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