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[英]How to use boost::graph dijkstra's algorithm if vertex properties are pointers?
[英]Boost::graph Dijkstra and custom objects and properties
我想使用boost的dijkstra算法(因為我在程序的其他部分使用了boost)。 我遇到的問題是將自定義對象(我相信它們被稱為property
)添加到adjacency_list
。
基本上我有一個自定義邊緣類,它維護有關邊緣和通過它連接的頂點的各種信息。 我想使用adjaceny_list
所需的邊緣屬性存儲我的自定義數據對象
我已經成功實現了提升提供的玩具示例。 我試圖使用自定義屬性無濟於事( 提升示例 , 提升屬性 )。 我只是將我的VEdge數據結構封裝在一個結構或其他東西中,我只需要能夠檢索它。 但我無法弄清楚如何將我的自定義數據結構包含到boost adjaceny_list
結構中。
在我的情況下,我有以下程序:
Main.cpp的:
#include <iostream>
#include <fstream>
#include "dijkstra.h"
#include <vector>
int
main(int, char *[])
{
// Generate the vector of edges from elsewhere in the program
std::vector<VEdge*> edges; //someclass.get_edges();
td* test = new td(edges);
test->run_d();
test->print_path();
return EXIT_SUCCESS;
}
Dijkstra.cpp:
#include <iostream>
#include <fstream>
#include "dijkstra.h"
using namespace boost;
td::td() {
kNumArcs = sizeof(kEdgeArray) / sizeof(Edge);
kNumNodes = 5;
}
td::td(std::vector<VEdge*> edges) {
// add edges to the edge property here
for(VEdge* e : edges) {
// for each edge, add to the kEdgeArray variable in some way
// The boost example forces the input to be an array of edge_property type.
// So here is where I will convert my raw VEdge data structure to
// the custom edge_property that I am struggling to understand how to create.
}
kNumArcs = sizeof(kEdgeArray) / sizeof(Edge);
kNumNodes = 5;
}
void td::run_d() {
kGraph = graph_t(kEdgeArray, kEdgeArray + kNumArcs, kWeights, kNumNodes);
kWeightMap = get(edge_weight, kGraph);
kP = std::vector<vertex_descriptor >(num_vertices(kGraph));
kD = std::vector<int>(num_vertices(kGraph));
kS = vertex(A, kGraph);
dijkstra_shortest_paths(kGraph, kS,
predecessor_map(boost::make_iterator_property_map(kP.begin(), get(boost::vertex_index, kGraph))).
distance_map(boost::make_iterator_property_map(kD.begin(), get(boost::vertex_index, kGraph))));
}
void td::print_path() {
std::cout << "distances and parents:" << std::endl;
graph_traits < graph_t >::vertex_iterator vi, vend;
for (boost::tie(vi, vend) = vertices(kGraph); vi != vend; ++vi) {
std::cout << "distance(" << kName[*vi] << ") = " << kD[*vi] << ", ";
std::cout << "parent(" << kName[*vi] << ") = " << kName[kP[*vi]] << std::
endl;
}
}
void td::generate_dot_file() {
std::cout << std::endl;
std::ofstream dot_file("figs/dijkstra-eg.dot");
dot_file << "digraph D {\n"
<< " rankdir=LR\n"
<< " size=\"4,3\"\n"
<< " ratio=\"fill\"\n"
<< " edge[style=\"bold\"]\n" << " node[shape=\"circle\"]\n";
graph_traits < graph_t >::edge_iterator ei, ei_end;
for (boost::tie(ei, ei_end) = edges(kGraph); ei != ei_end; ++ei) {
graph_traits < graph_t >::edge_descriptor e = *ei;
graph_traits < graph_t >::vertex_descriptor
u = source(e, kGraph), v = target(e, kGraph);
dot_file << kName[u] << " -> " << kName[v]
<< "[label=\"" << get(kWeightMap, e) << "\"";
if (kP[v] == u)
dot_file << ", color=\"black\"";
else
dot_file << ", color=\"grey\"";
dot_file << "]";
}
dot_file << "}";
}
Dijkstra.h:
#ifndef _TEMPD_H_
#define _TEMPD_H_
#pragma once
#include <boost/config.hpp>
#include <boost/graph/graph_traits.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/dijkstra_shortest_paths.hpp>
#include <boost/property_map/property_map.hpp>
using namespace boost;
typedef adjacency_list < listS, vecS, directedS,
no_property, property < edge_weight_t, int > > graph_t;
typedef graph_traits < graph_t >::vertex_descriptor vertex_descriptor;
typedef std::pair<int, int> Edge;
struct VEdge{
// custom variables here
VNode start;
VNode end;
int weight;
int id;
// other irrelevant data pertinent to my program that must be preserved
};
struct VNode {
// custom variables here
int x;
int y;
int id;
// other irrelevant data pertinent to my program that must be preserved
}
enum nodes { A, B, C, D, E };
class td {
public:
td();
td(std::vector<VEdge*>);
~td();
void run_d();
void print_path();
void generate_dot_file();
private:
Edge kEdgeArray[9] = { Edge(A, C), Edge(B, B), Edge(B, D), Edge(B, E),
Edge(C, B), Edge(C, D), Edge(D, E), Edge(E, A), Edge(E, B)
};
char kName[5] = {'A','B','C','D','E'};
int kWeights[9] = { 1, 2, 1, 2, 7, 3, 1, 1, 1 };
int kNumArcs;
int kNumNodes;
vertex_descriptor kS;
graph_t kGraph;
std::vector<int> kD;
std::vector<vertex_descriptor> kP;
property_map<graph_t, edge_weight_t>::type kWeightMap;
};
#endif
我知道我的例子有點做作,但它傳達了我想要完成的事情。 我知道我的edge_descriptor
需要一個自定義數據結構,它被發送到graph_t
typedef
。
所以我想改變我的Dijkstra.h文件看起來像這樣:
struct vertex_label_t {vertex_property_tag kind;};
struct edge_label_t {edge_property_tag kind;};
typedef property <vertex_custom_t, VNode*>,
property <vertex_label_t, string>,
property <vertex_root_t, ing> > > vertex_p;
typedef property <edge_custom_t, VEdge*>,
property <edge_label_t, string > > edge_p;
typedef adjacency_list < listS, vecS, directedS,
vertex_p, edge_p > graph_t;
typedef graph_traits < graph_t >::vertex_descriptor vertex_descriptor;
好的。 自https://stackoverflow.com/questions/28889423/boost-adjacency-list-swap-errors-when-using-boost-dijkstra以來,你已經走了很長的路。 樣本是獨立的,可以編譯¹
我想我可以連接一些點,希望這會有所幫助。
VEdge
對於最簡單的選項,我使用Bundled Properties , VEdge
如下方式定義VEdge
:
struct VEdge {
int id;
int source, target;
double weight;
// custom variables here
};
現在,我們將圖形定義為
using graph_t = boost::adjacency_list<boost::listS, boost::vecS,
boost::directedS, boost::no_property, VEdge>;
using weight_map_t = boost::property_map<graph_t, double VEdge::*>::type;
正如您所看到的那樣,權重貼圖具有更復雜的類型,如捆綁屬性的屬性貼圖中所述 。 你可以得到實際的地圖:
weight_map_t kWeightMap = boost::get(&VEdge::weight, kGraph);
現在,讓我們在VEdge
向量中重新創建問題的測試數據(A = 0 ... E = 4):
std::vector<VEdge> edges {
{ 2100, 0, 2, 1 },
{ 2101, 1, 1, 2 },
{ 2102, 1, 3, 1 },
{ 2103, 1, 4, 2 },
{ 2104, 2, 1, 7 },
{ 2105, 2, 3, 3 },
{ 2106, 3, 4, 1 },
{ 2107, 4, 0, 1 },
{ 2108, 4, 1, 1 },
};
test_dijkstra test(edges);
構造函數有一點點復雜性,只能從邊緣找到頂點的數量。 我使用Boost Range算法來查找最大頂點節點id並傳遞:
test_dijkstra::test_dijkstra(std::vector<VEdge> edges) {
using namespace boost::adaptors;
size_t max_node;
boost::partial_sort_copy(
edges | transformed([](VEdge const &e) -> size_t { return std::max(e.source, e.target); }),
boost::make_iterator_range(&max_node, &max_node + 1),
std::greater<size_t>());
auto e = edges | transformed([](VEdge const &ve) { return std::make_pair(ve.source, ve.target); });
kGraph = graph_t(e.begin(), e.end(), edges.begin(), max_node + 1);
}
請注意如何edges.begin()
:它不是“被強制為edge_property類型的數組”。 迭代器會很好。
現在dijkstra需要獲取weight_map
參數,因為它不再是默認的內部屬性:
void test_dijkstra::run_dijkstra() {
weight_map_t kWeightMap = boost::get(&VEdge::weight, kGraph);
vertex_descriptor kS = vertex(0, kGraph);
kP = std::vector<vertex_descriptor>(num_vertices(kGraph));
kD = std::vector<int>(num_vertices(kGraph));
dijkstra_shortest_paths(
kGraph, kS,
predecessor_map(boost::make_iterator_property_map(kP.begin(), get(boost::vertex_index, kGraph)))
.distance_map(boost::make_iterator_property_map(kD.begin(), get(boost::vertex_index, kGraph)))
.weight_map(kWeightMap));
}
對於此示例,我將A
轉換為0
作為起始頂點。 結果路徑與原始路徑完全相同
#include <boost/config.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/dijkstra_shortest_paths.hpp>
#include <boost/graph/graph_traits.hpp>
#include <boost/property_map/property_map.hpp>
#include <boost/range/algorithm.hpp>
#include <boost/range/adaptors.hpp>
#include <fstream>
#include <iostream>
struct VEdge {
int id;
int source, target;
double weight;
// custom variables here
};
class test_dijkstra {
using graph_t = boost::adjacency_list<boost::listS, boost::vecS, boost::directedS, boost::no_property, VEdge>;
using vertex_descriptor = boost::graph_traits<graph_t>::vertex_descriptor;
using edge_descriptor = boost::graph_traits<graph_t>::edge_descriptor;
using weight_map_t = boost::property_map<graph_t, double VEdge::*>::type;
public:
test_dijkstra(std::vector<VEdge>);
~test_dijkstra() {}
void run_dijkstra();
void print_path();
void generate_dot_file();
private:
graph_t kGraph;
std::vector<int> kD;
std::vector<vertex_descriptor> kP;
};
test_dijkstra::test_dijkstra(std::vector<VEdge> edges) {
using namespace boost::adaptors;
size_t max_node;
boost::partial_sort_copy(
edges | transformed([](VEdge const &e) -> size_t { return std::max(e.source, e.target); }),
boost::make_iterator_range(&max_node, &max_node + 1),
std::greater<size_t>());
auto e = edges | transformed([](VEdge const &ve) { return std::make_pair(ve.source, ve.target); });
kGraph = graph_t(e.begin(), e.end(), edges.begin(), max_node + 1);
}
void test_dijkstra::run_dijkstra() {
weight_map_t kWeightMap = boost::get(&VEdge::weight, kGraph);
vertex_descriptor kS = vertex(0, kGraph);
kP = std::vector<vertex_descriptor>(num_vertices(kGraph));
kD = std::vector<int>(num_vertices(kGraph));
dijkstra_shortest_paths(
kGraph, kS,
predecessor_map(boost::make_iterator_property_map(kP.begin(), get(boost::vertex_index, kGraph)))
.distance_map(boost::make_iterator_property_map(kD.begin(), get(boost::vertex_index, kGraph)))
.weight_map(kWeightMap));
}
void test_dijkstra::print_path() {
std::cout << "distances and parents:" << std::endl;
boost::graph_traits<graph_t>::vertex_iterator vi, vend;
for (boost::tie(vi, vend) = vertices(kGraph); vi != vend; ++vi) {
std::cout << "distance(" << *vi << ") = " << kD[*vi] << ", ";
std::cout << "parent(" << *vi << ") = " << kP[*vi] << "\n";
}
}
void test_dijkstra::generate_dot_file() {
weight_map_t kWeightMap = boost::get(&VEdge::weight, kGraph);
std::ofstream dot_file("figs/dijkstra-eg.dot");
dot_file << "digraph D {\n"
<< " rankdir=LR\n"
<< " size=\"4,3\"\n"
<< " ratio=\"fill\"\n"
<< " edge[style=\"bold\"]\n"
<< " node[shape=\"circle\"]\n";
boost::graph_traits<graph_t>::edge_iterator ei, ei_end;
for (boost::tie(ei, ei_end) = edges(kGraph); ei != ei_end; ++ei) {
boost::graph_traits<graph_t>::edge_descriptor e = *ei;
boost::graph_traits<graph_t>::vertex_descriptor u = source(e, kGraph), v = target(e, kGraph);
dot_file << u << " -> " << v << "[label=\"" << get(kWeightMap, e) << "\"";
if (kP[v] == u)
dot_file << ", color=\"black\"";
else
dot_file << ", color=\"grey\"";
dot_file << "]";
}
dot_file << "}";
}
int main() {
std::vector<VEdge> edges {
{ 2100, 0, 2, 1 },
{ 2101, 1, 1, 2 },
{ 2102, 1, 3, 1 },
{ 2103, 1, 4, 2 },
{ 2104, 2, 1, 7 },
{ 2105, 2, 3, 3 },
{ 2106, 3, 4, 1 },
{ 2107, 4, 0, 1 },
{ 2108, 4, 1, 1 },
};
test_dijkstra test(edges);
test.run_dijkstra();
test.print_path();
test.generate_dot_file();
}
VEdge*
如果你堅持使用屬性中的指針,一些事情會變得更復雜:
你不能使用double VEdge::*
weight_map_t
。 相反,您需要為此調整自定義屬性映射:
auto kWeightMap = boost::make_transform_value_property_map( [](VEdge* ve) { return ve->weight; }, boost::get(boost::edge_bundle, kGraph) );
從好的方面來說,您可以使用簡寫索引器表示法來評估edge_descriptor
邊緣屬性,如generate_dot_file()
所示:
dot_file << u << " -> " << v << "[label=\\"" << kGraph[e]->weight << "\\"";
VEdge
對象復制到捆綁包中,因此可能更有效 沒有進一步的麻煩(並沒有打擾內存泄漏):
#include <boost/config.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/dijkstra_shortest_paths.hpp>
#include <boost/graph/graph_traits.hpp>
#include <boost/property_map/property_map.hpp>
#include <boost/range/algorithm.hpp>
#include <boost/range/adaptors.hpp>
#include <boost/property_map/transform_value_property_map.hpp>
#include <fstream>
#include <iostream>
struct VEdge {
int id;
int source, target;
double weight;
// custom variables here
};
class test_dijkstra {
using graph_t = boost::adjacency_list<boost::listS, boost::vecS, boost::directedS, boost::no_property, VEdge*>;
using vertex_descriptor = boost::graph_traits<graph_t>::vertex_descriptor;
using edge_descriptor = boost::graph_traits<graph_t>::edge_descriptor;
public:
test_dijkstra(std::vector<VEdge*>);
~test_dijkstra() {}
void run_dijkstra();
void print_path();
void generate_dot_file();
private:
graph_t kGraph;
std::vector<int> kD;
std::vector<vertex_descriptor> kP;
};
test_dijkstra::test_dijkstra(std::vector<VEdge*> edges) {
using namespace boost::adaptors;
size_t max_node;
boost::partial_sort_copy(
edges | transformed([](VEdge const* e) -> size_t { return std::max(e->source, e->target); }),
boost::make_iterator_range(&max_node, &max_node + 1),
std::greater<size_t>());
auto e = edges | transformed([](VEdge const *ve) { return std::make_pair(ve->source, ve->target); });
kGraph = graph_t(e.begin(), e.end(), edges.begin(), max_node + 1);
}
void test_dijkstra::run_dijkstra() {
auto kWeightMap = boost::make_transform_value_property_map(
[](VEdge* ve) { return ve->weight; },
boost::get(boost::edge_bundle, kGraph)
);
vertex_descriptor kS = vertex(0, kGraph);
kP = std::vector<vertex_descriptor>(num_vertices(kGraph));
kD = std::vector<int>(num_vertices(kGraph));
dijkstra_shortest_paths(
kGraph, kS,
predecessor_map(boost::make_iterator_property_map(kP.begin(), get(boost::vertex_index, kGraph)))
.distance_map(boost::make_iterator_property_map(kD.begin(), get(boost::vertex_index, kGraph)))
.weight_map(kWeightMap));
}
void test_dijkstra::print_path() {
std::cout << "distances and parents:" << std::endl;
boost::graph_traits<graph_t>::vertex_iterator vi, vend;
for (boost::tie(vi, vend) = vertices(kGraph); vi != vend; ++vi) {
std::cout << "distance(" << *vi << ") = " << kD[*vi] << ", ";
std::cout << "parent(" << *vi << ") = " << kP[*vi] << "\n";
}
}
void test_dijkstra::generate_dot_file() {
std::ofstream dot_file("figs/dijkstra-eg.dot");
dot_file << "digraph D {\n"
<< " rankdir=LR\n"
<< " size=\"4,3\"\n"
<< " ratio=\"fill\"\n"
<< " edge[style=\"bold\"]\n"
<< " node[shape=\"circle\"]\n";
boost::graph_traits<graph_t>::edge_iterator ei, ei_end;
for (boost::tie(ei, ei_end) = edges(kGraph); ei != ei_end; ++ei) {
boost::graph_traits<graph_t>::edge_descriptor e = *ei;
boost::graph_traits<graph_t>::vertex_descriptor u = source(e, kGraph), v = target(e, kGraph);
dot_file << u << " -> " << v << "[label=\"" << kGraph[e]->weight << "\"";
if (kP[v] == u)
dot_file << ", color=\"black\"";
else
dot_file << ", color=\"grey\"";
dot_file << "]";
}
dot_file << "}";
}
int main() {
std::vector<VEdge*> edges {
new VEdge { 2100, 0, 2, 1 },
new VEdge { 2101, 1, 1, 2 },
new VEdge { 2102, 1, 3, 1 },
new VEdge { 2103, 1, 4, 2 },
new VEdge { 2104, 2, 1, 7 },
new VEdge { 2105, 2, 3, 3 },
new VEdge { 2106, 3, 4, 1 },
new VEdge { 2107, 4, 0, 1 },
new VEdge { 2108, 4, 1, 1 },
};
test_dijkstra test(edges);
test.run_dijkstra();
test.print_path();
test.generate_dot_file();
}
¹拍打愚蠢的錯別字后
²自成一體的Live On Coliru
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