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Location: AENC/switchchain/cpp/switchchain_successrates.cpp
2e3f21cc591d
4.1 KiB
text/x-c++src
Add dataset of fixed CCM constructionrates
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 | #include "exports.hpp"
#include "graph.hpp"
#include "graph_powerlaw.hpp"
#include "switchchain.hpp"
#include <algorithm>
#include <array>
#include <fstream>
#include <iostream>
#include <numeric>
#include <random>
#include <vector>
int main(int argc, char* argv[]) {
// Generate a random degree sequence
std::mt19937 rng(std::random_device{}());
// Goal:
// Degrees follow a power-law distribution with some parameter tau
// Expect: #tri = const * n^{ something }
// The goal is to find the 'something' by finding the number of triangles
// for different values of n and tau
//float tauValues[] = {2.5f};
float tauValues[] = {2.1f, 2.2f, 2.3f, 2.4f, 2.5f, 2.6f, 2.7f, 2.8f, 2.9f};
Graph g;
std::ofstream outfile;
if (argc >= 2)
outfile.open(argv[1]);
else
outfile.open("graphdata_successrates.m");
if (!outfile.is_open()) {
std::cout << "ERROR: Could not open output file.\n";
return 1;
}
outfile << '{';
bool outputComma = false;
for (int numVertices = 1000; numVertices <= 1000; numVertices += 1000) {
for (float tau : tauValues) {
// For a single n,tau take samples over several instances of
// the degree distribution.
for (int degreeSample = 0; degreeSample < 2000; ++degreeSample) {
DegreeSequence ds;
generatePowerlawGraph(numVertices, tau, g, ds, rng);
SwitchChain chain;
if (!chain.initialize(g)) {
std::cerr << "Could not initialize Markov chain.\n";
return 1;
}
std::cout << "Running n = " << numVertices << ", tau = " << tau
<< ". \t" << std::flush;
// Non time evol
int mixingTime = 32*(32.0f - 15.0f*(tau - 2.0f)) * numVertices; //40000;
constexpr int measurements = 50;
constexpr int measureSkip =
200; // Take a sample every ... steps
// Time Evol
//int mixingTime = 0;
//constexpr int measurements = 500;
//constexpr int measureSkip = 100;
int movesTotal = 0;
int movesSuccess = 0;
int triangles[measurements];
for (int i = 0; i < mixingTime; ++i) {
++movesTotal;
if (chain.doMove()) {
++movesSuccess;
}
}
// Time Evol
//std::vector<int> successRates;
//successRates.reserve(measurements);
//int successrate = 0;
for (int i = 0; i < measurements; ++i) {
for (int j = 0; j < measureSkip; ++j) {
++movesTotal;
if (chain.doMove()) {
++movesSuccess;
//++successrate;
}
}
triangles[i] = chain.g.countTriangles();
//successRates.push_back(successrate);
//successrate = 0;
}
std::cout << '('
<< 100.0f * float(movesSuccess) / float(movesTotal)
<< "% successrate). " << std::flush;
// std::cout << std::endl;
if (outputComma)
outfile << ',' << '\n';
outputComma = true;
long long trianglesTotal = 0;
for (int i = 0; i < measurements; ++i)
trianglesTotal += triangles[i];
float avgTriangles =
float(trianglesTotal) / float(measurements);
outfile << '{' << '{' << numVertices << ',' << tau << '}';
outfile << ',' << avgTriangles;
//outfile << ',' << successRates;
outfile << ',' << float(movesSuccess) / float(movesTotal);
outfile << '}' << std::flush;
std::cout << std::endl;
}
}
}
outfile << '}';
return 0;
}
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