configs = [
# (time_integrated, "fixed_weights", "fixed_box", "Time-Integrated (n_s > 0)"),
(time_integrated_negative_n_s, "fixed_weights", "fixed_box_negative", "Time-Integrated"),
(time_integrated, "flare", "flare", "Cluster Search")
]
cluster = True
job_ids = []
for j, cat in enumerate(individual_tdes[-1:]):
name = name_root + cat.replace(" ", "") + "/"
cat_path = individual_tde_cat(cat)
catalogue = load_catalogue(cat_path)
t_start = catalogue["start_time_mjd"]
t_end = catalogue["end_time_mjd"]
max_window = float(t_end - t_start)
src_res = dict()
lengths = np.logspace(-2, 0, 2) * max_window
# Loop over likelihood methods
for (llh_dict, mh_name, f_name, label) in configs:
t_start = ref_time - 30.
t_end = ref_time + 100.
# Ra and dec of source, from TNS (https://wis-tns.weizmann.ac.il/object/2018cow)
ra = 244.000927647
dec = 22.2680094118
# Distance to source,from http://www.astronomerstelegram.org/?read=11727
z = 0.014145
lumdist = Distance(z=z).to("Mpc").value
# Creates the .npy source catalogue
at2018cow_catalogue = custom_sources(name="AT2018cow",
ra=ra,
dec=dec,
weight=1.,
distance=lumdist,
start_time=t_start,
end_time=t_end,
ref_time=t_start)
at2018cow_cat_path = individual_tde_cat("AT2018cow")
try:
os.makedirs(os.path.dirname(at2018cow_cat_path))
except OSError:
pass
np.save(at2018cow_cat_path, at2018cow_catalogue)