def test_only_fill_value(self): fv = 100 arr = SparseArray(np.array([fv, fv, fv]), dtype=SparseDtype("int", fv)) assert len(arr._valid_sp_values) == 0 assert arr.max() == fv assert arr.min() == fv assert arr.max(skipna=False) == fv assert arr.min(skipna=False) == fv
def test_nan_fill_value(self, raw_data, max_expected, min_expected): arr = SparseArray(raw_data) max_result = arr.max() min_result = arr.min() assert max_result in max_expected assert min_result in min_expected max_result = arr.max(skipna=False) min_result = arr.min(skipna=False) if np.isnan(raw_data).any(): assert np.isnan(max_result) assert np.isnan(min_result) else: assert max_result in max_expected assert min_result in min_expected
def test_fill_value(self, fill_value, max_expected, min_expected): arr = SparseArray(np.array([fill_value, 0, 1]), dtype=SparseDtype("int", fill_value)) max_result = arr.max() assert max_result == max_expected min_result = arr.min() assert min_result == min_expected