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  • Java各种数据结构实现

    1、单向链表

    实现思路:创建Node类,包括自己的数据和指向下一个;创建Node类,包括头尾节点,实现添加、删除、输出等功能。

    tips:n = n.next不破坏链表结果,而n.next = n.next.next就等于是n节点的next属性变成了再下一个,即指向n+1个节点的指针丢失,但实际上n+1节点仍在,只不过从链表中去除。

    具体代码:

    public class NodeList<Integer> {
        class Node<Integer> {
            Node<Integer> next = null; //指向下一节点
            Integer data; //节点所存数据
            
            //Node类构造方法
            public Node(Integer d) {
                this.data = d;
            }
        }
        Node<Integer> head; //链表的头节点
        Node<Integer> last; //链表的尾节点
        int length; //链表长度
        
        //链表的无参构造方法
        public NodeList() {
            this.head = new Node<Integer>(null); //头节点为空
        }
        
        //创建链表的同时添加第一个数据
        public NodeList(Integer d) {
            this.head = new Node<Integer>(d);
            this.last = head; //此时头尾节点一样
            length++;
        }
        
        //尾部添加节点
        public void add(Integer d) {
            if (head == null) {
                head = new Node<Integer>(d);
                last = head;
                length++;
            } else {
                Node<Integer> newNode = new Node<Integer>(d);
                last.next = newNode; //令之前的尾节点指向新节点
                last = newNode; //新节点成为尾节点
                length++;
            }
        }
        
        //删除指定数据
        public boolean del(Integer d) {
            if (head == null) {
                return false;
            }
            Node<Integer> n = head; //从头开始判断
            if (n.data == d) {
                head = head.next;
                length--;
                return true;
            } 
            
            while (n.next != null) {
                if (n.next.data == d) {
                    n.next = n.next.next; //n节点指向了n+2节点
                    length--;
                    return true;
                }
                n = n.next; //正常移动不破坏链表
            }
            return false;
        }
        public void print() {
            if (head == null) {
                System.out.println("此链表为空!");
            }
            Node<Integer> n = head;
            while (n != null) {
                System.out.println(n.data+",");
                n = n.next;
            }
        }
    }
    View Code

    2016-12-13 16:22:13

    2、栈(链式结构)

    实现思路:仍然使用节点,最重要的是栈顶节点top,利用其完成压、弹栈操作。

    tips:出栈就是改栈顶为下一个,压栈就是新栈顶与原栈顶建立链接。

    具体代码:

    public class Stack {
        class Node {
            Object data;
            Node next = null;
            
            public Node(Object d) {
                this.data = d;
            }
        }
        
        Node top; //创建栈顶节点
        
        //出栈
        public Object pop() {
            if (top != null) {
                Object d = top.data;
                top = top.next; //栈顶改为下一个
                return d;
            }
            return null;
        }
        
        //压栈
        public void push(Object d) {
            Node n = new Node(d);
            n.next = top; //与原栈进行连接
            top = n;
        }
        
        //输出栈顶的元素
        public Object peek() {
            return top.data;
        }
    }
    View Code

    2016-12-14 14:14:12

    3、队列(链式结构)

    实现思路:创建首尾节点first、last,实现入队出队操作。

    tips:记得判断是否为空。

    具体代码:

    public class Queue {
        class Node {
            Object data;
            Node next;
            
            public Node(Object d) {
                this.data = d;
            }
        }
        
        //创建队首队尾指针
        Node first;
        Node last;
        
        //入队
        public void enQueue(Object d) {
            if (first == null) {
                first = new Node(d);
                last = first;
            } else {
                last.next = new Node(d); //原队尾指向新节点
                last = last.next; //更改队尾
            }
        }
        
        //出队
        public Object deQueue() {
            if (first != null) {
                Object item = first.data; //保存原队首数据
                first = first.next; //更改队首
                return item;
            }
            return null;
        }
    }
    View Code

    2016-12-14 14:27:16 

    4、树的遍历

    4.1、前序preorder

    顺序:根左右

    非递归:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Preorder in ArrayList which contains node values.
         */
        public List<Integer> preorderTraversal(TreeNode root) {
            Stack<TreeNode> stack = new Stack<TreeNode>();
            List<Integer> preorder = new ArrayList<Integer>();
            if (root == null) {
                return preorder;
            }
            stack.push(root);
            while (!stack.empty()) {
                TreeNode node = stack.pop();
                preorder.add(node.val);
                if (node.right != null) {
                    stack.push(node.right);
                }
                if (node.left != null) {
                    stack.push(node.left);
                }
            }
            return preorder;
        }
    }
    View Code

    Traverse:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Preorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> preorderTraversal(TreeNode root) {
            ArrayList<Integer> preorder = new ArrayList<Integer>();
            helper(root, preorder);
            return preorder;
        }
        private void helper(TreeNode root, ArrayList<Integer> preorder) {
            if (root == null) {
                return;
            }
            preorder.add(root.val);
            helper(root.left, preorder);
            helper(root.right, preorder);
        }
    View Code

    Divide & Conquer:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Preorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> preorderTraversal(TreeNode root) {
            ArrayList<Integer> preorder = new ArrayList<Integer>();
            if (root == null) {
                return preorder;
            }
            //Divide
            ArrayList<Integer> left = preorderTraversal(root.left);
            ArrayList<Integer> right = preorderTraversal(root.right);
            //Conquer
            preorder.add(root.val);
            preorder.addAll(left);
            preorder.addAll(right);
            return preorder;
        }
    }
    View Code

    4.2、中序inorder

    顺序:左根右

    非递归:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Inorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> inorderTraversal(TreeNode root) {
            Stack<TreeNode> stack = new Stack<TreeNode>();
            ArrayList<Integer> inorder = new ArrayList<Integer>();
            TreeNode curt = root;
            while (curt != null || !stack.empty()) {
                while (curt != null) {
                    stack.add(curt);
                    curt = curt.left;
                }
                curt = stack.peek();
                stack.pop();
                inorder.add(curt.val);
                curt = curt.right;
            }
            return inorder;
        }
    }
    View Code

    Traverse:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Inorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> inorderTraversal(TreeNode root) {
            ArrayList<Integer> inorder = new ArrayList<Integer>();
            helper(root, inorder);
            return inorder;
        }
        private void helper(TreeNode root, ArrayList<Integer> inorder) {
            if (root == null) {
                return;
            }
            helper(root.left, inorder);
            inorder.add(root.val);
            helper(root.right, inorder);
        }
    }
    View Code

    Divide & Conquer:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Inorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> inorderTraversal(TreeNode root) {
            ArrayList<Integer> inorder = new ArrayList<Integer>();
            if (root == null) {
                return inorder;
            }
            ArrayList<Integer> left = inorderTraversal(root.left);
            ArrayList<Integer> right = inorderTraversal(root.right);
            inorder.addAll(left);
            inorder.add(root.val);
            inorder.addAll(right);
            return inorder;
        }
    }
    View Code

    4.3、后序postorder

    顺序:左右根

    非递归:

    /**
     * Definition of TreeNode:
     * public class TreeNode {
     *     public int val;
     *     public TreeNode left, right;
     *     public TreeNode(int val) {
     *         this.val = val;
     *         this.left = this.right = null;
     *     }
     * }
     */
    public class Solution {
        /**
         * @param root: The root of binary tree.
         * @return: Postorder in ArrayList which contains node values.
         */
        public ArrayList<Integer> postorderTraversal(TreeNode root) {
            ArrayList<Integer> postorder = new ArrayList<Integer>();
            Stack<TreeNode> stack = new Stack<TreeNode>();
            TreeNode prev = null; //前一个遍历节点
            TreeNode curr = root;
            if (root == null) {
                return postorder;
            }
            stack.push(root);
            while (!stack.empty()) {
                curr = stack.peek();
                if (prev == null || prev.left == curr || prev.right == curr) {
                    //往下遍历
                    if (curr.left != null) {
                        stack.push(curr.left);
                    } else if (curr.right != null) {
                        stack.push(curr.right);
                    }
                } else if (curr.left == prev) {
                    //从左往上遍历
                    if (curr.right != null) {
                        stack.push(curr.right);
                    }
                } else {
                    //从右往上遍历
                    postorder.add(curr.val);
                    stack.pop();
                }
                prev = curr;
            }
            return postorder;
        }
    }
    View Code

    递归与上面一样

    2017-01-27

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  • 原文地址:https://www.cnblogs.com/kinghey-java-ljx/p/6170442.html
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