Changeset 11914 for trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting

Timestamp:

02/05/15 16:09:10 (10 years ago)

Author:

ascheibe

Message:

#2031 implemented review comments

Location:

trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting

Files:

• . (added)
• ExpFitting.cs (moved) (moved from trunk/sources/HeuristicLab.Analysis/3.3/Statistics/ExpFitting.cs) (4 diffs)
• IFitting.cs (moved) (moved from trunk/sources/HeuristicLab.Analysis/3.3/Statistics/IFitting.cs) (1 diff)
• LinearLeastSquaresFitting.cs (moved) (moved from trunk/sources/HeuristicLab.Analysis/3.3/Statistics/LinearLeastSquaresFitting.cs) (4 diffs)
• LogFitting.cs (moved) (moved from trunk/sources/HeuristicLab.Analysis/3.3/Statistics/LogFitting.cs) (2 diffs)

trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting/ExpFitting.cs

@@ -25 +25 @@
 namespace HeuristicLab.Analysis.Statistics {
   public class ExpFitting : IFitting {
-    private void LogFunc(double[] c, double[] x, ref double func, object obj) {
+    private void ExpFunc(double[] c, double[] x, ref double func, object obj) {
       func = Math.Exp(-c[0] * Math.Pow(x[0], 2));
     }
@@ -34 +34 @@
     }
 
-    public void Calculate(double[] dataPoints, out double p0, out double p1) {
+    public void Calculate(double[] dataPoints, out double p0) {
       var stdX = GetDefaultXValues(dataPoints.Count());
-      Calculate(dataPoints, stdX, out p0, out p1);
+      Calculate(dataPoints, stdX, out p0);
     }
 
-    public void Calculate(double[] y, double[] x, out double p0, out double p1) {
+    public void Calculate(double[] y, double[] x, out double p0) {
       if (y.Count() != x.Count()) {
         throw new ArgumentException("The lenght of x and y needs do be equal. ");
@@ -60 +60 @@
       alglib.lsfitcreatef(xx, y, c, diffstep, out state);
       alglib.lsfitsetcond(state, epsf, epsx, maxits);
-      alglib.lsfitfit(state, LogFunc, null, null);
+      alglib.lsfitfit(state, ExpFunc, null, null);
       alglib.lsfitresults(state, out info, out c, out rep);
 
       p0 = c[0];
-      p1 = c[0];
     }
 
-    public DataRow CalculateFittedLine(double[] dataPoints, string rowName) {
-      DataRow newRow = new DataRow(rowName);
-      double c0, c1;
-      Calculate(dataPoints, out c0, out c1);
+    public DataRow CalculateFittedLine(double[] dataPoints) {
+      DataRow newRow = new DataRow();
+      double c0;
+      Calculate(dataPoints, out c0);
       var stdX = GetDefaultXValues(dataPoints.Count());
 
@@ -80 +79 @@
     }
 
-    public DataRow CalculateFittedLine(double[] y, double[] x, string rowName) {
-      DataRow newRow = new DataRow(rowName);
-      double c0, c1;
-      Calculate(y, x, out c0, out c1);
+    public DataRow CalculateFittedLine(double[] y, double[] x) {
+      DataRow newRow = new DataRow();
+      double c0;
+      Calculate(y, x, out c0);
 
       for (int i = 0; i < x.Count(); i++) {

trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting/IFitting.cs

@@ -22 +22 @@
 namespace HeuristicLab.Analysis.Statistics {
   public interface IFitting {
-    void Calculate(double[] dataPoints, out double p0, out double p1);
-    void Calculate(double[] y, double[] x, out double p0, out double p1);
-
-    DataRow CalculateFittedLine(double[] dataPoints, string rowName);
-    DataRow CalculateFittedLine(double[] y, double[] x, string rowName);
+    DataRow CalculateFittedLine(double[] dataPoints);
+    DataRow CalculateFittedLine(double[] y, double[] x);
   }
 }

trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting/LinearLeastSquaresFitting.cs

@@ -25 +25 @@
 namespace HeuristicLab.Analysis.Statistics {
   public class LinearLeastSquaresFitting : IFitting {
-    public void Calculate(double[] dataPoints, out double p0, out double p1) {
+    public void Calculate(double[] dataPoints, out double slope, out double intercept) {
       var stdX = Enumerable.Range(0, dataPoints.Count()).Select(x => (double)x).ToArray();
-      Calculate(dataPoints, stdX, out p0, out p1);
+      Calculate(dataPoints, stdX, out slope, out intercept);
     }
 
-    public void Calculate(double[] y, double[] x, out double p0, out double p1) {
+    public void Calculate(double[] y, double[] x, out double slope, out double intercept) {
       if (y.Count() != x.Count()) {
         throw new ArgumentException("The lenght of x and y needs do be equal. ");
@@ -48 +48 @@
       }
 
-      p0 = (sxy - (n * avgx * avgy)) / (sxx - (n * avgx * avgx));
-      p1 = avgy - p0 * avgx;
+      slope = (sxy - (n * avgx * avgy)) / (sxx - (n * avgx * avgx));
+      intercept = avgy - slope * avgx;
     }
 
-    public double CalculateError(double[] dataPoints, double p0, double p1) {
+    public double CalculateError(double[] dataPoints, double slope, double intercept) {
       double r;
       double avgy = dataPoints.Average();
@@ -59 +59 @@
 
       for (int i = 0; i < dataPoints.Count(); i++) {
-        double y = p0 * i + p1;
+        double y = slope * i + intercept;
         sstot += Math.Pow(dataPoints[i] - avgy, 2);
         sserr += Math.Pow(dataPoints[i] - y, 2);
@@ -68 +68 @@
     }
 
-    public DataRow CalculateFittedLine(double[] y, double[] x, string rowName) {
-      double k, d;
-      Calculate(y, x, out k, out d);
+    public DataRow CalculateFittedLine(double[] y, double[] x) {
+      double slope, intercept;
+      Calculate(y, x, out slope, out intercept);
 
-      DataRow newRow = new DataRow(rowName);
+      DataRow newRow = new DataRow();
       for (int i = 0; i < x.Count(); i++) {
-        newRow.Values.Add(k * x[i] + d);
+        newRow.Values.Add(slope * x[i] + intercept);
       }
       return newRow;
     }
 
-    public DataRow CalculateFittedLine(double[] dataPoints, string rowName) {
-      DataRow newRow = new DataRow(rowName);
-      double c0, c1;
-      Calculate(dataPoints, out c0, out c1);
+    public DataRow CalculateFittedLine(double[] dataPoints) {
+      DataRow newRow = new DataRow();
+      double slope, intercept;
+      Calculate(dataPoints, out slope, out intercept);
       var stdX = Enumerable.Range(0, dataPoints.Count()).Select(x => (double)x).ToArray();
 
       for (int i = 0; i < stdX.Count(); i++) {
-        newRow.Values.Add(c0 * stdX[i] + c1);
+        newRow.Values.Add(slope * stdX[i] + intercept);
       }
 

trunk/sources/HeuristicLab.Analysis/3.3/Statistics/Fitting/LogFitting.cs

@@ -67 +67 @@
     }
 
-    public DataRow CalculateFittedLine(double[] dataPoints, string rowName) {
-      DataRow newRow = new DataRow(rowName);
+    public DataRow CalculateFittedLine(double[] dataPoints) {
+      DataRow newRow = new DataRow();
       double c0, c1;
       Calculate(dataPoints, out c0, out c1);
@@ -80 +80 @@
     }
 
-    public DataRow CalculateFittedLine(double[] y, double[] x, string rowName) {
-      DataRow newRow = new DataRow(rowName);
+    public DataRow CalculateFittedLine(double[] y, double[] x) {
+      DataRow newRow = new DataRow();
       double c0, c1;
       Calculate(y, x, out c0, out c1);