Java Code Examples for cern.colt.matrix.linalg.EigenvalueDecomposition#getRealEigenvalues()

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Example 1
Source File: PZTFactorizer.java    From RankSys with Mozilla Public License 2.0 6 votes vote down vote up 
private static DoubleMatrix2D getGt(final DenseDoubleMatrix2D p, final DenseDoubleMatrix2D q, double lambda) {
    final int K = p.columns();

    DenseDoubleMatrix2D A1 = new DenseDoubleMatrix2D(K, K);
    q.zMult(q, A1, 1.0, 0.0, true, false);
    for (int k = 0; k < K; k++) {
        A1.setQuick(k, k, lambda + A1.getQuick(k, k));
    }

    EigenvalueDecomposition eig = new EigenvalueDecomposition(A1);
    DoubleMatrix1D d = eig.getRealEigenvalues();
    DoubleMatrix2D gt = eig.getV();
    for (int k = 0; k < K; k++) {
        double a = sqrt(d.get(k));
        gt.viewColumn(k).assign(x -> a * x);
    }

    return gt;
}
Example 2
Source File: EPolyPC.java    From OSPREY3 with GNU General Public License v2.0 5 votes vote down vote up 
public EPolyPC( EPoly template, int fullOrder, int PCOrder, double PCFac) {
    //set up the principal component basis and the DOF information
    //coeffs will be added later
    //since we will be using this EPolyPC object when performing the fitting
    
    super(template.numDOFs,template.DOFmax,template.DOFmin,template.center,
            template.minE,null,fullOrder,template.DOFNames);
    
    //get the coordinate transformation into the eigenbasis of the template's Hessian
    //so we can use the high-eigenvalue directions as our principcal components
    DoubleMatrix2D hess = SeriesFitter.getHessian(template.coeffs,numDOFs,false);
    EigenvalueDecomposition edec = new EigenvalueDecomposition(hess);

    DoubleMatrix1D eigVals = edec.getRealEigenvalues();
    DoubleMatrix2D eigVecs = edec.getV();//The columns of eigVec are the eigenvectors

    invAxisCoeffs = eigVecs;//axisCoeffs' inverse is its transpose, since it's orthogonal
    axisCoeffs = Algebra.DEFAULT.transpose(eigVecs);
    

    this.fullOrder = fullOrder;
    this.PCOrder = PCOrder;


    //Now figure out what PC's to use
    //Let's try the criterion to use all PCs
    //whose eigenvalues' absolute values are within a factor of PCFac
    //of the biggest

    double maxEigVal = 0;
    for(int n=0; n<numDOFs; n++)
        maxEigVal = Math.max( Math.abs(eigVals.get(n)), maxEigVal );

    isPC = new boolean[numDOFs];

    for(int n=0; n<numDOFs; n++){
        if( Math.abs(eigVals.get(n)) >= maxEigVal*PCFac )
            isPC[n] = true;
    }
}