csiborgtools/scripts/field_prop.py

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# 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.
"""
MPI script to evaluate field properties at the galaxy positions.
"""
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from argparse import ArgumentParser
from datetime import datetime
from os import remove
from os.path import join
import numpy
from mpi4py import MPI
try:
import csiborgtools
except ModuleNotFoundError:
import sys
sys.path.append("../")
import csiborgtools
import utils
dumpdir = "/mnt/extraspace/rstiskalek/csiborg/"
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parser = ArgumentParser()
parser.add_argument("--survey", type=str, choices=["SDSS"])
parser.add_argument("--grid", type=int)
parser.add_argument("--MAS", type=str, choices=["NGP", "CIC", "TSC", "PCS"])
parser.add_argument("--halfwidth", type=float)
parser.add_argument("--smooth_scale", type=float, default=None)
args = parser.parse_args()
# Smooth scale of 0 means no smoothing. Note that this is in Mpc/h
args.smooth_scale = None if args.smooth_scale == 0 else args.smooth_scale
# Get MPI things
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nproc = comm.Get_size()
# Galaxy positions
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survey = utils.surveys[args.survey]()()
pos = numpy.vstack([survey[p] for p in ("DIST", "RA", "DEC")]).T
pos = pos.astype(numpy.float32)
# File paths
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fname = "out_{}_{}_{}_{}_{}".format(
survey.name, args.grid, args.MAS, args.halfwidth, args.smooth_scale)
ftemp = join(dumpdir, "temp_fields", fname + "_{}.npy")
fperm = join(dumpdir, "fields", fname + ".npy")
# Edit depending on what is calculated
dtype = {"names": ["delta", "phi"], "formats": [numpy.float32] * 2}
# CSiBORG simulation paths
paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
ics = paths.get_ics(tonew=False)
nsims = len(ics)
for n in csiborgtools.utils.split_jobs(nsims, nproc)[rank]:
print("Rank {}@{}: working on {}th IC.".format(rank, datetime.now(), n),
flush=True)
nsim = ics[n]
nsnap = max(paths.get_snapshots(nsim))
reader = csiborgtools.read.ParticleReader(paths)
box = csiborgtools.read.BoxUnits(nsnap, nsim, paths)
# Read particles and select a subset of them
particles = reader.read_particle(nsnap, nsim, ["x", "y", "z", "M"],
verbose=False)
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if args.halfwidth < 0.5:
particles = csiborgtools.read.halfwidth_select(
args.halfwidth, particles)
length = box.box2mpc(2 * args.halfwidth) * box.h # Mpc/h
else:
length = box.box2mpc(1) * box.h # Mpc/h
# Initialise the field object and output array
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field = csiborgtools.field.DensityField(particles, length, box, args.MAS)
out = numpy.full(pos.shape[0], numpy.nan, dtype=dtype)
# Calculate the overdensity field and interpolate at galaxy positions
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feval = field.overdensity_field(args.grid, args.smooth_scale,
verbose=False)
out["delta"] = field.evaluate_sky(feval, pos=pos, isdeg=True)[0]
# Potential
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feval = field.potential_field(args.grid, args.smooth_scale, verbose=False)
out["phi"] = field.evaluate_sky(feval, pos=pos, isdeg=True)[0]
# Calculate the remaining fields
# ...
# ...
# Dump the results
with open(ftemp.format(nsim), "wb") as f:
numpy.save(f, out)
# Wait for all ranks to finish
comm.Barrier()
if rank == 0:
print("Collecting files...", flush=True)
out = numpy.full((nsims, pos.shape[0]), numpy.nan, dtype=dtype)
for n in range(nsims):
nsim = ics[n]
with open(ftemp.format(nsim), "rb") as f:
fin = numpy.load(f, allow_pickle=True)
for name in dtype["names"]:
out[name][n, ...] = fin[name]
# Remove the temporary file
remove(ftemp.format(nsim))
print("Saving results to `{}`.".format(fperm), flush=True)
with open(fperm, "wb") as f:
numpy.save(f, out)