Python 实现顺序高斯消元法示例

我就废话不多说,直接上代码吧!

# coding: utf8

import numpy as np

# 设置矩阵

def getInput():

matrix_a = np.mat([[2, 3, 11, 5],

[1, 1, 5, 2],

[2, 1, 3, 2],

[1, 1, 3, 4]],dtype=float)

matrix_b = np.mat([2,1,-3,-3])

#答案:-2 0 1 1

return matrix_a, matrix_b

def SequentialGauss(mat_a):

for i in range(0, (mat_a.shape[0])-1):

if mat_a[i, i] == 0:

print("终断运算:")

print(mat_a)

break

else:

for j in range(i+1, mat_a.shape[0]):

mat_a[j:j+1 , :] = mat_a[j:j+1,:] - \

(mat_a[j,i]/mat_a[i,i])*mat_a[i, :]

return mat_a

def revert(new_mat):

#创建矩阵存放答案 初始化为0

x = np.mat(np.zeros(new_mat.shape[0], dtype=float))

number = x.shape[1]-1

# print(number)

b = number+1

x[0,number] = new_mat[number,b]/new_mat[number, number]

for i in range(number-1,-1,-1):

try:

x[0,i] = (new_mat[i,b]-np.sum(np.multiply(new_mat[i,i+1:b],x[0,i+1:b])))/(new_mat[i,i])

except:print("错误")

print(x)

if __name__ == "__main__":

mat_a, mat_b = getInput()

# 合并两个矩阵

print("原矩阵")

print(np.hstack((mat_a, mat_b.T)))

new_mat = SequentialGauss(np.hstack((mat_a, mat_b.T)))

print("三角矩阵")

print(new_mat)

print("方程的解")

revert(new_mat)

运行结果如下

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