On Fri, Feb 13, 2009 at 2:30 PM, <jason-s...@creativetrax.com> wrote:
> Eric Firing wrote:
>
>> Ryan May wrote:
>>
>>> On Fri, Feb 13, 2009 at 12:08 PM, <jason-s...@creativetrax.com <mailto:
>>> jason-s...@creativetrax.com>> wrote:
>>>
>>>
>>> A student of mine recently noticed that sometimes, quiver plots were
>>> coming up empty (using the plot_vector_field function from Sage, which
>>> passes everything on to quiver). Upon investigation, we saw that some
>>> of the array entries passed in were infinity because of where we
>>> happened to evaluate the function. It was relatively easy to correct
>>> in
>>> our case (change the evaluation to miss the bad point), but is there a
>>> better way to handle this? Can this be considered a bug in quiver
>>> (i.e.,
>>> returning a blank plot when one of the vectors has an infinite
>>> coordinate?).
>>>
>>> Here is some example code illustrating the problem:
>>>
>>>
>>> import pylab
>>> import numpy
>>> step=1
>>> X,Y = numpy.meshgrid(
>>> numpy.arange(-1,1.1,step),numpy.arange(-1,1.1,step) )
>>> U = 1/X
>>> V = Y
>>> pylab.figure()
>>> Q = pylab.quiver( X,Y,U, V)
>>> pylab.savefig("test.png")
>>>
>>> When you change step to something that avoids an evaluation at x=0
>>> (say,
>>> step=0.13), you get a nice plot.
>>>
>>> Is this something that we should be preprocessing in Sage before
>>> calling
>>> quiver, masking those "bad" points or something? I haven't used
>>> masking
>>> before, but I'd like to fix Sage's plot_vector_field function to
>>> return
>>> something sensible, even when the function happens to be infinite at
>>> one
>>> of the points.
>>>
>>>
>>> I'm not sure why quiver does not plot any arrows in that case, but it's
>>> also easy enough to mask out the values yourself:
>>>
>>> U = 1/X
>>> U = numpy.ma.array(U, mask=numpy.isinf(U))
>>> V = Y
>>> V = numpy.ma.array(V, mask=numpy.isinf(V))
>>>
>>> You can also catch NaN values by using ~numpy.isfinite() instead of
>>> numpy.isinf().
>>>
>>
>> This is a good use case for numpy.ma.masked_invalid:
>>
>> In [2]:numpy.ma.masked_invalid?
>> Type: function
>> Base Class: <type 'function'>
>> String Form: <function masked_invalid at 0xb62bccdc>
>> Namespace: Interactive
>> File: /usr/local/lib/python2.5/site-packages/numpy/ma/core.py
>> Definition: numpy.ma.masked_invalid(a, copy=True)
>> Docstring:
>> Mask the array for invalid values (NaNs or infs).
>> Any preexisting mask is conserved.
>>
>>
> Thanks for both of your replies. So I tried the following:
>
> import pylab
> import numpy
> step=1
> X,Y = numpy.meshgrid( numpy.arange(-1,1.1,step),numpy.arange(-1,1.1,step) )
> U = numpy.ma.masked_invalid(1/X)
> V = numpy.ma.masked_invalid(Y)
> pylab.figure()
> Q = pylab.quiver( X,Y,U, V)
> pylab.savefig("test.png")
>
> and I still didn't get a plot. I noticed two things:
>
> 1. The unmasked portion of each array might be different; I hope quiver can
> handle that.
>
> 2. Even when I called pylab.quiver(X,Y,U,U) (so that the masks lined up), I
> still didn't get a plot.
>
> Does quiver handle masks properly, or did I just do something wrong?
>
It should, but there was a release with a bug in the masked support for
quiver. What version are you running?
import matplotlib; print matplotlib.__version__
Ryan
--
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
Sent from: Norman Oklahoma United States.
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