updated tests

sleap_io/io/main.py

@@ -58,11 +58,7 @@ def load_nwb(filename: str) -> Labels:
     Returns:
         The dataset as a `Labels` object.
     """
-    with NWBHDF5IO(filename, "r", load_namespaces=True) as io:
-        nwb_processing = io.read().processing
-        if any("PoseTraining" in module for module in nwb_processing.values()):
-            return nwb.read_nwb_training(nwb_processing)
-        return nwb.read_nwb(filename)
+    return nwb.read_nwb(filename)
 
 
 def save_nwb(

sleap_io/io/nwb.py

@@ -823,7 +823,7 @@ def build_pose_estimation_container_for_track(
     for i, video in enumerate(labels.videos):
         camera = nwbfile.create_device(
             name=f"camera {i}",
-            description="Camera used to record video {i}",
+            description=f"Camera used to record video {i}",
             manufacturer="No specified manufacturer",
         )
         cameras.append(camera)

tests/io/test_main.py

@@ -24,10 +24,24 @@ def test_load_slp(slp_typical):
 
 def test_nwb(tmp_path, slp_typical):
     labels = load_slp(slp_typical)
-    save_nwb(labels, tmp_path / "test.nwb")
+    save_nwb(labels, tmp_path / "test_nwb.nwb", False)
     loaded_labels = load_nwb(tmp_path / "test_nwb.nwb")
     assert type(loaded_labels) == Labels
     assert type(load_file(tmp_path / "test_nwb.nwb")) == Labels
+    assert len(loaded_labels) == len(labels)
+
+    labels2 = load_slp(slp_typical)
+    labels2.videos[0].filename = "test"
+    save_nwb(labels2, tmp_path / "test_nwb.nwb", append=True)
+    loaded_labels = load_nwb(tmp_path / "test_nwb.nwb")
+    assert type(loaded_labels) == Labels
+    assert len(loaded_labels) == (len(labels) + len(labels2))
+    assert len(loaded_labels.videos) == 2
+
+
+def test_nwb_training(tmp_path, slp_typical):
+    labels = load_slp(slp_typical) 
+    save_nwb(labels, tmp_path / "test_nwb.nwb", True)
 
 
 def test_labelstudio(tmp_path, slp_typical):