Python实现二维曲线拟合的方法
程序员文章站
2022-07-06 11:55:33
如下所示:
from numpy import *
import numpy as np
import matplotlib.pyplot as plt...
如下所示:
from numpy import * import numpy as np import matplotlib.pyplot as plt plt.close() fig=plt.figure() plt.grid(true) plt.axis([0,10,0,8]) #列出数据 point=[[1,2],[2,3],[3,6],[4,7],[6,5],[7,3],[8,2]] plt.xlabel("x") plt.ylabel("y") #用于求出矩阵中各点的值 xsum = 0.0 x2sum = 0.0 x3sum = 0.0 x4sum = 0.0 isum = 0.0 ysum = 0.0 xysum = 0.0 x2ysum = 0.0 #列出各点的位置 for i in range(0,len(point)): xi=point[i][0] yi=point[i][1] plt.scatter(xi,yi,color="red") show_point = "("+ str(xi) +","+ str(yi) + ")" plt.text(xi,yi,show_point) xsum = xsum+xi x2sum = x2sum+xi**2 x3sum = x3sum + xi**3 x4sum = x4sum + xi**4 isum = isum+1 ysum = ysum+yi xysum = xysum+xi*yi x2ysum = x2ysum + xi**2*yi # 进行矩阵运算 # _mat1 设为 mat1 的逆矩阵 m1=[[isum,xsum, x2sum],[xsum, x2sum, x3sum],[x2sum, x3sum, x4sum]] mat1 = np.matrix(m1) m2=[[ysum], [xysum], [x2ysum]] mat2 = np.matrix(m2) _mat1 =mat1.geti() mat3 = _mat1*mat2 # 用list来提取矩阵数据 m3=mat3.tolist() a = m3[0][0] b = m3[1][0] c = m3[2][0] # 绘制回归线 x = np.linspace(0,10) y = a + b*x + c*x**2 plt.plot(x,y) show_line = "y="+str(a)+"+("+str(b)+"x)"+"+("+str(c)+"x2)"; plt.title(show_line) plt.show()
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