numpy求解方程组

numpy可以使用线性代数库(scipy.linalg)中的solve函数来求解线性方程组。通过将系数矩阵A和常数向量b作为参数传递给solve函数，即可得到方程组的解。下面是使用numpy求解线性方程组的代码示例：

import numpy as np
from scipy.linalg import solve

# 定义系数矩阵A和常数向量b
A = np.array([[3, 1, -2],
              [1, -1, 4],
              [2, 0, 3]])
b = np.array([5, -2, 2.5])

# 使用solve函数求解方程组
x = solve(A, b)

# 打印解向量x
print(x)

执行以上代码，将得到方程组的解向量x的值。在本例中，方程组的解为x=[1, -2, 0.5]。所提供的代码示例中使用了numpy包和scipy.linalg库的solve函数，该函数可以直接求解线性方程组。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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