matplotlib-users

[Matplotlib-users] Fast imshow plotting

[Joey W. <dou...@gm...>]

I am creating a script that generates images and displays them to the screen
in real time.  I created the following simple script:

__________________________

#!/usr/bin/env python

from pylab import *
from scipy import *

for k in range(1,10000):
    img = standard_normal((40,40))
    imshow(img,interpolation=None,animated=True,label="blah")
    clf()
    show()

__________________________

Now,  this script plots the image too slowly.  I am forced to use the clf()
function so that it doesn't slow down at each iteration of the for loop.  Is
there a way that I can plot this simple image faster?  What's the best way
to get imshow() to plot quickly?  Thanks for your help.

-Joey

Re: [Matplotlib-users] Fast imshow plotting

[Thomas R. <tho...@gm...>]

Not sure if this will help, but maybe you can do something like this?

---
#!/usr/bin/env python

from pylab import *
from scipy import *

img = standard_normal((40,40))
image = imshow(img,interpolation='nearest',animated=True,label="blah")

for k in range(1,10000):
     img = standard_normal((40,40))
     image.set_data(img)
     show()
---

Note, interpolation='nearest' can be faster than interpolation=None if  
your default interpolation is set to bicubic (which it probably is)

Does this speed things up?

Thomas

On May 1, 2009, at 3:31 PM, Joey Wilson wrote:

> I am creating a script that generates images and displays them to  
> the screen in real time.  I created the following simple script:
>
> __________________________
>
> #!/usr/bin/env python
>
> from pylab import *
> from scipy import *
>
> for k in range(1,10000):
>     img = standard_normal((40,40))
>     imshow(img,interpolation=None,animated=True,label="blah")
>     clf()
>     show()
>
> __________________________
>
> Now,  this script plots the image too slowly.  I am forced to use  
> the clf() function so that it doesn't slow down at each iteration of  
> the for loop.  Is there a way that I can plot this simple image  
> faster?  What's the best way to get imshow() to plot quickly?   
> Thanks for your help.
>
> -Joey
>
> ------------------------------------------------------------------------------
> Register Now & Save for Velocity, the Web Performance & Operations
> Conference from O'Reilly Media. Velocity features a full day of
> expert-led, hands-on workshops and two days of sessions from industry
> leaders in dedicated Performance & Operations tracks. Use code  
> vel09scf
> and Save an extra 15% before 5/3. http://p.sf.net/sfu/velocityconf_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Re: [Matplotlib-users] Fast imshow plotting

[Eric F. <ef...@ha...>]

Thomas Robitaille wrote:
> Not sure if this will help, but maybe you can do something like this?
> 
> ---
> #!/usr/bin/env python
> 
> from pylab import *
> from scipy import *

To run this as a standalone script, without ipython -pylab, you need to 
include:

ion()

> 
> img = standard_normal((40,40))
> image = imshow(img,interpolation='nearest',animated=True,label="blah")
> 
> for k in range(1,10000):
>      img = standard_normal((40,40))
>      image.set_data(img)
>      show()

show() should never be called more than once for a given figure; what 
you want here is draw().

Eric


> ---
> 
> Note, interpolation='nearest' can be faster than interpolation=None if  
> your default interpolation is set to bicubic (which it probably is)
> 
> Does this speed things up?
> 
> Thomas
> 
> On May 1, 2009, at 3:31 PM, Joey Wilson wrote:
> 
>> I am creating a script that generates images and displays them to  
>> the screen in real time.  I created the following simple script:
>>
>> __________________________
>>
>> #!/usr/bin/env python
>>
>> from pylab import *
>> from scipy import *
>>
>> for k in range(1,10000):
>>     img = standard_normal((40,40))
>>     imshow(img,interpolation=None,animated=True,label="blah")
>>     clf()
>>     show()
>>
>> __________________________
>>
>> Now,  this script plots the image too slowly.  I am forced to use  
>> the clf() function so that it doesn't slow down at each iteration of  
>> the for loop.  Is there a way that I can plot this simple image  
>> faster?  What's the best way to get imshow() to plot quickly?   
>> Thanks for your help.
>>
>> -Joey
>>
>> ------------------------------------------------------------------------------
>> Register Now & Save for Velocity, the Web Performance & Operations
>> Conference from O'Reilly Media. Velocity features a full day of
>> expert-led, hands-on workshops and two days of sessions from industry
>> leaders in dedicated Performance & Operations tracks. Use code  
>> vel09scf
>> and Save an extra 15% before 5/3. http://p.sf.net/sfu/velocityconf_______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 
> ------------------------------------------------------------------------------
> Register Now & Save for Velocity, the Web Performance & Operations 
> Conference from O'Reilly Media. Velocity features a full day of 
> expert-led, hands-on workshops and two days of sessions from industry 
> leaders in dedicated Performance & Operations tracks. Use code vel09scf 
> and Save an extra 15% before 5/3. http://p.sf.net/sfu/velocityconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Re: [Matplotlib-users] Fast imshow plotting

[Joey W. <dou...@gm...>]

Eric and Thomas,

Thanks for your help.  I was able to get it plotting MUCH faster.  Here's my
code:

#!/usr/bin/env python

from pylab import *
from scipy import *

ion()
img = standard_normal((50,100))
image = imshow(img,interpolation='nearest',animated=True,label="blah")

for k in range(1,100):
    img = standard_normal((100,100))
    image.set_data(img)
    draw()


Thanks again.
-Joey

On Sat, May 2, 2009 at 1:27 PM, Eric Firing <ef...@ha...> wrote:

> Thomas Robitaille wrote:
>
>> Not sure if this will help, but maybe you can do something like this?
>>
>> ---
>> #!/usr/bin/env python
>>
>> from pylab import *
>> from scipy import *
>>
>
> To run this as a standalone script, without ipython -pylab, you need to
> include:
>
> ion()
>
>
>> img = standard_normal((40,40))
>> image = imshow(img,interpolation='nearest',animated=True,label="blah")
>>
>> for k in range(1,10000):
>>     img = standard_normal((40,40))
>>     image.set_data(img)
>>     show()
>>
>
> show() should never be called more than once for a given figure; what you
> want here is draw().
>
> Eric
>
>
>
>  ---
>>
>> Note, interpolation='nearest' can be faster than interpolation=None if
>>  your default interpolation is set to bicubic (which it probably is)
>>
>> Does this speed things up?
>>
>> Thomas
>>
>> On May 1, 2009, at 3:31 PM, Joey Wilson wrote:
>>
>>  I am creating a script that generates images and displays them to  the
>>> screen in real time.  I created the following simple script:
>>>
>>> __________________________
>>>
>>> #!/usr/bin/env python
>>>
>>> from pylab import *
>>> from scipy import *
>>>
>>> for k in range(1,10000):
>>>    img = standard_normal((40,40))
>>>    imshow(img,interpolation=None,animated=True,label="blah")
>>>    clf()
>>>    show()
>>>
>>> __________________________
>>>
>>> Now,  this script plots the image too slowly.  I am forced to use  the
>>> clf() function so that it doesn't slow down at each iteration of  the for
>>> loop.  Is there a way that I can plot this simple image  faster?  What's the
>>> best way to get imshow() to plot quickly?   Thanks for your help.
>>>
>>> -Joey
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Register Now & Save for Velocity, the Web Performance & Operations
>>> Conference from O'Reilly Media. Velocity features a full day of
>>> expert-led, hands-on workshops and two days of sessions from industry
>>> leaders in dedicated Performance & Operations tracks. Use code  vel09scf
>>> and Save an extra 15% before 5/3.
>>> http://p.sf.net/sfu/velocityconf_______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Register Now & Save for Velocity, the Web Performance & Operations
>> Conference from O'Reilly Media. Velocity features a full day of expert-led,
>> hands-on workshops and two days of sessions from industry leaders in
>> dedicated Performance & Operations tracks. Use code vel09scf and Save an
>> extra 15% before 5/3. http://p.sf.net/sfu/velocityconf
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>