Try ifo/search group

bin/pygrb/pycbc_grb_trig_cluster

@@ -63,7 +63,7 @@ def slice_hdf5(inputfile, outfile, include, verbose=False):
         nevents = include.size
 
     with h5py.File(inputfile, "r") as h5in:
-        ifos = [k for k in h5in.keys() if k not in ("network", "search")]
+        ifos = [k for k in h5in.keys() if k != "network"]
 
         # find which single-ifo events to keep
         ifo_index = {

bin/pygrb/pycbc_grb_trig_combiner

@@ -185,7 +185,7 @@ def merge_hdf5_files(inputfiles, outputfile, verbose=False, **compression_kw):
 
     # handle search datasets as a special case
     # (they will the same in all files)
-    search_datasets = set(filter(lambda x: "search/" in x, dataset_names))
+    search_datasets = set(filter(lambda x: "/search/" in x, dataset_names))
 
     # record where we are in the global dataset
     position = defaultdict(int)
@@ -230,7 +230,7 @@ def bin_events(inputfile, bins, outdir, filetag,
     ifotag, _, seg = filename_metadata(inputfile)
 
     with h5py.File(inputfile, "r") as h5in:
-        ifos = [k for k in h5in.keys() if k not in ("network", "search")]
+        ifos = [k for k in h5in.keys() if k != "network"]
         times = h5in[column][()]
 
         for bin_, segl in bins.items():

pycbc/events/eventmgr.py

@@ -688,10 +688,6 @@ def __setitem__(self, name, data):
         th = numpy.array(
             [p['tmplt'].template_hash for p in self.template_params])
         f = fw(outname)
-        # Write timeslides to search group
-        f.prefix = 'search'
-        for ifo in self.ifos:
-            f['time_slides_'+ifo] = self.time_slides[ifo] 
         # Output network stuff
         f.prefix = 'network'
         network_events = numpy.array(
@@ -776,6 +772,7 @@ def __setitem__(self, name, data):
                     f['chisq_dof'] = numpy.zeros(len(ifo_events))
 
                 f['template_hash'] = th[tid]
+            f['search/time_slides'] = numpy.array(self.time_slides[ifo])
             if self.opt.trig_start_time:
                 f['search/start_time'] = numpy.array([
                              self.opt.trig_start_time[ifo]], dtype=numpy.int32)

pycbc/results/pygrb_postprocessing_utils.py

@@ -619,10 +619,10 @@ def load_time_slides(hdf_file_path):
     """Loads timeslides from PyGRB output file as a dictionary"""
     hdf_file = h5py.File(hdf_file_path, 'r')
     ifos = extract_ifos(hdf_file_path)
-    ids = numpy.arange(len(hdf_file[f'search/time_slides_{ifos[0]}']))
+    ids = numpy.arange(len(hdf_file[f'{ifos[0]}/search/time_slides']))
     time_slide_dict = {
         slide_id: {
-            ifo: hdf_file[f'search/time_slides_{ifo}'][slide_id]
+            ifo: hdf_file[f'{ifo}/search/time_slides'][slide_id]
             for ifo in ifos}
         for slide_id in ids}