class_docstr: Mixin for min and max methods.
  
  These are not implemented for dia_matrix, hence the separate class.
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docstr: Return the maximum of the matrix or maximum along an axis.
  This takes all elements into account, not just the non-zero ones.
  
  Parameters
  ----------
  axis : {-2, -1, 0, 1, None} optional
      Axis along which the sum 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
  --------
  min : The minimum value of a sparse matrix along a given axis.
  np.matrix.max : NumPy's implementation of 'max' for matrices
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code: def max(self, axis=None, out=None):
      """
      Return the maximum of the matrix or maximum along an axis.
      This takes all elements into account, not just the non-zero ones.
  
      Parameters
      ----------
      axis : {-2, -1, 0, 1, None} optional
          Axis along which the sum 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
      --------
      min : The minimum value of a sparse matrix along a given axis.
      np.matrix.max : NumPy's implementation of 'max' for matrices
  
      """
      return self._min_or_max(axis, out, np.maximum)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from .base import spmatrix, _ufuncs_with_fixed_point_at_zero
  from .sputils import isscalarlike, validateaxis, matrix
label_desc: Use image node_id 5 for calling the _minmax_mixin obj's underlying member method code with example usage: obj.max(axis, out) and returns: self