csiborgtools/scripts/fit_halos.py
Richard Stiskalek f48eb6dcb0
Dump radial profile information (#48)
* 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
2023-04-27 00:18:30 +01:00

208 lines
7.7 KiB
Python

# 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 `runsplit_halos`.
"""
from argparse import ArgumentParser
from datetime import datetime
from os.path import join
import numpy
from mpi4py import MPI
from tqdm import tqdm
try:
import csiborgtools
except ModuleNotFoundError:
import sys
sys.path.append("../")
import csiborgtools
parser = ArgumentParser()
parser.add_argument("--kind", type=str, choices=["halos", "clumps"])
args = parser.parse_args()
# Get MPI things
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nproc = comm.Get_size()
paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
partreader = csiborgtools.read.ParticleReader(paths)
nfwpost = csiborgtools.fits.NFWPosterior()
ftemp = join(paths.temp_dumpdir, "fit_clump_{}_{}_{}.npy")
cols_collect = [
("index", numpy.int32),
("npart", numpy.int32),
("totpartmass", numpy.float32),
("vx", numpy.float32),
("vy", numpy.float32),
("vz", numpy.float32),
("conc", numpy.float32),
("rho0", numpy.float32),
("r200c", numpy.float32),
("r500c", numpy.float32),
("m200c", numpy.float32),
("m500c", numpy.float32),
("lambda200c", numpy.float32),
("r200m", numpy.float32),
("m200m", numpy.float32),
]
def fit_clump(particles, clump_info, box):
"""
Fit an object. Can be eithe a clump or a parent halo.
"""
obj = csiborgtools.fits.Clump(particles, clump_info, box)
out = {}
out["npart"] = len(obj)
out["totpartmass"] = numpy.sum(obj["M"])
for i, v in enumerate(["vx", "vy", "vz"]):
out[v] = numpy.average(obj.vel[:, i], weights=obj["M"])
# Overdensity masses
out["r200c"], out["m200c"] = obj.spherical_overdensity_mass(200,
kind="crit")
out["r500c"], out["m500c"] = obj.spherical_overdensity_mass(500,
kind="crit")
out["r200m"], out["m200m"] = obj.spherical_overdensity_mass(200,
kind="matter")
# NFW fit
if out["npart"] > 10 and numpy.isfinite(out["r200c"]):
Rs, rho0 = nfwpost.fit(obj)
out["conc"] = Rs / out["r200c"]
out["rho0"] = rho0
# Spin within R200c
if numpy.isfinite(out["r200c"]):
out["lambda200c"] = obj.lambda_bullock(out["r200c"])
return out
def load_clump_particles(clumpid, particle_archive):
"""
Load a clump's particles from the particle archive. If it is not there, i.e
clump has no associated particles, return `None`.
"""
try:
part = particle_archive[str(clumpid)]
except KeyError:
part = None
return part
def load_parent_particles(clumpid, particle_archive, clumps_cat):
"""
Load a parent halo's particles.
"""
indxs = clumps_cat["index"][clumps_cat["parent"] == clumpid]
# We first load the particles of each clump belonging to this parent
# and then concatenate them for further analysis.
clumps = []
for ind in indxs:
parts = load_clump_particles(ind, particle_archive)
if parts is not None:
clumps.append([parts, None])
if len(clumps) == 0:
return None
return csiborgtools.match.concatenate_parts(clumps,
include_velocities=True)
# We now start looping over all simulations
for i, nsim in enumerate(paths.get_ics(tonew=False)):
if rank == 0:
print(f"{datetime.now()}: calculating {i}th simulation `{nsim}`.",
flush=True)
nsnap = max(paths.get_snapshots(nsim))
box = csiborgtools.read.BoxUnits(nsnap, nsim, paths)
# Archive of clumps, keywords are their clump IDs
particle_archive = numpy.load(paths.split_path(nsnap, nsim))
clumps_cat = csiborgtools.read.ClumpsCatalogue(nsim, paths, maxdist=None,
minmass=None, rawdata=True,
load_fitted=False)
# We check whether we fit halos or clumps, will be indexing over different
# iterators.
if args.kind == "halos":
ismain = clumps_cat.ismain
else:
ismain = numpy.ones(len(clumps_cat), dtype=bool)
ntasks = len(clumps_cat)
# We split the clumps among the processes. Each CPU calculates a fraction
# of them and dumps the results in a structured array. Even if we are
# calculating parent halo this index runs over all clumps.
jobs = csiborgtools.fits.split_jobs(ntasks, nproc)[rank]
out = csiborgtools.read.cols_to_structured(len(jobs), cols_collect)
for i, j in enumerate(tqdm(jobs)) if nproc == 1 else enumerate(jobs):
clumpid = clumps_cat["index"][j]
out["index"][i] = clumpid
# If we are fitting halos and this clump is not a main, then continue.
if args.kind == "halos" and not ismain[j]:
continue
if args.kind == "halos":
part = load_parent_particles(clumpid, particle_archive, clumps_cat)
else:
part = load_clump_particles(clumpid, particle_archive)
# We fit the particles if there are any. If not we assign the index,
# otherwise it would be NaN converted to integers (-2147483648) and
# yield an error further down.
if part is not None:
_out = fit_clump(part, clumps_cat[j], box)
for key in _out.keys():
out[key][i] = _out[key]
fout = ftemp.format(str(nsim).zfill(5), str(nsnap).zfill(5), rank)
if nproc == 0:
print(f"{datetime.now()}: rank {rank} saving to `{fout}`.", flush=True)
numpy.save(fout, out)
# We saved this CPU's results in a temporary file. Wait now for the other
# CPUs and then collect results from the 0th rank and save them.
comm.Barrier()
if rank == 0:
print(f"{datetime.now()}: collecting results for simulation `{nsim}`.",
flush=True)
# We write to the output array. Load data from each CPU and append to
# the output array.
out = csiborgtools.read.cols_to_structured(ntasks, cols_collect)
clumpid2outpos = {indx: i
for i, indx in enumerate(clumps_cat["index"])}
for i in range(nproc):
inp = numpy.load(ftemp.format(str(nsim).zfill(5),
str(nsnap).zfill(5), i))
for j, clumpid in enumerate(inp["index"]):
k = clumpid2outpos[clumpid]
for key in inp.dtype.names:
out[key][k] = inp[key][j]
# If we were analysing main halos, then remove array indices that do
# not correspond to parent halos.
if args.kind == "halos":
out = out[ismain]
fout = paths.structfit_path(nsnap, nsim, args.kind)
print(f"Saving to `{fout}`.", flush=True)
numpy.save(fout, out)
# We now wait before moving on to another simulation.
comm.Barrier()