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</style></head><body><div class="content"><h1>gramm examples and how-tos</h1><!--introduction--><!--/introduction--><h2>Contents</h2><div><ul><li><a href="#1">Example from the readme</a></li><li><a href="#9">Grouping options in gramm</a></li><li><a href="#10">Methods for visualizing Y~X relationships with X as categorical variable</a></li><li><a href="#11">Methods for visualizing X densities</a></li><li><a href="#12">Methods for visualizing Y~X relationship with both X and Y as continuous variables</a></li><li><a href="#13">Methods for visualizing custom confidence intervals</a></li><li><a href="#14">Methods for visualizing 2D densities</a></li><li><a href="#15">Methods for visualizing repeated trajectories</a></li><li><a href="#16">Methods for visualizing repeated densities (e.g. spike densities)</a></li><li><a href="#17">Options for separating groups across subplots with facet_grid()</a></li><li><a href="#18">Options for creating histograms with stat_bin()</a></li><li><a href="#21">Visualize x-y difference with inset histogram using stat_cornerhist()</a></li><li><a href="#22">Graphic and normalization options in stat_violin()</a></li><li><a href="#23">Options for dodging and spacing graphic elements in <tt>stat_summary()</tt> and <tt>stat_boxplot()</tt></a></li><li><a href="#25">Plotting text or labeling with geom_label()</a></li><li><a href="#26">Smooth continuous data with stat_smooth()</a></li><li><a href="#27">Superimposing gramm plots with update(): Using different groups for different stat_ and geom_ methods</a></li><li><a href="#29">Superimposing gramm plots with update(): Plotting all the data in the background of facets</a></li><li><a href="#30">Use custom layouts in gramm, marginal histogram example</a></li><li><a href="#31">Plot one variable against many others</a></li><li><a href="#32">Customizing color maps with set_color_options()</a></li><li><a href="#33">Customizing color/lightness maps and legends with set_color_options()</a></li><li><a href="#34">Using a continuous color scale</a></li><li><a href="#35">Changing the order of elements with set_order_options()</a></li><li><a href="#36">Customize the size and style of graphic elements with set_line_options() and set_point_options()</a></li><li><a href="#37">Decorate plot backgrounds with geom_polygon()</a></li><li><a href="#38">Advanced customization of gramm figures</a></li><li><a href="#39">Using different input formats for x and y (1D arrays, cells of arrays, 2D arrays)</a></li><li><a href="#45">Raw matlab code equivalent to the first figure (in paper.md)</a></li></ul></div><h2>Example from the readme<a name="1"></a></h2><p>Here we plot the evolution of fuel economy of new cars bewteen 1970 and 1980 (carbig dataset). Gramm is used to easily separate groups on the basis of the number of cylinders of the cars (color), and on the basis of the region of origin of the cars (subplot columns). Both the raw data (points) and a glm fit with 95% confidence interval (line+shaded area) are plotted.</p><p>We stat by loading the sample data (structure created from the carbig dataset)</p><pre class="codeinput">load <span class="string">example_data</span>;
</pre><p>Create a gramm object, provide x (year of production) and y (fuel economy) data, color grouping data (number of cylinders) and select a subset of the data</p><pre class="codeinput">g=gramm(<span class="string">'x'</span>,cars.Model_Year,<span class="string">'y'</span>,cars.MPG,<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
</pre><p>Subdivide the data in subplots horizontally by region of origin using facet_grid()</p><pre class="codeinput">g.facet_grid([],cars.Origin_Region);
</pre><p>Plot raw data as points</p><pre class="codeinput">g.geom_point();
</pre><p>Plot linear fits of the data with associated confidence intervals</p><pre class="codeinput">g.stat_glm();
</pre><p>Set appropriate names for legends</p><pre class="codeinput">g.set_names(<span class="string">'column'</span>,<span class="string">'Origin'</span>,<span class="string">'x'</span>,<span class="string">'Year of production'</span>,<span class="string">'y'</span>,<span class="string">'Fuel economy (MPG)'</span>,<span class="string">'color'</span>,<span class="string">'# Cylinders'</span>);
</pre><p>Set figure title</p><pre class="codeinput">g.set_title(<span class="string">'Fuel economy of new cars between 1970 and 1982'</span>);
</pre><p>Do the actual drawing</p><pre class="codeinput">figure(<span class="string">'Position'</span>,[100 100 800 400]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_01.png" alt=""> <h2>Grouping options in gramm<a name="9"></a></h2><p>With gramm there are a lot ways to map groups to visual properties of plotted data, or even subplots. Providing grouping variables to change visual properties is done in the constructor call <tt>gramm()</tt>. Grouping variables that determine subplotting are provided by calls to the <tt>facet_grid()</tt> or <tt>facet_wrap()</tt> methods. Note that <b>all the mappings presented below can be combined</b>, i.e. it's possible to previde different variables to each of the options.</p><p>In order to plot multiple, diferent gramm objects in the same figure, an array of gramm objects is created, and the <tt>draw()</tt> function called at the end on the whole array</p><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(1,1).geom_point();
g(1,1).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>);
g(1,1).set_title(<span class="string">'No groups'</span>);
g(1,2)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5,<span class="string">'color'</span>,cars.Cylinders);
g(1,2).geom_point();
g(1,2).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'color'</span>,<span class="string">'# Cyl'</span>);
g(1,2).set_title(<span class="string">'color'</span>);
g(1,3)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5,<span class="string">'lightness'</span>,cars.Cylinders);
g(1,3).geom_point();
g(1,3).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'lightness'</span>,<span class="string">'# Cyl'</span>);
g(1,3).set_title(<span class="string">'lightness'</span>);
g(2,1)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5,<span class="string">'size'</span>,cars.Cylinders);
g(2,1).geom_point();
g(2,1).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'size'</span>,<span class="string">'# Cyl'</span>);
g(2,1).set_title(<span class="string">'size'</span>);
g(2,2)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5,<span class="string">'marker'</span>,cars.Cylinders);
g(2,2).geom_point();
g(2,2).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'marker'</span>,<span class="string">'# Cyl'</span>);
g(2,2).set_title(<span class="string">'marker'</span>);
g(2,3)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5,<span class="string">'linestyle'</span>,cars.Cylinders);
g(2,3).geom_line();
g(2,3).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'linestyle'</span>,<span class="string">'# Cyl'</span>);
g(2,3).set_title(<span class="string">'linestyle'</span>);
g(3,1)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(3,1).facet_grid(cars.Cylinders,[]);
g(3,1).geom_point();
g(3,1).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'row'</span>,<span class="string">'# Cyl'</span>);
g(3,1).set_title(<span class="string">'subplot rows'</span>);
g(3,2)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.MPG,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(3,2).facet_grid([],cars.Cylinders);
g(3,2).geom_point();
g(3,2).set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'column'</span>,<span class="string">'# Cyl'</span>);
g(3,2).set_title(<span class="string">'subplot columns'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 800]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_02.png" alt=""> <h2>Methods for visualizing Y~X relationships with X as categorical variable<a name="10"></a></h2><p>The following methods can be used when Y data is continuous and X data discrete/categorical.</p><p>Here we also use an array of gramm objects in order to have multiple gramm plots on the same figure. The gramm objects use the same data, so we copy them after construction using the <tt>copy()</tt> method. We also duplicate the whole array of gramm objects before drawing in order to demonstrate the use of coord_flip() to exchange X and Y axes</p><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Origin_Region,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(1,2)=copy(g(1));
g(1,3)=copy(g(1));
g(2,1)=copy(g(1));
g(2,2)=copy(g(1));
<span class="comment">%Raw data as scatter plot</span>
g(1,1).geom_point();
g(1,1).set_title(<span class="string">'geom_point()'</span>);
<span class="comment">%Jittered scatter plot</span>
g(1,2).geom_jitter(<span class="string">'width'</span>,0.4,<span class="string">'height'</span>,0);
g(1,2).set_title(<span class="string">'geom_jitter()'</span>);
<span class="comment">%Averages with confidence interval</span>
g(1,3).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span>,<span class="string">'black_errorbar'</span>});
g(1,3).set_title(<span class="string">'stat_summary()'</span>);
<span class="comment">%Boxplots</span>
g(2,1).stat_boxplot();
g(2,1).set_title(<span class="string">'stat_boxplot()'</span>);
<span class="comment">%Violin plots</span>
g(2,2).stat_violin(<span class="string">'fill'</span>,<span class="string">'transparent'</span>);
g(2,2).set_title(<span class="string">'stat_violin()'</span>);
<span class="comment">%These functions can be called on arrays of gramm objects</span>
g.set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'# Cyl'</span>);
g.set_title(<span class="string">'Visualization of Y~X relationships with X as categorical variable'</span>);
gf = copy(g);
figure(<span class="string">'Position'</span>,[100 100 800 550]);
g.draw();
gf.set_title(<span class="string">'Visualization of Y~X relationships with X as categorical variable and flipped coordinates'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 550]);
gf.coord_flip();
gf.draw();
</pre><img vspace="5" hspace="5" src="examples_03.png" alt=""> <img vspace="5" hspace="5" src="examples_04.png" alt=""> <h2>Methods for visualizing X densities<a name="11"></a></h2><p>The following methods can be used in order to represent the density of a continuous variable. Note that here we represent the same data as in the previous figure, this time with Horsepower as X (over which the densities are represented), and separating the region of origin with subplots.</p><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(1,2)=copy(g(1));
g(2,1)=copy(g(1));
g(2,2)=copy(g(1));
<span class="comment">%Raw data as raster plot</span>
g(1,1).facet_grid(cars.Origin_Region,[]);
g(1,1).geom_raster();
g(1,1).set_title(<span class="string">'geom_raster()'</span>);
<span class="comment">%Histogram</span>
g(1,2).facet_grid(cars.Origin_Region,[]);
g(1,2).stat_bin(<span class="string">'nbins'</span>,8);
g(1,2).set_title(<span class="string">'stat_bin()'</span>);
<span class="comment">%Kernel smoothing density estimate</span>
g(2,1).facet_grid(cars.Origin_Region,[]);
g(2,1).stat_density();
g(2,1).set_title(<span class="string">'stat_density()'</span>);
<span class="comment">% Q-Q plot for normality</span>
g(2,2).facet_grid(cars.Origin_Region,[]);
g(2,2).stat_qq();
g(2,2).axe_property(<span class="string">'XLim'</span>,[-5 5]);
g(2,2).set_title(<span class="string">'stat_qq()'</span>);
g.set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'# Cyl'</span>,<span class="string">'row'</span>,<span class="string">''</span>,<span class="string">'y'</span>,<span class="string">''</span>);
g.set_title(<span class="string">'Visualization of X densities'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 550]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_05.png" alt=""> <h2>Methods for visualizing Y~X relationship with both X and Y as continuous variables<a name="12"></a></h2><p>The following methods can be used when both X and Y data are continuous</p><pre class="codeinput">clear <span class="string">g</span>
<span class="comment">%Raw data as scatter plot</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.Acceleration,<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
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(1,1).geom_point();
g(1,1).set_title(<span class="string">'geom_point()'</span>);
<span class="comment">%Generalized linear model fit</span>
g(1,2).stat_glm();
g(1,2).set_title(<span class="string">'stat_glm()'</span>);
<span class="comment">%Custom fit with provided function</span>
g(1,3).stat_fit(<span class="string">'fun'</span>,@(a,b,c,x)a./(x+b)+c,<span class="string">'intopt'</span>,<span class="string">'functional'</span>);
g(1,3).set_title(<span class="string">'stat_fit(''fun'',@(a,b,c,x)a./(x+b)+c)'</span>);
<span class="comment">%Spline smoothing</span>
g(2,1).stat_smooth();
g(2,1).set_title(<span class="string">'stat_smooth()'</span>);
<span class="comment">%Moving average</span>
g(2,2).stat_summary(<span class="string">'bin_in'</span>,10);
g(2,2).set_title(<span class="string">'stat_summary(''bin_in'',10)'</span>);
g.set_names(<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'Acceleration'</span>,<span class="string">'color'</span>,<span class="string">'# Cylinders'</span>);
<span class="comment">%Corner histogram</span>
g(2,3)=gramm(<span class="string">'x'</span>,(cars.Horsepower-nanmean(cars.Horsepower))/nanstd(cars.Horsepower),<span class="string">'y'</span>,-(cars.Acceleration-nanmean(cars.Acceleration))/nanstd(cars.Acceleration),<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(2,3).geom_point();
g(2,3).stat_cornerhist(<span class="string">'edges'</span>,-4:0.2:4,<span class="string">'aspect'</span>,0.6);
g(2,3).geom_abline();
g(2,3).set_title(<span class="string">'stat_cornerhist()'</span>);
g(2,3).set_names(<span class="string">'x'</span>,<span class="string">'z(Horsepower)'</span>,<span class="string">'y'</span>,<span class="string">'-z(Acceleration)'</span>);
g.set_title(<span class="string">'Visualization of Y~X relationship with both X and Y as continuous variables'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 550]);
g.draw();
</pre><pre class="codeoutput">Warning: Start point not provided, choosing random start point.
Warning: Start point not provided, choosing random start point.
Warning: Start point not provided, choosing random start point.
Less than 2 samples for CI computation...Skipping
Less than 2 samples for CI computation...Skipping
</pre><img vspace="5" hspace="5" src="examples_06.png" alt=""> <h2>Methods for visualizing custom confidence intervals<a name="13"></a></h2><p>With <tt>geom_interval()</tt> it is possible to plot custom confidence intervals by provinding <tt>'ymin'</tt> and <tt>'ymax'</tt> values to <tt>gramm()</tt>. All options to display confidence intervals in <tt>stat_summary()</tt> are available, including dodging. <tt>'ymin'</tt> and <tt>'ymax'</tt> are absolute, and not given relative to <tt>'y'</tt></p><pre class="codeinput">cars_table=struct2table(cars);
cars_summary=rowfun(@(hp)deal(nanmean(hp),bootci(200,@(x)nanmean(x),hp)'),cars_table(cars.Cylinders~=3 & cars.Cylinders~=5,:),<span class="keyword">...</span>
<span class="string">'InputVariables'</span>,{<span class="string">'Horsepower'</span>},<span class="keyword">...</span>
<span class="string">'GroupingVariables'</span>,{<span class="string">'Origin_Region'</span> <span class="string">'Cylinders'</span>},<span class="keyword">...</span>
<span class="string">'OutputVariableNames'</span>,{<span class="string">'hp_mean'</span> <span class="string">'hp_ci'</span>});
clear <span class="string">g</span>
<span class="comment">%Bars and error bars</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars_summary.Origin_Region,<span class="string">'y'</span>,cars_summary.hp_mean,<span class="keyword">...</span>
<span class="string">'ymin'</span>,cars_summary.hp_ci(:,1),<span class="string">'ymax'</span>,cars_summary.hp_ci(:,2),<span class="string">'color'</span>,cars_summary.Cylinders);
g(1,1).set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'# Cylinders'</span>);
g(1,1).geom_bar(<span class="string">'dodge'</span>,0.8,<span class="string">'width'</span>,0.6);
g(1,1).geom_interval(<span class="string">'geom'</span>,<span class="string">'black_errorbar'</span>,<span class="string">'dodge'</span>,0.8,<span class="string">'width'</span>,1);
<span class="comment">%points and error bars</span>
g(1,2)=gramm(<span class="string">'x'</span>,categorical(cars_summary.Cylinders),<span class="string">'y'</span>,cars_summary.hp_mean,<span class="keyword">...</span>
<span class="string">'ymin'</span>,cars_summary.hp_ci(:,1),<span class="string">'ymax'</span>,cars_summary.hp_ci(:,2),<span class="string">'color'</span>,cars_summary.Origin_Region);
g(1,2).set_names(<span class="string">'color'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'x'</span>,<span class="string">'# Cylinders'</span>);
g(1,3)=copy(g(1,2));
g(1,2).set_color_options(<span class="string">'map'</span>,<span class="string">'matlab'</span>);
g(1,2).geom_point(<span class="string">'dodge'</span>,0.2);
g(1,2).geom_interval(<span class="string">'geom'</span>,<span class="string">'errorbar'</span>,<span class="string">'dodge'</span>,0.2,<span class="string">'width'</span>,0.8);
<span class="comment">%Shaded area</span>
g(1,3).geom_interval(<span class="string">'geom'</span>,<span class="string">'area'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 450]);
g.axe_property(<span class="string">'YLim'</span>,[-10 190]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_07.png" alt=""> <h2>Methods for visualizing 2D densities<a name="14"></a></h2><p>The following methods can be used to visualize 2D densities for bivariate data</p><pre class="codeinput"><span class="comment">%Create point cloud with two categories</span>
N=10^4;
x=randn(1,N);
y=x+randn(1,N);
test=repmat([0 1 0 0],1,N/4);
y(test==0)=y(test==0)+3;
clear <span class="string">g</span>
<span class="comment">% Display points and 95% percentile confidence ellipse</span>
g(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,test);
g(1,1).set_names(<span class="string">'color'</span>,<span class="string">'grp'</span>);
g(1,1).geom_point();
<span class="comment">%'patch_opts' can be used to provide more options to the patch() internal</span>
<span class="comment">%call</span>
g(1,1).set_point_options(<span class="string">'base_size'</span>,2);
g(1,1).stat_ellipse(<span class="string">'type'</span>,<span class="string">'95percentile'</span>,<span class="string">'geom'</span>,<span class="string">'area'</span>,<span class="string">'patch_opts'</span>,{<span class="string">'FaceAlpha'</span>,0.1,<span class="string">'LineWidth'</span>,2});
g(1,1).set_title(<span class="string">'stat_ellispe()'</span>);
<span class="comment">%Plot point density as contour plot</span>
g(1,2)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,test);
g(1,2).stat_bin2d(<span class="string">'nbins'</span>,[10 10],<span class="string">'geom'</span>,<span class="string">'contour'</span>);
g(1,2).set_names(<span class="string">'color'</span>,<span class="string">'grp'</span>);
g(1,2).set_title(<span class="string">'stat_bin2d(''geom'',''contour'')'</span>);
<span class="comment">% %Plot density as point size (looks good only when axes have the same</span>
<span class="comment">% %scale, hence the 'DataAspectRatio' option, equivalent to axis equal)</span>
<span class="comment">% g(2,1)=gramm('x',x,'y',y,'color',test);</span>
<span class="comment">% g(2,1).stat_bin2d('nbins',{-10:0.4:10 ; -10:0.4:10},'geom','point');</span>
<span class="comment">% g(2,1).axe_property('DataAspectRatio',[1 1 1]);</span>
<span class="comment">% g(2,1).set_names('color','grp');</span>
<span class="comment">% g(2,1).set_title('stat_bin2d(''geom'',''point'')');</span>
<span class="comment">%Plot density as heatmaps (Heatmaps don't work with multiple colors, so we separate</span>
<span class="comment">%the categories with facets). With the heatmap we see better the</span>
<span class="comment">%distribution in high-density areas</span>
g(2,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y);
g(2,1).facet_grid([],test);
g(2,1).stat_bin2d(<span class="string">'nbins'</span>,[20 20],<span class="string">'geom'</span>,<span class="string">'image'</span>);
<span class="comment">%g(2,1).set_continuous_color('LCH_colormap',[0 100 ; 100 20 ;30 20]); %Let's try a custom LCH colormap !</span>
g(2,1).set_names(<span class="string">'column'</span>,<span class="string">'grp'</span>,<span class="string">'color'</span>,<span class="string">'count'</span>);
g(2,1).set_title(<span class="string">'stat_bin2d(''geom'',''image'')'</span>);
g(2,2)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,test);
g(2,2).geom_point(<span class="string">'alpha'</span>,0.05);
g(2,2).set_point_options(<span class="string">'base_size'</span>,6);
g(2,2).set_title(<span class="string">'geom_point(''alpha'',0.05)'</span>);
g.set_title(<span class="string">'Visualization of 2D densities'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600])
g.draw();
</pre><img vspace="5" hspace="5" src="examples_08.png" alt=""> <h2>Methods for visualizing repeated trajectories<a name="15"></a></h2><p>gramm supports 2D inputs for X and Y data (as 2D array or cell of arrays), which is particularly useful for representing repeated trajectories. Here for example we generate 50 trajectories, each of length 40. The grouping data is then given per trajectory and not per data point. Here the color grouping variable is thus given as a 1x50 cellstr.</p><pre class="codeinput"><span class="comment">%We generate 50 trajectories of length 40, with 3 groups</span>
N=50;
nx=40;
cval={<span class="string">'A'</span> <span class="string">'B'</span> <span class="string">'C'</span>};
cind=randi(3,N,1);
c=cval(cind);
x=linspace(0,3,nx);
y=arrayfun(@(c)sin(x*c)+randn(1,nx)/10+x*randn/5,cind,<span class="string">'UniformOutput'</span>,false);
clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,c);
g(1,2)=copy(g(1));
g(2,1)=copy(g(1));
g(2,2)=copy(g(1));
g(1,1).geom_point();
g(1,1).set_title(<span class="string">'geom_point()'</span>);
g(1,2).geom_line();
g(1,2).set_title(<span class="string">'geom_line()'</span>);
g(2,1).stat_smooth();
g(2,1).set_point_options(<span class="string">'base_size'</span>,3);
g(2,1).set_title(<span class="string">'stat_smooth()'</span>);
g(2,2).stat_summary();
g(2,2).set_title(<span class="string">'stat_summary()'</span>);
g.set_title(<span class="string">'Visualization of repeated trajectories '</span>);
figure(<span class="string">'Position'</span>,[100 100 800 550]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_09.png" alt=""> <h2>Methods for visualizing repeated densities (e.g. spike densities)<a name="16"></a></h2><p>With the support of 2D inputs for X and gramm's functionality for representing the density of data, useful neuroscientific plots can be generated when the provided X corresponds to spike trains: raster plots and peristimulus time histograms (PSTHs).</p><pre class="codeinput"><span class="comment">%We generate 50 spike trains, with 3 groups</span>
N=50;
cval={<span class="string">'A'</span> <span class="string">'B'</span> <span class="string">'C'</span>};
cind=randi(3,N,1);
c=cval(cind);
train_template=[zeros(1,300) ones(1,200)];
<span class="comment">%Pseudo-poisson spike trains</span>
spike_train=cell(N,1);
<span class="keyword">for</span> 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);
<span class="keyword">end</span>
clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,spike_train,<span class="string">'color'</span>,c);
g(1,1).geom_raster();
g(1,1).set_title(<span class="string">'geom_raster()'</span>);
g(1,2)=gramm(<span class="string">'x'</span>,spike_train,<span class="string">'color'</span>,c);
g(1,2).stat_bin(<span class="string">'nbins'</span>,25,<span class="string">'geom'</span>,<span class="string">'line'</span>);
g(1,2).set_title(<span class="string">'stat_bin()'</span>);
g.set_names(<span class="string">'x'</span>,<span class="string">'Time'</span>,<span class="string">'y'</span>,<span class="string">''</span>);
g.set_title(<span class="string">'Visualization of spike densities'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 350]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_10.png" alt=""> <h2>Options for separating groups across subplots with facet_grid()<a name="17"></a></h2><p>To separate groups in different rows and columns of sublots, the grouping variable just need to be passed to the <tt>facet_grid(goup_rows,group_columns)</tt> function or <tt>facet_wrap(group_columns)</tt>. Both have multiple options concerning the scaling of data between subplots.</p><div><ul><li>By default <tt>'scale','fixed'</tt> all subplots have the same limits</li><li><tt>'scale','free_x'</tt>: subplots on the same columns have the same x limits</li><li><tt>'scale','free_y'</tt>: subplots on the same rows have the same y limits</li><li><tt>'scale','free'</tt>: subplots on the same rows have the same y limits, subplots on the same columns have the same x limits</li><li><tt>'scale','independent'</tt>: subplots have independent limits</li></ul></div><p>In <tt>facet_grid()</tt>; the <tt>'space'</tt> option allows to set how the subplot axes themselves scale with the data. It should be used in conjunction with the corresponding <tt>'scale'</tt> option.</p><pre class="codeinput"><span class="comment">% Generating fake data</span>
N=1000;
colval={<span class="string">'A'</span> <span class="string">'B'</span> <span class="string">'C'</span>};
rowval={<span class="string">'I'</span> <span class="string">'II'</span>};
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 <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,c,<span class="string">'lightness'</span>,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(<span class="string">'No facets'</span>);
g(1,2).facet_grid(r,c);
g(1,2).geom_point();
g(1,2).no_legend();
g(1,2).set_title(<span class="string">'facet_grid()'</span>);
g(2,1).facet_grid(r,c,<span class="string">'scale'</span>,<span class="string">'free'</span>);
g(2,1).geom_point();
g(2,1).no_legend();
g(2,1).set_title(<span class="string">'facet_grid(''scale'',''free'')'</span>);
g(2,2).facet_grid(r,c,<span class="string">'scale'</span>,<span class="string">'free'</span>,<span class="string">'space'</span>,<span class="string">'free'</span>);
g(2,2).geom_point();
g(2,2).no_legend();
g(2,2).set_title(<span class="string">'facet_grid(''scale'',''free'',''space'',''free'')'</span>);
g(3,1).facet_grid(r,c,<span class="string">'scale'</span>,<span class="string">'free_x'</span>);
g(3,1).geom_point();
g(3,1).no_legend();
g(3,1).set_title(<span class="string">'facet_grid(''scale'',''free_x'')'</span>);
g(3,2).facet_grid(r,c,<span class="string">'scale'</span>,<span class="string">'independent'</span>);
g(3,2).geom_point();
g(3,2).no_legend();
g(3,2).set_title(<span class="string">'facet_grid(''scale'',''independent'')'</span>);
g.set_color_options(<span class="string">'lightness_range'</span>,[40 80],<span class="string">'chroma_range'</span>,[80 40]);
g.set_names(<span class="string">'column'</span>,<span class="string">''</span>,<span class="string">'row'</span>,<span class="string">''</span>);
<span class="comment">%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])</span>
gf = copy(g);
figure(<span class="string">'Position'</span>,[100 100 800 800]);
g.set_title(<span class="string">'facet_grid() options'</span>);
g.draw();
figure(<span class="string">'Position'</span>,[100 100 800 800]);
gf.set_title({<span class="string">'facet_grid() options'</span> <span class="string">'work together with coord_flip()'</span>});
gf.coord_flip();
gf.draw();
</pre><img vspace="5" hspace="5" src="examples_11.png" alt=""> <img vspace="5" hspace="5" src="examples_12.png" alt=""> <h2>Options for creating histograms with stat_bin()<a name="18"></a></h2><p>Example of different <tt>'geom'</tt> options:</p><div><ul><li><tt>'bar'</tt> (default), where color groups are side-by-side (dodged)</li><li><tt>'stacked_bar'</tt></li><li><tt>'line'</tt></li><li><tt>'overlaid_bar'</tt></li><li><tt>'point'</tt></li><li><tt>'stairs'</tt></li></ul></div><pre class="codeinput"><span class="comment">%Create variables</span>
x=randn(1200,1)-1;
cat=repmat([1 1 1 2],300,1);
x(cat==2)=x(cat==2)+2;
clear <span class="string">g5</span>
g5(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'color'</span>,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(); <span class="comment">%by default, 'geom' is 'bar', where color groups are side-by-side (dodged)</span>
g5(1,1).set_title(<span class="string">'''bar'' (default)'</span>);
g5(1,2).stat_bin(<span class="string">'geom'</span>,<span class="string">'stacked_bar'</span>); <span class="comment">%Stacked bars option</span>
g5(1,2).set_title(<span class="string">'''stacked_bar'''</span>);
g5(2,1).stat_bin(<span class="string">'geom'</span>,<span class="string">'line'</span>); <span class="comment">%Draw lines instead of bars, easier to visualize when lots of categories, default fill to edges !</span>
g5(2,1).set_title(<span class="string">'''line'''</span>);
g5(2,2).stat_bin(<span class="string">'geom'</span>,<span class="string">'overlaid_bar'</span>); <span class="comment">%Overlaid bar automatically changes bar coloring to transparent</span>
g5(2,2).set_title(<span class="string">'''overlaid_bar'''</span>);
g5(1,3).stat_bin(<span class="string">'geom'</span>,<span class="string">'point'</span>);
g5(1,3).set_title(<span class="string">'''point'''</span>);
g5(2,3).stat_bin(<span class="string">'geom'</span>,<span class="string">'stairs'</span>); <span class="comment">%Default fill is edges</span>
g5(2,3).set_title(<span class="string">'''stairs'''</span>);
g5.set_title(<span class="string">'''geom'' options for stat_bin()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g5.draw();
</pre><img vspace="5" hspace="5" src="examples_13.png" alt=""> <p>Example of alternative <tt>'fill'</tt> options</p><div><ul><li><tt>'face'</tt></li><li><tt>'all'</tt></li><li><tt>'edge'</tt></li><li><tt>'transparent'</tt></li></ul></div><pre class="codeinput">clear <span class="string">g6</span>
g6(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'color'</span>,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(<span class="string">'fill'</span>,<span class="string">'face'</span>);
g6(1,1).set_title(<span class="string">'''face'''</span>);
g6(1,2).stat_bin(<span class="string">'fill'</span>,<span class="string">'transparent'</span>);
g6(1,2).set_title(<span class="string">'''transparent'''</span>);
g6(1,3).stat_bin(<span class="string">'fill'</span>,<span class="string">'all'</span>);
g6(1,3).set_title(<span class="string">'''all'''</span>);
g6(2,1).stat_bin(<span class="string">'fill'</span>,<span class="string">'edge'</span>);
g6(2,1).set_title(<span class="string">'''edge'''</span>);
g6(2,2).stat_bin(<span class="string">'geom'</span>,<span class="string">'stairs'</span>,<span class="string">'fill'</span>,<span class="string">'transparent'</span>);
g6(2,2).set_title(<span class="string">'''transparent'''</span>);
g6(2,3).stat_bin(<span class="string">'geom'</span>,<span class="string">'line'</span>,<span class="string">'fill'</span>,<span class="string">'all'</span>);
g6(2,3).set_title(<span class="string">'''all'''</span>);
g6.set_title(<span class="string">'''fill'' options for stat_bin()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g6.draw();
</pre><img vspace="5" hspace="5" src="examples_14.png" alt=""> <p>Examples of other histogram-generation options</p><div><ul><li>Default binning</li><li><tt>'normalization','probability'</tt></li><li><tt>'normalization','cumcount'</tt></li><li><tt>'normalization','cdf'</tt></li><li><tt>'edges',-1:0.5:10</tt></li><li><tt>'normalization','countdensity'</tt> and custom edges</li></ul></div><pre class="codeinput">clear <span class="string">g7</span>
g7(1,1)=gramm(<span class="string">'x'</span>,x,<span class="string">'color'</span>,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(<span class="string">'geom'</span>,<span class="string">'overlaid_bar'</span>); <span class="comment">%Default binning (30 bins)</span>
<span class="comment">%Normalization to 'probability'</span>
g7(2,1).stat_bin(<span class="string">'normalization'</span>,<span class="string">'probability'</span>,<span class="string">'geom'</span>,<span class="string">'overlaid_bar'</span>);
g7(2,1).set_title(<span class="string">'''normalization'',''probability'''</span>,<span class="string">'FontSize'</span>,10);
<span class="comment">%Normalization to cumulative count</span>
g7(1,2).stat_bin(<span class="string">'normalization'</span>,<span class="string">'cumcount'</span>,<span class="string">'geom'</span>,<span class="string">'stairs'</span>);
g7(1,2).set_title(<span class="string">'''normalization'',''cumcount'''</span>,<span class="string">'FontSize'</span>,10);
<span class="comment">%Normalization to cumulative density</span>
g7(2,2).stat_bin(<span class="string">'normalization'</span>,<span class="string">'cdf'</span>,<span class="string">'geom'</span>,<span class="string">'stairs'</span>);
g7(2,2).set_title(<span class="string">'''normalization'',''cdf'''</span>,<span class="string">'FontSize'</span>,10);
<span class="comment">%Custom edges for the bins</span>
g7(1,3).stat_bin(<span class="string">'edges'</span>,-1:0.5:10,<span class="string">'geom'</span>,<span class="string">'overlaid_bar'</span>);
g7(1,3).set_title(<span class="string">'''edges'',-1:0.5:10'</span>,<span class="string">'FontSize'</span>,10);
<span class="comment">%Custom edges with non-constand width (normalization 'countdensity'</span>
<span class="comment">%recommended)</span>
g7(2,3).stat_bin(<span class="string">'geom'</span>,<span class="string">'overlaid_bar'</span>,<span class="string">'normalization'</span>,<span class="string">'countdensity'</span>,<span class="string">'edges'</span>,[-5 -4 -2 -1 -0.5 -0.25 0 0.25 0.5 1 2 4 5]);
g7(2,3).set_title({<span class="string">'''normalization'',''countdensity'','</span> <span class="string">'''edges'','</span> <span class="string">'[-5 -4 -2 -1 -0.5 -0.25 0 0.25 0.5 1 2 4 5]'</span>},<span class="string">'FontSize'</span>,10);
g7.set_title(<span class="string">'Other options for stat_bin()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g7.draw();
</pre><img vspace="5" hspace="5" src="examples_15.png" alt=""> <h2>Visualize x-y difference with inset histogram using stat_cornerhist()<a name="21"></a></h2><pre class="codeinput"><span class="comment">%Generate sample data</span>
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 <span class="string">g</span>
g=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y,<span class="string">'color'</span>,c);
g.facet_grid([],b);
g.geom_point();
g.stat_cornerhist(<span class="string">'edges'</span>,-4:0.1:2,<span class="string">'aspect'</span>,0.5);
g.geom_abline();
g.set_title(<span class="string">'Visualize x-y with stat_cornerhist()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g.draw();
<span class="comment">%Possibility to use axe handles of the inset axes to add elements or change</span>
<span class="comment">%properties</span>
plot(g.results.stat_cornerhist(2).child_axe_handle,[-2 -2],[0 50],<span class="string">'k:'</span>,<span class="string">'LineWidth'</span>,2)
<span class="comment">%set([g.results.stat_cornerhist.child_axe_handle],'XTick',[])</span>
</pre><img vspace="5" hspace="5" src="examples_16.png" alt=""> <h2>Graphic and normalization options in stat_violin()<a name="22"></a></h2><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Origin_Region,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Cylinders,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(1,1).set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'# Cyl'</span>);
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));
<span class="comment">%Jittered scatter plot</span>
g(1,1).geom_jitter(<span class="string">'width'</span>,0.6,<span class="string">'height'</span>,0,<span class="string">'dodge'</span>,0.7);
g(1,1).set_title(<span class="string">'jittered data'</span>);
g(1,2).stat_violin(<span class="string">'normalization'</span>,<span class="string">'area'</span>);
g(1,2).set_title(<span class="string">'''normalization'',''area'' (Default)'</span>);
g(1,3).stat_violin(<span class="string">'normalization'</span>,<span class="string">'width'</span>);
g(1,3).set_title(<span class="string">'''normalization'',''width'''</span>);
g(2,1).stat_violin(<span class="string">'normalization'</span>,<span class="string">'count'</span>,<span class="string">'fill'</span>,<span class="string">'all'</span>);
g(2,1).set_title(<span class="string">'''normalization'',''count'' , ''fill'',''all'''</span>);
g(2,2).stat_violin(<span class="string">'half'</span>,true,<span class="string">'normalization'</span>,<span class="string">'count'</span>,<span class="string">'width'</span>,1,<span class="string">'fill'</span>,<span class="string">'transparent'</span>);
g(2,2).set_title(<span class="string">'''half'',true , ''fill'',''transparent'''</span>);
g(2,3)=gramm(<span class="string">'x'</span>,cars.Origin_Region,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Origin_Region,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g(2,3).set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'Origin'</span>);
g(2,3).stat_violin(<span class="string">'normalization'</span>,<span class="string">'area'</span>,<span class="string">'dodge'</span>,0,<span class="string">'fill'</span>,<span class="string">'edge'</span>);
g(2,3).stat_boxplot(<span class="string">'width'</span>,0.15);
g(2,3).set_title(<span class="string">'with stat_boxplot()'</span>);
g(2,3).set_color_options(<span class="string">'map'</span>,<span class="string">'brewer_dark'</span>);
g.set_title(<span class="string">'Options for stat_violin()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_17.png" alt=""> <h2>Options for dodging and spacing graphic elements in <tt>stat_summary()</tt> and <tt>stat_boxplot()</tt><a name="23"></a></h2><p><tt>stat_summary()</tt> and <tt>stat_boxplot()</tt>, as well as <tt>stat_bin()</tt>, use a pair of options for setting the width of graphical elements (<tt>'width'</tt>) and setting how elements of different colors can be dodged to the side to avoid overlap (<tt>'dodge'</tt>)</p><pre class="codeinput"><span class="comment">%Create data</span>
x=repmat(1:10,1,100);
catx=repmat({<span class="string">'A'</span> <span class="string">'B'</span> <span class="string">'C'</span> <span class="string">'F'</span> <span class="string">'E'</span> <span class="string">'D'</span> <span class="string">'G'</span> <span class="string">'H'</span> <span class="string">'I'</span> <span class="string">'J'</span>},1,100);
y=randn(1,1000)*3;
c=repmat([1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 3 2 2 2 1 1 2 2 2 2 3 2 3 2 1 1 2 2 2 2 2 2 2],1,25);
y=2+y+x+c*0.5;
clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,catx,<span class="string">'y'</span>,y,<span class="string">'color'</span>,c);
g(2,1)=copy(g(1));
g(3,1)=copy(g(1));
g(4,1)=copy(g(1));
g(5,1)=copy(g(1));
g(1,1).stat_boxplot();
g(1,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(1,1).set_title(<span class="string">'''width'',0.6,''dodge'',0.7 (Default)'</span>);
g(2,1).stat_boxplot(<span class="string">'width'</span>,0.5,<span class="string">'dodge'</span>,0);
g(2,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(2,1).set_title(<span class="string">'''width'',0.5,''dodge'',0'</span>);
g(3,1).stat_boxplot(<span class="string">'width'</span>,1,<span class="string">'dodge'</span>,1);
g(3,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(3,1).set_title(<span class="string">'''width'',1,''dodge'',1'</span>);
g(4,1).stat_boxplot(<span class="string">'width'</span>,0.6,<span class="string">'dodge'</span>,0.4);
g(4,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(4,1).set_title(<span class="string">'''width'',0.6,''dodge'',0.4'</span>);
g(5,1).facet_grid([],c);
g(5,1).stat_boxplot(<span class="string">'width'</span>,0.5,<span class="string">'dodge'</span>,0,<span class="string">'notch'</span>,true);
g(5,1).set_title(<span class="string">'''width'',0.5,''dodge'',0,''notch'',true'</span>);
g.set_title(<span class="string">'Dodge and spacing options for stat_boxplot()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 1000]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_18.png" alt=""> <p>With <tt>stat_summary()</tt>, <tt>'width'</tt> controls the width of bars and error bars.</p><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,catx,<span class="string">'y'</span>,y,<span class="string">'color'</span>,c);
g(2,1)=copy(g(1));
g(3,1)=copy(g(1));
g(4,1)=copy(g(1));
g(5,1)=copy(g(1));
g(1,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span> <span class="string">'black_errorbar'</span>},<span class="string">'setylim'</span>,true);
g(1,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(1,1).set_title(<span class="string">'Default dodging with ''geom'',''bar'''</span>);
g(2,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span> <span class="string">'black_errorbar'</span>},<span class="string">'dodge'</span>,0.7,<span class="string">'width'</span>,0.7);
g(2,1).set_title(<span class="string">'''dodge'',0.7,''width'',0.7'</span>);
g(2,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(3,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'area'</span>});
g(3,1).set_title(<span class="string">'''geom'',''area'''</span>);
g(3,1).set_title(<span class="string">'No dodging with ''geom'',''area'''</span>);
g(4,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'point'</span> <span class="string">'errorbar'</span>},<span class="string">'dodge'</span>,0.3,<span class="string">'width'</span>,0.5);
g(4,1).set_title(<span class="string">'''dodge'',0.3,''width'',0.5'</span>);
g(4,1).geom_vline(<span class="string">'xintercept'</span>,0.5:1:10.5,<span class="string">'style'</span>,<span class="string">'k-'</span>);
g(5,1).facet_grid([],c);
g(5,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span> <span class="string">'black_errorbar'</span>},<span class="string">'width'</span>,0.5,<span class="string">'dodge'</span>,0);
g(5,1).set_title(<span class="string">'''width'',0.5,''dodge'',0'</span>);
g.set_title(<span class="string">'Dodge and width options for stat_summary()'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 1000]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_19.png" alt=""> <h2>Plotting text or labeling with geom_label()<a name="25"></a></h2><pre class="codeinput"><span class="comment">%Convert structure to a table</span>
cars_table=struct2table(cars);
<span class="comment">%Create short version of model names by removing manufacturer</span>
cars_table.ModelShort=cellfun(@(ma,mo)mo(length(ma)+1:end),cars_table.Manufacturer,cars_table.Model,<span class="string">'UniformOutput'</span>,false);
figure(<span class="string">'Position'</span>,[100 100 800 500]);
clear <span class="string">g</span>
<span class="comment">%Provide 'label' as data</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars_table.Horsepower,<span class="string">'y'</span>,cars_table.Acceleration,<span class="keyword">...</span>
<span class="string">'label'</span>,cars_table.ModelShort,<span class="string">'color'</span>,cars_table.Manufacturer,<span class="string">'subset'</span>,strcmp(cars_table.Origin_Region,<span class="string">'Japan'</span>));
<span class="comment">%geom_label() takes the same arguments as text().</span>
<span class="comment">%'BackgroundColor','EdgeColor' and 'Color' can be set to 'auto'</span>
g.geom_label(<span class="string">'VerticalAlignment'</span>,<span class="string">'middle'</span>,<span class="string">'HorizontalAlignment'</span>,<span class="string">'center'</span>,<span class="string">'BackgroundColor'</span>,<span class="string">'auto'</span>,<span class="string">'Color'</span>,<span class="string">'k'</span>);
g.set_limit_extra([0.2 0.2],[0.1 0.1]);
g.set_names(<span class="string">'color'</span>,<span class="string">'Manufacturer'</span>,<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'Acceleration'</span>);
g.set_color_options(<span class="string">'map'</span>,<span class="string">'brewer2'</span>);
g.draw();
figure(<span class="string">'Position'</span>,[100 100 800 500]);
clear <span class="string">g</span>
<span class="comment">%Compute number of models outside of gramm so that the output can be used</span>
<span class="comment">%as label</span>
temp_table=rowfun(@numel,cars_table,<span class="string">'OutputVariableNames'</span>,<span class="string">'N'</span>,<span class="string">'GroupingVariables'</span>,{<span class="string">'Origin_Region'</span>,<span class="string">'Model_Year'</span>},<span class="string">'InputVariables'</span>,<span class="string">'MPG'</span>);
g=gramm(<span class="string">'x'</span>,temp_table.Model_Year,<span class="string">'y'</span>,temp_table.N,<span class="string">'color'</span>,temp_table.Origin_Region,<span class="string">'label'</span>,temp_table.N);
g.geom_bar(<span class="string">'dodge'</span>,0.7,<span class="string">'width'</span>,0.6);
g.geom_label(<span class="string">'color'</span>,<span class="string">'k'</span>,<span class="string">'dodge'</span>,0.7,<span class="string">'VerticalAlignment'</span>,<span class="string">'bottom'</span>,<span class="string">'HorizontalAlignment'</span>,<span class="string">'center'</span>);
g.set_names(<span class="string">'color'</span>,<span class="string">'Origin'</span>,<span class="string">'x'</span>,<span class="string">'Year'</span>,<span class="string">'y'</span>,<span class="string">'Number of models'</span>);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_20.png" alt=""> <img vspace="5" hspace="5" src="examples_21.png" alt=""> <h2>Smooth continuous data with stat_smooth()<a name="26"></a></h2><pre class="codeinput">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(<span class="string">'Position'</span>,[100 100 800 500]);
clear <span class="string">g</span>
g=gramm(<span class="string">'x'</span>,x,<span class="string">'y'</span>,y);
g.geom_funline(<span class="string">'fun'</span>,@(x)sin(exp(x-5)/12));
g.geom_vline(<span class="string">'xintercept'</span>,2)
g.axe_property(<span class="string">'XLim'</span>,[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(<span class="string">'Raw input'</span>);
g(1,2).stat_smooth();
g(1,2).set_title(<span class="string">'stat_smooth() default'</span>);
g(1,3).stat_smooth(<span class="string">'lambda'</span>,<span class="string">'auto'</span>,<span class="string">'npoints'</span>,500);
g(1,3).set_title(<span class="string">'default with ''lambda'',''auto'''</span>);
g(2,1).stat_smooth(<span class="string">'method'</span>,<span class="string">'sgolay'</span>,<span class="string">'lambda'</span>,[31 3]);
g(2,1).set_title(<span class="string">'''method'',''sgolay'''</span>);
g(2,2).stat_smooth(<span class="string">'method'</span>,<span class="string">'moving'</span>,<span class="string">'lambda'</span>,31);
g(2,2).set_title(<span class="string">'''method'',''moving'''</span>);
g(2,3).stat_smooth(<span class="string">'method'</span>,<span class="string">'loess'</span>,<span class="string">'lambda'</span>,0.1);
g(2,3).set_title(<span class="string">'''method'',''loess'''</span>);
g.set_title(<span class="string">'Options for stat_smooth()'</span>);
g.draw();
</pre><pre class="codeoutput">
ans =
gramm with properties:
legend_axe_handle: []
title_axe_handle: []
facet_axes_handles: []
results: []
</pre><img vspace="5" hspace="5" src="examples_22.png" alt=""> <h2>Superimposing gramm plots with update(): Using different groups for different stat_ and geom_ methods<a name="27"></a></h2><p>By using the method update() after a first draw() call of a gramm object, it is possible to add or remove grouping variables. Here in a first gramm plot we make a glm fit of cars Acceleration as a function of Horsepower, across all countries and number of cylinders, and change the color options so that the fit appears in grey</p><pre class="codeinput">clear <span class="string">g10</span>
figure(<span class="string">'Position'</span>,[100 100 600 450]);
g10=gramm(<span class="string">'x'</span>,cars.Horsepower,<span class="string">'y'</span>,cars.Acceleration,<span class="string">'subset'</span>,cars.Cylinders~=3 & cars.Cylinders~=5);
g10.set_names(<span class="string">'color'</span>,<span class="string">'# Cylinders'</span>,<span class="string">'x'</span>,<span class="string">'Horsepower'</span>,<span class="string">'y'</span>,<span class="string">'Acceleration'</span>,<span class="string">'Column'</span>,<span class="string">'Origin'</span>);
g10.set_color_options(<span class="string">'chroma'</span>,0,<span class="string">'lightness'</span>,30);
g10.stat_glm(<span class="string">'geom'</span>,<span class="string">'area'</span>,<span class="string">'disp_fit'</span>,false);
g10.set_title(<span class="string">'Update example'</span>); <span class="comment">%Title must be provided before the first draw() call</span>
g10.draw();
snapnow;
</pre><img vspace="5" hspace="5" src="examples_23.png" alt=""> <p>After the first draw() call (optional), we call the update() method by specifying a new grouping variable determining colors. We also change the facet_grid() options, which will duplicate the fit made earlier across all new facets. Last, color options are reinitialized to default values</p><pre class="codeinput">g10.update(<span class="string">'color'</span>,cars.Cylinders);
g10.facet_grid([],cars.Origin_Region);
g10.set_color_options();
g10.geom_point();
g10.draw();
</pre><img vspace="5" hspace="5" src="examples_24.png" alt=""> <h2>Superimposing gramm plots with update(): Plotting all the data in the background of facets<a name="29"></a></h2><pre class="codeinput"><span class="comment">%Inspired by https://drsimonj.svbtle.com/plotting-background-data-for-groups-with-ggplot2</span>
load <span class="string">fisheriris.mat</span>
clear <span class="string">g</span>
figure(<span class="string">'Position'</span>,[100 100 800 600]);
<span class="comment">%Create an histogram of all the data in the background (no facet_ is given yet)</span>
g(1,1)=gramm(<span class="string">'x'</span>,meas(:,2));
g(1,1).set_names(<span class="string">'x'</span>,<span class="string">'Sepal Width'</span>,<span class="string">'column'</span>,<span class="string">''</span>);
g(1,1).stat_bin(<span class="string">'fill'</span>,<span class="string">'all'</span>); <span class="comment">%histogram</span>
g(1,1).set_color_options(<span class="string">'chroma'</span>,0,<span class="string">'lightness'</span>,75); <span class="comment">%We make it light grey</span>
g(1,1).set_title(<span class="string">'Overlaid histograms'</span>);
<span class="comment">%Create a scatter plot of all the data in the background (no facet_ is given yet)</span>
g(2,1)=gramm(<span class="string">'x'</span>,meas(:,2),<span class="string">'y'</span>,meas(:,1));
g(2,1).set_names(<span class="string">'x'</span>,<span class="string">'Sepal Width'</span>,<span class="string">'column'</span>,<span class="string">''</span>,<span class="string">'y'</span>,<span class="string">'Sepal Length'</span>);
g(2,1).geom_point(); <span class="comment">%Scatter plot</span>
g(2,1).set_color_options(<span class="string">'chroma'</span>,0,<span class="string">'lightness'</span>,75); <span class="comment">%We make it light grey</span>
g(2,1).set_point_options(<span class="string">'base_size'</span>,6);
g(2,1).set_title(<span class="string">'Overlaid scatter plots'</span>);
g.draw(); <span class="comment">%Draw the backgrounds</span>
g(1,1).update(<span class="string">'color'</span>,species); <span class="comment">%Add color with update()</span>
g(1,1).facet_grid([],species); <span class="comment">%Provide facets</span>
g(1,1).stat_bin(<span class="string">'dodge'</span>,0); <span class="comment">%Histogram (we set dodge to zero as facet_grid makes it useless)</span>
g(1,1).set_color_options(); <span class="comment">%Reset to default colors</span>
g(1,1).no_legend();
g(1,1).axe_property(<span class="string">'ylim'</span>,[-2 30]); <span class="comment">%We have to set y scale manually, as the automatic scaling from the first plot was forgotten</span>
g(2,1).update(<span class="string">'color'</span>,species); <span class="comment">%Add color with update()</span>
g(2,1).facet_grid([],species); <span class="comment">%Provide facets</span>
g(2,1).geom_point();
g(2,1).set_color_options();
g(2,1).no_legend();
<span class="comment">%Set global axe properties</span>
g.axe_property(<span class="string">'TickDir'</span>,<span class="string">'out'</span>,<span class="string">'XGrid'</span>,<span class="string">'on'</span>,<span class="string">'Ygrid'</span>,<span class="string">'on'</span>,<span class="string">'GridColor'</span>,[0.5 0.5 0.5]);
<span class="comment">%Draw the news elements</span>
g.draw();
</pre><img vspace="5" hspace="5" src="examples_25.png" alt=""> <h2>Use custom layouts in gramm, marginal histogram example<a name="30"></a></h2><pre class="codeinput">load <span class="string">fisheriris.mat</span>
clear <span class="string">g</span>
figure(<span class="string">'Position'</span>,[100 100 550 550]);
<span class="comment">%Create x data histogram on top</span>
g(1,1)=gramm(<span class="string">'x'</span>,meas(:,2),<span class="string">'color'</span>,species);
g(1,1).set_layout_options(<span class="string">'Position'</span>,[0 0.8 0.8 0.2],<span class="keyword">...</span><span class="comment"> %Set the position in the figure (as in standard 'Position' axe property)</span>
<span class="string">'legend'</span>,false,<span class="keyword">...</span><span class="comment"> % No need to display legend for side histograms</span>
<span class="string">'margin_height'</span>,[0.02 0.05],<span class="keyword">...</span><span class="comment"> %We set custom margins, values must be coordinated between the different elements so that alignment is maintained</span>
<span class="string">'margin_width'</span>,[0.1 0.02],<span class="keyword">...</span>
<span class="string">'redraw'</span>,false); <span class="comment">%We deactivate automatic redrawing/resizing so that the axes stay aligned according to the margin options</span>
g(1,1).set_names(<span class="string">'x'</span>,<span class="string">''</span>);
g(1,1).stat_bin(<span class="string">'geom'</span>,<span class="string">'stacked_bar'</span>,<span class="string">'fill'</span>,<span class="string">'all'</span>,<span class="string">'nbins'</span>,15); <span class="comment">%histogram</span>
g(1,1).axe_property(<span class="string">'XTickLabel'</span>,<span class="string">''</span>); <span class="comment">% We deactivate tht ticks</span>
<span class="comment">%Create a scatter plot</span>
g(2,1)=gramm(<span class="string">'x'</span>,meas(:,2),<span class="string">'y'</span>,meas(:,1),<span class="string">'color'</span>,species);
g(2,1).set_names(<span class="string">'x'</span>,<span class="string">'Sepal Width'</span>,<span class="string">'y'</span>,<span class="string">'Sepal Length'</span>,<span class="string">'color'</span>,<span class="string">'Species'</span>);
g(2,1).geom_point(); <span class="comment">%Scatter plot</span>
g(2,1).set_point_options(<span class="string">'base_size'</span>,6);
g(2,1).set_layout_options(<span class="string">'Position'</span>,[0 0 0.8 0.8],<span class="keyword">...</span>
<span class="string">'legend_pos'</span>,[0.83 0.75 0.2 0.2],<span class="keyword">...</span><span class="comment"> %We detach the legend from the plot and move it to the top right</span>
<span class="string">'margin_height'</span>,[0.1 0.02],<span class="keyword">...</span>
<span class="string">'margin_width'</span>,[0.1 0.02],<span class="keyword">...</span>
<span class="string">'redraw'</span>,false);
g(2,1).axe_property(<span class="string">'Ygrid'</span>,<span class="string">'on'</span>);
<span class="comment">%Create y data histogram on the right</span>
g(3,1)=gramm(<span class="string">'x'</span>,meas(:,1),<span class="string">'color'</span>,species);
g(3,1).set_layout_options(<span class="string">'Position'</span>,[0.8 0 0.2 0.8],<span class="keyword">...</span>
<span class="string">'legend'</span>,false,<span class="keyword">...</span>
<span class="string">'margin_height'</span>,[0.1 0.02],<span class="keyword">...</span>
<span class="string">'margin_width'</span>,[0.02 0.05],<span class="keyword">...</span>
<span class="string">'redraw'</span>,false);
g(3,1).set_names(<span class="string">'x'</span>,<span class="string">''</span>);
g(3,1).stat_bin(<span class="string">'geom'</span>,<span class="string">'stacked_bar'</span>,<span class="string">'fill'</span>,<span class="string">'all'</span>,<span class="string">'nbins'</span>,15); <span class="comment">%histogram</span>
g(3,1).coord_flip();
g(3,1).axe_property(<span class="string">'XTickLabel'</span>,<span class="string">''</span>);
<span class="comment">%Set global axe properties</span>
g.axe_property(<span class="string">'TickDir'</span>,<span class="string">'out'</span>,<span class="string">'XGrid'</span>,<span class="string">'on'</span>,<span class="string">'GridColor'</span>,[0.5 0.5 0.5]);
g.set_title(<span class="string">'Fisher Iris, custom layout'</span>);
g.set_color_options(<span class="string">'map'</span>,<span class="string">'d3_10'</span>);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_26.png" alt=""> <h2>Plot one variable against many others<a name="31"></a></h2><pre class="codeinput"><span class="comment">%Inspired by: https://drsimonj.svbtle.com/plot-some-variables-against-many-others</span>
<span class="comment">%Convert structure to a table</span>
cars_table=struct2table(cars);
<span class="comment">%Use stack to transform the wide table to a long format</span>
T=stack(cars_table,{<span class="string">'Displacement'</span> <span class="string">'Weight'</span> <span class="string">'Acceleration'</span>});
<span class="comment">%Use the variable resutling from the stacking as x</span>
g=gramm(<span class="string">'x'</span>,T.Displacement_Weight_Acceleration,<span class="string">'y'</span>,T.MPG,<span class="string">'color'</span>,T.Horsepower,<span class="string">'marker'</span>,T.Cylinders,<span class="string">'subset'</span>,T.Cylinders~=3 & T.Cylinders~=5 & T.Model_Year<75);
<span class="comment">%Use the stacking indicator as facet variable</span>
g.facet_wrap(T.Displacement_Weight_Acceleration_Indicator,<span class="string">'scale'</span>,<span class="string">'independent'</span>);
g.set_point_options(<span class="string">'base_size'</span>,7);
g.set_continuous_color(<span class="string">'LCH_colormap'</span>,[20 80 ; 40 30 ; 260 260 ]);
g.set_names(<span class="string">'y'</span>,<span class="string">'MPG'</span>,<span class="string">'x'</span>,<span class="string">'Value'</span>,<span class="string">'column'</span>,<span class="string">''</span>,<span class="string">'color'</span>,<span class="string">'HP'</span>,<span class="string">'marker'</span>,<span class="string">'# Cylinders'</span>);
g.geom_point();
g.axe_property(<span class="string">'TickDir'</span>,<span class="string">'out'</span>,<span class="string">'XGrid'</span>,<span class="string">'on'</span>,<span class="string">'Ygrid'</span>,<span class="string">'on'</span>,<span class="string">'GridColor'</span>,[0.5 0.5 0.5]);
figure(<span class="string">'Position'</span>,[100 100 700 350]);
g.draw();
</pre><img vspace="5" hspace="5" src="examples_27.png" alt=""> <h2>Customizing color maps with set_color_options()<a name="32"></a></h2><p>With the method set_color_options(), automatic color generation for color and lightness groups can be tweaked</p><pre class="codeinput"><span class="comment">%Default: LCH-based colormap with hue variation</span>
clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Origin,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Origin);
g(1,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span>},<span class="string">'dodge'</span>,0);
g(1,2)=copy(g(1));
g(1,3)=gramm(<span class="string">'x'</span>,cars.Origin,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'lightness'</span>,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(<span class="string">'Default LCH (''color'' groups)'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Possibility to change the hue range as well as lightness and chroma of</span>
<span class="comment">%the LCH-based colormap</span>
g(1,2).set_color_options(<span class="string">'hue_range'</span>,[-60 60],<span class="string">'chroma'</span>,40,<span class="string">'lightness'</span>,90);
g(1,2).set_title(<span class="string">'Modified LCH (''color'' groups)'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Possibility to change the lightness and chroma range of the LCH-based</span>
<span class="comment">%colormap when a 'lightness' variable is given</span>
g(1,3).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span>},<span class="string">'dodge'</span>,0);
g(1,3).set_color_options(<span class="string">'lightness_range'</span>,[0 95],<span class="string">'chroma_range'</span>,[0 0]);
g(1,3).set_title(<span class="string">'Modified LCH (''lightness'' groups)'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Go back to Matlab's defauls colormap</span>
g(2,1).set_color_options(<span class="string">'map'</span>,<span class="string">'matlab'</span>);
g(2,1).set_title(<span class="string">'Matlab 2014B+ '</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Brewer colormap 1</span>
g(2,2).set_color_options(<span class="string">'map'</span>,<span class="string">'brewer1'</span>);
g(2,2).set_title(<span class="string">'Color Brewer 1'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Brewer colormap 2</span>
g(2,3).set_color_options(<span class="string">'map'</span>,<span class="string">'brewer2'</span>);
g(2,3).set_title(<span class="string">'Color Brewer 2'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">%Some methods can be called on all objects at the same time !</span>
g.axe_property(<span class="string">'YLim'</span>,[0 140]);
g.axe_property(<span class="string">'XTickLabelRotation'</span>,60); <span class="comment">%Should work for recent Matlab versions</span>
g.set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'Origin'</span>,<span class="string">'lightness'</span>,<span class="string">'Origin'</span>);
g.set_title(<span class="string">'Colormap customizations examples'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600])
g.draw();
</pre><pre class="codeoutput">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
Less than 2 samples for CI computation...Skipping
Less than 2 samples for CI computation...Skipping
</pre><img vspace="5" hspace="5" src="examples_28.png" alt=""> <h2>Customizing color/lightness maps and legends with set_color_options()<a name="33"></a></h2><p>With the method set_color_options(), automatic color generation for color and lightness groups can be tweaked</p><pre class="codeinput">clear <span class="string">g</span>
g(1,1)=gramm(<span class="string">'x'</span>,cars.Origin_Region,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Origin_Region,<span class="string">'lightness'</span>,cars.Cylinders,<span class="keyword">...</span>
<span class="string">'subset'</span>,cars.Cylinders==4 | cars.Cylinders==6);
g(1,1).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span>},<span class="string">'dodge'</span>,1.3,<span class="string">'width'</span>,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) );
<span class="comment">% Default lightness/chroma is beter suited for more lightness categories</span>
g(1,1).set_title(<span class="string">'Default LCH, default legend'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">% It is possible to restrict the lightness/chroma changes across the</span>
<span class="comment">% lightness categories. Forcing the legend to 'separate' here makes the</span>
<span class="comment">% lightness legends use the first color instead of gray levels</span>
g(1,2).set_color_options(<span class="string">'lightness_range'</span>,[70 40],<span class="string">'chroma_range'</span>,[60 70],<span class="string">'legend'</span>,<span class="string">'separate'</span>);
g(1,2).set_title(<span class="string">'Modified LCH, lightness legend with color'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">% Pre-defined color/lightness maps can yeild better results than default</span>
<span class="comment">% parametric LCH colormaps</span>
g(1,3).set_color_options(<span class="string">'map'</span>,<span class="string">'brewer_paired'</span>);
g(1,3).set_title(<span class="string">'Brewer colormap'</span>,<span class="string">'FontSize'</span>,12);
<span class="comment">% Witht the 'expand' legend option, all ligthness/color combinations are</span>
<span class="comment">% presented in the legend</span>
g(2,1).set_color_options(<span class="string">'map'</span>,<span class="string">'d3_20'</span>,<span class="string">'legend'</span>,<span class="string">'expand'</span>);
g(2,1).set_title(<span class="string">'D3.js colormap, ''expand'' legend option'</span>,<span class="string">'FontSize'</span>,12);
g(2,2)=gramm(<span class="string">'x'</span>,cars.Origin,<span class="string">'y'</span>,cars.Horsepower,<span class="string">'color'</span>,cars.Origin,<span class="keyword">...</span>
<span class="string">'marker'</span>,cars.Origin,<span class="string">'subset'</span>,cars.Cylinders==4 | cars.Cylinders==6);
g(2,2).stat_summary(<span class="string">'geom'</span>,{<span class="string">'bar'</span>},<span class="string">'dodge'</span>,0,<span class="string">'width'</span>,0.15);
g(2,2).stat_summary(<span class="string">'geom'</span>,{<span class="string">'point'</span>},<span class="string">'dodge'</span>,0,<span class="string">'width'</span>,1);
g(2,2).set_point_options(<span class="string">'base_size'</span>,10);
g(2,3)=copy(g(2,2));
g(2,2).set_title(<span class="string">'D3.js colormap'</span>,<span class="string">'FontSize'</span>,12);
g(2,2).set_color_options(<span class="string">'map'</span>,<span class="string">'d3_10'</span>);
<span class="comment">% With the 'merge' legend option, plots that use the same categories for</span>
<span class="comment">% color and marker/linestyle/size will be combined</span>
g(2,3).set_color_options(<span class="string">'map'</span>,<span class="string">'d3_10'</span>,<span class="string">'legend'</span>,<span class="string">'merge'</span>);
g(2,3).set_title(<span class="string">'D3.js colormap, ''merge'' legend option'</span>,<span class="string">'FontSize'</span>,12);
g.axe_property(<span class="string">'YLim'</span>,[0 160]);
g.axe_property(<span class="string">'XTickLabelRotation'</span>,60); <span class="comment">%Should work for recent Matlab versions</span>
g.set_names(<span class="string">'x'</span>,<span class="string">'Origin'</span>,<span class="string">'y'</span>,<span class="string">'Horsepower'</span>,<span class="string">'color'</span>,<span class="string">'Origin'</span>,<span class="string">'marker'</span>,<span class="string">'Origin'</span>,<span class="string">'lightness'</span>,<span class="string">'# Cyl'</span>);
g.set_title(<span class="string">'Color/Lightness maps and legend customizations examples'</span>);
figure(<span class="string">'Position'</span>,[100 100 800 600]);
g.draw();
</pre><pre class="codeoutput">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
</pre><img vspace="5" hspace="5" src="examples_29.png" alt=""> <h2>Using a continuous color scale<a name="34"></a></h2><p>When the variable provided as 'color' contains too many different values (>15), or when set_continuous_color is used, gramm switches from a categorical color scale to a gradient-based continuous color scale.</p><pre class="codeinput">load <span class="string">spectra.mat</span>
<span class="comment">%Here we create x as a 1xN array (see example above), and use a MxN matrix</span>
<span class="comment">%for y. Color applies to the M rows of y.</span>
g18=gramm(<span class="string">'x'</span>,900:2:1700,<span class="string">'y'</span>,NIR,<span class="string">'color'</span>,octane);
g18.set_names(<span class="string">'x'</span>,<span class="string">'Wavelength (nm)'</span>,<span class="string">'y'</span>,<span class="string">'NIR'</span>,<span class="string">'color'</span>,<span class="string">'Octane'</span>);
g18.set_continuous_color(<span class="string">'colormap'</span>,<span class="string">'hot'</span>);
g18.geom_line;
figure(<span class="string">'Position'</span>,[100 100 800 450]);
g18.draw();
</pre><img vspace="5" hspace="5" src="examples_30.png" alt=""> <h2>Changing the order of elements with set_order_options()<a name="35"></a></h2><p>By default, gramm uses grouping data in increasing order of the group value (alphabetical for cellstr, numerical for arrays). Using set_order_options(), it is possible to fine tweak the orders of color, lightness, facet rows and columns, as well as categorical X</p><pre class="codeinput">y=[36 38 40 42 44 46];