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(v0.7.1.9036) preserve ab/mo classes in subsetting

new-mo-algorithm
parent
commit
bd252a2984
  1. 4
      DESCRIPTION
  2. 11
      NAMESPACE
  3. 19
      NEWS.md
  4. 9
      R/ab.R
  5. 14
      R/disk.R
  6. 119
      R/filter_ab_class.R
  7. 2
      R/mic.R
  8. 23
      R/mo.R
  9. 4
      R/rsi.R
  10. 2
      docs/LICENSE-text.html
  11. 74
      docs/articles/benchmarks.html
  12. BIN
      docs/articles/benchmarks_files/figure-html/unnamed-chunk-5-1.png
  13. 2
      docs/articles/index.html
  14. 2
      docs/authors.html
  15. 2
      docs/index.html
  16. 49
      docs/news/index.html
  17. 2
      docs/reference/as.rsi.html
  18. 34
      docs/reference/filter_ab_class.html
  19. 4
      docs/reference/index.html
  20. 2
      docs/reference/like.html
  21. 2
      docs/reference/translate.html
  22. 33
      man/filter_ab_class.Rd
  23. 5
      tests/testthat/test-mo.R

4
DESCRIPTION

@ -1,6 +1,6 @@ @@ -1,6 +1,6 @@
Package: AMR
Version: 0.7.1.9035
Date: 2019-08-11
Version: 0.7.1.9036
Date: 2019-08-12
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

11
NAMESPACE

@ -1,5 +1,7 @@ @@ -1,5 +1,7 @@
# Generated by roxygen2: do not edit by hand
S3method("[",ab)
S3method("[",mo)
S3method(as.data.frame,ab)
S3method(as.data.frame,mo)
S3method(as.double,mic)
@ -19,6 +21,7 @@ S3method(kurtosis,data.frame) @@ -19,6 +21,7 @@ S3method(kurtosis,data.frame)
S3method(kurtosis,default)
S3method(kurtosis,matrix)
S3method(pillar_shaft,ab)
S3method(pillar_shaft,disk)
S3method(pillar_shaft,mic)
S3method(pillar_shaft,mo)
S3method(pillar_shaft,rsi)
@ -33,8 +36,6 @@ S3method(print,mo) @@ -33,8 +36,6 @@ S3method(print,mo)
S3method(print,mo_renamed)
S3method(print,mo_uncertainties)
S3method(print,rsi)
S3method(pull,ab)
S3method(pull,mo)
S3method(skewness,data.frame)
S3method(skewness,default)
S3method(skewness,matrix)
@ -42,6 +43,7 @@ S3method(summary,mic) @@ -42,6 +43,7 @@ S3method(summary,mic)
S3method(summary,mo)
S3method(summary,rsi)
S3method(type_sum,ab)
S3method(type_sum,disk)
S3method(type_sum,mic)
S3method(type_sum,mo)
S3method(type_sum,rsi)
@ -86,6 +88,7 @@ export(filter_1st_cephalosporins) @@ -86,6 +88,7 @@ export(filter_1st_cephalosporins)
export(filter_2nd_cephalosporins)
export(filter_3rd_cephalosporins)
export(filter_4th_cephalosporins)
export(filter_5th_cephalosporins)
export(filter_ab_class)
export(filter_aminoglycosides)
export(filter_carbapenems)
@ -167,6 +170,8 @@ export(semi_join_microorganisms) @@ -167,6 +170,8 @@ export(semi_join_microorganisms)
export(set_mo_source)
export(skewness)
export(theme_rsi)
exportMethods("[.ab")
exportMethods("[.mo")
exportMethods(as.data.frame.ab)
exportMethods(as.data.frame.mo)
exportMethods(as.double.mic)
@ -192,8 +197,6 @@ exportMethods(print.mo) @@ -192,8 +197,6 @@ exportMethods(print.mo)
exportMethods(print.mo_renamed)
exportMethods(print.mo_uncertainties)
exportMethods(print.rsi)
exportMethods(pull.ab)
exportMethods(pull.mo)
exportMethods(scale_type.ab)
exportMethods(scale_type.mo)
exportMethods(skewness)

19
NEWS.md

@ -1,4 +1,4 @@ @@ -1,4 +1,4 @@
# AMR 0.7.1.9035
# AMR 0.7.1.9036
### Breaking
* Function `freq()` has moved to a new package, [`clean`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)). Creating frequency tables is actually not the scope of this package (never was) and this function has matured a lot over the last two years. Therefore, a new package was created for data cleaning and checking and it perfectly fits the `freq()` function. The [`clean`](https://github.com/msberends/clean) package is available on CRAN and will be installed automatically when updating the `AMR` package, that now imports it. In a later stage, the `skewness()` and `kurtosis()` functions will be moved to the `clean` package too.
@ -46,16 +46,13 @@ @@ -46,16 +46,13 @@
* Printed info now distinguishes between added and changes values
* Using Verbose mode (i.e. `eucast_rules(..., verbose = TRUE)`) returns more informative and readable output
* Using factors as input now adds missing factors levels when the function changes antibiotic results
* Added tibble printing support for classes `rsi`, `mic`, `ab` and `mo`. When using tibbles containing antibiotic columns, values `S` will print in green, values `I` will print in yellow and values `R` will print in red:
* Added tibble printing support for classes `rsi`, `mic`, `disk`, `ab` `mo`. When using tibbles containing antibiotic columns, values `S` will print in green, values `I` will print in yellow and values `R` will print in red. Microbial IDs (class `mo`) will emphasise on the genus and species, not on the kingdom.
```r
# (run this on your own console, as this page does not support colour printing)
tibble(mo = sample(AMR::microorganisms$fullname, 10),
drug1 = as.rsi(sample(c("S", "I", "R"), 10, replace = TRUE,
prob = c(0.6, 0.1, 0.3))),
drug2 = as.rsi(sample(c("S", "I", "R"), 10, replace = TRUE,
prob = c(0.6, 0.1, 0.3))),
drug3 = as.rsi(sample(c("S", "I", "R"), 10, replace = TRUE,
prob = c(0.6, 0.1, 0.3))))
library(dplyr)
septic_patients %>%
select(mo:AMC) %>%
as_tibble()
```
* Removed class `atc` - using `as.atc()` is now deprecated in favour of `ab_atc()` and this will return a character, not the `atc` class anymore
* Removed deprecated functions `abname()`, `ab_official()`, `atc_name()`, `atc_official()`, `atc_property()`, `atc_tradenames()`, `atc_trivial_nl()`
@ -69,8 +66,10 @@ @@ -69,8 +66,10 @@
* Fix for using `mo_*` functions where the coercion uncertainties and failures would not be available through `mo_uncertainties()` and `mo_failures()` anymore
* Deprecated the `country` parameter of `mdro()` in favour of the already existing `guideline` parameter to support multiple guidelines within one country
* The `name` of `RIF` is now Rifampicin instead of Rifampin
* The `antibiotics` data set is now sorted by name and all cephalosporines now have their generation between brackets
* The `antibiotics` data set is now sorted by name and all cephalosporins now have their generation between brackets
* Speed improvement for `guess_ab_col()` which is now 30 times faster for antibiotic abbreviations
* Improved `filter_ab_class()` to be more reliable and to support 5th generation cephalosporins
* Classes `ab` and `mo` will now be preserved in any subsetting
#### Other
* Added Dr Bart Meijer, Dr Dennis Souverein and Annick Lenglet as contributors

9
R/ab.R

@ -279,12 +279,13 @@ as.data.frame.ab <- function (x, ...) { @@ -279,12 +279,13 @@ as.data.frame.ab <- function (x, ...) {
}
}
#' @exportMethod pull.ab
#' @exportMethod [.ab
#' @export
#' @importFrom dplyr pull
#' @noRd
pull.ab <- function(.data, ...) {
pull(as.data.frame(.data), ...)
"[.ab" <- function (x, ...) {
# this function is needed to preserve the "ab" class for any subsetting, like df %>% filter(...)
y <- NextMethod()
structure(y, class = "ab")
}
#' @importFrom pillar type_sum

14
R/disk.R

@ -90,3 +90,17 @@ print.disk <- function(x, ...) { @@ -90,3 +90,17 @@ print.disk <- function(x, ...) {
cat("Class 'disk'\n")
print(as.integer(x), quote = FALSE)
}
#' @importFrom pillar type_sum
#' @export
type_sum.disk <- function(x) {
"disk"
}
#' @importFrom pillar pillar_shaft
#' @export
pillar_shaft.disk <- function(x, ...) {
out <- trimws(format(x))
out[is.na(x)] <- pillar::style_na(NA)
pillar::new_pillar_shaft_simple(out, align = "right", min_width = 3)
}

119
R/filter_ab_class.R

@ -22,12 +22,12 @@ @@ -22,12 +22,12 @@
#' Filter isolates on result in antibiotic class
#'
#' Filter isolates on results in specific antibiotic variables based on their class (ATC groups). This makes it easy to get a list of isolates that were tested for e.g. any aminoglycoside.
#' @param tbl a data set
#' @param ab_class an antimicrobial class, like \code{"carbapenems"}. More specifically, this should be a text that can be found in a 4th level ATC group (chemical subgroup) or a 5th level ATC group (chemical substance), please see \href{https://www.whocc.no/atc/structure_and_principles/}{this explanation on the WHOCC website}.
#' @param x a data set
#' @param ab_class an antimicrobial class, like \code{"carbapenems"}, as can be found in \code{AMR::antibiotics$group}
#' @param result an antibiotic result: S, I or R (or a combination of more of them)
#' @param scope the scope to check which variables to check, can be \code{"any"} (default) or \code{"all"}
#' @param ... parameters passed on to \code{\link[dplyr]{filter_at}}
#' @details The \code{\link{antibiotics}} data set will be searched for \code{ab_class} in the columns \code{atc_group1} and \code{atc_group2} (case-insensitive). Next, \code{tbl} will be checked for column names with a value in any abbreviations, codes or official names found in the \code{antibiotics} data set.
#' @details The \code{group} column in \code{\link{antibiotics}} data set will be searched for \code{ab_class} (case-insensitive). If no results are found, the \code{atc_group1} and \code{atc_group2} columns will be searched. Next, \code{x} will be checked for column names with a value in any abbreviations, codes or official names found in the \code{antibiotics} data set.
#' @rdname filter_ab_class
#' @keywords filter fillter_class
#' @importFrom dplyr filter_at %>% select vars any_vars all_vars
@ -62,7 +62,7 @@ @@ -62,7 +62,7 @@
#' septic_patients %>%
#' filter_aminoglycosides("R", "all") %>%
#' filter_fluoroquinolones("R", "all")
filter_ab_class <- function(tbl,
filter_ab_class <- function(x,
ab_class,
result = NULL,
scope = "any",
@ -71,7 +71,7 @@ filter_ab_class <- function(tbl, @@ -71,7 +71,7 @@ filter_ab_class <- function(tbl,
if (is.null(result)) {
result <- c("S", "I", "R")
}
# make result = "IR" work too:
# make result = "SI" work too:
result <- unlist(strsplit(result, ""))
if (!all(result %in% c("S", "I", "R"))) {
@ -81,8 +81,8 @@ filter_ab_class <- function(tbl, @@ -81,8 +81,8 @@ filter_ab_class <- function(tbl,
stop("`scope` must be one of: any, all", call. = FALSE)
}
vars_df <- colnames(tbl)[tolower(colnames(tbl)) %in% tolower(ab_class_vars(ab_class))]
atc_groups <- ab_class_atcgroups(ab_class)
vars_df <- colnames(x)[tolower(colnames(x)) %in% tolower(ab_class_vars(ab_class))]
ab_group <- find_ab_group(ab_class)
if (length(vars_df) > 0) {
if (length(result) == 1) {
@ -101,29 +101,29 @@ filter_ab_class <- function(tbl, @@ -101,29 +101,29 @@ filter_ab_class <- function(tbl,
}
}
if (length(vars_df) > 1) {
scope <- paste(scope, "of ")
scope <- paste(scope, "of columns ")
} else {
scope <- ""
scope <- "column "
}
message(blue(paste0("Filtering on ", atc_groups, ": ", scope,
message(blue(paste0("Filtering on ", ab_group, ": ", scope,
paste(bold(paste0("`", vars_df, "`")), collapse = scope_txt), operator, toString(result))))
tbl %>%
x %>%
filter_at(vars(vars_df),
scope_fn(. %in% result),
...)
} else {
warning(paste0("no antibiotics of class ", atc_groups, " found, leaving data unchanged"), call. = FALSE)
tbl
warning(paste0("no antibiotics of class ", ab_group, " found, leaving data unchanged"), call. = FALSE)
x
}
}
#' @rdname filter_ab_class
#' @export
filter_aminoglycosides <- function(tbl,
filter_aminoglycosides <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "aminoglycoside",
result = result,
scope = scope,
@ -132,11 +132,11 @@ filter_aminoglycosides <- function(tbl, @@ -132,11 +132,11 @@ filter_aminoglycosides <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_carbapenems <- function(tbl,
filter_carbapenems <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "carbapenem",
result = result,
scope = scope,
@ -145,11 +145,11 @@ filter_carbapenems <- function(tbl, @@ -145,11 +145,11 @@ filter_carbapenems <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_cephalosporins <- function(tbl,
filter_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "cephalosporin",
result = result,
scope = scope,
@ -158,12 +158,12 @@ filter_cephalosporins <- function(tbl, @@ -158,12 +158,12 @@ filter_cephalosporins <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_1st_cephalosporins <- function(tbl,
filter_1st_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
ab_class = "first-generation cephalosporin",
filter_ab_class(x = x,
ab_class = "cephalosporins (1st gen.)",
result = result,
scope = scope,
...)
@ -171,12 +171,12 @@ filter_1st_cephalosporins <- function(tbl, @@ -171,12 +171,12 @@ filter_1st_cephalosporins <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_2nd_cephalosporins <- function(tbl,
filter_2nd_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
ab_class = "second-generation cephalosporin",
filter_ab_class(x = x,
ab_class = "cephalosporins (2nd gen.)",
result = result,
scope = scope,
...)
@ -184,12 +184,12 @@ filter_2nd_cephalosporins <- function(tbl, @@ -184,12 +184,12 @@ filter_2nd_cephalosporins <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_3rd_cephalosporins <- function(tbl,
filter_3rd_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
ab_class = "third-generation cephalosporin",
filter_ab_class(x = x,
ab_class = "cephalosporins (3rd gen.)",
result = result,
scope = scope,
...)
@ -197,12 +197,12 @@ filter_3rd_cephalosporins <- function(tbl, @@ -197,12 +197,12 @@ filter_3rd_cephalosporins <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_4th_cephalosporins <- function(tbl,
filter_4th_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
ab_class = "fourth-generation cephalosporin",
filter_ab_class(x = x,
ab_class = "cephalosporins (4th gen.)",
result = result,
scope = scope,
...)
@ -210,11 +210,24 @@ filter_4th_cephalosporins <- function(tbl, @@ -210,11 +210,24 @@ filter_4th_cephalosporins <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_fluoroquinolones <- function(tbl,
filter_5th_cephalosporins <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(x = x,
ab_class = "cephalosporins (5th gen.)",
result = result,
scope = scope,
...)
}
#' @rdname filter_ab_class
#' @export
filter_fluoroquinolones <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "fluoroquinolone",
result = result,
scope = scope,
@ -223,11 +236,11 @@ filter_fluoroquinolones <- function(tbl, @@ -223,11 +236,11 @@ filter_fluoroquinolones <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_glycopeptides <- function(tbl,
filter_glycopeptides <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "glycopeptide",
result = result,
scope = scope,
@ -236,11 +249,11 @@ filter_glycopeptides <- function(tbl, @@ -236,11 +249,11 @@ filter_glycopeptides <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_macrolides <- function(tbl,
filter_macrolides <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "macrolide",
result = result,
scope = scope,
@ -249,11 +262,11 @@ filter_macrolides <- function(tbl, @@ -249,11 +262,11 @@ filter_macrolides <- function(tbl,
#' @rdname filter_ab_class
#' @export
filter_tetracyclines <- function(tbl,
filter_tetracyclines <- function(x,
result = NULL,
scope = "any",
...) {
filter_ab_class(tbl = tbl,
filter_ab_class(x = x,
ab_class = "tetracycline",
result = result,
scope = scope,
@ -262,8 +275,9 @@ filter_tetracyclines <- function(tbl, @@ -262,8 +275,9 @@ filter_tetracyclines <- function(tbl,
#' @importFrom dplyr %>% filter_at vars any_vars select
ab_class_vars <- function(ab_class) {
ab_class <- gsub("[^a-z0-9]+", ".*", ab_class)
ab_vars <- AMR::antibiotics %>%
filter_at(vars(c("atc_group1", "atc_group2")), any_vars(. %like% ab_class)) %>%
filter(group %like% ab_class) %>%
select(ab:name, abbreviations, synonyms) %>%
unlist() %>%
as.matrix() %>%
@ -272,18 +286,29 @@ ab_class_vars <- function(ab_class) { @@ -272,18 +286,29 @@ ab_class_vars <- function(ab_class) {
strsplit("|", fixed = TRUE) %>%
unlist() %>%
unique()
ab_vars[!is.na(ab_vars)]
ab_vars <- ab_vars[!ab_vars %in% c(NA, "", "NA") & nchar(ab_vars) > 2]
if (length(ab_vars) == 0) {
# try again, searching atc_group1 and atc_group2 columns
ab_vars <- AMR::antibiotics %>%
filter_at(vars(c("atc_group1", "atc_group2")), any_vars(. %like% ab_class)) %>%
select(ab:name, abbreviations, synonyms) %>%
unlist() %>%
as.matrix() %>%
as.character() %>%
paste(collapse = "|") %>%
strsplit("|", fixed = TRUE) %>%
unlist() %>%
unique()
ab_vars <- ab_vars[!ab_vars %in% c(NA, "", "NA") & nchar(ab_vars) > 2]
}
ab_vars
}
#' @importFrom dplyr %>% filter pull
ab_class_atcgroups <- function(ab_class) {
find_ab_group <- function(ab_class) {
ifelse(ab_class %in% c("aminoglycoside",
"carbapenem",
"cephalosporin",
"first-generation cephalosporin",
"second-generation cephalosporin",
"third-generation cephalosporin",
"fourth-generation cephalosporin",
"fluoroquinolone",
"glycopeptide",
"macrolide",
@ -291,7 +316,7 @@ ab_class_atcgroups <- function(ab_class) { @@ -291,7 +316,7 @@ ab_class_atcgroups <- function(ab_class) {
paste0(ab_class, "s"),
AMR::antibiotics %>%
filter(ab %in% ab_class_vars(ab_class)) %>%
pull("atc_group2") %>%
pull(group) %>%
unique() %>%
tolower() %>%
paste(collapse = "/")

2
R/mic.R

@ -289,6 +289,6 @@ type_sum.mic <- function(x) { @@ -289,6 +289,6 @@ type_sum.mic <- function(x) {
#' @export
pillar_shaft.mic <- function(x, ...) {
out <- trimws(format(x))
out[is.na(x)] <- NA
out[is.na(x)] <- pillar::style_na(NA)
pillar::new_pillar_shaft_simple(out, align = "right", min_width = 4)
}

23
R/mo.R

@ -1521,8 +1521,18 @@ type_sum.mo <- function(x) { @@ -1521,8 +1521,18 @@ type_sum.mo <- function(x) {
#' @export
pillar_shaft.mo <- function(x, ...) {
out <- format(x)
out[is.na(x)] <- pillar::style_na("NA")
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 11)
# grey out the kingdom (part before first "_")
first_parts <- unlist(lapply(gregexpr(pattern = '_', x[!is.na(x)], fixed = TRUE), min))
first_parts[first_parts < 0] <- 0
out[!is.na(x)] <- paste0(pillar::style_subtle(substr(x[!is.na(x)], 0, first_parts)),
substr(x[!is.na(x)], first_parts + 1, nchar(x)))
out[is.na(x)] <- pillar::style_na(" NA")
out[x == "UNKNOWN"] <- pillar::style_na(" UNKNOWN")
out <- gsub("_", pillar::style_subtle("_"), out)
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 12)
}
#' @exportMethod summary.mo
@ -1556,12 +1566,13 @@ as.data.frame.mo <- function(x, ...) { @@ -1556,12 +1566,13 @@ as.data.frame.mo <- function(x, ...) {
}
}
#' @exportMethod pull.mo
#' @exportMethod [.mo
#' @export
#' @importFrom dplyr pull
#' @noRd
pull.mo <- function(.data, ...) {
pull(as.data.frame(.data), ...)
"[.mo" <- function (x, ...) {
# this function is needed to preserve the "mo" class for any subsetting, like df %>% filter(...)
y <- NextMethod()
to_class_mo(y)
}
#' @rdname as.mo

4
R/rsi.R

@ -486,9 +486,9 @@ type_sum.rsi <- function(x) { @@ -486,9 +486,9 @@ type_sum.rsi <- function(x) {
#' @export
pillar_shaft.rsi <- function(x, ...) {
out <- trimws(format(x))
out[is.na(x)] <- pillar::style_subtle("NA")
out[is.na(x)] <- pillar::style_subtle(" NA")
out[x == "S"] <- bgGreen(white(" S "))
out[x == "I"] <- bgYellow(black(" I "))
out[x == "R"] <- bgRed(white(" R "))
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 4)
pillar::new_pillar_shaft_simple(out, align = "left", min_width = 3)
}

2
docs/LICENSE-text.html

@ -78,7 +78,7 @@ @@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>

74
docs/articles/benchmarks.html

@ -40,7 +40,7 @@ @@ -40,7 +40,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>
@ -185,7 +185,7 @@ @@ -185,7 +185,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">11 August 2019</h4>
<h4 class="date">12 August 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -210,14 +210,14 @@ @@ -210,14 +210,14 @@
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"><span class="co"># as.mo("sau") 8.3 8.5 14.0 9.1 9.2 39.0 10</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"><span class="co"># as.mo("stau") 31.0 32.0 38.0 32.0 47.0 53.0 10</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"><span class="co"># as.mo("staaur") 8.2 8.4 20.0 8.7 40.0 55.0 10</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"><span class="co"># as.mo("STAAUR") 8.2 8.4 10.0 8.9 9.4 24.0 10</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"><span class="co"># as.mo("S. aureus") 23.0 24.0 33.0 24.0 24.0 99.0 10</span></a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="co"># as.mo("S. aureus") 23.0 23.0 29.0 24.0 40.0 42.0 10</span></a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># as.mo("Staphylococcus aureus") 3.7 3.9 4.1 4.1 4.2 4.6 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"><span class="co"># as.mo("sau") 8.6 9.2 9.9 9.7 11.0 12 10</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"><span class="co"># as.mo("stau") 32.0 33.0 33.0 33.0 34.0 35 10</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"><span class="co"># as.mo("staaur") 8.7 9.0 13.0 9.6 11.0 26 10</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"><span class="co"># as.mo("STAAUR") 8.6 9.1 13.0 9.5 9.7 28 10</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"><span class="co"># as.mo("S. aureus") 24.0 24.0 28.0 25.0 26.0 41 10</span></a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="co"># as.mo("S. aureus") 24.0 24.0 37.0 24.0 39.0 120 10</span></a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># as.mo("Staphylococcus aureus") 4.0 4.2 6.0 4.3 4.6 21 10</span></a></code></pre></div>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Thermus islandicus</em> (<code>B_THERMS_ISL</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">T.islandicus &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"theisl"</span>),</a>
@ -229,12 +229,12 @@ @@ -229,12 +229,12 @@
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(T.islandicus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 270 270 280 290 290 300 10</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 280 290 290 290 300 300 10</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 130 130 150 150 160 160 10</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 130 130 150 150 150 160 10</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 46 48 54 50 63 71 10</span></a></code></pre></div>
<p>That takes 8.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("theisl") 270 280 290 290 310 320 10</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("THEISL") 280 290 300 290 300 310 10</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("T. islandicus") 140 140 150 140 160 170 10</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("T. islandicus") 140 150 160 160 160 170 10</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Thermus islandicus") 48 49 60 60 68 77 10</span></a></code></pre></div>
<p>That takes 9.5 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Thermus islandicus</em> (which is very uncommon):</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/par">par</a></span>(<span class="dt">mar =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">5</span>, <span class="dv">16</span>, <span class="dv">4</span>, <span class="dv">2</span>)) <span class="co"># set more space for left margin text (16)</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2"></a>
@ -280,8 +280,8 @@ @@ -280,8 +280,8 @@
<a class="sourceLine" id="cb5-24" data-line-number="24"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-27" data-line-number="27"><span class="co"># mo_name(x) 623 631 659 637 697 729 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.64 seconds (637 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb5-27" data-line-number="27"><span class="co"># mo_name(x) 596 622 635 626 635 704 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.63 seconds (626 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -294,10 +294,10 @@ @@ -294,10 +294,10 @@
<a class="sourceLine" id="cb6-5" data-line-number="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># A 6.290 6.730 7.170 7.010 7.760 8.09 10</span></a>
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># B 22.600 22.700 26.200 23.000 25.400 44.30 10</span></a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># C 0.798 0.806 0.874 0.844 0.891 1.05 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># A 6.700 6.950 7.410 7.600 7.730 8.06 10</span></a>
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># B 22.900 23.900 27.000 24.100 24.200 46.00 10</span></a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># C 0.772 0.833 0.876 0.874 0.918 1.03 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0009 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb7-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
<a class="sourceLine" id="cb7-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
@ -310,14 +310,14 @@ @@ -310,14 +310,14 @@
<a class="sourceLine" id="cb7-10" data-line-number="10"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># A 0.455 0.458 0.471 0.465 0.482 0.504 10</span></a>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># B 0.480 0.482 0.497 0.491 0.497 0.554 10</span></a>
<a class="sourceLine" id="cb7-15" data-line-number="15"><span class="co"># C 0.662 0.687 0.754 0.750 0.788 0.964 10</span></a>
<a class="sourceLine" id="cb7-16" data-line-number="16"><span class="co"># D 0.484 0.484 0.496 0.488 0.501 0.544 10</span></a>
<a class="sourceLine" id="cb7-17" data-line-number="17"><span class="co"># E 0.442 0.450 0.459 0.456 0.462 0.492 10</span></a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="co"># F 0.440 0.447 0.456 0.452 0.463 0.486 10</span></a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># G 0.450 0.452 0.462 0.459 0.463 0.485 10</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># H 0.455 0.461 0.467 0.467 0.471 0.492 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># A 0.472 0.475 0.553 0.562 0.607 0.675 10</span></a>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># B 0.474 0.482 0.560 0.493 0.577 0.973 10</span></a>
<a class="sourceLine" id="cb7-15" data-line-number="15"><span class="co"># C 0.766 0.820 0.899 0.881 0.941 1.070 10</span></a>
<a class="sourceLine" id="cb7-16" data-line-number="16"><span class="co"># D 0.459 0.485 0.539 0.503 0.569 0.744 10</span></a>
<a class="sourceLine" id="cb7-17" data-line-number="17"><span class="co"># E 0.421 0.448 0.470 0.456 0.488 0.543 10</span></a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="co"># F 0.430 0.457 0.534 0.495 0.592 0.738 10</span></a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># G 0.420 0.450 0.477 0.463 0.491 0.586 10</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># H 0.426 0.437 0.500 0.447 0.461 0.776 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
@ -344,13 +344,13 @@ @@ -344,13 +344,13 @@
<a class="sourceLine" id="cb8-18" data-line-number="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb8-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-21" data-line-number="21"><span class="co"># en 17.66 17.86 18.50 18.49 19.14 19.36 10</span></a>
<a class="sourceLine" id="cb8-22" data-line-number="22"><span class="co"># de 19.03 19.38 19.64 19.49 20.01 20.42 10</span></a>
<a class="sourceLine" id="cb8-23" data-line-number="23"><span class="co"># nl 24.40 25.23 30.77 25.78 41.94 44.93 10</span></a>
<a class="sourceLine" id="cb8-24" data-line-number="24"><span class="co"># es 19.18 19.22 23.30 19.53 21.34 39.20 10</span></a>
<a class="sourceLine" id="cb8-25" data-line-number="25"><span class="co"># it 19.02 19.24 23.53 19.57 20.35 50.89 10</span></a>
<a class="sourceLine" id="cb8-26" data-line-number="26"><span class="co"># fr 19.28 19.33 19.87 19.57 20.19 21.25 10</span></a>
<a class="sourceLine" id="cb8-27" data-line-number="27"><span class="co"># pt 18.89 19.14 19.77 19.67 20.21 20.99 10</span></a></code></pre></div>
<a class="sourceLine" id="cb8-21" data-line-number="21"><span class="co"># en 18.77 19.83 25.36 20.44 28.51 45.88 10</span></a>
<a class="sourceLine" id="cb8-22" data-line-number="22"><span class="co"># de 20.37 20.86 23.19 21.45 22.23 39.08 10</span></a>
<a class="sourceLine" id="cb8-23" data-line-number="23"><span class="co"># nl 26.50 27.09 27.74 27.58 28.10 29.74 10</span></a>
<a class="sourceLine" id="cb8-24" data-line-number="24"><span class="co"># es 20.82 21.18 21.66 21.27 22.04 23.64 10</span></a>
<a class="sourceLine" id="cb8-25" data-line-number="25"><span class="co"># it 19.82 20.65 25.98 21.22 22.13 50.42 10</span></a>
<a class="sourceLine" id="cb8-26" data-line-number="26"><span class="co"># fr 20.07 21.20 21.68 21.47 21.89 23.76 10</span></a>
<a class="sourceLine" id="cb8-27" data-line-number="27"><span class="co"># pt 19.87 20.63 22.76 21.07 21.68 38.11 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>

2
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@ -78,7 +78,7 @@ @@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>

2
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@ -42,7 +42,7 @@ @@ -42,7 +42,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>

49
docs/news/index.html

@ -78,7 +78,7 @@ @@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>
@ -225,9 +225,9 @@ @@ -225,9 +225,9 @@
</div>
<div id="amr-0-7-1-9035" class="section level1">
<div id="amr-0-7-1-9036" class="section level1">
<h1 class="page-header">
<a href="#amr-0-7-1-9035" class="anchor"></a>AMR 0.7.1.9035<small> Unreleased </small>
<a href="#amr-0-7-1-9036" class="anchor"></a>AMR 0.7.1.9036<small> Unreleased </small>
</h1>
<div id="breaking" class="section level3">
<h3 class="hasAnchor">
@ -289,15 +289,12 @@ @@ -289,15 +289,12 @@
</ul>
</li>
<li>
<p>Added tibble printing support for classes <code>rsi</code>, <code>mic</code>, <code>ab</code> and <code>mo</code>. When using tibbles containing antibiotic columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red:</p>
<p>Added tibble printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using tibbles containing antibiotic columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># (run this on your own console, as this page does not support colour printing)</span></a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="kw">tibble</span>(<span class="dt">mo =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/sample">sample</a></span>(AMR<span class="op">::</span>microorganisms<span class="op">$</span>fullname, <span class="dv">10</span>),</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="dt">drug1 =</span> <span class="kw"><a href="../reference/as.rsi.html">as.rsi</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/sample">sample</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>), <span class="dv">10</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, </a>
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.6</span>, <span class="fl">0.1</span>, <span class="fl">0.3</span>))),</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="dt">drug2 =</span> <span class="kw"><a href="../reference/as.rsi.html">as.rsi</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/sample">sample</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>), <span class="dv">10</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.6</span>, <span class="fl">0.1</span>, <span class="fl">0.3</span>))),</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"> <span class="dt">drug3 =</span> <span class="kw"><a href="../reference/as.rsi.html">as.rsi</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/sample">sample</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>), <span class="dv">10</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"> <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.6</span>, <span class="fl">0.1</span>, <span class="fl">0.3</span>))))</a></code></pre></div>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb3-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(mo<span class="op">:</span>AMC) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">as_tibble</a></span>()</a></code></pre></div>
</li>
<li>Removed class <code>atc</code> - using <code><a href="../reference/AMR-deprecated.html">as.atc()</a></code> is now deprecated in favour of <code><a href="../reference/ab_property.html">ab_atc()</a></code> and this will return a character, not the <code>atc</code> class anymore</li>
<li>Removed deprecated functions <code>abname()</code>, <code>ab_official()</code>, <code>atc_name()</code>, <code>atc_official()</code>, <code>atc_property()</code>, <code>atc_tradenames()</code>, <code>atc_trivial_nl()</code>
@ -316,8 +313,10 @@ @@ -316,8 +313,10 @@
<li>Fix for using <code>mo_*</code> functions where the coercion uncertainties and failures would not be available through <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> and <code><a href="../reference/as.mo.html">mo_failures()</a></code> anymore</li>
<li>Deprecated the <code>country</code> parameter of <code><a href="../reference/mdro.html">mdro()</a></code> in favour of the already existing <code>guideline</code> parameter to support multiple guidelines within one country</li>
<li>The <code>name</code> of <code>RIF</code> is now Rifampicin instead of Rifampin</li>
<li>The <code>antibiotics</code> data set is now sorted by name and all cephalosporines now have their generation between brackets</li>
<li><p>Speed improvement for <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> which is now 30 times faster for antibiotic abbreviations</p></li>
<li>The <code>antibiotics</code> data set is now sorted by name and all cephalosporins now have their generation between brackets</li>
<li>Speed improvement for <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> which is now 30 times faster for antibiotic abbreviations</li>
<li>Improved <code><a href="../reference/filter_ab_class.html">filter_ab_class()</a></code> to be more reliable and to support 5th generation cephalosporins</li>
<li><p>Classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting</p></li>
</ul>
<div id="other" class="section level4">
<h4 class="hasAnchor">
@ -339,7 +338,7 @@ @@ -339,7 +338,7 @@
<li>
<p>Function <code><a href="../reference/portion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/portion.html">portion_df()</a></code> to immediately show resistance percentages and number of available isolates:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="st"> </span><span class="kw">select</span>(AMX, CIP) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(AMX, CIP) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/portion.html">rsi_df</a></span>()</a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="co"># antibiotic interpretation value isolates</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="co"># 1 Amoxicillin SI 0.4442636 546</span></a>
@ -472,7 +471,7 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Tra @@ -472,7 +471,7 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Tra
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>()</a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="co"># grouped boxplots:</span></a>
<a class="sourceLine" id="cb6-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="st"> </span><span class="kw">group_by</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="st"> </span><span class="kw">freq</span>(age) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>()</a></code></pre></div>
</li>
@ -607,9 +606,9 @@ These functions use <code><a href="../reference/AMR-deprecated.html">as.atc()</a @@ -607,9 +606,9 @@ These functions use <code><a href="../reference/AMR-deprecated.html">as.atc()</a
<a class="sourceLine" id="cb11-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
<p>is equal to:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="st"> </span><span class="kw">mutate</span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb12-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/stats/topics/filter">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="st"> </span><span class="kw">select</span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb12-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
</li>
<li>New function <code><a href="../reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code>
</li>
@ -713,7 +712,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -713,7 +712,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<a class="sourceLine" id="cb16-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
<a class="sourceLine" id="cb16-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="st"> </span><span class="kw">mutate</span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="st"> </span><span class="kw">freq</span>(genus)</a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
<a class="sourceLine" id="cb16-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -721,7 +720,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -721,7 +720,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<a class="sourceLine" id="cb16-9" data-line-number="9"></a>
<a class="sourceLine" id="cb16-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
<a class="sourceLine" id="cb16-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-12" data-line-number="12"><span class="st"> </span><span class="kw">group_by</span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb16-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb16-13" data-line-number="13"><span class="st"> </span><span class="kw">freq</span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
</li>
<li>Header info is now available as a list, with the <code>header</code> function</li>
@ -734,7 +733,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -734,7 +733,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>New parameter <code>droplevels</code> to exclude empty factor levels when input is a factor</li>
<li>Factor levels will be in header when present in input data (maximum of 5)</li>
<li>Fix for using <code>select()</code> on frequency tables</li>
<li>Fix for using <code><a href="https://dplyr.tidyverse.org/reference/select.html">select()</a></code> on frequency tables</li>
</ul>
</li>
<li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
@ -814,14 +813,14 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -814,14 +813,14 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<li>
<p>Support for grouping variables, test with:</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="st"> </span><span class="kw">group_by</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-3" data-line-number="3"><span class="st"> </span><span class="kw">freq</span>(gender)</a></code></pre></div>
</li>
<li>
<p>Support for (un)selecting columns:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="st"> </span><span class="kw">freq</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="st"> </span><span class="kw">select</span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li>
<li>Check for <code><a href="https://www.rdocumentation.org/packages/hms/topics/Deprecated">hms::is.hms</a></code>
</li>
@ -978,7 +977,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -978,7 +977,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">select</span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
<a class="sourceLine" id="cb25-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
<a class="sourceLine" id="cb25-4" data-line-number="4"></a>
@ -1237,7 +1236,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a @@ -1237,7 +1236,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-0-7-1-9035">0.7.1.9035</a></li>
<li><a href="#amr-0-7-1-9036">0.7.1.9036</a></li>
<li><a href="#amr-0-7-1">0.7.1</a></li>
<li><a href="#amr-0-7-0">0.7.0</a></li>
<li><a href="#amr-0-6-1">0.6.1</a></li>

2
docs/reference/as.rsi.html

@ -80,7 +80,7 @@ @@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9035</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>

34
docs/reference/filter_ab_class.html

@ -80,7 +80,7 @@ @@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9036</span>
</span>
</div>
@ -234,40 +234,42 @@ @@ -234,40 +234,42 @@
</div>
<pre class="usage"><span class='fu'>filter_ab_class</span>(<span class='no'>tbl</span>, <span class='no'>ab_class</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<pre class="usage"><span class='fu'>filter_ab_class</span>(<span class='no'>x</span>, <span class='no'>ab_class</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_aminoglycosides</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_aminoglycosides</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_carbapenems</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_carbapenems</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_cephalosporins</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_cephalosporins</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_1st_cephalosporins</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_1st_cephalosporins</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_2nd_cephalosporins</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_2nd_cephalosporins</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_3rd_cephalosporins</span>(<span class='no'>tbl</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)