Updates o4c

.readthedocs.yaml

@@ -21,5 +21,5 @@ sphinx:
     configuration: doc/source/conf.py
     fail_on_warning: true
 
-formats:
-  - pdf
+#formats:
+#  - pdf

doc/source/slack.rst

@@ -5,5 +5,5 @@ Slack Posters
 
 slackbot class
 --------------------------------
-.. autoclass:: fast_response.slack_posters.slack
+.. autoclass:: fast_response.slack_posters.slack.slackbot
    :members:

fast_response/AlertFollowup.py

@@ -176,7 +176,7 @@ def write_circular(self, alert_results):
         ev_is_are = 'event is' if len(analysis_1000['coincident_events']) == 1 else 'events are'
         if not high_sig:
             if len(analysis_1000['coincident_events']) == 0:
-                coinc_and_p = ''
+                coinc_and_p = 'We report a p-value of {:.2f} in this time window. '.format(analysis_1000['p'])
             elif len(analysis_1000['coincident_events']) == 1:
                 coinc_and_p = 'We find that this additional event is well described by atmospheric\n' \
                     + 'background expectations, with a p-value of {:.2f}. '.format(analysis_1000['p'])
@@ -190,12 +190,12 @@ def write_circular(self, alert_results):
             coinc_and_p = 'We accordingly derive a p-value of {:.3f}.'.format(analysis_1000['p'])
             if analysis_1000['p'] < 0.01:
                 coinc_and_p = coinc_and_p + ' Due to the coincidences identified in this search, ' \
-                    + 'we strongly encourage followup observations.'
+                    + 'we strongly encourage followup observations. '
             else:
                 pass
             if analysis_2day['p'] < 0.01:
                 long_p_and_lim = 'In this case, we report a p-value of {:.3f}.'.format(analysis_2day['p']) \
-                    + ' Due to the coincidences identified in this search, we strongly encourage followup observations.'
+                    + ' Due to the coincidences identified in this search, we strongly encourage followup observations. '
             else:
                 long_p_and_lim = 'In this case, we report a p-value of {:.2f},'.format(analysis_2day['p']) \
                     + ' consistent with no significant \nexcess of track events. '

fast_response/FastResponseAnalysis.py

@@ -415,7 +415,7 @@ def plot_tsd(self, allow_neg=False):
                 bins = np.linspace(0., 25., 30)
 
             plt.hist(self.tsd, bins= bins, 
-                    label="Background Scrambles", density=True)
+                    label="{} Background Scrambles".format(len(self.tsd)), density=True)
             if self.ts >= -500.:
                 plt.axvline(self.ts, color = 'k', label = "Observed TS")
             else: 

fast_response/GWFollowup.py

@@ -405,8 +405,7 @@ def write_circular(self):
 
         else:
             #significance = '{:1.2f}'.format(self.significance(pvalue))
-
-            info = ' <dt>\t <ra>\t\t <dec>\t\t <angErr>\t\t\t <p_gwava>\t\t\t <p_llama>\n'
+            info = '|<dt>   |  <ra>  |  <dec>  |      <angErr>           |         <p_gwava>         |       <p_llama>        |\n'
             table = ''
             n_coincident_events=0
             for event in events:

fast_response/MonitoringAndMocks/Data_Display.py

@@ -16,16 +16,15 @@
 import subprocess, warnings
 warnings.filterwarnings('ignore', module='astropy._erfa')
 
-def dial_up(who="jessie"):
+def dial_up():
         cell_tower = "/home/jthwaites/private/"
-        # subprocess.call([cell_tower+"make_call.py", f"--{who}=True", '--troubleshoot=True'])
-        print('Calld')
+        subprocess.call([cell_tower+"make_call.py", '--troubleshoot=True'])
 
 path = os.environ.get('FAST_RESPONSE_OUTPUT')
 out_put = '/data/user/jthwaites/o4-mocks/'
 
 #Creating readable (and callable) files from ALL pickle files previously created in gw_gcn_listener
-mock_files = sorted(glob.glob(path+'/PickledMocks/*MS*.pickle'), reverse=True)[:1000]
+mock_files = sorted(glob.glob(path+'/PickledMocks/*MS*.pickle'), reverse=True)[:2000]
 
 def sort_mocks(mock_files):
     event_dict = pd.DataFrame({"Trigger_Time": [], "GCN_Alert": [], "End_Time": [],
@@ -160,7 +159,7 @@ def find_ts(i, ts_list):
 ax.plot_date(unique_days, initial, color = 'orange')
 
 now = datetime.now(timezone.utc)
-past = now + relativedelta(months=-2)
+past = now + relativedelta(months=-1)
 
 ax.set_xlim(past, now)
 ax.fmt_xdata = DateFormatter('%Y-%m-%d %H:%M:%S')
@@ -317,11 +316,11 @@ def find_ts(i, ts_list):
 ax.text(-0.1, 15, "Page Last Updated: {} UTC".format(now))
 plt.savefig('/home/mromfoe/public_html/O4_followup_monitoring/Update_Time.png')
 
-df = pd.DataFrame({"Name": ed["Name"][-15::-1],
-                    "Merger Time": ed["Trigger_Time"][-15::-1],
-                    "GCN Alert": ed["GCN_Alert"][-15::-1],
-                    "Script Finishes": ed["End_Time"][-15::-1],
-                    "Total Latency in Seconds": ed["Total_Latency"][-15::-1]})
+df = pd.DataFrame({"Name": ed["Name"][:15],
+                    "Merger Time": ed["Trigger_Time"][:15],
+                    "GCN Alert": ed["GCN_Alert"][:15],
+                    "Script Finishes": ed["End_Time"][:15],
+                    "Total Latency in Seconds": ed["Total_Latency"][:15]})
 html1 = df.to_html()
 
 text_file1 = open("/home/mromfoe/public_html/O4_followup_monitoring/Recent_Runs.html", "w")
@@ -391,8 +390,8 @@ def make_bg_pval_dist(fontsize=15, lower_y_bound=-3.5, load_all=False):
     #uniform_bins=np.logspace(lower_y_bound,0.,int(abs(lower_y_bound*7))+1) #evenly spaced bins in logspace
     #plt.step(uniform_bins[1:], np.diff(uniform_bins), label = 'Uniform p-value expectation', lw = 3.)
     plt.step(p_x_vals[1:], np.diff(p_x_vals), label = 'Uniform p-value distribution', lw = 3.)
-    plt.plot([0.1,0.1], [10**lower_y_bound, 1e0],linestyle='dotted', label=f'{lt_10per*100.:.2f} \% of p-values $<$ 0.1')
-    plt.plot([0.01, 0.01], [10**lower_y_bound, 1e0], linestyle='dashed',label=f'{lt_1per*100.:.2f} \% of p-values $<$ 0.01')
+    plt.plot([0.1,0.1], [10**lower_y_bound, 1e0],linestyle='dotted', label=f'{lt_10per*100.:.2f}% of p-values $<$ 0.1')
+    plt.plot([0.01, 0.01], [10**lower_y_bound, 1e0], linestyle='dashed',label=f'{lt_1per*100.:.2f}% of p-values $<$ 0.01')
 
     plt.xscale('log')
     plt.yscale('log')

fast_response/circular_templates/gw_gcn_template_high.txt

@@ -36,10 +36,11 @@ Properties of the coincident events are shown below.
 ...
 
 where:
-dt = Time of track event minus time of GW trigger (sec)
+dt = Time of track event minus time of GW trigger (sec).
 Angular uncertainty = Angular uncertainty of track event: the radius of a circle 
      representing 90% CL containment by area.
-p-value = the p-value for this specific track event from each search.
+p-value = the p-value for this specific track event from each search. 
+     Event p-values are provided when the per-event p-value is less than 0.1 in either search.
 
 The IceCube Neutrino Observatory is a cubic-kilometer neutrino detector operating at the 
 geographic South Pole, Antarctica. The IceCube realtime alert point of contact can be 

fast_response/circular_templates/gw_gcn_template_low.txt

@@ -12,10 +12,10 @@ During this time period IceCube was collecting good quality data.
 No significant track-like events are found in spatial coincidence of
 <name> calculated from the map circulated in the <noticeID> notice.
 
-IceCube's sensitivity assuming an E^-2 spectrum (E^2 dN/dE) to neutrino
-point sources within the locations spanned by the 90% spatial containment
-of <name> ranges from <lowSens> to <highSens> GeV cm^-2 in a 1000 second
-time window.
+IceCube’s sensitivity to neutrino point sources with an E^-2 spectrum, 
+expressed as E^2 dN/dE evaluated at 1 TeV, ranges from <lowSens> to <highSens> GeV cm^-2 
+within the 90% spatial containment region of <name> in a 1000 second 
+time window. 
 
 The IceCube Neutrino Observatory is a cubic-kilometer neutrino detector
 operating at the geographic South Pole, Antarctica. The IceCube realtime

fast_response/circular_templates/internal_followup.txt

@@ -4,14 +4,14 @@ The IceCube Collaboration (http://icecube.wisc.edu/) reports:
 
 IceCube has performed a search [1] for additional track-like muon neutrino events arriving from the direction of <alert_name> (<gcn_number>)
 in a time range of 1000 seconds centered on the alert event time (<start_utc> UTC to <stop_utc> UTC) during which IceCube was collecting good quality data. Excluding the event 
-that prompted the alert, <n_events> track-like <events_is_are> found within the 90% containment region of <alert_name>.<coincident_events_and_p_str>
-The IceCube sensitivity to neutrino point sources with an E^-2.5 spectrum (E^2 dN/dE at 1 TeV) within the locations spanned by the 90% spatial containment region of <alert_name> <short_sens_range> GeV cm^-2 in a 1000 second
+that prompted the alert, <n_events> track-like <events_is_are> found within the 90% containment region of <alert_name>. <coincident_events_and_p_str> 
+IceCube’s sensitivity to neutrino point sources with an E^-2.5 spectrum, expressed as E^2 dN/dE evaluated at 1 TeV, <short_sens_range> GeV cm^-2 within the 90% spatial containment region of <alert_name> in a 1000 second 
 time window. 90% of events IceCube would detect from a source at this declination 
 with an E^-2.5 spectrum have energies in the approximate energy range between <low_en> GeV and <high_en> GeV. 
 
 A subsequent search was performed including 2 days of data centered on the alert event time (<long_start_utc> UTC to <long_stop_utc> UTC). 
-<long_p_and_lim> The IceCube sensitivity to neutrino point sources with an E^-2.5 spectrum (E^2 dN/dE at 1 TeV) within the locations spanned by the 90%
-spatial containment region of <alert_name> <long_sens_range> GeV cm^-2 in a 2 day time window. 
+<long_p_and_lim> IceCube’s sensitivity to neutrino point sources with an E^-2.5 spectrum, expressed as E^2 dN/dE evaluated at 1 TeV, <long_sens_range> GeV cm^-2 within the 90% spatial containment region of <alert_name> in a 2 day
+time window. 
 
 The IceCube Neutrino Observatory is a cubic-kilometer neutrino detector operating at the geographic South Pole, Antarctica. The IceCube realtime alert point of contact can 
 be reached at roc@icecube.wisc.edu.

fast_response/listeners/gw_gcn_listener.py

@@ -78,7 +78,7 @@ def process_gcn(payload, root):
 
     if root.attrib['role']=='observation' and not mock:
         ## Call everyone because it's a real event!
-        call_command=['/home/jthwaites/private/make_call.py']
+        call_command=['/home/jthwaites/private/make_call.py', f'--name={name}']
 
         call_args = ['--justin']
         for arg in call_args:

fast_response/reports/ReportGenerator.py

@@ -231,7 +231,7 @@ def make_coinc_events_table(self, f):
                 for event in self.analysis.coincident_events:
                     event_table+=[
                         ("Run:Event",'{}:{}'.format(event['run'], event['event'])),
-                        ("Time","{}".format(
+                        ("Time (MJD)","{}".format(
                             event['time'])),
                         (r'$\alpha$, $\delta$',"{:3.2f}\degree, {:+3.2f}\degree"
                             .format(np.rad2deg(event['ra']), np.rad2deg(event['dec']))),

fast_response/scripts/combine_results_kafka.py

@@ -187,7 +187,7 @@ def parse_notice(record, wait_for_llama=False, heartbeat=False):
         if int(params['Significant'])==0: 
             subthreshold=True
             logger.warning('low-significance alert found. ')
-    if params['Group'] == 'Burst' or params["Pipeline"] =='CWB':
+    if params['Group'] == 'Burst' or params["Pipeline"] =='CWB' or params["Pipeline"]=='aframe':
         wait_for_llama = False
         m = 'Significant' if not subthreshold else 'Subthreshold'
         logger.warning('{} burst or CWB alert found. '.format(m))
@@ -293,7 +293,8 @@ def parse_notice(record, wait_for_llama=False, heartbeat=False):
                         if record.attrib['role']=='observation' and not heartbeat:
                             try: 
                                 subprocess.call(['/home/jthwaites/private/make_call.py', 
-                                                 '--troubleshoot_gcn=True', '--missing_llama=True'])
+                                                 '--troubleshoot_gcn=True', '--missing_llama=True',
+                                                 f'--name={name}'])
                             except:
                                 logger.warning('Failed to send alert to shifters: Issue finding LLAMA results. ')
                     if llama_results_finished:
@@ -302,7 +303,8 @@ def parse_notice(record, wait_for_llama=False, heartbeat=False):
                         if record.attrib['role']=='observation' and not heartbeat:
                             try: 
                                 subprocess.call(['/home/jthwaites/private/make_call.py', 
-                                                 '--troubleshoot_gcn=True', '--missing_uml=True'])
+                                                 '--troubleshoot_gcn=True', '--missing_uml=True',
+                                                 f'--name={name}'])
                             except:
                                 logger.warning('Failed to send alert to shifters: Issue finding UML results. ')
                 else:
@@ -311,7 +313,8 @@ def parse_notice(record, wait_for_llama=False, heartbeat=False):
 
                     if record.attrib['role']=='observation' and not heartbeat:
                         err_msg = ['/home/jthwaites/private/make_call.py', '--troubleshoot_gcn=True', 
-                                   '--missing_llama=True']
+                                   '--missing_llama=True',
+                                   f'--name={name}']
                         if not subthreshold: err_msg.append('--missing_uml=True')
 
                         try: 

fast_response/slack_posters/slack.py

@@ -15,7 +15,7 @@ class slackbot(object):
     Parameters
     ----------
     channel: str
-        Channel name to use in message
+        Channel name to post message
     """
 
     def __init__(self, channel_name):
@@ -33,8 +33,8 @@ def get_chan_id(self, channel_name):
 
         Parameters
         ----------
-        channel: str
-            Channel name
+        channel_name: str
+            Name of the channel to send to
         """
 
         chan_ids={}