Source code for pyleecan.Classes.ImportMatrix
# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Import/ImportMatrix.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Import/ImportMatrix
"""
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 .Import import Import
# Import all class method
# Try/catch to remove unnecessary dependencies in unused method
try:
from ..Methods.Import.ImportMatrix.edit_matrix import edit_matrix
except ImportError as error:
edit_matrix = error
from numpy import isnan
from ._check import InitUnKnowClassError
[docs]class ImportMatrix(Import):
"""Abstract class to Import/Generate 1D or D matrix"""
VERSION = 1
# cf Methods.Import.ImportMatrix.edit_matrix
if isinstance(edit_matrix, ImportError):
edit_matrix = property(
fget=lambda x: raise_(
ImportError(
"Can't use ImportMatrix method edit_matrix: " + str(edit_matrix)
)
)
)
else:
edit_matrix = edit_matrix
# 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, is_transpose=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 "is_transpose" in list(init_dict.keys()):
is_transpose = init_dict["is_transpose"]
# Set the properties (value check and convertion are done in setter)
self.is_transpose = is_transpose
# Call Import init
super(ImportMatrix, self).__init__()
# The class is frozen (in Import init), for now it's impossible to
# add new properties
def __str__(self):
"""Convert this object in a readeable string (for print)"""
ImportMatrix_str = ""
# Get the properties inherited from Import
ImportMatrix_str += super(ImportMatrix, self).__str__()
ImportMatrix_str += "is_transpose = " + str(self.is_transpose) + linesep
return ImportMatrix_str
def __eq__(self, other):
"""Compare two objects (skip parent)"""
if type(other) != type(self):
return False
# Check the properties inherited from Import
if not super(ImportMatrix, self).__eq__(other):
return False
if other.is_transpose != self.is_transpose:
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 Import
diff_list.extend(
super(ImportMatrix, self).compare(
other, name=name, ignore_list=ignore_list, is_add_value=is_add_value
)
)
if other._is_transpose != self._is_transpose:
if is_add_value:
val_str = (
" (self="
+ str(self._is_transpose)
+ ", other="
+ str(other._is_transpose)
+ ")"
)
diff_list.append(name + ".is_transpose" + val_str)
else:
diff_list.append(name + ".is_transpose")
# 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 Import
S += super(ImportMatrix, self).__sizeof__()
S += getsizeof(self.is_transpose)
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 Import
ImportMatrix_dict = super(ImportMatrix, self).as_dict(
type_handle_ndarray=type_handle_ndarray,
keep_function=keep_function,
**kwargs
)
ImportMatrix_dict["is_transpose"] = self.is_transpose
# The class name is added to the dict for deserialisation purpose
# Overwrite the mother class name
ImportMatrix_dict["__class__"] = "ImportMatrix"
return ImportMatrix_dict
[docs] def copy(self):
"""Creates a deepcopy of the object"""
# Handle deepcopy of all the properties
is_transpose_val = self.is_transpose
# Creates new object of the same type with the copied properties
obj_copy = type(self)(is_transpose=is_transpose_val)
return obj_copy
def _set_None(self):
"""Set all the properties to None (except pyleecan object)"""
self.is_transpose = None
# Set to None the properties inherited from Import
super(ImportMatrix, self)._set_None()
def _get_is_transpose(self):
"""getter of is_transpose"""
return self._is_transpose
def _set_is_transpose(self, value):
"""setter of is_transpose"""
check_var("is_transpose", value, "bool")
self._is_transpose = value
is_transpose = property(
fget=_get_is_transpose,
fset=_set_is_transpose,
doc=u"""1 to transpose the Imported/Generated matrix
:Type: bool
""",
)
