Commit 966a1b48 authored by ratto's avatar ratto
Browse files

boxplot utility, used in identification.

git-svn-id: https://www.dynare.org/svn/dynare/trunk@3380 ac1d8469-bf42-47a9-8791-bf33cf982152
parent a02dd60d
function sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% sout = myboxplot (data,notched,symbol,vertical,maxwhisker)
% % % % endif
if nargin < 5 | isempty(maxwhisker), maxwhisker = 1.5; end
if nargin < 4 | isempty(vertical), vertical = 1; end
if nargin < 3 | isempty(symbol), symbol = ['+','o']; end
if nargin < 2 | isempty(notched), notched = 0; end
if length(symbol)==1, symbol(2)=symbol(1); end
if notched==1, notched=0.25; end
a=1-notched;
% ## figure out how many data sets we have
if iscell(data),
nc = length(data);
else
% if isvector(data), data = data(:); end
nc = size(data,2);
end
% ## compute statistics
% ## s will contain
% ## 1,5 min and max
% ## 2,3,4 1st, 2nd and 3rd quartile
% ## 6,7 lower and upper confidence intervals for median
s = zeros(7,nc);
box = zeros(1,nc);
whisker_x = ones(2,1)*[1:nc,1:nc];
whisker_y = zeros(2,2*nc);
outliers_x = [];
outliers_y = [];
outliers2_x = [];
outliers2_y = [];
for i=1:nc
% ## Get the next data set from the array or cell array
if iscell(data)
col = data{i}(:);
else
col = data(:,i);
end
% ## Skip missing data
% % % % % % % col(isnan(col) | isna (col)) = [];
col(isnan(col)) = [];
% ## Remember the data length
nd = length(col);
box(i) = nd;
if (nd > 1)
% ## min,max and quartiles
% s(1:5,i) = statistics(col)(1:5);
s(1,i)=min(col);
s(5,i)=max(col);
s(2,i)=myprctilecol(col,25);
s(3,i)=myprctilecol(col,50);
s(4,i)=myprctilecol(col,75);
% ## confidence interval for the median
est = 1.57*(s(4,i)-s(2,i))/sqrt(nd);
s(6,i) = max([s(3,i)-est, s(2,i)]);
s(7,i) = min([s(3,i)+est, s(4,i)]);
% ## whiskers out to the last point within the desired inter-quartile range
IQR = maxwhisker*(s(4,i)-s(2,i));
whisker_y(:,i) = [min(col(col >= s(2,i)-IQR)); s(2,i)];
whisker_y(:,nc+i) = [max(col(col <= s(4,i)+IQR)); s(4,i)];
% ## outliers beyond 1 and 2 inter-quartile ranges
outliers = col((col < s(2,i)-IQR & col >= s(2,i)-2*IQR) | (col > s(4,i)+IQR & col <= s(4,i)+2*IQR));
outliers2 = col(col < s(2,i)-2*IQR | col > s(4,i)+2*IQR);
outliers_x = [outliers_x; i*ones(size(outliers))];
outliers_y = [outliers_y; outliers];
outliers2_x = [outliers2_x; i*ones(size(outliers2))];
outliers2_y = [outliers2_y; outliers2];
elseif (nd == 1)
% ## all statistics collapse to the value of the point
s(:,i) = col;
% ## single point data sets are plotted as outliers.
outliers_x = [outliers_x; i];
outliers_y = [outliers_y; col];
else
% ## no statistics if no points
s(:,i) = NaN;
end
end
% % % % if isempty(outliers2_y)
% % % % outliers2_y=
% ## Note which boxes don't have enough stats
chop = find(box <= 1);
% ## Draw a box around the quartiles, with width proportional to the number of
% ## items in the box. Draw notches if desired.
box = box*0.23/max(box);
quartile_x = ones(11,1)*[1:nc] + [-a;-1;-1;1;1;a;1;1;-1;-1;-a]*box;
quartile_y = s([3,7,4,4,7,3,6,2,2,6,3],:);
% ## Draw a line through the median
median_x = ones(2,1)*[1:nc] + [-a;+a]*box;
% median_x=median(col);
median_y = s([3,3],:);
% ## Chop all boxes which don't have enough stats
quartile_x(:,chop) = [];
quartile_y(:,chop) = [];
whisker_x(:,[chop,chop+nc]) = [];
whisker_y(:,[chop,chop+nc]) = [];
median_x(:,chop) = [];
median_y(:,chop) = [];
% % % %
% ## Add caps to the remaining whiskers
cap_x = whisker_x;
cap_x(1,:) =cap_x(1,:)- 0.05;
cap_x(2,:) =cap_x(2,:)+ 0.05;
cap_y = whisker_y([1,1],:);
% #quartile_x,quartile_y
% #whisker_x,whisker_y
% #median_x,median_y
% #cap_x,cap_y
%
% ## Do the plot
mm=min(min(data));
MM=max(max(data));
if vertical
plot (quartile_x, quartile_y, 'b', ...
whisker_x, whisker_y, 'b--', ...
cap_x, cap_y, 'k', ...
median_x, median_y, 'r', ...
outliers_x, outliers_y, [symbol(1),'r'], ...
outliers2_x, outliers2_y, [symbol(2),'r']);
set(gca,'XTick',1:nc);
set(gca, 'XLim', [0.5, nc+0.5]);
set(gca, 'YLim', [mm-(MM-mm)*0.05-eps, MM+(MM-mm)*0.05+eps]);
else
% % % % % plot (quartile_y, quartile_x, "b;;",
% % % % % whisker_y, whisker_x, "b;;",
% % % % % cap_y, cap_x, "b;;",
% % % % % median_y, median_x, "r;;",
% % % % % outliers_y, outliers_x, [symbol(1),"r;;"],
% % % % % outliers2_y, outliers2_x, [symbol(2),"r;;"]);
end
if nargout,
sout=s;
end
% % % endfunction
\ No newline at end of file
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