content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _feature_normalization(features, method, feature_type):
"""Normalize the given feature vector `y`, with the stated normalization `method`.
Args:
features (np.ndarray): The signal array
method (str): Normalization method.
'global': Uses global mean and standard deviation values ... | 0479363651a4bcf1622e7bdb0906b55e3adb1cce | 12,500 |
def get_constraint(name):
"""
Lookup table of default weight constraint functions.
Parameters
----------
name : Constraint, None, str
Constraint to look up. Must be one of:
- 'l1' : L1 weight-decay.
- 'l2' : L2 weight-decay.
- 'l1-l2' : Combined L1-L2 weight-decay.
- Constraint : A custom implementa... | 09927531f4c6770e86ad603063e4edb0b0c4ff48 | 12,501 |
def player_count(conn, team_id):
"""Returns the number of players associated with a particular team"""
c = conn.cursor()
c.execute("SELECT id FROM players WHERE team_id=?", (team_id,))
return len(c.fetchall()) | cfced6da6c8927db2ccf331dca7d23bba0ce67e5 | 12,502 |
def _RedisClient(address):
"""
Return a connection object connected to the socket given by `address`
"""
h1, h2 = get_handle_pair(conn_type=REDIS_LIST_CONN)
c = _RedisConnection(h1)
#redis_client = util.get_redis_client()
redis_client = util.get_cache_client()
ip, port = address
chan... | fc8bab786bb521fbd0715da3ab690575d1df865e | 12,503 |
import math
def format_timedelta(value,
time_format="{days} days, {hours2}:{minutes2}:{seconds2}"):
"""Format a datetie.timedelta. See """
if hasattr(value, 'seconds'):
seconds = value.seconds + value.days * 24 * 3600
else:
seconds = int(value)
seconds_total = seconds
minutes ... | 19dc2b175beb1d030f14ae7fe96cb16d66f6c219 | 12,504 |
def random_account_user(account):
"""Get a random user for an account."""
account_user = AccountUser.objects.filter(account=account).order_by("?").first()
return account_user.user if account_user else None | 5fe918af67710d0d1519f56eee15811430a0e139 | 12,505 |
def overwrite(main_config_obj, args):
"""
Overwrites parameters with input flags
Args:
main_config_obj (ConfigClass): config instance
args (dict): arguments used to overwrite
Returns:
ConfigClass: config instance
"""
# Sort on nested level to override shallow items first
args = dict(s... | 98ee9cf034a9b714ae18e737761b06bfd669bfa4 | 12,506 |
def max_delta(model, new_model):
"""Return the largest difference between any two corresponding
values in the models"""
return max( [(abs(model[i] - new_model[i])).max() for i in range(len(model))] ) | faf4a9fb2b24f7e7b4f357eef195e435950ea218 | 12,507 |
def wiener_khinchin_transform(power_spectrum, frequency, time):
"""
A function to transform the power spectrum to a correlation function by the Wiener Khinchin transformation
** Input:**
* **power_spectrum** (`list or numpy.array`):
The power spectrum of the signal.
* **frequency** (`lis... | 3cf8916c75632e3a0db52f907ce180eb766f9f2e | 12,508 |
def child_is_flat(children, level=1):
"""
Check if all children in section is in same level.
children - list of section children.
level - integer, current level of depth.
Returns True if all children in the same level, False otherwise.
"""
return all(
len(child) <= level + 1 or child... | e14f9210a90b40b419d21fffa1542212429d80be | 12,509 |
from pathlib import Path
def load_dataset(name, other_paths=[]):
"""Load a dataset with given (file) name."""
if isinstance(name, Dataset):
return name
path = Path(name)
# First, try if you have passed a fully formed dataset path
if path.is_file():
return _from_npy(name, classes=... | 3f3d2e7e7ec577098e1a1599c74638ced5d3c103 | 12,510 |
def isqrtcovresnet101b(**kwargs):
"""
iSQRT-COV-ResNet-101 model with stride at the second convolution in bottleneck block from 'Towards Faster Training
of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization,'
https://arxiv.org/abs/1712.01034.
Parameters:
----------... | fdf166fa3ce9e893e8e97d1057dac89d084d2217 | 12,511 |
def get_data(name: str, level: int, max_level: int) -> str:
"""從維基頁面爬取資料
參數:
name: 程式或節點名稱
level: 欲查詢的等級
回傳:
爬到的資料
"""
reply_msg = []
for dataframe in read_html(generate_url(name)):
if (max_level < dataframe.shape[0] < max_level + 3 and
dataframe... | 4e0f11a33c81993132d45f3fdad5f42c1288bbe5 | 12,512 |
import os
def is_processable(path: str, should_match_extension: str):
"""
Process scandir entries, copying the file if necessary
"""
if not os.path.isfile(path):
return False
filename = os.path.basename(path)
_, extension = os.path.splitext(filename)
if extension.lower() != should... | 5d99b821d3653ff452acac1e5fe48cab559c509e | 12,513 |
def insert_data(context, data_dict):
"""
:raises InvalidDataError: if there is an invalid value in the given data
"""
data_dict['method'] = _INSERT
result = upsert_data(context, data_dict)
return result | c631016be36f1988bfa9c98cea42a7f63fddc276 | 12,514 |
import time
def timestamp():
"""Get the unix timestamp now and retuen it.
Attention: It's a floating point number."""
timestamp = time.time()
return timestamp | 8e56a61659da657da9d5dda364d4d9e8f3d58ed2 | 12,515 |
from datetime import datetime
def _n64_to_datetime(n64):
"""Convert Numpy 64 bit timestamps to datetime objects. Units in seconds"""
return datetime.utcfromtimestamp(n64.tolist() / 1e9) | a25327f2cd0093635f86f3145f5674cc1945d3f8 | 12,516 |
import itertools
def cycle(iterable):
"""Make an iterator returning elements from the iterable and saving a copy of each.
When the iterable is exhausted, return elements from the saved copy. Repeats indefinitely.
This function uses single dispatch.
.. seealso:: :func:`itertools.cycle`
"""
re... | 13f479fca709dffa77eeca3d32ff7265c81588bf | 12,517 |
def get_availability_zone(name=None,state=None,zone_id=None,opts=None):
"""
`.getAvailabilityZone` provides details about a specific availability zone (AZ)
in the current region.
This can be used both to validate an availability zone given in a variable
and to split the AZ name into its compone... | 6cb20524c1e0a2539e221711f1153949ab72f8e1 | 12,518 |
def _add_u_eq(blk, uex=0.8):
"""Add heat transfer coefficent adjustment for feed water flow rate.
This is based on knowing the heat transfer coefficent at a particular flow
and assuming the heat transfer coefficent is porportial to feed water
flow rate raised to certain power (typically 0.8)
Args:
... | f6b34a8e75367b43dbe759d273aa4be7dc371c12 | 12,519 |
def find_process_in_list( proclist, pid ):
"""
Searches for the given 'pid' in 'proclist' (which should be the output
from get_process_list(). If not found, None is returned. Otherwise a
list
[ user, pid, ppid ]
"""
for L in proclist:
if pid == L[1]:
return L
r... | 19eab54b4d04b40a54a39a44e50ae28fbff9457c | 12,520 |
def solution(s, start_pos, end_pos):
"""
Find the minimal nucleotide from a range of sequence DNA.
:param s: String consisting of the letters A, C, G and T,
which correspond to the types of successive nucleotides in the sequence
:param start_pos: array with the start indexes for the intervals to check
:p... | 25ef2f7e9b009de0534f8dde132c0eb44e3fe374 | 12,521 |
def validate_address(value: str, context: dict = {}) -> str:
"""
Default address validator function. Can be overriden by providing a
dotted path to a function in ``SALESMAN_ADDRESS_VALIDATOR`` setting.
Args:
value (str): Address text to be validated
context (dict, optional): Validator c... | 65e04a4780432608aa049687da98bd05a527fbad | 12,522 |
import os
import random
def select_images(img_dir, sample_size=150, random_seed=42):
"""Selects a random sample of image paths."""
img_paths = []
for file in os.listdir(img_dir):
if file.lower().endswith('.jpeg'):
img_paths.append(os.path.join(img_dir, file))
if sample_size is not... | 999bf71eb6b8072bd91cbb98d9fe1b50d5e9b8ac | 12,523 |
import os
import json
def load_period_data(period):
""" Load period data JSON file
If the file does not exist and empty dictionary is returned.
"""
filename = os.path.join(PROTOCOL_DIR, PERIOD_FILE_TEMPLATE % period)
if not os.path.exists(filename):
return {}
with open(filename,... | c6c4c7121c55e1fd54d47a964054520f1f2fde97 | 12,524 |
from pathlib import Path
def _get_hg_repo(path_dir):
"""Parse `hg paths` command to find remote path."""
if path_dir == "":
return ""
hgrc = Path(path_dir) / ".hg" / "hgrc"
if hgrc.exists():
config = ConfigParser()
config.read(str(hgrc))
if "paths" in config:
... | 773ab4b45ba6883446c8e4a7725b7ac9d707440f | 12,525 |
def array_to_string(array,
col_delim=' ',
row_delim='\n',
digits=8,
value_format='{}'):
"""
Convert a 1 or 2D array into a string with a specified number
of digits and delimiter. The reason this exists is that the
basic nump... | 9e7f189049b1ad3eff3679568a84e7151e2c643c | 12,526 |
def get_dp_logs(logs):
"""Get only the list of data point logs, filter out the rest."""
filtered = []
compute_bias_for_types = [
"mouseout",
"add_to_list_via_card_click",
"add_to_list_via_scatterplot_click",
"select_from_list",
"remove_from_list",
]
for log in... | e0a7c579fa9218edbf942afdbdb8e6cf940d1a0c | 12,527 |
from typing import List
from typing import Dict
def assign_reports_to_watchlist(cb: CbThreatHunterAPI, watchlist_id: str, reports: List[Dict]) -> Dict:
"""Set a watchlist report IDs attribute to the passed reports.
Args:
cb: Cb PSC object
watchlist_id: The Watchlist ID to update.
reports: T... | 92bb0369211c1720fa4d9baa7a4e3965851339f2 | 12,528 |
def visualize_filter(
image,
model,
layer,
filter_index,
optimization_parameters,
transformation=None,
regularization=None,
threshold=None,
):
"""Create a feature visualization for a filter in a layer of the model.
Args:
image (array): the image to be modified by the fea... | 09940c0484361240929f61f04c9a96771b440033 | 12,529 |
def subtraction(x, y):
"""
Subtraction x and y
>>> subtraction(-20, 80)
-100
"""
assert isinstance(x, (int, float)), "The x value must be an int or float"
assert isinstance(y, (int, float)), "The y value must be an int or float"
return x - y | 203233897d31cb5bc79fca0f8c911b03d7deb5ba | 12,530 |
import aiohttp
async def paste(text: str) -> str:
"""Return an online bin of given text."""
session = aiohttp.ClientSession()
async with session.post("https://hasteb.in/documents", data=text) as post:
if post.status == 200:
response = await post.text()
return f"https://has... | d204f6f1db3aa33c98c4ebeae9888acc438f7dc3 | 12,531 |
def lr_step(base_lr, curr_iter, decay_iters, warmup_iter=0):
"""Stepwise exponential-decay learning rate policy.
Args:
base_lr: A scalar indicates initial learning rate.
curr_iter: A scalar indicates current iteration.
decay_iter: A list of scalars indicates the numbers of
iteration when the lear... | b8cfe670aba0bed1f84ae09c6271e681fad42864 | 12,532 |
def apo(coalg):
"""
Extending an anamorphism with the ability to halt.
In this version, a boolean is paired with the value that indicates halting.
"""
def run(a):
stop, fa = coalg(a)
return fa if stop else fa.map(run)
return run | a1e64d9ed49a8641095c8a8c20ae08c1cc6e9c19 | 12,533 |
def cat_sample(ps):
"""
sample from categorical distribution
ps is a 2D array whose rows are vectors of probabilities
"""
r = nr.rand(len(ps))
out = np.zeros(len(ps),dtype='i4')
cumsums = np.cumsum(ps, axis=1)
for (irow,csrow) in enumerate(cumsums):
for (icol, csel) in enumer... | 30009b31dba0eff23010bfe6d531e8c55e46873c | 12,534 |
def download_network(region, network_type):
"""Download network from OSM representing the region.
Arguments:
region {string} -- Location. E.g., "Manhattan Island, New York City, New York, USA"
network_type {string} -- Options: drive, drive_service, walk, bike, all, all_private
Retu... | d77c9464641c90cc029adc0649739b499298d173 | 12,535 |
def extract_text(text):
""" """
l = []
res = []
i = 0
while i < len(text) - 2:
h, i, _ = next_token(text, i)
obj = text[h:i]
l.append(obj)
for j, tok in enumerate(l):
if tok == b'Tf':
font = l[j-2]
fsize = float(l[j-1])
elif tok ==... | 9b0746be6f6fa39548fd34f3bffda7e8baf4a6ef | 12,536 |
def add_pruning_arguments_to_parser(parser):
"""Add pruning arguments to existing argparse parser"""
parser.add_argument('--do_prune', action='store_true',
help="Perform pruning when training a model")
parser.add_argument('--pruning_config', type=str,
default=... | 2a94e0986564f4af8fe580ca3500f06c04598f14 | 12,537 |
import itertools
from functools import reduce
import copy
def invokeRule(priorAnswers,
bodyLiteralIterator,
sip,
otherargs,
priorBooleanGoalSuccess=False,
step=None,
debug=False,
buildProof=False):
"""
Con... | 66be56a818a620c5c47a7537b612e91341c7d334 | 12,538 |
def read_ult_meta(filebase):
"""Convenience fcn for output of targeted metadata."""
meta = _parse_ult_meta(filebase)
return (meta["NumVectors"],
meta["PixPerVector"],
meta["ZeroOffset"],
meta["Angle"],
meta["PixelsPerMm"],
meta["FramesPerSec"],
... | b2237a2dab9faf98179f69de9e9a5f1dc7289f78 | 12,539 |
from typing import Iterable
from typing import List
def safe_identifiers_iterable(val_list: Iterable[str]) -> List[str]:
"""
Returns new list, all with safe identifiers.
"""
return [safe_identifier(val) for val in val_list] | 6b80d90cfac2ea527ace38cc6550571b5f120a7f | 12,540 |
def encode_varint(value, write):
""" Encode an integer to a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
on how those can be produced.
Arguments:
value (int): Value to encode
write (function): Called per byte that needs ... | 075286208008a0b7507eafe19158eebdb2af66b7 | 12,541 |
def heap_sort(li):
""" [list of int] => [list of int]
Heap sort: divides its input into a sorted and an unsorted region,
and it iteratively shrinks the unsorted region by extracting the
largest element from it and inserting it into the sorted region.
It does not waste time with a linear-time scan of... | a72be31e5256c880c157636aa7a15df013ce651d | 12,542 |
def vector_field(v, t, inf_mat, state_meta):
"""vector_field returns the temporal derivative of a flatten state vector
:param v: array of shape (1,mmax+1+(nmax+1)**2) for the flatten state vector
:param t: float for time (unused)
:param inf_mat: array of shape (nmax+1,nmax+1) representing the infection... | 31c8023966fd3e5c35b734759a3747f0d2752390 | 12,543 |
def newton(start, loss_fn, *args, lower=0, upper=None, epsilon=1e-9):
"""
Newton's Method!
"""
theta, origin, destination = args[0], args[1], args[2]
if upper is None:
upper = 1
start = lower
while True:
if loss_fn(start, theta, origin, destination) > 0:
start ... | bbd04297639fbc964c55a8c964e5bd5fb24d6e22 | 12,544 |
import torch
def eval_det_cls(pred, gt, iou_thr=None):
"""Generic functions to compute precision/recall for object detection for a
single class.
Args:
pred (dict): Predictions mapping from image id to bounding boxes \
and scores.
gt (dict): Ground truths mapping from image id ... | 762f70d95261509778a1b015af30eab68f951b15 | 12,545 |
import pathlib
from typing import List
from typing import Dict
import tqdm
def parse_g2o(path: pathlib.Path, pose_count_limit: int = 100000) -> G2OData:
"""Parse a G2O file. Creates a list of factors and dictionary of initial poses."""
with open(path) as file:
lines = [line.strip() for line in file.r... | 6c766401220849e337279e8b465f9d67477a1599 | 12,546 |
def _som_actor(env):
"""
Construct the actor part of the model and return it.
"""
nactions = np.product(env.action_shape)
model = keras.models.Sequential()
model.add(keras.layers.Flatten(input_shape=(1,) + env.observation_space.shape))
model.add(keras.layers.Dense(400))
model.add(keras.... | e3bc1f675b16b2d728b1c070324139f0d99071a7 | 12,547 |
def sendEmail():
"""email sender"""
send_email('Registration ATS',
['manavshrivastava@hotmail.com'],
'Thanks for registering ATS!',
'<h3>Thanks for registering with ATS!</h3>')
return "email sent to manavshrivastava@hotmail.com... | e9125c32adac8267aaa550e59e27db4a10746ace | 12,548 |
import scipy
def Pvalue(chi2, df):
"""Returns the p-value of getting chi2 from a chi-squared distribution.
chi2: observed chi-squared statistic
df: degrees of freedom
"""
return 1 - scipy.stats.chi2.cdf(chi2, df) | 1a2198e5d47396fc785a627d96513ded1d6894e0 | 12,549 |
def template(template_lookup_key: str) -> str:
"""Return template as string."""
with open(template_path(template_lookup_key), "r") as filepath:
template = filepath.read()
return template | d03bbc2baa8cb18174a468579bdea1da906de09d | 12,550 |
def filter_rows(df, condition, reason):
"""
:param reason:
:param df:
:param condition: boolean, true for row to keep
:return: filter country_city_codes df
"""
n_dropped = (condition == False).sum()
print(
f"\nexcluding {n_dropped} locations ({n_dropped / df.shape[0]:.1%}) due to... | 7e5e6925bfb7d90bc90b42fda202d80e8ef5e3f6 | 12,551 |
def parse_projected_dos(f):
"""Parse `projected_dos.dat` output file."""
data = np.loadtxt(f)
projected_dos = {"frequency_points": data[:, 0], "projected_dos": data[:, 1:].T}
pdos = orm.XyData()
pdos_list = [pd for pd in projected_dos["projected_dos"]]
pdos.set_x(projected_dos["frequency_points"... | 89c280e92c7598e3947d8ccda20b921c601c9b10 | 12,552 |
def get_from_parameters(a, b, c, alpha, beta, gamma):
"""
Create a Lattice using unit cell lengths and angles (in degrees).
This code is modified from the pymatgen source code [1]_.
Parameters
----------
a : :class:`float`:
*a* lattice parameter.
b : :class:`float`:
*b* la... | 076763f30da86b12747ede930993d99fc3b742d8 | 12,553 |
import random
def random_chinese_name():
"""生成随机中文名字
包括的名字格式：2个字名字**，3个字名字***，4个字名字****
:return:
"""
name_len = random.choice([i for i in range(4)])
if name_len == 0:
name = random_two_name()
elif name_len == 1:
name = random_three_name()
elif name_len == 2:
n... | c86232cb81c492e2301837f5e330e6140ee503f3 | 12,554 |
def power_list(lists: [list]) -> list:
""" power set across the options of all lists """
if len(lists) == 1:
return [[v] for v in lists[0]]
grids = power_list(lists[:-1])
new_grids = []
for v in lists[-1]:
for g in grids:
new_grids.append(g + [v])
return new_grids | 135e3cde20388d999456e2e8a2fed4d98fac581d | 12,555 |
import time
def send_email(from_email, to, subject, message, html=True):
"""
Send emails to the given recipients
:param from_email:
:param to:
:param subject:
:param message:
:param html:
:return: Boolean value
"""
try:
email = EmailMessage(subject, message, from_email,... | 28751bc30f51148c0389d4127229e6352a18cacb | 12,556 |
import random
def attack(health, power, percent_to_hit):
"""Calculates health from percent to hit and power of hit
Parameters:
health - integer defining health of attackee
power - integer defining damage of attacker
percent to hit - float defining percent chance to hit of attacker
... | 83a74908f76f389c798b28c5d3f9035d2d8aff6a | 12,557 |
def signal_requests_mock_factory(requests_mock: Mocker) -> Mocker:
"""Create signal service mock from factory."""
def _signal_requests_mock_factory(
success_send_result: bool = True, content_length_header: str = None
) -> Mocker:
requests_mock.register_uri(
"GET",
"h... | 543f73ec004911c87e9986cbd940a733f03287bf | 12,558 |
def test_dwt_denoise_trace():
""" Check that sample data fed into dwt_denoise_trace() can be processed
and that the returned signal is reasonable (for just one trace)"""
# Loma Prieta test station (nc216859)
data_files, origin = read_data_dir('geonet', 'us1000778i', '*.V1A')
trace = []
trace = ... | 4c526e7e76c8672322bec0323974ca2ee20e25dd | 12,559 |
def get_networks(project_id=None,
auth_token=None):
"""
Get a list of all routed networks
"""
url = CATALOG_HOST + "/routednetwork"
try:
response_body = _api_request(url=url,
http_method="GET",
project... | c2c9bfe05cfa416c9e37d04aefcc640d5d2250f7 | 12,560 |
def feature_registration(source,target, MIN_MATCH_COUNT = 12):
"""
Obtain the rigid transformation from source to target
first find correspondence of color images by performing fast registration
using SIFT features on color images.
The corresponding depth values of the matching keypoints is then use... | d5839ef3586acd84c57341f19700de38660f9a9f | 12,561 |
def set_metadata(testbench_config, testbench):
"""
Perform the direct substitutions from the sonar testbench metadata into the
the testbench
Args:
testbench_config (Testbench): Sonar testbench description
testbench (str): The testbench template
"""
for key, value in testbench_co... | 375712b92f7467ee4d49e5d9e91250464c81337d | 12,562 |
def index(a, x):
"""Locate the leftmost value exactly equal to x"""
i = bisect_left(a, x)
if i != len(a) and a[i] == x:
return i
raise ValueError | f77aed5c55750b848fdf51b66b38f3774c812e23 | 12,563 |
def convert_secondary_type_list(obj):
"""
:type obj: :class:`[mbdata.models.ReleaseGroupSecondaryType]`
"""
type_list = models.secondary_type_list()
[type_list.add_secondary_type(convert_secondary_type(t)) for t in obj]
return type_list | d84d20f6d82b462bda5bf04f6784effea47a0265 | 12,564 |
import matplotlib.pyplot as plt
def run(inputs, parameters = None):
"""Function to be callled by DOE and optimization. Design Variables are
the only inputs.
:param inputs: {'sma', 'linear', 'sigma_o'}"""
def thickness(x, t, chord):
y = af.Naca00XX(chord, t, [x], return_dict =... | 65c1951fb4bbed8ab2832ce4892a6c6308439f79 | 12,565 |
import json
def load_data(path):
"""Load JSON data."""
with open(path) as inf:
return json.load(inf) | 531fc2b27a6ab9588b1f047e25758f359dc21b6d | 12,566 |
from pathlib import Path
def get_extension(file_path):
"""
get_extension(file)
Gets the extension of the given file.
Parameters
----------
file_path
A path to a file
Returns
-------
str
Returns the extension of the file if it exists or None otherwise.
... | 7b1c4ba4f20ac913bb38292d4a704869cab6937e | 12,567 |
def rank_in_group(df, group_col, rank_col, rank_method="first"):
"""Ranks a column in each group which is grouped by another column
Args:
df (pandas.DataFrame): dataframe to rank-in-group its column
group_col (str): column to be grouped by
rank_col (str): column to be ranked for... | f2ae45641339bf4bc71bc48a415a28602ccf8da3 | 12,568 |
import six
def get_layer_options(layer_options, local_options):
"""
Get parameters belonging to a certain type of layer.
Parameters
----------
layer_options : list of String
Specifies parameters of the layer.
local_options : list of dictionary
Specifies local parameters in a m... | e40945395c4a96c0a0b9447eeb1d0b50cf661bd7 | 12,569 |
def expr(term:Vn,add:Vt,expr:Vn)->Vn:
"""
expr -> term + expr
"""
return {"add":[term,expr]} | f66475ecbd255ac4c4a04b0d705f1c052c4ee123 | 12,570 |
import json
def gene_box(cohort, order='median', percentage=False):
"""Box plot with counts of filtered mutations by gene.
percentage computes fitness as the increase with respect to
the self-renewing replication rate lambda=1.3.
Color allows you to use a dictionary of colors by gene.
... | 851c166246144b14d51863b4c775baa88ab87205 | 12,571 |
from typing import Union
from typing import List
def _clip_and_count(
adata: AnnData,
target_col: str,
*,
groupby: Union[str, None, List[str]] = None,
clip_at: int = 3,
inplace: bool = True,
key_added: Union[str, None] = None,
fraction: bool = True,
) -> Union[None, np.ndarray]:
""... | 20673965557afdcf75b3201cf743fff100981ec3 | 12,572 |
def create_training_patches(images, patch_size, patches_per_image=1, patch_stride=None):
"""
Returns a batch of image patches, given a batch of images.
Args:
images (list, numpy.array): Batch of images.
patch_size (tuple, list): The (width, height) of the patch to
return.
... | 5fce19d2d13f790500e0cbd42934dd6e83c6b084 | 12,573 |
import time
def get_prover_options(prover_round_tag='manual',
prover_round=-1) -> deephol_pb2.ProverOptions:
"""Returns a ProverOptions proto based on FLAGS."""
if not FLAGS.prover_options:
tf.logging.fatal('Mandatory flag --prover_options is not specified.')
if not tf.gfile.Exists(FL... | ee1ee9fb7ce573c543f0750d6b8fd1eed98deec9 | 12,574 |
def bracketpy(pystring):
"""Find CEDICT-style pinyin in square brackets and correct pinyin.
Looks for square brackets in the string and tries to convert its
contents to correct pinyin. It is assumed anything in square
brackets is CC-CEDICT-format pinyin.
e.g.: "拼音[pin1 yin1]" will be converted int... | 0499047ec45e6b9c66c27dd89663667b13ddbfb1 | 12,575 |
import psutil
def get_ram_usage_bytes(size_format: str = 'M'):
"""
Size formats include K = Kilobyte, M = Megabyte, G = Gigabyte
"""
total = psutil.virtual_memory().total
available = psutil.virtual_memory().available
used = total - available
# Apply size
if size_format == 'K':
... | 990987078b0ad3c2ac2ee76dcf96b7cdf01f0354 | 12,576 |
def weighted_crossentropy(weights, name='anonymous'):
"""A weighted version of tensorflow.keras.objectives.categorical_crossentropy
Arguments:
weights = np.array([0.5,2,10]) # Class one at 0.5, class 2 twice the normal weights, class 3 10x.
name: string identifying the loss to differentiate whe... | 071ab00a723d54194b4b27c889c638debe82f10a | 12,577 |
def _get_package_type(id):
"""
Given the id of a package this method will return the type of the
package, or 'dataset' if no type is currently set
"""
pkg = model.Package.get(id)
if pkg:
return pkg.type or u'dataset'
return None | c84e137e2b0adaf8719d757f178aa47d4a63c46a | 12,578 |
def _find_protruding_dimensions(f, care, fol):
"""Return variables along which `f` violates `care`."""
vrs = joint_support([f, care], fol)
dims = set()
for var in vrs:
other_vars = vrs - {var}
f_proj = fol.exist(other_vars, f)
care_proj = fol.exist(other_vars, care)
if (c... | 02da5718645652288c9fa6fcedc07198afe49a58 | 12,579 |
import os
import glob
def prepare_data(train_mode, dataset="Train"):
"""
Args:
dataset: choose train dataset or test dataset
For train dataset, output data would be ['.../t1.bmp',
'.../t2.bmp',..., 't99.bmp']
"""
# Defines list of data path lists for diffe... | 08a17868b36b20c495253e366fcb00a1d105cfa0 | 12,580 |
import random
def simulate_relatedness(genotypes, relatedness=.5, n_iter=1000, copy=True):
"""
Simulate relatedness by randomly copying genotypes between individuals.
Parameters
----------
genotypes : array_like
An array of shape (n_variants, n_samples, ploidy) where each
element... | e319f4e15c4c08eb90260b77efc25ea330aac4c9 | 12,581 |
def pages_substitute(content):
"""
Substitute tags in pages source.
"""
if TAG_USERGROUPS in content:
usergroups = UserGroup.objects.filter(is_active=True).order_by('name')
replacement = ", ".join(f"[{u.name}]({u.webpage_url})" for u in usergroups)
content = content.replace(TAG_U... | 13c2138256a0e1afa0ad376994849f2716020540 | 12,582 |
def vcfanno(vcf, out_file, conf_fns, data, basepath=None, lua_fns=None):
"""
annotate a VCF file using vcfanno (https://github.com/brentp/vcfanno)
"""
if utils.file_exists(out_file):
return out_file
if lua_fns is None:
lua_fns = []
vcfanno = config_utils.get_program("vcfanno", da... | 808488bd07c56b541694715193df4ae1cb51869c | 12,583 |
def clean(params: dict) -> str:
"""
Build clean rules for Makefile
"""
clean = "\t@$(RM) -rf $(BUILDDIR)\n"
if params["library_libft"]:
clean += "\t@make $@ -C " + params["folder_libft"] + "\n"
if params["library_mlx"] and params["compile_mlx"]:
clean += "\t@make $@ -C " + params["folder_mlx"] + "\n"
retur... | fb7dd0e7a2fbb080dd8b0d5d4489e9c5ef1367ec | 12,584 |
import re
def mathematica(quero: str, meta: str = '') -> bool:
"""mathematica
Rudimentar mathematical operations (boolean result)
Args:
quero (_type_, optional): _description_. Defaults to str.
Returns:
bool: True if evaluate to True.
"""
# neo_quero = quero.replace(' ', '')... | b05777e880688d8f3fc90ba9d54098f341054bd7 | 12,585 |
import sys
def fasta2vcf(f):
"""convert fasta to vcf dataframe
Input
-----
Fasta file, _ref is recognized as ref and _alt is used as alt, these are two keywords
Output
------
vcf dataframe: chr, pos, name, ref, alt, reference sequence
"""
my_dict = {}
for r in SeqIO.parse(f, "fasta"):
my_dict[r.id] ... | 673e69e644b6caf68f0738cfaa8204b80877a412 | 12,586 |
def time_pet(power,energy):
"""Usage: time_pet(power,energy)"""
return energy/power | 11e9c82b8c1be84995f9517e04ed5e1270801e27 | 12,587 |
def compute_sigma0(
T,
S,
**kwargs,
):
"""
compute the density anomaly referenced to the surface
"""
return compute_rho(T, S, 0, **kwargs) - 1000 | 300d5552c70e6fd6d8708345aa3eed53795309cf | 12,588 |
def get_neighbors_radius(nelx, nely, coord, connect, radius):
""" Check neighboring elements that have the centroid within the predetermined radius.
Args:
nelx (:obj:`int`): Number of elements on the x axis.
nely (:obj:`int`): Number of elements on the x axis
coord (:obj:`numpy.array`):... | 669e11d3a2890f1485e33e021b2671ff6f197c03 | 12,589 |
import copy
def merge_with(obj, *sources, **kwargs):
"""
This method is like :func:`merge` except that it accepts customizer which is invoked to produce
the merged values of the destination and source properties. If customizer returns ``None``,
merging is handled by this method instead. The customizer... | 94a16ae7d3f3e73ef8e27b32cd38a09c61ad1b2b | 12,590 |
def count_class_nbr_patent_cnt(base_data_list, calculate_type):
"""
统计在所有数据中不同分类号对应的专利数量
:param base_data_list:
:return:
"""
class_number_patent_cnt_dict = dict()
for base_data in base_data_list:
class_number_value = base_data[const.CLASS_NBR]
calculate_class_number_patent_co... | 6dfe06c2233fbfafc8083dc968d32520564319f8 | 12,591 |
def plot_pta_L(df):
"""
INPUTS
-df: pandas dataframe containing the data to plot
OUTPUTS
-saves pta graphs in .html
"""
title = generate_title_run_PTA(df, "Left Ear", df.index[0])
labels = {"title": title,
"x": "Frequency (Hz)",
"y": "Hearing Threshold (dB HL... | ec82b58a6a476bee5e864b8678bb90d2998d4a02 | 12,592 |
def create_graph(edge_num: int, edge_list: list) -> dict:
"""
Create a graph expressed with adjacency list
:dict_key : int (a vertex)
:dict_value : set (consisted of vertices adjacent to key vertex)
"""
a_graph = {i: set() for i in range(edge_num)}
for a, b in edge_list:
a_graph... | 6ec1a71cf82a3a669090df42ac7d53e1286fda2d | 12,593 |
from typing import Optional
from typing import Callable
from typing import Any
from typing import List
import inspect
def multikey_fkg_allowing_type_hints(
namespace: Optional[str],
fn: Callable,
to_str: Callable[[Any], str] = repr) -> Callable[[Any], List[str]]:
"""
Equivalent of :fun... | 33e04169618bae3e5d7239e5256afaa9f65355f6 | 12,594 |
def get_current_version() -> str:
"""Read the version of the package.
See https://packaging.python.org/guides/single-sourcing-package-version
"""
version_exports = {}
with open(VERSION_FILE) as file:
exec(file.read(), version_exports) # pylint: disable=exec-used
return version_exports["... | c283d58881aa381503bb3500bd7d745f25df0f7e | 12,595 |
import random
def seed_story(text_dict):
"""Generate random seed for story."""
story_seed = random.choice(list(text_dict.keys()))
return story_seed | 0c0f41186f6eaab84a1d197e9335b4c28fd83785 | 12,596 |
from pathlib import Path
import sys
def detect_conda_env():
"""Inspect whether `sys.executable` is within a conda environment and if it is,
return the environment name and Path of its prefix. Otherwise return None, None"""
prefix = Path(sys.prefix)
if not (prefix / 'conda-meta').is_dir():
# No... | 2cb88ebfbb8a2919300e1d0072540e448dcf35ad | 12,597 |
def _get_rel_att_inputs(d_model, n_heads): # pylint: disable=invalid-name
"""Global relative attentions bias initialization shared across the layers."""
assert d_model % n_heads == 0 and d_model % 2 == 0
d_head = d_model // n_heads
bias_initializer = init.RandomNormalInitializer(1e-6)
context_bias_layer = c... | 57f58f29a586571f1cc8fa1fc69956a4168cbf16 | 12,598 |
def two_time_pad():
"""A one-time pad simply involves the xor of a message with a key to produce a ciphertext: c = m ^ k.
It is essential that the key be as long as the message, or in other words that the key not be repeated for two distinct message blocks.
Your task:
In this problem you will b... | d4c45312f32b372a065365c78a991969e2bc53be | 12,599 |
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