Re: [matplotlib-devel] transforms bug: axhline with log y scale

Mike,

This is a gentle check--I suspect my original message, below, may have 
slipped under the radar.

Eric

Eric Firing wrote:
> Mike (or other transforms afficionados),
> 
> The thread "[Matplotlib-users] Bug saving semilogy plots with a axvline" 
> started by js...@fc... 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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