def test_robust_cv_series_fill_na():
fill = 1
data = pd.Series(np.zeros(100))
cv = utils.robust_cv(data, fill_value=fill)
assert np.isclose(cv, fill)
def test_robust_cv_series():
data = pd.Series(np.random.normal(size=100, loc=1))
cv = utils.robust_cv(data)
test_cv = utils.median_abs_deviation(data, scale="normal") / data.median()
assert np.isclose(cv, test_cv)
def test_robust_cv_fill_na():
fill = 1
data = np.zeros((100, 200))
data = pd.DataFrame(data)
cv = utils.robust_cv(data, fill_value=fill)
assert (cv == fill).all()
def test_robust_cv_all_zeros():
data = np.zeros((100, 200))
data = pd.DataFrame(data)
cv = utils.robust_cv(data)
assert cv.isna().all()
def test_robust_cv_valid_data(random_df):
data = random_df
cv = utils.robust_cv(data, fill_value=0)
cv_test = utils.mad(data) / data.median()
cv_test = cv_test.fillna(0)
assert np.isclose(cv, cv_test).all()
def test_robust_cv_single_row_df(single_row_df):
data = single_row_df
# nans are converted to inf, all values should be inf
assert utils.robust_cv(data).isna().all()