Added the improvements to _base and _base_series

aeon/base/_base.py

@@ -1,4 +1,34 @@
-"""Base class template for aeon estimators."""
+"""Base class template for aeon estimators.
+
+BaseAeonEstimator: Base class for aeon estimators.
+
+Main Features:
+- Provides a standard framework for defining estimators in aeon.
+- Manages estimator state, cloning, and dynamic tagging.
+
+Key Methods:
+- `reset(keep)`: Resets the estimator while preserving specific attributes.
+- `clone(random_state)`: Creates a copy of the estimator.
+- `get_class_tags() / get_class_tag(tag_name)`: Retrieves static class tags.
+- `get_tags() / get_tag(tag_name)`: Retrieves both static and dynamic tags.
+- `set_tags(**tag_dict)`: Modifies dynamic tags.
+- `get_fitted_params(deep)`: Extracts fitted parameters from the estimator.
+- `_check_is_fitted()`: Ensures the estimator is fitted before use.
+- `_create_test_instance()`: Generates test instances for validation.
+
+Attributes:
+- `is_fitted`: Boolean flag indicating if `fit()` has been called.
+- `_tags`: Dictionary containing static metadata about the estimator.
+- `_tags_dynamic`: Dictionary for dynamic metadata modifications.
+
+Sklearn Compatibility:
+- Overrides `__sklearn_is_fitted__()` for compatibility.
+- `_validate_data()` and `get_metadata_routing()` raise NotImplementedError.
+
+Helper Functions:
+- `_clone_estimator(base_estimator, random_state)`: Clones an estimator.
+"""
+
 
 __maintainer__ = ["MatthewMiddlehurst", "TonyBagnall"]
 __all__ = ["BaseAeonEstimator"]

aeon/base/_base_series.py

@@ -1,9 +1,33 @@
-"""Base class for estimators that fit single time series.
+"""
+Base class for estimators that fit single time series.
+
+This time series can be univariate or multivariate, with potential missing values.
+
+Class Name:
+    BaseSeriesEstimator
+
+Defining Methods:
+    - _preprocess_series(self, X, axis, store_metadata)
+      Preprocesses input X before calling fit, ensuring it is in a valid format.
+    
+    - _check_X(self, X, axis)
+      Validates input X, checking type, multivariate/univariate structure, and missing values.
+    
+    - _convert_X(self, X, axis)
+      Converts input X to the required internal format based on estimator tags.
+
+Inherited Methods:
+    - get_params(): Returns hyper-parameter details.
+    - get_fitted_params(): Returns fitted model parameters.
+
+State Attributes:
+    - metadata_: Stores metadata about input time series.
+    - axis: Determines the time point axis for input data.
+    - _tags: Dictionary defining estimator capabilities (e.g., univariate, multivariate support).
 
-This time series can be univariate or multivariate. The time series can potentially
-contain missing values.
 """
 
+
 __maintainer__ = ["TonyBagnall", "MatthewMiddlehurst"]
 __all__ = ["BaseSeriesEstimator"]