Re[2]: [Matplotlib-users] scipy.xplt to matplotlib

[Alan G I. <ai...@am...>]

On Mon, 30 May 2005, John Hunter apparently wrote: 
> If possible, I suggest creating just two line objects and 
> manipulating their data directly, as in 

> from math import sin, cos 
> import matplotlib.numerix as nx 
> import pylab 
> pylab.ion()  # interactive on, so each plot updates the window 

> pylab.hold('on') 
> allt = [0]          # grow these lists and set the line data with them 
> allsin = [sin(0)] 
> allcos = [cos(0)] 
> lsin, = pylab.plot(allt, allsin, 'g+') # lsin is a Line2D instance 
> lcos, = pylab.plot(allt, allcos, 'ro') # lcos is a Line2D instance 
> pylab.xlabel('Time t[s]') 
> pylab.ylabel('Response') 
> pylab.axis([0,10,-1,1]) 
> for t in nx.arange(0.1,10,0.1): 
>     allt.append(t) 
>     allsin.append(sin(t)) 
>     allcos.append(cos(t)) 
>     lsin.set_data(allt, allsin) 
>     lcos.set_data(allt, allcos) 
>     pylab.draw() 

> # to prevent the window from closing 
> raw_input() 


1. This is indeed much faster.
2. It still slows to a crawl as t grows. Should it?
3. The only thing that slows down is draw(), so the problem 
   does not lie with the updating of the line instances.

Alan Isaac

P.S. Suppose I run the script and then press enter in the 
shell before closing the graph window. I get the following 
'NULL tstate' error:
    Fatal Python error: PyEval_RestoreThread: Null tstate
    abnormal program termination
Perhaps this is to be expected.