wolffd@0: % ---
wolffd@0: % class ClipSimGraphMulti
wolffd@0: % Directed MultiGraph representing comparative clip similarities.
wolffd@0: % EACH pair of vertices has multiple directed edges connecting them
wolffd@0: %
wolffd@0: % each node represents a pair of clips,
wolffd@0: % an edge (a,b) -> (a,c) is present if there is at least one
wolffd@0: % users judging clip a more similar to clip b than to clip c
wolffd@0: % 
wolffd@0: % Each edge thus represent a single (are nearer to each othen than) 
wolffd@0: % expression
wolffd@0: % ---
wolffd@0: 
wolffd@0: classdef ClipSimGraphMulti < ClipSimGraph & handle
wolffd@0: 
wolffd@0:     
wolffd@0: properties
wolffd@0: 
wolffd@0: end
wolffd@0: 
wolffd@0: % ---
wolffd@0: %  the methods
wolffd@0: % ---
wolffd@0: methods
wolffd@0:         
wolffd@0: % constructor of the graph
wolffd@0: function G = ClipSimGraphMulti(comparison, comparison_ids)
wolffd@0:     
wolffd@0:     if nargin == 0
wolffd@0:         % ---
wolffd@0:         % empty constructor
wolffd@0:         % ---
wolffd@0:         
wolffd@0:     elseif nargin == 1
wolffd@0:         % todo: copy graph if same class
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % this uses an imput grpaph
wolffd@0:         % to create a new MD graph
wolffd@0:         % ---
wolffd@0:         
wolffd@0:         G = ClipSimGraphMulti();
wolffd@0: 
wolffd@0:         % ---
wolffd@0:         % Add the input graph to the empty one
wolffd@0:         % ---
wolffd@0:         G.add_graph(comparison);
wolffd@0:         
wolffd@0:     elseif nargin == 2
wolffd@0: 
wolffd@0: 
wolffd@0:         % ---
wolffd@0:         % handle automatic or manual input
wolffd@0:         % ---
wolffd@0:         for i = 1:size(comparison,1)
wolffd@0: 
wolffd@0:             % get clips and votes
wolffd@0:             clips = comparison_ids(comparison(i,1:3));
wolffd@0:             votes = comparison(i,4:6);
wolffd@0: 
wolffd@0:             % for each triplet position create an edge reflecting the 
wolffd@0:             % absolute and relative voting for this position
wolffd@0: 
wolffd@0:             % ---
wolffd@0:             % NOTE: we index 0 - 2 to ease the mod
wolffd@0:             % calculaton for the remaining indices
wolffd@0:             % ---
wolffd@0:             for v = 0:2
wolffd@0: 
wolffd@0:                 % ---
wolffd@0:                 % has at least one user voted this clip out?
wolffd@0:                 % If so, treat it as an outlier and determine score
wolffd@0:                 % ---
wolffd@0:                 if votes(v+1) > 0
wolffd@0: 
wolffd@0:                     a = mod(v+1, 3)+1;
wolffd@0:                     b = mod(v+2, 3)+1;
wolffd@0:                     c = v+1;
wolffd@0: 
wolffd@0: 
wolffd@0:                     % ---
wolffd@0:                     % every outlier vote results in two
wolffd@0:                     % dissimilarity equations, favored by 
wolffd@0:                     % the people who voted for the outlier
wolffd@0:                     % ---
wolffd@0:                     
wolffd@0:                     % edge 1     
wolffd@0:                     add_edge(G, clips(a), clips(b), clips(c), votes(v+1));
wolffd@0: 
wolffd@0:                     % edge 2
wolffd@0:                     add_edge(G, clips(b), clips(a), clips(c), votes(v+1));
wolffd@0:                 end
wolffd@0:             end
wolffd@0: 
wolffd@0:         end
wolffd@0:     end
wolffd@0:     
wolffd@0: % end constructor function
wolffd@0: end
wolffd@0: 
wolffd@0: function out = order(G)
wolffd@0:     
wolffd@0:    out = sum(G.V);
wolffd@0: end
wolffd@0: 
wolffd@0: function out = num_edges_multi(G)
wolffd@0:     out = sum(sum(G.E));
wolffd@0: end
wolffd@0: 
wolffd@0: function out = num_edges(G)
wolffd@0:     out = sum(sum(G.E ~= 0));
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0:  % ---
wolffd@0: % NOTE: the weight explains the multiplicity of each
wolffd@0: % edge, to correctily describe this, 
wolffd@0: % we just count the votes
wolffd@0: % ---
wolffd@0: function join_edge(G, a, b, c, weight)
wolffd@0: 
wolffd@0:     if nargin == 5
wolffd@0:         V1 = G.node(a, b);
wolffd@0:         V2 = G.node(a, c);
wolffd@0:     elseif nargin == 4
wolffd@0:         V1 = a;
wolffd@0:         V2 = b;
wolffd@0:         weight = c;
wolffd@0:     end
wolffd@0:     
wolffd@0:     if  G.edge(V1, V2) ~= 0
wolffd@0: 
wolffd@0:         % set add number to Edge index
wolffd@0:         G.E(V1, V2) = (G.E(V1, V2) + weight);
wolffd@0: 
wolffd@0:         cprint(3, 'edge weight %d %d %d updated \n',a ,b , c) ;
wolffd@0:     else
wolffd@0: 
wolffd@0:         error 'nodes not found';
wolffd@0:     end
wolffd@0: end  
wolffd@0: 
wolffd@0: % ---
wolffd@0: % This eliminates any order-2 cycles,
wolffd@0: % by substracting opposing edge counts
wolffd@0: % ---
wolffd@0: function remove_cycles_length2(G)
wolffd@0:     
wolffd@0:     G.E = max(0, G.E - G.E');
wolffd@0: end
wolffd@0: % ---
wolffd@0: % TODO: this back-and forth transform is a workaround 
wolffd@0: %  avoiding some costly other transformation which would
wolffd@0: %  happen during the direct digraph call
wolffd@0: % ---
wolffd@0: 
wolffd@0: function [Gs, s, id] = connected_components(G, varargin)
wolffd@0:     % ---
wolffd@0:     % get all connected subgraphs:
wolffd@0:     % ---
wolffd@0:     G2 = DiGraph(G);
wolffd@0:     
wolffd@0:     [GsDiGraph, s, id]  = connected_components@DiGraph(G2, varargin{:});
wolffd@0:     
wolffd@0:     for i = 1:numel(GsDiGraph)
wolffd@0:         Gs(i) = ClipSimGraphMulti(GsDiGraph(i));
wolffd@0:     end 
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0: end
wolffd@0: 
wolffd@0: methods (Hidden)
wolffd@0:     
wolffd@0: end
wolffd@0: end