content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from datetime import datetime
def get_slurm_params(n,runtime=None,mem=None,n_jobs=None):
"""Get remaining parameters to submit SLURM jobs based on specified parameters and number of files to process.
Parameters
----------
n : int
Number of files to process.
runtime : str, None
Tim... | f2bf08430fbde0dcc430fd3e01d6b5ca1bd64487 | 9,000 |
import time
import os
from datetime import datetime
def get_db_comment_text(file_name) -> DataFrame:
"""
db_comment 파일에서 text를 추출하여 DataFrame type으로 return
:param file_name: 입력 파일명 (str type)
:return: 입력 파일에서 추출한 text
"""
# :return: 입력 파일에서 추출한 text에 형태소 분석기로 명사 추출한 DataFrame
start_time =... | ec36b3ac6a25e3fb5052f32fc11efe306db12a0e | 9,001 |
def source_open() -> bool:
"""Open a source MS Excel spreadsheet file.
Returns
-------
boolean
Flag about successful processing.
"""
try:
Source.wbook = openpyxl.load_workbook(cmdline.workbook)
except Exception:
logger.error(
'Cannot open the MS Excel wo... | 19a2c214131afa6c1126bc1e0a4b4892a13bc32b | 9,002 |
from pathlib import Path
import yaml
import os
import requests
import json
def make_prompt(token: str, config: Path, model: str = ''):
"""Make a summary using the Studio21 API
Args:
token (str): Your api token to use.
config (Path): The path to the config file.
model (str, optional): ... | 865dde67278c21c1dee075c5a831281d59a311c8 | 9,003 |
import re
def get_license_match_error(lic, lic_file_path):
"""Returns an Error of the type 'warning' if the FreeRTOS license is present in the
input file. Otherwise an empty list is returned.
"""
# Get the words in the license template
with open('license.templ', 'r') as file:
template_lic ... | d3f53f3d25c4d56b41fb561cf37b845d1efdc9fe | 9,004 |
import queue
def start_workers(size, delete=False, migrate=False):
"""Starts FluxxWorkers.
:returns: Pair of queues.
"""
streams = (queue.Queue(), queue.Queue(maxsize=size))
for _ in range(THREAD_COUNT):
worker = FluxxWorker(streams, delete, migrate)
worker.daemon = True
... | 358d8d3bc0d12edbe9e422cdfc206de626fd2a7d | 9,005 |
def harmonizationApply(data, covars, model):
"""
Applies harmonization model with neuroCombat functions to new data.
Arguments
---------
data : a numpy array
data to harmonize with ComBat, dimensions are N_samples x N_features
covars : a pandas DataFrame
contains covar... | 7789d3a75d043df5048a7b0adced771c7e1ddd81 | 9,006 |
import re
def from_rkm(code):
"""Convert an RKM code string to a string with a decimal point.
Parameters
----------
code : str
RKM code string.
Returns
-------
str
String with a decimal point and an R value.
Examples
--------
>>> from pyaedt.circuit import fr... | 8cb41a58fab685e5e7de4af533fade1aeee09c2c | 9,007 |
def get_arguments(method, rpc_version):
"""
Get arguments for method in specified Transmission RPC version.
"""
if method in ('torrent-add', 'torrent-get', 'torrent-set'):
args = constants.TORRENT_ARGS[method[-3:]]
elif method in ('session-get', 'session-set'):
args = constants.SESSI... | dcd8b3f0e5e93409518d7e9d72ffe954c3b99915 | 9,008 |
import functools
def compose_local_noises(*functions: NoiseModel) -> NoiseModel:
"""Helper to compose multiple NoiseModel.
Args:
*functions: a list of functions
Returns:
The mathematical composition of *functions. The last element is applied
first. If *functions is [f, g, h], it ... | 4b6e90ff2def9a988d8aa66782d990971b8de586 | 9,009 |
import copy
def sls_build(
repository, tag="latest", base="opensuse/python", mods=None, dryrun=False, **kwargs
):
"""
.. versionchanged:: 2018.3.0
The repository and tag must now be passed separately using the
``repository`` and ``tag`` arguments, rather than together in the (now
d... | d3d047334ea8b02e61d26b3fc471eb2cedd7a8c5 | 9,010 |
import re
from datetime import datetime
def parse_date(date):
"""
Parses a date string and returns number of seconds from the EPOCH.
"""
# yyyy-mm-dd [hh:mm:ss[.s][ [+-]hh[:][mm]]]
p = re.compile( r'''(?P<year>\d{1,4}) # yyyy
- #
... | 44dbf7c9ded2004118b64827e5c5016dc3967ec6 | 9,011 |
def CorrectOrWrong(Input,word):
"""Check if Input is inside word"""
if Input in word:
return True
else:
return False | fa3f06fd156c2523334a057366e88c5b7b376eb1 | 9,012 |
def get_fair_metrics(dataset, pred, pred_is_dataset=False):
"""
Measure fairness metrics.
Parameters:
dataset (pandas dataframe): Dataset
pred (array): Model predictions
pred_is_dataset, optional (bool): True if prediction is already part of the dataset, column name 'labels'.
Retu... | 1cf4a8655bf569f5d8ddfa530f46c65fe8f2be3f | 9,013 |
from typing import Sequence
from typing import Dict
from typing import Union
from typing import Tuple
def make_params(
key_parts: Sequence[str],
variable_parts: VariablePartsType) -> Dict[str, Union[str, Tuple[str]]]:
"""
Map keys to variables. This map\
URL-pattern variables to\
a URL... | 4da736f2057e06be1ceb51968d6c205cd28b7093 | 9,014 |
def load_sentiments(file_name=DATA_PATH + "sentiments.csv"):
"""Read the sentiment file and return a dictionary containing the sentiment
score of each word, a value from -1 to +1.
"""
sentiments = {}
for line in open(file_name):
word, score = line.split(',')
sentiments[word] = float(... | a98ae77a051ea3b599ee2fd5036e1bd33c1f4d64 | 9,015 |
def run_example(
device_id: str,
server_host: str = "localhost",
server_port: int = 8004,
plot: bool = True,
scope_length: int = 8192,
historylength: int = 1,
):
"""run the example."""
apilevel_example = 6 # The API level supported by this example.
# Call a zhinst utility function ... | e7f46a532b90fc1f208ebc2ae37b2216e2bd7561 | 9,016 |
def get_draft_url(url):
"""
Return the given URL with a draft mode HMAC in its querystring.
"""
if verify_draft_url(url):
# Nothing to do. Already a valid draft URL.
return url
# Parse querystring and add draft mode HMAC.
url = urlparse.urlparse(url)
salt = get_random_string(... | f8eaaa7daaba2b5bfe448b5386e88d9f738b0f5d | 9,017 |
def make_datum(source: str, img_id: str, sent_id: int, sent: str):
"""
Create a datum from the provided infos.
:param source: the dataset of the particular sentence.
:param img_id: id of the image
:param sent_id: id of the sentence (of the image)
:param sent: the sentence
:return: a dict of ... | 4814093519aad09e0f81d6e0841d130e1b2e43a4 | 9,018 |
def list_for_consumer(req):
"""List allocations associated with a consumer."""
context = req.environ['placement.context']
context.can(policies.ALLOC_LIST)
consumer_id = util.wsgi_path_item(req.environ, 'consumer_uuid')
want_version = req.environ[microversion.MICROVERSION_ENVIRON]
# NOTE(cdent):... | 37575bb0d05491d8a2e0933134fa530bf7699b3b | 9,019 |
import os
def get_supermean(name, season, data_dir, obs_flag=None):
"""Calculated supermeans from retrieved data, which are pickled Iris cubes.
:param name: Cube name. Should be CF-standard name. If no CF-standard name
exists the STASH code in msi format (for example m01s30i403)
... | 22872ceeb6754ba33f6755cae5d2c363bf30f559 | 9,020 |
def get_zcl_attribute_size(code):
"""
Determine the number of bytes a given ZCL attribute takes up.
Args:
code (int): The attribute size code included in the packet.
Returns:
int: size of the attribute data in bytes, or -1 for error/no size.
"""
opts = (0x00, 0,
0x... | 99782c86be2413410c6819a59eadf0daba326af2 | 9,021 |
def get_mappings():
"""We process the mappings for two separate cases. (1) Variables that vary by year,
and (2) variables where there are multiple realizations each year.
"""
# Set up grid for survey years. Note that from 1996 we can only expect information every other
# year. We start with 1978 as ... | a02ac60889ab2ef9524a50ec7eb03fe6a8b54917 | 9,022 |
def _get_function_name_and_args(str_to_split):
"""
Split a string of into a meta-function name and list of arguments.
@param IN str_to_split String to split
@return Function name and list of arguments, as a pair
"""
parts = [s.strip() for s in str_to_split.split(" | ")]
if len(parts) < 2:
... | 1dae51c87e727d7fa6a3a8012f9768b9ca3364e7 | 9,023 |
import os
import time
def runAndWatch(container, cgroup, watchCgroup, notify=None, wallClockLimit=None,
cpuClockLimit=None, pollInterval=1, notifyInterval=10):
"""
Run a container and watch it for time limits. Returns a dictionary with
container statistics.
"""
inspection = inspectCont... | 24179f4e2f554bedb0ee0b8507d777723cf220b1 | 9,024 |
import requests
def replicas_on_delete():
"""
This is a route for ALL NODES.
A (previous) neighbor node sends POST requests to this route,
so that a key-value pair replica is deleted in the current NODE.
"""
# The hash ID of the node-owner of the primary replica
start_id = request.form[... | ff8b4cc06ce7a640914bdd58ff897dc060f22d4b | 9,025 |
import os
def load(train_dir=train_dir, test_dir=test_dir):
"""
Load the dataset into memory.
This uses a cache-file which is reloaded if it already exists,
otherwise the dataset is created and saved to
the cache-file. The reason for using a cache-file is that it
ensure the files are ordered ... | f19c9d2220cd68a7f2722b6fdc2170d70cff4367 | 9,026 |
def pdf2(sigma_matrix, grid):
"""Calculate PDF of the bivariate Gaussian distribution.
Args:
sigma_matrix (ndarray): with the shape (2, 2)
grid (ndarray): generated by :func:`mesh_grid`,
with the shape (K, K, 2), K is the kernel size.
Returns:
kernel (ndarrray): un-norm... | 7477b33eab034d9ca5cac63fd1eedd4f6789f1ba | 9,027 |
def spell_sql(*args,**kwargs):
"""
list=[]
"""
if len(args[0])<=0:
return None
sql="SELECT * from `emotion_data` WHERE id ={}".format(args[0][0])
for index in args[0][1:]:
sql +=" or id ={}".format(index)
return sql | 5e5b231be2dabca75abed332864c8ae3d93b750e | 9,028 |
def is_within_bounds(bounds, point):
""" Returns true if point is within bounds. point is a d-array and bounds is a
dx2 array. bounds is expected to be an np.array object.
"""
point = np.array(point)
if point.shape != (bounds.shape[0],):
return False
above_lb = np.all((point - bounds[:, 0] >= 0))
... | 926c107a808d98f62c0323746112b6f73b5f89fe | 9,029 |
def weight_reduce_loss(loss, weight=None, reduction='mean', avg_factor=None):
"""Apply element-wise weight and reduce loss.
Args:
loss (Tensor): Element-wise loss.
weight (Tensor): Element-wise weights.
reduction (str): Same as built-in losses of PyTorch.
avg_factor (float): Ava... | b19b937f9b774dcac09f8949c2d1762743e7958e | 9,030 |
def list_of_paths():
"""
It lists all the folders which not contain PET images
"""
return ['.DS_Store', 'localizer', 'Space_3D_T2_FLAIR_sag_p2', 'AXIAL_FLAIR', 'MPRAGE_ADNI_confirmed_REPEATX2', 'Axial_PD-T2_TSE',
'Axial_PD-T2_TSE_repeat', 'MPRAGE_SAG_ISO_p2_ND', 'Axial_PD-T2_TSE_confi... | bc74024d49396f80947b3cb0a45066381b7d3af4 | 9,031 |
def convert_onnx_to_ell(path, step_interval_msec=None, lag_threshold_msec=None):
"""
convert the importer model into a ELL model, optionally a steppable model if step_interval_msec
and lag_threshold_msec are provided.
"""
_logger = logger.get()
_logger.info("Pre-processing... ")
converter = ... | 28843c1b588d4c1772c5c4be10e1a535b940703d | 9,032 |
def cdfRosconi(cdfThickness=np.linspace(0,1,1000),
alpha=1.71e11, beta=8.17, gamma=55.54):
"""
TODO: Not Yet Implemented
* Input to this function has units of mm for default parameters.
** Default values of alpha, beta and gamma derived from:
Rosconi et al. Quantitative appro... | 3f774c4be62c2b1b01430c7dce6aae4374693ae1 | 9,033 |
def compute_error_model(model_metadata, X_test, y_test, target,error_metric):
"""Computes the model MRR based on test data
:param model_metadata: a dictionary containing metadata about a model
:param X_test: a dataframe containing features specfic to the model being evaluated
:param y_test: a datafra... | 9cb1ede604f863c1eeab12a593c8b62527599d12 | 9,034 |
def column(df, s, column) -> ReturnType:
"""Gets the series of the column named `column`
"""
return df.loc[s, column].to_numpy(), 0 | 8d400c2425a062566e61c23361dd6a1f6e0ba8b7 | 9,035 |
def features_to_id(features, intervals):
"""Convert list of features into index using spacings provided in intervals"""
id = 0
for k in range(len(intervals)):
id += features[k] * intervals[k]
# Allow 0 index to correspond to null molecule 1
id = id + 1
return id | 74b0b201888a69c045ef140959876dd3e909f20d | 9,036 |
import torch
def index_initial(n_batch, n_ch, tensor=True):
"""Tensor batch and channel index initialization.
Args:
n_batch (Int): Number of batch.
n_ch (Int): Number of channel.
tensor (bool): Return tensor or numpy array
Returns:
Tensor: Batch in... | 52a16ad4afcf931ba4cda9c014d47050970995c5 | 9,037 |
from distutils.spawn import find_executable
import os
def which(binary_name, pathvar=None):
""" Deduces the path corresponding to an executable name,
as per the UNIX command `which`. Optionally takes an
override for the $PATH environment variable.
Always returns a string - an empty one for... | 6a1c02ea939e119df72c4ad1b3e685614218574d | 9,038 |
def load_titanic(test_size=0.2, random_state=1, cache_dir=None, cache_subdir='datasets'):
""" load titanic database """
path = find_path(DatasetEnum.titanic, cache_dir=cache_dir, cache_subdir=cache_subdir)
df = pd.read_csv(path, sep=",", na_values=["?"], keep_default_na=True)
# Shuffle DF and compute ... | a222a684a55bde482664b0b3072fb04047360f50 | 9,039 |
def mock_function_fail(*args, **kwargs):
"""
Mock a function that 'fails', i.e., returns a 1.
"""
print("\nmock> f({}) ==> 1".format(args)) # pragma: no cover
return 1 # pragma: no cover | ec2085e51a0809c9656d1831429858e14baf3f63 | 9,040 |
def get_field_result(client_id, field_id, count=1):
"""
на входе: id-поля, id-карты,
выход: последний результат поля
:return:
"""
with connection.cursor() as cursor:
cursor.execute(
"""
SELECT directions_napravleniya.client_id, directions_issledovaniya.napravleniy... | 7191705462f1fceb3dfca866c5fed96fa8019886 | 9,041 |
def parse_basic_profile_forms():
"""Parses and validates basic profile forms in the request.
Returns:
A dictionary containing user profile.
Raises:
ValueError: When validation failed.
"""
return {
'display_name': get_form_string('display_name', 32),
'contact_email':... | c8409bcc7de6a2c0a320859f90d54215888febf8 | 9,042 |
def fixture_success(request):
"""
Test Cases:
1. Hitting uncovered route as base user (logged in flow). Will return 200
since uncovered route is an open endpoint and thus Anonymous users can also
access it.
2. Hitting uncovered route as base user and HEAD request
3. Hitting uncovered route a... | 26603ce9203372e9ced217f75505b149942eee98 | 9,043 |
from typing import Optional
import csv
def get_quote_name(quote_number: int) -> Optional[str]:
""" used to help applications look up quote names based on the number
users.
"""
assert type(quote_number) in (int, type(None))
if quote_number is None:
return None
for key, value in cs... | 4a96ee42b37879469a67cb657d97aa321770fd83 | 9,044 |
def calc_floodzone(row):
"""Extracts the FEMAZONE of an SFHA based on each row's attributes.
This function acts on individual rows of a pandas DataFrame using
the apply built-in.
Parameters
----------
row : Pandas Series
A row of a pandas DataFrame
Returns
-------
str
... | 5bb6f3f7cfc1b6bce41ad7a752845287759c16ad | 9,045 |
def trans_you(ori_image, img_db, target_size=(8, 8)):
"""Transfer original image to composition of images.
Parameters
----------
ori_image : numpy.ndarray
the original image
img_db : h5py.File
image datasets
target_size : tuple
Returns
-------
res_img : numpy.ndarra... | f9717d2ddc9052bee103010a23328f5445c4edc5 | 9,046 |
from re import A
from re import T
def new_assessment():
"""
RESTful CRUD controller to create a new 'complete' survey
- although the created form is a fully custom one
"""
# Load Model
table = s3db.survey_complete
s3db.table("survey_series")
def prep(r):
if r.interact... | a4b1f9ba0a7e70349607f5cc70fdac72d75fb236 | 9,047 |
import types
import random
async def random_pokemon(connection: asyncpg.Connection, /) -> types.Pokemon:
"""Returns a random :class:`types.Pokemon`."""
records = await tables.Pokemon.fetch(connection)
return await _pokemon(connection, random.choice(records)) | b60659f236a4cbea998a77df211da92c18e4f0b8 | 9,048 |
import re
def remove_space(text):
"""
Funcion que elimina espacios
:param str text: texto a procesar
"""
return re.sub(r"\s+", " ", text).strip() | 729d26bb6acbaa8da4c945d2ea6646ebb90f3122 | 9,049 |
import base64
def getFilePathBase():
"""
获取请求url文件的文件路径
:return: php->base64 code
"""
code = """
@ini_set("display_errors","0");
@set_time_limit(0);
@set_magic_quotes_runtime(0);
header("Content-Type:application/json");
$res = array();$res["path"] = dirname(__FILE__);
echo ("<ek>... | afcb1a5bf2972a2b13a32edcd8a9b968742bf7f3 | 9,050 |
def extractHeldSimple(q, factoryConfig=None):
"""All Held Glideins: JobStatus == 5
q: dictionary of Glideins from condor_q
factoryConfig (FactoryConfig): Factory configuartion (NOT USED, for interface)
Returns:
dict: dictionary of Held Glideins from condor_q
"""
# Held==5
... | c942991bb0370b63364c1b8d5644713865d9ea82 | 9,051 |
def neighbors(stats1, stats2, max_val=1e5):
"""stats from cv.connectedComponentsWithStats."""
pts1 = np.concatenate(
(stats1[:, :2], stats1[:, :2] + stats1[:, 2:4]), axis=0)
pts2 = np.concatenate(
(stats2[:, :2], stats2[:, :2] + stats2[:, 2:4]), axis=0)
dist = np.abs(pts1[:, None] - pts... | 1b6aecad76f968cd83d40ee6531fcbd6b3b0df6c | 9,052 |
from typing import Optional
def shortest_substring_containing_characters(text: str, char_set: set) -> Optional[str]:
"""
O(n) & O(k)
"""
start = 0
end = -1
count_char = defaultdict(int) # char and its count
found_set = set()
for index, char in enumerate(text):
if char in char... | 4682a01b1a4331dbada7a234c908d1c53639e69a | 9,053 |
def refine_grid(
grid,
cb,
grid_additions=(50, 50),
ntrail=2,
blurs=((), ()),
metric=None,
atol=None,
rtol=None,
extremum_refinement=None,
snr=False,
):
"""Refines an existing grid by adding points to it.
Parameters
----------
grid : array
cb : callbable
... | c84a365bcc271622fd49a01d89303aa2adb1c624 | 9,054 |
from datetime import datetime
def last_week(today: datetime=None, tz=None):
"""
Returns last week begin (inclusive) and end (exclusive).
:param today: Some date (defaults current datetime)
:param tz: Timezone (defaults pytz UTC)
:return: begin (inclusive), end (exclusive)
"""
if today is N... | a210707e2a479fe4e8b98a137c0ade684d4dd6da | 9,055 |
def get_velocity_limits():
"""
"""
velocity_limits = {}
for i in range(6):
try:
velocity_limits['a{}'.format(i+1)] = float(pm.textField(
't_A{}vel'.format(i+1),
q=True,
... | 68f58ed715a39478d119af1e1aabe54fa7ec6094 | 9,056 |
def decode_item_length(encoded_data: Bytes) -> int:
"""
Find the length of the rlp encoding for the first object in the
encoded sequence.
Here `encoded_data` refers to concatenation of rlp encoding for each
item in a sequence.
NOTE - This is a helper function not described in the spec. It was
... | d005b8050abaaba76bd5d3a24419f86c462af2b2 | 9,057 |
def pxor(a1, a2, fmt=None):
"""Bitwise XOR"""
return c2repr(_inconv(a1) ^ _inconv(a2), fmt) | a65ada1901fc5bfa202af5128c3e5b6e54d5f6dc | 9,058 |
from typing import Tuple
def milestone_2_test_1_initial_val(lattice_grid_shape: Tuple[int, int]) -> Tuple[np.ndarray, np.ndarray]:
"""
Return initial conditions
Args:
lattice_grid_shape: lattice grid [lx, ly]
Returns:
density with 0.5, but one peak in the middle, velocities 0
""... | 89d6ed57e93859182a92946e94adc2d26631f6e3 | 9,059 |
def test_element_html_call_get_attribute(monkeypatch, browser_driver):
"""Calls el_or_xpath WebElement attr get_attribute"""
called = []
class FakeWebElement:
def get_attribute(self, val):
called.append(('get_attribute', val))
return 42
@browser_driver.register
cla... | 7b3bcc3ba4a8c030b15649b240f75bf9bed71570 | 9,060 |
import time
def moving_dictators(session, system_ids):
"""
Show newly controlling dictators in the last 5 days.
Show all controlling dictators in monitored systems.
Subqueries galore, you've been warned.
Returns: A list of messages to send.
"""
gov_dic = session.query(Government.id).\
... | 9d9808d608190dae0a9f57980312e2ae830c492c | 9,061 |
def get_alt_for_q_with_constant_mach(q, mach, tol=5., SI=False, nmax=20):
# type: (float, float, float, bool, int) -> float
"""
Gets the altitude associated with a dynamic pressure.
Parameters
----------
q : float
the dynamic pressure lb/ft^2 (SI=Pa)
mach : float
the mach to... | f9286d7f742a8e8e3f25d63210180dbd7bc2fcc7 | 9,062 |
def addMetadataFlags(metadataChunk, numberOfMetadataChunks):
"""Adds binary flag the number of metadata chunks this upload has (uint8).
Arguments:
metadataChunk {bytes} -- First metadata chunk already encrypted, but before signing.
numberOfMetadataChunks {int} -- Self-explanatory.
Returns:
bytes -- Metadat... | aeaefd8e1cd62524d435ee95bc272a9a676680c0 | 9,063 |
def table(a):
"""get tabular view of obj, if available, else return obj"""
if misc.istablarray(a):
return a.__view__('table')
return a | e04b53f40203fbeeb3104f5e46bab87ab3304269 | 9,064 |
def parse_quadrupole(line):
"""
Quadrupole (type 1)
V1: zedge
V2: quad gradient (T/m)
V3: file ID
If > 0, then include fringe field (using Enge function) and
V3 = effective length of quadrupole.
V4: radius (m)
V5: x misalignment error (m)
V6: y misalignment error (m)... | 2e9748fb0eabe51383fcb1ff47a7278dda622e44 | 9,065 |
def cases_vides(pave):
"""fonction qui cherche toutes les cases vides ayant des cases adjacentes
pleines dans un pavé (où pavé est un tableau de tuiles ou de cases vides)
retourne le tableau contenant les positions de ces cases vides et les
cases adjacentes en fonction de leur position"""
result = [... | 2d2de1651f000f48ab32e484f3f6b465231248b5 | 9,066 |
def _create_scalar_tensor(vals, tensor=None):
"""Create tensor from scalar data"""
if not isinstance(vals, (tuple, list)):
vals = (vals,)
return _create_tensor(np.array(vals), tensor) | ef41eabc66eda8739a78931d53ccc6feb8dfc6bb | 9,067 |
import importlib
def is_importable(name):
""" Determines if a given package name can be found.
:param str name: The name of the pacakge
:returns: True if the package can be found
:rtype: bool
"""
return bool(importlib.util.find_spec(name)) | 548044b06d250af7f49dc3c9b4144490a5bbcc83 | 9,068 |
def make_pipeline(*steps, **kwargs):
"""Construct a Pipeline from the given estimators.
This is a shorthand for the Pipeline constructor; it does not require, and
does not permit, naming the estimators. Instead, their names will be set
to the lowercase of their types automatically.
Parameters
... | a036c345208333b6f6d9d33998d06b282c9aa711 | 9,069 |
import logging
def say_hello(name):
"""
Log client's name which entered our application and send message to it
"""
logging.info('User %s entered', name)
return 'Hello {}'.format(name) | b79865cca34d1430bf47afabf7c96741d59ac560 | 9,070 |
import numpy
def dual_edges_2(vertices):
"""
Compute the dual edge vectors of a triangle, expressed in the
triangle plane orthonormal basis.
:param vertices: The triangle vertices (3 by n matrix with the vertices as rows (where n is the dimension of the
space)).
:returns: The triangle dua... | 64ff173ef00dc4d916f00f67c7a35da25d81b535 | 9,071 |
def merge_dicts(dictionaries):
"""Merges multiple separate dictionaries into a single dictionary.
Parameters
----------
dictionaries : An iterable container of Python dictionaries.
Returns
-------
merged : A single dictionary that represents the result of merging the all the
... | 1a2b5f3c539937e2e27a55ce3914f7368f0a7296 | 9,072 |
from typing import Union
from typing import Callable
def noise_distribution_to_cost_function(
noise_distribution: Union[str, Callable]
) -> Callable[[str], str]:
"""
Parse noise distribution string to a cost function definition amici can
work with.
The noise distributions listed in the follow... | d26ae31211ab5a9fae2b350391ab2a835ba02758 | 9,073 |
from datetime import datetime
def serializer(cls, o):
"""
Custom class level serializer.
"""
# You can provide a custom serialize/deserialize logic for certain types.
if cls is datetime:
return o.strftime('%d/%m/%y')
# Raise SerdeSkip to tell serde to use the default serializer/deseri... | 6e9bfbb83ede2c2da412b70741d793c6e24e05ef | 9,074 |
def parse_args():
""" parse command-line arguments """
usage = """Usage: bcfg2_svnlog.py [options] -r <revision> <repos>"""
parser = OptionParser(usage=usage)
parser.add_option("-v", "--verbose", help="Be verbose", action="count")
parser.add_option("-c", "--config", help="Config file",
... | 30ac6035e375b692a516903055b7916a601e98a5 | 9,075 |
import array
def compute_com(kpt_ids, pose_keypoints):
"""Computes center of mass from available points for each pose.
Requires at least one arm (shoulder, elbow, wrist), neck and hips.
Required keypoints to return result: at least one arm with hip, neck and [nose OR ear]
:param kpt_id: IDs of keypo... | 16e884ef76bdc21695349e6f0f9f9948426c5b8c | 9,076 |
import os
def certificate(cert_name):
"""Return the path to the PEM file with the given name."""
return os.path.join(os.path.dirname(__file__), 'lib', cert_name) | 5dc02c85158ae7b020f069976a581d41f31d338c | 9,077 |
def _MinimumLineCount(text: str, min_line_count: int) -> str:
"""Private implementation of minimum number of lines.
Args:
text: The source to verify the line count of.
Returns:
src: The unmodified input src.
Raises:
NoCodeException: If src is less than min_line_count long.
"""
if len(text.str... | 037400aed0503dabee61a8d5088ca2e4b3ab34a6 | 9,078 |
def RationalQuadratic1d(
grid,
corrlen,
sigma,
alpha,
prior=None,
mu_basis=None,
mu_hyper=None,
energy=0.99
) -> Formula:
"""Rational quadratic kernel formula
"""
kernel_kwargs = {
"corrlen": corrlen,
"sigma": sigma,
"a... | 56d61ef851ac5c84336f7f6bda19885d85b42b26 | 9,079 |
def plot_feature_importance(feature_keys, feature_importances, ax=None, **kwargs):
"""
Plot features importance after model training (typically from scikit-learn)
Parameters
----------
feature_keys: list of string
feature_importances: `numpy.ndarray`
ax: `matplotlib.pyplot.axes`
Return... | aa3a747002d7c82f91de52e011b269b105c4bb70 | 9,080 |
def simulate_timestamps_till_horizon(mu, alpha, beta, Thorizon = 60, \
seed=None, node=None, output_rejected_data=False):
"""
Inputs:
mu, alpha, beta are parameters of intensity function of HP
"""
#################
# Initialisation
#################
rng = default_rng(seed) # get ins... | 6d9e7a7c747c7a07fe94069017b32a47e3d35ac2 | 9,081 |
import logging
import time
import torch
from datetime import datetime
def jp_inference_on_dataset(model, data_loader, evaluator):
"""
Run model on the data_loader and evaluate the metrics with evaluator.
Also benchmark the inference speed of `model.forward` accurately.
The model will be used in eval m... | e18113b4fc47bf48562bdee8dc8e4a2bdbe4c884 | 9,082 |
def boolToYes(b):
"""Convert a Boolean input into 'yes' or 'no'
Args:
b (bool): The Boolean value to be converted
Returns:
str: 'yes' if b is True, and 'no' otherwise.
"""
if b:
return "yes"
else:
return "no" | ff94b66b5a166592062bf1d5b286b425e7997304 | 9,083 |
def top_symptoms(dic, title):
"""Find and plot top symptoms in the dictionary based on count
Args:
dic (dict): Dictionary containing text-count pair
Returns:
[dictionary]: Top 5 symptoms with their count
"""
assert isinstance(dic, dict) and len(dic) > 0, "dic is not a nonempty dict... | 1acfcec04d2a5c11f7f1a4e90eb9142de042c875 | 9,084 |
def _calc_z(h: DataArray, zice: DataArray, zeta: DataArray,
s: DataArray, Cs: DataArray,
hc: float, Vtransform: int) -> DataArray:
"""
Calculate grid z-coord depth given water depth (h), iceshelf depth (zice),
sea surface (zeta), and vertical grid transformation parameters.
Inpu... | 6580d3c2825cbea0bba33d03b2c0ad62bbd5b227 | 9,085 |
def gap_loss(preds, D, A):
"""
This module implement the loss function in paper [Azada Zazi, Will Hang. et al, 2019] Nazi, Azade & Hang, Will & Goldie, Anna & Ravi, Sujith & Mirhoseini, Azalia. (2019). GAP: Generalizable Approximate Graph Partitioning Framework.
Args:
preds (tensor(float)): output ... | 9418ee8bda3e7b1a5284c36412fefa158eec0f91 | 9,086 |
def number_of_hole(img, hole_img, hole_counter):
""" 判斷hole的數量去執行相對應的函式
0個hole執行zero_of_hole
1個hole執行one_of_hole
2個hole執行my_text.set("Answer : 8")
大於2個hole則執行my_text.set("Error : holes number = " + str(hole_counter) + "( > 2 )")) """
switcher = {
... | 583fd05b0f10e3ea1c7cee11bd416b8d41d7f840 | 9,087 |
def get_merged_by_value_coords(spans_value, digits=None):
"""returns adjacent spans merged if they have the same value. Assumes
[(start, end, val), ..] structure and that spans_value is sorted in
ascending order.
Arguments:
- digits: if None, any data can be handled and exact values are
... | c186c503972b4b48e627c14df77bd5a780b59f5b | 9,088 |
def vint_mask_for_length(length):
"""
Returns the bitmask for the first byte of a variable-length integer (used for element ID and size descriptors).
:arg length: the length of the variable-length integer
:type length: int
:returns: the bitmask for the first byte of the variable-length integer
:rtype: int
... | 92fe3cb0fa09713ff4b650349294a2b241bb3918 | 9,089 |
from itertools import tee
def parse(tokens):
"""
S-expr ::= ( S-expr* ) | AtomSymbol | ' S-expr
' S-expr = (quote S-expr)
"""
def _parse(tokens):
while True:
token = next(tokens)
if token == "(":
s_expr = []
while True:
... | 90c8e3cd8482899749d30d5344390cfd5f24989f | 9,090 |
import numpy
import warnings
def preproc(raw,
dark=None,
flat=None,
solidangle=None,
polarization=None,
absorption=None,
mask=None,
dummy=None,
delta_dummy=None,
normalization_factor=1.0,
empty=None... | 9a21af39470b1f48c81d043a1d4a9ca045804093 | 9,091 |
import scipy
def lB_2_T(lB, T0=298, sigma=4E-10, ret_res=False):
"""Solves for temperature at given Bjerrum length under condition from Adhikari et al. 2019 that lB/l = 1.2 at 298 K."""
def cond(T, lB, sigma=sigma):
"""condition function whose root gives the temperature T given Bjerrum length lB."""
... | 73d349d95cd69076874e7147280322535b6b1651 | 9,092 |
from typing import Iterable
from typing import Union
import dataclasses
def make_datacls(
cls_name: str,
fields: Iterable[Union[tuple[str, type], tuple[str, type, dataclasses.Field]]],
init: bool = True,
**kwargs,
) -> type:
"""
Return a new dataclass. This function wraps the Python dataclasse... | d3797443212504605310ed75fbcb5ce37570b868 | 9,093 |
def square_loss(X, y, theta, reg_beta=0.0):
"""Computes squared loss and gradient.
Based on mean square margin loss.
X: (k, n) data items.
y: (k, 1) result (+1 or -1) for each data item in X.
theta: (n, 1) parameters.
reg_beta: optional regularization strength, for L2 regularization.
Retu... | 3a1cc74eed3abd9c3a7921c9ea02e2169594f504 | 9,094 |
import glob
def open_mf_wrf_dataset(paths, chunks=None, compat='no_conflicts', lock=None,
preprocess=None):
"""Open multiple WRF files as a single WRF dataset.
Requires dask to be installed. Note that if your files are sliced by time,
certain diagnostic variable computed out of a... | 9cf95b6da852406b2b24862604cd357c01f88a93 | 9,095 |
from typing import Optional
from pathlib import Path
def parse_args_and_add_yaml_variables(parser: ArgumentParser,
yaml_config_file: Optional[Path] = None,
project_root: Optional[Path] = None,
fail_on_unk... | 7d4c560a4887afd432da13df1e839cada329dd5a | 9,096 |
def load_graph(model_file):
"""Loads a TensorFlow graph from file."""
graph = tf.Graph()
with graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(model_file, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(o... | 41e097afd34631ce8b2b94c9a67121886a568ede | 9,097 |
def find_children(node, tag, xml_ns, ns_key):
"""
Finds the collection of children nodes
Parameters
----------
node : ElementTree.Element
tag : str
xml_ns : None|dict
ns_key : None|str
"""
if xml_ns is None:
return node.findall(tag)
elif ns_key is None:
retu... | b51d9f588661c3f609dc53adaa328f974e17d5fb | 9,098 |
import re
def normalize_string(string, ignore_spaces, ignore_punctuation):
"""Normalizes strings to prepare them for crashing comparison."""
string = string.upper()
if ignore_punctuation:
string = re.sub(r"[^1-9a-z \n\r\t]", "", string, flags=re.I)
if ignore_spaces:
string = re.sub(r"\... | 31de2b9644eb0943470430c6c3f2ea8a94dfb3cf | 9,099 |
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