# 第 3 章のプログラムは,事前に下記が実行されていることを仮定する。
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use("seaborn-ticks")
def H(j, x):
if j == 0:
return 1
elif j == 1:
return 2 * x
elif j == 2:
return -2 + 4 * x**2
else:
return 4 * x - 8 * x**3
cc = np.sqrt(5) / 4
a = 1/4 ##
def phi(j, x): ###
return np.exp(-(cc - a) * x**2) * H(j, np.sqrt(2 * cc) * x)
color = ["b", "g", "r", "k"]
x = np.linspace(-2, 2, 100)
plt.plot(x, phi(0, x), c=color[0], label="j = 0")
plt.ylim(-2, 8)
plt.ylabel("phi")
for i in range(0, 3):
plt.plot(x, phi(i, x), c=color[i + 1], label="j = %d" % i)
plt.title("Characteristic function of Gauss Kernel")
K = np.zeros((m, m))
for i in range(m):
for j in range(m):
K[i, j] = k(x[i], x[j])
values, vectors = np.linalg.eig(K)
lam = values / m
alpha = np.zeros((m, m))
for i in range(m):
alpha[:, i] = vectors[:, i] * np.sqrt(m) / (values[i] + 10e-16)
def F(y, i):
S = 0
for j in range(m):
S = S + alpha[j, i] * k(x[j], y)
return S