On 10 Nov 2007, at 7:51 AM, Michael V. DePalatis wrote:
...
> I recently discovered that if I import
> pylab after importing numpy, I get tons of warnings:
>
> Warning: divide by zero encountered in divide
> Warning: invalid value encountered in multiply
> Warning: overflow encountered in long_scalars
>
> with the last occurring far most often (interestingly, I do not get
> these warnings if pylab is imported before numpy). My question then is
> two fold:
>
> (1) Why do I only get these warnings depending on when I import pylab?
>
I am not sure: with the latest svn builds I get the message both
ways. Maybe the default error handling is different between the
version of numpy and matplotlib you have installed.
> (2) (a more general python question) How can I get these warning
> messages to give me *useful* information, such as where the
> problems
> are happening?
>
In numpy you can cause these to be exceptions by setting
numpy.seterr("raise")
Now you can see exactly where the exception happens.
If you don't want to stop execution at this point, you use a
callback. This will pop-open the debugger at the point of error, but
allow you to continue.
def f(err,flag):
import pdb; pdb.set_trace()
numpy.seterr("call")
numpy.seterrcall(f)
In general, with python warnings you can change them to exceptions by
using warnings.simplefilter('error',Warning) (see http://
docs.python.org/lib/module-warnings.html for details), however numpy
does not seem to issue warnings, instead opting to directly print a
message. (Anyone know why the warnings library is not used? Is this
a bug that should be fixed?)
Michael.
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