Cedric Roux
56c66c09aa
Pre-ci test passed git-svn-id: http://svn.eurecom.fr/openair4G/trunk@4000 818b1a75-f10b-46b9-bf7c-635c3b92a50f
52 lines
1.8 KiB
Matlab
52 lines
1.8 KiB
Matlab
function [out,n,n2] = plot_in_bins(x,y,edges,service)
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% [out] = plot_in_bins(data,bins)
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% This function puts the data y = y(x) in bins of x. For every bin it
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% calculates the average and the (95/85/50/5%) percentiles. The output is a
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% matrix with 4 columns corresponding to the computed statistics and
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% length(edges) row. See help histc for treatment of edges.
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clf
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if (length(x) ~= length(y))
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error('x and y must be the same size!');
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end
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x=x(:);
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y=y(:);
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[n, bin] = histc(x,edges);
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n1 = histc(x(y>0),edges);
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out = zeros(length(edges),5);
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n2 = zeros(size(n));
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for k=1:length(edges)
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n2(k) = sum(bin==k & ~isnan(y));
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out(k,1) = mean(y(bin==k & ~isnan(y)));
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% we would like the percentiles where (95/85/50/5%) of the values are
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% above. Matlab returns the percentiles of the values below. So we
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% calculate
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out(k,2:5) = prctile(y(bin==k & ~isnan(y)),[5 15 50 95]);
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end
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midpoints = (edges(1:end-1) + edges(2:end))/2;
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plot(midpoints,out(1:end-1,:));
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xlim([edges(1),edges(end)])
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yl = ylim;
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for i=1:length(midpoints)
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%text(edges(i),max(out(i,:)),sprintf('%d (%d %%)',n2(i),round(n2(i)/n(i))), 'HorizontalAlignment','left','VerticalAlignment','middle','Rotation',90);
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text(midpoints(i),min(0,yl(1)),sprintf(' %d',n2(i)), 'HorizontalAlignment','left','VerticalAlignment','middle','Rotation',90);
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end
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legend('Mean','95% prctile above','85% prctile above','50% prctile above','5% prctile above','Location','Best');
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if nargin == 4
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ax1 = gca;
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ax2 = axes('Position',get(ax1,'Position'));
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plot(midpoints,n1(1:end-1)./n2(1:end-1)*100,'Color','k','Linewidth',2,'Parent',ax2);
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set(ax2,'YAxisLocation','right');
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set(ax2,'Color','none');
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set(ax2,'XColor','k');
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set(ax2,'YColor','k');
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set(ax2,'ylim',[0, 100]);
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set(get(ax2,'ylabel'),'String','Service (%)');
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set(gcf,'CurrentAxes',ax1)
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end |