public EstimateResult compare(IEnumerable <Vertex> vertices, SnifferWifiMeasurement measurement)
{
measurement = getNStrongestAPMeasurement(measurement, 7);
if (vertices == null || measurement == null)
{
return(null);
}
bcs = WifiPosEngine.BestCandidateSet; //new BCS(5); //bcs.clear();
double curDist; //distance of current vertice in search space
EstimateResult result = new EstimateResult(null, double.MaxValue);
foreach (Vertex curVertex in vertices) //sammenlign med hver Vertex
{
foreach (SnifferWifiMeasurement curFP in curVertex.SnifferWifiMeasurements) //sammenlign med hvert fingerprint (usually only one - otherwise use more intelligent approach)
{
curDist = 0;
foreach (String mac in measurement.getMACs()) //all APs in sample
{
if (curFP.containsMac(mac))
{
curDist += Math.Pow((measurement.getAvgDbM(mac) - curFP.getAvgDbM(mac)), 2);
}
else
{
curDist += Math.Pow((measurement.getAvgDbM(mac) - MISSING_MAC_PENALTY), 2);
}
}
curDist = Math.Sqrt(curDist);
if (curDist < result.getDistance())
{
result.setDistance(curDist);
result.setVertex(curVertex);
}
bcs.add(curVertex, curDist); //add to best candidate set - which will take care of only using the best estimates.
}
}
//The following only yields a local error estimate within the primary- or secondary
//vertices and may thus not be appropriate
result.setErrorEstimate(Math.Ceiling(bcs.getMaxDistance()));
return(result);
}
public EstimateResult compare(IEnumerable<Vertex> vertices, SnifferWifiMeasurement measurement)
{
measurement = getNStrongestAPMeasurement(measurement, 7);
if (vertices == null || measurement == null)
return null;
bcs = WifiPosEngine.BestCandidateSet; //new BCS(5); //bcs.clear();
double curDist; //distance of current vertice in search space
EstimateResult result = new EstimateResult(null, double.MaxValue);
foreach (Vertex curVertex in vertices) //sammenlign med hver Vertex
{
foreach (SnifferWifiMeasurement curFP in curVertex.SnifferWifiMeasurements) //sammenlign med hvert fingerprint (usually only one - otherwise use more intelligent approach)
{
curDist = 0;
foreach (String mac in measurement.getMACs()) //all APs in sample
if (curFP.containsMac(mac))
curDist += Math.Pow((measurement.getAvgDbM(mac) - curFP.getAvgDbM(mac)), 2);
else
curDist += Math.Pow((measurement.getAvgDbM(mac) - MISSING_MAC_PENALTY), 2);
curDist = Math.Sqrt(curDist);
if (curDist < result.getDistance())
{
result.setDistance(curDist);
result.setVertex(curVertex);
}
bcs.add(curVertex, curDist); //add to best candidate set - which will take care of only using the best estimates.
}
}
//The following only yields a local error estimate within the primary- or secondary
//vertices and may thus not be appropriate
result.setErrorEstimate(Math.Ceiling(bcs.getMaxDistance()));
return result;
}
