Improve doc rendering (#310)

* improve doc rendering

* [pre-commit.ci] auto fixes from pre-commit.com hooks

* correct conf

* sort imports

* [pre-commit.ci] auto fixes from pre-commit.com hooks

* correct imports

---------

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

doc/_templates/class.rst

@@ -8,3 +8,8 @@
    {% block methods %}
    .. automethod:: __init__
    {% endblock %}
+
+.. _sphx_glr_backreferences_{{ fullname }}:
+
+.. minigallery:: {{ fullname }}
+    :add-heading:

doc/conf.py

@@ -18,8 +18,7 @@
 
 # mne update path
 import mne
-print(mne.datasets.sample.data_path(update_path=True))
-print(mne.datasets.eegbci.load_data(1, [6, 10, 14], update_path=True))
+print(mne.datasets.sample.data_path(update_path=True, download=False))
 
 matplotlib.use('Agg')
 import shlex
@@ -61,8 +60,11 @@
 plot_html_show_source_link = False
 
 sphinx_gallery_conf = {
-    'examples_dirs': ['../examples', '../tutorials'],
-    'gallery_dirs': ['auto_examples']
+    'examples_dirs': ['../examples'],
+    'gallery_dirs': ['auto_examples'],
+    'doc_module': 'pyriemann_qiskit',
+    'backreferences_dir': 'generated',
+    'plot_gallery': 'True',
 }
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']

doc/introduction.rst

@@ -80,4 +80,4 @@ References
 
 How to cite?
 ================================
-Anton Andreev, Grégoire Cattan, Sylvain Chevallier, and Quentin Barthélemy. ‘PyRiemann-Qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry’. Research Ideas and Outcomes 9 (20 March 2023). https://doi.org/10.3897/rio.9.e101006.
+Anton Andreev, Grégoire Cattan, Sylvain Chevallier, and Quentin Barthélemy. ‘pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry’. Research Ideas and Outcomes 9 (20 March 2023). https://doi.org/10.3897/rio.9.e101006.

examples/ERP/noplot_classify_P300_bi_illiteracy.py

@@ -12,24 +12,25 @@
 # License: BSD (3-clause)
 
 from enum import Enum
-from matplotlib import pyplot as plt
-import numpy as np
-import seaborn as sns
 import warnings
 
+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.spatialfilters import Xdawn
+import seaborn as sns
 from sklearn.ensemble import VotingClassifier
 from sklearn.pipeline import make_pipeline, Pipeline
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
 from sklearn.svm import SVC
+
 from pyriemann_qiskit.ensemble import JudgeClassifier
 
 # inject convex distance and mean to pyriemann (if not done already)
@@ -40,7 +41,6 @@
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
 
-
 print(__doc__)
 
 

examples/ERP/noplot_classify_P300_bi_quantum_mdm.py

@@ -23,9 +23,9 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
+
+from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import (
     # bi2012,
@@ -42,6 +42,7 @@
 )
 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

examples/ERP/noplot_firebase_moabb.py

@@ -23,27 +23,29 @@
 # Modified from plot_classify_P300_bi.py
 # License: BSD (3-clause)
 
+import warnings
+
+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.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.pipeline import make_pipeline
+from sklearn.decomposition import PCA
+
 from pyriemann_qiskit.utils import (
     generate_caches,
     filter_subjects_by_incomplete_results,
     add_moabb_dataframe_results_to_caches,
     convert_caches_to_dataframes,
 )
-from sklearn.pipeline import make_pipeline
-from matplotlib import pyplot as plt
-import warnings
-import seaborn as sns
-from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
-from moabb import set_log_level
-from moabb.datasets import bi2012
-from moabb.evaluations import WithinSessionEvaluation
-from moabb.paradigms import P300
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
-from sklearn.decomposition import PCA
 
 print(__doc__)
 

examples/ERP/plot_classify_EEG_quantum_svm.py

@@ -13,23 +13,24 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
+from matplotlib import pyplot as plt
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
-from pyriemann_qiskit.classification import QuanticSVM
-from pyriemann_qiskit.utils.filtering import NaiveDimRed
-from pyriemann_qiskit.datasets import get_mne_sample
 from sklearn.pipeline import make_pipeline
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import (
     confusion_matrix,
     ConfusionMatrixDisplay,
     balanced_accuracy_score,
 )
-from matplotlib import pyplot as plt
 
+from pyriemann_qiskit.classification import QuanticSVM
+from pyriemann_qiskit.utils.filtering import NaiveDimRed
+from pyriemann_qiskit.datasets import get_mne_sample
 
 print(__doc__)
 
+##############################################################################
 
 X, y = get_mne_sample(n_trials=-1)
 

examples/ERP/plot_classify_P300_bi.py

@@ -22,21 +22,23 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
-from pyriemann.estimation import XdawnCovariances
-from pyriemann.tangentspace import TangentSpace
-from sklearn.pipeline import make_pipeline
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
-from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+
+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.pipeline import make_pipeline
+from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.decomposition import PCA
+
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
-from sklearn.decomposition import PCA
 
 print(__doc__)
 

examples/MI/noplot_classify_alexmi_with_quantum_pipeline.py

@@ -12,13 +12,14 @@
 # Modified from ERP/classify_P300_bi_quantum_mdm.py
 # License: BSD (3-clause)
 
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
+
+from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import AlexMI
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import MotorImagery
+import seaborn as sns
 
 # inject cpm distance and mean to pyriemann (if not done already)
 from helpers.alias import ERPCov_MDM

examples/MI/noplot_multiclass_classification.py

@@ -13,21 +13,21 @@
 # Modified from plot_classify_EEG_quantum_svm
 # License: BSD (3-clause)
 
-from helpers.alias import ERPCov_MDM
-from pyriemann_qiskit.datasets import get_mne_sample
-from pyriemann_qiskit.pipelines import (
-    QuantumClassifierWithDefaultRiemannianPipeline,
-    QuantumMDMWithRiemannianPipeline,
-)
+from matplotlib import pyplot as plt
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import (
     confusion_matrix,
     ConfusionMatrixDisplay,
     balanced_accuracy_score,
 )
 from sklearn.decomposition import PCA
-from matplotlib import pyplot as plt
 
+from helpers.alias import ERPCov_MDM
+from pyriemann_qiskit.datasets import get_mne_sample
+from pyriemann_qiskit.pipelines import (
+    QuantumClassifierWithDefaultRiemannianPipeline,
+    QuantumMDMWithRiemannianPipeline,
+)
 
 print(__doc__)
 

examples/MI/plot_compare_dim_red.py

@@ -19,16 +19,19 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
+from sklearn.decomposition import PCA
+from sklearn.model_selection import StratifiedKFold, GridSearchCV
+
 from pyriemann_qiskit.datasets import get_mne_sample
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
 from pyriemann_qiskit.utils.filtering import NaiveDimRed
-from sklearn.decomposition import PCA
-from sklearn.model_selection import StratifiedKFold, GridSearchCV
 
 print(__doc__)
 
+###############################################################################
+
 X, y = get_mne_sample(n_trials=10)
 
 default_params = {

examples/other_datasets/plot_financial_data.py

@@ -30,26 +30,27 @@
 # Authors: Gregoire Cattan, Filipe Barroso
 # License: BSD (3-clause)
 
+import os
+import warnings
+
+from imblearn.under_sampling import NearMiss
+from matplotlib import pyplot as plt
+import numpy as np
+import pandas as pd
+from pyriemann.preprocessing import Whitening
+from pyriemann.estimation import XdawnCovariances
+from pyriemann.utils.viz import plot_waveforms
 from sklearn.base import TransformerMixin, BaseEstimator, ClassifierMixin
 from sklearn.experimental import enable_halving_search_cv  # noqa
-from sklearn.model_selection import HalvingGridSearchCV
+from sklearn.model_selection import HalvingGridSearchCV, train_test_split
 from sklearn.pipeline import make_pipeline
-from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.svm import SVC
 from sklearn.metrics import balanced_accuracy_score
-from imblearn.under_sampling import NearMiss
-from pyriemann.preprocessing import Whitening
-from pyriemann.estimation import XdawnCovariances
-from pyriemann.utils.viz import plot_waveforms
+
 from pyriemann_qiskit.classification import QuanticSVM
 from pyriemann_qiskit.utils.preprocessing import NdRobustScaler
-from matplotlib import pyplot as plt
-import warnings
-import pandas as pd
-import numpy as np
-import os
 
 print(__doc__)
 
@@ -86,7 +87,6 @@ def plot_ERP(X, title, n=10, ylim=None, add_digest=False):
 
 
 def merge_2axes(fig1, fig2, file_name1="f1.png", file_name2="f2.png"):
-    # Modified from [4]
     fig1.savefig(file_name1)
     fig2.savefig(file_name2)
     plt.close(fig1)
@@ -466,5 +466,3 @@ def predict(self, X):
 # .. [2] 'Synthetic Data of Transactions for Inmediate Loans Fraud'
 #         https://zenodo.org/records/7418458
 # .. [3] https://pyriemann.readthedocs.io/en/latest/auto_examples/ERP/plot_ERP.html
-#
-# .. [4] https://stackoverflow.com/questions/16748577

examples/other_datasets/plot_tutorial_quantum_svm_titanic_data.py

@@ -10,17 +10,18 @@
 # Author: Adrien Veres
 # License: BSD (3-clause)
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import seaborn as sns
-import matplotlib.pyplot as plt
 from sklearn.impute import KNNImputer
 from sklearn.preprocessing import LabelEncoder, StandardScaler
 from sklearn.decomposition import PCA
 from sklearn.model_selection import train_test_split
 from sklearn.linear_model import LogisticRegression
 from sklearn.svm import SVC
 from sklearn.metrics import balanced_accuracy_score
+
 from pyriemann_qiskit.classification import QuanticSVM
 
 print(__doc__)

examples/toys_dataset/plot_classifier_comparison.py

@@ -12,13 +12,14 @@
 # Modified for pyRiemann-qiskit by Gregoire Cattan
 # License: BSD 3 clause
 
-import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib.colors import ListedColormap
+import numpy as np
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
 from sklearn.datasets import make_moons, make_circles
 from sklearn.svm import SVC
+
 from pyriemann_qiskit.datasets import (
     generate_linearly_separable_dataset,
     generate_qiskit_dataset,

examples/toys_dataset/plot_learning_curve.py

@@ -11,13 +11,15 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
+import matplotlib.pyplot as plt
+from pyriemann.estimation import Shrinkage
+
 from pyriemann_qiskit.datasets.utils import get_mne_sample
 from pyriemann_qiskit.pipelines import QuantumMDMWithRiemannianPipeline
 from pyriemann_qiskit.utils.hyper_params_factory import get_spsa
-import matplotlib.pyplot as plt
 from pyriemann_qiskit.datasets import generate_linearly_separable_dataset
 from pyriemann_qiskit.classification import QuanticVQC
-from pyriemann.estimation import Shrinkage
+
 
 print(__doc__)