mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 08:48:02 +00:00
Add snapshots optionally directly to catalogue (#101)
* Add isinstance check * Add snapshot to cat * Rename mass_kind to mass_key * Remove import * Fix compatiblility * Remove old export * Rename import * Fix calling * Remove paths dependence * Update match script * Add check if halo has no particles
This commit is contained in:
Richard Stiskalek
GitHub
parent
7d5141cf7f
commit
a08109b997
7 changed files with 158 additions and 105 deletions
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@ -13,4 +13,4 @@
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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from .match import (ParticleOverlap, RealisationsMatcher, calculate_overlap, # noqa
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pos2cell, find_neighbour, matching_max) # noqa
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find_neighbour, matching_max) # noqa
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@ -92,22 +92,18 @@ class RealisationsMatcher(BaseMatcher):
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dlogmass : float, optional
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Tolerance on the absolute logarithmic mass difference of potential
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matches.
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mass_kind : str, optional
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Mass kind whose similarity is to be checked. Must be a valid key in the
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halo catalogue.
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"""
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_nmult = None
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_dlogmass = None
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_mass_kind = None
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_mass_key = None
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_overlapper = None
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def __init__(self, box_size, bckg_halfsize, nmult=1.0, dlogmass=2.0,
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mass_kind="totpartmass"):
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def __init__(self, box_size, bckg_halfsize, nmult=1.0, dlogmass=2.0):
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self.box_size = box_size
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self.bckg_halfsize = bckg_halfsize
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self.nmult = nmult
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self.dlogmass = dlogmass
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self.mass_kind = mass_kind
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self.mass_key = "totmass"
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self._overlapper = ParticleOverlap(box_size, bckg_halfsize)
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@ -116,6 +112,10 @@ class RealisationsMatcher(BaseMatcher):
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"""
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Multiplier of the sum of the initial Lagrangian patch sizes of a halo
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pair. Determines the range within which neighbors are returned.
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Returns
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-------
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float
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"""
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return self._nmult
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@ -130,6 +130,10 @@ class RealisationsMatcher(BaseMatcher):
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"""
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Tolerance on the absolute logarithmic mass difference of potential
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matches.
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Returns
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-------
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float
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"""
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return self._dlogmass
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@ -140,18 +144,22 @@ class RealisationsMatcher(BaseMatcher):
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self._dlogmass = float(value)
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@property
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def mass_kind(self):
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def mass_key(self):
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"""
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Mass kind whose similarity is to be checked. Must be a valid key in the
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Mass key whose similarity is to be checked. Must be a valid key in the
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halo catalogue.
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"""
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return self._mass_kind
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@mass_kind.setter
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def mass_kind(self, value):
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Returns
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-------
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str
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"""
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return self._mass_key
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@mass_key.setter
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def mass_key(self, value):
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if not isinstance(value, str):
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raise ValueError("`mass_kind` must be a string.")
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self._mass_kind = value
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raise ValueError("`mass_key` must be a string.")
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self._mass_key = value
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@property
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def overlapper(self):
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@ -195,15 +203,15 @@ class RealisationsMatcher(BaseMatcher):
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# snapshot.
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match_indxs = radius_neighbours(
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catx.knn(in_initial=True, subtract_observer=False, periodic=True),
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cat0.position(in_initial=True),
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radiusX=cat0["lagpatch_size"], radiusKNN=catx["lagpatch_size"],
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nmult=self.nmult, enforce_int32=True, verbose=verbose)
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cat0["lagpatch_coordinates"], radiusX=cat0["lagpatch_radius"],
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radiusKNN=catx["lagpatch_radius"], nmult=self.nmult,
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enforce_int32=True, verbose=verbose)
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# We next remove neighbours whose mass is too large/small.
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if self.dlogmass is not None:
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for i, indx in enumerate(match_indxs):
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# |log(M1 / M2)|
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p = self.mass_kind
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p = self.mass_key
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aratio = numpy.abs(numpy.log10(catx[p][indx] / cat0[p][i]))
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match_indxs[i] = match_indxs[i][aratio < self.dlogmass]
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@ -372,11 +380,17 @@ class ParticleOverlap(BaseMatcher):
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disable=not verbose
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)
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for hid in iterator:
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pos = cat.halo_particles(hid, "pos", in_initial=True)
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if pos is None:
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continue
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try:
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pos = cat.snapshot.halo_coordinates(hid, is_group=True)
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except ValueError as e:
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# If not particles found for this halo, just skip it.
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if str(e).startswith("Halo "):
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continue
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else:
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# If the error does not start with "Halo ", re-raise it
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raise
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mass = cat.halo_particles(hid, "mass", in_initial=True)
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mass = cat.snapshot.halo_masses(hid, is_group=True)
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pos = pos2cell(pos, self.box_size)
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@ -835,8 +849,8 @@ def load_processed_halo(hid, cat, ncells, nshift):
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maxs : len-3 tuple
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Maximum cell indices of the halo.
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"""
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pos = cat.halo_particles(hid, "pos", in_initial=True)
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mass = cat.halo_particles(hid, "mass", in_initial=True)
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pos = cat.snapshot.halo_coordinates(hid, is_group=True)
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mass = cat.snapshot.halo_masses(hid, is_group=True)
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pos = pos2cell(pos, ncells)
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mins, maxs = get_halo_cell_limits(pos, ncells=ncells, nshift=nshift)
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@ -921,7 +935,7 @@ def find_neighbour(nsim0, cats):
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assert all(isinstance(cat, type(cats[nsim0])) for cat in cats.values())
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cat0 = cats[nsim0]
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X = cat0.position(in_initial=False)
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X = cat0["lagpatch_coordinates"]
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nhalos = X.shape[0]
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num_cats = len(cats) - 1
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@ -946,7 +960,7 @@ def find_neighbour(nsim0, cats):
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###############################################################################
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def matching_max(cat0, catx, mass_kind, mult, periodic, overlap=None,
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def matching_max(cat0, catx, mass_key, mult, periodic, overlap=None,
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match_indxs=None, verbose=True):
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"""
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Halo matching algorithm based on [1].
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@ -957,7 +971,7 @@ def matching_max(cat0, catx, mass_kind, mult, periodic, overlap=None,
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Halo catalogue of the reference simulation.
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catx : instance of :py:class:`csiborgtools.read.BaseCatalogue`
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Halo catalogue of the cross simulation.
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mass_kind : str
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mass_key : str
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Name of the mass column.
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mult : float
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Multiple of R200c below which to consider a match.
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@ -985,13 +999,13 @@ def matching_max(cat0, catx, mass_kind, mult, periodic, overlap=None,
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Monthly Notices of the Royal Astronomical Society, Volume 516, Issue 3,
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November 2022, Pages 3592–3601, https://doi.org/10.1093/mnras/stac2407
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"""
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pos0 = cat0.position(in_initial=False)
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pos0 = cat0["cartesian_pos"]
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knnx = catx.knn(in_initial=False, subtract_observer=False,
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periodic=periodic)
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rad0 = cat0["r200c"]
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mass0 = numpy.log10(cat0[mass_kind])
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massx = numpy.log10(catx[mass_kind])
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mass0 = numpy.log10(cat0[mass_key])
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massx = numpy.log10(catx[mass_key])
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assert numpy.all(numpy.isfinite(mass0)) & numpy.all(numpy.isfinite(massx))
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@ -32,6 +32,8 @@ from ..params import paths_glamdring
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from ..utils import (cartesian_to_radec, great_circle_distance, number_counts,
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periodic_distance_two_points, real2redshift)
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from .paths import Paths
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from .snapshot import is_instance_of_base_snapshot_subclass
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###############################################################################
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# Base catalogue #
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@ -61,6 +63,7 @@ class BaseCatalogue(ABC):
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self._simname = None
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self._nsim = None
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self._nsnap = None
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self._snapshot = None
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self._paths = None
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@ -76,9 +79,9 @@ class BaseCatalogue(ABC):
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self._custom_keys = []
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def init_with_snapshot(self, simname, nsim, nsnap, paths, bounds, boxsize,
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observer_location, observer_velocity,
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cache_maxsize=64):
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def init_with_snapshot(self, simname, nsim, nsnap, paths, snapshot,
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bounds, boxsize, observer_location,
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observer_velocity, cache_maxsize=64):
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self.simname = simname
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self.nsim = nsim
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self.nsnap = nsnap
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@ -89,6 +92,8 @@ class BaseCatalogue(ABC):
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self.cache_maxsize = cache_maxsize
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self.snapshot = snapshot
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if bounds is not None:
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self._make_mask(bounds)
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@ -149,6 +154,31 @@ class BaseCatalogue(ABC):
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raise TypeError("`nsnap` must be an integer.")
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self._nsnap = int(nsnap)
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@property
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def snapshot(self):
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"""
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Corresponding particle snapshot. Can be either the final or initial
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one, depending on `which_snapshot`.
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Returns
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-------
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subclass of py:class:`csiborgtools.read.snapshot.BaseSnapshot`
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"""
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if self._snapshot is None:
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raise RuntimeError("`snapshot` is not set!")
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return self._snapshot
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@snapshot.setter
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def snapshot(self, snapshot):
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if snapshot is None:
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self._snapshot = None
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return
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if not is_instance_of_base_snapshot_subclass(snapshot):
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raise TypeError("`snapshot` must be a subclass of `BaseSnapshot`.")
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self._snapshot = snapshot
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@property
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def paths(self):
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"""
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@ -351,7 +381,7 @@ class BaseCatalogue(ABC):
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volume : float
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Volume in :math:`(cMpc / h)^3`.
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mass_key : str, optional
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Mass key of the catalogue.
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Mass key to get the halo masses.
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Returns
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-------
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@ -613,6 +643,8 @@ class CSiBORG1Catalogue(BaseCatalogue):
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IC realisation index.
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paths : py:class`csiborgtools.read.Paths`, optional
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Paths object.
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snapshot : subclass of py:class:`BaseSnapshot`, optional
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Snapshot object corresponding to the catalogue.
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bounds : dict, optional
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Parameter bounds; keys as parameter names, values as (min, max) or
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a boolean.
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@ -621,13 +653,13 @@ class CSiBORG1Catalogue(BaseCatalogue):
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cache_maxsize : int, optional
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Maximum number of cached arrays.
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"""
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def __init__(self, nsim, paths=None, bounds=None, observer_velocity=None,
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cache_maxsize=64):
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def __init__(self, nsim, paths=None, snapshot=None, bounds=None,
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observer_velocity=None, cache_maxsize=64):
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super().__init__()
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super().init_with_snapshot(
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"csiborg1", nsim, max(paths.get_snapshots(nsim, "csiborg1")),
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paths, bounds, 677.7, [338.85, 338.85, 338.85], observer_velocity,
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cache_maxsize)
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paths, snapshot, bounds, 677.7, [338.85, 338.85, 338.85],
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observer_velocity, cache_maxsize)
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self._custom_keys = []
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@ -691,6 +723,8 @@ class CSiBORG2Catalogue(BaseCatalogue):
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Simulation kind. Must be one of 'main', 'varysmall', or 'random'.
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paths : py:class`csiborgtools.read.Paths`, optional
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Paths object.
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snapshot : subclass of py:class:`BaseSnapshot`, optional
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Snapshot object corresponding to the catalogue.
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bounds : dict, optional
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Parameter bounds; keys as parameter names, values as (min, max) or
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a boolean.
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@ -699,12 +733,12 @@ class CSiBORG2Catalogue(BaseCatalogue):
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cache_maxsize : int, optional
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Maximum number of cached arrays.
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"""
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def __init__(self, nsim, nsnap, kind, paths=None, bounds=None,
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observer_velocity=None, cache_maxsize=64):
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def __init__(self, nsim, nsnap, kind, paths=None, snapshot=None,
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bounds=None, observer_velocity=None, cache_maxsize=64):
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super().__init__()
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super().init_with_snapshot(
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f"csiborg2_{kind}", nsim, nsnap, paths, bounds, 676.6,
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[338.3, 338.3, 338.3], observer_velocity, cache_maxsize)
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f"csiborg2_{kind}", nsim, nsnap, paths, snapshot, bounds,
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676.6, [338.3, 338.3, 338.3], observer_velocity, cache_maxsize)
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self._custom_keys = ["GroupFirstSub", "GroupContamination",
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"GroupNsubs"]
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@ -726,14 +760,14 @@ class CSiBORG2Catalogue(BaseCatalogue):
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@property
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def coordinates(self):
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# We flip x and z to undo MUSIC bug.
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# Loading directly the Gadget4 output, flip x and z to undo MUSIC bug.
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out = self._read_fof_catalogue("GroupPos")
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out[:, [0, 2]] = out[:, [2, 0]]
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return out
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@property
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def velocities(self):
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# We flip x and z to undo MUSIC bug.
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# Loading directly the Gadget4 output, flip x and z to undo MUSIC bug.
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out = self._read_fof_catalogue("GroupVel")
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out[:, [0, 2]] = out[:, [2, 0]]
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return out
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@ -789,6 +823,8 @@ class QuijoteCatalogue(BaseCatalogue):
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IC realisation index.
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paths : py:class`csiborgtools.read.Paths`, optional
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Paths object.
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snapshot : subclass of py:class:`BaseSnapshot`, optional
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Snapshot object corresponding to the catalogue.
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bounds : dict
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Parameter bounds; keys as parameter names, values as (min, max)
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tuples. Use `dist` for radial distance, `None` for no bound.
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@ -797,12 +833,13 @@ class QuijoteCatalogue(BaseCatalogue):
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cache_maxsize : int, optional
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Maximum number of cached arrays.
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"""
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def __init__(self, nsim, paths=None, bounds=None, observer_velocity=None,
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def __init__(self, nsim, paths=None, snapshot=None, bounds=None,
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observer_velocity=None,
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cache_maxsize=64):
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super().__init__()
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super().init_with_snapshot(
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"quijote", nsim, 4, paths, bounds, 1000, [500., 500., 500.,],
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observer_velocity, cache_maxsize)
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"quijote", nsim, 4, paths, snapshot, bounds, 1000,
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[500., 500., 500.,], observer_velocity, cache_maxsize)
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self._custom_keys = []
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self._bounds = bounds
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@ -718,3 +718,17 @@ class QuijoteField(CSiBORG1Field):
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"""
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def __init__(self, nsim, paths):
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super().__init__(nsim, paths)
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###############################################################################
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# Supplementary functions #
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###############################################################################
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def is_instance_of_base_snapshot_subclass(obj):
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"""
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Check if `obj` is an instance of a subclass of `BaseSnapshot`.
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"""
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return isinstance(obj, BaseSnapshot) and any(
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issubclass(cls, BaseSnapshot) for cls in obj.__class__.__bases__
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)
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@ -62,8 +62,6 @@ class PairOverlap:
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Halo catalogue corresponding to the reference simulation.
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catx : :py:class:`csiborgtools.read.CSiBORGHaloCatalogue`
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Halo catalogue corresponding to the cross simulation.
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paths : py:class`csiborgtools.read.Paths`
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CSiBORG paths object.
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min_logmass : float
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Minimum halo mass in :math:`\log_{10} M_\odot / h` to consider.
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maxdist : float, optional
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@ -75,15 +73,15 @@ class PairOverlap:
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_data = None
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_paths = None
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def __init__(self, cat0, catx, paths, min_logmass, maxdist=None):
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def __init__(self, cat0, catx, min_logmass, maxdist=None):
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if cat0.simname != catx.simname:
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raise ValueError("The two catalogues must be from the same "
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"simulation.")
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self._cat0 = cat0
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self._catx = catx
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self._paths = paths
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self.load(cat0, catx, paths, min_logmass, maxdist)
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self._paths = cat0.paths
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self.load(cat0, catx, min_logmass, maxdist)
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def load(self, cat0, catx, paths, min_logmass, maxdist=None):
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r"""
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@ -96,8 +94,6 @@ class PairOverlap:
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Halo catalogue corresponding to the reference simulation.
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catx : instance of :py:class:`csiborgtools.read.BaseCatalogue`
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Halo catalogue corresponding to the cross simulation.
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paths : py:class`csiborgtools.read.Paths`
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CSiBORG paths object.
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min_logmass : float
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Minimum halo mass in :math:`\log_{10} M_\odot / h` to consider.
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maxdist : float, optional
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@ -110,6 +106,7 @@ class PairOverlap:
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"""
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nsim0 = cat0.nsim
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nsimx = catx.nsim
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paths = cat0.paths
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# We first load in the output files. We need to find the right
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# combination of the reference and cross simulation.
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@ -473,7 +470,7 @@ class PairOverlap:
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###############################################################################
|
||||
|
||||
|
||||
def max_overlap_agreement(cat0, catx, min_logmass, maxdist, paths):
|
||||
def max_overlap_agreement(cat0, catx, min_logmass, maxdist):
|
||||
r"""
|
||||
Calculate whether for a halo `A` from catalogue `cat0` that has a maximum
|
||||
overlap with halo `B` from catalogue `catx` it is also `B` that has a
|
||||
|
|
@ -490,14 +487,12 @@ def max_overlap_agreement(cat0, catx, min_logmass, maxdist, paths):
|
|||
maxdist : float, optional
|
||||
Maximum halo distance in :math:`\mathrm{Mpc} / h` from the centre
|
||||
of the high-resolution region.
|
||||
paths : py:class`csiborgtools.read.Paths`
|
||||
CSiBORG paths object.
|
||||
|
||||
Returns
|
||||
-------
|
||||
agreement : 1-dimensional array of shape `(nhalos, )`
|
||||
"""
|
||||
kwargs = {"paths": paths, "min_logmass": min_logmass, "maxdist": maxdist}
|
||||
kwargs = {"min_logmass": min_logmass, "maxdist": maxdist}
|
||||
pair_forward = PairOverlap(cat0, catx, **kwargs)
|
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pair_backward = PairOverlap(catx, cat0, **kwargs)
|
||||
|
||||
|
|
@ -522,8 +517,7 @@ def max_overlap_agreement(cat0, catx, min_logmass, maxdist, paths):
|
|||
return agreement
|
||||
|
||||
|
||||
def max_overlap_agreements(cat0, catxs, min_logmass, maxdist, paths,
|
||||
verbose=True):
|
||||
def max_overlap_agreements(cat0, catxs, min_logmass, maxdist, verbose=True):
|
||||
"""
|
||||
Repeat `max_overlap_agreement` for many cross simulations.
|
||||
|
||||
|
|
@ -538,8 +532,7 @@ def max_overlap_agreements(cat0, catxs, min_logmass, maxdist, paths,
|
|||
agreements = [None] * len(catxs)
|
||||
desc = "Calculating maximum overlap agreement"
|
||||
for i, catx in enumerate(tqdm(catxs, desc=desc, disable=not verbose)):
|
||||
agreements[i] = max_overlap_agreement(cat0, catx, min_logmass,
|
||||
maxdist, paths)
|
||||
agreements[i] = max_overlap_agreement(cat0, catx, min_logmass, maxdist)
|
||||
|
||||
return numpy.asanyarray(agreements)
|
||||
|
||||
|
|
@ -596,8 +589,6 @@ class NPairsOverlap:
|
|||
Single reference simulation halo catalogue.
|
||||
catxs : list of :py:class:`csiborgtools.read.CSiBORGHaloCatalogue`
|
||||
List of cross simulation halo catalogues.
|
||||
paths : py:class`csiborgtools.read.Paths`
|
||||
CSiBORG paths object.
|
||||
min_logmass : float
|
||||
Minimum log mass of halos to consider.
|
||||
verbose : bool, optional
|
||||
|
|
@ -605,11 +596,11 @@ class NPairsOverlap:
|
|||
"""
|
||||
_pairs = None
|
||||
|
||||
def __init__(self, cat0, catxs, paths, min_logmass, verbose=True):
|
||||
def __init__(self, cat0, catxs, min_logmass, verbose=True):
|
||||
pairs = [None] * len(catxs)
|
||||
for i, catx in enumerate(tqdm(catxs, desc="Loading overlap objects",
|
||||
disable=not verbose)):
|
||||
pairs[i] = PairOverlap(cat0, catx, paths, min_logmass)
|
||||
pairs[i] = PairOverlap(cat0, catx, min_logmass)
|
||||
|
||||
self._pairs = pairs
|
||||
|
||||
|
|
|
|||
|
|
@ -22,7 +22,7 @@ from mpi4py import MPI
|
|||
from taskmaster import work_delegation
|
||||
|
||||
import csiborgtools
|
||||
from match_singlematch import pair_match, pair_match_max
|
||||
from match_overlap_single import pair_match, pair_match_max
|
||||
|
||||
|
||||
def get_combs(simname):
|
||||
|
|
|
|||
|
|
@ -43,39 +43,30 @@ def pair_match_max(nsim0, nsimx, simname, min_logmass, mult, verbose):
|
|||
verbose : bool
|
||||
Verbosity flag.
|
||||
"""
|
||||
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
|
||||
|
||||
if simname == "csiborg":
|
||||
mass_kind = "fof_totpartmass"
|
||||
if simname == "csiborg1":
|
||||
maxdist = 155
|
||||
periodic = False
|
||||
bounds = {"dist": (0, maxdist), mass_kind: (10**min_logmass, None)}
|
||||
cat0 = csiborgtools.read.CSiBORGHaloCatalogue(
|
||||
nsim0, paths, bounds=bounds, load_fitted=True, load_initial=False)
|
||||
catx = csiborgtools.read.CSiBORGHaloCatalogue(
|
||||
nsimx, paths, bounds=bounds, load_fitted=True, load_initial=False)
|
||||
bounds = {"dist": (0, maxdist), "totmass": (10**min_logmass, None)}
|
||||
cat0 = csiborgtools.read.CSiBORG1Catalogue(nsim0, bounds=bounds)
|
||||
catx = csiborgtools.read.CSiBORG1Catalogue(nsimx, bounds=bounds)
|
||||
elif "csiborg2" in simname:
|
||||
raise RuntimeError("CSiBORG2 currently not implemented..")
|
||||
elif simname == "quijote":
|
||||
mass_kind = "group_mass"
|
||||
maxdist = None
|
||||
periodic = True
|
||||
bounds = {mass_kind: (10**min_logmass, None)}
|
||||
cat0 = csiborgtools.read.QuijoteHaloCatalogue(
|
||||
nsim0, paths, 4, bounds=bounds, load_fitted=True,
|
||||
load_initial=False)
|
||||
catx = csiborgtools.read.QuijoteHaloCatalogue(
|
||||
nsimx, paths, 4, bounds=bounds, load_fitted=True,
|
||||
load_initial=False)
|
||||
bounds = {"totmass": (10**min_logmass, None)}
|
||||
cat0 = csiborgtools.read.QuijoteCatalogue(nsim0, bounds=bounds)
|
||||
catx = csiborgtools.read.QuijoteHaloCatalogue(nsimx, bounds=bounds)
|
||||
else:
|
||||
raise ValueError(f"Unknown simulation `{simname}`.")
|
||||
|
||||
reader = csiborgtools.summary.PairOverlap(cat0, catx, paths, min_logmass,
|
||||
maxdist=maxdist)
|
||||
reader = csiborgtools.summary.PairOverlap(cat0, catx, min_logmass, maxdist)
|
||||
out = csiborgtools.match.matching_max(
|
||||
cat0, catx, mass_kind, mult=mult, periodic=periodic,
|
||||
cat0, catx, "totmass", mult=mult, periodic=periodic,
|
||||
overlap=reader.overlap(from_smoothed=True),
|
||||
match_indxs=reader["match_indxs"], verbose=verbose)
|
||||
|
||||
fout = paths.match_max(simname, nsim0, nsimx, min_logmass, mult)
|
||||
fout = cat0.paths.match_max(simname, nsim0, nsimx, min_logmass, mult)
|
||||
if verbose:
|
||||
print(f"{datetime.now()}: saving to ... `{fout}`.", flush=True)
|
||||
numpy.savez(fout, **{p: out[p] for p in out.dtype.names})
|
||||
|
|
@ -108,23 +99,30 @@ def pair_match(nsim0, nsimx, simname, min_logmass, sigma, verbose):
|
|||
smooth_kwargs = {"sigma": sigma, "mode": "constant", "cval": 0}
|
||||
bounds = {"lagpatch_size": (0, None)}
|
||||
|
||||
if simname == "csiborg":
|
||||
if simname == "csiborg1":
|
||||
overlapper_kwargs = {"box_size": 2048, "bckg_halfsize": 512}
|
||||
mass_kind = "fof_totpartmass"
|
||||
bounds |= {"dist": (0, 155), mass_kind: (10**min_logmass, None)}
|
||||
cat0 = csiborgtools.read.CSiBORGCatalogue(
|
||||
nsim0, paths, "halo_catalogue", "FOF", mass_kind, bounds)
|
||||
catx = csiborgtools.read.CSiBORGCatalogue(
|
||||
nsimx, paths, "halo_catalogue", "FOF", mass_kind, bounds)
|
||||
bounds |= {"dist": (0, 150), "totmass": (10**min_logmass, None)}
|
||||
|
||||
snap0 = csiborgtools.read.CSIBORG1Snapshot(nsim0, 0)
|
||||
cat0 = csiborgtools.read.CSiBORG1Catalogue(nsim0, snapshot=snap0,
|
||||
bounds=bounds)
|
||||
|
||||
snapx = csiborgtools.read.CSIBORG1Snapshot(nsimx, 0)
|
||||
catx = csiborgtools.read.CSiBORGCatalogue(nsimx, snapshot=snapx,
|
||||
bounds=bounds)
|
||||
elif "csiborg2" in simname:
|
||||
raise RuntimeError("CSiBORG2 currently not implemented..")
|
||||
elif simname == "quijote":
|
||||
overlapper_kwargs = {"box_size": 512, "bckg_halfsize": 256}
|
||||
mass_kind = "group_mass"
|
||||
bounds |= {mass_kind: (10**min_logmass, None)}
|
||||
bounds |= {"totmass": (10**min_logmass, None)}
|
||||
|
||||
cat0 = csiborgtools.read.QuijoteCatalogue(
|
||||
nsim0, paths, "halo_catalogue", "FOF", mass_kind, bounds=bounds)
|
||||
catx = csiborgtools.read.QuijoteCatalogue(
|
||||
nsimx, paths, "halo_catalogue", "FOF", mass_kind, bounds=bounds)
|
||||
snap0 = csiborgtools.read.QuijoteSnapshot(nsim0, "ICs")
|
||||
cat0 = csiborgtools.read.QuijoteCatalogue(nsim0, snapshot=snap0,
|
||||
bounds=bounds)
|
||||
|
||||
snapx = csiborgtools.read.QuijoteSnapshot(nsimx, "ICs")
|
||||
catx = csiborgtools.read.QuijoteCatalogue(nsimx, snapshot=snapx,
|
||||
bounds=bounds)
|
||||
else:
|
||||
raise ValueError(f"Unknown simulation name: `{simname}`.")
|
||||
|
||||
|
|
@ -133,8 +131,7 @@ def pair_match(nsim0, nsimx, simname, min_logmass, sigma, verbose):
|
|||
delta_bckg = overlapper.make_bckg_delta(catx, delta=delta_bckg,
|
||||
verbose=verbose)
|
||||
|
||||
matcher = csiborgtools.match.RealisationsMatcher(mass_kind=mass_kind,
|
||||
**overlapper_kwargs)
|
||||
matcher = csiborgtools.match.RealisationsMatcher(**overlapper_kwargs)
|
||||
match_indxs, ngp_overlap = matcher.cross(cat0, catx, delta_bckg,
|
||||
verbose=verbose)
|
||||
|
||||
|
|
|
|||
Loading…
Reference in a new issue