Reverse Dependencies of PyAstronomy

The following projects have a declared dependency on PyAstronomy:

• astroemperor — PTMCMC sampler for exoplanet search
• CWITools — Analysis and Reduction Tools for PCWI/KCWI Data
• EclipsingBinaries — "Binary Star Package for Ball State University's Astronomy Research Group"
• Formosa — ForMoSA: Forward Modeling Tool for Spectral Analysis
• genepy3d — Python Library for 3D Quantitative Geometry in Computation Microscopy
• juice-geopipeline — no summary
• lagrange-points — un paquete para encontrar y graficar los puntos de Lagrange y potenciales de Roche de dos cuerpos
• LagRochePlot — Herramienta gráfica para visualizar los puntos de Lagrange y potencial de Roche.
• NGSF — Next Generation SuperFit in Python
• orbitronomy — The Orbitronomy library is designed to simplify the process of plotting, calculating, visualizing, and animating the orbits of celestial bodies in 3D space. It employs Kepler's elliptical orbit equations and Keplerian Elements, in conjunction with PyAstronomy, to perform precise orbital calculations. For 3D plotting, it integrates the capabilities of Matplotlib, enhancing its utility in astronomical simulations and analyses.
• platypos — PLAneTarY PhOtoevaporation Simulator
• pycrires — Data reduction pipeline for VLT/CRIRES+
• pydynamicalc — Pythonic photodynamical model generator, using three different configurations (quasi-circular, eccentric and osculating), in addition - an MCMC-coupled version is also provided, which allows optimization of planetary masses and eccentricities
• PyXCSAO — Replicates functionality of IRAF XCSAO
• reddutils — Small package for personal use
• reddutils-test — Small package for personal use
• species — Toolkit for atmospheric characterization of directly imaged exoplanets
• spectrum-overload — Spectrum class that overloads operators.
• SpotDIPy — An Easy Way for Stellar Doppler Imaging of Cool Single Stars
• tsanalysis — Machine Learning library for time series analysis
• verapy — velocidades radiais
• zfinder — Redshift finding algorithm