Re: [Matplotlib-users] imlim in ax.imshow

[Damon M. <dam...@gm...>]

On Tue, Oct 2, 2012 at 8:33 PM, Michael Aye <kmi...@gm...> wrote:
>>>>>>>>>
>>>>>>>> How nice of you to ask! ;)
>>>>>>>> Indeed: I had the case that image arrays inside an ImageGrid where
>>>>>>>> shown with some white overhead area around, e.g. for an image of 100
>>>>>>>> pixels on the x-axis, the imshow resulted in an x-axis that went from
>>>>>>>> -10 to 110. I was looking for a simple way to suppress that behavior
>>>>>>>> and let imshow instead use the exact image extent. I believe that the
>>>>>>>> plot command has such a flag, hasn't it? (I.e. to use the exact xdata
>>>>>>>> range and not try to beautify the plot?
>>>>>>>>
>>>>>>>> Michael
>>>>>>>
>>>>>>> Is the 'extent' keyword what you're looking for?
>>>>>>>
>>>>>>
>>>>>> No, because it needs detail. I was looking for a boolean switch that
>>>>>> basically says: Respect the data, not beauty.
>>>>>
>>>>> I don't understand what you mean by 'beauty'. If your image is 100
>>>>> pixels wide and 50 pixels tall, what is it about extent=[0,100,0,50]
>>>>> that doesn't do what you want?
>>>>>
>>>> As I wrote, that's not what is happening. I get extent=[-10,110,0,50].
>>>>
>>>>
>>>
>>> The following script works for me:
>>>
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>>
>>> image = np.random.random((100,50))
>>>
>>> fig = plt.figure()
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.imshow(image, extent=[0,100,0,50])
>>> plt.show()
>>>
>>>
>>
>> I think the problem is that Michael is using ImageGrid, and apparently
>> it is not using the tight autoscaling that imshow normally uses by default.
>
> I might have confused where I had the problem as I was trying out many
> a'things yesterday, so today I only can reproduce it with subplots. Can
> I activate tight autoscaling somehow? tight_layout only influences the
> axes towards each-other not the imshows itself.
>
>
>>
>> Eric
>>
>> ------------------------------------------------------------------------------
>> Don't let slow site performance ruin your business. Deploy New Relic APM
>> Deploy New Relic app performance management and know exactly
>> what is happening inside your Ruby, Python, PHP, Java, and .NET app
>> Try New Relic at no cost today and get our sweet Data Nerd shirt too!
>> http://p.sf.net/sfu/newrelic-dev2dev
>
>
>
>
> ------------------------------------------------------------------------------
> Don't let slow site performance ruin your business. Deploy New Relic APM
> Deploy New Relic app performance management and know exactly
> what is happening inside your Ruby, Python, PHP, Java, and .NET app
> Try New Relic at no cost today and get our sweet Data Nerd shirt too!
> http://p.sf.net/sfu/newrelic-dev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

I think you may have encountered a bug, as Ben pointed out. Here's a workaround:

import matplotlib
matplotlib.use('macosx')
import matplotlib.pyplot as plt
from numpy import arange, array

arr = arange(10000).reshape(100,100)
l = [arr,arr,arr,arr]
narr = array(l)

axes = []
fig = plt.figure()
for i in range(4):
    axes.append(fig.add_subplot(2, 2, i))

for ax, im in zip(axes, narr):
    ax.imshow(im, extent=[0,100,0,100])

plt.show()

-- 
Damon McDougall
http://www.damon-is-a-geek.com
B2.39
Mathematics Institute
University of Warwick
Coventry
West Midlands
CV4 7AL
United Kingdom