On 06/27/2011 03:38 AM, Jonathan Slavin wrote:
> I tried the suggested clean-up but saw no difference in performance. I
> left out a crucial piece of information, I think, in my earlier message.
> The delay in drawing occurs when I'm running the code from within
> ipython, invoked with the -pylab flag. When I run it directly from the
> command line, I get no such delay. I presume this is backend dependent.
> For my current purposes, just running it directly from the command line
> (i.e. something like: % python do_fits.py) works for me. The ability to
> interactively examine variables, as one can when running within ipython,
> would be nicer, however.
>
> Jon
>
>> On 06/24/2011 04:03 AM, Jonathan Slavin wrote:
>> > import matplotlib.pyplot as plt
>> > plt.ion()
>> > fig = plt.gcf()
>> > for obsid in obsids:
>> > <do fitting>
>> > plt.cla()
>> > fig = plt.gcf()
>> > ax = fig.add_axes([0.15,0.1,0.8,0.6])
>> > ax.plot(x,y)
>> > plt.draw()
>> > ans = raw_input('continue? ')
>> > if ans == 'n':
>> > break
>>
>> The behavior may depend on mpl version and backend, but with
>> 1.0.1 or
>> later, I think something like what you have will work with a
>> little
>> cleanup, e.g.:
>>
>> import matplotlib.pyplot as plt
>> import numpy as np
>>
>> plt.ion()
>> fig = plt.gcf()
>> ax = fig.add_axes([0.15,0.1,0.8,0.6])
>> for i in range(3):
>> ax.cla()
>> ax.plot(np.random.rand(10))
>> plt.draw()
>> raw_input("hit a key to proceed")
What happens if you replace the raw_input with the figure method
waitforbuttonpress? (Also available as a pyplot function.)
Eric
>>
>>
>> Eric
>
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