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PYthon Neural Analysis Package Pour Laboratoires d’Excellence

Project description

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PYthon Neural Analysis Package.

pynapple is a light-weight python library for neurophysiological data analysis. The goal is to offer a versatile set of tools to study typical data in the field, i.e. time series (spike times, behavioral events, etc.) and time intervals (trials, brain states, etc.). It also provides users with generic functions for neuroscience such as tuning curves and cross-correlograms.


Getting Started

Requirements

  • Python 3.6+
  • Pandas 1.0.3+
  • numpy 1.17+
  • scipy 1.3+
  • numba 0.46+
  • tabulate

Installation

pynapple can be installed with pip:

$ pip install pynapple

or directly from the source code:

$ # clone the repository
$ git clone https://github.com/PeyracheLab/pynapple.git
$ cd pynapple
$ # Install in editable mode with `-e` or, equivalently, `--editable`
$ pip install -e .

Basic Usage

After installation, the package can imported:

$ python
>>> import pynapple as nap

An example of the package can be seen below. The exemple data can be found here.

import numpy as np
import pandas as pd
import pynapple as nap
from matplotlib.pyplot import *

data_directory = '/your/path/to/A2929-200711'

# LOADING DATA
data = nap.load_session(data_directory, 'neurosuite')


spikes = data.spikes
position = data.position
wake_ep = data.epochs['wake']

# COMPUTING TUNING CURVES
tuning_curves = nap.compute_1d_tuning_curves(group = spikes, 
                                            feature = position['ry'], 
                                            ep = position['ry'].time_support, 
                                            nb_bins = 120,  
                                            minmax=(0, 2*np.pi) )
                                                

        
# PLOT
figure()
for i in spikes:
    subplot(6,7,i+1, projection = 'polar')
    plot(tuning_curves[i])
    

show()

Credits

Special thanks to Francesco P. Battaglia (https://github.com/fpbattaglia) for the development of the original TSToolbox (https://github.com/PeyracheLab/TStoolbox) and neuroseries (https://github.com/NeuroNetMem/neuroseries) packages, the latter constituting the core of pynapple.

This package was developped by Guillaume Viejo (https://github.com/gviejo) and other members of the Peyrache Lab.

Logo: Sofia Skromne Carrasco, 2021.

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