def test_fitted_copy(self):
m = FittedModel(
np.array([0, 1]),
np.array([2, 3]),
conf_int=np.array([[4, 5], [6, 7]]),
x_all=[4, 5],
y_all=(6, 7),
w_all=[8, 9],
)
fm = m.copy()
assert isinstance(fm, FittedModel)
assert fm.prepared
assert fm._gene == m._gene
assert fm._lineage == m._lineage
np.testing.assert_array_equal(fm.x_test, m.x_test)
assert fm.x_test is not m.x_test
np.testing.assert_array_equal(fm.y_test, m.y_test)
assert fm.y_test is not m.y_test
np.testing.assert_array_equal(fm.conf_int, m.conf_int)
assert fm.conf_int is not m.conf_int
np.testing.assert_array_equal(fm.x_all, m.x_all)
assert fm.x_all is not m.x_all
np.testing.assert_array_equal(fm.y_all, m.y_all)
assert fm.y_all is not m.y_all
np.testing.assert_array_equal(fm.w_all, m.w_all)
assert fm.y_all is not m.w_all
def test_from_model_normal_run(self, adata_cflare: AnnData):
m = create_model(adata_cflare).prepare(adata_cflare.var_names[0],
"1").fit()
m.predict()
m.confidence_interval()
fm = FittedModel.from_model(m)
assert fm.prepared
assert fm._gene == m._gene
assert fm._lineage == m._lineage
np.testing.assert_array_equal(fm.x_test, m.x_test)
assert fm.x_test is not m.x_test
np.testing.assert_array_equal(fm.y_test, m.y_test)
assert fm.y_test is not m.y_test
np.testing.assert_array_equal(fm.conf_int, m.conf_int)
assert fm.conf_int is not m.conf_int
np.testing.assert_array_equal(fm.x_all, m.x_all)
assert fm.x_all is not m.x_all
np.testing.assert_array_equal(fm.y_all, m.y_all)
assert fm.y_all is not m.y_all
np.testing.assert_array_equal(fm.w_all, m.w_all)
assert fm.y_all is not m.w_all
def test_wrong_conf_int_wrong_shape(self):
with pytest.raises(ValueError):
FittedModel(
np.array([0, 1]),
np.array([2, 3]),
conf_int=np.array([[4, 5], [6, 7], [8, 9]]),
)
def test_wrong_y_all_shape(self):
with pytest.raises(ValueError):
FittedModel(
np.array([[0, 1]]),
np.array([2, 3]),
x_all=np.array([[4, 5]]),
y_all=np.array([6, 8, 7]),
)
def test_only_partial_x_all(self):
fm = FittedModel(np.array([0, 1]), np.array([2, 3]), x_all=[4, 5], w_all=[6, 7])
np.testing.assert_array_equal(fm.x_test, [[0], [1]])
np.testing.assert_array_equal(fm.y_test, [2, 3])
assert fm.x_all is None
assert fm.w_all is None
assert fm.y_all is None
def test_zero_array(self):
fm = FittedModel(np.array([]), np.array([]))
np.testing.assert_array_equal(fm.x_test, np.array([[]]).reshape((0, 1)))
np.testing.assert_array_equal(fm.y_test, [])
assert fm.conf_int is None
assert fm.x_all is None
assert fm.w_all is None
assert fm.y_all is None
def test_non_array_input(self):
fm = FittedModel([0, 1, 2], [3, 4, 5])
np.testing.assert_array_equal(fm.x_test, [[0], [1], [2]])
np.testing.assert_array_equal(fm.y_test, [3, 4, 5])
assert fm.conf_int is None
assert fm.x_all is None
assert fm.w_all is None
assert fm.y_all is None
def test_wrong_conf_int(self):
fm = FittedModel(
np.array([0, 1]), np.array([2, 3]), conf_int=np.array([[4, 5], [6, 7]])
)
np.testing.assert_array_equal(fm.x_test, [[0], [1]])
np.testing.assert_array_equal(fm.y_test, [2, 3])
np.testing.assert_array_equal(fm.conf_int, [[4, 5], [6, 7]])
assert fm.x_all is None
assert fm.w_all is None
assert fm.y_all is None
def test_conf_int_raise_error_missing(self):
fm = FittedModel([0, 1, 2], [3, 4, 5])
with pytest.raises(RuntimeError):
fm.confidence_interval()
with pytest.raises(RuntimeError):
fm.default_confidence_interval()
def test_full_initialization(self):
fm = FittedModel(
np.array([0, 1]),
np.array([2, 3]),
conf_int=np.array([[4, 5], [6, 7]]),
x_all=[4, 5],
y_all=(6, 7),
w_all=[8, 9],
)
assert fm.prepared
np.testing.assert_array_equal(fm.x_test, [[0], [1]])
np.testing.assert_array_equal(fm.y_test, [2, 3])
np.testing.assert_array_equal(fm.conf_int, [[4, 5], [6, 7]])
np.testing.assert_array_equal(fm.x_all, [[4], [5]])
np.testing.assert_array_equal(fm.y_all, [[6], [7]])
np.testing.assert_array_equal(fm.w_all, [8, 9])
def test_normal_run(self):
fm = FittedModel(
np.array([0, 1]),
np.array([2, 3]),
conf_int=np.array([[4, 5], [6, 7]]),
x_all=[4, 5],
y_all=(6, 7),
w_all=[8, 9],
)
fm = fm.prepare()
assert fm is fm
fm = fm.fit()
assert fm is fm
np.testing.assert_array_equal(fm.predict(), [2, 3])
np.testing.assert_array_equal(fm.confidence_interval(), [[4, 5], [6, 7]])
np.testing.assert_array_equal(
fm.default_confidence_interval(), [[4, 5], [6, 7]]
)
def test_from_model_not_fitted_model(self, adata_cflare: AnnData):
m = create_model(adata_cflare).prepare(adata_cflare.var_names[0], "1")
with pytest.raises(ValueError):
FittedModel.from_model(m)
def from_model_wrong_type(self, adata_cflare):
m = create_model(adata_cflare)
with pytest.raises(TypeError):
FittedModel.from_model(m.model)
def test_wrong_xt_yt_shape(self):
with pytest.raises(ValueError):
FittedModel(np.array([1]), np.array([2, 3]))
def test_densify_only_first_axis(self):
with pytest.raises(ValueError):
FittedModel(np.array([[[0, 1]]]), np.array([2, 3]))
def test_wrong_conf_int_dim(self):
with pytest.raises(ValueError):
FittedModel(np.array([0, 1]), np.array([2, 3]), conf_int=np.array([4, 5]))
def test_wrong_xt_dum(self):
with pytest.raises(ValueError):
FittedModel(np.array([[0, 1], [1, 2]]), np.array([2, 3]))
