Hi, On Sun, 11 Oct 2020 at 00.27, Hongyi Zhao <hongyi.z...@gmail.com> wrote:
> On Sun, Oct 11, 2020 at 1:48 AM Robert Kern <robert.k...@gmail.com> wrote: > > > > You don't need to use vectorize() on fermi(). fermi() will work just > fine on arrays and should be much faster. > > Yes, it really does the trick. See the following for the benchmark > based on your suggestion: > > $ time python mu.py > [-10.999 -10.999 -10.999 ... 20. 20. 20. ] [4.973e-84 > 4.973e-84 4.973e-84 ... 4.973e-84 4.973e-84 4.973e-84] > > real 0m41.056s > user 0m43.970s > sys 0m3.813s > > > But are there any ways to further improve/increase efficiency? I believe it will get a bit better if you don’t column_stack an array 6000 times - maybe pre-allocate your output first? Andrea. > > Regards, > HY > > > > > On Sat, Oct 10, 2020, 8:23 AM Hongyi Zhao <hongyi.z...@gmail.com> wrote: > >> > >> Hi, > >> > >> My environment is Ubuntu 20.04 and python 3.8.3 managed by pyenv. I > >> try to run the script > >> < > https://notebook.rcc.uchicago.edu/files/acs.chemmater.9b05047/Data/bulk/dft/mu.py > >, > >> but it will keep running and never end. When I use 'Ctrl + c' to > >> terminate it, it will give the following output: > >> > >> $ python mu.py > >> [-10.999 -10.999 -10.999 ... 20. 20. 20. ] [4.973e-84 > >> 4.973e-84 4.973e-84 ... 4.973e-84 4.973e-84 4.973e-84] > >> > >> I have to terminate it and obtained the following information: > >> > >> ^CTraceback (most recent call last): > >> File "mu.py", line 38, in <module> > >> integrand=DOS*fermi_array(energy,mu,kT) > >> File > "/home/werner/.pyenv/versions/datasci/lib/python3.8/site-packages/numpy/lib/function_base.py", > >> line 2108, in __call__ > >> return self._vectorize_call(func=func, args=vargs) > >> File > "/home/werner/.pyenv/versions/datasci/lib/python3.8/site-packages/numpy/lib/function_base.py", > >> line 2192, in _vectorize_call > >> outputs = ufunc(*inputs) > >> File "mu.py", line 8, in fermi > >> return 1./(exp((E-mu)/kT)+1) > >> KeyboardInterrupt > >> > >> > >> Any helps and hints for this problem will be highly appreciated? > >> > >> Regards, > >> -- > >> Hongyi Zhao <hongyi.z...@gmail.com> > >> _______________________________________________ > >> NumPy-Discussion mailing list > >> NumPy-Discussion@python.org > >> https://mail.python.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > -- > Hongyi Zhao <hongyi.z...@gmail.com> > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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