Python implementation of the Tensor Maximum Entropy (TME)
Project description
TME
Python implementation of Tensor Maximum Entropy (TME)
Install:
pip install tensor-maximum-entropy
Usage example:
import numpy as np
import scipy.io
from tensor_maximum_entropy import TME
model_dim = 10
data = scipy.io.loadmat('./exampleData.mat')
dataTensor = data['dataTensor']
print(dataTensor.shape)
t = data['t']
mask = np.logical_and(t > - 50, t < 350)
TME(dataTensor, mask, model_dim)
The algorithm description can be found in the following article:
Elsayed, G.F.; Cunningham, J.P. Structure in Neural Population Recordings: An Expected Byproduct of Simpler Phenomena? Nat Neurosci 2017, 20, 1310–1318, doi:10.1038/nn.4617.
A matlab implementation can be found at the following link: https://github.com/gamaleldin/TME
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