def test_check_toeplitz():
data = get_data()
config = get_config_dict()
assert (-1, -1, -1) == data.check_toeplitz('cls')
assert (2750, 1000, 2000) == data.check_toeplitz('cov')
remove_yml_file(config)
del config['toeplitz']
data = Data(data=config)
assert (-1, -1, -1) == data.check_toeplitz('cls')
assert (-1, -1, -1) == data.check_toeplitz('cov')
remove_yml_file(config)
def test_read_saved_data():
data = get_data()
config = get_config_dict()
config['bpw_edges'] = [0, 10]
# Since there's a yml saved in outdir, it will read it instead of config
data2 = Data(data=config)
assert data.data == data2.data
remove_yml_file(data.data)
def test_initizalization():
input_file = get_input_file()
config = read_yaml_file(input_file)
# Check that inputting both a file path and config dictionary rieses an
# error
with pytest.raises(ValueError):
Data(input_file, data=config)
config['bpw_edges'] = [0, 10]
data2 = Data(data=config, override=True)
assert os.path.isfile('xcell/tests/cls/data.yml')
assert data2.data['bpw_edges'] == [0, 10]
remove_yml_file(config)
# Check ignore_existing_yml
data = get_data()
data2 = Data(data=config, ignore_existing_yml=True)
assert data2.data['bpw_edges'] != data.data['bpw_edges']
remove_yml_file(config)
# Check error is rised when override and ignore_existing_yml are True
with pytest.raises(ValueError):
data2 = Data(data=config, ignore_existing_yml=True, override=True)
nargs='+',
help=
'Skip the following tracers. It can be given as DELS__0 to skip only DELS__0 tracer or DELS to skip all DELS tracers'
)
parser.add_argument(
'--override_yaml',
default=False,
action='store_true',
help=
'Override the YAML file if already stored. Be ware that this could cause compatibility problems in your data!'
)
args = parser.parse_args()
##############################################################################
data = Data(data_path=args.INPUT, override=args.override_yaml)
queue = args.queue
njobs = args.njobs
onlogin = args.onlogin
if args.compute == 'cls':
launch_cls(data, queue, njobs, args.nc, args.mem, args.cls_fiducial,
onlogin, args.skip)
elif args.compute == 'cov':
launch_cov(data, queue, njobs, args.nc, args.mem, onlogin, args.skip)
elif args.compute == 'to_sacc':
if args.to_sacc_use_nl and args.to_sacc_use_fiducial:
raise ValueError(
'Only one of --to_sacc_use_nl or --to_sacc_use_fiducial can be set'
)
def get_data(fsky0=0.2,
fsky1=0.3,
dtype0='galaxy_density',
dtype1='galaxy_shear'):
config = get_config(fsky0, fsky1, dtype0, dtype1)
return Data(data=config)
def test_covariance_extra():
# Generate a config file with extra covariance
config = get_config().copy()
config['cov'].update({
'extra': {
'path':
os.path.join(tmpdir, 'dummy_cov.npy'),
'order': [
'Dummy-Dummy', 'Dummy-DummyWL', 'Dummy-DummyCV',
'DummyWL-DummyWL', 'DummyWL-DummyCV', 'DummyCV-DummyCV'
]
}
})
config['cls'].update({
'Dummy-Dummy': {
'compute': 'all'
},
'Dummy-DummyWL': {
'compute': 'all'
},
'Dummy-DummyCV': {
'compute': 'all'
},
'DummyWL-DummyWL': {
'compute': 'auto'
},
'DummyWL-DummyCV': {
'compute': 'all'
},
'DummyCV-DummyCV': {
'compute': 'all'
}
})
# Add extra difficulty by adding 2 more tracers
config['tracers']['DummyWL'] = config['tracers']['Dummy__1'].copy()
config['tracers']['DummyCV'] = config['tracers']['Dummy__0'].copy()
config['tracers']['DummyCV']['dtype'] = 'cmb_convergence'
# Overwrite 'data.yml' with new configuration
data = Data(data=config, override=True)
datafile = os.path.join(data.data['output'], 'data.yml')
# Populate a sacc file with cls and covG. This will be used as extra
# covariance later. Note that the tracers are in different order than in
# the config file when reading the yml file.
s = ClSack(datafile, 'cls_cov_dummy.fits', 'cls')
covmat = s.s.covariance.covmat
# Set B-modes to 0 as they are set to 0 when reading the extra covariance
for dt in s.s.get_data_types():
if 'b' in dt:
ix = s.s.indices(data_type=dt)
covmat[ix] = 0
covmat[:, ix] = 0
# Prepare the "extra" covariance. So far extra covs with B-modes are not
# implemented Keep only spin-0 and E-modes
# Not done in previous loop because the indices vary for the sacc file and
# not longer correspond to those in covmat
for dt in s.s.get_data_types():
if 'b' in dt:
s.s.remove_selection(data_type=dt)
# Reorder the covariance as stated in the config
ix_reorder_d = {k: [] for k in s.data.data['cls'].keys()}
for trs in s.s.get_tracer_combinations():
key = s.data.get_tracers_bare_name_pair(*trs)
ix_reorder_d[key].extend(s.s.indices(tracers=trs))
ix_reorder = []
for key in s.data.data['cov']['extra']['order']:
if key not in ix_reorder_d:
key = '-'.join(key.split('-')[::-1])
ix_reorder.extend(ix_reorder_d[key])
# Save the reordered covariance
np.save(config['cov']['extra']['path'],
s.s.covariance.covmat[ix_reorder][:, ix_reorder])
# Populate a sacc file with nls and cov extra (read previous cov)
s2 = ClSack(datafile, 'cls_cov_dummy.fits', 'nl')
covmat2 = s2.s.covariance.covmat
# Remove B-modes to test if spin-0 and E-modes are correctly taken into
# account
for dt in s2.s.get_data_types():
if 'b' in dt:
s2.s.remove_selection(data_type=dt)
# Check if the covariance is correctly read with no B-modes
cov_no_B = s.s.covariance.covmat
cov_no_B2 = s2.s.covariance.covmat
assert np.max(np.abs((cov_no_B - cov_no_B2) / np.mean(cov_no_B))) < 1e-5
# Check if the full covariance is correctly generated
assert np.max(np.abs((covmat2 - covmat) / np.mean(covmat))) < 1e-5
def test_get_tracer_matrix():
# No cls from data
c = get_config_dict()
data = Data(data=c)
m = data.get_tracer_matrix()
for t1, t2 in get_tracer_pair_iterator(data):
assert not m[(t1, t2)]['clcov_from_data']
remove_yml_file(c)
# All cls from data
c = get_config_dict()
c['cov']['cls_from_data'] = 'all'
data = Data(data=c)
m = data.get_tracer_matrix()
for t1, t2 in get_tracer_pair_iterator(data):
assert m[(t1, t2)]['clcov_from_data']
remove_yml_file(c)
# Group cls from data (all)
c = get_config_dict()
c['cov']['cls_from_data'] = {'DESgc-DESgc': {'compute': 'all'}}
data = Data(data=c)
m = data.get_tracer_matrix()
for t1, t2 in get_tracer_pair_iterator(data):
tpair = data.get_tracers_bare_name_pair(t1, t2)
if tpair == 'DESgc-DESgc':
assert m[(t1, t2)]['clcov_from_data']
else:
assert not m[(t1, t2)]['clcov_from_data']
remove_yml_file(c)
# Group cls from data (auto)
c = get_config_dict()
c['cov']['cls_from_data'] = {'DESgc-DESgc': {'compute': 'auto'}}
data = Data(data=c)
m = data.get_tracer_matrix()
for t1, t2 in get_tracer_pair_iterator(data):
tpair = data.get_tracers_bare_name_pair(t1, t2)
if tpair == 'DESgc-DESgc' and t1 == t2:
assert m[(t1, t2)]['clcov_from_data']
else:
assert not m[(t1, t2)]['clcov_from_data']
remove_yml_file(c)
# Some cls from data
c = get_config_dict()
c['cov']['cls_from_data'] = ['DESgc__0-DESgc__0', 'DESgc__1-DESwl__1']
data = Data(data=c)
m = data.get_tracer_matrix()
for t1, t2 in get_tracer_pair_iterator(data):
if t1 == 'DESgc__0' and t2 == 'DESgc__0':
assert m[(t1, t2)]['clcov_from_data']
elif t1 == 'DESgc__1' and t2 == 'DESwl__1':
assert m[(t1, t2)]['clcov_from_data']
elif t1 == 'DESwl__1' and t2 == 'DESgc__1':
assert m[(t1, t2)]['clcov_from_data']
else:
assert not m[(t1, t2)]['clcov_from_data']
remove_yml_file(c)
def test_input_from_another_file():
# This tests whether we can load yaml files that
# include other yaml files within them.
d = Data('xcell/tests/data/conftest.yml')
assert d.data['tracers']['DESgc__1']['bias'] == 1.76
remove_yml_file(d.data)
def get_data_from_dict():
input_dict = get_config_dict()
return Data(data=input_dict)
def get_data():
input_file = get_input_file()
return Data(input_file)