# Copyright (C) 2023 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 calculate the enclosed mass or bulk flow at different distances from the center of the box directly from the particles. Note that the velocity of an observer is not being subtracted from the bulk flow. The script is not parallelized in any way but it should not take very long, the main bottleneck is reading the data from disk. """ from argparse import ArgumentParser from datetime import datetime from gc import collect from os.path import join import numpy as np from astropy import units as u from astropy.coordinates import CartesianRepresentation, SkyCoord from tqdm import tqdm import csiborgtools from csiborgtools import fprint from csiborgtools.field import (field_enclosed_mass, particles_enclosed_mass, particles_enclosed_momentum) ############################################################################### # Read in information about the simulation # ############################################################################### def t(): return datetime.now() def get_reader(simname, paths, nsim): """Get the appropriate snapshot reader for the simulation.""" if simname == "csiborg1": nsnap = max(paths.get_snapshots(nsim, simname)) reader = csiborgtools.read.CSiBORG1Snapshot(nsim, nsnap, paths, flip_xz=True) elif "csiborg2" in simname: kind = simname.split("_")[-1] reader = csiborgtools.read.CSiBORG2Snapshot(nsim, 99, kind, paths, flip_xz=True) elif simname == "manticore_2MPP_N128_DES_V1": reader = csiborgtools.read.CSiBORG2XSnapshot(nsim) else: raise ValueError(f"Unknown simname: `{simname}`.") return reader def get_particles(reader, boxsize, get_velocity=True, verbose=True): """Get the snapshot particles.""" fprint("reading coordinates and calculating radial distance.", verbose) pos = reader.coordinates() dtype = pos.dtype pos -= boxsize / 2 dist = np.linalg.norm(pos, axis=1).astype(dtype) collect() if get_velocity: fprint("reading velocities.", verbose) vel = reader.velocities().astype(dtype) vrad = np.sum(pos * vel, axis=1) / dist del pos collect() fprint("reading masses.") mass = reader.masses() fprint("sorting arrays.") indxs = np.argsort(dist) dist = dist[indxs] mass = mass[indxs] if get_velocity: vel = vel[indxs] del indxs collect() if get_velocity: return dist, mass, vel, vrad return dist, mass ############################################################################### # Main # ############################################################################### def main_borg(args, folder): paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) boxsize = csiborgtools.simname2boxsize(args.simname) nsims = paths.get_ics(args.simname) distances = np.linspace(0, boxsize / 2, 101) cumulative_mass = np.zeros((len(nsims), len(distances))) cumulative_volume = np.zeros((len(nsims), len(distances))) for i, nsim in enumerate(tqdm(nsims, desc="Simulations")): if args.simname == "borg1": reader = csiborgtools.read.BORG1Field(nsim) field = reader.density_field() elif args.simname == "borg2" or args.simname == "borg2_all": reader = csiborgtools.read.BORG2Field(nsim) field = reader.density_field() else: raise ValueError(f"Unknown simname: `{args.simname}`.") cumulative_mass[i, :], cumulative_volume[i, :] = field_enclosed_mass( field, distances, boxsize) # Finally save the output fname = f"enclosed_mass_{args.simname}.npz" fname = join(folder, fname) np.savez(fname, enclosed_mass=cumulative_mass, distances=distances, enclosed_volume=cumulative_volume) def main_csiborg(args, folder): paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) boxsize = csiborgtools.simname2boxsize(args.simname) nsims = paths.get_ics(args.simname) distances = np.linspace(0, boxsize / 2, 501)[1:] # Initialize arrays to store the results cumulative_mass = np.zeros((len(nsims), len(distances))) mass135 = np.zeros(len(nsims)) masstot = np.zeros(len(nsims)) cumulative_vel_mono = np.zeros((len(nsims), len(distances))) cumulative_velocity = np.zeros((len(nsims), len(distances), 3)) for i, nsim in enumerate(tqdm(nsims, desc="Simulations")): reader = get_reader(args.simname, paths, nsim) rdist, mass, vel, vrad = get_particles(reader, boxsize, verbose=True) # Calculate masses cumulative_mass[i, :] = particles_enclosed_mass(rdist, mass, distances) mass135[i] = particles_enclosed_mass(rdist, mass, [135])[0] masstot[i] = np.sum(mass) # Calculate monopole momentum cumulative_vel_mono[i] = particles_enclosed_mass( rdist, vrad * mass, distances) # Calculate velocities cumulative_velocity[i, ...] = particles_enclosed_momentum( rdist, mass, vel, distances) # Normalize the momentum to get velocity out of it. for j in range(3): cumulative_velocity[i, :, j] /= cumulative_mass[i, :] cumulative_vel_mono[i, ...] /= cumulative_mass[i, ...] # Finally save the output fname = f"enclosed_mass_{args.simname}.npz" fname = join(folder, fname) np.savez(fname, enclosed_mass=cumulative_mass, mass135=mass135, masstot=masstot, distances=distances, cumulative_velocity=cumulative_velocity, cumulative_velocity_mono=cumulative_vel_mono) def main_from_field(args, folder): """Bulk flows in 3D fields""" paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) boxsize = csiborgtools.simname2boxsize(args.simname) nsims = paths.get_ics(args.simname) distances = np.linspace(0, boxsize / 2, 101)[1:] cumulative_mass = np.zeros((len(nsims), len(distances))) cumulative_volume = np.zeros((len(nsims), len(distances))) cumulative_vel_mono = np.zeros((len(nsims), len(distances))) cumulative_vel_x = np.zeros((len(nsims), len(distances))) cumulative_vel_y = np.zeros_like(cumulative_vel_x) cumulative_vel_z = np.zeros_like(cumulative_vel_x) for i, nsim in enumerate(tqdm(nsims, desc="Simulations")): if args.simname == "csiborg2X": reader = csiborgtools.read.CSiBORG2XField(nsim, paths) kwargs = {} elif args.simname == "CF4": reader = csiborgtools.read.CF4Field(nsim, paths) kwargs = {} elif args.simname == "CLONES": reader = csiborgtools.read.CLONESField(nsim, paths) kwargs = {"MAS": "SPH", "grid": 1024} elif args.simname == "Carrick2015": reader = csiborgtools.read.Carrick2015Field(paths) kwargs = {} elif args.simname == "Lilow2024": reader = csiborgtools.read.Lilow2024Field(paths) kwargs = {} else: raise ValueError(f"Unknown simname: `{args.simname}`.") density_field = reader.density_field(**kwargs) cumulative_mass[i, :], cumulative_volume[i, :] = field_enclosed_mass( density_field, distances, boxsize, verbose=False) del density_field collect() velocity_field = reader.velocity_field(**kwargs) radial_velocity_field = csiborgtools.field.radial_velocity( velocity_field, [0., 0., 0.]) cumulative_vel_mono[i, :], __ = field_enclosed_mass( radial_velocity_field, distances, boxsize, verbose=False) del radial_velocity_field collect() cumulative_vel_x[i, :], __ = field_enclosed_mass( velocity_field[0], distances, boxsize, verbose=False) cumulative_vel_y[i, :], __ = field_enclosed_mass( velocity_field[1], distances, boxsize, verbose=False) cumulative_vel_z[i, :], __ = field_enclosed_mass( velocity_field[2], distances, boxsize, verbose=False) del velocity_field collect() if args.simname in ["Carrick2015", "Lilow2024"]: # Carrick+2015 and Lilow+2024 box is in galactic coordinates, so we # need to convert the bulk flow vector to RA/dec Cartesian # representation. galactic_cartesian = CartesianRepresentation( cumulative_vel_x, cumulative_vel_y, cumulative_vel_z, unit=u.km/u.s) galactic_coord = SkyCoord(galactic_cartesian, frame='galactic') icrs_cartesian = galactic_coord.icrs.cartesian cumulative_vel_x = icrs_cartesian.x.to(u.km/u.s).value cumulative_vel_y = icrs_cartesian.y.to(u.km/u.s).value cumulative_vel_z = icrs_cartesian.z.to(u.km/u.s).value if args.simname in ["CLONES", "CF4"]: # CLONES is in supergalactic coordinates. supergalactic_cartesian = CartesianRepresentation( cumulative_vel_x, cumulative_vel_y, cumulative_vel_z, unit=u.km/u.s) supergalactic_coord = SkyCoord( supergalactic_cartesian, frame='supergalactic') icrs_cartesian = supergalactic_coord.icrs.cartesian cumulative_vel_x = icrs_cartesian.x.to(u.km/u.s).value cumulative_vel_y = icrs_cartesian.y.to(u.km/u.s).value cumulative_vel_z = icrs_cartesian.z.to(u.km/u.s).value cumulative_vel = np.stack( [cumulative_vel_x, cumulative_vel_y, cumulative_vel_z], axis=-1) cumulative_vel /= cumulative_volume[..., None] cumulative_vel_mono /= cumulative_volume # Finally save the output fname = f"enclosed_mass_{args.simname}.npz" fname = join(folder, fname) print(f"Saving to `{fname}`.") np.savez(fname, enclosed_mass=cumulative_mass, distances=distances, cumulative_velocity_mono=cumulative_vel_mono, cumulative_velocity=cumulative_vel, enclosed_volume=cumulative_volume) ############################################################################### # Command line interface # ############################################################################### if __name__ == "__main__": parser = ArgumentParser() parser.add_argument("--simname", type=str, help="Simulation name.", choices=["csiborg1", "csiborg2_main", "csiborg2_varysmall", "csiborg2_random", # noqa "borg1", "borg2", "borg2_all", "csiborg2X", "Carrick2015", # noqa "Lilow2024", "CLONES", "CF4", "manticore_2MPP_N128_DES_V1"]) # noqa args = parser.parse_args() folder = "/mnt/extraspace/rstiskalek/csiborg_postprocessing/field_shells" if args.simname in ["csiborg2X", "Carrick2015", "Lilow2024", "CLONES", "CF4"]: main_from_field(args, folder) elif "csiborg" in args.simname or args.simname == "manticore_2MPP_N128_DES_V1": # noqa main_csiborg(args, folder) elif "borg" in args.simname: main_borg(args, folder) else: raise ValueError(f"Unknown simname: `{args.simname}`.")