def get_injections(injfnames, FAR, zero_lag_segments, verbose = False):
"""
"""
def injection_was_made(geocent_end_time, geocent_end_time_ns, zero_lag_segments = zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(geocent_end_time, geocent_end_time_ns) in zero_lag_segments
found = []
missed = []
print("", file=sys.stderr)
for cnt, f in enumerate(injfnames):
print("getting injections below FAR: " + str(FAR) + ":\t%.1f%%\r" % (100.0 * cnt / len(injfnames),), end=' ', file=sys.stderr)
working_filename = dbtables.get_connection_filename(f, tmp_path = None, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("injection_was_made", 2, injection_was_made)
make_sim_inspiral = lsctables.SimInspiralTable.get_table(dbtables.get_xml(connection))._row_from_cols
for values in connection.cursor().execute("""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.combined_far < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR,)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
connection.close()
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
print("\nFound = %d Missed = %d" % (len(found), len(missed)), file=sys.stderr)
return found, missed
def get_far_threshold_and_segments(zerofname, live_time_program, instruments, verbose = False):
"""
return the false alarm rate of the most rare zero-lag coinc, and a
dictionary of the thinca segments indexed by instrument.
"""
# open database
working_filename = dbtables.get_connection_filename(zerofname, verbose = verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
# extract false alarm rate threshold
query = 'SELECT MIN(coinc_inspiral.combined_far) FROM coinc_inspiral JOIN coinc_event ON (coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id) WHERE (coinc_event.instruments == "' + str(instruments) + '") AND NOT EXISTS(SELECT * FROM time_slide WHERE time_slide.time_slide_id == coinc_event.time_slide_id AND time_slide.offset != 0);'
print(query)
far, = connection.cursor().execute(query).fetchone()
# extract segments.
seglists = db_thinca_rings.get_thinca_zero_lag_segments(connection, program_name = live_time_program)
# done
connection.close()
dbtables.discard_connection_filename(zerofname, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
print("WARNING replacing far with 10^-7", file=sys.stderr)
far = 1.0e-7
return far, seglists
def get_far_threshold_and_segments(zerofname,
live_time_program,
instruments,
verbose=False):
"""
return the false alarm rate of the most rare zero-lag coinc, and a
dictionary of the thinca segments indexed by instrument.
"""
# open database
working_filename = dbtables.get_connection_filename(zerofname,
verbose=verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
# extract false alarm rate threshold
query = 'SELECT MIN(coinc_inspiral.combined_far) FROM coinc_inspiral JOIN coinc_event ON (coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id) WHERE (coinc_event.instruments == "' + str(
instruments
) + '") AND NOT EXISTS(SELECT * FROM time_slide WHERE time_slide.time_slide_id == coinc_event.time_slide_id AND time_slide.offset != 0);'
print(query)
far, = connection.cursor().execute(query).fetchone()
# extract segments.
seglists = db_thinca_rings.get_thinca_zero_lag_segments(
connection, program_name=live_time_program)
# done
connection.close()
dbtables.discard_connection_filename(zerofname,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
print("WARNING replacing far with 10^-7", file=sys.stderr)
far = 1.0e-7
return far, seglists
def get_far_threshold_and_segments(zerofname,
instruments,
live_time_program,
veto_seg_name="vetoes",
verbose=True):
"""
return the false alarm rate of the most rare zero-lag coinc, and a
dictionary of the thinca segments indexed by instrument.
"""
# open database
working_filename = dbtables.get_connection_filename(zerofname,
verbose=verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
# extract false alarm rate threshold
query = 'SELECT MIN(coinc_inspiral.false_alarm_rate) FROM coinc_inspiral JOIN coinc_event ON (coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id) WHERE ( coinc_event.instruments = "' + instruments + '" AND NOT EXISTS(SELECT * FROM time_slide WHERE time_slide.time_slide_id == coinc_event.time_slide_id AND time_slide.offset != 0) );'
print("\n", query)
far, = connection.cursor().execute(query).fetchone()
# extract segments.
seglists = db_thinca_rings.get_thinca_zero_lag_segments(
connection, program_name=live_time_program)
# done
connection.close()
dbtables.discard_connection_filename(zerofname,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
return far, seglists
def get_injections(injfnames, FAR, zero_lag_segments, verbose = False):
"""
"""
def injection_was_made(geocent_end_time, geocent_end_time_ns, zero_lag_segments = zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(geocent_end_time, geocent_end_time_ns) in zero_lag_segments
found = []
missed = []
print >>sys.stderr, ""
for cnt, f in enumerate(injfnames):
print >>sys.stderr, "getting injections below FAR: " + str(FAR) + ":\t%.1f%%\r" % (100.0 * cnt / len(injfnames),),
working_filename = dbtables.get_connection_filename(f, tmp_path = None, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("injection_was_made", 2, injection_was_made)
make_sim_inspiral = lsctables.table.get_table(dbtables.get_xml(connection), lsctables.SimInspiralTable.tableName)._row_from_cols
for values in connection.cursor().execute("""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.combined_far < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR,)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
connection.close()
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
print >>sys.stderr, "\nFound = %d Missed = %d" % (len(found), len(missed))
return found, missed
def get_vetoes(fname, veto_segments_name = "vetoes", verbose=True): working_filename = dbtables.get_connection_filename(fname, verbose = verbose) connection = sqlite3.connect(working_filename) dbtables.DBTable_set_connection(connection) veto_segments = db_thinca_rings.get_veto_segments(connection, veto_segments_name) connection.close() dbtables.discard_connection_filename(fname, working_filename, verbose = verbose) dbtables.DBTable_set_connection(None) return veto_segments
def get_vetoes(fname, veto_segments_name="vetoes", verbose=True):
working_filename = dbtables.get_connection_filename(fname, verbose=verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
veto_segments = db_thinca_rings.get_veto_segments(connection,
veto_segments_name)
connection.close()
dbtables.discard_connection_filename(fname,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
return veto_segments
def measure_efficiency(filenames, threshold, live_time_program = "lalapps_power", upper_limit_scale = "E", tmp_path = None, verbose = False):
# FIXME: instruments are hard-coded. bad bad bad. sigh...
if upper_limit_scale == "E":
efficiency = EfficiencyData(("H1", "H2", "L1"), (lambda sim, instrument: sim.egw_over_rsquared), r"Equivalent Isotropic Energy ($M_{\odot} / \mathrm{pc}^{2}$)", 0.1)
elif upper_limit_scale == "hrss":
efficiency = EfficiencyData(("H1", "H2", "L1"), (lambda sim, instrument: sim.hrss), r"$h_{\mathrm{rss}}$", 0.1)
else:
raise ValueError("bad upper_limit_scale %s" % repr(upper_limit_scale))
#
# Iterate over injection files.
#
for n, filename in enumerate(filenames):
#
# Open the database file.
#
if verbose:
print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename)
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("coinc_detection_statistic", 2, coinc_detection_statistic)
database = SnglBurstUtils.CoincDatabase(connection, live_time_program)
if verbose:
SnglBurstUtils.summarize_coinc_database(database)
#
# Process database contents.
#
efficiency.add_contents(database, threshold)
#
# Done with this file.
#
database.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
#
# Compute efficiency from the data that have been collected
#
if verbose:
print >>sys.stderr, "binning and smoothnig efficiency data ..."
efficiency.finish(threshold)
#
# Done
#
return efficiency
def measure_efficiency(filenames, threshold, live_time_program = "lalapps_power", upper_limit_scale = "E", tmp_path = None, verbose = False):
# FIXME: instruments are hard-coded. bad bad bad. sigh...
if upper_limit_scale == "E":
efficiency = EfficiencyData(("H1", "H2", "L1"), (lambda sim, instrument: sim.egw_over_rsquared), r"Equivalent Isotropic Energy ($M_{\odot} / \mathrm{pc}^{2}$)", 0.1)
elif upper_limit_scale == "hrss":
efficiency = EfficiencyData(("H1", "H2", "L1"), (lambda sim, instrument: sim.hrss), r"$h_{\mathrm{rss}}$", 0.1)
else:
raise ValueError("bad upper_limit_scale %s" % repr(upper_limit_scale))
#
# Iterate over injection files.
#
for n, filename in enumerate(filenames):
#
# Open the database file.
#
if verbose:
print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename)
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("coinc_detection_statistic", 2, coinc_detection_statistic)
database = SnglBurstUtils.CoincDatabase(connection, live_time_program)
if verbose:
SnglBurstUtils.summarize_coinc_database(database)
#
# Process database contents.
#
efficiency.add_contents(database, threshold)
#
# Done with this file.
#
database.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
#
# Compute efficiency from the data that have been collected
#
if verbose:
print >>sys.stderr, "binning and smoothnig efficiency data ..."
efficiency.finish(threshold)
#
# Done
#
return efficiency
def measure_threshold(filenames, n_survivors, live_time_program = "lalapps_power", tmp_path = None, open_box = False, verbose = False): # # Initialize the book-keeping object. # rate_vs_threshold_data = RateVsThresholdData() # # Iterate over non-injection files. # for n, filename in enumerate(filenames): # # Open the database file. # if verbose: print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename) working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose) database = SnglBurstUtils.CoincDatabase(sqlite3.connect(working_filename), live_time_program) if verbose: SnglBurstUtils.summarize_coinc_database(database) # # Process database contents. # rate_vs_threshold_data.update_from(database, filename = filename, verbose = verbose) # # Done with this file. # database.connection.close() dbtables.discard_connection_filename(filename, working_filename, verbose = verbose) # # Determine likelihood threshold. # if verbose: print >>sys.stderr, "finishing rate vs. threshold measurement ..." rate_vs_threshold_data.finish(n_survivors, open_box = open_box, verbose = verbose) # # Done. # return rate_vs_threshold_data
def measure_threshold(filenames, n_survivors, live_time_program = "lalapps_power", tmp_path = None, open_box = False, verbose = False): # # Initialize the book-keeping object. # rate_vs_threshold_data = RateVsThresholdData() # # Iterate over non-injection files. # for n, filename in enumerate(filenames): # # Open the database file. # if verbose: print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename) working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose) database = SnglBurstUtils.CoincDatabase(sqlite3.connect(working_filename), live_time_program) if verbose: SnglBurstUtils.summarize_coinc_database(database) # # Process database contents. # rate_vs_threshold_data.update_from(database, filename = filename, verbose = verbose) # # Done with this file. # database.connection.close() dbtables.discard_connection_filename(filename, working_filename, verbose = verbose) # # Determine likelihood threshold. # if verbose: print >>sys.stderr, "finishing rate vs. threshold measurement ..." rate_vs_threshold_data.finish(n_survivors, open_box = open_box, verbose = verbose) # # Done. # return rate_vs_threshold_data
def process_file(filename, products, live_time_program, tmp_path = None, veto_segments_name = None, verbose = False):
#
# connect to database and summarize contents
#
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
contents = SnglBurstUtils.CoincDatabase(sqlite3.connect(working_filename), live_time_program, search = "StringCusp", veto_segments_name = veto_segments_name)
if verbose:
SnglBurstUtils.summarize_coinc_database(contents, filename = working_filename)
#
# augment summary with extra stuff we need. the filename
# is recorded for dumping debuggin information related to
# missed injections. if burca was run with the
# --coincidence-segments option then the value is copied
# into a segmentlistdict to facilitate the computation of
# livetime
#
contents.filename = filename
contents.coincidence_segments = ligolwprocess.get_process_params(contents.xmldoc, "lalapps_burca", "--coincidence-segments")
if contents.coincidence_segments:
# as a side-effect, this enforces the rule that
# burca has been run on the input file exactly once
contents.coincidence_segments, = contents.coincidence_segments
contents.coincidence_segments = segments.segmentlistdict.fromkeys(contents.seglists, segmentsUtils.from_range_strings(contents.coincidence_segments.split(","), boundtype = dbtables.lsctables.LIGOTimeGPS).coalesce())
else:
contents.coincidence_segments = None
#
# process contents
#
for n, product in enumerate(products):
if verbose:
print >>sys.stderr, "%s: adding to product %d ..." % (working_filename, n)
product.add_contents(contents, verbose = verbose)
#
# close
#
contents.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
def process_file(filename, products, live_time_program, tmp_path = None, veto_segments_name = None, verbose = False):
#
# connect to database and summarize contents
#
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
contents = SnglBurstUtils.CoincDatabase(sqlite3.connect(working_filename), live_time_program, search = "StringCusp", veto_segments_name = veto_segments_name)
if verbose:
SnglBurstUtils.summarize_coinc_database(contents, filename = working_filename)
#
# augment summary with extra stuff we need. the filename
# is recorded for dumping debuggin information related to
# missed injections. if burca was run with the
# --coincidence-segments option then the value is copied
# into a segmentlistdict to facilitate the computation of
# livetime
#
contents.filename = filename
contents.coincidence_segments = ligolwprocess.get_process_params(contents.xmldoc, "lalapps_burca", "--coincidence-segments")
if contents.coincidence_segments:
# as a side-effect, this enforces the rule that
# burca has been run on the input file exactly once
contents.coincidence_segments, = contents.coincidence_segments
contents.coincidence_segments = segments.segmentlistdict.fromkeys(contents.seglists, segmentsUtils.from_range_strings(contents.coincidence_segments.split(","), boundtype = dbtables.lsctables.LIGOTimeGPS).coalesce())
else:
contents.coincidence_segments = None
#
# process contents
#
for n, product in enumerate(products):
if verbose:
print >>sys.stderr, "%s: adding to product %d ..." % (working_filename, n)
product.add_contents(contents, verbose = verbose)
#
# close
#
contents.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
def update_coincs(self, fnames):
"""
This function iterates over the databases and updates the the likelihood
column with the proper lv stat
"""
for f in fnames:
working_filename = dbtables.get_connection_filename(zerofname, verbose = True)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
connection.create_function("lvstat", 3, self.lvstat)
query = "UPDATE coinc_event SET likelihood = (SELECT lvstat(coinc_event.instruments, coinc_inspiral.ifos, coinc_inspiral.false_alarm_rate) FROM coinc_inspiral WHERE coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id)"
print query
connection.cursor().execute(query)
connection.commit()
connection.close()
dbtables.discard_connection_filename(zerofname, working_filename, verbose = True)
dbtables.DBTable_set_connection(None)
def get_ifos(zerofname, verbose=True): # open database working_filename = dbtables.get_connection_filename(zerofname, verbose = verbose) connection = sqlite3.connect(working_filename) dbtables.DBTable_set_connection(connection) # extract false alarm rate threshold # FIXME This may not be robust if triggers are missing from a given category, for # example no triples in zero lag or time slides. query = 'SELECT distinct(ifos) FROM coinc_inspiral' ifo_list = [] for i in connection.cursor().execute(query): ifo_list.append(i) # done connection.close() dbtables.discard_connection_filename(zerofname, working_filename, verbose = verbose) dbtables.DBTable_set_connection(None) return ifo_list
def update_coincs(self, fnames):
"""
This function iterates over the databases and updates the the likelihood
column with the proper lv stat
"""
for f in fnames:
working_filename = dbtables.get_connection_filename(zerofname,
verbose=True)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
connection.create_function("lvstat", 3, self.lvstat)
query = "UPDATE coinc_event SET likelihood = (SELECT lvstat(coinc_event.instruments, coinc_inspiral.ifos, coinc_inspiral.false_alarm_rate) FROM coinc_inspiral WHERE coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id)"
print(query)
connection.cursor().execute(query)
connection.commit()
connection.close()
dbtables.discard_connection_filename(zerofname,
working_filename,
verbose=True)
dbtables.DBTable_set_connection(None)
def get_ifos(zerofname, verbose=True):
# open database
working_filename = dbtables.get_connection_filename(zerofname,
verbose=verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
# extract false alarm rate threshold
# FIXME This may not be robust if triggers are missing from a given category, for
# example no triples in zero lag or time slides.
query = 'SELECT distinct(ifos) FROM coinc_inspiral'
ifo_list = []
for i in connection.cursor().execute(query):
ifo_list.append(i)
# done
connection.close()
dbtables.discard_connection_filename(zerofname,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
return ifo_list
def get_far_threshold_and_segments(zerofname, instruments, live_time_program, veto_seg_name="vetoes", verbose = True): """ return the false alarm rate of the most rare zero-lag coinc, and a dictionary of the thinca segments indexed by instrument. """ # open database working_filename = dbtables.get_connection_filename(zerofname, verbose = verbose) connection = sqlite3.connect(working_filename) dbtables.DBTable_set_connection(connection) # extract false alarm rate threshold query = 'SELECT MIN(coinc_inspiral.false_alarm_rate) FROM coinc_inspiral JOIN coinc_event ON (coinc_event.coinc_event_id == coinc_inspiral.coinc_event_id) WHERE ( coinc_event.instruments = "' + instruments + '" AND NOT EXISTS(SELECT * FROM time_slide WHERE time_slide.time_slide_id == coinc_event.time_slide_id AND time_slide.offset != 0) );' print "\n", query far, = connection.cursor().execute(query).fetchone() # extract segments. seglists = db_thinca_rings.get_thinca_zero_lag_segments(connection, program_name = live_time_program) # done connection.close() dbtables.discard_connection_filename(zerofname, working_filename, verbose = verbose) dbtables.DBTable_set_connection(None) return far, seglists
def get_injections(self, instruments, FAR=float("inf")):
injfnames = self.inj_fnames
zero_lag_segments = self.zero_lag_segments[instruments]
verbose = self.opts.verbose
found = []
missed = []
print("", file=sys.stderr)
for cnt, f in enumerate(injfnames):
print("getting injections below FAR: " + str(FAR) + ":\t%.1f%%\r" %
(100.0 * cnt / len(injfnames), ),
end=' ',
file=sys.stderr)
working_filename = dbtables.get_connection_filename(
f, tmp_path=opts.tmp_space, verbose=verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
xmldoc = dbtables.get_xml(connection)
# DON'T BOTHER CONTINUING IF THE INSTRUMENTS OF INTEREST ARE NOT HERE
instruments_in_this_file = []
for i in connection.cursor().execute(
'SELECT DISTINCT(instruments) FROM coinc_event'):
if i[0]:
instruments_in_this_file.append(
frozenset(lsctables.instrument_set_from_ifos(i[0])))
if instruments not in instruments_in_this_file:
connection.close()
dbtables.discard_connection_filename(f,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
continue
# WORK OUT CORRECT SEGMENTS FOR THIS FILE WHERE WE SHOULD SEE INJECTIONS
segments = self.get_segments(connection, xmldoc)
segments -= self.veto_segments
#print thincasegments
zero_lag_segments = segments.intersection(
instruments) - segments.union(
set(segments.keys()) - instruments)
###############
# DEFINE THE INJECTION WAS MADE FUNCTION
def injection_was_made(geocent_end_time,
geocent_end_time_ns,
zero_lag_segments=zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(
geocent_end_time, geocent_end_time_ns) in zero_lag_segments
connection.create_function("injection_was_made", 2,
injection_was_made)
make_sim_inspiral = lsctables.SimInspiralTable.get_table(
dbtables.get_xml(connection)).row_from_cols
# INSPIRAL
if self.coinc_inspiral_table:
for values in connection.cursor().execute(
"""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.combined_far < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR, )):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# BURSTS
if self.multi_burst_table:
for values in connection.cursor().execute(
"""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN multi_burst ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == multi_burst.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND multi_burst.false_alarm_rate < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR, )):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
dbtables.discard_connection_filename(f,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
print("\nFound = %d Missed = %d" % (len(found), len(missed)),
file=sys.stderr)
return found, missed
def __init__(self, opts, flist):
self.segments = segments.segmentlistdict()
self.non_inj_fnames = []
self.inj_fnames = []
self.found = {}
self.missed = {}
self.opts = opts
self.veto_segments = segments.segmentlistdict()
self.zero_lag_segments = {}
self.instruments = []
self.livetime = {}
self.multi_burst_table = None
self.coinc_inspiral_table = None
for f in flist:
if opts.verbose:
print("Gathering stats from: %s...." % (f, ), file=sys.stderr)
working_filename = dbtables.get_connection_filename(
f, tmp_path=opts.tmp_space, verbose=opts.verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
xmldoc = dbtables.get_xml(connection)
# look for a sim table
try:
sim_inspiral_table = dbtables.lsctables.SimInspiralTable.get_table(
xmldoc)
self.inj_fnames.append(f)
sim = True
except ValueError:
self.non_inj_fnames.append(f)
sim = False
# FIGURE OUT IF IT IS A BURST OR INSPIRAL RUN
try:
self.multi_burst_table = dbtables.lsctables.MultiBurstTable.get_table(
xmldoc)
except ValueError:
self.multi_burst_table = None
try:
self.coinc_inspiral_table = dbtables.lsctables.CoincInspiralTable.get_table(
xmldoc)
except ValueError:
self.coinc_inspiral_table = None
if self.multi_burst_table and self.coinc_inspiral_table:
print("both burst and inspiral tables found. Aborting",
file=sys.stderr)
raise ValueError
if not sim:
self.get_instruments(connection)
self.segments += self.get_segments(connection, xmldoc)
#FIXME, don't assume veto segments are the same in every file!
self.veto_segments = self.get_veto_segments(connection)
dbtables.discard_connection_filename(f,
working_filename,
verbose=opts.verbose)
dbtables.DBTable_set_connection(None)
# remove redundant instruments
self.instruments = list(set(self.instruments))
# FIXME Do these have to be done by instruments?
self.segments -= self.veto_segments
# segments and livetime by instruments
for i in self.instruments:
self.zero_lag_segments[i] = self.segments.intersection(
i) - self.segments.union(set(self.segments.keys()) - i)
self.livetime[i] = float(abs(self.zero_lag_segments[i]))
max_mtotal = 100
mass_bins = 11
dist_bins = 50
opts, filenames = parse_command_line()
if opts.veto_segments_name is not None:
working_filename = dbtables.get_connection_filename(opts.full_data_file,
verbose=opts.verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
veto_segments = db_thinca_rings.get_veto_segments(connection,
opts.veto_segments_name)
connection.close()
dbtables.discard_connection_filename(opts.full_data_file,
working_filename,
verbose=opts.verbose)
dbtables.DBTable_set_connection(None)
else:
veto_segments = segments.segmentlistdict()
if not opts.burst_found and not opts.burst_missed:
FAR, seglists = get_far_threshold_and_segments(
opts.full_data_file,
opts.live_time_program,
instruments=lsctables.ifos_from_instrument_set(opts.instruments),
verbose=opts.verbose)
# times when only exactly the required instruments are on
seglists -= veto_segments
zero_lag_segments = seglists.intersection(
def __init__(self, filelist, live_time_program = None, veto_segments_name = None, data_segments_name = "datasegments", tmp_path = None, verbose = False):
self.segments = segments.segmentlistdict()
self.instruments = set()
self.table_name = None
self.found_injections_by_instrument_set = {}
self.missed_injections_by_instrument_set = {}
self.total_injections_by_instrument_set = {}
self.zerolag_fars_by_instrument_set = {}
self.ts_fars_by_instrument_set = {}
self.numslides = set()
for f in filelist:
if verbose:
print >> sys.stderr, "Gathering stats from: %s...." % (f,)
working_filename = dbtables.get_connection_filename(f, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
xmldoc = dbtables.get_xml(connection)
sim = False
# look for a sim inspiral table. This is IMR work we have to have one of these :)
try:
sim_inspiral_table = table.get_table(xmldoc, dbtables.lsctables.SimInspiralTable.tableName)
sim = True
except ValueError:
pass
# look for the relevant table for analyses
for table_name in allowed_analysis_table_names():
try:
setattr(self, table_name, table.get_table(xmldoc, table_name))
if self.table_name is None or self.table_name == table_name:
self.table_name = table_name
else:
raise ValueError("detected more than one table type out of " + " ".join(allowed_analysis_table_names()))
except ValueError:
setattr(self, table_name, None)
# the non simulation databases are where we get information about segments
if not sim:
self.numslides.add(connection.cursor().execute('SELECT count(DISTINCT(time_slide_id)) FROM time_slide').fetchone()[0])
[self.instruments.add(ifos) for ifos in get_instruments_from_coinc_event_table(connection)]
# save a reference to the segments for this file, needed to figure out the missed and found injections
self.this_segments = get_segments(connection, xmldoc, self.table_name, live_time_program, veto_segments_name, data_segments_name = data_segments_name)
# FIXME we don't really have any reason to use playground segments, but I put this here as a reminder
# self.this_playground_segments = segmentsUtils.S2playground(self.this_segments.extent_all())
self.segments += self.this_segments
# get the far thresholds for the loudest events in these databases
for (instruments_set, far, ts) in get_event_fars(connection, self.table_name):
if not ts:
self.zerolag_fars_by_instrument_set.setdefault(instruments_set, []).append(far)
else:
self.ts_fars_by_instrument_set.setdefault(instruments_set, []).append(far)
# get the injections
else:
# We need to know the segments in this file to determine which injections are found
self.this_injection_segments = get_segments(connection, xmldoc, self.table_name, live_time_program, veto_segments_name, data_segments_name = data_segments_name)
self.this_injection_instruments = []
distinct_instruments = connection.cursor().execute('SELECT DISTINCT(instruments) FROM coinc_event WHERE instruments!=""').fetchall()
for instruments, in distinct_instruments:
instruments_set = frozenset(lsctables.instrument_set_from_ifos(instruments))
self.this_injection_instruments.append(instruments_set)
segments_to_consider_for_these_injections = self.this_injection_segments.intersection(instruments_set) - self.this_injection_segments.union(set(self.this_injection_segments.keys()) - instruments_set)
found, total, missed = get_min_far_inspiral_injections(connection, segments = segments_to_consider_for_these_injections, table_name = self.table_name)
if verbose:
print >> sys.stderr, "%s total injections: %d; Found injections %d: Missed injections %d" % (instruments, len(total), len(found), len(missed))
self.found_injections_by_instrument_set.setdefault(instruments_set, []).extend(found)
self.total_injections_by_instrument_set.setdefault(instruments_set, []).extend(total)
self.missed_injections_by_instrument_set.setdefault(instruments_set, []).extend(missed)
# All done
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
if len(self.numslides) > 1:
raise ValueError('number of slides differs between input files')
elif self.numslides:
self.numslides = min(self.numslides)
else:
self.numslides = 0
distributions.numerator.increment(
weight=weight_func(sim),
**distributions.coinc_params([
event for event in events
if event.ifo not in contents.vetoseglists
or event.peak not in contents.vetoseglists[event.ifo]
], offsetvector))
#
# Clean up.
#
contents.xmldoc.unlink()
connection.close()
dbtables.discard_connection_filename(filename,
working_filename,
verbose=options.verbose)
#
# Output.
#
ligolw_search_summary.append_search_summary(xmldoc,
process,
ifos=segs.keys(),
inseg=segs.extent_all(),
outseg=segs.extent_all())
xmldoc.childNodes[-1].appendChild(
distributions.to_xml(u"string_cusp_likelihood"))
ligolw_process.set_process_end_time(process)
def dump_confidence_likelihood_scatter_data(globs, live_time_program = "lalapps_power", tmp_path = None, verbose = False):
#
# Collect file names.
#
if verbose:
print >>sys.stderr, "building file list ..."
filenames = sorted(filename for g in globs for filename in glob.glob(g))
#
# Initialize storage.
#
injections = []
background = []
zero_lag = []
#
# Iterate over files.
#
for n, filename in enumerate(filenames):
#
# Open the database file.
#
if verbose:
print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename)
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("coinc_detection_statistic", 2, coinc_detection_statistic)
database = SnglBurstUtils.CoincDatabase(connection, live_time_program)
if verbose:
SnglBurstUtils.summarize_coinc_database(database)
#
# Process database contents. Assume all files with
# sim_burst tables are the outputs of injection runs, and
# others aren't.
#
if database.sim_burst_table is None:
# non-injections
for id, l, c, is_background in bb_id_likelihood_confidence_background(database):
record = (coinc_detection_statistic(l, c), l, c)
if is_background:
if len(background) < 1e6:
heapq.heappush(background, record)
else:
heapq.heappushpop(background, record)
else:
if len(zero_lag) < 1e6:
heapq.heappush(zero_lag, record)
else:
heapq.heappushpop(zero_ag, record)
else:
# injections
create_sim_coinc_map_view(database.connection)
for a, l, c in database.connection.cursor().execute("""
SELECT
burst_coinc_amplitude,
burst_coinc_likelihood,
burst_coinc_confidence
FROM
sim_coinc_map
WHERE
sim_coinc_def_id == ?
""", (database.sce_definer_id,)):
record = (-a, l, c)
if len(injections) < 1e6:
heapq.heappush(injections, record)
else:
heapq.heappushpop(injections, record)
#
# Done with this file.
#
database.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
#
# Dump scatter plot data.
#
if verbose:
print >>sys.stderr, "writing scatter plot data ..."
f = file("lalapps_excesspowerfinal_background_scatter.dat", "w")
for a, l, c in background:
print >>f, "%.16g %.16g" % (l, c)
f = file("lalapps_excesspowerfinal_zero_lag_scatter.dat", "w")
for a, l, c in zero_lag:
print >>f, "%.16g %.16g" % (l, c)
f = file("lalapps_excesspowerfinal_injections_scatter.dat", "w")
for a, l, c in injections:
print >>f, "%.16g %.16g" % (l, c)
if verbose:
print >>sys.stderr, "done."
def get_injections(injfnames,
zero_lag_segments,
ifos="H1,H2,L1",
FAR=1.0,
verbose=True):
"""
The LV stat uses simulations above threshold, not some IFAR of the loudest event, so the default should be "inf"
"""
def injection_was_made(geocent_end_time,
geocent_end_time_ns,
zero_lag_segments=zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(geocent_end_time,
geocent_end_time_ns) in zero_lag_segments
found = []
missed = []
print("", file=sys.stderr)
for cnt, f in enumerate(injfnames):
print("getting injections: " + str(FAR) + ":\t%.1f%%\r" %
(100.0 * cnt / len(injfnames), ),
end=' ',
file=sys.stderr)
working_filename = dbtables.get_connection_filename(f,
tmp_path=None,
verbose=verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("injection_was_made", 2, injection_was_made)
make_sim_inspiral = lsctables.SimInspiralTable.get_table(
dbtables.get_xml(connection))._row_from_cols
# FIXME may not be done correctly if injections are done in timeslides
# FIXME may not be done correctly if injections aren't logarithmic in d
# do we really want d^3 waiting?
# FIXME do we really want injections independent of their FAR
for values in connection.cursor().execute(
"""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.false_alarm_rate < ?
AND coinc_inspiral.ifos == ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (
FAR,
ifos,
)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
connection.close()
dbtables.discard_connection_filename(f,
working_filename,
verbose=verbose)
dbtables.DBTable_set_connection(None)
print("\nFound = %d Missed = %d" % (len(found), len(missed)),
file=sys.stderr)
return found, missed
def __init__(self, flist, opts):
self.far = {}
self.segments = segments.segmentlistdict()
self.non_inj_fnames = []
self.inj_fnames = []
#self.der_fit = None
self.twoDMassBins = None
#self.dBin = {}
self.gw = None
self.found = {}
self.missed = {}
self.wnfunc = None
self.opts = opts
if opts.bootstrap_iterations: self.bootnum = int(opts.bootstrap_iterations)
else: self.bootnum = 100
self.veto_segments = segments.segmentlistdict()
self.zero_lag_segments = {}
self.instruments = []
self.livetime = {}
self.minmass = None
self.maxmass = None
self.mintotal = None
self.maxtotal = None
for f in flist:
if opts.verbose: print >> sys.stderr, "Gathering stats from: %s...." % (f,)
working_filename = dbtables.get_connection_filename(f, verbose = opts.verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
xmldoc = dbtables.get_xml(connection)
# look for a sim table
try:
sim_inspiral_table = table.get_table(xmldoc, dbtables.lsctables.SimInspiralTable.tableName)
self.inj_fnames.append(f)
sim = True
except ValueError:
self.non_inj_fnames.append(f)
sim = False
if not sim:
if opts.veto_segments_name is not None: self.veto_segments = db_thinca_rings.get_veto_segments(connection, opts.veto_segments_name)
self.get_instruments(connection)
self.segments += db_thinca_rings.get_thinca_zero_lag_segments(connection, program_name = opts.live_time_program)
self.get_far_thresholds(connection)
else:
self.get_mass_ranges(connection)
#connection.close()
dbtables.discard_connection_filename(f, working_filename, verbose = opts.verbose)
dbtables.DBTable_set_connection(None)
# FIXME Do these have to be done by instruments?
self.segments -= self.veto_segments
# compute far, segments and livetime by instruments
for i in self.instruments:
self.far[i] = min(self.far[i])
# FIXME this bombs if any of the FARS are zero. maybe it should continue
# and just remove that instrument combo from the calculation
if self.far[i] == 0:
print >> sys.stderr, "Encountered 0 FAR in %s, ABORTING" % (i,)
sys.exit(1)
self.zero_lag_segments[i] = self.segments.intersection(i) - self.segments.union(set(self.segments.keys()) - i)
# Livetime must have playground removed
self.livetime[i] = float(abs(self.zero_lag_segments[i] - segmentsUtils.S2playground(self.segments.extent_all())))
if opts.verbose: print >> sys.stderr, "%s FAR %e, livetime %f" % (",".join(sorted(list(i))), self.far[i], self.livetime[i])
# get a 2D mass binning
self.twoDMassBins = self.get_2d_mass_bins(self.minmass, self.maxmass, opts.mass_bins)
def dump_confidence_likelihood_scatter_data(globs, live_time_program = "lalapps_power", tmp_path = None, verbose = False):
#
# Collect file names.
#
if verbose:
print >>sys.stderr, "building file list ..."
filenames = sorted(filename for g in globs for filename in glob.glob(g))
#
# Initialize storage.
#
injections = []
background = []
zero_lag = []
#
# Iterate over files.
#
for n, filename in enumerate(filenames):
#
# Open the database file.
#
if verbose:
print >>sys.stderr, "%d/%d: %s" % (n + 1, len(filenames), filename)
working_filename = dbtables.get_connection_filename(filename, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("coinc_detection_statistic", 2, coinc_detection_statistic)
database = SnglBurstUtils.CoincDatabase(connection, live_time_program)
if verbose:
SnglBurstUtils.summarize_coinc_database(database)
#
# Process database contents. Assume all files with
# sim_burst tables are the outputs of injection runs, and
# others aren't.
#
if database.sim_burst_table is None:
# non-injections
for id, l, c, is_background in bb_id_likelihood_confidence_background(database):
record = (coinc_detection_statistic(l, c), l, c)
if is_background:
if len(background) < 1e6:
heapq.heappush(background, record)
else:
heapq.heappushpop(background, record)
else:
if len(zero_lag) < 1e6:
heapq.heappush(zero_lag, record)
else:
heapq.heappushpop(zero_ag, record)
else:
# injections
create_sim_coinc_map_view(database.connection)
for a, l, c in database.connection.cursor().execute("""
SELECT
burst_coinc_amplitude,
burst_coinc_likelihood,
burst_coinc_confidence
FROM
sim_coinc_map
WHERE
sim_coinc_def_id == ?
""", (database.sce_definer_id,)):
record = (-a, l, c)
if len(injections) < 1e6:
heapq.heappush(injections, record)
else:
heapq.heappushpop(injections, record)
#
# Done with this file.
#
database.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
#
# Dump scatter plot data.
#
if verbose:
print >>sys.stderr, "writing scatter plot data ..."
f = file("lalapps_excesspowerfinal_background_scatter.dat", "w")
for a, l, c in background:
print >>f, "%.16g %.16g" % (l, c)
f = file("lalapps_excesspowerfinal_zero_lag_scatter.dat", "w")
for a, l, c in zero_lag:
print >>f, "%.16g %.16g" % (l, c)
f = file("lalapps_excesspowerfinal_injections_scatter.dat", "w")
for a, l, c in injections:
print >>f, "%.16g %.16g" % (l, c)
if verbose:
print >>sys.stderr, "done."
max_mass = 99 min_mtotal = 25 max_mtotal = 100 mass_bins = 11 dist_bins = 50 opts, filenames = parse_command_line() if opts.veto_segments_name is not None: working_filename = dbtables.get_connection_filename(opts.full_data_file, verbose = opts.verbose) connection = sqlite3.connect(working_filename) dbtables.DBTable_set_connection(connection) veto_segments = db_thinca_rings.get_veto_segments(connection, opts.veto_segments_name) connection.close() dbtables.discard_connection_filename(opts.full_data_file, working_filename, verbose = opts.verbose) dbtables.DBTable_set_connection(None) else: veto_segments = segments.segmentlistdict() if not opts.burst_found and not opts.burst_missed: FAR, seglists = get_far_threshold_and_segments(opts.full_data_file, opts.live_time_program, instruments=lsctables.ifos_from_instrument_set(opts.instruments),verbose = opts.verbose) # times when only exactly the required instruments are on seglists -= veto_segments zero_lag_segments = seglists.intersection(opts.instruments) - seglists.union(set(seglists.keys()) - opts.instruments) live_time = float(abs(zero_lag_segments)) print(FAR, live_time)
def get_injections(injfnames, zero_lag_segments, ifos="H1,H2,L1", FAR=1.0, verbose = True):
"""
The LV stat uses simulations above threshold, not some IFAR of the loudest event, so the default should be "inf"
"""
def injection_was_made(geocent_end_time, geocent_end_time_ns, zero_lag_segments = zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(geocent_end_time, geocent_end_time_ns) in zero_lag_segments
found = []
missed = []
print >>sys.stderr, ""
for cnt, f in enumerate(injfnames):
print >>sys.stderr, "getting injections: " + str(FAR) + ":\t%.1f%%\r" % (100.0 * cnt / len(injfnames),),
working_filename = dbtables.get_connection_filename(f, tmp_path = None, verbose = verbose)
connection = sqlite3.connect(working_filename)
connection.create_function("injection_was_made", 2, injection_was_made)
make_sim_inspiral = lsctables.table.get_table(dbtables.get_xml(connection), lsctables.SimInspiralTable.tableName)._row_from_cols
# FIXME may not be done correctly if injections are done in timeslides
# FIXME may not be done correctly if injections aren't logarithmic in d
# do we really want d^3 waiting?
# FIXME do we really want injections independent of their FAR
for values in connection.cursor().execute("""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.false_alarm_rate < ?
AND coinc_inspiral.ifos == ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR,ifos,)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
connection.close()
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
print >>sys.stderr, "\nFound = %d Missed = %d" % (len(found), len(missed))
return found, missed
def get_injections(self, instruments, FAR=float("inf")):
injfnames = self.inj_fnames
zero_lag_segments = self.zero_lag_segments[instruments]
verbose = self.opts.verbose
found = []
missed = []
print >>sys.stderr, ""
for cnt, f in enumerate(injfnames):
print >>sys.stderr, "getting injections below FAR: " + str(FAR) + ":\t%.1f%%\r" % (100.0 * cnt / len(injfnames),),
working_filename = dbtables.get_connection_filename(f, tmp_path = opts.tmp_space, verbose = verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
xmldoc = dbtables.get_xml(connection)
# DON'T BOTHER CONTINUING IF THE INSTRUMENTS OF INTEREST ARE NOT HERE
instruments_in_this_file = []
for i in connection.cursor().execute('SELECT DISTINCT(instruments) FROM coinc_event'):
if i[0]: instruments_in_this_file.append(frozenset(lsctables.instrument_set_from_ifos(i[0])))
if instruments not in instruments_in_this_file:
connection.close()
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
continue
# WORK OUT CORRECT SEGMENTS FOR THIS FILE WHERE WE SHOULD SEE INJECTIONS
segments = self.get_segments(connection, xmldoc)
segments -= self.veto_segments
#print thincasegments
zero_lag_segments = segments.intersection(instruments) - segments.union(set(segments.keys()) - instruments)
###############
# DEFINE THE INJECTION WAS MADE FUNCTION
def injection_was_made(geocent_end_time, geocent_end_time_ns, zero_lag_segments = zero_lag_segments):
"""
return True if injection was made in the given segmentlist
"""
return lsctables.LIGOTimeGPS(geocent_end_time, geocent_end_time_ns) in zero_lag_segments
connection.create_function("injection_was_made", 2, injection_was_made)
make_sim_inspiral = lsctables.SimInspiralTable.get_table(dbtables.get_xml(connection)).row_from_cols
# INSPIRAL
if self.coinc_inspiral_table:
for values in connection.cursor().execute("""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN coinc_inspiral ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == coinc_inspiral.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND coinc_inspiral.combined_far < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR,)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# BURSTS
if self.multi_burst_table:
for values in connection.cursor().execute("""
SELECT
sim_inspiral.*,
-- true if injection matched a coinc below the false alarm rate threshold
EXISTS (
SELECT
*
FROM
coinc_event_map AS mapa
JOIN coinc_event_map AS mapb ON (
mapa.coinc_event_id == mapb.coinc_event_id
)
JOIN multi_burst ON (
mapb.table_name == "coinc_event"
AND mapb.event_id == multi_burst.coinc_event_id
)
WHERE
mapa.table_name == "sim_inspiral"
AND mapa.event_id == sim_inspiral.simulation_id
AND multi_burst.false_alarm_rate < ?
)
FROM
sim_inspiral
WHERE
-- only interested in injections that were injected
injection_was_made(sim_inspiral.geocent_end_time, sim_inspiral.geocent_end_time_ns)
""", (FAR,)):
sim = make_sim_inspiral(values)
if values[-1]:
found.append(sim)
else:
missed.append(sim)
# done
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
dbtables.DBTable_set_connection(None)
print >>sys.stderr, "\nFound = %d Missed = %d" % (len(found), len(missed))
return found, missed
# if the database contains a sim_inspiral table then it is assumed
# to represent an injection run. its rings must not added to the
# livetime, and it cannot provide background coincs, so it is just
# skipped altogether in this first pass.
#
if "sim_ringdown" in dbtables.get_table_names(connection):
if options.verbose:
print >>sys.stderr, "\tdatabase contains sim_ringdown table, skipping ..."
#
# close the database
#
connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = options.verbose)
continue
#
# compute and record background livetime
#
background.add_livetime(connection, options.live_time_program, veto_segments_name = options.veto_segments_name, verbose = options.verbose)
#
# count background coincs
#
if options.verbose:
print >>sys.stderr, "\tcollecting background statistics ..."
for on_instruments, participating_instruments, frequency, snr, uncombined_ifar, likelihood in connection.cursor().execute("""
def __init__(self, filelist, live_time_program = None, veto_segments_name = None, data_segments_name = "datasegments", tmp_path = None, verbose = False):
self.segments = segments.segmentlistdict()
self.instruments = set()
self.table_name = None
self.found_injections_by_instrument_set = {}
self.missed_injections_by_instrument_set = {}
self.total_injections_by_instrument_set = {}
self.zerolag_fars_by_instrument_set = {}
self.ts_fars_by_instrument_set = {}
self.numslides = set()
for f in filelist:
if verbose:
print >> sys.stderr, "Gathering stats from: %s...." % (f,)
working_filename = dbtables.get_connection_filename(f, tmp_path = tmp_path, verbose = verbose)
connection = sqlite3.connect(working_filename)
xmldoc = dbtables.get_xml(connection)
sim = False
# look for a sim inspiral table. This is IMR work we have to have one of these :)
try:
sim_inspiral_table = table.get_table(xmldoc, dbtables.lsctables.SimInspiralTable.tableName)
sim = True
except ValueError:
pass
# look for the relevant table for analyses
for table_name in allowed_analysis_table_names():
try:
setattr(self, table_name, table.get_table(xmldoc, table_name))
if self.table_name is None or self.table_name == table_name:
self.table_name = table_name
else:
raise ValueError("detected more than one table type out of " + " ".join(allowed_analysis_table_names()))
except ValueError:
setattr(self, table_name, None)
# the non simulation databases are where we get information about segments
if not sim:
self.numslides.add(connection.cursor().execute('SELECT count(DISTINCT(time_slide_id)) FROM time_slide').fetchone()[0])
[self.instruments.add(ifos) for ifos in get_instruments_from_coinc_event_table(connection)]
# save a reference to the segments for this file, needed to figure out the missed and found injections
self.this_segments = get_segments(connection, xmldoc, self.table_name, live_time_program, veto_segments_name, data_segments_name = data_segments_name)
# FIXME we don't really have any reason to use playground segments, but I put this here as a reminder
# self.this_playground_segments = segmentsUtils.S2playground(self.this_segments.extent_all())
self.segments += self.this_segments
# get the far thresholds for the loudest events in these databases
for (instruments_set, far, ts) in get_event_fars(connection, self.table_name):
if not ts:
self.zerolag_fars_by_instrument_set.setdefault(instruments_set, []).append(far)
else:
self.ts_fars_by_instrument_set.setdefault(instruments_set, []).append(far)
# get the injections
else:
# We need to know the segments in this file to determine which injections are found
self.this_injection_segments = get_segments(connection, xmldoc, self.table_name, live_time_program, veto_segments_name, data_segments_name = data_segments_name)
self.this_injection_instruments = []
distinct_instruments = connection.cursor().execute('SELECT DISTINCT(instruments) FROM coinc_event WHERE instruments!=""').fetchall()
for instruments, in distinct_instruments:
instruments_set = frozenset(lsctables.instrument_set_from_ifos(instruments))
self.this_injection_instruments.append(instruments_set)
segments_to_consider_for_these_injections = self.this_injection_segments.intersection(instruments_set) - self.this_injection_segments.union(set(self.this_injection_segments.keys()) - instruments_set)
found, total, missed = get_min_far_inspiral_injections(connection, segments = segments_to_consider_for_these_injections, table_name = self.table_name)
if verbose:
print >> sys.stderr, "%s total injections: %d; Found injections %d: Missed injections %d" % (instruments, len(total), len(found), len(missed))
self.found_injections_by_instrument_set.setdefault(instruments_set, []).extend(found)
self.total_injections_by_instrument_set.setdefault(instruments_set, []).extend(total)
self.missed_injections_by_instrument_set.setdefault(instruments_set, []).extend(missed)
# All done
dbtables.discard_connection_filename(f, working_filename, verbose = verbose)
if len(self.numslides) > 1:
raise ValueError('number of slides differs between input files')
elif self.numslides:
self.numslides = min(self.numslides)
else:
self.numslides = 0
def __init__(self, opts, flist):
self.segments = segments.segmentlistdict()
self.non_inj_fnames = []
self.inj_fnames = []
self.found = {}
self.missed = {}
self.opts = opts
self.veto_segments = segments.segmentlistdict()
self.zero_lag_segments = {}
self.instruments = []
self.livetime = {}
self.multi_burst_table = None
self.coinc_inspiral_table = None
for f in flist:
if opts.verbose: print >> sys.stderr, "Gathering stats from: %s...." % (f,)
working_filename = dbtables.get_connection_filename(f, tmp_path=opts.tmp_space, verbose = opts.verbose)
connection = sqlite3.connect(working_filename)
dbtables.DBTable_set_connection(connection)
xmldoc = dbtables.get_xml(connection)
# look for a sim table
try:
sim_inspiral_table = dbtables.lsctables.SimInspiralTable.get_table(xmldoc)
self.inj_fnames.append(f)
sim = True
except ValueError:
self.non_inj_fnames.append(f)
sim = False
# FIGURE OUT IF IT IS A BURST OR INSPIRAL RUN
try:
self.multi_burst_table = dbtables.lsctables.MultiBurstTable.get_table(xmldoc)
except ValueError:
self.multi_burst_table = None
try:
self.coinc_inspiral_table = dbtables.lsctables.CoincInspiralTable.get_table(xmldoc)
except ValueError:
self.coinc_inspiral_table = None
if self.multi_burst_table and self.coinc_inspiral_table:
print >>sys.stderr, "both burst and inspiral tables found. Aborting"
raise ValueError
if not sim:
self.get_instruments(connection)
self.segments += self.get_segments(connection,xmldoc)
#FIXME, don't assume veto segments are the same in every file!
self.veto_segments = self.get_veto_segments(connection)
dbtables.discard_connection_filename(f, working_filename, verbose = opts.verbose)
dbtables.DBTable_set_connection(None)
# remove redundant instruments
self.instruments = list(set(self.instruments))
# FIXME Do these have to be done by instruments?
self.segments -= self.veto_segments
# segments and livetime by instruments
for i in self.instruments:
self.zero_lag_segments[i] = self.segments.intersection(i) - self.segments.union(set(self.segments.keys()) - i)
self.livetime[i] = float(abs(self.zero_lag_segments[i]))