All Projects → threeML → astromodels

threeML / astromodels

Licence: BSD-3-Clause License
Spatial and spectral models for astrophysics

Programming Languages

python
139335 projects - #7 most used programming language
C++
36643 projects - #6 most used programming language
shell
77523 projects
Dockerfile
14818 projects

Projects that are alternatives of or similar to astromodels

sncosmo
Python library for supernova cosmology
Stars: ✭ 53 (+152.38%)
Mutual labels:  astronomy, astrophysics
amuse
Astrophysical Multipurpose Software Environment. This is the main repository for AMUSE
Stars: ✭ 115 (+447.62%)
Mutual labels:  astronomy, astrophysics
Virgo
📡 Virgo: A Versatile Spectrometer for Radio Astronomy
Stars: ✭ 85 (+304.76%)
Mutual labels:  astronomy, astrophysics
heyoka
C++ library for ODE integration via Taylor's method and LLVM
Stars: ✭ 151 (+619.05%)
Mutual labels:  astronomy, astrophysics
ldtk
Python toolkit for calculating stellar limb darkening profiles and model-specific coefficients using the stellar atmosphere spectrum library by Husser et al. (2013). Described in Parviainen & Aigrain, MNRAS 453, 3821–3826 (2015).
Stars: ✭ 26 (+23.81%)
Mutual labels:  astronomy, astrophysics
mwdust
Dust maps in the Milky Way
Stars: ✭ 21 (+0%)
Mutual labels:  astronomy, astrophysics
astrodash
Deep learning for the automated spectral classification of supernovae
Stars: ✭ 25 (+19.05%)
Mutual labels:  astronomy, astrophysics
naima
Derivation of non-thermal particle distributions through MCMC spectral fitting
Stars: ✭ 32 (+52.38%)
Mutual labels:  astronomy, astrophysics
yt astro analysis
yt astrophysical analysis modules
Stars: ✭ 18 (-14.29%)
Mutual labels:  astronomy, astrophysics
heyoka.py
Python library for ODE integration via Taylor's method and LLVM
Stars: ✭ 45 (+114.29%)
Mutual labels:  astronomy, astrophysics
PandExo
A Community Tool for Transiting Exoplanet Science with the JWST & HST
Stars: ✭ 23 (+9.52%)
Mutual labels:  astronomy, astrophysics
nmmn
Miscellaneous methods for: astronomy, dealing with arrays, statistical distributions, computing goodness-of-fit, numerical simulations and much more
Stars: ✭ 16 (-23.81%)
Mutual labels:  astronomy, astrophysics
phantom
Phantom Smoothed Particle Hydrodynamics and Magnetohydrodynamics code
Stars: ✭ 52 (+147.62%)
Mutual labels:  astronomy, astrophysics
kaggle-plasticc
Solution to Kaggle's PLAsTiCC Astronomical Classification Competition
Stars: ✭ 50 (+138.1%)
Mutual labels:  astronomy
TreeCorr
Code for efficiently computing 2-point and 3-point correlation functions. For documentation, go to
Stars: ✭ 85 (+304.76%)
Mutual labels:  astronomy
unity-excavator
Physical simulations on Unity
Stars: ✭ 20 (-4.76%)
Mutual labels:  astronomy
go-sunrise
Go package for calculating the sunrise and sunset times for a given location
Stars: ✭ 42 (+100%)
Mutual labels:  astronomy
Comet
A complete VOEvent transport system
Stars: ✭ 20 (-4.76%)
Mutual labels:  astronomy
ccd-reduction-and-photometry-guide
Read the CCD guide here:
Stars: ✭ 55 (+161.9%)
Mutual labels:  astronomy
P4J
Periodic time series analysis tools based on information theory
Stars: ✭ 42 (+100%)
Mutual labels:  astronomy

astromodels

CI codecov Documentation Status License GitHub contributors DOI

GitHub pull requests GitHub issues

PyPi

PyPI version fury.io PyPI - Downloads

Conda

Conda Conda

alt text

Astromodels is a very flexible framework to define models for likelihood or Bayesian analysis of astrophysical data.

Even though it has been designed having in mind analysis in the spectral domain, it can be used also as a toolbox containing functions of any variable.

Astromodels is not a modeling package, it only gives you the tools to build a model as complex as you need. You then need a separate package (such as 3ML) to fit that model to the data.

Some of the features which distinguish astromodels from other similar packages are: * a model can contain an arbitrary number of sources at different positions in the sky * parameters can be linked through any function (not only identity) * parameters can vary with auxiliary variables such as time. For example, you can build a model where some parameters vary with time, and you can fit the parameters of the function which describe this variability. Similary you can build models where parameters vary with the phase of a pulsar, and so on. * models can be saved in and loaded from YAML file (a human-readable format) * physical units are fully supported in input, but they are handled so that they don’t slow down the actualy computation of the models.

Astromodels has been designed with performance as priority, and is considerably faster than other python-based solution for the same problem, such as astropy.modeling and the modeling part of sherpa. Documentation: http://astromodels.readthedocs.org/en/latest/

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].