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Location: AENC/switchchain/cpp/switchchain_initialtris.cpp
56cc6fa35193
5.1 KiB
text/x-c++src
Add initial spectrum computation file
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 | #include "exports.hpp"
#include "graph.hpp"
#include "graph_gcm.hpp"
#include "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) {
DegreeSequence ds(numVertices);
powerlaw_distribution degDist(tau, 1, numVertices);
//std::poisson_distribution<> degDist(12);
// For a single n,tau take samples over several instances of
// the degree distribution.
// 500 samples seems to give reasonable results
for (int degreeSample = 0; degreeSample < 200; ++degreeSample) {
// Generate a graph
// might require multiple tries
for (int i = 1; ; ++i) {
std::generate(ds.begin(), ds.end(),
[°Dist, &rng] { return degDist(rng); });
// First make the sum even
unsigned int sum = std::accumulate(ds.begin(), ds.end(), 0);
if (sum % 2) {
continue;
// Can we do this: ??
ds.back()++;
}
if (g.createFromDegreeSequence(ds))
break;
// When 10 tries have not worked, output a warning
if (i % 10 == 0) {
std::cerr << "Warning: could not create graph from "
"degree sequence. Trying again...\n";
}
}
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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