I am using the
_w2021_46 and would like to insert fake moving objects in to calibrated exposures using gen3 middleware. I have a csv file of objects with
ra, dec, mag, mjd, exposure and would like to insert these in the appropriate exposures. Is there any direct functionality to achieve this.
gen2 I used to create a separate catalog per exposure, and then run the following:
processCcdWithFakes.py ../repo --calib ../repo/CALIB --rerun coadd:fakes_n1 -C processCcdWithFakes.py -c insertFakes.fakeType=Catalogs/123456.csv --id visit=123456 ccd=0..8^10..103 filter=HSC-R2 tract=tractlist
Is there a better way of doing this in gen3? I suppose the tedious route would be to register each of the Catalog files for every exposure as a dataset in a separate collection, and then pass the collection as an input to
pipetask as done here: [DM-31491] Make a RC2 fakes pipeline - Jira
I am pretty sure there is a better way to do this, perhaps adding an extra dimension of exposure to
fakeCat, but I suppose that will still require the code to be modified.
The documentation for
self.config.insertFakes.fakeType == "snapshot" is pretty sparse and it was unclear how I could use it either? And it seemed more suited to variable object rather than moving objects.
Could some one help out with this?