public MinHeapNode BuildHuffmanTree(char[] data, int[] freq, int size)
{
MinHeapNode left, right, top;
MinHeap minHeap = CreateAndBuildMinHeap(data, freq, size);
while (!IsSizeOne(minHeap))
{
// extract two min freq items from min heap
left = ExtractMin(minHeap);
right = ExtractMin(minHeap);
top = NewNode('$', left.Freq + right.Freq);
top.Left = left;
top.Right = right;
InsertMinHeap(minHeap, top);
}
return(ExtractMin(minHeap));
}
/// <summary>
/// Runtime O(n * log(n))
/// </summary>
/// <returns>The kth smallest.</returns>
/// <param name="arr">Arr.</param>
/// <param name="k">K.</param>
public int FindKthSmallest(int[] arr, int k)
{
// push into a heap
var minHeap = new MinHeap <int>();
for (var i = 0; i < arr.Length; i++)
{
minHeap.Insert(arr[i]);
}
// what is insert run time for a heap - log(n)
var min = int.MaxValue;
for (int i = 0; i < k; i++)
{
min = minHeap.ExtractMin();
}
return(min);
}
public void MinHeapify(MinHeap minHeap, int index)
{
int smallest = index;
int left = 2 * index + 1;
int right = 2 * index + 2;
if (left < minHeap.Size && minHeap.Nodes[left].Freq < minHeap.Nodes[smallest].Freq)
{
smallest = left;
}
if (right < minHeap.Size && minHeap.Nodes[right].Freq < minHeap.Nodes[smallest].Freq)
{
smallest = right;
}
if (smallest != index)
{
SwapMinHeapNode(minHeap.Nodes, smallest, index);
MinHeapify(minHeap, smallest);
}
}
public bool IsSizeOne(MinHeap minHeap)
{
return(minHeap.Size == 1);
}
