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Highlights from
Statistical Learning Toolbox

from Statistical Learning Toolbox by Dahua Lin
Functions for statistical learning, pattern recognition and computer vision, covering many topics.

Description of sledgeset
Home > sltoolbox > graph > sledgeset.m

sledgeset

PURPOSE ^

SLEDGESET Construct the edge set representation of a graph

SYNOPSIS ^

function Gd = sledgeset(G, uv)

DESCRIPTION ^

SLEDGESET Construct the edge set representation of a graph

 $ Syntax $
   - Gd = sledgeset(G)
   - Gd = sledgeset(G, uv)

 $ Arguments $
   - G:        The input graph (or bigraph)
   - Gd:       The output edge set representation of the graph
   - uv:       The using-value scheme

 $ Description $
   - Gd = sledgeset(G) constructs the edge set representation of the
     graph G with an automatic selection of uv scheme.

   - Gd = sledgeset(G, uv) constructs the edge set representation of 
     the graph G with a specified uv scheme.
     There are the following uv schems:
       - 'auto':   automatic selection (default)
                   If G has values then use the values for construction,
                   otherwise not use.
       - 'on':     force to use values, if G has no values then assign
                   1 to all edges
       - 'off':    force not to use values even if G has values.

 $ History $
   - Created by Dahua Lin, on Sep 9, 2006

CROSS-REFERENCE INFORMATION ^

This function calls:
  • sladjlist2edgeset SLADJLIST2EDGESET Converts the adjacency list to edge set
  • slgraphinfo SLGRAPHINFO Extracts basic information of a given graph representation
This function is called by:

SOURCE CODE ^

0001 function Gd = sledgeset(G, uv)
0002 %SLEDGESET Construct the edge set representation of a graph
0003 %
0004 % $ Syntax $
0005 %   - Gd = sledgeset(G)
0006 %   - Gd = sledgeset(G, uv)
0007 %
0008 % $ Arguments $
0009 %   - G:        The input graph (or bigraph)
0010 %   - Gd:       The output edge set representation of the graph
0011 %   - uv:       The using-value scheme
0012 %
0013 % $ Description $
0014 %   - Gd = sledgeset(G) constructs the edge set representation of the
0015 %     graph G with an automatic selection of uv scheme.
0016 %
0017 %   - Gd = sledgeset(G, uv) constructs the edge set representation of
0018 %     the graph G with a specified uv scheme.
0019 %     There are the following uv schems:
0020 %       - 'auto':   automatic selection (default)
0021 %                   If G has values then use the values for construction,
0022 %                   otherwise not use.
0023 %       - 'on':     force to use values, if G has no values then assign
0024 %                   1 to all edges
0025 %       - 'off':    force not to use values even if G has values.
0026 %
0027 % $ History $
0028 %   - Created by Dahua Lin, on Sep 9, 2006
0029 %
0030 
0031 %% parse and verify input
0032 
0033 gi = slgraphinfo(G);
0034 
0035 if nargin < 2 || isempty(uv)
0036     uv = 'auto';
0037 end
0038 
0039 %% decide scheme
0040 % sch:
0041 %   0:  no value -> no value
0042 %   1:  no value -> has value
0043 %   2:  has value -> no value
0044 %   3:  has value -> has value
0045 
0046 switch uv
0047     case 'auto'
0048         if gi.valued
0049             sch = 3;
0050         else
0051             sch = 0;
0052         end
0053     case 'on'
0054         if gi.valued
0055             sch = 3;
0056         else
0057             sch = 1;
0058         end
0059     case 'off'
0060         if gi.valued
0061             sch = 2;
0062         else
0063             sch = 0;
0064         end
0065     otherwise
0066         error('sltoolbox:invalidarg', ...
0067             'Invalid using-value scheme: %s', uv);
0068 end
0069 
0070 %% do construction
0071 
0072 switch gi.type
0073     case 'ge'
0074         Gd = struct('n', gi.n);
0075     case 'bi'
0076         Gd = struct('n', gi.n, 'nt', gi.nt);
0077 end
0078 
0079 switch gi.form
0080     case 'edgeset'
0081         switch sch
0082             case {0, 3}
0083                 Gd.edges = G.edges;
0084                 
0085             case 1
0086                 if ~isempty(G.edges)
0087                     vals = ones(size(G.edges, 1), 1);
0088                     Gd.edges = [G.edges, vals];
0089                 else
0090                     Gd.edges = [];
0091                 end
0092             case 2
0093                 if ~isempty(G.edges)
0094                     Gd.edges = G.edges(:, 1:2);
0095                 else
0096                     Gd.edges = [];
0097                 end
0098         end
0099         
0100     case 'adjlist'
0101         Gd.edges = sladjlist2edgeset(G.targets, sch);
0102         
0103     case 'adjmat'
0104         switch sch
0105             case {0, 2}
0106                 [I, J] = find(G);
0107                 Gd.edges = [I, J];
0108             case 1
0109                 [I, J] = find(G);
0110                 ne = length(I);
0111                 Gd.edges = [I, J, ones(ne, 1)];
0112             case 3
0113                 [I, J, V] = find(G);
0114                 Gd.edges = [I, J, V];
0115         end
0116 end
0117                 
0118
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