[8401] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16057] | 3 | * Copyright (C) 2002-2018 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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| 25 |
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[8371] | 26 | namespace HeuristicLab.Algorithms.DataAnalysis {
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[8612] | 27 | internal static class Util {
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[13721] | 28 | public static double ScalarProd(double[] v, double[] u) {
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| 29 | if (v.Length != u.Length) throw new InvalidOperationException();
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| 30 | double prod = 0.0;
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| 31 | for (int i = 0; i < v.Length; i++)
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| 32 | prod += v[i] * u[i];
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| 33 | return prod;
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[8323] | 34 | }
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| 35 |
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[8562] | 36 | public static double SqrDist(IEnumerable<double> x, IEnumerable<double> y) {
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| 37 | return x.Zip(y, (a, b) => (a - b) * (a - b)).Sum();
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| 38 | }
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| 39 |
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[8323] | 40 | public static double SqrDist(double x, double y) {
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| 41 | double d = x - y;
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[8463] | 42 | return d * d;
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[8323] | 43 | }
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| 44 |
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[13721] | 45 | public static double SqrDist(double[,] x, int i, int j, int[] columnIndices, double scale = 1.0) {
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| 46 | return SqrDist(x, i, x, j, columnIndices, scale);
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[8491] | 47 | }
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| 48 |
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[13721] | 49 | public static double SqrDist(double[,] x, int i, double[,] xt, int j, int[] columnIndices, double scale = 1.0) {
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[8491] | 50 | double ss = 0.0;
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[13721] | 51 | if (columnIndices == null) columnIndices = Enumerable.Range(0, x.GetLength(1)).ToArray();
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| 52 | for (int c = 0; c < columnIndices.Length; c++) {
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| 53 | var columnIndex = columnIndices[c];
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[8933] | 54 | double d = x[i, columnIndex] - xt[j, columnIndex];
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[8491] | 55 | ss += d * d;
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| 56 | }
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| 57 | return scale * scale * ss;
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| 58 | }
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[8562] | 59 |
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[13721] | 60 | public static double SqrDist(double[,] x, int i, int j, double[] scale, int[] columnIndices) {
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[8827] | 61 | return SqrDist(x, i, x, j, scale, columnIndices);
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[8491] | 62 | }
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| 63 |
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[13721] | 64 | public static double SqrDist(double[,] x, int i, double[,] xt, int j, double[] scale, int[] columnIndices) {
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[8491] | 65 | double ss = 0.0;
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[8827] | 66 | int scaleIndex = 0;
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[13721] | 67 | for (int c = 0; c < columnIndices.Length; c++) {
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| 68 | var columnIndex = columnIndices[c];
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[8933] | 69 | double d = x[i, columnIndex] - xt[j, columnIndex];
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[8827] | 70 | ss += d * d * scale[scaleIndex] * scale[scaleIndex];
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| 71 | scaleIndex++;
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[8491] | 72 | }
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[8933] | 73 | // must be at the end of scale after iterating over columnIndices
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| 74 | if (scaleIndex != scale.Length)
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| 75 | throw new ArgumentException("Lengths of scales and covariance functions does not match.");
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[8491] | 76 | return ss;
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| 77 | }
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[13721] | 78 | public static double ScalarProd(double[,] x, int i, int j, int[] columnIndices, double scale = 1.0) {
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| 79 | return ScalarProd(x, i, x, j, columnIndices, scale);
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[8562] | 80 | }
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[8491] | 81 |
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[13721] | 82 | public static double ScalarProd(double[,] x, int i, double[,] xt, int j, int[] columnIndices, double scale = 1.0) {
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[8562] | 83 | double sum = 0.0;
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[13721] | 84 | for (int c = 0; c < columnIndices.Length; c++) {
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| 85 | var columnIndex = columnIndices[c];
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[8933] | 86 | sum += x[i, columnIndex] * xt[j, columnIndex];
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[8562] | 87 | }
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| 88 | return scale * scale * sum;
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| 89 | }
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[13721] | 90 | public static double ScalarProd(double[,] x, int i, int j, double[] scale, int[] columnIndices) {
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[8678] | 91 | return ScalarProd(x, i, x, j, scale, columnIndices);
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[8562] | 92 | }
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| 93 |
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[13721] | 94 | public static double ScalarProd(double[,] x, int i, double[,] xt, int j, double[] scale, int[] columnIndices) {
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[8562] | 95 | double sum = 0.0;
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[8827] | 96 | int scaleIndex = 0;
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[13721] | 97 | for (int c = 0; c < columnIndices.Length; c++, scaleIndex++) {
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| 98 | var columnIndex = columnIndices[c];
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[8933] | 99 | sum += x[i, columnIndex] * scale[scaleIndex] * xt[j, columnIndex] * scale[scaleIndex];
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[8562] | 100 | }
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[8933] | 101 | // must be at the end of scale after iterating over columnIndices
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| 102 | if (scaleIndex != scale.Length)
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| 103 | throw new ArgumentException("Lengths of scales and covariance functions does not match.");
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| 104 |
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[8562] | 105 | return sum;
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| 106 | }
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| 107 |
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[8323] | 108 | public static IEnumerable<double> GetRow(double[,] x, int r) {
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| 109 | int cols = x.GetLength(1);
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[8982] | 110 | return GetRow(x, r, Enumerable.Range(0, cols));
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[8323] | 111 | }
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[8982] | 112 | public static IEnumerable<double> GetRow(double[,] x, int r, IEnumerable<int> columnIndices) {
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| 113 | return columnIndices.Select(c => x[r, c]);
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| 114 | }
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[8366] | 115 | public static IEnumerable<double> GetCol(double[,] x, int c) {
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| 116 | int rows = x.GetLength(0);
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| 117 | return Enumerable.Range(0, rows).Select(r => x[r, c]);
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| 118 | }
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[8323] | 119 | }
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| 120 | }
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