content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Union
from typing import Sequence
def average_false_positive_score(
y_true: Union[Sequence[int], np.ndarray, pd.Series],
y_pred: Union[Sequence[int], np.ndarray, pd.Series],
) -> float:
"""Calculates the average false positive score. Used for when we have more than 2 classes and want ou... | 4b789381e25efffc0aa811287bab8299edf6b962 | 15,243 |
import html
def display_text_paragraph(text: str):
"""Displays paragraph of text (e.g. explanation, plot interpretation)
Args:
text (str): Informational text
Returns:
html.Small: Wrapper for text paragraph
"""
return html.P(children=[text],
style={'font-size': '... | 8c4ae8f7b606b81726149891fb5db624647ba484 | 15,244 |
def is_numeric(_type) -> bool:
"""
Check if sqlalchemy _type is derived from Numeric
"""
return issubclass(_type.__class__, Numeric) | 1d604873e4043206b50ddc09c691331c4c50c49c | 15,245 |
def make_generic_time_plotter(
retrieve_data,
label,
dt,
time_unit=None,
title=None,
unit=None,
):
"""Factory function for creating plotters that can plot data over time.
The function returns a function which can be called whenever the plot should be drawn.
... | 3fa391a94973e5b98394e684d8e4018fa16811df | 15,246 |
def registration(request):
"""Registration product page
"""
if request.method == 'POST':
user_form = UserRegistrationForm(request.POST)
if user_form.is_valid():
# Create a new user object but avoid saving it yet
new_user = user_form.save(commit=False)
# Se... | d176a5027058124dfd30a247f924776a87f7aba3 | 15,247 |
def error_measure(predictions, labels):
""" calculate sum squared error of predictions """
return np.sum(np.power(predictions - labels, 2)) / (predictions.shape[0]) | 135b3b90047895ecff90aed6f4a37d73ef0ddd17 | 15,248 |
def add3(self, x, y):
"""Celery task: add numbers."""
return x + y | 0d1017953dcdd1a0791afe291ce005247547f198 | 15,249 |
def zscore(dat, mean, sigma):
"""Calculates zscore of a data point in (or outside of) a dataset
zscore: how many sigmas away is a value from the mean of a dataset?
Parameters
----------
dat: float
Data point
mean: float
Mean of dataset
sigma: flaot
Sigma of dataset
... | b11216e50632e2024af0a389184d5e1dba7ed4fd | 15,250 |
from typing import OrderedDict
from typing import Tuple
from re import S
def _create_ast_bilinear_form(terminal_expr, atomic_expr_field,
tests, d_tests,
trials, d_trials,
fields, d_fields, constants,
... | 0929f83f1cfcc6424b00d5b931017ec5af6ffaee | 15,251 |
import math
def asen(x):
"""
El arcoseno de un número.
El resultado está expresado en radianes.
.. math::
\\arcsin(x)
Args:
x (float): Argumento.
Returns:
El ángulo expresado en radianes.
"""
return math.asin(x) | c52f7fc504c1eb02eb240378b14b19b0752c7299 | 15,253 |
def get_mock_response(status_code: int, reason: str, text: str):
"""
Return mock response.
:param status_code: An int representing status_code.
:param reason: A string to represent reason.
:param text: A string to represent text.
:return: MockResponse object.
"""
MockResponse = namedtup... | e1743755c64796e5644a00e26414fc16c110c1b6 | 15,254 |
import traceback
def get_user_stack_depth(tb: TracebackType, f: StackFilter) -> int:
"""Determines the depth of the stack within user-code.
Takes a 'StackFilter' function that filters frames by whether
they are in user code or not and returns the number of frames
in the traceback that are within user... | e02f1ca3ee6aeb765a09806ecded5919a28b5df0 | 15,255 |
def unused(attr):
"""
This function check if an attribute is not set (has no value in it).
"""
if attr is None:
return True
else:
return False | febc225f3924fdb9de6cfbf7eba871cce5b6e374 | 15,256 |
def compute_npipelines_xgbrf_5_6():
"""Compute the total number of XGB/RF pipelines evaluated"""
df = _load_pipelines_df()
npipelines_rf = np.sum(df['pipeline'].str.contains('random_forest'))
npipelines_xgb = np.sum(df['pipeline'].str.contains('xgb'))
total = npipelines_rf + npipelines_xgb
resul... | 7e7b9ea536564b4796dcf9eea6866a8c64ce0c4e | 15,257 |
def get_evaluate_SLA(SLA_terms, topology, evaluate_individual):
"""Generate a function to evaluate if the flow reliability and latency requirements are met
Args:
SLA_terms {SLA} -- an SLA object containing latency and bandwidth requirements
topology {Topology} -- the reference topology object f... | 81fdaa07e3fc21066ab734bef0cc71457d40fb5b | 15,258 |
def latest_consent(user, research_study_id):
"""Lookup latest valid consent for user
:param user: subject of query
:param research_study_id: limit query to respective value
If latest consent for user is 'suspended' or 'deleted', this function
will return None. See ``consent_withdrawal_dates()`` f... | 2295b592a0c1fdaf3b1ed21e065f39e73a4bb622 | 15,259 |
def microarray():
""" Fake microarray dataframe
"""
data = np.arange(9).reshape(3, 3)
cols = pd.Series(range(3), name='sample_id')
ind = pd.Series([1058685, 1058684, 1058683], name='probe_id')
return pd.DataFrame(data, columns=cols, index=ind) | 7bca3cf21f2942819c62c597af8761ec04fa91ba | 15,260 |
from typing import Tuple
def find_next_tag(template: str, pointer: int, left_delimiter: str) -> Tuple[str, int]:
"""Find the next tag, and the literal between current pointer and that tag"""
split_index = template.find(left_delimiter, pointer)
if split_index == -1:
return (template[pointer:], le... | 82d091ef6738ffbe93e8ea8a0096161fc359e9cb | 15,261 |
def hasNLines(N,filestr):
"""returns true if the filestr has at least N lines and N periods (~sentences)"""
lines = 0
periods = 0
for line in filestr:
lines = lines+1
periods = periods + len(line.split('.'))-1
if lines >= N and periods >= N:
return True;
return Fa... | d75c4d241d7c4364c410f2dbae06f1c4d439b14e | 15,262 |
def CAMNS_LP(xs, N, lptol=1e-8, exttol=1e-8, verbose=True):
"""
Solve CAMNS problem via reduction to Linear Programming
Arguments:
----------
xs : np.ndarray of shape (M, L)
Observation matrix consisting of M observations
N : int
Number of observations
lp... | e7f0416e0fa6949e50341b7a0009e574ecf6b0be | 15,263 |
def hamiltonian_c(n_max, in_w, e, d):
"""apply tridiagonal real Hamiltonian matrix to a complex vector
Parameters
----------
n_max : int
maximum n for cutoff
in_w : np.array(complex)
state in
d : np.array(complex)
diagonal elements of Hamiltonian
e : np.array(com... | 9b78d86592622100322d7a4ec031c1bd531ca51a | 15,264 |
def unique_badge():
""" keep trying until a new random badge number has been found to return """
rando = str(randint(1000000000, 9999999999))
badge = User.query.filter_by(badge=rando).first()
print("rando badge query = {}".format(badge))
if badge:
unique_badge()
return rando | 64a60dd420516bdc08a8ac2102b83e0cf92086ef | 15,265 |
def mid_price(high, low, timeperiod: int = 14):
"""Midpoint Price over period 期间中点价格
:param high:
:param low:
:param timeperiod:
:return:
"""
return MIDPRICE(high, low, timeperiod) | 7092d057da86b12b10da6928367aee705e14569a | 15,266 |
import pickle
def load_pyger_pickle(filename):
""" Load pyger data from pickle file back into object compatible with pyger plotting methods
:param filename: File name of pickled output from calc_constraints()
This is only meant to be used to read in the initial constraints object produced by
calc_co... | 23f4d4f2e3cae514ed65d62035277417c9b246a8 | 15,267 |
from typing import OrderedDict
def createitemdict(index, tf2info):
"""Take a TF2 item and return a custom dict with a limited number of
keys that are used for search"""
item = tf2info.items[index]
name = item['item_name']
classes = tf2api.getitemclasses(item)
attributes = tf2api.getitemattribu... | 9f9eceb588c7dc031bab633eadc139095806d38a | 15,269 |
def port_list(request, board_id):
"""Get ports attached to a board."""
return iotronicclient(request).port.list() | 0fcf7fc4db60678c7e5ec4606e9b12174966912f | 15,270 |
def pure_python_npairs_per_object_3d(sample1, sample2, rbins, period=None):
"""
"""
if period is None:
xperiod, yperiod, zperiod = np.inf, np.inf, np.inf
else:
xperiod, yperiod, zperiod = period, period, period
npts1, npts2, num_rbins = len(sample1), len(sample2), len(rbins)
co... | 98b45bbbf50eea9e4dfa39cfd9093ec6fc0c0459 | 15,272 |
def cal_aic(X, y_pred, centers, weight=None):
"""Ref: https://en.wikipedia.org/wiki/Akaike_information_criterion
"""
if weight is None:
weight = np.ones(X.shape[0], dtype=X.dtype)
para_num = centers.shape[0] * (X.shape[1] + 1)
return cal_log_likelihood(X, y_pred, centers, weight) - para_num | fd6f7019dcd6aec7efb21ff159541cee0e56bdfb | 15,273 |
def get_gid(cfg, groupname):
"""
[description]
gets and returns the GID for a given groupname
[parameter info]
required:
cfg: the config object. useful everywhere
groupname: the name of the group we want to find the GID for
[return value]
returns an integer representing t... | ee139abfe8904de1983e505db7bf882580768080 | 15,274 |
from typing import Set
from typing import Dict
from typing import Any
def _elements_from_data(
edge_length: float,
edge_width: float,
layers: Set[TemperatureName],
logger: Logger,
portion_covered: float,
pvt_data: Dict[Any, Any],
x_resolution: int,
y_resolution: int,
) -> Any:
"""
... | 80bef4fc80a22da823365fcdc756b6e35d19cdf2 | 15,275 |
def GetControllers(wing_serial):
"""Returns control gain matrices for any kite serial number."""
if wing_serial == m.kWingSerial01:
airspeed_table = (
[30.0, 60.0, 90.0]
)
flap_offsets = (
[-0.209, -0.209, 0.0, 0.0, 0.009, 0.009, -0.005, 0.017]
)
longitudinal_gains_min_airspeed =... | e9e557909cfb9a7e885f14d20948436b653f4f31 | 15,276 |
def rotate(mat, degrees):
"""
Rotates the input image by a given number of degrees about its center.
Border pixels are extrapolated by replication.
:param mat: input image
:param degrees: number of degrees to rotate (positive is counter-clockwise)
:return: rotated image
"""
rot_mat = cv2... | 6de73e2701fdad422497dd53d271accc1f039128 | 15,277 |
def spec_defaults():
"""
Return a mapping with spec attribute defaults to ensure that the
returned results are the same on RubyGems 1.8 and RubyGems 2.0
"""
return {
'base_dir': None,
'bin_dir': None,
'cache_dir': None,
'doc_dir': None,
'gem_dir': None,
... | 5f220168e2cc63c4572c29c17cb4192a7a5d1427 | 15,278 |
def rdict(x):
"""
recursive conversion to dictionary
converts objects in list members to dictionary recursively
"""
if isinstance(x, list):
l = [rdict(_) for _ in x]
return l
elif isinstance(x, dict):
x2 = {}
for k, v in x.items():
x2[k] = rdict(v)
... | dd09486aa76ee1a27306510a1100502bae482015 | 15,279 |
import requests
from bs4 import BeautifulSoup
def get_pid(part_no):
"""Extract the PID from the part number page"""
url = 'https://product.tdk.com/en/search/capacitor/ceramic/mlcc/info?part_no=' + part_no
page = requests.get(url)
if (page.status_code != 200):
print('Error getting page({}): {}'... | 8cc01b011e23d3bc972cb5552662b55ab998dba0 | 15,280 |
def verbatim_det_lcs_all(plags, psr, susp_text, src_text, susp_offsets, src_offsets, th_shortest):
"""
DESCRIPTION: Uses longest common substring algorithm to classify a pair of documents being compared as verbatim plagarism candidate (the pair of documents), and removing the none verbatim cases if positive
... | d233f3745bdd458fe65cbbdbc056c8cca611d755 | 15,281 |
import multiprocessing
import logging
import multiprocessing.dummy as m
import multiprocessing as m
import itertools
def autopooler(n,
it,
*a,
chunksize=1,
dummy=False,
return_iter=False,
unordered=False,
**ka):
"""Uses multiprocessing.Pool or multiprocessing.dummy.Pool to r... | 489426a16977b632dd16fe351eee167c7eb5fb0d | 15,282 |
def grow_population(initial, days_to_grow):
"""
Track the fish population growth from an initial population, growing over days_to_grow number of days.
To make this efficient two optimizations have been made:
1. Instead of tracking individual fish (which doubles every approx. 8 days which will result O... | 88b8283e5c1e6de19acb76278ef16d9d6b94de00 | 15,283 |
import PySide.QtGui as QtGui
import PyQt5.QtGui as QtGui
def get_QBrush():
"""QBrush getter."""
try:
return QtGui.QBrush
except ImportError:
return QtGui.QBrush | 548226da434077ee1d0d1d2fb4a6762faf5f091d | 15,284 |
def apply_odata_query(query: ClauseElement, odata_query: str) -> ClauseElement:
"""
Shorthand for applying an OData query to a SQLAlchemy query.
Args:
query: SQLAlchemy query to apply the OData query to.
odata_query: OData query string.
Returns:
ClauseElement: The modified query... | 666dd05856db79ce90f29e864aeaf4188bd425d0 | 15,285 |
def get_sql(conn, data, did, tid, exid=None, template_path=None):
"""
This function will generate sql from model data.
:param conn: Connection Object
:param data: data
:param did: Database ID
:param tid: Table id
:param exid: Exclusion Constraint ID
:param template_path: Template Path
... | 45ec23f3e061491ad87ea0a59b7e08e32e5183a2 | 15,286 |
import six
import base64
def bytes_base64(x):
# type: (AnyStr) -> bytes
"""Turn bytes into base64"""
if six.PY2:
return base64.encodestring(x).replace('\n', '') # type: ignore
return base64.encodebytes(bytes_encode(x)).replace(b'\n', b'') | 543b0f1105545cda516890d2d6f4c5a8059c4365 | 15,287 |
def is_planar_enforced(gdf):
"""Test if a geodataframe has any planar enforcement violations
Parameters
----------
Returns
-------
boolean
"""
if is_overlapping(gdf):
return False
if non_planar_edges(gdf):
return False
_holes = holes(gdf)
if _holes.shape[... | 0587cd351fcc7355d0767a404e446d91f8c59d4d | 15,288 |
def bson2uuid(bval: bytes) -> UUID:
"""Decode BSON Binary UUID as UUID."""
return UUID(bytes=bval) | 6fc81f03b6eabee3496bab6b407d6c665b001667 | 15,289 |
def ape_insert_new_fex(cookie, in_device_primary_key, in_model, in_serial, in_vendor):
""" Auto-generated UCS XML API Method. """
method = ExternalMethod("ApeInsertNewFex")
method.cookie = cookie
method.in_device_primary_key = in_device_primary_key
method.in_model = in_model
method.in_serial = ... | 2d10c37f26357ac9714d0dfe91967f4029857cd5 | 15,290 |
import aiohttp
import asyncio
async def get_pool_info(address, api_url="https://rest.stargaze-apis.com/cosmos"):
"""Pool value and current rewards via rest API.
Useful links:
https://api.akash.smartnodes.one/swagger/#/
https://github.com/Smart-Nodes/endpoints
"""
rewards_url = f"{api_... | 34c54c840ed3a412002b99f798c23f495e1eb75d | 15,291 |
def _process_image(filename, coder):
"""Process a single image file.
Args:
filename: string, path to an image file e.g., '/path/to/example.JPG'.
coder: instance of ImageCoder to provide TensorFlow image coding utils.
Returns:
image_buffer: string, JPEG encoding of RGB image.
height:... | 111025b6dddcf7380fd912a84154b551df4be5f3 | 15,292 |
def mnist_reader(numbers):
"""
Read MNIST dataset with specific numbers you needed
:param numbers: A list of number from 0 - 9 as you needed
:return: A tuple of a numpy array with specific numbers MNIST training dataset,
labels of the training set and the length of the training dataset.
... | 627a7fd41047383cd5869fe83efea2c2b0e2d25a | 15,293 |
import six
def _ensure_list(alist): # {{{
"""
Ensure that variables used as a list are actually lists.
"""
# Authors
# -------
# Phillip J. Wolfram, Xylar Asay-Davis
if isinstance(alist, six.string_types):
# print 'Warning, converting %s to a list'%(alist)
alist = [alist]... | bd8115dad627f4553ded17757bfb838cfdb0200b | 15,294 |
def _parse_einsum_input(operands):
"""Parses einsum operands.
This function is based on `numpy.core.einsumfunc._parse_einsum_input`
function in NumPy 1.14.
Returns
-------
input_strings : str
Parsed input strings
output_string : str
Parsed output string
operands : list ... | 8c95c3d842a29fa637e6190e006638420b8a0d83 | 15,295 |
def convert_to_numpy(*args, **kwargs):
"""
Converts all tf tensors in args and kwargs to numpy array
Parameters
----------
*args :
positional arguments of arbitrary number and type
**kwargs :
keyword arguments of arbitrary number and type
Returns
-------
list
... | 8059832fc4841b4cb96dcc77e96dd354dba399c2 | 15,296 |
async def delete_contact(
contact_key: int, hash: str, resource: Resource = Depends(get_json_resource)
):
"""
Delete the contact with the given key.
If the record has changed since the hash was obtained, a 409 error is returned.
"""
try:
await resource.delete(contact_key, hash)
excep... | f984c5ece28ac8b58bb2d2137dcc94e2f3a7bf7c | 15,297 |
import jsonschema
def update_model_instance_meta_schema(request, file_type_id, **kwargs):
"""copies the metadata schema from the associated model program aggregation over to the model instance aggregation
"""
# Note: decorator 'authorise_for_aggregation_edit' sets the error_response key in kwargs
if ... | c6f67f2f6386065919239f7d868797d97aec6874 | 15,298 |
def _calculate_permutation_scores_per_col(estimator, X, y, sample_weight, col_idx,
random_state, n_repeats, scorer):
"""Calculate score when `col_idx` is permuted."""
random_state = check_random_state(random_state)
# Work on a copy of X to to ensure thread-safety i... | 52c49ac3e4fd53490af04c9d862b506214e08f95 | 15,299 |
def get_statement_at_line(source: str, lineno: int, checker):
"""Get statements at line *lineno* from a source string.
:param source: The source to get the statements from.
:param lineno: Line number which the statement must include. Counted from 1.
:param checker: A function that checks each statement... | d2066f5fafa1c20c4b5276e44d82ae95ffa2f59b | 15,300 |
def ptrace(Q, sel):
"""
Partial trace of the Qobj with selected components remaining.
Parameters
----------
Q : :class:`qutip.Qobj`
Composite quantum object.
sel : int/list
An ``int`` or ``list`` of components to keep after partial trace.
Returns
-------
oper : :cla... | a98e7bea41cff00b44534cecac7f86958ef47ebb | 15,301 |
from operator import index
def createConformations(outputfile, forcefield, smiles, sid):
"""Generate the conformations for a molecule and save them to disk."""
print(f'Generating {index}: {smiles}')
try:
mol = Molecule.from_smiles(smiles, allow_undefined_stereo=True)
fftop = Topology()
... | fce6cb1c7620b755a500e76822aa3ac27b7a12f4 | 15,302 |
import numpy
import math
def two_angle_circular_correlation_coef(angles1, angles2, mean1, mean2):
"""
Circular correlation measure. SenGupta 2001
"""
centered_a = angles1-mean1
centered_b = angles2-mean2
sin_centered_a = numpy.sin(centered_a)
sin_centered_b = numpy.sin(centered_b)
sin2... | 6a95f8726f45105c68b9c0b4f8f13191a88734e2 | 15,303 |
from typing import Union
import yaml
def format_data(data: Union[dict, list]) -> str:
"""
:param data: input data
:return: pretty formatted yaml representation of a dictionary
"""
return yaml.dump(data, sort_keys=False, default_flow_style=False) | b4e79a8957995fb8e2eaa549a6a208a48574a598 | 15,304 |
def eval_on_dataset(
model, state, dataset,
pmapped_eval_step):
"""Evaluates the model on the whole dataset.
Args:
model: The model to evaluate.
state: Current state associated with the model (contains the batch norm MA).
dataset: Dataset on which the model should be evaluated. Should already
... | dd2296f80db37687de6fc8a4bcf0046d43cda115 | 15,306 |
def factorize(n):
""" Prime factorises n """
# Loop upto sqrt(n) and check for factors
ret = []
sqRoot = int(n ** 0.5)
for f in xrange(2, sqRoot+1):
if n % f == 0:
e = 0
while n % f == 0:
n, e = n / f, e + 1
ret.append((f, e))
if n >... | bc4b4a26010f2f18c9989acd2b7d81615b21f8db | 15,308 |
import random
def createSimpleDataSet( numOfAttr, numOfObj ):
"""
This creates a simple data base with 3 attributes
The second one is 2 times the first one with some
Gauss noise. The third one is just random noise.
"""
database = []
for i in range(numOfObj):
data = data... | dd4e8005634bd49411a785982fe3112acaf8e544 | 15,309 |
import tqdm
import warnings
def clean_data(
data,
isz=None,
r1=None,
dr=None,
edge=0,
bad_map=None,
add_bad=None,
apod=True,
offx=0,
offy=0,
sky=True,
window=None,
darkfile=None,
f_kernel=3,
verbose=False,
*,
mask=None,
):
"""Clean data.
Par... | d50cb5b723661925c81f215e3bba903b4f9bb56c | 15,310 |
def select_points():
""" Select points (empty) objects.
Parameters:
None
Returns:
list: Empty objects or None.
"""
selected = bpy.context.selected_objects
if selected:
return [object for object in selected if object.type == 'EMPTY']
print('***** Point (empty) object... | 4134277f427518da188d8bcac4d5023d0b39e55a | 15,311 |
def mask_conv1d1(in_channels,
out_channels,
strides=1,
groups=1,
use_bias=False,
data_format="channels_last",
**kwargs):
"""
Masked 1-dim kernel version of the 1D convolution layer.
Parameters:
-------... | 0c06482e36ef55322ed3b52e68f321750843ef01 | 15,313 |
import decimal
def decimal_from_tuple(signed, digits, expo):
"""Build `Decimal` objects from components of decimal tuple.
Parameters
----------
signed : bool
True for negative values.
digits : iterable of ints
digits of value each in [0,10).
expo : int or {'F', 'n', 'N'}
... | c3b67505440600b5e9f3ce944c9018539b32bbf7 | 15,314 |
from typing import Dict
def metadata_update(
repo_id: str,
metadata: Dict,
*,
repo_type: str = None,
overwrite: bool = False,
token: str = None,
) -> str:
"""
Updates the metadata in the README.md of a repository on the Hugging Face Hub.
Example:
>>> from huggingface_hub impor... | 1faf2ae158d598a7538f86ce328ea22b55308507 | 15,315 |
def system_types():
"""
系统类型（工作空间类型）
:return:
"""
return Workspace.sys_types().values() | 968fbf7993d4ad645fe741ac48702440ba01a2e3 | 15,318 |
def get_rnd_simplex(dimension, random_state):
"""
Uniform random point on a simplex, i.e. x_i >= 0 and sum of the coordinates is 1.
Donald B. Rubin, The Bayesian bootstrap Ann. Statist. 9, 1981, 130-134.
https://cs.stackexchange.com/questions/3227/uniform-sampling-from-a-simplex
Parameters
----... | d5e1105655192fe13bcad5e3dd08a7247461d8bf | 15,319 |
def backup_generate_metadata(request, created_at='', secret=''):
"""
Generates metadata code for the backup.
Meant to be called by the local handler only with shared secret (not directly).
"""
if not secret == settings.GAEBAR_SECRET_KEY:
return HttpResponseForbidden()
backup = models.GaebarBackup.all... | 30ae381be8454a1df6b47fd5fc55af68f10e8b1f | 15,320 |
import torch
def contains_conv(module: torch.nn.Module) -> bool:
""" Returns `True` if given `torch.nn.Module` contains at least one convolution module/op (based on `deepcv.meta.nn.is_conv` for convolution definition) """
return any(map(module.modules, lambda m: is_conv(m))) | 0f9ae25fa1189c9c576089c913a5d7d9e2739c78 | 15,321 |
def _construct_cell(empty=False):
"""Constructs a test cell."""
cell = scheduler.Cell('top')
if empty:
return cell
rack1 = scheduler.Bucket('rack:rack1', traits=0, level='rack')
rack2 = scheduler.Bucket('rack:rack2', traits=0, level='rack')
cell.add_node(rack1)
cell.add_node(rack2)... | c1b8016b8ff048ab0ecad8c69f960ce3d099bd8c | 15,322 |
def gaussian_kernel(F: np.ndarray) -> np.ndarray:
"""Compute dissimilarity matrix based on a Gaussian kernel."""
D = squared_dists(F)
return np.exp(-D/np.mean(D)) | 62f97009c791213255d8bdb4efc0fcfa60c20bb0 | 15,323 |
def _parse_yearweek(yearweek):
"""Utility function to convert internal string representations of calender weeks into datetime objects. Uses strings of format `<year>-KW<week>`. Weeks are 1-based."""
year, week = yearweek_regex.search(yearweek).groups()
# datetime.combine(isoweek.Week(int(year), int(week)).w... | 319166595c506a73d125ed53a11433976aa4f106 | 15,324 |
def get_subpixel_indices(galtable, hpix=[], border=0.0, nside=0):
"""
Routine to get subpixel indices from a galaxy table.
Parameters
----------
galtable: `redmapper.Catalog`
A redmapper galaxy table master catalog
hpix: `list`, optional
Healpix number (ring format) of sub-region.... | 5a2d18f79ef8cc478752ef8059c71a512efced9f | 15,325 |
def is_common_secret_key(key_name: str) -> bool:
"""Return true if the key_name value matches a known secret name or pattern."""
if key_name in COMMON_SECRET_KEYS:
return True
return any(
[
key_name.lower().endswith(key_suffix)
for key_suffix in COMMON_SECRET_KEY_SUFF... | b0250f28638a0ad58a3a45dd8e333610fea378d5 | 15,326 |
def showgraphwidth(context, mapping):
"""Integer. The width of the graph drawn by 'log --graph' or zero."""
# just hosts documentation; should be overridden by template mapping
return 0 | 6e2fad8c80264a1030e5a113d66233c3adc28af8 | 15,328 |
def diff_last_filter(trail, key=lambda x: x['pid']):
""" Filter out trails with last two key different
"""
return trail if key(trail[-1]) != key(trail[-2]) else None | 82e67a98a1b09e11f2f1ebd76f470969b2dd1a51 | 15,329 |
def cpu_times():
"""Return a named tuple representing the following system-wide
CPU times:
(user, nice, system, idle, iowait, irq, softirq [steal, [guest,
[guest_nice]]])
Last 3 fields may not be available on all Linux kernel versions.
"""
procfs_path = get_procfs_path()
set_scputimes_n... | 70dd518296bc873add8a7164446e908d80e74174 | 15,330 |
def calc_centeroid(x, network: DTClustering, n_clusters: int):
"""クラスタ中心を計算します.
Notes:
Input x: [batch, sequence, feature, 1]
Output: [n_clusters, hidden sequence, hidden feature, 1]
"""
code = network.encode(x)
feature = code.view(code.shape[0], -1) # [batch, sequence * feature]
... | cf0a158d86105e34ad476dbfb7bc6ff911a65e52 | 15,331 |
def softXrayMono1(eV, k, m, c, rb_mm, bounce, inOff_deg, outOff_deg, verbose):
"""
# calculate premirror and grating angles for NSLS-II soft xray monos
# eV: energy
# k: central line density in mm-1
# m: diffraction order
# c: cff 0 < cff < infinity
# bounce = 'up' or 'down'
# inOff_deg ... | 3309b8ec7e3f5433025c4c676bf2966281df4d02 | 15,333 |
def createHelmholtz3dExteriorCalderonProjector(
context, hminusSpace, hplusSpace, waveNumber,
label=None, useInterpolation=False, interpPtsPerWavelength=5000):
"""
Create and return the exterior Calderon projector for the
Helmholtz equation in 3D.
*Parameters:*
- context (Context)
... | bfb6c139787355d07cb8c82475f34dcc349c55f3 | 15,334 |
def prepare_xrf_map(data, chunk_pixels=5000, n_chunks_min=4):
"""
Convert XRF map from it's initial representation to properly chunked Dask array.
Parameters
----------
data: da.core.Array, np.ndarray or RawHDF5Dataset (this is a custom type)
Raw XRF map represented as Dask array, numpy ar... | a8c4b442f367759237f77571c51e98bd1cc9d53a | 15,335 |
def colorbar_factory(cax, mappable, **kwargs):
"""
Create a colorbar on the given axes for the given mappable.
.. note::
This is a low-level function to turn an existing axes into a colorbar
axes. Typically, you'll want to use `~.Figure.colorbar` instead, which
automatically handle... | 37b0198ea77db887d92ee4fd45e6df73d49f4223 | 15,336 |
import time
def fourth_measurer_I_R(uniquePairsDf):
"""
fourth_measurer_I_R: computes the measure I_R that is based on the minimal number of tuples that should
be removed from the database for the constraints to hold.
The measure is computed via an ILP and the Gurobi optimizer is used to solve the ILP... | a8e29e0a70dfd2e2a4c151ca25b2f7fd528e25f3 | 15,337 |
def is_sublist_equal(list_one, list_two):
"""
Compare the values of two lists of equal length.
:param list_one: list - A list
:param list_two: list - A different list
:return EQUAL or UNEQUAL - If all values match, or not.
>>> is_sublist_equal([0], [0])
EQUAL
>>> is_sublist_equal([1],... | 717b4287e212498ef85719fbf4d8e5437f16db48 | 15,338 |
def black_box_function(x, y):
"""Function with unknown internals we wish to maximize.
This is just serving as an example, for all intents and
purposes think of the internals of this function, i.e.: the process
which generates its output values, as unknown.
"""
return -x ** 2 - (y - 1) ** 2 + 1 | 962c0dd5638ac71ee375f4bb1ba07b2bd241a6e8 | 15,339 |
def file_extension(path):
"""Lower case file extension."""
return audeer.file_extension(path).lower() | 264f8afd0a2328d342693b2ec893706760b5c7ae | 15,340 |
import math
def motion(x, u, dt):
"""
motion model
"""
x[2] += u[1] * dt
x[0] += u[0] * math.cos(x[2]) * dt
x[1] += u[0] * math.sin(x[2]) * dt
x[3] = u[0]
x[4] = u[1]
return x | e33adae2a6c5934dc7e0662570c42292eacbfd89 | 15,342 |
from typing import Union
from typing import Callable
def sweep(
sweep: Union[dict, Callable], entity: str = None, project: str = None,
) -> str:
"""Initialize a hyperparameter sweep.
To generate hyperparameter suggestions from the sweep and use them
to train a model, call `wandb.agent` with the sweep... | 50ba0d79a8fca5d5eba08b4e739845b797c0c839 | 15,343 |
def connection_end_point (id, node_uuid, nep_uuid, cep_uuid):
"""Retrieve NodeEdgePoint by ID
:param topo_uuid: ID of Topology
:type uuid: str
:param node_uuid: ID of Node
:type node_uuid: str
:param nep_uuid: ID of NodeEdgePoint
:type nep_uuid: str
:param cep_uuid: ID of ConnectionEndP... | 76dc345732d3209730b6022ba12cb2ca191e4a40 | 15,344 |
def remove_melt_from_perplex(perplex,melt_percent=-1):
""" Extrapolate high temperature values to remove melt content using sub-solidus values.
The assumption is that alpha and beta are constant and temperature-independent at high temperature."""
Tref = 273
Pref = 0
rho = perplex.rho.re... | 6d2473d7147cdecdcd64cbb7e3beafd3b5df5c6a | 15,345 |
def similarity_score(text_small, text_large, min_small = 10, min_large = 50):
"""
complexity: len(small) * len(large)
@param text_small: the smaller text
(in this case the text which's validity is being checked)
@param text_large: the larger text (in this case the scientific stud... | 8449b5273909382225f9de43d8fb936424d1a43e | 15,346 |
def abline(a_coords, b_coords, ax=None, **kwargs):
"""Draw a line connecting a point `a_coords` with a point `b_coords`.
Parameters
----------
a_coords : array-like, shape (2,)
xy coordinates of the start of the line.
b_coords : array-like, shape(2,)
xy coordiantes of the end of th... | e262b689046ac5dd75152b8472a841c7a1e5db29 | 15,347 |
def get_extensions():
"""
Returns supported extensions of the DCC
:return: list(str)
"""
return ['.hip', '.hiplc', '.hipnc', '.hip*'] | 414391db5cd4f8989967100bae347e741ca4b46c | 15,348 |
def calc_spatially_diffusion_factors(
regions,
fuel_disagg,
real_values,
low_congruence_crit,
speed_con_max,
p_outlier
):
"""
Calculate spatial diffusion values
Arguments
---------
regions : dict
Regions
fuel_disagg : dict
Disa... | 95361bb3f8ba5d3d47cd1a4ad065ec857e291f7b | 15,350 |
def get_set(path):
"""Returns a matrix of data given the path to the CSV file. The heading row and NaN values are excluded."""
df = pd.read_csv(path, sep=';', encoding='latin')
return df.dropna(subset=['PMID1', 'PMID2', 'Authorship'], how='any').values | aa701f440a9535d534826a50e8803fa0095bda25 | 15,351 |
def gaussian_target(img_shape, t, MAX_X=0.85, MIN_X=-0.85, MAX_Y=0.85, MIN_Y=-0.85, sigma2=10):
"""
Create a gaussian bivariate tensor for target or robot position.
:param t: (th.Tensor) Target position (or robot position)
"""
X_range = img_shape[1]
Y_range = img_shape[2]
XY_range = np.arang... | 47fbb46e2e46b1a4cc2cec3906e9c0dfb5282c0e | 15,354 |
def XMLToPython (pattern):
"""Convert the given pattern to the format required for Python
regular expressions.
@param pattern: A Unicode string defining a pattern consistent
with U{XML regular
expressions<http://www.w3.org/TR/xmlschema-2/index.html#regexs>}.
@return: A Unicode string specifyin... | 14072879e11ea0425903be314fdba6fb8bfd2538 | 15,355 |
import fcntl
import termios
import struct
def __termios(fd):
"""Try to discover terminal width with fcntl, struct and termios."""
#noinspection PyBroadException
try:
cr = struct.unpack('hh',
fcntl.ioctl(fd, termios.TIOCGWINSZ, '1234'))
except Exception:
retur... | 78f3450d65a453cfd22c575bbddb77fcfbef1496 | 15,356 |
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