Sparkobs

temporary name, clear lack of imagination

What is it?

Sparkobs is a lightweight package to create observation plans for various instruments, but faster than the speed of light (I might be lying about the speed of light part).

It is inspired by gwemopt and some of SkyPortal's code.

How to install it?

First clone the repository from github

git clone https://github.com/Theodlz/sparkobs.git

Optional Create a virtual environment

python -m venv env
source env/bin/activate

(you will need to have virtualenv installed)

Then go to the directory and install it

pip install .

How to use it?

This is very much of an alpha. In the long run, it will probably not even be a package, but its methods might be integrated in gwemopt instead.

For now, it only works for ZTF, which fields and tiles are precomputed and stored in data/ztf_fields.joblib.

You can run it on a skymap given its URL, for example:

python -m sparkobs --telescope="config/ztf.toml" --skymap="https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm/triggers/2023/bn230430325/quicklook/glg_healpix_all_bn230430325.fit"

or on a larger localization, for example:

python -m sparkobs --telescope="config/ztf.toml" --skymap="https://gracedb.ligo.org/api/superevents/MS230502c/files/bayestar.fits.gz,1" --level=0.95

You can specify the weights to use for the scheduler as such:

python -m sparkobs --telescope="config/ztf.toml" --skymap="https://gracedb.ligo.org/api/superevents/MS230502c/files/bayestar.fits.gz,1" --level=0.95 --weights 4 2 3

The weights correspond to: probability, distance, and airmass. That way, you can prioritize the probability of the event, or the distance, or the airmass, or a combination of those to create different strategies.

Also, you can run the integration tests with

python -m pytest sparkobs/tests.py

Let me know what you think, and feel free to contribute!