Source code for pyleecan.Classes.OptiSolver

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Optimization/OptiSolver.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 ._frozen import FrozenClass

from numpy import isnan
from ._check import InitUnKnowClassError

[docs]class OptiSolver(FrozenClass): """Optimization solver class""" 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, problem=-1, xoutput=-1, logger_name="Pyleecan.OptiSolver", is_keep_all_output=False, 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 "problem" in list(init_dict.keys()): problem = init_dict["problem"] if "xoutput" in list(init_dict.keys()): xoutput = init_dict["xoutput"] if "logger_name" in list(init_dict.keys()): logger_name = init_dict["logger_name"] if "is_keep_all_output" in list(init_dict.keys()): is_keep_all_output = init_dict["is_keep_all_output"] # Set the properties (value check and convertion are done in setter) self.parent = None self.problem = problem self.xoutput = xoutput self.logger_name = logger_name self.is_keep_all_output = is_keep_all_output # The class is frozen, for now it's impossible to add new properties self._freeze() def __str__(self): """Convert this object in a readeable string (for print)""" OptiSolver_str = "" if self.parent is None: OptiSolver_str += "parent = None " + linesep else: OptiSolver_str += "parent = " + str(type(self.parent)) + " object" + linesep if self.problem is not None: tmp = self.problem.__str__().replace(linesep, linesep + "\t").rstrip("\t") OptiSolver_str += "problem = " + tmp else: OptiSolver_str += "problem = None" + linesep + linesep if self.xoutput is not None: tmp = self.xoutput.__str__().replace(linesep, linesep + "\t").rstrip("\t") OptiSolver_str += "xoutput = " + tmp else: OptiSolver_str += "xoutput = None" + linesep + linesep OptiSolver_str += 'logger_name = "' + str(self.logger_name) + '"' + linesep OptiSolver_str += ( "is_keep_all_output = " + str(self.is_keep_all_output) + linesep ) return OptiSolver_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False if other.problem != self.problem: return False if other.xoutput != self.xoutput: return False if other.logger_name != self.logger_name: return False if other.is_keep_all_output != self.is_keep_all_output: 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() if (other.problem is None and self.problem is not None) or ( other.problem is not None and self.problem is None ): diff_list.append(name + ".problem None mismatch") elif self.problem is not None: diff_list.extend( other.problem, name=name + ".problem", ignore_list=ignore_list, is_add_value=is_add_value, ) ) if (other.xoutput is None and self.xoutput is not None) or ( other.xoutput is not None and self.xoutput is None ): diff_list.append(name + ".xoutput None mismatch") elif self.xoutput is not None: diff_list.extend( other.xoutput, name=name + ".xoutput", ignore_list=ignore_list, is_add_value=is_add_value, ) ) if other._logger_name != self._logger_name: if is_add_value: val_str = ( " (self=" + str(self._logger_name) + ", other=" + str(other._logger_name) + ")" ) diff_list.append(name + ".logger_name" + val_str) else: diff_list.append(name + ".logger_name") if other._is_keep_all_output != self._is_keep_all_output: if is_add_value: val_str = ( " (self=" + str(self._is_keep_all_output) + ", other=" + str(other._is_keep_all_output) + ")" ) diff_list.append(name + ".is_keep_all_output" + val_str) else: diff_list.append(name + ".is_keep_all_output") # 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 S += getsizeof(self.problem) S += getsizeof(self.xoutput) S += getsizeof(self.logger_name) S += getsizeof(self.is_keep_all_output) 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. """ OptiSolver_dict = dict() if self.problem is None: OptiSolver_dict["problem"] = None else: OptiSolver_dict["problem"] = self.problem.as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) if self.xoutput is None: OptiSolver_dict["xoutput"] = None else: OptiSolver_dict["xoutput"] = self.xoutput.as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) OptiSolver_dict["logger_name"] = self.logger_name OptiSolver_dict["is_keep_all_output"] = self.is_keep_all_output # The class name is added to the dict for deserialisation purpose OptiSolver_dict["__class__"] = "OptiSolver" return OptiSolver_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties if self.problem is None: problem_val = None else: problem_val = self.problem.copy() if self.xoutput is None: xoutput_val = None else: xoutput_val = self.xoutput.copy() logger_name_val = self.logger_name is_keep_all_output_val = self.is_keep_all_output # Creates new object of the same type with the copied properties obj_copy = type(self)( problem=problem_val, xoutput=xoutput_val, logger_name=logger_name_val, is_keep_all_output=is_keep_all_output_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" if self.problem is not None: self.problem._set_None() if self.xoutput is not None: self.xoutput._set_None() self.logger_name = None self.is_keep_all_output = None def _get_problem(self): """getter of problem""" return self._problem def _set_problem(self, value): """setter of problem""" if isinstance(value, str): # Load from file try: value = load_init_dict(value)[1] except Exception as e: self.get_logger().error( "Error while loading " + value + ", setting None instead" ) value = None if isinstance(value, dict) and "__class__" in value: class_obj = import_class( "pyleecan.Classes", value.get("__class__"), "problem" ) value = class_obj(init_dict=value) elif type(value) is int and value == -1: # Default constructor OptiProblem = import_class("pyleecan.Classes", "OptiProblem", "problem") value = OptiProblem() check_var("problem", value, "OptiProblem") self._problem = value if self._problem is not None: self._problem.parent = self problem = property( fget=_get_problem, fset=_set_problem, doc=u"""Problem to solve :Type: OptiProblem """, ) def _get_xoutput(self): """getter of xoutput""" return self._xoutput def _set_xoutput(self, value): """setter of xoutput""" if isinstance(value, str): # Load from file try: value = load_init_dict(value)[1] except Exception as e: self.get_logger().error( "Error while loading " + value + ", setting None instead" ) value = None if isinstance(value, dict) and "__class__" in value: class_obj = import_class( "pyleecan.Classes", value.get("__class__"), "xoutput" ) value = class_obj(init_dict=value) elif type(value) is int and value == -1: # Default constructor XOutput = import_class("pyleecan.Classes", "XOutput", "xoutput") value = XOutput() check_var("xoutput", value, "XOutput") self._xoutput = value if self._xoutput is not None: self._xoutput.parent = self xoutput = property( fget=_get_xoutput, fset=_set_xoutput, doc=u"""Optimization results containing every output :Type: XOutput """, ) def _get_logger_name(self): """getter of logger_name""" return self._logger_name def _set_logger_name(self, value): """setter of logger_name""" check_var("logger_name", value, "str") self._logger_name = value logger_name = property( fget=_get_logger_name, fset=_set_logger_name, doc=u"""Name of the logger to use :Type: str """, ) def _get_is_keep_all_output(self): """getter of is_keep_all_output""" return self._is_keep_all_output def _set_is_keep_all_output(self, value): """setter of is_keep_all_output""" check_var("is_keep_all_output", value, "bool") self._is_keep_all_output = value is_keep_all_output = property( fget=_get_is_keep_all_output, fset=_set_is_keep_all_output, doc=u"""Boolean to keep every output :Type: bool """, )