content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def plot_heatmap(df, title=""):
"""
Plotly heatmap wrapper
:param df: pd.DataFrame
:param title: str
"""
fig = go.Figure(
data=go.Heatmap(z=df.values, x=df.columns, y=df.index, colorscale="RdBu")
)
fig.update_layout(template=_TEMPLATE, title=title, legend_orientation="h")
ret... | 46c3d362bdbe742b54ad09a56f4638ef1497bcc2 | 3,646,357 |
def shift_transactions_forward(index, tindex, file, pos, opos):
"""Copy transactions forward in the data file
This might be done as part of a recovery effort
"""
# Cache a bunch of methods
seek=file.seek
read=file.read
write=file.write
index_get=index.get
# Initialize,
pv=z64... | c19009c15a04b4a55389b584fad1744ebde03187 | 3,646,360 |
def draw_disturbances(seed, shocks_cov, num_periods, num_draws):
"""Creates desired number of draws of a multivariate standard normal distribution."""
# Set seed
np.random.seed(seed)
# Input parameters of the distribution
mean = [0, 0, 0]
shocks_cov_matrix = np.zeros((3, 3), float)
np.fill... | d467a1d5fde3eb32debca2711597ef24dc117aaa | 3,646,361 |
def wheel(pos):
"""Generate rainbow colors across 0-255 positions."""
if pos>1280:
pos = 1280
if pos <= 255:
r = 255-pos
g = 0
b = 255
else:
pos = pos-256
if pos <= 255:
r = 0
g = pos
b = 255
else:
p... | 765df4262ce3b04fb8b06f9256ca51670e2f5bfb | 3,646,363 |
def optimize_profile(diff_matrix, x_points, dc_init, exp_norm_profiles,
display_result=True, labels=None):
"""
Fit the diffusion matrix
Parameters
----------
diff_matrix : tuple
tuple of (eigenvalues, eigenvectors) in reduced basis (dim n-1)
x_points : 1-D array_li... | f2550f6fe4cb267559676d30ef0156ce528178cf | 3,646,365 |
def getargsfromdoc(obj):
"""Get arguments from object doc"""
if obj.__doc__ is not None:
return getargsfromtext(obj.__doc__, obj.__name__) | d49510388be36a60259683f4560b1d01fe9f9bf6 | 3,646,366 |
def nms(dets, thresh):
"""Dispatch to either CPU or GPU NMS implementations.\
Accept dets as tensor"""
return pth_nms(dets, thresh) | e6dbe7b44e1975c080e58d02d6e07ef22b2d3711 | 3,646,367 |
def QFont_from_Font(font):
""" Convert the given Enaml Font into a QFont.
Parameters
----------
font : Font
The Enaml Font object.
Returns
-------
result : QFont
The QFont instance for the given Enaml font.
"""
qfont = QFont(font.family, font.pointsize, font.weight... | bb62daf4d46315a7a55135894dc78e1d2898fee2 | 3,646,370 |
from typing import OrderedDict
def _find_in_iterable_case_insensitive(iterable, name):
"""
Return the value matching ``name``, case insensitive, from an iterable.
"""
iterable = list(OrderedDict.fromkeys([k for k in iterable]))
iterupper = [k.upper() for k in iterable]
try:
match = ite... | 548c951b08fb07251fda1b8918282462c8d0351a | 3,646,371 |
def predict_all_points(data, order, coefficients):
"""
:param data: input data to create least squares prediction of order(order) of
:param order: order for least squares prediction
:param coefficients: coefficients of LPC
:return: returns estimation of entire data set. Will be of length (len(data) ... | 4725c735241f439bf986743cafdee0e995373966 | 3,646,373 |
def _unpack(msg, decode=True):
"""Unpack and decode a FETCHed message dictionary."""
if 'UID' in msg and 'BODY[]' in msg:
uid = msg['UID']
body = msg['BODY[]']
if decode:
idate = msg.get('INTERNALDATE', None)
flags = msg.get('FLAGS', ())
return (uid, IMAP4Message(body, uid, idate, flags))
else:
r... | 5c027dcd54d29f6d95647b66ad2d28998866dc3c | 3,646,374 |
import logging
def video_in(filename=INPUTPATH):
"""reads (max.20sec!) video file and stores every frame as PNG image for processing
returns image name and image files (as np array?)"""
#create video capture object
cap = cv2.VideoCapture(filename)
name = filename.split('/')[-1].split('.')[0]
i... | cb82d7c6865c3bfe5f3f52f9cb7adc55a8d2e002 | 3,646,375 |
from typing import List
def convert_all_timestamps(results: List[ResponseResult]) -> List[ResponseResult]:
"""Replace all date/time info with datetime objects, where possible"""
results = [convert_generic_timestamps(result) for result in results]
results = [convert_observation_timestamps(result) for resul... | f81121fcd387626a2baa0ecfb342d3381f6def7f | 3,646,376 |
def convert(s):
""" Take full markdown string and swap all math spans with img.
"""
matches = find_inline_equations(s) + find_display_equations(s)
for match in matches:
full = match[0]
latex = match[1]
img = makeimg(latex)
s = s.replace(full, img)
... | 684a6be3812aad8b602631c45af407ca878f9453 | 3,646,377 |
def _amplify_ep(text):
"""
check for added emphasis resulting from exclamation points (up to 4 of them)
"""
ep_count = text.count("!")
if ep_count > 4:
ep_count = 4
# (empirically derived mean sentiment intensity rating increase for
# exclamation points)
ep_amplifier = ep... | 8f78a5f24aa22b5f2b4927131bfccf22ccc69ff3 | 3,646,379 |
def inline_singleton_lists(dsk):
""" Inline lists that are only used once
>>> d = {'b': (list, 'a'),
... 'c': (f, 'b', 1)} # doctest: +SKIP
>>> inline_singleton_lists(d) # doctest: +SKIP
{'c': (f, (list, 'a'), 1)}
Pairs nicely with lazify afterwards
"""
dependencies = dict((... | a4c2a8b6d96d0bfac8e9ba88a4bed301c3054f0a | 3,646,380 |
def vegasflowplus_sampler(*args, **kwargs):
"""Convenience wrapper for sampling random numbers
Parameters
----------
`integrand`: tf.function
`n_dim`: number of dimensions
`n_events`: number of events per iteration
`training_steps`: number of training_iterations
Returns... | 1b53d83bd010a8113640858d46d66c9c0ef76ff8 | 3,646,381 |
def remove_recalculated_sectors(df, prefix='', suffix=''):
"""Return df with Total gas (sum of all sectors) removed
"""
idx = recalculated_row_idx(df, prefix='', suffix='')
return df[~idx] | 54272933f72d45cf555f76086c809eba14713242 | 3,646,382 |
def unparse_headers(hdrs):
"""Parse a dictionary of headers to a string.
Args:
hdrs: A dictionary of headers.
Returns:
The headers as a string that can be used in an NNTP POST.
"""
return "".join([unparse_header(n, v) for n, v in hdrs.items()]) + "\r\n" | 7c06127752d0c6be19894703ba95f2e827e89b8f | 3,646,383 |
def modify_natoms(row, BBTs, fg):
"""This function takes a row of a pandas data frame and calculates the new number of atoms
based on the atom difference indicated in itw functional groups
BBTs : list of instances of BBT class
fg : instance of the Parameters class (fg parameters)
returns : n_atoms (... | 2c2df3d2859d33128f982b936011c73bafb723bc | 3,646,384 |
def recreate_cursor(collection, cursor_id, retrieved, batch_size):
"""
Creates and returns a Cursor object based on an existing cursor in the
in the server. If cursor_id is invalid, the returned cursor will raise
OperationFailure on read. If batch_size is -1, then all remaining documents
on the curs... | 1a4987715e35f1cf09ac3046c36c752289797ee6 | 3,646,385 |
def nut00b(date1, date2):
"""
Wrapper for ERFA function ``eraNut00b``.
Parameters
----------
date1 : double array
date2 : double array
Returns
-------
dpsi : double array
deps : double array
Notes
-----
The ERFA documentation is below.
- - - - - - - - - -
... | a5235543aca0d6de6e79878ac3db1d208d237a0d | 3,646,386 |
def Join_Factors(*factor_data, merge_names=None, new_name=None, weight=None, style='SAST'):
"""合并因子,按照权重进行加总。只将非缺失的因子的权重重新归一合成。
Parameters:
===========
factor_data: dataframe or tuple of dataframes
merge_names: list
待合并因子名称，必须是data_frame中列的子集
new_name: str
合成因子名称
weight: lis... | 95db1eda297cb8cb05a1db9b1fae9c25a034685f | 3,646,387 |
from pathlib import Path
def _check_for_file_changes(filepath: Path, config: Config) -> bool:
"""Returns True if a file was modified in a working dir."""
# Run 'git add' to avoid false negatives, as 'git diff --staged' is used for
# detection. This is important when there are external factors that impact ... | c99da7e993e74f7dbe5789c48832afc59638762c | 3,646,388 |
import time
def wait_or_cancel(proc, title, message):
"""
Display status dialog while process is running and allow user to cancel
:param proc: subprocess object
:param title: title for status dialog
:param message: message for status dialog
:return: (process exit code, stdout output or None)
... | 8b60e459523933ee205210d4761b6b7d9d8acbfb | 3,646,389 |
def getg_PyInteractiveBody_one_in_two_out():
"""Return a graph that has a PyInteractiveBody with one input
and two outputs.
"""
@dl.Interactive(
[("num", dl.Int(dl.Size(32)))],
[('num_out', dl.Int(dl.Size(32))), ('val_out', dl.Bool())]
)
def interactive_func(node: dl.PythonNode):... | 31af32a5ece2f4c76635a8f37a0ac644c5f0e364 | 3,646,390 |
def batch_norm_relu(inputs, is_training):
"""Performs a batch normalization followed by a ReLU."""
# We set fused=True for a performance boost.
inputs = tf.layers.batch_normalization(
inputs=inputs,
axis=FLAGS.input_layout.find('C'),
momentum=FLAGS.batch_norm_decay,
epsilon=FLAGS.batch_nor... | ab771b9d8747bc27d747dd9dce42a6bc9a1d59d3 | 3,646,391 |
def knn(points, p, k):
"""
Calculates the k nearest neighbours of a point.
:param points: list of points
:param p: reference point
:param k: amount of neighbours
:return: list of k neighbours
"""
return sorted(points, key=lambda x: distance(p, x))[:k] | e1a806cd4c16b5ecbf66301406dafeb2b12c46db | 3,646,392 |
def ruleset_detail(request, slug):
"""
View for return the specific ruleset that user pass by using its slug in JSON format.
:param request: WSGI request from user
:return: Specific ruleset metadata in JSON format.
"""
# try to fetch ruleset from database
try:
ruleset = Ruleset.obje... | a122a2e20641a13d6a934c0261f199ff304ae622 | 3,646,393 |
import requests
import json
def send_slack_notification(message):
"""
Send slack notification
Arguments:
message {string} -- Slack notification message
Returns:
response {Response} -- Http response object
"""
response = requests.post(
SLACK_WEBHOOK,
data=json.d... | 6c5f0e51c1bfce19ff9a4aec77c1e4c98cd359fa | 3,646,394 |
def method_detect(method: str):
"""Detects which method to use and returns its object"""
if method in POSTPROCESS_METHODS:
if method == "rtb-bnb":
return RemovingTooTransparentBordersHardAndBlurringHardBorders()
elif method == "rtb-bnb2":
return RemovingTooTransparentBord... | cb1dafba5a7c225c093ab602c6e383cb7f499bba | 3,646,396 |
def approve_pipelines_for_publishing(pipeline_ids): # noqa: E501
"""approve_pipelines_for_publishing
# noqa: E501
:param pipeline_ids: Array of pipeline IDs to be approved for publishing.
:type pipeline_ids: List[]
:rtype: None
"""
return util.invoke_controller_impl() | 585d4972955e240f146c3d06d5a181dcad36d111 | 3,646,397 |
def get_x(document_id, word2wid, corpus_termfrequency_vector):
"""
Get the feature vector of a document.
Parameters
----------
document_id : int
word2wid : dict
corpus_termfrequency_vector : list of int
Returns
-------
list of int
"""
word_list = list(reuters.words(docu... | fca6e5a6071a6b48b83effb37d3b77a88ddf4046 | 3,646,398 |
def process_chain_of_trust(host: str, image: Image, req_delegations: list):
"""
Processes the whole chain of trust, provided by the notary server (`host`)
for any given `image`. The 'root', 'snapshot', 'timestamp', 'targets' and
potentially 'targets/releases' are requested in this order and afterwards
... | 391024aeaa814f3159c8f45a925afce105b7b339 | 3,646,399 |
import struct
def collect_js(
deps,
closure_library_base = None,
has_direct_srcs = False,
no_closure_library = False,
css = None):
"""Aggregates transitive JavaScript source files from unfurled deps."""
srcs = []
direct_srcs = []
ijs_files = []
infos = []
... | 7a243401280646103522ed339ff20c35f05e031d | 3,646,400 |
import termios
import struct
import fcntl
def send_control(uuid, type, data):
"""
Sends control data to the terminal, as for example resize events
"""
sp = sessions[uuid]
if type == 'resize':
winsize = struct.pack("HHHH", data['rows'], data['cols'], 0, 0)
fcntl.ioctl(sp['ptymaster... | 262ef0ccffac80c0293d1446eb0e38e50b2ce687 | 3,646,401 |
def dgausscdf(x):
"""
Derivative of the cumulative distribution function for the normal distribution.
"""
return gausspdf(x) | e968f20ca28555eb50d5766440c5f3f47522c1ff | 3,646,404 |
import tqdm
def model_datasets_to_rch(gwf, model_ds, print_input=False):
"""convert the recharge data in the model dataset to a recharge package
with time series.
Parameters
----------
gwf : flopy.mf6.modflow.mfgwf.ModflowGwf
groundwater flow model.
model_ds : xr.DataSet
datas... | b32442c508e17205737ddb8168fe323b57cfbb2f | 3,646,406 |
from typing import List
from datetime import datetime
def create_events_to_group(
search_query: str,
valid_events: bool,
group: Group,
amount: int = 1,
venue: bool = False,
) -> List[Event]:
"""
Create random test events and save them to a group
Arguments:
search_query {str} -... | 31045c8f9311d677d766d87ed9fc1d6848cc210d | 3,646,407 |
def alt_stubbed_receiver() -> PublicKey:
"""Arbitrary known public key to be used as reciever."""
return PublicKey("J3dxNj7nDRRqRRXuEMynDG57DkZK4jYRuv3Garmb1i98") | c07461fc060f9dc637e93cadd32604aae892f924 | 3,646,408 |
import base64
def create_api_headers(token):
"""
Create the API header.
This is going to be sent along with the request for verification.
"""
auth_type = 'Basic ' + base64.b64encode(bytes(token + ":")).decode('ascii')
return {
'Authorization': auth_type,
'Accept': 'applicatio... | 41ba1e22898dab2d42dde52e4458abc40640e957 | 3,646,409 |
def _combine(bundle, transaction_managed=False, rollback=False,
use_reversion=True):
"""
Returns one sreg and DHCP output for that SREG.
If rollback is True the sreg will be created and then rolleback, but before
the rollback all its HWAdapters will be polled for their DHCP output.
"""... | 0171e804e4f10167d85e92608a09bca55308edfa | 3,646,410 |
def get_node_session(*args, **kwargs):
"""Creates a NodeSession instance using the provided connection data.
Args:
*args: Variable length argument list with the connection data used
to connect to the database. It can be a dictionary or a
connection string.
**kwargs... | bb992b7e49a698dfb7b54b1492616913a6b5df27 | 3,646,411 |
def edit_role(payload, search_term):
"""Find and edit the role."""
role = Role.query.get(search_term)
# if edit request == stored value
if not role:
return response_builder(dict(status="fail",
message="Role does not exist."), 404)
try:
if payload... | 8690c8fc1c1aea5245d9cef540c355a2903a8484 | 3,646,413 |
def use_redis_cache(key, ttl_sec, work_func):
"""Attemps to return value by key, otherwise caches and returns `work_func`"""
redis = redis_connection.get_redis()
cached_value = get_pickled_key(redis, key)
if cached_value:
return cached_value
to_cache = work_func()
pickle_and_set(redis, k... | a2c631466aef18c7bb640b17e57421e257ad7314 | 3,646,414 |
def counting_sort(array, low, high):
"""Razeni pocitanim (CountingSort). Seradte zadane pole 'array'
pricemz o poli vite, ze se v nem nachazeji pouze hodnoty v intervalu
od 'low' po 'high' (vcetne okraju intervalu). Vratte serazene pole.
"""
counts = [0 for i in range(high - low + 1)]
for elem i... | bd4ccccdb24786ec3f3d867afe1adf340c9e53b5 | 3,646,415 |
import re
def normalize_archives_url(url):
"""
Normalize url.
will try to infer, find or guess the most useful archives URL, given a URL.
Return normalized URL, or the original URL if no improvement is found.
"""
# change new IETF mailarchive URLs to older, still available text .mail archive... | e8a5351af28338c77c3e94fdf2b81e22c7a6edfd | 3,646,416 |
def getIsolatesFromIndices(indices):
"""
Extracts the isolates from the indices of a df_X.
:param pandas.index indices:
cn.KEY_ISOLATE_DVH, cn.KEY_ISOLATE_MMP
:return dict: keyed by cn.KEY_ISOLATE_DVH, cn.KEY_ISOLATE_MMP
values correspond to rows element in the index
"""
keys = [n for n in indice... | 4e9200c722ce0c478d13eddcc799f4a8f7cab6db | 3,646,418 |
def save_group_geo_org(user_id, group_id, area_id, org_unit_id):
"""Method for attaching org units and sub-counties."""
try:
if org_unit_id:
geo_org_perm, ctd = CPOVCUserRoleGeoOrg.objects.update_or_create(
user_id=user_id, group_id=group_id, org_unit_id=org_unit_id,
... | ed7750760405e12f790454e247e54917184e7044 | 3,646,419 |
def tf_efficientnet_lite0(pretrained=False, **kwargs):
""" EfficientNet-Lite0 """
# NOTE for train, drop_rate should be 0.2, drop_path_rate should be 0.2
kwargs['bn_eps'] = BN_EPS_TF_DEFAULT
kwargs['pad_type'] = 'same'
model = _gen_efficientnet_lite(
'tf_efficientnet_lite0', channel_multipli... | 49ea1c68f168ad613222808e2fbb1ead52190243 | 3,646,420 |
import ast
from typing import Optional
def get_qualname(node: ast.AST) -> Optional[str]:
"""
If node represents a chain of attribute accesses, return is qualified name.
"""
parts = []
while True:
if isinstance(node, ast.Name):
parts.append(node.id)
break
eli... | 0d08b25a50b7d159f5df3b0b17282725eb748f38 | 3,646,422 |
def traceUsage(addr, register, steps):
"""
Given a start address, a register which holds a value and the number of steps,
this function disassembles forward #steps instructions and traces the value of <register>
until it is used in a call instruction. It then returns the offset added to <register> and the addre... | 78c805af660b5e98348de1bd1ae4b7ce9a57238b | 3,646,423 |
def array3d (surface):
"""pygame.surfarray.array3d (Surface): return array
Copy pixels into a 3d array.
Copy the pixels from a Surface into a 3D array. The bit depth of the
surface will control the size of the integer values, and will work
for any type of pixel format.
This function will temp... | a2079a540453d5ba69f5b10e292341ef6fcfb972 | 3,646,425 |
import torch
def masked_kl_div(input, target, mask):
"""Evaluate masked KL divergence between input activations and target distribution.
Parameters:
input (tensor) - NxD batch of D-dimensional activations (un-normalized log distribution).
target (tensor) - NxD normalized target distribution.
... | afdd704bac7caabd7d0cbbd2599af6c1a440ae1c | 3,646,426 |
def find_peaks(ts, mindist=100):
"""
Find peaks in time series
:param ts:
:return:
"""
extreme_value = -np.inf
extreme_idx = 0
peakvalues = []
peaktimes = []
find_peak = True
idx = 0
for r in ts.iteritems():
# print(r)
if find_peak:
# look fo... | 5f4dbf0b6c9e4e8961c14b1ba255ebcdf210c50b | 3,646,428 |
def get_flanking_seq(genome, scaffold, start, end, flanking_length):
"""
Get flanking based on Blast hit
"""
for rec in SeqIO.parse(genome, "fasta"):
if rec.id == scaffold:
return str(
rec.seq[int(start) - int(flanking_length) : int(end) + int(flanking_length)]
... | 509002a7099ad62b0449e1c5de9a1a7dd875bc0c | 3,646,430 |
import re
def d(vars):
"""List of variables starting with string "df" in reverse order. Usage: d(dir())
@vars list of variables output by dir() command
"""
list_of_dfs = [item for item in vars if (item.find('df') == 0 and item.find('_') == -1 and item != 'dfs')]
list_of_dfs.sort(key=lambda x:int(... | 4961ae70a61e45b81e06e55ee9553ff61fd45d18 | 3,646,431 |
import inspect
def get_class_namespaces(cls: type) -> tuple[Namespace, Namespace]:
"""
Return the module a class is defined in and its internal dictionary
Returns:
globals, locals
"""
return inspect.getmodule(cls).__dict__, cls.__dict__ | {cls.__name__: cls} | 46f275bcc328d9ca87ffdebf616d42096705d3fb | 3,646,432 |
from .io import select_driver
def write_stream(path, sync=True, *args, **kwargs):
"""Creates a writer object (context manager) to write multiple dataframes into one file. Must be used as context manager.
Parameters
----------
path : str, filename or path to database table
sync : bool, default True
Set to `Fal... | 8e2274e102b60b139b6e40f425682d06268e10a5 | 3,646,433 |
from typing import Dict
def diff(
df: DataFrame,
columns: Dict[str, str],
periods: int = 1,
axis: PandasAxis = PandasAxis.ROW,
) -> DataFrame:
"""
Calculate row-by-row or column-by-column difference for select columns.
:param df: DataFrame on which the diff will be based.
:param colum... | 38ed83fc7e1847a2c9e31abb217990becc1bc04f | 3,646,434 |
import base64
def decodeTx(data: bytes) -> Transaction:
"""Function to convert base64 encoded data into a transaction object
Args:
data (bytes): the data to convert
Returns a transaction object
"""
data = base64.b64decode(data)
if data[:1] != tx_flag:
return None
... | da52e9dcb641d2986fa47d15f9da8d1edea28659 | 3,646,435 |
def create_package_from_datastep(table):
"""Create an importable model package from a score code table.
Parameters
----------
table : swat.CASTable
The CAS table containing the score code.
Returns
-------
BytesIO
A byte stream representing a ZIP archive which can be importe... | 0874f1a755ed73af09091a7c0f1b3fb3e5e861e4 | 3,646,436 |
def _test_diff(diff: list[float]) -> tuple[float, float, float]:
"""Последовательный тест на медианную разницу с учетом множественного тестирования.
Тестирование одностороннее, поэтому p-value нужно умножить на 2, но проводится 2 раза.
"""
_, upper = seq.median_conf_bound(diff, config.P_VALUE / populat... | 024d0eaba612361e4fef39839bfd31474d5be5a6 | 3,646,437 |
def get_repo_of_app_or_library(app_or_library_name):
""" This function takes an app or library name and will return the corresponding repo
for that app or library"""
specs = get_specs()
repo_name = specs.get_app_or_lib(app_or_library_name)['repo']
if not repo_name:
return None
return Rep... | 72c0349354fdc11da3ff16f2dfa3126eb02fa381 | 3,646,438 |
from datetime import datetime
def get_index_price_change_by_ticker(fromdate: str, todate: str, market: str="KOSPI") -> DataFrame:
"""입력된 기간동안의 전체 지수 등락률
Args:
fromdate (str ): 조회 시작 일자 (YYMMDD)
todate (str ): 조회 종료 일자 (YYMMDD)
market (str, optional): 조회 시장 (KOSPI... | 6d65ffeaccd1e5fe307e1e5387e413db3c2eb5fe | 3,646,439 |
def axpy(alpha, x, y, stream=None):
"""y <- alpha*x + y """
global _blas
if not isinstance(alpha, Number): raise ValueError('alpha is not a numeric type')
validate_argument_dtype(x, 'x')
validate_argument_dtype(y, 'y')
if not _blas: _blas = Blas()
_blas.stream = stream
dtype = promote(... | 10b8c46b1fc160d637241750c408957b8f184ee9 | 3,646,440 |
def _unenroll_get_hook(app_context):
"""Add field to unenroll form offering data removal, if policy supports."""
removal_policy = _get_removal_policy(app_context)
return removal_policy.add_unenroll_additional_fields(app_context) | 6c8e6a06d45fecfa8828ce8a24ca9e1e910b1e9c | 3,646,441 |
from typing import Union
def query_fetch_bom_df(search_key: str, size: int) -> Union[pd.DataFrame, None]:
"""Fetch and return bom dataframe of the article
Runs recursive query on database to fetch the bom.
"""
# Recursive query
raw_query = f"""WITH cte AS (
SELECT *
FROM [{DB_NAM... | 753f0378590df1c2b3e50f7bad8d2b15490ae488 | 3,646,442 |
def zscore(collection, iteratee=None):
"""Calculate the standard score assuming normal distribution. If iteratee
is passed, each element of `collection` is passed through a iteratee before
the standard score is computed.
Args:
collection (list|dict): Collection to process.
iteratee (mix... | a813295f6cce309b936b94a9d70f082f435a4b89 | 3,646,443 |
from typing import Tuple
def AND(
*logicals: Tuple[func_xltypes.XlExpr]
) -> func_xltypes.XlBoolean:
"""Determine if all conditions in a test are TRUE
https://support.office.com/en-us/article/
and-function-5f19b2e8-e1df-4408-897a-ce285a19e9d9
"""
if not logicals:
raise xlerror... | ebdc5c4f2c3cab31a78507923eded284eb679fd4 | 3,646,444 |
def check_mask(mask):
"""Check if mask is valid by its area"""
area_ratio = np.sum(mask) / float(mask.shape[0] * mask.shape[1])
return (area_ratio > MASK_THRES_MIN) and (area_ratio < MASK_THRES_MAX) | a82f415d95ea07571da2aabeeddc6837b0a80f8d | 3,646,445 |
def supported_estimators():
"""Return a `dict` of supported estimators."""
allowed = {
'LogisticRegression': LogisticRegression,
'RandomForestClassifier': RandomForestClassifier,
'DecisionTreeClassifier': DecisionTreeClassifier,
'KNeighborsClassifier': KNeighborsClassifier,
... | 1bb76e81252c3b959a376f23f2462d4faef234a9 | 3,646,446 |
from hiicart.gateway.base import GatewayError
from hiicart.gateway.amazon.gateway import AmazonGateway
from hiicart.gateway.google.gateway import GoogleGateway
from hiicart.gateway.paypal.gateway import PaypalGateway
from hiicart.gateway.paypal2.gateway import Paypal2Gateway
from hiicart.gateway.paypal_adaptive.gateway... | c60e3e88cf6bb919208821d8ee214368d39dc7f6 | 3,646,447 |
import sqlite3
def execute_query(db, query):
"""get data from database
"""
result = []
with closing(sqlite3.connect(db)) as conn:
conn.row_factory = sqlite3.Row
cur = conn.cursor()
for row in cur.execute(query):
result.append({name: row[name] for name in row.keys()}... | 75476c8a9f14751eb46fc2891ba5e7bddecd3c0e | 3,646,448 |
def to_mgb_supported_dtype(dtype_):
"""get the dtype supported by megbrain nearest to given dtype"""
if (
dtype.is_lowbit(dtype_)
or dtype.is_quantize(dtype_)
or dtype.is_bfloat16(dtype_)
):
return dtype_
return _detail._to_mgb_supported_dtype(dtype_) | 864b5bb7099771705ad478e5e89db8f3035f1c4f | 3,646,450 |
def get_reset_state_name(t_fsm):
"""
Returns the name of the reset state.
If an .r keyword is specified, that is the name of the reset state.
If the .r keyword is not present, the first state defined
in the transition table is the reset state.
:param t_fsm: blifparser.BlifParser().blif.fsm ob... | c65ea80f94f91b31a179faebc60a97f7260675c4 | 3,646,451 |
def gridmake(*arrays):
"""
Expands one or more vectors (or matrices) into a matrix where rows span the
cartesian product of combinations of the input arrays. Each column of the
input arrays will correspond to one column of the output matrix.
Parameters
----------
*arrays : tuple/list of np.... | 56c5375024170fbd599500c0603e0e3dcc7f53d4 | 3,646,452 |
import logging
import math
def pagerotate(document: vp.Document, clockwise: bool):
"""Rotate the page by 90 degrees.
This command rotates the page by 90 degrees counter-clockwise. If the `--clockwise` option
is passed, it rotates the page clockwise instead.
Note: if the page size is not defined, an ... | 37f0a9e726f490c357afb48ace49484cfcae84ce | 3,646,453 |
import torch
def gauss_reparametrize(mu, logvar, n_sample=1):
"""Gaussian reparametrization"""
std = logvar.mul(0.5).exp_()
size = std.size()
eps = Variable(std.data.new(size[0], n_sample, size[1]).normal_())
z = eps.mul(std[:, None, :]).add_(mu[:, None, :])
z = torch.clamp(z, -4., 4.)
ret... | 5c4fa87c5287aae3727608a003c3c91c2ba5c1a9 | 3,646,456 |
def forward_pass(img, session, images_placeholder, phase_train_placeholder, embeddings, image_size):
"""Feeds an image to the FaceNet model and returns a 128-dimension embedding for facial recognition.
Args:
img: image file (numpy array).
session: The active Tensorflow session.
images_pl... | 846c05a167e116ca4efbe3888486a3ee740d33ef | 3,646,458 |
import urllib
def check_url(url):
"""Returns True if the url returns a response code between 200-300,
otherwise return False.
"""
try:
req = urllib.request.Request(url, headers=headers)
response = urllib.request.urlopen(req)
return response.code in range(200, 209)
except... | 79f20eeb14724b728f020ff4c680e49f6a1a2473 | 3,646,459 |
def build_permutation_importance(
data,
data_labels,
feature_names,
model,
metrics,
repeats=100,
random_seed=42
):
"""Calculates permutation feature importance."""
pi_results = {}
for metric in metrics:
pi = sklearn.inspection.permutation_i... | 3b0b87ddf53446156b20189dad7c3d0b3ae2a1c2 | 3,646,460 |
def _load_parent(collection, meta):
"""Determine the parent document for the document that is to be
ingested."""
parent = ensure_dict(meta.get("parent"))
parent_id = meta.get("parent_id", parent.get("id"))
if parent_id is None:
return
parent = Document.by_id(parent_id, collection=collect... | 2f53440fa9610f9e8ca494ec8ec27bf9d6a09273 | 3,646,461 |
import requests
def get_latest_sensor_reading(sensor_serial, metric):
"""
Get latest sensor reading from MT sensor
metrics: 'temperature', 'humidity', 'water_detection' or 'door'
"""
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"X-Cisco-Mera... | 88de9d770f3be91700e3c86ff6460e2fdaa35d01 | 3,646,462 |
def border_msg(msg: str):
"""
This function creates boarders in the top and bottom of text
"""
row = len(msg)
h = ''.join(['+'] + ['-' * row] + ['+'])
return h + "\n" + msg + "\n" + h | cdd9d17ba76014f4c80b9c429aebbc4ca6f959c3 | 3,646,463 |
def create_app(config_name='development'):
"""Returns flask app based on the configuration"""
flask_app = Flask(__name__)
flask_app.config.from_object(app_config[config_name])
flask_app.config['JSON_SORT_KEYS'] = False
flask_app.url_map.strict_slashes = False
flask_app.register_error_handler(400... | 783edefb40c2f3cc0aefa0788b0c1c04d581aa39 | 3,646,464 |
def auto_merge_paths(data, auto_merge_distance, auto_close_paths=True):
"""
This function connects all paths in the given dataset, for which the start or endpoints are closer than
auto_merge_distance.
:param data: Should be a list or tuple containing paths, attributes, svg_attributes.
:param auto_m... | 34ec7d0b853a70159ebef6244236475375a3ca9d | 3,646,465 |
def is_authorized(secure: AccessRestriction):
"""Returns authorization status based on the given access restriction.
:param secure: access restriction
:type secure: AccessRestriction
:return: authorization status (``True`` or ``False``)
"""
if secure == AccessRestriction.ALL:
return Tru... | e070ae5521db1079426b80b6ff8a3fc5c9a9ba09 | 3,646,466 |
def create_link_forum(**attrs):
"""Save a new link forum."""
link = build_link_forum(**attrs)
link.save()
return link | e94e1001e42f46cd1c1803fbff35d0eded89858e | 3,646,467 |
def prepare_scan():
"""
Returns a lexical scanner for HTSQL grammar.
"""
# Start a new grammar.
grammar = LexicalGrammar()
# Regular context.
query = grammar.add_rule('query')
# Whitespace characters and comments (discarded).
query.add_token(r'''
SPACE: [\s]+ | [#] [^\0\r... | ffc30354378a03f95be988b7ee62b01708795f41 | 3,646,469 |
def get_test_server(ctxt, **kw):
"""Return a Server object with appropriate attributes.
NOTE: The object leaves the attributes marked as changed, such
that a create() could be used to commit it to the DB.
"""
kw['object_type'] = 'server'
get_db_server_checked = check_keyword_arguments(
... | 03d754223274282b15aeb9b5cf636f6acd90024c | 3,646,470 |
def keras_model(optimizer="Adamax", activation="softplus", units=32):
"""Function to create model, required for KerasClassifier"""
model = Sequential()
model.add(Dense(units, activation="relu", input_dim=2500))
model.add(Dense(2, activation=activation))
model.compile(loss="categorical_crossentropy",... | ccd1cc5652a207e3c4c2bc170d43fe22b4375c0b | 3,646,471 |
def start_end_key(custom_cmp):
"""
Compare models with start and end dates.
"""
class K(object):
"""
Define comparison operators.
http://code.activestate.com/recipes/576653-convert-a-cmp-function-to-a-key-function/
"""
def __init__(self, obj, *args):
s... | b1d7b48cc3e9926b6138850ad3b8307adbb4f2f3 | 3,646,472 |
def get_previous_release_date():
""" Fetch the previous release date (i.e. the release date of the current live database) """
releases = Release.objects.all().order_by('-date')
return str(releases[1].date) | 764d90daaf5c60460f22e56063a40c261cb6b45e | 3,646,473 |
def readLensModeParameters(calibfiledir, lensmode='WideAngleMode'):
"""
Retrieve the calibrated lens correction parameters
"""
# For wide angle mode
if lensmode == 'WideAngleMode':
LensModeDefaults, LensParamLines = [], []
with open(calibfiledir, 'r') as fc:
# Read the... | 51245aa19f32ebb31df5748e0b40022ccae01e24 | 3,646,474 |
def scale(boxlist, y_scale, x_scale, scope=None):
"""scale box coordinates in x and y dimensions.
Args:
boxlist: BoxList holding N boxes
y_scale: (float) scalar tensor
x_scale: (float) scalar tensor
scope: name scope.
Returns:
boxlist: BoxList holding N boxes
"""
with... | adffbdce632470852e0499bb93915f93a7695d5a | 3,646,475 |
import requests
def fetch(uri: str, method: str = 'get', token: str = None):
""":rtype: (str|None, int)"""
uri = 'https://api.github.com/{0}'.format(uri)
auth = app.config['GITHUB_AUTH']
headers = {'Accept': 'application/vnd.github.mercy-preview+json'}
json = None
if token:
headers['A... | 14cde2808108173e6ab86f3eafb4c8e35daf4b40 | 3,646,476 |
from typing import OrderedDict
from typing import Mapping
from typing import Sequence
from typing import Container
from typing import Iterable
from typing import Sized
def nested_tuple(container):
"""Recursively transform a container structure to a nested tuple.
The function understands container types inher... | 60dac69865d753b14558d7156e40703e26fb57a1 | 3,646,477 |
from typing import OrderedDict
def _validate_args(func, args, kwargs):
"""Validate customer function args and convert them to kwargs."""
# Positional arguments validate
all_parameters = [param for _, param in signature(func).parameters.items()]
# Implicit parameter are *args and **kwargs
if any(pa... | 51d357d032dc0b26aeb32d1850b1a630bafab508 | 3,646,478 |
def _qual_arg(user_value,
python_arg_name,
gblock_arg_name,
allowable):
"""
Construct and sanity check a qualitative argument to
send to gblocks.
user_value: value to try to send to gblocks
python_arg_name: name of python argument (for error string)
gbl... | 7bf6717ee3dbeb533902773c86316d2bbdcd59a9 | 3,646,479 |
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