Matrix m2_czech = pca2.dissimilarityMatrix();
for(int i = 0; i < v1_strong.getColumnDimensionality(); i++) {
Matrix v1_i = v1_strong.getColumn(i);
// check, if distance of v1_i to the space of rv2 > delta
// (i.e., if v1_i spans up a new dimension)
double dist = Math.sqrt(v1_i.transposeTimes(v1_i).get(0, 0) - v1_i.transposeTimes(m2_czech).times(v1_i).get(0, 0));
// if so, insert v1_i into v2 and adjust v2
// and compute m2_czech new , increase lambda2
if(lambda2 < dimensionality && dist > delta) {
adjust(v2, e2_czech, v1_i, lambda2++);