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);
}
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;
}
