我正在解决Kattis问题Teque,并且必须实现一个teque(三端队列),只有四个操作:推到前面、推到后面、推到中间(中间)并在索引处读取项目。这个作业的重点是时间复杂度,所以我使用了一个带尾链表来轻松地在前面和后面添加元素。
对于push-to-middle函数,我没有在列表上调用size(),而是在Teque中存储了一个类变量来跟踪列表中元素的数量。这使得能够非常快速地查找。
class Teque {
public TailedLinkedList list;
public Kattio io = new Kattio(System.in, System.out);
public int numItems;
public Teque() {
this.list = new TailedLinkedList();
this.numItems = 0;
}
public void push_back(int x) {
numItems++;
list.addBack(x);
}
public void push_front(int x) {
numItems++;
list.addFront(x);
}
public void push_middle(int x) {
int median = (numItems + 1) / 2;
list.addAtIndex(median, x);
numItems++;
}
public int get(int i) {
int result = list.getItemAtIndex(i);
io.println(result);
io.flush();
return result;
}
}
TailedLinkedList的实现:
import java.util.*;
class TailedLinkedList implements ListInterface {
// attributes
public ListNode head;
public ListNode tail;
public int num_nodes;
// interface methods
// Return true if list is empty; otherwise return false.
public boolean isEmpty() { return (num_nodes == 0); }
// Return number of items in list
public int size() { return num_nodes; }
// return index of item if item is found in the list, otherwise return -1
public int indexOf(int item) {
int index = 0;
for (ListNode cur = head; cur != null; cur = cur.getNext()) {
if (cur.getItem() == item)
return index;
else
index++;
}
return -1;
}
// return true if item is in the list false otherwise
public boolean contains(int item) {
if (indexOf(item) != -1)
return true;
return false;
}
// get item at index
public int getItemAtIndex(int index) {
int counter = 0;
int item = 0;
if (index < 0 || index > size()-1) {
System.out.println("invalid index");
System.exit(1);
}
if (index == size()-1)
item = tail.getItem();
else {
for (ListNode cur = head; cur != null; cur = cur.getNext()) {
if (counter == index) {
item = cur.getItem();
break;
}
counter++;
}
}
return item;
}
// Return first item
public int getFirst() { return getItemAtIndex(0); }
// Return last item
public int getLast() { return getItemAtIndex(size()-1); }
// add item at position index, shifting all current items from index onwards to the right by 1
// pre: 0 <= index <= size()
public void addAtIndex(int index, int item) {
ListNode cur;
ListNode newNode = new ListNode(item);
if (index >= 0 && index <= size()) {
if (index == 0) // insert in front
insert(null,newNode);
else if (index == size()) // insert at the back, don't have to move all the way to the back
insert(tail,newNode);
else {
cur = getNodeAtIndex(index-1); // access node at index-1
insert(cur,newNode);
}
}
else { // index out of bounds
System.out.println("invalid index");
System.exit(1);
}
}
// Add item to front of list
public void addFront(int item) { addAtIndex(0,item); }
// Add item to back of list
public void addBack(int item) { addAtIndex(size(),item); }
// remove item at index and return it
// pre: 0 <= index < size()
public int removeAtIndex(int index) {
ListNode cur;
int item = 0;
// index within bounds and list is not empty
if (index >= 0 && index < size() && head != null) {
if (index == 0) // remove 1st item
item = remove(null);
else {
cur = getNodeAtIndex(index-1); // access node at index-1
item = remove(cur);
}
}
else { // index out of bounds
System.out.println("invalid index or list is empty");
System.exit(1);
}
return item;
}
// Remove first node of list
public int removeFront() { return removeAtIndex(0); }
// Remove last node of list
public int removeBack() { return removeAtIndex(size()-1); }
// Print values of nodes in list.
public void print() {
if (head == null)
System.out.println("Nothing to print...");
else {
ListNode cur = head;
System.out.print("List is: " + cur.getItem());
for (int i=1; i < num_nodes; i++) {
cur = cur.getNext();
System.out.print(", " + cur.getItem());
}
System.out.println(".");
}
}
// non-interface helper methods
public ListNode getHead() { return head; }
public ListNode getTail() { return tail; }
/* return the ListNode at index */
public ListNode getNodeAtIndex(int index) {
int counter = 0;
ListNode node = null;
if (index < 0 || index > size()-1) {
System.out.println("invalid index");
System.exit(1);
}
if (index == size()-1) // return tail if index == size()-1
return tail;
for (ListNode cur = head; cur != null; cur = cur.getNext()) {
if (counter == index) {
node = cur;
break;
}
counter++;
}
return node;
}
// insert newNode after the node referenced by cur
public void insert(ListNode cur, ListNode n) {
// insert in front
if (cur == null) {
n.setNext(head);
head = n; // update head
if (tail == null) // update tail if list originally empty
tail = head;
}
else { // insert anywhere else
n.setNext(cur.getNext());
cur.setNext(n);
if (cur == tail) // update tail if inserted new last item
tail = tail.getNext();
}
num_nodes++;
}
// remove the node referenced by cur.next, and return the item in the node
// if cur == null, remove the first node
public int remove(ListNode cur) {
int value;
if (cur == null) { // remove 1st node
value = head.getItem();
head = head.getNext(); // update head
if (num_nodes == 1) // update tail to null if only item in list is removed
tail = null;
}
else { // remove any other node
value = cur.getNext().getItem();
cur.setNext(cur.getNext().getNext());
if (cur.getNext() == null) // update tail if last item is removed
tail = cur;
}
num_nodes--;
return value;
}
}
然而,我的代码仍然超时(100 k行输入,限制2秒)。有没有什么地方可以立即明显地改进我的算法?时间复杂度为O(n)。
3条答案
按热度按时间8xiog9wr1#
push_midle
导致遍历列表的一半。一个解决方案是使用两个列表,前半部分和后半部分。如果列表变得不平衡,则在两个列表之间移动元素。(It ListIterator可能也会这样做;尽管对于一种幼稚的方法,必须担心ConcurrentModificationException。)
jmo0nnb32#
对Joop埃根的解决方案的修改是使用2个数组(前数组用于快速pushFront,后数组用于快速pushBack)。
有效内容:front[frontIndex.. frontMidIndex[ + back[backMidIndex .. backIndex[
pushFront:
pushBack:
pushMid(这需要更多的思考):
js4nwp543#
也许现在回答你的问题已经太晚了,但对那些正在与这个卡提斯问题作斗争的人来说,这是一个提示;
从我对数组(列表,队列,堆栈......)之间操作的理解来看,如果我们只使用类似数组的对象,那么很难保存添加/删除元素的时间,同时仍然有O(1)的时间复杂度来访问随机索引的元素。因此,我使用hashmap来达到O(1)的添加和访问复杂度。加上Joop埃根的想法,问题就可以解决了。