mirror of
https://github.com/Richard-Sti/csiborgtools.git
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f48eb6dcb0
* add radial position path * pep8 * Add basic fit profile dumping * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * Update TODO * Fix parts is None bug * Update nb
118 lines
4 KiB
Python
118 lines
4 KiB
Python
# Copyright (C) 2022 Richard Stiskalek
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# 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 split particles to individual files according to their clump. This is
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useful for calculating the halo properties directly from the particles.
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"""
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from datetime import datetime
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from gc import collect
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from glob import glob
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from os import remove
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from os.path import join
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import numpy
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from mpi4py import MPI
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from taskmaster import master_process, worker_process
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from tqdm import tqdm
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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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# Get MPI things
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comm = MPI.COMM_WORLD
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rank = comm.Get_rank()
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nproc = comm.Get_size()
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paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
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verbose = nproc == 1
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partcols = ["x", "y", "z", "vx", "vy", "vz", "M"]
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def do_split(nsim):
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nsnap = max(paths.get_snapshots(nsim))
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reader = csiborgtools.read.ParticleReader(paths)
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ftemp_base = join(
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paths.temp_dumpdir,
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"split_{}_{}".format(str(nsim).zfill(5), str(nsnap).zfill(5)),
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)
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ftemp = ftemp_base + "_{}.npz"
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# Load the particles and their clump IDs
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particles = reader.read_particle(nsnap, nsim, partcols, verbose=verbose)
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particle_clumps = reader.read_clumpid(nsnap, nsim, verbose=verbose)
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# Drop all particles whose clump index is 0 (not assigned to any clump)
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assigned_mask = particle_clumps != 0
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particle_clumps = particle_clumps[assigned_mask]
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particles = particles[assigned_mask]
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del assigned_mask
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collect()
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# Load the clump indices
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clumpinds = reader.read_clumps(nsnap, nsim, cols="index")["index"]
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# Some of the clumps have no particles, so we do not loop over them
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clumpinds = clumpinds[numpy.isin(clumpinds, particle_clumps)]
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# Loop over the clump indices and save the particles to a temporary file
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# every 10000 clumps. We will later read this back and combine into a
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# single file.
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out = {}
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for i, clind in enumerate(tqdm(clumpinds) if verbose else clumpinds):
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key = str(clind)
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out.update({str(clind): particles[particle_clumps == clind]})
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# REMOVE bump this back up
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if i % 10000 == 0 or i == clumpinds.size - 1:
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numpy.savez(ftemp.format(i), **out)
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out = {}
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# Clear up memory because we will be loading everything back
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del particles, particle_clumps, clumpinds
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collect()
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# Now load back in every temporary file, combine them into a single
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# dictionary and save as a single .npz file.
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out = {}
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for file in glob(ftemp_base + "*"):
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inp = numpy.load(file)
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for key in inp.files:
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out.update({key: inp[key]})
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remove(file)
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numpy.savez(paths.split_path(nsnap, nsim), **out)
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###############################################################################
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# MPI task delegation #
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###############################################################################
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if nproc > 1:
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if rank == 0:
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tasks = list(paths.get_ics(tonew=False))
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master_process(tasks, comm, verbose=True)
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else:
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worker_process(do_split, comm, verbose=False)
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else:
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tasks = paths.get_ics(tonew=False)
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for task in tasks:
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print("{}: completing task `{}`.".format(datetime.now(), task))
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do_split(task)
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comm.Barrier()
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