content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def irrf(valor=0):
"""
-> Função para cálcular o valor do IRRF.
:param valor: Valor base do salário para cálculo do IRRF.
:return: Retorna o valor do IRRF e alíquota utilizada.
"""
irrf = []
if valor < 1903.99:
irrf.append(0)
irrf.append(0)
elif va... | 53646b770b2c2359e1e8c4f725b27396cc972050 | 3,655,700 |
def find_adcp_files_within_period(working_directory,max_gap=20.0,max_group_size=6):
"""
Sorts a directory of ADCPRdiWorkHorseData raw files into groups by
closeness in time, with groups being separated by more than
'max_gap_minutes'. This method first sorts the files by start time, and
then spli... | 6e3afc4dd8532c579870541fe42519078e86f935 | 3,655,701 |
def regular_transport_factory(host, port, env, config_file):
"""
Basic unencrypted Thrift transport factory function.
Returns instantiated Thrift transport for use with cql.Connection.
Params:
* host .........: hostname of Cassandra node.
* port .........: port number to connect to.
* env .... | bccee131d61a9a251a63ee021e0ab0c5b6033c44 | 3,655,702 |
def smoothed_abs(x, eps=1e-8):
"""A smoothed version of |x| with improved numerical stability."""
return jnp.sqrt(jnp.multiply(x, x) + eps) | f0b63e9482e602b29b85ce3f0d602d9918557ada | 3,655,703 |
def increment(t1, seconds):
"""Adds seconds to a Time object."""
assert valid_time(t1)
seconds += time_to_int(t1)
return int_to_time(seconds) | f7807fc12a9ed9350d13d0f8c4c707c79165e9d5 | 3,655,704 |
import os
def add_absname(file):
"""Prefix a file name with the working directory."""
work_dir = os.path.dirname(__file__)
return os.path.join(work_dir, file) | 34d78ff980cbe16ace897cf164563badc9d36d2a | 3,655,705 |
def dense(input_shape, output_shape, output_activation='linear', name=None):
"""
Build a simple Dense model
Parameters
----------
input_shape: shape
Input shape
output_shape: int
Number of actions (Discrete only so far)
Returns
-------
model: Mode... | 6f7ba28834ecfe7b5e74aa40ef30fcd9aa531836 | 3,655,706 |
def dataset_labels(alldata, tag=None):
""" Return label for axis of dataset
Args:
ds (DataSet): dataset
tag (str): can be 'x', 'y' or 'z'
"""
if tag == 'x':
d = alldata.default_parameter_array()
return d.set_arrays[0].label
if tag == 'y':
d = alldata.default_... | 4ccd3af38d3f18e9fbf43e98f8a898426c6c1440 | 3,655,707 |
from typing import Optional
from typing import Any
from typing import Callable
from typing import Tuple
from typing import List
from typing import Union
def spread(
template: Template,
data: Optional[Any],
flavor: Flavor,
postprocess: Optional[Callable] = None,
start_at: int = 0,
replace_missi... | db354b3d190f1bff5b78c29a3ff6b4021287b27f | 3,655,708 |
from sklearn.model_selection import train_test_split
def train_validate_test_split(DataFrame, ratios=(0.6,0.2,0.2)):
"""
Parameters
----------
DataFrame : pandas.DataFrame
DataFrame
ratios : tuple
E.g.
(train, validate, test) = (0.6, 0.25, 0.15)
(trai... | 3d4b8424f66e72d3dd28328afb6465768b1778cb | 3,655,709 |
from typing import Union
def is_error(code: Union[Error, int]) -> bool:
"""Returns True, if error is a (fatal) error, not just a warning."""
if isinstance(code, Error): code = code.code
return code >= ERROR | 347bde61feb36ce70bf879d713ff9feb41e67085 | 3,655,710 |
def unpack_triple(item):
"""Extracts the indices and values from an object.
The argument item can either be an instance of SparseTriple or a
sequence of length three.
Example usage:
>>> st = SparseTriple()
>>> ind1, ind2, val = unpack_triple(st)
>>> quad_expr = [[], [], []]
>>> ind1, ... | bae536d313140952927875640f925876700bf981 | 3,655,711 |
def max_sequence(arr):
"""
The maximum sum subarray problem consists in finding the maximum sum of a contiguous subsequence in an array or
list of integers.
:param arr: an array or list of integers.
:return: the maximum value found within the subarray.
"""
best = 0
for x in range(len(arr... | 3ae6dafb4879476ba6e15610645f26299a4c6719 | 3,655,712 |
def get_by_username(username):
"""
Retrieve a user from the database by their username
:param username:
:return:
"""
return database.get(User, username, field="username") | 354d323c464cbdbaf72b88284b2305657d03a027 | 3,655,713 |
def evalPoint(u, v):
"""
Evaluates the surface point corresponding to normalized parameters (u, v)
"""
a, b, c, d = 0.5, 0.3, 0.5, 0.1
s = TWO_PI * u
t = (TWO_PI * (1 - v)) * 2
r = a + b * cos(1.5 * t)
x = r * cos(t)
y = r * sin(t)
z = c * sin(1.5 * t)
dv = PVector()
d... | a3598739dc28e9fcd47539e4a51b00c351eb4e3d | 3,655,714 |
def decode_funcname2(subprogram_die, address):
""" Get the function name from an PC address"""
for DIE in subprogram_die:
try:
lowpc = DIE.attributes['DW_AT_low_pc'].value
# DWARF v4 in section 2.17 describes how to interpret the
# DW_AT_high_pc attribute based on th... | b322282b9f908311dedbd73ade3d31bbb86cebe8 | 3,655,715 |
def get_reddit_slug(permalink):
"""
Get the reddit slug from a submission permalink, with '_' replaced by '-'
Args:
permalink (str): reddit submission permalink
Returns:
str: the reddit slug for a submission
"""
return list(filter(None, permalink.split("/")))[-1].replace("_", "... | 587239a0b7bbd88e10d49985dd6ebfd3768038d8 | 3,655,716 |
def newton_halley(func, x0, fprime, fprime2, args=(), tol=1.48e-8,
maxiter=50, disp=True):
"""
Find a zero from Halley's method using the jitted version of
Scipy's.
`func`, `fprime`, `fprime2` must be jitted via Numba.
Parameters
----------
func : callable and jitted
... | 96531b47a399ee0d897e5feadaa93eb56bee2b52 | 3,655,717 |
def staff_dash(request):
"""Route for displaying the staff dashboard of the site.
"""
# Empty context to populate:
context = {}
def get_account_name(path):
"""Method contains logic to extract the app name from a url path.
Method uses the django.urls.resolve method with basi... | 83d1d3027b64349dba5560934ba9d7bdb3536c91 | 3,655,718 |
import csv
def read_v1_file(path: str = "CBETHUSD.csv") -> tuple:
"""
Read the data from the file path, reconstruct the format the the data
and return a 3d matrix.
"""
lst = []
res = []
with open(path) as data:
reader = csv.reader(data)
next(reader) # skip the header row
... | 6fd80fda5f327464e63f34df1f16b923349bc7a4 | 3,655,719 |
import torch
def get_adjacent_th(spec: torch.Tensor, filter_length: int = 5) -> torch.Tensor:
"""Zero-pad and unfold stft, i.e.,
add zeros to the beginning so that, using the multi-frame signal model,
there will be as many output frames as input frames.
Args:
spec (torch.Tensor): input spect... | 4009b41fd4e729e16c749f4893f61b61ca922215 | 3,655,720 |
def K2(eps):
""" Radar dielectric factor |K|**2
Parameters
----------
eps : complex
nd array of complex relative dielectric constants
Returns
-------
nd - float
Radar dielectric factor |K|**2 real
"""
K_complex = (eps-1.0)/(eps+2.0)
return (K_complex*K_complex.... | 8754bee38a46de14d205764c4843cad7c4d5d88f | 3,655,721 |
def permutation_test_mi(x, y, B=100, random_state=None, **kwargs):
"""Permutation test for mutual information
Parameters
----------
x : 1d array-like
Array of n elements
y : 1d array-like
Array of n elements
n_classes : int
Number of classes
B : int
Number... | ea60f7ddf483f3a095971ab3c52a07e34ac863d5 | 3,655,722 |
def convert_time_units(value, value_unit="s", result_unit="s", case_sensitive=True):
"""
Convert `value` from `value_unit` to `result_unit`.
The possible time units are ``'s'``,``'ms'``, ``'us'``, ``'ns'``, ``'ps'``, ``'fs'``, ``'as'``.
If ``case_sensitive==True``, matching units is case sensitive.... | dab3fdb88a5d137d45efe440a6075cd0339194ac | 3,655,723 |
import tqdm
def compute_distribution_clusters(columns: list, dataset_name: str, threshold: float, pool: Pool,
chunk_size: int = None, quantiles: int = 256):
"""
Algorithm 2 of the paper "Automatic Discovery of Attributes in Relational Databases" from M. Zhang et al. [1]. This... | bdbdf233c02f6eced3504543c3adbd8ea12505f7 | 3,655,724 |
def get_eventframe_sequence(event_deque, is_x_first, is_x_flipped,
is_y_flipped, shape, data_format, frame_width,
frame_gen_method):
"""
Given a single sequence of x-y-ts events, generate a sequence of binary
event frames.
"""
inp = []
wh... | 9d65bfa59c42b327cc7f5c02a044f545ec5f5a5e | 3,655,725 |
def creation_sequence_to_weights(creation_sequence):
"""
Returns a list of node weights which create the threshold
graph designated by the creation sequence. The weights
are scaled so that the threshold is 1.0. The order of the
nodes is the same as that in the creation sequence.
"""
# Turn... | 80147c53ccb7f44fdca148cc422a0c149a5b7864 | 3,655,726 |
def get_seg_features(string):
"""
Segment text with jieba
features are represented in bies format
s donates single word
"""
seg_feature = []
for word in jieba.cut(string):
if len(word) == 1:
seg_feature.append(0)
else:
tmp = [2] * len(word)
... | 505ba3064cacc2719e11126ce504b8c84abe10e9 | 3,655,727 |
def print_device_info(nodemap):
"""
This function prints the device information of the camera from the transport
layer; please see NodeMapInfo example for more in-depth comments on printing
device information from the nodemap.
:param nodemap: Transport layer device nodemap.
:type nodemap: ... | 7f0affa8e8acaab48df8dc96c631ca9043f07482 | 3,655,728 |
import sys
def make_withdrawal(account):
"""Withdrawal Dialog."""
# @TODO: Use questionary to capture the withdrawal and set it equal to amount variable. Be sure that amount is a floating
# point number.
amount = questionary.text("How much would you like to withdraw").ask()
amount = float(amoun... | c4d9da902da3b6b85950cd6faa1b6e582e0509fe | 3,655,729 |
from typing import Optional
def coerce_to_pendulum_date(x: PotentialDatetimeType,
assume_local: bool = False) -> Optional[Date]:
"""
Converts something to a :class:`pendulum.Date`.
Args:
x: something that may be coercible to a date
assume_local: if ``True``, as... | d2fb5d830736290eb9ddadf9fcd664d0cba88d4b | 3,655,730 |
def loss_fixed_depl_noquench(params, loss_data):
"""
MSE loss function for fitting individual stellar mass histories.
Only main sequence efficiency parameters. Quenching is deactivated.
Depletion time is fixed at tau=0Gyr, i.e. gas conversion is instantaenous.
"""
(
lgt,
dt,
... | c987b17b2a64081006addf8ed9af6a3535b77bdd | 3,655,731 |
def plot_timeseries_comp(date1, value1, date2, value2, fname_list,
labelx='Time [UTC]', labely='Value',
label1='Sensor 1', label2='Sensor 2',
titl='Time Series Comparison', period1=0, period2=0,
ymin=None, ymax=None, dpi... | a33be4ba8fbbaa2c8ee31694a4ede0d43deb171c | 3,655,732 |
def identityMatrix(nrow, ncol):
"""
Create a identity matrix of the given dimensions
Works for square Matrices
Retuns a Matrix Object
"""
if nrow == ncol:
t = []
for i in range(nrow):
t.append([])
for j in range(ncol):
if i == j:
... | 3584c75cd0683f4dd547ac9708d03cdc5500dcef | 3,655,733 |
def extract_packages(matched, package_source):
"""
Extract packages installed in the "Successfully installed" line
e.g.
Successfully installed Abjad Jinja2-2.10 MarkupSafe-1.0 PyPDF2-1.26.0 Pygments-2.2.0 alabaster-0.7.10 \
babel-2.5.1 bleach-2.1.2 decorator-4.1.2 docutils-0.14 entrypoints-0... | a4cf9c18122dd89b2c46647fa328ab72c4d7dd8a | 3,655,734 |
from typing import List
from typing import Optional
from datetime import datetime
def create_relationship(
relationship_type: str,
created_by: Identity,
source: _DomainObject,
target: _DomainObject,
confidence: int,
object_markings: List[MarkingDefinition],
start_time: Optional[datetime] =... | 4d961aae8521c53c61090823484e8b12862b29e0 | 3,655,735 |
def _find_partition(G, starting_cell):
""" Find a partition of the vertices of G into cells of complete graphs
Parameters
----------
G : NetworkX Graph
starting_cell : tuple of vertices in G which form a cell
Returns
-------
List of tuples of vertices of G
Raises
------
Ne... | 92c63176d6c2f366c549a24982dbc64c9879a9b7 | 3,655,736 |
import torch
def projection_from_Rt(rmat, tvec):
"""
Compute the projection matrix from Rotation and translation.
"""
assert len(rmat.shape) >= 2 and rmat.shape[-2:] == (3, 3), rmat.shape
assert len(tvec.shape) >= 2 and tvec.shape[-2:] == (3, 1), tvec.shape
return torch.cat([rmat, tvec], ... | 90039ba7002be31d347b7793d542b1ff37abae3e | 3,655,737 |
def verify_df(df, constraints_path, epsilon=None, type_checking=None,
**kwargs):
"""
Verify that (i.e. check whether) the Pandas DataFrame provided
satisfies the constraints in the JSON .tdda file provided.
Mandatory Inputs:
df A Pandas DataFrame, to be checked.
... | 477180d390e3090ec7d8211b8cee7235d58d4eba | 3,655,738 |
import re
def _getallstages_pm(pmstr):
"""pmstr: a pipelinemodel name in quote
return a df: of all leaf stages of transformer.
to print return in a cell , use print_return(df)
"""
pm=eval(pmstr)
output=[]
for i,s in enumerate(pm.stages):
if str(type(s))=="<class 'pyspark.ml.p... | 8bb5643361aa5aa74c1ba477d725b575a2f15f0b | 3,655,739 |
def merge_config(log_conf: LogConf, conf: Config) -> Config:
"""
Create combined config object from system wide logger setting and current logger config
"""
#pylint: disable=too-many-locals
name = conf.name # take individual conf value, ignore common log_conf value
filename = _ITEM_OR_DEFAULT(... | f62d7a48d83dd201323ff710c17b4ffbf39750bc | 3,655,740 |
def midpVector(x):
""" return midpoint value (=average) in each direction
"""
if type(x) != list:
raise Exception("must be list")
dim = len(x)
#nx = x[0].shape
for i in range(1,dim):
if type(x[i]) != np.ndarray:
raise Exception("must be numpy array")
#if x[i... | 784dcfdeb012aa114167d4b965409ca2f81ed414 | 3,655,741 |
def buy_ticket(email, name, quantity):
"""
Attmempt to buy a ticket in the database
:param owner: the email of the ticket buyer
:param name: the name of the ticket being bought
:param quantity: the quantity of tickets being bought
:return: an error message if there is any, or None if register su... | cd64f745a44180594edce14eb0645f808ac645d8 | 3,655,742 |
from typing import Tuple
def update_bounds(
sig: float,
eps: float,
target_eps: float,
bounds: np.ndarray,
bound_eps: np.ndarray,
consecutive_updates: int
) -> Tuple[np.ndarray, np.ndarray, int]: # noqa:E121,E125
""" Updates bounds for sigma around a target pri... | a3426220fe20a4857ac51048ab8d703decaf3e9f | 3,655,743 |
def get_timeseries(rics, fields='*', start_date=None, end_date=None,
interval='daily', count=None,
calendar=None, corax=None, normalize=False, raw_output=False, debug=False):
"""
Returns historical data on one or several RICs
Parameters
----------
rics: string ... | 52f8cb2f5fc422df0c9b474f879797b997ae3a4d | 3,655,744 |
def usd(value):
"""Format value as USD."""
return f"${value:,.2f}" | 022502cebaced49e21a311fe0bed6feead124ee9 | 3,655,745 |
def random_mindist(N, mindist, width, height):
"""Create random 2D points with a minimal distance to each other.
Args:
N(int): number of points to generate
mindist(float): Minimal distance between each point
width(float): Specifies [0, width) for the x-coordinate
height(float): ... | 261627e47e72b95d90f9b9c409ce61535f2a4cf7 | 3,655,746 |
def deactivate_spotting(ID):
"""
Function to deactivate a spotting document in Elasticsearch
Params:
ID::str
id of the document to deactivate
Returns:
bool
If the changes have been applied or not
"""
if not ID:
return False
try:
globa... | 381c79a08e990b64a0a1032b5b54b874b8c53926 | 3,655,747 |
import watools.General.raster_conversions as RC
import watools.Functions.Start as Start
import numpy as np
def Fraction_Based(nc_outname, Startdate, Enddate):
"""
This functions calculated monthly total supply based ETblue and fractions that are given in the get dictionary script
Parameters
---------... | 378c149cc239eee31b10d90235b78cf15527b0e0 | 3,655,748 |
def _qrd_solve(r, pmut, ddiag, bqt, sdiag):
"""Solve an equation given a QR factored matrix and a diagonal.
Parameters:
r - **input-output** n-by-n array. The full lower triangle contains
the full lower triangle of R. On output, the strict upper
triangle contains the transpose of the strict low... | 3e9d75c135734770c248a39de5770c3b033262da | 3,655,749 |
import re
def find_version():
"""Extract the version number from the CLI source file."""
with open('pyweek.py') as f:
for l in f:
mo = re.match('__version__ = *(.*)?\s*', l)
if mo:
return eval(mo.group(1))
else:
raise Exception("No version in... | 128f2399a37b27412d2fdf6cf0901c1486709a09 | 3,655,750 |
import pandas.core.algorithms as algos
def remove_unused_levels(self):
"""
create a new MultiIndex from the current that removing
unused levels, meaning that they are not expressed in the labels
The resulting MultiIndex will have the same outward
appearance, meaning the same .values and ordering. ... | 8f07a2b943278d5d5ae7d78ab2c10e96acd349e4 | 3,655,751 |
def _transform_playlist(playlist):
"""Transform result into a format that more
closely matches our unified API.
"""
transformed_playlist = dict([
('source_type', 'spotify'),
('source_id', playlist['id']),
('name', playlist['name']),
('tracks', playlist['tracks']['total'])... | 62c19c132cbb9438c7a4b993e1d79111b79b86fd | 3,655,752 |
from typing import Dict
from typing import Hashable
from typing import Any
def decode_map_states(beliefs: Dict[Hashable, Any]) -> Any:
"""Function to decode MAP states given the calculated beliefs.
Args:
beliefs: An array or a PyTree container containing beliefs for different variables.
Returns:... | 3d8b9feecb3d612a4ff361f710ef1841cd016239 | 3,655,753 |
def plot_stretch_Q(datas, stretches=[0.01,0.1,0.5,1], Qs=[1,10,5,100]):
"""
Plots different normalizations of your image using the stretch, Q parameters.
Parameters
----------
stretches : array
List of stretch params you want to permutate through to find optimal image normalization.
... | d4dc4d52019aac10fc15dd96fd29c3abf6563446 | 3,655,754 |
def _isSpecialGenerateOption(target, optName):
"""
Returns ``True`` if the given option has a special generation function,
``False`` otherwise.
"""
return _getSpecialFunction(target, optName, '_generateSpecial') is not None | 387fcb96d0d13e45b38a645ee61f20441905a0f8 | 3,655,755 |
def count_active_days(enable_date, disable_date):
"""Return the number of days the segment has been active.
:param enable_date: The date the segment was enabled
:type enable_date: timezone.datetime
:param disable_date: The date the segment was disabled
:type disable_date: timezone.datetime
:ret... | 070a520c328dbe69491fc6eb991c816c9f4fccd8 | 3,655,756 |
def numpy_to_python_type(value):
"""
Convert to Python type from numpy with .item().
"""
try:
return value.item()
except AttributeError:
return value | f1d3a8ad77932342c182d7be76037fee3c869afe | 3,655,757 |
import tqdm
import os
def bigEI_numerical(Ey, t, P=1):
"""Return the column kp=0 of the matrix E_I, computed numerically."""
lmax = int(np.sqrt(Ey.shape[0]) - 1)
K = len(t)
map = starry.Map(ydeg=lmax, lazy=False)
theta = 360 / P * t
bigEI = np.zeros(K)
kp = 0
for k in tqdm(range(K), d... | f437a6b818b848fb8dc715ec04c693d6d3dbd161 | 3,655,758 |
import sys
import traceback
def db_select_all(db, query, data=None):
"""Select all rows"""
logger_instance.debug("query = <<%s>>"% (query[:100],))
cursor = db.cursor()
try:
cursor.execute(query, data)
except pymysql.MySQLError:
exc_type, exc_value, exc_traceback = sys.exc_info()
... | 44184540092ab698292fff9285f4bff0cb163be7 | 3,655,759 |
def threshold_abs(image, threshold):
"""Return thresholded image from an absolute cutoff."""
return image > threshold | 5032f632371af37e81c3ebcc587475422d5ff2bf | 3,655,760 |
def warp_images(img1_loc, img2_loc, h_loc):
"""
Fill documentation
"""
rows1, cols1 = img1_loc.shape[:2]
rows2, cols2 = img2_loc.shape[:2]
print("0")
list_of_points_1 = np.array(
[[0, 0], [0, rows1], [cols1, rows1], [cols1, 0]], np.float32).reshape(-1, 1, 2)
temp_points = np.arr... | ab5b364ded7647efb13c686a32acc8ee6c6487ba | 3,655,761 |
def ValidaCpf(msg='Cadastro de Pessoa Física (CPF): ', pont=True):
"""
-> Função para validar um CPF
:param msg: Mensagem exibida para usuário antes de ler o CPF.
:param pont: Se True, retorna um CPF com pontuação (ex: xxx.xxx.xxx-xx).
Se False, retorna um CPF sem pontuação (ex: xxxxxxxxxxx)
... | 3bdc298f7a2a3a4c16919a9caba21b71bbaf8539 | 3,655,762 |
def get_xml_path(xml, path=None, func=None):
"""
Return the content from the passed xml xpath, or return the result
of a passed function (receives xpathContext as its only arg)
"""
#doc = None
#ctx = None
#result = None
#try:
doc = etree.fromstring(xml)
#ctx = doc.xpathNewConte... | 81bcce1806f11217a04fbc401226d727e0150735 | 3,655,763 |
def readXYdYData(filename, comment_character='#'):
"""
Read in a file containing 3 columns of x, y, dy
Lines beginning with commentCharacter are ignored
"""
return read_columnar_data(filename, number_columns=3, comment_character=comment_character) | 92fd9253e0b50688034e3d85d6f4589a589be066 | 3,655,764 |
def hexlen(x):
"""
Returns the string length of 'x' in hex format.
"""
return len(hex(x))+2 | 404ec4c3656bb35b87df6ae147db93922f2da059 | 3,655,765 |
def get_db():
""" connectionを取得します """
if not hasattr(g, 'sqlite_db'):
g.sqlite_db = connect_db()
return g.sqlite_db | ba3d474ba854d9dea8e8f0056ebbfd81fc86b91a | 3,655,766 |
def list_manipulation(lst, command, location, value=None):
"""Mutate lst to add/remove from beginning or end.
- lst: list of values
- command: command, either "remove" or "add"
- location: location to remove/add, either "beginning" or "end"
- value: when adding, value to add
remove: remove ite... | c847257ea5508f60b84282c3ac8237b43cd3825a | 3,655,767 |
import six
def solve(
problem,
comm=_NoArgumentGiven,
dispatcher_rank=0,
log_filename=None,
results_filename=None,
**kwds
):
"""Solves a branch-and-bound problem and returns the
solution.
Note
----
This function also collects and summarizes runtime
workload statistics,... | 9c57c0748db0185fae1e731044e904d0f732b5de | 3,655,768 |
def solution(lst):
"""Given a non-empty list of integers, return the sum of all of the odd elements that are in even positions.
Examples
solution([5, 8, 7, 1]) ==> 12
solution([3, 3, 3, 3, 3]) ==> 9
solution([30, 13, 24, 321]) ==>0
"""
#[SOLUTION]
return sum([x for idx, x in enumerate(... | f98482cad7061d725389442c9811e33539df4fdc | 3,655,769 |
def summarize_traffic_mix(l_d_flow_records, d_filters={}):
"""
Filter the traffic flow data and execute the processing analysis logic for network behavior metrics.
"""
o_tcp_src_analysis = TopProtocolAnalysis()
o_tcp_dst_analysis = TopProtocolAnalysis()
o_upd_src_analysis = TopProtocolAnalysis... | 48b04cf0e1e4f8b50850a775994012af4a784728 | 3,655,770 |
def segment(X, upscale=1.0, denoise=False):
"""
:param X:
:param upscale:
:param denoise:
:return:
"""
if upscale > 1.0:
X = rescale(X, upscale)
if denoise:
X = denoise_wavelet(X)
thresh = filters.threshold_otsu(X)
bw = closing(X > thresh, square(3))
cleared... | e81be87bdb27b7cf1cf1de434997a87ecea0cae4 | 3,655,771 |
def get_image_info(doc):
"""Create dictionary with key->id, values->image information
"""
id_img = dict()
#add image information
for img_infor in doc['images']:
filename = img_infor['file_name']
width = img_infor['width']
height = img_infor['height']
id_img[img_infor['id']] = [filename, width,... | b8c91e67572e5863f773db579ce26fa86530f32e | 3,655,772 |
def __check_partial(detected,approx, width, height):
"""
Check if it's a partial shape
It's a partial shape if the shape's contours is on the image's edges.
Parameters
----------
detected : Shape
The detected shape
approx : numpy.ndarray
Approximates a polygonal curves.
... | 7808dd156de97fa467b7b471b77fa4abdeaede95 | 3,655,773 |
import re
def get_svg_size(filename):
"""return width and height of a svg"""
with open(filename) as f:
lines = f.read().split('\n')
width, height = None, None
for l in lines:
res = re.findall('<svg.*width="(\d+)pt".*height="(\d+)pt"', l)
if len(res) > 0:
# need to s... | 7732df636657950b050be409ef2439c975d6940d | 3,655,774 |
import time
import os
import glob
def bin_mgf(mgf_files,output_file = None, min_bin = 50, max_bin = 850, bin_size = 0.01, max_parent_mass = 850, verbose = False, remove_zero_sum_rows = True, remove_zero_sum_cols = True, window_filter = True, filter_window_size = 50, filter_window_retain = 3, filter_parent_peak = True... | f787a46415bbdc3bdbb52c62805618ad9edcec17 | 3,655,775 |
def index():
"""Video streaming home page which makes use of /mjpeg."""
return render_template('index.html') | 2fcc16af5bfc160a71f5eb74d1854b3c7e22587f | 3,655,776 |
def tex_quoted_no_underscore (s) :
"""Same as tex_quoted but does NOT quote underscores.
"""
if isinstance (s, pyk.string_types) :
s = _tex_pi_symbols.sub (_tex_subs_pi_symbols, s)
s = _tex_to_quote.sub (_tex_subs_to_quote, s)
s = _tex_tt_symbols.sub (_tex_subs_tt_symbols, s)
... | 96eca3b927e6c7cc84d721222ceb9e9405eb8763 | 3,655,777 |
import json
def load_from_json_file(filename):
"""
function that creates an Object from a “JSON file”
"""
with open(filename, 'r') as f:
return json.loads(f.read()) | ed46cf62548cfb7e1eb3683b688d18246b34be23 | 3,655,778 |
def _variable_to_field(v):
"""Transform a FuzzyVariable into a restx field"""
if isinstance(v.domain, FloatDomain):
a, b = v.domain.min, v.domain.max
f = fields.Float(description=v.name, required=True, min=a, max=b, example=(a + b) / 2)
elif isinstance(v.domain, CategoricalDomain):
r... | c97b25ff0abecedc6f44210d2672422d9c3eefd2 | 3,655,779 |
def abs_ang_mom(u, lat=None, radius=RAD_EARTH, rot_rate=ROT_RATE_EARTH,
lat_str=LAT_STR):
"""Absolute angular momentum."""
if lat is None:
lat = u[lat_str]
coslat = cosdeg(lat)
return radius*coslat*(rot_rate*radius*coslat + u) | 57525fa5ed995208eced76b74e4263c695340575 | 3,655,780 |
def main():
"""
Simple pyvmomi (vSphere SDK for Python) script that generates ESXi support bundles running from VCSA using vCenter Alarm
"""
# Logger for storing vCenter Alarm logs
vcAlarmLog = logging.getLogger('vcenter_alarms')
vcAlarmLog.setLevel(logging.INFO)
vcAlarmLogFile = os.path.join('/v... | 2c874bc06072896bb35f0288dd2ef4b5f69fe07f | 3,655,781 |
import collections
def _get_ngrams(segment, max_order):
"""Extracts all n-grams upto a given maximum order from an input segment.
Args:
segment: text segment from which n-grams will be extracted.
max_order: maximum length in tokens of the n-grams returned by this
methods.
Ret... | 561dfe8c18810ce40ce4c0ff391d6838816de116 | 3,655,782 |
def print_donors_list():
"""
print a list of existing donors
"""
print(mr.list_donors())
return False | 997860c036cac95f73242174198092a1d7d3ea9b | 3,655,783 |
def log_cef(name, severity, env, *args, **kwargs):
"""Simply wraps the cef_log function so we don't need to pass in the config
dictionary every time. See bug 707060. env can be either a request
object or just the request.META dictionary"""
c = {'cef.product': getattr(settings, 'CEF_PRODUCT', 'AMO'),
... | bb9631f32bf2a247760ff604e998e8058f203c9e | 3,655,784 |
def collimate(S, r, phasevec, print_values = False):
"""Collimate r phase vectors into a new phase vector on [S].
Output: the collimated phase vector ([b(0),b(1),...,b(L'-1)], L') on [S].
Parameters:
S: output phase vectors has all multipliers on [S]
r: arity, the number of phase vectors that is co... | 1e1eb6c55cd1b51e7303613d581fda97ad14bdb0 | 3,655,785 |
import io
def parse_and_load(gw, subj, primitive, cgexpr, g):
""" Parse the conceptual grammar expression for the supplied subject and, if successful, add
it to graph g.
:param gw: parser gateway
:param subj: subject of expression
:param primitive: true means subClassOf, false means equivalentClas... | cd5b1b27b5922fb6c0e377532192a6985a0a5783 | 3,655,786 |
def pushed(property_name, **kwargs) -> Signal:
"""
Returns the `pushed` Signal for the given property. This signal
is emitted, when a new child property is added to it.
From the perspective of a state, this can be achieved
with the `ContextWrapper.push(...)` function.<br>
__Hint:__ All key-wo... | 999e6b20a92648d5042c075400af45c809f08a32 | 3,655,787 |
async def delete_data(table_name: str,
filter: str = Header(None),
filterparam: str = Header(None),
current_user_role: bool = Depends(security.get_write_permission)):
"""
Parameters
- **table_name** (path): **Required** - Name of the ... | ffcf6e1aba2089846f103820eda0960bbccd4bba | 3,655,788 |
import dask.dataframe as dd
def _is_dask_series(ddf):
"""
Will determine if the given arg is a dask dataframe.
Returns False if dask is not installed.
"""
try:
return isinstance(ddf, dd.Series)
except:
return False | 5166928c0bd54bfc69a3d7862fadc41c3a0b6d19 | 3,655,789 |
import scipy
def square(t, A=1, f=1, D=0):
"""
t: time
A: the amplitude, the peak deviation of the function from zero.
f: the ordinary frequency, the number of oscillations (cycles) that occur each second of time.
D: non-zero center amplitude
"""
square_ = A*scipy.signal.square(
... | 8e1899891d5f0df6c171404c401e94f729233147 | 3,655,790 |
def self_distance_array(reference, box=None, result=None, backend="serial"):
"""Calculate all possible distances within a configuration `reference`.
If the optional argument `box` is supplied, the minimum image convention is
applied when calculating distances. Either orthogonal or triclinic boxes are
s... | 71ee400ad48f719316a0c3f3c101f432067e2387 | 3,655,791 |
import numpy
def mainRecursivePartitioningLoop(A, B, n_cutoff):
"""
"""
# Initialize storage objects
n = A.shape[0]
groups = numpy.zeros((n,), dtype=int)
groups_history = []
counts = {'twoway-single' : 0,
'twoway-pair' : 0,
'threeway-pair' : 0}
to_split = {... | e2983585825f068ce1bdcc26dfd91dd85be2e060 | 3,655,792 |
def corrSmatFunc(df, metric='pearson-signed', simFunc=None, minN=None):
"""Compute a pairwise correlation matrix and return as a similarity matrix.
Parameters
----------
df : pd.DataFrame (n_instances, n_features)
metric : str
Method for correlation similarity: pearson or spearman, optiona... | 3d8d3ad9c992f1f1518c8fc7699058e76f616c95 | 3,655,793 |
def rank(values, axis=0, method='average', na_option='keep',
ascending=True, pct=False):
"""
"""
if values.ndim == 1:
f, values = _get_data_algo(values, _rank1d_functions)
ranks = f(values, ties_method=method, ascending=ascending,
na_option=na_option, pct=pct)
... | 0dbdb923281f7dbf592cd7bd41615b235b0e0868 | 3,655,794 |
def _cmpopts(x, y):
"""Compare to option names.
The options can be of 2 forms: option_name or group/option_name. Options
without a group always comes first. Options are sorted alphabetically
inside a group.
"""
if '/' in x and '/' in y:
prex = x[:x.find('/')]
prey = y[:y.find('/... | 9da8f8f5666b2ea3f32eb092c6a3568947655400 | 3,655,795 |
def ask(question, choices):
"""Prompt user for a choice from a list. Return the choice."""
choices_lc = [x.lower() for x in choices]
user_choice = ""
match = False
while not match:
print question
user_choice = raw_input("[" + "/".join(choices) + "] ? ").strip().lower()
for ch... | 8a1f6019554dbb9e1ed6649b1a68040f99960fbe | 3,655,796 |
def get_and_validate_user(username, password):
"""
Check if user with username/email exists and specified
password matchs well with existing user password.
if user is valid, user is returned else, corresponding
exception is raised.
"""
user_model = apps.get_model("users", "User")
qs = ... | 05b6675c12446e961d85b8c39b0437d51a7c40b8 | 3,655,797 |
import re
import string
def process_tweet(tweet):
"""Process tweet function.
Input:
tweet: a string containing a tweet
Output:
tweets_clean: a list of words containing the processed tweet"""
stemmer = PorterStemmer()
stopwords_english = stopwords.words('english')
# R... | 2b69f70cfec5f90a6e58408fcd054cda7ad0f20a | 3,655,798 |
def oracle_query_id(sender_id, nonce, oracle_id):
"""
Compute the query id for a sender and an oracle
:param sender_id: the account making the query
:param nonce: the nonce of the query transaction
:param oracle_id: the oracle id
"""
def _int32(val):
return val.to_bytes(32, byteorder... | aa97834efd3df10951e05b99035dbef8210ba33d | 3,655,799 |
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