out_data = mgr.dict()
lock = multiprocessing.Lock()
n_tot = 0
n_processed = 0
with h5py.File(obs_param_name,'r') as obs_params:
for htmid_query in htmid_list:
if htmid_query not in htmid_to_obs:
continue
n_lc_so_far = 0
for name in out_data.keys():
n_lc_so_far += len(out_data[name][0])
print('now simulating ',htmid_query,n_lc_so_far)
query_level = htm.levelFromHtmid(htmid_query)
trixel_query = htm.trixelFromHtmid(htmid_query)
ra_query, dec_query = trixel_query.get_center()
radius_query = trixel_query.get_radius()
print(ra_query, dec_query, radius_query)
obs_query = ObservationMetaData(pointingRA=ra_query,
pointingDec=dec_query,
boundType='circle',
boundLength=radius_query)
col_names = ['ra', 'decl',
'umag', 'gmag', 'rmag',
'imag', 'zmag', 'ymag',
'lc_id', 't0', 'var_type',
'ebv', 'parallax',
'simobjid']
htmid_level_of_interest = htm.levelFromHtmid(htmid_of_interest)
obs_list = np.array(htmid_to_obs[htmid_of_interest])
obs_dex_list = obs_list-1
print(len(obs_list))
with h5py.File(obs_fname, 'r') as obs_file:
shld_be = 1 + np.arange(len(obs_file['obsHistID'].value), dtype=int)
np.testing.assert_array_equal(shld_be, obs_file['obsHistID'].value)
np.testing.assert_array_equal(obs_file['obsHistID'].value[obs_dex_list],
obs_list)
obs_subset = {}
for field_name in obs_file.keys():
obs_subset[field_name] = obs_file[field_name].value[obs_dex_list]
trixel_of_interest = htm.trixelFromHtmid(htmid_of_interest)
trixel_ra, trixel_dec = trixel_of_interest.get_center()
trixel_radius = 1.05*trixel_of_interest.get_radius()
trixel_obs = sims_utils.ObservationMetaData(pointingRA=trixel_ra,
pointingDec=trixel_dec,
boundType='circle',
boundLength=trixel_radius)
star_iter = star_db.query_columns(col_names,
obs_metadata=trixel_obs,
chunk_size=100000)
ct_tot = 0
ct_kplr = 0
ct_mlt = 0
ct_rrly = 0