matplotlib-users Mailing List for matplotlib

I tried to execute the following code:
http://matplotlib.org/faq/howto_faq.html#test-whether-a-point-is-inside-a-polygon
However I get errors I describe here:
http://stackoverflow.com/questions/16452509/matplotlib-pnpoly-example-results-in-error
>>>import numpy as np
>>>import matplotlib.nxutils as nx
>>>verts = np.array([ [0,0], [0, 1], [1, 1], [1,0]], float)
>>>nx.pnpoly(0.5, 0.5, verts)
Traceback (most recent call last):
 File "<console>", line 1, in <module>
 File "C:\Python27\lib\site-packages\matplotlib\nxutils.py", line 26, in
pnpoly
 return p.contains_point(x, y)
 File "C:\Python27\lib\site-packages\matplotlib\path.py", line 289, in
contains_point
 transform = transform.frozen()
AttributeError: 'float' object has no attribute 'frozen'
>>>nx.pnpoly(0.5, 1.5, verts)
Traceback (most recent call last):
 File "<console>", line 1, in <module>
 File "C:\Python27\lib\site-packages\matplotlib\nxutils.py", line 26, in
pnpoly
 return p.contains_point(x, y)
 File "C:\Python27\lib\site-packages\matplotlib\path.py", line 289, in
contains_point
 transform = transform.frozen()
AttributeError: 'float' object has no attribute 'frozen'
Apparently, nxutils is deprecated, which to me means it should still work
but a user on stackoverflow pointed out that there may be some code rot.
That said, the documentation on matplotlib.path.Path.contains_point is weak
(see below). Does anyone have an example of how I can do the exact same
thing in the code in the howto_faq but using the suggested function
(contains_point)?
http://matplotlib.org/1.2.1/api/path_api.html?highlight=contains_point#matplotlib.path.Path.contains_point
contains_point(point, transform=None, radius=0.0)
 Returns True if the path contains the given point.
 If transform is not None, the path will be transformed before performing
the test.
 radius allows the path to be made slightly larger or smaller.
contains_points(points, transform=None, radius=0.0)
 Returns a bool array which is True if the path contains the
corresponding point.
 If transform is not None, the path will be transformed before performing
the test.
 radius allows the path to be made slightly larger or smaller.
--
View this message in context: http://matplotlib.1069221.n5.nabble.com/re-matplotlib-pnpoly-example-results-in-error-tp41028.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

ImageGrid creates axes for colobar even if cbar_mode=None. These axes for
colorbar are set to invisible, so usually they are harmless.
tight_layout, however, do not care whether the axes is visible or not, and
the warning is because of these "invisible" axes for colorbars.
For comparison, if you turn on all colorbar with cbar_mode="each", the
warning will go away.
You may manually remove colorbar axes from the figure if you want,
```
for ax in grid.cbar_axes: fig._axstack.remove(ax)
```
but do this only when cbar_mode=None.
So, I think the warning is harmless.
I will make a pull request that make tight_layout to ignore any invisible
axes soon.
Regards,
-JJ
On Wed, May 8, 2013 at 10:21 PM, Jonathan Slavin <js...@cf...>wrote:
> Hi,
>
> I wrote a short routine to look through a set of images that result from
> slightly different processing of the same data. I want to compare three
> different images and be able to zoom them all in the same way and then
> move onto the next set of three. The best way that I've found to do
> that so far involves using mpl_toolkits.axes_grid1.ImageGrid. It all
> works fine. I found that to get the most image on screen at once, using
> the tight_layout=True argument to plt.figure gives excellent results.
> My one question is that I get the following warning:
>
> WARNING: This figure includes Axes that are not compatible with
> tight_layout, so its results might be incorrect. [matplotlib.figure]
>
> As I say, the results are good, so it's not really a problem, but I do
> wonder about the source of the warngin -- and whether re-using the code
> in a different way in the future could lead to problems. So, my
> question is: what is the problem pointed to by the warning and how could
> I avoid it (while still getting the same good results)?
>
> Regards,
> Jon
> --
> ______________________________________________________________
> Jonathan D. Slavin Harvard-Smithsonian CfA
> js...@cf... 60 Garden Street, MS 83
> phone: (617) 496-7981 Cambridge, MA 02138-1516
> cell: (781) 363-0035 USA
> ______________________________________________________________
>
>
>
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