POJ 1007 DNA Sorting

DNA序列排序算法
本文介绍了一种用于排序DNA序列的算法,该算法基于序列的“排序性”而非字母顺序进行排列,通过计算序列中逆序对的数量来衡量其排序程度,并使用归并排序稳定地按非递减排列。

 

DNA Sorting

Time Limit: 1000MS Memory Limit: 10000K
Total Submissions: 89359 Accepted: 35910

 

Description

One measure of ``unsortedness'' in a sequence is the number of pairs of entries that are out of order with respect to each other. For instance, in the letter sequence ``DAABEC'', this measure is 5, since D is greater than four letters to its right and E is greater than one letter to its right. This measure is called the number of inversions in the sequence. The sequence ``AACEDGG'' has only one inversion (E and D)---it is nearly sorted---while the sequence ``ZWQM'' has 6 inversions (it is as unsorted as can be---exactly the reverse of sorted). 

You are responsible for cataloguing a sequence of DNA strings (sequences containing only the four letters A, C, G, and T). However, you want to catalog them, not in alphabetical order, but rather in order of ``sortedness'', from ``most sorted'' to ``least sorted''. All the strings are of the same length. 

Input

The first line contains two integers: a positive integer n (0 < n <= 50) giving the length of the strings; and a positive integer m (0 < m <= 100) giving the number of strings. These are followed by m lines, each containing a string of length n.

Output

Output the list of input strings, arranged from ``most sorted'' to ``least sorted''. Since two strings can be equally sorted, then output them according to the orginal order.

Sample Input

10 6
AACATGAAGG
TTTTGGCCAA
TTTGGCCAAA
GATCAGATTT
CCCGGGGGGA
ATCGATGCAT

Sample Output

CCCGGGGGGA
AACATGAAGG
GATCAGATTT
ATCGATGCAT
TTTTGGCCAA
TTTGGCCAAA

 

 一样求逆序对数,根据逆序对数的数量稳定的排序(非递减),再输出DNA序列。依然是用归并排序,求逆序对数。

 

 

import java.util.Arrays;
import java.util.Scanner;

/**
 * Created by 小粤 on 2015/8/4.
 */
public class Main
{
    private static DNA[] dnas;
    private static char[] characters = new char[50];
    private static char[] aux = new char[50];

    public static void sort(int lo, int hi, int dnasIndex)
    {
        if (lo >= hi)
            return;

        int mid = (lo + hi) / 2;
        sort(lo, mid, dnasIndex);
        sort(mid + 1, hi, dnasIndex);
        merge(lo, mid, hi, dnasIndex);
    }

    private static void merge(int lo, int mid, int hi, int dnasIndex)
    {
        int i = lo, j = mid + 1;

        for (int k = lo; k <= hi; k++)
        {
            aux[k] = characters[k];
        }

        for (int k = lo; k <= hi; k++)
        {
            if (i > mid)
            {
                characters[k] = aux[j++];
            }
            else if (j > hi)
            {
                characters[k] = aux[i++];
            }
            else if (aux[j] < aux[i])
            {
                characters[k] = aux[j++];
                dnas[dnasIndex].counter += mid - i + 1;
            }
            else
            {
                characters[k] = aux[i++];
            }
        }
    }

    public static void main(String[] args)
    {
        Scanner scanner = new Scanner(System.in);

        int lengthOfStrings = scanner.nextInt();
        int numberOfStrings = scanner.nextInt();

        dnas = new DNA[numberOfStrings]; // Oh, shit! Because of Arrays.sort()..

        for (int i = 0; i < numberOfStrings; i++)
        {
            dnas[i] = new DNA();
            dnas[i].string = scanner.next();
            for (int j = 0; j < lengthOfStrings; j++)
            {
                characters[j] = dnas[i].string.charAt(j);
            }

            sort(0, lengthOfStrings - 1, i);
        }

        Arrays.sort(dnas);
        for (DNA dna : dnas)
        {
            System.out.println(dna);
        }
    }
}

class DNA implements Comparable<DNA>
{
    public String string;
    public int counter;

    @Override
    public int compareTo(DNA o)
    {
        return counter - o.counter;
    }

    @Override
    public String toString()
    {
        return string;
    }
}

 

 

 

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