/*
    * 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.fitting.leastsquares;
  
  import org.apache.commons.numbers.core.Precision;
  import org.apache.commons.geometry.euclidean.threed.Plane;
  import org.apache.commons.geometry.euclidean.threed.Planes;
  import org.apache.commons.geometry.euclidean.threed.Vector3D;
  import org.apache.commons.math4.legacy.exception.ConvergenceException;
  import org.apache.commons.math4.legacy.exception.TooManyEvaluationsException;
  import org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition;
  import org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresOptimizer.Optimum;
  import org.apache.commons.math4.legacy.optim.SimpleVectorValueChecker;
  import org.apache.commons.math4.core.jdkmath.JdkMath;
  import org.junit.Assert;
  import org.junit.Test;
  
  import java.io.IOException;
  
  /**
   * <p>Some of the unit tests are re-implementations of the MINPACK <a
   * href="http://www.netlib.org/minpack/ex/file17">file17</a> and <a
   * href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
   * The redistribution policy for MINPACK is available <a
   * href="http://www.netlib.org/minpack/disclaimer">here</a>/
   *
   */
  public class GaussNewtonOptimizerWithSVDTest
      extends AbstractLeastSquaresOptimizerAbstractTest {
  
      @Override
      public int getMaxIterations() {
          return 1000;
      }
  
      @Override
      public LeastSquaresOptimizer getOptimizer() {
          return new GaussNewtonOptimizer(Decomposition.SVD);
      }
  
      @Test
      public void testMaxEvaluations() throws Exception {
          try{
          CircleVectorial circle = new CircleVectorial();
          circle.addPoint( 30.0,  68.0);
          circle.addPoint( 50.0,  -6.0);
          circle.addPoint(110.0, -20.0);
          circle.addPoint( 35.0,  15.0);
          circle.addPoint( 45.0,  97.0);
  
          LeastSquaresProblem lsp = builder(circle)
                  .checkerPair(new SimpleVectorValueChecker(1e-30, 1e-30))
                  .maxIterations(Integer.MAX_VALUE)
                  .start(new double[]{98.680, 47.345})
                  .build();
  
          optimizer.optimize(lsp);
  
              fail(optimizer);
          }catch (TooManyEvaluationsException e){
              //expected
          }
      }
  
      @Override
      @Test
      public void testCircleFittingBadInit() {
          /*
           * This test converged to the wrong solution with this optimizer.
           * It seems that the state becomes so large that the convergence
           * checker's relative tolerance test passes.
           */
          try {
              super.testCircleFittingBadInit();
              fail(optimizer);
          } catch (AssertionError e) {
              //expected
          }
      }
  
      @Override
      @Test
      public void testHahn1()
          throws IOException {
         /*
          * TODO This test leads to a singular problem with the Gauss-Newton
          * optimizer. This should be inquired.
          */
         try{
             super.testHahn1();
             fail(optimizer);
         } catch (ConvergenceException e){
             //expected for LU
         } catch (TooManyEvaluationsException e){
             //expected for QR
         }
     }
 
     @Test
     @Override
     public void testGetIterations() {
         /* this diverges with SVD */
         try {
             super.testGetIterations();
             fail(optimizer);
         } catch (TooManyEvaluationsException e) {
             //expected
         }
     }
 
     @Test
     @Override
     public void testNonInvertible() throws Exception {
         /*  SVD can compute a solution to singular problems.
          *  In this case the target vector, b, is not in the
          *  span of the jacobian matrix, A. The closes point
          *  to b on the plane spanned by A is computed.
          */
         LinearProblem problem = new LinearProblem(new double[][]{
                 {1, 2, -3},
                 {2, 1, 3},
                 {-3, 0, -9}
         }, new double[]{1, 1, 1});
 
         Optimum optimum = optimizer.optimize(problem.getBuilder().build());
 
         Plane span = Planes.fromPoints(Vector3D.ZERO, Vector3D.of(1, 2, -3), Vector3D.of(2, 1, 0),
                                        Precision.doubleEquivalenceOfEpsilon(TOL));
         double expected = JdkMath.abs(span.offset(Vector3D.of(1, 1, 1)));
         double actual = optimum.getResiduals().getNorm();
 
         //verify
         Assert.assertEquals(expected, actual, TOL);
     }
 }