content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import functools
def action_logging(f):
"""
Decorator to log user actions
"""
@functools.wraps(f)
def wrapper(*args, **kwargs):
with create_session() as session:
if g.user.is_anonymous:
user = 'anonymous'
else:
user = g.user.username... | 60a54aae190b111bf522c873e34126bdf964f154 | 48,700 |
def ClassifyWspecifier(wspecifier):
"""Interprets type / filenames / options for the given wspecifier.
Args:
wspecifier: A string indicating the wspecifier.
Returns:
(WspecifierType, archive_filename, script_filename, WspecifierOptions)
for the given filename.
Examples:
... | 446ca165d4e028ab3be4eed21ff7f0e601d6f0a1 | 48,701 |
def canonicalize_instance_info(node):
"""
Convert what is returned from GCE into the butter standard format.
"""
return Instance(
instance_id=node.uuid,
public_ip=node.public_ips[0],
private_ip=node.private_ips[0],
state=node.state) | 6c5760fb231822f2b3edfc3f76937fb2e82ea464 | 48,702 |
def get_track( track_id ):
"""Returns data of a track having `track_id`
No request params.
"""
try:
track = g.user.get_track( track_id )
data = {
'title' : track.title,
'path' : track.path,
'artist' : track.artist,
... | 1def539d9065c562b61cb520848ec36ae4b120c3 | 48,703 |
def _is_rule_exists(nat_rules, rule_type,
original_ip, original_port,
translated_ip, translated_port, protocol):
"""
check if we already have some rule with same properties
"""
# gatewayNatRule properties may be None or string
# convert to str, bacause por... | c6ad5920b789e18d357941d71dd9e08922aa26a0 | 48,704 |
def lsgan_loss_generator(prob_fake_is_real):
"""Computes the LS-GAN loss as minimized by the generator.
Rather than compute the negative loglikelihood, a least-squares loss is
used to optimize the discriminators as per Equation 2 in:
Least Squares Generative Adversarial Networks
Xudong Mao,... | a524108b8486111e475ad56fa4e910bb9283592c | 48,705 |
from collections import defaultdict
def split_by_x(points):
"""Partitions an array of points into two by x-coordinate. All points with
the same x-coordinate should remain on the same side of the partition. All
points in the right partition should have strictly greater x-coordinates
than all points in ... | ff41bec793544a59791912c1d97b09ccb175e77e | 48,706 |
import json
def dumps(*args, **kwargs):
"""
See :func:`json.dumps()`.
"""
kwargs["ensure_ascii"] = True
kwargs["cls"] = _ExtendedJsonEncoder
return json.dumps(*args, **kwargs) | c3e06e4f06bf39b01fcde74a4924d6edc97035f4 | 48,707 |
def remove_quoted_text(line):
"""get rid of content inside quotes
and also removes the quotes from the input string"""
while line.count("\"") % 2 == 0 and line.count("\"") > 0:
first = line.find("\"")
second = line.find("\"", first+1)
line = line[0:first] + line[second+1:]
while ... | ef0776ddfd9d60474077fd106474728de10b9e8f | 48,708 |
def ryu_from_jsondict(jsondict):
""" Load a ryu object from a json dictionary
jsondict: A dictionary loaded by json.load
"""
assert len(jsondict) == 1
for oftype, value in jsondict.items():
cls = getattr(parser, oftype)
if issubclass(cls, parser.OFPFlowMod):
value["d... | c9db51a0b026749b118eeb09bccc237a874f70f3 | 48,709 |
def conv_block(
inp,
cweight,
bweight,
reuse,
scope,
use_stride=True,
activation=tf.nn.leaky_relu,
pn=False,
bn=False,
gn=False,
ln=False,
scale=None,
bias=None,
class_bias=None,
use_bias=False,
... | 3699166a4c626c7520b7fa372a27735f19672949 | 48,710 |
from typing import Tuple
import numpy
def qa_statistics(raster, mask, blocks, confidence=None) -> Tuple[float, float]:
"""Retrieve raster statistics efficacy and not clear ratio, based in Fmask values.
Notes:
Values 0 and 1 are considered `clear data`.
Values 2 and 4 are considered as `not cl... | cc45c084a9860414d66de893cf27387b4c55c7b7 | 48,711 |
from varappx.main.view_tools import authenticate as auth
def user_activation(email_to_file=None, rank_required=ADMIN_LEVEL):
"""Activate a user's account"""
# logger.info("Activate/deactivate user")
if auto_process_OPTIONS(request):
return auto_process_OPTIONS(request)
username = request.form[... | 03e688c10a618096d2e13d217cc1674cd75489f1 | 48,712 |
import re
def remove_emoji_and_non_alphanumeric(word_list):
"""
Remove both emojis and non-alphanumeric tokens in the given word list
parameters
-----------
:param word_list: list of str
:return: list of str
"""
filtered_list = [word for word in word_list if word not in emoji.UNICODE_... | d187a7ac23fde91cdbb5ce931050c4a5562a8564 | 48,713 |
import os
import logging
import json
def _GetJsonFileCreator(name, json_object):
"""Creates a creator function for an extended source context file.
Args:
name: (String) The name of the file to generate.
json_object: Any object compatible with json.dump.
Returns:
(callable()) A creator function that... | db74748d51303087fae6aec5b6b6f6deb7d665c0 | 48,714 |
def active_matrix_from_extrinsic_euler_zyx(e):
"""Compute active rotation matrix from extrinsic zyx Cardan angles.
Parameters
----------
e : array-like, shape (3,)
Angles for rotation around z-, y-, and x-axes (extrinsic rotations)
Returns
-------
R : array-like, shape (3, 3)
... | e4660706b7e2b651a2f3c02d6f9620ea4095becb | 48,715 |
def get_index_of_feature(feature_list, item):
"""
Gets the index of the feature in the provided feature list
:rtype : int
:param feature_list: List of features to search from
:param item: The feature to search
:return: The index where the feature was founded, -1 otherwise
"""
# getting... | 2f2d79d4caf953b60ecf841a23d86e8b4a00b937 | 48,716 |
import logging
import pytz
def get_timezone(WindowsZoneName=True):
"""
Get the TimeZone Name
if WindowsZoneName is True, then it returns the name used by the Microsoft Windows Platform
otherwise it returns the Olsen name (used by all other platforms)
Note: this needs to get tested on Windows
... | e175aae37bc544d8ecd51ad7cafafbc88b5862f7 | 48,717 |
def fix_ghdx_birth_weights(df):
"""Ensure the child birth weight is in grams and is a legal value.
The original survey allowed answers to weights to be coded in grams or
kilograms. The GHDx data has recoded the values into grams. However, a
few cases are clearly still coded in kilograms. The survey als... | a11e50a1a1db780389ad99051e7cf93a025155ae | 48,718 |
def __virtual__():
"""
Only load if boto is available.
"""
if "boto3_elasticache.cache_cluster_exists" in __salt__:
return "boto3_elasticache"
return (False, "boto3_elasticcache module could not be loaded") | d844dc256eaf81e5a368afd14ac7169969a4bab6 | 48,719 |
def parse_adjlist(lines, comments='#', delimiter=None,
create_using=None, nodetype=None):
"""Parse lines of a graph adjacency list representation.
Parameters
----------
lines : list or iterator of strings
Input data in adjlist format
create_using: NetworkX graph container... | b395366c1f5ae8a048b80f8d78de33e1dc234966 | 48,720 |
def get_slovakia():
"""
gets all the data for Slovakia
:return: object
"""
slovakia = Country('Slovak Republic')
slovakia.get_gdp('https://www.quandl.com/api/v3/datasets/WWDI/SVK_'
'NY_GDP_PCAP_CD.json?api_key=2jhCWecEKmuxzVY9ifwp')
slovakia.get_investment_inflows('https... | 98c6febb03c088e0f614e60573898aa680169297 | 48,721 |
from scipy.optimize import linear_sum_assignment as linear_assignment
def cluster_acc(y_true, y_pred):
"""
Calculate clustering accuracy. Require scikit-learn installed
# Arguments
y: true labels, numpy.array with shape `(n_samples,)`
y_pred: predicted labels, numpy.array with shape `(n_sa... | de82c781709b6c147177f54ab7363edf7365ad85 | 48,722 |
def calc_rms_df(df, measured_tox_col, modeled_tox_col):
"""
Calculate the root mean square deviation for two columns of a DataFrame
returns √[ ∑(x-y)² / n ]
"""
df_rms = df[[measured_tox_col, modeled_tox_col]].dropna()
toxobs = df_rms[measured_tox_col].tolist()
toxmod = df_rms[modeled_tox_co... | 9160881aa3ce08164aae1613eddf282ba1b43375 | 48,723 |
def dist(p1, p2):
"""
Distance between two points represented by arrays.
"""
return distance(p1[0], p1[1], p2[0], p2[1]) | 52f1a59c6aa125adcde80398712c30d7d61f2164 | 48,724 |
def trim_motif(pfm, motif, min_ic=0.2, pad=0):
"""
Given the PFM and motif (both L x 4 arrays) (the motif could be the
PFM itself), trims `motif` by cutting off flanks of low information
content in `pfm`. `min_ic` is the minimum required information
content. If specified this trimmed motif will be e... | ee8207336ff01c32f3e22bb6ea2bc1a2e53b4c1c | 48,725 |
def org_search():
"""
Organisation REST controller
- limited to just search.json for use in Autocompletes
- allows differential access permissions
"""
s3.prep = lambda r: r.representation == "json" and \
r.method == "search"
return s3_rest_controller(modu... | 6e74da5fbcaf8d48c4d39105a7d73d65e51b1419 | 48,726 |
def in_quiet_hours() -> bool:
"""Check whether the current time is within quiet hours.
Returns:
bool: True if within quiet hours
Raises:
AttributeError: if quiet hours weren't defined in config
"""
now = pendulum.now()
hour = now.hour
if config.QUIET_START > config.QUIET_E... | 782ccf47b045f8ff23a63dd81f81f89b0a11a5cf | 48,727 |
def int_to_smile(list_of_int):
"""
Convert the list of int to list of token according to the vocabulary
:param list_of_int: list of int representing the SMILES
:type list_of_int: list of int
:return: list of token
"""
return [p.tokens[s] for s in list_of_int] | 28475b1357e0de3304823840cc81482bf789b2f4 | 48,728 |
def searchLibary(keyword):
"""
Keyword based search for books, case insensitive in author and title
Args:
keyword (string): Keyword to search for
Return:
List of search results
"""
results = []
lk = keyword.lower()
for bookid, book in library.LIBRARY.items():
... | 1bef76e977983ed13898a6f0ab4ffb80729e36a7 | 48,729 |
def emprestarLivro(livro):
""" Emprestimo do livro
"""
return biblioteca_temp.emprestarLivro(livro) | 835a6621e0fd1ccd52e03cd21a228d7a6c2068fb | 48,730 |
from typing import Any
from operator import lt
def _heapify(items: list[Any], d: int, comp=lt) -> list[Any]:
"""Создать на месте кучу из списка за время O(log(len(items))).
:param items: список элементов
:param d: коэффициент ветвления (максимальное число потомков у одного элемента)
:param comp: функ... | 5c32093dc3beddaceea76e4e9c36839f31610f95 | 48,731 |
def build_generator_growth_layer_block(conv_layers, params, block_idx):
"""Builds generator growth block internals through call.
Args:
conv_layers: list, the current growth block's conv layers.
params: dict, user passed parameters.
block_idx: int, the current growth block's index.
... | 192701b6282ac8bd53b40b71b54e647e8aa9ec81 | 48,732 |
def isfloat(s):
"""**Returns**: True if s is the string representation of a number
:param s: the candidate string to test
**Precondition**: s is a string
"""
try:
x = float(s)
return True
except:
return False | 6967444007388793a70b9bd74d3153d6f88b6a4d | 48,733 |
import random
import string
def generate_password(length=10):
"""Generate rnadom password of the given length.
"""
return ''.join(
random.SystemRandom().choice(
string.ascii_lowercase + string.ascii_uppercase + string.digits
)
for _ in range(length)
) | e4d65ea76bee72c68afbfbcc011676e9ae35c588 | 48,734 |
import numpy
def reference_transit(samples, per, rp, a, inc, ecc, w, u, limb_dark):
"""Returns an Earth-like transit of width 1 and depth 1"""
f = numpy.ones(tls_constants.SUPERSAMPLE_SIZE)
duration = 1 # transit duration in days. Increase for exotic cases
t = numpy.linspace(-duration * 0.5, duratio... | 716ac7ecda59a608389d03c2a091434ebdef2bcf | 48,735 |
import math
def sol_rad_from_t(et_radiation, cs_radiation, temperature_min, temperature_max, coastal):
"""
Estimate incoming solar (or shortwave) radiation, *Rs*, (radiation hitting
a horizontal plane after scattering by the atmosphere) from min and max
temperature together with an empirical adjustmen... | 6952aa6509897494551839e412d5a15e51b5e30c | 48,736 |
def moving_avg(v, N):
"""
simple moving average.
Parameters
----------
v : list
data ta to average
N : integer
number of samples per average.
Returns
-------
m_avg : list
averaged data.
"""
s, m_avg = [0], []
for i, x in enumerate(v, 1):
... | 2e71eefb91ac694eaf06c2167e38ef497671145e | 48,737 |
def solve():
"""This method will compute and return the solution if it exists, as a list of (row, column) tuples, zero-based.
Else, an exception will be raised stating a loop was detected and that no solution exists."""
robot = Robot(number_of_rows, number_of_columns, ball_location, goal_location, block... | c24be000f6004ba6d3295b56f85b0a5921eb83c0 | 48,738 |
def hashed_password(username: str, password: str) -> str:
"""
ハッシュ化したパスワードを返す。
"""
tmp = adcconfig.SALT + username + password
return sha256(tmp.encode('utf-8')).hexdigest() | c91fff9edaf1a6dd487a4d912b77aaa27c5f197f | 48,739 |
def linierRegression(features, weights):
"""
Performs simple linier regression
"""
return np.dot(features, weights) | 24791550134b5f1efa102b956fa44be81053b001 | 48,740 |
from typing import List
def get_students(tas: List[str], gr:str)->List[str]:
""" From the list of all TAs, find TAs matching the constraint string
For example, gr could be "cs17|es18" this represents all the students
whole roll numbers start from cs17 or es18
This function returns the list of TAs fr... | b952fa3688b3ff107a5a1289fc3216244f4f0554 | 48,741 |
def calculate_prototypes_from_labels(embedding,
labels,
max_label=None):
"""Calculates prototypes from labels.
This function calculates prototypes (mean direction) from embedding features
for each label. This function is also used as the m... | d085117b45ec236d36528cafeb352030d5fce858 | 48,742 |
def get_mask(pos, shape, radius, include_edge=True, return_masks=False):
""" Create a binary mask that masks pixels farther than radius to all
given feature positions.
Optionally returns the masks that recover the individual feature pixels from
a masked image, as follows: ``image[mask][masks_single[i]]... | 2e46235cbd32ae5f4ae48fb1c7990d189c0464a9 | 48,743 |
def Volume(v,u,w):
"""Calculate volume of solid created by three vectors.
Returns int
Attributes
----------
v: Vector
First Vector
u: Vector
Second Vector
w: Vector
Third Vector
"""
return abs(DotProduct(CrossProduct(v,u), w)) | be1fc8285fa339820cc71e59390a2a5a92bc9ace | 48,744 |
def is_admin(user_id):
"""
Retrieves a user's admin status from the permissions directory.
"""
perms = get_current_permissions()
return user_id in perms["admins"] | 610528eb3ea18370261aa34aabf9ff05811bc9c0 | 48,745 |
def _get_commits(output):
"""Returns the commits message in the output. All commits must have
been made by `Alice Author` or `PY C` to be found.
"""
commits = []
save = False
cnt = 0
for row in output.split("\n"):
if row.strip() in ["Alice Author", "Alice Äuthòr", "PY C"]:
... | 0514d0c3279c7e14810403412284e6d07eb03d16 | 48,746 |
import platform
import glob
def scan():
"""scan for available ports. return a list of names"""
system_name = platform.system()
if system_name == 'Windows':
available = []
for i in range(200):
try:
s = serial.Serial(i)
available.append(s.portstr)
... | 2737052aa0f69454354d0ecc72e634940799285e | 48,747 |
def valid_value(value, quote=default_cookie_quote, unquote=default_unquote):
"""Validate a cookie value string.
This is generic across quote/unquote functions because it directly verifies
the encoding round-trip using the specified quote/unquote functions.
So if you use different quote/unquote function... | 19d5e46187701d187a81e9f38f35725052fad83d | 48,748 |
import os
def cmdLists(cmd):
"""
creates docker or singularity command(s) from either a
single command or a list of commands.
"""
if os.environ.get('CAT_BINARY_MODE') == 'docker':
if isinstance(cmd[0],list):
docList = []
for e in cmd:
docList.append(... | 46fbe3e9e3cd94efd617651125523411150281b6 | 48,749 |
import struct
def steg(in_path, out_path=None, data=None):
"""
The steg function (use the LSB of the color table entries to hide the data)
"""
# Must encode the length of the data so we know how much to read when extracting
if data is not None:
data_array = bytearray(data)
data_ar... | 1464dadec850816d20de9c13b5297b4c49fda59a | 48,750 |
def _make_specific_identifier(param_name, identifier):
# type: (str, str) -> str
"""
Only adds an underscore between the parameters.
"""
return "{}_{}".format(param_name, identifier) | 5268d366f04c616d8180e7cc4167030efdec9070 | 48,751 |
import torch
def resnet50(pretrained=False, pretrained_model_path=None, num_classes=None, expose_stages=None, dilations=None, stride_in_1x1=False):
"""Constructs a ResNet-50 model
Args:
pretrained (bool): if True, load pretrained model. Default: False
pretrained_model_path (str, optional): onl... | 634c3e0a2446fe1b470e0eba311d71cda6bb7cae | 48,752 |
def ReadTag(buffer, pos):
"""Read a tag from the buffer, and return a (tag_bytes, new_pos) tuple.
We return the raw bytes of the tag rather than decoding them. The raw
bytes can then be used to look up the proper decoder. This effectively allows
us to trade some work that would be done in pure-python (decodi... | 91c0a1e86816066768b15a3a2e7b8a8468900661 | 48,753 |
def emptyStack():
""" Empties the stack while collecting each element as it is removed.
Returns the collected elements. """
elements = ""
while not stack.isEmpty():
if isOperator(stack.peek()):
elements += stack.pop()
elif stack.peek() == '(':
raise ParensMism... | 72be5b7c6752093c8a30063d36f0bfa70bc5fb8d | 48,754 |
from typing import Union
import re
def get_brackets(title: str) -> Union[str, None]:
"""
Return the substring of the first instance of bracketed text.
"""
regex_brackets = re.search(r"\[(.*?)\]", title)
if regex_brackets is None:
return None
else:
return regex_brackets.group() | f1d985cf79ae881e8aca168c065d40e640a9c1ff | 48,755 |
def stack_3rd_dimension_along_axis(u_jkir, axis):
"""
Take the 3D input matrix, slice it along the 3rd axis and stack the resulting 2D matrices
along the selected matrix while maintaining the correct order.
:param u_jkir: 3D array of the shape [JK, I, R]
:param axis: 0 or 1
:... | db9e126503beb99b43032bea7df7ffb9cc432a07 | 48,756 |
from typing import Union
from typing import List
def _op_nodes(
graph: Union[tf.Graph, testutils.GraphDef]) -> List[testutils.NodeDef]:
"""Return arithmetic/nn operation nodes from a graph"""
graph_def = graph.as_graph_def() if isinstance(graph, tf.Graph) else graph
def _op(node): return node.op n... | 7e2d854a5bbdb3e2401d3df8ed8fbaa9f564acac | 48,757 |
def _compositeImageToVideoSegment(compositeImage):
"""
:param compositeImage:
:return:
@type compositeImage: CompositeImage
"""
if compositeImage is None or compositeImage.videomasks is None:
return []
return [segmentToVideoSegment(item) for item in compositeImage.videomasks] | b730e0f3152a512cb200436c4732abaed3c147e3 | 48,758 |
from bids import BIDSLayout
import warnings
def collect_sessions(bids_dir, session=None, strict=False, bids_validate=True):
"""
List the sessions under the BIDS root and checks that sessions
designated with the participant_label argument exist in that folder.
Returns the list of sessions to be finally... | 6c905038d5eca24c57197d574d1efb8c4ccf0a66 | 48,759 |
def _dof(mean_tau, sd_tau2):
"""
Returns the degrees of freedom for the chi-2 distribution from the mean and
variance of the uncertainty model, as reported in equation 5.5 of Al Atik
(2015)
"""
return (2.0 * mean_tau ** 4.) / (sd_tau2 ** 2.) | 9a4a395c9aea7b965a477550c7f254bf744cadc5 | 48,760 |
def stations():
"""Return a list of stations."""
print("Received Station API Request.")
# Query the station list
station_data = session.query(Station).all()
# Create a list of dictionaries
station_list = []
for station in station_data:
station_dict = {}
station_dict["id"] ... | 67ffb7a8691ea4f44420b0f0f0b4d4c4a2ecd3ba | 48,761 |
from typing import Iterable
import yaml
def yaml_load(string):
"""Parse multiple strings as yaml data. Multiple dictionaries are combined togather."""
if isinstance(string, str):
return ordered_load(string)
if not isinstance(string, Iterable):
raise TypeError('Invalid yaml_load argument t... | 3310aa780d774d325cabbbf353d45062a1c243a5 | 48,762 |
import requests
def get_checklist(identifier):
"""
Get the data for a checklist from its eBird web page.
Args:
identifier (str): the unique identifier for the checklist, e.g. S62633426
Returns:
(dict): all the fields extracted from the web page.
ToDo:
* scrape entry comm... | 87599c88523c303b29f34b3495576ef1e2523f3e | 48,763 |
def check_tensors_dtype_same(data_dtype, value_dtype, op_name):
"""Check tensors data type same."""
if data_dtype in value_dtype:
return True
raise TypeError(f"For '{op_name}', the value data type '{value_dtype}' "
f"is not consistent with assigned tensor data type {data_dtype}."... | f31e34dea4ccb83938319db82a7a679876505a75 | 48,764 |
import tqdm
def generate_data(data_dirs, save_dir):
"""
Routine for generating train data in tfrecords
Args:
data_dirs: where simulation data is.
save_dir: where tfrecords will go.
Returns: list of tfrecords.
"""
def data_generator():
def _get_data(dir):
... | 9a67f3219e32787016e726e4da6d1025b80fac3b | 48,765 |
def to_categories(df, cat_map):
""" Convert a dataframe to use categories, based on the category map created by table_category_map.
:param df: CHIS Dataframe to convert, loaded from Metatab
:param cat_map: category map, from table_category_map
:return:
"""
df = df.copy()
for col in df.c... | 66fb82fdc9d0d91e063e08a912673ab6acf0ef17 | 48,766 |
import sys
def hastty():
""" Whether (it looks like) a tty is available.
"""
try:
return sys.stdin and sys.stdin.isatty()
except Exception: # pragma: no cover
return False | 2baebe972f0c58f58d90cab133e4e5d774b2cb25 | 48,767 |
def xgcd(vals):
"""Calculate extended greatest commond divisor."""
_xgcd = Xgcd(vals)
return _xgcd.run() | cf4956bec4141780b1a6c3eedd311a4e727df4ae | 48,768 |
import os
def _get_i18n_locale(locale_name, react=False):
"""Retrieve a locale in a Jed-compatible format."""
# Ensure we have a valid locale. en_GB is our source locale and thus always considered
# valid, even if it doesn't exist (dev setup where the user did not compile any locales)
# since otherwi... | 1b8f496a39df735821b771f1f060ed7324414dbe | 48,769 |
def find_bad_frames(ds, reindex=True):
"""
Find the frames that have fewer cells than the previous frame.
Parameters
----------
ds : (S, T, ..., Y, X) DataSet
reindex : bool, default: True
Whether to reindex each frame as well.
Returns
-------
bad : list
With entrie... | 78ae0ff38834bf0bc29571e68b7cd1497e652fe9 | 48,770 |
import aiohttp
import os
async def get_steam_game_search(keyword: str) -> list:
"""
Return search result
Args:
keyword: Keyword to search(game name)
Examples:
get_steam_game_search("Monster Hunter")
Return:
[
str,
MessageChain
]
"""
... | 3bc2ecb8d9ee121eb4006a8be615061d4417c4fa | 48,771 |
def get_most_energetic_neutrino(particles):
"""Get most energetic neutrino.
Parameters
----------
particles : ndarray of dtype I3PARTICLE_T
Returns
-------
most_energetic_neutrino : shape () ndarray of dtype I3PARTICLE_T
"""
return get_best_filter(
particles=particles, fil... | 54add5340ba911a2e836b1386fd4ca6b5f72e9c8 | 48,772 |
def cria_coordenada(linha,coluna):
"""int x int -> tuple
Esta funcao recebe duas coordenadas do tipo inteiro, a primeira correspondente a linha e a segunda a coluna e devolve um elemento do tipo coordenada, ou seja, o tuplo (linha,coluna)"""
if 1<=linha<=4 and 1<=coluna<=4 and isinstance(linha,int) and isin... | b2d216a11706e4234cf9943525cfca72118a98f8 | 48,773 |
def identify_groups(ref_labels, pred_labels, return_overlaps=False):
"""Which predicted label explains which reference label?
A predicted label explains the reference label which maximizes the minimum
of ``relative_overlaps_pred`` and ``relative_overlaps_ref``.
Compare this with ``compute_association_... | b7c6588946c005c6507b5f486930514dd6b91864 | 48,774 |
def commit_config(node, raid_controller, reboot=False, realtime=False):
"""Apply all pending changes on a RAID controller.
:param node: an ironic node object.
:param raid_controller: id of the RAID controller.
:param reboot: indicates whether a reboot job should be automatically
crea... | eead48d5a8eeb6591343d598e6c232ad7bb437f5 | 48,775 |
from typing import Tuple
from typing import Optional
def link(g: Graph, subject: Node, predicate: URIRef) -> Tuple[Optional[URIRef], Optional[URIRef]]:
"""
Return the link URI and link type for subject and predicate
:param g: graph context
:param subject: subject of linke
:param predicate: link pr... | 3a329697413ebe0d6218d388d74306643590f3e3 | 48,776 |
def list_pages(page_obj: Page) -> Page:
"""
Gets a paginator page item and returns it with a list of pages to display like:
[1, 2, "…", 17, 18, 19, "…" 41, 42]
Currently not in use, simpler pages lists are implemented.
"""
last_page_number = page_obj.paginator.num_pages
pages_list = [1, 2]
... | 40b225f45fe4868c7b3ef361a7cc9df432efaf78 | 48,777 |
from typing import List
import json
def compare_apache_profiles(baseline_file, test_file, threshold=0.5) -> List:
"""
Compare baseline Apache access log profile against test profile.
:param baseline_file: file containing baseline profile
:param test_file: file containing test profile
:param thresh... | 0b94ad318fcb61be559767cbdba51def1b6db61f | 48,778 |
import os
import math
import subprocess
import re
async def ping(target: str, count: int = 3, timeout: int = 1000, interval: float = 1.0):
"""
PING 目标网络, 获取延迟丢包 (备用)
调用 Windows/Linux 系统 PING 命令, 支持 IPv6
:param target: 目标地址
:param count: 发送的回显请求数
:param timeout: 超时时间, Windows 有效
:param int... | f1c3d8e136613972efc94e365c1503dad76fa0b5 | 48,779 |
def cyclic_sort(nums):
"""
0 1 2 3 4 5
[1, 2, 3, 4, 5]
^
[1, 2, 3, 4, 5, 6]
^
"""
for i in range(0, len(nums)):
while nums[i] != i + 1:
j = nums[i] - 1
nums[i], nums[j] = nums[j], nums[i]
return nums | fc9f7061121d4509b260e03df4edeee63c0eb6b9 | 48,780 |
def _build_section_path_map():
"""
Simple wrapper around Django's low level cache; stores and populates
a list of all section urls using the low-level caching framework.
"""
paths = {}
Section = app_settings.get_extending_model()
for section in Section.objects.all():
paths[section.f... | e89657ec68e4c1dab31f172e4d5aa8f98681aa5e | 48,781 |
def unfold_arrow(arrow):
"""Extract a list of types from an arrow type
:param arrow: A type, preferably an arrow type
:type arrow: :class:`discopy.closed.Ty`
:return: A list of the arrow's components, or of the original type
:rtype: list
"""
if isinstance(arrow, Under):
return [arr... | 365a35e87bdb0edcd81cba8e44c4151cf5cb701c | 48,782 |
def test_step(X, m_pre, m_fp):
""" Test step used for mini-search-validation """
X = tf.concat(X, axis=0)
feat = m_pre(X) # (nA+nP, F, T, 1)
m_fp.trainable = False
emb_f = m_fp.front_conv(feat) # (BSZ, Dim)
emb_f_postL2 = tf.math.l2_normalize(emb_f, axis=1)
emb_gf = m_fp.div_enc(emb_f)
... | c444a0935640f09122999efa3c382be15daab833 | 48,783 |
import json
def calc_sett_rewards(badger, periodStartBlock, endBlock, cycle, unclaimedRewards):
"""
Calculate rewards for each sett, and sum them
"""
# ratio = digg_btc_twap(periodStartBlock,endBlock)
# diggAllocation = calculate_digg_allocation(ratio)
rewardsBySett = {}
noRewards = ["nati... | 7fa93585fbe5b1f461b24dc6a9a7d655aca4f7a7 | 48,784 |
def get_detector_module_slices(detector):
"""
Helper function to read data_origin and data_size from the NXdetector_modules in a
NXdetector. Returns a list of lists, where each sublist is a list of slices in
slow to fast order.
Assumes slices are stored in NeXus in slow to fast order.
"""
#... | a23e797579c0925b48b802e0189ce17d3f5bf12c | 48,785 |
def main(**prepared_args):
"""
main conversion runner
:param prepared_args kwargs:
:return:
"""
conversion_result = None
if prepared_args['conversion_type'] == 'csv_to_parquet':
conversion_result = converter_csv_to_parquet(prepared_args['source_file_path'],
... | 6c79bbd453e1b229329b0bb91e8b0b81e0b7d4a2 | 48,786 |
import json
import sys
def _format_json(data, theme):
"""Pretty print a dict as a JSON, with colors if pygments is present."""
output = json.dumps(data, indent=2, sort_keys=True)
if pygments and sys.stdout.isatty():
style = get_style_by_name(theme)
formatter = Terminal256Formatter(style=s... | e062338e4843cad1281b61ab92e36fe55328ab09 | 48,787 |
def get_tm_session(session_factory: sessionmaker, transaction_manager: TransactionManager) -> Session:
"""
Get a ``sqlalchemy.orm.Session`` instance backed by a transaction.
This function will hook the session to the transaction manager which
will take care of committing any changes.
- When using ... | 80ae17addd6f519d55234c11707b3e0311329e22 | 48,788 |
import tarfile
import logging
def get_test_from_anaconda(url):
"""
Given the URL of an anaconda tarball, return tests
"""
try:
tarball = get_file_from_recipe_url(url)
except tarfile.ReadError:
return None
try:
metafile = tarball.extractfile('info/recipe/meta.yaml')
... | f9ad72251a450d7c24e7eedd84cd89bf670a6b6b | 48,789 |
import numpy
def calculate_reservoir_rate(var, surf_mask, surf_type=None):
"""Inputs are two maps (var and surf_mask). Whereas there may be scripts that
calculate the masked means, this calculates the volume flow rate (ie, not the
flux density, but the total flux. This is currently written to only ... | 41c89b6fbdfd7a3234ec7f555e3c7c48d8181641 | 48,790 |
def get_schedules(filter_params, dbinfo=None, fields=None):
"""
Helper function to get schedule data for a request.
:param filter_params: dict mapping constraint keys with values. Valid constraints are
defined in the global ``constraints`` dict.
:param dbinfo: optional. If provided, defines (connec... | 4043cfd9d05321af043ed32ec99524ca92318430 | 48,791 |
async def get_forge_godly_description(message_content: str, message: discord.Message) -> str:
"""Returns the embed description for the forge_godly event"""
user_name_string = 'exhausted'
user_name_start = message_content.find(user_name_string) + len(user_name_string) + 1
user_name_end = message_content.... | 2b12ff6c5b9ecbcce83b19cf3bde017cde0b9fee | 48,792 |
from userbot.modules.sql_helper.spam_mute_sql import unmute
async def unmoot(unmot):
""" For .unmute command, unmute the replied/tagged person """
# Admin or creator check
chat = await unmot.get_chat()
admin = chat.admin_rights
creator = chat.creator
# If not admin and not creator, return
... | 523b60270ccb26ed1c148e068c2ec8f84968addd | 48,793 |
def objective_value(x, w):
"""Compute the value of a cut.
Args:
x (numpy.ndarray): binary string as numpy array.
w (numpy.ndarray): adjacency matrix.
Returns:
float: value of the cut
"""
X = np.outer(x, (1-x))
w_01 = np.where(w != 0, 1, 0)
return np.sum(w_01 * X) | ed6963759cd8f9a77bc5fdfd42018fc32b8c0994 | 48,794 |
def setEncoding(encoding = None):
""" 라이브러리용 엔코딩 설정 함수
기본 엔코딩 정보를 설정한다
인자값 목록 (모든 변수가 반드시 필요):
encoding : 문자열 엔코딩 정보
결과값 : 현재 설정된 기본 엔코딩 정보
"""
global _default_encoding
try:
str("dummy", encoding)
except:
return _default_encoding
_default_encoding = encoding or _default_encoding
return _defau... | a1b0cbe83d5d08ad16274dafa4f0c4965aa938a1 | 48,795 |
def _create_v2_request_with_keyranges(
sql, new_binds, keyspace_name, tablet_type, keyranges, not_in_transaction):
"""Make a request dict from arguments.
Args:
sql: Str sql with format tokens.
new_binds: Dict of bind variables.
keyspace_name: Str keyspace name.
tablet_type: Str tablet_type.
... | af3f539fee6646a3d97bd531f57f9203eb6dee91 | 48,796 |
def generate_meme(image_path, meme_text):
"""
Generate meme with image and text
"""
pic = Image.open(image_path).convert("RGBA")
pic = pic.resize((600, 300), Image.LANCZOS)
background = Image.new("RGBA", (900, 700), "white")
Image.Image.paste(background, pic, (150, 200))
draw = ImageDr... | 873468f16813a9e35af87523cf6f9578dd57c434 | 48,797 |
def shuffle(images, labels):
"""
Return shuffled data.
"""
permutation = np.random.permutation(images.shape[0])
return images[permutation], labels[permutation] | 56b5fabd93b21f875976b236843e40a4a3136577 | 48,798 |
import math
def Linear(input_size, hidden_size, with_bias=True):
"""tbd"""
fan_in = input_size
bias_bound = 1.0 / math.sqrt(fan_in)
fc_bias_attr = paddle.ParamAttr(initializer=nn.initializer.Uniform(
low=-bias_bound, high=bias_bound))
negative_slope = math.sqrt(5)
gain = math.sqrt(2.0 / (1 +... | e5f387dcdabc174717f6e431ce7d4afb4a7e305d | 48,799 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.