

@ignore_warnings
def _check_predict_proba(clf, X, y):
    proba = clf.predict_proba(X)
    log_proba = clf.predict_log_proba(X)
    y = np.atleast_1d(y)
    if (y.ndim == 1):
        y = np.reshape(y, ((- 1), 1))
    n_outputs = y.shape[1]
    n_samples = len(X)
    if (n_outputs == 1):
        proba = [proba]
        log_proba = [log_proba]
    for k in range(n_outputs):
        assert_equal(proba[k].shape[0], n_samples)
        assert_equal(proba[k].shape[1], len(np.unique(y[:, k])))
        assert_array_equal(proba[k].sum(axis=1), np.ones(len(X)))
        assert_array_equal(np.log(proba[k]), log_proba[k])

dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/tests/test_dummy.py _check_predict_proba/original