Distribution.h

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/* -*- Mode: C++; -*- */
/* VER: $Id$*/
// copyright (c) 2004 by Christos Dimitrakakis <dimitrak@idiap.ch>
/***************************************************************************
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 ***************************************************************************/
 
#ifndef DISTRIBUTION_H
#define DISTRIBUTION_H
 
#include <learning/real.h>
#include <cmath>
 
void setRandomSeed(unsigned int seed);
real urandom();
real urandom(real min, real max);

class Distribution {
 public:
    Distribution() {}
    virtual ~Distribution() {}
    virtual real generate() = 0; 
    virtual real pdf(real x) = 0; 
};

class ParametricDistribution : public Distribution {
public:
    ParametricDistribution() {}
    virtual ~ParametricDistribution() {}
    virtual void setVariance (real var) = 0; 
    virtual void setMean (real mean) = 0; 
};
 

class DiscreteDistribution : public Distribution {
public:
    int n_outcomes; 
    real* p; 
    DiscreteDistribution();
    DiscreteDistribution(int N); 
    virtual ~DiscreteDistribution();
    virtual real generate();
    virtual real pdf(real x);
};

class NormalDistribution : public ParametricDistribution {
private:
    bool cache;
    real normal_x, normal_y, normal_rho;
public:
    real m; 
    real s; 
    NormalDistribution() {m=0.0; s=1.0; cache = false;}
    NormalDistribution(real mean, real std)
    {
        setMean (mean);
        setVariance (std*std);
    }
    virtual ~NormalDistribution() { }
    virtual real generate();
    virtual real pdf(real x);
    virtual void setVariance (real var) 
    {s = sqrt(var);} 
    virtual void setMean (real mean)
    {m = mean;}
};

class UniformDistribution : public ParametricDistribution {
public:
    real m; 
    real s; 
    UniformDistribution() {m=0.0; s=1.0;}
    UniformDistribution(real mean, real std)
    {
        setMean (mean);
        setVariance (std*std);
    }
    virtual ~UniformDistribution() {}
    virtual real generate();
    virtual real pdf(real x);
    virtual void setVariance (real var) 
    {s = sqrt(12.0 * var);} 
    virtual void setMean (real mean)
    {m = mean;}
};
 

class LaplacianDistribution : public ParametricDistribution {
public:
    real l; 
    real m; 
    LaplacianDistribution() {m=0.0;l=1.0;}
    LaplacianDistribution(real lambda)
    {
        m = 0.0;
        l = lambda;
    }
    LaplacianDistribution(real mean, real var)
    {
        setMean (mean);
        setVariance (var);
    }
    virtual ~LaplacianDistribution() {}
    virtual real generate();
    virtual real pdf(real x);
    virtual void setVariance (real var)
    {l = sqrt(0.5 / var);}
    virtual void setMean (real mean)
    {m = mean;}
};

class ExponentialDistribution : public ParametricDistribution {
public:
    real l; 
    real m; 
    ExponentialDistribution() {m=0.0; l=1.0;}
    ExponentialDistribution(real lambda)
    {
        l = lambda;
    }
    ExponentialDistribution(real mean, real var)
    {
        setMean(mean);
        setVariance(var);
    }
    virtual ~ExponentialDistribution() {}
    virtual real generate();
    virtual real pdf(real x);
    virtual void setVariance (real var)
    {l = sqrt(1.0 / var);}
    virtual void setMean (real mean)
    {m = mean;}
};

class MultinomialGaussian : public Distribution {
public:
    int d; 
    MultinomialGaussian() {d=1;}
    MultinomialGaussian(int d)
    {
        this->d = d;
    }
    virtual ~MultinomialGaussian() {}
    virtual real generate();
    virtual real pdf(real x);
};
 
 
#endif