astro-salsa 1.0.0
Synthetic absorber catalog generator from astrophysical simulations
License: BSD 3-Clause
Keywords: simulation,spectra,astronomy,astrophysics

# SALSA
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SALSA: Synthetic Absorption Line Surveyor Application is a Python tool that
constructs synthetic absorber catalogs from hydrodynamic galaxy simulations.
Salsa heavily utilizes [yt](https://yt-project.org/) to access simulation data
and [Trident](http://trident-project.org/) to create light rays/sight lines and
generate synthetic spectra.

Observational studies generate large absorber catalogs by studying the absorption
line spectra of distant quasars, as their light passes through intervening galaxies.
Salsa can generate similar catalogs from cosmological and galactic simulations,
allowing research to study these simulations from an observers perspective. This
can give new insights into the data as well as help facilitate comparisons and
collaboration between simulations and observations.

Salsa allows us to dip into galactic simulations and start to chip away at the
many unknowns of the universe

A [JOSS paper](https://joss.theoj.org/papers/10.21105/joss.02581) was published for 
SALSA and we recommend reading it for an overview of the package and its possible uses. 
If you do use SALSA in a project we ask that you cite this paper.

For detailed information on how to install and run salsa, Read the Docs
[here](https://salsa.readthedocs.io)

## Install
If you have all the dependencies installed, you can clone the repository and
run these commands:
```
  $ git clone https://github.com/biboyd/SALSA.git
  $ cd SALSA
  $ pip install -e .
  $ python
  >>> import salsa
```
Now you should be all set to code!

### Installing dependencies
To help with installing dependencies, `enivronment.yml` is included in the
repository. First,
[install conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)
Then you should be able to create a conda environment via:
```
  $ conda env create --file environment.yml
  $ conda activate salsa-env
```
Note that you need gcc compiler installed (which it often already is on most machines).
For a more detailed description see the
[installation guide](https://salsa.readthedocs.io/en/latest/installation.html)
which also includes tips if you want to install dependencies on your own.

## Getting Started
For an annotated example [go here](https://salsa.readthedocs.io/en/latest/annotated_example.html). Or launch an interactive jupyter hosted on Binder
[here](https://mybinder.org/v2/gh/biboyd/SALSA/master?filepath=notebooks%2FExample_notebook.ipynb) (note that the notebook
may take some time to load as it generally has to build the repository).

If you want to explore on your own, the easiest way to get started is use
`salsa.generate_catalog()`. This takes:
  * The simulation dataset
  * Number of light rays/sightlines to make
  * Directory to save those light rays
  * A list of ions
  * Some other optional parameters.  
This creates a number light rays and then extracts absorbers for each ion. A
`pandas.DataFrame` is returned with information about all the absorbers which
can then be further analyzed.

## Contributing Guidelines
All contributions are welcome! This is an open-source project, built on many
other open-source projects. Contributing can take many forms including:
contributing code, testing and experimenting, or offering ideas for different
features.

If you are interested in contributing you can contact us directly at
boyd.brendan@stonybrook.edu or add an issue on this Github page.