pyleecan.Classes.VarLoadCurrent module

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

class VarLoadCurrent(OP_matrix=None, name='', desc='', datakeeper_list=- 1, is_keep_all_output=False, stop_if_error=False, var_simu=None, nb_simu=0, is_reuse_femm_file=True, postproc_list=- 1, pre_keeper_postproc_list=None, post_keeper_postproc_list=None, is_reuse_LUT=True, init_dict=None, init_str=None)

Bases: VarLoad

Generate a multisimulation with InputCurrent at variable operating point

VERSION = 1

generate_simulation_list(ref_simu=None)

Generate all the simulation for the multi-simulation

Parameters:

• self (VarLoadCurrent) – A VarLoadCurrent object

• ref_simu (Simulation) – Reference simulation to copy / update

Returns:

multisim_dict – dictionary containing the simulation and paramexplorer list

Return type:

dict

get_elec_datakeeper(symbol_list, is_multi=False)

Generate DataKeepers to store by default results from electric module :param self: A VarLoadCurrent object :type self: VarLoadCurrent :param symbol_list: List of the existing datakeeper (to avoid duplicate) :type symbol_list: list :param is_multi: True for multi-simulation of multi-simulation :type is_multi: bool

Returns:

dk_list – list of DataKeeper

Return type:

list

get_input_list()

Return a list of InputCurrent to set the Operating point

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)

Compare two objects and return list of differences

as_dict(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_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()

Creates a deepcopy of the object