public NonNegLsSolver(int numIsos, int maxRows, int maxTransitions, bool useFirstGuess = false)
{
_conditioner = new WeightedConditioner();
_firstGuess = new DenseMatrix(numIsos, maxTransitions);
_matrixAx = new DenseMatrix(maxRows, maxTransitions);
_matrixWs = new DenseMatrix(numIsos, maxTransitions);
_x = new DenseMatrix(numIsos, 1);
_z = new DenseMatrix(numIsos, 1);
_solutionCol = new DenseVector(numIsos);
_initializeCol = new DenseVector(numIsos);
_binnedDataCol = new DenseVector(maxRows);
_matrixAxCol = new DenseVector(maxRows);
_matrixWsCol = new DenseVector(numIsos);
_tol = null;
_maxIter = null;
_zSet = new SizedSet(numIsos);
_pSet = new SizedSet(numIsos);
_colMatrixB = new DenseMatrix(maxRows, 1);
_w = new DenseMatrix(numIsos, 1);
_matrixAxC = new DenseMatrix(maxRows, 1);
_matrixDiff = new DenseMatrix(maxRows, 1);
_matrixDiffBig = new DenseMatrix(maxRows, maxTransitions);
_useFirstGuess = useFirstGuess;
SetMathNetParameters();
}
private Matrix <double> GetMatrixColumns(Matrix <double> input, SizedSet columns)
{
double[,] matrixData = new double[input.RowCount, columns.Count];
for (int row = 0; row < input.RowCount; ++row)
{
int destColumn = 0;
foreach (var column in columns)
{
matrixData[row, destColumn++] = input[row, column];
}
}
return(DenseMatrix.OfArray(matrixData));
}
