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global var fix

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dr. M.S. (Matthijs) Berends 2019-02-27 19:02:47 +01:00
parent 95c49fdf79
commit cf3bdb54c7
10 changed files with 270 additions and 267 deletions
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1
R/globals.R
View File

@ -47,6 +47,7 @@ globalVariables(c(".",
"gramstain",
"index",
"Interpretation",
"input",
"item",
"key_ab",
"key_ab_lag",

28
R/mo.R
View File

@ -474,49 +474,49 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE,
x[i] <- microorganismsDT[mo == 'B_STRPT_PNE', ..property][[1]][1L]
next
}
if (toupper(x_trimmed[i]) %like% '^G[ABCDFGHK]S$') {
if (x_trimmed[i] %like% '^G[ABCDFGHK]S$') {
# Streptococci, like GBS = Group B Streptococci (B_STRPT_GRB)
x[i] <- microorganismsDT[mo == gsub("G([ABCDFGHK])S", "B_STRPT_GR\\1", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L]
next
}
if (toupper(x_trimmed[i]) %like% '(streptococc|streptokok).* [ABCDFGHK]$') {
if (x_trimmed[i] %like% '(streptococ|streptokok).* [ABCDFGHK]$') {
# Streptococci in different languages, like "estreptococos grupo B"
x[i] <- microorganismsDT[mo == gsub(".*(streptococ|streptokok|estreptococ).* ([ABCDFGHK])$", "B_STRPT_GR\\2", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L]
next
}
if (toupper(x_trimmed[i]) %like% 'group [ABCDFGHK] (streptococ|streptokok|estreptococ)') {
if (x_trimmed[i] %like% 'group [ABCDFGHK] (streptococ|streptokok|estreptococ)') {
# Streptococci in different languages, like "Group A Streptococci"
x[i] <- microorganismsDT[mo == gsub(".*group ([ABCDFGHK]) (streptococ|streptokok|estreptococ).*", "B_STRPT_GR\\1", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L]
next
}
# CoNS/CoPS in different languages (support for German, Dutch, Spanish, Portuguese) ----
if (tolower(x[i]) %like% '[ck]oagulas[ea] negatie?[vf]'
| tolower(x_trimmed[i]) %like% '[ck]oagulas[ea] negatie?[vf]'
| tolower(x[i]) %like% '[ck]o?ns[^a-z]?$') {
if (x[i] %like% '[ck]oagulas[ea] negatie?[vf]'
| x_trimmed[i] %like% '[ck]oagulas[ea] negatie?[vf]'
| x[i] %like% '[ck]o?ns[^a-z]?$') {
# coerce S. coagulase negative
x[i] <- microorganismsDT[mo == 'B_STPHY_CNS', ..property][[1]][1L]
next
}
if (tolower(x[i]) %like% '[ck]oagulas[ea] positie?[vf]'
| tolower(x_trimmed[i]) %like% '[ck]oagulas[ea] positie?[vf]'
| tolower(x[i]) %like% '[ck]o?ps[^a-z]?$') {
if (x[i] %like% '[ck]oagulas[ea] positie?[vf]'
| x_trimmed[i] %like% '[ck]oagulas[ea] positie?[vf]'
| x[i] %like% '[ck]o?ps[^a-z]?$') {
# coerce S. coagulase positive
x[i] <- microorganismsDT[mo == 'B_STPHY_CPS', ..property][[1]][1L]
next
}
if (tolower(x[i]) %like% 'gram[ -]?neg.*'
| tolower(x_trimmed[i]) %like% 'gram[ -]?neg.*') {
if (x[i] %like% 'gram[ -]?neg.*'
| x_trimmed[i] %like% 'gram[ -]?neg.*') {
# coerce S. coagulase positive
x[i] <- microorganismsDT[mo == 'B_GRAMN', ..property][[1]][1L]
next
}
if (tolower(x[i]) %like% 'gram[ -]?pos.*'
| tolower(x_trimmed[i]) %like% 'gram[ -]?pos.*') {
if (x[i] %like% 'gram[ -]?pos.*'
| x_trimmed[i] %like% 'gram[ -]?pos.*') {
# coerce S. coagulase positive
x[i] <- microorganismsDT[mo == 'B_GRAMP', ..property][[1]][1L]
next
}
if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_trimmed[i])) {
if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_trimmed[i], ignore.case = FALSE)) {
if (x_trimmed[i] %like% "Salmonella group") {
# Salmonella Group A to Z, just return S. species for now
x[i] <- microorganismsDT[mo == 'B_SLMNL', ..property][[1]][1L]

438
docs/articles/AMR.html
View File

@ -327,69 +327,69 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2011-09-11</td>
<td align="center">K7</td>
<td align="center">2012-02-27</td>
<td align="center">B4</td>
<td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2017-06-12</td>
<td align="center">M3</td>
<td align="center">Hospital C</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">2014-02-11</td>
<td align="center">T4</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2015-04-14</td>
<td align="center">N3</td>
<td align="center">Hospital B</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2015-03-15</td>
<td align="center">S9</td>
<tr class="even">
<td align="center">2017-03-09</td>
<td align="center">D1</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2013-10-22</td>
<td align="center">W9</td>
<td align="center">Hospital B</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2012-08-12</td>
<td align="center">C10</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2016-01-03</td>
<td align="center">I7</td>
<td align="center">Hospital C</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2017-11-25</td>
<td align="center">R3</td>
<td align="center">Hospital D</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2012-04-03</td>
<td align="center">B9</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
</tbody>
@ -411,8 +411,8 @@
#&gt;
#&gt; Item Count Percent Cum. Count Cum. Percent
#&gt; --- ----- ------- -------- ----------- -------------
#&gt; 1 M 10,472 52.4% 10,472 52.4%
#&gt; 2 F 9,528 47.6% 20,000 100.0%</code></pre>
#&gt; 1 M 10,333 51.7% 10,333 51.7%
#&gt; 2 F 9,667 48.3% 20,000 100.0%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researcher perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" title="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -443,10 +443,10 @@
<a class="sourceLine" id="cb14-19" title="19"><span class="co">#&gt; Kingella kingae (no changes)</span></a>
<a class="sourceLine" id="cb14-20" title="20"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb14-21" title="21"><span class="co">#&gt; EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-22" title="22"><span class="co">#&gt; Table 1: Intrinsic resistance in Enterobacteriaceae (1252 changes)</span></a>
<a class="sourceLine" id="cb14-22" title="22"><span class="co">#&gt; Table 1: Intrinsic resistance in Enterobacteriaceae (1264 changes)</span></a>
<a class="sourceLine" id="cb14-23" title="23"><span class="co">#&gt; Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-24" title="24"><span class="co">#&gt; Table 3: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co">#&gt; Table 4: Intrinsic resistance in Gram-positive bacteria (2741 changes)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co">#&gt; Table 4: Intrinsic resistance in Gram-positive bacteria (2835 changes)</span></a>
<a class="sourceLine" id="cb14-26" title="26"><span class="co">#&gt; Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-27" title="27"><span class="co">#&gt; Table 9: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-28" title="28"><span class="co">#&gt; Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria (no changes)</span></a>
@ -462,9 +462,9 @@
<a class="sourceLine" id="cb14-38" title="38"><span class="co">#&gt; Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-39" title="39"><span class="co">#&gt; Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb14-40" title="40"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb14-41" title="41"><span class="co">#&gt; =&gt; EUCAST rules affected 7,388 out of 20,000 rows</span></a>
<a class="sourceLine" id="cb14-41" title="41"><span class="co">#&gt; =&gt; EUCAST rules affected 7,417 out of 20,000 rows</span></a>
<a class="sourceLine" id="cb14-42" title="42"><span class="co">#&gt; -&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-43" title="43"><span class="co">#&gt; -&gt; changed 3,993 test results (0 to S; 0 to I; 3,993 to R)</span></a></code></pre></div>
<a class="sourceLine" id="cb14-43" title="43"><span class="co">#&gt; -&gt; changed 4,099 test results (0 to S; 0 to I; 4,099 to R)</span></a></code></pre></div>
</div>
<div id="adding-new-variables" class="section level1">
<h1 class="hasAnchor">
@ -489,8 +489,8 @@
<a class="sourceLine" id="cb16-3" title="3"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" title="4"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" title="5"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" title="6"><span class="co">#&gt; =&gt; Found 5,651 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb16-6" title="6"><span class="co">#&gt; =&gt; Found 5,647 first isolates (28.2% of total)</span></a></code></pre></div>
<p>So only 28.2% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@ -516,30 +516,30 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-02-18</td>
<td align="center">U6</td>
<td align="center">2010-01-07</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-16</td>
<td align="center">U6</td>
<td align="center">2010-01-14</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-10</td>
<td align="center">U6</td>
<td align="center">2010-02-07</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -549,10 +549,10 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-07-20</td>
<td align="center">U6</td>
<td align="center">2010-03-28</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -560,43 +560,43 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-07-24</td>
<td align="center">U6</td>
<td align="center">2010-05-25</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">U6</td>
<td align="center">2010-07-23</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-14</td>
<td align="center">U6</td>
<td align="center">2010-08-18</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2010-12-31</td>
<td align="center">U6</td>
<td align="center">2010-11-19</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -604,29 +604,29 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-02-02</td>
<td align="center">U6</td>
<td align="center">2010-12-05</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-02-16</td>
<td align="center">U6</td>
<td align="center">2011-02-04</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Only 1 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>If a column exists with a name like ‘key(…)ab’ the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" title="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -637,7 +637,7 @@
<a class="sourceLine" id="cb19-7" title="7"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" title="8"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" title="9"><span class="co">#&gt; [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
<a class="sourceLine" id="cb19-10" title="10"><span class="co">#&gt; =&gt; Found 15,906 first weighted isolates (79.5% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" title="10"><span class="co">#&gt; =&gt; Found 15,867 first weighted isolates (79.3% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -654,11 +654,11 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-02-18</td>
<td align="center">U6</td>
<td align="center">2010-01-07</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
@ -666,20 +666,20 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-16</td>
<td align="center">U6</td>
<td align="center">2010-01-14</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-10</td>
<td align="center">U6</td>
<td align="center">2010-02-07</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -690,10 +690,10 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-07-20</td>
<td align="center">U6</td>
<td align="center">2010-03-28</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -702,46 +702,46 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-07-24</td>
<td align="center">U6</td>
<td align="center">2010-05-25</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">U6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-07-23</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-14</td>
<td align="center">U6</td>
<td align="center">2010-08-18</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2010-12-31</td>
<td align="center">U6</td>
<td align="center">2010-11-19</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -750,35 +750,35 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-02-02</td>
<td align="center">U6</td>
<td align="center">2010-12-05</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-02-16</td>
<td align="center">U6</td>
<td align="center">2011-02-04</td>
<td align="center">E5</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 1, now 8 isolates are flagged. In total, 79.5% of all isolates are marked ‘first weighted’ - 51.3% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 7 isolates are flagged. In total, 79.3% of all isolates are marked ‘first weighted’ - 51.1% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" title="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,906 isolates for analysis.</p>
<p>So we end up with 15,867 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" title="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div>
@ -803,29 +803,29 @@
</tr></thead>
<tbody>
<tr class="odd">
<td>1</td>
<td align="center">2011-09-11</td>
<td align="center">K7</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">S</td>
<td>2</td>
<td align="center">2014-02-11</td>
<td align="center">T4</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">F</td>
<td align="center">Gram negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>2</td>
<td align="center">2017-06-12</td>
<td align="center">M3</td>
<td align="center">Hospital C</td>
<td>3</td>
<td align="center">2015-04-14</td>
<td align="center">N3</td>
<td align="center">Hospital B</td>
<td align="center">B_KLBSL_PNE</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
@ -835,32 +835,32 @@
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>3</td>
<td align="center">2015-03-15</td>
<td align="center">S9</td>
<td>4</td>
<td align="center">2017-03-09</td>
<td align="center">D1</td>
<td align="center">Hospital A</td>
<td align="center">B_STRPT_PNE</td>
<td align="center">S</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>4</td>
<td align="center">2016-01-03</td>
<td align="center">I7</td>
<td align="center">Hospital C</td>
<td>5</td>
<td align="center">2013-10-22</td>
<td align="center">W9</td>
<td align="center">Hospital B</td>
<td align="center">B_KLBSL_PNE</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram negative</td>
<td align="center">Klebsiella</td>
<td align="center">pneumoniae</td>
@ -868,31 +868,31 @@
</tr>
<tr class="odd">
<td>6</td>
<td align="center">2012-04-03</td>
<td align="center">B9</td>
<td align="center">2012-08-12</td>
<td align="center">C10</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">B_STRPT_PNE</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>8</td>
<td align="center">2012-12-23</td>
<td align="center">D1</td>
<td align="center">Hospital C</td>
<td>7</td>
<td align="center">2012-05-06</td>
<td align="center">V7</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">F</td>
<td align="center">Gram negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
@ -915,9 +915,9 @@
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" title="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(data_1st<span class="op">$</span>genus, data_1st<span class="op">$</span>species))</a></code></pre></div>
<p>Or can be used like the <code>dplyr</code> way, which is easier readable:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (15,906 x 13)</strong></p>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (15,867 x 13)</strong></p>
<p>Columns: 2<br>
Length: 15,906 (of which NA: 0 = 0.00%)<br>
Length: 15,867 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -934,33 +934,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,989</td>
<td align="right">50.2%</td>
<td align="right">7,989</td>
<td align="right">50.2%</td>
<td align="right">7,816</td>
<td align="right">49.3%</td>
<td align="right">7,816</td>
<td align="right">49.3%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,924</td>
<td align="right">24.7%</td>
<td align="right">11,913</td>
<td align="right">74.9%</td>
<td align="right">4,004</td>
<td align="right">25.2%</td>
<td align="right">11,820</td>
<td align="right">74.5%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,476</td>
<td align="right">15.6%</td>
<td align="right">14,389</td>
<td align="right">90.5%</td>
<td align="right">2,496</td>
<td align="right">15.7%</td>
<td align="right">14,316</td>
<td align="right">90.2%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,517</td>
<td align="right">9.5%</td>
<td align="right">15,906</td>
<td align="right">1,551</td>
<td align="right">9.8%</td>
<td align="right">15,867</td>
<td align="right">100.0%</td>
</tr>
</tbody>
@ -971,7 +971,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code>portion_R</code>, <code>portion_RI</code>, <code>portion_I</code>, <code>portion_IS</code> and <code>portion_S</code> can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox)</a>
<a class="sourceLine" id="cb25-2" title="2"><span class="co">#&gt; [1] 0.4769269</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" title="2"><span class="co">#&gt; [1] 0.4757673</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -984,19 +984,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4828164</td>
<td align="center">0.4797111</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4792111</td>
<td align="center">0.4868636</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4738384</td>
<td align="center">0.4661747</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4661534</td>
<td align="center">0.4581512</td>
</tr>
</tbody>
</table>
@ -1014,23 +1014,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4828164</td>
<td align="center">4772</td>
<td align="center">0.4797111</td>
<td align="center">4707</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4792111</td>
<td align="center">5628</td>
<td align="center">0.4868636</td>
<td align="center">5519</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4738384</td>
<td align="center">2389</td>
<td align="center">0.4661747</td>
<td align="center">2439</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4661534</td>
<td align="center">3117</td>
<td align="center">0.4581512</td>
<td align="center">3202</td>
</tr>
</tbody>
</table>
@ -1050,27 +1050,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.7335086</td>
<td align="center">0.9034923</td>
<td align="center">0.9759670</td>
<td align="center">0.7345189</td>
<td align="center">0.8976459</td>
<td align="center">0.9721085</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.7303889</td>
<td align="center">0.8998022</td>
<td align="center">0.9709954</td>
<td align="center">0.7433914</td>
<td align="center">0.8949065</td>
<td align="center">0.9767892</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.7303772</td>
<td align="center">0.9161570</td>
<td align="center">0.9775739</td>
<td align="center">0.7285215</td>
<td align="center">0.9153347</td>
<td align="center">0.9787712</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.7302100</td>
<td align="center">0.7315705</td>
<td align="center">0.0000000</td>
<td align="center">0.7302100</td>
<td align="center">0.7315705</td>
</tr>
</tbody>
</table>

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@ -218,13 +218,13 @@
<a class="sourceLine" id="cb2-9" title="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">3</span>)</a>
<a class="sourceLine" id="cb2-10" title="10"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-11" title="11"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" title="12"><span class="co">#&gt; as.mo("sau") 16.30 16.30 21.40 16.6 17.80 59.0 10</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co">#&gt; as.mo("stau") 33.20 33.20 37.10 33.3 33.40 71.7 10</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co">#&gt; as.mo("staaur") 16.40 16.60 29.50 17.5 50.10 69.3 10</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co">#&gt; as.mo("STAAUR") 16.30 16.40 19.70 16.5 16.70 49.0 10</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co">#&gt; as.mo("S. aureus") 24.30 24.40 33.00 25.0 26.50 65.5 10</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co">#&gt; as.mo("S. aureus") 24.30 24.30 35.60 24.8 28.50 91.0 10</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co">#&gt; as.mo("Staphylococcus aureus") 7.31 7.38 9.12 7.4 7.93 21.3 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-12" title="12"><span class="co">#&gt; as.mo("sau") 16.70 16.80 21.50 16.8 17.50 56.6 10</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co">#&gt; as.mo("stau") 33.70 34.00 46.60 40.2 50.50 83.7 10</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co">#&gt; as.mo("staaur") 16.70 16.80 28.60 17.3 41.90 59.7 10</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co">#&gt; as.mo("STAAUR") 16.60 16.70 21.90 17.1 20.00 56.6 10</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co">#&gt; as.mo("S. aureus") 24.50 24.90 25.40 25.2 26.10 26.7 10</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co">#&gt; as.mo("S. aureus") 24.60 25.00 31.30 25.1 25.30 85.1 10</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co">#&gt; as.mo("Staphylococcus aureus") 7.37 7.42 8.17 7.5 8.27 11.8 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" title="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>
@ -236,12 +236,12 @@
<a class="sourceLine" id="cb3-7" title="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">3</span>)</a>
<a class="sourceLine" id="cb3-8" title="8"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" title="9"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co">#&gt; as.mo("theisl") 288.0 289.0 317.0 328.0 329.0 335 10</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co">#&gt; as.mo("THEISL") 288.0 288.0 307.0 290.0 334.0 338 10</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co">#&gt; as.mo("T. islandicus") 73.0 73.3 82.6 73.4 73.9 126 10</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co">#&gt; as.mo("T. islandicus") 72.8 72.9 81.9 73.6 74.8 118 10</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co">#&gt; as.mo("Thermus islandicus") 65.2 65.7 83.1 65.9 109.0 114 10</span></a></code></pre></div>
<p>That takes 6.6 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" title="10"><span class="co">#&gt; as.mo("theisl") 289.0 291.0 314.0 312.0 336.0 343 10</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co">#&gt; as.mo("THEISL") 290.0 293.0 319.0 331.0 337.0 344 10</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co">#&gt; as.mo("T. islandicus") 73.5 73.8 90.6 75.1 114.0 118 10</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co">#&gt; as.mo("T. islandicus") 73.7 73.9 78.5 74.6 74.7 115 10</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co">#&gt; as.mo("Thermus islandicus") 66.5 67.3 80.3 69.5 107.0 108 10</span></a></code></pre></div>
<p>That takes 6.7 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" title="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" title="2"></a>
@ -287,8 +287,8 @@
<a class="sourceLine" id="cb5-24" title="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" title="25"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-26" title="26"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-27" title="27"><span class="co">#&gt; mo_fullname(x) 722 753 797 798 804 918 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.8 seconds (798 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb5-27" title="27"><span class="co">#&gt; mo_fullname(x) 732 768 800 794 799 949 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.79 seconds (793 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -300,10 +300,10 @@
<a class="sourceLine" id="cb6-4" title="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb6-5" title="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" title="6"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-7" title="7"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co">#&gt; A 11.20 11.300 15.800 11.500 11.500 51.000 10</span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co">#&gt; B 22.10 22.200 22.400 22.500 22.600 22.800 10</span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co">#&gt; C 0.31 0.315 0.461 0.548 0.567 0.567 10</span></a></code></pre></div>
<a class="sourceLine" id="cb6-7" title="7"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co">#&gt; A 10.900 11.300 11.900 11.500 11.700 15.200 10</span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co">#&gt; B 22.000 22.600 26.900 22.600 22.800 62.400 10</span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co">#&gt; C 0.311 0.502 0.531 0.533 0.577 0.765 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_fullname("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0005 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" title="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" title="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>
@ -317,14 +317,14 @@
<a class="sourceLine" id="cb7-10" title="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" title="11"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-12" title="12"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-13" title="13"><span class="co">#&gt; A 0.335 0.360 0.393 0.372 0.442 0.461 10</span></a>
<a class="sourceLine" id="cb7-14" title="14"><span class="co">#&gt; B 0.370 0.394 0.431 0.427 0.455 0.562 10</span></a>
<a class="sourceLine" id="cb7-15" title="15"><span class="co">#&gt; C 0.353 0.401 0.498 0.494 0.581 0.653 10</span></a>
<a class="sourceLine" id="cb7-16" title="16"><span class="co">#&gt; D 0.278 0.290 0.334 0.328 0.376 0.415 10</span></a>
<a class="sourceLine" id="cb7-17" title="17"><span class="co">#&gt; E 0.214 0.262 0.303 0.314 0.352 0.364 10</span></a>
<a class="sourceLine" id="cb7-18" title="18"><span class="co">#&gt; F 0.240 0.273 0.307 0.312 0.345 0.366 10</span></a>
<a class="sourceLine" id="cb7-19" title="19"><span class="co">#&gt; G 0.246 0.270 0.318 0.299 0.357 0.474 10</span></a>
<a class="sourceLine" id="cb7-20" title="20"><span class="co">#&gt; H 0.245 0.267 0.301 0.291 0.341 0.367 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-13" title="13"><span class="co">#&gt; A 0.274 0.333 0.417 0.412 0.481 0.611 10</span></a>
<a class="sourceLine" id="cb7-14" title="14"><span class="co">#&gt; B 0.337 0.353 0.403 0.411 0.438 0.461 10</span></a>
<a class="sourceLine" id="cb7-15" title="15"><span class="co">#&gt; C 0.336 0.362 0.530 0.528 0.682 0.755 10</span></a>
<a class="sourceLine" id="cb7-16" title="16"><span class="co">#&gt; D 0.263 0.316 0.340 0.331 0.360 0.474 10</span></a>
<a class="sourceLine" id="cb7-17" title="17"><span class="co">#&gt; E 0.252 0.326 0.326 0.329 0.345 0.389 10</span></a>
<a class="sourceLine" id="cb7-18" title="18"><span class="co">#&gt; F 0.250 0.300 0.319 0.327 0.351 0.351 10</span></a>
<a class="sourceLine" id="cb7-19" title="19"><span class="co">#&gt; G 0.240 0.246 0.288 0.277 0.325 0.351 10</span></a>
<a class="sourceLine" id="cb7-20" title="20"><span class="co">#&gt; H 0.242 0.257 0.304 0.294 0.332 0.395 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">
@ -351,13 +351,13 @@
<a class="sourceLine" id="cb8-18" title="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" title="19"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-20" title="20"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-21" title="21"><span class="co">#&gt; en 14.63 14.95 15.07 15.18 15.20 15.26 10</span></a>
<a class="sourceLine" id="cb8-22" title="22"><span class="co">#&gt; de 23.66 23.71 23.92 23.75 23.98 24.84 10</span></a>
<a class="sourceLine" id="cb8-23" title="23"><span class="co">#&gt; nl 23.29 23.66 27.61 23.75 23.83 63.02 10</span></a>
<a class="sourceLine" id="cb8-24" title="24"><span class="co">#&gt; es 23.41 23.63 27.79 23.77 23.81 64.45 10</span></a>
<a class="sourceLine" id="cb8-25" title="25"><span class="co">#&gt; it 23.33 23.58 23.92 23.88 23.94 24.74 10</span></a>
<a class="sourceLine" id="cb8-26" title="26"><span class="co">#&gt; fr 23.25 23.40 31.86 23.64 28.15 63.10 10</span></a>
<a class="sourceLine" id="cb8-27" title="27"><span class="co">#&gt; pt 23.31 23.77 28.00 24.01 24.74 63.00 10</span></a></code></pre></div>
<a class="sourceLine" id="cb8-21" title="21"><span class="co">#&gt; en 14.68 15.11 15.28 15.27 15.34 16.21 10</span></a>
<a class="sourceLine" id="cb8-22" title="22"><span class="co">#&gt; de 23.53 23.65 24.04 23.82 24.63 24.88 10</span></a>
<a class="sourceLine" id="cb8-23" title="23"><span class="co">#&gt; nl 23.36 23.53 27.76 23.81 23.87 63.45 10</span></a>
<a class="sourceLine" id="cb8-24" title="24"><span class="co">#&gt; es 23.59 23.83 23.94 23.96 24.07 24.22 10</span></a>
<a class="sourceLine" id="cb8-25" title="25"><span class="co">#&gt; it 23.30 23.76 27.92 23.83 24.18 64.01 10</span></a>
<a class="sourceLine" id="cb8-26" title="26"><span class="co">#&gt; fr 23.47 23.78 31.80 23.84 24.90 63.25 10</span></a>
<a class="sourceLine" id="cb8-27" title="27"><span class="co">#&gt; pt 23.28 23.69 27.97 23.85 24.42 64.14 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
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@ -46,6 +46,8 @@ test_that("as.mo works", {
expect_equal(as.character(as.mo("L. pneumophila")), "B_LGNLL_PNE")
expect_equal(as.character(as.mo("Strepto")), "B_STRPT")
expect_equal(as.character(as.mo("Streptococcus")), "B_STRPT") # not Peptostreptoccus
expect_equal(as.character(as.mo("Estreptococos grupo B")), "B_STRPT_GRB")
expect_equal(as.character(as.mo("Group B Streptococci")), "B_STRPT_GRB")
expect_equal(as.character(as.mo("B_STRPTC")), "B_STRPT") # old MO code (<=v0.5.0)
expect_equal(as.character(as.mo(c("GAS", "GBS"))), c("B_STRPT_GRA", "B_STRPT_GRB"))