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https://github.com/mrosseel/vast-automation

Using VaST and astropy to measure lightcurves of known and unknown variable stars
https://github.com/mrosseel/vast-automation

aavso lightcurves variable-stars vsx-catalog vsx-stars

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Using VaST and astropy to measure lightcurves of known and unknown variable stars

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README 

        
[![Build Status](https://travis-ci.com/mrosseel/vast-automation.svg?branch=master)](https://travis-ci.com/mrosseel/vast-automation)



# vast-automation



## Introduction



This project takes as input:

- a number of FITS files of the same region in the sky (time series)

- the resulting files of running VaST on these files

- the observatory location (settings.txt)



and produces a website containing this information:

- phase diagram charts of VSX stars and new variable candidates (as detected by VaST)

- light curves charts

- magnitude error vs JD chart

- Ensemble comparison star lightcurves

- Global charts on aperture vs airmass and aperture vs JD

- AAVSO reports



Most output can be turned off if it's of no interest.



## Preparation



### Importing VSX star catalog



* First time download of AAVSO VSX catalog: use the script `vsx_download.sh`

* If you want to update: use the same script.

* Is an update needed? Each time you download the VSX catalog, its date is written in `vsx_last_modified.txt`.

Compare this with the output of the script `vsx_check_last_modified.sh`.

* check that `vsx_catalog.bin` has been written successfully



### Importing UCAC4 star catalog



Getting the 900 files (9Gb):

- `wget ftp://cdsarc.u-strasbg.fr/0/more/UCAC4/u4b/*`



Checking that all 900 files were downloaded correctly:

- `md5sum -c md5sum.txt`



Also download some support files:

- `wget ftp://cdsarc.u-strasbg.fr/0/more/UCAC4/u4i/*` 



and place these two directories (u4b and u4i) in this location:

- `support/ucac4/UCAC4/`



## Run VAST on the fits files



`./vast -u -x 3 ../location/of/fits/*.fit`



This uses UTC time, and ignores the 'blended' flag for stars which are close to each other.

This will generate many vast files in the vast directory



## Process VAST results



Needed: python 3.8+



### run the command



*[Install poetry][https://python-poetry.org/docs/#installation] to manage the python dependencies.*



Install the dependencies and the virtual environment (do this once):



`poetry install`



Activate a python virtual environment (do this every time):



`poetry shell`



Run the actual processing software to get all options:



`./vast_process.sh -h`



## Generate a site



If you checked out the VSX dir you can update the submodule while being in the site/vsx/themes directory:



`git submodule update --init --recursive`



You can also download it from the github page and put in site/vsx/themes: 

https://github.com/theNewDynamic/gohugo-theme-ananke



## Example usage:



`./vast_process.sh --vsx --candidates -d support/vast-1.0rc84 --fitsdir ./fits --apikey abcde -r /bla/my-result-dir/`



Note that the fitsdir and apikey options are needed to perform automatic plate-solving via

astrometry.net. If you prefer to do your own plate-solving, put the solved image as new-image.fits

in the directory passed via `-d`



Note that the fitsdir should contain the same files as were used by VaST.



### look at the results



This command line above will generate vsx information and create phase diagrams for

all vast autocandidates and vsx stars.

Also a few extra files are generated:



* vsx_stars.txt

* vast_list_of_all_stars_pos.txt

* vast_autocandidates_pos.txt



### Local id catalog ( -l )



The file which can be passed is a CSV file.

Example:



```

# our_name, local_id, minmax, min, max, var_type, period, period_err, epoch

MY-STAR-NAME, 101, 16.03-15.15, 16.03, 15.15, RRAB, 0.15,0.015, 2458849.59206

```



Minimal example:

```

# our_name, local_id, minmax, min, max, var_type, period, period_err, epoch

MY-STAR-NAME, 101, , , , , , ,

```



### RADEC catalog ( -o )



This file is generated by the software, and is similar to the localid star file:

instead of a local id this file has ra/dec of the star.

The file which can be passed is a CSV file.

Example:



```

# our_name, ra, dec, minmax, min, max, var_type, period, period_err, epoch

MY-STAR-NAME, 10.123, 15.321, 16.03-15.15, 16.03, 15.15, RRAB, 0.15,0.015, 2458849.59206

```



Minimal example:

```

# our_name, ra, dec, minmax, min, max, var_type, period, period_err, epoch

MY-STAR-NAME, 10.123, 15.321, , , , , , ,

```



## Docker (no longer maintained)



The docker setup is currently mainly used to run Jupyter notebooks, but should also

be a well-setup environment to run vast-automation.



### Starting Docker



* have a working docker installation: https://www.docker.com/community-edition

* cd docker

* docker build . -t mrosseel/munipack-automation

* cd ..

* command: `./startJupyter.sh`

* you are automatically logged into a root shell of the docker container



### Docker & Jupyter lab



The docker image exposes a Jupyter lab instance on port 8888.

_Password is 'muni'_



## TODO



- for cli_inspect, add the chosen fits to the txt file

- for candidates, closest known vsx

- check out https://public.lanl.gov/palmer/fastchi.html for period determination

- check out https://github.com/toros-astro/astroalign for aligning

- stacking images to detect fainter stars+have better signal/noise ratio: https://github.com/fedhere/coaddfitim



## References



* https://books.google.ae/books?id=g_K3-bQ8lTUC&pg=PA236&lpg=PA236&dq=munipack+aperture&source=bl&ots=P4BKKI25HG&sig=Lj9Kg6EZi2pwKZXK5Hk5_B4qcVg&hl=en&sa=X&ved=0ahUKEwj4qr6o4evZAhWILcAKHdtnAqYQ6AEIRDAE#v=onepage&q&f=false

* https://www.aavso.org/how-report-new-variable-star-discoveries