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(v1.8.1) prerelease 1.8.1

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@ -44,7 +44,7 @@
</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="Released version">1.8.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span>
</div>
@ -198,14 +198,30 @@
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
<p>One of the most important features of this package is the complete
microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and
the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with
Standing in Nomenclature</a> (LPSN). We created a function
<code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid
microbial ID by using intelligent rules combined with the microbial
taxonomy.</p>
<p>Using the <code>microbenchmark</code> package, we can review the
calculation performance of this function. Its function
<code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions
independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/" class="external-link">microbenchmark</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></code></pre></div>
<p>In the next test, we try to coerce different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p>
<p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p>
<p>In the next test, we try to coerce different input values into the
microbial code of <em>Staphylococcus aureus</em>. Coercion is a
computational process of forcing output based on an input. For
microorganism names, coercing user input to taxonomically valid
microorganism names is crucial to ensure correct interpretation and to
enable grouping based on taxonomic properties.</p>
<p>The actual result is the same every time: it returns its
microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for
<em>Bacteria</em>, its taxonomic kingdom).</p>
<p>But the calculation time differs a lot:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>
@ -224,27 +240,40 @@
times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 10.0 12.0 20.0 12.0 15.0 53 25</span>
<span class="co"># as.mo("stau") 49.0 54.0 72.0 58.0 91.0 97 25</span>
<span class="co"># as.mo("STAU") 50.0 54.0 71.0 57.0 90.0 110 25</span>
<span class="co"># as.mo("staaur") 10.0 12.0 17.0 12.0 14.0 51 25</span>
<span class="co"># as.mo("STAAUR") 10.0 12.0 17.0 12.0 14.0 54 25</span>
<span class="co"># as.mo("S. aureus") 26.0 27.0 40.0 31.0 56.0 74 25</span>
<span class="co"># as.mo("S aureus") 26.0 27.0 39.0 29.0 58.0 68 25</span>
<span class="co"># as.mo("Staphylococcus aureus") 3.5 3.9 6.6 4.1 4.8 38 25</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 230.0 240.0 250.0 240.0 250.0 280 25</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 180.0 190.0 200.0 190.0 200.0 290 25</span>
<span class="co"># as.mo("MRSA") 11.0 12.0 19.0 13.0 14.0 50 25</span>
<span class="co"># as.mo("VISA") 21.0 22.0 32.0 25.0 50.0 60 25</span></code></pre></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 12.0 13 18.0 14.0 15.0 48 25</span>
<span class="co"># as.mo("stau") 54.0 59 80.0 91.0 96.0 99 25</span>
<span class="co"># as.mo("STAU") 53.0 61 77.0 66.0 94.0 100 25</span>
<span class="co"># as.mo("staaur") 12.0 13 19.0 14.0 16.0 62 25</span>
<span class="co"># as.mo("STAAUR") 12.0 13 16.0 14.0 15.0 48 25</span>
<span class="co"># as.mo("S. aureus") 28.0 30 38.0 33.0 35.0 69 25</span>
<span class="co"># as.mo("S aureus") 27.0 31 46.0 34.0 65.0 73 25</span>
<span class="co"># as.mo("Staphylococcus aureus") 3.7 4 6.7 4.3 4.5 36 25</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 260.0 270 290.0 280.0 290.0 360 25</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 190.0 210 220.0 210.0 220.0 330 25</span>
<span class="co"># as.mo("MRSA") 12.0 13 20.0 14.0 16.0 68 25</span>
<span class="co"># as.mo("VISA") 22.0 23 32.0 25.0 27.0 63 25</span></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></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 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 47 times slower to determine.</p>
<p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</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 200 milliseconds, this is only 5
input values per second. It is clear that accepted taxonomic names are
extremely fast, but some variations are up to 67 times slower to
determine.</p>
<p>To improve performance, we implemented two important algorithms to
save unnecessary calculations: <strong>repetitive results</strong> and
<strong>already precalculated results</strong>.</p>
<div class="section level3">
<h3 id="repetitive-results">Repetitive results<a class="anchor" aria-label="anchor" href="#repetitive-results"></a>
</h3>
<p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code>as.mo(c("E. coli", "E. coli"))</code> will check the value <code>"E. coli"</code> only once.</p>
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<p>Repetitive results are values that are present more than once in a
vector. Unique values will only be calculated once by
<code><a href="../reference/as.mo.html">as.mo()</a></code>. So running
<code>as.mo(c("E. coli", "E. coli"))</code> will check the value
<code>"E. coli"</code> only once.</p>
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a
helper function that returns the full microbial name (genus, species and
possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
@ -258,8 +287,8 @@
<span class="co"># what do these values look like? They are of class &lt;mo&gt;:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
<span class="co"># Class &lt;mo&gt;</span>
<span class="co"># [1] B_STPHY_AURS B_STRPT_EQNS B_KLBSL_PNMN B_STPHY_EPDR B_STPHY_AURS</span>
<span class="co"># [6] B_CRYNB_STRT</span>
<span class="co"># [1] B_ESCHR_COLI B_STRPT_MITS B_STRPT_ANGN B_STPHY_CONS B_ESCHR_COLI</span>
<span class="co"># [6] B_ESCHR_COLI</span>
<span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
<span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@ -275,13 +304,20 @@
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</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) 196 209 274 223 364 388 10</span></code></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.223 seconds. That is 112 nanoseconds on average. You only lose time on your unique input values.</p>
<span class="co"># mo_name(x) 207 225 288 233 370 414 10</span></code></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items
consisting of 90 unique values only takes 0.233 seconds. That is 117
nanoseconds on average. You only lose time on your unique input
values.</p>
</div>
<div class="section level3">
<h3 id="precalculated-results">Precalculated results<a class="anchor" aria-label="anchor" href="#precalculated-results"></a>
</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesnt take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see C below):</p>
<p>What about precalculated results? If the input is an already
precalculated result of a helper function such as
<code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesnt take any time at all. In other
words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it
will return the results immediately (see C below):</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
@ -289,11 +325,14 @@
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 8.00 9.16 9.19 9.28 9.46 9.73 10</span>
<span class="co"># B 23.40 27.20 32.60 27.90 28.10 80.20 10</span>
<span class="co"># C 1.85 2.25 2.40 2.47 2.62 2.90 10</span></code></pre></div>
<p>So going from <code>mo_name("Staphylococcus aureus")</code> to <code>"Staphylococcus aureus"</code> takes 0.0025 seconds - it doesnt even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 10.3 10.90 11.20 11.10 11.20 12.40 10</span>
<span class="co"># B 31.3 32.70 38.20 33.90 35.20 79.80 10</span>
<span class="co"># C 2.5 2.64 2.79 2.78 2.85 3.13 10</span></code></pre></div>
<p>So going from <code>mo_name("Staphylococcus aureus")</code> to
<code>"Staphylococcus aureus"</code> takes 0.0028 seconds - it doesnt
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="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
@ -307,20 +346,28 @@
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 1.76 1.80 2.07 1.95 2.26 2.90 10</span>
<span class="co"># B 1.69 1.73 1.90 1.81 2.03 2.48 10</span>
<span class="co"># C 1.71 1.77 1.92 1.91 2.05 2.17 10</span>
<span class="co"># D 1.68 1.71 1.76 1.76 1.82 1.88 10</span>
<span class="co"># E 1.68 1.70 1.89 1.89 2.04 2.26 10</span>
<span class="co"># F 1.67 1.75 1.93 1.89 2.11 2.35 10</span>
<span class="co"># G 1.70 1.76 1.97 1.88 2.12 2.43 10</span>
<span class="co"># H 1.67 1.71 1.83 1.75 1.98 2.14 10</span></code></pre></div>
<p>Of course, when running <code>mo_phylum("Firmicutes")</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 contains all phyla of all known bacteria, it can just return the initial value immediately.</p>
<span class="co"># A 2.30 2.55 2.68 2.66 2.85 2.94 10</span>
<span class="co"># B 2.27 2.38 2.59 2.56 2.83 2.88 10</span>
<span class="co"># C 2.22 2.25 2.51 2.47 2.74 2.87 10</span>
<span class="co"># D 2.21 2.40 2.68 2.73 2.94 3.08 10</span>
<span class="co"># E 2.22 2.28 2.46 2.45 2.56 2.81 10</span>
<span class="co"># F 2.19 2.34 2.52 2.48 2.71 3.04 10</span>
<span class="co"># G 2.23 2.40 2.52 2.46 2.62 2.88 10</span>
<span class="co"># H 2.13 2.25 2.42 2.47 2.50 2.77 10</span></code></pre></div>
<p>Of course, when running <code>mo_phylum("Firmicutes")</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 contains all phyla of all known
bacteria, it can just return the initial value immediately.</p>
</div>
<div class="section level3">
<h3 id="results-in-other-languages">Results in other languages<a class="anchor" aria-label="anchor" href="#results-in-other-languages"></a>
</h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost doest take extra time (compare “en” from the table below with the other languages):</p>
<p>When the system language is non-English and supported by this
<code>AMR</code> package, some functions will have a translated result.
This almost doest take extra time (compare “en” from the table below
with the other languages):</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">CoNS</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"CoNS"</span><span class="op">)</span>
<span class="va">CoNS</span>
@ -349,18 +396,19 @@
times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># da 1.9470 2.0220 2.190 2.0720 2.358 3.234 100</span>
<span class="co"># de 1.9560 2.0330 3.649 2.1610 2.401 50.670 100</span>
<span class="co"># en 0.8937 0.9124 1.022 0.9776 1.120 1.748 100</span>
<span class="co"># es 1.9710 2.0290 2.216 2.1000 2.391 3.109 100</span>
<span class="co"># fr 1.8280 1.8960 3.214 1.9420 2.237 71.550 100</span>
<span class="co"># it 1.9370 1.9970 2.163 2.0610 2.339 3.210 100</span>
<span class="co"># nl 1.9710 2.0280 2.698 2.1110 2.421 49.340 100</span>
<span class="co"># pt 1.8920 1.9600 2.119 2.0200 2.261 3.265 100</span>
<span class="co"># ru 1.8630 1.9420 2.779 2.0270 2.335 66.660 100</span>
<span class="co"># sv 1.8680 1.9190 4.062 1.9890 2.263 78.870 100</span></code></pre></div>
<p>Currently supported languages are Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish.</p>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># da 2.1730 2.476 3.956 2.609 2.873 45.180 100</span>
<span class="co"># de 2.2170 2.497 3.161 2.646 2.855 48.260 100</span>
<span class="co"># en 0.9509 1.122 1.640 1.183 1.321 38.430 100</span>
<span class="co"># es 2.1870 2.546 2.763 2.659 2.872 5.676 100</span>
<span class="co"># fr 1.9880 2.339 2.609 2.456 2.636 5.197 100</span>
<span class="co"># it 2.2580 2.475 4.081 2.619 2.867 47.080 100</span>
<span class="co"># nl 2.3120 2.535 2.792 2.664 2.822 8.113 100</span>
<span class="co"># pt 2.1930 2.417 3.329 2.528 2.783 48.600 100</span>
<span class="co"># ru 2.0470 2.360 2.596 2.481 2.683 6.030 100</span>
<span class="co"># sv 2.2030 2.443 3.077 2.545 2.703 43.350 100</span></code></pre></div>
<p>Currently supported languages are Danish, Dutch, English, French,
German, Italian, Portuguese, Russian, Spanish and Swedish.</p>
</div>
</div>
@ -374,12 +422,14 @@
<footer><div class="copyright">
<p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div>
<div class="pkgdown">
<p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p>
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