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Collection of tools to handle Neuropixel 1.0 and 2.0 data

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ibl-neuropixel

Collection of tools to handle Neuropixel 1.0 and 2.0 data (documentation coming soon...)

Installation

Minimum Python version supported is 3.10 pip install ibl-neuropixel

Destriping

Getting started

This relies on a fast fourier transform external library: pip install pyfftw.

Minimal working example to destripe a neuropixel binary file.

from pathlib import Path
from ibldsp.voltage import decompress_destripe_cbin
sr_file = Path('/datadisk/Data/spike_sorting/pykilosort_tests/imec_385_100s.ap.bin')
out_file = Path('/datadisk/scratch/imec_385_100s.ap.bin')

decompress_destripe_cbin(sr_file=sr_file, output_file=out_file, nprocesses=8)

Viewer

The best way to look at the results is to use viewephys, open an ephys viewer on the raw data.

  • tick the destripe box.
  • move to a desired location in the file
  • ctr+P will make the gain and axis the same on both windows

alt text

You can then move within the raw data file.

White Paper

The following describes the methods implemented in this repository. https://doi.org/10.6084/m9.figshare.19705522

Contribution

Pypi Release checklist:

  • Edit the version number in setup.py, and add release notes in release_notes.md
flake8
tag=X.Y.Z
git tag -a $tag 
git push origin %tag

Create new release with tag X.Y.Z (will automatically publish to PyPI)

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Collection of tools to handle Neuropixel 1.0 and 2.0 data

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