npc_ephys
Tools for accessing and processing raw ephys data, compatible with data in the cloud.
Usage
conda create -n npc_ephys python>=3.9
conda activate npc_ephys
pip install npc_ephys
Windows
wavpack-numcodecs
is used to read compressed ephys data from S3 (stored in Zarr format). On Windows, that requires C++
build tools to be installed: if pip install npc_ephys fails you'll likely need to download it from here.
Python
>>> import npc_ephys
# get device timing on sync clock using barcodes:
>>> recording_path = 's3://aind-ephys-data/ecephys_670248_2023-08-03_12-04-15/ecephys_clipped/Record Node 102/experiment1/recording1'
>>> sync_path = 's3://aind-ephys-data/ecephys_670248_2023-08-03_12-04-15/behavior/20230803T120415.h5'
>>> timing_data = next(npc_ephys.get_ephys_timing_on_sync(sync_path, recording_path))
>>> timing_data.device.name, timing_data.sampling_rate, timing_data.start_time
('Neuropix-PXI-100.ProbeA-AP', 30000.070518634246, 20.080209634424037)
# get a dataclass that reads SpikeInterface sorted data from the cloud
# - from a path:
>>> si = npc_ephys.get_spikeinterface_data('s3://codeocean-s3datasetsbucket-1u41qdg42ur9/4797cab2-9ea2-4747-8d15-5ba064837c1c')
# - or from a subject ID + date + session-index-on-date (separators are optional):
>>> si = npc_ephys.get_spikeinterface_data('670248_2023-08-03_0')
>>> si
SpikeInterfaceData(session='670248_2023-08-03_0', root=S3Path('s3://codeocean-s3datasetsbucket-1u41qdg42ur9/4797cab2-9ea2-4747-8d15-5ba064837c1c'))
# various bits of data are available for use:
>>> si.version
'0.97.1'
>>> ''.join(si.probes)
'ABCEF'
>>> si.quality_metrics_df('probeA').columns
Index(['num_spikes', 'firing_rate', 'presence_ratio', 'snr',
'isi_violations_ratio', 'isi_violations_count', 'rp_contamination',
'rp_violations', 'sliding_rp_violation', 'amplitude_cutoff',
'drift_ptp', 'drift_std', 'drift_mad', 'isolation_distance', 'l_ratio',
'd_prime'],
dtype='object')
>>> si.spike_indexes('probeA')
array([ 491, 738, 835, ..., 143124925, 143125165, 143125201])
>>> si.unit_indexes('probeA')
array([ 56, 61, 161, ..., 151, 72, 59])
make_units_table_from_spike_interface() automatically reads either the legacy
folder layout or the newer SpikeInterface SortingAnalyzer Zarr layout.
make_units_table_from_spike_interface_ks25() remains available as a
backwards-compatible alias.
Development
See instructions in https://github.com/AllenInstitute/npc_ephys/CONTRIBUTING.md and the original template: https://github.com/AllenInstitute/copier-pdm-npc/blob/main/README.md
1 maintainer
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