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