public double[] getCumulativeInertia() {
double tot = 0.0;
for (double val : ca.getRates()) {
tot += val;
}
double[] p = new double[ca.getRates().length];
for (int i = 0; i < p.length; i++) {
p[i] = ca.getRates()[i] / tot;
if (i > 0) p[i] += p[i - 1];
}
return p;
}
public ResultCA(CorrespondenceAnalysis ca, Word[] rowlabs, ConciseDocument[] collabs) {
this.rowlabs = rowlabs;
this.collabs = collabs;
principal = ca.getPrincipalMatrix();
n = principal.getRowDimension();
m = principal.getColumnDimension();
double[][] data = principal.getArray();
double[] rowmass = principal.getRowMass();
double[] colmass = principal.getColumnMass();
double trace = ca.getTrace();
this.ca = ca;
int nfactor = Math.min(n, m) - 1;
// First determine inertias of observations (rows) and
// variables (columns), and qualities of representation
// in the new factor space.
rinertia = new double[n]; // relative inertia
cinertia = new double[m];
rquality = new double[n]; // quality
cquality = new double[m];
for (int i = 0; i < n; i++) {
rinertia[i] = 0.0;
rquality[i] = 0.0;
for (int j = 0; j < m; j++) {
rinertia[i] += Math.pow((data[i][j] / rowmass[i] - colmass[j]), 2.0) / colmass[j];
}
rinertia[i] = rowmass[i] * rinertia[i] / trace;
for (int k = 1; k <= nfactor; k++) {
rquality[i] += ca.getRowCorrelations()[i][k];
}
}
for (int j = 0; j < m; j++) {
cinertia[j] = 0.0;
cquality[j] = 0.0;
for (int i = 0; i < n; i++) {
cinertia[j] += Math.pow((data[i][j] / colmass[j] - rowmass[i]), 2.0) / rowmass[i];
}
cinertia[j] = colmass[j] * cinertia[j] / trace;
for (int k = 1; k <= nfactor; k++) {
cquality[j] += ca.getColumnCorrelations()[j][k];
}
}
}
public double[][] getRowContributions() {
return ca.getRowContributions();
}
public double[][] getRowCorrelations() {
return ca.getRowCorrelations();
}
public double[][] getRowProjections() {
return ca.getRowProjections();
}
public double getTrace() {
return ca.getTrace();
}
public double[] getLambda() {
return ca.getEigenvalues();
}
public double[] getRatesOfInertia() {
return ca.getRates();
}
public double[][] getColumnContributions() {
return ca.getColumnContributions();
}
public double[][] getColumnCorrelations() {
return ca.getColumnCorrelations();
}
public double[][] getColumnProjections() {
return ca.getColumnProjections();
}
