From a7600ca6d4e5dfa62a16102f5a965f5e9891cf28 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 28 Jun 2016 10:32:31 +0200 Subject: Bump version for new release, rebuild static docs The test test_FOMC_ill-defined leads to errors on several architectures/distributions, as apparent from CRAN checks, so we need a new release. Static documentation rebuilt by staticdocs::build_site() --- vignettes/compiled_models.html | 38 +++++++++++++++++++------------------- 1 file changed, 19 insertions(+), 19 deletions(-) (limited to 'vignettes/compiled_models.html') diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index cec76ef9..12289676 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -250,21 +250,21 @@ mb.1 <- microbenchmark( print(mb.1) 
## Unit: seconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 25.422123 25.889685 26.065978 26.357247 26.387905
-##       Eigenvalue based  2.243667  2.254539  2.277770  2.265412  2.294821
-##      deSolve, compiled  1.849468  1.865343  1.871339  1.881219  1.882274
-##       max neval cld
-##  26.41856     3   b
-##   2.32423     3  a 
-##   1.88333     3  a
+## deSolve, not compiled 25.120822 25.185794 25.345704 25.250766 25.458146 +## Eigenvalue based 2.246793 2.255533 2.258865 2.264274 2.264901 +## deSolve, compiled 1.861661 1.893380 1.930436 1.925098 1.964823 +## max neval cld +## 25.665525 3 b +## 2.265527 3 a +## 2.004547 3 a 
autoplot(mb.1)
-

-

We see that using the compiled model is by a factor of 14 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 13.1 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:

rownames(smb.1) <- smb.1$expr
 smb.1["median"]/smb.1["deSolve, compiled", "median"]
##                          median
-## deSolve, not compiled 14.010730
-## Eigenvalue based       1.204226
+## deSolve, not compiled 13.116611
+## Eigenvalue based       1.176186
 ## deSolve, compiled      1.000000
@@ -285,20 +285,20 @@ smb.1["median"]/smb.1["deSolve, compiled", "median" 
smb.2 <- summary(mb.2)
 print(mb.2)
## Unit: seconds
-##                   expr       min       lq      mean    median        uq
-##  deSolve, not compiled 54.386189 54.39423 54.477986 54.402271 54.523884
-##      deSolve, compiled  3.424205  3.53522  3.574587  3.646236  3.649778
+##                   expr       min        lq      mean    median        uq
+##  deSolve, not compiled 54.536624 54.617928 54.690830 54.699231 54.767933
+##      deSolve, compiled  3.690661  3.693247  3.720722  3.695833  3.735753
 ##        max neval cld
-##  54.645498     3   b
-##   3.653319     3  a
+## 54.836635 3 b +## 3.775673 3 a 
smb.2["median"]/smb.2["deSolve, compiled", "median"]
##   median
 ## 1     NA
 ## 2     NA
autoplot(mb.2)
-

-

Here we get a performance benefit of a factor of 14.9 using the version of the differential equation model compiled from C code!

-

This vignette was built with mkin 0.9.43.9000 on

+

+

Here we get a performance benefit of a factor of 14.8 using the version of the differential equation model compiled from C code!

+

This vignette was built with mkin 0.9.44 on

## R version 3.3.1 (2016-06-21)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 8 (jessie)
-- cgit v1.2.1