From aaa14fc8802d9f4eb6b7f1e552c95efcf5ffa899 Mon Sep 17 00:00:00 2001 From: Richard Stiskalek Date: Wed, 13 Dec 2023 16:08:25 +0000 Subject: [PATCH] Add density field plot and start preparing CSiBORG2 (#94) * Add RAMSES2HDF5 conversion * Upload changes * Clean up * More clean up * updates * Little change * pep9 * Add basic SPH calculation for a snapshot * Add submit script * Remove echo * Little changes * Send off changes * Little formatting * Little updates * Add nthreads argument * Upload chagnes * Add nthreads arguemnts * Some local changes.. * Update scripts * Add submission script * Update script * Update params * Rename CSiBORGBox to CSiBORG1box * Rename CSiBORG1 reader * Move files * Rename folder again * Add basic plotting here * Add new skeletons * Move def * Update nbs * Edit directories * Rename files * Add units to converted snapshots * Fix empty dataset bug * Delete file * Edits to submission scripts * Edit paths * Update .gitignore * Fix attrs * Update weighting * Fix RA/dec bug * Add FORNAX cluster * Little edit * Remove boxes since will no longer need * Move func back * Edit to include sort by membership * Edit paths * Purge basic things * Start removing * Bring file back * Scratch * Update the rest * Improve the entire file * Remove old things * Remove old * Delete old things * Fully updates * Rename file * Edit submit script * Little things * Add print statement * Add here cols_to_structured * Edit halo cat * Remove old import * Add comment * Update paths manager * Move file * Remove file * Add chains --- .gitignore | 3 + csiborgtools/__init__.py | 17 +- csiborgtools/field/density.py | 10 +- csiborgtools/field/interp.py | 16 +- csiborgtools/field/utils.py | 7 +- csiborgtools/read/__init__.py | 6 +- csiborgtools/read/box_units.py | 276 ------- csiborgtools/read/halo_cat.py | 112 +-- csiborgtools/read/obs.py | 15 +- csiborgtools/read/paths.py | 491 ++++-------- csiborgtools/read/readsim.py | 631 --------------- csiborgtools/read/utils.py | 126 --- csiborgtools/utils.py | 2 +- notebooks/powerspectrum_test.ipynb | 2 +- old/cluster_crosspk.py | 4 +- old/fit_profiles.py | 2 +- old/mv_fofmembership.py | 2 +- old/pre_dumppart.py | 4 +- scripts/dump_to_ascii.py | 116 --- scripts/field_prop.py | 11 +- scripts/process_snapshot.py | 2 +- .../field_obs_vp.py | 0 scripts_independent/field_sph.py | 201 +++++ scripts_independent/field_sph.sh | 40 + scripts_independent/process_snapshot.py | 737 ++++++++++++++++++ scripts_independent/run_field_sph.py | 89 +++ scripts_independent/run_process_snapshot.py | 31 + scripts_independent/sort_ramseshdf5.py | 77 ++ scripts_plots/paper_environment.ipynb | 256 ++++++ scripts_plots/plot_data.py | 124 +-- 30 files changed, 1682 insertions(+), 1728 deletions(-) delete mode 100644 csiborgtools/read/box_units.py delete mode 100644 csiborgtools/read/readsim.py delete mode 100644 csiborgtools/read/utils.py delete mode 100644 scripts/dump_to_ascii.py rename {scripts => scripts_independent}/field_obs_vp.py (100%) create mode 100644 scripts_independent/field_sph.py create mode 100755 scripts_independent/field_sph.sh create mode 100644 scripts_independent/process_snapshot.py create mode 100644 scripts_independent/run_field_sph.py create mode 100644 scripts_independent/run_process_snapshot.py create mode 100644 scripts_independent/sort_ramseshdf5.py create mode 100644 scripts_plots/paper_environment.ipynb diff --git a/.gitignore b/.gitignore index 7a160cc..b305812 100644 --- a/.gitignore +++ b/.gitignore @@ -26,3 +26,6 @@ scripts_plots/*.sh notebooks/test.ipynb scripts/mgtree.py scripts/makemerger.py + +*.out +*/python.sh diff --git a/csiborgtools/__init__.py b/csiborgtools/__init__.py index 78f5862..3ddc9b6 100644 --- a/csiborgtools/__init__.py +++ b/csiborgtools/__init__.py @@ -20,11 +20,14 @@ from .utils import (center_of_mass, delta2ncells, number_counts, hms_to_degrees, dms_to_degrees, great_circle_distance) # noqa # Arguments to csiborgtools.read.Paths. -paths_glamdring = {"srcdir": "/mnt/extraspace/hdesmond/", - "postdir": "/mnt/extraspace/rstiskalek/CSiBORG/", - "borg_dir": "/users/hdesmond/BORG_final/", - "quijote_dir": "/mnt/extraspace/rstiskalek/Quijote", - } +paths_glamdring = { + "csiborg1_srcdir": "/mnt/extraspace/rstiskalek/csiborg1", + "csiborg2_main_srcdir": "/mnt/extraspace/rstiskalek/csiborg2_main", + "csiborg2_varysmall_srcdir": "/mnt/extraspace/rstiskalek/csiborg2_varysmall", # noqa + "csiborg2_random_srcdir": "/mnt/extraspace/rstiskalek/csiborg2_random", # noqa + "postdir": "/mnt/extraspace/rstiskalek/csiborg_postprocessing/", + "quijote_dir": "/mnt/extraspace/rstiskalek/quijote", + } neighbour_kwargs = {"rmax_radial": 155 / 0.705, @@ -76,4 +79,8 @@ clusters = {"Virgo": read.ObservedCluster(RA=hms_to_degrees(12, 27), dec=dms_to_degrees(12, 43), dist=16.5 * 0.7, name="Virgo"), + "Fornax": read.ObservedCluster(RA=hms_to_degrees(3, 38), + dec=dms_to_degrees(-35, 27), + dist=19 * 0.7, + name="Fornax"), } diff --git a/csiborgtools/field/density.py b/csiborgtools/field/density.py index fa7344b..8359e43 100644 --- a/csiborgtools/field/density.py +++ b/csiborgtools/field/density.py @@ -69,7 +69,7 @@ class DensityField(BaseField): Parameters ---------- - box : :py:class:`csiborgtools.read.CSiBORGBox` + box : :py:class:`csiborgtools.read.CSiBORG1Box` The simulation box information and transformations. MAS : str Mass assignment scheme. Options are Options are: 'NGP' (nearest grid @@ -167,7 +167,7 @@ class DensityField(BaseField): # # Parameters # ---------- -# box : :py:class:`csiborgtools.read.CSiBORGBox` +# box : :py:class:`csiborgtools.read.CSiBORG1Box` # The simulation box information and transformations. # MAS : str # Mass assignment scheme. Options are Options are: 'NGP' (nearest grid @@ -269,7 +269,7 @@ class VelocityField(BaseField): Parameters ---------- - box : :py:class:`csiborgtools.read.CSiBORGBox` + box : :py:class:`csiborgtools.read.CSiBORG1Box` The simulation box information and transformations. MAS : str Mass assignment scheme. Options are Options are: 'NGP' (nearest grid @@ -405,7 +405,7 @@ class PotentialField(BaseField): Parameters ---------- - box : :py:class:`csiborgtools.read.CSiBORGBox` + box : :py:class:`csiborgtools.read.CSiBORG1Box` The simulation box information and transformations. MAS : str Mass assignment scheme. Options are Options are: 'NGP' (nearest grid @@ -444,7 +444,7 @@ class TidalTensorField(BaseField): Parameters ---------- - box : :py:class:`csiborgtools.read.CSiBORGBox` + box : :py:class:`csiborgtools.read.CSiBORG1Box` The simulation box information and transformations. MAS : str Mass assignment scheme used to calculate the density field. Options diff --git a/csiborgtools/field/interp.py b/csiborgtools/field/interp.py index 5e468e8..309563a 100644 --- a/csiborgtools/field/interp.py +++ b/csiborgtools/field/interp.py @@ -139,7 +139,7 @@ def observer_vobs(velocity_field): return vobs -def make_sky(field, angpos, dist, box, volume_weight=True, verbose=True): +def make_sky(field, angpos, dist, boxsize, volume_weight=True, verbose=True): r""" Make a sky map of a scalar field. The observer is in the centre of the box the field is evaluated along directions `angpos` (RA [0, 360) deg, @@ -153,9 +153,9 @@ def make_sky(field, angpos, dist, box, volume_weight=True, verbose=True): angpos : 2-dimensional arrays of shape `(ndir, 2)` Directions to evaluate the field. dist : 1-dimensional array - Uniformly spaced radial distances to evaluate the field. - box : :py:class:`csiborgtools.read.CSiBORGBox` - The simulation box information and transformations. + Uniformly spaced radial distances to evaluate the field in `Mpc / h`. + boxsize : float + Box size in `Mpc / h`. volume_weight : bool, optional Whether to weight the field by the volume of the pixel. verbose : bool, optional @@ -168,11 +168,11 @@ def make_sky(field, angpos, dist, box, volume_weight=True, verbose=True): dx = dist[1] - dist[0] assert numpy.allclose(dist[1:] - dist[:-1], dx) assert angpos.ndim == 2 and dist.ndim == 1 + # We loop over the angular directions, at each step evaluating a vector # of distances. We pre-allocate arrays for speed. dir_loop = numpy.full((dist.size, 3), numpy.nan, dtype=numpy.float32) - boxdist = box.mpc2box(dist) - boxsize = box.box2mpc(1.) + ndir = angpos.shape[0] out = numpy.full(ndir, numpy.nan, dtype=numpy.float32) for i in trange(ndir) if verbose else range(ndir): @@ -181,7 +181,7 @@ def make_sky(field, angpos, dist, box, volume_weight=True, verbose=True): dir_loop[:, 2] = angpos[i, 1] if volume_weight: out[i] = numpy.sum( - boxdist**2 + dist**2 * evaluate_sky(field, pos=dir_loop, mpc2box=1 / boxsize)) else: out[i] = numpy.sum( @@ -244,7 +244,7 @@ def field2rsp(field, radvel_field, box, MAS, init_value=0.): radvel_field : 3-dimensional array of shape `(grid, grid, grid)` Radial velocity field in `km / s`. Expected to account for the observer velocity. - box : :py:class:`csiborgtools.read.CSiBORGBox` + box : :py:class:`csiborgtools.read.CSiBORG1Box` The simulation box information and transformations. MAS : str Mass assignment. Must be one of `NGP`, `CIC`, `TSC` or `PCS`. diff --git a/csiborgtools/field/utils.py b/csiborgtools/field/utils.py index 99d3432..76109ee 100644 --- a/csiborgtools/field/utils.py +++ b/csiborgtools/field/utils.py @@ -49,5 +49,8 @@ def nside2radec(nside): """ pixs = numpy.arange(healpy.nside2npix(nside)) theta, phi = healpy.pix2ang(nside, pixs) - theta -= numpy.pi / 2 - return 180 / numpy.pi * numpy.vstack([phi, theta]).T + + ra = 180 / numpy.pi * phi + dec = 90 - 180 / numpy.pi * theta + + return numpy.vstack([ra, dec]).T diff --git a/csiborgtools/read/__init__.py b/csiborgtools/read/__init__.py index 9d796a4..c6c4fc9 100644 --- a/csiborgtools/read/__init__.py +++ b/csiborgtools/read/__init__.py @@ -12,12 +12,8 @@ # 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. -from .box_units import CSiBORGBox, QuijoteBox # noqa from .halo_cat import (CSiBORGCatalogue, QuijoteCatalogue, # noqa - CSiBORGPHEWCatalogue, fiducial_observers) # noqa + fiducial_observers) # noqa from .obs import (SDSS, MCXCClusters, PlanckClusters, TwoMPPGalaxies, # noqa TwoMPPGroups, ObservedCluster, match_array_to_no_masking) # noqa from .paths import Paths # noqa -from .readsim import (CSiBORGReader, QuijoteReader, load_halo_particles, # noqa - make_halomap_dict) # noqa -from .utils import cols_to_structured, read_h5 # noqa diff --git a/csiborgtools/read/box_units.py b/csiborgtools/read/box_units.py deleted file mode 100644 index 21b6dfc..0000000 --- a/csiborgtools/read/box_units.py +++ /dev/null @@ -1,276 +0,0 @@ -# Copyright (C) 2022 Richard Stiskalek, Deaglan Bartlett -# 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. -""" -Simulation box unit transformations. -""" -from abc import ABC, abstractmethod, abstractproperty - -import numpy -from astropy import constants, units -from astropy.cosmology import LambdaCDM - -from .readsim import CSiBORGReader, QuijoteReader - -############################################################################### -# Base box # -############################################################################### - - -class BaseBox(ABC): - _name = "box_units" - _cosmo = None - - @property - def cosmo(self): - if self._cosmo is None: - raise ValueError("Cosmology not set.") - return self._cosmo - - @property - def H0(self): - r"""Present Hubble parameter in :math:`\mathrm{km} \mathrm{s}^{-1}`""" - return self.cosmo.H0.value - - @property - def rho_crit0(self): - """Present-day critical density in M_sun h^2 / cMpc^3.""" - rho_crit0 = self.cosmo.critical_density0 - return rho_crit0.to_value(units.solMass / units.Mpc**3) - - @property - def h(self): - """The little 'h' parameter at the time of the snapshot.""" - return self._h - - @property - def Om0(self): - """The present time matter density parameter.""" - return self.cosmo.Om0 - - @abstractproperty - def boxsize(self): - """Box size in cMpc.""" - pass - - @abstractmethod - def mpc2box(self, length): - r""" - Convert length from :math:`\mathrm{cMpc} / h` to box units. - - Parameters - ---------- - length : float - Length in :math:`\mathrm{cMpc}` - - Returns - ------- - float - """ - pass - - @abstractmethod - def box2mpc(self, length): - r""" - Convert length from box units to :math:`\mathrm{cMpc} / h`. - - Parameters - ---------- - length : float - Length in box units. - - Returns - ------- - float - """ - pass - - @abstractmethod - def solarmass2box(self, mass): - r""" - Convert mass from :math:`M_\odot / h` to box units. - - Parameters - ---------- - mass : float - Mass in :math:`M_\odot / h`. - - Returns - ------- - float - """ - pass - - @abstractmethod - def box2solarmass(self, mass): - r""" - Convert mass from box units to :math:`M_\odot / h`. - - Parameters - ---------- - mass : float - Mass in box units. - - Returns - ------- - float - """ - pass - - @abstractmethod - def m200c_to_r200c(self, m200c): - """ - Convert M200c to R200c in units of cMpc / h. - - Parameters - ---------- - m200c : float - M200c in units of M_sun / h. - - Returns - ------- - float - """ - pass - - -############################################################################### -# CSiBORG box # -############################################################################### - - -class CSiBORGBox(BaseBox): - r""" - CSiBORG box units class for converting between box and physical units. - - Paramaters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - paths : py:class`csiborgtools.read.Paths` - CSiBORG paths object. - """ - - def __init__(self, nsnap, nsim, paths): - """ - Read in the snapshot info file and set the units from it. - """ - partreader = CSiBORGReader(paths) - info = partreader.read_info(nsnap, nsim) - pars = ["boxlen", "time", "aexp", "H0", "omega_m", "omega_l", - "omega_k", "omega_b", "unit_l", "unit_d", "unit_t"] - for par in pars: - setattr(self, "_" + par, info[par]) - self._h = self._H0 / 100 - self._cosmo = LambdaCDM(H0=100, Om0=self._omega_m, - Ode0=self._omega_l, Tcmb0=2.725 * units.K, - Ob0=self._omega_b) - self._Msuncgs = constants.M_sun.cgs.value # Solar mass in grams - - def mpc2box(self, length): - conv = (self._unit_l / units.kpc.to(units.cm) / self._aexp) * 1e-3 - conv *= self._h - return length / conv - - def box2mpc(self, length): - conv = (self._unit_l / units.kpc.to(units.cm) / self._aexp) * 1e-3 - conv *= self._h - return length * conv - - def solarmass2box(self, mass): - conv = (self._unit_d * self._unit_l**3) / self._Msuncgs - conv *= self.h - return mass / conv - - def box2solarmass(self, mass): - conv = (self._unit_d * self._unit_l**3) / self._Msuncgs - conv *= self.h - return mass * conv - - def box2vel(self, vel): - r""" - Convert velocity from box units to :math:`\mathrm{km} \mathrm{s}^{-1}`. - - Parameters - ---------- - vel : float - Velocity in box units. - - Returns - ------- - vel : float - Velocity in :math:`\mathrm{km} \mathrm{s}^{-1}`. - """ - return vel * (1e-2 * self._unit_l / self._unit_t / self._aexp) * 1e-3 - - @property - def boxsize(self): - return self.box2mpc(1.) - - def m200c_to_r200c(self, m200c): - rho_crit = self.cosmo.critical_density(1 / self._aexp - 1) - rho_crit = rho_crit.to_value(units.solMass / units.Mpc**3) - r200c = (3 * m200c / (4 * numpy.pi * 200 * rho_crit))**(1 / 3) - return r200c / self._aexp - - -############################################################################### -# Quijote fiducial cosmology box # -############################################################################### - - -class QuijoteBox(BaseBox): - """ - Quijote cosmology box. - - Parameters - ---------- - nsnap : int - Snapshot number. - nsim : int - IC realisation index. - paths : py:class`csiborgtools.read.Paths` - Paths manager - """ - - def __init__(self, nsnap, nsim, paths): - zdict = {4: 0.0, 3: 0.5, 2: 1.0, 1: 2.0, 0: 3.0} - assert nsnap in zdict.keys(), f"`nsnap` must be in {zdict.keys()}." - info = QuijoteReader(paths).read_info(nsnap, nsim) - self._aexp = 1 / (1 + zdict[nsnap]) - self._h = info["h"] - self._cosmo = LambdaCDM(H0=100, Om0=info["Omega_m"], - Ode0=info["Omega_l"], Tcmb0=2.725 * units.K) - self._info = info - - @property - def boxsize(self): - return self._info["BoxSize"] - - def box2mpc(self, length): - return length * self.boxsize - - def mpc2box(self, length): - return length / self.boxsize - - def solarmass2box(self, mass): - return mass / self._info["TotMass"] - - def box2solarmass(self, mass): - return mass * self._info["TotMass"] - - def m200c_to_r200c(self, m200c): - raise ValueError("Not implemented for Quijote boxes.") diff --git a/csiborgtools/read/halo_cat.py b/csiborgtools/read/halo_cat.py index 6c31aa2..fe991cd 100644 --- a/csiborgtools/read/halo_cat.py +++ b/csiborgtools/read/halo_cat.py @@ -28,9 +28,9 @@ from sklearn.neighbors import NearestNeighbors from ..utils import (cartesian_to_radec, fprint, great_circle_distance, number_counts, periodic_distance_two_points, real2redshift) -from .box_units import CSiBORGBox, QuijoteBox +# TODO: removing these +from .box_units import CSiBORG1Box, QuijoteBox from .paths import Paths -from .readsim import load_halo_particles, make_halomap_dict ############################################################################### # Base catalogue # @@ -622,75 +622,7 @@ class CSiBORGCatalogue(BaseCatalogue): "csiborg", nsim, max(paths.get_snapshots(nsim, "csiborg")), halo_finder, catalogue_name, paths, mass_key, bounds, [338.85, 338.85, 338.85], observer_velocity, cache_maxsize) - self.box = CSiBORGBox(self.nsnap, self.nsim, self.paths) - - -############################################################################### -# Quijote PHEW without snapshot catalogue # -############################################################################### - - -class CSiBORGPHEWCatalogue(BaseCatalogue): - r""" - CSiBORG PHEW halo catalogue without snapshot. Units typically used are: - - Length: :math:`cMpc / h` - - Mass: :math:`M_\odot / h` - - Note that the PHEW catalogue is not very reliable. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - paths : py:class`csiborgtools.read.Paths` - Paths object. - mass_key : str, optional - Mass key of the catalogue. - bounds : dict, optional - Parameter bounds; keys as parameter names, values as (min, max) or - a boolean. - cache_maxsize : int, optional - Maximum number of cached arrays. - """ - def __init__(self, nsnap, nsim, paths, mass_key=None, bounds=None, - cache_maxsize=64): - super().__init__() - self.simname = "csiborg" - self.nsnap = nsnap - self.nsim = nsim - self.paths = paths - self.mass_key = mass_key - self.observer_location = [338.85, 338.85, 338.85] - - fname = paths.processed_phew(nsim) - self._data = File(fname, "r") - if str(nsnap) not in self._data.keys(): - raise ValueError(f"Snapshot {nsnap} not in the catalogue. " - f"Options are {self.get_snapshots(nsim, paths)}") - self.catalogue_name = str(nsnap) - self._is_closed = False - - self.cache_maxsize = cache_maxsize - - if bounds is not None: - self._make_mask(bounds) - - self._derived_properties = ["cartesian_pos", "spherical_pos", "dist"] - self.box = CSiBORGBox(self.nsnap, self.nsim, self.paths) - self.clear_cache() - - @staticmethod - def get_snapshots(nsim, paths): - """List of snapshots available for this simulation.""" - fname = paths.processed_phew(nsim) - - with File(fname, "r") as f: - snaps = [int(key) for key in f.keys() if key != "info"] - f.close() - - return numpy.sort(snaps) + self.box = CSiBORG1Box(self.nsnap, self.nsim, self.paths) ############################################################################### @@ -850,3 +782,41 @@ def find_boxed(pos, center, subbox_size, boxsize): start_index = i + 1 return indxs + + +############################################################################### +# Supplementary functions # +############################################################################### + + +def make_halomap_dict(halomap): + """ + Make a dictionary mapping halo IDs to their start and end indices in the + snapshot particle array. + """ + return {hid: (int(start), int(end)) for hid, start, end in halomap} + + +def load_halo_particles(hid, particles, hid2map): + """ + Load a halo's particles from a particle array. If it is not there, i.e + halo has no associated particles, return `None`. + + Parameters + ---------- + hid : int + Halo ID. + particles : 2-dimensional array + Array of particles. + hid2map : dict + Dictionary mapping halo IDs to `halo_map` array positions. + + Returns + ------- + parts : 1- or 2-dimensional array + """ + try: + k0, kf = hid2map[hid] + return particles[k0:kf + 1] + except KeyError: + return None \ No newline at end of file diff --git a/csiborgtools/read/obs.py b/csiborgtools/read/obs.py index 6e537ca..8cf949d 100644 --- a/csiborgtools/read/obs.py +++ b/csiborgtools/read/obs.py @@ -26,7 +26,6 @@ from astropy.io import fits from astropy.cosmology import FlatLambdaCDM from scipy import constants -from .utils import cols_to_structured ############################################################################### # Text survey base class # @@ -830,3 +829,17 @@ def match_array_to_no_masking(arr, surv): out[indx] = arr[i] return out + + +def cols_to_structured(N, cols): + """ + Allocate a structured array from `cols`, a list of (name, dtype) tuples. + """ + if not (isinstance(cols, list) + and all(isinstance(c, tuple) and len(c) == 2 for c in cols)): + raise TypeError("`cols` must be a list of (name, dtype) tuples.") + + names, formats = zip(*cols) + dtype = {"names": names, "formats": formats} + + return numpy.full(N, numpy.nan, dtype=dtype) diff --git a/csiborgtools/read/paths.py b/csiborgtools/read/paths.py index 1360caa..54b87ad 100644 --- a/csiborgtools/read/paths.py +++ b/csiborgtools/read/paths.py @@ -15,9 +15,9 @@ """ CSiBORG paths manager. """ -from glob import glob, iglob +from glob import glob from os import makedirs -from os.path import isdir, join +from os.path import basename, isdir, join from warnings import warn import numpy @@ -40,6 +40,7 @@ class Paths: Parameters ---------- + # HERE EDIT EVERYTHING srcdir : str, optional Path to the folder where the RAMSES outputs are stored. postdir: str, optional @@ -49,73 +50,158 @@ class Paths: quiote_dir : str, optional Path to the folder where Quijote simulations are stored. """ - _srcdir = None - _postdir = None - _borg_dir = None - _quijote_dir = None - - def __init__(self, srcdir=None, postdir=None, borg_dir=None, - quijote_dir=None): - self.srcdir = srcdir - self.postdir = postdir - self.borg_dir = borg_dir + def __init__(self, + csiborg1_srcdir=None, + csiborg2_main_srcdir=None, + csiborg2_random_srcdir=None, + csiborg2_varysmall_srcdir=None, + postdir=None, + quijote_dir=None + ): + self.csiborg1_srcdir = csiborg1_srcdir + self.csiborg2_main_srcdir = csiborg2_main_srcdir + self.csiborg2_random_srcdir = csiborg2_random_srcdir + self.csiborg2_varysmall_srcdir = csiborg2_varysmall_srcdir self.quijote_dir = quijote_dir - @property - def srcdir(self): - """Path to the folder where CSiBORG simulations are stored.""" - if self._srcdir is None: - raise ValueError("`srcdir` is not set!") - return self._srcdir + self.postdir = postdir - @srcdir.setter - def srcdir(self, path): - if path is None: - return - check_directory(path) - self._srcdir = path + def get_ics(self, simname, from_quijote_backup=False): + """ + Get available IC realisation IDs for a given simulation. - @property - def borg_dir(self): - """Path to the folder where BORG MCMC chains are stored.""" - if self._borg_dir is None: - raise ValueError("`borg_dir` is not set!") - return self._borg_dir + Parameters + ---------- + simname : str + Simulation name. + from_quijote_backup : bool, optional + Whether to return the ICs from the Quijote backup. - @borg_dir.setter - def borg_dir(self, path): - if path is None: - return - check_directory(path) - self._borg_dir = path + Returns + ------- + ids : 1-dimensional array + """ + if simname == "csiborg": + files = glob(join(self.csiborg1_srcdir, "chain_*")) + files = [int(basename(f).replace("chain_", "") for f in files)] + elif simname == "csiborg2_main": + files = glob(join(self.csiborg2_main_srcdir, "chain_*")) + files = [int(basename(f).replace("chain_", "") for f in files)] + elif simname == "csiborg2_random": + raise NotImplementedError("TODO") + elif simname == "csiborg2_varysmall": + raise NotImplementedError("TODO") + elif simname == "quijote" or simname == "quijote_full": + if from_quijote_backup: + files = glob(join(self.quijote_dir, "halos_backup", "*")) + else: + warn(("Taking only the snapshots that also have " + "a FoF catalogue!")) + files = glob(join(self.quijote_dir, "Snapshots_fiducial", "*")) + files = [int(f.split("/")[-1]) for f in files] + files = [f for f in files if f < 100] + else: + raise ValueError(f"Unknown simulation name `{simname}`.") - @property - def quijote_dir(self): - """Path to the folder where Quijote simulations are stored.""" - if self._quijote_dir is None: - raise ValueError("`quijote_dir` is not set!") - return self._quijote_dir + return numpy.sort(files) - @quijote_dir.setter - def quijote_dir(self, path): - if path is None: - return - check_directory(path) - self._quijote_dir = path + def snapshots(self, nsim, simname): + if simname == "csiborg": + fname = "ramses_out_{}" + if tonew: + fname += "_new" + return join(self.postdir, "output", fname.format(nsim)) + return join(self.csiborg1_srcdir, fname.format(nsim)) + elif simname == "csiborg2_main": + return join(self.csiborg2_main_srcdir, f"chain_{nsim}", "output") + elif simname == "csiborg2_random": + raise NotImplementedError("TODO") + elif simname == "csiborg2_varysmall": + raise NotImplementedError("TODO") + elif simname == "quijote": + return join(self.quijote_dir, "Snapshots_fiducial", str(nsim)) + else: + raise ValueError(f"Unknown simulation name `{simname}`.") - @property - def postdir(self): - """Path to the folder where post-processed files are stored.""" - if self._postdir is None: - raise ValueError("`postdir` is not set!") - return self._postdir + def snapshot(self, nsnap, nsim, simname): + """ + Path to an IC realisation snapshot. - @postdir.setter - def postdir(self, path): - if path is None: - return - check_directory(path) - self._postdir = path + Parameters + ---------- + nsnap : int + Snapshot index. For Quijote, `-1` indicates the IC snapshot. + nsim : inlot + IC realisation index. + simname : str + Simulation name. + + Returns + ------- + str + """ + if simname == "csiborg": + return join(self.csiborg1_srcdir, f"chain_{nsim}", + f"snapshot_{str(nsnap).zfill(5)}") + elif simname == "csiborg2_main": + return join(self.csiborg1_srcdir, f"chain_{nsim}", + f"snapshot_{str(nsnap).zfill(5)}") + elif simname == "csiborg2_random": + raise NotImplementedError("TODO") + elif simname == "csiborg2_varysmall": + raise NotImplementedError("TODO") + elif simname == "quijote": + raise NotImplementedError("TODO") + else: + raise ValueError(f"Unknown simulation name `{simname}`.") + + + # simpath = self.snapshots(nsim, simname, tonew=nsnap == 1) + # if simname == "csiborg": + # return join(simpath, f"output_{str(nsnap).zfill(5)}") + # else: + # if nsnap == -1: + # return join(simpath, "ICs", "ics") + # nsnap = str(nsnap).zfill(3) + # return join(simpath, f"snapdir_{nsnap}", f"snap_{nsnap}") + + def get_snapshots(self, nsim, simname): + """ + List of available snapshots of simulation. + + Parameters + ---------- + nsim : int + IC realisation index. + simname : str + Simulation name. + + Returns + ------- + snapshots : 1-dimensional array + """ + simpath = self.snapshots(nsim, simname, tonew=False) + + if simname == "csiborg": + # Get all files in simpath that start with output_ + snaps = glob(join(simpath, "output_*")) + # Take just the last _00XXXX from each file and strip zeros + snaps = [int(snap.split("_")[-1].lstrip("0")) for snap in snaps] + elif simname == "csiborg2_main": + snaps = glob(join(simpath, "snapshot_*")) + snaps = [basename(snap) for snap in snaps] + snaps = [int(snap.split("_")[1]) for snap in snaps] + elif simname == "csiborg2_random": + raise NotImplementedError("TODO") + elif simname == "csiborg2_varysmall": + raise NotImplementedError("TODO") + elif simname == "quijote": + snaps = glob(join(simpath, "snapdir_*")) + snaps = [int(snap.split("/")[-1].split("snapdir_")[-1]) + for snap in snaps] + else: + raise ValueError(f"Unknown simulation name `{simname}`.") + return numpy.sort(snaps) @staticmethod def quijote_fiducial_nsim(nsim, nobs=None): @@ -140,268 +226,6 @@ class Paths: return nsim return f"{str(nobs).zfill(2)}{str(nsim).zfill(3)}" - def borg_mcmc(self, nsim): - """ - Path to the BORG MCMC chain file. - - Parameters - ---------- - nsim : int - IC realisation index. - - Returns - ------- - str - """ - return join(self.borg_dir, "mcmc", f"mcmc_{nsim}.h5") - - def fof_cat(self, nsnap, nsim, simname, from_quijote_backup=False): - r""" - Path to the :math:`z = 0` FoF halo catalogue. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - simname : str - Simulation name. Must be one of `csiborg` or `quijote`. - from_quijote_backup : bool, optional - Whether to return the path to the Quijote FoF catalogue from the - backup. - - Returns - ------- - str - """ - if simname == "csiborg": - fdir = join(self.postdir, "halo_maker", f"ramses_{nsim}", - f"output_{str(nsnap).zfill(5)}", "FOF") - try_create_directory(fdir) - return join(fdir, "fort.132") - elif simname == "quijote": - if from_quijote_backup: - return join(self.quijote_dir, "halos_backup", str(nsim)) - else: - return join(self.quijote_dir, "Halos_fiducial", str(nsim)) - else: - raise ValueError(f"Unknown simulation name `{simname}`.") - - def get_ics(self, simname, from_quijote_backup=False): - """ - Get available IC realisation IDs for either the CSiBORG or Quijote - simulation suite. - - Parameters - ---------- - simname : str - Simulation name. Must be `csiborg` or `quijote`. - from_quijote_backup : bool, optional - Whether to return the ICs from the Quijote backup. - - Returns - ------- - ids : 1-dimensional array - """ - if simname == "csiborg": - files = glob(join(self.srcdir, "ramses_out*")) - files = [f.split("/")[-1] for f in files] # Only file names - files = [f for f in files if "_inv" not in f] # Remove inv. ICs - files = [f for f in files if "_new" not in f] # Remove _new - files = [f for f in files if "OLD" not in f] # Remove _old - files = [int(f.split("_")[-1]) for f in files] - try: - files.remove(5511) - except ValueError: - pass - elif simname == "quijote" or simname == "quijote_full": - if from_quijote_backup: - files = glob(join(self.quijote_dir, "halos_backup", "*")) - else: - warn(("Taking only the snapshots that also have " - "a FoF catalogue!")) - files = glob(join(self.quijote_dir, "Snapshots_fiducial", "*")) - files = [int(f.split("/")[-1]) for f in files] - files = [f for f in files if f < 100] - else: - raise ValueError(f"Unknown simulation name `{simname}`.") - - return numpy.sort(files) - - def snapshots(self, nsim, simname, tonew=False): - """ - Path to an IC snapshots folder. - - Parameters - ---------- - nsim : int - IC realisation index. - simname : str - Simulation name. Must be one of `csiborg` or `quijote`. - tonew : bool, optional - Whether to return the path to the '_new' IC realisation of - CSiBORG. Ignored for Quijote. - - Returns - ------- - str - """ - if simname == "csiborg": - fname = "ramses_out_{}" - if tonew: - fname += "_new" - return join(self.postdir, "output", fname.format(nsim)) - return join(self.srcdir, fname.format(nsim)) - elif simname == "quijote": - return join(self.quijote_dir, "Snapshots_fiducial", str(nsim)) - else: - raise ValueError(f"Unknown simulation name `{simname}`.") - - def get_snapshots(self, nsim, simname): - """ - List of available snapshots of simulation. - - Parameters - ---------- - nsim : int - IC realisation index. - simname : str - Simulation name. Must be one of `csiborg` or `quijote`. - - Returns - ------- - snapshots : 1-dimensional array - """ - simpath = self.snapshots(nsim, simname, tonew=False) - - if simname == "csiborg": - # Get all files in simpath that start with output_ - snaps = glob(join(simpath, "output_*")) - # Take just the last _00XXXX from each file and strip zeros - snaps = [int(snap.split("_")[-1].lstrip("0")) for snap in snaps] - elif simname == "quijote": - snaps = glob(join(simpath, "snapdir_*")) - snaps = [int(snap.split("/")[-1].split("snapdir_")[-1]) - for snap in snaps] - else: - raise ValueError(f"Unknown simulation name `{simname}`.") - return numpy.sort(snaps) - - def snapshot(self, nsnap, nsim, simname): - """ - Path to an IC realisation snapshot. - - Parameters - ---------- - nsnap : int - Snapshot index. For Quijote, `-1` indicates the IC snapshot. - nsim : int - IC realisation index. - simname : str - Simulation name. Must be one of `csiborg` or `quijote`. - - Returns - ------- - str - """ - simpath = self.snapshots(nsim, simname, tonew=nsnap == 1) - if simname == "csiborg": - return join(simpath, f"output_{str(nsnap).zfill(5)}") - else: - if nsnap == -1: - return join(simpath, "ICs", "ics") - nsnap = str(nsnap).zfill(3) - return join(simpath, f"snapdir_{nsnap}", f"snap_{nsnap}") - - def processed_output(self, nsim, simname, halo_finder): - """ - Path to the files containing all particles of a CSiBORG realisation at - :math:`z = 0`. - - Parameters - ---------- - nsim : int - IC realisation index. - simname : str - Simulation name. Must be one of `csiborg` or `quijote`. - halo_finder : str - Halo finder name. - - Returns - ------- - str - """ - if simname == "csiborg": - fdir = join(self.postdir, "processed_output") - elif simname == "quijote": - fdir = join(self.quijote_dir, "Particles_fiducial") - else: - raise ValueError(f"Unknown simulation name `{simname}`.") - - try_create_directory(fdir) - fname = f"parts_{halo_finder}_{str(nsim).zfill(5)}.hdf5" - return join(fdir, fname) - - def processed_phew(self, nsim): - """ - Path to the files containing PHEW CSiBORG catalogues. - - Parameters - ---------- - nsim : int - IC realisation index. - - Returns - ------- - str - """ - fdir = join(self.postdir, "processed_output") - try_create_directory(fdir) - return join(fdir, f"phew_{str(nsim).zfill(5)}.hdf5") - - def halomaker_particle_membership(self, nsnap, nsim, halo_finder): - """ - Path to the HaloMaker particle membership file (CSiBORG only). - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - halo_finder : str - Halo finder name. - - Returns - ------- - str - """ - fdir = join(self.postdir, "halo_maker", f"ramses_{nsim}", - f"output_{str(nsnap).zfill(5)}", halo_finder) - fpath = join(fdir, "*particle_membership*") - return next(iglob(fpath, recursive=True), None) - - def ascii_positions(self, nsim, kind): - """ - Path to ASCII files containing the positions of particles or halos. - - Parameters - ---------- - nsim : int - IC realisation index. - kind : str - Kind of data to extract. Must be one of `particles`, - `particles_rsp`, `halos`, `halos_rsp`. - """ - assert kind in ["particles", "particles_rsp", "halos", "halos_rsp"] - - fdir = join(self.postdir, "ascii_positions") - try_create_directory(fdir) - fname = f"pos_{kind}_{str(nsim).zfill(5)}.txt" - - return join(fdir, fname) - def overlap(self, simname, nsim0, nsimx, min_logmass, smoothed): """ Path to the overlap files between two CSiBORG simulations. @@ -569,29 +393,6 @@ class Paths: return join(fdir, fname) - def observer_peculiar_velocity(self, MAS, grid, nsim): - """ - Path to the files containing the observer peculiar velocity. - - Parameters - ---------- - MAS : str - Mass-assignment scheme. - grid : int - Grid size. - nsim : int - IC realisation index. - - Returns - ------- - str - """ - fdir = join(self.postdir, "environment") - try_create_directory(fdir) - - fname = f"obs_vp_{MAS}_{str(nsim).zfill(5)}_{grid}.npz" - return join(fdir, fname) - def cross_nearest(self, simname, run, kind, nsim=None, nobs=None): """ Path to the files containing distance from a halo in a reference diff --git a/csiborgtools/read/readsim.py b/csiborgtools/read/readsim.py deleted file mode 100644 index bedc7eb..0000000 --- a/csiborgtools/read/readsim.py +++ /dev/null @@ -1,631 +0,0 @@ -# Copyright (C) 2022 Richard Stiskalek, Harry Desmond -# 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. -""" -Functions to read in the particle and clump files. -""" -from abc import ABC, abstractmethod -from gc import collect -from os.path import getsize, isfile, join -from warnings import warn - -import numpy -import pynbody -from scipy.io import FortranFile -from tqdm import tqdm - -try: - import readgadget - from readfof import FoF_catalog -except ImportError: - warn("Could not import `readgadget` and `readfof`. Related routines will not be available", ImportWarning) # noqa -from tqdm import trange - -from ..utils import fprint -from .paths import Paths -from .utils import add_columns, cols_to_structured, flip_cols - - -class BaseReader(ABC): - """ - Base class for all readers. - """ - _paths = None - - @property - def paths(self): - """Paths manager.""" - return self._paths - - @paths.setter - def paths(self, paths): - assert isinstance(paths, Paths) - self._paths = paths - - @abstractmethod - def read_info(self, nsnap, nsim): - """ - Read simulation snapshot info. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - - Returns - ------- - info : dict - Dictionary of information paramaters. - """ - pass - - @abstractmethod - def read_snapshot(self, nsnap, nsim, kind, sort_like_final=False): - """ - Read snapshot. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - kind : str - Information to read. Can be `pid`, `pos`, `vel`, or `mass`. - sort_like_final : bool, optional - Whether to sort the particles like the final snapshot. - - Returns - ------- - n-dimensional array - """ - - @abstractmethod - def read_halo_id(self, nsnap, nsim, halo_finder, verbose=True): - """ - Read the (sub) halo membership of particles. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - halo_finder : str - Halo finder used when running the catalogue. - - Returns - ------- - out : 1-dimensional array of shape `(nparticles, )` - """ - - def read_catalogue(self, nsnap, nsim, halo_finder): - """ - Read in the halo catalogue. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - halo_finder : str - Halo finder used when running the catalogue. - - Returns - ------- - structured array - """ - - -############################################################################### -# CSiBORG particle reader # -############################################################################### - - -class CSiBORGReader(BaseReader): - """ - Object to read in CSiBORG snapshots from the binary files and halo - catalogues. - - Parameters - ---------- - paths : py:class`csiborgtools.read.Paths` - """ - def __init__(self, paths): - self.paths = paths - - def read_info(self, nsnap, nsim): - snappath = self.paths.snapshot(nsnap, nsim, "csiborg") - filename = join(snappath, "info_{}.txt".format(str(nsnap).zfill(5))) - with open(filename, "r") as f: - info = f.read().split() - # Throw anything below ordering line out - info = numpy.asarray(info[:info.index("ordering")]) - # Get indexes of lines with `=`. Indxs before/after be keys/vals - eqs = numpy.asarray([i for i in range(info.size) if info[i] == '=']) - - keys = info[eqs - 1] - vals = info[eqs + 1] - return {key: convert_str_to_num(val) for key, val in zip(keys, vals)} - - def read_snapshot(self, nsnap, nsim, kind): - sim = pynbody.load(self.paths.snapshot(nsnap, nsim, "csiborg")) - - if kind == "pid": - x = numpy.array(sim["iord"], dtype=numpy.uint64) - elif kind in ["pos", "vel", "mass"]: - x = numpy.array(sim[kind], dtype=numpy.float32) - else: - raise ValueError(f"Unknown kind `{kind}`.") - - # Because of a RAMSES bug x and z are flipped. - if kind in ["pos", "vel"]: - x[:, [0, 2]] = x[:, [2, 0]] - - del sim - collect() - - return x - - def read_halo_id(self, nsnap, nsim, halo_finder, verbose=True): - if halo_finder == "PHEW": - ids = self.read_phew_id(nsnap, nsim, verbose) - elif halo_finder in ["FOF"]: - ids = self.read_halomaker_id(nsnap, nsim, halo_finder, verbose) - else: - raise ValueError(f"Unknown halo finder `{halo_finder}`.") - return ids - - def open_particle(self, nsnap, nsim, verbose=True): - """Open particle files to a given CSiBORG simulation.""" - snappath = self.paths.snapshot(nsnap, nsim, "csiborg") - ncpu = int(self.read_info(nsnap, nsim)["ncpu"]) - nsnap = str(nsnap).zfill(5) - fprint(f"reading in output `{nsnap}` with ncpu = `{ncpu}`.", verbose) - - # First read the headers. Reallocate arrays and fill them. - nparts = numpy.zeros(ncpu, dtype=int) - partfiles = [None] * ncpu - for cpu in range(ncpu): - cpu_str = str(cpu + 1).zfill(5) - fpath = join(snappath, "part_{}.out{}".format(nsnap, cpu_str)) - - f = FortranFile(fpath) - # Read in this order - ncpuloc = f.read_ints() - if ncpuloc != ncpu: - infopath = join(snappath, f"info_{nsnap}.txt") - raise ValueError( - "`ncpu = {}` of `{}` disagrees with `ncpu = {}` " - "of `{}`.".format(ncpu, infopath, ncpuloc, fpath)) - ndim = f.read_ints() - nparts[cpu] = f.read_ints() - localseed = f.read_ints() - nstar_tot = f.read_ints() - mstar_tot = f.read_reals('d') - mstar_lost = f.read_reals('d') - nsink = f.read_ints() - - partfiles[cpu] = f - del ndim, localseed, nstar_tot, mstar_tot, mstar_lost, nsink - - return nparts, partfiles - - def open_unbinding(self, nsnap, nsim, cpu): - """Open PHEW unbinding files.""" - nsnap = str(nsnap).zfill(5) - cpu = str(cpu + 1).zfill(5) - fpath = join(self.paths.snapshots(nsim, "csiborg", tonew=False), - f"output_{nsnap}", f"unbinding_{nsnap}.out{cpu}") - return FortranFile(fpath) - - def read_phew_id(self, nsnap, nsim, verbose): - nparts, __ = self.open_particle(nsnap, nsim) - start_ind = numpy.hstack([[0], numpy.cumsum(nparts[:-1])]) - ncpu = nparts.size - - clumpid = numpy.full(numpy.sum(nparts), numpy.nan, dtype=numpy.int32) - for cpu in trange(ncpu, disable=not verbose, desc="CPU"): - i = start_ind[cpu] - j = nparts[cpu] - ff = self.open_unbinding(nsnap, nsim, cpu) - clumpid[i:i + j] = ff.read_ints() - ff.close() - - return clumpid - - def read_halomaker_id(self, nsnap, nsim, halo_finder, verbose): - fpath = self.paths.halomaker_particle_membership( - nsnap, nsim, halo_finder) - - fprint("loading particle IDs from the snapshot.", verbose) - pids = self.read_snapshot(nsnap, nsim, "pid") - - fprint("mapping particle IDs to their indices.", verbose) - pids_idx = {pid: i for i, pid in enumerate(pids)} - # Unassigned particle IDs are assigned a halo ID of 0. - fprint("mapping HIDs to their array indices.", verbose) - hids = numpy.zeros(pids.size, dtype=numpy.int32) - - # Read lin-by-line to avoid loading the whole file into memory. - with open(fpath, 'r') as file: - for line in tqdm(file, disable=not verbose, - desc="Processing membership"): - hid, pid = map(int, line.split()) - hids[pids_idx[pid]] = hid - - del pids_idx - collect() - - return hids - - def read_catalogue(self, nsnap, nsim, halo_finder): - if halo_finder == "PHEW": - return self.read_phew_clumps(nsnap, nsim) - elif halo_finder == "FOF": - return self.read_fof_halos(nsnap, nsim) - else: - raise ValueError(f"Unknown halo finder `{halo_finder}`.") - - def read_fof_halos(self, nsnap, nsim): - """ - Read in the FoF halo catalogue. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - - Returns - ------- - structured array - """ - info = self.read_info(nsnap, nsim) - h = info["H0"] / 100 - - fpath = self.paths.fof_cat(nsnap, nsim, "csiborg") - hid = numpy.genfromtxt(fpath, usecols=0, dtype=numpy.int32) - pos = numpy.genfromtxt(fpath, usecols=(1, 2, 3), dtype=numpy.float32) - totmass = numpy.genfromtxt(fpath, usecols=4, dtype=numpy.float32) - m200c = numpy.genfromtxt(fpath, usecols=5, dtype=numpy.float32) - - dtype = {"names": ["index", "x", "y", "z", "totpartmass", "m200c"], - "formats": [numpy.int32] + [numpy.float32] * 5} - out = numpy.full(hid.size, numpy.nan, dtype=dtype) - out["index"] = hid - out["x"] = pos[:, 0] * h + 677.7 / 2 - out["y"] = pos[:, 1] * h + 677.7 / 2 - out["z"] = pos[:, 2] * h + 677.7 / 2 - # Because of a RAMSES bug x and z are flipped. - flip_cols(out, "x", "z") - out["totpartmass"] = totmass * 1e11 * h - out["m200c"] = m200c * 1e11 * h - return out - - def read_phew_clumps(self, nsnap, nsim, verbose=True): - """ - Read in a PHEW clump file `clump_XXXXX.dat`. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - verbose : bool, optional - Verbosity flag. - - Returns - ------- - structured array - """ - nsnap = str(nsnap).zfill(5) - fname = join(self.paths.snapshots(nsim, "csiborg", tonew=False), - "output_{}".format(nsnap), - "clump_{}.dat".format(nsnap)) - - if not isfile(fname) or getsize(fname) == 0: - raise FileExistsError(f"Clump file `{fname}` does not exist.") - - data = numpy.genfromtxt(fname) - - if data.ndim == 1: - raise FileExistsError(f"Invalid clump file `{fname}`.") - - # How the data is stored in the clump file. - clump_cols = {"index": (0, numpy.int32), - "level": (1, numpy.int32), - "parent": (2, numpy.int32), - "ncell": (3, numpy.float32), - "x": (4, numpy.float32), - "y": (5, numpy.float32), - "z": (6, numpy.float32), - "rho-": (7, numpy.float32), - "rho+": (8, numpy.float32), - "rho_av": (9, numpy.float32), - "mass_cl": (10, numpy.float32), - "relevance": (11, numpy.float32), - } - - cols = list(clump_cols.keys()) - dtype = [(col, clump_cols[col][1]) for col in cols] - out = cols_to_structured(data.shape[0], dtype) - for col in cols: - out[col] = data[:, clump_cols[col][0]] - - # Convert to cMpc / h and Msun / h - out['x'] *= 677.7 - out['y'] *= 677.7 - out['z'] *= 677.7 - # Because of a RAMSES bug x and z are flipped. - flip_cols(out, "x", "z") - out["mass_cl"] *= 2.6543271649678946e+19 - - ultimate_parent, summed_mass = self.find_parents(out) - - out = add_columns(out, [ultimate_parent, summed_mass], - ["ultimate_parent", "summed_mass"]) - return out - - def find_parents(self, clumparr): - """ - Find ultimate parent haloes for every PHEW clump. - - Parameters - ---------- - clumparr : structured array - Clump array. Must contain `index` and `parent` columns. - - Returns - ------- - parent_arr : 1-dimensional array of shape `(nclumps, )` - The ultimate parent halo index of every clump. - parent_mass : 1-dimensional array of shape `(nclumps, )` - The summed substructure mass of ultimate parent clumps. - """ - clindex = clumparr["index"] - parindex = clumparr["parent"] - clmass = clumparr["mass_cl"] - - clindex_to_array_index = {clindex[i]: i for i in range(clindex.size)} - - parent_arr = numpy.copy(parindex) - for i in range(clindex.size): - cl = clindex[i] - par = parindex[i] - - while cl != par: - - element = clindex_to_array_index[par] - - cl = clindex[element] - par = parindex[element] - - parent_arr[i] = cl - - parent_mass = numpy.full(clindex.size, 0, dtype=numpy.float32) - # Assign the clump masses to the ultimate parent haloes. For each clump - # find its ultimate parent and add its mass to the parent mass. - for i in range(clindex.size): - element = clindex_to_array_index[parent_arr[i]] - parent_mass[element] += clmass[i] - - # Set this to NaN for the clumps that are not ultimate parents. - parent_mass[clindex != parindex] = numpy.nan - - return parent_arr, parent_mass - - -############################################################################### -# Quijote particle reader # -############################################################################### - - -class QuijoteReader(BaseReader): - """ - Object to read in Quijote snapshots from the binary files. - - Parameters - ---------- - paths : py:class`csiborgtools.read.Paths` - """ - def __init__(self, paths): - self.paths = paths - - def read_info(self, nsnap, nsim): - snapshot = self.paths.snapshot(nsnap, nsim, "quijote") - header = readgadget.header(snapshot) - out = {"BoxSize": header.boxsize / 1e3, # Mpc/h - "Nall": header.nall[1], # Tot num of particles - "PartMass": header.massarr[1] * 1e10, # Part mass in Msun/h - "Omega_m": header.omega_m, - "Omega_l": header.omega_l, - "h": header.hubble, - "redshift": header.redshift, - } - out["TotMass"] = out["Nall"] * out["PartMass"] - out["Hubble"] = (100.0 * numpy.sqrt( - header.omega_m * (1.0 + header.redshift)**3 + header.omega_l)) - return out - - def read_snapshot(self, nsnap, nsim, kind): - snapshot = self.paths.snapshot(nsnap, nsim, "quijote") - info = self.read_info(nsnap, nsim) - ptype = [1] # DM in Gadget speech - - if kind == "pid": - return readgadget.read_block(snapshot, "ID ", ptype) - elif kind == "pos": - pos = readgadget.read_block(snapshot, "POS ", ptype) / 1e3 # Mpc/h - pos = pos.astype(numpy.float32) - pos /= info["BoxSize"] # Box units - return pos - elif kind == "vel": - vel = readgadget.read_block(snapshot, "VEL ", ptype) - vel = vel.astype(numpy.float32) - vel *= (1 + info["redshift"]) # km / s - return vel - elif kind == "mass": - return numpy.full(info["Nall"], info["PartMass"], - dtype=numpy.float32) - else: - raise ValueError(f"Unsupported kind `{kind}`.") - - def read_halo_id(self, nsnap, nsim, halo_finder, verbose=True): - if halo_finder == "FOF": - path = self.paths.fof_cat(nsnap, nsim, "quijote") - cat = FoF_catalog(path, nsnap) - pids = self.read_snapshot(nsnap, nsim, kind="pid") - - # Read the FoF particle membership. - fprint("reading the FoF particle membership.") - group_pids = cat.GroupIDs - group_len = cat.GroupLen - - # Create a mapping from particle ID to FoF group ID. - fprint("creating the particle to FoF ID to map.") - ks = numpy.insert(numpy.cumsum(group_len), 0, 0) - pid2hid = numpy.full( - (group_pids.size, 2), numpy.nan, dtype=numpy.uint64) - for i, (k0, kf) in enumerate(zip(ks[:-1], ks[1:])): - pid2hid[k0:kf, 0] = i + 1 - pid2hid[k0:kf, 1] = group_pids[k0:kf] - pid2hid = {pid: hid for hid, pid in pid2hid} - - # Create the final array of hids matchign the snapshot array. - # Unassigned particles have hid 0. - fprint("creating the final hid array.") - hids = numpy.full(pids.size, 0, dtype=numpy.uint64) - for i in trange(pids.size, disable=not verbose): - hids[i] = pid2hid.get(pids[i], 0) - - return hids - else: - raise ValueError(f"Unknown halo finder `{halo_finder}`.") - - def read_catalogue(self, nsnap, nsim, halo_finder): - if halo_finder == "FOF": - return self.read_fof_halos(nsnap, nsim) - else: - raise ValueError(f"Unknown halo finder `{halo_finder}`.") - - def read_fof_halos(self, nsnap, nsim): - """ - Read in the FoF halo catalogue. - - Parameters - ---------- - nsnap : int - Snapshot index. - nsim : int - IC realisation index. - - Returns - ------- - structured array - """ - fpath = self.paths.fof_cat(nsnap, nsim, "quijote", False) - fof = FoF_catalog(fpath, nsnap, long_ids=False, swap=False, - SFR=False, read_IDs=False) - - cols = [("x", numpy.float32), - ("y", numpy.float32), - ("z", numpy.float32), - ("vx", numpy.float32), - ("vy", numpy.float32), - ("vz", numpy.float32), - ("group_mass", numpy.float32), - ("npart", numpy.int32), - ("index", numpy.int32) - ] - data = cols_to_structured(fof.GroupLen.size, cols) - - pos = fof.GroupPos / 1e3 - vel = fof.GroupVel * (1 + self.read_info(nsnap, nsim)["redshift"]) - for i, p in enumerate(["x", "y", "z"]): - data[p] = pos[:, i] - data[f"v{p}"] = vel[:, i] - data["group_mass"] = fof.GroupMass * 1e10 - data["npart"] = fof.GroupLen - # We want to start indexing from 1. Index 0 is reserved for - # particles unassigned to any FoF group. - data["index"] = 1 + numpy.arange(data.size, dtype=numpy.int32) - return data - - -############################################################################### -# Supplementary functions # -############################################################################### - - -def make_halomap_dict(halomap): - """ - Make a dictionary mapping halo IDs to their start and end indices in the - snapshot particle array. - """ - return {hid: (int(start), int(end)) for hid, start, end in halomap} - - -def load_halo_particles(hid, particles, hid2map): - """ - Load a halo's particles from a particle array. If it is not there, i.e - halo has no associated particles, return `None`. - - Parameters - ---------- - hid : int - Halo ID. - particles : 2-dimensional array - Array of particles. - hid2map : dict - Dictionary mapping halo IDs to `halo_map` array positions. - - Returns - ------- - parts : 1- or 2-dimensional array - """ - try: - k0, kf = hid2map[hid] - return particles[k0:kf + 1] - except KeyError: - return None - - -def convert_str_to_num(s): - """ - Convert a string representation of a number to its appropriate numeric type - (int or float). - - Parameters - ---------- - s : str - The string representation of the number. - - Returns - ------- - num : int or float - """ - try: - return int(s) - except ValueError: - try: - return float(s) - except ValueError: - warn(f"Cannot convert string '{s}' to number", UserWarning) - return s diff --git a/csiborgtools/read/utils.py b/csiborgtools/read/utils.py deleted file mode 100644 index 196e45a..0000000 --- a/csiborgtools/read/utils.py +++ /dev/null @@ -1,126 +0,0 @@ -# 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. -from os.path import isfile - -import numpy -from h5py import File - -############################################################################### -# Array manipulation # -############################################################################### - - -def cols_to_structured(N, cols): - """ - Allocate a structured array from `cols`, a list of (name, dtype) tuples. - """ - if not (isinstance(cols, list) - and all(isinstance(c, tuple) and len(c) == 2 for c in cols)): - raise TypeError("`cols` must be a list of (name, dtype) tuples.") - - names, formats = zip(*cols) - dtype = {"names": names, "formats": formats} - - return numpy.full(N, numpy.nan, dtype=dtype) - - -def add_columns(arr, X, cols): - """ - Add new columns `X` to a record array `arr`. Creates a new array. - """ - cols = [cols] if isinstance(cols, str) else cols - - # Convert X to a list of 1D arrays for consistency - if isinstance(X, numpy.ndarray) and X.ndim == 1: - X = [X] - elif isinstance(X, numpy.ndarray): - raise ValueError("`X` should be a 1D array or a list of 1D arrays.") - - if len(X) != len(cols): - raise ValueError("Mismatch between `X` and `cols` lengths.") - - if not all(isinstance(x, numpy.ndarray) and x.ndim == 1 for x in X): - raise ValueError("All elements of `X` should be 1D arrays.") - - if not all(x.size == arr.size for x in X): - raise ValueError("All arrays in `X` must have the same size as `arr`.") - - # Define new dtype - dtype = list(arr.dtype.descr) + [(col, x.dtype) for col, x in zip(cols, X)] - - # Create a new array and fill in values - out = numpy.empty(arr.size, dtype=dtype) - for col in arr.dtype.names: - out[col] = arr[col] - for col, x in zip(cols, X): - out[col] = x - - return out - - -def rm_columns(arr, cols): - """ - Remove columns `cols` from a structured array `arr`. Allocates a new array. - """ - # Ensure cols is a list - cols = [cols] if isinstance(cols, str) else cols - - # Check columns we wish to delete are in the array - missing_cols = [col for col in cols if col not in arr.dtype.names] - if missing_cols: - raise ValueError(f"Columns `{missing_cols}` not in `arr`.") - - # Define new dtype without the cols to be deleted - new_dtype = [(n, dt) for n, dt in arr.dtype.descr if n not in cols] - - # Allocate a new array and fill in values - out = numpy.empty(arr.size, dtype=new_dtype) - for name in out.dtype.names: - out[name] = arr[name] - - return out - - -def flip_cols(arr, col1, col2): - """ - Flip values in columns `col1` and `col2` of a structured array `arr`. - """ - if col1 not in arr.dtype.names or col2 not in arr.dtype.names: - raise ValueError(f"Both `{col1}` and `{col2}` must exist in `arr`.") - - arr[col1], arr[col2] = numpy.copy(arr[col2]), numpy.copy(arr[col1]) - - -############################################################################### -# h5py functions # -############################################################################### - - -def read_h5(path): - """ - Return and return and open `h5py.File` object. - - Parameters - ---------- - path : str - Path to the file. - - Returns - ------- - file : `h5py.File` - """ - if not isfile(path): - raise IOError(f"File `{path}` does not exist!") - return File(path, "r") diff --git a/csiborgtools/utils.py b/csiborgtools/utils.py index 8f50076..6cfbb98 100644 --- a/csiborgtools/utils.py +++ b/csiborgtools/utils.py @@ -244,7 +244,7 @@ def real2redshift(pos, vel, observer_location, observer_velocity, box, Observer location in `Mpc / h`. observer_velocity: 1-dimensional array `(3,)` Observer velocity in `km / s`. - box : py:class:`csiborg.read.CSiBORGBox` + box : py:class:`csiborg.read.CSiBORG1Box` Box units. periodic_wrap : bool, optional Whether to wrap around the box, particles may be outside the default diff --git a/notebooks/powerspectrum_test.ipynb b/notebooks/powerspectrum_test.ipynb index a767471..d0e16db 100644 --- a/notebooks/powerspectrum_test.ipynb +++ b/notebooks/powerspectrum_test.ipynb @@ -567,7 +567,7 @@ "metadata": {}, "outputs": [], "source": [ - "box = csiborgtools.read.CSiBORGBox(951, 7444, paths)\n", + "box = csiborgtools.read.CSiBORG1Box(951, 7444, paths)\n", "\n", "field_generator = csiborgtools.field.DensityField(box, \"PCS\")" ] diff --git a/old/cluster_crosspk.py b/old/cluster_crosspk.py index a2ce33d..fdb6841 100644 --- a/old/cluster_crosspk.py +++ b/old/cluster_crosspk.py @@ -50,8 +50,8 @@ nproc = comm.Get_size() MAS = "CIC" # mass asignment scheme paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) -box = csiborgtools.read.CSiBORGBox(paths) -reader = csiborgtools.read.CSiBORGReader(paths) +box = csiborgtools.read.CSiBORG1Box(paths) +reader = csiborgtools.read.CSiBORG1Reader(paths) ics = paths.get_ics("csiborg") nsims = len(ics) diff --git a/old/fit_profiles.py b/old/fit_profiles.py index 7f3ddba..a1bd141 100644 --- a/old/fit_profiles.py +++ b/old/fit_profiles.py @@ -59,7 +59,7 @@ for i, nsim in enumerate(nsims): now = datetime.now() print(f"{now}: calculating {i}th simulation `{nsim}`.", flush=True) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) f = csiborgtools.read.read_h5(paths.particles(nsim, "csiborg")) particles = f["particles"] diff --git a/old/mv_fofmembership.py b/old/mv_fofmembership.py index 5fdff29..c22b334 100644 --- a/old/mv_fofmembership.py +++ b/old/mv_fofmembership.py @@ -96,7 +96,7 @@ def sort_fofid(nsim, verbose=True): # Columns are halo ID, particle ID. fof = numpy.load(fpath) - reader = csiborgtools.read.CSiBORGReader(paths) + reader = csiborgtools.read.CSiBORG1Reader(paths) pars_extract = ["x"] # Dummy variable __, pids = reader.read_snapshot(nsnap, nsim, pars_extract, return_structured=False, verbose=verbose) diff --git a/old/pre_dumppart.py b/old/pre_dumppart.py index fba56dd..0565530 100644 --- a/old/pre_dumppart.py +++ b/old/pre_dumppart.py @@ -79,7 +79,7 @@ def main(nsim, simname, verbose): """ paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) if simname == "csiborg": - partreader = csiborgtools.read.CSiBORGReader(paths) + partreader = csiborgtools.read.CSiBORG1Reader(paths) else: partreader = csiborgtools.read.QuijoteReader(paths) @@ -114,7 +114,7 @@ def main(nsim, simname, verbose): # In case of CSiBORG, we need to convert the mass and velocities from # box units. if simname == "csiborg": - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) parts[:, [3, 4, 5]] = box.box2vel(parts[:, [3, 4, 5]]) parts[:, 6] = box.box2solarmass(parts[:, 6]) diff --git a/scripts/dump_to_ascii.py b/scripts/dump_to_ascii.py deleted file mode 100644 index 645c803..0000000 --- a/scripts/dump_to_ascii.py +++ /dev/null @@ -1,116 +0,0 @@ -# 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. -"""Convert the HDF5 CSiBORG particle file to an ASCII file.""" -from argparse import ArgumentParser - -import h5py -import numpy -from mpi4py import MPI -from taskmaster import work_delegation -from tqdm import trange - -import csiborgtools -from utils import get_nsims - - -def positions_to_ascii(positions, output_filename, boxsize=None, - chunk_size=50_000, verbose=True): - """ - Convert array of positions to an ASCII file. If `boxsize` is given, - multiples the positions by it. - """ - total_size = len(positions) - - if verbose: - print(f"Number of rows to write: {total_size}") - - with open(output_filename, 'w') as out_file: - # Write the header - out_file.write("#px py pz\n") - - # Loop through data in chunks - for i in trange(0, total_size, chunk_size, - desc=f"Writing to ... `{output_filename}`", - disable=not verbose): - - end = i + chunk_size - if end > total_size: - end = total_size - - data_chunk = positions[i:end] - # Convert to positions Mpc / h - data_chunk = data_chunk[:, :3] - - if boxsize is not None: - data_chunk *= boxsize - - chunk_str = "\n".join([f"{x:.4f} {y:.4f} {z:.4f}" - for x, y, z in data_chunk]) - out_file.write(chunk_str + "\n") - - -def extract_positions(nsim, simname, paths, kind): - """ - Extract either the particle or halo positions. - """ - if kind == "particles": - fname = paths.processed_output(nsim, simname, "FOF") - return h5py.File(fname, 'r')["snapshot_final/pos"][:] - - if kind == "particles_rsp": - raise NotImplementedError("RSP of particles is not implemented yet.") - - fpath = paths.observer_peculiar_velocity("PCS", 512, nsim) - vpec_observer = numpy.load(fpath)["observer_vp"][0, :] - cat = csiborgtools.read.CSiBORGHaloCatalogue( - nsim, paths, "halo_catalogue", "FOF", bounds={"dist": (0, 155.5)}, - observer_velocity=vpec_observer) - - if kind == "halos": - return cat["cartesian_pos"] - - if kind == "halos_rsp": - return cat["cartesian_redshift_pos"] - - raise ValueError(f"Unknown kind `{kind}`. Allowed values are: " - "`particles`, `particles_rsp`, `halos`, `halos_rsp`.") - - -def main(args, paths): - boxsize = 677.7 if "particles" in args.kind else None - pos = extract_positions(args.nsim, args.simname, paths, args.kind) - output_filename = paths.ascii_positions(args.nsim, args.kind) - positions_to_ascii(pos, output_filename, boxsize=boxsize) - - -if __name__ == "__main__": - parser = ArgumentParser() - parser.add_argument("--kind", type=str, required=True, - choices=["particles", "particles_rsp", "halos", "halos_rsp"], # noqa - help="Kind of data to extract.") - parser.add_argument("--nsims", type=int, nargs="+", default=None, - help="IC realisations. If `-1` processes all.") - parser.add_argument("--simname", type=str, default="csiborg", - choices=["csiborg"], - help="Simulation name") - args = parser.parse_args() - - paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) - nsims = get_nsims(args, paths) - - def _main(nsim): - main(nsim, paths, args.kind) - - work_delegation(_main, nsims, MPI.COMM_WORLD) diff --git a/scripts/field_prop.py b/scripts/field_prop.py index f7fddac..e417941 100644 --- a/scripts/field_prop.py +++ b/scripts/field_prop.py @@ -49,10 +49,11 @@ def density_field(nsim, parser_args, to_save=True): """ paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) fname = paths.processed_output(nsim, "csiborg", "halo_catalogue") if not parser_args.in_rsp: + # TODO I removed this function snap = csiborgtools.read.read_h5(fname)["snapshot_final"] pos = snap["pos"] mass = snap["mass"] @@ -94,7 +95,7 @@ def velocity_field(nsim, parser_args, to_save=True): paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) fname = paths.processed_output(nsim, "csiborg", "halo_catalogue") snap = csiborgtools.read.read_h5(fname)["snapshot_final"] @@ -127,7 +128,7 @@ def radvel_field(nsim, parser_args, to_save=True): paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) vel = numpy.load(paths.field("velocity", parser_args.MAS, parser_args.grid, nsim, parser_args.in_rsp)) @@ -154,7 +155,7 @@ def potential_field(nsim, parser_args, to_save=True): """ paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) if not parser_args.in_rsp: rho = numpy.load(paths.field( @@ -192,7 +193,7 @@ def environment_field(nsim, parser_args, to_save=True): """ paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) rho = numpy.load(paths.field( "density", parser_args.MAS, parser_args.grid, nsim, in_rsp=False)) diff --git a/scripts/process_snapshot.py b/scripts/process_snapshot.py index 7a91645..09c3901 100644 --- a/scripts/process_snapshot.py +++ b/scripts/process_snapshot.py @@ -371,4 +371,4 @@ if __name__ == "__main__": def _main(nsim): main(nsim, args) - work_delegation(_main, nsims, MPI.COMM_WORLD) + work_delegation(_main, nsims, MPI.COMM_WORLD) \ No newline at end of file diff --git a/scripts/field_obs_vp.py b/scripts_independent/field_obs_vp.py similarity index 100% rename from scripts/field_obs_vp.py rename to scripts_independent/field_obs_vp.py diff --git a/scripts_independent/field_sph.py b/scripts_independent/field_sph.py new file mode 100644 index 0000000..01eff58 --- /dev/null +++ b/scripts_independent/field_sph.py @@ -0,0 +1,201 @@ +# 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. +""" +Script to construct the density and velocity fields for a simulation snapshot. +The SPH filter is implemented in the cosmotool package. +""" +from argparse import ArgumentParser +from os import environ, remove +from os.path import join, exists +import subprocess +from datetime import datetime + +import hdf5plugin # noqa +import numpy as np +from h5py import File + + +def now(): + return datetime.now() + + +def generate_unique_id(file_path): + """ + Generate a unique ID for a file path. + """ + return file_path.replace('/', '_').replace(':', '_') + + +def prepare_random(temporary_output_path, npart=100, dtype=np.float32): + """ + Prepare a random dataset for the SPH filter. + """ + print("Preparing random dataset.", flush=True) + arr = np.full((npart, 7), np.nan, dtype=dtype) + + arr[:, :3] = np.random.uniform(0, 1, (npart, 3)) + arr[:, 3:6] = np.random.normal(0, 1, (npart, 3)) + arr[:, 6] = np.ones(npart, dtype=dtype) + + dset = np.random.random((npart, 7)).astype(dtype) + dset[:, 6] = np.ones(npart, dtype=dtype) + + with File(temporary_output_path, 'w') as target: + target.create_dataset("particles", data=dset, dtype=dtype) + + return 1. + + +def prepare_gadget(snapshot_path, temporary_output_path): + """ + Prepare a GADGET snapshot for the SPH filter. Assumes there is only a + single file per snapshot. + """ + with File(snapshot_path, 'r') as source, File(temporary_output_path, 'w') as target: # noqa + boxsize = source["Header"].attrs["BoxSize"] + + npart = sum(source["Header"].attrs["NumPart_Total"]) + nhighres = source["Header"].attrs["NumPart_Total"][1] + + dset = target.create_dataset("particles", (npart, 7), dtype=np.float32) + + # Copy to this dataset the high-resolution particles. + dset[:nhighres, :3] = source["PartType1/Coordinates"][:] + dset[:nhighres, 3:6] = source["PartType1/Velocities"][:] + dset[:nhighres, 6] = np.ones(nhighres, dtype=np.float32) * source["Header"].attrs["MassTable"][1] # noqa + + # Now copy the low-resolution particles. + dset[nhighres:, :3] = source["PartType5/Coordinates"][:] + dset[nhighres:, 3:6] = source["PartType5/Velocities"][:] + dset[nhighres:, 6] = source["PartType5/Masses"][:] + + return boxsize + + +def run_sph_filter(particles_path, output_path, boxsize, resolution, + SPH_executable): + """ + Run the SPH filter on a snapshot. + """ + if not exists(particles_path): + raise RuntimeError(f"Particles file `{particles_path}` does not exist.") # noqa + if not isinstance(boxsize, (int, float)): + raise TypeError("`boxsize` must be a number.") + if not isinstance(resolution, int): + raise TypeError("`resolution` must be an integer.") + if not exists(SPH_executable): + raise RuntimeError(f"SPH executable `{SPH_executable}` does not exist.") # noqa + + command = [SPH_executable, particles_path, str(1e14), str(boxsize), + str(resolution), str(0), str(0), str(0), output_path, "1"] + print(f"{now()}: executing `simple3DFilter`.", flush=True) + start_time = now() + process = subprocess.Popen( + command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, + universal_newlines=True) + + for line in iter(process.stdout.readline, ""): + print(line, end="", flush=True) + process.wait() + + if process.returncode != 0: + raise RuntimeError("`simple3DFilter`failed.") + else: + dt = now() - start_time + print(f"{now()}: `simple3DFilter`completed successfully in {dt}.", + flush=True) + + +def main(snapshot_path, output_path, resolution, scratch_space, SPH_executable, + snapshot_kind): + """ + Construct the density and velocity fields for a simulation snapshot using + `cosmotool` [1]. + + Parameters + ---------- + snapshot_path : str + Path to the simulation snapshot. + output_path : str + Path to the output HDF5 file. + resolution : int + Resolution of the density field. + scratch_space : str + Path to a folder where temporary files can be stored. + SPH_executable : str + Path to the `simple3DFilter` executable [1]. + snapshot_kind : str + Kind of the simulation snapshot. Currently only `gadget4` is supported. + + Returns + ------- + None + + References + ---------- + [1] https://bitbucket.org/glavaux/cosmotool/src/master/sample/simple3DFilter.cpp # noqa + """ + if snapshot_kind != "gadget4": + raise NotImplementedError("Only GADGET HDF5 snapshots are supported.") + + print("---------- SPH Density & Velocity Field Job Information ----------") + print(f"Snapshot path: {snapshot_path}") + print(f"Output path: {output_path}") + print(f"Resolution: {resolution}") + print(f"Scratch space: {scratch_space}") + print(f"SPH executable: {SPH_executable}") + print(f"Snapshot kind: {snapshot_kind}") + print("------------------------------------------------------------------") + print(flush=True) + + temporary_output_path = join( + scratch_space, generate_unique_id(snapshot_path)) + + if not temporary_output_path.endswith(".hdf5"): + raise RuntimeError("Temporary output path must end with `.hdf5`.") + + print(f"{now()}: preparing snapshot...", flush=True) + boxsize = prepare_gadget(snapshot_path, temporary_output_path) + print(f"{now()}: wrote temporary data to {temporary_output_path}.", + flush=True) + + run_sph_filter(temporary_output_path, output_path, boxsize, resolution, + SPH_executable) + print(f"{now()}: removing the temporary snapshot file.", flush=True) + try: + remove(temporary_output_path) + except FileNotFoundError: + pass + + +if __name__ == "__main__": + parser = ArgumentParser(description="Generate SPH density and velocity field.") # noqa + parser.add_argument("--snapshot_path", type=str, required=True, + help="Path to the simulation snapshot.") + parser.add_argument("--output_path", type=str, required=True, + help="Path to the output HDF5 file.") + parser.add_argument("--resolution", type=int, required=True, + help="Resolution of the density and velocity field.") + parser.add_argument("--scratch_space", type=str, required=True, + help="Path to a folder where temporary files can be stored.") # noqa + parser.add_argument("--SPH_executable", type=str, required=True, + help="Path to the `simple3DFilter` executable.") + parser.add_argument("--snapshot_kind", type=str, required=True, + choices=["gadget4"], + help="Kind of the simulation snapshot.") + args = parser.parse_args() + + main(args.snapshot_path, args.output_path, args.resolution, + args.scratch_space, args.SPH_executable, args.snapshot_kind) diff --git a/scripts_independent/field_sph.sh b/scripts_independent/field_sph.sh new file mode 100755 index 0000000..6c382bf --- /dev/null +++ b/scripts_independent/field_sph.sh @@ -0,0 +1,40 @@ +#!/bin/sh + +#SBATCH --ntasks-per-node=1 +#SBATCH --nodes=1 +#SBATCH --cpus-per-task=16 +#SBATCH --mem-per-cpu=7000 +#SBATCH -J SPH +#SBATCH -o output_%J.out +#SBATCH -e error_%J.err +#SBATCH -p cosma8-serial +#SBATCH -A dp016 +#SBATCH -t 04:00:00 +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --mail-user=richard.stiskalek@physics.ox.ac.uk + + +module purge +module load intel_comp/2019 +module load intel_mpi/2019 +module load hdf5 +module load fftw +module load gsl +module load cmake +module load python/3.10.12 +module list + +source /cosma/home/dp016/dc-stis1/csiborgtools/venv_csiborgtools/bin/activate +export OMP_NUM_THREADS=16 +export OMP_NESTED=true + +# ADD CHAINS HERE +snapshot_path="/cosma8/data/dp016/dc-stis1/csiborg2_main/chain_15517/output/snapshot_099_full.hdf5" +output_path="/cosma8/data/dp016/dc-stis1/csiborg2_main/field/chain_15517.hdf5" +resolution=256 +scratch_space="/cosma8/data/dp016/dc-stis1/csiborg2_main/field" +SPH_executable="/cosma8/data/dp016/dc-stis1/cosmotool/bld2/sample/simple3DFilter" +snapshot_kind="gadget4" + + +python3 field_sph.py --snapshot_path $snapshot_path --output_path $output_path --resolution $resolution --scratch_space $scratch_space --SPH_executable $SPH_executable --snapshot_kind $snapshot_kind diff --git a/scripts_independent/process_snapshot.py b/scripts_independent/process_snapshot.py new file mode 100644 index 0000000..d26cff0 --- /dev/null +++ b/scripts_independent/process_snapshot.py @@ -0,0 +1,737 @@ +# 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. +""" +Script to process simulation snapshots to sorted HDF5 files. Be careful +because reading the HDF5 file may require `hdf5plugin` package to be installed. +The snapshot particles are sorted by their halo ID, so that particles of a halo +can be accessed by slicing the array. + +CSiBORG1 reader will complain unless it can find the halomaker FOF files +where it expects them: + fdir = f"/mnt/extraspace/rstiskalek/csiborg1/chain_{self.nsim}/FOF" +""" +from abc import ABC, abstractmethod +from argparse import ArgumentParser +from datetime import datetime +from gc import collect +from glob import glob, iglob +from os import makedirs +from os.path import basename, dirname, exists, join +from warnings import catch_warnings, filterwarnings, warn + +import hdf5plugin +import numpy +import pynbody +import readgadget +from astropy import constants, units +from h5py import File +from numba import jit +from readfof import FoF_catalog +from tqdm import tqdm, trange + +MSUNCGS = constants.M_sun.cgs.value +BLOSC_KWARGS = {"cname": "blosclz", + "clevel": 9, + "shuffle": hdf5plugin.Blosc.SHUFFLE, + } + + +############################################################################### +# Utility functions # +############################################################################### + + +def now(): + """ + Return current time. + """ + return datetime.now() + + +def flip_cols(arr, col1, col2): + """ + Flip values in columns `col1` and `col2` of a structured array `arr`. + """ + if col1 not in arr.dtype.names or col2 not in arr.dtype.names: + raise ValueError(f"Both `{col1}` and `{col2}` must exist in `arr`.") + + arr[col1], arr[col2] = numpy.copy(arr[col2]), numpy.copy(arr[col1]) + + +def convert_str_to_num(s): + """ + Convert a string representation of a number to its appropriate numeric type + (int or float). + + Parameters + ---------- + s : str + The string representation of the number. + + Returns + ------- + num : int or float + """ + try: + return int(s) + except ValueError: + try: + return float(s) + except ValueError: + warn(f"Cannot convert string '{s}' to number", UserWarning) + return s + + +def cols_to_structured(N, cols): + """ + Allocate a structured array from `cols`, a list of (name, dtype) tuples. + """ + if not (isinstance(cols, list) + and all(isinstance(c, tuple) and len(c) == 2 for c in cols)): + raise TypeError("`cols` must be a list of (name, dtype) tuples.") + + names, formats = zip(*cols) + dtype = {"names": names, "formats": formats} + + return numpy.full(N, numpy.nan, dtype=dtype) + + +############################################################################### +# Base reader of snapshots # +############################################################################### + + +class BaseReader(ABC): + """Base reader layout that every subsequent reader should follow.""" + @abstractmethod + def read_info(self): + pass + + @abstractmethod + def read_snapshot(self, kind): + pass + + @abstractmethod + def read_halo_id(self, pids): + pass + + @abstractmethod + def read_halos(self): + pass + + +############################################################################### +# CSiBORG particle reader # +############################################################################### + + +class CSiBORG1Reader: + """ + Object to read in CSiBORG snapshots from the binary files and halo + catalogues. + + Parameters + ---------- + nsim : int + IC realisation index. + which_snapshot : str + Which snapshot to read. Options are `initial` or `final`. + """ + def __init__(self, nsim, which_snapshot): + self.nsim = nsim + base_dir = "/mnt/extraspace/hdesmond/" + + if which_snapshot == "initial": + self.nsnap = 1 + raise RuntimeError("TODO not implemented") + self.source_dir = None + elif which_snapshot == "final": + sourcedir = join(base_dir, f"ramses_out_{nsim}") + self.nsnap = max([int(basename(f).replace("output_", "")) + for f in glob(join(sourcedir, "output_*"))]) + self.source_dir = join(sourcedir, + f"output_{str(self.nsnap).zfill(5)}") + else: + raise ValueError(f"Unknown snapshot option `{which_snapshot}`.") + + self.output_dir = f"/mnt/extraspace/rstiskalek/csiborg1/chain_{self.nsim}" # noqa + self.output_snap = join(self.output_dir, + f"snapshot_{str(self.nsnap).zfill(5)}.hdf5") + self.output_cat = join(self.output_dir, + f"fof_{str(self.nsnap).zfill(5)}.hdf5") + self.halomaker_dir = join(self.output_dir, "FOF") + + def read_info(self): + filename = glob(join(self.source_dir, "info_*")) + if len(filename) > 1: + raise ValueError("Found too many `info` files.") + filename = filename[0] + + with open(filename, "r") as f: + info = f.read().split() + # Throw anything below ordering line out + info = numpy.asarray(info[:info.index("ordering")]) + # Get indexes of lines with `=`. Indxs before/after be keys/vals + eqs = numpy.asarray([i for i in range(info.size) if info[i] == '=']) + + keys = info[eqs - 1] + vals = info[eqs + 1] + return {key: convert_str_to_num(val) for key, val in zip(keys, vals)} + + def read_snapshot(self, kind): + with catch_warnings(): + filterwarnings("ignore", category=UserWarning) + sim = pynbody.load(self.source_dir) + + info = self.read_info() + + if kind == "pid": + x = numpy.array(sim["iord"], dtype=numpy.uint32) + elif kind == "pos": + x = numpy.array(sim[kind], dtype=numpy.float32) + # Convert box units to Mpc / h + box2mpc = (info["unit_l"] / units.kpc.to(units.cm) / info["aexp"] + * 1e-3 * info["H0"] / 100) + x *= box2mpc + elif kind == "mass": + x = numpy.array(sim[kind], dtype=numpy.float32) + # Convert box units to Msun / h + box2msun = (info["unit_d"] * info["unit_l"]**3 / MSUNCGS + * info["H0"] / 100) + x *= box2msun + elif kind == "vel": + x = numpy.array(sim[kind], dtype=numpy.float16) + # Convert box units to km / s + box2kms = (1e-2 * info["unit_l"] / info["unit_t"] / info["aexp"] + * 1e-3) + x *= box2kms + else: + raise ValueError(f"Unknown kind `{kind}`. " + "Options are: `pid`, `pos`, `vel` or `mass`.") + + # Because of a RAMSES bug x and z are flipped. + if kind in ["pos", "vel"]: + print(f"For kind `{kind}` flipping x and z.") + x[:, [0, 2]] = x[:, [2, 0]] + + del sim + collect() + + return x + + def read_halo_id(self, pids): + fpath = join(self.halomaker_dir, "*particle_membership*") + fpath = next(iglob(fpath, recursive=True), None) + if fpath is None: + raise FileNotFoundError(f"Found no Halomaker files in `{self.halomaker_dir}`.") # noqa + + print(f"{now()}: mapping particle IDs to their indices.") + pids_idx = {pid: i for i, pid in enumerate(pids)} + + # Unassigned particle IDs are assigned a halo ID of 0. + print(f"{now()}: mapping HIDs to their array indices.") + hids = numpy.zeros(pids.size, dtype=numpy.int32) + + # Read line-by-line to avoid loading the whole file into memory. + with open(fpath, 'r') as file: + for line in tqdm(file, desc="Reading membership"): + hid, pid = map(int, line.split()) + hids[pids_idx[pid]] = hid + + del pids_idx + collect() + + return hids + + def read_halos(self): + info = self.read_info() + h = info["H0"] / 100 + + fpath = join(self.halomaker_dir, "fort.132") + hid = numpy.genfromtxt(fpath, usecols=0, dtype=numpy.int32) + pos = numpy.genfromtxt(fpath, usecols=(1, 2, 3), dtype=numpy.float32) + totmass = numpy.genfromtxt(fpath, usecols=4, dtype=numpy.float32) + m200c = numpy.genfromtxt(fpath, usecols=5, dtype=numpy.float32) + + dtype = {"names": ["index", "x", "y", "z", "totpartmass", "m200c"], + "formats": [numpy.int32] + [numpy.float32] * 5} + out = numpy.full(hid.size, numpy.nan, dtype=dtype) + out["index"] = hid + out["x"] = pos[:, 0] * h + 677.7 / 2 + out["y"] = pos[:, 1] * h + 677.7 / 2 + out["z"] = pos[:, 2] * h + 677.7 / 2 + + # Because of a RAMSES bug x and z are flipped. + flip_cols(out, "x", "z") + out["totpartmass"] = totmass * 1e11 * h + out["m200c"] = m200c * 1e11 * h + + return out + + +############################################################################### +# CSiBORG2 particle reader # +############################################################################### + + +class CSiBORG2Reader(BaseReader): + """ + Object to read in CSiBORG2 snapshots. Because this is Gadget4 the final + snapshot is already sorted, however we still have to sort the initial + snapshot. + + Parameters + ---------- + nsim : int + IC realisation index. + which_snapshot : str + Which snapshot to read. Options are `initial` or `final`. + """ + def __init__(self, nsim, which_snapshot, kind): + self.nsim = nsim + if kind not in ["main", "random", "varysmall"]: + raise ValueError(f"Unknown kind `{kind}`.") + base_dir = f"/mnt/extraspace/rstiskalek/csiborg2_{kind}" + + if which_snapshot == "initial": + self.nsnap = 0 + elif which_snapshot == "final": + self.nsnap = 99 + else: + raise ValueError(f"Unknown snapshot option `{which_snapshot}`.") + + self.source_dir = join( + base_dir, f"chain_{nsim}", "output", + f"snapshot_{str(self.nsnap).zfill(3)}_full.hdf5") + + self.output_dir = join(base_dir, f"chain_{nsim}", "output") + self.output_snap = join( + self.output_dir, + f"snapshot_{str(self.nsnap).zfill(3)}_sorted.hdf5") + self.output_cat = None + + def read_info(self): + fpath = join(dirname(self.source_dir), "snapshot_99_full.hdf5") + + with File(fpath, 'r') as f: + header = f["Header"] + params = f["Parameters"] + + out = {"BoxSize": header.attrs["BoxSize"], + "MassTable": header.attrs["MassTable"], + "NumPart_Total": header.attrs["NumPart_Total"], + "Omega_m": params.attrs["Omega0"], + "Omega_l": params.attrs["OmegaLambda"], + "Omega_b": params.attrs["OmegaBaryon"], + "h": params.attrs["HubbleParam"], + "redshift": header.attrs["Redshift"], + } + return out + + def read_snapshot(self, kind): + raise RuntimeError("TODO Not implemented.") + + def read_halo_id(self, pids): + raise RuntimeError("TODO Not implemented.") + + def read_halos(self): + raise RuntimeError("TODO Not implemented.") + + +############################################################################### +# Quijote particle reader # +############################################################################### + + +class QuijoteReader: + """ + Object to read in Quijote snapshots from the binary files. + + Parameters + ---------- + nsim : int + IC realisation index. + which_snapshot : str + Which snapshot to read. Options are `initial` or `final`. + """ + def __init__(self, nsim, which_snapshot): + self.nsim = nsim + quijote_dir = "/mnt/extraspace/rstiskalek/quijote" + + if which_snapshot == "initial": + self.nsnap = -1 + snap_str = "ICs" + self.source_dir = join(quijote_dir, "Snapshots_fiducial", + str(nsim), "ICs", "ics") + elif which_snapshot == "final": + self.nsnap = 4 + snap_str = str(self.nsnap).zfill(3) + self.source_dir = join( + quijote_dir, "Snapshots_fiducial", + str(nsim), f"snapdir_{snap_str}", f"snap_{snap_str}") + else: + raise ValueError(f"Unknown snapshot option `{which_snapshot}`.") + + self.fof_dir = join(quijote_dir, "Halos_fiducial", str(nsim)) + self.output_dir = f"/mnt/extraspace/rstiskalek/quijote/fiducial_processed/chain_{self.nsim}" # noqa + self.output_snap = join(self.output_dir, f"snapshot_{snap_str}.hdf5") + self.output_cat = join(self.output_dir, f"fof_{snap_str}.hdf5") + + def read_info(self): + header = readgadget.header(self.source_dir) + out = {"BoxSize": header.boxsize / 1e3, # Mpc/h + "Nall": header.nall[1], # Tot num of particles + "PartMass": header.massarr[1] * 1e10, # Part mass in Msun/h + "Omega_m": header.omega_m, + "Omega_l": header.omega_l, + "h": header.hubble, + "redshift": header.redshift, + } + out["TotMass"] = out["Nall"] * out["PartMass"] + out["Hubble"] = (100.0 * numpy.sqrt( + header.omega_m * (1.0 + header.redshift)**3 + header.omega_l)) + return out + + def read_snapshot(self, kind): + info = self.read_info() + ptype = [1] # DM + + if kind == "pid": + return readgadget.read_block(self.source_dir, "ID ", ptype) + elif kind == "pos": + pos = readgadget.read_block(self.source_dir, "POS ", ptype) / 1e3 + return pos.astype(numpy.float32) + elif kind == "vel": + vel = readgadget.read_block(self.source_dir, "VEL ", ptype) + vel = vel.astype(numpy.float16) + vel *= (1 + info["redshift"]) # km / s + return vel + elif kind == "mass": + return numpy.full(info["Nall"], info["PartMass"], + dtype=numpy.float32) + else: + raise ValueError(f"Unknown kind `{kind}`. " + "Options are: `pid`, `pos`, `vel` or `mass`.") + + def read_halo_id(self, pids): + cat = FoF_catalog(self.fof_dir, self.nsnap) + + group_pids = cat.GroupIDs + group_len = cat.GroupLen + + # Create a mapping from particle ID to FoF group ID. + print(f"{now()}: mapping particle IDs to their indices.") + ks = numpy.insert(numpy.cumsum(group_len), 0, 0) + with catch_warnings(): + # Ignore because we are casting NaN as integer. + filterwarnings("ignore", category=RuntimeWarning) + pid2hid = numpy.full((group_pids.size, 2), numpy.nan, + dtype=numpy.uint64) + for i, (k0, kf) in enumerate(zip(ks[:-1], ks[1:])): + pid2hid[k0:kf, 0] = i + 1 + pid2hid[k0:kf, 1] = group_pids[k0:kf] + pid2hid = {pid: hid for hid, pid in pid2hid} + + # Create the final array of hids matchign the snapshot array. + # Unassigned particles have hid 0. + print(f"{now()}: mapping HIDs to their array indices.") + hids = numpy.full(pids.size, 0, dtype=numpy.uint32) + for i in trange(pids.size): + hids[i] = pid2hid.get(pids[i], 0) + + return hids + + def read_halos(self): + fof = FoF_catalog(self.fof_dir, self.nsnap, long_ids=False, swap=False, + SFR=False, read_IDs=False) + + cols = [("x", numpy.float32), + ("y", numpy.float32), + ("z", numpy.float32), + ("vx", numpy.float32), + ("vy", numpy.float32), + ("vz", numpy.float32), + ("GroupMass", numpy.float32), + ("npart", numpy.int32), + ("index", numpy.int32) + ] + data = cols_to_structured(fof.GroupLen.size, cols) + + pos = fof.GroupPos / 1e3 + vel = fof.GroupVel * (1 + self.read_info()["redshift"]) + for i, p in enumerate(["x", "y", "z"]): + data[p] = pos[:, i] + data[f"v{p}"] = vel[:, i] + data["GroupMass"] = fof.GroupMass * 1e10 + data["npart"] = fof.GroupLen + # We want to start indexing from 1. Index 0 is reserved for + # particles unassigned to any FoF group. + data["index"] = 1 + numpy.arange(data.size, dtype=numpy.uint32) + return data + + +############################################################################### +# Group Offsets # +############################################################################### + + +@jit(nopython=True, boundscheck=False) +def minmax_halo(hid, halo_ids, start_loop=0): + """ + Find the start and end index of a halo in a sorted array of halo IDs. + This is much faster than using `numpy.where` and then `numpy.min` and + `numpy.max`. + """ + start = None + end = None + + for i in range(start_loop, halo_ids.size): + n = halo_ids[i] + if n == hid: + if start is None: + start = i + end = i + elif n > hid: + break + return start, end + + +def make_offset_map(part_hids): + """ + Make group offsets for a list of particles' halo IDs. This is a + 2-dimensional array, where the first column is the halo ID, the second + column is the start index of the halo in the particle list, and the third + index is the end index of the halo in the particle list. The start index is + inclusive, while the end index is exclusive. + """ + unique_halo_ids = numpy.unique(part_hids) + unique_halo_ids = unique_halo_ids[unique_halo_ids != 0] + with catch_warnings(): + filterwarnings("ignore", category=RuntimeWarning) + halo_map = numpy.full((unique_halo_ids.size, 3), numpy.nan, + dtype=numpy.uint32) + start_loop, niters = 0, unique_halo_ids.size + for i in trange(niters): + hid = unique_halo_ids[i] + k0, kf = minmax_halo(hid, part_hids, start_loop=start_loop) + halo_map[i, :] = hid, k0, kf + start_loop = kf + + return halo_map, unique_halo_ids + + +############################################################################### +# Process the final snapshot and sort it by groups # +############################################################################### + + +def process_final_snapshot(nsim, simname): + """ + Read in the snapshot particles, sort them by their halo ID and dump + into a HDF5 file. Stores the first and last index of each halo in the + particle array for fast slicing of the array to acces particles of a single + halo. + """ + if simname == "csiborg1": + reader = CSiBORG1Reader(nsim, "final") + elif simname == "quijote": + reader = QuijoteReader(nsim, "final") + else: + raise RuntimeError(f"Simulation `{simname}` is not supported.") + + if not exists(reader.output_dir): + makedirs(reader.output_dir) + + print("---- Processing Final Snapshot Information ----") + print(f"Simulation index: {nsim}") + print(f"Simulation name: {simname}") + print(f"Output snapshot: {reader.output_snap}") + print(f"Output catalogue: {reader.output_cat}") + print("-----------------------------------------------") + print(flush=True) + + # First off load the particle IDs from the raw data. + pids = reader.read_snapshot("pid") + + # Then, load the halo ids and make sure their ordering is the same as the + # particle IDs ordering. + print(f"{now()}: loading HIDs.") + halo_ids = reader.read_halo_id(pids) + print(f"{now()}: sorting HIDs.") + + # Get a mask that sorts the halo ids and then write the information to + # the data files sorted by it. + sort_indxs = numpy.argsort(halo_ids) + halo_ids = halo_ids[sort_indxs] + + with File(reader.output_snap, 'w') as f: + print(f"{now()}: creating dataset `ParticleIDs`...", + flush=True) + f.create_dataset("ParticleIDs", data=pids[sort_indxs], + **hdf5plugin.Blosc(**BLOSC_KWARGS)) + del pids + collect() + + print(f"{now()}: creating dataset `Coordinates`...", + flush=True) + f.create_dataset( + "Coordinates", data=reader.read_snapshot("pos")[sort_indxs], + **hdf5plugin.Blosc(**BLOSC_KWARGS)) + + print(f"{now()}: creating dataset `Velocities`...", + flush=True) + f.create_dataset( + "Velocities", data=reader.read_snapshot("vel")[sort_indxs], + **hdf5plugin.Blosc(**BLOSC_KWARGS)) + + print(f"{now()}: creating dataset `Masses`...", + flush=True) + f.create_dataset( + "Masses", data=reader.read_snapshot("mass")[sort_indxs], + **hdf5plugin.Blosc(**BLOSC_KWARGS)) + + if simname == "csiborg1": + header = f.create_dataset("Header", (0,)) + header.attrs["BoxSize"] = 677.7 # Mpc/h + header.attrs["Omega0"] = 0.307 + header.attrs["OmegaBaryon"] = 0.0 + header.attrs["OmegaLambda"] = 0.693 + header.attrs["HubleParam"] = 0.6777 + header.attrs["Redshift"] = 0.0 + elif simname == "quijote": + info = reader.read_info() + + header = f.create_dataset("Header", (0,)) + header.attrs["BoxSize"] = info["BoxSize"] + header.attrs["Omega0"] = info["Omega_m"] + header.attrs["OmegaLambda"] = info["Omega_l"] + header.attrs["OmegaBaryon"] = 0.0 + header.attrs["HubleParam"] = info["h"] + header.attrs["Redshift"] = info["redshift"] + else: + raise ValueError(f"Unknown simname `{simname}`.") + + print(f"{now()}: done with `{reader.output_snap}`.", + flush=True) + + # Lastly, create the halo mapping and default catalogue. + print(f"{datetime.now()}: creating `GroupOffset`...") + halo_map, unique_halo_ids = make_offset_map(halo_ids) + # Dump the halo mapping. + with File(reader.output_cat, "w") as f: + f.create_dataset("GroupOffset", data=halo_map) + + # Add the halo finder catalogue + print(f"{now()}: adding the halo finder catalogue.") + with File(reader.output_cat, "r+") as f: + cat = reader.read_halos() + hid2pos = {hid: i for i, hid in enumerate(unique_halo_ids)} + + for key in cat.dtype.names: + x = numpy.full(unique_halo_ids.size, numpy.nan, + dtype=cat[key].dtype) + + for i in range(len(cat)): + j = hid2pos[cat["index"][i]] + x[j] = cat[key][i] + f.create_dataset(key, data=x) + + +def process_initial_snapshot(nsim, simname): + """ + Sort the initial snapshot particles according to their final snapshot and + add them to the final snapshot's HDF5 file. + """ + if simname == "csiborg1": + reader = CSiBORG1Reader(nsim, "initial") + output_snap_final = CSiBORG1Reader(nsim, "final").output_snap + elif simname == "quijote": + reader = QuijoteReader(nsim, "initial") + output_snap_final = QuijoteReader(nsim, "final").output_snap + elif "csiborg2" in simname: + reader = CSiBORG2Reader(nsim, "initial", simname.split("_")[1]) + output_snap_final = CSiBORG2Reader(nsim, "final", simname.split("_")[1]).output_snap # noqa + raise RuntimeError("TODO Not implemented.") + else: + raise RuntimeError(f"Simulation `{simname}` is not supported.") + + print("---- Processing Initial Snapshot Information ----") + print(f"Simulation index: {nsim}") + print(f"Simulation name: {simname}") + print(f"Output snapshot: {reader.output_snap}") + print(f"Output catalogue: {reader.output_cat}") + print("-----------------------------------------------") + print(flush=True) + + print(f"{now()}: loading and sorting the initial PID.") + sort_indxs = numpy.argsort(reader.read_snapshot("pid")) + + print(f"{now()}: loading the final particles.") + with File(output_snap_final, "r") as f: + sort_indxs_final = f["ParticleIDs"][:] + f.close() + + print(f"{now()}: sorting the particles according to the final snapshot.") + sort_indxs_final = numpy.argsort(numpy.argsort(sort_indxs_final)) + sort_indxs = sort_indxs[sort_indxs_final] + + del sort_indxs_final + collect() + + print(f"{now()}: loading and sorting the initial particle position.") + pos = reader.read_snapshot("pos")[sort_indxs] + + del sort_indxs + collect() + + # In Quijote some particles are positioned precisely at the edge of the + # box. Move them to be just inside. + if simname == "quijote": + boxsize = reader.read_info()["BoxSize"] + mask = pos >= boxsize + if numpy.any(mask): + spacing = numpy.spacing(pos[mask]) + assert numpy.max(spacing) <= 1e-3 + pos[mask] -= spacing + + print(f"{now()}: dumping particles `{reader.output_snap}`.") + with File(reader.output_snap, 'w') as f: + f.create_dataset("Coordinates", data=pos, + **hdf5plugin.Blosc(**BLOSC_KWARGS)) + + +############################################################################### +# Process the initial snapshot and sort it like the final snapshot # +############################################################################### + + +if __name__ == "__main__": + parser = ArgumentParser(description="Tool to manage the `raw` simulation data.") # noqa + parser.add_argument("--nsim", type=int, required=True, + help="Simulation index.") + parser.add_argument("--simname", type=str, required=True, + choices=["csiborg1", "quijote"], + help="Simulation name.") + parser.add_argument("--mode", type=int, required=True, choices=[0, 1, 2], + help="0: process final snapshot, 1: process initial snapshot, 2: process both.") # noqa + args = parser.parse_args() + + if args.mode == 0: + process_final_snapshot(args.nsim, args.simname) + elif args.mode == 1: + process_initial_snapshot(args.nsim, args.simname) + else: + process_final_snapshot(args.nsim, args.simname) + process_initial_snapshot(args.nsim, args.simname) diff --git a/scripts_independent/run_field_sph.py b/scripts_independent/run_field_sph.py new file mode 100644 index 0000000..88f8734 --- /dev/null +++ b/scripts_independent/run_field_sph.py @@ -0,0 +1,89 @@ +# 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. +""" +Script to write the SLURM submission script and submit it to the queue to +calculate the SPH density & velocity field. +""" +from os import system + + +def write_submit(chain_index, kind, resolution, nthreads): + if kind not in ["main", "random", "varysmall"]: + raise RuntimeError(f"Unknown kind `{kind}`.") + + txt = f"""#!/bin/sh + +#SBATCH --ntasks-per-node=1 +#SBATCH --nodes=1 +#SBATCH --cpus-per-task={nthreads} +#SBATCH --mem-per-cpu=7000 +#SBATCH -J SPH_{chain_index} +#SBATCH -o output_{chain_index}_%J.out +#SBATCH -e error_{chain_index}_%J.err +#SBATCH -p cosma8-serial +#SBATCH -A dp016 +#SBATCH -t 16:00:00 +#SBATCH --mail-type=BEGIN,END,FAIL +#SBATCH --mail-user=richard.stiskalek@physics.ox.ac.uk + + +module purge +module load intel_comp/2019 +module load intel_mpi/2019 +module load hdf5 +module load fftw +module load gsl +module load cmake +module load python/3.10.12 +module list + +source /cosma/home/dp016/dc-stis1/csiborgtools/venv_csiborgtools/bin/activate +export OMP_NUM_THREADS={nthreads} +export OMP_NESTED=true + +snapshot_path="/cosma8/data/dp016/dc-stis1/csiborg2_{kind}/chain_{chain_index}/output/snapshot_099_full.hdf5" +output_path="/cosma8/data/dp016/dc-stis1/csiborg2_{kind}/field/chain_{chain_index}_{resolution}.hdf5" +resolution={resolution} +scratch_space="/snap8/scratch/dp016/dc-stis1/" +SPH_executable="/cosma8/data/dp016/dc-stis1/cosmotool/bld2/sample/simple3DFilter" +snapshot_kind="gadget4" + +python3 field_sph.py --snapshot_path $snapshot_path --output_path $output_path --resolution $resolution --scratch_space $scratch_space --SPH_executable $SPH_executable --snapshot_kind $snapshot_kind +""" + fname = f"submit_SPH_{kind}_{chain_index}.sh" + print(f"Writing file: `{fname}`.") + with open(fname, "w") as txtfile: + txtfile.write(txt) + # Make the file executable + system(f"chmod +x {fname}") + return fname + + +if __name__ == "__main__": + # kind = "main" + # chains = [15617, 15717, 15817, 15917, 16017, 16117, 16217, 16317, 16417, 16517, 16617, 16717, 16817, 16917, 17017, 17117, 17217, 17317, 17417] + + # kind = "varysmall" + # chains = ["16417_001", "16417_025", "16417_050", "16417_075", "16417_100", "16417_125", "16417_150", "16417_175", "16417_200", "16417_225", "16417_250", "16417_275", "16417_300", "16417_325", "16417_350", "16417_375", "16417_400", "16417_425", "16417_450", "16417_475"] + + kind = "random" + chains = [1, 25, 50, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475] + + resolution = 1024 + nthreads = 32 + + for chain_index in chains: + fname = write_submit(chain_index, kind, resolution, nthreads) + system(f"sbatch {fname}") diff --git a/scripts_independent/run_process_snapshot.py b/scripts_independent/run_process_snapshot.py new file mode 100644 index 0000000..4688d3e --- /dev/null +++ b/scripts_independent/run_process_snapshot.py @@ -0,0 +1,31 @@ +# 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. +from os import system + +if __name__ == "__main__": + # Quijote chains + chains = [1] + simname = "quijote" + mode = 2 + + env = "/mnt/zfsusers/rstiskalek/csiborgtools/venv_csiborg/bin/python" + memory = 64 + + for chain in chains: + out = f"output_{simname}_{chain}_%j.out" + cmd = f"addqueue -q berg -o {out} -n 1x1 -m {memory} {env} process_snapshot.py --nsim {chain} --simname {simname} --mode {mode}" # noqa + print(cmd) + system(cmd) + print() diff --git a/scripts_independent/sort_ramseshdf5.py b/scripts_independent/sort_ramseshdf5.py new file mode 100644 index 0000000..ae93d84 --- /dev/null +++ b/scripts_independent/sort_ramseshdf5.py @@ -0,0 +1,77 @@ +# 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. + + +def add_initial_snapshot(nsim, simname, halo_finder, verbose): + """ + Sort the initial snapshot particles according to their final snapshot and + add them to the final snapshot's HDF5 file. + """ + paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) + fname = paths.processed_output(nsim, simname, halo_finder) + + if simname == "csiborg": + partreader = csiborgtools.read.CSiBORGReader(paths) + else: + partreader = csiborgtools.read.QuijoteReader(paths) + + fprint(f"processing simulation `{nsim}`.", verbose) + if simname == "csiborg": + nsnap0 = 1 + elif simname == "quijote": + nsnap0 = -1 + else: + raise ValueError(f"Unknown simulation `{simname}`.") + + fprint("loading and sorting the initial PID.", verbose) + sort_indxs = numpy.argsort(partreader.read_snapshot(nsnap0, nsim, "pid")) + + fprint("loading the final particles.", verbose) + with h5py.File(fname, "r") as f: + sort_indxs_final = f["snapshot_final/pid"][:] + f.close() + + fprint("sorting the particles according to the final snapshot.", verbose) + sort_indxs_final = numpy.argsort(numpy.argsort(sort_indxs_final)) + sort_indxs = sort_indxs[sort_indxs_final] + + del sort_indxs_final + collect() + + fprint("loading and sorting the initial particle position.", verbose) + pos = partreader.read_snapshot(nsnap0, nsim, "pos")[sort_indxs] + + del sort_indxs + collect() + + # In Quijote some particles are position precisely at the edge of the + # box. Move them to be just inside. + if simname == "quijote": + mask = pos >= 1 + if numpy.any(mask): + spacing = numpy.spacing(pos[mask]) + assert numpy.max(spacing) <= 1e-5 + pos[mask] -= spacing + + fprint(f"dumping particles for `{nsim}` to `{fname}`.", verbose) + with h5py.File(fname, "r+") as f: + if "snapshot_initial" in f.keys(): + del f["snapshot_initial"] + group = f.create_group("snapshot_initial") + group.attrs["header"] = "Initial snapshot data." + dset = group.create_dataset("pos", data=pos) + dset.attrs["header"] = "DM particle positions in box units." + + f.close() \ No newline at end of file diff --git a/scripts_plots/paper_environment.ipynb b/scripts_plots/paper_environment.ipynb new file mode 100644 index 0000000..0ca54d3 --- /dev/null +++ b/scripts_plots/paper_environment.ipynb @@ -0,0 +1,256 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" + ] + } + ], + "source": [ + "from os.path import join\n", + "\n", + "import csiborgtools\n", + "import healpy\n", + "import matplotlib.pyplot as plt\n", + "import numpy\n", + "import scienceplots # noqa\n", + "from cache_to_disk import cache_to_disk, delete_disk_caches_for_function\n", + "from h5py import File\n", + "\n", + "import plt_utils\n", + "\n", + "\n", + "sim2boxsize = {\"csiborg\" : 677.7,\n", + " \"csiborg2_main\": 676.7,\n", + " \"BORG\": 677.7,\n", + " }\n", + "\n", + "\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [], + "source": [ + "with File(\"/mnt/zfsusers/hdesmond/BORG_final/mcmc_9844.h5\", 'r') as f:\n", + " d = f[\"scalars/BORG_final_density\"][:]" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-1.0" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d.min()" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "\n", + "@cache_to_disk(30)\n", + "def _plot_sky_projected_density(nsim, simname, grid, nside, MAS=\"PCS\",\n", + " dmin=0, dmax=220, volume_weight=True):\n", + " paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)\n", + " # nsnap = max(paths.get_snapshots(nsim, simname))\n", + " # Some work here to get the box\n", + " boxsize = sim2boxsize[simname]\n", + "\n", + " if simname == \"csiborg\":\n", + " field = numpy.load(paths.field(\"density\", MAS, grid, nsim, in_rsp=False))\n", + " elif simname == \"BORG\":\n", + " with File(\"/mnt/zfsusers/hdesmond/BORG_final/mcmc_9844.h5\", 'r') as f:\n", + " field = f[\"scalars/BORG_final_density\"][:]\n", + " field = field.astype(numpy.float32)\n", + " # field = field.T\n", + " field += 1\n", + " else:\n", + " with File(\"/mnt/extraspace/rstiskalek/csiborg2_main/fields/chain_15517_1024.hdf5\", 'r') as f:\n", + " field = f[\"density\"][:].T\n", + "\n", + " # field /= numpy.mean(field)\n", + " # field += 1\n", + "\n", + " angpos = csiborgtools.field.nside2radec(nside)\n", + " dist = numpy.linspace(dmin, dmax, 1000)\n", + " return csiborgtools.field.make_sky(field, angpos=angpos, dist=dist,\n", + " boxsize=boxsize, volume_weight=volume_weight)" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_sky_projected_density(nsim, simname, grid, nside, MAS=\"PCS\",\n", + " dmin=0, dmax=220, volume_weight=True, ext=\"png\",\n", + " to_save=False):\n", + " dmap = _plot_sky_projected_density(nsim, simname, grid, nside, MAS,\n", + " dmin, dmax, volume_weight)\n", + " obs = numpy.genfromtxt(\"/mnt/zfsusers/rstiskalek/csiborgtools/data/2MPP.txt\")\n", + " \n", + " dist = obs[:, 6] * 3e5 / 100\n", + " \n", + " mask = (dist > dmin) & (dist < dmax)\n", + " obs = obs[mask]\n", + "\n", + " print(obs[:, 2].min(), obs[:, 2].max())\n", + "\n", + " with plt.style.context(plt_utils.mplstyle):\n", + " healpy.mollview(numpy.log10(dmap), fig=0, title=\"\", unit=\"\", rot=75)\n", + "\n", + " healpy.projscatter(numpy.pi / 2 - obs[:, 2], obs[:, 1], s=0.05, c=\"red\",\n", + " label=\"2M++ galaxies\")\n", + " \n", + " # for name in [\"Virgo\", \"Fornax\"]:\n", + " # d, ra, dec = csiborgtools.clusters[name].spherical_pos\n", + " # ra *= numpy.pi / 180\n", + " # dec *= numpy.pi / 180\n", + " # healpy.projscatter([numpy.pi / 2 - dec], [ra], s=30, c=\"black\", marker='x')\n", + " # healpy.projscatter(obs[:, 2] - numpy.pi / 2, obs[:, 1], s=0.25, c=\"red\",\n", + " # label=\"2M++ galaxies\")\n", + " # healpy.projscatter(obs[:, 2] - numpy.pi / 2 , obs[:, 1], s=1, c=\"red\",\n", + " # label=\"2M++ galaxies\")\n", + "\n", + " # if plot_groups:\n", + " # groups = csiborgtools.read.TwoMPPGroups(fpath=\"/mnt/extraspace/rstiskalek/catalogs/2M++_group_catalog.dat\") # noqa\n", + " # healpy.projscatter(numpy.deg2rad(groups[\"DEC\"] + 90),\n", + " # numpy.deg2rad(groups[\"RA\"]), s=1, c=\"blue\",\n", + " # label=\"2M++ groups\")\n", + "\n", + " # if plot_halos is not None or plot_groups:\n", + " # plt.legend(markerscale=5)\n", + "\n", + " if to_save:\n", + " # fout = join(plt_utils.fout, f\"sky_density_{simname}_{nsim}_from_{dmin}_to_{dmax}_vol{volume_weight}.{ext}\") # noqa\n", + " fout = \"test.png\"\n", + " print(f\"Saving to `{fout}`.\")\n", + " plt.savefig(fout, dpi=plt_utils.dpi, bbox_inches=\"tight\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 3145728/3145728 [06:06<00:00, 8572.34it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-1.50601 1.48367\n", + "Saving to `test.png`.\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# delete_disk_caches_for_function(\"_plot_sky_projected_density\")\n", + "plot_sky_projected_density(15517, \"csiborg2_main\", 512, 512, \"PCS\", dmin=100,\n", + " dmax=125, volume_weight=True, to_save=True)\n", + "# plt.savefig(\"test.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv_csiborg", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/scripts_plots/plot_data.py b/scripts_plots/plot_data.py index fecb83e..74a412e 100644 --- a/scripts_plots/plot_data.py +++ b/scripts_plots/plot_data.py @@ -307,7 +307,7 @@ def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS", print(f"Plotting projected field `{kind}`. ", flush=True) paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) + box = csiborgtools.read.CSiBORG1Box(nsnap, nsim, paths) if kind == "overdensity": field = load_field("density", nsim, grid, MAS=MAS, in_rsp=in_rsp) @@ -437,128 +437,6 @@ def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS", plt.close() -############################################################################### -# Sky distribution # -############################################################################### - - -def get_sky_label(kind, volume_weight: bool): - """ - Get the sky label for a given field kind. - """ - if volume_weight: - if kind == "density": - label = r"$\log \int_{0}^{R} r^2 \rho(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - if kind == "overdensity": - label = r"$\log \int_{0}^{R} r^2 \left[\delta(r, \mathrm{RA}, \mathrm{dec}) + 1\right] \mathrm{d} r$" # noqa - elif kind == "potential": - label = r"$\int_{0}^{R} r^2 \phi(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - elif kind == "radvel": - label = r"$\int_{0}^{R} r^2 v_r(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - else: - label = None - else: - if kind == "density": - label = r"$\log \int_{0}^{R} \rho(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - if kind == "overdensity": - label = r"$\log \int_{0}^{R} \left[\delta(r, \mathrm{RA}, \mathrm{dec}) + 1\right] \mathrm{d} r$" # noqa - elif kind == "potential": - label = r"$\int_{0}^{R} \phi(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - elif kind == "radvel": - label = r"$\int_{0}^{R} v_r(r, \mathrm{RA}, \mathrm{dec}) \mathrm{d} r$" # noqa - else: - label = None - return label - - -def plot_sky_distribution(field, nsim, grid, nside, smooth_scale=None, - MAS="PCS", plot_groups=True, dmin=0, dmax=220, - plot_halos=None, volume_weight=True, pdf=False): - r""" - Plot the sky distribution of a given field kind on the sky along with halos - and selected observations. - - TODO - ---- - - Add distance for groups. - - Parameters - ---------- - field : str - Field kind. - nsim : int - Simulation index. - grid : int - Grid size. - nside : int - Healpix nside of the sky projection. - smooth_scale : float - Smoothing scale in :math:`\mathrm{Mpc} / h`. - MAS : str, optional - Mass assignment scheme. - plot_groups : bool, optional - Whether to plot the 2M++ groups. - dmin : float, optional - Minimum projection distance in :math:`\mathrm{Mpc}/h`. - dmax : float, optional - Maximum projection distance in :math:`\mathrm{Mpc}/h`. - plot_halos : list, optional - Minimum halo mass to plot in :math:`M_\odot`. - volume_weight : bool, optional - Whether to volume weight the field. - pdf : bool, optional - Whether to save the figure as a pdf. - """ - paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) - nsnap = max(paths.get_snapshots(nsim, "csiborg")) - box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths) - - if field == "overdensity": - field = load_field("density", nsim, grid, MAS=MAS, in_rsp=False, - smooth_scale=smooth_scale) - density_gen = csiborgtools.field.DensityField(box, MAS) - field = density_gen.overdensity_field(field) + 1 - else: - field = load_field(kind, nsim, grid, MAS=MAS, in_rsp=False, - smooth_scale=smooth_scale) - - angpos = csiborgtools.field.nside2radec(nside) - dist = numpy.linspace(dmin, dmax, 500) - out = csiborgtools.field.make_sky(field, angpos=angpos, dist=dist, box=box, - volume_weight=volume_weight) - - with plt.style.context(plt_utils.mplstyle): - label = get_sky_label(kind, volume_weight) - if kind in ["density", "overdensity"]: - out = numpy.log10(out) - healpy.mollview(out, fig=0, title="", unit=label, rot=90) - - if plot_halos is not None: - bounds = {"dist": (dmin, dmax), - "totpartmass": (plot_halos, None)} - cat = csiborgtools.read.CSiBORGHaloCatalogue(nsim, paths, - bounds=bounds) - X = cat.position(cartesian=False) - healpy.projscatter(numpy.deg2rad(X[:, 2] + 90), - numpy.deg2rad(X[:, 1]), - s=5, c="red", label="CSiBORG haloes") - - if plot_groups: - groups = csiborgtools.read.TwoMPPGroups(fpath="/mnt/extraspace/rstiskalek/catalogs/2M++_group_catalog.dat") # noqa - healpy.projscatter(numpy.deg2rad(groups["DEC"] + 90), - numpy.deg2rad(groups["RA"]), s=1, c="blue", - label="2M++ groups") - - if plot_halos is not None or plot_groups: - plt.legend(markerscale=5) - - for ext in ["png"] if pdf is False else ["png", "pdf"]: - fout = join(plt_utils.fout, f"sky_{kind}_{nsim}_from_{dmin}_to_{dmax}_vol{volume_weight}.{ext}") # noqa - print(f"Saving to `{fout}`.") - plt.savefig(fout, dpi=plt_utils.dpi, bbox_inches="tight") - plt.close() - - ############################################################################### # Command line interface # ###############################################################################