Source code for pyleecan.Classes.OptiDesignVarSet

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Optimization/OptiDesignVarSet.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 .OptiDesignVar import OptiDesignVar

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 OptiDesignVarSet(OptiDesignVar): """Optimization""" 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, space=[0, 1], get_value=None, name="", symbol="", unit="", setter=None, getter=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 "space" in list(init_dict.keys()): space = init_dict["space"] if "get_value" in list(init_dict.keys()): get_value = init_dict["get_value"] 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 "setter" in list(init_dict.keys()): setter = init_dict["setter"] if "getter" in list(init_dict.keys()): getter = init_dict["getter"] # Set the properties (value check and convertion are done in setter) # Call OptiDesignVar init super(OptiDesignVarSet, self).__init__( space=space, get_value=get_value, name=name, symbol=symbol, unit=unit, setter=setter, getter=getter, ) # The class is frozen (in OptiDesignVar init), for now it's impossible to # add new properties def __str__(self): """Convert this object in a readeable string (for print)""" OptiDesignVarSet_str = "" # Get the properties inherited from OptiDesignVar OptiDesignVarSet_str += super(OptiDesignVarSet, self).__str__() return OptiDesignVarSet_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False # Check the properties inherited from OptiDesignVar if not super(OptiDesignVarSet, 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 OptiDesignVar diff_list.extend( super(OptiDesignVarSet, 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 OptiDesignVar S += super(OptiDesignVarSet, 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 OptiDesignVar OptiDesignVarSet_dict = super(OptiDesignVarSet, 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 OptiDesignVarSet_dict["__class__"] = "OptiDesignVarSet" return OptiDesignVarSet_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties if is None: space_val = None else: space_val = if self._get_value_str is not None: get_value_val = self._get_value_str else: get_value_val = self._get_value_func name_val = symbol_val = self.symbol unit_val = self.unit if self._setter_str is not None: setter_val = self._setter_str else: setter_val = self._setter_func if self._getter_str is not None: getter_val = self._getter_str else: getter_val = self._getter_func # Creates new object of the same type with the copied properties obj_copy = type(self)( space=space_val, get_value=get_value_val, name=name_val, symbol=symbol_val, unit=unit_val, setter=setter_val, getter=getter_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" # Set to None the properties inherited from OptiDesignVar super(OptiDesignVarSet, self)._set_None()