protected override void Run(Prediction prediction)
{
List <PostGIS.Point> predictionPoints = new List <PostGIS.Point>();
Area predictionArea = prediction.PredictionArea;
double areaMinX = predictionArea.BoundingBox.MinX;
double areaMaxX = predictionArea.BoundingBox.MaxX;
double areaMinY = predictionArea.BoundingBox.MinY;
double areaMaxY = predictionArea.BoundingBox.MaxY;
for (double x = areaMinX + prediction.PredictionPointSpacing / 2d; x <= areaMaxX; x += prediction.PredictionPointSpacing) // place points in the middle of the square boxes that cover the region - we get display errors from pixel rounding if the points are exactly on the boundaries
{
for (double y = areaMinY + prediction.PredictionPointSpacing / 2d; y <= areaMaxY; y += prediction.PredictionPointSpacing)
{
predictionPoints.Add(new PostGIS.Point(x, y, predictionArea.Shapefile.SRID));
}
}
List <PostGIS.Point> incidentPoints = new List <PostGIS.Point>(Incident.Get(TrainingStart, TrainingEnd, predictionArea, IncidentTypes.ToArray()).Select(i => i.Location));
predictionPoints.AddRange(incidentPoints);
Console.Out.WriteLine("Filtering prediction points to prediction area");
predictionPoints = predictionArea.Intersects(predictionPoints, prediction.PredictionPointSpacing / 2f).Select(i => predictionPoints[i]).ToList();
NpgsqlConnection connection = DB.Connection.OpenConnection;
try
{
Console.Out.WriteLine("Inserting points into prediction");
Point.CreateTable(prediction, predictionArea.Shapefile.SRID);
List <int> predictionPointIds = Point.Insert(connection, predictionPoints.Select(p => new Tuple <PostGIS.Point, string, DateTime>(p, PointPrediction.NullLabel, DateTime.MinValue)), prediction, predictionArea, false);
Console.Out.WriteLine("Running overall KDE for " + IncidentTypes.Count + " incident type(s)");
List <float> density = GetDensityEstimate(incidentPoints, _trainingSampleSize, false, 0, 0, predictionPoints, _normalize);
Dictionary <int, float> pointIdOverallDensity = new Dictionary <int, float>(predictionPointIds.Count);
int pointNum = 0;
foreach (int predictionPointId in predictionPointIds)
{
pointIdOverallDensity.Add(predictionPointId, density[pointNum++]);
}
Dictionary <int, Dictionary <string, double> > pointIdIncidentDensity = new Dictionary <int, Dictionary <string, double> >(pointIdOverallDensity.Count);
if (IncidentTypes.Count == 1)
{
string incident = IncidentTypes.First();
foreach (int pointId in pointIdOverallDensity.Keys)
{
Dictionary <string, double> incidentDensity = new Dictionary <string, double>();
incidentDensity.Add(incident, pointIdOverallDensity[pointId]);
pointIdIncidentDensity.Add(pointId, incidentDensity);
}
}
else
{
foreach (string incidentType in IncidentTypes)
{
Console.Out.WriteLine("Running KDE for incident \"" + incidentType + "\"");
incidentPoints = new List <PostGIS.Point>(Incident.Get(TrainingStart, TrainingEnd, predictionArea, incidentType).Select(i => i.Location));
density = GetDensityEstimate(incidentPoints, _trainingSampleSize, false, 0, 0, predictionPoints, _normalize);
if (density.Count > 0)
{
pointNum = 0;
foreach (int predictionPointId in predictionPointIds)
{
pointIdIncidentDensity.EnsureContainsKey(predictionPointId, typeof(Dictionary <string, double>));
pointIdIncidentDensity[predictionPointId].Add(incidentType, density[pointNum++]);
}
}
}
}
PointPrediction.CreateTable(prediction);
PointPrediction.Insert(GetPointPredictionValues(pointIdOverallDensity, pointIdIncidentDensity), prediction, false);
Smooth(prediction);
}
finally
{
DB.Connection.Return(connection);
}
}
private void SetIncidentsToolTip()
{
if (_setIncidentsToolTip)
{
int numIncidents = 0;
if (TrainingArea != null && IncidentTypes.Count > 0)
{
numIncidents = Incident.Count(trainingStart.Value, trainingEnd.Value, TrainingArea, IncidentTypes.ToArray());
}
toolTip.SetToolTip(incidentTypes, numIncidents + " total incidents selected");
}
}