/// <summary>
/// Fills values in the two-dimensional array of bits which define the connectedness
/// of clusters between each other.
/// </summary>
/// <param name="treeMatrix">Two-dimensional array of bits which define the connectedness
/// of clusters between each other.</param>
/// <param name="mu">Density parameter.</param>
private void GenerateData(BitArray[][] treeMatrix, Double mu)
{
for (int currentLevel = 0; currentLevel < container.Level; ++currentLevel)
{
if (treeMatrix[currentLevel].Length > 0)
{
uint branchSize = container.Branches[currentLevel][0];
int counter = 0, nodeNumber = 0;
for (int i = 0; i < treeMatrix[currentLevel].Length; i++)
{
for (int j = 0; j < treeMatrix[currentLevel][i].Length; j++)
{
if (counter == (branchSize * (branchSize - 1) / 2))
{
++nodeNumber;
counter = 0;
branchSize = container.Branches[currentLevel][nodeNumber];
}
double k = rand.NextDouble();
if (k <= (1 / Math.Pow(container.CountLeaves(currentLevel, nodeNumber), mu)))
{
treeMatrix[currentLevel][i][j] = true;
}
else
{
treeMatrix[currentLevel][i][j] = false;
}
++counter;
}
}
}
}
}
/// <summary>
/// Calculates the distribution of degrees of vertices that belong to the given cluster.
/// </summary>
/// <param name="numberNode">The index of cluster.</param>
/// <param name="currentLevel">The level of cluster.</param>
/// <returns>Distribution of degrees of vertices that belong to the given cluster.</returns>
private SortedDictionary <Double, Double> DegreeDistributionInCluster(int numberNode,
int currentLevel)
{
if (currentLevel == container.Level)
{
SortedDictionary <Double, Double> returned = new SortedDictionary <Double, Double>();
returned[0] = 1;
return(returned);
}
else
{
BitArray node = container.TreeNode(currentLevel, numberNode);
SortedDictionary <Double, Double> arraysReturned = new SortedDictionary <Double, Double>();
SortedDictionary <Double, Double> array = new SortedDictionary <Double, Double>();
int branchSize = (int)container.Branches[currentLevel][numberNode];
int branchStartPnt = container.FindBranches(currentLevel, numberNode);
for (int i = 0; i < branchSize; ++i)
{
array = DegreeDistributionInCluster(branchStartPnt + i, currentLevel + 1);
int countAjacentsNodes = container.CountConnectedBlocks(node, branchSize, i);
foreach (KeyValuePair <Double, Double> kvt in array)
{
Double key = kvt.Key;
for (int j = 0; j < branchSize; ++j)
{
int counter = 0;
if (container.AreConnectedTwoBlocks(node, branchSize, i, j))
{
key += container.CountLeaves(currentLevel + 1,
branchStartPnt + j);
++counter;
}
if (counter == countAjacentsNodes)
{
break;
}
}
if (arraysReturned.ContainsKey(key))
{
arraysReturned[key] += kvt.Value;
}
else
{
arraysReturned.Add(key, kvt.Value);
}
}
}
return(arraysReturned);
}
}
/// <summary>
/// Fills values in the two-dimensional array of bits which define the connectedness
/// of clusters between each other.
/// </summary>
/// <param name="treeMatrix">Two-dimensional array of bits which define the connectedness
/// of clusters between each other.</param>
/// <param name="mu">Density parameter.</param>
private void GenerateData(BitArray[][] treeMatrix, Double mu)
{
for (int currentLevel = 0; currentLevel < container.Level; ++currentLevel)
{
if (treeMatrix[currentLevel].Length > 0)
{
List <EdgesAddedOrRemoved> edgesOnCurrentLevel = new List <EdgesAddedOrRemoved>();
int branchSize = container.Branches[currentLevel][0];
int counter = 0, nodeNumber = 0;
for (int i = 0; i < treeMatrix[currentLevel].Length; i++)
{
for (int j = 0; j < treeMatrix[currentLevel][i].Length; j++)
{
if (counter == (branchSize * (branchSize - 1) / 2))
{
++nodeNumber;
counter = 0;
branchSize = container.Branches[currentLevel][nodeNumber];
}
double k = rand.NextDouble();
if (k <= (1 / Math.Pow(container.CountLeaves(currentLevel, nodeNumber), mu)))
{
treeMatrix[currentLevel][i][j] = true;
edgesOnCurrentLevel.Add(new EdgesAddedOrRemoved(i, j, true));
}
else
{
treeMatrix[currentLevel][i][j] = false;
}
++counter;
}
}
GenerationSteps.Add(edgesOnCurrentLevel);
}
}
}