On 7/11/06, Gary Ruben <[EMAIL PROTECTED]> wrote:
> On this topic, here is something I used the other day (just some
> different dash sequences):
>
> e, = plot(x, y, 'k', label=r'$\theta_3=%1.2f$'%(th3))
> setp(e, dashes={0:(1,0), 1:(2,2), 2:(10,4), 3:(10,4,4,4), 4:(10,2,2,2),
> 5:(15,2,6,2)}[i])
Thanks for these. In playing with this, both for my needs and to try
and contribute something for a permanent solution, I found something
really strange. Try running the following code in pylab:
"""Simple dashing test."""
import numpy as N
import pylab as P
dashes= { 0:(1,0),
1:(2,2),
2:(10,4),
3:(10,4,4,4),
4:(10,2,2,2),
5:(15,2,6,2) }
y = N.ones(10)+N.rand(10)
P.figure()
dashnums = dashes.keys()
dashnums.sort()
for d in dashnums:
P.plot(y,dashes=dashes[d])
# Bug??? Using this, nothing gets displayed:
y += 1
# But with this, it works fine:
#y = y+1
P.show()
# EOF
Uncomment the 'y=y+1' option, and all works fine. Here's where the
problem may be coming from, just try this in a terminal:
y = 1.0*arange(10)
plot(y)
y += rand(10)
show()
There are actually two issues here, one is definitely a bug, the other
one could be construed as a feature (albeit a surprising one):
- bug: that the script above doesn't display anything with current
SVN. I don't know why.
- feature?: that mpl holds on to the actual numpy memory buffer, so if
an array is modified in-place, any subsequent window update will
modify the plot. I can actually see this being quite useful for
monitoring a region of memory, though it can cause surprising behavior
if you are just trying to get successive plots. I guess I'm squarely
+1/-1 on how much I like it :)
I'll work a bit more on the dashing and send something later...
Cheers, and thanks for the hints!
f
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