suite2p#

Install NeuroConv with the additional dependencies necessary for reading suite2p data.

pip install "neuroconv[suite2p]"

Convert a suite2p output folder

Suite2p writes its segmentation output to one folder per plane (“plane0”, “plane1”), each holding the traces of every channel it segmented. Point Suite2pConverter at the folder containing them.

>>> from datetime import datetime
>>> from zoneinfo import ZoneInfo
>>> from neuroconv.converters import Suite2pConverter
>>>
>>> folder_path = OPHYS_DATA_PATH / "segmentation_datasets" / "suite2p"
>>> converter = Suite2pConverter(folder_path=folder_path, verbose=False)
>>>
>>> metadata = converter.get_metadata()
>>> # For data provenance we add the time zone information to the conversion
>>> session_start_time = datetime(2020, 1, 1, 12, 30, 0, tzinfo=ZoneInfo("US/Pacific"))
>>> metadata["NWBFile"].update(session_start_time=session_start_time)
>>> # Add subject information (required for DANDI upload)
>>> metadata["Subject"] = dict(subject_id="subject1", species="Mus musculus", sex="M", age="P30D")
>>>
>>> # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{path_to_save_nwbfile}"
>>> converter.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata)

That call covers any suite2p output folder, one plane or many, one channel or two. Each plane and channel is written as its own PlaneSegmentation and ImagingPlane with its own traces, named for the pair it came from (“PlaneSegmentationChan1Plane0”). The “combined” folder suite2p writes for a multi-plane session is skipped, since its ROIs are the per-plane ones concatenated.

NeuroConv aims to automatically add all the metadata annotations that are present in the source format. It is often the case that crucial information is not available there, such as the anatomical location, the meaning of the values, or a semantically meaningful description of the data. Follow the ophys how-to for a modality-relevant guide to adding this extra metadata, which makes the data more useful for future users and for the community as a whole. Its section on templates starts from scratch, and the reference template lists every element the metadata accepts.

Converting a single plane and channel

Use Suite2pSegmentationInterface to write one plane and one channel, chosen with the plane_name and channel_name arguments. To see what is available, use Suite2pSegmentationInterface.get_available_planes(folder_path) and Suite2pSegmentationInterface.get_available_channels(folder_path). When neither is specified, the first plane and channel are used.

>>> from datetime import datetime
>>> from zoneinfo import ZoneInfo
>>> from neuroconv.datainterfaces import Suite2pSegmentationInterface
>>>
>>> folder_path = OPHYS_DATA_PATH / "segmentation_datasets" / "suite2p"
>>> interface = Suite2pSegmentationInterface(folder_path=folder_path, plane_name="plane0", channel_name="chan1", verbose=False)
>>>
>>> metadata = interface.get_metadata()
>>> # For data provenance we add the time zone information to the conversion
>>> session_start_time = datetime(2020, 1, 1, 12, 30, 0, tzinfo=ZoneInfo("US/Pacific"))
>>> metadata["NWBFile"].update(session_start_time=session_start_time)
>>> # Add subject information (required for DANDI upload)
>>> metadata["Subject"] = dict(subject_id="subject1", species="Mus musculus", sex="M", age="P30D")
>>>
>>> # Choose a path for saving the nwb file and run the conversion
>>> nwbfile_path = f"{output_folder}/file2.nwb"
>>> interface.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata)

suite2p#

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