Re: [Matplotlib-users] scipy.xplt to matplotlib

[Fernando P. <Fer...@co...>]

Nils Wagner wrote:
> Hi all,
> 
> I am going to switch over to matplotlib.
> How can I convert the example with respect to matplotlib ?

[~/test]> cat xplot.py
#!/usr/bin/env python
"""xplt-based dynamic plot"""

from scipy import *

xplt.hold('on')
for t in arange(0,10,0.1):
    xplt.plot(t,sin(t),'g+')
    xplt.pause(10)
    xplt.plot(t,cos(t),'ro')
xplt.xlabel('Time t[s]')
xplt.ylabel('Response')

# to prevent the window from closing
raw_input()

[~/test]> cat pplot.py
#!/usr/bin/env python
"""pylab-based dynamic plot"""

from scipy import *

import pylab
pylab.ion()  # interactive on, so each plot updates the window

pylab.hold('on')
for t in arange(0,10,0.1):
    pylab.plot([t],[sin(t)],'g+')
    pylab.plot([t],[cos(t)],'ro')
pylab.xlabel('Time t[s]')
pylab.ylabel('Response')

# to prevent the window from closing
raw_input()

###

As you can see, all I did was pretty much do xplt->pylab, plus a few 
very minor changes.  The matplotlib website has a lot of documentation, 
including illustrated screenshots, an examples package, a tutorial and a 
full user's guide.  Since both mpl and xplt were trying to mimic matlab 
syntax, the transition should be pretty easy for you.

One word of caution: you'll notice that in the above, the xplt script 
runs very fast, while the mpl one is unacceptably slow (and it consumes 
a TON of cpu).  There may be a trick to provide acceptable update speeds 
for dynamically resized plots, but unfortunately I don't use that kind 
of plotting much, so I can't really offer much help there.

I get the feeling that there's an O(N^2) problem somewhere in there, 
because it seems to me that the plot update slows down worse than 
linearly as more points are added.  But I didn't really measure it, it's 
just a gut feeling.

Cheers,

f