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(v1.6.0.9015) italicise_taxonomy

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dr. M.S. (Matthijs) Berends 2021-05-03 10:47:32 +02:00
parent e405de079c
commit 12a8d59869
34 changed files with 625 additions and 126 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 1.6.0.9014
Date: 2021-04-30
Version: 1.6.0.9015
Date: 2021-05-03
Title: Antimicrobial Resistance Data Analysis
Authors@R: c(
person(role = c("aut", "cre"),

2
NAMESPACE
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@ -237,6 +237,8 @@ export(is.mo)
export(is.rsi)
export(is.rsi.eligible)
export(is_new_episode)
export(italicise_taxonomy)
export(italicize_taxonomy)
export(key_antibiotics)
export(key_antibiotics_equal)
export(key_antimicrobials)

5
NEWS.md
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@ -1,8 +1,9 @@
# `AMR` 1.6.0.9014
## <small>Last updated: 30 April 2021</small>
# `AMR` 1.6.0.9015
## <small>Last updated: 3 May 2021</small>
### New
* Function `custom_eucast_rules()` that brings support for custom AMR rules in `eucast_rules()`
* Function `italicise_taxonomy()` to make taxonomic names within a string italic, with support for markdown and ANSI
* Support for all four methods to determine first isolates as summarised by Hindler *et al* (doi: [10.1086/511864](https://doi.org/10.1086/511864)): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default.
* The `first_isolate()` function gained the argument `method` that has to be "phenotype-based", "episode-based", "patient-based", or "isolate-based". The old behaviour is equal to "episode-based". The new default is "phenotype-based" if antimicrobial test results are available, and "episode-based" otherwise. This new default will yield slightly more isolates for selection (which is a good thing).
* Since fungal isolates can also be selected, the functions `key_antibiotics()` and `key_antibiotics_equal()` are now deprecated in favour of the `key_antimicrobials()` and `antimicrobial_equal()` functions. Also, the new `all_antimicrobials()` function works like the old `key_antibiotics()` function, but includes any column with antimicrobial test results. Using `key_antimicrobials()` still only selects six preferred antibiotics for Gram-negatives, six for Gram-positives, and six universal antibiotics. It has a new `antifungal` argument to set antifungal agents (antimycotics).

1
R/ab.R
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@ -477,7 +477,6 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
if (length(x_unknown) > 0 & fast_mode == FALSE) {
warning_("These values could not be coerced to a valid antimicrobial ID: ",
vector_and(x_unknown), ".",
".",
call = FALSE)
}

1
R/custom_eucast_rules.R
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@ -93,6 +93,7 @@
#'
#' `r paste0(" * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("``", tolower(x), "``\\cr(", paste0(sort(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE)), collapse = ", "), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
#' @returns A [list] containing the custom rules
#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",

27
R/eucast_rules.R
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@ -65,7 +65,6 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' @details
#' **Note:** This function does not translate MIC values to RSI values. Use [as.rsi()] for that. \cr
#' **Note:** When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. \cr
#'
#' The file containing all EUCAST rules is located here: <https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv>. **Note:** Old taxonomic names are replaced with the current taxonomy where applicable. For example, *Ochrobactrum anthropi* was renamed to *Brucella anthropi* in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The file used as input for this `AMR` package contains the taxonomy updated until [`r CATALOGUE_OF_LIFE$yearmonth_LPSN`][catalogue_of_life()].
#'
@ -322,17 +321,6 @@ eucast_rules <- function(x,
}
cols_ab[match(x_new, names(cols_ab))]
}
markup_italics_where_needed <- function(x) {
# returns names found in family, genus or species as italics
if (!has_colour()) {
return(x)
}
x <- unlist(strsplit(x, " "))
ind <- gsub("[)(:]", "", x) %in% c(MO_lookup[which(MO_lookup$rank %in% c("family", "genus")), ]$fullname,
MO_lookup[which(MO_lookup$rank == "species"), ]$species)
x[ind] <- font_italic(x[ind], collapse = NULL)
paste(x, collapse = " ")
}
get_antibiotic_names <- function(x) {
x <- x %pm>%
strsplit(",") %pm>%
@ -343,6 +331,7 @@ eucast_rules <- function(x,
paste(collapse = ", ")
x <- gsub("_", " ", x, fixed = TRUE)
x <- gsub("except CAZ", paste("except", ab_name("CAZ", language = NULL, tolower = TRUE)), x, fixed = TRUE)
x <- gsub("except TGC", paste("except", ab_name("TGC", language = NULL, tolower = TRUE)), x, fixed = TRUE)
x <- gsub("cephalosporins (1st|2nd|3rd|4th|5th)", "cephalosporins (\\1 gen.)", x)
x
}
@ -655,9 +644,10 @@ eucast_rules <- function(x,
# Print rule -------------------------------------------------------------
if (rule_current != rule_previous) {
# is new rule within group, print its name
cat(markup_italics_where_needed(word_wrap(rule_current,
width = getOption("width") - 30,
extra_indent = 6)))
cat(italicise_taxonomy(word_wrap(rule_current,
width = getOption("width") - 30,
extra_indent = 6),
type = "ansi"))
warned <- FALSE
}
}
@ -795,9 +785,10 @@ eucast_rules <- function(x,
get_antibiotic_names(cols))
if (info == TRUE) {
# print rule
cat(markup_italics_where_needed(word_wrap(format_custom_query_rule(rule$query, colours = FALSE),
width = getOption("width") - 30,
extra_indent = 6)))
cat(italicise_taxonomy(word_wrap(format_custom_query_rule(rule$query, colours = FALSE),
width = getOption("width") - 30,
extra_indent = 6),
type = "ansi"))
warned <- FALSE
}
run_changes <- edit_rsi(x = x,

119
R/italicise_taxonomy.R Normal file
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@ -0,0 +1,119 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2021 Berends MS, Luz CF et al. #
# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Italicise Taxonomic Families, Genera, Species, Subspecies
#'
#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
#' @inheritSection lifecycle Maturing Lifecycle
#' @param string a character (vector)
#' @param type type of conversion of the taxonomic names, either "markdown" or "ansi", see *Details*
#' @details
#' This function finds the taxonomic names and makes them italic based on the [microorganisms] data set.
#'
#' The taxonomic names can be italicised using markdown (the default) by adding `*` before and after the taxonomic names, or using ANSI colours by adding `\033[3m` before and `\033[23m` after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.
#'
#' This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
#' @inheritSection AMR Read more on Our Website!
#' @export
#' @examples
#' italicise_taxonomy("An overview of Staphylococcus aureus isolates")
#' italicise_taxonomy("An overview of S. aureus isolates")
#'
#' cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
if (missing(type)) {
type <- "markdown"
}
meet_criteria(string, allow_class = "character")
meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("markdown", "ansi"))
if (type == "markdown") {
before <- "*"
after <- "*"
} else if (type == "ansi") {
if (!has_colour()) {
return(string)
}
before <- "\033[3m"
after <- "\033[23m"
}
vapply(FUN.VALUE = character(1),
string,
function(s) {
s_split <- unlist(strsplit(s, " "))
search_strings <- gsub("[^a-zA-Z-]", "", s_split)
ind_species <- search_strings != "" &
search_strings %in% MO_lookup[which(MO_lookup$rank %in% c("family",
"genus",
"species",
"subspecies",
"infraspecies",
"subsp.")),
"species",
drop = TRUE]
ind_fullname <- search_strings != "" &
search_strings %in% c(MO_lookup[which(MO_lookup$rank %in% c("family",
"genus",
"species",
"subspecies",
"infraspecies",
"subsp.")),
"fullname",
drop = TRUE],
MO_lookup[which(MO_lookup$rank %in% c("family",
"genus",
"species",
"subspecies",
"infraspecies",
"subsp.")),
"subspecies",
drop = TRUE])
# also support E. coli, add "E." to indices
has_previous_genera_abbr <- s_split[which(ind_species) - 1] %like_case% "^[A-Z][.]?$"
ind_species <- c(which(ind_species), which(ind_species)[has_previous_genera_abbr] - 1)
ind <- c(ind_species, which(ind_fullname))
s_split[ind] <- paste0(before, s_split[ind], after)
s_paste <- paste(s_split, collapse = " ")
# clean up a bit
s_paste <- gsub(paste0(after, " ", before), " ", s_paste, fixed = TRUE)
s_paste
},
USE.NAMES = FALSE)
}
#' @rdname italicise_taxonomy
#' @export
italicize_taxonomy <- function(string, type = c("markdown", "ansi")) {
italicise(string = string, type = type)
}

BIN
data-raw/AMR_latest.tar.gz
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2
docs/404.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>

2
docs/LICENSE-text.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>

153
docs/articles/benchmarks.html
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@ -39,7 +39,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9011</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>
@ -47,14 +47,14 @@
<ul class="nav navbar-nav">
<li>
<a href="../index.html">
<span class="fa fa-home"></span>
<span class="fas fa-home"></span>
Home
</a>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
<span class="fa fa-question-circle"></span>
<span class="fas fa-question-circle"></span>
How to
@ -63,77 +63,77 @@
<ul class="dropdown-menu" role="menu">
<li>
<a href="../articles/AMR.html">
<span class="fa fa-directions"></span>
<span class="fas fa-directions"></span>
Conduct AMR analysis
</a>
</li>
<li>
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Predict antimicrobial resistance
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Data sets for download / own use
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Conduct principal component analysis for AMR
</a>
</li>
<li>
<a href="../articles/MDR.html">
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<span class="fas fa-skull-crossbones"></span>
Determine multi-drug resistance (MDR)
</a>
</li>
<li>
<a href="../articles/WHONET.html">
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<span class="fas fa-globe-americas"></span>
Work with WHONET data
</a>
</li>
<li>
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Import data from SPSS/SAS/Stata
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Apply EUCAST rules
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Get properties of a microorganism
</a>
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Get properties of an antibiotic
</a>
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<a href="../articles/benchmarks.html">
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Other: benchmarks
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@ -142,21 +142,21 @@
</li>
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@ -165,14 +165,14 @@
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://github.com/msberends/AMR">
<span class="fab fa fab fa-github"></span>
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@ -187,8 +187,7 @@
</header><link href="benchmarks_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="benchmarks_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
</header><script src="benchmarks_files/header-attrs-2.7/header-attrs.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Benchmarks</h1>
@ -203,15 +202,15 @@
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="downlit">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/">microbenchmark</a></span><span class="op">)</span>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/">microbenchmark</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span></pre></div>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span></code></pre></div>
<p>In the next test, we try to ‘coerce’ different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p>
<p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p>
<p>But the calculation time differs a lot:</p>
<div class="sourceCode" id="cb2"><pre class="downlit">
<span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"sau"</span><span class="op">)</span>, <span class="co"># WHONET code</span>
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"stau"</span><span class="op">)</span>,
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"STAU"</span><span class="op">)</span>,
@ -225,21 +224,21 @@
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"MRSA"</span><span class="op">)</span>, <span class="co"># Methicillin Resistant S. aureus</span>
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"VISA"</span><span class="op">)</span>, <span class="co"># Vancomycin Intermediate S. aureus</span>
times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 25.0 25.0 30 26.0 26.0 83 25</span>
<span class="co"># as.mo("stau") 120.0 130.0 150 130.0 180.0 390 25</span>
<span class="co"># as.mo("STAU") 120.0 130.0 150 130.0 180.0 190 25</span>
<span class="co"># as.mo("staaur") 25.0 26.0 33 26.0 26.0 83 25</span>
<span class="co"># as.mo("STAAUR") 25.0 26.0 33 26.0 26.0 83 25</span>
<span class="co"># as.mo("S. aureus") 66.0 66.0 89 67.0 120.0 150 25</span>
<span class="co"># as.mo("S aureus") 66.0 66.0 74 66.0 67.0 120 25</span>
<span class="co"># as.mo("Staphylococcus aureus") 6.8 6.9 14 6.9 7.5 63 25</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 550.0 550.0 560 550.0 560.0 620 25</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 410.0 420.0 430 420.0 420.0 620 25</span>
<span class="co"># as.mo("MRSA") 25.0 26.0 31 26.0 26.0 83 25</span>
<span class="co"># as.mo("VISA") 46.0 47.0 65 47.0 98.0 110 25</span></pre></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 9.6 10.0 12.0 10 11.0 42 25</span>
<span class="co"># as.mo("stau") 52.0 55.0 74.0 59 94.0 110 25</span>
<span class="co"># as.mo("STAU") 51.0 53.0 73.0 57 91.0 100 25</span>
<span class="co"># as.mo("staaur") 9.5 9.9 11.0 10 12.0 13 25</span>
<span class="co"># as.mo("STAAUR") 9.4 10.0 18.0 10 12.0 52 25</span>
<span class="co"># as.mo("S. aureus") 24.0 26.0 31.0 26 29.0 62 25</span>
<span class="co"># as.mo("S aureus") 25.0 25.0 42.0 29 62.0 68 25</span>
<span class="co"># as.mo("Staphylococcus aureus") 2.5 2.9 3.2 3 3.5 4 25</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 240.0 240.0 260.0 250 260.0 390 25</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 150.0 190.0 190.0 190 190.0 250 25</span>
<span class="co"># as.mo("MRSA") 8.7 10.0 15.0 11 12.0 49 25</span>
<span class="co"># as.mo("VISA") 17.0 19.0 25.0 21 22.0 57 25</span></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 200 times slower to determine.</p>
<p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
@ -248,8 +247,8 @@
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
<p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code><a href="../reference/as.mo.html">as.mo(c("E. coli", "E. coli"))</a></code> will check the value <code>"E. coli"</code> only once.</p>
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="co"># start with the example_isolates data set</span>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span>
<span class="co"># take all MO codes from the 'mo' column</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -261,8 +260,8 @@
<span class="co"># what do these values look like? They are of class &lt;mo&gt;:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
<span class="co"># Class &lt;mo&gt;</span>
<span class="co"># [1] B_STPHY_EPDR B_STPHY_EPDR B_STPHY_CONS B_STPHY_CONS B_STPHY_EPDR</span>
<span class="co"># [6] B_ESCHR_COLI</span>
<span class="co"># [1] B_KLBSL_PNMN B_STPHY_EPDR B_STRPT_PNMN B_STRPT_EQNS B_ESCHR_COLI</span>
<span class="co"># [6] B_KLBSL_PNMN</span>
<span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
<span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@ -275,30 +274,30 @@
<span class="co"># now let's see:</span>
<span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>,
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 321 378 443 410 438 713 10</span></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.41 seconds. That is 205 nanoseconds on average. You only lose time on your unique input values.</p>
<span class="co"># mo_name(x) 155 182 233 228 242 350 10</span></code></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.228 seconds. That is 114 nanoseconds on average. You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see ‘C’ below):</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 17.00 17.1 17.10 17.10 17.20 17.20 10</span>
<span class="co"># B 57.20 57.3 68.90 57.60 58.40 117.00 10</span>
<span class="co"># C 3.66 3.7 3.74 3.74 3.77 3.89 10</span></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 0.0037 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="cb5"><pre class="downlit">
<span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 6.62 6.84 7.30 6.91 8.10 8.74 10</span>
<span class="co"># B 22.20 23.10 33.20 24.50 27.70 70.80 10</span>
<span class="co"># C 1.37 1.50 1.66 1.71 1.81 1.84 10</span></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 0.0017 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="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
C <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span><span class="op">)</span>,
D <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"Staphylococcaceae"</span><span class="op">)</span>,
@ -307,25 +306,25 @@
G <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_phylum</a></span><span class="op">(</span><span class="st">"Firmicutes"</span><span class="op">)</span>,
H <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_kingdom</a></span><span class="op">(</span><span class="st">"Bacteria"</span><span class="op">)</span>,
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 3.70 3.71 3.81 3.74 3.82 4.14 10</span>
<span class="co"># B 3.66 3.67 3.76 3.69 3.76 4.10 10</span>
<span class="co"># C 3.66 3.70 3.72 3.72 3.73 3.76 10</span>
<span class="co"># D 3.63 3.67 3.77 3.71 3.88 4.09 10</span>
<span class="co"># E 3.62 3.67 3.75 3.70 3.78 4.07 10</span>
<span class="co"># F 3.62 3.64 3.66 3.65 3.65 3.74 10</span>
<span class="co"># G 3.63 3.64 3.67 3.67 3.68 3.75 10</span>
<span class="co"># H 3.63 3.64 3.74 3.67 3.84 4.07 10</span></pre></div>
<span class="co"># A 1.19 1.21 1.43 1.28 1.65 2.03 10</span>
<span class="co"># B 1.19 1.24 1.38 1.26 1.53 1.83 10</span>
<span class="co"># C 1.24 1.28 1.45 1.36 1.41 2.24 10</span>
<span class="co"># D 1.20 1.22 1.33 1.23 1.41 1.77 10</span>
<span class="co"># E 1.21 1.22 1.35 1.27 1.38 1.69 10</span>
<span class="co"># F 1.20 1.21 1.34 1.26 1.37 1.71 10</span>
<span class="co"># G 1.17 1.22 1.31 1.27 1.31 1.71 10</span>
<span class="co"># H 1.21 1.27 1.42 1.37 1.47 1.84 10</span></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> anyway, there is no point in calculating the result. And because this package contains all phyla of all known bacteria, it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
<h3 class="hasAnchor">
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on an English system</span>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"en"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on an English system</span>
<span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span>
<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span> <span class="co"># or just mo_name("CoNS") on a Spanish system</span>
@ -342,16 +341,16 @@
fr <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"fr"</span><span class="op">)</span>,
pt <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"CoNS"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span>,
times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 43.15 43.49 48.88 43.66 43.81 122.3 100</span>
<span class="co"># de 79.59 80.39 88.27 80.89 81.11 135.8 100</span>
<span class="co"># nl 79.69 80.45 87.16 80.81 81.07 136.6 100</span>
<span class="co"># es 79.28 80.12 89.84 80.51 81.02 159.5 100</span>
<span class="co"># it 51.74 52.20 55.59 52.39 52.61 109.1 100</span>
<span class="co"># fr 51.43 51.88 54.83 52.05 52.29 105.5 100</span>
<span class="co"># pt 51.58 51.93 59.25 52.28 52.55 111.8 100</span></pre></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 17.19 17.50 22.00 17.76 18.54 61.02 100</span>
<span class="co"># de 31.08 31.53 39.66 32.04 35.34 76.23 100</span>
<span class="co"># nl 30.19 31.41 40.64 32.30 35.93 79.53 100</span>
<span class="co"># es 30.50 31.33 41.70 31.84 35.90 181.80 100</span>
<span class="co"># it 20.94 21.37 25.27 21.63 22.44 69.84 100</span>
<span class="co"># fr 20.62 21.00 27.09 21.41 23.12 79.50 100</span>
<span class="co"># pt 20.41 21.23 25.33 21.56 22.22 70.65 100</span></code></pre></div>
<p>Currently supported non-English languages are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>

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@ -0,0 +1,12 @@
// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
// be compatible with the behavior of Pandoc < 2.8).
document.addEventListener('DOMContentLoaded', function(e) {
var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
var i, h, a;
for (i = 0; i < hs.length; i++) {
h = hs[i];
if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
a = h.attributes;
while (a.length > 0) h.removeAttribute(a[0].name);
}
});

2
docs/articles/index.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>

2
docs/authors.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>

3
docs/extra.js
View File

@ -53,6 +53,9 @@ $(document).ready(function() {
$("pre.examples").html($("pre.examples").html().replaceAll("# }", ""));
}
// remove leading newline in code examples on changelog
$("body .template-news").html($("body .template-news").html().replaceAll('sourceCode R">\n<span', 'sourceCode R"><span'));
// PR for 'R for Data Science' on How To pages
if ($(".template-article").length > 0) {
$('#pkgdown-sidebar').prepend(

2
docs/index.html
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@ -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">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>

17
docs/news/index.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
</span>
</div>
@ -236,12 +236,12 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1609014" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9014">
<a href="#amr-1609014" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9014</h1>
<div id="last-updated-30-april-2021" class="section level2">
<div id="amr-1609015" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9015">
<a href="#amr-1609015" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9015</h1>
<div id="last-updated-3-may-2021" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-30-april-2021" class="anchor"></a><small>Last updated: 30 April 2021</small>
<a href="#last-updated-3-may-2021" class="anchor"></a><small>Last updated: 3 May 2021</small>
</h2>
<div id="new" class="section level3">
<h3 class="hasAnchor">
@ -249,6 +249,7 @@
<ul>
<li>Function <code><a href="../reference/custom_eucast_rules.html">custom_eucast_rules()</a></code> that brings support for custom AMR rules in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
</li>
<li>Function <code><a href="../reference/italicise_taxonomy.html">italicise_taxonomy()</a></code> to make taxonomic names within a string italic, with support for markdown and ANSI</li>
<li>Support for all four methods to determine first isolates as summarised by Hindler <em>et al</em> (doi: <a href="https://doi.org/10.1086/511864">10.1086/511864</a>): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default.
<ul>
<li>The <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function gained the argument <code>method</code> that has to be “phenotype-based”, “episode-based”, “patient-based”, or “isolate-based”. The old behaviour is equal to “episode-based”. The new default is “phenotype-based” if antimicrobial test results are available, and “episode-based” otherwise. This new default will yield slightly more isolates for selection (which is a good thing).</li>
@ -339,7 +340,7 @@
<span class="co">#&gt; Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></code></pre></div>
</li>
<li><p>Support for custom MDRO guidelines, using the new <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><a href="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
<li><p><code>ggplot()</code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
<li><p><code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
<li>
<p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
@ -396,7 +397,7 @@
<li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
<li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
<li>Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see <code>translate</code>)</li>
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> on any vector of MIC and disk diffusion values</li>
</ul>
</li>
<li>Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the <code>microorganisms</code> data set</li>

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datasets: datasets.html
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
last_built: 2021-04-30T08:14Z
last_built: 2021-05-03T08:19Z
urls:
reference: https://msberends.github.io/AMR//reference
article: https://msberends.github.io/AMR//articles

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<span class="navbar-brand">
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9013</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9015</span>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9010</span>
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@ -344,6 +344,11 @@
<p><img src='figures/lifecycle_maturing.svg' style=margin-bottom:5px /> <br />
The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href='https://github.com/msberends/AMR/issues'>to suggest changes at our repository</a> or <a href='AMR.html'>write us an email (see section 'Contact Us')</a>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on Our Website!</h2>
<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>custom_eucast_rules</span><span class='op'>(</span><span class='va'>AMC</span> <span class='op'>==</span> <span class='st'>"R"</span> <span class='op'>&amp;</span> <span class='va'>genus</span> <span class='op'>==</span> <span class='st'>"Klebsiella"</span> <span class='op'>~</span> <span class='va'>aminopenicillins</span> <span class='op'>==</span> <span class='st'>"R"</span>,

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</button>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9013</span>
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</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9013</span>
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</span>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9014</span>
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<h1>Italicise Taxonomic Families, Genera, Species, Subspecies</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/italicise_taxonomy.R'><code>R/italicise_taxonomy.R</code></a></small>
<div class="hidden name"><code>italicise_taxonomy.Rd</code></div>
</div>
<div class="ref-description">
<p>According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.</p>
</div>
<pre class="usage"><span class='fu'>italicise_taxonomy</span><span class='op'>(</span><span class='va'>string</span>, type <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"markdown"</span>, <span class='st'>"ansi"</span><span class='op'>)</span><span class='op'>)</span>
<span class='fu'>italicize_taxonomy</span><span class='op'>(</span><span class='va'>string</span>, type <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"markdown"</span>, <span class='st'>"ansi"</span><span class='op'>)</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>string</th>
<td><p>a character (vector)</p></td>
</tr>
<tr>
<th>type</th>
<td><p>type of conversion of the taxonomic names, either "markdown" or "ansi", see <em>Details</em></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>This function finds the taxonomic names and makes them italic based on the <a href='microorganisms.html'>microorganisms</a> data set.</p>
<p>The taxonomic names can be italicised using markdown (the default) by adding <code><a href='https://rdrr.io/r/base/Arithmetic.html'>*</a></code> before and after the taxonomic names, or using ANSI colours by adding <code>\033[3m</code> before and <code>\033[23m</code> after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.</p>
<p>This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".</p>
<h2 class="hasAnchor" id="maturing-lifecycle"><a class="anchor" href="#maturing-lifecycle"></a>Maturing Lifecycle</h2>
<p><img src='figures/lifecycle_maturing.svg' style=margin-bottom:5px /> <br />
The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href='https://github.com/msberends/AMR/issues'>to suggest changes at our repository</a> or <a href='AMR.html'>write us an email (see section 'Contact Us')</a>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on Our Website!</h2>
<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='fu'>italicise_taxonomy</span><span class='op'>(</span><span class='st'>"An overview of Staphylococcus aureus isolates"</span><span class='op'>)</span>
<span class='fu'>italicise_taxonomy</span><span class='op'>(</span><span class='st'>"An overview of S. aureus isolates"</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/cat.html'>cat</a></span><span class='op'>(</span><span class='fu'>italicise_taxonomy</span><span class='op'>(</span><span class='st'>"An overview of S. aureus isolates"</span>, type <span class='op'>=</span> <span class='st'>"ansi"</span><span class='op'>)</span><span class='op'>)</span>
</pre>
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</div>

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@ -100,6 +100,11 @@ It is possible to define antibiotic groups instead of single antibiotics for the
The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
}
\section{Read more on Our Website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\examples{
x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/italicise_taxonomy.R
\name{italicise_taxonomy}
\alias{italicise_taxonomy}
\alias{italicize_taxonomy}
\title{Italicise Taxonomic Families, Genera, Species, Subspecies}
\usage{
italicise_taxonomy(string, type = c("markdown", "ansi"))
italicize_taxonomy(string, type = c("markdown", "ansi"))
}
\arguments{
\item{string}{a character (vector)}
\item{type}{type of conversion of the taxonomic names, either "markdown" or "ansi", see \emph{Details}}
}
\description{
According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
}
\details{
This function finds the taxonomic names and makes them italic based on the \link{microorganisms} data set.
The taxonomic names can be italicised using markdown (the default) by adding \code{*} before and after the taxonomic names, or using ANSI colours by adding \verb{\\033[3m} before and \verb{\\033[23m} after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.
This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
}
\section{Maturing Lifecycle}{
\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:5px} \cr}
The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
}
\section{Read more on Our Website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\examples{
italicise_taxonomy("An overview of Staphylococcus aureus isolates")
italicise_taxonomy("An overview of S. aureus isolates")
cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
}

3
pkgdown/extra.js
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@ -53,6 +53,9 @@ $(document).ready(function() {
$("pre.examples").html($("pre.examples").html().replaceAll("# }", ""));
}
// remove leading newline in code examples on changelog
$("body .template-news").html($("body .template-news").html().replaceAll('sourceCode R">\n<span', 'sourceCode R"><span'));
// PR for 'R for Data Science' on How To pages
if ($(".template-article").length > 0) {
$('#pkgdown-sidebar').prepend(