Re: [sage-support] Benchmark linear system solve (sage x python(jupyter))

2016-04-04 Thread Nils Bruin
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:

Re: [sage-support] Benchmark linear system solve (sage x python(jupyter))

2016-04-04 Thread jmarcellopereira
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() > > > >

Re: [sage-support] Benchmark linear system solve (sage x python(jupyter))

2016-04-04 Thread Thierry Dumont
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

[sage-support] Benchmark linear system solve (sage x python(jupyter))

2016-03-30 Thread jmarcellopereira
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: