https://github.com/mrkrd/thorns

Spike analysis software
https://github.com/mrkrd/thorns

action-potentials computational-neuroscience psth python spike-trains spikes

Last synced: 1 day ago
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Spike analysis software

• Host: GitHub
• URL: https://github.com/mrkrd/thorns
• Owner: mrkrd
• License: gpl-3.0
• Created: 2014-06-23T14:10:40.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2022-03-10T22:27:31.000Z (over 2 years ago)
• Last Synced: 2024-10-07T22:11:32.757Z (about 1 month ago)
• Topics: action-potentials, computational-neuroscience, psth, python, spike-trains, spikes
• Language: Python
• Size: 828 KB
• Stars: 17
• Watchers: 3
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: COPYING.txt

Awesome Lists containing this project

README

        
thorns and waves

================

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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.

.. _`spike trains`: https://en.wikipedia.org/wiki/Spike_train

.. _`Werner Hemmert`: https://www.ei.tum.de/en/bai/home/

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/

.. _DEMO: https://github.com/mrkrd/thorns/blob/master/examples/thorns_demo.ipynb

.. _examples: examples

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

.. _TODO.org: TODO.org

License

-------

The project is licensed under the GNU General Public License v3 or

later (GPLv3+).