extra vignettes

.Rbuildignore

@@ -49,9 +49,8 @@ docs
 ^\.drone\.jsonnet$
 ^doc$
 ^Meta$
-vignettes/mevent\.Rmd
-vignettes/mevent-0\.cpp
-vignettes/mevent-1\.cpp
+vignettes/extra
 vignettes/build
-vignettes/mrgsolve_builds
 vignettes/mrgsolve-builds
+vignettes/extra/mrgsolve-builds/
+

.gitignore

@@ -17,3 +17,6 @@ Rchecks
 inst/maintenance/unit/tests.md
 doc
 Meta
+inst/maintenance/unit/mrgsolve-so*
+vignettes/mrgsolve-builds
+vignettes/extra/mrgsolve-builds/

Makefile

@@ -24,6 +24,8 @@ package:
 	make house
 	make doc
 	make build-vignettes
+	make vignettes2
+	make install
 
 check:
 	make house
@@ -35,10 +37,14 @@ check:
 cran:
 	make house
 	make doc
+	make vignettes2
 	make build-vignettes
 	export _MRGSOLVE_SKIP_MODLIB_BUILD_=false
 	R CMD CHECK --as-cran ${TARBALL}
 
+vignettes2:
+	Rscript vignettes/extra/make.R
+
 drone:
 	make house
 	R CMD build --md5 $(PKGDIR) 

vignettes/events.Rmd

@@ -35,7 +35,7 @@ Let's illustrate event objects with a one-compartment, PK model.  We read this
 model from the `mrgsolve` internal model library.
 
 ```{r,message=FALSE}
-mod <- modlib("pk1cmt", end = 216, delta = 0.1)
+mod <- house(end = 216, delta = 0.1)
 ```
 
 # Events
@@ -61,7 +61,7 @@ We can implement this series of doses by passing `e` in as the `events` argument
 to `mrgsim`
 
 ```{r}
-mod %>% mrgsim(events = e) %>% plot(EV1 + CP ~ time)
+mod %>% mrgsim(events = e) %>% plot(GUT + CP ~ time)
 ```
 
 
@@ -105,10 +105,10 @@ We can combine `e1` and `e3` with a collection operator
 c(e1, e4)
 ```
 
-`mrgsolve` also defines a `%then$` operator that lets you execute one event and 
-`%then%` a second event
+`mrgsolve` also defines a `seq()` method that lets you execute one event and 
+then a second event
 ```{r}
-e3 %then% e2
+seq(e3, e2)
 ```
 
 Notice that `e3` has both `ii` and `addl` defined.  This is required for 
@@ -138,10 +138,10 @@ data
 ```
 
 To simulate from this data set, we use the `data_set` function.  First, let's 
-load a population PK model
+add an OMEGA matrix to this model:
 
 ```{r,message=FALSE}
-mod <- modlib("popex")
+mod <- omat(mod, as_dmat(c(0.1, 0.1, 0.1, 0.1)))
 ```
 ```{r}
 mod %>% data_set(data) %>% mrgsim(end=336) %>% plot("GUT, DV")

vignettes/extra/global.R

@@ -0,0 +1,2 @@
+knitr::opts_chunk$set(message = FALSE, warning = FALSE, comment='.')
+options(mrgsolve.soloc = "mrgsolve-builds")

vignettes/extra/make.R

@@ -0,0 +1,6 @@
+message("making secondary vignettes")
+stopifnot(`rmarkdown is required` = require(rmarkdown))
+render("vignettes/extra/time-after-dose.Rmd", output_dir = "inst/doc", quiet = TRUE)
+render("vignettes/extra/modeled-event-time.Rmd", output_dir = "inst/doc", quiet = TRUE)
+res <- file.remove(list.files("inst/doc", pattern = "\\.md*", full.names=TRUE))
+res <- unlink("inst/doc/mtime_files", recursive = TRUE)

vignettes/mrgsolve.Rmd

@@ -16,8 +16,6 @@ vignette: >
 ---
 
 ```{r setup, echo = FALSE, message = FALSE, warning = FALSE, code = readLines("global.R")}
-mod <- mread_cache("pk1", modlib())
-mod <- mread_cache("pk2", modlib())
 set.seed(20202)
 ```
 

vignettes/steady-state.Rmd

@@ -57,7 +57,7 @@ Let's load a PK model
 library(dplyr)
 library(mrgsolve)
 
-mod <- modlib("pk2")
+mod <- house(end = 24, delta = 1)
 ```
 
 And let's imagine a 100 mg QD dosing regimen
@@ -75,7 +75,7 @@ Let's just look at trough concentrations and see how the trough develops over
 the dosing period
 
 ```{r}
-mod <- update(mod, delta = 24, end = 24*20, outvars = "CENT, PERIPH")
+mod <- update(mod, delta = 24, end = 24*20, outvars = "CENT, RESP")
 ```
 
 And simulate that out