assume the file to be in utf8
"""
return open(os.path.join(os.path.dirname(__file__), *rnames), encoding="utf8", mode="r").read() | 15b1acf39188810080c3c47908b011011f4d35ca | 5,291 |
import math
def PerpendicularDistanceToFinish(point_b_angle: float,
point_b: gps_pb2.Point) -> float:
"""
cos(B) = Adjacent / Hypotenuse
https://www.mathsisfun.com/algebra/trig-finding-side-right-triangle.html
"""
return math.cos(math.radians(point_b_angle)) * point_b.star... | 3c18c323c625893ab474c48eb00d48da543956ba | 5,292 |
import requests
from typing import List
def get_revolut_stocks() -> List[str]:
"""
Gets all tickers offered on Revolut trading platform.
Returns:
list(str)
"""
req = requests.get("https://globefunder.com/revolut-stocks-list/")
tickers = list(pd.read_html(req.content)[0]["Symbol"])
... | 3e7f41a04c653a954609cee618cbf89d962fef1d | 5,293 |
def response_text(response_class):
"""
Return the UTF-8 encoding of the API response.
:param response_class: class to cast the response to
:return: Text of the response casted to the specified class
"""
def _inner(f):
@wraps(f)
def wrapper(obj, *args, **kwargs):
res... | 43f0d4cde4790128073440172ed30850794de7a9 | 5,294 |
from typing import Tuple
def create_rankings(
a: Dataset, b: Dataset, n_samples: int = 100, unravel: bool = False, **kwargs: int
) -> Tuple[ndarray, ndarray]:
"""
Sample a dataset 'a' with 'n' negative samples given interactions in dataset 'a'
and 'b'.
Practically, this function allows you to gen... | 28282fc14d02b7f93d58d209d143a315e7b25422 | 5,295 |
def make_even(x):
"""Make number divisible by 2"""
if x % 2 != 0:
x -= 1
return x | 10129eb6abd718414d0ada53915672dcf4d7b5b6 | 5,296 |
def get_num_vehicles(session, query_filters):
"""Gets the total number of annotations."""
# pylint: disable-msg=E1101
num_vehicles_query = session.query(
func.count(Vehicle.id)) \
.join(Photo) \
.filter(Photo.test == True) \
# pylint: enable-msg=E1101
for query_filter i... | bf626edad29b136bb595dabb7e878649c08c0d84 | 5,297 |
def task_status_edit(request, status_id, response_format='html'):
"""TaskStatus edit"""
status = get_object_or_404(TaskStatus, pk=status_id)
if not request.user.profile.has_permission(status, mode='w'):
return user_denied(request, message="You don't have access to this Task Status")
if request... | 593384ab55bf889a1e87d7909e848a2dbacad68e | 5,298 |
import platform
def is_windows_system():
"""
| ##@函数目的: 获取系统是否为Windows
| ##@参数说明：True or False
| ##@返回值：
| ##@函数逻辑：
| ##@开发人：jhuang
| ##@时间：
"""
return 'Windows' in platform.system() | 6bfe296188b9dccf8338f0b2bbaaf146d9b22243 | 5,299 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.