Include Run ID in Geomean graphs

The logic for displaying the Run ID in the per-point metadata already
exists since it is already done for normal data points, so extend the
existing Geomean query to also include this information.

Since the Run ID information is now always present, additionally remove
several if-conditions that were previously used to handle it being
missing.

Change-Id: Iaa3406553286c5a4dc697a279559a14d482da926

Author: georges-arm

lnt/server/ui/views.py

@@ -997,30 +997,31 @@ def load_geomean_data(field, machine, limit, xaxis_date, revision_cache=None):
     ts = request.get_testsuite()
     values = session.query(sqlalchemy.sql.func.min(field.column),
                            ts.Order,
-                           sqlalchemy.sql.func.min(ts.Run.start_time)) \
+                           ts.Run.start_time,
+                           ts.Run.id) \
                     .filter(ts.Run.order_id == ts.Order.id) \
                     .filter(ts.Run.id == ts.Sample.run_id) \
                     .filter(ts.Test.id == ts.Sample.test_id) \
                     .filter(ts.Run.machine_id == machine.id) \
                     .filter(field.column.isnot(None)) \
-                    .group_by(ts.Order.llvm_project_revision, ts.Test, ts.Order.id)
+                    .group_by(ts.Order.llvm_project_revision, ts.Test, ts.Order.id, ts.Run.id)
 
     if limit:
         values = values.limit(limit)
 
     data = multidict.multidict(
-        ((order, date), val)
-        for val, order, date in values).items()
+        ((order, date, run_id), val)
+        for val, order, date, run_id in values).items()
 
     # Calculate geomean of each revision.
     if xaxis_date:
-        data = [(date, [(calc_geomean(vals), order, date)])
-                for ((order, date), vals) in data]
+        data = [(date, [(calc_geomean(vals), order, date, run_id)])
+                for ((order, date, run_id), vals) in data]
         # Sort data points according to date.
         data.sort(key=lambda sample: sample[0])
     else:
-        data = [(order.llvm_project_revision, [(calc_geomean(vals), order, date)])
-                for ((order, date), vals) in data]
+        data = [(order.llvm_project_revision, [(calc_geomean(vals), order, date, run_id)])
+                for ((order, date, run_id), vals) in data]
         # Sort data points according to order (revision).
         data.sort(key=lambda sample: convert_revision(sample[0], cache=revision_cache))
 
@@ -1235,7 +1236,7 @@ def trace_group(test_name, field_name, machine):
             # And the date on which they were taken.
             dates = [data_array[2] for data_array in datapoints]
             # Run ID where this point was collected.
-            run_ids = [data_array[3] for data_array in datapoints if len(data_array) == 4]
+            run_ids = [data_array[3] for data_array in datapoints]
 
             values = [v * normalize_by for v in values]
 
@@ -1260,20 +1261,17 @@ def trace_group(test_name, field_name, machine):
             # Generate point metadata.
             point_metadata = {"order": orders[agg_index].as_ordered_string(),
                               "orderID": orders[agg_index].id,
-                              "date": str(dates[agg_index])}
-            if run_ids:
-                point_metadata["runID"] = str(run_ids[agg_index])
-
+                              "date": str(dates[agg_index]),
+                              "runID": str(run_ids[agg_index])}
             meta.append(point_metadata)
 
             # Add the multisample points, if requested.
             if not hide_all_points and is_multisample:
                 for i, v in enumerate(values):
                     multisample_metadata = {"order": orders[i].as_ordered_string(),
                                             "orderID": orders[i].id,
-                                            "date": str(dates[i])}
-                    if run_ids:
-                        multisample_metadata["runID"] = str(run_ids[i])
+                                            "date": str(dates[i]),
+                                            "runID": str(run_ids[i])}
                     multisample_points_data["x"].append(point_label)
                     multisample_points_data["y"].append(v)
                     multisample_points_data["meta"].append(multisample_metadata)