HOP halo finder.
Halos are built by: 1. Calculating a density for each particle based on a smoothing kernel. 2. Recursively linking particles to other particles from lower density particles to higher. 3. Geometrically proximate chains are identified and 4. merged into final halos following merging rules.
Lower thresholds generally produce more halos, and the largest halos become larger. Also, halos become more filamentary and over-connected.
Eisenstein and Hut. “HOP: A New Group-Finding Algorithm for N-Body Simulations.” ApJ (1998) vol. 498 pp. 137-142
Parameters : | pf : EnzoStaticOutput object threshold : float
dm_only : bool
padding : float
Examples : ——- : >>> pf = load(“RedshiftOutput0000”) : >>> halos = HaloFinder(pf) : |
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Methods
nearest_neighbors_2D(haloID[, ...]) | For a halo its nearest neighbors in 2D using the kd tree. |
nearest_neighbors_3D(haloID[, ...]) | For a halo its nearest neighbors in 3D using the kd tree. |
write_out(filename) | Write out standard halo information to a text file. |
write_particle_lists(prefix) | Write out the particle data for halos to HDF5 files. |
write_particle_lists_txt(prefix) | Write out the names of the HDF5 files containing halo particle data |