From f3f415520c89f9d8526bf6fadc862ebd44be220d Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Thu, 17 Nov 2016 18:14:32 +0100
Subject: Remove trailing whitespace, clean headers

Also ignore test.R in the top level directory, as it is not meant to
be public
---
 vignettes/compiled_models.Rmd | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

(limited to 'vignettes/compiled_models.Rmd')

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
-- 
cgit v1.2.3

