logger.info(' downselecting to the %d most recent cleans' %
max_num_cln)
cleans = cleans[-max_num_cln:]
output = idq.combine_separated_output(these_columns,
[glitches, cleans])
### define weights over time
output['weight'] = calibration.weights(output['GPS'],
weight_type="uniform")
if not opts.dont_cluster:
cluster_dat = idq.dat(output_dir, classifier, ifo, "clustered",
usertag, gpsstart - lookback, lookback +
stride) ### write clustered dat file
logger.info(' writing %s' % cluster_dat)
idq.output_to_datfile(output, cluster_dat)
else:
cluster_dat = idq.dat(output_dir, classifier, ifo, "unclustered",
usertag, gpsstart - lookback,
lookback + stride)
logger.info(' writing %s' % cluster_dat)
idq.output_to_datfile(output, cluster_dat)
### compute rcg from output
r, c, g = idq.dat_to_rcg(output)
logger.info(' N_gch = %d , N_cln = %d' % (g[-1], c[-1]))
### dump into roc file
roc = idq.roc(output_dir, classifier, ifo, usertag,
gpsstart - lookback, lookback + stride)
raise ValueError(
"combiner=%s joint_p(c)=%s not understood" %
(combiner, combinersD[combiner]['joint_p(c)']))
### compute combined statistics
logger.info(' computing approximation to joint likelihood ratio')
L_joint = pofg_joint / pofc_joint ### compute likelihood
r_joint = L_joint / (1 + L_joint) ### compute rank
### put them into output
output['rank'] = r_joint
output['Likelihood'] = L_joint
### write datfile
logger.info(' writing %s' % dat)
idq.output_to_datfile(output, dat)
### convert datfiles to xml tables
logger.info(' Begin: converting %s dat file into xml files' %
combiner)
logger.info(' converting %s to xml tables' % dat)
### read dafile -> xml docs
(gchxml_doc,
clnxml_doc) = idq.datfile2xmldocs(dat,
ifo,
fapmap,
Lmap=False,
Effmap=effmap,
flavor=flavor,
gwchan=gwchannel,
cleans.sort(key=lambda l: l[these_columns['GPS']])
if len(glitches) > max_num_gch:
logger.info(' downselecting to the %d most recent glitches'%max_num_gch)
glitches = glitches[-max_num_gch:]
if len(cleans) > max_num_cln:
logger.info(' downselecting to the %d most recent cleans'%max_num_cln)
cleans = cleans[-max_num_cln:]
output = idq.combine_separated_output( these_columns, [glitches, cleans] )
### define weights over time
output['weight'] = calibration.weights( output['GPS'], weight_type="uniform" )
if not opts.dont_cluster:
cluster_dat = idq.dat(output_dir, classifier, ifo, "clustered", usertag, gpsstart-lookback, lookback+stride) ### write clustered dat file
logger.info(' writing %s'%cluster_dat)
idq.output_to_datfile( output, cluster_dat )
else:
cluster_dat = idq.dat(output_dir, classifier, ifo, "unclustered", usertag, gpsstart-lookback, lookback+stride)
logger.info(' writing %s'%cluster_dat)
idq.output_to_datfile( output, cluster_dat )
### compute rcg from output
r, c, g = idq.dat_to_rcg( output )
logger.info(' N_gch = %d , N_cln = %d'%(g[-1], c[-1]))
### dump into roc file
roc = idq.roc(output_dir, classifier, ifo, usertag, gpsstart-lookback, lookback+stride)
logger.info(' writting %s'%roc)
idq.rcg_to_file(roc, r, c, g)
pofc_joint = numpy.prod( pofc_joint, axis=0 )
else:
raise ValueError("combiner=%s joint_p(c)=%s not understood"%(combiner, combinersD[combiner]['joint_p(c)']))
### compute combined statistics
logger.info(' computing approximation to joint likelihood ratio')
L_joint = pofg_joint / pofc_joint ### compute likelihood
r_joint = L_joint / ( 1 + L_joint ) ### compute rank
### put them into output
output['rank'] = r_joint
output['Likelihood'] = L_joint
### write datfile
logger.info(' writing %s'%dat)
idq.output_to_datfile( output, dat )
### convert datfiles to xml tables
logger.info(' Begin: converting %s dat file into xml files'%combiner)
logger.info(' converting %s to xml tables' % dat)
### read dafile -> xml docs
(gchxml_doc, clnxml_doc) = idq.datfile2xmldocs(dat, ifo, fapmap, Lmap=False, Effmap=effmap, flavor=flavor,
gwchan=gwchannel, gwtrigs=gw_trig, prog=__prog__, options=opts.__dict__, version=__version__ )
### write documents
logger.info(' --> writing ' + gchxml)
idq.ligolw_utils.write_filename(gchxml_doc, gchxml, gz=gchxml.endswith('.gz'))
logger.info(' --> writing ' + clnxml)
idq.ligolw_utils.write_filename(clnxml_doc, clnxml, gz=clnxml.endswith('.gz'))
