fix(memh5): fix a bug where shared dataset names weren't correct

caput/memh5.py

@@ -2492,7 +2492,12 @@ def deep_group_copy(
     """
     Copy full data tree from one group to another.
 
-    Copies from g1 to g2. An axis downselection can be specified by supplying the
+    Copies from g1 to g2:
+    - The default behaviour creates a shallow copy of each dataset
+    - When deep_copy_dsets is True, datasets are fully deep copied
+    - Any datasets in `shared` will point to the object in g1 storage
+
+    An axis downselection can be specified by supplying the
     parameter 'selections'. For example to select the first two indexes in
     g1["foo"]["bar"], do
 
@@ -2534,6 +2539,8 @@ def deep_group_copy(
         enabled could break legacy code, so be very careful
     shared : list, optional
         List of datasets to share, if `deep_copy_dsets` is True. Otherwise, no effect.
+        Shared datasets just point to the existing object in g1 storage, and override
+        any other behaviour
 
     Returns
     -------
@@ -2547,6 +2554,7 @@ def deep_group_copy(
     # only the case if zarr is not installed
     if file_format.module is None:
         raise RuntimeError("Can't deep_group_copy zarr file. Please install zarr.")
+
     to_file = isinstance(g2, file_format.module.Group)
 
     # Prepare a dataset for writing out, applying selections and transforming any
@@ -2603,6 +2611,10 @@ def _prepare_dataset(dset):
             # needed until fixed: https://github.com/mpi4py/mpi4py/issues/177
             data = ensure_native_byteorder(data)
 
+        if deep_copy_dsets:
+            # Make sure that we get a deep copy of this dataset
+            data = deep_copy_dataset(data)
+
         dset_args = {"dtype": data.dtype, "shape": data.shape, "data": data}
         # If we're copying memory to memory we can allow distributed datasets
         if not to_file and isinstance(dset, MemDatasetDistributed):
@@ -2644,9 +2656,13 @@ def _prepare_compression_args(dset):
 
         return compression_kwargs
 
+    # Make sure shared dataset names are properly formatted
+    shared = {"/" + k if k[0] != "/" else k for k in shared}
+
     # Do a non-recursive traversal of the tree, recreating the structure and attributes,
     # and copying over any non-distributed datasets
     stack = [g1]
+
     while stack:
         entry = stack.pop()
         key = entry.name
@@ -2655,20 +2671,25 @@ def _prepare_compression_args(dset):
             if key != g1.name:
                 # Only create group if we are above the starting level
                 g2.create_group(key)
+
             stack += [entry[k] for k in sorted(entry, reverse=True)]
-        else:  # Is a dataset
-            dset_args = _prepare_dataset(entry)
-            compression_kwargs = _prepare_compression_args(entry)
-
-            if deep_copy_dsets and key not in shared:
-                # Make a deep copy of the dataset
-                dset_args["data"] = deep_copy_dataset(dset_args["data"])
-
-            g2.create_dataset(
-                key,
-                **dset_args,
-                **compression_kwargs,
-            )
+        else:
+            # This is a dataset
+            if key in shared:
+                # Just point to the existing dataset
+                parent_name, name = posixpath.split(posixpath.join(g2.name, key))
+                parent_name = format_abs_path(parent_name)
+                # Get the proper storage location for this dataset
+                g2[parent_name]._get_storage()[name] = g1._get_storage()[key]
+            else:
+                dset_args = _prepare_dataset(entry)
+                compression_kwargs = _prepare_compression_args(entry)
+
+                g2.create_dataset(
+                    key,
+                    **dset_args,
+                    **compression_kwargs,
+                )
 
         target = g2[key]
         copyattrs(entry.attrs, target.attrs, convert_strings=convert_attribute_strings)