Hi On Thu, Mar 24, 2011 at 4:17 PM, Skipper Seabold <jsseab...@gmail.com>wrote:
> On Thu, Mar 24, 2011 at 9:45 AM, Ralf Gommers > <ralf.gomm...@googlemail.com> wrote: > > 2011/3/24 Dmitrey <tm...@ukr.net>: > >> > >> Hi > >> > >> 2011/3/24 Dmitrey <tm...@ukr.net> > >>> > >>> >>> from numpy import inf, array > >>> >>> inf*0 > >>> nan > >>> > >>> (ok) > >>> > >>> >>> array(inf) * 0.0 > >>> StdErr: Warning: invalid value encountered in multiply > >>> nan > >>> > >>> My cycled calculations yields this thousands times slowing computations > >>> and making text output completely non-readable. > >> > >> Would old= seterr(invalid= 'ignore') be sufficient for you? > >> > >> yes for me, but I'm not sure for all those users who use my soft. Maybe > it > >> will hide some bugs in their objective functions and nonlinear > constraints > >> in numerical optimization and nonlinear equation systems. > > > > If we do what you request in your message subject your users will have > > the same issue. > > > > You can wrap (parts of) your code in something like: > > olderr = seterr(invalid= 'ignore') > > <do stuff> > > seterr(**olderr) > > > > Also, as Robert pointed out to me before np.errstate is a > context-manager for ignoring these warnings. I often wrap optimization > code with it. > I didn't realize that its context-manager, but that's really create! (Perhaps documents could reflect that.) Regards, eat > > In [3]: np.array(np.inf)*0. > Warning: invalid value encountered in multiply > Out[3]: nan > > In [4]: with np.errstate(all='ignore'): > ...: np.array(np.inf)*0. > ...: > ...: > Out[4]: nan > > In [5]: np.array(np.inf)*0. > Warning: invalid value encountered in multiply > Out[5]: nan > > Skipper > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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