Example usage for org.apache.commons.math3.linear RealVector copy

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealVector copy.

Prototype

public abstract RealVector copy();

Source Link

Document

Returns a (deep) copy of this vector.

Usage

From source file:hivemall.utils.math.MatrixUtils.java

/**
 * Lanczos tridiagonalization for a symmetric matrix C to make s * s tridiagonal matrix T.
 *
 * @see http://www.cas.mcmaster.ca/~qiao/publications/spie05.pdf
 * @param C target symmetric matrix/*from  w w w  . ja va  2  s . c om*/
 * @param a initial vector
 * @param T result is stored here
 */
public static void lanczosTridiagonalization(@Nonnull final RealMatrix C, @Nonnull final double[] a,
        @Nonnull final RealMatrix T) {
    Preconditions.checkArgument(Arrays.deepEquals(C.getData(), C.transpose().getData()),
            "Target matrix C must be a symmetric matrix");
    Preconditions.checkArgument(C.getColumnDimension() == a.length,
            "Column size of A and length of a should be same");
    Preconditions.checkArgument(T.getRowDimension() == T.getColumnDimension(), "T must be a square matrix");

    int s = T.getRowDimension();

    // initialize T with zeros
    T.setSubMatrix(new double[s][s], 0, 0);

    RealVector a0 = new ArrayRealVector(a.length);
    RealVector r = new ArrayRealVector(a);

    double beta0 = 1.d;

    for (int i = 0; i < s; i++) {
        RealVector a1 = r.mapDivide(beta0);
        RealVector Ca1 = C.operate(a1);

        double alpha1 = a1.dotProduct(Ca1);

        r = Ca1.add(a1.mapMultiply(-1.d * alpha1)).add(a0.mapMultiply(-1.d * beta0));

        double beta1 = r.getNorm();

        T.setEntry(i, i, alpha1);
        if (i - 1 >= 0) {
            T.setEntry(i, i - 1, beta0);
        }
        if (i + 1 < s) {
            T.setEntry(i, i + 1, beta1);
        }

        a0 = a1.copy();
        beta0 = beta1;
    }
}

---

From source file:edu.ucsf.valelab.saim.calculations.SaimParameterValidator.java

/**
 * Very simple validator that uses lower and upper bounds to restrict
 * parameter values//from   w  ww.  j  av  a 2  s .  c  om
 * @param params
 * @return 
 */
@Override
public RealVector validate(RealVector params) {
    if (params.getDimension() != 3)
        throw new DimensionMismatchException(params.getDimension(), 3);
    RealVector n = params.copy();
    for (int i = 0; i < 3; i++) {
        if (n.getEntry(i) < lowerBounds_[i])
            n.setEntry(i, lowerBounds_[i]);
        if (n.getEntry(i) > upperBounds_[i])
            n.setEntry(i, upperBounds_[i]);
    }
    return n;
}

---

From source file:edu.stanford.cfuller.imageanalysistools.fitting.NelderMeadMinimizer.java

/**
 * Constructs the initial simplex that is the starting point of the optimization given an initial guess at the minimum and a size scale for each parameter.
 * @param initialPoint      The initial guess at the minimum, one component per parameter.
 * @param componentScales   A size scale for each parameter that is used to set how large the initial simplex is.
 * @return                  A matrix containing p + 1 rows, each of which is one set of p parameters, which specify the simplex.
 *//*from  www . j a v a 2s.c  o m*/
public RealMatrix generateInitialSimplex(RealVector initialPoint, RealVector componentScales) {
    RealMatrix initialSimplex = new Array2DRowRealMatrix(initialPoint.getDimension() + 1,
            initialPoint.getDimension());

    initialSimplex.setRowVector(0, initialPoint);

    for (int i = 1; i < initialSimplex.getRowDimension(); i++) {
        RealVector newVector = initialPoint.copy();
        newVector.setEntry(i - 1, newVector.getEntry(i - 1) + componentScales.getEntry(i - 1));
        initialSimplex.setRowVector(i, newVector);
    }

    return initialSimplex;
}

---

From source file:org.grouplens.samantha.modeler.space.SynchronizedVariableSpace.java

final public List<RealVector> getVectorVarByName(String name) {
    List<RealVector> vars = new ArrayList<>();
    readLock.lock();/*from   w ww.ja v  a  2 s.  com*/
    try {
        for (RealVector var : vectorVars.get(name)) {
            vars.add(var.copy());
        }
        return vars;
    } finally {
        readLock.unlock();
    }
}

---

From source file:org.knime.al.util.noveltydetection.knfst.MatrixFunctions.java

public static RealVector sqrt(final RealVector vector) {
    final RealVector result = vector.copy();
    for (int e = 0; e < result.getDimension(); e++) {
        result.setEntry(e, Math.sqrt(result.getEntry(e)));
    }//www . j a va  2  s .co  m
    return result;
}

---

From source file:shapeCompare.PairingTools.java

public static RealVector alignPointFromShape2toShape1(RealVector trans2toOrigin, RealVector trans,
        RealMatrix rot, RealVector point) {

    RealVector translatedToOriginPoint = point.add(trans2toOrigin.copy());
    RealVector rotatedPoint = rot.operate(translatedToOriginPoint);
    RealVector translatedBackPoint = rotatedPoint.subtract(trans2toOrigin);

    RealVector translatedToShape1 = translatedBackPoint.add(trans);

    return translatedToShape1;
}

---