Merge branch 'fix/inconsistent-double-quotes' of https://github.com/A…

…naghDeshpande/aeon into fix/inconsistent-double-quotes

aeon/anomaly_detection/_cblof.py

@@ -16,8 +16,8 @@ class CBLOF(PyODAdapter):
 
     This class implements the CBLOF algorithm for anomaly detection
     using PyODAdadpter to be used in the aeon framework. All parameters are passed to
-    the PyOD model ``CBLOF`` except for ``window_size`` and ``stride``, which are used
-    to construct the sliding windows.
+    the PyOD model ``CBLOF`` except for ``window_size`` and ``stride``,
+    which are used to construct the sliding windows.
 
     The documentation for parameters has been adapted from the `PyOD documentation`_.
     .. _pyod_docs: https://pyod.readthedocs.io/en/latest/pyod.models.html#id117
@@ -143,9 +143,9 @@ def _get_test_params(cls, parameter_set="default"):
         params : dict
             Parameters to create testing instances of the class.
             Each dict are parameters to construct an "interesting" test instance, i.e.,
-            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid
-            test instance.
-            ``create_test_instance`` uses the first (or only) dictionary in ``params``.
+            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test
+            instance. ``create_test_instance`` uses the first (or only) dictionary
+            in ``params``.
         """
         return {
             "n_clusters": 4,

aeon/anomaly_detection/_copod.py

@@ -73,7 +73,8 @@ def _get_test_params(cls, parameter_set="default") -> dict:
         params : dict or list of dict, default={}
             Parameters to create testing instances of the class.
             Each dict are parameters to construct an "interesting" test instance, i.e.,
-            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test instance.
-            ``create_test_instance`` uses the first (or only) dictionary in ``params``.
+            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test
+            instance. ``create_test_instance`` uses the first (or only) dictionary
+            in ``params``.
         """
         return {}

aeon/anomaly_detection/_iforest.py

@@ -16,8 +16,8 @@ class IsolationForest(PyODAdapter):
 
     This class implements the Isolation Forest algorithm for anomaly detection
     using PyODAdadpter to be used in the aeon framework. All parameters are passed to
-    the PyOD model ``IForest`` except for ``window_size`` and ``stride``, which are used
-    to construct the sliding windows.
+    the PyOD model ``IForest`` except for ``window_size`` and ``stride``,
+    which are used to construct the sliding windows.
 
     The documentation for parameters has been adapted from the
     [PyOD documentation](https://pyod.readthedocs.io/en/latest/pyod.models.html#id405).

aeon/anomaly_detection/_kmeans.py

@@ -175,7 +175,8 @@ def _get_test_params(cls, parameter_set="default"):
         dict or list of dict, default={}
             Parameters to create testing instances of the class.
             Each dict are parameters to construct an "interesting" test instance, i.e.,
-            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test instance.
+            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid
+            test instance.
         """
         return {
             "n_clusters": 5,

aeon/anomaly_detection/_merlin.py

@@ -212,6 +212,7 @@ def _get_test_params(cls, parameter_set="default"):
         params : dict or list of dict, default={}
             Parameters to create testing instances of the class.
             Each dict are parameters to construct an "interesting" test instance, i.e.,
-            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test instance.
+            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid
+            test instance.
         """
         return {"min_length": 4, "max_length": 7}

aeon/anomaly_detection/_one_class_svm.py

@@ -16,8 +16,8 @@ class OneClassSVM(BaseAnomalyDetector):
 
     This class implements the OneClassSVM algorithm for anomaly detection
     from sklearn to be used in the aeon framework. All parameters are passed to
-    the sklearn ``OneClassSVM`` except for ``window_size`` and ``stride``, which are
-    used to construct the sliding windows.
+    the sklearn ``OneClassSVM`` except for ``window_size`` and ``stride``,
+    which are used to construct the sliding windows.
 
     The documentation for parameters has been adapted from
     (https://scikit-learn.org/dev/modules/generated/sklearn.svm.OneClassSVM.html).

aeon/anomaly_detection/_pyodadapter.py

@@ -162,7 +162,8 @@ def _get_test_params(cls, parameter_set="default"):
         params : dict or list of dict, default={}
             Parameters to create testing instances of the class.
             Each dict are parameters to construct an "interesting" test instance, i.e.,
-            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid test instance.
+            ``MyClass(**params)`` or ``MyClass(**params[i])`` creates a valid
+            test instance.
         """
         _check_soft_dependencies(*cls._tags["python_dependencies"])
 

aeon/transformations/series/__init__.py

@@ -6,8 +6,10 @@
     "ClaSPTransformer",
     "DFTSeriesTransformer",
     "Dobin",
+    "ExpSmoothingSeriesTransformer",
     "GaussSeriesTransformer",
     "MatrixProfileSeriesTransformer",
+    "MovingAverageSeriesTransformer",
     "PLASeriesTransformer",
     "SGSeriesTransformer",
     "StatsModelsACF",
@@ -31,8 +33,10 @@
 from aeon.transformations.series._clasp import ClaSPTransformer
 from aeon.transformations.series._dft import DFTSeriesTransformer
 from aeon.transformations.series._dobin import Dobin
+from aeon.transformations.series._exp_smoothing import ExpSmoothingSeriesTransformer
 from aeon.transformations.series._gauss import GaussSeriesTransformer
 from aeon.transformations.series._matrix_profile import MatrixProfileSeriesTransformer
+from aeon.transformations.series._moving_average import MovingAverageSeriesTransformer
 from aeon.transformations.series._pca import PCASeriesTransformer
 from aeon.transformations.series._pla import PLASeriesTransformer
 from aeon.transformations.series._scaled_logit import ScaledLogitSeriesTransformer

docs/api_reference/transformations.rst

@@ -165,8 +165,10 @@ Series transforms
     ClaSPTransformer
     DFTSeriesTransformer
     Dobin
+    ExpSmoothingSeriesTransformer
     GaussSeriesTransformer
     MatrixProfileSeriesTransformer
+    MovingAverageSeriesTransformer
     PLASeriesTransformer
     SGSeriesTransformer
     StatsModelsACF