/********************************************************
 *  ██████╗  ██████╗████████╗██╗
 * ██╔════╝ ██╔════╝╚══██╔══╝██║
 * ██║  ███╗██║        ██║   ██║
 * ██║   ██║██║        ██║   ██║
 * ╚██████╔╝╚██████╗   ██║   ███████╗
 *  ╚═════╝  ╚═════╝   ╚═╝   ╚══════╝
 * Geophysical Computational Tools & Library (GCTL)
 *
 * Copyright (c) 2023  Yi Zhang (yizhang-geo@zju.edu.cn)
 *
 * GCTL is distributed under a dual licensing scheme. You can redistribute 
 * it and/or modify it under the terms of the GNU Lesser General Public 
 * License as published by the Free Software Foundation, either version 2 
 * of the License, or (at your option) any later version. You should have 
 * received a copy of the GNU Lesser General Public License along with this 
 * program. If not, see <http://www.gnu.org/licenses/>.
 * 
 * If the terms and conditions of the LGPL v.2. would prevent you from using 
 * the GCTL, please consider the option to obtain a commercial license for a 
 * fee. These licenses are offered by the GCTL's original author. As a rule, 
 * licenses are provided "as-is", unlimited in time for a one time fee. Please 
 * send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget 
 * to include some description of your company and the realm of its activities. 
 * Also add information on how to contact you by electronic and paper mail.
 ******************************************************/

#include "../lib/core.h"
#include "../lib/algorithm.h"

using namespace gctl;

int main(int argc, char const *argv[]) try
{
/*
    array<double> x(201);
    x.sequence(-1.0, 0.01);
    kde k(0.02, x);

    array<double> d;
    array<double> a(100000);
    a.random_float(0.2, 0.2, RdNormal, 0);
    k.get_distribution(a, d);

    gaussian_para1d g1(0, 0.2);
    array<double> g(201);
    for (size_t i = 0; i < x.size(); i++)
    {
        g[i] = gaussian_dist1d(x[i], g1);
    }

    array<double> dm(201);
    array<double> am(100000, 0.0);

    for (size_t i = 0; i < am.size(); i++)
    {
        k.get_gradient_at(i, a, dm);

        for (size_t j = 0; j < x.size(); j++)
        {
            am[i] += 2.0*(d[j] - g[j])*dm[j];
        }

        std::cout << a[i] << " " << am[i] << "\n";
    }
    
    for (size_t i = 0; i < x.size(); i++)
    {
        std::cout << x[i] << " " << d[i] - g[i] << "\n";
    }
*/

    array<double> x(201), y(301);
    x.sequence(-1.0, 0.01);
    y.sequence(0.0, 0.01);
    kde2d k(0.1, 0.1, x, y);

    array<double> a(10000), b(10000);
    a.random_float(0, 0.2, RdNormal, 0);
    b.random_float(1.5, 0.3, RdNormal, 0);

    gaussian_para2d g1(0, 1.5, 0.2, 0.3, 0);

    array<double> d(201*301);
    //k.get_distribution(a, b, d);

    a[0] = 0;
    b[0] = 1.5;
    k.get_gradient_y_at(0, a, b, d);

    double t, sum = 0;
    for (size_t i = 0; i < y.size(); i++)
    {
        for (size_t j = 0; j < x.size(); j++)
        {
            std::cout << x[j] << " " << y[i] << " "
                //<< gaussian_dist2d(x[j], y[i], g1) << " "
                << d[201*i + j] << "\n";
        }
    }
    return 0;
}
catch(std::exception &e)
{
    GCTL_ShowWhatError(e.what(), GCTL_ERROR_ERROR, 0, 0, 0);
}