Update evaluate density scripts (#105)

* Edit docs

* Updated interpolated field paths

* Update field sampling script

* Add comments about flipping fields

* Fix little typo

* Edit docs

* Edit hard-coded values

* Fix paths issue

* Add docs

* Switch uncorrected dist to corrected

* Improve error message

* Convert numpy int to Python int

* Add flip of x and z

* Update README

* Edit README

* Fix bug in velocity field calculation

* Fix simple bug

* Add checked axes flipping

* Fix field units

* Update README
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Richard Stiskalek 2024-01-08 13:56:22 +01:00 committed by GitHub
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6 changed files with 268 additions and 167 deletions

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@ -1,26 +1,41 @@
# CSiBORG Tools
Tools for analysing the suite of Constrained Simulations in BORG (CSiBORG) simulations. The interface is designed to work with the following suites of simulations:
- CSiBORG1 dark matter-only RAMSES simulations (full support),
- CSiBORG2 dark matter-only Gadget4 simulations (planned full support),
- Quijote dark matter-only Gadget2 simulations (partial support),
however with little effort it can support other simulations as well.
Tools for analysing the suite of Constrained Simulations in BORG (CSiBORG) simulations. The interface is designed to work with the following suites of simulations: *CSiBORG1* (dark matter-only RAMSES), *CSiBORG2* (dark matter-only Gadget4), *Quijote* (dark-matter only Gadget2), however with little effort it can support other simulations as well.
## Ongoing projects
### Consistent halo reconstruction
- [ ] Make a sketch of the overlap definition and add it to the paper.
- [ ] Improve the storage system for overlaps and calculate it for all simulations.
### Enviromental dependence of galaxy properties
- [ ] Calculate the SPH density field for CSiBORG1.
- [x] Check that the velocity-field flipping of x and z coordinates is correct.
- [ ] Evaluate and share the density field for SDSS & SDSSxALFALFA for both CSiBORG2 and random fields.
- [ ] Check and verify the density field of galaxy colours (cannot do this now! Glamdring is super slow.)
#### Calculated data
##### SPH-density & velocity field:
- *CSiBORG2_main*, *CSiBORG2_random*, *CSiBORG2_varysmall*
- Evaluated for SDSS and SDSSxALFALFA in: *CSiBORG2_main*, *CSiBORG2_random*
## TODO
- [x] Prune old CSiBORG1 merger tree things.
- [x] Add visualiastion of the density field.
- [ ] Clear out `density` support.
- [ ] Add sorting of Gadget4 initial snapshot like final snapshot.
- [ ] Add full support for CSiBORG2 suite of simulations.
- [ ] Add SPH field calculation from cosmotools.
### Mass-assembly of massive clusters
- [ ] Make a list of nearby most-massive clusters.
- [ ] Write code to identify a counterpart of such clusters.
- [ ] Write code to make a plot of mass-assembly of all clusters within a certain mass range from the random simulations.
- [ ] Write code to compare mass-assembly of a specific cluster with respect to random ones.
## Adding a new simulation suite
### Effect of small-scale noise
- [ ] Study how the small-scale noise variation affects the overlap measure, halo concentration and spin.
box units
paths
readsim
halo_cat
### Gravitational-wave and large-scale structure
- [ ] Make the velocity field data available.
### CSiBORG meets X-ray
- [ ] Make available one example snapshot from the simulation. Mention the issue with x- and z-coordinates.
### CSiBORG advertising
- [ ] Decide on the webpage design and what to store there.
- [ ] Write a short letter describing the simulations.

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@ -249,17 +249,18 @@ class VelocityField(BaseField):
batch_vel = force_single_precision(batch_vel)
batch_mass = force_single_precision(batch_mass)
vel *= mass.reshape(-1, 1)
batch_vel *= batch_mass.reshape(-1, 1)
for i in range(3):
MASL.MA(pos, rho_vel[i], self.boxsize, self.MAS, W=vel[:, i],
verbose=False)
MASL.MA(batch_pos, rho_vel[i], self.boxsize, self.MAS,
W=batch_vel[:, i], verbose=False)
MASL.MA(pos, cellcounts, self.boxsize, self.MAS, W=mass,
verbose=False)
MASL.MA(batch_pos, cellcounts, self.boxsize, self.MAS,
W=batch_mass, verbose=False)
if end == nparts:
break
start = end
for i in range(3):
@ -272,7 +273,7 @@ class VelocityField(BaseField):
def radial_velocity(rho_vel, observer_velocity):
"""
Calculate the radial velocity field around the observer in the centre
of the box.
of the box, such that the observer velocity is 0.
Parameters
----------

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@ -367,10 +367,7 @@ class Paths:
-------
str
"""
if MAS == "SPH":
if kind not in ["density", "velocity"]:
raise ValueError("SPH field must be either `density` or `velocity`.") # noqa
if MAS == "SPH" and kind in ["density", "velocity"]:
if simname == "csiborg1":
raise ValueError("SPH field not available for CSiBORG1.")
elif simname == "csiborg2_main":
@ -416,7 +413,7 @@ class Paths:
fname = f"observer_peculiar_velocity_{simname}_{MAS}_{str(nsim).zfill(5)}_{grid}.npz" # noqa
return join(fdir, fname)
def field_interpolated(self, survey, kind, MAS, grid, nsim, in_rsp):
def field_interpolated(self, survey, simname, nsim, kind, MAS, grid):
"""
Path to the files containing the CSiBORG interpolated field for a given
survey.
@ -425,35 +422,32 @@ class Paths:
----------
survey : str
Survey name.
simname : str
Simulation name.
nsim : int
IC realisation index.
kind : str
Field type. Must be one of: `density`, `velocity`, `potential`,
`radvel`, `environment`.
Field type.
MAS : str
Mass-assignment scheme.
grid : int
Grid size.
nsim : int
IC realisation index.
in_rsp : bool
Whether the calculation is performed in redshift space.
Returns
-------
str
"""
raise NotImplementedError("This function is not implemented yet.")
assert kind in ["density", "velocity", "potential", "radvel",
"environment"]
fdir = join(self.postdir, "environment_interpolated")
if "csiborg" not in simname:
raise ValueError("Interpolated field only available for CSiBORG.")
if kind not in ["density", "potential", "radvel"]:
raise ValueError("Unsupported field type.")
fdir = join(self.postdir, "field_interpolated")
try_create_directory(fdir)
if in_rsp:
kind = kind + "_rsp"
fname = f"{survey}_{kind}_{MAS}_{str(nsim).zfill(5)}_grid{grid}.npz"
return join(fdir, fname)
nsim = str(nsim).zfill(5)
return join(fdir, f"{survey}_{simname}_{kind}_{MAS}_{nsim}_{grid}.npz")
def cross_nearest(self, simname, run, kind, nsim=None, nobs=None):
"""

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@ -516,10 +516,12 @@ class BaseField(ABC):
Base class for reading fields such as density or velocity fields.
"""
def __init__(self, nsim, paths):
if isinstance(nsim, numpy.integer):
nsim = int(nsim)
if not isinstance(nsim, int):
raise TypeError("`nsim` must be an integer")
self._nsim = nsim
raise TypeError(f"`nsim` must be an integer. Received `{type(nsim)}`.") # noqa
self._nsim = nsim
self._paths = paths
@property
@ -542,6 +544,8 @@ class BaseField(ABC):
-------
Paths
"""
if self._paths is None:
self._paths = Paths(**paths_glamdring)
return self._paths
@abstractmethod
@ -594,11 +598,12 @@ class CSiBORG1Field(BaseField):
----------
nsim : int
Simulation index.
paths : Paths
Paths object.
paths : Paths, optional
Paths object. By default, the paths are set to the `glamdring` paths.
"""
def __init__(self, nsim, paths):
def __init__(self, nsim, paths=None):
super().__init__(nsim, paths)
self._simname = "csiborg1"
def density_field(self, MAS, grid):
fpath = self.paths.field("density", MAS, grid, self.nsim, "csiborg1")
@ -606,9 +611,14 @@ class CSiBORG1Field(BaseField):
if MAS == "SPH":
with File(fpath, "r") as f:
field = f["density"][:]
field /= (677.7 * 1e3 / grid)**3 # Convert to h^2 Msun / kpc^3
else:
field = numpy.load(fpath)
# Flip x- and z-axes
if self._simname == "csiborg1":
field = field.T
return field
def velocity_field(self, MAS, grid):
@ -624,6 +634,13 @@ class CSiBORG1Field(BaseField):
else:
field = numpy.load(fpath)
# Flip x- and z-axes
if self._simname == "csiborg1":
field[0, ...] = field[0, ...].T
field[1, ...] = field[1, ...].T
field[2, ...] = field[2, ...].T
field[[0, 2], ...] = field[[2, 0], ...]
return field
@ -640,13 +657,13 @@ class CSiBORG2Field(BaseField):
----------
nsim : int
Simulation index.
paths : Paths
Paths object.
kind : str
CSiBORG2 run kind. One of `main`, `random`, or `varysmall`.
paths : Paths, optional
Paths object. By default, the paths are set to the `glamdring` paths.
"""
def __init__(self, nsim, paths, kind):
def __init__(self, nsim, kind, paths=None):
super().__init__(nsim, paths)
self.kind = kind
@ -675,11 +692,11 @@ class CSiBORG2Field(BaseField):
with File(fpath, "r") as f:
field = f["density"][:]
field *= 1e10 # Convert to Msun / h
field /= (676.6 * 1e3 / 1024)**3 # Convert to h^2 Msun / kpc^3
field = field.T # Flip x- and z-axes
field /= (676.6 * 1e3 / grid)**3 # Convert to h^2 Msun / kpc^3
else:
field = numpy.load(fpath)
field = field.T # Flip x- and z-axes
return field
def velocity_field(self, MAS, grid):
@ -688,7 +705,6 @@ class CSiBORG2Field(BaseField):
if MAS == "SPH":
with File(fpath, "r") as f:
# TODO: the x and z still have to be flipped.
density = f["density"][:]
v0 = f["p0"][:] / density
v1 = f["p1"][:] / density
@ -697,6 +713,12 @@ class CSiBORG2Field(BaseField):
else:
field = numpy.load(fpath)
# Flip x- and z-axes
field[0, ...] = field[0, ...].T
field[1, ...] = field[1, ...].T
field[2, ...] = field[2, ...].T
field[[0, 2], ...] = field[[2, 0], ...]
return field
@ -718,6 +740,7 @@ class QuijoteField(CSiBORG1Field):
"""
def __init__(self, nsim, paths):
super().__init__(nsim, paths)
self._simname = "quijote"
###############################################################################

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@ -30,7 +30,21 @@ from utils import get_nsims
def density_field(nsim, parser_args):
"""Calculate the density field."""
"""
Calculate and save the density field from the particle positions and
masses.
Parameters
----------
nsim : int
Simulation index.
parser_args : argparse.Namespace
Command line arguments.
Returns
-------
density_field : 3-dimensional array
"""
if parser_args.MAS == "SPH":
raise NotImplementedError("SPH is not implemented here. Use cosmotool")
@ -70,7 +84,21 @@ def density_field(nsim, parser_args):
def velocity_field(nsim, parser_args):
"""Calculate the velocity field."""
"""
Calculate and save the velocity field from the particle positions,
velocities and masses.
Parameters
----------
nsim : int
Simulation index.
parser_args : argparse.Namespace
Command line arguments.
Returns
-------
velocity_field : 4-dimensional array
"""
if parser_args.MAS == "SPH":
raise NotImplementedError("SPH is not implemented here. Use cosmotool")
@ -81,7 +109,7 @@ def velocity_field(nsim, parser_args):
snapshot = csiborgtools.read.CSIBORG1Snapshot(nsim, nsnap, paths)
elif "csiborg2" in parser_args.simname:
kind = parser_args.simname.split("_")[-1]
snapshot = csiborgtools.read.CSIBORG2Snapshot(nsim, nsnap, paths, kind)
snapshot = csiborgtools.read.CSIBORG2Snapshot(nsim, nsnap, kind, paths)
elif parser_args.simname == "quijote":
snapshot = csiborgtools.read.QuijoteSnapshot(nsim, nsnap, paths)
else:
@ -108,14 +136,27 @@ def velocity_field(nsim, parser_args):
def radvel_field(nsim, parser_args):
"""Calculate the radial velocity field."""
"""
Calculate and save the radial velocity field.
Parameters
----------
nsim : int
Simulation index.
parser_args : argparse.Namespace
Command line arguments.
Returns
-------
radvel_field : 3-dimensional array
"""
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
if parser_args.simname == "csiborg1":
field = csiborgtools.read.CSiBORG1Field(nsim, paths)
elif "csiborg2" in parser_args.simname:
kind = parser_args.simname.split("_")[-1]
field = csiborgtools.read.CSiBORG2Field(nsim, paths, kind)
field = csiborgtools.read.CSiBORG2Field(nsim, kind, paths)
elif parser_args.simname == "quijote":
field = csiborgtools.read.QuijoteField(nsim, paths)
else:
@ -136,11 +177,22 @@ def radvel_field(nsim, parser_args):
def observer_peculiar_velocity(nsim, parser_args):
"""
Calculate the peculiar velocity of an observer in the centre of the box
for several smoothing scales.
for several hard-coded smoothing scales.
Parameters
----------
nsim : int
Simulation index.
parser_args : argparse.Namespace
Command line arguments.
Returns
-------
observer_vp : 4-dimensional array
"""
boxsize = csiborgtools.simname2boxsize(parser_args.simname)
# NOTE thevse values are hard-coded.
smooth_scales = numpy.array([0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])
# NOTE these values are hard-coded.
smooth_scales = numpy.array([0., 2.0, 4.0, 8.0, 16.])
smooth_scales /= boxsize
if parser_args.simname == "csiborg1":

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@ -13,12 +13,13 @@
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""
Sample a CSiBORG field at galaxy positions and save the result to disk.
Script to sample a CSiBORG field at galaxy positions and save the result.
Supports additional smoothing of the field as well.
"""
from argparse import ArgumentParser
from distutils.util import strtobool
from os.path import join
import csiborgtools
import numpy
from astropy.cosmology import FlatLambdaCDM
from h5py import File
@ -26,54 +27,42 @@ from mpi4py import MPI
from taskmaster import work_delegation
from tqdm import tqdm
import csiborgtools
from utils import get_nsims
# TODO get rid of this.
# MPC2BOX = 1 / 677.7
SIM2BOXSIZE = {"csiborg1": 677.7,
"csiborg2_main": None,
"csiborg2_random": None,
"csiborg2_varysmall": None,
}
def steps(cls, survey_name):
"""Make a list of selection criteria to apply to a survey."""
if survey_name == "SDSS":
return [
# (lambda x: cls[x], ("IN_DR7_LSS",)),
# (lambda x: cls[x] < 17.6, ("ELPETRO_APPMAG_r", )),
(lambda x: cls[x] < 155.5, ("DIST", ))
]
else:
raise NotImplementedError(f"Survey `{survey_name}` not implemented.")
def open_galaxy_positions(survey_name, comm):
"""
Load the survey galaxy positions and indices, broadcasting them to all
ranks.
Load the survey's galaxy positions , broadcasting them to all ranks.
Parameters
----------
survey_name : str
Name of the survey.
comm : mpi4py.MPI.Comm
MPI communicator.
Returns
-------
pos : 2-dimensional array
Galaxy positions in the form of (distance, RA, DEC).
"""
rank, size = comm.Get_rank(), comm.Get_size()
if rank == 0:
if survey_name == "SDSS":
survey = csiborgtools.SDSS()()
pos = numpy.vstack([survey["DIST_UNCORRECTED"],
pos = numpy.vstack([survey["DIST"],
survey["RA"],
survey["DEC"]],
).T
pos = pos.astype(numpy.float32)
indxs = survey["INDEX"]
if survey_name == "SDSSxALFALFA":
elif survey_name == "SDSSxALFALFA":
survey = csiborgtools.SDSSxALFALFA()()
pos = numpy.vstack([survey["DIST_UNCORRECTED"],
pos = numpy.vstack([survey["DIST"],
survey["RA_1"],
survey["DEC_1"]],
).T
pos = pos.astype(numpy.float32)
indxs = survey["INDEX"]
elif survey_name == "GW170817":
samples = File("/mnt/extraspace/rstiskalek/GWLSS/H1L1V1-EXTRACT_POSTERIOR_GW170817-1187008600-400.hdf", 'r')["samples"] # noqa
cosmo = FlatLambdaCDM(H0=100, Om0=0.3175)
@ -82,121 +71,155 @@ def open_galaxy_positions(survey_name, comm):
samples["ra"][:] * 180 / numpy.pi,
samples["dec"][:] * 180 / numpy.pi],
).T
indxs = numpy.arange(pos.shape[0])
else:
raise NotImplementedError(f"Survey `{survey_name}` not "
"implemented.")
else:
pos = None
indxs = None
comm.Barrier()
if size > 1:
pos = comm.bcast(pos, root=0)
indxs = comm.bcast(indxs, root=0)
return pos, indxs
return pos
def evaluate_field(field, pos, nrand, smooth_scales=None, seed=42,
verbose=True):
def evaluate_field(field, pos, boxsize, smooth_scales, verbose=True):
"""
Evaluate the field at the given sky positions. Additionally, evaluate the
field at `nrand` random positions.
Evaluate the field at the given galaxy positions.
Parameters
----------
field : 3-dimensional array
Cartesian field to be evaluated.
pos : 2-dimensional array
Galaxy positions in the form of (distance, RA, DEC).
boxsize : float
Box size in `Mpc / h`.
smooth_scales : list
List of smoothing scales in `Mpc / h`.
verbose : bool
Verbosity flag.
Returns
-------
val : 2-dimensional array
Evaluated field.
"""
if smooth_scales is None:
smooth_scales = [0.]
nsample = pos.shape[0]
nsmooth = len(smooth_scales)
val = numpy.full((nsample, nsmooth), numpy.nan, dtype=field.dtype)
if nrand > 0:
rand_val = numpy.full((nsample, nsmooth, nrand), numpy.nan,
dtype=field.dtype)
else:
rand_val = None
mpc2box = 1. / boxsize
val = numpy.full((pos.shape[0], len(smooth_scales)), numpy.nan,
dtype=field.dtype)
for i, scale in enumerate(tqdm(smooth_scales, desc="Smoothing",
disable=not verbose)):
if scale > 0:
field_smoothed = csiborgtools.field.smoothen_field(
field, scale * MPC2BOX, boxsize=1, make_copy=True)
field, scale * mpc2box, boxsize=1, make_copy=True)
else:
field_smoothed = numpy.copy(field)
val[:, i] = csiborgtools.field.evaluate_sky(
field_smoothed, pos=pos, mpc2box=MPC2BOX)
field_smoothed, pos=pos, mpc2box=mpc2box)
if nrand == 0:
continue
for j in range(nrand):
gen = numpy.random.default_rng(seed + j)
pos_rand = numpy.vstack([
gen.permutation(pos[:, 0]),
gen.uniform(0, 360, nsample),
90 - numpy.rad2deg(numpy.arccos(gen.uniform(-1, 1, nsample))),
]).T
rand_val[:, i, j] = csiborgtools.field.evaluate_sky(
field_smoothed, pos=pos_rand, mpc2box=MPC2BOX)
return val, rand_val, smooth_scales
return val
def match_to_no_selection(val, rand_val, parser_args):
if parser_args.survey == "SDSSxALFALFA":
def match_to_no_selection(val, parser_args):
"""
Match the shape of the evaluated field to the shape of the survey without
any masking. Missing values are filled with `numpy.nan`.
Parameters
----------
val : n-dimensional array
Evaluated field.
parser_args : argparse.Namespace
Command line arguments.
Returns
-------
n-dimensional array
"""
if parser_args.survey == "SDSS":
survey = csiborgtools.SDSS()()
elif parser_args.survey == "SDSSxALFALFA":
survey = csiborgtools.SDSSxALFALFA()()
else:
raise NotImplementedError(
f"Survey `{parser_args.survey}` not implemented for matching to no selection.") # noqa
if val is not None:
val = csiborgtools.read.match_array_to_no_masking(val, survey)
if rand_val is not None:
rand_val = csiborgtools.read.match_array_to_no_masking(rand_val,
survey)
return val, rand_val
return csiborgtools.read.match_array_to_no_masking(val, survey)
def main(nsim, parser_args, pos, indxs, paths, verbose):
"""Load the field, interpolate it and save it to disk."""
fpath_field = paths.field(parser_args.kind, parser_args.MAS,
parser_args.grid, nsim, parser_args.in_rsp)
field = numpy.load(fpath_field)
def main(nsim, parser_args, pos, verbose):
"""
Main function to load the field, interpolate (and smooth it) it and save
the results to the disk.
val, rand_val, smooth_scales = evaluate_field(
field, pos, nrand=parser_args.nrand,
smooth_scales=parser_args.smooth_scales, verbose=verbose)
Parameters
----------
nsim : int
IC realisation.
parser_args : argparse.Namespace
Command line arguments.
pos : numpy.ndarray
Galaxy coordinates in the form of (distance, RA, DEC) where to evaluate
the field.
verbose : bool
Verbosity flag.
Returns
-------
None
"""
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
boxsize = csiborgtools.simname2boxsize(parser_args.simname)
# Get the appropriate field loader
if parser_args.simname == "csiborg1":
freader = csiborgtools.read.CSiBORG1Field(nsim)
elif "csiborg2" in parser_args.simname:
kind = parser_args.simname.split("_")[-1]
freader = csiborgtools.read.CSiBORG2Field(nsim, kind)
else:
raise NotImplementedError(f"Simulation `{parser_args.simname}` is not supported.") # noqa
# Get the appropriate field
if parser_args.kind == "density":
field = freader.density_field(parser_args.MAS, parser_args.grid)
else:
raise NotImplementedError(f"Field `{parser_args.kind}` is not supported.") # noqa
val = evaluate_field(field, pos, boxsize, parser_args.smooth_scales,
verbose=verbose)
if parser_args.survey == "GW170817":
kind = parser_args.kind
kind = kind + "_rsp" if parser_args.in_rsp else kind
fout = join(
"/mnt/extraspace/rstiskalek/GWLSS/",
f"{kind}_{parser_args.MAS}_{parser_args.grid}_{nsim}_H1L1V1-EXTRACT_POSTERIOR_GW170817-1187008600-400.npz") # noqa
f"{parser_args.kind}_{parser_args.MAS}_{parser_args.grid}_{nsim}_H1L1V1-EXTRACT_POSTERIOR_GW170817-1187008600-400.npz") # noqa
else:
fout = paths.field_interpolated(parser_args.survey, parser_args.kind,
parser_args.MAS, parser_args.grid,
nsim, parser_args.in_rsp)
fout = paths.field_interpolated(
parser_args.survey, parser_args.simname, nsim, parser_args.kind,
parser_args.MAS, parser_args.grid)
# The survey above had some cuts, however for compatibility we want
# the same shape as the `uncut` survey
val, rand_val = match_to_no_selection(val, rand_val, parser_args)
val = match_to_no_selection(val, parser_args)
if verbose:
print(f"Saving to ... `{fout}`.")
numpy.savez(fout, val=val, rand_val=rand_val, indxs=indxs,
smooth_scales=smooth_scales)
numpy.savez(fout, val=val, smooth_scales=parser_args.smooth_scales)
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument("--nsims", type=int, nargs="+", default=None,
help="IC realisations. If `-1` processes all.")
parser.add_argument("--simname", type=str, default="csiborg1",
choices=["csiborg1", "csiborg2_main", "csiborg2_random", "csiborg2_varysmall"], # noqa
help="Simulation name")
parser.add_argument("--survey", type=str, required=True,
choices=["SDSS", "SDSSxALFALFA", "GW170817"],
help="Galaxy survey")
@ -207,24 +230,17 @@ if __name__ == "__main__":
"potential"],
help="What field to interpolate.")
parser.add_argument("--MAS", type=str,
choices=["NGP", "CIC", "TSC", "PCS"],
choices=["NGP", "CIC", "TSC", "PCS", "SPH"],
help="Mass assignment scheme.")
parser.add_argument("--grid", type=int, help="Grid resolution.")
parser.add_argument("--in_rsp", type=lambda x: bool(strtobool(x)),
help="Field in RSP?")
parser.add_argument("--nrand", type=int, required=True,
help="Number of rand. positions to evaluate the field")
parser.add_argument("--simname", type=str, default="csiborg1",
choices=["csiborg1"], help="Simulation name")
args = parser.parse_args()
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
nsims = get_nsims(args, paths)
pos, indxs = open_galaxy_positions(args.survey, MPI.COMM_WORLD)
pos = open_galaxy_positions(args.survey, MPI.COMM_WORLD)
def _main(nsim):
main(nsim, args, pos, indxs, paths,
verbose=MPI.COMM_WORLD.Get_size() == 1)
main(nsim, args, pos, verbose=MPI.COMM_WORLD.Get_size() == 1)
work_delegation(_main, nsims, MPI.COMM_WORLD)