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(v1.4.0.9008) like variations

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dr. M.S. (Matthijs) Berends 2020-10-26 12:23:03 +01:00
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commit 760d69a3e0
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 1.4.0.9007
Date: 2020-10-21
Version: 1.4.0.9008
Date: 2020-10-26
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

2
NAMESPACE
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@ -65,6 +65,8 @@ S3method(unique,mo)
S3method(unique,rsi)
export("%like%")
export("%like_case%")
export("%not_like%")
export("%not_like_case%")
export(ab_atc)
export(ab_atc_group1)
export(ab_atc_group2)

8
NEWS.md
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@ -1,17 +1,19 @@
# AMR 1.4.0.9007
## <small>Last updated: 21 October 2020</small>
# AMR 1.4.0.9008
## <small>Last updated: 26 October 2020</small>
### New
* Functions `is_gram_negative()` and `is_gram_positive()` as wrappers around `mo_gramstain()`. They always return `TRUE` or `FALSE`, thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
* Functions `%not_like%` and `%like_perl%` as wrappers around `%like%`.
* Functions `%not_like%` and `%not_like_case%` as wrappers around `%like%` and `%like_case%`. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, etc.
### Changed
* For all function parameters in the code, it is now defined what the exact type of user input should be (inspired by the [`typed`](https://github.com/moodymudskipper/typed) package). If the user input for a certain function does not meet the requirements for a specific parameter (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 400 arguments were defined.
* Deprecated function `p_symbol()` that not really fits the scope of this package. It will be removed in a future version. See [here](https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R) for the source code to preserve it.
* Better determination of disk zones and MIC values when running `as.rsi()` on a data.frame
* Updated coagulase-negative staphylococci with Becker *et al.* 2020 (PMID 32056452), meaning that the species *S. argensis*, *S. caeli*, *S. debuckii*, *S. edaphicus* and *S. pseudoxylosus* are now all considered CoNS
* Fix for using parameter `reference_df` in `as.mo()` and `mo_*()` functions that contain old microbial codes (from previous package versions)
### Other
* All messages thrown by this package now have correct line breaks
* More extensive unit tests
# AMR 1.4.0

83
R/aa_helper_functions.R
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@ -71,7 +71,42 @@ addin_insert_in <- function() {
# No export, no Rd
addin_insert_like <- function() {
import_fn("insertText", "rstudioapi")(" %like% ")
stop_ifnot_installed("rstudioapi")
# we want Ctrl/Cmd + L to iterate over %like%, %not_like% and %like_case%, so determine context first
getSourceEditorContext <- import_fn("getSourceEditorContext", "rstudioapi")
insertText <- import_fn("insertText", "rstudioapi")
modifyRange <- import_fn("insertText", "rstudioapi")
document_range <- import_fn("document_range", "rstudioapi")
document_position <- import_fn("document_position", "rstudioapi")
# setSelectionRanges <- import_fn("setSelectionRanges", "rstudioapi")
context <- getSourceEditorContext()
current_row <- context$selection[[1]]$range$end[1]
current_col <- context$selection[[1]]$range$end[2]
current_row_txt <- context$contents[current_row]
pos_preceded_by <- function(txt) {
substr(current_row_txt, current_col - nchar(txt), current_col) == txt
}
replace_pos <- function(old, with) {
modifyRange(document_range(document_position(current_row, current_col - nchar(old)),
document_position(current_row, current_col)),
text = with,
id = context$id)
}
if (pos_preceded_by(" %like% ")) {
replace_pos(" %like% ", with = " %not_like% ")
} else if (pos_preceded_by(" %not_like% ")) {
replace_pos(" %not_like% ", with = " %like_case% ")
} else if (pos_preceded_by(" %like_case% ")) {
replace_pos(" %like_case% ", with = " %not_like_case% ")
} else if (pos_preceded_by(" %not_like_case% ")) {
replace_pos(" %not_like_case% ", with = " %like% ")
} else {
insertText(" %like% ")
}
}
check_dataset_integrity <- function() {
@ -231,6 +266,52 @@ import_fn <- function(name, pkg, error_on_fail = TRUE) {
})
}
# this alternative to the message() function:
# - wraps text to never break lines within words
# - ignores formatted text while wrapping
# - adds indentation dependent on the type of message (like NOTE)
# - add additional formatting functions like blue or bold text
message_ <- function(..., appendLF = TRUE, add_fn = list(font_blue)) {
msg <- paste0(c(...), collapse = "")
# we need to correct for already applied style, that adds text like "\033[31m\"
msg_stripped <- font_stripstyle(msg)
# where are the spaces now?
msg_stripped_wrapped <- paste0(strwrap(msg_stripped,
simplify = TRUE,
width = 0.95 * getOption("width")),
collapse = "\n")
msg_stripped_spaces <- which(unlist(strsplit(msg_stripped, "")) == " ")
msg_stripped_wrapped_spaces <- which(unlist(strsplit(msg_stripped_wrapped, "")) == " ")
# so these are the indices of spaces that need to be replaced
replace_spaces <- which(!msg_stripped_spaces %in% msg_stripped_wrapped_spaces)
# put it together
msg <- unlist(strsplit(msg, " "))
msg[replace_spaces] <- paste0(msg[replace_spaces], "\n")
msg <- paste0(msg, collapse = " ")
msg <- gsub("\n ", "\n", msg, fixed = TRUE)
if (msg_stripped %like% "^NOTE: ") {
indentation <- 6
} else {
indentation <- 0
}
msg <- gsub("\n", paste0("\n", strrep(" ", indentation)), msg, fixed = TRUE)
if (length(add_fn) > 0) {
if (!is.list(add_fn)) {
add_fn <- list(add_fn)
}
for (i in seq_len(length(add_fn))) {
msg <- add_fn[[i]](msg)
}
}
message(msg, appendLF = appendLF)
}
# this alternative to the stop() function:
# - adds the function name where the error was thrown
# - wraps text to never break lines within words
stop_ <- function(..., call = TRUE) {
msg <- paste0(c(...), collapse = "")
if (!isFALSE(call)) {

13
R/like.R
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@ -23,7 +23,7 @@
# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Pattern Matching
#' Pattern matching with keyboard shortcut
#'
#' Convenient wrapper around [grep()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
#' @inheritSection lifecycle Stable lifecycle
@ -41,9 +41,9 @@
#' * Checks if `pattern` is a regular expression and sets `fixed = TRUE` if not, to greatly improve speed
#' * Tries again with `perl = TRUE` if regex fails
#'
#' Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like `Ctrl+Shift+L` or `Cmd+Shift+L` (see `Tools` > `Modify Keyboard Shortcuts...`).
#' Using RStudio? This function can also be inserted in your code from the Addins menu and can have its own Keyboard Shortcut like `Ctrl+Shift+L` or `Cmd+Shift+L` (see `Tools` > `Modify Keyboard Shortcuts...`). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, then ` %like_case% `, then ` %not_like_case% ` and then back to ` %like% `.
#'
#' The `"%not_like%"` and `"%like_perl%"` functions are wrappers around `"%like%"`.
#' The `"%not_like%"` and `"%not_like_case%"` functions are wrappers around `"%like%"` and `"%like_case%"`.
#' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/master/R/like.R)
#' @seealso [grep()]
#' @inheritSection AMR Read more on our website!
@ -168,8 +168,15 @@ like <- function(x, pattern, ignore.case = TRUE) {
like(x, pattern, ignore.case = FALSE)
}
#' @rdname like
#' @export
"%not_like_case%" <- function(x, pattern) {
meet_criteria(x, allow_NA = TRUE)
meet_criteria(pattern, allow_NA = FALSE)
!like(x, pattern, ignore.case = FALSE)
}
"%like_perl%" <- function(x, pattern) {
meet_criteria(x, allow_NA = TRUE)
meet_criteria(pattern, allow_NA = FALSE)

19
R/mo.R
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@ -221,7 +221,9 @@ as.mo <- function(x,
suppressWarnings(
y <- data.frame(x = x, stringsAsFactors = FALSE) %pm>%
pm_left_join(reference_df, by = "x") %pm>%
pm_pull("mo")
pm_pull("mo") %pm>%
# run as.mo() for when using old microbial codes
as.mo()
)
} else if (all(x[!is.na(x)] %in% MO_lookup$mo)
@ -388,7 +390,6 @@ exec_as.mo <- function(x,
mo = character(0),
candidates = character(0),
stringsAsFactors = FALSE)
old_mo_warning <- FALSE
x_input <- x
# already strip leading and trailing spaces
@ -407,12 +408,15 @@ exec_as.mo <- function(x,
mo_source_isvalid(reference_df)
reference_df <- reference_df %pm>% pm_filter(!is.na(mo))
# keep only first two columns, second must be mo
# keep only first two columns, second must be named "mo"
if (colnames(reference_df)[1] == "mo") {
reference_df <- reference_df[, c(2, 1)]
} else {
reference_df <- reference_df[, c(1, 2)]
}
# some microbial codes might be old
reference_df$mo <- as.mo(reference_df$mo)
colnames(reference_df)[1] <- "x"
# remove factors, just keep characters
suppressWarnings(
@ -1529,11 +1533,6 @@ exec_as.mo <- function(x,
x <- structure(x, uncertainties = uncertainties)
}
if (old_mo_warning == TRUE & property != "mo") {
warning("The input contained old microorganism IDs from previous versions of this package.\nPlease use `as.mo()` on these old IDs to transform them to the new format.\nSUPPORT FOR THIS WILL BE DROPPED IN A FUTURE VERSION.", call. = FALSE)
}
x
}
@ -1934,7 +1933,9 @@ replace_old_mo_codes <- function(x, property) {
# assign on places where a match was found
x[which(!is.na(matched))] <- mo_new[which(!is.na(matched))]
if (property != "mo") {
message(font_blue("NOTE: Old microbial codes (from previous package versions) were replaced with current codes used by this package.\n Please update your MO codes with as.mo()." ))
message_(font_blue("NOTE: The input contained old microbial codes (from previous package versions). Please update your MO codes with as.mo()."))
} else {
message_(font_blue("NOTE:", length(matched), "old microbial codes (from previous package versions) were updated to current used codes."))
}
}
x

24
R/mo_property.R
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@ -29,7 +29,7 @@
#' @inheritSection lifecycle Stable lifecycle
#' @param x any character (vector) that can be coerced to a valid microorganism code with [as.mo()]
#' @param property one of the column names of the [microorganisms] data set or `"shortname"`
#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
#' @param ... other parameters passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern'
#' @param open browse the URL using [utils::browseURL()]
#' @details All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for [mo_ref()], [mo_authors()] and [mo_year()]. Please refer to this example, knowing that *Escherichia blattae* was renamed to *Shimwellia blattae* in 2010:
@ -310,18 +310,28 @@ mo_gramstain <- function(x, language = get_locale(), ...) {
#' @rdname mo_property
#' @export
is_gram_negative <- function(x, ...) {
is_gram_negative <- function(x, language = get_locale(), ...) {
meet_criteria(x, allow_NA = TRUE)
grams <- mo_gramstain(x, language = NULL, ...)
"Gram-negative" == grams & !is.na(grams)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
x.mo <- as.mo(x, language = language, ...)
metadata <- get_mo_failures_uncertainties_renamed()
grams <- mo_gramstain(x.mo, language = NULL)
load_mo_failures_uncertainties_renamed(metadata)
grams == "Gram-negative" & !is.na(grams)
}
#' @rdname mo_property
#' @export
is_gram_positive <- function(x, ...) {
is_gram_positive <- function(x, language = get_locale(), ...) {
meet_criteria(x, allow_NA = TRUE)
grams <- mo_gramstain(x, language = NULL, ...)
"Gram-positive" == grams & !is.na(grams)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
x.mo <- as.mo(x, language = language, ...)
metadata <- get_mo_failures_uncertainties_renamed()
grams <- mo_gramstain(x.mo, language = NULL)
load_mo_failures_uncertainties_renamed(metadata)
grams == "Gram-positive" & !is.na(grams)
}
#' @rdname mo_property

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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

54
docs/articles/PCA.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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,7 +187,8 @@
</header><script src="PCA_files/header-attrs-2.3/header-attrs.js"></script><script src="PCA_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="PCA_files/accessible-code-block-0.0.1/empty-anchor.js"></script><link href="PCA_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="PCA_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
@ -210,9 +211,9 @@
<a href="#transforming" class="anchor"></a>Transforming</h1>
<p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p>
<div class="sourceCode" id="cb1"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></span>)
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>)
<span class="fu"><a href="https://tibble.tidyverse.org/reference/glimpse.html">glimpse</a></span>(<span class="kw">example_isolates</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>
<span class="fu"><a href="https://tibble.tidyverse.org/reference/glimpse.html">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co"># Rows: 2,000</span>
<span class="co"># Columns: 49</span>
<span class="co"># $ date &lt;date&gt; 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002…</span>
@ -263,18 +264,17 @@
<span class="co"># $ CHL &lt;rsi&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ COL &lt;rsi&gt; NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, …</span>
<span class="co"># $ MUP &lt;rsi&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ RIF &lt;rsi&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span>
</pre></div>
<span class="co"># $ RIF &lt;rsi&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span></pre></div>
<p>Now to transform this to a data set with only resistance percentages per taxonomic order and genus:</p>
<div class="sourceCode" id="cb2"><pre class="downlit">
<span class="kw">resistance_data</span> <span class="op">&lt;-</span> <span class="kw">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(order = <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="kw">mo</span>), <span class="co"># group on anything, like order</span>
genus = <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="kw">mo</span>)) <span class="op">%&gt;%</span> <span class="co"># and genus as we do here</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">summarise_if</a></span>(<span class="kw">is.rsi</span>, <span class="kw">resistance</span>) <span class="op">%&gt;%</span> <span class="co"># then get resistance of all drugs</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">order</span>, <span class="kw">genus</span>, <span class="kw">AMC</span>, <span class="kw">CXM</span>, <span class="kw">CTX</span>,
<span class="kw">CAZ</span>, <span class="kw">GEN</span>, <span class="kw">TOB</span>, <span class="kw">TMP</span>, <span class="kw">SXT</span>) <span class="co"># and select only relevant columns</span>
<span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span> <span class="co"># and genus as we do here</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">summarise_if</a></span><span class="op">(</span><span class="va">is.rsi</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op">%&gt;%</span> <span class="co"># then get resistance of all drugs</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>,
<span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span><span class="op">)</span> <span class="co"># and select only relevant columns</span>
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="kw">resistance_data</span>)
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
<span class="co"># # A tibble: 6 x 10</span>
<span class="co"># # Groups: order [2]</span>
<span class="co"># order genus AMC CXM CTX CAZ GEN TOB TMP SXT</span>
@ -284,46 +284,40 @@
<span class="co"># 3 Actinomycetales Cutibacterium NA NA NA NA NA NA NA NA</span>
<span class="co"># 4 Actinomycetales Dermabacter NA NA NA NA NA NA NA NA</span>
<span class="co"># 5 Actinomycetales Micrococcus NA NA NA NA NA NA NA NA</span>
<span class="co"># 6 Actinomycetales Rothia NA NA NA NA NA NA NA NA</span>
</pre></div>
<span class="co"># 6 Actinomycetales Rothia NA NA NA NA NA NA NA NA</span></pre></div>
</div>
<div id="perform-principal-component-analysis" class="section level1">
<h1 class="hasAnchor">
<a href="#perform-principal-component-analysis" class="anchor"></a>Perform principal component analysis</h1>
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p>
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="kw">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span>(<span class="kw">resistance_data</span>)
<span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
<span class="co"># NOTE: Columns selected for PCA: AMC CXM CTX CAZ GEN TOB TMP SXT.</span>
<span class="co"># Total observations available: 7.</span>
</pre></div>
<span class="co"># Total observations available: 7.</span></pre></div>
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html">summary()</a></code> function:</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">pca_result</span>)
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
<span class="co"># Importance of components:</span>
<span class="co"># PC1 PC2 PC3 PC4 PC5 PC6 PC7</span>
<span class="co"># Standard deviation 2.154 1.6807 0.61365 0.33902 0.20757 0.03136 1.733e-16</span>
<span class="co"># Proportion of Variance 0.580 0.3531 0.04707 0.01437 0.00539 0.00012 0.000e+00</span>
<span class="co"># Cumulative Proportion 0.580 0.9331 0.98012 0.99449 0.99988 1.00000 1.000e+00</span>
</pre></div>
<span class="co"># Cumulative Proportion 0.580 0.9331 0.98012 0.99449 0.99988 1.00000 1.000e+00</span></pre></div>
<p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p>
</div>
<div id="plotting-the-results" class="section level1">
<h1 class="hasAnchor">
<a href="#plotting-the-results" class="anchor"></a>Plotting the results</h1>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span>(<span class="kw">pca_result</span>)
</pre></div>
<span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
<p>But we can’t see the explanation of the points. Perhaps this works better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that automatically adds the right labels and even groups:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="kw">pca_result</span>)
</pre></div>
<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
<p>You can also print an ellipse per group, and edit the appearance:</p>
<div class="sourceCode" id="cb7"><pre class="downlit">
<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="kw">pca_result</span>, ellipse = <span class="fl">TRUE</span>) <span class="op">+</span>
<span class="kw">ggplot2</span>::<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span>(title = <span class="st">"An AMR/PCA biplot!"</span>)
</pre></div>
<span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span>
<span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
</div>
</div>
@ -343,7 +337,7 @@
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
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docs/articles/SPSS.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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,13 +187,14 @@
</header><script src="SPSS_files/header-attrs-2.3/header-attrs.js"></script><script src="SPSS_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="SPSS_files/accessible-code-block-0.0.1/empty-anchor.js"></script><link href="SPSS_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="SPSS_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">08 October 2020</h4>
<h4 class="date">26 October 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
<div class="hidden name"><code>SPSS.Rmd</code></div>
@ -249,38 +250,37 @@
<p>To demonstrate the first point:</p>
<div class="sourceCode" id="cb1"><pre class="downlit">
<span class="co"># not all values are valid MIC values:</span>
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span>(<span class="fl">0.125</span>)
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="fl">0.125</span><span class="op">)</span>
<span class="co"># Class &lt;mic&gt;</span>
<span class="co"># [1] 0.125</span>
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span>(<span class="st">"testvalue"</span>)
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span><span class="op">(</span><span class="st">"testvalue"</span><span class="op">)</span>
<span class="co"># Class &lt;mic&gt;</span>
<span class="co"># [1] &lt;NA&gt;</span>
<span class="co"># the Gram stain is avaiable for all bacteria:</span>
<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)
<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
<span class="co"># [1] "Gram-negative"</span>
<span class="co"># Klebsiella is intrinsic resistant to amoxicllin, according to EUCAST:</span>
<span class="kw">klebsiella_test</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(mo = <span class="st">"klebsiella"</span>,
amox = <span class="st">"S"</span>,
stringsAsFactors = <span class="fl">FALSE</span>)
<span class="kw">klebsiella_test</span> <span class="co"># (our original data)</span>
<span class="va">klebsiella_test</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="st">"klebsiella"</span>,
amox <span class="op">=</span> <span class="st">"S"</span>,
stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
<span class="va">klebsiella_test</span> <span class="co"># (our original data)</span>
<span class="co"># mo amox</span>
<span class="co"># 1 klebsiella S</span>
<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(<span class="kw">klebsiella_test</span>, info = <span class="fl">FALSE</span>) <span class="co"># (the edited data by EUCAST rules)</span>
<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">klebsiella_test</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> <span class="co"># (the edited data by EUCAST rules)</span>
<span class="co"># mo amox</span>
<span class="co"># 1 klebsiella R</span>
<span class="co"># hundreds of trade names can be translated to a name, trade name or an ATC code:</span>
<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="st">"floxapen"</span>)
<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
<span class="co"># [1] "Flucloxacillin"</span>
<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span>(<span class="st">"floxapen"</span>)
<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
<span class="co"># [1] "floxacillin" "floxapen" "floxapen sodium salt"</span>
<span class="co"># [4] "fluclox" "flucloxacilina" "flucloxacillin" </span>
<span class="co"># [7] "flucloxacilline" "flucloxacillinum" "fluorochloroxacillin"</span>
<span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span>(<span class="st">"floxapen"</span>)
<span class="co"># [1] "J01CF05"</span>
</pre></div>
<span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span><span class="op">(</span><span class="st">"floxapen"</span><span class="op">)</span>
<span class="co"># [1] "J01CF05"</span></pre></div>
</div>
<div id="import-data-from-spsssasstata" class="section level2">
<h2 class="hasAnchor">
@ -294,10 +294,10 @@
<p>If additional packages are needed, RStudio will ask you if they should be installed on beforehand.</p>
<p>In the the window that opens, you can define all options (parameters) that should be used for import and you’re ready to go:</p>
<p><img src="https://github.com/msberends/AMR/raw/master/docs/import2.png"></p>
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>.</p>
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code>as_factor()</code>.</p>
<p>The difference is this:</p>
<div class="sourceCode" id="cb2"><pre class="downlit">
<span class="kw">SPSS_data</span>
<span class="va">SPSS_data</span>
<span class="co"># # A tibble: 4,203 x 4</span>
<span class="co"># v001 sex status statusage</span>
<span class="co"># &lt;dbl&gt; &lt;dbl+lbl&gt; &lt;dbl+lbl&gt; &lt;dbl&gt;</span>
@ -313,7 +313,7 @@
<span class="co"># 10 10018 0 1 66.6</span>
<span class="co"># # … with 4,193 more rows</span>
<span class="fu">as_factor</span>(<span class="kw">SPSS_data</span>)
<span class="fu">as_factor</span><span class="op">(</span><span class="va">SPSS_data</span><span class="op">)</span>
<span class="co"># # A tibble: 4,203 x 4</span>
<span class="co"># v001 sex status statusage</span>
<span class="co"># &lt;dbl&gt; &lt;fct&gt; &lt;fct&gt; &lt;dbl&gt;</span>
@ -327,8 +327,7 @@
<span class="co"># 8 10011 Male alive 73.1</span>
<span class="co"># 9 10017 Male alive 56.7</span>
<span class="co"># 10 10018 Female alive 66.6</span>
<span class="co"># # … with 4,193 more rows</span>
</pre></div>
<span class="co"># # … with 4,193 more rows</span></pre></div>
</div>
<div id="base-r" class="section level3">
<h3 class="hasAnchor">
@ -336,10 +335,9 @@
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/">great <code>haven</code> package</a> yourself:</p>
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="co"># download and install the latest version:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span>(<span class="st">"haven"</span>)
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
<span class="co"># load the package you just installed:</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://haven.tidyverse.org">haven</a></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">haven</span><span class="op">)</span> </pre></div>
<p>You can now import files as follows:</p>
<div id="spss" class="section level4">
<h4 class="hasAnchor">
@ -347,23 +345,21 @@
<p>To read files from SPSS into R:</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="co"># read any SPSS file based on file extension (best way):</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_spss</a></span>(file = <span class="st">"path/to/file"</span>)
<span class="fu">read_spss</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
<span class="co"># read .sav or .zsav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_sav</a></span>(file = <span class="st">"path/to/file"</span>)
<span class="fu">read_sav</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
<span class="co"># read .por file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_por</a></span>(file = <span class="st">"path/to/file"</span>)
</pre></div>
<p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>, as mentioned above.</p>
<span class="fu">read_por</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></pre></div>
<p>Do not forget about <code>as_factor()</code>, as mentioned above.</p>
<p>To export your R objects to the SPSS file format:</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="co"># save as .sav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>)
<span class="fu">write_sav</span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
<span class="co"># save as compressed .zsav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>, compress = <span class="fl">TRUE</span>)
</pre></div>
<span class="fu">write_sav</span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, compress <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></pre></div>
</div>
<div id="sas" class="section level4">
<h4 class="hasAnchor">
@ -371,20 +367,18 @@
<p>To read files from SAS into R:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="co"># read .sas7bdat + .sas7bcat files:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">read_sas</a></span>(data_file = <span class="st">"path/to/file"</span>, catalog_file = <span class="kw">NULL</span>)
<span class="fu">read_sas</span><span class="op">(</span>data_file <span class="op">=</span> <span class="st">"path/to/file"</span>, catalog_file <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span>
<span class="co"># read SAS transport files (version 5 and version 8):</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">read_xpt</a></span>(file = <span class="st">"path/to/file"</span>)
</pre></div>
<span class="fu">read_xpt</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span></pre></div>
<p>To export your R objects to the SAS file format:</p>
<div class="sourceCode" id="cb7"><pre class="downlit">
<span class="co"># save as regular SAS file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">write_sas</a></span>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>)
<span class="fu">write_sas</span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span><span class="op">)</span>
<span class="co"># the SAS transport format is an open format </span>
<span class="co"># (required for submission of the data to the FDA)</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">write_xpt</a></span>(data = <span class="kw">yourdata</span>, path = <span class="st">"path/to/file"</span>, version = <span class="fl">8</span>)
</pre></div>
<span class="fu">write_xpt</span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"path/to/file"</span>, version <span class="op">=</span> <span class="fl">8</span><span class="op">)</span></pre></div>
</div>
<div id="stata" class="section level4">
<h4 class="hasAnchor">
@ -392,17 +386,15 @@
<p>To read files from Stata into R:</p>
<div class="sourceCode" id="cb8"><pre class="downlit">
<span class="co"># read .dta file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_stata</a></span>(file = <span class="st">"/path/to/file"</span>)
<span class="fu">read_stata</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span>
<span class="co"># works exactly the same:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_dta</a></span>(file = <span class="st">"/path/to/file"</span>)
</pre></div>
<span class="fu">read_dta</span><span class="op">(</span>file <span class="op">=</span> <span class="st">"/path/to/file"</span><span class="op">)</span></pre></div>
<p>To export your R objects to the Stata file format:</p>
<div class="sourceCode" id="cb9"><pre class="downlit">
<span class="co"># save as .dta file, Stata version 14:</span>
<span class="co"># (supports Stata v8 until v15 at the time of writing)</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">write_dta</a></span>(data = <span class="kw">yourdata</span>, path = <span class="st">"/path/to/file"</span>, version = <span class="fl">14</span>)
</pre></div>
<span class="fu">write_dta</span><span class="op">(</span>data <span class="op">=</span> <span class="va">yourdata</span>, path <span class="op">=</span> <span class="st">"/path/to/file"</span>, version <span class="op">=</span> <span class="fl">14</span><span class="op">)</span></pre></div>
</div>
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@ -423,7 +415,7 @@
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
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document.addEventListener('DOMContentLoaded', function() {
// Do nothing if AnchorJS is used
if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
return;
}
const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
// Do nothing if sections are already anchored
if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
return null;
}
// Use section id when pandoc runs with --section-divs
const section_id = function(x) {
return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
? x.id : '');
};
// Add anchors
h.forEach(function(x) {
const id = x.id || section_id(x.parentElement);
if (id === '') {
return null;
}
let anchor = document.createElement('a');
anchor.href = '#' + id;
anchor.classList = ['anchor-section'];
x.classList.add('hasAnchor');
x.appendChild(anchor);
});
});

47
docs/articles/WHONET.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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,7 +187,8 @@
</header><script src="WHONET_files/header-attrs-2.3/header-attrs.js"></script><script src="WHONET_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="WHONET_files/accessible-code-block-0.0.1/empty-anchor.js"></script><link href="WHONET_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="WHONET_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to work with WHONET data</h1>
@ -206,9 +207,8 @@
<p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p>
<p>An example syntax could look like this:</p>
<div class="sourceCode" id="cb1"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://readxl.tidyverse.org">readxl</a></span>)
<span class="kw">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span>(path = <span class="st">"path/to/your/file.xlsx"</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://readxl.tidyverse.org">readxl</a></span><span class="op">)</span>
<span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></pre></div>
<p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example data set <code>WHONET</code></a>. We will use it for this analysis.</p>
</div>
<div id="preparation" class="section level3">
@ -216,11 +216,10 @@
<a href="#preparation" class="anchor"></a>Preparation</h3>
<p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="uri">https://www.tidyverse.org/</a>.</p>
<div class="sourceCode" id="cb2"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>) <span class="co"># part of tidyverse</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span>) <span class="co"># part of tidyverse</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></span>) <span class="co"># this package</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://github.com/msberends/cleaner">cleaner</a></span>) <span class="co"># to create frequency tables</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> <span class="co"># part of tidyverse</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="http://ggplot2.tidyverse.org">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</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="co"># this package</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://github.com/msberends/cleaner">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></pre></div>
<p>We will have to transform some variables to simplify and automate the analysis:</p>
<ul>
<li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our Catalogue of Life reference data set</a>, which contains all ~70,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
@ -228,19 +227,17 @@
</ul>
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="co"># transform variables</span>
<span class="kw">data</span> <span class="op">&lt;-</span> <span class="kw">WHONET</span> <span class="op">%&gt;%</span>
<span class="va">data</span> <span class="op">&lt;-</span> <span class="va">WHONET</span> <span class="op">%&gt;%</span>
<span class="co"># get microbial ID based on given organism</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(mo = <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="kw">Organism</span>)) <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">Organism</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span>(<span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="kw">AMP_ND10</span><span class="op">:</span><span class="kw">CIP_EE</span>), <span class="kw">as.rsi</span>)
</pre></div>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></pre></div>
<p>No errors or warnings, so all values are transformed succesfully.</p>
<p>We also created a package dedicated to data cleaning and checking, called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function can be used to create frequency tables.</p>
<p>So let’s check our data, with a couple of frequency tables:</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
<span class="kw">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="kw">mo</span>), nmax = <span class="fl">10</span>)
</pre></div>
<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</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">mo</span><span class="op">)</span>, nmax <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 500<br>
@ -344,15 +341,16 @@ Longest: 40</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="co"># our transformed antibiotic columns</span>
<span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span>
<span class="kw">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="kw">AMC_ND2</span>)
</pre></div>
<span class="va">data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">AMC_ND2</span><span class="op">)</span></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 500<br>
Levels: 3: S &lt; I &lt; R<br>
Available: 481 (96.2%, NA: 19 = 3.8%)<br>
Unique: 3</p>
<p>%SI: 78.59%</p>
<p>Drug: Amoxicillin/clavulanic acid (AMC, J01CR02)<br>
Drug group: Beta-lactams/penicillins<br>
%SI: 78.59%</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
@ -395,11 +393,10 @@ Unique: 3</p>
<a href="#a-first-glimpse-at-results" class="anchor"></a>A first glimpse at results</h3>
<p>An easy <code>ggplot</code> will already give a lot of information, using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="kw">data</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="kw">Country</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="kw">Country</span>, <span class="kw">AMP_ND2</span>, <span class="kw">AMC_ED20</span>, <span class="kw">CAZ_ED10</span>, <span class="kw">CIP_ED5</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span>(translate_ab = <span class="st">'ab'</span>, facet = <span class="st">"Country"</span>, datalabels = <span class="fl">FALSE</span>)
</pre></div>
<span class="va">data</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">'ab'</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></pre></div>
<p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
</div>
</div>
@ -417,7 +414,7 @@ Unique: 3</p>
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>

4
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@ -0,0 +1,4 @@
/* Styles for section anchors */
a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
a.anchor-section::before {content: '#';}
.hasAnchor:hover a.anchor-section {visibility: visible;}

33
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@ -0,0 +1,33 @@
// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
document.addEventListener('DOMContentLoaded', function() {
// Do nothing if AnchorJS is used
if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
return;
}
const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
// Do nothing if sections are already anchored
if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
return null;
}
// Use section id when pandoc runs with --section-divs
const section_id = function(x) {
return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
? x.id : '');
};
// Add anchors
h.forEach(function(x) {
const id = x.id || section_id(x.parentElement);
if (id === '') {
return null;
}
let anchor = document.createElement('a');
anchor.href = '#' + id;
anchor.classList = ['anchor-section'];
x.classList.add('hasAnchor');
x.appendChild(anchor);
});
});

BIN
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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">1.4.0.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,7 +187,8 @@
</header><script src="benchmarks_files/header-attrs-2.4/header-attrs.js"></script><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><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">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Benchmarks</h1>
@ -227,20 +228,34 @@
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">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") 12.0 13.0 25.0 15.0 40.0 43 10</span>
<span class="co"># as.mo("stau") 210.0 220.0 230.0 230.0 250.0 260 10</span>
<span class="co"># as.mo("STAU") 210.0 210.0 230.0 250.0 250.0 260 10</span>
<span class="co"># as.mo("staaur") 12.0 13.0 24.0 14.0 41.0 42 10</span>
<span class="co"># as.mo("STAAUR") 13.0 13.0 22.0 14.0 39.0 42 10</span>
<span class="co"># as.mo("S. aureus") 27.0 30.0 42.0 41.0 54.0 61 10</span>
<span class="co"># as.mo("S aureus") 24.0 29.0 45.0 43.0 60.0 66 10</span>
<span class="co"># as.mo("Staphylococcus aureus") 2.1 2.5 4.9 2.5 2.9 26 10</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 820.0 860.0 880.0 880.0 900.0 970 10</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 330.0 340.0 370.0 370.0 390.0 420 10</span>
<span class="co"># as.mo("MRSA") 11.0 13.0 22.0 14.0 41.0 44 10</span>
<span class="co"># as.mo("VISA") 21.0 22.0 48.0 47.0 51.0 140 10</span>
<span class="co"># as.mo("VRSA") 19.0 20.0 23.0 21.0 22.0 47 10</span></pre></div>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("sau") 26.0 26.0 50.0 26.0 26.0 180</span>
<span class="co"># as.mo("stau") 430.0 430.0 470.0 440.0 490.0 630</span>
<span class="co"># as.mo("STAU") 430.0 440.0 470.0 500.0 500.0 500</span>
<span class="co"># as.mo("staaur") 26.0 26.0 32.0 26.0 26.0 76</span>
<span class="co"># as.mo("STAAUR") 26.0 26.0 44.0 26.0 81.0 83</span>
<span class="co"># as.mo("S. aureus") 60.0 60.0 77.0 61.0 110.0 120</span>
<span class="co"># as.mo("S aureus") 60.0 61.0 94.0 110.0 120.0 120</span>
<span class="co"># as.mo("Staphylococcus aureus") 4.1 4.1 9.6 4.1 4.2 59</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 2200.0 2200.0 2200.0 2200.0 2300.0 2300</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 760.0 800.0 810.0 800.0 810.0 840</span>
<span class="co"># as.mo("MRSA") 26.0 26.0 37.0 26.0 26.0 83</span>
<span class="co"># as.mo("VISA") 42.0 42.0 59.0 42.0 92.0 97</span>
<span class="co"># as.mo("VRSA") 42.0 42.0 68.0 67.0 92.0 97</span>
<span class="co"># neval</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="562.5"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations can take up to 500-1000 times as much time.</p>
<p>To improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
@ -270,8 +285,8 @@
<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="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 150 154 195 179 197 301 10</span></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.179 seconds. You only lose time on your unique input values.</p>
<span class="co"># mo_name(x) 308 326 399 331 370 676 10</span></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.331 seconds. You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -285,10 +300,10 @@
<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="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 7.11 7.23 7.79 7.74 8.46 8.54 10</span>
<span class="co"># B 21.40 21.90 30.40 24.00 25.50 60.00 10</span>
<span class="co"># C 1.97 1.98 2.12 2.05 2.34 2.43 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 0.002 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>
<span class="co"># A 16.20 16.20 18.60 17.90 18.90 28.00 10</span>
<span class="co"># B 50.90 51.10 57.70 51.20 53.10 108.00 10</span>
<span class="co"># C 3.58 3.72 4.03 4.06 4.14 4.91 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 0.0041 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">microbenchmark</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>,
@ -302,14 +317,14 @@
<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="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 1.33 1.57 1.70 1.69 1.83 2.18 10</span>
<span class="co"># B 1.62 1.67 5.34 1.70 2.15 36.90 10</span>
<span class="co"># C 1.43 1.55 1.64 1.59 1.70 2.06 10</span>
<span class="co"># D 1.29 1.44 1.53 1.55 1.66 1.70 10</span>
<span class="co"># E 1.31 1.58 1.68 1.65 1.71 2.11 10</span>
<span class="co"># F 1.54 1.61 1.80 1.67 1.86 2.57 10</span>
<span class="co"># G 1.52 1.62 1.73 1.71 1.77 2.04 10</span>
<span class="co"># H 1.40 1.55 1.70 1.65 1.92 2.03 10</span></pre></div>
<span class="co"># A 3.62 3.62 3.66 3.64 3.67 3.80 10</span>
<span class="co"># B 3.57 3.59 3.68 3.64 3.72 4.01 10</span>
<span class="co"># C 3.63 3.64 3.65 3.64 3.67 3.71 10</span>
<span class="co"># D 3.57 3.58 3.62 3.61 3.67 3.69 10</span>
<span class="co"># E 3.56 3.57 3.60 3.59 3.60 3.68 10</span>
<span class="co"># F 3.55 3.58 3.73 3.65 3.85 4.01 10</span>
<span class="co"># G 3.54 3.56 3.62 3.58 3.61 3.93 10</span>
<span class="co"># H 3.53 3.57 3.59 3.58 3.63 3.66 10</span></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 ‘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">
@ -337,13 +352,13 @@
<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="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 14.20 14.66 20.04 15.14 16.90 58.67 100</span>
<span class="co"># de 17.15 17.85 24.30 18.27 20.00 59.17 100</span>
<span class="co"># nl 29.13 30.50 34.60 31.26 32.86 72.63 100</span>
<span class="co"># es 16.95 17.70 22.61 18.35 20.54 59.42 100</span>
<span class="co"># it 17.04 17.60 21.72 18.14 19.60 59.19 100</span>
<span class="co"># fr 16.82 17.52 21.71 18.05 19.63 61.06 100</span>
<span class="co"># pt 16.92 17.58 19.92 18.23 19.19 54.61 100</span></pre></div>
<span class="co"># en 35.85 36.13 41.92 36.29 36.84 318.20 100</span>
<span class="co"># de 42.37 42.67 45.11 42.91 43.19 95.04 100</span>
<span class="co"># nl 70.13 70.65 75.92 70.95 71.50 140.20 100</span>
<span class="co"># es 42.16 42.46 46.88 42.64 43.20 95.37 100</span>
<span class="co"># it 41.85 42.24 46.84 42.40 42.84 95.92 100</span>
<span class="co"># fr 42.13 42.53 48.41 42.71 43.27 95.21 100</span>
<span class="co"># pt 42.25 42.47 48.56 42.71 43.12 96.60 100</span></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>

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/* Styles for section anchors */
a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
a.anchor-section::before {content: '#';}
.hasAnchor:hover a.anchor-section {visibility: visible;}

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// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
document.addEventListener('DOMContentLoaded', function() {
// Do nothing if AnchorJS is used
if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
return;
}
const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
// Do nothing if sections are already anchored
if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
return null;
}
// Use section id when pandoc runs with --section-divs
const section_id = function(x) {
return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
? x.id : '');
};
// Add anchors
h.forEach(function(x) {
const id = x.id || section_id(x.parentElement);
if (id === '') {
return null;
}
let anchor = document.createElement('a');
anchor.href = '#' + id;
anchor.classList = ['anchor-section'];
x.classList.add('hasAnchor');
x.appendChild(anchor);
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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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

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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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,7 +187,8 @@
</header><script src="resistance_predict_files/header-attrs-2.3/header-attrs.js"></script><script src="resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js"></script><link href="resistance_predict_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="resistance_predict_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to predict antimicrobial resistance</h1>
@ -206,13 +207,12 @@
<p>As with many uses in R, we need some additional packages for AMR analysis. Our package works closely together with the <a href="https://www.tidyverse.org">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
<div class="sourceCode" id="cb1"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org">dplyr</a></span>)
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="http://ggplot2.tidyverse.org">ggplot2</a></span>)
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="kw"><a href="https://msberends.github.io/AMR">AMR</a></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>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="http://ggplot2.tidyverse.org">ggplot2</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="co"># (if not yet installed, install with:)</span>
<span class="co"># install.packages(c("tidyverse", "AMR"))</span>
</pre></div>
<span class="co"># install.packages(c("tidyverse", "AMR"))</span></pre></div>
</div>
<div id="prediction-analysis" class="section level2">
<h2 class="hasAnchor">
@ -236,7 +236,7 @@
<pre><code># NOTE: Using column `date` as input for `col_date`.</code></pre>
<p>This text is only a printed summary - the actual result (output) of the function is a <code>data.frame</code> containing for each year: the number of observations, the actual observed resistance, the estimated resistance and the standard error below and above the estimation:</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="kw">predict_TZP</span>
<span class="va">predict_TZP</span>
<span class="co"># year value se_min se_max observations observed estimated</span>
<span class="co"># 1 2002 0.20000000 NA NA 15 0.20000000 0.05616378</span>
<span class="co"># 2 2003 0.06250000 NA NA 32 0.06250000 0.06163839</span>
@ -266,36 +266,31 @@
<span class="co"># 26 2027 0.41315710 0.3244399 0.5018743 NA NA 0.41315710</span>
<span class="co"># 27 2028 0.43730688 0.3418075 0.5328063 NA NA 0.43730688</span>
<span class="co"># 28 2029 0.46175755 0.3597639 0.5637512 NA NA 0.46175755</span>
<span class="co"># 29 2030 0.48639359 0.3782932 0.5944939 NA NA 0.48639359</span>
</pre></div>
<span class="co"># 29 2030 0.48639359 0.3782932 0.5944939 NA NA 0.48639359</span></pre></div>
<p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="fu"><a href="../reference/plot.html">plot</a></span>(<span class="kw">predict_TZP</span>)
</pre></div>
<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
<p>This is the fastest way to plot the result. It automatically adds the right axes, error bars, titles, number of available observations and type of model.</p>
<p>We also support the <code>ggplot2</code> package with our custom function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing plots:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(<span class="kw">predict_TZP</span>)
</pre></div>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
<div class="sourceCode" id="cb7"><pre class="downlit">
<span class="co"># choose for error bars instead of a ribbon</span>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(<span class="kw">predict_TZP</span>, ribbon = <span class="fl">FALSE</span>)
</pre></div>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span>, ribbon <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-2.png" width="720"></p>
<div id="choosing-the-right-model" class="section level3">
<h3 class="hasAnchor">
<a href="#choosing-the-right-model" class="anchor"></a>Choosing the right model</h3>
<p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram-positive bacteria, the spread (i.e. standard error) is enormous:</p>
<div class="sourceCode" id="cb8"><pre class="downlit">
<span class="kw">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="kw">mo</span>, language = <span class="kw">NULL</span>) <span class="op">==</span> <span class="st">"Gram-positive"</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(col_ab = <span class="st">"VAN"</span>, year_min = <span class="fl">2010</span>, info = <span class="fl">FALSE</span>, model = <span class="st">"binomial"</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>()
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
</pre></div>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
<p>Vancomycin resistance could be 100% in ten years, but might also stay around 0%.</p>
<p>You can define the model with the <code>model</code> parameter. The model chosen above is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.</p>
@ -337,28 +332,26 @@
</table>
<p>For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:</p>
<div class="sourceCode" id="cb9"><pre class="downlit">
<span class="kw">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="kw">mo</span>, language = <span class="kw">NULL</span>) <span class="op">==</span> <span class="st">"Gram-positive"</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(col_ab = <span class="st">"VAN"</span>, year_min = <span class="fl">2010</span>, info = <span class="fl">FALSE</span>, model = <span class="st">"linear"</span>) <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>()
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
</pre></div>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"linear"</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
<p>This seems more likely, doesn’t it?</p>
<p>The model itself is also available from the object, as an <code>attribute</code>:</p>
<div class="sourceCode" id="cb10"><pre class="downlit">
<span class="kw">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span>(<span class="kw">predict_TZP</span>)<span class="op">$</span><span class="kw">model</span>
<span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">model</span>)<span class="op">$</span><span class="kw">family</span>
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span>
<span class="co"># </span>
<span class="co"># Family: binomial </span>
<span class="co"># Link function: logit</span>
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="kw">model</span>)<span class="op">$</span><span class="kw">coefficients</span>
<span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span>
<span class="co"># Estimate Std. Error z value Pr(&gt;|z|)</span>
<span class="co"># (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span>
<span class="co"># year 0.09883005 0.02295317 4.305725 1.664395e-05</span>
</pre></div>
<span class="co"># year 0.09883005 0.02295317 4.305725 1.664395e-05</span></pre></div>
</div>
</div>
</div>
@ -378,7 +371,7 @@
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
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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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -187,7 +187,8 @@
</header><script src="welcome_to_AMR_files/header-attrs-2.3/header-attrs.js"></script><script src="welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><script src="welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js"></script><link href="welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet">
<script src="welcome_to_AMR_files/anchor-sections-1.0/anchor-sections.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Welcome to the AMR package</h1>
@ -249,7 +250,7 @@
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>

4
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@ -0,0 +1,4 @@
/* Styles for section anchors */
a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
a.anchor-section::before {content: '#';}
.hasAnchor:hover a.anchor-section {visibility: visible;}

33
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@ -0,0 +1,33 @@
// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
document.addEventListener('DOMContentLoaded', function() {
// Do nothing if AnchorJS is used
if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
return;
}
const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
// Do nothing if sections are already anchored
if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
return null;
}
// Use section id when pandoc runs with --section-divs
const section_id = function(x) {
return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
? x.id : '');
};
// Add anchors
h.forEach(function(x) {
const id = x.id || section_id(x.parentElement);
if (id === '') {
return null;
}
let anchor = document.createElement('a');
anchor.href = '#' + id;
anchor.classList = ['anchor-section'];
x.classList.add('hasAnchor');
x.appendChild(anchor);
});
});

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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
docs/index.html
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@ -43,7 +43,7 @@
</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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

56
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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -236,20 +236,20 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1409007" class="section level1">
<h1 class="page-header" data-toc-text="1.4.0.9007">
<a href="#amr-1409007" class="anchor"></a>AMR 1.4.0.9007<small> Unreleased </small>
<div id="amr-1409008" class="section level1">
<h1 class="page-header" data-toc-text="1.4.0.9008">
<a href="#amr-1409008" class="anchor"></a>AMR 1.4.0.9008<small> Unreleased </small>
</h1>
<div id="last-updated-21-october-2020" class="section level2">
<div id="last-updated-26-october-2020" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-21-october-2020" class="anchor"></a><small>Last updated: 21 October 2020</small>
<a href="#last-updated-26-october-2020" class="anchor"></a><small>Last updated: 26 October 2020</small>
</h2>
<div id="new" class="section level3">
<h3 class="hasAnchor">
<a href="#new" class="anchor"></a>New</h3>
<ul>
<li>Functions <code><a href="../reference/mo_property.html">is_gram_negative()</a></code> and <code><a href="../reference/mo_property.html">is_gram_positive()</a></code> as wrappers around <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code>, thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</li>
<li>Functions <code>%not_like%</code> and <code>%like_perl%</code> as wrappers around <code><a href="../reference/like.html">%like%</a></code>.</li>
<li>Functions <code><a href="../reference/like.html">%not_like%</a></code> and <code><a href="../reference/like.html">%not_like_case%</a></code> as wrappers around <code><a href="../reference/like.html">%like%</a></code> and <code><a href="../reference/like.html">%like_case%</a></code>. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code><a href="../reference/like.html">%like%</a></code> and by pressing it again it will be replaced with <code><a href="../reference/like.html">%not_like%</a></code>, etc.</li>
</ul>
</div>
<div id="changed" class="section level3">
@ -260,12 +260,14 @@
<li>Deprecated function <code><a href="../reference/AMR-deprecated.html">p_symbol()</a></code> that not really fits the scope of this package. It will be removed in a future version. See <a href="https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R">here</a> for the source code to preserve it.</li>
<li>Better determination of disk zones and MIC values when running <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on a data.frame</li>
<li>Updated coagulase-negative staphylococci with Becker <em>et al.</em> 2020 (PMID 32056452), meaning that the species <em>S. argensis</em>, <em>S. caeli</em>, <em>S. debuckii</em>, <em>S. edaphicus</em> and <em>S. pseudoxylosus</em> are now all considered CoNS</li>
<li>Fix for using parameter <code>reference_df</code> in <code><a href="../reference/as.mo.html">as.mo()</a></code> and <code>mo_*()</code> functions that contain old microbial codes (from previous package versions)</li>
</ul>
</div>
<div id="other" class="section level3">
<h3 class="hasAnchor">
<a href="#other" class="anchor"></a>Other</h3>
<ul>
<li>All messages thrown by this package now have correct line breaks</li>
<li>More extensive unit tests</li>
</ul>
</div>
@ -468,7 +470,7 @@
<p>Making this package independent of especially the tidyverse (e.g. packages <code>dplyr</code> and <code>tidyr</code>) tremendously increases sustainability on the long term, since tidyverse functions change quite often. Good for users, but hard for package maintainers. Most of our functions are replaced with versions that only rely on base R, which keeps this package fully functional for many years to come, without requiring a lot of maintenance to keep up with other packages anymore. Another upside it that this package can now be used with all versions of R since R-3.0.0 (April 2013). Our package is being used in settings where the resources are very limited. Fewer dependencies on newer software is helpful for such settings.</p>
<p>Negative effects of this change are:</p>
<ul>
<li>Function <code>freq()</code> that was borrowed from the <code>cleaner</code> package was removed. Use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">cleaner::freq()</a></code>, or run <code><a href="https://github.com/msberends/cleaner">library("cleaner")</a></code> before you use <code>freq()</code>.</li>
<li>Function <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> that was borrowed from the <code>cleaner</code> package was removed. Use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">cleaner::freq()</a></code>, or run <code><a href="https://github.com/msberends/cleaner">library("cleaner")</a></code> before you use <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>.</li>
<li><del>Printing values of class <code>mo</code> or <code>rsi</code> in a tibble will no longer be in colour and printing <code>rsi</code> in a tibble will show the class <code>&lt;ord&gt;</code>, not <code>&lt;rsi&gt;</code> anymore. This is purely a visual effect.</del></li>
<li><del>All functions from the <code>mo_*</code> family (like <code><a href="../reference/mo_property.html">mo_name()</a></code> and <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) are noticeably slower when running on hundreds of thousands of rows.</del></li>
<li>For developers: classes <code>mo</code> and <code>ab</code> now both also inherit class <code>character</code>, to support any data transformation. This change invalidates code that checks for class length == 1.</li>
@ -796,7 +798,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="co">#&gt; invalid microorganism code, NA generated</span></pre></div>
<p>This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><a href="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</p>
</li>
<li><p>Function <code>freq()</code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code>freq()</code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
<li><p>Function <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
<li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
</ul>
</div>
@ -1059,7 +1061,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li>The <code><a href="../reference/age.html">age()</a></code> function gained a new parameter <code>exact</code> to determine ages with decimals</li>
<li>Removed deprecated functions <code>guess_mo()</code>, <code>guess_atc()</code>, <code>EUCAST_rules()</code>, <code>interpretive_reading()</code>, <code><a href="../reference/as.rsi.html">rsi()</a></code>
</li>
<li>Frequency tables (<code>freq()</code>):
<li>Frequency tables (<code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>):
<ul>
<li><p>speed improvement for microbial IDs</p></li>
<li><p>fixed factor level names for R Markdown</p></li>
@ -1068,12 +1070,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<p>support for boxplots:</p>
<div class="sourceCode" id="cb20"><pre class="downlit">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span><span class="op">(</span><span class="op">)</span>
<span class="co"># grouped boxplots:</span>
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span><span class="op">(</span><span class="op">)</span></pre></div>
</li>
</ul>
@ -1083,7 +1085,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li>Added ceftazidim intrinsic resistance to <em>Streptococci</em>
</li>
<li>Changed default settings for <code><a href="../reference/age_groups.html">age_groups()</a></code>, to let groups of fives and tens end with 100+ instead of 120+</li>
<li>Fix for <code>freq()</code> for when all values are <code>NA</code>
<li>Fix for <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> for when all values are <code>NA</code>
</li>
<li>Fix for <code><a href="../reference/first_isolate.html">first_isolate()</a></code> for when dates are missing</li>
<li>Improved speed of <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
@ -1315,7 +1317,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</ul>
</li>
<li>Frequency tables (<code>freq()</code> function):
<li>Frequency tables (<code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function):
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
@ -1324,15 +1326,15 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="co"># OLD WAY</span>
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">genus</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">genus</span><span class="op">)</span>
<span class="co"># NEW WAY</span>
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span>
<span class="co"># Even supports grouping variables:</span>
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span></pre></div>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span></pre></div>
</li>
<li><p>Header info is now available as a list, with the <code>header</code> function</p></li>
<li><p>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</p></li>
@ -1414,23 +1416,23 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code></p></li>
<li><p>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</p></li>
<li>
<p>Frequency tables - <code>freq()</code>:</p>
<p>Frequency tables - <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code>:</p>
<ul>
<li>
<p>Support for grouping variables, test with:</p>
<div class="sourceCode" id="cb32"><pre class="downlit">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
</li>
<li>
<p>Support for (un)selecting columns:</p>
<div class="sourceCode" id="cb33"><pre class="downlit">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="op">-</span><span class="va">count</span>, <span class="op">-</span><span class="va">cum_count</span><span class="op">)</span> <span class="co"># only get item, percent, cum_percent</span></pre></div>
</li>
<li><p>Check for <code><a href="https://hms.tidyverse.org/reference/Deprecated.html">hms::is.hms</a></code></p></li>
<li><p>Check for <code><a href="https://rdrr.io/pkg/hms/man/Deprecated.html">hms::is.hms</a></code></p></li>
<li><p>Now prints in markdown at default in non-interactive sessions</p></li>
<li><p>No longer adds the factor level column and sorts factors on count again</p></li>
<li><p>Support for class <code>difftime</code></p></li>
@ -1445,7 +1447,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Removed diacritics from all authors (columns <code>microorganisms$ref</code> and <code>microorganisms.old$ref</code>) to comply with CRAN policy to only allow ASCII characters</p></li>
<li><p>Fix for <code>mo_property</code> not working properly</p></li>
<li><p>Fix for <code>eucast_rules</code> where some Streptococci would become ceftazidime R in EUCAST rule 4.5</p></li>
<li><p>Support for named vectors of class <code>mo</code>, useful for <code>top_freq()</code></p></li>
<li><p>Support for named vectors of class <code>mo</code>, useful for <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">top_freq()</a></code></p></li>
<li><p><code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</p></li>
<li>
<p>AI improvements for <code>as.mo</code>:</p>
@ -1606,12 +1608,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<div class="sourceCode" id="cb40"><pre class="downlit">
<span class="va">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span><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="va">age</span>, <span class="va">gender</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></pre></div>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></pre></div>
<p>For lists, subsetting is possible:</p>
<div class="sourceCode" id="cb41"><pre class="downlit">
<span class="va">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>age <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">age</span>, gender <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">gender</span><span class="op">)</span>
<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span>
<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">age</span><span class="op">)</span>
<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span><span class="op">(</span><span class="va">gender</span><span class="op">)</span></pre></div>
</li>
</ul>
</div>
@ -1685,13 +1687,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>A vignette to explain its usage</li>
<li>Support for <code>rsi</code> (antimicrobial resistance) to use as input</li>
<li>Support for <code>table</code> to use as input: <code>freq(table(x, y))</code>
<li>Support for <code>table</code> to use as input: <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq(table(x, y))</a></code>
</li>
<li>Support for existing functions <code>hist</code> and <code>plot</code> to use a frequency table as input: <code><a href="https://rdrr.io/r/graphics/hist.html">hist(freq(df$age))</a></code>
</li>
<li>Support for <code>as.vector</code>, <code>as.data.frame</code>, <code>as_tibble</code> and <code>format</code>
</li>
<li>Support for quasiquotation: <code>freq(mydata, mycolumn)</code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
<li>Support for quasiquotation: <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq(mydata, mycolumn)</a></code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
</li>
<li>Function <code>top_freq</code> function to return the top/below <em>n</em> items as vector</li>
<li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>

4
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@ -1,4 +1,4 @@
pandoc: 2.9.2.1
pandoc: 2.7.3
pkgdown: 1.6.1
pkgdown_sha: ~
articles:
@ -12,7 +12,7 @@ articles:
datasets: datasets.html
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
last_built: 2020-10-21T13:25Z
last_built: 2020-10-26T10:52Z
urls:
reference: https://msberends.github.io/AMR//reference
article: https://msberends.github.io/AMR//articles

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9003</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9004</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

68
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@ -82,7 +82,7 @@
</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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -242,33 +242,33 @@
<p>Filter isolates on results in specific antimicrobial classes. This makes it easy to filter on isolates that were tested for e.g. any aminoglycoside, or to filter on carbapenem-resistant isolates without the need to specify the drugs.</p>
</div>
<pre class="usage"><span class='fu'>filter_ab_class</span>(<span class='kw'>x</span>, <span class='kw'>ab_class</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<pre class="usage"><span class='fu'>filter_ab_class</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>ab_class</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_carbapenems</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_carbapenems</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_1st_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_1st_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_2nd_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_2nd_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_3rd_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_3rd_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_4th_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_4th_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_5th_cephalosporins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_5th_cephalosporins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_glycopeptides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_glycopeptides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_macrolides</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_macrolides</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_penicillins</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)
<span class='fu'>filter_penicillins</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>filter_tetracyclines</span>(<span class='kw'>x</span>, result = <span class='kw'>NULL</span>, scope = <span class='st'>"any"</span>, <span class='kw'>...</span>)</pre>
<span class='fu'>filter_tetracyclines</span><span class='op'>(</span><span class='va'>x</span>, result <span class='op'>=</span> <span class='cn'>NULL</span>, scope <span class='op'>=</span> <span class='st'>"any"</span>, <span class='va'>...</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -310,43 +310,43 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<div class='dont-index'><p><code><a href='antibiotic_class_selectors.html'>antibiotic_class_selectors()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code> equivalent.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='fu'>filter_aminoglycosides</span>(<span class='kw'>example_isolates</span>)
<pre class="examples"><span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='va'>example_isolates</span><span class='op'>)</span>
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
<span class='co'># filter on isolates that have any result for any aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>()
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span>(<span class='st'>"aminoglycoside"</span>)
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='op'>)</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span><span class='op'>(</span><span class='st'>"aminoglycoside"</span><span class='op'>)</span>
<span class='co'># this is essentially the same as (but without determination of column names):</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(.vars = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
.vars_predicate = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='kw'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span><span class='op'>(</span>.vars <span class='op'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span><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'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span><span class='op'>)</span><span class='op'>)</span>,
.vars_predicate <span class='op'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span><span class='op'>(</span><span class='va'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>
<span class='co'># filter on isolates that show resistance to ANY aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"any"</span>)
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"any"</span><span class='op'>)</span>
<span class='co'># filter on isolates that show resistance to ALL aminoglycosides</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># any aminoglycoside and any fluoroquinolone</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>)
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='st'>"R"</span><span class='op'>)</span>
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># all aminoglycosides and all fluoroquinolones</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span>(), <span class='op'>~</span><span class='kw'>.</span> <span class='op'>==</span> <span class='st'>"R"</span>))
}
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span><span class='op'>(</span><span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='op'>~</span><span class='va'>.</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span>
<span class='op'>}</span>
<span class='co'># }</span>
</pre>
</div>
@ -364,7 +364,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>

2
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@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
docs/reference/ggplot_rsi.html
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@ -82,7 +82,7 @@
</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">1.4.0.9005</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
docs/reference/guess_ab_col.html
View File

@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

6
docs/reference/index.html
View File

@ -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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -581,9 +581,9 @@
</tr><tr>
<td>
<p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%like_case%`</a></code> </p>
<p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%not_like%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%not_like_case%`</a></code> </p>
</td>
<td><p>Pattern Matching</p></td>
<td><p>Pattern matching with keyboard shortcut</p></td>
</tr><tr>
<td>

2
docs/reference/key_antibiotics.html
View File

@ -82,7 +82,7 @@
</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">1.4.0.9001</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

4
docs/reference/lifecycle.html
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@ -84,7 +84,7 @@ This page contains a section for every lifecycle (with text borrowed from the af
</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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -295,7 +295,7 @@ The lifecycle of this function is <strong>questioning</strong>. This function mi
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>

17
docs/reference/like.html
View File

@ -6,7 +6,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Pattern Matching — like • AMR (for R)</title>
<title>Pattern matching with keyboard shortcut — like • AMR (for R)</title>
<!-- favicons -->
<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@ -48,7 +48,7 @@
<link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script>
<meta property="og:title" content="Pattern Matching — like" />
<meta property="og:title" content="Pattern matching with keyboard shortcut — like" />
<meta property="og:description" content="Convenient wrapper around grep() to match a pattern: x %like% pattern. It always returns a logical vector and is always case-insensitive (use x %like_case% pattern for case-sensitive matching). Also, pattern can be as long as x to compare items of each index in both vectors, or they both can have the same length to iterate over all cases." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -82,7 +82,7 @@
</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">1.4.0.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -233,7 +233,7 @@
<div class="row">
<div class="col-md-9 contents">
<div class="page-header">
<h1>Pattern Matching</h1>
<h1>Pattern matching with keyboard shortcut</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/like.R'><code>R/like.R</code></a></small>
<div class="hidden name"><code>like.Rd</code></div>
</div>
@ -246,7 +246,11 @@
<span class='va'>x</span> <span class='op'>%like%</span> <span class='va'>pattern</span>
<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span></pre>
<span class='va'>x</span> <span class='op'>%not_like%</span> <span class='va'>pattern</span>
<span class='va'>x</span> <span class='op'>%like_case%</span> <span class='va'>pattern</span>
<span class='va'>x</span> <span class='op'>%not_like_case%</span> <span class='va'>pattern</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -280,7 +284,8 @@
<li><p>Tries again with <code>perl = TRUE</code> if regex fails</p></li>
</ul>
<p>Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like <code>Ctrl+Shift+L</code> or <code>Cmd+Shift+L</code> (see <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>).</p>
<p>Using RStudio? This function can also be inserted in your code from the Addins menu and can have its own Keyboard Shortcut like <code>Ctrl+Shift+L</code> or <code>Cmd+Shift+L</code> (see <code>Tools</code> &gt; <code>Modify Keyboard Shortcuts...</code>). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code>%like%</code> and by pressing it again it will be replaced with <code>%not_like%</code>, then <code>%like_case%</code>, then <code>%not_like_case%</code> and then back to <code>%like%</code>.</p>
<p>The <code>"%not_like%"</code> and <code>"%not_like_case%"</code> functions are wrappers around <code>"%like%"</code> and <code>"%like_case%"</code>.</p>
<h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable lifecycle</h2>

8
docs/reference/mo_property.html
View File

@ -82,7 +82,7 @@
</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">1.4.0.9003</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -270,9 +270,9 @@
<span class='fu'>mo_gramstain</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>is_gram_negative</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>is_gram_negative</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>is_gram_positive</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>is_gram_positive</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>mo_snomed</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
@ -303,7 +303,7 @@
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_locale = "de")</a></code>, see <a href='translate.html'>translate</a>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale()</a></code>) and can be overwritten by setting the option <code>AMR_locale</code>, e.g. <code><a href='https://rdrr.io/r/base/options.html'>options(AMR_locale = "de")</a></code>, see <a href='translate.html'>translate</a>. Also used to translate text like "no growth". Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
</tr>
<tr>
<th>...</th>

46
docs/reference/pca.html
View File

@ -82,7 +82,7 @@
</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">1.4.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>
@ -242,15 +242,15 @@
<p>Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.</p>
</div>
<pre class="usage"><span class='fu'>pca</span>(
<span class='kw'>x</span>,
<span class='kw'>...</span>,
retx = <span class='fl'>TRUE</span>,
center = <span class='fl'>TRUE</span>,
scale. = <span class='fl'>TRUE</span>,
tol = <span class='kw'>NULL</span>,
rank. = <span class='kw'>NULL</span>
)</pre>
<pre class="usage"><span class='fu'>pca</span><span class='op'>(</span>
<span class='va'>x</span>,
<span class='va'>...</span>,
retx <span class='op'>=</span> <span class='cn'>TRUE</span>,
center <span class='op'>=</span> <span class='cn'>TRUE</span>,
scale. <span class='op'>=</span> <span class='cn'>TRUE</span>,
tol <span class='op'>=</span> <span class='cn'>NULL</span>,
rank. <span class='op'>=</span> <span class='cn'>NULL</span>
<span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -324,22 +324,22 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
<span class='co'># calculate the resistance per group first </span>
<span class='kw'>resistance_data</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(order = <span class='fu'><a href='mo_property.html'>mo_order</a></span>(<span class='kw'>mo</span>), <span class='co'># group on anything, like order</span>
genus = <span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='kw'>mo</span>)) <span class='op'>%&gt;%</span> <span class='co'># and genus as we do here</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise_all.html'>summarise_if</a></span>(<span class='kw'>is.rsi</span>, <span class='kw'>resistance</span>) <span class='co'># then get resistance of all drugs</span>
<span class='va'>resistance_data</span> <span class='op'>&lt;-</span> <span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span>order <span class='op'>=</span> <span class='fu'><a href='mo_property.html'>mo_order</a></span><span class='op'>(</span><span class='va'>mo</span><span class='op'>)</span>, <span class='co'># group on anything, like order</span>
genus <span class='op'>=</span> <span class='fu'><a href='mo_property.html'>mo_genus</a></span><span class='op'>(</span><span class='va'>mo</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span> <span class='co'># and genus as we do here</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise_all.html'>summarise_if</a></span><span class='op'>(</span><span class='va'>is.rsi</span>, <span class='va'>resistance</span><span class='op'>)</span> <span class='co'># then get resistance of all drugs</span>
<span class='co'># now conduct PCA for certain antimicrobial agents</span>
<span class='kw'>pca_result</span> <span class='op'>&lt;-</span> <span class='kw'>resistance_data</span> <span class='op'>%&gt;%</span>
<span class='fu'>pca</span>(<span class='kw'>AMC</span>, <span class='kw'>CXM</span>, <span class='kw'>CTX</span>, <span class='kw'>CAZ</span>, <span class='kw'>GEN</span>, <span class='kw'>TOB</span>, <span class='kw'>TMP</span>, <span class='kw'>SXT</span>)
<span class='va'>pca_result</span> <span class='op'>&lt;-</span> <span class='va'>resistance_data</span> <span class='op'>%&gt;%</span>
<span class='fu'>pca</span><span class='op'>(</span><span class='va'>AMC</span>, <span class='va'>CXM</span>, <span class='va'>CTX</span>, <span class='va'>CAZ</span>, <span class='va'>GEN</span>, <span class='va'>TOB</span>, <span class='va'>TMP</span>, <span class='va'>SXT</span><span class='op'>)</span>
<span class='kw'>pca_result</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='https://rdrr.io/r/stats/biplot.html'>biplot</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span>(<span class='kw'>pca_result</span>) <span class='co'># a new and convenient plot function</span>
}
<span class='va'>pca_result</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>pca_result</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/stats/biplot.html'>biplot</a></span><span class='op'>(</span><span class='va'>pca_result</span><span class='op'>)</span>
<span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span><span class='op'>(</span><span class='va'>pca_result</span><span class='op'>)</span> <span class='co'># a new and convenient plot function</span>
<span class='op'>}</span>
<span class='co'># }</span>
</pre>
</div>
@ -357,7 +357,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.9000.</p>
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>

2
docs/survey.html
View File

@ -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">1.4.0.9007</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9008</span>
</span>
</div>

2
inst/rstudio/addins.dcf
View File

@ -2,6 +2,6 @@ Name: Insert %in%
Binding: addin_insert_in
Interactive: false
Name: Insert %like%
Name: Insert %like% / %not_like%
Binding: addin_insert_like
Interactive: false

12
man/like.Rd
View File

@ -3,8 +3,10 @@
\name{like}
\alias{like}
\alias{\%like\%}
\alias{\%not_like\%}
\alias{\%like_case\%}
\title{Pattern Matching}
\alias{\%not_like_case\%}
\title{Pattern matching with keyboard shortcut}
\source{
Idea from the \href{https://github.com/Rdatatable/data.table/blob/master/R/like.R}{\code{like} function from the \code{data.table} package}
}
@ -13,7 +15,11 @@ like(x, pattern, ignore.case = TRUE)
x \%like\% pattern
x \%not_like\% pattern
x \%like_case\% pattern
x \%not_like_case\% pattern
}
\arguments{
\item{x}{a character vector where matches are sought, or an object which can be coerced by \code{\link[=as.character]{as.character()}} to a character vector.}
@ -37,7 +43,9 @@ The \verb{\%like\%} function:
\item Tries again with \code{perl = TRUE} if regex fails
}
Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like \code{Ctrl+Shift+L} or \code{Cmd+Shift+L} (see \code{Tools} > \verb{Modify Keyboard Shortcuts...}).
Using RStudio? This function can also be inserted in your code from the Addins menu and can have its own Keyboard Shortcut like \code{Ctrl+Shift+L} or \code{Cmd+Shift+L} (see \code{Tools} > \verb{Modify Keyboard Shortcuts...}). This addin iterates over all 'like' variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert \verb{\%like\%} and by pressing it again it will be replaced with \verb{\%not_like\%}, then \verb{\%like_case\%}, then \verb{\%not_like_case\%} and then back to \verb{\%like\%}.
The \code{"\%not_like\%"} and \code{"\%not_like_case\%"} functions are wrappers around \code{"\%like\%"} and \code{"\%like_case\%"}.
}
\section{Stable lifecycle}{

6
man/mo_property.Rd
View File

@ -57,9 +57,9 @@ mo_type(x, language = get_locale(), ...)
mo_gramstain(x, language = get_locale(), ...)
is_gram_negative(x, ...)
is_gram_negative(x, language = get_locale(), ...)
is_gram_positive(x, ...)
is_gram_positive(x, language = get_locale(), ...)
mo_snomed(x, language = get_locale(), ...)
@ -84,7 +84,7 @@ mo_property(x, property = "fullname", language = get_locale(), ...)
\arguments{
\item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}}
\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Use \code{language = NULL} or \code{language = ""} to prevent translation.}
\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Also used to translate text like "no growth". Use \code{language = NULL} or \code{language = ""} to prevent translation.}
\item{...}{other parameters passed on to \code{\link[=as.mo]{as.mo()}}, such as 'allow_uncertain' and 'ignore_pattern'}

7
tests/testthat/test-like.R
View File

@ -28,8 +28,13 @@ context("like.R")
test_that("`like` works", {
skip_on_cran()
expect_true(sum("test" %like% c("^t", "^s")) == 1)
expect_true("test" %like% "test")
expect_true("test" %like% "TEST")
expect_false("test" %like_case% "TEST")
expect_false("test" %not_like% "test")
expect_true("test" %not_like_case% "TEST")
expect_true(as.factor("test") %like% "TEST")
expect_identical(factor(c("Test case", "Something different", "Yet another thing")) %like% c("case", "diff", "yet"),
c(TRUE, TRUE, TRUE))