rename columns

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
 Version: 0.1.1
-Date: 2018-02-23
+Date: 2018-02-26
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(

NEWS

@@ -1,5 +1,5 @@
 ## 0.1.1
-- EUCAST_rules applies for amoxicillin even if ampicillin is missing
+- `EUCAST_rules` applies for amoxicillin even if ampicillin is missing
 - Edited column names to comply with GLIMS, the laboratory information system
 
 ## 0.1.0

R/data.R

@@ -29,7 +29,7 @@
 #'   \item{\code{trivial}}{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_units}}{Units of \code{ddd_units}}
-#'   \item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, bij parenteral treatment}
+#'   \item{\code{iv_ddd}}{Daily Defined 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"}}
@@ -56,7 +56,7 @@
 #'   \item{\code{species}}{Species name of microorganism, like \code{"coli"}}
 #'   \item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
 #'   \item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
-#'   \item{\code{type}}{Type of microorganism, like \code{"Bacterie"} en \code{"Schimmel/gist"} (these are Dutch)}
+#'   \item{\code{type}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
 #'   \item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
 #'   \item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
 #' }

R/first_isolates.R

@@ -364,7 +364,7 @@ first_isolate <- function(tbl,
 #' tbl$keyab <- key_antibiotics(tbl)
 #' }
 key_antibiotics <- function(tbl,
-                            col_bactcode = 'bacteriecode',
+                            col_bactcode = 'bactid',
                             info = TRUE,
                             amcl = 'amcl',
                             amox = 'amox',

R/rsi_analysis.R

@@ -254,26 +254,27 @@ rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FA
 #' @examples
 #' \dontrun{
 #' # use it directly:
-#' rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
+#' rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], col_ab = "amcl", coldate = "date")
 #'   
 #' # or with dplyr so you can actually read it:
 #' library(dplyr)
 #' tbl %>%
 #'   filter(first_isolate == TRUE,
 #'          genus == "Haemophilus") %>%
-#'   rsi_predict("amcl")
+#'   rsi_predict(col_ab = "amcl", coldate = "date")
 #'
 #' tbl %>%
 #'   filter(first_isolate_weighted == TRUE,
 #'          genus == "Haemophilus") %>%
 #'   rsi_predict(col_ab = "amcl",
+#'               coldate = "date",
 #'               year_max = 2050,
 #'               year_every = 5)
 #'
 #' }
 rsi_predict <- function(tbl,
                         col_ab,
-                        col_date = 'ontvangstdatum',
+                        col_date,
                         year_max = as.integer(format(as.Date(Sys.Date()), '%Y')) + 15,
                         year_every = 1,
                         model = 'binomial',