Mike (or other transforms afficionados),
The thread "[Matplotlib-users] Bug saving semilogy plots with a axvline"
started by [EMAIL PROTECTED] pointed to a bug that appears to be deep in
the transforms code. My head is spinning. The problem seems to be
related to the propagation of the _invalid attribute in transforms, in
the case of a mixed data/axes transform such as ashline uses. The
following one-line change in TransformNode, second line from the bottom,
works:
def invalidate(self):
"""
Invalidate this :class:`TransformNode` and all of its
ancestors. Should be called any time the transform changes.
"""
# If we are an affine transform being changed, we can set the
# flag to INVALID_AFFINE_ONLY
value = (self.is_affine) and self.INVALID_AFFINE or self.INVALID
# Shortcut: If self is already invalid, that means its parents
# are as well, so we don't need to do anything.
if self._invalid == value:
return
if not len(self._parents):
self._invalid = value
return
# Invalidate all ancestors of self using pseudo-recursion.
parent = None
stack = [self]
while len(stack):
root = stack.pop()
# Stop at subtrees that have already been invalidated
if root._invalid != value or root.pass_through:
root._invalid = self.INVALID # value <===========
stack.extend(root._parents.keys())
Now, I know this is the wrong solution, because it defeats all the
cleverness with the _invalid values; but perhaps it will save you a few
minutes in finding the right solution.
To reproduce the problem, do this in ipython -pylab:
axhline(5)
yscale('log')
ylim(0.5,30)
Eric
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