On Sat, Feb 8, 2014 at 10:48 AM, Alan G Isaac wrote:
> The documentation for FuncAnimation says
>
> http://matplotlib.org/api/animation_api.html#matplotlib.animation.FuncAnimation
>
> Makes an animation by repeatedly calling a function func,
> passing in (optional) arguments in fargs.
>
On Mon, Feb 24, 2014 at 2:44 PM, Derek Pyne wrote:
> Does anyone know the preferred method for stopping FuncAnimation? I am
> using it to record data from a oscilloscope and woud like to be able to
> pause and restart the data on demand. Is there any way I can send a button
> click event to it?
On 2014/03/06 4:18 AM, Asma Riyaz wrote:
> Hi,
>
> I am stuck at setting the color bar minimum and maximum values,
> according to what I found I need to set ticks to a numpy linspace array.
> Here is my code:
>
> *threshold=1.01
>
> fig = plt.figure(figsize=(25,25))
> plt.suptitle(file_ha
2014-03-05 21:13 GMT+01:00 Adam Hughes :
> Thanks Andreas. That is correct; however, I'd rather not make this change
> global. I only want a subset of my plots to have this behavior. I feel
> like changing the rcparams would change this globally and probably confuse
> users who don't know this i
I've seen examples for 2 axis using twinx, and examples using subplothost.
Any reason to choose one over the other?
--
Subversion Kills Productivity. Get off Subversion & Make the Move to Perforce.
With Perforce, you get
Yes the interpolation had to be set to nearest or bicubic or bilinear for
it to function properly!!
Thanks a lot!!
Asma
On Thu, Mar 6, 2014 at 4:48 AM, Pierre Haessig wrote:
> Le 05/03/2014 22:37, Asma Riyaz a écrit :
>
> img= mpimg.imread('/home/asmariyaz/Desktop/mytree.png')
> phyl_ax
Hi,
I am stuck at setting the color bar minimum and maximum values, according
to what I found I need to set ticks to a numpy linspace array. Here is my
code:
* threshold=1.01fig = plt.figure(figsize=(25,25))
plt.suptitle(file_handle.replace('.csv',''),font
Le 05/03/2014 22:37, Asma Riyaz a écrit :
> img= mpimg.imread('/home/asmariyaz/Desktop/mytree.png')
> phyl_ax.imshow(img,interpolation='nearest')
Ok, so here you could try replace 'nearest' by 'bilinear' or 'bicubic'.
I believe those are the most common choices for image resampling
(because
