[BUG] dev_to_val and val_to_dev does not respect inplace

chainladder/core/base.py

@@ -32,7 +32,6 @@
 from typing import Optional, TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from chainladder import Triangle
     from pandas import DataFrame, Series
     from numpy.typing import ArrayLike
     from pandas.core.indexes.datetimes import DatetimeIndex
@@ -666,12 +665,16 @@ def get_array_module(
                 + ", ".join([*modules])
             ) from e
 
-    def _auto_sparse(self) -> Triangle:
+    def _auto_sparse(self) -> None:
         """
         Auto sparsifies at 30Mb or more and 20% density or less.
+
+        Returns
+        -------
+            None
         """
         if not options.AUTO_SPARSE:
-            return self
+            return None
         n = np.prod(list(self.shape) + [8 / 1e6])
         if (
             self.array_backend == "numpy"
@@ -683,7 +686,7 @@ def _auto_sparse(self) -> Triangle:
             self.values.density < 0.2 and n > 30
         ):
             self.set_backend("numpy", inplace=True)
-        return self
+        return None
 
     @property
     def valuation(self):

chainladder/core/pandas.py

@@ -1313,7 +1313,7 @@ def agg_func(
             )
         obj._set_slicers()
         if auto_sparse:
-            obj = obj._auto_sparse()
+            obj._auto_sparse()
         obj.values = cast("BackendArray", num_to_nan(obj.values))
         if not keepdims and obj.shape == (1, 1, 1, 1):
             return obj.values[0, 0, 0, 0]
@@ -1380,7 +1380,7 @@ def aggregate(i, obj, axis, v):
             obj.odims = odims.values
         obj._set_slicers()
         if auto_sparse:
-            obj = obj._auto_sparse()
+            obj._auto_sparse()
         return obj
 
     set_method(cls=cls, func=agg_func, k=k)

chainladder/core/tests/test_grain.py

@@ -10,8 +10,19 @@
     from chainladder import Triangle
 
 
-def test_grain(qtr):
-    # this test is dense only in practice, since grain() applies auto_sparse, which is True by default
+def test_grain(qtr: Triangle) -> None:
+    """
+    Tests quarterly to annual grain conversion
+
+    Parameters
+    ----------
+    qtr : Triangle
+        The qtr sample dataset Triangle.
+
+    Returns
+    -------
+    None
+    """
     actual = qtr.iloc[0, 0].grain("OYDY")
     nan = np.nan
     expected = np.array([
@@ -28,7 +39,7 @@ def test_grain(qtr):
         [21, 422, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
         [13, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan],
     ])
-    np.testing.assert_array_equal(actual.values[0, 0, :, :], expected)
+    np.testing.assert_array_equal(actual.to_frame().values, expected)
 
 
 def test_grain_returns_valid_tri(qtr):

chainladder/core/tests/test_triangle.py

@@ -472,10 +472,9 @@ def test_dev_to_val_inplace_on_val_tri_returns_self(qtr: Triangle) -> None:
     """
     val_tri = qtr.dev_to_val()
     assert val_tri.is_val_tri
-
-    result = val_tri.dev_to_val(inplace=True)
-
-    assert result is val_tri
+    new_val_tri = val_tri.copy()
+    new_val_tri.dev_to_val(inplace=True)
+    assert new_val_tri == val_tri
 
 
 def test_valdev2(qtr):
@@ -491,8 +490,25 @@ def test_valdev3(qtr):
 
 
 def test_valdev4(raa: Triangle) -> None:
-    lhs = raa.dev_to_val()[raa.dev_to_val().development >= "1989"].values.flatten()
-    rhs = raa[raa.valuation >= "1989"].dev_to_val().values.flatten()
+    """
+    Tests slicing using the development axis of a valuation Triangle
+
+    Parameters
+    ----------
+    raa : Triangle
+        The raa sample dataset Triangle.
+
+    Returns
+    -------
+    None
+    """
+    lhs = (
+        raa
+        .dev_to_val()[raa.dev_to_val().development >= "1989"]
+        .to_frame()
+        .values.flatten()
+    )
+    rhs = raa[raa.valuation >= "1989"].dev_to_val().to_frame().values.flatten()
     np.testing.assert_array_equal(lhs[~np.isnan(lhs)], rhs[~np.isnan(rhs)])
 
 
@@ -1011,8 +1027,8 @@ def test_auto_sparse_disabled_returns_self(prism: Triangle) -> None:
     dense = small_prism.set_backend("numpy")
     cl.options.set_option("AUTO_SPARSE", False)
     try:
-        result = dense._auto_sparse()
-        assert result is dense
+        result = dense.copy()
+        result._auto_sparse()
         assert result.array_backend == "numpy"
     finally:
         cl.options.reset_option("AUTO_SPARSE")
@@ -1165,9 +1181,9 @@ def test_auto_sparse_converts_numpy_to_sparse(prism: Triangle) -> None:
     dense = small_prism.set_backend("numpy")
     assert dense.array_backend == "numpy"
 
-    result = dense._auto_sparse()
+    result = dense.copy()
+    result._auto_sparse()
 
-    assert result is dense
     assert result.array_backend == "sparse"
 
 
@@ -3433,7 +3449,7 @@ def test_feed_age_into_valuation_raises() -> None:
 
 def test_fill(clrd: Triangle) -> None:
     """
-    ``Fill`` method works as intended
+    ``fill`` method works as intended
     """
     fill_tri = clrd.iloc[2:4, 4:6].fill(100)
     # (10 + 1) * 10 / 2 is the number of valid values in one single triangle
@@ -3445,8 +3461,33 @@ def test_fill(clrd: Triangle) -> None:
 
 def test_full_fill(raa: Triangle) -> None:
     """
-    ``Fill`` method works as intended on full triangle
+    ``fill`` method works as intended on full triangle
     """
     full_tri = cl.Chainladder().fit(raa).full_triangle_
     fill_full_tri = full_tri.fill(200)
     assert np.all(fill_full_tri.values == np.broadcast_to([200], (1, 1, 10, 12)))
+
+
+def test_dev_val_inplace(raa: Triangle) -> None:
+    """
+    ``dev_to_val`` and ``val_to_dev`` methods respect ``inplace``
+
+    Parameters
+    ----------
+    raa : Triangle
+        The raa sample data set.
+
+    Returns
+    -------
+    None
+    """
+    raa_copy = raa.copy()
+    raa_copy2 = raa.copy()
+    assert raa_copy2.dev_to_val(True) is None
+    assert raa_copy == raa
+    assert raa_copy2 == raa_copy.dev_to_val()
+    raa_copy = raa.copy().dev_to_val()
+    raa_copy2 = raa_copy.copy()
+    assert raa_copy2.val_to_dev(True) is None
+    assert raa_copy2 == raa
+    assert raa_copy == raa_copy2.dev_to_val()