diff --git a/gstlal-inspiral/bin/gstlal_inspiral_lvalert_uberplotter b/gstlal-inspiral/bin/gstlal_inspiral_lvalert_uberplotter
index 2972da2e49b591488bd67ccef95762de59168100..457bf0fd549fe2115e713cdcea0c8b642bb93e00 100755
--- a/gstlal-inspiral/bin/gstlal_inspiral_lvalert_uberplotter
+++ b/gstlal-inspiral/bin/gstlal_inspiral_lvalert_uberplotter
@@ -58,6 +58,7 @@ from lal import series
from gstlal import far
from gstlal import lvalert_helper
from gstlal import plotfar
+from gstlal import plotpsd
import matplotlib
matplotlib.rcParams.update({
@@ -164,7 +165,7 @@ def plot_snrchisq(instrument, rankingstat, plot_type, max_snr, snrchisq = None):
#
# =============================================================================
#
-
+
def main(client=None):
#
@@ -191,15 +192,15 @@ def main(client=None):
lvnodes = ['test_gstlal_allsky']
else:
lvnodes = ['cbc_gstlal_allsky']
-
+
#
# start LVAlert listener loop:
#
try:
logging.info("connecting to %s" % options.lvalert_server_url)
- if client.connect():
+ if client.connect():
logging.info("connected to %s" % options.lvalert_server_url)
- else:
+ else:
logging.info("could not connect to %s, exiting" % options.lvalert_server_url)
exit()
@@ -219,7 +220,7 @@ def main(client=None):
except (KeyboardInterrupt, SystemExit):
logging.info("exit signal received, disconnecting from lvalert")
- client.abort()
+ client.abort()
#
# the uber plotter class that responds to alerts:
@@ -240,7 +241,7 @@ class uber_plotter(object):
logging.info("Alert Contents: %s" % lvalert_data)
gid = None
-
+
# check for the right filenames:
if "filename" in lvalert_data["data"]:
filename = os.path.split(urlparse.urlparse(lvalert_data["data"]["filename"]).path)[-1]
@@ -250,14 +251,14 @@ class uber_plotter(object):
logging.info("generating ranking plots for %s" % gid)
try:
self.generate_ranking_plots(gid)
- except Exception, err:
+ except Exception, err:
logging.info(traceback.print_exc())
elif filename in (u"psd.xml.gz",):
logging.info("psd.xml.gz available for %s" % gid)
logging.info("generating psd plots for %s" % gid)
try:
self.generate_psd_plots(gid)
- except Exception, err:
+ except Exception, err:
logging.info(traceback.print_exc())
else:
logging.info("filename is not 'ranking_data.xml.gz' or 'psd.xml.gz'. skipping")
@@ -265,118 +266,118 @@ class uber_plotter(object):
logging.info("json key filename not in lvalert data, skipping")
-# #
-#---- Generate plots from ranking stat file ----#
-# #
-
- def generate_ranking_plots(self, gid=None):
- #
- # download candidate's data
- #
- coinc_xmldoc, rankingstat, rankingstatpdf, fapfar = get_files(gracedb_client=self.gracedb, graceid=gid)
- coinc_event_table = lsctables.CoincTable.get_table(coinc_xmldoc)
- coinc_inspiral_table = lsctables.CoincInspiralTable.get_table(coinc_xmldoc)
- try:
- coinc_event, = coinc_event_table
- coinc_inspiral, = coinc_inspiral_table
- except ValueError:
- raise ValueError("document does not contain exactly one candidate")
- if [(row.search, row.search_coinc_type) for row in lsctables.CoincDefTable.get_table(coinc_xmldoc) if row.coinc_def_id == coinc_event.coinc_def_id] != [(InspiralCoincDef.search, InspiralCoincDef.search_coinc_type)]:
- raise ValueError("candidate is not an inspiral<-->inspiral coincidence")
- offsetvector = lsctables.TimeSlideTable.get_table(coinc_xmldoc).as_dict()[coinc_event.time_slide_id]
- sngl_inspirals = dict((row.ifo, row) for row in lsctables.SnglInspiralTable.get_table(coinc_xmldoc))
-
-
-
- for plot_type in ["background_pdf", "injection_pdf", "zero_lag_pdf", "LR"]:
- for instrument in rankingstat.instruments:
- if instrument in sngl_inspirals:
- # place marker on plot
- fig = plot_snrchisq(instrument, rankingstat, plot_type, self.opts.max_snr, (sngl_inspirals[instrument].snr, sngl_inspirals[instrument].chisq))
- else:
- # no sngl for this instrument
- fig = plot_snrchisq(instrument, rankingstat, plot_type, self.opts.max_snr)
- filename = "%s_%s_%s_snrchi.png" % (gid, instrument, plot_type)
- if not self.opts.no_upload:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "%s SNR, chisq PDF" % instrument, tagname = "background")
- if self.opts.output_path is not None:
- filename = os.path.join(self.opts.output_path, filename)
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
-
-
- fig = plotfar.plot_likelihood_ratio_ccdf(fapfar, (0., max(40., coinc_event.likelihood - coinc_event.likelihood % 5. + 5.)), ln_likelihood_ratio_markers = (coinc_event.likelihood,))
- filename = "%s_likehoodratio_ccdf.png" % gid
- if not self.opts.no_upload:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Likelihood Ratio CCDF", tagname = "background")
- if self.opts.output_path is not None:
- filename = os.path.join(self.opts.output_path, filename)
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
-
-
- fig = plotfar.plot_horizon_distance_vs_time(rankingstat, (coinc_inspiral.end - 14400., coinc_inspiral.end), tref = coinc_inspiral.end)
- filename = "%s_horizon_distances.png" % gid
- if not self.opts.no_upload:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Horizon Distances", tagname = "psd")
- if self.opts.output_path is not None:
- filename = os.path.join(self.opts.output_path, filename)
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
-
-
- fig = plotfar.plot_rates(rankingstat)
- filename = "%s_rates.png" % gid
- if not self.opts.no_upload:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Instrument combo rates", tagname = "background")
- if self.opts.output_path is not None:
- filename = os.path.join(self.opts.output_path, filename)
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
-
-
-# #
-#-------- Generate plots from psd file --------#
-# #
+ # #
+ #---- Generate plots from ranking stat file ----#
+ # #
+
+ def generate_ranking_plots(self, gid=None):
+ #
+ # download candidate's data
+ #
+ coinc_xmldoc, rankingstat, rankingstatpdf, fapfar = get_files(gracedb_client=self.gracedb, graceid=gid)
+ coinc_event_table = lsctables.CoincTable.get_table(coinc_xmldoc)
+ coinc_inspiral_table = lsctables.CoincInspiralTable.get_table(coinc_xmldoc)
+ try:
+ coinc_event, = coinc_event_table
+ coinc_inspiral, = coinc_inspiral_table
+ except ValueError:
+ raise ValueError("document does not contain exactly one candidate")
+ if [(row.search, row.search_coinc_type) for row in lsctables.CoincDefTable.get_table(coinc_xmldoc) if row.coinc_def_id == coinc_event.coinc_def_id] != [(InspiralCoincDef.search, InspiralCoincDef.search_coinc_type)]:
+ raise ValueError("candidate is not an inspiral<-->inspiral coincidence")
+ offsetvector = lsctables.TimeSlideTable.get_table(coinc_xmldoc).as_dict()[coinc_event.time_slide_id]
+ sngl_inspirals = dict((row.ifo, row) for row in lsctables.SnglInspiralTable.get_table(coinc_xmldoc))
+
+
+
+ for plot_type in ["background_pdf", "injection_pdf", "zero_lag_pdf", "LR"]:
+ for instrument in rankingstat.instruments:
+ if instrument in sngl_inspirals:
+ # place marker on plot
+ fig = plot_snrchisq(instrument, rankingstat, plot_type, self.opts.max_snr, (sngl_inspirals[instrument].snr, sngl_inspirals[instrument].chisq))
+ else:
+ # no sngl for this instrument
+ fig = plot_snrchisq(instrument, rankingstat, plot_type, self.opts.max_snr)
+ filename = "%s_%s_%s_snrchi.png" % (gid, instrument, plot_type)
+ if not self.opts.no_upload:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "%s SNR, chisq PDF" % instrument, tagname = "background")
+ if self.opts.output_path is not None:
+ filename = os.path.join(self.opts.output_path, filename)
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+
+
+ fig = plotfar.plot_likelihood_ratio_ccdf(fapfar, (0., max(40., coinc_event.likelihood - coinc_event.likelihood % 5. + 5.)), ln_likelihood_ratio_markers = (coinc_event.likelihood,))
+ filename = "%s_likehoodratio_ccdf.png" % gid
+ if not self.opts.no_upload:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Likelihood Ratio CCDF", tagname = "background")
+ if self.opts.output_path is not None:
+ filename = os.path.join(self.opts.output_path, filename)
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+
+
+ fig = plotfar.plot_horizon_distance_vs_time(rankingstat, (coinc_inspiral.end - 14400., coinc_inspiral.end), tref = coinc_inspiral.end)
+ filename = "%s_horizon_distances.png" % gid
+ if not self.opts.no_upload:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Horizon Distances", tagname = "psd")
+ if self.opts.output_path is not None:
+ filename = os.path.join(self.opts.output_path, filename)
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+
+
+ fig = plotfar.plot_rates(rankingstat)
+ filename = "%s_rates.png" % gid
+ if not self.opts.no_upload:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "Instrument combo rates", tagname = "background")
+ if self.opts.output_path is not None:
+ filename = os.path.join(self.opts.output_path, filename)
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+
+
+ # #
+ #-------- Generate plots from psd file --------#
+ # #
def generate_psd_plots(self, gid=None):
- psds = get_psds(gracedb_client=self.gracedb,
+ psds = get_psds(gracedb_client=self.gracedb,
graceid=gid, ignore_404 = self.opts.skip_404)
- if psds is None:
+ if psds is None:
logging.info("Could not get_psds, exiting loop")
return
- coinc_xmldoc = lvalert_helper.get_coinc_xmldoc(self.gracedb, gid)
+ coinc_xmldoc = lvalert_helper.get_coinc_xmldoc(self.gracedb, gid)
- #
- # PSD plot
- #
+ #
+ # PSD plot
+ #
- fig = plotpsd.plot_psds(psds, coinc_xmldoc, plot_width = 800)
- fig.tight_layout()
+ fig = plotpsd.plot_psds(psds, coinc_xmldoc, plot_width = 800)
+ fig.tight_layout()
- filename = "%s_psd.%s" % (gid, self.opts.format)
- if options.no_upload:
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
- else:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "strain spectral density plot", tagname = "psd")
+ filename = "%s_psd.%s" % (gid, self.opts.format)
+ if self.opts.no_upload:
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+ else:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "strain spectral density plot", tagname = "psd")
- #
- # Cumulative SNRs plot
- #
+ #
+ # Cumulative SNRs plot
+ #
- fig = plotpsd.plot_cumulative_snrs(psds, coinc_xmldoc, plot_width = 800)
- fig.tight_layout()
+ fig = plotpsd.plot_cumulative_snrs(psds, coinc_xmldoc, plot_width = 800)
+ fig.tight_layout()
- filename = "%s_cumulative_snrs.%s" % (gid, self.opts.format)
- if self.opts.no_upload:
- logging.info("writing %s ..." % filename)
- fig.savefig(filename)
- else:
- lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "cumulative SNRs plot", tagname = "psd")
+ filename = "%s_cumulative_snrs.%s" % (gid, self.opts.format)
+ if self.opts.no_upload:
+ logging.info("writing %s ..." % filename)
+ fig.savefig(filename)
+ else:
+ lvalert_helper.upload_fig(fig, self.gracedb, gid, filename = filename, log_message = "cumulative SNRs plot", tagname = "psd")
- logging.info("finished processing psd plot for %s" % gid)
+ logging.info("finished processing psd plot for %s" % gid)