# Path: kenchi/plotting.py
# def plot_anomaly_score(
#     anomaly_score, ax=None, bins='auto', figsize=None,
#     filename=None, hist=True, kde=True, threshold=None,
#     title=None, xlabel='Samples', xlim=None, ylabel='Anomaly score',
#     ylim=None, **kwargs
# ):
#     def _get_ax_hist(ax):
# def plot_roc_curve(
#     y_true, y_score, ax=None, figsize=None,
#     filename=None, title='ROC curve', xlabel='FPR', ylabel='TPR',
#     **kwargs
# ):
# def plot_graphical_model(
#     G, ax=None, figsize=None, filename=None,
#     random_state=None, title='GGM', **kwargs
# ):
# def plot_partial_corrcoef(
#     partial_corrcoef, ax=None, cbar=True, figsize=None,
#     filename=None, title='Partial correlation', **kwargs
# ):


import doctest
from kenchi import plotting
from sklearn.utils.testing import if_matplotlib



@if_matplotlib
def load_tests(loader, tests, ignore):
    tests.addTests(doctest.DocTestSuite(plotting))


# Path: kenchi/plotting.py
# def plot_anomaly_score(
#     anomaly_score, ax=None, bins='auto', figsize=None,
#     filename=None, hist=True, kde=True, threshold=None,
#     title=None, xlabel='Samples', xlim=None, ylabel='Anomaly score',
#     ylim=None, **kwargs
# ):
#     def _get_ax_hist(ax):
# def plot_roc_curve(
#     y_true, y_score, ax=None, figsize=None,
#     filename=None, title='ROC curve', xlabel='FPR', ylabel='TPR',
#     **kwargs
# ):
# def plot_graphical_model(
#     G, ax=None, figsize=None, filename=None,
#     random_state=None, title='GGM', **kwargs
# ):
# def plot_partial_corrcoef(
#     partial_corrcoef, ax=None, cbar=True, figsize=None,
#     filename=None, title='Partial correlation', **kwargs
# ):


# Path: kenchi/tests/test_plotting.py
import doctest
from kenchi import plotting
from sklearn.utils.testing import if_matplotlib




@if_matplotlib
def load_tests(loader, tests, ignore):
    tests.addTests(doctest.DocTestSuite(plotting))


    return tests