csiborgtools/scripts/run_initmatch.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 calculate the centre of mass of particles at redshift 70 that
are grouped in a clump at present redshift.

Optionally also dumps the clumps information, however watch out as this will
eat up a lot of memory.
"""
import numpy
from argparse import ArgumentParser
from distutils.util import strtobool
from datetime import datetime
from mpi4py import MPI
from os.path import join
from os import remove
from gc import collect
try:
    import csiborgtools
except ModuleNotFoundError:
    import sys
    sys.path.append("../")
    import csiborgtools

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

# Argument parser
parser = ArgumentParser()
parser.add_argument("--dump_clumps", type=lambda x: bool(strtobool(x)))
args = parser.parse_args()

init_paths = csiborgtools.read.CSiBORGPaths(to_new=True)
fin_paths = csiborgtools.read.CSiBORGPaths(to_new=False)
nsims = init_paths.ic_ids

# Output files
dumpdir = "/mnt/extraspace/rstiskalek/csiborg/"
ftemp = join(dumpdir, "temp_initmatch", "temp_{}_{}_{}.npy")
fpermcm = join(dumpdir, "initmatch", "clump_{}_cm.npy")
fpermpart = join(dumpdir, "initmatch", "clump_{}_particles.npy")

for nsim in nsims:
    if rank == 0:
        print("{}: reading simulation {}.".format(datetime.now(), nsim),
              flush=True)

    # Set the snapshot numbers
    init_paths.set_info(nsim, init_paths.get_minimum_snapshot(nsim))
    fin_paths.set_info(nsim, fin_paths.get_maximum_snapshot(nsim))
    # Set the readers
    init_reader = csiborgtools.read.ParticleReader(init_paths)
    fin_reader = csiborgtools.read.ParticleReader(fin_paths)

    # Read and sort the initial particle files by their particle IDs
    part0 = init_reader.read_particle(["x", "y", "z", "M", "ID"],
                                      verbose=False)
    part0 = part0[numpy.argsort(part0["ID"])]

    # Order the final snapshot clump IDs by the particle IDs
    pid = fin_reader.read_particle(["ID"], verbose=False)["ID"]
    clump_ids = fin_reader.read_clumpid(verbose=False)
    clump_ids = clump_ids[numpy.argsort(pid)]

    del pid
    collect()

    # Get rid of the clumps whose index is 0 -- those are unassigned
    mask = clump_ids > 0
    clump_ids = clump_ids[mask]
    part0 = part0[mask]
    del mask
    collect()

    if rank == 0:
        print("{}: dumping intermediate files.".format(datetime.now()),
              flush=True)

    # Grab unique clump IDs and loop over them
    unique_clumpids = numpy.unique(clump_ids)

    njobs = unique_clumpids.size
    jobs = csiborgtools.fits.split_jobs(njobs, nproc)[rank]
    for i in jobs:
        n = unique_clumpids[i]
        x0 = part0[clump_ids == n]

        # Center of mass and Lagrangian patch size
        dist, cm = csiborgtools.match.dist_centmass(x0)
        patch = csiborgtools.match.dist_percentile(dist, [99], distmax=0.075)

        # Dump the center of mass
        with open(ftemp.format(nsim, n, "cm"), 'wb') as f:
            numpy.save(f, cm)
        # Dump the Lagrangian patch size
        with open(ftemp.format(nsim, n, "lagpatch"), 'wb') as f:
            numpy.save(f, patch)
        # Dump the entire clump
        if args.dump_clumps:
            with open(ftemp.format(nsim, n, "clump"), "wb") as f:
                numpy.save(f, x0)

    del part0, clump_ids
    collect()

    comm.Barrier()
    if rank == 0:
        print("{}: collecting summary files...".format(datetime.now()),
              flush=True)
        # Collect the centre of masses, patch size, etc. and dump them
        dtype = {"names": ['x', 'y', 'z', "lagpatch", "ID"],
                 "formats": [numpy.float32] * 4 + [numpy.int32]}
        out = numpy.full(njobs, numpy.nan, dtype=dtype)

        for i, n in enumerate(unique_clumpids):
            # Load in CM vector
            fpath = ftemp.format(nsim, n, "cm")
            with open(fpath, "rb") as f:
                fin = numpy.load(f)
                out['x'][i] = fin[0]
                out['y'][i] = fin[1]
                out['z'][i] = fin[2]
            remove(fpath)

            # Load in the patch size
            fpath = ftemp.format(nsim, n, "lagpatch")
            with open(fpath, "rb") as f:
                out["lagpatch"][i] = numpy.load(f)
            remove(fpath)

            # Store the halo ID
            out["ID"][i] = n

        print("{}: dumping to .. `{}`.".format(
            datetime.now(), fpermcm.format(nsim)), flush=True)
        with open(fpermcm.format(nsim), 'wb') as f:
            numpy.save(f, out)

        if args.dump_clumps:
            print("{}: collecting particle files...".format(datetime.now()),
                  flush=True)
            out = [None] * unique_clumpids.size
            dtype = {"names": ["clump", "ID"],
                     "formats": [object, numpy.int32]}
            out = numpy.full(unique_clumpids.size, numpy.nan, dtype=dtype)
            for i, n in enumerate(unique_clumpids):
                fpath = ftemp.format(nsim, n, "clump")
                with open(fpath, 'rb') as f:
                    fin = numpy.load(f)
                out["clump"][i] = fin
                out["ID"][i] = n
                remove(fpath)
            print("{}: dumping to .. `{}`.".format(
                datetime.now(), fpermpart.format(nsim)), flush=True)
            with open(fpermpart.format(nsim), "wb") as f:
                numpy.save(f, out)

            del out
            collect()