some general cleanup

src/machineLearning/rapidGVF/rapidGVF.cpp

@@ -8,20 +8,12 @@
 #include "rapidGVF.h"
 #include "../trainingData.h"
 
-rapidGVF::rapidGVF()
-{
-    // Initialised with default configuration
-    this->gvf = new GVF();
-    this->currentGesture = GVFGesture();
-}
+rapidGVF::rapidGVF() {}
 
-rapidGVF::~rapidGVF()
-{
-    delete this->gvf;
-    this->currentGesture = NULL;
-}
+rapidGVF::~rapidGVF() {}
 
-bool rapidGVF::train(const rapidmix::trainingData &newTrainingData) {
+bool rapidGVF::train(const rapidmix::trainingData &newTrainingData)
+{
     
     if (newTrainingData.trainingSet.size() < 1) {
         // no recorded phrase
@@ -33,15 +25,14 @@ bool rapidGVF::train(const rapidmix::trainingData &newTrainingData) {
         return false;
     }
     
-    if(gvf->getState() != GVF::STATE_LEARNING)
+    if(gvf.getState() != GVF::STATE_LEARNING)
     {
-        gvf->setState(GVF::STATE_LEARNING);
+        gvf.setState(GVF::STATE_LEARNING);
     }
     
     //Go through every phrase
-
-    for (int h = 0; h < newTrainingData.trainingSet.size(); ++h) { //I changed this because the default set is gone. -MZ
-        this->gvf->startGesture();
+    for (int h = 0; h < newTrainingData.trainingSet.size(); ++h) {
+        gvf.startGesture();
         for (int i = 0; i < newTrainingData.trainingSet[h].elements.size(); ++i) {
             
             std::vector<double> vd = newTrainingData.trainingSet[h].elements[i].input;
@@ -50,53 +41,59 @@ bool rapidGVF::train(const rapidmix::trainingData &newTrainingData) {
             std::vector<float> vf(vd.begin(), vd.end());
             this->currentGesture.addObservation(vf);
         }
-        this->gvf->addGestureTemplate(this->currentGesture);
+        gvf.addGestureTemplate(this->currentGesture);
     }
     return true;
 }
 
-std::vector<double> rapidGVF::run(const std::vector<double> &inputVector){
+std::vector<double> rapidGVF::run(const std::vector<double> &inputVector)
+{
     
     if (inputVector.size() == 0) {
         return std::vector<double>();
     }
     
-    gvf->restart();
+    gvf.restart();
     
-    if(gvf->getState() != GVF::STATE_FOLLOWING)
+    if (gvf.getState() != GVF::STATE_FOLLOWING)
     {
-        gvf->setState(GVF::STATE_FOLLOWING);
+        gvf.setState(GVF::STATE_FOLLOWING);
     }
     
     // Using template <class InputIterator> vector to change for vec<double> to vec<float>
     std::vector<float> vf(inputVector.begin(),inputVector.end());
     
     this->currentGesture.addObservation(vf);
-    this->outcomes = this->gvf->update(this->currentGesture.getLastObservation());
+    outcomes = gvf.update(this->currentGesture.getLastObservation());
     
     std::vector<double> output;
-    output.push_back(this->outcomes.likeliestGesture);
-    output.insert(output.end(), this->outcomes.likelihoods.begin(), this->outcomes.likelihoods.end());
-    output.insert(output.end(), this->outcomes.alignments.begin(), this->outcomes.alignments.end());
+    output.push_back(outcomes.likeliestGesture);
+    output.insert(output.end(), outcomes.likelihoods.begin(), outcomes.likelihoods.end());
+    output.insert(output.end(), outcomes.alignments.begin(), outcomes.alignments.end());
     return output;
 }
 
-const std::vector<float> rapidGVF::getLikelihoods() {
+const std::vector<float> rapidGVF::getLikelihoods()
+{
     return outcomes.likelihoods;
 };
 
-const std::vector<float> rapidGVF::getAlignments() {
+const std::vector<float> rapidGVF::getAlignments()
+{
     return outcomes.alignments;
 };
 
-const std::vector<std::vector<float> > * rapidGVF::getDynamics() {
+const std::vector<std::vector<float> > * rapidGVF::getDynamics()
+{
     return &outcomes.dynamics;
 };
 
-const std::vector<std::vector<float> > * rapidGVF::getScalings() {
+const std::vector<std::vector<float> > * rapidGVF::getScalings()
+{
     return &outcomes.scalings;
 };
 
-const std::vector<std::vector<float> > * rapidGVF::getRotations() {
+const std::vector<std::vector<float> > * rapidGVF::getRotations()
+{
     return &outcomes.rotations;
 };

src/machineLearning/rapidGVF/rapidGVF.h

@@ -34,8 +34,8 @@ public:
     const std::vector<std::vector<float> > * getScalings();
     const std::vector<std::vector<float> > * getRotations();
     
-protected:
-    GVF * gvf;
+private:
+    GVF gvf;
     GVFGesture currentGesture;
     GVFOutcomes outcomes;
 };