Phenonaut

Fixed
- Exclude pptx files from black formatting
- Dataset constructor raises an error if features passed as metadata are not of type list
- merged dataset deletion with passed datasets
- test using dataset_groupby, corrected to groupby_datasets

Fixed
- RandomForest regressor no longer uses auto max_features hyperparameter, making it compatible with scikit-learn 1.1 onwards.

Changed
- The way versioning works internally to Phenonaut.
- Updated pyproject.toml to include powerpoint templates

Added
- New class of Error NotEnoughRowsError added to better flag runtime errors.
- Added checks to mp_value_score which ensure grouped dataframe groups have at least 3 rows required for calculations.
- In mp_value_score, groups with < 3 rows may be ignored by calling the function with raise_error_for_low_count_groups = False, in which case np.nan values will be returned for the group.

Changed
- Improved tests for mp_value_score, checking for correct behaviour within small groups with <3 rows.

Changed
- Refactored package to use pyproject.toml for install/build
- Updated classifier hyperparameters, `max_features='auto'` has been deprecated in scikit 1.1 and will be removed in 1.3. Now explicitly set to `max_features='sqrt'`.
- Removed progressbar2 in favour of tqdm throughout.

Fixed
- predict.profile updated to work with newer pandas
- Phenonaut.merge_datasets now honours the remove_merged flag

Added
- random_state argument for percent replicating, allowing passing of a np.random.Generator, or an int to seed a new Generator