/*
    * 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);
         }
     }
 }