MATLAB: Boxplot groups by mask set

boxplotgroupinggroups

I have a vector of data, and a set of masks defining my (possibly overlapping) groups:

data = rand(100,1)
grpMasks = [(1:100)'<25,  (1:100)'<60&(1:100)'>10,  (1:100)'>40,  rand(100,1)>0.5]

So my data is 100-by-1, I have 4 groups in a 100-by-4 logical mask. I want to make a boxplot with 4 boxes, 1 per mask.

boxplot(data, grpMasks)

Makes N boxes, where N is the number of unique row combinations in grpMasks.

I know that I can loop from 1 to 4, make a single boxplot and then shift each box's X-location, but I feel like that's unnecessarily messy. I've got my data, I've got a format of my groups. Can boxplot handle this form of grouping?

Best Answer

Ah! Here's my solution. Repeat the data for as many groups as you have, and then NaN out the data not belonging to each group:

data = rand(100,1);
grpMasks = [(1:100)'<25,  (1:100)'<60&(1:100)'>10,  (1:100)'>40,  rand(100,1)>0.5];
numGrps = size(grpMasks,2);
allData = data * ones(1,numGrps);
allData(~grpMasks) = nan;
boxplot(allData);

Related Solutions

MATLAB: Boxplot with vectors of different lengths

BOXPLOT works with grouping variables, so you can manually append all of your data together and then create a grouping variable that lets boxplot know which belongs to first and which for second. Take a look at the example below:

>> c_1=rand(1,20);
>> c_2=rand(1,100);
>> C = [c_1 c_2];
>> grp = [zeros(1,20),ones(1,100)];
>> boxplot(C,grp)

MATLAB: How to create variability charts

EDIT: file added to MATLAB File Exchange. Share and enjoy!

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.

Best Answer

Related Solutions

MATLAB: Boxplot with vectors of different lengths

MATLAB: How to create variability charts

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