# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Optimization/OptiProblem.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/OptiProblem
"""
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 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 OptiProblem(FrozenClass):
"""Multi-objectives optimization problem with some constraints"""
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,
simu=-1,
design_var=-1,
obj_func=-1,
eval_func=None,
constraint=-1,
preprocessing=None,
datakeeper_list=-1,
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 "simu" in list(init_dict.keys()):
simu = init_dict["simu"]
if "design_var" in list(init_dict.keys()):
design_var = init_dict["design_var"]
if "obj_func" in list(init_dict.keys()):
obj_func = init_dict["obj_func"]
if "eval_func" in list(init_dict.keys()):
eval_func = init_dict["eval_func"]
if "constraint" in list(init_dict.keys()):
constraint = init_dict["constraint"]
if "preprocessing" in list(init_dict.keys()):
preprocessing = init_dict["preprocessing"]
if "datakeeper_list" in list(init_dict.keys()):
datakeeper_list = init_dict["datakeeper_list"]
# Set the properties (value check and convertion are done in setter)
self.parent = None
self.simu = simu
self.design_var = design_var
self.obj_func = obj_func
self.eval_func = eval_func
self.constraint = constraint
self.preprocessing = preprocessing
self.datakeeper_list = datakeeper_list
# 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)"""
OptiProblem_str = ""
if self.parent is None:
OptiProblem_str += "parent = None " + linesep
else:
OptiProblem_str += (
"parent = " + str(type(self.parent)) + " object" + linesep
)
if self.simu is not None:
tmp = self.simu.__str__().replace(linesep, linesep + "\t").rstrip("\t")
OptiProblem_str += "simu = " + tmp
else:
OptiProblem_str += "simu = None" + linesep + linesep
if len(self.design_var) == 0:
OptiProblem_str += "design_var = []" + linesep
for ii in range(len(self.design_var)):
tmp = (
self.design_var[ii].__str__().replace(linesep, linesep + "\t") + linesep
)
OptiProblem_str += "design_var[" + str(ii) + "] =" + tmp + linesep + linesep
if len(self.obj_func) == 0:
OptiProblem_str += "obj_func = []" + linesep
for ii in range(len(self.obj_func)):
tmp = self.obj_func[ii].__str__().replace(linesep, linesep + "\t") + linesep
OptiProblem_str += "obj_func[" + str(ii) + "] =" + tmp + linesep + linesep
if self._eval_func_str is not None:
OptiProblem_str += "eval_func = " + self._eval_func_str + linesep
elif self._eval_func_func is not None:
OptiProblem_str += "eval_func = " + str(self._eval_func_func) + linesep
else:
OptiProblem_str += "eval_func = None" + linesep + linesep
if len(self.constraint) == 0:
OptiProblem_str += "constraint = []" + linesep
for ii in range(len(self.constraint)):
tmp = (
self.constraint[ii].__str__().replace(linesep, linesep + "\t") + linesep
)
OptiProblem_str += "constraint[" + str(ii) + "] =" + tmp + linesep + linesep
if self._preprocessing_str is not None:
OptiProblem_str += "preprocessing = " + self._preprocessing_str + linesep
elif self._preprocessing_func is not None:
OptiProblem_str += (
"preprocessing = " + str(self._preprocessing_func) + linesep
)
else:
OptiProblem_str += "preprocessing = None" + linesep + linesep
if len(self.datakeeper_list) == 0:
OptiProblem_str += "datakeeper_list = []" + linesep
for ii in range(len(self.datakeeper_list)):
tmp = (
self.datakeeper_list[ii].__str__().replace(linesep, linesep + "\t")
+ linesep
)
OptiProblem_str += (
"datakeeper_list[" + str(ii) + "] =" + tmp + linesep + linesep
)
return OptiProblem_str
def __eq__(self, other):
"""Compare two objects (skip parent)"""
if type(other) != type(self):
return False
if other.simu != self.simu:
return False
if other.design_var != self.design_var:
return False
if other.obj_func != self.obj_func:
return False
if other._eval_func_str != self._eval_func_str:
return False
if other.constraint != self.constraint:
return False
if other._preprocessing_str != self._preprocessing_str:
return False
if other.datakeeper_list != self.datakeeper_list:
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.simu is None and self.simu is not None) or (
other.simu is not None and self.simu is None
):
diff_list.append(name + ".simu None mismatch")
elif self.simu is not None:
diff_list.extend(
self.simu.compare(
other.simu,
name=name + ".simu",
ignore_list=ignore_list,
is_add_value=is_add_value,
)
)
if (other.design_var is None and self.design_var is not None) or (
other.design_var is not None and self.design_var is None
):
diff_list.append(name + ".design_var None mismatch")
elif self.design_var is None:
pass
elif len(other.design_var) != len(self.design_var):
diff_list.append("len(" + name + ".design_var)")
else:
for ii in range(len(other.design_var)):
diff_list.extend(
self.design_var[ii].compare(
other.design_var[ii],
name=name + ".design_var[" + str(ii) + "]",
ignore_list=ignore_list,
is_add_value=is_add_value,
)
)
if (other.obj_func is None and self.obj_func is not None) or (
other.obj_func is not None and self.obj_func is None
):
diff_list.append(name + ".obj_func None mismatch")
elif self.obj_func is None:
pass
elif len(other.obj_func) != len(self.obj_func):
diff_list.append("len(" + name + ".obj_func)")
else:
for ii in range(len(other.obj_func)):
diff_list.extend(
self.obj_func[ii].compare(
other.obj_func[ii],
name=name + ".obj_func[" + str(ii) + "]",
ignore_list=ignore_list,
is_add_value=is_add_value,
)
)
if other._eval_func_str != self._eval_func_str:
diff_list.append(name + ".eval_func")
if (other.constraint is None and self.constraint is not None) or (
other.constraint is not None and self.constraint is None
):
diff_list.append(name + ".constraint None mismatch")
elif self.constraint is None:
pass
elif len(other.constraint) != len(self.constraint):
diff_list.append("len(" + name + ".constraint)")
else:
for ii in range(len(other.constraint)):
diff_list.extend(
self.constraint[ii].compare(
other.constraint[ii],
name=name + ".constraint[" + str(ii) + "]",
ignore_list=ignore_list,
is_add_value=is_add_value,
)
)
if other._preprocessing_str != self._preprocessing_str:
diff_list.append(name + ".preprocessing")
if (other.datakeeper_list is None and self.datakeeper_list is not None) or (
other.datakeeper_list is not None and self.datakeeper_list is None
):
diff_list.append(name + ".datakeeper_list None mismatch")
elif self.datakeeper_list is None:
pass
elif len(other.datakeeper_list) != len(self.datakeeper_list):
diff_list.append("len(" + name + ".datakeeper_list)")
else:
for ii in range(len(other.datakeeper_list)):
diff_list.extend(
self.datakeeper_list[ii].compare(
other.datakeeper_list[ii],
name=name + ".datakeeper_list[" + str(ii) + "]",
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
S += getsizeof(self.simu)
if self.design_var is not None:
for value in self.design_var:
S += getsizeof(value)
if self.obj_func is not None:
for value in self.obj_func:
S += getsizeof(value)
S += getsizeof(self._eval_func_str)
if self.constraint is not None:
for value in self.constraint:
S += getsizeof(value)
S += getsizeof(self._preprocessing_str)
if self.datakeeper_list is not None:
for value in self.datakeeper_list:
S += getsizeof(value)
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.
"""
OptiProblem_dict = dict()
if self.simu is None:
OptiProblem_dict["simu"] = None
else:
OptiProblem_dict["simu"] = self.simu.as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
if self.design_var is None:
OptiProblem_dict["design_var"] = None
else:
OptiProblem_dict["design_var"] = list()
for obj in self.design_var:
if obj is not None:
OptiProblem_dict["design_var"].append(
obj.as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
)
else:
OptiProblem_dict["design_var"].append(None)
if self.obj_func is None:
OptiProblem_dict["obj_func"] = None
else:
OptiProblem_dict["obj_func"] = list()
for obj in self.obj_func:
if obj is not None:
OptiProblem_dict["obj_func"].append(
obj.as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
)
else:
OptiProblem_dict["obj_func"].append(None)
if self._eval_func_str is not None:
OptiProblem_dict["eval_func"] = self._eval_func_str
elif keep_function:
OptiProblem_dict["eval_func"] = self.eval_func
else:
OptiProblem_dict["eval_func"] = None
if self.eval_func is not None:
self.get_logger().warning(
"OptiProblem.as_dict(): "
+ f"Function {self.eval_func.__name__} is not serializable "
+ "and will be converted to None."
)
if self.constraint is None:
OptiProblem_dict["constraint"] = None
else:
OptiProblem_dict["constraint"] = list()
for obj in self.constraint:
if obj is not None:
OptiProblem_dict["constraint"].append(
obj.as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
)
else:
OptiProblem_dict["constraint"].append(None)
if self._preprocessing_str is not None:
OptiProblem_dict["preprocessing"] = self._preprocessing_str
elif keep_function:
OptiProblem_dict["preprocessing"] = self.preprocessing
else:
OptiProblem_dict["preprocessing"] = None
if self.preprocessing is not None:
self.get_logger().warning(
"OptiProblem.as_dict(): "
+ f"Function {self.preprocessing.__name__} is not serializable "
+ "and will be converted to None."
)
if self.datakeeper_list is None:
OptiProblem_dict["datakeeper_list"] = None
else:
OptiProblem_dict["datakeeper_list"] = list()
for obj in self.datakeeper_list:
if obj is not None:
OptiProblem_dict["datakeeper_list"].append(
obj.as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
)
else:
OptiProblem_dict["datakeeper_list"].append(None)
# The class name is added to the dict for deserialisation purpose
OptiProblem_dict["__class__"] = "OptiProblem"
return OptiProblem_dict
[docs] def copy(self):
"""Creates a deepcopy of the object"""
# Handle deepcopy of all the properties
if self.simu is None:
simu_val = None
else:
simu_val = self.simu.copy()
if self.design_var is None:
design_var_val = None
else:
design_var_val = list()
for obj in self.design_var:
design_var_val.append(obj.copy())
if self.obj_func is None:
obj_func_val = None
else:
obj_func_val = list()
for obj in self.obj_func:
obj_func_val.append(obj.copy())
if self._eval_func_str is not None:
eval_func_val = self._eval_func_str
else:
eval_func_val = self._eval_func_func
if self.constraint is None:
constraint_val = None
else:
constraint_val = list()
for obj in self.constraint:
constraint_val.append(obj.copy())
if self._preprocessing_str is not None:
preprocessing_val = self._preprocessing_str
else:
preprocessing_val = self._preprocessing_func
if self.datakeeper_list is None:
datakeeper_list_val = None
else:
datakeeper_list_val = list()
for obj in self.datakeeper_list:
datakeeper_list_val.append(obj.copy())
# Creates new object of the same type with the copied properties
obj_copy = type(self)(
simu=simu_val,
design_var=design_var_val,
obj_func=obj_func_val,
eval_func=eval_func_val,
constraint=constraint_val,
preprocessing=preprocessing_val,
datakeeper_list=datakeeper_list_val,
)
return obj_copy
def _set_None(self):
"""Set all the properties to None (except pyleecan object)"""
if self.simu is not None:
self.simu._set_None()
self.design_var = None
self.obj_func = None
self.eval_func = None
self.constraint = None
self.preprocessing = None
self.datakeeper_list = None
def _get_simu(self):
"""getter of simu"""
return self._simu
def _set_simu(self, value):
"""setter of simu"""
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__"), "simu")
value = class_obj(init_dict=value)
elif type(value) is int and value == -1: # Default constructor
Simulation = import_class("pyleecan.Classes", "Simulation", "simu")
value = Simulation()
check_var("simu", value, "Simulation")
self._simu = value
if self._simu is not None:
self._simu.parent = self
simu = property(
fget=_get_simu,
fset=_set_simu,
doc="""Default simulation
:Type: Simulation
""",
)
def _get_design_var(self):
"""getter of design_var"""
if self._design_var is not None:
for obj in self._design_var:
if obj is not None:
obj.parent = self
return self._design_var
def _set_design_var(self, value):
"""setter of design_var"""
if type(value) is list:
for ii, obj in enumerate(value):
if isinstance(obj, str): # Load from file
try:
obj = load_init_dict(obj)[1]
except Exception as e:
self.get_logger().error(
"Error while loading " + obj + ", setting None instead"
)
obj = None
value[ii] = None
if type(obj) is dict:
class_obj = import_class(
"pyleecan.Classes", obj.get("__class__"), "design_var"
)
value[ii] = class_obj(init_dict=obj)
if value[ii] is not None:
value[ii].parent = self
if value == -1:
value = list()
check_var("design_var", value, "[OptiDesignVar]")
self._design_var = value
design_var = property(
fget=_get_design_var,
fset=_set_design_var,
doc="""List of design variables
:Type: [OptiDesignVar]
""",
)
def _get_obj_func(self):
"""getter of obj_func"""
if self._obj_func is not None:
for obj in self._obj_func:
if obj is not None:
obj.parent = self
return self._obj_func
def _set_obj_func(self, value):
"""setter of obj_func"""
if type(value) is list:
for ii, obj in enumerate(value):
if isinstance(obj, str): # Load from file
try:
obj = load_init_dict(obj)[1]
except Exception as e:
self.get_logger().error(
"Error while loading " + obj + ", setting None instead"
)
obj = None
value[ii] = None
if type(obj) is dict:
class_obj = import_class(
"pyleecan.Classes", obj.get("__class__"), "obj_func"
)
value[ii] = class_obj(init_dict=obj)
if value[ii] is not None:
value[ii].parent = self
if value == -1:
value = list()
check_var("obj_func", value, "[OptiObjective]")
self._obj_func = value
obj_func = property(
fget=_get_obj_func,
fset=_set_obj_func,
doc="""List of objective functions
:Type: [OptiObjective]
""",
)
def _get_eval_func(self):
"""getter of eval_func"""
return self._eval_func_func
def _set_eval_func(self, value):
"""setter of eval_func"""
if value is None:
self._eval_func_str = None
self._eval_func_func = None
elif isinstance(value, str) and "lambda" in value:
self._eval_func_str = value
self._eval_func_func = eval(value)
elif isinstance(value, str) and isfile(value) and value[-3:] == ".py":
self._eval_func_str = value
f = open(value, "r")
exec(f.read(), globals())
self._eval_func_func = eval(basename(value[:-3]))
elif callable(value):
self._eval_func_str = None
self._eval_func_func = value
else:
raise CheckTypeError(
"For property eval_func Expected function or str (path to python file or lambda), got: "
+ str(type(value))
)
eval_func = property(
fget=_get_eval_func,
fset=_set_eval_func,
doc="""Function to evaluate before computing obj function and constraints
:Type: function
""",
)
def _get_constraint(self):
"""getter of constraint"""
if self._constraint is not None:
for obj in self._constraint:
if obj is not None:
obj.parent = self
return self._constraint
def _set_constraint(self, value):
"""setter of constraint"""
if type(value) is list:
for ii, obj in enumerate(value):
if isinstance(obj, str): # Load from file
try:
obj = load_init_dict(obj)[1]
except Exception as e:
self.get_logger().error(
"Error while loading " + obj + ", setting None instead"
)
obj = None
value[ii] = None
if type(obj) is dict:
class_obj = import_class(
"pyleecan.Classes", obj.get("__class__"), "constraint"
)
value[ii] = class_obj(init_dict=obj)
if value[ii] is not None:
value[ii].parent = self
if value == -1:
value = list()
check_var("constraint", value, "[OptiConstraint]")
self._constraint = value
constraint = property(
fget=_get_constraint,
fset=_set_constraint,
doc="""List containing the constraints
:Type: [OptiConstraint]
""",
)
def _get_preprocessing(self):
"""getter of preprocessing"""
return self._preprocessing_func
def _set_preprocessing(self, value):
"""setter of preprocessing"""
if value is None:
self._preprocessing_str = None
self._preprocessing_func = None
elif isinstance(value, str) and "lambda" in value:
self._preprocessing_str = value
self._preprocessing_func = eval(value)
elif isinstance(value, str) and isfile(value) and value[-3:] == ".py":
self._preprocessing_str = value
f = open(value, "r")
exec(f.read(), globals())
self._preprocessing_func = eval(basename(value[:-3]))
elif callable(value):
self._preprocessing_str = None
self._preprocessing_func = value
else:
raise CheckTypeError(
"For property preprocessing Expected function or str (path to python file or lambda), got: "
+ str(type(value))
)
preprocessing = property(
fget=_get_preprocessing,
fset=_set_preprocessing,
doc="""Function to execute a preprocessing on the simulation right before it is run.
:Type: function
""",
)
def _get_datakeeper_list(self):
"""getter of datakeeper_list"""
if self._datakeeper_list is not None:
for obj in self._datakeeper_list:
if obj is not None:
obj.parent = self
return self._datakeeper_list
def _set_datakeeper_list(self, value):
"""setter of datakeeper_list"""
if type(value) is list:
for ii, obj in enumerate(value):
if isinstance(obj, str): # Load from file
try:
obj = load_init_dict(obj)[1]
except Exception as e:
self.get_logger().error(
"Error while loading " + obj + ", setting None instead"
)
obj = None
value[ii] = None
if type(obj) is dict:
class_obj = import_class(
"pyleecan.Classes", obj.get("__class__"), "datakeeper_list"
)
value[ii] = class_obj(init_dict=obj)
if value[ii] is not None:
value[ii].parent = self
if value == -1:
value = list()
check_var("datakeeper_list", value, "[DataKeeper]")
self._datakeeper_list = value
datakeeper_list = property(
fget=_get_datakeeper_list,
fset=_set_datakeeper_list,
doc="""List of DataKeepers to run on every output
:Type: [DataKeeper]
""",
)
