Added visualization plots (#50)

docs/additional_information/changelog.rst

@@ -29,6 +29,7 @@ Added
   ``RobustPrincipalComponentAnalysis`` anomaly detectors.
 - Implemented ``HistogramBasedOutlierScore`` anomaly detector.
 - Implemented ``OneClassSupportVectorMachine`` anomaly detector.
+- Implemented methods to visualize time series and anomalies: ``plot_demarcated_anomalies``, ``plot_with_zoom``, and ``plot_anomaly_scores``.
 
 Changed
 ^^^^^^^

docs/api/visualization.rst

@@ -3,6 +3,89 @@ Visualization module
 
 .. automodule:: dtaianomaly.visualization
 
+.. plot::
+   :context: reset
+   :include-source: False
+
+   import matplotlib.pyplot as plt
+   plt.rcParams.update({
+       'figure.autolayout': True,
+       'figure.titlesize': 18
+   })
+
+
+.. autofunction:: dtaianomaly.visualization.plot_demarcated_anomalies
+
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_demarcated_anomalies
+   >>> X, y = demonstration_time_series()
+   >>> fig = plot_demarcated_anomalies(X, y, figsize=(10, 3))
+   >>> fig.suptitle("Example of 'plot_demarcated_anomalies'")  # doctest: +SKIP
+
+
 .. autofunction:: dtaianomaly.visualization.plot_time_series_colored_by_score
 
-.. autofunction:: dtaianomaly.visualization.plot_time_series_anomalies
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_time_series_colored_by_score
+   >>> X, y = demonstration_time_series()
+   >>> fig = plot_time_series_colored_by_score(X, y, figsize=(10, 3))
+   >>> fig.suptitle("Example of 'plot_time_series_colored_by_score' on the ground truth")  # doctest: +SKIP
+
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_time_series_colored_by_score
+   >>> from dtaianomaly.anomaly_detection import IsolationForest
+   >>> X, _ = demonstration_time_series()
+   >>> y_pred = IsolationForest(window_size=100).fit(X).predict_proba(X)
+   >>> fig = plot_time_series_colored_by_score(X, y_pred, figsize=(10, 3))
+   >>> fig.suptitle("Example of 'plot_time_series_colored_by_score' on predictions")  # doctest: +SKIP
+
+
+.. autofunction:: dtaianomaly.visualization.plot_anomaly_scores
+
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_anomaly_scores, plot_time_series_colored_by_score
+   >>> from dtaianomaly.anomaly_detection import IsolationForest
+   >>> X, y = demonstration_time_series()
+   >>> y_pred = IsolationForest(window_size=100).fit(X).predict_proba(X)
+   >>> fig = plot_anomaly_scores(X, y, y_pred, figsize=(10, 3), method_to_plot=plot_time_series_colored_by_score)
+   >>> fig.suptitle("Example of 'plot_anomaly_scores'")  # doctest: +SKIP
+
+
+.. autofunction:: dtaianomaly.visualization.plot_time_series_anomalies
+
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_time_series_anomalies
+   >>> from dtaianomaly.anomaly_detection import IsolationForest
+   >>> from dtaianomaly.thresholding import FixedCutoff
+   >>> X, _ = demonstration_time_series()
+   >>> y_pred = IsolationForest(window_size=100).fit(X).predict_proba(X)
+   >>> y_pred_binary = FixedCutoff(cutoff=0.9).threshold(y_pred)
+   >>> fig = plot_time_series_anomalies(X, y, y_pred_binary, figsize=(10, 3))
+   >>> fig.suptitle("Example of 'plot_time_series_anomalies'")  # doctest: +SKIP
+
+
+.. autofunction:: dtaianomaly.visualization.plot_with_zoom
+
+.. plot::
+   :context: close-figs
+
+   >>> from dtaianomaly.data import demonstration_time_series
+   >>> from dtaianomaly.visualization import plot_with_zoom
+   >>> X, y = demonstration_time_series()
+   >>> fig = plot_with_zoom(X, y, start_zoom=700, end_zoom=1200, figsize=(10, 3))
+   >>> fig.suptitle("Example of 'plot_with_zoom'")  # doctest: +SKIP

docs/conf.py

@@ -36,11 +36,17 @@
     'sphinx.ext.autosummary',
     'sphinx.ext.viewcode',
     'sphinx.ext.napoleon',
-    'numpydoc'
+    'numpydoc',
+    'matplotlib.sphinxext.plot_directive'
 ]
 
 numpydoc_show_class_members = False
 
+# Default settings for matplotlib.sphinxext.plot_directive
+plot_include_source = True
+plot_html_show_source_link = False
+plot_html_show_formats = False
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 

dtaianomaly/visualization/__init__.py

@@ -7,10 +7,13 @@
 along with the ground truth or predicted anomalies.
 """
 
-from .visualization import plot_time_series_colored_by_score, plot_time_series_anomalies
+from .visualization import plot_time_series_colored_by_score, plot_time_series_anomalies, plot_demarcated_anomalies, plot_with_zoom, plot_anomaly_scores, format_time_steps
 
 __all__ = [
     'plot_time_series_colored_by_score',
-    'plot_time_series_anomalies'
+    'plot_time_series_anomalies',
+    'plot_demarcated_anomalies',
+    'plot_with_zoom',
+    'plot_anomaly_scores',
+    'format_time_steps'
 ]
-