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Corrected background and module path in pygrb_plot_injs_results #4977

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merged 2 commits into from
Dec 8, 2024
Merged

Corrected background and module path in pygrb_plot_injs_results #4977

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15e4cc5
Corrected background and module path
pannarale Dec 6, 2024
531d428
Variable for readability
pannarale Dec 8, 2024
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24 changes: 20 additions & 4 deletions bin/pygrb/pycbc_pygrb_plot_injs_results
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ def complete_mass_data(injs, key, tag):
if key == 'mtotal':
data = mass1 + mass2
elif key == 'mchirp':
data = conversions.mchirp_from_mass1_mass2(mass1, mass2)
data = pycbc.conversions.mchirp_from_mass1_mass2(mass1, mass2)
else:
data = mass2 / mass1
data = np.where(data > 1, 1./data, data)
Expand Down Expand Up @@ -260,7 +260,7 @@ all_off_trigs = ppu.load_data(trig_file, ifos, data_tag='trigs',

# Extract needed trigger properties and store them as dictionaries
# Based on trial_dict: if vetoes were applied, trig_* are the veto survivors
keys = ['network/reweighted_snr']
keys = ['network/end_time_gc', 'network/reweighted_snr']
trig_data = ppu.extract_trig_properties(
trial_dict,
all_off_trigs,
Expand All @@ -269,9 +269,25 @@ trig_data = ppu.extract_trig_properties(
keys
)

background = list(trig_data['network/reweighted_snr'].values())
# Max BestNR values in each trial: these are stored in a dictionary keyed
# by slide_id, as arrays indexed by trial number
background = {k: np.zeros(len(v)) for k,v in trial_dict.items()}
for slide_id in slide_dict:
trig_times = trig_data[keys[0]][slide_id][:]
for j, trial in enumerate(trial_dict[slide_id]):
# True whenever the trigger is in the trial
trial_cut = (trial[0] <= trig_times) & (trig_times < trial[1])
# Move on if nothing was in the trial
if not trial_cut.any():
continue
# Max BestNR
background[slide_id][j] = max(trig_data[keys[1]][slide_id][trial_cut])
# Gather all values and max over them
background = list(background.values())
background = np.concatenate(background)
max_bkgd_reweighted_snr = background.max()
assert total_trials == len(background)
logging.info("Background bestNR calculated.")

# =======================
# Post-process injections
Expand Down Expand Up @@ -340,7 +356,7 @@ if len(list(found_after_vetoes['reweighted_snr'])) > 0:
"""
found_quieter['fap'] = np.array([sum(background > bestnr) for bestnr in
found_quieter['reweighted_snr']],
dtype=float) / len(background)
dtype=float) / total_trials

# 3) Missed due to vetoes
# TODO: needs function to cherry-pick a subset of inj_data specified by
Expand Down
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