Hi Sarah, sorry, I don't know where that code came from; it is not being supported. Over the years, things find there way into FS, often from a postdoc or visiting fellow, then they leave and the program becomes orphaned.
On 1/18/2023 5:31 PM, Sarah Lavelle wrote:
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Hi there,
I'm looking to use the *Dijkstra matlab code* provided by freesurfer, titled 'dijk.m'. It calculates the *shortest path* from node 's' to node 't'. I want to use this to calculate the distance from 1 vertex to another on an inflated cortical surface( in matlab.)
I currently have the surface imported into matlab in terms of 2 matrices: *vertices(V) and edges(E)*. (this was done using the 'freesurfer_read_surf' function. )
However, the input used to describe the cortical surface/graph in dijk.m is 'A'. After researching, I believe that 'A' the *weighted adjacency matrix* of the graph? Is that right? And if so, do you know how I can get 'A' using 'V' and 'E', so I can use it as an input in dijk.m?
Thanks, Sarah DIJK.M: 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) % % (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 (*MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* http://www.ie.ncsu.edu/kay/matlog http://secure-web.cisco.com/1cRs4G5kkiqFfc2Vy9yVEtcMD7rwIzApZJZ4z6EgLjvr3DLHEBrqNMkPdLpPPG6eaTDn_69VRybMDRk59JLCGgl3irDo8McGFpHK067QeeagFQgxoOHTenKhBH3nQlIscdq63huobF9n4iRndFKn4s00LLLjavEDvvGgDb7RdDAifzmQaGAJEX3i8zig0vPwUFDa7qFTQDQ0-FAkIzHR9DZM3BsbvzlWvQD7Q2_zJV6V4F6nhioRB3O0uSR0kWXxPCN_FIv9iVjC0FvkAGJHEgO77XjUBjRTiOxfnnZGxhWTqBs8NcNF7JmU7ebccrYqnIrOM1PRVO3_7FEJWyjZhWw/http%3A%2F%2Fwww.ie.ncsu.edu%2Fkay%2Fmatlog) % 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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