private void RunKMeans(string name, string dirName, string alignFile = null, DCDFile dcd = null)
{
DateTime cpuPart1 = DateTime.Now;
ClusterOutput clustOut;
DistanceMeasure distance = null;
if (dcd == null)
{
distance = CreateMeasure(name, dirName, opt.kmeans.kDistance, opt.kmeans.kAtoms, opt.kmeans.reference1Djury,
alignFile, opt.kmeans.hammingProfile, opt.kmeans.jury1DProfile);
}
else
{
distance = CreateMeasureForDCD(dcd, opt.kmeans.kDistance, opt.kmeans.kAtoms, opt.kmeans.reference1Djury,
opt.kmeans.alignmentFileName, opt.kmeans.hammingProfile, opt.kmeans.jury1DProfile);
}
kMeans km;
km = new kMeans(distance, opt.kmeans.kMeans_init);
if (beginJob != null)
{
beginJob(currentProcessName, km.ToString(), dirName, distance.ToString());
}
progressDic.Add(name, km);
distance.InitMeasure();
DateTime cpuPart2 = DateTime.Now;
clType = km.ToString();
if ((int)opt.kmeans.maxK <= 1)
{
throw new Exception("k in k-Means must be bigger then 1, right now is: " + (int)opt.kmeans.maxK);
}
if (distance.structNames.Count < 10)
{
throw new Exception("Number of structures to cluster must be bigger then 10 right now is: " + distance.structNames.Count);
}
clustOut = km.kMeansLevel((int)opt.kmeans.maxK, opt.kmeans.maxIter, new List <string>(distance.structNames.Keys));
UpdateOutput(name, dirName, alignFile, clustOut, distance.ToString(), cpuPart1, cpuPart2, km);
GC.SuppressFinalize(distance);
}
private void RunKMeans(string name, string dirName, string alignFile=null, DCDFile dcd = null)
{
DateTime cpuPart1 = DateTime.Now;
ClusterOutput clustOut;
DistanceMeasure distance = null;
if(dcd==null)
distance = CreateMeasure(name,dirName,opt.kmeans.kDistance, opt.kmeans.kAtoms, opt.kmeans.reference1Djury,
alignFile, opt.kmeans.hammingProfile, opt.kmeans.jury1DProfile);
else
distance =CreateMeasureForDCD(dcd, opt.kmeans.kDistance, opt.kmeans.kAtoms, opt.kmeans.reference1Djury,
opt.kmeans.alignmentFileName, opt.kmeans.hammingProfile, opt.kmeans.jury1DProfile);
kMeans km;
km = new kMeans(distance, opt.kmeans.kMeans_init);
progressDic.Add(name, km);
distance.InitMeasure();
DateTime cpuPart2 = DateTime.Now;
clType = km.ToString();
if ((int)opt.kmeans.maxK <= 1)
throw new Exception("k in k-Means must be bigger then 1, right now is: " + (int)opt.kmeans.maxK);
if (distance.structNames.Count < 10)
throw new Exception("Number of structures to cluster must be bigger then 10 right now is: " + distance.structNames.Count);
clustOut = km.kMeansLevel((int)opt.kmeans.maxK, opt.kmeans.maxIter,new List <string>(distance.structNames.Keys));
UpdateOutput(name, dirName,alignFile, clustOut, distance.ToString(), cpuPart1, cpuPart2,km);
GC.SuppressFinalize(distance);
}
ClusterOutput DivideSpaceKmeans(List <string> list)
{
kMeans km = new kMeans(dMeasure);
return(km.kMeansLevel(2, 30, list));
}
ClusterOutput DivideSpaceKmeans(List<string> list)
{
kMeans km = new kMeans(dMeasure);
return km.kMeansLevel(2,30, list);
}