# -*- 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 https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Optimization/OptiSolver
"""
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 ._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(
self.problem.compare(
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(
self.xoutput.compare(
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
""",
)
