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Dump radial profile information (#48)

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* add radial position path

* pep8

* Add basic fit profile dumping

* pep8

* pep8

* pep8

* pep8

* pep8

* pep8

* Update TODO

* Fix parts is None bug

* Update nb
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Richard Stiskalek 2023-04-27 01:18:30 +02:00 • committed by GitHub
parent 1a115f481d
commit f48eb6dcb0
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29 changed files with 512 additions and 395 deletions
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73
scripts/match_singlematch.py
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@ -33,66 +33,55 @@ parser.add_argument("--nsim0", type=int)
parser.add_argument("--nsimx", type=int)
parser.add_argument("--nmult", type=float)
parser.add_argument("--sigma", type=float)
parser.add_argument("--verbose", type=lambda x: bool(strtobool(x)), default=False)
parser.add_argument("--verbose", type=lambda x: bool(strtobool(x)),
default=False)
args = parser.parse_args()
paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
smooth_kwargs = {"sigma": args.sigma, "mode": "constant", "cval": 0.0}
overlapper = csiborgtools.match.ParticleOverlap()
matcher = csiborgtools.match.RealisationsMatcher()
# Load the raw catalogues (i.e. no selection) including the initial CM positions
# and the particle archives.
cat0 = csiborgtools.read.HaloCatalogue(
args.nsim0, paths, load_initial=True, rawdata=True
)
catx = csiborgtools.read.HaloCatalogue(
args.nsimx, paths, load_initial=True, rawdata=True
)
# Load the raw catalogues (i.e. no selection) including the initial CM
# positions and the particle archives.
cat0 = csiborgtools.read.HaloCatalogue(args.nsim0, paths, load_initial=True,
rawdata=True)
catx = csiborgtools.read.HaloCatalogue(args.nsimx, paths, load_initial=True,
rawdata=True)
halos0_archive = paths.initmatch_path(args.nsim0, "particles")
halosx_archive = paths.initmatch_path(args.nsimx, "particles")
# We generate the background density fields. Loads halos's particles one by one
# from the archive, concatenates them and calculates the NGP density field.
args.verbose and print(
"{}: generating the background density fields.".format(datetime.now()), flush=True
)
if args.verbose:
print(f"{datetime.now()}: generating the background density fields.",
flush=True)
delta_bckg = overlapper.make_bckg_delta(halos0_archive, verbose=args.verbose)
delta_bckg = overlapper.make_bckg_delta(
halosx_archive, delta=delta_bckg, verbose=args.verbose
)
delta_bckg = overlapper.make_bckg_delta(halosx_archive, delta=delta_bckg,
verbose=args.verbose)
# We calculate the overlap between the NGP fields.
args.verbose and print(
"{}: crossing the simulations.".format(datetime.now()), flush=True
)
match_indxs, ngp_overlap = matcher.cross(
cat0, catx, halos0_archive, halosx_archive, delta_bckg
)
if args.verbose:
print(f"{datetime.now()}: crossing the simulations.", flush=True)
match_indxs, ngp_overlap = matcher.cross(cat0, catx, halos0_archive,
halosx_archive, delta_bckg)
# We now smoothen up the background density field for the smoothed overlap calculation.
args.verbose and print(
"{}: smoothing the background field.".format(datetime.now()), flush=True
)
# We now smoothen up the background density field for the smoothed overlap
# calculation.
if args.verbose:
print(f"{datetime.now()}: smoothing the background field.", flush=True)
gaussian_filter(delta_bckg, output=delta_bckg, **smooth_kwargs)
# We calculate the smoothed overlap for the pairs whose NGP overlap is > 0.
args.verbose and print(
"{}: calculating smoothed overlaps.".format(datetime.now()), flush=True
)
smoothed_overlap = matcher.smoothed_cross(
cat0, catx, halos0_archive, halosx_archive, delta_bckg, match_indxs, smooth_kwargs
)
if args.verbose:
print(f"{datetime.now()}: calculating smoothed overlaps.", flush=True)
smoothed_overlap = matcher.smoothed_cross(cat0, catx, halos0_archive,
halosx_archive, delta_bckg,
match_indxs, smooth_kwargs)
# We save the results at long last.
fout = paths.overlap_path(args.nsim0, args.nsimx)
args.verbose and print(
"{}: saving results to `{}`.".format(datetime.now(), fout), flush=True
)
numpy.savez(
fout,
match_indxs=match_indxs,
ngp_overlap=ngp_overlap,
smoothed_overlap=smoothed_overlap,
sigma=args.sigma,
)
print("{}: all finished.".format(datetime.now()), flush=True)
if args.verbose:
print(f"{datetime.now()}: saving results to `{fout}`.", flush=True)
numpy.savez(fout, match_indxs=match_indxs, ngp_overlap=ngp_overlap,
smoothed_overlap=smoothed_overlap, sigma=args.sigma)
print(f"{datetime.now()}: all finished.", flush=True)