content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def atomic_coordinates_as_json(pk):
"""Get atomic coordinates from database."""
subset = models.Subset.objects.get(pk=pk)
vectors = models.NumericalValue.objects.filter(
datapoint__subset=subset).filter(
datapoint__symbols__isnull=True).order_by(
'datapoint_id', 'counter'... | 515854e789a15e845b0dbcd754e17bedfc0bcf69 | 11,000 |
def additional_bases():
""""Manually added bases that cannot be retrieved from the REST API"""
return [
{
"facility_name": "Koltyr Northern Warpgate",
"facility_id": 400014,
"facility_type_id": 7,
"facility_type": "Warpgate"
},
{
... | e2a5ad97ca1b424466f5ebe340466eaf9f627e7e | 11,001 |
def get_all_label_values(dataset_info):
"""Retrieves possible values for modeled labels from a `Seq2LabelDatasetInfo`.
Args:
dataset_info: a `Seq2LabelDatasetInfo` message.
Returns:
A dictionary mapping each label name to a tuple of its permissible values.
"""
return {
label_info.name: tuple(l... | 929db286b3f7ee8917618e9f46feabdff630d3b2 | 11,002 |
def load_input(file: str) -> ArrayLike:
"""Load the puzzle input and duplicate 5 times in each direction,
adding 1 to the array for each copy.
"""
input = puzzle_1.load_input(file)
input_1x5 = np.copy(input)
for _ in range(4):
input = np.clip(np.mod(input + 1, 10), a_min=1, a_max=Non... | 91b2cd7854a793ebbbfee2400eddb22304fc18bd | 11,003 |
def _get_xvals(end, dx):
"""Returns a integer numpy array of x-values incrementing by "dx"
and ending with "end".
Args:
end (int)
dx (int)
"""
arange = np.arange(0, end-1+dx, dx, dtype=int)
xvals = arange[1:]
return xvals | 24a4d7b7c470abb881700a1775008d16c35c1fc3 | 11,004 |
import torch
def top_filtering(logits, top_k=0, top_p=0.0, filter_value=-float('Inf')):
""" Filter a distribution of logits using top-k, top-p (nucleus) and/or threshold filtering
Args:
logits: logits distribution shape (vocabulary size)
top_k: <=0: no filtering, >0: keep only top ... | 5cbbd9959a80e72364f098fe031e5e3c78485826 | 11,005 |
def get_reference_shift( self, seqID ):
"""Get a ``reference_shift`` attached to a particular ``seqID``.
If none was provided, it will return **1** as default.
:param str seqID: |seqID_param|.
:type shift: Union[:class:`int`, :class:`list`]
:raises:
:TypeError: |indf_error|.
.. rubr... | 4a8f9fe683c9cf0085754ca2ebb9132bbae427ea | 11,006 |
import os
import sys
def which(cmd, mode=os.F_OK | os.X_OK, path=None):
"""Given a command, mode, and a PATH string, return the path which
conforms to the given mode on the PATH, or None if there is no such
file.
`mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result
of os.environ.get... | 31fff48dd7984de5008bedf8a1da9687111fcfbf | 11,007 |
def load_and_resolve_feature_metadata(eval_saved_model_path: Text,
graph: tf.Graph):
"""Get feature data (feature columns, feature) from EvalSavedModel metadata.
Like load_feature_metadata, but additionally resolves the Tensors in the given
graph.
Args:
eval_saved_mod... | 3377d66c962ccccab7b62abf563f88032a8a7b14 | 11,008 |
def greater_than_or_eq(quant1, quant2):
"""Binary function to call the operator"""
return quant1 >= quant2 | 920c28da125b567bc32a149aec6aaade3645ef87 | 11,009 |
def pr_define_role(pe_id,
role=None,
role_type=None,
entity_type=None,
sub_type=None):
"""
Back-end method to define a new affiliates-role for a person entity
@param pe_id: the person entity ID
@param role: the role... | 3f09ac9eca47347b51069a20b7b08b2192e2d452 | 11,010 |
def inherently_superior(df):
"""
Find rows in a dataframe with all values 'inherently superior',
meaning that all values for certain metrics are as high or higher
then for all other rows.
Parameters
----------
df : DataFrame
Pandas dataframe containing the columns to be compared... | 02dd6db624efd4f1daa4c0ef4f126c6c60c0376e | 11,011 |
def LineColourArray():
"""Line colour options array"""
Colour = [
'Black',
'dimgrey',
'darkgrey',
'silver',
'lightgrey',
'maroon',
'darkred',
'firebrick',
'red',
'orangered',
'darkorange',
'orange',
... | 94f91d17c6e539983ab38ca7fdadd211e6268bfb | 11,012 |
import errno
def os_to_maestral_error(exc, dbx_path=None, local_path=None):
"""
Gets the OSError and tries to add a reasonably informative error message.
.. note::
The following exception types should not typically be raised during syncing:
InterruptedError: Python will automatically ret... | 7a99ce147e2fbe0a3cc94535ee1d84c9337b3791 | 11,013 |
from typing import Any
def parse_ccu_sys_var(data: dict[str, Any]) -> tuple[str, Any]:
"""Helper to parse type of system variables of CCU."""
# pylint: disable=no-else-return
if data[ATTR_TYPE] == ATTR_HM_LOGIC:
return data[ATTR_NAME], data[ATTR_VALUE] == "true"
if data[ATTR_TYPE] == ATTR_HM_A... | 8b77dbbaa93739457a2e92aad79ac5b6bd3a6af0 | 11,014 |
def one_time_log_fixture(request, workspace) -> Single_Use_Log:
"""
Pytest Fixture for setting up a single use log file
At test conclusion, runs the cleanup to delete the single use text file
:return: Single_Use_Log class
"""
log_class = Single_Use_Log(workspace)
request.addfinalizer(log_cl... | 73332892ece76ee90c15d84294b70d935e8a2f4c | 11,015 |
import json
def details(request, path):
"""
Returns detailed information on the entity at path.
:param path: Path to the entity (namespaceName/.../.../.../)
:return: JSON Struct: {property1: value, property2: value, ...}
"""
item = CACHE.get(ENTITIES_DETAIL_CACHE_KEY)
# ENTITIES_DETAIL : {"namespaceNam... | b460dc76f18f35b48509a1b2d8daa104bc89fbb5 | 11,016 |
def ca_get_container_capability_set(slot, h_container):
"""
Get the container capabilities of the given slot.
:param int slot: target slot number
:param int h_container: target container handle
:return: result code, {id: val} dict of capabilities (None if command failed)
"""
slot_id = CK_SL... | cf97db8f201d0c5fce12902b92abdc3a819ac394 | 11,017 |
def load_pyfunc(model_file):
"""
Loads a Keras model as a PyFunc from the passed-in persisted Keras model file.
:param model_file: Path to Keras model file.
:return: PyFunc model.
"""
return _KerasModelWrapper(_load_model(model_file)) | eb21f47a55f35bf3707ba7c5cb56e72948d24866 | 11,018 |
def business_days(start, stop):
"""
Return business days between two datetimes (inclusive).
"""
return dt_business_days(start.date(), stop.date()) | 1fa8c38e6cceca448bc988cd0c1eb24a27508a78 | 11,019 |
def empty_nzb_document():
""" Creates xmldoc XML document for a NZB file. """
# http://stackoverflow.com/questions/1980380/how-to-render-a-doctype-with-pythons-xml-dom-minidom
imp = minidom.getDOMImplementation()
dt = imp.createDocumentType("nzb", "-//newzBin//DTD NZB 1.1//EN",
"http://... | 7cd8aa73f201b4f432aa6adaed18d133ec08fa48 | 11,020 |
def get_output_directory(create_statistics=None, undersample=None, oversample=None):
"""
Determines the output directory given the balance of the dataset as well as columns.
Parameters
----------
create_statistics: bool
Whether the std, min and max columns have been created
undersample: ... | c10859e1eba4afb61d967e56be8a8206f5202618 | 11,021 |
def removePrefixes(word, prefixes):
"""
Attempts to remove the given prefixes from the given word.
Args:
word (string): Word to remove prefixes from.
prefixes (collections.Iterable or string): Prefixes to remove from given word.
Returns:
(string): Word with prefixes removed.
... | 6932e5605b11eee004a350c7f9be831d8bb7ca9d | 11,022 |
def isSol(res):
"""
Check if the string is of the type ai bj ck
"""
if not res or res[0] != 'a' or res[-1] != 'c':
return False
l = 0
r = len(res)-1
while res[l] == "a":
l+=1
while res[r] == "c":
r-=1
if r-l+1 <= 0:
return False
... | 14030e52a588dc13029602e81a5f2068707bca17 | 11,023 |
import pandas
def _h1_to_dataframe(h1: Histogram1D) -> pandas.DataFrame:
"""Convert histogram to pandas DataFrame."""
return pandas.DataFrame(
{"frequency": h1.frequencies, "error": h1.errors},
index=binning_to_index(h1.binning, name=h1.name),
) | 28aa8cc36abd21a17e0a30f4bde2bb996753864b | 11,024 |
def wgt_area_sum(data, lat_wgt, lon_wgt):
"""wgt_area_sum() performas weighted area addition over a geographical area.
data: data of which last 2 dimensions are lat and lon. Strictly needs to be a masked array
lat_wgt: weights over latitude of area (usually cos(lat * pi/180))
lon_wgt: weights over long... | 725f7f199e634cf56afb846ebff2a0917a92c685 | 11,025 |
import os
def get_files_from_path(path, recurse=False, full_path=True):
"""
Get Files_Path From Input Path
:param full_path: Full path flag
:param path: Input Path
:param recurse: Whether Recursive
:return: List of Files_Path
"""
files_path_list = []
if not os.path.exists(path):
... | 156088cd175a24bdb0bdd04c00fa6229470aab1f | 11,026 |
def load(filename):
"""Load the labels and scores for Hits at K evaluation.
Loads labels and model predictions from files of the format:
Query \t Example \t Label \t Score
:param filename: Filename to load.
:return: list_of_list_of_labels, list_of_list_of_scores
"""
result_labels = []
re... | 8d9570d794ebf09eb393342f926a5536dd0c1a75 | 11,027 |
def expanding_sum(a, axis = 0, data = None, state = None):
"""
equivalent to pandas a.expanding().sum().
- works with np.arrays
- handles nan without forward filling.
- supports state parameters
:Parameters:
------------
a : array, pd.Series, pd.DataFrame or list/dict of these
... | ec3fb41784f7ce5ef268ec8e7d8fe8e65f222157 | 11,028 |
def accuracy(output, target, top_k=(1,)):
"""Calculate classification accuracy between output and target.
:param output: output of classification network
:type output: pytorch tensor
:param target: ground truth from dataset
:type target: pytorch tensor
:param top_k: top k of metric, k is an int... | 68b7c48e5bd832a637e7a06353c48ffa09b449cd | 11,029 |
from typing import Dict
from typing import Any
import os
import json
def read_configuration_from_file(path: str) -> Dict[str, Any]:
"""
Read the JSON file and return a dict.
:param path: path on file system
:return: raw, unchanged dict
"""
if os.path.isfile(path):
with open(path) as js... | 57a8ea69507d4941b00e9ec2849084536eb7d44f | 11,030 |
import typing
import logging
def logwrap(
func: typing.Optional[typing.Callable] = None,
*,
log: logging.Logger = _log_wrap_shared.logger,
log_level: int = logging.DEBUG,
exc_level: int = logging.ERROR,
max_indent: int = 20,
spec: typing.Optional[typing.Callable] = None,
blacklisted_na... | 4c48dafc6c4f062fd1d165fd30bcc99209eabed3 | 11,031 |
def sum_digits(number):
"""
Write a function named sum_digits which takes a number as input and
returns the sum of the absolute value of each of the number's decimal digits.
"""
return sum(int(n) for n in str(number) if n.isdigit()) | b6d8083a78d67a268316716174723f47d84b2287 | 11,032 |
import numpy
def label(input, structure=None, output=None):
"""Labels features in an array.
Args:
input (cupy.ndarray): The input array.
structure (array_like or None): A structuring element that defines
feature connections. ```structure``` must be centersymmetric. If
... | fe3e4b7ee30f7dc1ae0541133f7db3d02c7d3157 | 11,033 |
import functools
def get_experiment_fn(nnObj,data_dir, num_gpus,variable_strategy,use_distortion_for_training=True):
"""Returns an Experiment function.
Experiments perform training on several workers in parallel,
in other words experiments know how to invoke train and eval in a sensible
fashion for distribut... | 07ddb4ebac493826127464f76fd79ea17e7bf474 | 11,034 |
def calc_psnr(tar_img, ref_img):
""" Compute the peak signal to noise ratio (PSNR) for an image.
Parameters
----------
tar_img : sitk
Test image.
ref_img : sitk
Ground-truth image.
Returns
-------
psnr : float
The PSNR metric.
References
----------
..... | 61097170fb439b85583cd8aac8002c70d02c094b | 11,035 |
import networkx as nx
import os
def celegans(path):
"""Load the neural network of the worm C. Elegans [@watts1998collective].
The neural network consists of around 300 neurons. Each connection
between neurons is associated with a weight (positive integer)
capturing the strength of the connection.
Args:
... | fc7f63af1b70c58fab7655d33f6d9630d4bd003e | 11,036 |
from typing import Callable
from typing import Dict
from typing import Any
import functools
def glacier_wrap(
f: Callable[..., None],
enum_map: Dict[str, Dict[str, Any]],
) -> Callable[..., None]:
"""
Return the new function which is click-compatible
(has no enum signature arguments) from the arbi... | 01f3a90179bb0dba29ffb0b2fa9d91be15e0ee7e | 11,037 |
def _cluster_spec_to_device_list(cluster_spec, num_gpus_per_worker):
"""Returns a device list given a cluster spec."""
cluster_spec = multi_worker_util.normalize_cluster_spec(cluster_spec)
devices = []
for task_type in ("chief", "worker"):
for task_id in range(len(cluster_spec.as_dict().get(task_type, [])))... | 3032a28f80dbed1fd870e4fc2ea06d724fc529ce | 11,038 |
def group_by_time(df, col, by='day', fun='max', args=(), kwargs={}, index='categories'):
""" See <https://pandas.pydata.org/pandas-docs/stable/api.html#groupby>_ for the set of `fun` parameters
available. Examples are: 'count', 'max', 'min', 'median', etc
.. Tip:: Since Access inherits from Tim... | 6695d285b52757ee7dfd32ad5943aa433504322f | 11,039 |
def fetch(url, params=None, keepalive=False, requireValidCert=False,
debug=False):
"""
Fetches the desired @url using an HTTP GET request and appending and
@params provided in a dictionary.
If @keepalive is False, a fresh connection will be made for this request.
If @requireValidCert is True, then an exceptio... | 8edfa089e9ae40d32f4843e6c684b3a06783150a | 11,040 |
def param_rischDE(fa, fd, G, DE):
"""
Solve a Parametric Risch Differential Equation: Dy + f*y == Sum(ci*Gi, (i, 1, m)).
Given a derivation D in k(t), f in k(t), and G
= [G1, ..., Gm] in k(t)^m, return h = [h1, ..., hr] in k(t)^r and
a matrix A with m + r columns and entries in Const(k) such that
... | afb910a9590195fa637be9c64382419c1c79a885 | 11,041 |
from sys import path
import yaml
def main(df: pyam.IamDataFrame) -> pyam.IamDataFrame:
"""Main function for validation and processing (for the ARIADNE-intern instance)"""
# load list of allowed scenario names
with open(path / "scenarios.yml", "r") as stream:
scenario_list = yaml.load(stream, Load... | 8872d698e0e00baedfe24784b2db6b206ff32e04 | 11,042 |
import torch
def huber_loss(x, delta=1.):
""" Standard Huber loss of parameter delta
https://en.wikipedia.org/wiki/Huber_loss
returns 0.5 * x^2 if |a| <= \delta
\delta * (|a| - 0.5 * \delta) o.w.
"""
if torch.abs(x) <= delta:
return 0.5 * (x ** 2)
else:
return del... | b3493eb9d4e38fa36f92db80dc52a47c32caf3c9 | 11,043 |
def licenses_mapper(license, licenses, package): # NOQA
"""
Update package licensing and return package based on the `license` and
`licenses` values found in a package.
Licensing data structure has evolved over time and is a tad messy.
https://docs.npmjs.com/files/package.json#license
license(... | 5568c323b342cc09d966ddef3455381abdca1ccc | 11,044 |
def send_command(target, data):
"""sends a nudge api command"""
url = urljoin(settings.NUDGE_REMOTE_ADDRESS, target)
req = urllib2.Request(url, urllib.urlencode(data))
try:
return urllib2.urlopen(req)
except urllib2.HTTPError, e:
raise CommandException(
'An exception occu... | fc6967f84568b755db7f132f5fc511ef9687369f | 11,045 |
def logistic_log_partial_ij(x_i, y_i, beta, j):
"""i is index of point and j is index of derivative"""
return (y_i - logistic(dot(x_i, beta))) * x_i[j] | a24f704bc3178c6f2d8b37ad075f1beea3666964 | 11,046 |
def expected_win(theirs, mine):
"""Compute the expected win rate of my strategy given theirs"""
assert abs(theirs.r + theirs.p + theirs.s - 1) < 0.001
assert abs(mine.r + mine.p + mine.s - 1) < 0.001
wins = theirs.r * mine.p + theirs.p * mine.s + theirs.s * mine.r
losses = theirs.r * mine.s + theirs... | 92de2010287e0c027cb18c3dd01d95353e4653c4 | 11,047 |
def get_first_where(data, compare):
"""
Gets first dictionary in list that fit to compare-dictionary.
:param data: List with dictionarys
:param compare: Dictionary with keys for comparison {'key';'expected value'}
:return: list with dictionarys that fit to compare
"""
l = get_all_where(data, compare)
i... | fc961d7154aa265efd101a658f668ad2025c121f | 11,048 |
import numpy
def parse_megam_weights(s, features_count, explicit=True):
"""
Given the stdout output generated by ``megam`` when training a
model, return a ``numpy`` array containing the corresponding weight
vector. This function does not currently handle bias features.
"""
if numpy is None:
... | db172935fe7af892b420d515391565ccc2b44c55 | 11,049 |
from typing import Counter
def project_statistics(contributions):
"""Returns a dictionary containing statistics about all projects."""
projects = {}
for contribution in contributions:
# Don't count unreviewed contributions
if contribution["status"] == "unreviewed":
continue
... | 91c27b504fc974b26f4e76b8a3f78e3665a21efa | 11,050 |
def exportSDFVisual(visualobj, linkobj, visualdata, indentation, modelname):
"""Simple wrapper for visual data of links.
The visual object is required to determine the position (pose) of the
object.
If relative poses are used the data found in visualdata (key pose) is used.
Otherwise the pose of the... | f556a1eb1cef42adfde28c481a3443f149219518 | 11,051 |
import resource
def register_module():
"""Callback for module registration. Sets up URL routes."""
global custom_module # pylint: disable=global-statement
permissions = [
roles.Permission(EDIT_STUDENT_GROUPS_PERMISSION,
messages.EDIT_STUDENT_GROUPS_PERMISSION_DESCRIPTIO... | 82e8d57c2b0f73ae21b460da61ce047b4a25ebe3 | 11,052 |
from sys import version_info
def build_texttable(events):
"""
value['date'], value["target"], value['module_name'], value['scan_unique_id'],
value['options'], value['event']
build a text table with generated event related to the scan
:param events: ... | 477c40ce240aae8848d960c6c3bba1e52a4c6b67 | 11,053 |
def for_all_regions(get_client_func, catalog_entry, action_func, parsed_args):
"""
Run the provided function on all the available regions.
Available regions are determined based on the user service catalog entries.
"""
result = []
cache_key = 'todo'
cache_item = CACHE.get(cache_key, None... | 9b1dfba7939aada8ca3c4c894d2ebbde08e757c6 | 11,054 |
import scipy
def KL_distance(image1, image2):
"""
Given two images, calculate the KL divergence between the two
2d array is not supported, so we have to flatten the array and compare each pixel in the image1 to the corresponding pixel in the image2.
"""
return scipy.stats.entropy(image1.ravel(), ... | 6419c2f6456365e027fc7eff6f4b171e5eb4fc5f | 11,055 |
def stop_all_bots():
"""
This function address RestAPI call to stop polling for all bots which
have ever started polling.
:return:
"""
bots_stopped = procedures.stop_all() # Stop all bots.
botapi_logger.info('Successfully stopped {count} bots for polling in '
's... | 7e0bdaa0ae631e631cfbc56966311e59fc510d52 | 11,056 |
def load_word_embedding_dict(embedding, embedding_path, normalize_digits=True):
"""
load word embeddings from file
:param embedding:
:param embedding_path:
:return: embedding dict, embedding dimention, caseless
"""
print "loading embedding: %s from %s" % (embedding, embedding_path)
if em... | 98cda8061aa49c708bc6986a6ab036e8941967f6 | 11,057 |
import sys
def fibonacci(n: int) -> int:
"""Returns nth fib number, fib_0 = 0, fib_1 = 1, ..."""
print(sys.platform)
return nfibonacci(n + 1)[-1] | 4f6b0c61709ad76e0600c395495b5b94c03c15ae | 11,058 |
def random_exponential(shape=(40,60), a0=100, dtype=float) :
"""Returns numpy array of requested shape and type filled with exponential distribution for width a0.
"""
a = a0*np.random.standard_exponential(size=shape)
return a.astype(dtype) | 29d3e438145d4495191868c956942b9626b76918 | 11,059 |
import json
def get_mpi_components_from_files(fileList, threads=False):
"""
Given a list of files to read input data from, gets a percentage of time
spent in MPI, and a breakdown of that time in MPI
"""
percentDict = dict()
timeDict = dict()
for filename in fileList:
filename ... | 34549198676b823cf9e02ec927cb1e5fc30de2b8 | 11,060 |
import urllib
def get_character_url(name):
"""Gets a character's tibia.com URL"""
return url_character + urllib.parse.quote(name.encode('iso-8859-1')) | 62dc27528b7b9b303367551b8cba0a02204d0eb6 | 11,061 |
def parse_input(lines):
"""Parse the input document, which contains validity rules for the various
ticket fields, a representation of my ticket, and representations of a
number of other observed tickets.
Return a tuple of (rules, ticket, nearby_tickets)
"""
section = parse_sections(lines)
ru... | cccf2a9b47768428b2004caab1b3cab15a369a68 | 11,062 |
from dateutil import tz
def _cnv_prioritize(data):
"""Perform confidence interval based prioritization for CNVs.
"""
supported = {"cnvkit": {"inputs": ["call_file", "segmetrics"], "fn": _cnvkit_prioritize}}
pcall = None
priority_files = None
for call in data.get("sv", []):
if call["var... | a35c8b1d1fb7f38fc23439bbe5b9778062fc6aa7 | 11,063 |
from typing import Optional
def maximum(
left_node: NodeInput,
right_node: NodeInput,
auto_broadcast: str = "NUMPY",
name: Optional[str] = None,
) -> Node:
"""Return node which applies the maximum operation to input nodes elementwise."""
return _get_node_factory_opset1().create(
"Maxim... | 9ca2ac093059a9c7c2a1b310635c551d1982b1bb | 11,064 |
def create_template_error():
"""
Создает заготовку для генерации ошибок
"""
return {'response': False} | f15c27cc980cf1bda6b82353d01bbe7871fdbff1 | 11,065 |
from typing import Any
from typing import Tuple
import os
import logging
import sys
def download_and_extract_index(storage_bucket: Any, extract_destination_path: str) -> Tuple[str, Any, int]:
"""Downloads and extracts index zip from cloud storage.
Args:
storage_bucket (google.cloud.storage.bucket.Buc... | 6d4ab60f6c0e95a9b9a52afc58b510f03d32c8d1 | 11,066 |
def e_qest(model, m):
"""
Calculation of photocounting statistics estimation from
photon-number statistics estimation
Parameters
----------
model : InvPBaseModel
m : int
Photocount number.
"""
return quicksum(model.T[m, n] * model.PEST[n]
for n in model.... | b4b5f9fb4ba1c142af3d91d170fdb90ae960dd0e | 11,067 |
def load_input(fname):
"""Read in the data, return as a list."""
data = [""]
with open(fname, "r") as f:
for line in f.readlines():
if line.strip("\n"):
data[-1] += line.strip("\n") + " "
else:
data[-1] = data[-1].strip(" ")
dat... | f83021dd416e3a959996a16bb8d0a0e7352a471f | 11,068 |
import json
def parse_repo_layout_from_json(file_):
"""Parse the repo layout from a JSON file.
Args:
file_ (File): The source file.
Returns:
RepoLayout
Raises:
InvalidConfigFileError: The configuration file is invalid.
"""
def encode_dict(data):
new_data = {... | db1b7843c26ecc6796233e0cc193b41336fecf2d | 11,069 |
def SizeArray(input_matrix):
"""
Return the size of an array
"""
nrows=input_matrix.shape[0]
ncolumns=input_matrix.shape[1]
return nrows,ncolumns | 3ac45e126c1fea5a70d9d7b35e967896c5d3be0b | 11,070 |
def show_fun_elem_state_machine(fun_elem_str, xml_state_list, xml_transition_list,
xml_fun_elem_list):
"""Creates lists with desired objects for <functional_element> state, send them to
plantuml_adapter.py then returns url_diagram"""
new_fun_elem_list = set()
main_fun_el... | 3d8b1426e791bcc40c9850723da9bf350bea361f | 11,071 |
def get_bank_account_rows(*args, **kwargs):
"""
获取列表
:param args:
:param kwargs:
:return:
"""
return db_instance.get_rows(BankAccount, *args, **kwargs) | 0599b2bbae3b7bb044789db6c18f47604c3c9171 | 11,072 |
import importlib
def load_class(class_name, module_name):
"""Dynamically load a class from strings or raise a helpful error."""
# TODO remove this nasty python 2 hack
try:
ModuleNotFoundError
except NameError:
ModuleNotFoundError = ImportError
try:
loaded_module = importl... | 02ce2988e45b30da7603acc41fea4846481a94e3 | 11,073 |
def pybo_mod(tokens, tag_codes=[]):
"""extract text/pos tuples from Token objects"""
txt_tags = []
for token in tokens:
tags = []
tags.append(token.text)
# Select and order the tags
for tag_code in tag_codes:
tags.append(get_tag(token, tag_code))
txt_tags.... | e96bb6a4774a0e983f2288536921e98207aeaa4b | 11,074 |
def acf(
da: xr.DataArray, *, lag: int = 1, group: str | Grouper = "time.season"
) -> xr.DataArray:
"""Autocorrelation function.
Autocorrelation with a lag over a time resolution and averaged over all years.
Parameters
----------
da : xr.DataArray
Variable on which to calculate the diagn... | 630eb27574edb40f363f41656a23801f11cefb1c | 11,075 |
import requests
def username(UID: str) -> str:
"""
Get a users username from their user ID.
>>> username("zx7gd1yx")
'1'
>>> username("7j477kvj")
'AnInternetTroll'
>>> username("Sesame Street")
Traceback (most recent call last):
...
utils.UserError: User with uid 'Sesame Street' not found.
"""
R: dic... | c2d66af182a970783ef6e2236c1db3e5a3f80b50 | 11,076 |
import logging
def handle_exceptions(func):
"""Exception handler helper function."""
logging.basicConfig(level = logging.INFO)
def wrapper_func(*args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
logging.error(f'{func.__name__} raised an error... | 2d5c428e65cfb823d1afbf2d2c77f98b8722d685 | 11,077 |
def apply_hamming_window(image):
"""Cross correlate after applying hamming window to compensate side effects"""
window_h = np.hamming(image.shape[0])
window_v = np.hamming(image.shape[1])
image = np.multiply(image.T, window_h).T
return np.multiply(image, window_v) | f319506e9a51350664683ede7411e677bbf96ab3 | 11,078 |
from typing import Tuple
from functools import reduce
def calc_ewald_sum(dielectric_tensor: np.ndarray,
real_lattice_set: np.ndarray,
reciprocal_lattice_set: np.ndarray,
mod_ewald_param: float,
root_det_epsilon: float,
volu... | 5be08f833c8e44a4afeab48af0f5160278fbf88a | 11,079 |
import time
def proximal_descent(
x0, grad, prox, step_size, momentum='fista', restarting=None,
max_iter=100, early_stopping=True, eps=np.finfo(np.float64).eps,
obj=None, benchmark=False):
""" Proximal descent algorithm.
Parameters
----------
x0 : array, shape (n_l... | e6a05c2ef4295b67e3bc3ac2b1608b16d43bc09e | 11,080 |
import json
def sign_tx(path,
multisig_address,
redeemscript,
utxo_file,
output_file,
testnet=False):
"""
Sign a spend of a bitcoin 2-of-3 P2SH-multisig address
using a Trezor One Hardware Wallet
Args:
path: BIP32 path of... | d9e16f5ce241b52f0cef0edb675936e52d3d2cf8 | 11,081 |
from stable_baselines_custom.common.atari_wrappers import wrap_deepmind
def wrap_atari_dqn(env):
"""
wrap the environment in atari wrappers for DQN
:param env: (Gym Environment) the environment
:return: (Gym Environment) the wrapped environment
"""
return wrap_deepmind(env, frame_stack=True, ... | 6c47492fe412b5620f22db17a45aa42968ed9a62 | 11,082 |
def get_Theta_CR_i_d_t(pv_setup, Theta_A_d_t, I_s_i_d_t):
"""加重平均太陽電池モジュール温度 (6)
Args:
pv_setup(str): 太陽電池アレイ設置方式
Theta_A_d_t(ndarray): 日付dの時刻tにおける外気温度（℃）
I_s_i_d_t(ndarray): 日付dの時刻tにおける太陽電池アレイiの設置面の単位面積当たりの日射量（W/m2）
Returns:
ndarray: 日付dの時刻tにおける太陽電池アレイiの加重平均太陽電池モジュール温度
"""
... | 6c96d9c4692de19909feccf647fd39126358b29c | 11,083 |
from typing import Set
def or_equality(input_1: Variable, input_2: Variable, output: Variable) -> Set[Clause]:
"""
Encode an OR-Gate into a CNF.
:param input_1: variable representing the first input of the OR-Gate
:param input_2: variable representing the second input of the OR-Gate
:param output... | f101b1d7ae3d70e7849133562cd274275f8419a8 | 11,084 |
import math
def keyPosition_to_keyIndex(key_position: int, key: int) -> int:
"""
キーポジションからどのキーのノーツなのかを変換します
引数
----
key_position : int
-> キーポジション
key : int
-> 全体のキー数、4Kなら4と入力
戻り値
------
int
-> キーインデックス、指定したキーの0~キー-1の間の数
"""
return math.floor(key_position * key / 512) | e6edcc1711a283336da046e1f8f174cc7ff87760 | 11,085 |
import json
def load_file_recipes(fh, enabled_only=False, expensive=False, logger=logger):
"""
Load all the recipes from a given file handle.
:param enabled_only: Set True to limit to only enabled recipes.
:param expensive: Set True to use 'expensive' configurations.
:return: dict(name -> {recipe... | 8a372981da76f9dc060c79e6cf282612fec8a4b6 | 11,086 |
from masonite.routes import Patch
def patch(url, controller):
"""Shortcut for Patch HTTP class.
Arguments:
url {string} -- The url you want to use for the route
controller {string|object} -- This can be a string controller or a normal object controller
Returns:
masonite.routes.Pa... | c267ca8c2e2c55369584a94cd07aaf26b0b7ae4b | 11,087 |
def get_user(message: discord.Message, username: str):
""" Get member by discord username or osu username. """
member = utils.find_member(guild=message.guild, name=username)
if not member:
for key, value in osu_tracking.items():
if value["new"]["username"].lower() == username.lower():
... | 323ac71e24e4da516263df3a4683ed5fd87138ce | 11,088 |
import colorsys
def resaturate_color(color, amount=0.5):
"""
Saturates the given color by setting saturation to the given amount.
Input can be matplotlib color string, hex string, or RGB tuple.
"""
if not isinstance(color, np.ndarray) and color in matplotlib.colors.cnames:
color = matplot... | 2bd1b9b4d9e1d11390efc79f56a89bf7555cbe71 | 11,089 |
def create_reach_segment(upstream_point, downstream_point, polyline, identifier="HA",
junctionID=0, isEnd=False):
"""Returns a polyline based on two bounding vertices found on the line. """
part = polyline.getPart (0)
total_length = polyline.length
lineArray = arcpy.Array ()
... | c378fb05c1eda5cde35d5caf60a9d732578ae6d8 | 11,090 |
def sample_recipe(user, **params):
""" Helper function for creating recipes """
""" for not writing every single time this fields """
defaults = {
'title': 'Sample recipe',
'time_minutes': 10,
'price': 5.00
}
"""
Override any field of the defaults dictionary.
Updati... | 11fe56c88cc0c641b1c04b279b2346615b2257c9 | 11,091 |
def _unary_geo(op, left, *args, **kwargs):
# type: (str, np.array[geoms]) -> np.array[geoms]
"""Unary operation that returns new geometries"""
# ensure 1D output, see note above
data = np.empty(len(left), dtype=object)
data[:] = [getattr(geom, op, None) for geom in left]
return data | d302bdb41c74f7b127df4ccd24dd6bc56c694a56 | 11,092 |
def map_func(h, configs, args):
"""Polygons command line in parallel.
"""
if args.verbose:
cmd = "python {} -i {}/threshold{}.tif -o {}/threshold{}.shp -v".format(
configs["path"]["polygons"],
configs["path"]["output"],
h,
configs["path"]["output"],
h
)
print cmd
else:
cmd = "python {} -i {}/... | 4ff4e961b2d0eb9a19b277a0b8e2ef165aa43819 | 11,093 |
import os
def _runopenssl(pem, *args):
"""
Run the command line openssl tool with the given arguments and write
the given PEM to its stdin. Not safe for quotes.
"""
if os.name == 'posix':
command = "openssl " + " ".join(["'%s'" % (arg.replace("'", "'\\''"),) for arg in args])
else:
... | ce61d5855d73365d13b28c447566f6ebb75aa030 | 11,094 |
def check_health(request: HttpRequest) -> bool:
"""Check app health."""
return True | 20d572edd68e1518e51cbdbe331c17798bc850fe | 11,095 |
def return_galo_tarsilo(message):
"""Middle function for returning "gaucho" vídeo.
Parameters
----------
message : telebot.types.Message
The message object.
Returns
-------
msg : str
User/Chat alert list addition/removal.
"""
return 'https://www.youtube.com/watch?v... | 58307b763d139dc38220b9a93af15644ccd32959 | 11,096 |
def preimage_func(f, x):
"""Pre-image a funcation at a set of input points.
Parameters
----------
f : typing.Callable
The function we would like to pre-image. The output type must be hashable.
x : typing.Iterable
Input points we would like to evaluate `f`. `x` must be of a type acce... | 6ca0496aff52cff1ce07e327f845df4735e3266a | 11,097 |
import dbm
import sys
def get_spec_id(mat_quality, mat_faction=None):
"""
Get the material_spec id corresponding to the material quality and faction.
Args:
mat_quality (str): A material quality like Basic, Fine, Choice etc...
mat_faction (str): A material faction like Matis, Zoraï etc...
... | dbabe3fb6fd042a3510272aa8c353efd161b5651 | 11,098 |
def print_raw_data(raw_data, start_index=0, limit=200, flavor='fei4b', index_offset=0, select=None, tdc_trig_dist=False, trigger_data_mode=0):
"""Printing FEI4 raw data array for debugging.
"""
if not select:
select = ['DH', 'TW', "AR", "VR", "SR", "DR", 'TDC', 'UNKNOWN FE WORD', 'UNKNOWN WORD']
... | 23464a46d5a3d05702fae3381e3d7623ad9017b5 | 11,099 |
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