content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Union
def euclidean_distance(p1: Union[Vector, np.array], p2: Union[Vector, np.array]) -> float:
"""Euclidean distance between two 3D points. Support {Vector} and {np.array} as data types.
Arguments:
p1 {Union[Vector, np.array]} -- first 3D point
p2 {Union[Vector, np.array]... | 4ebad943fbb46f34ffbceb43a7b8ec90c8340f6f | 3,608,838 |
def suffix(pattern, k):
"""we define SUFFIX(Pattern) as the last (k-1)-mers in a k-mer Pattern"""
return pattern[-(k - 1):] | d6cec61ba024f551071a6ba9d6409963ff2ffe7d | 3,608,839 |
import time
def wait_for_reload(ctx):
"""
Wait for system to come up with max timeout as 25 Minutes
"""
begin = time.time()
pattern_to_match = r"RP\/0\/RP0\/CPU0\:ios(\([^()]*\))?#|RP\/[0-3]\/RS?P[0-1](?:\/CPU[0-3])?:ios#|rommon \d+ >|XML>"
if not ctx.is_console:
ctx.disconnect()
... | 9e20631997fa89f6b483bf692b7a3cdee0951b59 | 3,608,840 |
def get_api(alias=None):
"""
Returns global API object and if present,
otherwise raise MissingConfiguration exception.
:param alias: Alias of the API to retrieve
:type alias: str
:returns: An API object
:rtype: :class:`infermedica_api.webservice.API`
:raises: :class:`infermedica_api.ex... | 0f7575ea49591f31c123f4acfaa9582fe8386477 | 3,608,841 |
def mol_to_smiles(molecule, isomeric=True, explicit_hydrogen=True, mapped=True):
"""
Generate canonical SMILES with OpenEye.
Parameters
----------
molecule: oechem.OEMol
isomeric: bool
If True, SMILES will include chirality and stereo bonds
explicit_hydrogen: bool
If True, S... | 8e58b5941d81f426114c65a7cc14b05c84fd776f | 3,608,844 |
import torch
def conj(x):
"""
Computes the complex conjugate of complex-valued input tensor (x).
``conj(a + ib)`` = :math:`\\bar{a + ib} = a - ib`
Args:
x (torch.Tensor): A tensor.
Returns:
torch.Tensor: The conjugate.
"""
assert is_complex_as_real(x) or is_complex(x)
... | 2eb4768d90c3c683f6e4513de3ea3fccfffbcdc7 | 3,608,845 |
def runSingleThreaded(runFunction, arguments):
"""
Small overhead-function to iteratively run a function with a pre-determined input arguments
:param runFunction: The (``partial``) function to run, accepting ``arguments``
:param arguments: The arguments to passed to ``runFunction``, one r... | 9cdc34f5e44751667ec5a3bddcf2958b3302f4d1 | 3,608,848 |
def clean_year(year):
"""
Cleaning up year column
"""
if len(year) > 3 and year[0].isnumeric() and year[3].isnumeric() and year[1].isnumeric() and year[2].isnumeric():
return year[:4]
else:
return np.nan | 4bda1034e921bb450a6052b056fa46688e1203d0 | 3,608,849 |
def init_residual_weights_matrix(dim_in, dim_out, borrow=True):
"""Partial isometry initialization."""
if dim_out == dim_in:
weights = np.identity(dim_in)
else:
d = max(dim_in, dim_out)
weights = np.linalg.qr(np.random.randn(d,d))[0][:dim_in,:dim_out]
return theano.shared(np.asar... | acef4bac45b198655be4eb53204e8f4019ce7565 | 3,608,850 |
def calc_velocity(STRIDE_LENGTH, LEG_LENGTH, grav_const):
"""Calculate velocity of the dinossaur
"""
return ((STRIDE_LENGTH / LEG_LENGTH) - 1) * sqrt(LEG_LENGTH * grav_const) | 22b2b047a347ee256adf293d9548e2860ce65b35 | 3,608,852 |
import time
def velocidade(funcao):
"""
Função decoradora: Verifica o tempo que uma função leva para executar
"""
def envolve(*args, **kwargs):
""" Função que envolve e executa outra função """
# Tempo inicial
start = time() # Pega o tempo atual
# Executa a função
... | 2784eed306b4c2c90423bbb1eb05f54ee9cc4ace | 3,608,853 |
def comp(*args) -> bool:
"""Compare string lengths."""
return len(set([len(arg) for arg in args])) == 1 | c3bf069c723b37030531ffbbb84a0a91488a7345 | 3,608,855 |
def DC_LC(z):
"""Method for comoving distance in Linear Coasting model"""
return np.log(1.0+z) | 52d28730a7f8a69bb5aed1cf342608fe3e18ce82 | 3,608,857 |
def clip(num, num_min=None, num_max=None):
"""Clip to max and/or min values. To not use limit, give argument None
Args:
num (float): input number
num_min (float): minimum value, if less than this return this num
Use None to designate no minimum value.
num_max (float): maxim... | fe46f5a200ab24d517c57c5e1d93d4bf86192e13 | 3,608,858 |
def Singleton(name, bases, dict):
"""Use this metaclass on Converter subclasses to create a instance."""
return type(name, bases, dict)() | d7a196f0a645dac8150d9fba46b426882358a9a6 | 3,608,859 |
import collections
def build_model_metrics_aggregator(
model: model_lib.Model, metrics_type: computation_types.Type
) -> computation_impl.ConcreteComputation:
"""Creates a stateless aggregator for client metrics."""
@computations.federated_computation(
computation_types.at_clients(metrics_type))
def ... | 35b55d2808a7bc02659a564b9ca11c9cef108494 | 3,608,861 |
def sparse_std(a, axis=None):
"""Standard deviation of sparse matrix a
std = sqrt(var(a))
"""
return np.sqrt(vars(a, axis)) | 2bc56bbe70da190ccbb0234a7a9b61281058431c | 3,608,862 |
def reduce_with_mantid(ws, data_set, apply_db=False, apply_scaling_factor=False):
"""
@param ws: Mantid workspace
@param data_set: template object
"""
kwargs = {
"InputWorkspace": ws,
"NormalizationRunNumber": str(data_set.norm_file),
"SignalPeakPixelRange": data_set.... | dd1494074b9754c5e85fec1dfebc66489af1367a | 3,608,863 |
def calculate_fraction_of_sn_discovered(
log,
surveyCadenceSettings,
snSurveyDiscoveryTimes,
redshifts,
peakAppMagList,
snCampaignLengthList,
extraSurveyConstraints,
zmin,
zmax):
"""
*Given a list of the snSurveyDiscoveryTimes calculate the... | 70409bba2f7dd2601ed073ad140d75c8ec863942 | 3,608,864 |
def create_model_info(config, loss_func, accuracy):
"""Create a dictionary of relevant model info.
Parameters
----------
param : dict
Any parameter relevant for logging.
accuracy_log : dict
A dictionary containing accuracies.
Returns
-------
type
Description of ... | 25cd8f49a0c7c7fd9b52f3d33c8a8ac24167fbff | 3,608,866 |
def grid_coordinates(roi, x_divisions, y_divisions, position):
"""
Function that returns the grid coordinates of a given position.
To do so it computes, for a given area and taking into account
the number of x and y divisions which is the total amount of cells.
After that it maps the given position to the cell it ... | 1db6e8ed8b1c0abde965e3a5536867ae32ac2228 | 3,608,867 |
def splitmessage(message):
"""Returns a tuple containing the command and arguments from a message.
Returns None if there is no firstword found
"""
assert isinstance(message, str)
words = message.split()
if words:
return (words[0], words[1:]) | d8db56ef55097f9f8858de95ee3d7799c0dc127e | 3,608,868 |
def methods_of(obj):
"""Get all callable methods of an object that don't start with underscore.
returns a list of tuples of the form (method_name, method)
"""
result = []
for i in dir(obj):
if callable(getattr(obj, i)) and not i.startswith('_'):
result.append((i, getattr(obj, i)... | ca22a91b5c60749e7a6b700cb029baab6b64eeb7 | 3,608,869 |
import typing
def implement_insulation_widths(delphin_dict: dict, system: pd.DataFrame) -> typing.List[dict]:
"""Permutate width of system applied materials"""
# look up current material assume system
db_material = get_material_info(system.loc['insulation' + '_00', 'ID'])
insulation_select = ['insula... | 41fcf75890f09cb1568509d20dca0803dbef0db3 | 3,608,870 |
def make_moment_matcher(config):
"""make_moment_matcher(config: dict) -> (MM, dict)
Initialize an MM given `config` and return unconsumed part of `config`.
"""
return _make_mm_from_kwargs(**dict(DEFAULT_PARAMS, **config)) | 10704127ada70d70629c989bd39bb8306032d3ca | 3,608,871 |
def get_reddit_instance(refresh_token=None):
"""Get the interface to talk to Reddit
:param refresh_token: The refresh token given on a previous authentication,
which we can use to continue their session.
"""
user_agent = ('Dust. Giving users the power to remove their content.'
... | 110f17f4406a185e30185fd0eb482af95d3fc94f | 3,608,872 |
def num_allowed_shape_input():
"""
This function receives input from the user -
The total number of matchsticks for division
It returns the user's input
"""
while True:
num_allowed_s = raw_input("ENTER THE NUMBER OF MATCHSTICKS FOR DIVISION: ")
if num_... | 251b26e33671fa26ff5a63b880a7072e619454ce | 3,608,873 |
from textwrap import dedent
async def query(conn: pg.Connection, timestamp) -> Record:
"""
Returns current P2PK address counts by minimal balance.
Assumes snapshots are up to date.
"""
qry = dedent(
"""
select count(*) as total
, count(*) filter (where value >= 0.001 *... | daa5ef5c08c2ca94e3d8bf7486431ee039ef3c7c | 3,608,874 |
from typing import Dict
from bs4 import BeautifulSoup
def check_html_doc(
html_path: str,
all_links: bool = False,
top_root: str = None,
checked_links: Dict[str, UrlResult] = None,
) -> Dict[str, UrlResult]:
"""
Check links in an html document (file).
Parameters
----------
html_pa... | 58c7cb71b67859821bbf5fde38dab85fe5fe2007 | 3,608,875 |
def dec_to_str(total):
"""Converts decimals to strings for more natural speech."""
if total == 0.125:
return "an eighth"
elif total == 0.25:
return "a quarter"
elif total == 0.5:
return "a half"
elif total == 0.75:
return "three quarters"
else:
if total % ... | 05e170eb21f5f0b188a32a634b5c617536c64a11 | 3,608,876 |
from typing import Iterable
def make_location_trees(tables: Iterable[Table]) -> list[LocationTreeNode]:
"""
Return a graph representation of the origins for given tables
Graph is a collection of trees:
B LocationFile
L LocationBlock # table
B LocationBlock # include
... | a67701963170c7b61a8149ac3ccaca89741dd0e3 | 3,608,877 |
def _order_logging_keys(logger, method_name, event_dict): # pylint: disable=unused-argument
"""
Returns an OrderedDict with a spesific key order.
Unnamed keys are alphabetically sorted at the end.
"""
keys = len(SORT_ORDER)
return dict(sorted(event_dict.items(), key=lambda i: SORT_ORDER.get(i[0... | cf0b9f379f9f5a97b8578e5ac5a1a7ba10c2fa37 | 3,608,878 |
def maybe_cast_list(value, types):
"""
Try to coerce list values into more specific list subclasses in types.
"""
if not isinstance(value, list):
return value
if type(types) not in (list, tuple):
types = (types,)
for list_type in types:
if issubclass(list_type, list):
... | c3078c42087103ee8b0a8b3257d345e7d73c0fd7 | 3,608,879 |
def bilinear(image, warp):
"""
Bilinear interpolation.
Parameters
----------
array: nd-array
Input array for sampling.
warp: nd-array
Deformation coordinates.
Returns
-------
sample: nd-array
Sampled array data.
"""
result = n... | 80fe5bde81f878b91418898d26d628f18e152899 | 3,608,880 |
def forxml(uri):
""" Escape XML nasties in a URI """
return xmlutils.cleanxml(uri) | aefc461d7f9d2be53f4ef4fb0a10f9551b0eb334 | 3,608,881 |
def dh_noConv(value, pattern, limit):
"""Helper for decoding a single integer value, no conversion, no rounding."""
return dh(value, pattern, encNoConv, decSinglVal, limit) | 1107ca20edf660d66818bb9e3922cf36c34cefe3 | 3,608,883 |
import re
from typing import OrderedDict
def CustomExtension(observable=None, type='x-custom-observable', properties=None):
"""Decorator for custom extensions to STIX Cyber Observables.
"""
if not observable or not issubclass(observable, _Observable):
raise ValueError("'observable' must be a vali... | 6cbc0adb9191b710abca60804ab9b56ce79556f7 | 3,608,884 |
def read_wi_table(wi_file, wi_column):
"""
Reads in the relative adaptiveness file
"""
tmp_wi_dict = {}
line_number = 0
with open(wi_file, 'r') as infile:
for line in infile:
line_number += 1
if line_number == 1:
continue # skip header
... | 89a1b38e375678b8d221b7386dd742fe6745223c | 3,608,885 |
def uri_encode(data):
"""
Return URI encoding of the passed string.
Args:
data (str): String to encode
Raises:
None
Returns:
TYPE: str
"""
return quote(str(data)) | 3c0b7274f2661a4ba4939404669f51e16f98b11c | 3,608,886 |
def get_accuracy_by_dtype(predictions):
"""
Calculates model accuracy w/r to available data types.
Parameters:
predictions (pandas.Series): model predictions for each sample
Returns:
accuracies (pandas.Series): model accuracy w/r to data types
"""
d_types = list(set(predictions... | e4eb37cdcf6273b6daa3cf0431c88a892a544e25 | 3,608,887 |
def run_retina(params):
"""Run the retina using the specified parameters."""
tmpdir = tempfile.mkdtemp()
print "Setting up simulation"
pyNN.Timer.start() # start timer on construction
pyNN.setup(timestep=params['dt'],max_delay=params['syn_delay'])
pyNN.pynest.setDict([0],{'threads' : params['... | 6180c6e233cdb67cf2109f53611a9736e0393297 | 3,608,888 |
def detect_cycle(init_progs, compiled_moves):
"""Find a cycle length by repeating a list of compiled moves"""
progs = fastdance(list(init_progs), compiled_moves)
cycle = 1
while progs != init_progs:
progs = fastdance(progs, compiled_moves)
cycle += 1
return cycle | 782771b4e218bbe0c352cb503cff4de4b8a0d070 | 3,608,890 |
def get_thickness(system, axis):
"""Get the thickness of an atomic system along a basis vector direction.
Args:
system(ase.Atoms): The system from which the thickness is evaluated.
axis(int): The index of the unit cell basis in which direction the
thickness is evaluated.
Return... | 64e57ba302cc7f64ba45f16b32744522938c92e9 | 3,608,891 |
def affilation_wks(short_name, graph_df):
""" Find wich wks to use by postfix at command
:param short_name: command last word like Basketball_FF1
:param graph_df: pandas df of graph
:return: node_id and link_id
"""
row = get_row_by_keys(graph_df,
key_value=[short_name]... | bb5a63248d45c37275314972f36bcee12877ec31 | 3,608,893 |
def healthcheck():
"""Returns health information"""
return jsonify({
"message": "I feel good."
}) | 0bc6e43fcbb5c15771be417a0831822e9ef34971 | 3,608,895 |
def get_msg_fileslug(msg):
"""
for a given message,
which file/foia is this?
checks entire message thread for category labels
"""
convo = get_conversation(msg['conversationId'])
for msg in convo:
for cat in msg['categories']:
if 'file' in cat:
return cat | aa177140a15c3b26bbb307414be173e4ac7ea12c | 3,608,897 |
import numpy
def empty_like_pinned(a, dtype=None, order='K', subok=None, shape=None):
"""Returns a new, uninitialized NumPy array with the same shape and dtype
as those of the given array.
This is a convenience function which is just :func:`numpy.empty_like`,
except that the underlying memory is pinn... | f2a03e31ea8adbfecf81943b37dd7dc32606cfc7 | 3,608,899 |
from typing import List
import collections
import heapq
def findCheapestPrice(self, n: int, flights: List[List[int]], src: int, dst: int, K: int) -> int:
"""
>>> Dijkstra's Algorithm Variation
The differences are:
1. Also track the number of stops so far;
2. Now since ... | 27a06b0ebce16e3b2389ce28d9a6548bfd1bdf8c | 3,608,900 |
def get_row_col(i, axes):
"""Get the ith element of axes
"""
if isinstance(axes, np.ndarray):
# it contains subplots
if len(axes.shape) == 1:
return axes[i]
elif len(axes.shape) == 2:
nrow = axes.shape[0]
ncol = axes.shape[1]
row_i = i ... | 20c3af7e27072225699d61e16ed7968850205a28 | 3,608,901 |
from typing import Match
from typing import Optional
from typing import Union
async def rise_score_data(payload: dict, match: Match, nickname: Optional[str] = None) -> Union[MessageSegment, str]:
"""
上分数据
- `payload` : 传递给查分器的数据
- `match` : 正则结果
- `nickname` : 用户昵称
"""
dx_ra_lowest = 999
... | b6d6bba6b75779aafcd0ce8cc530c0e086ff43da | 3,608,902 |
from ecdsa import numbertheory, ellipticcurve, util
import base64
def verify_message(address, signature, message):
""" See http://www.secg.org/download/aid-780/sec1-v2.pdf for the math """
curve = curve_secp256k1
G = generator_secp256k1
order = G.order()
# extract r,s from signature
sig = base... | d4d37d5aa93cb2e02ae956204bcb850e14bb649a | 3,608,903 |
from typing import Iterable
from re import T
from typing import Tuple
def grouped(iterable: Iterable[T], n=2) -> Iterable[Tuple[T, ...]]:
"""s -> (s0,s1,s2,...sn-1), (sn,sn+1,sn+2,...s2n-1), ..."""
return zip(*[iter(iterable)] * n) | 38caab13c4e26cb504e3155765316da9235e2a3a | 3,608,904 |
import requests
import json
def get_cards_done(board_id, app_key, user_token, board_name):
"""Fetches and returns the number of cards in the Trello list under the passed name"""
# Constructing GET request to get all lists on the board
url = "https://api.trello.com/1/boards/%s/lists?cards=all&key=%s&token... | e957313ac72fdfc3b1499a09496bece614ba7a6f | 3,608,905 |
import numpy
def w_conj_kernel_fn(kernel_fn):
"""Wrap a kernel function for which we know that
kernel_fn(w) = conj(kernel_fn(-w))
Such that we only evaluate the function for positive w. This is
benificial when the underlying kernel function does caching, as it
improves the cache hit rate.
... | c5ba5bb741e9e696a94535c4373e84268a7ab95d | 3,608,906 |
def loadWorld(worldName, store):
"""
Load an imaginary world from a file.
The specified file should be a Python file defining a global callable named
C{world}, taking an axiom L{Store} object and returning an
L{ImaginaryWorld}. This world (and its attendant L{Store}) should contain
only a sing... | 801c98b5be82e9d5c9ca19db9adbe3078f500674 | 3,608,907 |
def _cosine_dist(u, v, w=None):
"""
:purpose:
Computes the cosine similarity between two 1D arrays
Unlike scipy's cosine distance, this returns similarity, which is 1 - distance
:params:
u, v : input arrays, both of shape (n,)
w : weights at each index of u and v. array of shape (n,)... | d4252f6d79e4b1254bf79d1933ef123ff8fadc16 | 3,608,908 |
import torch
def full(*args, **kwargs):
"""
In ``treetensor``, you can use ``ones`` to create a tree of tensors with the same value.
Example::
>>> import torch
>>> import treetensor.torch as ttorch
>>> ttorch.full((2, 3), 2.3) # the same as torch.full((2, 3), 2.3)
tensor... | 8c6df708b76a799c27a45979e9a43b3d3678ac8d | 3,608,910 |
def funnel(base, test):
"""Tests string against the base string to determine if it can be constructed
by removing one character from the base string
str, str -> bool
>>> funnel("leave", "eave")
True
>>> funnel("eave", "leave")
False
"""
return test in get_shortened_string_list(base) | 03e0b0e223ed9c1fabdf4411eb3ea3a938917d08 | 3,608,911 |
from bs4 import BeautifulSoup
from typing import Dict
from typing import List
def extract_back_matter_from_tei_xml(
sp: BeautifulSoup,
bib_dict: Dict,
ref_dict: Dict,
cleanup_bracket: bool
) -> List[Dict]:
"""
Parse back matter from soup
:param sp:
:param bib_dict:
... | 7f830bcd4588a29281ea96e90fdba5d00f4c75c4 | 3,608,912 |
def kearsley_rotation(reference_sites, other_sites):
"""
Kearsley, S.K. (1989). Acta Cryst. A45, 208-210.
On the orthogonal transformation used for structural comparison
Added by Peter H. Zwart, Nov 3rd, 2006.
Converted to C++ by Gabor Bunkoczi, Apr 2008.
"""
return matrix.sqr(superpose_kearsley_rotation... | 2833704e69a380d1c91c2448cb39a37e49bdb941 | 3,608,913 |
def lc_virus(playing_field):
"""
From https://leetcode.com/contest/weekly-contest-63/problems/contain-virus/
A virus is spreading rapidly, and your task is to quarantine the infected area by installing walls.
The world is modeled as a 2-D array of cells, where 0 represents uninfected cells, and 1 repre... | fb3991a8c19d7cbc3599231fd7fa6a9bf0c5b7e0 | 3,608,914 |
import math
def tan(x):
"""Get tan(x)"""
return math.tan(x) | 112b52faee2f08262515086fe59b2ff978001200 | 3,608,915 |
def gelu_ad_custom(head, in_data, target="cce"):
"""
Automatic differentiation of gelu with customize function.
In order to achieve higher precision, we could also self-define tanh part differentiate with simplify calculation.
"""
dtype = in_data.dtype
const1 = akg.tvm.const(0.044715, dtype)
... | aec594eed9954e79cf16a36a4e50911c9a7991f1 | 3,608,916 |
def ParticleFactory(variables, name="SamplingParticle", BaseClass=parcels.JITParticle):
"""Create a Particle class that samples the specified variables.
The variables that should be sampled will be prepended by ``var_`` as
class attributes, in case there are any namespace clashes with existing
variable... | 5c09acf1cc4a1ce3a3fdad7cbaf026cb5533a467 | 3,608,917 |
def piece_placed(x, y, player, board):
"""This function determines the piece played.
It takes the coordinates of the piece, the player number, and the board.
The pieces are zeros or ones and the function returns the piece on the board based on the number."""
if player == 0:
board[x][y] = 1
e... | ffcd46e11c3e5b0704ed66d6010dfc227106c752 | 3,608,918 |
def get_max_unsecured_debt_ratio(income):
"""Return the maximum unsecured-debt-to-income ratio, based on income."""
if not isinstance(income, (int, float)):
raise TypeError("Expected a real number.")
# Below this income, you should not have any unsecured debt.
min_income = 40000
if income <... | ffff63807842197e2f60ebfd29b54ecf895f6279 | 3,608,919 |
import glob
import shutil
def merger():
""" Function to combine all results csv into a single file. """
#import csv files from folders
path = r'C:/Users/luxon/OneDrive/Research/McQuade/Projects/NSF/OKN/phase1/Work/ml-hte-results-20200207' # Adam's tablet. will vary by OS, computer
# path = r'C:/Use... | 8b96d569cef54636cc009df797061b45c31c264b | 3,608,920 |
def calc_other_bias(probs):
"""
:param probs: list of negative log likelihoods for a corpus
:return: gender bias in corpus
"""
bias = 0
for idx in range(0, len(probs), 16):
bias -= probs[idx + 1] + probs[idx + 3] + probs[idx + 5] + probs[idx + 7]
bias += probs[idx + 8] + probs[id... | 2ceb6788e22277192475218db6e3175f259dc9ba | 3,608,921 |
def pubkey_to_merkletree(key, hashfunction, salt, prefix=""):
"""Convert a full signing-key pubkey into a merkletree dictionary"""
drval = dict()
part1 = key[0]
part2 = key[1]
if len(key) > 2:
breakpoint = int(len(key)/2)
part1, dpart1 = pubkey_to_merkletree(key[:breakpoint], hashfun... | 50e5283a7189aa0202e93201d70f7343719f1f13 | 3,608,922 |
def generate_test_case(num_nodes=500, num_edges=1000, num_communities=5,
connecting_strength_among_communities=0.01, random_state=None):
"""
:param num_nodes: int
:param num_edges: int
:param num_communities: int
:param connecting_strength_among_communities: float
:param r... | 417f4bf0a4c2089796dcdd2de749225c86bdb7b0 | 3,608,924 |
def deprocess_image(x):
"""normalize tensor: center on 0., ensure std is 0.1"""
x -= x.mean()
x /= (x.std() + K.epsilon())
x *= 0.1
# clip to [0, 1]
x += 0.5
x = np.clip(x, 0, 1)
# convert to RGB array
x *= 255
if K.image_data_format() == 'channels_first':
x = x.transpo... | 3ecf94411855e3a212fc0ebe2b60ff76bf30efd3 | 3,608,925 |
def DFFN_3tower_5depth(x_dict, dropout, reuse, is_training, n_classes):
"""Three towers. Each depth 5.
This is the train_paviaU network when input is 23.
20 steps/second.
94.5% on PaviaU 2%, lr 5e-5, within 10k
"""
with tf.variable_scope('DFFN', reuse=reuse):
x = x_dict['s... | 9945092ba2c983b218c0c8d9351aaede6f807a80 | 3,608,926 |
def build_list_all_request(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
"""List scan rulesets in Data catalog.
See https://aka.ms/azsdk/python/protocol/quickstart for how to incorporate this request builder into your code flow.
:return: Returns an :class:`~azure.purview.scanning.core.res... | 4b2cbf297ec89855f794bd0bb9046f525f23a7fa | 3,608,927 |
from typing import Any
import json
def is_jsonable(x: Any):
"""
Check if an object is json serializable.
Source: https://stackoverflow.com/a/53112659
"""
try:
json.dumps(x)
return True
except (TypeError, OverflowError):
return False | 3735de8bd1940d84c185142c0a4387366d7cd9c2 | 3,608,928 |
def plot_cumvar_pca(data,title):
"""Plots the cumulative variance explained by PCA for different
number of components"""
fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(10,8))
pca = PCA().fit(data)
axes[0,0].plot(np.cumsum(pca.explained_variance_ratio_),'bx',alpha=0.6)
axes[0,1].plot(np.cumsu... | e2e6758af3bc203df76f12d60be0b83ad8163036 | 3,608,929 |
def add_number_of_different_roles(dev_type: str) -> int:
"""
INPUT
dev_type - dev_type answer (separeted by ';')
OUTPUT
numeric value - number of different dev types
"""
try:
return len(dev_type.split(';'))
except:
return 0 | 78872b9101b128cc107a0194fc85b353f1d2f836 | 3,608,930 |
import time
def try_models(models, X_train, y_train, preprocessor):
""" Fits different regression models on the given
dataset and evaluates the mean absolute error.
Parameters
----------
models : dict
Dictionary of various regression models to try.
X_train : DataFrame
Traini... | 4d7c1acd19ef425ebb7185cb805ddf805af55619 | 3,608,931 |
def FormatCommentWithAnnotations(comment, type_name=''):
"""Format a comment string with additional RST for annotations.
Args:
comment: comment string.
type_name: optional, 'message' or 'enum' may be specified for additional
message/enum specific annotations.
Returns:
A string with additional ... | accf33ab834e9aeada2c3edfbd83427935e5e130 | 3,608,932 |
def _todict(matobj):
"""
A recursive function which constructs from matobjects nested dictionaries.
"""
dict = {}
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
if isinstance(elem, spio.matlab.mio5_params.mat_struct):
dict[strg] = _todict(elem)
else:... | cc5c594cecdb88183b36ce4be5b8c01424847936 | 3,608,933 |
def create_network_with_bn():
"""Creates a network contains both QConv2D and QDepthwiseConv2D layers."""
xi = Input((28, 28, 1))
x = Conv2D(32, (3, 3))(xi)
x = BatchNormalization()(x)
x = Activation("relu")(x)
x = DepthwiseConv2D((3, 3), activation="relu")(x)
x = BatchNormalization()(x)
x = Activation(... | 22a167a15326cc6d8830c6498402b45c91587c02 | 3,608,934 |
def GetBigQueryTableID(tag):
"""Returns the ID of the BigQuery table associated with tag. This ID is
appended at the end of the table name.
"""
# BigQuery table names can contain only alpha numeric characters and
# underscores.
return ''.join(c for c in tag if c.isalnum() or c == '_') | 0fe659fd3c7ca3df5f061289dad5635841146901 | 3,608,935 |
import timeit
from typing import DefaultDict
def dnscl_rpz(ip_address: str) -> str:
"""Return RPZ names queried by a client IP address.
Args:
ip_address (str): IP address to search.
Returns:
str: Search results found.
"""
start_time = timeit.default_timer()
rpz_dict: Default... | 0916933d64f5fca1145f3c1d31bbc6e8ae82c139 | 3,608,937 |
def rf_local_unequal_int(tile_col, scalar):
"""Return a Tile with values equal 1 if the cell is not equal to a scalar, otherwise 0"""
return _apply_scalar_to_tile('rf_local_unequal_int', tile_col, scalar) | ca9200dd94b786ae258ec2f91dca9934f280dd01 | 3,608,938 |
def get_process_list(node: Node):
"""Analyse the process description and return the Actinia process chain and the name of the processing result
:param node: The process node
:return: (output_objects, actinia_process_list)
"""
input_objects, process_list = check_node_parents(node=node)
output_o... | e14ecb3d43c1329cf707a21bb11c933e84875712 | 3,608,939 |
def run_text(query_string):
"""Run a query that should only return string contents."""
contents, types, result = run(query_string)
assert types is None
assert result is None
return contents | 6201bdde6a5fb42603b3d9a7e67629bb368dfc72 | 3,608,940 |
def Value_getNullValue():
"""Value_getNullValue() -> Value"""
return _yarp.Value_getNullValue() | efae2c7810f2ae277e10d68c0e6640e7d760982b | 3,608,941 |
def transform_landmark(landmark, t):
"""
Function applies transformation t to a single landmark represented by its coordinates in space.
It first creates poly data from its positions and then applies given transformation.
:param landmark: (x, y, z) coordinates of landmark to be transformed
:param t... | f058ba9060ba1e7f718c8c9d87e7cf332592ce27 | 3,608,942 |
import requests
def find_location(location):
"""
Takes a location as a string, and returns a dict of data
:param location: string
:return: dict
"""
params = {"address": location, "key": dev_key}
if bias:
params['region'] = bias
json = requests.get(geocode_api, params=params).j... | 44381de26b3db10e00b0f03be2a5b2da14dcf812 | 3,608,943 |
import token
import time
def sign_url_path(url, secret_key, expire_in=None, digest=None):
# type: (str, bytes, int, Callable) -> str
"""
Sign a URL (excluding the domain and scheme).
:param url: URL to sign
:param secret_key: Secret key
:param expire_in: Expiry time.
:param digest: Specif... | 946d0ae6d704d5a6b9da8517f1b37563471761cb | 3,608,944 |
from typing import Dict
from typing import List
def get_label_colour_map() -> Dict[str, str]:
"""converts a comma seperated list of organizations/repositories into a list
of tuples.
"""
def _preproc(label_colour: str) -> List[str]:
return label_colour.lower().split(sep="/")
return {
... | 440092d8f31fab679761453ec7abc8fb37b5f5d8 | 3,608,945 |
def log_modulo(a, b, m):
"""Computes discrete logarithm i.e.
finds x such that a^x = b (mod m)
Uses Shanks algorithms which takes O(sqrt(m)) time
"""
# find x in form x = np - q for some (n, p)
# => a^x = b ~ a^np = a^q * b
a, b = a % m, b % m
n = isqrt(m) + 1
# compute all a^q * b
... | 6f2c2afd9858ba7d3baaaa2e871cc336396d2042 | 3,608,946 |
def _linear_transform(src, dst):
""" Parameters of a linear transform from range specifications """
(s0, s1), (d0,d1) = src, dst
w = (d1 - d0) / (s1 - s0)
b = d0 - w*s0
return w, b | 7f55a2617721fdefcc724bcb8ce9f880d7bcd846 | 3,608,948 |
def feature_within_s(annolayer, list_of_s):
"""Extracts all <annolayer> from all sentence-elements in list_of_s;
returns a flat list of <annolayer>-elements;
"""
list_of_lists_of_feature = [s.findall('.//' + annolayer) for s in list_of_s]
list_of_feature = [element for sublist in list_of_lists_of_fe... | df6ed3603381a4b8d2ea12fc483fa37ea3068372 | 3,608,949 |
def _permute_facets(facets, ori, ori_map):
"""
Return a copy of `facets` array with vertices sorted lexicographically.
"""
assert_((in1d(nm.unique(ori), ori_map.keys())).all())
permuted_facets = facets.copy()
for key, ori_map in ori_map.iteritems():
perm = ori_map[1]
ip = nm.wh... | 0e09ad2b7555be8e77e564266e3920e5413d851e | 3,608,950 |
def showname(keyvalue):
"""filter koji za neku od prosledjenih kljuceva vraca vrednost"""
key_dict ={'P':'Accepted','C': 'Created','Z': 'Closed','O': 'On Wait'}
return key_dict[keyvalue] | 59453d5e0dd31696b99d01c8b927297adddec10c | 3,608,951 |
def findDomainRanges(r,r_surf_index,W,oldMiddleRange):
"""
Because the islands grow and shrink, the location of the boundaries are in
constant flux. This code figures out the boundaries and returns the
indices associates with all three regions.
"""
innerBCIndex=findNearest(r,r[r_surf_index]-W/2)
if innerB... | db213209e4bed1daf9d3e18ceb8f0e30db5d875e | 3,608,952 |
def create_taperedvia(AR, dr, Nseg):
"""Return the areas and view factor of a rectangular trench, where
the vertical wall is divided into identical sections.
Parameters
----------
AR : float
Aspect ratio, defined as the width to top diameter ratio
dr : Float
Ratio between the bo... | 408077ec50272236da497b93ec897213ae6b30eb | 3,608,953 |
import torchvision
import torch
def get_train_val_loaders(train_dir,
collate_fn,
height,
width,
no_data_augmentation=False,
max_trainset_size=np.infty,
seed=0,
... | 675be081fa34ad2c282674dbb59a9e81cb36581d | 3,608,954 |
def adjust_learning_rate(optimizer, epoch, gammas, schedule):
"""Sets the learning rate to the initial LR decayed by 10 at 600 and 900 epochs"""
lr = args.lr_
assert len(gammas) == len(schedule), "length of gammas and schedule should be equal"
for (gamma, step) in zip(gammas, schedule):
if (epoc... | 5fb413f4403aa9606758134929f684d2dd03a621 | 3,608,955 |
def get_organizations_from_ckan(portal_url, verify_ssl=False,
requests_timeout=REQUESTS_TIMEOUT):
"""Toma la url de un portal y devuelve su árbol de organizaciones.
Args:
portal_url (str): La URL del portal CKAN de origen.
verify_ssl(bool)... | fd280b3106d84b66c893877657f5ec0b3b2dc635 | 3,608,956 |
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