From 556598ba543cf655cdc0a6995cc579327f9540ad Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 9 Dec 2015 10:20:50 +0100 Subject: Static documentation rebuilt by staticdocs::build_site() --- inst/web/vignettes/FOCUS_D.html | 4 ++-- inst/web/vignettes/FOCUS_L.html | 4 ++-- inst/web/vignettes/FOCUS_Z.pdf | Bin 224838 -> 224828 bytes inst/web/vignettes/compiled_models.html | 38 ++++++++++++++++---------------- inst/web/vignettes/mkin.pdf | Bin 160269 -> 160263 bytes 5 files changed, 23 insertions(+), 23 deletions(-) (limited to 'inst/web/vignettes') diff --git a/inst/web/vignettes/FOCUS_D.html b/inst/web/vignettes/FOCUS_D.html index d9fc6e18..076ab4c5 100644 --- a/inst/web/vignettes/FOCUS_D.html +++ b/inst/web/vignettes/FOCUS_D.html @@ -10,7 +10,7 @@ - + Example evaluation of FOCUS Example Dataset D @@ -64,7 +64,7 @@ img { diff --git a/inst/web/vignettes/FOCUS_L.html b/inst/web/vignettes/FOCUS_L.html index 9584aee5..9797e2f1 100644 --- a/inst/web/vignettes/FOCUS_L.html +++ b/inst/web/vignettes/FOCUS_L.html @@ -10,7 +10,7 @@ - + Example evaluation of FOCUS Laboratory Data L1 to L3 @@ -65,7 +65,7 @@ img {
diff --git a/inst/web/vignettes/FOCUS_Z.pdf b/inst/web/vignettes/FOCUS_Z.pdf index 1d08173a..ba30cb0c 100644 Binary files a/inst/web/vignettes/FOCUS_Z.pdf and b/inst/web/vignettes/FOCUS_Z.pdf differ diff --git a/inst/web/vignettes/compiled_models.html b/inst/web/vignettes/compiled_models.html index c7f4fbea..bd39ae2d 100644 --- a/inst/web/vignettes/compiled_models.html +++ b/inst/web/vignettes/compiled_models.html @@ -10,7 +10,7 @@ - + Performance benefit by using compiled model definitions in mkin @@ -65,7 +65,7 @@ img {
@@ -104,21 +104,21 @@ smb.1 <- summary(mb.1) print(mb.1) 
## Unit: milliseconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 9538.4007 9570.3211 9605.6503 9602.2416 9639.2752
-##       Eigenvalue based  881.9438  885.9337  901.1558  889.9236  910.7618
-##      deSolve, compiled  692.0913  695.6109  697.9629  699.1304  700.8987
+##  deSolve, not compiled 9508.4631 9522.5843 9634.9196 9536.7055 9698.1479
+##       Eigenvalue based  872.6560  877.4544  888.3598  882.2527  896.2117
+##      deSolve, compiled  698.8148  700.5031  708.8625  702.1914  713.8864
 ##        max neval cld
-##  9676.3087     3   c
-##   931.5999     3  b 
-##   702.6669     3 a
+## 9859.5902 3 b +## 910.1707 3 a +## 725.5815 3 a 
autoplot(mb.1)
-

-

We see that using the compiled model is by a factor of 13.7 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 13.6 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 13.734549
-## Eigenvalue based       1.272901
+## deSolve, not compiled 13.581348
+## Eigenvalue based       1.256428
 ## deSolve, compiled      1.000000
@@ -136,19 +136,19 @@ 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 20.475764 20.494740 20.507391 20.513716 20.523205
-##      deSolve, compiled  1.244022  1.244327  1.261983  1.244631  1.270963
+##                   expr       min        lq      mean    median       uq
+##  deSolve, not compiled 21.324080 21.368031 21.460777 21.411981 21.52913
+##      deSolve, compiled  1.376772  1.414208  1.461651  1.451643  1.50409
 ##        max neval cld
-##  20.532695     3   b
-##   1.297295     3  a
+## 21.646269 3 b +## 1.556538 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 16.5 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 14.8 using the version of the differential equation model compiled from C code using the inline package!

This vignette was built with mkin 0.9.41.9000 on

## R version 3.2.2 (2015-08-14)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
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