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Diffstat (limited to 'FEAST/MIToolbox/RenyiEntropy.c')
| -rw-r--r-- | FEAST/MIToolbox/RenyiEntropy.c | 192 |
1 files changed, 0 insertions, 192 deletions
diff --git a/FEAST/MIToolbox/RenyiEntropy.c b/FEAST/MIToolbox/RenyiEntropy.c deleted file mode 100644 index c0c4bd4..0000000 --- a/FEAST/MIToolbox/RenyiEntropy.c +++ /dev/null @@ -1,192 +0,0 @@ -/******************************************************************************* -** RenyiEntropy.cpp -** Part of the mutual information toolbox -** -** Contains functions to calculate the Renyi alpha entropy of a single variable -** H_\alpha(X), the Renyi joint entropy of two variables H_\alpha(X,Y), and the -** conditional Renyi entropy H_\alpha(X|Y) -** -** Author: Adam Pocock -** Created 26/3/2010 -** -** 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 "ArrayOperations.h" -#include "CalculateProbability.h" -#include "Entropy.h" -#include "util.h" - -double calculateRenyiEntropy(double alpha, double *dataVector, int vectorLength) -{ - double entropy = 0.0; - double tempValue = 0.0; - int i; - ProbabilityState state = calculateProbability(dataVector,vectorLength); - - /*H_\alpha(X) = 1/(1-alpha) * log(2)(sum p(x)^alpha)*/ - for (i = 0; i < state.numStates; i++) - { - tempValue = state.probabilityVector[i]; - - if (tempValue > 0) - { - entropy += pow(tempValue,alpha); - /*printf("Entropy = %f, i = %d\n", entropy,i);*/ - } - } - - /*printf("Entropy = %f\n", entropy);*/ - - entropy = log(entropy); - - entropy /= log(2.0); - - entropy /= (1.0-alpha); - - /*printf("Entropy = %f\n", entropy);*/ - FREE_FUNC(state.probabilityVector); - state.probabilityVector = NULL; - - return entropy; -}/*calculateRenyiEntropy(double,double*,int)*/ - -double calculateJointRenyiEntropy(double alpha, double *firstVector, double *secondVector, int vectorLength) -{ - double jointEntropy = 0.0; - double tempValue = 0.0; - int i; - JointProbabilityState state = calculateJointProbability(firstVector,secondVector,vectorLength); - - /*H_\alpha(XY) = 1/(1-alpha) * log(2)(sum p(xy)^alpha)*/ - for (i = 0; i < state.numJointStates; i++) - { - tempValue = state.jointProbabilityVector[i]; - if (tempValue > 0) - { - jointEntropy += pow(tempValue,alpha); - } - } - - jointEntropy = log(jointEntropy); - - jointEntropy /= log(2.0); - - jointEntropy /= (1.0-alpha); - - FREE_FUNC(state.firstProbabilityVector); - state.firstProbabilityVector = NULL; - FREE_FUNC(state.secondProbabilityVector); - state.secondProbabilityVector = NULL; - FREE_FUNC(state.jointProbabilityVector); - state.jointProbabilityVector = NULL; - - return jointEntropy; -}/*calculateJointRenyiEntropy(double,double*,double*,int)*/ - -double calcCondRenyiEnt(double alpha, double *dataVector, double *conditionVector, int uniqueInCondVector, int vectorLength) -{ - /*uniqueInCondVector = is the number of unique values in the cond vector.*/ - - /*condEntropy = sum p(y) * sum p(x|y)^alpha(*/ - - /* - ** first generate the seperate variables - */ - - double *seperateVectors = safe_calloc(uniqueInCondVector*vectorLength,sizeof(double)); - int *seperateVectorCount = safe_calloc(uniqueInCondVector,sizeof(int)); - double seperateVectorProb = 0.0; - int i,j; - double entropy = 0.0; - double tempValue = 0.0; - int currentValue; - double tempEntropy; - ProbabilityState state; - - double **seperateVectors2D = safe_calloc(uniqueInCondVector,sizeof(double*)); - for(j=0; j < uniqueInCondVector; j++) - seperateVectors2D[j] = seperateVectors + (int)j*vectorLength; - - for (i = 0; i < vectorLength; i++) - { - currentValue = (int) (conditionVector[i] - 1.0); - /*printf("CurrentValue = %d\n",currentValue);*/ - seperateVectors2D[currentValue][seperateVectorCount[currentValue]] = dataVector[i]; - seperateVectorCount[currentValue]++; - } - - - - for (j = 0; j < uniqueInCondVector; j++) - { - tempEntropy = 0.0; - seperateVectorProb = ((double)seperateVectorCount[j]) / vectorLength; - state = calculateProbability(seperateVectors2D[j],seperateVectorCount[j]); - - /*H_\alpha(X) = 1/(1-alpha) * log(2)(sum p(x)^alpha)*/ - for (i = 0; i < state.numStates; i++) - { - tempValue = state.probabilityVector[i]; - - if (tempValue > 0) - { - tempEntropy += pow(tempValue,alpha); - /*printf("Entropy = %f, i = %d\n", entropy,i);*/ - } - } - - /*printf("Entropy = %f\n", entropy);*/ - - tempEntropy = log(tempEntropy); - - tempEntropy /= log(2.0); - - tempEntropy /= (1.0-alpha); - - entropy += tempEntropy; - - FREE_FUNC(state.probabilityVector); - } - - FREE_FUNC(seperateVectors2D); - seperateVectors2D = NULL; - - FREE_FUNC(seperateVectors); - FREE_FUNC(seperateVectorCount); - - seperateVectors = NULL; - seperateVectorCount = NULL; - - return entropy; -}/*calcCondRenyiEnt(double *,double *,int)*/ - -double calculateConditionalRenyiEntropy(double alpha, double *dataVector, double *conditionVector, int vectorLength) -{ - /*calls this: - **double calculateConditionalRenyiEntropy(double alpha, double *firstVector, double *condVector, int uniqueInCondVector, int vectorLength) - **after determining uniqueInCondVector - */ - int numUnique = numberOfUniqueValues(conditionVector, vectorLength); - - return calcCondRenyiEnt(alpha, dataVector, conditionVector, numUnique, vectorLength); -}/*calculateConditionalRenyiEntropy(double,double*,double*,int)*/ - |