Remove trailing whitespace, clean headers

Also ignore test.R in the top level directory, as it is not meant to
be public

1 files changed, 11 insertions, 11 deletions

diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd
index 9fd39d81..18e1a462 100644
--- a/vignettes/compiled_models.Rmd
+++ b/vignettes/compiled_models.Rmd
@@ -25,7 +25,7 @@ This evaluation is taken from the example section of mkinfit. When using an mkin
 equal to or greater than 0.9-36 and a C compiler (gcc) is available, you will see

 a message that the model is being compiled from autogenerated C code when

 defining a model using mkinmod. The `mkinmod()` function checks for presence of

-the gcc compiler using 

+the gcc compiler using

 

 ```{r check_gcc}

 Sys.which("gcc")

@@ -48,12 +48,12 @@ the microbenchmark package.
 library("microbenchmark")

 library("ggplot2")

 mb.1 <- microbenchmark(

-  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 

-                                    solution_type = "deSolve", 

+  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,

+                                    solution_type = "deSolve",

                                     use_compiled = FALSE, quiet = TRUE),

-  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D, 

+  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,

                                solution_type = "eigen", quiet = TRUE),

-  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 

+  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,

                                 solution_type = "deSolve", quiet = TRUE),

   times = 3, control = list(warmup = 0))

 

@@ -62,8 +62,8 @@ print(mb.1)
 autoplot(mb.1)

 ```

 

-We see that using the compiled model is by a factor of 

-`r round(smb.1[1, "median"]/smb.1[3, "median"], 1)` 

+We see that using the compiled model is by a factor of

+`r round(smb.1[1, "median"]/smb.1[3, "median"], 1)`

 faster than using the R version with the default ode solver, and it is even

 faster than the Eigenvalue based solution implemented in R which does not need

 iterative solution of the ODEs:

@@ -75,7 +75,7 @@ smb.1["median"]/smb.1["deSolve, compiled", "median"]
 

 ## Model that can not be solved with Eigenvalues

 

-This evaluation is also taken from the example section of mkinfit. 

+This evaluation is also taken from the example section of mkinfit.

 

 ```{r benchmark_FOMC_SFO, fig.height = 3}

 FOMC_SFO <- mkinmod(

@@ -83,7 +83,7 @@ FOMC_SFO <- mkinmod(
   m1 = mkinsub( "SFO"))

 

 mb.2 <- microbenchmark(

-  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, 

+  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,

                                     use_compiled = FALSE, quiet = TRUE),

   "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),

   times = 3, control = list(warmup = 0))

@@ -93,8 +93,8 @@ smb.2["median"]/smb.2["deSolve, compiled", "median"]
 autoplot(mb.2)

 ```

 

-Here we get a performance benefit of a factor of 

-`r round(smb.2[1, "median"]/smb.2[2, "median"], 1)` 

+Here we get a performance benefit of a factor of

+`r round(smb.2[1, "median"]/smb.2[2, "median"], 1)`

 using the version of the differential equation model compiled from C code!

 

 This vignette was built with mkin `r packageVersion("mkin")` on