/// <summary>
/// feature here is each row/SNP
/// </summary>
/// <param name="xMatrix"></param>
/// <param name="isOKToDestroyXMatrix"></param>
/// <param name="weightForEachFeature"></param>
/// <param name="parallelOptions"></param>
/// <returns></returns>
///!!! Should be possible to do this with a one pass algo instead of with two passes, one for the mean, and one for the rest
public static Matrix <string, string, double> CreateXMatrixWithColumnMeansZeroWithWeights(Matrix <string, string, double> xMatrix, bool isOKToDestroyXMatrix, IList <double> weightForEachFeature, ParallelOptions parallelOptions, out List <double> columnMeans)
{
//Console.WriteLine("create xMatrixWithColumnMeansZeroWithWeights");
List <double> columnMeansTmp = SpecialFunctions.CreateListWithDefaultElements <double>(xMatrix.ColCount);
Matrix <string, string, double> xMatrixWithColumnMeansZero;
{
xMatrixWithColumnMeansZero = isOKToDestroyXMatrix ? xMatrix : DenseMatrix <string, string, double> .CreateDefaultInstance(xMatrix.RowKeys, xMatrix.ColKeys, double.NaN);
Parallel.ForEach(Enumerable.Range(0, xMatrix.ColCount), parallelOptions, cidIndex =>
{
//Console.Write(string.Format("\r{0}/{1}\t", cidIndex, xMatrix.ColCount));
double sum = 0;
double weightSum = 0;
for (int varIndex = 0; varIndex < xMatrix.RowCount; ++varIndex)
{
sum += weightForEachFeature[varIndex] * xMatrix[varIndex, cidIndex];
weightSum += weightForEachFeature[varIndex];
}
//double columnMean = sum / xMatrix.RowCount;
double columnMean = sum / weightSum;
columnMeansTmp[cidIndex] = columnMean;
for (int varIndex = 0; varIndex < xMatrix.RowCount; ++varIndex)
{
xMatrixWithColumnMeansZero[varIndex, cidIndex] = xMatrix[varIndex, cidIndex] - columnMean;
}
});
Console.WriteLine();
}
columnMeans = columnMeansTmp;
return(xMatrixWithColumnMeansZero);
}
