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(v0.7.1.9079) small fixes

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dr. M.S. (Matthijs) Berends 2019-09-22 12:41:45 +02:00
parent 46b61e9a70
commit 57b0bd92a0
26 changed files with 302 additions and 297 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 0.7.1.9078
Date: 2019-09-20
Version: 0.7.1.9079
Date: 2019-09-22
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

4
NEWS.md
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@ -1,5 +1,5 @@
# AMR 0.7.1.9078
<small>Last updated: 20-Sep-2019</small>
# AMR 0.7.1.9079
<small>Last updated: 22-Sep-2019</small>
### Breaking
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:

1
R/freq.R
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@ -29,6 +29,7 @@ clean::freq
#' @export
#' @noRd
freq.mo <- function(x, ...) {
x <- as.mo(x) # to get the newest mo codes
x_noNA <- x[!is.na(x)]
grams <- mo_gramstain(x_noNA, language = NULL)
freq.default(x = x, ...,

1
R/globals.R
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@ -46,6 +46,7 @@ globalVariables(c(".",
"key_ab_lag",
"key_ab_other",
"kingdom",
"kingdom_index",
"lang",
"Last name",
"lookup",

2
R/mo.R
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@ -1721,7 +1721,7 @@ exec_as.mo <- function(x,
print(mo_renamed())
}
if (old_mo_warning == TRUE) {
if (old_mo_warning == TRUE & property != "mo") {
warning("The input contained old microorganism IDs from previous versions of this package. Please use as.mo() on these old codes.\nSUPPORT FOR THIS WILL BE DROPPED IN A FUTURE VERSION.", call. = FALSE)
}

4
R/mo_history.R
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@ -29,6 +29,7 @@ set_mo_history <- function(x, mo, uncertainty_level, force = FALSE, disable = FA
if (base::interactive() | force == TRUE) {
mo_hist <- read_mo_history(uncertainty_level = uncertainty_level, force = force)
warning_new_write <- FALSE
df <- data.frame(x, mo, stringsAsFactors = FALSE) %>%
distinct(x, .keep_all = TRUE) %>%
filter(!is.na(x) & !is.na(mo))
@ -55,8 +56,9 @@ set_mo_history <- function(x, mo, uncertainty_level, force = FALSE, disable = FA
# if (tryCatch(nrow(getOption("mo_remembered_results")), error = function(e) 1001) > 1000) {
# return(base::invisible())
# }
if (is.null(mo_hist) & interactive()) {
if (is.null(mo_hist) & interactive() & warning_new_write == FALSE) {
message(blue(paste0("NOTE: results are saved to ", mo_history_file(), ".")))
warning_new_write <- TRUE
}
tryCatch(write.csv(rbind(mo_hist,
data.frame(

3
cran-comments.md
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@ -1,4 +1,5 @@
# Version 0.8.0
* A NOTE for having a data directory over 3 MB. This is needed to offer users reference data for the complete taxonomy of microorganisms - one of the most important features of this pacakge. Has been this way since version 0.3.0.
* This package writes lines to `[user library]/AMR/mo_history/mo_history.csv` when using the `as.mo()` function, in the exact same way (and borrowed from) the `extrafont` package on CRAN (version 0.17) writes to the package folder. Users are notified about this and staged install still works. The CSV file is never newly created or deleted by this package, it only changes this file to improve speed and reliability of the `as.mo()` function. See the source code of `set_mo_history()` and `clear_mo_history()`.
* This package writes lines to `[user library]/AMR/mo_history/mo_history.csv` when using the `as.mo()` function, in the exact same way (and borrowed from) the `extrafont` package on CRAN (version 0.17) writes to their user library package folder. Users are notified about this with a `message()` and staged install on R >= 3.6.0 still works. The CSV file is never newly created or deleted by this package, it only changes this file to improve speed and reliability of the `as.mo()` function. See the source code of `set_mo_history()` and `clear_mo_history()`.

2
docs/LICENSE-text.html
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@ -78,7 +78,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

420
docs/articles/AMR.html
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@ -40,7 +40,7 @@
</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">0.7.1.9076</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>
@ -185,7 +185,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">20 September 2019</h4>
<h4 class="date">22 September 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -194,7 +194,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 20 September 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 22 September 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -210,21 +210,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-09-20</td>
<td align="center">2019-09-22</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2019-09-20</td>
<td align="center">2019-09-22</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2019-09-20</td>
<td align="center">2019-09-22</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -319,9 +319,20 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2011-05-18</td>
<td align="center">O8</td>
<td align="center">2014-05-20</td>
<td align="center">X4</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">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2011-12-18</td>
<td align="center">O9</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
@ -329,55 +340,44 @@
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2011-03-28</td>
<td align="center">Q8</td>
<td align="center">Hospital B</td>
<tr class="odd">
<td align="center">2015-10-10</td>
<td align="center">G10</td>
<td align="center">Hospital A</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2016-06-01</td>
<td align="center">N7</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</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="odd">
<td align="center">2015-12-27</td>
<td align="center">W2</td>
<td align="center">Hospital A</td>
<td align="center">2013-04-04</td>
<td align="center">O5</td>
<td align="center">Hospital B</td>
<td align="center">Klebsiella pneumoniae</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2014-05-30</td>
<td align="center">X6</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2015-07-30</td>
<td align="center">Q3</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</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">2016-11-03</td>
<td align="center">O8</td>
<td align="center">Hospital D</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">2016-05-23</td>
<td align="center">X1</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">S</td>
@ -405,8 +405,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,330 51.6% 10,330 51.6%
# 2 F 9,670 48.4% 20,000 100.0%</code></pre>
# 1 M 10,388 51.9% 10,388 51.9%
# 2 F 9,612 48.1% 20,000 100.0%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers 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="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -436,14 +436,14 @@
<a class="sourceLine" id="cb15-18" data-line-number="18"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb15-19" data-line-number="19"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb15-20" data-line-number="20"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,405 values changed)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,479 values changed)</span></a>
<a class="sourceLine" id="cb15-22" data-line-number="22"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb15-23" data-line-number="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-24" data-line-number="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,290 values changed)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,275 values changed)</span></a>
<a class="sourceLine" id="cb15-26" data-line-number="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-27" data-line-number="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,639 values changed)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,756 values changed)</span></a>
<a class="sourceLine" id="cb15-29" data-line-number="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb15-30" data-line-number="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb15-31" data-line-number="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -451,24 +451,24 @@
<a class="sourceLine" id="cb15-33" data-line-number="33"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb15-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-35" data-line-number="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,299 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (101 values changed)</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,209 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (121 values changed)</span></a>
<a class="sourceLine" id="cb15-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb15-39" data-line-number="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb15-40" data-line-number="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
<a class="sourceLine" id="cb15-41" data-line-number="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb15-42" data-line-number="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-43" data-line-number="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,427 out of 20,000 rows, making a total of 7,734 edits</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,481 out of 20,000 rows, making a total of 7,840 edits</span></a>
<a class="sourceLine" id="cb15-45" data-line-number="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb15-46" data-line-number="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,734 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 99 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,591 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,111 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 289 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,622 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 22 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,840 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 112 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,739 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,038 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 333 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,595 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 23 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-54" data-line-number="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-55" data-line-number="55"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-56" data-line-number="56"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -496,8 +496,8 @@
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb17-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"><span class="co"># </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="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,635 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>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,658 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>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-2" data-line-number="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>
@ -507,7 +507,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient O6, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient D8, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -523,21 +523,21 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-29</td>
<td align="center">O6</td>
<td align="center">2010-02-17</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</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">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-29</td>
<td align="center">O6</td>
<td align="center">2010-03-19</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -545,8 +545,8 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-31</td>
<td align="center">O6</td>
<td align="center">2010-05-22</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -556,8 +556,8 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-09-18</td>
<td align="center">O6</td>
<td align="center">2010-05-27</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -567,52 +567,52 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2011-03-23</td>
<td align="center">O6</td>
<td align="center">2010-09-23</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_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">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-03-24</td>
<td align="center">O6</td>
<td align="center">2010-10-27</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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="odd">
<td align="center">7</td>
<td align="center">2011-07-19</td>
<td align="center">O6</td>
<td align="center">2010-11-04</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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">8</td>
<td align="center">2011-08-04</td>
<td align="center">O6</td>
<td align="center">2010-12-12</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-08-15</td>
<td align="center">O6</td>
<td align="center">2010-12-17</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -622,18 +622,18 @@
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-08-22</td>
<td align="center">O6</td>
<td align="center">2010-12-29</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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>
</tbody>
</table>
<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>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>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="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="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>
@ -644,7 +644,7 @@
<a class="sourceLine" id="cb20-7" data-line-number="7"><span class="co"># </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="cb20-8" data-line-number="8"><span class="co"># </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="cb20-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,041 first weighted isolates (75.2% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,076 first weighted isolates (75.4% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -661,22 +661,22 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-29</td>
<td align="center">O6</td>
<td align="center">2010-02-17</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</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">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-29</td>
<td align="center">O6</td>
<td align="center">2010-03-19</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -685,20 +685,20 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-31</td>
<td align="center">O6</td>
<td align="center">2010-05-22</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-09-18</td>
<td align="center">O6</td>
<td align="center">2010-05-27</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -709,56 +709,56 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2011-03-23</td>
<td align="center">O6</td>
<td align="center">2010-09-23</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_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">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-03-24</td>
<td align="center">O6</td>
<td align="center">2010-10-27</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-07-19</td>
<td align="center">O6</td>
<td align="center">2010-11-04</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-08-04</td>
<td align="center">O6</td>
<td align="center">2010-12-12</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</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">9</td>
<td align="center">2011-08-15</td>
<td align="center">O6</td>
<td align="center">2010-12-17</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -769,23 +769,23 @@
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-08-22</td>
<td align="center">O6</td>
<td align="center">2010-12-29</td>
<td align="center">D8</td>
<td align="center">B_ESCHR_COLI</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>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 6 isolates are flagged. In total, 75.2% of all isolates are marked ‘first weighted’ - 47% 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 1, now 6 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 47.1% 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="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="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 15,041 isolates for analysis.</p>
<p>So we end up with 15,076 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="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>
@ -810,10 +810,10 @@
</tr></thead>
<tbody>
<tr class="odd">
<td>1</td>
<td align="center">2011-05-18</td>
<td align="center">O8</td>
<td align="center">Hospital B</td>
<td>2</td>
<td align="center">2011-12-18</td>
<td align="center">O9</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
@ -826,30 +826,14 @@
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>2</td>
<td align="center">2011-03-28</td>
<td align="center">Q8</td>
<td>5</td>
<td align="center">2013-04-04</td>
<td align="center">O5</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</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">TRUE</td>
</tr>
<tr class="odd">
<td>3</td>
<td align="center">2015-12-27</td>
<td align="center">W2</td>
<td align="center">Hospital A</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">R</td>
<td align="center">R</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>
<td align="center">Gram-negative</td>
@ -857,11 +841,27 @@
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>6</td>
<td align="center">2016-05-23</td>
<td align="center">X1</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</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>
<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>5</td>
<td align="center">2015-07-30</td>
<td align="center">Q3</td>
<td align="center">Hospital D</td>
<td>8</td>
<td align="center">2013-07-08</td>
<td align="center">O3</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -874,29 +874,29 @@
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>6</td>
<td align="center">2016-11-03</td>
<td align="center">O8</td>
<td align="center">Hospital D</td>
<td align="center">B_STPHY_AURS</td>
<td>9</td>
<td align="center">2014-01-06</td>
<td align="center">N2</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</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>
<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>7</td>
<td align="center">2013-04-03</td>
<td align="center">F8</td>
<td align="center">Hospital A</td>
<td>10</td>
<td align="center">2015-10-02</td>
<td align="center">H5</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</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">M</td>
@ -924,7 +924,7 @@
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,041 (of which NA: 0 = 0.00%)<br>
Length: 15,076 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -941,33 +941,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,491</td>
<td align="right">49.8%</td>
<td align="right">7,491</td>
<td align="right">49.8%</td>
<td align="right">7,447</td>
<td align="right">49.4%</td>
<td align="right">7,447</td>
<td align="right">49.4%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,732</td>
<td align="right">3,738</td>
<td align="right">24.8%</td>
<td align="right">11,223</td>
<td align="right">74.6%</td>
<td align="right">11,185</td>
<td align="right">74.2%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,223</td>
<td align="right">14.8%</td>
<td align="right">13,446</td>
<td align="right">89.4%</td>
<td align="right">2,305</td>
<td align="right">15.3%</td>
<td align="right">13,490</td>
<td align="right">89.5%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,595</td>
<td align="right">10.6%</td>
<td align="right">15,041</td>
<td align="right">1,586</td>
<td align="right">10.5%</td>
<td align="right">15,076</td>
<td align="right">100.0%</td>
</tr>
</tbody>
@ -978,7 +978,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code><a href="../reference/portion.html">portion_S()</a></code>, <code><a href="../reference/portion.html">portion_SI()</a></code>, <code><a href="../reference/portion.html">portion_I()</a></code>, <code><a href="../reference/portion.html">portion_IR()</a></code> and <code><a href="../reference/portion.html">portion_R()</a></code> can be used to determine the portion of a specific antimicrobial outcome. As per the EUCAST guideline of 2019, we calculate resistance as the portion of R (<code><a href="../reference/portion.html">portion_R()</a></code>) and susceptibility as the portion of S and I (<code><a href="../reference/portion.html">portion_SI()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_R</a></span>(AMX)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.4677216</span></a></code></pre></div>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.4692889</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="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb27-2" data-line-number="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>
@ -991,19 +991,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4646398</td>
<td align="center">0.4708452</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4578497</td>
<td align="center">0.4723226</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4776586</td>
<td align="center">0.4660508</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4822200</td>
<td align="center">0.4640650</td>
</tr>
</tbody>
</table>
@ -1021,23 +1021,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4646398</td>
<td align="center">4539</td>
<td align="center">0.4708452</td>
<td align="center">4579</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4578497</td>
<td align="center">5255</td>
<td align="center">0.4723226</td>
<td align="center">5257</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4776586</td>
<td align="center">2238</td>
<td align="center">0.4660508</td>
<td align="center">2165</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4822200</td>
<td align="center">3009</td>
<td align="center">0.4640650</td>
<td align="center">3075</td>
</tr>
</tbody>
</table>
@ -1057,27 +1057,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9236417</td>
<td align="center">0.8994794</td>
<td align="center">0.9942598</td>
<td align="center">0.9246677</td>
<td align="center">0.8941856</td>
<td align="center">0.9924802</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8206897</td>
<td align="center">0.9028213</td>
<td align="center">0.9868339</td>
<td align="center">0.8234552</td>
<td align="center">0.8972257</td>
<td align="center">0.9892812</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9228296</td>
<td align="center">0.9265809</td>
<td align="center">0.9951768</td>
<td align="center">0.9210808</td>
<td align="center">0.9266988</td>
<td align="center">0.9925094</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6171840</td>
<td align="center">0.6121475</td>
<td align="center">0.0000000</td>
<td align="center">0.6171840</td>
<td align="center">0.6121475</td>
</tr>
</tbody>
</table>

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@ -40,7 +40,7 @@
</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">0.7.1.9077</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>
@ -185,7 +185,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">20 September 2019</h4>
<h4 class="date">22 September 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -219,36 +219,36 @@
<a class="sourceLine" id="cb2-16" data-line-number="16"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<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>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 8.6 8.8 9.0 9.0 9.2</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 31.0 31.0 32.0 32.0 33.0</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 31.0 32.0 39.0 33.0 38.0</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 8.6 9.1 17.0 9.7 31.0</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 8.7 9.0 14.0 9.3 9.6</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 23.0 23.0 45.0 24.0 25.0</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 23.0 23.0 29.0 24.0 26.0</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 28.0 28.0 32.0 29.0 30.0</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 530.0 560.0 580.0 570.0 580.0</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 270.0 300.0 310.0 310.0 320.0</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 8.6 9.0 9.3 9.2 9.3</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 20.0 27.0 20.0 43.0</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 19.0 20.0 26.0 21.0 23.0</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 24.0 19.0 22.0</span></a>
<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 9.5 10</span></a>
<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 38.0 10</span></a>
<a class="sourceLine" id="cb2-37" data-line-number="37"><span class="co"># 61.0 10</span></a>
<a class="sourceLine" id="cb2-38" data-line-number="38"><span class="co"># 38.0 10</span></a>
<a class="sourceLine" id="cb2-39" data-line-number="39"><span class="co"># 35.0 10</span></a>
<a class="sourceLine" id="cb2-40" data-line-number="40"><span class="co"># 210.0 10</span></a>
<a class="sourceLine" id="cb2-41" data-line-number="41"><span class="co"># 56.0 10</span></a>
<a class="sourceLine" id="cb2-42" data-line-number="42"><span class="co"># 57.0 10</span></a>
<a class="sourceLine" id="cb2-43" data-line-number="43"><span class="co"># 660.0 10</span></a>
<a class="sourceLine" id="cb2-44" data-line-number="44"><span class="co"># 380.0 10</span></a>
<a class="sourceLine" id="cb2-45" data-line-number="45"><span class="co"># 10.0 10</span></a>
<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 46.0 10</span></a>
<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 48.0 10</span></a>
<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 42.0 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 8.5 8.6 11 8.7 9.1 34</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 31.0 31.0 39 31.0 56.0 58</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 31.0 34.0 39 34.0 35.0 60</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 8.5 8.7 15 8.9 9.6 67</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 8.6 8.7 14 9.0 9.9 36</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 23.0 23.0 40 25.0 26.0 180</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 23.0 24.0 30 26.0 30.0 51</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 28.0 28.0 31 29.0 29.0 51</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 570.0 600.0 620 620.0 640.0 710</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 280.0 310.0 320 320.0 330.0 340</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 8.4 8.6 11 8.8 9.5 35</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 19.0 21 20.0 22.0 24</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 19.0 19.0 27 23.0 41.0 46</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 22 21.0 22.0 43</span></a>
<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># neval</span></a>
<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-37" data-line-number="37"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-38" data-line-number="38"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-39" data-line-number="39"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-40" data-line-number="40"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-41" data-line-number="41"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-42" data-line-number="42"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-43" data-line-number="43"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-44" data-line-number="44"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-45" data-line-number="45"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 10</span></a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.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. 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>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
@ -260,19 +260,19 @@
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<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>(M.semesiae, <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="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1201.00 1327.00 1331.00 1340.00 1359.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1255.00 1298.00 1333.00 1340.00 1363.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1927.00 1943.00 1985.00 1995.00 2014.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1914.00 1953.00 1979.00 1977.00 1987.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 27.84 30.71 31.59 31.12 31.44</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1310.00 1340.0 1361.00 1358 1387.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1304.00 1320.0 1350.00 1341 1382.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1839.00 1968.0 1990.00 2006 2032.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1947.00 1978.0 2014.00 2019 2046.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 30.49 31.2 35.04 32 32.81</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1371.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1398.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2040.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2058.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 39.75 10</span></a></code></pre></div>
<p>That takes 15.7 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>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1401.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1411.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2049.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2088.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 63.03 10</span></a></code></pre></div>
<p>That takes 15.2 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>Methanosarcina semesiae</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>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5"></p>
<p>In reality, the <code><a href="../reference/as.mo.html">as.mo()</a></code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code><a href="../reference/as.mo.html">as.mo()</a></code> yourself:</p>
@ -309,8 +309,8 @@
<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>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 610 637 653 652 668 718 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.65 seconds (652 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 598 639 656 657 671 735 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.66 seconds (657 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -322,10 +322,10 @@
<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<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>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.280 6.560 9.940 6.720 6.860 39.30 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.500 22.900 24.300 23.000 24.900 30.90 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.805 0.829 0.871 0.847 0.869 1.09 10</span></a></code></pre></div>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.150 6.340 9.110 6.370 6.400 33.700 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.000 22.200 22.900 22.300 22.400 28.300 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.691 0.784 0.783 0.795 0.802 0.814 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<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 &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="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>
@ -339,14 +339,14 @@
<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>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.456 0.457 0.472 0.465 0.493 0.498 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.629 0.640 0.713 0.668 0.752 0.956 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.798 0.811 0.840 0.832 0.840 0.965 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.428 0.453 0.473 0.464 0.503 0.518 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.446 0.477 0.513 0.495 0.525 0.648 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.466 0.473 0.496 0.484 0.521 0.545 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.457 0.461 0.477 0.468 0.486 0.545 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.456 0.467 0.478 0.477 0.482 0.512 10</span></a></code></pre></div>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.462 0.471 0.480 0.482 0.491 0.498 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.609 0.627 0.645 0.638 0.657 0.714 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.651 0.731 0.771 0.772 0.806 0.887 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.431 0.457 0.488 0.468 0.485 0.675 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.450 0.452 0.466 0.465 0.473 0.500 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.461 0.466 0.481 0.474 0.495 0.514 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.449 0.453 0.465 0.464 0.471 0.495 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.455 0.458 0.481 0.465 0.485 0.594 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">
@ -373,13 +373,13 @@
<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 18.04 18.47 18.79 18.54 19.25 19.70 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.36 19.88 22.78 20.17 20.39 47.73 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 24.57 25.38 28.46 25.63 26.12 54.82 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 19.50 19.89 25.49 20.51 25.79 44.96 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.52 19.82 20.44 20.11 20.80 23.09 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.50 19.79 20.42 19.86 20.53 23.35 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 19.25 19.55 22.50 19.59 20.04 47.50 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 17.93 18.18 19.34 18.76 19.02 26.27 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.44 19.63 22.03 19.80 20.23 41.83 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 24.54 24.78 27.37 25.23 25.55 47.06 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 19.51 19.94 20.27 20.20 20.55 21.16 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.40 19.67 24.91 19.99 20.90 46.83 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.24 19.45 22.53 19.80 20.17 47.71 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 19.18 19.33 19.87 19.72 20.62 20.75 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>

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2
docs/articles/index.html
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@ -78,7 +78,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

2
docs/authors.html
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@ -78,7 +78,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

2
docs/index.html
View File

@ -42,7 +42,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

10
docs/news/index.html
View File

@ -78,7 +78,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>
@ -225,11 +225,11 @@
</div>
<div id="amr-0-7-1-9078" class="section level1">
<div id="amr-0-7-1-9079" class="section level1">
<h1 class="page-header">
<a href="#amr-0-7-1-9078" class="anchor"></a>AMR 0.7.1.9078<small> Unreleased </small>
<a href="#amr-0-7-1-9079" class="anchor"></a>AMR 0.7.1.9079<small> Unreleased </small>
</h1>
<p><small>Last updated: 20-Sep-2019</small></p>
<p><small>Last updated: 22-Sep-2019</small></p>
<div id="breaking" class="section level3">
<h3 class="hasAnchor">
<a href="#breaking" class="anchor"></a>Breaking</h3>
@ -1267,7 +1267,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-0-7-1-9078">0.7.1.9078</a></li>
<li><a href="#amr-0-7-1-9079">0.7.1.9079</a></li>
<li><a href="#amr-0-7-1">0.7.1</a></li>
<li><a href="#amr-0-7-0">0.7.0</a></li>
<li><a href="#amr-0-6-1">0.6.1</a></li>

2
docs/reference/as.mo.html
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@ -80,7 +80,7 @@
</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">0.7.1.9077</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

2
docs/reference/index.html
View File

@ -78,7 +78,7 @@
</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">0.7.1.9078</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

2
docs/reference/microorganisms.html
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@ -80,7 +80,7 @@
</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">0.7.1.9076</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

2
docs/reference/microorganisms.old.html
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@ -80,7 +80,7 @@
</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">0.7.1.9077</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
</span>
</div>

4
vignettes/benchmarks.Rmd
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@ -149,8 +149,8 @@ boxplot(microbenchmark(
'as.mo("P. brevis")' = as.mo("P. brevis", force_mo_history = TRUE),
'as.mo("E. coli")' = as.mo("E. coli", force_mo_history = TRUE),
times = 10),
horizontal = TRUE, las = 1, unit = "s", log = FALSE,
xlab = "", ylab = "Time in seconds",
horizontal = TRUE, las = 1, unit = "s", log = TRUE,
xlab = "", ylab = "Time in seconds (log)",
main = "Benchmarks per prevalence")
```