gistfile1.py

from causality.nonparametric.causal_reg import MutualInformation

import numpy as np
import pandas as pd

K = [[1., 0.5, 0.25],
     [0.5, 1., 0.5],
     [0.25, 0.5, 1.]]
X = np.random.multivariate_normal(mean=[0,0,0],cov=K, size=1000)
X = pd.DataFrame(X,columns=['x1','x2','x3'])
X.cov()

Ihat = MutualInformation()
Ihat.estimate(X, ['x1'], ['x2','x3'])

# compare with the exact value: 
# - 0.5 * np.log( 1 - X.corr()['x1']['x2']**2)