Bug summary

The current implementation seems to assume that the lower leftll, upper leftul, and lower rightlr corners are preserved under transformation. This need not be the case. For example, an affine transformation that simply switches coordinates produces a wrong result.

Code for reproduction

importnumpyasnpfrommatplotlib.transformsimportAffine2D,Bbox# Switch 'x' and 'y' coordinatesT=Affine2D(np.array([          [0,1,0],          [1,0,0],          [0,0,1]        ])      )# Unit vectorspts=np.array([  [1,0],  [0,1]])# Produce a Bbox from the unit vectorsbb=Bbox.null()bb.update_from_data_xy(pts)# Resultbb.transformed(T )

Actual outcome

In [84]: bb.transformed( T )Out[84]: Bbox([[0.0, 0.0], [0.0, 0.0]])

Expected outcome

bb.transformed( T ).height == 1.0bb.transformed( T ).width == 1.0

Additional information

The current implementation (v3.8.0) seems to assume that the lower leftll, upper leftul, and lower rightlr corners are preserved under transformation. A more general solution should probably transform each corner and fully recompute the bounding box.

Operating system

linux

Matplotlib Version

3.8.0

Matplotlib Backend

TkAgg

Python version

3.11.5

Jupyter version

No response

Installation

pip