updated expected test results

src/test/resources/results/armadillo/detectionObjectDetector/HelperA.h

+#ifndef HELPERA_H
+#define HELPERA_H
+#define _GLIBCXX_USE_CXX11_ABI 0
+#include <iostream>
+#include "armadillo.h"
+#include <stdarg.h>
+#include <initializer_list>
+using namespace arma;
+class HelperA{
+public:
+static mat getEigenVectors(mat A){
+vec eigenValues;
+mat eigenVectors;
+eig_sym(eigenValues,eigenVectors,A);
+return eigenVectors;
+}
+static vec getEigenValues(mat A){
+vec eigenValues;
+mat eigenVectors;
+eig_sym(eigenValues,eigenVectors,A);
+return eigenValues;
+}
+
+static mat getKMeansClusters(mat A, int k){
+mat clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
+}
+
+static mat getSqrtMat(mat A){
+cx_mat result=sqrtmat(A);
+return real(result);
+}
+};
+#endif

src/test/resources/results/armadillo/paperMatrixModifier/l0/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/armadillo/paperMatrixModifier/l1/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/armadillo/paperMatrixModifier/l2/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/armadillo/paperMatrixModifier/l3/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/armadillo/testMath/l0/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/testBasicGenericArrayInstance/HelperA.h

+#ifndef HELPERA_H
+#define HELPERA_H
+#define _GLIBCXX_USE_CXX11_ABI 0
+#include <iostream>
+#include "armadillo.h"
+#include <stdarg.h>
+#include <initializer_list>
+using namespace arma;
+class HelperA{
+public:
+static mat getEigenVectors(mat A){
+vec eigenValues;
+mat eigenVectors;
+eig_sym(eigenValues,eigenVectors,A);
+return eigenVectors;
+}
+static vec getEigenValues(mat A){
+vec eigenValues;
+mat eigenVectors;
+eig_sym(eigenValues,eigenVectors,A);
+return eigenValues;
+}
+
+static mat getKMeansClusters(mat A, int k){
+mat clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
+}
+
+static mat getSqrtMat(mat A){
+cx_mat result=sqrtmat(A);
+return real(result);
+}
+};
+#endif

src/test/resources/results/testBasicGenericInstance/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");
+     myfile2 << clusters;
+     myfile2.close();
+mat indexedData=getKMeansClustersIndexData(A.t(), clusters);
+
+std::ofstream myfile3;
+     myfile3.open("data after index.txt");
+     myfile3 << indexedData;
+     myfile3.close();
+	 
+return indexedData;
+}
+
+static mat getKMeansClustersIndexData(mat A, mat centroids){
+	mat result=mat(A.n_cols, 1);
+	for(int i=0;i<A.n_cols;++i){
+		result(i, 0) = getIndexForClusterCentroids(A, i, centroids);
+	}
+	return result;
+}
+
+static int getIndexForClusterCentroids(mat A, int colIndex, mat centroids){
+	int index=1;
+	double lowestDistance=getEuclideanDistance(A, colIndex, centroids, 0);
+	for(int i=1;i<centroids.n_cols;++i){
+		double curDistance=getEuclideanDistance(A, colIndex, centroids, i);
+		if(curDistance<lowestDistance){
+			lowestDistance=curDistance;
+			index=i+1;
+		}
+	}
+	return index;
+}
+
+static double getEuclideanDistance(mat A, int colIndexA, mat B, int colIndexB){
+	double distance=0;
+	for(int i=0;i<A.n_rows;++i){
+		double elementA=A(i,colIndexA);
+		double elementB=B(i,colIndexB);
+		double diff=elementA-elementB;
+		distance+=diff*diff;
+	}
+	return sqrt(distance);
 }
 
 static mat getSqrtMat(mat A){

src/test/resources/results/testMath/l0/HelperA.h

@@ -20,10 +20,60 @@ mat eigenVectors;
 eig_sym(eigenValues,eigenVectors,A);
 return eigenValues;
 }
+
 static mat getKMeansClusters(mat A, int k){
 mat clusters;
-kmeans(clusters,A,k,random_subset,10,true);
-return clusters;
+kmeans(clusters,A.t(),k,random_subset,20,true);
+printf("cluster centroid calculation done\n");
+std::ofstream myfile;
+     myfile.open("data after cluster.txt");
+     myfile << A;
+     myfile.close();
+	 
+	 std::ofstream myfile2;
+     myfile2.open("cluster centroids.txt");