duxfrederic / lightcurver Goto Github PK

Provide option for using sextractor

In Large pixel size + low S/N scenarios, stars are typically labelled as cosmics.

Explore options to make the identification of cosmics more flexible: the astroscrappy implementation allows it.

The way things are implemented now: a "footprint" in which the stars are found is used as the reference throughout the pipeline for referring back to the stars. (Every table carries a "footprint hash" key)

But this footprint does not include the filtering (which can be changed by user) on stars (magnitude range, max astrometric or photometric noise).

Possible solutions:

• include the limits in the hash representing the "footprint" (but risk of collision?)
• find an all new way of referring back to stars, even though everything now is built around querying by the hash of the footprint

First steps:

• given that the calculation of the hash of the footprint turned out to be the same throughout the pipeline, refactor it to see more clearly

• Implement in STARRED (work in progress)
• Publish new STARRED version with changes
• Increment minimal required STARRED version of this package
• Add infrastructure here to use the PSF distortion feature

The logging should happen on a unified interface.

Right now only r-band added, but Gaia offers relations to many other photometric bands.

• Add conversions to utilities/zeropoint_from_gaia.py
• Add photometric band param to config file
• Adapt utilities.zeropoint_from_gaia.calculate_zeropoints

STARRED's smart_guess function for PSF building sets the FWHM of the moffat function to 3 pixels. This is too small for a lot of wide field images, which are oversampled (typical pixel size: 0.2'', typical seeing: 1-1.5'')

• make it more flexible in STARRED
• create new STARRED release and push to pypi

Here:

• in new branch (create):
• modify requirements of this code base for newer version
• pass fwhm argument from estimate in our database

Finally:

• merge

I thought I had fixed this, but

• run the pipeline all the way to the completion of PSF estimation
• set redo_psf to true
• change the stars the PSF is allowed to use
• redo the PSF

Now the photometry selects two PSFs per frame, duplicating the frame. (-> two fluxes per frame)

Possibilities for fixing this:

• Enforce only one PSF per footprint hash per frame?
• Create new key for the PSF? (containing info on which stars are allowed to be used)
• just modify the deconvolution/photometry preparation query to select only one PSF? Which one then? Lowest chi-squared? Makes things hard to debug for user.