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Location: AENC/switchchain/cpp/switchchain.cpp - annotation
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#include "graph.hpp"
#include "powerlaw.hpp"
#include <algorithm>
#include <fstream>
#include <iostream>
#include <numeric>
#include <random>
#include <vector>
// Its assumed that u,v are distinct.
// Check if all four vertices are distinct
bool edgeConflicts(const Edge& e1, const Edge& e2) {
return (e1.u == e2.u || e1.u == e2.v || e1.v == e2.u || e1.v == e2.v);
}
class SwitchChain {
public:
SwitchChain()
: mt(std::random_device{}()), permutationDistribution(0.5)
// permutationDistribution(0, 2)
{
// random_device uses hardware entropy if available
// std::random_device rd;
// mt.seed(rd());
}
~SwitchChain() {}
bool initialize(const Graph& gstart) {
if (gstart.edgeCount() == 0)
return false;
g = gstart;
edgeDistribution.param(
std::uniform_int_distribution<>::param_type(0, g.edgeCount() - 1));
return true;
}
bool doMove() {
Edge e1, e2;
int e1index, e2index;
int timeout = 0;
// Keep regenerating while conflicting edges
do {
e1index = edgeDistribution(mt);
e2index = edgeDistribution(mt);
e1 = g.getEdge(e1index);
e2 = g.getEdge(e2index);
++timeout;
if (timeout % 100 == 0) {
std::cerr << "Warning: sampled " << timeout
<< " random edges but they keep conflicting.\n";
}
} while (edgeConflicts(e1, e2));
// Consider one of the three possible permutations
// 1) e1.u - e1.v and e2.u - e2.v (original)
// 2) e1.u - e2.u and e1.v - e2.v
// 3) e1.u - e2.v and e1.v - e2.u
bool switchType = permutationDistribution(mt);
return g.exchangeEdges(e1index, e2index, switchType);
}
Graph g;
std::mt19937 mt;
std::uniform_int_distribution<> edgeDistribution;
//std::uniform_int_distribution<> permutationDistribution;
std::bernoulli_distribution permutationDistribution;
};
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};
Graph g;
std::ofstream outfile("graphdata.m");
outfile << '{';
bool outputComma = false;
for (int numVertices = 200; numVertices <= 1000; numVertices += 100) {
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
for (int degreeSample = 0; degreeSample < 500; ++degreeSample) {
// Generate a graph
// might require multiple tries
for (int i = 1; ; ++i) {
std::generate(ds.begin(), ds.end(),
[°Dist, &rng] { return degDist(rng); });
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";
}
}
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;
constexpr int mixingTime = 40000;
constexpr int measureTime = 20000;
constexpr int measureSkip =
200; // Take a sample every ... steps
constexpr int measurements =
(measureTime - 1) / measureSkip + 1;
int movesDone = 0;
int triangles[measurements];
for (int i = 0; i < mixingTime; ++i) {
if (chain.doMove())
++movesDone;
}
for (int i = 0; i < measureTime; ++i) {
if (chain.doMove())
++movesDone;
if (i % measureSkip == 0)
triangles[i / measureSkip] = chain.g.countTriangles();
}
std::cout << movesDone << '/' << mixingTime + measureTime
<< " moves succeeded." << std::endl;
if (outputComma)
outfile << ',';
outputComma = true;
std::sort(ds.begin(), ds.end());
outfile << '{' << '{' << numVertices << ',' << tau << '}';
outfile << ',' << triangles << ',' << ds << '}' << std::flush;
}
}
}
outfile << '}';
return 0;
}
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