Previously, the mask was included as part of the CIData class, and it was extracted for parallel / serial calibration alongside the image, noise-map, etc.
I have decided to remove the mask from the CIData, as like AutoLens it is something we will want to update through the pipeline. Thus, we should have it set using a mask_function in phase.py, where the default_mask_function corresponds to a completely unmasked image (e.g. all False) with the same shape as the image. This mask is then extracted to the same cut-out as the image, noise-map etc and included in the 'ci_data_anallysis'.
To make it so that we can cleanly extract the mask we need to include it as in input variable in the CI_Data '_calibration_data' routines, and I guess we need these routines to output a CIDataAnalysis class which includes the (extracted) mask.
Previously, the mask was included as part of the CIData class, and it was extracted for parallel / serial calibration alongside the image, noise-map, etc.
I have decided to remove the mask from the CIData, as like AutoLens it is something we will want to update through the pipeline. Thus, we should have it set using a mask_function in phase.py, where the default_mask_function corresponds to a completely unmasked image (e.g. all False) with the same shape as the image. This mask is then extracted to the same cut-out as the image, noise-map etc and included in the 'ci_data_anallysis'.
To make it so that we can cleanly extract the mask we need to include it as in input variable in the CI_Data '_calibration_data' routines, and I guess we need these routines to output a CIDataAnalysis class which includes the (extracted) mask.