Add optional value column to EventsTable (#16)

spec/ndx-events.extensions.yaml

@@ -74,6 +74,14 @@ groups:
     neurodata_type_inc: DurationVectorData
     doc: Optional column containing the duration of each event, in seconds.
     quantity: '?'
+  - name: value
+    neurodata_type_inc: VectorData
+    doc: Optional column containing a value/parameter associated with each event.
+      For example, if you have three levels of reward (e.g., 1 drop, 2 drops, 3 drops),
+      instead of encoding each level of reward as its own event type (e.g., 'reward_value_1',
+      'reward_value_2', 'reward_value_3', you could encode 'reward' as the event type,
+      and the value for each event time could be 1, 2, or 3.
+    quantity: '?'
 - neurodata_type_def: TtlTypesTable
   neurodata_type_inc: EventTypesTable
   default_name: TtlTypesTable

src/pynwb/tests/test_events.py

@@ -281,6 +281,7 @@ def test_add_row(self):
             stimulus_type="",
             event_type=0,
             duration=0.1,
+            value="",
             # hed_tags=["(White, Circle)"],
         )
         events_table.add_row(
@@ -289,13 +290,15 @@ def test_add_row(self):
             stimulus_type="animal",
             event_type=1,
             duration=0.15,
+            value="giraffe",
         )
         events_table.add_row(
             timestamp=1.1,
             cue_type="green square",
             stimulus_type="",
             event_type=0,
             duration=0.1,
+            value="",
             # hed_tags=["(Green, Square)"],
         )
         events_table.add_row(
@@ -304,12 +307,14 @@ def test_add_row(self):
             stimulus_type="landscape",
             event_type=1,
             duration=0.15,
+            value="farm",
         )
         assert events_table["timestamp"].data == [0.1, 0.3, 1.1, 1.3]
         assert events_table["cue_type"].data == ["white circle", "", "green square", ""]
         assert events_table["stimulus_type"].data == ["", "animal", "", "landscape"]
         assert events_table["duration"].data == [0.1, 0.15, 0.1, 0.15]
         assert events_table["event_type"].data == [0, 1, 0, 1]
+        assert events_table["value"].data == ["", "giraffe", "", "farm"]
         # assert events_table["hed_tags"][0] == ["(White, Circle)"]
         # assert events_table["hed_tags"][2] == ["(Green, Square)"]
 
@@ -350,6 +355,7 @@ def test_roundtrip(self):
             stimulus_type="",
             event_type=0,
             duration=0.1,
+            value="",
             # hed_tags=["(White, Circle)"],
         )
         events_table.add_row(
@@ -358,13 +364,15 @@ def test_roundtrip(self):
             stimulus_type="animal",
             event_type=1,
             duration=0.15,
+            value="giraffe",
         )
         events_table.add_row(
             timestamp=1.1,
             cue_type="green square",
             stimulus_type="",
             event_type=0,
             duration=0.1,
+            value="",
             # hed_tags=["(Green, Square)"],
         )
         events_table.add_row(
@@ -373,6 +381,7 @@ def test_roundtrip(self):
             stimulus_type="landscape",
             event_type=1,
             duration=0.15,
+            value="farm",
         )
 
         task = Task()
@@ -396,6 +405,7 @@ def test_roundtrip(self):
             assert all(read_events_table["stimulus_type"].data[:] == ["", "animal", "", "landscape"])
             assert all(read_events_table["duration"].data[:] == [0.1, 0.15, 0.1, 0.15])
             assert all(read_events_table["event_type"].data[:] == [0, 1, 0, 1])
+            assert all(read_events_table["value"].data[:] == ["", "giraffe", "", "farm"])
             assert read_events_table["event_type"].table is read_event_types_table
 
 

src/spec/create_extension_spec.py

@@ -125,6 +125,19 @@ def main():
                 doc="Optional column containing the duration of each event, in seconds.",
                 quantity="?",
             ),
+            NWBDatasetSpec(
+                name="value",
+                neurodata_type_inc="VectorData",
+                doc=(
+                    "Optional column containing a value/parameter associated with each event. "
+                    "For example, if you have three levels of reward (e.g., 1 drop, 2 drops, "
+                    "3 drops), instead of encoding each level of reward as its own event "
+                    "type (e.g., 'reward_value_1', 'reward_value_2', 'reward_value_3', "
+                    "you could encode 'reward' as the event type, and the value for each "
+                    "event time could be 1, 2, or 3."
+                ),
+                quantity="?",
+            ),
         ],
     )