wolffd@0: % ---
wolffd@0: % fake partitioning for comparison 
wolffd@0: % to stober08:
wolffd@0: % ---
wolffd@0: classdef cvpartition_alltrain
wolffd@0:   
wolffd@0: properties (Hidden)
wolffd@0: 
wolffd@0:     mtest;
wolffd@0:     mtraining;
wolffd@0: end
wolffd@0: properties
wolffd@0:     N;
wolffd@0:     NumTestSets;
wolffd@0:     TrainSize;
wolffd@0:     TestSize;
wolffd@0: end
wolffd@0:     
wolffd@0:         
wolffd@0: methods 
wolffd@0:     
wolffd@0: % ---
wolffd@0: % constuctor: directly calculates the truncated testset
wolffd@0: % ---
wolffd@0: function P = cvpartition_alltrain(nData, nRuns)
wolffd@0:     
wolffd@0:     P.NumTestSets = nRuns;
wolffd@0:     P.N = nData; 
wolffd@0: 
wolffd@0:     % build training and test sets
wolffd@0:     for i = 1:P.NumTestSets
wolffd@0:         P.TrainSize(i) = nData;
wolffd@0:         P.TestSize(i) = nData;
wolffd@0:         P.mtraining{i} = ones(P.N, 1);
wolffd@0:         P.mtest{i} = ones(P.N, 1);
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: function out = test(P, i)
wolffd@0: 
wolffd@0:     out = P.mtest{i};
wolffd@0: end
wolffd@0: 
wolffd@0: function out = training(P, i)
wolffd@0: 
wolffd@0:     out = P.mtraining{i};
wolffd@0: end
wolffd@0: 
wolffd@0: end  
wolffd@0: end