Fix Version/s: None
Sprint:Alert Production F16 - 8
I've run a subtraction of two images, one with a clear supernova (SNR~100), the other taken a year later. The supernova shows up very clearly, but does not get properly identified by the object detection and measurement.
If run with config.doMerge=False then I get the first attachment, which shows the identification of a footprint in which the SN is found, but the X, Y position are set to be the presumably the first object that went in to the footprint. It's not re-centered at the SN.
If I run with config.doMerge=True, then I get the third attachment, in which I believe the SN has been subsumed into the larger object of the dipole at the galaxy center.
1. There is significant galaxy background (that's what I wanted to do the subtraction). This changes the noise properties and, from my understanding of a discussion on Hipchat, breaks assumptions made by the de-correlation step.
2. These images are from a NIR detector, so they are created from a sequence of raw images in a grid dither pattern, which have been processed and combined to make these final images. This means that the noise varies significantly across the image, from the center which is covered by all raw images, to the corners which are each just covered by one.
To recreate on lsst-dev.ncsa.illinois.edu:
Set up the LSST stack + some custom branches in pipe_tasks, ip_diffim, obs_file:
If you're testing for yourself, you may wish to change the output repo to your own cusomt repo so we don't accidentally confuse each other with various runs.
The active parts of diffimconfig.py are
For a quick start, the following will display the images: