static void Knn()
{
IPoints points = Dataset.LoadDataset(@"c:\temp\points.csv");
// Used for testing K nearest neighbor
IPointsKnn dataset = new PointsKnn();
dataset.Data.AddRange(points.Data.Select(i => i as IPKnn));
// Used for testing K nearest neighbor
var rect = new SingleDetectLibrary.Code.Data.Rectangle
{
XMin = -180,
XMax = 180,
YMin = -90,
YMax = 90,
MaxDistance = 20,
};
rect.Validate();
const int k = 3;
IAlgorithm algo = new Algorithm(dataset, rect, StrategyType.Grid);
var origin = new SingleDetectLibrary.Code.Data.P {
X = 0, Y = 0
};
algo.UpdateIndex(origin);
var duration = algo.UpdateKnn(origin, new KnnConfiguration {
K = k
});
// Print result
CW(string.Format("{0} msec. {1}:", algo.Strategy.Name, duration));
CW("K Nearest Neighbors:");
CW(string.Format("Origin: {0}", origin));
CW(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(CW);
// Update strategy
algo.SetAlgorithmStrategy(new NaiveStrategy());
// Use algo
duration = algo.UpdateKnn(origin, new KnnConfiguration {
K = k
});
// Print result
CW(string.Format("\n{0} msec. {1}:", algo.Strategy.Name, duration));
CW("K Nearest Neighbors:");
CW(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(CW);
}
// Example of usage:
// Get 3 nearest -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3
// Get 3 nearest type 1 -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3;type=1
// Get nearest within 1 km -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=1000000;dist=1
public JsonKnnReply Knn(string s)
{
var sw = new Stopwatch();
sw.Start();
var invalid = new JsonKnnReply {};
if (string.IsNullOrEmpty(s))
{
invalid.EMsg = "param is empty";
return invalid;
}
var arr = s.Split(new[] { ";" }, StringSplitOptions.RemoveEmptyEntries);
if (arr.Length < 3)
{
invalid.EMsg = string.Format("param length is not valid: {0}",arr.Length);
return invalid;
}
var nvc = new NameValueCollection();
foreach (var a in arr)
{
var kv = a.Split(new[] { "=" }, StringSplitOptions.RemoveEmptyEntries);
if (kv.Length != 2) continue;
nvc.Add(kv[0], kv[1]);
}
foreach (var key in Ajax.KnnReq)
{
if (nvc[key] != null) continue;
invalid.EMsg = string.Format("param {0} is missing", key);
return invalid;
}
try
{
var y = nvc[Ajax.lat].Replace("_", ".").ToDouble();
var x = nvc[Ajax.lon].Replace("_", ".").ToDouble();
var k = int.Parse(nvc[Ajax.k]);
var type = nvc[Ajax.type] == null ? -1 : int.Parse(nvc[Ajax.type]);
double? dist = null;
if(! string.IsNullOrEmpty(nvc[Ajax.dist])) dist = nvc[Ajax.dist].Replace("_", ".").ToDouble();
// knn algo
var algo = MemoryDatabase.Data as IKnnAlgorithm;
if (algo == null)
{
invalid.EMsg = "algorithm is not available";
return invalid;
}
// Use algo
var origin = new SingleDetectLibrary.Code.Data.P { X = x, Y = y, Type = type };
var knnSameTypeOnly = type != -1;
var conf = new KnnConfiguration {K = k, SameTypeOnly = knnSameTypeOnly, MaxDistance = dist};
var duration = algo.UpdateKnn(origin, conf);
var nns = algo.Knn.NNs.Select(p => p as PDist).ToList();
var gmsNns = new List<GmcPDist>();
foreach (var i in nns)
{
//i.Distance = Math.Round(i.Distance, 7);
var pdist = new GmcPDist
{
Id = i.Point.Uid.ToString(),
Point = i.Point,
Distance = Math.Round(i.Distance, 7)
};
gmsNns.Add(pdist);
}
var result =
new JsonKnnReply
{
Data = string.Format("Distance in km, x: {0}; y: {1}; k: {2}; sameTypeOnly: {3}, algo msec: {4}",
x.DoubleToString(), y.DoubleToString(), k, knnSameTypeOnly, duration),
Nns = gmsNns, // cannot be interface, thus casting
Msec = Sw(sw),
};
return result;
}
catch (Exception ex)
{
invalid.EMsg = string.Format("Parsing error param: {0}",
ex.Message);
return invalid;
}
}
static void Knn()
{
IPoints points = Dataset.LoadDataset(@"c:\temp\points.csv");
// Used for testing K nearest neighbor
IPointsKnn dataset = new PointsKnn();
dataset.Data.AddRange(points.Data.Select(i => i as IPKnn));
// Used for testing K nearest neighbor
var rect = new SingleDetectLibrary.Code.Data.Rectangle
{
XMin = -180,
XMax = 180,
YMin = -90,
YMax = 90,
MaxDistance = 20,
};
rect.Validate();
const int k = 3;
IAlgorithm algo = new Algorithm(dataset, rect, StrategyType.Grid);
var origin = new SingleDetectLibrary.Code.Data.P { X = 0, Y = 0 };
algo.UpdateIndex(origin);
var duration = algo.UpdateKnn(origin, new KnnConfiguration{K = k});
// Print result
CW(string.Format("{0} msec. {1}:", algo.Strategy.Name, duration));
CW("K Nearest Neighbors:");
CW(string.Format("Origin: {0}", origin));
CW(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(CW);
// Update strategy
algo.SetAlgorithmStrategy(new NaiveStrategy());
// Use algo
duration = algo.UpdateKnn(origin, new KnnConfiguration{K = k});
// Print result
CW(string.Format("\n{0} msec. {1}:", algo.Strategy.Name, duration));
CW("K Nearest Neighbors:");
CW(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(CW);
}
// Example of usage:
// Get 3 nearest -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3
// Get 3 nearest type 1 -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3;type=1
// Get nearest within 1 km -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=1000000;dist=1
public JsonKnnReply Knn(string s)
{
var sw = new Stopwatch();
sw.Start();
var invalid = new JsonKnnReply {
};
if (string.IsNullOrEmpty(s))
{
invalid.EMsg = "param is empty";
return(invalid);
}
var arr = s.Split(new[] { ";" }, StringSplitOptions.RemoveEmptyEntries);
if (arr.Length < 3)
{
invalid.EMsg = string.Format("param length is not valid: {0}", arr.Length);
return(invalid);
}
var nvc = new NameValueCollection();
foreach (var a in arr)
{
var kv = a.Split(new[] { "=" }, StringSplitOptions.RemoveEmptyEntries);
if (kv.Length != 2)
{
continue;
}
nvc.Add(kv[0], kv[1]);
}
foreach (var key in Ajax.KnnReq)
{
if (nvc[key] != null)
{
continue;
}
invalid.EMsg = string.Format("param {0} is missing", key);
return(invalid);
}
try
{
var y = nvc[Ajax.lat].Replace("_", ".").ToDouble();
var x = nvc[Ajax.lon].Replace("_", ".").ToDouble();
var k = int.Parse(nvc[Ajax.k]);
var type = nvc[Ajax.type] == null ? -1 : int.Parse(nvc[Ajax.type]);
double?dist = null;
if (!string.IsNullOrEmpty(nvc[Ajax.dist]))
{
dist = nvc[Ajax.dist].Replace("_", ".").ToDouble();
}
// knn algo
var algo = MemoryDatabase.Data as IKnnAlgorithm;
if (algo == null)
{
invalid.EMsg = "algorithm is not available";
return(invalid);
}
// Use algo
var origin = new SingleDetectLibrary.Code.Data.P {
X = x, Y = y, Type = type
};
var knnSameTypeOnly = type != -1;
var conf = new KnnConfiguration {
K = k, SameTypeOnly = knnSameTypeOnly, MaxDistance = dist
};
var duration = algo.UpdateKnn(origin, conf);
var nns = algo.Knn.NNs.Select(p => p as PDist).ToList();
var gmsNns = new List <GmcPDist>();
foreach (var i in nns)
{
//i.Distance = Math.Round(i.Distance, 7);
var pdist = new GmcPDist
{
Id = i.Point.Uid.ToString(),
Point = i.Point,
Distance = Math.Round(i.Distance, 7)
};
gmsNns.Add(pdist);
}
var result =
new JsonKnnReply
{
Data = string.Format("Distance in km, x: {0}; y: {1}; k: {2}; sameTypeOnly: {3}, algo msec: {4}",
x.DoubleToString(), y.DoubleToString(), k, knnSameTypeOnly, duration),
Nns = gmsNns, // cannot be interface, thus casting
Msec = Sw(sw),
};
return(result);
}
catch (Exception ex)
{
invalid.EMsg = string.Format("Parsing error param: {0}",
ex.Message);
return(invalid);
}
}
