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Java example source code file (SmoothingPolynomialBicubicSplineInterpolator.java)

This example Java source code file (SmoothingPolynomialBicubicSplineInterpolator.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

bicubicsplineinterpolatingfunction, deprecated, dimensionmismatchexception, gaussnewtonoptimizer, nodataexception, nonmonotonicsequenceexception, notpositiveexception, nullargumentexception, override, polynomialfitter, polynomialfunction, simplevectorvaluechecker, smoothingpolynomialbicubicsplineinterpolator

The SmoothingPolynomialBicubicSplineInterpolator.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.analysis.interpolation;

import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.NoDataException;
import org.apache.commons.math3.exception.NonMonotonicSequenceException;
import org.apache.commons.math3.exception.NotPositiveException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.util.MathArrays;
import org.apache.commons.math3.util.Precision;
import org.apache.commons.math3.optim.nonlinear.vector.jacobian.GaussNewtonOptimizer;
import org.apache.commons.math3.fitting.PolynomialFitter;
import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
import org.apache.commons.math3.optim.SimpleVectorValueChecker;

/**
 * Generates a bicubic interpolation function.
 * Prior to generating the interpolating function, the input is smoothed using
 * polynomial fitting.
 *
 * @since 2.2
 * @deprecated To be removed in 4.0 (see MATH-1166).
 */
@Deprecated
public class SmoothingPolynomialBicubicSplineInterpolator
    extends BicubicSplineInterpolator {
    /** Fitter for x. */
    private final PolynomialFitter xFitter;
    /** Degree of the fitting polynomial. */
    private final int xDegree;
    /** Fitter for y. */
    private final PolynomialFitter yFitter;
    /** Degree of the fitting polynomial. */
    private final int yDegree;

    /**
     * Default constructor. The degree of the fitting polynomials is set to 3.
     */
    public SmoothingPolynomialBicubicSplineInterpolator() {
        this(3);
    }

    /**
     * @param degree Degree of the polynomial fitting functions.
     * @exception NotPositiveException if degree is not positive
     */
    public SmoothingPolynomialBicubicSplineInterpolator(int degree)
        throws NotPositiveException {
        this(degree, degree);
    }

    /**
     * @param xDegree Degree of the polynomial fitting functions along the
     * x-dimension.
     * @param yDegree Degree of the polynomial fitting functions along the
     * y-dimension.
     * @exception NotPositiveException if degrees are not positive
     */
    public SmoothingPolynomialBicubicSplineInterpolator(int xDegree, int yDegree)
        throws NotPositiveException {
        if (xDegree < 0) {
            throw new NotPositiveException(xDegree);
        }
        if (yDegree < 0) {
            throw new NotPositiveException(yDegree);
        }
        this.xDegree = xDegree;
        this.yDegree = yDegree;

        final double safeFactor = 1e2;
        final SimpleVectorValueChecker checker
            = new SimpleVectorValueChecker(safeFactor * Precision.EPSILON,
                                           safeFactor * Precision.SAFE_MIN);
        xFitter = new PolynomialFitter(new GaussNewtonOptimizer(false, checker));
        yFitter = new PolynomialFitter(new GaussNewtonOptimizer(false, checker));
    }

    /**
     * {@inheritDoc}
     */
    @Override
    public BicubicSplineInterpolatingFunction interpolate(final double[] xval,
                                                          final double[] yval,
                                                          final double[][] fval)
        throws NoDataException, NullArgumentException,
               DimensionMismatchException, NonMonotonicSequenceException {
        if (xval.length == 0 || yval.length == 0 || fval.length == 0) {
            throw new NoDataException();
        }
        if (xval.length != fval.length) {
            throw new DimensionMismatchException(xval.length, fval.length);
        }

        final int xLen = xval.length;
        final int yLen = yval.length;

        for (int i = 0; i < xLen; i++) {
            if (fval[i].length != yLen) {
                throw new DimensionMismatchException(fval[i].length, yLen);
            }
        }

        MathArrays.checkOrder(xval);
        MathArrays.checkOrder(yval);

        // For each line y[j] (0 <= j < yLen), construct a polynomial, with
        // respect to variable x, fitting array fval[][j]
        final PolynomialFunction[] yPolyX = new PolynomialFunction[yLen];
        for (int j = 0; j < yLen; j++) {
            xFitter.clearObservations();
            for (int i = 0; i < xLen; i++) {
                xFitter.addObservedPoint(1, xval[i], fval[i][j]);
            }

            // Initial guess for the fit is zero for each coefficients (of which
            // there are "xDegree" + 1).
            yPolyX[j] = new PolynomialFunction(xFitter.fit(new double[xDegree + 1]));
        }

        // For every knot (xval[i], yval[j]) of the grid, calculate corrected
        // values fval_1
        final double[][] fval_1 = new double[xLen][yLen];
        for (int j = 0; j < yLen; j++) {
            final PolynomialFunction f = yPolyX[j];
            for (int i = 0; i < xLen; i++) {
                fval_1[i][j] = f.value(xval[i]);
            }
        }

        // For each line x[i] (0 <= i < xLen), construct a polynomial, with
        // respect to variable y, fitting array fval_1[i][]
        final PolynomialFunction[] xPolyY = new PolynomialFunction[xLen];
        for (int i = 0; i < xLen; i++) {
            yFitter.clearObservations();
            for (int j = 0; j < yLen; j++) {
                yFitter.addObservedPoint(1, yval[j], fval_1[i][j]);
            }

            // Initial guess for the fit is zero for each coefficients (of which
            // there are "yDegree" + 1).
            xPolyY[i] = new PolynomialFunction(yFitter.fit(new double[yDegree + 1]));
        }

        // For every knot (xval[i], yval[j]) of the grid, calculate corrected
        // values fval_2
        final double[][] fval_2 = new double[xLen][yLen];
        for (int i = 0; i < xLen; i++) {
            final PolynomialFunction f = xPolyY[i];
            for (int j = 0; j < yLen; j++) {
                fval_2[i][j] = f.value(yval[j]);
            }
        }

        return super.interpolate(xval, yval, fval_2);
    }
}

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