Commit 941e9bc7 authored by Sascha Niklas Schneiders's avatar Sascha Niklas Schneiders
Browse files

updated expected test results

parent 2eb7e07c
#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
......@@ -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){
......
......@@ -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){
......
......@@ -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){
......
......@@ -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){
......
......@@ -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){
......
#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
......@@ -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){
......
......@@ -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");