Dijkstra算法
开放分类: 算法、单源最短路径
关于 Dijkstra算法解决voronoi图的问题
macrolian 发表于: 2008-5-03 19:36 来源: Matlab中文学习站
我想用 Dijkstra算法解决voronoi图中求解最短路径的时候,有一个"dijkstra.m"的文件
代码如下:function [dist,path] = dijkstra(nodes,segments,start_id,finish_id)
%DIJKSTRA Calculates the shortest distance and path between points on a map
% using Dijkstra's Shortest Path Algorithm
%
% [DIST, PATH] = DIJKSTRA(NODES, SEGMENTS, SID, FID)
% Calculates the shortest distance and path between start and finish nodes SID and FID
%
% [DIST, PATH] = DIJKSTRA(NODES, SEGMENTS, SID)
% Calculates the shortest distances and paths from the starting node SID to all
% other nodes in the map
%
% Note:
% DIJKSTRA is set up so that an example is created if no inputs are provided,
% but ignores the example and just processes the inputs if they are given.
%
% Inputs:
% NODES should be an Nx3 or Nx4 matrix with the format [ID X Y] or [ID X Y Z]
% where ID is an integer, and X, Y, Z are cartesian position coordinates)
% SEGMENTS should be an Mx3 matrix with the format [ID N1 N2]
% where ID is an integer, and N1, N2 correspond to node IDs from NODES list
% such that there is an [undirected] edge/segment between node N1 and node N2
% SID should be an integer in the node ID list corresponding with the starting node
% FID (optional) should be an integer in the node ID list corresponding with the finish
%
% Outputs:
% DIST is the shortest Euclidean distance
% If FID was specified, DIST will be a 1x1 double representing the shortest
% Euclidean distance between SID and FID along the map segments. DIST will have
% a value of INF if there are no segments connecting SID and FID.
% If FID was not specified, DIST will be a 1xN vector representing the shortest
% Euclidean distance between SID and all other nodes on the map. DIST will have
% a value of INF for any nodes that cannot be reached along segments of the map.
% PATH is a list of nodes containing the shortest route
% If FID was specified, PATH will be a 1xP vector of node IDs from SID to FID.
% NAN will be returned if there are no segments connecting SID to FID.
% If FID was not specified, PATH will be a 1xN cell of vectors representing the
% shortest route from SID to all other nodes on the map. PATH will have a value
% of NAN for any nodes that cannot be reached along the segments of the map.
%
% Example:
% dijkstra; % calculates shortest path and distance between two nodes
% % on a map of randomly generated nodes and segments
%
% Example:
% nodes = [(1:10); 100*rand(2,10)]';
% segments = [(1:17); floor(1:0.5:9); ceil(2:0.5:10)]';
% figure; plot(nodes(:,2), nodes(:,3),'k.');
% hold on;
% for s = 1:17
% if (s <= 10) text(nodes(s,2),nodes(s,3),[' ' num2str(s)]); end
% plot(nodes(segments(s,2:3)',2),nodes(segments(s,2:3)',3),'k');
% end
% [d, p] = dijkstra(nodes, segments, 1, 10)
% for n = 2:length(p)
% plot(nodes(p(n-1:n),2),nodes(p(n-1:n),3),'r-.','linewidth',2);
% end
% hold off;
%
% Author: Joseph Kirk
% Email: jdkirk630 at gmail dot com
% Release: 1.3
% Release Date: 5/18/07
if (nargin < 3) % SETUP
% (GENERATE RANDOM EXAMPLE OF NODES AND SEGMENTS IF NOT GIVEN AS INPUTS)
% Create a random set of nodes/vertices,and connect some of them with
% edges/segments. Then graph the resulting map.
num_nodes = 40; L = 100; max_seg_length = 30; ids = (1:num_nodes)';
nodes = [ids L*rand(num_nodes,2)]; % create random nodes
h = figure; plot(nodes(:,2),nodes(:,3),'k.') % plot the nodes
text(nodes(num_nodes,2),nodes(num_nodes,3),...
[' ' num2str(ids(num_nodes))],'Color','b','FontWeight','b')
hold on
num_segs = 0; segments = zeros(num_nodes*(num_nodes-1)/2,3);
for i = 1:num_nodes-1 % create edges between some of the nodes
text(nodes(i,2),nodes(i,3),[' ' num2str(ids(i))],'Color','b','FontWeight','b')
for j = i+1:num_nodes
d = sqrt(sum((nodes(i,2:3) - nodes(j,2:3)).^2));
if and(d < max_seg_length,rand < 0.6)
plot([nodes(i,2) nodes(j,2)],[nodes(i,3) nodes(j,3)],'k.-')
% add this link to the segments list
num_segs = num_segs + 1;
segments(num_segs, = [num_segs nodes(i,1) nodes(j,1)];
end
end
end
segments(num_segs+1:num_nodes*(num_nodes-1)/2, = [];
axis([0 L 0 L])
% Calculate Shortest Path Using Dijkstra's Algorithm
% Get random starting/ending nodes,compute the shortest distance and path.
start_id = ceil(num_nodes*rand); disp(['start id = ' num2str(start_id)]);
finish_id = ceil(num_nodes*rand); disp(['finish id = ' num2str(finish_id)]);
[distance,path] = dijkstra(nodes,segments,start_id,finish_id);
disp(['distance = ' num2str(distance)]); disp(['path = [' num2str(path) ']']);
% If a Shortest Path exists,Plot it on the Map.
figure(h)
for k = 2:length(path)
m = find(nodes(:,1) == path(k-1));
n = find(nodes(:,1) == path(k));
plot([nodes(m,2) nodes(n,2)],[nodes(m,3) nodes(n,3)],'ro-','LineWidth',2);
end
title(['Shortest Distance from ' num2str(start_id) ' to ' ...
num2str(finish_id) ' = ' num2str(distance)])
hold off
else %--------------------------------------------------------------------------
% MAIN FUNCTION - DIJKSTRA'S ALGORITHM
% initializations
node_ids = nodes(:,1);
[num_map_pts,cols] = size(nodes);
table = sparse(num_map_pts,2);
shortest_distance = Inf(num_map_pts,1);
settled = zeros(num_map_pts,1);
path = num2cell(NaN(num_map_pts,1));
col = 2;
pidx = find(start_id == node_ids);
shortest_distance(pidx) = 0;
table(pidx,col) = 0;
settled(pidx) = 1;
path(pidx) = {start_id};
if (nargin < 4) % compute shortest path for all nodes
while_cmd = 'sum(~settled) > 0';
else % terminate algorithm early
while_cmd = 'settled(zz) == 0';
zz = find(finish_id == node_ids);
end
while eval(while_cmd)
% update the table
table(:,col-1) = table(:,col);
table(pidx,col) = 0;
% find neighboring nodes in the segments list
neighbor_ids = [segments(node_ids(pidx) == segments(:,2),3);
segments(node_ids(pidx) == segments(:,3),2)];
% calculate the distances to the neighboring nodes and keep track of the paths
for k = 1:length(neighbor_ids)
cidx = find(neighbor_ids(k) == node_ids);
if ~settled(cidx)
d = sqrt(sum((nodes(pidx,2:cols) - nodes(cidx,2:cols)).^2));
if (table(cidx,col-1) == 0) || ...
(table(cidx,col-1) > (table(pidx,col-1) + d))
table(cidx,col) = table(pidx,col-1) + d;
tmp_path = path(pidx);
path(cidx) = {[tmp_path{1} neighbor_ids(k)]};
else
table(cidx,col) = table(cidx,col-1);
end
end
end
% find the minimum non-zero value in the table and save it
nidx = find(table(:,col));
ndx = find(table(nidx,col) == min(table(nidx,col)));
if isempty(ndx)
break
else
pidx = nidx(ndx(1));
shortest_distance(pidx) = table(pidx,col);
settled(pidx) = 1;
end
end
if (nargin < 4) % return the distance and path arrays for all of the nodes
dist = shortest_distance';
path = path';
else % return the distance and path for the ending node
dist = shortest_distance(zz);
pat