Eric Firing wrote:
> Ryan May wrote:
>> On Fri, Feb 13, 2009 at 12:08 PM, <[email protected]
>> <mailto:[email protected]>> 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?
Jason
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