Change shift summary plot to look at lockloss by hour

locklost/summary.py

@@ -32,15 +32,13 @@ def grab_data(gps):
     """
     shift_times = {
         'H1': [np.arange(0, 8), np.arange(8, 16), np.arange(16, 24)],
-        'L1': [np.concatenate(([23], np.arange(0, 8))), np.arange(8, 12), np.arange(12, 22)]
+        'L1': [np.concatenate(([22, 23], np.arange(0, 8))), np.arange(8, 12), np.arange(12, 22)]
     }
     shift_names = ['owl', 'day', 'eve']
-    shifts = {
-        shift_names[x]: {
-            'time': shift_times[config.IFO][x],
-            'counts': 0
-        } for x in range(3)
-    }
+    shifts = defaultdict(lambda: defaultdict(int))
+    for x in range(3):
+        for time in shift_times[config.IFO][x]:
+            shifts[shift_names[x]][time] = 0
     transitions = defaultdict(int)
     observe_durations = []
     saturations = {
@@ -102,18 +100,18 @@ def check_tags(event, tags, tag_count):
 
 
 def check_shift(event, shifts):
-    """Checks which operating shift event happened during.
+    """Checks which operating shift and hour event happened during.
 
-    Checks which operator shift the lockloss gps happened during and increments
-    a counter for that shift (for locklosses from Observe).
+    Checks which operator shift and hour the lockloss gps happened during and
+    increments a counter for that hour (for locklosses from Observe).
     """
     if not event.has_tag('OBSERVE'):
         return shifts
     gt = gpstime.fromgps(event.gps)
     gt = gt.astimezone(local_tz)
-    for key in shifts:
-        if gt.hour in shifts[key]['time']:
-            shifts[key]['counts'] += 1
+    for shift_name in shifts:
+        if gt.hour in shifts[shift_name]:
+            shifts[shift_name][gt.hour] += 1
             break
     return shifts
 
@@ -280,26 +278,34 @@ def plot_summary(path, epoch):
         fig.savefig(outpath_plot, bbox_inches='tight')
         plt.close()
 
-    # Lockloss shift plot
-    counts = [x['counts'] for x in shifts.values()]
-    shifts = shifts.keys()
+    # Lockloss shift hour plot
+    colors = ['#1f77b4', '#dbcb2b', '#b41f2d']
+    times = []
+    counts =[]
+    shift_total = []
+    for shift_name in shifts:
+        times.append(shifts[shift_name].keys())
+        counts.append(shifts[shift_name].values())
+        shift_total.append(sum(shifts[shift_name].values()))
     fig, ax = plt.subplots(1, figsize=(22, 16))
-    shift_x = np.array([0, 1, 2])
-    ax.bar(
-        shift_x,
-        counts,
+    for time, count, shift, total, color in zip(times, counts, shifts.keys(), shift_total, colors):
+        ax.bar(
+        time,
+        count,
+        color=color,
+        label='{} total count: {}'.format(shift.upper(), total),
         align='center',
     )
-    ax.set_xlabel('Operating shift', labelpad=10)
+    ax.set_xlabel('Hour lockloss occurred ({})'.format(local_tz.zone), labelpad=10)
     ax.set_ylabel('Number of locklosses')
-    ax.set_title('Number of locklosses per shift: %s' % (epoch))
-    ax.set_xticks(shift_x)
-    ax.set_xticklabels(shifts, rotation=45, ha='right')
-    ax.set_xlim([-1, shift_x.size])
+    ax.set_title('Number of locklosses from observing by hour: {}'.format(epoch))
+    ax.set_xlim([-0.9, 23.9])
+    ax.grid()
+    plt.legend(loc='upper left')
     plt.gcf().text(0.02, 0.02, "Created: {}".format(gpsnow()), fontsize=16)
     fig.tight_layout()
 
-    outpath_plot = os.path.join(epoch_path, 'Lockloss_by_shift')
+    outpath_plot = os.path.join(epoch_path, 'Lockloss_by_hour')
     fig.savefig(outpath_plot, bbox_inches='tight')
     plt.close()