Source code for pyleecan.Classes.PostFunction
# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Post/PostFunction.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Post/PostFunction
"""
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 .Post import Post
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 PostFunction(Post):
"""Post-processing from a user-defined function"""
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, run=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 "run" in list(init_dict.keys()):
run = init_dict["run"]
# Set the properties (value check and convertion are done in setter)
self.run = run
# Call Post init
super(PostFunction, self).__init__()
# The class is frozen (in Post init), for now it's impossible to
# add new properties
def __str__(self):
"""Convert this object in a readeable string (for print)"""
PostFunction_str = ""
# Get the properties inherited from Post
PostFunction_str += super(PostFunction, self).__str__()
if self._run_str is not None:
PostFunction_str += "run = " + self._run_str + linesep
elif self._run_func is not None:
PostFunction_str += "run = " + str(self._run_func) + linesep
else:
PostFunction_str += "run = None" + linesep + linesep
return PostFunction_str
def __eq__(self, other):
"""Compare two objects (skip parent)"""
if type(other) != type(self):
return False
# Check the properties inherited from Post
if not super(PostFunction, self).__eq__(other):
return False
if other._run_str != self._run_str:
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 Post
diff_list.extend(
super(PostFunction, self).compare(
other, name=name, ignore_list=ignore_list, is_add_value=is_add_value
)
)
if other._run_str != self._run_str:
diff_list.append(name + ".run")
# 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 Post
S += super(PostFunction, self).__sizeof__()
S += getsizeof(self._run_str)
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 Post
PostFunction_dict = super(PostFunction, self).as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs,
)
if self._run_str is not None:
PostFunction_dict["run"] = self._run_str
elif keep_function:
PostFunction_dict["run"] = self.run
else:
PostFunction_dict["run"] = None
if self.run is not None:
self.get_logger().warning(
"PostFunction.as_dict(): "
+ f"Function {self.run.__name__} is not serializable "
+ "and will be converted to None."
)
# The class name is added to the dict for deserialisation purpose
# Overwrite the mother class name
PostFunction_dict["__class__"] = "PostFunction"
return PostFunction_dict
[docs] def copy(self):
"""Creates a deepcopy of the object"""
# Handle deepcopy of all the properties
if self._run_str is not None:
run_val = self._run_str
else:
run_val = self._run_func
# Creates new object of the same type with the copied properties
obj_copy = type(self)(run=run_val)
return obj_copy
def _set_None(self):
"""Set all the properties to None (except pyleecan object)"""
self.run = None
# Set to None the properties inherited from Post
super(PostFunction, self)._set_None()
def _get_run(self):
"""getter of run"""
return self._run_func
def _set_run(self, value):
"""setter of run"""
if value is None:
self._run_str = None
self._run_func = None
elif isinstance(value, str) and "lambda" in value:
self._run_str = value
self._run_func = eval(value)
elif isinstance(value, str) and isfile(value) and value[-3:] == ".py":
self._run_str = value
f = open(value, "r")
exec(f.read(), globals())
self._run_func = eval(basename(value[:-3]))
elif callable(value):
self._run_str = None
self._run_func = value
else:
raise CheckTypeError(
"For property run Expected function or str (path to python file or lambda), got: "
+ str(type(value))
)
run = property(
fget=_get_run,
fset=_set_run,
doc="""Post-processing that takes an output in argument
:Type: function
""",
)
