return currentSize == 0;

   }

   //插入一个节点

   public boolean insert(int key) {

      if(currentSize == maxSize) return false; //已满 不能插入

      Node newNode = new Node(key);

      heapArray[currentSize] = newNode; //先插入到最后

      trickleUp(currentSize++);   //从该节点开始向上筛选，并把currentSize的值加1

      return true;

   }

   //删除一个最大节点(根)

      public Node remove() {

         Node root = heapArray[0];//移除根节点

         heapArray[0] = heapArray[--currentSize];//最后一个节点移动到根节点的位置

         trickleDown(0); //向下筛选

         return root;

      }

   //向上筛选

   private void trickleUp(int index) {

      int parent = (index-1)/2;      //先找到父节点索引

      Node bottom = heapArray[index];

      while(index >0 && heapArray[parent].getKey() < bottom.getKey()) {

         //只要index>0且父节点的数据项的值小于自己的值 就继续向上

         heapArray[index] = heapArray[parent];

         index = parent;

         parent = (index-1)/2;

      }

      heapArray[index] = bottom;

   }

   //向下筛选

   private void trickleDown(int index) {

      int largeChild;

      Node top = heapArray[index];

      while(index < currentSize/2) { //只要不是叶节点  就继续向下筛选

         //首先获得其左右孩子节点中数值大的那个节点的下标

         int left = index*2+1;

         int right = index*2+2;

         if(right < currentSize && heapArray[left].getKey() < heapArray[right].getKey()) {

            largeChild = right;

         }else {

            largeChild = left;

         }

         //进行值的比较，把值大的子节点与该节点互换，并对值最大的那个节点再继续向下筛选

         if(top.getKey() >= heapArray[largeChild].getKey()) break;

         else {

            heapArray[index] = heapArray[largeChild];

            index  = largeChild;