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("%d/%d: %s" % (n + 1, len(filenames), filename), file=sys.stderr)
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("binning and smoothnig efficiency data ...", file=sys.stderr)
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("%d/%d: %s" % (n + 1, len(filenames), filename), file=sys.stderr)
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("finishing rate vs. threshold measurement ...", file=sys.stderr)
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
# FIXME: remove when LAL accepts unicode
contents.coincidence_segments = contents.coincidence_segments.encode('utf-8')
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("%s: adding to product %d ..." % (working_filename, n), file=sys.stderr)
product.add_contents(contents, verbose = verbose)
#
# close
#
contents.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = verbose)
a.coinc_event_id AS coinc_event_id,
b.event_id AS event_id
FROM
coinc_event_map AS a
JOIN coinc_event_map AS b ON (
a.table_name == 'sim_burst'
AND b.table_name == 'coinc_event'
AND b.coinc_event_id == a.coinc_event_id
)
""")
for n, plot in enumerate(coincplots):
if options.verbose:
print("adding to coinc plot %d ..." % options.coinc_plot[n], file=sys.stderr)
plot.add_contents(database)
database.connection.close()
dbtables.discard_connection_filename(filename, working_filename, verbose = options.verbose)
#
# compute the binning for the efficiency contour plots
#
def make_binning(plots):
plots = [plot for instrument in plots.keys() for plot in plots[instrument] if isinstance(plot, SimBurstUtils.Efficiency_hrss_vs_freq)]
if not plots:
return None
minx = min([min(plot.injected_x) for plot in plots])
maxx = max([max(plot.injected_x) for plot in plots])
miny = min([min(plot.injected_y) for plot in plots])
maxy = max([max(plot.injected_y) for plot in plots])
FROM
coinc_event_map AS a
JOIN coinc_event_map AS b ON (
a.table_name == 'sim_burst'
AND b.table_name == 'coinc_event'
AND b.coinc_event_id == a.coinc_event_id
)
""")
for n, plot in enumerate(coincplots):
if options.verbose:
print("adding to coinc plot %d ..." % options.coinc_plot[n],
file=sys.stderr)
plot.add_contents(database)
database.connection.close()
dbtables.discard_connection_filename(filename,
working_filename,
verbose=options.verbose)
#
# compute the binning for the efficiency contour plots
#
def make_binning(plots):
plots = [
plot for instrument in plots.keys() for plot in plots[instrument]
if isinstance(plot, SimBurstUtils.Efficiency_hrss_vs_freq)
]
if not plots:
return None
minx = min([min(plot.injected_x) for plot in plots])
def dump_confidence_likelihood_scatter_data(globs, live_time_program = "lalapps_power", tmp_path = None, verbose = False):
#
# Collect file names.
#
if verbose:
print("building file list ...", file=sys.stderr)
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("%d/%d: %s" % (n + 1, len(filenames), filename), file=sys.stderr)
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("writing scatter plot data ...", file=sys.stderr)
f = file("lalapps_excesspowerfinal_background_scatter.dat", "w")
for a, l, c in background:
print("%.16g %.16g" % (l, c), file=f)
f = file("lalapps_excesspowerfinal_zero_lag_scatter.dat", "w")
for a, l, c in zero_lag:
print("%.16g %.16g" % (l, c), file=f)
f = file("lalapps_excesspowerfinal_injections_scatter.dat", "w")
for a, l, c in injections:
print("%.16g %.16g" % (l, c), file=f)
if verbose:
print("done.", file=sys.stderr)