def h_a_powers(vals, path, fname, hpath):
return np.power(
vals.h, hdf5_get(path, fname, hpath, attr='h-scale-exponent')
) * \
np.power(
vals.a, hdf5_get(path, fname, hpath, attr='aexp-scale-exponent')
)
def _read_subfindtables(self):
_log('TreeTables: reading subfind tables:')
_log(' nodeIndex')
self.tf_tree_ids = hdf5_get(self.fpath, self.sfbase, '/Subhalo/nodeIndex', ncpu=self.ncpu)
_log(' SubGroupNumber')
self.tf_sgns = hdf5_get(self.fpath, self.sfbase, '/Subhalo/SubGroupNumber', ncpu=self.ncpu)
_log(' MassType')
self.tf_masstypes = hdf5_get(self.fpath, self.sfbase, '/Subhalo/MassType', ncpu=self.ncpu) * 1E10 / h * U.Msun
return
def _read_treetables(self):
_log('TreeTables: reading merger tree tables:')
_log(' nodeIndex')
self.tree_ids = hdf5_get(self.fpath, self.fbase, '/haloTrees/nodeIndex', ncpu=self.ncpu)
_log(' snapshotNumber')
self.sns = hdf5_get(self.fpath, self.fbase, '/haloTrees/snapshotNumber', ncpu=self.ncpu)
_log(' fofIndex')
self.gns = hdf5_get(self.fpath, self.fbase, '/haloTrees/fofIndex', ncpu=self.ncpu)
if self.use_snapshots:
_log(' positionInCatalogue')
self.tree_tabposs = hdf5_get(self.fpath, self.fbase, '/haloTrees/positionInCatalogue', ncpu=self.ncpu)
_log(' isInterpolated')
self.in_tab = np.logical_not(
hdf5_get(self.fpath, self.fbase, '/haloTrees/isInterpolated', ncpu=self.ncpu)
)
_log(' descendantIndex')
self.tree_descids = hdf5_get(self.fpath, self.fbase, '/haloTrees/descendantIndex', ncpu=self.ncpu)
_log(' mbpsContributed')
self.tree_mbpcs = hdf5_get(self.fpath, self.fbase, '/haloTrees/mbpsContributed', ncpu=self.ncpu)
return
def to_cgs(path, fname, hpath):
return hdf5_get(path,
fname,
hpath,
attr='Conversion factor to physical CGS '
'(including cosmological corrections)')