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📄 divideddifferenceinterpolator.java

📁 Apache的common math数学软件包
💻 JAVA
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/* * 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.math.analysis;import java.io.Serializable;import org.apache.commons.math.DuplicateSampleAbscissaException;/** * Implements the <a href=" * "http://mathworld.wolfram.com/NewtonsDividedDifferenceInterpolationFormula.html"> * Divided Difference Algorithm</a> for interpolation of real univariate * functions. For reference, see <b>Introduction to Numerical Analysis</b>, * ISBN 038795452X, chapter 2. * <p> * The actual code of Neville's evalution is in PolynomialFunctionLagrangeForm, * this class provides an easy-to-use interface to it.</p> * * @version $Revision: 620312 $ $Date: 2008-02-10 12:28:59 -0700 (Sun, 10 Feb 2008) $ * @since 1.2 */public class DividedDifferenceInterpolator implements UnivariateRealInterpolator,    Serializable {    /** serializable version identifier */    private static final long serialVersionUID = 107049519551235069L;    /**     * Computes an interpolating function for the data set.     *     * @param x the interpolating points array     * @param y the interpolating values array     * @return a function which interpolates the data set     * @throws DuplicateSampleAbscissaException if arguments are invalid     */    public UnivariateRealFunction interpolate(double x[], double y[]) throws        DuplicateSampleAbscissaException {        /**         * a[] and c[] are defined in the general formula of Newton form:         * p(x) = a[0] + a[1](x-c[0]) + a[2](x-c[0])(x-c[1]) + ... +         *        a[n](x-c[0])(x-c[1])...(x-c[n-1])         */        double a[], c[];        PolynomialFunctionLagrangeForm.verifyInterpolationArray(x, y);        /**         * When used for interpolation, the Newton form formula becomes         * p(x) = f[x0] + f[x0,x1](x-x0) + f[x0,x1,x2](x-x0)(x-x1) + ... +         *        f[x0,x1,...,x[n-1]](x-x0)(x-x1)...(x-x[n-2])         * Therefore, a[k] = f[x0,x1,...,xk], c[k] = x[k].         * <p>         * Note x[], y[], a[] have the same length but c[]'s size is one less.</p>         */        c = new double[x.length-1];        for (int i = 0; i < c.length; i++) {            c[i] = x[i];        }        a = computeDividedDifference(x, y);        PolynomialFunctionNewtonForm p;        p = new PolynomialFunctionNewtonForm(a, c);        return p;    }    /**     * Returns a copy of the divided difference array.     * <p>      * The divided difference array is defined recursively by <pre>     * f[x0] = f(x0)     * f[x0,x1,...,xk] = (f(x1,...,xk) - f(x0,...,x[k-1])) / (xk - x0)     * </pre></p>     * <p>     * The computational complexity is O(N^2).</p>     *     * @param x the interpolating points array     * @param y the interpolating values array     * @return a fresh copy of the divided difference array     * @throws DuplicateSampleAbscissaException if any abscissas coincide     */    protected static double[] computeDividedDifference(double x[], double y[])        throws DuplicateSampleAbscissaException {        int i, j, n;        double divdiff[], a[], denominator;        PolynomialFunctionLagrangeForm.verifyInterpolationArray(x, y);        n = x.length;        divdiff = new double[n];        for (i = 0; i < n; i++) {            divdiff[i] = y[i];      // initialization        }        a = new double [n];        a[0] = divdiff[0];        for (i = 1; i < n; i++) {            for (j = 0; j < n-i; j++) {                denominator = x[j+i] - x[j];                if (denominator == 0.0) {                    // This happens only when two abscissas are identical.                    throw new DuplicateSampleAbscissaException(x[j], j, j+i);                }                divdiff[j] = (divdiff[j+1] - divdiff[j]) / denominator;            }            a[i] = divdiff[0];        }        return a;    }}

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