content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def circle_location_Pass(circle_, image_, margin=0.15):
"""
Function for check if the circle_ is overlapping
with the margin of the image_.
"""
cy, cx, rad, accum = circle_
image_sizeY_, image_sizeX_ = image_.shape[0], image_.shape[1]
margin_min_x = int(image_sizeX_ * margin)
margin_max_... | 4ad94552bc1bf06282a691edede89a65f8b9c328 | 3,657,000 |
import ftplib
def session_factory(
base_class=ftplib.FTP,
port=21,
use_passive_mode=None,
*,
encrypt_data_channel=True,
debug_level=None,
):
"""
Create and return a session factory according to the keyword
arguments.
base_class: Base class to use for the session class (e. g.
... | 9fa29732dc14705317e4bbb3752330de5f0282c6 | 3,657,001 |
def calculate_molecular_mass(symbols):
"""
Calculate the mass of a molecule.
Parameters
----------
symbols : list
A list of elements.
Returns
-------
mass : float
The mass of the molecule
"""
mass = 0
for i in range(len(symbols)):
mass =... | 7ac18cffc02652428b51009d2bf304301def96dd | 3,657,002 |
def _color_str(string, color):
"""Simple color formatter for logging formatter"""
# For bold add 1; after "["
start_seq = '\033[{:d}m'.format(COLOR_DICT[color])
return start_seq + string + '\033[0m' | 715b0b597885f1cffa352cc01bdb743c3ed23dd4 | 3,657,003 |
def parser_tool_main(args):
"""Main function for the **parser** tool.
This method will parse a JSON formatted Facebook conversation,
reports informations and retrieve data from it, depending on the
arguments passed.
Parameters
----------
args : Namespace (dict-like)
Arguments passe... | 1e07a60e78b042c6c229410e5d1aaf306e692f61 | 3,657,004 |
from functools import reduce
def merge(from_args):
"""Merge a sequence of operations into a cross-product tree.
from_args: A dictionary mapping a unique string id to a
raco.algebra.Operation instance.
Returns: a single raco.algebra.Operation instance and an opaque
data structure suitable for pas... | e3690a26fc9e3e604984aab827617ffc535f63d3 | 3,657,005 |
import subprocess
import mimetypes
def get_content_type(file_resource):
"""Gets a file's MIME type.
Favors returning the result of `file -b --mime ...` if the command is
available and users have enabled it. Otherwise, it returns a type based on the
file's extension.
Args:
file_resource (resource_refer... | d58e60262cd762ae412580effc022f643132cb69 | 3,657,006 |
def graph(task_id):
"""Return the graph.json results"""
return get_file(task_id, "graph.json") | 4d8728d3b61cf62057525054d8eafa127b1c48ff | 3,657,007 |
def parse_components_from_aminochange(aminochange):
""" Returns a dictionary containing (if possible) 'ref', 'pos', and 'alt'
characteristics of the supplied aminochange string.
If aminochange does not parse, returns None.
:param aminochange: (str) describing amino acid change
:return: dict or Non... | 69877d635b58bdc3a8a7f64c3c3d86f59a7c7548 | 3,657,008 |
import random
import string
import csv
def get_logs_csv():
"""
get target's logs through the API in JSON type
Returns:
an array with JSON events
"""
api_key_is_valid(app, flask_request)
target = get_value(flask_request, "target")
data = logs_to_report_json(target)
keys = data[... | f9296cfc7c6559ebccbfa29268e3b22875fb9fed | 3,657,009 |
def _cache_key_format(lang_code, request_path, qs_hash=None):
"""
função que retorna o string que será a chave no cache.
formata o string usando os parâmetros da função:
- lang_code: código do idioma: [pt_BR|es|en]
- request_path: o path do request
- qs_hash: o hash gerado a partir dos parametro... | 365b1ff144f802e024da5d6d5b25b015463da8b3 | 3,657,010 |
from typing import Iterable
from pathlib import Path
from typing import Callable
from typing import Any
from typing import List
def select_from(paths: Iterable[Path],
filter_func: Callable[[Any], bool] = default_filter,
transform: Callable[[Path], Any] = None,
order_fun... | d952d7d81932c5f6d206c39a5ac12aae1e940431 | 3,657,011 |
import torch
from typing import Counter
def dbscan(data:torch.Tensor, epsilon:float, **kwargs) -> torch.Tensor:
"""
Generate mask using DBSCAN.
Note, data in the largest cluster have True values.
Parameters
----------
data: torch.Tensor
input data with shape (n_samples, n_features)
... | 0121b8b9dceaf9fc8399ffd75667afa6d34f66e1 | 3,657,012 |
import copy
def simulate_multivariate_ts(mu, alpha, beta, num_of_nodes=-1,\
Thorizon = 60, seed=None, output_rejected_data=False):
"""
Inputs:
mu: baseline intesnities M X 1 array
alpha: excitiation rates of multivariate kernel pf HP M X M array
beta: decay rates of kernel of multivariate HP
... | 85ab71fa3f2b16cbe296d21d6bc43c15c94aa40a | 3,657,013 |
import base64
def token_urlsafe(nbytes):
"""Return a random URL-safe text string, in Base64 encoding.
The string has *nbytes* random bytes. If *nbytes* is ``None``
or not supplied, a reasonable default is used.
>>> token_urlsafe(16) #doctest:+SKIP
'Drmhze6EPcv0fN_81Bj-nA'
"""
tok = to... | 1855dc44cec1ddd0c6c83d0f765c15fd98d1ec98 | 3,657,014 |
def sha206a_get_pk_useflag_count(pk_avail_count):
"""
calculates available Parent Key use counts
Args:
pk_avail_count counts available bit's as 1 (int)
Returns:
Status Code
"""
if not isinstance(pk_avail_count, AtcaReference):
status = Status.ATCA_BAD_PARAM
e... | 389174a21efe1ca78037b479895035b4bdd66b87 | 3,657,015 |
from typing import Tuple
def rotate_points_around_origin(
x: tf.Tensor,
y: tf.Tensor,
angle: tf.Tensor,
) -> Tuple[tf.Tensor, tf.Tensor]:
"""Rotates points around the origin.
Args:
x: Tensor of shape [batch_size, ...].
y: Tensor of shape [batch_size, ...].
angle: Tensor of shape [batch_si... | 8d4bf5f94964271f640def7d7e2b4242fbfe8e7b | 3,657,016 |
import inspect
def form_of(state):
"""Return the form of the given state."""
if hasattr(state, "__form__"):
if callable(state.__form__) and not inspect.isclass(state.__form__):
return state.__form__()
else:
return state.__form__
else:
raise ValueError(f"{st... | e39aa7db7b324ab38b65232b34b987b862812c54 | 3,657,017 |
def poly_to_geopandas(polys, columns):
"""
Converts a GeoViews Paths or Polygons type to a geopandas dataframe.
Parameters
----------
polys : gv.Path or gv.Polygons
GeoViews element
columns: list(str)
List of columns
Returns
-------
gdf : Geopandas dataframe
""... | 889fc5b1bf5bf15cd9612c40e7bf14b1c05043f6 | 3,657,018 |
def get_sequences(query_file=None, query_ids=None):
"""Convenience function to get dictionary of query sequences from file or IDs.
Parameters:
query_file (str): Path to FASTA file containing query protein sequences.
query_ids (list): NCBI sequence accessions.
Raises:
ValueError: Did... | 8056ce1c98b7a4faa4bb5a02505d527df31c7c8b | 3,657,019 |
import os
def _get_tickets(manifest, container_dir):
"""Get tickets."""
principals = set(manifest.get('tickets', []))
if not principals:
return False
tkts_spool_dir = os.path.join(
container_dir, 'root', 'var', 'spool', 'tickets')
try:
tickets.request_tickets(
... | 39d73322620ea9a6f1da4bfb693336dfc68748bb | 3,657,020 |
def random_show_date(database_connection: mysql.connector.connect) -> str:
"""Return a random show date from the ww_shows table"""
database_connection.reconnect()
cursor = database_connection.cursor(dictionary=True)
query = ("SELECT s.showdate FROM ww_shows s "
"WHERE s.showdate <= NOW() "... | e3afdf9aa1fe9a02adab72c424caa80d60280699 | 3,657,021 |
def get_output_tensor(interpreter, index):
"""Returns the output tensor at the given index."""
output_details = interpreter.get_output_details()[index]
tensor = np.squeeze(interpreter.get_tensor(output_details["index"]))
return tensor | 158db3fc7ba13ee44d422248a9b96b7738a486e3 | 3,657,022 |
def make_d_mappings(n_dir, chain_opts):
"""Generate direction to solution interval mapping."""
# Get direction dependence for all terms.
dd_terms = [dd for _, dd in yield_from(chain_opts, "direction_dependent")]
# Generate a mapping between model directions gain directions.
d_map_arr = (np.arange(... | fd9eddf81b4388e3fa40c9b65a591af9aabf9014 | 3,657,023 |
from typing import cast
from typing import Dict
import os
import cmd
import traceback
import pprint
def main():
"""Loop to test the postgres generation with REPL"""
envs = cast(Dict[str, str], os.environ)
if "HAYSTACK_DB" not in envs:
envs["HAYSTACK_DB"] = "sqlite3:///:memory:"
provider = get_... | caaaaafd9407417e4be334963c72a2b5d0c970fb | 3,657,024 |
def _calculateVolumeByBoolean(vtkDataSet1,vtkDataSet2,iV):
"""
Function to calculate the volumes of a cell intersecting a mesh.
Uses a boolean polydata filter to calculate the intersection,
a general implementation but slow.
"""
# Triangulate polygon and calc normals
baseC = vtkTools.datas... | a2c30133973527fb339c9d1e33cc2a937b35d958 | 3,657,025 |
def WebChecks(input_api, output_api):
"""Run checks on the web/ directory."""
if input_api.is_committing:
error_type = output_api.PresubmitError
else:
error_type = output_api.PresubmitPromptWarning
output = []
output += input_api.RunTests([input_api.Command(
name='web presubmit',
cmd=[
... | 5fb828cc98da71bd231423223336ec81e02505ff | 3,657,026 |
from HUGS.Util import load_hugs_json
def synonyms(species: str) -> str:
"""
Check to see if there are other names that we should be using for
a particular input. E.g. If CFC-11 or CFC11 was input, go on to use cfc-11,
as this is used in species_info.json
Args:
species (str): Input string ... | 31013464ce728cc3ed93b1a9318af3dbcf3f65ec | 3,657,027 |
def _blkid_output(out):
"""
Parse blkid output.
"""
flt = lambda data: [el for el in data if el.strip()]
data = {}
for dev_meta in flt(out.split("\n\n")):
dev = {}
for items in flt(dev_meta.strip().split("\n")):
key, val = items.split("=", 1)
dev[key.lower... | 2cbcbb3ec9b732c3c02183f43ca5a5d5e876af71 | 3,657,028 |
def as_iso_datetime(qdatetime):
""" Convert a QDateTime object into an iso datetime string.
"""
return qdatetime.toString(Qt.ISODate) | 8dba5d1d6efc0dc17adc26a5687923e067ca3c29 | 3,657,029 |
def spec_means_and_magnitudes(action_spec):
"""Get the center and magnitude of the ranges in action spec."""
action_means = tf.nest.map_structure(
lambda spec: (spec.maximum + spec.minimum) / 2.0, action_spec)
action_magnitudes = tf.nest.map_structure(
lambda spec: (spec.maximum - spec.minimum) / 2.0,... | 119054966a483bb60e80941a6bf9dc5a4a0778f6 | 3,657,030 |
def clean_data(df):
"""
Clean Data :
1. Clean and Transform Category Columns from categories csv
2.Drop Duplicates
3.Remove any missing values
Args:
INPUT - df - merged Dataframe from load_data function
OUTPUT - Returns df - cleaned Dataframe
"""
# Split categories into... | 752d675d8ac5e27c61c9b8c90acee4cdab8c08fc | 3,657,031 |
def commitFile(file: str = None, message: str = None, debug: bool = False) -> bool:
"""Commit a file when it is changed.
:param file: The name of the file we want to commit.
:type file: str
:param message: The commit message we want to use.
:type message: str
:param debug: If we want debug logg... | 2821da94cf727ee4d5098ccacc78c8368e7899aa | 3,657,032 |
def all_pairs_shortest_path_length(G,cutoff=None):
""" Compute the shortest path lengths between all nodes in G.
Parameters
----------
G : NetworkX graph
cutoff : integer, optional
depth to stop the search. Only paths of length <= cutoff are returned.
Returns
-------
lengths :... | 1d312a71bd97d4f1a51a8b1e24331d54055bc156 | 3,657,033 |
def get_cols_to_keep(gctoo, cid=None, col_bool=None, cidx=None, exclude_cid=None):
""" Figure out based on the possible columns inputs which columns to keep.
Args:
gctoo (GCToo object):
cid (list of strings):
col_bool (boolean array):
cidx (list of integers):
exclude_cid... | 1215a392ecb068e2d004c64cf56f2483c722f3f6 | 3,657,034 |
import shutil
def check_zenity():
""" Check if zenity is installed """
warning = '''zenity was not found in your $PATH
Installation is recommended because zenity is used to
indicate that protonfixes is doing work while waiting
for a game to launch. To install zenity use your system's
package ... | decea9be11e0eb1d866ed295cb33a06aa663a432 | 3,657,035 |
def get_auth_token():
"""
Return the zerotier auth token for accessing its API.
"""
with open("/var/snap/zerotier-one/common/authtoken.secret", "r") as source:
return source.read().strip() | bd74fde05fbb375f8899d4e5d552ad84bcd80573 | 3,657,036 |
def sph_harm_transform(f, mode='DH', harmonics=None):
""" Project spherical function into the spherical harmonics basis. """
assert f.shape[0] == f.shape[1]
if isinstance(f, tf.Tensor):
sumfun = tf.reduce_sum
def conjfun(x): return tf.conj(x)
n = f.shape[0].value
else:
s... | a88f9a71fa19a57441fdfe88e8b0632cc08fb413 | 3,657,037 |
def create_model(experiment_settings:ExperimentSettings) -> OuterModel:
"""
function creates an OuterModel with provided settings.
Args:
inner_settings: an instannce of InnerModelSettings
outer_settings: an instannce of OuterModelSettings
"""
model = OuterModel(experiment_settings.ou... | e6af03c5afd53a39e6929dba71990f91ff8ffbb3 | 3,657,038 |
import pickle
def LoadTrainingTime(stateNum):
"""
Load the number of seconds spent training
"""
filename = 'time_' + str(stateNum) + '.pth'
try:
timeVals = pickle.load( open(GetModelPath() + filename, "rb"))
return timeVals["trainingTime"]
except:
print("ERROR: Faile... | 1db59103bf3e31360237951241b90b3a85dae2bc | 3,657,039 |
def adjust_learning_rate(optimizer, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 15 epochs"""
lr = args.lr * (0.1 ** (epoch // args.lr_epochs))
print('Learning rate:', lr)
for param_group in optimizer.param_groups:
if args.retrain and ('mask' in param_group['key']): # ... | dc08034b0176ac0062d6fc7640a115f916a663a8 | 3,657,040 |
def disk_status(hardware, disk, dgtype):
"""
Status disk
"""
value = int(float(disk['used']) / float(disk['total']) * 100.0)
if value >= 90:
level = DiagnosticStatus.ERROR
elif value >= 70:
level = DiagnosticStatus.WARN
else:
level = DiagnosticStatus.OK
# Make boa... | f248ccb0ba07106c3ed923f9ac7bc2e85d9b5e63 | 3,657,041 |
def hr_admin(request):
""" Views for HR2 Admin page """
user = request.user
# extra_info = ExtraInfo.objects.select_related().get(user=user)
designat = HoldsDesignation.objects.select_related().get(user=user)
if designat.designation.name =='hradmin':
template = 'hr2Module/hradmin.h... | 1b2c1027f8f4caf716019d9e5500223f76119a0b | 3,657,042 |
import six
def test_extra():
"""Returns dict of extrapolation testing modules."""
return {name: module.test_extra() for name, module in six.iteritems(all_)} | 5538f81891c0388ae0f5e312cb6c521ee19d18a5 | 3,657,043 |
import torch
def _switch_component(
x: torch.Tensor, ones: torch.Tensor, zeros: torch.Tensor
) -> torch.Tensor:
"""
Basic component of switching functions.
Args:
x (torch.Tensor): Switch functions.
ones (torch.Tensor): Tensor with ones.
zeros (torch.Tensor): Zero tensor
R... | 8d60c09428440be704e8ced9b8ac19219a0d0b04 | 3,657,044 |
def get_vector(x_array, y_array, pair):
"""This function is for calculating a vector of a bone from the openpose skelleton"""
x = x_array[:,pair[0]]-x_array[:,pair[1]]
y = y_array[:,pair[0]]-y_array[:,pair[1]]
return [x, y] | e2bfcce3952c6b0a2c8cd9c67c4cd7b52547694d | 3,657,045 |
def update_bar(tweets_json, handle):
"""
Pull data from signal and updates aggregate bar graph
This is using thresholds that combine toxicity and severe toxicity models
suggested by Lucas.
"""
if not tweets_json:
raise PreventUpdate('no data yet!')
tweets_df = pd.read_json(tweets_j... | 1c523a455393ce211b8ef6483ee25b981e028bd0 | 3,657,046 |
import argparse
def defineConsole():
"""
defines the program console line commands
"""
parser = argparse.ArgumentParser(description="SBML to BNGL translator")
parser.add_argument(
"-f1", "--file1", type=str, help="reference file", required=True
)
parser.add_argument(
"-f2",... | 77f403040cf250810c5b4098c6b9818e5f17117e | 3,657,047 |
from typing import List
from typing import Dict
def render_foreign_derivation(tpl: str, parts: List[str], data: Dict[str, str]) -> str:
"""
>>> render_foreign_derivation("bor", ["en", "ar", "الْعِرَاق", "", "Iraq"], defaultdict(str))
'Arabic <i>الْعِرَاق</i> (<i>ālʿrāq</i>, “Iraq”)'
>>> render_foreign... | af3c37664e683d9bff610ad1fa53a167f5390988 | 3,657,048 |
def create_from_ray(ray):
"""Converts a ray to a line.
The line will extend from 'ray origin -> ray origin + ray direction'.
:param numpy.array ray: The ray to convert.
:rtype: numpy.array
:return: A line beginning at the ray start and extending for 1 unit
in the direction of the ray.
... | 6d0429abbacd235f95636369985bea8a17117409 | 3,657,049 |
from typing import List
def cluster_sampling(sents: List[Sentence], tag_type: str, **kwargs) -> List[int]:
"""Cluster sampling.
We create cluster sampling as a kind of diversity sampling method.
Different with most of sampling methods that are based on sentence level,
Cluster sampling method is imple... | a953ec5eced13e626a3b00769a7e5d505fcb1692 | 3,657,050 |
import os
def paths_to_dirs(paths): # type: (t.List[str]) -> t.List[str]
"""Returns a list of directories extracted from the given list of paths."""
dir_names = set()
for path in paths:
while True:
path = os.path.dirname(path)
if not path or path == os.path.sep:
... | 3472093ffb4870082e7d198410118169683ed786 | 3,657,051 |
def opts2dict(opts):
"""Converts options returned from an OptionParser into a dict"""
ret = {}
for k in dir(opts):
if callable(getattr(opts, k)):
continue
if k.startswith('_'):
continue
ret[k] = getattr(opts, k)
return ret | cfa828f0248ff7565aabbb5c37a7bc6fa38c6450 | 3,657,052 |
def combined_directions(a_list, b_list):
"""
Takes two NoteList objects.
Returns a list of (3)tuples each of the form:
(
int: a dir,
int: b dir,
(int: bar #, float: beat #)
)
"""
onsets = note_onsets(a_list, b_list)
a_dirs = directions(a_list)
b_dirs = directi... | 8b66d4de725c51b1abdedb8a8e4c48e78f4ca953 | 3,657,053 |
def _naive_csh_seismology(l, m, theta, phi):
"""
Compute the spherical harmonics according to the seismology convention, in a naive way.
This appears to be equal to the sph_harm function in scipy.special.
"""
return (lpmv(m, l, np.cos(theta)) * np.exp(1j * m * phi) *
np.sqrt(((2 * l + 1)... | ba2a17f0dfa6035a05d16c8af79310657fe6ecd7 | 3,657,054 |
def is_room_valid(room):
"""Check if room is valid."""
_, names, checksum = room
letters = defaultdict(int)
complete_name = ''.join(names)
for letter in complete_name:
letters[letter] += 1
sorted_alphabetic = sorted(letters)
sorted_by_occurrences = sorted(
sorted_alphabetic, ... | b893cf97ee28b033741e4b2797b2a4aef485324f | 3,657,055 |
from typing import Dict
def _get_attributes_entropy(dataset: FingerprintDataset,
attributes: AttributeSet
) -> Dict[Attribute, float]:
"""Give a dictionary with the entropy of each attribute.
Args:
dataset: The fingerprint dataset used to comput... | 616abbd292f10d0a01d7d56ab5636ac5883fa230 | 3,657,056 |
def _mag_shrink_hard(x, r, t):
""" x is the input, r is the magnitude and t is the threshold
"""
gain = (r >= t).float()
return x * gain | da795bcfc2a6e4bfa3e54d1334c9d8865141a4f1 | 3,657,057 |
from sys import base_prefix
def is_macports_env():
"""
Check if Python interpreter was installed via Macports command 'port'.
:return: True if Macports else otherwise.
"""
# Python path prefix should start with Macports prefix.
env_prefix = get_macports_prefix()
if env_prefix and base_pre... | b90c43f7ef267ab237e8f6c205eb2a62969b5539 | 3,657,058 |
def wiki_data(request, pro_id):
""" 文章标题展示 """
data = models.Wiki.objects.filter(project_id=pro_id).values('id', 'title', 'parent_id').order_by('deepth')
return JsonResponse({'status': True, 'data': list(data)}) | 6dfbb79b78133935356bd87cc24a294ed0001b73 | 3,657,059 |
import os
import json
def create_task_spec_def():
"""Returns the a :class:`TaskSpecDef` based on the environment variables for distributed training.
References
----------
- `ML-engine trainer considerations <https://cloud.google.com/ml-engine/docs/trainer-considerations#use_tf_config>`__
- `Tenso... | fdf1680e41f072ebf0c9b2b228095fba91d5af09 | 3,657,060 |
def many_capitalized_words(s):
"""Returns a function to check percentage of capitalized words.
The function returns 1 if percentage greater then 65% and 0 otherwise.
"""
return 1 if capitalized_words_percent(s) > 66 else 0 | cc82a2708defd545a1170bfeabb5848e3092fc39 | 3,657,061 |
def cmd_te_solution_build(abs_filename,wait=False,print_output=False,clear_output=False):
"""ソリューションをビルドする（テキストエディタ向け）
ファイルが含まれるVisual Studioを探し出してソリューションをビルドする。
VisualStudioの「メニュー -> ビルド -> ソリューションのビルド」と同じ動作。
abs_filename- ファイル名の絶対パス
(Ex.) c:/project/my_app/src/main.cpp
... | db48988d483da6ae9a012460e0d5fdd326d5ae40 | 3,657,062 |
def log_ratio_measure(
segmented_topics, accumulator, normalize=False, with_std=False, with_support=False):
"""
If normalize=False:
Popularly known as PMI.
This function calculates the log-ratio-measure which is used by
coherence measures such as c_v.
This is defined as: ... | 73fec59f84402066ccbbcd25d30cc69698f6b721 | 3,657,063 |
def _calculate_monthly_anomaly(data, apply_filter=False, base_period=None,
lat_name=None, lon_name=None, time_name=None):
"""Calculate monthly anomalies at each grid point."""
# Ensure that the data provided is a data array
data = rdu.ensure_data_array(data)
# Get coordi... | 397bffb8f22ae26cf2c41cd8c056951ef55d692d | 3,657,064 |
def process_song(song_id):
"""
歌曲id、歌曲名、歌手id、所属专辑id、歌词、评论数
process song information
:param song_id: 歌曲id
:return: 处理状态(True or False)
"""
log("正在处理歌曲：{}".format(song_id))
if db.hexists("song:" + song_id, "id"):
log("有缓存(已做过处理)，歌曲id:{}".format(song_id))
return True
els... | 148953bd42ce8aba3bf6b90aed7a5276dd0794c3 | 3,657,065 |
import os
def expand_path(path):
"""
Convert a path to an absolute path. This does home directory expansion,
meaning a leading ~ or ~user is translated to the current or given user's
home directory. Relative paths are relative to the current working
directory.
:param path: Relative or absolut... | dc73eb377fd5b16091596f4345ee024c3d42e5bc | 3,657,066 |
import pprint
def oxe_system_alaw_to_mulaw(host, token, mode):
"""Summary
Args:
host (TYPE): Description
token (TYPE): Description
mode (TYPE): Description
Returns:
TYPE: Description
"""
payload = {
'T0_Mu_Law': mode
}
packages.urllib3.disa... | 19bb98f8326e84cde83691028a2fc2585a7abe6e | 3,657,067 |
def update_weights(comment_weights, comment_usage):
"""Updates the weights used to upvote comments so that the actual voting
power usage is equal to the estimated usage.
"""
desired_usage = 1.0 - VP_COMMENTS / 100.0
actual_usage = 1.0 - comment_usage / 100.0
scaler = np.log(desired_usage) / np.l... | 19d2f0a9ec790c26000946c0b91ef3bc00f36905 | 3,657,068 |
import math
def smaller2k(n):
"""
Returns power of 2 which is smaller than n. Handles negative numbers.
"""
if n == 0: return 0
if n < 0:
return -2**math.ceil(math.log2(-n))
else:
return 2**math.floor(math.log2(n)) | 0d0bbbf95cb22bf1b9ffb29012075534bcc9646d | 3,657,069 |
from PIL import Image
from lxml import etree
import sys
import os.path
import pickle
import time
import urllib.request
import io
import requests
import tensorflow as tf
from mynet import CaffeNet
def create_anime_image_data(anime):
"""Create (or load) a dict for each anime that has a high level CNN
representation... | fbe6fc4bbfd3623c40bf78c8c33bc960bea307d2 | 3,657,070 |
def deferred_bots_for_alias(alias):
"""Returns a dict where the keys are bot names whose commands have an alias
that conflicts with the provided alias, and the values are a list of
prefixes that would cause that conflict."""
return {
# TODO Support more prefixes than one
config['name']: ... | 338776546622ed0bb6290b2d93ddb3129e764d02 | 3,657,071 |
import opcode
def modeify(intcode, i):
"""Apply a mode to a parameter"""
j = i + 1
_opcode = opcode(intcode[i])
params = intcode[j: j + _opcode['param_count']]
modes = _opcode['modes']
mode_covert = {
0: lambda x: intcode[x], # position mode
1: lambda x: x ... | 230fb2e43c33558d94a7d60c6dd16978098421aa | 3,657,072 |
def unwind(g, num):
"""Return <num> first elements from iterator <g> as array."""
return [next(g) for _ in range(num)] | 59b724ca27729b4fc20d19a40f95d590025307c4 | 3,657,073 |
def find_best_control(db, input_features, max_distance=200.0, debug=False, control_cache=None):
"""
Search all controls with AST vector magnitudes within max_distance and find the best hit (lowest product of AST*call distance)
against suitable controls. Does not currently use literal distance for the calculati... | 21589a3070f59f556a7cc540b5d69839fbb95327 | 3,657,074 |
import re
def CPPComments(text):
"""Remove all C-comments and replace with C++ comments."""
# Keep the copyright header style.
line_list = text.splitlines(True)
copyright_list = line_list[0:10]
code_list = line_list[10:]
copy_text = ''.join(copyright_list)
code_text = ''.join(code_list)
# Remove */ ... | 0dd490f5497c073534abc30944bd49d0a3cf7e3e | 3,657,075 |
def get_bulk_statement(
stmt_type, table_name, column_names, dicts=True, value_string="%s", odku=False
):
"""Get a SQL statement suitable for use with bulk execute functions
Parameters
----------
stmt_type : str
One of REPLACE, INSERT, or INSERT IGNORE. **Note:** Backend support for
... | ba2277fc6f84d79a97d70cf98d2e26f308b8fa82 | 3,657,076 |
def map_remove_by_value_range(bin_name, value_start, value_end, return_type, inverted=False):
"""Creates a map_remove_by_value_range operation to be used with operate or operate_ordered
The operation removes items, with values between value_start(inclusive) and
value_end(exclusive) from the map
Args:
... | 42a49aefb92f61a3064e532390bdcf26b6266f40 | 3,657,077 |
def rationalApproximation(points, N, tol=1e-3, lowest_order_only=True):
"""
Return rational approximations for a set of 2D points.
For a set of points :math:`(x,y)` where :math:`0 < x,y \\leq1`, return all
possible rational approximations :math:`(a,b,c) \\; a,b,c \\in \\mathbb{Z}`
such that :math:`... | 614c230ad7fd68cb60d0203cba2bd15e30f3f36a | 3,657,078 |
import subprocess
def get_notebook_server_instance(try_use_existing=False):
"""Create a notebook server instance to use. Optionally attempting to re-use existing
instances.
"""
pid = get_cache_pid()
servers = list_running_servers()
# If we already have a server, use that
for server in s... | b11932b2be3319be388913427ef7623690fa11f1 | 3,657,079 |
def to_dict(doc, fields):
"""Warning: Using this convenience fn is probably not as efficient as the
plain old manually building up a dict.
"""
def map_field(prop):
val = getattr(doc, prop)
if isinstance(val, list):
return [(e.to_dict() if hasattr(e, 'to_dict') else e) for e i... | cb51e3dfdf8c313f218e38d8693af9e7c6bf5045 | 3,657,080 |
import time
def _auto_wrap_external(real_env_creator):
"""Wrap an environment in the ExternalEnv interface if needed.
Args:
real_env_creator (fn): Create an env given the env_config.
"""
def wrapped_creator(env_config):
real_env = real_env_creator(env_config)
if not isinstanc... | ef7f0c7ecdf3eea61a4e9dc0ad709e80d8a09e08 | 3,657,081 |
def _get_binary_link_deps(
base_path,
name,
linker_flags = (),
allocator = "malloc",
default_deps = True):
"""
Return a list of dependencies that should apply to *all* binary rules that link C/C++ code.
This also creates a sanitizer configuration rule if necessary, s... | 06a52934a0c121b606c79a6f5ae58863645bba34 | 3,657,082 |
def create_dummy_ligand(ligand, cut_idx=None):
"""
Takes mol object and splits it based on a primary amine such that the frags can connect to
the tertiary amine on the Mo core.
Args:
cut_idx tuple(int):
ligand (mol):
Returns:
ligands List(mol) :
"""
# TODO AllChem.Rep... | b74bc21003c33234d310121331ab61887536709e | 3,657,083 |
def double2pointerToArray(ptr, n, m_sizes):
""" Converts ctypes 2D array into a 2D numpy array.
Arguments:
ptr: [ctypes double pointer]
n: [int] number of cameras
m_sizes: [list] number of measurements for each camera
Return:
arr_list: [list of ndarrays] list of numpy ... | f556c5a36f645c6047c3b487b7cd865edc3b76db | 3,657,084 |
def read_varint(stream: bytes):
"""
读取 varint。
Args:
stream (bytes): 字节流。
Returns:
tuple[int, int]，真实值和占用长度。
"""
value = 0
position = 0
shift = 0
while True:
if position >= len(stream):
break
byte = stream[position]
value += (byte... | 58c8187501dc08b37f777256474f95412649bf04 | 3,657,085 |
import argparse
def get_arguments():
"""
get commandline arguments
"""
# Parse command line arguments
parser = argparse.ArgumentParser(description="P1 reader interface")
parser.add_argument("--config-file",
default=__file__.replace('.py', '.yml').replace('/bin/', '/etc... | f35a364c96705c764064c536519dc9d3730d9310 | 3,657,086 |
def any(array, mapFunc):
"""
Checks if any of the elements of array returns true, when applied on a function that returns a boolean.
:param array: The array that will be checked, for if any of the elements returns true, when applied on the function. \t
:type array: [mixed] \n
:param mapFunc: The fun... | 1e635da691fd1c2fc9d99e15fd7fa0461a7bdf0e | 3,657,087 |
def qt_point_to_point(qt_point, unit=None):
"""Create a Point from a QPoint or QPointF
Args:
qt_point (QPoint or QPointF): The source point
unit (Unit): An optional unit to convert
values to in the output `Point`. If omitted, values
in the output `Point` will be plain `i... | 595dacc2d39d126822bf680e1ed1784c05deb6d7 | 3,657,088 |
import requests
import json
def apiRequest(method, payload=None):
"""
Get request from vk server
:param get: method for vkApi
:param payload: parameters for vkApi
:return: answer from vkApi
"""
if payload is None:
payload = {}
if not ('access_token' in payload):
pay... | b60c77aec5ae500b9d5e9901216c7ff7c93676ad | 3,657,089 |
def page_required_no_auth(f):
"""Full page, requires user to be logged out to access, otherwise redirects to main page."""
@wraps(f)
def wrapper(*args, **kwargs):
if "username" in session:
return redirect("/")
else:
return f(*args, **kwargs)
return wrapper | 7d7d314e10dcaf1d81ca5c713afd3da6a021247d | 3,657,090 |
import argparse
import re
def parse_arguments(args):
"""
Parse all given arguments.
:param args: list
:return: argparse.Namespace
"""
parser = argparse.ArgumentParser(
description=__description__,
epilog="Example-usage in apache-config:\n"
'CustomLog "| /path/to/anonip... | 7d24618fc40835488a7d05a748f462826311a30a | 3,657,091 |
import sympy
def generate_forward():
"""
Generate dataset with forward method
It tries to integrate random function.
The integral may not be symbolically possible, or may contains invalid operators.
In those cases, it returns None.
"""
formula = symbolic.fixed_init(15)
integrated = sympy.integrate(fo... | 91a91e5b23f3f59b49d8f7102585ff7fbfbbf6c4 | 3,657,092 |
import pickle
def load_agent(agent_args, domain_settings, experiment_settings):
"""
This function loads the agent from the results directory results/env_name/method_name/filename
Args:
experiment_settings
Return:
sarsa_lambda agent
"""
with open('results... | a5769c952d9fcc583b8fb909e6e772c83b7126ca | 3,657,093 |
def unpickle_robust(bytestr):
""" robust unpickle of one byte string """
fin = BytesIO(bytestr)
unpickler = robust_unpickler(fin)
return unpickler.load() | 42fee03886b36aef5ab517e0abcb2cc2ecfd6a8b | 3,657,094 |
def build_ins_embed_branch(cfg, input_shape):
"""
Build a instance embedding branch from `cfg.MODEL.INS_EMBED_HEAD.NAME`.
"""
name = cfg.MODEL.INS_EMBED_HEAD.NAME
return INS_EMBED_BRANCHES_REGISTRY.get(name)(cfg, input_shape) | 4d8242614426a13f9e93a241184bd3d8f57ef648 | 3,657,095 |
def atl03sp(ipx_region, parm, asset=icesat2.DEFAULT_ASSET):
"""
Performs ATL03 subsetting in parallel on ATL03 data and returns photon segment data.
See the `atl03sp <../api_reference/icesat2.html#atl03sp>`_ function for more details.
Parameters
----------
ipx_region: Query
... | 8c822af0d2f9b6e42bd6a1efeb29249a04079e66 | 3,657,096 |
def get_sample_activity_from_batch(activity_batch, idx=0):
"""Return layer activity for sample ``idx`` of an ``activity_batch``.
"""
return [(layer_act[0][idx], layer_act[1]) for layer_act in activity_batch] | 0302fdf215e63d6cbcd5dafc1bd36ae3d27712f2 | 3,657,097 |
def _reorder_for_qbb_experiment(df: pd.DataFrame) -> pd.DataFrame:
"""By default the entries are ordered alphabetically. We want SPOTA, EPOpt, PPO"""
print("Changed the order")
return df.iloc[[2, 0, 1]] | beccd22a765eb526ed855fd34dde4a05e2b394f2 | 3,657,098 |
def get_field(self, *args, is_squeeze=False, node=None, is_rthetaz=False):
"""Get the value of variables stored in Solution.
Parameters
----------
self : SolutionData
an SolutionData object
*args: list of strings
List of axes requested by the user, their units and values (optional)
... | e93455cbc4b306762336fd13603342e9d92badd1 | 3,657,099 |
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