单链表C ++的Lomuto分区方案

问题描述 投票:1回答:2

我需要一种算法,可以找到线性时间复杂度O(n)和恒定空间复杂度O(1)中单链表的中位数。

编辑:单链接列表是C样式的单链接列表。不允许stl(没有容器,没有函数,禁止所有stl,例如没有std :: forward_list)。不允许将数字移动到任何其他容器(如数组)中。O(logn)的空间复杂度是可以接受的,因为对于我的列表来说,实际上甚至小于100。另外,我也不允许使用STL函数,例如nth_element

[基本上,我将链表与3 * 10 ^ 6元素相连,我需要在3秒内获得中值,所以我不能使用排序算法对列表进行排序(这将是O(nlogn),并且将大概10到14秒。

我已经在网上进行了一些搜索,发现可以通过quickselect在O(n)和O(1)空间完全性中找到std :: vector的中位数(最坏的情况是在O(n ^ 2)中,但很少),例如:https://www.geeksforgeeks.org/quickselect-a-simple-iterative-implementation/

但是我找不到用于链表的算法。问题是我可以使用数组索引随机访问向量。如果我想修改该算法,那么复杂度会更大,因为。例如,当我将数据透视索引更改为左侧时,我实际上需要遍历列表以获取该新元素并走得更远(这将使我至少O(kn)的列表中有一个大k,甚至推动O(n ^ 2)...)。

编辑2:

我知道我有太多的变量,但是我一直在测试不同的东西,而我仍在编写代码...我当前的代码:

#include <bits/stdc++.h>

using namespace std;

template <class T> class Node {
    public:
    T data;
    Node<T> *next;
};

template <class T> class List {
    public:
    Node<T> *first;
};

template <class T> T getMedianValue(List<T> & l) {
    Node<T> *crt,*pivot,*incpivot;
    int left, right, lung, idx, lungrel,lungrel2, left2, right2, aux, offset;
    pivot = l.first;
    crt = pivot->next;
    lung = 1;
//lung is the lenght of the linked list (yeah it's lenght in romanian...)
//lungrel and lungrel2 are the relative lenghts of the part of 
//the list I am processing, e.g: 2 3 4 in a list with 1 2 3 4 5
    right = left = 0;
    while (crt != NULL) { 
        if(crt->data < pivot->data){
            aux = pivot->data;
            pivot->data = crt->data;
            crt->data = pivot->next->data;
            pivot->next->data = aux;
            pivot = pivot->next;
            left++;
        }
        else right++;
       // cout<<crt->data<<endl;
        crt = crt->next; 
        lung++; 
    }
    if(right > left) offset = left;
//  cout<<endl;
//  cout<<pivot->data<<" "<<left<<" "<<right<<endl;
//  printList(l);
//  cout<<endl;
    lungrel = lung;
    incpivot = l.first;
   // offset = 0;
    while(left != right){
        //cout<<"parcurgere"<<endl;
        if(left > right){
            //cout<<endl;
            //printList(l);
            //cout<<endl;
            //cout<<"testleft "<<incpivot->data<<" "<<left<<" "<<right<<endl;
            crt = incpivot->next;
            pivot = incpivot;
            idx = offset;left2 = right2 = lungrel = 0;
            //cout<<idx<<endl;
            while(idx < left && crt!=NULL){
                 if(pivot->data > crt->data){
                   //  cout<<"1crt "<<crt->data<<endl;
                     aux = pivot->data;
                     pivot->data = crt->data;
                     crt->data = pivot->next->data;
                     pivot->next->data = aux;
                     pivot = pivot->next;
                     left2++;lungrel++;
                  }
                  else {
                      right2++;lungrel++;
                      //cout<<crt->data<<" "<<right2<<endl;
                  }
                  //cout<<crt->data<<endl;
                  crt = crt->next;
                  idx++;
             }
             left = left2 + offset;
             right = lung - left - 1;
             if(right > left) offset = left;
             //if(pivot->data == 18) return 18;
             //cout<<endl;
             //cout<<"l "<<pivot->data<<" "<<left<<" "<<right<<" "<<right2<<endl;
           //  printList(l);
        }
        else if(left < right && pivot->next!=NULL){
            idx = left;left2 = right2 = 0;
            incpivot = pivot->next;offset++;left++;
            //cout<<endl;
            //printList(l);
            //cout<<endl;
            //cout<<"testright "<<incpivot->data<<" "<<left<<" "<<right<<endl;
            pivot = pivot->next;
            crt = pivot->next;
            lungrel2 = lungrel;
            lungrel = 0;
           // cout<<"p right"<<pivot->data<<" "<<left<<" "<<right<<endl;
            while((idx < lungrel2 + offset - 1) && crt!=NULL){
                 if(crt->data < pivot->data){
                //     cout<<"crt "<<crt->data<<endl;
                     aux = pivot->data;
                     pivot->data = crt->data;
                     crt->data = (pivot->next)->data;
                     (pivot->next)->data = aux;
                     pivot = pivot->next;
                 //    cout<<"crt2 "<<crt->data<<endl;
                     left2++;lungrel++;
                  }
                  else right2++;lungrel++;
                  //cout<<crt->data<<endl;
                  crt = crt->next;
                  idx++;
             }
             left = left2 + left;
             right = lung - left - 1;
                 if(right > left) offset = left;
            // cout<<"r "<<pivot->data<<" "<<left<<" "<<right<<endl;
           //  printList(l);
        }
        else{
            //cout<<cmx<<endl;
            return pivot->data;
        }
    }
    //cout<<cmx<<endl;
    return pivot->data;
}
template <class T> void printList(List<T> const & l) {
    Node<T> *tmp;
    if(l.first != NULL){
        tmp = l.first;
        while(tmp != NULL){
            cout<<tmp->data<<" ";
            tmp = tmp->next;
        }
    }
}
template <class T> void push_front(List<T> & l, int x)
{
    Node<T>* tmp = new Node<T>;

    tmp->data = x;

    tmp->next = l.first;
    l.first = tmp;
}

int main(){
    List<int> l;
    int n = 0;
    push_front(l, 19);
    push_front(l, 12);
    push_front(l, 11);
    push_front(l, 101);
    push_front(l, 91);
    push_front(l, 21);
    push_front(l, 9);
    push_front(l, 6);
    push_front(l, 25);
    push_front(l, 4);
    push_front(l, 18);
    push_front(l, 2);
    push_front(l, 8);
    push_front(l, 10);
    push_front(l, 200);
    push_front(l, 225);
    push_front(l, 170);
    printList(l);
    n=getMedianValue(l);
    cout<<endl;
    cout<<n;

    return 0;
}

您是否对如何使quickselect适应可能适用于我的问题的单列出的链接或其他算法有任何建议?

c++ list median quickselect nth-element
2个回答
1
投票

在您的问题中,您提到您无法将枢轴向左移动,因为这需要遍历列表。如果正确执行,则只需遍历整个列表两次:

  1. 一次查找列表的中间和结尾以便选择一个好的枢轴(例如,使用"median-of-three"规则)
  2. 一次进行实际排序

如果您不太在乎选择一个好的枢轴,并且很高兴只选择列表的第一个元素作为枢轴(这会导致最坏的情况,O(n ^ 2)time complexity,则第一步不是必需的)如果数据已经排序)。

如果您第一次记住列表的末尾时,通过维护指向末尾的指针,则不必再遍历该列表来查找末尾。另外,如果您使用的是标准Lomuto partition scheme(出于以下原因我没有使用),则还必须在列表中维护两个指针,它们代表标准Lomuto分区的ij索引方案。通过使用这些指针,应该永远不必遍历列表来访问单个元素。

此外,如果您维护了指向每个分区的中间和结尾的指针,那么当您以后必须对这些分区之一进行排序时,您将不必再次遍历该分区来找到中间和结尾。

我现在为链表创建了我自己的QuickSelect算法实现,下面已发布。

由于您说过链表是单链表,不能升级为双链表,所以我不能使用Hoare partition scheme,因为向后迭代单链表非常昂贵。因此,我改用效率通常较低的Lomuto partition scheme

[使用Lomuto分区方案时,通常选择第一个元素或最后一个元素作为枢轴。但是,选择其中任何一个都有缺点,即排序的数据将导致算法的最坏情况时间复杂度为O(n ^ 2)。可以通过根据"median-of-three" rule选择枢轴来防止这种情况,即从第一个元素,中间元素和最后一个元素的中值中选择一个枢轴。因此,在我的实现中,我使用的是“三个中位数”规则。

而且,Lomuto分区方案通常会创建两个分区,一个分区用于小于枢轴的值,一个分区用于大于或等于枢轴的值。但是,如果所有值都相同,这将导致O(n ^ 2)的最坏情况下的时间复杂度。因此,在我的实现中,我将创建三个分区,一个分区用于小于枢轴的值,一个分区用于大于枢轴的值,一个分区用于与枢轴相同的值。

尽管这些措施并未完全消除O(n ^ 2)在最坏情况下的时间复杂性的可能性,但至少使它变得极不可能。

[我遇到的一个重要问题是,对于偶数个元素,median定义为两个“中间”或“中间”元素的arithmetic mean。因此,我不能简单地调用函数find_nth_element,因为例如,如果元素总数为14,那么我将寻找第7位和第8位最大的元素。这意味着我将不得不两次调用这样的函数,这样效率低下。因此,我改写了一个可以一次搜索两个“中位数”元素的函数。尽管这使代码更加复杂,但是与不必两次调用同一函数的优点相比,由于附加的代码复杂度而导致的性能损失应最小。

[请注意,尽管我的实现可以在C ++编译器上完美地编译,但是由于不允许使用C ++标准模板库中的任何内容的限制,我不会将其称为教科书C ++代码。因此,我的代码是C代码和C ++代码的混合体。

#include <iostream>
#include <iomanip>
#include <cassert>

//remove the comment in the following line for extra debugging information
//#define PRINT_DEBUG_INFO

template <typename T>
struct Node
{
    T data;
    Node<T> *next;
};

// NOTE:
// The return type is not necessarily the same as the data type. The reason for this is
// that, for example, the data type "int" requires a "double" as a return type, so that 
// the arithmetic mean of "3" and "6" returns "4.5".
// This function may require template specializations to handle overflow or wrapping.
template<typename T, typename U>
U arithmetic_mean( const T &first, const T &second )
{
    return ( static_cast<U>(first) + static_cast<U>(second) ) / 2;
}

//the main loop of the function find_median can be in one of the following three states
enum LoopState
{
    //we are looking for one median value
    LOOPSTATE_LOOKINGFORONE,

    //we are looking for two median values, and the returned median
    //will be the arithmetic mean of the two
    LOOPSTATE_LOOKINGFORTWO,

    //one of the median values has been found, but we are still searching for
    //the second one
    LOOPSTATE_FOUNDONE
};

template <
    typename T, //type of the data
    typename U  //type of the return value
>
U find_median( Node<T> *list )
{
    //This variable points to the pointer to the first element of the current partition.
    //During the partition phase, the linked list will be broken and reassembled afterwards, so
    //the pointer this pointer points to will be nullptr until it is reassembled.
    Node<T> **pp_start = &list;

    //these pointer are maintained for accessing the middle of the list for selecting a pivot using
    //the "median-of-three" rule
    Node<T> *p_middle;
    Node<T> *p_end;

    //result is not defined if list is empty
    assert( *pp_start != nullptr );

    //in the main loop, this variable always holds the number of elements in the current partition
    int num_total = 1;

    // First, we must traverse the entire linked list in order to determine the number of elements,
    // in order to calculate k1 and k2. If it is odd, then the median is defined as the k'th smallest
    // element where k = n / 2. If the number of elements is even, then the median is defined as the
    // arithmetic mean of the k'th element and the (k+1)'th element.
    // We also set a pointer to the nodes in the middle and at the end, which will be required later
    // for selecting a pivot according to the "median-of-three" rule.
    p_middle = *pp_start;
    for ( p_end = *pp_start; p_end->next != nullptr; p_end = p_end->next )
    {
        num_total++;
        if ( num_total % 2 == 0 ) p_middle = p_middle->next;
    }   

    // find out whether we are looking for only one or two median values
    enum LoopState loop_state = num_total % 2 == 0 ? LOOPSTATE_LOOKINGFORTWO : LOOPSTATE_LOOKINGFORONE;

    //set k to the index of the middle element, or if there are two middle elements, to the left one
    int k = ( num_total - 1 ) / 2;

    //if we are looking for two median values, but we have only found one, then this variable will
    //hold the value of the one we found whether we have found one can be determined by the state of
    //the variable loop_state
    T val_found;

    for (;;)
    {
        assert( *pp_start != nullptr );
        assert( p_middle  != nullptr );
        assert( p_end     != nullptr );
        assert( num_total != 0 );

        if ( num_total == 1 )
        {
            switch ( loop_state )
            {
            case LOOPSTATE_LOOKINGFORONE:
                return (*pp_start)->data;
            case LOOPSTATE_FOUNDONE:
                return arithmetic_mean<T,U>( val_found, (*pp_start)->data );
            default:
                assert( false ); //this should be unreachable
            }
        }

        //select the pivot according to the "median-of-three" rule
        T pivot;
        if ( (*pp_start)->data < p_middle->data )
        {
            if ( p_middle->data < p_end->data )
                pivot = p_middle->data;
            else if ( (*pp_start)->data < p_end->data )
                pivot = p_end->data;
            else
                pivot = (*pp_start)->data;
        }
        else
        {
            if ( (*pp_start)->data < p_end->data )
                pivot = (*pp_start)->data;
            else if ( p_middle->data < p_end->data )
                pivot = p_end->data;
            else
                pivot = p_middle->data;
        }


        // We will be dividing the current partition into 3 new partitions (less-than,
        // equal-to and greater-than) each represented as a linked list. Each list
        // requires a pointer to the start of the list and a pointer to the pointer at
        // the end of the list to write the address of new elements to. Also, when
        // traversing the lists, we need to keep a pointer to the middle of the list,
        // as this information will be required for selecting a new pivot in the next
        // iteration of the loop. The latter is not required for the equal-to partition,
        // as it would never be used.
        Node<T> *p_less    = nullptr, **pp_less_end    = &p_less,    **pp_less_middle    = &p_less;
        Node<T> *p_equal   = nullptr, **pp_equal_end   = &p_equal;
        Node<T> *p_greater = nullptr, **pp_greater_end = &p_greater, **pp_greater_middle = &p_greater;

        // These pointers are only used as a cache to the location of end node. Despite
        // their similar name, their function is very different to pp_less_end and 
        // pp_greater_end.
        Node<T> *p_less_end    = nullptr;
        Node<T> *p_greater_end = nullptr;

        // counter for the number of elements in each partition
        int num_less = 0;
        int num_equal = 0;
        int num_greater = 0;

        // NOTE:
        // The following loop will temporarily split the linked list. It will be merged later.
        Node<T> *p_next_node = *pp_start;
        *pp_start = nullptr;
        for ( int a = 0; a < num_total; a++ )
        {
            assert( p_next_node != nullptr );

            Node<T> *p_current_node = p_next_node;
            p_next_node = p_next_node->next;

            if ( p_current_node->data < pivot )
            {
                //link node to pp_less
                assert( *pp_less_end == nullptr );
                *pp_less_end = p_current_node;
                pp_less_end = &p_current_node->next;
                p_current_node->next = nullptr;

                num_less++;
                if ( num_less % 2 == 0 )
                {
                    pp_less_middle = &(*pp_less_middle)->next;
                }

                //setting this variable is only done for caching purposes and is not
                //directly related to the logic of the other variable pp_less_end
                p_less_end = p_current_node;
            }
            else if ( p_current_node->data == pivot )
            {
                //link node to pp_equal
                assert( *pp_equal_end == nullptr );
                *pp_equal_end = p_current_node;
                pp_equal_end = &p_current_node->next;
                p_current_node->next = nullptr;

                num_equal++;
            }
            else
            {
                //link node to pp_greater
                assert( *pp_greater_end == nullptr );
                *pp_greater_end = p_current_node;
                pp_greater_end = &p_current_node->next;
                p_current_node->next = nullptr;

                num_greater++;
                if ( num_greater % 2 == 0 )
                {
                    pp_greater_middle = &(*pp_greater_middle)->next;
                }

                //setting this variable is only done for caching purposes and is not
                //directly related to the logic of the other variable pp_greater_end
                p_greater_end = p_current_node;
            }
        }

        assert( num_total == num_less + num_equal + num_greater );

#ifdef PRINT_DEBUG_INFO
        //when PRINT_DEBUG_INFO is defined, it will print the length of all partitions and their contents
        {
            Node<T> *p;
            std::cout << std::setfill( '0' );
            std::cout << "partition lengths: ";
            std::cout <<
                std::setw( 2 ) << num_less    << " " <<
                std::setw( 2 ) << num_equal   << " " <<
                std::setw( 2 ) << num_greater << " " <<
                std::setw( 2 ) << num_total   << "\n";
            std::cout << "less: ";
            for ( p = p_less; p != nullptr; p = p->next ) std::cout << p->data << " ";
            std::cout << "\nequal: ";
            for ( p = p_equal; p != nullptr; p = p->next ) std::cout << p->data << " ";
            std::cout << "\ngreater: ";
            for ( p = p_greater; p != nullptr; p = p->next ) std::cout << p->data << " ";
            std::cout << "\n\n" << std::flush;
        }
#endif

        //insert less-than partition into list
        assert( *pp_start == nullptr );
        *pp_start = p_less;

        //insert equal-to partition into list
        assert( *pp_less_end == nullptr );
        *pp_less_end = p_equal;

        //insert greater-than partition into list
        assert( *pp_equal_end == nullptr );
        *pp_equal_end = p_greater;

        //link list to previously cut off part
        assert( *pp_greater_end == nullptr );
        *pp_greater_end = p_next_node;

        //if less-than partition is large enough to hold both possible median values
        if ( k + 2 <= num_less )
        {
            //set the next iteration of the loop to process the less-than partition
            //pp_start is already set to the desired value
            p_middle = *pp_less_middle;
            p_end = p_less_end;
            num_total = num_less;
        }

        //else if less-than partition holds one of both possible median values
        else if ( k + 1 == num_less )
        {
            if ( loop_state == LOOPSTATE_LOOKINGFORTWO )
            {
                //the equal_to partition never needs sorting, because all members are already equal
                val_found = p_equal->data;
                loop_state = LOOPSTATE_FOUNDONE;
            }
            //set the next iteration of the loop to process the less-than partition
            //pp_start is already set to the desired value
            p_middle = *pp_less_middle;
            p_end = p_less_end;
            num_total = num_less;
        }

        //else if equal-to partition holds both possible median values
        else if ( k + 2 <= num_less + num_equal )
        {
            //the equal_to partition never needs sorting, because all members are already equal
            return p_equal->data;
        }

        //else if equal-to partition holds one of both possible median values
        else if ( k + 1 == num_less + num_equal )
        {
            switch ( loop_state )
            {
            case LOOPSTATE_LOOKINGFORONE:
                return p_equal->data;
            case LOOPSTATE_LOOKINGFORTWO:
                val_found = p_equal->data;
                loop_state = LOOPSTATE_FOUNDONE;
                k = 0;
                //set the next iteration of the loop to process the greater-than partition
                pp_start = pp_equal_end;
                p_middle = *pp_greater_middle;
                p_end = p_greater_end;
                num_total = num_greater;
                break;
            case LOOPSTATE_FOUNDONE:
                return arithmetic_mean<T,U>( val_found, p_equal->data );
            }
        }

        //else both possible median values must be in the greater-than partition
        else
        {
            k = k - num_less - num_equal;

            //set the next iteration of the loop to process the greater-than partition
            pp_start = pp_equal_end;
            p_middle = *pp_greater_middle;
            p_end = p_greater_end;
            num_total = num_greater;
        }
    }
}


// NOTE:
// The following code is not part of the algorithm, but is only intended to test the algorithm

template <typename T>
class List
{
public:
    List() : first( nullptr ) {}

    // the following is required to abide by the rule of three/five/zero
    // see: https://en.cppreference.com/w/cpp/language/rule_of_three
    List( const List<T> & ) = delete;
    List( const List<T> && ) = delete;
    List<T>& operator=( List<T> & ) = delete;
    List<T>& operator=( List<T> && ) = delete;

    ~List()
    {
        Node<T> *p = first;

        while ( p != nullptr )
        {
            Node<T> *temp = p;
            p = p->next;
            delete temp;
        }
    }

    void push_front( int data )
    {
        Node<T>* tmp = new Node<T>;

        tmp->data = data;

        tmp->next = first;
        first = tmp;
    }

    //member variables
    Node<T> *first;
};

int main()
{
    List<int> l;

    int unsorted_data[] = { 6, 19, 3, 7, 4, 9, 8, 2, 18, 4, 10, 11, 12, 10 };

    //create singly-linked list
    for ( int i = 0; i < sizeof( unsorted_data ) / sizeof( *unsorted_data ); i++ ) l.push_front( unsorted_data[i] );

    std::cout << "The median is: " << std::setprecision(10) << find_median<int,double>( l.first ) << std::endl;

    return 0;
}

我已经成功地使用一百万个随机生成的元素测试了我的代码,并且它几乎立即找到了正确的中位数。

所以您可以做的是使用迭代器来保持职位。我已经编写了上面与std :: forward_list一起使用的算法。我知道这不是完美的方法,但请尽快写下来,希望对您有所帮助。

    int partition(int leftPos, int rightPos, std::forward_list<int>::iterator& currIter, 
    std::forward_list<int>::iterator lowIter, std::forward_list<int>::iterator highIter) {
        auto iter = lowIter;
        int i = leftPos - 1;
        for(int j = leftPos; j < rightPos - 1; j++) {
           if(*iter <= *highIter) {
               ++currIter;
               ++i;
               std::iter_swap(currIter, iter);
           }
           iter++;
        }
        std::forward_list<int>::iterator newIter = currIter;
        std::iter_swap(++newIter, highIter);
        return i + 1;
    }

   std::forward_list<int>::iterator kthSmallest(std::forward_list<int>& list, 
   std::forward_list<int>::iterator left, std::forward_list<int>::iterator right, int size, int k) {
       int leftPos {0};
       int rightPos {size};
       int pivotPos {0};

       std::forward_list<int>::iterator resetIter = left;
       std::forward_list<int>::iterator currIter = left;
       ++left;
       while(leftPos <= rightPos) {
           pivotPos = partition(leftPos, rightPos, currIter, left, right);

           if(pivotPos == (k-1)) {
               return currIter;
           } else if(pivotPos > (k-1)) {
               right = currIter;
               rightPos = pivotPos - 1;
           } else {
               left = currIter;
               ++left;
               resetIter = left;
               ++left;
               leftPos = pivotPos + 1;
           }

           currIter = resetIter;
       }

       return list.end();
  }

调用第k个iter时,左迭代器应比您打算开始的地方小一个。这使我们可以在low中的partition()后面排名第一。这是一个执行它的例子:

int main() {
    std::forward_list<int> list {10, 12, 12, 13, 4, 5, 8, 11, 6, 26, 15, 21};
    auto startIter = list.before_begin();
    int k = 6;
    int size = getSize(list);

    auto kthIter = kthSmallest(list, startIter, getEnd(list), size - 1, k);
    std::cout << k << "th smallest: " << *kthIter << std::endl;

    return 0;
}

第六最小:10


1
投票

所以您可以做的是使用迭代器来保持职位。我已经编写了上面与std :: forward_list一起使用的算法。我知道这不是完美的方法,但请尽快写下来,希望对您有所帮助。

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