How to use the ecl.EclTypeEnum function in ecl

def constant_size_data_type(ecl_type):
    return (ecl_type in [
                        EclTypeEnum.ECL_CHAR_TYPE,
                        EclTypeEnum.ECL_FLOAT_TYPE,
                        EclTypeEnum.ECL_DOUBLE_TYPE,
                        EclTypeEnum.ECL_INT_TYPE,
                        EclTypeEnum.ECL_BOOL_TYPE,
                        EclTypeEnum.ECL_MESS_TYPE
                        ])

def constant_size_data_type(ecl_type):
    return (ecl_type in [
                        EclTypeEnum.ECL_CHAR_TYPE,
                        EclTypeEnum.ECL_FLOAT_TYPE,
                        EclTypeEnum.ECL_DOUBLE_TYPE,
                        EclTypeEnum.ECL_INT_TYPE,
                        EclTypeEnum.ECL_BOOL_TYPE,
                        EclTypeEnum.ECL_MESS_TYPE
                        ])

def constant_size_data_type(ecl_type):
    return (ecl_type in [
                        EclTypeEnum.ECL_CHAR_TYPE,
                        EclTypeEnum.ECL_FLOAT_TYPE,
                        EclTypeEnum.ECL_DOUBLE_TYPE,
                        EclTypeEnum.ECL_INT_TYPE,
                        EclTypeEnum.ECL_BOOL_TYPE,
                        EclTypeEnum.ECL_MESS_TYPE
                        ])

def warn_and_cast_data_type(data_type):
    if isinstance(data_type, EclDataType):
        return data_type
    if isinstance(data_type, EclTypeEnum):
        if not constant_size_data_type(data_type):
            raise ValueError("Cannot cast EclTypeEnum (%d) to EclDataType due "
                    "to non-constant size. Please provide an EclDataType instead.")

        dump_type_deprecation_warning()
        return EclDataType(data_type)

raise TypeError("index_frame must be pandas.DataFrame")
        if len(kw) == self.get_global_size():
            index = numpy.array( index_frame.index, dtype=numpy.int32 )
        elif len(kw) == self.get_num_active():
            index = numpy.array( index_frame["active"], dtype=numpy.int32 )
        else:
            raise ValueError("The keyword must have a 3D compatible length")

        if kw.type is EclTypeEnum.ECL_INT_TYPE:
            data = numpy.full( len(index), default, dtype=numpy.int32 )
            self._export_data_as_int( len(index), 
                                       index.ctypes.data_as(ctypes.POINTER(ctypes.c_int32)), 
                                       kw, 
                                       data.ctypes.data_as(ctypes.POINTER(ctypes.c_int32))   )
            return data
        elif kw.type is EclTypeEnum.ECL_FLOAT_TYPE or kw.type is EclTypeEnum.ECL_DOUBLE_TYPE:
            data = numpy.full( len(index), default, dtype=numpy.float64 )
            self._export_data_as_double( len(index), 
                                         index.ctypes.data_as(ctypes.POINTER(ctypes.c_int32)), 
                                         kw, 
                                         data.ctypes.data_as(ctypes.POINTER(ctypes.c_double))   )            
            return data
        else:
            raise TypeError("Keyword must be either int, float or double.")

def constant_size_data_type(ecl_type):
    return (ecl_type in [
                        EclTypeEnum.ECL_CHAR_TYPE,
                        EclTypeEnum.ECL_FLOAT_TYPE,
                        EclTypeEnum.ECL_DOUBLE_TYPE,
                        EclTypeEnum.ECL_INT_TYPE,
                        EclTypeEnum.ECL_BOOL_TYPE,
                        EclTypeEnum.ECL_MESS_TYPE
                        ])

def warn_and_cast_data_type(data_type):
    if isinstance(data_type, EclDataType):
        return data_type
    if isinstance(data_type, EclTypeEnum):
        if not constant_size_data_type(data_type):
            raise ValueError("Cannot cast EclTypeEnum (%d) to EclDataType due "
                    "to non-constant size. Please provide an EclDataType instead.")

        dump_type_deprecation_warning()
        return EclDataType(data_type)

as obtained from export_index.
        kw must have size of either global_size or num_active.
        The length of the numpy vector is the number of rows in index_frame.
        If kw is of length num_active, values in the output vector
        corresponding to inactive cells are set to default.
        """
        if not isinstance(index_frame, pandas.DataFrame):
            raise TypeError("index_frame must be pandas.DataFrame")
        if len(kw) == self.get_global_size():
            index = numpy.array( index_frame.index, dtype=numpy.int32 )
        elif len(kw) == self.get_num_active():
            index = numpy.array( index_frame["active"], dtype=numpy.int32 )
        else:
            raise ValueError("The keyword must have a 3D compatible length")

        if kw.type is EclTypeEnum.ECL_INT_TYPE:
            data = numpy.full( len(index), default, dtype=numpy.int32 )
            self._export_data_as_int( len(index), 
                                       index.ctypes.data_as(ctypes.POINTER(ctypes.c_int32)), 
                                       kw, 
                                       data.ctypes.data_as(ctypes.POINTER(ctypes.c_int32))   )
            return data
        elif kw.type is EclTypeEnum.ECL_FLOAT_TYPE or kw.type is EclTypeEnum.ECL_DOUBLE_TYPE:
            data = numpy.full( len(index), default, dtype=numpy.float64 )
            self._export_data_as_double( len(index), 
                                         index.ctypes.data_as(ctypes.POINTER(ctypes.c_int32)), 
                                         kw, 
                                         data.ctypes.data_as(ctypes.POINTER(ctypes.c_double))   )            
            return data
        else:
            raise TypeError("Keyword must be either int, float or double.")