# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Optimization/OptiDesignVarInterval.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Optimization/OptiDesignVarInterval
"""
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 ..Functions.save 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 OptiDesignVarInterval(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(OptiDesignVarInterval, 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)"""
OptiDesignVarInterval_str = ""
# Get the properties inherited from OptiDesignVar
OptiDesignVarInterval_str += super(OptiDesignVarInterval, self).__str__()
return OptiDesignVarInterval_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(OptiDesignVarInterval, 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(OptiDesignVarInterval, 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(OptiDesignVarInterval, 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
OptiDesignVarInterval_dict = super(OptiDesignVarInterval, 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
OptiDesignVarInterval_dict["__class__"] = "OptiDesignVarInterval"
return OptiDesignVarInterval_dict
[docs] def copy(self):
"""Creates a deepcopy of the object"""
# Handle deepcopy of all the properties
if self.space is None:
space_val = None
else:
space_val = self.space.copy()
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 = self.name
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(OptiDesignVarInterval, self)._set_None()
