neuropy is a Python application for interactive analysis of sorted neuronal spike data and raw LFP waveforms.
The user-facing data object hierarchy looks like this:
level:
Animal 1
|
Track 2 Track
| |
Recording 3 TrackSort
/ \ |
Experiment Sort 4 TrackNeuron
|
Neuron 5
Once data are loaded, they can be accessed in various ways:
animal.track.recording
animal.tr[trackid].r[recordingid]
recording.n[neuronid]
For example, to plot a population raster plot of all active cells in recording 5 of track 1 of animal example1, you can type:
example1.tr1.r05.praster()
Different object types have different analysis methods associated with them.
Thanks to IPython, tab completion should help you discover
analysis methods, and typing ?
after the method name or simply typing the opening
parenthesis should give you a docstring.
As for internal variable scope, this is how things work:
Main Qt event loop creates a
NeuropyWindow which runs an
IPython session which imports
neuropy modules
So, something like get_ipython()
only works from within those neuropy modules
that have been imported during the IPython session, but not in any of
NeuropyWindow
's methods.
Dependencies:
neuropy requires recent versions of the following to be installed:
- Python (2.7.x, 3.x hasn't been tested)
- IPython 1.0
- numpy
- scipy
- matplotlib
- PyQt4 (PySide will probably work too, but is untested)
- Cython
Optional:
neuropy is developed in Xubuntu 12.10. It should work in other Linux distributions. In principle, it should also work in Windows and OSX.
An older version is described in the paper [Python for large-scale electrophysiology] (http://www.frontiersin.org/Neuroinformatics/10.3389/neuro.11.009.2008/abstract).
To run:
$ python main.py # in the neuropy folder
To install for use as a library:
$ python setup.py install