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.

_images/GalPaK_cube_1101_from_paper_fig2.png

Authors

Acknowledgments

If you use GalPak3D in a publication, please cite Bouche et al. (2015) and link to http://galpak.irap.omp.eu. 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%.

Indices and tables