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diff --git a/FEAST/MIToolbox/Entropy.c b/FEAST/MIToolbox/Entropy.c
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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)*/
+