转Python SciPy库——拟合与插值

1.最小二乘拟合

实例1

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import leastsq


plt.figure(figsize=(9,9))
x=np.linspace(0,10,1000)
X = np.array([8.19, 2.72, 6.39, 8.71, 4.7, 2.66, 3.78])
Y = np.array([7.01, 2.78, 6.47, 6.71, 4.1, 4.23, 4.05])
#计算以p为参数的直线和原始数据之间的误差
def f(p):
    k, b = p
    return(Y-(k*X+b))
#leastsq使得f的输出数组的平方和最小，参数初始值为[1,0]
r = leastsq(f, [1,0])
k, b = r[0]
print("k=",k,"b=",b)

plt.scatter(X,Y, s=100, alpha=1.0, marker=\'o\',label=u\'数据点\')

y=k*x+b

ax = plt.gca()  #gca获取轴这个对象

ax.set_xlabel(..., fontsize=20)
ax.set_ylabel(..., fontsize=20)
#设置坐标轴标签字体大小

plt.plot(x, y, color=\'r\',linewidth=5, linestyle=":",markersize=20, label=u\'拟合曲线\')

plt.legend(loc=0, numpoints=1)
leg = plt.gca().get_legend()
ltext  = leg.get_texts()
plt.setp(ltext, fontsize=