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(v0.7.1.9036) preserve ab/mo classes in subsetting

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dr. M.S. (Matthijs) Berends
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>
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<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">11 August 2019</h4>
<h4 class="date">12 August 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -210,14 +210,14 @@
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"><span class="co"># as.mo("sau") 8.3 8.5 14.0 9.1 9.2 39.0 10</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"><span class="co"># as.mo("stau") 31.0 32.0 38.0 32.0 47.0 53.0 10</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"><span class="co"># as.mo("staaur") 8.2 8.4 20.0 8.7 40.0 55.0 10</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"><span class="co"># as.mo("STAAUR") 8.2 8.4 10.0 8.9 9.4 24.0 10</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"><span class="co"># as.mo("S. aureus") 23.0 24.0 33.0 24.0 24.0 99.0 10</span></a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="co"># as.mo("S. aureus") 23.0 23.0 29.0 24.0 40.0 42.0 10</span></a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># as.mo("Staphylococcus aureus") 3.7 3.9 4.1 4.1 4.2 4.6 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"><span class="co"># as.mo("sau") 8.6 9.2 9.9 9.7 11.0 12 10</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"><span class="co"># as.mo("stau") 32.0 33.0 33.0 33.0 34.0 35 10</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"><span class="co"># as.mo("staaur") 8.7 9.0 13.0 9.6 11.0 26 10</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"><span class="co"># as.mo("STAAUR") 8.6 9.1 13.0 9.5 9.7 28 10</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"><span class="co"># as.mo("S. aureus") 24.0 24.0 28.0 25.0 26.0 41 10</span></a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="co"># as.mo("S. aureus") 24.0 24.0 37.0 24.0 39.0 120 10</span></a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># as.mo("Staphylococcus aureus") 4.0 4.2 6.0 4.3 4.6 21 10</span></a></code></pre></div>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Thermus islandicus</em> (<code>B_THERMS_ISL</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">T.islandicus &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"theisl"</span>),</a>
@ -229,12 +229,12 @@
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(T.islandicus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 270 270 280 290 290 300 10</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 280 290 290 290 300 300 10</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 130 130 150 150 160 160 10</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 130 130 150 150 150 160 10</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 46 48 54 50 63 71 10</span></a></code></pre></div>
<p>That takes 8.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 270 280 290 290 310 320 10</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 280 290 300 290 300 310 10</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 140 140 150 140 160 170 10</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 140 150 160 160 160 170 10</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 48 49 60 60 68 77 10</span></a></code></pre></div>
<p>That takes 9.5 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Thermus islandicus</em> (which is very uncommon):</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/par">par</a></span>(<span class="dt">mar =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">5</span>, <span class="dv">16</span>, <span class="dv">4</span>, <span class="dv">2</span>)) <span class="co"># set more space for left margin text (16)</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2"></a>
@ -280,8 +280,8 @@
<a class="sourceLine" id="cb5-24" data-line-number="24"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-27" data-line-number="27"><span class="co"># mo_name(x) 623 631 659 637 697 729 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.64 seconds (637 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb5-27" data-line-number="27"><span class="co"># mo_name(x) 596 622 635 626 635 704 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.63 seconds (626 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -294,10 +294,10 @@
<a class="sourceLine" id="cb6-5" data-line-number="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># A 6.290 6.730 7.170 7.010 7.760 8.09 10</span></a>
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># B 22.600 22.700 26.200 23.000 25.400 44.30 10</span></a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># C 0.798 0.806 0.874 0.844 0.891 1.05 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># A 6.700 6.950 7.410 7.600 7.730 8.06 10</span></a>
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># B 22.900 23.900 27.000 24.100 24.200 46.00 10</span></a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># C 0.772 0.833 0.876 0.874 0.918 1.03 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0009 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb7-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
<a class="sourceLine" id="cb7-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
@ -310,14 +310,14 @@
<a class="sourceLine" id="cb7-10" data-line-number="10"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># A 0.455 0.458 0.471 0.465 0.482 0.504 10</span></a>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># B 0.480 0.482 0.497 0.491 0.497 0.554 10</span></a>
<a class="sourceLine" id="cb7-15" data-line-number="15"><span class="co"># C 0.662 0.687 0.754 0.750 0.788 0.964 10</span></a>
<a class="sourceLine" id="cb7-16" data-line-number="16"><span class="co"># D 0.484 0.484 0.496 0.488 0.501 0.544 10</span></a>
<a class="sourceLine" id="cb7-17" data-line-number="17"><span class="co"># E 0.442 0.450 0.459 0.456 0.462 0.492 10</span></a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="co"># F 0.440 0.447 0.456 0.452 0.463 0.486 10</span></a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># G 0.450 0.452 0.462 0.459 0.463 0.485 10</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># H 0.455 0.461 0.467 0.467 0.471 0.492 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># A 0.472 0.475 0.553 0.562 0.607 0.675 10</span></a>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># B 0.474 0.482 0.560 0.493 0.577 0.973 10</span></a>
<a class="sourceLine" id="cb7-15" data-line-number="15"><span class="co"># C 0.766 0.820 0.899 0.881 0.941 1.070 10</span></a>
<a class="sourceLine" id="cb7-16" data-line-number="16"><span class="co"># D 0.459 0.485 0.539 0.503 0.569 0.744 10</span></a>
<a class="sourceLine" id="cb7-17" data-line-number="17"><span class="co"># E 0.421 0.448 0.470 0.456 0.488 0.543 10</span></a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="co"># F 0.430 0.457 0.534 0.495 0.592 0.738 10</span></a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># G 0.420 0.450 0.477 0.463 0.491 0.586 10</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># H 0.426 0.437 0.500 0.447 0.461 0.776 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
@ -344,13 +344,13 @@
<a class="sourceLine" id="cb8-18" data-line-number="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb8-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-21" data-line-number="21"><span class="co"># en 17.66 17.86 18.50 18.49 19.14 19.36 10</span></a>
<a class="sourceLine" id="cb8-22" data-line-number="22"><span class="co"># de 19.03 19.38 19.64 19.49 20.01 20.42 10</span></a>
<a class="sourceLine" id="cb8-23" data-line-number="23"><span class="co"># nl 24.40 25.23 30.77 25.78 41.94 44.93 10</span></a>
<a class="sourceLine" id="cb8-24" data-line-number="24"><span class="co"># es 19.18 19.22 23.30 19.53 21.34 39.20 10</span></a>
<a class="sourceLine" id="cb8-25" data-line-number="25"><span class="co"># it 19.02 19.24 23.53 19.57 20.35 50.89 10</span></a>
<a class="sourceLine" id="cb8-26" data-line-number="26"><span class="co"># fr 19.28 19.33 19.87 19.57 20.19 21.25 10</span></a>
<a class="sourceLine" id="cb8-27" data-line-number="27"><span class="co"># pt 18.89 19.14 19.77 19.67 20.21 20.99 10</span></a></code></pre></div>
<a class="sourceLine" id="cb8-21" data-line-number="21"><span class="co"># en 18.77 19.83 25.36 20.44 28.51 45.88 10</span></a>
<a class="sourceLine" id="cb8-22" data-line-number="22"><span class="co"># de 20.37 20.86 23.19 21.45 22.23 39.08 10</span></a>
<a class="sourceLine" id="cb8-23" data-line-number="23"><span class="co"># nl 26.50 27.09 27.74 27.58 28.10 29.74 10</span></a>
<a class="sourceLine" id="cb8-24" data-line-number="24"><span class="co"># es 20.82 21.18 21.66 21.27 22.04 23.64 10</span></a>
<a class="sourceLine" id="cb8-25" data-line-number="25"><span class="co"># it 19.82 20.65 25.98 21.22 22.13 50.42 10</span></a>
<a class="sourceLine" id="cb8-26" data-line-number="26"><span class="co"># fr 20.07 21.20 21.68 21.47 21.89 23.76 10</span></a>
<a class="sourceLine" id="cb8-27" data-line-number="27"><span class="co"># pt 19.87 20.63 22.76 21.07 21.68 38.11 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>