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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.)
skyfield computes positions for the stars, planets, and satellites in orbit around the Earth. Its results should agree with the positions generated by the United States Naval Observatory and their Astronomical Almanac to within 0.0005 arcseconds (half a mas or milliarcsecond).
Orbital is a high level orbital mechanics package for Python.
Python read-only implementation of the EventIO file format.
This package provides a replacement for IRAF STSDAS SYNPHOT and ASTROLIB PYSYNPHOT, utilizing Astropy covering instrument specific portions of the old packages for HST.
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 spherical_geometry library is a Python package for handling spherical polygons that represent arbitrary regions of the sky.
Pymcfost is a Python interface to the 3D radiative transfer code MCFOST. The goal is to provide a simple and light interface to explore and plot a single (or a few) model(s).
This package provides an astronomical image processing tool - SIRIL. It is specially tailored for noise reduction and improving the signal/noise ratio of an image from multiple captures, as required in astronomy. SIRIL can align automatically or manually, stack and enhance pictures from various file formats, even image sequence files (films and SER files). It works well with limited system resources, like in embedded platforms, but is also very fast when run on more powerful computers and provides conversion to FITS from a large number of image formats.
This package implements a functionality to parse DS9 region files.
SunPy is package for solar physics and is meant to be a free alternative to the SolarSoft data analysis environment.
It includes an interface for searching and downloading data from multiple data providers, data containers for image and time series data, commonly used solar coordinate frames and associated transformations, as well as other functionality needed for solar data analysis.
pixell is a library for loading, manipulating and analyzing maps stored in rectangular pixelization. It is mainly intended for use with maps of the sky (e.g. CMB intensity and polarization maps, stacks of 21 cm intensity maps, binned galaxy positions or shear) in cylindrical projection, but its core functionality is more general.
INDI (Instrument-Neutral Device Interface) is a distributed XML-based control protocol designed to operate astronomical instrumentation. INDI is small, flexible, easy to parse, scalable, and stateless. It supports common DCS functions such as remote control, data acquisition, monitoring, and a lot more.
This package implements a functionality for analysing absorption and emission lines in 1-D spectra, especially galaxy and quasar spectra.
Photutils is an Astropy package for detection and photometry of astronomical sources.
This repository contains programs which can be used to compute properties of halos in spherical apertures in SWIFT snapshots. The resulting output halo catalogues can be read using the swiftsimio Python package.
The spectral-cube package provides an easy way to read, manipulate, analyze, and write data cubes with two positional dimensions and one spectral dimension, optionally with Stokes parameters.
It provides the following main features:
A uniform interface to spectral cubes, robust to the wide range of conventions of axis order, spatial projections, and spectral units that exist in the wild.
Easy extraction of cube sub-regions using physical coordinates.
Ability to easily create, combine, and apply masks to datasets.
Basic summary statistic methods like moments and array aggregates.
Designed to work with datasets too large to load into memory.
Python package for reading and analyzing simulations generated using the Gizmo code, in particular, the FIRE cosmological simulations.
SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of NumPy and MatPlotLib packages.
This package provides astronomical interstellar dust extinction curves implemented using the astropy.modeling framework.
Pynbody is an analysis framework for N-body and hydrodynamic astrophysical simulations supporting PKDGRAV/Gasoline, Gadget, Gadget4/Arepo, N-Chilada and RAMSES AMR outputs.
This package provides a Python implementation for computations of the position and velocity of an earth-orbiting satellite, given the satellite’s TLE orbital elements from a source like https://celestrak.org/.
It implements the most recent version of SGP4, and is regularly run against the SGP4 test suite to make sure that its satellite position predictions agree to within 0.1 mm with the predictions of the standard distribution of the algorithm. This error is far less than the 1–3 km/day by which satellites themselves deviate from the ideal orbits described in TLE files.
This package provides a Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.
Features:
pulsar transmission functions
inverse-noise-weighted transmission functions
individual pulsar sensitivity curves
pulsar timing array sensitivity curves as characteristic strain, strain sensitivity or energy density
power-law integrated sensitivity curves
sensitivity sky maps for pulsar timing arrays
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