Merge branch 'dev' into improve_html_repr_of_data

.github/workflows/project_action.yml

@@ -20,15 +20,15 @@ jobs:
       - name: Add to Developer Board
         env:
           TOKEN: ${{ steps.generate_token.outputs.token }}
-        uses: actions/[email protected].1
+        uses: actions/[email protected].2
         with:
           project-url: https://github.com/orgs/hdmf-dev/projects/7
           github-token: ${{ env.TOKEN }}
 
       - name: Add to Community Board
         env:
           TOKEN: ${{ steps.generate_token.outputs.token }}
-        uses: actions/[email protected].1
+        uses: actions/[email protected].2
         with:
           project-url: https://github.com/orgs/hdmf-dev/projects/8
           github-token: ${{ env.TOKEN }}

CHANGELOG.md

@@ -1,18 +1,15 @@
 # HDMF Changelog
 
-## HDMF 3.14.6 (Upcoming)
-
-### Bug fixes
-- Fixed mamba-related error in conda-based GitHub Actions. @rly [#1194](https://github.com/hdmf-dev/hdmf/pull/1194)
-
-## HDMF 3.14.5 (September 17, 2024)
+## HDMF 3.14.5 (Upcoming)
 
 ### Enhancements
 - Added support for overriding backend configurations of `h5py.Dataset` objects in `Container.set_data_io`. @pauladkisson [#1172](https://github.com/hdmf-dev/hdmf/pull/1172)
 
 ### Bug fixes
 - Fixed bug in writing of string arrays to an HDF5 file that were read from an HDF5 file that was introduced in 3.14.4. @rly @stephprince
   [#1189](https://github.com/hdmf-dev/hdmf/pull/1189)
+- Fixed export of scalar datasets with a compound data type. @stephprince [#1185](https://github.com/hdmf-dev/hdmf/pull/1185)
+- Fixed mamba-related error in conda-based GitHub Actions. @rly [#1194](https://github.com/hdmf-dev/hdmf/pull/1194)
 
 ## HDMF 3.14.4 (September 4, 2024)
 

src/hdmf/backends/hdf5/h5tools.py

@@ -700,6 +700,10 @@ def __read_dataset(self, h5obj, name=None):
                 kwargs['dtype'] = d.dtype
             elif h5obj.dtype.kind == 'V':  # scalar compound data type
                 kwargs['data'] = np.array(scalar, dtype=h5obj.dtype)
+                cpd_dt = h5obj.dtype
+                ref_cols = [check_dtype(ref=cpd_dt[i]) or check_dtype(vlen=cpd_dt[i]) for i in range(len(cpd_dt))]
+                d = BuilderH5TableDataset(h5obj, self, ref_cols)
+                kwargs['dtype'] = HDF5IO.__compound_dtype_to_list(h5obj.dtype, d.dtype)
             else:
                 kwargs["data"] = scalar
         else:

src/hdmf/validate/validator.py

@@ -147,7 +147,7 @@ def get_type(data, builder_dtype=None):
     # Case for h5py.Dataset and other I/O specific array types
     else:
         # Compound dtype
-        if builder_dtype and len(builder_dtype) > 1:
+        if builder_dtype and isinstance(builder_dtype, list):
             dtypes = []
             string_formats = []
             for i in range(len(builder_dtype)):
@@ -441,7 +441,7 @@ def validate(self, **kwargs):
             except EmptyArrayError:
                 # do not validate dtype of empty array. HDMF does not yet set dtype when writing a list/tuple
                 pass
-        if builder.dtype is not None and len(builder.dtype) > 1 and len(np.shape(builder.data)) == 0:
+        if isinstance(builder.dtype, list) and len(np.shape(builder.data)) == 0:
             shape = ()  # scalar compound dataset
         elif isinstance(builder.dtype, list):
             shape = (len(builder.data), )  # only 1D datasets with compound types are supported