![]() But because the priority queue outputs largest elements first, the elements that "come before" are actually output last. Note that the Compare parameter is defined such that it returns true if its first argument comes before its second argument in a weak ordering. The standard containers std::vector (including std::vector) and std::deque satisfy these requirements.Ī Compare type providing a strict weak ordering. Additionally, it must provide the following functions with the usual semantics: The container must satisfy the requirements of SequenceContainer, and its iterators must satisfy the requirements of LegacyRandomAccessIterator. The type of the underlying container to use to store the elements. The behavior is undefined if T is not the same type as Container::value_type. If we want to peek and see the largest node in a heap quickly, that is easy.The type of the stored elements. First, we replace the root node with the last item : The new priority queue is now violent the max heap’s property where the root node is smaller than its children: Then, we swap node with the greater child until it reaches the leaf or greater than both children: Now, is greater than its child of, we stop and reach our priority queue: The following code shows the details of the deletion function: ![]() Now, let’s apply to an example to understand how this process works. ![]() It keeps moving down the tree until the heap property is restored. Then, this item is compared with the child nodes and swap with the greater one. When removing the root node, we replace it with the last item of the priority queue. Next, we can remove the maximum element from the priority queue. As we know, the root node is the item with the highest priority in a max heap. If we add to the priority queue, we end up with: We notice that is greater than its parent, so we swap them: Then, is still greater than its new parent, so we swap them: Now, we notice that is smaller than its parent, so we stop and reach our priority queue: The following code shows the details of the insertion function: Let’s go through an example to understand the insertion process. This process continues until the new item is placed in the correct position. If it is found greater than its parent node, elements are swapped. At first, we insert the new item at the end of the priority queue. If we want to add a new node to a binary heap, we need to ensure that our two properties of the heap are maintained after the new node is added. The item at the root of the heap has the highest priority among all elements. ![]() We’ll use a binary heap to maintain a max-priority queue. The common operations that we can perform on a priority queue include insertion, deletion, and peek.
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