text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
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\PassOptionsToPackage{unicode=true}{hyperref} % options for packages loaded elsewhere
\PassOptionsToPackage{hyphens}{url}
%
\documentclass[]{book}
\usepackage{lmodern}
\usepackage{amssymb,amsmath}
\usepackage{ifxetex,ifluatex}
\usepackage{fixltx2e} % provides \textsubscript
\ifnum 0\ifxetex 1\fi\ifluatex 1\fi=0 % if pd... | {"hexsha": "a58b902b09f1ed1efeb60556baa3051d514e08cf", "size": 51574, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "docs/STA-326-2.0-R-programming-and-Data-Analysis.tex", "max_stars_repo_name": "statisticsmart/STA3262R", "max_stars_repo_head_hexsha": "779ec05d234db543e1569d6ce86b450a3c01b767", "max_stars_repo_li... |
'''
Created on Jul 19, 2017
@author: Daniel Sela, Arnon Sela
'''
from scipy.io import readsav
from astropy.io import fits
import os
def read_fits_file(file, fits_index=1):
try:
hdus = fits.open(file, memmap=True)
hdus_ext = hdus[fits_index]
match = hdus_ext.data
except Exception as e... | {"hexsha": "295592db4c7b45759607ebf08a664484f928b047", "size": 1344, "ext": "py", "lang": "Python", "max_stars_repo_path": "py/rotseana/read_data_file.py", "max_stars_repo_name": "danielsela42/rotseana", "max_stars_repo_head_hexsha": "2b006fa6fd3c4d951de5872d84418e1089b352a3", "max_stars_repo_licenses": ["BSD-3-Clause"... |
from django.conf import settings
from django.contrib.auth.models import User
from django.db import models
from django.db.models.signals import post_save
from django.dispatch import receiver
from rest_framework.authtoken.models import Token
import numpy as np
import numpy.random as nprand
import random
class Document(... | {"hexsha": "03a80f97e0d59f4d7bb93ba24c1d5ca622044d04", "size": 6049, "ext": "py", "lang": "Python", "max_stars_repo_path": "transcript/models.py", "max_stars_repo_name": "ciaranmccormick/mm-transcription-server", "max_stars_repo_head_hexsha": "d7e44756beb703bf24a7a2bfe2cdfeaae8a6b49d", "max_stars_repo_licenses": ["BSD-... |
function value = ch_indexi ( s, c )
%*****************************************************************************80
%
%% CH_INDEXI is the (case insensitive) first occurrence of a character in a string.
%
% Licensing:
%
% This code is distributed under the GNU LGPL license.
%
% Modified:
%
% 01 May 2004
%
% A... | {"author": "johannesgerer", "repo": "jburkardt-m", "sha": "1726deb4a34dd08a49c26359d44ef47253f006c1", "save_path": "github-repos/MATLAB/johannesgerer-jburkardt-m", "path": "github-repos/MATLAB/johannesgerer-jburkardt-m/jburkardt-m-1726deb4a34dd08a49c26359d44ef47253f006c1/chrpak/ch_indexi.m"} |
# -*- coding: utf-8 -*-
import cPickle
import numpy as np
from scipy.io.wavfile import read
from sklearn.mixture import GaussianMixture as GMM
from sklearn import preprocessing
import warnings
warnings.filterwarnings("ignore")
node = True
import os
import python_speech_features as mfcc
modelsPath = "models/" #path to... | {"hexsha": "ae1cd3fb9a76d2647eea364273d4e005e510c9f0", "size": 3437, "ext": "py", "lang": "Python", "max_stars_repo_path": "train.py", "max_stars_repo_name": "efecanxrd/Speech-Recognition", "max_stars_repo_head_hexsha": "a593b1f455cfe9e098a8300f4e670c07abc2453b", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1... |
import logging
from contextlib import contextmanager
import os
from os.path import dirname, join
import socket
from subprocess import Popen
import time
import requests
import pytest
from seldon_core.proto import prediction_pb2
from seldon_core.proto import prediction_pb2_grpc
import seldon_core.microservice as microser... | {"hexsha": "8a5260016795c0c905637aaa9b1d4e779cee6c9a", "size": 12158, "ext": "py", "lang": "Python", "max_stars_repo_path": "python/tests/test_microservice.py", "max_stars_repo_name": "Ogaday/seldon-core", "max_stars_repo_head_hexsha": "df61cac5fda069e381c0baa1ba4d24d724e8c062", "max_stars_repo_licenses": ["Apache-2.0"... |
from unittest import TestCase
import numpy as np
import pandas as pd
from pandas.testing import assert_series_equal
from datavalid.column_schema import ColumnSchema
from datavalid.exceptions import ColumnValidationError
class ColumnSchemaTestCase(TestCase):
def test_validate(self):
field = ColumnSchema(... | {"hexsha": "aa648b8ad0d3d1a4dbd1e5a8e5e2e6d957e1257a", "size": 1256, "ext": "py", "lang": "Python", "max_stars_repo_path": "datavalid/test_column_schema.py", "max_stars_repo_name": "pckhoi/datavalid", "max_stars_repo_head_hexsha": "fea40936261dcbcfd144a15a498abf0b556c64f1", "max_stars_repo_licenses": ["MIT"], "max_star... |
/*
* parser.cpp
*
* Created on: Apr 20, 2016
* Author: zmij
*/
#include <wire/idl/parser.hpp>
#include <iostream>
#include <iomanip>
#include <functional>
#include <boost/optional.hpp>
namespace wire {
namespace idl {
namespace parser {
parser::parser(::std::string const& cnt)
: contents{ cnt }, state... | {"hexsha": "dbeb5b006a0da5eef8206e1b57a6b294640a1c28", "size": 19964, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/wire/idl/parser.cpp", "max_stars_repo_name": "zmij/wire", "max_stars_repo_head_hexsha": "9981eb9ea182fc49ef7243eed26b9d37be70a395", "max_stars_repo_licenses": ["Artistic-2.0"], "max_stars_count... |
SUBROUTINE ISCATR
C* ROUTINE FOR THEORETICALLY COMPUTING INCOHERENT POWER SPECTRA
C AND THEIR DERIVATIVES WITH RESPECT TO ION AND ELECTRON TEMPERATURES,
C ELECTRON DENSITY, COLLISION FREQUENCY AND ION COMPOSITION.
C BY WES SWARTZ
C =============================================================
C
C CALL ... | {"hexsha": "c157c46a0a368ec91c58928cd449f12c7607577a", "size": 21158, "ext": "for", "lang": "FORTRAN", "max_stars_repo_path": "src/iscatspe.for", "max_stars_repo_name": "stephancb/IScatterSpectrum.jl", "max_stars_repo_head_hexsha": "b4512871b34ba27d852d6a19302115e617640529", "max_stars_repo_licenses": ["MIT"], "max_sta... |
\documentclass[class=report, float=false, crop=false]{standalone}
\usepackage[subpreambles=true]{standalone}
\input{preamble}
\graphicspath{{figures/images/}}
% \begin{cbunit}
\begin{document}
\chapter{Ellipsoids}
\label{appendix:ellipsoids}
\section{Definition}
An ellipsoid is a surface that may be obtained fro... | {"hexsha": "dafa53d90e4e834b222289ab07db4086e9777200", "size": 18670, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "Notes/appendices/app_ellipsoids.tex", "max_stars_repo_name": "yketa/Umea_2017_Notes", "max_stars_repo_head_hexsha": "3b0e564e9054383bd91ff46930afe5543e9845ca", "max_stars_repo_licenses": ["CC-BY-4.... |
# pylint: disable=missing-docstring
import unittest
import random
import numpy as np
import tensorflow as tf
import tf_encrypted as tfe
from tf_encrypted.tensor import int100factory
class TestLSB(unittest.TestCase):
def setUp(self):
tf.reset_default_graph()
def _core_lsb(self, tensor_factory, prime_factor... | {"hexsha": "227476035f6c87b2b997efdbbb901ae5d6b7e738", "size": 1186, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_lsb.py", "max_stars_repo_name": "gavinuhma/tf-encrypted", "max_stars_repo_head_hexsha": "4e18d78a151bbe91489a1773fb839b889ff5b460", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
# Copyright 2022, Lefebvre Dalloz Services
#
# 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 ag... | {"hexsha": "5cb1111b30a07f82f2936d23b39a64dd1b67f2da", "size": 5552, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/transformer_deploy/utils/generative_model.py", "max_stars_repo_name": "dumpmemory/transformer-deploy", "max_stars_repo_head_hexsha": "36993d8dd53c7440e49dce36c332fa4cc08cf9fb", "max_stars_repo... |
import numpy as np
import networkx as nx
import random
PORT_NODE_THRESHOLD = 80000
class Graph():
def __init__(self, nx_G, is_directed, p, q):
self.G = nx_G
self.is_directed = is_directed
self.p = p
self.q = q
def node2vec_walk(self, walk_length, start_node):
'''
Simulate a random walk starting from st... | {"hexsha": "e41244a5a3859ceba86f4810f9c7093901371101", "size": 1069, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/node2vec.py", "max_stars_repo_name": "amitzohar/node2vec", "max_stars_repo_head_hexsha": "c1ff2151789593f02af2f5eff6b3d15cfe360c22", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
#==============================================================================#
# EC2/test/runtests.jl
#
# Copyright OC Technology Pty Ltd 2014 - All rights reserved
#==============================================================================#
using AWSEC2
using AWSCore
using Test
AWSCore.set_debug_level(1)
#-... | {"hexsha": "37832794b8a716e43700eb08362e16858ce23845", "size": 1315, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/runtests.jl", "max_stars_repo_name": "daisy12321/AWSEC2.jl", "max_stars_repo_head_hexsha": "24b6c7706c40f92339516560d4d875ab7510fd28", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nu... |
///////////////////////////////////////////////////////////////////////////////
/// \file expr.hpp
/// Contains definition of expr\<\> class template.
//
// Copyright 2008 Eric Niebler. Distributed under the Boost
// Software License, Version 1.0. (See accompanying file
// LICENSE_1_0.txt or copy at http://www.boost... | {"hexsha": "0f06b10ec3e3b2e38f82ee3549b79c8494773711", "size": 4865, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "deps/src/boost_1_65_1/boost/proto/expr.hpp", "max_stars_repo_name": "shreyasvj25/turicreate", "max_stars_repo_head_hexsha": "32e84ca16aef8d04aff3d49ae9984bd49326bffd", "max_stars_repo_licenses": ["B... |
"""
Setting a parameter by cross-validation
=======================================================
Here we set the number of features selected in an Anova-SVC approach to
maximize the cross-validation score.
After separating 2 sessions for validation, we vary that parameter and
measure the cross-validation score. We... | {"hexsha": "5359d4a3d3ad1c962a16b6e59f04394f9752c869", "size": 5447, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/decoding/plot_haxby_grid_search.py", "max_stars_repo_name": "agramfort/nilearn", "max_stars_repo_head_hexsha": "f075440e6d97b5bf359bb25e9197dbcbbc26e5f2", "max_stars_repo_licenses": ["BSD... |
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
! This file was ported from Lean 3 source module order.circular
! leanprover-community/mathlib commit f2f413b9d4be3a02840d0663dace76e8fe3da053
! Please do not edit these li... | {"author": "leanprover-community", "repo": "mathlib3port", "sha": "62505aa236c58c8559783b16d33e30df3daa54f4", "save_path": "github-repos/lean/leanprover-community-mathlib3port", "path": "github-repos/lean/leanprover-community-mathlib3port/mathlib3port-62505aa236c58c8559783b16d33e30df3daa54f4/Mathbin/Order/Circular.lean... |
from enum import Enum
import cv2
import numpy as np
class FrameImageType(Enum):
COLOR = 1
DEPTH = 2
MASK = 3
def generate_frame_image_path(index: int, frame_image_type: FrameImageType, input_folder: str) -> str:
filename_prefix_by_frame_image_type = {
FrameImageType.COLOR: "color",
F... | {"hexsha": "ec230264d8be6a7e1c909f20fdde7a6106138768", "size": 1450, "ext": "py", "lang": "Python", "max_stars_repo_path": "apps/frameviewer/frameloading.py", "max_stars_repo_name": "Algomorph/NeuralTracking", "max_stars_repo_head_hexsha": "6312be8e18828344c65e25a423c239efcd3428dd", "max_stars_repo_licenses": ["Apache-... |
#include "rotation.h"
#include "himan_common.h"
#include <Eigen/Geometry>
using namespace Eigen;
template <typename T>
void himan::geoutil::rotate(himan::geoutil::position<T>& p, const himan::geoutil::rotation<T>& r)
{
// Map data structures to Eigen library objects
Map<Matrix<T, 3, 1>> P(p.Data());
Map<const Quat... | {"hexsha": "be174d641f33634657deb856aaf02cde35afea5c", "size": 4331, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "himan-lib/source/rotation.cpp", "max_stars_repo_name": "fox91/himan", "max_stars_repo_head_hexsha": "4bb0ba4b034675edb21a1b468c0104f00f78784b", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
from sklearn.neural_network import MLPClassifier
from sklearn.metrics import accuracy_score
from time import time
from sklearn.preprocessing import StandardScaler
import numpy as np
from sklearn.preprocessing import OneHotEncoder
def run_decomp_nn(k, estimator, f, x_train, x_test, y_train, y_test):
ica_x_train = ... | {"hexsha": "d1d7ca87b8b373d071adfb85b6aeccafc6653a7c", "size": 1964, "ext": "py", "lang": "Python", "max_stars_repo_path": "supervised/nn_util.py", "max_stars_repo_name": "travisMichael/unsupervisedLearning", "max_stars_repo_head_hexsha": "f01bd4e36833de4917811e51042e3937510e2701", "max_stars_repo_licenses": ["MIT"], "... |
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 23 10:27:40 2021
@author: Tom
"""
import liionpack as lp
import matplotlib.pyplot as plt
import numpy as np
import pybamm
plt.close('all')
# Circuit parameters
R_bus = 1e-4
R_series = 1e-2
R_int = 5e-2
I_app = 80.0
ref_voltage = 3.2
# Load the netlist
netlist = lp.rea... | {"hexsha": "76645ab3d5f64cde43c9b9c8d4a056f1306123ad", "size": 2177, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/scripts/load_netlist.py", "max_stars_repo_name": "tinosulzer/liionpack", "max_stars_repo_head_hexsha": "ed1c8e61d6e81c28d73eb0c39fc77e2ac39b6258", "max_stars_repo_licenses": ["MIT"], "max... |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 12 16:54:41 2018
@author: Aake
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as pl
import EOS
from scaling import scaling,cgs
#%% Void object
class void():
pass
evol=void()
#%% Soft gravity
sc=scaling()
m_planet=5.0
a_planet... | {"hexsha": "c4cacff4a0af176c9733bd871a522d87532dfa5b", "size": 3629, "ext": "py", "lang": "Python", "max_stars_repo_path": "data/eos/Tomida+Hori_2016/hydrostatic3.py", "max_stars_repo_name": "applejwjcat/dispatch", "max_stars_repo_head_hexsha": "4fad06ee952de181f6c51b91f179d6396bdfb333", "max_stars_repo_licenses": ["BS... |
# https://github.com/chatflip/ImageRecognitionDataset
#
import gzip
import os
import pickle
import shutil
import sys
import tarfile
import urllib.request
import zipfile
import numpy as np
from PIL import Image
import argparse
class ExpansionDataset(object):
'''docstring for ClassName'''
def __init__(self, a... | {"hexsha": "debf185e09b63976af382fcb22bc01fa4a62f5b8", "size": 18834, "ext": "py", "lang": "Python", "max_stars_repo_path": "util/ImageDatasetsDownloader.py", "max_stars_repo_name": "shizuo-kaji/PretrainCNNwithNoData", "max_stars_repo_head_hexsha": "6d076e4bc2effcd91e9275470db79e0125704087", "max_stars_repo_licenses": ... |
import sys
import numpy as np
MOD = 10**9 + 7
U = 10**6
def mod_cumprod(a, p=MOD):
l = len(a)
sql = int(np.sqrt(l) + 1)
a = np.resize(a, sql**2).reshape(sql, sql)
for i in range(sql - 1):
a[:, i + 1] *= a[:, i]
a[:, i + 1] %= p
for i in range(sql - 1):
a[i... | {"hexsha": "bf2fa14280aa96aee8cf9ac855625980e9f268f7", "size": 1350, "ext": "py", "lang": "Python", "max_stars_repo_path": "jp.atcoder/abc065/arc076_a/11896928.py", "max_stars_repo_name": "kagemeka/atcoder-submissions", "max_stars_repo_head_hexsha": "91d8ad37411ea2ec582b10ba41b1e3cae01d4d6e", "max_stars_repo_licenses":... |
"""Tests the DNC class implementation."""
import sonnet as snt
import tensorflow as tf
import unittest
from numpy.testing import assert_array_equal
from .. dnc import dnc
def suite():
"""Create testing suite for all tests in this module."""
suite = unittest.TestSuite()
suite.addTest(DNCTest('test_const... | {"hexsha": "ad37eeb2cebc0cdc3f7948458df4ee350c274e32", "size": 2711, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/testing/dnc_test.py", "max_stars_repo_name": "derrowap/DNC-TensorFlow", "max_stars_repo_head_hexsha": "3e9ad109f8101265ae422ba9c20e058aa70ef7df", "max_stars_repo_licenses": ["MIT"], "max_stars... |
# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
from extensions.front.mxnet.eltwise_scalar_replacers import MulScalarFrontReplacer
from extensions.front.mxnet.ssd_detection_output_replacer import SsdPatternDetectionOutputReplacer
from extensions.front.split_normali... | {"hexsha": "fe0d62ddacc7400566a7b32b527a2a6f49991533", "size": 4156, "ext": "py", "lang": "Python", "max_stars_repo_path": "model-optimizer/extensions/front/mxnet/ssd_anchor_reshape.py", "max_stars_repo_name": "monroid/openvino", "max_stars_repo_head_hexsha": "8272b3857ef5be0aaa8abbf7bd0d5d5615dc40b6", "max_stars_repo_... |
import numpy as np
import random, operator, os, json, sys
import folium
import pandas as pd
import osmnx as ox
import networkx as nx
import matplotlib.pyplot as plt
from deliveryrouting.generate_input import progressbar
class Fitness:
def __init__(self, route, origins_file, destinations_file):
self.route =... | {"hexsha": "7586a4d4c3a665fba3ff36df4b47a01430e83a6b", "size": 9363, "ext": "py", "lang": "Python", "max_stars_repo_path": "deliveryrouting/delivery_routing.py", "max_stars_repo_name": "balakumaran247/delivery_routing", "max_stars_repo_head_hexsha": "be1dbc19d567d917f2b9991b608a732d2e77ab3c", "max_stars_repo_licenses":... |
# ~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=~
# MIT License
#
# Copyright (c) 2022 Nathan Juraj Michlo
#
# 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 Softwar... | {"hexsha": "37f5c29786319c8796decafd72ba2fb5aa3bcd78", "size": 5325, "ext": "py", "lang": "Python", "max_stars_repo_path": "disent/dataset/sampling/_groundtruth__walk.py", "max_stars_repo_name": "nmichlo/msc-research", "max_stars_repo_head_hexsha": "625e57eca77bbfbc4728ccebdb0733e1613bd258", "max_stars_repo_licenses": ... |
import numpy as np
import pandas as pd
import requests
import sys
import csv
from scipy.spatial.distance import cdist
from scipy.spatial import distance
from pandas.core.frame import DataFrame
import matplotlib.pyplot as plt
LIVE_URL = "http://environment.data.gov.uk/flood-monitoring/id/stations?parameter=... | {"hexsha": "16d1321430ca0771cc96bdc69c813656f704a9cd", "size": 2403, "ext": "py", "lang": "Python", "max_stars_repo_path": "flood_tool/try_plot_rainfall_and_flood.py", "max_stars_repo_name": "oahul14/FloodRisk", "max_stars_repo_head_hexsha": "286fa1b183258befaffe81c6a4edca7ff490d04d", "max_stars_repo_licenses": ["MIT"]... |
import numpy
import os
import setuptools
from setuptools import setup, find_packages
import setuptools.command.develop
import setuptools.command.build_py
from tools import gitsemver
with open('README.md') as f:
longDescription = f.read()
with open('requirements.txt') as f:
required = f.read().splitlines()
vers... | {"hexsha": "95b1212ba2018d57bf0440b64465521c4805c1e3", "size": 2758, "ext": "py", "lang": "Python", "max_stars_repo_path": "setup.py", "max_stars_repo_name": "WattsUp/hardware-tools", "max_stars_repo_head_hexsha": "d9dc01429369bc071381cb25af7b984195aff8e5", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "... |
// A multi-threaded inclusive_scan with std::accumulate "lookahead"
// Copyright 2019 Jeff Trull <edaskel@att.net>
#ifndef INCLUSIVE_SCAN_MT_HPP
#define INCLUSIVE_SCAN_MT_HPP
#include "benchmark_scan.hpp"
#include "serial_scan.hpp"
#include <boost/asio.hpp>
#include <iterator>
#include <future>
template <typename ... | {"hexsha": "f0e200e0cf55eb24033d6dcd18be5de356bc1f20", "size": 2816, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "inclusive_scan_mt.hpp", "max_stars_repo_name": "jefftrull/MyParallelAlg", "max_stars_repo_head_hexsha": "87ca7ce89152c70c46ffabad897f4d8ed82a6e24", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
"""
This figure is meant to represent the neuronal event-related model
and a coefficient of +1 for Faces, -2 for Objects.
"""
import pylab
import numpy as np
from sympy import Symbol, Heaviside, lambdify
ta = [0,4,8,12,16]; tb = [2,6,10,14,18]
ba = Symbol('ba'); bb = Symbol('bb'); t = Symbol('t')
fa = sum([Heavisi... | {"hexsha": "e14c7562ddddf92681ee9f898ae4b8297675bc14", "size": 647, "ext": "py", "lang": "Python", "max_stars_repo_path": "doc/users/plots/neuronal_event.py", "max_stars_repo_name": "yarikoptic/NiPy-OLD", "max_stars_repo_head_hexsha": "8759b598ac72d3b9df7414642c7a662ad9c55ece", "max_stars_repo_licenses": ["BSD-3-Clause... |
The Looking Glass is a custom picture framing shop located inside the Pacific Auction Company facility.
Get 25 % off right now athttp://greenmachinedavis.com/coupon_lookingglass.html Little Green Coupon Machine
Follow us onhttp://www.facebook.com/home.php#!/pages/LookingGlassCustomFraming/199585876730294?skwall Fac... | {"hexsha": "747efcd516367369c586ad57d5f2e52adddbd9b4", "size": 327, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/The_Looking_Glass.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
\section{Abstract}
\begin{frame}
\begin{abstract}
Thermodynamics started with steam engines. At the end of the 19th century, Ludwig Boltzmann introduced the idea of statistical mechanics, i.e. the idea that complex microscopic interactions would \emph{emerge} by averaging (coarse graining) defined ensembles, and prov... | {"hexsha": "cc9f95f1c5300bbb66af628d6c6d3e691e261486", "size": 1206, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "0) CommonTeX_Code/abstract.tex", "max_stars_repo_name": "bobksgithub/Info2Thermo_Lectures", "max_stars_repo_head_hexsha": "7766dda1f32dd322962397285f6a47cc46be13b2", "max_stars_repo_licenses": ["MIT... |
[STATEMENT]
lemma real_neg_pp_np_help: "\<And>x. f x \<le> (0::real) \<Longrightarrow> np f x = -f x \<and> pp f x = 0"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<And>x. f x \<le> 0 \<Longrightarrow> np f x = - f x \<and> pp f x = 0
[PROOF STEP]
(*<*)
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<And>x. ... | {"llama_tokens": 1013, "file": "Integration_RealRandVar", "length": 14} |
import os
from gensim import models
import json
import numpy as np
from keras.models import *
from keras.layers import *
import keras
from sklearn.metrics import *
import keras.backend as K
import pandas as pd
import argparse
pd.options.mode.chained_assignment = None
def readJson(filename):
print "Reading [%s]..." %... | {"hexsha": "b8507b6eee1b3ad59e75b6539c24cacb44eb0766", "size": 13258, "ext": "py", "lang": "Python", "max_stars_repo_path": "cvqa-r-nouns/task2-lstm-mlp-folds.py", "max_stars_repo_name": "andeeptoor/qpr-qe-datasets", "max_stars_repo_head_hexsha": "4359af17e7df335abe38a18d046f94f9cef57277", "max_stars_repo_licenses": ["... |
%!TEX root = main.tex
\section{Related Work}
\label{sec:related_work}
To the best of our knowledge, we are the first to formally address the problem of optimizing
the driver's strategy in ride-hailing platforms like Uber and Lyft.
Apart from
some recent popular-press articles that
offer, often contradictory, advic... | {"hexsha": "a6701185f225620f61fb8d412429045983f75de6", "size": 8156, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "paper/WSDM-2018/related.tex", "max_stars_repo_name": "chdhr-harshal/uber-driver-strategy", "max_stars_repo_head_hexsha": "f21f968e7aa04d8105bf42e046ab120f813aa12f", "max_stars_repo_licenses": ["MIT"... |
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['savefig.dpi']=300
a=[666618,588597,443497,269913,197146,195835,139682,134647,130100,125753]
for i in range(len(a)):
a[i]=a[i]/10000
data={'country':['美国','巴西','印度','墨西哥','秘... | {"hexsha": "eea6444ac8dfd56fd652bb337615c256ac830fbf", "size": 1462, "ext": "py", "lang": "Python", "max_stars_repo_path": "1.py", "max_stars_repo_name": "fita23689/MachineLearning", "max_stars_repo_head_hexsha": "6da571ab1e7067392b67df566a6d040b68530f31", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "m... |
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 29 09:22:10 2018
@author: gregoire
"""
#srcfolder=r'L:\processes\analysis\rams\temp_to_add_to_4076'
#anafolder=r'L:\processes\analysis\rams\20181130.142222.run'
#srcfolder=r'L:\processes\analysis\rams\temp_to_add_to_4832'
#anafolder=r'L:\processes\analysis\rams\20181130.... | {"hexsha": "ee73009d16f0f11f3feb1d430c835538dd8e612a", "size": 5723, "ext": "py", "lang": "Python", "max_stars_repo_path": "one_off_routines/20181129_ingest_CU_Bcknd.py", "max_stars_repo_name": "johnmgregoire/JCAPDataProcess", "max_stars_repo_head_hexsha": "c8120e5b2f8fc840a6307b40293dccaf94bd8c2c", "max_stars_repo_lic... |
!##############################################################################
!# ****************************************************************************
!# <name> CahnHilliard_partridiscr </name>
!# ****************************************************************************
!#
!# <purpose>
!# This module contai... | {"hexsha": "5dee01e65771373808b8f8404343d565ff161a59", "size": 13731, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "area51/Archive/CHNS_Kay/src/CahnHilliard_partridiscr.f90", "max_stars_repo_name": "tudo-math-ls3/FeatFlow2", "max_stars_repo_head_hexsha": "56159aff28f161aca513bc7c5e2014a2d11ff1b3", "max_stars... |
[STATEMENT]
lemma cong_exp_trans[trans]:
"[a ^ b = c] (mod n) \<Longrightarrow> [a = d] (mod n) \<Longrightarrow> [d ^ b = c] (mod n)"
"[c = a ^ b] (mod n) \<Longrightarrow> [a = d] (mod n) \<Longrightarrow> [c = d ^ b] (mod n)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (\<lbrakk>[a ^ b = c] (mod n); [a = ... | {"llama_tokens": 469, "file": "Probabilistic_Prime_Tests_Algebraic_Auxiliaries", "length": 2} |
module parcel_netcdf
use constants, only : one
use netcdf_utils
use netcdf_writer
use netcdf_reader
use parcel_container, only : parcels, n_parcels
use parameters, only : nx, ny, nz, extent, lower, max_num_parcels
use config, only : package_version, cf_version
use timer, only : start_tim... | {"hexsha": "a48a96c4bf4a8a941b46584a8bfca41243bf22fc", "size": 20241, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/3d/parcels/parcel_netcdf.f90", "max_stars_repo_name": "matt-frey/epic", "max_stars_repo_head_hexsha": "954ebc44f2c041eee98bd14e22a85540a0c6c4bb", "max_stars_repo_licenses": ["BSD-3-Clause"]... |
import numpy as np
import torch.nn as nn
import random
import pytest
from test.utils import convert_and_test
class LayerTest(nn.Module):
def __init__(self, out, eps, momentum):
super(LayerTest, self).__init__()
self.bn = nn.BatchNorm2d(out, eps=eps, momentum=momentum)
def forward(self, x):
... | {"hexsha": "73459aa2b7218bfb4a90e677c73140a8f970c648", "size": 761, "ext": "py", "lang": "Python", "max_stars_repo_path": "test/layers/normalizations/test_bn2d.py", "max_stars_repo_name": "dawnclaude/onnx2keras", "max_stars_repo_head_hexsha": "3d2a47c0a228b91fd434232274e216e491da36e3", "max_stars_repo_licenses": ["MIT"... |
"""
Combine the contours estimated:
* directly with the classification CNN
* computing normal curvature on dmap estimated with the regression CNN
Extract cells using watershed.
"""
"""
This file is part of Cytometer
Copyright 2021 Medical Research Council
SPDX-License-Identifier: Apache-2.0
Author: Ramon Casero <rcas... | {"hexsha": "43c98ef0054814722ea54b865ebf22c12d8abb62", "size": 6720, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/klf14_b6ntac_exp_0009_combine_dmap_contour_estimates.py", "max_stars_repo_name": "rcasero/cytometer", "max_stars_repo_head_hexsha": "d76e58fa37f83f6a666d556ba061530d787fcfb2", "max_stars_r... |
[STATEMENT]
lemma fMin_finsert[simp]: "fMin (finsert x A) = (if A = {||} then x else min x (fMin A))"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. fMin (finsert x A) = (if A = {||} then x else min x (fMin A))
[PROOF STEP]
by transfer simp | {"llama_tokens": 104, "file": null, "length": 1} |
///////////////////////////////////////////////////////////////////////////////
// Copyright Christopher Kormanyos 2015.
// Copyright Paul Bristow 2015.
// 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": "39c4fb9c432d603ea7c36beaa3d13b79e9e37564", "size": 3186, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "test/test_negatable_basic_narrowing_constructors.cpp", "max_stars_repo_name": "BoostGSoC15/fixed-point", "max_stars_repo_head_hexsha": "d71b4a622ded821a2429d8d857097441c2a10246", "max_stars_repo_lic... |
'''Core functionality'''
from __future__ import print_function, division
import os, sys, glob, numpy as np, matplotlib, scipy, time
from scipy import stats, interpolate, optimize
from math import pi
import numpy.lib.recfunctions as rf
import mla
from mla.spectral import *
from mla.tools import *
from mla.ti... | {"hexsha": "5e4a905511552a0d85c7c2290e86f7ee2a6f3cd5", "size": 24862, "ext": "py", "lang": "Python", "max_stars_repo_path": "mla/mla/core.py", "max_stars_repo_name": "jasonfan1997/umd_icecube_analysis_tutorial", "max_stars_repo_head_hexsha": "50bf3af27f81d719953ac225f199e733b5c0bddf", "max_stars_repo_licenses": ["Apach... |
import numpy as np
import pytest
import pdffitx.modeling.fitobjs as fitobjs
from pdffitx.modeling.fitobjs import MyParser, GenConfig, ConConfig
from pdffitx.modeling.running import multi_phase
@pytest.mark.parametrize(
"meta",
[
None,
{'qmin': 1, 'qmax': 24, 'qdamp': 0.04, 'qbroad': 0.02}
... | {"hexsha": "13518e89850f6b5bc35d048459a18b66902b7b26", "size": 3128, "ext": "py", "lang": "Python", "max_stars_repo_path": "pdffitx/tests/modeling/test_fitobjs.py", "max_stars_repo_name": "st3107/pdffitx", "max_stars_repo_head_hexsha": "c746f6dfaf5656e9bb62508a9847c00567b34bbe", "max_stars_repo_licenses": ["BSD-3-Claus... |
[STATEMENT]
lemma hm_update_op_refine: "(hm_update_op, h.update_op) \<in> hmr_rel \<rightarrow> nat_rel \<rightarrow> Id \<rightarrow> \<langle>hmr_rel\<rangle>nres_rel"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (hm_update_op, h.update_op) \<in> hmr_rel \<rightarrow> nat_rel \<rightarrow> Id \<rightarrow> \<lan... | {"llama_tokens": 1331, "file": "Refine_Imperative_HOL_IICF_Impl_Heaps_IICF_Abs_Heapmap", "length": 5} |
from multiprocessing.dummy import Pool as ThreadPool
from bilisupport import BANGUMIINFO, EXTERNAL_BANGUMI, RECOMMENDINFO
import numpy as np
from bert_serving.client import BertClient
import numpy as np
import pickle
GPU_SERVER = '10.113.63.16'
bc = BertClient(ip=GPU_SERVER)
similarity_matrix = []
def cosin_similarity... | {"hexsha": "7298f46481e614d536f772a294023096e21b341f", "size": 1803, "ext": "py", "lang": "Python", "max_stars_repo_path": "local/calculate_similarity.py", "max_stars_repo_name": "Ririkoo/DanmakuAnime", "max_stars_repo_head_hexsha": "8c8b93d80bc777f4789631526b04214564ab15d6", "max_stars_repo_licenses": ["MIT"], "max_st... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import solve_ivp
from scipy.optimize import minimize
class SIRPredict:
'''
Represents the SIR model facilities to compute and predict the spread of
a virus given the value of i
'''
def __init__(self, population: int, beta: fl... | {"hexsha": "1f8c48da0281c53029338806ff0493eeafe4b0aa", "size": 4297, "ext": "py", "lang": "Python", "max_stars_repo_path": "sir.py", "max_stars_repo_name": "giuliocorradini/SIRVisualizer", "max_stars_repo_head_hexsha": "c6f19c8040defce4d163e16f2b7c7dc69e06e7f1", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nu... |
/**
* Copyright (C) 2012 ciere consulting, ciere.com
* Copyright (C) 2012 Jeroen Habraken
* Copyright (c) 2011 Joel de Guzman
* Copyright (C) 2011, 2012 Object Modeling Designs
*
* Distributed under the Boost Software License, Version 1.0. (See accompanying
* file LICENSE_1_0.txt or copy at h... | {"hexsha": "3338313d48baae5c75233e81ad952ae54573bf77", "size": 7736, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "libs/spirit/example/qi/json/json/detail/value_impl.hpp", "max_stars_repo_name": "Abce/boost", "max_stars_repo_head_hexsha": "2d7491a27211aa5defab113f8e2d657c3d85ca93", "max_stars_repo_licenses": ["B... |
file = matopen("temp.mat","w")
#title:"Lock Prediction"
#write(file,"title",title)
#length:6 -> {"Actual", "Our contention model", "LR+class", "quad+class", "Dec. tree regression", "Orig. Thomasian"};
#length:5 -> {"Our contention model", "LR+class", "quad+class", "Dec. tree regression", "Orig. Thomasian"};
lenOfLegen... | {"hexsha": "33dfc7a47f0adad3217f99b9e8edc0285da867ab", "size": 2250, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "predict_mat/julia/write_mat_lockP.jl", "max_stars_repo_name": "barzan/dbseer", "max_stars_repo_head_hexsha": "3ad0718f665a5beffa65df7be8998986dcdbf3db", "max_stars_repo_licenses": ["Apache-2.0"], "... |
#############################################################################
##
#W example.gd
##
## This file contains a sample of a GAP implementation file.
##
#############################################################################
##
#M SomeOperation( <val> )
##
## performs some operation on <val>
##
Ins... | {"hexsha": "941f7c586f9c8183d87b2bfe614d1b5dc2924bc7", "size": 1323, "ext": "gi", "lang": "GAP", "max_stars_repo_path": "analyzer/libs/pygments/tests/examplefiles/example.gi", "max_stars_repo_name": "oslab-swrc/juxta", "max_stars_repo_head_hexsha": "481cd6f01e87790041a07379805968bcf57d75f4", "max_stars_repo_licenses": ... |
#!/usr/bin/env python
"""Generate temperatures along given order parameter."""
import argparse
import numpy as np
import pandas as pd
from scipy import interpolate
from scipy.optimize import minimize
def main():
args = parse_args()
aves = pd.read_csv(args.inp_filename, sep=" ")
if args.rtag:
ave... | {"hexsha": "4a6cb8e4d4be91843f4059b0cfbd3f9dca5d5744", "size": 2426, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/simutils/generate_ptmc_temps.py", "max_stars_repo_name": "cumberworth/origamipy", "max_stars_repo_head_hexsha": "cd005b140342dbe4c7708ab234102be54328648a", "max_stars_repo_licenses": ["MIT... |
from PIL import Image
from yuv_reader import YUVReader
from reprojection import Reprojection
from optparse import OptionParser
from six.moves import cPickle
import matplotlib.pyplot as plt
import numpy as np
import os
from dataset_preparation.ballet_camera import BalletCamera
def main():
parser = OptionParser()
... | {"hexsha": "999cebca4d646e21095081c45d2a460c7f9f1e3c", "size": 3792, "ext": "py", "lang": "Python", "max_stars_repo_path": "reprojection/process_video.py", "max_stars_repo_name": "aTeK7/deep-stereo1.4", "max_stars_repo_head_hexsha": "dd2150097d0ed1c05791e4d80cf9b404f98a6880", "max_stars_repo_licenses": ["MIT"], "max_st... |
// Copyright (c) 2001-2009 Hartmut Kaiser
//
// 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)
#if !defined(BOOST_SPIRIT_FORMAT_MANIP_MAY_05_2007_1202PM)
#define BOOST_SPIRIT_FORMAT_MANIP_MAY_05_2007_1202PM
#incl... | {"hexsha": "32c2bc5c13f6c47d8f606f5097dfce437e5f5369", "size": 4023, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "boost/spirit/home/qi/stream/match_manip.hpp", "max_stars_repo_name": "mike-code/boost_1_38_0", "max_stars_repo_head_hexsha": "7ff8b2069344ea6b0b757aa1f0778dfb8526df3c", "max_stars_repo_licenses": ["... |
#!/usr/bin/env python
"""
Make plots showing how to calculate the p-value
"""
import matplotlib.pyplot as pl
from scipy.stats import norm
from scipy.special import erf
import numpy as np
mu = 0. # the mean, mu
sigma = 1. # standard deviation
x = np.linspace(-4, 4, 1000) # x
# set plot to render labels using latex
... | {"hexsha": "3a2824e653c6bf59617658c15069f733d19ba0fd", "size": 1242, "ext": "py", "lang": "Python", "max_stars_repo_path": "figures/scripts/pvalue.py", "max_stars_repo_name": "mattpitkin/GraWIToNStatisticsLectures", "max_stars_repo_head_hexsha": "09175a3a8cb3c9f0f15535d64deaef1275eac870", "max_stars_repo_licenses": ["M... |
'''
Created on Jan 14, 2017
@author: safdar
'''
from operations.baseoperation import Operation
from sklearn.externals import joblib
from statistics import mean
import numpy as np
import cv2
from extractors.helper import buildextractor
import os
from utils.plotter import Image
import PIL
import time
from operations.ve... | {"hexsha": "b2f6dcd4d9731fb083e3202b305a212afc16001b", "size": 12753, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/operations/vehicledetection/vehiclefinder.py", "max_stars_repo_name": "safdark/advanced-lane-lines", "max_stars_repo_head_hexsha": "27edcc444ac532e84749d667fc579970d2059aff", "max_stars_repo_... |
# ==============================================================
# Author: Rodolfo Ferro
# Twitter: @FerroRodolfo
#
# ABOUT COPYING OR USING PARTIAL INFORMATION:
# This script has been originally created by Rodolfo Ferro.
# Any explicit usage of this script or its contents is granted
# according to the license provided... | {"hexsha": "8cd3a133b2a8017ca73bfc1f948fde7c4b5b39da", "size": 2110, "ext": "py", "lang": "Python", "max_stars_repo_path": "app.py", "max_stars_repo_name": "RodolfoFerro/streamlit-example", "max_stars_repo_head_hexsha": "fd1e921a447fa8c25fd3f862456905b11bf4a3c6", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 9... |
import os
import argparse
import cv2
import numpy as np
import sys
import time
from threading import Thread
import importlib.util
class VideoStream:
"""Camera object that controls video streaming from the Picamera"""
def __init__(self, resolution=(640, 480), framerate=30):
# Initialize the PiCamera a... | {"hexsha": "b682c38c1dcf6ec765f7ff7a75100ac1c7e99dd4", "size": 5423, "ext": "py", "lang": "Python", "max_stars_repo_path": "1.night traffic/final.py", "max_stars_repo_name": "alex-coch/TDI-Machine-Learning", "max_stars_repo_head_hexsha": "975c87339a21038bcf1c811e382d3dbf52fd9995", "max_stars_repo_licenses": ["Apache-2.... |
# Copyright 2021 The TensorFlow Authors. 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 required by applica... | {"hexsha": "f891215f25853666ba35a7c86bc68d34b358fe66", "size": 3703, "ext": "py", "lang": "Python", "max_stars_repo_path": "tony-examples/mnist-tensorflow/mnist_estimator_distributed.py", "max_stars_repo_name": "ashahab/TonY", "max_stars_repo_head_hexsha": "9bf6eec72e36ee8d8db295fa1be729cf7a780a97", "max_stars_repo_lic... |
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
#%matplotlib inline
#reading in an image
image = mpimg.imread('test_images/solidWhiteRight.jpg')
#printing out some stats and plotting
print('This image is:', type(image), 'with dimensions:'... | {"hexsha": "df96165e6553c4985203846157590d10d3959135", "size": 7047, "ext": "py", "lang": "Python", "max_stars_repo_path": "lane_line_tracker.py", "max_stars_repo_name": "nialldevlin/Lane-Line-Tracker", "max_stars_repo_head_hexsha": "fe1127d895790ab0c0a8292fdf1fab0551ef6bbb", "max_stars_repo_licenses": ["MIT"], "max_st... |
import torch
from tqdm import tqdm
import torch.nn as nn
import numpy as np
import random
class DenseRetriever(nn.Module):
def __init__(self, unpaired_sents, vocab, add_sos=True, add_eos=True):
super().__init__()
self.pad_id = vocab.pad
self.eos_id = vocab.eos
self.sos... | {"hexsha": "741711ae630639202188e04cc67fe44611e96be0", "size": 4463, "ext": "py", "lang": "Python", "max_stars_repo_path": "model/DenseRetriever.py", "max_stars_repo_name": "xiaofei05/TSST", "max_stars_repo_head_hexsha": "450d0d8c18002b50a50b4b642ace7769d476e889", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
########################################
## File Name: belief_types.jl
## Author: Haruki Nishimura (hnishimura@stanford.edu)
## Date Created: 2020/05/12
## Description: Belief Type Definitions for SACBP
########################################
import Distributions: Normal, MvNormal
import Plots.Plot
using LinearAlgebr... | {"hexsha": "9517e5b2eaf210be6f2d001f6bb97ef2808e6fc9", "size": 2631, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/belief_types.jl", "max_stars_repo_name": "StanfordMSL/SACBP.jl", "max_stars_repo_head_hexsha": "f759dcdaa3a39f5195d0ae2939ac5a40fc5d1a8a", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
!! Copyright (C) Stichting Deltares, 2012-2016.
!!
!! This program is free software: you can redistribute it and/or modify
!! it under the terms of the GNU General Public License version 3,
!! as published by the Free Software Foundation.
!!
!! This program is distributed in the hope that it will be useful,
!! b... | {"hexsha": "a19ab777b2ae65499b945d6cca67b4cce1447425", "size": 3407, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "docker/water/delft3d/tags/v6686/src/engines_gpl/waq/packages/waq_kernel/src/waq_process/tfalg.f", "max_stars_repo_name": "liujiamingustc/phd", "max_stars_repo_head_hexsha": "4f815a738abad43531d02a... |
import numpy as np
import pandas as pd
from pandas import (
DataFrame,
Series,
date_range,
timedelta_range,
)
import pandas._testing as tm
def _check_mixed_int(df, dtype=None):
# GH#41672
result = DataFrame([], columns=['lang', 'name'])
result = result.agg({'name': lambda y: y.values})
... | {"hexsha": "16d769afb93f1944e5ac1df23d954ebcfea17ad5", "size": 507, "ext": "py", "lang": "Python", "max_stars_repo_path": "pandas/tests/frame/test_aggregate.py", "max_stars_repo_name": "weikhor/pandas", "max_stars_repo_head_hexsha": "ae6538f5df987aa382ec1499679982aaff1bfd86", "max_stars_repo_licenses": ["PSF-2.0", "Apa... |
module Verifier where
open import Definitions
open import NatEquality using (_≟_ ; equality-disjoint)
check1 : (m n : ℕ) → Equal? m n
check1 = _≟_
check2 : (m n : ℕ) → m ≡ n → m ≢ n → ⊥
check2 = equality-disjoint
| {"hexsha": "dd5f327ee64ca7ee2db177706147e01c06629842", "size": 217, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "problems/NatEquality/Verifier.agda", "max_stars_repo_name": "danr/agder", "max_stars_repo_head_hexsha": "ece25bed081a24f02e9f85056d05933eae2afabf", "max_stars_repo_licenses": ["BSD-3-Clause"], "max... |
//==============================================================================
// Copyright 2003 - 2012 LASMEA UMR 6602 CNRS/Univ. Clermont II
// Copyright 2009 - 2012 LRI UMR 8623 CNRS/Univ Paris Sud XI
//
// Distributed under the Boost Software License, Version 1.0.
// ... | {"hexsha": "d1433a1e368abd60ad2e0ddbb0eefe7b0584faf1", "size": 1797, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "modules/boost/simd/sdk/include/boost/simd/sdk/memory/is_aligned.hpp", "max_stars_repo_name": "pbrunet/nt2", "max_stars_repo_head_hexsha": "2aeca0f6a315725b335efd5d9dc95d72e10a7fb7", "max_stars_repo_... |
import kagglegym
import numpy as np
import pandas as pd
import bz2
import base64
import pickle as pk
import warnings
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.linear_model import LinearRegression
# The "environment" is our interface.
env = kagglegym.make()
# We get our initial observation by call... | {"hexsha": "57bdc28cecf06a7f9863949afb132253dd7118cb", "size": 4699, "ext": "py", "lang": "Python", "max_stars_repo_path": "main.py", "max_stars_repo_name": "anthonyhu/twosigma-LETH-Al", "max_stars_repo_head_hexsha": "10306e35fdd7e0d2b7f3d19dce27674ad07fcddb", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count... |
'''
Calculates PV from OpenMARS data.
'''
import numpy as np
import xarray as xr
import os, sys
import glob
import analysis_functions as funcs
import PVmodule as PV
def calculate_pfull(psurf, siglev):
r"""Calculates full pressures using surface pressures and sigma coordinates
psurf : array-like
... | {"hexsha": "f4966e9351a7af0dcbccc21be78dacede0424733", "size": 5307, "ext": "py", "lang": "Python", "max_stars_repo_path": "calculate_PV_OpenMARS.py", "max_stars_repo_name": "BrisClimate/Roles_of_latent_heat_and_dust_on_the_Martian_polar_vortex", "max_stars_repo_head_hexsha": "11b4e1ba958eefbc03f9491cb68485637b696346",... |
[STATEMENT]
lemma C_eq_normalizeQ:
"DenyAll \<in> set (policy2list p) \<Longrightarrow> allNetsDistinct (policy2list p) \<Longrightarrow>
all_in_list (policy2list p) (Nets_List p) \<Longrightarrow>
C (list2FWpolicy (normalizeQ p)) = C p"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>DenyAll \<in... | {"llama_tokens": 213, "file": "UPF_Firewall_FWNormalisation_NormalisationIntegerPortProof", "length": 1} |
import time
import pyro
import torch
import networkx as nx
import pyro.distributions as dist
torch.set_default_tensor_type(torch.DoubleTensor)
class ApproximateCounterfactual():
"""A class for performing Pyro-based approximate inference with a Structural Causal Model.
Has the ability to handle and operate on... | {"hexsha": "baaeb8e23c69ae09f19b66d806ca0c2c88350e0f", "size": 18584, "ext": "py", "lang": "Python", "max_stars_repo_path": "approximate.py", "max_stars_repo_name": "Jude188/TwinNetworks", "max_stars_repo_head_hexsha": "3213358c7ac869e1c72c82554b1a3724ff368bad", "max_stars_repo_licenses": ["MIT", "Unlicense"], "max_sta... |
import re
from io import StringIO
import numpy as np
import pandas
from pycosmosac.molecule import mole, cavity
from pycosmosac.utils import elements
def get_molecule(data):
sdata = re.search(r"!DATE[a-zA-Z0-9:\s]+\n(.+)end\s*", data, re.DOTALL).group(1)
df = pandas.read_csv(StringIO(sdata), names=['atomidenti... | {"hexsha": "be2abddf732d1e623a2923f1814c0fe2376273a3", "size": 2486, "ext": "py", "lang": "Python", "max_stars_repo_path": "pycosmosac/cosmo/read_cosmo_bagel.py", "max_stars_repo_name": "fishjojo/pycosmosac", "max_stars_repo_head_hexsha": "9984a0ca2c9093142de60112f4c9a7fe33865946", "max_stars_repo_licenses": ["MIT"], "... |
[STATEMENT]
lemma lindemann_weierstrass_integral:
fixes u :: complex and f :: "complex poly"
defines "df \<equiv> \<lambda>n. (pderiv ^^ n) f"
defines "m \<equiv> degree f"
defines "I \<equiv> \<lambda>f u. exp u * (\<Sum>j\<le>degree f. poly ((pderiv ^^ j) f) 0) -
(\<Sum>j\<le>degree f. ... | {"llama_tokens": 14321, "file": "E_Transcendental_E_Transcendental", "length": 71} |
import numpy as np
from pySDC.core.Errors import ParameterError
from pySDC.core.Problem import ptype
from pySDC.implementations.datatype_classes.mesh import mesh, imex_mesh
class buck_converter(ptype):
"""
Example implementing the buck converter model as in the description in the PinTSimE project
Attribu... | {"hexsha": "d77f850ab187d7bfdc85e2f6559dd5f5964ffd4c", "size": 3906, "ext": "py", "lang": "Python", "max_stars_repo_path": "pySDC/implementations/problem_classes/BuckConverter.py", "max_stars_repo_name": "brownbaerchen/pySDC", "max_stars_repo_head_hexsha": "31293859d731646aa09cef4345669eac65501550", "max_stars_repo_lic... |
import numpy as np
import cv2
from keras.models import load_model
from mtcnn.mtcnn import MTCNN
from PIL import Image
from sklearn.svm import SVC
from SVMclassifier import model as svm
from SVMclassifier import out_encoder
model = load_model('../models/facenet_keras.h5')
# get the face embedding for one face
def get... | {"hexsha": "1fe97dde192c7abb68781329d90b28256715e635", "size": 3139, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/real_time_face_rec.py", "max_stars_repo_name": "esgyu/AI_PROJECT_SERVER", "max_stars_repo_head_hexsha": "b0c1d1ac44bd88d5a32920065bfbc3844c649fbc", "max_stars_repo_licenses": ["MIT"], "max_sta... |
from __future__ import division
import numpy as np
from ..utils.importing import import_file
class ObjectDetector(object):
"""
Object detection workflow.
This workflow is used to train image object detection tasks, typically
when the dataset cannot be stored in memory.
Submissions need to conta... | {"hexsha": "fe3356435421c4b30c7cc10371472fb392611ae8", "size": 5706, "ext": "py", "lang": "Python", "max_stars_repo_path": "rampwf/workflows/object_detector.py", "max_stars_repo_name": "mehdidc/ramp-workflow", "max_stars_repo_head_hexsha": "68146005369b31c1c855c2372172d355440994a1", "max_stars_repo_licenses": ["BSD-3-C... |
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 24 15:03:29 2017
@author: r.dewinter
"""
from predictorEGO import predictorEGO
from hypervolume import hypervolume
from paretofrontFeasible import paretofrontFeasible
import copy
import numpy as np
import time
import pygmo as pg
def optimizeSMSEGOcriterio... | {"hexsha": "94b2c8f44558a2ab38d8b689dcc3912ad4b8bcb2", "size": 1970, "ext": "py", "lang": "Python", "max_stars_repo_path": "CEGO/optimizeSMSEGOcriterion.py", "max_stars_repo_name": "napa-jmm/CEGO", "max_stars_repo_head_hexsha": "172d511133a608ca5bf265d9ebd2937b8a171b3e", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
"""Reconstruct current density distribution of Maryland multigate device.
Device ID: JS311_2HB-2JJ-5MGJJ-MD-001_MG2.
Scan ID: JS311-BHENL001-2JJ-2HB-5MGJJ-MG2-060.
Fridge: vector9
This scan contains Fraunhofer data for a linear multigate -1-2-3-4-5-
Gates 1 and 5 are grounded; gates 2 and 4 are shorted.
Both Vg3 and ... | {"hexsha": "afa41bbf2fb9fdb9feddcb9472e2bebe0fe8d408", "size": 6331, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/jj/JS311_2HB-2JJ-5MGJJ-MD-001/analyze_md_multigate_060.py", "max_stars_repo_name": "ShabaniLab/DataAnalysis", "max_stars_repo_head_hexsha": "e234b7d0e4ff8ecc11e58134e6309a095abcd2c0", "max... |
# -*- coding: utf-8 -*-
from kaplot import *
import scipy
class NFWTri(object):
def __init__(self, p, q, nfw_xaxis):
self.p = p
self.q = q
self.nfw_xaxis = nfw_xaxis
def run(self, args, opts, scope):
global logrho_model
N = 8
#sigmas = zeros(N) + arange(1,N)
logsigmas = zeros(N) #(arange(N)-N/2.)*0... | {"hexsha": "23583ab4aa5f7d90a9cb667cab259b36bc1e46eb", "size": 6551, "ext": "py", "lang": "Python", "max_stars_repo_path": "mab/gd/tri/potential.py", "max_stars_repo_name": "maartenbreddels/mab", "max_stars_repo_head_hexsha": "112dcfbc4a74b07aff13d489b3776bca58fe9bdf", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
# 4. faza: Analiza podatkov
# Uvozimo funkcijo za uvoz spletne strani.
# source("lib/xml.r")
# Preberemo spletno stran v razpredelnico.
# cat("Uvažam spletno stran...\n")
# tabela <- preuredi(uvozi.obcine(), obcine)
# Narišemo graf v datoteko PDF.
# cat("Rišem graf...\n")
# pdf("slike/naselja.pdf", width=6, height=4... | {"hexsha": "aea27f7526119237af53fd5f0ed1d3e31d60b07b", "size": 18669, "ext": "r", "lang": "R", "max_stars_repo_path": "analiza/analiza.r", "max_stars_repo_name": "statijana/APPR-2014-15", "max_stars_repo_head_hexsha": "4117ab91075a70b2dd0eb3ed23d39b2b7629b65c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nul... |
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from kern import CombinationKernel
from ...util.caching import Cache_this
import itertools
def numpy_invalid_op_as_exception(func):
"""
A decorator that allows catching numpy in... | {"hexsha": "a3b4997332109fe2f65f659336043e692db0ef56", "size": 3511, "ext": "py", "lang": "Python", "max_stars_repo_path": "GPy/kern/_src/prod.py", "max_stars_repo_name": "strongh/GPy", "max_stars_repo_head_hexsha": "775ce9e64c1e8f472083b8f2430134047d97b2fa", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_coun... |
[STATEMENT]
lemma delete_Linorder:
assumes "k > 0" "root_order k t" "sorted_less (leaves t)" "Laligned t u" "bal t" "x \<le> u"
shows "leaves (delete k x t) = del_list x (leaves t)"
and "Laligned (delete k x t) u"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. leaves (delete k x t) = del_list x (leaves t) &&... | {"llama_tokens": 714, "file": "BTree_BPlusTree_Set", "length": 4} |
function [exp,waschanged] = exp_replacerepeated(exp,rules)
% Apply substitution rules to some expression until it no longer changes.
% [Out-Expression,Changed] = exp_replacerepeated(In-Expression,Rule-List)
%
% Rules may contain blanks and placeholders.
%
% In:
% In-Expression : some expression in which substitution ... | {"author": "goodshawn12", "repo": "REST", "sha": "e34ce521fcb36e7813357a9720072dd111edf797", "save_path": "github-repos/MATLAB/goodshawn12-REST", "path": "github-repos/MATLAB/goodshawn12-REST/REST-e34ce521fcb36e7813357a9720072dd111edf797/dependencies/BCILAB/code/expressions/exp_replacerepeated.m"} |
SUBROUTINE chint(a,b,c,cint,n)
INTEGER n
REAL a,b,c(n),cint(n)
INTEGER j
REAL con,fac,sum
con=0.25*(b-a)
sum=0.
fac=1.
do 11 j=2,n-1
cint(j)=con*(c(j-1)-c(j+1))/(j-1)
sum=sum+fac*cint(j)
fac=-fac
11 continue
cint(n)=con*... | {"hexsha": "f98cf05c71ac0664e1930289a6410e50f8018fde", "size": 408, "ext": "for", "lang": "FORTRAN", "max_stars_repo_path": "NR-Functions/Numerical Recipes- Example & Functions/Functions/chint.for", "max_stars_repo_name": "DingdingLuan/nrfunctions_fortran", "max_stars_repo_head_hexsha": "37e376dab8d6b99e63f6f1398d0c33d... |
import os
import re
import matplotlib.pyplot as plt
from skimage.transform import resize, rescale
import numpy as np
from tensorflow.keras.layers import Dense, Flatten, Conv2D, Input, MaxPooling2D, Dropout, UpSampling2D,add
from tensorflow.keras import regularizers
from tensorflow.keras.models import Model
#---------... | {"hexsha": "57445f1b72561bd6d3caccae2dd31118a1bcf942", "size": 4777, "ext": "py", "lang": "Python", "max_stars_repo_path": "isr.ipynb.py", "max_stars_repo_name": "SACHIN446/Image-Super-Resolution-Using-AutoEncoder", "max_stars_repo_head_hexsha": "64c295214d881529fd3844e9931f7c7b9391e580", "max_stars_repo_licenses": ["M... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 5 15:22:56 2020
@author: matthew
"""
#%%
def deformation_wrapper(lons_mg, lats_mg, deformation_ll, source, dem = None,
asc_or_desc = 'asc', incidence = 23, **kwargs):
""" A function to prepare grids of pixels and d... | {"hexsha": "675b96d5167b39ec36aa1ae541a9f8390170123a", "size": 40871, "ext": "py", "lang": "Python", "max_stars_repo_path": "syinterferopy/syinterferopy.py", "max_stars_repo_name": "matthew-gaddes/Synthetic-interferograms", "max_stars_repo_head_hexsha": "3cbc553c7a687dd9f94a984231064861ee8363be", "max_stars_repo_licens... |
"""
I/O module for BRAIN files (Matlab NDT library of Universiy of Bristol).
Implemented as of 20/6/2016:
- dtype of variables is according to settings.py
- get element dimensions from el_x1, el_y1, el_z1, el_x2, el_y2, el_z2:
Information calculated is probe orientation dependent.
"""
import numpy as np
from ... | {"hexsha": "a8738520e3d3b1a67f1e4958aa4e1a2e71e664c1", "size": 5527, "ext": "py", "lang": "Python", "max_stars_repo_path": "arim/io/brain.py", "max_stars_repo_name": "will-jj/arim", "max_stars_repo_head_hexsha": "fc15efe171a41355090123fcea10406ee75efe31", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 14, "max_... |
### Author Douwe Spaanderman - 16 June 2020 ###
# This script reads all the files maf files and creates a major list of files
import pandas as pd
from pathlib import Path
import warnings
import numpy as np
import argparse
import time
import json
# Currently use sys to get other script - in Future use package
import ... | {"hexsha": "8ecbe4547a38a6e09ca382b733ec47a3bc6ebc66", "size": 10487, "ext": "py", "lang": "Python", "max_stars_repo_path": "CellCulturePy/Panel/maf.py", "max_stars_repo_name": "Douwe-Spaanderman/Broad_DJ_AI", "max_stars_repo_head_hexsha": "d151b35d2c05b7ca12653abca4f73cf438399b0f", "max_stars_repo_licenses": ["MIT"], ... |
#!/usr/local/sci/bin/python2.7
#*****************************
#
# general Python gridding script
#
#
#************************************************************************
'''
Author: Robert Dunn
Created: March 2016
Last update: 12 April 2016
Location: /project/hadobs2/hadisdh/marine/PROGS/Build
-------------------... | {"hexsha": "4f942cab1ceb5060ca2034a7b717095c4ea2d9e4", "size": 45215, "ext": "py", "lang": "Python", "max_stars_repo_path": "EUSTACE_SST_MAT/gridding_cam.py", "max_stars_repo_name": "Kate-Willett/HadISDH_Marine_Build", "max_stars_repo_head_hexsha": "293b4c89dc6e04e47d3f6e3645cf0f610beca2f2", "max_stars_repo_licenses": ... |
[STATEMENT]
lemma LeftDerivationFix_grow_prefix:
assumes LDF: "LeftDerivationFix (b1@[X]@b2) (length b1) D j c"
assumes prefix_b1: "LeftDerives1 prefix e r b1"
shows "LeftDerivationFix (prefix@[X]@b2) (length prefix) ((e, r)#D) j c"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. LeftDerivationFix (prefix @ [X]... | {"llama_tokens": 7017, "file": "LocalLexing_Ladder", "length": 43} |
import sys
import os
import re
from typing import Union
import shutil
import io
import threading
import concurrent.futures
import queue
import lzma
import configparser
import logging
from collections import OrderedDict
import multiprocessing
import numpy as np
from . import converter
# ============================... | {"hexsha": "387622497f2d3ef0982378355b8ba5054fbc0901", "size": 22655, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/py/cavitylearn/data.py", "max_stars_repo_name": "akors/cavitylearn", "max_stars_repo_head_hexsha": "a03d159cbefce83d4c4c731a9c2573e7261faf91", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
import gzip
import os
import pickle
import torch
from torch import nn
import torch.utils.data as data_utils
import numpy as np
import torchvision
from torchvision import transforms
'''
spherical MNIST related
'''
def load_spherical_data(path='/workspace/tasks/spherical', batch_size=32):
data_file = os.path.jo... | {"hexsha": "391f88e24cd10127fbab3ba7b69ef0868d35b187", "size": 6413, "ext": "py", "lang": "Python", "max_stars_repo_path": "old/bananas/darts/cnn/utils_data.py", "max_stars_repo_name": "rtu715/NAS-Bench-360", "max_stars_repo_head_hexsha": "d075006848c664371855c34082b0a00cda62be67", "max_stars_repo_licenses": ["MIT"], "... |
[STATEMENT]
lemma emb_step_arg: "is_App t \<Longrightarrow> t \<rightarrow>\<^sub>e\<^sub>m\<^sub>b (arg t)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. is_App t \<Longrightarrow> t \<rightarrow>\<^sub>e\<^sub>m\<^sub>b arg t
[PROOF STEP]
by (metis emb_step.intros(2) tm.collapse(2)) | {"llama_tokens": 115, "file": "Lambda_Free_EPO_Embeddings", "length": 1} |
# This code is part of Qiskit.
#
# (C) Copyright IBM 2021.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative wo... | {"hexsha": "e1a532f7b66f1cf23c4ff4f9a7f8d6a6801b0e2c", "size": 10917, "ext": "py", "lang": "Python", "max_stars_repo_path": "qiskit_nature/problems/second_quantization/lattice/lattices/triangular_lattice.py", "max_stars_repo_name": "jschuhmac/qiskit-nature", "max_stars_repo_head_hexsha": "b8b1181d951cf8fa76fe0db9e5ea19... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 6 07:50:51 2018
@author: markditsworth
"""
import zen
import numpy as np
import traceback
def out_degree_dist(G,output_file):
try:
ddist = zen.degree.ddist(G,normalize=False,direction='out_dir')
n = len(ddist)
k = np.a... | {"hexsha": "03d8c50b0503144d5baa8d8f74ac25bfd47f1487", "size": 2579, "ext": "py", "lang": "Python", "max_stars_repo_path": "Scripts/Out_Degree_Dist_Calc.py", "max_stars_repo_name": "markditsworth/RedditCommentAnalysis", "max_stars_repo_head_hexsha": "4db34accdda2e8c13747acc66e67aceeb6bdfbbc", "max_stars_repo_licenses":... |
# %% Imports
import argparse
from collections import namedtuple
from pathlib import Path
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# %% Flags
parser = argparse.ArgumentParser(description='Export Wandb results')
parser.add_argument('--tag', type=str)
flags = parser.pa... | {"hexsha": "9d477af1235821c1c2c1c5a9f086d59ebb1ba85b", "size": 5640, "ext": "py", "lang": "Python", "max_stars_repo_path": "experiments/single_network/plot_results.py", "max_stars_repo_name": "nitarshan/robust-generalization-measures", "max_stars_repo_head_hexsha": "8e9012991ddef1603bab5b6ab31ace6fbfc67ac6", "max_stars... |
module BoundaryCondition
export set_outlet_nonreflect_boundary!,set_outlet_costant_p_boundary!,
set_inlet_constant_h!,set_outlet_costant_h_boundary!,set_inlet_interface!,set_outlet_interface!,
get_L_from_interface,get_L_from_nonreflect,get_d_from_L_inflow,get_d_from_L_outflow
using..Systems
function get_L_from_inter... | {"hexsha": "b46181cf459c6f9f857da268035284e950ad5343", "size": 11395, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/BoundaryCondition.jl", "max_stars_repo_name": "liyuxuan48/thermo-network", "max_stars_repo_head_hexsha": "92bbcc909a74232e8caa18c3f99d5f96b746de12", "max_stars_repo_licenses": ["MIT"], "max_st... |
#!/usr/bin/env python3
# Author: Octavio Castillo Reyes
# Contact: octavio.castillo@bsc.es
"""Define functions a 3D CSEM/MT solver using high-order vector finite element method (HEFEM)."""
# ---------------------------------------------------------------
# Load python modules
# ---------------------------------------... | {"hexsha": "892b375da211ecea69f5d5889c81a48be8dc6344", "size": 26261, "ext": "py", "lang": "Python", "max_stars_repo_path": "petgem/solver.py", "max_stars_repo_name": "MTA09/petgem", "max_stars_repo_head_hexsha": "eb9ad46b3c88d3fd13fb0270eb00d2a147dbb798", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_count":... |
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