python数据分析入门——matplotlib的中文显示问题&最小二乘法

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 10 23:20:26 2016

@author: Administrator
"""

import numpy as np
from scipy.optimize import leastsq
import pylab as pl


‘‘‘
针对matplotlib显示中文的办法
只需添加下面三行代码
‘‘‘
import matplotlib as mpl
mpl.rcParams["font.sans-serif"] = ["Microsoft YaHei"]
mpl.rcParams[‘axes.unicode_minus‘] = False

def func(x, p):
	‘‘‘
	数据拟合所需要的函数
	A*sin(2*K*np.pi*x + theta)
	‘‘‘
	A, k, theta = p
	return A*np.sin(2*k*np.pi*x + theta)

def residuals(p , y, x):
	‘‘‘
	实验数据和拟合函数之差，p为拟合需要的参数
	‘‘‘
	return (y-func(x, p))
	
x = np.linspace(0, -2*np.pi, 100)
A, k, theta = 10, 0.34, np.pi/6  # 真实数据的函数参数
y0 = func(x, [A, k, theta])  # 真实数据
y1 = y0 + 2 * np.random.randn(len(x))  # 加入噪声之后的数据

p0 = [7, 0.2, 0]  # 第一次猜测的函数拟合函数
# 调用leastsq进行数据拟合
# residuals为计算误差的函数
# p0为拟合参数的初始值
# args为需要拟合的实验数据
plsq = leastsq(residuals, p0, args=(y1, x))
print("真实参数-->", [A, k, theta])
print("拟合参数-->", plsq[0])

pl.plot(x, y0, label = "真实数据")
pl.plot(x, y1, label = "带噪声的实验数据")
pl.plot(x, func(x, plsq[0]), label = "拟合数据")
pl.legend()
pl.show()