JWST Data Analysis Tool Notebooks (pyinthesky)

JDAT and Jdaviz

The James Webb Space Telescope Data Analysis Tool (JDAT) team at the Space Telescope Science Institute (STScI) is developing analysis and visualization tools for the upcoming James Webb Space Telescope (JWST). JDAT is involved with the development of astropy core and its affiliated analysis tools (such as specutils and photutils). JDAT is also responsible for the development of the JWST Data Analysis Visualization tools (Jdaviz). Jdaviz is a package of astronomical data analysis and visualization tools based on the Jupyter platform. The Jdaviz package includes the following visualization applications:




Visualization and quick-look analysis for 1D astronomical spectra.


Visualization and analysis tool for data cubes from integral field units (IFUs).


Visualization and quick-look analysis tool for multi-object spectroscopy (MOS).

See also

JDAT Notebooks

The JDAT team is seeking help from the scientific community to develop example notebooks that outline scientific workflows utilizing the analysis and visualization tools developed by the team. These notebooks will be made available to the public to serve as teaching resources and a form of interactive documentation of the analysis tools.

The submitted notebooks should satisfy the following goals:

  1. Reduce and analyze JWST data (we currently use simulated or similar data).

  2. Showcase analysis and visualization tools.

  3. Drive development by identifying missing functionalities in the tools and libraries.


Completed notebooks are rendered and made available to the public in the jdat_notebooks repository. Development of new notebooks is facilitated through the dat_pyinthesky repository.

JDAT Development Sprints

The JDAT team at STScI develops the Jdaviz applications during two week sprints through out the year. During this time developers are available to assist with the development of notebooks. Notebook leads are strongly encouraged to participate in the JDAT sprints while composing their notebooks because it offers an opportunity to work with the developers and gain exposure to the latest tools. During a Sprint, we expect notebook leads to learn how to contribute their science expertise towards the development of tools via GitHub issues, JIRA tickets, Jupyter Notebook coding, communication with developers, and all the machinery in between. The JDAT team also has staff members dedicated to helping notebook leads with GitHub and Box related workflows. If you are interested in joining these sprints, please contact one of the maintainers of the dat_pyinthesky repository or file a ticket in the STScI help desk. STScI and affilated staff should refer to the STScI Notebook Leads section for instructions.