pyleecan.Classes.OutLossModel module

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

class OutLossModel(name='', loss_density=None, coeff_dict=None, group=None, loss_model=None, scalar_value=None, init_dict=None, init_str=None)[source]

Bases: FrozenClass

Gather the loss module outputs

VERSION = 1
get_mesh_solution()

Returns the MeshSolution object corresponding to the losses

Parameters:

self (OutLossModel) – Result of a Loss model computation

Returns:

MS – Losses as fct(freq) on the machine mesh

Return type:

MeshSolution

get_loss_scalar(felec=None)

Get loss power from coefficients stored in coeff_dict

Parameters:

  • self (OutLossModel) – an OutLossModel object

  • felec (float) – the electrical frequency [Hz]

Returns:

Ploss – loss power for the specified frequency [W]

Return type:

float

plot_mesh(group_names=None)

Plot the losses on the mesh solution

Parameters:

  • self (OutLossModel) – An OutLossModel object

  • group_names (list) – a list of str corresponding to group name(s)

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 name

Name of the loss

Type:

str

property loss_density

Loss density

Type:

ndarray

property coeff_dict

dict of coefficients to compute the scalar value with respcet to frequency

Type:

dict

property group

group to which the loss applies

Type:

str

property loss_model

The name of the loss model used to compute the loss stored in this output

Type:

str

property scalar_value

To store the value of get_loss_scalar (for scalar losses or with coeff_dict cleaned)

Type:

float