adding README

.Rbuildignore

@@ -5,3 +5,6 @@ Makefile
 ^vera_.*\.tar\.gz
 vera\.Rcheck
 \.Rhistory
+README.md
+README.Rmd
+README.html

.gitignore

@@ -1,4 +1,9 @@
+README.html
+vera.Rcheck
+test.R
+vera*.tar.gz
 .Rproj.user
 .Rhistory
 .RData
 .Ruserdata
+.DS_Store

R/vera.R

@@ -36,9 +36,10 @@ dvalue <- function(sim,ref,scale) {
 #' @param var output names (compartment or capture) as character vector
 #' or comma-separated string
 #' @param eps parameter change value for sensitivity analysis
+#' @param ... arguments passed to `fun`
 #'
 #' @export
-lsa <- function(mod, fun, par, var, eps=1E-8) {
+lsa <- function(mod, fun, par, var, eps=1E-8, ...) {
   parameters <- mrgsolve::param(mod)
   par_names <- names(parameters)
   par_sens <- cvec_cs(par)
@@ -53,7 +54,7 @@ lsa <- function(mod, fun, par, var, eps=1E-8) {
   }
   parm <- as.numeric(parameters)[par_sens]
   var <- cvec_cs(var)
-  base <- fun(parm)
+  base <- fun(parm,...)
   if(!all(var %in% names(base))) {
     col_bad <- setdiff(var,names(base))
     col_bad <- paste0(col_bad,collapse=',')
@@ -76,7 +77,7 @@ lsa <- function(mod, fun, par, var, eps=1E-8) {
   tosim <- lapply(seq_along(new_p), function(i) {
     base_par[i] <- new_p[i]
   })
-  out <- lapply(tosim,fun)
+  out <- lapply(tosim,fun,...)
   out <- lapply(out, function(x) x[,cols_keep])
   out <- lapply(out, make_long, cols = var)
   for(i in seq_along(tosim)) {

README.Rmd

@@ -0,0 +1,62 @@
+---
+title: "local sensitivity analysis with mrgsolve"
+output: github_document
+---
+
+```{r,setup,include=FALSE}
+knitr::opts_chunk$set(
+  comment = '.', message=FALSE, warning = FALSE, 
+  fig.path = "man/images/readme-"
+)
+```
+
+# Model
+Load the vera package and a model from the mrgsolve package.  We 
+increase the tolerance a bit as well as the maximum step size.
+```{r,message=FALSE}
+library(vera)
+
+mod <- modlib(
+  "pbpk", 
+  end = 12, delta = 0.1, 
+  atol = 1E-20, rtol = 1E-12, hmax=0.5
+)
+```
+
+# Scenario
+Create a function that uses the model to simulate a certain scenario.  For now, 
+we just simulate a single dose.
+```{r}
+fun <- function(p,dose) {
+  mod %>% 
+    param(p) %>% 
+    ev(dose) %>% 
+    mrgsim_df()
+}
+
+d <- ev(amt = 100)
+```
+
+# Sensitivity analysis
+
+Use `vera::lsa()`.  We pick the paramters that we want to fiddle with (`par`)
+and the output that we want to look at (`Cp` and `Amu` - the amount in the 
+muscle compartment).  `d` gets passed through to the function as `dose`. 
+```{r}
+out <- lsa(mod, fun, par = "Kpli,Kpmu,BW,Ka", var = "Cp,Amu", dose = d)
+```
+
+# Ouput
+
+The output is long and ready to send in to `ggplot2`.  
+```{r}
+head(out)
+```
+
+There is a default plotting method as well.
+
+```{r}
+plot(out)
+```
+
+

README.md

@@ -0,0 +1,68 @@
+local sensitivity analysis with mrgsolve
+================
+
+# Model
+
+Load the vera package and a model from the mrgsolve package. We increase
+the tolerance a bit as well as the maximum step size.
+
+``` r
+library(vera)
+
+mod <- modlib(
+  "pbpk", 
+  end = 12, delta = 0.1, 
+  atol = 1E-20, rtol = 1E-12, hmax=0.5
+)
+```
+
+# Scenario
+
+Create a function that uses the model to simulate a certain scenario.
+For now, we just simulate a single dose.
+
+``` r
+fun <- function(p,dose) {
+  mod %>% 
+    param(p) %>% 
+    ev(dose) %>% 
+    mrgsim_df()
+}
+
+d <- ev(amt = 100)
+```
+
+# Sensitivity analysis
+
+Use `vera::lsa()`. We pick the paramters that we want to fiddle with
+(`par`) and the output that we want to look at (`Cp` and `Amu` - the
+amount in the muscle compartment). `d` gets passed through to the
+function as `dose`.
+
+``` r
+out <- lsa(mod, fun, par = "Kpli,Kpmu,BW,Ka", var = "Cp,Amu", dose = d)
+```
+
+# Ouput
+
+The output is long and ready to send in to `ggplot2`.
+
+``` r
+head(out)
+```
+
+    .   time var    value  par       sens
+    . 1  0.0  Cp 0.000000 Kpli  0.0000000
+    . 2  0.0  Cp 0.000000 Kpli  0.0000000
+    . 3  0.1  Cp 0.913300 Kpli -0.2344372
+    . 4  0.2  Cp 1.240780 Kpli -0.2207772
+    . 5  0.3  Cp 1.425315 Kpli -0.2315567
+    . 6  0.4  Cp 1.546065 Kpli -0.2460310
+
+There is a default plotting method as well.
+
+``` r
+plot(out)
+```
+
+![](man/images/readme-unnamed-chunk-5-1.png)<!-- -->