def test_not_one_hot(self):
a = np.array(
[[1, 0, 1], [0, 0, 1], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 1, 0]],
dtype="bool",
)
with pytest.raises(ValueError):
_series_from_one_hot_matrix(a)
def test_dtype(self):
a = np.array(
[[0, 0, 1], [0, 0, 2], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 1, 0]],
dtype="int8",
)
with pytest.raises(TypeError):
_series_from_one_hot_matrix(a)
def test_name_mismatch(self):
a = np.array(
[[0, 0, 1], [0, 0, 1], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 1, 0]],
dtype="bool",
)
names = ["0", "1"]
with pytest.raises(ValueError):
_series_from_one_hot_matrix(a, names=names)
def _create_states(
self,
probs: Union[np.ndarray, Lineage],
n_cells: int,
check_row_sums: bool = False,
return_not_enough_cells: bool = False,
) -> pd.Series:
if n_cells <= 0:
raise ValueError(
f"Expected `n_cells` to be positive, found `{n_cells}`.")
a_discrete, not_enough_cells = _fuzzy_to_discrete(
a_fuzzy=probs,
n_most_likely=n_cells,
remove_overlap=False,
raise_threshold=0.2,
check_row_sums=check_row_sums,
)
states = _series_from_one_hot_matrix(
membership=a_discrete,
index=self.adata.obs_names,
names=probs.names if isinstance(probs, Lineage) else None,
)
return (states,
not_enough_cells) if return_not_enough_cells else states
def test_normal_run(self):
a = np.array(
[[0, 0, 1], [0, 0, 1], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 1, 0]],
dtype="bool",
)
res = _series_from_one_hot_matrix(a)
assert_array_nan_equal(
np.array(res).astype(np.float32),
np.array([2, 2, np.nan, 0, 0, 1], dtype=np.float32),
)
np.testing.assert_array_equal(res.cat.categories, ["0", "1", "2"])
def test_normal_return(self):
a = np.array(
[[0, 0, 1], [0, 0, 1], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 1, 0]],
dtype="bool",
)
actual_series = _series_from_one_hot_matrix(a)
expected_series = pd.Series(index=range(6), dtype="category")
expected_series = expected_series.cat.add_categories(["0", "1", "2"])
expected_series[0] = "2"
expected_series[1] = "2"
expected_series[3] = "0"
expected_series[4] = "0"
expected_series[5] = "1"
assert actual_series.equals(expected_series)
assert (actual_series.cat.categories == expected_series.cat.categories).all()
