tensor-maximum-entropy

Name	tensor-maximum-entropy JSON
Version	0.0.2 JSON
	download
home_page	https://github.com/ArdeleanRichard/TME
Summary	Python implementation of the Tensor Maximum Entropy (TME)
upload_time	2024-05-08 05:44:53
maintainer	None
docs_url	None
author	Eugen-Richard Ardelean
requires_python	>=3.7
license	MIT
keywords
VCS
bugtrack_url
requirements	numpy matplotlib scipy scikit-learn
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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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