The glue-astronomy plugin for glue provides a collection of astronomy-specific functionality

pysiaf is a python package to access, interpret, maintain, and generate Handling of Science Instrument Aperture Files, in particular for JWST. Tools for applying the frame transformations, plotting, comparison, and validation are provided.

This package implements a functionality to produce map based simulations for the Simons Observatory or other CMB experiments. It creates simulated maps in HEALPix and CAR pixelization based on:

• foreground models included in PySM

• custom foregrounds models from the so_pysm_models package

• precomputed Cosmic Microwave Background simulations

• noise simulations based on expected performance and simulated hitmaps

• effect of gaussian beam convolution

Ginga is a toolkit designed for building viewers for scientific image data in Python, visualizing 2D pixel data in numpy arrays. It can view astronomical data such as contained in files based on the FITS (Flexible Image Transport System) file format. It is written and is maintained by software engineers at the National Astronomical Observatory of Japan (NAOJ), the Space Telescope Science Institute (STScI), and other contributing entities.

The Ginga toolkit centers around an image display object which supports zooming and panning, color and intensity mapping, a choice of several automatic cut levels algorithms and canvases for plotting scalable geometric forms. In addition to this widget, a general purpose "reference" FITS viewer is provided, based on a plugin framework. A fairly complete set of standard plugins are provided for features that we expect from a modern FITS viewer: panning and zooming windows, star catalog access, cuts, star pick/FWHM, thumbnails, etc.

This package provides source-only AOCommon collection of functionality that is reused in several astronomical applications, such as wsclean, aoflagger, DP3 and everybeam.

This package provides a sunpy FIDO plugin for accessing data in the Solar Orbiter Archive.

Stuff is a program that simulates "perfect" astronomical catalogues. It generates object lists in ASCII which can read by the SkyMaker program to produce realistic astronomical fields. Stuff is part of the EFIGI development project.

WCSTools is a set of software utilities, written in C, which create, display and manipulate the world coordinate system of a FITS or IRAF image, using specific keywords in the image header which relate pixel position within the image to position on the sky. Auxiliary programs search star catalogs and manipulate images.

FITS/XISF image viewer with multithreaded image loading. It is intended primarily for viewing astro photos and images with support of following formats:

• FITS 8, 16 bit integer and 32 bit float

• XISF 8, 16 bit integer and 32 bit float

• RAW CR2, DNG, NEF

• JPEG, PNG, BMP, GIF, PBM, PGM, PPM and SVG images

Features:

• using same stretch function as PixInsight

• OpenGL accelerated drawing

• index and search FITS XISF header data

• quick mark images and then copy/move marked files

• convert FITS <-> XISF

• convert FITS/XISF -> JPEG/PNG

• image statistics mean, media, min, max

• support for WCS

• thumbnails

• convert CFA images to colour - debayer

• color space aware

PypeIt is a Python package for semi-automated reduction of astronomical spectroscopic data. Its algorithms build on decades-long development of previous data reduction pipelines by the developers.

It is designed to be used by both advanced spectroscopists with prior data reduction expertise and astronomers with no prior experience of data reduction. It is highly configurable and designed to be applied to any standard slit-imaging spectrograph, including long-slit, multi-slit, as well as cross-dispersed echelle spectra.

This package provides a Python package of Roman Datamodels for the calibration pipelines started with the JWST calibration pipelines. The goal for the JWST pipelines was motivated primarily by the need to support FITS data files, specifically with isolating the details of where metadata and data were located in the FITS file from the representation of the same items within the Python code. That is not a concern for Roman since FITS format data files will not be used by the Roman calibration pipelines.

SWarp is a program that resamples and co-adds together FITS images using any arbitrary astrometric projection defined in the WCS standard.

MARTINI is a modular package for the creation of synthetic resolved HI line observations (data cubes) of smoothed-particle hydrodynamics simulations of galaxies. The various aspects of the mock-observing process are divided logically into sub-modules handling the data cube, source, beam, noise,spectral model and SPH kernel. MARTINI is object-oriented: each sub-module provides a class (or classes) which can be configured as desired. For most sub-modules, base classes are provided to allow for straightforward customization. Instances of each sub-module class are given as parameters to the Martini class; a mock observation is then constructed by calling a handful of functions to execute the desired steps in the mock-observing process.

Event reconstruction framework for Imaging Atmospheric Cherenkov Telescopes developed for CTAO.

Radio Beam is a simple toolkit for reading beam information from FITS headers and manipulating beams. Some example applications include:

• Convolution and deconvolution

• Unit conversion (Jy to/from K)

• Handle sets of beams for spectral cubes with varying resolution between channels

• Find the smallest common beam from a set of beams

• Add the beam shape to a matplotlib plot

Provides DataModel, which is the base class for data models implemented in the JWST and Roman calibration software.

Generalized World Coordinate System (GWCS) is an Astropy affiliated package providing tools for managing the World Coordinate System of astronomical data.

GWCS takes a general approach to the problem of expressing transformations between pixel and world coordinates. It supports a data model which includes the entire transformation pipeline from input coordinates (detector by default) to world coordinates.

Astropy is a single core package for Astronomy in Python. It contains much of the core functionality and some common tools needed for performing astronomy and astrophysics.

HEALPix of a sphere produces a subdivision of a spherical surface in which each pixel covers the same surface area as every other pixel. This package provides the dynamic library for the C language implementation of HEALPix.

The Advanced Scientific Data Format (ASDF) is a next-generation interchange format for scientific data. This package contains the Python implementation of the ASDF Standard.

Pynbody is an analysis framework for N-body and hydrodynamic astrophysical simulations supporting PKDGRAV/Gasoline, Gadget, Gadget4/Arepo, N-Chilada and RAMSES AMR outputs.

Stackistry implements the lucky imaging principle of astronomical imaging: creating a high-quality still image out of a series of many (possibly thousands) low quality ones (blurred, deformed, noisy). The resulting image stack typically requires post-processing, including sharpening (e.g. via deconvolution). Such post-processing is not performed by Stackistry.

POLIASTRO is a Python library for interactive Astrodynamics and Orbital Mechanics, with a focus on ease of use, speed, and quick visualization. It provides a simple and intuitive API, and handles physical quantities with units.

Some features include orbit propagation, solution of the Lambert's problem, conversion between position and velocity vectors and classical orbital elements and orbit plotting, among others. It focuses on interplanetary applications, but can also be used to analyze artificial satellites in Low-Earth Orbit (LEO).

This package provides ALFA, which can identify and fit hundreds of lines in emission line spectra in just a few seconds with following features:

• A population of synthetic spectra is generated using a reference line catalogue.

• The goodness of fit for each synthetic spectrum is calculated. The best sets of parameters are retained and the rest discarded.

• A new population of synthetic spectra is obtained by averaging pairs of the best performers.

• A small fraction of the parameters of the lines in the new generation are randomly altered.

• The process repeats until a good fit is obtained.