| /* |
| * 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.math4.legacy.analysis.interpolation; |
| |
| import org.apache.commons.math4.legacy.TestUtils; |
| import org.apache.commons.math4.legacy.analysis.UnivariateFunction; |
| import org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction; |
| import org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction; |
| import org.apache.commons.math4.legacy.exception.DimensionMismatchException; |
| import org.apache.commons.math4.legacy.exception.NonMonotonicSequenceException; |
| import org.apache.commons.math4.legacy.exception.NumberIsTooSmallException; |
| import org.junit.Assert; |
| import org.junit.Test; |
| |
| /** |
| * Test the LinearInterpolator. |
| */ |
| public class LinearInterpolatorTest { |
| |
| /** error tolerance for spline interpolator value at knot points */ |
| protected double knotTolerance = 1E-12; |
| |
| /** error tolerance for interpolating polynomial coefficients */ |
| protected double coefficientTolerance = 1E-6; |
| |
| /** error tolerance for interpolated values */ |
| protected double interpolationTolerance = 1E-12; |
| |
| @Test |
| public void testInterpolateLinearDegenerateTwoSegment() { |
| double x[] = {0.0, 0.5, 1.0}; |
| double y[] = { 0.0, 0.5, 1.0 }; |
| UnivariateInterpolator i = new LinearInterpolator(); |
| UnivariateFunction f = i.interpolate(x, y); |
| verifyInterpolation(f, x, y); |
| |
| // Verify coefficients using analytical values |
| PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials(); |
| double target[] = {y[0], 1d}; |
| TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance); |
| target = new double[]{y[1], 1d}; |
| TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance); |
| |
| // Check interpolation |
| Assert.assertEquals(0.0,f.value(0.0), interpolationTolerance); |
| Assert.assertEquals(0.4,f.value(0.4), interpolationTolerance); |
| Assert.assertEquals(1.0,f.value(1.0), interpolationTolerance); |
| } |
| |
| @Test |
| public void testInterpolateLinearDegenerateThreeSegment() { |
| double x[] = {0.0, 0.5, 1.0, 1.5}; |
| double y[] = { 0.0, 0.5, 1.0, 1.5 }; |
| UnivariateInterpolator i = new LinearInterpolator(); |
| UnivariateFunction f = i.interpolate(x, y); |
| verifyInterpolation(f, x, y); |
| |
| // Verify coefficients using analytical values |
| PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials(); |
| double target[] = {y[0], 1d}; |
| TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance); |
| target = new double[]{y[1], 1d}; |
| TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance); |
| target = new double[]{y[2], 1d}; |
| TestUtils.assertEquals(polynomials[2].getCoefficients(), target, coefficientTolerance); |
| |
| // Check interpolation |
| Assert.assertEquals(0,f.value(0), interpolationTolerance); |
| Assert.assertEquals(1.4,f.value(1.4), interpolationTolerance); |
| Assert.assertEquals(1.5,f.value(1.5), interpolationTolerance); |
| } |
| |
| @Test |
| public void testInterpolateLinear() { |
| double x[] = { 0.0, 0.5, 1.0 }; |
| double y[] = { 0.0, 0.5, 0.0 }; |
| UnivariateInterpolator i = new LinearInterpolator(); |
| UnivariateFunction f = i.interpolate(x, y); |
| verifyInterpolation(f, x, y); |
| |
| // Verify coefficients using analytical values |
| PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials(); |
| double target[] = {y[0], 1d}; |
| TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance); |
| target = new double[]{y[1], -1d}; |
| TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance); |
| } |
| |
| @Test |
| public void testIllegalArguments() { |
| // Data set arrays of different size. |
| UnivariateInterpolator i = new LinearInterpolator(); |
| try { |
| double xval[] = { 0.0, 1.0 }; |
| double yval[] = { 0.0, 1.0, 2.0 }; |
| i.interpolate(xval, yval); |
| Assert.fail("Failed to detect data set array with different sizes."); |
| } catch (DimensionMismatchException iae) { |
| // Expected. |
| } |
| // X values not sorted. |
| try { |
| double xval[] = { 0.0, 1.0, 0.5 }; |
| double yval[] = { 0.0, 1.0, 2.0 }; |
| i.interpolate(xval, yval); |
| Assert.fail("Failed to detect unsorted arguments."); |
| } catch (NonMonotonicSequenceException iae) { |
| // Expected. |
| } |
| // Not enough data to interpolate. |
| try { |
| double xval[] = { 0.0 }; |
| double yval[] = { 0.0 }; |
| i.interpolate(xval, yval); |
| Assert.fail("Failed to detect unsorted arguments."); |
| } catch (NumberIsTooSmallException iae) { |
| // Expected. |
| } |
| } |
| |
| /** |
| * verifies that f(x[i]) = y[i] for i = 0..n-1 where n is common length. |
| */ |
| protected void verifyInterpolation(UnivariateFunction f, double x[], double y[]) { |
| for (int i = 0; i < x.length; i++) { |
| Assert.assertEquals(f.value(x[i]), y[i], knotTolerance); |
| } |
| } |
| } |