@ignore_warnings
def test_sensitivity_specificity_support_errors():
 (y_true, y_pred, _) = make_prediction(binary=True)
 assert_raises(ValueError, sensitivity_specificity_support, y_true, y_pred, pos_label=2, average='binary')
 assert_raises(ValueError, sensitivity_specificity_support, [0, 1, 2], [1, 2, 0], average='mega')

@ ignore_warnings def test_sensitivity_specificity_support_errors ( ) : ( y_true , y_pred , _ ) = make_prediction ( binary = True ) assert_raises ( ValueError , sensitivity_specificity_support , y_true , y_pred , pos_label = 2 , average = 'binary' ) assert_raises ( ValueError , sensitivity_specificity_support , [ 0 , 1 , 2 ] , [ 1 , 2 , 0 ] , average = 'mega' )
test either if an error is raised depending on parameters .