How to create variability charts?
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Eric Sampson
il 1 Feb 2013
Commentato: Eric Sampson
il 18 Ott 2013
I've tried looking through the Stats Toolbox and the File Exchange, and can't find anything that would do the trick. Anyone have an idea?
Thanks!
3 Commenti
Shashank Prasanna
il 1 Feb 2013
If you know how the 'understanding is included' in that chart, you can use that information and create a boxplot. There is nothing this specialized that is offered in the statistics toolbox. You could put in a ticket with the mathworks as a suggested enhancement along with your usecase.
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Matt Tearle
il 1 Feb 2013
Modificato: Matt Tearle
il 22 Mar 2013
Based on your comment above, boxplot with nominal grouping variables will do it:
x = randn(400,1);
y1 = nominal(round(rand(400,1)),{'little','lots'});
y2 = nominal(round(rand(400,1)),{'large','small'});
y3 = nominal(round(rand(400,1)),{'gourmet','plain'});
boxplot(x,[y1,y2,y3])
Hopefully this is basically how your data is already arranged. x contains all 400 observations of the response variable. y1, y2, and y3 are nominal arrays that record each observation's status for the three categories.
The boxplot labeling doesn't emphasize the hierarchy, but the results are correct.
EDIT TO ADD Oops, I got the grouping variables backward. Anyway, this is getting close to what you posted:
boxplot(x,[y3,y2,y1],...
'plotstyle','compact','labelorientation','horizontal',...
'factorseparator',[1,2])
The only problem is that the vertical arrangement of the group labels is backwards, for showing the hierarchy. This can be hacked, though, if you need:
h = findobj(get(gca,'children'),'type','text');
tl = get(h,'position');
tl = cat(1,tl{:});
tl(:,2) = flipud(tl(:,2));
for k = 1:length(h)
set(h(k),'position',tl(k,:))
end
EDIT TO ADD (2): Not pretty, but here's a function that does a reasonable job of approximating the graphic:
function variabilityplot(x,y)
n = size(y,2);
numgrps = zeros(1,n);
for k = 1:n
numgrps(k) = numel(unique(y(:,k)));
end
numgrps = cumprod(numgrps);
N = numgrps(n);
y = fliplr(y);
boxplot(x,y,...
'plotstyle','compact','labelorientation','horizontal',...
'factorseparator',1:n);
hbxplt = get(gca,'children');
hall = get(hbxplt,'children');
halltype = get(hall,'type');
hsepln = hall(end-n+1:end);
htxt = hall(strcmpi('text',halltype));
set(htxt,'units','data')
txtpos = get(htxt,'position');
txtpos = cat(1,txtpos{:});
txtpos(:,2) = flipud(txtpos(:,2));
x = reshape(txtpos(:,1),N,n);
for k = 2:n
m = numgrps(k-1);
for j = 1:N
ii = floor((j-1)/m);
i1 = 1 + m*ii;
i2 = m*(1+ii);
x(j,k) = mean(x(i1:i2,1));
end
end
txtpos(:,1) = x(:);
for k = 1:length(htxt)
set(htxt(k),'position',txtpos(k,:))
end
tlcol = 0.5*[1,1,1];
txtpos = get(htxt,'extent');
txtpos = cat(1,txtpos{:});
xl = xlim;
yl = ylim;
y1 = min(yl);
y2 = min(txtpos(:,2));
y = linspace(y1,y2,n+1);
for k = 2:(n+1)
line(xl,[y(k),y(k)],'parent',gca,'clipping','off','color',tlcol)
end
line(xl(1)*[1,1],[y1,y2],'parent',gca,'clipping','off','color',tlcol)
line(xl(2)*[1,1],[y1,y2],'parent',gca,'clipping','off','color',tlcol)
for j = 1:n
newy = get(hsepln(j),'YData');
newy(newy==yl(2)) = y(j+1);
line(get(hsepln(j),'XData'),newy,'parent',gca,'clipping','off','color',tlcol)
end
delete(hsepln(1))
Trying it out:
x = randn(400,1);
y1 = nominal(randi(2,400,1),{'little','lots'});
y2 = nominal(randi(3,400,1),{'large','medium','small'});
y3 = nominal(randi(2,400,1),{'gourmet','plain','aardvark','potato'},[1,2,3,4]);
y = [y1,y2,y3];
variabilityplot(x,y)
If you think it's useful, I'll clean it up a bit and put it on the File Exchange soon.
8 Commenti
Matt Tearle
il 22 Mar 2013
@Eric: sorry it took a while, but if you're still interested, I've now added it to the FEx (link is in my answer above). The figure resizing issue is tricky -- in the end I took the easy(ish) way out and just turned that aspect off entirely.
Più risposte (1)
Shashank Prasanna
il 1 Feb 2013
But I am not certain there is something that generates a plot that looks exactly like that. You may have to generate a boxplot and add all the labels below them after that.
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