code: def _der(self,*args):
          '''
          Evaluate the derivative of the function.  The first input must exist and should be an array.
          Returns an array of identical shape to args[0] (if it exists).  This is an array of zeros.
          '''
          if len(args) > 0:
              if _isscalar(args[0]):
                  return 0.0
              else:
                  shape = args[0].shape
                  return np.zeros(shape)
          else:
              return 0.f _der(self,*args):
          '''
          Evaluate the derivative of the function.  The first input must exist and should be an array.
          Returns an array of identical shape to args[0] (if it exists).  This is an array of zeros.
          '''
          if len(args) > 0:
              if _isscalar(args[0]):
                  return 0.0
              else:
                  shape = args[0].shape
                  return np.zeros(shape)
          else:
              return 0.0
docs: Evaluate the derivative of the function.  The first input must exist and should be an array.
          Returns an array of identical shape to args[0] (if it exists).  This is an array of zeros.