Repository made for the PNG & Entropy Paper

From the Materials & Methods in:

A quick and easy way to estimate entropy and mutual information for neuroscience

Mickael Zbili(1), Sylvain Rama(2)

1, Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, Geneva, Switzerland.

2, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.

List of Python scripts: All scripts were done in Anaconda 3.7 with Numpy, Pandas, pyABF, pyPNG and Bokeh.

pyABF: https://pypi.org/project/pyabf/

pyPNG: https://pypi.org/project/pypng/

Demo_EntropyByWordsLetters.py:

Python script made to demonstrate the impact of quantization and sampling (parameters v and T) on the calculation of entropy.

BatchHsHnFromFile.py:

Main script to calculate all the possible values of entropy according to the T, v and Size parameters. This will ask for a list of abf or csv data files and will create an Excel Spreadsheet with all Hs & Hn values for each data file.

PlotHsHnFromExcel.py:

This will take the HS & Hn Excel files created by BatchHsHnFromFile.py, plot the values and perform the 3 quadratic extrapolations. The final values of Rs and Rn will be used to calculate I = Rs - Rn.

Main_Entropy_Module.py:

Main Module to calculate Entropy by the direct way with correction of the sampling bias. This is needed by the two previous scripts.

BatchSaveAsPNG.py:

This script will convert csv or abf files to PNG, save a direct file and a transposed copy and log the PNG Rates (file sizes divided by the number of pixels in the image) in an Excel file.

GenerateRandomNoise.py:

This will create Gaussian White noise and sort it or not. Then save it as a csv, for later analyze of Hs & Hn or save it as PNG.

PNG_Scripts.llb:

series of Labview scripts made using Labview 2017 and Vision 2017.

They are used for figures 2, 3, 4, 5 and 6. See the top level vi in the llb for description.