Dijkstra’s algorithm is an algorithm for finding the shortest path in a graph.
First drawing the graph:
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import networkx as nx import matplotlib.pyplot as plt from networkx.drawing.nx_agraph import write_dot, graphviz_layout def coloring_tree(G): visited_list=[] for i in G.nodes(): visited_list.append( g.nodes[i]['visited'] ) graph_color_map=[] for i in visited_list: graph_color_map.append('red') pos =graphviz_layout(G, prog='dot') labels = nx.get_edge_attributes(G,'weight') nx.draw(G,pos,with_labels=True, arrows=True, node_color = graph_color_map) nx.draw_networkx_edge_labels(G, pos,edge_labels=labels) plt.show() return g=nx.DiGraph() g.add_node('a',visited=False) g.add_node('b',visited=False) g.add_node('c',visited=False) g.add_node('d',visited=False) g.add_node('e',visited=False) g.add_node('f',visited=False) g.add_node('g',visited=False) g.add_node('h',visited=False) g.add_node('i',visited=False) g.add_edge('a','b',weight=4) g.add_edge('a','h',weight=8) g.add_edge('b','a',weight=4) g.add_edge('b','c',weight=8) g.add_edge('b','h',weight=11) g.add_edge('c','b',weight=8) g.add_edge('c','d',weight=7) g.add_edge('c','f',weight=4) g.add_edge('c','i',weight=2) g.add_edge('d','d',weight=7) g.add_edge('d','e',weight=9) g.add_edge('d','f',weight=14) g.add_edge('e','d',weight=9) g.add_edge('e','f',weight=10) g.add_edge('f','c',weight=4) g.add_edge('f','d',weight=14) g.add_edge('f','e',weight=10) g.add_edge('f','g',weight=2) g.add_edge('g','f',weight=2) g.add_edge('g','h',weight=1) g.add_edge('g','i',weight=6) g.add_edge('h','a',weight=8) g.add_edge('g','b',weight=11) g.add_edge('h','g',weight=1) g.add_edge('h','i',weight=7) g.add_edge('i','c',weight=2) g.add_edge('i','g',weight=6) g.add_edge('i','h',weight=7) coloring_tree(g) |
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#include <iostream> #include <vector> #include <string> #include <list> #include <limits> // for numeric_limits #include <set> #include <utility> // for pair #include <algorithm> #include <iterator> typedef int vertex_t; typedef double weight_t; const weight_t max_weight = std::numeric_limits<double>::infinity(); struct neighbor { vertex_t target; weight_t weight; neighbor(vertex_t arg_target, weight_t arg_weight) : target(arg_target), weight(arg_weight) { } }; typedef std::vector<std::vector<neighbor> > adjacency_list_t; void DijkstraComputePaths(vertex_t source, const adjacency_list_t &adjacency_list, std::vector<weight_t> &min_distance, std::vector<vertex_t> &previous) { int n = adjacency_list.size(); min_distance.clear(); min_distance.resize(n, max_weight); min_distance[source] = 0; previous.clear(); previous.resize(n, -1); std::set<std::pair<weight_t, vertex_t> > vertex_queue; vertex_queue.insert(std::make_pair(min_distance[source], source)); while (!vertex_queue.empty()) { weight_t dist = vertex_queue.begin()->first; vertex_t u = vertex_queue.begin()->second; vertex_queue.erase(vertex_queue.begin()); // Visit each edge exiting u const std::vector<neighbor> &neighbors = adjacency_list[u]; for (std::vector<neighbor>::const_iterator neighbor_iter = neighbors.begin(); neighbor_iter != neighbors.end(); neighbor_iter++) { vertex_t v = neighbor_iter->target; weight_t weight = neighbor_iter->weight; weight_t distance_through_u = dist + weight; if (distance_through_u < min_distance[v]) { vertex_queue.erase(std::make_pair(min_distance[v], v)); min_distance[v] = distance_through_u; previous[v] = u; vertex_queue.insert(std::make_pair(min_distance[v], v)); } } } } std::list<vertex_t> DijkstraGetShortestPathTo( vertex_t vertex, const std::vector<vertex_t> &previous) { std::list<vertex_t> path; for ( ; vertex != -1; vertex = previous[vertex]) path.push_front(vertex); return path; } int main() { adjacency_list_t adjacency_list(9); adjacency_list[0].push_back(neighbor(1, 4)); adjacency_list[0].push_back(neighbor(7, 8)); adjacency_list[1].push_back(neighbor(0, 4)); adjacency_list[1].push_back(neighbor(2, 8)); adjacency_list[1].push_back(neighbor(7, 11)); adjacency_list[2].push_back(neighbor(1, 8)); adjacency_list[2].push_back(neighbor(3, 7)); adjacency_list[2].push_back(neighbor(5, 4)); adjacency_list[2].push_back(neighbor(8, 2)); adjacency_list[3].push_back(neighbor(3, 7)); adjacency_list[3].push_back(neighbor(4, 9)); adjacency_list[3].push_back(neighbor(5, 14)); adjacency_list[4].push_back(neighbor(3, 9)); adjacency_list[4].push_back(neighbor(5, 10)); adjacency_list[5].push_back(neighbor(2, 4)); adjacency_list[5].push_back(neighbor(3, 14)); adjacency_list[5].push_back(neighbor(4, 10)); adjacency_list[5].push_back(neighbor(6, 2)); adjacency_list[6].push_back(neighbor(5, 2)); adjacency_list[6].push_back(neighbor(7, 1)); adjacency_list[6].push_back(neighbor(8, 6)); adjacency_list[7].push_back(neighbor(0, 9)); adjacency_list[7].push_back(neighbor(1, 9)); adjacency_list[7].push_back(neighbor(6, 9)); adjacency_list[7].push_back(neighbor(8, 9)); adjacency_list[8].push_back(neighbor(2, 2)); adjacency_list[8].push_back(neighbor(6, 6)); adjacency_list[8].push_back(neighbor(7, 7)); std::vector<weight_t> min_distance; std::vector<vertex_t> previous; DijkstraComputePaths(0, adjacency_list, min_distance, previous); std::cout << "Distance from 0 to 5: " << min_distance[5] << std::endl; std::list<vertex_t> path = DijkstraGetShortestPathTo(5, previous); std::cout << "Path : "; std::copy(path.begin(), path.end(), std::ostream_iterator<vertex_t>(std::cout, " ")); std::cout << std::endl; return 0; } |
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Distance from 0 to 5: 16 Path : 0 1 2 5 |
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Hi, thanks for sharing, but how to use a data file here with an adjacency list?