matplotlib-users Mailing List for matplotlib

This is what my animation function (i.e. the one that gets called by
`FuncAnimation`) looks like:

        import numpy as np
        ...
        def mpl_animation_function(n):
            print "animating timestep: ", n
            
            if n > 0:
                previous_relevant_patch_indices =
np.ravel(patch_indices_per_timestep[n-1])
                for index in previous_relevant_patch_indices:
                    (patches[index]).set_visible(False)
                    
            relevant_patch_indices = np.ravel(patch_indices_per_timestep[n])
            
            for index in relevant_patch_indices:
                (patches[index]).set_visible(True)
                
            return patches,

`patches` is a pre-generated list of patches (possibly large), that have
already been added to an `axes` instance.


This function is awfully time-consuming as the number of patches becomes
large. 

One idea I had was to parallelize the `for` loop, but likely that won't work
because of issues with the `axes` instance being accessed and modified in
parallel -- so I am afraid of fruitlessly spending time there. Do I have any
other options, or is parallelization possible?



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Sorry Tom -- I missed your message, it seems. I suppose I'll leave the SO
link for now because I got an answer which I accepted. In the future, I'll
post the question here itself.



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This is coming out of the pandas plotting tools, you might get better
answers on their mailing list.

Tom

On Sat, May 16, 2015 at 11:51 AM Juan Wu <wuj...@gm...> wrote:

> Hi, List experts,
>
> I have a matplotlib problem when I tried to use a tool called HDDM. As
> HDDM is another issue, I here just post my problem with Matplotlib. In
> short, the error alarm appeard when I input fig = plt.figure(). I am a
> beginner with those stuff.
>
> I would appreciate if anyone can give me any good pointers.
>
> Thanks so much,
> Juan
>
> ==================
>
> In [8]: fig = plt.figure()
> <matplotlib.figure.Figure at 0x13293890>
>
> In [9]: ax = fig.add_subplot(111, xlabel='RT', ylabel='count',
> title='RT distributions')
>
> In [10]: for i, subj_data in data.groupby('subj_idx'):
>     ...:     subj_data.rt.hist(bins=20, histtype='step', ax=ax)
>     ...:     plt.savefig('hddm_demo_fig_00.pdf')
>
> <matplotlib.figure.Figure at 0x1354cb70>
> Traceback (most recent call last):
>
>   File "<ipython-input-15-3b0b3c83094c>", line 2, in <module>
>     subj_data.rt.hist(bins=20, histtype='step', ax=ax)
>
>   File "C:\Anaconda\lib\site-packages\pandas\tools\plotting.py", line
> 2830, in hist_series
>     raise AssertionError('passed axis not bound to passed figure')
>
> AssertionError: passed axis not bound to passed figure
>
> (relevant link:
> https://groups.google.com/forum/#!topic/hddm-users/yBeIRJaHGwo
> there very few experts view and reply questions)
>
>
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Hi, List experts,

I have a matplotlib problem when I tried to use a tool called HDDM. As
HDDM is another issue, I here just post my problem with Matplotlib. In
short, the error alarm appeard when I input fig = plt.figure(). I am a
beginner with those stuff.

I would appreciate if anyone can give me any good pointers.

Thanks so much,
Juan

==================

In [8]: fig = plt.figure()
<matplotlib.figure.Figure at 0x13293890>

In [9]: ax = fig.add_subplot(111, xlabel='RT', ylabel='count',
title='RT distributions')

In [10]: for i, subj_data in data.groupby('subj_idx'):
    ...:     subj_data.rt.hist(bins=20, histtype='step', ax=ax)
    ...:     plt.savefig('hddm_demo_fig_00.pdf')

<matplotlib.figure.Figure at 0x1354cb70>
Traceback (most recent call last):

  File "<ipython-input-15-3b0b3c83094c>", line 2, in <module>
    subj_data.rt.hist(bins=20, histtype='step', ax=ax)

  File "C:\Anaconda\lib\site-packages\pandas\tools\plotting.py", line
2830, in hist_series
    raise AssertionError('passed axis not bound to passed figure')

AssertionError: passed axis not bound to passed figure

(relevant link: https://groups.google.com/forum/#!topic/hddm-users/yBeIRJaHGwo
there very few experts view and reply questions)