def test_plot_confusion_matrix_ticklabels_false(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `ticklabels` option set to False.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
ticklabels=False)
return ax.figure
def test_plot_confusion_matrix_ticklabels_n_labels(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `ticklabels` option and print every 2 labels.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
ticklabels=2)
return ax.figure
def test_plot_confusion_matrix_stats_fscore(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `stats` option with categorical values.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix_cat,
self.y_pred_matrix_cat,
stats='f1-score')
return ax.figure
def test_plot_confusion_matrix_ticklabels_cat(self):
"""
Test of the `plot_confusion_matrix` function.
Use categorical predictions.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix_cat,
self.y_pred_matrix_cat)
return ax.figure
def test_plot_confusion_matrix_stats_acc(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `stats` option.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
stats='accuracy')
return ax.figure
def test_plot_confusion_matrix_stats_prec(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `stats` option with precision for all classes.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
stats='precision')
return ax.figure
def test_plot_confusion_matrix_normalize(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `normalize` option.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
normalize='all')
return ax.figure
def test_plot_confusion_matrix_labels_filter(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `labels_filter` option.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
labels_filter=[3, 1])
return ax.figure
def test_plot_confusion_matrix_sample_weight(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `sample_weigth` option.
"""
weights = range(1, len(self.y_true_matrix) + 1)
ax = bplt.plot_confusion_matrix(self.y_true_matrix,
self.y_pred_matrix,
sample_weight=weights)
return ax.figure
def test_plot_confusion_matrix_stats_error(self):
"""
Test of the `plot_confusion_matrix` function.
Check with the `stats` option when the key of the stat is wrong.
"""
# Check the error message using a mock.
with unittest.mock.patch('logging.Logger.error') as mock_logging:
ax = bplt.plot_confusion_matrix(self.y_true_matrix_cat,
self.y_pred_matrix_cat,
stats='acc')
mock_logging.assert_called_with(
"Wrong key acc, possible values: "
"['precision', 'recall', 'f1-score', 'support'].")
return ax.figure
def test_plot_confusion_matrix(self):
"""
Test of the `plot_confusion_matrix` function.
"""
ax = bplt.plot_confusion_matrix(self.y_true_matrix, self.y_pred_matrix)
return ax.figure