Update HDMF pin to 4.1.2 and shape error test

Author: rly

CHANGELOG.md

@@ -13,6 +13,7 @@
 
 ### Changed
 - Change UI of documentation assistant to be an accordion that is always visible. @bendichter [#2124](https://github.com/NeurodataWithoutBorders/pynwb/pull/2124)
+- Updated minimum HDMF version to 4.1.2 and updated tests accordingly. @rly []()
 
 
 ## PyNWB 3.1.2 (August 13, 2025)

environment-ros3.yml

@@ -6,7 +6,7 @@ channels:
 dependencies:
   - python==3.13
   - h5py==3.12.1
-  - hdmf==4.1.0
+  - hdmf==4.1.2
   - matplotlib==3.9.2
   - numpy==2.1.3
   - pandas==2.2.3

pyproject.toml

@@ -34,7 +34,7 @@ classifiers = [
 ]
 dependencies = [
     "h5py>=3.2.0",
-    "hdmf>=4.1.0,<5",
+    "hdmf>=4.1.2,<5",
     "numpy>=1.24.0",
     "pandas>=1.2.0",
     "python-dateutil>=2.8.2",

requirements-min.txt

@@ -1,6 +1,6 @@
 # minimum versions of package dependencies for installing PyNWB
 h5py==3.2.0
-hdmf==4.1.1
+hdmf==4.1.2
 numpy==1.24.0
 pandas==1.2.0
 python-dateutil==2.8.2

requirements.txt

@@ -1,6 +1,6 @@
 # pinned dependencies to reproduce an entire development environment to use PyNWB
 h5py==3.12.1
-hdmf==4.1.1
+hdmf==4.1.2
 numpy==2.1.1; python_version > "3.9"  # numpy 2.1+ is not compatible with py3.9
 numpy==2.0.2; python_version == "3.9"
 pandas==2.2.3

tests/unit/test_ecephys.py

@@ -86,8 +86,11 @@ def test_link(self):
 
     def test_invalid_data_shape(self):
         table, region = self._create_table_and_region()
-        with self.assertRaisesWith(ValueError, ("ElectricalSeries.__init__: incorrect shape for 'data' (got '(2, 2, 2, "
-                                                "2)', expected '((None,), (None, None), (None, None, None))')")):
+        msg = (
+            "ElectricalSeries.__init__: incorrect shape for data: got (2, 2, 2, 2), "
+            "and expected (*,) or (*, *) or (*, *, *)"
+        )
+        with self.assertRaisesWith(ValueError, msg):
             ElectricalSeries(name='test_ts1', data=np.ones((2, 2, 2, 2)), electrodes=region,
                              timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])