add release notes (#390)

Author: FabianHofmann

doc/release_notes.rst

@@ -4,6 +4,7 @@ Release Notes
 Upcoming Version
 ----------------
 
+* When creating slices for variables and constraints (important for the `solve` function), the slicing is now fixed in case now dimension to slice is available.
 * Added a pandas priority attribute. With this change, the operation with pandas objects is now prioritizing linopy objects over pandas objects. This is useful when the using linopy objects in arithmetic operations with pandas objects, e.g. `a * x` where `a` is a pandas Series/DataFrame and `x` is a linopy variable.
 * The method :meth:`model.to_file <linopy.model.Model.to_file>` now includes a progress argument to enable or disable the progress bar while writing.
 

linopy/common.py

@@ -523,6 +523,10 @@ def iterate_slices(
 
     # leading dimension (the dimension with the largest size)
     sizes = {dim: ds.sizes[dim] for dim in slice_dims}
+    if not sizes:
+        yield ds
+        return
+
     leading_dim = max(sizes, key=sizes.get)  # type: ignore
     size_of_leading_dim = ds.sizes[leading_dim]
 

test/test_common.py

@@ -522,14 +522,22 @@ def test_iterate_slices_slice_size_none():
         assert ds.equals(s)
 
 
-def test_iterate_slices_invalid_slice_dims():
+def test_iterate_slices_empty_slice_dims():
     ds = xr.Dataset(
         {"var": (("x", "y"), np.random.rand(10, 10))},  # noqa: NPY002
         coords={"x": np.arange(10), "y": np.arange(10)},
     )
-    with pytest.raises(ValueError):
-        list(iterate_slices(ds, slice_size=50, slice_dims=[]))
+    slices = list(iterate_slices(ds, slice_size=50, slice_dims=[]))
+    assert len(slices) == 1
+    for s in slices:
+        assert ds.equals(s)
+
 
+def test_iterate_slices_invalid_slice_dims():
+    ds = xr.Dataset(
+        {"var": (("x", "y"), np.random.rand(10, 10))},  # noqa: NPY002
+        coords={"x": np.arange(10), "y": np.arange(10)},
+    )
     with pytest.raises(ValueError):
         list(iterate_slices(ds, slice_size=50, slice_dims=["z"]))