example_funcgmm_probability.cpp

Programa para el testeo de las funciones.Para compilar o código example_funcgmm_probability.cpp:

g++ -static -o example_funcgmm_probability example_funcgmm_probability.cpp -lpdsmlmm -lpdsramm -lpdsspmm

Para executar o programa:

./example_funcgmm_probability

Retornando por consola:

┌──────────────────────────────┐
│    GMM                       │
│    IterationConf init data   │
├──────────────────────────────┤
│        MinError: 1.0000e-06  │
│         MaxIter: 2000        │
└──────────────────────────────┘
┌──────────────────────────────┐
│            Iter: 71          │
│       LastError: 7.6973e-07  │
│ Elapsed time(s): 0.002359    │
└──────────────────────────────┘
Dat:
Pi[0]: 0.3328
Pi[1]: 0.3195
Pi[2]: 0.3476
Mu[0]:
0.98662265997179     -0.00021508510074319 
Mu[1]:
-0.48555456702506 -0.90962657141875 
Mu[2]:
-0.50986272323955 0.82924594851797  
Sinv[0]:
10.577538761397  0.43347439875572 
0.43347439875572 18.994450171649  
Sinv[1]:
18.206494777711  0.15027393378441 
0.15027393378441 2.9001288199875  
Sinv[2]:
17.289970505333  -1.3245918459504 
-1.3245918459504 6.275061020014   
Det[0]: 0.004981899938309
Det[1]: 0.018947073977717
Det[2]: 0.0093684646413172

example_funcgmm_probability_data.png

example_funcgmm_probability_prob.png

example_funcgmm_probability_prob2.png

example_funcgmm_probability_prob3.png

example_funcgmm_probability_clusters.png

example_funcgmm_probability_clusters2.png

example_funcgmm_probability_clusters3.png

Código example_funcgmm_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=3;
    Pds::Octave::Plot::PointsX2D(X,"testando.m","example_funcgmm_probability_data.png");
    Pds::Octave::MarkerSize=12;
    
    // Mu, Sigma estimation
    Pds::DataGMM Dat=Pds::Clustering::GMM(Conf,X,3,1.0);
    Dat.Print("Dat:\n");
    /*
    Dat.ExportFile("Dat.txt");
    Pds::DataGMM Dat2("Dat.txt");
    Dat2.Print("\nDat2:\n");
    std::ofstream myfile;
    myfile.open("Dat2.txt");
    Dat2.SaveInStream(myfile);
    myfile.close();
    Pds::DataGMM Dat3;
    std::ifstream myinfile("Dat2.txt", std::ifstream::in);
    Dat3.LoadFromStream(myinfile);
    myinfile.close();
    Dat3.Print("\nDat3:\n");
    */
    
    // Gaussian Mixture Model density
    P=Pds::Probability::GMMDensity(X,Dat.Pi,Dat.Mu,Dat.Sinv);
    Pds::Octave::Plot::ScatterX2DY(X,P,"testando.m","example_funcgmm_probability_prob.png");
    
    P=Pds::Probability::GMMDensity(X,Dat.Pi,Dat.Mu,Dat.Sinv,Dat.Det);
    Pds::Octave::Plot::ScatterX2DY(X,P,"testando.m","example_funcgmm_probability_prob2.png");
    
    P=Pds::Probability::GMMDensity(X,Dat);
    Pds::Octave::Plot::ScatterX2DY(X,P,"testando.m","example_funcgmm_probability_prob3.png");
    
    // Gaussian Mixture Model partial density
    Pds::Matrix A;
    Pds::Vector ID;
    
    A=Pds::Probability::GMMPartial(X,Dat.Pi,Dat.Mu,Dat.Sinv);
    ID=A.OperateRows(Pds::ArgMax);
    Pds::Octave::Plot::ScatterX2DY(X,ID,"testando.m","example_funcgmm_probability_clusters.png");
    
    A=Pds::Probability::GMMPartial(X,Dat.Pi,Dat.Mu,Dat.Sinv,Dat.Det);
    ID=A.OperateRows(Pds::ArgMax);
    Pds::Octave::Plot::ScatterX2DY(X,ID,"testando.m","example_funcgmm_probability_clusters2.png");
    
    A=Pds::Probability::GMMPartial(X,Dat);
    ID=A.OperateRows(Pds::ArgMax);
    Pds::Octave::Plot::ScatterX2DY(X,ID,"testando.m","example_funcgmm_probability_clusters3.png");
 
    return 0;
}