all: switchchain switchchain_exponent switchchain_initialtris switchchain_dsp

switchchain_dsp:

#include "exports.hpp"

#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() {

        int e1index, e2index;

        int timeout = 0;

        // Keep regenerating while conflicting edges

        do {

            e1index = edgeDistribution(mt);

            e2index = edgeDistribution(mt);

            if (++timeout % 100 == 0) {

                std::cerr << "Warning: sampled " << timeout

                          << " random edges but they keep conflicting.\n";

            }

        } while (edgeConflicts(g.getEdge(e1index), g.getEdge(e2index)));

        // 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;

};

double getProperty(const DegreeSequence& ds) {

    std::vector<std::vector<double>> vals(ds.size());

    for (auto& v : vals) {

        v.resize(ds.size(), 0);

    }

    auto D = 0u;

    for (auto d : ds)

        D += d;

    double factor = 1.0 / double(D);

    for (auto i = 0u; i < ds.size(); ++i) {

        for (auto j = i + 1; j < ds.size(); ++j) {

            vals[i][j] = 1.0 - std::exp(-ds[i] * ds[j] * factor);

        }

    }

    double result = 0.0;

    for (auto i = 0u; i < ds.size(); ++i) {

        for (auto j = i + 1; j < ds.size(); ++j) {

            for (auto k = j + 1; k < ds.size(); ++k) {

                result += vals[i][j] * vals[j][k] * vals[i][k];

            }

        }

    }

    return result;

}

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, 2.5f, 2.9f};

    Graph g;

    Graph g1;

    Graph g2;

    std::ofstream outfile("graphdata_dsp.m");

    outfile << '{';

    bool outputComma = false;

    for (int numVertices = 1000; numVertices <= 1000; numVertices += 1000) {

        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 < 2000; ++degreeSample) {

                // Generate a graph

                // might require multiple tries

                for (int i = 1; ; ++i) {

                    std::generate(ds.begin(), ds.end(),

                                  [&degDist, &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";

                    }

                }

                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;

                int mixingTime = 32*(32.0f - 10.0f*(tau - 2.0f)) * numVertices; //40000;

                constexpr int measurements = 50;

                constexpr int measureSkip =

                    200; // Take a sample every ... steps

                int movesDone = 0;

                long long trianglesTotal = 0;

                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::flush;

                //std::cout << std::endl;

                if (outputComma)

                    outfile << ',' << '\n';

                outputComma = true;

                float avgTriangles =

                    float(trianglesTotal) / float(measurements);

                outfile << '{' << '{' << numVertices << ',' << tau << '}';

                outfile << ',' << avgTriangles;

                outfile << ',' << getProperty(ds) << '}' << std::flush;

                std::cout << std::endl;

            }

        }

    }

    outfile << '}';

    return 0;

}