content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import time
def get_ntp_time(ntp_server_url):
"""
通过ntp server获取网络时间
:param ntp_server_url: 传入的服务器的地址
:return: time.strftime()格式化后的时间和日期
"""
ntp_client = ntplib.NTPClient()
ntp_stats = ntp_client.request(ntp_server_url)
fmt_time = time.strftime('%X', time.localtime(ntp_stats.tx_time))... | 17881970361994e329e1154478c8abb8171461f9 | 16,100 |
def read_data(path, names, verbose=False):
"""
Read time-series from MATLAB .mat file.
Parameters
----------
path : str
Path (relative or absolute) to the time series file.
names : list
Names of the requested time series incl. the time array itself
verbose : bool, optional
... | 978870d4517b5e5ab66186747c326794d6d43814 | 16,101 |
async def search(q: str, person_type: str = 'student') -> list:
"""
Search by query.
:param q: `str` query to search for
:param person_type: 'student', 'lecturer', 'group', 'auditorium'
:return: list of results
"""
url = '/'.join((BASE_URL, SEARCH_INDPOINT))
params = {'term': q,
... | 83913866f45a44202ccddbc9352fef9799caf751 | 16,102 |
def format_data_hex(data):
"""Convert the bytes array to an hex representation."""
# Bytes are separated by spaces.
return ' '.join('%02X' % byte for byte in data) | 27239052d9ca0b12c19977e79d512e0cab04182e | 16,103 |
import glob
import os
def eval_test(test_path, gt_path, test_prefix='', gt_prefix='',
test_format='png', gt_format='png', exigence=2, desync=0):
"""
Evaluates some test results against a given ground truth
:param test_path: (str) relative or absolute path to the test results images
:par... | b71475bf3c51e5a69e8498e60b8131a00fcd3d6f | 16,104 |
from datetime import datetime
import requests
import dateutil
def get_installation_token(installation):
"""
Get access token for installation
"""
now = datetime.datetime.now().timestamp()
if installation_token_expiry[installation] is None or now + 60 > installation_token_expiry[installation]:
... | e5bf43f601ca9e155dcf296179d778b78b2cc67a | 16,105 |
def disp(cog_x, cog_y, src_x, src_y):
"""
Compute the disp parameters
Parameters
----------
cog_x: `numpy.ndarray` or float
cog_y: `numpy.ndarray` or float
src_x: `numpy.ndarray` or float
src_y: `numpy.ndarray` or float
Returns
-------
(disp_dx, disp_dy, disp_norm, disp_ang... | e9d8166827e86a8e2180ba357a450aca817fdff4 | 16,106 |
def get_landmark_from_prob(prob, thres=0.5, mode="mean", binary_mask=False):
"""Compute landmark location from the model probablity maps
Inputs:
prob : [RO, E1], the model produced probablity map for a landmark
thres : if np.max(prob)<thres, determine there is no landmark detected
m... | fad614088e587e389f15b0700bf442a956d498b0 | 16,107 |
import socket
def request(
url,
timeout: float,
method="GET",
data=None,
response_encoding="utf-8",
headers=None,
):
"""
Helper function to perform HTTP requests
"""
req = Request(url, data=data, method=method, headers=headers or {})
try:
return urlopen(req, timeout... | 80f130101290442d538fa3f416f5650800547c6b | 16,108 |
from typing import Any
from typing import Optional
from typing import get_args
from typing import get_origin
def get_annotation_affiliation(annotation: Any, default: Any) -> Optional[Any]:
"""Helper for classifying affiliation of parameter
:param annotation: annotation record
:returns: classified value o... | db6efd7dfb0ed0272e7491547669de8f235b2b35 | 16,109 |
import os
import glob
def find_config_files(
path=['~/.vcspull'], match=['*'], filetype=['json', 'yaml'], include_home=False
):
"""Return repos from a directory and match. Not recursive.
Parameters
----------
path : list
list of paths to search
match : list
list of globs to se... | 3138839e8914451a4138c3e24d375089c5c866b0 | 16,110 |
def sort_dict(original):
"""Recursively sorts dictionary keys and dictionary values in alphabetical order"""
if isinstance(original, dict):
res = (
dict()
) # Make a new "ordered" dictionary. No need for Collections in Python 3.7+
for k, v in sorted(original.items()):
... | 8c194af76160b0e4d3bad135720e051a4d4622b0 | 16,111 |
import requests
def playonyt(topic):
"""Will play video on following topic, takes about 10 to 15 seconds to load"""
url = 'https://www.youtube.com/results?q=' + topic
count = 0
cont = requests.get(url)
data = str(cont.content)
lst = data.split('"')
for i in lst:
count+=1
if... | 49f4285dc0e0086d30776fc0668bac0e4c19dbc5 | 16,112 |
def train_classifier(classifier, features, labels):
"""This function must concern itself with training the classifier
on the specified data."""
return classifier.fit(features, labels) | ef74548aeb6e245d8728caf3205163c249046aae | 16,113 |
def work_on_disk(dev, root_mb, swap_mb, image_path):
"""Creates partitions and write an image to the root partition."""
root_part = "%s-part1" % dev
swap_part = "%s-part2" % dev
if not is_block_device(dev):
LOG.warn(_("parent device '%s' not found"), dev)
return
make_partitions(dev,... | 195ded6deae958b7efa41bcfdda1d3d68cabb23d | 16,114 |
def get_annotation_names(viewer):
"""Detect the names of nodes and edges layers"""
layer_nodes_name = None
layer_edges_name = None
for layer in viewer.layers:
if isinstance(layer, napari.layers.points.points.Points):
layer_nodes_name = layer.name
elif isinstance(layer, napar... | 20e64a6719b945eceda341d5a42da178818cb1a1 | 16,115 |
def remap(kx,ky,lx,ly,qomt,datai):
"""
remap the k-space variable back to shearing
periodic frame to reflect the time dependent
Eulerian wave number
"""
ndim = datai.ndim
dim = np.array(datai.shape)# datai[nz,ny,nx]
sh_data = np.empty([dim[0],dim[1],dim[2]])
tp_data = np.empty([dim[0],dim[2]])
sh... | 6ea415df88c0db2ba26ef0fc8daa35b12a101ef8 | 16,116 |
def fips_disable():
"""
Disables FIPS on RH/CentOS system. Note that you must reboot the
system in order for FIPS to be disabled. This routine prepares
the system to disable FIPS.
CLI Example:
.. code-block:: bash
salt '*' ash.fips_disable
"""
installed_fips_pkgs = _get_install... | d31cc5ad6dd71ec0f3d238051a7b2a64b311c0fd | 16,117 |
import java.lang
import sys
def get_os_platform():
"""return platform name, but for Jython it uses os.name Java property"""
ver = sys.platform.lower()
if ver.startswith('java'):
ver = java.lang.System.getProperty("os.name").lower()
print('platform: %s' % (ver))
return ver | df717ae12fadf0ced75f4f1148ceed11701a7f25 | 16,118 |
from datetime import datetime
def buy_sell_fun_mp_org(datam, S1=1.0, S2=0.8):
"""
斜率指标交易策略标准分策略
"""
start_t = datetime.datetime.now()
print("begin-buy_sell_fun_mp:", start_t)
dataR = pd.DataFrame()
for code in datam.index.levels[1]:
# data = price.copy()
# price = datam.que... | 8d3b78b9d266c3c39b8491677caa0f4dfb9f839a | 16,119 |
import collections
import abc
def marshall_namedtuple(obj):
"""
This method takes any atomic value, list, dictionary or namedtuple,
and recursively it tries translating namedtuples into dictionaries
"""
recurse = lambda x: map(marshall_namedtuple, x)
obj_is = partial(isinstance, obj)
if ha... | 87d24fe1b273bfcf481679a96710be757baf08a5 | 16,120 |
import torch
def prep_image(img, inp_dim):
"""
Prepare image for inputting to the neural network.
Returns a Variable
"""
# print("prepping images")
img = cv2.resize(img, (inp_dim, inp_dim))
img = img[:,:,::-1].transpose((2,0,1)).copy()
img = torch.from_numpy(img).float().div(255... | 02ebc73a32a24d59c53da9bfb99485f3a4f6dee2 | 16,121 |
from typing import Dict
from typing import List
import math
def best_broaders(supers_for_all_entities: Dict,
per_candidate_links_and_supers: List[Dict],
num_best: int = 5,
super_counts_field: str = "broader_counts",
doprint=False,
... | 9aa9826c43e67a28eeca463b107296e093709246 | 16,122 |
def clump_list_sort(clump_list):
"""Returns a copy of clump_list, sorted by ascending minimum density. This
eliminates overlap when passing to
yt.visualization.plot_modification.ClumpContourCallback"""
minDensity = [c['Density'].min() for c in clump_list]
args = np.argsort(minDensity)
list... | 732e747e36c37f9d65ef44b6aa060d5c9d04e3d1 | 16,123 |
from typing import Dict
from typing import Any
from typing import Type
import types
from typing import Optional
def _prepare_artifact(
metadata_handler: metadata.Metadata,
uri: Text,
properties: Dict[Text, Any],
custom_properties: Dict[Text, Any],
reimport: bool, output_artifact_class: Type[types.... | d30dcd579c73c71173f10207ab80d05c761c7185 | 16,124 |
import re
def ParseCLILines(lines, skipStartLines=0, lastSkipLineRe=None, skipEndLines=0):
"""Delete first few and last few lines in an array"""
if skipStartLines > 0:
if lastSkipLineRe != None:
# sanity check. Make sure last line to skip matches the given regexp
if None == re.... | dc445765f42df25b8d046e3f2303d85109a3d419 | 16,125 |
def initialize_parameters(n_x, n_h, n_y):
"""
Argument:
n_x -- size of the input layer
n_h -- size of the hidden layer
n_y -- size of the output layer
Returns:
params -- python dictionary containing your parameters:
W1 -- weight matrix of shape (n_h, n_x)
... | 785985b79b9284ba8c6058c8e9c4018955407cf8 | 16,126 |
import os
def _NormalizedSource(source):
"""Normalize the path.
But not if that gets rid of a variable, as this may expand to something
larger than one directory.
Arguments:
source: The path to be normalize.d
Returns:
The normalized path.
"""
normalized = os.path.normpath(source)
if sou... | 5ecaeddf2c3941bbfb0d89ee902a961f7aeab838 | 16,127 |
from datetime import datetime
def get_df_from_sampled_trips(step_trip_list, show_service_data=False, earliest_datetime=None):
"""Get dataframe from sampled trip list.
Parameters
----------
step_trip_list : list of lists
List of trip lists occuring in the same step.
show_service_data: bool... | 36bba80f0c46862df0390cf4e4279eeb33002e86 | 16,128 |
def compute_v_y(transporter, particles):
"""
Compute values of V y on grid specified in bunch configuration
:param transporter: transport function
:param particles: BunchConfiguration object, specification of grid
:return: matrix with columns: x, theta_x, y, theta_y, pt, V y
"""
return __com... | 4a17e0c0e4612534483187b6779bcf5c179c0fcc | 16,129 |
def gabor_kernel_nodc(frequency, theta=0, bandwidth=1, gamma=1,
n_stds=3, offset=0):
"""
Return complex 2D Gabor filter kernel with no DC offset.
This function is a modification of the gabor_kernel function of scikit-image
Gabor kernel is a Gaussian kernel modulated by a ... | f725561a1eb56b6e23c1046c33b0abec49201122 | 16,130 |
def run_fn(fn_args: TrainerFnArgs):
"""Train the model based on given args.
Args:
fn_args: Holds args used to train the model as name/value pairs.
"""
# get transform component output
tf_transform_output = tft.TFTransformOutput(fn_args.transform_output)
# read input data
train_dataset... | 15c8202ad6955052bbd1da2984aedb9887c390af | 16,131 |
def log_likelihood(X, Y, Z, data, boolean=True, **kwargs):
"""
Log likelihood ratio test for conditional independence. Also commonly known
as G-test, G-squared test or maximum likelihood statistical significance
test. Tests the null hypothesis that X is independent of Y given Zs.
Parameters
--... | 00493131d78506c5a6cbb9e04bda51b69f1a04ca | 16,132 |
def conjugada_matriz_vec(mat:list):
"""
Funcion que realiza la conjugada de una matriz o vector complejo.
:param mat: Lista que representa la matriz o vector complejo.
:return: lista que representa la matriz o vector resultante.
"""
fila = len(mat)
columnas = len(mat[0])
resul = []
f... | ad883dae9161f4e60f933caf93703544e16bfb4d | 16,133 |
def features2matrix(feature_list):
"""
Args:
feature_list (list of Feature):
Returns:
(np.ndarray, list of str): matrix and list of key of features
"""
matrix = np.array([feature.values for feature in feature_list], dtype=float)
key_lst = [feature.key for feature in feature_li... | f60cdb904489cca3ab926dbc8d396804367e4a7a | 16,134 |
import os
def GenDataFrameFromPath(path, pattern='*.png', fs=False):
"""
generate a dataframe for all file in a dir with the specific pattern of file name.
use: GenDataFrameFromPath(path, pattern='*.png')
"""
fnpaths = list(path.glob(pattern))
df = pd.DataFrame(dict(zip(['fnpath'], [fnpaths]))... | 899026131fe8eb18a2c5c6cf0df6a4ebfa287986 | 16,135 |
import re
def is_heading(line):
"""Determine whether a given line is a section header
that describes subsequent lines of a report.
"""
has_cattle = re.search(r'steer?|hfrs?|calves|cows?|bulls?', line, re.IGNORECASE)
has_price = re.search(r'\$[0-9]+\.[0-9]{2}', line)
return bool(has_cattle) a... | ccbc80f7db61f7ba82aa88e54112d1995d457764 | 16,136 |
def get_channel_messages(channel_id):
""" Holt fuer einen bestimmten Kanal die Nachrichten aus der Datenbank"""
session = get_cassandra_session()
future = session.execute_async("SELECT * FROM messages WHERE channel_id=%s", (channel_id,))
try:
rows = future.result()
except Exception:
... | 7a3821dd8e93c4d49dfeecea200a881fdcb3f1a4 | 16,137 |
def train(traj,
pol, targ_pol, qf, targ_qf,
optim_pol, optim_qf,
epoch, batch_size, # optimization hypers
tau, gamma, # advantage estimation
sampling,
):
"""
Train function for deep deterministic policy gradient
Parameters
----------
tra... | 14c09f3ce1f30366be3b8d0e0b965bdc1c677834 | 16,138 |
import os
def upsample_gtiff(files: list, scale: float) -> list:
"""
Performs array math to artificially increase the resolution of a geotiff. No interpolation of values. A scale
factor of X means that the length of a horizontal and vertical grid cell decreases by X. Be careful, increasing the
resolut... | 93e158d4beae9d4d179e9908e6dce639de1770d3 | 16,139 |
def merge_dicts(dict1, dict2):
""" _merge_dicts
Merges two dictionaries into one.
INPUTS
@dict1 [dict]: First dictionary to merge.
@dict2 [dict]: Second dictionary to merge.
RETURNS
@merged [dict]: Merged dictionary
"""
merged = {**dict1, **dict2}
return merged | 67e96ba9c9831e6e2aa4bbd6cd8b8d1d5edb93c4 | 16,140 |
import pagure.api
import pagure.lib.query
def check_api_acls(acls, optional=False):
"""Checks if the user provided an API token with its request and if
this token allows the user to access the endpoint desired.
:arg acls: A list of access control
:arg optional: Only check the API token is valid. Skip... | 81d658036c5b31e3471e48ef44f4eb26e571c49a | 16,141 |
import os
def get_data():
"""
Return data files
:return:
"""
data = {}
for df in get_manifest():
d, f = os.path.split(df)
if d not in data:
data[d] = [df]
else:
data[d].append(df)
return list(data.items()) | 3add894e03e153dc82aebcaca3a0099ac98b0a1c | 16,142 |
def china_province_head_fifteen():
"""
各省前15数据
:return:
"""
return db_request_service.get_china_province_head_fifteen(ChinaTotal, ChinaProvince) | 18dc3f22c05b3580bcd983361efc03bd3cdae43b | 16,143 |
import tempfile
import os
from datetime import datetime
import glob
import shutil
def exec_sedml_docs_in_archive(sed_doc_executer, archive_filename, out_dir, apply_xml_model_changes=False,
sed_doc_executer_supported_features=(Task, Report, DataSet, Plot2D, Curve, Plot3D, Surface),
... | 508ac3f83e7365c58f830081bf16470e0ad43e43 | 16,144 |
def pipeline(x_train,
y_train,
x_test,
y_test,
param_dict=None,
problem='classification'):
"""Trains and evaluates a DNN classifier.
Args:
x_train: np.array or scipy.sparse.*matrix array of features of training data
y_train: np.array 1-D arra... | f01e20851c91dd9f6b3db889fdf713edc1eb37b9 | 16,145 |
def model_selection(modelname, num_out_classes,
dropout=None):
"""
:param modelname:
:return: model, image size, pretraining<yes/no>, input_list
"""
if modelname == 'xception':
return TransferModel(modelchoice='xception',
num_out_classes=num_o... | 67ba26ab4f7cbe8f4540eb10f2ef6e598b49ea2f | 16,146 |
def Packet_computeBinaryPacketLength(startOfPossibleBinaryPacket):
"""Packet_computeBinaryPacketLength(char const * startOfPossibleBinaryPacket) -> size_t"""
return _libvncxx.Packet_computeBinaryPacketLength(startOfPossibleBinaryPacket) | 58139b8d874d9292e63b6eb6afdbd9c5c2fa6f9d | 16,147 |
def build_check_query(check_action: Action) -> str:
"""Builds check query from action item
Parameters
----------
check_action : action
check action to build query from
Returns
-------
str
query to execute
"""
return f"""
UPDATE todos
SET completed = ... | a6b8f5b328e3bb9eedf61a325e54d6cae9704a55 | 16,148 |
import itertools
def gen_positions(n, n_boulders):
"""Generates state codes for boulders. Includes empty rows
Parameters:
n: number of rows/columns
n_boulders: number of boulders per row
return value:
Possible boulder and alien states
"""
boulder_positions=[]; b_p=[]
a... | 0a20594f2e021bf8e190f6c7c726159fde0b8367 | 16,149 |
def analysis_linear_correlation(data1:np.array,
data2:np.array,
alpha:float = .05,
return_corr:bool = True,
verbose:bool = False)->bool:
"""
## Linear correlation analysis to test i... | 6eaf34a12281949236d28143399024ed30e834ad | 16,150 |
def sha256(buffer=None):
"""Secure Hash Algorithm 2 (SHA-2) with 256 bits hash value."""
return Hash("sha256", buffer) | 2e33c38c0f7b9dd019104a18e6842243773686ca | 16,151 |
import math
import torch
def nmc_eig(model, design, observation_labels, target_labels=None,
N=100, M=10, M_prime=None, independent_priors=False):
"""
Nested Monte Carlo estimate of the expected information
gain (EIG). The estimate is, when there are not any random effects,
.. math::
... | 8de69e87677a4a74fd04ce4cf302221121d00b2d | 16,152 |
import scipy
def _orient_eigs(eigvecs, phasing_track, corr_metric=None):
"""
Orient each eigenvector deterministically according to the orientation
that correlates better with the phasing track.
Parameters
----------
eigvecs : 2D array (n, k)
`k` eigenvectors (as columns).
phasing... | d6feebbd7b7748549ebc494bf8b00f0d9e313f7c | 16,153 |
def test_CreativeProject_auto_multivariate_functional(max_iter, max_response, error_lim, model_type):
"""
test that auto method works for a particular multivariate (bivariate) function
"""
# define data
covars = [(0.5, 0, 1), (0.5, 0, 1)] # covariates come as a list of tuples (one per covariate: (... | ee0cc1d34a1836c8ea9ec2b23de175f4b6d8ca75 | 16,154 |
def crossValidate(x, y, cv=5, K=None):
"""
:param y: N*L ranking vectors
:return:
"""
results = {"perf": []}
## cross validation ##
np.random.seed(1100)
kf = KFold(n_splits=cv, shuffle=True, random_state=0)
for train, test in kf.split(x):
x_train = x[train, :]
y_trai... | 820f5b53a38d2a64a3a1ee740d0fded020000bb7 | 16,155 |
def make_word_groups(vocab_words):
"""
:param vocab_words: list of vocabulary words with a prefix.
:return: str of prefix followed by vocabulary words with
prefix applied, separated by ' :: '.
This function takes a `vocab_words` list and returns a string
with the prefix and the words... | f940c602939ca3a9bab013f5847918f7ba4536ae | 16,156 |
def gpi_g10s40(rescale=False):
"""
Multiply by the 'rescale' factor to adjust hole sizes and centers in entrance pupil (PM)
(Magnify the physical mask coordinates up to the primary mirror size)
"""
demag = gpi_mag_asdesigned()
if rescale:
demag = demag/rescale # rescale 1.1 gives a bigge... | 4be151f7e99332be0f67d00619fe75def90c2b5d | 16,157 |
import inspect
def test_close_sections():
"""Parse sections without blank lines in between."""
def f(x, y, z):
"""
Parameters
----------
x :
X
y :
Y
z :
Z
Raises
------
Error2
error.
... | 793d92d989f3caa020c06ea798f7f34703abd747 | 16,158 |
import sys
def get_good_contours(proc_image, image, bb, savedir, max_num_add=None):
"""
Adapted from `click_and_crop_v3.py`, except that we have to make the contours.
Here, we're going to inspect and check that the contours are reasonable.
Returns a list of processed contours that I'll then use for l... | 4437c44c249b1bd4bf6bcef90d38defdcbe9bc48 | 16,159 |
def _int_converter(value):
"""Convert string value to int.
We do not use the int converter default exception since we want to make
sure the exact http response code.
Raises: exception_handler.BadRequest if value can not be parsed to int.
Examples:
/<request_path>?count=10 parsed to {'count':... | 6b5c99635211bf8ce2e3c2adc784f2a4e9ee355f | 16,160 |
from typing import List
def split_rule(rules, rule_name, symbols_to_extract: List[str], subrule_name: str):
"""
Let only options which are starting with symbols from symbols_to_extract.
Put the rest to a subrule.
"""
r = rule_by_name(rules, rule_name)
assert isinstance(r.body, Antlr4Selection... | aa4d2aac62c488e3cd8d002556edea3aaef7185b | 16,161 |
def ESS(works_prev, works_incremental):
"""
compute the effective sample size (ESS) as given in Eq 3.15 in https://arxiv.org/abs/1303.3123.
Parameters
----------
works_prev: np.array
np.array of floats representing the accumulated works at t-1 (unnormalized)
works_incremental: np.array
... | 514ca2462708a4c163f45e92854159d50eb5f3a8 | 16,162 |
def new_line_over():
"""Creates a new line over the cursor.
The cursor is also moved to the beginning of the new line. It is
not possible to create more than one new line over the cursor
at a time for now.
Usage:
`In a config file:`
.. code-block:: yaml
- new_line_over:
`Usi... | 41da4d301240a8ea3d9108dd1d957a30cff1097b | 16,163 |
import json
def lambda_handler(event, context):
"""Calls custom job waiter developed by user
Arguments:
event {dict} -- Dictionary with details on previous processing step
context {dict} -- Dictionary with details on Lambda context
Returns:
{dict} -- Dictionary with Processed Buc... | e5a4055a39d0df1fabd3ad5f70a2859524378f44 | 16,164 |
def put_path(components, value):
"""Recursive function to put value in component"""
if len(components) > 1:
new = components.pop(0)
value = put_path(components, value)
else:
new = components[0]
return {new: value} | 77db4064a77cf1cdcde1d74d901410525722b66e | 16,165 |
def con_orthogonal_checkboard(X,c_v1,c_v2,c_v3,c_v4,num,N):
"""for principal / isothermic / developable mesh / aux_diamond / aux_cmc
(v1-v3)*(v2-v4)=0
"""
col = np.r_[c_v1,c_v2,c_v3,c_v4]
row = np.tile(np.arange(num),12)
d1 = X[c_v2]-X[c_v4]
d2 = X[c_v1]-X[c_v3]
d3 = X[c_v4]-X[c_v2]
... | f05228d6caa49f60a2a9f515ce5590e6f13127e0 | 16,166 |
def _PropertyGridInterface_GetPropertyValues(self, dict_=None, as_strings=False, inc_attributes=False):
"""
Returns all property values in the grid.
:param `dict_`: A to fill with the property values. If not given,
then a new one is created. The dict_ can be an object as well,
in which ... | 06974bec88351d5e8743b43e7c0495bb40545ef0 | 16,167 |
def get_pipelines(exp_type, cal_ver=None, context=None):
"""Given `exp_type` and `cal_ver` and `context`, locate the appropriate SYSTEM CRDSCFG
reference file and determine the sequence of pipeline .cfgs required to process that
exp_type.
"""
context = _get_missing_context(context)
cal_ver = _g... | 7fb4a02ffe7598df4621b2fd4a6863094616fd41 | 16,168 |
def distance_to_line(p,a,b):
"""
Computes the perpendicular distance from a point to an infinite line.
Parameters
----------
p : (x,y)
Coordinates of a point.
a : (x,y)
Coordinates of a point on a line.
b : (x,y)
Coordinates of another point on a line.
Return... | 1b1d0ef37587cd8cb0f5730ac78c39ec8b42faec | 16,169 |
def pearsonr(A, B):
"""
A broadcasting method to compute pearson r and p
-----------------------------------------------
Parameters:
A: matrix A, (i*k)
B: matrix B, (j*k)
Return:
rcorr: matrix correlation, (i*j)
pcorr: matrix correlation p, (i*j)
Example:
... | f66ca9eb6c6367580043ab9d512400c826d30d39 | 16,170 |
def inst_bench(dt, gt, bOpts, tp=None, fp=None, score=None, numInst=None):
"""
ap, rec, prec, npos, details = inst_bench(dt, gt, bOpts, tp = None, fp = None, sc = None, numInst = None)
dt - a list with a dict for each image and with following fields
.boxInfo - info that will be used to cpmpute the ... | 9f8e12863205c24247003a4c95cf52f99086a6a6 | 16,171 |
from typing import Tuple
from typing import List
def _tee(
cmd: str, executable: str, abort_on_error: bool
) -> Tuple[int, List[str]]:
"""
Execute command "cmd", capturing its output and removing empty lines.
:return: list of strings
"""
_LOG.debug("cmd=%s executable=%s", cmd, executable)
... | 4aafdac48b9deb4810b96f99ffc178464b79372a | 16,172 |
def normalized_str(token):
"""
Return as-is text for tokens that are proper nouns or acronyms, lemmatized
text for everything else.
Args:
token (``spacy.Token`` or ``spacy.Span``)
Returns:
str
"""
if isinstance(token, SpacyToken):
return token.text if preserve_case(... | c5e30b48716fa99bfbcf8252b3ecd018cc921cbe | 16,173 |
def scatter_nd(*args, **kwargs):
""" See https://www.tensorflow.org/api_docs/python/tf/scatter_nd .
"""
return tensorflow.scatter_nd(*args, **kwargs) | 5b5d457c91df73314de6d81c105132d6b69eb1aa | 16,174 |
from typing import Union
from typing import Tuple
def concatenate_sequences(X: Union[list, np.ndarray], y: Union[list, np.ndarray],
sequence_to_value: bool = False) \
-> Tuple[np.ndarray, np.ndarray, np.ndarray]:
"""
Concatenate multiple sequences to scikit-learn compatible n... | b4b2489eeb601ce5378f6cf7b2cce7daf68bdf1d | 16,175 |
def get_export_table_operator(table_name, dag=None):
"""Get templated BigQueryToCloudStorageOperator.
Args:
table_name (string): Name of the table to export.
dag (airflow.models.DAG): DAG used by context_manager. e.g. `with get_dag() as dag: get_export_table_operator(..., dag=dag)`. Defaults to... | b1fd75caf10bc5fefbba4b5702bf05ab1ec6be6c | 16,176 |
def run_command_with_code(cmd, redirect_output=True,
check_exit_code=True):
"""Runs a command in an out-of-process shell.
Returns the output of that command. Working directory is self.root.
"""
if redirect_output:
stdout = sp.PIPE
else:
stdout = None
p... | 45e8592def8290f45458a183bed410072cc15000 | 16,177 |
import logging
async def delete_project(
delete_project_request: DeleteProject, token: str = Depends(oauth2_scheme)
):
"""[API router to delete project on AWS Rekognition]
Args:
delete_project_request (DeleteProject): [AWS Rekognition create project request]
token (str, optional): [Bearer... | 5711adf3ee9177952561d825a733ee169b6f97b0 | 16,178 |
from typing import Union
import ast
def _create_element_invocation(span_: span.Span, callee: Union[ast.NameRef,
ast.ModRef],
arg_array: ast.Expr) -> ast.Invocation:
"""Creates a function invocation on the first element of ... | 0449c27fc6e7f16054bddfd99bd9e64109b9ee0e | 16,179 |
import os
import logging
def _CreateClassToFileNameDict(test_apk):
"""Creates a dict mapping classes to file names from size-info apk."""
constants.CheckOutputDirectory()
test_apk_size_info = os.path.join(constants.GetOutDirectory(), 'size-info',
os.path.basename(test_apk) + ... | 96ba6c74217d212ee50d454225f334528919292c | 16,180 |
import time
def train_deeper_better(train_data, train_labels, test_data, test_labels, params):
"""Same as 'train_deeper', but now with tf.contrib.data.Dataset input pipeline."""
default_params = {
'regularization_coeff': 0.00001,
'keep_prob': 0.5,
'batch_size': 128,
'fc1_size':... | c2d2c56ac7dbb52d072f2397540d4d793ac0d0c4 | 16,181 |
def redirect_return():
"""Redirects back from page with url generated by url_return."""
return redirect(str(Url.get_return())) | f1ce09afef02651e0331a930e53211f9eb4f2a54 | 16,182 |
def setup(coresys: CoreSys) -> EvaluateBase:
"""Initialize evaluation-setup function."""
return EvaluateOperatingSystem(coresys) | daf3bd3ddca0085d6305535b27c28d70ac240dac | 16,183 |
def _weight_initializers(seed=42):
"""Function returns initilializers to be used in the model."""
kernel_initializer = tf.keras.initializers.TruncatedNormal(
mean=0.0, stddev=0.02, seed=seed
)
bias_initializer = tf.keras.initializers.Zeros()
return kernel_initializer, bias_initializer | 1c7652b787d4a69d3a43983c2c291c09337d06d0 | 16,184 |
import os
def inputs(eval_data, data_dir, batch_size):
"""Construct input for eye evaluation using the Reader ops.
Args:
eval_data: bool, indicating if one should use the train or eval data set.
data_dir: Path to the eye data directory.
batch_size: Number of images per batch.
Returns:
... | e5b8457bcc370df37e995db100ac5d0470df2fa8 | 16,185 |
def get_non_ready_rs_pod_names(namespace):
"""
get names of rs pods that are not ready
"""
pod_names = []
rs_pods = get_pods(namespace, selector='redis.io/role=node')
if not rs_pods:
logger.info("Namespace '%s': cannot find redis enterprise pods", namespace)
return []
fo... | 167922c4fa03127a3371f2c5b7516bb6462c6253 | 16,186 |
def lookup_material_probase(information_extractor, query, num):
"""Lookup material in Probase"""
material_params = {
'instance': query,
'topK': num
}
result = information_extractor.lookup_probase(material_params)
rank = information_extractor.rank_probase_result_material(result)
r... | 9cecf99e3a9689f85788df21ef01d4e86c9a392d | 16,187 |
def get_unexpected_exit_events(op):
"""Return all unexpected exit status events."""
events = get_events(op)
if not events:
return None
return [e for e in events if is_unexpected_exit_status_event(e)] | 171158d16c34e2764bc8c91f4888863c162043c4 | 16,188 |
async def delete_user(username: str) -> GenericResponse:
"""Delete concrete user by username"""
try:
await MongoDbWrapper().remove_user(username)
except Exception as exception_message:
raise DatabaseException(error=exception_message)
return GenericResponse(detail="Deleted user") | 8b2756922ab79d058097105fa8cd000396350a3b | 16,189 |
def get_changelog():
"""download ChangeLog.txt from github, extract latest version number, return a tuple of (latest_version, contents)
"""
# url will be chosen depend on frozen state of the application
source_code_url = 'https://github.com/pyIDM/pyIDM/raw/master/ChangeLog.txt'
new_release_url = 'h... | 7c8df0cbc5fa85642e4e23106006445f59539a1f | 16,190 |
def get_train_tags(force=False):
""" Download (if needed) and read the training tags.
Keyword Arguments
-----------------
force : bool
If true, overwrite existing data if it already exists.
"""
download_train_tags(force=force)
return read_tags(train_tags_file_path) | 5d67422a275011a719c0121206397fb99e6e4f70 | 16,191 |
def select_own(ligands, decoys, scores):
"""Select ligand ids and decoy ids from full ranked ids."""
#scores format is full OUTDOCK line
selected = set(ligands)
selected.update(decoys)
results = []
for scoreline in scores:
#id = scoreline[extract_all.zincCol] #refer to correct column alw... | 444555a30571e61fad7eac36389e2dd638313744 | 16,192 |
def create_app():
"""
生成FatAPI对象
:return:
"""
app = FastAPI(
debug=settings.DEBUG,
title=settings.PROJECT_NAME, # 项目名称
description=settings.DESCRIPTION, # 项目简介
docs_url=f"{settings.API_V1}/docs", # 自定义 docs文档的访问路径
redoc_url=f"{settings.API_V1}/redocs", # 禁... | 10e106e9968344cf8382ecbd24b1029b3548be79 | 16,193 |
def cmp_text_file(text, file):
"""returns True when text and file content are identical
"""
fh = open(file)
ftext = fh.read()
fh.close()
return cmp(ftext, text) | ecf10004cd3fa230d0e794c4c89e45ca91e7e40e | 16,194 |
def get_alignment_summary(seq_info):
"""
Determine the consensus sequence of an alignment, and create position matrix
Definition of consensus: most common base represented at that position.
"""
consensus_sequence = []
position_matrix = []
for position in seq_info:
#Ignore any ambi... | f91e4dcea2f4570a194524970fdbc95eacc455b2 | 16,195 |
def calculate_pcx_chord_emission(impact_factor, Ti, w0, mu, Lnu, Vouter, rmax=40.0, nr=101, nlambda=2000,
Lne=2.5, R_outer=35):
"""Calculates PCX emission with only the outer boundary spinning for a given impact factor
Args:
impact_factor (float): impact factor for chor... | 611d80973d3767b16fbd26c7ccebee8fc5390c95 | 16,196 |
def _get_variables(exp:Experiment, config: dict) -> dict:
"""Process the configuration's variables before rendering it"""
return {key: value.format(exp=exp) for key, value in config.get("variables", {}).items()} | 1b819c93ef079557908c216dc5c9fa75d55fe0f3 | 16,197 |
def func_calc_M(S):
"""
Use molecules structure/symbol to calculate molecular weight
Parameter:
S : structrue in a format: (atomType number) separated by '-' or blank space
number of '-' and spaces does not matter
precendent: '-' > blank space
Examp... | ed8e3d5ccd5305caccfac64cb0ecb200fde650eb | 16,198 |
def find_NN(ngbrof, ngbrin, distance_ULIM=NP.inf, flatten=False, parallel=False,
nproc=None):
"""
-----------------------------------------------------------------------------
Find all nearest neighbours of one set of locations in another set of
locations within a specified distance.
... | 131d136ad92900f3ee624982f70234070d0d76a6 | 16,199 |
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