Abstract

ipyaladin allows to view astronomical data interactively within Jupyter notebook.

In this presentation, we will demonstrate the new capabilities of ipyaladin and its new compatibility with the Astropy ecosystem.

We will highlight the new features of the latest versions of the ipyaladin widget. A few lines of code allows one to visualize any catalog downloaded thanks to astroquery. It is then possible to make a visual sub-selection of this catalog by drawing a circle or a rectangle in the interactive widget. This sub-table can then be retrieved in a new astropy Table. ipyaladin also allows to display FITS files from disk or from astropy's objects. The other way around also works: the image survey currently displayed in the widget can be cutout into a new FITS file. An other new functionality is the display of sky regions -- with astropy-regions support. Approximated sky regions (Multi-Order Coverage) can also be overlayed onto the view by the supporting the Astropy-affiliated module MOCpy.

We will showcase how these new methods enable a workflow in which the programmatic approach within Python benefits from constant visual checks in a widget on the side of the notebook's cells.

Running the demo!

You can download the files:
- ADASS2024_ipya_BBgDrSO.ipynb
- requirements_24vnFxP.txt
- chandra_fQoZFZw.fits

In a folder with these files, create a new python (>=3.8, <=3.12) environment:

python -m venv ./.adass-ipyaladin
source .adass-ipyaladin/bin/activate (or .adass-ipyaladin\Scripts\activate.batin the Windows command window)

And install the required dependencies with:

pip install -r requirements_24vnFxP.txt

You can launch Jupyter and execute the cells:

python -m jupyterlab

When you're done, deactivate the environment with

deactivate