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/*******************************************************************************
** Entropy.cpp
** Part of the mutual information toolbox
**
** Contains functions to calculate the entropy of a single variable H(X),
** the joint entropy of two variables H(X,Y), and the conditional entropy
** H(X|Y)
**
** Author: Adam Pocock
** Created 19/2/2010
**
** Copyright 2010 Adam Pocock, The University Of Manchester
** www.cs.manchester.ac.uk
**
** This file is part of MIToolbox.
**
** MIToolbox is free software: you can redistribute it and/or modify
** it under the terms of the GNU Lesser General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.
**
** MIToolbox is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU Lesser General Public License for more details.
**
** You should have received a copy of the GNU Lesser General Public License
** along with MIToolbox. If not, see <http://www.gnu.org/licenses/>.
**
*******************************************************************************/
#include "MIToolbox.h"
#include "CalculateProbability.h"
#include "Entropy.h"
double calculateEntropy(double *dataVector, int vectorLength)
{
double entropy = 0.0;
double tempValue = 0.0;
int i;
ProbabilityState state = calculateProbability(dataVector,vectorLength);
/*H(X) = - sum p(x) log p(x)*/
for (i = 0; i < state.numStates; i++)
{
tempValue = state.probabilityVector[i];
if (tempValue > 0)
{
entropy -= tempValue * log(tempValue);
}
}
entropy /= log(2.0);
FREE_FUNC(state.probabilityVector);
state.probabilityVector = NULL;
return entropy;
}/*calculateEntropy(double *,int)*/
double calculateJointEntropy(double *firstVector, double *secondVector, int vectorLength)
{
double jointEntropy = 0.0;
double tempValue = 0.0;
int i;
JointProbabilityState state = calculateJointProbability(firstVector,secondVector,vectorLength);
/*H(XY) = - sumx sumy p(xy) log p(xy)*/
for (i = 0; i < state.numJointStates; i++)
{
tempValue = state.jointProbabilityVector[i];
if (tempValue > 0)
{
jointEntropy -= tempValue * log(tempValue);
}
}
jointEntropy /= log(2.0);
FREE_FUNC(state.firstProbabilityVector);
state.firstProbabilityVector = NULL;
FREE_FUNC(state.secondProbabilityVector);
state.secondProbabilityVector = NULL;
FREE_FUNC(state.jointProbabilityVector);
state.jointProbabilityVector = NULL;
return jointEntropy;
}/*calculateJointEntropy(double *, double *, int)*/
double calculateConditionalEntropy(double *dataVector, double *conditionVector, int vectorLength)
{
/*
** Conditional entropy
** H(X|Y) = - sumx sumy p(xy) log p(xy)/p(y)
*/
double condEntropy = 0.0;
double jointValue = 0.0;
double condValue = 0.0;
int i;
JointProbabilityState state = calculateJointProbability(dataVector,conditionVector,vectorLength);
/*H(X|Y) = - sumx sumy p(xy) log p(xy)/p(y)*/
/* to index by numFirstStates use modulus of i
** to index by numSecondStates use integer division of i by numFirstStates
*/
for (i = 0; i < state.numJointStates; i++)
{
jointValue = state.jointProbabilityVector[i];
condValue = state.secondProbabilityVector[i / state.numFirstStates];
if ((jointValue > 0) && (condValue > 0))
{
condEntropy -= jointValue * log(jointValue / condValue);
}
}
condEntropy /= log(2.0);
FREE_FUNC(state.firstProbabilityVector);
state.firstProbabilityVector = NULL;
FREE_FUNC(state.secondProbabilityVector);
state.secondProbabilityVector = NULL;
FREE_FUNC(state.jointProbabilityVector);
state.jointProbabilityVector = NULL;
return condEntropy;
}/*calculateConditionalEntropy(double *, double *, int)*/
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