Supernovae.jl

Provides methods for reading in and plotting supernova lightcurves from text files. Extremely flexible reading methods allow for almost any reasonable lightcurve data file syntax to be read.

Prerequisites

To automatically download passbands from the SVO Filter Profile Service, you must install the python package astroquery. This is installed as part of the build process, installing into a Conda.jl conda environment.

Install

$ git clone [email protected]:OmegaLambda1998/Supernovae.jl.git 
$ cd Supernovae.jl
$ make

This will instantiate and build Supernovae.jl, installing all required Julia packages, and setting up a Conda environment for the required Python packages. Finally it will run the tests to make sure everything is working. If you want to skip testing run make install instead. You can also run ./scripts/Supernovae -v ./Examples/Inputs/2021zby/2021zby_data.toml to load and plot the lightcurve of 2021zby. This will create a .svg plot in ./Examples/Outputs/2021zby/.

Usage

$ ./scripts/Supernovae -v path/to/input.toml

Details on how to build the input files which control Supernovae.jl can be found in Usage.

Example data file

The following example input file can be found in the Examples directory. base_path is the directory containing your input file.

[ global ]
filter_path = "../Filters" # Defaults to base_path / Filters
output_path = "../../Outputs/2021zby" # Defaults to base_path / Output

# Data
[ data ]
# First include information about the supernova
name = "2021zby" # Required
zeropoint = 8.9 # Required
redshift = 0.02559 # Required
max_flux_err = 2.5e2 # Optional, set's the maximum allowed value for the uncertainty in the flux, assumes same units as flux
peak_time = true # Default false. Can either be true, in which case all times will become relative to the peak data point. Alternatively, give a value, and all times will be relative to that value
peak_time_unit = "d" # Optional, default to d

[[ data.observations ]] # Now load in different observations of the supernova. This can either be one file with all observations, or you can load in multiple files
name = "atlas" # Required, Human readable name to distinguish observations
path = "atlas_1007.dat" # Required, Accepts either relative (to Supernova) or absolute path
delimiter = " " # Optional, defaults to comma
facility = "Misc"
instrument = "Atlas" # Optional, will overwrite anything in the file 
upperlimit = "flux_err"

# Since this file contains a header that isn't in the expected format, you can optionally specify what each header corresponds to.
# If you do this you MUST specify the time, flux, and flux error.
# You can also specify the filter, instrument, or upperlimit columns if they're in the file. If not, specify them above
header.time.col = "MJD"
header.time.unit = "d"

header.flux.col = "uJy"
header.flux.unit = "µJy"

header.flux_err.col = "duJy"
header.flux_err.unit = "µJy"

header.passband.col = "F"

[[ data.observations ]]
name = "tess 6hr"
path = "tess_2_6hrlc.txt"
delimiter = " "
comment = "#" # Optional, defines what is a comment (will be removed). Defaults to #
facility = "tess"
instrument = "tess"
passband = "Red"
filter_name = "Tess"
upperlimit = false
flux_offset = 0.296 # Defaults to 0, assumes same units as flux

[[ plot.lightcurve ]]
filters = ["Red", "orange"]
markersize = 21
marker."tess 6hr" = "utriangle"
rename."tess 6hr" = "Tess (6hr)"
marker.atlas = "circle"
rename.atlas = "Atlas"
colour.Red = "red"
rename.Red = "Tess: Red"
rename.orange = "Atlas: Orange (+150 μJy)"
colour.orange = "orange"
offset.orange = 150
legend = true

Further details can be found in the documentation.