#include <iostream>
#include <vector>
#include <algorithm>
#include "omp.h"

double RandomDouble(double min = -1, double max = 1)
{
    double f = (double)std::rand() / RAND_MAX;
    return min + f * (max - min);
}

std::vector<double> RandomDoubleVector(size_t size, double min = -1, double max = 1)
{
    std::vector<double> vector = std::vector<double>(size);
    for (int i = 0; i < size; ++i) {
        vector[i] = RandomDouble(min, max);
    }

    return vector;
}

#define MATRIX_SIZE 100

class Matrix {
public:
    Matrix(size_t size = MATRIX_SIZE) : _size(size), _data(size * size) {}
    Matrix(size_t size, std::vector<double> data) : _size(size), _data(size * size) {
        _data = data;
    }

    Matrix(const Matrix& other)
    {
        _size = other._data.size();
        _data.resize(_size * _size);
        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                this->operator()(i, j) = other(i, j);
    }
    Matrix& operator=(const Matrix& other) {
        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                this->operator()(i, j) = other(i, j);

        return *this;
    }

    double& operator()(size_t i, size_t j) {
        return _data[i * _size + j];
    }
    double operator()(size_t i, size_t j) const {
        return _data[i * _size + j];
    }
    static Matrix I(size_t size) {
        Matrix matrix = Matrix(size);
        for (size_t i = 0; i < size; ++i)
            matrix(i, i) = 1;

        return matrix;
    }
    static Matrix Zero(size_t size) {
        Matrix matrix = Matrix(size);
        return matrix;
    }

    static Matrix RandomMatrix(size_t size, double min = -1, double max = 1) {
        Matrix matrix = Matrix(size);
        for (size_t i = 0; i < size; ++i)
            for (size_t j = 0; j < size; ++j)
                matrix(i, j) = RandomDouble(min, max);

        return matrix;
    }

    Matrix operator+(const Matrix& b) {
        Matrix sum = Matrix(_size, _data);
        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                sum(i, j) += b(i, j);

        return sum;
    }

    Matrix operator+(const double & d) {
        Matrix sum = Matrix(_size, _data);
        for (size_t i = 0; i < _size; ++i)
            sum(i, i) += d;

        return sum;
    }

    Matrix operator+=(const Matrix& b) {
        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                operator()(i, j) += b(i, j);

        return *this;
    }

    Matrix operator*(const Matrix& b) {
        Matrix product = Matrix(_size);

        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                for (size_t k = 0; k < _size; ++k) {
                    product(i, j) += operator()(i, k) * b(k, j);
                }

        return product;
    }

    Matrix operator*(const double& d) {
        Matrix scalarMult = Matrix(_size, _data);
        for (size_t i = 0; i < _size; ++i)
            for (size_t j = 0; j < _size; ++j)
                scalarMult(i, j) *= d;

        return scalarMult;
    }

    Matrix Pow(size_t n) {
        Matrix result = Matrix(_size);

        for (size_t i = 0; i < _size; i++)
        {
            result(i, i) = 1;
        }

        for (size_t i = 0; i < n; i++) {
            result = result * *this;
        }

        return result;
    }

    void Show() {
        for (size_t i = 0; i < _size; ++i) {
            for (size_t j = 0; j < _size; ++j)
                std::cout << operator()(i, j) << " ";
            std::cout << std::endl;
        }
        std::cout << std::endl;
    }

    const size_t GetSize() {
        return _size;
    }
    double* GetData() {
        return _data.data();
    }

private:
    size_t _size;
    std::vector<double> _data;
};

Matrix ForwardSum(std::vector<double> polinomialCoefs, Matrix& A)
{
    auto result = Matrix(A.GetSize());
    for (size_t n = 0; n < polinomialCoefs.size(); n++) {
        result += A.Pow(n) * polinomialCoefs[n];
    }

    return result;
}

#pragma omp declare reduction( + : Matrix: \
    omp_out = omp_out + omp_in)

int main(int argc, char* argv[]) {
    size_t matrixSize = MATRIX_SIZE;
    Matrix A = Matrix::RandomMatrix(matrixSize);
    std::vector<double> polinomialCoefs = RandomDoubleVector(20, -5, 5);

    std::cout << omp_get_max_threads();

    int threadsCount;

    clock_t begin = clock();

    Matrix result = Matrix::Zero(matrixSize);

#pragma omp parallel for reduction(+ : result)
    for (int currentThread = 0; currentThread < omp_get_num_threads(); currentThread++) {
        threadsCount = omp_get_num_threads();

        std::vector<size_t> indexes(0);

        for (int i = currentThread; i < polinomialCoefs.size(); i += threadsCount) {
            indexes.push_back(i);
        }

        Matrix APowered = A.Pow(threadsCount);
        Matrix I = Matrix::I(matrixSize);
        Matrix part = Matrix::I(matrixSize) * polinomialCoefs[indexes[indexes.size() - 1]];
        for (int n = indexes.size() - 2; n >= 0; n--) {
            part = part * APowered + I * polinomialCoefs[indexes[n]];
        }

        part = A.Pow(currentThread) * part;

        result += part;
    }
#pragma omp barrier

    clock_t end = clock();

    if (true) {
        std::cout << "\nDone in " << double(end - begin) / CLOCKS_PER_SEC << " sec." << std::endl;
        //result.Show();
        //ForwardSum(polinomialCoefs, A).Show();
    }


    return 0;
}