1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21 


22  using System;


23  using System.Collections.Generic;


24  using System.Linq;


25  using HeuristicLab.Core;


26  using HeuristicLab.Data;


27 


28  namespace HeuristicLab.Algorithms.DataAnalysis {


29  internal static class Util {


30  public static double ScalarProd(IEnumerable<double> v, IEnumerable<double> u) {


31  return v.Zip(u, (vi, ui) => vi * ui).Sum();


32  }


33 


34  public static double SqrDist(IEnumerable<double> x, IEnumerable<double> y) {


35  return x.Zip(y, (a, b) => (a  b) * (a  b)).Sum();


36  }


37 


38  public static double SqrDist(double x, double y) {


39  double d = x  y;


40  return d * d;


41  }


42 


43  public static double SqrDist(double[,] x, int i, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {


44  return SqrDist(x, i, x, j, scale, columnIndices);


45  }


46 


47  public static double SqrDist(double[,] x, int i, double[,] xt, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {


48  double ss = 0.0;


49  if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));


50  foreach (int columnIndex in columnIndices) {


51  double d = x[i, columnIndex]  xt[j, columnIndex];


52  ss += d * d;


53  }


54  return scale * scale * ss;


55  }


56 


57  public static double SqrDist(double[,] x, int i, int j, double[] scale, IEnumerable<int> columnIndices = null) {


58  return SqrDist(x, i, x, j, scale, columnIndices);


59  }


60 


61  public static double SqrDist(double[,] x, int i, double[,] xt, int j, double[] scale, IEnumerable<int> columnIndices = null) {


62  double ss = 0.0;


63  if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));


64  int scaleIndex = 0;


65  foreach (int columnIndex in columnIndices) {


66  double d = x[i, columnIndex]  xt[j, columnIndex];


67  ss += d * d * scale[scaleIndex] * scale[scaleIndex];


68  scaleIndex++;


69  }


70  // must be at the end of scale after iterating over columnIndices


71  if (scaleIndex != scale.Length)


72  throw new ArgumentException("Lengths of scales and covariance functions does not match.");


73  return ss;


74  }


75  public static double ScalarProd(double[,] x, int i, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {


76  return ScalarProd(x, i, x, j, scale, columnIndices);


77  }


78 


79  public static double ScalarProd(double[,] x, int i, double[,] xt, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {


80  double sum = 0.0;


81  if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));


82  foreach (int columnIndex in columnIndices) {


83  sum += x[i, columnIndex] * xt[j, columnIndex];


84  }


85  return scale * scale * sum;


86  }


87  public static double ScalarProd(double[,] x, int i, int j, double[] scale, IEnumerable<int> columnIndices = null) {


88  return ScalarProd(x, i, x, j, scale, columnIndices);


89  }


90 


91  public static double ScalarProd(double[,] x, int i, double[,] xt, int j, double[] scale, IEnumerable<int> columnIndices = null) {


92  double sum = 0.0;


93  if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));


94  int scaleIndex = 0;


95  foreach (int columnIndex in columnIndices) {


96  sum += x[i, columnIndex] * scale[scaleIndex] * xt[j, columnIndex] * scale[scaleIndex];


97  scaleIndex++;


98  }


99  // must be at the end of scale after iterating over columnIndices


100  if (scaleIndex != scale.Length)


101  throw new ArgumentException("Lengths of scales and covariance functions does not match.");


102 


103  return sum;


104  }


105 


106  public static IEnumerable<double> GetRow(double[,] x, int r) {


107  int cols = x.GetLength(1);


108  return GetRow(x, r, Enumerable.Range(0, cols));


109  }


110  public static IEnumerable<double> GetRow(double[,] x, int r, IEnumerable<int> columnIndices) {


111  return columnIndices.Select(c => x[r, c]);


112  }


113  public static IEnumerable<double> GetCol(double[,] x, int c) {


114  int rows = x.GetLength(0);


115  return Enumerable.Range(0, rows).Select(r => x[r, c]);


116  }


117  }


118  }

