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