Examples of net.algart.math.functions.AbstractFunc

net.algart.math.functions.AbstractFunc

A skeletal implementation of the {@link Func} interface to minimizethe effort required to implement this interface.

Warning: in most cases, we strongly recommend to override the overloaded versions of get method ( {@link #get()}, {@link #get(double)}, {@link #get(double,double)}, {@link #get(double,double,double)}), if they are applicable for your function. The default implementations, provided by this class, work relatively slowly, because they allocate a little Java array for passing to the basic {@link #get(double)} method. For example, if you create a function with two argumentsf(x₀, x₁) = x₀/x₁, you should override the version with two arguments: {@link #get(double,double)}.

AlgART Laboratory 2007–2014
@author Daniel Alievsky @version 1.2 @since JDK 1.5

        final double rScaleInv = 1.0 / r.array().maxPossibleValue(1.0);
        final double gScaleInv = 1.0 / g.array().maxPossibleValue(1.0);
        final double bScaleInv = 1.0 / b.array().maxPossibleValue(1.0);
        final double destScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double rScaleInv = 1.0 / r.array().maxPossibleValue(1.0);
        final double gScaleInv = 1.0 / g.array().maxPossibleValue(1.0);
        final double bScaleInv = 1.0 / b.array().maxPossibleValue(1.0);
        final double destScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double rScaleInv = 1.0 / r.array().maxPossibleValue(1.0);
        final double gScaleInv = 1.0 / g.array().maxPossibleValue(1.0);
        final double bScaleInv = 1.0 / b.array().maxPossibleValue(1.0);
        final double destScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double rScaleInv = 1.0 / r.array().maxPossibleValue(1.0);
        final double gScaleInv = 1.0 / g.array().maxPossibleValue(1.0);
        final double bScaleInv = 1.0 / b.array().maxPossibleValue(1.0);
        final double destScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double rScaleInv = 1.0 / r.array().maxPossibleValue(1.0);
        final double gScaleInv = 1.0 / g.array().maxPossibleValue(1.0);
        final double bScaleInv = 1.0 / b.array().maxPossibleValue(1.0);
        final double destScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double hScaleInv = 1.0 / hue.array().maxPossibleValue(1.0);
        final double sScaleInv = 1.0 / saturation.array().maxPossibleValue(1.0);
        final double vScaleInv = 1.0 / value.array().maxPossibleValue(1.0);
        final double resultScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double hScaleInv = 1.0 / hue.array().maxPossibleValue(1.0);
        final double sScaleInv = 1.0 / saturation.array().maxPossibleValue(1.0);
        final double vScaleInv = 1.0 / value.array().maxPossibleValue(1.0);
        final double resultScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        final double hScaleInv = 1.0 / hue.array().maxPossibleValue(1.0);
        final double sScaleInv = 1.0 / saturation.array().maxPossibleValue(1.0);
        final double vScaleInv = 1.0 / value.array().maxPossibleValue(1.0);
        final double resultScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

        if (attachmentInformation == null)
            throw new NullPointerException("Null attachmentInformation");
        Matrix<? extends PIntegerArray> packed = asNeighbourhoodBitMaps(skeleton);
        switch (attachmentInformation) {
            case NEIGHBOUR_INDEX_OF_ATTACHING_BRANCH:
                return Matrices.asFuncMatrix(false, new AbstractFunc() {
                    @Override
                    public double get(double... x) {
                        return get(x[0]);
                    }


                    @Override
                    public double get(double x0) {
                        int apertureBits = (int) x0; // precise operations, because x0 is "int" 31-bit value
                        if ((apertureBits & 1) == 0) {
                            return TYPE_ZERO;
                        }
                        return pixelTypeOrAttachingBranch(apertureBits >>> 1);
                    }
                }, IntArray.class, packed);
            case NEIGHBOUR_INDEX_OF_ATTACHED_NODE:
                return Matrices.asFuncMatrix(false, new AbstractFunc() {
                    @Override
                    public double get(double... x) {
                        return get(x[0]);
                    }

View Full Code Here

        final double hScaleInv = 1.0 / hue.array().maxPossibleValue(1.0);
        final double sScaleInv = 1.0 / saturation.array().maxPossibleValue(1.0);
        final double lScaleInv = 1.0 / lightness.array().maxPossibleValue(1.0);
        final double resultScale = Arrays.maxPossibleValue(resultType, 1.0);
        return Matrices.asFuncMatrix(
            new AbstractFunc() {
                @Override
                public double get(double... x) {
                    return get(x[0], x[1], x[2]);
                }

View Full Code Here

0 1

TOP

Related Classes of net.algart.math.functions.AbstractFunc

net.algart.external.ImageConversions

net.algart.matrices.skeletons.ApertureBasedSkeletonPixelClassifier

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.