Quality metric from spike trains
Project description
slidingRefractory
Code to perform a new test of whether neurons have contaminated refractory periods, with a sliding window
Python
Installation
Install using pip:
pip install slidingRP
Install using sources in development mode. First clone the repository.
cd slidingRefractory
pip install -e .
Minimal working example
from pathlib import Path
import numpy as np
import pandas as pd
from slidingRP import metrics
# get the small test datasets from the github repository first
repo_path = "/home/ibladmin/Documents/PYTHON/int-brain-lab/slidingRefractory"
TEST_DATA_PATH = Path(repo_path).joinpath("test-data", "integration")
params = {'sampleRate': 30000, 'binSizeCorr': 1 / 30000}
spikes = pd.read_parquet(TEST_DATA_PATH.joinpath('spikes.pqt'))
table = metrics.slidingRP_all(spikes.times, spikes.clusters, **params)
assert np.allclose(pd.read_parquet(TEST_DATA_PATH.joinpath("rp_table.pqt")), pd.DataFrame(table), equal_nan=True)
Contribute
Run unit tests
pytest python/test_*
Upload package
rm -fR dist
rm -fR build
python setup.py sdist bdist_wheel
twine upload dist/*
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