Current time at conference location: 7:21 pm ET
Sunday, January 12, 2025 | 9:00 AM ET - 5:00 PM ET
Session Title
Python Data Analysis with the James Webb and Roman Space Telescopes
Session Type
Workshops
Room
Chesapeake 4-5
Summary
This workshop will cover several tools used for the data analysis and visualization of JWST and Roman data. This includes the Jdaviz visualization and data analysis package, the Advanced Scientific Data Format (ASDF) package, specreduce, photutils PSF photometry, and generalized world coordinate systems (gwcs). The goals are to introduce participants to these tools and provide hands-on time for participants to use the tools and ask questions to the developers. The format will include short presentations followed by instructor-guided tutorials using Jupyter notebooks.

Jdaviz is a package of astronomical data analysis visualization tools based on the Jupyter platform. These GUI-based tools link data visualization and interactive analysis. Presenters will provide examples of the latest features available in the various configurations (Specviz, Cubeviz, Imviz, and Specviz2d) and will guide attendees through basic and advanced workflows to analyze JWST spectra and images.

The Advanced Scientific Data Format (ASDF) is a next-generation interchange format for scientific data. It will be used as the data format for Roman Space Telescope Level 1 - 4 data products.

The workshop will also cover the Astropy packages specreduce (spectral extraction), photutils PSF photometry, and the generalized world coordinates system package (gwcs).

There will be time spent on hands-on exercises. Participants must bring a laptop with the software installed. Instructions on installing the necessary software will be provided before the workshop and help will be available at the workshop for those that experience problems with installations.

The prerequisites are a familiarity with astronomical data analysis. Basic Python experience is highly recommended to be able to participate in the exercises. Those without Python experience will still be able to use Jdaviz and gain useful information about the capabilities for data analysis in Python.