introduce MockTransformer to be a placeholder during deprecation

aeon/testing/mock_estimators/__init__.py

@@ -15,6 +15,7 @@
     "MockMultivariateSeriesTransformer",
     "MockSeriesTransformerNoFit",
     "MockUnivariateSeriesTransformer",
+    "MockTransformer",
 ]
 
 from aeon.testing.mock_estimators._mock_classifiers import (
@@ -41,3 +42,4 @@
     MockSeriesTransformerNoFit,
     MockUnivariateSeriesTransformer,
 )
+from aeon.testing.mock_estimators._mock_transformers import MockTransformer

aeon/testing/mock_estimators/_mock_transformers.py

@@ -0,0 +1,53 @@
+from aeon.transformations.base import BaseTransformer
+
+
+class MockTransformer(BaseTransformer):
+    """Mock transformer to alter data.
+
+    Parameters
+    ----------
+    power : int or float, default=0.5
+        The power to raise the input timeseries to.
+
+    Attributes
+    ----------
+    power : int or float
+        User supplied power.
+
+    offset : int or float, or iterable.
+        User supplied offset value.
+        Scalar or 1D iterable with as many values as X columns in transform.
+    """
+
+    _tags = {
+        "input_data_type": "Series",
+        # what is the abstract type of X: Series, or Panel
+        "output_data_type": "Series",
+        "X_inner_type": ["pd.DataFrame", "pd.Series"],
+        "fit_is_empty": True,
+        "transform-returns-same-time-index": True,
+        "capability:multivariate": True,
+        "capability:inverse_transform": True,
+    }
+
+    def __init__(self, power=0.5):
+        self.power = power
+
+        if not isinstance(self.power, (int, float)):
+            raise ValueError(
+                f"Expected `power` to be int or float, but found {type(self.power)}."
+            )
+        super().__init__()
+
+    def _transform(self, X, y=None):
+        """Transform X and return a transformed version."""
+        return X.pow(self.power)
+
+    def _inverse_transform(self, X, y=None):
+        """Reverse transformation on `X`."""
+        return X.pow(1.0 / self.power)
+
+    @classmethod
+    def get_test_params(cls, parameter_set="default"):
+        """Return testing parameter settings for the estimator."""
+        return {"power": 2.5, "offset": 1}

aeon/transformations/compose.py

@@ -102,9 +102,9 @@ class TransformerPipeline(_HeterogenousMetaEstimator, BaseTransformer):
 
     Examples
     --------
-    >>> from aeon.transformations.exponent import ExponentTransformer
-    >>> t1 = ExponentTransformer(power=2)
-    >>> t2 = ExponentTransformer(power=0.5)
+    >>> from aeon.testing.mock_estimators import MockTransformer
+    >>> t1 = MockTransformer(power=2)
+    >>> t2 = MockTransformer(power=0.5)
 
         Example 1, option A: construct without strings (unique names are generated for
         the two components t1 and t2)