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MatthewMiddlehurstMatthewMiddlehurst
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[ENH,REF] Unequal length collection transforms (#2903)
* move and update unequal transforms * unequal transforms * comment * better sorting * extra transform test * changes for review
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33 files changed

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‎.github/workflows/pr_examples.yml

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name: PR Examples
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name: PR examples
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on:
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push:

‎aeon/classification/compose/_pipeline.py

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@@ -61,14 +61,14 @@ class ClassifierPipeline(BaseCollectionPipeline, BaseClassifier):
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Examples
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--------
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>>> from aeon.transformations.collection import Resizer
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>>> from aeon.transformations.collection.unequal_length import Resizer
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>>> from aeon.classification.convolution_based import RocketClassifier
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>>> from aeon.datasets import load_unit_test
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>>> from aeon.classification.compose import ClassifierPipeline
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>>> X_train, y_train = load_unit_test(split="train")
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>>> X_test, y_test = load_unit_test(split="test")
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>>> pipeline = ClassifierPipeline(
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... Resizer(length=10), RocketClassifier(n_kernels=50)
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... Resizer(resized_length=10), RocketClassifier(n_kernels=50)
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... )
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>>> pipeline.fit(X_train, y_train)
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ClassifierPipeline(...)
@@ -104,8 +104,8 @@ def _get_test_params(cls, parameter_set="default"):
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`MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
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"""
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from aeon.classification.distance_based import KNeighborsTimeSeriesClassifier
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from aeon.transformations.collection import Truncator
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from aeon.transformations.collection.feature_based import SevenNumberSummary
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from aeon.transformations.collection.unequal_length import Truncator
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return {
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"transformers": [

‎aeon/classification/compose/tests/test_pipeline.py

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@@ -21,22 +21,22 @@
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AutocorrelationFunctionTransformer,
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HOG1DTransformer,
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Normalizer,
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Padder,
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Tabularizer,
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)
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from aeon.transformations.collection.feature_based import SevenNumberSummary
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from aeon.transformations.collection.unequal_length import Padder
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@pytest.mark.parametrize(
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"transformers",
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
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SevenNumberSummary(),
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[Padder(pad_length=15), Tabularizer(), StandardScaler()],
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[Padder(pad_length=15), SevenNumberSummary()],
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[Padder(padded_length=15), Tabularizer(), StandardScaler()],
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[Padder(padded_length=15), SevenNumberSummary()],
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[Tabularizer(), StandardScaler(), SevenNumberSummary()],
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
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SevenNumberSummary(),
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],
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],
@@ -67,14 +67,14 @@ def test_classifier_pipeline(transformers):
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@pytest.mark.parametrize(
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"transformers",
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[
70-
[Padder(pad_length=15), Tabularizer()],
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[Padder(padded_length=15), Tabularizer()],
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SevenNumberSummary(),
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[Tabularizer(), StandardScaler()],
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[Padder(pad_length=15), Tabularizer(), StandardScaler()],
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[Padder(pad_length=15), SevenNumberSummary()],
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[Padder(padded_length=15), Tabularizer(), StandardScaler()],
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[Padder(padded_length=15), SevenNumberSummary()],
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[Tabularizer(), StandardScaler(), SevenNumberSummary()],
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
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SevenNumberSummary(),
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],
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],

‎aeon/classification/tests/test_sklearn_compatability.py

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@@ -35,7 +35,7 @@
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from aeon.classification.interval_based import CanonicalIntervalForestClassifier
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from aeon.testing.data_generation import make_example_3d_numpy
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from aeon.transformations.collection import Resizer
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from aeon.transformations.collection.unequal_length import Resizer
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# StratifiedGroupKFold(n_splits=2), removed because it is not available in sklearn 0.24
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CROSS_VALIDATION_METHODS = [
@@ -60,7 +60,7 @@
6060
COMPOSITE_ESTIMATORS = [
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Pipeline(
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[
63-
("transform", Resizer(length=10)),
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("transform", Resizer(resized_length=10)),
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("clf", CanonicalIntervalForestClassifier._create_test_instance()),
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]
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),

‎aeon/clustering/compose/_pipeline.py

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Original file line numberDiff line numberDiff line change
@@ -60,14 +60,14 @@ class ClustererPipeline(BaseCollectionPipeline, BaseClusterer):
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Examples
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--------
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>>> from aeon.transformations.collection import Resizer
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>>> from aeon.transformations.collection.unequal_length import Resizer
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>>> from aeon.clustering import TimeSeriesKMeans
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>>> from aeon.datasets import load_unit_test
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>>> from aeon.clustering.compose import ClustererPipeline
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>>> X_train, y_train = load_unit_test(split="train")
6868
>>> X_test, y_test = load_unit_test(split="test")
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>>> pipeline = ClustererPipeline(
70-
... Resizer(length=10), TimeSeriesKMeans._create_test_instance()
70+
... Resizer(resized_length=10), TimeSeriesKMeans._create_test_instance()
7171
... )
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>>> pipeline.fit(X_train, y_train)
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ClustererPipeline(...)
@@ -108,8 +108,8 @@ def _get_test_params(cls, parameter_set="default"):
108108
`MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
109109
"""
110110
from aeon.clustering import TimeSeriesKMeans
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from aeon.transformations.collection import Truncator
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from aeon.transformations.collection.feature_based import SevenNumberSummary
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from aeon.transformations.collection.unequal_length import Truncator
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return {
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"transformers": [

‎aeon/clustering/compose/tests/test_pipeline.py

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@@ -19,22 +19,22 @@
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AutocorrelationFunctionTransformer,
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HOG1DTransformer,
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Normalizer,
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Padder,
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Tabularizer,
2423
)
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from aeon.transformations.collection.feature_based import SevenNumberSummary
25+
from aeon.transformations.collection.unequal_length import Padder
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2727

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@pytest.mark.parametrize(
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"transformers",
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
3232
SevenNumberSummary(),
33-
[Padder(pad_length=15), Tabularizer(), StandardScaler()],
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[Padder(pad_length=15), SevenNumberSummary()],
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[Padder(padded_length=15), Tabularizer(), StandardScaler()],
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[Padder(padded_length=15), SevenNumberSummary()],
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[Tabularizer(), StandardScaler(), SevenNumberSummary()],
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
3838
SevenNumberSummary(),
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],
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],
@@ -66,14 +66,14 @@ def test_clusterer_pipeline(transformers):
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@pytest.mark.parametrize(
6767
"transformers",
6868
[
69-
[Padder(pad_length=15), Tabularizer()],
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[Padder(padded_length=15), Tabularizer()],
7070
SevenNumberSummary(),
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[Tabularizer(), StandardScaler()],
72-
[Padder(pad_length=15), Tabularizer(), StandardScaler()],
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[Padder(pad_length=15), SevenNumberSummary()],
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[Padder(padded_length=15), Tabularizer(), StandardScaler()],
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[Padder(padded_length=15), SevenNumberSummary()],
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[Tabularizer(), StandardScaler(), SevenNumberSummary()],
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[
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Padder(pad_length=15),
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Padder(padded_length=15),
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SevenNumberSummary(),
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],
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],

‎aeon/pipeline/tests/test_make_pipeline.py

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@@ -12,21 +12,22 @@
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from aeon.pipeline import make_pipeline
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from aeon.regression import DummyRegressor
1414
from aeon.testing.data_generation import make_example_3d_numpy
15-
from aeon.transformations.collection import Padder, Tabularizer
15+
from aeon.transformations.collection import Tabularizer
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from aeon.transformations.collection.feature_based import SevenNumberSummary
17+
from aeon.transformations.collection.unequal_length import Padder
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1819

1920
@pytest.mark.parametrize(
2021
"pipeline",
2122
[
22-
[Padder(pad_length=15), DummyClassifier()],
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[Padder(padded_length=15), DummyClassifier()],
2324
[SevenNumberSummary(), RandomForestClassifier(n_estimators=2)],
24-
[Padder(pad_length=15), DummyRegressor()],
25+
[Padder(padded_length=15), DummyRegressor()],
2526
[SevenNumberSummary(), RandomForestRegressor(n_estimators=2)],
26-
[Padder(pad_length=15), TimeSeriesKMeans._create_test_instance()],
27+
[Padder(padded_length=15), TimeSeriesKMeans._create_test_instance()],
2728
[SevenNumberSummary(), KMeans(n_clusters=2, max_iter=3)],
28-
[Padder(pad_length=15), SevenNumberSummary()],
29-
[Padder(pad_length=15), Tabularizer(), StandardScaler()],
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[Padder(padded_length=15), SevenNumberSummary()],
30+
[Padder(padded_length=15), Tabularizer(), StandardScaler()],
3031
],
3132
)
3233
def test_make_pipeline(pipeline):

‎aeon/regression/compose/_pipeline.py

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Original file line numberDiff line numberDiff line change
@@ -99,8 +99,8 @@ def _get_test_params(cls, parameter_set="default"):
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`MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance.
100100
"""
101101
from aeon.regression.distance_based import KNeighborsTimeSeriesRegressor
102-
from aeon.transformations.collection import Truncator
103102
from aeon.transformations.collection.feature_based import SevenNumberSummary
103+
from aeon.transformations.collection.unequal_length import Truncator
104104

105105
return {
106106
"transformers": [

‎aeon/regression/compose/tests/test_pipeline.py

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Original file line numberDiff line numberDiff line change
@@ -21,22 +21,22 @@
2121
AutocorrelationFunctionTransformer,
2222
HOG1DTransformer,
2323
Normalizer,
24-
Padder,
2524
Tabularizer,
2625
)
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from aeon.transformations.collection.feature_based import SevenNumberSummary
27+
from aeon.transformations.collection.unequal_length import Padder
2828

2929

3030
@pytest.mark.parametrize(
3131
"transformers",
3232
[
33-
Padder(pad_length=15),
33+
Padder(padded_length=15),
3434
SevenNumberSummary(),
35-
[Padder(pad_length=15), Tabularizer(), StandardScaler()],
36-
[Padder(pad_length=15), SevenNumberSummary()],
35+
[Padder(padded_length=15), Tabularizer(), StandardScaler()],
36+
[Padder(padded_length=15), SevenNumberSummary()],
3737
[Tabularizer(), StandardScaler(), SevenNumberSummary()],
3838
[
39-
Padder(pad_length=15),
39+
Padder(padded_length=15),
4040
SevenNumberSummary(),
4141
],
4242
],
@@ -67,14 +67,14 @@ def test_regressor_pipeline(transformers):
6767
@pytest.mark.parametrize(
6868
"transformers",
6969
[
70-
[Padder(pad_length=15), Tabularizer()],
70+
[Padder(padded_length=15), Tabularizer()],
7171
SevenNumberSummary(),
7272
[Tabularizer(), StandardScaler()],
73-
[Padder(pad_length=15), Tabularizer(), StandardScaler()],
74-
[Padder(pad_length=15), SevenNumberSummary()],
73+
[Padder(padded_length=15), Tabularizer(), StandardScaler()],
74+
[Padder(padded_length=15), SevenNumberSummary()],
7575
[Tabularizer(), StandardScaler(), SevenNumberSummary()],
7676
[
77-
Padder(pad_length=15),
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Padder(padded_length=15),
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SevenNumberSummary(),
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],
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],

‎aeon/testing/estimator_checking/_yield_transformation_checks.py

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Original file line numberDiff line numberDiff line change
@@ -169,6 +169,9 @@ def check_transformer_output(estimator, datatype):
169169
Xt2 = _run_estimator_method(estimator, "fit_transform", datatype, "train")
170170
assert deep_equals(Xt, Xt2, ignore_index=True)
171171

172+
Xt3 = _run_estimator_method(estimator, "transform", datatype, "train")
173+
assert deep_equals(Xt, Xt3, ignore_index=True)
174+
172175

173176
def check_channel_selectors(estimator, datatype):
174177
"""Test channel selectors have fit and select at least one channel."""

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