def setUpClass(cls):
cls._tile_radius = angularSeparation(0.0, 0.0, 2.0, 2.0)
dir_name = os.path.join(getPackageDir('sims_catUtils'), 'tests')
cls._tmpdir = tempfile.mkdtemp(dir=dir_name)
cls._temp_gal_db = os.path.join(cls._tmpdir, 'test_galaxies.db')
ra_min = -2.25
cls._ra_min = ra_min
ra_max = 2.251
cls._d_ra = 0.05
ra_grid = np.arange(ra_min, ra_max, cls._d_ra)
dec_grid = np.arange(ra_min, ra_max, cls._d_ra)
print('raw grid %d' % len(ra_grid))
ra_dec_mesh = np.meshgrid(ra_grid, dec_grid)
ra_grid = ra_dec_mesh[0].flatten()
dec_grid = ra_dec_mesh[1].flatten()
# add a very small offset so that numerical precision
# does not foul things up on the tile boundaries
rng = np.random.RandomState(7163)
ra_grid += 1.0e-5 * (rng.random_sample(len(ra_grid)) - 0.5)
dec_grid += 1.0e-5 * (rng.random_sample(len(dec_grid)) - 0.5)
galtag = (100 * np.round(45 + ra_grid / cls._d_ra) +
np.round(45 + dec_grid / cls._d_ra)).astype(int)
assert len(galtag) == len(np.unique(galtag))
htmid_grid = htm.findHtmid(ra_grid, dec_grid, 21)
print('got htmid %d' % len(htmid_grid))
print(htm.levelFromHtmid(htmid_grid.min()))
print(htm.levelFromHtmid(htmid_grid.max()))
assert htm.levelFromHtmid(htmid_grid.min()) == 21
assert htm.levelFromHtmid(htmid_grid.max()) == 21
gid = np.arange(len(ra_grid), dtype=int)
assert len(galtag) == len(np.unique(galtag))
print(ra_grid.max(), ra_grid.min())
with sqlite3.connect(cls._temp_gal_db) as conn:
c = conn.cursor()
query = '''CREATE TABLE galaxy(htmid int, id int,
galid text, ra real, dec real, galtag int, redshift)'''
c.execute(query).fetchall()
values = ((int(hh), int(ii), str(ii), r, d, int(g), 0.5)
for hh, ii, r, d, g in zip(htmid_grid, gid, ra_grid,
dec_grid, galtag))
c.executemany('INSERT INTO galaxy VALUES (?,?,?,?,?,?,?)', values)
mgr = multiprocessing.Manager()
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',
parser = argparse.ArgumentParser()
parser.add_argument('--do_1', default=False, action='store_true')
parser.add_argument('--do_2', default=False, action='store_true')
parser.add_argument('--do_3', default=False, action='store_true')
parser.add_argument('--do_4', default=False, action='store_true')
args = parser.parse_args()
with open('data/htmid_to_obs_map.pickle', 'rb') as in_file:
htmid_map = pickle.load(in_file)
tx_dict = htm.getAllTrixels(6)
tx_list = []
for htmid in tx_dict:
if htm.levelFromHtmid(htmid) == 6:
tx_list.append(tx_dict[htmid])
gal_n_ra, gal_n_dec = equatorialFromGalactic(0.0, 90.0)
gal_s_ra, gal_s_dec = equatorialFromGalactic(0.0, -90.0)
if args.do_1:
######### Region 1
#1) ~600 deg2 along ecliptic plane, say |latitude| < 30 and a 100 deg stretch
# in longitude, but with |galactic latitude| > 30 deg
# must be fully inside one of these two half spaces to have
# |galactic latitude| > 30
gal_n_30_hs = htm.halfSpaceFromRaDec(gal_n_ra, gal_n_dec, 60.0)
gal_s_30_hs = htm.halfSpaceFromRaDec(gal_s_ra, gal_s_dec, 60.0)
htmid_to_obs_fname = "data/htmid_to_obs_map.pickle"
assert os.path.isfile(htmid_to_obs_fname)
with open(htmid_to_obs_fname, 'rb') as in_file:
htmid_to_obs = pickle.load(in_file)
md5_hasher = hashlib.md5()
with open(obs_fname, 'rb') as in_file:
for chunk in iter(lambda: in_file.read(4096), b""):
md5_hasher.update(chunk)
md5_sum = md5_hasher.hexdigest()
assert md5_sum == htmid_to_obs['md5_sum']
htmid_of_interest = 9484
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)
'htmid to obsHistID')
args = parser.parse_args()
if args.obs_params is None:
raise RuntimeError("must specify obs_params")
if args.out_file is None:
raise RuntimeError("must specify out_file")
trixel_level = 6
trixel_dict = htm.getAllTrixels(trixel_level)
trixel_arr = []
trixel_ra = []
trixel_dec = []
trixel_radius = []
for htmid in trixel_dict:
if htm.levelFromHtmid(htmid) == trixel_level:
tx = trixel_dict[htmid]
trixel_arr.append(tx)
ra, dec = tx.get_center()
trixel_ra.append(ra)
trixel_dec.append(dec)
trixel_radius.append(tx.get_radius())
del trixel_dict
trixel_arr = np.array(trixel_arr)
trixel_ra = np.array(trixel_ra)
trixel_dec = np.array(trixel_dec)
trixel_radius = np.array(trixel_radius)
htmid_to_obs = {}
