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: Divide this matrix by a second sparse matrix.
code: def _divide_sparse(self, other):
      """
      Divide this matrix by a second sparse matrix.
      """
      if other.shape != self.shape:
          raise ValueError("inconsistent shapes")
  
      r = self._binopt(other, "_eldiv_")
  
      if np.issubdtype(r.dtype, np.inexact):
          # Eldiv leaves entries outside the combined sparsity
          # pattern empty, so they must be filled manually.
          # Everything outside of other's sparsity is NaN, and everything
          # inside it is either zero or defined by eldiv.
          out = np.empty(self.shape, dtype=self.dtype)
          out.fill(np.nan)
          row, col = other.nonzero()
          out[row, col] = 0
          r = r.tocoo()
          out[r.row, r.col] = r.data
          out = matrix(out)
      else:
          # integers types go with nan <-> 0
          out = r
  
      return out
  
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 48 for calling the _cs_matrix obj's underlying member method code with example usage: obj._divide_sparse(other) and returns: out