refactor: update is auto response right to is auto reward right

docs/trials_table_mapping.md

@@ -71,13 +71,13 @@ Columns are grouped by the raw source they map from.
 
 ### From `TrialOutcome.json` (`SoftwareEvents` stream)
 
-> **Note:** For `is_auto_response_right`, `True` means right and `False`
+> **Note:** For `is_auto_reward_right`, `True` means right and `False`
 > means left.
 
 | Trials column | Mapping |
 | --- | --- |
-| `auto_waterL` / `auto_waterR` | From `is_auto_response_right`. `1` on the auto-responded side; `0` on the other side, when there was no auto-response (`None`), or when the trial is missing. |
-| `bait_left` / `bait_right` | Boolean. `bait_right` is `True` if `p_reward_right == 1` and `is_auto_response_right` is `None` or `False`. `bait_left` is `True` if `p_reward_left == 1` and `is_auto_response_right` is `None` or `True`. |
+| `auto_waterL` / `auto_waterR` | From `is_auto_reward_right`. `1` on the auto-responded side; `0` on the other side, when there was no auto-response (`None`), or when the trial is missing. |
+| `bait_left` / `bait_right` | Boolean. `bait_right` is `True` if `p_reward_right == 1` and `is_auto_reward_right` is `None` or `False`. `bait_left` is `True` if `p_reward_left == 1` and `is_auto_reward_right` is `None` or `True`. |
 | `response_duration` | `response_deadline_duration`. |
 | `reward_consumption_duration` | `Trial -> reward_consumption_duration`. |
 | `reward_probabilityL` / `reward_probabilityR` | The **block** probability from `Trial -> metadata -> p_reward_left` / `p_reward_right`. The top-level `trial.p_reward_left` / `p_reward_right` is the per-trial probability, not the block probability, so it is not used here. `None` when the trial or its metadata is missing. |
@@ -152,6 +152,6 @@ These were mapped during exploration but are no longer in scope:
 | Date | Change |
 | --- | --- |
 | 2026-06-17 | `animal_response` now decodes the `Response` event's `{ "Item1": <time>, "Item2": <choice> }` payload via `Item2` (`True` → right `1`, `False` → left `0`, missing/`None` → no response `2`), rather than treating the whole payload as the choice. |
-| 2026-06-17 | `auto_waterL` / `auto_waterR` now encode no auto-response (`is_auto_response_right` is `None`) and missing trials as `0` instead of `NULL`. The columns are non-nullable (`int`, default `0`). |
+| 2026-06-17 | `auto_waterL` / `auto_waterR` now encode no auto-response (`is_auto_reward_right` is `None`) and missing trials as `0` instead of `NULL`. The columns are non-nullable (`int`, default `0`). |
 | 2026-06-20 | Added `reward_size_left` / `reward_size_right` (reward volume in uL) from `task_parameters.reward_size`, and `side_bias` from the per-trial `TrialMetrics` event (`bias` field). |
 | 2026-06-20 | `reward_probabilityL` / `reward_probabilityR` now read the block probability from `trial.metadata.p_reward_left` / `p_reward_right` instead of the top-level per-trial `trial.p_reward_left` / `p_reward_right`. |

pyproject.toml

@@ -17,7 +17,7 @@ readme = "README.md"
 version = "0.0.0"
 
 dependencies = [
-    "aind-behavior-dynamic-foraging[data] @ git+https://github.com/AllenNeuralDynamics/Aind.Behavior.DynamicForaging.git@f517d14ff965763a8f713b8a1be5dfb26b9312e1",
+    "aind-behavior-dynamic-foraging[data] @ git+https://github.com/AllenNeuralDynamics/Aind.Behavior.DynamicForaging.git@baab12133b22f599c1ba0583260eca9eca216cc0",
     "ipykernel",
 ]
 

src/dynamic_foraging_processing/processing/_trial_table.py

@@ -327,18 +327,18 @@ def _is_baited(trial: t.Optional[Trial], *, is_right: bool) -> bool:
         probability is ``1``) *and* the trial was not auto-responded to *that
         same* port.
 
-        ``is_auto_response_right`` encodes the auto-response: ``True`` means the
+        ``is_auto_reward_right`` encodes the auto-response: ``True`` means the
         trial was auto-responded to the right, ``False`` to the left, and
         ``None`` means there was no auto-response.
 
         In plain English, for the right port the conditions are:
 
         * ``p_reward_right == 1`` — reward is certain on the right, and
         * the trial was *not* auto-responded to the right
-          (``is_auto_response_right`` is ``None`` or ``False``).
+          (``is_auto_reward_right`` is ``None`` or ``False``).
 
         The left port is the mirror image (``p_reward_left == 1`` and not
-        auto-responded to the left, i.e. ``is_auto_response_right`` is ``None``
+        auto-responded to the left, i.e. ``is_auto_reward_right`` is ``None``
         or ``True``).
 
         Parameters
@@ -358,25 +358,25 @@ def _is_baited(trial: t.Optional[Trial], *, is_right: bool) -> bool:
         --------
         Right port guaranteed reward, no auto-response → baited:
 
-        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_response_right=None)
+        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_reward_right=None)
         >>> TrialTableBuilder._is_baited(trial, is_right=True)
         True
 
         Same trial, but auto-responded to the right collects (forfeits) the bait:
 
-        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_response_right=True)
+        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_reward_right=True)
         >>> TrialTableBuilder._is_baited(trial, is_right=True)
         False
 
         Left port without guaranteed reward → not baited:
 
-        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_response_right=None)
+        >>> trial = Trial(p_reward_right=1, p_reward_left=0, is_auto_reward_right=None)
         >>> TrialTableBuilder._is_baited(trial, is_right=False)
         False
         """
         if trial is None:
             return False
-        auto = trial.is_auto_response_right
+        auto = trial.is_auto_reward_right
         if is_right:
             # Right stays baited unless the animal was auto-responded right.
             return trial.p_reward_right == 1 and auto in (None, False)
@@ -385,16 +385,16 @@ def _is_baited(trial: t.Optional[Trial], *, is_right: bool) -> bool:
 
     @staticmethod
     def _auto_water(trial: t.Optional[Trial], *, is_right: bool) -> int:
-        """Encode autowater for a side from ``is_auto_response_right``.
+        """Encode autowater for a side from ``is_auto_reward_right``.
 
         Returns ``1`` if the auto response was to the requested side, else ``0``.
-        A missing trial or no auto-response (``is_auto_response_right`` is
+        A missing trial or no auto-response (``is_auto_reward_right`` is
         ``None``) counts as no autowater (``0``). ``is_right`` is ``True`` for
         right.
         """
-        if trial is None or trial.is_auto_response_right is None:
+        if trial is None or trial.is_auto_reward_right is None:
             return 0
-        return int(trial.is_auto_response_right is is_right)
+        return int(trial.is_auto_reward_right is is_right)
 
     @staticmethod
     def _block_reward_probability(trial: t.Optional[Trial], *, is_right: bool) -> t.Optional[float]:

src/dynamic_foraging_processing/utils/rewards.py

@@ -46,7 +46,7 @@ def get_annotated_rewards(
       timestamps are correlated to the reward-delivery timestamps with
       :func:`find_closest_timestamps`.
     - ``automatic`` -- otherwise, when the matching trial auto-responded
-      (``is_auto_response_right is not None``).
+      (``is_auto_reward_right is not None``).
     - ``earned`` -- otherwise (no matching trial, or no auto-response).
 
     Parameters
@@ -80,7 +80,7 @@ def get_annotated_rewards(
     for trial_index in trial_indices_in_reward_times:
         outcome = _parse_outcome(trial_outcome_df.iloc[trial_index]["data"])
         trial = outcome.trial if outcome is not None else None
-        if trial is None or trial.is_auto_response_right is None:
+        if trial is None or trial.is_auto_reward_right is None:
             annotated_rewards.append("earned")
         else:
             annotated_rewards.append("automatic")

tests/test_nwb/test_acquisition/test_acquisition_builder.py

@@ -67,7 +67,7 @@ def _outcome_payload(auto) -> dict:
             "reward_consumption_duration": 1.0,
             "quiescence_period_duration": 0.5,
             "inter_trial_interval_duration": 4.0,
-            "is_auto_response_right": auto,
+            "is_auto_reward_right": auto,
         },
         "is_right_choice": True,
         "is_rewarded": True,

tests/test_processing/test_trial_table.py

@@ -104,7 +104,7 @@ def _outcome(
         "reward_consumption_duration": 1.0,
         "quiescence_period_duration": 0.5,
         "inter_trial_interval_duration": 4.0,
-        "is_auto_response_right": auto,
+        "is_auto_reward_right": auto,
     }
     if block_p_left is not None or block_p_right is not None:
         trial["metadata"] = {"p_reward_left": block_p_left, "p_reward_right": block_p_right}

tests/test_utils/test_rewards.py

@@ -19,7 +19,7 @@ def _outcome_payload(auto=None) -> dict:
             "reward_consumption_duration": 1.0,
             "quiescence_period_duration": 0.5,
             "inter_trial_interval_duration": 4.0,
-            "is_auto_response_right": auto,
+            "is_auto_reward_right": auto,
         },
         "is_right_choice": True,
         "is_rewarded": True,
@@ -46,7 +46,7 @@ def test_get_annotated_rewards_marks_default_trials_as_earned():
 
 
 def test_get_annotated_rewards_marks_auto_response_trials_as_automatic():
-    """Trials with ``is_auto_response_right`` set (either side) are ``automatic``."""
+    """Trials with ``is_auto_reward_right`` set (either side) are ``automatic``."""
     reward_times = np.array([0.15, 0.42])
     trial_outcome_df = _trial_outcome_df(np.array([0.1, 0.4]), autos=[True, False])