[MNT] Improve coverage for base package

[TonyBagnall]

Closes #955. Adds tests for BaseIntervalForest to improve coverage of aeon/base/_estimators/interval_based/base_interval_forest.py, targeting the many branches that were
previously untested.

Changes

• Changed the test test_autoets_uses_provided_seasonal_period() because the simulated data gives a perfect seasonal fit, causing numeric issues when numba is off. Could possibly be an edge case bug, but fix it to pass codecov for now.

All changes are in aeon/base/_estimators/interval_based/tests/test_base_interval_forest.py. No source code was modified. 21 new test functions were added covering:

• Invalid base_estimator (non-BaseEstimator input)
• Invalid series_transformers (string input; invalid item in list)
• Invalid n_intervals (wrong-length nested list; float type; unknown string; invalid inner/outer list items)
• Invalid min_interval_length / max_interval_length (list wrong length; invalid float item; invalid type)
• interval_features as a single callable
• interval_features as a nested list (callables, transformers, mixed)
• Invalid interval_features (wrong-length list; invalid type; invalid list items)
• Invalid att_subsample_size (int < 1; float > 1 or ≤ 0; invalid type; invalid list values)
• att_subsample_size as a per-series-transformer list (including None entries)
• att_subsample_size larger than the number of features (warning path)
• Invalid interval_selection_method (non-string; unknown string)
• Supervised selection with transformer interval_features (should raise)
• Invalid replace_nan; valid replace_nan with "nan" and numeric values
• time_limit_in_minutes > 0 contract path
• Regressor _predict path via IntervalForestRegressor
• fit_predict for regressor and fit_predict / fit_predict_proba for classifier
• temporal_importance_curves with return_dict=True and normalise_time_points=True
• temporal_importance_curves error cases (regressor; non-decision-tree base estimator)

All new tests use small synthetic datasets (make_example_3d_numpy) and minimal n_estimators to keep runtime fast.

[aeon-actions-bot]

Thank you for contributing to aeon

I have added the following labels to this PR based on the title: [ maintenance ].
I have added the following labels to this PR based on the changes made: [ forecasting ]. Feel free to change these if they do not properly represent the PR.

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• Disable numba cache loading
• Regenerate expected results for testing
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[hadifawaz1999]

LGTM, always good to improve coverage