def process(fitsfilename):
sky_map, metadata = fits.read_sky_map(fitsfilename, nest=None)
coinc_event_id = metadata['objid']
try:
runtime = metadata['runtime']
except KeyError:
runtime = float('nan')
row = db.execute("""
SELECT DISTINCT sim.simulation_id AS simulation_id, sim.longitude AS ra, sim.latitude AS dec,
ci.combined_far AS far, ci.snr AS snr
FROM coinc_event_map AS cem1 INNER JOIN coinc_event_map AS cem2
ON (cem1.coinc_event_id = cem2.coinc_event_id)
INNER JOIN sim_inspiral AS sim ON (cem1.event_id = sim.simulation_id)
INNER JOIN coinc_inspiral AS ci ON (cem2.event_id = ci.coinc_event_id)
WHERE cem1.table_name = 'sim_inspiral'
AND cem2.table_name = 'coinc_event' AND cem2.event_id = ?""",
(coinc_event_id,)).fetchone()
if row is None:
raise ValueError(
"No database record found for event '{0}' in '{1}'".format(
coinc_event_id, command.sqlite_get_filename(db)))
simulation_id, true_ra, true_dec, far, snr = row
searched_area, searched_prob, offset, searched_modes, contour_areas, area_probs, contour_modes = postprocess.find_injection(
sky_map, true_ra, true_dec, contours=[0.01 * p for p in contours],
areas=areas, modes=modes, nest=metadata['nest'])
if snr is None:
snr = float('nan')
if far is None:
far = float('nan')
distmean = metadata.get('distmean', float('nan'))
diststd = metadata.get('diststd', float('nan'))
ret = [coinc_event_id, simulation_id, far, snr, searched_area, searched_prob, offset, runtime, distmean, diststd] + contour_areas + area_probs
if modes:
ret += [searched_modes] + contour_modes
return ret
def process(fitsfilename):
(prob, distmu, distsigma, distnorm), metadata = fits.read_sky_map(
fitsfilename, nest=None, distances=True)
coinc_event_id = metadata['objid']
try:
runtime = metadata['runtime']
except KeyError:
runtime = float('nan')
row = db.execute("""
SELECT DISTINCT sim.simulation_id AS simulation_id,
sim.longitude AS ra, sim.latitude AS dec, sim.distance AS distance,
ci.combined_far AS far, ci.snr AS snr
FROM coinc_event_map AS cem1 INNER JOIN coinc_event_map AS cem2
ON (cem1.coinc_event_id = cem2.coinc_event_id)
INNER JOIN sim_inspiral AS sim ON (cem1.event_id = sim.simulation_id)
INNER JOIN coinc_inspiral AS ci ON (cem2.event_id = ci.coinc_event_id)
WHERE cem1.table_name = 'sim_inspiral'
AND cem2.table_name = 'coinc_event' AND cem2.event_id = ?""",
(coinc_event_id,)).fetchone()
if row is None:
raise ValueError(
"No database record found for event '{0}' in '{1}'".format(
coinc_event_id, command.sqlite_get_filename(db)))
simulation_id, true_ra, true_dec, true_dist, far, snr = row
searched_area, searched_prob, offset, searched_modes, contour_areas, area_probs, contour_modes = postprocess.find_injection(
prob, true_ra, true_dec, contours=[0.01 * p for p in contours],
areas=areas, modes=modes, nest=metadata['nest'])
searched_prob_distance = distance.marginal_cdf(
true_dist, prob, distmu, distsigma, distnorm)
if snr is None:
snr = float('nan')
if far is None:
far = float('nan')
distmean = metadata.get('distmean', float('nan'))
diststd = metadata.get('diststd', float('nan'))
log_bci = metadata.get('log_bci', float('nan'))
log_bsn = metadata.get('log_bsn', float('nan'))
ret = [coinc_event_id, simulation_id, far, snr, searched_area,
searched_prob, searched_prob_distance, offset, runtime, distmean,
diststd, log_bci, log_bsn] + contour_areas + area_probs
if modes:
ret += [searched_modes] + contour_modes
return ret
def process(fitsfilename):
sky_map, metadata = fits.read_sky_map(fitsfilename, nest=None)
coinc_event_id = metadata['objid']
try:
runtime = metadata['runtime']
except KeyError:
runtime = float('nan')
simulation_id, true_ra, true_dec, far, snr = db.execute("""
SELECT DISTINCT sim.simulation_id AS simulation_id, sim.longitude AS ra, sim.latitude AS dec,
ci.combined_far AS far, ci.snr AS snr
FROM coinc_event_map AS cem1 INNER JOIN coinc_event_map AS cem2
ON (cem1.coinc_event_id = cem2.coinc_event_id)
INNER JOIN sim_inspiral AS sim ON (cem1.event_id = sim.simulation_id)
INNER JOIN coinc_inspiral AS ci ON (cem2.event_id = ci.coinc_event_id)
WHERE cem1.table_name = 'sim_inspiral'
AND cem2.table_name = 'coinc_event' AND cem2.event_id = ?""",
(coinc_event_id,)).fetchone()
searched_area, searched_prob, offset, searched_modes, contour_areas, area_probs, contour_modes = postprocess.find_injection(
sky_map, true_ra, true_dec, contours=[0.01 * p for p in contours],
areas=areas, modes=modes, nest=metadata['nest'])
if snr is None:
snr = float('nan')
if far is None:
far = float('nan')
ret = [coinc_event_id, simulation_id, far, snr, searched_area, searched_prob, offset, runtime] + contour_areas + area_probs
if modes:
ret += [searched_modes] + contour_modes
return ret
def process(fitsfilename):
sky_map, metadata = fits.read_sky_map(fitsfilename, nest=None)
coinc_event_id = metadata['objid']
try:
runtime = metadata['runtime']
except KeyError:
runtime = float('nan')
simulation_id, true_ra, true_dec, far, snr = db.execute("""
SELECT DISTINCT sim.simulation_id AS simulation_id, sim.longitude AS ra, sim.latitude AS dec,
ci.combined_far AS far, ci.snr AS snr
FROM coinc_event_map AS cem1 INNER JOIN coinc_event_map AS cem2
ON (cem1.coinc_event_id = cem2.coinc_event_id)
INNER JOIN sim_inspiral AS sim ON (cem1.event_id = sim.simulation_id)
INNER JOIN coinc_inspiral AS ci ON (cem2.event_id = ci.coinc_event_id)
WHERE cem1.table_name = 'sim_inspiral'
AND cem2.table_name = 'coinc_event' AND cem2.event_id = ?""",
(coinc_event_id,)).fetchone()
searched_area, searched_prob, offset, searched_modes, contour_areas, area_probs, contour_modes = postprocess.find_injection(
sky_map, true_ra, true_dec, contours=[0.01 * p for p in contours],
areas=areas, modes=modes, nest=metadata['nest'])
if snr is None:
snr = float('nan')
if far is None:
far = float('nan')
ret = [coinc_event_id, simulation_id, far, snr, searched_area, searched_prob, offset, runtime] + contour_areas + area_probs
if modes:
ret += [searched_modes] + contour_modes
return ret
