如何将此代码从Dijkstra转换为Astar
how to convert this code from Dijkstra to Astar?
所以我有一个项目,由于速度原因我想切换到Astar。
但C++不是我的强项。谁能帮助我(或告诉我如何做.)将算法从Dijkstra转换为Astar?
我找到了这个 Astar 实现:http://code.google.com/p/a-star-algorithm-implementation/
但是我不知道如何在我现有的代码中使用它。
这是获得算法的图形文件:
#include "Graph.h"
#include <iostream>
#include <algorithm>
#include <stack>
Graph::Graph(void)
{
}
Graph::~Graph(void)
{
while(!mNodes.empty())
{
delete mNodes.back();
mNodes.pop_back();
}
}
void Graph::addNode(int name, bool exists, Node** NodeID )
{
Node* pStart = NULL;
mNodes.push_back(new Node(name,exists));
std::vector<Node*>::iterator itr;
itr = mNodes.begin()+mNodes.size()-1;
pStart = (*itr);
if(exists == true)pStart->DoesExist_yes();
*NodeID = pStart;
}
void Graph::connect_oneway(Node* pFirst, Node* pSecond, int moveCost)
{
if(pFirst != NULL && pSecond != NULL)
{
pFirst->createEdge(pSecond, moveCost);
}
}
#define MAX_NODES (32768)
#define MAX_CONNECTIONS (5)
#include <time.h>
int * Graph::findPath_r(Node* pStart, Node* pEnd)
{
int *arr = new int[MAX_NODES+2];
for (int i=0; i<MAX_NODES; i++)
arr[i] = -1;
arr[0] = 0;
if(pStart == pEnd)
{
return arr;
}
std::vector<Node*> openList;
openList.push_back(pStart);
Node* pCurrNode = NULL;
while(!openList.empty())
{
//Get best node from open list (lowest F value).
//Since we sort the list at the end of the previous loop we know
//the front node is the best
pCurrNode = openList.front();
//Exit if we're are the goal
if(pCurrNode == pEnd)
break;
//Remove the node from the open list and place it in the closed
openList.erase(openList.begin());
pCurrNode->setClosed(true); //We use a flag instead of a list for speed
//Test all of the edge nodes from the current node
std::vector<Edge*>* pEdges = pCurrNode->getEdges();
Node* pEdgeNode = NULL;
for(std::vector<Edge*>::iterator i = pEdges->begin(); i != pEdges->end(); ++i)
{
pEdgeNode = (*i)->pNode;
//If it's closed we've already analysed it
if(!pEdgeNode->getClosed() && pCurrNode->DoesExist() == true)
{
if(!inList(pEdgeNode,&openList))
{
openList.push_back(pEdgeNode);
pEdgeNode->setGCost(pCurrNode->getGCost()+(*i)->moveCost);
pEdgeNode->calcFCost();
pEdgeNode->setParent(pCurrNode);
}
else
{
//If this is a better node (lower G cost)
if(pEdgeNode->getGCost() > pCurrNode->getGCost()+(*i)->moveCost)
{
pEdgeNode->setGCost(pCurrNode->getGCost()+(*i)->moveCost);
pEdgeNode->calcFCost();
pEdgeNode->setParent(pCurrNode);
}
}
}
}
//Place the lowest F cost item in the open list at the top, so we can
//access it easily next iteration
std::sort(openList.begin(), openList.end(), Graph::compareNodes);
}
//Make sure we actually found a path
if(pEnd->getParent() != NULL)
{
//Output the path
//Use a stack because it is LIFO
std::stack<Node*> path;
while(pCurrNode != NULL)
{
path.push(pCurrNode);
pCurrNode = pCurrNode->getParent();
}
int counter = 0;
arr[1] = 0;
while(!path.empty())
{
arr[counter+2] = path.top()->getName();
counter++;
arr[1] += path.top()->getGCost();
path.pop();
}
arr[0] = counter;
return arr;
}
return arr;
}
bool Graph::inList(Node* pNode, std::vector<Node*>* pList)
{
for(std::vector<Node*>::iterator i = pList->begin(); i != pList->end(); ++i)
{
if((*i) == pNode)
{
return true;
}
}
return false;
}
bool Graph::compareNodes(Node* pFirst, Node* pSecond)
{
return pFirst->getFCost() < pSecond->getFCost();
}
void Graph::reset(void)
{
for(std::vector<Node*>::iterator i = mNodes.begin(); i != mNodes.end(); ++i)
{
(*i)->reset();
}
}
查找路径的函数是这样的:图形::findPath_r
我真正想做的是保留边缘(因为它们决定了道路是双向还是单向)。
以下是其他文件:图.h
#ifndef _GRAPH_H_
#define _GRAPH_H
#include "Node.h"
class Graph
{
public:
Graph(void);
~Graph(void);
//void addNode(int name, bool exists);
void addNode(int name, bool exists, Node** NodeID );
void connect_oneway(int ppFirst, int ppSecond, int moveCost);
void connect_oneway(Node* pFirst, Node* pSecond, int moveCost);
//int * findPath_r(int start, int end);
int * findPath_r(Node* pStart, Node* pEnd);
void reset(void);
private:
void findNodesx(int firstName, Node** ppFirstNode);
bool inList(Node* pNode, std::vector<Node*>* pList);
static bool compareNodes(Node* pFirst, Node* pSecond);
std::vector<Node*> mNodes;
};
#endif
节点.h
#ifndef _NODE_H_
#define _NODE_H_
#include <string>
#include <vector>
//Forward declare Node so Edge can see it
class Node;
struct Edge
{
Edge(Node* node, int cost) : pNode(node), moveCost(cost){}
Node* pNode;
int moveCost;
};
class Node
{
public:
Node(void);
Node(int name, bool exists);
~Node(void);
void createEdge(Node* pTarget, int moveCost);
void setGCost(int cost);
void setClosed(bool closed);
void setParent(Node* pParent);
int getGCost(void);
int getFCost(void);
bool getClosed(void);
Node* getParent(void);
int getName(void);
bool DoesExist(void);
bool DoesExist_yes(void);
std::vector<Edge*>* getEdges(void);
void calcFCost(void);
void reset(void);
private:
int mGCost;
int mTotal;
bool mClosed;
Node* mpParent;
int mName;
bool mHeur;
std::vector<Edge*> mEdges;
};
#endif
节点.cpp
#include "Node.h"
Node::Node(void)
{
}
Node::Node(/*const std::string&*/int name, bool exists) : mGCost(0), mTotal(0), mClosed(false), mpParent(NULL), mName(name), mHeur(exists)
{
}
Node::~Node(void)
{
while(!mEdges.empty())
{
delete mEdges.back();
mEdges.pop_back();
}
}
int Node::getName(void)
{
return mName;
}
void Node::createEdge(Node* pTarget, int moveCost)
{
mEdges.push_back(new Edge(pTarget, moveCost));
}
void Node::setClosed(bool closed)
{
mClosed = closed;
}
bool Node::getClosed(void)
{
return mClosed;
}
std::vector<Edge*>* Node::getEdges(void)
{
return &mEdges;
}
int Node::getGCost(void)
{
return mGCost;
}
void Node::setGCost(int cost)
{
mGCost = cost;
}
void Node::calcFCost(void)
{
mTotal = mGCost;
}
void Node::setParent(Node* pParent)
{
mpParent = pParent;
}
int Node::getFCost(void)
{
return mTotal;
}
bool Node::DoesExist(void)
{
return mHeur;
}
bool Node::DoesExist_yes(void)
{
mHeur = true;
return true;
}
Node* Node::getParent(void)
{
return mpParent;
}
void Node::reset(void)
{
mGCost = 0;
mTotal = 0;
mClosed = false;
mpParent = NULL;
}
你提到了GoogleCode上的一个库。你想做什么是很清楚的,我认为最好的是自己编写你的实现。
首先,您应该知道Dijsktra是A *的特例。在 A* 中,您有一个名为 h 的启发式方法;A* = 当 h 为空函数时 Dijsktra 的可能实现。
然后,关于您的实现,让我们从 Node
.它将需要以下功能:
constructor, destructor
create/get edge
set/get parent
set/is closed (for speed)
set/get GCost
set/get FCost
set/is obstacle (name way more descriptive than 'DoesExist')
set/get position
reset
// optional method:
get name
希望这部分代码不会发生太大变化。启发式代码将放置在路径查找器中。Edge
类保持不变。
现在最大的:Graph
.您无需删除任何公共方法。
您将需要一种启发式方法。对于将要描述的实现,您将需要一个可接受的一致启发式方法:
- 它不能高估到目标的距离(允许)
- 它必须是单调的(一致的)
一般大小写签名为 int getHCost(Node* node);
。如果你总是返回 0,你将有一个 Dijsktra 算法,这不是你想要的。在这里,我们将采用节点和目标之间的欧几里得距离。计算速度比曼哈顿距离慢,但结果更好。之后可以更改此设置。
int getHCost(Node* node, Note* goal);
这意味着您必须将节点放置在 3D 空间中。请注意,启发式是启发式的,即对距离的估计。
我不会写代码。我将编写一些适合您情况的伪代码。原始伪代码位于维基百科A*页面上。此伪代码是您的findPath_r
函数:
function A*(start,goal)
set all nodes to not closed // The set of nodes already evaluated.
openset = {start} // The set of tentative nodes to be evaluated, initially containing the start node
start.gcost = 0 // Cost from start along best known path.
// Estimated total cost from start to goal through y.
start.fcost = start.gcost + getHCost(start, goal)
while openset is not empty
current = the node in openset having the lowest f_cost (usually the first if you use a sorted list)
if current == goal
return construct_path(goal)
remove current from openset
current.closed = true
for each neighbor in (node connected by edge in current.edges) // Here is the condition for one-way edges
if neighbor.closed or neighbor.obstacle
continue
gcost = current.gcost + dist_between(current,neighbor) // via edge distance
if neighbor not in openset
add neighbor to openset
neighbor.parent = current
neighbor.gcost = gcost
neighbor.fcost = neighbor.gcost + getHCost(neighbor, goal)
else if gcost < neighbor.gcost
neighbor.parent = current
neighbor.gcost = gcost
neighbor.fcost = neighbor.gcost + getHCost(neighbor, goal)
update neighbor position in openset
return failure
function construct_path(current_node)
std::vector<Node*> path
while current_node != 0
path.push_front(current_node)
current_node = current_node.parent
return path
上面的实现使用单向边。
你能够用C++编写Dijsktra算法,所以用C++编写这个伪代码应该不是问题。
第二部分,表演。首先,衡量;)。
我有一些提示可以提高性能:
- 使用内存池进行分配解除分配
- 对打开列表使用侵入性列表(您也可以使用此技术使其自动排序)
我建议您阅读初学者的A*,即使您不使用tilemap,这也是一个有用的阅读材料。
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