gdbdir = config.get('gdb general', 'main_gdb_dir')
if not opts.skip_gracedb_upload:
if config.has_option('gdb general', 'gdb_url'):
gracedb = GraceDb(config.get('gdb general', 'gdb_url'))
else:
gracedb = GraceDb()
if config.has_option(opts.classifier, 'plotting_label'):
plotting_label = config.get(opts.classifier, 'plotting_label')
else:
plotting_label = opts.classifier
#===================================================================================================
rank_channame = idq.channame(ifo, opts.classifier, "%s_rank" % tag)
fap_channame = idq.channame(ifo, opts.classifier, "%s_fap" % tag)
fapUL_channame = idq.channame(ifo, opts.classifier, "%s_fapUL" % tag)
#===================================================================================================
# get all *.gwf files in range
if opts.verbose:
print "Finding relevant *.gwf files"
rank_filenames = []
fap_filenames = []
all_files = idq.get_all_files_in_range(realtimedir,
opts.plotting_gps_start,
opts.plotting_gps_end,
pad=0,
gdbdir = config.get('gdb general','main_gdb_dir')
if not opts.skip_gracedb_upload:
if config.has_option('gdb general', 'gdb_url'):
gracedb = GraceDb(config.get('gdb general', 'gdb_url'))
else:
gracedb = GraceDb()
if config.has_option(opts.classifier, 'plotting_label'):
plotting_label = config.get(opts.classifier, 'plotting_label')
else:
plotting_label = opts.classifier
#===================================================================================================
rank_channame = idq.channame(ifo, opts.classifier, "%s_rank"%tag)
fap_channame = idq.channame(ifo, opts.classifier, "%s_fap"%tag)
fapUL_channame = idq.channame(ifo, opts.classifier, "%s_fapUL"%tag)
#===================================================================================================
# get all *.gwf files in range
if opts.verbose:
print "Finding relevant *.gwf files"
rank_filenames = []
fap_filenames = []
all_files = idq.get_all_files_in_range(realtimedir, opts.plotting_gps_start, opts.plotting_gps_end, pad=0, suffix='.gwf')
for filename in all_files:
if opts.classifier == idq.extract_fap_name(filename): # and ifo in filename: ### this last bit not needed?
if 'rank' in filename:
#========================
# which classifiers
#========================
### ensure we have a section for each classifier and fill out dictionary of options
classifiersD, mla, ovl = idq.config_to_classifiersD(config)
### get combiners information and add these to classifiersD
combinersD, referenced_classifiers = idq.config_to_combinersD(config)
for combiner, value in combinersD.items():
classifiersD[combiner] = value
classifiers = sorted(classifiersD.keys())
### compute channel names stored in frames
channameD = dict((name, {
'rank': idq.channame(ifo, name, "%s_rank" % usertag),
'fap': idq.channame(ifo, name, "%s_fap" % usertag),
'fapUL': idq.channame(ifo, name, "%s_fapUL" % usertag)
}) for name in classifiers)
#if mla:
# ### reading parameters from config file needed for mla
# auxmvc_coinc_window = config.getfloat('build_auxmvc_vectors','time-window')
# auxmc_gw_signif_thr = config.getfloat('build_auxmvc_vectors','signif-threshold')
# auxmvc_selected_channels = config.get('general','selected-channels')
# auxmvc_unsafe_channels = config.get('general','unsafe-channels')
#========================
# realtime
#========================
realtimedir = config.get('general', 'realtimedir')
segsum = lsctables.New( lsctables.SegmentSumTable, columns=["process_id", "segment_sum_id", "start_time", "start_time_ns", "end_time", "end_time_ns", "comment", "segment_def_id"] )
segtab = lsctables.New( lsctables.SegmentTable, columns=["process_id", "segment_def_id", "segment_id", "start_time", "start_time_ns", "end_time", "end_time_ns"] )
xml_element.appendChild( segdef )
xml_element.appendChild( segsum )
xml_element.appendChild( segtab )
### iterate through classifiers
for classifier in opts.classifier:
logger.info('Begin: generating segments for %s'%classifier)
faps = fapsD[classifier]
logger.info(' found %d files'%(len(faps)))
### need to load in time-series from frames here!
chan = idq.channame(ifo, classifier, "%s_fap"%usertag)
t, ts = idq.combine_gwf(faps, [chan]) ### loads in the data from frames
logger.info(' found %d continous segments'%(len(t)))
### set up segdef row
fap2segdef_id = {}
for FAPthr in opts.FAPthr:
segdef_id = segdef.get_next_id()
segdef_row = lsctables.SegmentDef()
segdef_row.process_id = proc_id
segdef_row.segment_def_id = segdef_id
segdef_row.ifos = ifo
segdef_row.name = classifier
segdef_row.version = 1
#========================
# which classifiers
#========================
### ensure we have a section for each classifier and fill out dictionary of options
classifiersD, mla, ovl = idq.config_to_classifiersD( config )
### get combiners information and add these to classifiersD
combinersD, referenced_classifiers = idq.config_to_combinersD( config )
for combiner, value in combinersD.items():
classifiersD[combiner] = value
classifiers = sorted(classifiersD.keys())
### compute channel names stored in frames
channameD = dict( (name, {'rank':idq.channame(ifo, name, "%s_rank"%usertag),
'fap':idq.channame(ifo, name, "%s_fap"%usertag),
'fapUL':idq.channame(ifo, name, "%s_fapUL"%usertag)}) for name in classifiers )
#if mla:
# ### reading parameters from config file needed for mla
# auxmvc_coinc_window = config.getfloat('build_auxmvc_vectors','time-window')
# auxmc_gw_signif_thr = config.getfloat('build_auxmvc_vectors','signif-threshold')
# auxmvc_selected_channels = config.get('general','selected-channels')
# auxmvc_unsafe_channels = config.get('general','unsafe-channels')
#========================
# realtime
#========================
realtimedir = config.get('general', 'realtimedir')
"end_time_ns"
])
xml_element.appendChild(segdef)
xml_element.appendChild(segsum)
xml_element.appendChild(segtab)
### iterate through classifiers
for classifier in opts.classifier:
logger.info('Begin: generating segments for %s' % classifier)
faps = fapsD[classifier]
logger.info(' found %d files' % (len(faps)))
### need to load in time-series from frames here!
chan = idq.channame(ifo, classifier, "%s_fap" % usertag)
t, ts = idq.combine_gwf(faps, [chan]) ### loads in the data from frames
logger.info(' found %d continous segments' % (len(t)))
### set up segdef row
fap2segdef_id = {}
for FAPthr in opts.FAPthr:
segdef_id = segdef.get_next_id()
segdef_row = lsctables.SegmentDef()
segdef_row.process_id = proc_id
segdef_row.segment_def_id = segdef_id
segdef_row.ifos = ifo
segdef_row.name = classifier
segdef_row.version = 1
