csiborgtools/scripts/run_fit_halos.py

# Copyright (C) 2022 Richard Stiskalek
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
"""
A script to fit halos (concentration, ...). The particle array of each CSiBORG
realisation must have been split in advance by `run_split_halos`.
"""

import numpy
from datetime import datetime
from os.path import join
from mpi4py import MPI
try:
    import csiborgtools
except ModuleNotFoundError:
    import sys
    sys.path.append("../")
    import csiborgtools
import utils

F64 = numpy.float64
I64 = numpy.int64

# Simulations and their snapshot to analyze
Nsims = [9844]
Nsnap = 1016

# Get MPI things
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nproc = comm.Get_size()


dumpdir = utils.dumpdir
loaddir = join(utils.dumpdir, "temp")
cols_collect = [("npart", I64), ("totpartmass", F64), ("Rs", F64),
                ("rho0", F64), ("conc", F64), ("rmin", F64),
                ("rmax", F64), ("r200", F64), ("r500", F64),
                ("m200", F64), ("m500", F64)]

# NOTE later loop over sims too
Nsim = Nsims[0]
simpath = csiborgtools.io.get_sim_path(Nsim)
box = csiborgtools.units.BoxUnits(Nsnap, simpath)

jobs = csiborgtools.fits.split_jobs(utils.Nsplits, nproc)[rank]
for icount, Nsplit in enumerate(jobs):
    print("{}: rank {} working {} / {} jobs.".format(datetime.now(), rank,
                                                     icount + 1, len(jobs)))
    parts, part_clumps, clumps = csiborgtools.fits.load_split_particles(
        Nsplit, loaddir, Nsim, Nsnap, remove_split=False)

    N = clumps.size
    cols = [("index", I64), ("npart", I64), ("totpartmass", F64),
            ("Rs", F64), ("rho0", F64), ("conc", F64),
            ("rmin", F64), ("rmax", F64),
            ("r200", F64), ("r500", F64), ("m200", F64), ("m500", F64)]
    out = csiborgtools.utils.cols_to_structured(N, cols)
    out["index"] = clumps["index"]

    for n in range(N):
        # Pick clump and its particles
        xs = csiborgtools.fits.pick_single_clump(n, parts, part_clumps, clumps)
        clump = csiborgtools.fits.Clump.from_arrays(*xs, rhoc=box.box_rhoc)
        out["npart"][n] = clump.Npart
        out["rmin"][n] = clump.rmin
        out["rmax"][n] = clump.rmax
        out["totpartmass"][n] = clump.total_particle_mass

        # Spherical overdensity radii and masses
        rs, ms = clump.spherical_overdensity_mass([200, 500])
        out["r200"][n] = rs[0]
        out["r500"][n] = rs[1]
        out["m200"][n] = ms[0]
        out["m500"][n] = ms[1]

        # NFW profile fit
        if clump.Npart > 10 and numpy.isfinite(out["r200"][n]):
            nfwpost = csiborgtools.fits.NFWPosterior(clump)
            logRs, __ = nfwpost.maxpost_logRs()
            Rs = 10**logRs
            if not numpy.isnan(logRs):
                out["Rs"][n] = Rs
                out["rho0"][n] = nfwpost.rho0_from_Rs(Rs)
                out["conc"][n] = out["r200"][n] / Rs

    csiborgtools.io.dump_split(out, Nsplit, Nsim, Nsnap, dumpdir)

# Force all ranks to wait
comm.Barrier()
# Use the rank 0 to combine outputs for this CSiBORG realisation
if rank == 0:
    print("Collecting results!")
    out_collected = csiborgtools.io.combine_splits(
        utils.Nsplits, Nsim, Nsnap, utils.dumpdir, cols_collect,
        remove_splits=True, verbose=False)
    fname = join(utils.dumpdir, "ramses_out_{}_{}.npy"
                 .format(str(Nsim).zfill(5), str(Nsnap).zfill(5)))
    print("Saving results to `{}`.".format(fname))
    numpy.save(fname, out_collected)
    print("All finished! See ya!")