fix: serialization was broken for N>1D complex storage histograms

src/boost_histogram/histogram.py

@@ -1250,7 +1250,7 @@ def __setitem__(self, index: IndexingExpr, value: ArrayLike | Accumulator) -> No
                     pass
 
                 else:
-                    msg = f"Mismatched shapes in dimension {n}"
+                    msg = f"Mismatched shapes {value_shape} in dimension {n}"
                     msg += f", {value_shape[n]} != {request_len}"
                     if use_underflow or use_overflow:
                         msg += f" or {request_len + use_underflow + use_overflow}"

src/boost_histogram/serialization/_storage.py

@@ -108,11 +108,9 @@ def _data_from_dict(data: dict[str, Any], /) -> np.typing.NDArray[Any]:
     if storage_type in {"int", "double"}:
         return data["values"]
     if storage_type == "weighted":
-        return np.stack([data["values"], data["variances"]]).T
+        return np.stack([data["values"], data["variances"]], axis=-1)
     if storage_type == "mean":
-        return np.stack(
-            [data["counts"], data["values"], data["variances"]],
-        ).T
+        return np.stack([data["counts"], data["values"], data["variances"]], axis=-1)
     if storage_type == "weighted_mean":
         return np.stack(
             [
@@ -121,6 +119,7 @@ def _data_from_dict(data: dict[str, Any], /) -> np.typing.NDArray[Any]:
                 data["values"],
                 data["variances"],
             ],
-        ).T
+            axis=-1,
+        )
 
     raise TypeError(f"Unsupported storage type: {storage_type}")

tests/test_serialization_uhi.py

@@ -151,9 +151,6 @@ def test_round_trip_weighted() -> None:
     data = to_uhi(h)
     h2 = from_uhi(data)
 
-    print(h.view())
-    print(h2.view())
-
     assert pytest.approx(np.array(h.axes[0])) == np.array(h2.axes[0])
     assert np.asarray(h) == pytest.approx(h2)
 
@@ -285,3 +282,29 @@ def test_remove_writer_info() -> None:
         "writer_info": {"boost-histogram": {"foo": "bar"}},
     }
     assert remove_writer_info(d, library="c") == d
+
+
+def test_convert_weight() -> None:
+    h = bh.Histogram(
+        bh.axis.Regular(3, 13, 10, __dict__={"name": "x"}),
+        bh.axis.StrCategory(["one", "two"]),
+        storage=bh.storage.Weight(),
+    )
+    data = h._to_uhi_()
+    h2 = bh.Histogram(data)
+
+    assert h == h2
+
+
+def test_convert_weightmean() -> None:
+    h = bh.Histogram(
+        bh.axis.Regular(12, 0, 1),
+        bh.axis.StrCategory(["a", "b", "c", "d", "e", "f", "g"]),
+        bh.axis.Boolean(),
+        bh.axis.Integer(1, 18),
+        storage=bh.storage.WeightedMean(),
+    )
+    data = h._to_uhi_()
+    h2 = bh.Histogram(data)
+
+    assert h.axes == h2.axes