Source code for pyleecan.Classes.OptiObjective

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Optimization/OptiObjective.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at

from os import linesep
from sys import getsizeof
from logging import getLogger
from ._check import check_var, raise_
from ..Functions.get_logger import get_logger
from import save
from ..Functions.load import load_init_dict
from ..Functions.Load.import_class import import_class
from copy import deepcopy
from .DataKeeper import DataKeeper

from numpy import array, ndarray
from ntpath import basename
from os.path import isfile
from ._check import CheckTypeError
import numpy as np
import random
from numpy import isnan
from ._check import InitUnKnowClassError

[docs]class OptiObjective(DataKeeper): """Class to distinguish normal DataKeeper from optimization objectives """ VERSION = 1 # generic save method is available in all object save = save # get_logger method is available in all object get_logger = get_logger def __init__( self, name="", symbol="", unit="", keeper=None, error_keeper=None, result=-1, result_ref=None, physic=None, 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 pyleecan type, -1 will call the default constructor - __init__ (init_dict = d) d must be a dictionary 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 pyleecan 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 "name" in list(init_dict.keys()): name = init_dict["name"] if "symbol" in list(init_dict.keys()): symbol = init_dict["symbol"] if "unit" in list(init_dict.keys()): unit = init_dict["unit"] if "keeper" in list(init_dict.keys()): keeper = init_dict["keeper"] if "error_keeper" in list(init_dict.keys()): error_keeper = init_dict["error_keeper"] if "result" in list(init_dict.keys()): result = init_dict["result"] if "result_ref" in list(init_dict.keys()): result_ref = init_dict["result_ref"] if "physic" in list(init_dict.keys()): physic = init_dict["physic"] # Set the properties (value check and convertion are done in setter) # Call DataKeeper init super(OptiObjective, self).__init__( name=name, symbol=symbol, unit=unit, keeper=keeper, error_keeper=error_keeper, result=result, result_ref=result_ref, physic=physic, ) # The class is frozen (in DataKeeper init), for now it's impossible to # add new properties def __str__(self): """Convert this object in a readeable string (for print)""" OptiObjective_str = "" # Get the properties inherited from DataKeeper OptiObjective_str += super(OptiObjective, self).__str__() return OptiObjective_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False # Check the properties inherited from DataKeeper if not super(OptiObjective, self).__eq__(other): return False return True
[docs] def compare(self, other, name="self", ignore_list=None, is_add_value=False): """Compare two objects and return list of differences""" if ignore_list is None: ignore_list = list() if type(other) != type(self): return ["type(" + name + ")"] diff_list = list() # Check the properties inherited from DataKeeper diff_list.extend( super(OptiObjective, self).compare( other, name=name, ignore_list=ignore_list, is_add_value=is_add_value ) ) # Filter ignore differences diff_list = list(filter(lambda x: x not in ignore_list, diff_list)) 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 DataKeeper S += super(OptiObjective, self).__sizeof__() return S
[docs] def as_dict(self, type_handle_ndarray=0, keep_function=False, **kwargs): """ Convert this object in a json serializable dict (can be use in __init__). type_handle_ndarray: int How to handle ndarray (0: tolist, 1: copy, 2: nothing) keep_function : bool True to keep the function object, else return str Optional keyword input parameter is for internal use only and may prevent json serializability. """ # Get the properties inherited from DataKeeper OptiObjective_dict = super(OptiObjective, self).as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) # The class name is added to the dict for deserialisation purpose # Overwrite the mother class name OptiObjective_dict["__class__"] = "OptiObjective" return OptiObjective_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties name_val = symbol_val = self.symbol unit_val = self.unit if self._keeper_str is not None: keeper_val = self._keeper_str else: keeper_val = self._keeper_func if self._error_keeper_str is not None: error_keeper_val = self._error_keeper_str else: error_keeper_val = self._error_keeper_func if self.result is None: result_val = None else: result_val = self.result.copy() if hasattr(self.result_ref, "copy"): result_ref_val = self.result_ref.copy() else: result_ref_val = self.result_ref physic_val = self.physic # Creates new object of the same type with the copied properties obj_copy = type(self)( name=name_val, symbol=symbol_val, unit=unit_val, keeper=keeper_val, error_keeper=error_keeper_val, result=result_val, result_ref=result_ref_val, physic=physic_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" # Set to None the properties inherited from DataKeeper super(OptiObjective, self)._set_None()