private void binaryReport(Forms.RunningProcess.frmRunningProcessDialog rd)
{
KMeansClusterCollection gCol = (KMeansClusterCollection)clusterCollection;
for (int i = 0; i < gCol.Count; i++)
{
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
rd.addMessage("\n\nCluster " + Labels[i] + ":\nMeans: " + String.Join(", ", (from double d in mns select d.ToString()).ToArray()));
}
}
private void kmeansReport(Forms.RunningProcess.frmRunningProcessDialog rd)
{
KMeansClusterCollection gCol = kmeans.Clusters;
for (int i = 0; i < gCol.Count; i++)
{
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
double[,] cov = gClust.Covariance;
double[,] corr = getCorr(cov);
rd.addMessage("\n\nStratum " + Labels[i] + ":\nMeans: " + String.Join(", ", (from double d in mns select d.ToString()).ToArray()) + "\nCovariance:");
for (int j = 0; j < VariableFieldNames.Length; j++)
{
string[] covStrArr = new string[VariableFieldNames.Length];
for (int l = 0; l < covStrArr.Length; l++)
{
covStrArr[l] = cov[l, j].ToString();
}
rd.addMessage("\n" + String.Join(",", covStrArr));
}
rd.addMessage("\nCorr:");
for (int j = 0; j < VariableFieldNames.Length; j++)
{
string[] corrStrArr = new string[VariableFieldNames.Length];
for (int l = 0; l < corrStrArr.Length; l++)
{
corrStrArr[l] = corr[l, j].ToString();
}
rd.addMessage("\n" + String.Join(",", corrStrArr));
}
}
}
private static void fillStrataReport(string modelPath, Forms.RunningProcess.frmRunningProcessDialog rp, double proportion, double alpha)
{
dataPrepStrata strata = new dataPrepStrata();
strata.buildModel(modelPath);
List<string> lbl = strata.Labels;
rp.addMessage("Samples by strata (Stratum; number of samples)");
rp.addMessage("-".PadRight(45, '-'));
int[] samples = sampleSizeMaxStrata(modelPath, proportion, alpha);
for (int i = 0; i < samples.Length; i++)
{
rp.addMessage("\t" + lbl[i] + "; " + samples[i].ToString());
}
rp.addMessage("-".PadRight(45, '-'));
rp.addMessage("Total number of samples = " + samples.Sum().ToString());
}
private static void fillPcaReport(string modelPath, Forms.RunningProcess.frmRunningProcessDialog rp, double proportion = 0.1, double alpha = 0.05)
{
dataPrepPrincipleComponents pca = new dataPrepPrincipleComponents();
pca.buildModel(modelPath);
double[] meanVector = pca.MeanVector;
double[] std = pca.StdVector;
int numSamp = sampleSizeMaxMean(meanVector, std, proportion, alpha);
rp.addMessage("\nTotal Number of Samples = " + numSamp.ToString());
}
private static void fillCovCorr(string modelPath, Forms.RunningProcess.frmRunningProcessDialog rp, double proportion = 0.1, double alpha = 0.05)
{
dataPrepVarCovCorr covCorr = new dataPrepVarCovCorr();
covCorr.buildModel(modelPath);
double[,] covCorrArr = covCorr.CovarianceMatrix;
double[] means = covCorr.MeanVector;
string[] varFieldNames = covCorr.VariableFieldNames;
int[] nAndIndex = sampleSizeMaxMean(covCorrArr,means, proportion, alpha);
string vName = varFieldNames[nAndIndex[1]];
double mean = means[nAndIndex[1]];
double std = covCorr.StdVector[nAndIndex[1]];
rp.addMessage("\nTotal Number of Samples = " + nAndIndex[0].ToString() + "\n\nMax sample from variable " + vName + "\n\tMean = " + mean.ToString() + "\n\tSTD = " +std.ToString());
}
private static void fillCluserReport(string modelPath, Forms.RunningProcess.frmRunningProcessDialog rp, double proportion = 0.1, double alpha = 0.05)
{
dataPrepClusterKmean clus = new dataPrepClusterKmean();
clus.buildModel(modelPath);
List<string> lbl = clus.Labels;
rp.addMessage("Samples by class (Cluster; number of samples)");
rp.addMessage("-".PadRight(45, '-'));
int[] samples = sampleSizeMaxCluster(modelPath, proportion, alpha);
for (int i = 0; i < samples.Length; i++)
{
rp.addMessage("\t"+lbl[i] + "; " + samples[i].ToString());
}
rp.addMessage("-".PadRight(45, '-'));
rp.addMessage("Total number of samples = " + samples.Sum().ToString());
}
private static void fillAaReport(string modelPath,Forms.RunningProcess.frmRunningProcessDialog rp,double proportion=0.1, double alpha=0.05)
{
rp.addMessage("\nTotal Number of Samples = " + sampleSizeKappa(modelPath, proportion,alpha).ToString());
}
