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@ -40,7 +40,7 @@
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9069</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9070</span>
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</span>
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</div>
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@ -185,7 +185,7 @@
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<h1>Benchmarks</h1>
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<h4 class="author">Matthijs S. Berends</h4>
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<h4 class="date">01 September 2019</h4>
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<h4 class="date">02 September 2019</h4>
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<div class="hidden name"><code>benchmarks.Rmd</code></div>
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@ -220,35 +220,35 @@
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<a class="sourceLine" id="cb2-17" data-line-number="17"><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>
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<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
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<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq</span></a>
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<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 8.6 8.9 12.0 9.6 10.0</span></a>
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<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 33.0 33.0 39.0 34.0 50.0</span></a>
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<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 33.0 33.0 40.0 35.0 49.0</span></a>
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<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 9.0 9.2 11.0 9.6 9.8</span></a>
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<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 8.8 9.2 11.0 9.6 9.9</span></a>
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<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 23.0 25.0 29.0 26.0 27.0</span></a>
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<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 24.0 26.0 25.0 25.0</span></a>
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<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 4.0 4.2 4.4 4.2 4.6</span></a>
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<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 1500.0 1500.0 1600.0 1600.0 1700.0</span></a>
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<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 530.0 540.0 550.0 550.0 560.0</span></a>
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<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 8.2 8.7 12.0 9.1 9.5</span></a>
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<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 20.0 35.0 21.0 37.0</span></a>
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<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 19.0 19.0 23.0 20.0 21.0</span></a>
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<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 19.0 20.0 19.0 20.0</span></a>
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<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 8.4 8.8 11.0 9.1 9.9</span></a>
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<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 32.0 33.0 37.0 34.0 35.0</span></a>
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<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 32.0 33.0 40.0 34.0 52.0</span></a>
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<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 9.1 9.2 9.4 9.3 9.4</span></a>
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<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 8.6 9.1 11.0 9.3 9.7</span></a>
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<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 24.0 25.0 33.0 26.0 45.0</span></a>
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<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 25.0 27.0 25.0 26.0</span></a>
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<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 4.0 4.1 4.5 4.3 4.6</span></a>
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<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 1500.0 1600.0 1700.0 1700.0 1700.0</span></a>
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<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 550.0 550.0 560.0 560.0 580.0</span></a>
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<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 8.7 9.0 9.4 9.2 10.0</span></a>
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<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 20.0 26.0 21.0 37.0</span></a>
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<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 19.0 19.0 20.0 20.0 20.0</span></a>
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<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 24.0 20.0 21.0</span></a>
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<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># max neval</span></a>
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<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 25.0 10</span></a>
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<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 52.0 10</span></a>
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<a class="sourceLine" id="cb2-37" data-line-number="37"><span class="co"># 53.0 10</span></a>
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<a class="sourceLine" id="cb2-38" data-line-number="38"><span class="co"># 29.0 10</span></a>
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<a class="sourceLine" id="cb2-39" data-line-number="39"><span class="co"># 28.0 10</span></a>
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<a class="sourceLine" id="cb2-40" data-line-number="40"><span class="co"># 50.0 10</span></a>
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<a class="sourceLine" id="cb2-41" data-line-number="41"><span class="co"># 40.0 10</span></a>
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<a class="sourceLine" id="cb2-42" data-line-number="42"><span class="co"># 5.2 10</span></a>
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<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 27.0 10</span></a>
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<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 61.0 10</span></a>
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<a class="sourceLine" id="cb2-37" data-line-number="37"><span class="co"># 58.0 10</span></a>
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<a class="sourceLine" id="cb2-38" data-line-number="38"><span class="co"># 10.0 10</span></a>
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<a class="sourceLine" id="cb2-39" data-line-number="39"><span class="co"># 26.0 10</span></a>
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<a class="sourceLine" id="cb2-40" data-line-number="40"><span class="co"># 48.0 10</span></a>
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<a class="sourceLine" id="cb2-41" data-line-number="41"><span class="co"># 42.0 10</span></a>
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<a class="sourceLine" id="cb2-42" data-line-number="42"><span class="co"># 5.9 10</span></a>
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<a class="sourceLine" id="cb2-43" data-line-number="43"><span class="co"># 1700.0 10</span></a>
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<a class="sourceLine" id="cb2-44" data-line-number="44"><span class="co"># 580.0 10</span></a>
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<a class="sourceLine" id="cb2-45" data-line-number="45"><span class="co"># 36.0 10</span></a>
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<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 110.0 10</span></a>
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<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 35.0 10</span></a>
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<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 34.0 10</span></a></code></pre></div>
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<a class="sourceLine" id="cb2-44" data-line-number="44"><span class="co"># 590.0 10</span></a>
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<a class="sourceLine" id="cb2-45" data-line-number="45"><span class="co"># 10.0 10</span></a>
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<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 41.0 10</span></a>
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<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 21.0 10</span></a>
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<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 45.0 10</span></a></code></pre></div>
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<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="1125"></p>
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<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>
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<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>
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@ -261,12 +261,12 @@
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<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>
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<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
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<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq max neval</span></a>
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<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 300 300 310 320 320 330 10</span></a>
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<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 290 300 300 300 320 320 10</span></a>
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<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 130 140 150 140 150 160 10</span></a>
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<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 140 160 160 160 170 170 10</span></a>
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<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 49 52 57 55 56 72 10</span></a></code></pre></div>
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<p>That takes 1.1 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>
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<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 300 300 320 320 330 340 10</span></a>
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<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 290 320 330 320 330 400 10</span></a>
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<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 150 150 160 170 170 170 10</span></a>
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<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 140 150 150 150 160 170 10</span></a>
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<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 53 55 65 59 76 80 10</span></a></code></pre></div>
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<p>That takes 1.2 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>
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<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 uncommon):</p>
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<p><img src="benchmarks_files/figure-html/unnamed-chunk-6-1.png" width="1125"><img src="benchmarks_files/figure-html/unnamed-chunk-6-2.png" width="1125"><img src="benchmarks_files/figure-html/unnamed-chunk-6-3.png" width="1125"></p>
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<p>Uncommon microorganisms take a lot more time than common microorganisms. To relieve this pitfall and further improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
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@ -300,8 +300,8 @@
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<a class="sourceLine" id="cb4-24" 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>
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<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
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<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
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<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 582 614 622 620 624 677 10</span></a></code></pre></div>
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<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.62 seconds (619 ms). You only lose time on your unique input values.</p>
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<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 625 659 686 689 698 746 10</span></a></code></pre></div>
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<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.69 seconds (688 ms). You only lose time on your unique input values.</p>
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</div>
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<div id="precalculated-results" class="section level3">
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<h3 class="hasAnchor">
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@ -313,11 +313,11 @@
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<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
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<a class="sourceLine" id="cb5-5" 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>
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<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
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<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
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<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.520 6.600 6.790 6.800 6.930 7.080 10</span></a>
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<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.100 22.300 25.600 23.200 23.500 42.800 10</span></a>
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<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.705 0.772 0.816 0.806 0.854 0.977 10</span></a></code></pre></div>
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<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>
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<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
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<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.930 7.380 7.87 7.580 8.20 9.54 10</span></a>
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<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 23.700 25.700 30.50 26.000 29.60 59.00 10</span></a>
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<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.859 0.912 0.99 0.958 1.05 1.24 10</span></a></code></pre></div>
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<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.001 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>
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<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it <-<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>
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<a class="sourceLine" id="cb6-2" 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>
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<a class="sourceLine" id="cb6-3" 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>
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@ -330,14 +330,14 @@
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<a class="sourceLine" id="cb6-10" 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>
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<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
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<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
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<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.470 0.477 0.506 0.492 0.498 0.674 10</span></a>
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||||
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.623 0.634 0.674 0.669 0.708 0.744 10</span></a>
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<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.778 0.819 0.845 0.844 0.866 0.915 10</span></a>
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<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.462 0.471 0.483 0.482 0.492 0.515 10</span></a>
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<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.462 0.464 0.476 0.472 0.479 0.518 10</span></a>
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<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.460 0.466 0.475 0.470 0.482 0.510 10</span></a>
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<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.456 0.465 0.478 0.477 0.486 0.513 10</span></a>
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<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.459 0.464 0.472 0.470 0.475 0.509 10</span></a></code></pre></div>
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<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.478 0.490 0.512 0.509 0.530 0.579 10</span></a>
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||||
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.644 0.670 0.711 0.673 0.740 0.930 10</span></a>
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<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.697 0.815 0.887 0.840 0.992 1.150 10</span></a>
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<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.456 0.486 0.511 0.503 0.521 0.643 10</span></a>
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<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.465 0.477 0.534 0.497 0.556 0.804 10</span></a>
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||||
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.459 0.472 0.490 0.477 0.509 0.556 10</span></a>
|
||||
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.466 0.488 0.526 0.522 0.544 0.637 10</span></a>
|
||||
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.455 0.455 0.476 0.465 0.485 0.535 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">
|
||||
@ -364,13 +364,13 @@
|
||||
<a class="sourceLine" id="cb7-18" 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="cb7-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 17.64 17.88 20.31 18.36 19.05 37.62 10</span></a>
|
||||
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.15 19.25 21.73 19.75 20.40 37.72 10</span></a>
|
||||
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 24.34 24.48 36.33 24.88 26.21 121.60 10</span></a>
|
||||
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 18.95 19.09 19.29 19.28 19.53 19.61 10</span></a>
|
||||
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.02 19.10 22.80 19.24 20.42 36.65 10</span></a>
|
||||
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.01 19.04 19.21 19.15 19.20 19.94 10</span></a>
|
||||
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 18.94 19.08 22.28 19.55 20.36 38.81 10</span></a></code></pre></div>
|
||||
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 19.02 19.15 20.50 19.34 21.18 27.84 10</span></a>
|
||||
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.56 20.25 28.34 22.84 39.77 50.78 10</span></a>
|
||||
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 26.12 26.25 27.73 27.17 28.60 31.65 10</span></a>
|
||||
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 20.02 20.58 22.36 22.26 23.95 25.71 10</span></a>
|
||||
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 20.30 20.47 23.21 21.23 24.56 34.71 10</span></a>
|
||||
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 20.14 20.56 31.97 21.47 23.47 125.00 10</span></a>
|
||||
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 19.83 20.24 22.74 20.46 22.65 38.93 10</span></a></code></pre></div>
|
||||
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
Reference in New Issue
Block a user