On Monday, April 4, 2016 at 8:00:54 PM UTC-7, jmarcell...@ufpi.edu.br wrote:
>
> it is true. but ... there is a way to improve the outcome?
>
If you look at the code, it's likely this bit:
M = self._column_ambient_module()
try:
vec = M(b)
except TypeError:
it is true. but ... there is a way to improve the outcome?
Em segunda-feira, 4 de abril de 2016 10:49:56 UTC-3, tdumont escreveu:
>
> Le 30/03/2016 22:33, jmarcell...@ufpi.edu.br a écrit :
> >
> > start = time.time()
> >
> > x = np.linalg.solve(A,B)
> >
> > end = time.time()
> >
> > print
Le 30/03/2016 22:33, jmarcellopere...@ufpi.edu.br a écrit :
start = time.time()
x = np.linalg.solve(A,B)
end = time.time()
print(end - start)
I have tried this juste now; sage version is 7.0
I get :
1) first version:
CPU times: user 6.88 s, sys: 76 ms, total: 6.95 s
Wall time: 2.03 s
2
Hello everyone
I tested the code below and noticed that the code done in python proved faster.
does anyone know why?
Sagemath code:
A = random_matrix(RDF,5000,5000)
B = random_vector(RDF,5000)
%time
x =A\B
CPU time: 11.11 s, Wall time: 11.10 s
or
%time
x = A.solve_right(B)
CPU time: 11.
