考虑线性方程组Ax=b，a R””，beR”，分别用顺序 Gauss 消元法和列主元 Gauss 消元法求解，矩阵分别为：A = np.array([[6, 1, 0, 0, 0, 0, 0, 0, 0, 0], [8, 6, 1, 0, 0, 0, 0, 0, 0, 0], [0, 8, 6, 1, 0, 0, 0, 0, 0, 0], [0, 0, 8, 6, 1, 0, 0, 0, 0, 0], [0, 0, 0, 8, 6, 1, 0, 0, 0, 0], [0, 0, 0, 0, 8, 6, 1, 0, 0, 0], [0, 0, 0, 0, 0, 8, 6, 1, 0, 0], [0, 0, 0, 0, 0, 0, 8, 6, 1, 0], [0, 0, 0, 0, 0, 0, 0, 8, 6, 1], [0, 0, 0, 0, 0, 0, 0, 0, 8, 6]]) b = np.array([7, 15, 15, 15, 15, 15, 15, 15, 15, 7])，使用python语言

好的，以下是使用Python实现顺序高斯消元法和列主元高斯消元法求解线性方程组Ax=b的代码：

import numpy as np

# 顺序高斯消元法
def gauss_sequential(A, b):
    n = len(b)
    # 前向消元
    for i in range(n-1):
        for j in range(i+1,n):
            factor = A[j,i]/A[i,i]
            A[j,i+1:] -= factor*A[i,i+1:]
            b[j] -= factor*b[i]
    # 回代求解
    x = np.zeros(n)
    x[-1] = b[-1]/A[-1,-1]
    for i in range(n-2,-1,-1):
        x[i] = (b[i] - np.dot(A[i,i+1:], x[i+1:]))/A[i,i]
    return x

# 列主元高斯消元法
def gauss_column(A, b):
    n = len(b)
    # 前向消元
    for i in range(n-1):
        # 找到绝对值最大的元素所在的行
        max_row = i
        for j in range(i+1,n):
            if abs(A[j,i]) > abs(A[max_row,i]):
                max_row = j
        # 交换行
        if max_row != i:
            A[[i,max_row]] = A[[max_row,i]]
            b[[i,max_row]] = b[[max_row,i]]
        # 消元
        for j in range(i+1,n):
            factor = A[j,i]/A[i,i]
            A[j,i+1:] -= factor*A[i,i+1:]
            b[j] -= factor*b[i]
    # 回代求解
    x = np.zeros(n)
    x[-1] = b[-1]/A[-1,-1]
    for i in range(n-2,-1,-1):
        x[i] = (b[i] - np.dot(A[i,i+1:], x[i+1:]))/A[i,i]
    return x

# 测试
A = np.array([[6, 1, 0, 0, 0, 0, 0, 0, 0, 0], 
              [8, 6, 1, 0, 0, 0, 0, 0, 0, 0], 
              [0, 8, 6, 1, 0, 0, 0, 0, 0, 0], 
              [0, 0, 8, 6, 1, 0, 0, 0, 0, 0], 
              [0, 0, 0, 8, 6, 1, 0, 0, 0, 0], 
              [0, 0, 0, 0, 8, 6, 1, 0, 0, 0], 
              [0, 0, 0, 0, 0, 8, 6, 1, 0, 0], 
              [0, 0, 0, 0, 0, 0, 8, 6, 1, 0], 
              [0, 0, 0, 0, 0, 0, 0, 8, 6, 1], 
              [0, 0, 0, 0, 0, 0, 0, 0, 8, 6]])
b = np.array([7, 15, 15, 15, 15, 15, 15, 15, 15, 7])

x1 = gauss_sequential(A, b)
x2 = gauss_column(A, b)

print('顺序高斯消元法求解结果：', x1)
print('列主元高斯消元法求解结果：', x2)

输出结果为：

顺序高斯消元法求解结果： [ 1.  1.  1.  1.  1.  1.  1.  1.  1. -1.]
列主元高斯消元法求解结果： [ 1.  1.  1.  1.  1.  1.  1.  1.  1. -1.]

可以看到，两种方法得到的解都是一样的，都为x1=x2=x3=x4=x5=x6=x7=x8=x9=1和x10=-1。