Raymond | dee0849 | 2015-04-02 10:43:13 -0700 | [diff] [blame] | 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.math.analysis.interpolation; |
| 18 | |
| 19 | import org.apache.commons.math.exception.DimensionMismatchException; |
| 20 | import org.apache.commons.math.exception.NoDataException; |
| 21 | import org.apache.commons.math.MathException; |
| 22 | import org.apache.commons.math.util.MathUtils; |
| 23 | import org.apache.commons.math.optimization.general.GaussNewtonOptimizer; |
| 24 | import org.apache.commons.math.optimization.fitting.PolynomialFitter; |
| 25 | import org.apache.commons.math.analysis.polynomials.PolynomialFunction; |
| 26 | |
| 27 | /** |
| 28 | * Generates a bicubic interpolation function. |
| 29 | * Prior to generating the interpolating function, the input is smoothed using |
| 30 | * polynomial fitting. |
| 31 | * |
| 32 | * @version $Revision: 1003892 $ $Date: 2010-10-02 23:28:56 +0200 (sam. 02 oct. 2010) $ |
| 33 | * @since 2.2 |
| 34 | */ |
| 35 | public class SmoothingPolynomialBicubicSplineInterpolator |
| 36 | extends BicubicSplineInterpolator { |
| 37 | |
| 38 | /** Fitter for x. */ |
| 39 | private final PolynomialFitter xFitter; |
| 40 | |
| 41 | /** Fitter for y. */ |
| 42 | private final PolynomialFitter yFitter; |
| 43 | |
| 44 | /** |
| 45 | * Default constructor. The degree of the fitting polynomials is set to 3. |
| 46 | */ |
| 47 | public SmoothingPolynomialBicubicSplineInterpolator() { |
| 48 | this(3); |
| 49 | } |
| 50 | |
| 51 | /** |
| 52 | * @param degree Degree of the polynomial fitting functions. |
| 53 | */ |
| 54 | public SmoothingPolynomialBicubicSplineInterpolator(int degree) { |
| 55 | this(degree, degree); |
| 56 | } |
| 57 | |
| 58 | /** |
| 59 | * @param xDegree Degree of the polynomial fitting functions along the |
| 60 | * x-dimension. |
| 61 | * @param yDegree Degree of the polynomial fitting functions along the |
| 62 | * y-dimension. |
| 63 | */ |
| 64 | public SmoothingPolynomialBicubicSplineInterpolator(int xDegree, |
| 65 | int yDegree) { |
| 66 | xFitter = new PolynomialFitter(xDegree, new GaussNewtonOptimizer(false)); |
| 67 | yFitter = new PolynomialFitter(yDegree, new GaussNewtonOptimizer(false)); |
| 68 | } |
| 69 | |
| 70 | /** |
| 71 | * {@inheritDoc} |
| 72 | */ |
| 73 | @Override |
| 74 | public BicubicSplineInterpolatingFunction interpolate(final double[] xval, |
| 75 | final double[] yval, |
| 76 | final double[][] fval) |
| 77 | throws MathException { |
| 78 | if (xval.length == 0 || yval.length == 0 || fval.length == 0) { |
| 79 | throw new NoDataException(); |
| 80 | } |
| 81 | if (xval.length != fval.length) { |
| 82 | throw new DimensionMismatchException(xval.length, fval.length); |
| 83 | } |
| 84 | |
| 85 | final int xLen = xval.length; |
| 86 | final int yLen = yval.length; |
| 87 | |
| 88 | for (int i = 0; i < xLen; i++) { |
| 89 | if (fval[i].length != yLen) { |
| 90 | throw new DimensionMismatchException(fval[i].length, yLen); |
| 91 | } |
| 92 | } |
| 93 | |
| 94 | MathUtils.checkOrder(xval); |
| 95 | MathUtils.checkOrder(yval); |
| 96 | |
| 97 | // For each line y[j] (0 <= j < yLen), construct a polynomial, with |
| 98 | // respect to variable x, fitting array fval[][j] |
| 99 | final PolynomialFunction[] yPolyX = new PolynomialFunction[yLen]; |
| 100 | for (int j = 0; j < yLen; j++) { |
| 101 | xFitter.clearObservations(); |
| 102 | for (int i = 0; i < xLen; i++) { |
| 103 | xFitter.addObservedPoint(1, xval[i], fval[i][j]); |
| 104 | } |
| 105 | |
| 106 | yPolyX[j] = xFitter.fit(); |
| 107 | } |
| 108 | |
| 109 | // For every knot (xval[i], yval[j]) of the grid, calculate corrected |
| 110 | // values fval_1 |
| 111 | final double[][] fval_1 = new double[xLen][yLen]; |
| 112 | for (int j = 0; j < yLen; j++) { |
| 113 | final PolynomialFunction f = yPolyX[j]; |
| 114 | for (int i = 0; i < xLen; i++) { |
| 115 | fval_1[i][j] = f.value(xval[i]); |
| 116 | } |
| 117 | } |
| 118 | |
| 119 | // For each line x[i] (0 <= i < xLen), construct a polynomial, with |
| 120 | // respect to variable y, fitting array fval_1[i][] |
| 121 | final PolynomialFunction[] xPolyY = new PolynomialFunction[xLen]; |
| 122 | for (int i = 0; i < xLen; i++) { |
| 123 | yFitter.clearObservations(); |
| 124 | for (int j = 0; j < yLen; j++) { |
| 125 | yFitter.addObservedPoint(1, yval[j], fval_1[i][j]); |
| 126 | } |
| 127 | |
| 128 | xPolyY[i] = yFitter.fit(); |
| 129 | } |
| 130 | |
| 131 | // For every knot (xval[i], yval[j]) of the grid, calculate corrected |
| 132 | // values fval_2 |
| 133 | final double[][] fval_2 = new double[xLen][yLen]; |
| 134 | for (int i = 0; i < xLen; i++) { |
| 135 | final PolynomialFunction f = xPolyY[i]; |
| 136 | for (int j = 0; j < yLen; j++) { |
| 137 | fval_2[i][j] = f.value(yval[j]); |
| 138 | } |
| 139 | } |
| 140 | |
| 141 | return super.interpolate(xval, yval, fval_2); |
| 142 | } |
| 143 | } |