#include "switchchain.hpp"
#include "exports.hpp"
#include "graph.hpp"
#include "graph_gcm.hpp"
#include "graph_spectrum.hpp"
#include "graph_powerlaw.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[] = {2.1f, 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_spectrum.m");

    if (!outfile.is_open()) {
        std::cout << "ERROR: Could not open output file.\n";
        return 1;
    }

    outfile << '{';
    bool outputComma = false;

    for (int numVertices = 500; numVertices <= 500; 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 < 5; ++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;

                //int mixingTime = (32.0f - 26.0f*(tau - 2.0f)) * numVertices; //40000;
                //constexpr int measurements = 50;
                //constexpr int measureSkip =
                //    200; // Take a sample every ... steps
                int mixingTime = 0;
                constexpr int measurements = 50000;
                constexpr int measureSkip = 1;


                int movesTotal = 0;
                int movesSuccess = 0;

                int triangles[measurements];

                for (int i = 0; i < mixingTime; ++i) {
                    ++movesTotal;
                    if (chain.doMove()) {
                        ++movesSuccess;
                    }
                }

                for (int i = 0; i < measurements; ++i) {
                    for (int j = 0; j < measureSkip; ++j) {
                        ++movesTotal;
                        if (chain.doMove()) {
                            ++movesSuccess;
                        }
                    }
                    triangles[i] = chain.g.countTriangles();
                }

                std::cout << '('
                          << 100.0f * float(movesSuccess) / float(movesTotal)
                          << "% successrate). " << std::flush;
                // std::cout << std::endl;

                GraphSpectrum gs(g);

                if (outputComma)
                    outfile << ',' << '\n';
                outputComma = true;

                //std::sort(ds.begin(), ds.end());
                outfile << '{' << '{' << numVertices << ',' << tau << '}';
                outfile << ',' << triangles;
                outfile << ',' << g.edgeCount();
                outfile << ',' << gs.computeAdjacencySpectrum();
                outfile << ',' << gs.computeLaplacianSpectrum();
                outfile << '}' << std::flush;

                std::cout << std::endl;
            }
        }
    }
    outfile << '}';
    return 0;
}