function [itrn,itst]=crossval(num_data,num_folds)% CROSSVAL Partitions data for cross-validation.%% Synopsis:%  [itrn,itst] = crossval(num_data,num_folds)%% Description:%  This function randomly partitions data into the training%  and testing parts. The number of partitionings is determined%  by the num_folds. If num_folds==1 then makes only one random%  partitioning of data into training and testing in ratio 50:50.% % Input:%  num_data [1x1] number of data.%  num_folds [1x1] number of folders.%% Output:%  itrn{i} Indices of training data of i-th folder.%  itst{i} Indices of testing data i-th folder.%% About: Statistical Pattern Recognition Toolbox% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac% <a href="http://www.cvut.cz">Czech Technical University Prague</a>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a>% Modifications:% 19-aug-2004, VF, comments repared% 17-may-2004, VF% 21-Jan-2003, VF% 14-Jan-2003, VF% 7-jan-2003, VF, created% random partitioning inx=randperm(num_data);itrn=cell(1,num_folds);itst=cell(1,num_folds);if num_folds == 1,  half = fix(num_data/2);  itrn{1}=inx(1:half);  itst{1}=inx(half+1:end);else  num_column=ceil(num_data/num_folds);  part=[1:num_data zeros(1,num_column*num_folds-num_data)];  part=reshape(part,num_column,num_folds)';  for i=1:num_folds,    tst_inx=part(i,:);    tst_inx=tst_inx(find(tst_inx));    trn_inx=part(find([1:num_folds]~=i),:);    trn_inx=trn_inx(find(trn_inx));    itrn{i}=inx(trn_inx);    itst{i}=inx(tst_inx);  endendreturn;% EOF