This package provides an access to the JWST Science Calibration Pipeline processes data from all JWST instruments and observing modes by applying various science corrections sequentially, producing both fully-calibrated individual exposures and high-level data products (mosaics, extracted spectra, etc.).

CFITSIO provides simple high-level routines for reading and writing Flexible Image Transport System files that insulate the programmer from the internal complexities of the FITS format. CFITSIO also provides many advanced features for manipulating and filtering the information in FITS files.

This simulation program lets you explore our universe in three dimensions. Celestia simulates many different types of celestial objects. From planets and moons to star clusters and galaxies, you can visit every object in the expandable database and view it from any point in space and time. The position and movement of solar system objects is calculated accurately in real time at any rate desired.

This package provides Python implementation of ASDF - a proposed next generation interchange format for scientific data. ASDF aims to exist in the same middle ground that made FITS so successful, by being a hybrid text and binary format: containing human editable metadata for interchange, and raw binary data that is fast to load and use. Unlike FITS, the metadata is highly structured and is designed up-front for extensibility.

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.

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.

hvpy is a Python API wrapper around the formal https://api.helioviewer.org/docs/v2/.

This package implements a functionality of AI-powered automated pipeline for lens modeling, with lenstronomy as the modeling engine.

Features:

• AI-automated forward modeling for large samples of galaxy-scale lenses

• flexible: supports both fully automated and semi-automated (with user tweaks) modes

• multi-band lens modeling made simple

• supports both galaxy–galaxy and galaxy–quasar systems

• effortless syncing between local machines and High-Performance Computing Cluster

This package provides a structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles. Focused on driving physically-meaningful inquiry, it has been applied in domains such as astrophysics, seismology, nuclear engineering, molecular dynamics, and oceanography.

POPPY is a Python package that simulates physical optical propagation including diffraction. It implements a flexible framework for modeling Fraunhofer and Fresnel diffraction and point spread function formation, particularly in the context of astronomical telescopes.

POPPY was developed as part of a simulation package for the James Webb Space Telescope, but is more broadly applicable to many kinds of imaging simulations. It is not, however, a substitute for high fidelity optical design software such as Zemax or Code V, but rather is intended as a lightweight alternative for cases for which diffractive rather than geometric optics is the topic of interest, and which require portability between platforms or ease of scripting.

SPLASH is visualisation tool for Smoothed Particle Hydrodynamics (SPH) simulations in one, two and three dimensions, developed mainly for astrophysics. It uses a command-line menu but data can be manipulated interactively in the plotting window.

The concept of the pvextractor package is simple - given a path defined in sky coordinates, and a spectral cube, extract a slice of the cube along that path, and along the spectral axis, producing a position-velocity or position-frequency slice.

PSFEx extracts models of the PSF from FITS images processed with SExtractor, and measures the quality of images. The generated PSF models can be used for model-fitting photometry or morphological analyses.

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.

SNCosmo is a Python library for supernova cosmology analysis. It aims to make such analysis both as flexible and clear as possible.

European Southern Observatory Data Processing System EDPS is a system to automatically organise data from ESO instruments for pipeline processing and running the pipeline on these data. It is used for quality control at ESO. The current public release is a beta version without a GUI. A GUI is being developed and the system is meant to eventually replace the older EsoReflex environment.

This package provides ASDF schemas for validating transform tags. Users should not need to install this directly; instead, install an implementation package such as asdf-astropy.

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 a a simple program to predict the levels of background emission in JWST observations, for use in proposal planning.

It accesses a precompiled background cache prepared by Space Telescope Science Institute. The background cache is hosted by the Mikulski Archive for Space Telescopes (MAST), so you need internet access to run the tool with the remote cache. It is possible to download the full background cache to your local machine.

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.

CRDS is a package used for working with astronomical reference files for the HST and JWST telescopes. CRDS is useful for performing various operations on reference files or reference file assignment rules. CRDS is used to assign, check, and compare reference files and rules, and also to predict those datasets which should potentially be reprocessed due to changes in reference files or assignment rules. CRDS has versioned rules which define the assignment of references for each type and instrument configuration. CRDS has web sites corresponding to each project http://hst-crds.stsci.edu or https://jwst-crds.stsci.edu/ which record information about reference files and provide related services.

healpy is a Python package to handle pixelated data on the sphere. It is based on the Hierarchical Equal Area isoLatitude Pixelization (HEALPix) scheme and builds with the HEALPix C++ library.

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 a functionality to reproject astronomical images using various techniques via a uniform interface, where reprojection is the re-gridding of images from one world coordinate system to another e.g. changing the pixel resolution, orientation, coordinate system.