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""" | |
Three ways of computing the Hellinger distance between two discrete | |
probability distributions using NumPy and SciPy. | |
""" | |
import numpy as np | |
from scipy.linalg import norm | |
from scipy.spatial.distance import euclidean | |
_SQRT2 = np.sqrt(2) # sqrt(2) with default precision np.float64 | |
def hellinger1(p, q): | |
return norm(np.sqrt(p) - np.sqrt(q)) / _SQRT2 | |
def hellinger2(p, q): | |
return euclidean(np.sqrt(p), np.sqrt(q)) / _SQRT2 | |
def hellinger3(p, q): | |
return np.sqrt(np.sum((np.sqrt(p) - np.sqrt(q)) ** 2)) / _SQRT2 |
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