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(v1.7.1.9031) dplyr grouping fix on windows?

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dr. M.S. (Matthijs) Berends 2021-08-30 14:07:46 +02:00
parent d6a916d70b
commit e6ce25162e
13 changed files with 80 additions and 62 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 1.7.1.9030 Version: 1.7.1.9031
Date: 2021-08-29 Date: 2021-08-30
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

4
NEWS.md
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@ -1,5 +1,5 @@
# `AMR` 1.7.1.9030 # `AMR` 1.7.1.9031
## <small>Last updated: 29 August 2021</small> ## <small>Last updated: 30 August 2021</small>
### Breaking changes ### Breaking changes
* Removed `p_symbol()` and all `filter_*()` functions (except for `filter_first_isolate()`), which were all deprecated in a previous package version * Removed `p_symbol()` and all `filter_*()` functions (except for `filter_first_isolate()`), which were all deprecated in a previous package version

4
R/aa_helper_functions.R
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@ -736,6 +736,7 @@ get_current_data <- function(arg_name, call) {
if (!is.null(cur_data_all)) { if (!is.null(cur_data_all)) {
out <- tryCatch(cur_data_all(), error = function(e) NULL) out <- tryCatch(cur_data_all(), error = function(e) NULL)
if (is.data.frame(out)) { if (is.data.frame(out)) {
messsage("==> RETURNING cur_data_all()")
return(structure(out, type = "dplyr_cur_data_all")) return(structure(out, type = "dplyr_cur_data_all"))
} }
} }
@ -748,14 +749,17 @@ get_current_data <- function(arg_name, call) {
if (!is.null(env$`.data`) && is.data.frame(env$`.data`)) { if (!is.null(env$`.data`) && is.data.frame(env$`.data`)) {
# an element `.data` will be in the environment when using `dplyr::select()` # an element `.data` will be in the environment when using `dplyr::select()`
# (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`) # (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`)
messsage("==> RETURNING dplyr_selector")
return(structure(env$`.data`, type = "dplyr_selector")) return(structure(env$`.data`, type = "dplyr_selector"))
} else if (!is.null(env$xx) && is.data.frame(env$xx)) { } else if (!is.null(env$xx) && is.data.frame(env$xx)) {
# an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]` # an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
messsage("==> RETURNING base_R 1")
return(structure(env$xx, type = "base_R")) return(structure(env$xx, type = "base_R"))
} else if (!is.null(env$x) && is.data.frame(env$x)) { } else if (!is.null(env$x) && is.data.frame(env$x)) {
# an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]` # an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]`
messsage("==> RETURNING base_R 2")
return(structure(env$x, type = "base_R")) return(structure(env$x, type = "base_R"))
} }
} }

46
R/first_isolate.R
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@ -23,9 +23,9 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== # # ==================================================================== #
#' Determine First (Weighted) Isolates #' Determine First Isolates
#' #'
#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package. #' Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports [grouping with the `dplyr` package][dplyr::group_by()] .
#' @inheritSection lifecycle Stable Lifecycle #' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*. #' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class #' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
@ -34,7 +34,7 @@
#' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored. #' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
#' @param col_specimen column name of the specimen type or group #' @param col_specimen column name of the specimen type or group
#' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU) #' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU)
#' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first (weighted) isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()]. #' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*. #' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*.
#' @param testcodes_exclude a [character] vector with test codes that should be excluded (case-insensitive) #' @param testcodes_exclude a [character] vector with test codes that should be excluded (case-insensitive)
#' @param icu_exclude a [logical] to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`) #' @param icu_exclude a [logical] to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
@ -102,9 +102,9 @@
#' #'
#' This is a more reliable method, since it also *weighs* the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram: #' This is a more reliable method, since it also *weighs* the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:
#' #'
#' 1. Using `type = "points"` and argument `points_threshold` #' 1. Using `type = "points"` and argument `points_threshold` (default)
#' #'
#' This method weighs *all* antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as 0.5 points, a difference from S to R (or vice versa) counts as 1 point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be selected as a first weighted isolate. #' This method weighs *all* antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as `0.5` points, a difference from S to R (or vice versa) counts as `1` point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be selected as a first weighted isolate.
#' #'
#' All antimicrobials are internally selected using the [all_antimicrobials()] function. The output of this function does not need to be passed to the [first_isolate()] function. #' All antimicrobials are internally selected using the [all_antimicrobials()] function. The output of this function does not need to be passed to the [first_isolate()] function.
#' #'
@ -218,7 +218,7 @@ first_isolate <- function(x = NULL,
meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x)) meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
# method # method
method <- coerce_method(method) method <- coerce_method(method)
meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based", "p", "e", "i")) meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
# key antimicrobials # key antimicrobials
if (length(col_keyantimicrobials) > 1) { if (length(col_keyantimicrobials) > 1) {
meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = nrow(x)) meet_criteria(col_keyantimicrobials, allow_class = "character", has_length = nrow(x))
@ -256,11 +256,11 @@ first_isolate <- function(x = NULL,
method <- "episode-based" method <- "episode-based"
} }
if (info == TRUE & message_not_thrown_before("first_isolate.method")) { if (info == TRUE & message_not_thrown_before("first_isolate.method")) {
message_(paste0("Determining first isolates using the '", font_bold(method), "' method", message_(paste0("Determining first isolates ",
ifelse(method %in% c("episode-based", "phenotype-based"), ifelse(method %in% c("episode-based", "phenotype-based"),
ifelse(is.infinite(episode_days), ifelse(is.infinite(episode_days),
" without a specified episode length", "without a specified episode length",
paste(" and an episode length of", episode_days, "days")), paste("using an episode length of", episode_days, "days")),
"")), "")),
as_note = FALSE, as_note = FALSE,
add_fn = font_black) add_fn = font_black)
@ -360,7 +360,7 @@ first_isolate <- function(x = NULL,
} }
# remove testcodes # remove testcodes
if (!is.null(testcodes_exclude) & info == TRUE & message_not_thrown_before("first_isolate.excludingtestcodes")) { if (!is.null(testcodes_exclude) & info == TRUE & message_not_thrown_before("first_isolate.excludingtestcodes")) {
message_("Excluding test codes: ", toString(paste0("'", testcodes_exclude, "'")), message_("Excluding test codes: ", vector_and(testcodes_exclude, quotes = TRUE),
add_fn = font_black, add_fn = font_black,
as_note = FALSE) as_note = FALSE)
} }
@ -454,9 +454,7 @@ first_isolate <- function(x = NULL,
episode_days = episode_days), episode_days = episode_days),
use.names = FALSE) use.names = FALSE)
weighted.notice <- ""
if (!is.null(col_keyantimicrobials)) { if (!is.null(col_keyantimicrobials)) {
weighted.notice <- "weighted "
if (info == TRUE & message_not_thrown_before("first_isolate.type")) { if (info == TRUE & message_not_thrown_before("first_isolate.type")) {
if (type == "keyantimicrobials") { if (type == "keyantimicrobials") {
message_("Basing inclusion on key antimicrobials, ", message_("Basing inclusion on key antimicrobials, ",
@ -583,16 +581,16 @@ first_isolate <- function(x = NULL,
} }
# mark up number of found # mark up number of found
n_found <- format(n_found, big.mark = big.mark, decimal.mark = decimal.mark) n_found <- format(n_found, big.mark = big.mark, decimal.mark = decimal.mark)
if (p_found_total != p_found_scope) { message_(paste0("=> Found ",
msg_txt <- paste0("=> Found ", font_bold(paste0(n_found,
font_bold(paste0(n_found, " first ", weighted.notice, "isolates")), ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
" (", method, ", ", p_found_scope, " within scope and ", p_found_total, " of total where a microbial ID was available)") " first isolates")),
} else { " (",
msg_txt <- paste0("=> Found ", ifelse(p_found_total != p_found_scope,
font_bold(paste0(n_found, " first ", weighted.notice, "isolates")), paste0(p_found_scope, " within scope and "),
" (", method, ", ", p_found_total, " of total where a microbial ID was available)") ""),
} p_found_total, " of total where a microbial ID was available)"),
message_(msg_txt, add_fn = font_black, as_note = FALSE) add_fn = font_black, as_note = FALSE)
} }
x$newvar_first_isolate x$newvar_first_isolate
@ -619,7 +617,7 @@ filter_first_isolate <- function(x = NULL,
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x)) meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE) meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
method <- coerce_method(method) method <- coerce_method(method)
meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based", "p", "e", "i")) meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
subset(x, first_isolate(x = x, subset(x, first_isolate(x = x,
col_date = col_date, col_date = col_date,
@ -637,7 +635,7 @@ coerce_method <- function(method) {
method <- tolower(as.character(method[1L])) method <- tolower(as.character(method[1L]))
method[method %like% "^(p$|pheno)"] <- "phenotype-based" method[method %like% "^(p$|pheno)"] <- "phenotype-based"
method[method %like% "^(e$|episode)"] <- "episode-based" method[method %like% "^(e$|episode)"] <- "episode-based"
method[method %like% "^patient"] <- "patient-based" method[method %like% "^pat"] <- "patient-based"
method[method %like% "^(i$|iso)"] <- "isolate-based" method[method %like% "^(i$|iso)"] <- "isolate-based"
method method
} }

22
R/guess_ab_col.R
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@ -179,7 +179,7 @@ get_column_abx <- function(x,
} else { } else {
return(NA_character_) return(NA_character_)
} }
}) }, USE.NAMES = FALSE)
x_columns <- x_columns[!is.na(x_columns)] x_columns <- x_columns[!is.na(x_columns)]
x <- x[, x_columns, drop = FALSE] # without drop = FALSE, x will become a vector when x_columns is length 1 x <- x[, x_columns, drop = FALSE] # without drop = FALSE, x will become a vector when x_columns is length 1
@ -192,13 +192,27 @@ get_column_abx <- function(x,
# add from self-defined dots (...): # add from self-defined dots (...):
# such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone") # such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
all_okay <- TRUE
dots <- list(...) dots <- list(...)
if (length(dots) > 0) { if (length(dots) > 0) {
newnames <- suppressWarnings(as.ab(names(dots), info = FALSE)) newnames <- suppressWarnings(as.ab(names(dots), info = FALSE))
if (any(is.na(newnames))) { if (any(is.na(newnames))) {
warning_("Invalid antibiotic reference(s): ", toString(names(dots)[is.na(newnames)]), if (info == TRUE) {
message_(" WARNING", add_fn = list(font_yellow, font_bold), as_note = FALSE)
}
warning_("Invalid antibiotic reference(s): ", vector_and(names(dots)[is.na(newnames)], quotes = FALSE),
call = FALSE, call = FALSE,
immediate = TRUE) immediate = TRUE)
all_okay <- FALSE
}
unexisting_cols <- which(!vapply(FUN.VALUE = logical(1), dots, function(col) all(col %in% x_columns)))
if (length(unexisting_cols) > 0) {
if (info == TRUE) {
message_(" ERROR", add_fn = list(font_red, font_bold), as_note = FALSE)
}
stop_("Column(s) not found: ", vector_and(unlist(dots[[unexisting_cols]]), quotes = FALSE),
call = FALSE)
all_okay <- FALSE
} }
# turn all NULLs to NAs # turn all NULLs to NAs
dots <- unlist(lapply(dots, function(dot) if (is.null(dot)) NA else dot)) dots <- unlist(lapply(dots, function(dot) if (is.null(dot)) NA else dot))
@ -211,7 +225,7 @@ get_column_abx <- function(x,
} }
if (length(out) == 0) { if (length(out) == 0) {
if (info == TRUE) { if (info == TRUE & all_okay == TRUE) {
message_("No columns found.") message_("No columns found.")
} }
pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE) pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE)
@ -232,7 +246,7 @@ get_column_abx <- function(x,
} }
# succeeded with auto-guessing # succeeded with auto-guessing
if (info == TRUE) { if (info == TRUE & all_okay == TRUE) {
message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE) message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
} }

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data-raw/AMR_latest.tar.gz
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4
docs/articles/datasets.html
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <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">1.7.1.9030</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9031</span>
</span> </span>
</div> </div>
@ -190,7 +190,7 @@
<div class="page-header toc-ignore"> <div class="page-header toc-ignore">
<h1 data-toc-skip>Data sets for download / own use</h1> <h1 data-toc-skip>Data sets for download / own use</h1>
<h4 data-toc-skip class="date">29 August 2021</h4> <h4 data-toc-skip class="date">30 August 2021</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="hidden name"><code>datasets.Rmd</code></div> <div class="hidden name"><code>datasets.Rmd</code></div>

12
docs/news/index.html
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@ -92,7 +92,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <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">1.7.1.9030</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9031</span>
</span> </span>
</div> </div>
@ -240,12 +240,12 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small> <small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div> </div>
<div id="amr-1719030" class="section level1"> <div id="amr-1719031" class="section level1">
<h1 class="page-header" data-toc-text="1.7.1.9030"> <h1 class="page-header" data-toc-text="1.7.1.9031">
<a href="#amr-1719030" class="anchor" aria-hidden="true"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9030</h1> <a href="#amr-1719031" class="anchor" aria-hidden="true"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9031</h1>
<div id="last-updated-29-august-2021" class="section level2"> <div id="last-updated-30-august-2021" class="section level2">
<h2 class="hasAnchor"> <h2 class="hasAnchor">
<a href="#last-updated-29-august-2021" class="anchor" aria-hidden="true"></a><small>Last updated: 29 August 2021</small> <a href="#last-updated-30-august-2021" class="anchor" aria-hidden="true"></a><small>Last updated: 30 August 2021</small>
</h2> </h2>
<div id="breaking-changes" class="section level3"> <div id="breaking-changes" class="section level3">
<h3 class="hasAnchor"> <h3 class="hasAnchor">

22
docs/reference/first_isolate.html
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@ -6,7 +6,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Determine First (Weighted) Isolates — first_isolate • AMR (for R)</title> <title>Determine First Isolates — first_isolate • AMR (for R)</title>
<!-- favicons --> <!-- favicons -->
<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"> <link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@ -48,9 +48,9 @@
<link href="../extra.css" rel="stylesheet"> <link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script> <script src="../extra.js"></script>
<meta property="og:title" content="Determine First (Weighted) Isolates — first_isolate" /> <meta property="og:title" content="Determine First Isolates — first_isolate" />
<meta property="og:description" content="Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler et al. in 2007 (doi: 10.1086/511864 <meta property="og:description" content="Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler et al. in 2007 (doi: 10.1086/511864
). To determine patient episodes not necessarily based on microorganisms, use is_new_episode() that also supports grouping with the dplyr package." /> ). To determine patient episodes not necessarily based on microorganisms, use is_new_episode() that also supports grouping with the dplyr package ." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" /> <meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
<meta name="twitter:card" content="summary_large_image" /> <meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:creator" content="@msberends" /> <meta name="twitter:creator" content="@msberends" />
@ -94,7 +94,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <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">1.7.1.9030</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9031</span>
</span> </span>
</div> </div>
@ -238,14 +238,14 @@
<div class="row"> <div class="row">
<div class="col-md-9 contents"> <div class="col-md-9 contents">
<div class="page-header"> <div class="page-header">
<h1>Determine First (Weighted) Isolates</h1> <h1>Determine First Isolates</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/first_isolate.R'><code>R/first_isolate.R</code></a></small> <small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/first_isolate.R'><code>R/first_isolate.R</code></a></small>
<div class="hidden name"><code>first_isolate.Rd</code></div> <div class="hidden name"><code>first_isolate.Rd</code></div>
</div> </div>
<div class="ref-description"> <div class="ref-description">
<p>Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler <em>et al.</em> in 2007 (doi: <a href='https://doi.org/10.1086/511864'>10.1086/511864</a> <p>Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler <em>et al.</em> in 2007 (doi: <a href='https://doi.org/10.1086/511864'>10.1086/511864</a>
). To determine patient episodes not necessarily based on microorganisms, use <code><a href='get_episode.html'>is_new_episode()</a></code> that also supports grouping with the <code>dplyr</code> package.</p> ). To determine patient episodes not necessarily based on microorganisms, use <code><a href='get_episode.html'>is_new_episode()</a></code> that also supports <a href='https://dplyr.tidyverse.org/reference/group_by.html'>grouping with the <code>dplyr</code> package</a> .</p>
</div> </div>
<div class="ref-usage sourceCode"><pre class='sourceCode r'><code><span class='fu'>first_isolate</span><span class='op'>(</span> <div class="ref-usage sourceCode"><pre class='sourceCode r'><code><span class='fu'>first_isolate</span><span class='op'>(</span>
@ -314,7 +314,7 @@
</tr> </tr>
<tr> <tr>
<th>col_keyantimicrobials</th> <th>col_keyantimicrobials</th>
<td><p>(only useful when <code>method = "phenotype-based"</code>) column name of the key antimicrobials to determine first (weighted) isolates, see <code><a href='key_antimicrobials.html'>key_antimicrobials()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use <code>col_keyantimicrobials = FALSE</code> to prevent this. Can also be the output of <code><a href='key_antimicrobials.html'>key_antimicrobials()</a></code>.</p></td> <td><p>(only useful when <code>method = "phenotype-based"</code>) column name of the key antimicrobials to determine first isolates, see <code><a href='key_antimicrobials.html'>key_antimicrobials()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use <code>col_keyantimicrobials = FALSE</code> to prevent this. Can also be the output of <code><a href='key_antimicrobials.html'>key_antimicrobials()</a></code>.</p></td>
</tr> </tr>
<tr> <tr>
<th>episode_days</th> <th>episode_days</th>
@ -429,8 +429,8 @@
<p>This is a more reliable method, since it also <em>weighs</em> the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:</p><ol> <p>This is a more reliable method, since it also <em>weighs</em> the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:</p><ol>
<li><p>Using <code>type = "points"</code> and argument <code>points_threshold</code></p> <li><p>Using <code>type = "points"</code> and argument <code>points_threshold</code> (default)</p>
<p>This method weighs <em>all</em> antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as 0.5 points, a difference from S to R (or vice versa) counts as 1 point. When the sum of points exceeds <code>points_threshold</code>, which defaults to <code>2</code>, an isolate will be selected as a first weighted isolate.</p> <p>This method weighs <em>all</em> antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as <code>0.5</code> points, a difference from S to R (or vice versa) counts as <code>1</code> point. When the sum of points exceeds <code>points_threshold</code>, which defaults to <code>2</code>, an isolate will be selected as a first weighted isolate.</p>
<p>All antimicrobials are internally selected using the <code><a href='key_antimicrobials.html'>all_antimicrobials()</a></code> function. The output of this function does not need to be passed to the <code>first_isolate()</code> function.</p></li> <p>All antimicrobials are internally selected using the <code><a href='key_antimicrobials.html'>all_antimicrobials()</a></code> function. The output of this function does not need to be passed to the <code>first_isolate()</code> function.</p></li>
<li><p>Using <code>type = "keyantimicrobials"</code> and argument <code>ignore_I</code></p> <li><p>Using <code>type = "keyantimicrobials"</code> and argument <code>ignore_I</code></p>
<p>This method only weighs specific antimicrobial agents, called <em>key antimicrobials</em>. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S or R (or vice versa) will lead to this.</p> <p>This method only weighs specific antimicrobial agents, called <em>key antimicrobials</em>. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S or R (or vice versa) will lead to this.</p>

4
docs/reference/index.html
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@ -92,7 +92,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <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">1.7.1.9030</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9031</span>
</span> </span>
</div> </div>
@ -393,7 +393,7 @@
<td> <td>
<p><code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code> </p> <p><code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code> </p>
</td> </td>
<td><p>Determine First (Weighted) Isolates</p></td> <td><p>Determine First Isolates</p></td>
</tr><tr> </tr><tr>
<td> <td>

2
inst/tinytest/test-first_isolate.R
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@ -133,9 +133,7 @@ if (AMR:::pkg_is_available("dplyr")) {
first_isolate(info = TRUE)) first_isolate(info = TRUE))
# groups # groups
message("get to first isolates L136")
x <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate()) x <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate())
message("get to first isolates L138")
y <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate(.)) y <- example_isolates %>% group_by(ward_icu) %>% mutate(first = first_isolate(.))
expect_identical(x, y) expect_identical(x, y)

10
man/first_isolate.Rd
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@ -3,7 +3,7 @@
\name{first_isolate} \name{first_isolate}
\alias{first_isolate} \alias{first_isolate}
\alias{filter_first_isolate} \alias{filter_first_isolate}
\title{Determine First (Weighted) Isolates} \title{Determine First Isolates}
\source{ \source{
Methodology of this function is strictly based on: Methodology of this function is strictly based on:
\itemize{ \itemize{
@ -60,7 +60,7 @@ filter_first_isolate(
\item{col_icu}{column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)} \item{col_icu}{column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)}
\item{col_keyantimicrobials}{(only useful when \code{method = "phenotype-based"}) column name of the key antimicrobials to determine first (weighted) isolates, see \code{\link[=key_antimicrobials]{key_antimicrobials()}}. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use \code{col_keyantimicrobials = FALSE} to prevent this. Can also be the output of \code{\link[=key_antimicrobials]{key_antimicrobials()}}.} \item{col_keyantimicrobials}{(only useful when \code{method = "phenotype-based"}) column name of the key antimicrobials to determine first isolates, see \code{\link[=key_antimicrobials]{key_antimicrobials()}}. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use \code{col_keyantimicrobials = FALSE} to prevent this. Can also be the output of \code{\link[=key_antimicrobials]{key_antimicrobials()}}.}
\item{episode_days}{episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see \emph{Source}.} \item{episode_days}{episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see \emph{Source}.}
@ -90,7 +90,7 @@ filter_first_isolate(
A \code{\link{logical}} vector A \code{\link{logical}} vector
} }
\description{ \description{
Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler \emph{et al.} in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use \code{\link[=is_new_episode]{is_new_episode()}} that also supports grouping with the \code{dplyr} package. Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler \emph{et al.} in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use \code{\link[=is_new_episode]{is_new_episode()}} that also supports \link[dplyr:group_by]{grouping with the \code{dplyr} package} .
} }
\details{ \details{
To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below. To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below.
@ -147,9 +147,9 @@ This is the most common method to correct for duplicate isolates. Patients are c
This is a more reliable method, since it also \emph{weighs} the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram: This is a more reliable method, since it also \emph{weighs} the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:
\enumerate{ \enumerate{
\item Using \code{type = "points"} and argument \code{points_threshold} \item Using \code{type = "points"} and argument \code{points_threshold} (default)
This method weighs \emph{all} antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as 0.5 points, a difference from S to R (or vice versa) counts as 1 point. When the sum of points exceeds \code{points_threshold}, which defaults to \code{2}, an isolate will be selected as a first weighted isolate. This method weighs \emph{all} antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as \code{0.5} points, a difference from S to R (or vice versa) counts as \code{1} point. When the sum of points exceeds \code{points_threshold}, which defaults to \code{2}, an isolate will be selected as a first weighted isolate.
All antimicrobials are internally selected using the \code{\link[=all_antimicrobials]{all_antimicrobials()}} function. The output of this function does not need to be passed to the \code{\link[=first_isolate]{first_isolate()}} function. All antimicrobials are internally selected using the \code{\link[=all_antimicrobials]{all_antimicrobials()}} function. The output of this function does not need to be passed to the \code{\link[=first_isolate]{first_isolate()}} function.
\item Using \code{type = "keyantimicrobials"} and argument \code{ignore_I} \item Using \code{type = "keyantimicrobials"} and argument \code{ignore_I}

8
tests/tinytest.R
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@ -33,9 +33,13 @@ if (identical(Sys.getenv("R_RUN_TINYTEST"), "true")) {
testdir = ifelse(AMR:::dir.exists("inst/tinytest"), testdir = ifelse(AMR:::dir.exists("inst/tinytest"),
"inst/tinytest", "inst/tinytest",
"tinytest"), "tinytest"),
verbose = FALSE) verbose = 99,
cat(attributes(out)$duration, "\n") color = FALSE)
cat("SUMMARY:\n")
print(summary(out)) print(summary(out))
cat("WARNINGS:\n")
print(warnings()) print(warnings())
cat(attributes(out)$duration, "\n")
} }
} }