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# numpy.linalg.matrix_norm

linalg.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.

  Parameters:
    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`.

  See also

  `numpy.linalg.norm`

    Generic norm function

  Examples

      >>> 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