def test_fbeta(caplog):
"""Unit test of fbeta_scorer"""
caplog.set_level(logging.INFO)
golds = np.array([0, 1, 0, 1, 0, 1])
preds = np.array([0, 0, 0, 0, 0, 1])
metric_dict = fbeta_scorer(golds, None, preds, pos_label=1, beta=2)
assert isequal(metric_dict, {"f2": 0.3846153846153846})
metric_dict = fbeta_scorer(golds, None, preds, pos_label=0, beta=2)
assert isequal(metric_dict, {"f2": 0.8823529411764706})
def test_fbeta(caplog):
"""Unit test of fbeta_scorer."""
caplog.set_level(logging.INFO)
metric_dict = fbeta_scorer(GOLDS, PROBS, PREDS, pos_label=1, beta=2)
assert isequal(metric_dict, {"f2": 0.3846153846153846})
metric_dict = fbeta_scorer(GOLDS, None, PREDS, pos_label=1, beta=2)
assert isequal(metric_dict, {"f2": 0.3846153846153846})
metric_dict = fbeta_scorer(GOLDS, None, PREDS, pos_label=0, beta=2)
assert isequal(metric_dict, {"f2": 0.8823529411764706})
metric_dict = fbeta_scorer(PROB_GOLDS, PROBS, PREDS, pos_label=1, beta=2)
assert isequal(metric_dict, {"f2": 0.3846153846153846})
metric_dict = fbeta_scorer(PROB_GOLDS, None, PREDS, pos_label=1, beta=2)
assert isequal(metric_dict, {"f2": 0.3846153846153846})
metric_dict = fbeta_scorer(PROB_GOLDS, None, PREDS, pos_label=0, beta=2)
assert isequal(metric_dict, {"f2": 0.8823529411764706})