diff --git a/DESCRIPTION b/DESCRIPTION
index c8fe257f..42cf300b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: AMR
Version: 0.1.1
-Date: 2018-02-26
+Date: 2018-03-13
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(
diff --git a/NAMESPACE b/NAMESPACE
index 9232c22b..76dccd3d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -3,6 +3,8 @@
S3method(as.double,mic)
S3method(as.integer,mic)
S3method(as.numeric,mic)
+S3method(barplot,mic)
+S3method(barplot,rsi)
S3method(plot,mic)
S3method(plot,rsi)
S3method(print,mic)
@@ -32,6 +34,8 @@ export(semi_join_bactlist)
exportMethods(as.double.mic)
exportMethods(as.integer.mic)
exportMethods(as.numeric.mic)
+exportMethods(barplot.mic)
+exportMethods(barplot.rsi)
exportMethods(plot.mic)
exportMethods(plot.rsi)
exportMethods(print.mic)
diff --git a/R/classes.R b/R/classes.R
index e1f3bdad..88db4caa 100644
--- a/R/classes.R
+++ b/R/classes.R
@@ -125,7 +125,7 @@ summary.rsi <- function(object, ...) {
#' @exportMethod plot.rsi
#' @export
-#' @importFrom dplyr %>% group_by summarise filter mutate if_else
+#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
#' @importFrom graphics plot text
#' @noRd
plot.rsi <- function(x, ...) {
@@ -150,12 +150,43 @@ plot.rsi <- function(x, ...) {
ylab = 'Percentage',
xlab = 'Antimicrobial Interpretation',
main = paste('Susceptibilty Analysis of', x_name),
+ axes = FALSE,
...)
+ # x axis
+ axis(side = 1, at = 1:n_distinct(data$x), labels = levels(data$x), lwd = 0)
+ # y axis, 0-100%
+ axis(side = 2, at = seq(0, 100, 5))
+
text(x = data$x,
- y = data$s + 5,
+ y = data$s + 4,
labels = paste0(data$s, '% (n = ', data$n, ')'))
}
+
+#' @exportMethod barplot.rsi
+#' @export
+#' @importFrom dplyr %>% group_by summarise filter mutate if_else n_distinct
+#' @importFrom graphics plot text
+#' @noRd
+barplot.rsi <- function(x, ...) {
+ x_name <- deparse(substitute(x))
+
+ data <- data.frame(rsi = x, cnt = 1) %>%
+ group_by(rsi) %>%
+ summarise(cnt = sum(cnt)) %>%
+ droplevels()
+
+ barplot(table(rsi_data),
+ col = c('green3', 'orange2', 'red3'),
+ xlab = 'Antimicrobial Interpretation',
+ main = paste('Susceptibilty Analysis of', x_name),
+ ylab = 'Frequency',
+ axes = FALSE,
+ ...)
+ # y axis, 0-100%
+ axis(side = 2, at = seq(0, max(data$cnt) + max(data$cnt) * 1.1, by = 25))
+}
+
#' Class 'mic'
#'
#' This transforms a vector to a new class\code{mic}, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
@@ -169,6 +200,7 @@ plot.rsi <- function(x, ...) {
#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
#' is.mic(mic_data)
#' plot(mic_data)
+#' barplot(mic_data)
#'
#' \donttest{
#' library(dplyr)
@@ -357,21 +389,29 @@ summary.mic <- function(object, ...) {
#' @noRd
plot.mic <- function(x, ...) {
x_name <- deparse(substitute(x))
-
+ create_barplot_mic(x, x_name, ...)
+}
+
+#' @exportMethod barplot.mic
+#' @export
+#' @importFrom dplyr %>% group_by summarise
+#' @importFrom graphics plot text
+#' @noRd
+barplot.mic <- function(x, ...) {
+ x_name <- deparse(substitute(x))
+ create_barplot_mic(x, x_name, ...)
+}
+
+create_barplot_mic <- function(x, x_name, ...) {
data <- data.frame(mic = x, cnt = 1) %>%
group_by(mic) %>%
summarise(cnt = sum(cnt)) %>%
droplevels()
-
- plot(x = data$mic,
- y = data$cnt,
- lwd = 2,
- ylim = c(-0.5, max(5, max(data$cnt))),
- ylab = 'Frequency',
- xlab = 'MIC value',
- main = paste('MIC values of', x_name),
- ...)
- text(x = data$mic,
- y = -0.5,
- labels = paste('n =', data$cnt))
+ barplot(table(droplevels(x)),
+ ylab = 'Frequency',
+ xlab = 'MIC value',
+ main = paste('MIC values of', x_name),
+ axes = FALSE,
+ ...)
+ axis(2, seq(0, max(data$cnt)))
}
diff --git a/README.md b/README.md
index 4e42b958..3258613f 100644
--- a/README.md
+++ b/README.md
@@ -13,22 +13,26 @@ AMR can also be predicted for the forthcoming years with the `rsi_predict` funct
It also contains functions to translate antibiotic codes from the lab (like `"AMOX"`) or the [WHO](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like `"J01CA04"`) to trivial names (like `"amoxicillin"`) and vice versa.
## How to get it?
-[](http://cran.r-project.org/package=AMR)[](http://cran.r-project.org/package=AMR)[](https://travis-ci.org/msberends/AMR)
+This package is available on CRAN and also here on GitHub.
-This package is available on CRAN (latest stable version) and also here on GitHub (latest development version).
+### From CRAN (recommended, latest stable version)
+[](http://cran.r-project.org/package=AMR)
+[](http://cran.r-project.org/package=AMR)
-### Latest stable version from CRAN (recommended)
-For RStudio:
-- Click on `Tools` and then `Install Packages...`
-- Type in `AMR` and press Install
+- RStudio:
+ - Click on `Tools` and then `Install Packages...`
+ - Type in `AMR` and press Install
+
+- R console:
+ - `install.packages("AMR")`
+
+### From GitHub (latest development version)
+[](https://travis-ci.org/msberends/AMR)
+[](https://github.com/msberends/AMR/releases)
+[](https://github.com/msberends/AMR/commits/master)
-Or in the R console:
-```r
-install.packages("AMR")
-```
-
-### Latest development version from GitHub
```r
+install.packages("devtools")
devtools::install_github("msberends/AMR")
```
@@ -155,6 +159,8 @@ bactlist # A tibble: 2,507 x 10
2 Department of Medical, Market and Innovation (MMI), Certe Medische diagnostiek & advies, Groningen, the Netherlands
## Copyright
+[](https://github.com/msberends/AMR/blob/master/LICENSE)
+
This R package is licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/master/LICENSE). In a nutshell, this means that this package:
- May be used for commercial purposes
diff --git a/man/ablist.Rd b/man/ablist.Rd
index 7d203e99..ed3ba3bc 100644
--- a/man/ablist.Rd
+++ b/man/ablist.Rd
@@ -12,9 +12,9 @@
\item{\code{official}}{Official name by the WHO, like \code{"amoxicillin and enzyme inhibitor"}}
\item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
\item{\code{trivial_nl}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
- \item{\code{oral_ddd}}{Daily Defined Dose (DDD) according to the WHO, oral treatment}
+ \item{\code{oral_ddd}}{Defined Daily Dose (DDD) according to the WHO, oral treatment}
\item{\code{oral_units}}{Units of \code{ddd_units}}
- \item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, parenteral treatment}
+ \item{\code{iv_ddd}}{Defined Daily Dose (DDD) according to the WHO, parenteral treatment}
\item{\code{iv_units}}{Units of \code{iv_ddd}}
\item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
\item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
diff --git a/man/as.mic.Rd b/man/as.mic.Rd
index c524fdca..db7bbe9c 100644
--- a/man/as.mic.Rd
+++ b/man/as.mic.Rd
@@ -18,12 +18,13 @@ is.mic(x)
New class \code{mic}
}
\description{
-This transforms a vector to a new class\code{mic}, which is an ordered factor valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
+This transforms a vector to a new class\code{mic}, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
}
\examples{
mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
is.mic(mic_data)
plot(mic_data)
+barplot(mic_data)
\donttest{
library(dplyr)
diff --git a/man/atc_property.Rd b/man/atc_property.Rd
index edd82fbe..c4e5a6cd 100644
--- a/man/atc_property.Rd
+++ b/man/atc_property.Rd
@@ -20,7 +20,7 @@ atc_property(atc_code, property, administration = "O",
\item{url}{url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.}
}
\description{
-Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic. \strong{This function requires an internet connection.}
+Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. \strong{This function requires an internet connection.}
}
\details{
Abbreviations for the property \code{"Adm.R"} (parameter \code{administration}):
@@ -51,7 +51,7 @@ Abbreviations for the property \code{"U"} (unit):
}
\examples{
\donttest{
-atc_property("J01CA04", "DDD", "O") # oral DDD of amoxicillin
-atc_property("J01CA04", "DDD", "P") # parenteral DDD of amoxicillin
+atc_property("J01CA04", "DDD", "O") # oral DDD (Defined Daily Dose) of amoxicillin
+atc_property("J01CA04", "DDD", "P") # parenteral DDD (Defined Daily Dose) of amoxicillin
}
}
diff --git a/man/first_isolate.Rd b/man/first_isolate.Rd
index 68a6c280..51e9fe3d 100644
--- a/man/first_isolate.Rd
+++ b/man/first_isolate.Rd
@@ -53,7 +53,7 @@ Determine first (weighted) isolates of all microorganisms of every patient per e
\strong{Why this is so important} \cr
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode \href{https://www.ncbi.nlm.nih.gov/pubmed/17304462}{[1]}. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
- \strong{\code{points_threshold}} \cr
+ \strong{Using parameter \code{points_threshold}} \cr
To compare key antibiotics, the difference between antimicrobial interpretations will be measured. A difference from I to S|R (or vice versa) means 0.5 points. A difference from S to R (or vice versa) means 1 point. When the sum of points exceeds \code{points_threshold}, an isolate will be (re)selected as a first weighted isolate.
}
\examples{