wolffd@0: % ---
wolffd@0: % class ClipSimGraph
wolffd@0: % Directed graph representing comparative clip similarities.
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: % The Edges thus represent the (are nearer to each othen than) 
wolffd@0: % expression
wolffd@0: % ---
wolffd@0: 
wolffd@0: classdef ClipSimGraph < ClipPairGraph
wolffd@0: 
wolffd@0: % ---
wolffd@0: %  the methods
wolffd@0: % ---
wolffd@0: methods
wolffd@0: 
wolffd@0:     
wolffd@0: % constructor of the graph
wolffd@0: function G = ClipSimGraph(comparison, comparison_ids)
wolffd@0:     
wolffd@0:     % ---
wolffd@0:     % handle manual input
wolffd@0:     % ---
wolffd@0:     
wolffd@0:     if nargin == 1
wolffd@0:         % ---
wolffd@0:         % this uses an imput grpaph
wolffd@0:         % to create a new MD graph
wolffd@0:         % ---
wolffd@0:         
wolffd@0:         G = ClipSimGraph();
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:         % ---
wolffd@0:         % TODO: Copy Clip Pair Information if neccessary
wolffd@0:         % this is by now a handle copy
wolffd@0:         % ---
wolffd@0:         clas = cat(1, class(comparison), superclasses(comparison));
wolffd@0:         if strcellfind(clas, 'ClipPairGraph')
wolffd@0:             
wolffd@0:             G.vid_map = comparison.vid_map;
wolffd@0:         end
wolffd@0:         
wolffd@0:     elseif nargin == 2
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:                 % TODO: how to determine the weight?
wolffd@0:                 % There are two options: relative in the triple
wolffd@0:                 % and counting absolute hits.
wolffd@0:                 % first we go for the relative ones.
wolffd@0:                 % The other is implemented in ClipSimGraphMulti
wolffd@0:                 % ---
wolffd@0:                 
wolffd@0:                 % ---
wolffd@0:                 % add an edge saying sim(a,b) > sim(a,c)
wolffd@0:                 % ---
wolffd@0:                 G.add_edge(clips(a), clips(b), clips(c), votes(c) / (sum(votes))); 
wolffd@0:                
wolffd@0:                 % ---
wolffd@0:                 % every outlier vote results in two
wolffd@0:                 % dissimilarity equations
wolffd@0:                 % ---
wolffd@0:                 
wolffd@0:                 % edge 2
wolffd@0:                 G.add_edge(clips(b), clips(a), clips(c), votes(c) / (sum(votes)));
wolffd@0: 
wolffd@0:             end
wolffd@0: 
wolffd@0:         end
wolffd@0:         end
wolffd@0:     end
wolffd@0: 
wolffd@0: end
wolffd@0:     
wolffd@0: % end constructor function
wolffd@0: 
wolffd@0: 
wolffd@0: function [weights, a, b, c] = similarities(G)
wolffd@0:     % ---
wolffd@0:     % returns the weights of edges meaning sim(a,b) > sim(a,c)
wolffd@0:     % ---    
wolffd@0:     % get edge weights
wolffd@0:     [weights, a, b, c] = edges(G);
wolffd@0: end
wolffd@0: 
wolffd@0: % ---
wolffd@0: % add an edge saying sim(a,b) > sim(a,c)
wolffd@0: % ---
wolffd@0: % function add_edge(G, a, b, c, weight)
wolffd@0: 
wolffd@0: function remove_edge(G, a, b, c)
wolffd@0: 
wolffd@0:     if nargin == 4
wolffd@0:         V1 = add_node(G, a, b);
wolffd@0:         V2 = add_node(G, a, c);
wolffd@0:         
wolffd@0:     elseif nargin == 3
wolffd@0:         V1 = a;
wolffd@0:         V2 = b;
wolffd@0:     end
wolffd@0: 
wolffd@0:     % ---
wolffd@0:     % call superclass
wolffd@0:     % --- 
wolffd@0:     remove_edge@DiGraph(G, V1, V2);
wolffd@0:  end  
wolffd@0:  
wolffd@0: function set_edge(G, a, b, c, weight)
wolffd@0:     if nargin == 5
wolffd@0:         V1 = add_node(G, a, b);
wolffd@0:         V2 = add_node(G, a, c);
wolffd@0:         
wolffd@0:     elseif nargin == 4
wolffd@0:         V1 = a;
wolffd@0:         V2 = b;
wolffd@0:         weight = c;
wolffd@0:     end
wolffd@0: 
wolffd@0:     % ---
wolffd@0:     % call superclass
wolffd@0:     % --- 
wolffd@0:     set_edge@DiGraph(G, V1, V2, weight);
wolffd@0: end  
wolffd@0: 
wolffd@0: % ---
wolffd@0: % simple mix of two sets of info about the same
wolffd@0: % nodes: mean.
wolffd@0: % NOTE: if there's more than two infos, the earlier
wolffd@0: % information will loose influence
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 Edge to weight
wolffd@0:         G.E(V1, V2) = (G.E(V1, V2) + weight) /2;
wolffd@0: 
wolffd@0:         cprint(4, '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: end
wolffd@0: end
wolffd@0: 
wolffd@0: