Gundam is a package to count pairs and calculate spatial two-point correlation functions of large galaxy samples. Its main features are :
- Speed
By calling Fortran routines that implement efficient skip-list/linked-list algorithms, Gundam can be extremely fast
- Parallel
Can automatically run in parallel to use all cores available. It employs the OpenMP framework to make use of multi-core CPUs
- User-friendly
By carefully wrapping Fortran code in a suitable Python framework, Gundam is very easy to use. A typical run consists of just 3 lines of code : (1) read data, (2) define parameters, (3) get counts
- Error estimates, user-defined weights, fiber corrections
Gundam can estimate bootstrap errors, weight pair counts, and even correct counts for fiber collisions
- Plotting functions
Gundam can produce nice, paper ready plots for 1D and 2D correlations, complete with ratios, labels and even power-law fits
- Extensible
Desgined in 3 layers of main, auxiliary and wrapper routines, it is quite easy to extend functionality by novice as well as seasoned users
Pair counts and correlation functions can be saved in ASCII files, as well as in a dictionary-like object that holds all calculations, input parameters and log messages. Share this object with your collaborators instead of just the final plot.
Though intended primarily for redshift surveys, it can also be adapted for simulation data and ultimately for any set of points in space.
@author: Emilio Donoso <edonoso@conicet.gov.ar>