?? dijk.m
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function [D,P] = dijk(A,s,t)
%DIJK Shortest paths from nodes 's' to nodes 't' using Dijkstra algorithm.
% [D,P] = dijk(A,s,t)
% A = n x n node-node weighted adjacency matrix of arc lengths
% (Note: A(i,j) = 0 => Arc (i,j) does not exist;
% A(i,j) = NaN => Arc (i,j) exists with 0 weight)
% s = FROM node indices
% = [] (default), paths from all nodes
% t = TO node indices
% = [] (default), paths to all nodes
% D = |s| x |t| matrix of shortest path distances from 's' to 't'
% = [D(i,j)], where D(i,j) = distance from node 'i' to node 'j'
% = Inf, if no path from 'i' to 'j'
% P = |s| x n matrix of predecessor indices, where P(i,j) is the
% index of the predecessor to node 'j' on the path from 's(i)' to
% 'j',where P(i,i) = 0 and P(i,j) = NaN is 'j' not on path to
% 's(i)' (use PRED2PATH to convert P to paths)
% = path from 's' to 't', if |s| = |t| = 1
%
% Example:
% A = [0 1 3 0
% 0 0 0 2
% 0 0 0 4
% 0 0 0 0]
% [d,p] = dijk(A,1,4) % (Single path) d = 3
% % p = 1 2 4
%
% [D,P] = dijk(A) % (All paths) D = 0 1 3 3
% % Inf 0 Inf 2
% % Inf Inf 0 4
% % Inf Inf Inf 0
% % P = 0 1 1 2
% % NaN 0 NaN 2
% % NaN NaN 0 3
% % NaN NaN NaN 0
% p = pred2path(P,1,4) % p = 1 2 4
%
% (If A is a triangular matrix, then computationally intensive node
% selection step not needed since graph is acyclic (triangularity is a
% sufficient, but not a necessary, condition for a graph to be acyclic)
% and A can have non-negative elements)
%
% (If |s| >> |t|, then DIJK is faster if DIJK(A',t,s) used, where D is now
% transposed and P now represents successor indices)
%
% (Based on Fig. 4.6 in Ahuja, Magnanti, and Orlin, Network Flows,
% Prentice-Hall, 1993, p. 109.)
% Copyright (c) 1994-2006 by Michael G. Kay
% Matlog Version 9 13-Jan-2006 (http://www.ie.ncsu.edu/kay/matlog)
% Input Error Checking ****************************************************
error(nargchk(1,3,nargin))
[n,cA] = size(A);
if nargin < 2 || isempty(s), s = (1:n)'; else s = s(:); end
if nargin < 3 || isempty(t), t = (1:n)'; else t = t(:); end
if ~any(any(tril(A) ~= 0)) % A is upper triangular
isAcyclic = 1;
elseif ~any(any(triu(A) ~= 0)) % A is lower triangular
isAcyclic = 2;
else % Graph may not be acyclic
isAcyclic = 0;
end
if n ~= cA
error('A must be a square matrix');
elseif ~isAcyclic && any(any(A < 0))
error('A must be non-negative');
elseif any(s < 1 | s > n)
error(['"s" must be an integer between 1 and ',num2str(n)]);
elseif any(t < 1 | t > n)
error(['"t" must be an integer between 1 and ',num2str(n)]);
end
% End (Input Error Checking) **********************************************
A = A'; % Use transpose to speed-up FIND for sparse A
D = zeros(length(s),length(t));
if nargout > 1, P = NaN*ones(length(s),n); end
for i = 1:length(s)
j = s(i);
Di = Inf*ones(n,1); Di(j) = 0;
isLab = false(length(t),1);
if isAcyclic == 1
nLab = j - 1;
elseif isAcyclic == 2
nLab = n - j;
else
nLab = 0;
UnLab = 1:n;
isUnLab = true(n,1);
end
if nargout > 1, P(i,s(i)) = 0; end %Change from NaN to indicate no pred
while nLab < n && ~all(isLab)
if isAcyclic
Dj = Di(j);
else % Node selection
[Dj,jj] = min(Di(isUnLab));
j = UnLab(jj);
UnLab(jj) = [];
isUnLab(j) = 0;
end
nLab = nLab + 1;
if length(t) < n, isLab = isLab | (j == t); end
[jA,kA,Aj] = find(A(:,j));
Aj(isnan(Aj)) = 0;
if isempty(Aj), Dk = Inf; else Dk = Dj + Aj; end
if nargout > 1, P(i,jA(Dk < Di(jA))) = j; end
Di(jA) = min(Di(jA),Dk);
if isAcyclic == 1 % Increment node index for upper triangular A
j = j + 1;
elseif isAcyclic == 2 % Decrement node index for lower triangular A
j = j - 1;
end
end
D(i,:) = Di(t)';
end
if nargout > 1 && length(s) == 1 && length(t) == 1
P = pred2path(P,s,t);
end
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