Hi Chris,
Thanks for that tip. I'll give it a try. They are big images (2048 x
2048) so it seems like your suggestion should work.
Jon
On Tue, Oct 14, 2014 at 12:18 PM, Chris Beaumont <cbeaum...@cfa.harvard.edu>
wrote:
> I've found that, for big images, the *first* draw is very slow, due to the
> intensity scaling of the image, which happens at full resolution. Panning
> and zooming afterwards is fast because the intensity scaling is cached, but
> changing the data array or updating the norm kwarg is slow again. I made
> ModestImage (https://github.com/ChrisBeaumont/mpl-modest-image) to deal
> with this -- it dynamically downsamples images to screen resolution. This
> makes the first draw after updating the data or norm much faster, while
> slowing down subsequent redraws. Perhaps this could help you out?
>
> cheers,
> chris
>
> On Tue, Oct 14, 2014 at 12:08 PM, Benjamin Root <ben.r...@ou.edu> wrote:
>
>> Only if there are multiple figures (plt.draw() operates on the current
>> active figure, while fig.draw() explicitly operates upon that figure).
>> Another possibility is that the bottleneck truly is the IO. Depending on
>> exactly how fits work, it might be lazily loading data for you, so the test
>> without the display of the images might not actually be loading any data
>> into memory.
>>
>> Ben Root
>>
>> On Tue, Oct 14, 2014 at 11:22 AM, Slavin, Jonathan <
>> jsla...@cfa.harvard.edu> wrote:
>>
>>> Hmm. I just saw that you suggest fig.draw(). Is there a difference
>>> with plt.draw()?
>>>
>>> Jon
>>>
>>> On Tue, Oct 14, 2014 at 11:20 AM, Slavin, Jonathan <
>>> jsla...@cfa.harvard.edu> wrote:
>>>
>>>> Hi Ben,
>>>>
>>>> Sorry, in my little example, I left out a few things. I do update
>>>> first after the first call. And I do call draw() after other calls. So
>>>> here is a more accurate representation of what I do:
>>>>
>>>> first = True
>>>> fig = plt.figure()
>>>> for file in files:
>>>> hdu = fits.open(file)
>>>> image = hdu[0].data
>>>> hdu.close()
>>>> if first:
>>>> ax = fig,add_subplot(1,1,1)
>>>> im = ax.imshow(image)
>>>> plt.show()
>>>> first = False
>>>> else:
>>>> im.set_data(image)
>>>> plt.draw()
>>>> ans = raw_input('continue?')
>>>> if ans == 'n':
>>>> break
>>>>
>>>> Jon
>>>>
>>>>
>>>> On Tue, Oct 14, 2014 at 10:42 AM, Benjamin Root <ben.r...@ou.edu>
>>>> wrote:
>>>>
>>>>> Also, you aren't updating "first" after the first call, so it is
>>>>> constantly making new axes and recalling imshow().
>>>>>
>>>>> Ben Root
>>>>>
>>>>> On Tue, Oct 14, 2014 at 10:41 AM, Benjamin Root <ben.r...@ou.edu>
>>>>> wrote:
>>>>>
>>>>>> What is happening is that you are not telling the image to redraw, so
>>>>>> you are only seeing it refresh for other reasons. Try adding a fig.draw()
>>>>>> call prior to the raw_input() call.
>>>>>>
>>>>>> Cheers!
>>>>>> Ben Root
>>>>>>
>>>>>> On Tue, Oct 14, 2014 at 10:03 AM, Slavin, Jonathan <
>>>>>> jsla...@cfa.harvard.edu> wrote:
>>>>>>
>>>>>>> Hi all,
>>>>>>>
>>>>>>> In my work lately I have often wanted to browse through a series of
>>>>>>> images. This means displaying the image(s), looking at it/them and then
>>>>>>> continuing. I have coded this in a few different ways, but it is
>>>>>>> generally
>>>>>>> pretty slow -- which is to say that the image display takes more than a
>>>>>>> couple seconds (~4) after I tell it to continue to the next image. I
>>>>>>> tested the loop without image display and it was a factor of ~80 times
>>>>>>> faster than it was with image display, so it's doesn't have anything to
>>>>>>> do
>>>>>>> with reading the images from disk. My latest approach is basically:
>>>>>>> first = True
>>>>>>> fig = plt.figure()
>>>>>>> for file in imagefiles:
>>>>>>> # read in image data (fits files)
>>>>>>> if first:
>>>>>>> ax = fig.add_suplot(1,1,1)
>>>>>>> im = ax.imshow(image)
>>>>>>> else:
>>>>>>> im.set_data(image)
>>>>>>> ans = raw_input('continue?')
>>>>>>> if ans == 'n':
>>>>>>> break
>>>>>>>
>>>>>>> Is there a more efficient way to do this?
>>>>>>>
>>>>>>> Regards,
>>>>>>> Jon
>>>>>>>
>>>>>>> --
>>>>>>> ________________________________________________________
>>>>>>> Jonathan D. Slavin Harvard-Smithsonian CfA
>>>>>>> jsla...@cfa.harvard.edu 60 Garden Street, MS 83
>>>>>>> phone: (617) 496-7981 Cambridge, MA 02138-1516
>>>>>>> fax: (617) 496-7577 USA
>>>>>>> ________________________________________________________
>>>>>>>
>>>>>>>
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>>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> ________________________________________________________
>>>> Jonathan D. Slavin Harvard-Smithsonian CfA
>>>> jsla...@cfa.harvard.edu 60 Garden Street, MS 83
>>>> phone: (617) 496-7981 Cambridge, MA 02138-1516
>>>> fax: (617) 496-7577 USA
>>>> ________________________________________________________
>>>>
>>>>
>>>
>>>
>>> --
>>> ________________________________________________________
>>> Jonathan D. Slavin Harvard-Smithsonian CfA
>>> jsla...@cfa.harvard.edu 60 Garden Street, MS 83
>>> phone: (617) 496-7981 Cambridge, MA 02138-1516
>>> fax: (617) 496-7577 USA
>>> ________________________________________________________
>>>
>>>
>>
>>
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>
>
> --
> *************************************
> Chris Beaumont
> Senior Software Engineer
> Harvard Center for Astrophysics
> 60 Garden Street, MS 42
> Cambridge, MA 02138
> chrisbeaumont.org
> *************************************
>
--
________________________________________________________
Jonathan D. Slavin Harvard-Smithsonian CfA
jsla...@cfa.harvard.edu 60 Garden Street, MS 83
phone: (617) 496-7981 Cambridge, MA 02138-1516
fax: (617) 496-7577 USA
________________________________________________________
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