如下所示:
from matplotlib import pyplot as plt import numpy as np from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = Axes3D(fig) #列出实验数据 point=[[2,3,48],[4,5,50],[5,7,51],[8,9,55],[9,12,56]] plt.xlabel("X1") plt.ylabel("X2") #表示矩阵中的值 ISum = 0.0 X1Sum = 0.0 X2Sum = 0.0 X1_2Sum = 0.0 X1X2Sum = 0.0 X2_2Sum = 0.0 YSum = 0.0 X1YSum = 0.0 X2YSum = 0.0 #在图中显示各点的位置 for i in range(0,len(point)): x1i=point[i][0] x2i=point[i][1] yi=point[i][2] ax.scatter(x1i, x2i, yi, color="red") show_point = "["+ str(x1i) +","+ str(x2i)+","+str(yi) + "]" ax.text(x1i,x2i,yi,show_point) ISum = ISum+1 X1Sum = X1Sum+x1i X2Sum = X2Sum+x2i X1_2Sum = X1_2Sum+x1i**2 X1X2Sum = X1X2Sum+x1i*x2i X2_2Sum = X2_2Sum+x2i**2 YSum = YSum+yi X1YSum = X1YSum+x1i*yi X2YSum = X2YSum+x2i*yi # 进行矩阵运算 # _mat1 设为 mat1 的逆矩阵 m1=[[ISum,X1Sum,X2Sum],[X1Sum,X1_2Sum,X1X2Sum],[X2Sum,X1X2Sum,X2_2Sum]] mat1 = np.matrix(m1) m2=[[YSum],[X1YSum],[X2YSum]] mat2 = np.matrix(m2) _mat1 =mat1.getI() mat3 = _mat1*mat2 # 用list来提取矩阵数据 m3=mat3.tolist() a0 = m3[0][0] a1 = m3[1][0] a2 = m3[2][0] # 绘制回归线 x1 = np.linspace(0,9) x2 = np.linspace(0,12) y = a0+a1*x1+a2*x2 ax.plot(x1,x2,y) show_line = "y="+str(a0)+"+"+str(a1)+"x1"+"+"+str(a2)+"x2" plt.title(show_line) plt.show()
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