Order imports (#324)

* Update .pre-commit-config.yaml

add isort

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* Update heavy_benchmark.py

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* Update noplot_classify_P300_bi_quantum_mdm.py

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* Update .pre-commit-config.yaml

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* Update plot_classifier_comparison.py

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* Update plot_classifier_comparison.py

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* Update pipelines.py

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* Update plot_classifier_comparison.py

* Update noplot_classify_alexmi_with_quantum_pipeline.py

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* Update heavy_benchmark.py

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* Update .pre-commit-config.yaml

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.pre-commit-config.yaml

@@ -39,3 +39,9 @@ repos:
       - id: prettier
         args: [--print-width=90, --prose-wrap=always]
         exclude: ^(.github/|.devcontainer/|doc/_static/|doc/conf.py|pyriemann_qiskit/_version.py|setup.py)
+
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+        args: ["--profile=black", "--known-local-folder=helpers"]

benchmarks/hb_nch.py

@@ -7,13 +7,14 @@
 @author: anton andreev
 """
 
+import os
+
+from heavy_benchmark import benchmark_alpha, plot_stat
+from pyriemann.classification import MDM
 from pyriemann.estimation import XdawnCovariances
 from sklearn.pipeline import make_pipeline
-from pyriemann.classification import MDM
-import os
 
 from pyriemann_qiskit.classification import QuanticNCH
-from heavy_benchmark import benchmark_alpha, plot_stat
 
 # start configuration
 hb_max_n_subjects = 3

benchmarks/heavy_benchmark.py

@@ -16,55 +16,40 @@
 """
 # Author: Anton Andreev
 
-from pyriemann.estimation import Covariances
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
+
+import moabb.analysis.plotting as moabb_plt
 import pandas as pd
+import seaborn as sns
+from matplotlib import pyplot as plt
 from moabb import set_log_level
-
-# P300 databases
+from moabb.analysis.meta_analysis import (
+    compute_dataset_statistics,
+    find_significant_differences,
+)
 from moabb.datasets import (
-    BI2013a,
+    BNCI2014_001,
+    BNCI2014_004,
     BNCI2014_008,
     BNCI2014_009,
     BNCI2015_003,
-    # EPFLP300,
-    # Lee2019_ERP,
+    BI2013a,
     BI2014a,
     BI2014b,
     BI2015a,
     BI2015b,
-)
-
-# Motor imagery databases
-from moabb.datasets import (
-    BNCI2014_001,
-    Zhou2016,
-    # BNCI2015_001,
-    # BNCI2014_002,
-    BNCI2014_004,
-    # BNCI2015_004, #not tested
-    # AlexMI,
-    Weibo2014,
     Cho2017,
     GrosseWentrup2009,
+    Lee2019_MI,
     PhysionetMI,
+    Schirrmeister2017,
     Shin2017A,
-    Lee2019_MI,  # new
-    Schirrmeister2017,  # new
-)
-from moabb.evaluations import (
-    WithinSessionEvaluation,
-    CrossSubjectEvaluation,
-)
-from moabb.paradigms import P300, MotorImagery, LeftRightImagery
-
-import moabb.analysis.plotting as moabb_plt
-from moabb.analysis.meta_analysis import (
-    compute_dataset_statistics,
-    find_significant_differences,
+    Weibo2014,
+    Zhou2016,
 )
+from moabb.evaluations import CrossSubjectEvaluation, WithinSessionEvaluation
+from moabb.paradigms import P300, LeftRightImagery, MotorImagery
+from pyriemann.estimation import Covariances
 
 print(__doc__)
 print("Version 1.0 24/06/2024")

benchmarks/lb_base.py

@@ -20,7 +20,6 @@
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
 
-
 print(__doc__)
 
 ##############################################################################

benchmarks/light_benchmark.py

@@ -13,18 +13,19 @@
 
 import warnings
 
+from lb_base import run
 from moabb import set_log_level
-from pyriemann.estimation import XdawnCovariances, Shrinkage
+from pyriemann.estimation import Shrinkage, XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
+from sklearn.decomposition import PCA
+from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.pipeline import make_pipeline
+
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
     QuantumMDMWithRiemannianPipeline,
 )
 from pyriemann_qiskit.utils import distance, mean  # noqa
-from sklearn.decomposition import PCA
-from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
-from sklearn.pipeline import make_pipeline
-from lb_base import run
 
 print(__doc__)
 

benchmarks/light_benchmark_nch_min_hull.py

@@ -13,13 +13,13 @@
 
 import warnings
 
+from lb_base import run
 from moabb import set_log_level
 from pyriemann.estimation import XdawnCovariances
-from pyriemann_qiskit.classification import QuanticNCH
-from pyriemann_qiskit.utils import distance, mean  # noqa
 from sklearn.pipeline import make_pipeline
 
-from lb_base import run
+from pyriemann_qiskit.classification import QuanticNCH
+from pyriemann_qiskit.utils import distance, mean  # noqa
 
 print(__doc__)
 

benchmarks/light_benchmark_nch_qaoacv.py

@@ -13,15 +13,15 @@
 
 import warnings
 
+from lb_base import run
 from moabb import set_log_level
 from pyriemann.estimation import XdawnCovariances
-from pyriemann_qiskit.classification import QuanticNCH
-from pyriemann_qiskit.utils import distance, mean  # noqa
-from pyriemann_qiskit.utils.hyper_params_factory import create_mixer_rotational_X_gates
 from qiskit_algorithms.optimizers import SPSA
 from sklearn.pipeline import make_pipeline
 
-from lb_base import run
+from pyriemann_qiskit.classification import QuanticNCH
+from pyriemann_qiskit.utils import distance, mean  # noqa
+from pyriemann_qiskit.utils.hyper_params_factory import create_mixer_rotational_X_gates
 
 print(__doc__)
 

doc/conf.py

@@ -12,18 +12,21 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys
 import os
+import sys
+
 import matplotlib
 
 # mne update path
 import mne
+
 print(mne.datasets.sample.data_path(update_path=True, download=False))
 
 matplotlib.use('Agg')
 import shlex
-import sphinx_gallery
+
 import sphinx_bootstrap_theme
+import sphinx_gallery
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
@@ -95,6 +98,7 @@
 # The short X.Y version.
 sys.path.insert(0, os.path.abspath(os.path.pardir))
 import pyriemann_qiskit
+
 version = pyriemann_qiskit.__version__
 # The full version, including alpha/beta/rc tags.
 release = pyriemann_qiskit.__version__

examples/ERP/noplot_autoencoders_example.py

@@ -17,6 +17,7 @@
 import logging
 import warnings
 
+import seaborn as sns
 from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import Hinss2021
@@ -25,13 +26,12 @@
 from pyriemann.estimation import Covariances
 from pyriemann.tangentspace import TangentSpace
 from qiskit_algorithms.optimizers import COBYLA
-import seaborn as sns
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
 from sklearn.pipeline import make_pipeline
 
 from pyriemann_qiskit.autoencoders import BasicQnnAutoencoder
 from pyriemann_qiskit.utils.filtering import ChannelSelection
-from pyriemann_qiskit.utils.preprocessing import Vectorizer, Devectorizer
+from pyriemann_qiskit.utils.preprocessing import Devectorizer, Vectorizer
 
 print(__doc__)
 

examples/ERP/noplot_classify_P300_bi_illiteracy.py

@@ -11,36 +11,36 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
-from enum import Enum
 import warnings
+from enum import Enum
 
+import numpy as np
+import seaborn as sns
 from matplotlib import pyplot as plt
 from mne.decoding import Vectorizer
 from moabb import set_log_level
 from moabb.datasets.compound_dataset import BI_Il
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
-import numpy as np
-from pyriemann.estimation import XdawnCovariances
-from pyriemann.tangentspace import TangentSpace
 from pyriemann.classification import MDM
+from pyriemann.estimation import XdawnCovariances
 from pyriemann.spatialfilters import Xdawn
-import seaborn as sns
-from sklearn.ensemble import VotingClassifier
-from sklearn.pipeline import make_pipeline, Pipeline
+from pyriemann.tangentspace import TangentSpace
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.ensemble import VotingClassifier
+from sklearn.pipeline import Pipeline, make_pipeline
 from sklearn.svm import SVC
 
 from pyriemann_qiskit.ensemble import JudgeClassifier
-
-# inject convex distance and mean to pyriemann (if not done already)
-from pyriemann_qiskit.utils import distance, mean  # noqa
 from pyriemann_qiskit.pipelines import (
+    QuantumClassifierWithDefaultRiemannianPipeline,
     QuantumMDMVotingClassifier,
     QuantumMDMWithRiemannianPipeline,
-    QuantumClassifierWithDefaultRiemannianPipeline,
 )
 
+# inject convex distance and mean to pyriemann (if not done already)
+from pyriemann_qiskit.utils import distance, mean  # noqa
+
 print(__doc__)
 
 

examples/ERP/noplot_classify_P300_bi_quantum_mdm.py

@@ -25,32 +25,21 @@
 
 import warnings
 
+import seaborn as sns
 from matplotlib import pyplot as plt
 from moabb import set_log_level
-from moabb.datasets import (
-    # bi2012,
-    # bi2013a,
-    # bi2014a,
-    # bi2014b,
-    # bi2015a,
-    # bi2015b,
-    # BNCI2014008,
-    BNCI2014009,
-    # BNCI2015003,
-    # EPFLP300,
-    # Lee2019_ERP,
-)
+from moabb.datasets import BNCI2014009
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
-import seaborn as sns
 
-# inject cpm distance and mean to pyriemann (if not done already)
-from pyriemann_qiskit.utils import distance, mean  # noqa
 from pyriemann_qiskit.pipelines import (
     QuantumMDMVotingClassifier,
     QuantumMDMWithRiemannianPipeline,
 )
 
+# inject cpm distance and mean to pyriemann (if not done already)
+from pyriemann_qiskit.utils import distance, mean  # noqa
+
 print(__doc__)
 
 ##############################################################################

examples/ERP/noplot_classify_P300_nch.py

@@ -21,14 +21,14 @@
 
 import warnings
 
+import seaborn as sns
 from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import bi2013a
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
 from pyriemann.classification import MDM
 from pyriemann.estimation import XdawnCovariances
-import seaborn as sns
 from sklearn.pipeline import make_pipeline
 
 from pyriemann_qiskit.classification import QuanticNCH

examples/ERP/noplot_firebase_moabb.py

@@ -25,26 +25,24 @@
 
 import warnings
 
+import seaborn as sns
 from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import bi2012
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
-import seaborn as sns
+from sklearn.decomposition import PCA
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
 from sklearn.pipeline import make_pipeline
-from sklearn.decomposition import PCA
 
+from pyriemann_qiskit.pipelines import QuantumClassifierWithDefaultRiemannianPipeline
 from pyriemann_qiskit.utils import (
-    generate_caches,
-    filter_subjects_by_incomplete_results,
     add_moabb_dataframe_results_to_caches,
     convert_caches_to_dataframes,
-)
-from pyriemann_qiskit.pipelines import (
-    QuantumClassifierWithDefaultRiemannianPipeline,
+    filter_subjects_by_incomplete_results,
+    generate_caches,
 )
 
 print(__doc__)

examples/ERP/plot_classify_EEG_quantum_svm.py

@@ -16,17 +16,17 @@
 from matplotlib import pyplot as plt
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
-from sklearn.pipeline import make_pipeline
-from sklearn.model_selection import train_test_split
 from sklearn.metrics import (
-    confusion_matrix,
     ConfusionMatrixDisplay,
     balanced_accuracy_score,
+    confusion_matrix,
 )
+from sklearn.model_selection import train_test_split
+from sklearn.pipeline import make_pipeline
 
 from pyriemann_qiskit.classification import QuanticSVM
-from pyriemann_qiskit.utils.filtering import NaiveDimRed
 from pyriemann_qiskit.datasets import get_mne_sample
+from pyriemann_qiskit.utils.filtering import NaiveDimRed
 
 print(__doc__)