content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from pandas import read_fwf
def load_dataframe(fobj, compression='gzip'):
"""Given an open file for `hip_main.dat.gz`, return a parsed dataframe.
If your copy of ``hip_main.dat`` has already been unzipped, pass the
optional argument ``compression=None``.
"""
try:
except ImportError:
... | 662738a84f315761d0e2d27f98a15df7c83eb325 | 3,617,600 |
import os
import sys
def generate_passphrase(passphrase_length, word_list):
"""Generate the passphrase string.
For each word, read 2 bytes from the kernel-space CSPRNG via ``os.urandom``
and convert them to an integer which serves as a list index. A list of
65,536 words is probably enough so we don'... | dc6aa86392f1c49f47c6f169ec98ef5e555f9451 | 3,617,601 |
def enum(*sequential, **named):
"""
Handy way to fake an enumerated type in python.
Example
-------
>>> Numbers = enum(ONE=1, TWO=2, THREE='three')
>>> Numbers.ONE
1
>>> Numbers.TWO
2
>>> Numbers.THREE
'three'
Source
------
"http://stackoverflow.com/questions/36... | 3bcce013c8111fccda6e3dd08d40a0128fcdb3d8 | 3,617,602 |
def get_granted_queue_consumer_config(group_id, topic, version, cluster_type, is_pattern):
"""
获取已经授权的producer记录
:param group_id: 需要授权的topic
:param topic: queue队列 topic
:param version 版本号
:param cluster_type 集群类型
:param is_pattern 是否为正则表示的topic
:return: {list} db中对应的完整记录列表
"""
if... | 954b392f5b8c75b286ef771434c2d28c5df7afa8 | 3,617,603 |
def getUnitType(index):
"""
Returns the <index>th UnitType.
"""
try:
return UNITS[index]
except IndexError:
BugUtil.error("ReligionUtil - invalid unit type %i", index)
return None | 70ef993160698031ef438c473e2f125e8f69997d | 3,617,604 |
def get_account_history():
"""
get_account_history
"""
account = request.args.get('account', None)
if account is None:
return jsonify({})
token = request.args.get('token', None)
limit = request.args.get('limit', 100)
offset = request.args.get('offset', 0)
hist_type = request... | 5b386c8c7eb1fe5943f8a04c7b81b97f33b507d6 | 3,617,605 |
def token_view(request, token):
"""Show form to let user set password.
"""
i = get_object_or_404(Invitation, token=token)
if i.is_expired():
raise Http404
if request.method == 'GET':
try:
user = User.objects.get(email=i.accepter)
if user.is_active is True:
... | 998ced088759d44974c6275861b174e147df7f9e | 3,617,606 |
def _match_by_tag(inp, params):
"""Match joints by tags. Use Munkres algorithm to calculate the best match
for keypoints grouping.
Note:
number of keypoints: K
max number of a image: M
L: 2 if use flip test else 1
Args:
inp(tuple):
tag_k (np.ndarray[KxMxL]):... | f04dcf485d2b24b8cda4395d45ff6a03337aa96b | 3,617,607 |
def mean_(x, dimension, track_types = True, **kwargs):
"""Calculate the mean of a set of values.
Parameters
----------
x : :obj:`xarray.DataArray`
The data cube to be reduced.
dimension : :obj:`str`
Name of the dimension to apply the reduction function to.
track_types : :obj:`bool`
... | f5c76000736139eb5ff71b54fffede14e0b62760 | 3,617,608 |
import six
import yaml
def UpdateThresholdRules(ref, args, req):
"""Add threshold rule to budget."""
messages = GetMessagesModule()
client = apis.GetClientInstance('billingbudgets', 'v1beta1')
budgets = client.billingAccounts_budgets
get_request_type = messages.BillingbudgetsBillingAccountsBudgetsGetRequest... | 9f4bde1b600719f454a66d7d0f3b400c3e4d2fbe | 3,617,609 |
from typing import Callable
import json
def synonym(
string: str,
threshold: float = 0.5,
top_n=5,
cleaning=augmentation_textcleaning,
**kwargs
):
"""
augmenting a string using synonym, https://github.com/huseinzol05/Malaya-Dataset#90k-synonym
Parameters
----------
string: str... | 225dbefe6fa1e39a2bf8141f2167d0c13d49f590 | 3,617,610 |
from pathlib import Path
from typing import Tuple
def get_path(dir_path: Path,
dir_name: str = "movie",
counting_format: str = "%03d",
file_pattern: str = "") -> Tuple[Path, int, str, str]:
"""
Looks up all directories with matching dir_name
and counting format in di... | 4e508e52ebb7768bbdad9f849ffff55ce476ac74 | 3,617,611 |
import typing
import textwrap
import yaml
def _update_yaml_write_lines(
lines: typing.List[str],
configs: typing.Dict[str, typing.Any],
block: YamlBlock,
parent: YamlBlock,
) -> typing.List[str]:
"""
Replace the specified block within the YAML file lines object with the new configs.
This ... | f9e70015c2622cf09ef07b185836ec8fec237df9 | 3,617,612 |
import random
def get_manufacturerid() -> str:
"""
Get manufacturer id from MANUFACTURER_ID list
:return: id
"""
return MANUFACTURER_ID["manufacturer_" + str(random.randint(0, N_MANUFACTURERS - 1))] | cef941f409cbdadd168c03ea542331ebf2d7f803 | 3,617,613 |
import copy
def _get_args_for_wrapping(wrapped, new_sig, func_name, doc, qualname, module_name, attrs):
"""
Internal method used by @wraps and create_wrapper
:param wrapped:
:param new_sig:
:param func_name:
:param doc:
:param qualname:
:param module_name:
:param attrs:
:retur... | 600794f744c2afe123656f82f66fba5645590ccf | 3,617,614 |
def generate_next_step(flat_model, model_curr_conf):
"""
Generate next conf to try
"""
todo_quants = [deepcopy(model_curr_conf) for _ in range(len(flat_model))]
for index, conf in enumerate(todo_quants):
conf[index] -=1
todo_quants = list(filter( lambda x: not 1 in x ,todo_quan... | 130ebe2a2ca18b209950141303242c43f3534a62 | 3,617,615 |
def build_train_op(loss):
"""Sets up the training Ops.
Args:
loss: Loss tensor, from build_loss().
Returns:
train_op, global_step, learning_rate.
"""
global_step = tf.Variable(0, name='global_step', trainable=False)
learning_rate = tf.train.exponential_decay(INIT_LEARNING_RATE, glo... | a6dff882ff455732ff9fff1756ef1407a44997af | 3,617,616 |
import os
def get_local_apps(category=CATEGORY_ALL):
"""Returns a list of apps that can be found in the apps folder"""
apps = [App(folder_name) for folder_name in os.listdir("apps") if filesystem.is_dir("apps/" + folder_name)]
return [app for app in apps if app.matches_category(category)] | 84e6c15cfcde25e445bdb3cccb3693b8f5d4016d | 3,617,617 |
import os, random
def getRandom():
""" Download a random PDB and return the path name.
Returns
path name of downloaded file
"""
URL = "ftp://ftp.rcsb.org/pub/pdb/data/structures/all/pdb/"
pdblines = os.popen("ncftpls %s" % URL).readlines()
pdbline = pdblines.join()
pdbline ... | c1cea0d937cd5165c7ebd3d46cf4764e28d7748b | 3,617,618 |
def logistic_sigmoid(x, a):
"""Computes so-called logistic curve, a sigmoidal function used in modelling
population growth etc. In this implementation, the parameter a regulates the slope
or 'growth rate' of the sigmoid's rising portion. When a=0, the function collapses
to the identity function y=x.
... | 5984767c317cb40629097fd8941eb54d0e8c4717 | 3,617,619 |
def first_deriv_partials(dts, q, n_segments=1, n_simpson_intervals_per_segment=2, order=4):
"""
This method provides the Jacobian of a temporal first derivative
A "segment" is defined as a portion of the quantity vector q with a
constant delta t (or delta x, etc).
This routine is designed to be use... | a107994d5496de3c53072ffab720be88fd269ab3 | 3,617,620 |
import os
def processed_file_path(source_path, asset_roots, target_directory,
target_extension):
"""Take the path to an asset and convert it to target path.
Args:
source_path: Path to the source file.
asset_roots: List of potential root directories each input file.
target_dire... | 749bda062d90dae1763d802f2a557d50682e8a4d | 3,617,621 |
def zoom(scale, center, group):
"""zoom(scale, center, group) -> float
Change the zoom and pan of a group's display. The scale argument is the new zoom factor.
If the scale is given, but not the center, the zoom is set to that factor and the view is
positioned so the cursor is pointing at the same place it was bef... | fe6c5cafed738d5e53a043fa86e66b22cab0a6af | 3,617,622 |
def _border_type(player, tile, adj_tile):
"""
Used by map drawing routine. Checks if 'adj_tile' is connected to and can
be seen from 'tile'
:param text_game_maker.player.player.Player player: player object
:param text_game_maker.tile.tile.Tile tile: first tile
:param text_game_maker.tile.tile.T... | b8f27e11d02f134a42b1eacc45164fa9602ffddc | 3,617,623 |
import argparse
def parse_args():
""" Load command line args """
parser = argparse.ArgumentParser()
parser.add_argument('--inf', metavar="<file>", help=('Credible set json'), type=str, required=True)
parser.add_argument('--outf', metavar="<str>", help=("Output"), type=str, required=True)
args = pa... | 4d07ed1993759bbce97f280a6cf1d3b869482986 | 3,617,624 |
def _log_calculate(beta): # pragma: no cover
"""
TODO: Replace this with more efficient algorithm
alpha in GF(p^m) and generates field
beta in GF(p^m)
gamma = log_primitive_element(beta), such that: alpha^gamma = beta
"""
# Naive algorithm
result = 1
for i in range(0, ORDER - 1):
... | ac974cc88d78acb7320e22448e9a4ba6c6b10941 | 3,617,625 |
def partion(arr, start, end):
"""
将元素以基准元素进行分区，基准元素左边都小于等于它，右边都大于等于他
:param arr:
:param start:
:param end:
:return:
"""
key = arr[start]
while start < end:
while start < end and arr[end] >= key:
end -= 1
swap(arr, start, end)
while start < end ... | d71b568fd2d07edbdb836267040e718a6dba239f | 3,617,626 |
def map_fbs_flows(fbs, from_fba_source, v, **kwargs):
"""
Identifies the mapping file and applies mapping to fbs flows
:param fbs: flow-by-sector dataframe
:param from_fba_source: str Source name of fba list to look for mappings
:param v: dictionary, The datasource parameters
:param kwargs: incl... | 4995566bb1538b5c6b706850075b99d3b0563442 | 3,617,627 |
from pathlib import Path
def _parse_collection_dir(directory: Path) -> list:
"""
Parse Ansible collection
:param directory: Collection directory
:return: List of parsed Ansible tasks that are prepared for scanning
"""
parsed_collection = []
for role in (list((directory / "roles").rglob("*"... | 4238848fd6856efcbd1cd8a722567c4b11490475 | 3,617,628 |
def adda_hyperparams(lr_target=1e-5, lr_discriminator=1e-4, wd=5e-5, scheduler=False):
"""
Return a dictionary of hyperparameters for the ADDA algorithm.
Default parameters are the best ones as found through a hyperparameter search.
Arguments:
----------
lr_target: float
Learning rate f... | af7cf7402485f4af4fd7c6a1a2ffb5fcd753cf93 | 3,617,629 |
import logging
import pathlib
def get_system_library_path():
"""return the path to the system Photos library as string"""
""" only works on MacOS 10.15 """
""" on earlier versions, returns None """
_, major, _ = _get_os_version()
if int(major) < 15:
logging.debug(
f"get_system_... | 399a4f2da70ebf72f4134f5e890e3dd1bd5adce2 | 3,617,630 |
import urllib
import sys
import json
def testServerAPIAddCreator(serverURL):
"""
Create a creator and listen for a 200 response
Note the UUID
"""
method = moduleName + '.' + 'testServerAPIAddCreator'
Graph.logQ.put( [logType , logLevel.DEBUG , method , "entering"])
testResult = Tru... | 73e1a5c57e8935a4b4a016b761bbc104b7e0fe29 | 3,617,631 |
import os
def calicoupgrade(command, prompt_resp='yes'):
"""
Convenience function for abstracting away calling the calicoctl-upgrade
command.
:param command: The calicoctl-upgrade command line parms as a single string.
:return: The output from the command with leading and trailing
whitespac... | 1e3c0d07bb6169fc8af35274075b7ca860c25a2b | 3,617,632 |
import numpy
def get_topic_terms(model, topicid, topn, id2token):
"""
Return a list of `(word_id, probability)` 2-tuples for the most
probable words in topic `topicid`.
Only return 2-tuples for the topn most probable words (ignore the rest).
"""
topic = model.state.get_lambda()[topicid]
to... | b0ca1fd35fb7e8ce89a497c37bfd82b9dd884027 | 3,617,633 |
def gmv(cov):
"""
Returns the weights of the Global Minimum Vol portfolio
given covariace matrix
"""
n = cov.shape[0]
return msr(0, np.repeat(1, n), cov) | 24b1362dad13be80e13d6caecc470907f4d685a6 | 3,617,634 |
import json
def placement_rest_api():
"""Perform placement optimization after validating the request and fetching policies
Make a call to the call-back URL with the output of the placement request.
Note: Call to Conductor for placement optimization may have redirects, so account for them
"""
reque... | dd850c802d86dcfa343abfded8b109b881fecde2 | 3,617,635 |
def ecef_to_teme(ecef: np.array, jd: float, t_tt: float, lod: float, xp: float, yp: float, eqeterms: int):
""" Earth-Centered, Earth-Fixed (ECEF) to True Equator, Mean Equinox frame
coordinate system conversion. TEME frame is used for the NORAD two-line elements.
TODO: Vectorize
Args:
ecef (n... | 4aa95c59f3778009e37b77d243625feb1e51ddcd | 3,617,636 |
def account():
"""Account and update account route """
form = UpdateAccountForm()
if form.validate_on_submit():
# if form.picture.data:
# picture_file = save_picture(form.picture.data)
# current_user.image_file = form.picture.data
current_user.image_file = form.pictur... | f8e4c90e525e5f3d05b8afcf9a719044853774a1 | 3,617,637 |
import warnings
def keep_corelated_data(data: DataFrameOrArrayGeneric, threshold: float = 0.5) -> DataFrameOrArrayGeneric:
"""Remove columns that are not corelated enough to predicted columns. Predicted column is supposed to be 0.
Args:
data (DataFrameOrArrayGeneric): Time series data.
thresh... | 3d082b026641aedabc26d071bbed6f7be3810267 | 3,617,638 |
def max_pool_forward_naive(x, pool_param):
"""
A naive implementation of the forward pass for a max pooling layer.
Inputs:
- x: Input data, of shape (N, C, H, W)
- pool_param: dictionary with the following keys:
- 'pool_height': The height of each pooling region
- 'pool_width': The width of each pool... | 8e38f5d72a35ee206aada709a93152db04a232f7 | 3,617,639 |
def _find_gd_env_buf(gd_address: int, gd_mem: bytes, new_gd_offset: int, arch):
"""
Search for `struct global_data.env_buf` in `gd_mem`.
If found, the offset of this field into `gd_mem` is returned.
Otherwise a `ValueError` is raised.
"""
search_offset = new_gd_offset + arch.word_size
searc... | 30fcf142290add7764ee76020570c316b5d84367 | 3,617,640 |
import operator
def give_recom_result(user_vec, item_vec, userid):
"""
user lfm model result give fix userid recom result
:param user_vec: lfm model result
:param item_vec: lfm model result
:param userid: user
:return: list :[(itemid,score),(itemid1,score1)]
"""
fix_num = 80
if u... | fe796936916b403523b96627f520f16464eb94e3 | 3,617,641 |
import requests
def save_file(fileName):
"""Saves a file of a given name, and returns the json response."""
return requests.post(BASEURL+"documents",headers=HEADS,files={'requester.py': open('requester.py', 'rb')}) | 12e227f5fa0b5684b34c38c3c6c4543c1bb63ca5 | 3,617,642 |
import json
def load_label(label_path):
"""
Loads a label from a JSON file
"""
with open(label_path, 'r') as label_file:
label = json.load(label_file)
return label | f6a2873abee024d64ede78f18a96f0a1b95abd0b | 3,617,643 |
def get2d23d(depth, camera_pose, K, pt1, pt2, znear, zfar, width=480, height=640):
"""
input:
depth: image depth(in coordinate)
camera_pose: orign camera_pose
K: camera intrinsic
pt1: orign 2d Point
pt2: matchinfg 2d point
znear,zfar: depth clip range
retur... | dace3aa40b0c9792d005b974347200f4f1812896 | 3,617,644 |
import copy
def clip_image(image,roi=[],rotangle=0.0,cp=False):
"""
Clip an image given the roi
Parameters:
-----------
* roi is a list [c1,r1,c2,r2] = [x1,y1,x2,y2]
Note take x as the horizontal image axis index (col index),
and y as vertical axis index (row index).
Therefore,... | 4fe385cf7a15fac59f0a4989970b1523a922deb6 | 3,617,645 |
from platypush.backend import Backend
from typing import Optional
import re
def get_backend_name_by_class(backend) -> Optional[str]:
"""Gets the common name of a backend (e.g. "http" or "mqtt") given its class. """
if isinstance(backend, Backend):
backend = backend.__class__
class_name = backen... | 13fc8c76df9446ded5c81d7f6db1ae52cc8214e4 | 3,617,646 |
import time
import torch
def run_one_epoch(
epoch, loader, model, criterion, optimizer, meters, phase='train', ema=None, scheduler=None, eta=None, epoch_dict=None, single_sample=False):
"""run one epoch for train/val/test/cal"""
t_start = time.time()
assert phase in ['train', 'val', 'test', 'cal']... | 40aae97098058122fe70acb518bbe531d1928874 | 3,617,647 |
import sys
def query_yes_no(question, default='yes'):
"""Ask a yes/no question via raw_input() and return their answer.
"question" is a string that is presented to the user.
"default" is the presumed answer if the user just hits <Enter>.
It must be "yes" (the default), "no" or None (meaning
... | 4ea47d555bdbfc818067a911246af09cc8c25c61 | 3,617,648 |
def load_signature_library(filename):
"""
Load a signature library from a .sig file.
:param filename: input filename
:return: instance of `TrieNode`, the root of the signature trie.
"""
with open(filename, 'rb') as f:
buf = f.read()
return SignatureLibraryReader().deserialize(buf) | ae8d639473ef0424688d315acc82c67a0b19aa09 | 3,617,649 |
def create_random_datetime(start, end):
"""
This function will return a random datetime between two datetime
objects.
Borrowed from: http://bit.ly/gM45o4
"""
delta = end - start
int_delta = (delta.days * 24 * 60 * 60) + delta.seconds
random_second = randrange(int_delta)
return (sta... | 3d71be3bfe19bdbb0c0e4eca7c3a25b15733b3da | 3,617,650 |
import yaml
def get_task_config(task_name, is_remote):
"""Return powercycle task config."""
if is_remote:
config_location = powercycle.abs_path(
f"{powercycle_constants.REMOTE_DIR}/{POWERCYCLE_TASKS_CONFIG}")
else:
config_location = powercycle.abs_path(POWERCYCLE_TASKS_CONFIG)... | b03c6d3e3690d543c82b3780b4a8a72861cd11cd | 3,617,651 |
import os
def construct_data_reader(run_args):
"""
Construct Protobuf message for Python data reader.
The Python data reader will import this Python file to access the
sample access functions.
"""
module_file = os.path.abspath(run_args.data_module_file)
os.environ["DATA_CONFIG"] = os.pa... | 5eae0b8c3635a322bd47c1d5fdb73a079d686bc5 | 3,617,652 |
def resize(anns, size, output_size):
"""
Parameters
----------
anns : List[Dict]
Sequences of annotation of objects, containing `bbox` of [l, t, w, h].
size : Sequence[int]
Size of the original image.
output_size : Union[Number, Sequence[int]]
Desired output size. If size... | 800135ac9d65f55ae96d04fc645ac0d2b913b76c | 3,617,653 |
def get_league_entries_by_summoner(summoner_ids):
"""
https://developer.riotgames.com/api/methods#!/985/3356
Args:
summoner_ids (int | list<int>): the summoner ID(s) to get league entries for
Returns:
dict<str, list<League>>: the summoner(s)' league entries
"""
# Can only have ... | 7e0b72e8502a59e8ae1728830497988a4e2a88be | 3,617,654 |
def scheduler() -> BackgroundScheduler:
"""Retrieve the scheduler, intended mostly for unit testing purposes."""
if not _SCHEDULER:
raise EngineError("Scheduler is not available")
return _SCHEDULER | a45993a2806725fd315fa4d9926adfa6cc50c65d | 3,617,655 |
def toDiscrete(m):
"""
Args:
- m (m,n) : np.array with the occupancy grid
Returns:
- discrete_m : thresholded m
"""
y_size, x_size = m.shape
m_occupied = np.zeros(m.shape)
m_free = np.zeros(m.shape)
m_occluded = np.zeros(m.shape)
#Handpicked
occupied_value = 0.8... | 9d045d09a338ccf5dcd4a3a816f5eb0af77fdec6 | 3,617,656 |
def has_overlap(x0, xd, y0, yd):
"""Return True if the ranges overlap.
Parameters
----------
x0, y0 : float
The min values of the ranges
xd, yd : float
The widths of the ranges
"""
return x0 + xd >= y0 and y0 + yd >= x0 | 6b2a6eff892e28376ed08bf8f60c67f49cdeff44 | 3,617,657 |
def _ecdf_vals(data, formal=False):
"""
Get x, y, values of an ECDF for plotting.
Parameters
----------
data : ndarray
One dimensional Numpay array with data.
formal : bool, default False
If True, generate x and y values for formal ECDF (staircase). If
False, generate x ... | 1bae53fbbeeea51add956e1f4e6e7eb434b7ade0 | 3,617,658 |
def add_classification(hw_data, index):
"""
Add a column at the end of the data to capture wind severity.
0 if wind speed is < 50
1 if wind speed is >= 50
"""
sev_wind = hw_data[:, index] >= 50
sev_wind = sev_wind.astype(int)
sev_wind = sev_wind.reshape(len(sev_wind), 1)
hw_data = ap... | c855043f1ba5b762b7abe347672c924209de648e | 3,617,659 |
from typing import List
import re
def check_airflow_versions_in_quick_start_guide() -> List[DocBuildError]:
"""Check that a airflow version is presented in example in the quick start guide for Docker."""
build_errors = []
build_error = assert_file_contains(
file_path=f"{DOCS_DIR}/apache-airflow/s... | 4b775e8f1d84574e2fea8419fe7bf5065d5c9af0 | 3,617,660 |
def load(filename):
""" Load nifti1 single or pair from `filename`
Parameters
----------
filename : str
filename of image to be loaded
Returns
-------
img : Nifti1Image or Nifti1Pair
nifti1 single or pair image instance
Raises
------
ImageFileError: if `filenam... | 22d10861ea273d18a15f1ff385a8e9ae4a26b288 | 3,617,661 |
import attr
def test_input_spec_func_1b_except(use_validator):
""" the function w/o annotated, but input_spec is used
metadata checks raise an error
"""
@mark.task
def testfunc(a):
return a
my_input_spec = SpecInfo(
name="Input",
fields=[
(
... | 89c27fcd7fb6443fa950bb31acee4b19f42ce487 | 3,617,662 |
import itertools
import math
def corr1(xydata):
"""corr1(xydata) -> float
Calculate an estimate of the Pearson's correlation coefficient with
a single pass over iterable xydata. See also the function corr which may
be more accurate but requires multiple passes over the data.
>>> data = zip([0, 5... | a22261826b45b2cbbc48cba8c18dbff241865db3 | 3,617,663 |
from typing import Tuple
def vehicle_capacity_is_respected(solution: Solution) -> Tuple[bool, str]:
"""
Verifies the vehicle capacities are respected by each tour of the solution.
"""
problem = Problem()
for route in solution.routes:
if any(stacks.used_capacity() > problem.capacity
... | 0edb3c7d8ab464827e732c19d9d0bb2230872156 | 3,617,664 |
import os
def find_doctests(suffix, ignore_suffix=None):
"""Find doctests matching a certain suffix."""
doctest_files = []
# Match doctests against the suffix.
if resource_exists('lazr.restfulclient', 'docs'):
for name in resource_listdir('lazr.restfulclient', 'docs'):
if ignore_su... | 778909af84e30b0a62888af0fb74b735c4101b46 | 3,617,665 |
def get_pwn_cutoff(ra,dec,rad_search=2., deathline = 1.e34):
"""
Set cutoff for PWN based on association with pulsars in ATNF catalog
Only pulsars with Edot > 1.e34 erg/s are considered, because cutoffs at ~1 TeV
should have already been detected
:param ra: R.A. of PWN center, deg
:param dec: De... | 23cb431ff933575ed537e5afbdc1b0df52291749 | 3,617,666 |
def _any(series, values):
""" Returns the index of rows from series containing any of the
given values.
Parameters
----------
series : pandas.Series
The data to be queried
values : list-like
The values to be tested
Returns
-------
index : pandas.index
The i... | fb663895f97a2456e144e070ed2b09fd2308a13b | 3,617,667 |
def parse_hhcc(self, data: str, source_mac: str, rssi: float):
"""HHCC parser"""
if len(data) == 13:
device_type = "HHCCJCY10"
hhcc_mac = source_mac
xvalue_1 = data[4:7]
xvalue_2 = data[7:10]
xvalue_3 = data[10:13]
packet_id = data[4:13].hex()
(moist, temp... | 879591a3f65bea671a186542445b6a605770b4db | 3,617,668 |
def CIFAR10(train=True, path=None):
"""Thin wrapper around torchvision.datasets.CIFAR10
"""
mean, std = [0.491, 0.482, 0.447], [0.247, 0.243, 0.262]
normalize = transforms.Normalize(mean=mean, std=std)
if train:
preproc = [transforms.RandomHorizontalFlip(), transforms.RandomCrop(32, 4)]
... | 94e5a57a32786caa49746b754b1d961a6edf1731 | 3,617,669 |
def get_app_base_url():
""" Returns the QRadar app proxy prefix. """
return app_qpylib.get_app_base_url() | 10fdac9e547ecae4bcdd99be8ef1b0338c264bb7 | 3,617,670 |
def create_plotgroup(template_plot_type='bitmap',**params):
"""
Create a new PlotGroup and add it to the plotgroups list.
Convenience function to make it simpler to use the name of the
PlotGroup as the key in the plotgroups list.
template_plot_type: Whether the plots are bitmap images or curves
... | 45cbb35054e44436e191b274ed0f4b88ae49c29a | 3,617,671 |
import hashlib
def create_file_map(directory_dict):
"""
Create a dictionary that maps the hash value of each unique file to a list
of the full paths of each copy of that file, even if those files have
different names.
:param directory_dict: dictionary mapping directory -> list of files
:retur... | f977a5a6737ba66965f630f3c230505a1fa442e9 | 3,617,672 |
def get_dc_token(region_name=constants.SYSTEM_CONTROLLER_REGION):
"""Get token for the dcmanager user.
Note: Although region_name can be specified, the token used here is a
"project-scoped" token (i.e., not specific to the subcloud/region name).
A token obtained using one region_name can be re-used acr... | 7dd77025b4e4ef40b616466cb233cb67b5b78a24 | 3,617,673 |
def calculate_multiplier(aggregate_add_on, value, RC):
"""
Calculates multiplier depending on Replacement Cost (RC).
Returns
-------
Multiplier.
"""
market_value = calculate_market_value(value)
if RC > 0:
multiplier = 1
return multiplier
else:
floor = 0.05
... | 710a228bfa3be2bd495aece19308dfff04175e5d | 3,617,674 |
def gen_col_list(num_signals):
"""
Given the number of signals returns
a list of columns for the data.
E.g. 3 signals returns the list: ['Time','Signal1','Signal2','Signal3']
"""
col_list = ['Time']
for i in range(1, num_signals + 1):
col = 'Signal' + str(i)
col_list.append(c... | 35fe1457c9e256f90f7695e066dcc3202f212d98 | 3,617,675 |
def calculate_eigenspaces(kr_max, theta, phi, rad):
"""Calculate the eigenspaces for the corresponding eigenfrequencies of
the sphere
Parameters
----------
k_max : float
The largest wave number to be included
theta : array, float
Azimuth angle
phi : array, float
Elev... | cb835533f65716336d3bc157c70d20a19743077c | 3,617,676 |
def get_sequence(message, message_object_list, sequence_list, sequence=None, index=None):
"""Returns a sequence i.e. more than 2 messages"""
if not sequence:
sequence = []
index = 0
if message not in sequence and not any(message in s for s in sequence_list) is True:
message[3] = True... | fcbc4b70839fbff9bdac4e30878a2e78ae9c2127 | 3,617,677 |
def fit_moffat(arr):
"""
Params
------
arr (2d np array of odd sizes)
Return
------
model (astropy model object)
"""
# sanity check of input data type
if isinstance(arr, ac.kernels.Kernel):
arr = arr.array
elif isinstance(arr, np.ndarray):
pass
else:
raise Exception("[psfmatch] input needs to be a ... | fd630be0338f52735a457c6a1c6e0dbf4ed68c18 | 3,617,678 |
import random
import calendar
def date_generator(
num_dates: int = 1,
start_year: int = 1950,
end_year: int = current_year,
as_list: bool = False,
):
"""
Function to generate date(s). Specify the number of dates (num_dates, defaults to 1),\n
start year (start_year, defaults to 1950),\n
... | 888f1d10d29a2767a463ccc1e57f11b3a7a149b9 | 3,617,679 |
import requests
def test_batch_create(requests_mock):
"""
Test batch creation
"""
metadata = Gen3Metadata("https://example.com")
metadata_list = [
{"guid": "3c42c819-1dfe-4c3e-8d46-c3ec7eb99bf4", "data": {"foo": "bar"}},
{"guid": "dfa1a1dc-98f4-46be-ba8f-ae9b42b0ee50", "data": {"fo... | e4db6a3771dfcbd803b6f653223fecde9eca302e | 3,617,680 |
def f_isASCII(*args):
"""f_isASCII(flags_t F, void ?) -> bool"""
return _idaapi.f_isASCII(*args) | 3fec966271398b648dc1dc5912a3a048e70523b7 | 3,617,681 |
def generate_ical_string(key: str) -> str:
"""generates iCalendar string from testdata and returns it"""
c = Calendar()
for row in _testdata["iCalendar"].get(key, []):
c.events.add(
Event(
name=row["name"],
begin=row["begin"],
end=row["end"... | 3b8bfb25b8d310eeb80c1c88c69d60cd79b054d3 | 3,617,682 |
import os
def read_parfile(parfile):
"""load a pest-compatible .par file into a pandas.DataFrame
Parameters
----------
parfile : str
pest parameter file name
Returns
-------
pandas.DataFrame : pandas.DataFrame
"""
assert os.path.exists(parfile), "Pst.parrep(): parfile no... | e66fe741ae3671fac916d0c15826de5c5c20db03 | 3,617,683 |
def int_to_bytes(int_: int, architecture: int = None) -> Bytes:
"""Get Bytes object
:param int_: number integer to convert to Bytes
:type: int
:param architecture: bytes length
:type: int
:return: bytes representation
:type: Bytes
"""
bin_ = f'{bin(int_)[2:]}'
bytes... | de16ba99ea770c34e6631532882d07f7f55da39f | 3,617,684 |
import sys
async def login_headless(root: Root, url: URL) -> None:
"""
Log into Neuro Platform from non-GUI server environment.
URL is a platform entrypoint URL.
The command works similar to "neuro login" but instead of
opening a browser for performing OAuth registration prints
an URL that s... | 02c1e5b67dc3054df614c07fe25787bc8d015677 | 3,617,685 |
from pybullet_planning.interfaces.env_manager.pose_transformation import all_between
from pybullet_planning.interfaces.robots.joint import set_joint_positions, get_custom_limits
from pybullet_planning.interfaces.robots.link import get_self_link_pairs, get_moving_links
from pybullet_planning.interfaces.debug_utils.debug... | 28c829f87c9f7f179559cc19af23683e888ebfce | 3,617,686 |
import builtins
def decode_bytes(b):
"""Tries to decode the bytes using XONSH_ENCODING if available,
otherwise using sys.getdefaultencoding().
"""
session = getattr(builtins, "__xonsh__", None)
env = os_environ if session is None else getattr(session, "env", os_environ)
enc = env.get("XONSH_EN... | b82fe9012d5a6f0ba5707bc6f0a04017f87a60cd | 3,617,687 |
import numpy
def cropobjects_merge_bbox(cropobjects):
"""Computes the bounding box of a CropObject that would
result from merging the given list of CropObjects."""
# Find extremes. This will define the output cropobject.
t, l, b, r = numpy.inf, numpy.inf, -1, -1
for c in cropobjects:
t = m... | 559e96dda48cb5e733c59a3168032037e0eb06e4 | 3,617,688 |
import psutil
def starttime(pid):
"""starttime(pid) -> float
Arguments:
pid (int): PID of the process.
Returns:
The time (in seconds) the process started after system boot
"""
return psutil.Process(pid).create_time() - psutil.boot_time() | eda12b68605eb9602469f74884b812cdeb0abf26 | 3,617,689 |
def generate_nested_list(root,nodes):
"""
Generates a nested list representation of the tree
with specified node as root. Useful for checking
equality of trees or subtrees.
To do: make the nested list form a property that is computed when needed.
"""
nl = []
if root.children is None: r... | fa75493c8ccc4b720ee404baa9eb3996ce78f3eb | 3,617,690 |
def build_group_objects(env1, admin_api_key1, group_links):
"""
Builds a list of Group objects that will be used to more quickly check for users in groups
"""
Groups_List = [] # initialize a python list of objects
if not (group_links is None):
for i in np.arange(0, np.shape(group_links)[0])... | 4438c3aae7e544091bbf463df0cf36a8381c6378 | 3,617,691 |
def queryset_filter_tag(queryset, **kwargs):
""" template tag which allows queryset filtering. Usage:
{% filter_tag books author=author as mybooks %}
{% for book in mybooks %}
{% endfor %}
"""
return queryset.filter(**kwargs) | 5959285ec8b19945003a98f910028eb35d75299c | 3,617,692 |
import torch
def render(H, W, focal, cx, cy, chunk=1024*32, rays=None, c2w=None, ndc=True,
near=0., far=1.,
use_viewdirs=False, c2w_staticcam=None,
**kwargs):
"""Render rays
Args:
H: int. Height of image in pixels.
W: int. Width of image in pixels.
focal: flo... | 1dba826206df1d951f10c3ab8aac7018cdd15d69 | 3,617,693 |
def abstract(func):
"""
An abstract decorator. Raises a NotImplementedError if called.
:param func: The function.
:return: The wrapper function.
"""
# noinspection PyUnusedLocal
# pylint: disable=unused-argument
def wrapper(*args, **kwargs):
raise NotImplementedError('{} has... | 3497ae41c4987499cddc610e518a8a9251cadb31 | 3,617,694 |
def is_greyscale_image(image: np.ndarray) -> bool:
"""
A function that checks if an image is a greyscale image (an image where pixels are a number - has 1 color channel)
:param image: the image to be checked, a numpy array
"""
return len(image.shape) == 2 | 72df92a91b2720138f73aa8817a7ad7a8803685f | 3,617,695 |
def __get_site_amp_ratio(pga: float, db_vs30: float, user_vs30: float, im: IM):
"""
Calculates a PGA_1100 estimate; uses it to calculate a site amplification ratio for the difference in vs30
between the user and the modelled vs30
Scaling is only defined for pSA and PGA otherwise no scaling is applied -... | 31c0bc41beb92c6595019283a40f600be046c520 | 3,617,696 |
def cosineXform(a, b, c):
"""
Spherical trig transform to take alpha, beta, gamma to expressions
for cos(alpha*). See ref below.
[1] R. J. Neustadt, F. W. Cagle, Jr., and J. Waser, ``Vector algebra and
the relations between direct and reciprocal lattice quantities''. Acta
Cryst. (1968)... | 537cf31ceb59189b71b1394598ca3b89ee5de40a | 3,617,697 |
import pandas
def load_escolas():
"""Load and return the dadosabertos.poa.br escolas dataset.
The escolas dataset is a public open dataset from Prefeitura de Porto Alegre, Rio Grande do Sul, Brazil.
Examples
--------
>>> from dyrapy.datasets import load_escolas
>>> cadastro, matriculas = loa... | 7f9f265564fb1ce18f4871bf124b3b14ed62b0ce | 3,617,698 |
def svn_fs_node_created_path(*args):
"""svn_fs_node_created_path(svn_fs_root_t * root, char const * path, apr_pool_t pool) -> svn_error_t"""
return _fs.svn_fs_node_created_path(*args) | aecc149c53665815960a95966c20681e23cc9a93 | 3,617,699 |
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