public virtual bool inputModified()
{
return(decomp.inputModified());
}
/**
* Decomposes the matrix using the QR algorithm. Care was taken to minimize unnecessary memory copying
* and cache skipping.
*
* @param orig The matrix which is being decomposed. Not modified.
* @return true if it decomposed the matrix or false if an error was detected. This will not catch all errors.
*/
//public bool decompose(DMatrixRMaj orig)
//{
// if (orig.numCols != orig.numRows)
// throw new ArgumentException("Matrix must be square.");
// if (orig.numCols <= 0)
// return false;
// int N = orig.numRows;
// // compute a similar tridiagonal matrix
// if (!decomp.decompose(orig))
// return false;
// double[] diag = this.diag;
// double[] off = this.off;
// if (diag == null || diag.Count() < N)
// {
// this.diag = diag = new double[N];
// this.off = off = new double[N - 1];
// }
// decomp.getDiagonal(diag, off);
// // Tell the helper to work with this matrix
// helper.init(diag, off, N);
// if (computeVectors)
// {
// if (computeVectorsWithValues)
// {
// return extractTogether();
// }
// else
// {
// return extractSeparate(N);
// }
// }
// else
// {
// return computeEigenValues();
// }
//}
public bool inputModified()
{
return(decomp.inputModified());
}
