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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.interpolation;
+
+import java.io.Serializable;
+
+import org.apache.commons.math.DuplicateSampleAbscissaException;
+import org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm;
+import org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm;
+
+/**
+ * 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 evaluation is in PolynomialFunctionLagrangeForm,
+ * this class provides an easy-to-use interface to it.</p>
+ *
+ * @version $Revision: 825919 $ $Date: 2009-10-16 16:51:55 +0200 (ven. 16 oct. 2009) $
+ * @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 PolynomialFunctionNewtonForm 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])
+ */
+ 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>
+ */
+ final double[] c = new double[x.length-1];
+ System.arraycopy(x, 0, c, 0, c.length);
+
+ final double[] a = computeDividedDifference(x, y);
+ return new PolynomialFunctionNewtonForm(a, c);
+
+ }
+
+ /**
+ * 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(final double x[], final double y[])
+ throws DuplicateSampleAbscissaException {
+
+ PolynomialFunctionLagrangeForm.verifyInterpolationArray(x, y);
+
+ final double[] divdiff = y.clone(); // initialization
+
+ final int n = x.length;
+ final double[] a = new double [n];
+ a[0] = divdiff[0];
+ for (int i = 1; i < n; i++) {
+ for (int j = 0; j < n-i; j++) {
+ final double 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;
+ }
+}