v0.1.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: NMdata
 Type: Package
 Title: Preparation, Checking and Post-Processing Data for PK/PD Modeling
-Version: 0.0.17.911
+Version: 0.1.0
 Authors@R: c(person("Philip", "Delff", email = "[email protected]", role = c("aut", "cre")))
 Maintainer: Philip Delff <[email protected]>
 Description: Efficient tools for preparation, checking and post-processing of data in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem. Attention is paid to ensure consistency, traceability, and Nonmem compatibility of Data. Rigorously checks final Nonmem datasets. Implemented in 'data.table', but easily integrated with 'base' and 'tidyverse'.

R/NMcheckData.R

@@ -180,11 +180,13 @@
 ##' }
 ##' @return A table with findings
 ##' @examples
+##' \dontrun{
 ##' dat <- readRDS(system.file("examples/data/xgxr2.rds", package="NMdata"))
 ##' NMcheckData(dat)
 ##' dat[EVID==0,LLOQ:=3.5]
 ##' ## expecting LLOQ only for samples
 ##' NMcheckData(dat,cols.num=list(c("STUDY"),"EVID==0"=c("LLOQ")))
+##' }
 ##' @import data.table
 ##' @export
 

R/NMscanData.R

@@ -151,7 +151,9 @@
 ##'  \item{NULL}{The NULL argument to specify missing value string in input data is not respected. If delimited input data is read (as opposed to rds files), missing values are assumed to be represented by dots (.).}
 ##' }
 ##' @examples
+##' \dontrun{
 ##' res1 <- NMscanData(system.file("examples/nonmem/xgxr001.lst", package="NMdata"))
+##' }
 ##' @return A data set of class 'NMdata'.
 ##' @family DataRead
 ##' @import data.table

R/NMscanMultiple.R

@@ -18,11 +18,13 @@
 ##' @param ... Additional arguments passed to NMscanData.
 ##' @return All results stacked, class as defined by as.fun
 ##' @examples
+##' \dontrun{
 ##' res <- NMscanMultiple(dir=system.file("examples/nonmem", package="NMdata"),
 ##' file.pattern="xgxr01.*\\.lst",as.fun="data.table")
 ##' res.mean <- res[,.(meanPRED=exp(mean(log(PRED)))),by=.(model,NOMTIME)]
 ##' library(ggplot2)
-##' ggplot(res.mean,aes(NOMTIME,meanPRED,colour=model))+geom_line() 
+##' ggplot(res.mean,aes(NOMTIME,meanPRED,colour=model))+geom_line()
+##' }
 ##' @export
 
 

R/NMwriteData.R

@@ -48,15 +48,15 @@
 ##'     Nonmem.
 ##' @param save Save defined files? Default is TRUE. If a variable is
 ##'     used to control whether a script generates outputs (say
-##'     `writeOutputs=TRUE/FALSE`), if you use `save=writeOutputs` to
-##'     comply with this.
+##'     \code{writeOutputs=TRUE/FALSE)}, if you use
+##'     \code{save=writeOutputs} to comply with this.
 ##' @param args.NMgenText List of arguments to pass to NMgenText - the
 ##'     function that generates text suggestion for INPUT and DATA
 ##'     sections in the Nonmem control stream. You can use these
 ##'     arguments to get a text suggestion you an use directly in
-##'     Nonmem - and NMwriteSection can even update multiple Nonmem
-##'     control streams based on the result. This will update your
-##'     control streams to match your new data file with just one
+##'     Nonmem - and \code{NMwriteSection} can even update multiple
+##'     Nonmem control streams based on the result. This will update
+##'     your control streams to match your new data file with just one
 ##'     command.
 ##' @param csv.trunc.as.nm If TRUE, csv file will be truncated
 ##'     horizontally (columns will be dropped) to match the $INPUT

R/findCovs.R

@@ -39,10 +39,12 @@
 ##' ## occasion level
 ##' findCovs(findVars(dt1,"ID"),c("ID","OCC"))
 ##' ## Based on a "real data example"
+##' \dontrun{
 ##' dat <- NMscanData(system.file("examples/nonmem/xgxr001.lst", package = "NMdata"))
 ##' findCovs(dat,by="ID")
 ##' ### Without an ID column we get non-varying columns
 ##' findCovs(dat)
+##' }
 ##' @export
 
 

R/flagsAssign.R

@@ -48,6 +48,7 @@
 ##' @import data.table
 ##' @family DataCreate
 ##' @examples
+##' \dontrun{
 ##' pk <- readRDS(file=system.file("examples/data/xgxr2.rds",package="NMdata"))
 ##' dt.flags <- data.frame(
 ##'        flagn=10,
@@ -59,6 +60,7 @@
 ##'         col.flagn="flagn",col.flagc="flagc")
 ##' unique(pk[,c("EVID","flagn","flagc","BLQ")])
 ##' flagsCount(pk[EVID==0],dt.flags,col.flagn="flagn",col.flagc="flagc")
+##' }
 ##' @export
 
 

R/flagsCount.R

@@ -67,6 +67,7 @@
 ##' @import data.table
 ##' @family DataCreate
 ##' @examples
+##' \dontrun{
 ##' pk <- readRDS(file=system.file("examples/data/xgxr2.rds",package="NMdata"))
 ##' dt.flags <- data.frame(
 ##'        flagn=10,
@@ -78,6 +79,7 @@
 ##'         col.flagn="flagn",col.flagc="flagc")
 ##' unique(pk[,c("EVID","flagn","flagc","BLQ")])
 ##' flagsCount(pk[EVID==0],dt.flags,col.flagn="flagn",col.flagc="flagc")
+##' }
 ##' @export
 
 

R/lstExtractTime.R

@@ -8,11 +8,13 @@
 ##' NMdata:::lstExtractTime(file)
 ##' file <- system.file("examples/nonmem/xgxr003.mod",package="NMdata")
 ##' NMdata:::lstExtractTime(file)
-##' 
+##'
+##' \dontrun{
 ##' all.lsts <- list.files(
 ##'   system.file("examples/nonmem",package="NMdata"),
 ##'   pattern="\\.lst",full.names=TRUE)
 ##' lapply(all.lsts,NMdata:::lstExtractTime)
+##' }
 ##' @keywords internal
 
 lstExtractTime <- function(file,tz.lst="as.is"){

R/zzz.R

@@ -7,5 +7,5 @@ NMdataConf(reset=TRUE)
 
 ##' @importFrom utils packageVersion
 .onAttach <- function(libname,pkgname){
-    packageStartupMessage(paste0("This is NMdata ",packageVersion("NMdata"),". Browse NMdata documentation at\nhttps://philipdelff.github.io/NMdata/"))
+    packageStartupMessage(paste0("NMdata ",packageVersion("NMdata"),". Browse NMdata documentation at\nhttps://philipdelff.github.io/NMdata/"))
 }

README.Rmd

@@ -61,7 +61,7 @@ the
 <a href="https://htmlpreview.github.io/?https://github.com/philipdelff/NMdata/blob/master/vignettes/NMdata-cheat.html"><img src="man/figures/cheatsheet_icon_0010.png" alt="CheatSheet" width="200"/></a>
 
 ### How to install
-`NMdata` is on [CRAN](https://cran.r-project.org/), [MRAN](https://mran.microsoft.com/), and [MPN](https://mpn.metworx.com). To install from the package archive you are already using, do:
+`NMdata` is on [CRAN](https://cran.r-project.org/package=NMdata) and [MPN](https://mpn.metworx.com/docs/packages/NMdata). To install from the package archive you are already using, do:
 
 ```
 install.packages("NMdata")

README.md

@@ -46,16 +46,15 @@ the
 [Cheatsheet](https://htmlpreview.github.io/?https://github.com/philipdelff/NMdata/blob/master/vignettes/NMdata-cheat.html).
 
 <!-- ![Cheatsheet](man/figures/cheatsheet_icon_0010.png){width="15%"} -->
-
 <!-- [Cheatsheet](https://htmlpreview.github.io/?https://github.com/philipdelff/NMdata/blob/master/devel/NMdata-cheat.html) -->
 
 <a href="https://htmlpreview.github.io/?https://github.com/philipdelff/NMdata/blob/master/vignettes/NMdata-cheat.html"><img src="man/figures/cheatsheet_icon_0010.png" alt="CheatSheet" width="200"/></a>
 
 ### How to install
 
-`NMdata` is on [CRAN](https://cran.r-project.org/),
-[MRAN](https://mran.microsoft.com/), and [MPN](https://mpn.metworx.com).
-To install from the package archive you are already using, do:
+`NMdata` is on [CRAN](https://cran.r-project.org/package=NMdata) and
+[MPN](https://mpn.metworx.com/docs/packages/NMdata). To install from the
+package archive you are already using, do:
 
     install.packages("NMdata")
     library(NMdata)
@@ -120,7 +119,7 @@ ggplot(res.plot,aes(TIME))+
     labs(y="Concentration (unit)",colour="Observations",
          subtitle="NOTICE:\nObservations are coloured by a character column fetched from input data.\nSamples below LLOQ are rows added from input data.\nPlots are correctly sorted because factor levels of dose are preserved from input data.")+
     theme_bw()+theme(legend.position="bottom")
-#> Warning: Removed 2 row(s) containing missing values (geom_path).
+#> Warning: Removed 2 rows containing missing values (`geom_line()`).
 ```
 
 <img src="man/figures/README-NMscanData-example1-plot-1.png" width="100%" />
@@ -156,15 +155,17 @@ read multiple models and compare their predictions.
 ``` r
 res <- NMscanMultiple(dir=system.file("examples/nonmem", package="NMdata"),
 file.pattern="xgxr.*\\.lst",as.fun="data.table",quiet=TRUE)
-#> No missing values identified
+#> Input and output data were searched for candidate unique row identifiers. None
+#> found. To skip this check, please use merge.by.row=TRUE or merge.by.row=FALSE.
+#> 
 #> 
 #> Overview of model scanning results:
-#>                                                                             lst
-#> 1: /tmp/RtmpTd9QIu/temp_libpath102521020f9b7/NMdata/examples/nonmem/xgxr001.lst
-#> 2: /tmp/RtmpTd9QIu/temp_libpath102521020f9b7/NMdata/examples/nonmem/xgxr002.lst
-#> 3: /tmp/RtmpTd9QIu/temp_libpath102521020f9b7/NMdata/examples/nonmem/xgxr003.lst
-#> 4: /tmp/RtmpTd9QIu/temp_libpath102521020f9b7/NMdata/examples/nonmem/xgxr014.lst
-#> 5: /tmp/RtmpTd9QIu/temp_libpath102521020f9b7/NMdata/examples/nonmem/xgxr018.lst
+#>                                                                            lst
+#> 1: /tmp/Rtmp82nZom/temp_libpath1370126d22f6/NMdata/examples/nonmem/xgxr001.lst
+#> 2: /tmp/Rtmp82nZom/temp_libpath1370126d22f6/NMdata/examples/nonmem/xgxr002.lst
+#> 3: /tmp/Rtmp82nZom/temp_libpath1370126d22f6/NMdata/examples/nonmem/xgxr003.lst
+#> 4: /tmp/Rtmp82nZom/temp_libpath1370126d22f6/NMdata/examples/nonmem/xgxr014.lst
+#> 5: /tmp/Rtmp82nZom/temp_libpath1370126d22f6/NMdata/examples/nonmem/xgxr018.lst
 #>    nrows ncols success warning
 #> 1:   905    40    TRUE   FALSE
 #> 2:   905    34    TRUE   FALSE
@@ -195,7 +196,7 @@ reached CRAN, installing from Github is easy too.
     ## Option 2: Install explicitly from CRAN
     install.packages("NMdata",repos="https://cloud.r-project.org")
     library(NMdata)
-    
+
     ## Option 3: Install from github
     library(remotes)
     install_github("philipdelff/NMdata")