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# -*- coding: utf-8 -*-
"""
Created on Mon Aug 17 19:17:54 2020
@author: Philipe_Leal
# Reference from: https://www.earthdatascience.org/courses/use-data-open-source-python/intro-raster-data-python/raster-data-processing/reproject-raster/
"""
import os
import numpy as np
import rasterio as rio
from rasterio.warp im... | {"hexsha": "d72ffaa1d1e5d5b090a00e19a547ef369224364b", "size": 1513, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/rasterio/rasterio_reprojection.py", "max_stars_repo_name": "PhilipeRLeal/xarray_case_studies", "max_stars_repo_head_hexsha": "b7771fefde658f0d450cbddd94637ce7936c5f52", "max_stars_repo_lic... |
/*
* Copyright (C) 2012-2014 Open Source Robotics Foundation
*
* 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... | {"hexsha": "223c80477320bd119a519df3cebbf5ee8b52a7d9", "size": 31674, "ext": "hh", "lang": "C++", "max_stars_repo_path": "gazebo/rendering/Scene.hh", "max_stars_repo_name": "hyunoklee/Gazebo", "max_stars_repo_head_hexsha": "619218c0bb3dc8878b6c4dc2fddf3f7ec1d85497", "max_stars_repo_licenses": ["ECL-2.0", "Apache-2.0"],... |
[STATEMENT]
lemma e_lam_intro[intro]: "\<lbrakk> v = VFun f;
\<forall> v1 v2. (v1,v2) \<in> set f \<longrightarrow> v2 \<in> E e ((x,v1)#\<rho>) \<rbrakk>
\<Longrightarrow> v \<in> E (ELam x e) \<rho>"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>v = VFun f; \<forall>v1 v2. (v1, v2) \<in> set f ... | {"llama_tokens": 200, "file": "Decl_Sem_Fun_PL_DenotLam5", "length": 1} |
%ASAGLOB_MEAN_ADJ Subtraction of the signal mean identifier
% Declaring the variable ASAGLOB_MEAN_ADJ in the base workspace, for
% example by typing at the command prompt,
% ASAglob_mean_adj = 1;
% will enable the ARMASA functions, ARMASEL, SIG2AR, SIG2MA and
% SIG2ARMA to read out the value of ASAGLOB_ME... | {"author": "Sable", "repo": "mcbench-benchmarks", "sha": "ba13b2f0296ef49491b95e3f984c7c41fccdb6d8", "save_path": "github-repos/MATLAB/Sable-mcbench-benchmarks", "path": "github-repos/MATLAB/Sable-mcbench-benchmarks/mcbench-benchmarks-ba13b2f0296ef49491b95e3f984c7c41fccdb6d8/1330-armasa/ARMASA/ASA/ASAglob_mean_adj/Cont... |
#!/usr/bin/env python
# Siconos is a program dedicated to modeling, simulation and control
# of non smooth dynamical systems.
#
# Copyright 2021 INRIA.
#
# 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 L... | {"hexsha": "26a57247e85dc31c42e831bdee383bb1f0edeaaa", "size": 3486, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/control/Relay/SimpleExampleRelay_with_plugin.py", "max_stars_repo_name": "siconos/siconos-tutorials", "max_stars_repo_head_hexsha": "821365a6ce679fc3d606b272ff069134e3c6aa4b", "max_stars_... |
# IMPORT DEPENDENCIES
import datetime as dt
import pandas as pd
import numpy as np
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func
from flask import Flask, jsonify
####################
# SQL DATABASE SETUP
#############... | {"hexsha": "34c20e30efba2d18590c676e5f6cc3a83c8fd0a1", "size": 2986, "ext": "py", "lang": "Python", "max_stars_repo_path": "app.py", "max_stars_repo_name": "mauricio4337/Surfs-up", "max_stars_repo_head_hexsha": "8a9910d1bd35ef48222782b569f71b75071b0d0a", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "max_st... |
import gym
import numpy as np
from EnvOpenDogRun import EnvOpenDogRun
import time
import eogmaneo
env = EnvOpenDogRun(renders=True)
env.seed(0)
########################### Create Agent ###########################
# Create hierarchy
cs = eogmaneo.ComputeSystem(8)
lds = []
layerSize = 3
for i in range(3):
ld = ... | {"hexsha": "4e0a5abb07686a001b4a89c2d8b838b897e41d75", "size": 2434, "ext": "py", "lang": "Python", "max_stars_repo_path": "OpenDogRunTest.py", "max_stars_repo_name": "222464/OpenDogSimulator", "max_stars_repo_head_hexsha": "12249c63b2721e6090986b4cbe810258c5cc8250", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
import numpy as np
from tqdm import tqdm
from agents import GreedyAgent
from agents import RandomJammer
from RLagents import Agent
def instant_reward(SNR, SINR):
gain = [10*np.log2(1.+x) - 10*np.log2(1.+y) for x, y in zip(SNR, SINR)]
return sum(gain)
def simulate_random(env, N_JAMMER, N_CHANNEL, J_POWERS, C_pow... | {"hexsha": "61e52f8b3df78bc88b078a668f6f5039c2cc77a8", "size": 4533, "ext": "py", "lang": "Python", "max_stars_repo_path": "simulation.py", "max_stars_repo_name": "Juncheng-Dong/MARL-JAM", "max_stars_repo_head_hexsha": "b05792b0f2dab2bfe093781c696b73eb3c07d1af", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nu... |
from openeo import Connection
from openeo.rest.datacube import DataCube, PGNode, THIS
from openeo.rest.job import RESTJob
from openeo.processes import *
import numpy as np
import math
import xarray as xr
def fit_function_season(x:ProcessBuilder,parameters):
pi=math.pi
a0 = array_element(parameters,0)
a1 = ... | {"hexsha": "bbf8691708865e92f3359df3a71f7fdb65740263", "size": 8893, "ext": "py", "lang": "Python", "max_stars_repo_path": "change_detection_utils.py", "max_stars_repo_name": "openEOPlatform/SRR2_notebooks", "max_stars_repo_head_hexsha": "549405407d22e94b0c022dc79d58208923269ead", "max_stars_repo_licenses": ["Apache-2.... |
// Copyright David Stone 2020.
// 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)
#pragma once
#include <tm/stat/calculate_ivs_and_evs.hpp>
#include <tm/stat/ev.hpp>
#include <tm/stat/iv.hpp>
#include <tm/string_... | {"hexsha": "1f186a3fe9a87f81c5a8466a7b928515ec7f0181", "size": 3147, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "source/tm/clients/pokemon_lab/write_team_file.hpp", "max_stars_repo_name": "davidstone/technical-machine", "max_stars_repo_head_hexsha": "fea3306e58cd026846b8f6c71d51ffe7bab05034", "max_stars_repo_l... |
\documentclass[../main.tex]{subfiles}
\begin{document}
\chapter{Recurrence Relations}
As we mentioned briefly about the power of recursion is in the whole algorithm design and analysis, we dedicate this chapter to recurrence relation. To summarize, recurrence relation can help with:
\begin{itemize}
\item Recurrence... | {"hexsha": "b7c48849e9a07dae168a80067293643ceedc4d96", "size": 21857, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "Easy-Book/chapters/chapter_recurrence_relation.tex", "max_stars_repo_name": "stungkit/Algorithms-and-Coding-Interviews", "max_stars_repo_head_hexsha": "131199fea0b082d92c0f272a495c7a56a3242b71", "m... |
# MIT License
#
# Copyright (c) 2020 Archis Joglekar
#
# 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, mer... | {"hexsha": "5d1d625a9697b2cc8c985fac92e96cf4adf4c3f6", "size": 7368, "ext": "py", "lang": "Python", "max_stars_repo_path": "vlapy/manager.py", "max_stars_repo_name": "kyleniemeyer/VlaPy", "max_stars_repo_head_hexsha": "efbd38f0d53fb4a5ffa61ecbfbc14d3383eb0f48", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 22,... |
[STATEMENT]
lemma nth_map_out_of_bound: "i \<ge> length xs \<Longrightarrow> map f xs ! i = [] ! (i - length xs)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. length xs \<le> i \<Longrightarrow> map f xs ! i = [] ! (i - length xs)
[PROOF STEP]
by (induct xs arbitrary:i, auto) | {"llama_tokens": 108, "file": "Jordan_Normal_Form_Matrix", "length": 1} |
import re
import itertools
import os
import string
import requests
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from collections import Counter
from bs4 import BeautifulSoup
from nltk.corpus import stopwords
uri_re = r'(?i)\b((?:htt... | {"hexsha": "0ca05cb59527347b570087bff48bce6e956970f9", "size": 7942, "ext": "py", "lang": "Python", "max_stars_repo_path": "data_helpers.py", "max_stars_repo_name": "duyunshu/nlp-transfer-borealisai", "max_stars_repo_head_hexsha": "8ff658ab66647cf641cb6fb8276cc3ca5ad0e8e3", "max_stars_repo_licenses": ["Apache-2.0"], "m... |
import sys
sys.path.append("../src")
from pyroomacoustics import ShoeBox, Room
import gym
import numpy as np
import matplotlib.pyplot as plt
import torch
import room_types
import agent
import audio_room
import utils
import constants
import nussl
from datasets import BufferData
import time
import audio_processing
fro... | {"hexsha": "712b2fa39675e55cb0dc578f4324808a18a95987", "size": 2713, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_transforms.py", "max_stars_repo_name": "pseeth/otoworld", "max_stars_repo_head_hexsha": "636ca717c6e571b465ddcd836fa430ccdc53debf", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
using MagmaThermoKinematics.Diffusion3D
using ParallelStencil
using ParallelStencil.FiniteDifferences3D
using Plots
using LinearAlgebra
using SpecialFunctions
using Test
const CreatePlots = false # easy way to deactivate plotting throughout
# Initialize for multiple threads (GPU is not tested here)
@init_paral... | {"hexsha": "e22b7c530eb08c97cb5682a96779add9107a4032", "size": 6869, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/test_Diffusion3D.jl", "max_stars_repo_name": "boriskaus/MagmaThermoKinematics.jl", "max_stars_repo_head_hexsha": "5bff99c6f50982028ecb2dc251cf18a81790e0c8", "max_stars_repo_licenses": ["MIT"],... |
[STATEMENT]
lemma all_subset_all_inI: "map interval_of a all_subset I" if "a all_in I"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. map interval_of a all_subset I
[PROOF STEP]
using that
[PROOF STATE]
proof (prove)
using this:
map real_of_float a all_in I
goal (1 subgoal):
1. map interval_of a all_subset I
[PROO... | {"llama_tokens": 149, "file": "Taylor_Models_Taylor_Models", "length": 2} |
\documentclass{article}
\usepackage[utf8]{inputenc}
\usepackage{amsmath,amssymb}
\newcommand\set[1]{\left\{#1\right\}}
\begin{document}
\section{Exercise 7}
Given 5 women and 9 men.
Let $\mathbb P(F)$ denote the probability that a female member is chosen.
Let $\mathbb P(F\,|\,F)$ denote the probability that a female ... | {"hexsha": "0444f76ab448db6210fa072fb5385dc8226ad96e", "size": 2830, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "probability_theory_practicals/ex7/solution.tex", "max_stars_repo_name": "prokls/math-lecture-notes", "max_stars_repo_head_hexsha": "d1a94e128d13ce4399a9cc55323b2f8e0d9494fd", "max_stars_repo_license... |
#!/usr/bin/env python
import roslib; roslib.load_manifest("dynamixel_hr_ros")
import rospy
from std_msgs.msg import *
import json
from dynamixel_hr_ros.msg import *
from dxl import *
import logging
import time
import pygame
import numpy as np
import math
import csv
import itertools
from threading import Timer
loggin... | {"hexsha": "01ae1fd5eb9670ddf7debc5e96ada7375d0bbb5a", "size": 1722, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/motion_control.py", "max_stars_repo_name": "CuriosityLabTAU/puppet_ros", "max_stars_repo_head_hexsha": "817c90e5b17d599a3f323d251691e11a03e56674", "max_stars_repo_licenses": ["BSD-2-Clause... |
"""
autostep.py
===========
"""
from __future__ import print_function
import serial
import atexit
import json
import time
import numpy as np
import matplotlib.pyplot as plt
import threading
class Autostep(serial.Serial):
"""
Provides a serial interface to the autostep firmware for controlling the
LM647... | {"hexsha": "68a3e178d833b137dad0179d08b1d1a7eb39b5ae", "size": 29657, "ext": "py", "lang": "Python", "max_stars_repo_path": "software/python/autostep/autostep/autostep.py", "max_stars_repo_name": "hanhanhan-kim/autostep", "max_stars_repo_head_hexsha": "4072bcd47be7c25b48b0503198f031e98a4102be", "max_stars_repo_licenses... |
"""
Run offline logistic regression at each timestep, as an oracle.
This works like a performance upper bound.
Also this is closed set setting. Assuming fully labeled.
Author: Mengye Ren (mren@cs.toronto.edu)
"""
from __future__ import (absolute_import, division, print_function,
unicode_literal... | {"hexsha": "7b2cb18ccf03fb80a50365813d4b0327a46d2d92", "size": 9085, "ext": "py", "lang": "Python", "max_stars_repo_path": "fewshot/experiments/run_offline.py", "max_stars_repo_name": "sebamenabar/oc-fewshot-public", "max_stars_repo_head_hexsha": "2dad8c9f24cb1bfe72d8b13b33d28f6788d86ca8", "max_stars_repo_licenses": ["... |
import numpy
def special_mean_val(input_data, threshold):
mask = input_data > threshold;
temp=numpy.extract(mask,input_data)
final = numpy.mean(temp)
# print "Mean value was "+str(final)
return final;
| {"hexsha": "b0dde089b20c8bce5917dbaeb61bfc54fd4abaa9", "size": 242, "ext": "py", "lang": "Python", "max_stars_repo_path": "pyISTTOK/special_mean_val.py", "max_stars_repo_name": "arcozelo/python4isttokoper", "max_stars_repo_head_hexsha": "c17b0dc8c33ca37aaa3c4095a046aa4f22abae40", "max_stars_repo_licenses": ["MIT"], "ma... |
import os
import h5py
import math
import copy
from tqdm import tqdm
import torch
import torch.nn as nn
import itertools
import numpy as np
import utils.io as io
from utils.constants import save_constants, Constants
from .models.object_encoder import ObjectEncoder
from .models.cap_encoder import CapEncoder
from .models... | {"hexsha": "fbd24705b51dfd1bdfa2fcee4501803a3eb5ad87", "size": 7943, "ext": "py", "lang": "Python", "max_stars_repo_path": "exp/ground/eval_flickr_phrase_loc.py", "max_stars_repo_name": "ChopinSharp/info-ground", "max_stars_repo_head_hexsha": "12fba3c478b806f2fe068faac81237fd0f458b80", "max_stars_repo_licenses": ["Apac... |
import unittest
import logging
import os
import pandas as pd
import numpy as np
import cmapPy.pandasGEXpress.setup_GCToo_logger as setup_logger
import cmapPy.pandasGEXpress.parse_gct as pg
import cmapPy.pandasGEXpress.GCToo as GCToo
FUNCTIONAL_TESTS_PATH = "cmapPy/pandasGEXpress/tests/functional_tests/"
logger = log... | {"hexsha": "7fca7d2a3e91d0bc471820addd04b3e527e07e1e", "size": 13955, "ext": "py", "lang": "Python", "max_stars_repo_path": "cmapPy/pandasGEXpress/tests/python2_tests/test_parse_gct.py", "max_stars_repo_name": "dblyon/cmapPy", "max_stars_repo_head_hexsha": "d310d092dbf0a0596448c9bd1f75ffff0bb92f09", "max_stars_repo_lic... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
from plasticity.model._base import BasePlasticity
from plasticity.model.optimizer import Optimizer, SGD
from plasticity.model.weights import BaseWeights, Normal
__author__ = ['Nico Curti', 'Lorenzo Squadrani', 'SimoneGasperini']
__email__ = ['nico.cur... | {"hexsha": "b61f9f11f6c3636a0662677b261b045fbfbe8436", "size": 5930, "ext": "py", "lang": "Python", "max_stars_repo_path": "plasticity/model/hopfield.py", "max_stars_repo_name": "Nico-Curti/plasticity", "max_stars_repo_head_hexsha": "8159871d0aa31b096788e5aab785a1a969725ddf", "max_stars_repo_licenses": ["MIT"], "max_st... |
Rebol [
Title: "Core tests run with crash recovery"
File: %run-recover.r
Copyright: [2012 "Saphirion AG"]
License: {
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... | {"hexsha": "e5f574a8839e44c95bdc7519642ef4a5a3247bd4", "size": 1542, "ext": "r", "lang": "R", "max_stars_repo_path": "run-recover.r", "max_stars_repo_name": "0branch/rebol-test", "max_stars_repo_head_hexsha": "e3906c9439ce27a23b727bc45473e057a2206476", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 5, "m... |
# Preliminaries
#-------------------------------------------------
#install.packages('perm')
library(perm)
rm(list = ls())
# Fisher
#-------------------------------------------------
#permutations in a matrix
perms <- chooseMatrix(8, 4)
#observed values in treated [0,1,0,0,0,1,1,1]
A <- matrix(c(0.462, 0.731, 0.571, ... | {"hexsha": "c7e27951edc7e718fa97f6283f851deae2b3dd09", "size": 3662, "ext": "r", "lang": "R", "max_stars_repo_path": "homework7.r", "max_stars_repo_name": "samuxiii/r-projects", "max_stars_repo_head_hexsha": "13a17bdf5a3db2efcf785c4810bb55c86459bfb3", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max_st... |
export BrickletAnalogOutV2Identity
struct BrickletAnalogOutV2Identity
uid::String
connected_uid::String
position::Char
hardware_version::Vector{Integer}
firmware_version::Vector{Integer}
device_identifier::Integer
end
export BrickletAnalogOutV2
"""
Generates configurable DC voltage between 0... | {"hexsha": "12c1d6a3852a9f8c1ee05e56c98105bfeb7135ba", "size": 2020, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/devices/bricklet_analog_out_v2.jl", "max_stars_repo_name": "jonschumacher/PyTinkerforge.jl", "max_stars_repo_head_hexsha": "a37dfc8141bf86b9298277c66dec24387ccad6db", "max_stars_repo_licenses":... |
Jacob Lamoure is a user who edits pages on occasion.
| {"hexsha": "1cbcbea568e0d6bca7d7a7e7145701e95a3caedb", "size": 53, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/jlamoure.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nul... |
import matplotlib
import GUI
import VTKReader
import flow2D
import flow3D
import matplotlib.pyplot as plt
import numpy as np
def main():
times = [49.039, 69.635, 99.246, 108.474, 122.344]
xlabels = [500, 750, 1000, 1250, 1500]
plt.rcParams.update({'font.size': 16})
plt.rc('font', family='serif')
... | {"hexsha": "a946ca8db91455925dbaf16b9f5e15e6fb58e0f1", "size": 1715, "ext": "py", "lang": "Python", "max_stars_repo_path": "proposal/RQ3_Plot.py", "max_stars_repo_name": "Ayakuya/CSCI596FinalProject", "max_stars_repo_head_hexsha": "227eff80d6428ab0e192e29334fc63c7d6deda3a", "max_stars_repo_licenses": ["MIT"], "max_star... |
#include <iostream>
#include <vector>
#include <string>
#include <memory>
#include <Eigen/Dense>
#include "../include/layer.h"
using namespace Eigen;
int main()
{
using std::cout;
using std::endl;
using std::vector;
using std::string;
using std::shared_ptr;
using std::make_shared;
using na... | {"hexsha": "3a901d770e65c9040041b33ce6e345ffcae7e8f7", "size": 1830, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "test/test_batchnorm.cpp", "max_stars_repo_name": "potedo/zeroDL_cpp", "max_stars_repo_head_hexsha": "4d5b376d2cc3d0d8e1180662e906957c4a142bb4", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
cr .( include2 loading... )
| {"hexsha": "2c17eeaf748ad072470c2b26a6c73873e9e1a319", "size": 29, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "test/include2.f", "max_stars_repo_name": "amckewan/mcforth", "max_stars_repo_head_hexsha": "9c13abf10958fea1f5b10125206a8a485fa95001", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "max_... |
!****************************************************************************************************
!
! Subroutine : Write Calculation Results
!
!****************************************************************************************************
subroutine write_cgns(fid)
use iric
use global_variables
... | {"hexsha": "f72adf5199febead5113757c5b2fb41bf2a07272", "size": 1424, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/write_cgns.f90", "max_stars_repo_name": "kskinoue0612/iric-v4_solver", "max_stars_repo_head_hexsha": "df716c1ee5d5830abf1b269faaea4e52cf8f04bf", "max_stars_repo_licenses": ["MIT"], "max_star... |
\section{Eulerian-Lagrangian method}
So far we have said little about the backtracked values like $\bs{u}^*$.
These are calculated in SELFE via Eulerian-Lagrangian method (ELM).
| {"hexsha": "1e65d3c852816381a861e8ecb298c5a5931fb593", "size": 180, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "documents/form_elm.tex", "max_stars_repo_name": "water-e/BayDeltaSCHISM", "max_stars_repo_head_hexsha": "b532b51ef58a6ef3dbb4e74f82008a46db0f7686", "max_stars_repo_licenses": ["Apache-2.0"], "max_sta... |
"""
Code adapted based on: https://github.com/HobbitLong/SupContrast.
"""
from __future__ import print_function
import os
import sys
import argparse
import time
import math
import random
import numpy as np
import tensorboard_logger as tb_logger
import torch
from torch import nn
import torch.backends.cudnn as cudnn
fr... | {"hexsha": "d18c276e6ada2338ec99b2bcfa85f6835f1fdfee", "size": 16270, "ext": "py", "lang": "Python", "max_stars_repo_path": "ExCon/eval.py", "max_stars_repo_name": "DarrenZhang01/ExCon", "max_stars_repo_head_hexsha": "2467c2fa8c0c52edaf54091d2bfecd132eeae594", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count... |
"""Calculate the change in frequency for clades over time (aka the delta frequency or dfreq).
Design discussion is located on GitHub at https://github.com/nextstrain/ncov/pull/595
"""
import argparse
from augur.frequency_estimators import logit_transform
from augur.utils import annotate_parents_for_tree, read_node_data... | {"hexsha": "56a4f8057bf91be0666790bed54a21ed6d3a247b", "size": 7744, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/calculate_delta_frequency.py", "max_stars_repo_name": "ainisyahida/Ida_Waffy", "max_stars_repo_head_hexsha": "7c647df8abfc733d5c17368a84cd23312fac4bc4", "max_stars_repo_licenses": ["MIT"],... |
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
# Data preprocessing
data = pd.read_csv("RealEstate.csv")
# Converting Pandas dataframe to numpy array
X = data.Size.values.reshape(-1, 1)
Y = data.Price.values.reshape(-1, 1)
m = X.shape[0] # n... | {"hexsha": "792c9bc24640ff220a96521d6017e4e85991c16d", "size": 1198, "ext": "py", "lang": "Python", "max_stars_repo_path": "1-simple-linear-regression/slr_sklearn.py", "max_stars_repo_name": "arnakoguzhan/machine-learning", "max_stars_repo_head_hexsha": "c0df1d1e37d001af7ddc5ae06dd3eba0788d126f", "max_stars_repo_licens... |
import sys
import theano.sandbox.cuda
theano.sandbox.cuda.use('gpu{0}'.format(sys.argv[1]))
from deepjets.learning import test_model, train_model, cross_validate_model
from deepjets.models import get_maxout, load_model
from deepjets.utils import prepare_datasets
import numpy as np
n_images=400000
test_frac=0.5
sig_fi... | {"hexsha": "6cb19a165bb71fd02f02b429dc22b63378f8000b", "size": 1627, "ext": "py", "lang": "Python", "max_stars_repo_path": "etc/benchmark_maxout.py", "max_stars_repo_name": "deepjets/deepjets", "max_stars_repo_head_hexsha": "fc9c610d4fd80975d8d25eb0d7cd41d7dd318c75", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_st... |
! md_nve_lj.f90
! Molecular dynamics, NVE ensemble
PROGRAM md_nve_lj
!------------------------------------------------------------------------------------------------!
! This software was written in 2016/17 !
! by Michael P. Allen <m.p.allen@warwick.ac.uk... | {"hexsha": "cfbe3751764ccbe805844c447be453209f4474c0", "size": 11208, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "examples-master/md_nve_lj.f90", "max_stars_repo_name": "JungHoonJung/2021MD", "max_stars_repo_head_hexsha": "29bfae7a750217d50654e4973a2be6fb0d968bdf", "max_stars_repo_licenses": ["MIT"], "max_... |
#include <bits/stdc++.h>
#include <boost/tokenizer.hpp>
int64_t departure_time;
std::vector<int64_t> buses;
std::vector<std::pair<int64_t, int64_t>> buses_ids;
struct Euclid {
int64_t mi, mj;
};
int64_t next_time(const int64_t bus, int64_t departure_time) {
return bus * (departure_time / bus + 1) % departure_tim... | {"hexsha": "492b603a1b1a630133bb42619b0a17b64cf94f06", "size": 1999, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "2020/13.cpp", "max_stars_repo_name": "mdelorme/advent_of_code", "max_stars_repo_head_hexsha": "47142d501055fc0d36989db9b189be7e6756d779", "max_stars_repo_licenses": ["Unlicense"], "max_stars_count":... |
SUBROUTINE partition(nocc,modims,auxdims,PQ,PQ_inv,auxmomo,
\ oneeint,oneekin,alpha,pair)
! use omp_lib
Integer*4 nocc,modims,auxdims
Real*8 PQ(auxdims,auxdims), PQ_inv(auxdims,auxdims)
Real*8 auxmomo(modims,modims,auxdims), oneeint(modims,modims)
Real*8 oneekin(modims,modims),... | {"hexsha": "421e67f9fe220617da7e2fbc0c899bad814cd569", "size": 13228, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "src/partition.f", "max_stars_repo_name": "hongzhouye/mpe-mol", "max_stars_repo_head_hexsha": "325146f24193266d83c92932c20d40e0fc3b52b6", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_co... |
//
// execution/detail/submit_receiver.hpp
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Copyright (c) 2003-2022 Christopher M. Kohlhoff (chris at kohlhoff dot com)
//
// 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": "d784f6c8efc6e7b8c96cc115d36f0e675ae4c564", "size": 7468, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "AqooleEngine/src/main/cpp/boost/boost/asio/execution/detail/submit_receiver.hpp", "max_stars_repo_name": "kodai731/Aqoole-Engine-Android-Vulkan-Rendering-Engine-", "max_stars_repo_head_hexsha": "72c... |
#!/usr/bin/env python
from satistjenesten import io
import argparse
import os
import numpy
from datetime import datetime
def make_output_filepath(input_filename, output_dir):
output_basename = os.path.basename(input_filename)
output_filename = os.path.join(output_dir, os.path.splitext(output_basename)[0] + '.j... | {"hexsha": "56ec5da6d98572444da96ed3af20ec100f1d300c", "size": 2346, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/add_graphics_poseidon.py", "max_stars_repo_name": "mitkin/satistjenesten", "max_stars_repo_head_hexsha": "77c82e58580de907c5e85a6b9c2b8dc51daa84c9", "max_stars_repo_licenses": ["MIT"], "ma... |
(*
This is the definition of formal syntax for Dan Grossman's Thesis,
"SAFE PROGRAMMING AT THE C LEVEL OF ABSTRACTION".
Getting the heap really right including issues of searching
through the heap, assigning into the heap and getting an
address in the heap.
Alpha conversion can probably be ignored here.... | {"author": "briangmilnes", "repo": "CycloneCoqSemantics", "sha": "190c0fc57d5aebfde244efb06a119f108de7a150", "save_path": "github-repos/coq/briangmilnes-CycloneCoqSemantics", "path": "github-repos/coq/briangmilnes-CycloneCoqSemantics/CycloneCoqSemantics-190c0fc57d5aebfde244efb06a119f108de7a150/backup.3/TestingTheHeap.v... |
/*
Copyright (c) 2016 Xavier Leclercq
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, ... | {"hexsha": "c4e434a425a6fee0d7a2ebfa5c350edd4e1effef", "size": 3655, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "UICore/Source/Themes/ThemesFileRepository.cpp", "max_stars_repo_name": "codesmithyide/codesmithy", "max_stars_repo_head_hexsha": "9be7c2c45fa1f533aa7a7623b8f610737c720bca", "max_stars_repo_licenses"... |
(* Title: HOL/Auth/n_german_lemma_on_inv__47.thy
Author: Yongjian Li and Kaiqiang Duan, State Key Lab of Computer Science, Institute of Software, Chinese Academy of Sciences
Copyright 2016 State Key Lab of Computer Science, Institute of Software, Chinese Academy of Sciences
*)
header{*The n_german... | {"author": "lyj238Gmail", "repo": "newParaVerifier", "sha": "5c2d49bf8e6c46c60efa53c98b0ba5c577d59618", "save_path": "github-repos/isabelle/lyj238Gmail-newParaVerifier", "path": "github-repos/isabelle/lyj238Gmail-newParaVerifier/newParaVerifier-5c2d49bf8e6c46c60efa53c98b0ba5c577d59618/examples/n_german/n_german_lemma_o... |
import datetime
import gym
import multiprocessing
import numpy as np
from obstacle_tower_env import ObstacleTowerEnv, ObstacleTowerEvaluation
import os
from prettyprinter import pprint
import tensorboard
import tensorflow as tf
import tensorflow_probability as tfp
import time
from models.curiosity.agent import TowerAg... | {"hexsha": "4f1273deedd09ee5d1a4b3468c1b49d1dcf08e16", "size": 13044, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/models/curiosity/curiosity_agent.py", "max_stars_repo_name": "cstrojans/obstacle-tower-challenge", "max_stars_repo_head_hexsha": "3acbf0c6fda8d6cd4b09f3f112310d73058f1597", "max_stars_repo_li... |
// Copyright (c) 2014 The Bitcoin Core developers
// Distributed under the MIT software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#include "betting/bet.h"
#include "betting/bet_db.h"
#include "random.h"
#include "uint256.h"
#include "test/test_wagerr.h"
#inclu... | {"hexsha": "1e870d105608b907105fa869f80b01def8d4481f", "size": 5032, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/test/betting_tests.cpp", "max_stars_repo_name": "JSponaugle/wagerr", "max_stars_repo_head_hexsha": "7bfebaf7e480b4553736b537e0cb430d5f4d8b88", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
> module Nat.CoprimeProperties
> import Nat.Coprime
> import Nat.GCD
> import Nat.GCDOperations
> import Nat.GCDProperties
> import Nat.Divisor
> import Nat.DivisorOperations
> import Nat.DivisorProperties
> import Nat.OperationsProperties
> import Nat.GCDAlgorithm
> import Nat.GCDEuclid
> import Pairs.Operations
> im... | {"hexsha": "2a04a20f1d35e2d3a4caabcdf231ce0f483449c1", "size": 5973, "ext": "lidr", "lang": "Idris", "max_stars_repo_path": "Nat/CoprimeProperties.lidr", "max_stars_repo_name": "zenntenn/IdrisLibs", "max_stars_repo_head_hexsha": "a81c3674273a4658cd205e9bd1b6f95163cefc3e", "max_stars_repo_licenses": ["BSD-2-Clause"], "m... |
# ENVISIoN
#
# Copyright (c) 2020 Amanda Aasa & Amanda Svennblad
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,... | {"hexsha": "92416b902549f383bdbf593820c8932274add651", "size": 12506, "ext": "py", "lang": "Python", "max_stars_repo_path": "envisionpy/processor_network/Bandstructure3DNetworkHandler.py", "max_stars_repo_name": "Vevn/ENVISIoN", "max_stars_repo_head_hexsha": "d0e48a5ec38ed95375f632eafdc5814415f0f570", "max_stars_repo_l... |
#!/usr/bin/env Rscript
data = read.csv("hw1_data.csv")
isJune = data[['Month']] == 6
mean(data[isJune,][['Temp']])
| {"hexsha": "ca83a57c252866a3149f0d84888b44a25ef67b82", "size": 117, "ext": "r", "lang": "R", "max_stars_repo_path": "assignment-1/09.r", "max_stars_repo_name": "xiongchiamiov/computing-for-data-analysis", "max_stars_repo_head_hexsha": "6e938a7c64b3780819328c6713e2f2d501f813f3", "max_stars_repo_licenses": ["WTFPL"], "ma... |
\documentclass[17pt, a4paper]{article}
\usepackage[utf8]{inputenc}
\usepackage{geometry, enumitem}
\geometry{a4paper, margin=1in}
\begin{document}
\begin{center}
{\Large Week 8 - Tutorial}\\
\vspace{5mm}
{\large Lim Jun Qing}\\
\vspace{3mm}
{\large 30029937}\\
\vspace{3mm}
\end{center}
\section{Revi... | {"hexsha": "cde24bd931915161513f61ea9dbb0d46048a5db4", "size": 4512, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "tutorial_labs/week-8/review.tex", "max_stars_repo_name": "itsjunqing/fit2100-operating-systems", "max_stars_repo_head_hexsha": "019c80ab37d0e240f8c701e003cc01289b758f62", "max_stars_repo_licenses": ... |
from Bio import pairwise2
from Bio.PDB import NeighborSearch
from Bio.PDB.Structure import Structure
from Bio.SubsMat.MatrixInfo import blosum62
from classes import BoundingBox, PhysicalResidue, PhysicalAtom
from chainDesc import ChainDesc
import numpy
from math import sqrt
from database_parser import database
def ge... | {"hexsha": "3b88cd92180b1ca185b1c5134eb0ffc13cb9c317", "size": 8250, "ext": "py", "lang": "Python", "max_stars_repo_path": "pdb_parser.py", "max_stars_repo_name": "zedrian/smat", "max_stars_repo_head_hexsha": "423d98999cdb70104169944047e84c9cec315514", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 2, "max_star... |
"""Quantum Generator for performance testing"""
import random
from typing import Any, Dict, List, Optional, Union, cast
import numpy as np
import qiskit
from qiskit import QuantumRegister
from qiskit.circuit import QuantumCircuit
from qiskit.circuit.library import TwoLocal
from qiskit.providers.aer import AerSimulator... | {"hexsha": "bed767cfbc6413b58822fc668158395603807ab2", "size": 9250, "ext": "py", "lang": "Python", "max_stars_repo_path": "quantumGAN/performance_testing/performance_quantum_generator.py", "max_stars_repo_name": "tomiock/qGAN", "max_stars_repo_head_hexsha": "fb98a2b5286eb479665ade353efa40bd6e55dc36", "max_stars_repo_l... |
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
m = 1e-3
i_load = np.logspace(-5,-3)
i_load = np.linspace(1e-5,1e-3,200)
i_s = 1e-12
i_ph = 1e-3
V_T = 1.38e-23*300/1.6e-19
V_D = V_T*np.log((i_ph - i_load)/(i_s) + 1)
P_load = V_D*i_load
plt.subplot(2,1,1)
plt.plot(i_load/m,V_D)
plt.yl... | {"hexsha": "38c1ff3e1dc0d0c354c6662c41dde89e3d2957a2", "size": 510, "ext": "py", "lang": "Python", "max_stars_repo_path": "py/pv.py", "max_stars_repo_name": "wulffern/aic2022", "max_stars_repo_head_hexsha": "65773f672c5fd3936c035d073edf0da6c37ea98f", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max_sta... |
+SW_IMAGE=${BUILD_DIR}/esw/I-FENCE.I-01.elf
+REF_FILE=${FWRISC}/ve/fwrisc/tests/riscv-compliance/riscv-test-suite/rv32i/references/I-FENCE.I-01.reference_output
+gtest-filter=riscv_compliance_tests.runtest
+hpi.entry=fwrisc_tests.riscv_compliance_main
| {"hexsha": "f821710ae35b75b2dd02d64db639cb9821ab7543", "size": 253, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "ve/fwrisc_rv32e/sim/tests/fwrisc_riscv_compliance_rv32i_I-FENCE.f", "max_stars_repo_name": "Kamran-10xe/fwrisc", "max_stars_repo_head_hexsha": "5c742c60ba620944ba19741c02782fb6b45d514e", "max_stars... |
# Written by Jonathan Saewitz, released June 7th, 2016
# Released under the MIT License (https://opensource.org/licenses/MIT)
import requests, matplotlib.pyplot as plt, numpy, time, plotly.plotly as plotly, plotly.graph_objs as go
from datetime import datetime
from collections import Counter
from time import mktime
fr... | {"hexsha": "49082d1c36e8973863baf4375f3ef7c76f2045a7", "size": 11405, "ext": "py", "lang": "Python", "max_stars_repo_path": "aces.py", "max_stars_repo_name": "Statistica/Aces", "max_stars_repo_head_hexsha": "3bc8f56170aff78c73b2f1294005d0d8a563075c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max_sta... |
#include <boost/test/unit_test.hpp>
#include "polynome.h"
BOOST_AUTO_TEST_SUITE(test_polynome)
BOOST_AUTO_TEST_CASE(initialization_1) {
Polynome<long long> p(10);
BOOST_CHECK_EQUAL(p.taille(), 1);
BOOST_CHECK_EQUAL(p.valeur(42), 10);
}
BOOST_AUTO_TEST_CASE(initialization_2) {
... | {"hexsha": "b87b5e60e212885d9027b9205b61395848791260", "size": 2782, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "tests/polynome.cpp", "max_stars_repo_name": "ZongoForSpeed/ProjectEuler", "max_stars_repo_head_hexsha": "2e2d45f984d48a1da8275886c976f909a0de94ce", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
import numba as nb
import numpy as np
MIN_FLOAT64 = np.finfo(np.float64).min
@nb.njit(cache=False)
def _make_dtw_matrix(
score_matrix: np.ndarray,
gap_open_penalty: float = 0.0,
gap_extend_penalty: float = 0.0,
):
"""
Make cost matrix using dynamic time warping
Parameters
----------
... | {"hexsha": "0a1bdc8fbfd7e4438643b77c0d7e7f07b27ff270", "size": 4969, "ext": "py", "lang": "Python", "max_stars_repo_path": "caretta/dynamic_time_warping.py", "max_stars_repo_name": "TurtleTools/caretta", "max_stars_repo_head_hexsha": "cc7d87bd0ac24eccabaa957f755d13fe0a89d035", "max_stars_repo_licenses": ["BSD-3-Clause"... |
import torch
import numpy
from pathlib import Path
from . import model_output_manager as mom
import traceback
import warnings
import sys
from typing import *
def warn_with_traceback(message, category, filename, lineno, file=None, line=None):
log = file if hasattr(file, 'write') else sys.stderr
traceback.prin... | {"hexsha": "6dd3938b273ce5cb94506de67d3d1b1c71d7b017", "size": 15298, "ext": "py", "lang": "Python", "max_stars_repo_path": "model_loader_utils.py", "max_stars_repo_name": "msf235/network_analysis", "max_stars_repo_head_hexsha": "650498a7ac882bc8c7a9dcad05c3576f38129ade", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
import numpy as np
class Box2d(object):
def __init__(self, cx, cy, w, h, theta):
"""
w : along x axis
h : along y axis
theta : the angle between w and x
"""
self.cx = cx
self.cy = cy
self.w = w
self.h = h
self.theta = theta
self... | {"hexsha": "84a54dfdf362ce72af599923fa1e69f9cb6e2b14", "size": 3362, "ext": "py", "lang": "Python", "max_stars_repo_path": "pylib/src/util/math/box2d.py", "max_stars_repo_name": "HaiDang9719/pixel_link_VMNDOC", "max_stars_repo_head_hexsha": "5f05346b05d583bff4676f45501c2e8ac12d4c53", "max_stars_repo_licenses": ["MIT"],... |
from pyomo.environ import *
def create_variables(M, p_min_arr, p_max_arr, p_evs_min_arr, p_evs_max_arr, v_min_arr,
v_max_arr, i_min_arr, i_max_arr, soc_min_arr, soc_max_arr,):
M.V_nodes_now = Var(M.nodes, )
# bounds=(v_min_arr[0, M.t_current_ind], v_max_arr[0, M.t_current_ind]))
M.P_... | {"hexsha": "bf9b775cd5d757dea61c23bf830ebe131e61d36b", "size": 3649, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/planners/exact/__create_variables.py", "max_stars_repo_name": "griprox/EVCP_partially_observable_locations", "max_stars_repo_head_hexsha": "558e9c4c18ad2228dd2f904287bf9aea6210a601", "max_star... |
/*
* producer_tests.cpp
*
* Created on: 21 Jun 2011
* Author: Ben Gray (@benjamg)
*/
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE kafkaconnect
#include <boost/test/unit_test.hpp>
#include <boost/thread.hpp>
#include "../producer.hpp"
void handle_error(boost::system::error_code const& error, int ... | {"hexsha": "2798042491e4500949d85683a50ec9ac7331bc27", "size": 2411, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/tests/producer_error_tests.cpp", "max_stars_repo_name": "datasift/kafka-cpp", "max_stars_repo_head_hexsha": "a11753c6a1a2af52d3087905108c90845de547ae", "max_stars_repo_licenses": ["Apache-2.0"],... |
[STATEMENT]
lemma iD_flag_is_inv [elim, simp]:
fixes ip rt
assumes "ip\<in>iD(rt)"
shows "the (flag rt ip) = inv"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. the (flag rt ip) = Aodv_Basic.inv
[PROOF STEP]
proof -
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. the (flag rt ip) = Aodv_Basic.inv
[PROOF ... | {"llama_tokens": 596, "file": "AODV_variants_e_all_abcd_E_Aodv_Data", "length": 9} |
# -*- coding: utf-8 -*-
"""
Utility functions for +other SQL modules.
"""
import numpy as np
import pandas as pd
import os
import sqlalchemy
get_pk_stmt = "SELECT ORDINAL_POSITION AS [index], COLUMN_NAME AS name FROM {db}.INFORMATION_SCHEMA.KEY_COLUMN_USAGE WHERE TABLE_NAME = '{table}' AND CONSTRAINT_NAME LIKE 'PK%' ... | {"hexsha": "faae3929d78a837efce6e8ca83667bf8791e0e9d", "size": 6152, "ext": "py", "lang": "Python", "max_stars_repo_path": "pdsql/util.py", "max_stars_repo_name": "mullenkamp/pdsql", "max_stars_repo_head_hexsha": "4a6d31b2ea066a6b28653b7199331c6818222a21", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 3... |
#include <boost/test/unit_test.hpp>
BOOST_AUTO_TEST_SUITE(Algorithms)
BOOST_AUTO_TEST_SUITE(DynamicProgramming)
BOOST_AUTO_TEST_SUITE(Memoization_tests)
//------------------------------------------------------------------------------
//------------------------------------------------------------------------------
BOO... | {"hexsha": "b960ed8c3fc5aef90a9a9dd39960a176b7c2e804", "size": 540, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "Voltron/Source/UnitTests/Algorithms/DynamicProgramming/Memoization_tests.cpp", "max_stars_repo_name": "ernestyalumni/HrdwCCppCUDA", "max_stars_repo_head_hexsha": "17ed937dea06431a4d5ca103f993ea69a691... |
#phasing.py in A05_package
#NOT DONE
import pandas as pd
import numpy as np
df = pd.read_table(input_file, sep="\t") # out_metl.sv_haps.txt
df = df.sort_values('name')
def makeNewColumns():
df["hap1_overlap_bcs_bp_new"] = df["hap1_overlap_bcs_bp"]
df["hap2_overlap_bcs_bp_new"] = df["hap2_overlap_bcs_bp"]... | {"hexsha": "2bedea65439c3eb1e6b88ceb1cc2a4f94f1208a5", "size": 6892, "ext": "py", "lang": "Python", "max_stars_repo_path": "SVassembly/phasing_haplotypes.py", "max_stars_repo_name": "AV321/SVPackage", "max_stars_repo_head_hexsha": "c9c625af7f5047ddb43ae79f8beb2ce9aadf7697", "max_stars_repo_licenses": ["MIT"], "max_star... |
[STATEMENT]
lemma set_permutations_of_list_impl:
"set (permutations_of_list_impl xs) = permutations_of_multiset (mset xs)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. set (permutations_of_list_impl xs) = permutations_of_multiset (mset xs)
[PROOF STEP]
by (induction xs rule: permutations_of_list_impl.induct)
... | {"llama_tokens": 168, "file": null, "length": 1} |
##############################################################################
#
# Author: Frank Bieberly
# Date: 30 April 2019
# Name: record_orbcomm.py
# Description:
# This script will record samples from any overhead satellite (or it will wait
# until a satellite is overhead). It will create 100 2-second recordings... | {"hexsha": "c247d8bf7a1c7481af3946e53351694a4354b249", "size": 4814, "ext": "py", "lang": "Python", "max_stars_repo_path": "record_orbcomm.py", "max_stars_repo_name": "b7500af1/orbcomm_decoder", "max_stars_repo_head_hexsha": "a0f805a7efc3ea7460158967453e9f7a2e2ba598", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
"""
Created on Sun Feb 17 02:03:54 2019
Author: Gerardo A. Rivera Tello
Email: grivera@igp.gob.pe
-----
Copyright (c) 2019 Instituto Geofisico del Peru
-----
"""
from dask.distributed import Client, LocalCluster
from distributed.diagnostics.progressbar import progress
from... | {"hexsha": "1d9c4054b61e2c1ce8075e55f0004a2236b5619f", "size": 5405, "ext": "py", "lang": "Python", "max_stars_repo_path": "Region_data/argo_region_nc.py", "max_stars_repo_name": "DangoMelon/turbo-octo-winner", "max_stars_repo_head_hexsha": "ae455606c5e92cdd5005ced7a9593092a246cd86", "max_stars_repo_licenses": ["MIT"],... |
# Copyright (c) 2020, NVIDIA CORPORATION. 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 ... | {"hexsha": "56d46e295d90146c3ae36502d93fc157512f911b", "size": 6799, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/modify_onnx_model_opset10.py", "max_stars_repo_name": "sujitahirrao/automl-video-ondevice", "max_stars_repo_head_hexsha": "554ffb45908a711f93a8fc67825fbf1927f30b50", "max_stars_repo_licen... |
// Copyright (c) 2015-2018 Daniel Cooke
// Use of this source code is governed by the MIT license that can be found in the LICENSE file.
#ifndef fasta_hpp
#define fasta_hpp
#include <string>
#include <vector>
#include <cstdint>
#include <fstream>
#include <memory>
#include <boost/filesystem/path.hpp>
#include "bioi... | {"hexsha": "4f9695c552aa26c8dfa164e67cd65a86c470dbb8", "size": 2327, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/io/reference/fasta.hpp", "max_stars_repo_name": "gmagoon/octopus", "max_stars_repo_head_hexsha": "493643d8503239aead9c7e8a7f8bc19fb97b37d5", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
function p = preprocess_bilinear_bounds(p)
if ~isempty(p.integer_variables)
for i = 1:size(p.bilinears,1)
if ismember(p.bilinears(i,2),p.integer_variables)
if ismember(p.bilinears(i,3),p.integer_variables)
p.integer_variables = [p.integer_variables p.bilinears(i,1)];
... | {"author": "zarathustr", "repo": "LibQPEP", "sha": "99e5c23e746ace0bac4a86742c31db6fcf7297ba", "save_path": "github-repos/MATLAB/zarathustr-LibQPEP", "path": "github-repos/MATLAB/zarathustr-LibQPEP/LibQPEP-99e5c23e746ace0bac4a86742c31db6fcf7297ba/MATLAB/YALMIP/modules/global/preprocess_bilinear_bounds.m"} |
\documentclass[]{article}
\usepackage{lmodern}
\usepackage{amssymb,amsmath}
\usepackage{ifxetex,ifluatex}
\usepackage{fixltx2e} % provides \textsubscript
\ifnum 0\ifxetex 1\fi\ifluatex 1\fi=0 % if pdftex
\usepackage[T1]{fontenc}
\usepackage[utf8]{inputenc}
\else % if luatex or xelatex
\ifxetex
\usepackage{mat... | {"hexsha": "792f576cd09be61f785edad69fe8e63d93e791e2", "size": 4360, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "intro_to_data_modeling/week2/hw_4_1.tex", "max_stars_repo_name": "bwilson668/gt", "max_stars_repo_head_hexsha": "d474598425d70f774a6d509761640ebc4516a1f5", "max_stars_repo_licenses": ["MIT"], "max_s... |
import os
import sys
from PIL import Image
import torch
import torchvision
from torchvision.transforms import *
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data import Dataset, DataLoader
import numpy as np
import math
from collections import OrderedDict
import torch.nn.functional as F
im... | {"hexsha": "4755fd4d48b31ad60d06b86d214f1858612b5b64", "size": 1659, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/old_models/avmodel.py", "max_stars_repo_name": "GeWu-Lab/OGM-GE_CVPR2022", "max_stars_repo_head_hexsha": "08b3f2498dd3e89f57fe9a12b5bf0c162eba1fbf", "max_stars_repo_licenses": ["MIT"], "max... |
import data.finsupp
lemma finsupp.on_finset_mem_support {α β : Type*} [decidable_eq α] [decidable_eq β] [has_zero β]
(s : finset α) (f : α → β) (hf : ∀ (a : α), f a ≠ 0 → a ∈ s) :
∀ a : α, a ∈ (finsupp.on_finset s f hf).support ↔ f a ≠ 0 :=
by { intro, rw [finsupp.mem_support_iff, finsupp.on_finset_apply] }
l... | {"author": "skbaek", "repo": "cvx", "sha": "c50c790c9116f9fac8dfe742903a62bdd7292c15", "save_path": "github-repos/lean/skbaek-cvx", "path": "github-repos/lean/skbaek-cvx/cvx-c50c790c9116f9fac8dfe742903a62bdd7292c15/src/missing_mathlib/data/finsupp.lean"} |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | {"hexsha": "ca0d8fef9e16d62d61efad18ad5a4fa39fe9392d", "size": 8135, "ext": "py", "lang": "Python", "max_stars_repo_path": "python/tvm/contrib/ethosu/cascader/graph.py", "max_stars_repo_name": "XiaoSong9905/tvm", "max_stars_repo_head_hexsha": "48940f697e15d5b50fa1f032003e6c700ae1e423", "max_stars_repo_licenses": ["Apac... |
import os
import numpy as np
import tensorflow as tf
from tensorflow.python.client import timeline
from keras.utils import to_categorical
from keras import callbacks, optimizers, layers
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
# Build Model
def build_model(bs):
input... | {"hexsha": "95411d403c89da43ef1e4e9d79a8dc0ec550d024", "size": 2924, "ext": "py", "lang": "Python", "max_stars_repo_path": "keras_timeline.py", "max_stars_repo_name": "YalongLiu/keras-timeline", "max_stars_repo_head_hexsha": "39f73222b8e80ef9df41b40b4cb1446b7aaef3e6", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
# -*- coding: utf-8 -*-
"""
Houseprint unit test based on previously saved houseprint file.
Created on Mon Dec 30 02:37:25 2013
@author: roel
"""
import os, sys
import unittest
import inspect
import numpy as np
from opengrid_dev.library.houseprint import houseprint
class HouseprintTest(unittest.TestCase):
"""
... | {"hexsha": "d7bb37df09a229c316e9d683ef11cb439eb5b581", "size": 12639, "ext": "py", "lang": "Python", "max_stars_repo_path": "opengrid_dev/library/houseprint/tests/test_houseprint_cached.py", "max_stars_repo_name": "opengridcc/opengrid_dev", "max_stars_repo_head_hexsha": "cc6dc9d615197e4901a8d213fe81fc71bcd602c4", "max_... |
Describe Users/ttong88 here.
20100426 17:11:06 nbsp Hey ttong, welcome to the wiki! Thanks for the updates to the campus rec stuff. Do you work for CR? Some more info on the upcoming 5K Run for Recreation 5k would be great! Users/TomGarberson
20100604 17:21:09 nbsp stay safe even when broksies arent around Users/... | {"hexsha": "658cb813d187dcfa16f02c71a89545b09908639a", "size": 334, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/ttong88.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nul... |
function tauc = taucv(alfa,f,n)
%TAUCV Upper percentage point of the tau distribution.
% tauc=taucv(alfa,f,n) computes the critical value of tau distribution
% for the Type I error--significance level (alfa), degree of freedom (f)
% and the number of observations (n). It is used in Pope test for outl... | {"author": "Sable", "repo": "mcbench-benchmarks", "sha": "ba13b2f0296ef49491b95e3f984c7c41fccdb6d8", "save_path": "github-repos/MATLAB/Sable-mcbench-benchmarks", "path": "github-repos/MATLAB/Sable-mcbench-benchmarks/mcbench-benchmarks-ba13b2f0296ef49491b95e3f984c7c41fccdb6d8/3435-taucv/taucv.m"} |
import numpy as np
from copy import deepcopy
try:
# Python 2 module
from itertools import izip_longest as zip_longest
except ImportError:
# Python 3 module
from itertools import zip_longest
def add_conv(layers, max_out_ch, conv_kernel):
out_channel = np.random.randint(3, max_out_ch)
conv_kerne... | {"hexsha": "2ac1fc9eb02fc8bb986cad265a6f571ed8ace3b0", "size": 6435, "ext": "py", "lang": "Python", "max_stars_repo_path": "psoCNN/utils.py", "max_stars_repo_name": "Thejineaswar/Efficient-architecture-search-in-multidimensional-space-using-Swarm-Intelligence-algorithm-for-DR", "max_stars_repo_head_hexsha": "97a1ff8a34... |
"""
Implementation of networks.
MIT License
Copyright (c) 2019 Roland Zimmermann, Laurenz Hemmen
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... | {"hexsha": "330f03d20f75c9f94c3428aacf6a0ed584f482a2", "size": 15093, "ext": "py", "lang": "Python", "max_stars_repo_path": "network.py", "max_stars_repo_name": "FlashTek/spking-bayesian-networks", "max_stars_repo_head_hexsha": "724380167070e994e5f52b4fddf2cc5d0930a177", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
import os
import tempfile
from typing import Any, Dict
import pandas as pd
import numpy as np
from sklearn import datasets, metrics
from sklearn.linear_model import LogisticRegression
from h1st.model.ml_model import MLModel
from h1st.model.ml_modeler import MLModeler
from h1st.model.oracle.student import AdaBoostModel,... | {"hexsha": "935912e3ae6812dddbc52d69d06dfaf467f5bfe1", "size": 15032, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/model/test_ts_oracle.py", "max_stars_repo_name": "TheVinhLuong102/H1st", "max_stars_repo_head_hexsha": "0c6f56d3a078817c36b208ae4f4c519cb35d5c18", "max_stars_repo_licenses": ["Apache-2.0"],... |
import numpy as np
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import glob, os.path, os, pickle
import argparse
#global params
fig_dims = (12,8)
axis_label = 32
legend_label = 30
axis_scale = 2
default_script="dc2"
def load_data_pkl(pathname):
... | {"hexsha": "152ebd0c7ee4f235979fa91f5779919c3f229a98", "size": 4089, "ext": "py", "lang": "Python", "max_stars_repo_path": "analysis/motivation_plot.py", "max_stars_repo_name": "joshuaminwookang/mlrl_synthesis", "max_stars_repo_head_hexsha": "2959cab327dd7ffa8094b084e219ad9701557757", "max_stars_repo_licenses": ["MIT"]... |
/*
* This is part of the fl library, a C++ Bayesian filtering library
* (https://github.com/filtering-library)
*
* Copyright (c) 2015 Max Planck Society,
* Autonomous Motion Department,
* Institute for Intelligent Systems
*
* This Source Code Form is subject to the terms of the MIT License (MIT).
... | {"hexsha": "d5a6ea24848571ae9964922474f0c146f2c821bc", "size": 3165, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "test/gaussian_filter/robust_gaussian_filter_test.cpp", "max_stars_repo_name": "aeolusbot-tommyliu/fl", "max_stars_repo_head_hexsha": "a50d0c9620a8f86e0cd14a5e22ee0f022d00bd02", "max_stars_repo_licen... |
[STATEMENT]
lemma dim_vec_of_list[simp]: "dim_vec (vec_of_list x) = length x"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. dim_vec (vec_of_list x) = length x
[PROOF STEP]
by (transfer, auto) | {"llama_tokens": 86, "file": "Berlekamp_Zassenhaus_Berlekamp_Type_Based", "length": 1} |
#################################################################################
# The Institute for the Design of Advanced Energy Systems Integrated Platform
# Framework (IDAES IP) was produced under the DOE Institute for the
# Design of Advanced Energy Systems (IDAES), and is copyright (c) 2018-2021
# by the softwar... | {"hexsha": "9139442c0b748c22785a682512c30ed5d4f5ebdc", "size": 7295, "ext": "py", "lang": "Python", "max_stars_repo_path": "idaes/surrogate/ripe/mechs.py", "max_stars_repo_name": "eslickj/idaes-pse", "max_stars_repo_head_hexsha": "328ed07ffb0b4d98c03e972675ea32c41dd2531a", "max_stars_repo_licenses": ["RSA-MD"], "max_st... |
\section{Statement}
The Rubin Observatory Construction Project has no remit to provide services or systems capable of supporting access by non-data-rights holders to data products after the two year proprietary period has elapsed.
That said, we do not regard doing so as an insurmountable task.
In particular:
\begin{... | {"hexsha": "b5254d316c089bbffdca583a3f3f7140e6e22890", "size": 1351, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "body.tex", "max_stars_repo_name": "lsst-dm/dmtn-144", "max_stars_repo_head_hexsha": "c914e9c14d314ea1462cfff6c2d220334f497387", "max_stars_repo_licenses": ["CC-BY-4.0"], "max_stars_count": null, "ma... |
[STATEMENT]
lemma ad_agr_list_eq: "set ys \<subseteq> AD \<Longrightarrow> ad_agr_list AD (map Inl xs) (map Inl ys) \<Longrightarrow> xs = ys"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>set ys \<subseteq> AD; ad_agr_list AD (map Inl xs) (map Inl ys)\<rbrakk> \<Longrightarrow> xs = ys
[PROOF STEP]
by (fa... | {"llama_tokens": 171, "file": "Eval_FO_Ailamazyan", "length": 1} |
#include <networkit/graph/Graph.hpp>
#include <networkit/io/EdgeListReader.hpp>
#include <networkit/centrality/DegreeCentrality.hpp>
#include <networkit/graph/BFS.hpp>
#include <boost/program_options.hpp>
#include <networkit/centrality/CoreDecomposition.hpp>
#include "../include/decompositions/hDegreeCentrality.hpp"
#i... | {"hexsha": "7144b7362ea93204475bb388202786f07e1259d4", "size": 6164, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/main.cpp", "max_stars_repo_name": "acalio/Decompositions", "max_stars_repo_head_hexsha": "bdb8ca8c5207e28f91634bae49bfe46108ec43e8", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, ... |
# coding=utf-8
# Copyright 2019 The Tensor2Tensor Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | {"hexsha": "fa628f7adbca49209a17bfc56df6f5eba24330d0", "size": 10234, "ext": "py", "lang": "Python", "max_stars_repo_path": "t2t_bert/utils/tensor2tensor/envs/gym_env_problem.py", "max_stars_repo_name": "yyht/bert", "max_stars_repo_head_hexsha": "480c909e0835a455606e829310ff949c9dd23549", "max_stars_repo_licenses": ["A... |
import os
import re
import numpy as np
from scipy.io import loadmat
from sklearn.preprocessing import StandardScaler
def get_outliers(x, thresh=10):
x_sorted = -np.sort(-x)[:10]
arg_sorted = np.argsort(-x)[:10]
if len(x_sorted.shape) == 1:
x_sorted = x_sorted[:, np.newaxis]
median = np.median(... | {"hexsha": "8c8c414ee99ac1146cb61fd705bcde4b2ab5bd84", "size": 4942, "ext": "py", "lang": "Python", "max_stars_repo_path": "seizure/cnn_trainer/loader.py", "max_stars_repo_name": "IraKorshunova/kaggle-seizure-detection", "max_stars_repo_head_hexsha": "c9b72dfcf1dfe4c80a099781210c98b9f72745c0", "max_stars_repo_licenses"... |
import apricot
import math
import numpy as np
import torch
from scipy.sparse import csr_matrix
from torch.utils.data import DataLoader
from torch.utils.data import Dataset
from torch.utils.data import Subset
from torch.utils.data.sampler import SubsetRandomSampler
from .calculate_class_budgets import calculate_class_... | {"hexsha": "81ee59b63d37ff57bce30e5d0a723a58eb69ebcd", "size": 40888, "ext": "py", "lang": "Python", "max_stars_repo_path": "distil/utils/supervised_strategy_wrappers.py", "max_stars_repo_name": "SatyadevNtv/distil", "max_stars_repo_head_hexsha": "c8c3489920a24537a849eb8446efc9c2e19ab193", "max_stars_repo_licenses": ["... |
using Roots
function detach_indexer(repo::Repository, id::AbstractString)::Tuple{Indexer,Repository}
# Get requested indexer
i = findfirst(x -> x.id == id, repo.indexers)
if isnothing(i)
throw(UnknownIndexerError())
end
indexer = repo.indexers[i]
# Remove indexer from repository
in... | {"hexsha": "c91737eeba9bf88d32457a98cf757cb571b0f873", "size": 1650, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/service.jl", "max_stars_repo_name": "graphprotocol/AllocationOpt.jl", "max_stars_repo_head_hexsha": "2ba0ee88e4ed8897dcb698612e03a9814819217a", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
\chapter{Algorithms for Parametric Runs}
\label{sec:algParRun}
The here described algorithms for
parametric runs can be used to determine how sensitive a function is
with respect to a change in the independent variables.
They can also be used to do a parametric
sweep of a function over a set of parameters.
The algor... | {"hexsha": "fd3115be816656881a5a334bc5c27331b508a564", "size": 6369, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "src/manual/algParametric.tex", "max_stars_repo_name": "bergsee/GenOpt", "max_stars_repo_head_hexsha": "3925277af881cea6e12e3d1bf0285bd657bbcced", "max_stars_repo_licenses": ["BSD-3-Clause-LBNL"], "m... |
[STATEMENT]
lemma inverse_functors_\<Phi>_\<Psi>:
shows "inverse_functors S S' \<Psi> \<Phi>"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. inverse_functors (\<cdot>) (\<cdot>\<acute>) \<Psi> \<Phi>
[PROOF STEP]
proof -
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. inverse_functors (\<cdot>) (\<cdot>\<acute... | {"llama_tokens": 1130, "file": "Category3_SetCategory", "length": 15} |
import numpy as np
from memory import Memory
from function_approx import FunctionApprox
from EpsilonPolicy import Epsilon_policy
class Agent:
"""
The agent class, the central class containing the logic and learning capabilities of the
simulation. Contains the double-Q learning algorithm and the two networ... | {"hexsha": "a415597f4abf92979aa2d1ad54921ddf8051c923", "size": 3945, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/agent.py", "max_stars_repo_name": "AI-Gio/LunarLander", "max_stars_repo_head_hexsha": "867425223a186bc0dd3378e3bd2888cd525d2834", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "... |
using Makie, GeoMakie
using GeoMakie.GeoJSON
# Acquire data
states = download("https://github.com/openpolis/geojson-italy/raw/master/geojson/limits_IT_provinces.geojson")
states_bytes = read(states)
geo = GeoJSONTables.read(states_bytes)
states_str = read(states, String)
using JSON
geo = GeoJSON.dict2geo(JSON.parse(... | {"hexsha": "5ceb9b0095a5e8896efbae728ade29986b7ae994", "size": 752, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "examples/italy.jl", "max_stars_repo_name": "Datseris/GeoMakie.jl", "max_stars_repo_head_hexsha": "1aaca3db84c68b96e8d5a7e73a86a6ab85b3f902", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1,... |
"""Camera QC
This module runs a list of quality control metrics on the camera and extracted video data.
Example - Run right camera QC, downloading all but video file
qc = CameraQC(eid, 'right', download_data=True, stream=True)
qc.run()
Example - Run left camera QC with session path, update QC field in Alyx
... | {"hexsha": "67e06ff0b59a8236423528f677fc11f4c540948b", "size": 42159, "ext": "py", "lang": "Python", "max_stars_repo_path": "ibllib/qc/camera.py", "max_stars_repo_name": "hanhou/ibllib", "max_stars_repo_head_hexsha": "bc29ecb44212d8dd899be987cf407b28e9c0d3be", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
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