source: branches/3106_AnalyticContinuedFractionsRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/ContinuedFractionRegression/Transformation.cs @ 17984

Last change on this file since 17984 was 17984, checked in by gkronber, 2 months ago

#3106 updated implementation based on the reply by Moscato

File size: 3.1 KB
Line 
1using System;
2using HeuristicLab.Data;
3
4namespace HeuristicLab.Algorithms.DataAnalysis.ContinuedFractionRegression {
5  public class Transformation {
6
7    DoubleMatrix dataMatrix;
8
9    private double[] tempMinMax;
10    private double[] phiMinMax;
11    private double[] phipMinMax;
12
13    public Transformation(DoubleMatrix dataMatrix) {
14      this.dataMatrix = dataMatrix;
15      transform0();
16    }
17
18    private void transform0() { // care! change the other two transformations accordingly!
19      tempMinMax = findMinMax(0);
20      minMaxTransformation(this.dataMatrix, tempMinMax, 0);
21      log10Transformation(this.dataMatrix, 2);
22    }
23
24    public double[] transform0(double[] orig) {
25      double[] trans = new double[3];
26      trans[0] = minMaxTransformation(tempMinMax, orig[0]);
27      trans[1] = orig[1];
28      trans[2] = log10Transformation(orig[2]);
29
30      return trans;
31    }
32
33    public void useSameTransformation(DoubleMatrix dataMatrix) {
34      minMaxTransformation(dataMatrix, tempMinMax, 0);
35      log10Transformation(dataMatrix, 2);
36    }
37
38    //another transformation - not as good as i thougt
39    private void transform1() { // care! change retransformation accordingly!
40      tempMinMax = findMinMax(0);
41      minMaxTransformation(this.dataMatrix, this.tempMinMax, 0);
42      phiMinMax = findMinMax(1);
43      minMaxTransformation(this.dataMatrix, this.phiMinMax, 1);
44      log10Transformation(2); // no negativ values!
45      phipMinMax = findMinMax(2);
46      minMaxTransformation(this.dataMatrix, this.phipMinMax, 2); // Min and Max have to be different!
47    }
48
49    public double[] transform1(double[] orig) {
50      double[] trans = new double[3];
51      trans[0] = minMaxTransformation(tempMinMax, orig[0]);
52      trans[1] = minMaxTransformation(phiMinMax, orig[1]);
53      trans[2] = log10Transformation(orig[2]);
54      trans[2] = minMaxTransformation(phipMinMax, trans[2]);
55
56      return trans;
57    }
58    //
59
60    private double[] findMinMax(int column) {
61      // the first row has index 0
62      double[] MinMax = new double[2] { double.MaxValue, double.MinValue };
63      // find min and max in column
64      for (int i = 0; i < dataMatrix.Rows; i++) {
65        if (dataMatrix[i, column] < MinMax[0])
66          MinMax[0] = dataMatrix[i, column];
67        if (dataMatrix[i, column] > MinMax[1])
68          MinMax[1] = dataMatrix[i, column];
69      }
70      return MinMax;
71    }
72
73    private void minMaxTransformation(DoubleMatrix matrix, double[] minMax, int column) {
74      // transform all values in column
75      for (int i = 0; i < matrix.Rows; i++) {
76        matrix[i, column] = (matrix[i, column] - minMax[0]) / (minMax[1] - minMax[0]);
77      }
78    }
79
80    private double minMaxTransformation(double[] minMax, double x) {
81      return (x - minMax[0]) / (minMax[1] - minMax[0]);
82    }
83
84    private void log10Transformation(DoubleMatrix matrix, int column) {
85      // the first row has index 0
86      for (int i = 0; i < matrix.Rows; i++) {
87        matrix[i, column] = Math.Log10(matrix[i, column]);
88      }
89    }
90
91    private double log10Transformation(double x) {
92      return Math.Log10(x);
93    }
94  }
95
96}
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