content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def stringify_array(v,
maxDepth=None,
maxItems=-1,
maxStrlen=-1):
"""
Convert a dict to a string representation.
Parameters:
d(dict) : the data dict to convert
maxDepth (int|None): if > 0, then ellipsise structures deeper than th... | 17bf5008c7a263c102f0fa03fdcc708c0fcc9a0f | 3,638,400 |
import pickle
def rpickle(picke_file, state=None):
"""
Save the state of the gps file treated
"""
logger.warning('Running rpickle ...')
results = []
if picke_file.isfile():
with open(picke_file, 'rb') as read_pickle:
results += pickle.load(read_pickle)
# print results
... | a3f0cc46d6992032d008053e679ec75c64805141 | 3,638,401 |
import jsonschema
import json
import pkg_resources
import os
def test_pydist():
"""Make sure pydist.json exists and validates against our schema."""
# XXX this test may need manual cleanup of older wheels
def open_json(filename):
return json.loads(open(filename, 'rb').read().decode('utf-8'))
... | e29ee534accf932ac2b1b407a8c6bc83201e10f7 | 3,638,402 |
def should_print(test_function):
"""should_print is a helper for testing code that uses print
For example, if you had a function like this:
```python
def hello(name):
print('Hello,', name)
```
You might want to test that it prints "Hello, Nate" if you give it the
name "Nate". To d... | 16a1f675d3dced411fe5a6ffdc566db61ca7890f | 3,638,403 |
def fista(y, A, At, reg_weight, noise_eng, max_iter=100, update_reg=False, **kwargs):
"""
The FISTA algorithm for the ell1 minimisation problem:
min_x |y - Ax|^2 + reg * |x|_1
:param y: the given measurements (here it is the Fourier transform at certain frequencies)
:param A: the mapping from the sp... | dece002fff126c68bb6427eb37de5972a24bec00 | 3,638,404 |
def produce_segmentation(indices: list[list[int]], wav_name: str) -> list[dict]:
"""produces the segmentation yaml content from the indices of the probabilistic_dac
Args:
indices (list[list[int]]): output of the probabilistic_dac function
wav_name (str): the name of the wav file (with the .wav ... | cd8267e90f5e69589325a4e261d3f8136b36cc53 | 3,638,405 |
def trac_get_tracs_for_object(obj, user=None, trac_type=None):
"""
Returns tracs for a specific object.
"""
content_type = ContentType.objects.get_for_model(type(obj))
qs = Trac.objects.filter(content_type=content_type, object_id=obj.pk)
if user:
qs = qs.filter(user=user)
if trac_typ... | 9617fc5e417e40fb27bfe90b2f87434902cdb70b | 3,638,406 |
def size_from_ftp(ftp, url):
"""Get size of a file on an FTP server.
Parameters
----------
ftp : FTP
An open ftplib FTP session.
url : str
File URL.
Returns
-------
int
Size in bytes.
"""
url = urlparse(url)
return ftp.size(url.path) | 50d21fa95669a9863b32de3a67eda78de713fe7c | 3,638,407 |
def set_name_line(hole_lines, name):
"""Define the label of each line of the hole
Parameters
----------
hole_lines: list
a list of line object of the slot
name: str
the name to give to the line
Returns
-------
hole_lines: list
List of line object with label
... | a57667f269dac62d39fa127b2a4bcd438a8a989b | 3,638,408 |
import torch
def dist_to_boxes(points, boxes):
"""
Calculates combined distance for each point to all boxes
:param points: (N, 3)
:param boxes: (N, 7) [x, y, z, h, w, l, ry]
:return: distances_array: (M) torch.Tensor of [(N), (N), ...] distances
"""
distances_array = torch.Tensor([])
b... | b3305ec8a4c8d5e0d5cf520e9e22d2c5377fe1de | 3,638,409 |
import logging
import os
def print_listdir(x):
"""."""
log = logging.getLogger('SIP.workflow.function')
log.info('HERE A')
print('Task id = {} {}'.format(x, os.listdir('.')))
return x, os.listdir('.') | 738fa091d5f7f9bca0bf43edfbf09eafcba87ba3 | 3,638,410 |
def blackwhite2D(data,xsize=None,ysize=None,show=1):
"""blackwhite2D(data,xsize=None,ysize=None,show=1)) - display list or array data as black white image
default popup window with (300x300) pixels
"""
if type(data) == type([]):
data = array(data)
w,h = data.shape[1],data.shape[0]
... | 78a76fab9f3eb989697b695c8d7b82c877f8dc9a | 3,638,411 |
def contains_digit(s):
"""Find all files that contain a number and store their patterns.
"""
isdigit = str.isdigit
return any(map(isdigit, s)) | 941bcee8b6fbca6a60a8845f88a3b5765e3711bb | 3,638,412 |
def to_signed(dtype):
"""
Return dtype that can hold data of passed dtype but is signed.
Raise ValueError if no such dtype exists.
Parameters
----------
dtype : `numpy.dtype`
dtype whose values the new dtype needs to be able to represent.
Returns
-------
`numpy.dtype`
"... | 7be15d324eef6f9686a5866a92ad365a67949424 | 3,638,413 |
def listen_for_wakeword():
"""Continuously detecting the appeareance of wakeword from the audio stream. Higher priority than the listen() function.
Returns:
(bool): return True if detected wakeword, False otherwise.
"""
gotWakeWord = core.listen_for_wakeword()
return gotWakeWord | 49f600ed303fb9bea11cb9247653c66272fc5491 | 3,638,414 |
import sys
def import_string(import_name):
"""Returns a callable for a given setuptools style import string
:param import_name: A console_scripts style import string
"""
import_name = str(import_name).replace(":", ".")
try:
import_module(import_name)
except ImportError:
if "."... | 2e636dd65c5432f46999e14c46b63ca9e1db7570 | 3,638,415 |
from scipy.stats import kurtosis
def kurtosis(x,y):
"""
Calculate kurtosis of the probability
distribution of the forecast error if
an observation and forecast vector are given.
Both vectors must have same length, so pairs of
elements with same index are compared.
Description:
Ku... | b4242f58db8a48dbe9bec03ec641ae78858c28f7 | 3,638,416 |
def preprocess_text(sentence):
"""Handle some weird edge cases in parsing, like 'i' needing to be capitalized
to be correctly identified as a pronoun"""
cleaned = []
words = sentence.split(' ')
for w in words:
if w == 'i':
w = 'I'
if w == "i'm":
w = "I'm"
... | 4e1d69eaf0adc1ede6bc67563e499602e320e76b | 3,638,417 |
import pkgutil
import os
def _GetModuleFromPathViaPkgutil(module_path, name_to_give):
"""Loads module by using pkgutil.get_importer mechanism."""
importer = pkgutil.get_importer(os.path.dirname(module_path))
if importer:
if hasattr(importer, '_par'):
# par zipimporters must have full path from the zip... | d95eaf07f355a1fbb726d331e2a61ea4e8cf94e1 | 3,638,418 |
def weighted_l2_loss(gt_value, pred_value, weights):
"""Computers an l2 loss given broadcastable weights and inputs."""
diff = pred_value - gt_value
squared_diff = diff * diff
if isinstance(gt_value, float):
gt_shape = [1]
else:
gt_shape = gt_value.get_shape().as_list()
if isinstance(weights, float)... | e7ebc8486a965912b28136013af0e5f4ade403bd | 3,638,419 |
def csr_scale_rows(*args):
"""
csr_scale_rows(npy_int32 const n_row, npy_int32 const n_col, npy_int32 const [] Ap, npy_int32 const [] Aj,
npy_bool_wrapper [] Ax, npy_bool_wrapper const [] Xx)
csr_scale_rows(npy_int32 const n_row, npy_int32 const n_col, npy_int32 const [] Ap, npy_int32 const [] Aj,
... | 887f6c51d297649232d6fd297380c551dbb47008 | 3,638,420 |
import os
def get_homography_calibration_files(fullpath=True):
"""
Returns a list of the homography calibration yaml files in the homgraphies directory
of the mct configuration.
"""
file_list = os.listdir(homographies_dir)
dummy, params_file = os.path.split(homography_calibrator_params_file)
... | b6ddcdbee2305fb136a380e0c530aa534f584981 | 3,638,421 |
def complexity_hjorth(signal):
"""**Hjorth's Complexity and Parameters**
Hjorth Parameters are indicators of statistical properties initially introduced by Hjorth
(1970) to describe the general characteristics of an EEG trace in a few quantitative terms, but
which can applied to any time series. The pa... | af5b5fb8925055da4cf48facadd1bed257e40f76 | 3,638,422 |
import pandas
def load_gecko():
"""
target variable is column "A375 Percent rank"
"""
data_nonessential = pandas.read_excel(settings.pj(settings.offtarget_data_dir, 'GeCKOv2_Non_essentials_Achilles_A375_complete.xls')) #(4697, 31)
data_all_A375 = pandas.read_csv(settings.pj(settings.offtarget_data... | 31c2db07261fb1b242f4c52808c3b7e6312b1e54 | 3,638,423 |
def get_sample_eclat(name):
"""Read a tweet sample from a sample file and return it in a format eclat
can process.
"""
sampleFile = open(name)
X = []
Y = []
line = sampleFile.readline()
while line != '':
row = line.split()
Y.append(int(row[0]))
x = []
... | dd5daa2cd19b087c4b59379b8d3b2c2ea9ec27de | 3,638,424 |
from datetime import datetime
def submission_storage_path(instance, filename):
"""
Function DocString
"""
string = '/'.join(['submissions', instance.submission_user.user_nick, str(instance.submission_question.question_level), str(instance.submission_question.question_level_id)])
string += '/'+... | 587785869da8906234bb572e9d635a892dc3270b | 3,638,425 |
def distance_to_center(n):
"""Return Manhattan distance to center of spiral of length <n>."""
dist = distances_to_center()
for _ in range(n - 1):
next(dist)
return next(dist) | 1301d0370a3f3dca72fb003073522376fd0790c0 | 3,638,426 |
import logging as log
def detect_tachycardia(heart_rate, age):
"""
This function makes best guess as to whether tachycardia is being exhibited
:param float heart_rate: heart rate in bpm
:param int age: age of user/patient
:return ble tachycardia: whether or not tachycardia detected
"""
lo... | 2e6dafb581da8599cc71b790f10f45a9789bd617 | 3,638,427 |
from typing import List
from typing import Mapping
from typing import Any
from typing import Optional
import inspect
async def _assert_preconditions_async(preconditions: List[List[Contract]],
resolved_kwargs: Mapping[str, Any]) -> Optional[BaseException]:
"""Assert that the p... | d89c355ed56e350a619e1d7324c8341bb74f827c | 3,638,428 |
import re
def moveGeneratorFromStrList (betaStringList, string_mode = True):
""" generate the final output of move sequence as a list of dictionary.
Input :
['F5-LH', 'F5-RH', 'E8-LH', 'H10-RH', 'E13-LH', 'I14-RH', 'E15-LH', 'G18-RH']
Length of the list: how many moves in this climb to the target... | c2905fffd9d1873c79239199027697e5c6162731 | 3,638,429 |
from datetime import datetime
def generateVtBar(row):
"""生成K线"""
bar = VtBarData()
symbol, exchange = row['symbol'].split('.')
bar.symbol = symbol
bar.exchange = exchangeMapReverse[exchange]
if bar.exchange in ['SSE', 'SZSE']:
bar.vtSymbol = '.'.join([bar.symbol, bar.exc... | 5beecf78f932c8e1bf76c680157ecd29fbdf9567 | 3,638,430 |
import sqlite3
def index_with_links():
"""post request that the form link uses
"""
db = sqlite3.connect('link_shortner.db')
c = db.cursor()
link = request.forms.get('link')
generated_id = gen_id()
#row = db.execute('SELECT * from links where link_id=?', generate_id).fetchone()
c.execut... | 38e4ee6e63bacbc55a40533759c06b836a050e56 | 3,638,431 |
import torch
import os
def SinGAN_generate(Gs, Zs, reals, styles, NoiseAmp, opt, in_s=None, scale_v=1, scale_h=1, n=0, gen_start_scale=0, num_samples=10):
"""
Generate image with the given parameters.
Returns:
I_curr(torch.cuda.FloatTensor) : Current Image
"""
#if torch.is_tensor(in_s) == ... | a6dbd66a8b991033e58ac507c52982d6742c0254 | 3,638,432 |
def divide_blend(img_x: np.ndarray, img_y: np.ndarray) -> np.ndarray:
"""
Blend image x and y in 'divide' mode
:param img_x: input grayscale image on top
:param img_y: input grayscale image at bottom
:return:
"""
result = np.zeros_like(img_x, np.float_)
height, width = img_x.shape
f... | 27207b209c871a794162ee5b2932344a185668e7 | 3,638,433 |
from typing import Hashable
from typing import Optional
from typing import Tuple
from typing import Any
def table_to_bipartite_graph(
table: Tabular,
first_part_col: Hashable,
second_part_col: Hashable,
*,
node_part_attr: str = "part",
edge_weight_attr: str = "weight",
first_part_data: Opt... | ba37a806e96a4c1747fddf9789115d7a1eb4d074 | 3,638,434 |
def init_wavefunction(n_sites,bond_dim,**kwargs):
"""
A function that initializes the coefficients of a wavefunction for L sites (from 0 to L-1) and arranges
them in a tensor of dimension n_0 x n_1 x ... x n_L for L sites. SVD
is applied to this tensor iteratively to obtain the matrix product state.
... | 8f1a4d456945d9a345f560ee3d87dadbf353e7d3 | 3,638,435 |
def num_channels_to_num_groups(num_channels):
"""Returns number of groups to use in a GroupNorm layer with a given number
of channels. Note that these choices are hyperparameters.
Args:
num_channels (int): Number of channels.
"""
if num_channels < 8:
return 1
if num_channels < 3... | e2095fba2b1b9cdada72d354ddcd781d99e4aa48 | 3,638,436 |
def response_message(status, message, status_code):
"""
method to handle response messages
"""
return jsonify({
"status": status,
"message": message
}), status_code | e9dd25f237f264835d507af01a71ef9c826bf28d | 3,638,437 |
def glDrawBuffers( baseOperation, n=None, bufs=None ):
"""glDrawBuffers( bufs ) -> bufs
Wrapper will calculate n from dims of bufs if only
one argument is provided...
"""
if bufs is None:
bufs = n
n = None
bufs = arrays.GLenumArray.asArray( bufs )
if n is None:
n = a... | ef5a83ea633138d4cb18d8d2d20736d8c1942bc0 | 3,638,438 |
def compare_rendered(obj1, obj2):
"""
Return True/False if the normalized rendered version of
two folium map objects are the equal or not.
"""
return normalize(obj1) == normalize(obj2) | b7debf048ea41b882003283b6e3b94d257f0e0fa | 3,638,439 |
async def _get_device_client_adapter(settings_object):
"""
get a device client adapter for the given settings object
"""
if not settings_object.device_id and not settings_object.id_scope:
return None
adapter = adapters.create_adapter(settings_object.adapter_address, "device_client")
ad... | 411b52a4e916d55b46933afbfa4e8513243b4397 | 3,638,440 |
def is_reserved(word):
"""
Determines if word is reserved
:param word: String representing the variable
:return: True if word is reserved and False otherwise
"""
lorw = ['define','define-struct']
return word in lorw | 0b0e3706bcafe36fc52e6384617223078a141fb2 | 3,638,441 |
def verify_figure_hash(name, figure=None):
"""
Verifies whether a figure has the same hash as the named hash in the current hash library.
If the hash library does not contain the specified name, the hash is added to the library.
Parameters
----------
name : string
The identifier for the... | 09ee240c9efbeddd4a0f33401d80b918175a579e | 3,638,442 |
def x_span_contains_y(x_spans, y_spans):
"""
Return whether all elements of y_spans are contained by some elements of x_spans
:param x_spans:
:type x_spans:
:param y_spans:
:type y_spans:
"""
for i, j in y_spans:
match_found = False
for m, n in x_spans:
i... | c366a5a5543e2fe9f6325cd3d31eccffb921693c | 3,638,443 |
import argparse
def parse_args():
"""Parse arguments and return them
:returns: argparse object
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'-c',
'--config',
help='configuration file',
required=True)
return parser.parse_args() | d0fc1399c058f53558e08f13811c9709e518fd84 | 3,638,444 |
import time
def log(fn):
"""
logging decorator for the for the REST method calls. Gets all important information
about the request and response, takes the time to complete the calls and writes it
to the logs.
"""
def wrapped(self, *args):
try:
start = time()
ret... | 8efcfcf043c220565092971749a12876a55641dc | 3,638,445 |
def deal_line(text_str1, text_str2, para_bound=None):
"""行合并和段落拆分"""
global result_text
text_str2 = text_str2.strip()
len_text_str2 = len(text_str2)
if len_text_str2 > 3 and len(set(text_str2)) == 1: # 处理 ***** 这类分割线
st = list(set(text_str2))[0]
# new_file.write(' ' + st * 24 +... | b984cefd842071fed3359ac36f8bae46e916e956 | 3,638,446 |
def resized_image(image: np.ndarray, max_size: int) -> np.ndarray:
"""Resize image to feature_process_size."""
h, w = image.shape[:2]
size = max(w, h)
if 0 < max_size < size:
dsize = w * max_size // size, h * max_size // size
return cv2.resize(image, dsize=dsize, interpolation=cv2.INTER_... | a32f0639b8b59cef8817861d123b5c304b7c243c | 3,638,447 |
def load_folder_list(args, ndict):
"""
Args:
dict : "name_run" -> path
"""
l = []
for p in ndict:
print("loading %s" % p)
l.append(load_pickle_to_dataframe(args, p))
d = pd.concat(l)
d = d.sort_values("name_run")
print("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... | bd434fd93b3cb06a18d40edc48f8119442e7f0ff | 3,638,448 |
def charge_initial():
"""
Not currently in use, parking spot id gets passed in and it carries over
and passes it into the stripe charge view.
"""
spot_id = int(request.args.get('id'))
spot = AddressEntry.query.get(spot_id)
return render_template('users/charge_initial.html', key=stripe_keys['... | f971b5c69954ce2026d2c4b08d6877c9f7da6067 | 3,638,449 |
import csv
def read_csv_from_file(file):
"""
Reads the CSV data from the open file handle and returns a list of dicts.
Assumes the CSV data includes a header row and uses that header row as
fieldnames in the dict. The following fields are required and are
case-sensitive:
- ``artist``
... | 89cfce0be6270076230051a6e852d1add3f4dcaf | 3,638,450 |
def findOutliers(time, flux, gap=None,
threshold_sigma=4,
precision_days=0.0205,
maxClusterLen = 2
):
"""
Identify single point outliers.
Preserves consecutive outliers, and those that are evenly spaced in
time. This protects short dur... | 223f0c06febb9699f5d8fda6fa8b4d2f54713e45 | 3,638,451 |
def identify_denonavr_receivers():
"""
Identify DenonAVR using SSDP and SCPD queries.
Returns a list of dictionaries which includes all discovered Denon AVR
devices with keys "host", "modelName", "friendlyName", "presentationURL".
"""
# Sending SSDP broadcast message to get devices
devices ... | 712cba308d150ec179a390c27ae6931595cdffa9 | 3,638,452 |
def get_index_settings(index):
"""Returns ES settings for this index"""
return (get_es().indices.get_settings(index=index)
.get(index, {}).get('settings', {})) | 6d5d13bc30fdf8db666206bb07c3310394f3ff44 | 3,638,453 |
import hashlib
import six
def make_hashkey(seed):
"""
Generate a string key by hashing
"""
h = hashlib.md5()
h.update(six.b(str(seed)))
return h.hexdigest() | 38d088005cb93fc0865933bbb706be171e72503a | 3,638,454 |
import asyncio
async def report(database, year, month, limit):
"""Get a report."""
matches_query = """
select count(*) as count
from matches
where extract(year from played)=:year and extract(month from played)=:month
"""
players_query = """
select count(distinct players... | 91059c5a8bd44536f24a7edbb88ff27b9036b83a | 3,638,455 |
import sys
def compose_ntx_graph(input_file=None, delimiter=None, weighted=None):
"""
This function creates a networkx graph from provided file
:param input_file: Input file path
:param delimiter: separator for the column of the input file
:param weighted: Simple yes/no if the input file is weight... | d2622fac8ca97083c49a054406ccb44752f54871 | 3,638,456 |
def dy3(vector, g, m1, m2, L1, L2):
"""
Abbreviations
M = m0 + m1
S = sin(y1 - y2)
C = cos(y1 - y2)
s1 = sin(y1)
s2 = sin(y2)
Equation
y3' = g*[m2 * C * s2 - M * s1] - S*m2*[L1 * y3^2 * C + L2*y4^2]
-------------------------------------------------------------
... | b93086cfcbb9d5f32143279ad01972d3f8719a78 | 3,638,457 |
from typing import Any
def getType(resp: falcon.Response, class_type: str, method: str) -> Any:
"""Return the @type of object allowed for POST/PUT."""
for supportedOp in get_doc(resp).parsed_classes[class_type]["class"].supportedOperation:
if supportedOp.method == method:
return supportedO... | d20b77b4f40d266e685ce87f67d8f2fcbcfbe3eb | 3,638,458 |
def full_data_numeric():
"""DataFrame with numeric data
"""
data_dict = {'a': [2, 2, 2, 3, 4, 4, 7, 8, 8, 8],
'c': [1, 2, 3, 4, 4, 4, 7, 9, 9, 9],
'e': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
}
df = pd.DataFrame(data_dict)
return df | ebd105f2648475dc7dcd40f51482d18e29486254 | 3,638,459 |
def fix(x):
"""
Replaces spaces with tabs, removes spurious newlines, and lstrip()s each
line. Makes it really easy to create BED files on the fly for testing and
checking.
"""
s = ""
for i in x.splitlines():
i = i.lstrip()
if i.endswith('\t'):
add_tab = '\t'
... | ecd3a4d7f470feae1b697025c8fbf264d5c6b149 | 3,638,460 |
def get_collect_method(collect_method_name):
"""Return the collect method."""
try:
collect_method = CollectMethod.get(name=collect_method_name)
except ValueError:
raise RuntimeError(f'Collect Method {collect_method_name} not found!')
return collect_method | b80fcb916d461deea1784386062017291292f218 | 3,638,461 |
def TriangleBackwardSub(U,b):
"""C = TriangleBackwardSub(U,b)
Solve linear system UC = b
"""
C = solve(U,b)
return C | 95c7fb76ad02a5546a79b95f18b51fe385307329 | 3,638,462 |
from unittest.mock import patch
def test_binance_query_balances_unknown_asset(function_scope_binance):
"""Test that if a binance balance query returns unknown asset no exception
is raised and a warning is generated. Same for unsupported asset."""
binance = function_scope_binance
def mock_unknown_asse... | 7521fd3039398c3eedccb16e16202687b4c28b2d | 3,638,463 |
def petsc_to_stencil(x, Xh):
""" converts a numpy array to StencilVector or BlockVector format"""
x = x.array
u = array_to_stencil(x, Xh)
return u | 6df02bbbfb9e9e386ca03510f2e4d563a6fed1aa | 3,638,464 |
from typing import Optional
import contextlib
def index_internal_txs_task(self) -> Optional[int]:
"""
Find and process internal txs for monitored addresses
:return: Number of addresses processed
"""
with contextlib.suppress(LockError):
with only_one_running_task(self):
logger.... | b1a40ec713ff8d302f5c47b2c5d41300c699f3b4 | 3,638,465 |
import math
def make_lagrangian(func, equality_constraints):
"""Make a Lagrangian function from an objective function `func` and `equality_constraints`
Args:
func (callable): Unary callable with signature `f(x, *args, **kwargs)`
equality_constraints (callable): Unary callable with signature `... | c5795cded21e9cc4a7092eee63b88a4fac3b346a | 3,638,466 |
import argparse
def render_task(task: todotxt.Task, namespace: argparse.Namespace, level: int = 0) -> str:
"""Render one task."""
indent = (level - 1) * " " + "- " if level else ""
rendered_task = colorize(reference(task, namespace), namespace)
rendered_blocked_tasks = render_blocked_tasks(task, name... | ff50a060c7898bba5aac02f85d9eefd903465cf0 | 3,638,467 |
def ungroup(expr):
"""Helper to undo pyparsing's default grouping of And expressions,
even if all but one are non-empty.
"""
return TokenConverter(expr).addParseAction(lambda t: t[0]) | c007a51e5073d8a3cbcbe52ca32ad84d58f4100a | 3,638,468 |
import os
def remove_tmp_directories():
"""
remove tmp directories submitted in tmp_directories
Returns:
True
"""
for tmp_dir in tmp_directories:
os.remove(tmp_dir)
return True | 43d37e8382ada5073f072832a83f78f027003048 | 3,638,469 |
from typing import Type
from typing import List
from typing import cast
def get_actual_type(arg_type: Type, kind: int,
tuple_counter: List[int]) -> Type:
"""Return the type of an actual argument with the given kind.
If the argument is a *arg, return the individual argument item.
"""
... | cb113cea89f5fd6835314c53b35afce4fa3b74a1 | 3,638,470 |
def test_qnn_legalize():
"""Test directly replacing an operator with a new one"""
def before():
x = relay.var("x", shape=(1, 64, 56, 56), dtype='int8')
y = relay.qnn.op.requantize(x,
input_scale=1,
input_zero_point=0,
... | b6f4a930e5c7156e60a5b26583b6e8fc48a6f441 | 3,638,471 |
import yaml
def load(data, schema, yamlLoader=yaml.UnsafeLoader):
"""
Loads the given data and validates it according to the schema provided.
Data must be either JSON or YAML, it must be a dictionary, a path, or a string of JSON.
Schema must be JSON, it must be a dictionary, a path, or a string of JSO... | e7f29e1b61e60ce1cac5b1b1217f1df645691c17 | 3,638,472 |
from typing import List
def calculate_slice_rotations(im_stack: np.ndarray, max_rotation:float = 45) -> List[float]:
"""Calculate the rotation angle to align each slice so the
objects long axis is aligned with the horizontal axis.
Parameters
----------
im_stack : np.ndarray
A stack of ima... | 42c0fdbdf02e937f449cb3ca137588003c715651 | 3,638,473 |
def calc_rest_interval(data):
"""
SubTool for Investigate: after median_deviation filters through all the
points run entropy on the remaining non_rest points. This will filter the
close but could still be rest points.
"""
lst, rest = median_deviation(data)
average = median(data)
st_entr... | 7710e0784a5a025d99c8ead9799b1062942e3cdc | 3,638,474 |
def get_objanno(fin_anno, godag, namespace='all'):
"""Get annotation object"""
fin_full = get_anno_fullname(fin_anno)
return get_objanno_factory(fin_full, godag=godag, namespace=namespace) | 5e071190596ab37943d4001b4f03cf20d6395e06 | 3,638,475 |
def create_table_descriptives(datasets):
"""Merge dataset descriptives."""
df = pd.concat(
[pd.read_json(ds, orient="index") for ds in datasets],
axis=0
)
df.index.name = "dataset_name"
return df | 7c4554381ffb14572d949c27035411567d69e25d | 3,638,476 |
def get_ngram_universe(sequence, n):
"""
Computes the universe of possible ngrams given a sequence. Where n is equal to the length of the sequence, the resulting number represents the sequence universe.
Example
--------
>>> sequence = [2,1,1,4,2,2,3,4,2,1,1]
>>> ps.get_ngram_universe(sequence, 3)
64
"""
# if... | 3dbfe1822fdefb3e683b3f2b36926b4bb066468f | 3,638,477 |
from typing import Union
from typing import Iterable
def as_nested_dict(
obj: Union[DictLike, Iterable[DictLike]], dct_class: type = DotDict
) -> Union[DictLike, Iterable[DictLike]]:
"""
Given a obj formatted as a dictionary, transforms it (and any nested dictionaries)
into the provided dct_class
... | a89261253174ce5b75d61343f0b45d3fe65e12f9 | 3,638,478 |
def twoindices_positive_up_to(n, m):
"""
build 2D integer indices up to n (each scanned from 0 to n)
"""
if not isinstance(n, int) or n <= 0:
raise ValueError("%s is not a positive integer" % str(n))
nbpos_n = n + 1
nbpos_m = m + 1
gripos = np.mgrid[: n : nbpos_n * 1j, : m : nbpo... | 63f850703f7598f1a4611c13700aa1921d77dd1a | 3,638,479 |
import os
import glob
def get_data_lists(data, MOT=False):
""" Prepare rolo data for SORT
Arguments:
data: config of the following form:
{
'image_folder': data_folder + 'images/train/',
'annot_folder': data_folder + 'annotations/train/',
... | 537c3a8e1ffa8ab0a6835738b2032f26e1157406 | 3,638,480 |
def ban_user(request, user):
"""Bans a given user."""
user = User.query.filter_by(username=user).first()
if user is None:
raise NotFound()
next = request.next_url or url_for('admin.bans')
if user.is_banned:
request.flash(_(u'The user is already banned.'))
return redirect(next... | dd8c2a43a3843a6055e9e690d8cffee8cfac2b0e | 3,638,481 |
def lastDate():
"""[summary]
lastDate() function: return the total revenue of the nearest day
Returns:
[type]: [description]
"""
lastDate = totalDate().tail(1)
last_date = lastDate.iloc[0]['total'].round(2)
return last_date | 93130bf39dc2a82fa2cae11a6ea11468211f61b6 | 3,638,482 |
from libmkMeteo import mkmeteo4lingrars
from liblingraRS import lingrars
def processlingrarow(col, rows, pixelWidth, pixelHeight, xO, yO, plot, netcdffile, rsdir, becsmosdir):
"""
Launch a single pixel of processing for LingraRS
:param col: column in Grassland raster file
:param rows: total rows in Gr... | b0b19c514ed1ca1ad324962fac0023b7af501503 | 3,638,483 |
import json
def multitask_result(request):
"""多任务结果"""
task_id = request.GET.get('task_id')
task_obj = models.Task.objects.get(id=task_id)
results = list(task_obj.tasklog_set.values('id','status',
'host_user_bind__host__hostname',
'host... | c9c37fe4852a8c04662a5061445c1565400e94a1 | 3,638,484 |
from typing import Dict
def process_xpath_list(node, property_manifest: Dict):
"""
Return a list of values as a result of running a list of XPath
expressions against an input node
:param node: Input node
:param property_manifest: Manifest snippet of the property
:return: List of values
"""... | e52ef3a7ff6b2f74554a69a5fec53125c077f6e5 | 3,638,485 |
def collect_username_and_password(db: Session) -> UserCreate:
"""Collect username and password information and validate"""
username = get_username("Enter your username: ")
password = get_password("Enter your password: ")
verify_pass = get_password("Enter your password again: ")
if password != verif... | be1557a4aa24cfb653c5e03f7f3cb340be1a6c1b | 3,638,486 |
def replace_header(input_df):
"""replace headers of the dataframe with first row of sheet"""
new_header = input_df.iloc[0]
input_df = input_df[1:]
input_df.columns=new_header
return input_df | c8946fc269dd313b80df421af8d0b3fc6c47aed7 | 3,638,487 |
def cartToRadiusSq(cartX, cartY):
"""Convert Cartesian coordinates into their corresponding radius squared."""
return cartX**2 + cartY**2 | 3fb79d2c056f06c2fbf3efc14e08a36421782dbd | 3,638,488 |
def unique_entity_id(entity):
"""
:param entity: django model
:return: unique token combining the model type and id for use in HTML
"""
return "%s-%s" % (type(entity).__name__, entity.id) | c58daf9a115c9840707ff5e807efadad36a86ce8 | 3,638,489 |
def normalize_tuple(value, n, name):
"""Transforms a single int or iterable of ints into an int tuple.
# Arguments
value: The value to validate and convert. Could be an int, or any iterable
of ints.
n: The size of the tuple to be returned.
name: The name of the argument being ... | cf396bac48b720686bb65ae7ab91b2e4cb22ac0e | 3,638,490 |
def load_user(user_id):
"""
@login_manager.user_loader Passes in a user_id to this function and in return the
function queries the database and gets a user's id as a response...
"""
return User.query.get(int(user_id)) | 2c2a2e7f6f9a5bc7392056bfd16402c9d2e96c22 | 3,638,491 |
def replaceall(table, a, b):
"""
Convenience function to replace all instances of `a` with `b` under all
fields. See also :func:`convertall`.
.. versionadded:: 0.5
"""
return convertall(table, {a: b}) | 19d6c0fb60c71994de02deafb5ec9c2995aba622 | 3,638,492 |
def get_job_metadata(ibs, jobid):
"""
Web call that returns the metadata of a job
CommandLine:
# Run Everything together
python -m wbia.web.job_engine --exec-get_job_metadata
# Start job queue in its own process
python -m wbia.web.job_engine job_engine_tester --bg
#... | 24ba96d6a71f105057a9fc9012de9edb187787d5 | 3,638,493 |
import math
def create_learning_rate_scheduler(max_learn_rate, end_learn_rate, warmup_proportion, n_epochs):
"""Learning rate scheduler, that increases linearly within warmup epochs
then exponentially decreases to end_learn_rate.
Args:
max_learn_rate: Float. Maximum learning rate.
end_lea... | 5c5649e429ad5f138894d30064c24bf23e547f85 | 3,638,494 |
def matchyness(section, option):
"""Assign numerical 'matchyness' value between target and value
Parameters:
section -- target value
option -- proposed match
"""
if section != option:
return _hc.NEQ
if isinstance(section, rt.flask_placeholder):
if isinstance(option, rt.flask_placeholder):
return _hc.PP ... | c8e3773a8afe190181fd7552460852a27b2534d3 | 3,638,495 |
def log_sum_exp_elem(*a):
"""
:param a: elements
:return: (a[0].exp() + a[1].exp() + ...).log()
"""
bias = max(a).detach()
ans = bias + sum([(ai-bias).exp() for ai in a]).log()
return ans | a87871a7c8af9d2c6c8db683ba63124319d09a0d | 3,638,496 |
def car_portrayal(agent):
"""Visualises the cars for the Mesa webserver
:return: Dictionary containing the settings of an agent"""
if agent is None:
return
portrayal = {}
# update portrayal characteristics for each CarAgent object
if isinstance(agent, CarAgent):
if agent.is_fro... | 68c0bffb02299f2b03abf6ee2dc590375ad8e2a5 | 3,638,497 |
import re
from typing import OrderedDict
def _load_spc_format_type_a(filepath: str):
"""load A(w,k) in the spc format type a
Args:
filepath (str): output filename
Returns:
np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray: kcrt, Awk, kdist, energy, kpath
"""
with open(fi... | 0a5c3f316875495e37502dd426e6eee7dd76ee53 | 3,638,498 |
def variable_to_json(var):
"""Converts a Variable object to dict/json struct"""
o = {}
o['x'] = var.x
o['y'] = var.y
o['name'] = var.name
return o | 86497a7915e4825e6e2cbcfb110c9bc4c229efed | 3,638,499 |
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