content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def gamescriptToJson(title: str, version: str = None) -> dict:
"""
Get game script heirarchy as a dictionary (for saving as json, etc)
"""
scripts = GameScript.objects.all().filter(title=title)
if version:
scripts = scripts.filter(version=version)
if len(scripts) == 0:
print("No... | c76779b76b69fb1816f9e96136fdee903212d831 | 3,659,400 |
def is_ignored_faces(faces):
"""Check if the faces are ignored faces.
Args:
faces: Encoded face from face_recognition.
Returns:
bool: If a not ignored face appeared, return false, otherwise true.
"""
global ignored_faces
for face in faces:
matches = face_recognition.co... | bda7703cfb471ac5c95cb6aa30f6d758129ae8a5 | 3,659,401 |
from typing import Optional
def get_prediction_model_status(hub_name: Optional[str] = None,
prediction_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> ... | 14ff24d3f7edf674c5cd29a643ae28a1a3d8ed99 | 3,659,402 |
def build_2d_grid(ir):
""" Build simple grid with a column for each gate."""
grid = []
for g in ir.gates:
step = [None] * ir.ngates
if g.is_single():
step[g.idx0] = g
if g.is_ctl():
step[g.ctl] = g.ctl
step[g.idx1] = g
grid.append(step)
... | 55c17327fb530301ca505b42cdb8d47426491374 | 3,659,403 |
import argparse
import os
def parse_args():
"""
Wrapper function of argument parsing process.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--save_loc', type=str, default='.',
help='where to save results'
)
parser.add_argument(
'--log_dir', type=str,... | 2083d01de27f7f3b4481fe90dbc39614257aeb5d | 3,659,404 |
from typing import Union
from typing import List
from typing import Tuple
from typing import Dict
from typing import Any
import copy
def emmental_collate_fn(
batch: Union[List[Tuple[Dict[str, Any], Dict[str, Tensor]]], List[Dict[str, Any]]],
min_data_len: int = 0,
max_data_len: int = 0,
) -> Union[Tuple[D... | b18c7ebf50f5554055da5de8a2ddce9e758ea1ef | 3,659,405 |
def trap_jac_factory(j, dt):
"""Factory function to return a function for evaluating the Jacobian
of the trapezoidal formula. This returns a function of x_n (x at
this time step).
:param j: Jacobian of the function of x.
:param dt: time step.
:returns: trap_jac, callable which takes x_n and ev... | 5e6c365b6b92c13577249d34e7580827dc894604 | 3,659,406 |
from pathlib import Path
def get_position_object(file_path: FilePathType):
"""
Read position data from .bin or .pos file and convert to
pynwb.behavior.SpatialSeries objects. If possible it should always
be preferred to read position data from the `.bin` file to ensure
samples are locked to ecephys... | 2d20e5b0a4f7077748650e7a3e3054c79b68185c | 3,659,407 |
import random
def throw_dice(n):
"""Throw `n` dice, returns list of integers"""
results = []
while n > 0:
results += [random.randint(1,6)]
n = n-1
return results | 68c56b468ecd1eff59932099dd4620bae9581f45 | 3,659,408 |
import json
def verify_token_signature(token):
"""Verify the signature of the token and return the claims
such as subject/username on valid signature"""
key = jwk.JWK.from_password(flask.current_app.config.get("SECRET_KEY"))
try:
jwttoken = jwt.JWT(key=key, jwt=token, algs=["HS256"])
r... | d93233acb8a26ba0552ddc26777ccab4e40c4306 | 3,659,409 |
def logtime_r2(t, y, ppd):
"""
Convert y=f(t) data from linear in time to logarithmic in time.
Args:
t: is the input time vector, linearly spaced
y: is the input vector of y values
ppd: number of points per decade for the output
Returns:
A 3-tuple (tout, you... | ed77d7665488d3620d5cb62f4ba443b2361944b4 | 3,659,410 |
def parcours_serpentin(n):
"""Retourne la liste des indices (colonne,ligne) (!!attention ici
ligne et colonne sont inversées!!) des cases correspondant à un
parcours de tableau de taille n x n en serpentin.
Ex: pour T = [ [1,2,3],
[4,5,6],
[7,8,9] ]
le parcour... | 189e486ad82d75923244daf51c223254f7b29fcc | 3,659,411 |
def bdev_rbd_unregister_cluster(client, name):
"""Remove Rados cluster object from the system.
Args:
name: name of Rados cluster object to unregister
"""
params = {'name': name}
return client.call('bdev_rbd_unregister_cluster', params) | 03bf70352b8df65044eba1c9ece4b156590e11bc | 3,659,412 |
def get_rndc_secret():
"""Use the singleton from the DesignateBindCharm to retrieve the RNDC
secret
:returns: str or None. Secret if available, None if not.
"""
return DesignateBindCharm.singleton.get_rndc_secret() | b6fb5aebd272a6bc4db7d6541112566109e28195 | 3,659,413 |
def transform_tweet(source_tweet):
"""
Perform transformation on one tweet, producing a new, transformed tweet.
:param source_tweet: Tweet text to transform
:type source_tweet: str
:return: Transformed tweet text
:rtype: str
"""
no_emojis = replace_emojis(source_tweet)
as_tokens = tokenize_string(no_... | 9c4722200c7c85157aefca0c65946b6dd0e264d5 | 3,659,414 |
import json
def pdFrame(file):
"""Creates a pandas data frame from a json log file
Args:
file: json log file to read
Returns:
pandas data frame
"""
logger.debug("creating pandas data frame from {}".format(file))
data = []
with open(file) as f:
for line in f:
... | bfb299820e4cd3001de89f3598a664a11988edc4 | 3,659,415 |
import scipy
import time
def fitDataBFGSM2(M, val, c_w_l, init=None, nozero=True, k=3e34, lam=1., name='W_Abundances_grid_puestu_adpak_fitscaling_74_0.00000_5.00000_1000_idlsave'): #init is the three initial values of the gaussian needed to fit the data
""" function for determining the optimal fit given the desir... | 35ddd0690e2ed60d6271f9be232cea3d808d562f | 3,659,416 |
def set_complete_cfg_spacy(false_or_true: str):
"""Set all SpaCy configuration parameters to the same logical value."""
return pytest.helpers.backup_config_params(
cfg.cls_setup.Setup._DCR_CFG_SECTION_SPACY,
[
(cfg.cls_setup.Setup._DCR_CFG_SPACY_TKN_ATTR_CLUSTER, false_or_true),
... | 10ac74714e11b8c8492de7ec1d2809323819b8eb | 3,659,417 |
import sys
import traceback
def guard_unexpected_errors(func):
"""Decorator to be used in PyObjC callbacks where an error bubbling up
would cause a crash. Instead of crashing, print the error to stderr and
prevent passing to PyObjC layer.
For Python 3, print the exception using chaining. Accomplished... | 42b8e4ce05cca51272679ab5024d07798dafb357 | 3,659,418 |
def get_lun_ids(service_instance=None):
"""
Return a list of LUN (Logical Unit Number) NAA (Network Addressing Authority) IDs.
"""
if service_instance is None:
service_instance = get_service_instance(opts=__opts__, pillar=__pillar__)
hosts = utils_esxi.get_hosts(service_instance=service_in... | 6194a8f73a71730d928391a492d5e8fe0fdb3f50 | 3,659,419 |
def parse_midi_file(midi_file,
max_notes=float('Inf'),
max_time_signatures=1,
max_tempos=1,
ignore_polyphonic_notes=True,
convert_to_drums=False,
steps_per_quarter=16):
"""Summary
Parameters
... | 6c3ce0135bf45a8992f94197f5b10ab472407f40 | 3,659,420 |
def filter_prediction(disable_valid_filter, disable_extra_one_word_filter, pred_token_2dlist_stemmed):
"""
Remove the duplicate predictions, can optionally remove invalid predictions and extra one word predictions
:param disable_valid_filter:
:param disable_extra_one_word_filter:
:param pred_token_2... | 8cbeb93c6fdfdc64cfa5819baa903699544ccb3d | 3,659,421 |
def simple_dict_event_extractor(row, condition_for_creating_event, id_field, timestamp_field, name_of_event):
"""
Takes a row of the data df and returns an event record {id, event, timestamp}
if the row satisfies the condition (i.e. condition_for_creating_event(row) returns True)
"""
if condition_fo... | 2195acf5df6f465fdf3160df3abbac54e5ac0320 | 3,659,422 |
def split_fused_prelu(input_graph_def: util.GraphDef) -> util.GraphDef:
"""
This function looks for fused operations that include a 'Prelu'-activation.
Matching nodes will be split into individual operations.
TFJS uses fused operations for performance.
Some fused activations aren't supported by TF ... | 36b22afa67dd9259aae9f7be8ec6c4ffdf7c1167 | 3,659,423 |
import gc
def test_harvest_lost_resources(pool):
"""Test unreferenced resources are returned to the pool."""
def get_resource_id():
"""
Ensures ``Resource`` falls out of scope before calling
``_harvest_lost_resources()``.
"""
return id(pool.get_resource()._resource)
... | 04b8b29520c2ae9c2c47cef412659e9c567c6a8a | 3,659,424 |
def __call__for_keras_init_v1(self, shape, dtype=None, partition_info=None):
""" Making keras VarianceScaling initializers v1 support dynamic shape.
"""
if dtype is None:
dtype = self.dtype
scale = self.scale
scale_shape = shape
if partition_info is not None:
scale_shape = partition_info.full_shape
... | 860dc27ecd133b5bb193c4856736f9bb1a52d243 | 3,659,425 |
def create_line(net, from_bus, to_bus, length_km, std_type, name=None, index=None, geodata=None,
df=1., parallel=1, in_service=True, max_loading_percent=nan):
""" create_line(net, from_bus, to_bus, length_km, std_type, name=None, index=None, \
geodata=None, df=1., parallel=1, in_serv... | 218a3a16bce0d746465991c0992f614bddf98892 | 3,659,426 |
def get_initmap(X, A=None, standardize=False, cov_func=None):
""" Give back parameters such that we have the L U decomposition of the
product with A (if given, or the PCA scores if not).
That is we will get back:
X[:, perm]*L*U + b = ((X-meanvec)/stdvec)*A
where A are PCA directions if not g... | 53ec26f8efe4c0869b4e4423419db32ed08128e0 | 3,659,427 |
def read_FQ_matlab(file_open):
""" Opens FISH-quant result files generated with Matlab (tab-delimited text file).
Args:
file_open (string): string containing the full file name.
Returns:
dictionary containing outlines of cells, and if present the detected spots.
"""
# Open file
... | 01c2c2263573e754c216c69496f648a883bb1843 | 3,659,428 |
def create_default_reporting_options(embedded=True, config={}):
"""
config must follow this scheme:
{
`table_name`: {
`option1`: `value1`
}
}
The different options will depend on the table role.
- for ALL tables:
{n
'data' : {
'remove_... | cc7d341a0d63979bbf3223a241c5707acf057547 | 3,659,429 |
def get_patient_note(state, patient_id, note_id, *args, **kwargs):
"""
Return a note for a patient.
---
tags: ["FHIR"]
parameters:
- name: patient_id
in: path
description: ID of the patient of interest
required: true
schema:
type: string
... | 399212c31d2ae34b96a5617ca73063745c22621c | 3,659,430 |
def _html_build_item(tag: str, text: str, attributes: map = None, include_tags=True) -> str:
"""Builds an HTML inline element and returns the HTML output.
:param str tag: the HTML tag
:param str text: the text between the HTML tags
:param map attributes: map of attributes
:param bool include_ta... | 13b165a98679c2ebaf9a1dec7619a3297c729a63 | 3,659,431 |
from typing import Dict
from typing import Optional
import random
def sim_sample(
out_prefix: str,
sample_id: int,
chrom_start: int = 0,
chrom_end: int = 10000,
start_rate: float = 0.001,
end_rate: float = 0.01,
mut_rate: float = 0.01,
) -> Dict[str, File]:
"""
Simulate sequencing ... | d8a858b3f8099dd57cdc7abb4f1473e238038536 | 3,659,432 |
def vif_col(X, y, col_name):
"""计算vif
计算具体一个column的vif，
一般阈值在5或者10，超过这个数字则表明有
共线性。
Attributes:
X (pd.DataFrame): 自变量
y (pd.Series): 因变量
col_name (str): 需要判断的列
References:
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani.
An Introduct... | 6d9c88d928934d60182b597a89c6da6d1f7d1194 | 3,659,433 |
def get_mesh_stat(stat_id_start_str, attr_value, xmin, ymin, xmax, ymax):
"""
地域メッシュの統計情報を取得する
@param stat_id_start_str 統計IDの開始文字 この文字から始まるIDをすべて取得する.
@param attr_value cat01において絞り込む値
@param xmin 取得範囲
@param ymin 取得範囲
@param xmax 取得範囲
@param ymax 取得範囲
"""
rows = database_proxy.ge... | 9a861925436c2cf10eb4773be9dfa79c901d43f4 | 3,659,434 |
def babel_extract(fileobj, keywords, comment_tags, options):
"""Babel extraction method for Jinja templates.
.. versionchanged:: 2.3
Basic support for translation comments was added. If `comment_tags`
is now set to a list of keywords for extraction, the extractor will
try to find the best... | 35ee7c05ee91afc1ccf7c752bdff72e3c3d30d78 | 3,659,435 |
def main(directory='.', verbose=True):
"""Lists "data" files recursively in a given directory, tar files
are extracted.
The "data" files have :file:`info` and :file:`pickle` extensions.
TODO: not only recognize .tar and .tar.gz and .tgz but .zip...
"""
filelist = list()
director... | 40cf44878b88e2a0ea312602e98ea7c6821c4c03 | 3,659,436 |
import numpy
def onedthreegaussian(x, H, A1, dx1, w1, A2, dx2, w2, A3, dx3, w3):
"""
Returns two 1-dimensional gaussian of form
H+A*numpy.exp(-(x-dx)**2/(2*w**2))
"""
g1 = A1 * numpy.exp(-(x-dx1)**2 / (2*w1**2))
g2 = A2 * numpy.exp(-(x-dx2)**2 / (2*w2**2))
g3 = A3 * numpy.exp(-(x-dx3)**2 /... | f93ea1339fe1498fdaeaee91f75b7ba316455646 | 3,659,437 |
def match_any_if_key_matches(audit_id, result_to_compare, args):
"""
We want to compare things if we found our interested key
Even if the list does not have my interested name, it will pass
Match dictionary elements dynamically. Match from a list of available dictionaries
There is an argument: matc... | 2fc5f4dea92fdc231f496b1cbe4d78554a32e930 | 3,659,438 |
from typing import Optional
from typing import Union
def confusion_matrix_by_prob(true: np.ndarray,
predicted_prob: np.ndarray,
thresholds: Optional[Union[list, tuple, np.ndarray]] = None,
pos_label: Union[bool, str, int] = _DEFAUL... | 29bc8808ae1f35f13e52ac26e4e1993c423c6dc6 | 3,659,439 |
from typing import Sequence
from typing import Mapping
import itertools
def group_slaves_by_key_func(
key_func: _GenericNodeGroupingFunctionT,
slaves: Sequence[_GenericNodeT],
sort_func: _GenericNodeSortFunctionT = None,
) -> Mapping[_KeyFuncRetT, Sequence[_GenericNodeT]]:
""" Given a function for gro... | c3e286d2ff618758cd86c16f1b6685faea4b4d7a | 3,659,440 |
def init_clfs():
""" init classifiers to train
Returns:
dict, clfs
"""
clfs = dict()
# clfs['xgb'] = XGBClassifier(n_jobs=-1)
clfs['lsvc'] = LinearSVC()
return clfs | 4725656eda4e6991cc215bcd5a209ff23171eea6 | 3,659,441 |
def get_field_types():
"""Get a dict with all registration field types."""
return get_field_definitions(RegistrationFormFieldBase) | a9fe05535a541a7a5ada74dc9138a6c2ab29f528 | 3,659,442 |
def get_md_links(filepath):
"""Get markdown links from a md file.
The links' order of appearance in the file IS preserved in the output.
This is to check for syntax of the format [...](...).
The returned 'links' inside the () are not checked for validity or
subtle differences (e.g. '/' vs no '/' at... | 3076f77802965cb281101530f4ab360e5996f627 | 3,659,443 |
import tqdm
def dask_to_zarr(df, z, loc, chunk_size, nthreads: int, msg: str = None):
# TODO: perhaps change name of Dask array so it does not get confused with a dataframe
"""
Creates a Zarr hierarchy from a Dask array.
Args:
df (): Dask array.
z (): Zarr hierarchy.
loc (): L... | aa05321183cf086f6a397f6a3cb1f3493eb6689d | 3,659,444 |
def get_reactor_logs(project_id, application_id, api_key=None, **request_kwargs):
"""
Get the logs of a Reactor script.
:param project_id: The Project of the Application.
:type project_id: str
:param application_id: The Application to get the script logs for.
:type application_id: str
:para... | 82743619292f387708e7b1dc3fe93c59e232d1cf | 3,659,445 |
import os
def bids_init(bids_src_dir, overwrite=False):
"""
Initialize BIDS source directory
:param bids_src_dir: string
BIDS source directory
:param overwrite: string
Overwrite flag
:return True
"""
# Create template JSON dataset description
datadesc_json = os.path.j... | 3f728dbeaabf575fb6395a28175e8d94d4260e68 | 3,659,446 |
def summation_i_squared(n):
"""Summation without for loop"""
if not isinstance(n, int) or n < 1:
return None
return int(((n*(n+1)*(2*n+1))/6)) | dec0aba274bcaf3e3a821db5962af51d39835438 | 3,659,447 |
def str_to_number(this):
"""
Convert string to a Number
"""
try:
return mknumber(int(this.value))
except ValueError:
return mknumber(float(this.value)) | e67df9c0de5a5cdbc76a3026f7e31cd3190013c4 | 3,659,448 |
import logging
def _LinterRunCommand(cmd, debug, **kwargs):
"""Run the linter with common RunCommand args set as higher levels expect."""
return cros_build_lib.RunCommand(cmd, error_code_ok=True, print_cmd=debug,
debug_level=logging.NOTICE, **kwargs) | a48355f692b9c75d8ad14bf899f2e9a305bd25a2 | 3,659,449 |
def plotTSNE(Xdata, target = None, useMulti=True, num=2500, savename=None, njobs=4, size=4, cmap=None, dim=(12,8)):
"""
Plot TSNE for training data
Inputs:
> Xdata: The training feature data (DataFrame)
> target: The training target data (Series)
> num (2500 by default): The number o... | 9751f861df2d67516e93218000d23e23ba0ad4fe | 3,659,450 |
import os
def _get_distance(captcha_url):
"""
获取缺口距离
:param captcha_url: 验证码 url
:return:
"""
save_path = os.path.abspath('...') + '\\' + 'images'
if not os.path.exists(save_path):
os.mkdir(save_path)
img_path = _pic_download(captcha_url, 'captcha')
img1 = cv2.imread(img_p... | a1e79e775bf2c298992b1a0f986318b2ca70edd8 | 3,659,451 |
def adjust_contrast(img, contrast_factor):
"""Adjust contrast of an Image.
Args:
img (PIL Image): PIL Image to be adjusted.
contrast_factor (float): How much to adjust the contrast. Can be any
non negative number. 0 gives a solid gray image, 1 gives the
original image while 2 increases the contr... | aedd8bb489df64138189626585228ffc086e2428 | 3,659,452 |
def matplotlib_view(gviz: Digraph):
"""
Views the diagram using Matplotlib
Parameters
---------------
gviz
Graphviz
"""
return gview.matplotlib_view(gviz) | 9eb0a686c6d01a7d24273bbbc6ddb9b4ee7cb9ac | 3,659,453 |
def shuf_repeat(lst, count):
""" Xiaolong's code expects LMDBs with the train list shuffled and
repeated, so creating that here to avoid multiple steps. """
final_list = []
ordering = range(len(lst))
for _ in range(count):
np.random.shuffle(ordering)
final_list += [lst[i] for i in or... | fea9478aaa37f5b1c58d4a41126055d9cfa4b035 | 3,659,454 |
def create_query(table_name, schema_dict):
"""
see datatypes documentation here:
https://www.postgresql.org/docs/11/datatype.html
"""
columns = db_schema[table_name]
return (
f"goodbooks_{table_name}",
[f"{column} {value}" for column, value in columns.items()],
) | 3b330d57f45ca053cfbe90952adc7aa1658ab76d | 3,659,455 |
from typing import Any
from typing import Tuple
def new_document(
source_path: str, settings: Any = None
) -> Tuple[nodes.document, JSONReporter]:
"""Return a new empty document object.
Replicates ``docutils.utils.new_document``, but uses JSONReporter,
which is also returned
Parameters
-----... | 9ec26dd8f8b9c7a2e3a4bc56520b7872e7b53a7a | 3,659,456 |
import requests
def delete_repleciation(zfssrcfs, repel_uuid):
"""ZFS repleciation action status
accepts: An exsistng ZFS action uuid (id).
returns: the ZFS return status code.
"""
r = requests.delete(
"%s/api/storage/v1/replication/actions/%s"
% (url, repel_uuid), auth=zfsauth, ve... | f62ad1ec3e31ac7c54cf749982690631bb7b72d2 | 3,659,457 |
from pathlib import Path
import random
import torch
import sys
def load_checkpoint(
neox_args, model, optimizer, lr_scheduler, inference=False, iteration=None
):
"""Load a model checkpoint and return the iteration."""
if neox_args.deepspeed:
load_optim_and_scheduler = (
not neox_ar... | 7395cc48a1be6c86cf15cd4576257d7f3b5c0f19 | 3,659,458 |
import aiohttp
def get_logged_in_session(websession: aiohttp.ClientSession) -> RenaultSession:
"""Get initialised RenaultSession."""
return RenaultSession(
websession=websession,
country=TEST_COUNTRY,
locale_details=TEST_LOCALE_DETAILS,
credential_store=get_logged_in_credential... | 87a5a439c5ca583c01151f340ce79f2f4a79558c | 3,659,459 |
def __getStationName(name, id):
"""Construct a station name."""
name = name.replace("Meetstation", "")
name = name.strip()
name += " (%s)" % id
return name | daab36ed8020536c8dd2c073c352634696a63f3e | 3,659,460 |
import io
import os
import torch
def load_hist(path):
"""
load spatial histogram
"""
# load all hist properties
logpYX = io.loadmat(os.path.join(path, 'logpYX'))['value']
xlab = io.loadmat(os.path.join(path, 'xlab'))['value']
ylab = io.loadmat(os.path.join(path, 'ylab'))['value']
rg_bi... | e494f5e351c8c098b26bd0e7f417ec634a15d9c3 | 3,659,461 |
def post_url(url):
"""Post url argument type
:param str url: the post url
:rtype: str
:returns: the post url
"""
url = url.strip()
if len(url) == 0:
raise ArgumentTypeError("A url is required")
elif len(url) > Url.URL_LENGTH:
raise ArgumentTypeError("The url length is o... | 65d3c670580d6abfcfefcc8bcff35ca4e7d51f5c | 3,659,462 |
def create_planner(request):
"""Create a new planner and redirect to new planner page."""
user = request.user
plan = Plan.objects.create(author=user)
plan.save()
return HttpResponseRedirect(reverse('planner:edit_plan', args=[plan.id], )) | ab22dfa950208b44c308690dcff6e0f228faa406 | 3,659,463 |
def rule_matching_evaluation(df, model, seed_num, rein_num, eval_num, label_map, refer_label, lime_flag=True, scan_flag=False
, content_direction='forward', xcol_name='text', n_cores=20):
"""A integrated rule extraction, refinement and validation process.
On the dataset, sample base... | 9ed0d5653797544de384c41ef6d9e402d2a57403 | 3,659,464 |
def login():
""" Typical login page """
# if current user is already logged in, then don't log in again
if current_user.is_authenticated:
return redirect(url_for('index'))
form = LoginForm()
if form.validate_on_submit():
user = User.query.filter_by(username=form.username.data).first... | e4114979a6b5b5845f32442bb66ee0798357f4e7 | 3,659,465 |
def create_timeperiod_map(
start: spec.Timestamp = None,
end: spec.Timestamp = None,
length: spec.Timelength = None,
) -> spec.TimeperiodMap:
"""create Timeperiod with representation TimeperiodMap
## Inputs
- start: Timestamp
- end: Timestamp
- length: Timelength
## Returns
- T... | c8087ea252e86b97c55376bfb21b93c2b50e3b19 | 3,659,466 |
import requests
async def patched_send_async(self, *args, **kwargs):
"""Patched send function that push to queue idx of server to which request is routed."""
buf = args[0]
if buf and len(buf) >= 6:
op_code = int.from_bytes(buf[4:6], byteorder=PROTOCOL_BYTE_ORDER)
# Filter only caches opera... | c78c9b437547266b4bfa82627c45e3c7c6450049 | 3,659,467 |
from datetime import datetime
def add_event_records(df, event_type, event_date):
"""Add event records for the event type."""
log(f'Adding {DATASET_ID} event records for {event_type}')
this_year = datetime.now().year
df = df.loc[df[event_date].notnull(), :].copy()
df['event_id'] = db.create_ids(df,... | d3e804d9b24274e5a87e1e470f1f758214e1f805 | 3,659,468 |
def _renderPath(path,drawFuncs,countOnly=False,forceClose=False):
"""Helper function for renderers."""
# this could be a method of Path...
points = path.points
i = 0
hadClosePath = 0
hadMoveTo = 0
active = not countOnly
for op in path.operators:
if op == _MOVETO:
if f... | 17a2fc3224b2ba80de9dee0110468c4d934281b7 | 3,659,469 |
def _search_focus(s, code=None):
""" Search for a particular module / presentation.
The search should return only a single item. """
if not code:
code = input("Module code (e.g. TM129-17J): ")
results = _search_by_code(s, code)
if not len(results):
print('Nothing found for "{}"... | 8eec36dbe48c1825d742c9834776a7a0705429b6 | 3,659,470 |
def parse_line(sample):
"""Parse an ndjson line and return ink (as np array) and classname."""
class_name = sample["word"]
inkarray = sample["drawing"]
stroke_lengths = [len(stroke[0]) for stroke in inkarray]
total_points = sum(stroke_lengths)
np_ink = np.zeros((total_points, 3), dtype=np.float3... | 19d20f7e67b58d699c0aea47f1f03095a957f757 | 3,659,471 |
def evalRPN(self, tokens):
# ! 求解逆波兰式，主要利用栈
"""
:type tokens: List[str]
:rtype: int
"""
stack = []
for item in tokens:
# print(stack)
if item.isdigit():
stack.append(int(item))
if item[0] == '-' and len(item) > 1 and item[1:].isdigit():
stack... | 6b2050f6f635324878116371cd81a6d25ea31240 | 3,659,472 |
def _validate_flags():
"""Returns True if flag values are valid or prints error and returns False."""
if FLAGS.list_ports:
print("Input ports: '%s'" % (
"', '".join(midi_hub.get_available_input_ports())))
print("Ouput ports: '%s'" % (
"', '".join(midi_hub.get_available_output_ports())))
... | 812791a8c71cc354a1ebe32f3fa9a3cc0f1c0182 | 3,659,473 |
def proto_test(test):
"""
If test is a ProtoTest, I just return it. Otherwise I create a ProtoTest
out of test and return it.
"""
if isinstance(test, ProtoTest):
return test
else:
return ProtoTest(test) | 3326ea07ae5e4f90d3ae49cedee7b16aa97a3c65 | 3,659,474 |
def get_frames():
"""Get frames for an episode
Params:
episode: int
The episode for which the frames shall be returned
Returns:
frames: dict
The frames for an episode per timestep
"""
episode = int(request.args.get('user'))
frames = data_preprocessor.get_f... | 1180c38175ef07f5e58ce8b77d748f6c1c1ab17b | 3,659,475 |
def remove(s1,s2):
"""
Returns a copy of s, with all characters in s2 removed.
Examples:
remove('abc','ab') returns 'c'
remove('abc','xy') returns 'abc'
remove('hello world','ol') returns 'he wrd'
Parameter s1: the string to copy
Precondition: s1 is a string
Parameter ... | 089107767063309d1cc34360ae290e7fa74133e7 | 3,659,476 |
import re
import os
def get_firebase_db_url():
"""Grabs the databaseURL from the Firebase config snippet. Regex looks
scary, but all it is doing is pulling the 'databaseURL' field from the
Firebase javascript snippet"""
regex = re.compile(r'\bdatabaseURL\b.*?["\']([^"\']+)')
cwd = os.path.dirname(... | aafc688c20adc060046ebd96b047741bedae600f | 3,659,477 |
def get_issuer_plan_ids(issuer):
"""Given an issuer id, return all of the plan ids registered to that issuer."""
df = pd.read_csv(PATH_TO_PLANS)
df = df[df.IssuerId.astype(str) == issuer]
return set(df.StandardComponentId.unique()) | b41b36b70000736acde63673961f92231a62f9a4 | 3,659,478 |
def add_args(parser):
"""
parser : argparse.ArgumentParser
return a parser added with args required by fit
"""
# Training settings
parser.add_argument('--model', type=str, default='mobilenet', metavar='N',
help='neural network used in training')
parser.add_argument('... | e1e2d1e61976b8f2dea6d6ab5f928b72bcdd15a5 | 3,659,479 |
def parse_coords(lines):
"""Parse skbio's ordination results file into coords, labels, eigvals,
pct_explained.
Returns:
- list of sample labels in order
- array of coords (rows = samples, cols = axes in descending order)
- list of eigenvalues
- list of percent variance explained
F... | fec53839f5f995f94f07120cac5bab1ba66f7b4c | 3,659,480 |
def run_ann(model, train, test, params_save_path, iteration, optimizer, loss, callbacks=None, valid=None,
shuffle_training=True,
batch_size=16,
num_epochs=30):
"""
Run analog network with cross-validation
:param batch_size: batch size during training
:param model: ref... | 9df68d8c6cdf6df08177bd1cc5d3116c10ae073e | 3,659,481 |
def get_sector(session, sector_name=None, sector_id=None):
""" Get a sector by it's name or id. """
return get_by_name_or_id(session, Sector, model_id=sector_id, name=sector_name) | 69de99bbdd630fb0cc5412c2b3124dff819287ed | 3,659,482 |
def is_valid_pre_6_2_version(xml):
"""Returns whether the given XML object corresponds to an XML output file of Quantum ESPRESSO pw.x pre v6.2
:param xml: a parsed XML output file
:return: boolean, True when the XML was produced by Quantum ESPRESSO with the old XML format
"""
element_header = xml.f... | 80bda73addc68a88b2a1dc5828c0553cbaf7e6f2 | 3,659,483 |
import warnings
def exportdf (df =None, refout:str =None, to:str =None, savepath:str =None,
modname:str ='_wexported_', reset_index:bool =True):
"""
Export dataframe ``df`` to `refout` files. `refout` file can
be Excell sheet file or '.json' file. To get more details about
the `wr... | 0bc6d2750f236c5f3e529b2489be47658ddbf2d9 | 3,659,484 |
def clean_bpoa_seniority_list(csv):
"""Clean a digitized BPOA seniority list."""
dirty = pd.read_csv(csv)
clean = pd.DataFrame()
clean["job_title"] = dirty["Rank"]
clean["last_name"] = dirty["Last name"]
clean["first_name"] = dirty["First Name"]
clean = clean.apply(correct_name, axis=1)
... | b1af748d92c4cdced4a77fd3799dada318c0f57e | 3,659,485 |
def topk(table, metric, dimensions, is_asc, k, **kwargs):
""" This function returns both the results according to the intent
as well as the debiasing suggestions.
Some of the oversights considered in this intent are-
1. Regression to the mean
2. Looking at tails to find causes - TODO
Args:
... | be8387b349da558d07fdb86fc8261f9153869028 | 3,659,486 |
def addMovieElement(findings, data):
""" Helper Function which handles unavailable information for each movie"""
if len(findings) != 0:
data.append(findings[0])
else:
data.append("")
return data | af3c45c8b8d4c0cb7ba1cac4925d0f5998affe93 | 3,659,487 |
from typing import Optional
def get_bst_using_min_and_max_value(preorder: list) -> Node:
"""
time complexity: O(n)
space complexity: O(n)
"""
def construct_tree(min_: int, max_: int) -> Optional[Node]:
nonlocal pre_index
nonlocal l
if pre_index >= l:
return No... | 809c74967e73c82a428f317d8551432bb392d5ea | 3,659,488 |
import math
def qwtStepSize(intervalSize, maxSteps, base):
"""this version often doesn't find the best ticks: f.e for 15: 5, 10"""
minStep = divideInterval(intervalSize, maxSteps, base)
if minStep != 0.0:
# # ticks per interval
numTicks = math.ceil(abs(intervalSize / minStep)) - 1
... | 57d1c4140e32dbf4a8bd0e306b9c10d4e9dae9bd | 3,659,489 |
def get_trimmed_glyph_name(gname, num):
"""
Glyph names cannot have more than 31 characters.
See https://docs.microsoft.com/en-us/typography/opentype/spec/...
recom#39post39-table
Trims an input string and appends a number to it.
"""
suffix = '_{}'.format(num)
return gname[:31... | a5e90163d15bd4fc0b315414fffd2ac227768ab0 | 3,659,490 |
def vmatrix(ddir, file_prefix):
""" generate vmatrix DataFile
"""
name = autofile.name.vmatrix(file_prefix)
writer_ = autofile.write.vmatrix
reader_ = autofile.read.vmatrix
return factory.DataFile(ddir=ddir, name=name,
writer_=writer_, reader_=reader_) | b9303e08f10e0604fde7b40116b74e66aac553dc | 3,659,491 |
import os
def fetch_precision_overlay(precision):
"""
Returns the overlay for the given precision value as cv2 image.
"""
overlay_folder = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
'../assets/precision_overlays'
)
img_path = os.path.join(
overlay_fold... | 7d8e8c82676bc4686f9b08b171a6deb60fb60a9e | 3,659,492 |
import ast
from typing import Callable
from typing import MutableMapping
from typing import Union
import inspect
def get_argument_sources(
source: Source,
node: ast.Call,
func: Callable,
vars_only: bool,
pos_only: bool
) -> MutableMapping[str, Union[ast.AST, str]]:
"""Get t... | 1ab344b5ccf9754ade06210e74540db51fe8c671 | 3,659,493 |
def _register_dataset(service, dataset, compression):
"""Registers a dataset with the tf.data service.
This transformation is similar to `register_dataset`, but supports additional
parameters which we do not yet want to add to the public Python API.
Args:
service: A string or a tuple indicating how to con... | e95edfeaccc324bf7d732658846a3ef25c1a371c | 3,659,494 |
def rivers_by_station_number(stations,N):
"""function that uses stations_by_rivers to return a dictionary that it then
itterates each river for, summing the number of stations on the river into tuples"""
stationsOfRivers = stations_by_rivers(stations)
listOfNumberStations = []
for river in stationsO... | ca159843f10cbadf5a35529c45656121672972e0 | 3,659,495 |
import itertools
def generate_itoa_dict(
bucket_values=[-0.33, 0, 0.33], valid_movement_direction=[1, 1, 1, 1]):
"""
Set cartesian product to generate action combination
spaces for the fetch environments
valid_movement_direction: To set
"""
action_space_extended = [bucket_values if... | b8264174857aeb9d64226cce1cd1625f7e65b726 | 3,659,496 |
import dateutil
from datetime import datetime
def try_convert(value, datetime_to_ms=False, precise=False):
"""Convert a str into more useful python type (datetime, float, int, bool), if possible
Some precision may be lost (e.g. Decimal converted to a float)
>>> try_convert('false')
False
>>> try... | 59f8a16310e4ac6604a145dcff1ff390df259da9 | 3,659,497 |
def signin(request, auth_form=AuthenticationForm,
template_name='accounts/signin_form.html',
redirect_field_name=REDIRECT_FIELD_NAME,
redirect_signin_function=signin_redirect, extra_context=None):
"""
Signin using email or username with password.
Signs a user in by combinin... | 6a8536fb3a0c551ae4cdb7f01de622c012d0734c | 3,659,498 |
import random
def run_syncdb(database_info):
"""Make sure that the database tables are created.
database_info -- a dictionary specifying the database info as dictated by Django;
if None then the default database is used
Return the identifier the import process should use.
"""
... | 19da3e97226363fbee885ff8ee24c7abe0489d3c | 3,659,499 |
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