#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;
}