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common_task.py

Task

Bases: SpyglassMixin, Manual

Source code in src/spyglass/common/common_task.py 
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@schema
class Task(SpyglassMixin, dj.Manual):
    definition = """
     task_name: varchar(80)
     ---
     task_description = NULL: varchar(2000)    # description of this task
     task_type = NULL: varchar(2000)           # type of task
     task_subtype = NULL: varchar(2000)        # subtype of task
     """

    @classmethod
    def insert_from_nwbfile(cls, nwbf):
        """Insert tasks from an NWB file.

        Parameters
        ----------
        nwbf : pynwb.NWBFile
            The source NWB file object.
        """
        tasks_mod = nwbf.processing.get("tasks")
        if tasks_mod is None:
            logger.warn(f"No tasks processing module found in {nwbf}\n")
            return
        for task in tasks_mod.data_interfaces.values():
            if cls.check_task_table(task):
                cls.insert_from_task_table(task)

    @classmethod
    def insert_from_task_table(cls, task_table):
        """Insert tasks from a pynwb DynamicTable containing task metadata.

        Duplicate tasks will not be added.

        Parameters
        ----------
        task_table : pynwb.core.DynamicTable
            The table representing task metadata.
        """
        taskdf = task_table.to_dataframe()
        for task_entry in taskdf.iterrows():
            task_dict = dict()
            task_dict["task_name"] = task_entry[1].task_name
            task_dict["task_description"] = task_entry[1].task_description
            cls.insert1(task_dict, skip_duplicates=True)

    @classmethod
    def check_task_table(cls, task_table):
        """Check whether the pynwb DynamicTable containing task metadata conforms to the expected format.


        The table should be an instance of pynwb.core.DynamicTable and contain the columns 'task_name' and
        'task_description'.

        Parameters
        ----------
        task_table : pynwb.core.DynamicTable
            The table representing task metadata.

        Returns
        -------
        bool
            Whether the DynamicTable conforms to the expected format for loading data into the Task table.
        """
        return (
            isinstance(task_table, pynwb.core.DynamicTable)
            and hasattr(task_table, "task_name")
            and hasattr(task_table, "task_description")
        )

insert_from_nwbfile(nwbf) classmethod

Insert tasks from an NWB file.

Parameters:

Name Type Description Default
nwbf NWBFile

The source NWB file object.

 required
Source code in src/spyglass/common/common_task.py 
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@classmethod
def insert_from_nwbfile(cls, nwbf):
    """Insert tasks from an NWB file.

    Parameters
    ----------
    nwbf : pynwb.NWBFile
        The source NWB file object.
    """
    tasks_mod = nwbf.processing.get("tasks")
    if tasks_mod is None:
        logger.warn(f"No tasks processing module found in {nwbf}\n")
        return
    for task in tasks_mod.data_interfaces.values():
        if cls.check_task_table(task):
            cls.insert_from_task_table(task)

insert_from_task_table(task_table) classmethod

Insert tasks from a pynwb DynamicTable containing task metadata.

Duplicate tasks will not be added.

Parameters:

Name Type Description Default
task_table DynamicTable

The table representing task metadata.

 required
Source code in src/spyglass/common/common_task.py 
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@classmethod
def insert_from_task_table(cls, task_table):
    """Insert tasks from a pynwb DynamicTable containing task metadata.

    Duplicate tasks will not be added.

    Parameters
    ----------
    task_table : pynwb.core.DynamicTable
        The table representing task metadata.
    """
    taskdf = task_table.to_dataframe()
    for task_entry in taskdf.iterrows():
        task_dict = dict()
        task_dict["task_name"] = task_entry[1].task_name
        task_dict["task_description"] = task_entry[1].task_description
        cls.insert1(task_dict, skip_duplicates=True)

check_task_table(task_table) classmethod

Check whether the pynwb DynamicTable containing task metadata conforms to the expected format.

The table should be an instance of pynwb.core.DynamicTable and contain the columns 'task_name' and 'task_description'.

Parameters:

Name Type Description Default
task_table DynamicTable

The table representing task metadata.

 required

Returns:

Type Description
bool

Whether the DynamicTable conforms to the expected format for loading data into the Task table.
Source code in src/spyglass/common/common_task.py 
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@classmethod
def check_task_table(cls, task_table):
    """Check whether the pynwb DynamicTable containing task metadata conforms to the expected format.


    The table should be an instance of pynwb.core.DynamicTable and contain the columns 'task_name' and
    'task_description'.

    Parameters
    ----------
    task_table : pynwb.core.DynamicTable
        The table representing task metadata.

    Returns
    -------
    bool
        Whether the DynamicTable conforms to the expected format for loading data into the Task table.
    """
    return (
        isinstance(task_table, pynwb.core.DynamicTable)
        and hasattr(task_table, "task_name")
        and hasattr(task_table, "task_description")
    )

TaskEpoch

Bases: SpyglassMixin, Imported

Source code in src/spyglass/common/common_task.py 
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@schema
class TaskEpoch(SpyglassMixin, dj.Imported):
    # Tasks, session and time intervals
    definition = """
     -> Session
     epoch: int  # the session epoch for this task and apparatus(1 based)
     ---
     -> Task
     -> [nullable] CameraDevice
     -> IntervalList
     task_environment = NULL: varchar(200)  # the environment the animal was in
     camera_names : blob # list of keys corresponding to entry in CameraDevice
     """

    def make(self, key):
        nwb_file_name = key["nwb_file_name"]
        nwb_file_abspath = Nwbfile().get_abs_path(nwb_file_name)
        nwbf = get_nwb_file(nwb_file_abspath)
        camera_names = dict()

        # the tasks refer to the camera_id which is unique for the NWB file but
        # not for CameraDevice schema, so we need to look up the right camera
        # map camera ID (in camera name) to camera_name

        for device in nwbf.devices.values():
            if isinstance(device, ndx_franklab_novela.CameraDevice):
                # get the camera ID
                camera_id = int(str.split(device.name)[1])
                camera_names[camera_id] = device.camera_name

        # find the task modules and for each one, add the task to the Task
        # schema if it isn't there and then add an entry for each epoch

        tasks_mod = nwbf.processing.get("tasks")
        if tasks_mod is None:
            logger.warn(f"No tasks processing module found in {nwbf}\n")
            return

        for task in tasks_mod.data_interfaces.values():
            if self.check_task_table(task):
                # check if the task is in the Task table and if not, add it
                Task.insert_from_task_table(task)
                key["task_name"] = task.task_name[0]

                # get the CameraDevice used for this task (primary key is
                # camera name so we need to map from ID to name)

                camera_ids = task.camera_id[0]
                valid_camera_ids = [
                    camera_id
                    for camera_id in camera_ids
                    if camera_id in camera_names.keys()
                ]
                if valid_camera_ids:
                    key["camera_names"] = [
                        {"camera_name": camera_names[camera_id]}
                        for camera_id in valid_camera_ids
                    ]
                else:
                    logger.warn(
                        f"No camera device found with ID {camera_ids} in NWB "
                        + f"file {nwbf}\n"
                    )
                # Add task environment
                if hasattr(task, "task_environment"):
                    key["task_environment"] = task.task_environment[0]

                # get the interval list for this task, which corresponds to the
                # matching epoch for the raw data. Users should define more
                # restrictive intervals as required for analyses

                session_intervals = (
                    IntervalList() & {"nwb_file_name": nwb_file_name}
                ).fetch("interval_list_name")
                for epoch in task.task_epochs[0]:
                    # TODO in beans file, task_epochs[0] is 1x2 dset of ints,
                    # so epoch would be an int

                    key["epoch"] = epoch
                    target_interval = str(epoch).zfill(2)
                    for interval in session_intervals:
                        if (
                            target_interval in interval
                        ):  # TODO this is not true for the beans file
                            break
                    # TODO case when interval is not found is not handled
                    key["interval_list_name"] = interval
                    self.insert1(key)

    @classmethod
    def update_entries(cls, restrict={}):
        existing_entries = (cls & restrict).fetch("KEY")
        for row in existing_entries:
            if (cls & row).fetch1("camera_names"):
                continue
            row["camera_names"] = [
                {"camera_name": (cls & row).fetch1("camera_name")}
            ]
            cls.update1(row=row)

    @classmethod
    def check_task_table(cls, task_table) -> bool:
        """Check whether the pynwb DynamicTable containing task metadata
        conforms to the expected format.

        The table should be an instance of pynwb.core.DynamicTable and contain
        the columns 'task_name', 'task_description', 'camera_id', 'and
        'task_epochs'.

        Parameters
        ----------
        task_table : pynwb.core.DynamicTable
            The table representing task metadata.

        Returns
        -------
        bool
            Whether the DynamicTable conforms to the expected format for
            loading data into the TaskEpoch table.
        """

        # TODO this could be more strict and check data types, but really it
        # should be schematized
        return (
            Task.check_task_table(task_table)
            and hasattr(task_table, "camera_id")
            and hasattr(task_table, "task_epochs")
        )

check_task_table(task_table) classmethod

Check whether the pynwb DynamicTable containing task metadata conforms to the expected format.

The table should be an instance of pynwb.core.DynamicTable and contain the columns 'task_name', 'task_description', 'camera_id', 'and 'task_epochs'.

Parameters:

Name Type Description Default
task_table DynamicTable

The table representing task metadata.

 required

Returns:

Type Description
bool

Whether the DynamicTable conforms to the expected format for loading data into the TaskEpoch table.
Source code in src/spyglass/common/common_task.py 
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@classmethod
def check_task_table(cls, task_table) -> bool:
    """Check whether the pynwb DynamicTable containing task metadata
    conforms to the expected format.

    The table should be an instance of pynwb.core.DynamicTable and contain
    the columns 'task_name', 'task_description', 'camera_id', 'and
    'task_epochs'.

    Parameters
    ----------
    task_table : pynwb.core.DynamicTable
        The table representing task metadata.

    Returns
    -------
    bool
        Whether the DynamicTable conforms to the expected format for
        loading data into the TaskEpoch table.
    """

    # TODO this could be more strict and check data types, but really it
    # should be schematized
    return (
        Task.check_task_table(task_table)
        and hasattr(task_table, "camera_id")
        and hasattr(task_table, "task_epochs")
    )