content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def sum_fun(x, backend):
"""
Base function for summing all elements in a tensor
"""
func = "sum"
if backend == "tensorflow":
backend = "tensorflow.math"
func = "reduce_sum"
return get_func(func, backend)(x) | 6c5231f67ed3f464dd7bf3bbbe3b0ed6c6fb6740 | 67,365 |
def measure_naptan_groups(gdf, naptan_column_name="LocalityName"):
"""[summary] this function measures the number of groups present within
the given geodataframe, when groupbed the [default LocalityNames]
Args:
gdf ([type]): [description]
naptan_column_name ([type]): [description]
Ret... | 725ce929fb19f0e2fdf051f6daf9c1d86e125d0f | 67,367 |
def CreateParser():
"""Expose _CreateParser publicly."""
# Name _CreateParser is needed for commandline library.
return _CreateParser() | 888ec2237c0e4bda8c44f5fece4f184f1e870e2c | 67,368 |
def update_dataset(dataset_id: int,
request: schemas.DatasetUpdate,
db: Session = Depends(deps.get_db),
current: model.User = Depends(deps.get_current_user)):
"""
Update a dataset.
"""
dataset = crud.dataset.get(db=db, id=dataset_id)
if datase... | 5a72a30b0a27cd9df97c6131cd76785fc5050504 | 67,369 |
def calculate_ts_stability_index_batch(ts, **kwargs):
"""Returns series with stability index calculated for every point of ts, where possible"""
si_values = []
timestamps = []
for time, row in ts.iterrows():
ts_history = ts[:time].iloc[:-1]
try:
si_value = calculate_ts_stabil... | a9bfaa3e3d8393443c1113d5356616067795ca0b | 67,370 |
import click
import functools
def ip_lookup_command(function):
"""Decorator that groups decorators common to ip and quick subcommand."""
@click.command()
@click.argument("ip_address", callback=ip_addresses_parameter, nargs=-1)
@click.option("-k", "--api-key", help="Key to include in API requests")
... | 1da900e8fd96e486f58e10708c99e797a818905a | 67,371 |
from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
def _is_parameter_search_estimator(estimator):
"""
:return: `True` if the specified scikit-learn estimator is a parameter search estimator,
such as `GridSearchCV`. `False` otherwise.
"""
parameter_search_estimators = [
... | 24a1c51cea98b36923d6ac827d1c4481d75bb460 | 67,372 |
from typing import Dict
from typing import List
import re
def clean_utterance(utterance: Dict[str, str],
remove_english: bool = False,
english_words: set = None,
punctuation: str = None,
special_cases: List[str] = None) -> (List[str], int... | 362b835ec894495d74c984b082bb173ca2e27e1a | 67,373 |
def get_all_functiondef(root):
"""
Get all FunctionDef nodes
:param root:
:return:
"""
if root['name']=='FunctionDef':
# block(FunctionDef) begin id
begin_id=root['id']
end_id=get_end_id(root)
return 'begin:%s,end:%s'%(begin_id,begin_id+end_id-1)
else:
... | b6687059c958d49795f0d2fb521bd8ca488c5507 | 67,374 |
def bookmark_json(userkey, urlhash):
""" Serialise bookmark to json """
try:
bookmark = Bookmark.get(
Bookmark.url_hash == urlhash,
Bookmark.userkey == userkey,
Bookmark.status == Bookmark.VISIBLE
)
return jsonify(bookmark.to_dict())
except Bookmar... | 30321366ee5a32484664599d9223ff56ee0768e9 | 67,375 |
from typing import Mapping
def betaReduce(lhs, lhsEnv, rhs, rhsEnv):
"""β-reduction: (λV.M)N → M[V := N]"""
exp = lhs.exp
if isinstance(exp, Mapping):
return (exp.exp, Env(Mapping(exp.var, clos(rhs, rhsEnv)), lhsEnv))
else:
return (exp, Env(clos(rhs, rhsEnv), lhsEnv)) | 1bd36a551280721596e502be0db2e5aa0a0b6d8b | 67,376 |
def _check_for_iocs(loop, context, indent):
"""
Check the variables modified in a loop to see if they were
set to interesting IOCs.
"""
indent_str = " " * indent
lhs_visitor = lhs_var_visitor()
loop.accept(lhs_visitor)
lhs_var_names = lhs_visitor.variables
ioc_str = indent_str + "# C... | f9d4a8fa2e1953314cb422882a2eb6d1e1f7b7eb | 67,377 |
import ssl
import concurrent
async def patch(
uri: str,
headers: t.Dict[str, str] = {},
body: t.Optional[bytes] = None,
json: t.Union[t.Dict[str, t.Any], JsonApiData] = None,
query: t.Dict[str, t.List[str]] = {},
timeout: t.Optional[float] = None,
blocksize: int = 8192,
datacls: t.Type... | 32101f2a036ee846fdd8a0c5ed7873f5726a3bfe | 67,378 |
def edit_orcid(request):
"""
Send a user to orcid.org for authorization to link to their ORCID account, then redirect them to
views/auth_orcid to save their iD and other token information. Also provide the option to unlink their
ORCID account from their account.
"""
if request.method == 'POST'... | 2305ac8e38430919a807bdd0612115992b416065 | 67,379 |
import math
def calculate_distance(psi, angle_in_degrees):
""" Calculate the distance the mudball flies. """
angle_in_radians = math.radians(angle_in_degrees)
distance = .5 * psi ** 2 * math.sin(angle_in_radians) * math.cos(angle_in_radians)
return distance | 47eb9acb71f5c11b26002ec38e37410db62c2e05 | 67,380 |
import json
def clear_dataflow_run(dataflow_run_id:str):
"""
Clear an orphaned dataflow run.
:param dataflow_run_id:
:return:
"""
payload = {"orchAction": "clear_dataflow_run",
"dataflow_run_id": dataflow_run_id}
json_payload = json.dumps(payload)
pickledJsonObj = __bo... | 453fee04e72c54b7f2891f5e7f5b89d913778f42 | 67,381 |
def custom_path_fs_io_manager(init_context):
"""Built-in IO manager that allows users to custom output file path per output definition.
It requires users to specify a base directory where all the step output will be stored in. It
serializes and deserializes output values (assets) using pickling and stores ... | 04aeaa321d0b998959401ca6190cc45385edae79 | 67,382 |
def sghmc_naive_nomh_noresample_multi(du_hat_func, epsilon, nt, m, M, V, theta_init, r_init, formula):
"""
This is a function to realize Naive Stochastic Gradient Hamiltonian Monte Carlo
without Metropolis-Hastings correction in multidimensional cases without resampling
procedure.
"""
B = 1/2*... | e704394e1f7f8960bea804e6f1a9188acc069ff5 | 67,383 |
import pathlib
import json
def load_json(filepath):
"""
Loads the metrics in a dictionary.
:param log_dir: The directory in which the log is saved
:param metrics_file_name: The name of the metrics file
:return: A dict with the metrics
"""
if isinstance(filepath, pathlib.Path):
fil... | 1dd8ff7822228bc0173a66df626902a723338d55 | 67,384 |
def super_scrub(data):
"""Run words through a comprehensive list of filtering functions.
Expects a dictionary with key "words"
"""
for technique in data['words']:
data['words'][technique] = normalization.uniquify(
normalization.remove_odd_sounding_words(
normalizatio... | d81557232ac99b89d24144c5d44bd94d41340d87 | 67,385 |
from typing import Callable
import random
def choose(option1: Callable = lambda: None, option2: Callable = lambda: None):
"""
Randomly run either option 1 or option 2
:param option1: a possible function to run
:param option2: another possible function to run
:return: the result of the function
... | 0f0ecbc945de9f6d5698cd86103265eccf5708e6 | 67,386 |
def compute_embeddings(encoder, data_batches):
"""Computes sequence embeddings according to a specified encoder."""
vectors = []
for batch in iter(data_batches):
X, Y = batch
X_embedded = encoder(X)
for vec in np.array(X_embedded):
vectors.append(vec)
vectors = np.ar... | 5c9d6e9bb617e43522044255948639c01d6b06a4 | 67,387 |
def while_array_parser(self, desc, node=None, parent=None, attr_index=None,
rawdata=None, root_offset=0, offset=0, **kwargs):
"""
"""
try:
orig_offset = offset
if node is None:
parent[attr_index] = node = desc.get(NODE_CLS, self.node_cls)\
... | 365d8d115f4b677177f1214c78d4957a78745252 | 67,388 |
def get_all() -> [User]:
"""
Helper function to return all users
:returns: all users.
"""
return User.objects.all() | 79864d2a862610bed414f2ad7cebbee20055e638 | 67,389 |
def get_category(id):
""" Get category. """
category = Category.query.get(id)
if category is not None:
response = {"category": category.to_dict()}
return make_response(jsonify(response), 200)
abort(404) | 15e1030b4c3b6e5d00f7697cd7e392a5bc5fcd8d | 67,390 |
def get_repo_service():
"""Factory method that returns configured RepoService instance.
If the service is not configured, returns None. Also acts as a mocking point
for unit tests.
"""
cas_service = cas.get_cas_service()
if not cas_service: # pragma: no cover
return None
return RepoService(
ca... | 75966851961208486c1d28e5051f30266dfe7d0d | 67,391 |
from typing import List
def search_etfs(to_search) -> List[str]:
"""Search for an etf string in list of ETFs
Parameters
----------
to_search: str
String to match
Returns
-------
matching_etfs: List[str]
List of matching ETF names
"""
all_symbols, all_names = get_a... | f56972605a45c5308a311eef1dac5ea34736aa2d | 67,392 |
def separable_hnn_siren(input_h_s=None, input_model=None):
"""
Separable Hamiltonian network using Siren network.
:return:
"""
if input_h_s:
h_s = input_h_s
model = input_model
else:
network = SirenNet(
dim_in=2,
dim_hidden=100,
dim_ou... | 08a1ef7d25304fcbd1d5ef568a420b70e0da0464 | 67,393 |
async def update_password(username: str = Form(...), old_password: str = Form(...), new_password: str = Form(...)):
"""パスワードの更新"""
res = search_username(cur=cur,username=username)
if res == None:
raise HTTPException(status_code = 400,detail="ユーザーが登録されていません。")
if not verify_password(old_pass... | bbec78a71eaf91fa92eeb1dd6d0f19fb7b767f63 | 67,394 |
import time
def num_to_str_data(str_date: int) -> str:
"""
num to str format
:param str_date: time of int format
:type str_date: int
:return: format time
:rtype: str
"""
str_date = str_date / 1000
str_date = time.localtime(str_date)
strp_time = time.strftime("%Y-%m-%d %H:%M:%S"... | e3fb56132a9d365d7bbc89e11e010d0d1ed19ea9 | 67,395 |
def transform_response_to_context_format(data: dict, keys: list) -> dict:
"""
Transform API response data to suitable XSOAR context data.
Remove 'x-ms' prefix and replace '-' to '_' for more readable and conventional variables.
Args:
data (dict): Data to exchange.
keys (list): Keys to fi... | 34f1a613654deb71581bcd33757b8741840ae44f | 67,396 |
def GetsoftwareVersions(node, layers='core') :
"""Get the schema:softwareVersion(s) we find on this node (or [] ), within any of the specified layers."""
return GetTargets(Unit.GetUnit("softwareVersion", True), node, layers=layers ) | 851678659540482c4b289410f1e9407c97990fbc | 67,397 |
from typing import List
import re
from typing import Iterator
def txt_channel_finder(bot: Red, chaninfo: str) -> List[discord.TextChannel]:
"""
custom text channel finder
"""
_id_regex = re.compile(r"([0-9]{15,21})$")
def _get_id_match(argument):
return _id_regex.match(argument)
matc... | f751af05bdcdf207a42fd08e77fc780e14478fef | 67,398 |
import torch
def calculate_gradcam_metrics(no_norm_gc_mask_numpy: torch.Tensor, segm: torch.Tensor):
"""
Measure gradcam metric
@param segm - true mask, shape B x 3 x H x W
@param no_norm_gc_mask_numpy - Grad-CAM output w/o normalization, shape B x 1 x H x W
@return sum of gradcam attention of ev... | 4d3ab9c9a694b88ef83efcc94271d21d0c1f8e17 | 67,399 |
def gaussian_noise(img):
""" Apply random noise to the image. """
cv.randu(img, 0, 255)
return {
"points": None,
"line_map": None
} | 3ec289b7eb71db0c235082ea476952c0140f4f53 | 67,400 |
def per_field_value(values, fields):
""" This normalises all patches relative to their field.
'fields' is a map of field numbers to a list of patches in that field.
"""
field_list = list(fields.values())
# We calculate the maximum and minimum values for each field.
maxs = [max((values[inde... | b51e344463d4d75f21ab8fc3a58d6201249fc2dc | 67,401 |
import torch
def one_hot(y, K, smooth_eps = 0): # pylint: disable=invalid-name
"""One-hot encodes a tensor with optional label smoothing.
Args:
y: A tensor containing the ground-truth labels of shape (N,), i.e. one label
for each element in the batch.
K: The number of classes.
smooth_eps: Labe... | ee47f9c778d875834c49c098ded4936edb104887 | 67,402 |
def grids(request, template_name="grid/grids.html"):
"""lists grids
Template context:
* ``grids`` - all grid objects
"""
# annotations providing bad counts
#grids = Grid.objects.annotate(gridpackage_count=Count('gridpackage'), feature_count=Count('feature'))
return render(request, template... | 36110a0d5ce9192c9cf931b44c6aba2d193947bf | 67,404 |
import random
def generate():
"""
Generates a quote based on the internal markov chain.
:raises: ValueError: if parsing has not occured and the internal chain is invalid
"""
# If not parsed, fail.
if not _GRAPH[_START]:
raise ValueError("Please initilise the internal chain using parse(... | 1b5f55c2c6387dd829508c8eb2f9789f8685b42f | 67,405 |
def f_rank_classif(X, y):
"""
Same idea as f_classif, but computed on ranks
"""
X, y = check_X_y(X, y, accept_sparse=["csr", "csc", "coo"])
assert(isinstance(X, np.ndarray))
X = np.array([rankdata(feat_vector) for feat_vector in X])
args = [X[safe_mask(X, y == k)] for k in np.unique(y)]
... | 958e4bfb2d9c82f55094a2957eae197fc0d702e3 | 67,406 |
def index(request):
"""The home page."""
continent_counts, total_countries = display_country_totals()
context = {
'countries_per': continent_counts, # amount of countries per continent
'total_countries': total_countries, # total amount of countries in world
}
return render(request, '... | 11439688de8f20ca559d257e96ccfe15050e0716 | 67,407 |
def get_order_coeff_from_expr(expr, symb, order):
"""
example:
3*s**2 -4*s + 5, s, 3 -> 0
3*s**2 -4*s + 5, s, 2 -> 3
3*s**2 -4*s + 5, s, 1 -> -4
3*s**2 -4*s + 5, s, 9 -> 0
"""
p = sp.Poly(expr, symb, domain = "EX")
default = 0
return p.as_dict().get( (order,), def... | 791205bf4af1f8aeeb12fb22bfeb73ca8037885a | 67,408 |
def decodeTcpdump(FileName,**options):
"""
Function to extract RSSI information stored in a .txt file
Input
FileName Name of .txt file, input as string including file type termination
Output
addressList Dictionary with address names and index where they are stored
RSSI m... | ca04d1fa2e3d1d103ee032112461aedfb5d211ef | 67,409 |
import torch
def train(model, scaler, train_loader, epochs, optimizer, criterion, train_on_gpu):
"""
This is the training method that is called by the PyTorch training script. The parameters
passed are as follows:
model - The PyTorch model that we wish to train.
scaler - Scaler object... | 8ddad0b42a1fbabc961db8ae3bf8b2a9ac4c0714 | 67,410 |
from datetime import datetime
def home():
"""Renders the home page."""
return render_template('index.html',
posts=posts,
title='Contact',
year=datetime.now().year,
message='Your contact page.') | 6b97257331bae9134e6f92022f89dfaa3b30e7ba | 67,411 |
def getClasses():
"""
Returns a list of class ids from the database
"""
if 'email' not in session or session['email'] is None:
abort(401)
email = mailsane.normalize(session['email'])
if email.error:
abort(400)
return jsonify({'classList' : dbworker.getClasses(str(email)), '... | cc83b795dbfed3a0f7beb957d93683669d9e7e13 | 67,412 |
from typing import Optional
def disconnect(ip: Optional[str]) -> bool:
"""
Disconnect from the given device ip
:param ip: device ip
:return: true if successfully disconnected
"""
log().verbose(f"Disconnecting from {ip}..")
if execute("disconnect", ip=ip):
zope.event.notify(events.A... | 88198c24324b8eedfcb91c418a66980914e2636b | 67,413 |
def run_in_executor(executor, func, *args, **kwargs):
"""Run a blocking function in a separate thread in the tornado ioloop.
Copied from function which is added in a later version: https://www.tornadoweb.org/en/stable/_modules/tornado/ioloop.html#IOLoop.run_in_executor
Improves a little on the function by... | b31fc90a91c1a2cc021c5bb0b573283bc110e5b0 | 67,414 |
from typing import Callable
def trigger_redraw(fn: Callable) -> Callable:
"""Method decorator for functions that need to trigger a re-draw.
Parameters
----------
fn : Callable
The function that needs to trigger a re-draw, e.g. because it changes
the appearance of the canvas.
Retu... | 4ef063fd85a81e3167cddf98a1311bd40ae04c1c | 67,416 |
def rsa_pkcs1v15_verify(certificate_or_public_key, signature, data, hash_algorithm):
"""
Verifies an RSASSA-PKCS-v1.5 signature.
When the hash_algorithm is "raw", the operation is identical to RSA
public key decryption. That is: the data is not hashed and no ASN.1
structure with an algorithm identi... | 788b5473fc8310c3b88ec7c39514039cb8f988d0 | 67,417 |
from typing import Optional
def to_timedelta(
arg,
unit: Optional[str] = None,
errors: str = "raise",
):
"""
Convert argument to timedelta.
Parameters
----------
arg : str, timedelta, list-like or Series
The data to be converted to timedelta.
unit : str, optional
D... | 77ec21509d69b60512d31be81dce6cf5d2317e9b | 67,418 |
def scheduling_blocks():
"""Return list of Scheduling Block instances known to SDP."""
sbi_list = SchedulingBlockInstanceList()
return dict(active=sbi_list.active,
completed=sbi_list.completed,
aborted=sbi_list.aborted) | a3171d351ca0a863340e22d2610c5c96999a393c | 67,419 |
def odd_ext(x, n, axis=-1):
"""Generate a new ndarray by making an odd extension of x along an axis.
Parameters
----------
x : ndarray
The array to be extended.
n : int
The number of elements by which to extend x at each end of the axis.
axis : int
The axis along which t... | bd5b1da526e8a97dcc8d26f42f56d695057021b2 | 67,420 |
import itertools
def patches_from_ct(ct_array, meta, patch_shape=None, centroids=None, stride=None, pad_value=0):
""" Given a CT scan, and a list of centroids return the list of patches
of the desired patch shape.
This is just a wrapper over crop_patch generator.
Args:
ct_array (np.ndarray):... | dd3f7e034477938c3239eda210904034de3ab64a | 67,421 |
def delivery_point_deliveries_waiting(request, campaign_id, delivery_point_id,
campaign, delivery_point, multi_tenant):
"""
:return: JsonResponse
"""
columns = _columns
if multi_tenant:
deliveries = GoodDelivery.objects.filter(Q(choosen_delivery_point__c... | 4411159e21d013c4e9218715c26cf4d809e51912 | 67,422 |
def inserisciNumero():
"""Permette di inserire all'utente un numero di fibonacci valido"""
num = int(raw_input("Inserisci il numero di Fibonacci da calcolare:\n"))
while num < 0:
num = int(raw_input("Inserisci un numero di Fibonacci valido (>= 0):\n"))
return num | 54c4315085201478232a8361910d349fc1fef210 | 67,423 |
def eval_generalized_normal_pdf(eval_at, mu=0.0, alpha=1.0, p=10.0, lower=-np.inf, upper=np.inf):
"""Evaluate the generalized normal pdf, scaled/shifted
See `sample_generalized_normal` for parameter definitions.
"""
generalized_normal = stats.gennorm(beta=p, loc=mu, scale=alpha)
unnormed_eval_pdf ... | 5fb01f00ad8d47630c02c60387fdd09a02d85a98 | 67,424 |
import re
def wrap_with_span(string, arg):
""" Wraps all instances of a string with a span element"""
words = arg.split(' ')
for word in words:
if word[-1].lower() == 's':
word = word[:-1]
pattern = re.compile(r'\b({0}[\w\d]*)\b'.format(word), flags=re.I)
for (match) ... | 9390f0f12d673c9a809760c1e7ff614d4fc079ef | 67,425 |
import pathlib
def resolve_extension_name(ext):
"""Search in extension folders and return fully-qualified extension name."""
basepath = pathlib.Path(".").resolve()
matching_ext = list(basepath.glob(f"**/*extension*/{ext}.py"))
if len(matching_ext) != 1:
matching_ext = list(basepath.glob(f"**/*... | 7582e47057417ac1b1b0e41c4cb61637222f91e9 | 67,426 |
def get_content_success(app_name):
"""
Retorna a mensagem de sucesso em caso de execução bem sucedida
:param app_name: Nome do app que está sendo criado
:type app_name: str
"""
params = {'app': app_name}
return render_to_string('app_generator/command/success.txt', params) | d5b5bb84a4e69b3866c396b3e7ee8e6cf7ac93ab | 67,427 |
def encumberance_desc( pc, show_ceiling=True ):
"""Return a string describing this PC's encumberance level."""
mass = sum( i.mass for i in pc.contents )
ec = pc.get_encumberance_ceilings()
el = pc.encumberance_level()
if show_ceiling:
return "{0}.{1}/{2}.{3}lbs {4}".format( mass//10, mass%10... | 833d3f66d50243902910b6af98809c529f397ae2 | 67,428 |
def correlation_by_exemplar(brands, exemplars, validation_scores, analyze_fn_str, outf):
""" Report the overall correlation with the validation scores using each exemplar in isolation. """
analyze_fn = getattr(analyze, analyze_fn_str)
keys = sorted(k for k in validation_scores.keys() if k in set(x[0] for x ... | e600e1a9b82a448dcff9d865a4366696d76131f0 | 67,430 |
def get_discont_price(S: float, i: float, n: int) -> float:
""" "
Parameters
----------
S : float
Сума
i : float
Річна ставка складних відсотків
n: int
Кількість років
Returns
-------
P : float
ціна
"""
return S / ((1 + i) ** n) | a5578e8dc80a27c9188c9213d43c3caae09b030a | 67,431 |
def plot_matrix_sizes(plots_no):
"""Calculate the size of the matrix fitting 'plots_no' plots.
Args:
plots_no (int): the number of plots in the matrix.
Returns:
tuple containing the number of row 'rows_no' and columns 'cols_no'.
"""
rows_no = floor(sqrt(plots_no))
cols_no = rows_no + ceil((plots_no - rows_no... | bcab52b63ac6973a92541b68073df0ac18a8847c | 67,432 |
def de_unicode(input):
""" json output ends up as unicode strings some/all of the time
this turns them into strings.
"""
if isinstance(input, dict):
foo=dict()
for key,value in input.iteritems():
foo[de_unicode(key)] = de_unicode(value)
return foo
elif isinstance(input, list):
foo = []
... | 003eea311e22c7c0b1ff2bcadf83a61be406601d | 67,433 |
def import_name(modulename, name=None):
""" Import identifier ``name`` from module ``modulename``.
If ``name`` is omitted, ``modulename`` must contain the name after the
module path, delimited by a colon.
Parameters:
modulename (str): Fully qualified module name, e.g. ``x.y.z``... | a320063e878db935f8a2409c7487617e2c9f1802 | 67,434 |
def get_widgets(request):
"""Return a set of all available widgets."""
return WIDGETS | b286e3468f3e323617feb76541d5b01059c4cd5b | 67,436 |
def find_bounding_shape(virtual_size, available_shape):
"""
Finds a tuple of the same length as ``available_shape``, with every element
not greater than the corresponding element of ``available_shape``,
and product not lower than ``virtual_size``.
"""
assert virtual_size <= product(available_sha... | 46801faf463b34fe39ecaf71e7821444d29bb0eb | 67,437 |
def path_to_route(path_dataframe,edge_dataframe,tiploc_mapping_nodes):
"""Map the TIPLOC route onto the network route by mapping TIPLOC to network nodes and
Finding the equivalent route on a network for given node-node paths that might not be adjacent to each other
By estimating the shortest path between co... | 8bb849a6dcbfba47dd29bfccdbe6e7876b0a268d | 67,438 |
def thickness_params(xarray, mask_values= 0):
"""Return the plotting parameters for the surface oil thickness
:arg xarray: Output netcdf Lagrangian file loaded with xarray
:returns: tuple consisting of truncated array bounding the oil data needed, the x and y bounds for
further visualisation... | ac0f413376ef5c185f389d2a2814667b14366716 | 67,439 |
def createOutputTask1(DLmodel, testTokenizedSentences, testEncodedSentences, testClasses, testDocMapping, bertUtils, neji_classes=None):
"""
Runs the trained model on the unseen data split (validation or test), returning the resulting entity predictions
:param DLmodel:
:param testTokenizedSentences:
... | dfcbc32d394d76093a073a452d83206fff81080d | 67,441 |
def sort_012(arr):
"""
Given an input array consisting on only 0, 1, and 2, sort the array in a single traversal.
Args:
arr(list): List to be sorted
"""
if arr is None:
return arr
zero_index = 0
current_index = 0
two_index = len(arr) - 1
while current_index < len(arr... | d1fa4ee67c9d6b62928b5ea1e2fc1daf011db29d | 67,442 |
def handle_aborted(fsm_ctx):
"""
:param ctx: FSM Context
:return: True if successful other False
"""
global plugin_ctx
if plugin_ctx.nextlevel:
nextlevel_processing(plugin_ctx)
report_install_status(ctx=plugin_ctx, op_id=get_op_id(fsm_ctx.ctrl.before))
# Indicates the failure
... | 07488733031cf4989ece92728054f56363f7bc97 | 67,443 |
from operator import and_
def get_next_cat(last_index: int) -> models.Cat:
"""Get next cat.
Args:
last_index (int): View index of last seen cat.
"""
cat = None
if last_index != -1:
cat = models.Cat.query.filter(and_(models.Cat.disabled == False, models.Cat.index > last_index)).orde... | 055493449a0ad56739c16553474f767a2488c011 | 67,444 |
def txt_split(filename):
"""Strip '#' from first line and get string list of column
:filename: file to get header from
:returns: [string],ndarray
"""
with open(filename,'r') as f:
header=f.readline()
#strip header and split into words
header=header.translate(None,'#')
... | 52799d21f60a5a23f1571bbf3ea98b9d921f0ef5 | 67,445 |
def QueryChanges(host, param_dict, first_param=None, limit=None, o_params=None,
sortkey=None):
"""
Queries a gerrit-on-borg server for changes matching query terms.
Args:
param_dict: A dictionary of search parameters, as documented here:
http://gerrit-documentation.googlecode.com/svn... | c0618cbcb6975c7bafd3eec366fade451e040b47 | 67,446 |
def update(user_id, account_id, calendar_id, event_id, body):
"""
This function updates an account based on the provided information
:param user_id: user_id passed-in URL
:param account_id: account_id passed-in URL
:param calendar_id: calendar_id passed-in URL
:param event_id: event_id passed-i... | e432c33de97aaaf3da000a7f8641189aad64b6ab | 67,447 |
def stop_process(client, pid):
"""获取进程状态"""
stop_result = ""
command = 'kill -9 "%s" '
stdin, stdout, stderr = client.exec_command(command % pid) # 执行bash命令
kill_status = stdout.read()
error = stderr.read()
if error or kill_status:
error = error.split(':')[3].strip()
stop_re... | 454bb8763017119efe360cb5f7c07b9a353ba345 | 67,448 |
from typing import OrderedDict
from typing import Union
def match_state_dict(
model_dict : OrderedDict[str, Tensor],
pretrained_dict: OrderedDict[str, Tensor],
exclude : Union[tuple, list] = ()
) -> OrderedDict[str, Tensor]:
"""Filter out unmatched keys btw the model's `state_dict` and the
... | 4e27bab6d14c074a4d39b9ade24c2bb78045b36d | 67,449 |
import json
def get_original_df(handler):
"""Get the original dataframe which was uploaded to the webapp."""
data_dir = get_user_dir(handler)
meta_path = op.join(data_dir, 'meta.cfg')
if op.isfile(meta_path):
with open(meta_path, 'r') as fout: # noqa: No encoding for json
meta = j... | 71b1e49aef8ab43f2d029caa663c10ba0fe54139 | 67,450 |
def pil_gen(pil_mask_c, hmi_dat, threshperc=0.05, lx=800, ly=800,
polyor=4):
"""
Generate PIL polynomial.
Parameters
----------
pil_mask_c : list
PIL mask.
hmi_dat : list
Array of HMI values associated with the flare.
threshperc: float, optional
Percentag... | 0ebd5c967336ce4bb90763c2413e2d46d11c99df | 67,451 |
def _append_x(clifford, qubit):
"""Apply an X gate to a Clifford.
Args:
clifford (Clifford): a Clifford.
qubit (int): gate qubit index.
Returns:
Clifford: the updated Clifford.
"""
clifford.table.phase ^= clifford.table.Z[:, qubit]
return clifford | 73a747ec0f8ea7245f6be9fe3805fa9fecf0665d | 67,453 |
def isprime(n, k=10):
"""test if n is a prime number
if n is less than 100, check if n is in a set of small primes
else check if n is prime using the Miller-Rabin test
>>> isprime(2) and isprime(2**1279-1)
True
>>> isprime(1) or isprime(-2)
False"""
if n == 2:
return True
if ... | d02d84e97ab545e084d90a1dcfe30c2693d51092 | 67,454 |
def add_overlap_ellipse(segm, ellipse_params, label, thr_overlap=1.):
""" add to existing image ellipse with specific label
if the new ellipse does not ouvelap with already existing object / ellipse
:param ndarray segm: segmentation
:param tuple ellipse_params: parameters
:param int label: selected... | a2b3e7d5c96854114793c22e7e9bb34a7f061ae6 | 67,455 |
import functools
def cowell(k, r, v, tofs, rtol=1e-11, *, ad=None, **ad_kwargs):
"""Propagates orbit using Cowell's formulation.
Parameters
----------
k : ~astropy.units.Quantity
Standard gravitational parameter of the attractor.
r : ~astropy.units.Quantity
Position vector.
v ... | c6b188130811216b0f72912e3918623a8e20702f | 67,459 |
from typing import Tuple
import bisect
def find_closest(m: 'Metric', key: metric_key) -> Tuple[metric_key, metric_key]:
""" assumes keys are sorted."""
if m.keysmin >= key: # neet to extrapolate
left, right = m.all_keys[:2]
elif m.keysmax <= key:
left, right = m.all_keys[-2:]
else:
... | a92f6d1eef1b05727395652c2a904216a0b51781 | 67,460 |
def list_rune(*args, nodes, attrs, context):
"""Creates an unordered list."""
style = " - " if len(args) < 1 else args[0]
def list_recurse(s, i, n): # style, indent, nodes
for node in n:
if isdata(node):
yield i + s + node.data
if len(node.nodes) > 0:
... | 260456b0035796f57807b0c3f1e30c8684dd8fa6 | 67,462 |
def calculate():
"""
Perform a super important calculation.
"""
return 12 | b6aa643b9f6e24f579fdc273c2dec512692cdc4b | 67,463 |
from typing import List
def connect_mini_buckets(mini_buckets:List[Bucket])->List[int]:
"""
connect mini buckets with possibly different variable labels by maximal separators
"""
mini_bucket_inds = []
g_score = dict()
for src in range(len(mini_buckets)):
g_score[src] = dict()
f... | b0a3d03d4faa1c912fa2952a2edb376be9d2a280 | 67,464 |
def check_if_get_event_types_succeeds(frauddetector_client, event_type_to_check: str):
"""
This calls get_event_types and returns True if the response contains an event type: (True, event_type)
If the call does not return any event types, return (False, None)
:param frauddetector_client: frauddetector b... | ceb961770f643f8c88b20b2ee0cea2209d9ffcd3 | 67,465 |
def get_cleanse_logs(user_cleanse_id):
"""Shows all cleanse logs for a specific user cleanse"""
return CleanseLog.query.filter(CleanseLog.user_cleanse_id == user_cleanse_id).all() | f3be3573d19e9aa6065e2546a02cdc9b3c802fb6 | 67,466 |
def shard_hset(connection, base, key, value, total_elements, shard_size):
"""分片式的hset函数"""
shard = shard_key(base, key, total_elements, shard_size)
return connection.hset(shard, key, value) | 444511a3ce202f0bd5992cdfe33ec9e99c1e50a4 | 67,467 |
def load_fermi_image():
"""Load Fermi counts image for the Galactic center region.
Returns
-------
hdu : `~astropy.io.fits.ImageHDU`
Image HDU
Examples
--------
.. plot::
:include-source:
from photutils import datasets
hdu = datasets.load_fermi_image()
... | 94ae2e1ee302897ff7989e3f8ca88ae1a3f7c544 | 67,468 |
def color(red: int, green: int, blue: int, white: int = 0):
"""Convert the provided red, green, blue color to a 24-bit color value.
Each color component should be a value 0-255 where 0 is the lowest intensity
and 255 is the highest intensity.
Note the sequencing has been changed from RGB (most signific... | e821999f1a66d1bc8a7bec4dc298679b205165ad | 67,469 |
def N_(msg):
"""Designate a string to be found by gettext but not to be translated."""
return msg | e82c1f4219e53be05e863bfd636bec932ddd7f5c | 67,470 |
def getticket():
"""
获取 jsapi_ticket
http://mp.weixin.qq.com/wiki/7/aaa137b55fb2e0456bf8dd9148dd613f.html#.E9.99.84.E5.BD.951-JS-SDK.E4.BD.BF.E7.94.A8.E6.9D.83.E9.99.90.E7.AD.BE.E5.90.8D.E7.AE.97.E6.B3.95
"""
access_token = request.args.get('access_token', None)
if not access_token:
ret... | 33c5477109ae2a2a40fec4444e18de32d7129026 | 67,471 |
import json
def _get_needed_packages(json_file, test=None):
"""
Returns a dict with needed packages based on a JSON file.
If a test is specified it will return the dict just for that test.
"""
needed_packages = {}
with open(json_file) as f:
test_packages = json.load(f)
for key,va... | b929e57beda05372b03936598db275e87a318962 | 67,472 |
def calc_eigenvectors(verts: [[float]]):
"""
It computes eigenvectors from a set of vertices.
----------------------------
Args:
verts (obj: 'list' of obj: 'list' of float): The list of vertices
Returns:
eigenvalues (obj: 'list'): The list of eigenvalues
eigenvectors (obj: 'l... | e8d7e6a675718075da23fc4cc461fd9cff4e485c | 67,474 |
def get_parser():
"""
Get parser object for `eco_mocks_create.py` script.
Returns
-------
args:
input arguments to the script
"""
## Define parser object
description_msg = 'Downloads the necessary catalogues from the web'
parser = ArgumentParser(description=description_msg,... | a3fd681a723abff5b1e5526e33598483fe84997d | 67,476 |
def grid_creator():
"""formats the given grid from project euler"""
a = '08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08'
b = '49 49 99 40 17 81 18 57 60 87 17 40 98 43 69 48 04 56 62 00'
c = '81 49 31 73 55 79 14 29 93 71 40 67 53 88 30 03 49 13 36 65'
d = '52 70 95 23 04 60 11 42 69 2... | 1a08ad9671fb14a03671b803e4045c5c7d3b9286 | 67,477 |
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