Compute the statistics used in matlab boxplots.

boxplot_statistics.m

function [q1,q2,q3,w0,w1,outliers] = boxplot_statistics(data, whisker)
    if ~exist('whisker', 'var')
        % whisker is 1.5 by default
        whisker = 1.5;
    end

    % quantile(data,3) will return the 25th, 50th, and 75th percentile
    % for each column
    quants = quantile(data, 3);
    q1 = quants(1,:);
    q2 = quants(2,:);
    q3 = quants(3,:);

    % Compute the upper and lower thresholds for outlier classification
    upper_thresh = q3 + whisker .* (q3-q1);
    lower_thresh = q1 - whisker .* (q3-q1);

    % Outliers are points above the upper_thresh or below lower_thresh
    outliers = (data > upper_thresh) | (data < lower_thresh);

    % To compute the whiskers, take max and min (per column). Setting
    % outlier values to NaN causes them to be ignored.
    data(outliers) = NaN;
    w0 = min(data,[],1);
    w1 = max(data,[],1);
end