text: # -*- coding: utf-8 -*-
  # File generated according to Generator/ClassesRef/DataFreq.csv
  # WARNING! All changes made in this file will be lost!
  """Method code available at https://github.com/Eomys/SciDataTool/tree/master/SciDataTool/Methods//DataFreq
  """
  
  from os import linesep
  from sys import getsizeof
  from ._check import set_array, check_var, raise_
  from ..Functions.save import save
  from ..Functions.copy import copy
  from ..Functions.load import load_init_dict
  from ..Functions.Load.import_class import import_class
  from .DataND import DataND
  
  # Import all class method
  # Try/catch to remove unnecessary dependencies in unused method
  try:
      from ..Methods.DataFreq.freq_to_time import freq_to_time
  except ImportError as error:
      freq_to_time = error
  
  
  from numpy import array, array_equal
  from ._check import InitUnKnowClassError
  
  
  class DataFreq(DataND):
      """Class for fields defined in Fourier space"""
  
      VERSION = 1
  
      # cf Methods.DataFreq.freq_to_time
      if isinstance(freq_to_time, ImportError):
          freq_to_time = property(
              fget=lambda x: raise_(
                  ImportError(
                      "Can't use DataFreq method freq_to_time: " + str(freq_to_time)
                  )
              )
          )
      else:
          freq_to_time = freq_to_time
      # save and copy methods are available in all object
      save = save
      copy = copy
  
      def __init__(
          self,
          axes=None,
          FTparameters=-1,
          values=None,
          is_real=True,
          symbol="",
          name="",
          unit="",
          normalizations=-1,
          init_dict=None,
          init_str=None,
      ):
          """Constructor of the class. Can be use in three ways :
          - __init__ (arg1 = 1, arg3 = 5) every parameters have name and default values
              for SciDataTool type, -1 will call the default constructor
          - __init__ (init_dict = d) d must be a dictionnary with property names as keys
          - __init__ (init_str = s) s must be a string
          s is the file path to load
  
          ndarray or list can be given for Vector and Matrix
          object or dict can be given for SciDataTool Object"""
  
          if init_str is not None:  # Load from a file
              init_dict = load_init_dict(init_str)[1]
          if init_dict is not None:  # Initialisation by dict
              assert type(init_dict) is dict
              # Overwrite default value with init_dict content
              if "axes" in list(init_dict.keys()):
                  axes = init_dict["axes"]
              if "FTparameters" in list(init_dict.keys()):
                  FTparameters = init_dict["FTparameters"]
              if "values" in list(init_dict.keys()):
                  values = init_dict["values"]
              if "is_real" in list(init_dict.keys()):
                  is_real = init_dict["is_real"]
              if "symbol" in list(init_dict.keys()):
                  symbol = init_dict["symbol"]
              if "name" in list(init_dict.keys()):
                  name = init_dict["name"]
              if "unit" in list(init_dict.keys()):
                  unit = init_dict["unit"]
              if "normalizations" in list(init_dict.keys()):
                  normalizations = init_dict["normalizations"]
          # Set the properties (value check and convertion are done in setter)
          # Call DataND init
          super(DataFreq, self).__init__(
              axes=axes,
              FTparameters=FTparameters,
              values=values,
              is_real=is_real,
              symbol=symbol,
              name=name,
              unit=unit,
              normalizations=normalizations,
          )
          # The class is frozen (in DataND init), for now it's impossible to
          # add new properties
  
      def __str__(self):
          """Convert this object in a readeable string (for print)"""
  
          DataFreq_str = ""
          # Get the properties inherited from DataND
          DataFreq_str += super(DataFreq, self).__str__()
          return DataFreq_str
  
      def __eq__(self, other):
          """Compare two objects (skip parent)"""
  
          if type(other) != type(self):
              return False
  
          # Check the properties inherited from DataND
          if not super(DataFreq, self).__eq__(other):
              return False
          return True
  
      def compare(self, other, name="self"):
          """Compare two objects and return list of differences"""
  
          if type(other) != type(self):
              return ["type(" + name + ")"]
          diff_list = list()
  
          # Check the properties inherited from DataND
          diff_list.extend(super(DataFreq, self).compare(other, name=name))
          return diff_list
  
      def __sizeof__(self):
          """Return the size in memory of the object (including all subobject)"""
  
          S = 0  # Full size of the object
  
          # Get size of the properties inherited from DataND
          S += super(DataFreq, self).__sizeof__()
          return S
  
      def as_dict(self, **kwargs):
          """
          Convert this object in a json serializable dict (can be use in __init__).
          Optional keyword input parameter is for internal use only
          and may prevent json serializability.
          """
  
          # Get the properties inherited from DataND
          DataFreq_dict = super(DataFreq, self).as_dict(**kwargs)
          # The class name is added to the dict for deserialisation purpose
          # Overwrite the mother class name
          DataFreq_dict["__class__"] = "DataFreq"
          return DataFreq_dict
  
      def _set_None(self):
          """Set all the properties to None (except SciDataTool object)"""
  
          # Set to None the properties inherited from DataND
          super(DataFreq, self)._set_None()
  