List of scalarMultiply() Examples

Examples of scalarMultiply()

org.apache.commons.math.geometry.Vector3D.scalarMultiply()
Multiply the instance by a scalar @param a scalar @return a new vector
org.apache.commons.math3.geometry.euclidean.twod.Vector2D.scalarMultiply()
{@inheritDoc}
org.apache.commons.math3.linear.Array2DRowRealMatrix.scalarMultiply()
{@inheritDoc}
org.apache.commons.math3.linear.RealMatrix.scalarMultiply()
Returns the result multiplying each entry of this by d. @param d value to multiply all entries by @return d * this

Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

                    .add(roneu) // regard old matrix
                    .add(arpos.scalarMultiply( // plus rank one update
                                              ccovmu + (1 - negalphaold) * negccov) // plus rank mu update
                         .multiply(times(repmat(weights, 1, dimension),
                                         arpos.transpose())))
                    .subtract(Cneg.scalarMultiply(negccov));
            } else {
                // Adapt covariance matrix C - nonactive
                C = C.scalarMultiply(oldFac) // regard old matrix
                    .add(roneu) // plus rank one update
                    .add(arpos.scalarMultiply(ccovmu) // plus rank mu update

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Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

     * instead.
     */
    @Deprecated
    protected void updateJacobian() {
        final RealMatrix weightedJacobian = computeWeightedJacobian(point);
        weightedResidualJacobian = weightedJacobian.scalarMultiply(-1).getData();
    }


    /**
     * Computes the Jacobian matrix.
     *

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Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

        ccovmuSep = Math.min(1 - ccov1, ccovmu * (dimension + 1.5) / 3);
        chiN = Math.sqrt(dimension) *
            (1 - 1 / ((double) 4 * dimension) + 1 / ((double) 21 * dimension * dimension));
        // intialize CMA internal values - updated each generation
        xmean = MatrixUtils.createColumnRealMatrix(guess); // objective variables
        diagD = insigma.scalarMultiply(1 / sigma);
        diagC = square(diagD);
        pc = zeros(dimension, 1); // evolution paths for C and sigma
        ps = zeros(dimension, 1); // B defines the coordinate system
        normps = ps.getFrobeniusNorm();

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Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

                    .add(roneu) // regard old matrix
                    .add(arpos.scalarMultiply( // plus rank one update
                                              ccovmu + (1 - negalphaold) * negccov) // plus rank mu update
                         .multiply(times(repmat(weights, 1, dimension),
                                         arpos.transpose())))
                    .subtract(Cneg.scalarMultiply(negccov));
            } else {
                // Adapt covariance matrix C - nonactive
                C = C.scalarMultiply(oldFac) // regard old matrix
                    .add(roneu) // plus rank one update
                    .add(arpos.scalarMultiply(ccovmu) // plus rank mu update

View Full Code Here

Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

     * instead.
     */
    @Deprecated
    protected void updateJacobian() {
        final RealMatrix weightedJacobian = computeWeightedJacobian(point);
        weightedResidualJacobian = weightedJacobian.scalarMultiply(-1).getData();
    }


    /**
     * Computes the Jacobian matrix.
     *

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Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

        ccovmuSep = Math.min(1 - ccov1, ccovmu * (dimension + 1.5) / 3);
        chiN = Math.sqrt(dimension) *
            (1 - 1 / ((double) 4 * dimension) + 1 / ((double) 21 * dimension * dimension));
        // intialize CMA internal values - updated each generation
        xmean = MatrixUtils.createColumnRealMatrix(guess); // objective variables
        diagD = insigma.scalarMultiply(1 / sigma);
        diagC = square(diagD);
        pc = zeros(dimension, 1); // evolution paths for C and sigma
        ps = zeros(dimension, 1); // B defines the coordinate system
        normps = ps.getFrobeniusNorm();

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Examples of org.apache.commons.math3.linear.RealMatrix.scalarMultiply()

                    .add(roneu) // regard old matrix
                    .add(arpos.scalarMultiply( // plus rank one update
                                              ccovmu + (1 - negalphaold) * negccov) // plus rank mu update
                         .multiply(times(repmat(weights, 1, dimension),
                                         arpos.transpose())))
                    .subtract(Cneg.scalarMultiply(negccov));
            } else {
                // Adapt covariance matrix C - nonactive
                C = C.scalarMultiply(oldFac) // regard old matrix
                    .add(roneu) // plus rank one update
                    .add(arpos.scalarMultiply(ccovmu) // plus rank mu update

View Full Code Here

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