[8401] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11171] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8401] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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[8323] | 21 |
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[8612] | 22 | using System;
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[8323] | 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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[8612] | 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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[8323] | 27 |
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[8371] | 28 | namespace HeuristicLab.Algorithms.DataAnalysis {
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[8612] | 29 | internal static class Util {
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[8323] | 30 | public static double ScalarProd(IEnumerable<double> v, IEnumerable<double> u) {
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| 31 | return v.Zip(u, (vi, ui) => vi * ui).Sum();
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| 32 | }
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| 33 |
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[8562] | 34 | public static double SqrDist(IEnumerable<double> x, IEnumerable<double> y) {
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| 35 | return x.Zip(y, (a, b) => (a - b) * (a - b)).Sum();
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| 36 | }
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| 37 |
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[8323] | 38 | public static double SqrDist(double x, double y) {
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| 39 | double d = x - y;
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[8463] | 40 | return d * d;
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[8323] | 41 | }
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| 42 |
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[8678] | 43 | public static double SqrDist(double[,] x, int i, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {
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| 44 | return SqrDist(x, i, x, j, scale, columnIndices);
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[8491] | 45 | }
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| 46 |
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[8678] | 47 | public static double SqrDist(double[,] x, int i, double[,] xt, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {
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[8491] | 48 | double ss = 0.0;
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[8678] | 49 | if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));
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[8933] | 50 | foreach (int columnIndex in columnIndices) {
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| 51 | double d = x[i, columnIndex] - xt[j, columnIndex];
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[8491] | 52 | ss += d * d;
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| 53 | }
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| 54 | return scale * scale * ss;
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| 55 | }
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[8562] | 56 |
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[8678] | 57 | public static double SqrDist(double[,] x, int i, int j, double[] scale, IEnumerable<int> columnIndices = null) {
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[8827] | 58 | return SqrDist(x, i, x, j, scale, columnIndices);
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[8491] | 59 | }
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| 60 |
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[8678] | 61 | public static double SqrDist(double[,] x, int i, double[,] xt, int j, double[] scale, IEnumerable<int> columnIndices = null) {
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[8491] | 62 | double ss = 0.0;
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[8678] | 63 | if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));
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[8827] | 64 | int scaleIndex = 0;
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[8933] | 65 | foreach (int columnIndex in columnIndices) {
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| 66 | double d = x[i, columnIndex] - xt[j, columnIndex];
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[8827] | 67 | ss += d * d * scale[scaleIndex] * scale[scaleIndex];
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| 68 | scaleIndex++;
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[8491] | 69 | }
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[8933] | 70 | // must be at the end of scale after iterating over columnIndices
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| 71 | if (scaleIndex != scale.Length)
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| 72 | throw new ArgumentException("Lengths of scales and covariance functions does not match.");
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[8491] | 73 | return ss;
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| 74 | }
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[8678] | 75 | public static double ScalarProd(double[,] x, int i, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {
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| 76 | return ScalarProd(x, i, x, j, scale, columnIndices);
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[8562] | 77 | }
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[8491] | 78 |
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[8678] | 79 | public static double ScalarProd(double[,] x, int i, double[,] xt, int j, double scale = 1.0, IEnumerable<int> columnIndices = null) {
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[8562] | 80 | double sum = 0.0;
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[8678] | 81 | if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));
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[8933] | 82 | foreach (int columnIndex in columnIndices) {
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| 83 | sum += x[i, columnIndex] * xt[j, columnIndex];
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[8562] | 84 | }
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| 85 | return scale * scale * sum;
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| 86 | }
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[8678] | 87 | public static double ScalarProd(double[,] x, int i, int j, double[] scale, IEnumerable<int> columnIndices = null) {
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| 88 | return ScalarProd(x, i, x, j, scale, columnIndices);
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[8562] | 89 | }
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| 90 |
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[8678] | 91 | public static double ScalarProd(double[,] x, int i, double[,] xt, int j, double[] scale, IEnumerable<int> columnIndices = null) {
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[8562] | 92 | double sum = 0.0;
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[8678] | 93 | if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1));
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[8827] | 94 | int scaleIndex = 0;
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[8933] | 95 | foreach (int columnIndex in columnIndices) {
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| 96 | sum += x[i, columnIndex] * scale[scaleIndex] * xt[j, columnIndex] * scale[scaleIndex];
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[8827] | 97 | scaleIndex++;
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[8562] | 98 | }
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[8933] | 99 | // must be at the end of scale after iterating over columnIndices
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| 100 | if (scaleIndex != scale.Length)
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| 101 | throw new ArgumentException("Lengths of scales and covariance functions does not match.");
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| 102 |
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[8562] | 103 | return sum;
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| 104 | }
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| 105 |
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[8323] | 106 | public static IEnumerable<double> GetRow(double[,] x, int r) {
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| 107 | int cols = x.GetLength(1);
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[8982] | 108 | return GetRow(x, r, Enumerable.Range(0, cols));
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[8323] | 109 | }
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[8982] | 110 | public static IEnumerable<double> GetRow(double[,] x, int r, IEnumerable<int> columnIndices) {
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| 111 | return columnIndices.Select(c => x[r, c]);
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| 112 | }
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[8366] | 113 | public static IEnumerable<double> GetCol(double[,] x, int c) {
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| 114 | int rows = x.GetLength(0);
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| 115 | return Enumerable.Range(0, rows).Select(r => x[r, c]);
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| 116 | }
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[8323] | 117 | }
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| 118 | }
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