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Produce Fermi all-sky HEALPIX high-energy images #11
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Hi Chris, -Dan
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It's either TS or SQRT_TS.
I'd prefer HEALPIX to avoid the issues at the pole. |
I just talked to @OlgaVorokh (GSoC student for Gammapy this summer). She will write a script to make Gauss-smoothed HEALPIX counts images from event lists using healpy, as a start on this task. |
We started a script here: https://github.com/gammapy/gammapy-extra/blob/master/experiments/healpix/fermi_counts_hpx.py |
Note to self: I moved the example dataset and script to here: |
Just a note: if HiPS generation in Python doesn't become available soon (hipspy/hips#119), then doing it via the Java hipsgen for Fermi-LAT is also possible. That's what we did for HGPS, see example here: |
@adonath - as discussed, please move https://github.com/gammapy/gamma-sky/blob/master/gammasky/maps.py to your repo, and also remove the FErmi map fetch here: Line 31 in 22074c2
and then we simply access Fermi-LAT HiPS from gamma-sky.net, but producing them is part of the other project / repo. |
For the http://gamma-sky.net/ webpage we want to produce all-sky HEALPIX high-energy images.
We'll then convert those to http://aladin.u-strasbg.fr/hips/ and serve them as default image instead of the one from http://alasky.u-strasbg.fr/Fermi/Color/ which we use now.
My suggestion would be to make RGB images for the energy bands
These are the energy bands I used many years ago (2011 I think) and the maps were interesting. See https://github.com/cdeil/fermi-ts-maps for Galactic plane images ... I also have old all-sky images in CAR and AIT, but I think we should just re-do them.
As for which quantity to show, my experience is that sqrt(TS) is good.
Other options would be smoothed counts or excess or flux.
Having catalog model images and residual images would also be very cool, to see where the catalog represents the data well and where it doesn't.
I don't have a working set of Python scripts any more to produce those TS images. So if someone else has them or is willing to write them and share scripts and / or maps, that would be great!
cc @woodmd @tburnett @dankocevski @adonath @vorugantia
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