#mainidqdir = config.get('general', 'idqdir') ### get the main directory where idq pipeline is going to be running. ifo = config.get('general', 'ifo') usertag = config.get('general', 'usertag') if usertag: usertag = "_%s" % usertag #======================== # 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()) #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 #========================
config = ConfigParser.SafeConfigParser() config.read(opts.config_file) mainidqdir = config.get('general', 'idqdir') ### get the main directory where idq pipeline is going to be running. usertag = config.get('general', 'usertag') ifo = config.get('general', 'ifo') #======================== # which classifiers #======================== ### ensure we have a section for each classifier and fill out dictionary of options classifiersD, mla, ovl = idq.config_to_classifiersD( config ) combinersD, _ = idq.config_to_combinersD( config ) classifiers = sorted(classifiersD.keys() + combinersD.keys()) ### check that all requested classifiers exist... for classifier in opts.classifier: if classifier not in classifiers: logger.info('WARNING: %s not present in config file : %s. skipping...'%(classifier, opts.config_file)) opts.classifier.remove(classifier) opts.classifier = sorted(list(set(opts.classifier))) ### check that FAPthrs make sense opts.FAPthr = [FAPthr for FAPthr in opts.FAPthr if (FAPthr >=0) and (FAPthr <= 1)] opts.FAPthr = sorted(list(set(opts.FAPthr)))
#mainidqdir = config.get('general', 'idqdir') ### get the main directory where idq pipeline is going to be running. ifo = config.get('general', 'ifo') usertag = config.get('general', 'usertag') if usertag: usertag = "_%s"%usertag #======================== # 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()) #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 #========================
config.read(opts.config_file) mainidqdir = config.get( 'general', 'idqdir' ) ### get the main directory where idq pipeline is going to be running. usertag = config.get('general', 'usertag') ifo = config.get('general', 'ifo') #======================== # which classifiers #======================== ### ensure we have a section for each classifier and fill out dictionary of options classifiersD, mla, ovl = idq.config_to_classifiersD(config) combinersD, _ = idq.config_to_combinersD(config) classifiers = sorted(classifiersD.keys() + combinersD.keys()) ### check that all requested classifiers exist... for classifier in opts.classifier: if classifier not in classifiers: logger.info( 'WARNING: %s not present in config file : %s. skipping...' % (classifier, opts.config_file)) opts.classifier.remove(classifier) opts.classifier = sorted(list(set(opts.classifier))) ### check that FAPthrs make sense opts.FAPthr = [ FAPthr for FAPthr in opts.FAPthr if (FAPthr >= 0) and (FAPthr <= 1)