Function to return all PyNWB objects in the file that are instances of the neurodata_type class

get_neurodata_type_objects.py

from pynwb import NWBHDF5IO, NWBFile


def get_neurodata_type_objs_io(io: NWBHDF5IO, neurodata_type: str, namespace: str):
    """Return all PyNWB objects in the file that have a neurodata type from a namespace.

    This works regardless of whether the extension was imported earlier in the python execution.

    All objects that are instances of the class associated with the given neurodata_type in the
    given namespace will be returned. This includes objects that are instances of a subclass.

    For example, if an extension defines a new neurodata type OnePhotonSeries that extends
    ImageSeries, then `get_neurodata_type_objects_in_file(io, "ImageSeries", "core")` will
    include all OnePhotonSeries objects.

    .. code-block:: python

        from pynwb import NWBHDF5IO
        with NWBHDF5IO(filepath, mode="r", load_namespaces=True) as io:
            obj_list = get_neurodata_type_objs_io(io, "Subject", "core")

    """

    # if the extension python module has been imported, this line will return the custom API
    # class defined in the extension (my.extension.module.path.class_name).
    # otherwise, this line will return the class generated for reading data with this
    # neurodata type based on the cached namespace in the file (abc.class_name).
    pynwb_cls = io.manager.type_map.get_dt_container_cls(neurodata_type, namespace)

    read_nwbfile = io.read()
    return get_neurodata_type_objs(read_nwbfile, pynwb_cls)


def get_neurodata_type_objs(nwbfile: NWBFile, pynwb_class: type):
    """Return all PyNWB objects in the file that are instances of the pynwb_class class.

    This includes objects that are instances of a subclass.

    .. code-block:: python

        from pynwb import ImageSeries
        obj_list = get_neurodata_type_objects(nwbfile, ImageSeries)

    """
    ret = [obj for obj in nwbfile.objects.values() if isinstance(obj, pynwb_class)]
    return ret


def print_obj_info(io: NWBHDF5IO, obj_list: list):
    for i, obj in enumerate(obj_list):
        builder = io.manager.get_builder(obj)

        print("%d: %s '%s'" % (i, type(obj), obj.name))
        print("\tObject ID: %s" % obj.object_id)
        print("\tHDF5 path: %s" % builder.path)


if __name__ == "__main__":
    # an example data file downloaded from dandiset 000021 that has an extension to the Subject neurodata type
    filepath = "/Users/rly/Documents/NWB_Data/dandisets/000021/sub-699733573_ses-715093703_probe-810755797_ecephys.nwb"

    with NWBHDF5IO(filepath, mode="r", load_namespaces=True) as io:
        # two different approaches to getting the objects
        # 1) by IO object, neurodata type, and namespace
        obj_list = get_neurodata_type_objs_io(io, "EcephysSpecimen", "ndx-aibs-ecephys")
        print_obj_info(io, obj_list)

        # because ndx-aibs-ecephys.EcephysSpecimen extends core.Subject, the following will return the same objects
        obj_list = get_neurodata_type_objs_io(io, "Subject", "core")
        print_obj_info(io, obj_list)

        # 2) by NWBFile object and PyNWB class
        from pynwb.file import Subject

        # because ndx-aibs-ecephys.EcephysSpecimen extends core.Subject, the following will return the same objects
        nwbfile = io.read()
        obj_list = get_neurodata_type_objs(nwbfile, Subject)
        print_obj_info(io, obj_list)