matlab实现花式箱体图

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⛄ 内容介绍

箱形图（英文：Box plot），又称为盒须图、盒式图、盒状图或箱线图，是一种用作显示一组数据分散情况资料的统计图。因型状如箱子而得名。在各种领域也经常被使用，常见于品质管理，快速识别异常值。

箱形图最大的优点就是不受异常值的影响，能够准确稳定地描绘出数据的离散分布情况，同时也利于数据的清洗。

⛄ 完整代码

%DABOXPLOT_DEMO a few examples of DABOXPLOT functionality ​%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%​rng('default')​% data in a cell array data1{1} = randn([60,4]); % Humansdata1{2} = randn([60,4]); % Dogsdata1{3} = randn([60,4]); % Goddata1{4} = randn([60,4]); % Potato​% data in a numreic array (+ grouping indices)data2 = [randn([30,4]); randn([30,4]);...         randn([30,4]); randn([30,4])];group_inx = [ones(1,30), 2.*ones(1,30), 3.*ones(1,30), 4.*ones(1,30)];​% skewed data in a numeric array (+ group indices)data3 = [pearsrnd(0,1,-1,5,25,1); pearsrnd(0,1,-2,7,25,1); ...    pearsrnd(0,1,1,8,25,1)];group_inx2 = [ones(1,25), 2.*ones(1,25), 3.*ones(1,25)];​​% data with group differences in a cell arraydata4{1} = randn([60,3]) + (0:0.5:1);          % Humansdata4{2} = randn([60,3]) + (2:2:6);            % Dogs​​group_names = {'Humans', 'Dogs' , 'God', 'Potato'};condition_names = {'Water', 'Land', 'Moon', 'Hyperspace'};​% an alternative color scheme for some plotsc =  [0.45, 0.80, 0.69;...      0.98, 0.40, 0.35;...      0.55, 0.60, 0.79;...      0.90, 0.70, 0.30];     figure('Name', 'daboxplot_demo','WindowStyle','docked');​% default boxplots for one group and three conditions subplot(3,3,1)h = daboxplot(data2(:,1:3),'groups',group_inx(1:30));​% non-filled boxplots and cutomized medianssubplot(3,3,2)h = daboxplot(data2(:,1:3),'groups',group_inx(1:60),'outsymbol','kx',...    'xtlabels', condition_names,'fill',0,'legend',group_names(1:2));ylabel('Performance');xl = xlim; xlim([xl(1), xl(2)+1]);     % make more space for the legendset(h.md,'Color','k','LineWidth',1.5); % customize median lines​​% filled boxplots, different color scheme, non-jittered scatter underneathsubplot(3,3,3)h = daboxplot(data2(:,1:3),'groups',group_inx(1:90),'outsymbol','k+',...    'xtlabels', condition_names,'legend',group_names(1:3),'color',c,...    'whiskers',0,'scatter',2,'jitter',0,'scattersize',13);ylabel('Performance');xl = xlim; xlim([xl(1), xl(2)+1]);    % make more space for the legend​​% transparent boxplots with no whiskers and jittered datapoints underneathsubplot(3,2,3)h = daboxplot(data1,'scatter',2,'whiskers',0,'boxalpha',0.7,...    'xtlabels', condition_names); ylabel('Performance');xl = xlim; xlim([xl(1), xl(2)+0.75]);       % make space for the legendlegend([h.bx(1,:)],group_names);            % add the legend manuallyset(gca,'FontSize',9);​​% different color scheme, a color flip, different outlier symbolsubplot(3,2,4)h = daboxplot(data2,'groups',group_inx,'xtlabels', condition_names,...    'colors',c,'fill',0,'whiskers',0,'scatter',2,'outsymbol','k*',...    'outliers',1,'scattersize',16,'flipcolors',1,'boxspacing',1.2,...    'legend',group_names); ylabel('Performance');xl = xlim; xlim([xl(1), xl(2)+0.75]); % make more space for the legendset(gca,'FontSize',9);​​% different color scheme, data scattered on topsubplot(3,2,5:6)h = daboxplot(data2,'groups',group_inx,...    'xtlabels', condition_names,'colors',c,'whiskers',0,...    'scatter',1,'scattersize',15,'scatteralpha',0.5,...    'boxspacing',0.8,'legend',group_names); ylabel('Performance');set(gca,'FontSize',9.5);xl = xlim; xlim([xl(1), xl(2)+0.2]);    % make more space for the legend​​%--------------------------------------------------------------------------figure('Name', 'daboxplot_demo2','WindowStyle','docked');​% three groups, one condition, indicating means with dotted linessubplot(2,2,1)h = daboxplot(data3,'groups',group_inx2,'mean',1,'color',c,...    'xtlabels',group_names);ylabel('Performance');​% using linkline to emphasize interaction effects (group*condition)subplot(2,2,2)h = daboxplot(data4,'linkline',1,...    'xtlabels', condition_names,'legend',group_names(1:3),...    'whiskers',0,'outliers',1,'outsymbol','r*','scatter',2,'boxalpha',0.6);ylabel('Performance'); ylim([-2.5 8.8]);xl = xlim; xlim([xl(1), xl(2)]);    % make more space for the legend​% TIP: to make the plots vertical use camroll(-90)​

function h = daboxplot(Y,varargin)%DABOXPLOT draws neat boxplots for multiple groups and multiple conditions %% Description:%%   Creates boxplots organized by condition and colored by group. Supports %   various options such as scatter, transparency, outliers, mean and %   group linking lines, scaling, etc, to maximize data readability. See %   daboxplot_demo. for examples of the use and functionality.  %% Syntax:%%   daboxplot(Y)%   daboxplot(Y,param,val,...)%   h = daboxplot(Y)%   h = daboxplot(Y,param,val,...)%% Input Arguments:%%   Y - data input (matrix or cell array) containing all conditions and all%   groups. If Y is a matrix, each column has to correspond to different%   condition, while the groups need to be specified in 'groups' vector.%   If Y is a cell array, each cell has to contain data matrices for each %   group (columns being different conditions). In such case, the grouping %   is done automatically based on the cell structure.   %% Optional Input Parameter Name/Value Pairs:%%   NAME              VALUE%%   'groups'          A vector containing grouping variables. By default%                     assumes a single group for a matrix data input. %%   'fill'            0 - non-filled boxplots (contrours only)%                     1 - boxplots filled with color (default)%%   'colors'          The RGB matrix for box colors of different groups%                     (each row corresponding to a different group). If%                     boxplots are filled, these are the fill colors with %                     the edges being black. If boxplots are not filled,%                     these colors are used for edges. These colors can be %                     also used for scatter data instead (see 'flipcolors')%                     Default colors: default matlab colors%   %   'whiskers'        Draws whiskers to show min and max data values after %                     disregarding the outliers (see outlier description)%                     0 - no whiskers%                     1 - draw whiskers (default)                     %%   'scatter'         0 - no datta scatter (deffault)%                     1 - on top of the boxplot %                     2 - underneath the boxplot%%   'scattersize'     Size of the scatter markers. Default: 15%%   'scattercolors'   Colors for the scattered data: {face, edge}%                     Default: {'k','w'}%%   'flipcolors'      Will flip the colors of scatter points and boxplots%                     0 - boxplots colored by group (default)%                     1 - scatter is colored by group%%   'scatteralpha'    Transparency of scattered data (between 0 and 1)%                     Default: 1 (completely non-transparent)%%   'jitter'          0 - do not jitter scattered data %                     1 - jitter scattered data (default)%%   'mean'            0 - do not mark the mean (default)%                     1 - mark the mean with a dotted line% %   'outliers'        Highlights the outliers in the plot. The outliers %                     are values below Q1-1.5*IQR and above Q3+1.5*IQR.%                     0 - do not highlight outliers  %                     1 - highlight outliers (default)%%   'outsymbol'       Symbol and color for highlighting outliers.%                     Default: 'rx' (red crosses).%%   'boxalpha'        Boxplot transparency (between 0 and 1)%                     Default: 1 (completely non-transparent)%%   'boxspacing'      A real number to scale spacing between boxes in the %                     same condition. Note that negative values result in %                     partially overlapping boxes within the same condition%                     Default: 1%%   'boxwidth'        A real number to scale the width of all boxes. Note %                     that this also controls the spacing between different %                     conditions (while spacings in the same condition are %                     controlled by 'boxspacing')                      %                     Default: 1%%   'linkline'        Superimposes lines linking boxplots across conditions%                     for each group. Helps to see more clearly possible %                     interaction effects between conditions and groups.%                     0 - no dash lines (default)%                     1 - dash lines%%   'xtlabels'        Xtick labels (a cell of chars) for conditions. If%                     there is only 1 condition and multiple groups, then %                     xticks and xtlabels will automatically mark different%                     groups.%                     Default: conditions/groups are numbered in the input %                     order%%   'legend'          Names of groups (a cell) for creating a legend%                     Default: no legend%%   'outlierfactor'   Multiple of the interquartile range used to find%                     outliers. Outliers are values below %                     Q1-outlierfactor*IQR and above Q3+outlierfactor*IQR%                     Default: 1.5%% Output Arguments:%%   h - a structure containing handles for further customization of%   the produced plot:%       cpos - condition positions%       gpos - group positions%       %       graphics objects:%       bx - boxplot box %       md - median line%       mn - mean line%       sc - scattered data markers%       ot - outlier markers%       wh - whiskers %       ln - line linking boxplots %       lg - legend%%% For examples have a look at daboxplot_demo.m%%% Povilas Karvelis <karvelis.povilas@gmail.com>% 15/04/2019%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%​h = struct;p = inputParser;​% specify default optionsaddOptional(p, 'groups', []);addOptional(p, 'fill', 1); addOptional(p, 'colors', get(gca,'colororder'));addOptional(p, 'whiskers', 1);addOptional(p, 'scatter', 0); addOptional(p, 'scattersize', 15)addOptional(p, 'scattercolors', {'k','w'}); addOptional(p, 'flipcolors', 0);addOptional(p, 'scatteralpha', 1); addOptional(p, 'jitter', 1);addOptional(p, 'mean', 0);addOptional(p, 'outliers', 1); addOptional(p, 'outsymbol', 'rx'); addOptional(p, 'boxalpha', 1);addOptional(p, 'boxspacing', 1);addOptional(p, 'boxwidth', 1);addOptional(p, 'linkline',0);addOptional(p, 'xtlabels', []);addOptional(p, 'legend', []);addOptional(p, 'outlierfactor', 1.5);​​% parse the input optionsparse(p, varargin{:});confs = p.Results;    ​% get group indices and labelsif ~isempty(confs.groups)    [Gi,Gn,Gv] = grp2idx(confs.groups);    num_groups = numel(Gv);end​% find the number of groupsif iscell(Y)        num_groups = numel(Y);        y = []; Gi = [];        for g = 1:num_groups        y = [y; Y{g}];        Gi = [Gi; g*ones(size(Y{g},1),1)];    end              % default numbered group labels    if ~exist('Gn','var')        for g = 1:num_groups            Gn{g} = num2str(g);        end    end        Y = y; % replace the cell with a data array    elseif ismatrix(Y)     % assume 1 group if none are specified    if isempty(confs.groups)       Gi = ones(size(Y,1),1);       num_groups = 1;    end       end        % find condition positionsif any(size(Y)==1)    Y = Y(:);    cpos = 1;else    cpos = 1:size(Y,2);endnum_locs = numel(cpos);​% use condition positions to scale spacingsgpos=[];if num_locs==1    gpos = (1:num_groups)';    box_width = 1/3*confs.boxwidth;    cpos=gpos;else        if num_groups==1        gpos = cpos;        box_width = 1/3*confs.boxwidth;    else        box_width = (2/3)/(num_groups+1)*confs.boxwidth;  % calculate box width         loc_sp = (box_width/3)*confs.boxspacing; % local spacing between boxplots​        % set group positions for each group        for g = 1:num_groups            gpos = [gpos; cpos + (g-(num_groups+1)/2)*(box_width + loc_sp)];        end    endend​h.gpos = gpos;h.cpos = cpos; ​% loop over groupsfor g = 1:num_groups         % get percentiles    pt = prctile(Y(Gi==g,:),[2 9 25 50 75 91 98]);     means = mean(Y(Gi==g,:));        if size(pt,1)==1 pt=pt'; end % a fix for plotting one condition        IQR = (pt(5,:)-pt(3,:));            % create coordinates for drawing boxes    y25 = reshape([pt(3,:); pt(3,:)], 1, []);    y75 = reshape([pt(5,:); pt(5,:)], 1, []);​    x1 = [gpos(g,:) - box_width/2; gpos(g,:) - box_width/2];    x2 = [gpos(g,:) + box_width/2; gpos(g,:) + box_width/2];​    box_ycor = [y75; y25];            box_xcor = reshape([x1; x2],2,[]);     box_mdcor = reshape([pt(4,:); pt(4,:)], 1, []);    box_mncor = reshape([means; means], 1, []);        % create coordinates for drawing whiskers with cross-hatches and ends        hat_xcor = [gpos(g,:) - box_width/4; gpos(g,:) + box_width/4];        whi_xcor = [gpos(g,:); gpos(g,:)];                % draw one box at a time    for k = 1:num_locs                data_vals = Y(Gi==g,k); % data for a single box                % determine outliers and whisker length         ol = data_vals<(pt(3,k)-confs.outlierfactor*IQR(k)); % indices of lower outliers        ou = data_vals>(pt(5,k)+confs.outlierfactor*IQR(k)); % indices of upper outliers    ​        whi_ycor(:,1,k) = [min(data_vals(~ol)), pt(3,k)]; % lower whisker                whi_ycor(:,2,k) = [max(data_vals(~ou)), pt(5,k)]; % upper whisker                        % jitter or not        if confs.jitter==1            xdata =  gpos(g,k).*ones(numel(Y(Gi==g,k)),1) + ...                (box_width/3).*(0.5 - rand(numel(Y(Gi==g,k)),1));        elseif confs.jitter==0            xdata = gpos(g,k).*ones(numel(Y(Gi==g,k)),1);        end        ​        % index values for each box        wk = (1:2)+2*(k-1);        Xx = box_xcor(1:2,wk);         Yy = box_ycor(1:2,wk); ​        % filled or not filled boxes        if confs.fill==0                        % no fill box            h.bx(k,g) = line([Xx(:,1)' Xx(1,:) Xx(:,2)' Xx(2,:)],...                [Yy(:,1)' Yy(1,:) Yy(:,2)' Yy(2,:)],...                'color',confs.colors(g,:),'LineWidth',1.5);             hold on;                                % draw the median            h.md(k,g) = line(Xx(1,:), box_mdcor(wk),...                'color',confs.colors(g,:), 'LineWidth', 2);                                    % draw the mean            if confs.mean==1                h.mn(k,g) = line(Xx(1,:),box_mncor(wk),'LineStyle',':',...                    'color',confs.colors(g,:),'LineWidth', 1.5);            end                               elseif confs.fill==1            % box filled with color             h.bx(k,g) = fill([Xx(:,1)' Xx(1,:) Xx(:,2)' Xx(2,[2,1])],...                 [Yy(:,1)' Yy(1,:) Yy(:,2)' Yy(2,:)],confs.colors(g,:));                        set(h.bx(k,g),'FaceAlpha',confs.boxalpha);             hold on;​            % draw the median            h.md(k,g) = line(Xx(1,:), box_mdcor(wk),...                'color','k', 'LineWidth', 2);                        % draw the mean            if confs.mean==1                h.mn(k,g) = line(Xx(1,:),box_mncor(wk),'LineStyle',':',...                    'color','k','LineWidth', 1.5);            end        end                        ox = data_vals>max(data_vals); % default - no outliers                % draw outliers        if confs.outliers==1                        ox = data_vals<whi_ycor(1,1,k) | data_vals>whi_ycor(1,2,k);            h.ot(k,g) = scatter(xdata(ox),data_vals(ox),confs.scattersize,...                confs.outsymbol);                    end                        if confs.whiskers==1            % draw whiskers            h.wh(k,g,:) = plot(whi_xcor(:,k),whi_ycor(:,1,k),'k-',...                 hat_xcor(:,k),[whi_ycor(1,1,k) whi_ycor(1,1,k)],'k-',...                 whi_xcor(:,k),whi_ycor(:,2,k),'k-',...                 hat_xcor(:,k),[whi_ycor(1,2,k) whi_ycor(1,2,k)],'k-',...                 'LineWidth',1);                                      end ​        % scatter on top of the boxplots        if confs.scatter==1 || confs.scatter==2                        h.sc(k,g) = scatter(xdata(~ox),data_vals(~ox),...                confs.scattersize,...                'MarkerFaceColor', confs.scattercolors{1},...                'MarkerEdgeColor', confs.scattercolors{2},...                'MarkerFaceAlpha', confs.scatteralpha);             hold on;            end                    end                    % put scattered data underneath boxplots    if confs.scatter==2        uistack(h.sc(:,g),'bottom')    end           if confs.linkline==1       h.ln(g) = line(gpos(g,:),pt(4,:),'color',confs.colors(g,:),...           'LineStyle','-.','LineWidth',1.5);     end    end​% move lines to the backgroundif confs.linkline==1    uistack(h.ln,'bottom')end​​% flip scatter and box colors and make a legendif confs.flipcolors==1            box_class = class(h.bx); % box filled or no        if strcmp(box_class,'matlab.graphics.primitive.Patch')        set(h.bx,'FaceColor',confs.scattercolors{1});        set(h.md,'Color',confs.scattercolors{2});                if confs.mean==1            set(h.mn,'Color',confs.scattercolors{2});        end    else        set(h.bx,'Color',confs.scattercolors{1});        set(h.md,'Color',confs.scattercolors{1});                if confs.mean==1            set(h.mn,'Color',confs.scattercolors{1});        end    end​    for g = 1:num_groups       set(h.sc(:,g),'MarkerFaceColor',confs.colors(g,:))    end        % add a legend based on scatter colors    if ~isempty(confs.legend)        h.lg = legend(h.sc(1,:),confs.legend);    endelse        % add a legend based on box colors    if ~isempty(confs.legend)        h.lg = legend(h.bx(1,:),confs.legend);    endend​% set ticks and labelsset(gca,'XTick',cpos,'XTickLabels',cpos,'box','off');if ~isempty(confs.xtlabels)    set(gca,'XTickLabels',confs.xtlabels,'XTick',cpos);end  ​xlim([gpos(1)-3*box_width, gpos(end)+3*box_width]); % adjust x-axis margins​end​

⛄ 运行结果

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