parameters: (self, value)
return_statement: return D
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 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 or None.
          """
          # Grad: 1 for a largest index.
          value = np.array(value).ravel(order='F')
          idx = np.argmax(value)
          D = np.zeros((value.size, 1))
          D[idx] = 1
          return D
function_tokens: def _column_grad ( self , value ) : # Grad: 1 for a largest index. value = np . array ( value ) . ravel ( order = 'F' ) idx = np . argmax ( value ) D = np . zeros ( ( value . size , 1 ) ) D [ idx ] = 1 return D