//private long AddGeneratedActivity(EventCluster ec, int eventCount, DataTable photos)
private long AddGeneratedActivity(EventCluster ec, int eventCount, string genedName)
{
Activity act = new Activity();
//DataRow p1 = photos.Rows[ec.ecIndex1];
//string[] parts1 = p1["dateTaken"].ToString().Split('^');
//DataRow p2 = photos.Rows[ec.ecIndex2];
//string[] parts2 = p2["dateTaken"].ToString().Split('^');
act.ActivityKind = "Generated";
//act.EndDate = (DateTime)p2["dateTaken"];
act.EndDate = ec.endTime;
act.Source = "LinearClusterIndexer";
act.SourceId = genedName + eventCount.ToString();
act.ActivityName = genedName + eventCount.ToString();
act.Latitude = 0;
act.Longitude = 0;
TimePeriod tpStart = new TimePeriod();
tpStart.Year = (short)act.StartDate.Year;
tpStart.Month = (short)act.StartDate.Month;
tpStart.Hour = (short)act.StartDate.Hour;
tpStart.Day = act.StartDate.DayOfWeek.ToString();
tpStart.DayNumber = (short)act.StartDate.Day;
//tpStart.AltKey = Convert.ToDateTime(parts1[0]);
tpStart.AltKey = ec.startTime;
act.StartDate = tpStart.AltKey;
TimePeriod tpEnd = new TimePeriod();
tpEnd.Year = (short)act.EndDate.Year;
tpEnd.Month = (short)act.EndDate.Month;
tpEnd.Hour = (short)act.EndDate.Hour;
tpEnd.Day = act.EndDate.DayOfWeek.ToString();
tpEnd.DayNumber = (short)act.EndDate.Day;
//tpEnd.AltKey = Convert.ToDateTime(parts1[0]);
tpEnd.AltKey = ec.endTime;
//act.StartDate = tpEnd.AltKey;
Address loc = new Address();
//return _store.AddActivity(_userId, act, tpStart, tpEnd, loc);
return _store.AddActivity(_userId, act, tpStart, tpEnd, loc);
}
private List<EventCluster> BuildEventClusterListFromPhotos(DataTable photos, double[] diffs, int windowSize, double K)
{
double localGapMean = 0;
int lastClusterIndex = 0;
List<EventCluster> gapList = new List<EventCluster>();
int rowCount = photos.Rows.Count;
// ignore the first _diff value as it will always be zero
for (int i = 1; i < rowCount; i++)
{
localGapMean = CalculateLocalGapMean(i, diffs, windowSize, rowCount);
if (Math.Log(diffs[i]) >= K + localGapMean)
{
EventCluster ec = new EventCluster();
ec.diffIndex = i;
ec.ecIndex1 = lastClusterIndex;
ec.ecIndex2 = i - 1;
DataRow dr = photos.Rows[ec.ecIndex1];
ec.startTime = (DateTime)dr["datetaken"];
dr = photos.Rows[ec.ecIndex2];
ec.endTime = (DateTime)dr["datetaken"];
lastClusterIndex = i;
gapList.Add(ec);
}
}
return gapList;
}
private List<EventCluster> BuildEventClusterListFromEventClusters(List<EventCluster> ecList, double[] diffs, int windowSize, double K)
{
double localGapMean = 0;
int lastClusterIndex = 0;
List<EventCluster> gapList = new List<EventCluster>();
int eventCount = ecList.Count;
// ignore the first _diff value as it will always be zero
for (int i = 1; i < eventCount; i++)
{
localGapMean = CalculateLocalGapMean(i, diffs, windowSize, eventCount);
if (Math.Log(diffs[i]) >= K + localGapMean)
{
EventCluster ec = new EventCluster();
ec.diffIndex = i;
ec.ecIndex1 = lastClusterIndex;
ec.ecIndex2 = i - 1;
EventCluster first = ecList[ec.ecIndex1];
ec.startTime = first.startTime;
EventCluster second = ecList[ec.ecIndex2];
ec.endTime = second.endTime;
lastClusterIndex = i;
gapList.Add(ec);
}
}
return gapList;
}
