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1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  package org.apache.commons.math4.legacy.analysis.interpolation;
18  
19  import org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction;
20  import org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction;
21  import org.apache.commons.math4.legacy.core.MathArrays;
22  import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
23  import org.apache.commons.math4.legacy.exception.NonMonotonicSequenceException;
24  import org.apache.commons.math4.legacy.exception.NumberIsTooSmallException;
25  import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
26  
27  /**
28   * Computes a clamped cubic spline interpolation for the data set.
29   * <p>
30   * The {@link #interpolate(double[], double[], double, double)} method returns a {@link PolynomialSplineFunction}
31   * consisting of n cubic polynomials, defined over the subintervals determined by the x values,
32   * {@code x[0] < x[i] ... < x[n]}.  The x values are referred to as "knot points."</p>
33   * <p>
34   * The value of the PolynomialSplineFunction at a point x that is greater than or equal to the smallest
35   * knot point and strictly less than the largest knot point is computed by finding the subinterval to which
36   * x belongs and computing the value of the corresponding polynomial at <code>x - x[i]</code> where
37   * <code>i</code> is the index of the subinterval. See {@link PolynomialSplineFunction} for more details.
38   * </p>
39   * <p>
40   * The interpolating polynomials satisfy: <ol>
41   * <li>The value of the PolynomialSplineFunction at each of the input x values equals the
42   *  corresponding y value.</li>
43   * <li>Adjacent polynomials are equal through two derivatives at the knot points (i.e., adjacent polynomials
44   *  "match up" at the knot points, as do their first and second derivatives).</li>
45   * <li>The <i>clamped boundary condition</i>, i.e., the PolynomialSplineFunction takes "a specific direction" at both
46   * its start point and its end point by providing the desired first derivative values (slopes) as function parameters to
47   * {@link #interpolate(double[], double[], double, double)}.</li>
48   * </ol>
49   * <p>
50   * The clamped cubic spline interpolation algorithm implemented is as described in R.L. Burden, J.D. Faires,
51   * <u>Numerical Analysis</u>, 9th Ed., 2010, Cengage Learning, ISBN 0-538-73351-9, pp 153-156.
52   * </p>
53   *
54   */
55  public class ClampedSplineInterpolator extends SplineInterpolator {
56      /**
57       * Computes an interpolating function for the data set.
58       * @param x the arguments for the interpolation points
59       * @param y the values for the interpolation points
60       * @param fpo first derivative at the starting point of the returned spline function (starting slope), satisfying
61       *            clamped boundary condition S′(x0) = f′(x0)
62       * @param fpn first derivative at the ending point of the returned spline function (ending slope), satisfying
63       *            clamped boundary condition S′(xn) = f′(xn)
64       * @return a function which interpolates the data set
65       * @throws DimensionMismatchException if {@code x} and {@code y}
66       * have different sizes.
67       * @throws NumberIsTooSmallException if the size of {@code x < 3}.
68       * @throws org.apache.commons.math4.legacy.exception.NonMonotonicSequenceException
69       * if {@code x} is not sorted in strict increasing order.
70       */
71      public PolynomialSplineFunction interpolate(final double[] x, final double[] y,
72                                                  final double fpo, final double fpn)
73              throws DimensionMismatchException, NumberIsTooSmallException, NonMonotonicSequenceException {
74          if (x.length != y.length) {
75              throw new DimensionMismatchException(x.length, y.length);
76          }
77  
78          if (x.length < 3) {
79              throw new NumberIsTooSmallException(LocalizedFormats.NUMBER_OF_POINTS,
80                                                  x.length, 3, true);
81          }
82  
83          // Number of intervals.  The number of data points is n + 1.
84          final int n = x.length - 1;
85  
86          MathArrays.checkOrder(x);
87  
88          // Differences between knot points
89          final double h[] = new double[n];
90          for (int i = 0; i < n; i++) {
91              h[i] = x[i + 1] - x[i];
92          }
93  
94          final double mu[] = new double[n];
95          final double z[] = new double[n + 1];
96          final double alpha[] = new double[n + 1];
97          final double l[] = new double[n + 1];
98  
99          alpha[0] = 3d * (y[1] - y[0]) / h[0] - 3d * fpo;
100         alpha[n] = 3d * fpn - 3d * (y[n] - y[n - 1]) / h[n - 1];
101 
102         mu[0] = 0.5d;
103         l[0] = 2d * h[0];
104         z[0] = alpha[0] / l[0];
105 
106         for (int i = 1; i < n; i++) {
107 
108             alpha[i] = (3d / h[i]) * (y[i + 1] - y[i]) - (3d / h[i - 1]) * (y[i] - y[i - 1]);
109             l[i] = 2d * (x[i + 1] - x[i - 1]) - h[i - 1] * mu[i - 1];
110             mu[i] = h[i] / l[i];
111             z[i] = (alpha[i] - h[i - 1] * z[i - 1]) / l[i];
112         }
113         // cubic spline coefficients --  b is linear, c quadratic, d is cubic (original y's are constants)
114         final double b[] = new double[n];
115         final double c[] = new double[n + 1];
116         final double d[] = new double[n];
117         l[n] = h[n - 1] * (2d - mu[n - 1]);
118         z[n] = (alpha[n] - h[n - 1] * z[n - 1]) / l[n];
119         c[n] = z[n];
120 
121         for (int j = n - 1; j >= 0; j--) {
122             c[j] = z[j] - mu[j] * c[j + 1];
123             b[j] = ((y[j + 1] - y[j]) / h[j]) - h[j] * (c[j + 1] + 2d * c[j]) / 3d;
124             d[j] = (c[j + 1] - c[j]) / (3d * h[j]);
125         }
126 
127         final PolynomialFunction polynomials[] = new PolynomialFunction[n];
128         final double coefficients[] = new double[4];
129         for (int i = 0; i < n; i++) {
130             coefficients[0] = y[i];
131             coefficients[1] = b[i];
132             coefficients[2] = c[i];
133             coefficients[3] = d[i];
134             polynomials[i] = new PolynomialFunction(coefficients);
135         }
136         return new PolynomialSplineFunction(x, polynomials);
137     }
138 }