pyleecan.Classes.EEC_LSRPM module¶
Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Simulation/EEC_LSRPM
- class EEC_LSRPM(type_skin_effect=1, OP=None, Tsta=20, Trot=20, Xkr_skinS=1, Xke_skinS=1, Xkr_skinR=1, Xke_skinR=1, R1=None, fluxlink=None, init_dict=None, init_str=None)[source]¶
Bases:
EEC
Electrical Equivalent Circuit for LSRPM
- VERSION = 1¶
- comp_parameters(output, Tsta=None, Trot=None)¶
Compute the parameters dict for the equivalent electrical circuit: resistance, inductance and back electromotive force :param self: an EEC_LSRPM object :type self: EEC_LSRPM :param output: an Output object :type output: Output
- solve(b, sym_pos=False, lower=False, overwrite_a=False, overwrite_b=False, check_finite=True, assume_a='gen', transposed=False)¶
Solves the linear equation set
a * x = b
for the unknownx
for squarea
matrix.If the data matrix is known to be a particular type then supplying the corresponding string to
assume_a
key chooses the dedicated solver. The available options aregeneric matrix
‘gen’
symmetric
‘sym’
hermitian
‘her’
positive definite
‘pos’
If omitted,
'gen'
is the default structure.The datatype of the arrays define which solver is called regardless of the values. In other words, even when the complex array entries have precisely zero imaginary parts, the complex solver will be called based on the data type of the array.
- Parameters:
a ((N, N) array_like) – Square input data
b ((N, NRHS) array_like) – Input data for the right hand side.
sym_pos (bool, optional, deprecated) –
Assume a is symmetric and positive definite.
Deprecated since version 0.19.0: This keyword is deprecated and should be replaced by using
assume_a = 'pos'
. sym_pos will be removed in SciPy 1.11.0.lower (bool, optional) – If True, only the data contained in the lower triangle of a. Default is to use upper triangle. (ignored for
'gen'
)overwrite_a (bool, optional) – Allow overwriting data in a (may enhance performance). Default is False.
overwrite_b (bool, optional) – Allow overwriting data in b (may enhance performance). Default is False.
check_finite (bool, optional) – Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.
assume_a (str, optional) – Valid entries are explained above.
transposed (bool, optional) – If True,
a^T x = b
for real matrices, raises NotImplementedError for complex matrices (only for True).
- Returns:
x – The solution array.
- Return type:
(N, NRHS) ndarray
- Raises:
ValueError – If size mismatches detected or input a is not square.
LinAlgError – If the matrix is singular.
LinAlgWarning – If an ill-conditioned input a is detected.
NotImplementedError – If transposed is True and input a is a complex matrix.
Examples
Given a and b, solve for x:
>>> a = np.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]]) >>> b = np.array([2, 4, -1]) >>> from scipy import linalg >>> x = linalg.solve(a, b) >>> x array([ 2., -2., 9.]) >>> np.dot(a, x) == b array([ True, True, True], dtype=bool)
Notes
If the input b matrix is a 1-D array with N elements, when supplied together with an NxN input a, it is assumed as a valid column vector despite the apparent size mismatch. This is compatible with the numpy.dot() behavior and the returned result is still 1-D array.
The generic, symmetric, Hermitian and positive definite solutions are obtained via calling ?GESV, ?SYSV, ?HESV, and ?POSV routines of LAPACK respectively.
- comp_joule_losses(output)¶
Compute the electrical Joule losses
- Parameters:
self (Electrical) – an Electrical object
output (Output) – an Output object
- 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.