private static void RandomizeConstantRegion(int[] o, int startInd, int endInd)
 {
     int len = endInd - startInd;
     Random2 r = new Random2();
     int[] p = r.NextPermutation(len);
     int[] permuted = new int[len];
     for (int i = 0; i < len; i++){
         permuted[i] = o[startInd + p[i]];
     }
     Array.Copy(permuted, 0, o, startInd, len);
 }
 private static void ReplaceMissingsByGaussianForOneColumn(double width, double shift, IMatrixData data, int colInd)
 {
     List<float> allValues = new List<float>();
     for (int i = 0; i < data.RowCount; i++){
         float x = data[i, colInd];
         if (!float.IsNaN(x) && !float.IsInfinity(x)){
             allValues.Add(x);
         }
     }
     double stddev;
     double mean = ArrayUtils.MeanAndStddev(allValues.ToArray(), out stddev);
     double m = mean - shift*stddev;
     double s = stddev*width;
     Random2 r = new Random2();
     for (int i = 0; i < data.RowCount; i++){
         if (float.IsNaN(data[i, colInd]) || float.IsInfinity(data[i, colInd])){
             data[i, colInd] = (float) r.NextGaussian(m, s);
             data.IsImputed[i, colInd] = true;
         }
     }
 }
Beispiel #3
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        public void ProcessData(IMatrixData mdata, Parameters param, ref IMatrixData[] supplTables,
			ref IDocumentData[] documents, ProcessInfo processInfo)
        {
            Random2 rand = new Random2();
            double std = param.GetDoubleParam("Standard deviation").Value;
            for (int i = 0; i < mdata.RowCount; i++){
                for (int j = 0; j < mdata.ExpressionColumnCount; j++){
                    mdata[i, j] += (float) rand.NextGaussian(0, std);
                }
            }
        }
 public static void ReplaceMissingsByGaussianWholeMatrix(double width, double shift, IMatrixData data)
 {
     int[] colInds = ArrayUtils.ConsecutiveInts(data.ExpressionColumnCount);
     List<float> allValues = new List<float>();
     for (int i = 0; i < data.RowCount; i++){
         foreach (int t in colInds){
             float x = data[i, t];
             if (!float.IsNaN(x) && !float.IsInfinity(x)){
                 allValues.Add(x);
             }
         }
     }
     double stddev;
     double mean = ArrayUtils.MeanAndStddev(allValues.ToArray(), out stddev);
     double m = mean - shift*stddev;
     double s = stddev*width;
     Random2 r = new Random2();
     for (int i = 0; i < data.RowCount; i++){
         foreach (int t in colInds){
             if (float.IsNaN(data[i, t]) || float.IsInfinity(data[i, t])){
                 data[i, t] = (float) r.NextGaussian(m, s);
                 data.IsImputed[i, t] = true;
             }
         }
     }
 }
        public void ProcessData(IMatrixData mdata, Parameters param, ref IMatrixData[] supplTables,
			ref IDocumentData[] documents, ProcessInfo processInfo)
        {
            int nrows = param.GetIntParam("Number of rows").Value;
            nrows = Math.Min(nrows, mdata.RowCount);
            Random2 rand = new Random2();
            int[] rows = ArrayUtils.SubArray(rand.NextPermutation(mdata.RowCount), nrows);
            PerseusPluginUtils.FilterRows(mdata, param, rows);
        }