From 30f55769fe2f042c7753144051dd34eec3596adc Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 18 Nov 2016 16:48:21 +0100 Subject: Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE) Again with the jranke branch of jranke/pkgdown --- docs/articles/compiled_models.html | 57 +++++++++++++++++++++++--------------- 1 file changed, 35 insertions(+), 22 deletions(-) (limited to 'docs/articles/compiled_models.html') diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html index ce149bc5..31340867 100644 --- a/docs/articles/compiled_models.html +++ b/docs/articles/compiled_models.html @@ -16,14 +16,27 @@ 
## Unit: milliseconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 6341.1795 6363.5977 6373.7748 6386.0158 6390.0724
-##       Eigenvalue based  907.1699  908.8498  921.8335  910.5297  929.1653
-##      deSolve, compiled  747.5311  752.3718  754.2086  757.2125  757.5474
+##  deSolve, not compiled 6559.0772 6574.0500 6642.0659 6589.0229 6683.5603
+##       Eigenvalue based  921.0723  931.1284  940.3973  941.1845  950.0598
+##      deSolve, compiled  736.6534  741.6706  756.3600  746.6878  766.2132
 ##        max neval cld
-##  6394.1290     3   c
-##   947.8008     3  b 
-##   757.8823     3 a
+## 6778.0978 3 c +## 958.9351 3 b +## 785.7386 3 a 
autoplot(mb.1)

-

We see that using the compiled model is by a factor of 8.4 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 8.8 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:

rownames(smb.1) <- smb.1$expr
 smb.1["median"]/smb.1["deSolve, compiled", "median"]
##                         median
-## deSolve, not compiled 8.433585
-## Eigenvalue based      1.202476
+## deSolve, not compiled 8.824334
+## Eigenvalue based      1.260479
 ## deSolve, compiled     1.000000
@@ -113,19 +126,19 @@ smb.1["median"]/smb
smb.2 <- summary(mb.2)
 print(mb.2)
## Unit: seconds
-##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 13.214250 13.248908 13.384577 13.283565 13.469740
-##      deSolve, compiled  1.303868  1.307484  1.332879  1.311099  1.347384
+##                   expr       min        lq      mean   median        uq
+##  deSolve, not compiled 13.587184 13.616178 13.673277 13.64517 13.716324
+##      deSolve, compiled  1.307508  1.317114  1.337594  1.32672  1.352637
 ##        max neval cld
-##  13.655915     3   b
-##   1.383669     3  a
+## 13.787476 3 b +## 1.378553 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 10.1 using the version of the differential equation model compiled from C code!

+

Here we get a performance benefit of a factor of 10.3 using the version of the differential equation model compiled from C code!

This vignette was built with mkin 0.9.44.9000 on

## R version 3.3.2 (2016-10-31)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
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