SimpleDiscreteDistribution.cpp

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//
// File: SimpleDiscreteDistribution.cpp
// Authors:
//   Julien Dutheil
// Created: ?
//
 
/*
  Copyright or © or Copr. Bio++ Development Team, (November 17, 2004)
  
  This software is a computer program whose purpose is to provide classes
  for numerical calculus.
  
  This software is governed by the CeCILL license under French law and
  abiding by the rules of distribution of free software. You can use,
  modify and/ or redistribute the software under the terms of the CeCILL
  license as circulated by CEA, CNRS and INRIA at the following URL
  "http://www.cecill.info".
  
  As a counterpart to the access to the source code and rights to copy,
  modify and redistribute granted by the license, users are provided only
  with a limited warranty and the software's author, the holder of the
  economic rights, and the successive licensors have only limited
  liability.
  
  In this respect, the user's attention is drawn to the risks associated
  with loading, using, modifying and/or developing or reproducing the
  software by the user in light of its specific status of free software,
  that may mean that it is complicated to manipulate, and that also
  therefore means that it is reserved for developers and experienced
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  knowledge of the CeCILL license and that you accept its terms.
*/
 
 
#include "../../Text/TextTools.h"
#include "../../Utils/MapTools.h"
#include "../NumConstants.h"
#include "SimpleDiscreteDistribution.h"
 
using namespace bpp;
using namespace std;
 
 
SimpleDiscreteDistribution::SimpleDiscreteDistribution(const map<double, double>& distribution,
                                                       double prec,
                                                       bool fixed) :
  AbstractDiscreteDistribution(distribution.size(), prec, "Simple."),
  givenRanges_()
{
  double sum = 0;
  for (map<double, double>::const_iterator i = distribution.begin(); i != distribution.end(); i++)
  {
    distribution_[i->first] = i->second;
    sum += i->second;
  }
  if (fabs(1. - sum) > precision())
    throw Exception("SimpleDiscreteDistribution. Probabilities must equal 1 (sum =" + TextTools::toString(sum) + ").");
 
  if (!fixed)
  {
    unsigned int n = 1;
    double x, y = 1;
    for (map<double, double>::const_iterator i = distribution.begin(); i != distribution.end(); i++)
    {
      addParameter_(new Parameter("Simple.V" + TextTools::toString(n), i->first));
 
      if (n != numberOfCategories_)
      {
        x = i->second;
        addParameter_(new Parameter("Simple.theta" + TextTools::toString(n), x / y, Parameter::PROP_CONSTRAINT_IN));
        y -= x;
      }
      n++;
    }
  }
  discretize();
}
 
SimpleDiscreteDistribution::SimpleDiscreteDistribution(const vector<double>& values,
                                                       const vector<double>& probas,
                                                       double prec,
                                                       bool fixed
                                                       ) :
  AbstractDiscreteDistribution(values.size(), prec, "Simple."),
  givenRanges_()
{
  if (values.size() != probas.size())
  {
    throw Exception("SimpleDiscreteDistribution. Values and probabilities vectors must have the same size (" + TextTools::toString(values.size()) + " != " + TextTools::toString(probas.size()) + ").");
  }
  size_t size = values.size();
 
  for (size_t i = 0; i < size; i++)
  {
    if (distribution_.find(values[i]) != distribution_.end())
      throw Exception("SimpleDiscreteDistribution: two given values are equal");
    else
      distribution_[values[i]] = probas[i];
  }
 
  double sum = VectorTools::sum(probas);
  if (fabs(1. - sum) > precision())
    throw Exception("SimpleDiscreteDistribution. Probabilities must equal 1 (sum =" + TextTools::toString(sum) + ").");
 
  if (!fixed)
  {
    double y = 1;
    for (size_t i = 0; i < size - 1; i++)
    {
      addParameter_(new Parameter("Simple.V" + TextTools::toString(i + 1), values[i]));
      addParameter_(new Parameter("Simple.theta" + TextTools::toString(i + 1), probas[i] / y, Parameter::PROP_CONSTRAINT_IN));
      y -= probas[i];
    }
    addParameter_(new Parameter("Simple.V" + TextTools::toString(size), values[size - 1]));
  }
 
  discretize();
}
 
SimpleDiscreteDistribution::SimpleDiscreteDistribution(const std::vector<double>& values,
                                                       const std::map<size_t, std::vector<double> >& ranges,
                                                       const std::vector<double>& probas,
                                                       double prec,
                                                       bool fixed) :
  AbstractDiscreteDistribution(values.size(), prec, "Simple."),
  givenRanges_()
{
  if (values.size() != probas.size())
  {
    throw Exception("SimpleDiscreteDistribution. Values and probabilities vectors must have the same size (" + TextTools::toString(values.size()) + " != " + TextTools::toString(probas.size()) + ").");
  }
  size_t size = values.size();
 
  for (size_t i = 0; i < size; i++)
  {
    if (distribution_.find(values[i]) != distribution_.end())
      throw Exception("SimpleDiscreteDistribution: two given values are equal");
    else
      distribution_[values[i]] = probas[i];
  }
 
  double sum = VectorTools::sum(probas);
  if (fabs(1. - sum) > precision())
    throw Exception("SimpleDiscreteDistribution. Probabilities must equal 1 (sum =" + TextTools::toString(sum) + ").");
 
  if (!fixed)
  {
    double y = 1;
    for (size_t i = 0; i < size - 1; i++)
    {
      map<size_t, vector<double> >::const_iterator it = ranges.find(i + 1);
      if (it == ranges.end())
        addParameter_(new Parameter("Simple.V" + TextTools::toString(i + 1), values[i]));
      else
      {
        if (values[i] >= it->second[0] &&  values[i] <= it->second[1])
        {
          addParameter_(new Parameter("Simple.V" + TextTools::toString(i + 1), values[i], std::make_shared<IntervalConstraint>(it->second[0], it->second[1], true, true)));
          givenRanges_[i + 1] = it->second;
        }
        else
          throw Exception("SimpleDiscreteDistribution. Value and given range of parameter V" + TextTools::toString(i + 1) + " do not match: " + TextTools::toString(values[i]) + " vs [" + TextTools::toString(it->second[0]) + ";" + TextTools::toString(it->second[1]) + "]");
      }
      addParameter_(new Parameter("Simple.theta" + TextTools::toString(i + 1), probas[i] / y, Parameter::PROP_CONSTRAINT_IN));
      y -= probas[i];
    }
 
    map<size_t, vector<double> >::const_iterator it = ranges.find(size);
    if (it == ranges.end())
      addParameter_(new Parameter("Simple.V" + TextTools::toString(size), values[size - 1]));
    else
    {
      if (values[size - 1] >= it->second[0] &&  values[size - 1] <= it->second[1])
      {
        addParameter_(new Parameter("Simple.V" + TextTools::toString(size), values[size - 1], std::make_shared<IntervalConstraint>(it->second[0], it->second[1], true, true)));
        givenRanges_[size] = it->second;
      }
      else
        throw Exception("SimpleDiscreteDistribution. Value and given range of parameter V" + TextTools::toString(size) + " do not match: " + TextTools::toString(values[size - 1]) + " vs [" + TextTools::toString(it->second[0]) + ";" + TextTools::toString(it->second[1]) + "]");
    }
  }
 
  discretize();
}
 
 
SimpleDiscreteDistribution::SimpleDiscreteDistribution(const SimpleDiscreteDistribution& sdd) :
  AbstractDiscreteDistribution(sdd),
  givenRanges_(sdd.givenRanges_)
{}
 
SimpleDiscreteDistribution& SimpleDiscreteDistribution::operator=(const SimpleDiscreteDistribution& sdd)
{
  AbstractDiscreteDistribution::operator=(sdd);
  givenRanges_ = sdd.givenRanges_;
 
  return *this;
}
 
void SimpleDiscreteDistribution::fireParameterChanged(const ParameterList& parameters)
{
  if (getNumberOfParameters() != 0)
  {
    AbstractDiscreteDistribution::fireParameterChanged(parameters);
    size_t size = distribution_.size();
 
    distribution_.clear();
    double x = 1.0;
    double v;
    for (size_t i = 0; i < size; i++)
    {
      v = getParameterValue("V" + TextTools::toString(i + 1));
      double v2(v);
      if (distribution_.find(v2) != distribution_.end())
      {
        int j(1);
        while (true)
        {
          v2 = v + j * precision();
          if (v2 < intMinMax_->getUpperBound() && (distribution_.find(v2) == distribution_.end()))
            break;
 
          v2 = v - j * precision();
          if (v2 > intMinMax_->getLowerBound() && (distribution_.find(v2) == distribution_.end()))
            break;
          j++;
        }
        // approximation to avoid useless computings:
        // setParameterValue("V"+TextTools::toString(i+1),v);
      }
      if (i < size - 1)
      {
        distribution_[v2] = getParameterValue("theta" + TextTools::toString(i + 1)) * x;
        x *= 1 - getParameterValue("theta" + TextTools::toString(i + 1));
      }
      else
        distribution_[v2] = x;
    }
  }
 
  discretize();
}
 
double SimpleDiscreteDistribution::qProb(double x) const
{
  double s = -NumConstants::VERY_BIG();
  double x2 = x;
  for (map<double, double>::const_iterator it = distribution_.begin(); it != distribution_.end(); it++)
  {
    x2 -= it->second;
    if (x2 < 0)
      return s;
    else
      s = it->second;
  }
 
  return s;
}
 
double SimpleDiscreteDistribution::pProb(double x) const
{
  double s = 0;
  for (map<double, double>::const_iterator it = distribution_.begin(); it != distribution_.end(); it++)
  {
    if (it->first >= x)
      s += it->second;
    else
      break;
  }
 
  return s;
}
 
double SimpleDiscreteDistribution::Expectation(double a) const
{
  double s = 0;
  for (map<double, double>::const_iterator it = distribution_.begin(); it != distribution_.end(); it++)
  {
    if (it->first >= a)
      s += it->second;
    else
      break;
  }
 
  return s;
}
 
 
void SimpleDiscreteDistribution::discretize()
{
  // Compute a new arbitray bounderi:
  vector<double> values = MapTools::getKeys<double, double, AbstractDiscreteDistribution::Order>(distribution_);
 
  // Fill from 0 to numberOfCategories_-2 with midpoints:
  for (unsigned int i = 0; i < numberOfCategories_ - 1; i++)
  {
    bounds_[i] = (values[i] + values[i + 1]) / 2.;
  }
}
 
void SimpleDiscreteDistribution::restrictToConstraint(const Constraint& c)
{
  if (getNumberOfParameters() == 0)
    return;
 
  const IntervalConstraint* pi = dynamic_cast<const IntervalConstraint*>(&c);
 
  if (!pi)
    throw Exception("SimpleDiscreteDistribution::restrictToConstraint: Non-interval exception");
 
  map<double, double>::const_iterator it;
 
  for (it = distribution_.begin(); it != distribution_.end(); it++)
  {
    if (!pi->isCorrect(it->first))
      throw Exception("Impossible to restrict to Constraint value " + TextTools::toString(it->first));
  }
 
  AbstractDiscreteDistribution::restrictToConstraint(c);
 
  size_t size = distribution_.size();
  for (size_t i = 0; i < size; i++)
  {
    map<size_t, vector<double> >::const_iterator itr = givenRanges_.find(i + 1);
    if (itr == givenRanges_.end())
      getParameter_("V" + TextTools::toString(i + 1)).setConstraint(intMinMax_);
    else
    {
      std::shared_ptr<Constraint> pc = getParameter_("V" + TextTools::toString(i + 1)).removeConstraint();
      getParameter_("V" + TextTools::toString(i + 1)).setConstraint(std::shared_ptr<Constraint>(*pc & *intMinMax_));
    }
  }
}