mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-10-19 05:35:05 +02:00
2e99b901ac
* rm get_positions * Add comment * add halfwidth func * Update docs * Add imprt * Evaluate multiple fields simulatenously * add halfwidth selection * Change order of grav field and tensor field * Add gravitational field norm * Add eigenvalue calculation * Sorted eigenvalues * add init script * add progress * Add surveys * Add more survey flexibility * Minor changes * add survey names * rm name * Fix list bug * Fig bugs when running the script * add phi to dtype * fix dump bug * Add comment * Add smoothing options * Add further comment * Update TODO
121 lines
3.8 KiB
Python
121 lines
3.8 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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NOTE:
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- Calculate for the entire box or just for a smaller region?
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- Add argparser for different options.
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- In the argparser add options to smoothen the field.
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"""
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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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halfwidth = 0.5
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MAS = "CIC"
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grid = 256
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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 = "SDSS"
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survey = utils.surveys[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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ftemp = join(utils.dumpdir, "temp_fields", "out_" + survey.name + "_{}.npy")
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fperm = join(utils.dumpdir, "fields", "out_{}.npy".format(survey.name))
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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[:10]
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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 halfwidth < 0.5:
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particles = csiborgtools.read.halfwidth_select(halfwidth, particles)
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length = box.box2mpc(2 * 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, 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(grid, 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(grid, 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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