Import pose

CHANGELOG.md

@@ -14,8 +14,10 @@
     - Set `probe_id` as `probe_description` when inserting from nwb file #1220
     - Default `AnalysisNwbfile.create` permissions are now 777 #1226
 - Position
+    - Allow population of missing `PositionIntervalMap` entries during population of `DLCPoseEstimation` #1208
     - Allow population of missing `PositionIntervalMap` entries during population
         of `DLCPoseEstimation` #1208
+    - Enable import of existing pose data to `ImportedPose` in position pipeline #1225
 
 ## [0.5.4] (December 20, 2024)
 

docs/src/ForDevelopers/UsingNWB.md

@@ -256,6 +256,14 @@ hdmf.common.table.DynamicTable </b>
 | PositionSource.SpatialSeries |           id           |   int(nwbf.processing.behavior.position.\[index\]) (the enumerated index number) |               |                       |
 | RawPosition.PosObject        | raw_position_object_id |                            nwbf.processing.behavior.position.\[index\].object_id |               |                       |
 
+<b> NWBfile Location: nwbf.processing.behavior.PoseEstimation </br> Object type:
+(ndx_pose.PoseEstimation) </b>
+
+| Spyglass Table               |          Key           |                                                                 NWBfile Location | Config option |                 Notes |
+| :--------------------------- | :--------------------: | -------------------------------------------------------------------------------: | ------------: | --------------------: |
+| ImportedPose | interval_list_name | pose_{PoseEstimation.name}_valid_times |
+| ImportedPose.BodyPart | pose | nwbf.processing.behavior.PoseEstimation.pose_estimation_series.name |
+
 <b> NWBfile Location: nwbf.processing.video_files.video </br> Object type:
 pynwb.image.ImageSeries </b>
 

pyproject.toml

@@ -15,6 +15,7 @@ authors = [
     { name = "Ryan Ly", email = "rly@lbl.gov" },
     { name = "Daniel Gramling", email = "daniel.gramling@ucsf.edu" },
     { name = "Chris Brozdowski", email = "chris.broz@ucsf.edu" },
+    { name = "Samuel Bray", email = "sam.bray@ucsf.edu" },
 ]
 classifiers = [
     "Programming Language :: Python :: 3",
@@ -45,6 +46,7 @@ dependencies = [
     "ipympl",
     "matplotlib",
     "ndx_franklab_novela>=0.1.0",
+    "ndx-pose",
     "non_local_detector",
     "numpy",
     "opencv-python",

src/spyglass/common/populate_all_common.py

@@ -83,6 +83,8 @@ def single_transaction_make(
             if table.__name__ == "PositionSource":
                 # PositionSource only uses nwb_file_name - full calls redundant
                 key_source = dj.U("nwb_file_name") & key_source
+            if table.__name__ == "ImportedPose":
+                key_source = Nwbfile()
 
             for pop_key in (key_source & file_restr).fetch("KEY"):
                 try:
@@ -116,6 +118,7 @@ def populate_all_common(
     List
         A list of keys for InsertError entries if any errors occurred.
     """
+    from spyglass.position.v1.imported_pose import ImportedPose
     from spyglass.spikesorting.imported import ImportedSpikeSorting
 
     declare_all_merge_tables()
@@ -143,6 +146,7 @@ def populate_all_common(
             PositionSource,  # Depends on Session
             VideoFile,  # Depends on TaskEpoch
             StateScriptFile,  # Depends on TaskEpoch
+            ImportedPose,  # Depends on Session
         ],
         [
             RawPosition,  # Depends on PositionSource

src/spyglass/position/position_merge.py

@@ -3,6 +3,7 @@
 from pandas import DataFrame
 
 from spyglass.common.common_position import IntervalPositionInfo as CommonPos
+from spyglass.position.v1.imported_pose import ImportedPose
 from spyglass.position.v1.position_dlc_selection import DLCPosV1
 from spyglass.position.v1.position_trodes_position import TrodesPosV1
 from spyglass.utils import SpyglassMixin, _Merge
@@ -13,6 +14,7 @@
     "IntervalPositionInfo": CommonPos,
     "DLCPosV1": DLCPosV1,
     "TrodesPosV1": TrodesPosV1,
+    "ImportedPose": ImportedPose,
 }
 
 
@@ -63,6 +65,17 @@ class CommonPos(SpyglassMixin, dj.Part):
         -> CommonPos
         """
 
+    class ImportedPose(SpyglassMixin, dj.Part):
+        """
+        Table to pass-through upstream Pose information from NWB file
+        """
+
+        definition = """
+        -> PositionOutput
+        ---
+        -> ImportedPose
+        """
+
     def fetch1_dataframe(self) -> DataFrame:
         """Fetch a single dataframe from the merged table."""
         # proj replaces operator restriction to enable

src/spyglass/position/v1/imported_pose.py

@@ -0,0 +1,152 @@
+import datajoint as dj
+import ndx_pose
+import numpy as np
+import pandas as pd
+import pynwb
+
+from spyglass.common import IntervalList, Nwbfile
+from spyglass.utils.dj_mixin import SpyglassMixin
+from spyglass.utils.nwb_helper_fn import (
+    estimate_sampling_rate,
+    get_valid_intervals,
+)
+
+schema = dj.schema("position_v1_imported_pose")
+
+
+@schema
+class ImportedPose(SpyglassMixin, dj.Manual):
+    """
+    Table to ingest pose data generated prior to spyglass.
+    Each entry corresponds to on ndx_pose.PoseEstimation object in an NWB file.
+    PoseEstimation objects should be stored in nwb.processing.behavior
+    Assumptions:
+    - Single skeleton object per PoseEstimation object
+    """
+
+    _nwb_table = Nwbfile
+
+    definition = """
+    -> IntervalList
+    ---
+    pose_object_id: varchar(80) # unique identifier for the pose object
+    skeleton_object_id: varchar(80) # unique identifier for the skeleton object
+    """
+
+    class BodyPart(SpyglassMixin, dj.Part):
+        definition = """
+        -> master
+        part_name: varchar(80)
+        ---
+        part_object_id: varchar(80)
+        """
+
+    def make(self, key):
+        self.insert_from_nwbfile(key["nwb_file_name"])
+
+    def insert_from_nwbfile(self, nwb_file_name):
+        file_path = Nwbfile().get_abs_path(nwb_file_name)
+        interval_keys = []
+        master_keys = []
+        part_keys = []
+        with pynwb.NWBHDF5IO(file_path, mode="r") as io:
+            nwb = io.read()
+            behavior_module = nwb.get_processing_module("behavior")
+
+            # Loop through all the PoseEstimation objects in the behavior module
+            for name, obj in behavior_module.data_interfaces.items():
+                if not isinstance(obj, ndx_pose.PoseEstimation):
+                    continue
+
+                # use the timestamps from the first body part to define valid times
+                timestamps = list(obj.pose_estimation_series.values())[
+                    0
+                ].timestamps[:]
+                sampling_rate = estimate_sampling_rate(
+                    timestamps, filename=nwb_file_name
+                )
+                valid_intervals = get_valid_intervals(
+                    timestamps,
+                    sampling_rate=sampling_rate,
+                    min_valid_len=sampling_rate,
+                )
+                interval_key = {
+                    "nwb_file_name": nwb_file_name,
+                    "interval_list_name": f"pose_{name}_valid_intervals",
+                    "valid_times": valid_intervals,
+                    "pipeline": "ImportedPose",
+                }
+                interval_keys.append(interval_key)
+
+                # master key
+                master_key = {
+                    "nwb_file_name": nwb_file_name,
+                    "interval_list_name": interval_key["interval_list_name"],
+                    "pose_object_id": obj.object_id,
+                    "skeleton_object_id": obj.skeleton.object_id,
+                }
+                master_keys.append(master_key)
+
+                # part keys
+                for part, part_obj in obj.pose_estimation_series.items():
+                    part_key = {
+                        "nwb_file_name": nwb_file_name,
+                        "interval_list_name": interval_key[
+                            "interval_list_name"
+                        ],
+                        "part_name": part,
+                        "part_object_id": part_obj.object_id,
+                    }
+                    part_keys.append(part_key)
+
+        IntervalList().insert(interval_keys, skip_duplicates=True)
+        self.insert(master_keys, skip_duplicates=True)
+        self.BodyPart().insert(part_keys, skip_duplicates=True)
+
+    def fetch_pose_dataframe(self, key=dict()):
+        """Fetch pose data as a pandas DataFrame
+
+        Parameters
+        ----------
+        key : dict
+            Key to fetch pose data for
+
+        Returns
+        -------
+        pd.DataFrame
+            DataFrame containing pose data
+        """
+        key = (self & key).fetch1("KEY")
+        pose_estimations = (
+            (self & key).fetch_nwb()[0]["pose"].pose_estimation_series
+        )
+
+        index = None
+        pose_df = {}
+        for body_part in pose_estimations.keys():
+            if index is None:
+                index = pd.Index(
+                    pose_estimations[body_part].timestamps[:],
+                    name="time",
+                )
+
+            part_df = {
+                "video_frame_ind": np.nan,
+                "x": pose_estimations[body_part].data[:, 0],
+                "y": pose_estimations[body_part].data[:, 1],
+                "likelihood": pose_estimations[body_part].confidence[:],
+            }
+
+            pose_df[body_part] = pd.DataFrame(part_df, index=index)
+
+        pose_df
+        return pd.concat(pose_df, axis=1)
+
+    def fetch_skeleton(self, key=dict()):
+        nwb = (self & key).fetch_nwb()[0]
+        nodes = nwb["skeleton"].nodes[:]
+        int_edges = nwb["skeleton"].edges[:]
+        named_edges = [[nodes[i], nodes[j]] for i, j in int_edges]
+        named_edges
+        skeleton = {"nodes": nodes, "edges": named_edges}
+        return skeleton