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(v1.1.0.9015) new default eucast_rules

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dr. M.S. (Matthijs) Berends
2020-05-20 12:00:17 +02:00
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@ -39,7 +39,7 @@
</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">1.1.0.9009</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.1.0.9015</span>
</span>
</div>
@ -186,7 +186,7 @@
<h1 data-toc-skip>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 May 2020</h4>
<h4 class="date">20 May 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd"><code>vignettes/benchmarks.Rmd</code></a></small>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -221,36 +221,21 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">S.aureus</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">2</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("sau") 7.5 9.0 21.0 11.0 37.0 43.0</span>
<span class="co"># as.mo("stau") 130.0 130.0 170.0 170.0 180.0 280.0</span>
<span class="co"># as.mo("STAU") 130.0 140.0 150.0 150.0 170.0 180.0</span>
<span class="co"># as.mo("staaur") 7.3 9.7 13.0 11.0 11.0 37.0</span>
<span class="co"># as.mo("STAAUR") 7.3 9.2 13.0 9.8 10.0 45.0</span>
<span class="co"># as.mo("S. aureus") 10.0 11.0 23.0 12.0 12.0 120.0</span>
<span class="co"># as.mo("S aureus") 9.9 12.0 23.0 13.0 40.0 43.0</span>
<span class="co"># as.mo("Staphylococcus aureus") 5.7 6.4 7.4 7.2 8.8 9.5</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 850.0 860.0 870.0 870.0 880.0 910.0</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 330.0 350.0 360.0 360.0 370.0 390.0</span>
<span class="co"># as.mo("MRSA") 7.7 9.2 12.0 9.7 11.0 39.0</span>
<span class="co"># as.mo("VISA") 19.0 21.0 25.0 22.0 24.0 55.0</span>
<span class="co"># as.mo("VRSA") 18.0 22.0 30.0 25.0 26.0 57.0</span>
<span class="co"># as.mo(22242419) 140.0 150.0 170.0 150.0 190.0 210.0</span>
<span class="co"># neval</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span></pre></body></html></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 8.7 9.4 13.0 9.5 11 39.0 10</span>
<span class="co"># as.mo("stau") 140.0 150.0 160.0 170.0 180 180.0 10</span>
<span class="co"># as.mo("STAU") 140.0 140.0 160.0 150.0 170 180.0 10</span>
<span class="co"># as.mo("staaur") 8.7 9.6 16.0 11.0 11 41.0 10</span>
<span class="co"># as.mo("STAAUR") 8.7 9.2 13.0 10.0 11 37.0 10</span>
<span class="co"># as.mo("S. aureus") 10.0 12.0 23.0 13.0 39 41.0 10</span>
<span class="co"># as.mo("S aureus") 9.4 10.0 11.0 11.0 12 12.0 10</span>
<span class="co"># as.mo("Staphylococcus aureus") 7.5 7.5 8.3 8.4 9 9.3 10</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 890.0 930.0 940.0 940.0 950 980.0 10</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 370.0 390.0 420.0 400.0 440 510.0 10</span>
<span class="co"># as.mo("MRSA") 8.0 8.9 15.0 10.0 11 39.0 10</span>
<span class="co"># as.mo("VISA") 20.0 21.0 36.0 25.0 53 60.0 10</span>
<span class="co"># as.mo("VRSA") 19.0 22.0 29.0 24.0 26 53.0 10</span>
<span class="co"># as.mo(22242419) 150.0 150.0 170.0 150.0 160 290.0 10</span></pre></body></html></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="562.5"></p>
<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.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside of this is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
@ -263,17 +248,17 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">M.semesiae</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq</span>
<span class="co"># as.mo("metsem") 146.500 150.900 173.300 183.300 191.800</span>
<span class="co"># as.mo("METSEM") 145.700 153.400 169.300 172.300 185.300</span>
<span class="co"># as.mo("M. semesiae") 8.586 8.790 9.909 10.140 10.250</span>
<span class="co"># as.mo("M. semesiae") 8.613 8.719 12.350 9.756 10.210</span>
<span class="co"># as.mo("Methanosarcina semesiae") 6.153 6.357 9.325 6.729 7.826</span>
<span class="co"># max neval</span>
<span class="co"># 193.60 10</span>
<span class="co"># 187.40 10</span>
<span class="co"># 12.52 10</span>
<span class="co"># 38.46 10</span>
<span class="co"># 31.48 10</span></pre></body></html></div>
<span class="co"># as.mo("metsem") 163.900 165.300 180.600 176.600 192.600</span>
<span class="co"># as.mo("METSEM") 153.500 156.100 177.300 176.000 200.400</span>
<span class="co"># as.mo("M. semesiae") 9.155 10.250 15.980 10.800 12.790</span>
<span class="co"># as.mo("M. semesiae") 9.498 10.160 16.700 10.560 11.050</span>
<span class="co"># as.mo("Methanosarcina semesiae") 7.006 7.345 7.993 7.814 8.413</span>
<span class="co"># max neval</span>
<span class="co"># 206.600 10</span>
<span class="co"># 206.800 10</span>
<span class="co"># 38.630 10</span>
<span class="co"># 46.810 10</span>
<span class="co"># 9.659 10</span></pre></body></html></div>
<p>Looking up arbitrary codes of less prevalent microorganisms costs the most time. Full names (like <em>Methanosarcina semesiae</em>) are always very fast and only take some thousands of seconds to coerce - they 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>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-6-1.png" width="900"></p>
@ -308,8 +293,8 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 1660 1700 1760 1750 1810 1910 10</span></pre></body></html></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.75 seconds. You only lose time on your unique input values.</p>
<span class="co"># mo_name(x) 1690 1710 1770 1760 1810 1870 10</span></pre></body></html></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.76 seconds. You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -321,10 +306,10 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 5.650 6.030 6.36 6.430 6.660 7.130 10</span>
<span class="co"># B 9.860 9.890 14.20 10.900 11.200 46.300 10</span>
<span class="co"># C 0.232 0.237 0.30 0.302 0.355 0.369 10</span></pre></body></html></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 6.240 6.490 6.860 6.910 7.15 7.510 10</span>
<span class="co"># B 10.500 10.600 15.300 12.000 12.10 49.300 10</span>
<span class="co"># C 0.198 0.243 0.266 0.278 0.29 0.322 10</span></pre></body></html></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0003 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"><html><body><pre class="r"><span class="no">run_it</span> <span class="kw">&lt;-</span> <span class="fu">microbenchmark</span>(<span class="kw">A</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),
<span class="kw">B</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),
@ -338,14 +323,14 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 0.209 0.214 0.229 0.221 0.229 0.299 10</span>
<span class="co"># B 0.199 0.206 0.225 0.209 0.214 0.373 10</span>
<span class="co"># C 0.201 0.207 0.217 0.213 0.222 0.247 10</span>
<span class="co"># D 0.200 0.203 0.214 0.206 0.222 0.266 10</span>
<span class="co"># E 0.200 0.200 0.213 0.209 0.216 0.264 10</span>
<span class="co"># F 0.195 0.205 0.216 0.207 0.217 0.284 10</span>
<span class="co"># G 0.191 0.194 0.206 0.203 0.206 0.261 10</span>
<span class="co"># H 0.190 0.195 0.205 0.198 0.209 0.256 10</span></pre></body></html></div>
<span class="co"># A 0.248 0.253 0.266 0.256 0.271 0.323 10</span>
<span class="co"># B 0.248 0.254 0.272 0.255 0.257 0.420 10</span>
<span class="co"># C 0.245 0.259 0.265 0.268 0.271 0.286 10</span>
<span class="co"># D 0.248 0.252 0.268 0.261 0.278 0.323 10</span>
<span class="co"># E 0.250 0.256 0.265 0.261 0.268 0.312 10</span>
<span class="co"># F 0.237 0.238 0.249 0.243 0.246 0.317 10</span>
<span class="co"># G 0.239 0.242 0.252 0.245 0.245 0.319 10</span>
<span class="co"># H 0.233 0.241 0.262 0.256 0.272 0.347 10</span></pre></body></html></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> anyway, 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">
@ -372,13 +357,13 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 20.58 21.00 24.57 21.31 21.81 65.96 100</span>
<span class="co"># de 21.28 21.81 25.34 22.15 22.73 62.52 100</span>
<span class="co"># nl 25.15 25.68 32.14 26.03 27.25 167.40 100</span>
<span class="co"># es 21.35 21.78 27.39 22.14 23.29 67.97 100</span>
<span class="co"># it 21.42 21.83 26.19 22.31 22.84 71.71 100</span>
<span class="co"># fr 21.43 21.82 27.43 22.25 23.39 69.29 100</span>
<span class="co"># pt 21.42 21.92 28.71 22.23 22.89 187.40 100</span></pre></body></html></div>
<span class="co"># en 20.99 21.59 26.64 22.35 22.94 69.49 100</span>
<span class="co"># de 22.02 22.54 26.83 22.98 23.87 63.13 100</span>
<span class="co"># nl 25.78 26.55 34.69 27.25 28.22 182.90 100</span>
<span class="co"># es 21.92 22.67 26.97 23.26 24.01 62.68 100</span>
<span class="co"># it 21.96 22.58 25.11 22.90 23.50 66.81 100</span>
<span class="co"># fr 21.82 22.76 27.53 23.26 23.84 66.75 100</span>
<span class="co"># pt 21.76 22.56 25.84 23.13 23.90 63.63 100</span></pre></body></html></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>