WhiteMatter data conversion

Install NeuroConv with the additional dependencies necessary for reading WhiteMatter data.

pip install "neuroconv[whitematter]"

Convert WhiteMatter data to NWB using WhiteMatterRecordingInterface.

>>> from datetime import datetime
>>> from zoneinfo import ZoneInfo
>>> from pathlib import Path
>>> from neuroconv.datainterfaces import WhiteMatterRecordingInterface
>>>
>>> # For this data interface we need to pass the file_path with the location of the data
>>> file_path = f"{ECEPHY_DATA_PATH}/whitematter/HSW_2024_12_12__10_28_23__70min_17sec__hsamp_64ch_25000sps_stub.bin"
>>> # Change the file_path to the location of the data in your system
>>> sampling_frequency = 25_000.0
>>> num_channels = 64
>>> interface = WhiteMatterRecordingInterface(
...    file_path=file_path,
...    sampling_frequency=sampling_frequency,
...    num_channels=num_channels,
... )
>>>
>>> # Extract what metadata we can from the source files
>>> metadata = interface.get_metadata()
>>> # session_start_time is required for conversion. If it cannot be inferred
>>> # automatically from the source files you must supply one.
>>> session_start_time = datetime(2020, 1, 1, 12, 30, 0, tzinfo=ZoneInfo("US/Pacific"))
>>> metadata["NWBFile"].update(session_start_time=session_start_time)
>>>
>>>  # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{path_to_save_nwbfile}"  # This should be something like: "./saved_file.nwb"
>>> interface.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata, overwrite=True)

Specifying Metadata

The example above show how to convert WhiteMatter data without specifying any metadata, in which case the metadata will be automatically generated with default values. To ensure that the NWB file is properly annotated, specify the metadata using the format described below.

>>> ecephys_metadata = {
...     "Ecephys": {
...         "ElectricalSeries": { # This should match the es_key used in the interface
...             "name" : "ElectricalSeries",
...             "description": "My description of the electrical series data",
...         },
...         "Device": [
...             {
...                 "name": "MyDevice",
...                 "description": "My description of the device",
...             },
...         ],
...         "ElectrodeGroup": [
...             {
...                 "name": "MyElectrodeGroup",
...                 "description": "My description of the electrode group",
...                 "location": "location of the electrode group ex. hippocampus",
...                 "device": "MyDevice",
...             }
...         ],
...     }
... }

This metadata can then be easily incorporated into the conversion by updating the metadata dictionary.

>>> from datetime import datetime
>>> from zoneinfo import ZoneInfo
>>> from pathlib import Path
>>> from neuroconv.datainterfaces import WhiteMatterRecordingInterface
>>> from neuroconv.utils import dict_deep_update
>>>
>>> # For this data interface we need to pass the file_path with the location of the data
>>> file_path = f"{ECEPHY_DATA_PATH}/whitematter/HSW_2024_12_12__10_28_23__70min_17sec__hsamp_64ch_25000sps_stub.bin"
>>> # Change the file_path to the location of the data in your system
>>> sampling_frequency = 25_000.0
>>> num_channels = 64
>>> interface = WhiteMatterRecordingInterface(
...    file_path=file_path,
...    sampling_frequency=sampling_frequency,
...    num_channels=num_channels,
... )
>>>
>>> # Extract what metadata we can from the source files
>>> metadata = interface.get_metadata()
>>> # session_start_time is required for conversion. If it cannot be inferred
>>> # automatically from the source files you must supply one.
>>> session_start_time = datetime(2020, 1, 1, 12, 30, 0, tzinfo=ZoneInfo("US/Pacific"))
>>> metadata["NWBFile"].update(session_start_time=session_start_time)
>>> metadata = dict_deep_update(metadata, ecephys_metadata)
>>>
>>>  # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{path_to_save_nwbfile}"  # This should be something like: "./saved_file.nwb"
>>> interface.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata, overwrite=True)