What operating system are you on and how did you install numpy? From a package manager, from source, by downloading from somewhere...? On Dec 16, 2015 9:34 AM, "Edward Richards" <edwardlricha...@gmail.com> wrote:
> I recently did a conceptual experiment to estimate the computational time > required to solve an exact expression in contrast to an approximate > solution (Helmholtz vs. Helmholtz-Kirchhoff integrals). The exact solution > requires a matrix inversion, and in my case the matrix would contain ~15000 > rows. > > On my machine MATLAB seems to perform this matrix inversion with random > matrices about 9x faster (20 sec vs 3 mins). I thought the performance > would be roughly the same because I presume both rely on the same LAPACK > solvers. > > I will not actually need to solve this problem (even at 20 sec it is > prohibitive for broadband simulation), but if I needed to I would > reluctantly choose MATLAB . I am simply wondering why there is this > performance gap, and if there is a better way to solve this problem in > numpy? > > Thank you, > > Ned > > #Python version > > import numpy as np > > testA = np.random.randn(15000, 15000) > > testb = np.random.randn(15000) > > %time testx = np.linalg.solve(testA, testb) > > %MATLAB version > > testA = randn(15000); > > testb = randn(15000, 1); > tic(); testx = testA \ testb; toc(); > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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