Bug summary

ax.transData does not honor xlim and ylim. The document at https://matplotlib.org/stable/users/explain/artists/transforms_tutorial.html#data-coordinates seems to suggest that data limits are updated automatically when new data are added to the axes, but it's not the case, which breaks ax.transData, since it reads an old version of data limits.

Code for reproduction

from matplotlib import pyplot as plt

fig, ax = plt.subplots(figsize=(10, 10), dpi=100)
print(f"fig size: {fig.get_size_inches() * fig.dpi}")

ax.plot([0, 10], [0, 10], 'o')

print(f"(10, 10) in data coordinates: {ax.transData.transform((10, 10))}")

ax.set_xlim(ax.get_xlim())  # just ax.get_xlim() or ax.viewLim or ax.autoscale_view() is enough
ax.set_ylim(ax.get_ylim())

print(f"(10, 10) in data coordinates: {ax.transData.transform((10, 10))}")

Actual outcome

fig size: [1000. 1000.]
(10, 10) in data coordinates: [7875. 7810.]
(10, 10) in data coordinates: [864.77272727 845. ]

Expected outcome

fig size: [1000. 1000.]
(10, 10) in data coordinates: [864.77272727 845. ]
(10, 10) in data coordinates: [864.77272727 845. ]

Additional information

The wording from https://matplotlib.org/stable/users/explain/artists/transforms_tutorial.html#data-coordinates suggests that data limits are updated automatically when new data are added, but it requires manual trigger of set_xlim/set_ylim (or get_xlim/get_ylim which calls ax.viewLim).

This is quite confusing. I would hope that either the documentation is updated to notify the user to explicitly update the data limits, or even better, let transData/transLimits always use the latest data limits.

Operating system

No response

Matplotlib Version

3.8.3

Matplotlib Backend

No response

Python version

No response

Jupyter version

No response

Installation

None