Loading deepchem/metrics/tests/test_metrics.py +0 −3 Original line number Diff line number Diff line Loading @@ -77,17 +77,14 @@ def test_concordance_index(): y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([3, 1, 5, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 0.7 # best case y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([1, 3, 5, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 1.0 # duplicate prediction value y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([1, 3, 4, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 0.95 Loading
deepchem/metrics/tests/test_metrics.py +0 −3 Original line number Diff line number Diff line Loading @@ -77,17 +77,14 @@ def test_concordance_index(): y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([3, 1, 5, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 0.7 # best case y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([1, 3, 5, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 1.0 # duplicate prediction value y_true = np.array([1, 3, 5, 4, 2]) y_pred = np.array([1, 3, 4, 4, 2]) assert metric.compute_singletask_metric(y_true, y_pred) == 0.95
