def test_halo_lc():
'''Test loading halo light cones
'''
from abacusnbody.data.compaso_halo_catalog import CompaSOHaloCatalog
cat = CompaSOHaloCatalog(
curdir /
'halo_light_cones/AbacusSummit_base_c000_ph001-abridged/z2.250/',
fields='all',
subsamples=True)
assert (cat.halo_lc == True)
HALO_LC_CAT = refdir / 'halo_lc_cat.asdf'
HALO_LC_SUBSAMPLES = refdir / 'halo_lc_subsample.asdf'
# generate reference
#ref = cat.halos
#ref.write(HALO_LC_CAT, format='asdf', all_array_storage='internal', all_array_compression='blsc')
#ref = cat.subsamples
#ref.write(HALO_LC_SUBSAMPLES, format='asdf', all_array_storage='internal', all_array_compression='blsc')
ref = Table.read(HALO_LC_CAT)
halos = cat.halos
for col in ref.colnames:
assert check_close(ref[col], halos[col])
assert halos.meta == ref.meta
ref = Table.read(HALO_LC_SUBSAMPLES)
ss = cat.subsamples
for col in ref.colnames:
assert check_close(ref[col], ss[col])
assert ss.meta == ref.meta
def test_halos_clean(tmp_path):
'''Test loading a base (uncleaned) halo catalog
'''
from abacusnbody.data.compaso_halo_catalog import CompaSOHaloCatalog
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=True,
fields='all',
cleaned=True)
# to regenerate reference
#ref = cat.halos
#ref.write(HALOS_OUTPUT_CLEAN, all_array_storage='internal', all_array_compression='blsc')
ref = Table.read(HALOS_OUTPUT_CLEAN)
halos = cat.halos
for col in ref.colnames:
assert check_close(ref[col], halos[col])
# all haloindex values should point to this slab
assert np.all((halos['haloindex'] /
1e12).astype(int) == cat.header['FullStepNumber'])
# ensure that all deleted halos in ref are marked as merged in EXAMPLE_SIM
assert np.all(halos['is_merged_to'][ref['N'] == 0] != -1)
# no deleted halos in ref should have merged particles in EXAMPLE_SIM
assert np.all(halos['N_merge'][ref['N'] == 0] == 0)
assert halos.meta == ref.meta
def test_subsamples_clean(tmp_path):
'''Test loading particle subsamples
'''
from abacusnbody.data.compaso_halo_catalog import CompaSOHaloCatalog
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=True,
fields='all',
cleaned=True)
# to regenerate reference
#ref = cat.subsamples
#import asdf; asdf.compression.set_compression_options(typesize='auto')
#ref.write(PARTICLES_OUTPUT_CLEAN, format='asdf', all_array_storage='internal', all_array_compression='blsc')
ref = Table.read(PARTICLES_OUTPUT_CLEAN)
ss = cat.subsamples
for col in ref.colnames:
assert check_close(ref[col], ss[col])
# total number of particles in ref should be equal to the sum total of npout{AB} in EXAMPLE_SIM
assert len(ref) == np.sum(cat.halos['npoutA']) + np.sum(
cat.halos['npoutB'])
assert cat.subsamples.meta == ref.meta
def test_subsamples_unclean(tmp_path):
'''Test loading particle subsamples
'''
from abacusnbody.data.compaso_halo_catalog import CompaSOHaloCatalog
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=dict(A=True),
fields='all',
cleaned=False)
lenA = len(cat.subsamples)
assert lenA == 2975
assert cat.subsamples.colnames == ['pos', 'vel']
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=dict(B=True),
fields='all',
cleaned=False)
lenB = len(cat.subsamples)
assert lenB == 7082
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=True,
fields='all',
cleaned=False)
assert len(cat.subsamples) == lenA + lenB
# to regenerate reference
#ref = cat.subsamples
#import asdf; asdf.compression.set_compression_options(typesize='auto')
#ref.write(PARTICLES_OUTPUT_UNCLEAN, format='asdf', all_array_storage='internal', all_array_compression='blsc')
ref = Table.read(PARTICLES_OUTPUT_UNCLEAN)
ss = cat.subsamples
for col in ref.colnames:
assert check_close(ref[col], ss[col])
assert cat.subsamples.meta == ref.meta
def test_halos_unclean(tmp_path):
'''Test loading a base (uncleaned) halo catalog
'''
from abacusnbody.data.compaso_halo_catalog import CompaSOHaloCatalog
cat = CompaSOHaloCatalog(EXAMPLE_SIM / 'halos' / 'z0.000',
subsamples=True,
fields='all',
cleaned=False)
# to regenerate reference
#ref = cat.halos
#ref.write(HALOS_OUTPUT_UNCLEAN, all_array_storage='internal', all_array_compression='blsc')
ref = Table.read(HALOS_OUTPUT_UNCLEAN)
halos = cat.halos
for col in ref.colnames:
assert check_close(ref[col], halos[col])
assert halos.meta == ref.meta
def test_hod(tmp_path, reference_mode = False):
'''Test loading a halo catalog
'''
from abacusnbody.hod import prepare_sim
from abacusnbody.hod.abacus_hod import AbacusHOD
config = yaml.safe_load(open(EXAMPLE_CONFIG))
# inform abacus_hod where the simulation files are, relative to the cwd
config['sim_params']['sim_dir'] = pjoin(TESTDIR, 'halo_light_cones')
sim_params = config['sim_params']
HOD_params = config['HOD_params']
clustering_params = config['clustering_params']
# reference mode
if reference_mode:
print("Generating new reference files...")
prepare_sim.main(EXAMPLE_CONFIG)
# additional parameter choices
want_rsd = HOD_params['want_rsd']
bin_params = clustering_params['bin_params']
# create a new abacushod object
newBall = AbacusHOD(sim_params, HOD_params, clustering_params)
mock_dict = newBall.run_hod(newBall.tracers, want_rsd, write_to_disk = True, Nthread = 2)
# test mode
else:
simname = config['sim_params']['sim_name'] # "AbacusSummit_base_c000_ph006"
simdir = config['sim_params']['sim_dir']
z_mock = config['sim_params']['z_mock']
# all output dirs should be under tmp_path
config['sim_params']['output_dir'] = pjoin(tmp_path, 'data_mocks_summit_new') + '/'
config['sim_params']['subsample_dir'] = pjoin(tmp_path, "data_subs") + '/'
config['sim_params']['scratch_dir'] = pjoin(tmp_path, "data_gals") + '/'
savedir = config['sim_params']['subsample_dir'] + simname+"/z"+str(z_mock).ljust(5, '0')
# check subsample file match
prepare_sim.main(EXAMPLE_CONFIG, params = config)
newhalos = h5py.File(savedir+'/halos_xcom_0_seed600_abacushod_oldfenv_MT_new.h5', 'r')['halos']
temphalos = h5py.File(EXAMPLE_SUBSAMPLE_HALOS, 'r')['halos']
for i in range(len(newhalos)):
for j in range(len(newhalos[i])):
assert check_close(newhalos[i][j], temphalos[i][j])
newparticles = h5py.File(savedir+'/particles_xcom_0_seed600_abacushod_oldfenv_MT_new.h5', 'r')['particles']
tempparticles = h5py.File(EXAMPLE_SUBSAMPLE_PARTS, 'r')['particles']
for i in range(len(newparticles)):
for j in range(len(newparticles[i])):
assert check_close(newparticles[i][j], tempparticles[i][j])
# additional parameter choices
want_rsd = HOD_params['want_rsd']
write_to_disk = HOD_params['write_to_disk']
bin_params = clustering_params['bin_params']
rpbins = np.logspace(bin_params['logmin'], bin_params['logmax'], bin_params['nbins'])
pimax = clustering_params['pimax']
pi_bin_size = clustering_params['pi_bin_size']
# create a new abacushod object
newBall = AbacusHOD(sim_params, HOD_params, clustering_params)
# throw away run for jit to compile, write to disk
mock_dict = newBall.run_hod(newBall.tracers, want_rsd, write_to_disk = True, Nthread = 2)
savedir_gal = config['sim_params']['output_dir']\
+"/"+simname+"/z"+str(z_mock).ljust(5, '0') +"/galaxies_rsd/LRGs.dat"
data = ascii.read(EXAMPLE_LRGS)
data1 = ascii.read(savedir_gal)
for ekey in data.keys():
assert check_close(data[ekey], data1[ekey])
savedir_gal = config['sim_params']['output_dir']\
+"/"+simname+"/z"+str(z_mock).ljust(5, '0') +"/galaxies_rsd/ELGs.dat"
data = ascii.read(EXAMPLE_ELGS)
data1 = ascii.read(savedir_gal)
for ekey in data.keys():
assert check_close(data[ekey], data1[ekey])