Ledapy is a minimal port of Ledalab (www.ledalab.de) for Python. It runs in the command line and does not provide a GUI. However, it is suitable for integration with other packages, including MIDAS.
Ledapy requires Python 3 and the following packages
- numpy
- scipy
- sympy
Optionally, if one wants to plot
- matplotlib
Ledapy is available on PyPi. To install, run pip3 install ledapy.
There are some .mat files in this repository, provided so that Ledapy's results can be compared to Ledalab's (which can be run separately in Matlab).
A test run can be initated as follows
git clone https://github.com/HIIT/Ledapy.git
cd Ledapy
python3
import ledapy
import scipy.io as sio
from numpy import array as npa
filename = 'EDA1_long_100Hz.mat'
sampling_rate = 100
matdata = sio.loadmat(filename)
rawdata = npa(matdata['data']['conductance'][0][0][0], dtype='float64')
phasicdata = ledapy.runner.getResult(rawdata, 'phasicdata', sampling_rate, downsample=4, optimisation=2)
import matplotlib.pyplot as plt # note: requires matplotlib, not installed by default
plt.plot(phasicdata)
plt.show()
You should obtain something like this:
note that optimisation is performed automatically. To compare results with Ledalab, remember to press the ‘optimise’ button