diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml index 35ad8b10..1fda8806 100644 --- a/.github/workflows/check.yaml +++ b/.github/workflows/check.yaml @@ -57,7 +57,7 @@ jobs: - {os: ubuntu-22.04, r: '4.1', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - {os: ubuntu-22.04, r: '4.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - {os: ubuntu-22.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - - {os: ubuntu-22.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} + - {os: ubuntu-22.04, r: '3.5', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - {os: ubuntu-22.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - {os: ubuntu-22.04, r: '3.3', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} - {os: ubuntu-22.04, r: '3.2', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"} diff --git a/DESCRIPTION b/DESCRIPTION index bcaec972..7d4bdd5c 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 1.8.1.9045 -Date: 2022-08-28 +Version: 1.8.1.9046 +Date: 2022-08-29 Title: Antimicrobial Resistance Data Analysis Description: Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by diff --git a/NEWS.md b/NEWS.md index 8952f05a..49406de8 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# AMR 1.8.1.9045 +# AMR 1.8.1.9046 ### New * EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations. diff --git a/R/data.R b/R/data.R index eb3543bf..644d5886 100755 --- a/R/data.R +++ b/R/data.R @@ -27,7 +27,7 @@ #' #' Two data sets containing all antibiotics/antimycotics and antivirals. Use [as.ab()] or one of the [`ab_*`][ab_property()] functions to retrieve values from the [antibiotics] data set. Three identifiers are included in this data set: an antibiotic ID (`ab`, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (`atc`) as defined by the WHO, and a Compound ID (`cid`) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes. #' @format -#' ## For the [antibiotics] data set: a [tibble[tibble::tibble] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables: +#' ## For the [antibiotics] data set: a [tibble][tibble::tibble] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables: #' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available #' - `cid`\cr Compound ID as found in PubChem #' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO @@ -43,7 +43,7 @@ #' - `iv_units`\cr Units of `iv_ddd` #' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use [ab_loinc()] to retrieve them quickly, see [ab_property()]. #' -#' ## For the [antivirals] data set: a [tibble[tibble::tibble] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables: +#' ## For the [antivirals] data set: a [tibble][tibble::tibble] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables: #' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC #' - `cid`\cr Compound ID as found in PubChem #' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO @@ -76,7 +76,7 @@ #' #' A data set containing the full microbial taxonomy (**last updated: `r CATALOGUE_OF_LIFE$yearmonth_LPSN`**) of `r nr2char(length(unique(microorganisms$kingdom[!microorganisms$kingdom %like% "unknown"])))` kingdoms from the Catalogue of Life (CoL) and the List of Prokaryotic names with Standing in Nomenclature (LPSN). MO codes can be looked up using [as.mo()]. #' @inheritSection catalogue_of_life Catalogue of Life -#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables: #' - `mo`\cr ID of microorganism as used by this package #' - `fullname`\cr Full name, like `"Escherichia coli"` #' - `kingdom`, `phylum`, `class`, `order`, `family`, `genus`, `species`, `subspecies`\cr Taxonomic rank of the microorganism @@ -134,7 +134,7 @@ #' #' A data set containing old (previously valid or accepted) taxonomic names according to the Catalogue of Life. This data set is used internally by [as.mo()]. #' @inheritSection catalogue_of_life Catalogue of Life -#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables: #' - `fullname`\cr Old full taxonomic name of the microorganism #' - `fullname_new`\cr New full taxonomic name of the microorganism #' - `ref`\cr Author(s) and year of concerning scientific publication @@ -152,7 +152,7 @@ #' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes #' #' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with [set_mo_source()]. They will all be searched when using [as.mo()] and consequently all the [`mo_*`][mo_property()] functions. -#' @format A [tibble[tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables: #' - `code`\cr Commonly used code of a microorganism #' - `mo`\cr ID of the microorganism in the [microorganisms] data set #' @details @@ -166,7 +166,7 @@ #' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates #' #' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. This data set contains randomised fictitious data, but reflects reality and can be used to practise AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html). -#' @format A [tibble[tibble::tibble] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables: #' - `date`\cr Date of receipt at the laboratory #' - `patient`\cr ID of the patient #' - `age`\cr Age of the patient @@ -183,7 +183,7 @@ #' Data Set with Unclean Data #' #' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice. -#' @format A [tibble[tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables: #' - `patient_id`\cr ID of the patient #' - `date`\cr date of receipt at the laboratory #' - `hospital`\cr ID of the hospital, from A to C @@ -198,7 +198,7 @@ #' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example #' #' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names are created using online surname generators and are only in place for practice purposes. -#' @format A [tibble[tibble::tibble] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables: #' - `Identification number`\cr ID of the sample #' - `Specimen number`\cr ID of the specimen #' - `Organism`\cr Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using [as.mo()]. @@ -234,7 +234,7 @@ #' Data Set for R/SI Interpretation #' #' Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`). Use [as.rsi()] to transform MICs or disks measurements to R/SI values. -#' @format A [tibble[tibble::tibble] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables: #' - `guideline`\cr Name of the guideline #' - `method`\cr Either `r vector_or(rsi_translation$method)` #' - `site`\cr Body site, e.g. "Oral" or "Respiratory" @@ -258,7 +258,7 @@ #' Data Set with Bacterial Intrinsic Resistance #' #' Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations. -#' @format A [tibble[tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables: #' - `mo`\cr Microorganism ID #' - `ab`\cr Antibiotic ID #' @details @@ -275,7 +275,7 @@ #' Data Set with Treatment Dosages as Defined by EUCAST #' #' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()]. -#' @format A [tibble[tibble::tibble] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables: +#' @format A [tibble][tibble::tibble] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables: #' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available #' - `name`\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO #' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)` diff --git a/R/guess_ab_col.R b/R/guess_ab_col.R index b9cb2066..15c59477 100755 --- a/R/guess_ab_col.R +++ b/R/guess_ab_col.R @@ -30,7 +30,7 @@ #' @param search_string a text to search `x` for, will be checked with [as.ab()] if this value is not a column in `x` #' @param verbose a [logical] to indicate whether additional info should be printed #' @param only_rsi_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `` (see [as.rsi()]) on beforehand (defaults to `FALSE`) -#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic. **Longer columns names take precedence over shorter column names.** +#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic. #' @return A column name of `x`, or `NULL` when no result is found. #' @export #' @examples @@ -40,13 +40,10 @@ #' ) #' #' guess_ab_col(df, "amoxicillin") -#' # [1] "amox" #' guess_ab_col(df, "J01AA07") # ATC code of tetracycline -#' # [1] "tetr" #' #' guess_ab_col(df, "J01AA07", verbose = TRUE) #' # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline). -#' # [1] "tetr" #' #' # WHONET codes #' df <- data.frame( @@ -54,19 +51,8 @@ #' AMC_ED20 = "S" #' ) #' guess_ab_col(df, "ampicillin") -#' # [1] "AMP_ND10" #' guess_ab_col(df, "J01CR02") -#' # [1] "AMC_ED20" #' guess_ab_col(df, as.ab("augmentin")) -#' # [1] "AMC_ED20" -#' -#' # Longer names take precendence: -#' df <- data.frame( -#' AMP_ED2 = "S", -#' AMP_ED20 = "S" -#' ) -#' guess_ab_col(df, "ampicillin") -#' # [1] "AMP_ED20" guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE, only_rsi_columns = FALSE) { meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE) meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = TRUE) diff --git a/R/plot.R b/R/plot.R index cdad32e7..a8d79859 100644 --- a/R/plot.R +++ b/R/plot.R @@ -65,7 +65,11 @@ #' \donttest{ #' if (require("ggplot2")) { #' autoplot(some_mic_values) +#' } +#' if (require("ggplot2")) { #' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro") +#' } +#' if (require("ggplot2")) { #' autoplot(some_rsi_values) #' } #' } diff --git a/_pkgdown.yml b/_pkgdown.yml index 16a399f4..1788cd8f 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -54,7 +54,7 @@ footer: right: [logo] components: devtext: 'AMR (for R). Developed at the University of Groningen in collaboration with non-profit organisations
Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.' - logo: '' + logo: '' home: sidebar: diff --git a/index.md b/index.md index a1f140a6..c38a3c44 100644 --- a/index.md +++ b/index.md @@ -175,11 +175,11 @@ To find out how to conduct AMR data analysis, please [continue reading here to g The development of this package is part of, related to, or made possible by:
- - - - - + + + + +
### Copyright diff --git a/man/WHONET.Rd b/man/WHONET.Rd index ddebd0b1..4539b891 100644 --- a/man/WHONET.Rd +++ b/man/WHONET.Rd @@ -5,7 +5,7 @@ \alias{WHONET} \title{Data Set with 500 Isolates - WHONET Example} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 500 observations and 53 variables: +A \link[tibble:tibble]{tibble} with 500 observations and 53 variables: \itemize{ \item \verb{Identification number}\cr ID of the sample \item \verb{Specimen number}\cr ID of the specimen diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd index 3e4313ee..04cb8b05 100644 --- a/man/antibiotics.Rd +++ b/man/antibiotics.Rd @@ -6,7 +6,7 @@ \alias{antivirals} \title{Data Sets with 566 Antimicrobial Drugs} \format{ -\subsection{For the \link{antibiotics} data set: a [tibble\link[tibble:tibble]{tibble::tibble} with 464 observations and 14 variables:}{ +\subsection{For the \link{antibiotics} data set: a \link[tibble:tibble]{tibble} with 464 observations and 14 variables:}{ \itemize{ \item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available \item \code{cid}\cr Compound ID as found in PubChem @@ -25,7 +25,7 @@ } } -\subsection{For the \link{antivirals} data set: a [tibble\link[tibble:tibble]{tibble::tibble} with 102 observations and 9 variables:}{ +\subsection{For the \link{antivirals} data set: a \link[tibble:tibble]{tibble} with 102 observations and 9 variables:}{ \itemize{ \item \code{atc}\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC \item \code{cid}\cr Compound ID as found in PubChem diff --git a/man/dosage.Rd b/man/dosage.Rd index cfe0a79e..b407a958 100644 --- a/man/dosage.Rd +++ b/man/dosage.Rd @@ -5,7 +5,7 @@ \alias{dosage} \title{Data Set with Treatment Dosages as Defined by EUCAST} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 169 observations and 9 variables: +A \link[tibble:tibble]{tibble} with 169 observations and 9 variables: \itemize{ \item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available \item \code{name}\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO diff --git a/man/example_isolates.Rd b/man/example_isolates.Rd index fcb21288..34f0d87c 100644 --- a/man/example_isolates.Rd +++ b/man/example_isolates.Rd @@ -5,7 +5,7 @@ \alias{example_isolates} \title{Data Set with 2,000 Example Isolates} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 2,000 observations and 46 variables: +A \link[tibble:tibble]{tibble} with 2,000 observations and 46 variables: \itemize{ \item \code{date}\cr Date of receipt at the laboratory \item \code{patient}\cr ID of the patient diff --git a/man/example_isolates_unclean.Rd b/man/example_isolates_unclean.Rd index 8fbe04fa..aa620b9b 100644 --- a/man/example_isolates_unclean.Rd +++ b/man/example_isolates_unclean.Rd @@ -5,7 +5,7 @@ \alias{example_isolates_unclean} \title{Data Set with Unclean Data} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 3,000 observations and 8 variables: +A \link[tibble:tibble]{tibble} with 3,000 observations and 8 variables: \itemize{ \item \code{patient_id}\cr ID of the patient \item \code{date}\cr date of receipt at the laboratory diff --git a/man/figures/logo_rug.png b/man/figures/logo_rug.png deleted file mode 100755 index 23d14c38..00000000 Binary files a/man/figures/logo_rug.png and /dev/null differ diff --git a/man/figures/logo_rug.svg b/man/figures/logo_rug.svg new file mode 100644 index 00000000..37d19c79 --- /dev/null +++ b/man/figures/logo_rug.svg @@ -0,0 +1,274 @@ + + + + + + + + + + + + + diff --git a/man/guess_ab_col.Rd b/man/guess_ab_col.Rd index 70386cef..7cd7d6ea 100644 --- a/man/guess_ab_col.Rd +++ b/man/guess_ab_col.Rd @@ -27,7 +27,7 @@ A column name of \code{x}, or \code{NULL} when no result is found. This tries to find a column name in a data set based on information from the \link{antibiotics} data set. Also supports WHONET abbreviations. } \details{ -You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \link{antibiotics} data set for any column containing a name or code of that antibiotic. \strong{Longer columns names take precedence over shorter column names.} +You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \link{antibiotics} data set for any column containing a name or code of that antibiotic. } \examples{ df <- data.frame( @@ -36,13 +36,10 @@ df <- data.frame( ) guess_ab_col(df, "amoxicillin") -# [1] "amox" guess_ab_col(df, "J01AA07") # ATC code of tetracycline -# [1] "tetr" guess_ab_col(df, "J01AA07", verbose = TRUE) # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline). -# [1] "tetr" # WHONET codes df <- data.frame( @@ -50,17 +47,6 @@ df <- data.frame( AMC_ED20 = "S" ) guess_ab_col(df, "ampicillin") -# [1] "AMP_ND10" guess_ab_col(df, "J01CR02") -# [1] "AMC_ED20" guess_ab_col(df, as.ab("augmentin")) -# [1] "AMC_ED20" - -# Longer names take precendence: -df <- data.frame( - AMP_ED2 = "S", - AMP_ED20 = "S" -) -guess_ab_col(df, "ampicillin") -# [1] "AMP_ED20" } diff --git a/man/intrinsic_resistant.Rd b/man/intrinsic_resistant.Rd index 8e1e33b0..60c5df38 100644 --- a/man/intrinsic_resistant.Rd +++ b/man/intrinsic_resistant.Rd @@ -5,7 +5,7 @@ \alias{intrinsic_resistant} \title{Data Set with Bacterial Intrinsic Resistance} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 134,956 observations and 2 variables: +A \link[tibble:tibble]{tibble} with 134,956 observations and 2 variables: \itemize{ \item \code{mo}\cr Microorganism ID \item \code{ab}\cr Antibiotic ID diff --git a/man/microorganisms.Rd b/man/microorganisms.Rd index 778f085c..a22ae510 100755 --- a/man/microorganisms.Rd +++ b/man/microorganisms.Rd @@ -5,7 +5,7 @@ \alias{microorganisms} \title{Data Set with 70,764 Microorganisms} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 70,764 observations and 16 variables: +A \link[tibble:tibble]{tibble} with 70,764 observations and 16 variables: \itemize{ \item \code{mo}\cr ID of microorganism as used by this package \item \code{fullname}\cr Full name, like \code{"Escherichia coli"} diff --git a/man/microorganisms.codes.Rd b/man/microorganisms.codes.Rd index 2df9a756..52a742fc 100644 --- a/man/microorganisms.codes.Rd +++ b/man/microorganisms.codes.Rd @@ -5,7 +5,7 @@ \alias{microorganisms.codes} \title{Data Set with 5,604 Common Microorganism Codes} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 5,604 observations and 2 variables: +A \link[tibble:tibble]{tibble} with 5,604 observations and 2 variables: \itemize{ \item \code{code}\cr Commonly used code of a microorganism \item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set diff --git a/man/microorganisms.old.Rd b/man/microorganisms.old.Rd index 4e3b214e..cc24fe44 100644 --- a/man/microorganisms.old.Rd +++ b/man/microorganisms.old.Rd @@ -5,7 +5,7 @@ \alias{microorganisms.old} \title{Data Set with Previously Accepted Taxonomic Names} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 14,338 observations and 4 variables: +A \link[tibble:tibble]{tibble} with 14,338 observations and 4 variables: \itemize{ \item \code{fullname}\cr Old full taxonomic name of the microorganism \item \code{fullname_new}\cr New full taxonomic name of the microorganism diff --git a/man/plot.Rd b/man/plot.Rd index 20ee1d24..a26b8b7e 100644 --- a/man/plot.Rd +++ b/man/plot.Rd @@ -147,7 +147,11 @@ plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "uk") \donttest{ if (require("ggplot2")) { autoplot(some_mic_values) +} +if (require("ggplot2")) { autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro") +} +if (require("ggplot2")) { autoplot(some_rsi_values) } } diff --git a/man/rsi_translation.Rd b/man/rsi_translation.Rd index 8b2776a5..996871de 100644 --- a/man/rsi_translation.Rd +++ b/man/rsi_translation.Rd @@ -5,7 +5,7 @@ \alias{rsi_translation} \title{Data Set for R/SI Interpretation} \format{ -A [tibble\link[tibble:tibble]{tibble::tibble} with 20,369 observations and 11 variables: +A \link[tibble:tibble]{tibble} with 20,369 observations and 11 variables: \itemize{ \item \code{guideline}\cr Name of the guideline \item \code{method}\cr Either "DISK" or "MIC" diff --git a/pkgdown/logos/logo_rug.png b/pkgdown/logos/logo_rug.png deleted file mode 100755 index 23d14c38..00000000 Binary files a/pkgdown/logos/logo_rug.png and /dev/null differ diff --git a/pkgdown/logos/logo_rug.svg b/pkgdown/logos/logo_rug.svg new file mode 100644 index 00000000..37d19c79 --- /dev/null +++ b/pkgdown/logos/logo_rug.svg @@ -0,0 +1,274 @@ + + + + + + + + + + + + +