This Fortran code performs tensor classification on finite element hydrodynamics simulations - currently smoothed particle hydrodynamics (SPH) simulations only
Science using these algorithms was first published in Forgan et al (2016), Monthly Notices of the Royal Astronomical Society, Volume 457, Issue 3, p.2501-2513, DOI: 10.1093/mnras/stw103
HEALTH WARNING: This is a heavily refactored combination of several codes used in the above work, and as such is still in testing
- Reads in SPH snapshot files (currently sphNG formats only)
- Computes neighbour lists for SPH data (assuming snapshot's smoothing lengths)
- Computes either the (symmetric) velocity shear tensor or tidal tensor, and their eigenvalues/eigenvectors
- Classifies fluid elements by number of "positive" eigenvalues
- Permits decomposition of snapshots into classified components
- Python plotting scripts
- Spiral Fitting Algorithms (Forgan et al, in review)
- Ability to read in more SPH file formats
- Ability to process grid, Voronoi and meshless simulations
- Fortran compiler (gfortran recommended) and Makefile software (e.g. gmake)
- Python for plotting scripts (scripts developed in Python 2.7) - dependencies include numpy, matplotlib and f2py
To compile the code, navigate to the src/ directly and type
> make
to compile the main program
Once compiled, the code is executed with the command
> ./tache
The code reads in a single input parameter file tache.params, which should be modified before execution
The accompanying spiralfind program is compiled via
>make spiralfind
and run by
>./spiralfind
Which reads in spiralfind.params upon execution.
Example parameter files for both tache and spiralfind are available in the paramfiles directory