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