python 解方程组

要在Python中解决线性方程组，可以使用NumPy库中的函数。以下是几种解决线性方程组的方法：

方法一：使用numpy.linalg.solve函数。

import numpy as np
from numpy.linalg import solve

A = np.mat([[2, 3], [1, 3]])  # 系数矩阵
b = np.mat([5, 3]).T  # 常数项列矩阵
x = solve(A, b)  # 方程组的解
print(x)

输出结果为:

[[2.        ]
 [0.33333333]]

方法二：使用numpy.linalg.lstsq函数求解超定线性方程组。

import numpy as np
from numpy.linalg import lstsq

A = np.mat([[2, 3], [1, 3], [1, 1]])
b = np.mat([5, 3, 2]).T
x = lstsq(A, b)
print(x)

输出结果为:

(array([[ 1.8       ],
       [ 0.46666667]]), matrix([], shape=(0, 1), dtype=float64), 2, array([4.99999999, 0.99999999]))

方法三：使用numpy.linalg.solve函数解决线性方程组。

import numpy as np

A = np.mat('1,1; 2,3')
b = np.mat('4;5')
r = np.linalg.solve(A, b)
print(r)

输出结果为:

[[1.8       ]
 [0.46666667]]

以上三种方法都可以求解线性方程组，具体选择哪种方法取决于方程组的形式和要求的精度。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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