Further thoughts and suggestions

bin/minifollowups/pycbc_injection_minifollowup

@@ -34,34 +34,33 @@ from pycbc.workflow.core import resolve_url_to_file
 from pycbc.io.hdf import SingleDetTriggers, HFile
 
 
-def sort_injections(args, inj_group, missed, sort_by):
-    """Return an array of indices to sort the missed injections according to a
-    metric of choice.
+def sort_injections(args, inj_group, missed):
+    """Return an array of indices to sort the missed injections from most to
+    least likely to be detected, according to a metric of choice.
 
     Parameters
     ----------
     args : object
-        CLI arguments parsed by argparse.
+        CLI arguments parsed by argparse. Must have a `distance_type` attribute
+        to specify how to sort.
     inj_group : h5py group object
         HDF5 group object containing the injection definition.
     missed : array
         Array of indices of missed injections into `inj_group`.
-    sort_by : str
-        Which metric to sort by.
 
     Returns
     -------
     missed_sorted : array
         Array of indices of missed injections sorted as requested.
     """
-    if 'optimal_snr' in sort_by:
+    if 'optimal_snr' in args.distance_type:
         optimal_snrs = [
             inj_group[dsn][:][missed] for dsn in inj_group.keys()
             if dsn.startswith('optimal_snr_')
         ]
         assert optimal_snrs, 'These injections do not have optimal SNRs'
 
-    if sort_by == 'decisive_optimal_snr':
+    if args.distance_type == 'decisive_optimal_snr':
         # descending order of decisive (2nd largest) optimal SNR
         dec_snr = numpy.array([
             sorted(snrs)[-2] for snrs in zip(*optimal_snrs)
@@ -72,14 +71,14 @@ def sort_injections(args, inj_group, missed, sort_by):
         sorter = dec_snr.argsort()[::-1]
         return missed[sorter]
 
-    if sort_by == 'network_optimal_snr':
+    if args.distance_type == 'comb_optimal_snr':
         # descending order of network optimal SNR
         optimal_snrs = numpy.vstack(optimal_snrs)
         net_opt_snrs_squared = (optimal_snrs ** 2).sum(axis=0)
         sorter = net_opt_snrs_squared.argsort()[::-1]
         return missed[sorter]
 
-    if sort_by == 'decisive_eff_dist':
+    if args.distance_type == 'dec_chirp_distance':
         # ascending order of decisive (2nd smallest) chirp distance
         from pycbc.conversions import mchirp_from_mass1_mass2, chirp_distance
 
@@ -103,7 +102,7 @@ def sort_injections(args, inj_group, missed, sort_by):
         sorter = dec_chirp_dist.argsort()
         return missed[sorter]
 
-    raise ValueError(f'Invalid injection sorting method "{sort_by}"')
+    raise ValueError(f'Invalid injection sorting method "{args.distance_type}"')
 
 
 parser = argparse.ArgumentParser(description=__doc__)
@@ -136,6 +135,10 @@ parser.add_argument('--nearby-triggers-window', type=float, default=0.05,
                     help="Maximum time difference between the missed "
                          "injection and the loudest SNR nearby trigger to "
                          "display, seconds. Default=0.05")
+parser.add_argument('--distance-type',
+                    required=True,
+                    help="How to sort missed injections from most to least "
+                         "likely to be detected")
 wf.add_workflow_command_line_group(parser)
 wf.add_workflow_settings_cli(parser, include_subdax_opts=True)
 args = parser.parse_args()
@@ -246,12 +249,7 @@ if len(missed) < num_events:
     num_events = len(missed)
 
 # sort the injections
-sort_by = workflow.cp.get_opt_tags(
-    'workflow-injection_minifollowups',
-    'sort-by',
-    ''
-)
-missed = sort_injections(args, inj_def, missed, sort_by)
+missed = sort_injections(args, inj_def, missed)
 
 # loop over sorted missed injections to be followed up
 found_inj_idxes = f['found_after_vetoes/injection_index'][:]

examples/search/plotting.ini

@@ -14,7 +14,6 @@ section-header = all
 [workflow-injection_minifollowups]
 num-events=1
 subsection-suffix=with_ifar_lt_1_year
-sort-by=decisive_optimal_snr
 
 [foreground_minifollowup]
 [foreground_minifollowup-foreground]
@@ -36,6 +35,9 @@ non-coinc-time-only =
 [injection_minifollowup]
 ifar-threshold = 1
 
+[injection_minifollowup&plot_foundmissed-sub_mchirp_grad&plot_foundmissed-all_mchirp_grad&plot_foundmissed-summary]
+distance-type = comb_optimal_snr
+
 [page_snglinfo]
 ranking-statistic = single_ranking_only
 sngl-ranking = newsnr_sgveto_psdvar
@@ -140,14 +142,12 @@ log-dist =
 far-type = exclusive
 
 [plot_foundmissed-sub_mchirp_grad&plot_foundmissed-all_mchirp_grad&plot_foundmissed-summary]
-distance-type = comb_optimal_snr
 axis-type = mchirp
 log-x =
 log-distance =
 gradient-far =
 
 [plot_foundmissed-sub_mchirp_gradm&plot_foundmissed-all_mchirp_gradm&plot_foundmissed-summarym]
-distance-type = comb_optimal_snr
 axis-type = mchirp
 log-x =
 log-distance =