BestModel FindBestToModel(List<string> targets,DistanceMeasures distance,string dirName,string alignFile,string profileName,string model)
{
BestModel vOut=new BestModel();
List<string> localNames = new List<string>(2);
List<string> fileNames = new List<string>(targets.Count);
foreach (var item in targets)
fileNames.Add(dirName + Path.DirectorySeparatorChar + item);
fileNames.Add(model);
//dist=PrepareDistance(distance,fileNames,alignFile,profileName);
string[] aux = model.Split(Path.DirectorySeparatorChar);
InitBestModel(distance, ref vOut);
foreach (var item in targets)
{
/* localNames.Clear();
localNames.Add(model);
localNames.Add(item);
dist = PrepareDistance(distance, fileNames, alignFile, profileName);*/
int value=0;
//value = dist.GetDistance(aux[aux.Length - 1], item);
value = GetDist(distance, dirName, model, item);
CheckBest(distance, value, item, ref vOut);
}
return vOut;
}
void InitBestModel(DistanceMeasures distance,ref BestModel model)
{
switch (distance)
{
case DistanceMeasures.HAMMING:
model.value = int.MinValue;
break;
case DistanceMeasures.MAXSUB:
case DistanceMeasures.RMSD:
case DistanceMeasures.GDT_TS:
model.value = int.MaxValue;
break;
}
}
void CheckBest(DistanceMeasures distance,int value,string item,ref BestModel best)
{
switch (distance)
{
case DistanceMeasures.HAMMING:
if (best.value <= value)
{
best.value = value;
best.modelName = item;
}
break;
case DistanceMeasures.MAXSUB:
case DistanceMeasures.GDT_TS:
case DistanceMeasures.RMSD:
if (best.value >= value)
{
best.value=value;
best.modelName = item;
}
break;
}
}
public void GetFraction(object param)
{
float fraction = 0;
float avrDiff=0;
int counter = 0;
int end;
DistanceMeasures distance=((fractionParams)param).distance;
string profileName = ((fractionParams)param).profileName;
double distThreshold = ((fractionParams)param).distThreshold;
int clustersNum = ((fractionParams)param).clustersNum;
results = new DataTable();
try
{
DataColumn col;
col=results.Columns.Add("Output", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Best Model", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Distance To Native", typeof(double));
col.AllowDBNull = true;
col=results.Columns.Add("Best found", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Distance to best model", typeof(double));
col.AllowDBNull = true;
maxV = output.Count;
foreach (var item in output)
{
string[] kkk = item.dirName.Split(Path.DirectorySeparatorChar);
List<List<string>> clusters = item.GetClusters(10);
List<string> list = new List<string>();
foreach (var cl in clusters)
foreach (var target in cl)
list.Add(target);
string native = item.dirName + ".pdb";
if (item.dirName.Contains("."))
{
string[] aux = item.dirName.Split('.');
native = aux[0] + ".pdb";
}
string fileBestModel = item.dirName + "_" + distance.ToString() + "_bestmodel.dat";
BestModel bestToNative;
if (!File.Exists(fileBestModel))
{
bestToNative = FindBestToModel(list, distance, item.dirName, "", "", native);
StreamWriter st = new StreamWriter(fileBestModel);
st.WriteLine(bestToNative.modelName + " " + bestToNative.value);
st.Close();
}
else
{
StreamReader st = new StreamReader(fileBestModel);
string line = st.ReadLine();
string[] aux = line.Split(' ');
bestToNative.modelName = aux[0];
bestToNative.value = Convert.ToInt32(aux[1], System.Globalization.CultureInfo.InvariantCulture);
st.Close();
}
if (bestToNative.value == int.MaxValue)
continue;
// list.Clear();
if (clusters.Count > 0)
clusters.Sort(delegate(List<string> first, List<string> second)
{ return second.Count.CompareTo(first.Count); });
string represent = "";
//And now best five
BestModel vOut = new BestModel();
InitBestModel(distance, ref vOut);
end = clustersNum;
if (clusters.Count < clustersNum)
end = clusters.Count;
for (int i = 0; i < end; i++)
//for (int i = 0; i < clusters.Count; i++)
{
if (profileName != null)
represent = CLusterRepresentJury(item.dirName, clusters[i], profileName)[0].Key;
else
{
if (item.juryLike != null)
represent = item.juryLike[i].Key;
else
{
/* if (clusters.Count > 1)
{
represent = CLusterRepresent(distance,item.dirName, clusters[i],"",profileName);
}
else*/
represent = clusters[i][0];
}
}
int vDist = GetDist(distance, item.dirName, bestToNative.modelName, represent);
//int vDist = GetDist(distance, item.dirName, native, represent);
CheckBest(distance, vDist, represent, ref vOut);
}
if (bestToNative.value == errorValue || vOut.value == errorValue)
{
if (bestToNative.value == errorValue && vOut.value != errorValue)
results.Rows.Add(item.name, bestToNative.modelName, double.NaN, vOut.modelName, vOut.value / 100.0);
else
if(bestToNative.value != errorValue && vOut.value == errorValue)
results.Rows.Add(item.name, bestToNative.modelName, bestToNative.value / 100.0, vOut.modelName, double.NaN);
else
results.Rows.Add(item.name, bestToNative.modelName, double.NaN, vOut.modelName, double.NaN);
}
else
results.Rows.Add(item.name, bestToNative.modelName, bestToNative.value / 100.0, vOut.modelName, vOut.value / 100.0);
if (vOut.value!=errorValue && vOut.value-bestToNative.value < distThreshold * 100)
//if (vOut.value != errorValue && vOut.value < distThreshold * 100)
{
fraction++;
}
if (vOut.value!=errorValue)
{
counter++;
avrDiff += vOut.value;
}
//dist = null;
GC.Collect();
currentV++;
}
avrDiff /= counter;
fraction /= counter;
results.Rows.Add(null, null, null, null, null);
results.Rows.Add("AVR:"," "+Math.Round(avrDiff / 100,2),null,"Fraction:",Math.Round(fraction,2));
}
catch(Exception ex)
{
exc = ex;
}
//Console.WriteLine("avrDiff=" + avrDiff + " fraction=" + fraction+" pearson="+Pearson());
currentV = maxV;
}
public void GetFraction(object param)
{
float fraction = 0;
float avrDiff=0;
int counter = 0;
int end;
DistanceMeasures distance=((fractionParams)param).distance;
string profileName = ((fractionParams)param).profileName;
double distThreshold = ((fractionParams)param).distThreshold;
int clustersNum = ((fractionParams)param).clustersNum;
results = new DataTable();
try
{
DataColumn col;
col=results.Columns.Add("Output", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Best Model", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Distance To Native", typeof(double));
col.AllowDBNull = true;
col=results.Columns.Add("Best found", typeof(string));
col.AllowDBNull = true;
col=results.Columns.Add("Distance to best model", typeof(double));
col.AllowDBNull = true;
maxV = output.Count;
foreach (var item in output)
{
string[] kkk = item.dirName.Split(Path.DirectorySeparatorChar);
List<List<string>> clusters = item.GetClusters(10);
List<string> list = new List<string>();
foreach (var cl in clusters)
foreach (var target in cl)
list.Add(target);
string native = item.dirName + ".pdb";
if (item.dirName.Contains("."))
{
string[] aux = item.dirName.Split('.');
native = aux[0] + ".pdb";
}
string fileBestModel = item.dirName + "_" + distance.ToString() + "_bestmodel.dat";
BestModel bestToNative;
if (!File.Exists(fileBestModel))
{
bestToNative = FindBestToModel(list, distance, item.dirName, "", "", native);
StreamWriter st = new StreamWriter(fileBestModel);
st.WriteLine(bestToNative.modelName + " " + bestToNative.value);
st.Close();
}
else
{
StreamReader st = new StreamReader(fileBestModel);
string line = st.ReadLine();
string[] aux = line.Split(' ');
bestToNative.modelName = aux[0];
bestToNative.value = Convert.ToInt32(aux[1]);
st.Close();
}
if (bestToNative.value == int.MaxValue)
continue;
// list.Clear();
if (clusters.Count > 0)
clusters.Sort(delegate(List<string> first, List<string> second)
{ return second.Count.CompareTo(first.Count); });
string represent = "";
//And now best five
BestModel vOut = new BestModel();
InitBestModel(distance, ref vOut);
end = clustersNum;
if (clusters.Count < clustersNum)
end = clusters.Count;
for (int i = 0; i < end; i++)
//for (int i = 0; i < clusters.Count; i++)
{
if (profileName != null)
represent = CLusterRepresentJury(item.dirName, clusters[i], profileName)[0].Key;
else
{
if (item.juryLike != null)
represent = item.juryLike[i].Key;
else
{
/* if (clusters.Count > 1)
{
represent = CLusterRepresent(distance,item.dirName, clusters[i],"",profileName);
}
else*/
represent = clusters[i][0];
}
}
//int vDist = GetDist(distance, item.dirName, bestToNative.modelName, represent);
int vDist = GetDist(distance, item.dirName, native, represent);
CheckBest(distance, vDist, represent, ref vOut);
}
if (bestToNative.value == errorValue || vOut.value == errorValue)
{
if (bestToNative.value == errorValue && vOut.value != errorValue)
results.Rows.Add(item.name, bestToNative.modelName, double.NaN, vOut.modelName, vOut.value / 100.0);
else
if(bestToNative.value != errorValue && vOut.value == errorValue)
results.Rows.Add(item.name, bestToNative.modelName, bestToNative.value / 100.0, vOut.modelName, double.NaN);
else
results.Rows.Add(item.name, bestToNative.modelName, double.NaN, vOut.modelName, double.NaN);
}
else
results.Rows.Add(item.name, bestToNative.modelName, bestToNative.value / 100.0, vOut.modelName, vOut.value / 100.0);
if (vOut.value!=errorValue && Math.Abs(vOut.value-bestToNative.value) < distThreshold * 100)
{
fraction++;
}
if (vOut.value!=errorValue)
{
counter++;
avrDiff += vOut.value;
}
dist = null;
GC.Collect();
currentV++;
}
avrDiff /= counter;
fraction /= counter;
results.Rows.Add(null, null, null, null, null);
results.Rows.Add("AVR:"," "+Math.Round(avrDiff / 100,2),null,"Fraction:",Math.Round(fraction,2));
}
catch(Exception ex)
{
exc = ex;
}
//Console.WriteLine("avrDiff=" + avrDiff + " fraction=" + fraction+" pearson="+Pearson());
currentV = maxV;
}
BestModel FindBestToModel(List<string> targets,DistanceMeasures distance,string dirName,string alignFile,string profileName,string model)
{
BestModel vOut=new BestModel();
List<string> localNames = new List<string>(2);
List<string> fileNames = new List<string>(targets.Count);
foreach (var item in targets)
fileNames.Add(dirName + Path.DirectorySeparatorChar + item);
fileNames.Add(model);
//dist=PrepareDistance(distance,fileNames,alignFile,profileName);
string[] aux = model.Split(Path.DirectorySeparatorChar);
InitBestModel(distance, ref vOut);
foreach (var item in targets)
{
/* localNames.Clear();
localNames.Add(model);
localNames.Add(item);
dist = PrepareDistance(distance, fileNames, alignFile, profileName);*/
int value=0;
//value = dist.GetDistance(aux[aux.Length - 1], item);
value = GetDist(distance, dirName, model, item);
CheckBest(distance, value, item, ref vOut);
}
return vOut;
}
void CheckBest(DistanceMeasures distance,int value,string item,ref BestModel best)
{
switch (distance)
{
case DistanceMeasures.HAMMING:
if (best.value <= value)
{
best.value = value;
best.modelName = item;
}
break;
case DistanceMeasures.MAXSUB:
case DistanceMeasures.GDT_TS:
case DistanceMeasures.RMSD:
if (best.value >= value)
{
best.value=value;
best.modelName = item;
}
break;
}
}
void InitBestModel(DistanceMeasures distance,ref BestModel model)
{
switch (distance)
{
case DistanceMeasures.HAMMING:
model.value = int.MinValue;
break;
case DistanceMeasures.MAXSUB:
case DistanceMeasures.RMSD:
case DistanceMeasures.GDT_TS:
model.value = int.MaxValue;
break;
}
}
