# scipy.sparse.bsr_matrix.nanmax

bsr_matrix.nanmax(axis=None, out=None)

  Return the maximum of the matrix or maximum along an axis, ignoring any NaNs. This takes all elements into account, not just the non-zero ones.

  New in version 1.11.0.

  Parameters:
    axis{-2, -1, 0, 1, None} optional

      Axis along which the maximum is computed. The default is to compute the maximum over all the matrix elements, returning a scalar (i.e., axis = None).

    out None, optional

      This argument is in the signature solely for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used.

  Returns:
    amax coo_matrix or scalar

      Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is a sparse.coo_matrix of dimension `a.ndim - 1`.

  See also

  `nanmin`

    The minimum value of a sparse matrix along a given axis, ignoring NaNs.

  `max`

    The maximum value of a sparse matrix along a given axis, propagating NaNs.

  `numpy.nanmax`

    NumPy’s implementation of ‘nanmax’.