np.linalg.solve(np. linalg. solve)

矩阵中更高级的一些运算可以在NumPy的线性代数子库linalg中找到。例如inv函数计算逆矩阵,solve函数可以求解多元一次方程组。下面是solve函数的一个例子:

>>> a = np.random.rand(10,10)
>>> b = np.random.rand(10)
>>> x = np..solve(a,b)
>>> np.sum(np.abs(np.dot(a,x) - b))
3.1433189384699745e-15

solve函数有两个参数a和b。a是一个N*N的二维数组,而b是一个长度为N的一维数组,solve函数找到一个长度为N的一维数组x,使得a和x的矩阵乘积正好等于b,数组x就是多元一次方程组的解。

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Some of the more advanced operations in the matrix can be found in the linear algebra sub library linalg of numpy. For example, the inv function calculates the inverse matrix, and the solve function can solve the multivariate linear equations. The following is an example of the solve function:

>>> a = np.random.rand(10,10)
>>> b = np.random.rand(10)
>>> x = np..solve(a,b)
>>> np.sum(np.abs(np.dot(a,x) - b))
3.1433189384699745e-15

The solve function has two parameters a and B. A is a two-dimensional array of n * n, and B is a one-dimensional array with length n. The solve function finds a one-dimensional array x with length N, so that the matrix product of a and X is exactly equal to B, and array x is the solution of the system of multivariate primary equations.