… full one

build/buildgaimc.m

@@ -0,0 +1,87 @@
+%% build the gaimc distribution
+function buildgaimc(varargin)
+if ~isempty(strmatch('all',varargin))
+    buildlist = {'test','pages','zip'};
+else
+    buildlist = varargin;
+end    
+tobuild = @(type,buidlist) ~isempty(strmatch(type,buildlist));
+gaimcversion = '1.0';
+mypath = fileparts(mfilename('fullpath'));
+oldpath = pwd;
+matlablpath=path;
+try
+    if tobuild('test',buildlist)
+        fprintf('Running tests...\n\n');
+        cd(mypath)      % move to where we think we are
+        cd ../          % in main gaimc directory
+        addpath(pwd);   % add it to the path
+        cd test         % run tests
+        try
+            test_main
+        catch ME
+            fprintf('*************\n')
+            fprintf('Tests failed!\n');
+            fprintf('*************\n')
+            fprintf('\n');
+            fprintf('Build halted.\n');
+            fprintf('\n');
+            fprintf('Test error:\n');
+            rethrow(ME);
+        end
+	end
+    
+    if tobuild('pages',buildlist)
+        fprintf('Building demos...\n\n');
+        cd(mypath)      % move to where we think we are
+        cd ../          % in main gaimc directory
+        addpath(pwd);   % add it to the path
+        cd demo
+        try
+            publish('demo');
+            publish('airports');
+            publish('performance_comparison_simple');
+            if tobuild('pages_fullperf')
+                publish('performance_comparison');
+            end
+        catch ME
+            fprintf('******************\n')
+            fprintf('Publishing failed!\n');
+            fprintf('******************\n')
+            fprintf('\n');
+            fprintf('Build halted.\n');
+            fprintf('\n');
+            fprintf('Test error:\n');
+            rethrow(ME);
+        end
+    end
+    
+    if tobuild('zip',buildlist)
+        cd(mypath)      % move to where we think we are
+        try
+            cd ../../
+            [status,result] = system(...
+                sprintf('zip -r gaimc/build/gaimc-%s.zip gaimc/*.m gaimc/demo gaimc/test gaimc/graphs',...
+                gaimcversion));
+            result
+        catch ME
+            fprintf('******************\n')
+            fprintf('Zipping failed!\n');
+            fprintf('******************\n')
+            fprintf('\n');
+            fprintf('Build halted.\n');
+            fprintf('\n');
+            fprintf('Error:\n');
+            rethrow(ME);
+        end
+    end        
+        
+catch ME
+    cd(oldpath); % move to where we think we are
+    path(matlabpath);
+    rethrow(ME)
+end
+
+cd(oldpath); 
+path(matlabpath);
+    

build/matlab_central_notes.txt

@@ -0,0 +1,35 @@
+Picture: minnesota graph (demo_08.png)
+
+Title : gaimc : Graph Algorithms In Matlab Code
+Summary (100 chars) :
+Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.
+Description (5000 chars) :
+
+While MatlabBGL uses the Boost Graph Library for efficient graph routines,
+gaimc implements everything in pure Matlab code.  While the routines are 
+slower, they aren't as slow as I initially thought.  Since people often
+have problems getting MatlabBGL to compile on new versions of Matlab
+or on new architectures, this library is then a complement to MatlabBGL.
+
+See the published M-files for a few examples of the capabilities.
+
+Functions
+  depth first search (dfs) 
+  breadth first search (bfs)
+  connected components (scomponents)
+  maximum weight bipartite matching (bipartite_matching)
+  Dijkstra's shortest paths (dijkstra)
+  Prim's minimum spanning tree (mst_prim)
+  clustering coefficients (clustercoeffs)
+  directed clustering coefficients (dirclustercoeffs)
+  core numbers (corenums)
+
+The project is maintained at github : http://github.com/dgleich/gaimc/tree/master
+
+Tags:
+
+graph, network, dijkstra, core numbers, prim, dfs, bfs, connected components,
+strongly connected components, clustering coefficients, directed clustering coefficients,
+directed network, directed graph, depth first search, breadth first search,
+shortest paths, minimum spanning tree, mst
+  

demo/airports.m

@@ -67,12 +67,10 @@
 % That's the US, now we need to plot our data on top of it.
 [X,Y] = gplot(T,xy); % get the information to reproduce a gplot
 plotm(Y,X,'k.-','LineWidth',1.5); % plot the lines on the map 
-%% 
-% We need to clear the axes after the mapping toolbox
-clf;
+
 %%
 % Let's just look at the continential US too.
-figure; ax = usamap('conus');
+clf; ax = usamap('conus');
 states = shaperead('usastatelo', 'UseGeoCoords', true, 'Selector',...
     {@(name) ~any(strcmp(name,{'Alaska','Hawaii'})), 'Name'});
 faceColors = makesymbolspec('Polygon',...
@@ -85,9 +83,6 @@
 % One interesting aspect of this map is that major airline hubs (Chicago,
 % New York, etc. are not well represented.  One possible explaination is
 % that they have larger delays than other regional airports.
-%
-% Clear the figure again before proceeding.
-clf;
 
 %% Honolulu to St. Johns?
 % Before, we saw that the lengthiest route was between St. John's and

demo/demo.m

@@ -83,7 +83,7 @@
 
 %%
 % Load the example matrix from the Boost Graph Library 
-load('graphs/dfs_example');
+load_gaimc_graph('dfs_example');
 figure(1); graph_draw(A,xy,'labels',labels);
 
 %%
@@ -99,7 +99,7 @@
 
 %%
 % Let's look at breadth first search too, using a different example.
-load('graphs/bfs_example');
+load_gaimc_graph('bfs_example');
 figure(1); clf; graph_draw(A,xy,'labels',labels);
 
 %%
@@ -161,7 +161,8 @@
 
 %%
 % Now, we just call MST and look at the result.
-T = mst_prim(A);
+% T = mst_prim(A);
+% This command means we can't run the demo, so it's commented out.
 
 %%
 % Oops, travel time isn't symmetric!  Let's just pick the longest possible
@@ -220,6 +221,7 @@
 %%
 % We also have a largest_component function that makes it easy to just get
 % the largest connected component.
+clf;
 [Acc,f] = largest_component(A);
 graph_draw(Acc,xy(f,:)) 
 %%
@@ -236,7 +238,7 @@
 
 %%
 % Load a road network to use for statistical computations
-load('graphs/minnesota');
+load_gaimc_graph('minnesota');
 gplot(A,xy);
 
 %%
@@ -280,7 +282,7 @@
 
 %%
 % Load and convert the graph.  
-load ('graphs/all_shortest_paths_example');
+load_gaimc_graph('all_shortest_paths_example');
 A = spfun(@(x) x-min(min(A))+1,A); % remove the negative edges
 As = convert_sparse(A);
 %%
@@ -305,4 +307,4 @@
 toc
 %%
 % And just to check, let's make sure the output is the same.
-isequal(D,D2)
+isequal(D,D2)