text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
|---|---|
import warnings
warnings.warn("Module is deprecated.", DeprecationWarning)
### Note, these are placeholder solutions
# Since this module is meant to offer safety wrappers around some numpy
# functions, if we can't import numpy, then gracefully handle the import error
# and define stubs.
try:
from numpy import am... | {"hexsha": "80cd9184af86f6dfdd95b15390c1655462097c14", "size": 1514, "ext": "py", "lang": "Python", "max_stars_repo_path": "enthought/util/nan_ops_for_numpy.py", "max_stars_repo_name": "enthought/etsproxy", "max_stars_repo_head_hexsha": "4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347", "max_stars_repo_licenses": ["BSD-3-Clau... |
import torch
import os
import numpy as np
from config.config import Configuration
FEATS_PATH_NPY = '/xxx/projects/tmp_extraction_features/log/feats.pth'
IMG_PATH_NPY = '/xxx/projects/tmp_extraction_features/log/img_path.npy'
def euclidean_distance(qf, gf):
m = qf.shape[0]
n = gf.shape[0]
dist_mat = torch.... | {"hexsha": "f92c023200d113634a32f02264067e0f6f98cf97", "size": 1210, "ext": "py", "lang": "Python", "max_stars_repo_path": "data-purifying-GCN/graph-clustering/convert_npy_for_gcn.py", "max_stars_repo_name": "lulujianjie/efficient-person-generation-for-reid", "max_stars_repo_head_hexsha": "1bb29c7c280e3322a65af36b37dee... |
import os
import random
import socket
from collections import deque
from typing import Any, Dict, List, Literal, cast
import cv2
import gym
import numpy as np
from gym import spaces
from gym.utils import seeding
from py4j.java_gateway import GatewayParameters, JavaGateway
from carl.envs.mario.level_image_gen import Le... | {"hexsha": "d38a792ead94b5a01924542ca744f9a002f5b7b0", "size": 6816, "ext": "py", "lang": "Python", "max_stars_repo_path": "carl/envs/mario/mario_env.py", "max_stars_repo_name": "automl/genRL", "max_stars_repo_head_hexsha": "b7382fec9006d7da768ad7252194c6c5f1b2bbd7", "max_stars_repo_licenses": ["Apache-2.0"], "max_star... |
[STATEMENT]
lemma "\<lparr>xc = x, yc = y, zc = z\<rparr> = p\<lparr>zc := z\<rparr>"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lparr>xc = x, yc = y, zc = z\<rparr> = p\<lparr>zc := z\<rparr>
[PROOF STEP]
nitpick [expect = genuine]
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lparr>xc = x, yc = y, zc =... | {"llama_tokens": 199, "file": null, "length": 2} |
from data import load_corpus, convert_id_to_text
from bert_phrase_sim import BERT_sim
from model1e_phrase_sim import BERT1E_sim
from model1f_phrase_sim import BERT1F_sim
from wordvec_based_phrase_sim import wordvec_sim
import numpy as np
import codecs, argparse
parser = argparse.ArgumentParser()
parser.add_argument("-... | {"hexsha": "57d03989a30ba7235ceb870b3cf61c59f7648eb2", "size": 10335, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/baseline_wo_ted.py", "max_stars_repo_name": "yukiar/phrase_alignment_cted", "max_stars_repo_head_hexsha": "7706ca1b8be849f2413d813ea1f3c77919b635ee", "max_stars_repo_licenses": ["MIT"], "max_... |
#https://stackoverflow.com/questions/49429368/how-to-solve-memory-issues-problems-while-multiprocessing-using-pool-map
#https://pypi.org/project/memory-profiler/
import cProfile
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
import random
import seaborn as sns
import sta... | {"hexsha": "3b9c318f9408dde84f29042ac8697428c83d6724", "size": 1763, "ext": "py", "lang": "Python", "max_stars_repo_path": "contact-tracing/code/Python/test.py", "max_stars_repo_name": "sbenthall/privacy-abm", "max_stars_repo_head_hexsha": "eb40ff0aedf0d212bdc43c2e019a29599869f7d4", "max_stars_repo_licenses": ["MIT"], ... |
import re
import numpy as np
def parse_gaussian(filename):
find_natoms = "NAtoms= "
find_energy = "SCF Done: E("
find_force = "Atomic Forces "
natoms = 0
f = open(filename, 'r')
for line in f:
if find_natoms in line:
numbers = re.findall(r'\d+', lin... | {"hexsha": "6dc83ce65e82f131e1b5508a16baaa6ef4a44df9", "size": 1326, "ext": "py", "lang": "Python", "max_stars_repo_path": "qml_md/read_forces.py", "max_stars_repo_name": "charnley/qml-md", "max_stars_repo_head_hexsha": "54fa7f4c1960e624585904c6517ab4cb21a0c916", "max_stars_repo_licenses": ["Intel"], "max_stars_count":... |
# Copyright (c) 2021, salesforce.com, inc.
# All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
# For full license text, see the LICENSE file in the repo root
# or https://opensource.org/licenses/BSD-3-Clause
import unittest
import numpy as np
from warp_drive.managers.data_manager import CUDADataManager
fr... | {"hexsha": "290306801f53b7bcc03c95691e22e4b3bb80e649", "size": 3247, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/warp_drive/test_data_manager.py", "max_stars_repo_name": "MetaMind/warp-drive", "max_stars_repo_head_hexsha": "ecc17aae6c75a00c46b0e9f3297963f1beb697c0", "max_stars_repo_licenses": ["BSD-3-C... |
# import the necessary packages
from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
import numpy as np
import argparse
import cv2
import os
class detector:
def __init__(self,save_path):
... | {"hexsha": "655741a08c070e027933c3ca6c9d15d706b27b8c", "size": 3569, "ext": "py", "lang": "Python", "max_stars_repo_path": "utils/test_face_detectors.py", "max_stars_repo_name": "visiont3lab/mask-detector-covid", "max_stars_repo_head_hexsha": "48d28fffa1278ae48657938262b17b8bd07e6986", "max_stars_repo_licenses": ["MIT"... |
import tensorflow as tf
import numpy as np
import librosa
import librosa.filters
if __name__ == "__main__":
try:
tf.enable_eager_execution()
except ValueError as e:
if e.args[0] != 'tf.enable_eager_execution must be called at program startup.':
raise e
# persistent variables
_mel... | {"hexsha": "b4d5c0290340bc38ddb2ed54f0c236f6fb8a2e46", "size": 3987, "ext": "py", "lang": "Python", "max_stars_repo_path": "melspec.py", "max_stars_repo_name": "ljuvela/GELP", "max_stars_repo_head_hexsha": "6d1084aa7471530224c8f0498efcce696069ec87", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 27, "max... |
#! /bin/env python
import os
import argparse
import numpy as np
import pandas as pd
import atat_module
import matplotlib as mpl
pd.set_option('display.max_rows', None)
parser = argparse.ArgumentParser(
description="Print the output of a file generated by a program in ATAT.")
parser.add_argument('-c', nargs='*', m... | {"hexsha": "1d2effe2a5511d803cecbc70ba007660a3ba1321", "size": 4071, "ext": "py", "lang": "Python", "max_stars_repo_path": "print-as-df.py", "max_stars_repo_name": "terencezl/atat-tools", "max_stars_repo_head_hexsha": "f61d772a58f0c768fcbb33474eb3bcbd4f68d926", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nul... |
\documentclass[apjl]{emulateapj}
%\documentclass[letterpaper,12pt,preprint]{aastex}
% packages
\usepackage{amssymb,amsmath,amsbsy}
\usepackage{booktabs}
\usepackage{multirow}
\usepackage{url}
% commands
\newcommand{\given}{\,|\,}
\newcommand{\dd}{\mathrm{d}}
\newcommand{\transpose}[1]{{#1}^{\mathsf{T}}}
\newcommand{\... | {"hexsha": "7a16821f98c668dcbc30168aaeeca02d8a7886e6", "size": 41842, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "documents/letter/ms.tex", "max_stars_repo_name": "adrn/tilt-shift", "max_stars_repo_head_hexsha": "23d1a024bcec4061de09df834ad7cbe97b9f37ba", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
% AUTORIGHTS
% Copyright (C) 2007 Princeton University
%
% This file is part of Ferret Toolkit.
%
% Ferret Toolkit is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2, or (at your option)
... | {"hexsha": "7a37ce5519f78b228661e00b638d2423a02fcd43", "size": 3111, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "pkgs/netapps/netferret/src/server/doc/spec/index.tex", "max_stars_repo_name": "manggoguy/parsec-modified", "max_stars_repo_head_hexsha": "d14edfb62795805c84a4280d67b50cca175b95af", "max_stars_repo_l... |
"""Iterative deconvolution solvers"""
import warnings
import numpy as np
from scipy import optimize, signal
from scipy.sparse.linalg import LinearOperator
from .utils import (convolution_matrix, convolution_output_size,
least_squares_cost, asanyoperator)
def least_squares(A, y, gamma_L2=0, gam... | {"hexsha": "9c97bd0e2ca9963f0e71090047d1e199c2cbe665", "size": 4485, "ext": "py", "lang": "Python", "max_stars_repo_path": "regper/iterative.py", "max_stars_repo_name": "jakevdp/regper", "max_stars_repo_head_hexsha": "bd2361a7bdf27a61c6b06ea509b3f25f5786d814", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_cou... |
import numpy as np
import pandas as pd
"""this actually includes dissimilarity analysis functions, not just distances
"""
def dissimilarity_nominal(dataset=None, p=None, m=None, weights=None):
"""computes the dissimilarity b/t two objects (for nominal
attributes). Can input either a column dataset or directl... | {"hexsha": "db55a20389559b300afd539ac02acf73de09238d", "size": 17321, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/distances.py", "max_stars_repo_name": "summeryriddles/geopolymeric-tribbles", "max_stars_repo_head_hexsha": "70407e4b754cd6cbafe603755ae1b4d3679115e0", "max_stars_repo_licenses": ["MIT"],... |
let
counter = 0
global clearcounter() = counter = 0
global counter!() = (counter += 1; (counter > 100) && throw("Excessive Recursion Error"))
end
| {"hexsha": "284b6c4c6a89a4a6e822b1d93e9768e224c1436b", "size": 158, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/main/counter.jl", "max_stars_repo_name": "UnofficialJuliaMirrorSnapshots/AbstractLogic.jl-bd85187e-0531-4a3e-9fea-713204a818a2", "max_stars_repo_head_hexsha": "1b8adac10854471ec7ce83b9039cdeb1e4... |
# * Ponderomotive potential
@doc raw"""
ponderomotive_potential(f)
Return the [ponderomotive
potential](https://en.wikipedia.org/wiki/Ponderomotive_energy)
``U_p``, which is the cycle-average quiver energy of a free electron
in an electromagnetic field `f`. It is given by
```math
U_p =
\frac{e^2E_0^2}{4m\omega^2}... | {"hexsha": "8b00fe83ef44e28980dd1573153bf56efdd2cc79", "size": 2424, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/strong_field_properties.jl", "max_stars_repo_name": "jagot/ElectricFields.jl", "max_stars_repo_head_hexsha": "626fcd1beebf472487f11cd588661e2d5303de7d", "max_stars_repo_licenses": ["MIT"], "max... |
[STATEMENT]
lemma update_eqD: "update k v al = update k v' al' \<Longrightarrow> v = v'"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. update k v al = update k v' al' \<Longrightarrow> v = v'
[PROOF STEP]
proof (induct al arbitrary: al')
[PROOF STATE]
proof (state)
goal (2 subgoals):
1. \<And>al'. update k v [] = ... | {"llama_tokens": 998, "file": null, "length": 11} |
import numpy as np
# quaternion representation: [x, y, z, w]
# JPL convention
def skew(vec):
"""
Create a skew-symmetric matrix from a 3-element vector.
"""
x, y, z = vec
return np.array([
[0, -z, y],
[z, 0, -x],
[-y, x, 0]])
def to_rotation(q):
"""
... | {"hexsha": "0013e0baf4e307abb23344d8a3e1f39151f3bd20", "size": 5227, "ext": "py", "lang": "Python", "max_stars_repo_path": "utils.py", "max_stars_repo_name": "shanmo/OrcVIO-Stereo-Python", "max_stars_repo_head_hexsha": "849ddaeb4623e89ef84d0bf954cd76bb0cd30351", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 3,... |
# from Par_file
const ANGULAR_WIDTH_XI_IN_DEGREES_VAL = 60.0
const ANGULAR_WIDTH_ETA_IN_DEGREES_VAL = 60.0
const NEX_XI_VAL = 336
const NEX_ETA_VAL = 336
const REGIONAL_MOHO_MESH = true
# some constant values
const R_UNIT_SPHERE = one(Float64)
const NGLLX = 5
const NGLLY = 5
const NGLLZ = 5
const MIDX = 3
const MIDY ... | {"hexsha": "e8506af9f258ec9c7aac6829a691ff34a70dee2d", "size": 568, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "FWI_tools/specfem_helper.jl/src/setting/constants.jl", "max_stars_repo_name": "ziyixi/SeisScripts", "max_stars_repo_head_hexsha": "a484bc1747eae52b2441f0bfd47ac7e093150f1d", "max_stars_repo_licenses... |
# Copyright (c) 2020,21 NVIDIA CORPORATION & AFFILIATES.. All rights reserved.
#
# 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 re... | {"hexsha": "3ead941ef015c68bb6786daecaafb421a9840f3c", "size": 4273, "ext": "py", "lang": "Python", "max_stars_repo_path": "utils/utils_functions.py", "max_stars_repo_name": "nv-tlabs/DIB-R-Single-Image-3D-Reconstruction", "max_stars_repo_head_hexsha": "faa6364cc6ec464f81f960a9fa6b55bbf3443d5f", "max_stars_repo_license... |
/*
Test tree
Ref : https://www.boost.org/doc/libs/1_75_0/libs/test/doc/html/boost_test/tests_organization/test_tree.html
Boost.test，其 Unit Test Framework，會經由 Test tree 結構，逐步執行開發者設計的測試內容，其順序依序如下
MAIN / MODULE
└ SUITE
└ CASE
*/
// 定義測試模組名稱
// 在此可選用 BOOST_TEST_MAIN、BOOST_TEST_MODULE
#define BOOST_TEST_MODULE Exam... | {"hexsha": "035099dc2a9d1fa18ba4b7f2f8509e02fc34ccc9", "size": 691, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/test/base/main.cpp", "max_stars_repo_name": "eastmoon/tutorial-c-boost", "max_stars_repo_head_hexsha": "06530df17ea1fafce54c820a50f9d092fbd3ec90", "max_stars_repo_licenses": ["BSL-1.0"], "max_sta... |
# -*- coding: utf-8 -*-
__all__ = ["disk_model"]
import numpy as np
import scipy.constants as sc
from astropy.convolution import convolve_fft
from astropy.convolution import Gaussian2DKernel
def disk_model(inc=30., mstar=1.0, dist=100., Npix=128, r_max=150., vchan=200.,
Nchan=64, noise=2.0, Tkin0=40.... | {"hexsha": "a8be76b67ec2c1d9c448d87294437058294bfc3e", "size": 3457, "ext": "py", "lang": "Python", "max_stars_repo_path": "notebooks/diskmodel.py", "max_stars_repo_name": "mirca/bettermoments", "max_stars_repo_head_hexsha": "50000f3db738ba11d30504ad00e3a4452ae23f64", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
[STATEMENT]
lemma ffb_prop: "fb\<^sub>\<F> f = \<partial> \<circ> bd\<^sub>\<F> (op\<^sub>K f) \<circ> \<partial>"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. fb\<^sub>\<F> f = \<partial> \<circ> bd\<^sub>\<F> (op\<^sub>K f) \<circ> \<partial>
[PROOF STEP]
by (simp add: ffb_def map_dual_def) | {"llama_tokens": 132, "file": "Transformer_Semantics_Kleisli_Transformers", "length": 1} |
[STATEMENT]
lemma (in \<Z>) dghm_dag_Rel_is_iso_dghm:
"\<dagger>\<^sub>D\<^sub>G\<^sub>.\<^sub>R\<^sub>e\<^sub>l \<alpha> : op_dg (dg_Rel \<alpha>) \<mapsto>\<mapsto>\<^sub>D\<^sub>G\<^sub>.\<^sub>i\<^sub>s\<^sub>o\<^bsub>\<alpha>\<^esub> dg_Rel \<alpha>"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<dagger>\<... | {"llama_tokens": 7464, "file": "CZH_Foundations_czh_digraphs_CZH_DG_Rel", "length": 28} |
import unittest
import numpy as np
from ensemble_boxes import *
class TestWBF(unittest.TestCase):
def test_box_and_model_avg(self):
boxes_list = [
[
[0.10, 0.10, 0.50, 0.50], # cluster 2
[0.11, 0.11, 0.51, 0.51], # cluster 2
[0.60, 0.60, 0.80, 0.... | {"hexsha": "e8b88f4c6826437bfe631eb35faefab982061d95", "size": 10535, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_bbox.py", "max_stars_repo_name": "Sergey-Zlobin/Weighted-Boxes-Fusion", "max_stars_repo_head_hexsha": "773ed6f9513ade442c0f89885f3a36d95cf0629d", "max_stars_repo_licenses": ["MIT"], "m... |
[STATEMENT]
lemma word_less_nowrapI: "x < z - k \<Longrightarrow> k \<le> z \<Longrightarrow> 0 < k \<Longrightarrow> x < x + k"
for x z k :: "'a::len word"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>x < z - k; k \<le> z; 0 < k\<rbrakk> \<Longrightarrow> x < x + k
[PROOF STEP]
by uint_arith | {"llama_tokens": 128, "file": null, "length": 1} |
# MINLP written by GAMS Convert at 04/21/18 13:51:17
#
# Equation counts
# Total E G L N X C B
# 4241 1603 946 1692 0 0 0 0
#
# Variable counts
# x b i s1s s2s sc ... | {"hexsha": "76811ddbffadd4c5e4dfe16ed523124e4b7d0e24", "size": 517559, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/examples/minlplib/crudeoil_lee2_08.py", "max_stars_repo_name": "ouyang-w-19/decogo", "max_stars_repo_head_hexsha": "52546480e49776251d4d27856e18a46f40c824a1", "max_stars_repo_licenses": ["... |
import unittest
import numpy as np
import torch
from torch.autograd import Variable, grad, gradcheck
from qmctorch.wavefunction.jastrows.elec_elec_nuclei.jastrow_factor_electron_electron_nuclei import JastrowFactorElectronElectronNuclei
from qmctorch.wavefunction.jastrows.elec_elec_nuclei.kernels.boys_handy_jastrow_ke... | {"hexsha": "b2d31fef1c497064ac8254e5ff8ad35b26f38b7c", "size": 4359, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/wavefunction/jastrows/elec_elec_nuc/test_three_body_jastrow_boys_handy.py", "max_stars_repo_name": "NLESC-JCER/QMCTorch", "max_stars_repo_head_hexsha": "c56472cd3e9cc59f2e01a880e674b7270d2cd... |
function z = quad_pos_over_lin( x, y, dim )
%QUAD_POS_OVER_LIN Sum of squares of positives over linear.
% Z=QUAD_POS_OVER_LIN(X,Y), where X is a vector and Y is a scalar, is equal to
% SUM(MAX(X,0).^2)./Y if Y is positive, and +Inf otherwise. Both X and Y must
% be real.
%
% For matrices, QUAD_POS_OVER_LIN(X,Y... | {"author": "goodshawn12", "repo": "REST", "sha": "e34ce521fcb36e7813357a9720072dd111edf797", "save_path": "github-repos/MATLAB/goodshawn12-REST", "path": "github-repos/MATLAB/goodshawn12-REST/REST-e34ce521fcb36e7813357a9720072dd111edf797/dependencies/BCILAB/dependencies/cvx-1.21.b795/functions/quad_pos_over_lin.m"} |
!##############################################################################
! ________ _____ ______________
! / ____/ |/ / / / /_ __/ _/ /
! / /_ / /|_/ / / / / / / / // /
! / __/ / / / / /_/ / / / _/ // /___
! /_/ /_/ /_/\____/ /_/ /___/_____/
!
! Copy... | {"hexsha": "91f3c065bec1092b9483e1772fb367808dfa557b", "size": 12246, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/datastructs/list.f90", "max_stars_repo_name": "princemahajan/FMUTIL", "max_stars_repo_head_hexsha": "30f19755291276287a2ab0cbf25b466f8a4be8d7", "max_stars_repo_licenses": ["Apache-2.0"], "m... |
# MIT License
#
# Copyright (c) 2017 Tom Runia
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, pu... | {"hexsha": "343f56a583e8caa058ebadc3c837a30874dad286", "size": 6647, "ext": "py", "lang": "Python", "max_stars_repo_path": "feature_extraction/example_classification.py", "max_stars_repo_name": "ec500-software-engineering/project-07-aurora-borealis-classification", "max_stars_repo_head_hexsha": "9ad1627741a6b3af4a9ba11... |
[STATEMENT]
lemma exec_mbindFStop_E:
assumes seq : "(\<sigma> \<Turnstile> (s \<leftarrow> mbind\<^sub>F\<^sub>a\<^sub>i\<^sub>l\<^sub>S\<^sub>t\<^sub>o\<^sub>p (a#S) ioprog ; (P s)))"
and some: "\<And>b \<sigma>'. ioprog a \<sigma> = Some(b,\<sigma>') \<Longrightarrow> (\<sigma>'\<Turnstile> (s \<leftarrow> mbind\... | {"llama_tokens": 2298, "file": "Clean_src_Symbex_MonadSE", "length": 18} |
function CatStr(s1::Array,sep::AbstractString,s2::Array)
#Assume s1 and s2 are arrays of String
#Also sep is a string
s12 = s1 .* [sep] .* s2
return s12
end
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module Prinz
using ModelingToolkit
using ..NeuronBuilder
import ..get_parameters, ..get_states, ..default_params, ..default_states
include("channels.jl")
include("calc_dynamics.jl")
export get_parameters, get_states, default_params, default_states
end
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//------------------------------------------------------------------------------
/// \file BinaryTrees_tests.cpp
/// \date 20201023 03:44
//------------------------------------------------------------------------------
#include "DataStructures/BinaryTrees.h"
#include <boost/test/unit_test.hpp>
#include <string>
#inclu... | {"hexsha": "fdef3fd2d83d39ae79ff4f1f73d122e21275c9c9", "size": 13990, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "Voltron/Source/UnitTests/DataStructures/BinaryTrees_tests.cpp", "max_stars_repo_name": "ernestyalumni/HrdwCCppCUDA", "max_stars_repo_head_hexsha": "17ed937dea06431a4d5ca103f993ea69a6918734", "max_s... |
import numpy as np
import math
import pandas as pd
import sys
import minimize as mini
delta = 10e-4
if len(sys.argv) > 1:
method = sys.argv[1]
else:
method = "newton"
print('method:',method)
# f(x, y) = 100(y-x²)² + (1-x)²
def f(entry):
x, y = entry[0], entry[1]
return 100*(y-x**2)**2 + (1-x)**2
def... | {"hexsha": "cfeb1bc3716792c418317a5db577ff66e4d47927", "size": 824, "ext": "py", "lang": "Python", "max_stars_repo_path": "proj.py", "max_stars_repo_name": "gabriel-valle/minimizer", "max_stars_repo_head_hexsha": "eb3e42ca5fa4667c712ad2228a6c8af3bdb73185", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "m... |
import os.path as osp
import tempfile
import mmcv
from .builder import DATASETS
from .custom import CustomDataset
import numpy as np
from PIL import Image
@DATASETS.register_module()
class PascalVOCDataset(CustomDataset):
"""Pascal VOC dataset.
Args:
split (str): Split txt file for Pascal VOC.
""... | {"hexsha": "2b670ebef044f6006075d9f38f82e6ada40e5c25", "size": 5015, "ext": "py", "lang": "Python", "max_stars_repo_path": "mmseg/datasets/voc.py", "max_stars_repo_name": "aim-uofa/NRD_decoder", "max_stars_repo_head_hexsha": "275f0a1e74bb24cd8555fa8bcccb488d5bf1ed8c", "max_stars_repo_licenses": ["Apache-2.0"], "max_sta... |
[STATEMENT]
lemma strongBisimWeakPsiCong:
fixes \<Psi> :: 'b
and P :: "('a, 'b, 'c) psi"
and Q :: "('a, 'b, 'c) psi"
assumes "\<Psi> \<rhd> P \<sim> Q"
shows "\<Psi> \<rhd> P \<doteq> Q"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<Psi> \<rhd> P \<doteq> Q
[PROOF STEP]
using assms
[PROOF STATE]
p... | {"llama_tokens": 2037, "file": "Psi_Calculi_Weak_Psi_Congruence", "length": 19} |
'''
Author: Shangjie Lyu
GitHub: https://github.com/josephlyu
The figures for the UK page, using data from
Public Health Englend's COVID-19 UK API and
Oxford University's GitHub repository.
Link1: https://coronavirus.data.gov.uk/developers-guide
Link2: https://github.com/OxCGRT/covid-policy-tracker
'''
i... | {"hexsha": "3823ff308d4818e381654aed783a93fa728cc392", "size": 23831, "ext": "py", "lang": "Python", "max_stars_repo_path": "figures/figures_uk.py", "max_stars_repo_name": "josephlyu/Covid19-UK-Dashboard", "max_stars_repo_head_hexsha": "e6b0ac4c01d4a6426172589a4b8fe927aeed6901", "max_stars_repo_licenses": ["Apache-2.0"... |
import numpy as np
import keras
import tensorflow as tf
import keras.backend as K
from keras.activations import tanh, softmax
from keras.layers import LSTM, Dense, Layer, Lambda
class PointerAttention(Layer):
'''
https://www.tensorflow.org/text/tutorials/nmt_with_attention
'''
def __init__(self, units... | {"hexsha": "4801103bc406477478cb444cf1e4d78737a626b9", "size": 3689, "ext": "py", "lang": "Python", "max_stars_repo_path": "pointer_lstm.py", "max_stars_repo_name": "hakeemta/pointer-networks", "max_stars_repo_head_hexsha": "8c0e80fd63d25c560a9b5f8eb0d4a0354fc32e6a", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#include <boost/property_tree/ptree.hpp>
#include <boost/property_tree/json_parser.hpp>
#include <boost/foreach.hpp>
#include <iostream>
#include <libnotify.h>
#ifdef __clang__
# define COMPILER "clang++"
#else
# define COMPILER "g++"
#endif
using namespace std;
struct coordinate_t {
double x;
double y;
double... | {"hexsha": "4883ef5fb8101bb66e28f7ad82b34c3e2497c7e1", "size": 1812, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "json/test_boost_ptree.cpp", "max_stars_repo_name": "mkitto/benchmarks", "max_stars_repo_head_hexsha": "070e222ef648c23e645a8c3fafcb25fe2288d817", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
function RBMs.sample_h_from_v(rbm::CenteredRBM, v::AbstractArray; β::Real = true)
inputs = RBMs.inputs_v_to_h(rbm, v)
return RBMs.transfer_sample(hidden(rbm), inputs; β)
end
function RBMs.sample_v_from_h(rbm::CenteredRBM, h::AbstractArray; β::Real = true)
inputs = RBMs.inputs_h_to_v(rbm, h)
return RBMs... | {"hexsha": "7591dc54db1ddd3257a66c158eb00447499fd5f7", "size": 1293, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/sampling.jl", "max_stars_repo_name": "cossio/CenteredRBMs.jl", "max_stars_repo_head_hexsha": "20076d5c4c5c1a95fbdf098e9616caa400b8d2f8", "max_stars_repo_licenses": ["MIT"], "max_stars_count": n... |
[STATEMENT]
lemma omega_subid: "\<Omega> x (d y) \<le> d y"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<Omega> x (d y) \<le> d y
[PROOF STEP]
by (simp add: Omega_def local.a_subid_aux2) | {"llama_tokens": 91, "file": "KAD_Modal_Kleene_Algebra_Applications", "length": 1} |
#ifndef TRIPS_HPP
#define TRIPS_HPP
#include <vector>
#include <boost/unordered_set.hpp>
//struct Trip {
// // last attribute is the index
// // So should be size + 1
// uint64_t * attributes;
//};
//struct TripKey {
// uint64_t * attributes;
//};
typedef uint64_t Trip;
typedef uint64_t TripKey;
typedef std::vect... | {"hexsha": "508b1239dc328279868e7eed4ce058e4a6f09999", "size": 409, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/mongo/db/kdtree/Trip.hpp", "max_stars_repo_name": "harishd10/mongodb", "max_stars_repo_head_hexsha": "69dd944e2e7cac2a3f56c99f2a20d45651b8db24", "max_stars_repo_licenses": ["Apache-2.0"], "max_st... |
import numpy as np
from scipy.stats import kurtosis, skew
class descriptor_stats(object):
'''
A class containing standardized statistics to compute over each
representation
These statistics include:
mean, standard deviation, kurtosis, and skewness
Population covariance is also considered ... | {"hexsha": "03a1c41524b7d401567623489a4be3002f7906b3", "size": 7027, "ext": "py", "lang": "Python", "max_stars_repo_path": "pyxtal_ml/descriptors/stats.py", "max_stars_repo_name": "qzhu2017/ML-DOS", "max_stars_repo_head_hexsha": "c58ebdfc77746175771af0862ed5737c4eaa3eec", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
# inference with mxnet
import mxnet as mx
from tensorflow.keras.preprocessing import image
import numpy as np
from collections import namedtuple
Batch = namedtuple('Batch', ['data'])
ctx = mx.gpu()
# load model
sym, arg_params, aux_params = mx.model.load_checkpoint('models/retinaface-R50', 0)
mod = mx.mod.Module(sy... | {"hexsha": "b5ae768d822ab300d8222f73c3c96d67d8f3c47e", "size": 988, "ext": "py", "lang": "Python", "max_stars_repo_path": "mxnet_inference.py", "max_stars_repo_name": "pmathewjacob/insightface-attendance", "max_stars_repo_head_hexsha": "447b669e3d176bb1c78a6108334d6470a8fb25a8", "max_stars_repo_licenses": ["MIT"], "max... |
"""Deep Dreaming using Caffe and Google's Inception convolutional neural network."""
# pylint: disable=invalid-name, wrong-import-position
from collections import namedtuple, OrderedDict
import logging
import multiprocessing as mp
import os
from pathlib import Path
import queue
import re
import sys
os.environ['GLOG_... | {"hexsha": "db6bc89eee48e160d7d46e5de3dc53e687ea8443", "size": 18584, "ext": "py", "lang": "Python", "max_stars_repo_path": "deep_dream/deep_dream.py", "max_stars_repo_name": "THinnerichs/deep_dream", "max_stars_repo_head_hexsha": "ae4dafb4128cbda4b4a8bbdcb4aa69c2d2cdf7f0", "max_stars_repo_licenses": ["MIT"], "max_star... |
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 05 13:41:23 2018
@author: DanielM
"""
from neuron import h
import numpy as np
import net_globalrev
from burst_generator_inhomogeneous_poisson import inhom_poiss
import os
import argparse
import scipy.stats as stats
# Parse command line inputs
# Command line signature:
#... | {"hexsha": "e63634bada9a69952abe5c892a56362210213224", "size": 2352, "ext": "py", "lang": "Python", "max_stars_repo_path": "rd/nw_testing.py", "max_stars_repo_name": "danielmk/pyDentateeLife2020", "max_stars_repo_head_hexsha": "b4a9f2beaa0c74dbc9583e2cf228856612596f8a", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
# -*- coding: utf-8 -*-
"""
Hosmer-Lemeshow test
@author: Alex (stackoverflow)
"""
import pandas as pd
import numpy as np
from scipy.stats import chi2
def hosmer_lemeshow_test(pihat,real_label):
# pihat=model.predict()
pihatcat=pd.cut(pihat, np.percentile(pihat,[0,25,50,75,100]),labels=False,include_lowest=T... | {"hexsha": "7270b5a0c11d85091d6ef7a76f0cd6710fb00897", "size": 1713, "ext": "py", "lang": "Python", "max_stars_repo_path": "eslearn/statistical_analysis/el_hosmer_lemeshow_test.py", "max_stars_repo_name": "lichao312214129/easylearn", "max_stars_repo_head_hexsha": "e77b51b26e0c75b3a4d59dd5a71cf1b63ac4347d", "max_stars_r... |
from classes.trainers.Trainer import Trainer
from classes.cv.FeatureSelector import FeatureSelector
from classes.factories.ClassifiersFactory import ClassifiersFactory
from classes.handlers.ParamsHandler import ParamsHandler
from classes.factories.DataSplitterFactory import DataSplitterFactory
import numpy as np
impor... | {"hexsha": "a51b81c354e7fb78730c380680aaac0f3d102923", "size": 9092, "ext": "py", "lang": "Python", "max_stars_repo_path": "classes/trainers/TaskFusionTrainer.py", "max_stars_repo_name": "canary-for-cognition/multimodal-ml-framework", "max_stars_repo_head_hexsha": "379963e2815165b28a28c983d32dd17656fba9a9", "max_stars_... |
#!/usr/bin/env python3
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from mpl_tools.helpers import add_to_labeled_items, add_colorbar, savefig
from matplotlib.colors import LinearSegmentedColormap
import pickle
import itertools as it
dchi2 = r'$\Delta \chi^2$'
colors... | {"hexsha": "31afb5d4d3485165777a032f401f19d70bc3a733", "size": 14368, "ext": "py", "lang": "Python", "max_stars_repo_path": "packages/junosens-v2/macro/plot-scanedges-v1.py", "max_stars_repo_name": "gnafit/gna", "max_stars_repo_head_hexsha": "c1a58dac11783342c97a2da1b19c97b85bce0394", "max_stars_repo_licenses": ["MIT"]... |
module GraphKernels
using Graphs
using SimpleValueGraphs
using SimpleValueGraphs: AbstractValGraph
using LinearAlgebra: dot, diag
using Statistics: mean, std
using LIBSVM
using Random: MersenneTwister, randperm
using ThreadsX
import LIBSVM: svmtrain, svmpredict
using KernelFunctions: kernelmatrix, kernelmatrix_diag
... | {"hexsha": "e415f6fc2194b0e57adc72a5335b6241bfc79d6b", "size": 2588, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/GraphKernels.jl", "max_stars_repo_name": "simonschoelly/GraphKernels.jl", "max_stars_repo_head_hexsha": "f04797de0b86a39172b6adbcfcee35ec4b39f91b", "max_stars_repo_licenses": ["MIT"], "max_star... |
MODULE m_brzone
use m_juDFT
!
! This subroutine finds the corner-points, the edges, and the
! faces of the irreducible wedge of the brillouin zone (IBZ).
!
CONTAINS
SUBROUTINE brzone(
> rcmt,nsym,idrot,mface,nbsz,nv48,
= cpoint,
< ... | {"hexsha": "73dec495b2e1e9fb00d26c029f5f376c17b5f287", "size": 18291, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "kpoints/brzone.f", "max_stars_repo_name": "MRedies/FLEUR", "max_stars_repo_head_hexsha": "84234831c55459a7539e78600e764ff4ca2ec4b6", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "... |
#!/usr/bin/env python
import rospy
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped, Pose
from styx_msgs.msg import TrafficLightArray, TrafficLight
from styx_msgs.msg import Lane
from sensor_msgs.msg import Image
from cv_bridge import CvBridge
from light_classification.tl_classifier import TLCla... | {"hexsha": "d39b1292efffab60d87febd858743d52b35a7921", "size": 9707, "ext": "py", "lang": "Python", "max_stars_repo_path": "ros/src/tl_detector/tl_detector.py", "max_stars_repo_name": "roshea6/CarND-Capstone", "max_stars_repo_head_hexsha": "aec95e200dccad5488df269353b04fc067557890", "max_stars_repo_licenses": ["MIT"], ... |
(* Title: Inductive definition of termination
Author: Tobias Nipkow, 2001/2006
Maintainer: Tobias Nipkow
*)
theory PsTermi imports PsLang begin
subsection\<open>Termination\<close>
inductive
termi :: "com \<Rightarrow> state \<Rightarrow> bool" (infixl "\<down>" 50)
where
Do[iff]: "f s \<not... | {"author": "data61", "repo": "PSL", "sha": "2a71eac0db39ad490fe4921a5ce1e4344dc43b12", "save_path": "github-repos/isabelle/data61-PSL", "path": "github-repos/isabelle/data61-PSL/PSL-2a71eac0db39ad490fe4921a5ce1e4344dc43b12/SeLFiE/Example/afp-2020-05-16/thys/Abstract-Hoare-Logics/Procs/PsTermi.thy"} |
### ============== ### ============== ###
## Behavioural Rules Model ##
## Martin Zumaya Hernandez ##
## EXAMPLE SIMULATION SCRIPT ##
### ============== ### ============== ###
### ============ INCLUDE PACKAGES ============ ###
@everywhere using CollectiveDynamics.BehaviouralRules
##... | {"hexsha": "a6d92368e874818b38d3061801777ea7bc8c971f", "size": 3868, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "examples/behavioural_rules_simulation.jl", "max_stars_repo_name": "carterian8/CollectiveDynamics.jl", "max_stars_repo_head_hexsha": "add9604e8132646da5a1f66a41239c8fa86c363a", "max_stars_repo_licen... |
/**
* @file descartes_tesseract_kinematics.h
* @brief Implememntatino of a wrapper around tesseract kinematics for the descartes_light kinematics interface
*
* @author Matthew Powelson
* @author Levi Armstrong
* @date September 17, 2019
* @version TODO
* @bug No known bugs
*
* @copyright Copyright (c) 2019, S... | {"hexsha": "1319790e02a0d2c88e593941b7b08020b12f0887", "size": 7802, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "tesseract/tesseract_planning/tesseract_motion_planners/include/tesseract_motion_planners/descartes/impl/descartes_tesseract_kinematics.hpp", "max_stars_repo_name": "steviedale/tesseract", "max_stars... |
import sys
import pytest
import torch
import torch.nn as nn
import numpy as np
from fmoe.gates import NaiveGate
from fmoe.layers import FMoE
from fmoe.linear import FMoELinear
from fmoe.megatron.layers import _megatron_init_method
def _assert_numerical(names, moe_out_list, raw_out_list, rank, precision=1e-3):
f... | {"hexsha": "e040d5f9d0ad7469cf012a33f807596d3a329ecd", "size": 4999, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_mimo.py", "max_stars_repo_name": "dumpmemory/fastmoe", "max_stars_repo_head_hexsha": "5083a7367f2defcf5e1022dcdce39022acf5ca11", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_co... |
/*=============================================================================
Copyright (c) 2001-2011 Joel de Guzman
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)
=========================================... | {"hexsha": "797af98ffa6f52d8ffebe491800d36631d8ad4b6", "size": 2698, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "openbmc/build/tmp/deploy/sdk/witherspoon-2019-08-08/sysroots/armv6-openbmc-linux-gnueabi/usr/src/debug/boost/1.69.0-r0/boost_1_69_0/boost/fusion/support/category_of.hpp", "max_stars_repo_name": "sot... |
[STATEMENT]
lemma map_le_on_disj_right:
"\<lbrakk> h' \<subseteq>\<^sub>m h ; h\<^sub>0 \<bottom> h\<^sub>1 ; h' = h\<^sub>1 ++ h\<^sub>0 \<rbrakk> \<Longrightarrow> h\<^sub>0 \<subseteq>\<^sub>m h"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>h' \<subseteq>\<^sub>m h; h\<^sub>0 \<bottom> h\<^sub>1; h' ... | {"llama_tokens": 200, "file": "Separation_Algebra_Map_Extra", "length": 1} |
import os
import random
import sys
sys.path.append('../')
import pandas as pd
import numpy as np
import talib
from pandas_datareader import data as pdr
import fix_yahoo_finance as yf
import xgboost as xgb
import operator
from sklearn.svm import SVC
from sklearn.model_selection import GridSearchCV
from sklearn.metrics... | {"hexsha": "3a9fc6280ba3fd4915c90e93a412191d5b7416d4", "size": 10600, "ext": "py", "lang": "Python", "max_stars_repo_path": "source_project/experiments/stock.py", "max_stars_repo_name": "leckie-chn/SemEval17-5", "max_stars_repo_head_hexsha": "5ca1e1f3972c58c32305f8614cfecc5e5de646cd", "max_stars_repo_licenses": ["Apach... |
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE "C/C++ Unit Tests for ArangoDB"
#include <boost/test/unit_test.hpp>
| {"hexsha": "2abd9e17a4cf98f73ba8ee13d77bc1a1d7dba1f7", "size": 122, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "UnitTests/Basics/Runner.cpp", "max_stars_repo_name": "morsdatum/ArangoDB", "max_stars_repo_head_hexsha": "9cfc6d5cd50b8f451ebdedd77e2c5257fa72a573", "max_stars_repo_licenses": ["Apache-2.0"], "max_st... |
// Copyright 2014 Jonathan Graehl-http://graehl.org/
//
// 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 applicab... | {"hexsha": "5a4cae2af58cb66e41974e9844e32ba04dd0091e", "size": 1508, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "graehl/shared/shell.hpp", "max_stars_repo_name": "graehl/carmel", "max_stars_repo_head_hexsha": "4a5d0990a17d0d853621348272b2f05a0dab3450", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_coun... |
# -*- coding: utf-8 -*-
import xgboost as xgb
import pandas as pd
import numpy as np
from utils import *
from os import path
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.preprocessing import StandardScaler
project_path = path.join(path.dirname(__file__... | {"hexsha": "d9edecd16accdaff09cd33c7217bb67cc07ca504", "size": 1169, "ext": "py", "lang": "Python", "max_stars_repo_path": "data/external/repositories/251229/kaggle-cooking-master/script/xgb.py", "max_stars_repo_name": "Keesiu/meta-kaggle", "max_stars_repo_head_hexsha": "87de739aba2399fd31072ee81b391f9b7a63f540", "max_... |
import pygame
import cmath
import math as m
from pygame import *
from cmath import *
import matplotlib as mat
import numpy as np
xmax = 20
ymax = 16
inter = 1
interx = 1
tmax = 10
intert = 10
j = sqrt(-1)
WOUT_Last = [ 0, 0]
def ln(x):
try:
return log(abs(x)) - j * ( atan( x.real / ( .0000001 + x.imag... | {"hexsha": "263e7e6620431ac3382f73e246249d2e79bea192", "size": 4831, "ext": "py", "lang": "Python", "max_stars_repo_path": "Test.py", "max_stars_repo_name": "HackersForHarambe/Python-Repository", "max_stars_repo_head_hexsha": "b8c36483e51fe8b48a134ec78e3d3f10eeb49cb9", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
function csr_to_sparse_test()
i = [1;2;3]
j = [3;4;4]
v = [8;9;10]
(rp,ci,ai,m) = sparse_to_csr(i,j,v)
(nzi,nzj,nzv) = csr_to_sparse(rp,ci,ai)
A = sparse(nzi,nzj,nzv,length(rp)-1,maximum(ci))
# more tests added here
# clique to sparse test
rp = collect(1:5:26)
ci = vec(resha... | {"hexsha": "1ca6750460e662ff3f2f4ee9f8cb95797d47c2a5", "size": 780, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/csr_to_sparse_test.jl", "max_stars_repo_name": "MeherChaitanya04/Julia", "max_stars_repo_head_hexsha": "644e96c3109f7210c6a71898fc61a777ba20d49b", "max_stars_repo_licenses": ["MIT"], "max_stars... |
"""
Copyright 2013 Steven Diamond
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 to in writing, software... | {"hexsha": "c4564b58af68e78bfb2a664c467fcd74d1fbe272", "size": 3210, "ext": "py", "lang": "Python", "max_stars_repo_path": "cvxpy/atoms/affine/conv.py", "max_stars_repo_name": "jasondark/cvxpy", "max_stars_repo_head_hexsha": "56aaa01b0e9d98ae5a91a923708129a7b37a6f18", "max_stars_repo_licenses": ["ECL-2.0", "Apache-2.0"... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from Bio import SeqIO
import re
import numpy as np
import os
import random
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.collections import PatchCollection
class Region :
def __init__(self, start, stop, id) :
self.start ... | {"hexsha": "68ae03a14211d81fd918b62c634b865c80575506", "size": 9905, "ext": "py", "lang": "Python", "max_stars_repo_path": "Finder.py", "max_stars_repo_name": "AntoineHo/STRIP", "max_stars_repo_head_hexsha": "53a6e9197c0e079c2a1c686d1bf5b8710ced8525", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": null, ... |
import chainer
import chainer.functions as F
from scipy.misc import imresize
class Backprop:
""" Backprop
"""
def __init__(self, model, target_layer="conv5_3", prob_layer="prob"):
""" init
"""
self.model = model
self.xp = self.model.xp
self.target_layer = target_lay... | {"hexsha": "83b0c5632cd1d59beea159e4684305e289b5c8bf", "size": 6350, "ext": "py", "lang": "Python", "max_stars_repo_path": "grad-cam/backprop.py", "max_stars_repo_name": "daisuke-motoki/chainer-practice", "max_stars_repo_head_hexsha": "0e3b8924a61d2926e88e316961077eeac1c8a592", "max_stars_repo_licenses": ["MIT"], "max_... |
import sys
import re
import numpy as np
import torch
infile='celeba_full_64x64_5bit.npy'
img = torch.tensor(np.load(infile))
img = img.permute(0, 3, 1, 2)
torch.save(img, re.sub('.npy$', '.pth', infile))
| {"hexsha": "1c71b66f494868200f8dc2c6e6533b7efd6ec1a9", "size": 205, "ext": "py", "lang": "Python", "max_stars_repo_path": "Codes/Resflow_Procs/preprocessing/convert_to_pth.py", "max_stars_repo_name": "aahmadian-liu/ood-likefree-invertible", "max_stars_repo_head_hexsha": "977e70eccaa7f2eb09724b5bf6f28156f4940461", "max_... |
import numpy as np
import onnx
from tests.utils.common import check_onnx_model
from tests.utils.common import make_model_from_nodes
def _test_gather(
input_array: np.ndarray,
indices: np.ndarray,
opset_version: int,
**kwargs,
) -> None:
test_inputs = {
'x': input_array,
... | {"hexsha": "42afa36c405d1af2b4ea97d61f3b61b3d63c0ad3", "size": 1325, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/node_converters/gather_test.py", "max_stars_repo_name": "niobeus/onnx2torch", "max_stars_repo_head_hexsha": "d2dc0a0927ced3ac32d4a1dc925a5528874b5c0c", "max_stars_repo_licenses": ["Apache-2.... |
module Term
import Data.Fin
%logging 1
%logging declare.def 3
mutual
data Bdr : (cut : Bool) -> (vars : Nat) -> Type where
Lam : Bdr cut vars
Pi : Chk cut vars -> Bdr cut vars
-- Checkable terms (i.e. introduction forms)
data Chk : (cut : Bool) -> (vars : Nat) -> Type where
Bnd : Bdr cut vars ->... | {"hexsha": "481716c5e51382306284fa059bd5000081b46fd8", "size": 773, "ext": "idr", "lang": "Idris", "max_stars_repo_path": "idris2/tests/idris2/basic044/Term.idr", "max_stars_repo_name": "Qqwy/Idris2-Erlang", "max_stars_repo_head_hexsha": "945f9c12d315d73bfda2d441bc5f9f20696b5066", "max_stars_repo_licenses": ["BSD-3-Cla... |
# Created on: Jun 01, 2020
# Author: Marek Ryn
# Imports
from PIL import Image, ImageDraw, ImageFont
import numpy as np
import matplotlib.pyplot as plt
class FontCompressor:
@staticmethod
def _getm(cc):
m = 0
if cc > 10: m = 1
if cc > 92: m = 2
if cc > 174: m = 3
r... | {"hexsha": "965109cfbd4473a53d1490bdab2bdb9215996830", "size": 5472, "ext": "py", "lang": "Python", "max_stars_repo_path": "TFT Tools/fontcompressor.py", "max_stars_repo_name": "MarekRyn/ILI9341-Toolkit", "max_stars_repo_head_hexsha": "0d494db158d8cc1a328ed97fc5c4f7e5f11a74e0", "max_stars_repo_licenses": ["MIT"], "max_... |
# -*- coding: utf-8 -*-
import logging
import numpy as np
from mit_d3m import load_dataset
from mlblocks import MLPipeline
from sklearn.model_selection import KFold, StratifiedKFold
LOGGER = logging.getLogger(__name__)
def get_split(X, y, indexes):
if hasattr(X, 'iloc'):
X = X.iloc[indexes]
else:
... | {"hexsha": "fb08e3143afaf6a85985b4fb3ae008b0d7f1b953", "size": 2167, "ext": "py", "lang": "Python", "max_stars_repo_path": "piex/scoring.py", "max_stars_repo_name": "HDI-Project/PiEx", "max_stars_repo_head_hexsha": "fdc2167fe7b7007c178499a9062c2ff07fe7c31c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 8, "ma... |
import os
import numpy
from numpy import *
import math
from scipy import integrate, linalg
from matplotlib import pyplot
from pylab import *
def build_freestream_rhs(panels, freestream):
"""
Builds the right-hand side of the system
arising from the freestream contribution.
Parameters
---... | {"hexsha": "5b28fb5f4321469e4b80d82e8268908451643240", "size": 1045, "ext": "py", "lang": "Python", "max_stars_repo_path": "steapy/build_rhs.py", "max_stars_repo_name": "Sparsh-Sharma/SteaPy", "max_stars_repo_head_hexsha": "d6f3bee7eb1385c83f65f345d466ef740db4ed3b", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
#include <boost/compute/container/mapped_view.hpp>
| {"hexsha": "7bfde59977bd0d60d0400aa0795532e726896a05", "size": 51, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/boost_compute_container_mapped_view.hpp", "max_stars_repo_name": "miathedev/BoostForArduino", "max_stars_repo_head_hexsha": "919621dcd0c157094bed4df752b583ba6ea6409e", "max_stars_repo_licenses": [... |
// -----------------------------------------------------------------------------
// Fern © Geoneric
//
// This file is part of Geoneric Fern which is available under the terms of
// the GNU General Public License (GPL), version 2. If you do not want to
// be bound by the terms of the GPL, you may purchase a proprietary... | {"hexsha": "f556055f0ee6e6c32589f6235d54b9d947b7939b", "size": 3723, "ext": "cc", "lang": "C++", "max_stars_repo_path": "pcraster/pcraster-4.2.0/pcraster-4.2.0/source/fern/source/fern/io/netcdf/coards/test/read_test.cc", "max_stars_repo_name": "quanpands/wflow", "max_stars_repo_head_hexsha": "b454a55e4a63556eaac3fbabd9... |
\title{SCOREC Fall 2015 URP Projects}
\author{
Dan Zaide, Brian Granzow, Dan Ibanez, and Cameron Smith \\
}
\date{\today}
\documentclass[12pt]{article}
\usepackage{hyperref}
\usepackage{graphicx}
\begin{document}
\maketitle
Let's begin with a little bit about meshes. We can look at the world around us.
Everyt... | {"hexsha": "ae1d747ebd9224be124d267dcbebdf722e2a82c0", "size": 6718, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "projectsF15.tex", "max_stars_repo_name": "SCOREC/urp", "max_stars_repo_head_hexsha": "53a8a8469e46597b19448603ae6399d86cdcfa39", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_count": 1, "m... |
\section{Definitions, Families of Curves}
\subsection{Definitions}
\begin{definition}[Order]
Order of a DE is the highest-ordered derivative appearing in it.
So
\begin{equation}
\frac{d^2y}{dx^2}+2b(\frac{dy}{dx})^3+y=0
\end{equation}
is a 2nd order DE. In general,
\begin{equation}
... | {"hexsha": "3182a009152181a5e794461eea97c08aefc7d6ba", "size": 2887, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "differential-equations/tex/unit-1.tex", "max_stars_repo_name": "sidnb13/latex-notes", "max_stars_repo_head_hexsha": "bbd935b7ff9781169775c052625b1917a47d5dcc", "max_stars_repo_licenses": ["MIT"], "m... |
#!/usr/bin/python
"""
"""
import numpy as np
import time
import h5py
import sys
import os
from larch import Group
def read_xrd_hdf5(fname, verbose=False, _larch=None):
# Reads a HDF5 file created for XRD mapping
h5file = h5py.File(fname, 'r')
addr = 'entry/data/data'
for section in ('entry/data/data... | {"hexsha": "d4a3368a56c34b95224bea0e93f142e19c0d9d15", "size": 877, "ext": "py", "lang": "Python", "max_stars_repo_path": "larch/io/xrd_hdf5.py", "max_stars_repo_name": "kbuc/xraylarch", "max_stars_repo_head_hexsha": "3abb0d6bdc65cf2747a03dd114d98df317c0ac9f", "max_stars_repo_licenses": ["BSD-2-Clause"], "max_stars_cou... |
function test_pull1412
% MEM 2gb
% WALLTIME 00:10:00
% DEPENDENCY ft_heartrate
cd(dccnpath('/home/common/matlab/fieldtrip/data/test/pull1412'));
%%
% this corresponds to the preprocessed dataset 006_3013065.02_rest1 from bug3433
load datappg
cfg = [];
cfg.channel = 'HR';
cfg.threshold = 0.7;
cfg.method = 'findpeak... | {"author": "fieldtrip", "repo": "fieldtrip", "sha": "c2039be598a02d86b39aae76bfa7aaa720f9801c", "save_path": "github-repos/MATLAB/fieldtrip-fieldtrip", "path": "github-repos/MATLAB/fieldtrip-fieldtrip/fieldtrip-c2039be598a02d86b39aae76bfa7aaa720f9801c/test/test_pull1412.m"} |
'''
Created on 2020. 4. 16.
@author: Inwoo Chung (gutomitai@gmail.com)
'''
import numpy as np
import pandas as pd
import os
from abc import ABC, abstractmethod
import time
import json
import platform
from tqdm import tqdm
from tensorflow.keras.models import Model, load_model
from tensorflow.keras.l... | {"hexsha": "41c19d040de711b5638b43ad37330fdcf1ed58d6", "size": 15504, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/style_based_gan/style_based_gan_trainer.py", "max_stars_repo_name": "tonandr/keras_unsupervised", "max_stars_repo_head_hexsha": "fd2a2494bca2eb745027178e220b42b5e5882f94", "max_stars_rep... |
import networkx as nx
from networkx.drawing.nx_agraph import graphviz_layout
import pandas as pd
from ..utils import dict_to_repr
class PSSTNetwork(object):
def __init__(self, case, prog='sfdp'):
self._case = case
self.regenerate_network()
self.recalculate_positions(prog=prog)
@pro... | {"hexsha": "68fc911dd69ff503dcc80f5af8da6b204d40d2f8", "size": 6545, "ext": "py", "lang": "Python", "max_stars_repo_path": "psst/network/__init__.py", "max_stars_repo_name": "djinnome/psst", "max_stars_repo_head_hexsha": "f86019adaa0440fbfbadd1068eb7dac78e5640e7", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
# ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Ke Sun (sunk@mail.ustc.edu.cn)
# ------------------------------------------------------------------------------
"""
Modified by Myung-Joon Kwon
mjkwon2021@gmail.com
J... | {"hexsha": "4a9fb5974d7e2e20ccbd4e6c54aeb894feead54e", "size": 5882, "ext": "py", "lang": "Python", "max_stars_repo_path": "lib/core/function.py", "max_stars_repo_name": "mjkwon2021/CAT-Net", "max_stars_repo_head_hexsha": "d7054580e30f99bd6adc05f5c5e39feee9fd1fcb", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <boost/test/unit_test.hpp>
#include "ParserFlatbuffersSerializeFixture.hpp"
#include "../Deserializer.hpp"
#include <string>
BOOST_AUTO_TEST_SUITE(Deserializer)
struct PadFixture : public ParserFlatbuffersSerializeFixtu... | {"hexsha": "b18710a38162c02a56d6f2e836967fb532345f96", "size": 5429, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/armnnDeserializer/test/DeserializePad.cpp", "max_stars_repo_name": "VinayKarnam/armnn", "max_stars_repo_head_hexsha": "98525965c7cfecd9bf48297b433b2122cd1b4a1d", "max_stars_repo_licenses": ["MIT... |
[STATEMENT]
lemma invertible_left_cancel [simp]:
"\<lbrakk> invertible x; x \<in> M; y \<in> M; z \<in> M \<rbrakk> \<Longrightarrow> x \<cdot> y = x \<cdot> z \<longleftrightarrow> y = z"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>invertible x; x \<in> M; y \<in> M; z \<in> M\<rbrakk> \<Longrightarro... | {"llama_tokens": 172, "file": "Jacobson_Basic_Algebra_Group_Theory", "length": 1} |
Require Import Blech.Defaults.
Require Import Coq.Setoids.Setoid.
Require Import Coq.Classes.SetoidClass.
Require Import Blech.Bishop.
Require Import Blech.Proset.
Require Import Blech.Proset.Heyting.
Import ProsetNotations.
Import HeytingNotations.
(* Ostensibly, a first order system of logic is a free heyting alg... | {"author": "mstewartgallus", "repo": "category-fun", "sha": "436a90c0f9e8a729da6416a2c0e54611ca5e4575", "save_path": "github-repos/coq/mstewartgallus-category-fun", "path": "github-repos/coq/mstewartgallus-category-fun/category-fun-436a90c0f9e8a729da6416a2c0e54611ca5e4575/theories/Proset/Heyting/Free.v"} |
function iterative_probabilistic_improvement(tuning_run::Run,
reference::RemoteChannel;
threshold::AbstractFloat = 2.)
cost_calls = tuning_run.cost_evaluations
iteration = 1
name = "Itera... | {"hexsha": "989104114941c5b35c8e83a0965ebb1f4d352e72", "size": 1224, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/core/search/techniques/iterative_probabilistic_improvement.jl", "max_stars_repo_name": "JuliaPackageMirrors/StochasticSearch.jl", "max_stars_repo_head_hexsha": "58e48c8812fb402e4a46ffff1d5bcb87... |
DGTTRF Example Program Results
Details of factorization
Second superdiagonal of U
-1.0000 1.9000 8.0000
First superdiagonal of U
2.3000 -5.0000 -0.9000 7.1000
Main diagonal of U
3.4000 3.6000 7.0000 -6.0000 -1.0154
Multipliers
0.8824 0.0196 0.1401 -0.0148
Vector of in... | {"hexsha": "baacf48cafbf6bc5344e514eaf0326f388dd21aa", "size": 378, "ext": "r", "lang": "R", "max_stars_repo_path": "examples/baseresults/dgttrf_example.r", "max_stars_repo_name": "numericalalgorithmsgroup/LAPACK_examples", "max_stars_repo_head_hexsha": "0dde05ae4817ce9698462bbca990c4225337f481", "max_stars_repo_licens... |
C$Procedure ZZDIV ( Safer division )
DOUBLE PRECISION FUNCTION ZZDIV ( NUMR, DENOM )
C$ Abstract
C
C Safely calculate the value NUMR/DENOM, avoiding the possibility
C of floating point exceptions (FPE), due to numeric underflow,
C numeric overflow, or divide-by-zero.
C
C$ Disclaimer
C
C THIS SOF... | {"hexsha": "b3dc04249550d6480634393fa3486ef12dd9bc32", "size": 10994, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "source/nasa_f/zzdiv.f", "max_stars_repo_name": "agforero/FTFramework", "max_stars_repo_head_hexsha": "6caf0bc7bae8dc54a62da62df37e852625f0427d", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | {"hexsha": "40da78d8cf41cc3d9a6dc7957b58580b0dde21bf", "size": 8105, "ext": "py", "lang": "Python", "max_stars_repo_path": "imperative/python/megengine/functional/loss.py", "max_stars_repo_name": "chenbo123222/MegEngine", "max_stars_repo_head_hexsha": "8230ea2d0b16422136ad27b4073d523b524aa4e6", "max_stars_repo_licenses... |
from collections import namedtuple
import os
from gym import spaces
from typing import Callable, Dict, List, Optional
import numpy as np
from lanro.simulation import PyBulletSimulation
from lanro.utils import RGBCOLORS
DEBUG = int("DEBUG" in os.environ and os.environ["DEBUG"])
JointInfo = namedtuple('JointInfo', [
... | {"hexsha": "f40688449d41149301c01e371b8340bf2aa38858", "size": 18829, "ext": "py", "lang": "Python", "max_stars_repo_path": "lanro/robots/pybrobot.py", "max_stars_repo_name": "knowledgetechnologyuhh/lannro-gym", "max_stars_repo_head_hexsha": "ac3afcf7d8ed854d75368135b023edf055644dd2", "max_stars_repo_licenses": ["MIT"]... |
// Copyright 2015-2018 Hans Dembinski
//
// 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)
#ifndef BOOST_HISTOGRAM_AXIS_CATEGORY_HPP
#define BOOST_HISTOGRAM_AXIS_CATEGORY_HPP
#include <algorithm>
#include <boost/... | {"hexsha": "f5d63a3b5819d3badabcf5a3be437ff423af9e3f", "size": 6925, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "include/boost/histogram/axis/category.hpp", "max_stars_repo_name": "henryiii/histogram", "max_stars_repo_head_hexsha": "d9f000cb86a4b4ac5ebfcb395616fa9aaa28e06c", "max_stars_repo_licenses": ["BSL-1.... |
import numpy as np
import cv2
import matplotlib.pyplot as plt
import os
import random
import sys
import tensorflow as tf
from tensorflow import keras
# BUILDING MODEL
def down_conv_block(x, filters, kernel_size=(3, 3), padding='SAME', strides=1):
c = keras.layers.Conv2D(filters, kernel_size=kernel_size, paddin... | {"hexsha": "7e55f7db77533b2acd256c109281181e4750d4ce", "size": 2044, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/model.py", "max_stars_repo_name": "RaghavPrabhakar66/Kaggle-Data-Science-Bowl-2018", "max_stars_repo_head_hexsha": "fd30fc30d438faaf22bf054da911e7b698fc8f41", "max_stars_repo_licenses": ["... |
{- Byzantine Fault Tolerant Consensus Verification in Agda, version 0.9.
Copyright (c) 2020, 2021, Oracle and/or its affiliates.
Licensed under the Universal Permissive License v 1.0 as shown at https://opensource.oracle.com/licenses/upl
-}
-- This module proves the two "VotesOnce" proof obligations for our fake... | {"hexsha": "aa4fe33f6c3f2379b58ec9fcbb7d316955dc8d26", "size": 12674, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "LibraBFT/Impl/Properties/VotesOnce.agda", "max_stars_repo_name": "cwjnkins/bft-consensus-agda", "max_stars_repo_head_hexsha": "71aa2168e4875ffdeece9ba7472ee3cee5fa9084", "max_stars_repo_licenses"... |
SUBROUTINE STR_GET_ITEM
& (item_number,string,item,first_character,last_character)
c***********************************************************************
c subroutine str_get_item
c***********************************************************************
c Program Source: ... | {"hexsha": "d4ff5abdc11cf081461b45e671211c3ab7ef17f6", "size": 2786, "ext": "for", "lang": "FORTRAN", "max_stars_repo_path": "LWPCv21/lib/str_get_item.for", "max_stars_repo_name": "spinorkit/LWPC", "max_stars_repo_head_hexsha": "6144eac3b1ac1322d0ee363ec689bf8123bdeebd", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
import os
import json
import pandas as pd
import numpy as np
import gensim.downloader as api
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument("--data", type=str, default="./train.csv", help="path to training data")
parser.add_argument("--approach", type=int, default=1, choices=[1, 2, ... | {"hexsha": "3d58cc6a02ecbd28d35c4de1222a63152ddab1f6", "size": 3588, "ext": "py", "lang": "Python", "max_stars_repo_path": "Assignment2/dataset.py", "max_stars_repo_name": "tezansahu/CS728_assignments", "max_stars_repo_head_hexsha": "98d8721b82ddab174b86647f1cd7c412d768b6b9", "max_stars_repo_licenses": ["Apache-2.0"], ... |
import numpy as np
import pandas as pd
import pytest
from pandas.testing import assert_index_equal
from evalml.pipelines import RegressionPipeline
def test_regression_init():
clf = RegressionPipeline(
component_graph=["Imputer", "One Hot Encoder", "Random Forest Regressor"]
)
assert clf.parameter... | {"hexsha": "d82c0f1c5c881435f3627fad48881539f7f6c582", "size": 3713, "ext": "py", "lang": "Python", "max_stars_repo_path": "evalml/tests/pipeline_tests/regression_pipeline_tests/test_regression.py", "max_stars_repo_name": "peterataylor/evalml", "max_stars_repo_head_hexsha": "917f07845c4a319bb08c7aaa8df9e09623df11c8", "... |
#!/usr/bin/env python3
import cv2
import numpy as np
from pathlib import Path
import histogram
from matplotlib import pyplot as plt
import os
import multiprocessing
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('clutter', help='directory containing clutter data')
parser.add_argument('out', he... | {"hexsha": "da9341dcba6a3981bea85472085e7f3e0f050adb", "size": 5940, "ext": "py", "lang": "Python", "max_stars_repo_path": "solution_baseline/solution.py", "max_stars_repo_name": "NathanRVance/cv2", "max_stars_repo_head_hexsha": "fe3ddd56ec8a6010981b3f8861aea53541991028", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
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