Support more and less sophisticated approaches to read the confirmed …

…trip count

This now supports both the leaderboard branch and the main branches.
If we have computeConfirmed, we use it.
If we don't have it, we just read the number of trips that are unlabeled. Note
that this does not take into account the high confidence label assist trips, so
it is only approximate, and should be handled better once we improve the
accuracy of label assist.

#873 (comment)

```
./e-mission-py.bash bin/monitor/check_participant_status.py
storage not configured, falling back to sample, default configuration
URL not formatted, defaulting to "Stage_database"
Connecting to database URL localhost:27017
False    4
Name: user_input, dtype: int64
For test_jun_20: Trip count = 6, location count = 285, first trip = 2016-06-20T08:41:15.856000-07:00, last trip = 2016-06-20T17:12:39.767000-07:00, confirmed_pct (2016-05-25T00:00:00+00:00 -> 2016-06-25T00:00:00+00:00) = exactly 66.67
```

```
./e-mission-py.bash bin/monitor/check_participant_status.py
storage not configured, falling back to sample, default configuration
URL not formatted, defaulting to "Stage_database"
Connecting to database URL localhost
For test_jun_20: Trip count = 6, location count = 285, first trip = 2016-06-20T08:41:15.856000-07:00, last trip = 2016-06-20T17:12:39.767000-07:00, confirmed_pct  = approximately 0.67
```

bin/monitor/check_participant_status.py

@@ -13,5 +13,10 @@
     now = arrow.now()
     month_ago = now.shift(months=-1)
     last_month_tq = estt.TimeQuery("data.start_ts", month_ago.timestamp, now.timestamp)
-    confirmed_pct, valid_replacement_pct, score = ecwu.User.computeConfirmed(ue["uuid"], last_month_tq)
-    print(f"For {ue['user_email']}: Trip count = {trip_count}, location count = {location_count}, first trip = {first_trip_time}, last trip = {last_trip_time}, confirmed_pct ({month_ago} -> {now}) = {confirmed_pct:.2f}")
+    if 'computeConfirmed' in vars(ecwu.User):
+        confirmed_pct, valid_replacement_pct, score = ecwu.User.computeConfirmed(ue["uuid"], last_month_tq)
+        print(f"For {ue['user_email']}: Trip count = {trip_count}, location count = {location_count}, first trip = {first_trip_time}, last trip = {last_trip_time}, confirmed_pct ({month_ago} -> {now}) = exactly {confirmed_pct:.2f}")
+    else:
+        confirmed_count = edb.get_analysis_timeseries_db().count_documents({"user_id": ue["uuid"], "metadata.key": "analysis/confirmed_trip", "data.user_input": {"$ne": {}}})
+        confirmed_pct = confirmed_count / trip_count
+        print(f"For {ue['user_email']}: Trip count = {trip_count}, location count = {location_count}, first trip = {first_trip_time}, last trip = {last_trip_time}, confirmed_pct  = approximately {confirmed_pct:.2f}")