content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def is_gzip_file(view):
"""
Given a view, determine if that view (probably) contains a gzipped file
or not. This is currently based on a combination of the extension and the
file being a binary file with the right magic bytes.
"""
return (view.encoding() == "Hexadecimal" and
view.sub... | f457e373d59d7688a9ec3e5e64b2ab6c92115d25 | 61,188 |
from typing import Callable
import functools
def get_v_panel_from_i(cell_param=np.array([6.48000332e+00, 6.37762333e-10,
8.45318984e-04, 1.65194938e+03,
3.14194723e-02]),
I_min: float = -4, I_max: float = 7,... | 6fa736bffc1f32df41364442249195a0b066ac4a | 61,190 |
import json
def get_project(project_id: int) -> json:
"""
:param project_id:
:return:
"""
query_result = db.session.query(Project).filter(Project.id == project_id).all()
if len(query_result) == 1:
info = {
"name": query_result[0].name,
"description": query_result[0].description
}
return j... | d25670cad7d2ce74ddc5706d333d570b090c2006 | 61,191 |
def fetchone_to_dict(sql, params=None, db='default'):
"""
返回一行数据
:param sql: sql语句
:param params: sql语句参数
:param db: Django数据库名
:return: 例如：{"id": id, "username": 'username', "first_name": 'first_name'}
"""
cursor = connections[db].cursor()
cursor.execute(sql, params)
desc = curs... | 79ef4f0c9e66fda994aa5d4e223a6872f92e515e | 61,192 |
def make_zip_handler(zipfilename, max_age=None, public=None):
"""Factory function to construct a custom ZipHandler instance.
Args:
zipfilename: The filename of a zipfile.
max_age: Optional expiration time; defaults to ZipHandler.MAX_AGE.
public: Optional public flag; defaults to ZipHandler.PUBLIC.
... | a9833e0a07f36060efbb06099493d0a87202ce55 | 61,193 |
def rotmatrix(ang, raxis, axis=0):
"""Construct a 3d rotation matrix representing a rotation of
ang degrees around the specified rotation axis raxis, which can be "x", "y", "z"
or 0, 1, 2. If ang is a scalar, the result will be [3,3]. Otherwise,
it will be ang.shape + (3,3)."""
ang = np.asarray(ang)
raxis = raxi... | 767484648c70ff961d223e23d226ce44dabd1afe | 61,194 |
def watershed_group_add(request):
"""
Controller for adding a watershed_group.
"""
if request.is_ajax() and request.method == 'POST':
#get/check information from AJAX request
post_info = request.POST
watershed_group_name = post_info.get('watershed_group_name')
watershed_g... | ad18b5667f0effe6fb8bd9dd787ce967d418816e | 61,195 |
def is_trivial_pair(p):
"""Is the critical pair trivial?"""
u, v = p; return u == v | ee4b42a9f1345c7260c3992db4c2445b32273a01 | 61,196 |
def multiplicativeAttraction(vGamble,pGamble,timePressure,neta,framing,x,need,c):
"""Here we assume time prssure with enhance the framing effect, and an additive risk attraction term """
expectation = pGamble * vGamble + 0
varGamble = pGamble * (vGamble - expectation) ** 2 + (1 - pGamble) * (0 - expectation... | c1c96ac867162c1c78033550641719be430e468b | 61,198 |
def pairs_to_dict(response, decode_keys=False, decode_string_values=False):
"""Create a dict given a list of key/value pairs"""
if response is None:
return {}
if decode_keys or decode_string_values:
# the iter form is faster, but I don't know how to make that work
# with a str_if_byt... | 3303d4549e23bc2c1b360091f8f2d97cf50d0f65 | 61,199 |
def regularization_kernel(COEF_in, sigma):
"""
Inputs:
COEF Biot-Savart Kernel
sigma regularization radius
Outputs:
KAPPA Regularization Kernel
"""
COEF = COEF_in.astype(np.float32)
COEF_MAG = np.abs(COEF)
# Make sure the magnitude doesn't go to ... | 90f5aafa1c94e75a98fd1d184d73e21040f66bd3 | 61,200 |
def load_wikitext(path, name="2", eos=None):
"""Loads the WikiText dataset
Returns the train, validation test set, each as a list of sentences
(each sentence is a list of words)
Args:
path (str): Path to the folder containing the
``wikitext-{2|103}-v1.zip`` file
name (str):... | f4e45e3b49302f1cb88cfe64c4fa3956c6a6d55e | 61,201 |
def response(code=200, data=None, error=None, msg=None):
"""
:param code: 状态码
:param data: 返回数据
:param error: 错误信息
:param msg: 提示信息
"""
if code is not None and code >= 400:
error = HTTP_STATUS_CODES.get(code, "unknown error")
pay_load = {
"code": code,
"data": d... | 8043dd56a0928895f9397c39782feeb38fc59028 | 61,202 |
def normalize_meaning(source_string):
"""Escape all HTML tags if any"""
flag = 0
index = 0
# Trash is a list containing all the html tags found in the source string
trash = []
for c in source_string:
if c == '<':
# Flag the start of the html tag
flag = index
... | be22cbcbf09c4d5705f5d854e4b562d570d3f216 | 61,203 |
def verify_vxlan(device, enable_password):
"""
Verifies the interface vxlan 1 status is up/up.
Args:
device (jsonrpclib.jsonrpc.ServerProxy): Instance of the class jsonrpclib.jsonrpc.ServerProxy\
with the uri 'https://%s:%s@%s/command-api' %(username, password, ip).
enable_passw... | d2f7d7455b675260448b599e21e6bcb96fe10f2a | 61,204 |
def get_heart_rate_units_str():
"""Returns the units in which heart rate is displayed."""
return "bpm" | f7a17f7d6d71124e53a72cfdc8192c78b7beba10 | 61,205 |
def cut_list(list, length):
""" This function allows to cut a list into parts of a certain length.
It returns a new list which takes less memory and contains for each index a part of the initial list.
Args :
list : list of the images path of the whole database\n
length (int)... | 210a1ad7db3058396ad32493a91b5c70176fb77c | 61,206 |
import json
def _convert_vars_to_json(env_dict):
"""Converts 'variables' in the given environment dict into string."""
if ('variables' in env_dict and
isinstance(env_dict.get('variables'), dict)):
env_dict['variables'] = json.dumps(env_dict['variables'])
return env_dict | 8dbf0456fd29833ff42570e011a45b368aa2ac0c | 61,208 |
def signal_smooth(signal, method="convolution", kernel="boxzen", size=10, alpha=0.1):
"""Signal smoothing.
Signal smoothing can be achieved using either the convolution of a filter kernel with the input
signal to compute the smoothed signal (Smith, 1997) or a LOESS regression.
Parameters
---------... | c85d8a47f971a037c748c76e3aafea425ede7fd6 | 61,209 |
def getprimarymode(image_list, bid):
"""Determine the primary mode of the science frame for the block
"""
primary_mode=None
instr=[]
obsmode=[]
detmode=[]
for img in image_list:
if img[10]==bid:
instr.append(img[5])
obsmode.append(img[6])
detmode.append(img[7])... | f50f585fb9e9888be0a478c230767f8ee7907fac | 61,210 |
from typing import List
def retrieve_all_source_files(source: str) -> List[str]:
"""Utility to aggregate all source files for future processing
Args:
source: The relative path to your source directory
Returns:
A list of existing Python files from your source directory
"""
all_fi... | 4fd710395fe05fce3a4f8dddc29a464175a7b121 | 61,211 |
import math
def day_of_the_week(year, month, day):
""" given a calendar date, the routine returns a tuple with the Day Of The Week in number and in plaintext
0 for Sunday 1 for Monday and so on up to 6 Saturday
"""
doth = {0:'Sunday', 1:'Monday', 2:'Tuesday',
3:'Wednesday', 4:'Thursday... | 7b84b17b435fe92cea17246a07b8289ac8eba97a | 61,212 |
def convert_row(row):
"""
prints an array of 0's,1's,and 2's as their tictactoe characters
"""
row_string = ''
for num in row:
row_string+=(convert_num(num) + '|')
return row_string | 21894eb0ea59b6637a27a9d56f5070f4977708b3 | 61,213 |
from typing import Optional
async def uninstall(
skill: Uninstall = Body(
default=None,
description="Information about the skill to uninstall",
example='{"skill": "https://github.com/JarbasSkills/skill-parrot.git",\
"dialog": "the skill-parrot skill has been uninstalled",... | 5f9a4d702da31f14f68e5b554c0d9f591d96b893 | 61,214 |
def sgd(step_size):
"""Construct init and update step functions for stochastic gradient descent.
Args:
step_size: positive scalar, or a callable representing a step size schedule
that maps the iteration index to positive scalar.
Returns:
An (init_fun, update_fun) pair.
"""
step_size = make_sch... | 320f7b1042957c1ac9c87426ff49bfa0debcd12b | 61,215 |
def match_hobbies(hobbies_flat,h1,h2,num_hobbies,num_matches):
"""
Match hobbies between two persons seating next to each other.
Note that hobby 0 is a dummy value and should be ignored.
"""
return [num_matches == sum([(Element(hobbies_flat,h1*num_hobbies+i) != 0) *
(Element(hob... | 36e20a8487b0469487b7f7284c9e414a7ed2ddf3 | 61,216 |
def get_payload() -> bytes:
"""
This function returns the data to send over the socket to the server.
This data should cause the server to crash and generate a core dump. Make
sure to return a `bytes` object and not an `str` object.
WARNINGS:
0. Don't delete this function or change it's name/p... | d40adaccaa860a734d697c426fa7bdad53e3753f | 61,217 |
def announce_challenge(p1, p2):
"""Generates an announcement to be posted by the discord bot as an embed
Params:
p1: player1 (the challenger) as a discord.Member object.
p2: player2 (the challengee) as a discord.Member object.
return:
Dictionary with content, title, ... | 15f9510f0423ae3291e63f58de82bfbef66805af | 61,219 |
def convert(s):
"""Convert hex to binary or vice versa."""
if flag_reverse:
try:
v = int(s, 10)
except ValueError:
return s
return "0x" + hex(v)[2:].zfill(8)
else:
try:
v = int(s, 16)
except ValueError:
return s
return bin(v)[2:].zfill(8) | ec933881cb45b7950ca0f30c3bb3814677a4e995 | 61,220 |
from typing import Union
from pathlib import Path
from typing import Optional
def first(filename: Union[str, Path], preamble_length: int = 25) -> Optional[int]:
"""
Return the first number that cannot be written as the sum of two numbers
among the previous `preamble_length` numbers
If no such set of ... | be3d8ad7efbf092d65f3fd0c4dc3d00222ac9439 | 61,221 |
from datetime import datetime
def getTimestring():
"""Return int only string of current datetime with milliseconds."""
(dt, micro) = datetime.utcnow().strftime('%Y%m%d%H%M%S.%f').split('.')
dt = "%s%03d" % (dt, int(micro) / 1000)
return dt | c94e83fd39d00c29a909626e3851e36d89baf06e | 61,222 |
def listing(characters, outstream, *, metadata=None, partial=False, **kwargs):
"""
Create an html character listing
Args:
characters (list): Character info dicts to show
outstream (stream): Output stream
metadata_format (string|None): Whether to include metadata, and what
... | 25e2da382a60f28d4a42a144eff400bb8595834c | 61,223 |
from typing import Optional
def format_fields_as_txt(
additional_fields: Optional[FieldDocCollection] = None,
field_prefix: str = '',
color: bool = False) -> str:
"""Return a formated string containing the documentation about the audio
fields.
"""
if additional_fields:
... | 8507d550013ce501feefe4c58194433661446e03 | 61,224 |
def PPTS(y_true,y_pred,gamma):
"""
Compute peak percentage threshold statistic
args:
y_true:the observed records
y_pred:the predictions
gamma:lower value percentage
"""
# y_true
r = pd.DataFrame(y_true,columns=['r'])
# print('original time series:\n{}'.format(r))
... | 22775d5356f7f754dee21beb53621e18c64e26f3 | 61,225 |
def trapz(f, x):
"""
Numerically integrates f(x) using trapezoid method.
"""
return np.trapz(f, x) | e0355ddcb6b841ab5392483e325e54ba390c1cbe | 61,226 |
def dpsi_periodic(x, t, n=1):
"""
derivative of Stream function for periodic boundary conditions
"""
return -n * 2 * pi * np.sin(n * 2 * pi * x + 0.5 * t / (n * pi)) | 8395eb5fce4e3a951c7d335fed0d2bef1ad0e847 | 61,227 |
def flatten_probas(preds, targets, ignore=None):
"""
Flattens predictions in the batch
"""
B, C, H, W = preds.size()
preds = preds.permute(0, 2, 3, 1).contiguous().view(-1, C) # B * H * W, C = P, C
targets = targets.view(-1)
if ignore is None:
return preds, targets
valid = (targ... | 4765c2b22ab526e762fa5877ca30299b4de851b7 | 61,228 |
def _convert_partials_type(type_: dtypes.dtype) -> _ir.op.MatMulPartialsType:
"""Convert the dtype to an _internal.ir partials type
Args:
type_ (dtypes.dtype): The top level dtype
Raises:
ValueError: If not float[16|32]
Returns:
_ir.op.MatMulPartialsType: The internal partials... | cd5ee5540a5666206770aa754f147badc8ced231 | 61,230 |
from typing import Union
from typing import Optional
from typing import Iterable
def scatter_nd(indices: Union[ivy.Array, ivy.NativeArray], updates: Union[ivy.Array, ivy.NativeArray],
shape: Optional[Iterable[int]] = None, tensor: Optional[Union[ivy.Array, ivy.NativeArray]] = None,
reduc... | e6b13713ee3fc7d540ab872cb31792cdb4c055c3 | 61,231 |
import torch
def dcca_model(stim_data, resp_data, o_dim, learning_rate=1e-3, use_all_singular_values=False, epoch_num=12, batch_size=2048, reg_par=1e-4, dropout=0.05, best_only=True, path_name="", seeds=np.ceil(np.random.rand(10)*100)):
"""
ARGUMENTS:
stim_data : A THREE ELEMENT LIST OF STIMULI DAT... | 92228ddf99177965035c625ab7fa9edec3e7ecb1 | 61,232 |
def _get_ids(tokens, tokenizer, max_seq_length):
"""Token ids from Tokenizer vocab"""
token_ids = tokenizer.convert_tokens_to_ids(tokens)
input_ids = token_ids + [0] * (max_seq_length - len(token_ids))
return input_ids | 114053372ec61135c6214bc351a282d1a81432f3 | 61,234 |
def returnInstance(Type,runInfoDict, caller):
"""
Returns an object construction pointer from this module.
@ In, Type, string, requested object
@ In, caller, object, requesting object
@ Out, __interFaceDict, instance, instance of the object
"""
if Type in knownTypes():
return __interFaceDict[T... | 6c0931f5af73f1145e189a2df46ba352cff0f741 | 61,235 |
import csv
def getExternalAuthors(filename):
"""
Returns the external authors of the network. The first column minus the ones that appear on the second column
"""
inside_authors = {}
outside_authors = {}
with open(filename, "r") as fp:
reader = csv.reader(fp, delimiter=',')
for... | 2774c3af691ed33c3070dbd7d28f6629afa947fa | 61,236 |
def remove_uptake_and_secretion_reactions(reactions):
"""
Remove all the uptake and secretion reactions added to a model, eg. when you are running multiple simulations.
:param reactions: The reactions dict
:type reactions: dict
:return: The enzymes, compounds, and reactions data structure
:rtype... | 7f3e412fc98fc28b054557b2c4795c251d3facd1 | 61,237 |
def to_float(num):
"""
引数をFloatに変換します。
"""
return float(num) if type(num) is str else num | b2692edb3037359853bcd22fa5059efa20976a70 | 61,238 |
def get_changed_files(base_branch='develop'):
"""
Return a list of changed file paths against the `base_branch`.
Or locally only if `base_branch` is None.
Raise an exception on errors.
"""
# this may fail with exceptions
cmd = 'git', 'diff', '--name-only',
if base_branch:
cmd += ... | 77ca5f4d993a476c45b6a5cac2b373a8aacce9c9 | 61,239 |
def H(z):
"""
H(z): Function to return the Hubble parameter as measured
by an observer at redshift, z.
"""
result = 100.0*E(z)
return result | 6c417ad65a3e9659c0e0c585db4a49dbad47dbbc | 61,240 |
def get_fast_slow_calc(distance, **kwargs):
"""returns FastSlow instance for a given distance name"""
return fast_slow_dist(distance, **kwargs) | 395d7419a508d66c090b8ca5fc673287fdf8ee00 | 61,241 |
def to_collection(spocs):
"""
Transforms a list of spocs to a sponsored collection dictionary.
AdZerk does not support fields for a collection. We set them on all creatives and get them from an arbitrary one.
:param spocs: A list of spocs
:return: A dictionary with collection fields (title, flight_i... | c5c01739c4790d1b5243bc4b7d7d349fd3c5c6c5 | 61,242 |
def silence(score0, score1, leader=None):
"""Announce nothing (see Phase 2)."""
return leader, "" | 6f9360400205b244667075e65f3a747b5f98ba16 | 61,243 |
def random_split(dataset_size, split_ratio=0.9, seed=0, shuffle=True):
"""random splitter"""
np.random.seed(seed)
indices = list(range(dataset_size))
np.random.shuffle(indices)
split = int(split_ratio * dataset_size)
train_idx, valid_idx = indices[:split], indices[split:]
log.info("train_set... | 50f430af94c4537b556fe48792b876d6a86e0668 | 61,244 |
import requests
def wms_getcapabilities(response, hostname, params, script_root, permissions):
"""Return WMS GetCapabilities or GetProjectSettings filtered by
permissions.
:param requests.Response response: Response object
:param str hostname: host name
:param obj params: Request parameters
:... | a8c7131d7a0fb2baf64b5f079e2c4ec5a788b43c | 61,245 |
def get_peds_in_area(traj_data: pd.DataFrame, measurement_area: pygeos.Geometry) -> pd.DataFrame:
"""Filters the trajectory date to pedestrians which are inside the given area.
Args:
traj_data (pd.DataFrame): trajectory data to filter
measurement_area (pygeos.Geometry):
Returns:
F... | 43cae4cb164c4b075adf32fb4867f340672a3969 | 61,246 |
def volt2SPL(volt, gain, sensitivity=-35, dBref=94):
"""
convert volt amplitude to instantaneous sound pressure level SPL
Parameters
----------
volt : 1d ndarray of integers floats
Vector containing the sound waveform in volt
gain : integer
Total gain applied to t... | 2195ffb9ec21b16bb7f15fc3888461b1226fcc9f | 61,247 |
def estimate_AR1_halflife(df):
"""Estimate AR(1) half-life of columns in DataFrame"""
if not isinstance(df, (pd.DataFrame, pd.Series)):
raise TypeError(f"Type {type(df)} not supported (DataFrame/Series)")
data = df.to_numpy()
if data.squeeze().ndim == 2:
return np.array([estimate_AR1_ha... | 7e8c00f18d9bbca71326555879ef15b252708b23 | 61,248 |
def infer_species_from_prefix(name):
"""
Trying to parse prefixes of alleles such as:
HLA-A
but also ones with dashes in the species prefix:
H-2-K
and also those lacking any dashes such as:
H2K
...we also need to consider that alleles, haplotypes, etc may come
immediat... | f49048202c9fc065a932bce5bf1f1b9292f445e9 | 61,250 |
from functools import reduce
def merge(s, p):
"""Merge union-find s with permutation p (as cycles)."""
def find(x):
while s[x] != x:
x = s[x]
return x
def union(x, y):
x = find(x)
s[find(y)] = x
return x
for cycle in p:
reduce(union, cycle)
... | b65e1151c678fc9627840799770499b5fe91f71e | 61,251 |
from typing import Tuple
def _distorted_bounding_box_crop(
image_bytes: tf.Tensor,
*,
jpeg_shape: tf.Tensor,
bbox: tf.Tensor,
min_object_covered: float,
aspect_ratio_range: Tuple[float, float],
area_range: Tuple[float, float],
max_attempts: int,
) -> tf.Tensor:
"""Generates cropped_i... | 2dccd66df93f063f46750b8c88a1656178f7ec68 | 61,252 |
def pluralize( string ):
""" Correctly convert singular noung to plural noun. """
if string.endswith('y'):
plural = string[:-1] + 'ies'
elif string.endswith('us'):
plural = string[:-2] + 'i'
else:
plural = string + 's'
return plural | 7179c02f71f0044735c6573d64784456fcabc6cc | 61,253 |
import csv
def get_sampleID_and_sex(args):
"""
Retrieve sample IDs (samples with "-T*") and patient sex from title file
"""
sample2sex = {}
with open(args.title_file_path, "rU") as titleFile:
tfDict = csv.DictReader(titleFile, delimiter="\t")
for row in tfDict:
if row[... | a3cc0419bfcb0eb658700f4d49981887ccc7a69f | 61,254 |
def effectiveInterval(A,B,a,bcomp):
"""
Determines the range along segment a that is closer to the component bcomp
than to either adjacent component.
Parameters
----------
A : [(x,y),(x,y)...]
The main polyline.
B : [(x,y),(x,y)...]
The other polyline
a : Integer
... | 564ca7e25fc1bfee0906b1f9b2a328a652201a14 | 61,255 |
def clamp(val, min, max):
"""Clamp the value between min and max."""
if val <= min:
return min
elif val >= max:
return max
return val | 57411c7d7fd53508889606e820c8a4158f551da1 | 61,256 |
import torch
def validate_one(input, target, model):
"""Perform validation on the validation set"""
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1... | 0e654355794c2e5d2d70c570d6959aa1cd56e19b | 61,257 |
def getNextFirstCharColumn(row, x):
"""
Gets the first right pixel culumn of a char in a text row image
Parameters
----------
row(numpy.ndarray) : Text row image
x(int) : Starting x coord to search
Returns
-------
int : X coord indicating the columns starting pixel of char
Use... | 718500f3d5ed29b2122e0b6b8d7369a68c4dc222 | 61,258 |
def image(path, x=None, y=None, anchor='center', **kwargs):
"""
Function to create an image.
:param path: local file path or url of image to upload
:type path: str
:param args: left top corner of image and width and height of image
:type args: two Tuples (left, top), (width, height) or four int... | 2fb8365c4e1572b4dc136a4b8fffe1c111bec773 | 61,259 |
def reverse_key_value(orig_dict):
"""
DESCRIPTION
-----------
Reverse the key value pairs of a dictionary object.
PARAMETERS
----------
orig_dict : dict
A dictionary object.
RETURNS
-------
rev_dict : dict
A dictionary with the values of the original dictionar... | 92599452e511193ce34c4421b13029023fb9c762 | 61,260 |
from typing import cast
def validate_integer(value: str) -> bool:
"""
Validates an integer value.
"""
return cast(bool, INTEGER_RE.match(value)) | ee1f75ca864e57ec53633963958c7780e48de632 | 61,261 |
import numpy
def make_labels(X):
"""Helper function that generates a single 1D array with labels which
are good targets for stock logistic regression.
Parameters
==========
X : numpy.ndarray
The input data matrix. This must be an array with 3 dimensions or an
iterable containin... | d10ac3b9213bd6a2d43d24059295ff2779b1cd39 | 61,262 |
import urllib
def location_html(location):
"""
Gets the html for a location object.
"""
if not location:
return u''
html = u''
if location.name:
address = location.get_display(exclude_fields=['phone']).encode('utf-8')
address = urllib.quote_plus(address)
url ... | 535a88d8b62b0ae052b89c1878135d691bf34134 | 61,263 |
from astropy.io import fits
def dendro_import_fits(filename):
"""Import 'filename' and construct a dendrogram from it"""
with fits.open(filename) as hdus:
data = hdus[1].data
index_map = hdus[2].data
newick = ''.join(chr(x) for x in hdus[3].data.flat)
return parse_dendrogram(newi... | a191ee5d275acd81e1bf4def6501828a6e83e61f | 61,264 |
def cv_h(P, h):
""" Specific isochoric heat capacity [kJ / kg K]"""
return cv(P, T_h(P, h)) | 2879d9df227156998b8c6e46163b3c8017a791c8 | 61,266 |
import unittest
def load_tests_from_testcase(test_case_class, args):
"""
load tests from testcase class
Args:
test_case_class: TestCase class object
args: parse args
Returns: unittest.TestSuite()
"""
if 'all' in args.case_list:
# Load all test cases
# test_suit... | 1c5384ec9d3296e1c7c18e2848a8f32089ace675 | 61,268 |
import torch
def train(_model: torch.nn.Module, _criterion: torch.nn.MSELoss, dataset_train: DataLoader, dataset_test: DataLoader,
_optimizer: torch.optim.Optimizer, n_epochs: int, device: torch.device, test_metrics: dict, log):
"""
Trains the given model according to a certain criterion and logging... | 5f98faf9a0ef3594f0edf5b5af57d3a35343439b | 61,269 |
def sweep_lin(f0, f1, duration, fs):
"""Generates a linear sine sweep
Parameters
----------
f0: float
The frequency [Hz] at which to begin the sine sweep
f1: float
The frequency [Hz] at which to stop the sine sweep
duration: float
The length of time [seconds] over which ... | 1bf11d764ded84ba20015766f7799c6b53830107 | 61,270 |
import cudf._lib as libcudf
from cudf.core.column import NumericalColumn
from cudf.core.buffer import Buffer
def prefixsum(vals):
"""Compute the full prefixsum.
Given the input of N. The output size is N + 1.
The first value is always 0. The last value is the sum of *vals*.
"""
# Allocate out... | 7ebb33602736c84e78750c8e755aaaac8e547b2c | 61,272 |
from typing import List
from typing import Dict
def BellmanFord(graph: List[Dict[str, int]], V: int, E: int, src: int) -> int:
"""
Returns shortest paths from a vertex src to all
other vertices.
"""
mdist = [float("inf") for i in range(V)]
mdist[src] = 0.0
for i in range(V - 1):
f... | e94c56b917248dfa2babb648baac653f02ddadad | 61,273 |
def build_factorial(factor_count, run_count):
"""Builds a regular two-level design based on a number of factors and runs.
Full two-level factorial designs may be run for up to 9 factors. These
designs permit estimation of all main effects and all interaction effects.
If the number of runs requested is ... | a6e324fbeeb59733ea849e2e2b404b869ab1f729 | 61,275 |
def say_hello(name):
""" Greeter Endpoint"""
resp = handlers.greeter(name)
return Response(resp, mimetype='plain/text') | 9f83c11c37ea668aa10c97d884da4841b2a857f4 | 61,276 |
def GetAlertProperties(services, cnxn, project_id, incident_id, trooper_queue,
msg):
"""Create a dict of issue property values for the alert to be created with.
Args:
cnxn: connection to SQL database.
project_id: the ID of the Monorail project, in which the alert should
be crea... | 3af6c0c5cb615629b86726b157393823bca00afd | 61,277 |
def PyTmHMSXtoS(h, m, s, x):
"""
Convert hours-minutes-seconds-milliseconds to seconds as float
Parameters
----------
h: int, hours
m: int, minutes
s: int, seconds
x: float, milliseconds
Returns
-------
float, seconds
"""
return h * 3600.0 + m * 60.0 + s + x | 550362fe48d4e6c8c94b0c885611b607c8e39e63 | 61,278 |
def _update_visited():
""" Updates the visited count by one in the cache
:return: The visited count in string form.
"""
visited = cache.get('visited')
if not visited:
visited = 0
else:
visited = int(visited)
visited += 1
cache.set('visited', str(visited))
return str(v... | b5ad3a449fcd6cd5014616823d18e74bcc9af45f | 61,280 |
def get_model_and_assets(num_poles=1):
"""Returns a tuple containing the model XML string and a dict of assets."""
return _make_model(num_poles), common.ASSETS | 5cf6866a78f9cda526841c49db5556e1d27e1e60 | 61,282 |
def search(index=None):
"""
查询记录：如果没有索引名称的话默认就会查询全部的索引信息
:param index:查询的索引名称
:return:
"""
if not index:
return es.search()
else:
return es.search(index=index) | 52f8f22c98fdf79541b1bacd48bc101c73f17481 | 61,285 |
def tp_interval_has_another_wave(to_check_data:np.ndarray, threshold_val:Real, threshold_pos:Real) -> bool:
"""
check if there is another wave (normal, inverted, or biphasic) within tp interval
"""
positive_wave_pos = np.where(np.array(to_check_data)>threshold_val)[0].tolist()
negative_wave_pos = n... | 940c0d36ca253c33bd48178d2738b3d12467fa46 | 61,286 |
def get_square_box(box):
"""Get a square box out of the given box, by expanding it."""
left_x = box[0]
top_y = box[1]
right_x = box[2]
bottom_y = box[3]
box_width = right_x - left_x
box_height = bottom_y - top_y
# Check if box is already a square. If not, make it a square.
diff = b... | 6504aac3ab6447e71cd70f7ad5ea5335c1406ac7 | 61,287 |
def permute_to_N_HW_K(tensor, K):
"""
Transpose/reshape a tensor from (N, K, H, W) to (N, (HxW), K)
"""
assert tensor.dim() == 4, tensor.shape
N, _, H, W = tensor.shape
tensor = tensor.view(N, K, H, W)
tensor = tensor.permute(0, 2, 3, 1)
tensor = tensor.reshape(N, -1, K) # Size=(N,HW,K)... | e075ded87423905a64b17dbd9888308c5ba73080 | 61,288 |
def getMBAp(mol):
"""
#################################################################
Calculation of Moreau-Broto autocorrelation descriptors based on
carbon-scaled atomic polarizability.
#################################################################
"""
res={}
for i in range(8):
... | 57109df4a681afdf336dcddc2333be2ef9a2dfb3 | 61,290 |
def selfplay_single_player(model, env, games=10):
"""
Since the model will is playing a single player game
the self play algorithm needs to be adjusted to account for this
Parameters
----------
model : muzero
muzero - since we are working with only one model (since it's single player) no need for model storage... | 0a98eb312c8f22e31cc209cd132ecd6e8b850a22 | 61,292 |
import base64
def get_mole_prediction():
"""
predicts mole picture, wether it is bengign or malignant
:return: json
"""
json = request.get_json()
chat_id = str(json["chat_id"])
encoded_image = json["encoded_image"]
img = base64.b64decode(encoded_image)
img = Image.open(BytesIO(img... | a08ca0d55611f6e4b9629f10268c873af2086faa | 61,293 |
def detect_corners(data, target_idx=9):
"""
data: [{'img': [np.ndarray]}]
return: [{'corners', [(x,y)]}]
"""
aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_4X4_50)
aruco_param = cv2.aruco.DetectorParameters_create()
aruco_param.cornerRefinementMethod = cv2.aruco.CORNER_REFINE_S... | 6cf3fd902cc4bfdf1b58119f7a943f9f7d0ba959 | 61,294 |
from functools import reduce
def qsimplify(expr):
"""
Simplify expression by recursively evaluating the quantity arguments.
If units are encountered, as it can be when using Constant, they are
converted to quantity.
"""
def redmul(x, y):
"""
Function used to combine args in m... | 191fdc3415d56655751ead9e317b7032c637bdc3 | 61,296 |
def get_feedback_rating(doctype, docname):
""" get and return the latest feedback rating if available """
rating= frappe.get_all("Communication", filters={
"reference_doctype": doctype,
"reference_name": docname,
"communication_type": "Feedback"
}, fields=["rating"], order_by="creation desc", as_list=True)
... | 51bbfbb58dfa4d12cb38c382fa7c9905f39b3fa2 | 61,297 |
import functools
def condition(model):
"""
La condition à remplir pour arreté la compression
"""
mean = functools.reduce(lambda x ,y : x+y , model)/len(model)
return mean<NB_BITS_MEAN | cc7c761b02f96ed9f4002e1eb375568fcdba15ce | 61,298 |
def main_scoped_model_class():
"""
A custom Python model class defined in the ``__main__`` scope.
"""
return get_model_class() | 39a46ad14f04d6c12976304f31ccee74c6d48b60 | 61,299 |
from pathlib import Path
def directory_size_bytes(dir_path):
"""Return the size of the directory's contents in bytes."""
dir_path = Path(dir_path)
if not dir_path.is_dir():
raise QgrRuntimeError(f'`dir_path` must be a directory. Got {dir_path}')
contents = dir_path.glob('**/*')
total_size... | d5ef21a98e60e03d3cc3a3635b80749a818f7ab8 | 61,300 |
def gf_factor(f, p, K, **args):
"""Factor (non square-free) polynomials in `GF(p)[x]`.
Given a possibly non square-free polynomial `f` in `GF(p)[x]`, returns
its complete factorization into irreducibles::
f_1(x)**e_1 f_2(x)**e_2 ... f_d(x)**e_d
where each `f_i` is a moni... | 0d411ad75fd4ec1e58b92da13881b9557e26db03 | 61,301 |
def get_first_attachment(email):
"""Return the file path of the first attachment from an email.
Parameters
----------
email : Message
An email |Message| object.
Returns
-------
|str| or |None|
The file path to the first attachment in the email, if one
exists and is ... | b066a7ebe660f7b6bd8f91a8fa9aa958dcae135b | 61,302 |
def instance2xml_base(anno, bbox_type='xyxy'):
"""bbox_type: xyxy (xmin, ymin, xmax, ymax); xywh (xmin, ymin, width, height)"""
assert bbox_type in ['xyxy', 'xywh']
E = objectify.ElementMaker(annotate=False)
anno_tree = E.annotation(
E.folder('VOC2014_instance/person'),
E.filename(anno['... | a739b4a4ce61db319a625625b2a412a3f3fcbbe2 | 61,303 |
import json
def _dump_user_paths(user, paths, **kwargs):
"""Helper function for dumping a user paths file. Returns whether or
not the dump occured successfully.
"""
if 'raise_errors' not in kwargs:
kwargs['raise_errors'] = False
user_path_file = _user_path_file(user)
with flock(user_pa... | fc7b17f952af6c173fcf42eef1b1855f58a22347 | 61,304 |
def get_reading_type(meter_id, quantity_id, start_date, end_date, my_cursor):
"""
Return the reading type for meter METER_ID with quantity id QUANTITY_ID
between START_DATE and END_DATE (Totalization, Interval) or NONE if an error
occurs. Uses cursor MY_CURSOR.
"""
monotonic_sql = """
SE... | c7be18e960cad51a759380e3084622debaa469a5 | 61,305 |
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