punchbowl.levelq.flow

Attributes

ORDER_QP

Functions

levelq_CNN_core_flow(→ list[ndcube.NDCube])	Run the LQ CNN flow.
levelq_CTM_core_flow(→ list[ndcube.NDCube])	Level quickPUNCH core flow.

Module Contents

punchbowl.levelq.flow.ORDER_QP = ['CR1', 'CR2', 'CR3', 'CNN']

punchbowl.levelq.flow.levelq_CNN_core_flow(data_list: list[str] | list[ndcube.NDCube], output_filename: list[str] | None = None, files_to_fit: list[str | ndcube.NDCube | punchbowl.util.DataLoader] | None = None, outlier_limits: str | None = None, data_root: str | None = None) → list[ndcube.NDCube]

Run the LQ CNN flow.

This flow is designed to run on a batch of input CR4 images to facilitate more efficient PCA fitting.

Parameters:

• data_list (list[str | NDCube]) – The input images, either as paths or NDCubes

• output_filename (list[str]) – Optional output paths at which the CNN files should be written

• files_to_fit (list[str | NDCube | DataLoader]) – Additional files to use for the PCA fitting, but not to actually be filtered or output

• outlier_limits (str) – A path to a LimitSet to use for outlier rejection in the PCA fitting

• data_root (str) – The root directory which the paths in data_list are relative to

Returns:

output_cubes – The CNN data cubes

Return type:

list[NDCube]

punchbowl.levelq.flow.levelq_CTM_core_flow(data_list: list[str] | list[ndcube.NDCube], output_filename: list[str] | None = None) → list[ndcube.NDCube]

Level quickPUNCH core flow.