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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" aria-hidden="true" tabindex="-1"></a>A <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"A"</span>, <span class="cn">NULL</span>,</span> <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> <span class="dv">1</span>,</span> <span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a> <span class="at">inc =</span> <span class="cf">function</span>(self) {</span> <span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a> self<span class="sc">$</span>x <span class="ot"><-</span> self<span class="sc">$</span>x <span class="sc">+</span> <span class="dv">1</span></span> <span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span>x</span> <span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> [1] 1</span></span> <span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span><span class="fu">inc</span>()</span> <span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span>x</span> <span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a><span class="co">#> [1] 2</span></span> <span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span><span class="fu">inc</span>()</span> <span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span><span class="fu">inc</span>()</span> <span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a>A<span class="sc">$</span>x</span> <span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>StatChull <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatChull"</span>, Stat,</span> <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales) {</span> <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> data[<span class="fu">chull</span>(data<span class="sc">$</span>x, data<span class="sc">$</span>y), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span> <span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="fu">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>)</span> <span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>stat_chull <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">geom =</span> <span class="st">"polygon"</span>,</span> <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, ...) {</span> <span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatChull, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping, <span class="at">geom =</span> geom, </span> <span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_chull</span>(<span class="at">fill =</span> <span class="cn">NA</span>, <span class="at">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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy, <span class="at">colour =</span> drv)) <span class="sc">+</span> </span> <span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_chull</span>(<span class="at">fill =</span> <span class="cn">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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_chull</span>(<span class="at">geom =</span> <span class="st">"point"</span>, <span class="at">size =</span> <span class="dv">4</span>, <span class="at">colour =</span> <span class="st">"red"</span>) <span class="sc">+</span></span> <span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">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" aria-hidden="true" tabindex="-1"></a>StatLm <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatLm"</span>, Stat, </span> <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="fu">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales) {</span> <span id="cb7-5"><a href="#cb7-5" aria-hidden="true" tabindex="-1"></a> rng <span class="ot"><-</span> <span class="fu">range</span>(data<span class="sc">$</span>x, <span class="at">na.rm =</span> <span class="cn">TRUE</span>)</span> <span id="cb7-6"><a href="#cb7-6" aria-hidden="true" tabindex="-1"></a> grid <span class="ot"><-</span> <span class="fu">data.frame</span>(<span class="at">x =</span> rng)</span> <span id="cb7-7"><a href="#cb7-7" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb7-8"><a href="#cb7-8" aria-hidden="true" tabindex="-1"></a> mod <span class="ot"><-</span> <span class="fu">lm</span>(y <span class="sc">~</span> x, <span class="at">data =</span> data)</span> <span id="cb7-9"><a href="#cb7-9" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">$</span>y <span class="ot"><-</span> <span class="fu">predict</span>(mod, <span class="at">newdata =</span> grid)</span> <span id="cb7-10"><a href="#cb7-10" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb7-11"><a href="#cb7-11" aria-hidden="true" tabindex="-1"></a> grid</span> <span id="cb7-12"><a href="#cb7-12" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb7-13"><a href="#cb7-13" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb7-14"><a href="#cb7-14" aria-hidden="true" tabindex="-1"></a></span> <span id="cb7-15"><a href="#cb7-15" aria-hidden="true" tabindex="-1"></a>stat_lm <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">geom =</span> <span class="st">"line"</span>,</span> <span id="cb7-16"><a href="#cb7-16" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb7-17"><a href="#cb7-17" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, ...) {</span> <span id="cb7-18"><a href="#cb7-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb7-19"><a href="#cb7-19" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatLm, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping, <span class="at">geom =</span> geom, </span> <span id="cb7-20"><a href="#cb7-20" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb7-21"><a href="#cb7-21" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb7-22"><a href="#cb7-22" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb7-23"><a href="#cb7-23" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb7-24"><a href="#cb7-24" aria-hidden="true" tabindex="-1"></a></span> <span id="cb7-25"><a href="#cb7-25" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb7-26"><a href="#cb7-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb7-27"><a href="#cb7-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">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" aria-hidden="true" tabindex="-1"></a>StatLm <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatLm"</span>, Stat, </span> <span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="fu">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb8-4"><a href="#cb8-4" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales, params, <span class="at">n =</span> <span class="dv">100</span>, <span class="at">formula =</span> y <span class="sc">~</span> x) {</span> <span id="cb8-5"><a href="#cb8-5" aria-hidden="true" tabindex="-1"></a> rng <span class="ot"><-</span> <span class="fu">range</span>(data<span class="sc">$</span>x, <span class="at">na.rm =</span> <span class="cn">TRUE</span>)</span> <span id="cb8-6"><a href="#cb8-6" aria-hidden="true" tabindex="-1"></a> grid <span class="ot"><-</span> <span class="fu">data.frame</span>(<span class="at">x =</span> <span class="fu">seq</span>(rng[<span class="dv">1</span>], rng[<span class="dv">2</span>], <span class="at">length =</span> n))</span> <span id="cb8-7"><a href="#cb8-7" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb8-8"><a href="#cb8-8" aria-hidden="true" tabindex="-1"></a> mod <span class="ot"><-</span> <span class="fu">lm</span>(formula, <span class="at">data =</span> data)</span> <span id="cb8-9"><a href="#cb8-9" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">$</span>y <span class="ot"><-</span> <span class="fu">predict</span>(mod, <span class="at">newdata =</span> grid)</span> <span id="cb8-10"><a href="#cb8-10" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb8-11"><a href="#cb8-11" aria-hidden="true" tabindex="-1"></a> grid</span> <span id="cb8-12"><a href="#cb8-12" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb8-13"><a href="#cb8-13" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb8-14"><a href="#cb8-14" aria-hidden="true" tabindex="-1"></a></span> <span id="cb8-15"><a href="#cb8-15" aria-hidden="true" tabindex="-1"></a>stat_lm <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">geom =</span> <span class="st">"line"</span>,</span> <span id="cb8-16"><a href="#cb8-16" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb8-17"><a href="#cb8-17" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, <span class="at">n =</span> <span class="dv">50</span>, <span class="at">formula =</span> y <span class="sc">~</span> x, </span> <span id="cb8-18"><a href="#cb8-18" aria-hidden="true" tabindex="-1"></a> ...) {</span> <span id="cb8-19"><a href="#cb8-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb8-20"><a href="#cb8-20" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatLm, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping, <span class="at">geom =</span> geom, </span> <span id="cb8-21"><a href="#cb8-21" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb8-22"><a href="#cb8-22" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">n =</span> n, <span class="at">formula =</span> formula, <span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb8-23"><a href="#cb8-23" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb8-24"><a href="#cb8-24" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb8-25"><a href="#cb8-25" aria-hidden="true" tabindex="-1"></a></span> <span id="cb8-26"><a href="#cb8-26" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb8-27"><a href="#cb8-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb8-28"><a href="#cb8-28" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_lm</span>(<span class="at">formula =</span> y <span class="sc">~</span> <span class="fu">poly</span>(x, <span class="dv">10</span>)) <span class="sc">+</span> </span> <span id="cb8-29"><a href="#cb8-29" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_lm</span>(<span class="at">formula =</span> y <span class="sc">~</span> <span class="fu">poly</span>(x, <span class="dv">10</span>), <span class="at">geom =</span> <span class="st">"point"</span>, <span class="at">colour =</span> <span class="st">"red"</span>, <span class="at">n =</span> <span class="dv">20</span>)</span></code></pre></div> <p><img src="data:image/png;base64,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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" aria-hidden="true" tabindex="-1"></a><span class="co">#' @export</span></span> <span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a><span class="co">#' @inheritParams ggplot2::stat_identity</span></span> <span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a><span class="co">#' involve \code{y} and \code{x}</span></span> <span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a><span class="co">#' @param n Number of points used for interpolation.</span></span> <span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a>stat_lm <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">geom =</span> <span class="st">"line"</span>,</span> <span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, <span class="at">n =</span> <span class="dv">50</span>, <span class="at">formula =</span> y <span class="sc">~</span> x, </span> <span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a> ...) {</span> <span id="cb9-10"><a href="#cb9-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb9-11"><a href="#cb9-11" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatLm, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping, <span class="at">geom =</span> geom, </span> <span id="cb9-12"><a href="#cb9-12" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb9-13"><a href="#cb9-13" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">n =</span> n, <span class="at">formula =</span> formula, <span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb9-14"><a href="#cb9-14" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb9-15"><a href="#cb9-15" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>StatDensityCommon <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatDensityCommon"</span>, Stat, </span> <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a> <span class="at">setup_params =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(params<span class="sc">$</span>bandwidth))</span> <span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(params)</span> <span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a> xs <span class="ot"><-</span> <span class="fu">split</span>(data<span class="sc">$</span>x, data<span class="sc">$</span>group)</span> <span id="cb10-9"><a href="#cb10-9" aria-hidden="true" tabindex="-1"></a> bws <span class="ot"><-</span> <span class="fu">vapply</span>(xs, bw.nrd0, <span class="fu">numeric</span>(<span class="dv">1</span>))</span> <span id="cb10-10"><a href="#cb10-10" aria-hidden="true" tabindex="-1"></a> bw <span class="ot"><-</span> <span class="fu">mean</span>(bws)</span> <span id="cb10-11"><a href="#cb10-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">message</span>(<span class="st">"Picking bandwidth of "</span>, <span class="fu">signif</span>(bw, <span class="dv">3</span>))</span> <span id="cb10-12"><a href="#cb10-12" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb10-13"><a href="#cb10-13" aria-hidden="true" tabindex="-1"></a> params<span class="sc">$</span>bandwidth <span class="ot"><-</span> bw</span> <span id="cb10-14"><a href="#cb10-14" aria-hidden="true" tabindex="-1"></a> params</span> <span id="cb10-15"><a href="#cb10-15" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb10-16"><a href="#cb10-16" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb10-17"><a href="#cb10-17" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales, <span class="at">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb10-18"><a href="#cb10-18" aria-hidden="true" tabindex="-1"></a> d <span class="ot"><-</span> <span class="fu">density</span>(data<span class="sc">$</span>x, <span class="at">bw =</span> bandwidth)</span> <span id="cb10-19"><a href="#cb10-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">data.frame</span>(<span class="at">x =</span> d<span class="sc">$</span>x, <span class="at">y =</span> d<span class="sc">$</span>y)</span> <span id="cb10-20"><a href="#cb10-20" aria-hidden="true" tabindex="-1"></a> } </span> <span id="cb10-21"><a href="#cb10-21" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb10-22"><a href="#cb10-22" aria-hidden="true" tabindex="-1"></a></span> <span id="cb10-23"><a href="#cb10-23" aria-hidden="true" tabindex="-1"></a>stat_density_common <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">geom =</span> <span class="st">"line"</span>,</span> <span id="cb10-24"><a href="#cb10-24" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb10-25"><a href="#cb10-25" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, <span class="at">bandwidth =</span> <span class="cn">NULL</span>,</span> <span id="cb10-26"><a href="#cb10-26" aria-hidden="true" tabindex="-1"></a> ...) {</span> <span id="cb10-27"><a href="#cb10-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb10-28"><a href="#cb10-28" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatDensityCommon, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping, <span class="at">geom =</span> geom, </span> <span id="cb10-29"><a href="#cb10-29" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb10-30"><a href="#cb10-30" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">bandwidth =</span> bandwidth, <span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb10-31"><a href="#cb10-31" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb10-32"><a href="#cb10-32" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb10-33"><a href="#cb10-33" aria-hidden="true" tabindex="-1"></a></span> <span id="cb10-34"><a href="#cb10-34" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, <span class="at">colour =</span> drv)) <span class="sc">+</span> </span> <span id="cb10-35"><a href="#cb10-35" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>()</span> <span id="cb10-36"><a href="#cb10-36" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a></span> <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, <span class="at">colour =</span> drv)) <span class="sc">+</span> </span> <span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>(<span class="at">bandwidth =</span> <span class="fl">0.5</span>)</span></code></pre></div> <p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAKgCAYAAABEPM/FAAAEDmlDQ1BrQ0dDb2xvclNwYWNlR2VuZXJpY1JHQgAAOI2NVV1oHFUUPpu5syskzoPUpqaSDv41lLRsUtGE2uj+ZbNt3CyTbLRBkMns3Z1pJjPj/KRpKT4UQRDBqOCT4P9bwSchaqvtiy2itFCiBIMo+ND6R6HSFwnruTOzu5O4a73L3PnmnO9+595z7t4LkLgsW5beJQIsGq4t5dPis8fmxMQ6dMF90A190C0rjpUqlSYBG+PCv9rt7yDG3tf2t/f/Z+uuUEcBiN2F2Kw4yiLiZQD+FcWyXYAEQfvICddi+AnEO2ycIOISw7UAVxieD/Cyz5mRMohfRSwoqoz+xNuIB+cj9loEB3Pw2448NaitKSLLRck2q5pOI9O9g/t/tkXda8Tbg0+PszB9FN8DuPaXKnKW4YcQn1Xk3HSIry5ps8UQ/2W5aQnxIwBdu7yFcgrxPsRjVXu8HOh0qao30cArp9SZZxDfg3h1wTzKxu5E/LUxX5wKdX5SnAzmDx4A4OIqLbB69yMesE1pKojLjVdoNsfyiPi45hZmAn3uLWdpOtfQOaVmikEs7ovj8hFWpz7EV6mel0L9Xy23FMYlPYZenAx0yDB1/PX6dledmQjikjkXCxqMJS9WtfFCyH9XtSekEF+2dH+P4tzITduTygGfv58a5VCTH5PtXD7EFZiNyUDBhHnsFTBgE0SQIA9pfFtgo6cKGuhooeilaKH41eDs38Ip+f4At1Rq/sjr6NEwQqb/I/DQqsLvaFUjvAx+eWirddAJZnAj1DFJL0mSg/gcIpPkMBkhoyCSJ8lTZIxk0TpKDjXHliJzZPO50dR5ASNSnzeLvIvod0HG/mdkmOC0z8VKnzcQ2M/Yz2vKldduXjp9bleLu0ZWn7vWc+l0JGcaai10yNrUnXLP/8Jf59ewX+c3Wgz+B34Df+vbVrc16zTMVgp9um9bxEfzPU5kPqUtVWxhs6OiWTVW+gIfywB9uXi7CGcGW/zk98k/kmvJ95IfJn/j3uQ+4c5zn3Kfcd+AyF3gLnJfcl9xH3OfR2rUee80a+6vo7EK5mmXUdyfQlrYLTwoZIU9wsPCZEtP6BWGhAlhL3p2N6sTjRdduwbHsG9kq32sgBepc+xurLPW4T9URpYGJ3ym4+8zA05u44QjST8ZIoVtu3qE7fWmdn5LPdqvgcZz8Ww8BWJ8X3w0PhQ/wnCDGd+LvlHs8dRy6bLLDuKMaZ20tZrqisPJ5ONiCq8yKhYM5cCgKOu66Lsc0aYOtZdo5QCwezI4wm9J/v0X23mlZXOfBjj8Jzv3WrY5D+CsA9D7aMs2gGfjve8ArD6mePZSeCfEYt8CONWDw8FXTxrPqx/r9Vt4biXeANh8vV7/+/16ffMD1N8AuKD/A/8leAvFY9bLAAAAOGVYSWZNTQAqAAAACAABh2kABAAAAAEAAAAaAAAAAAACoAIABAAAAAEAAAKgoAMABAAAAAEAAAKgAAAAAMw48TsAAEAASURBVHgB7L0HlGRXdff7r1ydc5qeHHty0CgHhAARJDAYgx/6CMbC8GzMZ/zMM172MzyzYC3bep+1DOb5fdj+wIAQwQFJICFZEeU0OefpntBpOqfK7+zbqp6anu7qCvfeuuF/ZklVdcM5Z//27erd5+zgSakGNhIgARIgARIgARIgARIwiYDXpHE4DAmQAAmQAAmQAAmQAAloBGiA8kEgARIgARIgARIgARIwlQANUFNxczASIAESIAESIAESIAEaoHwGSIAESIAESIAESIAETCVAA9RU3ByMBEiABEiABEiABEiABiifARIgARIgARIgARIgAVMJ+E0dLWOwkZERxOPxjCOFvw2FQkgmk4jFYoV3YsM7g8EgotGoDWde+JRFZskcRl0XztAud1LXdtFU8fOkrotnaJceRNfSnPy7S2ySiooKu6ikZPMsmQEaiUR0M0Crqqq0h1n6dFMrLy/H6Oiom0SG6FqMz7GxMVfJ7UZdV1ZWIpFIUNcueNLll7X8Ycmfa+crW77LpDn5d5fP53O+InWQkFvwOkBkFyRAAiRAAiRAAiRAArkToAGaOyteSQIkQAIkQAIkQAIkoAMBGqA6QGQXJEACJEACJEACJEACuROgAZo7K15JAiRAAiRAAiRAAiSgAwEaoDpAZBckQAIkQAIkQAIkQAK5E6ABmjsrXkkCJEACJEACJEACJKADARqgOkBkFyRAAiRAAiRAAiRAArkToAGaOyteSQIkQAIkQAIkQAIkoAMBGqA6QGQXJEACJEACJEACJEACuROgAZo7K15JAiRAAiRAAiRAAiSgAwEaoDpAZBckQAIkQAIkQAIkQAK5E6ABmjsrXkkCJEACJEACJEACJKADARqgOkBkFyRAAiRAAiRAAiRAArkToAGaOyteSQIkQAIkQAIkQAIkoAMBGqA6QGQXJEACJEACJEACJEACuROgAZo7K15JAiRAAiRAAiRAAiSgAwEaoDpAZBckQAIkQAIkQAIkQAK5E6ABmjsrXkkCJEACJEACJEACJKADARqgOkBkFyRAAiRAAiRAAiRAArkToAGaOyteSQIkQAIkQAIkQAIkoAMBGqA6QGQXJEACJEACJEACJEACuROgAZo7K15JAiRAAiRAAiRAAiSgAwEaoDpAZBckQAIkQAIkQAIkQAK5E6ABmjsrXkkCJEACJEACJEACJKADARqgOkBkFyRAAiRAAiRAAiRAArkToAGaOyteaXMCsWQMw/ERm0vB6ZMACZAACZCA/Qn47S8CJSCB7AReGHoN//PCD3Bo/BiS6l+9vxZ3NbwTv9P226gP1Ga/mWdJgARIgARIgAR0J0ADVHek7NAqBOKpBP727Lfxs75HsKViPb609PdR46/C3rGD+Pe+X+KXl57E/7P6q9hetckqU+Y8SIAESIAESMAVBGiAukLN7hMylUrhK6f+Fo8PPIsvLfl93NPyIXg8Hg3E+xregd9t+xi+fPLr+NzRP8X/UEborbXXuw8SJSYBEiABEiCBEhGgD2iJwHNYYwl8t/sneGzgaXx1xZ/gv7X+5ozxmR61JdiE/7nuPlxbtRX/54mv4cj4ifQpvpIACZAACZAACRhMgAaowYDZvfkEDowdxbfPfRcfb/kwPtB457wTCHmD2hb80nA7/uTEX2E0Pj7vtTxBAiRAAiRAAiSgHwEaoPqxZE8WIJBQfp9fO/M/sKJsKf774nsXnFGZL4z7Vn8Fg/Eh/HXntxa8nheQAAmQAAmQAAkUT4AGaPEM2YOFCPy871c4Pnkaf7HsjxDwBnKa2bLwYvwfSz6HRy89BYmYZyMBEiABEiABEjCWAA1QY/mydxMJTCUj+P8ufB/vqLsl78j2Dzfdha2VG3Ff5/8LyRfKRgIkQAIkQAIkYBwBGqDGsWXPJhP4We8jGIgN4fPtn857ZImQ//LSz6MrcgE/6X047/t5AwmQAAmQAAmQQO4EaIDmzopXWpiA5Px8oOc/8M76WzX/z0Kmur5iDe5WCer/6cIDGEswIKkQhryHBEiABEiABHIhQAM0F0q8xvIEnh58Hj3RPnyi5beKmuv/3v5JTCQn8GDPz4vqhzeTAAmQAAmQAAnMT4AG6PxseMZGBH7S8zA2VqzDpsqOoma9KNSK9zfciQe6/x2Ticmi+uLNJEACJEACJEACcxOgATo3Fx61EYFTk2exa2w/Ptr8AV1mLTXiR9UW/L/3PapLf+yEBEiABEiABEjgSgI0QK/kwU82JPBQ/+Oo9FXgzvq36TJ7SUz/jrpbNZ9S8S1lIwESIAESIAES0JcADVB9ebI3kwlI4vlf9P8X3lP/doS9Id1G/2Trb6E72ounBp7XrU92RAIkQAIkQAIkME2ABiifBFsTeH1kLwZUFaP3NbxDVznEl3RzxXqVkukhXftlZyRAAiRAAiRAAgANUD4Ftibw+MAzaA40YptKIq93+2jz+7F77ABOTJzWu2v2RwIkQAIkQAKuJkAD1NXqt7fw4p/5zOCLeFf9bZBE8nq3dymf0mpfFf6t75d6d83+SIAESIAESMDVBGiAulr99hb+DbX9PpwYxTvrbjNEkJA3iPc3vgu/vPQkpMwnGwmQAAmQAAmQgD4EaIDqw5G9lIDAM0MvoCnQoGq4bzBs9A81vU+rivT04AuGjcGOSYAESIAESMBtBGiAuk3jDpL3uaFXcGvt9YZsv6cxrSpbhk0VHXio7/H0Ib6SAAmQAAmQAAkUSYAGaJEAeXtpCBydOKGV3ry99ibDJ/D+xjvx+ugebTzDB+MAJEACJEACJOACAjRAXaBkJ4r4/NBrCHmCuLZ6m+HivVsFI/k8Pjx66SnDx+IAJEACJEACJOAGAjRA3aBlB8r40vDruKZqi67J5+fDVOOvxi011ykD9On5LuFxEiABEiABEiCBPAjQAM0DFi+1BoHR+Bj2jR3CTTU7TZvQ+xruwInJ0zjOnKCmMedAJEACJEACziVAA9S5unWsZK8MvIkEkrjRRAP0ttobUe4tgyS+ZyMBEiABEiABEiiOgL+42wu/u6ysDH6/PsP7fD6EQiHU1dUVPiEb3hkIBFwns+j6peE30BpqxjWLjPf/zHws3tX8Njw59Dz+cvOfZB425b0bdS3fD6Jv/lyb8oiVdJD07wLquqRqMGVw+S6T5mRdx+NxU1jafRB9LMACKExOTkIvJTU2NiIajWJkZKSAmdj3FvkBHhwctK8ABcxcdP3rvpdxbeU202W/vfJGPNT9K7x07jWsr1hTwOwLv8WNum5oaEAikcDQ0FDh4Gx4pxt1XV9fj1QqZfrPdKkfDzfqWmSW5uTfXeXl5aV+tGwxPrfgbaEmTjJNoHuqF6cnOnF99fb0IdNexee0wluOJwd/bdqYHIgESIAESIAEnEiABqgTtepgmV4eeEOTTiLgzW5BVZrzttob8OTA82YPzfFIgARIgARIwFEEaIA6Sp3OF+blS29gSdkizQe0FNK+s/5WdEbO4wSj4UuBn2OSAAmQAAk4hAANUIco0i1ivDq4C9fX7iiZuDdW79Ryjz7F2vAl0wEHLo6AcrVEIllcH7ybBEiABIolULIgpGInzvvdR2AgNoRT42fxuWWfLJnwZb6wyj96LZ5WBujn2j9RsnlwYBLIl8CZvgBePF6G106WI54AFtXFccvaCdzaMQGvJ9/eeD0JkAAJFEeAK6DF8ePdJhLYM3ZAG+3aWnPTL80WUerPH5s8hQuRntmn+JkELEng6UPluO/RBhzvDuHOzWP4retG0FiVwE9ercG3/6seUzFaoJZUHCdFAg4mQAPUwcp1mmi7RvejKdiA5eVLSirarbXXw6v+PTf0cknnwcFJIBcCj++rwL+9VoNb103g//qNPty1bQxv3zCBz90xiN9/xwBO9QY0I1RWRdlIgARIwCwCNEDNIs1xiiawZ+wgdtaVdvVThKhVteG3VW5UBuhLRcvEDkjASAJ7zobw0K4qvHPTGP63G0bg91052uYlEfz+OwdxWm3P/+y16itP8hMJkAAJGEiABqiBcNm1fgSmkhEcnTihDNCt+nVaRE9vq7sRb47uw1hivIheeCsJGEdgYNyLH7xYi43tEXzomtF5B1rbGsVvXjuC549WYF9XaN7reIIESIAE9CRAA1RPmuzLMAKHxo8hnkrgWgusgIqQb1O14WU+L6uyoGwkYEUCP3m5Bj5vCp+6dQieBVw871Bb8mtbI/jpq9WIsYqgFdXJOZGA4wjQAHWcSp0p0L6xQwh4AthY3WEJAZeFF2NpqB2/HnrFEvPhJEggk8CBcyHsPxfGb6mVzcqwyruUQ/vo9SMYHPPh2cMVOVzNS0iABEigOAI0QIvjx7tNInBg/Ag6ylcj6A2YNOLCw0gw0ovDryOZYlLFhWnxCrMIJNXj+B+vV2FlUxTXrZrKeVhJy3TD6kk8vr+SUfE5U+OFJEAChRKgAVooOd5nKoED40exqWKdqWMuNJgYoIPxYYhxzEYCViHw6skydA8H8KGdI3lP6b1bxzTj87nD5XnfyxtIgARIIB8CNEDzocVrS0KgL3oJPdE+bKpcX5Lx5xt0R+VmlHnD2irofNfwOAmYSSCpdttlBXND+xRWtcTyHlpyg+5cOaltw7NaUt74eAMJkEAeBGiA5gGLl5aGwEG1+iltY8Xa0kxgnlEDyh3g+uodygB9bZ4reJgEzCWw52wYvSN+vGfLWMED37F+AsOTPuw+Ey64D95IAiRAAgsRoAG6ECGeLzkBMUArfRVa0E/JJzNrArfUXIeDKkJfyoSykUCpCTx5oALLle/n6gJWP9NzX9oYw/LGKH59lNvwaSZ8JQES0J8ADVD9mbJHnQmIgSern56FcsnoPG4u3UldeGlMx5QLLV5jJAGp9X6mP4h3biw+N+1tqj78iZ4QeoZnZa43UgD2TQIk4CoCNEBdpW57CntIrYButFgAUppkW6gZK8NL6QeaBsLXkhF47kg5asoS2Lo098j3+Sa7Y/kkQv4kXjnBVdD5GPE4CZBAcQRogBbHj3cbTOBCpBvDiVFsKLeW/2em2LIK+srIm0ilcsu3mHkv35OAHgQmIh7sOlOGm9dOqOTzxfcY9APblk3htVNl6rkuvj/2QAIkQAKzCejwVTW7S34mAf0IHB4/rnW2vmKNfp3q3NNNNTu1dExHVKlQNhIoBYHXlaEYTwA3rZnQbfhrVTT84LgPp3qtk3tXN+HYEQmQQMkJ0AAtuQo4gWwEDk8cR7WvCotCrdkuK+m57VWbEVRVml5iWc6S6sHNg7+stso7FkVRX6lfUYSOtqiqopTAm2pllY0ESIAE9CZAA1RvouxPVwKyArq+YrWuferdWdgbwg5lhL48wrrwerNlfwsTuDDoR+elAG5crd/qp4zqVb8dtil/UknHxG34hfXAK0iABPIjQAM0P1682mQCsq29TpXgtHq7ofoa7FX16icTk1afKufnMALipxkOJHUJPpqNZsfyKS0n6CkVYc9GAiRAAnoSoAGqJ032pSuB/tgABuJD9jBAa65BPBXHG6P7dGXAzkggGwFZmXzjVFgzPgMqcEjvtqY1ivJgEvs6mZReb7bsjwTcToAGqNufAAvLf3TipDa7jvJVFp7l9NTWlq1Evb9WRcPvsvxcOUHnEDitViYHxv2QgCEjmkTUb2iPYH9XyIju2ScJkICLCdAAdbHyrS66GKAhTxDLwoutPlUtSb6U5Xxl+E3Lz5UTdA6BN06XoSKUxDoVMGRU27xkCt3DAfSPMim9UYzZLwm4kQANUDdq3SYyH1X+n6vLV8DnsccvvhtqduDU1Fn0RS/ZhDCnaWcCsv2+W9V+375sUpfcn/OxkBVQjyeFg+e4CjofIx4nARLInwAN0PyZ8Q6TCBybOIW1Zdbffk/jkBVQaa+N7E4f4isJGEZAtt+HJ3zYrgKFjGwVoRRWqPrwB2iAGomZfZOA6wjQAHWdyu0h8FQygs6p8yoAaaU9Jqxm2RJs0twFXqUBahud2Xmie9TqpwQIrVWBQkY3WQU91h3Skt0bPRb7JwEScAcBGqDu0LPtpDwxcQZJ9W+tDQKQMuFeX70dr41yBTSTCd8bQ2CvikwX/0w9Sm8uNMP1iyKIJTyqKlJwoUt5ngRIgARyIkADNCdMvMhsAscmpyPg1ygfUDu166q2oyfah7NT5+w0bc7VZgQk+XzfqN+Q3J9zoVimtuDL1Grr4Qv0A52LD4+RAAnkT4AGaP7MeIcJBE5OnkFbsBmVvgoTRtNviJ3VW+FR/+gHqh9T9nQ1gX0qLZLfl8J6VX7TjCZVkda0RHH0IldAzeDNMUjADQRogLpByzaU8fjEaawqs9fqp2Cu8Vcrv9VVeH1kjw2pc8p2ISCJ4TvaIggFVCi8SW2dGk9Kfk7FPCaNyGFIgAScTIAGqJO1a2PZTkyexhobGqCC/DrlB/r66B5VP9s848DGqubU8yQwOunFmf4AtiyJ5HlncZdLrtFkyoPj3VwFLY4k7yYBEhACNED5HFiOwEBsEIPxYZUDdLnl5pbLhK6t2oah+AiOKyOajQT0JnDwvPhherBxsbHpl2bPu602riW9pwE6mww/kwAJFEKABmgh1HiPoQROKP9PaattugK6o2ozfOpvu9eZjknTI/+nLwHJx9leF0NdRVLfjhfozaN23te0RrgCugAnniYBEsiNAA3Q3DjxKhMJiAHqVf+W26AE51xYyn1l2FixTm3D753rNI+RQMEEksrmlEj0jYvN3X5PT1gCkToH6Aea5sFXEiCBwgnQAC2cHe80iIBEwC8NtyPota+v2bXV2/Dm6D7lM2fuKpVBKmG3FiFwSlU/mox6scnk7fe0+KuVAZpSfqBShYmNBEiABIohQAO0GHq81xACJyfPqgj4ZYb0bVanO5Uf6FhiHEdUPXs2EtCLwMFzYYQDSaxoiunVZV79tNfHtfFP9tj3j8O8BObFJEAChhGgAWoYWnZcKAFZAV1VtrzQ2y1x39bKDfB7/HiD2/CW0IdTJiHb75J+yYzqR3Mx8yo/UDF+T7Ii0lx4eIwESCAPAjRA84DFS40n0Bvt11YO7b4CWuYLY1NFhwpEoh+o8U+NO0YYnfKqPJx+bGg3J/n8fFRXNkdxRm3Biz8qGwmQAAkUSoAGaKHkeJ8hBGT7XdrKsL234EWGnVVbsHt0PxKphHxkI4GiCBy5INveHqxvL00AUnryq5QBGol7cV6VA2UjARIggUIJ0AAtlBzvM4TAKWWASgqjZTaNgM+EIoFI48kJ+oFmQuH7ggkcUdvvTVVxNFSW9g+a5WoL3oMUTvXRD7RgZfJGEiAB9ZuejQQsRODU1FksURHwAa/9o2y3pP1AuQ1voSfMvlMR/8/1i0q7+in0wqr856K6OE732v9n1L5PA2dOAvYnQAPU/jp0lASnJjux0uYR8GmFhL0hzQ9U0jGxkUAxBLqHfBia8KHDAgaoyCGBSKe5AlqMSnkvCbieAA1Q1z8C1gJwWm3BrwgvtdakipiN5gc6doD5QItgyFuBIxdD8HhSkHrsVmjLm6LoG/VjPKLC4tlIgARIoAACNEALgMZbjCEwGBvGcGJUrYA6xwC9pmqrFtV/dOKkMdDYqysIiP/nssYYyoIpS8i7XM1F2hmuglpCH5wECdiRAA1QO2rNoXM+PdWpSbY8vMQxEk7nA/VpVZEcIxQFMZWApDs61h3EulZrrH6K8K21cYT8SZzppx+oqQ8DByMBBxGgAeogZdpdlDMONEAlH+iG8rXKAGU+ULs/n6Wa/3Ttda9l/D+FgySkX6pWQc/SAC3VY8FxScD2BGiA2l6FzhFAApBagk0o95U5RygliWzD7xo9oGpoW2P71FFwXSDMsYtB+L0prFR+l1Zq4hLAFVAraYRzIQF7EaABai99OXq2Z6fOqQAk52y/p5V1TfUWjCjf1uOTp9OH+EoCORM4qgKQVqjk7wGL5X0XP9CxKR8GxvhrJGdl8kISIIEZAvzmmEHBN6UmID6gyxxogG6r3KgS7nrVKijTMZX6GbPb+Anl/3lS5du0kv9nmuHShulApLOXmJA+zYSvJEACuROgAZo7K15pIIFoMooLkR5HroBW+MrRUb6agUgGPj9O7VpqrkdV2cu1baVPQD+bcWNVAhWhJDrpBzobDT+TAAnkQIAGaA6QeInxBDqnzqvifiksL3PeFrzQ21G1Wa2A7jceJEdwFIFj3SEEfOrn4q20R1YTTlZBGYhkNa1wPiRgDwI5GaBHjx7FE088gf7+/gWlGh0dxTPPPLPgdbyABDIJnJ7q0j46KQVTpnw7qrZgID6EM5PTcmae43sSmI+ApF9apfw//b75rijtcTFAuwaYiqm0WuDoJGBPAgsaoPfffz/uu+8+7N69G/feey86OzuzSvp3f/d3+N73vpf1Gp4kgdkEzioDtMwb1qLgZ59zwuftVZs0MXaN0Q/UCfo0Q4Z4AjjVG8QaC+X/nC33EmWAjke8DESaDYafSYAEFiSQ1QA9c+YMnn/+eXznO9/Bl7/8ZXzsYx/DAw88MG+nskp69uzZec/zBAnMR+CMioBfGm6f77Ttj9f6q7GqbLmWjsn2wlAAUwjI1nYs4cHaVuv5f6YBLKmfDkTiKmiaCF9JgARyJZA1scepU6ewZcsWeL3TduqOHTvwy1/+cs6+e3p68KMf/Qh/+Id/iG9961tXXRONRjE5OTlzPJFIqNrG+tQRln7S/80M4JI3ejEsNS5JwSTb77nKk+t1pZYrc/xr1Db880Ov5Cxj5r3y3o4yz5ahkM9ulFtkPt7zlv9nU9yyum+qTiIcSKJLRcJvW1Z8nlK36rqQnws73yN6dqOu7awzI+ae1QC9ePEiampqZsatrq7GpUuXZj6n3yRVrbhvfOMb+OIXv4hQKJQ+fMXr97//fW0rP33wxz/+MbZv357+WPSr3+9HeXl50f3YrYPW1la7TXnO+XbtvoA7229HLvIEAgFb6vrtiVvw096HEa9OYXF525wcsh3MhU22++16rqzMWYUJctGD6LrzWaBjMbC43do/46vU9HrHK9XPbmUuomW9xo3PuBtllofAyXJPTExkfc55cppAVgPU5/NBVirTLR6PY65fBg8++CA6Ojqwbds2HD58OH35Fa9vf/vb0dLSMnOsvr4eg4ODM5+LeSOGsczNbUqvqKjA+Ph4Megsce9AdBDDsRG0eZoXfCaqqqq0Z9KOut7gW6Pxfrrr13h/8515sXeKrvMRWnQtf9w64RnPR27R9cjoOA531eI926bUz8RUPrebfm1bbRnePBVU8xwueOzKykqtUpgbde02mUXX0sbGxgp+Xqx+o9hObAsTyGqANjU1Yd++y0ETAwMDaGu7euXm0UcfRV9fH37+859rXyKRSAS/8Ru/gYceemhmBqtWrYL8l25y/dSUPl+s8kCLAapXf+k5Wv1V/hhwgszHRk9qqNt8zQvKI7qWP4rsKHc1KtEeasUrA2/iXdW35fV4OUXX+QgthphddZ2PnLOvFV0fO59AJO7BisYJ9awXv7U9eww9Py+q8eDJ8TD6hyKoDBdWblZ2r6RUrR1/roth6cafa5FZmpN17cbd2EJ+DrIGIV177bU4cOAAurq6NAPvkUcewXXXXaeNI/6c6YAjCUySACT575vf/CZWrFhxhfFZyMR4j3sIdEbOa8IuDan9Roe3HZVbsFvVhWcjgWwETqj0S1L/fUWjtY1PkWHxW4FI55iOKZtKeY4ESGAWgawGqGxtf/azn8VnPvMZfOITn4Dk+Lznnnu0Lg4ePIgvfOELs7rjRxLIn4AEINX5a1Hlr8j/ZpvdIQnppeToYKzw7UqbiczpFkDgeE8Qy1TyeavVf59LlLbaOHzKWKYBOhcdHiMBEpiPQNYteLnp7rvvxrvf/W7Itnrad0OO79y5Ew8//LC8vaKtX78e//qv/3rFMX4ggWwEpAqSk1MwZcqezge6Z+wA3l53c+YpvicBjUBS7WJL/s9b19kjkMGnljHECD03uOCvE2qYBEiABGYIZF0BTV8lUceZxmf6OF9JQA8CmgEacm4O0ExGy8KLUa9We1mWM5MK32cS6Or3YCLqVQnorZv/M3O+8r69Lobz3IKfjYWfSYAEshDIyQDNcj9PkUBRBCTwQHxAxTBzS5Nt+N1jrAvvFn3nK+eR816VIzGFlc3TSd7zvb8U1y+uj+PikB9SvYmNBEiABHIhQAM0F0q8xjACfbFLmEpGXLMFLyC3KwP0yPgJTCYuF2YwDDA7th0BMUAX18VVgvfCIspLIbCsgCZTHnQPcxu+FPw5JgnYkQANUDtqzUFzlu13aUvDixwkVXZRdlRuRgJJ7B2bO2du9rt51ukExABd3WL96PdMPbSrFVBp5wcDmYf5ngRIgATmJUADdF40PGEGgXQKpiUu8QEVpmvKV6DcW8ZteDMeMJuN0Tfiw9C4x3YGaFU4iapwAhcYiGSzJ47TJYHSEaABWjr2HFkRkBXQxkA9yn3uKbfo8/iwtXIj84HyJ+AqAidV9Ls0u62AypzbldvAeRqggoKNBEggBwI0QHOAxEuMI9AVuYAlIfdsv6dJ7qjahP3jhxFPMWojzYSvwAmV/7O1Vq0mliVth0OLhOcWvO30xgmTQKkI0AAtFXmOqxFwUw7QTJVvq9ykBV8dGT+eeZjvXU5ADNCOdvsZn6K2RWoFdHjCh/GIx+VapPgkQAK5EKABmgslXmMYgXPaCqg7coBmQtxU2QG/x49dTMeUicXV70envOgd8WNdu32i3zMVJlvw0i5wFTQTC9+TAAnMQ4AG6DxgeNh4An3RdAom923Bh70hbChfQz9Q4x8z24xwsmc6gtyuK6CttTEtfykDkWzzyHGiJFBSAjRAS4rf3YOL/6e0xS70ARW5tyk/0L1jB+UtGwngpNp+l0jy1lp7roAGVQrQpqoEA5H4LJMACeREgAZoTph4kREEZPtdmlsN0O3KD3QwPowzk11G4GWfNiNwQkXAr7JZ/s/ZiBepVdCLQ8wFOpsLP5MACVxNgAbo1Ux4xCQCnVMXUOuvRpW/wqQRrTWMrIBKox+otfRSitlElftk16UAVjfbKwH9bFZtyg9USnKykQAJkMBCBGiALkSI5w0j4NYApDRQMb5XhJdiz+iB9CG+upTA6b6gVspyVYt96r/Ppaq22jgmol4MTfBXy1x8eIwESOAyAX5LXGbBdyYTEAN0cajN5FGtNdx2tQq6e4wGqLW0Yv5sTqnt96A/icX19jZAFykDVBpXQc1/hjgiCdiNAA1Qu2nMQfPtmrpIA1T5gZ6LXER/bMBBmqUo+RKQ/J/LG2Pw2fwbuaUmDq8nhYusiJTvI8DrScB1BGz+dec6fTlG4NH4GEYSo1gcdl8KpkwlygqotN3chs/E4qr3SRX0frovYPsAJFGaGNDN1XFcYCCSq55hCksChRCgAVoINd5TNIF0CiY3luHMhNeuXBCaAg3Yw3RMmVhc9V7yZk7FvFhl8wCktNLED5Rb8GkafCUBEpiPAA3Q+cjwuKEELqdgcrcPqEDeVrmRgUiGPm3W7vyk8v/0IIUVTfb2/0xTpgGaJsFXEiCBbARogGajw3OGERD/T6kG1BRsMGwMu3Qs6ZiOTpzAZGLSLlPmPHUkIAnopY56WdCeCehnoxBZZEV3aJy/Xmaz4WcSIIHLBPgNcZkF35lI4LwKvFkUbDVxROsOJQnpE0hi3/hh606SMzOMwKleZ/h/pgG1qkAkaReHmQ80zYSvJEACVxOgAXo1Ex4xgYBEfi9xeQBSGvPa8pUo84YZiJQG4qLXQbVKODDud4z/p6hOgpC0SHgmpHfRk0xRSSB/AjRA82fGO3QgID6gEoDDpiKHPT5sqVzPuvAufBjE/1OaUwKQRBa/D2hUNeG7GQkvONhIgATmIUADdB4wPGwcgVgyjp5ov+tzgGYS3qa24feOHUIilcg8zPcOJyAJ6GvLE6ivTDpKUgYiOUqdFIYEDCFAA9QQrOw0G4GL0R7l8aiqvnAFdAaT5AOdTE7h2MSpmWN843wCEoDkpNXPtMbaamPopg9oGgdfSYAE5iBAA3QOKDxkLIHuSA82V6yH23OAZlIWHl71j/lAM6k4+/1UzINzKgfoSofk/8zUlgQijUe8GJvyZB7mexIgARKYIUADdAYF35hF4GzkPPariO+2UItZQ1p+nHJfGdaVr2IgkuU1pd8Ez6jqR6mUB6tbovp1apGeWmumXUm4CmoRhXAaJGBBAjRALagUp0/pfKRbq/4T8k4HYDhd3lzl0xLSjx3I9XJeZ3MCEoAU8ifRrvJmOq1JTXio5PoMRHKaZikPCehHgAaofizZU44ELigDdFGIOUBn4xI/0L7YJQgfNucTkAAkqX7kdeC3cCiQQl1FkrlAnf8YU0ISKJiAA7/6CmbBG00iIDlA22mAXkV7qyrJKY1+oFehcdyBpCp6JAnonej/mVaW+IF2MxdoGgdfSYAEZhGgAToLCD8aT0C24BkBfzXn5mCjVh1q9yi34a+m46wj5wf8iMS9WOVA/8+0psQA7RlWSUHZSIAESGAOAjRA54DCQ8YRGI2PYyQxyhXQeRBvq9rIFdB52DjpsGy/ezwpbQveSXJlytJaG1dVnnyIOs/FNVNMvicBEiiQAA3QAsHxtsIIXIhe1G5kHfi5+Uld+JOTZzAaH5v7Ah51BAEJQJLgo7DylXRqmw5E8qhVUNaEd6qOKRcJFEOABmgx9Hhv3gQuqByg0liGc250EgmfUv+kKhKbcwmIAepk/0/RnGzBS2MqJg0D/0cCJDCLAA3QWUD40VgC4v/pV7XPW5S/I9vVBFaVLUeVr1Jtw9MP9Go6zjgyOO7FoNqadmIFpEwNVZclURZMcgU0EwrfkwAJzBCgATqDgm/MIHBeRcC3Bpvh9fDRm4u3x+PB1soN9AOdC45Djkn5TWlODkBKq6qlWgKRuAWf5sFXEiCBywRoBVxmwXcmEJAVUKZgyg5a0jEdGDuCWJLRG9lJ2fOsbL/XlSdQr/JkOr2JH2jPCA1Qp+uZ8pFAIQRogBZCjfcUTEAM0EXBtoLvd8ONkpA+koriyMRxN4jrOhk1/08Hp1/KVKhmgKoV0JRzY60yxeV7EiCBPAjQAM0DFi8tnsCFaA9XQBfAuLFineYny4T0C4Cy4empmAfnB/2O9/9Mq0YCkWIJj/J55a+aNBO+kgAJTBPgtwKfBNMIDMSGMJWcUmU4W0wb044Dhb0hdJSvoR+oHZW3wJxP9wXUaqDHNQZoS01CI8Jt+AUeDJ4mARcSoAHqQqWXSuR0jXPWgV9YA5IPdA8rIi0MymZXSABSyJ/UcoDabOoFTbepKq4l3GcgUkH4eBMJOJoADVBHq9dawl2IdmsTYhDSwnqRikgD8SF0Tp1f+GJeYRsC0/k/Y/C65JvXrypxNlQmGAlvmyeUEyUB8wi45GvQPKAcaX4CkoQ+6AmgwV83/0U8oxGQhPTS6AeqYXDE/5Iq6P2M2oJ3egL62cpiKqbZRPiZBEhACNAA5XNgGgEtAj7UqrbkPKaNadeB6gN1WBpq5za8XRU4x7zPDQQQiXux2iUR8GkETMWUJsFXEiCBTAI0QDNp8L2hBMQHdFGQAUi5QpZ8oFwBzZWW9a870RtQBRhSWN4Ys/5kdZxhc3VCi4KPMq2tjlTZFQnYnwANUPvr0DYSSAomBiDlri7xAz091Ynh+EjuN/FKyxI4pRLQL66PIRRwV1JMWQEFPOhlQnrLPpucGAmUggAN0FJQd+mYF5UPKFMw5a78tB/o3rFDud/EKy1L4ISKgF/V4q7VT1GG+IBKowGqYeD/SIAE3iJAA5SPgikEBmKDWnWfNm7B58x7RXgpanxV2M10TDkzs+qF/aM+jEz6sLo5atUpGjavWlVyVFJPMRWTYYjZMQnYkgANUFuqzX6Tlgh4aVwBzV13Eqy1VW3D0w80d2ZWvVJWP6WtclkAUlofTcoPtHdE5WRiIwESIIG3CNAA5aNgCoF0DlD6gOaHW7bhD40fRTTpvq3b/EhZ+2oxQCUpe3WZysXkwqalYqIPqAs1T5FJYH4CNEDnZ8MzOhJgDtDCYG5TFZGiqRj2jxwurAPeZQkCkoDebemXMsE3q0Ck3mF/5iG+JwEScDkBGqAufwDMEv+iioBvDTYzB2iewDdWrEVAJe9/Y3BPnnfycqsQGJvyaP6Pbt1+Fz1IKqaJqBfCgo0ESIAEhAANUD4HphCQFVBuv+ePOugNYkPFGrwxtDf/m3mHJQjM+H+6MAAprYBmRsKnUfCVBEjgLQI0QPkomEJADFBGwBeGWhLSv0kDtDB4FrhLtt8rwwm01CQsMJvSTIGpmErDnaOSgJUJlMwpp6ysDH6/PsP7fD6EQiHU1bmrxnggELCNzN2xXvxm7V1Fz1d0LdHhbtL1LbHr8f3un2EwOIKVFcus/H2i69zk+0H0bXddn+kPYv3iVM5y2OnnOleFyzdzVTiFkWil4hC+6rb07wK76/oqwRY44ERdLyAyRGZpTtZ1PM6yXws9B3JeHwswl5FmXTM5OQm9lNTY2IhoNIqREXdVjJEf4MHBwVlkrfdxSFXymUhMoi5ZXfR8RdexWAzDw8PWE9SgGa3Gcq3n586/hLqmaoNGsV63DQ0NSCQSGBoast7kcpyRlJ883duK7UtH1bM/kdNddvm5zkmYjIuaqhrQ2avKcg5erc/6+nqkUqmivx8yhrPFW6fqOhv8tOFph99d2eTIdq68vDzbaZ57iwC34PkoGE5AasBLYx34wlDXBWqwsnyZygd6oLAOeFfJCEj5zWTKoyLgmUarSfmBshpSyR5FDkwCliNAA9RyKnHehKQEp7S2UIvzhDNJop21W5mQ3iTWeg4jAUhSBUhqwLu9SU14JqN3+1NA+UngMgEaoJdZ8J1BBC5Ge+H3+NAUaDBoBOd3e03dVpydOofBmHtcD5ygVTFAVzbH4OU3rZaKKRr3YmiCMJzwbFMGEiiWAL8JiiXI+xckIDlAmwNN8Hr4uC0Ia54Lrq3dpp3ZO3Zwnit42GoEEqro0ek+dyegz9SJVIKSxm34TCp8TwLuJUCLwL26N01yLQVTqNm08Zw4kES/1/lrsJt+oLZRb2d/ALGE+H9GbTNnIycqyeil9bEmvJGY2TcJ2IYADVDbqMq+E5UVUAYgFa+/rZUbwBXQ4jma1YNsv/u9KSxvpAEqzEOBFKrLElwBNesB5DgkYHECNEAtriAnTK870ssAJB0UKXXhD40fRzRJg0YHnIZ3cVwZoMsaYwiULNmd4SLmPYBUROIWfN7YeAMJOJIADVBHqtU6Qkn+z+HEKKsg6aCSbVWbEEvFlBF6TIfe2IWRBJIpQCogcfv9SsqyDc9I+CuZ8BMJuJUADVC3at4kuSUCXlprkD6gxSLfUL4GQU+AfqDFgjTh/guDfkxGvVjTGjFhNPsMISug/aN+lXTePnPmTEmABIwhQAPUGK7s9S0Cl3OA0gAt9qEIeAPYULGO+UCLBWnC/ce7g6pkbEpLwWTCcLYZokmtgEpg1iBTMdlGZ5woCRhFgAaoUWTZr0agmyuguj4J2yo3Yu/oQa1soa4dszNdCYj/51KVfD6sAm/YLhOQFVBpfSN0jL1Mhe9IwJ0EaIC6U++mSS0R8PX+WoS8QdPGdPJAYoCKT+2ZqS4ni2l72SQCfnUrg8VmK3I6F2iKBuhsMPxMAi4kQAPUhUo3U+SLjIDXFfe2qo1af8wHqitWXTu7OOTH2JRP+X/SAJ0NNqgWPmvKkwxEmg2Gn0nAhQRogLpQ6WaKLEFIbQxA0g15jb8aK8JLsUdtw7NZk4Dm/4kUVjfTAJ1LQ0zFNBcVHiMB9xGgAeo+nZsqsWzBtwVbTB3T6YNpfqAsyWlZNYv/56K6OMpD9P+cS0lNVQn0jfrmOsVjJEACLiJAA9RFyjZb1HhK/aKJXkIry3Dqil624Tsj5zEQG9S1X3amDwFZAV3L7fd5YcoKaB9TMc3LhydIwC0EaIC6RdMlkFOMz6T6xxVQfeFLRSRpe7gKqi9YHXrrGfZhZFL8P5n/cz6ckoopzlRM8+HhcRJwDQEaoK5RtfmCyva7NPqA6st+abgddSqzAP1A9eWqR2/Hu0OqG+X/2UL/z/l4TkfCMxXTfHx4nATcQoAGqFs0XQI5Z3KAcgted/riB8oVUN2xFt3hMbX93q78PyvD9P+cDyZzgc5HhsdJwF0EaIC6S9+mSispmMLeMGpV5DabvgTED/TwxHFEklxp05dscb2J/yfTL2VnqKViKlM14RmIlB0Uz5KAwwnQAHW4gksp3nQEPEtwGqGD7coPNJ6K48D4ESO6Z58FEOgd8WFY+X+upf/ngvSaJBCJ1ZAW5MQLSMDJBGiAOlm7JZZNtuBbmQPUEC10lK9ByBOkH6ghdAvr9NjFaf9ProAuzE9LxaQMdjYSIAH3EqAB6l7dGy65bMHTADUGc8Drx8aKdfQDNQZvQb2m/T8rmP9zQX7aCqhKxcRGAiTgXgI0QN2re8MllxXQNgYgGcZZ/ED3qlRMqRQDXgyDnEfHYoAy/2duwJpVKqaYSsU0NMFfQbkR41Uk4DwC/Ol3nk4tIdFofAwTyUmugBqoDckHOpoYw6mpswaOwq5zISD13yX/57o25v/MhRdTMeVCideQgLMJ0AB1tn5LJl13tE8bmzlAjVPB1soNWufMB2oc41x7ltVPD/N/5ooLjaocpzSW5MwZGS8kAccRoAHqOJVaQ6CZHKAMQjJMIdX+KqwML1N+oAcMG4Md50bg6MUgljSw/ntutICyYAqVIVWql5HwuSLjdSTgOAI0QB2nUmsIdFH5f0prCTZaY0IOnYX4gTIhfWmVKy64UgFpLbff81KElOTkCmheyHgxCTiKAA1QR6nTOsJ0qwj4Bn8dAt6AdSblwJlIPtBzkYvojw04UDp7iHR+0I/xiBfrWlkUIB+NMRdoPrR4LQk4jwANUOfp1BISaTlAGQFvuC4kEEka/UANRz3vAEdV/k+vJ4VVrP8+L6O5Tmi5QFkNaS40PEYCriBAA9QVajZfSC0FE/0/DQe/ONymrTTTD9Rw1PMOIP6fy5tiCAeYDmteSHOckEj4qZgXY1OeOc7yEAmQgNMJ0AB1uoZLJJ8YoC3BphKN7q5ht1dtoh9oiVSeSIr/ZxAd9P/MWwPiAyqNgUh5o+MNJOAIAjRAHaFGawmRTCXRG+0HUzCZo5dtlRtxdOIEJhNT5gzIUWYInO0PIBJX/p9t9P+cgZLjm5lcoNyGz5EYLyMBZxGgAeosfVpCGgmISSDJJPQmaWOr8gONpxI4OH7UpBE5TJqA+H8GfCmsaKIBmmaS62tlOKXcFpIqEp4lOXNlxutIwEkEaIA6SZsWkeVyCqZmi8zI2dPoqFiNsDfEfKAlUPORC0GsVsFHfl8JBnfAkFKSk6mYHKBIikACBRCgAVoANN6SnYCkYJLGOvDZOel11u/xYVNFB/1A9QKaYz/ROHCqT/l/LmL5zRyRXXVZowpEog/oVVh4gARcQYAGqCvUbK6QEoAU8ARQ7681d2AXjyZ+oHvHDkH8b9nMIXCiJ4hE0sMApCJwMxVTEfB4KwnYnAANUJsr0IrTn46Ab4THw/QqZulnm4qEH0uM4+TkWbOGdP04Ry6EUBFKYnG9WgplK4iAJKMfm/Jhki60BfHjTSRgZwI0QO2sPYvOvTvaxwAkk3WzpWIDPOof84GaB/6wMkAl/RL/ziqcuayASusZ4h+rhVPknSRgTwI0QO2pN0vPWlZAW5kD1FQdVfkrsKpsOf1ATaI+OumFlOCk/2dxwNOpmLppgBYHkneTgA0J0AC1odKsPuUetQLawipIpqtJ6sKzJKc52I+o6kdQK84di7h3XAzxmvKklsaKK6DFUOS9JGBPAkzAZk+9WXbWkWQUg/FhJqEvgYa2VW3Ez/oe0YoANAcbSzADmw85MQH/yRPw9vbAMzYGBAJINjUhvmIlUo1XVvWS7fdm5b/YUDm9hWxzyUs2fXFfkEj4nmGuhZRMCRyYBEpEgAZoicA7dVjZfpfGMpzma1gi4aXtHTuId9W/zfwJ2HREb/dFBJ99Gv79++BJJJAKhZCqqgaiEXhHRjSpEouXIHLHO5HYMM1YDNCtS1l5Sg+VNyo/0O4hJlLVgyX7IAE7EaABaidt2WCusv0ujT6g5itrUagVTYEGzQ+UBmgO/GMxhB77BQIvv6QMzipE33EnYlu3ItWQsXosq6LHjyL4wvMo//53EV+9Bqff/QkMT/iwnvk/c4C88CXiB7q3K7TwhbyCBEjAUQRogDpKnaUXRiLgpbWGWAWpFNqQVVD6gS5M3tPXh7IffA/eS/2I3vkeRG9VK8b+Ob4Oy8sR37pd+89/YD9CD/0HTvzbG/DWrWT994Ux53RFk6qGNDAKxJjNKidevIgEnEJgjm9cp4hGOUpBQFZAK7zlqPRVlGJ4148p+UCfHnwBk4lJlPnKXM9jLgC+M6dR9r1/Qaq8AhOf/+9ILmqf67KrjsU3bUZi2XLs/2kKqyePofLoWcgxtuIIyApoSgV09Y14UMZsTMXB5N0kYCMC9Py2kbLsMNXpJPRXBmzYYd5OmaOsgCaQxP7xI04RSVc5fKdOouxfvoNkcwvG//CPcjY+05OIllfhSHANNpZ3I/yjH8B35HD6FF8LJCA+oNKYiqlAgLyNBGxKgAaoTRVn1WlLHXj6f5ZOO2vLVyHsDTMf6Bwq8HZ1ouy7/4JE+2JMfOazgNpez7edVOU3Ywkv1rynA4lVq1H2wPfhPX8u3254fQYBySTg8aRUJDyXPzOw8C0JOJ4ADVDHq9hcAcUHlDlAzWWeOZrf48Pmig76gWZCUe89AwPK+PxntfLZjMlP3wsECwt6OXR+uvzm0uYkJj/+KSRVeqayf/1fKm2TcmJkK4iAT/0WaqwCepmMviB+vIkE7EqABqhdNWfReYsPaGuIW/ClVI9sw+8bO4RkKlnKaVhn7GgUZd//X8roDE4bn6FwwXMTA1SqH3llsU6la5r81KfhiccRfvABIJUquF+339hSyxVQtz8DlN99BGiAuk/nhkk8lhjHeHKCdeANI5xbx5KQXvRwYvJMbjc4/Krwf/wM3v5+TH7i00hVqqW2AtvQhBcXhgLY2B6Z6SFVW4fJj35MS2AfeP65meN8kx+BVjFAuQKaHzReTQI2J0AD1OYKtNL0mQPUGtrYUrlBxRR76Aeq1BF4/VUE9uzG1Ad/E8n23KLd59OirH5Km53/M9GxHtEbbkToiV9pVZTmu5/H5ycgK6C9Kgo+yUXk+SHxDAk4jAANUIcptJTipHOAsgpSKbUALQXWmrIVyg/0QGknUuLRPSrHZ+jhhxDbpvJ47ryu6NmIAbq4PgapXz67Rd53t1Y9KfxvP+VW/Gw4OXxuqUkhnvBAVpnZSIAE3EGAP+3u0LMpUvawDKcpnHMZRLbh96iSnK5tyh8z/LMfq1yfZdrqZ7EcksrmlPKbGzK236/oUwU1TX3ow/B1ntVWXa84xw8LEpAVUGn9I0xNvSAsXkACDiGQkwF69OhRPPHEE+hXflTZ2sGDB/HUU09haGgo22U851AC3ZE+1PqrVRqgwiKMHYqlJGJtrdyEi9Ee9Eaz/8yWZHImDBp46UX4z5zB1Ic/CoSLT8h/qi+Ayaj3Cv/P2WIk1q5DbPMWBB9/DJianH2an7MQkBVQaX2jrAmfBRNPkYCjCCxogN5///247777sHv3btx7773o7OycE8CXvvQlPPjggzh06BA+97nP4dw55sabE5SDD06nYGIEvBVULJHw0vaMuW8b3qP+AA49/ihi11wLMQr1aLL9Hg4ksbI5mrU72Yr3RCIIPfVk1ut48koC4SCUa0MK/aNcAb2SDD+RgHMJZDVAz6gVhOeffx7f+c538OUvfxkf+9jH8MADKt3IrHb69GnEYjF8/etfxxe+8AXs2LEDTz7JL+BZmBz/UaogtQZZA94Kil4UakFToMGV+UBDjzyEVCCAqbver5sqDpwLa+mXJGdltpaqq1d15W9D4KUXVO7RS9ku5blZBJrVKihXQGdB4UcScDCBrF+np06dwpYtW+D1Tl8mhqWscM5uK1aswN///d9rh2X7fe/evVi2bNkVlyUSCURVPr70fynmzLuCjxM+SBQ8A5Cso8ltahvebX6gvuPHEDi4H9H33FVQpaO5tDesAmPODfizbr9n3he9/Q6kwmGE/uvxzMN8vwAB8QPlCugCkHiaBBxEIOt+x8WLF1FTUzMjbnV1NS5dmv+vevET/Zu/+Rt0dHTg5ptvnrlP3nz3u9/VtvLTB3/84x9j+/bt6Y9FvwbUikdFRUXR/ditg7a2NstMuffNfqxpWAWj5yS6Li+gjKJlQBU4kXy53jZ5I/7vg/ehuqkGFf78y04WOE3dbysry82HM6X+yJ34+7+DZ+UqNLz/A6q8oz6lHQ/unRbpjh21qK+qzUm+6Ac+iOiPf4Saj/w2vKr0Z74tX13n278Vr29vAHad8hn+/WE12d2oa9GBk+WemJiw2mNmyflkNUB9Ph9k5TLd4qriR7ZfBnfeeSduueUWfPOb39S247/2ta+lb8Wtt94KMWDTrb6+XrdgpaqqKsjcJifd5fgvBvf4+HgaaUlfB2PDmEpGUJuq0k2vcwlUWVmpPZPU9Vx0rjy2PrAaiVQCz3e9jBvqrrnypA0+ia6TKvw81y9zz6+fhffiBST++EuIDg/rJuErR8qxtNELb2JMPds5dqv8T32/fARjKi1T8lO/m+NN05dZ6ec6r4kXcbHI3FTlwUTEj3Pdw6gMuyMhqFt1LY+KVX53FfHYznur2E5sCxPIaoA2NTVh3759M70MqHrKc/3V0tPToxkd69at01amPvShD+GP//iPZ+6TN3JO/ku3vr4+3QxG+SF2owEaVtt8VjHEzk50aqqtR62hcxJdyx9FVpE7/Twb/VqIrpf5FquMBGG8OrALW8MbjJ6i7v3LKnfOulZR5xWP/RJxlfNzqqUV6gHRZT4JlX7pYFc1bl8/nvczF7jtdoSUERq5/R1aDfpcJ1SIrnPt26rXycJGk7Y+4UdXXwzLG2NWnaqu83KjrkVmaU7+DnfjDl0hPxjTzp3z3HnttdfiwIED6Orq0gy8Rx55BNddd512tTw8Z8+e1d7LCsWf/dmfYWpqSvv8zDPPYPXq1fP0ysNOJCApmKS1BBudKJ4tZfJ7fNhc0eGKQKTgs89o0eeRd79XV12d6AliKubFpsWXy2/mOkDs+htVHtIKBJ99OtdbXH3d5VygXD1y9YNA4V1DIKsBKlvmn/3sZ/GZz3wGn/jEJzA6Oop77rlHgyM5PyXiXZoEIX34wx/Wrv30pz+N3t5ezSDVTvJ/riCQroLUHKABaiWFSzqm/eOHVYnDq6v3WGmexczFMzKC4IvPI3bjzZAodD3bgXMhVISSWN5UwIqc8lWO3XIr/Ht2wTM0qOe0HNlXjXJTDvmTKhI+68acI2WnUCTgRgIL/qTffffdePe7342Iym0nPlnptnPnTjz88MPpj/j4xz+uGaeyCsrl5xksrnkjEfAN/joEvAHXyGwHQaUi0j9dfAAnJ89iTfkKO0w57zkGn1Ep3zxeRN7+jrzvXegGSb+0sX0K3gLjmaI33oTgM08j+MLziNz9gYWGc/35xqqEioTnCqjrHwQCcAWBrCugaQISdZxpfKaPz36VdE00PmdTccfnnlgfWkNMQm81bW+u2ACP+ufUhPSewQEEXntVy72p0mDoir9vxIeeYX9B2+8zE1FVmGLXXa/NUfkozRzmm7kJNFXFmQt0bjQ8SgKOI5CTAeo4qSmQ7gSmc4AyCb3uYIvssMpfgVVlyx2bDzT49FNAMKgM0LcVSerq2/er7XevJzV//ferb5nzSPTmW4BYFIE3Xpuc19F3AABAAElEQVTzPA9eJtBYneAW/GUcfEcCjiZAA9TR6jVPOKmC1EL/T/OA5zGS+IHuGT2Yxx32uFRb/XzzdURvuU3Ve5+OrNVz5vu7wlilSm+Wh4pLCSR+qfENmxBU9elVXik9p+i4vprUFrwk/o/GHScaBSIBEphFgAboLCD8mD8BqWrVG73EKkj5ozPlDjFAL0S70ad05KQmke/a6ufNt+ou1mTUg+PdQWxekn/0+1yTialVUK8qzek7dmSu0zz2FgHZglcOvbg0tmB4ApmRAAnYnAANUJsr0ArTH4wPIZaKsQ68FZQxxxwkEEmak8pyekaG4e3qROSOdxqy+nn4QkhlDvAoA1Qfv83EylVIqPyk2iroHDrioWkCEoQkjTXhp3nw/yTgZAI0QJ2sXZNkS6dgYh14k4DnOUx7qA2NgXrsHXPONnzw18/B19+H2M7pvMR5Ilnw8n1dIVWZJ46WmsuV4Ba8aYELYioi3nfsKDxZyhkv0IXjT9dXJDS/234VAMZGAiTgbAI0QJ2tX1OkkwAkaTRATcFd0CBbKzc4ZwVUFb4IvPoKJNG7SrtREI9sN4mb5kGVfmnLUn1WP9Njxbbv0FwGAq+/kj7E11kEVCIV1FcyEGkWFn4kAUcSoAHqSLWaK5SsgEqqn6Zgg7kDc7ScCWyr3ISjEycwldTHpzHngQ24MPjSCyqYJzGdesmA/k/1BTAe8erm/zkzxVAYsa3bVTT861A1RmcO882VBCQQiVvwVzLhJxJwIgEaoE7UqskyyQqobPFK6Uc2axKQQKR4KoEDYzYPgonFEFAGaGz7NUhV1xgCe19nGOXBJFarCHi9m+QE9Y6NwX/4kN5dO6a/RuX60M9qSI7RJwUhgfkI0ACdjwyP50xgOgcok9DnDKwEF64rX42QJ6j8QO1t+ARU2iWP2oKP3Xa7YRT3qfRLmxar6kcGfDsmlyxForWNOUGzaE9WQC+N+VQQWJaLeIoESMD2BAz4irU9EwqQJwHZgm8N0gDNE5uplwe8fmysWGdvP1DlnBl8/tdIrN+AZLMxRQ96hn3oHfEr/0/jXBUkcMp39Agkkp/tagKyAppIejA4zh2Vq+nwCAk4hwANUOfosmSScAW0ZOjzGljSMe1TK6CSt9WOTbatvZf6Dal6lOYh2+8+b/HVj9L9zfWqBSOp5dXArjfnOu36Y02qGpI01oR3/aNAAA4nQAPU4Qo2WrxkKom+WD9zgBoNWof+tyo/0JHEKE5PderQm/ldBF5Qq5/tiyE5NY1qe9X2+9rWKMIBA410VbM+rlZx/cqdgO1qAo0qCl5aH1MxXQ2HR0jAQQRogDpImaUQ5VJsUAtuaQk2lmJ4jpkHAUnFJM2OfqDe8+fhP31quuxmHjLnc+nopBenewPYqnP6pbnmENuxE76+Pi2Z/lzn3XwspIz/6rIEA5Hc/BBQdlcQoAHqCjUbJ2RPtF/rnDlAjWOsV881/mosDy+xpR9o8MVfI1lVhfiWrXrhuKofST4v655bdKp+dNUAGQcS6zqQVDlMuQ2fASXjrVREYiqmDCB8SwIOJEAD1IFKNVOknmivNlxr0JigEDNlccNYko5pz+gBW4nqGRuFf+8exG64CfAZF5iyV/l/LmuIobZCZaI3uik54ionqH/fHuYEnYO1VKFiKqY5wPAQCTiIAA1QBymzFKJIBLxX/WsI1JVieI6ZJwHxA+2MnMdgzD4R2FL1SFrs+hvylDb3yyMxD45cDGHrMn2rH2WbgQQjecfH4Tt+LNtlrjzHFVBXqp1Cu4wADVCXKVxvcXtVAJJUQPIxCb3eaA3pT1ZApUk0vB1aKhFH4JWXtdXCVGWVYVM+dD6EeMKj/D+NS780e/LJpcuQrG9AYM+u2adc/1lWQKdiXoxNeVzPggBIwKkEaIA6VbMmydWttuBbAgxAMgl30cMsL1uCGl+VbfxAU7t3wTs6guhNtxQte7YO9naGIEZPW20822W6n4ttU9vwBw8CUf2rLuk+WRM7lGT00rgNbyJ0DkUCJhOgAWoycKcNJ0FILfT/tJVat6p8oHvHlNFjg5Z65mkkVPWg5OLFhs02oVw+D5wLm7r9nhYmrgxQTyyqSnPaQx/peRv92vhWLlAGIhlNmv2TQOkI0AAtHXtHjDydhJ4roHZSpviBHhw/iljS3NW+fBklz3UBJ08geuPN+d6a1/XHu4OYiHqxzYT0S7MnlmxuQaKtTQuymn3OzZ+rwkmE/EmugLr5IaDsjidAA9TxKjZOQC0JvVoBZRlO4xgb0bPkA42mYjgycdyI7nXrM6lWP1FZaWjqJZnsnrNhLe/kiqaYbnPPpyMtGl6V5sSUeQFQ+cyvVNdKRSSugJaKPsclAeMJ0AA1nrFjR+iPDSCBJLfgbaZhqQnvV0Fjlk5Ir4yx5Ksvw3PzrYDfbxhhqUoq6Zck+bynRPEusc1b4UkklC+ovdJjGaaUtzqWmvB9I8bp3uj5s38SIIHsBGiAZufDs1kIyPa7NFZBygLJgqfC3hDWla+2tB+olqBdBeZ4bn2boQTP9AcwPOkzpfrRfIKkGhq0EqOB/Xvnu8SVxyUQifXgXal6Cu0SAjRAXaJoI8RkFSQjqJrTp/iBWnkFNPDKS/Bs2gxPo7H+xbL9XhZMYl1baaPQpcKTlg90atKcB8AGo4gBOqzKo0at7apsA5KcIglYkwANUGvqxRazkipIPpWEvjFQb4v5cpKXCWxTfqB9sUu4EOm+fNAi73yq5ruvtwe+2+8wfEZigG5ePAVfib8JY5u2TG/DH2I0fFrpsgUPeBiIlAbCVxJwGIESf+06jKbLxJEV0KZgI7wePkZ2U72sgErbY8GE9AHl+5msrdVWQI3kemHQr4Jc/NhmYvWj+eTRtuEXtSOwf998l7jueDoXKAORXKd6CuwSArQcXKJoI8SUMpz0/zSCrPF9Nqs/HFpV/lar5QP1qNKUfmWExa69Hh6vsV9Pu9XqZ8CXwoZ286ofZdNsfPMW+I4dRYrb8BqmuoqE+uM2pf2RkI0bz5EACdiTgLHf8PZkwlnnSEC24FuCTTlezcusRkDSMVnNAPW/+TqgQtPFADW6yfb7xvYpBC0SaB1TBqhEw6f2cRVUdC9/fzRUqkCkEZ/RjwL7JwFbE/iHf/gHvPbaa7aTgQao7VRmnQn3qDrwsorGZk8CUhf++MRpTCSsE/gSfO0VxNdvRKq62lCofcqoOT8YsMT2e1rQVGMTEi2tSO1+M33I9a9N1SoVk3KTYCMBEpifwLe+9S288sor819g0TM0QC2qGKtPK5FSKxPRS2hmHXirq2re+W1RK6BJ9e/AuEqCboHmU1WPvP39iF1/g+GzkdVPnzeFzUussf2eFjiuIv9TB/YDsdIkxU/Pwyqv4gdKH1CraIPzIAF9CdAA1Zena3q7FBvUktCzCpJ9Vb62fBXC3rBl0jEFXn0Fybp6JNasNRyq+H+ua4uoFEwqE72FWnzjJkDlP9VSMlloXqWaSpOKhB8Y8yGZLNUMOC4JWI/AE088gXvvvRcf+chH8Pjjj18xwRdffBF//dd/jZ/+9Kf4wAc+gK9//ev4/Oc/j4Ry78lsX/ziF/HSSy9lHjL9PQ1Q05E7Y8Bu5f8pjT6g9tWnVEPaWLHWEn6gWvDRwf3Tvp8GlyQaGvdCEtBvt0D0++ynJ6ki4dHQiACrImloGlU5zmTKg4Fx+oHOflb42Z0EfvWrX2mGZUr5yu/cuRO/+7u/i7Nnz87AOHbsGO6//378xV/8BWpVNpGamhr80z/9E5566qmZa8RI/fa3v41Vq1bNHCvFGzrXlIK6A8ZkEnoHKFGJIH6gP+19RMX9pFQpyhLVolTzuBx8dK3hYGX1U0SV8ptWbJ5t2+F7+UVoy34GZwKwovyZc8pMxdSotuPZSMDtBGTl8s///M/xla98RUPx0Y9+FGvXXrlr1Nvbi8ceeww7duzQrnn22Wfxwx/+EHfeeaf2+Qc/+AHe+973oqWlpaQ4uQJaUvz2HVzKcEoS+oZAnX2F4Mwh+UBHE2M4PdVZUhrB115VwUcbkKoyNvhIhBT/zzUtUVSGrbX9nlaAVxmg3okJ+M6cTh9y7WtjpSSjV6mYWBPetc8ABb9MYFylqTt+/DjuuOOOmYMrVqy4ygANhULYtm3bzDWf/vSn8Z//+Z+YUN8rkUhE256XY6VuNEBLrQGbji8GqOSSZBJ6myrwrWlvqVyvvStlWU7fqZMq+KgPseuMT700qko7nugJWnL7feZJWr0GyfJy+FkVCQG1R1dbnmQg0szDwTduJjA6Oqo2RpKIx6+sTxsIBK7AIlvv3ozdk/e85z2orKzEQw89hF/84hfw+Xy4++67r7inFB9ogJaCugPGFAO0hSmYbK/JGn81loeXlNQPNPD6q1rlo8SadYbz3NsZVutpavvdgv6faeElAX9CpaLy0w9UQyKBSP1MxZR+PPjqYgKtra2Q/yQIKd36+vqwb4HcwX6/H5/85Cfxk5/8BA8++CA+/vGPY7bRmu7PzFf6gJpJ20FjSRWkRaHS+o84CGdJRZF0TCVbAVVbQlL5KHq72lLK+IvdKCDi/7myKaatqhk1hh79xjdsREAl5fd2X0SytU2PLm3bR5MKRDrTd+UKj22F4cRJoEgCv/M7v4Mf/ehHmj/n1q1b8dWvflXz4V+oW9lyT/uEvvzyywtdbsp5roCagtl5g0yvgLIKkhM0KxWRzkx1YTg+Yro4gd27oPKDqOj36wwfeyLiwdGLQWxbbs3go0wAcZWKKqVWLbgNDzSqFVAmo898OvjezQS+8Y1v4F3vehfuuusutLW14dy5czOGZTYuHR0dEIM1/ZrtWrPOcQXULNIOGkdLQh8bYAomh+hUApGk7Rs7jFtrjffDzMQWeP0VJNZ1IFVTm3nYkPf7usJaSh8rpl+6SuBgEAnlCyoGaPSOd1512k0HJBI+lvBgeMKLGuUPykYCbiYgvp2SVkmqH42NjaGxsfEKHLLSOV+AkVVWPtMT5gpomgRfcybQr4xPqaDDJPQ5I7P0hSvDS1Hpq1AG6CFT5+ntPAtfd7cpdd9FsF1nwljaENXqi5sqaIGDyTa891wXPKPmr0wXOGVDbpNynNJYEckQvOzUpgTC4fBVxqfdRKEBajeNWWC+4v8prTnALXgLqKPoKUj+zy0V6033Aw2o1EvJqirEO6Yj8YsWJEsHUzEPjlwIWTv6fdb84x0btCP+I4dnnXHXx5lcoEzF5C7FU1rHE6AB6ngV6y9g71sGaGuIBqj+dEvTowQiSU14ca8wpUWmENi7B7FrVOJ5lRLE6La/K4R40oPtNvD/TLNIVVcj2b7Y9X6gUi61IsRUTOnngq8k4BQCNECdokkT5ZAVUCnj2OBnEnoTsRs6lPiBTiancGLSnOTngT17gFjUtO333Wr7vb0uhmYVUW2nJsn5fSeOK1YxO01b97lKKiYGIumOlR2SQEkJ0AAtKX57Di4R8E2BxpKWbrQnOevOelPlOnjUv70qEMmMFnhNBR+tWo1UQ4Phw0WVC+HB82Fss3Duz/kgxFU+UI8yPn0nT8x3iSuOSyqm/hHjV8pdAZNCkoBFCNAAtYgi7DQNpmCyk7Zym6sEIa0qW25KQnrvhfPwnT+nKh/dkNvkirzq4LmwFkVti+j3WbIm29uRVFvx/iPmBojNmkbJP3IFtOQq4ARIQHcCNEB1R+r8Dnui/YyAd6CaJR+oGZHwWvCRKjUZ37jJFIq7VPL5lpo4FtVdWb7OlMF1GESCkfyH3W6AJjAR9UJyubKRAAk4gwANUGfo0VQpuqO9Wh14UwflYIYTkECkc5GLGIgNGjdWNIrAnl2I79gJqETrRreYcvk8oAKQti+bNHoow/qXLAHe4WF4L14wbAyrd9z4ViqmXpbktLqqOD8SyJmA8b8Bcp4KL7QDgbiKkr6kDJRW1oG3g7rymqOsgEqThPS3192U1725XuzftxeeqSnTtt8Pnw8hEvfaKv3SbJaSkF6riqTSMUXbFs0+7YrPzSoZvbQ+5Qe6vNHdAVmuUDiFnJfA0NDQvOeKPVFba3xBkMw5cgU0kwbfL0igP3qJSegXpGTPC5aFF2uZDY5NGBcJH1TBR/HlK5BsbjYFktR+b6yMY0mDPbffNUhSFWnlKvhcnA+0qiyJkD+Jfq6AmvJzw0FIwAwCNEDNoOygMWaS0AevLP/lIBFdLcqmyg68OvKmIQy8Pd3wqepHZgUfJVTVRim/aYfa7wsBl214YYeJiYUudex5iYTvZSS8Y/VLwdxHgAao+3RelMS9sekqSNyCLwqjZW/eVNGBQxPHIK4WerfAq68gVVaG+OYtenc9Z39HLwYxqQJX7Bj9Plug+Lr18KRS8B87OvuUaz4zEt41qqagLiFAA9QlitZLzOkk9H7U+831FdFr/uwnOwHxA51KRnBs4mT2C/M9q3JZBna/idiOa4BAIN+7C7p+15ky1JUnHOEzKPlSE01N8B81J09rQcANvklWQMUHlI0ESMAZBGiAOkOPpkkhOUCbmYTeNN5mD7SxYh286p/e6Zj8+1Xw0eSkadvvSdl+7wxpyedVqXtHtIRKx+Q7egQQ4VzYZAV0dMqHqZhDFOpCHVJkEsgkULIo+HA4rLKw6DO8T9WSDoVCMDuCKxNkKd4H1EqS2TIPnB3G4vI208dN8xVde5RFYbbc6fFL9WqWrmtRi3WVq3E4ekJXxok33wBU5aPqdR05IxRde73eguZxsMuLsYgPt27yF3R/zpM04ML5dJ26ZieSzz+HmqFBeFRQkpNa+ndBtp/rFYum10si6hltrU05Qvz5dO0I4eYRQmSWlk3X89xqm8OJhP4uTLYRPo+J6mMB5jFg+tIplYpFLyU1NjYiqvILjoyMpLt3xWtdXR2GVX5AM9u58fNYEm43fdy0jA1qKzKmtnOp6zQR/V83la/DiwOv66Zjb/dFlKtSklO/fQ/ieTyv9fX12ndEIc/4CwerUBX2o6ViUMmhPyMje5z357qpGRXBEKaUMR9tcFYQoMicUj6u2XRdrv4YAZpx6sIkaoMRI1VgWt/z6tq0GZg/kBiesoiQTdfmz0rfEcuUr7uT265duzTxduzYUZSYJTNAZdbyhaNHk37S/+nRn136KIXM4gO6s2qbbrorlLVez06h45t9n5m63lyxHj/rfQT90QE0BOqKFtX/yktIqcpHsU2b5Yc+7/7y1bUMsUelX5La7x7Id0PeQ5b0hnl1rVaE46tXa+mYUu96d0nnaNTg2XRdU5ZAwJfS/ECzXWfU3Izod15dGzGYhfp0q9wWUkHBU+nv78ddd92FP/iDP0CxBih9QAtWg/tujCXjbyWhb3Kf8C6SeEvlek1aSUhfdItGVPDRLhV8pCofmRR8dLovgOFJn2aAFj1/i3WQkKpI58/BMzZqsZkZPx3x5W1UfqC9IyVdNzFeUI5AAhYm8Hu/93tobW3VZYb8SdYFozs66YtdkvUktARpgDpZ45KQvtZfrQUivb3IikiBPXsA5W4Tvf5G05BJ8vnyYBJrW6OmjWnWQPG1HQirwXxHjyKufELd1polEn6UkfBu0zvlnUVgcBDeR34+62BhH5N3vhfKoszp5n/+539GS0sL1qxZk9P1C11EA3QhQjw/Q0Ai4KXRAJ1B4tg3sg2vRyR8QG2/J1TwUUqlEDKryfb7lqVT8Dlwfyel/OcSLa0qHdMRVxqgEgn/xmln+9eZ9XPCcWxMQAU5eS5d0keAeG6lbU+cOIFvf/vbeOGFF/BXf/VXuoxNA1QXjO7opDvaqwlKA9T5+pZt+H+5+KCWkN7vKWzFydvVCd+F85j8b580DVjXJT8ujfnxkWXODUhMqEwCgddfnU7HpAXmmIa35ANJLtChCS+iqrJqkL+9Sq4PTqBEBFTgdeKPv2Ta4PF4HJ/61Kfwj//4j6ioqNBtXP4I64bS+R31RvsR9ARQH2ASeqdre8tbCemPT5zC+orCtluCL7+EZFU14hs2moZLtt+lZvj6Rc6Ikp4LXFwZoMFfPwvvuS4kly6b6xLHHpMVUKjQMqkJv6hO3rORAAkYTeDQoUN47bXXcOedd2pDRSIRLZPBhQsXNKO00PFpgBZKzoX3yQpoM2vAu0LzUpIznZC+IAN0fBz+fXsQvf0O5bBY2ApqIaBl+33TYhX4ZN6QhUyzqHsSy5YjFQxq2/BRtxmgagVUmtSEpwFa1GPEm0kgZwJbtmzR0h+mb/jTP/1TVFVV4S//8i/Thwp6daCXVEEceFMOBCQFE7ffcwDlgEvKfWVYVbYM+8YLi4QPvrVFHLvuBtNo9Az70D0ccGT0+xUQVQGP+Oo1mgF6xXEXfKirSMDvVamY1AooGwmQgL0J8KfY3vozdfYShLRSGSVs7iAg2/CvjkwnHM5LYlUqMvDKy4irvJ+p6uq8bi3mYtl+F+Nko1oBdXpLrF0H/0P/CY9aaU7p6JNldW7et1IxsSa81TXF+TmZwN/+7d/qIh5XQHXB6I5OZAW0lSmY3KFsJaUEIp2LXMRAbCgvmf2HD8GrykXGbrolr/uKvVi238X3MxywWeb5AgQXP1CPyrDvO360gLvtfUtTVYK5QO2tQs6eBDQCNED5IOREIJaMYTA+xC34nGg546ItFRs0QfbnmZA+8NILSLQtQmL5CtNADIx70XkpiK2q+pEbWqpOlSlVqa38Kh+o21pTdZxb8G5TOuV1JAEaoI5Uq/5C9agIeGn0AdWfrVV7lIT0Vb5K7M/DD1TqvvtV3ffozeaufu5Vq58eTwpblrjDAJVnJqGS0vuOKQPUbrVGi3zgJRn9oPqDI8Yg+CJJ8nYSKC0BGqCl5W+b0ZkD1Daq0m2iHlX7cLOKhs+nJGfgxeeRVD6J8W07dJtHLh3t6QxjTUsUlWHnb7+necg2vHd8DF6Va9VNTVZAtVRMKt8rGwmQgH0J0AC1r+5MnXm6ChJ9QE3FXvLBJBDpwPgRJFPJBeciATFa3Xcpu6kitc1qY1MenOhR2++q+pGbWmLFSqQUZ7dtwzcrH1BpkoqJjQRIwL4EaIDaV3emzrwn1o+wN4QaVSOczT0EJBBpMjmFE5NnFhRaym7KdnDsxpsWvFbPC/Z1hdWwHtf4f86wCwQgRqjv2JGZQ254U1eZUGVWVSqmEfP+yHEDV8pIAmYToAFqNnGbjtejktDT/9Omyiti2ptUTXhpCwYiqVJtAVX5KL51O1Kq+pGZba/afl/aEEN9xcKrtGbOy4yxZBve13kWmHLP6u90KiaJhOcKqBnPGMcgAaMI0AA1iqzD+tWS0AeaHCYVxVmIQJW/AivDSxdMSC9b796xUURvvW2hLnU9H4l5cPhCyHXb72mIkg/Uo/Ku+k8cTx9yxWuzKsnZyxVQV+iaQjqXAA1Q5+pWV8m6I6yCpCtQG3W2WW3D7xs7NP+M1bZ74PnnEF+zFkmVfsnMdkgZn/GE2n53mf9nmnGyuQXJ2trpaPj0QRe8NksqJhqgLtA0RXQyARqgTtaujrLJFjwDkHQEaqOuxA/0zFQXRuNjc87apxLP+3p7EH3b2+c8b+TBvZ0hNKnVMDfXBY+vUVWRXJaQvklSMU0wFZORP1vsmwSMJkAD1GjCDuh/KhnBcGIUrSFuwTtAnXmLsDmdkH6efKChZ59Gon0xEqo+uZktoVw+D6gAJLeufqZZJ9atg3dwEJ6+3vQhx7/KCqikYmJNeMermgI6mAANUAcrVy/R0imYWoLNenXJfmxEYFXZMpR7y+bMB+o7fUoLgonebv7qp6Remoh6XW+AxpXhn/J64Zek9C5psgIqjYFILlE4xXQkARqgjlSrvkKlk9BzC15frnbpzevxYmPFOi0f6Ow5B59+EsnGRsQ3bp59yvDPEv1eGU5gRXPM8LEsPUC4DIklS11lgNZVJOBnKiZLP5acHAksRIAG6EKEeB7pFdBWroC69mkQP9D9Y0dUvs3LlYa857qU7+ExRG5/B6BW4Mxu+5T/55YlEUhaHrc3iYb3nToJqHRYbmjTqZhUJPwoc4G6Qd+U0RoEHnvsMXz1q1/FqVOndJmQ+b81dJk2OzGTgKRgqvRVoMJXbuawHMtCBDapkpwjyg+4M3K57GPoySeQrKtDfLu5ZTcFy7kBPwbG/dji0uj32Y9GXNIxxWLwnTk9+5RjP0tN+N5h5gJ1rIIpmKUI7Nu3D/fccw8qVKnlsrIyXeZGA1QXjM7uhCmYnK3fXKSTFVBp6brw2urnkcOI3vFOwGe+ESDb7wFfCh1tkVym7/hrkioILFVerspyuqcqUnMNc4E6/sGmgJYgEFc7K3v37sXWrVtx7733oq2tTZd5cf9CF4zO7oQpmJyt31ykqw/UYVGwVauI9P7GdyH0xONI1tcjtmNnLrfrfs0+ZYBuaI8gyG+wabbKBSK+ei18Wjqm9+vO24odSjL64UkfpBhBKHDZNcSKc+WcSEBPAj0qL/e3zv6LLl3eu/gerChfmrWv48eP4/7770dXVxf+6I/+CD/84Q+zXp/rSX5950rKxddJENK2qk0uJkDRhYCsgu4bPwTv2TMq4OUIJj/y2yVZ/Rwc96JrIIC3rR+nYjIIyDZ82b498IyMIFVtbjnUjGmY9la24KX1jfqwuN4dvq+mweVAliYgqRH3j+qz2zGWmFhQ1vXr1+MrX/kKvvOd7+hmfMqgNEAXRM8LxAeUAUh8DqQi0n8NPIfkiw8j0dSkfD+vKQmU/Sr3pwcpbFYBSGyXCSTWrtU+yCpo/JprL59w6DvZgpcmJTlpgDpUyRRrTgLLyhbjoWu+N+c5Ox2kD6idtFWCuY7GxzGRnERLkEnoS4DfUkNuVoFICSRxZPgQou9+b0ki3wXIvq4QVjTFUBVWmejZZgikqmuQaGl1TTqm2vKkcsFIMhfozBPANyRgLwI0QO2lL9NnK/6f0pgD1HT0lhuwI7wSgaQHu1ap+uubtpRkflPK3+/YRZV+idHvc/LX0jGp1FhIusM4l234nmFu5M35MPAgCVicAA1Qiyuo1NO7OGOAsgpSqXVR6vHLX38DG4bKsHt1uGRTOXxBGb/KCOb2+9wqED9Q78QEvBcup8ua+0pnHJWSnH1qC56NBEjAfgRogNpPZ6bOOJ2EnlvwpmK33mDKqAn+1+PY4l2GvcmzJZvffrX93qiin9tqGXQylxISy1cg5fe7ZhteDNAeGqBzPQo8RgK6EvjgBz+IRx99VNc+aYDqitN5nUkAUp2/BiFv0HnCUaKcCYSe+JWW6Hxjx53oi11Cb7Q/53v1ujCpMu0cUAYoVz+zEA0EkFi5Cj6X1IWXLfjxiBcTEZbDyvJU8BQJWJIADVBLqsU6k5rOAcrtd+toxPyZeLs6EXj1ZS3p/Kbm6cj3dEJ6M2dzpi+AsYhPld+cMnNY240l2/C+TrVKHXE+J1kBlcZVUNs9ppwwCYAGKB+CrARkBZTb71kROftkIoHwf/wbkk3NiN52O9pDbWpFvBb7xw+bLrekXwoHkljdEjV9bDsNmFizFh4VhOQ/ccJO0y5ormkDVFIxsZEACdiLAA1Qe+nL9NlKEnpGwJuO3TIDBp97Ft7ui5j68Edmks5vruzQKiKZPUnx/5TqRz5+a2VFn1SpmJIqJdN0VaSsl9r+ZGU4hfIgUzHZXpEUwJUE+FXuSrXnJnQqlUKP8vVjEvrceDntKu/FCwg+9QRiN92M5LLlM+JJPtDDE8cRT01Xopk5YeCbgTEvLgwFsHkxk8/nglm24f1u8QOVmvBMxZTLY8FrSMBSBGiAWkod1prMQHwIsVSMBmixalGGvGdoEGLQyWqilEq0fIvFEP7xj5Cqq0fkPXddMV2piCSl4E5Onr7iuJEfDpybrn60cbHz/Rr14Cj5QL0DA/D0mx8spsf88+mjhZHw+eDitSRgGQJ0nLGMKqw3Edl+l0Yf0AJ0E40isGcX/AcOwHfmFDzqc2ZLhcNILF4CWamSpO6p+vrM0yV/H3r45/D292HiD74AqMjqzLaxYp0qhemBBCKtK1+decqw97L9vlxVP5ItV7aFCcRXr0HK44FfleWMNTYufIONr2hRK6C7z5YuN62N0XHqJFBSAjRAS4rf2oN3R6YN0LYQo+Bz1pQK2gm8/CKCTz8Jj8qdmVi+XAveSbYtQqq8HJDV0LExeHu6lWF6GqHHH0Po0V9oqXNiN92C+IaNJStxmZbR/+brCL7+Kqbe/0Ek2xenD8+8VvoqsCK8RPmBHsFHmt8/c9yoN1EV6Hy0O4T3bR01agjn9auetaT6A0e24WM33uw8+TIkklRM0bgXQ+Ne1Fa4owJUhvh8SwK2JUAD1LaqM37iEgHvU4kSGgPWWp0zXvLCRvCoFcOyB36gbbXHt1+DyP/P3nvAx3Vc5+Lf7t2GXgiAAHsDC8DeSXXJkmxLbpEdRbbluMhK7Dwnz3FiJ/kl/1+Sl/dSnBc7finudmwr7k0usmRZvVLsBEk0AiBAAiBIdCy27/7PXGhZQJQt9+6duXuGP2mxd+/MnPnO7O7ZM+d85/Y3IFFdPctgW6auBwJwnziu0xwVfOu/EK+qRuiOOxHdstUSQ9R5tkvPeo/Q/JEbbpxFdmAjHcOfIA9oLlpLH1U/ijmwkeM/04JbeNc9zz8L0I8iaFpafVW6OZkJL6iYyouuPWlQaR0sKyOQbwhwDGi+aTyN9Yoj+GpPFTSHfb+80oBjzlsF8XfRv/0rHMEgJj/yPxC8/4E5jM+rhiooQGT3Hkx+7H9i8uGPIF5ejoLv/jcK//VfoDXnxsBLSuO4SAb0f30VwlsbfOf9ycszPm4u2oDOYDfGo/4ZXzfyYtM5L8oLY1hSSa5QbikjIAxQEfqh0Y8KO7cpA5QSJjkRyc5q5rXZEAH2gNpQqUYtSZTh5Az4+dF0HT+qJ+zEVq5C4D3vA8RRewZNVLAJiCo2HWfgfewXKPz6VyBi+UL30DF3RUUGI6bexTE8hMIvfx4ggzjw/g9dF/c5faSNRMUkWpO/GfvKpsjpp99j1POTZIA2svczbTjjS5dBxBqLH0dib9m1eehbrIKO3gfG+IeyXXXM67InAuwBtadeDVlVH3OAzouj1nxKNz6jDRsR+OCHMzY+r55IGAuTf/CHCLz7vXAODqLwc59BjI7nHePmxEA6By6g8PP/DlDSyuRDv4dEcfHV4sz495qCFfA5fboBOuMNBl08N+jAkN9Fx++c/Z42pE6n/gMmH+iY9Ex49oCmvUW4AyNgJQJsgFqJvuRzT5HQcwLSbGpynjtHMZ/fQoy8lMEH3mN4nF1081b4P/FJhO9+ExKvHUDRp/+BeDl/DYSN48LU2lpR+J//pns8J3//D3TapdnWe/V1EZbRUFhvehzokU6NiOcTWFfHsX1X45/q3zodU+95PfEt1T4q3lcjuEC5GpKKqmOZ8xgBNkDzWPlzLT0Sj2IwMsxH8LOA5JgYR8E3vkZJQwumjt01k47/XC6Eb70d2v/6e0S2b9cN0KJ/+nu4RXLJNGqnWUSd+XI0Cs8Tv0LBV7+EGMV8+j/6h0iUp3fML47hm/wtM49v0NWjXU7UU+lNn5vplzKBNCrKclJHrb01k+7K9BEe0EsTGiWrKSMyC8oI5D0CbIDm/RaYGYCByEUk6B+X4ZwBH6JS8n3vO3BEIwi87wOA1zvDTcZecpSWIvT2++D/4z/VPa6CuqnoH/5ONyJF/GbKjWR3nWxC0Wf/GZ6nf0PG7W0IfOjhjEIHNlEi0jAVKzgf6kt5+nRunCRHb2uvk+M/0wFt2r2ikIBgVrD7MbzgAk0kHLg4zmkN07YAP2UEpEWA363SqsZawfpe5wCtZQ7Q6xThfulF/Qs98OD7Uz6yvm6QDC8kyJgI/s574LjjLniee2bqP+IcFQlQ0Q0NerJJvLYOIM/p5UY0PM7+frgoXtV9+BDFlV5ClEprhh54kHg+F1++Ld0/RE140QQf6GIvzWlwO9HtQCzuQONijv/MBlq9LOfxYzoHrYjztWNbSFygol0Y1VBXzmwJdtQxr8laBCYmJqgmiRvnz5/H0qVL9b+zleiqb6lsh+L+dkIgWQWpzsMxoFfrVZQ29D72c4R37ka0cePVL+X0b8EvGrrvXQi9+V64KQvfRQaG91e/hCMe1yvgJIookcjrAeioXZT+dJDnM0FGaXR9A4LvuE/3omYrsKiQVe1egBOUCf/GBbdlO9x1/Y92OlFdGkdtOZ+rXgdOGhd0PtCXXiB+2j7EFy1Ko6c6t1YWUwEILfF6HCi5zrkxAjZGYMTvwC+OGFP96w2bQlhYNn8Bh7/4i79Ac3MzDh8+jPe+97347Gc/mzXCbIBmDaE9BxAk9AWU5VzqKrHnAjNcle9H36eKRkUIveWtGY5gcDfBI7pnn/6fiAnVzvVM1ZsfJ6OTnic0FxJl5YgvXIjYsmWAx9hwgY1FFAdqEiH9ETJAd65i4zPbHSNYFRIUoyzKcoZtaoAKx67gA2Uu0Gx3C/dXAYFghEohnzXGfNtXTwmeZamtOkoOjYvEF50gh4YRzZgVGCEJjyEVApwBf706XEePwEUcnZN63Kcxvz6vnyWLKx6PfgSfS85HcQz/+fPfgEhaczuN+zg5P+zC8IQDm1ewAZrFjpjqKvbFipU6HyhuMd5TnbV8Bg0g4kDZADUITB5GagRqy+P4x/eYQ8s318JvuukmiuJx6P/NdV+qr3ESUqpI5dl9bIBOUzh5E0XiT3TtesQaqF47Nx0BkYgUTkTQGjhjKCKniHxe0C81Lp3/aMjQiW06WHTdemhdnYZSeMkGlfCA9jMXqGxqYXlshEBxChzR6SyXDdB00Mqje0USEldBuqJwkfAjqJeCshy9XxHN0r8aigTNj4OO4VsMlePkeS82LCG2Abehw+btYIIP1EHJaNoZY38oyARoLXlAJ8NOTATtmWglE9YsCyNgBAJsgBqBog3HEB7QOs6A1zUrDE9hgEb27KX67pyUdfV2L9QKsJqqIjX5jatbL+Kbzgx4sHUFez+vxjqbvwUzQryk1NZ0TAvLpsI12AuazU7hvoxA7hBIKWirpaUFZ8+exXYiwq6qqppVuvb2dvT09GDv3r1UUrpg1vv4BbkRGI9OYDIeYA/o62oSfJlEiYrwHXfKrTiLpNtEiUiHJ04YNntrH8UsEv3SlpXGBLobJpjiA8XWrtUNULvmiIsYUNFEHOiahRHFtcXiMwJyIfC5z33OcIHm9YB+5jOfwac//WkcOXIEH/rQh9Dd3T2jEH/8x3+ML3zhCxDG6vvf/34cOHBgxvv4ovwIiBrwojEFE5VHHxuF+5WXEb7xJqqRzowAM+1eURHpbPAcxA8XI9opOn4vK4xhWRUboEbgmRxD0DEJDljH4GDykq0eRbWssoIYJyLZSqu8GDsjMKcHtKurC88//zx+8IMfwOl04jvf+Q4eeeQR/Pmf//k1mDQ1Nemp+d/85jf16+vWrdPv3b179zX38RM1EEhygHIMKLEWPfs01TGkcpg33aKG8iyQUlAxidZEfKD7ynZmLcGpXi8aFgk/3ZwfT1nPk28DRNes1TliBR1TZMF+Wy5feEH5CN6WquVF2RCBOT2gHR0d2Lx5s258irWLI/hTp05dB0NDQwO++MUvXr4+OjqKYJCrl1wGRLE/RAKSSCxZ6Jk93EKxJWUkrkNUfjjwKsL76Mu6sDCjMfKh0+qC5fARZ6wgpM+2DYxpuETlFBsW2/WgOFuEsuhfVESVr5ZM0TFlMYzMXUUiElMxyawhlo0RuILAnC6GPqqcUVZ2haG0lOpRD85wfCO8o8mYz4GBAQhP6J/+6Z9emYX++upXv6of5Scvfvvb38aWLVuST7N+dFGVl8I8NBJqa2uzxm76AGNDE6jxVmHpoqXTX5LiudB1cr+ZKVD4h9+HiCSr+K13wnHV+8DMOeca2wxdzzVfOq9tq9iItkgnspXxSC+FPVDA7c1by6nUG/Ryb9mOmc46ZLnXrDWHd+xE5PHHUEax/I6ry7VKsvBs111PH1kvtAILqmupMpIki5pHjGzXPM/w0r5s53UHAgFpcZdJsDkNUI2qZ8SIuiPZBAv+XF/8nZ2d+NSnPoUPfOADeiJSsp943LNnD/7sz/7s8iVh2I5RiUAjmuCmErLlm9dVGNyTk5NGQHjNGF1j3XoCklH6uWbwLJ8IXYs9afobPBSC88lfI0GZ7+OizIpBezXT5Zul60zlmd6vsXAdftj/i6zf06+1FmJlDZmgET9iHvLYUWlR03U9fTEWPzdV1ytXQaPTqfFjR4H6tRav9Mr0ReSdFdVVsv08qyhwIZ4oQnvPOBZXys+iYKqur8Ar1V9izaJlq2upFjVNGOGU4zY/AnMaoNVUb/r48eOXRxkaGkJdXd3l51f/cfr0aT029OMf/zhuueX6eLnGxkaI/5JNlHMyagOKDS0MUKPGS8oo+6PX6zVlzecDfXT8Xm3K2Nlimitdu196Ed5gAJN79yNhgpGfLg5m6TpdOWa7f51nNYYjI2gbPoPF3pk/I2brm7weI3vh9LkS3NHo1/ee+LErfmzw+zqJkAGPNQtR7PMheuIYwnQcL0vzkUxGGKDlPvHFX4Su/igqfPKHgcn+vjZjf4g1i2bn93XSyDYDPzuNOacBumvXLvzrv/6rTq0kDM+f/exnSCYWCa+EOG5fvnw5Ll26hE9+8pP427/9W2zbts1O+OTlWnpDF7Cl+MqPhbwDgTwxnhefR3RDAxJV1Xm3/EwWLEpyinZiojljA7SDuD9DUSc26AlImUjBfeZFgDwzIhnJRWwl4TfeM+/tqt1QURiHxxXnRCTVFMfypoxAeXl5yvfKfuOcfmIR8/nwww/joYcewoMPPojx8XG8+93v1td08uRJfOxjH9P//t73voeRkRH80R/9EW6++Wb9v7e//e2yr53lmwEBUdP7UoQ83Z78JVzXWlt0uprI/htnQIgvzYSA8JhXuxfomfAzvZ7KtdO9Hqp8FMeKauZwTAWvTO+JEUuJs68XjnFjQqAylcOMfiJappYI6TkT3gx0eUxGwFgE5vSAiqnuvfde3H333QhRTNzVdUB37tyJRx99VJfmox/9KMR/3NRH4GLkEqWAJMgAXaj+YjJcgeflFxGjo8rYmvoMR8jPbo1F67IzQIn/c11dmGrA5yd+uVq14AP10WRaayuilJRktyaomDgT3m5a5fXYEYGUPurdlI56tfFpRyB4TVMIiON30WrztAyng+KctZZmRPbumwKE/58yApuKN6DZ345o4kriYqqd/SEHugfdfPyeKmBZ3JcoK0dsYS1VRcqeNisLMUzrKqiY+kc1iik1bQoemBFgBAxAICUD1IB5eAhFEEiS0C/KUw+o+8ArxH/uRmS7/TxDZm9BUZIzlAijbbIj7ala+rzkd3dgPcd/po1dJh1i5AV1tRFfEbEM2K3VlkcRplji4Un+erObbnk99kKA36H20mfWqxFlOAudBShxFWc9lnIDUMa1++BriGzdClBWLrf0EGgoWqsXMMiEkP40VT9aUBxFTWn63tP0pOS7BQLRdevhIHYH5/lztgNEeEBF6x+ZN8LMdmvnBTECKiHABqhK2sqBrKIKUp03P+M/Xc2n4ZwYR2T33hwgbb8pijTi8PQtQxNlwqfbRALShkXhdLvx/RkiEFuxEgm3h7Lh09dVhlPmrFtNaRROR4ITkXKGOE/ECGSGABugmeFm21594Qt5mwHvPngAMaosFV+6zLb6NXthgo5J1IRPp4nym0MTLj5+Twe0bO+lKkix1aspDrQl25Gk6y+S2KpKKBOePaDS6YYFYgSuRoAN0KvR4L8hYkDzMQPeQRRjevLRjl28C7JAYCPFgXYGuzER86c8SjMdv4vym+vqQin34RuzRyC6dj2cPd2CETz7wSQboY7iQJmKSTKlsDiMwDQE2ACdBki+PxUGaD5mwLuOHNJVH922Pd+3QFbrTxLSn/Sn7llrpuP3pQsiKPJy2nJW4KfZOUp8oA5KFdeTkdLsK/vteiY8e0BlVxPLl+cIsAGa5xvg6uUPUSnFYDyUl0fw7sOHEKPEjERxydWQ8N9pIrC6YCW8Do9eESmVrnGyOVv7vXT8zvGfqeBl5D2JBVWI0392pGMSmfATIQ0TQWKm58YIMAJSIsAGqJRqsUYoEf8pWr4dwTt7z0Pr72PqJQO2ncuhYQNlw59MMQ5UcH9Ohp1Yz8fvBqCf/hDCC6pRWU67kWbWlU9V0+obcacPCvdgBBiBnCDABmhOYFZjEpEBL9qiPMuCdx85jATRLona79yyR2AjVUQSNeFTaeL43a0lsLqGPaCp4GX0PYKOSTA/iNKcdmpTVEwJ9PExvJ3UymuxGQJsgNpModksR3hAhQeryl2ZzTBq9SUibtexI4hs2kwE9MwbaITyRBzoYHQY/a//oJlrTJGAJIxPN0M/F0ymvRZbtQYJ2vd2o2Py0H6qLOaa8KZtHB6YETAAATZADQDRLkP0URnOhZ5q4tDLn22hdXbAOTaG6FZOPjJqH4tMeNHmI6SPEF94x4CH6ZeMAj6TcajMcmzlKp0BIpPuMvepI0J69oDKrCGWLd8RyB9LI981ncL6pzhA84uE3nXsKOIlpfqXcAoQ8S0pILDIW4sKV/m8fKBnyPiMxh1Ev8TH7ynAatot0XUboHWfBYIB0+awYmBBxcQGqBXI85yMQGoIsAGaGk55cVevqIKUTzXgRenNpuOIbqbjdye/FYzc5Doh/TxxoM1U/73QE9cpmIycm8dKDwG9LKcIRWlrS6+j5HcLA3QsoGEyxJnwkquKxctTBPhbN08VP9Oye8P9eZWApLW36fWwI1u2zQQHX8sCAXEMf2qyDbHE7LXdWygBqb42TCEfWUzEXbNGIFFdjXhlpe2O4YUBKlrfKAcYZ71JeABGwAQE2AA1AVQVhxSVa8R/+ZQB7z5+DPHyci69acKGFQZoMB7EmQAd7c7QhFeqe8jN9EszYGPFJeEFtVsikuACFY1Lclqxo3hORmB+BNgAnR+jvLgjScGUN0fwdPzuOtWE6KYtgINdcEZvckHFJFqT//SMQ7f2e4h6UsR/cvnNGQHK8UWdjml8DM5e+9Ax+dwJVBTF0MtcoDneTTwdI5AaAmyApoaT7e9KktDniwdUP34PBBDZTAYoN8MRKHEVY7lvCZomZi7JKaoflRXEUFs++xG94ULxgLMicJmOqTU1/tZZB5LsBUFI3zfMR/CSqYXFYQR0BNgA5Y2gI9Ab6oeD/tW4q/MCERclH8XLyhBfsjQv1mvFIsUx/GxUTIKAft0i9n5aoZcZ5/R4bEnHxJnwM2qbLzICUiDABqgUarBeiL7wAKrdC+B25oG3QGT8nqTj942U/c7H76Ztvk1kgHZQDGggdi29z1jAif5RN9ZRAhI3eRDQ6ZjOdtmKjkkYoKOcCS/PJmNJGIGrEGAD9Cow8vlP4QEV/I350HTy+clJMkA35cNyLVtjIxmgcfp30t96jQwtfR79+Vrm/7wGF6ufXKFjulZfVsuVzfyLkpnwXJIzGxi5LyNgCgJsgJoCq3qDTpHQ16gneAYSC+9nvKgYseUrMujNXVJFYF3hKrgdbjJAr40D7aHs963LAlhApRK5yYPAFB3TAria7RMHOkXFJGrCu+UBmiVhBBgBHQE2QHkj6Aj0UhnOfPGAuk6eQLShkcnnTd77bicdsxeupjjQazPhj571odCbMHl2Hj4TBKLr10MTiUgJe+jHS5nwoiZ8L3tAM9kO3IcRMBUBNkBNhVeNwQOxIIajo3nBAeo8dw7O0VFEGzeqoRzFpRRxoCeuqog0NOHEpXEX0y9JqtcpOqZxomM6L6mE6YsljuF7ORM+feC4ByNgMgJsgJoMsArDJymY8oEDVHB/JjxexNbUq6Aa5WXcWLwBA5FLuBge1Nci6JdEW8sJSDoOsv3vMh1T87Vea9nkTEeeRRVkgLIHNB3I+F5GICcIsAGaE5jlnkQcv4uWDxygevb7OiJJd+VBtr8E2+4KIf1UXKFIQKoti6CsMC6BdCzCdQi43YitXmOrqkiLiAt0IqhhPMhfd9fpmy8wAhYiwO9IC8GXZere8JQBWuexdxKSY2gQ2oV+iv/k4/dc7b1lvsUo00qoItKUAdra52XvZ67Az3Ce6PoNcPZ0A35/hiPI1S1ZE56P4eXSC0vDCLABynsAgoJJcIB6nFP0OHaFxHX6FBJOJ0ScG7fcIbCxeCoO9OKYhuFJDUy/lDvsM5lJ8IE6KAnJ1XYte0EmY8nQR9SEdzgSHAcqgzJYBkbgKgTYAL0KjHz9cyoDfqHtl+86dXKKeqmw0PZrlWmBoiLSKeICbe4TVDgJ8oByBSSZ9DNdlkRlJWLVNUTHZI84ULcGVJfEmIppuqL5OSNgMQJsgFqsABmm7w33YZGnVgZRzJMhGIQgoNfpl8ybhUeeAQFhgPrjkzjaG4PISC722YPiZ4al2uZSjI7hXa3kAaWqYXZoiysiOM+Z8HZQJa/BRgiwAWojZWa6lHzgABVfpg76Mo2ub8gUJu6XIQLiCF60jv5CPn7PEMNcdxNxoA6qFqbHguZ6chPm0zPhyQC1Cb2pCQjxkIxA7hFgAzT3mEs1Y75wgLqaTyG+oAqi2gu33CJQ7irFisROhEJkgPLxe27Bz3C22IqVSHi9tjmGFx7QUNSJoQk6j+fGCDACUiDABqgUarBOiGQGvK2P4MnzqbU0I7qBvZ9W7bRV4TdS9GcC9cz/aZUK0ptX0xCtX2cbA1R4QEU7z3yg6e0DvpsRMBEBNkBNBFeFoUUGvGiLvfaNAXWe64GTKGXEsSI3axAo8u9AwNsKzR20RgCeNW0E9LKcfb1wUOUw1VsVJSF5XHGcH+Ka8KrrkuW3DwJsgNpHlxmtRBigDvpXa2MOUBd5P8VxYmzlqoww4k7ZIzA5vAyjRQdw2t+W/WA8Qk4QiBEdk0gXc7Wonw3vdACCD5S5QHOydXgSRiAlBNgATQkm+950ngzQGk8V3E77VgYS/J/hzVsBOlbklnsELoxqmAx6MVF8GCf86hszuUfQmhkTJSWIL14CzSZ0TIvpGJ4z4a3ZSzwrIzATAmyAzoRKHl07H+4nCib7coA6xsbg7D2PxLLleaRVuZbaptd/T2Bh1SCaJqYqIsklIUszGwIibtrVRl7r6FQM5Wz3qXBdJCINjLkQiakgLcvICNgfATZA7a/jOVcojuDtHP+ptTZTgAF9f4r679wsQaC13wPhfdpYtvRySU5LBOFJ00ZAp2OKhKF1nEm7r2wdxB6MJxzo50Qk2VTD8uQpAmyA5qnik8sWR/CLvXXJp7Z7dDU3I1a3CInSMtutTZUFtZEBKrLfNxEhfV94AIORYVVEz3s5xRF8vLiEsuFPKY/F4sqIvobzw5yIpLwyeQG2QIANUFuoMbNFTMT8GI9NYJHXpkfwsRhc7a1c+z2z7WFIrwGq/z4aoPrvxP+ZJKQ/McFxoIaAm4tBHA7E1q+H67T6OivyJlBWGMO5IfvGu+diS/AcjIBRCLABahSSCo4jvJ+i2ZUDVOvphoNKcMbW8vG7Vduztc9DUyewZmEYy31LUKqV8DG8VcrIcF5xDO8cHoJz4EKGI8jTbYlekpM9oPJohCXJZwTYAM1j7Z8P9emrt+sRvEb0MQmfD7HlK/JYy9Yuve2C95r67xuL1uEEJyJZq5Q0Z4/Wr0WCGCQ0YpNQvS2upEx49oCqrkaW3yYIsAFqE0VmsgzhAXU5NCwkGiY7NldLC6Kr65l+yULligSkq6sfbSregJP+FkoGiVsoFU+dFgJe+hFHHLouG9AxCQ/oREjDyCR/9aW1B/hmRsAEBPhdaAKoqgwpDNA6omByOuy3DRwT4zr9Uoyz3y3bjhdF/Oekdo0BupESkfzxSXQGeyyTiydOHwFBx6R1dQKTk+l3lqjHkmQiEldEkkgrMcA0RQAAQABJREFULEq+ImA/yyNfNZnBuqcy4O1ZglNrbZmiX1q7PgNkuIsRCLRdEPGfuNYALZ7SRxMnIhkBcc7GiK5vgCORgIveVyq3mtIY3FqCE5FUViLLbhsE2AC1jSrTX0gvxYAusmkNePFFGatZiER5efrAcA9DEBD0S7VlEZT4rhy3l7tKsdS7iCoiMSG9ISDnaJDEggX6+8l1+mSOZjRnGid94y0qj5AByolI5iDMozICqSPABmjqWNnqzgR5M4QHdIkdOUBpbRpVb+Hsd2u3bJL/c7oU4hieqZimoyL/c5ENr3tA41d+UMgv9fUSLlkQRQ8boNcDw1cYgRwjwAZojgGXZbpLkSGEEmFbVkFy9vbC6Z+AyN7lZg0CgxMahvyua47fk5KIRKT2QBcCsUDyEj8qgECM4kAdgcBULKgC8s4moogDFfHJYfWri862RL7OCCiBABugSqjJeCGF91M0O1IwudpakHC5EFu12njgeMSUEBDeT9Hqif9zettUtAFx+ndqkmqMc1MGAUFnligoIFJ6temYhAGaoAhxroikzNZjQW2KABugNlXsfMtKcoDa8QheJCDFVqwE3BznNd8+MOv1dkpAqi6JUuWZ649r1xWugtvh5mN4s8A3a1wKoNSP4RU3QEVNeFEcgeNAzdooPC4jkBoCbICmhpPt7jpHCUjFWhHKKCnEVi0cgna2C1GufmSpWmeL/xRCuZ1urC9cw4lIlmoos8lFNrzz0kU4Ll3KbAAJevncCYhs+J5BLskpgTpYhDxGgA3QPFW+8IDasQSn1nEGDqoBH+P4T8t2tiD5vjg+c/xnUigRB8qJSEk01HmMEq9ugjyhqmfDL6VjeE5EUmffsaT2RIANUHvqdd5VCQ/oEl/dvPepdoOrrRXx4hLE6xapJrpt5G2/HP8ZmnVNmygT/mJkEBfCF2e9h1+QEAFfwVRVJMWP4UUcaO+wG4on9Eu4QVgkRiB1BNgATR0rW92pG6A2pGDSWlvJ+0nlN7lZhoAgoK8sjtJ/18d/JoXaTB5Q0bgufBIRdR4vV0WijHhV29IFEURiDvSP8jG8qjpkudVHwLJ3n8/ng6ZphiAoxvF4PCgrKzNkPFUGcVOSTSZrDsVCuvepvnxVRv2txEfo2uFwzCh3YngIiYsDcL35Xnhtthcy1bUVuuq46EPDkviMOkrKU4YyLHBXoCVyBveV3Zu8fM2j0LWTjnsz2ePXDKTYE9l1ndi9F4mfP4rSnrNw7NpjCLouYq0Q3MS50nXj6/mJlwKl2LAiZsgaMhlEdl1nsqb5+og1i5YrXc8njxmvx9m1nhKslhmgoVAIMYrVM6IJ4zMSiWB8fNyI4ZQZQ3xBZ7LmzkC3vsaqRGVG/a0ESHx4RaPRGeV2HTkMLwnnX7YMCZvthUx1nWtdTQSJ3maoALdt8JOOgnNOLwjpDw8fn1GXoqMwSsRnRCZ7fM6JJX9Rel2T86CAqozFDx1CiJKSjGhC1+JLO1e6dpDQ5YVetJ6PYuuSCSOWkNEY0us6o1XN3UmsWbRc6Xpuacx5VTjYuM2PgGUGqPi1a9SvBDGWkePND5scd2S65u7AeX0Bizz0JaLgL7XZ1u0U9EsLaxErKobdgrtmW7McO/GKFK194ieAA2sWhubdW8IA/XLvIwjHInA5Zj8NUXGPXkEk/b9U0HWkoQGeV15GnH7401FW+ouc1kOsWbRc6locw3dfmjJ8p4mTs6cq6NpoMKzQtdFr4PGMQYBjQI3BUalRRAa8g/7VkQFqm0ZfYFp7O2e/W6zQtn4vSgtiOs3NfKKIOFBRjattsmO+W/l1yRCIbmiEIxiE1qmu7paRASq4QF+3fSVDmMVhBOyPABug9tfxdSvsIQO01lNNfIyWOcCvkynbC86+vtfLb3ICUrZYZtNfJCDNVP1opjEbi9bpP4SOT5ye6WW+JjEC8aXLEKeTBpXpmIQHNBgRlGHZe3AlVhWLxghIiwAboNKqxjzBzoV6scRrL5oirb0VCToKjK1cZR5wPPKcCATCIv7ThTW115ffnKljkVaI1QUriJCeDdCZ8JH6GiWHxdZvULosp/CAitZ96fWMJKkBZ+EYAfshwAao/XQ674rOBe1ngAr+z9iy5YBHxCByswKBMwMevcZ2qh5QIaOoC8+E9FZoK/s5ow2NcA4Nwdnfl/1gFoxQTmViS3wxdNMxPDdGgBHIPQJsgOYec0tnFAHgggN0qZ1I6CkrXsSicfUjS7cWBAF9kTeOunJRazu1JuJAu0PnMRIdS60D3yUNAlGqNpag7HXXqVPSyJSuIMILyh7QdFHj+xkBYxBgA9QYHJUZRVSfCScitjqCF7XfHWSEii9EbtYhIOI/V9eEiac1dRlESU7R2AuaOmbS3En0d7E19UrHgS6vIgN0kBORpNlTLEheIcAGaF6pG+ih+E/RltooBlSj4/cE8a7FFy/JM23Ks9wwOT3PUixdqvGfSclX+ZahWCtiAzQJiGKP+jF8TzccY2p6sJeRASoSkQbGOBFJsa3H4toAATZAbaDEdJYg4j9Fs1MdeFd7G6Kr14DK5qQDBd9rIAKdFz2IJxwpZ8AnpxZVrTZSNjwnIiURUetRlOUUzaVobfjlyUQk8oJyYwQYgdwiwN/YucXb8tmEB7TCVaZ7nSwXxggBJifhPH9OPwo0YjgeIzME2ij+0+uKY2nlVGZxOqOIRKQmfwsZsLPXjk9nPL43dwgkSkohKJlUpWMqo0SkMuKtFd57bowAI5BbBNgAzS3els8mDFA7Hb+7OtrhoMSq6BqO/7Ryc7VT/OeqmkhGTujNxQ2YiPnRGey2cgk8d4YIiGN4jU4hEA5lOIK13UQc6NlLHmuF4NkZgTxEgA3QPFN6j6Bg8tmHA1R88cXLypCors4zTcqz3Bg5LsURfH1tZgbIpuL1+mKYkF4enaYjiTBARRKgi0rhqtiEAdpD/LXxqWqgKi6BZWYElESADVAl1Za50LbzgJIBGmPvZ+YbwoCeXXR8GYmJ+u+pEdBPn7LMVYrlviU4PqEunc/0NeXT8/jCWsQXLCA6ppNKLnt5VRjhqBP9I/apDKekIljovEOADdA8UrngWhRHnXY5gneMjMB56RIdv9fnkRblW6rg/3RpCQhPUqZtM8WBsgc0U/Ss7xdt2DiViBRXL443uW/FDylujAAjkDsE2ADNHdaWz9QTPK/LsNQmR/Ci/KZosTWUAc/NMgRE/OdK8iK5s2CyEXGgHcGzGI/6LVsHT5w5AtHGjXAEAnpBiMxHsaZnkTeBqpIoui6yAWqNBnjWfEWADdA80vwVDtDFtli1oF+K0fGfyMTlZg0CIm5OlOBcneHxe1JqYYCK1sR14ZOQKPUoyuDGi4qUPYZfQd77Lk5EUmrPsbDqI8AGqPo6THkF3eQBFaTfFe6ylPvIfKPW3s7eT4sVdJ6SNwSRd31tZvGfSfHXFKxAobMAxzgONAmJWo/EwRsjTlDXqSa15H5d2hXVYfQOuygWVEnxWWhGQEkE2ABVUm2ZCW2nBCRnfx+cE+NMv5TZVjCslyi/6XQksKo68/hPIYzT4SRC+vUcB2qYZnI/UITiQJ3Dw3D2ThW7yL0Emc+4kjygopBCDxPSZw4i92QE0kSADdA0AVP5dkHBZJ/4z3YkhNdl1SqVVaK87CIBaSlVk/G6s+ew2Ux14UVFpATxunJTD4FY/Vok3G4lvaBLqICC+CHVycfw6m08llhZBNgAVVZ16QveHTyHZV67xH+2Ir5kKeD1pQ8E9zAMAZGAVJ9l/GdSmCQhfQcT0ichUeuRjM/o2nVwnVTvGN5NDEzCCOVEJLW2HEurNgJsgKqtv5SlH4uOYzQ2jmXEt6h6S8Ri0Do6mH7JYkX2j2iYCGlYk2X8Z3IZwgMqGvOBJhFR71Fkw2t9vXAMDSkn/EoKI2EDVDm1scAKI8AGqMLKS0d0kYAk2jKfDTygXZ1wUNm/GPN/prMFDL+3/YKXxkxgTU12CUhJwQQh/QrfUkpEUpPQPLmOfH6Mrm/QQ2NUTEZaQQbokN+F0Un+WsznPcxrzx0C/E7LHdaWztQdet0AtcMRfHOzHmsmqF+4WYeASEBaVB5FIfEoGtXEMTwT0huFpgXjFBYitnKVksfwKykTXrRO5gO1YOPwlPmIABugeaJ1O1EwJVpO619ycHHpPCu3r0hAMur4PbmOLWSAdlIMqAgZ4aYmAvoxvDil8KtVVKCmNIYib5wMUI+awLPUjIBiCLABqpjCMhVXGKDLbXD8ngiFgI4zHP+Z6UYwqN/guIbhSc2wBKSkWMIAFY35QJOIqPeoV0UiJgMVa8OvIi9oBxVW4MYIMALmI8AGqPkYSzFDd0hkwNsgAamNym9SEhLHf1q7rUT2u2hrDMqAT65mlW+5XiyBDdAkIuo9JsrKESOGCtfJE8oJv5LimbuJCzSmXkl75bBmgRkBNkDzZA+cJQ+oHRKQ4qcoQaWoGPG6RXmiOTmXKeI/q6l+dlmhsd/UDocDm4s2cCKSnGpPWSr9GJ5K5UKcWCjUVtVEEIkxIb1CKmNRFUaADVCFlZeq6EOREUzE/LagYIqfPgWsWw+QocLNOgR0/k+D6Jemr2JLSSPVhG9BLBGb/hI/VwSBaOMmOKJRuFqaFZF4SswVVWGdkL5jwK2U3CwsI6AiAmyAqqi1NGUWBPSiKR8DSkkNiZ5uONZP8UWmCQPfbhACgqZmYMxl+PF7UjwRBxqMB3FqjMItuCmJQLymBrHqaria1DqG97xOSN/BiUhK7jsWWi0E2ABVS18ZSXuFgkntGFDXmfap9bMBmtE+MKpTMv7TqApI0+XaREfwTvp3aOTY9Jf4uUIIRDduIg/oaYA8oSo1cQx/hhORVFIZy6ooAmyAKqq4dMQ+Sx7QClc5SlxF6XST7l5NxJQtqIKDPCvcrENAGKAVhTEsKDHniLxQK0B94Uq8NswGqHVazn5m/RieYkD19232w+VsBJFYN0oMD4LpgRsjwAiYhwAboOZhK83IXWSALrdBCU4XGaDOhimaHmnAzUNBhAFqNP/ndBi3Fm9kD+h0UBR7HqdM+Hh5uXLH8Kter+x1huNAFdtxLK5qCLABqprGMpBXeEBXKG6AitrSzqFBODewAZrBFjCsy2TIgfPDLsP5P6cLKOJAe4P96AtemP4SP1cIAeEF1ctyxo1lSzATgnJidlhQHOVjeDNB5rEZAUKADVCbb4N4Io4enYRe8fhP8n6Kgo9sgFq7YafiPx2UgGQuvY7wgIp2kONArVV4lrOLOFDn5CS0zo4sR8ptd3EMn4x1zu3MPBsjkD8IsAFqc133hwcQTkToCH6p0ivV2luJ+7MOjpJSpdehuvCC/7PYF0NtuTnxn0l86rw1qKX/OBEpiYiaj7HlKxAvLlbuGF4YoH0jLvjJ48+NEWAEzEGADVBzcJVm1K5gjy6L0hRMVNZPowz42Jq10uCar4KI+u9mZb9Px3RXxVb2gE4HRbXnTieiDRunqiLR+1iVtlqPA3XgDP3g4sYIMALmIMAGqDm4SjOqSEASlDZLvepWDnL29cFJHKDRNfXS4JqPggQjDnQPuU3j/5yO6c6KLTg93obJWGD6S/xcIQT0Y/ixMTiJw1eVJjz8wtPPx/CqaIzlVBEBNkBV1FoaMp8lD+gSbx3cTnUre4jj94SmIbZyZRor51uNRkBUh0kkHKg3qQLSdHl3VWxDnP4dnyAuSW7KIhBbvQaJggK4TxxXag1ryAsqQk64MQKMgDkIsAFqDq7SjNoZ6FGegsnV1orYsuWAxysNrvkoSFu/F4WeOBZV5IZYfENJPYq0QhydaMpHuO2zZvrxGN3QqF4cKP3Q6hl0Q3j+uTECjIDxCLABajymUo0oYkBXFiyTSqa0hKEqKlpXJ8V/8vF7WriZcLPwBonYOGeOvo81h4ZtZRvZADVBl7keMiKy4YeJSu38VFngXM+fyXwi1jlOHn+uC58JetyHEZgfATZA58dI2TtE7NzFyKDSHlDtbBcckQii9ZyAZOVGDJPT8+wld86O35Nr3Vm+VT+CjyXMzbpPzseP5iAQW7sOCTrBcDWpcwy/uDKqe/xbyfPPjRFgBIxHgA1Q4zGVZsTOYLcuy0qfuh5QUcYv4fNBVFXhZh0CnRc9iMVzF/+ZXKnIhA/Eg2iZPJO8xI8qIuByUTZ8g1JxoMLTL+iYWon5gRsjwAgYjwAboMZjKs2IXRT/KdoKhTlARfxndNVqYqDnrWrlxmqjL2GvK46llZGcirGtbBM0YnE4Ms5xoDkF3oTJohs3w3npEpz9fSaMbs6Qa+tC6CbPP8eBmoMvj5rfCPC3uo3130nxn2VaCSrcZWquMhDQY8aY/9N69enxn+QNyvXvgALNh/VFa3Bk4oT1ILAEWSEQXbceCbcHLoWy4ddSIpKIA2U+0KxUz50ZgRkRYAN0RljscbGLjuBXKJyA5DrTBgeRV3P8p7X7MULhl+IIPlcE9NNXu614E3tAp4Oi4nO3G9H165UyQBcT40ORN87H8CruN5ZZegTYAJVeRZkLKCiYVip8/K61tSFeXo5EdXXmIHDPrBEQyUfRWO7jP5OCby/ZhKHoCM5SUQVuaiMQ3bQF2sAFOC/0K7EQB8WB1teG0NLHcaBKKIyFVAoBNkCVUlfqwoqs4Z5Qr/rxn1x+M3Wlm3Sn4P/0UPzn8qrcxn8ml7OluFH/k+NAk4io+xhdv4GO4d1KeUHX1U3xgU5yXXh1Nx5LLiUCbIBKqZbshToX6kMkEcGqAiJwV7A5hgbhpP9i9cz/abX6RBbwquoINIs+LSrd5foPqcPjHAdq9V7Ien6PByIWVKU40HXkAU3AwcfwWSufB2AErkXAoq+Ua4XgZ8Yj0BHo1gddpWgMqIuO3xO0Ak5AMn5vpDNiLA4i4qb4zxyV35xNNnEMz4lIs6Gj1vXoZjqGpyN458CAEoKLuvBlhTE09zEfqBIKYyGVQYANUGVUlZ6gggPU6/CgzrMwvY6S3K0R/VJ80WIkiookkSg/xei66EaE4j/XkhfIyradEpGEV38gfMlKMXhuAxDQj+GJF9R1/KgBo+VmiPVEx9TcywZobtDmWfIFATZAbarpjsBZyoBfSmUTFVRxPA6RAc/Z79ZvTlEFxq0lLIv/TCKwvWSz/icfwycRUfiRKiIJI1SlY/j1i8IYGHNh2K/g56nCW4VFtzcC/G6yqX6FAbrKp2b8p6gX7SAO0BiX37R8dwoC+lVU/92lWStKnbeGvPk1YAPUWj0YNfuVY/gLRg1p6jjCAyraafaCmoozD55fCLABakN9J4g7U5DQq5qA5Gpt0TNlYytW2lA76ixJxH+eofhPQcYtQxNe0EPj6tQSlwEzWWW4nA1//JisIl4jV1lhHIvKI3wMfw0q/IQRyA4BNkCzw0/K3n3hCwhS/ezVimbAi/jP2Eoqv0lxYtysQ6CL+D9F/KfgQZShiUSkjuBZjETHZBCHZcgGgeQxvCIGqFjqhsUh3QNKv++5MQKMgAEIpGSAtrS04IknnsAlquM7X2tubkZXV9d8t/HrJiJwho7fRVPSAxoKQus+i+jatSYixEOngoA4fhfxnyss4v+cLuOOy3Gg7AWdjo2Kz/VjeEFKr0ht+AYyQP0hJ7oH3SrCzTIzAtIhMK8B+pnPfAaf/vSnceTIEXzoQx9Cd3f3rIvo7OzEJz7xCZw+fXrWe/gF8xEQ8Z9uhxtLvHXmT2bwDK72djgoCYnjPw0GNoPhWol2Rob4z6Toy31LUOWupGN45gNNYqLyY3R9AxLEC+pSxAu6hmKhxQ+yU+c5G17lfceyy4PAnAao8GQ+//zz+OIXv4hPfepTeOCBB/DII4/MKP1Pf/pTfPzjH0dZWdmMr/PF3CEgPKAr6Mtac1icOZLBknX6pdIyxBfWZtCbuxiFgGzxn8l1iWP4Q+NqxA0mZebHWRAQteE3NMB9TA06JjdFBAk6spNsgM6iUL7MCKSHwJwGaEdHBzZv3gync+q27du349SpUzPOUFBQgK985Suop8o1DlFAl5tlCHQEuyj+c4Vl82czsUhAivHxezYQGtK3UxL+z+mL2VGyBa2THRiPTkx/iZ8riEB081Y4By8hQWE3KjRxDC/eG1yWUwVtsYyyIzBnlkdfX981Hs3S0lIMDg7OuKa77rrr8nWRhT29feMb38BnP/vZy5e/9rWvYdOmTZefZ/OHMHhdlLAijOB8amLdCxdeSzQvsO843IN7l9x13WuyYxOneLAgld/03f8AyqatKyl7Utc+ny95KS8eZ9K1mQt/7gyo/nsCuxsrLaNgEmt2k5fs6j3+xsLb8fdnP4cOVw/uWnirmRBYNnaudW3ZQmniRGUlAj/4LhyHD8Gzpv4aXVsp12xz3+IBvn/AgV5/DW5YNttdqV/PJ10nURFrFu3q93XyNbs8BoNBuyzF1HXMaYBqmoZYLHZZgGg0mrGRt2XLFjz88MOXxyopKcHEhDFejCKqliPkzDelC4M7QHyZV7dzgT4EYgEscy02DN+rxzf174MHde95cPkKkPAzTsW6nhEWwy8e6yik7HcgGJg0fOxUBywsLIT4QXX1Hq9z1KDSXYFn+17C/qKdqQ6l1H0zva+VWkCawjo2bUH01Vfg/K13XqPrNIfJye0llH+0sKwIr7bEsGVp9kZGvulaKEmsWRihk5PWfbaYvVmSRrbZ86g+/pwGaHV1NY4fv5JxOjQ0hLq6zBJbhAEq/ku2ixcvwu/3J59m9Sg2dCQSMWy8rITJYWcPBfBPx/DEyFSIxGJn7XWv5VC0jKYqaDoOx5Kl0D+WZtkbQtfih9D0dWc0oUKdZtK1WeJH6DdnW38J3rxl3FKchZdb/LCcrusdVJbz5aGD1103C49cj5tLXed6bTPNpzVuROGBVxAl+jV/ReVMt0h1rWGRhoOdPvqN7CdDKjvR8k3XAi2xZtGmv6/1izb5n/jxzG1+BOaMAd21axeamprQ09Ojf+n/7Gc/w+7du/VRhVfi7Fk14nbmh8E+d7QHuvQa8Eu9i9RaFBka2pl2ol9ap5bcNpS286IHUeL/XCcJAf10iHeWbkXL5BmOA50OjKLPY3T0juJixF87oMQKNpLnczyo4Szx5HJjBBiBzBGY0wAVMZ/i2Pyhhx7Cgw8+iPHxcbz73e/WZzt58iQ+9rGPZT4z9zQFgfbJTp3/U7Ua8FpXJxzhMBugpuyK9AZt7fPA64pjmST8n9Ol30l8oAn6x1WRpiOj6HMK9XJu34nEodcAomCTvdUvDOvvjxPnmI5Jdl2xfHIjMOcRvBD93nvvxd13341QKEQ/Uosvr2bnzp149NFHLz9P/vE3f/M3yT/50QIE2gOdWF+4xoKZs5tSa2lGgo7X40sNiOzPTpS8791C/J9r6EtWm/PnqXUwiQILla5yHCQ6plsr9lsnCM9sGAKOXXSy9twz0DrOQPeIGjay8QO5iN1OVEU60ePDW7bNHKtu/Kw8IiNgPwRS+ooRmahXG5/2g8EeK4omYnoN+DWFK5VbkKBfitavBXF+KSe7nQQORwFRgnNdnRz132fDdmfpFrw2xnygs+Gj2nWHeO+Xl8N17IgSom9eGsK5ITeG/Px5pYTCWEgpEeB3j5RqyUyos0GK1U1EUV+glgHqGBuFRuX4omvXZ7Zw7mUYAu0XPIjFKf6zTo7677MtbHfJNrQGzmCU68LPBpFS1x30w1N4Qd1NVOWKkgxlb41LQnBQGIjwgnJjBBiBzBBgAzQz3KTs1Ubxn6KtUcwAdbW00Ec5EFvHCUi6Ai38nyi/WeiJY3Gl3EaA8ICKdpC9oBbuFmOndu7aAwclt7ooHEf2VuKLU5naCI53swEqu65YPnkRYANUXt2kLZmI/yx3laLasyDtvlZ2EPGf8bpFSJSUWikGz00ItFACkig36HTIDYeoC1/jrsKBcTXKOMqNphzSOYj/N15VDddRNY7htywL6u+XQFjyN4sc6mUpGIHrEGAD9DpI1L0gShSq5v0koke42lsRXcfH71bvPFFesJvi2mSP/0zitJvomF4bYwM0iYcdHiNbt8F1+iQQyp7k3Ww8hAEaTzjQxNnwZkPN49sUATZAbaRY4QFVLf5TO9sFB5Uti63fYCNNqLmU1n4PVR6SP/4zie6u0m2UdNeNi+GZywMn7+NHdRCIbN2OeHkFXMQ/LXurLo1hcUUER87yMbzsumL55ESADVA59ZK2VONRP/rCA6gvXJV2Xys76PRLouLNsuVWisFzEwKt/V6UFcRQW36l/K7MwOwhA1S01/gYXmY1pSVboqoKoM8D99HDafWz6mbhBT113gvBHsGNEWAE0kOADdD08JL27rZAhy7bWsUMUFfL6SnyeaZfsnxvNfd6sG6R3NnvV4O00FONZd7FeHVMjZjBq2Xnv2dHILJtO7T2NjjGx2a/SZJXtq0IkvHp1I1QSURiMRgBZRBgA1QZVc0taCuVJnTSP5ViQB0jI0S/1E/xn3z8Prd2zX91ZNKJ/lE31kvO/zkdiT2l23GADdDpsCj9PLplK0SRddcx+eN7F1dEUV0SpWP4AqUxZ+EZASsQYAPUCtRNmFMkIInMYK/TY8Lo5gwpvJ8J+qKJcQKSOQCnMWpL71RZwfWS839OX9JuOobvp9CTs8Fz01/i54oikCguoWpIa+E+fEiJFWwnL+jxbi8ifAyvhL5YSHkQYANUHl1kJUkLeUCVO34/fQrxJUuRuKrEa1YgcOeMEWgm+qWFZVGUF8lfi/vqRYpMeAf9e2VUjZjBq2Xnv2dHILJ9B7Te83AOXJj9Jkle2b4igBAdw5+kWFBujAAjkDoCbICmjpW0d8aoBKfIgF9XuFpaGa8TLBKBdqYdUc5+vw4aKy40EwG9at5PgVOpqwQNRfUUB8oGqBX7xqw5ow2NSHi8cCngBV26IIqa0igOd/ExvFn7gce1JwJsgNpAr11UgjOciGB94RplViOMTwcZodH1DcrIbFdB+0ZcGJ3UsF6hBKSrdbG3dIeeCS9+iHGzCQIeD6IbN01lwydEnTS5246VARzv4Wx4ubXE0smGABugsmkkA3nE8btoKnlAXc2nEafKR/HFizNYMXcxEgGR/e50JKgCUtjIYXM2ljBAJ2J+nPS35GxOnsh8BMQxvFMkKnZMfb6ZP2PmM+x4PRuea8NnjiH3zD8E2AC1gc6b/e2oclei0l2hzGpEtZPoBvZ+yqCw05SAtKIqggKP/J6mmfDaUtwAn9OHV/gYfiZ4lL0WW7Ua8bIySkY6KP0aFlE2vCClf62Dj+GlVxYLKA0CbIBKo4rMBWmebFfq+N3Z2wvn6CgboJmr3LCeMco5aqMKSKoevwsg3E43dpZsxsujamRNG6Y8uw9E3MCRbTvgOnEcCMvvnd+1KqAnIomSttwYAUZgfgTYAJ0fI+nvEAboOoXiP4X3M+FyEdVKvfTY2l3AjgGPnsG7QdH4z6R+xDH8iYlT+lF88ho/qo9AZMdOOMj4dDWRESp520kGqPhBx8lIkiuKxZMGATZApVFFZoL0hi5gPDahlAfURfRLsfq15LpyZ7Zo7mUYAqcp/tPnjmNFdcSwMa0YaF/ZDsQQx2tj8pOXW4GPqnMmqmsQW7oM7kPyH8NXEoVZ/cIwXj3Dx/Cq7jeWO7cIsAGaW7wNn615sk0fc0ORGhnwjrExOM/10PF7o+FY8IDpI3CauAvXUfUjTfFPglUFyyFKc740Kr+hkr6W8ruH8IKKRCTHyLD0QOxeHcCZATcujWvSy8oCMgJWI6D4147V8Fk//2l/G0q0Yiz21lkvTAoSCO+naNENG1K4m28xEwE/xap1D7qh+vF7EqP9pbvw4uhryaf8aBMEIlu2ARQPqkJlJFEVyU22J3tBbbL5eBmmIsAGqKnwmj/4KX8rNhSqE0vpOtWEOB2pJYiCiZu1CDRT9nuCqgg1LA5ZK4hBs+8v24m+8AV0BXoMGpGHkQKBggJEGzbSMbz8Py4Ek8SWZUG80l4ABehLpVAvC5G/CLABqrjuT9MRfEMRxVOq0EIhaO1tiDZuVEFa28t4io7fq0uiqCqxB4H7ntLt0OBkL6gNd25k1244BweV4ATdVz+JwQmXzi5hQ1XwkhgBwxBgA9QwKHM/0PlAP4ajo3opwtzPnv6MrtYWOGIx8mZw/Gf66BnfQxigG2zi/RTolLiKsJk4QfkY3vi9YvWIgjEjXkqcoAp4QUVMdUVRDC+RF5QbI8AIzI4AG6CzYyP9K8fHpuIpVfGAuk6eQLyqCvGahdJja3cBzw9T+c2AhkYbGaBCZzeU7cah8WMIxu0RVmD3fZjy+gQn6M5dcB0nOqZQMOVuVtzoJBrQfWsmcYRqwwfCzAlqhQ54TjUQYANUDT3NKOXx0VMo00rUSEAiz6covxmhWC5u1iNw6pyXMt/VLb85G4I3lu9GOEEVaZiOaTaIlL0e2bELiIThPiY/1da++gCiFNlygCsjKbvfWHDzEWAD1HyMTZtBeEAbitaZNr6RA+s0KsEgohs3GTksj5UhAifp+H0NcRZ63WqW35xt2esKV6PavQAvjL462y18XVEEEgsWQJTndL92QPoVLCiOUXWxMF5oKZReVhaQEbAKATZArUI+y3kTlGJ5ggzQRkUSkFxNdPxOme8iA56btQgEIw60X/DY7vg9ieqNdAz//AgboEk87PQY2b0HWk83nBf6pV/WTev8OD/sRudFLrghvbJYQEsQYAPUEtizn7Q7dB5j0QkyQBXwgMbjcJ1sIu8nHb87OCYqe+1nN0IzVT+KJxxoXGLPOMmbyvcSHdMA2ic7swOKe0uHQLRxExJEy+Q+IP8PjE1LQygriOF59oJKt49YIDkQYANUDj2kLUXTRLPeZ2Px+rT75rqD1n0Wzolxol/i4/dcYz/TfCfP+1BZFEVdeXSml5W/trd0G9wON57nY3jldXndAqh8b2TbdiKlp4pXUbn3r6gudsPaSRzqLMAkFX3gxggwAtciwAbotXgo86zJ34w670JUuSull9l14jgShYV6/Jb0wuaBgCcpAcmu3k+hvgKtADtLtuA5Poa35W6O7N4LRyAAVxNlxEvebiQDNBYHXmzjWFDJVcXiWYAAG6AWgG7ElE3+FmwpU4NPU9Av6dnvRKXCzVoEzg25MDKpYaNNj9+T6N5Cx/DHJ05hJDqWvMSPNkEgXluHGMWSu199RfoVlRfF9cpIzzUXUtiL9OKygIxAThFgiyCncBszWTgeRvNkO7aXy3+k7RQJAyMjiG6SX1ZjtCP3KE3k/XRpCayrs2f8ZxJ9EQcap38vsBc0CYmtHsN79sHV2QHnwID067qtwa9XRmrq8UovKwvICOQSATZAc4m2QXMJ4zOaiGJbmfxGnfv4MT1pILZGkXKhBulI1mGaenxYWxuCxyWrhMbItYjCU+oLVuLZkZeNGZBHkQqB6JatSPh85AWVX79rFkawpDKCp04VSYUhC8MIWI0AG6BWayCD+Y9PnIbLoWFTqfwJSCJOSy+9qWkZrJS7GInARNChU8JssvnxexKzW8v362U5xYkBN5shIJKRtu+cSkaKRKRf3O3kBW3t90KEwHBjBBiBKQTYAFVwJ4jYtrUFq+HTfFJLrx+/Dw8jsnmL1HLmi3Anz/mQgAMbiR4mH9qtFfsRiAfx6tiRfFhu3q0xsuf1ZKTj8ldG2rkyQLy7QTzNXtC826e84NkRYAN0dmykfeUYGaBbihuklS8pmCiZJzj7+Pg9iYi1jyco/nNxRQSiSks+tAYq0rDQU42nh1/Kh+Xm3RrjC2sRXbkKnpfl16+LDoBW1UT00pwjk/y1m3eblRc8IwL8TpgRFnkv9ocGMBC5hM2yG6BUqcl14hgigvuTj98t31CiLvUpKr+5aWnQcllyKYA4hn925CXKQCYuHG62QyCybz+0cz1wnjsn/dpuXu+H5kzgGfaCSq8rFjA3CLABmhucDZvluP+UPtaWYrkpmLSzXXCOjkIkC3CzHoE2Kr0ZjDixOU+O35OI315xA4aiIzolU/IaP9oHAVHcIl5SQl7QF6RfVJE3gf31ATxHlZECYSaml15hLKDpCLABajrExk5wdPwkatxVREJfY+zABo/mOnYE8aJixFavMXhkHi4TBI53+1BKZQGXV8mfsJHJ+mbrs71kM8q0EvxmWH4DZbY18PU5EKDTFUFM76JwH/j9c9wox0t3NPoRjjogeEG5MQL5jgAboIrtgCMTTdhaIrf3E6L2+3HKft+8GWDyeSl2mDBARW1qR545XgRbxM3l+9gAlWIXmiNEhDhBxWeO5+ABcyYwcFQRf71rVQC/oWP4sNyVRA1cNQ/FCMyMABugM+Mi5VV/bBKtkx3YVrxRSvmSQmntbXD6J+j4fVvyEj9aiED3oAvDVP1oy7L8iv9MQn5n5c3oC1/AKX9r8hI/2giBRGkpohs3wy2SkcgQlb3dvWkC/qATL7ayF1R2XbF85iLABqi5+Bo6uqBfEtVdtpXIbYC6jx5GvKICseUrDF0/D5YZAsfI++l1xW1f/Wg2dPaWbkexVoQnh56f7Ra+rjgC4RtupIprw3CdapJ+JbXlMWxbEcSvm4ohkgO5MQL5igAboApp/tD4Cf2LtL5glbxSh8NwNVHt963k/cy3815JtXL0rA+NRD7vztNaAG6nm47h9+LXw89KqiEWK1sE4vRjN7Z4CdwvqhHr+8bNExB0TE815embMluFc39bIMAGqEJqPDx+HFvp+N3pkFdtrlMn4SAjNLpth0LI2lfUgTENfSPuvD1+T2r2ropbcC7Uh9P+tuQlfrQZAuEbbpqqD3/+vPQrW1IZxdblQfz0gAsR9oJKry8W0BwE5LVkzFmvsqOGqJxgk78FO0rkrv/uPnwIsUWLEa9ZqCzWdhJceD8F9+DGPCm/OZvu9pXtQJGzEE8MsRd0NoxUvy4o33RKpheeU2Ip92ydwNAEOBZUCW2xkGYgwAaoGaiaMOYJqv8eSUTIAKXMckmbY3wcWluLXqNZUhHzTixhgK6rC6HAk8i7tV+9YI/TA8EJ+vjQM1df5r/thICgZNp3AzFwHIVjbEz6lS2uiGLv2jh+dbyYM+Kl1xYLaAYCbICagaoJYx4cP4YCpw8bqLygrM1FyUci7jO6lcnnZdDRkN+JrktubKOjPm7AXZW36tnwIpmPmz0RCAtKJqJ+cytATC808K59UYxTRjzXiLfnfuRVzY0AG6Bz4yPNq4dej/8UvIayNvehg4itXYdEcYmsIuaVXEe7fBQvjLyP/0wqfS8dw5e7SvGrwaeTl/jRbggUFSGyYyc8r7wMhEPSr25RZQL71gT0jPjJUJ6R9EqvHRbQbATYADUbYQPGF/Gfwmuzq3SLAaOZM4Tz/Dlo/X304b/LnAl41LQRONxVgLW1YRT78vv4PQmc+PF2JyUjiWP4WIIzP5K42O0xfOMtQDAI92vyE9ML7O/ZOo5wzIHHTxTbTRW8HkZgTgTYAJ0THjlePErVj8IU/7mrRF5id/fB15AoLER0Q4McoOW5FMN0/N5x0Y3tKwJ5jsS1y3/zgtv12vAHxo5c+wI/sw0CiaoqRBs3wvP8c0BM/h8aFUVx3LbBj6dPF1FSEn8l22Yj8kLmRYB3+7wQWX+D+LIURNoNRfXWCzOTBNEoBPl8ZNt2wOWa6Q6+lmMEjrx+/C6oXrhdQWBLcSPqPAvxi8HfXLnIf9kOgfAtt00R0x8/psTaRHUkryuBRw9z+JISCmMhDUGADVBDYDR3kFfHDpP3c6u0/J+ukyfgCAQQ2bXHXCB49JQROEjH7+vq+Ph9OmAOSpJ784I78NTwCwjE2Ds8HR+7PI8vXYboqtXwPKtGvG+hN4E3bxnHgY4CnKXEQW6MQD4gwAao5Foei45TDes27KFygrI294FXEVuyFPHaOllFzCu5Bsc1dF30YMdKNrBmUvxbqu5EIB7Ek2SEcrMvAuFbb9fj0rVmNVgPbl4/iZrSGH5woNS+SuGVMQJXIcAG6FVgyPjngbGjSNC/vWVyGqCOwUFoZ9oR2c3eT1n2z8FOH1xEPr91GR+/z6ST5b4l2FS0AY9eenyml/maTRAQjByiKIb3KTXCLTT6Nr5v1xjODHhwsMNnEy3wMhiB2RGwLGDP6/WikJJWjGgaERB7PB6Ultrvl+Oh88exyFeLTTXXJ/e4KN7S6jUnnnoSIF36brwZBT7zPzSdguPP7bZ83Ubs23TGSEfXh84WYMuKGGqr1Y4nE+9roW8z9vj9S9+Gv2z+B4y5J7CkYFE6qjD93nR0bbowOZpArDmRSBiu68Q9bwG+9HmU9PXCsW59jlaT+jTTdX1DI/BCWxQ/OVyGGxo98NrwNF6sWTQz3tepI2/unWIvc5sfAcsM0DDVC4/H4/NLmMIdwpiNRCLw+/0p3K3WLc9eehk3lO+acW3ijWzpmin5qODFFxDbup1oRCjbNAf4ix8aUZrX0nVbsIVS1fX5IQ3nBov0eDK/X34exLmgFD80xGeEGbq+rXg/vA4Pvn32x/jo0vfPJUbOX0tV1zkXzMQJha7Fl7bhuq5fC9/CWiR+9lOEKExItjaTrt+5K4i//VElfvAS8Pad9vtOE2sWzXBdS6RcYZNwmx8BywxQ8WETM4giQ4xl5Hjzw5abO7oCPXrllr0l22fEyuo16yXv/BMI7d6LuEG6TAVZq9edioxG35Pqml9pL6Rs2jgaFk2qwEAzL0yprnvegabdUOgowB2VN+EnF3+FD9e9R6oEP7PWPA0CqZ6KNZu17tDtd6Dg248A7W2IrVwl3bqnfw9Wl8RwW6MfT5wowu5Vfiwsox/3NmpCz6JNX7eNlshLSREBjgFNESgrbntx9ADoEBK7JU1Acr/8EmKUbRpfvNgKeHjOaQiIz/XXzhRg24ogPJb9tJwmlMRP31H1JvSHB/DK2CGJpWTRskUgumkLYtXV8Dz5RLZD5az/PVsmUOKL47uvlOVsTp6IEcg1AmyA5hrxNOZ7fvRVbC3ZiBJXURq9cnOrk6oeubo6Ed63PzcT8izzItDa78HwpIY9qzn7fV6w6IadVFlsmXcxfnjxl6nczveoigDFEYfvuBMuSpbUOjuUWIXXncC7do+huc+L1zghSQmdsZDpI8AGaPqY5aTHJHEUHho/gZvK5Mwud7/0IuJUdzm6eWtO8OBJ5kfglfYCVBTGUE/lN7mlhsB9Nffg2eGXcDE8mFoHvktJBMTnVKy6Bp4nfqWM/OIkY+OSoE7LxHXilVEbC5oGAmyApgFWLm99efQgookobiqX0AAl0nn3kUNT1EuvB5TnEhue63oEQhEHjp71YTd5P52O61/nKzMj8NaquwkvDT++9NjMN/BVeyAgvKB33g0XeUC1tlZl1nT/3jGEog786KD9GF6UUQILahoCbICaBm12Az878gqWeOuwqmB5dgOZ0Nt94BW9xnJkDx+/mwBvRkMeptKboagTe9dMZtQ/XzuVu0pxV+Ut+OHAL+gHn72SPfJVp7OtO7ppM2J1i+B9XJ0fGwuKY3jLtgm81FaA1j7PbEvj64yAkgiwASqh2uKJOF6gBKSby/fKJx1lu3tefhHRjZuQKC+XT748lehlOn5fVRO2XcZsLtR5f81bMRC5hGfoKJ6bjRGgMqyhu98E7VwPXE0nlFnobRv8WF4VwbdeKkM4qozYLCgjMC8CbIDOC1Hubzg2cQrD0RHcWi6fh9HVdBzOkRGEb7ol98DwjDMiMDCmof2CF/vr2fs5I0DzXNxUvAENhWvx7Qs/nudOfll1BGLrNyC6YiU8j1PimUE81GZjQtEDePCGUQz7Nfz0MB/Fm403j587BNgAzR3WKc/09PCLKNVKsL1kU8p9cnWj57ln6QN8BeJEv8RNDgRebJ3i/txBSQvcMkPg3QvfgcMTJ9Dsb89sAO6lDAKhN90D7eJFuA8eUEbmRRVRKi4xgWdOFdKPTRuWR1JGEyyokQiwAWokmgaN9ZvhF3ALHb9rlBwhUxM137Xz5xC56VaZxMprWWJUTEwcv+9aFaSyfUQEyi0jBO6qvBVV7kp868IPM+rPndRBIL58BSKNmygj/nEgrE61sLs2TWDpggi+8UI5RNIhN0ZAdQTYAJVMg6f9begN9+MNlTdLJhngefYZxKuqEd1wfV166YTNE4GOdfswEdRw41o+fs9G5W6nC/fXvA2PDz2NgfClbIbivgogEHrTm+GY9OufaQqIq4uo0bf17940ihHi+v3hayWqiM1yMgKzIsAG6KzQWPPCk8PPochZiL2SVT9y9vbC1dqM8M23AiIoiZsUCDzXXIhlC8JYRkkK3LJD4F0198LlcOORCz/KbiDuLT0CCfohHaEiGp7nnoFjdER6eZMC1pVH8bbt43ihtQhN57jeeBIXflQTAbYkJNPbr4ee07PfPU65KDc8T/8G8dJSRLbvkAyx/BWnf0RDa78XN69n76cRu6CMKJl+q/pN+MHAzzEenTBiSB5DYgRCd9wFEI+x97FfSCzl9aLd3uDH2toQvvlCGcYD/BV+PUJ8RRUEePdKpCmRANET6tV5CSUSC86BAaItOU7ez9v0D2yZZMtnWZ5tLkKhJ46dKwP5DIOha39w4TsRToTxnYGfGjouDyYhAoWFCAly+qNHoFFZYVUasUnRUfwIYnEHvvki14pXRW8s5/UIsAF6PSaWXXls6CkUa0XYX7bTMhlmmtjz9JNIUNnNyB4JeUlnEjgPrgUpCUGU3txH1EseVx4sOEdLrPXW4N4Fd+KR/h9ClMPlZm8EInv3I15bC++jRMGlCC2T0EhFURzv2T9Kx/A+PEWZ8dwYARURYANUEq0J8vnHBp/CGypugkzH7w6iKxEeAj320830H5JsF7xMlVHCVKLvFj5+N1wlH6x7AOMxP7438KjhY/OAkiFA8eyht74DGsW4u195WTLh5hZH1IoXyYc/oTKdPYP8K3RutPhVGRFgA1QSrRwcP4aLkUHcs+ANkkg0JYb3N08gUUjeT/IUcJMDgTixLT19ugibl4VQVcLlI43WylLfInof3oH/6v8ee0GNBlfC8WKrViOybTu8TzwGx/i4hBLOLtI7d4+iujSKLz9TAXEqwo0RUAkBNkAl0dbPL/0atZ4a7CjZLIlElOx+oR+uY0cRvpViPz1yJUVJA5IFghzv9uLSuAt3NHKijFnwP7zoQUyQF5Qz4s1CWK5xQ29+iy6Q9+dqxf6K8JuHbh3BKCUjfYvjQeXaVCzNvAiwATovRObfIGLNnhx+Xve6OESEuSTN8/hjSJRQ5jt7PyXRyJQYTzYVYzlRL61ZyNRLZilmia8Ob6t6I77R/32MRsfMmobHlQSBREkJQm+6F276wa21nJZEqtTEENRMD+wbw+GuAjzN8aCpgcZ3SYEAG6ASqOHXQ88iEA/iLVVECyJJc57tgvvUSYTvJJk49lMSrQBnqAxfx0UP3rDRL41MdhXk4UXvRSQewZd6H7HrEnldVyEQ2b1HrxPv+zHxwIbUqZAklrBndYDiQf1EUF+KMwMcq3+VWvlPiRFgA1QC5fzk0uPYWrwRy31LJJBmSgTvL3+OWHUNIjt2SSMTCwI8fqIY1SVRbFvOdd/N3g81niq8t/ad+C4lI50L9pk9HY9vNQJ0+hS877fhmBiH91dqcYMK6N61ZwxLKyP48tMVGJ3kr3artxPPPz8CvEvnx8jUO84EunB0ogn3Vb/Z1HnSGVxwfrrIAxp60z1c9Sgd4Ey+99yQS6dduXPjBBejMhnr5PAfqLsfpVox/qXnC8lL/GhjBBLV1XTqczfcL78E7Uy7Uit1a8CHbx8mflDoSUnikRsjIDMCbIBarJ3vU9WVUq0Ed1beYrEkr08fjcL7y18gSpmhsYZGOWRiKXQEHjtWjPLCGPauYX7KXG2JIq0QH1vyITw98iJeHTucq2l5HgsRCN90C+JLl8H3/e8CQbVOGiqJH1QkJXVedOO7r5RaiCJPzQjMjwAboPNjZNodAUo+Etnvb6u6G15JSm96XngOjuEhhO59m2nr5oHTR6DnkgNHzvpw16YJuMjTwS13CIj3Z2PRWvzj2X/XY0JzNzPPZAkCxA0auP8BOPwT8D36E0tEyGbStXVhvHP3mF4v/tlmJqnPBkvuay4CbICai++co/9s8En445N4Z829c96Xqxcdo6PwPPUkIrv3Ir5oUa6m5XlSQOD7L7tQVhjHDVT5iFtuERDMFH++/A/RFezRuUFzOzvPZgUCiapqhO55C9yHD8J1/JgVImQ1560bJnWS+u+/WormXk9WY3FnRsAsBNgANQvZecZNJBL49oUf48ayPVjmWzzP3bl52ftzqvyiaQjd9cbcTMizpIRA9yU3Xmt34k2bJ+DmgicpYWb0TY1F6/A7NW/DFykjvivQY/TwPJ6ECAj6ueiGBvh+9H04hoYklHBuke7fO0pUbWF8iUjq+0b4g2NutPhVKxBgA9QK1GnOF0YP6B6V9yz8LYskuHZarbUF7hPHdC48UN13bvIg8NPDJagpS+AGKrvHzToE/seSD6LKXYG/7vq/EKVzudkfgcA770eCinAU/Pc3gZhaVcc0+nZ/+LZhlPji+I8nKzBGZPXcGAGZEOAdaZE2RJm/tQWrsbdsu0USXDVtOAzfj3+I6PIViOzafdUL/KfVCIjjs9O9Xvz2/ijEFwo36xAo1Arw/634BI5NnNQJ6q2ThGfOGQL0Yzz47gfh7D1PyZk/y9m0Rk1U6E3gD95AMf1UpvM/yQgVj9wYAVkQ4K80CzRxfOIUDo0fx/vrftuC2a+f0ksVjxxjowjd9y5AokpM10uaX1dEzXdBLL1sQQT717HHTQbtix+M99NR/L+f/zqa/WrR9MiAn4oyxFasROjuN8Hz4gtUmviIckuoLo3hI28YRu+Im+iZynWaJuUWwQLbEgE2QC1Q61f6vo3F3lrcJQH1kl7x6KUXEL79DYjXLLQADZ5yNgRebivA+WE37ts1xr8LZgPJgusfX/owlnkX41Nn/g7+GIdFWKCCnE8ZuflWRBo3wfeD75E3tDfn82c74crqCD506zBO0WmKqBlPKQjcGAHLEWADNMcqOOVvxXMjr+CDdQ9Ac1jMpxMOoeB730a8bhHCt96eYyR4urkQCIQdELGfW5cHUF8bnutWfi3HCAjKtH9a85cYiFzC33T+S45n5+ksQUBUSfrt30G8cgEKvvE1vVqSJXJkMenmpSG8Z/8oXj1TSCcrJVmMxF0ZAWMQYAPUGBxTHuU/zn8dizy1eMsCqrFucfP+7FEI6qUgcd6J7Hdu8iDwKBmfoYgT9+0cl0coluQyAqsLVuCvVnwcvx5+Fl/vI8JybvZHwOtF4H0fgEP8cP/G1wEq2qFa218fwDt2juGpU8X4+ZFi1cRneW2GABugOVTo4fETeHH0Nfz+4vfB7bSWFsN14jg8r72ql9uML6zNIQo81XwInCXapeeIQPpNW8axoEStzNv51man19+84A4IFovPnfsKnhl+yU5L47XMgkBiwQIE3vu7cJ4/B993/xsqnmXfudGPN24exy+PleCJE8x4Mouq+XIOEGADNAcgJ6f4bM+XIDwn99AXl5VNcNr5fvg9RNdvQOSGm6wUheeehoCo3/zIS2VYWBaF+KLgJjcCIh70hrJd+POO/wORXMjN/gjEqExx8F2/A/Ej3vvznyq54Ldun8AdjRP4yaFSPHmSjVAllWgDodkAzZESfzX4NE74T+OPljwEp8NC2OnYqOCRbxC3nVf/EM3R8nmaFBF44kQxzg+58J4bRpl2KUXMrLxNxHH/0+q/pB+Wy/Gx1r9E+2SnleLw3DlCILp1m14pSWTGi+pxKrb7do3jtg1+/IiYNp5sYiNURR2qLrOFlpDq0KUuv6j5/pmeL2Jf6U7cVL4n9Y4m3Cn4Pp39fQi850EkmHDeBIQzH/IcGZ6/PFaM29PvmYIAACMMSURBVBr8WF0TyXwg7plTBAqIH/T/1f8fnaT+4ZZP4kygK6fz82TWIBC56RaEbr0N3id+BfcLz1kjRJazvmvPmP5586ODpfjVcTZCs4STu6eJABugaQKWye2ifN9QdASfXPbRTLob1sf94vNwH3oNobe+HXEinecmDwIRymf4+nPlWFAcw1u3c+KRPJpJTZIKdxm+sP7TqHCV4qHmT+CkvyW1jnyX0giE33gPwvtvgI/KGLuJzk7F9q7dY7hr4wQePVyKnxzk7HgVdaiqzGyAmqy51skOfOvCD/C7te/CioKlJs82+/Ba82mKV3oU4b37ENmzb/Yb+RVLEBCE8xfGXPjgzSPwWJufZsn67TBplbsSX1r/f1HrqcGHm/8Ez4+8aodl8RrmQSD01nfQ5+p++B79ibKe0LcT28Zbt4/hiaZinSc0znUv5tE6v2wEAmyAGoHiLGNEEzH8dec/67RLH1703lnuMv+y81wPxX1+E7E19Qi95e3mT8gzpIXAoU4fnmspwtt3jGNZFR+9pwWeZDdXusvxZTJCtxZvxB+1/RX+q+97kknI4piBQOhtZIS+7gn1/PpxM6Ywfcw3bvbjd/aOQhTA+MJTFQirxzJlOkY8gbEIsAFqLJ7XjPZlOnpvnmzH36z8Ewjyaiua4+IACr72ZcSrq4k+5H3M92mFEuaYs3fYpXsctiwLUlYqZ73PAZUyLxVphfh/a/8ODyx8Bz577ku6ITocGVVGfhY0AwSIqF54QkNUUc77m1/DS7H2UNCNePP6SXz4tmE093nxmccWYHSSTYQMdgN3SREB3l0pApXubceIkkUYoO+jo/etJRvT7W7I/Y7BQRR+6QuArwCBDz4EeH2GjMuDGIOAP+TA58nTUFYYx/tuHDFmUB5FCgREdvyfLvsIZcj/FQT/77uaPozfDD0vhWwshHkIhO96I4IUY+8+8IpeMQmhoHmTmTTy1uUh/M+7BzHoJ4aHn1ehZ5BjgkyCOu+HZQPUhC0gvB2iTvS6wjX4g8XvN2GG+Yd0DF5C4Rf/gzyeTkx++PeRKObg8vlRy90dEeKXF8dc/pATH7ljCAUeLs6cO/RzN9OdlTfje41fRH3hSvzJmb/FHxJV09ngudwJwDPlHIHI/hsRJLJ67cwZFP7Hv0E4AlRrK4mF41P3DNLnUhz//MsqHOxg54VqOlRBXjZADdZSjOI+/+zM/8YkUS+JetFup9vgGeYfznmhH4WfJ+PTqWHy4Y8gUV4+fye+I2cIxMnWFBnvnRc9eJiOuxaWcbWjnIFvwUR13hr857p/xP9e9Wc4PdmG+058CH/X9Vn0hvotkIanzAUC0caNmPzIH8BBHtCif/ssRBKoak1UYfsTMkIblwTx1ecq8P1XSyEKZXBjBIxCgA1Qo5B8fZxPd/8nXhs/ir9f/RdY7K0zePT5h9O6Osn4/HckfF5M/v5HkaionL8T35EzBBJkfD7yYhmOnvXhd28awbq6cM7m5omsRUCU7nx009fxe1SK9/GhZ/DW47+r/1g9Mt5krWA8uykIxBctxuTHPo7Y4iUo+PpX4HnsF0BMrR+bPneCfiSPUILkGJ6h8sD//MsFuDSumYIXD5p/CGh/Tc2KZU9OTlKMtjE/pwoLC+l9HUMoFLJiKZfn/Frfd/DVvm/jT5b+Pu6pesPl62b9UVBQgGDwSoyR6+hhFHzzvxCvrcPkQ78HlJSaNbVl4wpdi31jta4zAUB4Pv+bymy+3F6Ad+8bxd41V3Q333jTdT3f/XZ4Xeg6QRb71Xtc9XWJE5EdJZvx2zVvQYlWjN8Mv4BHLvwIjw0+hdHoGMqJR3RxaZ2t1pyKzsT+Fs1OutYX5PEgunU7QElKnmeegqulGbEVqy4XAVHlfb16YYR+LIfwSnshnj5dhHKKW19SmVmavG11rSt86n9utxs+H4ctXAXJjH866APekuCzixcvIhrNbANPX0lVVRXC4TDGxsamv5Sz5z8Y+Pn/396ZAEdVpXv8351OZyULIUEgEJBNAqJsoiIMPsXBUdRxXHGfYZznuI06M2q9Ukee1qxVauk49Xxj+dBxRMvCh4hvdNzYBJFFBXSQfQmBJGQhe3p733dCtwGydEIvuX3/hzrcm9vnnuV3+p7+7ne+8x08uecZ3NT/Ktw/RIS/GITc3FxUVVWZ1ZYp/3gX7uWfwHP6GWi65jpAHoBEDNrXHo8HNTXWWlWsU1cLVuRgnbhcmnvOEZw3uqFb3RPq627dZe3EeXl55sWyujpxF2ipyc6nNevwzuF/Ynn1GjT5mzEo9RSclTkRk7POEHdOYzEwpb+1OzKM2vft29e8bJjxLIz0Vkyis1Opr78GR+0RNMtiJc95M5Ar33ErtVkXTupL9MY9aVDPHdfLi3RWWvcUSTqWabBSu7v7fdOX5+zs7O7eZrv0FEAj0OWvH3obv9v7LH7Y72I8MvQ+edl1RCDXrrPQB7l6926kLnwVOri1zPo+Ws6/wLxtd323NVNYUQBtbHHghY9zse2gGzedV4Opwxu7DZ8CaLeRWe6GRl8T1hxZj8+bvsTy8tUoOWojmuvKwRhZ0Dipzxno5+6LoamFGCJRtaWJEuwggJq+klm6lP97B8lrVkOn6N0334rqnFaBzEp9+dmONGMTqnW+csoRnDOiUZW8YQUKoGFhskUiCqAn2c3/La6Wni/5H/wo/xL8R9G9MRM+tdrZ27fB9+rLCCQloenaufCNHHWSren9t1tNAC2tdpnV7kcanZg3swrFg3pm80kBtPd/NyNVw2BfH2opx1fizm2zbOv5bcMO6MYW62q/DBWT4UwXO/NTcIoscjrFnY/+sgNTQXIeCtz9kH/0qD5JrRBsI4Ae7YykXTuNr9CkskPwTJqM5u9fjECWtTRm6iP0DVmYpNrQ4QUtuGZqDQbndT2rSQHUCk9kbOpIAbSHnJv9LfjP3U9h6eEP8OMB1+Huwp/0MKfu3+aQ6eeUxYuQ/PUWeMcUo+lHV9vGzZKVBFDVEixcnWWmqP79gioMyOl6cO7o2xAUSjr6PBGv22EKvr1+66yvj3hrsbtpH/Y1HcD+5lKUthxCaXMZDraUocxTYabw2+aZ5kw1AmlBcj8RUDWqoJpvtgsdIALrQBFg05Na7S/b3hfrc7sJoIavrFvIFrt935LFZnFSy7TpaJkxE5DpWyuFzftTjCB6WBYnnTOyEZdOqDU2oh21gQJoR2Tsd91lvyaffIvVj5+6WtreuBuPDX0AV+TPPvlMw8lBbGbdK5fD/dEHgMsF523z0Dj6tHDuZJoYEqhrcuD1NdlYvzsNE4oaceO0Gvr5jCH/RC4qy9UH4zOLTWyvnbXeOiOIlrVUoNxzGGUth+VYIccK7GjcY+xNK73H2tSahU8iiBamDMRgiTq9X5Q6SGIhshNomr89XnG9JjNXzgsvQs1pxUj5+EO4VyyDe/Uqs6WnZ9oMUSpkxrV64RY+rrAZpw0ox0dfZ+AfX2Xi851p+N6YeswaV48+qd2zDw23TKZLDAIUQLvRj7pe642yJWZ7vVxXNl467SmMy4yBACirvl0b1iPlg/fhqKmGZ8pUM2WTW1ioltzdaAGTRpOALufTFe5vrWv1l3fjtGqcKxoBBhKIFYE+rkxoHJ42tMMiW2T25pAIpKo9PdB8SGxNS4296b7mA1hTsx41vtrQvTrODUsdglPTikwcIflq3rrnPUOECGRkoPnSy9Ay/XvQlfLuFaJkkOiZMAmeaecZryYRKilq2bjEM9NFp9fLeNeA9zdlYpmslNeoiy0vKK5D30wKolGDb+GMKYCG2Xlf13+L3+15Dpvqv8GcvFmyzd6dMtBnhHl3D5PJau/kDevgXvYxnJWV8Iq2s/nWH1tiQOphiy17278OuPG/67Ow93AyzhzSKPZQ4lIng4OuZTs0gSvudroxOFW0nRLbCzrNr7M8u03ci52Ne7H2yEYsKn8XfvmnQRdGjUwbZnZ4GpV+qpyfKoJpETRvhp4RCMiq6ebLf4iWCy5E8qerkPzZarg//wzeoUPhmTwV3tPHy3bKKT3LPEZ3ZaYGZFFSLS4U7ecHWzKwQnyHLvsmHWcWNWGGCKOj6Pc4Rj1hjWJoA9pFP+2Uaav/OvAK3q9chiEpg/BQ0V04J3tyF3ed3MeOinK4136G5HVrAfGX6jttDJr/7UL4hxQdk3FntmLHJEygP3qTDahqPNX+Sd/4d5S5xS+eB1dOPoLTBvZsoVFn3WTHvqYNaGffiNh/pprTXWJ/ukNMj7Y17BITpF2yOGqnmfLX2siEskzbD4YKpK1xuBFSdVFUV8GWNqACpdPnWkyuXF99YfaVd4m3k4C41vMWj4V3/JnwjhptCVd76gFk1bcihIogerjOhYIsL84fF8C0MT64fIk7e0c3TF098a2fUwBth5NOta85sgGvly3GsurVyHPl4icD5+Kq/Etla83oKI0dR2rg2rQJyWKUnrRvLwLuFHgmyhTMudPgL2jfD2Cng1c77UqES71BANUV7brAaOXWdJTXuozgOXt8ndh7NoXtiqS7fWHHvqYA2t1vSXzSqwN9FUi/bdxpVuurUKpCakvAYyqkNqYjRFuqQqkeg9P4bRc/UQDtvO9UKZG8cQOSv9wIZ0VFqzAqXk98o8fAK8eA+FHtzUE34fimJAWfbkvDpv2p8MqGUEPzPWbMHD+4KeG2I6YAGt63kQJoG07/qt+Of1Ytk11JPjb2UarxnNv/SrPIKCXSU0vydquCZpK4UnLJPsHOkv3Gf6dv+Aix/ZnYOt0iQmhnwY5CSbwE0Kp6JzbtSzVbaG4Vf57q8u70wc2YKcb2sdhO0459TQG0s6e/d3+mDvZ1Gr9VMN1hjttEY6qr9YNBV+Eb29LUIoztdxqGp4ttqSfbVvalPXmunaUH4NqyufV3Y/8+Mxb5RQD1DRsuuywNg2/IEPjzCwBn79xp252Wi7Xbk7Biix9bS93wBxzo18eLMQObzVg6sn8L+nTTuX3wO9VbjhRAw+uJsATQrVu3Ys+ePZg4cSJUAOgohJtO7+8NOyGp8f0XtVuMbz3djUTdmKQ703B+7jRc1u8iTOlzZmT8eopG1VF5GEkHSuDcvx9Je/cY4dMhQqhqOr0jRsAn7pS8Y8Z2a+VjTwavjvrOKtdjJYCqS5FdFcnYcchtBsmDNcky0AcwrMCDSUMbMXlYU0wHSTv2NQVQqzyV4dezzleP7Q27sbNpt1mVryZOujpfV+wHQ2ZShlmFP1gUAIUpA0xUd1G6I1RBcn7UZqGC5cfyeLLPtaOuDkk7tkncgaRdEmWHQQ36u+IbNAj+AQPNmgFf//6tQmkvcPGkbdagOyHpFP03B1KwRUyZ/iXHqobWfeZVIB0mGtIheR4MFtOmgbkeqH2pVQIF0PB6qksB9KmnnsKWLVswcuRIfPrpp3j22WcxRN6wjg/hpgveFysB1B/wo8JTaXzm6Rv5LjGo1zfxrQ3bUeWtMdVR1yNnZ03C9JypOCtrAnqk7RRhUqfRnbJtoEMeLKcInM7DFXDKgOAsK4PD02oX6JcBQG05fUVD4T11OPyFg8V4qvWhC7IJ93iyg1e45fSmdJEUQD3illMHvAoRNsuPuHBI4oEqF0qqklHf3Ko9yE33YeQp4mZE7DrHDmqOqdDZlrsd+5oCaNtvQGKfu7NSsKNuNzaVf429TSWtsbnErNCvlin+YHDIa2C/5L7Gt6n6M1WH+/q3xrzkXLM4qm9ytuwSld0r/JsG693RMeLPdX1968yaaEaTZFbNWVoqv0nf2Vrq708grx9UY+rPle1Pc3LgFwf46gQ/kNVH9qgX1089/D3qqI3HX28rgB7/mY7F2+Wlf2dZMnZXuM14rBpSDX1SfTJV7xU7Up/RmOZl+tA3w2cWe2aniU1pz35Gj69CRP6mABoexk4NGneL4fOKFSvw5ptvijbfiYULF+LVV1/Fww8/fEzu4aY75qYY/KHTQOeunxOyRdIidcBSNyKX95uNsRmjxZ/eGDOYBavjEKFR3yodsgJdNpg3R0dLM9As581i49cksVH28ZbFQQ6N9XVwavrGY93tBFJT4dcHPT8f3rHj4DtlgLyNDkBAHnqG3kFgwcocbBBfnRpUu9lXBjR1Fn/eqAbz5l2U3yIDHFey947eYi0SmUCmeBQZn12Mwf4BJzSz3tdg3ESVissoncIvVaf74kZKZ6y2i+2pak8b/U0n3OdyuJCVlGl8mfYRrapqVjPMMd0IpzrblZaUCnXWn2piilE+qALC7XCLpjVZjslIlnz03OVIkugyMUnO9Z/L4TRHhx4lOiXGNYhLJ120qjEU5DfLKTsuOcvLjP2o87AoR8SrStKO7a2/daGEojnV87Q0BNIzJIqwmqYxFYFUuaYr8CUGUlIBt1u0rMmyEEqOsjhK/VIHJOpRBdhAkp6LROjU6DS79RmTAD1XZY2mayf066PCZSPOlq09NXjEVvSg7CanSoGDNaIkkLirPNn4GvX42u79GUC6O2AUBJkpftGW+uXv1pgq17NFkaCpc0Vg7eludKZC/C+iBNr/FhwtYufOnRg/frwRPvWSTsEvXbr0hAqEk+7vf/87nn/++dC9f/nLX1BcXBz6+2ROVDhOki99qgh9x4f5Yx9EX3cOhqQXYljGEOhA11lofvN1+Nd9fmIS3ehWHkyHPJC6U4VDHnRHv3xg2DA45O3RkZ0Dh7xNOvrmyXWJ8gBHO2i7CwrE1sdGIdjXKToYnmS46jxg9mR9qwYKJCa7dIiSwdTE+O8O07Z5du1rl/xQ2fE7bsc26/e9o3YPw9C2j8MJ5w3eBpS3VOJws8SWKlS2VKPKU43qlhrUeGqhC6VqPXVQbep+8XdaJ+lVsG3wNsruUScKrycU0MmF0X1GYGvtdpPi/elvYGzW6E5SH/tRzJ7rdmYttSYqDAZkxi4g/qUhMVBzBIFaiaJUgcRAQ33rUYTXgCpZRJg1UV2AdDM4xCQgUFICkSmR/tIrHfb18dkOkneSScdfFHdgNaIHqhDleKW4ra2sc6Baqqrbg9Y2JkkESuWzeqluo0w+Di0IYPNeJ8YUBjBzQvSVCk3KiaFLAp0KoKWivs8W32TBkJWVhcPy9nR8CCfdqFGjcOWVV4ZuzRABrvE4rWHow26eqLrbJ9uaNTeLpvK4cFXBpd9dEaVmo+dYTeV3Hx49u2QOcMFF8obX+nZn/K7J256+8WkIPnbB49G7TjxEqG0nZvzdFRW47fZFT5OXAL845m+vr78jE97Z4FZTJJPYK98Njb01sK97a89Evl527Oug8qCn45lOzRc48lCQmgecqIfotJPU60mTv7k1+prRLOfqcqrF7zGzZ3ruDXjh8UuUo86s+eToNUef0YDq/Xo9F9nd+l3rFX2tOy5pHCQbm4Qbjs4QQk3LWmTg1L/NICp2TSLUmugXUVN+l1ujHwFV4kg6lyiLdAzvaV8Hq+iW7AaKeKIxnNAi1fKJ7BmDn2bod4qhawKdCqCqVVTBLhi88sVSAeD4EE66yZMnQ2MwqA1oba28ukQgqDasRabLI5Kfajg1BoN+kVSwbUe4DSaJ11G1QxFpc7wa0INyta89MojZrd127Gu3vPTp+MO+7sGDYrFbkmUaV3+049nXsrkxMpFmosGnEyIauzOrLoqv2qbwf9cs/1zrVHuaxhPlgo6+gmoDqrJEvPq69kQ9VUdV7fF1VYoxdE2g00crX+wXK8VWJBj0fIDYMR4fwk13/H38mwRIgARIgARIgARIwH4EOhVAp0yZgs2bN2Pfvn3mjWXJkiU466yzDCWdPlfXTBo6S2cS8D8SIAESIAESIAESIAESOEqg0yl4tfm8/fbbMW/ePOhOFUVFRZg7d665VV0zzZ8/H2+//TY6S0fSJEACJEACJEACJEACJNCWQJd+QDWx2tzpoo9MNVTuJISbTrOIlR/QTqpr+Y8i7kPOAkQi6QfUAs0NVdGOfU0/oKHuT/gTbsWZ8F0camBnfkBDiSx+Qj+g4XVgpxrQYBZqIK6xqxBuuq7y4eckQAIkQAIkQAIkQAKJS6BTG9DEbTZbRgIkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CFEDjRZ7lkgAJkAAJkAAJkIBNCVAAtWnHs9kkQAIkQAIkQAIkEC8CjoCEeBUeqXLnzJmDKVOm4NFHH41UlsynlxK46qqrMHr0aDz55JO9tIasVqQIzJ07FwMHDsSf/vSnSGXJfHopgdtuuw2ZmZl49tlne2kNWa1IEbjjjjvg8/nwwgsvRCpL5mNRAgmhAdUvs9/vt2gXsNrdIcC+7g4ta6fVZ5rPtbX7MNzas6/DJWX9dBzDrd+HkWpBQgigkYLBfEiABEiABEiABEiABKJPwBX9IqJfwvTp0zF8+PDoF8QS4k5g2rRpZlo27hVhBaJO4Oyzz0bfvn2jXg4LiD8BNaFKS0uLf0VYg6gTmDRpEhLA8i/qnOxQQELYgNqho9hGEiABEiABEiABEkgUApyCT5SeZDtIgARIgARIgARIwCIELC+AVlRU4L333sPWrVstgpzV7CmBqqoqfPDBBygtLe1pFrzPYgT0ueazbbFO62Z1m5ubsXLlSqxatQoej6ebdzO5lQh4vV6sXr0aX3/9tZWqzbpGiYClBdCNGzdC3Xd8++23+PWvf4233norSpiYbbwJLF68GPfccw927dqFxx9/HE8//XS8q8Tyo0ygurraPNf6g8WQmAQaGhrws5/9LCSA3njjjVCBlCHxCGhfX3/99fjss8+wcOFC3HvvvYnXSLaoWwQsvQhJhZAnnngCZ5xxBq655hrMmzcPl1xyCdxud7cgMHHvJqBuO1555RX88Y9/xLBhw3DDDTeY/r7llluQm5vbuyvP2vWYwB/+8AcuQuoxPWvc+Pbbbxu/vg899JCp8EsvvWQ03uPHj7dGA1jLsAl8+OGHKC4uxi9+8QtzjwqjOruhfp0Z7EnAsgKoqvL379+P4EDVv39/pKeno6SkxAgp9uzOxGx1UlISFixYgIyMDNPApqYm1NXVGWfGidlitmrJkiXm5aKwsJAwEpjA2rVrccUVV2DNmjXmedaXSqfT0hNzCdxbJ9e0AQMGYNu2bTh06BBqa2uhMxxUIJwcU6vfbdknvayszAgkDocj1AfZ2dmorKwM/c2TxCEQFD7VYfUzzzyD2bNno1+/fonTQLYkREBfLBctWoS77rordI0niUmgvLwcr732Gt59912888470Cn4xsbGxGyszVul7pdUA6qaTzWdu/nmm1FQUGBzKvZuvmUFUNWK6dRs26Ba0dTU1LaXeJ5ABNQ27JFHHjELFe6///4EahmbEiSgz7Bus/rLX/6SfiGDUBL4qGP4yJEjMX/+fPz2t7/F0KFDsWzZsgRusX2b9uKLLxrNp67VUBvQpUuXYsWKFfYFwpbDslPweXl5qK+vNwbrKSkppitV+6l7RzMkHgE1YH/wwQcxaNAg/OpXv4K+gDAkHoHdu3fjm2++wX333Wcap6uidZZDvV2oUMqQWARUA6ZasWAYNWqUWSGtMxwMiUVg/fr1RuupM5UaZ82aBTXB0I1kGOxJwLIaUJfLhalTp0KN2DUsX77c2JPQpiQxv8iPPfZYaLEChc/E7GNt1YgRI/DJJ5/g/fffN/Hqq682P1oUPhOzz2fMmGFcq6lpTUtLi1kNH7TrT8wW27dVuovdhg0bDACd6Vi3bh10tzMG+xKw9E5Ie/bsMW5aVCBRw/VHH30U+gbNkFgEVCN2++23m0a1tfl97rnnQovQEqvFbE2QwPPPP28WF956663BSzwmEAHVcP/+9783Wk81sVEhheY1CdTBbZpSU1ODP//5z2bxsM5e6varP//5z7norA0ju51aWgANdpaupsvJyQn+ySMJkAAJkICFCKiJjSoRaMNvoU7rYVXVi4nOYGpksDeBhBBA7d2FbD0JkAAJkAAJkAAJWIuAZW1ArYWZtSUBEiABEiABEiABEggSoAAaJMEjCZAACZAACZAACZBATAhQAI0JZhZCAiRAAiRAAiRAAiQQJEABNEiCRxIgARIgARIgARIggZgQoAAaE8wshARIIBoEdF/pxx9/HHV1dSZ73WFFt3Q82aAugTTfffv2nWxWvJ8ESIAESKAdAhRA24HCSyRAAtYgcPDgQfzmN78JCaBvvPGG2Vf8ZGuvrmI0XwqgJ0uS95MACZBA+wToiKt9LrxKAiRgQQKLFi2yYK1ZZRIgARKwHwFqQO3X52wxCViWgG7XqDtgXX755bjjjjvMriptG6M7rfztb38LXVqwYAGuuOIK/OAHP8DDDz+MyspK85nuwPPTn/4UmzZtwl133YU5c+bg6aefDmlSQxnwhARIgARIICoEKIBGBSszJQESiAaBO++8E0888QTOPfdcs3f4DTfccEwxuof8ypUrzbWXX34Z9913H6ZPn45rr70WH330ES688ELzmc/nw1//+lfMmjULjY2NuOyyy4xge8sttyAQCByTJ/8gARIgARKIPAFOwUeeKXMkARKIAoGvvvoKL774IjZv3ozi4mJTwtixY/HAAw+0W9qqVaswefJks7e4w+EwgujixYuhC4yCYfbs2SZP/XvSpEkmLlu2DBMmTAgm4ZEESIAESCAKBKgBjQJUZkkCJBB5Al988QX69+8fEj61BBUgOwrXXXcdli9fjhEjRuDuu+/Gtm3bzDElJSV0y8UXXxw6V6EzPz8fGzZsCF3jCQmQAAmQQHQIUACNDlfmSgIkEGEC1dXV8Pv9x0yRu1wdT+Kcf/75UKFVBVGdlldhderUqdB8gqGoqCh4CtWS5uTk0A40RIQnJEACJBA9AhRAo8eWOZMACUSQwMSJE1FWVmaEymC2H374YfD0hON7771nFh09+eST2Lhxo9Fs6jS+Xg8GtQsNhr179xotqZbDQAIkQAIkEF0CFECjy5e5kwAJRIiA2nOqzef8+fPN6ncVJl944YUOc//yyy9x0003GaFSFxapz1Cv14vhw4eH7tGFSmvXroU6tH/kkUfMdP2MGTNCn/OEBEiABEggOgQ6nr+KTnnMlQRIgAR6RCA1NdXscqQr2tWuU4MuQNJp9vbCPffcYzSf55xzDtSxvNPpxDPPPGMWJunfGqZMmYKZM2eaqf1x48Zh6dKlyMrKQk1NTXtZ8hoJkAAJkECECDhEM0CfIxGCyWxIgARiQ6C8vBx9+vSBCqVdBbUbLSkpQWFhobHz1PQqgKalpRnXTNOmTTMCpy5AYiABEiABEogNAWpAY8OZpZAACUSQQHeERdV8Dh48uMPS3W63Wf3eYQJ+QAIkQAIkEHECtAGNOFJmSAIk0NsJ6Ip3FWJV+GQgARIgARKIPQFOwceeOUskARIgARIgARIgAVsToAbU1t3PxpMACZAACZAACZBA7AlQAI09c5ZIAiRAAiRAAiRAArYmQAHU1t3PxpMACZAACZAACZBA7AlQAI09c5ZIAiRAAiRAAiRAArYmQAHU1t3PxpMACZAACZAACZBA7AlQAI09c5ZIAiRAAiRAAiRAArYm8P8H9qE8gh7wRwAAAABJRU5ErkJggg==" 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" aria-hidden="true" tabindex="-1"></a>StatDensityCommon <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatDensity2"</span>, Stat, </span> <span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a> <span class="at">default_aes =</span> <span class="fu">aes</span>(<span class="at">y =</span> <span class="fu">stat</span>(density)),</span> <span id="cb12-4"><a href="#cb12-4" aria-hidden="true" tabindex="-1"></a></span> <span id="cb12-5"><a href="#cb12-5" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales, <span class="at">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb12-6"><a href="#cb12-6" aria-hidden="true" tabindex="-1"></a> d <span class="ot"><-</span> <span class="fu">density</span>(data<span class="sc">$</span>x, <span class="at">bw =</span> bandwidth)</span> <span id="cb12-7"><a href="#cb12-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">data.frame</span>(<span class="at">x =</span> d<span class="sc">$</span>x, <span class="at">density =</span> d<span class="sc">$</span>y)</span> <span id="cb12-8"><a href="#cb12-8" aria-hidden="true" tabindex="-1"></a> } </span> <span id="cb12-9"><a href="#cb12-9" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb12-10"><a href="#cb12-10" aria-hidden="true" tabindex="-1"></a></span> <span id="cb12-11"><a href="#cb12-11" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, drv, <span class="at">colour =</span> <span class="fu">stat</span>(density))) <span class="sc">+</span> </span> <span id="cb12-12"><a href="#cb12-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>(<span class="at">bandwidth =</span> <span class="dv">1</span>, <span class="at">geom =</span> <span class="st">"point"</span>)</span> <span id="cb12-13"><a href="#cb12-13" aria-hidden="true" tabindex="-1"></a><span class="co">#> Warning: `stat(density)` was deprecated in ggplot2 3.4.0.</span></span> <span id="cb12-14"><a href="#cb12-14" aria-hidden="true" tabindex="-1"></a><span class="co">#> ℹ Please use `after_stat(density)` instead.</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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, <span class="at">fill =</span> drv)) <span class="sc">+</span> </span> <span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>(<span class="at">bandwidth =</span> <span class="dv">1</span>, <span class="at">geom =</span> <span class="st">"area"</span>, <span class="at">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" aria-hidden="true" tabindex="-1"></a>StatDensityCommon <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"StatDensityCommon"</span>, Stat, </span> <span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="st">"x"</span>,</span> <span id="cb14-3"><a href="#cb14-3" aria-hidden="true" tabindex="-1"></a> <span class="at">default_aes =</span> <span class="fu">aes</span>(<span class="at">y =</span> <span class="fu">stat</span>(density)),</span> <span id="cb14-4"><a href="#cb14-4" aria-hidden="true" tabindex="-1"></a></span> <span id="cb14-5"><a href="#cb14-5" aria-hidden="true" tabindex="-1"></a> <span class="at">setup_params =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb14-6"><a href="#cb14-6" aria-hidden="true" tabindex="-1"></a> min <span class="ot"><-</span> <span class="fu">min</span>(data<span class="sc">$</span>x) <span class="sc">-</span> <span class="dv">3</span> <span class="sc">*</span> params<span class="sc">$</span>bandwidth</span> <span id="cb14-7"><a href="#cb14-7" aria-hidden="true" tabindex="-1"></a> max <span class="ot"><-</span> <span class="fu">max</span>(data<span class="sc">$</span>x) <span class="sc">+</span> <span class="dv">3</span> <span class="sc">*</span> params<span class="sc">$</span>bandwidth</span> <span id="cb14-8"><a href="#cb14-8" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb14-9"><a href="#cb14-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">list</span>(</span> <span id="cb14-10"><a href="#cb14-10" aria-hidden="true" tabindex="-1"></a> <span class="at">bandwidth =</span> params<span class="sc">$</span>bandwidth,</span> <span id="cb14-11"><a href="#cb14-11" aria-hidden="true" tabindex="-1"></a> <span class="at">min =</span> min,</span> <span id="cb14-12"><a href="#cb14-12" aria-hidden="true" tabindex="-1"></a> <span class="at">max =</span> max,</span> <span id="cb14-13"><a href="#cb14-13" aria-hidden="true" tabindex="-1"></a> <span class="at">na.rm =</span> params<span class="sc">$</span>na.rm</span> <span id="cb14-14"><a href="#cb14-14" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb14-15"><a href="#cb14-15" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb14-16"><a href="#cb14-16" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb14-17"><a href="#cb14-17" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_group =</span> <span class="cf">function</span>(data, scales, min, max, <span class="at">bandwidth =</span> <span class="dv">1</span>) {</span> <span id="cb14-18"><a href="#cb14-18" aria-hidden="true" tabindex="-1"></a> d <span class="ot"><-</span> <span class="fu">density</span>(data<span class="sc">$</span>x, <span class="at">bw =</span> bandwidth, <span class="at">from =</span> min, <span class="at">to =</span> max)</span> <span id="cb14-19"><a href="#cb14-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">data.frame</span>(<span class="at">x =</span> d<span class="sc">$</span>x, <span class="at">density =</span> d<span class="sc">$</span>y)</span> <span id="cb14-20"><a href="#cb14-20" aria-hidden="true" tabindex="-1"></a> } </span> <span id="cb14-21"><a href="#cb14-21" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb14-22"><a href="#cb14-22" aria-hidden="true" tabindex="-1"></a></span> <span id="cb14-23"><a href="#cb14-23" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, <span class="at">fill =</span> drv)) <span class="sc">+</span> </span> <span id="cb14-24"><a href="#cb14-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>(<span class="at">bandwidth =</span> <span class="dv">1</span>, <span class="at">geom =</span> <span class="st">"area"</span>, <span class="at">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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, drv, <span class="at">fill =</span> <span class="fu">stat</span>(density))) <span class="sc">+</span> </span> <span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_density_common</span>(<span class="at">bandwidth =</span> <span class="dv">1</span>, <span class="at">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="https://www.amazon.com/dp/B00I60M26G/ref=cm_sw_su_dp">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" aria-hidden="true" tabindex="-1"></a>GeomSimplePoint <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"GeomSimplePoint"</span>, Geom,</span> <span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="fu">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a> <span class="at">default_aes =</span> <span class="fu">aes</span>(<span class="at">shape =</span> <span class="dv">19</span>, <span class="at">colour =</span> <span class="st">"black"</span>),</span> <span id="cb16-4"><a href="#cb16-4" aria-hidden="true" tabindex="-1"></a> <span class="at">draw_key =</span> draw_key_point,</span> <span id="cb16-5"><a href="#cb16-5" aria-hidden="true" tabindex="-1"></a></span> <span id="cb16-6"><a href="#cb16-6" aria-hidden="true" tabindex="-1"></a> <span class="at">draw_panel =</span> <span class="cf">function</span>(data, panel_params, coord) {</span> <span id="cb16-7"><a href="#cb16-7" aria-hidden="true" tabindex="-1"></a> coords <span class="ot"><-</span> coord<span class="sc">$</span><span class="fu">transform</span>(data, panel_params)</span> <span id="cb16-8"><a href="#cb16-8" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">pointsGrob</span>(</span> <span id="cb16-9"><a href="#cb16-9" aria-hidden="true" tabindex="-1"></a> coords<span class="sc">$</span>x, coords<span class="sc">$</span>y,</span> <span id="cb16-10"><a href="#cb16-10" aria-hidden="true" tabindex="-1"></a> <span class="at">pch =</span> coords<span class="sc">$</span>shape,</span> <span id="cb16-11"><a href="#cb16-11" aria-hidden="true" tabindex="-1"></a> <span class="at">gp =</span> grid<span class="sc">::</span><span class="fu">gpar</span>(<span class="at">col =</span> coords<span class="sc">$</span>colour)</span> <span id="cb16-12"><a href="#cb16-12" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb16-13"><a href="#cb16-13" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb16-14"><a href="#cb16-14" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb16-15"><a href="#cb16-15" aria-hidden="true" tabindex="-1"></a></span> <span id="cb16-16"><a href="#cb16-16" aria-hidden="true" tabindex="-1"></a>geom_simple_point <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">stat =</span> <span class="st">"identity"</span>,</span> <span id="cb16-17"><a href="#cb16-17" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb16-18"><a href="#cb16-18" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, ...) {</span> <span id="cb16-19"><a href="#cb16-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb16-20"><a href="#cb16-20" aria-hidden="true" tabindex="-1"></a> <span class="at">geom =</span> GeomSimplePoint, <span class="at">mapping =</span> mapping, <span class="at">data =</span> data, <span class="at">stat =</span> stat, </span> <span id="cb16-21"><a href="#cb16-21" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb16-22"><a href="#cb16-22" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb16-23"><a href="#cb16-23" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb16-24"><a href="#cb16-24" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb16-25"><a href="#cb16-25" aria-hidden="true" tabindex="-1"></a></span> <span id="cb16-26"><a href="#cb16-26" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb16-27"><a href="#cb16-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">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" aria-hidden="true" tabindex="-1"></a>GeomSimplePolygon <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"GeomPolygon"</span>, Geom,</span> <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a> <span class="at">required_aes =</span> <span class="fu">c</span>(<span class="st">"x"</span>, <span class="st">"y"</span>),</span> <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb17-4"><a href="#cb17-4" aria-hidden="true" tabindex="-1"></a> <span class="at">default_aes =</span> <span class="fu">aes</span>(</span> <span id="cb17-5"><a href="#cb17-5" aria-hidden="true" tabindex="-1"></a> <span class="at">colour =</span> <span class="cn">NA</span>, <span class="at">fill =</span> <span class="st">"grey20"</span>, <span class="at">linewidth =</span> <span class="fl">0.5</span>,</span> <span id="cb17-6"><a href="#cb17-6" aria-hidden="true" tabindex="-1"></a> <span class="at">linetype =</span> <span class="dv">1</span>, <span class="at">alpha =</span> <span class="dv">1</span></span> <span id="cb17-7"><a href="#cb17-7" aria-hidden="true" tabindex="-1"></a> ),</span> <span id="cb17-8"><a href="#cb17-8" aria-hidden="true" tabindex="-1"></a></span> <span id="cb17-9"><a href="#cb17-9" aria-hidden="true" tabindex="-1"></a> <span class="at">draw_key =</span> draw_key_polygon,</span> <span id="cb17-10"><a href="#cb17-10" aria-hidden="true" tabindex="-1"></a></span> <span id="cb17-11"><a href="#cb17-11" aria-hidden="true" tabindex="-1"></a> <span class="at">draw_group =</span> <span class="cf">function</span>(data, panel_params, coord) {</span> <span id="cb17-12"><a href="#cb17-12" aria-hidden="true" tabindex="-1"></a> n <span class="ot"><-</span> <span class="fu">nrow</span>(data)</span> <span id="cb17-13"><a href="#cb17-13" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (n <span class="sc"><=</span> <span class="dv">2</span>) <span class="fu">return</span>(grid<span class="sc">::</span><span class="fu">nullGrob</span>())</span> <span id="cb17-14"><a href="#cb17-14" aria-hidden="true" tabindex="-1"></a></span> <span id="cb17-15"><a href="#cb17-15" aria-hidden="true" tabindex="-1"></a> coords <span class="ot"><-</span> coord<span class="sc">$</span><span class="fu">transform</span>(data, panel_params)</span> <span id="cb17-16"><a href="#cb17-16" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a> first_row <span class="ot"><-</span> coords[<span class="dv">1</span>, , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span> <span id="cb17-18"><a href="#cb17-18" aria-hidden="true" tabindex="-1"></a></span> <span id="cb17-19"><a href="#cb17-19" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">polygonGrob</span>(</span> <span id="cb17-20"><a href="#cb17-20" aria-hidden="true" tabindex="-1"></a> coords<span class="sc">$</span>x, coords<span class="sc">$</span>y, </span> <span id="cb17-21"><a href="#cb17-21" aria-hidden="true" tabindex="-1"></a> <span class="at">default.units =</span> <span class="st">"native"</span>,</span> <span id="cb17-22"><a href="#cb17-22" aria-hidden="true" tabindex="-1"></a> <span class="at">gp =</span> grid<span class="sc">::</span><span class="fu">gpar</span>(</span> <span id="cb17-23"><a href="#cb17-23" aria-hidden="true" tabindex="-1"></a> <span class="at">col =</span> first_row<span class="sc">$</span>colour,</span> <span id="cb17-24"><a href="#cb17-24" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> scales<span class="sc">::</span><span class="fu">alpha</span>(first_row<span class="sc">$</span>fill, first_row<span class="sc">$</span>alpha),</span> <span id="cb17-25"><a href="#cb17-25" aria-hidden="true" tabindex="-1"></a> <span class="at">lwd =</span> first_row<span class="sc">$</span>linewidth <span class="sc">*</span> .pt,</span> <span id="cb17-26"><a href="#cb17-26" aria-hidden="true" tabindex="-1"></a> <span class="at">lty =</span> first_row<span class="sc">$</span>linetype</span> <span id="cb17-27"><a href="#cb17-27" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb17-28"><a href="#cb17-28" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb17-29"><a href="#cb17-29" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb17-30"><a href="#cb17-30" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb17-31"><a href="#cb17-31" aria-hidden="true" tabindex="-1"></a>geom_simple_polygon <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, <span class="at">stat =</span> <span class="st">"chull"</span>,</span> <span id="cb17-32"><a href="#cb17-32" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb17-33"><a href="#cb17-33" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, ...) {</span> <span id="cb17-34"><a href="#cb17-34" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb17-35"><a href="#cb17-35" aria-hidden="true" tabindex="-1"></a> <span class="at">geom =</span> GeomSimplePolygon, <span class="at">mapping =</span> mapping, <span class="at">data =</span> data, <span class="at">stat =</span> stat, </span> <span id="cb17-36"><a href="#cb17-36" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb17-37"><a href="#cb17-37" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb17-38"><a href="#cb17-38" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb17-39"><a href="#cb17-39" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb17-40"><a href="#cb17-40" aria-hidden="true" tabindex="-1"></a></span> <span id="cb17-41"><a href="#cb17-41" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb17-42"><a href="#cb17-42" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb17-43"><a href="#cb17-43" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_simple_polygon</span>(<span class="fu">aes</span>(<span class="at">colour =</span> class), <span class="at">fill =</span> <span class="cn">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" aria-hidden="true" tabindex="-1"></a>GeomPolygonHollow <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"GeomPolygonHollow"</span>, GeomPolygon,</span> <span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a> <span class="at">default_aes =</span> <span class="fu">aes</span>(<span class="at">colour =</span> <span class="st">"black"</span>, <span class="at">fill =</span> <span class="cn">NA</span>, <span class="at">linewidth =</span> <span class="fl">0.5</span>, <span class="at">linetype =</span> <span class="dv">1</span>,</span> <span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a> <span class="at">alpha =</span> <span class="cn">NA</span>)</span> <span id="cb18-4"><a href="#cb18-4" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb18-5"><a href="#cb18-5" aria-hidden="true" tabindex="-1"></a>geom_chull <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">mapping =</span> <span class="cn">NULL</span>, <span class="at">data =</span> <span class="cn">NULL</span>, </span> <span id="cb18-6"><a href="#cb18-6" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> <span class="st">"identity"</span>, <span class="at">na.rm =</span> <span class="cn">FALSE</span>, <span class="at">show.legend =</span> <span class="cn">NA</span>, </span> <span id="cb18-7"><a href="#cb18-7" aria-hidden="true" tabindex="-1"></a> <span class="at">inherit.aes =</span> <span class="cn">TRUE</span>, ...) {</span> <span id="cb18-8"><a href="#cb18-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">layer</span>(</span> <span id="cb18-9"><a href="#cb18-9" aria-hidden="true" tabindex="-1"></a> <span class="at">stat =</span> StatChull, <span class="at">geom =</span> GeomPolygonHollow, <span class="at">data =</span> data, <span class="at">mapping =</span> mapping,</span> <span id="cb18-10"><a href="#cb18-10" aria-hidden="true" tabindex="-1"></a> <span class="at">position =</span> position, <span class="at">show.legend =</span> show.legend, <span class="at">inherit.aes =</span> inherit.aes,</span> <span id="cb18-11"><a href="#cb18-11" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(<span class="at">na.rm =</span> na.rm, ...)</span> <span id="cb18-12"><a href="#cb18-12" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb18-13"><a href="#cb18-13" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb18-14"><a href="#cb18-14" aria-hidden="true" tabindex="-1"></a></span> <span id="cb18-15"><a href="#cb18-15" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mpg, <span class="fu">aes</span>(displ, hwy)) <span class="sc">+</span> </span> <span id="cb18-16"><a href="#cb18-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb18-17"><a href="#cb18-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">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 will look at the boxplot layer as an example instead of creating a new one 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" aria-hidden="true" tabindex="-1"></a>StatBoxplot<span class="sc">$</span>setup_params</span> <span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> <ggproto method></span></span> <span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Wrapper function></span></span> <span id="cb19-4"><a href="#cb19-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (...) </span></span> <span id="cb19-5"><a href="#cb19-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> setup_params(..., self = self)</span></span> <span id="cb19-6"><a href="#cb19-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> </span></span> <span id="cb19-7"><a href="#cb19-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb19-8"><a href="#cb19-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (self, data, params) </span></span> <span id="cb19-9"><a href="#cb19-9" aria-hidden="true" tabindex="-1"></a><span class="co">#> {</span></span> <span id="cb19-10"><a href="#cb19-10" aria-hidden="true" tabindex="-1"></a><span class="co">#> params$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = TRUE, </span></span> <span id="cb19-11"><a href="#cb19-11" aria-hidden="true" tabindex="-1"></a><span class="co">#> group_has_equal = TRUE, main_is_optional = TRUE)</span></span> <span id="cb19-12"><a href="#cb19-12" aria-hidden="true" tabindex="-1"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb19-13"><a href="#cb19-13" aria-hidden="true" tabindex="-1"></a><span class="co">#> has_x <- !(is.null(data$x) && is.null(params$x))</span></span> <span id="cb19-14"><a href="#cb19-14" aria-hidden="true" tabindex="-1"></a><span class="co">#> has_y <- !(is.null(data$y) && is.null(params$y))</span></span> <span id="cb19-15"><a href="#cb19-15" aria-hidden="true" tabindex="-1"></a><span class="co">#> if (!has_x && !has_y) {</span></span> <span id="cb19-16"><a href="#cb19-16" aria-hidden="true" tabindex="-1"></a><span class="co">#> cli::cli_abort("{.fn {snake_class(self)}} requires an {.field x} or {.field y} aesthetic.")</span></span> <span id="cb19-17"><a href="#cb19-17" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span> <span id="cb19-18"><a href="#cb19-18" aria-hidden="true" tabindex="-1"></a><span class="co">#> params$width <- params$width %||% (resolution(data$x %||% </span></span> <span id="cb19-19"><a href="#cb19-19" aria-hidden="true" tabindex="-1"></a><span class="co">#> 0) * 0.75)</span></span> <span id="cb19-20"><a href="#cb19-20" aria-hidden="true" tabindex="-1"></a><span class="co">#> if (!is_mapped_discrete(data$x) && is.double(data$x) && !has_groups(data) && </span></span> <span id="cb19-21"><a href="#cb19-21" aria-hidden="true" tabindex="-1"></a><span class="co">#> any(data$x != data$x[1L])) {</span></span> <span id="cb19-22"><a href="#cb19-22" aria-hidden="true" tabindex="-1"></a><span class="co">#> cli::cli_warn(c("Continuous {.field {flipped_names(params$flipped_aes)$x}} aesthetic", </span></span> <span id="cb19-23"><a href="#cb19-23" aria-hidden="true" tabindex="-1"></a><span class="co">#> i = "did you forget {.code aes(group = ...)}?"))</span></span> <span id="cb19-24"><a href="#cb19-24" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span> <span id="cb19-25"><a href="#cb19-25" aria-hidden="true" tabindex="-1"></a><span class="co">#> params</span></span> <span id="cb19-26"><a href="#cb19-26" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span></code></pre></div> <p>Following this is a call to <code>flip_data()</code> which will make sure the data is in horizontal orientation. The rest of the code can then simply assume that the data is in a specific orientation. The same thing happens in <code>setup_data()</code>:</p> <div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a>StatBoxplot<span class="sc">$</span>setup_data</span> <span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> <ggproto method></span></span> <span id="cb20-3"><a href="#cb20-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Wrapper function></span></span> <span id="cb20-4"><a href="#cb20-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (...) </span></span> <span id="cb20-5"><a href="#cb20-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> setup_data(..., self = self)</span></span> <span id="cb20-6"><a href="#cb20-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> </span></span> <span id="cb20-7"><a href="#cb20-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb20-8"><a href="#cb20-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (self, data, params) </span></span> <span id="cb20-9"><a href="#cb20-9" aria-hidden="true" tabindex="-1"></a><span class="co">#> {</span></span> <span id="cb20-10"><a href="#cb20-10" aria-hidden="true" tabindex="-1"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb20-11"><a href="#cb20-11" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$x <- data$x %||% 0</span></span> <span id="cb20-12"><a href="#cb20-12" aria-hidden="true" tabindex="-1"></a><span class="co">#> data <- remove_missing(data, na.rm = params$na.rm, vars = "x", </span></span> <span id="cb20-13"><a href="#cb20-13" aria-hidden="true" tabindex="-1"></a><span class="co">#> name = "stat_boxplot")</span></span> <span id="cb20-14"><a href="#cb20-14" aria-hidden="true" tabindex="-1"></a><span class="co">#> flip_data(data, params$flipped_aes)</span></span> <span id="cb20-15"><a href="#cb20-15" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span></code></pre></div> <p>The data is flipped (if needed), manipulated, and flipped back as it is returned.</p> <p>During the computation, this sandwiching between <code>flip_data()</code> is used as well, but right before the data is returned it will also get a <code>flipped_aes</code> column denoting if the data is flipped or not. This allows the stat to communicate to the geom that orientation has already been determined.</p> </div> <div id="omnidirecitonal-geoms" class="section level3"> <h3>Omnidirecitonal geoms</h3> <p>The setup for geoms is pretty much the same, with a few twists. <code>has_flipped_aes()</code> is also used in <code>setup_params()</code>, where it will usually be picked up from the <code>flipped_aes</code> column given by the stat. In <code>setup_data()</code> you will often see that <code>flipped_aes</code> is reassigned, to make sure it exist prior to position adjustment. This is needed if the geom is used together with a stat that doesn’t handle orientation (often <code>stat_identity()</code>):</p> <div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true" tabindex="-1"></a>GeomBoxplot<span class="sc">$</span>setup_data</span> <span id="cb21-2"><a href="#cb21-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> <ggproto method></span></span> <span id="cb21-3"><a href="#cb21-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Wrapper function></span></span> <span id="cb21-4"><a href="#cb21-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (...) </span></span> <span id="cb21-5"><a href="#cb21-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> setup_data(...)</span></span> <span id="cb21-6"><a href="#cb21-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> </span></span> <span id="cb21-7"><a href="#cb21-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb21-8"><a href="#cb21-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (data, params) </span></span> <span id="cb21-9"><a href="#cb21-9" aria-hidden="true" tabindex="-1"></a><span class="co">#> {</span></span> <span id="cb21-10"><a href="#cb21-10" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$flipped_aes <- params$flipped_aes</span></span> <span id="cb21-11"><a href="#cb21-11" aria-hidden="true" tabindex="-1"></a><span class="co">#> data <- flip_data(data, params$flipped_aes)</span></span> <span id="cb21-12"><a href="#cb21-12" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$width <- data$width %||% params$width %||% (resolution(data$x, </span></span> <span id="cb21-13"><a href="#cb21-13" aria-hidden="true" tabindex="-1"></a><span class="co">#> FALSE) * 0.9)</span></span> <span id="cb21-14"><a href="#cb21-14" aria-hidden="true" tabindex="-1"></a><span class="co">#> if (!is.null(data$outliers)) {</span></span> <span id="cb21-15"><a href="#cb21-15" aria-hidden="true" tabindex="-1"></a><span class="co">#> suppressWarnings({</span></span> <span id="cb21-16"><a href="#cb21-16" aria-hidden="true" tabindex="-1"></a><span class="co">#> out_min <- vapply(data$outliers, min, numeric(1))</span></span> <span id="cb21-17"><a href="#cb21-17" aria-hidden="true" tabindex="-1"></a><span class="co">#> out_max <- vapply(data$outliers, max, numeric(1))</span></span> <span id="cb21-18"><a href="#cb21-18" aria-hidden="true" tabindex="-1"></a><span class="co">#> })</span></span> <span id="cb21-19"><a href="#cb21-19" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$ymin_final <- pmin(out_min, data$ymin)</span></span> <span id="cb21-20"><a href="#cb21-20" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$ymax_final <- pmax(out_max, data$ymax)</span></span> <span id="cb21-21"><a href="#cb21-21" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span> <span id="cb21-22"><a href="#cb21-22" aria-hidden="true" tabindex="-1"></a><span class="co">#> if (is.null(params) || is.null(params$varwidth) || !params$varwidth || </span></span> <span id="cb21-23"><a href="#cb21-23" aria-hidden="true" tabindex="-1"></a><span class="co">#> is.null(data$relvarwidth)) {</span></span> <span id="cb21-24"><a href="#cb21-24" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$xmin <- data$x - data$width/2</span></span> <span id="cb21-25"><a href="#cb21-25" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$xmax <- data$x + data$width/2</span></span> <span id="cb21-26"><a href="#cb21-26" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span> <span id="cb21-27"><a href="#cb21-27" aria-hidden="true" tabindex="-1"></a><span class="co">#> else {</span></span> <span id="cb21-28"><a href="#cb21-28" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$relvarwidth <- data$relvarwidth/max(data$relvarwidth)</span></span> <span id="cb21-29"><a href="#cb21-29" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$xmin <- data$x - data$relvarwidth * data$width/2</span></span> <span id="cb21-30"><a href="#cb21-30" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$xmax <- data$x + data$relvarwidth * data$width/2</span></span> <span id="cb21-31"><a href="#cb21-31" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span> <span id="cb21-32"><a href="#cb21-32" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$width <- NULL</span></span> <span id="cb21-33"><a href="#cb21-33" aria-hidden="true" tabindex="-1"></a><span class="co">#> if (!is.null(data$relvarwidth)) </span></span> <span id="cb21-34"><a href="#cb21-34" aria-hidden="true" tabindex="-1"></a><span class="co">#> data$relvarwidth <- NULL</span></span> <span id="cb21-35"><a href="#cb21-35" aria-hidden="true" tabindex="-1"></a><span class="co">#> flip_data(data, params$flipped_aes)</span></span> <span id="cb21-36"><a href="#cb21-36" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>GeomBoxplot<span class="sc">$</span>required_aes</span> <span id="cb22-2"><a href="#cb22-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> [1] "x|y" "lower|xlower" "upper|xupper" "middle|xmiddle"</span></span> <span id="cb22-3"><a href="#cb22-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> [5] "ymin|xmin" "ymax|xmax"</span></span></code></pre></div> <p>This tells ggplot2 that either all the aesthetics before <code>|</code> are required or all the aesthetics after are required.</p> </div> <div id="ambiguous-layers" class="section level3"> <h3>Ambiguous layers</h3> <p>Some layers will not have a clear interpretation of their data in terms of orientation. A classic example is <code>geom_line()</code> which just by convention runs along the x-axis. There is nothing in the data itself that indicates that. For these geoms the user must indicate a flipped orientation by setting <code>orientation = "y"</code>. The stat or geom will then call <code>has_flipped_aes()</code> with <code>ambiguous = TRUE</code> to cancel any guessing based on data format. As an example we can see the <code>setup_params()</code> method of <code>GeomLine</code>:</p> <div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a>GeomLine<span class="sc">$</span>setup_params</span> <span id="cb23-2"><a href="#cb23-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> <ggproto method></span></span> <span id="cb23-3"><a href="#cb23-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Wrapper function></span></span> <span id="cb23-4"><a href="#cb23-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (...) </span></span> <span id="cb23-5"><a href="#cb23-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> setup_params(...)</span></span> <span id="cb23-6"><a href="#cb23-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> </span></span> <span id="cb23-7"><a href="#cb23-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> <Inner function (f)></span></span> <span id="cb23-8"><a href="#cb23-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> function (data, params) </span></span> <span id="cb23-9"><a href="#cb23-9" aria-hidden="true" tabindex="-1"></a><span class="co">#> {</span></span> <span id="cb23-10"><a href="#cb23-10" aria-hidden="true" tabindex="-1"></a><span class="co">#> params$flipped_aes <- has_flipped_aes(data, params, ambiguous = TRUE)</span></span> <span id="cb23-11"><a href="#cb23-11" aria-hidden="true" tabindex="-1"></a><span class="co">#> params</span></span> <span id="cb23-12"><a href="#cb23-12" aria-hidden="true" tabindex="-1"></a><span class="co">#> }</span></span></code></pre></div> </div> </div> <div id="creating-your-own-theme" class="section level2"> <h2>Creating your own theme</h2> <p>If you’re going to create your own complete theme, there are a few things you need to know:</p> <ul> <li>Overriding existing elements, rather than modifying them</li> <li>The four global elements that affect (almost) every other theme element</li> <li>Complete vs. incomplete elements</li> </ul> <div id="overriding-elements" class="section level3"> <h3>Overriding elements</h3> <p>By default, when you add a new theme element, it inherits values from the existing theme. For example, the following code sets the key colour to red, but it inherits the existing fill colour:</p> <div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1" aria-hidden="true" tabindex="-1"></a><span class="fu">theme_grey</span>()<span class="sc">$</span>legend.key</span> <span id="cb24-2"><a href="#cb24-2" aria-hidden="true" tabindex="-1"></a><span class="co">#> List of 5</span></span> <span id="cb24-3"><a href="#cb24-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ fill : chr "grey95"</span></span> <span id="cb24-4"><a href="#cb24-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ colour : logi NA</span></span> <span id="cb24-5"><a href="#cb24-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linewidth : NULL</span></span> <span id="cb24-6"><a href="#cb24-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb24-7"><a href="#cb24-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ inherit.blank: logi TRUE</span></span> <span id="cb24-8"><a href="#cb24-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> - attr(*, "class")= chr [1:2] "element_rect" "element"</span></span> <span id="cb24-9"><a href="#cb24-9" aria-hidden="true" tabindex="-1"></a></span> <span id="cb24-10"><a href="#cb24-10" aria-hidden="true" tabindex="-1"></a>new_theme <span class="ot"><-</span> <span class="fu">theme_grey</span>() <span class="sc">+</span> <span class="fu">theme</span>(<span class="at">legend.key =</span> <span class="fu">element_rect</span>(<span class="at">colour =</span> <span class="st">"red"</span>))</span> <span id="cb24-11"><a href="#cb24-11" aria-hidden="true" tabindex="-1"></a>new_theme<span class="sc">$</span>legend.key</span> <span id="cb24-12"><a href="#cb24-12" aria-hidden="true" tabindex="-1"></a><span class="co">#> List of 5</span></span> <span id="cb24-13"><a href="#cb24-13" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ fill : chr "grey95"</span></span> <span id="cb24-14"><a href="#cb24-14" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ colour : chr "red"</span></span> <span id="cb24-15"><a href="#cb24-15" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linewidth : NULL</span></span> <span id="cb24-16"><a href="#cb24-16" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb24-17"><a href="#cb24-17" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ inherit.blank: logi FALSE</span></span> <span id="cb24-18"><a href="#cb24-18" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>new_theme <span class="ot"><-</span> <span class="fu">theme_grey</span>() <span class="sc">%+replace%</span> <span class="fu">theme</span>(<span class="at">legend.key =</span> <span class="fu">element_rect</span>(<span class="at">colour =</span> <span class="st">"red"</span>))</span> <span id="cb25-2"><a href="#cb25-2" aria-hidden="true" tabindex="-1"></a>new_theme<span class="sc">$</span>legend.key</span> <span id="cb25-3"><a href="#cb25-3" aria-hidden="true" tabindex="-1"></a><span class="co">#> List of 5</span></span> <span id="cb25-4"><a href="#cb25-4" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ fill : NULL</span></span> <span id="cb25-5"><a href="#cb25-5" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ colour : chr "red"</span></span> <span id="cb25-6"><a href="#cb25-6" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linewidth : NULL</span></span> <span id="cb25-7"><a href="#cb25-7" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ linetype : NULL</span></span> <span id="cb25-8"><a href="#cb25-8" aria-hidden="true" tabindex="-1"></a><span class="co">#> $ inherit.blank: logi FALSE</span></span> <span id="cb25-9"><a href="#cb25-9" aria-hidden="true" tabindex="-1"></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> <colgroup> <col width="23%" /> <col width="33%" /> <col width="42%" /> </colgroup> <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" aria-hidden="true" tabindex="-1"></a>df <span class="ot"><-</span> <span class="fu">data.frame</span>(<span class="at">x =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">3</span>, <span class="at">y =</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">3</span>)</span> <span id="cb26-2"><a href="#cb26-2" aria-hidden="true" tabindex="-1"></a>base <span class="ot"><-</span> <span class="fu">ggplot</span>(df, <span class="fu">aes</span>(x, y)) <span class="sc">+</span> </span> <span id="cb26-3"><a href="#cb26-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span> <span id="cb26-4"><a href="#cb26-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>()</span> <span id="cb26-5"><a href="#cb26-5" aria-hidden="true" tabindex="-1"></a></span> <span id="cb26-6"><a href="#cb26-6" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>base <span class="sc">+</span> <span class="fu">theme</span>(<span class="at">text =</span> <span class="fu">element_text</span>(<span class="at">colour =</span> <span class="st">"red"</span>))</span></code></pre></div> <p><img 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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" aria-hidden="true" tabindex="-1"></a>layout <span class="ot"><-</span> <span class="cf">function</span>(data, params) {</span> <span id="cb28-2"><a href="#cb28-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">data.frame</span>(<span class="at">PANEL =</span> <span class="fu">c</span>(1L, 2L), <span class="at">SCALE_X =</span> 1L, <span class="at">SCALE_Y =</span> 1L)</span> <span id="cb28-3"><a href="#cb28-3" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>mapping <span class="ot"><-</span> <span class="cf">function</span>(data, layout, params) {</span> <span id="cb29-2"><a href="#cb29-2" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="fu">is.null</span>(data) <span class="sc">||</span> <span class="fu">nrow</span>(data) <span class="sc">==</span> <span class="dv">0</span>) {</span> <span id="cb29-3"><a href="#cb29-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(<span class="fu">cbind</span>(data, <span class="at">PANEL =</span> <span class="fu">integer</span>(<span class="dv">0</span>)))</span> <span id="cb29-4"><a href="#cb29-4" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb29-5"><a href="#cb29-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">rbind</span>(</span> <span id="cb29-6"><a href="#cb29-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(data, <span class="at">PANEL =</span> 1L),</span> <span id="cb29-7"><a href="#cb29-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(data, <span class="at">PANEL =</span> 2L)</span> <span id="cb29-8"><a href="#cb29-8" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb29-9"><a href="#cb29-9" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>render <span class="ot"><-</span> <span class="cf">function</span>(panels, layout, x_scales, y_scales, ranges, coord, data,</span> <span id="cb30-2"><a href="#cb30-2" aria-hidden="true" tabindex="-1"></a> theme, params) {</span> <span id="cb30-3"><a href="#cb30-3" aria-hidden="true" tabindex="-1"></a> <span class="co"># Place panels according to settings</span></span> <span id="cb30-4"><a href="#cb30-4" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (params<span class="sc">$</span>horizontal) {</span> <span id="cb30-5"><a href="#cb30-5" aria-hidden="true" tabindex="-1"></a> <span class="co"># Put panels in matrix and convert to a gtable</span></span> <span id="cb30-6"><a href="#cb30-6" aria-hidden="true" tabindex="-1"></a> panels <span class="ot"><-</span> <span class="fu">matrix</span>(panels, <span class="at">ncol =</span> <span class="dv">2</span>)</span> <span id="cb30-7"><a href="#cb30-7" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb30-8"><a href="#cb30-8" aria-hidden="true" tabindex="-1"></a> <span class="at">widths =</span> <span class="fu">unit</span>(<span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="at">heights =</span> <span class="fu">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="at">clip =</span> <span class="st">"on"</span>)</span> <span id="cb30-9"><a href="#cb30-9" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add spacing according to theme</span></span> <span id="cb30-10"><a href="#cb30-10" aria-hidden="true" tabindex="-1"></a> panel_spacing <span class="ot"><-</span> <span class="cf">if</span> (<span class="fu">is.null</span>(theme<span class="sc">$</span>panel.spacing.x)) {</span> <span id="cb30-11"><a href="#cb30-11" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing</span> <span id="cb30-12"><a href="#cb30-12" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb30-13"><a href="#cb30-13" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing.x</span> <span id="cb30-14"><a href="#cb30-14" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb30-15"><a href="#cb30-15" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_col_space</span>(panel_table, panel_spacing)</span> <span id="cb30-16"><a href="#cb30-16" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb30-17"><a href="#cb30-17" aria-hidden="true" tabindex="-1"></a> panels <span class="ot"><-</span> <span class="fu">matrix</span>(panels, <span class="at">ncol =</span> <span class="dv">1</span>)</span> <span id="cb30-18"><a href="#cb30-18" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb30-19"><a href="#cb30-19" aria-hidden="true" tabindex="-1"></a> <span class="at">widths =</span> <span class="fu">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="at">heights =</span> <span class="fu">unit</span>(<span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="at">clip =</span> <span class="st">"on"</span>)</span> <span id="cb30-20"><a href="#cb30-20" aria-hidden="true" tabindex="-1"></a> panel_spacing <span class="ot"><-</span> <span class="cf">if</span> (<span class="fu">is.null</span>(theme<span class="sc">$</span>panel.spacing.y)) {</span> <span id="cb30-21"><a href="#cb30-21" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing</span> <span id="cb30-22"><a href="#cb30-22" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb30-23"><a href="#cb30-23" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing.y</span> <span id="cb30-24"><a href="#cb30-24" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb30-25"><a href="#cb30-25" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_row_space</span>(panel_table, panel_spacing)</span> <span id="cb30-26"><a href="#cb30-26" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb30-27"><a href="#cb30-27" aria-hidden="true" tabindex="-1"></a> <span class="co"># Name panel grobs so they can be found later</span></span> <span id="cb30-28"><a href="#cb30-28" aria-hidden="true" tabindex="-1"></a> panel_table<span class="sc">$</span>layout<span class="sc">$</span>name <span class="ot"><-</span> <span class="fu">paste0</span>(<span class="st">"panel-"</span>, <span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">2</span>))</span> <span id="cb30-29"><a href="#cb30-29" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb30-30"><a href="#cb30-30" aria-hidden="true" tabindex="-1"></a> <span class="co"># Construct the axes</span></span> <span id="cb30-31"><a href="#cb30-31" aria-hidden="true" tabindex="-1"></a> axes <span class="ot"><-</span> <span class="fu">render_axes</span>(ranges[<span class="dv">1</span>], ranges[<span class="dv">1</span>], coord, theme, </span> <span id="cb30-32"><a href="#cb30-32" aria-hidden="true" tabindex="-1"></a> <span class="at">transpose =</span> <span class="cn">TRUE</span>)</span> <span id="cb30-33"><a href="#cb30-33" aria-hidden="true" tabindex="-1"></a></span> <span id="cb30-34"><a href="#cb30-34" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add axes around each panel</span></span> <span id="cb30-35"><a href="#cb30-35" aria-hidden="true" tabindex="-1"></a> panel_pos_h <span class="ot"><-</span> <span class="fu">panel_cols</span>(panel_table)<span class="sc">$</span>l</span> <span id="cb30-36"><a href="#cb30-36" aria-hidden="true" tabindex="-1"></a> panel_pos_v <span class="ot"><-</span> <span class="fu">panel_rows</span>(panel_table)<span class="sc">$</span>t</span> <span id="cb30-37"><a href="#cb30-37" aria-hidden="true" tabindex="-1"></a> axis_width_l <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertWidth</span>(</span> <span id="cb30-38"><a href="#cb30-38" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobWidth</span>(axes<span class="sc">$</span>y<span class="sc">$</span>left[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-39"><a href="#cb30-39" aria-hidden="true" tabindex="-1"></a> axis_width_r <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertWidth</span>(</span> <span id="cb30-40"><a href="#cb30-40" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobWidth</span>(axes<span class="sc">$</span>y<span class="sc">$</span>right[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-41"><a href="#cb30-41" aria-hidden="true" tabindex="-1"></a> <span class="do">## We do it reverse so we don't change the position of panels when we add axes</span></span> <span id="cb30-42"><a href="#cb30-42" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="fu">rev</span>(panel_pos_h)) {</span> <span id="cb30-43"><a href="#cb30-43" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_cols</span>(panel_table, axis_width_r, i)</span> <span id="cb30-44"><a href="#cb30-44" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb30-45"><a href="#cb30-45" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>y<span class="sc">$</span>right, <span class="fu">length</span>(panel_pos_v)), <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> i <span class="sc">+</span> <span class="dv">1</span>, </span> <span id="cb30-46"><a href="#cb30-46" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-47"><a href="#cb30-47" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_cols</span>(panel_table, axis_width_l, i <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb30-48"><a href="#cb30-48" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb30-49"><a href="#cb30-49" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>y<span class="sc">$</span>left, <span class="fu">length</span>(panel_pos_v)), <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> i, </span> <span id="cb30-50"><a href="#cb30-50" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-51"><a href="#cb30-51" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb30-52"><a href="#cb30-52" aria-hidden="true" tabindex="-1"></a> <span class="do">## Recalculate as gtable has changed</span></span> <span id="cb30-53"><a href="#cb30-53" aria-hidden="true" tabindex="-1"></a> panel_pos_h <span class="ot"><-</span> <span class="fu">panel_cols</span>(panel_table)<span class="sc">$</span>l</span> <span id="cb30-54"><a href="#cb30-54" aria-hidden="true" tabindex="-1"></a> panel_pos_v <span class="ot"><-</span> <span class="fu">panel_rows</span>(panel_table)<span class="sc">$</span>t</span> <span id="cb30-55"><a href="#cb30-55" aria-hidden="true" tabindex="-1"></a> axis_height_t <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertHeight</span>(</span> <span id="cb30-56"><a href="#cb30-56" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobHeight</span>(axes<span class="sc">$</span>x<span class="sc">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-57"><a href="#cb30-57" aria-hidden="true" tabindex="-1"></a> axis_height_b <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertHeight</span>(</span> <span id="cb30-58"><a href="#cb30-58" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobHeight</span>(axes<span class="sc">$</span>x<span class="sc">$</span>bottom[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb30-59"><a href="#cb30-59" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="fu">rev</span>(panel_pos_v)) {</span> <span id="cb30-60"><a href="#cb30-60" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_rows</span>(panel_table, axis_height_b, i)</span> <span id="cb30-61"><a href="#cb30-61" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb30-62"><a href="#cb30-62" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>x<span class="sc">$</span>bottom, <span class="fu">length</span>(panel_pos_h)), <span class="at">t =</span> i <span class="sc">+</span> <span class="dv">1</span>, <span class="at">l =</span> panel_pos_h, </span> <span id="cb30-63"><a href="#cb30-63" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-64"><a href="#cb30-64" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_rows</span>(panel_table, axis_height_t, i <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb30-65"><a href="#cb30-65" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb30-66"><a href="#cb30-66" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>x<span class="sc">$</span>top, <span class="fu">length</span>(panel_pos_h)), <span class="at">t =</span> i, <span class="at">l =</span> panel_pos_h, </span> <span id="cb30-67"><a href="#cb30-67" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb30-68"><a href="#cb30-68" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb30-69"><a href="#cb30-69" aria-hidden="true" tabindex="-1"></a> panel_table</span> <span id="cb30-70"><a href="#cb30-70" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-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" aria-hidden="true" tabindex="-1"></a><span class="co"># Stat-transformed data or not.</span></span> <span id="cb31-3"><a href="#cb31-3" aria-hidden="true" tabindex="-1"></a>facet_duplicate <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">horizontal =</span> <span class="cn">TRUE</span>, <span class="at">shrink =</span> <span class="cn">TRUE</span>) {</span> <span id="cb31-4"><a href="#cb31-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggproto</span>(<span class="cn">NULL</span>, FacetDuplicate,</span> <span id="cb31-5"><a href="#cb31-5" aria-hidden="true" tabindex="-1"></a> <span class="at">shrink =</span> shrink,</span> <span id="cb31-6"><a href="#cb31-6" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(</span> <span id="cb31-7"><a href="#cb31-7" aria-hidden="true" tabindex="-1"></a> <span class="at">horizontal =</span> horizontal</span> <span id="cb31-8"><a href="#cb31-8" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb31-9"><a href="#cb31-9" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb31-10"><a href="#cb31-10" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb31-11"><a href="#cb31-11" aria-hidden="true" tabindex="-1"></a></span> <span id="cb31-12"><a href="#cb31-12" aria-hidden="true" tabindex="-1"></a>FacetDuplicate <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"FacetDuplicate"</span>, Facet,</span> <span id="cb31-13"><a href="#cb31-13" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_layout =</span> layout,</span> <span id="cb31-14"><a href="#cb31-14" aria-hidden="true" tabindex="-1"></a> <span class="at">map_data =</span> mapping,</span> <span id="cb31-15"><a href="#cb31-15" aria-hidden="true" tabindex="-1"></a> <span class="at">draw_panels =</span> render</span> <span id="cb31-16"><a href="#cb31-16" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>p <span class="ot"><-</span> <span class="fu">ggplot</span>(mtcars, <span class="fu">aes</span>(<span class="at">x =</span> hp, <span class="at">y =</span> mpg)) <span class="sc">+</span> <span class="fu">geom_point</span>()</span> <span id="cb32-2"><a href="#cb32-2" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a>p <span class="sc">+</span> <span class="fu">facet_duplicate</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="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" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(scales)</span> <span id="cb34-2"><a href="#cb34-2" aria-hidden="true" tabindex="-1"></a></span> <span id="cb34-3"><a href="#cb34-3" aria-hidden="true" tabindex="-1"></a>facet_trans <span class="ot"><-</span> <span class="cf">function</span>(trans, <span class="at">horizontal =</span> <span class="cn">TRUE</span>, <span class="at">shrink =</span> <span class="cn">TRUE</span>) {</span> <span id="cb34-4"><a href="#cb34-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggproto</span>(<span class="cn">NULL</span>, FacetTrans,</span> <span id="cb34-5"><a href="#cb34-5" aria-hidden="true" tabindex="-1"></a> <span class="at">shrink =</span> shrink,</span> <span id="cb34-6"><a href="#cb34-6" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> <span class="fu">list</span>(</span> <span id="cb34-7"><a href="#cb34-7" aria-hidden="true" tabindex="-1"></a> <span class="at">trans =</span> scales<span class="sc">::</span><span class="fu">as.trans</span>(trans),</span> <span id="cb34-8"><a href="#cb34-8" aria-hidden="true" tabindex="-1"></a> <span class="at">horizontal =</span> horizontal</span> <span id="cb34-9"><a href="#cb34-9" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb34-10"><a href="#cb34-10" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb34-11"><a href="#cb34-11" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb34-12"><a href="#cb34-12" aria-hidden="true" tabindex="-1"></a></span> <span id="cb34-13"><a href="#cb34-13" aria-hidden="true" tabindex="-1"></a>FacetTrans <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"FacetTrans"</span>, Facet,</span> <span id="cb34-14"><a href="#cb34-14" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_layout =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb34-16"><a href="#cb34-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">data.frame</span>(<span class="at">PANEL =</span> <span class="fu">c</span>(1L, 2L), <span class="at">SCALE_X =</span> 1L, <span class="at">SCALE_Y =</span> <span class="fu">c</span>(1L, 2L))</span> <span id="cb34-17"><a href="#cb34-17" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb34-18"><a href="#cb34-18" aria-hidden="true" tabindex="-1"></a> <span class="co"># Same as before</span></span> <span id="cb34-19"><a href="#cb34-19" aria-hidden="true" tabindex="-1"></a> <span class="at">map_data =</span> <span class="cf">function</span>(data, layout, params) {</span> <span id="cb34-20"><a href="#cb34-20" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="fu">is.null</span>(data) <span class="sc">||</span> <span class="fu">nrow</span>(data) <span class="sc">==</span> <span class="dv">0</span>) {</span> <span id="cb34-21"><a href="#cb34-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(<span class="fu">cbind</span>(data, <span class="at">PANEL =</span> <span class="fu">integer</span>(<span class="dv">0</span>)))</span> <span id="cb34-22"><a href="#cb34-22" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-23"><a href="#cb34-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">rbind</span>(</span> <span id="cb34-24"><a href="#cb34-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(data, <span class="at">PANEL =</span> 1L),</span> <span id="cb34-25"><a href="#cb34-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(data, <span class="at">PANEL =</span> 2L)</span> <span id="cb34-26"><a href="#cb34-26" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb34-27"><a href="#cb34-27" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb34-28"><a href="#cb34-28" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a> <span class="at">init_scales =</span> <span class="cf">function</span>(layout, <span class="at">x_scale =</span> <span class="cn">NULL</span>, <span class="at">y_scale =</span> <span class="cn">NULL</span>, params) {</span> <span id="cb34-30"><a href="#cb34-30" aria-hidden="true" tabindex="-1"></a> scales <span class="ot"><-</span> <span class="fu">list</span>()</span> <span id="cb34-31"><a href="#cb34-31" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(x_scale)) {</span> <span id="cb34-32"><a href="#cb34-32" aria-hidden="true" tabindex="-1"></a> scales<span class="sc">$</span>x <span class="ot"><-</span> <span class="fu">lapply</span>(<span class="fu">seq_len</span>(<span class="fu">max</span>(layout<span class="sc">$</span>SCALE_X)), <span class="cf">function</span>(i) x_scale<span class="sc">$</span><span class="fu">clone</span>())</span> <span id="cb34-33"><a href="#cb34-33" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-34"><a href="#cb34-34" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(y_scale)) {</span> <span id="cb34-35"><a href="#cb34-35" aria-hidden="true" tabindex="-1"></a> y_scale_orig <span class="ot"><-</span> y_scale<span class="sc">$</span><span class="fu">clone</span>()</span> <span id="cb34-36"><a href="#cb34-36" aria-hidden="true" tabindex="-1"></a> y_scale_new <span class="ot"><-</span> y_scale<span class="sc">$</span><span class="fu">clone</span>()</span> <span id="cb34-37"><a href="#cb34-37" aria-hidden="true" tabindex="-1"></a> y_scale_new<span class="sc">$</span>trans <span class="ot"><-</span> params<span class="sc">$</span>trans</span> <span id="cb34-38"><a href="#cb34-38" aria-hidden="true" tabindex="-1"></a> <span class="co"># Make sure that oob values are kept</span></span> <span id="cb34-39"><a href="#cb34-39" aria-hidden="true" tabindex="-1"></a> y_scale_new<span class="sc">$</span>oob <span class="ot"><-</span> <span class="cf">function</span>(x, ...) x</span> <span id="cb34-40"><a href="#cb34-40" aria-hidden="true" tabindex="-1"></a> scales<span class="sc">$</span>y <span class="ot"><-</span> <span class="fu">list</span>(y_scale_orig, y_scale_new)</span> <span id="cb34-41"><a href="#cb34-41" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-42"><a href="#cb34-42" aria-hidden="true" tabindex="-1"></a> scales</span> <span id="cb34-43"><a href="#cb34-43" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb34-44"><a href="#cb34-44" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a> <span class="at">train_scales =</span> <span class="cf">function</span>(x_scales, y_scales, layout, data, params) {</span> <span id="cb34-46"><a href="#cb34-46" aria-hidden="true" tabindex="-1"></a> <span class="co"># Transform data for second panel prior to scale training</span></span> <span id="cb34-47"><a href="#cb34-47" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="sc">!</span><span class="fu">is.null</span>(y_scales)) {</span> <span id="cb34-48"><a href="#cb34-48" aria-hidden="true" tabindex="-1"></a> data <span class="ot"><-</span> <span class="fu">lapply</span>(data, <span class="cf">function</span>(layer_data) {</span> <span id="cb34-49"><a href="#cb34-49" aria-hidden="true" tabindex="-1"></a> match_id <span class="ot"><-</span> <span class="fu">match</span>(layer_data<span class="sc">$</span>PANEL, layout<span class="sc">$</span>PANEL)</span> <span id="cb34-50"><a href="#cb34-50" aria-hidden="true" tabindex="-1"></a> y_vars <span class="ot"><-</span> <span class="fu">intersect</span>(y_scales[[<span class="dv">1</span>]]<span class="sc">$</span>aesthetics, <span class="fu">names</span>(layer_data))</span> <span id="cb34-51"><a href="#cb34-51" aria-hidden="true" tabindex="-1"></a> trans_scale <span class="ot"><-</span> layer_data<span class="sc">$</span>PANEL <span class="sc">==</span> 2L</span> <span id="cb34-52"><a href="#cb34-52" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> y_vars) {</span> <span id="cb34-53"><a href="#cb34-53" aria-hidden="true" tabindex="-1"></a> layer_data[trans_scale, i] <span class="ot"><-</span> y_scales[[<span class="dv">2</span>]]<span class="sc">$</span><span class="fu">transform</span>(layer_data[trans_scale, i])</span> <span id="cb34-54"><a href="#cb34-54" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-55"><a href="#cb34-55" aria-hidden="true" tabindex="-1"></a> layer_data</span> <span id="cb34-56"><a href="#cb34-56" aria-hidden="true" tabindex="-1"></a> })</span> <span id="cb34-57"><a href="#cb34-57" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-58"><a href="#cb34-58" aria-hidden="true" tabindex="-1"></a> Facet<span class="sc">$</span><span class="fu">train_scales</span>(x_scales, y_scales, layout, data, params)</span> <span id="cb34-59"><a href="#cb34-59" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb34-60"><a href="#cb34-60" aria-hidden="true" tabindex="-1"></a> <span class="co"># this is where we actually modify the data. It cannot be done in $map_data as that function</span></span> <span id="cb34-61"><a href="#cb34-61" aria-hidden="true" tabindex="-1"></a> <span class="co"># doesn't have access to the scales</span></span> <span id="cb34-62"><a href="#cb34-62" aria-hidden="true" tabindex="-1"></a> <span class="at">finish_data =</span> <span class="cf">function</span>(data, layout, x_scales, y_scales, params) {</span> <span id="cb34-63"><a href="#cb34-63" aria-hidden="true" tabindex="-1"></a> match_id <span class="ot"><-</span> <span class="fu">match</span>(data<span class="sc">$</span>PANEL, layout<span class="sc">$</span>PANEL)</span> <span id="cb34-64"><a href="#cb34-64" aria-hidden="true" tabindex="-1"></a> y_vars <span class="ot"><-</span> <span class="fu">intersect</span>(y_scales[[<span class="dv">1</span>]]<span class="sc">$</span>aesthetics, <span class="fu">names</span>(data))</span> <span id="cb34-65"><a href="#cb34-65" aria-hidden="true" tabindex="-1"></a> trans_scale <span class="ot"><-</span> data<span class="sc">$</span>PANEL <span class="sc">==</span> 2L</span> <span id="cb34-66"><a href="#cb34-66" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> y_vars) {</span> <span id="cb34-67"><a href="#cb34-67" aria-hidden="true" tabindex="-1"></a> data[trans_scale, i] <span class="ot"><-</span> y_scales[[<span class="dv">2</span>]]<span class="sc">$</span><span class="fu">transform</span>(data[trans_scale, i])</span> <span id="cb34-68"><a href="#cb34-68" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-69"><a href="#cb34-69" aria-hidden="true" tabindex="-1"></a> data</span> <span id="cb34-70"><a href="#cb34-70" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb34-71"><a href="#cb34-71" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a> <span class="at">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" aria-hidden="true" tabindex="-1"></a> data, theme, params) {</span> <span id="cb34-75"><a href="#cb34-75" aria-hidden="true" tabindex="-1"></a> <span class="co"># Place panels according to settings</span></span> <span id="cb34-76"><a href="#cb34-76" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (params<span class="sc">$</span>horizontal) {</span> <span id="cb34-77"><a href="#cb34-77" aria-hidden="true" tabindex="-1"></a> <span class="co"># Put panels in matrix and convert to a gtable</span></span> <span id="cb34-78"><a href="#cb34-78" aria-hidden="true" tabindex="-1"></a> panels <span class="ot"><-</span> <span class="fu">matrix</span>(panels, <span class="at">ncol =</span> <span class="dv">2</span>)</span> <span id="cb34-79"><a href="#cb34-79" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb34-80"><a href="#cb34-80" aria-hidden="true" tabindex="-1"></a> <span class="at">widths =</span> <span class="fu">unit</span>(<span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="at">heights =</span> <span class="fu">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="at">clip =</span> <span class="st">"on"</span>)</span> <span id="cb34-81"><a href="#cb34-81" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add spacing according to theme</span></span> <span id="cb34-82"><a href="#cb34-82" aria-hidden="true" tabindex="-1"></a> panel_spacing <span class="ot"><-</span> <span class="cf">if</span> (<span class="fu">is.null</span>(theme<span class="sc">$</span>panel.spacing.x)) {</span> <span id="cb34-83"><a href="#cb34-83" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing</span> <span id="cb34-84"><a href="#cb34-84" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb34-85"><a href="#cb34-85" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing.x</span> <span id="cb34-86"><a href="#cb34-86" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-87"><a href="#cb34-87" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_col_space</span>(panel_table, panel_spacing)</span> <span id="cb34-88"><a href="#cb34-88" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb34-89"><a href="#cb34-89" aria-hidden="true" tabindex="-1"></a> panels <span class="ot"><-</span> <span class="fu">matrix</span>(panels, <span class="at">ncol =</span> <span class="dv">1</span>)</span> <span id="cb34-90"><a href="#cb34-90" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_matrix</span>(<span class="st">"layout"</span>, panels, </span> <span id="cb34-91"><a href="#cb34-91" aria-hidden="true" tabindex="-1"></a> <span class="at">widths =</span> <span class="fu">unit</span>(<span class="dv">1</span>, <span class="st">"null"</span>), <span class="at">heights =</span> <span class="fu">unit</span>(<span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">1</span>), <span class="st">"null"</span>), <span class="at">clip =</span> <span class="st">"on"</span>)</span> <span id="cb34-92"><a href="#cb34-92" aria-hidden="true" tabindex="-1"></a> panel_spacing <span class="ot"><-</span> <span class="cf">if</span> (<span class="fu">is.null</span>(theme<span class="sc">$</span>panel.spacing.y)) {</span> <span id="cb34-93"><a href="#cb34-93" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing</span> <span id="cb34-94"><a href="#cb34-94" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb34-95"><a href="#cb34-95" aria-hidden="true" tabindex="-1"></a> theme<span class="sc">$</span>panel.spacing.y</span> <span id="cb34-96"><a href="#cb34-96" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-97"><a href="#cb34-97" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_row_space</span>(panel_table, panel_spacing)</span> <span id="cb34-98"><a href="#cb34-98" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-99"><a href="#cb34-99" aria-hidden="true" tabindex="-1"></a> <span class="co"># Name panel grobs so they can be found later</span></span> <span id="cb34-100"><a href="#cb34-100" aria-hidden="true" tabindex="-1"></a> panel_table<span class="sc">$</span>layout<span class="sc">$</span>name <span class="ot"><-</span> <span class="fu">paste0</span>(<span class="st">"panel-"</span>, <span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">2</span>))</span> <span id="cb34-101"><a href="#cb34-101" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-102"><a href="#cb34-102" aria-hidden="true" tabindex="-1"></a> <span class="co"># Construct the axes</span></span> <span id="cb34-103"><a href="#cb34-103" aria-hidden="true" tabindex="-1"></a> axes <span class="ot"><-</span> <span class="fu">render_axes</span>(ranges[<span class="dv">1</span>], ranges, coord, theme, </span> <span id="cb34-104"><a href="#cb34-104" aria-hidden="true" tabindex="-1"></a> <span class="at">transpose =</span> <span class="cn">TRUE</span>)</span> <span id="cb34-105"><a href="#cb34-105" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-106"><a href="#cb34-106" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add axes around each panel</span></span> <span id="cb34-107"><a href="#cb34-107" aria-hidden="true" tabindex="-1"></a> grobWidths <span class="ot"><-</span> <span class="cf">function</span>(x) {</span> <span id="cb34-108"><a href="#cb34-108" aria-hidden="true" tabindex="-1"></a> <span class="fu">unit</span>(<span class="fu">vapply</span>(x, <span class="cf">function</span>(x) {</span> <span id="cb34-109"><a href="#cb34-109" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">convertWidth</span>(</span> <span id="cb34-110"><a href="#cb34-110" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobWidth</span>(x), <span class="st">"cm"</span>, <span class="cn">TRUE</span>)</span> <span id="cb34-111"><a href="#cb34-111" aria-hidden="true" tabindex="-1"></a> }, <span class="fu">numeric</span>(<span class="dv">1</span>)), <span class="st">"cm"</span>)</span> <span id="cb34-112"><a href="#cb34-112" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-113"><a href="#cb34-113" aria-hidden="true" tabindex="-1"></a> panel_pos_h <span class="ot"><-</span> <span class="fu">panel_cols</span>(panel_table)<span class="sc">$</span>l</span> <span id="cb34-114"><a href="#cb34-114" aria-hidden="true" tabindex="-1"></a> panel_pos_v <span class="ot"><-</span> <span class="fu">panel_rows</span>(panel_table)<span class="sc">$</span>t</span> <span id="cb34-115"><a href="#cb34-115" aria-hidden="true" tabindex="-1"></a> axis_width_l <span class="ot"><-</span> <span class="fu">grobWidths</span>(axes<span class="sc">$</span>y<span class="sc">$</span>left)</span> <span id="cb34-116"><a href="#cb34-116" aria-hidden="true" tabindex="-1"></a> axis_width_r <span class="ot"><-</span> <span class="fu">grobWidths</span>(axes<span class="sc">$</span>y<span class="sc">$</span>right)</span> <span id="cb34-117"><a href="#cb34-117" aria-hidden="true" tabindex="-1"></a> <span class="do">## We do it reverse so we don't change the position of panels when we add axes</span></span> <span id="cb34-118"><a href="#cb34-118" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (params<span class="sc">$</span>horizontal) {</span> <span id="cb34-119"><a href="#cb34-119" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="fu">rev</span>(<span class="fu">seq_along</span>(panel_pos_h))) {</span> <span id="cb34-120"><a href="#cb34-120" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_cols</span>(panel_table, axis_width_r[i], panel_pos_h[i])</span> <span id="cb34-121"><a href="#cb34-121" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table,</span> <span id="cb34-122"><a href="#cb34-122" aria-hidden="true" tabindex="-1"></a> axes<span class="sc">$</span>y<span class="sc">$</span>right[i], <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> panel_pos_h[i] <span class="sc">+</span> <span class="dv">1</span>,</span> <span id="cb34-123"><a href="#cb34-123" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-124"><a href="#cb34-124" aria-hidden="true" tabindex="-1"></a></span> <span id="cb34-125"><a href="#cb34-125" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_cols</span>(panel_table, axis_width_l[i], panel_pos_h[i] <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb34-126"><a href="#cb34-126" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table,</span> <span id="cb34-127"><a href="#cb34-127" aria-hidden="true" tabindex="-1"></a> axes<span class="sc">$</span>y<span class="sc">$</span>left[i], <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> panel_pos_h[i],</span> <span id="cb34-128"><a href="#cb34-128" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-129"><a href="#cb34-129" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-130"><a href="#cb34-130" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb34-131"><a href="#cb34-131" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">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" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table,</span> <span id="cb34-133"><a href="#cb34-133" aria-hidden="true" tabindex="-1"></a> axes<span class="sc">$</span>y<span class="sc">$</span>right, <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> panel_pos_h <span class="sc">+</span> <span class="dv">1</span>,</span> <span id="cb34-134"><a href="#cb34-134" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-135"><a href="#cb34-135" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_cols</span>(panel_table, axis_width_l[<span class="dv">1</span>], panel_pos_h <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb34-136"><a href="#cb34-136" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table,</span> <span id="cb34-137"><a href="#cb34-137" aria-hidden="true" tabindex="-1"></a> axes<span class="sc">$</span>y<span class="sc">$</span>left, <span class="at">t =</span> panel_pos_v, <span class="at">l =</span> panel_pos_h,</span> <span id="cb34-138"><a href="#cb34-138" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-139"><a href="#cb34-139" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-140"><a href="#cb34-140" aria-hidden="true" tabindex="-1"></a></span> <span id="cb34-141"><a href="#cb34-141" aria-hidden="true" tabindex="-1"></a> <span class="do">## Recalculate as gtable has changed</span></span> <span id="cb34-142"><a href="#cb34-142" aria-hidden="true" tabindex="-1"></a> panel_pos_h <span class="ot"><-</span> <span class="fu">panel_cols</span>(panel_table)<span class="sc">$</span>l</span> <span id="cb34-143"><a href="#cb34-143" aria-hidden="true" tabindex="-1"></a> panel_pos_v <span class="ot"><-</span> <span class="fu">panel_rows</span>(panel_table)<span class="sc">$</span>t</span> <span id="cb34-144"><a href="#cb34-144" aria-hidden="true" tabindex="-1"></a> axis_height_t <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertHeight</span>(</span> <span id="cb34-145"><a href="#cb34-145" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobHeight</span>(axes<span class="sc">$</span>x<span class="sc">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-146"><a href="#cb34-146" aria-hidden="true" tabindex="-1"></a> axis_height_b <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertHeight</span>(</span> <span id="cb34-147"><a href="#cb34-147" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobHeight</span>(axes<span class="sc">$</span>x<span class="sc">$</span>bottom[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-148"><a href="#cb34-148" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="fu">rev</span>(panel_pos_v)) {</span> <span id="cb34-149"><a href="#cb34-149" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_rows</span>(panel_table, axis_height_b, i)</span> <span id="cb34-150"><a href="#cb34-150" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb34-151"><a href="#cb34-151" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>x<span class="sc">$</span>bottom, <span class="fu">length</span>(panel_pos_h)), <span class="at">t =</span> i <span class="sc">+</span> <span class="dv">1</span>, <span class="at">l =</span> panel_pos_h, </span> <span id="cb34-152"><a href="#cb34-152" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-153"><a href="#cb34-153" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_rows</span>(panel_table, axis_height_t, i <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb34-154"><a href="#cb34-154" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, </span> <span id="cb34-155"><a href="#cb34-155" aria-hidden="true" tabindex="-1"></a> <span class="fu">rep</span>(axes<span class="sc">$</span>x<span class="sc">$</span>top, <span class="fu">length</span>(panel_pos_h)), <span class="at">t =</span> i, <span class="at">l =</span> panel_pos_h, </span> <span id="cb34-156"><a href="#cb34-156" aria-hidden="true" tabindex="-1"></a> <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-157"><a href="#cb34-157" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-158"><a href="#cb34-158" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-159"><a href="#cb34-159" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add strips</span></span> <span id="cb34-160"><a href="#cb34-160" aria-hidden="true" tabindex="-1"></a> strips <span class="ot"><-</span> <span class="fu">render_strips</span>(</span> <span id="cb34-161"><a href="#cb34-161" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> <span class="fu">data.frame</span>(<span class="at">name =</span> <span class="fu">c</span>(<span class="st">"Original"</span>, <span class="fu">paste0</span>(<span class="st">"Transformed ("</span>, params<span class="sc">$</span>trans<span class="sc">$</span>name, <span class="st">")"</span>))),</span> <span id="cb34-162"><a href="#cb34-162" aria-hidden="true" tabindex="-1"></a> <span class="at">labeller =</span> label_value, <span class="at">theme =</span> theme)</span> <span id="cb34-163"><a href="#cb34-163" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-164"><a href="#cb34-164" aria-hidden="true" tabindex="-1"></a> panel_pos_h <span class="ot"><-</span> <span class="fu">panel_cols</span>(panel_table)<span class="sc">$</span>l</span> <span id="cb34-165"><a href="#cb34-165" aria-hidden="true" tabindex="-1"></a> panel_pos_v <span class="ot"><-</span> <span class="fu">panel_rows</span>(panel_table)<span class="sc">$</span>t</span> <span id="cb34-166"><a href="#cb34-166" aria-hidden="true" tabindex="-1"></a> strip_height <span class="ot"><-</span> <span class="fu">unit</span>(grid<span class="sc">::</span><span class="fu">convertHeight</span>(</span> <span id="cb34-167"><a href="#cb34-167" aria-hidden="true" tabindex="-1"></a> grid<span class="sc">::</span><span class="fu">grobHeight</span>(strips<span class="sc">$</span>x<span class="sc">$</span>top[[<span class="dv">1</span>]]), <span class="st">"cm"</span>, <span class="cn">TRUE</span>), <span class="st">"cm"</span>)</span> <span id="cb34-168"><a href="#cb34-168" aria-hidden="true" tabindex="-1"></a> <span class="cf">for</span> (i <span class="cf">in</span> <span class="fu">rev</span>(<span class="fu">seq_along</span>(panel_pos_v))) {</span> <span id="cb34-169"><a href="#cb34-169" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_rows</span>(panel_table, strip_height, panel_pos_v[i] <span class="sc">-</span> <span class="dv">1</span>)</span> <span id="cb34-170"><a href="#cb34-170" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (params<span class="sc">$</span>horizontal) {</span> <span id="cb34-171"><a href="#cb34-171" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, strips<span class="sc">$</span>x<span class="sc">$</span>top, </span> <span id="cb34-172"><a href="#cb34-172" aria-hidden="true" tabindex="-1"></a> <span class="at">t =</span> panel_pos_v[i], <span class="at">l =</span> panel_pos_h, <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-173"><a href="#cb34-173" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb34-174"><a href="#cb34-174" aria-hidden="true" tabindex="-1"></a> panel_table <span class="ot"><-</span> gtable<span class="sc">::</span><span class="fu">gtable_add_grob</span>(panel_table, strips<span class="sc">$</span>x<span class="sc">$</span>top[i], </span> <span id="cb34-175"><a href="#cb34-175" aria-hidden="true" tabindex="-1"></a> <span class="at">t =</span> panel_pos_v[i], <span class="at">l =</span> panel_pos_h, <span class="at">clip =</span> <span class="st">"off"</span>)</span> <span id="cb34-176"><a href="#cb34-176" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-177"><a href="#cb34-177" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-178"><a href="#cb34-178" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-179"><a href="#cb34-179" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb34-180"><a href="#cb34-180" aria-hidden="true" tabindex="-1"></a> panel_table</span> <span id="cb34-181"><a href="#cb34-181" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb34-182"><a href="#cb34-182" aria-hidden="true" tabindex="-1"></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" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(mtcars, <span class="fu">aes</span>(<span class="at">x =</span> hp, <span class="at">y =</span> mpg)) <span class="sc">+</span> <span class="fu">geom_point</span>() <span class="sc">+</span> <span class="fu">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" aria-hidden="true" tabindex="-1"></a>facet_bootstrap <span class="ot"><-</span> <span class="cf">function</span>(<span class="at">n =</span> <span class="dv">9</span>, <span class="at">prop =</span> <span class="fl">0.2</span>, <span class="at">nrow =</span> <span class="cn">NULL</span>, <span class="at">ncol =</span> <span class="cn">NULL</span>, </span> <span id="cb36-2"><a href="#cb36-2" aria-hidden="true" tabindex="-1"></a> <span class="at">scales =</span> <span class="st">"fixed"</span>, <span class="at">shrink =</span> <span class="cn">TRUE</span>, <span class="at">strip.position =</span> <span class="st">"top"</span>) {</span> <span id="cb36-3"><a href="#cb36-3" aria-hidden="true" tabindex="-1"></a> </span> <span id="cb36-4"><a href="#cb36-4" aria-hidden="true" tabindex="-1"></a> facet <span class="ot"><-</span> <span class="fu">facet_wrap</span>(<span class="sc">~</span>.bootstrap, <span class="at">nrow =</span> nrow, <span class="at">ncol =</span> ncol, <span class="at">scales =</span> scales, </span> <span id="cb36-5"><a href="#cb36-5" aria-hidden="true" tabindex="-1"></a> <span class="at">shrink =</span> shrink, <span class="at">strip.position =</span> strip.position)</span> <span id="cb36-6"><a href="#cb36-6" aria-hidden="true" tabindex="-1"></a> facet<span class="sc">$</span>params<span class="sc">$</span>n <span class="ot"><-</span> n</span> <span id="cb36-7"><a href="#cb36-7" aria-hidden="true" tabindex="-1"></a> facet<span class="sc">$</span>params<span class="sc">$</span>prop <span class="ot"><-</span> prop</span> <span id="cb36-8"><a href="#cb36-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggproto</span>(<span class="cn">NULL</span>, FacetBootstrap,</span> <span id="cb36-9"><a href="#cb36-9" aria-hidden="true" tabindex="-1"></a> <span class="at">shrink =</span> shrink,</span> <span id="cb36-10"><a href="#cb36-10" aria-hidden="true" tabindex="-1"></a> <span class="at">params =</span> facet<span class="sc">$</span>params</span> <span id="cb36-11"><a href="#cb36-11" aria-hidden="true" tabindex="-1"></a> )</span> <span id="cb36-12"><a href="#cb36-12" aria-hidden="true" tabindex="-1"></a>}</span> <span id="cb36-13"><a href="#cb36-13" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-14"><a href="#cb36-14" aria-hidden="true" tabindex="-1"></a>FacetBootstrap <span class="ot"><-</span> <span class="fu">ggproto</span>(<span class="st">"FacetBootstrap"</span>, FacetWrap,</span> <span id="cb36-15"><a href="#cb36-15" aria-hidden="true" tabindex="-1"></a> <span class="at">compute_layout =</span> <span class="cf">function</span>(data, params) {</span> <span id="cb36-16"><a href="#cb36-16" aria-hidden="true" tabindex="-1"></a> id <span class="ot"><-</span> <span class="fu">seq_len</span>(params<span class="sc">$</span>n)</span> <span id="cb36-17"><a href="#cb36-17" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-18"><a href="#cb36-18" aria-hidden="true" tabindex="-1"></a> dims <span class="ot"><-</span> <span class="fu">wrap_dims</span>(params<span class="sc">$</span>n, params<span class="sc">$</span>nrow, params<span class="sc">$</span>ncol)</span> <span id="cb36-19"><a href="#cb36-19" aria-hidden="true" tabindex="-1"></a> layout <span class="ot"><-</span> <span class="fu">data.frame</span>(<span class="at">PANEL =</span> <span class="fu">factor</span>(id))</span> <span id="cb36-20"><a href="#cb36-20" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-21"><a href="#cb36-21" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (params<span class="sc">$</span>as.table) {</span> <span id="cb36-22"><a href="#cb36-22" aria-hidden="true" tabindex="-1"></a> layout<span class="sc">$</span>ROW <span class="ot"><-</span> <span class="fu">as.integer</span>((id <span class="sc">-</span> 1L) <span class="sc">%/%</span> dims[<span class="dv">2</span>] <span class="sc">+</span> 1L)</span> <span id="cb36-23"><a href="#cb36-23" aria-hidden="true" tabindex="-1"></a> } <span class="cf">else</span> {</span> <span id="cb36-24"><a href="#cb36-24" aria-hidden="true" tabindex="-1"></a> layout<span class="sc">$</span>ROW <span class="ot"><-</span> <span class="fu">as.integer</span>(dims[<span class="dv">1</span>] <span class="sc">-</span> (id <span class="sc">-</span> 1L) <span class="sc">%/%</span> dims[<span class="dv">2</span>])</span> <span id="cb36-25"><a href="#cb36-25" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb36-26"><a href="#cb36-26" aria-hidden="true" tabindex="-1"></a> layout<span class="sc">$</span>COL <span class="ot"><-</span> <span class="fu">as.integer</span>((id <span class="sc">-</span> 1L) <span class="sc">%%</span> dims[<span class="dv">2</span>] <span class="sc">+</span> 1L)</span> <span id="cb36-27"><a href="#cb36-27" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-28"><a href="#cb36-28" aria-hidden="true" tabindex="-1"></a> layout <span class="ot"><-</span> layout[<span class="fu">order</span>(layout<span class="sc">$</span>PANEL), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span> <span id="cb36-29"><a href="#cb36-29" aria-hidden="true" tabindex="-1"></a> <span class="fu">rownames</span>(layout) <span class="ot"><-</span> <span class="cn">NULL</span></span> <span id="cb36-30"><a href="#cb36-30" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-31"><a href="#cb36-31" aria-hidden="true" tabindex="-1"></a> <span class="co"># Add scale identification</span></span> <span id="cb36-32"><a href="#cb36-32" aria-hidden="true" tabindex="-1"></a> layout<span class="sc">$</span>SCALE_X <span class="ot"><-</span> <span class="cf">if</span> (params<span class="sc">$</span>free<span class="sc">$</span>x) id <span class="cf">else</span> 1L</span> <span id="cb36-33"><a href="#cb36-33" aria-hidden="true" tabindex="-1"></a> layout<span class="sc">$</span>SCALE_Y <span class="ot"><-</span> <span class="cf">if</span> (params<span class="sc">$</span>free<span class="sc">$</span>y) id <span class="cf">else</span> 1L</span> <span id="cb36-34"><a href="#cb36-34" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-35"><a href="#cb36-35" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(layout, <span class="at">.bootstrap =</span> id)</span> <span id="cb36-36"><a href="#cb36-36" aria-hidden="true" tabindex="-1"></a> },</span> <span id="cb36-37"><a href="#cb36-37" aria-hidden="true" tabindex="-1"></a> <span class="at">map_data =</span> <span class="cf">function</span>(data, layout, params) {</span> <span id="cb36-38"><a href="#cb36-38" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> (<span class="fu">is.null</span>(data) <span class="sc">||</span> <span class="fu">nrow</span>(data) <span class="sc">==</span> <span class="dv">0</span>) {</span> <span id="cb36-39"><a href="#cb36-39" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(<span class="fu">cbind</span>(data, <span class="at">PANEL =</span> <span class="fu">integer</span>(<span class="dv">0</span>)))</span> <span id="cb36-40"><a href="#cb36-40" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb36-41"><a href="#cb36-41" aria-hidden="true" tabindex="-1"></a> n_samples <span class="ot"><-</span> <span class="fu">round</span>(<span class="fu">nrow</span>(data) <span class="sc">*</span> params<span class="sc">$</span>prop)</span> <span id="cb36-42"><a href="#cb36-42" aria-hidden="true" tabindex="-1"></a> new_data <span class="ot"><-</span> <span class="fu">lapply</span>(<span class="fu">seq_len</span>(params<span class="sc">$</span>n), <span class="cf">function</span>(i) {</span> <span id="cb36-43"><a href="#cb36-43" aria-hidden="true" tabindex="-1"></a> <span class="fu">cbind</span>(data[<span class="fu">sample</span>(<span class="fu">nrow</span>(data), n_samples), , <span class="at">drop =</span> <span class="cn">FALSE</span>], <span class="at">PANEL =</span> i)</span> <span id="cb36-44"><a href="#cb36-44" aria-hidden="true" tabindex="-1"></a> })</span> <span id="cb36-45"><a href="#cb36-45" aria-hidden="true" tabindex="-1"></a> <span class="fu">do.call</span>(rbind, new_data)</span> <span id="cb36-46"><a href="#cb36-46" aria-hidden="true" tabindex="-1"></a> }</span> <span id="cb36-47"><a href="#cb36-47" aria-hidden="true" tabindex="-1"></a>)</span> <span id="cb36-48"><a href="#cb36-48" aria-hidden="true" tabindex="-1"></a></span> <span id="cb36-49"><a href="#cb36-49" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(diamonds, <span class="fu">aes</span>(carat, price)) <span class="sc">+</span> </span> <span id="cb36-50"><a href="#cb36-50" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">alpha =</span> <span class="fl">0.1</span>) <span class="sc">+</span> </span> <span id="cb36-51"><a href="#cb36-51" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_bootstrap</span>(<span class="at">n =</span> <span class="dv">9</span>, <span class="at">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>