mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-10-18 20:15:05 +02:00
f1dbe6f03f
* Add verbosity statements * More verbosity * Save masses too * Add CDF new plot * Blank line * Fix RVS sampling bug * Add R200 conversion * Simplify plotting routines * Remove imoprt
103 lines
3.5 KiB
Python
103 lines
3.5 KiB
Python
# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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"""
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Script to find the nearest neighbour of each halo in a given halo catalogue
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from the remaining catalogues in the suite (CSIBORG or Quijote). The script is
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MPI parallelized over the reference simulations.
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"""
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from argparse import ArgumentParser
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from datetime import datetime
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from distutils.util import strtobool
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import numpy
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import yaml
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from mpi4py import MPI
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from taskmaster import work_delegation
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from utils import open_catalogues
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try:
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import csiborgtools
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except ModuleNotFoundError:
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import sys
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sys.path.append("../")
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import csiborgtools
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def find_neighbour(args, nsim, cats, paths, comm):
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"""
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Find the nearest neighbour of each halo in the given catalogue.
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Parameters
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----------
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args : argparse.Namespace
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Command line arguments.
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nsim : int
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Simulation index.
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cats : dict
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Dictionary of halo catalogues. Keys are simulation indices, values are
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the catalogues.
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paths : csiborgtools.paths.Paths
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Paths object.
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comm : mpi4py.MPI.Comm
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MPI communicator.
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Returns
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-------
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None
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"""
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ndist, cross_hindxs = csiborgtools.match.find_neighbour(nsim, cats)
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mass_key = "totpartmass" if args.simname == "csiborg" else "group_mass"
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cat0 = cats[nsim]
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mass = cat0[mass_key]
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rdist = cat0.radial_distance(in_initial=False)
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fout = paths.cross_nearest(args.simname, args.run, nsim)
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if args.verbose:
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print(f"Rank {comm.Get_rank()} writing to `{fout}`.", flush=True)
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numpy.savez(fout, ndist=ndist, cross_hindxs=cross_hindxs, mass=mass,
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ref_hindxs=cat0["index"], rdist=rdist)
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if __name__ == "__main__":
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parser = ArgumentParser()
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parser.add_argument("--run", type=str, help="Run name")
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parser.add_argument("--simname", type=str, choices=["csiborg", "quijote"],
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help="Simulation name")
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parser.add_argument("--nsims", type=int, nargs="+", default=None,
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help="Indices of simulations to cross. If `-1` processes all simulations.") # noqa
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parser.add_argument("--Rmax", type=float, default=155/0.705,
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help="High-resolution region radius")
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parser.add_argument("--verbose", type=lambda x: bool(strtobool(x)),
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default=False)
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args = parser.parse_args()
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with open("./match_finsnap.yml", "r") as file:
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config = yaml.safe_load(file)
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comm = MPI.COMM_WORLD
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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cats = open_catalogues(args, config, paths, comm)
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def do_work(nsim):
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return find_neighbour(args, nsim, cats, paths, comm)
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work_delegation(do_work, list(cats.keys()), comm,
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master_verbose=args.verbose)
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comm.Barrier()
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if comm.Get_rank() == 0:
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print(f"{datetime.now()}: all finished. Quitting.")
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