This worked great, thanks so much for your help!
Cheers
Stan
On 8/29/10 2:29 AM, Jae-Joon Lee wrote:
> I just remembered that there has been a bug in old version of
> matplotlib that annotation_clip parameter is not correctly set when
> given as a keyword parameter of "annotate" function. The bug
I just remembered that there has been a bug in old version of
matplotlib that annotation_clip parameter is not correctly set when
given as a keyword parameter of "annotate" function. The bug has been
fixed.
http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg15068.html
As a work
On 8/28/10 3:59 PM, Stan Schymanski wrote:
> Hi JJ,
>
> Thanks for the advice. However, the annotation_clip=False addition does
> not make a difference to me. I am using Matplotlib from within Sage,
> though; not sure if this makes it behave differently.
>
FYI, matplotlib in Sage is still at matp
Hi JJ,
Thanks for the advice. However, the annotation_clip=False addition does
not make a difference to me. I am using Matplotlib from within Sage,
though; not sure if this makes it behave differently.
Cheers
Stan
On 8/28/10 5:09 PM, Jae-Joon Lee wrote:
> I think this change has been there for
I think this change has been there for a while.
For recent versions of matplotlib, the default behavior of annotate is
that, when xycoords=="data", the arrow is drawn only when the
annotated point is inside the axes.
To override this behavior, use annotation_clip keyword parameter.
pylab.annotate
On Fri, Aug 27, 2010 at 7:21 AM, Stan Schymanski wrote:
> Dear all,
>
> I don't know which update it was that broke it, but this used to work:
>
> import numpy
> import pylab
> pylab.clf()
> fig = pylab.figure(1,figsize=(8,5))
> ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1,5),
> ylim=(-4
Dear all,
I don't know which update it was that broke it, but this used to work:
import numpy
import pylab
pylab.clf()
fig = pylab.figure(1,figsize=(8,5))
ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1,5),
ylim=(-4,3))
t = numpy.arange(0.0, 5.0, 0.01)
s = numpy.cos(2*numpy.pi*t)
line, =
