To run with the profiler.

test_neuroscope_memory

from pathlib import Path


def run_neuroscope(spikeextractors_backend):

    from datetime import datetime
    from nwb_conversion_tools import NWBConverter, NeuroscopeRecordingInterface

    file_path = Path(
        "/home/heberto/globus_data/Buzsaki/TingleyD/DT1/DT1_rLS_20150723_1584um/DT1_rLS_20150723_1584um.dat"
    )
    file_path = Path("/home/heberto/ephy_testing_data/neuroscope/test1/test1.dat")
    stub_test = True
    
    nwbfile_path = str(f"./{file_path.stem}_{stub_test=}_{spikeextractors_backend=}.nwb")

    class TestConverter(NWBConverter):
        data_interface_classes = dict(NeuroscopeRecording=NeuroscopeRecordingInterface)

    conversion_options = dict()
    conversion_options.update(
        NeuroscopeRecording=dict(stub_test=stub_test, es_key="ElectricalSeries_raw", iterator_opts=dict(buffer_gb=4.0))
    )

    interface_kwargs = dict(file_path=str(file_path), spikeextractors_backend=spikeextractors_backend)
    converter = TestConverter(source_data=dict(NeuroscopeRecording=interface_kwargs))

    metadata = converter.get_metadata()
    metadata["NWBFile"].update(session_start_time=datetime.now().astimezone().strftime("%Y-%m-%dT%H:%M:%S"))
    converter.run_conversion(
        nwbfile_path=nwbfile_path, conversion_options=conversion_options, overwrite=True, metadata=metadata
    )


if __name__ == "__main__":
    spikeextractors_backend = False
    run_neuroscope(spikeextractors_backend)