On Sun, 11 Oct 2020 at 07.52, Hongyi Zhao <hongyi.z...@gmail.com> wrote:
> On Sun, Oct 11, 2020 at 1:33 PM Andrea Gavana <andrea.gav...@gmail.com> > wrote: > > > > > > > > On Sun, 11 Oct 2020 at 07.14, Andrea Gavana <andrea.gav...@gmail.com> > wrote: > >> > >> 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. > > > > > > > > I’m sorry, scratch that: I’ve seen a ghost white space in front of your > column_stack call and made me think you were stacking your results very > many times, which is not the case. > > Still not so clear on your solutions for this problem. Could you > please post here the corresponding snippet of your enhancement? I have no solution, I originally thought you were calling “column_stack” 6000 times in the loop, but that is not the case, I was mistaken. My apologies for that. The timings of your approach is highly dependent on the size of your “energy” and “DOS” array - not to mention calling trapz 6000 times in a loop. Maybe there’s a better way to do it with another approach, but at the moment I can’t think of one... > > Regards, > HY > > > >> > >> > >>> > >>> > >>> 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 > > > > _______________________________________________ > > 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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