Source code for pyleecan.Classes.Structural
# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Simulation/Structural.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Simulation/Structural
"""
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
# Import all class method
# Try/catch to remove unnecessary dependencies in unused method
try:
from ..Methods.Simulation.Structural.run import run
except ImportError as error:
run = error
try:
from ..Methods.Simulation.Structural.comp_axes import comp_axes
except ImportError as error:
comp_axes = error
from numpy import isnan
from ._check import InitUnKnowClassError
[docs]class Structural(FrozenClass):
"""Structural module abstract object"""
VERSION = 1
# Check ImportError to remove unnecessary dependencies in unused method
# cf Methods.Simulation.Structural.run
if isinstance(run, ImportError):
run = property(
fget=lambda x: raise_(
ImportError("Can't use Structural method run: " + str(run))
)
)
else:
run = run
# cf Methods.Simulation.Structural.comp_axes
if isinstance(comp_axes, ImportError):
comp_axes = property(
fget=lambda x: raise_(
ImportError("Can't use Structural method comp_axes: " + str(comp_axes))
)
)
else:
comp_axes = comp_axes
# 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, logger_name="Pyleecan.Structural", 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 "logger_name" in list(init_dict.keys()):
logger_name = init_dict["logger_name"]
# Set the properties (value check and convertion are done in setter)
self.parent = None
self.logger_name = logger_name
# 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)"""
Structural_str = ""
if self.parent is None:
Structural_str += "parent = None " + linesep
else:
Structural_str += "parent = " + str(type(self.parent)) + " object" + linesep
Structural_str += 'logger_name = "' + str(self.logger_name) + '"' + linesep
return Structural_str
def __eq__(self, other):
"""Compare two objects (skip parent)"""
if type(other) != type(self):
return False
if other.logger_name != self.logger_name:
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._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")
# 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.logger_name)
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.
"""
Structural_dict = dict()
Structural_dict["logger_name"] = self.logger_name
# The class name is added to the dict for deserialisation purpose
Structural_dict["__class__"] = "Structural"
return Structural_dict
[docs] def copy(self):
"""Creates a deepcopy of the object"""
# Handle deepcopy of all the properties
logger_name_val = self.logger_name
# Creates new object of the same type with the copied properties
obj_copy = type(self)(logger_name=logger_name_val)
return obj_copy
def _set_None(self):
"""Set all the properties to None (except pyleecan object)"""
self.logger_name = None
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
""",
)
