@Override
public EigenvalueTableModel getEigenvalueTableModel() {
double varianceSum = 0.0d;
for (Eigenvector wv : eigenVectors) {
varianceSum += wv.getEigenvalue();
}
return new EigenvalueTableModel(eigenVectors, cumulativeVariance, varianceSum);
}
@Override
public double[] getCumulativeVariance() {
double[] cumulativeVariance = new double[attributeNames.length];
double varianceSum = 0.0d;
int i = 0;
for (Eigenvector wv : eigenVectors) {
varianceSum += wv.getEigenvalue();
cumulativeVariance[i++] = varianceSum;
}
return cumulativeVariance;
}
/** Calculates the cumulative variance. */
private void calculateCumulativeVariance() {
double sumvariance = 0.0d;
for (Eigenvector ev : this.eigenVectors) {
sumvariance += ev.getEigenvalue();
}
this.variances = new double[this.eigenVectors.size()];
this.cumulativeVariance = new double[variances.length];
double cumulative = 0.0d;
int counter = 0;
for (Eigenvector ev : this.eigenVectors) {
double proportion = ev.getEigenvalue() / sumvariance;
this.variances[counter] = proportion;
cumulative += proportion;
this.cumulativeVariance[counter] = cumulative;
counter++;
}
}
