| /* |
| * 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.MathIllegalArgumentException; |
| import org.apache.commons.math3.analysis.BivariateFunction; |
| import org.apache.commons.math3.distribution.UniformRealDistribution; |
| import org.apache.commons.math3.random.RandomGenerator; |
| import org.apache.commons.math3.random.Well19937c; |
| import org.junit.Assert; |
| import org.junit.Test; |
| |
| /** |
| * Test case for the bicubic interpolator. |
| * |
| * @deprecated as of 3.4 replaced by {@link org.apache.commons.math3.analysis.interpolation.PiecewiseBicubicSplineInterpolator} |
| */ |
| @Deprecated |
| public final class BicubicSplineInterpolatorTest { |
| /** |
| * Test preconditions. |
| */ |
| @Test |
| public void testPreconditions() { |
| double[] xval = new double[] {3, 4, 5, 6.5}; |
| double[] yval = new double[] {-4, -3, -1, 2.5}; |
| double[][] zval = new double[xval.length][yval.length]; |
| |
| BivariateGridInterpolator interpolator = new BicubicSplineInterpolator(); |
| |
| @SuppressWarnings("unused") |
| BivariateFunction p = interpolator.interpolate(xval, yval, zval); |
| |
| double[] wxval = new double[] {3, 2, 5, 6.5}; |
| try { |
| p = interpolator.interpolate(wxval, yval, zval); |
| Assert.fail("an exception should have been thrown"); |
| } catch (MathIllegalArgumentException e) { |
| // Expected |
| } |
| |
| double[] wyval = new double[] {-4, -3, -1, -1}; |
| try { |
| p = interpolator.interpolate(xval, wyval, zval); |
| Assert.fail("an exception should have been thrown"); |
| } catch (MathIllegalArgumentException e) { |
| // Expected |
| } |
| |
| double[][] wzval = new double[xval.length][yval.length + 1]; |
| try { |
| p = interpolator.interpolate(xval, yval, wzval); |
| Assert.fail("an exception should have been thrown"); |
| } catch (DimensionMismatchException e) { |
| // Expected |
| } |
| wzval = new double[xval.length - 1][yval.length]; |
| try { |
| p = interpolator.interpolate(xval, yval, wzval); |
| Assert.fail("an exception should have been thrown"); |
| } catch (DimensionMismatchException e) { |
| // Expected |
| } |
| } |
| |
| /** |
| * Interpolating a plane. |
| * <p> |
| * z = 2 x - 3 y + 5 |
| */ |
| @Test |
| public void testInterpolation1() { |
| final int sz = 21; |
| double[] xval = new double[sz]; |
| double[] yval = new double[sz]; |
| // Coordinate values |
| final double delta = 1d / (sz - 1); |
| for (int i = 0; i < sz; i++) { |
| xval[i] = -1 + 15 * i * delta; |
| yval[i] = -20 + 30 * i * delta; |
| } |
| |
| // Function values |
| BivariateFunction f = new BivariateFunction() { |
| public double value(double x, double y) { |
| return 2 * x - 3 * y + 5; |
| } |
| }; |
| double[][] zval = new double[xval.length][yval.length]; |
| for (int i = 0; i < xval.length; i++) { |
| for (int j = 0; j < yval.length; j++) { |
| zval[i][j] = f.value(xval[i], yval[j]); |
| } |
| } |
| |
| BivariateGridInterpolator interpolator = new BicubicSplineInterpolator(); |
| BivariateFunction p = interpolator.interpolate(xval, yval, zval); |
| double x, y; |
| |
| final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed. |
| final UniformRealDistribution distX |
| = new UniformRealDistribution(rng, xval[0], xval[xval.length - 1]); |
| final UniformRealDistribution distY |
| = new UniformRealDistribution(rng, yval[0], yval[yval.length - 1]); |
| |
| final int numSamples = 50; |
| final double tol = 6; |
| for (int i = 0; i < numSamples; i++) { |
| x = distX.sample(); |
| for (int j = 0; j < numSamples; j++) { |
| y = distY.sample(); |
| // System.out.println(x + " " + y + " " + f.value(x, y) + " " + p.value(x, y)); |
| Assert.assertEquals(f.value(x, y), p.value(x, y), tol); |
| } |
| // System.out.println(); |
| } |
| } |
| |
| /** |
| * Interpolating a paraboloid. |
| * <p> |
| * z = 2 x<sup>2</sup> - 3 y<sup>2</sup> + 4 x y - 5 |
| */ |
| @Test |
| public void testInterpolation2() { |
| final int sz = 21; |
| double[] xval = new double[sz]; |
| double[] yval = new double[sz]; |
| // Coordinate values |
| final double delta = 1d / (sz - 1); |
| for (int i = 0; i < sz; i++) { |
| xval[i] = -1 + 15 * i * delta; |
| yval[i] = -20 + 30 * i * delta; |
| } |
| |
| // Function values |
| BivariateFunction f = new BivariateFunction() { |
| public double value(double x, double y) { |
| return 2 * x * x - 3 * y * y + 4 * x * y - 5; |
| } |
| }; |
| double[][] zval = new double[xval.length][yval.length]; |
| for (int i = 0; i < xval.length; i++) { |
| for (int j = 0; j < yval.length; j++) { |
| zval[i][j] = f.value(xval[i], yval[j]); |
| } |
| } |
| |
| BivariateGridInterpolator interpolator = new BicubicSplineInterpolator(); |
| BivariateFunction p = interpolator.interpolate(xval, yval, zval); |
| double x, y; |
| |
| final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed. |
| final UniformRealDistribution distX |
| = new UniformRealDistribution(rng, xval[0], xval[xval.length - 1]); |
| final UniformRealDistribution distY |
| = new UniformRealDistribution(rng, yval[0], yval[yval.length - 1]); |
| |
| final int numSamples = 50; |
| final double tol = 251; |
| for (int i = 0; i < numSamples; i++) { |
| x = distX.sample(); |
| for (int j = 0; j < numSamples; j++) { |
| y = distY.sample(); |
| // System.out.println(x + " " + y + " " + f.value(x, y) + " " + p.value(x, y)); |
| Assert.assertEquals(f.value(x, y), p.value(x, y), tol); |
| } |
| // System.out.println(); |
| } |
| } |
| } |