parameters: (element, test_elements, assume_unique=False, invert=False)
return_statement: return in1d(element, test_elements, assume_unique=assume_unique,
                  invert=invert).reshape(element.shape)
docstring: Calculates `element in test_elements`, broadcasting over
      `element` only.
  
      The output is always a masked array of the same shape as `element`.
      See `numpy.isin` for more details.
  
      See Also
      --------
      in1d       : Flattened version of this function.
      numpy.isin : Equivalent function for ndarrays.
  
      Notes
      -----
      .. versionadded:: 1.13.0
docstring_summary: Calculates `element in test_elements`, broadcasting over
      `element` only.
docstring_tokens: Calculates element in test_elements broadcasting over element only .
function: def isin(element, test_elements, assume_unique=False, invert=False):
      """
      Calculates `element in test_elements`, broadcasting over
      `element` only.
  
      The output is always a masked array of the same shape as `element`.
      See `numpy.isin` for more details.
  
      See Also
      --------
      in1d       : Flattened version of this function.
      numpy.isin : Equivalent function for ndarrays.
  
      Notes
      -----
      .. versionadded:: 1.13.0
  
      """
      element = ma.asarray(element)
      return in1d(element, test_elements, assume_unique=assume_unique,
                  invert=invert).reshape(element.shape)
function_tokens: def isin ( element , test_elements , assume_unique = False , invert = False ) : element = ma . asarray ( element ) return in1d ( element , test_elements , assume_unique = assume_unique , invert = invert ) . reshape ( element . shape )