pylbo.visualisation.modes.mode_data

Classes

ModeVisualisationData

Class that contains the data used for eigenmode visualisations.

Module Contents

class pylbo.visualisation.modes.mode_data.ModeVisualisationData(ds: pylbo.data_containers.LegolasDataSet, omega: list[complex], ef_name: str = None, use_real_part: bool = True, complex_factor: complex = None, add_background: bool = False)[source]

Class that contains the data used for eigenmode visualisations.

Parameters:

ds (LegolasDataSet) – The dataset containing the eigenfunctions and modes to visualise.
omega (list[complex]) – The (approximate) eigenvalue(s) of the mode(s) to visualise.
ef_name (str) – The name of the eigenfunction to visualise.
use_real_part (bool) – Whether to use the real part of the eigenmode solution.
complex_factor (complex) – A complex factor to multiply the eigenmode solution with.
add_background (bool) – Whether to add the equilibrium background to the eigenmode solution.

ds[source]

The dataset containing the eigenfunctions and modes to visualise.

Type:: LegolasDataSet

omega[source]

The (approximate) eigenvalue(s) of the mode(s) to visualise.

Type:: list[complex]

eigenfunction[source]

The eigenfunction of the mode(s) to visualise.

Type:: list[np.ndarray]

use_real_part[source]

Whether to use the real part of the eigenmode solution.

Type:: bool

complex_factor[source]

The complex factor to multiply the eigenmode solution with.

Type:: complex

add_background[source]

Whether to add the equilibrium background to the eigenmode solution.

Type:: bool

ds[source]

use_real_part[source]

complex_factor[source]

add_background[source]

_print_bg_info = True[source]

_ef_name[source]

_ef_name_latex[source]

_all_efs[source]

omega[source]

eigenfunction[source]

property k2: float[source]: The k2 wave number of the eigenmode solution.

property k3: float[source]: The k3 wave number of the eigenmode solution.

property part_name: str[source]: Returns the name of the part of the eigenmode solution to use, i.e. ‘real’ or ‘imag’.

get_ef_name_latex() → str[source]: Returns the latex representation of the eigenfunction name.

_validate_complex_factor(complex_factor: complex) → complex[source]

Validates the complex factor.

Parameters:: complex_factor (complex) – The complex factor to validate.
Returns:: The complex factor if it is valid, otherwise 1.
Return type:: complex

get_mode_solution(ef: numpy.ndarray, omega: complex, u2: float | numpy.ndarray, u3: float | numpy.ndarray, t: float | numpy.ndarray) → numpy.ndarray[source]

Calculates the full eigenmode solution for given coordinates and time. If a complex factor was given, the eigenmode solution is multiplied with the complex factor. If use_real_part is True the real part of the eigenmode solution is returned, otherwise the complex part.

Parameters:

ef (np.ndarray) – The eigenfunction to use.
omega (complex) – The eigenvalue to use.
u2 (Union[float, np.ndarray]) – The y coordinate(s) of the eigenmode solution.
u3 (Union[float, np.ndarray]) – The z coordinate(s) of the eigenmode solution.
t (Union[float, np.ndarray]) – The time(s) of the eigenmode solution.

Returns:

The real or imaginary part of the eigenmode solution for the given set of coordinate(s) and time(s).

Return type:

np.ndarray

get_background(shape: tuple[int, Ellipsis], name=None) → numpy.ndarray[source]

Returns the background of the eigenmode solution.

Parameters:

shape (tuple[int, ...]) – The shape of the eigenmode solution.
name (str) – The name of the background to use. If None, the background name will be inferred from the eigenfunction name.

Returns:

The background of the eigenmode solution, sampled on the eigenfunction grid and broadcasted to the same shape as the eigenmode solution.

Return type:

np.ndarray

_sample_background_on_ef_grid(bg: numpy.ndarray) → numpy.ndarray[source]

Samples the background array on the eigenfunction grid.

Parameters:: bg (np.ndarray) – The background array with Gaussian grid spacing
Returns:: The background array with eigenfunction grid spacing
Return type:: np.ndarray

_get_background_name() → str[source]

Returns the name of the background.

Returns:: The closest match between the eigenfunction name and the equilibrium name.
Return type:: str
Raises:: ValueError – If the eigenfunction name is a magnetic vector potential component.