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Location: AENC/switchchain/cpp/switchchain_initialtris.cpp
8ea4e5028ea8
4.1 KiB
text/x-c++src
Add more canonical property datasets
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 | #include "exports.hpp"
#include "graph.hpp"
#include "graph_gcm.hpp"
#include "graph_powerlaw.hpp"
#include "switchchain.hpp"
#include <algorithm>
#include <fstream>
#include <iostream>
#include <numeric>
#include <random>
#include <vector>
int main() {
// 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[] = {2.1f, 2.2f, 2.3f, 2.4f, 2.5f, 2.6f, 2.7f, 2.8f, 2.9f};
Graph g;
std::ofstream outfile("graphdata_initialtris.m");
outfile << '{';
bool outputComma = false;
for (int numVertices = 200; numVertices <= 2000; numVertices += 400) {
for (float tau : tauValues) {
// For a single n,tau take samples over several instances of
// the degree distribution.
for (int degreeSample = 0; degreeSample < 200; ++degreeSample) {
DegreeSequence ds;
generatePowerlawGraph(numVertices, tau, g, ds, rng);
std::cout << "Running n = " << numVertices << ", tau = " << tau
<< "." << std::flush;
//
// Test the GCM1 and GCM2 success rate
//
long long gcmTris1 = 0;
long long gcmTris2 = 0;
int successrate1 = 0;
int successrate2 = 0;
for (int i = 0; i < 100; ++i) {
Graph gtemp;
// Take new highest degree every time
if (greedyConfigurationModel(ds, gtemp, rng, false)) {
++successrate1;
gcmTris1 += gtemp.countTriangles();
}
// Finish all pairings of highest degree first
if (greedyConfigurationModel(ds, gtemp, rng, true)) {
++successrate2;
gcmTris2 += gtemp.countTriangles();
}
}
SwitchChain chain;
if (!chain.initialize(g)) {
std::cerr << "Could not initialize Markov chain.\n";
return 1;
}
int mixingTime = (32.0f - 20.0f * (tau - 2.0f)) * numVertices;
constexpr int measurements = 20;
constexpr int measureSkip = 200;
int movesDone = 0;
long long trianglesTotal = 0;
std::cout << " .. \t" << std::flush;
for (int i = 0; i < mixingTime; ++i) {
if (chain.doMove())
++movesDone;
}
for (int i = 0; i < measurements; ++i) {
for (int j = 0; j < measureSkip; ++j)
if (chain.doMove())
++movesDone;
trianglesTotal += chain.g.countTriangles();
}
std::cout << movesDone << '/' << mixingTime + measurements * measureSkip
<< " moves succeeded ("
<< 100.0f * float(movesDone) /
float(mixingTime + measurements * measureSkip)
<< "%).";
//std::cout << std::endl;
if (outputComma)
outfile << ',' << '\n';
outputComma = true;
float avgTriangles =
float(trianglesTotal) / float(measurements);
outfile << '{';
outfile << '{' << numVertices << ',' << tau << '}';
outfile << ',' << avgTriangles;
outfile << ',' << '{' << gcmTris1 << ',' << successrate1 << '}';
outfile << ',' << '{' << gcmTris2 << ',' << successrate2 << '}';
outfile << '}' << std::flush;
std::cout << std::endl;
}
}
}
outfile << '}';
return 0;
}
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