sort sir history

man/add_custom_microorganisms.Rd

@@ -58,8 +58,9 @@ mo_name("Enterobacter asburiae/cloacae")
 # now add a custom entry - it will be considered by as.mo() and
 # all mo_*() functions
 add_custom_microorganisms(
-  data.frame(genus = "Enterobacter",
-             species = "asburiae/cloacae"
+  data.frame(
+    genus = "Enterobacter",
+    species = "asburiae/cloacae"
   )
 )
 
@@ -81,8 +82,10 @@ mo_info("Enterobacter asburiae/cloacae")
 
 # the function tries to be forgiving:
 add_custom_microorganisms(
-  data.frame(GENUS = "BACTEROIDES / PARABACTEROIDES SLASHLINE",
-             SPECIES = "SPECIES")
+  data.frame(
+    GENUS = "BACTEROIDES / PARABACTEROIDES SLASHLINE",
+    SPECIES = "SPECIES"
+  )
 )
 mo_name("BACTEROIDES / PARABACTEROIDES")
 mo_rank("BACTEROIDES / PARABACTEROIDES")
@@ -93,9 +96,11 @@ mo_family("Bacteroides/Parabacteroides")
 
 # for groups and complexes, set them as species or subspecies:
 add_custom_microorganisms(
-  data.frame(genus = "Citrobacter", 
-             species = c("freundii", "braakii complex"),
-             subspecies = c("complex", ""))
+  data.frame(
+    genus = "Citrobacter",
+    species = c("freundii", "braakii complex"),
+    subspecies = c("complex", "")
+  )
 )
 mo_name(c("C. freundii complex", "C. braakii complex"))
 mo_species(c("C. freundii complex", "C. braakii complex"))

man/antibiotic_class_selectors.Rd

@@ -214,20 +214,17 @@ example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
 # dplyr -------------------------------------------------------------------
 \donttest{
 if (require("dplyr")) {
-
   # get AMR for all aminoglycosides e.g., per ward:
   example_isolates \%>\%
     group_by(ward) \%>\%
     summarise(across(aminoglycosides(), resistance))
 }
 if (require("dplyr")) {
-
   # You can combine selectors with '&' to be more specific:
   example_isolates \%>\%
     select(penicillins() & administrable_per_os())
 }
 if (require("dplyr")) {
-
   # get AMR for only drugs that matter - no intrinsic resistance:
   example_isolates \%>\%
     filter(mo_genus() \%in\% c("Escherichia", "Klebsiella")) \%>\%
@@ -235,7 +232,6 @@ if (require("dplyr")) {
     summarise(across(not_intrinsic_resistant(), resistance))
 }
 if (require("dplyr")) {
-
   # get susceptibility for antibiotics whose name contains "trim":
   example_isolates \%>\%
     filter(first_isolate()) \%>\%
@@ -243,19 +239,16 @@ if (require("dplyr")) {
     summarise(across(ab_selector(name \%like\% "trim"), susceptibility))
 }
 if (require("dplyr")) {
-
   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
   example_isolates \%>\%
     select(carbapenems())
 }
 if (require("dplyr")) {
-
   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
   example_isolates \%>\%
     select(mo, aminoglycosides())
 }
 if (require("dplyr")) {
-
   # any() and all() work in dplyr's filter() too:
   example_isolates \%>\%
     filter(
@@ -264,25 +257,21 @@ if (require("dplyr")) {
     )
 }
 if (require("dplyr")) {
-
   # also works with c():
   example_isolates \%>\%
     filter(any(c(carbapenems(), aminoglycosides()) == "R"))
 }
 if (require("dplyr")) {
-
   # not setting any/all will automatically apply all():
   example_isolates \%>\%
     filter(aminoglycosides() == "R")
 }
 if (require("dplyr")) {
-
   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
   example_isolates \%>\%
     select(mo, ab_class("mycobact"))
 }
 if (require("dplyr")) {
-
   # get bug/drug combinations for only glycopeptides in Gram-positives:
   example_isolates \%>\%
     filter(mo_is_gram_positive()) \%>\%
@@ -298,7 +287,6 @@ if (require("dplyr")) {
     select(penicillins()) # only the 'J01CA01' column will be selected
 }
 if (require("dplyr")) {
-
   # with recent versions of dplyr this is all equal:
   x <- example_isolates[carbapenems() == "R", ]
   y <- example_isolates \%>\% filter(carbapenems() == "R")

man/as.ab.Rd

@@ -91,7 +91,6 @@ ab_name("eryt")
 
 \donttest{
 if (require("dplyr")) {
-
   # you can quickly rename 'sir' columns using set_ab_names() with dplyr:
   example_isolates \%>\%
     set_ab_names(where(is.sir), property = "atc")

man/as.sir.Rd

@@ -125,7 +125,7 @@ your_data \%>\% mutate(across(where(is.disk), as.sir))
 \item For \strong{interpreting a complete data set}, with automatic determination of MIC values, disk diffusion diameters, microorganism names or codes, and antimicrobial test results. This is done very simply by running \code{as.sir(your_data)}.
 }
 
-For points 2, 3 and 4: Use \code{\link[=sir_interpretation_history]{sir_interpretation_history()}} to retrieve a \link{data.frame} (or \link[tibble:tibble]{tibble} if the \code{tibble} package is installed) with all results of the last \code{\link[=as.sir]{as.sir()}} call.
+\strong{For points 2, 3 and 4: Use \code{\link[=sir_interpretation_history]{sir_interpretation_history()}}} to retrieve a \link{data.frame} (or \link[tibble:tibble]{tibble} if the \code{tibble} package is installed) with all results of the last \code{\link[=as.sir]{as.sir()}} call.
 }
 
 \subsection{Supported Guidelines}{

man/first_isolate.Rd

@@ -179,13 +179,11 @@ if (require("dplyr")) {
     filter(first_isolate())
 }
 if (require("dplyr")) {
-
   # short-hand version:
   example_isolates \%>\%
     filter_first_isolate(info = FALSE)
 }
 if (require("dplyr")) {
-
   # flag the first isolates per group:
   example_isolates \%>\%
     group_by(ward) \%>\%

man/get_episode.Rd

@@ -44,11 +44,12 @@ is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
 df[which(get_episode(df$date, 60) == 3), ]
 
 # the functions also work for less than a day, e.g. to include one per hour:
-get_episode(c(
-  Sys.time(),
-  Sys.time() + 60 * 60
-),
-episode_days = 1 / 24
+get_episode(
+  c(
+    Sys.time(),
+    Sys.time() + 60 * 60
+  ),
+  episode_days = 1 / 24
 )
 
 \donttest{
@@ -85,7 +86,6 @@ if (require("dplyr")) {
     )
 }
 if (require("dplyr")) {
-
   # grouping on patients and microorganisms leads to the same
   # results as first_isolate() when using 'episode-based':
   x <- df \%>\%
@@ -102,7 +102,6 @@ if (require("dplyr")) {
   identical(x, y)
 }
 if (require("dplyr")) {
-
   # but is_new_episode() has a lot more flexibility than first_isolate(),
   # since you can now group on anything that seems relevant:
   df \%>\%

man/ggplot_sir.Rd

@@ -138,13 +138,11 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
 \examples{
 \donttest{
 if (require("ggplot2") && require("dplyr")) {
-
   # get antimicrobial results for drugs against a UTI:
   ggplot(example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP)) +
     geom_sir()
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # prettify the plot using some additional functions:
   df <- example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP)
   ggplot(df) +
@@ -155,21 +153,18 @@ if (require("ggplot2") && require("dplyr")) {
     theme_sir()
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # or better yet, simplify this using the wrapper function - a single command:
   example_isolates \%>\%
     select(AMX, NIT, FOS, TMP, CIP) \%>\%
     ggplot_sir()
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # get only proportions and no counts:
   example_isolates \%>\%
     select(AMX, NIT, FOS, TMP, CIP) \%>\%
     ggplot_sir(datalabels = FALSE)
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # add other ggplot2 arguments as you like:
   example_isolates \%>\%
     select(AMX, NIT, FOS, TMP, CIP) \%>\%
@@ -182,14 +177,12 @@ if (require("ggplot2") && require("dplyr")) {
     )
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # you can alter the colours with colour names:
   example_isolates \%>\%
     select(AMX) \%>\%
     ggplot_sir(colours = c(SI = "yellow"))
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # but you can also use the built-in colour-blind friendly colours for
   # your plots, where "S" is green, "I" is yellow and "R" is red:
   data.frame(
@@ -202,7 +195,6 @@ if (require("ggplot2") && require("dplyr")) {
     scale_sir_colours(Value4 = "S", Value5 = "I", Value6 = "R")
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # resistance of ciprofloxacine per age group
   example_isolates \%>\%
     mutate(first_isolate = first_isolate()) \%>\%
@@ -216,14 +208,12 @@ if (require("ggplot2") && require("dplyr")) {
     ggplot_sir(x = "age_group")
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # a shorter version which also adjusts data label colours:
   example_isolates \%>\%
     select(AMX, NIT, FOS, TMP, CIP) \%>\%
     ggplot_sir(colours = FALSE)
 }
 if (require("ggplot2") && require("dplyr")) {
-
   # it also supports groups (don't forget to use the group var on `x` or `facet`):
   example_isolates \%>\%
     filter(mo_is_gram_negative(), ward != "Outpatient") \%>\%

man/mo_property.Rd

@@ -405,7 +405,6 @@ mo_species("EHEC")
 mo_fullname("K. pneu rh")
 mo_shortname("K. pneu rh")
 
-
 \donttest{
 # Becker classification, see ?as.mo ----------------------------------------
 

man/proportion.Rd

@@ -204,7 +204,6 @@ if (require("dplyr")) {
     )
 }
 if (require("dplyr")) {
-
   # scoped dplyr verbs with antibiotic selectors
   # (you could also use across() of course)
   example_isolates \%>\%