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add distance cut

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This commit is contained in:
rstiskalek 2022-11-25 16:45:27 +00:00
parent d8adf56614
commit 2a5d6a03b6
1 changed files with 17 additions and 9 deletions
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26
csiborgtools/read/make_cat.py
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@ -34,9 +34,11 @@ class HaloCatalogue:
---------- ----------
paths : py:class:`csiborgtools.read.CSiBORGPaths` paths : py:class:`csiborgtools.read.CSiBORGPaths`
CSiBORG paths-handling object with set `n_sim` and `n_snap`. CSiBORG paths-handling object with set `n_sim` and `n_snap`.
minimum_m500 : float, optional min_m500 : float, optional
The minimum :math:`M_{rm 500c} / M_\odot` mass. By default no The minimum :math:`M_{rm 500c} / M_\odot` mass. By default no
threshold. threshold.
max_dist : float, optional
The maximum comoving distance of a halo. By default no upper limit.
""" """
_box = None _box = None
_paths = None _paths = None
@ -44,11 +46,12 @@ class HaloCatalogue:
_knn = None _knn = None
_positions = None _positions = None
def __init__(self, paths, minimum_m500=None): def __init__(self, paths, min_m500=None, max_dist=None):
self._box = BoxUnits(paths) self._box = BoxUnits(paths)
minimum_m500 = 0 if minimum_m500 is None else minimum_m500 min_m500 = 0 if min_m500 is None else min_m500
max_dist = numpy.infty if max_dist is None else max_dist
self._paths = paths self._paths = paths
self._set_data(minimum_m500) self._set_data(min_m500, max_dist)
# Initialise the KNN # Initialise the KNN
knn = NearestNeighbors() knn = NearestNeighbors()
knn.fit(self.positions) knn.fit(self.positions)
@ -122,7 +125,7 @@ class HaloCatalogue:
""" """
return self.paths.n_sim return self.paths.n_sim
def _set_data(self, minimum_m500): def _set_data(self, min_m500, max_dist):
""" """
Loads the data, merges with mmain, does various coordinate transforms. Loads the data, merges with mmain, does various coordinate transforms.
""" """
@ -157,12 +160,15 @@ class HaloCatalogue:
data = self.box.convert_from_boxunits(data, convert_cols) data = self.box.convert_from_boxunits(data, convert_cols)
# Cut on mass. Note that this is in Msun # Cut on mass. Note that this is in Msun
data = data[data["m500"] > minimum_m500] data = data[data["m500"] > min_m500]
# Now calculate spherical coordinates # Now calculate spherical coordinates
d, ra, dec = cartesian_to_radec(data) d, ra, dec = cartesian_to_radec(data)
data = add_columns(data, [d, ra, dec], ["dist", "ra", "dec"]) data = add_columns(data, [d, ra, dec], ["dist", "ra", "dec"])
# Cut on separation
data = data[data["dist"] < max_dist]
# Pre-allocate the positions array # Pre-allocate the positions array
self._positions = numpy.vstack( self._positions = numpy.vstack(
[data["peak_{}".format(p)] for p in ("x", "y", "z")]).T [data["peak_{}".format(p)] for p in ("x", "y", "z")]).T
@ -265,9 +271,11 @@ class CombinedHaloCatalogue:
paths : py:class`csiborgtools.read.CSiBORGPaths` paths : py:class`csiborgtools.read.CSiBORGPaths`
CSiBORG paths-handling object. Doest not have to have set set `n_sim` CSiBORG paths-handling object. Doest not have to have set set `n_sim`
and `n_snap`. and `n_snap`.
minimum_m500 : float, optional min_m500 : float, optional
The minimum :math:`M_{rm 500c} / M_\odot` mass. By default no The minimum :math:`M_{rm 500c} / M_\odot` mass. By default no
threshold. threshold.
max_dist : float, optional
The maximum comoving distance of a halo. By default no upper limit.
verbose : bool, optional verbose : bool, optional
Verbosity flag for reading the catalogues. Verbosity flag for reading the catalogues.
""" """
@ -275,7 +283,7 @@ class CombinedHaloCatalogue:
_n_snaps = None _n_snaps = None
_cats = None _cats = None
def __init__(self, paths, minimum_m500=None, verbose=True): def __init__(self, paths, min_m500=None, max_dist=None, verbose=True):
# Read simulations and their maximum snapshots # Read simulations and their maximum snapshots
# NOTE remove this later and take all cats # NOTE remove this later and take all cats
self._n_sims = paths.ic_ids[:10] self._n_sims = paths.ic_ids[:10]
@ -286,7 +294,7 @@ class CombinedHaloCatalogue:
for i in trange(self.N) if verbose else range(self.N): for i in trange(self.N) if verbose else range(self.N):
paths = deepcopy(paths) paths = deepcopy(paths)
paths.set_info(self.n_sims[i], self.n_snaps[i]) paths.set_info(self.n_sims[i], self.n_snaps[i])
cats[i] = HaloCatalogue(paths, minimum_m500) cats[i] = HaloCatalogue(paths, min_m500, max_dist)
self._cats = cats self._cats = cats
@property @property