#!/usr/bin/env python

# -*- coding:utf-8 -*-

# FileName: 005_interpolate.py

#

# Description:

#

# Version: 1.0

# Created: 2018-06-13 11:05:00

# Last Modified: 2019-09-03 10:50:53

# Revision: none

# Compiler: gcc

#

# Author: zt ()

# Organization:

import matplotlib.pyplot as plt

import numpy as np

import scipy.interpolate as scin

def f(x):

return np.sin(x)

n = np.arange(0, 10)

x = np.linspace(0, 9, 100)

y_meas = f(n) + 0.1 * np.random.randn(len(n))

y_real = f(x)

linear_interpolation = scin.interp1d(n, y_meas)

y_interp1 = linear_interpolation(x)

cublic_interpolation = scin.interp1d(n, y_meas, kind='cubic')

y_interp2 = cublic_interpolation(x)

fig, ax = plt.subplots(figsize=(10, 4))

ax.plot(n, y_meas, 'bs', label='noisy_data')

ax.plot(x, y_real, 'k', lw=2, label='true function')

ax.plot(x, y_interp1, 'r', label='linear interp')

ax.plot(x, y_interp2, 'g', label='cubic interp')

ax.legend(loc=3)

plt.show()