content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def create_queries(cson_content):
"""Create the queries from the CSON configuration file
Args:
cson_content: The CSON configuration file content.
Returns:
The CSON configuration file content with key instead of description for the queries.
Raises:
ValueError: The CSON if malfo... | 628a704e16d2ccace2aa5cb487a3f28ae63043dc | 3,602,680 |
import re
def extract_airlines_from_flight_text(flight_text):
"""
:param flight_text: Raw flight text string, e.g.,
"3:45 PM – 8:15 PM+1\nUnited\n13h 30m\nSFO–PVG\nNonstop\n$4,823",
"12:51 PM – 4:50 PM+1\nDelta\nChina Southern\n12h 59m\nSEA–PVG\nNonstop\n$4,197",
"2:10 AM – 1:25 PM+1\... | 188f040c15e62f4eace72cb90ef74825c4b803fc | 3,602,681 |
def find_centroid_of_flux(image, mask=None):
"""Find center of flux in an image
function giving the tuple of the position of weighted average of
the flux in a square image
indentical result as calculateCentroid from drp_stella.images
@input image poststamp image for which to find center
@in... | bc6f03c0fee7fb5cfeebb62b8a1b5646f58b8a40 | 3,602,683 |
import copy
import time
def sim_mabs_norm(algo_list: list, locs: list, scales: list, num_sims: int, horizon: int, algo_name: list,
batch: bool =False, batch_size: int =0) -> list:
"""Run simulations Multi-Armed Bandit Algorithms on rewards given by Gaussian distributions.
:param algo_list: ... | 1491ae1fd4baf7e335c24cc4974fae412ee5c440 | 3,602,684 |
def ts_to_list(ts): # Completed
"""
Helper function used to convert a pandas time
series object back to a python list object.
"""
if isinstance(ts, pd.core.series.Series):
ts = ts.values.tolist()
return ts | ea0955bb05f5a9f4b30a8571419a2b02d640d4c3 | 3,602,685 |
def get_inputs(inputs, mask=None):
"""Extract and normalize the arrays from inputs"""
gmax = inputs[0][:,:,1].max()
o = inputs[0][:,:,0]/gmax
n = inputs[1][:,:,0]/gmax
return o,n | 329dfce70d65dec8d5f177239b7f88c977519867 | 3,602,686 |
import torch
def _bbox_pre_decode(points: torch.Tensor, bbox_pred: torch.Tensor,
stride: torch.Tensor):
"""compute real bboxes."""
points = points[..., :2]
bbox_pos_center = torch.cat([points, points], dim=-1)
bboxes = bbox_pred * stride + bbox_pos_center
return bboxes | 27aec66f69c31e1147dc544808f4ce10954b1272 | 3,602,687 |
def return_data():
"""Return the images data
Params:
None
Returns:
(array): containing data informations of image
"""
path_csv = '20200416_2'
figures = []
dict_results = daily_average(path_csv)
figures.append(dict_results['figure'])
figures.append(weekly_percentage(... | 2a167aa8e4262b006e3c83e881166a867d90eebc | 3,602,688 |
def formatTime(t):
"""Check if hour, minute, second variable has format hh, mm or ss if not change format.
:param t: string time hh, mm or ss
:return: string time in correct format eg. hh=02 instead of hh=2
"""
if len(t) < 2:
t = "0" + t
return t | 8011fc25a001964af1f1e0b0cb4e54f7d7aec721 | 3,602,690 |
def song_value(songtitle, artist, chart):
""" Returns the value of a song in a chart
Run through one billboard chart objekt and return the "value" of the song
with the specified title and artist in this chart.
If the song is not on the chart 0 is returend.
... | 637b5a83938729e1ecf131804c12f38f7aba6247 | 3,602,691 |
def extract_patches(path, numPatchesPerImage, patchSize):
"""
:param path: path to a RGB fundus image
:param numPatchesPerImage: number of patches to extract per image
:param patchSize: patch is nxn size
:return: patches: matrix with an image patch in each row
"""
img = load(path)
img ... | f6d1b111bde5c5cc695ff79d7a4cccec82f225bf | 3,602,692 |
def integrate(values, ax_val, index, Nper, is_aper, is_phys, is_mean=False):
"""Returns the integral of values along given axis
Parameters
----------
values: ndarray
array to integrate
ax_val: ndarray
axis values
index: int
index of axis along which to derivate
Nper:... | ac213f3f78ef32908055bfcc931cc3359234f6a4 | 3,602,693 |
def processImage(path, regions, ftypes, fiducials, outparams, fmtdict):
"""Processes a single image and returns a feature vector, or raises an Exception"""
fc = FeatureComputer(mstr=regions, fstr=ftypes)
fvec = fc.compute(path, fiducials=fiducials, outparams=outparams, fmtdict=fmtdict)
return fvec | 801fe0c4742e606866ac5aff6e02eb59cb956e33 | 3,602,694 |
def _create_connection(network, ip_address, mac_address, ip_allocation_mode,
primary_interface=False, nic_order=0):
"""
repack fields to dict
"""
return {'network': network,
'ip_address': ip_address,
'mac_address': mac_address,
'ip_allocatio... | da2c38d853ab9ba458031265e6ca6d33f2a54185 | 3,602,695 |
def rf_tile_stats(tile_col):
"""Compute the Tile-wise floating point statistics"""
return _apply_column_function('rf_tile_stats', tile_col) | 96fab4598cb001fae06c9f14cc748802b2b63309 | 3,602,696 |
def resize(x: np.ndarray, factor: float=2)-> np.ndarray:
"""
resizes an image by the factor. If factor
< 1, reduces the size, >1 increases the size
This doesn't perform interpolation
Parameters
-------------
x: np.ndarray
an image as an array
factor: float
the resize fa... | 723c0f338ba07f6b62f8e51a6f6d3fcb45e923db | 3,602,697 |
def _cluster_quality_sumsquares(data, clusters):
"""Within-clusters sum of squares
"""
min_distance = np.min(_cluster_quality_distance(data, clusters), axis=1)
return np.sum(min_distance**2) | 04f7156550133896551c20a1b6ad8805d9952c9b | 3,602,698 |
def remove_signature(message):
"""Remove the 3 Letter signature and the '/' found at the beginning of a valid message"""
return message[1:] | a802dc5abfea09e05fad51936dd76e17719900e7 | 3,602,699 |
def plot_fl_bars(sta, pval=None, ax=None, imshow_params={"cmap":'gray',"vmin":-1, "vmax":1,
"aspect":"auto", "interpolation":"nearest"}):
"""
Plot the response to a 1D spatial stimulus like Flickering_bars.
params:
- sta: The STA to the 1D st... | e46647686d5f718f40e5a9060e3df3bfddfe2986 | 3,602,701 |
from datetime import datetime
def sendpredictivemodel_timeline(year, month, day):
"""
Predictive model from https://pechlilab.shinyapps.io/output/ by day
---
tags:
- Data
responses:
200:
description: '.csv'
content:
text/plain:
... | a756c21ce61bfd584df5e7db4dcf1ddc0fa1bf00 | 3,602,702 |
def release_lock(conn, lockname, identifier):
"""
Signal/release a lock.
Args:
conn: redi connection
lockname: name of the lock to be released
identifier: lock will only be released if identifier matches the
identifier that was provided when the lock was acquired.
R... | f7ea73c3806621ff3ca7f82f2cf899a28c700ebf | 3,602,703 |
def find_adv_chunk(doc):
"""
Returns a dictionary representing a adverb chunk
with a subject, a verb and an adverb
"""
for noun_chunk in doc.noun_chunks:
# print("noun_chunk is {}".format(noun_chunk))
if noun_chunk.root.dep_ != 'nsubj':
continue
subj = noun_chunk.root
if subj.head.dep_ == 'ROOT':
ver... | 64775754733a6b5a3ce342b1f0475b188cb00319 | 3,602,704 |
import textwrap
def get_comment_from_location(location):
"""Return comment text from location.
Args:
location: descriptor_pb2.SourceCodeInfo.Location instance to get
comment from.
Returns:
Comment as string.
"""
return textwrap.dedent(location.leading_comments or
... | d86213ddee50128c8363d2a31a740c5677244612 | 3,602,705 |
def make_env(env_id, rank, seed=0):
"""
Utility function for multiprocessed env.
:param env_id: (str) the environment ID
:param num_env: (int) the number of environments you wish to have in subprocesses
:param seed: (int) the inital seed for RNG
:param rank: (int) index of the subprocess
""... | c1a2c89ea4880e9b02f78df97358881628c57913 | 3,602,706 |
def yugioh_card_name_regex(cards_json):
"""Compile a regex matching a yugioh card id."""
return regex_or([card["name"] for card in cards_json]) | 219efa77e6fce78e5456534c84214ea4488ada12 | 3,602,707 |
def get_good_tags(soup):
"""
Good Tags are the Tags with a positive rating (Benis > 0)
:param soup:
:return: A List of all positiv tags
"""
soup = Bs(soup, "html.parser") # Need an explizit cast due to ducktyping problems with the find() in Python and BS
# Alle Guten Tags filtern
good_... | 2973ef2f2537bd5271c673d91f07d12ad4173084 | 3,602,708 |
def edges2graph(edges, N=10000):
"""Creates MultiGraph from list of edges."""
H = nx.MultiGraph()
H.add_nodes_from(np.arange(N))
H.add_edges_from(edges)
return H | a934b43bf988927edfb44ae629724b2a08e6ca1d | 3,602,709 |
import ctypes
def pckopn(name: str, ifname: str, ncomch: int) -> int:
"""
Create a new PCK file, returning the handle of the opened file.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/pckopn_c.html
:param name: The name of the PCK file to be opened.
:param ifname: The internal filenam... | 392fbf87ee0b53cd190fa6d136fa28e20b6eb09c | 3,602,711 |
from typing import Callable
from typing import Optional
def build_model_delta_optimizer_process(
model_fn: _ModelConstructor,
model_to_client_delta_fn: Callable[[Callable[[], model_lib.Model]],
ClientDeltaFn],
server_optimizer_fn: _OptimizerConstructor,
*,
we... | a2d6e95618ef5d9a6971a435a0905c2a133aad29 | 3,602,712 |
import platform
def is_linux():
"""Determines if the system is Linux."""
return platform.uname()[0] == 'Linux' | 6c50b3ba3495b9f850e69b0ebf98834375a5cb85 | 3,602,713 |
def check_scale_xsmode(xsmode):
"""checking if the scale of xsmode assumes ESLOG(log) or ESLIN(linear)
Args:
xsmode: xsmode
Return:
ESLOG/ESLIN/UNKNOWN
"""
if xsmode=="lpf" or xsmode=="LPF" or xsmode=="modit" or xsmode=="MODIT" or xsmode=="redit" or xsmode=="REDIT":
pri... | db6097abc196677063cb6851ce6036fb6e9b61f9 | 3,602,714 |
def distort_elastic_cv2(image, alpha=80, sigma=20, random_state=None):
"""Elastic deformation of images as per [Simard2003].
"""
if random_state is None:
random_state = np.random.RandomState(None)
shape_size = image.shape[:2]
# Downscaling the random grid and then upsizing post filter
... | bc1e8276480c023d6afc1a5b8e49706c408c0df6 | 3,602,715 |
def square_list(original_list):
"""
It returns the a list which each element squared
Args:
original_list: the list which needs to be added
Returns:
a list with the value: [elem1*elem1,elem2*elem2]
"""
return [multiplication(x, x) for x in original_list] | 986c0c41cf0f49fd108812e2badf175c6ab30d3a | 3,602,716 |
import warnings
def round(a, mode=None):
"""round_mode(a) with mode in [half_away_from_zero, half_to_even].
Default to half_to_even."""
if mode is None:
mode = "half_to_even"
if config.warn__round:
warnings.warn(
"aesara.tensor.round() changed its default from"
... | 89a036036f53b84be05d0aa8808492ed69b1d0ba | 3,602,718 |
import logging
def send_request(guid, args):
"""Send a request to the PrimeNet server."""
try:
if idx:
args["ss"] = 19191919
args["sh"] = "ABCDABCDABCDABCDABCDABCDABCDABCD"
else:
secure_v5_url(guid, args)
r = s.get(primenet_v5_burl, params=args, time... | 594914117df83895b020a40cd9f03b0c6e76579d | 3,602,719 |
def modify_metrics(modify_product, service):
""" Modify/add/remove metrics/limits"""
# pylint: disable=unused-argument
new_metric = service.metrics.create(rawobj.Metric('custom'))
service.app_plans.list()[0].limits(new_metric).create({
'metric_id': new_metric['id'], 'period': 'minute', 'value': ... | 65025958fa54e85035cc751ac08dd4b6bead4195 | 3,602,720 |
def get_terrapos_residual():
"""Get Terrapos residual Dataset by reading Terrapos residual output file
Returns:
dset (Dataset): Dataset with following fields:
==================== ================== =================================================================
Field ... | 2ef745f39dc2457bd872486e22ad062c53ebe5be | 3,602,721 |
def get_name(test):
"""Gets the name of a test.
PARAMETERS:
test -- dict; test cases for a question. Expected to contain a key
'name', which either maps to a string or a iterable of
strings (in which case the first string will be used)
RETURNS:
str; the name of the test
... | e9d5a5013b062077c499e0351786819c9bd6bd90 | 3,602,722 |
def remove_file(path: str) -> bool:
"""
Removes a file
Parameters
----------
path : str
Path to remove
Returns
-------
bool
True if removed, false if failed or doesn't exist
"""
with SQLiteCursor() as cursor:
cursor.execute("DELETE FROM tblFile WHERE Fil... | ff7d8e37a1c93f42bebadc9d33b929c6e160c57a | 3,602,723 |
from io import StringIO
import struct
def make_wave_header(frame_rate):
"""
Generate WAV header that precedes actual audio data sent to the speech
translation service. :param frame_rate: Sampling frequency (8000 for 8kHz
or 16000 for 16kHz). :return: binary string
"""
if frame_rate not in [80... | 8597981ab85cddd4f5edbd3613a620fb694e50e6 | 3,602,724 |
def blur_detect(im, threshold=7):
"""
Negative log-likelihood on the inverse gradient norm,
normalized by image size
"""
nll = -np.log(blur_measure(im))
return nll > threshold, nll | b8ff41d85101340cae7ad14423f216e4c6e6f677 | 3,602,726 |
import random
def generar_contrasena():
"""generar_contraseña es una funcion que contiene listas
Las cuales se unifican en otra lista llamada caracteres
en la cual en el ciclo for se genera una contraseña aleatoria de 10 caracteres
donde el modulo random elije los caracteres y los inserta en una nuev... | 2e3cf3057e9db3a4a761217693c0f557afddcbe0 | 3,602,727 |
def check_if_points_escape_box(u, box_boundaries):
"""
Determine if points u in 2D plane have escaped from box_boundaries limits.
Parameters
----------
u : ndarray, shape(n, 2),
Points in plane.
box_boundaries : list of 2 tuples of floats,
Values are interpreted as [[x_... | 41b04b72821bc39f387c7557be1b11f14e65c71d | 3,602,728 |
def assign_parents(filtered_tm_gp, unfiltered_tm_gp, chrom_sizes, denovo_gp, min_distance=0.9, stranded=True):
"""
Main function for assigning parental genes. Parental gene assignment methodology:
A) Each denovo transcript is evaluated for overlapping any transMap transcripts.
Overlap is defined as havi... | a1c27fc59e880d73cf180457d3e2b2a2fa9466b4 | 3,602,729 |
from typing import Any
import random
def assign_new_ids(items: dict[str, Any]) -> list[str]:
"""
Assigns new IDs to any item ID that starts with "NEW:" or is an empty
string. Will modify the dict in place. Will return a list of new item IDs
assigned.
"""
new_items = []
for item_id in items... | 4fb3466566f0fd9981e1c99cb429da629c843dab | 3,602,730 |
def deserialize_model(data, klass):
"""
Deserializes list or dict to model.
:param data: dict, list.
:type data: dict | list
:param klass: class literal.
:return: model object.
"""
instance = klass()
if not instance.swagger_types:
return data
for attr, attr_type in ite... | 42d27abb2a4adbb3eea48a2831f893ccf0d1051d | 3,602,731 |
def isatty(stream):
"""Check if a stream is attached to a console.
Args:
stream (:obj:`io.IOBase`):
Stream to check.
Returns:
:obj:`bool`
"""
return stream.isatty() if hasattr(stream, "isatty") else False | 4ec38e35413f0f8af76da5e2681f5502acf3d61e | 3,602,732 |
def preprocess_bert(sents, max_seq_len, tokenizer):
"""Loads a data file into a list of `InputBatch`s."""
features = []
for sent in sents:
# Remove double whitespaces
sent = " ".join(str(sent).split())
tokens = tokenizer.tokenize(sent)
if len(tokens) > max_seq_len - 2:
... | 992f02f2ae60a13b5f6bdc1e4082972f9c392334 | 3,602,733 |
def BestPairForLocalCorr(sample, percentile=0.05):
"""Find the pair of attributes with low correlation in the first percentiles and high correlation in the last percentiles or vice-versa.
Returns the pair with the highest difference.
Args:
sample (DataFrame): A DataFrame.
percentile (fl... | 32e36fd6637a6fa50f0311933e0e02e2ebb7d2c8 | 3,602,734 |
from datetime import datetime
async def register_ticket(ticket: Ticket, member: User) -> bool:
"""Registers the user to the ticket by appending a row with the relevant information
to the work sheet
"""
work_sheet = await get_worksheet(SHEET_ID, WORKSHEET)
row = ["", "", "", "", ""]
row[REG_BAR... | 96814f3e1f7b04e221c52d538f8852095f80249a | 3,602,735 |
def plain_decoder_factory():
"""Fixture returning PlainDecoder instance for the purpose of testing."""
return decoders.PlainDecoder() | eea660853d4b13f142e3eb7e3c5e6cc7c35a1338 | 3,602,736 |
def load_config(prefix="PF_"):
"""Load configuration from environmental file and environmental variables."""
envvar_settings = get_envvar(prefix=prefix)
verbose = envvar_settings.get("verbose", False)
dotenv_path = envvar_settings.get("config_dotenv_path", None)
settings = load_dotenv_config(doten... | 674b0004c2094cf99b16d0f955d135c3bbf45ef1 | 3,602,737 |
import pathlib
def load_catalog(catalog_path=None, catalog_file='catalog.json', include_filename=False, keys_only=False):
"""Get the set of available datasets from the catalog (nodes in the transformer graph).
Parameters
----------
include_filename: boolean
if True, returns a tuple: (list, fi... | ef2dd6f4c523b75d9d38f502cd10c70a5a34e8dd | 3,602,738 |
def orient_2D(p1, p2, p3):
""" Determine the orientation 2D points p1, p2, p3
Args:
p1,p2,p3: 2D points.
Returns:
positive if (p1, p2, p3) is in counterclockwise order.
negative if (p1, p2, p3) is in clockwise order.
0.0 if they are collinear.
"""
return PyMesh.orie... | 201b0f9db493148b5390b75aa2e5a68464c655da | 3,602,739 |
def _fileserver_mesh_import(url, filename):
"""Internal function that adds primitive support for DAE files
to the _mesh_import function of compas.robots."""
file_extension = _get_file_format(url)
if file_extension == 'dae':
# Magic!
return _dae_mesh_importer(filename)
else:
... | 568629088716ce0611645f985ea983e77cec0c43 | 3,602,740 |
def remove_whitespace(string: str) -> str:
"""
This function replace whitespaces for void string -> ''
Input: string with (or without) whitespace
Output: string without whitespace
"""
try:
if len(string) == 0 or (len(string) == 1 and string != ' '):
return string... | 6c5db5739913a9c31d70797a220e65ba511e7567 | 3,602,741 |
def get_consecutive_path_counts_visits(path_counts: pd.DataFrame,
j1: object,
j2: object) -> pd.DataFrame:
"""
Obtains path counts between two given consecutive columns from the given
table of path counts.
Args:
path_... | d90a209c8c09fa360dee89d7a401d4ba4baa7313 | 3,602,742 |
def getOption(conf, section, name, option):
"""Convenience function to retrieve a parsed and converted value from a
:class:`ConfigParser`.
:param conf: ConfigParser instance or similar
:param section: Section name
:param name: :class:`Option` name
:param option: :class:`Option` instance to use ... | fd67d331c22dda27e6ff0bcd16b0c08979aeb4be | 3,602,743 |
def _weibull_dist(dims, r=5.7, k=0.34):
"""Generate burst times following a Weibull distribution.
Args:
r (float): Rate parameter
k (float): Shape parameter
"""
lam = 1/(r*gamma(1 + 1/k))
if not any([isinstance(p, np.ndarray) for p in (r, k)]):
return lam*np.random.weibull(k... | c56677d323e47c7b938d1420a57bddd0487095bd | 3,602,744 |
def parameter_indices(*params):
"""
Parameter indices
"""
param_inds = dict([("P_kna", 0), ("g_K1", 1), ("g_Kr", 2), ("g_Ks", 3),\
("g_Na", 4), ("g_bna", 5), ("g_CaL", 6), ("g_bca", 7), ("g_to", 8),\
("K_mNa", 9), ("K_mk", 10), ("P_NaK", 11), ("K_NaCa", 12), ("K_sat",\
13), ("Km_... | 6012452a48fc770b6da28a6ac09817a3c299282b | 3,602,745 |
def remove_plane(xarr, x_range=None, y_range=None):
"""
Remove plane background from 2D data.
xarr is a multidimensional array of ndim >= 2.
x_range and y_range are slices for x-axis and y-axis where the slope of the plane is calculated.
Example:
flattened = remove_plane(xarr, (xarr.P3 < -0... | 99ad68c7166874451f9e6b021a66502ca8aab826 | 3,602,746 |
def egcd(a, b):
"""
Calculate the extended Euclidean algorithm. ax + by = gcd(a,b)
Args:
a (int): An integer.
b (int): Another integer.
Returns:
int: Greatest common denominator.
int: x coefficient of Bezout's identity.
int: y coefficient of Bezout's identity.
... | 87b35ff4e28529d1de2a6fb0063b69cee5dfec74 | 3,602,748 |
def gtag_script_tag():
"""
Render Google "Global Site Tag" HTML for, e.g., Google Analytics if the GTAG_ID setting is
present, non-None and non-empty. If the GTAG_ID setting is not present, None or empty, renders
the empty string.
"""
if not hasattr(settings, 'GTAG_ID'):
return ''
... | 63a34db421f3c7fde8e8f9043a858fc9ad19095a | 3,602,749 |
import uuid
from pathlib import Path
from typing import Optional
async def delete_user_from_group_handler(
token_restricted: bool = Depends(is_token_restricted),
group_id: uuid.UUID = Path(...),
username: Optional[str] = Form(None),
email: Optional[str] = Form(None),
current_user: models.User = De... | 6103a3198806668f111c5ee00ee30614d25801c1 | 3,602,751 |
def get_node_name(material, node_id):
"""
Get the name of a node based on its id
Args:
material (unicode): Material to get node name from
node_id (int): Node id to get name of
"""
return cmds.shaderfx(sfxnode=material, getPropertyValue=(node_id, "name")) | 5f44b1e8c6679a2e0e26c5378d6ef3e3ccb4d662 | 3,602,754 |
def get_recent_games(home_team_id, away_team_id):
"""
Get a list game ids for the 20 most recent games played for each team specified.
---Params---
home_team_id: int
away_team_id: int
---Returns---
a tuple of 2 lists. ---> ([home team game ids], [away team game ids])
"""
# Ensure... | d19aae83547ae55dab176f3bf90b8f31bd9cf43e | 3,602,755 |
def merc_lon(x):
"""Convert x in meter to longitude
"""
return (x / 6378137.000) / np.pi * 180 | e82acc50e33829fb371c44d1892d882f1c1b8e2d | 3,602,756 |
from unittest.mock import patch
async def test_flux_after_sunrise_before_sunset(hass, legacy_patchable_time):
"""Test the flux switch after sunrise and before sunset."""
platform = getattr(hass.components, "test.light")
platform.init()
assert await async_setup_component(
hass, light.DOMAIN, {l... | a8f2b5bcb3fb4f74677fd32c940705044955bf82 | 3,602,757 |
def Mirror2D(src, dst):
"""\
Flip an image horizontally.
:param src: source image
:param dst: destination image
:return: None
"""
return _ecvl.Mirror2D(src, dst) | 6c40d26f85ac011b8133333b1f125b1ee9d8c9c5 | 3,602,758 |
def rand_median(cube, ncomb, subset, nchoose=None):
"""
median combine `ncomb`` frames randomly from amongst `nchoose` in the interval
`subset`
Parameters
----------
cube
ncomb
subset
nchoose
Returns
-------
"""
if isinstance(subset, int):
subset = (0, subs... | 580dbe6b710d7e1ba25becbc919a2c9f195f488c | 3,602,759 |
def get_temp_filename(filename):
"""Returns the name of a valid temporary file."""
global config_dict
tmpdir=config_dict['tmpdir'][0]
return tmpdir+"/"+filename | 4e39163ad11a5702bb506cbc5b1213a8f90d595c | 3,602,760 |
def old(sym):
""" Return the "old" version of symbol "sym", that is, the one
representing "sym" in the pre_state.
"""
return sym.prefix('old_') | 4cc24bd0448195ee1c373106679177ce428e5937 | 3,602,761 |
def sample_faces(vertices, faces, n_samples=10**4):
"""
Samples point cloud on the surface of the model defined as vectices and
faces. This function uses vectorized operations so fast at the cost of some
memory.
Parameters:
vertices - n x 3 matrix
faces - n x 3 matrix
n_sampl... | 4bb6ce61c26bc54338e7c9c986a8d2335226f699 | 3,602,762 |
from typing import List
import logging
def uppercase_columns(df: DataFrame, col_list: List) -> DataFrame:
"""
Rewrite the selected columns with upper cases
:param df: dataframe
:param col_list: string array of columns to be upper-cased
:return: dataframe
"""
for col in col_list:
df... | 0d93c2b709e78d96c21866d39c3d960456a70f88 | 3,602,763 |
def policy_v2_1(probability=0.7, magnitude=5):
"""Randomly select one transformation from {color} transformations,
and then randomly select two transformations from {shape} transformations."""
policy = {
# color augment
0: [[('Mixup', probability, magnitude)], [('Gaussian_noise', probabi... | 8938e3a020663fe4cd72cd0a01f87fd60ad4ae91 | 3,602,764 |
def possible_edges(g, color_labels=[1, 2, 3, 4]):
"""
"""
g_adj, g_color = util.nx_to_adj(g)
out = []
for i in range(g_adj.shape[0]):
for j in range(i+1, g_adj.shape[1]):
if g_adj[i, j] == 0:
for c in color_labels:
out.append((i, j, c))
... | 5330818144a563dfb9dd05e2460602f36627d735 | 3,602,765 |
def owned(exp, object_class, target_class, query):
"""Get objects for which the user is owner.
Note: only the first id from the list of ids is used.
Args:
ids: the ids of owners.
Returns:
sqlalchemy.sql.elements.BinaryExpression if an object of `object_class`
is owned by one of the given users.
... | dea080461e64c57fd21a0f684b8f3ab5ad62873b | 3,602,769 |
from typing import Union
from typing import Tuple
def max(x: Union[ivy.Array, ivy.NativeArray],
axis: Union[int, Tuple[int]] = None,
keepdims: bool = False) \
-> ivy.Array:
"""
Calculates the maximum value of the input array ``x``.
.. note::
When the number of elements over ... | 22010b8bdd016b7aee7bcc6a7743af59bbad5671 | 3,602,770 |
def generate_AIF(scan_time_seconds, injection_start_time_seconds, time_interval_seconds, image_numpy=[], AIF_label_numpy=[], AIF_value_data=[], AIF_mode='label_average', dimension=4, AIF_label_value=1):
""" This function attempts to create AIFs both from 2D and 3D ROIs, or reroutes to population AIFs.
"""
... | aee3e491b3e8916112fa6583fc9f0b6446a47608 | 3,602,771 |
def get_files(paths, recursive=True, recurion_limit=None):
"""Given a list of paths, return a list of paths
"""
# For now we support only individual files
dirs = list(filter(op.isdir, paths))
if dirs:
raise NotImplementedError(
"ATM supporting only listing of individual files, no... | 5a969b332768f8e42640a3a5e4a5d8bb9b7cbbf3 | 3,602,772 |
from typing import Optional
def current_user() -> Optional[User]:
"""
Information about the currently logged in user, if any.
Returns a :class:`User` object after validating saved credentials, renewing
and updating them if necessary.
Returns ``None`` if there are no saved credentials or if they'... | a9c11d03ac78078de98fe16719c8d7e89e3178f3 | 3,602,774 |
from typing import Counter
def return_anagrams(letters: str) -> list:
"""
This returns all length anagrams from the input string.
:param: a string of alphabets
:return: a list of anagrams
:example:
$ python3 anagram_solver.py dive
>> ['de', 'ed', 'id', 'di', 'ie', 'vei', 'div', 'vie', 'd... | 7b63c00233d3708f4264d5bee35d317700705288 | 3,602,775 |
def canada(container, images):
""" Creates the Canada tab container within a parent container"""
multipane = ttk.Notebook(container)
f2 = ttk.Frame(multipane)
f5 = ttk.Frame(multipane)
multipane.add(f2, text='Southeast Canada')
multipane.add(f5, text='Canadian Prairie')
multipane.grid(row... | b62f7533b941def30f795949aab6b62be6990456 | 3,602,776 |
import sparknlp
import sparknlp_jsl
def get_authenticated_spark(SPARK_NLP_LICENSE, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, JSL_SECRET, gpu=False, ):
"""
Authenticates enviroment if not already done so and returns Spark Context with Healthcare Jar loaded
0. If no Spark-NLP-Healthcare, install it via PyPi... | 4cae6d4144975739910c7b175d778c5129d23540 | 3,602,777 |
def get_memory_version(bv, insn):
""" Get the version of the ssa memory for the `MediumLevelILInstruction`. For
the `LowLevelILInstruction` it finds out if the insn is memory operation
"""
if is_mlil(bv, insn):
if insn.ssa_memory_version > 0:
return insn.ssa_memory_version
elif "mem#0" in str... | 01ab0994fa3ff300f31f12867595671ca68b62cb | 3,602,778 |
def make_image_set_from_image_entries(modeladmin, request, queryset):
"""Make an `ImageSet` of the selected `ImageEntry`s.
This is an action on `ImageEntry`.
"""
return _make_image_set_from_images(queryset.all()) | 1af2fb2a3b7c75ac7eb57241e7f7a9ddcd1de9c6 | 3,602,779 |
def chi2(data, data_r, model, dof=1):
"""
Finds the chi squared (or reduced chi squared)
Notes
-----
The data, data_r and model arrays must have the same size.
Parameters
----------
data : array
Array containing the data
data_r : array
Array containing the errors (o... | fd47e12d0d32332ec810f00f12df9b94b53735db | 3,602,780 |
def _make_row(*column_messages, **kwargs):
"""Makes a formatted string.
Args:
*column_messages (str): Messages.
**kwargs:
Returns:
"""
color = kwargs.get("color", None)
col_size = kwargs.get("column_size", 40)
message = ""
for m in column_messages:
if m is not ... | 47e7a369974ad3ed9ecf93047ad9100aa101ab25 | 3,602,782 |
def join(bot, input):
"""Joins a channel, admins only"""
if not input.admin: return False
bot.write_packet(ID.HON_CS_JOIN_CHANNEL,input.group(2))
bot.config.set_add('channels',input.group(2).lower())
bot.reply("Joined channel: {0}".format(input.group(2))) | 63433ac90e9d6c35f6bfee097321921d1dfc30a7 | 3,602,783 |
def linear_gd(df_train, df_test, Y):
""" linear gradient descent """
binary = utils.check_binary(df_train[Y])
model = gd.gradient(df_train, df_train[Y], .00001, max_iterations=50)
print model
predict = gd.predict(df_train, model, binary)
print predict
error_train = mystats.get_error(predict,... | 5b9cd3d9194606b92eec41db3ea4227fee2b3f7d | 3,602,784 |
def get_extended_due_date(node):
"""
Gets the actual due date for the logged in student for this node, returning
the extendeded due date if one has been granted and it is later than the
global due date, otherwise returning the global due date for the unit.
"""
if isinstance(node, dict):
... | 2a90373e10bdb301bc13368d3d1464f2f2aeafa0 | 3,602,786 |
from typing import Optional
def get_default_url(prefix: str, identifier: str) -> Optional[str]:
"""Get the default URL for the given CURIE."""
entry = get_resource(prefix)
if entry is None:
return None
return entry.get_default_url(identifier) | aaca83779fc21d26a426ceebce9cbcfb0c8c7f9d | 3,602,788 |
from typing import Sequence
def create_home_pos_task(env_spec: EnvSpec, obs_labels: Sequence[str], state_des: np.ndarray) -> MaskedTask:
"""
Create a task for moving the robot to safe position.
.. note::
This task was designed with an RcsPySim environment in mind, but is not restricted to these e... | 93c3af36f5469d491fd88a1551bb660480595c6f | 3,602,789 |
from typing import OrderedDict
def scalable():
"""Scalable network. No parameters are tied to network size."""
fullconfig = configs.get_config('emergeplasticity')
fullconfig['train_steps'] = 4001
config = fullconfig['plasticnet']
config['hebb']['weight'] = False
config['hebb']['hebb_strength... | 1d5cfad09f6c4f32152e38496f4fad5726d881b0 | 3,602,790 |
def get_type_for_example(items):
"""
If all else fails, just use strings for examples.
"""
if not items:
type4example = DEFAULT_EXAMPLE_TYPE
else:
usable_items = [item for item in items if item != conf.UNKNOWN_ITEM]
item_type_names, _item_type_nice_names = get_item_type_names... | 05e058754cdbdad53cbe5cc80d8983c65ef3bae7 | 3,602,791 |
def milliseconds_to_time_clock_exp(milliseconds):
"""
Converts time components to a string suitable to be used on time expression
fot ttml
"""
if milliseconds is None:
return None
expression = '%(hours)02d:%(minutes)02d:%(seconds)02d.%(milliseconds)03d'
return expression % utils.mill... | 0cb623aab9074b9650b9736422770b2c46a90b0e | 3,602,792 |
from typing import Type
from typing import List
from typing import Union
def _create_gpflow_combination_kernel(
c: Type, children_types: List[Type]
) -> Union[gpflow.kernels.Sum, gpflow.kernels.Product]:
"""
Create GPflow combination kernel, either gpflow.kernels.Sum or gpflow.kernels.Product.
:param ... | 302db58e8de2b3131473552a7b7a0f71619c8847 | 3,602,793 |
def clean_delete_data(data):
""" Clean up the data so it's easier to process """
# Shouldn't be any extra rows, but just in case, drop all with no contents
data.dropna(inplace=True, how='all')
# replace NaN
data = data.replace(np.nan, '', regex=True)
# trim all columns
data = data.applymap... | fb6ea71ba2d9e936e103aeab08683674c4246518 | 3,602,794 |
def _remove_stopwords(line, nlp):
""" Helper function for removing stopwords from the given text line. """
line_nlp = nlp(line)
line_tokens = [tok.text for tok in line_nlp]
filtered_line = list()
# Filter
for tok in line_tokens:
lexeme = nlp.vocab[tok]
if not lexeme.is_stop:
... | 58932dc254874ea7a9e93e7e8d7fbf9f306f740b | 3,602,795 |
def get_concatenated_data(data_set_fnames, shuffle=True, seed=None):
"""Helper to take a set of data.npz filenames (from label-maker) and concatenate them"""
x_trains, x_tests = [], []
y_trains, y_tests = [], []
# Load each dataset and append
for data_set_fname in data_set_fnames:
pilot_se... | 5bacaf5ed8c3cdf70da099a2c53f6da780da255f | 3,602,796 |
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