Hi, I added this lines at the end of boxplot.m % Distribute handles nq = 1:size(quartile_x,2); hs.box = h(nq); nw = nq(end) + [1:2*size(whisker_x,2)]; hs.whisker = h(nw); nm = nw(end)+ [1:size(median_x,2)]; hs.median = h(nm); no = nm(end) + [1:size(outliers_y,2)]; hs.outliers = h(no); no2 = no(end) + [1:size(outliers2_y,2)]; hs.outliers2 = h(no2);
and the function now returns a second argument with the handles to the graphics elements. This allows configuration of the visualization. In particular I wanted to remove outliers (which I thought was possible by input arguments). Shall I add this to the repository? -- M. Sc. Juan Pablo Carbajal ----- PhD Student University of Zürich http://ailab.ifi.uzh.ch/carbajal/ ------------------------------------------------------------------------------ Virtualization & Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ _______________________________________________ Octave-dev mailing list Octave-dev@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/octave-dev
