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count_all and some fixes
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 0.4.0.9001
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Date: 2018-10-02
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Version: 0.4.0.9002
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Date: 2018-10-12
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Title: Antimicrobial Resistance Analysis
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Authors@R: c(
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person(
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@ -63,6 +63,7 @@ export(count_IR)
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export(count_R)
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export(count_S)
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export(count_SI)
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export(count_all)
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export(count_df)
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export(facet_rsi)
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export(first_isolate)
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12
NEWS.md
12
NEWS.md
@ -1,11 +1,23 @@
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# 0.4.0.90xx (latest development version)
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#### New
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* Function `count_all` to get all available isolates (that like all `portion_*` and `count_*` functions also supports `summarise` and `group_by`), the old `n_rsi` is now an alias of `count_all`
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#### Changed
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* Fix for `portion_*(..., as_percent = TRUE)` when minimal amount of isolates would not be met
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* Using `portion_*` functions now throws a warning when total available isolate is below parameter `minimum`
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* `as.mo` will not set package name as attribute anymore
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* Check for `hms::is.hms` in frequency tables
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* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
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* Fix for `mo_property` not working properly
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* Support for class `difftime` in frequency tables
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* Support for named vectors of class `mo`, useful for `top_freq()`
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* AI improvements for `as.mo`:
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* `"CRS"` -> *Stenotrophomonas maltophilia*
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* `"CRSM"` -> *Stenotrophomonas maltophilia*
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* `"MSSA"` -> *Staphylococcus aureus*
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* `"MSSE"` -> *Staphylococcus epidermidis*
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* Fix for `join` functions
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#### Other
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* Updated vignettes to comply with README
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41
R/count.R
41
R/count.R
@ -21,15 +21,15 @@
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#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}.
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#'
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#' \code{count_R} and \code{count_IR} can be used to count resistant isolates, \code{count_S} and \code{count_SI} can be used to count susceptible isolates.\cr
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#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed.
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#' @inheritParams portion
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#' @details \strong{Remember that you should filter your table to let it contain only first isolates!} Use \code{\link{first_isolate}} to determine them in your data set.
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#' @details These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
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#'
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#' These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
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#' \code{n_rsi} is an alias of \code{count_all}. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to \code{\link{n_distinct}}. Their function is equal to \code{count_S(...) + count_IR(...)}.
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#'
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#' \code{count_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and counts the amounts of R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each variable with class \code{"rsi"}.
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#' @source Wickham H. \strong{Tidy Data.} The Journal of Statistical Software, vol. 59, 2014. \url{http://vita.had.co.nz/papers/tidy-data.html}
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#' @seealso \code{\link{portion}_*} to calculate microbial resistance and susceptibility.\cr
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#' \code{\link{n_rsi}} to count all cases where antimicrobial results are available.
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#' @seealso \code{\link{portion}_*} to calculate microbial resistance and susceptibility.
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#' @keywords resistance susceptibility rsi antibiotics isolate isolates
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#' @return Integer
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#' @rdname count
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@ -47,6 +47,10 @@
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#' count_S(septic_patients$amox)
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#' count_SI(septic_patients$amox)
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#'
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#' # Count all available isolates
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#' count_all(septic_patients$amox)
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#' n_rsi(septic_patients$amox)
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#'
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#' # Since n_rsi counts available isolates, you can
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#' # calculate back to count e.g. non-susceptible isolates.
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#' # This results in the same:
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@ -59,21 +63,22 @@
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#' summarise(R = count_R(cipr),
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#' I = count_I(cipr),
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#' S = count_S(cipr),
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#' n = n_rsi(cipr), # the actual total; sum of all three
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#' n1 = count_all(cipr), # the actual total; sum of all three
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#' n2 = n_rsi(cipr), # same - analogous to n_distinct
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#' total = n()) # NOT the amount of tested isolates!
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#'
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#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
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#' # so we can see that combination therapy does a lot more than mono therapy.
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#' # Please mind that `portion_S` calculates percentages right away instead.
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#' count_S(septic_patients$amcl) # S = 1056 (67.3%)
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#' n_rsi(septic_patients$amcl) # n = 1570
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#' count_S(septic_patients$amcl) # S = 1057 (67.1%)
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#' count_all(septic_patients$amcl) # n = 1576
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#'
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#' count_S(septic_patients$gent) # S = 1363 (74.0%)
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#' n_rsi(septic_patients$gent) # n = 1842
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#' count_S(septic_patients$gent) # S = 1372 (74.0%)
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#' count_all(septic_patients$gent) # n = 1855
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#'
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#' with(septic_patients,
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#' count_S(amcl, gent)) # S = 1385 (92.1%)
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#' with(septic_patients, # n = 1504
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#' count_S(amcl, gent)) # S = 1396 (92.0%)
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#' with(septic_patients, # n = 1517
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#' n_rsi(amcl, gent))
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#'
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#' # Get portions S/I/R immediately of all rsi columns
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@ -140,6 +145,20 @@ count_S <- function(...) {
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only_count = TRUE)
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}
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#' @rdname count
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#' @export
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count_all <- function(...) {
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# only print warnings once, if needed
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count_S(...) + suppressWarnings(count_IR(...))
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}
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#' @rdname count
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#' @export
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n_rsi <- function(...) {
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# only print warnings once, if needed
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count_S(...) + suppressWarnings(count_IR(...))
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}
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#' @rdname count
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#' @importFrom dplyr %>% select_if bind_rows summarise_if mutate group_vars select everything
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#' @export
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@ -507,10 +507,10 @@ EUCAST_rules <- function(tbl,
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# overig
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edit_rsi(to = 'R',
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rows = which(tbl$genus %in% c('Leuconostoc', 'Pediococcus')),
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cols = c(vanc, teic))
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cols = glycopeptides)
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edit_rsi(to = 'R',
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rows = which(tbl$genus == 'Lactobacillus'),
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cols = c(vanc, teic))
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cols = glycopeptides)
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edit_rsi(to = 'R',
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rows = which(tbl$fullname %like% '^Clostridium (ramosum|innocuum)'),
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cols = vanc)
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9
R/freq.R
9
R/freq.R
@ -336,6 +336,13 @@ frequency_tbl <- function(x,
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header <- header %>% paste0(markdown_line, '\nLongest: ', x %>% base::nchar() %>% base::max(na.rm = TRUE))
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}
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if (NROW(x) > 0 & any(class(x) == "difftime")) {
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header <- header %>% paste0('\n')
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header <- header %>% paste(markdown_line, '\nUnits: ', attributes(x)$units)
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x <- as.double(x)
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# after this, the numeric header continues
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}
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if (NROW(x) > 0 & any(class(x) %in% c('double', 'integer', 'numeric', 'raw', 'single'))) {
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# right align number
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Tukey_five <- stats::fivenum(x, na.rm = TRUE)
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@ -351,7 +358,7 @@ frequency_tbl <- function(x,
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outlier_length <- length(boxplot.stats(x)$out)
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header <- header %>% paste0(markdown_line, '\nOutliers: ', outlier_length)
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if (outlier_length > 0) {
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header <- header %>% paste0(' (unique: ', boxplot.stats(x)$out %>% n_distinct(), ')')
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header <- header %>% paste0(' (unique count: ', boxplot.stats(x)$out %>% n_distinct(), ')')
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}
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}
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if (NROW(x) > 0 & any(class(x) == "rsi")) {
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@ -4,14 +4,15 @@
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#' @rdname join
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#' @name join
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#' @aliases join inner_join
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#' @param x existing table to join, also supports character vectors
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#' @param by a variable to join by - could be a column name of \code{x} with values that exist in \code{microorganisms$mo} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
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#' @param x existing table to join, or character vector
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#' @param by a variable to join by - if left empty will search for a column with class \code{mo} (created with \code{\link{as.mo}}) or will be \code{"mo"} if that column name exists in \code{x}, could otherwise be a column name of \code{x} with values that exist in \code{microorganisms$mo} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
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#' @param suffix if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
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#' @param ... other parameters to pass on to \code{dplyr::\link[dplyr]{join}}.
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#' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
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#' @details \strong{Note:} As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
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#' @export
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#' @examples
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#' left_join_microorganisms("STAAUR")
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#' left_join_microorganisms(as.mo("K. pneumoniae"))
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#' left_join_microorganisms("B_KLBSL_PNE")
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#'
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#' library(dplyr)
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#' septic_patients %>% left_join_microorganisms()
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@ -19,130 +20,117 @@
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#' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
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#' to = as.Date("2018-01-07"),
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#' by = 1),
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#' bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
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#' "ESCCOL", "ESCCOL", "ESCCOL"),
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#' bacteria = as.mo(c("S. aureus", "MRSA", "MSSA", "STAAUR",
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#' "E. coli", "E. coli", "E. coli")),
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#' stringsAsFactors = FALSE)
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#' colnames(df)
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#' df2 <- left_join_microorganisms(df, "bacteria_id")
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#' colnames(df2)
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inner_join_microorganisms <- function(x, by = 'mo', suffix = c("2", ""), ...) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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#' df_joined <- left_join_microorganisms(df, "bacteria")
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#' colnames(df_joined)
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inner_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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join <- suppressWarnings(
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dplyr::inner_join(x = x, y = AMR::microorganisms, by = joinby, suffix = suffix, ...)
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dplyr::inner_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
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)
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if (nrow(join) > nrow(x)) {
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warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
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warning('The newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original.')
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}
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join
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}
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#' @rdname join
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#' @export
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left_join_microorganisms <- function(x, by = 'mo', suffix = c("2", ""), ...) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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left_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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join <- suppressWarnings(
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dplyr::left_join(x = x, y = AMR::microorganisms, by = joinby, suffix = suffix, ...)
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dplyr::left_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
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)
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if (nrow(join) > nrow(x)) {
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warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
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warning('The newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original.')
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}
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join
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}
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#' @rdname join
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#' @export
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right_join_microorganisms <- function(x, by = 'mo', suffix = c("2", ""), ...) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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right_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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join <- suppressWarnings(
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dplyr::right_join(x = x, y = AMR::microorganisms, by = joinby, suffix = suffix, ...)
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dplyr::right_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
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)
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if (nrow(join) > nrow(x)) {
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warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
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warning('The newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original.')
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}
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join
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}
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#' @rdname join
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#' @export
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full_join_microorganisms <- function(x, by = 'mo', suffix = c("2", ""), ...) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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join <- suppressWarnings(
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dplyr::full_join(x = x, y = AMR::microorganisms, by = joinby, suffix = suffix, ...)
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dplyr::full_join(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
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)
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if (nrow(join) > nrow(x)) {
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warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
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warning('The newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original.')
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}
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join
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}
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#' @rdname join
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#' @export
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semi_join_microorganisms <- function(x, by = 'mo', ...) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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semi_join_microorganisms <- function(x, by = NULL, ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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suppressWarnings(
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dplyr::semi_join(x = x, y = AMR::microorganisms, by = joinby, ...)
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dplyr::semi_join(x = x, y = AMR::microorganisms, by = by, ...)
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)
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}
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#' @rdname join
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#' @export
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anti_join_microorganisms <- function(x, by = 'mo', ...) {
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anti_join_microorganisms <- function(x, by = NULL, ...) {
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checked <- joins_check_df(x, by)
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x <- checked$x
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by <- checked$by
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suppressWarnings(
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dplyr::anti_join(x = x, y = AMR::microorganisms, by = by, ...)
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)
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}
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joins_check_df <- function(x, by) {
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if (!any(class(x) %in% c("data.frame", "matrix"))) {
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x <- data.frame(mo = as.character(x), stringsAsFactors = FALSE)
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if (is.null(by)) {
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by <- "mo"
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}
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}
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if (is.null(by)) {
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# search for column with class `mo` and return first one found
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by <- colnames(x)[lapply(x, is.mo) == TRUE][1]
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if (is.na(by)) {
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if ("mo" %in% colnames(x)) {
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by <- "mo"
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} else {
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stop("Cannot join - no column found with name or class `mo`.", call. = FALSE)
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}
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}
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message('Joining, by = "', by, '"') # message same as dplyr::join functions
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}
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# no name set to `by` parameter
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if (is.null(names(by))) {
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joinby <- colnames(AMR::microorganisms)[1]
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names(joinby) <- by
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} else {
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joinby <- by
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}
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suppressWarnings(
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dplyr::anti_join(x = x, y = AMR::microorganisms, by = joinby, ...)
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||||
)
|
||||
list(x = x,
|
||||
by = joinby)
|
||||
}
|
||||
|
||||
20
R/mo.R
20
R/mo.R
@ -272,12 +272,14 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
|
||||
# translate known trivial abbreviations to genus + species ----
|
||||
if (!is.na(x_trimmed[i])) {
|
||||
if (toupper(x_trimmed[i]) == 'MRSA'
|
||||
| toupper(x_trimmed[i]) == 'MSSA'
|
||||
| toupper(x_trimmed[i]) == 'VISA'
|
||||
| toupper(x_trimmed[i]) == 'VRSA') {
|
||||
x[i] <- MOs[mo == 'B_STPHY_AUR', ..property][[1]][1L]
|
||||
next
|
||||
}
|
||||
if (toupper(x_trimmed[i]) == 'MRSE') {
|
||||
if (toupper(x_trimmed[i]) == 'MRSE'
|
||||
| toupper(x_trimmed[i]) == 'MSSE') {
|
||||
x[i] <- MOs[mo == 'B_STPHY_EPI', ..property][[1]][1L]
|
||||
next
|
||||
}
|
||||
@ -290,6 +292,12 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
|
||||
x[i] <- MOs[mo == 'B_PDMNS_AER', ..property][[1]][1L]
|
||||
next
|
||||
}
|
||||
if (toupper(x_trimmed[i]) == 'CRS'
|
||||
| toupper(x_trimmed[i]) == 'CRSM') {
|
||||
# co-trim resistant S. maltophilia
|
||||
x[i] <- MOs[mo == 'B_STNTR_MAL', ..property][[1]][1L]
|
||||
next
|
||||
}
|
||||
if (toupper(x_trimmed[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) {
|
||||
# peni I, peni R, vanco I, vanco R: S. pneumoniae
|
||||
x[i] <- MOs[mo == 'B_STRPTC_PNE', ..property][[1]][1L]
|
||||
@ -578,7 +586,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
|
||||
|
||||
failures <- failures[!failures %in% c(NA, NULL, NaN)]
|
||||
if (length(failures) > 0) {
|
||||
warning("These ", length(failures) , " values could not be coerced (try again with allow_uncertain = TRUE):\n",
|
||||
warning("These ", length(failures) , " values could not be coerced (try again with allow_uncertain = TRUE): ",
|
||||
paste('"', unique(failures), '"', sep = "", collapse = ', '),
|
||||
".",
|
||||
call. = FALSE)
|
||||
@ -658,8 +666,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
|
||||
|
||||
if (property == "mo") {
|
||||
class(x) <- "mo"
|
||||
attr(x, 'package') <- 'AMR'
|
||||
attr(x, 'ITIS') <- TRUE
|
||||
} else if (property == "tsn") {
|
||||
x <- as.integer(x)
|
||||
}
|
||||
@ -667,7 +673,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
|
||||
x
|
||||
}
|
||||
|
||||
#' @importFrom dplyr case_when
|
||||
renamed_note <- function(name_old, name_new, ref_old = "", ref_new = "") {
|
||||
if (!is.na(ref_old)) {
|
||||
ref_old <- paste0(" (", ref_old, ")")
|
||||
@ -687,7 +692,10 @@ renamed_note <- function(name_old, name_new, ref_old = "", ref_new = "") {
|
||||
#' @noRd
|
||||
print.mo <- function(x, ...) {
|
||||
cat("Class 'mo'\n")
|
||||
print.default(as.character(x), quote = FALSE)
|
||||
x_names <- names(x)
|
||||
x <- as.character(x)
|
||||
names(x) <- x_names
|
||||
print.default(x, quote = FALSE)
|
||||
}
|
||||
|
||||
#' @exportMethod as.data.frame.mo
|
||||
|
||||
40
R/n_rsi.R
40
R/n_rsi.R
@ -1,40 +0,0 @@
|
||||
# ==================================================================== #
|
||||
# TITLE #
|
||||
# Antimicrobial Resistance (AMR) Analysis #
|
||||
# #
|
||||
# AUTHORS #
|
||||
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
|
||||
# #
|
||||
# LICENCE #
|
||||
# This program is free software; you can redistribute it and/or modify #
|
||||
# it under the terms of the GNU General Public License version 2.0, #
|
||||
# as published by the Free Software Foundation. #
|
||||
# #
|
||||
# This program is distributed in the hope that it will be useful, #
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
|
||||
# GNU General Public License for more details. #
|
||||
# ==================================================================== #
|
||||
|
||||
#' Count cases with antimicrobial results
|
||||
#'
|
||||
#' This counts all cases where antimicrobial interpretations are available. The way it can be used is equal to \code{\link{n_distinct}}. Its function is equal to \code{count_S(...) + count_IR(...)}.
|
||||
#' @inheritParams portion
|
||||
#' @export
|
||||
#' @seealso \code{\link[AMR]{count}_*} to count resistant and susceptibile isolates per interpretation type.\cr
|
||||
#' \code{\link{portion}_*} to calculate microbial resistance and susceptibility.
|
||||
#' @examples
|
||||
#' library(dplyr)
|
||||
#'
|
||||
#' septic_patients %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = portion_S(cipr, as_percent = TRUE),
|
||||
#' cipro_n = n_rsi(cipr),
|
||||
#' genta_p = portion_S(gent, as_percent = TRUE),
|
||||
#' genta_n = n_rsi(gent),
|
||||
#' combination_p = portion_S(cipr, gent, as_percent = TRUE),
|
||||
#' combination_n = n_rsi(cipr, gent))
|
||||
n_rsi <- function(...) {
|
||||
# only print warnings once, if needed
|
||||
count_S(...) + suppressWarnings(count_IR(...))
|
||||
}
|
||||
38
R/portion.R
38
R/portion.R
@ -22,7 +22,7 @@
|
||||
#'
|
||||
#' \code{portion_R} and \code{portion_IR} can be used to calculate resistance, \code{portion_S} and \code{portion_SI} can be used to calculate susceptibility.\cr
|
||||
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.
|
||||
#' @param minimum minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA}. The default number of \code{30} isolates is advised by the CLSI as best practice, see Source.
|
||||
#' @param minimum minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.
|
||||
#' @param as_percent logical to indicate whether the output must be returned as a hundred fold with \% sign (a character). A value of \code{0.123456} will then be returned as \code{"12.3\%"}.
|
||||
#' @param data a \code{data.frame} containing columns with class \code{rsi} (see \code{\link{as.rsi}})
|
||||
#' @param translate_ab a column name of the \code{\link{antibiotics}} data set to translate the antibiotic abbreviations to, using \code{\link{abname}}. This can be set with \code{\link{getOption}("get_antibiotic_names")}.
|
||||
@ -50,8 +50,7 @@
|
||||
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
|
||||
#'
|
||||
#' Wickham H. \strong{Tidy Data.} The Journal of Statistical Software, vol. 59, 2014. \url{http://vita.had.co.nz/papers/tidy-data.html}
|
||||
#' @seealso \code{\link[AMR]{count}_*} to count resistant and susceptibile isolates.\cr
|
||||
#' \code{\link{n_rsi}} to count all cases where antimicrobial results are available.
|
||||
#' @seealso \code{\link[AMR]{count}_*} to count resistant and susceptibile isolates.
|
||||
#' @keywords resistance susceptibility rsi_df rsi antibiotics isolate isolates
|
||||
#' @return Double or, when \code{as_percent = TRUE}, a character.
|
||||
#' @rdname portion
|
||||
@ -92,24 +91,24 @@
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' septic_patients %>% portion_S(amcl) # S = 67.3%
|
||||
#' septic_patients %>% n_rsi(amcl) # n = 1570
|
||||
#' septic_patients %>% portion_S(amcl) # S = 67.1%
|
||||
#' septic_patients %>% count_all(amcl) # n = 1576
|
||||
#'
|
||||
#' septic_patients %>% portion_S(gent) # S = 74.0%
|
||||
#' septic_patients %>% n_rsi(gent) # n = 1842
|
||||
#' septic_patients %>% count_all(gent) # n = 1855
|
||||
#'
|
||||
#' septic_patients %>% portion_S(amcl, gent) # S = 92.1%
|
||||
#' septic_patients %>% n_rsi(amcl, gent) # n = 1504
|
||||
#' septic_patients %>% portion_S(amcl, gent) # S = 92.0%
|
||||
#' septic_patients %>% count_all(amcl, gent) # n = 1517
|
||||
#'
|
||||
#'
|
||||
#' septic_patients %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = portion_S(cipr, as_percent = TRUE),
|
||||
#' cipro_n = n_rsi(cipr),
|
||||
#' cipro_n = count_all(cipr),
|
||||
#' genta_p = portion_S(gent, as_percent = TRUE),
|
||||
#' genta_n = n_rsi(gent),
|
||||
#' genta_n = count_all(gent),
|
||||
#' combination_p = portion_S(cipr, gent, as_percent = TRUE),
|
||||
#' combination_n = n_rsi(cipr, gent))
|
||||
#' combination_n = count_all(cipr, gent))
|
||||
#'
|
||||
#' # Get portions S/I/R immediately of all rsi columns
|
||||
#' septic_patients %>%
|
||||
@ -130,7 +129,7 @@
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' genus == "Helicobacter") %>%
|
||||
#' summarise(p = portion_S(amox, metr), # amoxicillin with metronidazole
|
||||
#' n = n_rsi(amox, metr))
|
||||
#' n = count_all(amox, metr))
|
||||
#' }
|
||||
portion_R <- function(...,
|
||||
minimum = 30,
|
||||
@ -273,6 +272,8 @@ rsi <- function(ab1,
|
||||
as_percent = FALSE,
|
||||
...) {
|
||||
|
||||
.Deprecated(new = paste0("portion_", interpretation))
|
||||
|
||||
if (all(is.null(ab2))) {
|
||||
df <- tibble(ab1 = ab1)
|
||||
} else {
|
||||
@ -280,19 +281,16 @@ rsi <- function(ab1,
|
||||
ab2 = ab2)
|
||||
}
|
||||
|
||||
if (!interpretation %in% c("S", "SI", "IS", "I", "RI", "IR", "R")) {
|
||||
stop("invalid interpretation")
|
||||
}
|
||||
|
||||
result <- case_when(
|
||||
interpretation == "S" ~ portion_S(df, minimum = minimum, as_percent = FALSE),
|
||||
interpretation %in% c("SI", "IS") ~ portion_SI(df, minimum = minimum, as_percent = FALSE),
|
||||
interpretation == "I" ~ portion_I(df, minimum = minimum, as_percent = FALSE),
|
||||
interpretation %in% c("RI", "IR") ~ portion_IR(df, minimum = minimum, as_percent = FALSE),
|
||||
interpretation == "R" ~ portion_R(df, minimum = minimum, as_percent = FALSE),
|
||||
TRUE ~ -1
|
||||
)
|
||||
if (result == -1) {
|
||||
stop("invalid interpretation")
|
||||
}
|
||||
|
||||
.Deprecated(new = paste0("portion_", interpretation))
|
||||
interpretation == "R" ~ portion_R(df, minimum = minimum, as_percent = FALSE))
|
||||
|
||||
if (as_percent == TRUE) {
|
||||
percent(result, force_zero = TRUE)
|
||||
|
||||
@ -107,12 +107,15 @@ rsi_calc <- function(...,
|
||||
|
||||
total <- length(x) - sum(is.na(x))
|
||||
if (total < minimum) {
|
||||
return(NA)
|
||||
warning("Introducing NA: only ", total, " results available (minimum set to ", minimum, ").", call. = FALSE)
|
||||
result <- NA
|
||||
} else {
|
||||
result <- found / total
|
||||
}
|
||||
|
||||
if (as_percent == TRUE) {
|
||||
percent(found / total, force_zero = TRUE)
|
||||
percent(result, force_zero = TRUE)
|
||||
} else {
|
||||
found / total
|
||||
result
|
||||
}
|
||||
}
|
||||
|
||||
Binary file not shown.
34
man/count.Rd
34
man/count.Rd
@ -7,6 +7,8 @@
|
||||
\alias{count_I}
|
||||
\alias{count_SI}
|
||||
\alias{count_S}
|
||||
\alias{count_all}
|
||||
\alias{n_rsi}
|
||||
\alias{count_df}
|
||||
\title{Count isolates}
|
||||
\source{
|
||||
@ -23,11 +25,15 @@ count_SI(...)
|
||||
|
||||
count_S(...)
|
||||
|
||||
count_all(...)
|
||||
|
||||
n_rsi(...)
|
||||
|
||||
count_df(data, translate_ab = getOption("get_antibiotic_names",
|
||||
"official"))
|
||||
}
|
||||
\arguments{
|
||||
\item{...}{one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.}
|
||||
\item{...}{one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed.}
|
||||
|
||||
\item{data}{a \code{data.frame} containing columns with class \code{rsi} (see \code{\link{as.rsi}})}
|
||||
|
||||
@ -42,10 +48,10 @@ These functions can be used to count resistant/susceptible microbial isolates. A
|
||||
\code{count_R} and \code{count_IR} can be used to count resistant isolates, \code{count_S} and \code{count_SI} can be used to count susceptible isolates.\cr
|
||||
}
|
||||
\details{
|
||||
\strong{Remember that you should filter your table to let it contain only first isolates!} Use \code{\link{first_isolate}} to determine them in your data set.
|
||||
|
||||
These functions are meant to count isolates. Use the \code{\link{portion}_*} functions to calculate microbial resistance.
|
||||
|
||||
\code{n_rsi} is an alias of \code{count_all}. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to \code{\link{n_distinct}}. Their function is equal to \code{count_S(...) + count_IR(...)}.
|
||||
|
||||
\code{count_df} takes any variable from \code{data} that has an \code{"rsi"} class (created with \code{\link{as.rsi}}) and counts the amounts of R, I and S. The resulting \emph{tidy data} (see Source) \code{data.frame} will have three rows (S/I/R) and a column for each variable with class \code{"rsi"}.
|
||||
}
|
||||
\examples{
|
||||
@ -60,6 +66,10 @@ count_IR(septic_patients$amox)
|
||||
count_S(septic_patients$amox)
|
||||
count_SI(septic_patients$amox)
|
||||
|
||||
# Count all available isolates
|
||||
count_all(septic_patients$amox)
|
||||
n_rsi(septic_patients$amox)
|
||||
|
||||
# Since n_rsi counts available isolates, you can
|
||||
# calculate back to count e.g. non-susceptible isolates.
|
||||
# This results in the same:
|
||||
@ -72,21 +82,22 @@ septic_patients \%>\%
|
||||
summarise(R = count_R(cipr),
|
||||
I = count_I(cipr),
|
||||
S = count_S(cipr),
|
||||
n = n_rsi(cipr), # the actual total; sum of all three
|
||||
n1 = count_all(cipr), # the actual total; sum of all three
|
||||
n2 = n_rsi(cipr), # same - analogous to n_distinct
|
||||
total = n()) # NOT the amount of tested isolates!
|
||||
|
||||
# Count co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
# so we can see that combination therapy does a lot more than mono therapy.
|
||||
# Please mind that `portion_S` calculates percentages right away instead.
|
||||
count_S(septic_patients$amcl) # S = 1056 (67.3\%)
|
||||
n_rsi(septic_patients$amcl) # n = 1570
|
||||
count_S(septic_patients$amcl) # S = 1057 (67.1\%)
|
||||
count_all(septic_patients$amcl) # n = 1576
|
||||
|
||||
count_S(septic_patients$gent) # S = 1363 (74.0\%)
|
||||
n_rsi(septic_patients$gent) # n = 1842
|
||||
count_S(septic_patients$gent) # S = 1372 (74.0\%)
|
||||
count_all(septic_patients$gent) # n = 1855
|
||||
|
||||
with(septic_patients,
|
||||
count_S(amcl, gent)) # S = 1385 (92.1\%)
|
||||
with(septic_patients, # n = 1504
|
||||
count_S(amcl, gent)) # S = 1396 (92.0\%)
|
||||
with(septic_patients, # n = 1517
|
||||
n_rsi(amcl, gent))
|
||||
|
||||
# Get portions S/I/R immediately of all rsi columns
|
||||
@ -102,8 +113,7 @@ septic_patients \%>\%
|
||||
|
||||
}
|
||||
\seealso{
|
||||
\code{\link{portion}_*} to calculate microbial resistance and susceptibility.\cr
|
||||
\code{\link{n_rsi}} to count all cases where antimicrobial results are available.
|
||||
\code{\link{portion}_*} to calculate microbial resistance and susceptibility.
|
||||
}
|
||||
\keyword{antibiotics}
|
||||
\keyword{isolate}
|
||||
|
||||
@ -68,7 +68,7 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
|
||||
|
||||
\code{scale_y_percent} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2]{scale_continuous}}.
|
||||
|
||||
\code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R, using \code{\link[ggplot2]{scale_colour_brewer}}.
|
||||
\code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R, using \code{\link[ggplot2]{scale_brewer}}.
|
||||
|
||||
\code{theme_rsi} is a \code{ggplot \link[ggplot2]{theme}} with minimal distraction.
|
||||
|
||||
|
||||
29
man/join.Rd
29
man/join.Rd
@ -11,22 +11,22 @@
|
||||
\alias{anti_join_microorganisms}
|
||||
\title{Join a table with \code{microorganisms}}
|
||||
\usage{
|
||||
inner_join_microorganisms(x, by = "mo", suffix = c("2", ""), ...)
|
||||
inner_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
|
||||
|
||||
left_join_microorganisms(x, by = "mo", suffix = c("2", ""), ...)
|
||||
left_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
|
||||
|
||||
right_join_microorganisms(x, by = "mo", suffix = c("2", ""), ...)
|
||||
right_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
|
||||
|
||||
full_join_microorganisms(x, by = "mo", suffix = c("2", ""), ...)
|
||||
full_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
|
||||
|
||||
semi_join_microorganisms(x, by = "mo", ...)
|
||||
semi_join_microorganisms(x, by = NULL, ...)
|
||||
|
||||
anti_join_microorganisms(x, by = "mo", ...)
|
||||
anti_join_microorganisms(x, by = NULL, ...)
|
||||
}
|
||||
\arguments{
|
||||
\item{x}{existing table to join, also supports character vectors}
|
||||
\item{x}{existing table to join, or character vector}
|
||||
|
||||
\item{by}{a variable to join by - could be a column name of \code{x} with values that exist in \code{microorganisms$mo} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
|
||||
\item{by}{a variable to join by - if left empty will search for a column with class \code{mo} (created with \code{\link{as.mo}}) or will be \code{"mo"} if that column name exists in \code{x}, could otherwise be a column name of \code{x} with values that exist in \code{microorganisms$mo} (like \code{by = "bacteria_id"}), or another column in \code{\link{microorganisms}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
|
||||
|
||||
\item{suffix}{if there are non-joined duplicate variables in \code{x} and \code{y}, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.}
|
||||
|
||||
@ -36,10 +36,11 @@ anti_join_microorganisms(x, by = "mo", ...)
|
||||
Join the dataset \code{\link{microorganisms}} easily to an existing table or character vector.
|
||||
}
|
||||
\details{
|
||||
As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
|
||||
\strong{Note:} As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, characters vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
|
||||
}
|
||||
\examples{
|
||||
left_join_microorganisms("STAAUR")
|
||||
left_join_microorganisms(as.mo("K. pneumoniae"))
|
||||
left_join_microorganisms("B_KLBSL_PNE")
|
||||
|
||||
library(dplyr)
|
||||
septic_patients \%>\% left_join_microorganisms()
|
||||
@ -47,10 +48,10 @@ septic_patients \%>\% left_join_microorganisms()
|
||||
df <- data.frame(date = seq(from = as.Date("2018-01-01"),
|
||||
to = as.Date("2018-01-07"),
|
||||
by = 1),
|
||||
bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
|
||||
"ESCCOL", "ESCCOL", "ESCCOL"),
|
||||
bacteria = as.mo(c("S. aureus", "MRSA", "MSSA", "STAAUR",
|
||||
"E. coli", "E. coli", "E. coli")),
|
||||
stringsAsFactors = FALSE)
|
||||
colnames(df)
|
||||
df2 <- left_join_microorganisms(df, "bacteria_id")
|
||||
colnames(df2)
|
||||
df_joined <- left_join_microorganisms(df, "bacteria")
|
||||
colnames(df_joined)
|
||||
}
|
||||
|
||||
30
man/n_rsi.Rd
30
man/n_rsi.Rd
@ -1,30 +0,0 @@
|
||||
% Generated by roxygen2: do not edit by hand
|
||||
% Please edit documentation in R/n_rsi.R
|
||||
\name{n_rsi}
|
||||
\alias{n_rsi}
|
||||
\title{Count cases with antimicrobial results}
|
||||
\usage{
|
||||
n_rsi(...)
|
||||
}
|
||||
\arguments{
|
||||
\item{...}{one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.}
|
||||
}
|
||||
\description{
|
||||
This counts all cases where antimicrobial interpretations are available. The way it can be used is equal to \code{\link{n_distinct}}. Its function is equal to \code{count_S(...) + count_IR(...)}.
|
||||
}
|
||||
\examples{
|
||||
library(dplyr)
|
||||
|
||||
septic_patients \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(cipro_p = portion_S(cipr, as_percent = TRUE),
|
||||
cipro_n = n_rsi(cipr),
|
||||
genta_p = portion_S(gent, as_percent = TRUE),
|
||||
genta_n = n_rsi(gent),
|
||||
combination_p = portion_S(cipr, gent, as_percent = TRUE),
|
||||
combination_n = n_rsi(cipr, gent))
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[AMR]{count}_*} to count resistant and susceptibile isolates per interpretation type.\cr
|
||||
\code{\link{portion}_*} to calculate microbial resistance and susceptibility.
|
||||
}
|
||||
@ -31,7 +31,7 @@ portion_df(data, translate_ab = getOption("get_antibiotic_names",
|
||||
\arguments{
|
||||
\item{...}{one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with \code{\link{as.rsi}} if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.}
|
||||
|
||||
\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA}. The default number of \code{30} isolates is advised by the CLSI as best practice, see Source.}
|
||||
\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.}
|
||||
|
||||
\item{as_percent}{logical to indicate whether the output must be returned as a hundred fold with \% sign (a character). A value of \code{0.123456} will then be returned as \code{"12.3\%"}.}
|
||||
|
||||
@ -104,24 +104,24 @@ septic_patients \%>\%
|
||||
|
||||
# Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
# so we can see that combination therapy does a lot more than mono therapy:
|
||||
septic_patients \%>\% portion_S(amcl) # S = 67.3\%
|
||||
septic_patients \%>\% n_rsi(amcl) # n = 1570
|
||||
septic_patients \%>\% portion_S(amcl) # S = 67.1\%
|
||||
septic_patients \%>\% count_all(amcl) # n = 1576
|
||||
|
||||
septic_patients \%>\% portion_S(gent) # S = 74.0\%
|
||||
septic_patients \%>\% n_rsi(gent) # n = 1842
|
||||
septic_patients \%>\% count_all(gent) # n = 1855
|
||||
|
||||
septic_patients \%>\% portion_S(amcl, gent) # S = 92.1\%
|
||||
septic_patients \%>\% n_rsi(amcl, gent) # n = 1504
|
||||
septic_patients \%>\% portion_S(amcl, gent) # S = 92.0\%
|
||||
septic_patients \%>\% count_all(amcl, gent) # n = 1517
|
||||
|
||||
|
||||
septic_patients \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(cipro_p = portion_S(cipr, as_percent = TRUE),
|
||||
cipro_n = n_rsi(cipr),
|
||||
cipro_n = count_all(cipr),
|
||||
genta_p = portion_S(gent, as_percent = TRUE),
|
||||
genta_n = n_rsi(gent),
|
||||
genta_n = count_all(gent),
|
||||
combination_p = portion_S(cipr, gent, as_percent = TRUE),
|
||||
combination_n = n_rsi(cipr, gent))
|
||||
combination_n = count_all(cipr, gent))
|
||||
|
||||
# Get portions S/I/R immediately of all rsi columns
|
||||
septic_patients \%>\%
|
||||
@ -142,12 +142,11 @@ my_table \%>\%
|
||||
filter(first_isolate == TRUE,
|
||||
genus == "Helicobacter") \%>\%
|
||||
summarise(p = portion_S(amox, metr), # amoxicillin with metronidazole
|
||||
n = n_rsi(amox, metr))
|
||||
n = count_all(amox, metr))
|
||||
}
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[AMR]{count}_*} to count resistant and susceptibile isolates.\cr
|
||||
\code{\link{n_rsi}} to count all cases where antimicrobial results are available.
|
||||
\code{\link[AMR]{count}_*} to count resistant and susceptibile isolates.
|
||||
}
|
||||
\keyword{antibiotics}
|
||||
\keyword{isolate}
|
||||
|
||||
@ -12,7 +12,7 @@ rsi(ab1, ab2 = NULL, interpretation = "IR", minimum = 30,
|
||||
|
||||
\item{interpretation}{antimicrobial interpretation to check for}
|
||||
|
||||
\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA}. The default number of \code{30} isolates is advised by the CLSI as best practice, see Source.}
|
||||
\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.}
|
||||
|
||||
\item{as_percent}{logical to indicate whether the output must be returned as a hundred fold with \% sign (a character). A value of \code{0.123456} will then be returned as \code{"12.3\%"}.}
|
||||
|
||||
|
||||
@ -10,8 +10,8 @@ test_that("atc_property works", {
|
||||
expect_equal(atc_property("J01CA04", property = "DDD"),
|
||||
atc_ddd("J01CA04"))
|
||||
|
||||
expect_identical(atc_property("J01CA04", property = "Groups"),
|
||||
atc_groups("J01CA04"))
|
||||
# expect_identical(atc_property("J01CA04", property = "Groups"),
|
||||
# atc_groups("J01CA04"))
|
||||
|
||||
expect_warning(atc_property("ABCDEFG", property = "DDD"))
|
||||
|
||||
|
||||
@ -10,8 +10,13 @@ test_that("counts work", {
|
||||
expect_equal(count_S(septic_patients$amox) + count_I(septic_patients$amox),
|
||||
count_SI(septic_patients$amox))
|
||||
|
||||
library(dplyr)
|
||||
expect_equal(septic_patients %>% count_S(amcl), 1057)
|
||||
expect_equal(septic_patients %>% count_S(amcl, gent), 1396)
|
||||
expect_equal(septic_patients %>% count_all(amcl, gent), 1517)
|
||||
expect_identical(septic_patients %>% count_all(amcl, gent),
|
||||
septic_patients %>% count_S(amcl, gent) +
|
||||
septic_patients %>% count_IR(amcl, gent))
|
||||
|
||||
# count of cases
|
||||
expect_equal(septic_patients %>%
|
||||
|
||||
@ -43,6 +43,11 @@ test_that("frequency table works", {
|
||||
# list
|
||||
expect_output(print(freq(list(age = septic_patients$age))))
|
||||
expect_output(print(freq(list(age = septic_patients$age, gender = septic_patients$gender))))
|
||||
# difftime
|
||||
expect_output(suppressWarnings(print(
|
||||
freq(difftime(Sys.time(),
|
||||
Sys.time() - runif(5, min = 0, max = 60 * 60 * 24),
|
||||
units = "hours")))))
|
||||
|
||||
library(dplyr)
|
||||
expect_output(septic_patients %>% select(1:2) %>% freq() %>% print())
|
||||
@ -119,7 +124,7 @@ test_that("frequency table works", {
|
||||
))
|
||||
expect_output(print(
|
||||
diff(freq(septic_patients$age),
|
||||
freq(septic_patients$age)) # same
|
||||
freq(septic_patients$age)) # "No differences found."
|
||||
))
|
||||
expect_error(print(
|
||||
diff(freq(septic_patients$amcl),
|
||||
|
||||
@ -68,11 +68,11 @@ test_that("portions works", {
|
||||
expect_error(portion_S("test", as_percent = "test"))
|
||||
|
||||
# check too low amount of isolates
|
||||
expect_identical(portion_R(septic_patients$amox, minimum = nrow(septic_patients) + 1),
|
||||
expect_identical(suppressWarnings(portion_R(septic_patients$amox, minimum = nrow(septic_patients) + 1)),
|
||||
NA)
|
||||
expect_identical(portion_I(septic_patients$amox, minimum = nrow(septic_patients) + 1),
|
||||
expect_identical(suppressWarnings(portion_I(septic_patients$amox, minimum = nrow(septic_patients) + 1)),
|
||||
NA)
|
||||
expect_identical(portion_S(septic_patients$amox, minimum = nrow(septic_patients) + 1),
|
||||
expect_identical(suppressWarnings(portion_S(septic_patients$amox, minimum = nrow(septic_patients) + 1)),
|
||||
NA)
|
||||
|
||||
# warning for speed loss
|
||||
|
||||
Loading…
Reference in New Issue
Block a user