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import math
import numpy as np
from frob_norm import frob_norm
def gauss_kernel(X_1, X_2, sigma):
"""
Calculates the Gaussian Kernel.
X_1: first representations.
X_2: second representations.
sigma: kernel width.
"""
x1_l = len(X_1)
x1_range = range(x1_l)
x2_l = len(X_2)
x2_range = range(x2_l)
inv_sigma = -0.5 / (sigma*sigma)
K = np.zeros((x1_l, x2_l))
for i in x1_range:
for j in x2_range:
f_norm = frob_norm(X_1[i] - X_2[j])
# print(f_norm)
K[i, j] = math.exp(inv_sigma * f_norm)
return K
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