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[REF] Refactor Anomaly Detection Module into Submodules by Algorithm Family (#2694)
* Refactor Anomaly Detection Module into Submodules by Algorithm Family * updated documentation and references * implemented suggested changes * minor changes * added headers for remaining algorithm family * removing tree-based header
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Diff for: ‎aeon/anomaly_detection/__init__.py

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@@ -1,31 +1,7 @@
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"""Time Series Anomaly Detection."""
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__all__ = [
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"CBLOF",
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"COPOD",
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"DWT_MLEAD",
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"IsolationForest",
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"KMeansAD",
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"LeftSTAMPi",
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"LOF",
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"MERLIN",
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"OneClassSVM",
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"ROCKAD",
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"PyODAdapter",
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"STOMP",
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"STRAY",
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"BaseAnomalyDetector",
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]
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from aeon.anomaly_detection._cblof import CBLOF
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from aeon.anomaly_detection._copod import COPOD
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from aeon.anomaly_detection._dwt_mlead import DWT_MLEAD
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from aeon.anomaly_detection._iforest import IsolationForest
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from aeon.anomaly_detection._kmeans import KMeansAD
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from aeon.anomaly_detection._left_stampi import LeftSTAMPi
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from aeon.anomaly_detection._lof import LOF
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from aeon.anomaly_detection._merlin import MERLIN
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from aeon.anomaly_detection._one_class_svm import OneClassSVM
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from aeon.anomaly_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection._rockad import ROCKAD
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from aeon.anomaly_detection._stomp import STOMP
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from aeon.anomaly_detection._stray import STRAY
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from aeon.anomaly_detection.base import BaseAnomalyDetector

Diff for: ‎aeon/anomaly_detection/distance_based/__init__.py

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"""Distance basedTime Series Anomaly Detection."""
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__all__ = [
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"CBLOF",
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"KMeansAD",
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"LeftSTAMPi",
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"LOF",
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"MERLIN",
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"OneClassSVM",
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"STOMP",
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]
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from aeon.anomaly_detection.distance_based._cblof import CBLOF
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from aeon.anomaly_detection.distance_based._kmeans import KMeansAD
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from aeon.anomaly_detection.distance_based._left_stampi import LeftSTAMPi
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from aeon.anomaly_detection.distance_based._lof import LOF
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from aeon.anomaly_detection.distance_based._merlin import MERLIN
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from aeon.anomaly_detection.distance_based._one_class_svm import OneClassSVM
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from aeon.anomaly_detection.distance_based._stomp import STOMP

Diff for: ‎aeon/anomaly_detection/_cblof.py renamed to ‎aeon/anomaly_detection/distance_based/_cblof.py

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@@ -7,7 +7,7 @@
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import numpy as np
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from aeon.anomaly_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection.outlier_detection._pyodadapter import PyODAdapter
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/_kmeans.py renamed to ‎aeon/anomaly_detection/distance_based/_kmeans.py

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@@ -65,7 +65,7 @@ class KMeansAD(BaseAnomalyDetector):
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Examples
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--------
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>>> import numpy as np
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>>> from aeon.anomaly_detection import KMeansAD
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>>> from aeon.anomaly_detection.distance_based import KMeansAD
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>>> X = np.array([1, 2, 3, 4, 1, 2, 3, 3, 2, 8, 9, 8, 1, 2, 3, 4], dtype=np.float64)
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>>> detector = KMeansAD(n_clusters=3, window_size=4, stride=1, random_state=0)
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>>> detector.fit_predict(X)

Diff for: ‎aeon/anomaly_detection/_left_stampi.py renamed to ‎aeon/anomaly_detection/distance_based/_left_stampi.py

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@@ -44,7 +44,7 @@ class LeftSTAMPi(BaseAnomalyDetector):
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Internally,this is applying the incremental approach outlined below.
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>>> import numpy as np # doctest: +SKIP
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>>> from aeon.anomaly_detection import LeftSTAMPi # doctest: +SKIP
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>>> from aeon.anomaly_detection.distance_based import LeftSTAMPi # doctest: +SKIP
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>>> X = np.random.default_rng(42).random((10)) # doctest: +SKIP
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>>> detector = LeftSTAMPi(window_size=3, n_init_train=3) # doctest: +SKIP
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>>> detector.fit_predict(X) # doctest: +SKIP

Diff for: ‎aeon/anomaly_detection/_lof.py renamed to ‎aeon/anomaly_detection/distance_based/_lof.py

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import numpy as np
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from aeon.anomaly_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection.outlier_detection._pyodadapter import PyODAdapter
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/_merlin.py renamed to ‎aeon/anomaly_detection/distance_based/_merlin.py

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@@ -43,7 +43,7 @@ class MERLIN(BaseAnomalyDetector):
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Examples
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--------
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>>> import numpy as np
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>>> from aeon.anomaly_detection import MERLIN
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>>> from aeon.anomaly_detection.distance_based import MERLIN
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>>> X = np.array([1, 2, 3, 4, 1, 2, 3, 4, 2, 3, 4, 5, 1, 2, 3, 4])
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>>> detector = MERLIN(min_length=4, max_length=5)
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>>> detector.fit_predict(X)

Diff for: ‎aeon/anomaly_detection/_one_class_svm.py renamed to ‎aeon/anomaly_detection/distance_based/_one_class_svm.py

File renamed without changes.

Diff for: ‎aeon/anomaly_detection/_stomp.py renamed to ‎aeon/anomaly_detection/distance_based/_stomp.py

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@@ -38,7 +38,7 @@ class STOMP(BaseAnomalyDetector):
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Examples
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--------
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>>> import numpy as np
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>>> from aeon.anomaly_detection import STOMP # doctest: +SKIP
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>>> from aeon.anomaly_detection.distance_based import STOMP # doctest: +SKIP
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>>> X = np.random.default_rng(42).random((10, 2), dtype=np.float64)
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>>> detector = STOMP(X, window_size=2) # doctest: +SKIP
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>>> detector.fit_predict(X, axis=0) # doctest: +SKIP

Diff for: ‎aeon/anomaly_detection/distance_based/tests/__init__.py

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"""Distance based test code."""

Diff for: ‎aeon/anomaly_detection/tests/test_cblof.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_cblof.py

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import numpy as np
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import pytest
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from aeon.anomaly_detection import CBLOF
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from aeon.anomaly_detection.distance_based import CBLOF
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from aeon.testing.data_generation import make_example_1d_numpy
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_kmeans.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_kmeans.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import KMeansAD
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from aeon.anomaly_detection.distance_based import KMeansAD
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def test_kmeansad_univariate():

Diff for: ‎aeon/anomaly_detection/tests/test_left_stampi.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_left_stampi.py

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import numpy as np
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import pytest
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from aeon.anomaly_detection._left_stampi import LeftSTAMPi
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from aeon.anomaly_detection.distance_based._left_stampi import LeftSTAMPi
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from aeon.testing.data_generation import make_example_1d_numpy
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_lof.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_lof.py

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import numpy as np
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import pytest
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from aeon.anomaly_detection import LOF
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from aeon.anomaly_detection.distance_based import LOF
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from aeon.testing.data_generation import make_example_1d_numpy
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_merlin.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_merlin.py

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import numpy as np
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from aeon.anomaly_detection import MERLIN
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from aeon.anomaly_detection.distance_based import MERLIN
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TEST_DATA = np.array(
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[

Diff for: ‎aeon/anomaly_detection/tests/test_one_class_svm.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_one_class_svm.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import OneClassSVM
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from aeon.anomaly_detection.distance_based import OneClassSVM
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def test_one_class_svm_univariate():

Diff for: ‎aeon/anomaly_detection/tests/test_stomp.py renamed to ‎aeon/anomaly_detection/distance_based/tests/test_stomp.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import STOMP
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from aeon.anomaly_detection.distance_based import STOMP
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/distribution_based/__init__.py

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"""Distribution based Time Series Anomaly Detection."""
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__all__ = [
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"COPOD",
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"DWT_MLEAD",
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]
7+
8+
from aeon.anomaly_detection.distribution_based._copod import COPOD
9+
from aeon.anomaly_detection.distribution_based._dwt_mlead import DWT_MLEAD

Diff for: ‎aeon/anomaly_detection/_copod.py renamed to ‎aeon/anomaly_detection/distribution_based/_copod.py

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import numpy as np
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from aeon.anomaly_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection.outlier_detection._pyodadapter import PyODAdapter
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/_dwt_mlead.py renamed to ‎aeon/anomaly_detection/distribution_based/_dwt_mlead.py

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@@ -78,7 +78,7 @@ class DWT_MLEAD(BaseAnomalyDetector):
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Examples
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--------
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>>> import numpy as np
81-
>>> from aeon.anomaly_detection import DWT_MLEAD
81+
>>> from aeon.anomaly_detection.distribution_based import DWT_MLEAD
8282
>>> X = np.array([1, 2, 3, 4, 1, 2, 3, 3, 2, 8, 9, 8, 1, 2, 3, 4], dtype=np.float64)
8383
>>> detector = DWT_MLEAD(
8484
... start_level=1, quantile_boundary_type='percentile', quantile_epsilon=0.01

Diff for: ‎aeon/anomaly_detection/distribution_based/tests/__init__.py

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"""Distribution based test code."""

Diff for: ‎aeon/anomaly_detection/tests/test_copod.py renamed to ‎aeon/anomaly_detection/distribution_based/tests/test_copod.py

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import numpy as np
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import pytest
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from aeon.anomaly_detection import COPOD
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from aeon.anomaly_detection.distribution_based import COPOD
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from aeon.testing.data_generation import make_example_1d_numpy
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_dwt_mlead.py renamed to ‎aeon/anomaly_detection/distribution_based/tests/test_dwt_mlead.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import DWT_MLEAD
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from aeon.anomaly_detection.distribution_based import DWT_MLEAD
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def test_dwt_mlead_output():

Diff for: ‎aeon/anomaly_detection/outlier_detection/__init__.py

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"""Time Series Outlier Detection."""
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__all__ = [
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"IsolationForest",
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"PyODAdapter",
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"STRAY",
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]
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from aeon.anomaly_detection.outlier_detection._iforest import IsolationForest
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from aeon.anomaly_detection.outlier_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection.outlier_detection._stray import STRAY

Diff for: ‎aeon/anomaly_detection/_iforest.py renamed to ‎aeon/anomaly_detection/outlier_detection/_iforest.py

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import numpy as np
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from aeon.anomaly_detection._pyodadapter import PyODAdapter
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from aeon.anomaly_detection.outlier_detection._pyodadapter import PyODAdapter
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/_pyodadapter.py renamed to ‎aeon/anomaly_detection/outlier_detection/_pyodadapter.py

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--------
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>>> import numpy as np
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>>> from pyod.models.lof import LOF # doctest: +SKIP
62-
>>> from aeon.anomaly_detection import PyODAdapter # doctest: +SKIP
62+
>>> from aeon.anomaly_detection.outlier_detection import (
63+
... PyODAdapter
64+
... ) # doctest: +SKIP
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>>> X = np.random.default_rng(42).random((10, 2), dtype=np.float64)
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>>> detector = PyODAdapter(LOF(), window_size=2) # doctest: +SKIP
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>>> detector.fit_predict(X, axis=0) # doctest: +SKIP

Diff for: ‎aeon/anomaly_detection/_stray.py renamed to ‎aeon/anomaly_detection/outlier_detection/_stray.py

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Examples
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--------
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>>> from aeon.anomaly_detection import STRAY
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>>> from aeon.anomaly_detection.outlier_detection import STRAY
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>>> from aeon.datasets import load_airline
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>>> import numpy as np
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>>> X = load_airline()

Diff for: ‎aeon/anomaly_detection/outlier_detection/tests/__init__.py

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"""Outlier based test code."""

Diff for: ‎aeon/anomaly_detection/tests/test_iforest.py renamed to ‎aeon/anomaly_detection/outlier_detection/tests/test_iforest.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import IsolationForest
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from aeon.anomaly_detection.outlier_detection import IsolationForest
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_pyod_adapter.py renamed to ‎aeon/anomaly_detection/outlier_detection/tests/test_pyod_adapter.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import PyODAdapter
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from aeon.anomaly_detection.outlier_detection import PyODAdapter
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from aeon.utils.validation._dependencies import _check_soft_dependencies
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Diff for: ‎aeon/anomaly_detection/tests/test_stray.py renamed to ‎aeon/anomaly_detection/outlier_detection/tests/test_stray.py

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import numpy as np
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from sklearn.preprocessing import MinMaxScaler
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from aeon.anomaly_detection import STRAY
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from aeon.anomaly_detection.outlier_detection import STRAY
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def test_default_1D():

Diff for: ‎aeon/anomaly_detection/whole_series/__init__.py

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"""Whole Time Series Anomaly Detection."""
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__all__ = [
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"ROCKAD",
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]
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from aeon.anomaly_detection.whole_series._rockad import ROCKAD

Diff for: ‎aeon/anomaly_detection/_rockad.py renamed to ‎aeon/anomaly_detection/whole_series/_rockad.py

File renamed without changes.

Diff for: ‎aeon/anomaly_detection/whole_series/tests/__init__.py

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"""Whole series anomaly detection tests."""

Diff for: ‎aeon/anomaly_detection/tests/test_rockad.py renamed to ‎aeon/anomaly_detection/whole_series/tests/test_rockad.py

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import pytest
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from sklearn.utils import check_random_state
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from aeon.anomaly_detection import ROCKAD
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from aeon.anomaly_detection.whole_series import ROCKAD
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def test_rockad_univariate():

Diff for: ‎docs/api_reference/anomaly_detection.rst

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format, and learning type as an overview table in its documentation. Some detectors
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support multiple learning types.
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Detectors
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---------
16+
.. note::
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19-
.. currentmodule:: aeon.anomaly_detection
18+
Not all algorithm families are currently implemented. The documentation includes
19+
placeholders for planned categories which will be supported in future.
20+
21+
Distance-based
22+
--------------
23+
24+
.. currentmodule:: aeon.anomaly_detection.distance_based
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.. autosummary::
2227
:toctree: auto_generated/
2328
:template: class.rst
2429

2530
CBLOF
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COPOD
27-
DWT_MLEAD
28-
IsolationForest
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KMeansAD
3032
LeftSTAMPi
3133
LOF
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MERLIN
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OneClassSVM
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PyODAdapter
35-
ROCKAD
3636
STOMP
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38+
Distribution-based
39+
-----------------
40+
41+
.. currentmodule:: aeon.anomaly_detection.distribution_based
42+
43+
.. autosummary::
44+
:toctree: auto_generated/
45+
:template: class.rst
46+
47+
COPOD
48+
DWT_MLEAD
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50+
Encoding-based
51+
--------------
52+
53+
The algorithms for this family are not implemented yet.
54+
55+
Forecasting-based
56+
-----------------
57+
58+
The algorithms for this family are not implemented yet.
59+
60+
Outlier-Detection
61+
-----------------
62+
63+
.. currentmodule:: aeon.anomaly_detection.outlier_detection
64+
65+
.. autosummary::
66+
:toctree: auto_generated/
67+
:template: class.rst
68+
69+
IsolationForest
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PyODAdapter
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STRAY
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73+
Reconstruction-based
74+
--------------------
75+
76+
The algorithms for this family are not implemented yet.
77+
78+
Whole-Series
79+
------------
80+
81+
.. currentmodule:: aeon.anomaly_detection.whole_series
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83+
.. autosummary::
84+
:toctree: auto_generated/
85+
:template: class.rst
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ROCKAD
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Base
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----
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