text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
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# Copyright 2015 Hewlett-Packard Development Company, L.P.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | {"hexsha": "1909ab5da465dab7b98ac67379f30a34fce705ec", "size": 31556, "ext": "py", "lang": "Python", "max_stars_repo_path": "openstack_health/api.py", "max_stars_repo_name": "MountakBernotas/https-github.com-openstack-openstack-health", "max_stars_repo_head_hexsha": "9073777993eac43a2a9bfd9e341d6fd48ab15955", "max_star... |
!! # check to see if value exceeds threshold
integer function user_exceeds_th(blockno,&
qval,qmin,qmax,quad, &
dx,dy,dz,xc,yc,zc,threshold, &
init_flag, is_ghost)
implicit none
double precision :: qval,... | {"hexsha": "85c0e847de7fb11652847eaeb2bdf3271476367f", "size": 927, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "applications/clawpack/advection/3d/swirl/user_exceeds_th.f90", "max_stars_repo_name": "ECLAIRWaveS/ForestClaw", "max_stars_repo_head_hexsha": "0a18a563b8c91c55fb51b56034fe5d3928db37dd", "max_star... |
import numpy as np
import megengine as mge
from scipy.spatial.transform import Rotation
def np_dcm2euler(mats: np.ndarray, seq: str = "zyx", degrees: bool = True):
"""Converts rotation matrix to euler angles
Args:
mats: (B, 3, 3) containing the B rotation matricecs
seq: Sequence of euler rota... | {"hexsha": "0119cfe56fefad520741136d2975f7c5f2480640", "size": 1569, "ext": "py", "lang": "Python", "max_stars_repo_path": "common/so3.py", "max_stars_repo_name": "megvii-research/OMNet", "max_stars_repo_head_hexsha": "3585d4d63da3606c6433ec34714df74ef7ad74d4", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 10,... |
# Copyright (c) 2022 Dai HBG
"""
该脚本用于测试某一个信号矩阵top n股票做多的收益
日志
2022-01-21
- 需要过滤涨停板
"""
import numpy as np
def top_n_tester(signal: np.array, ret: np.array, top: np.array, zdt_top: np.array, position_date_dic: dict,
order_code_dic: dict, s: int, e: int, n: int = 10):
abs_ret = [] # 绝对收益
... | {"hexsha": "01bcfdbd2732575e454e2d717a044e9904e66020", "size": 956, "ext": "py", "lang": "Python", "max_stars_repo_path": "QBG/Tester/tools/top_n_tester.py", "max_stars_repo_name": "GYMS-PKU/Daily-Frequency-Quant", "max_stars_repo_head_hexsha": "808eda9930efecff04ecf98abf617404cadd0003", "max_stars_repo_licenses": ["MI... |
using OVERTVerify
using LazySets
using Dates
using JLD2
function run_query(query_number, avoid_set, controller_name)
controller = "nnet_files/jmlr/tora_"*controller_name*"_controller.nnet"
println("Controller: ", controller_name)
query = OvertQuery(
Tora, # problem
controller, # network file
Id(), #... | {"hexsha": "878af8360ee0e5c8cdc52b1272347dc2b744a6ea", "size": 1717, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/examples/jmlr/tora_satisfiability.jl", "max_stars_repo_name": "sisl/OvertVerify.jl", "max_stars_repo_head_hexsha": "c76fe7703b5068cbdc91e058d815f1fcbda44d70", "max_stars_repo_licenses": ["MIT"]... |
[STATEMENT]
lemma Says_Nonce_not_used_guard: "[| Says A' B \<lbrace>A'',r,I,L\<rbrace> \<in> set evs;
Nonce n \<notin> used evs |] ==> L \<in> guard n Ks"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>Says A' B \<lbrace>A'', r, I, L\<rbrace> \<in> set evs; Nonce n \<notin> used evs\<rbrakk> \<Longrightarro... | {"llama_tokens": 175, "file": null, "length": 1} |
# Copyright 2018 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... | {"hexsha": "f47353ee0b1fe8aec6d1c17bc99825bf21284925", "size": 15461, "ext": "py", "lang": "Python", "max_stars_repo_path": "tensorflow_probability/python/bijectors/reshape_test.py", "max_stars_repo_name": "souravsingh/probability", "max_stars_repo_head_hexsha": "0519b63094fdaa4e326357a0cdff056d5ef76cd8", "max_stars_re... |
program t
! from Tom Henderson
implicit none
character (len=100) :: lawyers
integer :: x, y, zzz
x = 2
y = 1
zzz = x +
ay
print *, 'zzz = ',zzz
zz
az = x *
ay
print *, 'zzz = ',zzz
zzz = x -
ay
print *, '... | {"hexsha": "5f191e4fba827684a2a75acb734df1d718cdc3e8", "size": 1705, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "tests/t0212x/t.f", "max_stars_repo_name": "maddenp/ppp", "max_stars_repo_head_hexsha": "81956c0fc66ff742531817ac9028c4df940cc13e", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 2, ... |
'''
This file is designed to determine how often the market index is in a relative bear or bull market state.
This file runs through every daily price of the S&P 500 Index and uses the following steps:
1- Look back over past 180 days
2- Set two thresholds- one that is slightly below the max of last 180 day prices, and ... | {"hexsha": "47db8df46bfc97e0faa5a1523f7811c4ca25fa26", "size": 2894, "ext": "py", "lang": "Python", "max_stars_repo_path": "TrendTrading/ProbModel/CheckScripts/comprehensiveStatusChecks.py", "max_stars_repo_name": "benjabee10/WKUResearch", "max_stars_repo_head_hexsha": "5cc384c0e0c1afc82c38a9e6eb63b80c85af7c97", "max_s... |
/***********************************************************************
* created: Sun May 25 2014
* author: Timotei Dolean <timotei21@gmail.com>
*************************************************************************/
/***************************************************************************
* C... | {"hexsha": "ff10627a3f62c738b42a37ec88e5f0a42447274d", "size": 10577, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "tests/unit/ListView.cpp", "max_stars_repo_name": "bolry/cegui", "max_stars_repo_head_hexsha": "58b776a157409cb13092b77d68ab2618cf5c6e05", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 257.... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
:copyright:
Nienke Brinkman (nienke.brinkman@erdw.ethz.ch), 2020
:license:
None
"""
import obspy
import instaseis
from typing import Union as _Union
import numpy as np
import SS_MTI.SourceTimeFunction as _STF
def make_GF(
or_time: obspy.UTCDateTime,
... | {"hexsha": "508842350dea3b688f103c5f84fbdb20491a5052", "size": 7303, "ext": "py", "lang": "Python", "max_stars_repo_path": "SS_MTI/GreensFunctions.py", "max_stars_repo_name": "nienkebrinkman/SS_MTI", "max_stars_repo_head_hexsha": "2632214f7df9caaa53d33432193ba0602470d21a", "max_stars_repo_licenses": ["BSD-3-Clause"], "... |
/-
Copyright (c) 2018 Simon Hudon. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Simon Hudon
-/
import Lean.Elab.Term
import Lean.Meta.Tactic.Apply
import Lean.Meta.Tactic.Assumption
import Lean.Elab.DeclarationRange
import Mathlib.Control.SimpSet
/-!
# HigherOrder a... | {"author": "leanprover-community", "repo": "mathlib4", "sha": "b9a0a30342ca06e9817e22dbe46e75fc7f435500", "save_path": "github-repos/lean/leanprover-community-mathlib4", "path": "github-repos/lean/leanprover-community-mathlib4/mathlib4-b9a0a30342ca06e9817e22dbe46e75fc7f435500/Mathlib/Tactic/HigherOrder.lean"} |
from glob import glob
from tifffile import imread
import mxnet as mx
import mxnet.ndarray as nd
import numpy as np
from matplotlib import pyplot as plt
from mxnet import gpu, cpu
import time, os
import cv2
from glob import glob
import sys
sys.path.insert(0, 'D:\Github\cellpose')
import cellpose
from cellpose import ut... | {"hexsha": "fe8a349e8b0a8b095bdcb351deb387513e6fe73e", "size": 7184, "ext": "py", "lang": "Python", "max_stars_repo_path": "cellpose/collect_datasets.py", "max_stars_repo_name": "haoxusci/cellpose", "max_stars_repo_head_hexsha": "ea3cdf687cb026608f2e6a97d3d1e4fac61257d3", "max_stars_repo_licenses": ["BSD-3-Clause"], "m... |
module rex
implicit none
public :: rex_init
public :: rex_seed
public :: rex_exchange
public :: rex_id
public :: rex_rank
public :: rex_finalize
private
include "mpif.h"
! MPI message tag used for replica exchange messages. This is an arbitrary
! number that is not used for an... | {"hexsha": "dc9421ef16ffa9d8f3469d432bc9daeba1338456", "size": 5922, "ext": "f95", "lang": "FORTRAN", "max_stars_repo_path": "rex.f95", "max_stars_repo_name": "snsinfu/f95-replica-exchange", "max_stars_repo_head_hexsha": "9c400bbe1192d7f102574334590b2a12624a6f63", "max_stars_repo_licenses": ["BSL-1.0"], "max_stars_coun... |
# -*- coding: utf-8 -*-
# @Time : 19-8-2 下午3:08
# @Author : zj
from classifier.nn_classifier import NN
from tests.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
import numpy as np
import pytest
def rel_error(x, y):
""" returns relative error """
return np.max(np.abs(x - y) ... | {"hexsha": "77b3ad1dbd6b9b76b178eddfa5ada597e6c27d5a", "size": 9939, "ext": "py", "lang": "Python", "max_stars_repo_path": "coding/tests/test_nn_classifier.py", "max_stars_repo_name": "deep-learning-algorithm/cs231n", "max_stars_repo_head_hexsha": "b4da574a00622f1993ae3fe9ef777d751ed7e591", "max_stars_repo_licenses": [... |
import fileinput
import statistics
import numpy as np
from scipy import stats
degree_data = []
for line in fileinput.input():
line = line.strip()
identifier, degree = line.split('\t')
degree_data.append(int(degree))
if degree_data:
m, c = stats.mode(degree_data)
mode = m[0]
mode_frequency = c... | {"hexsha": "ce284f7d46d9be2054f0c6007aad1ada2f32614d", "size": 851, "ext": "py", "lang": "Python", "max_stars_repo_path": "code/calculate_degree_stats.py", "max_stars_repo_name": "vphill/metadata-record-graphs", "max_stars_repo_head_hexsha": "69462d7f1fb852b6c6a7d5e27b2221c594456b4b", "max_stars_repo_licenses": ["BSD-3... |
[STATEMENT]
lemma inverse_prod_list_field:
"prod_list (map (\<lambda>x. inverse (f x)) xs) = inverse (prod_list (map f xs :: _ :: field list))"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (\<Prod>x\<leftarrow>xs. inverse (f x)) = inverse (prod_list (map f xs))
[PROOF STEP]
by (induction xs) simp_all | {"llama_tokens": 120, "file": "Landau_Symbols_Landau_Real_Products", "length": 1} |
\documentclass[stock,9pt,nohan]{oblivoir}
\usepackage{fapapersize}
\usefapapersize{3in,4.5in,.333in,*,.333in,.333in}
\usepackage{gensymb}
\linespread{1.25}
\frenchspacing
\usepackage[verbose=true]{microtype}
\renewcommand{\contentsname}{Table of Contents}
\newcommand{\gamever}{Alpha 1}
\newcommand{\titleEN}{A Poc... | {"hexsha": "dbeac1dbe4fbac014b9d17ddca07f5fe247bb648", "size": 5106, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "assets/books/userguide_ENG.tex", "max_stars_repo_name": "curioustorvald/Terrarum", "max_stars_repo_head_hexsha": "6697f2f5cd77e2fb108ecdab4141b9d23086a4fa", "max_stars_repo_licenses": ["Apache-2.0"]... |
[STATEMENT]
lemma eq_key_imp_eq_value:
"v1 = v2"
if "distinct (map fst xs)" "(k, v1) \<in> set xs" "(k, v2) \<in> set xs"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. v1 = v2
[PROOF STEP]
proof -
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. v1 = v2
[PROOF STEP]
from that
[PROOF STATE]
proof (chain)
pickin... | {"llama_tokens": 899, "file": null, "length": 14} |
\section{Blockchain Scalability Proposals}\label{appendix:blockchain_scalability}
Here, we review some proposals to solve the Strong Byzantine Generals’ (SBG) problem while scaling the blockchain, and to allow blockchain-like behavior at greater scales.
This list is not intended to be exhaustive.
\subsection{Base Con... | {"hexsha": "9444dada0e1c3bfd3a78c3078bedc256b6dc8ecd", "size": 11041, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "src/appendix02_blockchain_scalability.tex", "max_stars_repo_name": "bigchaindb/whitepaper", "max_stars_repo_head_hexsha": "ef42daf8c06bea0bb04747963b3ae23f667ea338", "max_stars_repo_licenses": ["CC... |
[STATEMENT]
lemma isCont_If_ge:
fixes a :: "'a :: linorder_topology"
assumes "continuous (at_left a) g" and f: "(f \<longlongrightarrow> g a) (at_right a)"
shows "isCont (\<lambda>x. if x \<le> a then g x else f x) a" (is "isCont ?gf a")
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. isCont (\<lambda>x. if x \... | {"llama_tokens": 1190, "file": null, "length": 13} |
import Base: show, string, typejoin
abstract type AbstractLogicTerm end
abstract type SententialTerm{T<:AbstractLogicTerm} <: AbstractLogicTerm end
abstract type JunctionTerm{T<:AbstractLogicTerm} <: SententialTerm{T} end
abstract type QuantifierTerm{T<:AbstractLogicTerm} <: SententialTerm{T} end
# we make Variable <... | {"hexsha": "0e93bd26278d728c0b58f1ebd93abecd549c0238", "size": 4003, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/types.jl", "max_stars_repo_name": "william-macready/FirstOrderLogic.jl", "max_stars_repo_head_hexsha": "6a1a7ee0c5ad4a6fcfa34e907d39ba9f61ab3b57", "max_stars_repo_licenses": ["MIT"], "max_stars... |
using Interp1d
using Documenter
DocMeta.setdocmeta!(Interp1d, :DocTestSetup, :(using Interp1d); recursive=true)
makedocs(;
modules=[Interp1d],
authors="Atsushi Sakai <asakai.amsl+github@gmail.com> and contributors",
repo="https://github.com/AtsushiSakai/Interp1d.jl/blob/{commit}{path}#{line}",
sitenam... | {"hexsha": "86c079ee4a9d0842d0ea30e4ec60e9934010be5c", "size": 678, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "docs/make.jl", "max_stars_repo_name": "AtsushiSakai/Interp1d.jl", "max_stars_repo_head_hexsha": "0253a2e5669a2b65af0456d8ff161644efae37eb", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 2, ... |
def rdm_concat_df(path, outfile=None, prefix=None, addata=None, columns=None):
'''function to create an dictionary containing
all RDMs from a given dictory'''
global dict_rdms
global DefaultListOrderedDict
from os.path import join as opj
import sys
from glob import glob
from scipy.... | {"hexsha": "e6bd038807f88a0fab7de019838865578527aebc", "size": 2062, "ext": "py", "lang": "Python", "max_stars_repo_path": "urial/utils/rdm_concat_df.py", "max_stars_repo_name": "MirjamSchneider/URIAL", "max_stars_repo_head_hexsha": "be3edb5299dc812f4e4fa75bcb9d71c853209c8a", "max_stars_repo_licenses": ["BSD-3-Clause"]... |
using Bootstrap
## COPY
function Base.copy(d::NamedTuple{(:X, :Y), Tuple{FreqTab, FreqTab}})
return (X = copy(d.X), Y = copy(d.Y))
end
function Base.copy(t::FreqTab)
FreqTab(
copy(t.table),
copy(t.raw),
copy(t.interval),
merge(t.stats)
)
end
function copy(x::SGEquateResu... | {"hexsha": "ba3f075a09695d17ab2529e5e15238a98b287a0a", "size": 5511, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/SEE.jl", "max_stars_repo_name": "takuizum/Equate.jl", "max_stars_repo_head_hexsha": "8ba0055ef69fc086fd4b39cff545a623d5a793fe", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "max_st... |
from utils import *
from sample_generator import *
from cvxopt import matrix
from l1 import l1
import numpy as np
import math
import os
def denoise_step(sample, H=3, dn1=1., dn2=1.):
def get_denoise_value(idx):
start_idx, end_idx = get_neighbor_idx(len(sample), idx, H)
idxs = np.arange(start_idx,... | {"hexsha": "86a9b57311f32b13c80f2e042ca2e90ec2edc63e", "size": 5809, "ext": "py", "lang": "Python", "max_stars_repo_path": "RobustSTL.py", "max_stars_repo_name": "leezhi403/LeeDoYup-RobustSTL", "max_stars_repo_head_hexsha": "69ca042ab53ea204a5c17571eb460afcced3937a", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
import numpy as np
import matplotlib.pyplot as plt
xs = np.fromfile('utcs.dat', dtype=np.uint32)
ys = np.fromfile('values.dat', dtype=np.uint64)
print('Loaded')
xs = np.random.choice(xs, size=1000000)
ys = np.random.choice(ys, size=1000000) / 1e8
xmin = xs.min()
ymin = ys.min()
xmax = xs.max()
ymax = ys.max()
print... | {"hexsha": "3df94df13b78860764d893dd3f797accc90c4b8f", "size": 478, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/heatmap.py", "max_stars_repo_name": "NewProggie/fast-dat-parser", "max_stars_repo_head_hexsha": "70c28f16cb5ee33f9cb56c2db81069d27eaca0c4", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import os
import h5py
import numpy as np
import vigra
import json
from math import sqrt
from cremi.evaluation import NeuronIds
from cremi import Volume
from skunkworks.postprocessing.watershed.dam_ws import DamWatershed
def cremi_scores(seg, gt):
if 0 in gt:
gt[gt == 0] = -1
seg = Volume(seg)
met... | {"hexsha": "9cf5b79e4a5682d62564640c4ecaba761f70f9e3", "size": 1702, "ext": "py", "lang": "Python", "max_stars_repo_path": "experiments/cremi/offset-experiments/no_ignore_bb.py", "max_stars_repo_name": "constantinpape/inferno-experiments", "max_stars_repo_head_hexsha": "7eb034c330a69b58406ca25f35981b01ca0fdc2d", "max_s... |
from numpy.core.numeric import NaN
from numpy.lib.type_check import nan_to_num
from src.utils import softmax
import numpy as np
from copy import deepcopy
class NaiveBayes:
"""
A Naive Bayes classifier for binary data.
"""
def __init__(self, smoothing=1):
"""
Args:
smoothin... | {"hexsha": "7feb0ccecab96550e3c833d55cce88809de54e5e", "size": 12550, "ext": "py", "lang": "Python", "max_stars_repo_path": "naive_bayes_and_expectation_maximization/src/naive_bayes.py", "max_stars_repo_name": "WallabyLester/Machine_Learning_From_Scratch", "max_stars_repo_head_hexsha": "6042cf421f5de2db61fb570b7c4de64d... |
from collections import OrderedDict
import pytest
import pandas as pd
import numpy as np
from prepnet.category.ordinal_converter import OrdinalConverter
from prepnet.category.onehot_converter import OnehotConverter
def test_ordinal_converter():
input_series = pd.Series(['frame', 'frame', 'old', 'test', 'old', '... | {"hexsha": "0866d174d9ea4170867da5d340f976b09f50e539", "size": 2245, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_category.py", "max_stars_repo_name": "elda27/prepnet", "max_stars_repo_head_hexsha": "0f05018969496321aaa770b7e22bda858dab0ad6", "max_stars_repo_licenses": ["MIT"], "max_stars_count": n... |
// Boost.GIL (Generic Image Library) - tests
//
// Copyright 2020 Olzhas Zhumabek <anonymous.from.applecity@gmail.com>
//
// Use, modification and distribution are subject to the Boost Software License,
// Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
#ifndef... | {"hexsha": "97fcd8cde5d2e33b8894d0629fde1ffe7f079e69", "size": 4732, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "include/boost/gil/image_processing/hough_parameter.hpp", "max_stars_repo_name": "harsh-4/gil", "max_stars_repo_head_hexsha": "6da59cc3351e5657275d3a536e0b6e7a1b6ac738", "max_stars_repo_licenses": ["... |
import h5py
from bisect import bisect_left
import matplotlib.pyplot as plt
import numpy as np
class brianPlotter:
def __init__(self, hdf5name , permision = "w"):
self.hdf = h5py.File(hdf5name, permision)
def saveData(self, dataName , dataArray , downsample=True):
self.grp = self.hdf.create_gr... | {"hexsha": "efaadb1e2212b77ba68e0b43cf39c261c3999fa4", "size": 4514, "ext": "py", "lang": "Python", "max_stars_repo_path": "utilities/brianPlotter.py", "max_stars_repo_name": "Jbwasse2/snn-rl", "max_stars_repo_head_hexsha": "29b040655f432bd390bc9d835b86cbfdf1a622e4", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
import os
import numpy as np
from bmtk.builder import NetworkBuilder
from bmtk.utils.io.spike_trains import PoissonSpikesGenerator
build_virtual_net = True
cell_models = [
{
'model_name': 'Scnn1a', 'ei': 'e', 'morphology': 'Scnn1a_473845048_m.swc',
'model_template': 'ctdb:Biophys1.hoc',
'... | {"hexsha": "37998fc2914f987a5b78a8cb62559fc4ecb4cc1e", "size": 2650, "ext": "py", "lang": "Python", "max_stars_repo_path": "docs/examples/bio_basic_features/build_network.py", "max_stars_repo_name": "tjbanks/bmtk", "max_stars_repo_head_hexsha": "52fee3b230ceb14a666c46f57f2031c38f1ac5b1", "max_stars_repo_licenses": ["BS... |
import torch
import numpy as np
class BeamSearcher():
def __init__(self, width, eos):
self.width = width
self.eos = eos
self.hypos = [{'seq': [], 'score': 0} for _ in range(width)]
self.parent_hypos = [i for i in range(width)]
self.end_hypos = []
def step(self, step, l... | {"hexsha": "8a61ef2140b20f378b6475e8a6070eb6b37fd3a3", "size": 1810, "ext": "py", "lang": "Python", "max_stars_repo_path": "torch_models/models/beam_searcher.py", "max_stars_repo_name": "Ryou0634/pytorch_models", "max_stars_repo_head_hexsha": "cd48f9b3797839df5dbf4e51bed81de44e7b962e", "max_stars_repo_licenses": ["BSD-... |
# Beispielprogramm für das Buch "Python Challenge"
#
# Copyright 2020 by Michael Inden
import numpy as np
numbers = np.array([[1, 2, 3, 4],
[1, 2, 3, 4],
[1, 2, 3, 4]])
print(np.flip(numbers, 1))
numbers2 = np.array([[1, 1, 1, 1],
[2, 2, 2, 2],
... | {"hexsha": "2d942ad3b37cf341e23474a2ef2bc9d0cea6d0ed", "size": 372, "ext": "py", "lang": "Python", "max_stars_repo_path": "Python/zzz_training_challenge/Python_Challenge/solutions/ch06_arrays/intro/intro_numpy_flip.py", "max_stars_repo_name": "Kreijeck/learning", "max_stars_repo_head_hexsha": "eaffee08e61f2a34e01eb8f9f... |
using LightGraphs, Plots, StatsPlots, Distributions, GraphRecipes, GraphIO, ParserCombinator, JSON
using GraphIO: GML
gr()
theme(:juno)
N = 50
k = 1
function gen_graph(N, k)
G = barabasi_albert(N, k)
path = a_star(G, 1, N)
uni = Set{Int}()
for e ∈ path
push!(uni, e.src)
push!(uni, e.... | {"hexsha": "838ceeefe12ff6cb7c9c56e962c767f37be261a1", "size": 1046, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "scripts/BI/examples/path/gen.jl", "max_stars_repo_name": "shalinkpatel/GCN_Integration", "max_stars_repo_head_hexsha": "253fa4321606acf0ee0a98667bf6e5eb8ec96cf1", "max_stars_repo_licenses": ["MIT"]... |
function readSP3(gpsWeek, day)
# Construct string
#sp3File = datadir("igs") * "\\igs" * string(gpsWeek) * string(day) * ".sp3"
sp3File = datadir("igs", "igs" * string(gpsWeek) * string(day) * ".sp3")
if !isfile(sp3File)
throw(ErrorException("The file " * sp3File * " does not exist and... | {"hexsha": "e48afee58a2540b7798a0024eb4ebdb07102be1d", "size": 5299, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/GPS/readSP3.jl", "max_stars_repo_name": "GrantHecht/OptimalEstimationProject", "max_stars_repo_head_hexsha": "42e595d1991a8f81cbfb36856528d572b45cc598", "max_stars_repo_licenses": ["MIT"], "max... |
################################################################################
# Copyright (C) 2011-2012,2014 Jaakko Luttinen
#
# This file is licensed under the MIT License.
################################################################################
"""
Module for the Dirichlet distribution node.
"""
import ... | {"hexsha": "8825136a848c5f197c7281a130f07dd49eb9a65f", "size": 11102, "ext": "py", "lang": "Python", "max_stars_repo_path": "bayespy/inference/vmp/nodes/dirichlet.py", "max_stars_repo_name": "dungvtdev/upsbayescpm", "max_stars_repo_head_hexsha": "f6ee877c689046d3c57a2ac06742cfe4a0b6550e", "max_stars_repo_licenses": ["M... |
import warnings
warnings.filterwarnings("ignore")
import string
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
import numpy as np
import pandas as pd
from tensorflow.python.keras.preprocessing.text import Tokenizer
from sklearn.metrics import precision_recall_fscore_support
from termcolor imp... | {"hexsha": "6fc7d531590683a81b34eb3cce49787fd7210845", "size": 4237, "ext": "py", "lang": "Python", "max_stars_repo_path": "impl/withPSL/RNN/NELL_cnn_random_multiple_features.py", "max_stars_repo_name": "wso2-incubator/knowledge-graph-optimizations", "max_stars_repo_head_hexsha": "4740c27eb5facf6e3ed594400bfb8533ac38de... |
using Distributions, SpecialFunctions, FastGaussQuadrature
struct PositiveStable <: ContinuousUnivariateDistribution
α::Float64
β::Float64
θ::Float64
ρ::Float64
PositiveStable(α::Real,β::Real) = ( β < -1 || β > 1 ||
(β == -1 && α <= 1) || α <= 0 || α > 2 ) ?
error("Parameters' requirements unmet:\n (... | {"hexsha": "ec533aee3ca4a55304b27fcc24320ac513fb8254", "size": 14125, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/positivestable.jl", "max_stars_repo_name": "jorgeignaciogc/StableMeander.jl", "max_stars_repo_head_hexsha": "5e7d9be7ce032445a4c8d7e98a59fbc1d04169ed", "max_stars_repo_licenses": ["MIT"], "max... |
# EGEDA TPES plots for each economy
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
from openpyxl import Workbook
import xlsxwriter
import pandas.io.formats.excel
# Import the recently created data frame that joins OSeMOSYS results to EGEDA historical
EGEDA_years = pd.read_csv('./da... | {"hexsha": "815b1e8fa4b6faef72aafdc3781df041f970bec0", "size": 44287, "ext": "py", "lang": "Python", "max_stars_repo_path": "workflow/scripts/2_charts_tables/2017_egeda/TPES_economy.py", "max_stars_repo_name": "asia-pacific-energy-research-centre/8th_outlook_visualisations", "max_stars_repo_head_hexsha": "a8fed78db955f... |
C (C) Copyright 1996-2016 ECMWF.
C
C This software is licensed under the terms of the Apache Licence Version 2.0
C which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
C In applying this licence, ECMWF does not waive the privileges and immunities
C granted to it by virtue of its status as an intergov... | {"hexsha": "9def760b15ff1daee865d882ff97bde179443ed5", "size": 2092, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "test/old/fortran/mark.f", "max_stars_repo_name": "dtip/magics", "max_stars_repo_head_hexsha": "3247535760ca962f859c203295b508d442aca4ed", "max_stars_repo_licenses": ["ECL-2.0", "Apache-2.0"], "max... |
# -- coding: utf-8 --
import tensorflow as tf
import numpy as np
from data.data_hour import *
import pandas as pd
import argparse
from gcn_model.hyparameter import parameter
file='/Users/guojianzou/Traffic-speed-prediction/data/data_hour/'
class HA():
def __init__(self,
site_id=0,
... | {"hexsha": "90fda9e1d06dcc01444060245f73cfa476e4a5d5", "size": 3737, "ext": "py", "lang": "Python", "max_stars_repo_path": "MT-STFLN /comparison_model/ha.py", "max_stars_repo_name": "zouguojian/Traffic-speed-prediction", "max_stars_repo_head_hexsha": "4b9917a9e1147c37b64e51be3c060af4bdb9544d", "max_stars_repo_licenses"... |
#coverage:ignore
""" Determine costs for DF decomposition in QC """
from typing import Tuple
import numpy as np
from numpy.lib.scimath import arccos, arcsin # has analytc continuation to cplx
from openfermion.resource_estimates.utils import QR, QI, power_two
def compute_cost(n: int,
lam: float,
... | {"hexsha": "53c778a44e560f36094ab6f924ab1881bd85a6c5", "size": 7438, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/openfermion/resource_estimates/df/compute_cost_df.py", "max_stars_repo_name": "cvmxn1/OpenFermion", "max_stars_repo_head_hexsha": "cf53c063d0f124a02ff8776bb7f8afb110d4bde6", "max_stars_repo_li... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from matplotlib import pyplot as plt
from astropy.stats import mad_std
from astropy.io import fits
from photutils import CircularAperture
from astropy.convolution import convolve_fft, Topha... | {"hexsha": "4625cdeae578d6bef6b0e725565f406597180b11", "size": 4608, "ext": "py", "lang": "Python", "max_stars_repo_path": "toolkit/star_selection.py", "max_stars_repo_name": "bmorris3/rem", "max_stars_repo_head_hexsha": "be758a989fba62eac2a24bc201e855ee08173b47", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
import os.path
import scipy.io as io
import numpy as np
_folder_path = os.path.abspath("./CVACaseStudy/CVACaseStudy/")
FILE_NAMES = (
('Training Data', 'Training.mat'),
('Faulty Case 1', 'FaultyCase1.mat'),
('Faulty Case 2', 'FaultyCase2.mat'),
('Faulty Case 3', 'FaultyCase3.mat'),
('Faulty Case 4... | {"hexsha": "33b093461f193c3ae15e4a049496f4ed0ec413bc", "size": 2197, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/sfamanopt/load_cva.py", "max_stars_repo_name": "hsaafan/SSFA", "max_stars_repo_head_hexsha": "61c093c323c324b0eb7d2c93ef62252d71db6f16", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
C
C
C Support routines for PGPLOT tcl binding
C
C+ pgInitStream
C
subroutine pgInitStream( device, psize, paspect, nx, ny, id, s )
C ----------------------------------------------------------------
C
C Select and open a new stream for graphical output
C
C Given:
C device specification
character ... | {"hexsha": "3938611b2051816bc8a424a9647b7ae397044747", "size": 7084, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "anm3d/pgplot_util.f", "max_stars_repo_name": "CavendishAstrophysics/anmap", "max_stars_repo_head_hexsha": "efb611d7f80a3d14dc55e46cd01e8a622f6fd294", "max_stars_repo_licenses": ["BSD-3-Clause"], "... |
"""
sepp_base
~~~~~~~~~
A more abstract approach to SEPP type algorithms.
"""
from . import predictors
from . import logger as _ocp_logger
from . import data as _ocp_data
import numpy as _np
import datetime as _datetime
import logging as _logging
_logger = _logging.getLogger(__name__)
class ModelBase():
"""Inte... | {"hexsha": "175360094e78bd956c69a2fa63284255e863fa6b", "size": 29946, "ext": "py", "lang": "Python", "max_stars_repo_path": "open_cp/sepp_base.py", "max_stars_repo_name": "sumau/PredictCode", "max_stars_repo_head_hexsha": "e2a2d5a8fa5d83f011c33e18d4ce6ac7e1429aa8", "max_stars_repo_licenses": ["Artistic-2.0"], "max_star... |
import torch
import numpy
import matplotlib.pyplot as plt
from torch import nn
from einops.layers.torch import Rearrange
from einops import rearrange, repeat
class PatchEmbedding(nn.Module):
"""Creates the patches for the model input"""
def __init__(
self,
dim,
channels=3,
... | {"hexsha": "ffc31773a9c45770b8da5ab40cb702eca3683574", "size": 2362, "ext": "py", "lang": "Python", "max_stars_repo_path": "transformers/patch_emb.py", "max_stars_repo_name": "mhun1/transformers", "max_stars_repo_head_hexsha": "06376fabd7ccc15bf7fa5a4a4a142961a8c41e79", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import numpy as np
def randomcolor():
''' PICKS COLORS RANDOMLY
'''
colors = []
for i in range(20):
colors.append(list((np.random.randint(0, 255, 3) / 255)))
return colors
| {"hexsha": "ff7fcbb0bfdbde3d1f79a429a9fe598acfe02aeb", "size": 206, "ext": "py", "lang": "Python", "max_stars_repo_path": "astetik/style/random_colors.py", "max_stars_repo_name": "meirm/astetik", "max_stars_repo_head_hexsha": "ea05ce57a0bf1e8bd7ef18c4d5ca8d7ad3fb4be7", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
% book : Signals and Systems Laboratory with MATLAB
% authors : Alex Palamides & Anastasia Veloni
% Fast Fourier Transform of the sequence x=[1 2 3],n=0,1,2
x=[1 2 3];
Xk1=fft(x)
Xk2=dft(x)
| {"author": "Sable", "repo": "mcbench-benchmarks", "sha": "ba13b2f0296ef49491b95e3f984c7c41fccdb6d8", "save_path": "github-repos/MATLAB/Sable-mcbench-benchmarks", "path": "github-repos/MATLAB/Sable-mcbench-benchmarks/mcbench-benchmarks-ba13b2f0296ef49491b95e3f984c7c41fccdb6d8/28762-signals-and-systems-laboratory-with-ma... |
using GeometryBasics
import GeometryBasics
import GeometryBasics as gb
using Test
x = Rect(Vec(0.0, 0.0), Vec(1.0, 1.0))
y = Rect(Vec(0.5, 0.7), Vec(1.0, 1.0))
#z = GeometryBasics.intersect(x,y)
# """
# intersect(h1::Rect, h2::Rect)
# Perform a intersection between two Rects.
# """
# function intersect(h1::Rect... | {"hexsha": "1c77acf13eac7d628bac362e7b7baef79656de03", "size": 2646, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "learn/learn_GeometryBasics.jl", "max_stars_repo_name": "ykyang/org.allnix.julia", "max_stars_repo_head_hexsha": "58933a5848dec81c53d591b4163e9a70df62ddd8", "max_stars_repo_licenses": ["Apache-2.0"]... |
import sys
import signal
import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import time
from datetime import timedelta
import pygame
import pygame.camera
import pygame.surfarray
from PIL import Image
import numpy as np
image_path = 'image.jpg'
# getting image from camera
pygame.camera.init()
# pygame.camera.list_came... | {"hexsha": "f1d255079fcba00519d3a1afd498677dd13635de", "size": 1173, "ext": "py", "lang": "Python", "max_stars_repo_path": "Classifier/Old/Camera.py", "max_stars_repo_name": "mugroma3/ClassiPi", "max_stars_repo_head_hexsha": "8a70a5f5691d28c57f084b370f4688b70e8f406a", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
[STATEMENT]
lemma fold_sum_aux:
assumes "\<forall>u \<in> set (a # xs). \<forall>v \<in> set (a # xs). f v + W u v \<ge> f u"
shows "sum_list (map f (a # xs @ [a])) \<le> sum_list (map f (a # xs @ [a])) + weight (a # xs @ [a])"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. sum_list (map f (a # xs @ [a])) \<le> ... | {"llama_tokens": 422, "file": "Monad_Memo_DP_example_Bellman_Ford", "length": 2} |
function v = subsref( x, S )
try
v = subsref( x.value_, S );
catch
cvx_throw( 'Invalid tuple reference: %s%s', inputname(1), cvx_subs2str( S ) );
end
% Copyright 2005-2014 CVX Research, Inc.
% See the file LICENSE.txt for full copyright information.
% The command 'cvx_where' will show where this file is locate... | {"author": "yu-jiang", "repo": "radpbook", "sha": "88b9fa7d0a541099cdd1ac29383c89e087d1d895", "save_path": "github-repos/MATLAB/yu-jiang-radpbook", "path": "github-repos/MATLAB/yu-jiang-radpbook/radpbook-88b9fa7d0a541099cdd1ac29383c89e087d1d895/tools/cvx-w64/cvx/lib/@cvxtuple/subsref.m"} |
import unittest
import numpy as np
import json
import os, shutil, tempfile
from model import Model
class ModelTests(unittest.TestCase):
def setUp(self):
self.model = Model()
self.test_model_dir = tempfile.mkdtemp()
self.mock_train_set = (np.zeros((1, 10000)), np.zeros((1,)))
self... | {"hexsha": "2b7d53cbda8dab4d35589786aadde63ffc0030e4", "size": 5997, "ext": "py", "lang": "Python", "max_stars_repo_path": "IMDB_binary_classification/test/test_model.py", "max_stars_repo_name": "donK23/Thoughtful_DL", "max_stars_repo_head_hexsha": "8cd1b3b0ad35281b2e02a7e8581a606ae659284d", "max_stars_repo_licenses": ... |
import os.path
import logging
import numpy as np
from typing import Union
import PyMieSim
from PyMieSim.Tools.LPModes import GetFarFieldLP
from PyMieSim.Tools.Mesh import FibonacciMesh
from PyMieSim.Tools.BaseClasses import BaseDetector, MeshProperty
from PyMieSim.Tools.ErrorMsg import *
from PyMi... | {"hexsha": "a360e1d0d36bdf05eaa24772bedd158592130805", "size": 9241, "ext": "py", "lang": "Python", "max_stars_repo_path": "PyMieSim/Detector.py", "max_stars_repo_name": "MartinPdS/PyMieSim", "max_stars_repo_head_hexsha": "2560c7f4009df5d05bcb0ce8e929aa7baa7be8de", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
import common
import config
import Matlab
import math
import sys
import numpy as np
import cv2
CAUSAL_DO_NOT_SMOOTH = True
def rand_index(max_index, a_len):
if a_len > max_index:
index = np.array([])
return
index = np.zeros((1, a_len))
available = range(1, max_index)
"""
From... | {"hexsha": "fe9a013d363f4587ca50dea18218bc0eb9e2033d", "size": 27454, "ext": "py", "lang": "Python", "max_stars_repo_path": "Python/multiscale_synchro_decision.py", "max_stars_repo_name": "Spectavi/video-diff", "max_stars_repo_head_hexsha": "4ad28aea48877937f6b5b25f374f9c14eaf79212", "max_stars_repo_licenses": ["BSD-3-... |
# -*- coding: utf-8 -*-
"""
Merge two X/y. Takes care of reading two feature/label files, merges them and shuffels them
and writes them to new output directory.
Of course, I could also generalize to two lists of X and ys, respectively but this might lead
to even worse practices.
One big approximation of all of this i... | {"hexsha": "e3f5095371789eab5e0dc65df332b76733095db0", "size": 4840, "ext": "py", "lang": "Python", "max_stars_repo_path": "run/merge_two_x_y.py", "max_stars_repo_name": "kjappelbaum/mof_oxidation_states", "max_stars_repo_head_hexsha": "1bbfe9d84802b2248a23ac3d3ee999ed649fe816", "max_stars_repo_licenses": ["MIT"], "max... |
import torch
import numpy as np
import argparse
import mmcv
from mmcv.runner import load_checkpoint, init_dist, get_dist_info, build_optimizer, set_random_seed
from mmcv import Config, DictAction
from mmaction.models import build_recognizer
from dataloader.dataloaderTCN import DataloaderTCN
from scipy.io import savem... | {"hexsha": "90077805a2b88a470c07bb5128961a69520a0db3", "size": 4963, "ext": "py", "lang": "Python", "max_stars_repo_path": "features_extraction/feature_extractor.py", "max_stars_repo_name": "vinayakShenoy/Video-Swin-Transformer", "max_stars_repo_head_hexsha": "bd90abce394eca0db90d80c334c8b05aba2233b2", "max_stars_repo_... |
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE DeriveFunctor #-}
{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE TypeSynonymInstances #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE G... | {"hexsha": "9fc969954a0d74d2e86e8f63efa63eea13d0515d", "size": 54507, "ext": "hs", "lang": "Haskell", "max_stars_repo_path": "factorio-module-selector.hs", "max_stars_repo_name": "Rotsor/factorio-module-selector", "max_stars_repo_head_hexsha": "22a595ba36bbf9ca337bba0dfbe3c387308f43b3", "max_stars_repo_licenses": ["Unl... |
\documentclass[a4paper,10pt]{book}
\usepackage{textcomp}
\usepackage{amsmath}
\usepackage{amsthm}
\usepackage[top=0.5in, bottom=0.5in, left=0.5in, right=0.5in]{geometry}
\usepackage{setspace}
\newtheorem{theorem}{Theorem}[chapter]
\newtheorem{lemma}[theorem]{Lemma}
\theoremstyle{definition}
\newtheorem{definition}[t... | {"hexsha": "1290f6d412b54adb53d47f0a6cf771c6cda9bf0e", "size": 6954, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "src/Metric_Graphs.tex", "max_stars_repo_name": "siddhartha-gadgil/MetricGeometryCourse", "max_stars_repo_head_hexsha": "92ec7727f358107a8ad61a7229bc94e2aa9bbafc", "max_stars_repo_licenses": ["MIT"],... |
from re import L
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
def test_plotting():
station = "test_station"
dates = [2019, 2020, 2021, 2022]
levels = [12, 18, 45, 90]
plt.plot(dates, levels)
plt.xlabel('date')
plt.ylabel('water level (m)')
plt.xticks(rotation=45);
... | {"hexsha": "e189bcc454e2fc56b5132714fa2cf651d3a9cee9", "size": 377, "ext": "py", "lang": "Python", "max_stars_repo_path": "test_plot.py", "max_stars_repo_name": "reib2/Lab-3-Flood-Warning", "max_stars_repo_head_hexsha": "9f86b4b8a7fa9508ddaa0e9754d64ff6c4e38f66", "max_stars_repo_licenses": ["MIT"], "max_stars_count": n... |
"""
Crossmap class
"""
from contextlib import suppress
from yaml import dump
from logging import info, warning, error
from os import mkdir, remove
from os.path import exists
from shutil import rmtree
from scipy.sparse import vstack
from .settings import CrossmapSettings
from .dbmongo import CrossmapMongoDB as Crossmap... | {"hexsha": "fc056ccf3b2eb196b50cedd77ca90723e19f0910", "size": 14916, "ext": "py", "lang": "Python", "max_stars_repo_path": "crossmap/crossmap.py", "max_stars_repo_name": "tkonopka/crossmap", "max_stars_repo_head_hexsha": "237e4319a77281490c4e037918977230fea43d7e", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
from utils import gif
from skimage import io, color
import os
import cv2
import nrrd
import numpy as np
import argparse
from parse_config import ConfigParser
import torch
from dataloader.preprocessor import BUSIDataProcessor
from model import models
from utils import prepare_device
def get_prediction(model, device, pa... | {"hexsha": "28d67566830aaf3710399d9449298f16cfe5e506", "size": 4662, "ext": "py", "lang": "Python", "max_stars_repo_path": "test.py", "max_stars_repo_name": "tqxli/breast_ultrasound_lesion_segmentation_PyTorch", "max_stars_repo_head_hexsha": "d378a624a12b6156364f4f72c3fc60cc0c47f6f0", "max_stars_repo_licenses": ["MIT"]... |
#ifndef BOOST_DETAIL_ATOMIC_GCC_PPC_HPP
#define BOOST_DETAIL_ATOMIC_GCC_PPC_HPP
// Copyright (c) 2009 Helge Bahmann
//
// Distributed under the Boost Software License, Version 1.0.
// See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
#include <boost/atomic/detail/base.hpp>
... | {"hexsha": "cb1dcb9fff380af6aaccae249d23c1bc4d1340a8", "size": 54715, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "Dependencies/Theron/Include/External/boost/atomic/detail/gcc-ppc.hpp", "max_stars_repo_name": "sosan/NoahGameFrame", "max_stars_repo_head_hexsha": "38c54014c5c4620b784b2c1d2cab256f42bae186", "max_s... |
import base64
import hashlib
import json
import numpy as np
import hypney
export, __all__ = hypney.exporter()
@export
def hashablize(obj):
"""Convert a container hierarchy into one that can be hashed.
See http://stackoverflow.com/questions/985294
"""
try:
hash(obj)
except TypeError:
... | {"hexsha": "3ca336a62f5cea5cf412f189daae83ca36a6102c", "size": 1715, "ext": "py", "lang": "Python", "max_stars_repo_path": "hypney/utils/hashing.py", "max_stars_repo_name": "JelleAalbers/hypney", "max_stars_repo_head_hexsha": "3e38e21743fc9babe0ed47af299d08242a9b6d32", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
# =============================================================================
# @author: Shuo Zhou, The University of Sheffield
# =============================================================================
import numpy as np
from scipy.linalg import eig
from numpy.linalg import multi_dot
from sklearn.base import B... | {"hexsha": "cc0c8df8eb59e503f03d5525dfdb03144a32e031", "size": 4753, "ext": "py", "lang": "Python", "max_stars_repo_path": "pydale/transformer/_mida.py", "max_stars_repo_name": "sz144/TPy", "max_stars_repo_head_hexsha": "689e38bdc2549015bc45cfacfe42e20a51c76e5a", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 4... |
abstract type Adjoint_rep_Gaugefields_4D{NC,NumofBasis} <: Adjoint_rep_Gaugefields{NC,4,NumofBasis}
end
include("./Adjoint_rep_gaugefields_4D_wing.jl")
function Base.size(U::Adjoint_rep_Gaugefields_4D{NC,NumofBasis}) where {NC,NumofBasis}
return NumofBasis,NumofBasis,U.NX,U.NY,U.NZ,U.NT
end | {"hexsha": "8c4bcd724b896641d20bb8b85060fa96ff098d95", "size": 300, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/4D/Adjoint_rep_gaugefields_4D.jl", "max_stars_repo_name": "akio-tomiya/Gaugefields.jl", "max_stars_repo_head_hexsha": "dd2180dfe54eba7826ddd45a13ab2f5a007857d1", "max_stars_repo_licenses": ["MIT... |
[STATEMENT]
lemma dim_gen_eigenspace: assumes "jordan_nf A n_as"
shows "dim_gen_eigenspace A ev k
= (\<Sum> n \<leftarrow> map fst [(n, e)\<leftarrow>n_as . e = ev]. min k n)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. local.dim_gen_eigenspace A ev k = sum_list (map (min k) (map fst (filter (\<lambda>(n, e... | {"llama_tokens": 828, "file": "Jordan_Normal_Form_Jordan_Normal_Form_Uniqueness", "length": 8} |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 26 11:18:02 2022
This script reads daily temperature values from NOAA GHCN-Daily archive,
and calculates heatwave magnitude index. FMI Sodankylä station data is
read from FMI database.
@author: rantanem
"""
import pandas as pd
import numpy as np
... | {"hexsha": "bbf797a58ea6203b6f0ed0d96655e83a8ef918b8", "size": 5858, "ext": "py", "lang": "Python", "max_stars_repo_path": "validation/ghcn-daily_hwm.py", "max_stars_repo_name": "fmidev/resiclim-climateatlas", "max_stars_repo_head_hexsha": "b0c4c0ba6e3d189524cc89904636129733916f69", "max_stars_repo_licenses": ["MIT"], ... |
# Advent of Code 2018, Day 20
# (c) blu3r4y
from copy import copy
import networkx as nx
from parglare import Parser, Grammar
from parglare.actions import pass_single, pass_inner
GRAMMAR = r"""
root: '^' expression '$';
expression: element+;
element: direction | branch;
branch: '(' option+ ')';
option: expression |... | {"hexsha": "3bda85115bdd1a86db858a4feb8b4683840d2d5f", "size": 3218, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/day20.py", "max_stars_repo_name": "blu3r4y/AdventOfCode2018", "max_stars_repo_head_hexsha": "5ef6ee251f9184e0f66657d0eb8b5b129a6f93e5", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 2... |
# -*- coding: utf-8 -*-
from datetime import datetime
import numpy as np
from pandas._libs.tslibs import ccalendar
def test_get_day_of_year():
assert ccalendar.get_day_of_year(2001, 3, 1) == 60
assert ccalendar.get_day_of_year(2004, 3, 1) == 61
assert ccalendar.get_day_of_year(1907, 12, 31) == 365
a... | {"hexsha": "b5d562a7b5a9c2bd5d55801dce8223341a6c2d7e", "size": 593, "ext": "py", "lang": "Python", "max_stars_repo_path": "pandas/tests/tslibs/test_ccalendar.py", "max_stars_repo_name": "vimalromeo/pandas", "max_stars_repo_head_hexsha": "7c14e4f14aff216be558bf5d4d2d00b4838c2360", "max_stars_repo_licenses": ["PSF-2.0", ... |
using ConcreteStructs
using DynamicIterators
using DynamicIterators: dub
using Base.Iterators: SizeUnknown, IsInfinite
import DynamicIterators: dyniterate, evolve
export Chain
@concrete terse struct Chain{K,M} <: AbstractMeasure
κ::K
μ::M
end
function basemeasure(mc::Chain)
Chain(basemeasure ∘ mc.κ, base... | {"hexsha": "aac0739750d4e7b712cdce2352b47f3ca3eb524e", "size": 4433, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/combinators/chain.jl", "max_stars_repo_name": "jw3126/MeasureTheory.jl", "max_stars_repo_head_hexsha": "419d2f2fc3cb27c9b1d969d2e05022f3a4a01f66", "max_stars_repo_licenses": ["MIT"], "max_stars... |
import cv2
from asteroid import Asteroid
import random
import numpy as np
from spaceship import Spaceship
import config
import utils
from gym import Env
class Simulation(Env):
action_space = [0, 119, 97, 115, 100, 32]
def __init__(self):
self.reset()
def reset(self):
self.ship = Spaceshi... | {"hexsha": "f323f83010c6b09b0c2e44b9b442ab19cfb4c781", "size": 3085, "ext": "py", "lang": "Python", "max_stars_repo_path": "simulation.py", "max_stars_repo_name": "Elbrasch/AstroidsReinforcedLearning", "max_stars_repo_head_hexsha": "400d3a51d9ebc5ba48a7fba34c05c783aaff66ab", "max_stars_repo_licenses": ["MIT"], "max_sta... |
import numpy as np
from ..util.backend_functions import backend as bd
from .diffractive_element import DOE
class RectangularSlit(DOE):
def __init__(self, width, height, x0 = 0, y0 = 0):
"""
Creates a slit centered at the point (x0, y0) with width width and height height
"""
global... | {"hexsha": "ea4332171fab8e8bfd86e966092486217e810a3d", "size": 806, "ext": "py", "lang": "Python", "max_stars_repo_path": "diffractsim/diffractive_elements/rectangular_slit.py", "max_stars_repo_name": "rafael-fuente/diffractsim", "max_stars_repo_head_hexsha": "7287635d2bfa76f8b1eb24c6208796f761dd6144", "max_stars_repo_... |
#include <iostream>
#include "gtest/gtest.h"
#include <Eigen/Core>
#include "mean_curvature_solver.h"
#include "uniform_lb_operator.h"
#include "cotangent_lb_operator.h"
class MeanCurvatureSolverTest : public ::testing::Test {
protected:
MeanCurvatureSolverTest() : mUnifromMCS(mcurv::uniformLBOperatorStrategy),
... | {"hexsha": "f2bb1a16f9f2c3b52f07ba58aa8a511e9870093c", "size": 1360, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "testing/unit_tests/test_mean_curvature_solver.cpp", "max_stars_repo_name": "dybiszb/MeanCurvatureLibrary", "max_stars_repo_head_hexsha": "b168911ef6bf08b283e7a225cc006b850fe26400", "max_stars_repo_l... |
# encoding: UTF-8
# 首先写系统内置模块
import sys
import os
from datetime import datetime, timedelta, date
from time import sleep
import copy
import logging
# 第三方模块
import talib as ta
import math
import numpy
import requests
import execjs
import pykalman
# vntrader基础模块
from vnpy.trader.vtConstant import EM... | {"hexsha": "9644ba0e85872fd05c394e69bc66c662263ff8fe", "size": 80304, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/Strategy/strategy30_NonStdArbitrageExecutor.py", "max_stars_repo_name": "frikyalong/vnpy", "max_stars_repo_head_hexsha": "d8ea554e34ff285c97cc2ddb4e881a1f0a6f02d3", "max_stars_repo_licen... |
struct MultiDiscreteNonParametricSampler{T <: Real, S <: AbstractVector{T}, A <: AliasTable} <: Sampleable{Multivariate,Discrete}
support::Vector{S}
probabilities::S
aliastable::A
function MultiDiscreteNonParametricSampler{T,S}(support::Vector{S}, probs::AbstractVector{<:Real}) where {T <: Real, S<:Abs... | {"hexsha": "a95c4cd8c6f11f8ffbad2dda5058d68cae555fbb", "size": 9449, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/io/smps/sampler.jl", "max_stars_repo_name": "rtwalker/StochasticPrograms.jl", "max_stars_repo_head_hexsha": "2e59f0ad0504515855bbef411c67653b5723b3a2", "max_stars_repo_licenses": ["MIT"], "max_... |
\documentclass[main.tex]{subfiles}
\begin{document}
\subsection{GW interferometry in the TT gauge}
\marginpar{Friday\\ 2020-5-1, \\ compiled \\ \today}
% We were discussing the basics of GW interferometry.
The TT gauge is a coordinate system in which the mirrors are free-falling (in the \(xy\) plane at least, and f... | {"hexsha": "901023c7206d1500ecb99580fd900d49e9695078", "size": 14867, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "ap_second_semester/gravitational_physics/may01.tex", "max_stars_repo_name": "jacopok/notes", "max_stars_repo_head_hexsha": "805ebe1be49bbd14c6b46b24055f9fc7d1cd2586", "max_stars_repo_licenses": ["A... |
!------------------------------------------------------------------------------------------
! File: HMC_Module_Phys_ET.f90
! Author: Fabio Delogu
!
! Created on April 2, 2014, 5:19 PM
!------------------------------------------------------------------------------------------
!------------------------------------... | {"hexsha": "4ade231bf03c7d52e4abbf3dc3bec4ff0435edab", "size": 16666, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "HMC_Module_Phys_ET.f90", "max_stars_repo_name": "c-hydro/hmc-dev", "max_stars_repo_head_hexsha": "49577101335633e543ecef35f5dbf1fd48792667", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_st... |
import cv2
import numpy as np
# TODO: please add gray image support
def save_grad_img(grads, out_path):
"""
Save gradients as img
:param grads: gradients obtained from visulaziation model
:param out_path: the path to save gradients image
:return:
"""
grads = grads - grads.min()
grads ... | {"hexsha": "b2ad6ed36dfcb95f3fe9db5de60acfe665009e03", "size": 1075, "ext": "py", "lang": "Python", "max_stars_repo_path": "vis/utils.py", "max_stars_repo_name": "sunalbert/lucid.pytorch", "max_stars_repo_head_hexsha": "1bcc87a41c99bef1d64d37116c8a2440d11b0def", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 11... |
! RUN: %python %S/test_errors.py %s %flang_fc1
! Test that the interface of specific intrinsics passed as dummy arguments
! are correctly validated against actual arguments explicit interface.
intrinsic :: abs, dabs
interface
subroutine foo(f)
interface
function f(x)
real :: f
... | {"hexsha": "91ce2bfccc7f60143f7bb0442575be37af5a3d38", "size": 884, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "flang/test/Semantics/call20.f90", "max_stars_repo_name": "mkinsner/llvm", "max_stars_repo_head_hexsha": "589d48844edb12cd357b3024248b93d64b6760bf", "max_stars_repo_licenses": ["Apache-2.0"], "max... |
# Copyright 2020 KCL-BMEIS - King's College London
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed... | {"hexsha": "c23836cb9a481b39032f9d0d71bba5495db10f66", "size": 7901, "ext": "py", "lang": "Python", "max_stars_repo_path": "exetera/core/csvdataset.py", "max_stars_repo_name": "deng113jie/ExeTera", "max_stars_repo_head_hexsha": "613532a419b93a9838bf5ae5594fc7bb9738cd03", "max_stars_repo_licenses": ["Apache-2.0"], "max_... |
include("utils.jl")
@testset "Stiefel" begin
@testset "Real" begin
M = Stiefel(3,2)
@testset "Basics" begin
x = [1.0 0.0; 0.0 1.0; 0.0 0.0]
@test representation_size(M) == (3,2)
@test manifold_dimension(M) == 3
@test_throws DomainError is_manifold_poi... | {"hexsha": "cc7c34bafda2a1416236d22dbaa606157f137e2c", "size": 5655, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/stiefel.jl", "max_stars_repo_name": "manuelweisser/Manifolds.jl", "max_stars_repo_head_hexsha": "07f889a290ece01569c6c53bb0c96a5608923a0c", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
import nltk
nltk.download('stopwords')
import re
import numpy as np
import pandas as pd
from pprint import pprint
import gensim
import gensim.corpora as corpora
from gensim.utils import simple_preprocess
from gensim.models import CoherenceModel
# spacy for lemmatization
import spacy
# Plotting tools
import pyLDAvis... | {"hexsha": "003fa0288a0586e999b0d3c7cd5701cc9d0af8d2", "size": 4687, "ext": "py", "lang": "Python", "max_stars_repo_path": "daily_gratitude/daily_grat/topicmodeling.py", "max_stars_repo_name": "abigail432/daily_gratitude", "max_stars_repo_head_hexsha": "4427b4f7d5c6b7349b718a17aeac62b603f80d66", "max_stars_repo_license... |
# Modified from the SHAPE-MaP pipeline to call mutations
# in miRNA cutting assay data. Functions were kepts and
# main loop was wrapped in an if __name__ == "__main__"
# statement
#
# Part of the SHAPE-MaP data analysis pipeline (ShapeMapper).
# Counts up mutations from sequencing data.
# Copyright Steven Busan 2014
... | {"hexsha": "44b68aa9119fabfd3064d5d8ea4a1e0196daba95", "size": 6550, "ext": "py", "lang": "Python", "max_stars_repo_path": "variomics_pipeline/countMutations.py", "max_stars_repo_name": "grice/DroSeq", "max_stars_repo_head_hexsha": "4fd30f301420927eaae0c9a64cdd67155ff94321", "max_stars_repo_licenses": ["MIT"], "max_sta... |
import rpy2.robjects as ro
import rpy2.robjects.conversion as conversion
import rpy2.rinterface as rinterface
from rpy2.rinterface import SexpVector, INTSXP
import numpy
from rpy2.robjects.vectors import DataFrame, Vector, ListVector
original_conversion = conversion.py2ri
# The possible kind codes are listed at
# ... | {"hexsha": "0efe11597cf83dface429190c1d553f98539cf1c", "size": 2630, "ext": "py", "lang": "Python", "max_stars_repo_path": "tools/MethylSig/rpy2/rpy/robjects/numpy2ri.py", "max_stars_repo_name": "psnehal/MethylSig", "max_stars_repo_head_hexsha": "5efad71e71ff2515feff2e49579c856ef9a1bbd8", "max_stars_repo_licenses": ["C... |
import os
import struct
import moderngl.experimental as mgl
import numpy as np
from objloader import Obj
from PIL import Image
from pyrr import Matrix44
from example_window import Example, run_example
def local(*path):
return os.path.join(os.path.dirname(__file__), '..', *path)
class MugExample(Example):
... | {"hexsha": "aa0e42dd0faae6698555ddadcc670d7bb0313359", "size": 5284, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/experimental/mug_mockup.py", "max_stars_repo_name": "dougbrion/ModernGL", "max_stars_repo_head_hexsha": "6de8938ccd0042c1389a32b697af5f9c9d279e41", "max_stars_repo_licenses": ["MIT"], "ma... |
using ModelingToolkit, DifferentialEquations, Plots
@variables t
D = Differential(t)
function dynamics(; name, τ=0.01, a_max=300.0, V₀=300.0, x_T=5E3, y_T=0.0)
states = @variables x(t) y(t) γ(t) a(t) a_cmd(t) r(t) σ(t) λ(t) V(t)
ps = @parameters τ = τ a_max = a_max x_T = x_T y_T = y_T
eqs = [
D(x)... | {"hexsha": "c8e56eddf14a680f74cf600d6fba67db5f1a28a0", "size": 7327, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "main/LCG_e_0/main_mtk_LCG_e_0.jl", "max_stars_repo_name": "nhcho91/FlightGNC.jl", "max_stars_repo_head_hexsha": "d6a44a434c7ad124bc7271c070d86d64e639582a", "max_stars_repo_licenses": ["MIT"], "max_... |
[STATEMENT]
lemma sender_ip_valid:
"paodv i \<TTurnstile>\<^sub>A onll \<Gamma>\<^sub>A\<^sub>O\<^sub>D\<^sub>V (\<lambda>((\<xi>, _), a, _). anycast (\<lambda>m. not_Pkt m \<longrightarrow> msg_sender m = i) a)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. paodv i \<TTurnstile>\<^sub>A onll \<Gamma>\<^sub>A\<^s... | {"llama_tokens": 233, "file": "AODV_variants_d_fwdrreqs_D_Seq_Invariants", "length": 1} |
/**
@file
Copyright John Reid 2007, 2013
*/
#include "bio-pch.h"
#include "bio/defs.h"
#include "bio/matrix_test_data.h"
#include "bio/fragment_test_data.h"
#include "bio/site_test_data.h"
#include "bio/biobase_db.h"
#include "bio/biobase_data_traits.h"
#include "bio/biobase_tf.h"
#include "bio/biobase_binding_mod... | {"hexsha": "ca166150c96b96f68a674b267de83323bd7f36f0", "size": 11048, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "C++/src/bio/lib/test_data.cpp", "max_stars_repo_name": "JohnReid/biopsy", "max_stars_repo_head_hexsha": "1eeb714ba5b53f2ecf776d865d32e2078cbc0338", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
[STATEMENT]
lemma securessel2:
assumes "ssel (STMap TAddr (STValue (TUInt 256))) (STR ''balance'') [SENDER] ep env cd st = Normal ((loc, type), st')"
and "fmlookup (storage st) (STR ''Victim'') = Some s"
and "ReadL\<^sub>i\<^sub>n\<^sub>t (accessBalance (accounts st) (STR ''Victim'')) - SUMM s \<ge> bal \... | {"llama_tokens": 4944, "file": "Solidity_Reentrancy", "length": 17} |
C %W% %G%
C****************************************************************
C
C File: p_gtbase.f
C Purpose: IPF shell program to process /OLD_BASE commands
C
C Author: Walt Powell Date: 20 February 1992
C Modified: 20 February 1992
C Called by:
C
C***********************************... | {"hexsha": "26e5ed62d5405cb3cbd6947e36faa1d3f20d12d0", "size": 5211, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "ipf/p_gtbase.f", "max_stars_repo_name": "mbheinen/bpa-ipf-tsp", "max_stars_repo_head_hexsha": "bf07dd456bb7d40046c37f06bcd36b7207fa6d90", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 14,... |
import numpy as np
from utils import load_data, load_polblogs_data
dataset = "polblogs"
if dataset == "polblogs":
tmp_adj, features, labels, idx_train, idx_test = load_polblogs_data()
print (sum(sum(tmp_adj)))
print (tmp_adj.shape)
else:
_, features, labels, idx_train, idx_val, idx_test, tmp_adj = load... | {"hexsha": "46a6e4f0e5cbbd725fcf3671ea23c0d2a63f25b1", "size": 598, "ext": "py", "lang": "Python", "max_stars_repo_path": "GUA/utils_polblogs.py", "max_stars_repo_name": "Anou9531/GUA", "max_stars_repo_head_hexsha": "354acceb69656e76fb4ee296c66ae42c18cd939f", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 20, "... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import print_function
from astropy.tests.helper import pytest, remote_data
from .utils import turn_off_internet
# this contains imports plugins that configure py.test for astropy tests.
# by importing them here in conftest.py they are disc... | {"hexsha": "9bca6d3f69ffece7acf42a68a4ce9bf4d880a7c0", "size": 1261, "ext": "py", "lang": "Python", "max_stars_repo_path": "astroquery/conftest.py", "max_stars_repo_name": "AlexaVillaume/astroquery", "max_stars_repo_head_hexsha": "85402770b9c0d4b98ce9ac451f41a6be1f838076", "max_stars_repo_licenses": ["BSD-3-Clause"], "... |
#!/bin/py
#
# inexact Newton-conjugate gradient method
#
# solve:
# min f(x) = 1/2 x.t (I + mu * A) x + sigma/4 (x.t A x)^2
#
import numpy as np
def mycg(A,b,maxiter,tol,x):
""" Conjugate Gradient Method. """
""" MYCG(A,B,maxiter,tol,x0) solves the system of linear equations A*X=B """
""" for X. Th... | {"hexsha": "126e954cfba8ddb8cdc96958d593304c618f7d4a", "size": 1347, "ext": "py", "lang": "Python", "max_stars_repo_path": "inv_prob/ps2/in-cg.py", "max_stars_repo_name": "nicholasmalaya/paleologos", "max_stars_repo_head_hexsha": "11959056caa80d3c910759b714a0f8e42f986f0f", "max_stars_repo_licenses": ["MIT"], "max_stars... |
% To be compiled with pdf LaTeX
% This file is to be included into master file via \input command
% Note that there is no \begin{document} \end{document} brackets!
\newpage
\section{Control}
\label{sec:control}
%\subsection{Nomenclature}
%\mbox{}
%$\bm{s}$ - vector of wavefront sensor measurements conca... | {"hexsha": "389c71b8030994fd30db9d06e6838e9265d38942", "size": 64660, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "_docGMT/Control.tex", "max_stars_repo_name": "cmcorreia/oomao", "max_stars_repo_head_hexsha": "59787859283e89cdb8c2ee88388198f283be9abb", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 7, "... |
#
# Copyright (c) 2019-2021 James Thorne.
#
# This file is part of factual error correction.
# See https://jamesthorne.co.uk for further info.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
... | {"hexsha": "8cc1addaafbae8e66a9e0d5be99f1c045f40ba04", "size": 15912, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/error_correction/modelling/error_correction_module.py", "max_stars_repo_name": "gruentee/acl2021-factual-error-correction", "max_stars_repo_head_hexsha": "b500f589cc3e73ffa6958c7dab8c07f2535a... |
from __future__ import print_function
from time import time, ctime
from urllib2 import urlopen
import os.path
import json
import numpy as np
from backtest.data import DataSource
from backtest.util import parse_date, parse_time
def create_argument_parser(parser):
default_end = int(time())
default_start = de... | {"hexsha": "b1836247fb2be37e6bebc2e9a4e0a1e80eeb6028", "size": 3389, "ext": "py", "lang": "Python", "max_stars_repo_path": "backtest/data/cli/get.py", "max_stars_repo_name": "dead-beef/backtest", "max_stars_repo_head_hexsha": "052c558aeeffbae7c2fde0a13bcecec3ca4d6bd0", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
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