content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def add_anomaly_data(egg_data: pd.DataFrame) -> pd.DataFrame:
"""
Given a dataframe of egg data, add a column for each anomaly metric, and populate it with the
results of running the breakpoint analysis on each row
Args:
egg_data (pd.DataFrame): the dataframe containing the egg temperature data
... | 74a65f25275e816eb4cf59c3a6aa11daa30ea41e | 3,625,342 |
import struct
def set_wm_strut_partial(window, left, right, top, bottom, left_start_y,
left_end_y, right_start_y, right_end_y, top_start_x,
top_end_x, bottom_start_x, bottom_end_x):
"""
Sets the partial struts for a window.
:param window: A windo... | b6da1a199d1ca3194efee425c6f704d03093c28e | 3,625,343 |
def get_connection(database_name: str):
"""Hakee yhteyden tietokantaan ja palauttaa sen.
"""
return connection | 9970b6e9804806c3fb7e97b40f66ef8e20a280c6 | 3,625,344 |
def generate_graph_seq2seq_io_data(
df, x_offsets, y_offsets, add_time_in_day=True, add_day_in_week=False, scaler=None
):
"""
Generate samples from
:param df:
:param x_offsets:
:param y_offsets:
:param add_time_in_day:
:param add_day_in_week:
:param scaler:
:return:
# x: ... | 0140bdbe039748b1b1690e30b179154c7adaf6f4 | 3,625,345 |
def execute(cmd, stderr_to_stdout=False, stdin=None, cwd=None):
"""Execute a command in the shell and return a tuple (rc, stdout, stderr)"""
if stderr_to_stdout:
stderr = STDOUT
else:
stderr = PIPE
p = Popen(cmd, shell=False, bufsize=0, close_fds=True, stdin=stdin, stdout=PIPE, stderr=s... | db50c409e0fd24003c304d1f1d27e8341913fd84 | 3,625,346 |
import random
def get_random_number_with_zero(min_num: int, max_num: int) -> str:
"""
Get a random number in range min_num - max_num of len max_num (padded with 0).
@param min_num: the lowest number of the range in which the number should be generated
@param max_num: the highest number of the range i... | bdc9f192286262566d2b2a87e8124abdf745ecbd | 3,625,347 |
from typing import List
import torch
def cluster_props(all_props: List[CollisionProp]) -> dict:
""" Many provided properties are overlapping -- some subsumes some others, cluster them for later usage.
:return: a dict of central points -> sorted props in decreasing order of their epsilons
"""
d = defau... | 44fefaeb620caf7eb6f66ec0e35052df8396fea6 | 3,625,348 |
from comtypes.automation import VARIANT
def COMMETHOD(idlflags, restype, methodname, *argspec):
"""Specifies a COM method slot with idlflags.
XXX should explain the sematics of the arguments.
"""
paramflags = []
argtypes = []
# collect all helpstring instances
# We should suppress docstr... | 0686af6b9adf193320a3bff57b5a1bb8c7b29c15 | 3,625,349 |
def _validate_rpc_ip(rpc_server_ip):
"""Validates given ip for use as rpc host bind address.
"""
if not is_valid_ipv4(rpc_server_ip):
raise NetworkControllerError(desc='Invalid rpc ip address.')
return rpc_server_ip | 24defd4633d13b1bed2d53ec9663e6abcc05b904 | 3,625,350 |
def normalize_data(df):
"""Normalizes a dataframe."""
scaler=MinMaxScaler()
df[FEATURE_NAMES] = scaler.fit_transform(df[FEATURE_NAMES])
return df | 1a718dc75d451269e0b5c83e5d10a0a1631b9728 | 3,625,351 |
def hex_to_root(hex_string: str) -> Root:
"""
Convert hex string to trie root.
Parameters
----------
hex_string :
The hexadecimal string to be converted to trie root.
Returns
-------
root : `Root`
Trie root obtained from the given hexadecimal string.
"""
return ... | d5685289a3474cc6af6c8436822c4b6cefa0b835 | 3,625,352 |
def redis_connection():
"""
Returns a redis connection from one of our pools.
"""
pool = ConnectionPoolManager.connection_pool(**CONNECTION_KWARGS)
return Redis(connection_pool=pool) | 08a1484b1406f5d5935a6caa057d0f537b645f02 | 3,625,353 |
def count_simple(a, alphabet_len):
"""Counts items in a. """
result = zeros(alphabet_len, Int)
for i in ravel(a):
result[i] += 1
return result | e6c0629175bd90d8942e05f8177e3ffbf1944699 | 3,625,354 |
def _select_manager(backend_name):
"""Select the proper LockManager based on the current backend used by Celery.
:raise NotImplementedError: If Celery is using an unsupported backend.
:param str backend_name: Class name of the current Celery backend. Usually value of
current_app.extensions['celery... | d12de5e954a4d0b0d64c39f515a5736fb341ad8d | 3,625,357 |
import warnings
def ivim_model_selector(gtab, fit_method='LM', **kwargs):
"""
Selector function to switch between the 2-stage Levenberg-Marquardt based
NLLS fitting method (also containing the linear fit): `LM` and the Variable
Projections based fitting method: `VarPro`.
Parameters
----------... | 58aaf65baed294b344a3eae0e42f8f049ca34d6a | 3,625,358 |
def temperature():
"""
Raspberry Pi temperature
"""
return render_template("temperature.html") | 6ccdf487f1760e812c83d75140e0b8653813f71d | 3,625,359 |
import math
def convert_size_bytes_to_human_readable_format(size_bytes):
"""
Converts a size in bytes to a human readable format.
:param size_bytes: The size in bytes
:return: Bytes converted to readable format
"""
if size_bytes == 0:
return "0B"
size_name = ("B", "KiB", "MiB", "G... | b14d345e5990e431997adeba09b5cee701f83fd0 | 3,625,360 |
def activate(client, name, file_=None):
"""Activate a model view.
Args:
client (obj):
creopyson Client.
name (str):
View name.
`file_` (str, optional):
Model name. Defaults is current active model.
Returns:
None
"""
data = {"name... | cd928a364261e9f73cecbafc010f8eff2c5a39ab | 3,625,361 |
def delete_table(userId, id):
"""
Deletes a table from the db. Only can be called via the saved_search.html
"""
try:
savedSearch = SavedSearch.objects(id=id).first()
tableName = savedSearch.name
doDelete = True
message = tableName+" deleted successfully!"
if saved... | bb13d1c40157e2457adb31c94a58bbe421771e48 | 3,625,362 |
def _get_heatmap(job_name, build_number, builds, group_field, count_skips, project=None):
"""Run the aggregation to get the Jenkins heatmap report"""
# Get the run IDs for the last 5 Jenkins builds
build_min = build_number - (builds - 1)
build_max = build_number + 1
build_range = [str(bnum) for bnum... | 7652ca6cb5e573a88c2eb8ca2949d71ebf8004e0 | 3,625,363 |
def control_4_5_ensure_route_tables_are_least_access(regions):
"""Summary
Returns:
TYPE: Description
"""
result = True
failReason = ""
offenders = []
offenders_links = []
control = "4.5"
description = "Ensure routing tables for VPC peering are least access"
scored = Fals... | aa1f4e57703877e33a85f7f412bd00be9761310e | 3,625,364 |
def kiv_pred(df: Kerneldict, lam: float, xi: float, stage: int) -> np.ndarray:
"""Kernel instrumental variable prediction."""
n = len(df["y1"])
m = len(df["y2"])
brac = make_psd(df["K_ZZ"]) + lam * np.eye(n)
W = np.linalg.solve(brac, df["K_XX"]).T @ df["K_Zz"]
brac2 = make_psd(W @ W.T) + m * xi * make_psd(... | 8ada371e3596631af4b2cfb0b2f7af35e7e75461 | 3,625,365 |
def _query_multi_armed_bandit_probabilities():
"""Get query results.
Queries above BANDIT_PROBABILITY_QUERY and yields results
from bigquery. This query is sorted by strategies implemented."""
client = big_query.Client()
return client.query(query=BANDIT_PROBABILITY_QUERY).rows | 181a38cd4602830c68ccd008d0ae857ea36ee86d | 3,625,366 |
from datetime import datetime
import logging
import json
def check_jobs():
"""Check if various jobs have been running.
The following URL parameters can be provided:
- names:
- Comma separated list of names of tasks to check.
- seconds (default 3600)
- How many seconds are allowed since last completio... | ffb6da52342eb28cfc811918fb62dd7dede5f4e6 | 3,625,367 |
def med(data, mw=24, sf=16, sigma=5.0):
"""
Median baseline correction
Algorith described in:
Friedrichs, M.S. JBNMR 1995 5 147-153.
Parameters:
* data Array of spectral data.
* mw Median Window size in pts.
* sf Smooth window size in pts.
* sigma Standard-deviation of Gaus... | 0c00f8740b61b5706f5be275e3a6cba9594cb1fa | 3,625,368 |
def raoult_liquido(fraccion_vapor, presion_vapor, presion):
"""Calcula la fraccion molar de liquido mediante la ec de Raoult"""
return fraccion_vapor * presion / presion_vapor | bd15f53ee74ef3dc1925ee3da7133a9c3f455333 | 3,625,369 |
def deletePlayers():
"""Remove all the player records from the database."""
dbcursor = connect()
dbcursor.execute("TRUNCATE players")
return 1 | 57fb88118faec5b7a4836f176c210786a57bd5bd | 3,625,370 |
def recursepath(path, reverse=False):
# type: (Text, bool) -> List[Text]
"""Get intermediate paths from the root to the given path.
Arguments:
path (str): A PyFilesystem path
reverse (bool): Reverses the order of the paths
(default `False`).
Returns:
list: A list of... | a00286a2933eac2a5e8115fe9bb9bfd6de4d0c64 | 3,625,371 |
def pack_items(arrays, key_encoding="utf-8"):
"""
Packs the specified items by computing the relevant file offsets
and return the list of ItemDescriptors and the overall size of the
file.
"""
num_items = len(arrays)
# We store the keys in sorted order in the key block.
sorted_keys = sort... | da01e3e8662fa925c94c642ecfb771e7d880ac10 | 3,625,372 |
def list_datasets():
"""Returns the list of available FiftyOne datasets.
Returns:
a list of :class:`Dataset` names
"""
# pylint: disable=no-member
return sorted(foo.DatasetDocument.objects.distinct("name")) | 727d397f2e2e6d62b7faa7e76b75f0b78ba71c62 | 3,625,373 |
def wayPointDistribution(rx, ry, ryaw, s):
"""
:param rx:
:param ry:
:param ryaw:
:param s:
:return: generate the efficients of the reference line
"""
x_list = []
y_list = []
theta_list = []
s_list = []
for i in range(len(rx)):
if 20 * i > (len(rx) - 1):
break
x_list.append(rx[20 * i])
y_list.app... | 0813888ae810a617804af8129baa38c8f388aed2 | 3,625,374 |
import bottleneck as bn
def rolling_median_(a, n, axis = 0, data = None, instate = None):
"""
Equivalent to rolling_median(a) but returns also the state.
For full documentation, look at rolling_median.__doc__
"""
state = instate or dict(vec = None)
return _data_state(['data','vec'],_rolli... | c3d3a3ad892bbe2fe39d7ad7823d10d8bed38fca | 3,625,375 |
def implemented_motifs():
"""
Returns
-------
List strings of all implemented motif definitions
"""
return ['Sheet', 'Gamma', 'Herringbone',
'Sandwich'] | 63564c7e1b3e7e5f8f6b93354a3e268a79e9c5de | 3,625,376 |
def left(direction):
"""rotates the direction counter-clockwise"""
return (direction + 3) % 4 | f8136385e5fec11bf26a97f77e336b04ce783571 | 3,625,377 |
def union(list1, list2):
"""Union of two lists, returns the elements that appear in one list OR the
other.
Args:
list1 (list): A list of elements.
list2 (list): A list of elements.
Returns:
result_list (list): A list with the union elements.
Examples:
>>> union([1,2,3... | 983e96ceb4f4eeb2b4b2d96362a0977be0cb2222 | 3,625,378 |
def render_analytics_code():
"""
Renders the new google analytics snippet.
"""
return {
'ANALYTICS_TRACKING_ID': getattr(settings, 'ANALYTICS_TRACKING_ID',
'UA-XXXXXXX-XX'),
'ANALYTICS_DOMAIN': getattr(settings, 'ANALYTICS_DOMAIN', 'auto')
} | e88e928ce43b91eef5fc3b85a8af54d6fd5b0224 | 3,625,379 |
import urlparse
def valid_proxy(proxy):
"""Return 1 if the proxy string looks like a valid url, for an
proxy URL else return 0."""
scheme, netloc, url, params, query, fragment = urlparse.urlparse(proxy)
if scheme != 'http' or params or query or fragment:
return 0
return 1 | f3e9bddd49eb5fa31260876343a15c2b7b5bf7af | 3,625,380 |
def oauth2_from_dict(oauth2_dictionary: dict):
"""
The function converts a dictionary of OAuth2 to a OAuth2 object.
:param oauth2_dict: A dictionary that contains the keys of a OAuth2.
:type oauth2_dict: dict
:rtype: ibmpairs.authentication.OAuth2
:raises Exception: if not a di... | 66d36c6dc2f6eaf6b87907854bdc8e9c59864749 | 3,625,381 |
def _initiate_pipeline_stop(
mlmd_handle: metadata.Metadata,
pipeline_uid: task_lib.PipelineUid) -> metadata_store_pb2.Execution:
"""Initiates a pipeline stop operation.
Upon success, MLMD is updated to signal that the pipeline given by
`pipeline_uid` must be stopped.
Args:
mlmd_handle: A handle t... | 87c857e10d95cd79cd22460f8ee3c613d8d1dc1f | 3,625,383 |
def slot_schedule_difference(old_schedule, new_schedule):
"""Compute the difference between two schedules from a slot perspective
Parameters
----------
old_schedule : list or tuple
of :py:class:`resources.ScheduledItem` objects
new_schedule : list or tuple
of :py:class:`resources.Sc... | fbc21d67e2738131246c62f1ccc7b539fef44c9c | 3,625,384 |
def drive_cancellation_seq(
drive_op_code, ramsey_qubit_names, operation_dict,
sweep_points, n_pulses=1, pihalf_spacing=None, prep_params=None,
cal_points=None, upload=True, sequence_name='drive_cancellation_seq'):
"""
Sweep pulse cancellation parameters and measure Ramsey on qubits the
... | 5140bb2a97f34d45bc29d164cee725907f756682 | 3,625,385 |
def generate_inputs(generate_calc_job_node, fixture_localhost, generate_structure, generate_kpoints_mesh):
"""Create the required inputs for the ``ProjwfcCalculation``."""
entry_point_name = 'quantumespresso.pw'
inputs = {'structure': generate_structure(), 'kpoints': generate_kpoints_mesh(4)}
parent_ca... | 25d15d6123a5ab1c5f26a050cfe1925cb185b127 | 3,625,386 |
import re
def list_all_links_in_page(source: str):
"""Return all the urls in 'src' and 'href' tags in the source.
Args:
source: a strings containing the source code of a webpage.
Returns:
A list of all the 'src' and 'href' links
in the source code of the webpage.
"""
retu... | f17f2ac2724fcfdd041e2ad001557a0565b51e00 | 3,625,387 |
def resp_delete_successfully(msg):
"""Response 202"""
response = jsonify({
'message': f'{msg} delete successfully.'
})
response.status_code = 202
return response | 449585ee86d16c41f4a0ee5f2cee9276ca39e8d4 | 3,625,388 |
import math
def embedding_column_v2(categorical_column,
dimension,
combiner='mean',
initializer=None,
max_sequence_length=0,
learning_rate_fn=None,
embedding_lookup_device=No... | aa776edad95892fd7e1f74810497e078dd561649 | 3,625,389 |
def synthesize_data():
"""
synthesize the (block, program) pairs
:return: train_shape, train_prog, val_shape, val_prog
"""
# == training data ==
data = []
label = []
n_samples = [5000,
30000, 5000, 5000, 5000, 10000,
5000, 5000, 5000, 5000, 30000,
... | 41a254326e116dcc9f0942ba984e549c0ed52540 | 3,625,390 |
from bs4 import BeautifulSoup
def parse_predict_data(html: str) -> list[tuple]:
"""Returns the following tuple: (week, (away_data, home_data))
"""
predict_meta = FTE_PREDICT_STATS
parsed = []
soup = BeautifulSoup(html, HTML_PARSER)
# build field processor based on predict metadata
field... | b1edfa0ced51fce0dad8b2182a375643eee3a0d0 | 3,625,391 |
def get_direction(source, destination):
"""Find the direction drone needs to move to get from src to dest."""
lat_diff = abs(source[0] - destination[0])
long_diff = abs(source[1] - destination[1])
if lat_diff > long_diff:
if source[0] > destination[0]:
return "S"
else:
... | 224a8df79cbafbcf1eed8df522ab7f58cc93598d | 3,625,392 |
def newAction(
parent,
text,
slot=None,
shortcut=None,
icon=None,
tip=None,
checkable=False,
enabled=True,
checked=False,
):
"""Create a new action and assign callbacks, shortcuts, etc."""
a = QtWidgets.QAction(text, parent)
if icon is ... | a58e20293bca2888360151cb9ef905c3c4a17f5e | 3,625,394 |
def _echelon_form(M, iszerofunc=_iszero, simplify=False, with_pivots=False,
dotprodsimp=None):
"""Returns a matrix row-equivalent to ``M`` that is in echelon form. Note
that echelon form of a matrix is *not* unique, however, properties like the
row space and the null space are preserved.
Parame... | c6e0f1afe21432c18ef4da705074f9c348cc4da5 | 3,625,395 |
def div23():
"""
Returns the divider 22222222222222222222222
:return: divider23
"""
return divider23 | 61dbccd02231227e60c5ac70787cb473c5c6ca45 | 3,625,397 |
from datetime import datetime
import pytz
def datetime_to_timestamp(dt):
"""Converts a `datetime.date` or `datetime.datetime` to milliseconds since
epoch.
Args:
dt: a `datetime.date` or `datetime.datetime`
Returns:
the number of milliseconds since epoch
"""
if type(dt) is dat... | 328b1aaa45477cc9f6502b8a8210f174b4ececc3 | 3,625,398 |
def get_specific_dummies(df, col_map=None, prefix=None, suffix=None, return_df=True):
""" Given a mapping of column_name: list of values, one hot the values
in the column and concat to dataframe. Optional arguments to add prefixes
and/or suffixes to created column names.
Example col_map: {'foo':['... | 98f2adcd49a59c4c9774e166019aedf9e59d9939 | 3,625,399 |
def create_controls(pagesize):
"""
Create an LDAP control with a page size of "pagesize".
"""
if LDAP24API:
return SimplePagedResultsControl(True, size=pagesize, cookie='')
else:
return SimplePagedResultsControl(ldap.LDAP_CONTROL_PAGE_OID, True,
... | 4875878b6e96fb3d06cf580f4a82f1104bf520e3 | 3,625,401 |
def threshold_measurement(state, instruction, shots):
"""
NOTE: This function calculates only by using torontonian.
"""
if not np.allclose(state.xpxp_mean_vector, np.zeros_like(state.xpxp_mean_vector)):
raise NotImplementedError(
"Threshold measurement for displaced states are not s... | 5f07f01ebb2883d6a36f4e27003d1c6341fea779 | 3,625,402 |
def white(N, sigma=1, prng=None):
""" Create white noise.
Parameters
---------
N : numeric
Length of 1d noise array to return
sigma : numeric
Standard deviation
prng : np.random.RandomState, None
A RandomState instance, or None
"""
prng = process_prng(pr... | 40178bb71786ed9da558f7dcd34090e033e9a202 | 3,625,403 |
from pathlib import Path
from typing import Tuple
from typing import List
import gzip
def get_sequence(
series: pd.Series, path_to_pdb: Path
) -> Tuple[str, str, int, int, List[int]]:
"""Gets a sequence of from PDB file, CATH fragment indexes and secondary structure labels.
Parameters
----------
... | 17b3132b0d1050154595bb746cfc1e3ddf505ddb | 3,625,404 |
def generate_without_options():
"""
Returns 1 to 6 Pokemon based on default generator values
"""
# Generator chooses how many Pokemon to generate
number_of_pokemon = randint(1,6)
try:
api_response = _send_api_request(num_pokemon=number_of_pokemon)
except:
return statement(re... | e8104227b0494b6cd4e9475b421542e6dbd86de7 | 3,625,406 |
import numpy
def fit_harmonic_decay(data, deltat=1.0, numcoef=DEFCOEF, axis=-1):
"""Fit harmonic functions with exponential decay.
Can be used to fit frequency-domain fluorescence image data with
photobleaching.
Parameters
----------
data : array_like
Experimental data (observed valu... | 07a3c2080ed58f6febc1271a335dc9fef5750887 | 3,625,407 |
import math
def lab_to_lch(lab):
"""Din99o Lab to Lch."""
l, a, b = lab
h = math.degrees(math.atan2(b, a))
c = math.sqrt(a ** 2 + b ** 2)
# Achromatic colors will often get extremely close, but not quite hit zero.
# Essentially, we want to discard noise through rounding and such.
if c <=... | 6c63eb19a7581f2bf41053cef99fc0dc23b79d6c | 3,625,408 |
def moments(data, n_neighbors=30, n_pcs=30, mode='connectivities', method='umap', metric='euclidean', use_rep=None,
recurse_neighbors=False, renormalize=False, copy=False):
"""Computes moments for velocity estimation.
Arguments
---------
data: :class:`~anndata.AnnData`
Annotated dat... | c6e2db61e2b12274039342454fc87849723d8ed8 | 3,625,409 |
def QuadRemeshAsync1(thisMesh, parameters, guideCurves, progress, cancelToken, multiple=False):
"""
Quad remesh this mesh asynchronously.
Args:
guideCurves (IEnumerable<Curve>): A curve array used to influence mesh face layout
The curves should touch the input mesh
Set Guide... | b59c11c8c42e2131828c22ff17eb26cbbf7c6b0c | 3,625,410 |
def are_close(col1, col2):
"""This function used to compare values of collections with numeric data
"""
if len(col1) != len(col2):
raise ValueError("Different size of input collections")
result = []
for x, y in zip(col1, col2):
result.append(abs(abs(x) - abs(y)) < 0.4)
r = T... | 72896f522a5fc7cb9f4f96e873c14797009877fe | 3,625,411 |
def compute_depression(input_dem, scale_factor=1, curvature_percentile=75, return_polygon=True, alpha=0.5):
"""
Compute depressions and return a new image with largest depressions filled in.
Parameters
----------
input_dem : np.array, rd.rdarray
2d array of elevation DNs, a DEM
... | 3341b7c88ad82a0437a2a264ac91f00bf24de471 | 3,625,412 |
from typing import Dict
from typing import Any
def _deregister_ec2_instance(
public_address: str, require_no_running_jobs: bool, region_name: str
) -> bool:
"""
Deregisters an EC2 instance. If require_no_running_jobs is true, then only
deregisters if there are no currently running jobs on the instance... | c43f15b3ba3bedfb478889caaf91eeb1fee7df41 | 3,625,413 |
def mse(pred, labs):
"""
Calculates MSE
:param pred: sequence of Strings / predicted score values as strings
:param labs: sequence of Strings / true score values as strings
:return: (Int, Int) / MSE of valid samples AND number of invalid samples
"""
idx = np.where(np.array([isfloat(x) for x ... | 69b28cfadde29b9d80ec07d41a82521e04e048bb | 3,625,415 |
def described_field_type(singular_type_field):
"""
Human readable equivalent of a singular avro type - e.g. long -> number.
"""
if isinstance(singular_type_field, dict):
if "logicalType" in singular_type_field:
return singular_type_field["logicalType"]
else:
if si... | 11514dec5fe2ee6b501a5c03d7321ed1f6a861af | 3,625,416 |
def package_releases(name, show_hidden=True):
"""return a list of package releases"""
return pypi.package_releases(name, show_hidden) | e820369935e56b3b0074257cedeaf633fd08512c | 3,625,418 |
def _randomize_network(network, keep):
"""
This function returns a network with the same nodes and edge number as the input network.
However, each edge is placed randomly.
:param network: NetworkX object
:param keep: List of conserved edges
:return: Randomized network
"""
null = nx.Grap... | eb0881625bdd73f0a94018feb0facb76c868ffb9 | 3,625,419 |
import six
def get_docstring(value, module_name=None):
"""
Return the docstring for the given value; or C{None} if it
does not have a docstring.
@rtype: C{unicode}
"""
docstring = getattr(value, '__doc__', None)
if docstring is None:
return None
elif isinstance(docstring, six.t... | e68e997e843d4110ec608ad6eadac46fdef74eda | 3,625,420 |
import requests
def _classswitch_file(url, header, params):
"""
文件存储类型转换请求
:param url:string类型，文件存储类型转换的url
:param header: dict类型，http 请求header，键值对类型分别为string，比如{'User-Agent': 'Google Chrome'}
:param params: dict类型，http 请求的查询参数，键值对类型分别为string类型
:return: ret: return message, None if response s... | c61af20073932c67a5d4607325eee780da224ccb | 3,625,422 |
def cofa(session=None):
"""
Return location class of current COFA.
Parameters
----------
session: db session to use
"""
h = Handling(session)
located = h.cofa()
h.close()
return located | 363fb61bee4cc0e5c9b95a2c2623050f693e2b0e | 3,625,423 |
def identity(*args, **kwargs):
"""
An identity function used as a default task to test the timing of.
"""
return args, kwargs | 472808f6b5260569538f26513f24ffcb1bd88c4d | 3,625,424 |
def _with_largest_possible_masks(oneof):
"""Add masks to enable all possible ops / filters in the search space."""
if oneof.tag == basic_specs.OP_TAG:
n = len(oneof.choices)
mask = tf.constant([1 / n] * n, dtype=tf.float32)
elif oneof.tag == basic_specs.FILTERS_TAG:
largest_index = None
for i, cho... | c7a9bfb4bb875abe3f6232873f64ad70334c71f8 | 3,625,425 |
def list_merger_list0(*lists):
"""Picks leading list, discards everything else"""
return lists[0] | c571adb593de991f633a28b086e61fa7888cbc7e | 3,625,426 |
def serialize():
"""
Get dict with internal data
"""
with _exception_log_lock:
return {'exceptions': _exceptions.copy()} | aacebcf8d18e7f1654ed2e16ed846dfe35668532 | 3,625,427 |
def cmp(a,b):
"""3-way comparison like the cmp operator in perl"""
if a is None:
a = ''
if b is None:
b = ''
return (a > b) - (a < b) | 97c5a33e9161196119abbc323841be0b1cfdda14 | 3,625,428 |
def _pixel_to_map(coordinates, geotransform):
"""Apply a geographical transformation to return map coordinates from
pixel coordinates.
Parameters
----------
coordinates : :class:`numpy:numpy.ndarray`
2d array of pixel coordinates
geotransform : :class:`numpy:numpy.ndarray`
geogr... | 4aee896d9185625b838c12215835e513996f15b7 | 3,625,429 |
def median_filter(ts: pd.Series, stats: pd.DataFrame = None,
second_pass=False):
"""Apply rolling median filter to time series"""
_ts = ts.dropna() # Make sure there are no empty values
filtered = _ts.copy()
# Assing rolling median from 2nd to 2nd last index
filtered.iloc[1:-1] ... | d9b21f26eb47584aea0376ab0f4a2ca3d055432d | 3,625,430 |
def calculate_pairwise_correlations(df_variable: pd.DataFrame) -> dict:
"""For each pair of modalities, calculate correlations, and put them together into a column"""
modalities = list(df_variable.columns.values)
df_dict = {}
modality_iterator = itt.combinations(modalit... | 9aef93cf3ccf040f7c4a0ee804a171f38ac7646c | 3,625,431 |
from datetime import datetime
def event_context_vars(env_deployment):
"""Return context variables for zaza-events configuration params.
Note that it is cached because env_deployment is immutable, and the date
should only be evaluated the first time.
The "bundle" var is derived from the first model i... | b618e00cec98e93c3ec44df400a1c5e022063c27 | 3,625,432 |
def update_model(model, player, winner, board_hist, move_hist, learnig_rate):
"""
Updates 2 layer policy network weights using gradient descent (policy gradients) according to the played game data.
Parameters
----------
model: dict {"W1": [numpy Hx9 array], "W2": [numpy 9xH array]}
Policy n... | c7dd57005fc8892be2d3682b562d8097277758a6 | 3,625,434 |
def init(base_url, username=None, password=None, verify=True):
"""Initialize ubersmith API module with HTTP request handler."""
handler = RequestHandler(base_url, username, password, verify)
set_default_request_handler(handler)
return handler | 07b0ab1f076b0ae79dc6f4eaba87078d9f8c700e | 3,625,435 |
def view_mol(option, maps=None, out_put=None, target_id=None, extra=None):
"""Function to render the 3D coordinates of a molecule
Takes a PDB code as input
Returns an SD block"""
my_mols = Molecule.objects.filter(prot_id__code=option)
new_mol = ""
for mol in my_mols:
new_mol += (str(mol.... | e42b583e63f3ac2ad6cb7d241754491604b66455 | 3,625,436 |
def left_fit_width(s, width, fill=' '):
"""Make a string fixed width by padding or truncating.
Note: fill can't be full width character.
"""
s = trim_width(s, width)
s += fill * (width - str_width(s))
return s | 11d285b6065ac1f95d9a9f9f31bd55849c53f8d6 | 3,625,437 |
def create_item_selection_window():
"""
This function contains all the logic of the item selection window and will run the window by it's own.
:return: None
"""
item_selection_window = sg.Window("Item selection", generate_item_selection_layout(), finalize=True,
... | d33eb2858786dc38d90b22147ec1145236c206c3 | 3,625,438 |
def check(consumer_households_in_siumulation, prosumer_households_in_siumulation):
"""[summary]
Checks if a new user needs to be added to the simulation or if a user is removed
Args:
consumer_households_in_siumulation ([list]): [List of current consumers in the simulation]
prosumer_hous... | 00d84b25ce1533406b78aa455c8605269978983b | 3,625,439 |
def create_model(inner_settings:InnerModelSettings,outer_settings:OuterModelSettings) -> OuterModel:
"""
function creates an OuterModel with provided settings.
Args:
inner_settings: an instannce of InnerModelSettings
outer_settings: an instannce of OuterModelSettings
"""
model = Out... | 28e0f47b2130ecb4a5e08886c08e9589af04a932 | 3,625,440 |
def create_logdir(method, weight, label, rd):
""" Directory to save training logs, weights, biases, etc."""
return "bigan/train_logs/mnist/{}/{}/{}/{}".format(weight, method, label, rd) | 4b4edcc9c0c36720e76013a6fb0faf1b49472bc0 | 3,625,441 |
def ontocreate():
"""View function for the standard vocabulary creator module.
Returns:
str: HTML page for the standard creator module.
"""
form = OntologyDescript()
form2 = InvertLangButton()
return render_template("ontocreate.html", form=form, form2=form2) | 83197d6062ed8d78882980542949f43ba8df3982 | 3,625,442 |
def log_spherical_gaussian(theta, variance):
"""Unnormalized log density of a spherical Gaussian"""
return -np.sum(theta**2) / (2 * variance) | d113c4014b72a41c2f0cb252a2a6b6e2ae5f3e0b | 3,625,443 |
def apply_target(rule, substitutions):
"""Return target string with non-terminals replaced with substitutions."""
if rule.arity != len(substitutions):
raise ValueError
output = []
for token in rule.target:
if token == NT_1:
output.append(substitutions[0])
elif token == NT_2:
output.appen... | 595333291d2fcce159c927f09666de7a1f7be3bf | 3,625,444 |
import io
import sqlite3
def adapt_array(arr):
"""
"""
# https://stackoverflow.com/a/18622264
# http://stackoverflow.com/a/31312102/190597 (SoulNibbler)
out = io.BytesIO()
np.save(out, arr)
out.seek(0)
return sqlite3.Binary(out.read()) | 74ca1db4ed25dd60f6ec91ade3c150be313fd1c6 | 3,625,445 |
from typing import List
def usage_stats_invalid_messages_exist(messages: List[str]) -> bool:
"""
Since the usage stats functionality does not raise exceptions but merely logs them, we need to check the logs for errors.
"""
return any(
[
UsageStatsExceptionPrefix.INVALID_MESSAGE.va... | 3de0e6bc0fa82c57b07209e8ccda5ade3465f668 | 3,625,446 |
def spike_train_from_string(s, edges, sep=' ', is_sorted=False):
""" Converts a string of times into a :class:`.SpikeTrain`.
:param s: the string with (ordered) spike times.
:param edges: interval defining the edges of the spike train.
Given as a pair of floats (T0, T1) or a single float... | 1ecfaa7b8ac7320eef95e8b4db16775669adef9a | 3,625,447 |
def batch_effective_sample_size(x, mu, var, logger=None):
"""
Calculate the effective sample size of sequence generated by MCMC.
:param x:
:param mu: mean of the variable
:param var: variance of the variable
:param logger: log
:return: effective sample size of the sequence
We calculate ... | 808b4bb4f5294c58d6c3eee42af772d9818c91f9 | 3,625,449 |
def copy_ecf_ord_players_post_2006_rules(widget, logwidget=None):
"""Import a new ECF downloadable OGD rating list csv file.
widget - the manager object for the ecf data import tab.
Downloads have been produced in this format since mid-2020.
These are available for all lists since 1994 according to
... | af72186f0cad73e0d37dcd996991d901912de1c7 | 3,625,450 |
from io import StringIO
import io
def _str_io(*args, **kwargs):
"""Helper for PY2/Py3 StringIO"""
if StringIO:
return StringIO.StringIO(*args, **kwargs)
return io.StringIO(*args, **kwargs) | b9013fae9ca9231dfb74064ee293727734c38697 | 3,625,451 |
import functools
def eval_mode(f):
"""a decorator designed for nn.Module methods which wraps the function call in the eval context.
Note:
you can use this decorator for any function that takes a model as first parameter.
but it's reccommended to use on nn.Module methods.
"""
@functoo... | 740936b7118dda0e4a28c73914344de50d73e9cb | 3,625,452 |
from datetime import datetime
def read_logs(start_time=None):
""" Read all log messages after a certain time from the latest text file log
Parameters
----------
start_time : datetime
The earliest timestamp from which to read logs
Returns
-------
string, datetime
The relev... | 8a3a3feeb7c98fe5938e81e2fd5afa06bbd7b02a | 3,625,453 |
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