Package org.ejml.simple

Examples of org.ejml.simple.SimpleMatrix.normF()

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        SimpleMatrix _W = SimpleMatrix.wrap(W);
        SimpleMatrix _Vt = SimpleMatrix.wrap(Vt);

        SimpleMatrix foundA = _U.mult(_W).mult(_Vt);

        return SpecializedOps.diffNormF(orig,foundA.getMatrix())/foundA.normF();
    }

    /**
     * <p>
     * Computes a metric which measures the the quality of an eigen value decomposition.  If a
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        SimpleMatrix L = A.mult(V);
        SimpleMatrix R = V.mult(D);

        SimpleMatrix diff = L.minus(R);

        double top = diff.normF();
        double bottom = L.normF();

        double error = top/bottom;

        return error;
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            if( max > 0 && v.getNumElements() > 1 ) {
                // normalize to reduce overflow issues
                v = v.divide(max);

                // compute the magnitude of the vector
                double tau = v.normF();

                if( v.get(0) < 0 )
                    tau *= -1.0;

                double u_0 = v.get(0) + tau;
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        SimpleMatrix A_found = U.mult(B).mult(Vt);
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        double top = A_found.minus(A).normF();
        double bottom = A.normF();

        return top/bottom;
    }

    private static void runAlgorithms( DenseMatrix64F mat  )
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        SimpleMatrix A_found = T.mult(T.transpose());
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        double top = A_found.minus(A).normF();
        double bottom = A.normF();

        return top/bottom;
    }

    private static void runAlgorithms( DenseMatrix64F mat  )
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        SimpleMatrix R = SimpleMatrix.wrap(alg.getR(null,true));

        SimpleMatrix A_found = Q.mult(R);
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        return A.minus(A_found).normF()/A.normF();
    }

    public static double evaluate( QRPDecomposition<DenseMatrix64F> alg , DenseMatrix64F orig ) {

        double maxValue = CommonOps.elementMaxAbs(orig);
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        SimpleMatrix P = SimpleMatrix.wrap(alg.getPivotMatrix(null));

        SimpleMatrix A_found = Q.mult(R);
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        return A.mult(P).minus(A_found).normF()/A.normF();
    }

    private static void runAlgorithms( DenseMatrix64F mat  )
    {
        System.out.println("qr               = "+ evaluate(new QRDecompositionHouseholder(),mat));
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        SimpleMatrix A_found = O.mult(T).mult(O.transpose());
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        double top = A_found.minus(A).normF();
        double bottom = A.normF();

        return top/bottom;
    }

    private static void runAlgorithms( DenseMatrix64F mat  )
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