Class Summaries

source code

This class stores information about the foreground and background in a 
database for making calculation of uncombined fars and combined fars quick 
and efficient.

bkg_stats groups triggers by experiment_id, ifos, and param_group 
(param_group is an arbitrary integer representing the param bin, e.g., 
mchirp [3.48,7.4), to which a trigger belongs; if no binning is done, then
it is 0 for all triggers). It stores ALL the triggers in all the time 
slides (except zero-lag) within that group.

sngl_slide_stats groups triggers by experiment_id, experiment_summ_id, ifos, and 
param_group. It therefore groups all triggers within each time slide 
separately. It is used to subtract triggers within the same slide when calculating
uncombined fars for the background. Therefore, it only stores slide triggers;
for any zero-lag datatype sngl_slide_stats is just an empty list.

datatypes maps the list of datatypes for an experiment to the corresponding
experiment_summ_ids:
datatypes[experiment_id][datatype] = [esid1, esid2, etc.]

frg_durs stores the duration for each experiment_summ_id. Its keys are 
[experiment_id][experimen_summ_id].

bkg_durs stores the background duration for each time-slide and zero-lag, 
i.e., for each experiment_summ_id. This is the sum of all other slide
datatypes sharing the same experiment_id except for the given slide. 

max_bkg_fars stores the maximum background fars of all the categories 
within each time slide. It's keys are (experiment_summ_id, ifo_group). 
The maximum background far is just the total number of triggers within a 
category divided by the background duration for that time slide.
If opts.combine_fars is set to across_all a category is defined by the 
param bin in which a trigger exists and the ifos that took part in the 
trigger. So, if there are three param bins and we've excluded H2,L1 triggers 
in H1,H2,L1 time, then there are 6 categories for H1,H2,L1 time: three param
bins each for H1,L1 and H1,H2,L1 coincident triggrs. Thus, ifo_group will 
be set to "ALL_IFOS" and there will be 6 max_bkg_fars stored for each 
experiment_summ_id in triple time.
If opts.combine_fars is set to across_param_only, then a category is 
defined only by the param bins; ifo coincidences are treated as 
separate experiments. Thus, ifo_group will be set to whatever
coinc. trigger we are considering and there will only be 3 max_bkg_fars 
stored for that entry.

zero_lag_ids stores the esid of all zero-lag "slides" of an experiment.
    zero_lag_ids[ experiment_id ] = [experiment_summ_id1, experiment_summ_id2, etc.]