style: formatted with black

docs/source/conf.py

@@ -74,7 +74,8 @@
 sphinx_gallery_conf = {
     'examples_dirs': ['../../examples', '../../tutorials'],
     'gallery_dirs': ['auto_examples', 'auto_tutorials'],
-    'backreferences_dir': False}
+    'backreferences_dir': False,
+}
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
@@ -124,34 +125,29 @@
 html_theme_options = {
     # Navigation bar title. (Default: ``project`` value)
     # 'navbar_title': "Demo",
-
     # Tab name for entire site. (Default: "Site")
     # 'navbar_site_name': "Site",
-
     # A list of tuples containing pages or urls to link to.
     # Valid tuples should be in the following forms:
     #    (name, page)                 # a link to a page
     #    (name, "/aa/bb", 1)          # a link to an arbitrary relative url
     #    (name, "http://example.com", True) # arbitrary absolute url
     # Note the "1" or "True" value above as the third argument to indicate
     # an arbitrary url.
-    'navbar_links': [("API", "api"),
-                     ("Gallery", "auto_examples/index"),
-                     ("Tutorials", "auto_tutorials/index")],
-
+    'navbar_links': [
+        ("API", "api"),
+        ("Gallery", "auto_examples/index"),
+        ("Tutorials", "auto_tutorials/index"),
+    ],
     # Render the next and previous page links in navbar. (Default: true)
     'navbar_sidebarrel': False,
-
     # Render the current pages TOC in the navbar. (Default: true)
     'navbar_pagenav': True,
-
     # Tab name for the current pages TOC. (Default: "Page")
     'navbar_pagenav_name': "Page",
-
     # Global TOC depth for "site" navbar tab. (Default: 1)
     # Switching to -1 shows all levels.
     'globaltoc_depth': 2,
-
     # Include hidden TOCs in Site navbar?
     #
     # Note: If this is "false", you cannot have mixed ``:hidden:`` and
@@ -160,19 +156,15 @@
     #
     # Values: "true" (default) or "false"
     'globaltoc_includehidden': "true",
-
     # HTML navbar class (Default: "navbar") to attach to <div> element.
     # For black navbar, do "navbar navbar-inverse"
     'navbar_class': "navbar navbar-inverse",
-
     # Fix navigation bar to top of page?
     # Values: "true" (default) or "false"
     'navbar_fixed_top': "true",
-
     # Location of link to source.
     # Options are "nav" (default), "footer" or anything else to exclude.
     'source_link_position': "footer",
-
     # Bootswatch (http://bootswatch.com/) theme.
     #
     # Options are nothing (default) or the name of a valid theme
@@ -185,7 +177,6 @@
     # - Bootstrap 2: https://bootswatch.com/2
     # - Bootstrap 3: https://bootswatch.com/3
     'bootswatch_theme': "united",
-
     # Choose Bootstrap version.
     # Values: "3" (default) or "2" (in quotes)
     'bootstrap_version': "3",
@@ -219,15 +210,12 @@
     # The paper size ('letterpaper' or 'a4paper').
     #
     # 'papersize': 'letterpaper',
-
     # The font size ('10pt', '11pt' or '12pt').
     #
     # 'pointsize': '10pt',
-
     # Additional stuff for the LaTeX preamble.
     #
     # 'preamble': '',
-
     # Latex figure (float) alignment
     #
     # 'figure_align': 'htbp',
@@ -237,19 +225,15 @@
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, 'moabb.tex', 'moabb Documentation',
-     'Alexandre Barachant', 'manual'),
+    (master_doc, 'moabb.tex', 'moabb Documentation', 'Alexandre Barachant', 'manual'),
 ]
 
 
 # -- Options for manual page output ------------------------------------------
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [
-    (master_doc, 'moabb', 'moabb Documentation',
-     [author], 1)
-]
+man_pages = [(master_doc, 'moabb', 'moabb Documentation', [author], 1)]
 
 
 # -- Options for Texinfo output ----------------------------------------------
@@ -258,9 +242,15 @@
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, 'moabb', 'moabb Documentation',
-     author, 'moabb', 'One line description of project.',
-     'Miscellaneous'),
+    (
+        master_doc,
+        'moabb',
+        'moabb Documentation',
+        author,
+        'moabb',
+        'One line description of project.',
+        'Miscellaneous',
+    ),
 ]
 
 

examples/plot_cross_session_motor_imagery.py

@@ -54,12 +54,11 @@
 
 pipelines = {}
 
-pipelines['CSP + LDA'] = make_pipeline(CSP(n_components=8),
-                                       LDA())
+pipelines['CSP + LDA'] = make_pipeline(CSP(n_components=8), LDA())
 
-pipelines['RG + LR'] = make_pipeline(Covariances(),
-                                     TangentSpace(),
-                                     LogisticRegression(solver='lbfgs'))
+pipelines['RG + LR'] = make_pipeline(
+    Covariances(), TangentSpace(), LogisticRegression(solver='lbfgs')
+)
 
 ##############################################################################
 # Evaluation
@@ -79,8 +78,9 @@
 dataset.subject_list = dataset.subject_list[:2]
 datasets = [dataset]
 overwrite = False  # set to True if we want to overwrite cached results
-evaluation = CrossSessionEvaluation(paradigm=paradigm, datasets=datasets,
-                                    suffix='examples', overwrite=overwrite)
+evaluation = CrossSessionEvaluation(
+    paradigm=paradigm, datasets=datasets, suffix='examples', overwrite=overwrite
+)
 
 results = evaluation.process(pipelines)
 
@@ -98,21 +98,28 @@
 
 fig, axes = plt.subplots(1, 2, figsize=[8, 4], sharey=True)
 
-sns.stripplot(data=results, y='score', x='pipeline', ax=axes[0], jitter=True,
-              alpha=.5, zorder=1, palette="Set1")
-sns.pointplot(data=results, y='score', x='pipeline', ax=axes[0],
-              zorder=1, palette="Set1")
+sns.stripplot(
+    data=results,
+    y='score',
+    x='pipeline',
+    ax=axes[0],
+    jitter=True,
+    alpha=0.5,
+    zorder=1,
+    palette="Set1",
+)
+sns.pointplot(data=results, y='score', x='pipeline', ax=axes[0], zorder=1, palette="Set1")
 
 axes[0].set_ylabel('ROC AUC')
 axes[0].set_ylim(0.5, 1)
 
 # paired plot
-paired = results.pivot_table(values='score', columns='pipeline',
-                             index=['subject', 'session'])
+paired = results.pivot_table(
+    values='score', columns='pipeline', index=['subject', 'session']
+)
 paired = paired.reset_index()
 
-sns.regplot(data=paired, y='RG + LR', x='CSP + LDA', ax=axes[1],
-            fit_reg=False)
+sns.regplot(data=paired, y='RG + LR', x='CSP + LDA', ax=axes[1], fit_reg=False)
 axes[1].plot([0, 1], [0, 1], ls='--', c='k')
 axes[1].set_xlim(0.5, 1)
 

examples/plot_cross_session_multiple_datasets.py

@@ -66,8 +66,7 @@
 freqs = paradigm.used_events(datasets[0])
 
 pipeline = {}
-pipeline["CCA"] = make_pipeline(
-    SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
+pipeline["CCA"] = make_pipeline(SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
 
 ##############################################################################
 # Get data (optional)
@@ -97,8 +96,9 @@
 
 overwrite = True  # set to True if we want to overwrite cached results
 
-evaluation = CrossSessionEvaluation(paradigm=paradigm, datasets=datasets,
-                                    suffix='examples', overwrite=overwrite)
+evaluation = CrossSessionEvaluation(
+    paradigm=paradigm, datasets=datasets, suffix='examples', overwrite=overwrite
+)
 results = evaluation.process(pipeline)
 
 print(results.head())
@@ -109,6 +109,13 @@
 #
 # Here we plot the results, indicating the score for each session and subject
 
-sns.catplot(data=results, x='session', y='score', hue='subject',
-            col='dataset', kind='bar', palette='viridis')
+sns.catplot(
+    data=results,
+    x='session',
+    y='score',
+    hue='subject',
+    col='dataset',
+    kind='bar',
+    palette='viridis',
+)
 plt.show()

examples/plot_cross_session_ssvep.py

@@ -64,8 +64,7 @@
 freqs = paradigm.used_events(dataset)
 
 pipeline = {}
-pipeline["CCA"] = make_pipeline(
-    SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
+pipeline["CCA"] = make_pipeline(SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
 
 ##############################################################################
 # Get data (optional)
@@ -90,8 +89,9 @@
 
 overwrite = True  # set to True if we want to overwrite cached results
 
-evaluation = CrossSessionEvaluation(paradigm=paradigm, datasets=dataset,
-                                    suffix='examples', overwrite=overwrite)
+evaluation = CrossSessionEvaluation(
+    paradigm=paradigm, datasets=dataset, suffix='examples', overwrite=overwrite
+)
 results = evaluation.process(pipeline)
 
 print(results.head())
@@ -103,7 +103,6 @@
 # Here we plot the results, indicating the score for each session and subject
 
 plt.figure()
-sns.barplot(data=results, y='score', x='session',
-            hue='subject', palette='viridis')
+sns.barplot(data=results, y='score', x='session', hue='subject', palette='viridis')
 
 plt.show()

examples/plot_cross_subject_ssvep.py

@@ -88,11 +88,11 @@
     ExtendedSSVEPSignal(),
     Covariances(estimator='lwf'),
     TangentSpace(),
-    LogisticRegression(solver='lbfgs', multi_class='auto'))
+    LogisticRegression(solver='lbfgs', multi_class='auto'),
+)
 
 pipelines = {}
-pipelines['CCA'] = make_pipeline(
-    SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
+pipelines['CCA'] = make_pipeline(SSVEP_CCA(interval=interval, freqs=freqs, n_harmonics=3))
 
 ##############################################################################
 # Evaluation
@@ -107,14 +107,16 @@
 
 overwrite = False  # set to True if we want to overwrite cached results
 
-evaluation = CrossSubjectEvaluation(paradigm=paradigm,
-                                    datasets=dataset, overwrite=overwrite)
+evaluation = CrossSubjectEvaluation(
+    paradigm=paradigm, datasets=dataset, overwrite=overwrite
+)
 results = evaluation.process(pipelines)
 
 # Filter bank processing, determine automatically the filter from the
 # stimulation frequency values of events.
-evaluation_fb = CrossSubjectEvaluation(paradigm=paradigm_fb,
-                                       datasets=dataset, overwrite=overwrite)
+evaluation_fb = CrossSubjectEvaluation(
+    paradigm=paradigm_fb, datasets=dataset, overwrite=overwrite
+)
 results_fb = evaluation_fb.process(pipelines_fb)
 
 ###############################################################################
@@ -129,10 +131,17 @@
 # Here we plot the results.
 
 fig, ax = plt.subplots(facecolor='white', figsize=[8, 4])
-sns.stripplot(data=results, y='score', x='pipeline', ax=ax, jitter=True,
-              alpha=.5, zorder=1, palette="Set1")
-sns.pointplot(data=results, y='score', x='pipeline', ax=ax,
-              zorder=1, palette="Set1")
+sns.stripplot(
+    data=results,
+    y='score',
+    x='pipeline',
+    ax=ax,
+    jitter=True,
+    alpha=0.5,
+    zorder=1,
+    palette="Set1",
+)
+sns.pointplot(data=results, y='score', x='pipeline', ax=ax, zorder=1, palette="Set1")
 ax.set_ylabel('Accuracy')
 ax.set_ylim(0.1, 0.6)
 plt.savefig('ssvep.png')