thorns and waves
__|________|_____|_|_|___|_____|____||_____|_____|_____|____|_____|___||______ _|_______________________|______|_________|_______|_____|____|__|________|_|__ _____|___|__|_____|_______|____|_________________________|__|_________|_______ ___|_______|_____|______|_____|_______|__|___|________|______|___|____________ __|__|_______|_____|__|___|______|________|______|______|_____|_______THORNS__
With thorns you can analyze and display spike trains generated by neurons. It can be useful for the analysis of experimental and simulation data using Python. For example, you can easily calculate peristimulus time histogram (PSTH), interspike time histogram (ISIH), vector strength (VS), entrainment and visualize action potentials with raster plot.
waves is a submodule with some useful signal processing and generation functions, e.g. generate ramped tone, amplitude modulation tone, FFT filter, set level (dB_SPL).
The software was originally developed during my PhD in the group of Werner Hemmert at the TUM. It is oriented towards auditory research, but it could be easily extended.
Usage
Don’t forget to check our IPython Notebook DEMO and scripts in the examples directory!
Initialize and load spike trains:
import thorns as th from thorns.datasets import load_anf_zilany2014 spike_trains = load_anf_zilany2014()
Calculate vector strength:
th.vector_strength(spike_trains, freq=1000)
Raster plot:
th.plot_raster(spike_trains) th.show()
Generate and plot AM tone:
import thorns.waves as wv
sound = wv.amplitude_modulated_tone(
fs=48e3,
fm=100,
fc=1e3,
m=0.7,
duration=0.1,
)
wv.plot_signal(sound, fs=48e3)
wv.show()
You can also browse the API documentation at https://pythonhosted.org/thorns/
Features
Analyzes and displays spike trains
Uses pandas.DataFrame as the main data container (spike trains, results)
Handy signal processing and generating functions: thorns.waves
Map implementation with various backend (also parallel) and caching: thorns.util.map()
Dumpdb: quickly dump map()’s results in one script and load from another one: thorns.util.dumpdb(), thorns.util.loaddb()
Pure Python
Installation
In order to use thorns, you’ll need to install the following dependencies first:
Python (2.7)
Numpy
Scipy
Pandas
PyTables / tables
Matplotlib
py-notify (optional, enables notifications)
Next, type in your command line:
pip install thorns
Contribute
Open tasks: TODO.org (best viewed in Emacs org-mode)
Issue Tracker: https://github.com/mrkrd/thorns/issues
Source Code: https://github.com/mrkrd/thorns
License
The project is licensed under the GNU General Public License v3 or later (GPLv3+).
Metadata
Release files for thorns 1
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