Welcome to GalPaK’s documentation!

GalPaK 3D is a tool to extract Galaxy Parameters and Kinematics from 3-Dimensional data, using reverse deconvolution with the Bayesian analysis procedure Markov Chain Monte Carlo.




If you use GalPak3D in a publication, please cite Bouche et al. 2015 and link to the ACL entry http://www.ascl.net/1501.014 Please also send me a reference to your paper.

Do’s and Don’t

The algorithm should never be used blindly and we stress that one should always
  1. look at the convergence of the parameters using plot_mcmc(),
  2. investigate possible covariance in the parameters using plot_correlations() and/or fix a parameter with the option known_parameters to remove the degenerancy,
  3. adjust the MCMC algorithm with the option random_scale (lower than 1 [default] for higher acceptance rate and vice versa) to ensure an acceptance rate of 30 to 50%.

Parameters description

A description of the parameters meaning can be found here

Indices and tables