parameters: (self, value)
return_statement: return sp.csc_matrix(D_null.A.ravel(order='F')).T
docstring: Gives the (sub/super)gradient of the atom w.r.t. a column argument.
  
          Matrix expressions are vectorized, so the gradient is a matrix.
  
          Args:
              value: A numeric value for a column.
  
          Returns:
              A NumPy ndarray matrix or None.
docstring_summary: Gives the (sub/super)gradient of the atom w.r.t. a column argument.
docstring_tokens: Gives the ( sub / super ) gradient of the atom w . r . t . a column argument .
function: def _column_grad(self, value):
          """Gives the (sub/super)gradient of the atom w.r.t. a column argument.
  
          Matrix expressions are vectorized, so the gradient is a matrix.
  
          Args:
              value: A numeric value for a column.
  
          Returns:
              A NumPy ndarray matrix or None.
          """
          rows = self.args[0].size
          D_null = sp.csc_matrix((rows, 1), dtype='float64')
          D_null += (value > 0)
          D_null -= (value < 0)
          return sp.csc_matrix(D_null.A.ravel(order='F')).T
function_tokens: def _column_grad ( self , value ) : rows = self . args [ 0 ] . size D_null = sp . csc_matrix ( ( rows , 1 ) , dtype = 'float64' ) D_null += ( value > 0 ) D_null -= ( value < 0 ) return sp . csc_matrix ( D_null . A . ravel ( order = 'F' ) ) . T