【可视化】基于matlab绘制分组或堆叠条形图

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本文围绕Matlab展开，介绍了分组或堆叠条形图，包括类型、优缺点及使用注意事项，还阐述其在多领域的应用。同时列举了Matlab在智能优化算法、机器学习、图像处理、路径规划等多个科研领域的应用场景及相关问题。

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分组或堆叠条形图

分组或堆叠条形图是将数据按类别分组并以条形图的形式显示的一种图表。它可以帮助我们比较不同类别的数据，并了解它们之间的关系。分组或堆叠条形图通常用于显示分类数据，例如性别、年龄、收入等。

分组或堆叠条形图有两种常见的类型：分组条形图和堆叠条形图。分组条形图将不同类别的条形图并排放置，而堆叠条形图将不同类别的条形图叠加在一起。分组条形图更适合于比较不同类别的数据，而堆叠条形图更适合于显示不同类别的数据在总数据中的占比。

分组或堆叠条形图的优点在于它可以直观地显示数据，并且易于理解。它还可以帮助我们发现数据中的趋势和规律。但是，分组或堆叠条形图也有其局限性。例如，它只能显示有限数量的数据，并且当数据量较大时，分组或堆叠条形图可能会变得难以阅读。

为了使分组或堆叠条形图更加有效，我们可以注意以下几点：

选择合适的类别：分组或堆叠条形图的类别应该是有意义的，并且应该与研究问题相关。
使用合适的颜色：分组或堆叠条形图的颜色应该易于区分，并且应该与类别的含义相匹配。
添加标签和注释：分组或堆叠条形图应该有清晰的标签和注释，以便读者能够理解图表中的数据。
避免使用过多的数据：分组或堆叠条形图中的数据量应该适中，以便读者能够轻松地理解图表中的信息。

分组或堆叠条形图是一种常用的图表类型，它可以帮助我们比较不同类别的数据，并了解它们之间的关系。通过注意上述几点，我们可以使分组或堆叠条形图更加有效地传达信息。

分组或堆叠条形图的应用

分组或堆叠条形图广泛应用于各个领域，例如：

市场营销：分组或堆叠条形图可以用来比较不同产品或服务的销售额，或者比较不同地区或市场的销售额。
金融：分组或堆叠条形图可以用来比较不同股票或基金的收益率，或者比较不同国家的经济增长率。
教育：分组或堆叠条形图可以用来比较不同学校或班级的考试成绩，或者比较不同学生的学习成绩。
医疗保健：分组或堆叠条形图可以用来比较不同疾病的发病率或死亡率，或者比较不同治疗方法的有效性。

分组或堆叠条形图是一种简单而有效的图表类型，它可以帮助我们比较不同类别的数据，并了解它们之间的关系。通过注意上述几点，我们可以使分组或堆叠条形图更加有效地传达信息。

📣 完整代码

% daboxplot_demo a few examples of daboxplot functionality %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%clear allrng('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);            % Dogsgroup_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 = dabarplot(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(2,3,1)h = daboxplot(data3,'groups',group_inx2,'mean',1,'color',c,...    'xtlabels',group_names);ylabel('Performance');set(gca,'FontSize',12)% using linkline to emphasize interaction effects (group*condition)subplot(2,3,2)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 legendset(gca,'FontSize',12)% using withinline to emphasize within group differences between conditionssubplot(2,3,3)h = daboxplot(data4{1}(:,1:2),'xtlabels', condition_names(1:2),'whiskers',0,...    'scatter',1,'scattersize',25,'scatteralpha',0.6,'withinlines',1,'outliers',0);set(gca,'FontSize',12)% 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)%%   'outfactor'       Multiple of the interquartile range used to find%                     outliers: below Q1-outfactor*IQR and above %                     Q3+outfactor*IQR%                     Default: 1.5%%   '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%%   'withinlines'     Draws a line between each pair of data points in %                     paired datasets. Meant to be used only when plotting%                     one group.%                     0 - no lines (default)%                     1 - 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%%% 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% Also see: daviolinplot.m and dabarplot.m%%% Povilas Karvelis% 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, 'outfactor', 1.5);addOptional(p, 'outsymbol', 'rx'); addOptional(p, 'boxalpha', 1);addOptional(p, 'boxspacing', 1);addOptional(p, 'boxwidth', 1);addOptional(p, 'linkline',0);addOptional(p, 'withinlines',0);addOptional(p, 'xtlabels', []);addOptional(p, 'legend', []);% 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    endendh.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 % 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.outfactor*IQR(k)); % indices of lower outliers        ou = data_vals>(pt(5,k)+confs.outfactor*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                % store data in case it's needed for withinlines        scdata(:,:,k,g) = [xdata, data_vals];        % 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        % draw whiskers        if confs.whiskers==1                        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             % link the medians of the boxplots with a line    if confs.linkline==1       h.ln(g) = line(gpos(g,:),pt(4,:),'color',confs.colors(g,:),...           'LineStyle','-.','LineWidth',1.5);     end        % link individual within group data points    if confs.withinlines==1        for s = 1:size(scdata,1)                            h.wl(g) = plot(squeeze(scdata(s,1,:,g)),...                squeeze(scdata(s,2,:,g)),'color', [0.8 0.8 0.8]);            uistack(h.wl(g),'bottom')        end    end    % put scattered data underneath boxplots    if confs.scatter==1                if confs.mean==1            uistack(h.mn(:,g),'bottom')        end        uistack(h.md(:,g),'bottom')        uistack(h.bx(:,g),'bottom')                if confs.whiskers==1            uistack(h.wh(:,g,:),'bottom')                end           elseif confs.scatter==2        uistack(h.sc(:,g),'bottom')    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 marginsend