On Friday, March 15, 2019 at 10:59:06 PM UTC+1, Kwankyu Lee wrote:
>
> Hi,
>
> If the determinant is obviously zero, then you don't need to run the
> computation. If a preprocessing to check zero rows or columns is added,
> then the determinant computation would become slower for usual nontrivia
Indeed the determinant code in matrix2.pyx is a huge mess. Some
dispatch is unavoidable but many specialized matrix implement
their own determinant function:
matrix_complex_ball_dense.pyx
matrix_double_dense.pyx
matrix_gap.pyx
matrix_integer_dense.pyx
matrix_mod2_dense.pyx
matrix_modn_sparse.pyx
I think the problem is that it computes the characteristic polynomial and
then takes the constant term. That seems a bit wasteful, no?
c = self.charpoly(var, algorithm="df")[0]
Martin
Am Freitag, 15. März 2019 23:07:04 UTC+1 schrieb Dima Pasechnik:
>
> On Fri, Mar 15, 2019 at 02:59:05PM -0
On Fri, Mar 15, 2019 at 02:59:05PM -0700, Kwankyu Lee wrote:
>
> If the determinant is obviously zero, then you don't need to run the
> computation. If a preprocessing to check zero rows or columns is added,
> then the determinant computation would become slower for usual nontrivial
> cases.
I
Hi,
If the determinant is obviously zero, then you don't need to run the
computation. If a preprocessing to check zero rows or columns is added,
then the determinant computation would become slower for usual nontrivial
cases.
Cheers.
On Saturday, March 16, 2019 at 2:15:06 AM UTC+9, Maximili
