example_funcpwc_probability.cpp

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
    
int main(void)
{
    Pds::Octave::XLabel="x1";
    Pds::Octave::YLabel="x2";
    Pds::Octave::DAspect=true;
    
    Pds::IterationConf Conf; Conf.Show=true; Conf.SetMinError(1.0e-6);
    unsigned int L=1000;
    Pds::Matrix X;
    Pds::Vector Y;
    Pds::Vector P;
    
    // Generating data X=[x1 x2]
    Pds::DataSet::Classification::LoadKGaussian(L,3,X,Y);
    
    Pds::Octave::MarkerSize=4;
    Pds::Octave::Plot::PointsX2D(X,"testando.m","example_funcpwc_probability_data.png");
    
    // Mu, Sigma estimation
    Pds::Matrix Sinv=X.CovMatrix().Inv();
    
    // density function
    P=Pds::Probability::PWCDensity(X,X,Sinv,0.1);
    
    Pds::Octave::MarkerSize=12;
    Pds::Octave::Plot::ScatterX2DY(X,P,"testando.m","example_funcpwc_probability_prob.png");
    
    // density function
    P=Pds::Probability::PWCDensity(X,X,Sinv,0.1,1.0/Sinv.Det());
    
    Pds::Octave::MarkerSize=12;
    Pds::Octave::Plot::ScatterX2DY(X,P,"testando.m","example_funcpwc_probability_prob2.png");
 
    return 0;
}