高斯赛德尔迭代非常常用，看到网上很多例子写的不够简洁，这里我写了一个，供参考
import numpy as npdef gauss_seidel(A,b,x1,eps=1.e-6):n = len(A)max_iter = 200iters = 0while abs(np.dot(A[0,:],x1) - b)[0] > eps and iters < max_iter:#对二维矩阵，只判断了一行 #判断，为了减少计算量，只判断第一个点和最后一个点for i in range(n):median_value1 = 0.for j in range(0,n):if j != i: #只需要挖掉i==j的点就可以了median_value1 = median_value1+A[i,j]*x1[j]x1[i] = (b[i] - median_value1 )/A[i,i]iters += 1return x1,itersA = np.array([
[10.,-1.,-2],
[-1.,10.,-2.],
[-1.,-1.,5. ]
])
b = [72.,83.,42.]
initial = np.array([1.,1.,1.])x1,iters = gauss_seidel(A,b,initial)
print("iters = ",iters)
print("solution = ",x1)
print(np.dot(A,x1))
