content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def sched_var(func):
"""This decorator marks the given function as a scheduler variable. The
function must take no arguments (other than self)."""
# The scheduler plugin class will search for these.
func.is_sched_var = True
func.is_deferable = False
# Wrap the function function so it keeps it'... | 99a01aa59ec633cf8d0cd06258f0d726d21df6f7 | 3,611,611 |
import logging
def posgres_raw(query_sql, query_args=None, *, as_dict=True, alias=None, filterData=None, modifyData=None, **kwargs):
""" Returns the answer to a raw sql statement to ther database.
table (str) - Which table to get data from
Example Input: posgres_select("SELECT * FROM property")
Example Input: ... | 11168f2e882674bb967841c48f84e55c08496e56 | 3,611,612 |
def file_upload_url():
""" file_upload_url: returns url to upload files
Args: None
Returns: string url to file_upload endpoint
"""
return FILE_UPLOAD_URL.format(domain=DOMAIN) | 4ac3a8f20fd212d4f9c28697a793bb6d8759e38d | 3,611,613 |
def parse_command_line(version=None,
self_description=None,
version_date=None,
default_config_file_path=None,
):
"""parse command line arguments
Also add current version and version date to description
"""
# de... | fbf9613087d7a629f56d4b1f6260b71ab36e283f | 3,611,614 |
def appium_bytes(value, encoding):
"""
Return a bytes-like object. Has _appium_ prefix to avoid overriding built-in bytes.
:param value: A value to convert
:type value: string
:param encoding: A encoding which will convert to
:type encoding: string
:return: A bytes-like object
:rtype:... | b7acc045584ffad834bb24f30fe930736f55d699 | 3,611,616 |
from typing import List
import csv
def read_sts_inputs(path: str) -> List[str]:
"""Read input texts from a tsv file, formatted like the official STS benchmark"""
inputs = []
with open(path, 'r', encoding='utf8') as fh:
reader = csv.reader(fh, delimiter='\t', quoting=csv.QUOTE_NONE)
for row... | 6af4e934d648b550298e71584eaf47e4267316ac | 3,611,617 |
def extract_keys(dict, keys, no_key_val=_sentinel):
"""Removes the specified keys from the given dictionary, and returns a dictionary containing those key:value
pairs. Default behaviour is to ignore those keys which can't be found in the original dictionary. The optional
argument :no_key_val: can be set to ... | eb420734b1969e8a01b47caef023443d0e1f48e7 | 3,611,619 |
def resnet101(num_classes, pretrained=False, dropout1=0.25, dropout2=0.25, alpha=0.25, gamma=2.0,
loss_with_no_bboxes=False, no_bboxes_alpha=0.5, no_bboxes_gamma=2, **kwargs):
"""Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
... | 688e0ded410033c63c3db6c10f65a334447a2b97 | 3,611,620 |
def vuvu_to_vuhw(vuvu):
"""
Function to transform between top left and bottom right corner box representation (vuvu) to
center_dimensions box representation (vuhw) .
:param vuvu: N x 4 tensor represeting v_min, u_min, v_max, u_max, the corners of the bounding boxes.
:return: vuhw: N x 4 tensor rep... | a9dc162d1b7d8d66099f2fb500d808e10d492809 | 3,611,621 |
import asyncio
async def async_unload_entry(hass, config_entry):
"""Unload an AirVisual config entry."""
unload_ok = all(
await asyncio.gather(
*[
hass.config_entries.async_forward_entry_unload(config_entry, component)
for component in PLATFORMS
... | 14b761200e6ec54340f6543e447d7c240ebfb5ca | 3,611,622 |
def application_doesnt_match(service, custom_application, custom_app_plan, lifecycle_hooks, request):
"""Second application that doesn't match jwt claim check policy"""
plan = custom_app_plan(rawobj.ApplicationPlan(blame(request, "aplan")), service)
application = custom_application(rawobj.Application(blame(... | 19b6ef733e505522423d88f9de14ef753854cde3 | 3,611,623 |
def delete_appliance_for_rediscovery(
self,
ne_pk: str,
) -> bool:
"""Delete an appliance from Orchestrator for rediscovery
.. list-table::
:header-rows: 1
* - Swagger Section
- Method
- Endpoint
* - appliance
- DELETE
- /appliance/delete... | 8be2817f55408314ef27baac022801059f3f2340 | 3,611,624 |
def increase_index(idx: str) -> str:
"""Increases an index by one unit.
If the index is numeric, in the range '00' to '98', it adds one
to the index and returns an index in the range '01' to '99'.
If the index is already '99', there is an Exception error.
If the index is alphanumeric, with the fir... | 1bcaa8d27ed83d295197c4f398e77d49ad47bb6d | 3,611,626 |
def compare_flow_fields(F1, F2, n_min=1):
"""Compare two flow fields.
"""
# Compute the element-by-element difference
dX_diff = F1.dX_fit - F2.dX_fit
dX_diff_mag = np.linalg.norm(dX_diff, axis=2) # n_grid x n_grid
# Filter by the number of observations. Find the number of observations for
... | 26dc0cd321861050899cfe5e0189966eff6efd4f | 3,611,627 |
import itertools
def rollup_dataseries(dataseries):
"""
Rollup dataseries.
Roll up a sites data series by parameter group if a series has them. Data
types for the parameter group is the join of the data types for each measured
parameter code. Similarly, the start and end dates are the earliest an... | 9ac13333d05a6410b1fd4497528f8eca6d1d7f45 | 3,611,628 |
def determine_smallest_atom_index_in_scan(atom1: 'rdkit.Chem.rdchem.Atom',
atom2: 'rdkit.Chem.rdchem.Atom',
) -> int:
"""
Determine the smallest atom index in mol connected to ``atom1`` which is not ``atom2``.
Returns a heav... | dd15837711401f52ff9ab3f561b4d82556990a9c | 3,611,629 |
def quartiles(xs):
"""Divisions between quartiles."""
return quantiles(xs, 0.25, 0.5, 0.75) | 599d8a81c8b7774096eb2f062448cf8dd4818a17 | 3,611,632 |
from datetime import datetime
import time
def formatTimeFromNow(secs=0):
""" Properly Format Time that is `x` seconds in the future
:param int secs: Seconds to go in the future (`x>0`) or the
past (`x<0`)
:return: Properly formated time for Graphene (`%Y-%m-%dT%H:%M:%S`)
... | 9723ab0656ff4017412ab1fbd5465375ec8df1af | 3,611,633 |
from datetime import datetime
def get_utc_timestamp() -> Text:
"""Get utc timestamp.
Returns:
Text: utc timestamp
"""
return str(datetime.datetime.utcnow().timestamp() * 1000) | 85de30cf745c545dadc26d7dbc6c866238e6c5cf | 3,611,634 |
def ConvolutionalVAE(*args, **kwargs):
"""
Constructs a Convolutional VAE.
References
[1]. Oktay, Ozan, et al. “Attention U-Net: Learning Where to Look for the Pancreas.” ArXiv:1804.03999 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1804.03999.
>>> import deeply
>>> model = deeply.hub("... | fd082d63e2940dc07a2ce007b8f4da251411c834 | 3,611,635 |
def to_2d_np(a: ndarray, type: str="col") -> ndarray:
"""
Turns a 1D Tensor into 2D
"""
assert a.ndim == 1, \
"Input tensors must be 1 dimensional"
if type == "col":
return a.reshape(-1, 1)
elif type == "row":
return a.reshape(1, -1) | 07933cd3851d65b61034b3b3d7b9caa46b809c1e | 3,611,636 |
def standardize_parameter_type(original_type):
"""Standardize parameter type descriptions
Args:
original_type (str): The original type
Returns:
str: The standarized type name
"""
original_type = original_type.lower()
if 'unc' in original_type:
return 'uncertainty'
i... | 49a93bebd8ee4918bdf420ee8c285d6574a3d3d0 | 3,611,639 |
def insert_xlnx_pragmas(lines):
"""Insert HLS pragmas for Xilinx program
Replace the comments of "// hls_pipeline" and "// hls_unroll" with
HLS pragmas
For "// hls pipeline", find the previous for loop before hitting any "}".
Insert "#pragma HLS PIPELINE II=1" below the for loop.
For "// hls un... | 9ad5e5253473ecbcf82d4e739b7c6d7dd82ba7c6 | 3,611,642 |
def check_unboundness(A_times_delta_x):
"""Check if LP is unbounded
"""
if np.all(A_times_delta_x <= 0):
logger.info('LP is unbounded')
return True
else:
return False | c8a91036fd3768b1774fba650796886d8eafa913 | 3,611,643 |
from typing import Tuple
import torch
import math
def real_fourier_basis(n: int) -> Tuple[torch.Tensor, torch.Tensor]:
"""Make a Fourier basis.
Args:
n: The basis size
Returns:
An array of shape `(n_domain, n_funs)` containing the basis functions, and an
array containing the spec... | 704aacf8e34f2713ee5e01b8c0de2350c8e03ae2 | 3,611,644 |
def to_output_type(array, output_type, order='F'):
"""Used to convert arrays while creating datasets
for testing.
Parameters
----------
array : array
Input array to convert
output_type : string
Type of to convert to
Returns
-------
Converted array
"""
if out... | 701691824ddd2364ff6770d93d13389cf8aa4dc4 | 3,611,645 |
def _define_names(d_t, d_y, treatment_names, output_names):
"""
Helper function to get treatment and output names
Parameters
----------
d_t: tuple of int
Tuple of number of treatment (exclude control in discrete treatment scenario).
d_y: tuple of int
Tuple of number of outcome.
... | a475968ed70070175f5ef164d1748def62548c9d | 3,611,646 |
import urllib3
def scrape_lat_lon_fly(stationID):
"""
Add latitude, longitude and elevation data to the stationID that is
inputted as the argument to the function. Boom.
:param stationID: str
a unique identifier for the weather underground personal
weather station
:return: (latitud... | e1a78f3adfb7ce890306d31deba4e15410bb079c | 3,611,647 |
from typing import List
from typing import Callable
def _add_standard_processes(process_registry: ProcessRegistry, process_ids: List[str]):
"""
Add standard processes as implemented by the openeo-processes-python project.
"""
def wrap(process: Callable):
"""Adapter to connect the kwargs style... | da5b162fdc8002670864cd1e1e5069b40f0d8a8b | 3,611,648 |
def __num_children(self, vertex=None):
"""
Get the the number of children of the given vertices.
If :attr:`vertex` is ``None``, the function will return the number of children of every non leaf
node of the tree.
:param vertex: a vertex index or a 1d array of vertex indices
(default to ``np... | e1385a67cfc79dd1fa18805c85e8e2fd59336c16 | 3,611,649 |
from datetime import datetime
def parse_time_interval(time_start, time_end):
"""created time values for time_start and time_end, while time_end
will be replaced with time_start+ a duration if the duration is
given in time_end. The format of the duration is intuitive through
the timeparse module. YOu c... | b4348e1995514030528fad9330d726eb5079d758 | 3,611,650 |
def _as_vw_string(x, y=None):
"""Convert {feature: value} to something _VW understands
Parameters
----------
x : {<feature>: <value>}
y : int or float
"""
result = str(y)
x = " ".join(["%s:%f" % (key, value) for (key, value) in list(x.items())])
return result + " | " + x | 89e10d3bb8ad47ad4add6baee83280fa700ca65e | 3,611,651 |
from io import StringIO
import csv
def _read_header(f, header_param):
"""
Read and parse data from 1st line of a file.
:param f: :func:`file` or :class:`~StringIO.StringIO` object from which to
read 1st line.
:type f: file
:param header_param: Parameters used to parse the data from the he... | 294bb6846384378b1dd9950e649757a6448089d0 | 3,611,652 |
def classifier_layer_fn(in_dim, out_dim, layer_name, fn=tf.nn.relu):
"""Build a function for a neural network classifier layer."""
with tf.name_scope(layer_name + '_vars'):
weights, biases = classifier_variables(in_dim, out_dim)
def nn_layer_ops(x):
with tf.name_scope(layer_name + '_ops')... | ce0f153f033ab603373763368edc4e70d5b53590 | 3,611,653 |
def svn_client_revprop_get(*args):
"""
svn_client_revprop_get(char propname, svn_string_t propval, char URL, svn_opt_revision_t revision,
svn_revnum_t set_rev,
svn_client_ctx_t ctx, apr_pool_t pool) -> svn_error_t
"""
return apply(_client.svn_client_revprop_get, args) | b4725ec347ea9fbd7ab15d0a2ffb10112907b5b3 | 3,611,654 |
import typing
def do_action(view: View, defx: Defx,
action_name: str, context: Context) -> bool:
"""
Do "action_name" action.
"""
if not defx._source:
return True
actions: typing.Dict[str, ActionTable] = defx._source.kind.get_actions()
if action_name not in actions:
... | bb45de3c896b7bdcef8d40236a5743517d5230d1 | 3,611,656 |
from numpy import where
def qinit(x,y):
"""
Dam break
"""
eta = where(x<10, 40., 0.)
return eta | aa81ca9782917ce730ec70f4281a7b708c368308 | 3,611,657 |
def parkinson_volatility(high_prices, low_prices, window, time_scale=1, plot=False):
"""
Estimando a volatilidade a partir dos preços de Alta e de Baixa
Args:
high (pd.DataFrame): série de preços de alta de uma ação
low (pd.DataFrame): série de preços de baixa de uma ação
window (in... | 49b0f4b10eb80d17a801660c04cfe32e9d9e7dd9 | 3,611,658 |
def DatetimeToUTCMillis(date):
"""Converts a datetime object to milliseconds since the epoch in UTC.
Args:
date: A datetime to convert.
Returns:
The number of milliseconds since the epoch, in UTC, represented by the input
datetime.
"""
return DatetimeToUTCMicros(date) / 1000 | 0020e7b15ee0e7ff541d4e1691940e4114de42c5 | 3,611,660 |
from typing import AsyncIterable
from typing import Optional
from typing import Union
from typing import IO
from typing import List
async def _async_forward(async_chunks: AsyncIterable,
out: Optional[Union[TeeCapture, IO[str]]]
) -> Optional[str]:
"""Prints/capture... | 2e9d861cd905a2f4576e6ba026e98bfccb8b80c2 | 3,611,661 |
def _try_parse_int(value: str):
"""
try parse integer from string
param value: string to parse
return int
"""
try:
return int(value)
except ValueError:
raise ValueError("Cannot parse int from string") | 50b4f5c3d3e703c2c6c329e2f1abb25a948e488d | 3,611,662 |
import numpy as np
def df_to_latex(
df,
col_aligns="",
header="",
caption="",
bold_max_cols=None,
na_rep="-",
supertabular=False,
midrule_after=None):
"""Converts a pandas dataframe into a latex table.
:col_aligns: Optional format string for... | 6f073dd35c343a81e3222ac2e90fea2c2f5bd1d1 | 3,611,663 |
def _gather_shape_rule(operand, indices, *, dimension_numbers,
slice_sizes, unique_indices, indices_are_sorted,
mode, fill_value):
"""Validates the well-formedness of the arguments to Gather.
The code implements the checks based on the detailed operation semantics of
... | 052ac40add46eadc3e0d4cd43096290cf5d86c62 | 3,611,664 |
def tf_mixed_norm_solver(M, G, alpha_space, alpha_time, wsize=64, tstep=4,
n_orient=1, maxit=200, tol=1e-8, log_objective=True,
active_set_size=None, debias=True, return_gap=False,
verbose=None):
"""Solve TF L21+L1 inverse solver with BCD an... | 12dd13a8d45ef4afd0b515b4c4d6dcdf82f3c154 | 3,611,665 |
def stddev(in_list):
"""
Calculates standard deviation of given list
:param in_list: list of values
:return: float rounded to 5 decimal places
"""
var = zvariance.variance(in_list)
std_dev = sqrt(var)
return round(std_dev, 5) | 8225b943b87ea2c966b130fd5afc9b06d6306b8e | 3,611,666 |
def retrieve_single_timeseries(ticker, secs=60, ndays=5):
"""
Grabs data from Google finance. It retrieves the data for `ticker` at
`secs` intervals for the most recent `ndays`. The fields it retrieves
for each interval is (time, open price, close price, volume of trade)
Parameters
----------
... | 95fc69f4920d92895d2c9f8a8e852f78f2a06a8d | 3,611,667 |
def select_os(parsed_host: dict):
"""
Out of all suggested OSs for the given host from Nmap, select the most
likely one using cosine similarity string matching. First a string of
relevant information is created, second the OS whose information is the
most similar to the matching string is returned.
... | 4216686c724e1738471c939d567befc3d6f1c08d | 3,611,668 |
def index_settings(shards=5, refresh_interval=None):
"""Configure an index in ES with support for text transliteration."""
return {
"index": {
"number_of_shards": shards,
"refresh_interval": refresh_interval,
"analysis": {
"analyzer": {
... | 29028b545da2e5ee2b0239029d34f863d1d9d943 | 3,611,669 |
def create_gray_frame(frame):
"""Create and return an undistorted grayscale image"""
h, w = frame.shape[:2]
new_matrix, _ = cv2.getOptimalNewCameraMatrix(Pose.camera_matrix,
Pose.dist_coeffs,
(w, h), 1, (w, h... | 748aff0f5a02a7a98bc56f2c46645c59b630c4a7 | 3,611,670 |
def make_nan_inf_summary(df: pd.DataFrame, max_loss: float) -> pd.DataFrame:
"""
makes a summary fot the the amount of nan and infinity values in the given data frame
will throw a ValueError if the percent of nan and inf is greater than the given threshold
prints a summary of the nan's and inf of there ... | 0ea0be6a822861e5896176cf96d5a6bb9d50954f | 3,611,671 |
def choose_downloaded_komoot_tour():
"""
Choose a previously downloaded tour. Tour can be passed to
:func:`komoog.gpx.convert_tour_to_gpx_tracks`
afterwards.
"""
tours = read_tours()
for idx in range(len(tours)):
print(f"({idx+1}) {tours[idx]['name']}")
tour_id = int(input("To... | 66cf0878728fab6fa6265d61f2a488dde2478091 | 3,611,672 |
from datetime import datetime
def list_(limit: int = None, offset: int = None,
siri_route_ids: str = None, siri_route__line_refs: str = None, siri_route__operator_refs: str = None,
journey_ref_prefix: str = None,
journey_refs: str = None,
vehicle_refs: str = None,
sch... | 86fc2ce2a2609e6f2325f755c64812c8bbd093ba | 3,611,674 |
def fit_cpmfgp_with_dataset(dataset, *args, **kwargs):
""" Fits and returns a CPMFGP. """
config = dataset.config
mfgp_fitter = cpgp.CPMFGPFitter(dataset.ZZ_train, dataset.XX_train, dataset.YY_train,
fidel_space=config.fidel_space, domain=config.domain,
fidel_space_kernel_ordering=config.fidel_space_order... | 4478386e52d121d32951d84152c77e50bb5f4408 | 3,611,675 |
import time
def test_approach(approach: str, sample_no: int, func, args: tuple) -> str:
""" For a given Sample #sample_no evaluates an approach by running func with provided args and logs run time """
res = f"{approach.capitalize()} Programming Approach for the Example #{sample_no}\n"
start = time.time()+... | ef34e7552a887fd4bee221a5d80bb3d5ab0003a9 | 3,611,676 |
def call_command(cmd, verbosity="ERROR"):
"""
simple wrapper for call command
"""
p = Popen(cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE)
output, err = p.communicate("get output")
rc = p.returncode
if not rc == 0:
raise Exception("{0} ==> command: {1}".format(err, " ".join(cmd)))
return output | 2b153bb00f920fb9c5509fa6f76953073a8eec49 | 3,611,677 |
def walk(i, j):
"""
Walks through the String without crossing the boundaries,
making sure that i < j-1
"""
if i < j - 1:
i += 1
# It is necessary to check again if i < j-1, after we incremented i
if i < j - 1:
j -= 1
return i, j | 1597c41408179f5a371ec14e36494ec5ee3a7aa0 | 3,611,678 |
def run(configbase, filebase, options, progname):
"""
Command line tool to create and display ROs managed by the Overlay RO service.
"""
status = 0
# Create new Overlay RO and returns its URI
with HTTP_Session(options.serviceuri) as rovsession:
try:
rovsession.doRequest(optio... | de8d13f7f520dcf728f73c5485d50494ae631d79 | 3,611,679 |
def equation_loglogw2(x, a, b, c, d, e):
"""Equation form for loglogw2 """
return exp(a + b * log(log(x+1)) + (sqrt(x) * (c/2))) | 662fa157f5b4073780f5bbb383841867af7f6cd7 | 3,611,680 |
import uuid
def converter_spark_em_pandas(df):
"""
Converte o dataframe Spark em Pandas, adicionando uma coluna
de identificador unico e deterministico para cada linha da tabela
"""
data = df.toPandas()
data["ID_REGISTRO_TABELA"] = data.apply(
lambda row: uuid.uuid5(
uuid.UUID('a658b648-167e-4d4... | 99febbc364025afb39772fa6008f5b4217f394ae | 3,611,681 |
def kwargs_to_str(kwargs):
""" Returns a string of the form '(kw1=val1, kw2=val2)'. """
if len(kwargs) == 0:
return ""
else:
return "(" + ", ".join(f"{k}={v}" for k, v in kwargs.items()) + ")" | 39d50d77620061b99861fb7a1fea77ae2a2dc376 | 3,611,682 |
def get_crypt_key():
"""
Lazily generate the crypt key and return it
"""
# pylint: disable=global-statement
global __CRYPT_KEY__
if not __CRYPT_KEY__:
__CRYPT_KEY__ = _get_system_uuid()
return __CRYPT_KEY__ | b95972e33deb86450295da8440a6fe9213b3aed3 | 3,611,683 |
def index():
"""
Parameters:
----------
None.
Returns
--------
A rendered version of index.html and a http response code 200
The function renders the index page for the app
"""
global core_module
if not core_module: core_module = core_module()
... | 897b29517b9f8e566cd853eb81c529c3aac78001 | 3,611,684 |
def fpH(pH, c_Na, c_acide):
"""
Calcule la valeur de la fonction dont la racine correspond à l'équilibre
de la solution.
Entrée :
pH
c_Na (mol/L)
c_acide (mol/L)
Sortie :
valeur de la fonction
"""
Ke = 10**(- pKe)
Ka = 10**(... | 7ece0157f041057344239f0901f50c62dbc34719 | 3,611,685 |
def detect(source, config=None, path=None):
"""Analyze and detect minimum versions from source code. A default config will be used if it isn't
specified. If path is specified, it will occur in errors instead of the default '<unknown>'.
"""
visitor = visit(source, config, path)
if isinstance(visitor, SourceVis... | a71d576c877aa1ed9284b40f7047926833a5da98 | 3,611,687 |
def set_coredump_network_config(
host,
username,
password,
dump_ip,
protocol=None,
port=None,
host_vnic="vmk0",
dump_port=6500,
esxi_hosts=None,
credstore=None,
):
"""
Set the network parameters for a network coredump collection.
Note that ESXi requires that the dump... | a047c3f4c5ed866c34fd65c10cb251d04bbb3f52 | 3,611,688 |
def Verification(verification_list, value):
"""
Essa função verifica se algum jogador já venceu a partida,
retorna um valor booleano que determina o próximo jogador.
:param verification_list:
:param value:
:return bool:
"""
cont = 0 # define um contador.
for i in DIM.WIN: # verifi... | f90b6c53a385d409d6b2f973d7bac61d6dc58529 | 3,611,689 |
import json
def train_agent(env_config_path, agent_config_path, num_episodes):
"""train agent"""
f1, f2 = open(env_config_path), open(agent_config_path)
env_config, agent_config = json.load(f1), json.load(f2)
env, agent = config(env_config, agent_config)
evaluation = MyEvaluation(env, agent, outpu... | e02e20491c068bd9fb8c403ce74fb47eae07121e | 3,611,690 |
def add_CRUD_pset(pset, sm, model_name):
"""Adds the ServerModel CRUD function to the Primitve Set
Parameters
----------
pset : PrimitiveSet
the primitive set for adding the controller functions
sm : ServerModel
the ServerModel with the CRUD functions
model_name : str
... | f0960c3b96789adfa2e56039ca7c072819438984 | 3,611,691 |
def to_litres(gallons):
"""Convert US gallons to metric litres"""
return 3.78541 * gallons | d1a7be6f01c89b848128218cbec19913e76658cd | 3,611,692 |
import requests
def get_nioshtic_wikidata_mapping():
"""
Retrieves a mapping between NIOSHTIC and Wikidata identifiers from the
Wikidata Query Service, query.wikidata.org
@return dictionary {nioshtic: {identifier_label: value}}
"""
prefix = 'http://www.wikidata.org/entity/'
q = (
... | 7216f8ed354bb394e39ceb906d41e19d1e41e589 | 3,611,694 |
import uuid
from datetime import datetime
def create_new_fabric_person_from_token(headers, check_unique=False):
"""
Extract info from identity token and create a FabricPerson entry for this person,
including a new UUID. Return a PeopleLong based on that info.
:param headers: request headers with cooki... | 83f76bec65c644aaf79708d33d98a43d64806a05 | 3,611,695 |
def _gsspp(X,p,n,fun=ss):
"""
Generalized Spatial Sign Pre-Processing for Centred Data
"""
return(np.multiply(X,fun(_norms(X),p,n))) | bfa85e78bdffed7e152dbde1c9590f5bee52dd40 | 3,611,696 |
import random
import copy
def distr_labeldata_unequal(label_data, num_workers):
"""
Idea:
1. For each label, distribute disproportionate allocation to workers.
2. Apply the worker's allocation to label_data and store in distr_labeldata,
where the keys are workers and the values are the labeled... | dab112ba98e9d5d68fbb519f1c7e3f2a6ea24e17 | 3,611,697 |
def random_conv_encode(k, generator_matrix, memory, p=0.5):
"""
Generates a random sequence of k-bits, each Bernoulli(p) and then encodes
them convolutionally. Returns the original sequence, and the convolutionally
encoded one, using the generator matrix and memory.
"""
message_bits = generate_random_binar... | 1419fcda911f0d52161b0e8091ef076e86efc1b7 | 3,611,699 |
import json
def readJsonTextarea2(request):
"""JSONでの応答練習"""
template = loader.get_template('practice/json-textarea2.html')
# ----------------------------
# 1
# 1. host1/webapp1/templates/practice/json-textarea2.html を取ってきます
# ... | df428a65fbd0e29801e4aeb2f11226ae251a2928 | 3,611,700 |
def _smart_fusion_strategy(ents):
"""This strategy adds the entities scores if one entity occurs multiple times with the same tag, and afterwards
applies the fusion strategy."""
deduplicated_ents = []
for idx, ent in enumerate(ents):
next_ent = ents[idx + 1] if idx + 1 < len(ents) else None
... | 7b1fd80fe7a7feec69502fc240c045bca9f722cf | 3,611,701 |
def bayesian_regret(voters, winner):
"""
Calculate bayesian regret
voters : array (a, n)
Voter preferences; n-dimensional voter cardinal preferences for n issues.
winner : array shape (n)
Winner preferences for winner and `n`-dimensional issues.
"""
voters =... | faf1d9e4b16c410665be4179bceeeca7339f6fba | 3,611,702 |
def run(process_class, *args, **inputs):
"""
Synchronously (i.e. blocking) run a workfunction or process.
:param process_class: The process class or workfunction
:param _attributes: Optional attributes (only for process)
:param args: Positional arguments for a workfunction
:param inputs: The li... | 44dc23b378b51bb30b3bba74558df909083a60e8 | 3,611,703 |
from datetime import datetime
def plotter(fdict):
""" Go """
pgconn = get_dbconn('coop')
ctx = get_autoplot_context(fdict, get_description())
station = ctx['station']
t1 = ctx['t1']
t2 = ctx['t2']
table = "alldata_%s" % (station[:2],)
nt = NetworkTable("%sCLIMATE" % (station[:2],))
... | 8313ed7cb5da0a607f194b874ad23aa3a7de606c | 3,611,705 |
def cu_projection(param: str, date: date, cu_projections) -> int:
"""
Get the Columbia model's prediction
of the param for the date
"""
scenario = cu_model_scenario(tuple([s for s in cu_projections.keys()]))
quantile = cu_model_quantile()
# Extract quantiles of the model distribution
xs... | 16e240e1553b52c2fdd60e46fe55b3c18b4b7b71 | 3,611,707 |
def dicthash(d:dict)->Hash:
""" Calculate hashsum of a Python dict. Top-level fields starting from '_' are ignored """
string="_".join(str(k)+"="+str(v) for k,v in sorted(d.items()) if len(k)>0 and k[0]!='_')
return md5(string.encode('utf-8')).hexdigest() | 39adff8a7cec0ec70695013332db9eed5b03b0ab | 3,611,708 |
def _urlparse_qs(url):
"""
Parse a URL query string and return the components as a dictionary.
Based on the cgi.parse_qs method.This is a utility function provided
with urlparse so that users need not use cgi module for
parsing the url query string.
Arguments:
:type url: str
:param ur... | 3516b35f814d5bf9a549540858d632cfb0a99e17 | 3,611,709 |
def erfc_inverse(x):
""" erfc-1(x) = - 1/sqrt(2) * normal_quantile( 0.5 * x)"""
return -0.70710678118654752440 * normal_quantile(0.5 * x) | f1994c8fdee5ae94624562210fe4621594636204 | 3,611,710 |
def extract_8_statistical_features(data):
"""
Extract 8 statistical features: mean, standard deviation, length,
minimum val, first quartile, second quartile,
third quartile, maximum val
:parameter data: pandas DataFrame of the data who... | 9aae0c143fd0eb1183fa77e7cb86d3806d73cd99 | 3,611,711 |
import array
def bin_stats(x, y, xbins, stat='average'):
"""Given the variable y=f(x), and
the bins limits xbins, return the
corresponding statistics, e.g. <y(xbins)>
Options are rms, median y average
"""
nbins = len(xbins)
if stat == 'average' or stat == 'mean': func = mean
elif sta... | ea97d56cde01bfa4ebd7eaf4d0c53a5f2d48c4c8 | 3,611,712 |
from typing import Sequence
def all_unique(lst):
"""Returns True if all elements of Sequence `lst` are unique.
False otherwise.
"""
assert isinstance(lst, Sequence)
return bool(len(set(lst)) == len(lst)) | 546d4254d5ca287952eec6af2bda048e60bb6b89 | 3,611,713 |
def ingredient_fractions_predictor() -> IngredientFractionsPredictor:
"""Build a Ingredient Fractions predictor for testing."""
return IngredientFractionsPredictor(
name='Ingredient fractions predictor',
description='Computes total ingredient fractions',
input_descriptor=formulation,
... | 934ab59171ceb3bd2227092ab3e5eea300884d95 | 3,611,714 |
def record_fuzz_target(engine, binary_name, job_type):
"""Record existence of fuzz target."""
if not binary_name:
logs.log_error('Expected binary_name.')
return None
project = data_handler.get_project_name(job_type)
key_name = data_types.fuzz_target_fully_qualified_name(
engine, project, binary_n... | 5b88599944eeb74c2da43d395e9877d4e9d7eba9 | 3,611,715 |
def svm_loss(x: NPArray, y: NPIntArray) -> tuple[float, NPArray]:
"""
Computes the loss and gradient using for multiclass SVM classification.
Inputs:
- x: Input data, of shape (N, C) where x[i, j] is the score for the jth class
for the ith input.
- y: Vector of labels, of shape (N,) where y[i... | e5d8709d3323e9a8dacc3ed7344c6208fdbcfefc | 3,611,716 |
def make_constellation(config):
"""Builds the constellation model."""
n_caps = 3
encoder = SetTransformer(
n_layers=4,
n_heads=4,
n_dims=128,
n_output_dims=32,
n_outputs=n_caps,
layer_norm=True,
dropout_rate=0.,
)
decoder = ConstellationCapsule(
n_caps=n_caps... | a250df9a70be5637eee079e1471e3a4baa2f3ba9 | 3,611,717 |
def scale_matrix(
factor: float,
origin: np.ndarray = None,
direction: np.ndarray = None
) -> np.ndarray:
"""
Return matrix to scale by factor around origin in direction.
Use factor -1 for point symmetry.
"""
if direction is None:
# uniform scaling
M = np.array(
... | 92b000567245b4cf7732ee66ffd32e389fbf365c | 3,611,719 |
def plot_h(data, cols, wspace=.1, plot_kw=None, **kwargs):
"""
Plot horizontally
Args:
data: DataFrame of data
cols: columns to be plotted
wspace: spacing between plots
plot_kw: kwargs for each plot
**kwargs: kwargs for the whole plot
Returns:
axes for p... | dc3f62442da33f3bc45df70ec0e6ee41cab658ab | 3,611,720 |
def generate_average_csv(fname, fields, trait_list):
""" Generate CSV called fname with fields and trait_list """
csv = open(fname, 'w')
csv.write(','.join(map(str, fields)) + '\n')
csv.write(','.join(map(str, trait_list)) + '\n')
csv.close()
return fname | 43195ea054ea537a4860c07c03c96efc263c472f | 3,611,721 |
from typing import Set
def get_s2_patches_with_no_19_class_target() -> Set[str]:
"""
List all patches from the BigEarthNet-S2 dataset that
have _no_ defined classes with the 19-class nomenclature.
Note: This set still includes patches with snow, clouds, or shadows.
To re-build the file, it is ne... | 9132457f706df6dfe2f538a25210c936d528d565 | 3,611,723 |
import torch
from typing import Tuple
from typing import List
def winnow_model(model: torch.nn.Module, input_shape: Tuple,
list_of_modules_to_winnow: List[Tuple[torch.nn.Module, List]] = None,
reshape=True, in_place=False, verbose=False):
""" This API is used to winnow a model w... | 41643e9bb832669293220693282d2232b7ae321a | 3,611,724 |
import tqdm
def get_expr_dict(input_tuple):
"""Returns the quantification results as a dict of dicts."""
bamfname, contig, start, stop, length, worker_ind = input_tuple
if worker_ind == None: worker_ind = 0
if contig is None:
desc_str='all_reads'
else:
desc_str='chr_'+contig
region = dict(
... | 036f8f683e32c189ca64be0e2b8a7a2b4564bfd2 | 3,611,725 |
def arg_parsing(req):
"""
:type req: class 'ow_lander.srv._Grind.GrindRequest'
"""
if req.use_defaults :
# Default trenching values
x_start = 1.65
y_start = 0.0
depth = 0.05
length = 0.6
parallel = True
ground_position = constants.DEFAULT_GROUND_HEIGHT
else :
x_start = req... | 981d0faca672fe5d508dde24cef24500f0885ca5 | 3,611,726 |
def adjacency_lattice_square(sidelength, num_cells, search_radius, periodic_bc=False):
"""
periodic_bc: wrap around boundary condition (False default)
"""
assert num_cells == sidelength ** 2
adjacency_arr_uptri = np.zeros((num_cells, num_cells))
# build only upper diagonal part of A
for a in... | 4fedf6dffc6b9fe92bf164d8a2ae8a176126f026 | 3,611,727 |
import math
def determine_aha_part(seg_sa, affine_sa, three_slices=False):
""" Determine the AHA part for each slice. """
# Label class in the segmentation
label = {'BG': 0, 'LV': 1, 'Myo': 2, 'RV': 3}
# Sort the z-axis positions of the slices with both endo and epicardium
# segmentations
X, ... | 0fe5f26f172a9fc77fcfb98b562b583760982949 | 3,611,728 |
def swap_scientific_notation_float(line: deque, precision: int) -> deque:
"""
Returns a deque representing 'pycode_as_deque' with any python floats that
will get "cut-off" by the 'precision' arg when they are rounded as being
rendered as strings in python's "e format" scientific notation.
A float ... | 8ddc47cff96a98309f6c646769116e26e6c693db | 3,611,729 |
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