Hi there,
I'm attempting to port some code over to matplotlib 0.98.x.
Previously, I was able to do something like:
axes_object.pcolormesh(x,y,v)
axes_object.set_xscale('log')
axes_object.set_yscale('log')
and then save the figure. However, now this fails because the
sequence of transformations it applies is not affine. (assert
transform.is_affine in collections.py:QuadMesh.) If I want to have
the same effect -- a log-spaced pcolormesh -- what is the appropriate
sequence of calls? I'd like to avoid pre-applying the log and
plotting on a linear-scale plot, as the code also overplots analytic
functions in the same figure.
Thanks!
-Matt
I think this was just an oversight in the refactoring of transformations for 0.98. This should work now in SVN r5716. Look here if you want to patch your local copy -->
Cheers,
Mike
Matthew Turk wrote:
ยทยทยท
Hi there,
I'm attempting to port some code over to matplotlib 0.98.x.
Previously, I was able to do something like:
axes_object.pcolormesh(x,y,v)
axes_object.set_xscale('log')
axes_object.set_yscale('log')
and then save the figure. However, now this fails because the
sequence of transformations it applies is not affine. (assert
transform.is_affine in collections.py:QuadMesh.) If I want to have
the same effect -- a log-spaced pcolormesh -- what is the appropriate
sequence of calls? I'd like to avoid pre-applying the log and
plotting on a linear-scale plot, as the code also overplots analytic
functions in the same figure.
Thanks!
-Matt
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Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA