From 5bd8716b2e4c880b798d1e5e231d49816bbdebd1 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Sun, 21 Jun 2015 18:16:08 +0200 Subject: Rebuild vignettes with the released package installed --- vignettes/compiled_models.Rmd | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) (limited to 'vignettes/compiled_models.Rmd') diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd index 5d83cf3a..3b24acbb 100644 --- a/vignettes/compiled_models.Rmd +++ b/vignettes/compiled_models.Rmd @@ -53,9 +53,11 @@ rownames(smb.1) <- c("deSolve, not compiled", "Eigenvalue based", "deSolve, comp print(smb.1) ``` -We see that using the compiled model is almost a factor of 8 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: +We see that using the compiled model is by a factor of +`r round(smb.1["deSolve, not compiled", "median"]/smb.1["deSolve, compiled", "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: ```{r} smb.1["median"]/smb.1["deSolve, compiled", "median"] @@ -81,5 +83,7 @@ smb.2["median"]/smb.2["deSolve, compiled", "median"] ``` -Here we get a performance benefit of more than a factor of 10 using the version -of the differential equation model compiled from C code using the inline package! +Here we get a performance benefit of a factor of +`r round(smb.2["deSolve, not compiled", "median"]/smb.2["deSolve, compiled", "median"], 1)` +using the version of the differential equation model compiled from C code using +the inline package! -- cgit v1.2.3