HIGH_PROFILE label for RRT

gwcelery/tasks/rrt_utils.py

+
+from . import gracedb
+
+import json
+import tempfile
+
+from ligo.skymap.io import read_sky_map
+from ligo.skymap.postprocess.crossmatch import crossmatch
+
+
+
+def high_profile_label(em_bright,
+                       pastro,
+                       skymap,
+                       superevent):
+    
+    superevent_id = superevent['superevent_id']
+    # condition 1
+    if 'RAVEN_ALERT' in superevent['labels']:
+        ## code to apply the HIGH PROFILE
+        # Satisfies condition 1 
+        gracedb.create_label.si('HIGH_PROFILE', superevent_id)
+    
+    #condition 2
+    far_dict = {}
+    gw_events = superevent["gw_events"]
+    for events in gw_events:
+        events_dict = gracedb.get_event._orig_run(events).json()
+        far_dict[events_dict["group"]] = events_dict["far"]
+    # search for lowest far
+    if min(far_dict, key=far_dict.get) is "Burst":
+        ## code to apply HIGH PROFILE
+        # Satisfies condition 2
+        gracedb.create_label.si('HIGH_PROFILE', superevent_id)
+
+    # condition 3
+    
+    em_bright_dict = json.loads(em_bright)
+    has_remnant = em_bright_dict['HasRemnant']
+
+    pastro_dict = json.loads(pastro)
+    p_bns = pastro_dict['BNS']
+    p_terr = pastro_dict['Terrestrial']
+    p_nsbh = pastro_dict['NSBH']
+
+    with tempfile.NamedTemporaryFile(content=skymap) as skymap_file:
+      gw_skymap = read_sky_map(skymap_file, moc=True)
+      cl = 90
+      result = crossmatch(gw_skymap, contours=[cl / 100])
+      greedy_area = result.contour_areas[0]