private double[,] ComputeCorrelationMatrix(List<double>[] ListValueDesc)
{
int NumDesc = ListValueDesc.Length;
double[,] CorrelationMatrix = new double[NumDesc, NumDesc];
if (GlobalInfo.OptionsWindow.radioButtonMIC.Checked)
{
double[][] dataset1 = new double[NumDesc][];
string[] VarNames = new string[NumDesc];
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
{
dataset1[iDesc] = new double[ListValueDesc[iDesc].Count];
Array.Copy(ListValueDesc[iDesc].ToArray(), dataset1[iDesc], ListValueDesc[iDesc].Count);
VarNames[iDesc] = iDesc.ToString();
}
data.Dataset data1 = new data.Dataset(dataset1, VarNames, 0);
VarPairQueue Qu = new VarPairQueue(data1);
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
for (int jDesc = 0; jDesc < NumDesc; jDesc++)
{
Qu.addPair(iDesc, jDesc);
}
Analysis ana = new Analysis(data1, Qu);
AnalysisParameters param = new AnalysisParameters();
double resparam = param.commonValsThreshold;
analysis.results.FullResult Full = new analysis.results.FullResult();
//List<analysis.results.BriefResult> Brief = new List<analysis.results.BriefResult>();
analysis.results.BriefResult Brief = new analysis.results.BriefResult();
java.lang.Class t = java.lang.Class.forName("analysis.results.BriefResult");
//java.lang.Class restype = null;
ana.analyzePairs(t, param);
// object o = (ana.varPairQueue().peek());
// ana.getClass();
// int resNum = ana.numResults();
analysis.results.Result[] res = ana.getSortedResults();
// double main = res[0].getMainScore();
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
for (int jDesc = 0; jDesc < NumDesc; jDesc++)
{
int X = int.Parse(res[jDesc + iDesc * NumDesc].getXVar());
int Y = int.Parse(res[jDesc + iDesc * NumDesc].getYVar());
CorrelationMatrix[X, Y] = res[jDesc + iDesc * NumDesc].getMainScore();
}
}
else
{
//return null;
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
for (int jDesc = 0; jDesc < NumDesc; jDesc++)
{
try
{
if (GlobalInfo.OptionsWindow.radioButtonPearson.Checked)
CorrelationMatrix[iDesc, jDesc] = (alglib.pearsoncorr2(ListValueDesc[iDesc].ToArray(), ListValueDesc[jDesc].ToArray()));
else if (GlobalInfo.OptionsWindow.radioButtonSpearman.Checked)
CorrelationMatrix[iDesc, jDesc] = (alglib.spearmancorr2(ListValueDesc[iDesc].ToArray(), ListValueDesc[jDesc].ToArray()));
}
catch
{
//Console.WriteLine("Input string is not a sequence of digits.");
return null;
}
}
}
return CorrelationMatrix;
}
public void DisplayMINE(List<double>[] ListValueDesc)
{
int NumDesc = ListValueDesc.Length;
double[,] CorrelationMatrix = new double[NumDesc, NumDesc];
double[][] dataset1 = new double[NumDesc][];
string[] VarNames = new string[NumDesc];
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
{
dataset1[iDesc] = new double[ListValueDesc[iDesc].Count];
Array.Copy(ListValueDesc[iDesc].ToArray(), dataset1[iDesc], ListValueDesc[iDesc].Count);
VarNames[iDesc] = iDesc.ToString();
}
data.Dataset data1 = new data.Dataset(dataset1, VarNames, 0);
VarPairQueue Qu = new VarPairQueue(data1);
for (int iDesc = 0; iDesc < NumDesc; iDesc++)
for (int jDesc = 0; jDesc < iDesc; jDesc++)
{
Qu.addPair(iDesc, jDesc);
}
Analysis ana = new Analysis(data1, Qu);
AnalysisParameters param = new AnalysisParameters();
double resparam = param.commonValsThreshold;
// analysis.results.FullResult Full = new analysis.results.FullResult();
//List<analysis.results.BriefResult> Brief = new List<analysis.results.BriefResult>();
//analysis.results.BriefResult Brief = new analysis.results.BriefResult();
java.lang.Class t = java.lang.Class.forName("analysis.results.BriefResult");
//java.lang.Class restype = null;
ana.analyzePairs(t, param);
// object o = (ana.varPairQueue().peek());
// ana.getClass();
// int resNum = ana.numResults();
analysis.results.Result[] res = ana.getSortedResults();
List<string[]> ListValues = new List<string[]>();
List<string> NameX = CompleteScreening.ListDescriptors.GetListNameActives();
List<bool> ListIscolor = new List<bool>();
for (int Idx = 0; Idx < res.Length; Idx++)
{
ListValues.Add(res[Idx].toString().Split(','));
ListValues[Idx][0] = NameX[int.Parse(ListValues[Idx][0])];
ListValues[Idx][1] = NameX[int.Parse(ListValues[Idx][1])];
}
string[] ListNames = res[0].getHeader().Split(',');
ListNames[0] = "Descriptor A";
ListNames[1] = "Descriptor B";
for (int NIdx = 0; NIdx < ListNames.Length; NIdx++)
{
if (NIdx == 0) ListIscolor.Add(false);
else if (NIdx == 1) ListIscolor.Add(false);
else ListIscolor.Add(true);
}
cDisplayTable DisplayForTable = new cDisplayTable("MINE Analysis results", ListNames, ListValues, GlobalInfo, true);
}
public void Run()
{
// define names
string[] VarNames = new string[Input.Count];
double[][] dataset = new double[Input.Count][];
int Idx = 0;
foreach (var item in Input)
{
dataset[Idx] = new double[item.Count];
Array.Copy(item.ToArray(), dataset[Idx], item.Count);
VarNames[Idx++] = item.Name;
}
//// define data
data.Dataset data_Set = new data.Dataset(dataset, VarNames, 0);
analysis.VarPairQueue Qu = new analysis.VarPairQueue(data_Set);
for(int Idx_0=0;Idx_0<this.Input.Count;Idx_0++)
for (int Idx_1 = 0; Idx_1 <= Idx_0; Idx_1++)
Qu.addPair(Idx_1,Idx_0);
Analysis ana = new Analysis(data_Set, Qu);
AnalysisParameters param = new AnalysisParameters();
double resparam = param.commonValsThreshold;
java.lang.Class t = java.lang.Class.forName("analysis.results.FullResult");
if(this.Is_BriefReport)
t = java.lang.Class.forName("analysis.results.BriefResult");
ana.analyzePairs(t, param);
analysis.results.Result[] res = ana.getSortedResults();
List<string[]> ListValues = new List<string[]>();
List<bool> ListIscolor = new List<bool>();
for (Idx = 0; Idx < res.Length; Idx++)
{
ListValues.Add(res[Idx].toString().Split(','));
}
string[] ListNames = res[0].getHeader().Split(',');
this.Output = new cListExtendedTable();
for (int IdxTest = 2; IdxTest < ListNames.Length; IdxTest++) // loop over all the different type of results
{
// remove useless informations
if (ListNames[IdxTest] == "MI via KDE") continue;
if (ListNames[IdxTest] == "Fisher") continue;
if (ListNames[IdxTest] == "last value") continue;
if (ListNames[IdxTest] == "MAS found at (X)") continue;
if (ListNames[IdxTest] == "MAS found at (Y)") continue;
if (ListNames[IdxTest] == "MICfound at (Y)") continue;
double[,] TmpTable = new double[VarNames.Length, VarNames.Length];
for (int i = 0; i < res.Length; i++) // loop over the different pairs
{
string TmpName0 = res[i].getXVar();
string TmpName1 = res[i].getYVar();
int Idx_var0 = 0;
int Idx_var1 = 0;
for (Idx_var0 = 0; Idx_var0 < VarNames.Length; Idx_var0++)
if(VarNames[Idx_var0]==TmpName0)
break;
for (Idx_var1 = 0; Idx_var1 < VarNames.Length; Idx_var1++)
if (VarNames[Idx_var1] == TmpName1)
break;
double Value=0;
double.TryParse(res[i].toString().Split(',')[IdxTest], out Value);
TmpTable[Idx_var0, Idx_var1] = TmpTable[Idx_var1, Idx_var0] = Value;
}
cExtendedTable NewTable = new cExtendedTable(TmpTable);
NewTable.ListRowNames = new List<string>();
for (int i = 0; i < VarNames.Length; i++)
{
NewTable.ListRowNames.Add(VarNames[i]);
NewTable[i].Name = VarNames[i];
if (CurrentScreening != null)
{
int IdxDesc = cGlobalInfo.CurrentScreening.ListDescriptors.GetDescriptorIndex(NewTable[i].Name);
if (IdxDesc > -1)
{
NewTable[i].Tag = cGlobalInfo.CurrentScreening.ListDescriptors[IdxDesc];
}
}
}
NewTable.Name = ListNames[IdxTest];
this.Output.Add(NewTable);
}
}
