def test_custom_nindex_impute_1(pos1, pos2, expected, mw_data): mw_data[pos1, pos2] = np.nan imputed = impy.moving_window(mw_data, nindex=-1) return_na_check(imputed) assert imputed[pos1, pos2] == expected
def test_defaults_impute(pos1, pos2, expected, mw_data): mw_data[pos1, pos2] = np.nan imputed = impy.moving_window(mw_data) return_na_check(imputed) assert imputed[pos1, pos2] == expected
def test_custom_fn_impute(pos1, pos2, expected, mw_data): mw_data[pos1, pos2] = np.nan imputed = impy.moving_window(mw_data, func=lambda l: max(l) * 2) return_na_check(imputed) assert imputed[pos1, pos2] == expected
def test_random_(test_data): data = test_data(SHAPE) imputed = impy.random(data) return_na_check(imputed)
def test_em_(test_data): data = test_data(SHAPE) imputed = impy.em(data) return_na_check(imputed)
def test_locf_(test_data): data = test_data(SHAPE) imputed = impy.locf(data) return_na_check(imputed)
def test_complete_case_(test_data): data = test_data(SHAPE) imputed = complete_case(data) return_na_check(imputed)
def test_buck_iter(buck_test_data): imputed = impy.buck_iterative(buck_test_data) return_na_check(imputed)
def test_mean(test_data): data = test_data(SHAPE) imputed = impy.mean(data) return_na_check(imputed)
def test_return_type(knn_test_data): imputed = impy.fast_knn(knn_test_data) return_na_check(imputed)