Accept array-like input vars with no dimension labels (#126)

* infer dimension labels + clean-up

* add test

* update release notes

* black

doc/whats_new.rst

@@ -10,6 +10,10 @@ Enhancements
 ~~~~~~~~~~~~
 
 - Added :attr:`xsimlab.Model.cache` public property (:issue:`125`).
+- Parameter ``input_vars`` of :func:`~xsimlab.create_setup` and
+  :func:`xarray.Dataset.xsimlab.update_vars` now accepts array-like values
+  with no explicit dimension label(s), in this case those labels are inferred
+  from model variables' metadata (:issue:`126`).
 
 Bug fixes
 ~~~~~~~~~

xsimlab/tests/test_xr_accessor.py

@@ -196,12 +196,19 @@ def test_set_input_vars(self, model, in_dataset):
             xr.testing.assert_equal(ds[vname], in_dataset[vname])
             assert ds[vname].attrs == in_dataset[vname].attrs
 
+        # test errors
         in_vars[("not_an", "input_var")] = None
 
         with pytest.raises(KeyError) as excinfo:
             ds.xsimlab._set_input_vars(model, in_vars)
         assert "not valid key(s)" in str(excinfo.value)
 
+        # test implicit dimension label
+        in_vars = {("add", "offset"): [1, 2, 3, 4, 5]}
+        ds.xsimlab._set_input_vars(model, in_vars)
+
+        assert ds["add__offset"].dims == ("x",)
+
     def test_update_clocks(self, model):
         ds = xr.Dataset()
         with pytest.raises(ValueError) as excinfo:

xsimlab/xr_accessor.py

@@ -296,16 +296,24 @@ def _set_input_vars(self, model, input_vars):
                 + f" is/are not valid key(s) for input variables in model {model}",
             )
 
-        for (p_name, var_name), data in input_vars.items():
-            p_obj = model[p_name]
-            var = variables_dict(type(p_obj))[var_name]
+        for var_key, data in input_vars.items():
+            var_metadata = model.cache[var_key]["metadata"]
+            xr_var_name = model.cache[var_key]["name"]
 
-            xr_var_name = p_name + "__" + var_name
-            xr_var = as_variable(data)
+            try:
+                xr_var = as_variable(data)
+            except TypeError:
+                # try retrieve dimension labels from model variable's
+                # dimension labels that match the number of dimensions
+                ndims = len(np.shape(data))
+                dim_labels = {len(d): d for d in var_metadata["dims"]}
+                dims = dim_labels[ndims]
+
+                xr_var = as_variable((dims, data))
 
-            if var.metadata["description"]:
-                xr_var.attrs["description"] = var.metadata["description"]
-            xr_var.attrs.update(var.metadata["attrs"])
+            if var_metadata["description"]:
+                xr_var.attrs["description"] = var_metadata["description"]
+            xr_var.attrs.update(var_metadata["attrs"])
 
             # maybe delete first to avoid merge conflicts
             # (we just want to replace here)
@@ -851,6 +859,9 @@ def create_setup(
         Values are anything that can be easily converted to
         :class:`xarray.Variable` objects, e.g., single values, array-like,
         ``(dims, data, attrs)`` tuples or xarray objects.
+        For array-like values with no dimension labels, xarray-simlab will look
+        in ``model`` variables metadata for labels matching the number
+        of dimensions of those arrays.
     output_vars : dict, optional
         Dictionary with model variable names to save as simulation output
         (time-dependent or time-independent). Entries of the dictionary look