`numpy.linalg:matrix_norm`

Signature

def matrix_norm(x, /, keepdims = False, ord = fro)

Computes the matrix norm of a matrix (or a stack of matrices) x.

This function is Array API compatible.

x : array_like: Input array having shape (..., M, N) and whose two innermost dimensions form MxN matrices.
keepdims : bool, optional: If this is set to True, the axes which are normed over are left in the result as dimensions with size one. Default: False.
ord : {1, -1, 2, -2, inf, -inf, 'fro', 'nuc'}, optional: The order of the norm. For details see the table under Notes in numpy.linalg.norm.

from numpy import linalg as LA
a = np.arange(9) - 4
a
b = a.reshape((3, 3))
b

✓

array([[-4, -3, -2],
       [-1,  0,  1],
       [ 2,  3,  4]])

LA.matrix_norm(b)
LA.matrix_norm(b, ord='fro')
LA.matrix_norm(b, ord=np.inf)
LA.matrix_norm(b, ord=-np.inf)

✗

np.float64(2.0)

LA.matrix_norm(b, ord=1)
LA.matrix_norm(b, ord=-1)
LA.matrix_norm(b, ord=2)
LA.matrix_norm(b, ord=-2)

✗

np.float64(3.757577037301703e-16)