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} code > span.ot { color: #007020; } code > span.al { color: #ff0000; font-weight: bold; } code > span.fu { color: #900; font-weight: bold; } code > span.er { color: #a61717; background-color: #e3d2d2; } </style> </head> <body> <h1 class="title toc-ignore">Extending ggplot2</h1> <p>This vignette documents the official extension mechanism provided in ggplot2 2.0.0. This vignette is a high-level adjunct to the low-level details found in <code>?Stat</code>, <code>?Geom</code> and <code>?theme</code>. You’ll learn how to extend ggplot2 by creating a new stat, geom, or theme.</p> <p>As you read this document, you’ll see many things that will make you scratch your head and wonder why on earth is it designed this way? Mostly it’s historical accident - I wasn’t a terribly good R programmer when I started writing ggplot2 and I made a lot of questionable decisions. We cleaned up as many of those issues as possible in the 2.0.0 release, but some fixes simply weren’t worth the effort.</p> <div id="ggproto" class="section level2"> <h2>ggproto</h2> <p>All ggplot2 objects are built using the ggproto system of object oriented programming. This OO system is used only in one place: ggplot2. This is mostly historical accident: ggplot2 started off using <a href="https://cran.r-project.org/package=proto">proto</a> because I needed mutable objects. This was well before the creation of (the briefly lived) <a href="http://vita.had.co.nz/papers/mutatr.html">mutatr</a>, reference classes and R6: proto was the only game in town.</p> <p>But why ggproto? Well when we turned to add an official extension mechanism to ggplot2, we found a major problem that caused problems when proto objects were extended in a different package (methods were evaluated in ggplot2, not the package where the extension was added). We tried converting to R6, but it was a poor fit for the needs of ggplot2. We could’ve modified proto, but that would’ve first involved understanding exactly how proto worked, and secondly making sure that the changes didn’t affect other users of proto.</p> <p>It’s strange to say, but this is a case where inventing a new OO system was actually the right answer to the problem! Fortunately Winston is now very good at creating OO systems, so it only took him a day to come up with ggproto: it maintains all the features of proto that ggplot2 needs, while allowing cross package inheritance to work.</p> <p>Here’s a quick demo of ggproto in action:</p> <div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1"></a>A <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"A"</span>, <span class="ot">NULL</span>,</span> <span id="cb1-2"><a href="#cb1-2"></a> <span class="dt">x =</span> <span class="dv">1</span>,</span> <span id="cb1-3"><a href="#cb1-3"></a> <span class="dt">inc =</span> <span class="cf">function</span>(self) {</span> <span id="cb1-4"><a href="#cb1-4"></a> self<span class="op">$</span>x <-<span class="st"> </span>self<span class="op">$</span>x <span class="op">+</span><span class="st"> </span><span class="dv">1</span></span> <span id="cb1-5"><a href="#cb1-5"></a> }</span> <span id="cb1-6"><a href="#cb1-6"></a>)</span> <span id="cb1-7"><a href="#cb1-7"></a>A<span class="op">$</span>x</span> <span id="cb1-8"><a href="#cb1-8"></a><span class="co">#> [1] 1</span></span> <span id="cb1-9"><a href="#cb1-9"></a>A<span class="op">$</span><span class="kw">inc</span>()</span> <span id="cb1-10"><a href="#cb1-10"></a>A<span class="op">$</span>x</span> <span id="cb1-11"><a href="#cb1-11"></a><span class="co">#> [1] 2</span></span> <span id="cb1-12"><a href="#cb1-12"></a>A<span class="op">$</span><span class="kw">inc</span>()</span> <span id="cb1-13"><a href="#cb1-13"></a>A<span class="op">$</span><span class="kw">inc</span>()</span> <span id="cb1-14"><a href="#cb1-14"></a>A<span class="op">$</span>x</span> <span id="cb1-15"><a href="#cb1-15"></a><span class="co">#> [1] 4</span></span></code></pre></div> <p>The majority of ggplot2 classes are immutable and static: the methods neither use nor modify state in the class. They’re mostly used as a convenient way of bundling related methods together.</p> <p>To create a new geom or stat, you will just create a new ggproto that inherits from <code>Stat</code>, <code>Geom</code> and override the methods described below.</p> </div> <div id="creating-a-new-stat" class="section level2"> <h2>Creating a new stat</h2> <div id="the-simplest-stat" class="section level3"> <h3>The simplest stat</h3> <p>We’ll start by creating a very simple stat: one that gives the convex hull (the <em>c</em> hull) of a set of points. First we create a new ggproto object that inherits from <code>Stat</code>:</p> <div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1"></a>StatChull <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatChull"</span>, Stat,</span> <span id="cb2-2"><a href="#cb2-2"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales) {</span> <span id="cb2-3"><a href="#cb2-3"></a> data[<span class="kw">chull</span>(data<span class="op">$</span>x, data<span class="op">$</span>y), , drop =<span class="st"> </span><span class="ot">FALSE</span>]</span> <span id="cb2-4"><a href="#cb2-4"></a> },</span> <span id="cb2-5"><a href="#cb2-5"></a> </span> <span id="cb2-6"><a href="#cb2-6"></a> <span class="dt">required_aes =</span> <span class="kw">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>)</span> <span id="cb2-7"><a href="#cb2-7"></a>)</span></code></pre></div> <p>The two most important components are the <code>compute_group()</code> method (which does the computation), and the <code>required_aes</code> field, which lists which aesthetics must be present in order for the stat to work.</p> <p>Next we write a layer function. Unfortunately, due to an early design mistake I called these either <code>stat_()</code> or <code>geom_()</code>. A better decision would have been to call them <code>layer_()</code> functions: that’s a more accurate description because every layer involves a stat <em>and</em> a geom.</p> <p>All layer functions follow the same form - you specify defaults in the function arguments and then call the <code>layer()</code> function, sending <code>...</code> into the <code>params</code> argument. The arguments in <code>...</code> will either be arguments for the geom (if you’re making a stat wrapper), arguments for the stat (if you’re making a geom wrapper), or aesthetics to be set. <code>layer()</code> takes care of teasing the different parameters apart and making sure they’re stored in the right place:</p> <div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1"></a>stat_chull <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">geom =</span> <span class="st">"polygon"</span>,</span> <span id="cb3-2"><a href="#cb3-2"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb3-3"><a href="#cb3-3"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, ...) {</span> <span id="cb3-4"><a href="#cb3-4"></a> <span class="kw">layer</span>(</span> <span id="cb3-5"><a href="#cb3-5"></a> <span class="dt">stat =</span> StatChull, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping, <span class="dt">geom =</span> geom, </span> <span id="cb3-6"><a href="#cb3-6"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb3-7"><a href="#cb3-7"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb3-8"><a href="#cb3-8"></a> )</span> <span id="cb3-9"><a href="#cb3-9"></a>}</span></code></pre></div> <p>(Note that if you’re writing this in your own package, you’ll either need to call <code>ggplot2::layer()</code> explicitly, or import the <code>layer()</code> function into your package namespace.)</p> <p>Once we have a layer function we can try our new stat:</p> <div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb4-2"><a href="#cb4-2"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb4-3"><a href="#cb4-3"></a><span class="st"> </span><span class="kw">stat_chull</span>(<span class="dt">fill =</span> <span class="ot">NA</span>, <span class="dt">colour =</span> <span class="st">"black"</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>(We’ll see later how to change the defaults of the geom so that you don’t need to specify <code>fill = NA</code> every time.)</p> <p>Once we’ve written this basic object, ggplot2 gives a lot for free. For example, ggplot2 automatically preserves aesthetics that are constant within each group:</p> <div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy, <span class="dt">colour =</span> drv)) <span class="op">+</span><span class="st"> </span></span> <span id="cb5-2"><a href="#cb5-2"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb5-3"><a href="#cb5-3"></a><span class="st"> </span><span class="kw">stat_chull</span>(<span class="dt">fill =</span> <span class="ot">NA</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>We can also override the default geom to display the convex hull in a different way:</p> <div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb6-2"><a href="#cb6-2"></a><span class="st"> </span><span class="kw">stat_chull</span>(<span class="dt">geom =</span> <span class="st">"point"</span>, <span class="dt">size =</span> <span class="dv">4</span>, <span class="dt">colour =</span> <span class="st">"red"</span>) <span class="op">+</span></span> <span id="cb6-3"><a href="#cb6-3"></a><span class="st"> </span><span class="kw">geom_point</span>()</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> </div> <div id="stat-parameters" class="section level3"> <h3>Stat parameters</h3> <p>A more complex stat will do some computation. Let’s implement a simple version of <code>geom_smooth()</code> that adds a line of best fit to a plot. We create a <code>StatLm</code> that inherits from <code>Stat</code> and a layer function, <code>stat_lm()</code>:</p> <div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1"></a>StatLm <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatLm"</span>, Stat, </span> <span id="cb7-2"><a href="#cb7-2"></a> <span class="dt">required_aes =</span> <span class="kw">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb7-3"><a href="#cb7-3"></a> </span> <span id="cb7-4"><a href="#cb7-4"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales) {</span> <span id="cb7-5"><a href="#cb7-5"></a> rng <-<span class="st"> </span><span class="kw">range</span>(data<span class="op">$</span>x, <span class="dt">na.rm =</span> <span class="ot">TRUE</span>)</span> <span id="cb7-6"><a href="#cb7-6"></a> grid <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">x =</span> rng)</span> <span id="cb7-7"><a href="#cb7-7"></a> </span> <span id="cb7-8"><a href="#cb7-8"></a> mod <-<span class="st"> </span><span class="kw">lm</span>(y <span class="op">~</span><span class="st"> </span>x, <span class="dt">data =</span> data)</span> <span id="cb7-9"><a href="#cb7-9"></a> grid<span class="op">$</span>y <-<span class="st"> </span><span class="kw">predict</span>(mod, <span class="dt">newdata =</span> grid)</span> <span id="cb7-10"><a href="#cb7-10"></a> </span> <span id="cb7-11"><a href="#cb7-11"></a> grid</span> <span id="cb7-12"><a href="#cb7-12"></a> }</span> <span id="cb7-13"><a href="#cb7-13"></a>)</span> <span id="cb7-14"><a href="#cb7-14"></a></span> <span id="cb7-15"><a href="#cb7-15"></a>stat_lm <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">geom =</span> <span class="st">"line"</span>,</span> <span id="cb7-16"><a href="#cb7-16"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb7-17"><a href="#cb7-17"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, ...) {</span> <span id="cb7-18"><a href="#cb7-18"></a> <span class="kw">layer</span>(</span> <span id="cb7-19"><a href="#cb7-19"></a> <span class="dt">stat =</span> StatLm, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping, <span class="dt">geom =</span> geom, </span> <span id="cb7-20"><a href="#cb7-20"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb7-21"><a href="#cb7-21"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb7-22"><a href="#cb7-22"></a> )</span> <span id="cb7-23"><a href="#cb7-23"></a>}</span> <span id="cb7-24"><a href="#cb7-24"></a></span> <span id="cb7-25"><a href="#cb7-25"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb7-26"><a href="#cb7-26"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb7-27"><a href="#cb7-27"></a><span class="st"> </span><span class="kw">stat_lm</span>()</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p><code>StatLm</code> is inflexible because it has no parameters. We might want to allow the user to control the model formula and the number of points used to generate the grid. To do so, we add arguments to the <code>compute_group()</code> method and our wrapper function:</p> <div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1"></a>StatLm <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatLm"</span>, Stat, </span> <span id="cb8-2"><a href="#cb8-2"></a> <span class="dt">required_aes =</span> <span class="kw">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb8-3"><a href="#cb8-3"></a> </span> <span id="cb8-4"><a href="#cb8-4"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales, params, <span class="dt">n =</span> <span class="dv">100</span>, <span class="dt">formula =</span> y <span class="op">~</span><span class="st"> </span>x) {</span> <span id="cb8-5"><a href="#cb8-5"></a> rng <-<span class="st"> </span><span class="kw">range</span>(data<span class="op">$</span>x, <span class="dt">na.rm =</span> <span class="ot">TRUE</span>)</span> <span id="cb8-6"><a href="#cb8-6"></a> grid <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">x =</span> <span class="kw">seq</span>(rng[<span class="dv">1</span>], rng[<span class="dv">2</span>], <span class="dt">length =</span> n))</span> <span id="cb8-7"><a href="#cb8-7"></a> </span> <span id="cb8-8"><a href="#cb8-8"></a> mod <-<span class="st"> </span><span class="kw">lm</span>(formula, <span class="dt">data =</span> data)</span> <span id="cb8-9"><a href="#cb8-9"></a> grid<span class="op">$</span>y <-<span class="st"> </span><span class="kw">predict</span>(mod, <span class="dt">newdata =</span> grid)</span> <span id="cb8-10"><a href="#cb8-10"></a> </span> <span id="cb8-11"><a href="#cb8-11"></a> grid</span> <span id="cb8-12"><a href="#cb8-12"></a> }</span> <span id="cb8-13"><a href="#cb8-13"></a>)</span> <span id="cb8-14"><a href="#cb8-14"></a></span> <span id="cb8-15"><a href="#cb8-15"></a>stat_lm <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">geom =</span> <span class="st">"line"</span>,</span> <span id="cb8-16"><a href="#cb8-16"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb8-17"><a href="#cb8-17"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, <span class="dt">n =</span> <span class="dv">50</span>, <span class="dt">formula =</span> y <span class="op">~</span><span class="st"> </span>x, </span> <span id="cb8-18"><a href="#cb8-18"></a> ...) {</span> <span id="cb8-19"><a href="#cb8-19"></a> <span class="kw">layer</span>(</span> <span id="cb8-20"><a href="#cb8-20"></a> <span class="dt">stat =</span> StatLm, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping, <span class="dt">geom =</span> geom, </span> <span id="cb8-21"><a href="#cb8-21"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb8-22"><a href="#cb8-22"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">n =</span> n, <span class="dt">formula =</span> formula, <span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb8-23"><a href="#cb8-23"></a> )</span> <span id="cb8-24"><a href="#cb8-24"></a>}</span> <span id="cb8-25"><a href="#cb8-25"></a></span> <span id="cb8-26"><a href="#cb8-26"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb8-27"><a href="#cb8-27"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb8-28"><a href="#cb8-28"></a><span class="st"> </span><span class="kw">stat_lm</span>(<span class="dt">formula =</span> y <span class="op">~</span><span class="st"> </span><span class="kw">poly</span>(x, <span class="dv">10</span>)) <span class="op">+</span><span class="st"> </span></span> <span id="cb8-29"><a href="#cb8-29"></a><span class="st"> </span><span class="kw">stat_lm</span>(<span class="dt">formula =</span> y <span class="op">~</span><span class="st"> </span><span class="kw">poly</span>(x, <span class="dv">10</span>), <span class="dt">geom =</span> <span class="st">"point"</span>, <span class="dt">colour =</span> <span class="st">"red"</span>, <span class="dt">n =</span> <span class="dv">20</span>)</span></code></pre></div> <p><img 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" style="display: block; margin: auto;" /></p> <p>Note that we don’t <em>have</em> to explicitly include the new parameters in the arguments for the layer, <code>...</code> will get passed to the right place anyway. But you’ll need to document them somewhere so the user knows about them. Here’s a brief example. Note <code>@inheritParams ggplot2::stat_identity</code>: that will automatically inherit documentation for all the parameters also defined for <code>stat_identity()</code>.</p> <div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1"></a><span class="co">#' @export</span></span> <span id="cb9-2"><a href="#cb9-2"></a><span class="co">#' @inheritParams ggplot2::stat_identity</span></span> <span id="cb9-3"><a href="#cb9-3"></a><span class="co">#' @param formula The modelling formula passed to \code{lm}. Should only </span></span> <span id="cb9-4"><a href="#cb9-4"></a><span class="co">#' involve \code{y} and \code{x}</span></span> <span id="cb9-5"><a href="#cb9-5"></a><span class="co">#' @param n Number of points used for interpolation.</span></span> <span id="cb9-6"><a href="#cb9-6"></a>stat_lm <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">geom =</span> <span class="st">"line"</span>,</span> <span id="cb9-7"><a href="#cb9-7"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb9-8"><a href="#cb9-8"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, <span class="dt">n =</span> <span class="dv">50</span>, <span class="dt">formula =</span> y <span class="op">~</span><span class="st"> </span>x, </span> <span id="cb9-9"><a href="#cb9-9"></a> ...) {</span> <span id="cb9-10"><a href="#cb9-10"></a> <span class="kw">layer</span>(</span> <span id="cb9-11"><a href="#cb9-11"></a> <span class="dt">stat =</span> StatLm, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping, <span class="dt">geom =</span> geom, </span> <span id="cb9-12"><a href="#cb9-12"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb9-13"><a href="#cb9-13"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">n =</span> n, <span class="dt">formula =</span> formula, <span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb9-14"><a href="#cb9-14"></a> )</span> <span id="cb9-15"><a href="#cb9-15"></a>}</span></code></pre></div> <p><code>stat_lm()</code> must be exported if you want other people to use it. You could also consider exporting <code>StatLm</code> if you want people to extend the underlying object; this should be done with care.</p> </div> <div id="picking-defaults" class="section level3"> <h3>Picking defaults</h3> <p>Sometimes you have calculations that should be performed once for the complete dataset, not once for each group. This is useful for picking sensible default values. For example, if we want to do a density estimate, it’s reasonable to pick one bandwidth for the whole plot. The following Stat creates a variation of the <code>stat_density()</code> that picks one bandwidth for all groups by choosing the mean of the “best” bandwidth for each group (I have no theoretical justification for this, but it doesn’t seem unreasonable).</p> <p>To do this we override the <code>setup_params()</code> method. It’s passed the data and a list of params, and returns an updated list.</p> <div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1"></a>StatDensityCommon <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatDensityCommon"</span>, Stat, </span> <span id="cb10-2"><a href="#cb10-2"></a> <span class="dt">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb10-3"><a href="#cb10-3"></a> </span> <span id="cb10-4"><a href="#cb10-4"></a> <span class="dt">setup_params =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb10-5"><a href="#cb10-5"></a> <span class="cf">if</span> (<span class="op">!</span><span class="kw">is.null</span>(params<span class="op">$</span>bandwidth))</span> <span id="cb10-6"><a href="#cb10-6"></a> <span class="kw">return</span>(params)</span> <span id="cb10-7"><a href="#cb10-7"></a> </span> <span id="cb10-8"><a href="#cb10-8"></a> xs <-<span class="st"> </span><span class="kw">split</span>(data<span class="op">$</span>x, data<span class="op">$</span>group)</span> <span id="cb10-9"><a href="#cb10-9"></a> bws <-<span class="st"> </span><span class="kw">vapply</span>(xs, bw.nrd0, <span class="kw">numeric</span>(<span class="dv">1</span>))</span> <span id="cb10-10"><a href="#cb10-10"></a> bw <-<span class="st"> </span><span class="kw">mean</span>(bws)</span> <span id="cb10-11"><a href="#cb10-11"></a> <span class="kw">message</span>(<span class="st">"Picking bandwidth of "</span>, <span class="kw">signif</span>(bw, <span class="dv">3</span>))</span> <span id="cb10-12"><a href="#cb10-12"></a> </span> <span id="cb10-13"><a href="#cb10-13"></a> params<span class="op">$</span>bandwidth <-<span class="st"> </span>bw</span> <span id="cb10-14"><a href="#cb10-14"></a> params</span> <span id="cb10-15"><a href="#cb10-15"></a> },</span> <span id="cb10-16"><a href="#cb10-16"></a> </span> <span id="cb10-17"><a href="#cb10-17"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales, <span class="dt">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb10-18"><a href="#cb10-18"></a> d <-<span class="st"> </span><span class="kw">density</span>(data<span class="op">$</span>x, <span class="dt">bw =</span> bandwidth)</span> <span id="cb10-19"><a href="#cb10-19"></a> <span class="kw">data.frame</span>(<span class="dt">x =</span> d<span class="op">$</span>x, <span class="dt">y =</span> d<span class="op">$</span>y)</span> <span id="cb10-20"><a href="#cb10-20"></a> } </span> <span id="cb10-21"><a href="#cb10-21"></a>)</span> <span id="cb10-22"><a href="#cb10-22"></a></span> <span id="cb10-23"><a href="#cb10-23"></a>stat_density_common <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">geom =</span> <span class="st">"line"</span>,</span> <span id="cb10-24"><a href="#cb10-24"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb10-25"><a href="#cb10-25"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, <span class="dt">bandwidth =</span> <span class="ot">NULL</span>,</span> <span id="cb10-26"><a href="#cb10-26"></a> ...) {</span> <span id="cb10-27"><a href="#cb10-27"></a> <span class="kw">layer</span>(</span> <span id="cb10-28"><a href="#cb10-28"></a> <span class="dt">stat =</span> StatDensityCommon, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping, <span class="dt">geom =</span> geom, </span> <span id="cb10-29"><a href="#cb10-29"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb10-30"><a href="#cb10-30"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">bandwidth =</span> bandwidth, <span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb10-31"><a href="#cb10-31"></a> )</span> <span id="cb10-32"><a href="#cb10-32"></a>}</span> <span id="cb10-33"><a href="#cb10-33"></a></span> <span id="cb10-34"><a href="#cb10-34"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, <span class="dt">colour =</span> drv)) <span class="op">+</span><span class="st"> </span></span> <span id="cb10-35"><a href="#cb10-35"></a><span class="st"> </span><span class="kw">stat_density_common</span>()</span> <span id="cb10-36"><a href="#cb10-36"></a><span class="co">#> Picking bandwidth of 0.345</span></span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1"></a></span> <span id="cb11-2"><a href="#cb11-2"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, <span class="dt">colour =</span> drv)) <span class="op">+</span><span class="st"> </span></span> <span id="cb11-3"><a href="#cb11-3"></a><span class="st"> </span><span class="kw">stat_density_common</span>(<span class="dt">bandwidth =</span> <span class="fl">0.5</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>I recommend using <code>NULL</code> as a default value. If you pick important parameters automatically, it’s a good idea to <code>message()</code> to the user (and when printing a floating point parameter, using <code>signif()</code> to show only a few significant digits).</p> </div> <div id="variable-names-and-default-aesthetics" class="section level3"> <h3>Variable names and default aesthetics</h3> <p>This stat illustrates another important point. If we want to make this stat usable with other geoms, we should return a variable called <code>density</code> instead of <code>y</code>. Then we can set up the <code>default_aes</code> to automatically map <code>density</code> to <code>y</code>, which allows the user to override it to use with different geoms:</p> <div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1"></a>StatDensityCommon <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatDensity2"</span>, Stat, </span> <span id="cb12-2"><a href="#cb12-2"></a> <span class="dt">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb12-3"><a href="#cb12-3"></a> <span class="dt">default_aes =</span> <span class="kw">aes</span>(<span class="dt">y =</span> <span class="kw">stat</span>(density)),</span> <span id="cb12-4"><a href="#cb12-4"></a></span> <span id="cb12-5"><a href="#cb12-5"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales, <span class="dt">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb12-6"><a href="#cb12-6"></a> d <-<span class="st"> </span><span class="kw">density</span>(data<span class="op">$</span>x, <span class="dt">bw =</span> bandwidth)</span> <span id="cb12-7"><a href="#cb12-7"></a> <span class="kw">data.frame</span>(<span class="dt">x =</span> d<span class="op">$</span>x, <span class="dt">density =</span> d<span class="op">$</span>y)</span> <span id="cb12-8"><a href="#cb12-8"></a> } </span> <span id="cb12-9"><a href="#cb12-9"></a>)</span> <span id="cb12-10"><a href="#cb12-10"></a></span> <span id="cb12-11"><a href="#cb12-11"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, drv, <span class="dt">colour =</span> <span class="kw">stat</span>(density))) <span class="op">+</span><span class="st"> </span></span> <span id="cb12-12"><a href="#cb12-12"></a><span class="st"> </span><span class="kw">stat_density_common</span>(<span class="dt">bandwidth =</span> <span class="dv">1</span>, <span class="dt">geom =</span> <span class="st">"point"</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>However, using this stat with the area geom doesn’t work quite right. The areas don’t stack on top of each other:</p> <div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, <span class="dt">fill =</span> drv)) <span class="op">+</span><span class="st"> </span></span> <span id="cb13-2"><a href="#cb13-2"></a><span class="st"> </span><span class="kw">stat_density_common</span>(<span class="dt">bandwidth =</span> <span class="dv">1</span>, <span class="dt">geom =</span> <span class="st">"area"</span>, <span class="dt">position =</span> <span class="st">"stack"</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>This is because each density is computed independently, and the estimated <code>x</code>s don’t line up. We can resolve that issue by computing the range of the data once in <code>setup_params()</code>.</p> <div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb14-1"><a href="#cb14-1"></a>StatDensityCommon <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"StatDensityCommon"</span>, Stat, </span> <span id="cb14-2"><a href="#cb14-2"></a> <span class="dt">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb14-3"><a href="#cb14-3"></a> <span class="dt">default_aes =</span> <span class="kw">aes</span>(<span class="dt">y =</span> <span class="kw">stat</span>(density)),</span> <span id="cb14-4"><a href="#cb14-4"></a></span> <span id="cb14-5"><a href="#cb14-5"></a> <span class="dt">setup_params =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb14-6"><a href="#cb14-6"></a> min <-<span class="st"> </span><span class="kw">min</span>(data<span class="op">$</span>x) <span class="op">-</span><span class="st"> </span><span class="dv">3</span> <span class="op">*</span><span class="st"> </span>params<span class="op">$</span>bandwidth</span> <span id="cb14-7"><a href="#cb14-7"></a> max <-<span class="st"> </span><span class="kw">max</span>(data<span class="op">$</span>x) <span class="op">+</span><span class="st"> </span><span class="dv">3</span> <span class="op">*</span><span class="st"> </span>params<span class="op">$</span>bandwidth</span> <span id="cb14-8"><a href="#cb14-8"></a> </span> <span id="cb14-9"><a href="#cb14-9"></a> <span class="kw">list</span>(</span> <span id="cb14-10"><a href="#cb14-10"></a> <span class="dt">bandwidth =</span> params<span class="op">$</span>bandwidth,</span> <span id="cb14-11"><a href="#cb14-11"></a> <span class="dt">min =</span> min,</span> <span id="cb14-12"><a href="#cb14-12"></a> <span class="dt">max =</span> max,</span> <span id="cb14-13"><a href="#cb14-13"></a> <span class="dt">na.rm =</span> params<span class="op">$</span>na.rm</span> <span id="cb14-14"><a href="#cb14-14"></a> )</span> <span id="cb14-15"><a href="#cb14-15"></a> },</span> <span id="cb14-16"><a href="#cb14-16"></a> </span> <span id="cb14-17"><a href="#cb14-17"></a> <span class="dt">compute_group =</span> <span class="cf">function</span>(data, scales, min, max, <span class="dt">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb14-18"><a href="#cb14-18"></a> d <-<span class="st"> </span><span class="kw">density</span>(data<span class="op">$</span>x, <span class="dt">bw =</span> bandwidth, <span class="dt">from =</span> min, <span class="dt">to =</span> max)</span> <span id="cb14-19"><a href="#cb14-19"></a> <span class="kw">data.frame</span>(<span class="dt">x =</span> d<span class="op">$</span>x, <span class="dt">density =</span> d<span class="op">$</span>y)</span> <span id="cb14-20"><a href="#cb14-20"></a> } </span> <span id="cb14-21"><a href="#cb14-21"></a>)</span> <span id="cb14-22"><a href="#cb14-22"></a></span> <span id="cb14-23"><a href="#cb14-23"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, <span class="dt">fill =</span> drv)) <span class="op">+</span><span class="st"> </span></span> <span id="cb14-24"><a href="#cb14-24"></a><span class="st"> </span><span class="kw">stat_density_common</span>(<span class="dt">bandwidth =</span> <span class="dv">1</span>, <span class="dt">geom =</span> <span class="st">"area"</span>, <span class="dt">position =</span> <span class="st">"stack"</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, drv, <span class="dt">fill =</span> <span class="kw">stat</span>(density))) <span class="op">+</span><span class="st"> </span></span> <span id="cb15-2"><a href="#cb15-2"></a><span class="st"> </span><span class="kw">stat_density_common</span>(<span class="dt">bandwidth =</span> <span class="dv">1</span>, <span class="dt">geom =</span> <span class="st">"raster"</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> </div> <div id="exercises" class="section level3"> <h3>Exercises</h3> <ol style="list-style-type: decimal"> <li><p>Extend <code>stat_chull</code> to compute the alpha hull, as from the <a href="https://cran.r-project.org/package=alphahull">alphahull</a> package. Your new stat should take an <code>alpha</code> argument.</p></li> <li><p>Modify the final version of <code>StatDensityCommon</code> to allow the user to specify the <code>min</code> and <code>max</code> parameters. You’ll need to modify both the layer function and the <code>compute_group()</code> method.</p> <p>Note: be careful when adding parameters to a layer function. The following names <em>col</em>, <em>color</em>, <em>pch</em>, <em>cex</em>, <em>lty</em>, <em>lwd</em>, <em>srt</em>, <em>adj</em>, <em>bg</em>, <em>fg</em>, <em>min</em>, and <em>max</em> are intentionally renamed to accomodate base graphical parameter names. For example, a value passed as <em>min</em> to a layer appears as <em>ymin</em> in the <code>setup_params</code> list of params. It is recommended you avoid using these names for layer parameters.</p></li> <li><p>Compare and contrast <code>StatLm</code> to <code>ggplot2::StatSmooth</code>. What key differences make <code>StatSmooth</code> more complex than <code>StatLm</code>?</p></li> </ol> </div> </div> <div id="creating-a-new-geom" class="section level2"> <h2>Creating a new geom</h2> <p>It’s harder to create a new geom than a new stat because you also need to know some grid. ggplot2 is built on top of grid, so you’ll need to know the basics of drawing with grid. If you’re serious about adding a new geom, I’d recommend buying <a href="http://amzn.com/B00I60M26G">R graphics</a> by Paul Murrell. It tells you everything you need to know about drawing with grid.</p> <div id="a-simple-geom" class="section level3"> <h3>A simple geom</h3> <p>It’s easiest to start with a simple example. The code below is a simplified version of <code>geom_point()</code>:</p> <div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb16-1"><a href="#cb16-1"></a>GeomSimplePoint <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"GeomSimplePoint"</span>, Geom,</span> <span id="cb16-2"><a href="#cb16-2"></a> <span class="dt">required_aes =</span> <span class="kw">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb16-3"><a href="#cb16-3"></a> <span class="dt">default_aes =</span> <span class="kw">aes</span>(<span class="dt">shape =</span> <span class="dv">19</span>, <span class="dt">colour =</span> <span class="st">"black"</span>),</span> <span id="cb16-4"><a href="#cb16-4"></a> <span class="dt">draw_key =</span> draw_key_point,</span> <span id="cb16-5"><a href="#cb16-5"></a></span> <span id="cb16-6"><a href="#cb16-6"></a> <span class="dt">draw_panel =</span> <span class="cf">function</span>(data, panel_params, coord) {</span> <span id="cb16-7"><a href="#cb16-7"></a> coords <-<span class="st"> </span>coord<span class="op">$</span><span class="kw">transform</span>(data, panel_params)</span> <span id="cb16-8"><a href="#cb16-8"></a> grid<span class="op">::</span><span class="kw">pointsGrob</span>(</span> <span id="cb16-9"><a href="#cb16-9"></a> coords<span class="op">$</span>x, coords<span class="op">$</span>y,</span> <span id="cb16-10"><a href="#cb16-10"></a> <span class="dt">pch =</span> coords<span class="op">$</span>shape,</span> <span id="cb16-11"><a href="#cb16-11"></a> <span class="dt">gp =</span> grid<span class="op">::</span><span class="kw">gpar</span>(<span class="dt">col =</span> coords<span class="op">$</span>colour)</span> <span id="cb16-12"><a href="#cb16-12"></a> )</span> <span id="cb16-13"><a href="#cb16-13"></a> }</span> <span id="cb16-14"><a href="#cb16-14"></a>)</span> <span id="cb16-15"><a href="#cb16-15"></a></span> <span id="cb16-16"><a href="#cb16-16"></a>geom_simple_point <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">stat =</span> <span class="st">"identity"</span>,</span> <span id="cb16-17"><a href="#cb16-17"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb16-18"><a href="#cb16-18"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, ...) {</span> <span id="cb16-19"><a href="#cb16-19"></a> <span class="kw">layer</span>(</span> <span id="cb16-20"><a href="#cb16-20"></a> <span class="dt">geom =</span> GeomSimplePoint, <span class="dt">mapping =</span> mapping, <span class="dt">data =</span> data, <span class="dt">stat =</span> stat, </span> <span id="cb16-21"><a href="#cb16-21"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb16-22"><a href="#cb16-22"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb16-23"><a href="#cb16-23"></a> )</span> <span id="cb16-24"><a href="#cb16-24"></a>}</span> <span id="cb16-25"><a href="#cb16-25"></a></span> <span id="cb16-26"><a href="#cb16-26"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb16-27"><a href="#cb16-27"></a><span class="st"> </span><span class="kw">geom_simple_point</span>()</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>This is very similar to defining a new stat. You always need to provide fields/methods for the four pieces shown above:</p> <ul> <li><p><code>required_aes</code> is a character vector which lists all the aesthetics that the user must provide.</p></li> <li><p><code>default_aes</code> lists the aesthetics that have default values.</p></li> <li><p><code>draw_key</code> provides the function used to draw the key in the legend. You can see a list of all the build in key functions in <code>?draw_key</code></p></li> <li><p><code>draw_panel()</code> is where the magic happens. This function takes three arguments and returns a grid grob. It is called once for each panel. It’s the most complicated part and is described in more detail below.</p></li> </ul> <p><code>draw_panel()</code> has three arguments:</p> <ul> <li><p><code>data</code>: a data frame with one column for each aesthetic.</p></li> <li><p><code>panel_params</code>: a list of per-panel parameters generated by the coord. You should consider this an opaque data structure: don’t look inside it, just pass along to <code>coord</code> methods.</p></li> <li><p><code>coord</code>: an object describing the coordinate system.</p></li> </ul> <p>You need to use <code>panel_params</code> and <code>coord</code> together to transform the data <code>coords <- coord$transform(data, panel_params)</code>. This creates a data frame where position variables are scaled to the range 0–1. You then take this data and call a grid grob function. (Transforming for non-Cartesian coordinate systems is quite complex - you’re best off transforming your data to the form accepted by an existing ggplot2 geom and passing it.)</p> </div> <div id="collective-geoms" class="section level3"> <h3>Collective geoms</h3> <p>Overriding <code>draw_panel()</code> is most appropriate if there is one graphic element per row. In other cases, you want graphic element per group. For example, take polygons: each row gives one vertex of a polygon. In this case, you should instead override <code>draw_group()</code>.</p> <p>The following code makes a simplified version of <code>GeomPolygon</code>:</p> <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1"></a>GeomSimplePolygon <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"GeomPolygon"</span>, Geom,</span> <span id="cb17-2"><a href="#cb17-2"></a> <span class="dt">required_aes =</span> <span class="kw">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb17-3"><a href="#cb17-3"></a> </span> <span id="cb17-4"><a href="#cb17-4"></a> <span class="dt">default_aes =</span> <span class="kw">aes</span>(</span> <span id="cb17-5"><a href="#cb17-5"></a> <span class="dt">colour =</span> <span class="ot">NA</span>, <span class="dt">fill =</span> <span class="st">"grey20"</span>, <span class="dt">size =</span> <span class="fl">0.5</span>,</span> <span id="cb17-6"><a href="#cb17-6"></a> <span class="dt">linetype =</span> <span class="dv">1</span>, <span class="dt">alpha =</span> <span class="dv">1</span></span> <span id="cb17-7"><a href="#cb17-7"></a> ),</span> <span id="cb17-8"><a href="#cb17-8"></a></span> <span id="cb17-9"><a href="#cb17-9"></a> <span class="dt">draw_key =</span> draw_key_polygon,</span> <span id="cb17-10"><a href="#cb17-10"></a></span> <span id="cb17-11"><a href="#cb17-11"></a> <span class="dt">draw_group =</span> <span class="cf">function</span>(data, panel_params, coord) {</span> <span id="cb17-12"><a href="#cb17-12"></a> n <-<span class="st"> </span><span class="kw">nrow</span>(data)</span> <span id="cb17-13"><a href="#cb17-13"></a> <span class="cf">if</span> (n <span class="op"><=</span><span class="st"> </span><span class="dv">2</span>) <span class="kw">return</span>(grid<span class="op">::</span><span class="kw">nullGrob</span>())</span> <span id="cb17-14"><a href="#cb17-14"></a></span> <span id="cb17-15"><a href="#cb17-15"></a> coords <-<span class="st"> </span>coord<span class="op">$</span><span class="kw">transform</span>(data, panel_params)</span> <span id="cb17-16"><a href="#cb17-16"></a> <span class="co"># A polygon can only have a single colour, fill, etc, so take from first row</span></span> <span id="cb17-17"><a href="#cb17-17"></a> first_row <-<span class="st"> </span>coords[<span class="dv">1</span>, , drop =<span class="st"> </span><span class="ot">FALSE</span>]</span> <span id="cb17-18"><a href="#cb17-18"></a></span> <span id="cb17-19"><a href="#cb17-19"></a> grid<span class="op">::</span><span class="kw">polygonGrob</span>(</span> <span id="cb17-20"><a href="#cb17-20"></a> coords<span class="op">$</span>x, coords<span class="op">$</span>y, </span> <span id="cb17-21"><a href="#cb17-21"></a> <span class="dt">default.units =</span> <span class="st">"native"</span>,</span> <span id="cb17-22"><a href="#cb17-22"></a> <span class="dt">gp =</span> grid<span class="op">::</span><span class="kw">gpar</span>(</span> <span id="cb17-23"><a href="#cb17-23"></a> <span class="dt">col =</span> first_row<span class="op">$</span>colour,</span> <span id="cb17-24"><a href="#cb17-24"></a> <span class="dt">fill =</span> scales<span class="op">::</span><span class="kw">alpha</span>(first_row<span class="op">$</span>fill, first_row<span class="op">$</span>alpha),</span> <span id="cb17-25"><a href="#cb17-25"></a> <span class="dt">lwd =</span> first_row<span class="op">$</span>size <span class="op">*</span><span class="st"> </span>.pt,</span> <span id="cb17-26"><a href="#cb17-26"></a> <span class="dt">lty =</span> first_row<span class="op">$</span>linetype</span> <span id="cb17-27"><a href="#cb17-27"></a> )</span> <span id="cb17-28"><a href="#cb17-28"></a> )</span> <span id="cb17-29"><a href="#cb17-29"></a> }</span> <span id="cb17-30"><a href="#cb17-30"></a>)</span> <span id="cb17-31"><a href="#cb17-31"></a>geom_simple_polygon <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, <span class="dt">stat =</span> <span class="st">"chull"</span>,</span> <span id="cb17-32"><a href="#cb17-32"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb17-33"><a href="#cb17-33"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, ...) {</span> <span id="cb17-34"><a href="#cb17-34"></a> <span class="kw">layer</span>(</span> <span id="cb17-35"><a href="#cb17-35"></a> <span class="dt">geom =</span> GeomSimplePolygon, <span class="dt">mapping =</span> mapping, <span class="dt">data =</span> data, <span class="dt">stat =</span> stat, </span> <span id="cb17-36"><a href="#cb17-36"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb17-37"><a href="#cb17-37"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb17-38"><a href="#cb17-38"></a> )</span> <span id="cb17-39"><a href="#cb17-39"></a>}</span> <span id="cb17-40"><a href="#cb17-40"></a></span> <span id="cb17-41"><a href="#cb17-41"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb17-42"><a href="#cb17-42"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb17-43"><a href="#cb17-43"></a><span class="st"> </span><span class="kw">geom_simple_polygon</span>(<span class="kw">aes</span>(<span class="dt">colour =</span> class), <span class="dt">fill =</span> <span class="ot">NA</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>There are a few things to note here:</p> <ul> <li><p>We override <code>draw_group()</code> instead of <code>draw_panel()</code> because we want one polygon per group, not one polygon per row.</p></li> <li><p>If the data contains two or fewer points, there’s no point trying to draw a polygon, so we return a <code>nullGrob()</code>. This is the graphical equivalent of <code>NULL</code>: it’s a grob that doesn’t draw anything and doesn’t take up any space.</p></li> <li><p>Note the units: <code>x</code> and <code>y</code> should always be drawn in “native” units. (The default units for <code>pointGrob()</code> is a native, so we didn’t need to change it there). <code>lwd</code> is measured in points, but ggplot2 uses mm, so we need to multiply it by the adjustment factor <code>.pt</code>.</p></li> </ul> <p>You might want to compare this to the real <code>GeomPolygon</code>. You’ll see it overrides <code>draw_panel()</code> because it uses some tricks to make <code>polygonGrob()</code> produce multiple polygons in one call. This is considerably more complicated, but gives better performance.</p> </div> <div id="inheriting-from-an-existing-geom" class="section level3"> <h3>Inheriting from an existing Geom</h3> <p>Sometimes you just want to make a small modification to an existing geom. In this case, rather than inheriting from <code>Geom</code> you can inherit from an existing subclass. For example, we might want to change the defaults for <code>GeomPolygon</code> to work better with <code>StatChull</code>:</p> <div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1"></a>GeomPolygonHollow <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"GeomPolygonHollow"</span>, GeomPolygon,</span> <span id="cb18-2"><a href="#cb18-2"></a> <span class="dt">default_aes =</span> <span class="kw">aes</span>(<span class="dt">colour =</span> <span class="st">"black"</span>, <span class="dt">fill =</span> <span class="ot">NA</span>, <span class="dt">size =</span> <span class="fl">0.5</span>, <span class="dt">linetype =</span> <span class="dv">1</span>,</span> <span id="cb18-3"><a href="#cb18-3"></a> <span class="dt">alpha =</span> <span class="ot">NA</span>)</span> <span id="cb18-4"><a href="#cb18-4"></a> )</span> <span id="cb18-5"><a href="#cb18-5"></a>geom_chull <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">mapping =</span> <span class="ot">NULL</span>, <span class="dt">data =</span> <span class="ot">NULL</span>, </span> <span id="cb18-6"><a href="#cb18-6"></a> <span class="dt">position =</span> <span class="st">"identity"</span>, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>, <span class="dt">show.legend =</span> <span class="ot">NA</span>, </span> <span id="cb18-7"><a href="#cb18-7"></a> <span class="dt">inherit.aes =</span> <span class="ot">TRUE</span>, ...) {</span> <span id="cb18-8"><a href="#cb18-8"></a> <span class="kw">layer</span>(</span> <span id="cb18-9"><a href="#cb18-9"></a> <span class="dt">stat =</span> StatChull, <span class="dt">geom =</span> GeomPolygonHollow, <span class="dt">data =</span> data, <span class="dt">mapping =</span> mapping,</span> <span id="cb18-10"><a href="#cb18-10"></a> <span class="dt">position =</span> position, <span class="dt">show.legend =</span> show.legend, <span class="dt">inherit.aes =</span> inherit.aes,</span> <span id="cb18-11"><a href="#cb18-11"></a> <span class="dt">params =</span> <span class="kw">list</span>(<span class="dt">na.rm =</span> na.rm, ...)</span> <span id="cb18-12"><a href="#cb18-12"></a> )</span> <span id="cb18-13"><a href="#cb18-13"></a>}</span> <span id="cb18-14"><a href="#cb18-14"></a></span> <span id="cb18-15"><a href="#cb18-15"></a><span class="kw">ggplot</span>(mpg, <span class="kw">aes</span>(displ, hwy)) <span class="op">+</span><span class="st"> </span></span> <span id="cb18-16"><a href="#cb18-16"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb18-17"><a href="#cb18-17"></a><span class="st"> </span><span class="kw">geom_chull</span>()</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>This doesn’t allow you to use different geoms with the stat, but that seems appropriate here since the convex hull is primarily a polygonal feature.</p> </div> <div id="exercises-1" class="section level3"> <h3>Exercises</h3> <ol style="list-style-type: decimal"> <li><p>Compare and contrast <code>GeomPoint</code> with <code>GeomSimplePoint</code>.</p></li> <li><p>Compare and contrast <code>GeomPolygon</code> with <code>GeomSimplePolygon</code>.</p></li> </ol> </div> </div> <div id="geoms-and-stats-with-multiple-orientation" class="section level2"> <h2>Geoms and Stats with multiple orientation</h2> <p>Some layers have a specific orientation. <code>geom_bar()</code> e.g. have the bars along one axis, <code>geom_line()</code> will sort the input by one axis, etc. The original approach to using these geoms in the other orientation was to add <code>coord_flip()</code> to the plot to switch the position of the x and y axes. Following ggplot2 v3.3 all the geoms will natively work in both orientations without <code>coord_flip()</code>. The mechanism is that the layer will try to guess the orientation from the mapped data, or take direction from the user using the <code>orientation</code> parameter. To replicate this functionality in new stats and geoms there’s a few steps to take. We wll look at the boxplot layer as an example instead of creating a new from scratch.</p> <div id="omnidirectional-stats" class="section level3"> <h3>Omnidirectional stats</h3> <p>The actual guessing of orientation will happen in <code>setup_params()</code> using the <code>has_flipped_aes()</code> helper:</p> <div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb19-1"><a href="#cb19-1"></a>StatBoxplot<span class="op">$</span>setup_params</span> <span id="cb19-2"><a href="#cb19-2"></a><span class="co">#> <ggproto method></span></span> <span id="cb19-3"><a href="#cb19-3"></a><span class="co">#> <Wrapper function></span></span> <span id="cb19-4"><a href="#cb19-4"></a><span class="co">#> function (...) </span></span> <span id="cb19-5"><a href="#cb19-5"></a><span class="co">#> f(...)</span></span> <span id="cb19-6"><a href="#cb19-6"></a><span class="co">#> </span></span> <span id="cb19-7"><a href="#cb19-7"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb19-8"><a href="#cb19-8"></a><span class="co">#> function (data, params) </span></span> <span id="cb19-9"><a href="#cb19-9"></a><span class="co">#> {</span></span> <span id="cb19-10"><a href="#cb19-10"></a><span class="co">#> params$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = TRUE, </span></span> <span id="cb19-11"><a href="#cb19-11"></a><span class="co">#> group_has_equal = TRUE, main_is_optional = TRUE)</span></span> <span id="cb19-12"><a href="#cb19-12"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb19-13"><a href="#cb19-13"></a><span class="co">#> has_x <- !(is.null(data$x) && is.null(params$x))</span></span> <span id="cb19-14"><a href="#cb19-14"></a><span class="co">#> has_y <- !(is.null(data$y) && is.null(params$y))</span></span> <span id="cb19-15"><a href="#cb19-15"></a><span class="co">#> if (!has_x && !has_y) {</span></span> <span id="cb19-16"><a href="#cb19-16"></a><span class="co">#> abort("stat_boxplot() requires an x or y aesthetic.")</span></span> <span id="cb19-17"><a href="#cb19-17"></a><span class="co">#> }</span></span> <span id="cb19-18"><a href="#cb19-18"></a><span class="co">#> params$width <- params$width %||% (resolution(data$x %||% </span></span> <span id="cb19-19"><a href="#cb19-19"></a><span class="co">#> 0) * 0.75)</span></span> <span id="cb19-20"><a href="#cb19-20"></a><span class="co">#> if (is.double(data$x) && !has_groups(data) && any(data$x != </span></span> <span id="cb19-21"><a href="#cb19-21"></a><span class="co">#> data$x[1L])) {</span></span> <span id="cb19-22"><a href="#cb19-22"></a><span class="co">#> warn(glue("Continuous {flipped_names(params$flipped_aes)$x} aesthetic -- did you forget aes(group=...)?"))</span></span> <span id="cb19-23"><a href="#cb19-23"></a><span class="co">#> }</span></span> <span id="cb19-24"><a href="#cb19-24"></a><span class="co">#> params</span></span> <span id="cb19-25"><a href="#cb19-25"></a><span class="co">#> }</span></span></code></pre></div> <p>Following this is a call to <code>flip_data()</code> which will make sure the data is in horizontal orientation. The rest of the code can then simply assume that the data is in a specific orientation. The same thing happens in <code>setup_data()</code>:</p> <div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1"></a>StatBoxplot<span class="op">$</span>setup_data</span> <span id="cb20-2"><a href="#cb20-2"></a><span class="co">#> <ggproto method></span></span> <span id="cb20-3"><a href="#cb20-3"></a><span class="co">#> <Wrapper function></span></span> <span id="cb20-4"><a href="#cb20-4"></a><span class="co">#> function (...) </span></span> <span id="cb20-5"><a href="#cb20-5"></a><span class="co">#> f(...)</span></span> <span id="cb20-6"><a href="#cb20-6"></a><span class="co">#> </span></span> <span id="cb20-7"><a href="#cb20-7"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb20-8"><a href="#cb20-8"></a><span class="co">#> function (data, params) </span></span> <span id="cb20-9"><a href="#cb20-9"></a><span class="co">#> {</span></span> <span id="cb20-10"><a href="#cb20-10"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb20-11"><a href="#cb20-11"></a><span class="co">#> data$x <- data$x %||% 0</span></span> <span id="cb20-12"><a href="#cb20-12"></a><span class="co">#> data <- remove_missing(data, na.rm = params$na.rm, vars = "x", </span></span> <span id="cb20-13"><a href="#cb20-13"></a><span class="co">#> name = "stat_boxplot")</span></span> <span id="cb20-14"><a href="#cb20-14"></a><span class="co">#> flip_data(data, params$flipped_aes)</span></span> <span id="cb20-15"><a href="#cb20-15"></a><span class="co">#> }</span></span></code></pre></div> <p>The data is flipped (if needed), manipulated, and flipped back as it is returned.</p> <p>During the computation, this sandwiching between <code>flip_data()</code> is used as well, but right before the data is returned it will also get a <code>flipped_aes</code> column denoting if the data is flipped or not. This allow the stat to communicate to the geom that orientation has already been determined.</p> </div> <div id="omnidirecitonal-geoms" class="section level3"> <h3>Omnidirecitonal geoms</h3> <p>The setup for geoms is pretty much the same, with a few twists. <code>has_flipped_aes()</code> is also used in <code>setup_params()</code>, where it will usually be picked up from the <code>flipped_aes</code> column given by the stat. In <code>setup_data()</code> you will often see that <code>flipped_aes</code> is reassigned, to make sure it exist prior to position adjustment. This is needed if the geom is used together with a stat that doesn’t handle orientation (often <code>stat_identity()</code>):</p> <div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb21-1"><a href="#cb21-1"></a>GeomBoxplot<span class="op">$</span>setup_data</span> <span id="cb21-2"><a href="#cb21-2"></a><span class="co">#> <ggproto method></span></span> <span id="cb21-3"><a href="#cb21-3"></a><span class="co">#> <Wrapper function></span></span> <span id="cb21-4"><a href="#cb21-4"></a><span class="co">#> function (...) </span></span> <span id="cb21-5"><a href="#cb21-5"></a><span class="co">#> f(...)</span></span> <span id="cb21-6"><a href="#cb21-6"></a><span class="co">#> </span></span> <span id="cb21-7"><a href="#cb21-7"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb21-8"><a href="#cb21-8"></a><span class="co">#> function (data, params) </span></span> <span id="cb21-9"><a href="#cb21-9"></a><span class="co">#> {</span></span> <span id="cb21-10"><a href="#cb21-10"></a><span class="co">#> data$flipped_aes <- params$flipped_aes</span></span> <span id="cb21-11"><a href="#cb21-11"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb21-12"><a href="#cb21-12"></a><span class="co">#> data$width <- data$width %||% params$width %||% (resolution(data$x, </span></span> <span id="cb21-13"><a href="#cb21-13"></a><span class="co">#> FALSE) * 0.9)</span></span> <span id="cb21-14"><a href="#cb21-14"></a><span class="co">#> if (!is.null(data$outliers)) {</span></span> <span id="cb21-15"><a href="#cb21-15"></a><span class="co">#> suppressWarnings({</span></span> <span id="cb21-16"><a href="#cb21-16"></a><span class="co">#> out_min <- vapply(data$outliers, min, numeric(1))</span></span> <span id="cb21-17"><a href="#cb21-17"></a><span class="co">#> out_max <- vapply(data$outliers, max, numeric(1))</span></span> <span id="cb21-18"><a href="#cb21-18"></a><span class="co">#> })</span></span> <span id="cb21-19"><a href="#cb21-19"></a><span class="co">#> data$ymin_final <- pmin(out_min, data$ymin)</span></span> <span id="cb21-20"><a href="#cb21-20"></a><span class="co">#> data$ymax_final <- pmax(out_max, data$ymax)</span></span> <span id="cb21-21"><a href="#cb21-21"></a><span class="co">#> }</span></span> <span id="cb21-22"><a href="#cb21-22"></a><span class="co">#> if (is.null(params) || is.null(params$varwidth) || !params$varwidth || </span></span> <span id="cb21-23"><a href="#cb21-23"></a><span class="co">#> is.null(data$relvarwidth)) {</span></span> <span id="cb21-24"><a href="#cb21-24"></a><span class="co">#> data$xmin <- data$x - data$width/2</span></span> <span id="cb21-25"><a href="#cb21-25"></a><span class="co">#> data$xmax <- data$x + data$width/2</span></span> <span id="cb21-26"><a href="#cb21-26"></a><span class="co">#> }</span></span> <span id="cb21-27"><a href="#cb21-27"></a><span class="co">#> else {</span></span> <span id="cb21-28"><a href="#cb21-28"></a><span class="co">#> data$relvarwidth <- data$relvarwidth/max(data$relvarwidth)</span></span> <span id="cb21-29"><a href="#cb21-29"></a><span class="co">#> data$xmin <- data$x - data$relvarwidth * data$width/2</span></span> <span id="cb21-30"><a href="#cb21-30"></a><span class="co">#> data$xmax <- data$x + data$relvarwidth * data$width/2</span></span> <span id="cb21-31"><a href="#cb21-31"></a><span class="co">#> }</span></span> <span id="cb21-32"><a href="#cb21-32"></a><span class="co">#> data$width <- NULL</span></span> <span id="cb21-33"><a href="#cb21-33"></a><span class="co">#> if (!is.null(data$relvarwidth)) </span></span> <span id="cb21-34"><a href="#cb21-34"></a><span class="co">#> data$relvarwidth <- NULL</span></span> <span id="cb21-35"><a href="#cb21-35"></a><span class="co">#> flip_data(data, params$flipped_aes)</span></span> <span id="cb21-36"><a href="#cb21-36"></a><span class="co">#> }</span></span></code></pre></div> <p>In the <code>draw_*()</code> method you will once again sandwich any data manipulation between <code>flip_data()</code> calls. It is important to make sure that the data is flipped back prior to creating the grob or calling draw methods from other geoms.</p> </div> <div id="dealing-with-required-aesthetics" class="section level3"> <h3>Dealing with required aesthetics</h3> <p>Omnidirectional layers usually have two different sets of required aesthetics. Which set is used is often how it knows the orientation. To handle this gracefully the <code>required_aes</code> field of <code>Stat</code> and <code>Geom</code> classes understands the <code>|</code> (or) operator. Looking at <code>GeomBoxplot</code> we can see how it is used:</p> <div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb22-1"><a href="#cb22-1"></a>GeomBoxplot<span class="op">$</span>required_aes</span> <span id="cb22-2"><a href="#cb22-2"></a><span class="co">#> [1] "x|y" "lower|xlower" "upper|xupper" "middle|xmiddle"</span></span> <span id="cb22-3"><a href="#cb22-3"></a><span class="co">#> [5] "ymin|xmin" "ymax|xmax"</span></span></code></pre></div> <p>This tells ggplot2 that either all the aesthetics before <code>|</code> are required or all the aesthetics after are required.</p> </div> <div id="ambiguous-layers" class="section level3"> <h3>Ambiguous layers</h3> <p>Some layers will not have a clear interpretation of their data in terms of orientation. A classic example is <code>geom_line()</code> which just by convention runs along the x-axis. There is nothing in the data itself that indicates that. For these geoms the user must indicate a flipped orientation by setting <code>orientation = "y"</code>. The stat or geom will then call <code>has_flipped_aes()</code> with <code>ambiguous = TRUE</code> to cancel any guessing based on data format. As an example we can see the <code>setup_params()</code> method of <code>GeomLine</code>:</p> <div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb23-1"><a href="#cb23-1"></a>GeomLine<span class="op">$</span>setup_params</span> <span id="cb23-2"><a href="#cb23-2"></a><span class="co">#> <ggproto method></span></span> <span id="cb23-3"><a href="#cb23-3"></a><span class="co">#> <Wrapper function></span></span> <span id="cb23-4"><a href="#cb23-4"></a><span class="co">#> function (...) </span></span> <span id="cb23-5"><a href="#cb23-5"></a><span class="co">#> f(...)</span></span> <span id="cb23-6"><a href="#cb23-6"></a><span class="co">#> </span></span> <span id="cb23-7"><a href="#cb23-7"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb23-8"><a href="#cb23-8"></a><span class="co">#> function (data, params) </span></span> <span id="cb23-9"><a href="#cb23-9"></a><span class="co">#> {</span></span> <span id="cb23-10"><a href="#cb23-10"></a><span class="co">#> params$flipped_aes <- has_flipped_aes(data, params, ambiguous = TRUE)</span></span> <span id="cb23-11"><a href="#cb23-11"></a><span class="co">#> params</span></span> <span id="cb23-12"><a href="#cb23-12"></a><span class="co">#> }</span></span></code></pre></div> </div> </div> <div id="creating-your-own-theme" class="section level2"> <h2>Creating your own theme</h2> <p>If you’re going to create your own complete theme, there are a few things you need to know:</p> <ul> <li>Overriding existing elements, rather than modifying them</li> <li>The four global elements that affect (almost) every other theme element</li> <li>Complete vs. incomplete elements</li> </ul> <div id="overriding-elements" class="section level3"> <h3>Overriding elements</h3> <p>By default, when you add a new theme element, it inherits values from the existing theme. For example, the following code sets the key colour to red, but it inherits the existing fill colour:</p> <div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1"></a><span class="kw">theme_grey</span>()<span class="op">$</span>legend.key</span> <span id="cb24-2"><a href="#cb24-2"></a><span class="co">#> List of 5</span></span> <span id="cb24-3"><a href="#cb24-3"></a><span class="co">#> $ fill : chr "grey95"</span></span> <span id="cb24-4"><a href="#cb24-4"></a><span class="co">#> $ colour : logi NA</span></span> <span id="cb24-5"><a href="#cb24-5"></a><span class="co">#> $ size : NULL</span></span> <span id="cb24-6"><a href="#cb24-6"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb24-7"><a href="#cb24-7"></a><span class="co">#> $ inherit.blank: logi TRUE</span></span> <span id="cb24-8"><a href="#cb24-8"></a><span class="co">#> - attr(*, "class")= chr [1:2] "element_rect" "element"</span></span> <span id="cb24-9"><a href="#cb24-9"></a></span> <span id="cb24-10"><a href="#cb24-10"></a>new_theme <-<span class="st"> </span><span class="kw">theme_grey</span>() <span class="op">+</span><span class="st"> </span><span class="kw">theme</span>(<span class="dt">legend.key =</span> <span class="kw">element_rect</span>(<span class="dt">colour =</span> <span class="st">"red"</span>))</span> <span id="cb24-11"><a href="#cb24-11"></a>new_theme<span class="op">$</span>legend.key</span> <span id="cb24-12"><a href="#cb24-12"></a><span class="co">#> List of 5</span></span> <span id="cb24-13"><a href="#cb24-13"></a><span class="co">#> $ fill : chr "grey95"</span></span> <span id="cb24-14"><a href="#cb24-14"></a><span class="co">#> $ colour : chr "red"</span></span> <span id="cb24-15"><a href="#cb24-15"></a><span class="co">#> $ size : NULL</span></span> <span id="cb24-16"><a href="#cb24-16"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb24-17"><a href="#cb24-17"></a><span class="co">#> $ inherit.blank: logi FALSE</span></span> <span id="cb24-18"><a href="#cb24-18"></a><span class="co">#> - attr(*, "class")= chr [1:2] "element_rect" "element"</span></span></code></pre></div> <p>To override it completely, use <code>%+replace%</code> instead of <code>+</code>:</p> <div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb25-1"><a href="#cb25-1"></a>new_theme <-<span class="st"> </span><span class="kw">theme_grey</span>() <span class="op">%+replace%</span><span class="st"> </span><span class="kw">theme</span>(<span class="dt">legend.key =</span> <span class="kw">element_rect</span>(<span class="dt">colour =</span> <span class="st">"red"</span>))</span> <span id="cb25-2"><a href="#cb25-2"></a>new_theme<span class="op">$</span>legend.key</span> <span id="cb25-3"><a href="#cb25-3"></a><span class="co">#> List of 5</span></span> <span id="cb25-4"><a href="#cb25-4"></a><span class="co">#> $ fill : NULL</span></span> <span id="cb25-5"><a href="#cb25-5"></a><span class="co">#> $ colour : chr "red"</span></span> <span id="cb25-6"><a href="#cb25-6"></a><span class="co">#> $ size : NULL</span></span> <span id="cb25-7"><a href="#cb25-7"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb25-8"><a href="#cb25-8"></a><span class="co">#> $ inherit.blank: logi FALSE</span></span> <span id="cb25-9"><a href="#cb25-9"></a><span class="co">#> - attr(*, "class")= chr [1:2] "element_rect" "element"</span></span></code></pre></div> </div> <div id="global-elements" class="section level3"> <h3>Global elements</h3> <p>There are four elements that affect the global appearance of the plot:</p> <table> <thead> <tr class="header"> <th>Element</th> <th>Theme function</th> <th>Description</th> </tr> </thead> <tbody> <tr class="odd"> <td>line</td> <td><code>element_line()</code></td> <td>all line elements</td> </tr> <tr class="even"> <td>rect</td> <td><code>element_rect()</code></td> <td>all rectangular elements</td> </tr> <tr class="odd"> <td>text</td> <td><code>element_text()</code></td> <td>all text</td> </tr> <tr class="even"> <td>title</td> <td><code>element_text()</code></td> <td>all text in title elements (plot, axes & legend)</td> </tr> </tbody> </table> <p>These set default properties that are inherited by more specific settings. These are most useful for setting an overall “background” colour and overall font settings (e.g. family and size).</p> <div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb26-1"><a href="#cb26-1"></a>df <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">x =</span> <span class="dv">1</span><span class="op">:</span><span class="dv">3</span>, <span class="dt">y =</span> <span class="dv">1</span><span class="op">:</span><span class="dv">3</span>)</span> <span id="cb26-2"><a href="#cb26-2"></a>base <-<span class="st"> </span><span class="kw">ggplot</span>(df, <span class="kw">aes</span>(x, y)) <span class="op">+</span><span class="st"> </span></span> <span id="cb26-3"><a href="#cb26-3"></a><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span></span> <span id="cb26-4"><a href="#cb26-4"></a><span class="st"> </span><span class="kw">theme_minimal</span>()</span> <span id="cb26-5"><a href="#cb26-5"></a></span> <span id="cb26-6"><a href="#cb26-6"></a>base</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb27-1"><a href="#cb27-1"></a>base <span class="op">+</span><span class="st"> </span><span class="kw">theme</span>(<span class="dt">text =</span> <span class="kw">element_text</span>(<span class="dt">colour =</span> <span class="st">"red"</span>))</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>You should generally start creating a theme by modifying these values.</p> </div> <div id="complete-vs-incomplete" class="section level3"> <h3>Complete vs incomplete</h3> <p>It is useful to understand the difference between complete and incomplete theme objects. A <em>complete</em> theme object is one produced by calling a theme function with the attribute <code>complete = TRUE</code>.</p> <p>Theme functions <code>theme_grey()</code> and <code>theme_bw()</code> are examples of complete theme functions. Calls to <code>theme()</code> produce <em>incomplete</em> theme objects, since they represent (local) modifications to a theme object rather than returning a complete theme object per se. When adding an incomplete theme to a complete one, the result is a complete theme.</p> <p>Complete and incomplete themes behave somewhat differently when added to a ggplot object:</p> <ul> <li><p>Adding an incomplete theme augments the current theme object, replacing only those properties of elements defined in the call to <code>theme()</code>.</p></li> <li><p>Adding a complete theme wipes away the existing theme and applies the new theme.</p></li> </ul> </div> </div> <div id="creating-a-new-faceting" class="section level2"> <h2>Creating a new faceting</h2> <p>One of the more daunting exercises in ggplot2 extensions is to create a new faceting system. The reason for this is that when creating new facetings you take on the responsibility of how (almost) everything is drawn on the screen, and many do not have experience with directly using <a href="https://cran.r-project.org/package=gtable">gtable</a> and <a href="https://cran.r-project.org/package=grid">grid</a> upon which the ggplot2 rendering is built. If you decide to venture into faceting extensions, it is highly recommended to gain proficiency with the above-mentioned packages.</p> <p>The <code>Facet</code> class in ggplot2 is very powerful as it takes on responsibility of a wide range of tasks. The main tasks of a <code>Facet</code> object are:</p> <ul> <li><p>Define a layout; that is, a partitioning of the data into different plot areas (panels) as well as which panels share position scales.</p></li> <li><p>Map plot data into the correct panels, potentially duplicating data if it should exist in multiple panels (e.g. margins in <code>facet_grid()</code>).</p></li> <li><p>Assemble all panels into a final gtable, adding axes, strips and decorations in the process.</p></li> </ul> <p>Apart from these three tasks, for which functionality must be implemented, there are a couple of additional extension points where sensible defaults have been provided. These can generally be ignored, but adventurous developers can override them for even more control:</p> <ul> <li><p>Initialization and training of positional scales for each panel.</p></li> <li><p>Decoration in front of and behind each panel.</p></li> <li><p>Drawing of axis labels</p></li> </ul> <p>To show how a new faceting class is created we will start simple and go through each of the required methods in turn to build up <code>facet_duplicate()</code> that simply duplicate our plot into two panels. After this we will tinker with it a bit to show some of the more powerful possibilities.</p> <div id="creating-a-layout-specification" class="section level3"> <h3>Creating a layout specification</h3> <p>A layout in the context of facets is a <code>data.frame</code> that defines a mapping between data and the panels it should reside in as well as which positional scales should be used. The output should at least contain the columns <code>PANEL</code>, <code>SCALE_X</code>, and <code>SCALE_Y</code>, but will often contain more to help assign data to the correct panel (<code>facet_grid()</code> will e.g. also return the faceting variables associated with each panel). Let’s make a function that defines a duplicate layout:</p> <div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb28-1"><a href="#cb28-1"></a>layout <-<span class="st"> </span><span class="cf">function</span>(data, params) {</span> <span id="cb28-2"><a href="#cb28-2"></a> <span class="kw">data.frame</span>(<span class="dt">PANEL =</span> <span class="kw">c</span>(1L, 2L), <span class="dt">SCALE_X =</span> 1L, <span class="dt">SCALE_Y =</span> 1L)</span> <span id="cb28-3"><a href="#cb28-3"></a>}</span></code></pre></div> <p>This is quite simple as the faceting should just define two panels irrespectively of the input data and parameters.</p> </div> <div id="mapping-data-into-panels" class="section level3"> <h3>Mapping data into panels</h3> <p>In order for ggplot2 to know which data should go where it needs the data to be assigned to a panel. The purpose of the mapping step is to assign a <code>PANEL</code> column to the layer data identifying which panel it belongs to.</p> <div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb29-1"><a href="#cb29-1"></a>mapping <-<span class="st"> </span><span class="cf">function</span>(data, layout, params) {</span> <span id="cb29-2"><a href="#cb29-2"></a> <span class="cf">if</span> (<span class="kw">is.null</span>(data) <span class="op">||</span><span class="st"> </span><span class="kw">nrow</span>(data) <span class="op">==</span><span class="st"> </span><span class="dv">0</span>) {</span> <span id="cb29-3"><a href="#cb29-3"></a> <span class="kw">return</span>(<span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> <span class="kw">integer</span>(<span class="dv">0</span>)))</span> <span id="cb29-4"><a href="#cb29-4"></a> }</span> <span id="cb29-5"><a href="#cb29-5"></a> <span class="kw">rbind</span>(</span> <span id="cb29-6"><a href="#cb29-6"></a> <span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> 1L),</span> <span id="cb29-7"><a href="#cb29-7"></a> <span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> 2L)</span> <span id="cb29-8"><a href="#cb29-8"></a> )</span> <span id="cb29-9"><a href="#cb29-9"></a>}</span></code></pre></div> <p>here we first investigate whether we have gotten an empty <code>data.frame</code> and if not we duplicate the data and assign the original data to the first panel and the new data to the second panel.</p> </div> <div id="laying-out-the-panels" class="section level3"> <h3>Laying out the panels</h3> <p>While the two functions above have been deceivingly simple, this last one is going to take some more work. Our goal is to draw two panels beside (or above) each other with axes etc.</p> <div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb30-1"><a href="#cb30-1"></a>render <-<span class="st"> </span><span class="cf">function</span>(panels, layout, x_scales, y_scales, ranges, coord, data,</span> <span id="cb30-2"><a href="#cb30-2"></a> theme, params) {</span> <span id="cb30-3"><a href="#cb30-3"></a> <span class="co"># Place panels according to settings</span></span> <span id="cb30-4"><a href="#cb30-4"></a> <span class="cf">if</span> (params<span class="op">$</span>horizontal) {</span> <span id="cb30-5"><a href="#cb30-5"></a> <span class="co"># Put panels in matrix and convert to a gtable</span></span> <span id="cb30-6"><a href="#cb30-6"></a> panels <-<span class="st"> </span><span class="kw">matrix</span>(panels, <span class="dt">ncol =</span> <span class="dv">2</span>)</span> <span id="cb30-7"><a href="#cb30-7"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb30-8"><a href="#cb30-8"></a> <span class="dt">widths =</span> <span class="kw">unit</span>(<span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="dt">heights =</span> <span class="kw">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="dt">clip =</span> <span class="st">"on"</span>)</span> <span id="cb30-9"><a href="#cb30-9"></a> <span class="co"># Add spacing according to theme</span></span> <span id="cb30-10"><a href="#cb30-10"></a> panel_spacing <-<span class="st"> </span><span class="cf">if</span> (<span class="kw">is.null</span>(theme<span class="op">$</span>panel.spacing.x)) {</span> <span id="cb30-11"><a href="#cb30-11"></a> theme<span class="op">$</span>panel.spacing</span> <span id="cb30-12"><a href="#cb30-12"></a> } <span class="cf">else</span> {</span> <span id="cb30-13"><a href="#cb30-13"></a> theme<span class="op">$</span>panel.spacing.x</span> <span id="cb30-14"><a href="#cb30-14"></a> }</span> <span id="cb30-15"><a href="#cb30-15"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_col_space</span>(panel_table, panel_spacing)</span> <span id="cb30-16"><a href="#cb30-16"></a> } <span class="cf">else</span> {</span> <span id="cb30-17"><a href="#cb30-17"></a> panels <-<span class="st"> </span><span class="kw">matrix</span>(panels, <span class="dt">ncol =</span> <span class="dv">1</span>)</span> <span id="cb30-18"><a href="#cb30-18"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb30-19"><a href="#cb30-19"></a> <span class="dt">widths =</span> <span class="kw">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="dt">heights =</span> <span class="kw">unit</span>(<span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="dt">clip =</span> <span class="st">"on"</span>)</span> <span id="cb30-20"><a href="#cb30-20"></a> panel_spacing <-<span class="st"> </span><span class="cf">if</span> (<span class="kw">is.null</span>(theme<span class="op">$</span>panel.spacing.y)) {</span> <span id="cb30-21"><a href="#cb30-21"></a> theme<span class="op">$</span>panel.spacing</span> <span id="cb30-22"><a href="#cb30-22"></a> } <span class="cf">else</span> {</span> <span id="cb30-23"><a href="#cb30-23"></a> theme<span class="op">$</span>panel.spacing.y</span> <span id="cb30-24"><a href="#cb30-24"></a> }</span> <span id="cb30-25"><a href="#cb30-25"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_row_space</span>(panel_table, panel_spacing)</span> <span id="cb30-26"><a href="#cb30-26"></a> }</span> <span id="cb30-27"><a href="#cb30-27"></a> <span class="co"># Name panel grobs so they can be found later</span></span> <span id="cb30-28"><a href="#cb30-28"></a> panel_table<span class="op">$</span>layout<span class="op">$</span>name <-<span class="st"> </span><span class="kw">paste0</span>(<span class="st">"panel-"</span>, <span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">2</span>))</span> <span id="cb30-29"><a href="#cb30-29"></a> </span> <span id="cb30-30"><a href="#cb30-30"></a> <span class="co"># Construct the axes</span></span> <span id="cb30-31"><a href="#cb30-31"></a> axes <-<span class="st"> </span><span class="kw">render_axes</span>(ranges[<span class="dv">1</span>], ranges[<span class="dv">1</span>], coord, theme, </span> <span id="cb30-32"><a href="#cb30-32"></a> <span class="dt">transpose =</span> <span class="ot">TRUE</span>)</span> <span id="cb30-33"><a href="#cb30-33"></a></span> <span id="cb30-34"><a href="#cb30-34"></a> <span class="co"># Add axes around each panel</span></span> <span id="cb30-35"><a href="#cb30-35"></a> panel_pos_h <-<span class="st"> </span><span class="kw">panel_cols</span>(panel_table)<span class="op">$</span>l</span> <span id="cb30-36"><a href="#cb30-36"></a> panel_pos_v <-<span class="st"> </span><span class="kw">panel_rows</span>(panel_table)<span class="op">$</span>t</span> <span id="cb30-37"><a href="#cb30-37"></a> axis_width_l <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertWidth</span>(</span> <span id="cb30-38"><a href="#cb30-38"></a> grid<span class="op">::</span><span class="kw">grobWidth</span>(axes<span class="op">$</span>y<span class="op">$</span>left[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-39"><a href="#cb30-39"></a> axis_width_r <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertWidth</span>(</span> <span id="cb30-40"><a href="#cb30-40"></a> grid<span class="op">::</span><span class="kw">grobWidth</span>(axes<span class="op">$</span>y<span class="op">$</span>right[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-41"><a href="#cb30-41"></a> <span class="co">## We do it reverse so we don't change the position of panels when we add axes</span></span> <span id="cb30-42"><a href="#cb30-42"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">rev</span>(panel_pos_h)) {</span> <span id="cb30-43"><a href="#cb30-43"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_r, i)</span> <span id="cb30-44"><a href="#cb30-44"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb30-45"><a href="#cb30-45"></a> <span class="kw">rep</span>(axes<span class="op">$</span>y<span class="op">$</span>right, <span class="kw">length</span>(panel_pos_v)), <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> i <span class="op">+</span><span class="st"> </span><span class="dv">1</span>, </span> <span id="cb30-46"><a href="#cb30-46"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-47"><a href="#cb30-47"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_l, i <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb30-48"><a href="#cb30-48"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb30-49"><a href="#cb30-49"></a> <span class="kw">rep</span>(axes<span class="op">$</span>y<span class="op">$</span>left, <span class="kw">length</span>(panel_pos_v)), <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> i, </span> <span id="cb30-50"><a href="#cb30-50"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-51"><a href="#cb30-51"></a> }</span> <span id="cb30-52"><a href="#cb30-52"></a> <span class="co">## Recalculate as gtable has changed</span></span> <span id="cb30-53"><a href="#cb30-53"></a> panel_pos_h <-<span class="st"> </span><span class="kw">panel_cols</span>(panel_table)<span class="op">$</span>l</span> <span id="cb30-54"><a href="#cb30-54"></a> panel_pos_v <-<span class="st"> </span><span class="kw">panel_rows</span>(panel_table)<span class="op">$</span>t</span> <span id="cb30-55"><a href="#cb30-55"></a> axis_height_t <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertHeight</span>(</span> <span id="cb30-56"><a href="#cb30-56"></a> grid<span class="op">::</span><span class="kw">grobHeight</span>(axes<span class="op">$</span>x<span class="op">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-57"><a href="#cb30-57"></a> axis_height_b <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertHeight</span>(</span> <span id="cb30-58"><a href="#cb30-58"></a> grid<span class="op">::</span><span class="kw">grobHeight</span>(axes<span class="op">$</span>x<span class="op">$</span>bottom[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-59"><a href="#cb30-59"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">rev</span>(panel_pos_v)) {</span> <span id="cb30-60"><a href="#cb30-60"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_rows</span>(panel_table, axis_height_b, i)</span> <span id="cb30-61"><a href="#cb30-61"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb30-62"><a href="#cb30-62"></a> <span class="kw">rep</span>(axes<span class="op">$</span>x<span class="op">$</span>bottom, <span class="kw">length</span>(panel_pos_h)), <span class="dt">t =</span> i <span class="op">+</span><span class="st"> </span><span class="dv">1</span>, <span class="dt">l =</span> panel_pos_h, </span> <span id="cb30-63"><a href="#cb30-63"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-64"><a href="#cb30-64"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_rows</span>(panel_table, axis_height_t, i <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb30-65"><a href="#cb30-65"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb30-66"><a href="#cb30-66"></a> <span class="kw">rep</span>(axes<span class="op">$</span>x<span class="op">$</span>top, <span class="kw">length</span>(panel_pos_h)), <span class="dt">t =</span> i, <span class="dt">l =</span> panel_pos_h, </span> <span id="cb30-67"><a href="#cb30-67"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-68"><a href="#cb30-68"></a> }</span> <span id="cb30-69"><a href="#cb30-69"></a> panel_table</span> <span id="cb30-70"><a href="#cb30-70"></a>}</span></code></pre></div> </div> <div id="assembling-the-facet-class" class="section level3"> <h3>Assembling the Facet class</h3> <p>Usually all methods are defined within the class definition in the same way as is done for <code>Geom</code> and <code>Stat</code>. Here we have split it out so we could go through each in turn. All that remains is to assign our functions to the correct methods as well as making a constructor</p> <div class="sourceCode" id="cb31"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb31-1"><a href="#cb31-1"></a><span class="co"># Constructor: shrink is required to govern whether scales are trained on </span></span> <span id="cb31-2"><a href="#cb31-2"></a><span class="co"># Stat-transformed data or not.</span></span> <span id="cb31-3"><a href="#cb31-3"></a>facet_duplicate <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">shrink =</span> <span class="ot">TRUE</span>) {</span> <span id="cb31-4"><a href="#cb31-4"></a> <span class="kw">ggproto</span>(<span class="ot">NULL</span>, FacetDuplicate,</span> <span id="cb31-5"><a href="#cb31-5"></a> <span class="dt">shrink =</span> shrink,</span> <span id="cb31-6"><a href="#cb31-6"></a> <span class="dt">params =</span> <span class="kw">list</span>(</span> <span id="cb31-7"><a href="#cb31-7"></a> <span class="dt">horizontal =</span> horizontal</span> <span id="cb31-8"><a href="#cb31-8"></a> )</span> <span id="cb31-9"><a href="#cb31-9"></a> )</span> <span id="cb31-10"><a href="#cb31-10"></a>}</span> <span id="cb31-11"><a href="#cb31-11"></a></span> <span id="cb31-12"><a href="#cb31-12"></a>FacetDuplicate <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"FacetDuplicate"</span>, Facet,</span> <span id="cb31-13"><a href="#cb31-13"></a> <span class="dt">compute_layout =</span> layout,</span> <span id="cb31-14"><a href="#cb31-14"></a> <span class="dt">map_data =</span> mapping,</span> <span id="cb31-15"><a href="#cb31-15"></a> <span class="dt">draw_panels =</span> render</span> <span id="cb31-16"><a href="#cb31-16"></a>)</span></code></pre></div> <p>Now with everything assembled, lets test it out:</p> <div class="sourceCode" id="cb32"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb32-1"><a href="#cb32-1"></a>p <-<span class="st"> </span><span class="kw">ggplot</span>(mtcars, <span class="kw">aes</span>(<span class="dt">x =</span> hp, <span class="dt">y =</span> mpg)) <span class="op">+</span><span class="st"> </span><span class="kw">geom_point</span>()</span> <span id="cb32-2"><a href="#cb32-2"></a>p</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <div class="sourceCode" id="cb33"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb33-1"><a href="#cb33-1"></a>p <span class="op">+</span><span class="st"> </span><span class="kw">facet_duplicate</span>()</span></code></pre></div> <p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAKgCAYAAABEPM/FAAAEGWlDQ1BrQ0dDb2xvclNwYWNlR2VuZXJpY1JHQgAAOI2NVV1oHFUUPrtzZyMkzlNsNIV0qD8NJQ2TVjShtLp/3d02bpZJNtoi6GT27s6Yyc44M7v9oU9FUHwx6psUxL+3gCAo9Q/bPrQvlQol2tQgKD60+INQ6Ium65k7M5lpurHeZe58853vnnvuuWfvBei5qliWkRQBFpquLRcy4nOHj4g9K5CEh6AXBqFXUR0rXalMAjZPC3e1W99Dwntf2dXd/p+tt0YdFSBxH2Kz5qgLiI8B8KdVy3YBevqRHz/qWh72Yui3MUDEL3q44WPXw3M+fo1pZuQs4tOIBVVTaoiXEI/MxfhGDPsxsNZfoE1q66ro5aJim3XdoLFw72H+n23BaIXzbcOnz5mfPoTvYVz7KzUl5+FRxEuqkp9G/Ajia219thzg25abkRE/BpDc3pqvphHvRFys2weqvp+krbWKIX7nhDbzLOItiM8358pTwdirqpPFnMF2xLc1WvLyOwTAibpbmvHHcvttU57y5+XqNZrLe3lE/Pq8eUj2fXKfOe3pfOjzhJYtB/yll5SDFcSDiH+hRkH25+L+sdxKEAMZahrlSX8ukqMOWy/jXW2m6M9LDBc31B9LFuv6gVKg/0Szi3KAr1kGq1GMjU/aLbnq6/lRxc4XfJ98hTargX++DbMJBSiYMIe9Ck1YAxFkKEAG3xbYaKmDDgYyFK0UGYpfoWYXG+fAPPI6tJnNwb7ClP7IyF+D+bjOtCpkhz6CFrIa/I6sFtNl8auFXGMTP34sNwI/JhkgEtmDz14ySfaRcTIBInmKPE32kxyyE2Tv+thKbEVePDfW/byMM1Kmm0XdObS7oGD/MypMXFPXrCwOtoYjyyn7BV29/MZfsVzpLDdRtuIZnbpXzvlf+ev8MvYr/Gqk4H/kV/G3csdazLuyTMPsbFhzd1UabQbjFvDRmcWJxR3zcfHkVw9GfpbJmeev9F08WW8uDkaslwX6avlWGU6NRKz0g/SHtCy9J30o/ca9zX3Kfc19zn3BXQKRO8ud477hLnAfc1/G9mrzGlrfexZ5GLdn6ZZrrEohI2wVHhZywjbhUWEy8icMCGNCUdiBlq3r+xafL549HQ5jH+an+1y+LlYBifuxAvRN/lVVVOlwlCkdVm9NOL5BE4wkQ2SMlDZU97hX86EilU/lUmkQUztTE6mx1EEPh7OmdqBtAvv8HdWpbrJS6tJj3n0CWdM6busNzRV3S9KTYhqvNiqWmuroiKgYhshMjmhTh9ptWhsF7970j/SbMrsPE1suR5z7DMC+P/Hs+y7ijrQAlhyAgccjbhjPygfeBTjzhNqy28EdkUh8C+DU9+z2v/oyeH791OncxHOs5y2AtTc7nb/f73TWPkD/qwBnjX8BoJ98VQNcC+8AAAA4ZVhJZk1NACoAAAAIAAGHaQAEAAAAAQAAABoAAAAAAAKgAgAEAAAAAQAAAqCgAwAEAAAAAQAAAqAAAAAAzDjxOwAAQABJREFUeAHs3QecFPX9//HPcQccvYMUFYwIsaAQC4oECxj/amzYEBRUgibYxULEH4IlIdhQNPZuolgiBhWJgGhUREVFBRFQKQqC9HL0++f9TXbdu927270tt9/Z1/fxgNudmf3O9/uc2e9+5jvfmckr/k8yEgIIIIAAAggggAACGRKolqH1sBoEEEAAAQQQQAABBJwAASg7AgIIIIAAAggggEBGBQhAM8rNyhBAAAEEEEAAAQQIQNkHEEAAAQQQQAABBDIqUJCptS1fvtxmzpxpHTp0sHbt2oVXu2jRIvvhhx/C75s0aWLt27cPv+cFAgggEDSBL7/80pYtW2a/+tWvrGHDhuHqffLJJ7Zly5bw+7322ssaN24cfs8LBBBAICgCeZm4Cn7ChAn2/PPPW/fu3W3q1Kl29tln2/HHH+8M/+///s9+/PHHcCPcqVMn69u3b1B8qQcCCCBQQmDIkCFWWFhoLVq0sH//+992++23W5s2bWz79u127LHHuqA09IF+/frZfvvtF3rLXwQQQCAwAmnvAdVdniZNmmQjRoywtm3b2v7772/33HNPOACdN2+ejRo1ynbbbbe4UNeuXWs7duyIa9nq1avbtm3b4lo22xaqVq2a1ahRw/WG+HinLJU/Ly8v7m2Vbf4KEBQQ6J+PSfvO1q1bfSy66XurfcfH8qvcjRo1KtP922+/dW3Sbbfd5pbZtGmTvfnmmzZgwAD77rvvXCCq9jDetGrVqngXde2Jj6aqYEFBgeXn55foHY674lmwoMqv3y0f23Lt0zVr1vT2t0jl177ja1sue+07PpZfv0N169Yt8xuY9gBUG//uu+92BVAw+O6771rb/wSiSmp81YCuWLHC3n77bTviiCNcA+xm/u+/adOmuQY6NO388893PQeh9+X9VeW14/mYFMApCJKfj42Wyq9/Pn5ptL/UqlXLBQq+ll/7vvx9TKGy+1j+nTt3lkuu4Udjxoxxy6xZs8Y+++wz+93vfufe62BcPaETJ050P/a9evWy2rVrl8jv0UcfNQWxSvXr17fBgweXmF/em5Brectk6zwdlKgtV3voY1L51Zb42pbrt0jfx4r272zcNr4HoLJXAOpjZ1pFnYVpD0BDO+S6devcqfWioiJ76KGH3OQFCxa4hvbDDz90P/iXX365nXfeeeHeUS2k0/OffvppKBvXK6IvczxJX5h4l40nv0wuE2podeTsY1L5Q/98LL/K7PMPns/7vsqufcfH7268AYbOCqmns2PHjtatWzf3Ffn6669t7ty57iyRgky1k48//rg1bdo0/BVSkPrFF1+49xovn4gR+0SYMeMvQvbx7h8ZL2A5K4z8LfK1/D7/Fqnsof2nnM2UlbMq2l8yMgY0JKPCqKfzlltusfHjx7vGc/369eFTVuod1RH+I488EvpI1F/1lsbbK9WgQQNT/j4etanbXRcf6OKtio4iopCyYIJ6W/TjuHHjxiwoTeJF0Pi8DRs2eFt+nQZevXp14hXPgk/oe6t956effsqC0iRehJYtW8b1IZ0B0tkh/R05cqT7qw+Gej1vuukmd8GmxoGWlZYuXVrWrKjpPu8T9erVc2eE1P77mFR+db7E+9uVTXXUd1EHQfo++tgLp04c9SKqPfcxNWvWzDZv3uxiGd/KH4pjyip32s/RaczR9OnT3foVyffo0cNdcKSrQHUKKvJHUuNA1ePpY8BYFjDTEUAAgZCA2jf1ciop0DzllFPso48+cu+///77EmMc1R4mEmC6TPgPAQQQ8EQg7QGojp7uv/9+mzFjhiNR47ty5UrbfffdTRcUXXHFFe7IUL2julpeAaq6m0kIIIBA0ATU23nddde5Hg3VTXcF2XPPPV01dXZIbaWSlpsyZYodeeSR7j3/IYAAAkETSPsAQ/V6amynGtYHH3zQXU2nK+LVrax/p556qg0aNMidmtCgep12IiGAAAJBFNBFSL1793ZtnsYY670CUqXTTz/djQvVOHidatZFSF26dAkiA3VCAAEELKNjQDUGI9Yl+TrlrnkKQCtKjAGtSCg75jMGtGq3g8/j/XJhDKjaPI3rCo33jNxb1Pup4FTjpypKiZyi93mfYAxoRXtC+uYzBjR9tvHkHOQxoGnvAY0EjhV8ar5OuccTfEbmxWsEEEDAVwG1ebGCT9WnrOm+1pVyI4AAArEEGGwZS4VpCCCAAAIIIIAAAmkTIABNGy0ZI4AAAggggAACCMQSIACNpcI0BBBAAAEEEEAAgbQJEICmjZaMEUAAAQQQQAABBGIJEIDGUmEaAggggAACCCCAQNoECEDTRkvGCCCAAAIIIIAAArEECEBjqTANAQQQQAABBBBAIG0CBKBpoyVjBBBAAAEEEEAAgVgCBKCxVJiGAAIIIIAAAgggkDYBAtC00ZIxAggggAACCCCAQCwBAtBYKkxDAAEEEEAAAQQQSJsAAWjaaMkYAQQQQAABBBBAIJYAAWgsFaYhgAACCCCAAAIIpE2AADRttGSMAAIIIIAAAgggEEuAADSWCtMQQAABBBBAAAEE0iZAAJo2WjJGAAEEEEAAAQQQiCVQEGtiLk9bsWKFvfLKK7Z9+3Y74YQTrHXr1rnMQd0RQCCHBWbNmmVTpkyxOnXqWP/+/a1GjRo5rEHVEUAglQIEoBGaCxcutJ49e9rOnTvdvxEjRtiECROsS5cuEUvxEgEEEAi+wFNPPWXXXXed5efnW0FBgQ0fPtxmz55tDRs2DH7lqSECCKRdgFPw/yNWj+ehhx5qGzdutKKiItuyZYubM2DAANu0aVPaNwQrQAABBLJFQAfj1157rRUXF7uzQZs3b3aB6KWXXpotRaQcCCDguQAB6P824NatW61WrVpRm1OB6Q8//BA1nQkIIIBAUAW++uqrqJ7OHTt22KeffhrUKlMvBBDIsAAB6P/Aq1WrZtWrV4/iX7NmjTVq1ChqOhMQQACBoAo0b97c9XyWrh9jQEuL8B4BBCorQAD6P7nCwkK7/fbboxyHDRtmTZo0iZrOBAQQQCCoAp07d7ZevXqVqJ7Ggr7wwgslpvEGAQQQqKwAFyFFyB1//PE2adIku+OOO0yn5HXVZ+lGOGJxXiKAAAKBFbj33nvt4IMPtvHjx7vT8UOHDrW2bdsGtr5UDAEEMitAAFrKe99997VHH3201FTeIoAAArknoINw/SMhgAACqRbgFHyqRckPAQQQQAABBBBAoFwBAtByeZiJAAIIIIAAAgggkGoBAtBUi5IfAggggAACCCCAQLkCBKDl8jATAQQQQAABBBBAINUCBKCpFiU/BBBAAAEEEEAAgXIFCEDL5WEmAggggAACCCCAQKoFCEBTLUp+CCCAAAIIIIAAAuUKEICWy8NMBBBAAAEEEEAAgVQLEICmWpT8EEAAAQQQQAABBMoVIAAtl4eZCCCAAAIIIIAAAqkWIABNtSj5IYAAAggggAACCJQrQABaLg8zEUAAAQQQQAABBFItQACaalHyQwABBBBAAAEEEChXgAC0XB5mIoAAAggggAACCKRagAA01aLkhwACCCCAAAIIIFCuAAFouTzMRAABBBBAAAEEEEi1AAFoqkXJDwEEEEAAAQQQQKBcAQLQcnmYiQACCCCAAAIIIJBqAQLQVIuSHwIIIIAAAggggEC5AgSg5fIwEwEEEEAAAQQQQCDVAgSgqRYlPwQQQAABBBBAAIFyBQhAy+VhJgIIIIAAAggggECqBQhAUy1KfggggAACCCCAAALlChCAlsvDTAQQQAABBBBAAIFUCxCAplqU/BBAAAEEEEAAAQTKFSAALZeHmQgggAACCCCAAAKpFiAATbUo+SGAAAIIIIAAAgiUK0AAWi4PMxFAAAEEEEAAAQRSLVCQ6gyDkN+mTZvs3XffdVXp1q2b1a5dOwjVog4IIIBAwgJLliyxGTNmWP369a1nz54Jf54PIIAAArEE8or/k2LNyNZpGzZssIKC+OJmLbd9+/aEqrJ8+XI74IAD3GdEs2bNGps3b561adMmoXySXbhatWpWo0YN27Jli3m2iVzVVf68vDzbsWNHshRV8vmaNWu6fcfX8levXt22bdtWJXbJrlTfW+0/W7duTTarjH9e39VatWplbL2bN2+Oe12V2Sdef/11O/vss03fBx2YN2zY0BYsWGDKK5PJ531CTiq/2hIf23K149r+vv4Wqfz5+fkJxwKZ3L/LW5fste8kGsuUl2em5uk3qF69emWuzrsAdMWKFXFviAYNGtj69ett586dZQJEztBysQLN9u3b2+TJk+MOfCPzrOxr7XSNGzc2BcQ+BkEKnvUjtXHjxsoSVOnnWrRoYTrY8bX8jRo1stWrV1epYWVXru+t9p2ffvqpsllU6edatmyZsfUvXbo07nUluk+o5/Pggw8ukb8CqXPOOcduueWWEtPT/UY/YoWFhab238ek8hcVFcX925VNddR3sWnTpu776ONBrfZZ7Ttqz31MzZo1Mx1oKpbxLYXimLLKzRjQCJlVq1bF7L1QI69AkIQAAgjkisAHH3wQ1XuhXpg33ngjVwioJwIIpFGAADQCV0dJsU6R6MipTp06EUvyEgEEEAi2gMZ86vRl6aReDRICCCCQrAABaIRg3bp17ZJLLnHd9RGT7aKLLjKdFiQhgAACuSLQq1cv22OPPdz4v1CdNZbukUceCb3lLwIIIFBpgfiu5ql09v598IorrrDmzZvb/fff78Z8DhgwwPr37+9fRSgxAgggkKTAhAkT7OKLL7bp06e7C5D+/Oc/W8eOHZPMlY8jgAAC/7k4D4Rogb59+5r+kRBAAIFcFtDdCO67775cJqDuCCCQJgFOwacJlmwRQAABBBBAAAEEYgsQgMZ2YSoCCCCAAAIIIIBAmgQIQNMES7YIIIAAAggggAACsQUIQGO7MBUBBBBAAAEEEEAgTQIEoGmCJVsEEEAAAQQQQACB2AIEoLFdmIoAAggggAACCCCQJgEC0DTBki0CCCCAAAIIIIBAbAEC0NguTEUAAQQQQAABBBBIkwABaJpgyRYBBBBAAAEEEEAgtgABaGwXpiKAAAIIIIAAAgikSYAANE2wZIsAAggggAACCCAQW4AANLYLUxFAAAEEEEAAAQTSJEAAmiZYskUAAQQQQAABBBCILUAAGtuFqQgggAACCCCAAAJpEiAATRMs2SKAAAIIIIAAAgjEFiAAje3CVAQQQAABBBBAAIE0CRCApgmWbBFAAAEEEEAAAQRiCxCAxnZhKgIIIIAAAggggECaBAhA0wRLtggggAACCCCAAAKxBQhAY7swFQEEEEAAAQQQQCBNAgSgaYIlWwQQQAABBBBAAIHYAgSgsV2YigACCCCAAAIIIJAmAQLQNMGSLQIIIIAAAggggEBsAQLQ2C5MRQABBBBAAAEEEEiTAAFommDJFgEEEEAAAQQQQCC2AAFobBemIoAAAggggAACCKRJgAA0TbBkiwACCCCAAAIIIBBbgAA0tgtTEUAAAQQQQAABBNIkQACaJliyRQABBBBAAAEEEIgtQAAa24WpCCCAAAIIIIAAAmkSIABNEyzZIoAAAggggAACCMQWIACN7cJUBBBAAAEEEEAAgTQJEICmCZZsEUAAAQQQQAABBGILEIDGdmEqAggggAACCCCAQJoECEDTBEu2CCCAAAIIIIAAArEFCEBjuzAVAQQQQAABBBBAIE0CBKBpgiVbBBBAAAEEEEAAgdgCBKCxXZiKAAIIIIAAAgggkCYBAtA0wZItAggggAACCCCAQGwBAtDYLkxFAAEEEEAAAQQQSJNA4APQjRs32uzZs23p0qVpIsyObLdt22ZfffWVLVq0KDsKRCkQQCDrBJYvX25z5861DRs2ZF3ZUlmgtWvX2tdff20rV65MZbbkhQACKRQIdAD6ySefWNeuXe20006zX/3qVzZixIgU0mVPVsuWLbMePXrYySef7Op76qmn2s6dO7OngJQEAQSqXOCOO+6www47zNQ+7LXXXvb+++9XeZnSUYDJkyfboYce6uq533772RNPPJGO1ZAnAggkKRDYAFRH+ocffritWLHC1qxZ45geeOABGzduXJJk2fXxLVu2WJcuXey7776zdevWucJ98MEHdvPNN2dXQSkNAghUmcCbb75p119/vW3atMlWr17tytG7d2/XblRZodKwYvV6nnPOOa7NX7VqlVvD0KFD7d///nca1kaWCCCQjEBgA9BJkyZZnTp1omyefvrpqGk+T/j444+tQYMGJapQXFwcuEC7RAV5gwACCQk8+uijUcvXqFHDXn/99ajpPk946aWXrFq16J+1v//97z5Xi7IjEEiB6G9qQKqpRihWQ1S9evWA1PC/1SgoKLC8vLyoOu3YsSNqGhMQQCA3BRRslk5qH/Pz80tP9vq96pML7b7XG4nCI/A/gcAGoCeccIKVDjb1fvjw4YHa+AceeKC1adOmxA9JYWGhXXbZZYGqJ5VBAIHKC1x88cVR7eHmzZvtzDPPrHymWfjJPn36mA7KS6crrrii9CTeI4BAFQsENgCtX7++ffjhh64xUuBZr149u/POO61Tp05VTJ7a1etof/z48e40vF5r2IEa24suuii1KyI3BBDwVkAHqi+++KIrvw5QO3To4C5CKj18x9sK/q/gOhh/44033Fmh2rVrW4sWLUyn5XfffXffq0b5EQicQPShYoCquMsuu7jbEukWRboqvGbNmgGq3c9VqVWrln3xxRememr8Z6zTbT8vzSsEEMhFgV69etm3337rzpZo2E7QTr+Htmn79u1t4cKF7q3afdrDkAx/EcgugUAHoKJWr2DpU/HZtQlSV5pcqWfqxMgJgdwSCOpBeOmtGOs0fOlleI8AAlUrkLFT8Lot0sSJE90ReOkq68bIumr9p59+Kj2L9wgggEDgBL788kvT/SpDt4gLVVC3VXv33Xftvffec2c0QtP5iwACCARNICMB6IQJE+zqq6+2JUuW2LBhw+zVV18NO2pc5ujRo003jb/gggt4kk9YhhcIIBBEgSFDhphuC6QntF144YWuXVQ9i4qKbMCAATZ16lTT7eKuueYaN6QmiAbUCQEEEEj7KXiNSVTvpp5C1LZtW9t///3tnnvuseOPP97dBPmdd96xF154wZ0qf/bZZ+2ZZ54x3TiYhAACCARNQGMwNVb7tttuc1XTjeF1k3gFns8995wdcsghdvnll7t5Ck71UAk9zY2EAAIIBE0g7QGoBrvffffdzk0Nr04vKRBV+uabb9xV6aH7tumJPpG9o1pGp6hCT7TQe13ZGO/g+dBA+1j3yVRe2ZxCJqG/2VzWWGVTufUv3m0VK4+qnuZz+UP7flUbVmb9KrvP5S+vzu3atbMxY8a4RdS2ffbZZ/a73/3OvZ8/f74dc8wx4Y+rPVQvaWQAunTpUtdTqoU0zlFXtMebfDbVd9Hn8ofKrg4Z35LslXxtD/UbFPL3zV7lVdl9Lb/KXV5KewAaWrkeE9m3b1/XeD700ENushrTyNuA6NZJK1euDH3E/dWpqrvuuis8TbfU2GeffcLvK3qhK8R9Tk2bNvW5+Fa3bl1vy6+y+1z+5s2be2uvgvtYfl11HU/SWaFRo0ZZx44drVu3bu4jy5YtM7WBoaTXGrYUmXT6/qOPPnKT5KMzSIkkH00j6+dz+WM9mS+ybtn+unHjxtlexHLL53Nbrn3Hx/1HZ3jKSxkLQNWYvvLKK/b222+7cU+6d6WOTCKf2LN9+3YrHTDqhvKR9+5s2LBhVJBaVgW1wTSuKt4fhbLyqYrpuqJdZnpus6/l1/bVza59TGpste/on49J971dv369j0V3Da1699auXetl+Zs0aVJhudXTefjhh7uzQzfffLONHDkyrvbwuuuuMx3MK+mK9tIH7OWt2Od9Qme+dDul0hdtlVffbJqn8usCs8jfu2wqX3ll0XdRHUWy97H8+h3SvuNrW66YZ+vWrVZRMFfeNqyqebLXvl9WSnsAKriZM2e600jqju3Ro4fde++9pqtAmzVrZrNmzQqXTafaW7ZsGX6vF7vuuqv7F5q4YsUKtzFC78v7q2BW6/cxgAt1XWvYgo9f+tB2kb+PSafKdEDka/m1z/tadn1v5e9r+cvb33/88Uf3Q64bwathPuWUU9yDI/QZne2IHG6k12r/ItN+++0X+dZ0Fine5PM+oWDb531C5VdbrjbFtxQaNqCyqw6+JQXQCoR8bU/krxjAx/JXdNu3tF8Fr568+++/32bMmOH2W91ySUftejLFQQcd5G6gvnjxYvfF/Oc//2kHH3ywb/s35UUAAQTiElAvhnoxQ2cGdMX7nnvu6T7bvXt3e/3119083ZJOt2Lq3LlzXPmyEAIIIOCbQNp7QNWTp6s6FYQ++OCD7rSRrohX76fSoEGDbODAgaZTngpKzz77bN8MKS8CCCAQl4AuQurdu7dr99Qro/cKSJV69uzpLtLU88x1wcdZZ53l5seVMQshgAACngnk/ad7N2OX5W3YsCHmRR3q1tf4mHgGCesUfLynMTRuRePgfDwFr65rBeW6gb+Pp+A15ka93xs3bvTsK/Hf4uoZ0tpffS1/o0aN3PhhH/H1vdW+4+uDKUoPI4q1DdQmqRc01vgotVkahqBThxWlRE7B+7xPaPyqrvhX++9jUvk1BjHe365sqqO+ixoeou+jr6fgte+oPfcxqbNObYWPY/pDcUxZ7hW3cGV9shLTywowtYPrHwkBBBDIBQH1cMYKPlV3BSskBBBAIOgCaR8DGnRA6ocAAggggAACCCCQmAABaGJeLI0AAggggAACCCCQpAABaJKAfBwBBBBAAAEEEEAgMQEC0MS8WBoBBBBAAAEEEEAgSQEC0CQB+TgCCCCAAAIIIIBAYgIEoIl5sTQCCCCAAAIIIIBAkgIEoEkC8nEEEEAAAQQQQACBxAQIQBPzYmkEEEAAAQQQQACBJAUIQJME5OMIIIAAAggggAACiQkQgCbmxdIIIIAAAggggAACSQoQgCYJyMcRQAABBBBAAAEEEhMgAE3Mi6URQAABBBBAAAEEkhQgAE0SkI8jgAACCCCAAAIIJCZAAJqYF0sjgAACCCCAAAIIJClAAJokIB9HAAEEEEAAAQQQSEyAADQxL5ZGAAEEEEAAAQQQSFKAADRJQD6OAAIIIIAAAgggkJgAAWhiXiyNAAIIIIAAAgggkKQAAWiSgHwcAQQQQAABBBBAIDEBAtDEvFgaAQQQQAABBBBAIEkBAtAkAfk4AggggAACCCCAQGICBKCJebE0AggggAACCCCAQJICBKBJAvJxBBBAAAEEEEAAgcQECEAT82JpBBBAAAEEEEAAgSQFCECTBOTjCCCAAAIIIIAAAokJEIAm5sXSCCCAAAIIIIAAAkkKEIAmCcjHEUAAAQQQQAABBBITIABNzIulEUAAAQQQQAABBJIUIABNEpCPI4AAAggggAACCCQmQACamBdLI4AAAggggAACCCQpQACaJCAfRwABBBBAAAEEEEhMgAA0MS+WRgABBBBAAAEEEEhSgAA0SUA+jgACCCCAAAIIIJCYAAFoYl4sjQACCCCAAAIIIJCkAAFokoB8HAEEEEAAAQQQQCAxAQLQxLxYGgEEEEAAAQQQQCBJAQLQJAH5OAIIIIAAAggggEBiAgSgiXmxNAIIIIAAAggggECSAgSgSQLycQQQQAABBBBAAIHEBAhAE/NiaQQQQAABBBBAAIEkBQhAkwTk4wgggAACCCCAAAKJCRCAJubF0ggggAACCCCAAAJJChCAJgnIxxFAAAEEEEAAAQQSEyAATcyLpRFAAAEEEEAAAQSSFCAATRKQjyOAAAIIIIAAAggkJkAAmpgXSyOAAAIIIIAAAggkKUAAmiQgH0cAAQQQQAABBBBITIAANDEvlkYAAQQQQAABBBBIUoAANElAPo4AAggggAACCCCQmAABaGJeLI0AAggggAACCCCQpAABaJKAfBwBBBBAAAEEEEAgMQEC0MS8WBoBBBBAAAEEEEAgSQEC0CQB+TgCCCCAAAIIIIBAYgIFiS1e9UsXFhZatWrxxc3Vq1e3evXqWXFxcdUXPMES5Ofnu0/UrVvXy/JrG+lfqB4JVr/KF8/LyzPta76Wv6CgwOrXr1/ljpUpgL63cvex/JluaxIx8nmfqFGjhmtPEqlvZfa9dH1G+7Taw0zvH6moT+j3tk6dOrZz585UZJnRPEK/Q6F6ZHTlKViZyq3938d9f8eOHeUKeBeAbtmyJe4vgTbcpk2b4l6+XKkMz9QOpwDI1/KrwdUPXlFRUYblUrO6WrVq2datW51/anLMbC6y37hxY2ZXmqK16XurAwBfy6+DxkylRIx83ie0P2i/SKS+mdoG8axHwdvmzZutoh/kePLK9DLab9Qeqi3fvn17plef9PpU/po1a3q77ygO2LZtm5flVxxQXvIuANURZLxf4tCyiR61/fDDD/bqq686txNPPNFatGhRnmFa5oXKrL/x1jctBalkpurBCvlXMosq/5iv9oLz2V5l97n8mdxxE2kbKms6ffp0+/e//+3OJl1wwQXuwDKTddS69F2sbPkzXdZY61PZfW1PFPgr+Vp+Hbz4Wna5a9/xdd9X8F9eKn9ueZ8M6LzZs2dbz5493RGTNvrw4cNt4sSJ1qlTp4DWmGohgAACsQXuvvtuGz16tJupH5MRI0bYV1995eXpwNg1ZCoCCFSVQHyDKauqdBler07vK/hU0mudglU677zz3OkT94b/EEAAgRwQmDNnjv35z392Z2DU06o2UUHoNddckwO1p4oIIJBuAQLQCOF169a500wRk9xLjTtatWpV6cm8RwABBAIrMHfu3KieTo0BnDlzZmDrTMUQQCBzAgSgEdYaKK7T7qWTAlMfr0ArXQ/eI4AAAvEKNGvWzI2dK718w4YNS0/iPQIIIJCwAAFoBFnt2rXt1ltvjZjy35d33HGHZfLK1qgCMAEBBBDIsEC3bt3skEMOCa9VF6PoFPzTTz8dnsYLBBBAoLICXIRUSu60006z9u3b29ixY11vaP/+/a179+6lluItAgggEHyBp556yh5++GF3IWbjxo1t2LBh1rx58+BXnBoigEDaBQhAYxDvv//+9tBDD8WYwyQEEEAgtwQGDhxo+kdCAAEEUinAKfhUapIXAggggAACCCCAQIUCBKAVErEAAggggAACCCCAQCoFCEBTqUleCCCAAAIIIIAAAhUKEIBWSMQCCCCAAAIIIIAAAqkUIABNpSZ5IYAAAggggAACCFQoQABaIRELIIAAAggggAACCKRSgAA0lZrkhQACCCCAAAIIIFChAAFohUQsgAACCCCAAAIIIJBKAQLQVGqSFwIIIIAAAggggECFAgSgFRKxAAIIIIAAAggggEAqBQhAU6lJXggggAACCCCAAAIVChCAVkjEAggggAACCCCAAAKpFCAATaUmeSGAAAIIIIAAAghUKEAAWiERCyCAAAIIIIAAAgikUoAANJWa5IUAAggggAACCCBQoQABaIVELIAAAggggAACCCCQSgEC0FRqkhcCCCCAAAIIIIBAhQIEoBUSsQACCCCAAAIIIIBAKgUIQFOpSV4IIIAAAggggAACFQoQgFZIxAIIIIAAAggggAACqRQgAE2lJnkhgAACCCCAAAIIVChAAFohEQsggAACCCCAAAIIpFKAADSVmuSFAAIIIIAAAgggUKEAAWiFRKlfYPv27TZ37lz77rvvUp85OSKAAAIeCaxdu9bmzJljy5cv96jUFBUBBJIVIABNVjDBz69YscKOPPJIO/nkk+2www6z4447znbs2JFgLiyOAAII+C8wbdo0O/TQQ+20006zAw44wP7617/6XylqgAACcQkQgMbFlJqFtm7davvvv78tWLDAdNSv9Nlnn9kNN9yQmhWQCwIIIOCJgNrBPn362Jo1a2z16tWu1DfddJNNmTLFkxpQTAQQSEaAADQZvQQ/q2CzQYMGJT5VXFxsL7/8colpvEEAAQSCLvCPf/zD8vPzo6r5zDPPRE1jAgIIBE+AADSD27RGjRqWl5cXtUb1jJIQQACBXBJQexgrAC0sLMwlBuqKQM4KEIBmcNN36tTJ9thjDysoKAivVY3tJZdcEn7PCwQQQCAXBM4888yYAeiQIUNyofrUEYGcFyAAzeAuoN7PF154wZo2bWrVqlWz2rVr26WXXmqXXXZZBkvBqhBAAIGqF2jRooVNnjzZHZDrQLx58+Y2btw4a9euXdUXjhIggEDaBX7uikv7qliBBNTQzpw5EwwEEEAg5wXatm1rixYtynkHABDIRQF6QHNxq1NnBBBAAAEEEECgCgUIQKsQn1UjgAACCCCAAAK5KEAAmotbnTojgAACCCCAAAJVKEAAWoX4rBoBBBBAAAEEEMhFAQLQXNzq1BkBBBBAAAEEEKhCAQLQKsRn1QgggAACCCCAQC4KEIDm4lanzggggAACCCCAQBUKEIBWIT6rRgABBBBAAAEEclGAADQXtzp1RgABBBBAAAEEqlCAALQK8Vk1AggggAACCCCQiwIEoLm41akzAggggAACCCBQhQIEoFWIz6oRQAABBBBAAIFcFCAAzcWtTp0RQAABBBBAAIEqFCAArUJ8Vo0AAggggAACCOSiAAFoLm516owAAggggAACCFShAAFoFeKzagQQQAABBBBAIBcFCjJV6dWrV9vHH39s++yzj7Vs2TK82kWLFtkPP/wQft+kSRNr3759+D0vEEAAgaAJzJ8/3xYvXmxdu3a1WrVqhav3ySef2JYtW8Lv99prL2vcuHH4PS8QQACBoAhkJAAdP368vfDCC/brX//a/e3YsaNdfvnlzvDhhx+2H3/80Ro2bOjed+rUiQA0KHsX9UAAgSiBK6+80vLz8+0Xv/iF3X///XbVVVfZwQcfbNu3b7err77afvWrX4U/069fPwLQsAYvEEAgSAJpD0B37NhhTz31lI0ePdratWtnffv2tTPOOMP69+9vjRo1snnz5tmoUaNst912C5IrdUEAAQSiBL744gtbsWKFaxM1s0OHDvbss8+6APS7776zNm3auPYw6oNMQAABBAImkPYAVEf6TzzxhNWpU8fRbd682TZs2GAKTDdt2mSrVq1yDfLbb79tRxxxhGuAI41fe+01e/nll8OTrrnmmqhlwjNLvahevbrraSguLi41J/vfVqv23+G5DRo0MF/Ln5eXZzVq1Mh+7BglVNl1atTX8mvf1wGej6mgoMC0//tY/oq+q3vvvbc9+OCD4c2ydu1aU5uopINxBaATJ050p+F79epltWvXDi+rF7fddpt9/fXXbprOGo0cObLE/PLesE+Up5Peedqn5V/R/pHeUlQud7WFSvXq1fO2/IpD5O9jUtkLCwtN+5BvSWd1yksZuQgpFHzu3LnTxowZY8cee6w1bdrUFixY4BraDz/80AWkOi3/6quvliivvrD6XOhfiZm8yWqBUMOV1YWkcAhkUECBdWjM5/Lly11P6LnnnutKoMBy7ty5tn79evdXZ4p++umnEqULtYOhvyVm8iarBWgPq2bz4F417vGsNe8/AV5Gugc1sF5H61rdjTfe6HqWFB2rsQ31dLz77rv26KOP2iOPPFJm2XX6qqKoOvRh9R4qfzXWvqWaNWu6sV/6kVJvsW9JPYc64ty4caNvRXflbdGiheup97X8+k7pwj8fk7632ndKB1++1CXyIsuyyvztt9/atddeawo+TzjhBLeYzggphXo9b7rpJjdsSeNAy0pLly4ta1bUdJ/3CfW+qRdI7b+PSeUvKiqK+7crm+qo76I6jPR93LZtWzYVLa6yqOdQ+47OvPqYmjVr5s6SKJbxLYXimLLKnZEeUDWsQ4YMcV34alRDpzXXrFlT4kdS40B1QZKPAWNZwExHAAEEIgXmzJljV1xxhQ0ePDgcfGr+999/X+IKeLWHiQSYkevgNQIIIJDtAhkJQIcPH+4G21933XVuTGYIReOf1BDryFA9oxMmTLAePXq48V+hZfiLAAIIBEVAvUgax642UW1dZNI4eF0Vr6SD9ilTptiRRx4ZuQivEUAAgcAIpH1Uq472p0+f7v6NGzcuDDd27FjTLZdOPfVUGzRokDs1Ub9+fVMPKQkBBBAIooDaQJ35ueyyy8LV030+daHl6aef7q6AP++889ypZl2E1KVLl/ByvEAAAQSCJJCxMaDloemUu8ZnKACtKDEGtCKh7JjPGNCq3Q4+j/fLhTGg5e0d6v3Ula8aP1VRSuQUvc/7BGNAK9oT0jefMaDps40n5yCPAU17D2g8wLoyNJ7gM568WAYBBBDwWSB0EZLPdaDsCCCAQEUCGRkDWlEhmI8AAggggAACCCCQOwIEoLmzrakpAggggAACCCCQFQIEoFmxGSgEAggggAACCCCQOwIEoLmzrakpAggggAACCCCQFQJZcRFSVUssWbLE7rzzTlu3bp2ddNJJJW4OXdVlY/0IIIBAJgXee+89e/bZZ93TqC699FLbfffdM7l61oUAAjkikPMBqILPbt26ucdd6nZQeha9Gl3dNJ+EAAII5JLAU0895R4RGqrz3//+d3vppZesa9euoUn8RQABBFIikPOn4E855RT3fNvIx3/qefRz585NCTCZIIAAAj4IrFy5skTwGSrzH/7wB9u6dWvoLX8RQACBlAjkfAAaq2HVTdR/+OGHlACTCQIIIOCDwKpVq0xPZSqdNDQpLy+v9GTeI4AAAkkJ5HwAuueee0Y1rmqI27ZtmxQsH0YAAQR8EmjevLlFngkKlb2oqCiqjQzN4y8CCCBQWYGcD0DvueceKy4udgPuQ4jDhg2zdu3ahd7yFwEEEAi8gB6BOmbMGFdPPZ2uoKDACgsLberUqe514AGoIAIIZFQg5y9CatWqlc2bN8/uvfde9zz6Y4891g477LCMbgRWhgACCGSDQK9evVzA+eKLL7qD8j59+libNm2yoWiUAQEEAiaQ8wGotmedOnXsmmuuCdimpToIIIBA4gIdOnSwP/7xj4l/kE8ggAACCQjk/Cn4BKxYFAEEEEAAAQQQQCAFAgSgKUAkCwQQQAABBBBAAIH4BQhA47diSQQQQAABBBBAAIEUCBCApgCRLBBAAAEEEEAAAQTiFyAAjd+KJRFAAAEEEEAAAQRSIEAAmgJEskAAAQQQQAABBBCIX4AANH4rlkQAAQQQQAABBBBIgQABaAoQyQIBBBBAAAEEEEAgfgEC0PitWBIBBBBAAAEEEEAgBQIEoClAJAsEEEAAAQQQQACB+AUIQOO3YkkEEEAAAQQQQACBFAgQgKYAkSwQQAABBBBAAAEE4hcgAI3fiiURQAABBBBAAAEEUiBAAJoCRLJAAAEEEEAAAQQQiF+AADR+K5ZEAAEEEEAAAQQQSIEAAWgKEMkCAQQQQAABBBBAIH4BAtD4rVgSAQQQQAABBBBAIAUCBKApQCQLBBBAAAEEEEAAgfgFCEDjt2JJBBBAAAEEEEAAgRQIEICmAJEsEEAAAQQQQAABBOIXIACN34olEUAAAQQQQAABBFIgQACaAkSyQAABBBBAAAEEEIhfgAA0fiuWRAABBBBAAAEEEEiBAAFoChDJAgEEEEAAAQQQQCB+AQLQ+K1YEgEEEEAAAQQQQCAFAgSgKUAkCwQQQAABBBBAAIH4BQhA47diSQQQQAABBBBAAIEUCBCApgCRLBBAAAEEEEAAAQTiFyAAjd+KJRFAAAEEEEAAAQRSIEAAmgJEskAAAQQQQAABBBCIX6Ag/kVZMtUCO3bssBUrVlhBQYFt377d6tat6/6lej3khwACCGS7wKZNm2z9+vWWn59vahsbNWpkNWrUyPZiUz4EEKikAAFoJeGS/diyZcusT58+tmjRIisqKrLq1avbtm3b7KabbrILLrgg2ez5PAIIIOCNwJQpU+zSSy81BaGbN2+22rVru9eTJ0+2X/7yl97Ug4IigED8ApyCj98qZUsq4OzSpYvNnTvXBZ/KWMGn0g033GCTJk1yr/kPAQQQCLrAvHnzrF+/frZq1SoXfKq+CkSVjj76aFu6dKl7zX8IIBAsAQLQKtie7733ntWvX7/MNT/00ENlzmMGAgggECSBxx9/vMzqFBYW2uuvv17mfGYggIC/AgSgVbDt8vLyrFo16KuAnlUigIBHAsXFxab2koQAAsETIAqqgm3atWvXMtdas2ZNu/zyy8uczwwEEEAgSAJnnnlmmdXZsmWL/fa3vy1zPjMQQMBfgbgvQpo9e7a7MrF0VdWTp6u3d9llF1PwRKpYQAPsp02bZvvvv78zUyOrqz119efQoUOtW7duFWfCEggggEAABDp16mRPPvmknXvuuaZT7qGLkBo2bGhPPfWUNW3aNAC1pAoIIFBaIO4A9LDDDrO1a9eW/nz4fa1atWz48OF27bXXhqfxomyBZs2a2eLFi7kNU9lEzEEAgRwR6Nmzp82fP7/EbZgUgNKpkSM7ANXMSYG4A9ARI0bYgw8+aJdddpn95je/sSVLlrjB4ffff7+NHz/eFixYYFdeeaXttddedsopp+QkZqKVVo+neo5JCCCAQK4L6MyQ/pEQQCA3BOIKQHfu3Ol6N1966SU76qijnMzuu+/uThV/+eWX7rZBClB1O40333yTADQ39h1qiQACCCCAAAIIVEogrgBUY3J078rddtstaiWtWrUK36dN87/66quoZVI5QVdEqucwnhRa1serKENXyYf+xlPfbFpG5Q75Z1O5EimL6hDvvpZIvplY1md7ld3X8uuq7UymRPZPX03l6Xt7Intf2xOVO7QNEtnf3Iey4D+V2Vd78fncHqrs5aW4AlCdFtEY0CFDhtioUaOsQ4cOLs+ZM2ea7uH217/+1Y0Pfe655+y0004rb31Jz9OYoNAXoqLM9IhLlT3TPwoVlSue+aEvuq/l1zYK/Yunvtm2jL44ujCsoi9QtpU7VB7tP3Xq1Am99eqvvrfad3wsf6bbmkSMfN4n9KQ4fRcTqW827fSh8md6/0iFQej3Vtd56Gyob0nl93nf136v/cfHfb+i/SWuAFQ7nG6OftJJJ1nHjh1Np9+VscaBnn/++XbOOefY4MGD3ZN9TjzxxLTun+qN1XPT40kNGjRwg9orQognr0wvo0BbV4Ru2LAh5t0HMl2eRNen4E1fmo0bNyb60axYXo2t9jVfy6/naK9bty4rLBMthL63Sr6WX3cFyVRKxMjnfaJevXquPUykvpnaBvGsR+XXWcR4f7viyTNTy6gdV3uotjD0xL5MrTsV69EBbei3NBX5ZToPxQJbt251sUym153s+iq6iDDuAHTPPfe0Dz/80PQUn08++cRt0MMPP9w6d+7syqgLkEaPHu1llJ4sMp9HAAEEEEAAAQQQiF8g7gBUWSoK1xGoeuUU2eqILpQUoJIQQAABBBBAAAEEEKhIIO4A9NNPP3VXt3/33XfuNPzy5ctt1apVdvbZZ9ujjz7K/doqkmY+AggggAACCCCAgBOI+1Gcf/jDH6xHjx5u3OecOXPcDdRnzJhh06dPt7vuugtOBBBAAAEEEEAAAQTiEogrANXgY13xrjGerVu3dhnryrKDDjrIPflo4sSJca2MhRBAAAEEEEAAAQQQiCsA1eX/ujL1448/jhL7+uuvrUWLFlHTmYAAAggggAACCCCAQCyBuMeAXn/99TZw4EDr16+fHXvsse6WDG+88YY99thjdvvtt9vUqVNd/uoh1eM4SQgggAACCCCAAAIIxBKIOwD9v//7P3ezed2IXv8i04UXXhh+q/uBjh07NvyeFwgggAACCCCAAAIIRArEHYD++OOPcT1RSDd9JSGAAAIIIIAAAgggUJZA3NGi7vu5ZcsW05XvekJMZNIY0E6dOkVO4jUCCCCAAAIIIIAAAjEF4g5Ax4wZYzfccEPMx0GdfvrpNm7cuJgrYCICCCCAAAIIIIAAApECcQWgepa6bsH0pz/9yc4999yox23m5eVF5slrBBBAAAEEEEAAAQTKFIgrANUjOH/66Sc7+eSTrV69emVmxgwEEEAAAQQQQAABBCoSiOs+oIWFhda3b1+78847bdOmTRXlyXwEEEAAAQQQQAABBMoUiKsHVJ/WbZj22Wcfu++++9wFR3oSUigdddRRdvPNN4fe8hcBBBBAAAEEEEAAgTIF4g5ATzzxRGvZsqX95je/sUaNGpXIcN999y3xnjcIIIAAAggggAACCJQlEFcAumHDBps1a5bNnj3bfvnLX5aVF9MRQAABBBBAAAEEEKhQ4Ofz6OUsWrduXdt9992tqKionKWYhQACCCCAAAIIIIBAxQJx9YAqmxEjRljv3r1tyJAh1q5dO6tVq1Y49+bNm7vxoeEJvEAAAQQQQAABBBBAoAyBuAPQyy67zD0L/uKLL47KihvRR5EkPEHDHHSh12effWatW7e2Rx55xBo3bpxwPnwAAQQQ8F3gq6++suuvv95WrlxpRx55pN12222+V4nyI4BAKYG4A9DyngWfn59fKlveJiKwfft222uvvaygoMD0+uuvv3bvFy5caNzkPxFJlkUAAd8Fli5daj179jQ9AEVp0aJFNnPmTHvvvfd8rxrlRwCBCIG4A1A9C56UHoEHH3zQatSoYbrhv9KOHTtc4KkegFtvvTXmStVjOnHiRJszZ467LZbuTqD7tZIQQAABnwUuuOCCcPCpemzevNnmzp1r48ePt8MOOyxm1b777jubMGGCLVu2zLp37+7u1hJzQSYigEDWCMQdgGZNiQNYkFWrVoWDz1D11BOqnoBYSb3R3bp1i3oowKeffmoaj0tCAAEEfBVYs2ZNVNHVG6qn8cVKr732ml100UXu7JHmP/roo24Y0/Tp042zc7HEmIZAdgjEdRV8dhQ1uKU49NBDrXr16lEVPO6446KmqXe0c+fOUcGnFtTTqoqLi6M+wwQEEEDAF4Ejjjgiqj3UGZ9DDjkkqgoapjRw4MBw8Bla4IcffrBRo0aF3vIXAQSyUIAANAs2ytFHH21nnnmmK0nt2rWtTp067lTT4MGDo0qnQfllnWqfP3++qaEmIYAAAr4K3HjjjS4A1bAktYc6OB8zZozFeuDJhx9+GLM91IH4G2+84SsB5UYgJwQ4BZ8lm/kvf/mLu83VvHnzrEWLFnbCCSfELJka5LJ6Obds2cIpp5hqTEQAAV8EFHjqYPrll1+2devW2YEHHhiz91P1qV+/fpnVatCgQZnzmIEAAlUvQABa9dsgXAKdYop1mim8wH9e6KEAl19+ud1+++0lTjtVq1bNhg0b5noMIpfnNQIIIOCjwMknn1xhsY855hj3dD6Nfy99YH7//fdX+HkWQACBqhPgFHzV2Vd6zbonqwJQ9ZSqt6BVq1buFJUG4pMQQACBXBLQ1e+nnXaaeziKTtfrlnY6/a52kYQAAtkrQA9o9m6bckumm//rHwkBBBDIZQHdK1ljRPWPhAAC/gjQA+rPtqKkCCCAAAIIIIBAIAQIQAOxGakEAggggAACCCDgjwABqD/bKqqkt9xyi+29997u9iR///vfo+YzAQEEEMgFAT2449RTT7Vf/OIX7slwuj8oCQEEsluAMaDZvX3KLN3ZZ59tb731Vnj+VVdd5Z6XPHr06PA0XiCAAAK5INCuXTv3CGPVtaioyPRwj3Hjxtnhhx+eC9Wnjgh4KUAPqIeb7ZtvvikRfIaq8Mwzz9jq1atDb/mLAAIIBF7gpptuCgefkZUdNGhQ5FteI4BAlgkQgGbZBomnOHrMXFlp06ZNZc1iOgIIIBA4gWXLlsWsE21hTBYmIpA1AgSgWbMp4i/IfvvtZ7rxfKzUrFmzWJOZhgACCARS4KijjopZr9122y3mdCYigEB2CMSOYrKjbJSiDAE9Ym7s2LFRc1966SV3Y/qoGUxAAAEEAirQu3dv+/Wvf12idgUFBTGHKZVYiDcIIFClAlyEVKX8lV+5HlPXsWNHd/NlNbZ6OtKee+5Z+Qz5JAIIIOCpwLPPPmtPP/20ewJSkyZN7M9//nOZZ4k8rSLFRiBwAgSgHm9SBaB//etfPa4BRUcAAQRSI9CvXz/TPxICCPghwCl4P7YTpUQAAQQQQAABBAIjQAAamE1JRRBAAAEEEEAAAT8ECED92E6UEgEEEEAAAQQQCIwAAWhgNiUVQQABBBBAAAEE/BAgAPVjO1FKBBBAAAEEEEAgMAIEoIHZlFQEAQQQQAABBBDwQ4AA1I/tRCkRQAABBBBAAIHACBCABmZTUhEEEEAAAQQQQMAPAQJQP7YTpUQAAQQQQAABBAIjQAAamE1JRRBAAAEEEEAAAT8ECED92E6UEgEEEEAAAQQQCIwAAWhgNiUVQQABBBBAAAEE/BAgAPVjO1FKBBBAAAEEEEAgMAIEoIHZlFQEAQQQQAABBBDwQ4AA1I/tRCkRQAABBBBAAIHACGQsAF29erW9+eabtnTp0ii8uXPn2qRJk+ynn36KmscEBBBAIGgC8+fPt6lTp1pRUVGJqm3ZssXeffdde++992zbtm0l5vEGAQQQCJJARgLQ8ePH26WXXmrffvutjRgxwu66666w4Z133mmjR4+2Tz75xC644AJbtGhReB4vEEAAgaAJXHnllfbAAw+YDrwHDBhgM2bMcFVUMKr3Ckyffvppu+aaa6y4uDho1ac+CCCAgBMoSLfDjh077KmnnnJBZrt27axv3752xhlnWP/+/W3t2rX2zjvv2AsvvGDVqlWzZ5991p555hkbOnRouotF/ggggEDGBb744gtbsWKFaxO18g4dOrh27+CDD7bnnnvODjnkELv88stduS688EL74IMPrGvXrhkvJytEAAEE0i2Q9gA0Pz/fnnjiCatTp46ry+bNm23Dhg2mwPSbb76xTp06ueBTM7t06WKvvvpqiTp///33JXpFd9ttNyssLCyxTFlvFNRWr17dy16EgoL/bhqVX4a+JZVf5a5Ro4ZvRXflzcvLM9XB1/Jr3/e57PL3sfwV9Vjuvffe9uCDD4a/EzoIV5uopNPyxxxzTHie2sPZs2eXCED1Xp9Rkk/btm3d63j+83mfUFvi6z6hbaPyqy3XNvAthX6L9FfbwLcke99/i3wtf0X7e9oDUO2soeBz586dNmbMGDv22GOtadOmbjxogwYNwvtz/fr1beXKleH3evHKK6+UOGX/0ksv2T777FNimfLexBuslpdHVc5r1KhRVa4+6XWHtn3SGVVBBrVr1zb98zU1adLE16K7cvtYfrVx5SU1yLVq1XKLLF++3PWEXn311e79smXLTG1gKOn1kiVLQm/d31tuucU++ugj97p58+buDFKJBSp446NpZJV8Ln9ou0fWx6fXDRs29Km4UWX1uS3XvuPj/rNp06ao7RA5ISMBqFaowfUjR450vZHXX3+9K4OievWEhtL27dujkM8666wSvQIKaHQKK55Ut25d27hxo5c9oOrdUHCugLyiH7V4LDK9jI72dcRc+iKLTJejsuvTD53KXtEXqLL5p/tzCl7WrVuX7tWkJX99b7X/6MJF35J6QBUYVpQ0Hv7aa6+18847L9zDGU97+Je//CXcY6rvV7xtocrj8z6hdr9mzZq2atWqimizcr6CH/0GRv7eZWVBYxRK+5k6QvR91G+0b0nfK+07vrbljRs3dvuOYhnfkvad8gL/jASg2vBqbFu3bm062tcOodSsWTObNWtW2FSNS8uWLcPv9UI7fmQvoBrceL8E+jHQF97HAC5kpPL72Gipp0f/4t1WJTZ6lryRu6/l177vc9l9Ln9Fu++cOXPcOPcrrrjCevToEV5cZ4UiAyy93nXXXcPz9UJtaGSKdVeRyPmRr302VRvuc/lVdl/bk9Bpd1/Lr++A9h+f20Nfyx+KYyLbocjXGRmQMnz4cDfY/rrrrgsHnyrEQQcdZBqUv7RG25UAADxrSURBVHjxYrdz/POf/zQNxichgAACQRTQreZ0dbvaxMjgU3Xt3r27vf76666HU8vpVkydO3cOIgN1QgABBCztPaA62p8+fbr7N27cuDD52LFj3QVIgwYNsoEDB5q6mXfffXc7++yzw8vwAoFYAuoF/9e//uUuwjjuuOPK7eKP9XmmIVBVAmoD16xZY5dddlm4CGr7Xn75ZevZs6e7B2ifPn3c2QMNP9KdQ0gIlCfw2Wef2ccff2waNnTSSSeVtyjzEMgqgbz/nBqo8hvN6YbLGh+jsV8VpUROwWsM5fr16708Ba8xK/ph0oUKPp6C1xhWjeNL9bgVXQXcq1cvd2Gbdl3lr8a39NCNivajiua3aNHC3a0h1eWvaL2pmh8as5Wq/DKZj7632nd8fTBFsvui2ixdcKDxUxWlRE7B+7xP1KtXz939JJExrxXZZXK+yq8x5ak+DayOnNtvv90dsOh3VBcKzZw5M659J97667uo4SH6Pvr4cAR9j3Qxsu6+42PSUEXdKUPtgm8pFMeUVe6MnIIva+Wh6drB4wk+Q8vzNzcFNJZYvUQKPNWYhIJD3VM2C46jcnOjUOuUCyhYiSf4TPmKydArAT285dZbb3WdN6HgVrfoGjVqlFf1oLC5K5AVAWju8lPzRAQ0Vjjytl2hz86bN881wqH3/EUAAQSCLqDbcZW+zaB6KN96662gV536BUSAADQgGzIXqqHTS1u3bo2qqoZvkBBAAIFcEtCQitI95bpiPZ7bgOWSE3XNXgEC0OzdNpSslIDGZeqCtcijfo011TioyGmlPsZbBBBAIHACp556qrVp08bd41KVU/Cpf/fee2/g6kqFgilQ8Sj3YNabWnkqMHToUNtzzz3tsccec1fB62riI4880tPaUGwEEECgcgK6z/LkyZPthhtucHdPUM/nn/70J3chUuVy5FMIZFaAADSz3qwtBQKnn3666R8JAQQQyGUB9XjefPPNuUxA3T0W4BS8xxuPoiOAAAIIIIAAAj4KEID6uNUoMwIIIIAAAggg4LEAAajHG4+iI4AAAggggAACPgoQgPq41SgzAggggAACCCDgsQAXIXm88SpT9DfffNM9Uu2AAw6wjh07ViaLKv+MnqU9bdo0dw88PRlJj/siIYAAAokI6OlBU6ZMcY+X1J00Yj3kIpH8qmrZuXPnmp6KpGfB6zHFJAR8ESAA9WVLpaCcxx13nC1YsMDlpOfK3nTTTXbBBRekIOfMZaHyK+jUfT937NjhHsk5a9Ys96zizJWCNSGAgM8COohVO6LH+e7cudM9Z/vtt992t3jzqV5PPvmk3XjjjabHWevxxHvssYc7ONctmkgIZLsAe2m2b6EUle+uu+6yTz/91DW0Cj6VRowYYZ999lmK1pD+bDZv3mzdu3d3j93UM4/V4Oo2JDwLPv32rAGBIAkcdNBBtnTpUlM7EmoPzzjjDFOvqC/piy++sOuuu87ULqoOxcXFtmjRIrvjjjt8qQLlzHEBAtAc2QEmTpwYVVM9xu29996Lmp6tExYuXGj169cvUTw1ul9++SXPgi+hwhsEEChPQI/vVdsRmRTIffPNN5GTsvq12u7ST4DTs+DfeOONrC43hUMgJEAAGpII+N/GjRu73sLIaqoBLh3QRc7Pttf16tVz47VKlyvW8+FLL8N7BBBAICRQOnDTdJ2W96k91JhVnXovnTQWlISADwIEoD5spRSUceTIkSUCUPV+qhegT58+Kcg9M1m0atXK+vXrZ7Vq1QqvUBcgjRo1KqonILwALxBAAIFSAsOHD4+6eLF379626667lloye9+qvM2aNXOPJA6VUkOSxo4dG3rLXwSyWoAANKs3T+oKp+enf/TRR7bvvvvabrvtZqeddprNnz/ffBusrnGr1157rbtYYJ999rExY8bYOeeckzoockIAgcAL9O3b1x5++GHr0KGDtW/f3l3Ic88993hVb3Ui6MKpY4891rXpnTt3Nt3lpGnTpl7Vg8LmrgBXwefQtt9ll11s0qRJ3td40KBBpn8kBBBAoLICRx99tOmfz0kdCPfff7/PVaDsOSxAD2gOb3yqjgACCCCAAAIIVIUAAWhVqLNOBBBAAAEEEEAghwUIQHN441N1BBBAAAEEEECgKgQIQKtCnXUigAACCCCAAAI5LMBFSDm88X2tup6A9P7777tnwevJSLoalIQAAgjkooAe0KEn2un+n926dctFAursqQC/3J5uuFwt9pIlS6xXr17unqbbt293j+OcPXu2NWzYMFdJqDcCCOSowD/+8Q+7+uqr3Q3p9VhR3YppwoQJJe75nKM0VNsDAU7Be7CRKOJ/BfTEo4MPPtg9v1lPLQk9C37AgAEQIYAAAjkl8NVXX9ngwYNt06ZNrk1U5T///HO79957c8qByvorQADq77bLuZLrVJMexxmZ9DjRTz/9lGfBR6LwGgEEAi+gm9CXfqSozgqNHz8+8HWngsEQIAANxnbMiVroEZxqYEsnngVfWoT3CCAQdAEdjMca/96oUaOgV536BUSAADQgGzIXqtGmTRv3CNHSz4IfNmxY1HOdc8GDOiKAQO4K6FnwCjarV68eRtCz4O+6667we14gkM0CXISUzVuHskUJjBo1yl1w9Pzzz1vt2rXt4osvtrPOOitqOSYggAACQRaoUaOGvfPOO9avXz+bO3euuwr+zjvvtFatWgW52tQtQAIEoAHamLlSlaFDh5r+kRBAAIFcFlAQOm7cuFwmoO4eC3AK3uONR9ERQAABBBBAAAEfBQhAfdxqlBkBBBBAAAEEEPBYgADU441H0RFAAAEEEEAAAR8FCEB93GqUGQEEEEAAAQQQ8FiAANTjjUfREUAAAQQQQAABHwUIQH3capQZAQQQQAABBBDwWIAA1OONR9ERQAABBBBAAAEfBQhAPdlqb7zxhh122GG2995728CBA23nzp2elJxiIoAAAqkTKC4utttuu826dOni/nEfzNTZkhMCmRTgRvSZ1K7kuqZOnWqDBg2ybdu2uRzefPNN69Onjz333HOVzJGPIYAAAn4KnHvuuTZ58uRw4a+99lpbt26dOzAPT+QFAghkvQA9oFm/icwGDx4cDj5V3K1bt9qsWbNs+vTpHpSeIiKAAAKpEVi8eHGJ4FO5btmyxfSIXhICCPglQADqwfbSKafSKS8vzzZt2lR6Mu8RQACBwAps2LDB6tevH1W/zZs3R01jAgIIZLcAAWh2bx9XumOOOcby8/NLlHTNmjXWuXPnEtN4gwACCARZYI899rAGDRqUqKLaxrp165aYxhsEEMh+AQLQ7N9G7vRSYWGh1ahRwzW+amx1UVKjRo08KD1FRAABBFIjULNmTXvxxRddZuoJbdiwobVr184+/vjj1KyAXBBAIGMCXISUMerKr0jB57x58+ydd94xnYI65JBDrHHjxpXPkE8igAACngq0adPG5s+fb++//74VFBS4u4NUr17d09pQbARyV4AA1KNt371796RKq9P2f/nLX2zZsmV2+OGH2/nnn59UfnwYAQQQqAqB2rVr29FHH53UqmfPnm0PPPCAu6izf//+1rVr16Ty48MIIJCYAAFoYl7eLq1B+rqHqHoKdDuniRMn2gsvvGCvvfaat3Wi4AgggEBlBD788EM77bTTwncXGT9+vDs479evX2Wy4zMIIFAJAcaAVgLNx49cddVV7kKm0L1EVQed1icA9XFrUmYEEEhG4KSTTgoHn6F8RowYYStXrgy95S8CCKRZgAA0zcDZkv3ChQttx44dJYqjYPT7778vMY03CCCAQNAFatWqFVVFXeC0YsWKqOlMQACB9AgQgKbHNety3X///d3p98iC6Yb27du3j5zEawQQQCDwAq1atYqq46pVq2yXXXaJms4EBBBIjwABaHpcsy7X66+/3p1yCl0tqqP93/72t3bEEUdkXVkpEAIIIJBOgYcffthlr6voq1X778/gY4895m7rlM71kjcCCPwswEVIP1sE+pWuGtVj7HTVp04zHXjggXb88ccHus5UDgEEEIgl0KFDB/v888/tiSeecAfmOhjXRZokBBDInAABaOasq3xNemLIH/7whyovBwVAAAEEqlqgSZMmduWVV1Z1MVg/AjkrwCn4nN30VBwBBBBAAAEEEKgaAQLQqnFnrQgggAACCCCAQM4K5BX/J/lUez2KUgPH40labvv27fEsmnXLaGC8nv2+ZcsW82wTOUuVPy8vL+rWT1kHXUaBdJGW9p3St64qY/Gsmxx64EDWFSyOAoUuDNFdGnxLO3fuNI23zlTSAybiTewT8Uqlfjnt02pLfGzL1Y6rPfT1t0jl1/AzX2MB2Wvf8bH8utVjvXr1yvxCxRfJlfnxzM8oKiqKe0M0aNDA1q9fb/pR8C1pp9Pz3teuXetlEKTgWT94Gzdu9I3elbdFixamfc3X8jdq1MhWr17tpb2+t9p3fC1/JgPQRIx83if0I1ZYWOjtPqHyJ/LblU1fXH0X9Xuk39LIB5lkUxnLK4uCf+076rzyMTVr1sx0oCl/35L2m/KSdwFoeZVhXu4KvPjiizZlyhRr3ry5XXPNNRbrRtO5q0PNEUAgVwQUrNx3333urie6//OAAQNyperU0zMBAlDPNhjFjRYYOHCg/etf/wrf51S3mtItVnSVKwkBBBDIFQGdqt1jjz1cj58C0eeee850f9Np06blCgH19EiAi5A82lgUNVrg/fffd8+zD50a0l+N9xk6dGj0wkxBAAEEAiwwatQo1/5Fjg3W45aff/75ANeaqvkqQADq65aj3E7gu+++szp16pTQUC/A/PnzS0zjDQIIIBB0gblz50ZdM7Bp0yZbuHBh0KtO/TwUIAD1cKNR5J8F2rVr9/Ob/73SoHOdhiIhgAACuSSgpznFuvAjVjuZSy7UNTsFCECzc7tQqjgFunbtascdd1x4aV19rwuQxo4dG57GCwQQQCAXBC677DJ3uyQdhCvp6u+OHTta7969c6H61NEzAS5C8myDUdxogTFjxthRRx3lBto3bdrUBg8e7Bre6CWZggACCARXQAHnkiVL3AG4/nbq1Mn69esX3ApTM68FCEC93nwUPiRw0kknmf6REEAAgVwW0ENALr300lwmoO6eCHAK3pMNRTERQAABBBBAAIGgCBCABmVLUg8EEEAAAQQQQMATAQJQTzYUxUQAAQQQQAABBIIiQAAalC1JPRBAAAEEEEAAAU8ECEA92VAUEwEEEEAAAQQQCIoAAWhQtiT1QAABBBBAAAEEPBEgAPVkQ1FMBBBAAAEEEEAgKAIEoEHZktQDAQQQQAABBBDwRIAA1JMNRTERQAABBBBAAIGgCBCABmVLUg8EEEAAAQQQQMATAQJQTzYUxUQAAQQQQAABBIIiQAAalC1JPRBAAAEEEEAAAU8ECEA92VAUEwEEEEAAAQQQCIoAAWhQtiT1QAABBBBAAAEEPBEgAPVkQ1HMsgXWrVtn5557ru21117Wvn17++CDD8pemDkIIIBAgAVmzZplv/71r61jx452yCGH2MqVKwNcW6rms0CBz4Wn7Ajs2LHDNbT5+fmm10qnn366jRs3zrp27QoQAgggkDMCP/74ox177LHh+q5fv94OPfRQmzFjhjVs2DA8nRcIZIMAPaDZsBUoQ6UFXnnlFatdu3Y4+FRG27dvt5EjR1Y6Tz6IAAII+CgwYsQIy8vLCxe9uLjYtm3bZk8++WR4Gi8QyBYBAtBs2RKUo1ICRUVFVq1a9G68YcOGSuXHhxBAAAFfBdTjqaAzMikAVTtJQiDbBKJ/ubOthJQHgXIENNZp8+bNJZYoLCy0E088scQ03iCAAAJBF+jdu3eJHlDVd+fOnXbMMccEverUz0MBAlAPNxpF/lmgTZs29re//c1N0BinunXrujFQQ4YM+XkhXiGAAAI5IHDyySdb//79XU0bN25s9evXt7Fjx1rnzp1zoPZU0TcBLkLybYtR3iiBww8/3D7//HP74osvrFGjRtapU6eoZZiAAAII5ILArbfeauedd54tX77c2rZta61bt86FalNHDwUIQD3caBQ5WqBJkybWo0eP6BlMQQABBHJMQLej0z8SAtkswCn4bN46lA0BBBBAAAEEEAigAAFoADcqVUIAAQQQQAABBLJZgAA0m7cOZUMAAQQQQAABBAIoQAAawI1KlRBAAAEEEEAAgWwWIADN5q1D2RBAAAEEEEAAgQAKEIAGcKNSJQQQQAABBBBAIJsFuA1TNm8dyoZAhgR0H9WpU6e6G/mfc845Vr169QytmdUggAAC2SUwceJEW7hwoe2666523HHHZVfhAlQaAtAAbUyqgkBlBJ599lnTk6MKCgqsWrVqNmzYMJs9e7bpyVIkBBBAIJcEzjzzTJs5c6Zt2bLFtm/f7p4i9eqrr+YSQcbqyin4jFGzIgSyT2DRokV25ZVXuudFb9261TZv3mz5+fl2xRVXZF9hKRECCCCQRoFx48bZO++8Yxs3bnTBp1alg/FnnnkmjWvN3awJQHN321NzBGL2dO7YscM+/vhjdBBAAIGcEpgxY0ZUfdUT+v7770dNZ0LyAgSgyRuSAwLeCjRv3jx8pB9ZCcaARmrwGgEEckGgVatWVlhYWKKqagtbt25dYhpvUiNAAJoaR3JBwEuBLl262JFHHlmi7DoF//zzz5eYxhsEEEAg6AK///3vw8OQVFcFn9u2bXNj5INe96qoHwFoVaizTgSySOCBBx6wkSNH2oEHHmhHH320TZ482fbYY48sKiFFQQABBNIvUKtWLdO4+AEDBthhhx1mffr0sblz53JXkDTRcxV8mmBzPdvPPvvMXdiy11578eX1YGcYOHCg6R8JAQRSK7Bp0yabNWuWu7hvn332SW3m5JZyAd0N5Kabbkp5vmQYLUAAGm3ClCQENGD7jDPOsHnz5llxcbGtXbvWPv30U9NYQxICCCCQSwLqTTv55JPdLX3WrVtnbdq0sbfffpuD8lzaCahrmQKcgi+ThhmVEejRo4d98skntmbNGhd8Ko9TTjnFjaOpTH58BgEEEPBRQD2fXbt2tWXLltnq1atNd5dYvHixu8+uj/WhzAikWoAANNWiOZ7fkiVLoq6qXrVqlesRzXEaqo8AAjkkoFuZNWjQoESNd+7caa+88kqJabxBIFcFCEBzdcunqd4axF06rV+/3mrUqFF6Mu8RQACBwArUrFkzZt3UE0pCAAEzAlD2gpQKXHrppSXuo6ZHO3bo0MH23HPPlK6HzBBAAIFsFjj44INd2xd5T10FpVzgks1bjbJlUoAANJPaObCuSy65xBSEqidUp5/69u1rb7zxRg7UnCoigAACJQV0P10dgCvwbNKkiQs+9axxEgIImHEVPHtBygUuv/xyu+aaa9yVnnqmLgkBBBDIRQH1fk6aNMnq1atnRUVFUePjc9GEOiMQEqAHNCTB35QJ3HrrrbbbbrtZo0aN3FN2tm7dmrK8Y2W0fPlyO+6446xt27amR6m98MILsRZjGgIIIJBRgQ0bNribmav3U7eiu+2229K+ft3m6YADDrBf/OIX7rZP3333XdrXyQoQqIwAAWhl1PhMmQLXXXedPfzww6ZbkOiKz2+++cbOPffcMpdPdsbmzZtdY6t7jYYC3SFDhti//vWvZLPm8wgggEClBXQfZD2I45133gm3Tffee69rHyudaQUfXLBggZ111lmmg3L1uKoN1tPNfvzxxwo+yWwEMi9AAJp580Cv8emnn3bP0g1VUs/R1VORFIimI73++utWt27dElkrEL3rrrtKTOMNAgggkEkB3YapTp06LggMrVcP6rjvvvtCb1P+N1YPq666HzduXMrXRYYIJCtAAJqsIJ8vIVBYWFjivd6oAUzXrUe2b99ueXl5UetUzygJAQQQqCoBtU2xbj+XznHxobNAkXVW26uOABIC2SaQ0YuQNB5GvWHdunULO+hRZT/88EP4vcbKtG/fPvyeF34J/L//9//sH//4R4mjfm33dN2G6aijjrLSDbqC4HSe9vdri1DaygisWLHCPcFGY4rVJqUjffXVV+6WZRq7HEp6iph6yUJJp3AbN24cestfjwQ0DrN27druKUihYqttOuaYY0JvU/63X79+prNCkUkB6EknnRQ5idcIJCQwf/58N6xO7VGsTqaEMotYOGM9oOqRuvHGG238+PERqzc3Huaxxx5zQYsClxkzZpSYzxu/BO644w7bddddraCgwBo2bGj77LOPzZ49O2YvZSpqpuDgzTffdFnptk/6cvTv39/9S0X+5JF7As8884wdfvjh7uKR/fbbLy0XtX377bd21VVX2Zw5c8LA6jG7+uqrw22h2sPvv/8+PJ8XfgmoLXrttddcoXUVvE7H6wD97rvvTltFjjzySBs+fLjLXxeB6uDl2WefdRckpW2lZBxYAY1jHjx4sNtvdfuwPfbYw/S0w1SljPSAavzfH//4R3dfyNKPJps3b56NGjXKXTWdqkqRT9UJ6LYj77//vi1dutS08+6yyy6mm9GnM3Xs2NE0+F4/6vXr13dXfqZzfeQdXIEPPvjABYGRNdR9bdXwdunSJXJypV/rIFwH3aXbQl2t3KZNG9ceVjpzPphVAs2aNbOFCxeGLwLS9k13uvDCC6137962cuVK1/6W3s/SvX7yD46AbqmoHvXIIW06iJo+fbo7oEq2phkJQHVF9PXXX+++EKEjQhVc0/WccJ3u0q0jjjjiiKjgQYOndWFLKI0ePdr9GITel/c3Pz/f3YuyvGWydV5oXKOOYn1ManhVB12FmamkntdUJZVdPRaxHi2aqnWkMx/t+02bNk3nKtKWt8ou/6oov3odSyeVZeLEiXGdOtVBV0VJ+9QjjzziesKUdyjpYFwBital0/C9evVyp3BD8/VXB/JffPGFm6Te/wcffDBydrmvfd4ndBCrf1WxT5SLGufM1q1buwPyePaPOLMsd7FUOoX2UZ3RylT5y61cgjNVfv1L5anjBIuQ1OL63qrNKOvRrkllXsGHJ0+eXCL41OLaB+bOnRtXexg5nCjWqjISgO67775u3W+99VaJMqjXSgX88MMPHbCi7fPOO8+OP/748HItWrSwTp06hd+rhy3eAdXa6eJdNryCLHmhxlansXVazscvfegHQ+X3McleY6d8Lb/P+77Krv2nKr67umhE64/8zqksmh5PefS5WBeeRH4HIscARq7n66+/dg37/vvv73rzH3roIXv88cdLBF3qiVV5lHRaN54yhdbt8z6hdt/38vvclod+izLZoRDab5P9q/1GQZyvbbnKLvdEvuvJmoU+rzvMqJMwMilmi/e7GNm+ReYRep2RADS0stJ/f/nLX7rxTqFePl2o8uijj5YIQHv06GH6F0rqLV27dm3obbl/deph/fr1Ge2FK7dACczU0Y6O2FT+dF1BnkBxEl5UP8L60Sh9gVDCGVXRB2Sv0w6+ll/fqXi/J1VEXOZq9b3VvlMV5df44SeeeKJEY6/v34ABA+Iuj3rOK5N+97vfmf7pwhUlNfTqDdWFJaE0cODA0Ev3V0Nd4k0+7xMKtvWdrIp9Il7f8pbz+UlI+i7KXheTVkUQVJ5rPPMUPIfKH8/y2baMfkvVFigWyHTS8COdvdb6lXTwq99EXWAXz3exol7b9A7Oq0BrzZo1Ja4Q1NNzdMNcH4+yKqgqsxFAwAMBPT1Gw4RCp710R44pU6aU6IVMVzV0wVGoodc61B4mEmCmq1zkiwACuSlw9tlnu2E/qr0ORNQZqDM16gFNRarSHlBF0FdeeaW7Sk9HKBMmTHAVDJ1iSkUFyQMBBBBIREB3bli8eHEiH0nJshoHryfYDB061I2PV+B7ySWXpCRvMkEAAQQqIxA6M1OZz1b0mSrtAVVvw6mnnmqDBg0yRdp6nKJOgZEQyCWBadOmWefOna1du3butlW6epWUewKnn366O82pcfBnnHGGu+o+VVfe554mNfZVQE+x051N2v7n/riKD3wdu+mrfybLnfefQaIVX7aZ5hLplLvGl+gWOhUljQGNd4f0fQyo7uGmHhHGgFa0V6R+vi5+0z6Z7jGguvI5coyzTm1ov9VtLuL5PpRVc433W716dVmzs3p6aAzoTz/9lNXlLKtwLVu2LGtWXNN1dxANAaho/JQyS+QUvc/7RGgMqNp/H5PvY0B1Vb2+j+keA3rzzTe760BCt/3R+Ee1jxqXXdnk+xhQ3VFGHlUxBrSy5qHPqQ0r70EaVdoDGiqkTrkn82Mbyoe/CPgmMGLEiBJF1vGgHqf34osvlpjOm9wR0EVI8QSfuSNCTXNF4L777itx2x+1hToY1x1zSMETyIoANHis1AiB+ARi9bBW1S034isxSyGAAALpESjrwCvdPa/pqQ25ViRAAFqREPMRSKPAWWedFZW7TrfoJuQkBBBAIJcEevbsGb7PbajeOvWsu1GQgidAABq8bUqNPBLQ83VDF95pjJ6eNvL888+7C5I8qgZFRQABBJIWGDt2rHvAgnpC1RbqQuXPP//cjYlOOnMyyDqBKr0NU9ZpUCAEqkDgT3/6k1100UVukL+edKNAlIQAAgjkmoACzzlz5rh/Ou2uh9Xo/pOkYAoQgAZzu1IrzwR233130z8SAgggkOsCCjxJwRfgFHzwtzE1RAABBBBAAAEEskqAHtCs2hwUBoHEBBYuXOge4KB7rXXv3j2xD7M0AgggECAB3bJJ94rVjey5cCn7NywBaPZvI0qIQEyB8ePHu0fZaozUunXr3FOUJk2alLLn9MZcKRMRQACBLBQYOHCg6XG2eoiDHvN94403uqcsZmFRKdL/BDgFz66AgIcCc+fOtd///vdWVFTkgk9VQdP0GDsSAgggkEsCjz/+uL322mvu6XUKPpVGjhxpH3/8cS4xeFdXAlDvNhkFRsDs3XfftVq1apWg0CNqJ0yYUGIabxBAAIGgC/zzn/+MqqIea/zWW29FTWdC9ggQgGbPtqAkCMQtULduXdMzjksn3TuPhAACCOSSgG5dp4AzMql9rFevXuQkXmeZAAFolm0QioNAPAKnnHKKNWnSpMQ98tQA33PPPfF8nGUQQACBwAgMGzasxBOUNA50y5Ytdt555wWmjkGsCAFoELcqdQq8gC48mjZtmnXr1s2aN2/ubtisMVCtWrUKfN2pIAIIIBAp0LZtW9MV8LryvWXLlnbMMcfY7NmzSxygRy7P6+wQiD6Hlx3lohQIIFCBgILQv/3tbxUsxWwEEEAg+AKtW7d2B+XBr2lwakgPaHC2JTVBAAEEEEAAAQS8ECAA9WIzUUgEEEAAAQQQQCA4AgSgwdmW1AQBBBBAAAEEEPBCgADUi81EIRFAAAEEEEAAgeAIEIAGZ1tSEwQQQAABBBBAwAsBAlAvNhOFRAABBBBAAAEEgiNAABqcbUlNEEAAAQQQQAABLwQIQL3YTBQSAQQQQAABBBAIjgABaHC2JTVBAAEEEEAAAQS8ECAA9WIzUUgEEEAAAQQQQCA4AgSgwdmW1AQBBBBAAAEEEPBCgADUi81EIRFAAAEEEEAAgeAIEIAGZ1tSEwQQQAABBBBAwAsBAlAvNhOFRAABBBBAAAEEgiNAABqcbUlNEEAAAQQQQAABLwQIQL3YTBQSAQQQQAABBBAIjgABaHC2JTXJQYGVK1fau+++a3Pnzs3B2lNlBBBA4GeBBQsW2Pvvv28rVqz4eSKvslagIGtLRsEQQKBcgenTp9v5559veXl5tnr1ajv++OPtoYceKvczzEQAAQSCKHDLLbfY448/bjVq1HDt4QMPPGC//e1vg1jVwNSJHtDAbEoqkksCixcvtlNPPdXWrFnjGlvV/bXXXrNHHnkklxioKwIIIGAvvvii3XvvvbZx48Zwe3jhhRfanDlz0MliAQLQLN44FA2BsgSmTp1qtWvXLjG7uLjYnnvuuRLTeIMAAggEXWDcuHFRVSwoKLBJkyZFTWdC9ggQgGbPtqAkCMQtUL16dcvPz49avnRQGrUAExBAAIGACcRq9xSAFhYWBqymwaoOAWiwtie1yRGBk046yerUqWPVqv38FVZAOnr06BwRoJoIIIDAfwWuvvpqU8AZShoXv3nzZjvnnHNCk/ibhQI//3plYeEoEgIIxBbQEf+0adOsdevW7ii/ZcuW9uSTT1r79u1jf4CpCCCAQEAF9t57b3v11VfdsCQdmB944IE2c+bMqGFKAa2+t9X6+ZDB2ypQcARyU6BevXr2wQcf5GblqTUCCCAQIbDffvvZ/PnzI6bwMtsF6AHN9i1E+RBAAAEEEEAAgYAJEIAGbINSHQQQQAABBBBAINsFCECzfQtRPgQQQAABBBBAIGACBKAB26BUBwEEEEAAAQQQyHYBAtBs30KUDwEEEEAAAQQQCJgAAWjANijVQQABBBBAAAEEsl2AADTbtxDlQwABBBBAAAEEAiZAABqwDUp1EEAAAQQQQACBbBcgAM32LUT5EEAAAQQQQACBgAkQgAZsg1IdBBBAAAEEEEAg2wUIQLN9C1E+BBBAAAEEEEAgYAIEoAHboFQHAQQQQAABBBDIdgEC0GzfQpQPAQQQQAABBBAImAABaMA2KNVBAAEEEEAAAQSyXaAg2wtYunz5+fmWl5dXenLM99WqVbPq1avbzp07Y87P5omqp1JBQYGpHr4llVt1kL+vyefyh/Z9H+1Vdn3Hfd53MuWeiJHP+0So3U+kvpnaBvGsR/ZqE+P97Yonz0wto3Irhf5mar2pWo/2HZ/bcu0zvn53K9rfvQxA4/0ihDZacXFxqvbljOUTqqMaXB/LH/rS16hRI2NmqVyRvjiqg8/l97Xs+t7K38fyZ/q7moiRr6b6Xvu8T6j8oQBIf31LoTLrN0nbwbekMvvelvtc/vL2F+8C0K1bt9r27dvLq1N4nr4wmzZt8rIHtGbNmla7dm0rKiqyHTt2hOvkywv9MCp43rhxoy9FLlHOunXrmvY1X8svf1/Lru+tgiVfy9+gQYMS+1I63yRi5PM+EQoiEqlvOt0TzVvlV1se729Xovmnc3m143Xq1LHNmzfbtm3b0rmqtOSt9kQHhr7uO4oD5O5j+RXH/P/27jtWivJr4Pi5UqT3jogIKkREQZohJCiXYsQ/jBKBhKIion+gRkUNQiQqEkxEUZoJIUaMQYxREVCUIgiEAFJEBIMUASkCgvS67z2P74y7e+/MLj/u7s7z7HcSvTOzszvn+ZzZh7NTwwb7fs6EtYbXEEAAAQQQQAABBCIvQAEa+RQRIAIIIIAAAggg4JYABahb+aQ1CCCAAAIIIIBA5AUoQCOfIgJEAAEEEEAAAQTcEqAAdSuftAYBBBBAAAEEEIi8AAVo5FNEgAgggAACCCCAgFsCFKBu5ZPWIIAAAggggAACkRegAI18iggQAQQQQAABBBBwS4AC1K180hoEEEAAAQQQQCDyAhSgkU8RASKAAAIIIIAAAm4JUIC6lU9agwACCCCAAAIIRF6AAjTyKSJABBBAAAEEEEDALQEKULfySWsQQAABBBBAAIHIC1CARj5FBIgAAggggAACCLglQAHqVj5pDQIIIIAAAgggEHkBCtDIp4gAEUAAAQQQQAABtwQoQN3KJ61BAAEEEEAAAQQiL0ABGvkUESACCCCAAAIIIOCWAAWoW/mkNQgggAACCCCAQOQFKEAjnyICRAABBBBAAAEE3BKgAHUrn7QGAQQQQAABBBCIvAAFaORTRIAIIIAAAggggIBbAhSgbuWT1iCAAAIIIIAAApEXoACNfIoIEAEEEEAAAQQQcEuAAtStfNIaBBBAAAEEEEAg8gIUoJFPEQEigAACCCCAAAJuCVCAupVPWoMAAggggAACCERegAI08ikiQAQQQAABBBBAwC0BClC38klrEEAAAQQQQACByAtQgEY+RQSIAAIIIIAAAgi4JUAB6lY+aQ0CCCCAAAIIIBB5AQrQyKeIABFAAAEEEEAAAbcEKEDdyietQQABBBBAAAEEIi9AARr5FBEgAggggAACCCDglgAFqFv5pDUIIIAAAggggEDkBShAI58iAkQAAQQQQAABBNwSoAB1K5+0BgEEEEAAAQQQiLwABWjkU0SACCCAAAIIIICAWwIUoG7lk9YggAACCCCAAAKRF6AAjXyKCBABBBBAAAEEEHBLgALUrXzSGgQQQAABBBBAIPICFKCRTxEBIoAAAggggAACbglQgLqVT1qDAAIIIIAAAghEXoACNPIpIkAEEEAAAQQQQMAtAQpQt/JJaxBAAAEEEEAAgcgLlI18hASIQAQE1qxZIzt37pTGjRtLly5dSozo1KlTsmjRIrlw4YJ0795datSoUeJyzEQAAQRsFbh8+bIsWLBAjh8/Lp06dZLmzZuX2JQ9e/bI8uXLpXLlynL//ffLNdewv6tEqDyeSQGax8mn6ekJvPzyy/LZZ59JQUGBnDx5Unr06CEffvhhwpuPHDkihYWFcvbsWbl06ZJZ7ocffpCbbropYTkmEEAAAVsFtPjs1auX/PHHHxKLxUw/N336dFNgxrdp6dKlMnjwYLn22mvl4sWL8uSTT8r27dulUqVK8YsxnucC/CTJ8w2A5ocLfPPNN6bY1L2bWnzqoJ3r7Nmz/TdqR9y2bVs5dOiQ2SvgLdevXz9TkPoLMoIAAghYLDB8+HBTSJ44ccLvD0eMGCG7d+/2W3Xw4EEZMGCAORKkfaH+KC9Tpow8++yz/jKMIKACFKBsBwiECCxbtqzYq3qI/fvvv/fnawere0e1EI0fTp8+ndAxx7/GOAIIIGCbwLp16+TcuXMJYetezrVr1/rzNmzYUOz0Iz0q9OOPP/rLMIKAClCAsh0gECJQs2ZNcxgpfpGyZctKnTp1/FlafJYvX96f9kb0HKlq1ap5k/xFAAEErBaoVatWsfj1h3Z8P6fnvmvBmTxwDmiyCNMUoGwDCIQI6CEn/YWvRacO2onqOU2jR4/231WhQgUZM2ZMsUJ10KBB0rBhQ385RhBAAAGbBSZMmJBwMZH2i/Xr1zfnxXvt0guTOnfunNAf6nKzZs3yFuEvAkaAApQNAYEQgapVq4oeUtILjG655RbzV6eTT6YfOHCgzJw5U1q3bi2tWrWScePGyfjx40M+mZcQQAABuwT0XHc9lK79XLNmzWTo0KGyatWqYo3QizSHDBkiN954o9xxxx0yZ84cuf3224stx4z8FigoOm8t8cS1iHv89ddfZg9UOmFWr15d9GRpvXLPtkH3uunhDr2wpaTDGVFvjx6SLleunOjFOzYO+qteT6C3NX49deDvv/+2kV70e6vbzuHDh62MP5t7vffv35+2kc3bhP4Q1CMN2v/bOGj8Z86cSfvfrii1Ub+LesqRfh/1/HfbBt37qtuOd3GobfHXrVvXXMiltYxtg1fHBMXNHtAgGeYjgAACCCCAAAIIZEQgqwWo/gJZsWJFsYZs27ZNFi5caO0ej2INYgYCCCCQQmDr1q2ya9euhKX0CmPtI1euXGnl3qaExjCBAAIIhAhkrQDVW9W8+uqr8uWXXyaEM3HiRHnrrbdk/fr18thjj5kb3CYswAQCCCDgmIA+Veu5556TX3/91W+ZHqLV8+aWLFliLtgYOXJksVt7+QszggACCFgukJUCdMeOHaZjTT6HQX/966O6PvjgA3nxxRelf//+8vHHH1tOSvgIIIBAsID+CNebcuu5rvGDPtxAryB+5ZVXZMqUKaK3t1m9enX8IowjgAACzgj8e2+ZDDdHO9JRo0aJPq5w/vz5/tq0MG3Tpo1/W4d27drJvHnz/Nd1RA/Px+8laN++vVSpUiVhmaAJffqCnnxs2XVWpjnebX80fhsvotL41b9ixYpB6Yn0fL23p558b2v8ersoW2PX7cbW+NPpazQvM2bMkEmTJpkHGHhfBH1UYc+ePb1J0f5wy5Yt5pY23kz9wa79qA7aN+jtbtIdbDXV9ml/ot9JW7dpjV8vyNA+xbZBv486xN+OzqY26Hav/rZuOzbHr9/ZsCErBajeskEHfYRh/KBXcMbvBdCb2Xqdq7fc4sWL5Z133vEm5fPPP5frrrvOn041ol8am4f4G/za2A5bv/RqrbHbHH9JN8e3aRvSG1rbNqTzYzG+yIwvWA8cOJBwQ2/97u/duzeBYNq0af5TZ+rVq2eOICUskGKCbSIFUAZf1h8MNg96Jb/Ng819uW47Nm4/uvMxbMhKARoUgP6yir/FkN7gO3kj0fNC9R6L3qC3xdGOOp1BO3C98CmdfxTS+bxsLqP/UOhtmPS2I/FG2Yzhatalv/T1v1Qb4NWsI5Pv1X/cdVuz9TZMWrwdO3Ysk0QZ+2z93uq2k/xjNGMrLOUPbtCgwf/0ien0h7rnVPtJHXTPSLp9oS5v8zahxY/uTLD11lx61E6vg/Byp/mwZdDvYu3atY29jfF7e59t7cttvg2T1jHJ98yO3+5zWoAq7KZNm/x4jh49WuzJMdqA+F/tV3ovNd3DEL+XwV+ZJSMuxG8JdbEwsS9GktUZNn9v/xcovdei9oHeoONNmjTxJs3f5L0g+rjXKxlsNfXi9v5eSZujsqzGbmP88THHj0fFNVUcXsze31TLR+11jdv7L2qxXW08WbkIKSjIDh06yObNm2XPnj3ml+HcuXOlY8eOQYszHwEEEHBWoGvXrrJgwQKzp0z39OmtmPTJMwwIIICAiwI53QOqh9qGDRtmHuelh5ubNm0qAwYMcNGZNiGAAAKhAvq4V70HqN4NRA+v9+vXzzzuMPRNvIgAAghYKpDVArRbt26i/8UPffr0kV69eonegDndq9vj3884AgggYKPA2LFjE8LWc9Vee+018/hgPRdepxkQQAABVwUi0cN5F6y4iky7EEAAgXQFbL/aON12shwCCOS3QE7PAc1velqPAAIIIIAAAgjkpwAFaH7mnVYjgAACCCCAAAI5E6AAzRk9K0YAAQQQQAABBPJTgAI0P/NOqxFAAAEEEEAAgZwJUIDmjJ4VI4AAAggggAAC+SlAAZqfeafVCCCAAAIIIIBAzgQoQHNGz4oRQAABBBBAAIH8FKAAzc+802oEEEAAAQQQQCBnAhSgOaNnxQgggAACCCCAQH4KUIDmZ95pNQIIIIAAAgggkDMBCtCc0bNiBBBAAAEEEEAgPwUoQPMz77QaAQQQQAABBBDImUBBrGjI2dpZcaDAsmXL5IknnpCFCxdKkyZNApfjhcwItG/fXh5//HGTg8ysgU8NEhgzZoxs2rRJvvjii6BFmJ9nAuPHj5fFixeb/jDPmp7z5up38eGHH5Y5c+ZI69atcx5PvgXQvXt36d27t7zwwgvONZ09oBFNqf4uuHz5ckSjcz8stee3WW7yrPZs+7mxj+pa9bt46dKlqIbndFzev0X0h7lJs8v9IQVobrYp1ooAAggggAACCOStQNm8bXnEG16vXj2z271SpUoRj9TN8AoLC6V58+ZuNi7irbrtttukatWqEY+S8LIp0KpVK7lw4UI2V8m6/l+gRo0a5t8i/cuQfYFu3bpJy5Yts7/iLKyRc0CzgMwqEEAAAQQQQAABBP4T4BD8fxaMIYAAAggggAACCGRBoMyrRUMW1sMqAgROnjwpa9askeuvvz5hiW3btslPP/0k1atXl/jD8OfOnZPVq1fL3r17pUGDBlKmTJmE9zGRnoAezlP3I0eOSP369aWgoMB/4+HDh2X58uXmooc6der483UkKC8JCzGRUuCXX36Rn3/+WWrVqiUVKlTwlw/bvsPy4n8AI1YLlNQfsk1kPqVh/WFQnxeWl8xH7NYagvrDsD4vKC82yVCA5jBbZ8+eFb3lzG+//SY9evTwI5k4caK5Bc358+dl8uTJ0qVLF1OInjlzRh555BE5deqUrFixQpYsWSK9evVKKJ78D2EkUODAgQPy6KOPGjf94k+fPl369OkjZcuWlfXr18szzzwjer6TztfiSM8/0yEoL4Er4oUSBZ5//nnZunWr6PY8ZcoUueuuu6RatWpmOmj7DstLiSthpnUCJfWHYX0e20TppDisPwzq88LyUjpR5c+nBPWHYdt3UF6sUyu6tQJDDgR+//33WNG91WLDhg2LFd3fy49g586dsQceeCBWdMsRM++TTz6JjRs3zozPnDkzVrTh+cvqe1etWuVPM5KewKRJk2IzZszwFx49enRs7ty5ZnrQoEGxDRs2mPGijjlWVJjGin7px8Ly4n8QIykFduzYERsxYoS/XNH9HWO6XesQtn0H5cW8kf9ZLxDUH7JNZD61Qf1hWJ8XlpfMR+zOGsL6w6A+LywvtslwDmiOfjKcPn1aRo0aJf3790+IoGiDlDZt2sg11/ybmnbt2smWLVvMMtu3bxed9ob417x5/E0toDf4HzhwoL/g8ePHzd63ixcvmlMb1F8HPTSvpz/s27dPwvLifxAjKQWaNWsm7777rlnu2LFjsnHjRmnatKmZDtq+w/KScoUsYIVAUH/INpH59AX1h2F9XlBeMh+tW2sI6g/D+rywvNimQwGao4zpEyX0djPJw/79+83hdm++HprU8xR10EMlOu0N8a958/ibWqB8+fJSrlw5s6A+XUXPp7333nvl0KFDUrly5YRTGvQc3KNHj0pYXlKvkSWSBfQJXw8++KDUrFnTnGKirwdt32F5Sf5cpu0UCOoP2SYyn8+g/jCszwvKS+ajdXMNyf1hWJ8XlhfbdChAI5Yxvago/okf+kuoYsWKJsqw1yLWDCvC+eqrr2TatGny9ttvS5UqVcwFXfH22gj11/NAsS/dlPbs2VOKTnswj5l9/fXXzYcHGSfPj89L6UbFp0VNIDn3Xn+YPJ9t4uozl6o/9Ox1Tcn+8a9dfST59wnJ/WGyr4q4+G8RBWjEtvW6deuaPW5eWLr3rWHDhmZSr8jWaW/Q8UaNGnmT/L0CgY8++kg+/fRTee+99/xDwLVr1zYXeOnVnd7gGYflxVuWv6kFDh48aO4koEvq6Q1F5zvL2rVrzRuDtu+wvKReI0vYLMA2kZ3sldQfhvV5QXnJTrTurCWoPwzr88LyYpsMBWjEMtahQwfZvHmz7Nmzx/zi0b1EHTt2NFF27dpVFixYIHq1qN6eYeXKldK2bduItSD64cyfP18WLVokU6dONed5ehHrVfCdOnUS3ROgw7Jly8whYj1MHJYX7/38TS2g5/q99NJLZhvWpfVODi1atDBvDNq+w/KSeo0sYbMA20TmsxfUH4b1eUF5yXy0bq0hqD8M6/PC8mKbDk9CynHGli5dKtoBTJgwwY/k66+/Nnvm9B6JeoGGHqLUDVJ3wY8dO9YUqHqRUr9+/aRv377++xhJT+Chhx4S/eUZf+9PPR/x6aeflt27d8vIkSPNISY11ttk3XzzzeaDg/KS3lpZyhOYNWuW6DlPephJT8IfOnSo2ZMftn2H5cX7XP7aL5DcH7JNZD6nYf1hUJ8XlpfMR+zWGoL6w7A+LygvtslQgEY0Y3pjYD0UrOcmJg8nTpww54VqUcqQGQG9QrukZx+H5SUzkbj5qZcvXzZ7QeMfsuC1NGz7DsqL917+uinANpG7vIb1eWF5yV3E9q05rD8M6vPC8mKLAAWoLZkiTgQQQAABBBBAwBEBzgF1JJE0AwEEEEAAAQQQsEWAAtSWTBEnAggggAACCCDgiAAFqCOJpBkIIIAAAggggIAtAhSgtmSKOBFAAAEEEEAAAUcEKEAdSSTNQACB6Ap4t63ZtWtXdIMkMgQQQCCLAlwFn0VsVoUAAvkpoA+P0EfqLl68WO6+++78RKDVCCCAQJwAe0DjMBhFAAEEEEAAAQQQyLwAdzLPvDFrQAABBIzA8ePHzZO2Nm7cKLfeeqsZb9CggXnt/fffN0+G2rZtm3lUbOvWrWXIkCHSqlUr9BBAAAHnBNgD6lxKaRACCERVYPDgwaJPMOndu7fMmzdP7rvvPj/Ub7/91hScs2fPNo/Z3bx5szlcv2/fPn8ZRhBAAAFXBNgD6komaQcCCERe4KmnnpI333zTxNmkSRPp27ev/PPPP1KtWjUz7/z587JixQrRx+wOHDhQWrRoIePGjZPJkydHvm0EiAACCFyJAHtAr0SLZRFAAIGrEOjcubP/7jvvvNOM//nnn/68wsJCU3x6M3r27Cnr1q3zJvmLAAIIOCNAAepMKmkIAghEXcDb06lxFhQUmHBjsZgf9g033OCP60itWrXk1KlTCfOYQAABBFwQoAB1IYu0AQEEnBDQ2zTFD9999520a9cufhbjCCCAgBMCFKBOpJFGIICACwJ6dfzMmTPlzJkz5u+GDRtEL1xiQAABBFwT4CIk1zJKexBAwFqBbt26yRtvvCHDhw+XOnXqyNSpU+Wee+6xtj0EjgACCAQJUIAGyTAfAQQQKCWBChUqSPy5nvqxer5n8ryWLVuapyXprZcaNWrknydaSmHwMQgggEBkBChAI5MKAkEAAQT+FWjcuDEUCCCAgNMCnAPqdHppHAII2CJQo0YNqVq1qi3hEicCCCBwVQIFRYeA/rsHyFV9FG9GAAEEEEAAAQQQQCC1AHtAUxuxBAIIIIAAAggggEApClCAliImH4UAAggggAACCCCQWoACNLURSyCAAAIIIIAAAgiUogAFaCli8lEIIIAAAggggAACqQUoQFMbsQQCCCCAAAIIIIBAKQpQgJYiJh+FAAIIIIAAAgggkFrg/wA29/nBWnXhvQAAAABJRU5ErkJggg==" style="display: block; margin: auto;" /></p> </div> <div id="doing-more-with-facets" class="section level3"> <h3>Doing more with facets</h3> <p>The example above was pretty useless and we’ll now try to expand on it to add some actual usability. We are going to make a faceting that adds panels with y-transformed axes:</p> <div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb34-1"><a href="#cb34-1"></a><span class="kw">library</span>(scales)</span> <span id="cb34-2"><a href="#cb34-2"></a></span> <span id="cb34-3"><a href="#cb34-3"></a>facet_trans <-<span class="st"> </span><span class="cf">function</span>(trans, <span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">shrink =</span> <span class="ot">TRUE</span>) {</span> <span id="cb34-4"><a href="#cb34-4"></a> <span class="kw">ggproto</span>(<span class="ot">NULL</span>, FacetTrans,</span> <span id="cb34-5"><a href="#cb34-5"></a> <span class="dt">shrink =</span> shrink,</span> <span id="cb34-6"><a href="#cb34-6"></a> <span class="dt">params =</span> <span class="kw">list</span>(</span> <span id="cb34-7"><a href="#cb34-7"></a> <span class="dt">trans =</span> scales<span class="op">::</span><span class="kw">as.trans</span>(trans),</span> <span id="cb34-8"><a href="#cb34-8"></a> <span class="dt">horizontal =</span> horizontal</span> <span id="cb34-9"><a href="#cb34-9"></a> )</span> <span id="cb34-10"><a href="#cb34-10"></a> )</span> <span id="cb34-11"><a href="#cb34-11"></a>}</span> <span id="cb34-12"><a href="#cb34-12"></a></span> <span id="cb34-13"><a href="#cb34-13"></a>FacetTrans <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"FacetTrans"</span>, Facet,</span> <span id="cb34-14"><a href="#cb34-14"></a> <span class="co"># Almost as before but we want different y-scales for each panel</span></span> <span id="cb34-15"><a href="#cb34-15"></a> <span class="dt">compute_layout =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb34-16"><a href="#cb34-16"></a> <span class="kw">data.frame</span>(<span class="dt">PANEL =</span> <span class="kw">c</span>(1L, 2L), <span class="dt">SCALE_X =</span> 1L, <span class="dt">SCALE_Y =</span> <span class="kw">c</span>(1L, 2L))</span> <span id="cb34-17"><a href="#cb34-17"></a> },</span> <span id="cb34-18"><a href="#cb34-18"></a> <span class="co"># Same as before</span></span> <span id="cb34-19"><a href="#cb34-19"></a> <span class="dt">map_data =</span> <span class="cf">function</span>(data, layout, params) {</span> <span id="cb34-20"><a href="#cb34-20"></a> <span class="cf">if</span> (<span class="kw">is.null</span>(data) <span class="op">||</span><span class="st"> </span><span class="kw">nrow</span>(data) <span class="op">==</span><span class="st"> </span><span class="dv">0</span>) {</span> <span id="cb34-21"><a href="#cb34-21"></a> <span class="kw">return</span>(<span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> <span class="kw">integer</span>(<span class="dv">0</span>)))</span> <span id="cb34-22"><a href="#cb34-22"></a> }</span> <span id="cb34-23"><a href="#cb34-23"></a> <span class="kw">rbind</span>(</span> <span id="cb34-24"><a href="#cb34-24"></a> <span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> 1L),</span> <span id="cb34-25"><a href="#cb34-25"></a> <span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> 2L)</span> <span id="cb34-26"><a href="#cb34-26"></a> )</span> <span id="cb34-27"><a href="#cb34-27"></a> },</span> <span id="cb34-28"><a href="#cb34-28"></a> <span class="co"># This is new. We create a new scale with the defined transformation</span></span> <span id="cb34-29"><a href="#cb34-29"></a> <span class="dt">init_scales =</span> <span class="cf">function</span>(layout, <span class="dt">x_scale =</span> <span class="ot">NULL</span>, <span class="dt">y_scale =</span> <span class="ot">NULL</span>, params) {</span> <span id="cb34-30"><a href="#cb34-30"></a> scales <-<span class="st"> </span><span class="kw">list</span>()</span> <span id="cb34-31"><a href="#cb34-31"></a> <span class="cf">if</span> (<span class="op">!</span><span class="kw">is.null</span>(x_scale)) {</span> <span id="cb34-32"><a href="#cb34-32"></a> scales<span class="op">$</span>x <-<span class="st"> </span><span class="kw">lapply</span>(<span class="kw">seq_len</span>(<span class="kw">max</span>(layout<span class="op">$</span>SCALE_X)), <span class="cf">function</span>(i) x_scale<span class="op">$</span><span class="kw">clone</span>())</span> <span id="cb34-33"><a href="#cb34-33"></a> }</span> <span id="cb34-34"><a href="#cb34-34"></a> <span class="cf">if</span> (<span class="op">!</span><span class="kw">is.null</span>(y_scale)) {</span> <span id="cb34-35"><a href="#cb34-35"></a> y_scale_orig <-<span class="st"> </span>y_scale<span class="op">$</span><span class="kw">clone</span>()</span> <span id="cb34-36"><a href="#cb34-36"></a> y_scale_new <-<span class="st"> </span>y_scale<span class="op">$</span><span class="kw">clone</span>()</span> <span id="cb34-37"><a href="#cb34-37"></a> y_scale_new<span class="op">$</span>trans <-<span class="st"> </span>params<span class="op">$</span>trans</span> <span id="cb34-38"><a href="#cb34-38"></a> <span class="co"># Make sure that oob values are kept</span></span> <span id="cb34-39"><a href="#cb34-39"></a> y_scale_new<span class="op">$</span>oob <-<span class="st"> </span><span class="cf">function</span>(x, ...) x</span> <span id="cb34-40"><a href="#cb34-40"></a> scales<span class="op">$</span>y <-<span class="st"> </span><span class="kw">list</span>(y_scale_orig, y_scale_new)</span> <span id="cb34-41"><a href="#cb34-41"></a> }</span> <span id="cb34-42"><a href="#cb34-42"></a> scales</span> <span id="cb34-43"><a href="#cb34-43"></a> },</span> <span id="cb34-44"><a href="#cb34-44"></a> <span class="co"># We must make sure that the second scale is trained on transformed data</span></span> <span id="cb34-45"><a href="#cb34-45"></a> <span class="dt">train_scales =</span> <span class="cf">function</span>(x_scales, y_scales, layout, data, params) {</span> <span id="cb34-46"><a href="#cb34-46"></a> <span class="co"># Transform data for second panel prior to scale training</span></span> <span id="cb34-47"><a href="#cb34-47"></a> <span class="cf">if</span> (<span class="op">!</span><span class="kw">is.null</span>(y_scales)) {</span> <span id="cb34-48"><a href="#cb34-48"></a> data <-<span class="st"> </span><span class="kw">lapply</span>(data, <span class="cf">function</span>(layer_data) {</span> <span id="cb34-49"><a href="#cb34-49"></a> match_id <-<span class="st"> </span><span class="kw">match</span>(layer_data<span class="op">$</span>PANEL, layout<span class="op">$</span>PANEL)</span> <span id="cb34-50"><a href="#cb34-50"></a> y_vars <-<span class="st"> </span><span class="kw">intersect</span>(y_scales[[<span class="dv">1</span>]]<span class="op">$</span>aesthetics, <span class="kw">names</span>(layer_data))</span> <span id="cb34-51"><a href="#cb34-51"></a> trans_scale <-<span class="st"> </span>layer_data<span class="op">$</span>PANEL <span class="op">==</span><span class="st"> </span>2L</span> <span id="cb34-52"><a href="#cb34-52"></a> <span class="cf">for</span> (i <span class="cf">in</span> y_vars) {</span> <span id="cb34-53"><a href="#cb34-53"></a> layer_data[trans_scale, i] <-<span class="st"> </span>y_scales[[<span class="dv">2</span>]]<span class="op">$</span><span class="kw">transform</span>(layer_data[trans_scale, i])</span> <span id="cb34-54"><a href="#cb34-54"></a> }</span> <span id="cb34-55"><a href="#cb34-55"></a> layer_data</span> <span id="cb34-56"><a href="#cb34-56"></a> })</span> <span id="cb34-57"><a href="#cb34-57"></a> }</span> <span id="cb34-58"><a href="#cb34-58"></a> Facet<span class="op">$</span><span class="kw">train_scales</span>(x_scales, y_scales, layout, data, params)</span> <span id="cb34-59"><a href="#cb34-59"></a> },</span> <span id="cb34-60"><a href="#cb34-60"></a> <span class="co"># this is where we actually modify the data. It cannot be done in $map_data as that function</span></span> <span id="cb34-61"><a href="#cb34-61"></a> <span class="co"># doesn't have access to the scales</span></span> <span id="cb34-62"><a href="#cb34-62"></a> <span class="dt">finish_data =</span> <span class="cf">function</span>(data, layout, x_scales, y_scales, params) {</span> <span id="cb34-63"><a href="#cb34-63"></a> match_id <-<span class="st"> </span><span class="kw">match</span>(data<span class="op">$</span>PANEL, layout<span class="op">$</span>PANEL)</span> <span id="cb34-64"><a href="#cb34-64"></a> y_vars <-<span class="st"> </span><span class="kw">intersect</span>(y_scales[[<span class="dv">1</span>]]<span class="op">$</span>aesthetics, <span class="kw">names</span>(data))</span> <span id="cb34-65"><a href="#cb34-65"></a> trans_scale <-<span class="st"> </span>data<span class="op">$</span>PANEL <span class="op">==</span><span class="st"> </span>2L</span> <span id="cb34-66"><a href="#cb34-66"></a> <span class="cf">for</span> (i <span class="cf">in</span> y_vars) {</span> <span id="cb34-67"><a href="#cb34-67"></a> data[trans_scale, i] <-<span class="st"> </span>y_scales[[<span class="dv">2</span>]]<span class="op">$</span><span class="kw">transform</span>(data[trans_scale, i])</span> <span id="cb34-68"><a href="#cb34-68"></a> }</span> <span id="cb34-69"><a href="#cb34-69"></a> data</span> <span id="cb34-70"><a href="#cb34-70"></a> },</span> <span id="cb34-71"><a href="#cb34-71"></a> <span class="co"># A few changes from before to accommodate that axes are now not duplicate of each other</span></span> <span id="cb34-72"><a href="#cb34-72"></a> <span class="co"># We also add a panel strip to annotate the different panels</span></span> <span id="cb34-73"><a href="#cb34-73"></a> <span class="dt">draw_panels =</span> <span class="cf">function</span>(panels, layout, x_scales, y_scales, ranges, coord,</span> <span id="cb34-74"><a href="#cb34-74"></a> data, theme, params) {</span> <span id="cb34-75"><a href="#cb34-75"></a> <span class="co"># Place panels according to settings</span></span> <span id="cb34-76"><a href="#cb34-76"></a> <span class="cf">if</span> (params<span class="op">$</span>horizontal) {</span> <span id="cb34-77"><a href="#cb34-77"></a> <span class="co"># Put panels in matrix and convert to a gtable</span></span> <span id="cb34-78"><a href="#cb34-78"></a> panels <-<span class="st"> </span><span class="kw">matrix</span>(panels, <span class="dt">ncol =</span> <span class="dv">2</span>)</span> <span id="cb34-79"><a href="#cb34-79"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb34-80"><a href="#cb34-80"></a> <span class="dt">widths =</span> <span class="kw">unit</span>(<span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="dt">heights =</span> <span class="kw">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="dt">clip =</span> <span class="st">"on"</span>)</span> <span id="cb34-81"><a href="#cb34-81"></a> <span class="co"># Add spacing according to theme</span></span> <span id="cb34-82"><a href="#cb34-82"></a> panel_spacing <-<span class="st"> </span><span class="cf">if</span> (<span class="kw">is.null</span>(theme<span class="op">$</span>panel.spacing.x)) {</span> <span id="cb34-83"><a href="#cb34-83"></a> theme<span class="op">$</span>panel.spacing</span> <span id="cb34-84"><a href="#cb34-84"></a> } <span class="cf">else</span> {</span> <span id="cb34-85"><a href="#cb34-85"></a> theme<span class="op">$</span>panel.spacing.x</span> <span id="cb34-86"><a href="#cb34-86"></a> }</span> <span id="cb34-87"><a href="#cb34-87"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_col_space</span>(panel_table, panel_spacing)</span> <span id="cb34-88"><a href="#cb34-88"></a> } <span class="cf">else</span> {</span> <span id="cb34-89"><a href="#cb34-89"></a> panels <-<span class="st"> </span><span class="kw">matrix</span>(panels, <span class="dt">ncol =</span> <span class="dv">1</span>)</span> <span id="cb34-90"><a href="#cb34-90"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb34-91"><a href="#cb34-91"></a> <span class="dt">widths =</span> <span class="kw">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="dt">heights =</span> <span class="kw">unit</span>(<span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="dt">clip =</span> <span class="st">"on"</span>)</span> <span id="cb34-92"><a href="#cb34-92"></a> panel_spacing <-<span class="st"> </span><span class="cf">if</span> (<span class="kw">is.null</span>(theme<span class="op">$</span>panel.spacing.y)) {</span> <span id="cb34-93"><a href="#cb34-93"></a> theme<span class="op">$</span>panel.spacing</span> <span id="cb34-94"><a href="#cb34-94"></a> } <span class="cf">else</span> {</span> <span id="cb34-95"><a href="#cb34-95"></a> theme<span class="op">$</span>panel.spacing.y</span> <span id="cb34-96"><a href="#cb34-96"></a> }</span> <span id="cb34-97"><a href="#cb34-97"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_row_space</span>(panel_table, panel_spacing)</span> <span id="cb34-98"><a href="#cb34-98"></a> }</span> <span id="cb34-99"><a href="#cb34-99"></a> <span class="co"># Name panel grobs so they can be found later</span></span> <span id="cb34-100"><a href="#cb34-100"></a> panel_table<span class="op">$</span>layout<span class="op">$</span>name <-<span class="st"> </span><span class="kw">paste0</span>(<span class="st">"panel-"</span>, <span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">2</span>))</span> <span id="cb34-101"><a href="#cb34-101"></a> </span> <span id="cb34-102"><a href="#cb34-102"></a> <span class="co"># Construct the axes</span></span> <span id="cb34-103"><a href="#cb34-103"></a> axes <-<span class="st"> </span><span class="kw">render_axes</span>(ranges[<span class="dv">1</span>], ranges, coord, theme, </span> <span id="cb34-104"><a href="#cb34-104"></a> <span class="dt">transpose =</span> <span class="ot">TRUE</span>)</span> <span id="cb34-105"><a href="#cb34-105"></a> </span> <span id="cb34-106"><a href="#cb34-106"></a> <span class="co"># Add axes around each panel</span></span> <span id="cb34-107"><a href="#cb34-107"></a> grobWidths <-<span class="st"> </span><span class="cf">function</span>(x) {</span> <span id="cb34-108"><a href="#cb34-108"></a> <span class="kw">unit</span>(<span class="kw">vapply</span>(x, <span class="cf">function</span>(x) {</span> <span id="cb34-109"><a href="#cb34-109"></a> grid<span class="op">::</span><span class="kw">convertWidth</span>(</span> <span id="cb34-110"><a href="#cb34-110"></a> grid<span class="op">::</span><span class="kw">grobWidth</span>(x), <span class="st">"cm"</span>, <span class="ot">TRUE</span>)</span> <span id="cb34-111"><a href="#cb34-111"></a> }, <span class="kw">numeric</span>(<span class="dv">1</span>)), <span class="st">"cm"</span>)</span> <span id="cb34-112"><a href="#cb34-112"></a> }</span> <span id="cb34-113"><a href="#cb34-113"></a> panel_pos_h <-<span class="st"> </span><span class="kw">panel_cols</span>(panel_table)<span class="op">$</span>l</span> <span id="cb34-114"><a href="#cb34-114"></a> panel_pos_v <-<span class="st"> </span><span class="kw">panel_rows</span>(panel_table)<span class="op">$</span>t</span> <span id="cb34-115"><a href="#cb34-115"></a> axis_width_l <-<span class="st"> </span><span class="kw">grobWidths</span>(axes<span class="op">$</span>y<span class="op">$</span>left)</span> <span id="cb34-116"><a href="#cb34-116"></a> axis_width_r <-<span class="st"> </span><span class="kw">grobWidths</span>(axes<span class="op">$</span>y<span class="op">$</span>right)</span> <span id="cb34-117"><a href="#cb34-117"></a> <span class="co">## We do it reverse so we don't change the position of panels when we add axes</span></span> <span id="cb34-118"><a href="#cb34-118"></a> <span class="cf">if</span> (params<span class="op">$</span>horizontal) {</span> <span id="cb34-119"><a href="#cb34-119"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">rev</span>(<span class="kw">seq_along</span>(panel_pos_h))) {</span> <span id="cb34-120"><a href="#cb34-120"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_r[i], panel_pos_h[i])</span> <span id="cb34-121"><a href="#cb34-121"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table,</span> <span id="cb34-122"><a href="#cb34-122"></a> axes<span class="op">$</span>y<span class="op">$</span>right[i], <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> panel_pos_h[i] <span class="op">+</span><span class="st"> </span><span class="dv">1</span>,</span> <span id="cb34-123"><a href="#cb34-123"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-124"><a href="#cb34-124"></a></span> <span id="cb34-125"><a href="#cb34-125"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_l[i], panel_pos_h[i] <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb34-126"><a href="#cb34-126"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table,</span> <span id="cb34-127"><a href="#cb34-127"></a> axes<span class="op">$</span>y<span class="op">$</span>left[i], <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> panel_pos_h[i],</span> <span id="cb34-128"><a href="#cb34-128"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-129"><a href="#cb34-129"></a> }</span> <span id="cb34-130"><a href="#cb34-130"></a> } <span class="cf">else</span> {</span> <span id="cb34-131"><a href="#cb34-131"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_r[<span class="dv">1</span>], panel_pos_h)</span> <span id="cb34-132"><a href="#cb34-132"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table,</span> <span id="cb34-133"><a href="#cb34-133"></a> axes<span class="op">$</span>y<span class="op">$</span>right, <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> panel_pos_h <span class="op">+</span><span class="st"> </span><span class="dv">1</span>,</span> <span id="cb34-134"><a href="#cb34-134"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-135"><a href="#cb34-135"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_cols</span>(panel_table, axis_width_l[<span class="dv">1</span>], panel_pos_h <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb34-136"><a href="#cb34-136"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table,</span> <span id="cb34-137"><a href="#cb34-137"></a> axes<span class="op">$</span>y<span class="op">$</span>left, <span class="dt">t =</span> panel_pos_v, <span class="dt">l =</span> panel_pos_h,</span> <span id="cb34-138"><a href="#cb34-138"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-139"><a href="#cb34-139"></a> }</span> <span id="cb34-140"><a href="#cb34-140"></a></span> <span id="cb34-141"><a href="#cb34-141"></a> <span class="co">## Recalculate as gtable has changed</span></span> <span id="cb34-142"><a href="#cb34-142"></a> panel_pos_h <-<span class="st"> </span><span class="kw">panel_cols</span>(panel_table)<span class="op">$</span>l</span> <span id="cb34-143"><a href="#cb34-143"></a> panel_pos_v <-<span class="st"> </span><span class="kw">panel_rows</span>(panel_table)<span class="op">$</span>t</span> <span id="cb34-144"><a href="#cb34-144"></a> axis_height_t <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertHeight</span>(</span> <span id="cb34-145"><a href="#cb34-145"></a> grid<span class="op">::</span><span class="kw">grobHeight</span>(axes<span class="op">$</span>x<span class="op">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-146"><a href="#cb34-146"></a> axis_height_b <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertHeight</span>(</span> <span id="cb34-147"><a href="#cb34-147"></a> grid<span class="op">::</span><span class="kw">grobHeight</span>(axes<span class="op">$</span>x<span class="op">$</span>bottom[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-148"><a href="#cb34-148"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">rev</span>(panel_pos_v)) {</span> <span id="cb34-149"><a href="#cb34-149"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_rows</span>(panel_table, axis_height_b, i)</span> <span id="cb34-150"><a href="#cb34-150"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb34-151"><a href="#cb34-151"></a> <span class="kw">rep</span>(axes<span class="op">$</span>x<span class="op">$</span>bottom, <span class="kw">length</span>(panel_pos_h)), <span class="dt">t =</span> i <span class="op">+</span><span class="st"> </span><span class="dv">1</span>, <span class="dt">l =</span> panel_pos_h, </span> <span id="cb34-152"><a href="#cb34-152"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-153"><a href="#cb34-153"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_rows</span>(panel_table, axis_height_t, i <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb34-154"><a href="#cb34-154"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, </span> <span id="cb34-155"><a href="#cb34-155"></a> <span class="kw">rep</span>(axes<span class="op">$</span>x<span class="op">$</span>top, <span class="kw">length</span>(panel_pos_h)), <span class="dt">t =</span> i, <span class="dt">l =</span> panel_pos_h, </span> <span id="cb34-156"><a href="#cb34-156"></a> <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-157"><a href="#cb34-157"></a> }</span> <span id="cb34-158"><a href="#cb34-158"></a> </span> <span id="cb34-159"><a href="#cb34-159"></a> <span class="co"># Add strips</span></span> <span id="cb34-160"><a href="#cb34-160"></a> strips <-<span class="st"> </span><span class="kw">render_strips</span>(</span> <span id="cb34-161"><a href="#cb34-161"></a> <span class="dt">x =</span> <span class="kw">data.frame</span>(<span class="dt">name =</span> <span class="kw">c</span>(<span class="st">"Original"</span>, <span class="kw">paste0</span>(<span class="st">"Transformed ("</span>, params<span class="op">$</span>trans<span class="op">$</span>name, <span class="st">")"</span>))),</span> <span id="cb34-162"><a href="#cb34-162"></a> <span class="dt">labeller =</span> label_value, <span class="dt">theme =</span> theme)</span> <span id="cb34-163"><a href="#cb34-163"></a> </span> <span id="cb34-164"><a href="#cb34-164"></a> panel_pos_h <-<span class="st"> </span><span class="kw">panel_cols</span>(panel_table)<span class="op">$</span>l</span> <span id="cb34-165"><a href="#cb34-165"></a> panel_pos_v <-<span class="st"> </span><span class="kw">panel_rows</span>(panel_table)<span class="op">$</span>t</span> <span id="cb34-166"><a href="#cb34-166"></a> strip_height <-<span class="st"> </span><span class="kw">unit</span>(grid<span class="op">::</span><span class="kw">convertHeight</span>(</span> <span id="cb34-167"><a href="#cb34-167"></a> grid<span class="op">::</span><span class="kw">grobHeight</span>(strips<span class="op">$</span>x<span class="op">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="ot">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-168"><a href="#cb34-168"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="kw">rev</span>(<span class="kw">seq_along</span>(panel_pos_v))) {</span> <span id="cb34-169"><a href="#cb34-169"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_rows</span>(panel_table, strip_height, panel_pos_v[i] <span class="op">-</span><span class="st"> </span><span class="dv">1</span>)</span> <span id="cb34-170"><a href="#cb34-170"></a> <span class="cf">if</span> (params<span class="op">$</span>horizontal) {</span> <span id="cb34-171"><a href="#cb34-171"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, strips<span class="op">$</span>x<span class="op">$</span>top, </span> <span id="cb34-172"><a href="#cb34-172"></a> <span class="dt">t =</span> panel_pos_v[i], <span class="dt">l =</span> panel_pos_h, <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-173"><a href="#cb34-173"></a> } <span class="cf">else</span> {</span> <span id="cb34-174"><a href="#cb34-174"></a> panel_table <-<span class="st"> </span>gtable<span class="op">::</span><span class="kw">gtable_add_grob</span>(panel_table, strips<span class="op">$</span>x<span class="op">$</span>top[i], </span> <span id="cb34-175"><a href="#cb34-175"></a> <span class="dt">t =</span> panel_pos_v[i], <span class="dt">l =</span> panel_pos_h, <span class="dt">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-176"><a href="#cb34-176"></a> }</span> <span id="cb34-177"><a href="#cb34-177"></a> }</span> <span id="cb34-178"><a href="#cb34-178"></a> </span> <span id="cb34-179"><a href="#cb34-179"></a> </span> <span id="cb34-180"><a href="#cb34-180"></a> panel_table</span> <span id="cb34-181"><a href="#cb34-181"></a> }</span> <span id="cb34-182"><a href="#cb34-182"></a>)</span></code></pre></div> <p>As is very apparent, the <code>draw_panel</code> method can become very unwieldy once it begins to take multiple possibilities into account. The fact that we want to support both horizontal and vertical layout leads to a lot of if/else blocks in the above code. In general, this is the big challenge when writing facet extensions so be prepared to be very meticulous when writing these methods.</p> <p>Enough talk - lets see if our new and powerful faceting extension works:</p> <div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb35-1"><a href="#cb35-1"></a><span class="kw">ggplot</span>(mtcars, <span class="kw">aes</span>(<span class="dt">x =</span> hp, <span class="dt">y =</span> mpg)) <span class="op">+</span><span class="st"> </span><span class="kw">geom_point</span>() <span class="op">+</span><span class="st"> </span><span class="kw">facet_trans</span>(<span class="st">'sqrt'</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> </div> </div> <div id="extending-existing-facet-function" class="section level2"> <h2>Extending existing facet function</h2> <p>As the rendering part of a facet class is often the difficult development step, it is possible to piggyback on the existing faceting classes to achieve a range of new facetings. Below we will subclass <code>facet_wrap()</code> to make a <code>facet_bootstrap()</code> class that splits the input data into a number of panels at random.</p> <div class="sourceCode" id="cb36"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb36-1"><a href="#cb36-1"></a>facet_bootstrap <-<span class="st"> </span><span class="cf">function</span>(<span class="dt">n =</span> <span class="dv">9</span>, <span class="dt">prop =</span> <span class="fl">0.2</span>, <span class="dt">nrow =</span> <span class="ot">NULL</span>, <span class="dt">ncol =</span> <span class="ot">NULL</span>, </span> <span id="cb36-2"><a href="#cb36-2"></a> <span class="dt">scales =</span> <span class="st">"fixed"</span>, <span class="dt">shrink =</span> <span class="ot">TRUE</span>, <span class="dt">strip.position =</span> <span class="st">"top"</span>) {</span> <span id="cb36-3"><a href="#cb36-3"></a> </span> <span id="cb36-4"><a href="#cb36-4"></a> facet <-<span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>.bootstrap, <span class="dt">nrow =</span> nrow, <span class="dt">ncol =</span> ncol, <span class="dt">scales =</span> scales, </span> <span id="cb36-5"><a href="#cb36-5"></a> <span class="dt">shrink =</span> shrink, <span class="dt">strip.position =</span> strip.position)</span> <span id="cb36-6"><a href="#cb36-6"></a> facet<span class="op">$</span>params<span class="op">$</span>n <-<span class="st"> </span>n</span> <span id="cb36-7"><a href="#cb36-7"></a> facet<span class="op">$</span>params<span class="op">$</span>prop <-<span class="st"> </span>prop</span> <span id="cb36-8"><a href="#cb36-8"></a> <span class="kw">ggproto</span>(<span class="ot">NULL</span>, FacetBootstrap,</span> <span id="cb36-9"><a href="#cb36-9"></a> <span class="dt">shrink =</span> shrink,</span> <span id="cb36-10"><a href="#cb36-10"></a> <span class="dt">params =</span> facet<span class="op">$</span>params</span> <span id="cb36-11"><a href="#cb36-11"></a> )</span> <span id="cb36-12"><a href="#cb36-12"></a>}</span> <span id="cb36-13"><a href="#cb36-13"></a></span> <span id="cb36-14"><a href="#cb36-14"></a>FacetBootstrap <-<span class="st"> </span><span class="kw">ggproto</span>(<span class="st">"FacetBootstrap"</span>, FacetWrap,</span> <span id="cb36-15"><a href="#cb36-15"></a> <span class="dt">compute_layout =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb36-16"><a href="#cb36-16"></a> id <-<span class="st"> </span><span class="kw">seq_len</span>(params<span class="op">$</span>n)</span> <span id="cb36-17"><a href="#cb36-17"></a></span> <span id="cb36-18"><a href="#cb36-18"></a> dims <-<span class="st"> </span><span class="kw">wrap_dims</span>(params<span class="op">$</span>n, params<span class="op">$</span>nrow, params<span class="op">$</span>ncol)</span> <span id="cb36-19"><a href="#cb36-19"></a> layout <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">PANEL =</span> <span class="kw">factor</span>(id))</span> <span id="cb36-20"><a href="#cb36-20"></a></span> <span id="cb36-21"><a href="#cb36-21"></a> <span class="cf">if</span> (params<span class="op">$</span>as.table) {</span> <span id="cb36-22"><a href="#cb36-22"></a> layout<span class="op">$</span>ROW <-<span class="st"> </span><span class="kw">as.integer</span>((id <span class="op">-</span><span class="st"> </span>1L) <span class="op">%/%</span><span class="st"> </span>dims[<span class="dv">2</span>] <span class="op">+</span><span class="st"> </span>1L)</span> <span id="cb36-23"><a href="#cb36-23"></a> } <span class="cf">else</span> {</span> <span id="cb36-24"><a href="#cb36-24"></a> layout<span class="op">$</span>ROW <-<span class="st"> </span><span class="kw">as.integer</span>(dims[<span class="dv">1</span>] <span class="op">-</span><span class="st"> </span>(id <span class="op">-</span><span class="st"> </span>1L) <span class="op">%/%</span><span class="st"> </span>dims[<span class="dv">2</span>])</span> <span id="cb36-25"><a href="#cb36-25"></a> }</span> <span id="cb36-26"><a href="#cb36-26"></a> layout<span class="op">$</span>COL <-<span class="st"> </span><span class="kw">as.integer</span>((id <span class="op">-</span><span class="st"> </span>1L) <span class="op">%%</span><span class="st"> </span>dims[<span class="dv">2</span>] <span class="op">+</span><span class="st"> </span>1L)</span> <span id="cb36-27"><a href="#cb36-27"></a></span> <span id="cb36-28"><a href="#cb36-28"></a> layout <-<span class="st"> </span>layout[<span class="kw">order</span>(layout<span class="op">$</span>PANEL), , drop =<span class="st"> </span><span class="ot">FALSE</span>]</span> <span id="cb36-29"><a href="#cb36-29"></a> <span class="kw">rownames</span>(layout) <-<span class="st"> </span><span class="ot">NULL</span></span> <span id="cb36-30"><a href="#cb36-30"></a></span> <span id="cb36-31"><a href="#cb36-31"></a> <span class="co"># Add scale identification</span></span> <span id="cb36-32"><a href="#cb36-32"></a> layout<span class="op">$</span>SCALE_X <-<span class="st"> </span><span class="cf">if</span> (params<span class="op">$</span>free<span class="op">$</span>x) id <span class="cf">else</span> 1L</span> <span id="cb36-33"><a href="#cb36-33"></a> layout<span class="op">$</span>SCALE_Y <-<span class="st"> </span><span class="cf">if</span> (params<span class="op">$</span>free<span class="op">$</span>y) id <span class="cf">else</span> 1L</span> <span id="cb36-34"><a href="#cb36-34"></a></span> <span id="cb36-35"><a href="#cb36-35"></a> <span class="kw">cbind</span>(layout, <span class="dt">.bootstrap =</span> id)</span> <span id="cb36-36"><a href="#cb36-36"></a> },</span> <span id="cb36-37"><a href="#cb36-37"></a> <span class="dt">map_data =</span> <span class="cf">function</span>(data, layout, params) {</span> <span id="cb36-38"><a href="#cb36-38"></a> <span class="cf">if</span> (<span class="kw">is.null</span>(data) <span class="op">||</span><span class="st"> </span><span class="kw">nrow</span>(data) <span class="op">==</span><span class="st"> </span><span class="dv">0</span>) {</span> <span id="cb36-39"><a href="#cb36-39"></a> <span class="kw">return</span>(<span class="kw">cbind</span>(data, <span class="dt">PANEL =</span> <span class="kw">integer</span>(<span class="dv">0</span>)))</span> <span id="cb36-40"><a href="#cb36-40"></a> }</span> <span id="cb36-41"><a href="#cb36-41"></a> n_samples <-<span class="st"> </span><span class="kw">round</span>(<span class="kw">nrow</span>(data) <span class="op">*</span><span class="st"> </span>params<span class="op">$</span>prop)</span> <span id="cb36-42"><a href="#cb36-42"></a> new_data <-<span class="st"> </span><span class="kw">lapply</span>(<span class="kw">seq_len</span>(params<span class="op">$</span>n), <span class="cf">function</span>(i) {</span> <span id="cb36-43"><a href="#cb36-43"></a> <span class="kw">cbind</span>(data[<span class="kw">sample</span>(<span class="kw">nrow</span>(data), n_samples), , <span class="dt">drop =</span> <span class="ot">FALSE</span>], <span class="dt">PANEL =</span> i)</span> <span id="cb36-44"><a href="#cb36-44"></a> })</span> <span id="cb36-45"><a href="#cb36-45"></a> <span class="kw">do.call</span>(rbind, new_data)</span> <span id="cb36-46"><a href="#cb36-46"></a> }</span> <span id="cb36-47"><a href="#cb36-47"></a>)</span> <span id="cb36-48"><a href="#cb36-48"></a></span> <span id="cb36-49"><a href="#cb36-49"></a><span class="kw">ggplot</span>(diamonds, <span class="kw">aes</span>(carat, price)) <span class="op">+</span><span class="st"> </span></span> <span id="cb36-50"><a href="#cb36-50"></a><span class="st"> </span><span class="kw">geom_point</span>(<span class="dt">alpha =</span> <span class="fl">0.1</span>) <span class="op">+</span><span class="st"> </span></span> <span id="cb36-51"><a href="#cb36-51"></a><span class="st"> </span><span class="kw">facet_bootstrap</span>(<span class="dt">n =</span> <span class="dv">9</span>, <span class="dt">prop =</span> <span class="fl">0.05</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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" style="display: block; margin: auto;" /></p> <p>What we are doing above is to intercept the <code>compute_layout</code> and <code>map_data</code> methods and instead of dividing the data by a variable we randomly assigns rows to a panel based on the sampling parameters (<code>n</code> determines the number of panels, <code>prop</code> determines the proportion of data in each panel). It is important here that the layout returned by <code>compute_layout</code> is a valid layout for <code>FacetWrap</code> as we are counting on the <code>draw_panel</code> method from <code>FacetWrap</code> to do all the work for us. Thus if you want to subclass FacetWrap or FacetGrid, make sure you understand the nature of their layout specification.</p> <div id="exercises-2" class="section level3"> <h3>Exercises</h3> <ol style="list-style-type: decimal"> <li>Rewrite FacetTrans to take a vector of transformations and create an additional panel for each transformation.</li> <li>Based on the FacetWrap implementation rewrite FacetTrans to take the strip.placement theme setting into account.</li> <li>Think about which caveats there are in FacetBootstrap specifically related to adding multiple layers with the same data.</li> </ol> </div> </div> <!-- code folding --> <!-- dynamically load mathjax for compatibility with self-contained --> <script> (function () { var script = document.createElement("script"); script.type = "text/javascript"; script.src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"; document.getElementsByTagName("head")[0].appendChild(script); })(); </script> </body> </html>