/*
    * 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.analysis.BivariateFunction;
  import org.apache.commons.statistics.distribution.ContinuousDistribution;
  import org.apache.commons.statistics.distribution.UniformContinuousDistribution;
  import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
  import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
  import org.apache.commons.rng.UniformRandomProvider;
  import org.apache.commons.rng.simple.RandomSource;
  import org.junit.Assert;
  import org.junit.Test;
  
  /**
   * Test case for the bicubic interpolator.
   */
  public final class BicubicInterpolatorTest {
      /**
       * 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 BicubicInterpolator();
  
          @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 testPlane() {
          BivariateFunction f = new BivariateFunction() {
                  @Override
                  public double value(double x, double y) {
                      return 2 * x - 3 * y + 5;
                  }
              };
  
          testInterpolation(3000,
                            1e-13,
                            f,
                            false);
      }
  
      /**
      * Interpolating a paraboloid.
      * <p>
      * z = 2 x<sup>2</sup> - 3 y<sup>2</sup> + 4 x y - 5
      */
     @Test
     public void testParaboloid() {
         BivariateFunction f = new BivariateFunction() {
                 @Override
                 public double value(double x, double y) {
                     return 2 * x * x - 3 * y * y + 4 * x * y - 5;
                 }
             };
 
         testInterpolation(3000,
                           1e-12,
                           f,
                           false);
     }
 
     /**
      * @param numSamples Number of test samples.
      * @param tolerance Allowed tolerance on the interpolated value.
      * @param f Test function.
      * @param print Whether to print debugging output to the console.
      */
     private void testInterpolation(int numSamples,
                                    double tolerance,
                                    BivariateFunction f,
                                    boolean print) {
         final int sz = 21;
         final double[] xval = new double[sz];
         final 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;
         }
 
         final 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]);
             }
         }
 
         final BicubicInterpolator interpolator = new BicubicInterpolator();
         final BicubicInterpolatingFunction p = interpolator.interpolate(xval, yval, zval);
 
         final UniformRandomProvider rng = RandomSource.WELL_19937_C.create();
         final ContinuousDistribution.Sampler distX = UniformContinuousDistribution.of(xval[0], xval[xval.length - 1]).createSampler(rng);
         final ContinuousDistribution.Sampler distY = UniformContinuousDistribution.of(yval[0], yval[yval.length - 1]).createSampler(rng);
 
         int count = 0;
         while (true) {
             double x = distX.sample();
             double y = distY.sample();
             if (!p.isValidPoint(x, y)) {
                 if (print) {
                     System.out.println("# " + x + " " + y);
                 }
                 continue;
             }
 
             if (count++ > numSamples) {
                 break;
             }
             final double expected = f.value(x, y);
             final double actual = p.value(x, y);
 
             if (print) {
                 System.out.println(x + " " + y + " " + expected + " " + actual);
             }
 
             Assert.assertEquals(expected, actual, tolerance);
         }
     }
 }