def test_pearson_spearman(caplog): """Unit test of pearson_spearman_scorer""" caplog.set_level(logging.INFO) golds = np.array([1, 0, 1, 0, 1, 0]) probs = np.array([0.8, 0.6, 0.9, 0.7, 0.7, 0.2]) metric_dict = pearson_spearman_scorer(golds, probs, None) assert isequal(metric_dict, {"pearson_spearman": 0.7342997297919428})
def test_pearson_spearman(caplog): """Unit test of pearson_spearman_scorer""" caplog.set_level(logging.INFO) golds = np.array([1, 0, 1, 0, 1, 0]) probs = np.array([0.8, 0.6, 0.9, 0.7, 0.7, 0.2]) metric_dict = pearson_spearman_scorer(golds, probs, None) assert isequal( metric_dict, { "pearson_correlation": 0.6764814252025461, "pearson_pvalue": 0.14006598491201774, "spearman_correlation": 0.7921180343813395, "spearman_pvalue": 0.06033056705743058, "pearson_spearman": 0.7342997297919428, }, )
def test_pearson_spearman(caplog): """Unit test of pearson_spearman_scorer.""" caplog.set_level(logging.INFO) metric_dict = pearson_spearman_scorer(GOLDS, UNARY_PROBS, None) assert isequal(metric_dict, {"pearson_spearman": 0.5804143674717547})