The question is if Python Numpy library can use back subsitution to solve Ax=b if possible, that is, if A is lower triangular? Do numerical linear algebra packages do this? I would think Numpy would detect the triangular state and use the proper approach, but a Google search returns things like scipy.linalg.lu_solve or scipy.linalg.cho_solve, which I assume are to be used in case when we know we have a triangular matrix?
Thanks in advance,