Addresses issue #23129: Fixed log scale order dependency when using Collections

[Gerson-M-Ferreira]

This PR attempts to resolve issue #23129, in which there is an order dependency when using logaritmic scales and a Collection as data.

PR summary

Error Description

The error in axis computation originates from the add_collection() method within the _AxesBase class (found in lib/matplotlib/axes/_base.py). Specifically, the issue lies in how the axis limits are computed.

datalim = collection.get_datalim(self.transData)

Analysis

Further investigation into the get_datalim() method in the Collection class (lib/matplotlib/collections.py) reveals that data limits are influenced by a non-affine transformation:

    if not transform.is_affine:
        paths = [transform.transform_path_non_affine(p) for p in paths]

In scenarios where the axis scale is set after adding the data collection, and so the log scale is not yet applied, the data limits are computed as if the data were affine, and yet the correct behavior is achieved. In other words, the shape of the data should not impact bounding limit computation. Therefore, the non-affine transformation is not only unnecessary but also detrimental, as it produces inaccurate results, and its removal solves the issue.

Unit Test

Finnaly, a unit test was added, test_collection_log_datalim_order_dependency() (to lib/matplotlib/tests/test_collections.py), which validates the order dependency, ensuring the correctness of the fix.

PR checklist

• "closes [Bug]: Autoscaling incorrect when scale set before adding collection #23129"
• new and changed code is tested
• Plotting related features are demonstrated in an example
• [N/A] New Features and API Changes are noted with a directive and release note
• [N/A] Documentation complies with general and docstring guidelines

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[Gerson-M-Ferreira]

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