@SuppressWarnings("unchecked")
@ApiMethod(name = "insertRecords", path = "findmytrain/v1/insertRecords")
public void insertRecords(Record record) {
// this method is used to add the timestamp of the server to the record
// object
// and then the object is persisted
// duplicate testing is not done here since there is no way of having
// duplicate entries here
// changed code: record timestamp from string to long
// Date date = new Date();
// String timeStamp = Long.toString(date.getTime());
record.setTimeStamp(new Date().getTime());
PersistenceManager pm = PMF.get().getPersistenceManager();
try {
pm.makePersistent(record);
} finally {
pm.close();
}
}
@SuppressWarnings("unchecked")
@ApiMethod(name = "checkTrainAndStationStatus", path = "findmytrain/v1/checkStatus")
public List<String> checkTrainAndStationStatus(
@Named("Train id") String id, @Named("Currnet Station") String station) {
// this method returns the list of stations for a selected train and
// whether that train has passed each station
final int STATION_GAP = 5; // five station from the current station to
// both directions are considered for the
// calculation
final int RECORD_THRESHOLD = 10;
final double PROBABILITY_THRESHOLD_LEFT = 0.65;
final double PROBABILITY_THRESHOLD_NOT_LEFT = 0.35;
final double TRANSITION_THRESHOLD = 0.2;
final int RECORD_CONSIDERATION_LIMIT_NUMBER = 50;
final int RECORD_CONSIDERATION_LIMIT_MINUTES = 30; // this value can be
// reduced when the
// number of users
// become
// higher.(since
// there will be
// more data to
// analyze with in
// the given time
// period)
final long ONE_MINUTE_IN_MILLIS = 60000;
List<String> result = new ArrayList<String>();
List<Train> trains = new ArrayList<Train>();
List<Record> records = new ArrayList<Record>();
PersistenceManager pm = PMF.get().getPersistenceManager();
Query queryTrain = pm.newQuery(Train.class);
queryTrain.setFilter("trainid == argTrainId");
queryTrain.declareParameters("String argTrainId");
Query queryRecord = pm.newQuery(Record.class);
queryTrain.setFilter("trainid == argTrainId");
queryTrain.declareParameters("String argTrainId");
trains = (List<Train>) queryTrain.execute(id);
records = (List<Record>) queryRecord.execute(id);
List<Stop> stops = new ArrayList<Stop>();
List<Record> tempRecords;
int stationIndex = 0;
int initialOneCount;
int initialZeroCount;
double probabilityInitial;
double probabilityTransition;
int[] centralDifference;
int transitionCount;
Date atRequest = new Date();
SimpleDateFormat parser = new SimpleDateFormat("HH:mm");
String serverTime = parser.format(atRequest);
Date serverDate = null;
Date lowerLimit = null;
try {
serverDate = parser.parse(serverTime);
lowerLimit =
new Date(
serverDate.getTime() - (RECORD_CONSIDERATION_LIMIT_MINUTES * ONE_MINUTE_IN_MILLIS));
} catch (ParseException e) {
e.printStackTrace();
}
stops = trains.get(0).getStops();
for (int i = 0; i < stops.size(); i++) {
if (stops.get(i).getStation().equals(station)) stationIndex = i;
}
int loopStart = stationIndex >= STATION_GAP ? stationIndex - STATION_GAP : 0;
int loopEnd =
stationIndex + STATION_GAP < stops.size() ? stationIndex + STATION_GAP : stops.size();
for (int i = loopStart; i < loopEnd; i++) {
Stop tempStop = stops.get(i);
String tempStatus = "not sure"; // for the situation where there are
// not enough data present
tempRecords = new ArrayList<Record>(); // these are the records used
// to process the data for
// each selected station
initialOneCount = 0;
initialZeroCount = 0;
for (Record r : records) {
if (r.getStation().equals(tempStop.getStation())) {
tempRecords.add(r);
}
}
// case where there is no data
if (tempRecords.size() < RECORD_THRESHOLD) {
result.add(tempStop.getStation() + ":" + tempStatus);
continue;
}
// when there is enough data
sortRecords(tempRecords);
// selecting a set of record to perform the analysis based on their
// recentness and the number of records
int k = 0;
for (int j = 0; j < tempRecords.size(); j++) {
Date tempDate = new Date(tempRecords.get(j).getTimeStamp());
String tempTime = parser.format(tempDate);
try {
Date recordDate = parser.parse(tempTime);
if (recordDate.after(lowerLimit)) {
k = j;
break;
}
} catch (ParseException e) {
e.printStackTrace();
}
}
if (tempRecords.size() - k < RECORD_CONSIDERATION_LIMIT_NUMBER) {
if (tempRecords.size() < RECORD_CONSIDERATION_LIMIT_NUMBER) {
k = 0;
} else k = tempRecords.size() - RECORD_CONSIDERATION_LIMIT_NUMBER;
}
for (int j = k; j < tempRecords.size(); j++) {
// counting the initial ones and zeros
System.out.print(j + " ");
if (tempRecords.get(j).getStatus() == 1) initialOneCount++;
else initialZeroCount++;
}
System.out.println();
probabilityInitial = (double) initialOneCount / (tempRecords.size());
if (probabilityInitial > PROBABILITY_THRESHOLD_LEFT) {
tempStatus = "left";
} else if (probabilityInitial < PROBABILITY_THRESHOLD_NOT_LEFT) {
tempStatus = "not left";
} else {
// using the first central difference formula
centralDifference = new int[tempRecords.size() - 1];
for (int j = 1; j < tempRecords.size(); j++) {
centralDifference[j - 1] =
tempRecords.get(j).getStatus() - tempRecords.get(j - 1).getStatus();
}
transitionCount = 0;
for (int j : centralDifference) {
if (j == 1) transitionCount++;
}
probabilityTransition = (double) transitionCount / centralDifference.length;
if (probabilityTransition < TRANSITION_THRESHOLD) {
tempStatus = "left";
} else {
tempStatus = "not sure";
}
}
// at this point data can be further checked to refine the results
result.add(tempStop.getStation() + ":" + tempStatus);
}
return result;
}
