plot-gradient.py

import numpy as np
import matplotlib.pyplot as plt
import math

def valid_convolve(x, y, n):
    b = np.ones(n)/ n
    y2 = np.convolve(y, b, mode="valid")
    return (x[n-1:], y2)

def convolve_gradient(x, y, n, dx = 1):
	x2, y2 = valid_convolve(x, y, n)
	y3 = np.gradient(y2, dx)
	return (x2, y3)

x = np.linspace(0, 10, 500)
y1 = x * x + 3 * x + 10
y2 = y1 + np.random.randn(500)*0.3 # ノイズを混ぜる

fig = plt.figure()
ax = []
ax.append(fig.add_subplot(1, 3, 1))
ax[-1].plot(x, y1 ,linewidth=1)
ax[-1].plot(x, y2 ,linewidth=1)

#ax.append(fig.add_subplot(1, 3, 2))
X, Y = valid_convolve(x, y2, 100)
ax[-1].plot(X, Y ,linewidth=1)

ax.append(fig.add_subplot(1, 3, 2))
X, Y = convolve_gradient(x, y2, 100)
ax[-1].plot(X, Y ,linewidth=1)

ax.append(fig.add_subplot(1, 3, 3))
X2, Y2 = convolve_gradient(X, Y, 100)
ax[-1].plot(X2, Y2 ,linewidth=1)

plt.show()