Here is my modification.
Bbox = matplotlib.transforms.Bbox.from_bounds(.4, .1, .5, .3)
trans = ax.transAxes + fig.transFigure.inverted()
l, b, w, h = matplotlib.transforms.TransformedBbox(Bbox, trans).bounds
axins = fig.add_axes([l, b, w, h])
On Mon, Feb 23, 2009 at 2:49 PM, Johann Rohwer <j...@sun.ac.za> wrote:
> Johann Rohwer wrote:
>
> To answer my own question, after browsing the docstrings I came up with the
> following attached minimal script to illustrate a solution to the problem.
> However, it appears crufty. Specifically,
>
> 1. Can the fig.add_axes() call not take a transform directly as optional
> argument, like in fig.add_axes([.4, .1, .5, .3], transform=ax.transAxes)?
> This would appear the natural solution but does not work.
>
The axes position should be given in the normalized figure coordinates.
> 2. The transformed bounding box gives coordinates in points, necessitating
> the division by figure width and figure height to revert back to fractional
> coordinates.
With my modification, you don't need this anymore.
>
> 3. Re-calculating [l, b, w, h] from tBbox seems cumbersome. Can the
> add_axes() not call a Bbox instance directly?
Also see my modification.
I'm sorry but I don't understand what you mean by "add_axes() not call
a Bbox instance directly?".
IHTH,
-JJ
>
> I'm sure I'm missing something obvious but don't have the time to delve into
> the transforms sourcecode, so any pointer is appreciated :-)
>
> Johann
>
>
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-OSBC tackles the biggest issue in open source: Open Sourcing the Enterprise
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