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")
>
>
> Eric
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