int main(int argc, char *argv[])
{
int input;
bool isMaxHeap = true, isMinHeap = false;
std::printf("Test MaxHeap\n");
Heap <int> MaxHeap(50, isMaxHeap);
for (int i = 0; i < 30; i++) {
MaxHeap.Push(i*2+3);
}
std::printf("Top = %d\n", MaxHeap.Top());
for (int i = 0; i < 5; i++) {
MaxHeap.Pop();
std::printf("Top = %d\n", MaxHeap.Top());
}
std::putchar(10);
std::printf("Test MinHeap\n");
Heap <int> MinHeap(50, isMinHeap);
for (int i = 0; i < 30; i++) {
MinHeap.Push(i*2+3);
}
std::printf("Top = %d\n", MinHeap.Top());
for (int i = 0; i < 5; i++) {
MinHeap.Pop();
std::printf("Top = %d\n", MinHeap.Top());
}
return 0;
}
int Merge (int arrays[][4], int k, int n, int result[])
{
int i=0, j=0, r=0;
HeapNode *node = NULL, *minnode = NULL;
Heap *h = NULL;
init_heap (&h, k);
for (i=0; i<k; i++) {
node = newnode();
node->data = arrays[i][0];
node->array = i;
node->index = 1;
HeapAdd (h, node, i);
}
MinHeap (h);
r = 0;
for (i=0; i<n*k; i++) {
minnode = getMin (h);
result[r++] = minnode->data;
if (minnode->index < n) {
minnode->data = arrays[minnode->array][minnode->index];
minnode->index++;
} else {
minnode->data = MAX;
}
MinHeapify (h, 0);
}
return 0;
}
int GetEdge( int CurrentSize )
{ /* 给定当前堆的大小CurrentSize，将当前最小边位置弹出并调整堆 */
struct EdgeType temp;
/* 将最小边与当前堆的最后一个位置的边交换 */
temp = ESet[0];
ESet[0] = ESet[CurrentSize-1];
ESet[CurrentSize-1] = temp;
/* 将剩下的边继续调整成最小堆 */
MinHeap(0, CurrentSize-1);
return CurrentSize-1; /* 返回最小边所在位置 */
}
/*
Creates the Huffman tree reusing the given HuffmanNodes.
nodes: an array of HuffmanNode*
length: the length of nodes array
returns: the pointer to the root of the huffman tree
*/
HuffmanNode *genHuffmanTree(HuffmanNode **nodes, int length) {
MinHeap min = MinHeap(nodes, length);//create the array with minHeap constructor
while (min.heapSize > 1)//it will run until the array has size one
{
HuffmanNode *L, *R;//we make the nodes for left and right
L = min.extractMin();//we extract the min from the heap and assign it to left
R = min.extractMin();//we do the same for the right
HuffmanNode *internal = new HuffmanNode(L->frequency + R->frequency, L, R);//we create an internal node with the sum of the frequency left and right.
//we also assign left and right to be child of internal
min.insert(internal);//we insert the internal node back into the heap
}
return min.extractMin();//we extract the min but since we only got one element left in the array, this should be the root.
}
void
klargest (int arr[], int n, int k)
{
if (n <= 0 || k <= 0 || n < k ) return;
int i = 0, min = 0;
Heap *h = NULL;
init_heap (&h, k);
for (i=0; i<k; i++) {
AddHeap (h, arr[i], i);
}
MinHeap (h);
for (; i<n; i++) {
Heapmin (h, &min);
if (arr[i] > min) {
ReplaceMin (h, arr[i]);
MinHeapify (h, 0);
}
}
printHeap (h);
return;
}
void InitializeESet ( int M )
{ /* 初始化最小堆 */
int i;
for (i=M/2; i>=0; i--) MinHeap(i, M);
}