Creating Jdaviz-readable Products#
Spectroscopic data products (1D, 2D, and 3D) can be loaded
in the different jdaviz configurations using
essentially two methods, i.e., loading Spectrum objects or
from FITS files. Here, we list a few ways in which data can be packaged to be easily loaded
into a jdaviz configuration.
Data in a database#
If the data are stored in a database, we recommend storing a Spectrum object
per entry. This would allow the user to query the data and visualize it in
jdaviz with few lines of code; also see Providing scripts to load the data as Spectrum objects.
Data in FITS files#
If the data are stored as FITS files, we propose three options:
Using an available specutils loader#
Available loaders can be listed with the following commands:
from specutils import Spectrum
Spectrum.read.list_formats()
The majority are fairly specific to missions and instruments. Four formats
are more generic and adaptable: ASCII, ECSV, tabular-fits, and
wcs1d-fits. More information on how to create files that are readable by
these loaders can be found on the specutils GitHub repository.
Creating a dedicated loader#
The specutils documentation on how to create a custom loader
is available. We are working on the necessary documentation to prompt
jdaviz to recognize a custom loader developed in specutils.
Providing scripts to load the data as Spectrum objects#
If none of the above is an acceptable option, the user can create the data
products with their custom format and provide scripts or Jupyter Notebooks
that show how to read the products and create Spectrum objects
that can be read into jdaviz.