content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import List
def construct_outgoing_unicast_answers(
answers: _AnswerWithAdditionalsType, ucast_source: bool, questions: List[DNSQuestion], id_: int
) -> DNSOutgoing:
"""Add answers and additionals to a DNSOutgoing."""
out = DNSOutgoing(_FLAGS_QR_RESPONSE | _FLAGS_AA, multicast=False, id_=id_)
... | 6d9b2036850dbf58f4c83a28479008becf518ed0 | 3,619,400 |
import matplotlib.pyplot as mp
import numpy as np
def parabola(list1, list2, list3, plo=False, pri=False, **kwargs):
"""Plots a parabola on pre-existing graph between points
list1, list2, and list3,
returns the parameters of the parabola
as in the form y = ax^2 + bx + c,
and optionally prints the ... | 286c90e94c06431cd22f478a4843c43d2e5a2e43 | 3,619,401 |
def attention_mask(nd, ns, *, dtype):
"""1's in the lower triangle, counting from the lower right corner.
Same as tf.matrix_band_part(tf.ones([nd, ns]), -1, ns-nd), but doesn't produce garbage on TPUs.
"""
i = np.arange(nd)[:, None]
j = np.arange(ns)
m = i >= j - ns + nd
return np.array(m, ... | 9f660e93ae589d5501d02e187e41d9bc4fbe7c88 | 3,619,402 |
def preview_progress(Task_Options, net, device, preview_loader):
"""Returns preprocessed and augmented input and target data.
For details on all input parameter dictionaries, see:
/spectrai/spectrai/configs/*.yml
Arguments:
Task_Options: dictionary of task options
net: PyTorch neural ... | 7fde77638323815659dc7e24341e507cb07cf3c5 | 3,619,403 |
def is_cellv2_init_ready():
"""Determine if we're ready to initialize the cell v2 databases
Cells v2 init requires transport_url and database connections to be set
in nova.conf.
"""
amqp = ch_context.AMQPContext()
shared_db = nova_cc_context.NovaCellV2SharedDBContext()
if (ch_utils.CompareO... | 2bac1f9c8f0f25fcc96cf768d378f59eb0a0f971 | 3,619,404 |
from typing import Any
def get_calendar(obj: Any, dim: str = "time") -> str:
"""Return the calendar of an object.
Parameters
----------
obj : Any
An object defining some date.
If `obj` is an array/dataset with a datetime coordinate, use `dim` to specify its name.
Values must have ei... | a5603b3a322252390e8310fa124a88df27ed5a5e | 3,619,405 |
def twilio_settings_doctype_in_integrations() -> bool:
"""Check Twilio Settings doctype exists in integrations module or not.
"""
return frappe.db.exists("DocType", {'name': 'Twilio Settings', 'module': 'Integrations'}) | 5fcaedec7e8eaf6363622833809d6ddeea16bfcb | 3,619,406 |
async def item_unoshield(ctx):
"""
Okay so we're playing uno now apparently,
this acually seems pretty useful though.
The reverse shield can reverse a single rob or nuke.
After that it just disappears. like, \*poof\*, and its gone.
*\* oh yeah, and it doubles the amount robbed. so thats nice..... | 3025869f0327edee97bc97df527eefd96ad6d16b | 3,619,407 |
def merge_two(n1,n2):
"""
Given two sorted linked list with head nodes
n1 and n2, merges n2 into n1 so that the resulting
list is still sorted.
"""
if n1 is None:
return n2
if n2 is None:
return n1
n_prev1 = None; n_prev2 = None
while True:
while (n1 i... | 95e31b18c9c86b5c5d1314e1b394d91c268e6a52 | 3,619,408 |
def find_golden_token():
"""
Function indentical to the 'find_silver_token', excepts for the fact that the sought token now are golden.
Also in this case the tokens are searched only in the semi-plane in front of the robot (-90 < token.rot_y < 90).
"""
dist=100
for token in R.see():
... | b4aadc890fa14d3f52361cd4f92bc9e9e6e8abb6 | 3,619,409 |
def filter_data_of_insts(data, to_remove=set()):
"""
Remove midi.Pattern or MidiObj from an iterable data container if they contain
instrument numbers in 'to_remove'. These numbers are same as midi standard -1.
"""
ret = []
for x in data:
keep = True
for evnt in utils.evnt_gen(x)... | 1e776b1579ab1cf58ce3a46a6e8f2fb1f48fdbbc | 3,619,410 |
def build_text_row(node):
"""Build a row for the french data"""
french_word = bhsa2french.get(str(node), {})
row_data = {'bhsa_node': node}
ref = french_word.get('ref')
row_data.update({
'french': french_word.get('french', ''),
'french_verse': frenchverses.get(ref, ''),
})
... | 0b78c1721a8544ed12dc0cd646ecd2fec5b8e896 | 3,619,411 |
from typing import Dict
from typing import Any
def to_json_schema(
schema: Dict[str, Any], *, nullable_name: str, copy: bool = True, is_response_schema: bool = False
) -> Dict[str, Any]:
"""Convert Open API parameters to JSON Schema.
NOTE. This function is applied to all keywords (including nested) durin... | f7de7f9caa18d634d1aef9f921860c2b67f022b3 | 3,619,412 |
from typing import Dict
from typing import Tuple
def harm_longterm(
out_dep: pd.DataFrame,
out_ctl: pd.DataFrame,
selected: np.array,
outcomes: Dict,
) -> Tuple[float, int]:
"""Calculate the harm from a long-term credit outcome."""
# Impact rates
sel_acq_nsuc = np.logical_and(out_dep.succe... | 6800b41fab9e755e8ab564a7460827bcc9fd30a1 | 3,619,413 |
async def upload_nextcloud_zipfile(file_name: str):
""" Upload a .zip File to later be imported into Mealie """
file = BACKUP_DIR.joinpath(file_name)
if file.is_file:
return FileResponse(
file, media_type="application/octet-stream", filename=file_name
)
else:
return ... | f24dc49d0e76236fbb68cd69583f50b4cdaf1542 | 3,619,414 |
def rotators_encrypt(_rotators, _text):
"""
The rotators work by being given both an initial value as well as a
frequency of how often it shifts up.
The last rotator always increments one for every character encoded/decoded
and other rotators can be configured for different frequencies.
If Rotat... | 7a12e370d74ae40079205b20f11e19a301063b1f | 3,619,415 |
def ms_ssim(img1, img2, max_val=255, filter_size=11, filter_sigma=1.5,
k1=0.01, k2=0.03, weights=None):
"""Return the MS-SSIM score between `img1` and `img2`.
This function implements Multi-Scale Structural Similarity (MS-SSIM) Image
Quality Assessment according to Zhou Wang's paper, "Multi-sca... | b7a3a76343cb8996585d8a7c599874f6e40ed059 | 3,619,416 |
import lingam
def estimate_corr(data, algorithm="ica", lower_limit=0.01, prior_knowledge=None):
"""Generate DAG of pair-wise LiNGAM coefficient"""
def _model(alg, _kwargs):
if alg == "ica":
return lingam.ICALiNGAM(**_kwargs)
elif alg == "direct":
return lingam.DirectLi... | cb95a24fe82b93a8d9a955a7231aae854ce6e925 | 3,619,417 |
def fluo_amplitude(elem, line, excitation=None, barn_unit=False):
"""Get the fluorescence cross section for a given element/line
Parameters
----------
elem : string or number
element
line : string
emission line Siegban (e.g. 'LA1') or IUPAC (e.g. 'L3M5')
excitation : float (opti... | bf7fa71a6eaae1ce9ad215ecaba26f9b258e9652 | 3,619,418 |
def fmt_sec(sec):
"""Take a time in seconds and convert it to mm:ss.ms"""
return fmt_ms(int(sec) * 1000) | bf991385e53ac7b149062aca2b1d63d6be0c2eb5 | 3,619,419 |
def accountingEnabledForRecord(record):
"""
Determine if accounting is enabled for the given record.
"""
enabledRecordGUIDs = config.AccountingPrincipals
if "*" in enabledRecordGUIDs:
return True
return record.uid in enabledRecordGUIDs | 7f7f3ad1fb7da72ff573063994b20f37aa3c9c60 | 3,619,420 |
def inventory_reset():
""" Removes all inventory from the database """
Inventory.remove_all()
return make_response('', status.HTTP_204_NO_CONTENT) | da334e34f6b4c75f5f9c684b7984c9a503c8fc3a | 3,619,421 |
def make_data_fn(is_training, timesteps2use):
"""returns data function for processing and returning a feed dictionary to be passed to model"""
def data_fn(data):
text_batch = Variable(data[0].long(), requires_grad=False, volatile=not is_training)
mask = Variable(data[1], requires_grad=False, volatile=not is_train... | 5916f237a137a129243f1a3c0d843d1de7053494 | 3,619,422 |
def shift_left(x, axis=1):
"""Shift the input to the right by padding and slicing on axis."""
pad_widths = [(0, 0)] * len(x.shape)
pad_widths[axis] = (0, 1)
padded = jnp.pad(
x, pad_widths, mode='constant', constant_values=x.dtype.type(0)
)
# print(padded)
return lax.dynamic_slice_in... | 6381b105887e75a10e4bbd84ac9bb85154301d7b | 3,619,423 |
def load_cows(filename):
"""
Read the contents of the given file. Assumes the file contents contain
data in the form of comma-separated cow name, weight pairs, and return a
dictionary containing cow names as keys and corresponding weights as values.
Parameters:
filename - the name of the data ... | aa44df075a4aa8d44d37743b8a351ef57133d148 | 3,619,424 |
def find_bin_edges(cbins):
""" Given bin centres, find the bin edges.
Examples
--------
>>> print find_bin_edges([1, 2.1, 3.3, 4.6])
[ 0.45 1.55 2.7 3.95 5.25]
"""
cbins = np.asarray(cbins)
edges = cbins[:-1] + 0.5 * (cbins[1:] - cbins[:-1])
edges = np.concatenate( ([2*cbins[0]... | ab235735cf6ccacebea4fe51cb11a022412721f6 | 3,619,425 |
import torch
def retrieval_collate(data):
"""Creates mini-batch tensors from the list of tuples (src_seq, trg_seq)."""
# separate source and target sequences
t2i_batch, i2t_batch = list(zip(*data))
# t2i
def generate_inputs(_batch):
sent, att_feats, img_masks, box_feats, obj_labels, pos_l... | 14ebc659e5d5e40cb7819eeec0d5376dcececc61 | 3,619,426 |
def index():
"""
represents dashboard home page
"""
member = Member.query.count()
product = Product.query.count()
paid_off = Order.query.filter_by(paid_off=True).count()
unpaid_off = Order.query.filter_by(paid_off=False).count()
return render_template(
"dashboard/index.html",
... | f0cd4c3f75e279b673d3751228026227719d311b | 3,619,427 |
def wrap_hashlib(hasher, length=None):
"""
Wraps hashlib's functions, returning a function that returns the hex-digest of its input.
>>> from hashlib import sha1
>>> wrap_hashlib(sha1)(b'heyo')
'f8bb1031d6d82b30817a872b8a2ec31d5380cee5'
:param hasher: A function from :mod:`hashlib`
:return... | dbd07d4151a5c5c523fe75c3f29b72abfd15c3b8 | 3,619,428 |
from googleapiclient import discovery
def export_fhir_store_gcs(project_id, location, dataset_id, fhir_store_id, gcs_uri):
"""Export resources to a Google Cloud Storage bucket by copying
them from the FHIR store.
See https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-clie... | 3ac26fd0ba4733d1a5bf0ca3d7ae639d378142c8 | 3,619,429 |
from pathlib import Path
async def read_fastq_headers(path: Path) -> list:
"""
Return a list of FASTQ headers for the FASTQ file located at `path`. Only accepts uncompressed FASTQ files.
:param path: the path to the FASTQ file
:return: a list of FASTQ headers
"""
headers = list()
had_pl... | e344c86346544a0c8c1c854d30661058ae9550a5 | 3,619,430 |
from typing import Counter
def batch_status():
"""
Same as status, but for a list of IDs.
INput message shall be { "ids": [id1, id2, ...] } where ids are task-ids
The returned global status will be PENDING unless all tasks are SUCCESSful
:return: json message with {"status": global status, "progre... | 33c4bb7ccf7f1ec1447baa2c62d924f2f1e7a8ce | 3,619,431 |
import os
import requests
def download_wukrii(program_abs_path, wukrii_page_num):
"""Downloads latest Wukrii comics."""
# Create/change appropriate comic folder.
comic_folder = os.path.join(program_abs_path, "wukrii")
if os.path.exists(comic_folder):
os.chdir(comic_folder)
else:
os... | ff89400ade4eefc4ac4df400cfb0289bd6951ea7 | 3,619,432 |
def _get_lastword_range(prefix, stringlist, tokenizer=None):
"""
Get the range of lastword tokenized index in label_ids
Args:
prefix: list(str), list of text with its last word removed(a.k.a. "prefix") in form of str
stringlist: list(str), list of text, same as it is in split_by_last_word
... | 6a3a74752d52fb3712fb43976ff47b1ee3f84492 | 3,619,433 |
def is_valid_solution(G, c, k):
"""
Checks whether D is a valid mapping of G, by checking every room adheres to the stress budget.
Args:
G: networkx.Graph
c: List of cities to remove
k: List of edges to remove (List of tuples)
Returns:
bool: false if removing k and c disc... | caea354dab043cc038c92f83f8d709e6807e8dee | 3,619,434 |
def get_loss_layer(mlp_out, action, precision, batch_size):
"""The loss layer used for the MLP network is obtained through this class."""
scale_factor = tf.constant(2*batch_size, dtype='float')
uP = batched_matrix_vector_multiply(action - mlp_out, precision)
uPu = tf.reduce_sum(uP*(action - mlp_out)) #... | 7051df7c6868fa485a45933bd4da0ecaa2285e7f | 3,619,435 |
def view_task_info(token, dstore):
"""
Display statistical information about the tasks performance.
It is possible to get full information about a specific task
with a command like this one, for a classical calculation::
$ oq show task_info:classical
"""
args = token.split(':')[1:] # cal... | 38304935b8990b1895f6d2e945e2c187e356773d | 3,619,436 |
def revision_exists(git_dir, revision):
"""
check if the provided revision exists
With attempt to find if the provided revision values (be it a branch, tag or
hash value) exists in the provided Git directory.
Args:
git_dir: the Git directory
revision: the revision (branch, tag, has... | b04398d523da53acaccc66472ef50cf5efb78821 | 3,619,437 |
import os
import time
def isOldEnough(nzbFile):
""" Determine if the NZB file's modification time is > Hellanzb.NZBQUEUE_MDELAY """
mtime = os.stat(nzbFile).st_mtime
now = time.time()
if mtime < now and now - mtime < Hellanzb.NZBQUEUE_MDELAY:
debug('Delaying enqueue of %s: mtime: %i Hellanzb.N... | 5d1a96d7a774d0af475361aaaf484428ed13b65f | 3,619,438 |
import re
def isBlank(s):
""" Returns True if string contains only space characters."""
return bool(re.compile("^\s*$").match(s)) | 1e6f7f7cefa4fea3d5b7443d74a265a79c3db3d7 | 3,619,439 |
from gluon.contrib.simplejson import dumps
from os import mkdir
from PIL import Image
from sys import path
def nicedit_image_upload():
"""
Controller to upload images with nicedit
"""
page_id = request.args(0)
pathname = path.join(request.folder,'static','images', 'pages_content', page_id)
i... | 98d0efb4d80b775a3b57010a23138fe23fa3de45 | 3,619,440 |
def __extract_tzd(m):
"""Return the Time Zone Designator as an offset in seconds from UTC."""
if not m:
return 0
tzd = m.group("tzd")
if not tzd:
return 0
if tzd == "Z":
return 0
hours = int(m.group("tzdhours"), 10)
minutes = m.group("tzdminutes")
if minutes:
... | 5e786cab67a2151df8ed8851dc19a6adbc365aea | 3,619,441 |
def measure(dataframe, lasers=[405, 488, 561, 638], channels=[1, 2, 3, 4, 5, 6],
create_fcs=False, outfile_name='sample_output.fcs'):
"""
This is a function that will measure fluorescence
intensity for any given sample DataFrame and laser/channel
parameters. Output will be just a pandas Data... | 5cb8ec3a0ad0145b799bc44e15235a1d377704f1 | 3,619,442 |
def print_errors_result(result, verbose=False):
"""
"""
spacers = 4
if verbose:
print(f"\nTotal Stats\n{spacers*' '}max. err.: {result[0]:6.3f};")
print(f"{(spacers-2)*' '}c-avg. err.: {result[1]:6.3f};")
print(f"{(spacers-2)*' '}t-avg. err.: {result[2]:6.3f}")
r... | 83fadbb6fe977c262a822d7217f0103cd7f9ecde | 3,619,443 |
def filter_country_stats(stats, top_n, latest_date):
"""Filter the top n country statistics
Arguments:
stats {dict} -- The country statistics
top_n {int} -- The top n results to retrieve
latest_date {datetime} -- The latest date
Returns:
dict -- The filtered country... | 66b0cedea261887c53fd197b1ffda56866ff8627 | 3,619,444 |
def list_dict(l):
"""
return a dictionary with all items of l being the keys of the dictionary
"""
return dict([(i,None) for i in l]) | cb5a9c3acc4a0e6d162482d6b72e1eb52f6fad53 | 3,619,445 |
def readnetcdfInitial(name, value,default = 0.0):
"""
load initial condition from netcdf format
"""
filename = os.path.normpath(name)
try:
nf1 = Dataset(filename, 'r')
except:
msg = "Netcdf Initial file: \n"
raise CWATMFileError(filename,msg)
if value in nf1.variable... | 346aad3162927f59cbb7a46b638ab1607dd158e7 | 3,619,446 |
from operator import ne
def value_at_location(x, single_vol=False, single_pts=False, force_post_absolute_val=True):
"""
Extracts value at given point.
"""
# vol is batch_size, *vol_shape, nb_feats
# loc_pts is batch_size, nb_surface_pts, D or D+1
vol, loc_pts = x
fn = lambda y: ne.ut... | ca68d189604edf8a06734a8528990dfd1d693b29 | 3,619,447 |
def is_reference(key: str) -> bool:
"""
Does this key represent a berglas reference
"""
return key.startswith(REFERENCE_PREFIX) | 700a7fcaaadfa636dc72f44d135bb9f9272d6d19 | 3,619,448 |
def compute_heuristic_conn_4(init_pos, coord):
"""Returns Manhattan heuristic for distance from coord to init_pos
init_pos - coordinate of position of goal configuration
coord - coordinate of configuration for which heursitic is
being computed
Returns the heuristic distance to goal t... | 873fcbad5ebadcb8d0f0009c6d3bb615146bab5a | 3,619,449 |
import pandas
import types
def hpat_pandas_series_floordiv(self, other, level=None, fill_value=None, axis=0):
"""
Pandas Series method :meth:`pandas.Series.floordiv` implementation.
.. only:: developer
Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_op5
... | 3abe10214fbbb336ad13078e87e310c2ecae01cc | 3,619,450 |
def subs_si(expr: Expr) -> Expr:
"""Substitute any ConstantSymbols in an Expression with their value in a SI units
Args:
expr:
Expr, the sympy expression in which to substitute constant symbols for values
Returns:
Expr, the substituted expression
"""
return _subs_const_... | 3caa133c24508f7d54cbe0f6a7eba46a4834479d | 3,619,451 |
def generateGenericCell(nBuildings, pAgents, pPHHagents,
pAgriculture, pDHN, pPVplants,
pHeatpumps, pCHP, pBTypes,
nSepBSLAgents, pAgricultureBSLsep,
region, hist=0):
""" Create a cell of a generic energy system
The... | 62272f03b6c3e6bffe03fb4e7a3f9c058cace9fa | 3,619,452 |
def cancel_and_stop_intent_handler(handler_input):
"""Single handler for Cancel and Stop Intent."""
speech_text = "OK Mate calm down."
attr = handler_input.attributes_manager.session_attributes
attr['readShows'] = False
attr['readMovies'] = False
attr['readBoth'] = False
attr['active_reques... | c31bdbdb7810e0afd71e073c4bbc6f6486294782 | 3,619,453 |
def get_excluded_apps_and_models(excludes):
"""
:param excludes: list of app labels ("app_label.model_name" or "app_label") to exclude
:return: Tuple containing two sets: Set of AppConfigs to exclude, Set of model classes to excluded.
"""
excluded_apps = set()
excluded_models = set()
for exc... | 57fb09de6dc2162386a7e15a15a8ebe7c5795a2a | 3,619,454 |
import subprocess
import argparse
def subprocess_run(args, **kwargs):
"""
Emulate Python 3 "subprocess.run"
Don't help the caller remember to say: stdin=subprocess.PIPE
"""
# Trust the library, if available
if hasattr(subprocess, "run"):
run = subprocess.run(args, **kwargs) # pyli... | 39ed817b56b6c3869d8565a0fc5a862bcd331441 | 3,619,455 |
def frequency(text, char):
""" Counts frequency of a character in a string. """
count = 0
for c in text:
if c == char:
count += 1
return count | 5a58161f6aed1f8ba88ed6490891b544b23449cd | 3,619,456 |
def Interpolate(a,h,image,BP,sig_data=1,K=Squared_Expo,width=9):
"""
Interpolate(a,h,image,BP,sig_data=1,K=Squared_Expo,width=9)
Correcting the values of bad pixels by interpolation.
Parameters
----------
a: float
Same as in GPR_Kernel.
h: float or shape (2,) array-like
... | d55a5b42dcb3787770f75b92ebad5989d9d34945 | 3,619,457 |
import warnings
def ripser(
X,
maxdim=1,
thresh=np.inf,
coeff=2,
distance_matrix=False,
do_cocycles=False,
metric="euclidean",
):
"""Compute persistence diagrams for X data array. If X is not a distance matrix, it will be converted to a distance matrix using the chosen metric.
Par... | 2053225473556b8d9d15314ab12b74248616292c | 3,619,458 |
from typing import List
import itertools
def slice_spec_from_stats( # pylint: disable=invalid-name
statistics: statistics_pb2.DatasetFeatureStatisticsList,
categorical_uniques_threshold: int = 100,
max_cross_size: int = 2) -> List[slicer.SingleSliceSpec]:
"""Generates slicing spec from statistics.
A... | ffbcc6d229bec3016f8dfc746e186de061f30409 | 3,619,459 |
def is_benchmark_supported(benchmark : Benchmark):
"""returns True if the provided benchmark is supported by the tool and if the given benchmark should appear on the generated benchmark list"""
# Check for unsupported input languages: everything but PRISM currently
if benchmark.is_prism():
# Tempor... | 54d635d7f39e1a89ad42c11d3810bc7b20e03b0d | 3,619,460 |
from typing import Optional
def get_regional_map_file(
atlas_id: str,
parcellation_id: str,
region_id: str,
space_id: Optional[str] = None):
"""
Returns a regional map for given region name.
"""
roi, space_of_interest = parse_region_selection(
atlas_id, parcella... | 1d5a70fb5972f0a43f1eae5938e309df33928ded | 3,619,461 |
import sys
import os
def main():
"""
NAME
ani_depthplot.py
DESCRIPTION
plots tau, V3_inc, V1_dec, P and chi versus core_depth
SYNTAX
ani_depthplot.py [command line optins]
# or, for Anaconda users:
ani_depthplot_anaconda [command line options]
OPTIONS
... | f92407df0a88ca0565f75a967ca50b55c1319dd0 | 3,619,462 |
def get_parent_execution(execution_db):
"""Get the action execution for the parent workflow
Useful for finding the parent workflow. Pass in any ActionExecutionDB instance,
and this function will return the action execution of the parent workflow.
:param execution_db: The ActionExecutionDB instance for... | 1dddbbd9cbb3edcd1b8c9c7d536551f6aa14b22e | 3,619,463 |
def counts(short_question, course_code):
"""Return number of comments by star for a given course code, question,
and fiscal year.
"""
course_code = course_code.upper()
# Unpack arguments
fiscal_year = request.args.get('fiscal_year', '')
# Run query; return dict of 0s in case of invalid arguments
try:
counts... | 129d6d145458d2e4502cb563ab608dcdb85378aa | 3,619,464 |
from skmob.core import trajectorydataframe
import pandas as pd
import logging
def get_route_geometry(locs_or_traj):
"""
Computes a map-matched geometry for a list of locations or TrajDataFrame
Parameters
----------
locs_or_traj : list | TrajDataFrame
Either a list of coordinates in the fo... | 7a87ac19e4615d38aa180f14c2381b6a51db9e36 | 3,619,465 |
import os
def build_index(root, base_url):
"""
Create a new data.xml index file, by combining the xml description
files for various packages and collections. ``root`` should be the
path to a directory containing the package xml and zip files; and
the collection xml files. The ``root`` directory is expecte... | 4bced06d755d9d952674e857b29eb72344eccb1a | 3,619,466 |
from typing import Tuple
import struct
async def read_scoreframe(data: bytearray) -> Tuple[ScoreFrame, int]:
""" Read an osu! scoreframe from `data`. """
offset = 29
s = ScoreFrame(*struct.unpack('<iBHHHHHHiHH?BB?', data[:offset]))
if s.score_v2:
s.combo_portion, s.bonus_portion = struct.unpa... | 45e1ea7faebacc62be08cd84f877291560b85726 | 3,619,467 |
from operator import and_
from operator import or_
def status_log_for_each_instrument():
"""Get a dictionary containing the most recent log entry for each instrument with log entries.
Returns
-------
Dictionary with the instrument ids for each log as the key and a dictionary for the log's 'author', '... | 6ed2f7016a91c0084cdb94216385c37e400e24de | 3,619,468 |
def update_blog(title):
"""This defines the creation of a new form
"""
blog = Blog.query.filter_by(title = title).first()
form = BlogForm()
if form.validate_on_submit():
blog.title = form.title.data
blog.meta_title = form.meta_title.data
blog.body = form.blog.data
bl... | b2bc77fe6647ac3cefb7923103865dfccc1a1d6b | 3,619,469 |
def softmax_pooler_output(nr_class, *, exclusive_classes=True, **cfg):
"""Select features from the pooler output, (if necessary) mean-pool them
to produce one vector per item, and then softmax them.
The gradients of the class vectors are incremented in the backward pass,
to allow fine-tuning.
"""
... | 3a5610cafb182b60eda30d17e78c4f33429e6517 | 3,619,470 |
def get_latest_tle_from_restapi(number):
"""
:param number: get the latest TLE from Restful API
:return: a TLE
"""
return "see restful_client.py" | ac6c5e908bea386a12427ac07cd0249cf1b6f7e7 | 3,619,471 |
import pandas as pd
import os
def mroz2(path):
"""mroz
Data loads lazily. Type data(mroz) into the console.
A data.frame with 753 rows and 22 variables:
- inlf. =1 if in lab frce, 1975
- hours. hours worked, 1975
- kidslt6. # kids < 6 years
- kidsge6. # kids 6-18
- age. woman's age in yrs
... | 285f1e6d81bb369661425fb510a59e06a426fe7a | 3,619,472 |
import time
def measure_command(func, kwargs):
""" Measures the execution time of a function
:param func: function
:param kwargs: dict
keyword arguments
:return: float, result
(time, result of fucntion)
"""
time_start = time.time()
r = func(**kwargs)
dt = time.time() -... | 33ca8627681b3f32d8d39fc088175a6a38d51097 | 3,619,473 |
from bs4 import BeautifulSoup
def get_soup_object(response_content: str) -> BeautifulSoup:
"""
Note: possible to get page even if content is not desired
"""
# TODO: error handling here if empty string
return BeautifulSoup(response_content, "lxml") | 486306d5a42f286d36fa96fd01a606154ccaa2ec | 3,619,474 |
import os
import zipfile
def in_pyz():
""" Determine if running in pyz archive """
pyz_file = os.path.abspath(os.path.dirname(__file__))
if zipfile.is_zipfile(pyz_file):
return True
else:
return False | 0f9eae66abeec4f6f916cd037e16c743b0f3a77b | 3,619,475 |
def generator(input_dim=2,activation_function='linear',bias=True):
"""
Purpose:
-------
This is a network that can used to represent element in a given presentation. The choice is the one made in the paper.
Arguments:
---------
dim : integer dime... | eb7eeb5245abbbfe911941db83070d3ce987f08c | 3,619,476 |
from datetime import datetime
def _test_dt(code):
"""判断股票上市时间是否晚于指定时间"""
try:
return datetime.datetime(2005, 1, 1) >= get_ipo_date(code)
except:
return False | ff0fb6beb759235bb05637be735f73c1a8270ef4 | 3,619,477 |
from typing import List
from typing import Optional
from typing import Mapping
def edit_equipment_type(
client: SymphonyClient,
name: str,
new_positions_list: List[str],
new_port_definitions: List[EquipmentPortDefinition],
new_properties: Optional[Mapping[str, PropertyValue]] = None,
) -> Equipmen... | 3c69176d7175c411f0a96359d3379e0b1e0cff1d | 3,619,478 |
def get_color(pred_class, labels):
"""
Function to color the barplots. Defaults to blue, but it colors
the prediction green/red if it's correct/incorrect
:param pred_class:
:param labels:
:return:
"""
num_classes = 10 # Hard coded for the 10 MNIST labels
target_class = np.argmax(lab... | 3bc47c2c28d6177e01f2513b7c826a852e1c7e61 | 3,619,479 |
def add_member(client_session, esg_name, pool_name, member_name, member_ip, port=None, monitor_port=None, weight=None,
max_conn=None, min_conn=None):
"""
This function creates a Member inside a Server Pool on an ESG
:type client_session: nsxramlclient.client.NsxClient
:param client_sessi... | c58f6d28ebc0da3929f1d2572da6e0e227085073 | 3,619,480 |
def check_auth_shared_secret(auth = True,
):
"""
Authentication via HMAC signatures, nonces, and a local keypair DB.
"""
def decorator(func):
def proxyfunc(self, *args, **kw):
user_key = dict(self.request.headers).get("Key", False)
... | 441d1d8e898ca561f8c0cec59dfa17461d305f47 | 3,619,481 |
def _find_new_wire(wires: Wires) -> int:
"""Finds a new wire label that is not in ``wires``."""
ctr = 0
while ctr in wires:
ctr += 1
return ctr | b03afa0f77615f37d6c1f2f11d5d72c73fadeba5 | 3,619,482 |
import psutil
def is_linux_ready(path):
"""
linux下的文件是否已经准备好
:param path:
:return:
"""
for proc in psutil.process_iter():
try:
for item in proc.open_files():
if path == item.path:
return False
except Exception:
pass
... | b373cbcb34977bce784021787c5b55b7bf06df99 | 3,619,483 |
import time
import torch
def evaluate_model(
model, eval_loader, device, k=1, split_name="VAL", log_file="log.txt"
):
"""
Evaluate model (nn.Module) on data loaded by eval_loader (torch.utils.data.DataLoader)
Check top `k` (default: 1) predictions for each class while evaluating class accuracies
R... | cf5b636dcd5e1cce7092e7e7cd107e63e8b98f24 | 3,619,484 |
import inspect
from functools import partial
def cli_handle_exception(exception_handler, exception_classes):
"""
deal with exception stack info, and then just throw the wrapper exception by cli
>>> def cli_handler1(ex):
... assert False, 'Need root permission'
>>> @cli_handle_exception(cli_han... | 2cfa6a074de1c55142a4f8f2d71ed08a66ec726a | 3,619,485 |
def getMonthlyReportList(userId, year, month):
"""選択された月の1ヶ月分の月報データを取得するMapperを呼び出す
:param userId: 登録ユーザID
:param year: 登録年
:param month: 登録月
"""
dto = __getList(userId, year, month)
return dto | be54298534bda05ca65a48aa69a2158fa94a5c10 | 3,619,486 |
def frequency_sort(items):
"""
Return rating by frequency
"""
if sorted(items) == list(set(items)):
return items
elif len(set([items.count(x) for x in items])) == 1:
return sorted(items)
else:
return sorted(
sorted(items, reverse=True), key=lambda k: (item... | e782c137c5efececd46db6d9ac013790e943d8c8 | 3,619,487 |
def read_ts_guess_atomic_numbers(content):
"""Read structure from xtbscan.log file """
atom_symbols = []
number_of_atoms = int(content.split('\n')[0].strip())
ts_guess_energy, ts_index = read_ts_guess_energy(content)
ts_index = int(ts_index)
i = 0
for line in content.split('\n'):
i... | a24f1d23377c82c320d108944c21c8833ed35628 | 3,619,488 |
def templatepartsmap(spec, t, partnames):
"""Create a mapping of {part: ref}"""
partsmap = {spec.ref: spec.ref} # initial ref must exist in t
if spec.mapfile:
partsmap.update((p, p) for p in partnames if p in t)
elif spec.ref:
for part in partnames:
ref = '%s:%s' % (spec.ref... | 22ea9a0d474d832cf427568ee2e04adf1e00e0d4 | 3,619,489 |
def _gen_chamnet_v2(depth_multiplier, num_classes=1000, **kwargs):
""" Generate Chameleon Network (ChamNet)
Paper: https://arxiv.org/abs/1812.08934
Ref Impl: https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/modeling/backbone/fbnet_modeldef.py
FIXME: this a bit of a... | 51f70f287f837a3f2e88c18e92ddbdf6ec347db0 | 3,619,490 |
def two_p(name, space="nm", index_key=None):
"""
Return expression representing a 1-boson operator
name (str): Name of operator
space (str): Name of boson space
"""
x = Idx(0, space, fermion=False)
y = Idx(1, space, fermion=False)
t1 = Term(
1, [Sigma(x), Sigma(y)], [Tensor([x, ... | 0645ca6a27ea8b40b9f9ebb9fc2cf9ac4722a80b | 3,619,491 |
import re
def create_sig_selectors(width, bandwidth, scheme):
"""Generate indices for LSH band selectors
:param width:
:type width: int
:param bandwidth:
:type bandwidth: int
:param scheme:
:type scheme: str
:return:
:rtype: tuple
"""
split_res = re.split(r'\b([a-zA-Z]+)(... | a1ee500b62f91452d6ea9674f0c797258ef40c0e | 3,619,492 |
import numpy
def non_nan_values_per_image(input_data):
"""Create boolean mask to index nans in original data,
assuming all samples in the dataset have nans at the same position"""
boolean_nan_idx = numpy.isnan(input_data[:, 0, 0])
count = numpy.count_nonzero(numpy.isnan(input_data[:, 0, 0]))
non_n... | e963193bd4d5fcfcefb06b1e3687010ecf851745 | 3,619,493 |
def fit_pipeline(j_dataset, j_model, df):
"""
fit the model with data provided in the dataframe df, and information on the dataset in json format
:param j_dataset: dataset info in json format
:param j_model: model as a json
:param df: data as dataframe (including x and y columns and columns not use... | d6260b1c9813574b70c7db92a8b2acf9790be0e0 | 3,619,494 |
def _find_sub_prog():
"""
Returns the first job submission command found on the system.
Currently, only qsub and sbatch are supported
"""
possible_sub_prog_list = ['sbatch', 'qsub']
for prog in possible_sub_prog_list:
if popen('command -v ' + prog).read() != '':
return prog
... | 3842751031238e64c3f10b203c60fb0eccf7b702 | 3,619,495 |
import os
def processed_json_filename(path):
"""Take the path to a raw json asset and return the filename of the binary asset."""
return os.path.basename(processed_json_path(path)) | 4a110484a1a37aabcf71d964c1be29c9dfeb31e2 | 3,619,496 |
from typing import Tuple
from typing import Dict
from typing import Any
from typing import List
def generate_evaluation_table(
evaluation_directory: str,
) -> Tuple[Dict[str, Any], List[Dict[str, Any]], str]:
"""
Generate a table from the currently selected results.json summary file.
Parameters
-... | 586603cb3f2f21d334e7ffe41f590a5e850c3499 | 3,619,497 |
import json
def recommendation(request):
"""
Get:
Returns a list of recommendations
Input:
{
from: optional(str),
to: optional(str),
}
Output:
[
Recommendations
]
===
Input:
{
feedback_id: int,
feedback: str,
}
Output... | 0a51d3426ac59c19e2773cd23f5dc2a9ce50d09e | 3,619,498 |
def get_active_days_in_range(
range_start, range_end, ad_delivery_start_time_series, last_active_date_series):
"""Calculate the days an ad was active in a given range.
Args:
range_start: datetime.date Start of period of interest
range_end: datetime.date End of period of interest
... | e94c1f7e38342395790236d109dde2688ec3b50c | 3,619,499 |
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