content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def spline(xyz, s=3, k=2, nest=-1):
""" Generate B-splines as documented in
http://www.scipy.org/Cookbook/Interpolation
The scipy.interpolate packages wraps the netlib FITPACK routines
(Dierckx) for calculating smoothing splines for various kinds of
data and geometries. Although the data is evenly ... | 97500c7a63bc076abd770c43fd3f6d23c30baa03 | 3,658,374 |
import time
def load_supercomputers(log_file, train_ratio=0.5, windows_size=20, step_size=0, e_type='bert', mode="balance",
no_word_piece=0):
""" Load BGL, Thunderbird, and Spirit unstructured log into train and test data
Parameters
----------
log_file: str, the file path of ra... | 2282b8cbd975160e57ff62106a7e0bad3f337e5a | 3,658,375 |
def is_running(service: Service) -> bool:
"""Is the given pyodine daemon currently running?
:raises ValueError: Unknown `service`.
"""
try:
return bool(TASKS[service]) and not TASKS[service].done()
except KeyError:
raise ValueError("Unknown service type.") | 160c7c8da0635c9c11ebdaf711b794fc0a09adff | 3,658,376 |
def PropertyWrapper(prop):
"""Wrapper for db.Property to make it look like a Django model Property"""
if isinstance(prop, db.Reference):
prop.rel = Relation(prop.reference_class)
else:
prop.rel = None
prop.serialize = True
return prop | 9f93a37dffd433fd87ffa4bfdb65680a9ad1d02d | 3,658,377 |
def drowLine(cord,orient,size):
"""
The function provides the coordinates of the line.
Arguments:
starting x or y coordinate of the line, orientation
(string. "vert" or "hor") and length of the line
Return:
list of two points (start and end of the line)
"""
glo... | bc688cfe33dcf42ddac6770bbdf91ccc19c1b427 | 3,658,378 |
def bluetoothRead():
""" Returns the bluetooth address of the robot (if it has been previously stored)
arguments:
none
returns:
string - the bluetooth address of the robot, if it has been previously stored; None otherwise
"""
global EEPROM_BLUETOOTH_ADDRESS
... | c4e08d438b91b3651f27b374c0b38069ddd1eaaf | 3,658,379 |
def is_step_done(client, step_name):
"""Query the trail status using the client and return True if step_name has completed.
Arguments:
client -- A TrailClient or similar object.
step_name -- The 'name' tag of the step to check for completion.
Returns:
True -- if the step has succeeded.... | a5373d7e00f0c8526f573356b5d71a2ac08aa516 | 3,658,380 |
def on_chat_send(message):
"""Broadcast chat message to a watch room"""
# Check if params are correct
if 'roomId' not in message:
return {'status_code': 400}, request.sid
room_token = message['roomId']
# Check if room exist
if not db.hexists('rooms', room_token):
{'status_code'... | 01c7f15602653848c9310e90c0a353648fafbb52 | 3,658,381 |
from typing import Union
def arima(size: int = 100,
phi: Union[float, ndarray] = 0,
theta: Union[float, ndarray] = 0,
d: int = 0,
var: float = 0.01,
random_state: float = None) -> ndarray:
# inherit from arima_with_seasonality
"""Simulate a realization from a... | 24c3ac8af295d25facf0e65a4fc0925b22db9444 | 3,658,382 |
def gt_dosage(gt):
"""Convert unphased genotype to dosage"""
x = gt.split(b'/')
return int(x[0])+int(x[1]) | 819fc9beb834f57e44bcb0ac3e1d3c664c7efd42 | 3,658,383 |
from typing import Optional
from typing import Dict
from typing import Any
def create_key_pair_in_ssm(
ec2: EC2Client,
ssm: SSMClient,
keypair_name: str,
parameter_name: str,
kms_key_id: Optional[str] = None,
) -> Optional[KeyPairInfo]:
"""Create keypair in SSM."""
keypair = create_key_pai... | 40cca5fd938aa6709a4d844c912b294c6aaba552 | 3,658,384 |
def sumofsq(im, axis=0):
"""Compute square root of sum of squares.
Args:
im: Raw image.
axis: Channel axis.
Returns:
Square root of sum of squares of input image.
"""
out = np.sqrt(np.sum(im.real * im.real + im.imag * im.imag, axis=axis))
return out | 6aa791d3c6a2e8e6fff0dbe0a364350d48fb4794 | 3,658,385 |
def biquad_bp2nd(fm, q, fs, q_warp_method="cos"):
"""Calc coeff for bandpass 2nd order.
input:
fm...mid frequency in Hz
q...bandpass quality
fs...sampling frequency in Hz
q_warp_method..."sin", "cos", "tan"
output:
B...numerator coefficients Laplace transfer function
A...denominator... | c7330f9bd4a1941359a54ea6e6d7e8fe7801f55e | 3,658,388 |
def pullAllData():
""" Pulls all available data from the database
Sends all analyzed data back in a json with fileNames and list of list
of all "spots" intensities and backgrounds.
Args:
db.d4Images (Mongo db collection): Mongo DB collection with processed
... | 97674c981af48f37e90667c00947673f1df34c66 | 3,658,389 |
def f2():
"""
>>> # +--------------+-----------+-----------+------------+-----------+--------------+
>>> # | Chromosome | Start | End | Name | Score | Strand |
>>> # | (category) | (int32) | (int32) | (object) | (int64) | (category) |
>>> # |--------------+--... | 159c5167bacbeed38578a8b574b31fa2f57f9467 | 3,658,390 |
def latin(n, d):
"""
Build latin hypercube.
Parameters
----------
n : int
Number of points.
d : int
Size of space.
Returns
-------
lh : ndarray
Array of points uniformly placed in d-dimensional unit cube.
"""
# spread function
def spread(points):... | 416d8c8086eeeaf6e8ea0bf14c300750025455be | 3,658,391 |
def _get_valid_dtype(series_type, logical_type):
"""Return the dtype that is considered valid for a series
with the given logical_type"""
backup_dtype = logical_type.backup_dtype
if ks and series_type == ks.Series and backup_dtype:
valid_dtype = backup_dtype
else:
valid_dtype = logic... | 7b4bcd724d2d7a4029a794456882a8f59fc29006 | 3,658,392 |
def geometric_mean_longitude(t='now'):
"""
Returns the geometric mean longitude (in degrees).
Parameters
----------
t : {parse_time_types}
A time (usually the start time) specified as a parse_time-compatible
time string, number, or a datetime object.
"""
T = julian_centuries... | c47f106392f507d7750f86cba6a7c16ba3270b11 | 3,658,393 |
def get_or_create(model, **kwargs):
"""Get or a create a database model."""
instance = model.query.filter_by(**kwargs)
if instance:
return instance
else:
instance = model(**kwargs)
db.session.add(instance)
return instance | 6af359ebda80b81a0d02762d576ff407f0c186c4 | 3,658,396 |
def test_class_id_cube_strategy_elliptic_paraboloid(experiment_enviroment,
renormalize,
thread_flag):
""" """
tm, dataset, experiment, dictionary = experiment_enviroment
class_id_params = {
"class... | fc5a17e5bf6b158ce242b4289938dec4d2d2e32b | 3,658,397 |
from typing import Dict
from typing import List
def apply_filters(filters: Dict, colnames: List, row: List) -> List:
"""
Process data based on filter chains
:param filters:
:param colnames:
:param row:
:return:
"""
if filters:
new_row = []
for col, data in zip(colnames,... | e52e8b2773dc4e794076b8a480e5eaaab50de06e | 3,658,398 |
def kaiming(shape, dtype, partition_info=None):
"""Kaiming initialization as described in https://arxiv.org/pdf/1502.01852.pdf"""
return tf.random.truncated_normal(shape) * tf.sqrt(2 / float(shape[0])) | 153213279909bf01e9782e0e56d270632c502b27 | 3,658,399 |
def trunc_artist(df: pd.DataFrame, artist: str, keep: float = 0.5, random_state: int = None):
"""
Keeps only the requested portion of songs by the artist
(this method is not in use anymore)
"""
data = df.copy()
df_artist = data[data.artist == artist]
data = data[data.artist != artist]
... | 7157e223bdf87d0463820565e40eade3e1725ae5 | 3,658,400 |
async def test_postprocess_results(original, expected):
"""Test Application._postprocess_results."""
callback1_called = False
callback2_called = False
app = Application("testing")
@app.result_postprocessor
async def callback1(app, message):
nonlocal callback1_called
callback1_c... | 9c2a6bdfcb281d62959135be01693baaaf266780 | 3,658,401 |
def task_migrate():
"""Create django databases"""
return {
'actions': ['''cd CCwebsite && python3 manage.py migrate''']
} | d0d146c2e628abbe33714ae0ff6a546aab9842cc | 3,658,403 |
import numpy
def distance_to_arc(alon, alat, aazimuth, plons, plats):
"""
Calculate a closest distance between a great circle arc and a point
(or a collection of points).
:param float alon, alat:
Arc reference point longitude and latitude, in decimal degrees.
:param azimuth:
Arc a... | e8868a2ce9125cc75e587a8a408f5b479b6a198a | 3,658,404 |
def model_predict(test_data: FeatureVector):
"""
Endpoint to make a prediction with the model. The endpoint `model/train` should have been used before this one.
Args:
test_data (FeatureVector): A unit vector of feature
"""
try:
y_predicted = api.ml_model.predict_proba(test_data.to_... | c8b473d09092e03be85e986287350dd3115cf88d | 3,658,405 |
def search_folders(project, folder_name=None, return_metadata=False):
"""Folder name based case-insensitive search for folders in project.
:param project: project name
:type project: str
:param folder_name: the new folder's name
:type folder_name: str. If None, all the folders in the project will ... | cf8a9d95efcdb90d0891ef4ca588edf6375ed2af | 3,658,407 |
def tempo_para_percorrer_uma_distancia(distancia, velocidade):
""" Recebe uma distância e a velocidade de movimentação, e retorna
as horas que seriam gastas para percorrer em linha reta"""
horas = distancia / velocidade
return round(horas,2) | e7754e87e010988284a6f89497bb1c5582ea0e85 | 3,658,408 |
import math
def getCorrection(start, end, pos):
"""Correct the angle for the trajectory adjustment
Function to get the correct angle correction when the robot deviates from
it's estimated trajectory.
Args:
start: The starting position of the robot.
end: The position the robot is suppos... | 9f1073cb4c071abfecac20c85c56e5fb1638de6e | 3,658,409 |
import logging
def main(input_filepath, output_filepath):
""" Runs data processing scripts to turn raw data from (../raw) into
cleaned data ready to be analyzed (saved in ../processed).
"""
logger = logging.getLogger(__name__)
logger.info('making final data set from raw data...')
df = loa... | fe799a34f9cb5811228853469dbff92592a87e69 | 3,658,410 |
def string2symbols(s):
"""
Convert string to list of chemical symbols.
Args:
s:
Returns:
"""
i = None
n = len(s)
if n == 0:
return []
c = s[0]
if c.isdigit():
i = 1
while i < n and s[i].isdigit():
i += 1
return int(s[:i]) * s... | 1f08ba5c02536f4b67c9bd573c0dde8fbe46dc74 | 3,658,411 |
import csv
from typing import Counter
def get_dictionary(filename, dict_size=2000):
"""
Read the tweets and return a list of the 'max_words' most common words.
"""
all_words = []
with open(filename, 'r') as csv_file:
r = csv.reader(csv_file, delimiter=',', quotechar='"')
for row in... | 20917b0c9cda18d5436b438e0cdcf0c83d464899 | 3,658,413 |
def find_last_index(l, x):
"""Returns the last index of element x within the list l"""
for idx in reversed(range(len(l))):
if l[idx] == x:
return idx
raise ValueError("'{}' is not in list".format(x)) | f787b26dd6c06507380bf2e336a58887d1f1f7ea | 3,658,414 |
import requests
import zipfile
import io
def download_query_alternative(user, password, queryid, batch_size=500):
"""
This is an alternative implementation of the query downloader.
The original implementation only used a batch size of 20 as this allowed for using
plain LOC files. Unfortunately this i... | 2de7c3b453809c86093d1884438613985f7041b3 | 3,658,415 |
def parse_template(templ_str, event):
"""
Parses a template string and find the corresponding element in an event data structure.
This is a highly simplified version of the templating that is supported by
the Golang template code - it supports only a single reference to a sub
element of the event s... | ec5c3822c390cbb4beff6428b91cd8b12157f2e3 | 3,658,416 |
import time
def current_time_hhmm() -> str:
"""
Uses the time library to get the current time in hours and minutes
Args:
None
Returns:
str(time.gmtime().tm_hour) + ":" + str(time.gmtime().tm_min) (str):
Current time formatted as hour:minutes
"... | c7902ac8a8fb2528bacf6a5bc8459865604dd204 | 3,658,417 |
def configure(node):
""" Generates the script to set the hostname in a node """
script = []
script.append(Statements.exec("hostname %s" % node.getName()))
script.append(Statements.createOrOverwriteFile(
"/etc/hostname", [node.getName()]))
script.append(Statements.exec(
"sed -i 's/127... | b0acf0f6a1363f1c7ad5a8e6dce6cb5d45586135 | 3,658,420 |
import random
def processOptional(opt):
"""
Processes the optional element 50% of the time, skips it the other 50% of the time
"""
rand = random.random()
if rand <= 0.5:
return ''
else:
return processRHS(opt.option) | bda8130952f11f4df9342764d749dd6c93109d8e | 3,658,421 |
def remove_non_paired_trials(df):
"""Remove non-paired trials from a dataset.
This function will remove any trials from the input dataset df that do not
have a matching pair. A matching pair are trial conditions A->B and B->A.
"""
# Define target combinations
start_pos = np.concatenate(df['sta... | 30b5b86d9354c55dd2514114dc1180f397f2e56c | 3,658,422 |
def compute_weighted_means_ds(ds,
shp,
ds_name='dataset',
time_range=None,
column_names=[],
averager=False,
df_output=pd.DataFrame(),
... | e575d17eefe8de66c0b6fd63abcf5d3bd6cac6ae | 3,658,423 |
def action_remove(indicator_id, date, analyst):
"""
Remove an action from an indicator.
:param indicator_id: The ObjectId of the indicator to update.
:type indicator_id: str
:param date: The date of the action to remove.
:type date: datetime.datetime
:param analyst: The user removing the ac... | 806c818cd4c18624d9713a02d5c1826cab43a631 | 3,658,424 |
def repack_orb_to_dalton(A, norb, nclosed, nact, nvirt):
"""Repack a [norb, norb] matrix into a [(nclosed*nact) +
(nclosed*nvirt) + (nact*nvirt)] vector for contraction with the CI
Hamiltonian.
"""
assert norb == nclosed + nact + nvirt
assert A.shape == (norb, norb)
# These might be availa... | 05b356e9ded74c180d2a220f147cd69e91a5b597 | 3,658,425 |
def get_config(section="MAIN", filename="config.ini"):
"""
Function to retrieve all information from token file.
Usually retrieves from config.ini
"""
try:
config = ConfigParser()
with open(filename) as config_file:
config.read_file(config_file)
return config[sect... | 32d6c579b0ce002a601ea9041b54e9ce03858eb4 | 3,658,426 |
def _worst_xt_by_core(cores) -> float:
"""
Assigns a default worst crosstalk value based on the number of cores
"""
worst_crosstalks_by_core = {7: -84.7, 12: -61.9, 19: -54.8} # Cores: Crosstalk in dB
worst_xt = worst_crosstalks_by_core.get(cores) # Worst aggregate intercore XT
return worst_xt | 331fdd7dc20db6909a6952483cfa9699f983a721 | 3,658,427 |
def _CheckUploadStatus(status_code):
"""Validates that HTTP status for upload is 2xx."""
return status_code / 100 == 2 | d799797af012e46945cf413ff54d2ee946d364ba | 3,658,428 |
def load(path: str, **kwargs) -> BELGraph:
"""Read a BEL graph.
:param path: The path to a BEL graph in any of the formats
with extensions described below
:param kwargs: The keyword arguments are passed to the importer
function
:return: A BEL graph.
This is the universal loader, which me... | 871c7e3becac089758c94f7416def0020e63f9c1 | 3,658,429 |
from typing import Optional
def smooth_l1_loss(
prediction: oneflow._oneflow_internal.BlobDesc,
label: oneflow._oneflow_internal.BlobDesc,
beta: float = 1.0,
name: Optional[str] = None,
) -> oneflow._oneflow_internal.BlobDesc:
"""This operator computes the smooth l1 loss.
The equation is:
... | ddebf5ba77ca8e4d2a964e5c86e05a0b61db9ded | 3,658,430 |
def get_model_fields(model, concrete=False): # type: (Type[Model], Optional[bool]) -> List[Field]
"""
Gets model field
:param model: Model to get fields for
:param concrete: If set, returns only fields with column in model's table
:return: A list of fields
"""
if not hasattr(model._meta, 'g... | 9e9172b2e606041c6f9dbf3a991e79d73518227f | 3,658,431 |
def loss_fun(para):
"""
This is the loss function
"""
return -data_processing(my_cir(para)) | 5703755e3f5547be933f85224c103c58acbeaabb | 3,658,432 |
def GetDynTypeMgr():
"""Get the dynamic type manager"""
return _gDynTypeMgr | 7acf02dd2072ea819c847f53fbf11e68146b2400 | 3,658,433 |
def identifyEntity(tweet, entities):
"""
Identify the target entity of the tweet from the list of entities
:param tweet:
:param entities:
:return:
"""
best_score = 0 # best score over all entities
targetEntity = "" # the entity corresponding to the best score
for word in tweet:
... | d6825dfddf01706ee266e0f1c82128a42bcb8554 | 3,658,434 |
def _apply_D_loss(scores_fake, scores_real, loss_func):
"""Compute Discriminator losses and normalize loss values
Arguments
---------
scores_fake : list
discriminator scores of generated waveforms
scores_real : list
discriminator scores of groundtruth waveforms
loss_func : objec... | 9432962af57193c07a268d00a3f1f01d372cb6a0 | 3,658,436 |
import tempfile
def get_temp_dir():
"""
Get path to the temp directory.
Returns:
str: The path to the temp directory.
"""
return fix_slashes( tempfile.gettempdir() ) | 3d0dd90c8187ac7b13913e7d4cd2b481c712fa6b | 3,658,437 |
import random
def pick_op(r, maxr, w, maxw):
"""Choose a read or a write operation"""
if r == maxr or random.random() >= float(w) / maxw:
return "write"
else:
return "read" | a45f53bf12538412b46f78e2c076966c26cf61ac | 3,658,438 |
def sim_nochange(request):
""" Return a dummy YATSM model container with a no-change dataset
"No-change" dataset is simply a timeseries drawn from samples of one
standard normal.
"""
X, Y, dates = _sim_no_change_data()
return setup_dummy_YATSM(X, Y, dates, [0]) | a39ba5824644764ae2aaf4e4d95c68d1c26bd132 | 3,658,439 |
from functools import reduce
import operator
def get_queryset_descendants(nodes, include_self=False, add_to_result=None):
"""
RUS: Запрос к базе данных потомков. Если нет узлов,
то возвращается пустой запрос.
:param nodes: список узлов дерева, по которым необходимо отыскать потомков
:param include... | 7de9fe6c146c9569bc78b714b75238b770f9157e | 3,658,441 |
from operator import mul
def op_mul(lin_op, args):
"""Applies the linear operator to the arguments.
Parameters
----------
lin_op : LinOp
A linear operator.
args : list
The arguments to the operator.
Returns
-------
NumPy matrix or SciPy sparse matrix.
The resu... | a1f770d2132fc9c3a60d4de3c3d87f59a03241eb | 3,658,442 |
def comparator(x, y):
"""
default comparator
:param x:
:param y:
:return:
"""
if x < y:
return -1
elif x > y:
return 1
return 0 | 53fc36f1afc3347689a1230c5ee3ba25d90f1239 | 3,658,443 |
def set_trait(age, age_risk_map, sex, sex_risk_map, race, race_risk_map):
""" A trait occurs based on some mix of """
if age in age_risk_map:
risk_from_age = age_risk_map[age]
else:
risk_from_age = 0
if sex in sex_risk_map:
risk_from_sex = sex_risk_map[sex]
else:
ri... | fe9f6c75ae4d7f80c2da86af4315b35fe29df482 | 3,658,444 |
def tidy_expression(expr, design=None):
"""Converts expression matrix into a tidy 'long' format."""
df_long = pd.melt(
_reset_index(
expr, name='gene'), id_vars=['gene'], var_name='sample')
if design is not None:
df_long = pd.merge(
df_long,
_reset_index... | 7c904e13a55f38cc05309b5927f2fdbb23c3f8c9 | 3,658,446 |
def get_optimizer(name):
"""Get an optimizer generator that returns an optimizer according to lr."""
if name == 'adam':
def adam_opt_(lr):
return tf.keras.optimizers.Adam(lr=lr)
return adam_opt_
else:
raise ValueError('Unknown optimizer %s.' % name) | 8c97ee9f4b77d0fc80914ac7cbb49a448d48644a | 3,658,448 |
from typing import List
def get_multi(response: Response, common: dict = Depends(common_parameters)) -> List[ShopToPriceSchema]:
"""List prices for a shop"""
query_result, content_range = shop_to_price_crud.get_multi(
skip=common["skip"],
limit=common["limit"],
filter_parameters=common... | f97868e66c7743127d2d2951b732ff4c62708ae5 | 3,658,449 |
from datetime import datetime
def send_crash(request, machine_config_info, crashlog):
"""
Save houdini crashes
"""
machine_config = get_or_save_machine_config(
machine_config_info, get_ip_address(request),
datetime.datetime.now())
save_crash(machine_config, crashlog, datetime.datet... | 43e44950bdb4b6dc305bb1f36651daa31b4f813e | 3,658,450 |
def apply_HAc_dense(A_C, A_L, A_R, Hlist):
"""
Construct the dense effective Hamiltonian HAc and apply it to A_C.
For testing.
"""
d, chi, _ = A_C.shape
HAc = HAc_dense(A_L, A_R, Hlist)
HAc_mat = HAc.reshape((d*chi*chi, d*chi*chi))
A_Cvec = A_C.flatten()
A_C_p = np.dot(HAc_mat, A_Cv... | b13f9db7287fcdf275e8f7c9a7fb542e7b79323c | 3,658,452 |
def min_index(array, i, j):
"""Pomocna funkce pro razeni vyberem. Vrati index nejmensiho prvku
v poli 'array' mezi 'i' a 'j'-1.
"""
index = i
for k in range(i, j):
if array[k] < array[index]:
index = k
return index | 4c59362fac2e918ba5a0dfe9f6f1670b3e95d68c | 3,658,453 |
def filterControlChars(value, replacement=' '):
"""
Returns string value with control chars being supstituted with replacement character
>>> filterControlChars(u'AND 1>(2+3)\\n--')
u'AND 1>(2+3) --'
"""
return filterStringValue(value, PRINTABLE_CHAR_REGEX, replacement) | a0f508d281f0c12311a5c2aa2f898def5eb38913 | 3,658,454 |
import csv
def write_trt_rpc(cell_ID, cell_time, lon, lat, area, rank, hmin, hmax, freq,
fname, timeformat='%Y%m%d%H%M'):
"""
writes the rimed particles column data for a TRT cell
Parameters
----------
cell_ID : array of ints
the cell ID
cell_time : array of datetime... | fd634914a8c3d96d10d4dcc81514d492d6be899c | 3,658,456 |
def get_tag(string: str) -> Tag:
"""Получить тему."""
return Tag.objects.get(tag=string) | 816bbaecc4cf45e2fc75b1e428842b5502a353bc | 3,658,457 |
def average_precision(gt, pred):
"""
Computes the average precision.
This function computes the average prescision at k between two lists of
items.
Parameters
----------
gt: set
A set of ground-truth elements (order doesn't matter)
pred: list
A list of predicted elements (order does mat... | ca265471d073b6a0c7543e24ef0ba4f872737997 | 3,658,458 |
import math
def rotate_coo(x, y, phi):
"""Rotate the coordinates in the *.coo files for data sets
containing images at different PAs.
"""
# Rotate around center of image, and keep origin at center
xin = 512.
yin = 512.
xout = 512.
yout = 512.
cos = math.cos(math.radians(phi))
... | a57a4c36119e96d757bd23f28a0790f6d68661fc | 3,658,459 |
def ip_block_array():
"""
Return an ipBlock array instance fixture
"""
return ['10.0.0.1', '10.0.0.2', '10.0.0.3'] | c74756f34b97d2550cb238bd63e0c9505f3935d3 | 3,658,460 |
from pathlib import Path
import joblib
def load_model(model_name, dir_loc=None, alive_bar_on=True):
"""Load local model_name=model_s if present, else fetch from hf.co."""
if dir_loc is None:
dir_loc = ""
dir_loc = Path(dir_loc).absolute().as_posix()
file_loc = f"{dir_loc}/{model_name}"
if... | 1847e061c6980fd4fd185f79d48682cbf7cb14ff | 3,658,461 |
from typing import Generator
def get_dev_requirements() -> Generator:
"""Yield package name and version for Python developer requirements."""
return get_versions("DEVELOPMENT") | 728658648d6bce6fecbf4c1bc6b6de42c315b3c0 | 3,658,462 |
def _ndb_key_to_cloud_key(ndb_key):
"""Convert a ndb.Key to a cloud entity Key."""
return datastore.Key(
ndb_key.kind(), ndb_key.id(), project=utils.get_application_id()) | ce71b0d13f2e37ded12bf87ad133492a9b68d0c7 | 3,658,463 |
def inference(H, images, train=True):
"""Build the MNIST model up to where it may be used for inference.
Parameters
----------
images: Images placeholder, from inputs().
train: whether the network is used for train of inference
Returns
-------
softmax_linear: Output tensor with the com... | bf7e0f60bdc85d52fb6778cc40eedaa63c0387e3 | 3,658,464 |
def UniqueLattice(lattice_vectors,ind):
"""
Takes a list with two tuples, each representing a lattice vector and a list with the genes of an individual.
Returns a list with two tuples, representing the equivalent lattice vectors with the smallest cell circunference.
"""
x_1 = lattice_vectors(0,ind)
... | e2474a54cf3351ff112ecb6d139eec8eac2ef1fa | 3,658,466 |
def register_errors(app: Flask):
"""注册需要的错误处理程序包到 Flask 程序实例 app 中"""
@app.errorhandler(400) # Bad Request 客户端请求的语法错误，服务器无法理解
def bad_request(e):
return render_template('error.html', description=e.description, code=e.code), 400
@app.errorhandler(404) # Not Found 服务器无法根据客户端的请求找到资源（网页）
def... | 27634a139aab88215b77e53a25758d6096571a09 | 3,658,467 |
def websafe_encode(data):
"""Encodes a byte string into websafe-base64 encoding.
:param data: The input to encode.
:return: The encoded string.
"""
return urlsafe_b64encode(data).replace(b'=', b'').decode('ascii') | ed5b06d2fab3dcc64275cb0046cabd88f63894ec | 3,658,468 |
from typing import Union
def gravatar(email: Union[str, list]) -> str:
"""Converts the e-mail address provided into a gravatar URL.
If the provided string is not a valid e-mail address, this
function just returns the original string.
Args:
email: e-mail address to convert.
Returns:
... | 8807eefd40472068310455c1c477933dbaa67be0 | 3,658,469 |
def bar_2_MPa(value):
"""
converts pressure in bar to Pa
:param value: pressure value in bar
:return: pressure value in Pa
"""
return value * const.bar / const.mega | d6c8084a6603f74bd1fb11739e4f4d9100cf14de | 3,658,470 |
def walk(x, y, model, theta, conditions=None, var2=0.01, mov=100,
d=1, tol=1e-3, mode=True):
"""Executes the walker implementation.
Parameters
----------
x : np.ndarray
An $(m, n)$ dimensional array for (cols, rows).
y : np.ndarray
An $n$ dimensional array that will be ... | ef7386f4c7141edfcdeb041b47d741e186f207e2 | 3,658,471 |
def izbor_letov():
"""Glavna stran."""
# Iz cookieja dobimo uporabnika in morebitno sporočilo
(username, ime, priimek) = get_potnik()
c.execute("SELECT distinct drzava FROM lokacija ORDER BY drzava")
drzave=c.fetchall()
drzava_kje = bottle.request.forms.drzava_kje
mesto_kje = bottle.request.forms.mesto_kje
l... | 664de2c3cf2507ac43efa22105a51b1e14ad441a | 3,658,472 |
def generate_data_from_cvs(csv_file_paths):
"""Generate data from list of csv_file_paths. csv_file_paths contains path to CSV file, column_name, and its label
`csv_file_paths`: A list of CSV file path, column_name, and label
"""
data = []
for item in csv_file_paths:
values = read_csv(item[0]... | 1c9f393a18edc9c2fcc3f28cdbeb71fb9c006731 | 3,658,473 |
import math
import torch
def log_density_gaussian(x, mu, logvar):
"""Calculates log density of a gaussian.
Parameters
----------
mu: torch.Tensor or np.ndarray or float
Mean.
logvar: torch.Tensor or np.ndarray or float
Log variance.
"""
normalization = - 0.5 * (math.log(2... | 3fdc751aa58b3ec82e1aa454f593879d5da4c310 | 3,658,474 |
def invalid_hexadecimal(statement):
"""Identifies problem caused by invalid character in an hexadecimal number."""
if statement.highlighted_tokens: # Python 3.10
prev = statement.bad_token
wrong = statement.next_token
else:
prev = statement.prev_token
wrong = statement.bad_t... | a0b252001dd1f0f466302a131c2a460743a8c197 | 3,658,475 |
def get_pool_name(pool_id):
"""Returns AS3 object name for TLS profiles related to pools
:param pool_id: octavia pool id
:return: AS3 object name
"""
return "{}{}".format(constants.PREFIX_TLS_POOL, pool_id) | 2a850d48f52d822712cdfc3543532c9b0dd80fd6 | 3,658,476 |
def search_sliceable_by_yielded_chunks_for_str(sliceable, search_string, starting_index, down, case_insensitive):
"""This is the main entry point for everything in this module."""
for chunk, chunk_start_idx in search_chunk_yielder(sliceable, starting_index, down):
found_at_chunk_idx = search_list_for_st... | 7179179403098cd1d3993a35cf59c9162384ac4d | 3,658,477 |
def split_page(array, limit, index):
"""
按限制要求分割数组，返回下标所指向的页面
:param array: 需要分割的数组
:param limit: 每个数组的大小
:param index: 需要返回的分割后的数组
:return: 数组
"""
end = index * limit
start = end - limit
return array[start:end] | ecce83d6e2e09d47e124536f294ece1e1631e6b6 | 3,658,478 |
def creatKdpCols(mcTable, wls):
"""
Create the KDP column
Parameters
----------
mcTable: output from getMcSnowTable()
wls: wavelenght (iterable) [mm]
Returns
-------
mcTable with an empty column 'sKDP_*' for
storing the calculated KDP of a given wavelength.
"""
... | 9adc20c1ff94778bec4551156b5774863eb2203f | 3,658,479 |
def get_products_by_user(user_openid, allowed_keys=None, filters=None):
"""Get all products that user can manage."""
return IMPL.get_products_by_user(user_openid, allowed_keys=allowed_keys,
filters=filters) | 458664aa75c5b423ccfb2a80287c565cae51e0d0 | 3,658,480 |
def sample_from_ensemble(models, params, weights=None, fallback=False, default=None):
"""Sample models in proportion to weights and execute with
model_params. If fallback is true then call different model from
ensemble if the selected model throws an error. If Default is not
None then return default if ... | c771108cb36cff2cb48af22a9efaad749d267ce0 | 3,658,481 |
def Flatten(matrix):
"""Flattens a 2d array 'matrix' to an array."""
array = []
for a in matrix:
array += a
return array | 00389b4dd295274d8081331d6ae78f233f0b5b59 | 3,658,482 |
def create_verification_token(
data: dict
) -> VerificationTokenModel:
"""
Save a Verification Token instance to database.
Args:
data (dictionary):
Returns:
VerificationToken:
Verification Token entity of VerificationTokenModel object
Raises:
None
"""
... | 9008bc298c8e8075031f7e14e8cb0f288e894869 | 3,658,483 |
from typing import Union
from typing import Sequence
from typing import Tuple
def _find_highest_cardinality(arrays: Union[int, Sequence, np.ndarray, Tuple]) -> int:
"""Find the highest cardinality of the given array.
Args:
arrays: a list of arrays or a single array
Returns:
The highest ... | abe9ad85ffabb88f9097b9c2de97319f1342f586 | 3,658,484 |
def rowmap(table, rowmapper, header, failonerror=False):
"""
Transform rows via an arbitrary function. E.g.::
>>> import petl as etl
>>> table1 = [['id', 'sex', 'age', 'height', 'weight'],
... [1, 'male', 16, 1.45, 62.0],
... [2, 'female', 19, 1.34, 55.4],
... | dabceae8171330d3f8c4cdba7b50be2106ad1438 | 3,658,486 |
def squeeze(dataset, how: str = 'day'):
"""
Squeezes the data in dataset by close timestamps
Args:
dataset (DataFrame) - the data to squeeze
how (str) - one of 'second', 'minute', 'hour', 'day', 'month' (default day)
Returns:
dataset (DataFrame) - a dataframe where the indexes are squeez... | e41cbc4e054218b1f88ed0745fcc980df29ac8d4 | 3,658,487 |
def callback():
"""
Process response for "Login" try from Dropbox API.
If all OK - redirects to ``DROPBOX_LOGIN_REDIRECT`` url.
Could render template with error message on:
* oAuth token is not provided
* oAuth token is not equal to request token
* Error response from Dropbox API
Def... | 8b35d67d065a5ec65606b6e505cfccc51460fe1c | 3,658,488 |
def get_ws_param(args, attr):
"""get the corresponding warm start parameter, if it is not exists, use the value of the general parameter"""
assert hasattr(args, attr), 'Invalid warm start parameter!'
val = getattr(args, attr)
if hasattr(args, 'ws_' + attr):
ws_val = getattr(args, 'ws_' + attr)
... | ea1d762654153602f8ad54048e54995c26304e40 | 3,658,489 |
def _redundant_relation(lex: lmf.Lexicon, ids: _Ids) -> _Result:
"""redundant relation between source and target"""
redundant = _multiples(chain(
((s['id'], r['relType'], r['target']) for s, r in _sense_relations(lex)),
((ss['id'], r['relType'], r['target']) for ss, r in _synset_relations(lex)),... | cc32c55a35cd7056a249ad05bd0b483af18fcd3a | 3,658,490 |
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