pyleecan.Classes.Loss module

Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Loss/Loss

class Loss(logger_name='Pyleecan.Loss', model_dict=None, Tsta=20, Trot=20, is_get_meshsolution=False, init_dict=None, init_str=None)[source]

Bases: FrozenClass

Loss module object that contain the loss models.

VERSION = 1
run()

Run the Loss module

Parameters:

self (Loss) – A Loss model

comp_axes(output)

Compute the axes required in Loss module

Parameters:

  • self (Loss) – a Loss object

  • output (Output) – an Output object (to update)

Returns:

axes_dict – Dict containing Time and Angle axes including (anti-)periodicties used in any Force module

Return type:

{Data}

comp_all_losses(axes_dict=None)

Compute all the losses models set in model_dict

Parameters:

  • self (Loss) – A Loss object

  • axes_dict (dict) – Dict containing axes for loss calculation

save(save_path='', is_folder=False, type_handle_old=2, type_compression=0)

Save the object to the save_path

Parameters:

  • self – A pyleecan object

  • save_path (str) – path to the folder to save the object

  • is_folder (bool) – to split the object in different files: separate simulation machine and materials (json only)

  • type_handle_old (int) – How to handle old file in folder mode (0:Nothing, 1:Delete, 2:Move to “Backup” folder)

  • type_compression (int) – Available only for json, 0: no compression, 1: gzip

get_logger()

Get the object logger or its parent’s one

Parameters:

obj – A pyleecan object

Returns:

logger – Pyleecan object dedicated logger

Return type:

logging.Logger

compare(other, name='self', ignore_list=None, is_add_value=False)[source]

Compare two objects and return list of differences

as_dict(type_handle_ndarray=0, keep_function=False, **kwargs)[source]

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_functionbool

True to keep the function object, else return str

Optional keyword input parameter is for internal use only and may prevent json serializability.

copy()[source]

Creates a deepcopy of the object

property logger_name

Name of the logger to use

Type:

str

property model_dict

Dict of loss model whose key is a lamination and value is the associated loss model (alternative to model_index/model_list)

Type:

{LossModel}

property Tsta

Average stator temperature for Electrical calculation

Type:

float

property Trot

Average rotor temperature for Electrical calculation

Type:

float

property is_get_meshsolution

True to save loss density map as meshsolution

Type:

bool