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Update units to be consistent. (#78)

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* Fix Quijote units

* Updates to units

* Fix how things are loaded

* Updating definitions & conventions

* Clear up how fiducial observers in quijote work

* Refactorize array manip

* Move function definition

* More code refactoring

* Remove unused argument

* Remove `convert_from_box`

* Make a note

* Converting particle units

* Add notes about units

* Remove box constants

* Add rho_crit0

* Fix spherical overdensity mass units

* Refactor more code

* Edit catalogue kwargs

* Edit the docstring

* Edit bounds

* Add new checks for empty array

* Remove unused import

* Remove old code

* Remove old function

* Update real 2 redshift

* Clear up the RSP conv

* Add comments

* Add some units
This commit is contained in:
Richard Stiskalek 2023-07-28 21:07:28 +02:00 • committed by GitHub
parent fb4b4edf19
commit acb8d9571c
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23 changed files with 695 additions and 1079 deletions
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9
scripts/fit_hmf.py
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@ -59,12 +59,12 @@ def get_counts(nsim, bins, paths, parser_args):
if simname == "csiborg":
cat = csiborgtools.read.CSiBORGHaloCatalogue(
nsim, paths, bounds=bounds, with_lagpatch=False,
load_initial=False)
nsim, paths, bounds=bounds, load_initial=False)
logmass = numpy.log10(cat["totpartmass"])
counts = csiborgtools.fits.number_counts(logmass, bins)
elif simname == "quijote":
cat0 = csiborgtools.read.QuijoteHaloCatalogue(nsim, paths, nsnap=4)
cat0 = csiborgtools.read.QuijoteHaloCatalogue(nsim, paths, nsnap=4,
load_initial=False)
nmax = int(cat0.box.boxsize // (2 * parser_args.Rmax))**3
counts = numpy.full((nmax, len(bins) - 1), numpy.nan,
dtype=numpy.float32)
@ -74,7 +74,8 @@ def get_counts(nsim, bins, paths, parser_args):
logmass = numpy.log10(cat["group_mass"])
counts[nobs, :] = csiborgtools.fits.number_counts(logmass, bins)
elif simname == "quijote_full":
cat = csiborgtools.read.QuijoteHaloCatalogue(nsim, paths, nsnap=4)
cat = csiborgtools.read.QuijoteHaloCatalogue(nsim, paths, nsnap=4,
load_initial=False)
logmass = numpy.log10(cat["group_mass"])
counts = csiborgtools.fits.number_counts(logmass, bins)
else: