numpy.linalg.matrix_norm

linalg.matrix_norm(x, /, *, keepdims=False, ord='fro')[source]

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

This function is Array API compatible.

Parameters:

xarray_like

Input array having shape (…, M, N) and whose two innermost dimensions form MxN matrices.

keepdimsbool, 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.

See also

numpy.linalg.norm

Generic norm function

Examples

Try it in your browser!

>>> from numpy import linalg as LA
>>> a = np.arange(9) - 4
>>> a
array([-4, -3, -2, ...,  2,  3,  4])
>>> b = a.reshape((3, 3))
>>> b
array([[-4, -3, -2],
       [-1,  0,  1],
       [ 2,  3,  4]])

>>> LA.matrix_norm(b)
7.745966692414834
>>> LA.matrix_norm(b, ord='fro')
7.745966692414834
>>> LA.matrix_norm(b, ord=np.inf)
9.0
>>> LA.matrix_norm(b, ord=-np.inf)
2.0

>>> LA.matrix_norm(b, ord=1)
7.0
>>> LA.matrix_norm(b, ord=-1)
6.0
>>> LA.matrix_norm(b, ord=2)
7.3484692283495345
>>> LA.matrix_norm(b, ord=-2)
1.8570331885190563e-016 # may vary

Go BackOpen In Tab