Example #1
0
  public static Matrix2D Process(Matrix2D _mat, boolean removeNZRows) {

    MatrixDescriptor desc = _mat.getMatrixDescriptor();

    // Calculates the mean
    System.out.println("Calculating Mean and Standar Deviation");
    Matrix2D meanSDMat = RateOfMean.ColumnMeanAndStandardDeviation(_mat, removeNZRows);

    // Calculate the standard score
    Matrix2D standardScore = new Matrix2D(desc);
    int numColumns = desc.getNumCols();

    for (int column = 0; column < numColumns; column++) {
      System.out.println("Processing column " + column + " of " + numColumns);
      float _mean = meanSDMat.GetElement(RateOfMean.Mean, desc.getColumnAt(column));
      float _sd = meanSDMat.GetElement(RateOfMean.StandardDeviation, desc.getColumnAt(column));

      boolean denZero = Float.compare(0, _sd) == 0;

      for (int row = 0; row < desc.getNumRows(); row++) {

        float z = 0;
        if (!denZero) z = (_mat.GetElement(row, column) - _mean) / _sd;

        standardScore.SetElement(desc.getRowAt(row), desc.getColumnAt(column), z);
      }
    }

    return standardScore;
  }
Example #2
0
  public static Matrix3D Process(Matrix3D _cube, Definitions.Algorithm _algorithm) {

    Matrix3D res = new Matrix3D();
    Set<Map.Entry<String, Matrix2D>> records = _cube.getIterator();

    // Mean and standard deviation
    System.out.println("Processing Mean and SD");
    Matrix2D _meanMat = RateOfMean.ColumnDepthMeanAndStandardDeviation(_cube, true, _algorithm);

    System.out.println("Processing layers...");
    int c = 0;
    boolean print = false;
    boolean print2 = false;
    for (Map.Entry<String, Matrix2D> entry : records) {

      Matrix2D layer = entry.getValue();
      MatrixDescriptor layerDesc = layer.getMatrixDescriptor();
      Matrix2D layerSS = new Matrix2D(layerDesc);
      // Matrix2D layerSS = layer.DoGPUStandardScore(_meanMat);

      for (int col = 0; col < layerDesc.getNumCols(); col++) {
        String colName = layerDesc.getColumnAt(col);
        float _mean = _meanMat.GetElement(RateOfMean.Mean, layerDesc.getColumnAt(col));
        float _sd = _meanMat.GetElement(RateOfMean.StandardDeviation, colName);

        for (int row = 0; row < layerDesc.getNumRows(); row++) {

          float _vv = layer.GetElement(row, col);
          if (_vv >= 8 && print == false) {
            print = true;
            float _ss = (layer.GetElement(row, col) - _mean) / _sd;
            System.out.println(_ss);
          }

          layerSS.SetElement(
              layerDesc.getRowAt(row),
              layerDesc.getColumnAt(col),
              (layer.GetElement(row, col) - _mean) / _sd);
        }
      }

      if (print == true && print2 == false) {
        print2 = true;
        layerSS.Debug();
      }

      res.AddLayer(entry.getKey(), layerSS);

      System.out.println("Standard Score of matrix " + c + " of " + records.size());
      c++;
    }

    return res;
  }