算法找到的最大差异在一系列的数字

Question

我有一系列的几百万数字。

double* const data = new double (3600000);

我需要迭代过阵列，并找到的范围(最大值阵列中减去最小值)。然而，有一个陷阱。我只想找到的范围，其中最小和最大值在1 000个样本。

所以我需要找到的最大值：范围(数据+0、数据+1000)、范围(数据+1、数据+1001)、范围(数据+2、数据+1002),...., 范围(数据+3599000、数据+3600000).

我希望这是有道理的。基本上我可以做它喜欢上面的，但是我在寻找一个更有效率的算法，如果一个存在。我认为上面的算法是O(n)，但我觉得这是可能的最优化。一个想法我玩是跟踪最近的最大值和最小值和多远回他们，那么只有走回头路的时候有必要的。

我会编码这C++，但一个很好的算法在伪码会就好了。此外，如果这个数字我试图找到有一个名称，我想知道它是什么。

谢谢。

Answer 1

你描述的算法实际上是O（N），但我认为常数太高了。另一个看起来合理的解决方案是使用O（N * log（N））算法，方法如下：

* create sorted container (std::multiset) of first 1000 numbers
* in loop (j=1, j<(3600000-1000); ++j)
   - calculate range
   - remove from the set number which is now irrelevant (i.e. in index *j - 1* of the array)
   - add to set new relevant number  (i.e. in index *j+1000-1* of the array)

我认为它应该更快，因为常数要低得多。

Answer 2

这种类型的问题属于一个分支的算法被称为流算法。这是该研究的问题，需要不只一个O(n)的解决方案，但也需要工作在一个单一的传过来的数据。数据输入作为一个流算，算法可以救不了所有的数据，然后，然后就永远失去了。算法需要得到一些答案有关的数据，例如最低或中位数。

具体而言你是在寻找一个最大的(或者更常见的文学-最小)，在一个窗口，通过一个流。

这里的一个演示 在一个 文章 提到这个问题作为一个分问题是什么，他们正在试图获得。它可能会给你一些想法。

我认为，概要的解决方案是类似的东西-保持窗口在流在每个步骤中的一个元件是插入到窗口和一是从另一侧面(一个滑动窗口)。该项目实际上保持存在并不是所有的1000个项目在窗口，但所选的代表都会好的候选人是最低的(或最大值)。

阅读的文章。它的升技复杂的，但后2-3读你可以得到它的窍门。

Answer 3

这是 min-queue 的良好应用 - 一个队列（First-In，First-Out = FIFO），它可以同时跟踪它所包含的最小元素，并且具有摊销的常数 - 时间更新。当然，最大队列基本上是相同的。

一旦你有了这个数据结构，你可以考虑CurrentMax（过去1000个元素）减去CurrentMin，将其存储为BestSoFar，然后推送一个新值并弹出旧值，然后再次检查。这样，不断更新BestSoFar，直到最终值成为您问题的解决方案。每一步都需要摊销常数时间，所以整个事情是线性的，我所知道的实现有一个很好的标量常数（它很快）。

我不知道有关min-queue的任何文档 - 这是我与同事合作提出的数据结构。您可以通过在内部跟踪数据的每个连续子序列中的最少元素的二叉树来实现它。它简化了您只能从结构的一端弹出数据的问题。

如果您对更多细节感兴趣，我可以尝试提供它们。我正在考虑将这个数据结构写成arxiv的论文。另请注意，Tarjan和其他人之前已经建立了一个更强大的min-deque结构，可以在这里工作，但实现起来要复杂得多。您可以 google for“mindeque”阅读有关Tarjan等人的工作。

Answer 4

std::multiset<double> range;
double currentmax = 0.0;
for (int i = 0;  i < 3600000;  ++i)
{
    if (i >= 1000)
        range.erase(range.find(data[i-1000]));
    range.insert(data[i]);
    if (i >= 999)
        currentmax = max(currentmax, *range.rbegin());
}

注意未经测试的代码。

编辑：修复了一个错误。

Answer 5

1. 读入前1000个数字。
2. 创建一个跟踪当前1000号码的1000元素链接列表。
3. 创建一个指向链接列表节点的指针的1000个元素数组，1-1映射。
4. 根据链表节点的值对指针数组进行排序。这将重新排列数组，但保持链表完好无损。
5. 现在可以通过检查指针数组的第一个和最后一个元素来计算前1000个数字的范围。
6. 删除第一个插入的元素，可以是头部或尾部，具体取决于您创建链接列表的方式。使用节点的值对指针数组执行二进制搜索，以找到要删除的节点的指针，并将数组移一遍以将其删除。
7. 将第1001个元素添加到链接列表，并通过执行插入排序的一个步骤，将指针插入到数组中的正确位置。这将使数组保持排序。
8. 现在你有了分钟。最多1到1001之间的数字值，可以使用指针数组的第一个和最后一个元素计算范围。
9. 现在应该明白你需要为数组的其余部分做些什么。

算法应为O（n），因为删除和插入受log（1e3）限制，其他一切都需要恒定时间。

Answer 6

我决定看什么最有效的算法我可以想到的了解决这个问题是使用实际代码和实际时间安排。我首先创建了一个简单的解决方案，一个轨道的最低/最高于以前的条目采用一个圆形的缓冲器和测试装置来测量速度。在简单的解决方案，每个数据价值对比的设置的最低/最高价值，所以这是关于window_size*计测试(这里窗的大小于原来的问题是1000和数3600000).

然后我想到如何使它更快。首先，我创造了一个解决方案，使用先进先出的队列储存window_size价值观和一个链表以储存值上升了其中每个节点的联系名单也是一个节点在队列中。处理数据的价值，该项目结束时的先进先出是从链表和队列中。新的价值加入到队列和一个线索是用于查找位置在的联系名单。最小和最大价值，然后可以从中读取的开始和结束的联系名单。这是快速的，但不会规模与增加window_size(即线性).

所以我决定添加一个二元树的系统尝试加速搜索的一部分算法。最后的时间window_size=1000和count=3600000是：

Simple: 106875
Quite Complex: 1218
Complex: 1219

这既是预期和意外。预计在使用排序链表的帮助下，意想不到的在于开销的具有自我平衡的树没有抵消优势的一个快速搜索。我尝试后两个增加窗的大小和发现总是几乎完全相同的一window_size的100000.

这一切都显示，得出结论：大约算法是一回事，执行是另一回事。

无论如何，对于那些有兴趣，这里的代码我写了(有相当一点!):

范围。h:

#include <algorithm>
#include <iostream>
#include <ctime>

using namespace std;

//  Callback types.
typedef void (*OutputCallback) (int min, int max);
typedef int (*GeneratorCallback) ();

//  Declarations of the test functions.
clock_t Simple (int, int, GeneratorCallback, OutputCallback);
clock_t QuiteComplex (int, int, GeneratorCallback, OutputCallback);
clock_t Complex (int, int, GeneratorCallback, OutputCallback);

main.cpp:

#include "Range.h"

int
  checksum;

//  This callback is used to get data.
int CreateData ()
{
  return rand ();
}

//  This callback is used to output the results.
void OutputResults (int min, int max)
{
  //cout << min << " - " << max << endl;
  checksum += max - min;
}

//  The program entry point.
void main ()
{
  int
    count = 3600000,
    window = 1000;

  srand (0);
  checksum = 0;
  std::cout << "Simple: Ticks = " << Simple (count, window, CreateData, OutputResults) << ", checksum = " << checksum << std::endl;
  srand (0);
  checksum = 0;
  std::cout << "Quite Complex: Ticks = " << QuiteComplex (count, window, CreateData, OutputResults) << ", checksum = " << checksum << std::endl;
  srand (0);
  checksum = 0;
  std::cout << "Complex: Ticks = " << Complex (count, window, CreateData, OutputResults) << ", checksum = " << checksum << std::endl;
}

Simple.cpp:

#include "Range.h"

//  Function to actually process the data.
//  A circular buffer of min/max values for the current window is filled
//  and once full, the oldest min/max pair is sent to the output callback
//  and replaced with the newest input value. Each value inputted is 
//  compared against all min/max pairs.
void ProcessData
(
  int count,
  int window,
  GeneratorCallback input,
  OutputCallback output,
  int *min_buffer,
  int *max_buffer
)
{
  int
    i;

  for (i = 0 ; i < window ; ++i)
  {
    int
      value = input ();

    min_buffer [i] = max_buffer [i] = value;

    for (int j = 0 ; j < i ; ++j)
    {
      min_buffer [j] = min (min_buffer [j], value);
      max_buffer [j] = max (max_buffer [j], value);
    }
  }

  for ( ; i < count ; ++i)
  {
    int
      index = i % window;

    output (min_buffer [index], max_buffer [index]);

    int
      value = input ();

    min_buffer [index] = max_buffer [index] = value;

    for (int k = (i + 1) % window ; k != index ; k = (k + 1) % window)
    {
      min_buffer [k] = min (min_buffer [k], value);
      max_buffer [k] = max (max_buffer [k], value);
    }
  }

  output (min_buffer [count % window], max_buffer [count % window]);
}

//  A simple method of calculating the results.
//  Memory management is done here outside of the timing portion.
clock_t Simple
(
  int count,
  int window,
  GeneratorCallback input,
  OutputCallback output
)
{
  int
    *min_buffer = new int [window],
    *max_buffer = new int [window];

  clock_t
    start = clock ();

  ProcessData (count, window, input, output, min_buffer, max_buffer);

  clock_t
    end = clock ();

  delete [] max_buffer;
  delete [] min_buffer;

  return end - start;
}

QuiteComplex.cpp:

#include "Range.h"

template <class T>
class Range
{
private:
  //  Class Types

  //  Node Data
  //  Stores a value and its position in various lists.
  struct Node
  {
    Node
      *m_queue_next,
      *m_list_greater,
      *m_list_lower;

    T
      m_value;
  };

public:
  //  Constructor
  //  Allocates memory for the node data and adds all the allocated
  //  nodes to the unused/free list of nodes.
  Range
  (
    int window_size
  ) :
    m_nodes (new Node [window_size]),
    m_queue_tail (m_nodes),
    m_queue_head (0),
    m_list_min (0),
    m_list_max (0),
    m_free_list (m_nodes)
  {
    for (int i = 0 ; i < window_size - 1 ; ++i)
    {
      m_nodes [i].m_list_lower = &m_nodes [i + 1];
    }

    m_nodes [window_size - 1].m_list_lower = 0;
  }

  //  Destructor
  //  Tidy up allocated data.
  ~Range ()
  {
    delete [] m_nodes;
  }

  //  Function to add a new value into the data structure.
  void AddValue
  (
    T value
  )
  {
    Node
      *node = GetNode ();

    //  clear links
    node->m_queue_next = 0;

    //  set value of node
    node->m_value = value;

    //  find place to add node into linked list
    Node
      *search;

    for (search = m_list_max ; search ; search = search->m_list_lower)
    {
      if (search->m_value < value)
      {
        if (search->m_list_greater)
        {
          node->m_list_greater = search->m_list_greater;
          search->m_list_greater->m_list_lower = node;
        }
        else
        {
          m_list_max = node;
        }

        node->m_list_lower = search;
        search->m_list_greater = node;
      }
    }

    if (!search)
    {
      m_list_min->m_list_lower = node;
      node->m_list_greater = m_list_min;
      m_list_min = node;
    }
  }

  //  Accessor to determine if the first output value is ready for use.
  bool RangeAvailable ()
  {
    return !m_free_list;
  }

  //  Accessor to get the minimum value of all values in the current window.
  T Min ()
  {
    return m_list_min->m_value;
  }

  //  Accessor to get the maximum value of all values in the current window.
  T Max ()
  {
    return m_list_max->m_value;
  }

private:
  //  Function to get a node to store a value into.
  //  This function gets nodes from one of two places:
  //    1. From the unused/free list
  //    2. From the end of the fifo queue, this requires removing the node from the list and tree
  Node *GetNode ()
  {
    Node
      *node;

    if (m_free_list)
    {
      //  get new node from unused/free list and place at head
      node = m_free_list;

      m_free_list = node->m_list_lower;

      if (m_queue_head)
      {
        m_queue_head->m_queue_next = node;
      }

      m_queue_head = node;
    }
    else
    {
      //  get node from tail of queue and place at head
      node = m_queue_tail;

      m_queue_tail = node->m_queue_next;
      m_queue_head->m_queue_next = node;
      m_queue_head = node;

      //  remove node from linked list
      if (node->m_list_lower)
      {
        node->m_list_lower->m_list_greater = node->m_list_greater;
      }
      else
      {
        m_list_min = node->m_list_greater;
      }

      if (node->m_list_greater)
      {
        node->m_list_greater->m_list_lower = node->m_list_lower;
      }
      else
      {
        m_list_max = node->m_list_lower;
      }
    }

    return node;
  }

  //  Member Data.
  Node
    *m_nodes,
    *m_queue_tail,
    *m_queue_head,
    *m_list_min,
    *m_list_max,
    *m_free_list;
};

//  A reasonable complex but more efficent method of calculating the results.
//  Memory management is done here outside of the timing portion.
clock_t QuiteComplex
(
  int size,
  int window,
  GeneratorCallback input,
  OutputCallback output
)
{
  Range <int>
    range (window);

  clock_t
    start = clock ();

  for (int i = 0 ; i < size ; ++i)
  {   
    range.AddValue (input ());

    if (range.RangeAvailable ())
    {
      output (range.Min (), range.Max ());
    }
  }

  clock_t
    end = clock ();

  return end - start;
}

Complex.cpp:

#include "Range.h"

template <class T>
class Range
{
private:
  //  Class Types

  //  Red/Black tree node colours.
  enum NodeColour
  {
    Red,
    Black
  };

  //  Node Data
  //  Stores a value and its position in various lists and trees.
  struct Node
  {
    //  Function to get the sibling of a node.
    //  Because leaves are stored as null pointers, it must be possible
    //  to get the sibling of a null pointer. If the object is a null pointer
    //  then the parent pointer is used to determine the sibling.
    Node *Sibling
    (
      Node *parent
    )
    {
      Node
        *sibling;

      if (this)
      {
        sibling = m_tree_parent->m_tree_less == this ? m_tree_parent->m_tree_more : m_tree_parent->m_tree_less;
      }
      else
      {
        sibling = parent->m_tree_less ? parent->m_tree_less : parent->m_tree_more;
      }

      return sibling;
    }

    //  Node Members
    Node
      *m_queue_next,
      *m_tree_less,
      *m_tree_more,
      *m_tree_parent,
      *m_list_greater,
      *m_list_lower;

    NodeColour
      m_colour;

    T
      m_value;
  };

public:
  //  Constructor
  //  Allocates memory for the node data and adds all the allocated
  //  nodes to the unused/free list of nodes.
  Range
  (
    int window_size
  ) :
    m_nodes (new Node [window_size]),
    m_queue_tail (m_nodes),
    m_queue_head (0),
    m_tree_root (0),
    m_list_min (0),
    m_list_max (0),
    m_free_list (m_nodes)
  {
    for (int i = 0 ; i < window_size - 1 ; ++i)
    {
      m_nodes [i].m_list_lower = &m_nodes [i + 1];
    }

    m_nodes [window_size - 1].m_list_lower = 0;
  }

  //  Destructor
  //  Tidy up allocated data.
  ~Range ()
  {
    delete [] m_nodes;
  }

  //  Function to add a new value into the data structure.
  void AddValue
  (
    T value
  )
  {
    Node
      *node = GetNode ();

    //  clear links
    node->m_queue_next = node->m_tree_more = node->m_tree_less = node->m_tree_parent = 0;

    //  set value of node
    node->m_value = value;

    //  insert node into tree
    if (m_tree_root)
    {
      InsertNodeIntoTree (node);
      BalanceTreeAfterInsertion (node);
    }
    else
    {
      m_tree_root = m_list_max = m_list_min = node;
      node->m_tree_parent = node->m_list_greater = node->m_list_lower = 0;
    }

    m_tree_root->m_colour = Black;
  }

  //  Accessor to determine if the first output value is ready for use.
  bool RangeAvailable ()
  {
    return !m_free_list;
  }

  //  Accessor to get the minimum value of all values in the current window.
  T Min ()
  {
    return m_list_min->m_value;
  }

  //  Accessor to get the maximum value of all values in the current window.
  T Max ()
  {
    return m_list_max->m_value;
  }

private:
  //  Function to get a node to store a value into.
  //  This function gets nodes from one of two places:
  //    1. From the unused/free list
  //    2. From the end of the fifo queue, this requires removing the node from the list and tree
  Node *GetNode ()
  {
    Node
      *node;

    if (m_free_list)
    {
      //  get new node from unused/free list and place at head
      node = m_free_list;

      m_free_list = node->m_list_lower;

      if (m_queue_head)
      {
        m_queue_head->m_queue_next = node;
      }

      m_queue_head = node;
    }
    else
    {
      //  get node from tail of queue and place at head
      node = m_queue_tail;

      m_queue_tail = node->m_queue_next;
      m_queue_head->m_queue_next = node;
      m_queue_head = node;

      //  remove node from tree
      node = RemoveNodeFromTree (node);
      RebalanceTreeAfterDeletion (node);

      //  remove node from linked list
      if (node->m_list_lower)
      {
        node->m_list_lower->m_list_greater = node->m_list_greater;
      }
      else
      {
        m_list_min = node->m_list_greater;
      }

      if (node->m_list_greater)
      {
        node->m_list_greater->m_list_lower = node->m_list_lower;
      }
      else
      {
        m_list_max = node->m_list_lower;
      }
    }

    return node;
  }

  //  Rebalances the tree after insertion
  void BalanceTreeAfterInsertion
  (
    Node *node
  )
  {
    node->m_colour = Red;

    while (node != m_tree_root && node->m_tree_parent->m_colour == Red)
    {
      if (node->m_tree_parent == node->m_tree_parent->m_tree_parent->m_tree_more)
      {
        Node
          *uncle = node->m_tree_parent->m_tree_parent->m_tree_less;

        if (uncle && uncle->m_colour == Red)
        {
          node->m_tree_parent->m_colour = Black;
          uncle->m_colour = Black;
          node->m_tree_parent->m_tree_parent->m_colour = Red;
          node = node->m_tree_parent->m_tree_parent;
        }
        else
        {
          if (node == node->m_tree_parent->m_tree_less)
          {
            node = node->m_tree_parent;
            LeftRotate (node);
          }

          node->m_tree_parent->m_colour = Black;
          node->m_tree_parent->m_tree_parent->m_colour = Red;
          RightRotate (node->m_tree_parent->m_tree_parent);
        }
      }
      else
      {
        Node
          *uncle = node->m_tree_parent->m_tree_parent->m_tree_more;

        if (uncle && uncle->m_colour == Red)
        {
          node->m_tree_parent->m_colour = Black;
          uncle->m_colour = Black;
          node->m_tree_parent->m_tree_parent->m_colour = Red;
          node = node->m_tree_parent->m_tree_parent;
        }
        else
        {
          if (node == node->m_tree_parent->m_tree_more)
          {
            node = node->m_tree_parent;
            RightRotate (node);
          }

          node->m_tree_parent->m_colour = Black;
          node->m_tree_parent->m_tree_parent->m_colour = Red;
          LeftRotate (node->m_tree_parent->m_tree_parent);
        }
      }
    }
  }

  //  Adds a node into the tree and sorted linked list
  void InsertNodeIntoTree
  (
    Node *node
  )
  {
    Node
      *parent = 0,
      *child = m_tree_root;

    bool
      greater;

    while (child)
    {
      parent = child;
      child = (greater = node->m_value > child->m_value) ? child->m_tree_more : child->m_tree_less;
    }

    node->m_tree_parent = parent;

    if (greater)
    {
      parent->m_tree_more = node;

      //  insert node into linked list
      if (parent->m_list_greater)
      {
        parent->m_list_greater->m_list_lower = node;
      }
      else
      {
        m_list_max = node;
      }

      node->m_list_greater = parent->m_list_greater;
      node->m_list_lower = parent;
      parent->m_list_greater = node;
    }
    else
    {
      parent->m_tree_less = node;

      //  insert node into linked list
      if (parent->m_list_lower)
      {
        parent->m_list_lower->m_list_greater = node;
      }
      else
      {
        m_list_min = node;
      }

      node->m_list_lower = parent->m_list_lower;
      node->m_list_greater = parent;
      parent->m_list_lower = node;
    }
  }

  //  Red/Black tree manipulation routine, used for removing a node
  Node *RemoveNodeFromTree
  (
    Node *node
  )
  {
    if (node->m_tree_less && node->m_tree_more)
    {
      //  the complex case, swap node with a child node
      Node
        *child;

      if (node->m_tree_less)
      {
        // find largest value in lesser half (node with no greater pointer)
        for (child = node->m_tree_less ; child->m_tree_more ; child = child->m_tree_more)
        {
        }
      }
      else
      {
        // find smallest value in greater half (node with no lesser pointer)
        for (child = node->m_tree_more ; child->m_tree_less ; child = child->m_tree_less)
        {
        }
      }

      swap (child->m_colour, node->m_colour);

      if (child->m_tree_parent != node)
      {
        swap (child->m_tree_less, node->m_tree_less);
        swap (child->m_tree_more, node->m_tree_more);
        swap (child->m_tree_parent, node->m_tree_parent);

        if (!child->m_tree_parent)
        {
          m_tree_root = child;
        }
        else
        {
          if (child->m_tree_parent->m_tree_less == node)
          {
            child->m_tree_parent->m_tree_less = child;
          }
          else
          {
            child->m_tree_parent->m_tree_more = child;
          }
        }

        if (node->m_tree_parent->m_tree_less == child)
        {
          node->m_tree_parent->m_tree_less = node;
        }
        else
        {
          node->m_tree_parent->m_tree_more = node;
        }
      }
      else
      {
        child->m_tree_parent = node->m_tree_parent;
        node->m_tree_parent = child;

        Node
          *child_less = child->m_tree_less,
          *child_more = child->m_tree_more;

        if (node->m_tree_less == child)
        {
          child->m_tree_less = node;
          child->m_tree_more = node->m_tree_more;
          node->m_tree_less = child_less;
          node->m_tree_more = child_more;
        }
        else
        {
          child->m_tree_less = node->m_tree_less;
          child->m_tree_more = node;
          node->m_tree_less = child_less;
          node->m_tree_more = child_more;
        }

        if (!child->m_tree_parent)
        {
          m_tree_root = child;
        }
        else
        {
          if (child->m_tree_parent->m_tree_less == node)
          {
            child->m_tree_parent->m_tree_less = child;
          }
          else
          {
            child->m_tree_parent->m_tree_more = child;
          }
        }
      }

      if (child->m_tree_less)
      {
        child->m_tree_less->m_tree_parent = child;
      }

      if (child->m_tree_more)
      {
        child->m_tree_more->m_tree_parent = child;
      }

      if (node->m_tree_less)
      {
        node->m_tree_less->m_tree_parent = node;
      }

      if (node->m_tree_more)
      {
        node->m_tree_more->m_tree_parent = node;
      }
    }

    Node
      *child = node->m_tree_less ? node->m_tree_less : node->m_tree_more;

    if (node->m_tree_parent->m_tree_less == node)
    {
      node->m_tree_parent->m_tree_less = child;
    }
    else
    {
      node->m_tree_parent->m_tree_more = child;
    }

    if (child)
    {
      child->m_tree_parent = node->m_tree_parent;
    }

    return node;
  }

  //  Red/Black tree manipulation routine, used for rebalancing a tree after a deletion
  void RebalanceTreeAfterDeletion
  (
    Node *node
  )
  {
    Node
      *child = node->m_tree_less ? node->m_tree_less : node->m_tree_more;

    if (node->m_colour == Black)
    {
      if (child && child->m_colour == Red)
      {
        child->m_colour = Black;
      }
      else
      {
        Node
          *parent = node->m_tree_parent,
          *n = child;

        while (parent)
        {
          Node
            *sibling = n->Sibling (parent);

          if (sibling && sibling->m_colour == Red)
          {
            parent->m_colour = Red;
            sibling->m_colour = Black;

            if (n == parent->m_tree_more)
            {
              LeftRotate (parent);
            }
            else
            {
              RightRotate (parent);
            }
          }

          sibling = n->Sibling (parent);

          if (parent->m_colour == Black &&
            sibling->m_colour == Black &&
            (!sibling->m_tree_more || sibling->m_tree_more->m_colour == Black) &&
            (!sibling->m_tree_less || sibling->m_tree_less->m_colour == Black))
          {
            sibling->m_colour = Red;
            n = parent;
            parent = n->m_tree_parent;
            continue;
          }
          else
          {
            if (parent->m_colour == Red &&
              sibling->m_colour == Black &&
              (!sibling->m_tree_more || sibling->m_tree_more->m_colour == Black) &&
              (!sibling->m_tree_less || sibling->m_tree_less->m_colour == Black))
            {
              sibling->m_colour = Red;
              parent->m_colour = Black;
              break;
            }
            else
            {
              if (n == parent->m_tree_more &&
                sibling->m_colour == Black &&
                (sibling->m_tree_more && sibling->m_tree_more->m_colour == Red) &&
                (!sibling->m_tree_less || sibling->m_tree_less->m_colour == Black))
              {
                sibling->m_colour = Red;
                sibling->m_tree_more->m_colour = Black;
                RightRotate (sibling);
              }
              else
              {
                if (n == parent->m_tree_less &&
                  sibling->m_colour == Black &&
                  (!sibling->m_tree_more || sibling->m_tree_more->m_colour == Black) &&
                  (sibling->m_tree_less && sibling->m_tree_less->m_colour == Red))
                {
                  sibling->m_colour = Red;
                  sibling->m_tree_less->m_colour = Black;
                  LeftRotate (sibling);
                }
              }

              sibling = n->Sibling (parent);
              sibling->m_colour = parent->m_colour;
              parent->m_colour = Black;

              if (n == parent->m_tree_more)
              {
                sibling->m_tree_less->m_colour = Black;
                LeftRotate (parent);
              }
              else
              {
                sibling->m_tree_more->m_colour = Black;
                RightRotate (parent);
              }
              break;
            }
          }
        }
      }
    }
  }

  //  Red/Black tree manipulation routine, used for balancing the tree
  void LeftRotate
  (
    Node *node
  )
  {
    Node
      *less = node->m_tree_less;

    node->m_tree_less = less->m_tree_more;

    if (less->m_tree_more)
    {
      less->m_tree_more->m_tree_parent = node;
    }

    less->m_tree_parent = node->m_tree_parent;

    if (!node->m_tree_parent)
    {
      m_tree_root = less;
    }
    else
    {
      if (node == node->m_tree_parent->m_tree_more)
      {
        node->m_tree_parent->m_tree_more = less;
      }
      else
      {
        node->m_tree_parent->m_tree_less = less;
      }
    }

    less->m_tree_more = node;
    node->m_tree_parent = less;
  }

  //  Red/Black tree manipulation routine, used for balancing the tree
  void RightRotate
  (
    Node *node
  )
  {
    Node
      *more = node->m_tree_more;

    node->m_tree_more = more->m_tree_less;

    if (more->m_tree_less)
    {
      more->m_tree_less->m_tree_parent = node;
    }

    more->m_tree_parent = node->m_tree_parent;

    if (!node->m_tree_parent)
    {
      m_tree_root = more;
    }
    else
    {
      if (node == node->m_tree_parent->m_tree_less)
      {
        node->m_tree_parent->m_tree_less = more;
      }
      else
      {
        node->m_tree_parent->m_tree_more = more;
      }
    }

    more->m_tree_less = node;
    node->m_tree_parent = more;
  }

  //  Member Data.
  Node
    *m_nodes,
    *m_queue_tail,
    *m_queue_head,
    *m_tree_root,
    *m_list_min,
    *m_list_max,
    *m_free_list;
};

//  A complex but more efficent method of calculating the results.
//  Memory management is done here outside of the timing portion.
clock_t Complex
(
  int count,
  int window,
  GeneratorCallback input,
  OutputCallback output
)
{
  Range <int>
    range (window);

  clock_t
    start = clock ();

  for (int i = 0 ; i < count ; ++i)
  {   
    range.AddValue (input ());

    if (range.RangeAvailable ())
    {
      output (range.Min (), range.Max ());
    }
  }

  clock_t
    end = clock ();

  return end - start;
}

Answer 7

算法理念：

获取前1000个数据值并对其进行排序
排序中的最后一个 - 第一个是范围（数据+ 0，数据+ 999）。
然后从排序堆中删除具有值data [0]
的第一个元素 并添加元素数据[1000]
现在，排序中的最后一个 - 第一个是范围（数据+ 1，数据+ 1000）。
重复完成

// This should run in (DATA_LEN - RANGE_WIDTH)log(RANGE_WIDTH)
#include <set>
#include <algorithm>
using namespace std;

const int DATA_LEN = 3600000;
double* const data = new double (DATA_LEN);

....
....

const int RANGE_WIDTH = 1000;
double range = new double(DATA_LEN - RANGE_WIDTH);
multiset<double> data_set;
data_set.insert(data[i], data[RANGE_WIDTH]);

for (int i = 0 ; i < DATA_LEN - RANGE_WIDTH - 1 ; i++)
{
   range[i] = *data_set.end() - *data_set.begin();
   multiset<double>::iterator iter = data_set.find(data[i]);
   data_set.erase(iter);
   data_set.insert(data[i+1]);
}
range[i] = *data_set.end() - *data_set.begin();

// range now holds the values you seek

你可能应该通过1个错误来检查这个错误，但是想法就在那里。