/*
    * 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
    *
    *      https://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.
   */
  
  /*
   * This is not the original file distributed by the Apache Software Foundation
   * It has been modified by the Hipparchus project
   */
  package org.hipparchus.optim.nonlinear.vector.leastsquares;
  
  import java.io.BufferedReader;
  import java.io.IOException;
  import java.io.InputStream;
  import java.io.InputStreamReader;
  
  import org.hipparchus.util.FastMath;
  
  /**
   * A factory to create instances of {@link StatisticalReferenceDataset} from
   * available resources.
   */
  public class StatisticalReferenceDatasetFactory {
  
      private StatisticalReferenceDatasetFactory() {
          // Do nothing
      }
  
      /**
       * Creates a new buffered reader from the specified resource name.
       *
       * @param name the name of the resource
       * @return a buffered reader
       * @throws IOException if an I/O error occured
       */
      public static BufferedReader createBufferedReaderFromResource(final String name)
          throws IOException {
          final InputStream resourceAsStream;
          resourceAsStream = StatisticalReferenceDatasetFactory.class
              .getResourceAsStream(name);
          if (resourceAsStream == null) {
              throw new IOException("could not find resource " + name);
          }
          return new BufferedReader(new InputStreamReader(resourceAsStream));
      }
  
      public static StatisticalReferenceDataset createKirby2()
          throws IOException {
          final BufferedReader in = createBufferedReaderFromResource("Kirby2.dat");
          StatisticalReferenceDataset dataset = null;
          try {
              dataset = new StatisticalReferenceDataset(in) {
  
                  @Override
                  public double getModelValue(final double x, final double[] a) {
                      final double p = a[0] + x * (a[1] + x * a[2]);
                      final double q = 1.0 + x * (a[3] + x * a[4]);
                      return p / q;
                  }
  
                  @Override
                  public double[] getModelDerivatives(final double x,
                                                      final double[] a) {
                      final double[] dy = new double[5];
                      final double p = a[0] + x * (a[1] + x * a[2]);
                      final double q = 1.0 + x * (a[3] + x * a[4]);
                      dy[0] = 1.0 / q;
                      dy[1] = x / q;
                      dy[2] = x * dy[1];
                      dy[3] = -x * p / (q * q);
                      dy[4] = x * dy[3];
                      return dy;
                  }
              };
          } finally {
              in.close();
          }
          return dataset;
      }
  
      public static StatisticalReferenceDataset createHahn1()
          throws IOException {
          final BufferedReader in = createBufferedReaderFromResource("Hahn1.dat");
          StatisticalReferenceDataset dataset = null;
          try {
              dataset = new StatisticalReferenceDataset(in) {
  
                 @Override
                 public double getModelValue(final double x, final double[] a) {
                     final double p = a[0] + x * (a[1] + x * (a[2] + x * a[3]));
                     final double q = 1.0 + x * (a[4] + x * (a[5] + x * a[6]));
                     return p / q;
                 }
 
                 @Override
                 public double[] getModelDerivatives(final double x,
                                                     final double[] a) {
                     final double[] dy = new double[7];
                     final double p = a[0] + x * (a[1] + x * (a[2] + x * a[3]));
                     final double q = 1.0 + x * (a[4] + x * (a[5] + x * a[6]));
                     dy[0] = 1.0 / q;
                     dy[1] = x * dy[0];
                     dy[2] = x * dy[1];
                     dy[3] = x * dy[2];
                     dy[4] = -x * p / (q * q);
                     dy[5] = x * dy[4];
                     dy[6] = x * dy[5];
                     return dy;
                 }
             };
         } finally {
             in.close();
         }
         return dataset;
     }
 
     public static StatisticalReferenceDataset createMGH17()
         throws IOException {
         final BufferedReader in = createBufferedReaderFromResource("MGH17.dat");
         StatisticalReferenceDataset dataset = null;
         try {
             dataset = new StatisticalReferenceDataset(in) {
 
                 @Override
                 public double getModelValue(final double x, final double[] a) {
                     return a[0] + a[1] * FastMath.exp(-a[3] * x) + a[2] *
                            FastMath.exp(-a[4] * x);
                 }
 
                 @Override
                 public double[] getModelDerivatives(final double x,
                                                     final double[] a) {
                     final double[] dy = new double[5];
                     dy[0] = 1.0;
                     dy[1] = FastMath.exp(-x * a[3]);
                     dy[2] = FastMath.exp(-x * a[4]);
                     dy[3] = -x * a[1] * dy[1];
                     dy[4] = -x * a[2] * dy[2];
                     return dy;
                 }
             };
         } finally {
             in.close();
         }
         return dataset;
     }
 
     public static StatisticalReferenceDataset createLanczos1()
         throws IOException {
         final BufferedReader in =
             createBufferedReaderFromResource("Lanczos1.dat");
         StatisticalReferenceDataset dataset = null;
         try {
             dataset = new StatisticalReferenceDataset(in) {
 
                 @Override
                 public double getModelValue(final double x, final double[] a) {
                     System.out.println(a[0]+", "+a[1]+", "+a[2]+", "+a[3]+", "+a[4]+", "+a[5]);
                     return a[0] * FastMath.exp(-a[3] * x) +
                            a[1] * FastMath.exp(-a[4] * x) +
                            a[2] * FastMath.exp(-a[5] * x);
                 }
 
                 @Override
                 public double[] getModelDerivatives(final double x,
                     final double[] a) {
                     final double[] dy = new double[6];
                     dy[0] = FastMath.exp(-x * a[3]);
                     dy[1] = FastMath.exp(-x * a[4]);
                     dy[2] = FastMath.exp(-x * a[5]);
                     dy[3] = -x * a[0] * dy[0];
                     dy[4] = -x * a[1] * dy[1];
                     dy[5] = -x * a[2] * dy[2];
                     return dy;
                 }
             };
         } finally {
             in.close();
         }
         return dataset;
     }
 
     /**
      * Returns an array with all available reference datasets.
      *
      * @return the array of datasets
      * @throws IOException if an I/O error occurs
      */
     public StatisticalReferenceDataset[] createAll()
         throws IOException {
         return new StatisticalReferenceDataset[] {
             createKirby2(), createMGH17()
         };
     }
 }