main.cpp

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#include <iostream>
#include <fstream>

#include "geostat.h"

int main(void)
{
        // dimension of control space
        const size_t dim_cspace = 2;
        // number of samples
        const size_t num_samples = 16;

        // kriging predictor
        CGeostat krig;

        // initialize kriging predictor
        krig.initialize(num_samples, dim_cspace);


        //
        // define a domain of control space
        //
        gsl_vector *lower = gsl_vector_alloc(dim_cspace);
        gsl_vector *upper = gsl_vector_alloc(dim_cspace);
        //
        //control parameter c1 : 0 <= c1 <= 4.0
        gsl_vector_set(lower, 0, 0.0);
        gsl_vector_set(upper, 0, 4.0);
        //
        // control parameter c2 : 0 <= c2 <= 5.0
        gsl_vector_set(lower, 1, 0.0);
        gsl_vector_set(upper, 1, 5.0);
        //
        // set domain
        krig.setDomain(lower, upper);
        //
        gsl_vector_free(lower);
        gsl_vector_free(upper);


        //
        // sample data
        //
        gsl_vector *c = gsl_vector_alloc(dim_cspace);

        double tmp, pred, var;
        for (size_t i = 0;i < num_samples;i++)
        {
                //
                // regular sampling point...
                gsl_vector_set(c, 0, static_cast<double>(i / 4));
                gsl_vector_set(c, 1, static_cast<double>(i % 4));
                //
                // coordinate of i-th sample
                krig.setCoordinate(i, c);

                //
                // randomly generated sample data
                tmp = static_cast<double>(rand()) / static_cast<double>(RAND_MAX);
                //
                // data of i-th sample
                krig.setData(i, tmp);
        }


        //
        // precomputation of statistical analysis
        //
        //  using Spherical variogram model
        //  power coefficient = 0 (only use for stable variogram model)
        //  step width (h_step = 0.1)
        krig.estimate(CVariogram::VARIO_SPH, 0, 0.1);


        //
        // output file stream
        std::ofstream ofkrig;
        ofkrig.open("krig.csv");

        //
        // prediction: 100x100 sample point
        //
        for (size_t i = 0;i < 100;i++)
        {
                // target parameter c1
                gsl_vector_set(c, 0, 0.04 * i);
                for (size_t j = 0;j < 100;j++)
                {
                        // target parameter c2
                        gsl_vector_set(c, 1, 0.04 * j);

                        // predictive value and estimate variance at parameter c
                        krig.getPredictData(pred, var, c);
                        ofkrig << pred << ", ";
                }
                ofkrig << std::endl;
        }
        ofkrig.close();
        
        gsl_vector_free(c);

        return 0;
}

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