punchbowl.level3.f_corona_model

Functions

solve_qp_cube(→ numpy.ndarray)	Fast solver for the quadratic programming problem.
model_fcorona_for_cube(→ numpy.ndarray)	Model the F corona given a list of times and a corresponding data cube, .
construct_f_corona_background(→ ndcube.NDCube)	Build f corona background model.
subtract_f_corona_background(→ ndcube.NDCube)	Subtract f corona background.
subtract_f_corona_background_task(→ ndcube.NDCube)	Subtracts a background f corona model from an observation.
create_empty_f_background_model(→ numpy.ndarray)	Create an empty background model.

Module Contents

punchbowl.level3.f_corona_model.solve_qp_cube(input_vals: numpy.ndarray, cube: numpy.ndarray) → numpy.ndarray

Fast solver for the quadratic programming problem.

Parameters:

• input_vals (np.ndarray) – array of times

• cube (np.ndarray) – array of data

Returns:

Array of coefficients for solving polynomial

Return type:

np.ndarray

punchbowl.level3.f_corona_model.model_fcorona_for_cube(xt: numpy.ndarray, cube: numpy.ndarray, smooth_level: float | None = 4) → numpy.ndarray

Model the F corona given a list of times and a corresponding data cube, .

Parameters:

• xt (np.ndarray) – time array

• cube (np.ndarray) – observation array

• smooth_level (float | None) – If None, no smoothing is applied. Otherwise, the top and bottom smooth_level standard deviations of data are rejected.

Return type:

np.ndarray

punchbowl.level3.f_corona_model.construct_f_corona_background(data_list: list[str], layer: int) → ndcube.NDCube

Build f corona background model.

punchbowl.level3.f_corona_model.subtract_f_corona_background(data_object: ndcube.NDCube, before_f_background_model: ndcube.NDCube, after_f_background_model: ndcube.NDCube) → ndcube.NDCube

Subtract f corona background.

punchbowl.level3.f_corona_model.subtract_f_corona_background_task(observation: ndcube.NDCube, before_f_background_model_path: str, after_f_background_model_path: str) → ndcube.NDCube

Subtracts a background f corona model from an observation.

This algorithm linearly interpolates between the before and after models.

Parameters:

• observation (NDCube) – an observation to subtract an f corona model from

• before_f_background_model_path (str) – path to a NDCube f corona background map before the observation

• after_f_background_model_path (str) – path to a NDCube f corona background map after the observation

Returns:

A background subtracted data frame

Return type:

NDCube

punchbowl.level3.f_corona_model.create_empty_f_background_model(data_object: ndcube.NDCube) → numpy.ndarray

Create an empty background model.