Advanced examples for gramm

Grouping options in gramm

websave('example_data','https://github.com/piermorel/gramm/raw/master/sample_data/example_data.mat'); %Download data from repository

load example_data.mat

 

clear g

g(1,1)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g(1,1).geom_point();

g(1,1).set_names('x','Horsepower','y','MPG');

g(1,1).set_title('No groups');

 

 

g(1,2)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5,'color',cars.Cylinders);

g(1,2).geom_point();

g(1,2).set_names('x','Horsepower','y','MPG','color','# Cyl');

g(1,2).set_title('color');

 

g(1,3)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5,'lightness',cars.Cylinders);

g(1,3).geom_point();

g(1,3).set_names('x','Horsepower','y','MPG','lightness','# Cyl');

g(1,3).set_title('lightness');

 

g(2,1)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5,'size',cars.Cylinders);

g(2,1).geom_point();

g(2,1).set_names('x','Horsepower','y','MPG','size','# Cyl');

g(2,1).set_title('size');

 

g(2,2)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5,'marker',cars.Cylinders);

g(2,2).geom_point();

g(2,2).set_names('x','Horsepower','y','MPG','marker','# Cyl');

g(2,2).set_title('marker');

 

g(2,3)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5,'linestyle',cars.Cylinders);

g(2,3).geom_line();

g(2,3).set_names('x','Horsepower','y','MPG','linestyle','# Cyl');

g(2,3).set_title('linestyle');

 

g(3,1)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g(3,1).facet_grid(cars.Cylinders,[]);

g(3,1).geom_point();

g(3,1).set_names('x','Horsepower','y','MPG','row','# Cyl');

g(3,1).set_title('subplot rows');

 

 

g(3,2)=gramm('x',cars.Horsepower,'y',cars.MPG,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g(3,2).facet_grid([],cars.Cylinders);

g(3,2).geom_point();

g(3,2).set_names('x','Horsepower','y','MPG','column','# Cyl');

g(3,2).set_title('subplot columns');

 

 

figure('Position',[100 100 800 800]);

g.draw();

Additional visualization layers

Visualizing X densities

clear g

 

g(1,1)=gramm('x',cars.Horsepower,'color',cars.Cylinders,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g(1,2)=copy(g(1));

g(2,1)=copy(g(1));

g(2,2)=copy(g(1));

 

%Raw data as raster plot

g(1,1).facet_grid(cars.Origin_Region,[]);

g(1,1).geom_raster();

g(1,1).set_title('geom_raster()');

 

%Histogram

g(1,2).facet_grid(cars.Origin_Region,[]);

g(1,2).stat_bin('nbins',8);

g(1,2).set_title('stat_bin()');

 

%Kernel smoothing density estimate

g(2,1).facet_grid(cars.Origin_Region,[]);

g(2,1).stat_density();

g(2,1).set_title('stat_density()');

 

% Q-Q plot for normality

g(2,2).facet_grid(cars.Origin_Region,[]);

g(2,2).stat_qq();

g(2,2).axe_property('XLim',[-5 5]);

g(2,2).set_title('stat_qq()');

 

g.set_names('x','Horsepower','color','# Cyl','row','','y','');

g.set_title('Visualization of X densities');

figure('Position',[100 100 800 550]);

g.draw();

Visualizing custom confidence intervals

cars_summary=rowfun(@(hp)deal(nanmean(hp),bootci(200,@(x)nanmean(x),hp)'),cars(cars.Cylinders~=3 & cars.Cylinders~=5,:),...

'InputVariables',{'Horsepower'},...

'GroupingVariables',{'Origin_Region' 'Cylinders'},...

'OutputVariableNames',{'hp_mean' 'hp_ci'});

 

clear g

%Bars and error bars

g(1,1)=gramm('x',cars_summary.Origin_Region,'y',cars_summary.hp_mean,...

'ymin',cars_summary.hp_ci(:,1),'ymax',cars_summary.hp_ci(:,2),'color',cars_summary.Cylinders);

g(1,1).set_names('x','Origin','y','Horsepower','color','# Cylinders');

g(1,1).geom_bar('dodge',0.8,'width',0.6);

g(1,1).geom_interval('geom','black_errorbar','dodge',0.8,'width',1);

 

%points and error bars

g(1,2)=gramm('x',categorical(cars_summary.Cylinders),'y',cars_summary.hp_mean,...

'ymin',cars_summary.hp_ci(:,1),'ymax',cars_summary.hp_ci(:,2),'color',cars_summary.Origin_Region);

g(1,2).set_names('color','Origin','y','Horsepower','x','# Cylinders');

g(1,3)=copy(g(1,2));

g(1,2).set_color_options('map','matlab');

 

g(1,2).geom_point('dodge',0.2);

g(1,2).geom_interval('geom','errorbar','dodge',0.2,'width',0.8);

 

%Shaded area

g(1,3).geom_interval('geom','area');

 

figure('Position',[100 100 800 450]);

g.axe_property('YLim',[-10 190]);

g.draw();

Visualizing repeated densities (e.g. spike densities)

%We generate 50 spike trains, with 3 groups

N=50;

cval={'A' 'B' 'C'};

cind=randi(3,N,1);

c=cval(cind);

train_template=[zeros(1,300) ones(1,200)];

%Pseudo-poisson spike trains

spike_train=cell(N,1);

for k=1:N

temp_train=rand*0.05+train_template/(cind(k)*8);

U=rand(size(temp_train));

spike_train{k}=find(U<temp_train);

end

 

clear g

g(1,1)=gramm('x',spike_train,'color',c);

g(1,1).geom_raster();

g(1,1).set_title('geom_raster()');

 

g(1,2)=gramm('x',spike_train,'color',c);

g(1,2).stat_bin('nbins',25,'geom','line');

g(1,2).set_title('stat_bin()');

 

g.set_names('x','Time','y','');

g.set_title('Visualization of spike densities');

 

figure('Position',[100 100 800 350]);

g.draw();

Visualizing x-y difference with inset histogram using stat_cornerhist()

%Generate sample data

N=200;

x=randn(1,N*4);

y=x+randn(1,N*4)/2;

c=repmat([1 2],1,N*2);

b=repmat([1 2 2 2],1,N);

y(c==1 & b==2)=y(c==1 & b==2)+2;

 

 

clear g

g=gramm('x',x,'y',y,'color',c);

g.facet_grid([],b);

g.geom_point();

g.stat_cornerhist('edges',-4:0.1:2,'aspect',0.5);

g.geom_abline();

 

g.set_title('Visualize x-y with stat_cornerhist()');

figure('Position',[100 100 800 600]);

g.draw();

 

%Possibility to use axe handles of the inset axes to add elements or change

%properties

plot(g.results.stat_cornerhist(2).child_axe_handle,[-2 -2],[0 50],'k:','LineWidth',2)

Plotting text or labeling with geom_label()

%Create short version of model names by removing manufacturer

cars.ModelShort=cellfun(@(ma,mo)mo(length(ma)+1:end),cars.Manufacturer,cars.Model,'UniformOutput',false);

 

figure('Position',[100 100 800 500]);

clear g

%Provide 'label' as data

g=gramm('x',cars.Horsepower,'y',cars.Acceleration,...

'label',cars.ModelShort,'color',cars.Manufacturer,'subset',strcmp(cars.Origin_Region,'Japan'));

%geom_label() takes the same arguments as text().

%'BackgroundColor','EdgeColor' and 'Color' can be set to 'auto'

g.geom_label('VerticalAlignment','middle','HorizontalAlignment','center','BackgroundColor','auto','Color','k');

g.set_limit_extra([0.2 0.2],[0.1 0.1]);

g.set_names('color','Manufacturer','x','Horsepower','y','Acceleration');

g.set_color_options('map','brewer2');

g.draw();

 

% geom_label works when 3D data is provided

figure('Position',[100 100 800 500]);

g=gramm('x',cars.Horsepower,'y',cars.Acceleration,'z',cars.MPG,...

'label',cars.ModelShort,'color',cars.Manufacturer,'subset',strcmp(cars.Origin_Region,'Japan'));

g.geom_label('VerticalAlignment','middle','HorizontalAlignment','center','BackgroundColor','auto','Color','k');

g.set_limit_extra([0.2 0.2],[0.1 0.1]);

g.set_names('color','Manufacturer','x','Horsepower','y','Acceleration','z','MPG');

g.set_color_options('map','brewer2');

g.draw();

 

 

figure('Position',[100 100 800 500]);

clear g

%Compute number of models outside of gramm so that the output can be used

%as label

temp_table=rowfun(@numel,cars,'OutputVariableNames','N','GroupingVariables',{'Origin_Region','Model_Year'},'InputVariables','MPG');

g=gramm('x',temp_table.Model_Year,'y',temp_table.N,'color',temp_table.Origin_Region,'label',temp_table.N);

g.geom_bar('dodge',0.7,'width',0.6);

g.geom_label('color','k','dodge',0.7,'VerticalAlignment','bottom','HorizontalAlignment','center');

g.set_names('color','Origin','x','Year','y','Number of models');

g.draw();

In-depth options

Scaling options for facet_grid()

• By default 'scale','fixed' all subplots have the same limits
• 'scale','free_x': subplots on the same columns have the same x limits
• 'scale','free_y': subplots on the same rows have the same y limits
• 'scale','free': subplots on the same rows have the same y limits, subplots on the same columns have the same x limits
• 'scale','independent': subplots have independent limits

% Generating fake data

N=1000;

colval={'A' 'B' 'C'};

rowval={'I' 'II'};

cind=randi(3,N,1);

c=colval(cind);

rind=randi(2,N,1);

r=rowval(rind);

 

x=randn(N,1);

y=randn(N,1);

 

x(cind==1 & rind==1)=x(cind==1 & rind==1)*5;

x=x+cind*3;

y(cind==3 & rind==2)=y(cind==3 & rind==2)*3;

y=y-rind*4;

 

clear g

g(1,1)=gramm('x',x,'y',y,'color',c,'lightness',r);

g(1,2)=copy(g(1));

g(2,1)=copy(g(1));

g(2,2)=copy(g(1));

g(3,1)=copy(g(1));

g(3,2)=copy(g(1));

 

g(1,1).geom_point();

g(1,1).set_title('No facets');

 

g(1,2).facet_grid(r,c);

g(1,2).geom_point();

g(1,2).no_legend();

g(1,2).set_title('facet_grid()');

 

 

g(2,1).facet_grid(r,c,'scale','free');

g(2,1).geom_point();

g(2,1).no_legend();

g(2,1).set_title('facet_grid(''scale'',''free'')');

 

g(2,2).facet_grid(r,c,'scale','free','space','free');

g(2,2).geom_point();

g(2,2).no_legend();

g(2,2).set_title('facet_grid(''scale'',''free'',''space'',''free'')');

 

g(3,1).facet_grid(r,c,'scale','free_x');

g(3,1).geom_point();

g(3,1).no_legend();

g(3,1).set_title('facet_grid(''scale'',''free_x'')');

 

g(3,2).facet_grid(r,c,'scale','independent');

g(3,2).geom_point();

g(3,2).no_legend();

g(3,2).set_title('facet_grid(''scale'',''independent'')');

 

g.set_color_options('lightness_range',[40 80],'chroma_range',[80 40]);

g.set_names('column','','row','');

%g.axe_property('color',[0.9 0.9 0.9],'XGrid','on','YGrid','on','GridColor',[1 1 1],'GridAlpha',0.8,'TickLength',[0 0],'XColor',[0.3 0.3 0.3],'YColor',[0.3 0.3 0.3])

 

gf = copy(g);

 

figure('Position',[100 100 800 800]);

g.set_title('facet_grid() options');

g.draw();

%Export

g.export('file_name','scaling_export','file_type','png');

Options for creating histograms with stat_bin()

• 'bar' (default), where color groups are side-by-side (dodged)
• 'stacked_bar'
• 'line'
• 'overlaid_bar'
• 'point'
• 'stairs'

%Create variables

x=randn(1200,1)-1;

cat=repmat([1 1 1 2],300,1);

x(cat==2)=x(cat==2)+2;

 

clear g5

g5(1,1)=gramm('x',x,'color',cat);

g5(1,2)=copy(g5(1));

g5(1,3)=copy(g5(1));

g5(2,1)=copy(g5(1));

g5(2,2)=copy(g5(1));

g5(2,3)=copy(g5(1));

 

g5(1,1).stat_bin(); %by default, 'geom' is 'bar', where color groups are side-by-side (dodged)

g5(1,1).set_title('''bar'' (default)');

 

g5(1,2).stat_bin('geom','stacked_bar'); %Stacked bars option

g5(1,2).set_title('''stacked_bar''');

 

g5(2,1).stat_bin('geom','line'); %Draw lines instead of bars, easier to visualize when lots of categories, default fill to edges !

g5(2,1).set_title('''line''');

 

g5(2,2).stat_bin('geom','overlaid_bar'); %Overlaid bar automatically changes bar coloring to transparent

g5(2,2).set_title('''overlaid_bar''');

 

g5(1,3).stat_bin('geom','point');

g5(1,3).set_title('''point''');

 

 

g5(2,3).stat_bin('geom','stairs'); %Default fill is edges

g5(2,3).set_title('''stairs''');

 

g5.set_title('''geom'' options for stat_bin()');

 

figure('Position',[100 100 800 600]);

g5.draw();

• 'face'
• 'all'
• 'edge'
• 'transparent'

clear g6

g6(1,1)=gramm('x',x,'color',cat);

g6(1,2)=copy(g6(1));

g6(1,3)=copy(g6(1));

g6(2,1)=copy(g6(1));

g6(2,2)=copy(g6(1));

g6(2,3)=copy(g6(1));

 

 

g6(1,1).stat_bin('fill','face');

g6(1,1).set_title('''face''');

 

g6(1,2).stat_bin('fill','transparent');

g6(1,2).set_title('''transparent''');

 

g6(1,3).stat_bin('fill','all');

g6(1,3).set_title('''all''');

 

g6(2,1).stat_bin('fill','edge');

g6(2,1).set_title('''edge''');

 

g6(2,2).stat_bin('geom','stairs','fill','transparent');

g6(2,2).set_title('''transparent''');

 

 

g6(2,3).stat_bin('geom','line','fill','all');

g6(2,3).set_title('''all''');

 

g6.set_title('''fill'' options for stat_bin()');

 

figure('Position',[100 100 800 600]);

g6.draw();

• Default binning
• 'normalization','probability'
• 'normalization','cumcount'
• 'normalization','cdf'
• 'edges',-1:0.5:10
• 'normalization','countdensity' and custom edges

clear g7

g7(1,1)=gramm('x',x,'color',cat);

g7(1,2)=copy(g7(1));

g7(1,3)=copy(g7(1));

g7(2,1)=copy(g7(1));

g7(2,2)=copy(g7(1));

g7(2,3)=copy(g7(1));

 

g7(1,1).stat_bin('geom','overlaid_bar'); %Default binning (30 bins)

 

%Normalization to 'probability'

g7(2,1).stat_bin('normalization','probability','geom','overlaid_bar');

g7(2,1).set_title('''normalization'',''probability''','FontSize',10);

 

%Normalization to cumulative count

g7(1,2).stat_bin('normalization','cumcount','geom','stairs');

g7(1,2).set_title('''normalization'',''cumcount''','FontSize',10);

 

%Normalization to cumulative density

g7(2,2).stat_bin('normalization','cdf','geom','stairs');

g7(2,2).set_title('''normalization'',''cdf''','FontSize',10);

 

%Custom edges for the bins

g7(1,3).stat_bin('edges',-1:0.5:10,'geom','overlaid_bar');

g7(1,3).set_title('''edges'',-1:0.5:10','FontSize',10);

 

%Custom edges with non-constand width (normalization 'countdensity'

%recommended)

g7(2,3).stat_bin('geom','overlaid_bar','normalization','countdensity','edges',[-5 -4 -2 -1 -0.5 -0.25 0 0.25 0.5 1 2 4 5]);

g7(2,3).set_title({'''normalization'',''countdensity'',' '''edges'',' '[-5 -4 -2 -1 -0.5 -0.25 0 0.25 0.5 1 2 4 5]'},'FontSize',10);

 

g7.set_title('Other options for stat_bin()');

 

figure('Position',[100 100 800 600]);

g7.draw();

Options for continuous data with stat_smooth()

x=0:0.02:9.8;

y=sin(exp(x-5)/12);

y(x<2)=y(x<2)+randn(1,sum(x<2))/2;

y(x>=2)=y(x>=2)+randn(1,sum(x>=2))/8;

 

figure('Position',[100 100 800 500]);

clear g

g=gramm('x',x,'y',y);

g.geom_funline('fun',@(x)sin(exp(x-5)/12));

g.geom_vline('xintercept',2);

g.axe_property('XLim',[0 9.8]);

g(1,2)=copy(g(1));

g(1,3)=copy(g(1));

g(2,1)=copy(g(1));

g(2,2)=copy(g(1));

g(2,3)=copy(g(1));

g(1,1).geom_point();

g(1,1).set_title('Raw input');

 

g(1,2).stat_smooth();

g(1,2).set_title('stat_smooth() default');

 

g(1,3).stat_smooth('lambda','auto','npoints',500);

g(1,3).set_title('default with ''lambda'',''auto''');

 

g(2,1).stat_smooth('method','sgolay','lambda',[31 3]);

g(2,1).set_title('''method'',''sgolay''');

 

g(2,2).stat_smooth('method','moving','lambda',31);

g(2,2).set_title('''method'',''moving''');

 

 

g(2,3).stat_smooth('method','loess','lambda',0.1,'setylim',true);

g(2,3).set_title('''method'',''loess'',''setylim'',''true''');

 

g.set_title('Options for stat_smooth()');

g.draw();

Advanced use

Superimposing gramm plots with update(): Using different groups for different stat_ and geom_ methods

clear g10

figure('Position',[100 100 600 450]);

g10=gramm('x',cars.Horsepower,'y',cars.Acceleration,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g10.set_names('color','# Cylinders','x','Horsepower','y','Acceleration','Column','Origin');

g10.set_color_options('chroma',0,'lightness',30);

g10.stat_glm('geom','area','disp_fit',false);

g10.set_title('Update example'); %Title must be provided before the first draw() call

g10.draw();

snapnow;

g10.update('color',cars.Cylinders);

g10.facet_grid([],cars.Origin_Region);

g10.set_color_options();

g10.geom_point();

g10.draw();

Superimposing gramm plots with update(): Plotting all the data in the background of facets

%Inspired by https://drsimonj.svbtle.com/plotting-background-data-for-groups-with-ggplot2

 

load fisheriris.mat

 

clear g

figure('Position',[100 100 800 600]);

%Create an histogram of all the data in the background (no facet_ is given yet)

g(1,1)=gramm('x',meas(:,2));

g(1,1).set_names('x','Sepal Width','column','');

g(1,1).stat_bin('fill','all'); %histogram

g(1,1).set_color_options('chroma',0,'lightness',75); %We make it light grey

g(1,1).set_title('Overlaid histograms');

 

%Create a scatter plot of all the data in the background (no facet_ is given yet)

g(2,1)=gramm('x',meas(:,2),'y',meas(:,1));

g(2,1).set_names('x','Sepal Width','column','','y','Sepal Length');

g(2,1).geom_point(); %Scatter plot

g(2,1).set_color_options('chroma',0,'lightness',75); %We make it light grey

g(2,1).set_point_options('base_size',6);

g(2,1).set_title('Overlaid scatter plots');

 

g.draw(); %Draw the backgrounds

 

g(1,1).update('color',species); %Add color with update()

g(1,1).facet_grid([],species); %Provide facets

g(1,1).stat_bin('dodge',0); %Histogram (we set dodge to zero as facet_grid makes it useless)

g(1,1).set_color_options(); %Reset to default colors

g(1,1).no_legend();

g(1,1).axe_property('ylim',[-2 30]); %We have to set y scale manually, as the automatic scaling from the first plot was forgotten

 

g(2,1).update('color',species); %Add color with update()

g(2,1).facet_grid([],species); %Provide facets

g(2,1).geom_point();

g(2,1).set_color_options();

g(2,1).no_legend();

 

%Set global axe properties

g.axe_property('TickDir','out','XGrid','on','Ygrid','on','GridColor',[0.5 0.5 0.5]);

%Draw the news elements

g.draw();

%Export

g.export('file_name','overlaid_export','file_type','png');

Use custom layouts in gramm, marginal histogram example

load fisheriris.mat

 

clear g

figure('Position',[100 100 550 550]);

 

%Create x data histogram on top

g(1,1)=gramm('x',meas(:,2),'color',species);

g(1,1).set_layout_options('Position',[0 0.8 0.8 0.2],... %Set the position in the figure (as in standard 'Position' axe property)

'legend',false,... % No need to display legend for side histograms

'margin_height',[0.02 0.05],... %We set custom margins, values must be coordinated between the different elements so that alignment is maintained

'margin_width',[0.1 0.02],...

'redraw',false); %We deactivate automatic redrawing/resizing so that the axes stay aligned according to the margin options

g(1,1).set_names('x','');

g(1,1).stat_bin('geom','stacked_bar','fill','all','nbins',15); %histogram

g(1,1).axe_property('XTickLabel',''); % We deactivate tht ticks

 

%Create a scatter plot

g(2,1)=gramm('x',meas(:,2),'y',meas(:,1),'color',species);

g(2,1).set_names('x','Sepal Width','y','Sepal Length','color','Species');

g(2,1).geom_point(); %Scatter plot

g(2,1).set_point_options('base_size',6);

g(2,1).set_layout_options('Position',[0 0 0.8 0.8],...

'legend_pos',[0.83 0.75 0.2 0.2],... %We detach the legend from the plot and move it to the top right

'margin_height',[0.1 0.02],...

'margin_width',[0.1 0.02],...

'redraw',false);

g(2,1).axe_property('Ygrid','on');

 

%Create y data histogram on the right

g(3,1)=gramm('x',meas(:,1),'color',species);

g(3,1).set_layout_options('Position',[0.8 0 0.2 0.8],...

'legend',false,...

'margin_height',[0.1 0.02],...

'margin_width',[0.02 0.05],...

'redraw',false);

g(3,1).set_names('x','');

g(3,1).stat_bin('geom','stacked_bar','fill','all','nbins',15); %histogram

g(3,1).coord_flip();

g(3,1).axe_property('XTickLabel','');

 

%Set global axe properties

g.axe_property('TickDir','out','XGrid','on','GridColor',[0.5 0.5 0.5]);

g.set_title('Fisher Iris, custom layout');

g.set_color_options('map','d3_10');

g.draw();

%Export

g.export('file_name','layout_export','file_type','png');

Plot one variable against many others

%Inspired by: https://drsimonj.svbtle.com/plot-some-variables-against-many-others

 

 

%Use stack to transform the wide table to a long format

T=stack(cars,{'Displacement' 'Weight' 'Acceleration'});

 

%Use the variable resutling from the stacking as x

g=gramm('x',T.Displacement_Weight_Acceleration,'y',T.MPG,'color',T.Horsepower,'marker',T.Cylinders,'subset',T.Cylinders~=3 & T.Cylinders~=5 & T.Model_Year<75);

%Use the stacking indicator as facet variable

g.facet_wrap(T.Displacement_Weight_Acceleration_Indicator,'scale','independent');

g.set_point_options('base_size',7);

g.set_continuous_color('LCH_colormap',[20 80 ; 40 30 ; 260 260 ]);

g.set_names('y','MPG','x','Value','column','','color','HP','marker','# Cylinders');

g.geom_point();

 

g.axe_property('TickDir','out','XGrid','on','Ygrid','on','GridColor',[0.5 0.5 0.5]);

figure('Position',[100 100 700 350]);

g.draw();

Create a broken axis

x=[randn(1,50)*2 randn(1,50)*8+70];

y=-x;

g(1,1)=gramm('x',x,'y',y);

g(1,1).geom_point();

g(1,1).set_title('Without broken axis');

 

 

g(2,1)=gramm('x',x,'y',y);

g(2,1).facet_grid([],x>20,"scale","free_x","space","free_x","column_labels",false);

g(2,1).geom_point();

g(2,1).set_title('With broken axis');

figure('Position',[100 100 800 600]);

g.draw();

g(2,1).facet_axes_handles(2).YAxis.Visible='off';

g(2,1).facet_axes_handles(1).XLim=[-5 6];

g(2,1).facet_axes_handles(1).XTick=-5:5:5;

g(2,1).facet_axes_handles(2).XLim=[50 90];

g(2,1).facet_axes_handles(2).XTick=50:5:90;

Customizing gramm's output

Customizing color maps with set_color_options()

%Default: LCH-based colormap with hue variation

clear g

g(1,1)=gramm('x',cars.Origin,'y',cars.Horsepower,'color',cars.Origin);

g(1,1).geom_bar('EdgeColor','none');

g(1,2)=copy(g(1));

g(1,3)=gramm('x',cars.Origin,'y',cars.Horsepower,'lightness',cars.Origin);

g(2,1)=copy(g(1));

g(2,2)=copy(g(1));

g(2,3)=copy(g(1));

 

 

 

g(1,1).set_title('Default LCH (''color'' groups)','FontSize',12);

 

%Possibility to change the hue range as well as lightness and chroma of

%the LCH-based colormap

g(1,2).set_color_options('hue_range',[-60 60],'chroma',40,'lightness',90);

g(1,2).set_title('Modified LCH (''color'' groups)','FontSize',12);

 

%Possibility to change the lightness and chroma range of the LCH-based

%colormap when a 'lightness' variable is given

g(1,3).geom_bar('EdgeColor','none');

g(1,3).set_color_options('lightness_range',[0 95],'chroma_range',[0 0]);

g(1,3).set_title('Modified LCH (''lightness'' groups)','FontSize',12);

 

%Go back to Matlab's defauls colormap

g(2,1).set_color_options('map','matlab');

g(2,1).set_title('Matlab 2014B+ ','FontSize',12);

 

%Brewer colormap 1

g(2,2).set_color_options('map','brewer1');

g(2,2).set_title('Color Brewer 1','FontSize',12);

 

%Brewer colormap 2

g(2,3).set_color_options('map','brewer2');

g(2,3).set_title('Color Brewer 2','FontSize',12);

 

%Some methods can be called on all objects at the same time !

g.axe_property('YLim',[0 140]);

g.axe_property('XTickLabelRotation',60); %Should work for recent Matlab versions

g.set_names('x','Origin','y','Horsepower','color','Origin','lightness','Origin');

g.set_title('Colormap customizations examples');

 

figure('Position',[100 100 800 600])

g.draw();

Customizing color/lightness maps and legends with set_color_options()

clear g

 

g(1,1)=gramm('x',cars.Origin_Region,'y',cars.Horsepower,'color',cars.Origin_Region,'lightness',cars.Cylinders,...

'subset',cars.Cylinders==4 | cars.Cylinders==6);

%g(1,1).stat_summary('geom',{'bar'},'dodge',1.3,'width',1.2);

g(1,1).geom_bar('EdgeColor','none','dodge',1.3,'width',1.2);

g(1,2) = copy( g(1,1) );

g(1,3) = copy( g(1,1) );

g(2,1) = copy( g(1,1) );

g(2,2) = copy( g(1,1) );

 

% Default lightness/chroma is beter suited for more lightness categories

g(1,1).set_title('Default LCH, default legend','FontSize',12);

 

% It is possible to restrict the lightness/chroma changes across the

% lightness categories. Forcing the legend to 'separate' here makes the

% lightness legends use the first color instead of gray levels

g(1,2).set_color_options('lightness_range',[70 40],'chroma_range',[60 70],'legend','separate');

g(1,2).set_title('Modified LCH, lightness legend with color','FontSize',12);

 

% Pre-defined color/lightness maps can yeild better results than default

% parametric LCH colormaps

g(1,3).set_color_options('map','brewer_paired');

g(1,3).set_title('Brewer colormap','FontSize',12);

 

% Witht the 'expand' legend option, all ligthness/color combinations are

% presented in the legend

g(2,1).set_color_options('map','d3_20','legend','expand');

g(2,1).set_title('D3.js colormap, ''expand'' legend option','FontSize',12);

 

 

g(2,2)=gramm('x',cars.Origin,'y',cars.Horsepower,'color',cars.Origin,...

'marker',cars.Origin,'subset',cars.Cylinders==4 | cars.Cylinders==6);

g(2,2).stat_summary('geom',{'bar'},'dodge',0,'width',0.15);

g(2,2).stat_summary('geom',{'point'},'dodge',0,'width',1);

g(2,2).set_point_options('base_size',10);

g(2,3)=copy(g(2,2));

 

g(2,2).set_title('D3.js colormap','FontSize',12);

g(2,2).set_color_options('map','d3_10');

 

% With the 'merge' legend option, plots that use the same categories for

% color and marker/linestyle/size will be combined

g(2,3).set_color_options('map','d3_10','legend','merge');

g(2,3).set_title('D3.js colormap, ''merge'' legend option','FontSize',12);

 

g.axe_property('YLim',[0 160]);

g.axe_property('XTickLabelRotation',60); %Should work for recent Matlab versions

g.set_names('x','Origin','y','Horsepower','color','Origin','marker','Origin','lightness','# Cyl');

g.set_title('Color/Lightness maps and legend customizations examples');

 

figure('Position',[100 100 800 600]);

g.draw();

Less than 2 samples for CI computation...Skipping Less than 2 samples for CI computation...Skipping Less than 2 samples for CI computation...Skipping Less than 2 samples for CI computation...Skipping

%Export

g.export('file_name','colorlegend_export','file_type','png');

Using a continuous color scale

websave('example_spectra','https://github.com/piermorel/gramm/raw/master/sample_data/example_spectra.mat'); %Download data from repository

load example_spectra.mat

 

%Here we create x as a 1xN array (see example above), and use a MxN matrix

%for y. Color applies to the M rows of y.

g18=gramm('x',900:2:1700,'y',NIR,'color',octane);

g18.set_names('x','Wavelength (nm)','y','NIR','color','Octane');

g18.set_continuous_color('colormap','hot');

g18.geom_line;

figure('Position',[100 100 800 450]);

g18.draw();

Changing the order of elements with set_order_options()

y=[36 38 40 42 44 46];

x={'XS' 'S' 'M' 'L' 'XL' 'XXL'};

 

 

clear g

%By default, both x and lightness are ordered according to sorted (here

%alphabetically) input

g(1,2)=gramm('x',x,'y',y,'lightness',x);

g(1,2).geom_bar('EdgeColor','none');

g(1,2).set_title('Default output');

 

 

%By using set_order_options('x',0), x are presented in the raw input order. The

%color is still sorted

g(2,1)=gramm('x',x,'y',y,'lightness',x);

g(2,1).geom_bar('EdgeColor','none');

g(2,1).set_order_options('x',0);

g(2,1).set_title('x in input order');

 

%By using set_order_options('x',0,'lightness',{'XS' 'S' 'M' 'L' 'XL'

%'XXL'}), we also order lightness in the desired order, here by

%directly providing the desired order.

g(2,2)=gramm('x',x,'y',y,'lightness',x);

g(2,2).geom_bar('EdgeColor','none');

%g(2,2).set_order_options('x',0,'lightness',{'XS' 'S' 'M' 'L' 'XL' 'XXL'});

g(2,2).set_title({'x in input order' 'lightness in custom order'});

%Examples below do not fail but might truncate data

g(2,2).set_order_options('x',0,'lightness',{'XXL' 'XL' 'L' 'B' 'M' 'S' 'XS' }); %additional category is ignored

%g(2,2).set_order_options('x',0,'lightness',{'XXL' 'XL' 'L' 'M' 'XS'}) %Missing category is truncated

%Examples below fail due to type problems

%g(2,2).set_order_options('x',0,'lightness',{'XXL' 'XL' 'L' 'M' 'S' 1})

 

%It is also possible to set up a custom order (indices within the sorted

%input), here used to inverse lightness map. This way is a bit more

%practical for floating point numerical variables. For cells of string, the

%way above is easier.

g(2,3)=gramm('x',x,'y',y,'lightness',x);

g(2,3).geom_bar('EdgeColor','none');

g(2,3).set_order_options('x',0,'lightness',[6 4 1 2 3 5]);

g(2,3).set_title({'x in input order' 'lightness in custom order'});

%Example below properly fail

%g(2,3).set_order_options('x',0,'lightness',[6 4 1 2 3 3])

 

g.set_names('x','US size','y','EU size','lightness','US size');

g.axe_property('YLim',[0 48]);

 

figure('Position',[100 100 800 600]);

g.draw();

ordering given as values ordering given as indices

Customize the size and style of graphic elements with set_line_options() and set_point_options()

clear g

x=repmat(1:10,1,5);

y=reshape(bsxfun(@times,1:5,(1:10)'),1,50);

sz=reshape(repmat(1:5,10,1),1,50);

 

g(1,1)=gramm('x',x,'y',y,'size',sz);

g(1,1).geom_point();

g(1,1).geom_line();

g(1,1).set_title('Default');

 

g(1,2)=gramm('x',x,'y',y,'color',sz,'size',sz);

g(1,2).geom_point();

g(1,2).set_point_options('border_color','k','border_width',2);

g(1,2).set_color_options('legend','merge');

g(1,2).set_title('Black point border color');

 

g(1,3)=gramm('x',x,'y',y,'color',sz,'size',sz);

g(1,3).geom_point('alpha',0);

g(1,3).set_color_options('legend','merge');

g(1,3).set_point_options('border_color','auto','border_width',1.5);

g(1,3).set_title('Auto point border color and 0 point alpha');

 

g(2,1)=gramm('x',x,'y',y,'size',sz);

g(2,1).geom_point();

g(2,1).geom_line();

g(2,1).set_line_options('base_size',1,'step_size',0.2,'style',{':' '-' '--' '-.'});

g(2,1).set_point_options('base_size',4,'step_size',1);

g(2,1).set_title('Modified point/line base & step size + line style');

 

g(2,2)=gramm('x',x,'y',y,'size',sz,'subset',sz~=3 & sz~=4);

g(2,2).geom_line();

g(2,2).geom_point();

g(2,2).set_title('Default (size according to category)');

 

g(2,3)=gramm('x',x,'y',y,'size',sz,'subset',sz~=3 & sz~=4);

g(2,3).geom_line();

g(2,3).geom_point();

g(2,3).set_line_options('use_input',true,'input_fun',@(s)1.5+s);

g(2,3).set_point_options('use_input',true,'input_fun',@(s)5+s*2);

g(2,3).set_title('Size according to value');

 

g.set_title('Customization of line and point options');

 

figure('Position',[100 100 1000 600]);

g.draw();

Decorate plot backgrounds with geom_polygon()

clear g

g=gramm('x',cars.Model_Year,'y',cars.MPG,'color',cars.Cylinders,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g.facet_grid([],cars.Origin_Region);

g.geom_point();

g.stat_glm('geom','line');

g.set_names('column','','x','Year of production','y','Fuel economy (MPG)','color','# Cylinders');

 

g(1,2)=copy(g(1));

g(2,1)=copy(g(1));

g(2,2)=copy(g(1));

 

% Color mapping for the polygons

cmap = [1 0.5 0.5; % red (bad gas mileage)

1 1 0.5; % yellow (reasonable gas mileage)

0.5 1 0.5]; % green (good gas mileage)

 

% Standard geom_polygon call, 'x' and 'y' are used to provide polygons vertex coordinates, Possibility to manually set fill, color, style and alpha.

g(1,1).geom_polygon('x',{[50 90 90 50] ; [50 90 90 50] ; [50 90 90 50]},'y',{[5 5 20 20]; [20 20 30 30]; [30 30 50 50]},'color',cmap,'alpha',0.3);

 

% Simplified geom_polygon call, 'x' was omitted and only pairs of 'y' values are provided,

% specifying lower and upper limits of horizontal areas.

g(1,2).geom_polygon('y',{[5 20]; [20 30]; [30 50]},'color',cmap);

 

%Possibility to set color and fill by indices (using a column vector of

%integers. Colormap generated between 1 and max(vector))

g(2,1).geom_polygon('y',{[5 20]; [20 30]; [30 50]},'color',[1 ; 3; 2]);

 

% Single fill, alpha, color and styles are automatically extended to all polygons in the call

g(2,2).geom_polygon('y',{[5 20]; [30 50]},'color',[1 0 0],'line_style',{'--'},'line_color',[0 0 0.5]);

% Possibility to do multiple calls

g(2,2).geom_polygon('x',{[72 80 76]},'y',{[22 22 28]}); %Default is grey

 

g.set_title('Decorate plot backgrounds with geom_polygon()');

 

figure('Position',[100 100 800 600]);

g.draw();

Advanced customization of gramm figures

• Text sizes and fonts are changed with set_text_options()
• Y grid is turned on on all facets with axe_property('YGrid','on')
• A vertical line and text is added to only one of the facets by using the facet_axes_handles public property of gramm objects
• All points are made smaller by using their handles results.grom_point_handle in the set() function
• Similarly, all confidence areas are made grey g.results.stat_glm.area_handle
• A subset of the glm lines are made thicker by calling set() on a subset teir handles |g.results.stat_glm(g.results.color==4).line_handle]

f=figure('Position',[100 100 800 500]);

%Create fake button

c=uicontrol('Style','pushbutton','String','Dummy','Units','normalized','Position',[0.8 0.45 0.15 0.1]);

%Create uipanel to put our gramm plots

p=uipanel('Position',[0.05 0.1 0.7 0.8],'Parent',f,'BackgroundColor',[1 1 1]);

 

% Starting with the example figure

load example_data;

g=gramm('x',cars.Model_Year,'y',cars.MPG,'color',cars.Cylinders,'subset',cars.Cylinders~=3 & cars.Cylinders~=5);

g.facet_grid([],cars.Origin_Region);

g.stat_glm();

g.geom_point();

g.set_names('column','Origin','x','Year of production','y','Fuel economy (MPG)','color','# Cylinders');

g.set_title('Fuel economy of new cars between 1970 and 1982');

g.axe_property('YGrid','on');

g.set_parent(p);

 

g.set_text_options('font','Courier',...

'base_size',12,...

'label_scaling',0.8,...

'legend_scaling',1.5,...

'legend_title_scaling',1.5,...

'facet_scaling',1,...

'title_scaling',1.5);

 

g.draw();

 

%It's possible to use the axes handles to add elements to single axes

line([75 75],[0 50],'Color','k','LineStyle','--','Parent',g.facet_axes_handles(1));

text(75.3,47,{'Important' 'event'},'Parent',g.facet_axes_handles(1),'FontName','Courier');

 

%It's also possible to change properties of graphical elements

%Either all at once

set([g.results.geom_point_handle],'SizeData',25);

set([g.results.stat_glm.area_handle],'FaceColor',[0.4 0.4 0.4]);

%Or on a subset of them (here only for the lines of glms of 4-cylinder cars)

set([g.results.stat_glm(g.results.color==4).line_handle],'LineWidth',3);

Gramm input formats for x and y (1D arrays, cells of arrays, 2D arrays)

Y=[1 2 3 4 5 2 3 4 5 6 3 4 5 6 7];

X=[1 2 3 4 5 0 1 2 3 4 -1 0 1 2 3];

C=[1 1 1 1 1 2 2 2 2 2 2 2 2 2 2];

figure

g11=gramm('x',X,'y',Y,'color',C);

g11.geom_line();

g11.draw();

G=[1 1 1 1 1 2 2 2 2 2 3 3 3 3 3];

figure

g12=gramm('x',X,'y',Y,'color',C,'group',G);

g12.geom_line();

g12.draw();

Y=[1 2 3 4 5;2 3 4 5 6; 3 4 5 6 7];

X=[1 2 3 4 5; 0 1 2 3 4; -1 0 1 2 3];

C=[1 2 2];

figure

g13=gramm('x',X,'y',Y,'color',C);

g13.geom_line();

g13.draw();

X=[1 2 3 4 5];

figure

g14=gramm('x',X,'y',Y,'color',C);

g14.geom_line();

g14.draw();

Y={[1 2 3 4 5] [2 3 4 5 6] [3 4 5 6 7]};

X={[1 2 3 4 5] [0 1 2 3 4] [-1 0 1 2 3]};

figure

g15=gramm('x',X,'y',Y,'color',C);

g15.geom_line();

g15.draw();

 

Y={[1 2 3 4 5] [2 3 4 5 6] [3 4 5 6 7]};

X=[1 2 3 4 5];

figure

g16=gramm('x',X,'y',Y,'color',C);

g16.geom_line();

g16.draw();

Y={[1 2 3 4 5] [3 4 5] [3 4 5 6 7]};

X={[1 2 3 4 5] [1 2 3] [-1 0 1 2 3]};

figure

g17=gramm('x',X,'y',Y,'color',C);

g17.geom_line();

g17.draw();

Raw matlab code equivalent to the demo figure

figure('Position',[100 100 800 400],'Color',[1 1 1]);

 

% Define groups

cyl = [4 6 8]; % Manually

orig = unique(cars.Origin_Region); % Based on data

 

% Loop over groups

for oi = 1:length(orig) % External loop on the axes

 

% Axes creation

ax = subplot(1,length(orig),oi);

hold on

 

for ci = 1:length(cyl) %Internal loop on the colors

 

% Data selection

sel = strcmp(cars.Origin_Region,orig{oi}) & ...

cars.Cylinders==cyl(ci) & ...

~isnan(cars.Model_Year) & ~isnan(cars.MPG);

 

% Plotting of raw data

plot(cars.Model_Year(sel),cars.MPG(sel),'.', ...

'MarkerSize',15);

 

% Keep the same color for the statistics

ax.ColorOrderIndex = ax.ColorOrderIndex - 1;

 

% Statistics (linear fit and plotting)

b = [ones(sum(sel),1) cars.Model_Year(sel)] \ ...

cars.MPG(sel);

x_fit = [min(cars.Model_Year(sel)) ...

max(cars.Model_Year(sel))];

plot(x_fit, x_fit * b(2) + b(1),'LineWidth',1.5);

end

 

% Axes legends

title(['Origin: ' orig{oi}]);

xlabel('Year');

ylabel('Fuel Economy (MPG)');

end

% Ugly color legend

l = legend('4','','6','','8','','Location','southeast');

title(l,'#Cyl');