from scipy.interpolate import Akima1DInterpolator as Akima
from scipy.interpolate import PchipInterpolator as pchip
from scipy.interpolate import CubicSpline as cubic
import numpy as np
import matplotlib.pyplot as plt

plt.ion()
np.random.seed()

def show_plot(x, y):
    p = pchip(x, y)
    c = cubic(x, y, bc_type='natural')
    c2 = cubic(x, y)
    a = Akima(x, y)

    xp = np.sort(x[0] + (x[-1] - x[0])*np.random.random(200))

    plt.plot(x, y, 'b+', ms=8, mec='r')
    plt.plot(xp, c(xp), 'y-', lw=3, alpha=0.7)     # yellow for Cubic/natural
    plt.plot(xp, c2(xp), 'y-', lw=3, alpha=0.3)    # light-yellow for Cubic/not-a-knot
    plt.plot(xp, a(xp), 'b-', lw=2, alpha=0.5)     # light-blue for Akima
    plt.plot(xp, p(xp), 'm-', lw=1, alpha=1)       # red for pchip
    plt.draw()

x = range(20)
y = 10 * np.sort(np.random.random(20))
show_plot(x, y)

x = range(20)
y = 10 * np.random.random(20)
show_plot(x, y)

x = 10 * np.sort(np.random.random(20))
y = 10 * np.sort(np.random.random(20))
show_plot(x, y)

x = 10 * np.sort(np.random.random(20))
y = 10 * np.random.random(20)
show_plot(x, y)