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Commit 4c79554e authored by Patrick Godwin's avatar Patrick Godwin
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gstlal_inspiral_lvalert_uberplotter: fix issues with mixing tabs/spaces,... 

gstlal_inspiral_lvalert_uberplotter: fix issues with mixing tabs/spaces, missing psdutil import, options typo
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gstlal-inspiral/bin/gstlal_inspiral_lvalert_uberplotter
+ 108
− 107
View file @ 4c79554e
......@@ -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)
......
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