class_docstr: base matrix class for compressed row and column oriented matrices
class_docstr_tok: ["base","matrix","class","for","compressed","row","and","column","oriented","matrices"]
docstr: Reduce nonzeros with a ufunc over the minor axis when non-empty
  
  Can be applied to a function of self.data by supplying data parameter.
  
  Warning: this does not call sum_duplicates()
  
  Returns
  -------
  major_index : array of ints
      Major indices where nonzero
  
  value : array of self.dtype
      Reduce result for nonzeros in each major_index
code: def _minor_reduce(self, ufunc, data=None):
      """Reduce nonzeros with a ufunc over the minor axis when non-empty
  
      Can be applied to a function of self.data by supplying data parameter.
  
      Warning: this does not call sum_duplicates()
  
      Returns
      -------
      major_index : array of ints
          Major indices where nonzero
  
      value : array of self.dtype
          Reduce result for nonzeros in each major_index
      """
      if data is None:
          data = self.data
      major_index = np.flatnonzero(np.diff(self.indptr))
      value = ufunc.reduceat(
          data, downcast_intp_index(self.indptr[major_index])
      )
      return major_index, value
  
imports: from __future__ import division, print_function, absolute_import
  from warnings import warn
  import operator
  import numpy
  from scipy._lib.six import zip
  from scipy._lib._util import _prune_array
  from .base import spmatrix, isspmatrix, SparseEfficiencyWarning
  from .data import _data_matrix, _minmax_mixin
  from .dia import dia_matrix
  from .None import _sparsetools
  from .sputils import upcast, upcast_char, to_native, isdense, isshape, getdtype, isscalarlike, IndexMixin, get_index_dtype, downcast_intp_index, get_sum_dtype, check_shape, matrix, asmatrix
label_desc: Use image node_id 25 for calling the _cs_matrix obj's underlying member method code with example usage: obj._minor_reduce(ufunc, data) and returns: major_index,  value