Analysis of electrophysiological data recorded with the Axona recording system
Project description
## Synopsis
Tools for the analysis of electrophysiological data collected primarily with Axona recording products using Python.
## Code Example
Main entry class is Trial contained in dacq2py_util i.e.
` import dacq2py_util T = dacq2py_util.Trial('/path/to/dataset/mytrial') `
The “usual” Axona dataset includes the following files:
mytrial.set
mytrial.1
mytrial.2
mytrial.3
mytrial.4
mytrial.pos
mytrial.eeg
Note that you shouldn’t specify a suffix when constructing the filename in the code example above.
You can now start analysing your data! i.e.
` T.plotEEGPower() T.plotMap(tetrode=1, cluster=4) `
## Motivation
Analysis using Axona’s Tint cluster cutting program is great but limited. This extends that functionality.
## Installation
Easiest way is with pip (under Linux, don’t know how this works under other OS’s):
> pip install dacq2py
This should install all the pre-requisites, which are as follows:
numpy
scipy
matplotlib
scikits-learn
[astropy](http://www.astropy.org/) (for NaN-friendly convolution)
skimage
[mahotas](http://mahotas.readthedocs.org/en/latest/)
Optional packages include:
[klustakwik](https://github.com/klusta-team/klustakwik)
Download the files and extract to a folder and make sure it’s on your Python path
## API Reference
Most classes/ methods have some explanatory text. The files in the docs folder are extracted from that using standard Python tools.
## Tests
To be implemented.
## Contributors
Robin Hayman.
## License
Do what you want license.
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