Source code for pyleecan.Classes.LossModelSteinmetz

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Simulation/LossModelSteinmetz.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/LossModelSteinmetz
"""

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 .LossModel import LossModel

# Import all class method
# Try/catch to remove unnecessary dependencies in unused method
try:
    from ..Methods.Simulation.LossModelSteinmetz.comp_coeff import comp_coeff
except ImportError as error:
    comp_coeff = error


from numpy import isnan
from ._check import InitUnKnowClassError


[docs]class LossModelSteinmetz(LossModel): """Steinmetz Loss Model Class""" VERSION = 1 # cf Methods.Simulation.LossModelSteinmetz.comp_coeff if isinstance(comp_coeff, ImportError): comp_coeff = property( fget=lambda x: raise_( ImportError( "Can't use LossModelSteinmetz method comp_coeff: " + str(comp_coeff) ) ) ) else: comp_coeff = comp_coeff # 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, k_hy=None, k_ed=None, alpha_f=None, alpha_B=None, name="", is_show_fig=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 "k_hy" in list(init_dict.keys()): k_hy = init_dict["k_hy"] if "k_ed" in list(init_dict.keys()): k_ed = init_dict["k_ed"] if "alpha_f" in list(init_dict.keys()): alpha_f = init_dict["alpha_f"] if "alpha_B" in list(init_dict.keys()): alpha_B = init_dict["alpha_B"] if "name" in list(init_dict.keys()): name = init_dict["name"] if "is_show_fig" in list(init_dict.keys()): is_show_fig = init_dict["is_show_fig"] # Set the properties (value check and convertion are done in setter) self.k_hy = k_hy self.k_ed = k_ed self.alpha_f = alpha_f self.alpha_B = alpha_B # Call LossModel init super(LossModelSteinmetz, self).__init__(name=name, is_show_fig=is_show_fig) # The class is frozen (in LossModel init), for now it's impossible to # add new properties def __str__(self): """Convert this object in a readeable string (for print)""" LossModelSteinmetz_str = "" # Get the properties inherited from LossModel LossModelSteinmetz_str += super(LossModelSteinmetz, self).__str__() LossModelSteinmetz_str += "k_hy = " + str(self.k_hy) + linesep LossModelSteinmetz_str += "k_ed = " + str(self.k_ed) + linesep LossModelSteinmetz_str += "alpha_f = " + str(self.alpha_f) + linesep LossModelSteinmetz_str += "alpha_B = " + str(self.alpha_B) + linesep return LossModelSteinmetz_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False # Check the properties inherited from LossModel if not super(LossModelSteinmetz, self).__eq__(other): return False if other.k_hy != self.k_hy: return False if other.k_ed != self.k_ed: return False if other.alpha_f != self.alpha_f: return False if other.alpha_B != self.alpha_B: 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 LossModel diff_list.extend( super(LossModelSteinmetz, self).compare( other, name=name, ignore_list=ignore_list, is_add_value=is_add_value ) ) if ( other._k_hy is not None and self._k_hy is not None and isnan(other._k_hy) and isnan(self._k_hy) ): pass elif other._k_hy != self._k_hy: if is_add_value: val_str = ( " (self=" + str(self._k_hy) + ", other=" + str(other._k_hy) + ")" ) diff_list.append(name + ".k_hy" + val_str) else: diff_list.append(name + ".k_hy") if ( other._k_ed is not None and self._k_ed is not None and isnan(other._k_ed) and isnan(self._k_ed) ): pass elif other._k_ed != self._k_ed: if is_add_value: val_str = ( " (self=" + str(self._k_ed) + ", other=" + str(other._k_ed) + ")" ) diff_list.append(name + ".k_ed" + val_str) else: diff_list.append(name + ".k_ed") if ( other._alpha_f is not None and self._alpha_f is not None and isnan(other._alpha_f) and isnan(self._alpha_f) ): pass elif other._alpha_f != self._alpha_f: if is_add_value: val_str = ( " (self=" + str(self._alpha_f) + ", other=" + str(other._alpha_f) + ")" ) diff_list.append(name + ".alpha_f" + val_str) else: diff_list.append(name + ".alpha_f") if ( other._alpha_B is not None and self._alpha_B is not None and isnan(other._alpha_B) and isnan(self._alpha_B) ): pass elif other._alpha_B != self._alpha_B: if is_add_value: val_str = ( " (self=" + str(self._alpha_B) + ", other=" + str(other._alpha_B) + ")" ) diff_list.append(name + ".alpha_B" + val_str) else: diff_list.append(name + ".alpha_B") # 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 LossModel S += super(LossModelSteinmetz, self).__sizeof__() S += getsizeof(self.k_hy) S += getsizeof(self.k_ed) S += getsizeof(self.alpha_f) S += getsizeof(self.alpha_B) 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 LossModel LossModelSteinmetz_dict = super(LossModelSteinmetz, self).as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) LossModelSteinmetz_dict["k_hy"] = self.k_hy LossModelSteinmetz_dict["k_ed"] = self.k_ed LossModelSteinmetz_dict["alpha_f"] = self.alpha_f LossModelSteinmetz_dict["alpha_B"] = self.alpha_B # The class name is added to the dict for deserialisation purpose # Overwrite the mother class name LossModelSteinmetz_dict["__class__"] = "LossModelSteinmetz" return LossModelSteinmetz_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties k_hy_val = self.k_hy k_ed_val = self.k_ed alpha_f_val = self.alpha_f alpha_B_val = self.alpha_B name_val = self.name is_show_fig_val = self.is_show_fig # Creates new object of the same type with the copied properties obj_copy = type(self)( k_hy=k_hy_val, k_ed=k_ed_val, alpha_f=alpha_f_val, alpha_B=alpha_B_val, name=name_val, is_show_fig=is_show_fig_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" self.k_hy = None self.k_ed = None self.alpha_f = None self.alpha_B = None # Set to None the properties inherited from LossModel super(LossModelSteinmetz, self)._set_None() def _get_k_hy(self): """getter of k_hy""" return self._k_hy def _set_k_hy(self, value): """setter of k_hy""" check_var("k_hy", value, "float") self._k_hy = value k_hy = property( fget=_get_k_hy, fset=_set_k_hy, doc=u"""Hysteresis loss coefficient :Type: float """, ) def _get_k_ed(self): """getter of k_ed""" return self._k_ed def _set_k_ed(self, value): """setter of k_ed""" check_var("k_ed", value, "float") self._k_ed = value k_ed = property( fget=_get_k_ed, fset=_set_k_ed, doc=u"""Eddy current loss coefficient :Type: float """, ) def _get_alpha_f(self): """getter of alpha_f""" return self._alpha_f def _set_alpha_f(self, value): """setter of alpha_f""" check_var("alpha_f", value, "float") self._alpha_f = value alpha_f = property( fget=_get_alpha_f, fset=_set_alpha_f, doc=u"""Hysteresis loss power coefficient for the frequency :Type: float """, ) def _get_alpha_B(self): """getter of alpha_B""" return self._alpha_B def _set_alpha_B(self, value): """setter of alpha_B""" check_var("alpha_B", value, "float") self._alpha_B = value alpha_B = property( fget=_get_alpha_B, fset=_set_alpha_B, doc=u"""Hysteresis loss power coefficient for the flux density magnitude :Type: float """, )