APLpy is a Python module aimed at producing publication-quality plots of astronomical imaging data in FITS format. The module uses matplotlib, a powerful and interactive plotting package. It is capable of creating output files in several graphical formats, including EPS, PDF, PS, PNG, and SVG.

Main features:

• Make plots interactively or using scripts

• Show grayscale, colorscale, and 3-color RGB images of FITS files

• Generate co-aligned FITS cubes to make 3-color RGB images

• Make plots from FITS files with arbitrary WCS (e.g. position-velocity)

• Slice multi-dimensional FITS cubes

• Overlay any number of contour sets

• Overlay markers with fully customizable symbols

• Plot customizable shapes like circles, ellipses, and rectangles

• Overlay ds9 region files

• Overlay coordinate grids

• Show colorbars, scalebars, and beams

• Customize the appearance of labels and ticks

• Hide, show, and remove different contour and marker layers

• Pan, zoom, and save any view as a full publication-quality plot

• Save plots as EPS, PDF, PS, PNG, and SVG

This package provides a flexible toolbox for observation planning and scheduling. When complete, the goal is to be easy for Python beginners and new observers to to pick up, but powerful enough for observatories preparing nightly and long-term schedules.

Features:

• calculate rise/set/meridian transit times, alt/az positions for targets at observatories anywhere on Earth

• built-in plotting convenience functions for standard observation planning plots (airmass, parallactic angle, sky maps)

• determining observability of sets of targets given an arbitrary set of constraints (i.e., altitude, airmass, moon separation/illumination, etc.)

This package implement functionality for computation of non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee, an affine-invariant ensemble sampler for Markov Chain Monte Carlo.

Package Raccoon cleans the "wiggles" (i.e., low-frequency sinusoidal artifacts) in the JWST-NIRSpec IFS (integral field spectroscopy) data. These wiggles are caused by resampling noise or aliasing artifacts.

The spherical_geometry library is a Python package for handling spherical polygons that represent arbitrary regions of the sky.

This package provides an image processing toolbox for Solar Physics.

PHD2 is the enhanced,second generation version of the PHD guiding software from Stark Labs.

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.

This package provides a tool to create Calibration References Data System-formatted reference files for James Webb Space Telescope from a set of input dark current files and a set of flat field files.

This package implements functionality of spectroscopic reduction in observations from Optical and Near-infrared spectroscopy instruments.

EsoRex is the European Southern Observatory Recipe Execution Tool. It can list, configure and execute Common Pipeline Library-based recipes from the command line.

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

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

Weightwatcher is a program hat combines weight-maps, flag-maps and polygon data in order to produce control maps which can directly be used in astronomical image-processing packages like Drizzle, Swarp or SExtractor.

This package contains FIT and CSV files required for WebbPSF installation and distributed separately from it.

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.

lenstronomy is a multi-purpose software package to model strong gravitational lenses. lenstronomy finds application for time-delay cosmography and measuring the expansion rate of the Universe, for quantifying lensing substructure to infer dark matter properties, morphological quantification of galaxies, quasar-host galaxy decomposition and much more.

This package provides tools for machine learning and data mining in astronomy.

The GNU Astronomy Utilities (Gnuastro) is a suite of programs for the manipulation and analysis of astronomical data.

AOFlagger is a tool that can find and remove radio-frequency interference (RFI) in radio astronomical observations. It can make use of Lua scripts to make flagging strategies flexible, and the tools are applicable to a wide set of telescopes.

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 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.

DRMS module provides an easy-to-use interface for accessing HMI, AIA and MDI data with Python. It uses the publicly accessible JSOC (http://jsoc.stanford.edu/) DRMS server by default, but can also be used with local NetDRMS sites.