nept¶
nept is short for neuroelectrophysiology tools and is a library that we use in the van der Meer lab at Dartmouth College for analyzing neural electrophysiological recording data and associated behaviors.
Documentation¶
Getting started¶
If you don’t already have python 3, we recommend you download it using Miniconda from Continuum Analytics.
We recommend using a separate python environment.
Open a new terminal, create and activate a new conda environment:
conda create -n yourenv python=3.5
activate yourenv [Windows] or source activate yourenv [Linux]
Install package dependencies:
conda install matplotlib jupyter scipy numpy pandas pytest coverage
For Shapely, try:
pip install shapely
If that fails, in Windows, download the most recent wheel file here. Once downloaded, install with wheel.
pip install yourshapelyinstall.whl
Installation¶
Clone nept from Github and use a developer installation:
git clone https://github.com/vandermeerlab/nept.git
Set up a developer installation:
cd nept
python setup.py develop
All set! You’re ready to start using the nept module.
import nept
nept Modules¶
The nept modules are used for the analysis of neural electrophysiological recording data and associated behaviors.
nept.co_occurrence module¶
nept.decoding module¶
nept.lfp_filtering module¶
nept.loaders_mclust module¶
nept.loaders_neuralynx module¶
nept.maze_breakdown module¶
nept.medpc module¶
nept.place_fields module¶
nept.tuning_curves module¶
nept.utils module¶
License¶
The nept library is free software, distributed under a MIT license.