diff --git a/articles/Integrating-User-Defined-Functions-into-rxode2.html b/articles/Integrating-User-Defined-Functions-into-rxode2.html index 648ddca30..c40e2ea86 100644 --- a/articles/Integrating-User-Defined-Functions-into-rxode2.html +++ b/articles/Integrating-User-Defined-Functions-into-rxode2.html @@ -250,8 +250,8 @@

R based user functionsprint(mb) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> withoutC 7.754378 8.111007 8.768889 8.302625 8.536936 14.293111 100 -#> withC 2.065438 2.156628 2.514262 2.288734 2.795845 6.822972 100 +#> withoutC 7.700982 7.783596 8.392695 7.881032 8.027655 13.621363 100 +#> withC 2.101960 2.155324 2.819911 2.776638 3.191577 9.593712 100

The C version is almost twice as fast as the R version. You may have noticed the conversion also created C versions of the first derivative. This is done automatically and gives not just C versions of function, diff --git a/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/benmchmark1-1.png b/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/benmchmark1-1.png index 61a9937a7..c5cc6c114 100644 Binary files a/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/benmchmark1-1.png and b/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/benmchmark1-1.png differ diff --git a/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/convertC-1.png b/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/convertC-1.png index 6dd77880c..8746d40d0 100644 Binary files a/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/convertC-1.png and b/articles/Integrating-User-Defined-Functions-into-rxode2_files/figure-html/convertC-1.png differ diff --git a/articles/Modifying-Models.html b/articles/Modifying-Models.html index 51cfb6849..7427b9223 100644 --- a/articles/Modifying-Models.html +++ b/articles/Modifying-Models.html @@ -1418,7 +1418,7 @@

Creating more comple #> cp <- center/v #> }) #> } -#> <environment: 0x556f93bd3b80> +#> <environment: 0x55f49c636d78>

Note that these functions do not modify the ini({}) block. You may have to modify the ini block first to make it a valid rxode2/nlmixr2 model.

diff --git a/articles/rxode2-cmt.html b/articles/rxode2-cmt.html index 69866859c..ed13680f4 100644 --- a/articles/rxode2-cmt.html +++ b/articles/rxode2-cmt.html @@ -158,7 +158,7 @@

Advanced Features, Model Types, Techni

Changing rxode2 compartment numbers

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-cmt.Rmd
rxode2-cmt.Rmd
@@ -381,8 +381,8 @@

How rxode2 assigns compartment n 
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
 summary(pbpk)
-
#> rxode2 2.1.1.9000 model named rx_45cececb1f44bc6825377e86555bf32a model (ready). 
-#> DLL: /tmp/RtmpQvsiAp/rxode2/rx_45cececb1f44bc6825377e86555bf32a__.rxd/rx_45cececb1f44bc6825377e86555bf32a_.so
+
#> rxode2 2.1.1.9000 model named rx_888e3ca6bf91062251a0666640a91082 model (ready). 
+#> DLL: /tmp/RtmpVdj7Cq/rxode2/rx_888e3ca6bf91062251a0666640a91082__.rxd/rx_888e3ca6bf91062251a0666640a91082_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -732,7 +732,7 @@ 
Appending compartments to the model
 
 ode.1c.ka$simulationModel

 
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’

-
#> rxode2 2.1.1.9000 model named rx_3c2c707bde58bb58ac7dd2fb5996f24e model (ready). 
+
#> rxode2 2.1.1.9000 model named rx_155ca4092dddb690ae2ee099e46ed405 model (ready). 
 #> x$state: depot, center
 #> x$stateExtra: eff
 #> x$params: V, KA, CL
diff --git a/articles/rxode2-covariates.html b/articles/rxode2-covariates.html
index 97d129071..efd67a70e 100644
--- a/articles/rxode2-covariates.html
+++ b/articles/rxode2-covariates.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Covariates

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-covariates.Rmd
       
rxode2-covariates.Rmd

diff --git a/articles/rxode2-data-frame.html b/articles/rxode2-data-frame.html
index 4da1dcdf8..cec9e4b81 100644
--- a/articles/rxode2-data-frame.html
+++ b/articles/rxode2-data-frame.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Data Frames

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-data-frame.Rmd
       
rxode2-data-frame.Rmd

diff --git a/articles/rxode2-datasets.html b/articles/rxode2-datasets.html
index 443f4dc2c..d21dd8b4e 100644
--- a/articles/rxode2-datasets.html
+++ b/articles/rxode2-datasets.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Event Types

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-datasets.Rmd
       
rxode2-datasets.Rmd

diff --git a/articles/rxode2-event-table.html b/articles/rxode2-event-table.html
index 0ed76ab13..4411f4d04 100644
--- a/articles/rxode2-event-table.html
+++ b/articles/rxode2-event-table.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
Easy rxode2 Event Tables

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-event-table.Rmd
       
rxode2-event-table.Rmd

diff --git a/articles/rxode2-event-types.html b/articles/rxode2-event-types.html
index fed1a2e76..48e10dc65 100644
--- a/articles/rxode2-event-types.html
+++ b/articles/rxode2-event-types.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Event Types

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-event-types.Rmd
       
rxode2-event-types.Rmd

diff --git a/articles/rxode2-events-classic.html b/articles/rxode2-events-classic.html
index d605a6f18..a9c20453f 100644
--- a/articles/rxode2-events-classic.html
+++ b/articles/rxode2-events-classic.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
Classic rxode2 Events

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-events-classic.Rmd
       
rxode2-events-classic.Rmd

diff --git a/articles/rxode2-intro.html b/articles/rxode2-intro.html
index 2cd49edb8..b91a3649e 100644
--- a/articles/rxode2-intro.html
+++ b/articles/rxode2-intro.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
Introduction to rxode2

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-intro.Rmd
       
rxode2-intro.Rmd

diff --git a/articles/rxode2-model-types.html b/articles/rxode2-model-types.html
index 4d1ff19d0..5bf5d26de 100644
--- a/articles/rxode2-model-types.html
+++ b/articles/rxode2-model-types.html
@@ -163,7 +163,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 additional model types

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-model-types.Rmd
       
rxode2-model-types.Rmd

@@ -238,18 +238,18 @@ 
Solved compartment modelsVC or V),
 Peripheral/Tissue (VP, VT). While more
 translations are available, some example translations are below:

-

-
Another popular parameterization is in terms of micro-constants.
+

+
Another popular parameterization is in terms of micro-constants.
 rxode2 assumes compartment 1 is the central compartment.
 The elimination constant would be specified by K,
 Ke or Kel. Some example translations are
 below:

-

-
The last parameterization possible is using alpha and
+

+
The last parameterization possible is using alpha and
 V and/or A/B/C. Some
 example translations are below:

-

-
Once the linCmt() sleuthing is complete, the
+

+
Once the linCmt() sleuthing is complete, the
 1, 2 or 3 compartment model
 solution is used as the value of linCmt().

 
The compartments where you can dose in a linear solved system are
diff --git a/articles/rxode2-nesting.html b/articles/rxode2-nesting.html
index 8baf1307b..6b027bb80 100644
--- a/articles/rxode2-nesting.html
+++ b/articles/rxode2-nesting.html
@@ -158,7 +158,7 @@ 
Advanced Features, Model Types, Techni
   

       
Nesting levels in rxode2

             
-            
2024-01-23

+            
2024-01-30

       
       Source: vignettes/rxode2-nesting.Rmd
       
rxode2-nesting.Rmd

@@ -313,24 +313,24 @@ 
Uncertainty in Model parametersdimnames(tMat) <- list(names(theta), names(theta))
 
 tMat

-
#>               TKA          TCl           V2           Q          V3         Kin
-#> TKA   0.097505124 -0.062632381  0.002185946 -0.05914820 -0.03199291  0.05191104
-#> TCl  -0.062632381  0.143171198 -0.008142099  0.05343880 -0.05722191  0.02899693
-#> V2    0.002185946 -0.008142099  0.154042336 -0.02971687  0.05260648 -0.01051195
-#> Q    -0.059148203  0.053438800 -0.029716875  0.22633127 -0.03319782 -0.02766129
-#> V3   -0.031992913 -0.057221913  0.052606476 -0.03319782  0.13971052 -0.05199069
-#> Kin   0.051911038  0.028996932 -0.010511954 -0.02766129 -0.05199069  0.07440267
-#> Kout  0.002767053 -0.029273941  0.027177995  0.05301177 -0.01928564 -0.01900449
-#> EC50  0.042999966  0.029589661  0.025228785 -0.02581527 -0.06561574  0.05785742
-#>              Kout        EC50
-#> TKA   0.002767053  0.04299997
-#> TCl  -0.029273941  0.02958966
-#> V2    0.027177995  0.02522879
-#> Q     0.053011769 -0.02581527
-#> V3   -0.019285641 -0.06561574
-#> Kin  -0.019004494  0.05785742
-#> Kout  0.084064882  0.01531464
-#> EC50  0.015314645  0.07068059
+
#>               TKA          TCl          V2            Q           V3
+#> TKA   0.126848583 -0.032826578 -0.01782012  0.073985411  0.059556312
+#> TCl  -0.032826578  0.151271663  0.03931559 -0.051646177 -0.007039095
+#> V2   -0.017820116  0.039315589  0.12984576 -0.020526430 -0.020795502
+#> Q     0.073985411 -0.051646177 -0.02052643  0.117838807  0.038811836
+#> V3    0.059556312 -0.007039095 -0.02079550  0.038811836  0.143854965
+#> Kin   0.045394641 -0.081603448 -0.09260154  0.041152976  0.040346612
+#> Kout  0.000167824  0.003345854  0.05728777  0.001139339  0.049801997
+#> EC50 -0.027327195 -0.038015655 -0.07461475 -0.001034485 -0.001467119
+#>               Kin         Kout         EC50
+#> TKA   0.045394641  0.000167824 -0.027327195
+#> TCl  -0.081603448  0.003345854 -0.038015655
+#> V2   -0.092601542  0.057287774 -0.074614754
+#> Q     0.041152976  0.001139339 -0.001034485
+#> V3    0.040346612  0.049801997 -0.001467119
+#> Kin   0.164699412  0.005776729  0.058097097
+#> Kout  0.005776729  0.093264071 -0.020050191
+#> EC50  0.058097097 -0.020050191  0.066070112

Nesting Variability @@ -408,16 +408,16 @@

Solving the problem#> # A tibble: 8,000 x 24 #> sim.id id `inv.Cl(inv==1)` `inv.Cl(inv==2)` `inv.Ka(inv==1)` #> <int> <fct> <dbl> <dbl> <dbl> -#> 1 1 1 0.0561 0.00268 0.0989 -#> 2 1 2 0.0561 0.00268 0.0989 -#> 3 1 3 0.0561 0.00268 0.0989 -#> 4 1 4 0.0561 0.00268 0.0989 -#> 5 1 5 0.0561 0.00268 0.0989 -#> 6 1 6 0.0561 0.00268 0.0989 -#> 7 1 7 0.0561 0.00268 0.0989 -#> 8 1 8 0.0561 0.00268 0.0989 -#> 9 1 9 0.0561 0.00268 0.0989 -#> 10 1 10 0.0561 0.00268 0.0989 +#> 1 1 1 -0.122 0.155 -0.132 +#> 2 1 2 -0.122 0.155 -0.132 +#> 3 1 3 -0.122 0.155 -0.132 +#> 4 1 4 -0.122 0.155 -0.132 +#> 5 1 5 -0.122 0.155 -0.132 +#> 6 1 6 -0.122 0.155 -0.132 +#> 7 1 7 -0.122 0.155 -0.132 +#> 8 1 8 -0.122 0.155 -0.132 +#> 9 1 9 -0.122 0.155 -0.132 +#> 10 1 10 -0.122 0.155 -0.132 #> # i 7,990 more rows #> # i 19 more variables: `inv.Ka(inv==2)` <dbl>, `eye.Cl(eye==1)` <dbl>, #> # `eye.Cl(eye==2)` <dbl>, `eye.Ka(eye==1)` <dbl>, `eye.Ka(eye==2)` <dbl>, @@ -434,14 +434,14 @@

Solving the problem#> #> -- First part of data (object): -- #> # A tibble: 976,000 x 21 -#> sim.id id time inv.Cl inv.Ka eye.Cl eye.Ka iov.Cl iov.Ka C2 C3 -#> <int> <int> [h] <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 1 0 0.0561 0.0989 -0.369 0.216 0.0635 -0.0104 0 0 -#> 2 1 1 0.1 0.0561 0.0989 0.339 0.195 0.0635 -0.0104 -0.671 -0.00418 -#> 3 1 1 4 0.0561 0.0989 -0.369 0.216 0.0635 -0.0104 -11.2 -2.33 -#> 4 1 1 4.1 0.0561 0.0989 0.339 0.195 0.0635 -0.0104 -27.5 -2.41 -#> 5 1 1 8 0.0561 0.0989 -0.369 0.216 0.0635 -0.0104 -44.1 -6.06 -#> 6 1 1 8.1 0.0561 0.0989 0.339 0.195 0.0635 -0.0104 -16.4 -6.17 +#> sim.id id time inv.Cl inv.Ka eye.Cl eye.Ka iov.Cl iov.Ka C2 C3 +#> <int> <int> [h] <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 1 0 -0.122 -0.132 0.178 0.202 0.140 -0.114 0 0 +#> 2 1 1 0.1 -0.122 -0.132 0.0179 0.590 0.140 -0.114 21.4 0.0308 +#> 3 1 1 4 -0.122 -0.132 0.178 0.202 0.140 -0.114 27.4 8.06 +#> 4 1 1 4.1 -0.122 -0.132 0.0179 0.590 0.140 -0.114 16.5 8.11 +#> 5 1 1 8 -0.122 -0.132 0.178 0.202 0.140 -0.114 5.53 8.05 +#> 6 1 1 8.1 -0.122 -0.132 0.0179 0.590 0.140 -0.114 2.26 8.03 #> # i 975,994 more rows #> # i 10 more variables: CL <dbl>, KA <dbl>, ef0 <dbl>, depot <dbl>, centr <dbl>, #> # peri <dbl>, eff <dbl>, occ <fct>, eye <fct>, inv <fct> @@ -463,63 +463,63 @@

Solving the problem
 print(head(s$params))

#>   sim.id id inv.Cl(inv==1) inv.Cl(inv==2) inv.Ka(inv==1) inv.Ka(inv==2)
-#> 1      1  1     0.05613725    0.002676121     0.09886939     -0.1145422
-#> 2      1  2     0.05613725    0.002676121     0.09886939     -0.1145422
-#> 3      1  3     0.05613725    0.002676121     0.09886939     -0.1145422
-#> 4      1  4     0.05613725    0.002676121     0.09886939     -0.1145422
-#> 5      1  5     0.05613725    0.002676121     0.09886939     -0.1145422
-#> 6      1  6     0.05613725    0.002676121     0.09886939     -0.1145422
+#> 1      1  1     -0.1215069      0.1545973     -0.1315419     0.04715879
+#> 2      1  2     -0.1215069      0.1545973     -0.1315419     0.04715879
+#> 3      1  3     -0.1215069      0.1545973     -0.1315419     0.04715879
+#> 4      1  4     -0.1215069      0.1545973     -0.1315419     0.04715879
+#> 5      1  5     -0.1215069      0.1545973     -0.1315419     0.04715879
+#> 6      1  6     -0.1215069      0.1545973     -0.1315419     0.04715879
 #>   eye.Cl(eye==1) eye.Cl(eye==2) eye.Ka(eye==1) eye.Ka(eye==2) iov.Cl(occ==1)
-#> 1    -0.36889783     0.33918164      0.2162948     0.19535253     0.06345274
-#> 2    -0.14895018     0.07424926      0.1097794     0.15293130     0.05229912
-#> 3    -0.15606853     0.11696081     -0.1158629     0.07757864     0.02750855
-#> 4     0.01562668    -0.19437159      0.3422191    -0.19985282     0.07953385
-#> 5     0.06257184    -0.37364710     -0.3959396    -0.01406317     0.03389101
-#> 6     0.07229385     0.43743875     -0.3090004     0.24403413     0.04431553
+#> 1     0.17768102     0.01792468     0.20248907     0.59034041     0.14004312
+#> 2     0.06489535     0.29199480     0.29632489     0.21877654     0.11411853
+#> 3     0.26209113     0.24908804     0.02238583     0.19128359    -0.03635801
+#> 4    -0.05790927     0.11175879     0.29045175     0.10784750    -0.11147278
+#> 5     0.11253973    -0.54106107     0.12217645    -0.06972935     0.11371664
+#> 6    -0.12160938     0.21721757     0.16076583     0.19466692     0.14876658
 #>   iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2)       V2       V3      TCl
-#> 1    0.079961183    -0.01035850     0.05980327 40.18099 296.9346 19.00838
-#> 2    0.144455837    -0.02503950    -0.05779184 40.18099 296.9346 19.00838
-#> 3    0.009428645     0.21422583     0.04698294 40.18099 296.9346 19.00838
-#> 4   -0.064550794    -0.11564902    -0.05483477 40.18099 296.9346 19.00838
-#> 5   -0.006710996    -0.15198013     0.04304332 40.18099 296.9346 19.00838
-#> 6    0.014598965    -0.06497242    -0.02679635 40.18099 296.9346 19.00838
-#>         eta.Cl        TKA      eta.Ka        Q       Kin     Kout     EC50
-#> 1  0.325220393 -0.1308913 -0.70691415 10.82697 0.8761277 1.110527 199.9781
-#> 2 -0.239072540 -0.1308913  0.09798957 10.82697 0.8761277 1.110527 199.9781
-#> 3 -0.365966014 -0.1308913 -0.22095613 10.82697 0.8761277 1.110527 199.9781
-#> 4 -0.385975216 -0.1308913  0.43595833 10.82697 0.8761277 1.110527 199.9781
-#> 5 -0.494204338 -0.1308913 -0.43747789 10.82697 0.8761277 1.110527 199.9781
-#> 6 -0.005687513 -0.1308913  0.18786647 10.82697 0.8761277 1.110527 199.9781
+#> 1 0.006036892 -0.114443871 0.12691051 39.87968 297.0515 18.18964 +#> 2 -0.045177500 0.088364808 -0.05786029 39.87968 297.0515 18.18964 +#> 3 -0.071183712 0.055763391 0.05496106 39.87968 297.0515 18.18964 +#> 4 -0.008961117 -0.001915763 -0.12189986 39.87968 297.0515 18.18964 +#> 5 -0.044598387 -0.015648688 0.03349536 39.87968 297.0515 18.18964 +#> 6 0.082074695 0.088764338 -0.04455202 39.87968 297.0515 18.18964 +#> eta.Cl TKA eta.Ka Q Kin Kout EC50 +#> 1 0.346512208 0.5115992 0.15779437 10.4914 1.230806 0.550272 200.0012 +#> 2 -0.429153012 0.5115992 -0.06162353 10.4914 1.230806 0.550272 200.0012 +#> 3 -0.594006469 0.5115992 0.41790229 10.4914 1.230806 0.550272 200.0012 +#> 4 -0.017669131 0.5115992 -0.21379448 10.4914 1.230806 0.550272 200.0012 +#> 5 0.005789727 0.5115992 0.02455379 10.4914 1.230806 0.550272 200.0012 +#> 6 -0.244988767 0.5115992 -0.34299309 10.4914 1.230806 0.550272 200.0012 
 print(head(s$params %>% filter(sim.id == 2)))
#>   sim.id id inv.Cl(inv==1) inv.Cl(inv==2) inv.Ka(inv==1) inv.Ka(inv==2)
-#> 1      2  1      0.3716316      0.1462637      0.2201585     -0.1795746
-#> 2      2  2      0.3716316      0.1462637      0.2201585     -0.1795746
-#> 3      2  3      0.3716316      0.1462637      0.2201585     -0.1795746
-#> 4      2  4      0.3716316      0.1462637      0.2201585     -0.1795746
-#> 5      2  5      0.3716316      0.1462637      0.2201585     -0.1795746
-#> 6      2  6      0.3716316      0.1462637      0.2201585     -0.1795746
+#> 1      2  1    -0.01057313     -0.2681566      0.1124571     -0.1934464
+#> 2      2  2    -0.01057313     -0.2681566      0.1124571     -0.1934464
+#> 3      2  3    -0.01057313     -0.2681566      0.1124571     -0.1934464
+#> 4      2  4    -0.01057313     -0.2681566      0.1124571     -0.1934464
+#> 5      2  5    -0.01057313     -0.2681566      0.1124571     -0.1934464
+#> 6      2  6    -0.01057313     -0.2681566      0.1124571     -0.1934464
 #>   eye.Cl(eye==1) eye.Cl(eye==2) eye.Ka(eye==1) eye.Ka(eye==2) iov.Cl(occ==1)
-#> 1     0.16696543    0.070457235     0.04083151      0.2307054     0.05856952
-#> 2     0.11722824   -0.017176892    -0.04952944     -0.2212587     0.08642440
-#> 3     0.02993742   -0.042805106     0.01951154     -0.3526755     0.22378102
-#> 4    -0.04845361   -0.071353576    -0.19917086     -0.7232118     0.08176182
-#> 5    -0.47189049   -0.009489383     0.07986463      0.2155951    -0.11265072
-#> 6    -0.30771112   -0.270450225     0.14291960     -0.1234880    -0.13191721
-#>   iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2)       V2       V3     TCl
-#> 1     0.11407708   -0.025806967    0.096592475 39.76595 296.7083 18.6806
-#> 2     0.03995586   -0.030545407   -0.064031061 39.76595 296.7083 18.6806
-#> 3    -0.05760596    0.040064339   -0.132986456 39.76595 296.7083 18.6806
-#> 4     0.10317142   -0.023111088    0.073936889 39.76595 296.7083 18.6806
-#> 5     0.03014249   -0.009342765    0.078688405 39.76595 296.7083 18.6806
-#> 6     0.03136129    0.038632834    0.007001786 39.76595 296.7083 18.6806
-#>       eta.Cl       TKA     eta.Ka        Q       Kin    Kout    EC50
-#> 1 -0.1793494 -0.145803  0.2898582 10.44525 0.5898876 1.22986 199.855
-#> 2  0.5037215 -0.145803 -0.4326681 10.44525 0.5898876 1.22986 199.855
-#> 3  0.2406049 -0.145803 -0.1300759 10.44525 0.5898876 1.22986 199.855
-#> 4 -0.2885122 -0.145803 -0.8424224 10.44525 0.5898876 1.22986 199.855
-#> 5 -0.4313984 -0.145803  0.1490218 10.44525 0.5898876 1.22986 199.855
-#> 6  0.3886682 -0.145803  0.2832276 10.44525 0.5898876 1.22986 199.855
+#> 1 0.188192979 0.15446999 0.06496711 -0.0363898042 0.12166973 +#> 2 0.238059374 -0.15031874 -0.05673069 -0.0380056984 0.03976102 +#> 3 -0.009181288 0.27973679 -0.09273052 0.0008831785 -0.06182943 +#> 4 0.127782122 -0.25292487 -0.28648116 -0.2964420340 0.04841083 +#> 5 0.069248352 0.01308512 0.27893736 0.0179776517 -0.05728655 +#> 6 0.185834266 -0.34968461 -0.21868525 0.1113316292 0.30223133 +#> iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2) V2 V3 TCl +#> 1 0.03663079 -0.11113535 0.03930488 40.30603 297.3599 18.67602 +#> 2 -0.06971917 0.04701878 -0.10809105 40.30603 297.3599 18.67602 +#> 3 -0.05006046 0.02070942 0.05511813 40.30603 297.3599 18.67602 +#> 4 -0.14295695 -0.13590835 -0.11438424 40.30603 297.3599 18.67602 +#> 5 0.01508066 0.04698955 -0.09478923 40.30603 297.3599 18.67602 +#> 6 0.14507034 0.12851272 0.06502513 40.30603 297.3599 18.67602 +#> eta.Cl TKA eta.Ka Q Kin Kout EC50 +#> 1 -0.43592595 0.4782224 0.09977002 10.54849 1.471684 1.390875 199.8732 +#> 2 -0.30435078 0.4782224 -0.16682736 10.54849 1.471684 1.390875 199.8732 +#> 3 0.09160909 0.4782224 0.05367372 10.54849 1.471684 1.390875 199.8732 +#> 4 0.36520870 0.4782224 0.10092741 10.54849 1.471684 1.390875 199.8732 +#> 5 0.42367115 0.4782224 -0.01304600 10.54849 1.471684 1.390875 199.8732 +#> 6 -0.49519424 0.4782224 0.03113892 10.54849 1.471684 1.390875 199.8732

For between eye variability and between occasion variability each individual simulates a number of variables that become the between eye and between occasion variability; In the case of the eye:

diff --git a/articles/rxode2-pipeline.html b/articles/rxode2-pipeline.html index 1f288c049..3c7ffc3c7 100644 --- a/articles/rxode2-pipeline.html +++ b/articles/rxode2-pipeline.html @@ -158,7 +158,7 @@
Advanced Features, Model Types, Techni

rxode2 in a pipeline

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-pipeline.Rmd
rxode2-pipeline.Rmd
diff --git a/articles/rxode2-plot.html b/articles/rxode2-plot.html index 05411e976..ccbafa63f 100644 --- a/articles/rxode2-plot.html +++ b/articles/rxode2-plot.html @@ -160,7 +160,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

-

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+

2024-01-30

Source: vignettes/rxode2-plot.Rmd
rxode2-plot.Rmd
diff --git a/articles/rxode2-plot_files/figure-html/unnamed-chunk-10-1.png b/articles/rxode2-plot_files/figure-html/unnamed-chunk-10-1.png index 39dbb8a9a..3e6b366c8 100644 Binary files a/articles/rxode2-plot_files/figure-html/unnamed-chunk-10-1.png and b/articles/rxode2-plot_files/figure-html/unnamed-chunk-10-1.png differ diff --git a/articles/rxode2-plot_files/figure-html/unnamed-chunk-6-1.png b/articles/rxode2-plot_files/figure-html/unnamed-chunk-6-1.png index b18bb4ee0..5c11f93e4 100644 Binary files a/articles/rxode2-plot_files/figure-html/unnamed-chunk-6-1.png and b/articles/rxode2-plot_files/figure-html/unnamed-chunk-6-1.png differ diff --git a/articles/rxode2-plot_files/figure-html/unnamed-chunk-7-1.png b/articles/rxode2-plot_files/figure-html/unnamed-chunk-7-1.png index 09ceec962..b35b93d21 100644 Binary files a/articles/rxode2-plot_files/figure-html/unnamed-chunk-7-1.png and b/articles/rxode2-plot_files/figure-html/unnamed-chunk-7-1.png differ diff --git a/articles/rxode2-plot_files/figure-html/unnamed-chunk-8-1.png b/articles/rxode2-plot_files/figure-html/unnamed-chunk-8-1.png index 510b6544c..6136ebc84 100644 Binary files a/articles/rxode2-plot_files/figure-html/unnamed-chunk-8-1.png and b/articles/rxode2-plot_files/figure-html/unnamed-chunk-8-1.png differ diff --git a/articles/rxode2-prior-data.html b/articles/rxode2-prior-data.html index 1ea74691b..c463d1bb3 100644 --- a/articles/rxode2-prior-data.html +++ b/articles/rxode2-prior-data.html @@ -158,7 +158,7 @@
Advanced Features, Model Types, Techni

Using Prior Data for ODE solving

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-prior-data.Rmd
rxode2-prior-data.Rmd
diff --git a/articles/rxode2-rxUse.html b/articles/rxode2-rxUse.html index c052658ad..9756d748c 100644 --- a/articles/rxode2-rxUse.html +++ b/articles/rxode2-rxUse.html @@ -160,7 +160,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-rxUse.Rmd
rxode2-rxUse.Rmd
diff --git a/articles/rxode2-shiny.html b/articles/rxode2-shiny.html index edc4b38f3..a8ad791c2 100644 --- a/articles/rxode2-shiny.html +++ b/articles/rxode2-shiny.html @@ -158,7 +158,7 @@
Advanced Features, Model Types, Techni

rxode2 and Shiny

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-shiny.Rmd
rxode2-shiny.Rmd
diff --git a/articles/rxode2-sim-var.html b/articles/rxode2-sim-var.html index 5103d89f3..0cea68fbe 100644 --- a/articles/rxode2-sim-var.html +++ b/articles/rxode2-sim-var.html @@ -158,7 +158,7 @@
Advanced Features, Model Types, Techni

rxode2 Simulation

-

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+

2024-01-30

Source: vignettes/rxode2-sim-var.Rmd
rxode2-sim-var.Rmd
diff --git a/articles/rxode2-single-subject.html b/articles/rxode2-single-subject.html index 073042231..1d9eb6b93 100644 --- a/articles/rxode2-single-subject.html +++ b/articles/rxode2-single-subject.html @@ -158,7 +158,7 @@
Advanced Features, Model Types, Techni

Single Subject ODE solving -- differences from multiple subject

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+

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Source: vignettes/rxode2-single-subject.Rmd
rxode2-single-subject.Rmd
diff --git a/articles/rxode2-speed.html b/articles/rxode2-speed.html index 77d61d96a..ee26fc8ff 100644 --- a/articles/rxode2-speed.html +++ b/articles/rxode2-speed.html @@ -160,7 +160,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

-

2024-01-23

+

2024-01-30

Source: vignettes/rxode2-speed.Rmd
rxode2-speed.Rmd
@@ -263,8 +263,8 @@

A note about t output. You can see the differences below:

 summary(mod1$simulationModel)
-#> rxode2 2.1.1.9000 model named rx_dde7adafaa5c6f5a2e1f34b01767a0af model (✔ ready). 
-#> DLL: /tmp/RtmpQvsiAp/rxode2/rx_dde7adafaa5c6f5a2e1f34b01767a0af__.rxd/rx_dde7adafaa5c6f5a2e1f34b01767a0af_.so
+#> rxode2 2.1.1.9000 model named rx_ec464bc9eace073a4527d87acadfddb4 model (✔ ready). 
+#> DLL: /tmp/RtmpVdj7Cq/rxode2/rx_ec464bc9eace073a4527d87acadfddb4__.rxd/rx_ec464bc9eace073a4527d87acadfddb4_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -282,8 +282,8 @@ 
A note about t
 #> })
 summary(mod1$simulationIniModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.1.1.9000 model named rx_e44e9ee38545b57dae62d04510ccab81 model (✔ ready). 
-#> DLL: /tmp/RtmpQvsiAp/rxode2/rx_e44e9ee38545b57dae62d04510ccab81__.rxd/rx_e44e9ee38545b57dae62d04510ccab81_.so
+#> rxode2 2.1.1.9000 model named rx_5a172c6836cda6d471133865d1613f08 model (✔ ready). 
+#> DLL: /tmp/RtmpVdj7Cq/rxode2/rx_5a172c6836cda6d471133865d1613f08__.rxd/rx_5a172c6836cda6d471133865d1613f08_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -309,8 +309,8 @@ 
A note about t
 #> })
 summary(mod2f$simulationModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.1.1.9000 model named rx_525381b0d2a180cfde7f4fecb32b3a45 model (✔ ready). 
-#> DLL: /tmp/RtmpQvsiAp/rxode2/rx_525381b0d2a180cfde7f4fecb32b3a45__.rxd/rx_525381b0d2a180cfde7f4fecb32b3a45_.so
+#> rxode2 2.1.1.9000 model named rx_d175dc97754e25b6601589d6579909e4 model (✔ ready). 
+#> DLL: /tmp/RtmpVdj7Cq/rxode2/rx_d175dc97754e25b6601589d6579909e4__.rxd/rx_d175dc97754e25b6601589d6579909e4_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -366,8 +366,8 @@ 
A note about t
 #> })
 summary(mod2f$simulationIniModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.1.1.9000 model named rx_1e1e825cbc5725fe5238d9a808269d13 model (✔ ready). 
-#> DLL: /tmp/RtmpQvsiAp/rxode2/rx_1e1e825cbc5725fe5238d9a808269d13__.rxd/rx_1e1e825cbc5725fe5238d9a808269d13_.so
+#> rxode2 2.1.1.9000 model named rx_1fa541ac46daeb5fc30a38552ebd1a28 model (✔ ready). 
+#> DLL: /tmp/RtmpVdj7Cq/rxode2/rx_1fa541ac46daeb5fc30a38552ebd1a28__.rxd/rx_1fa541ac46daeb5fc30a38552ebd1a28_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -553,10 +553,10 @@ 
Compare the times between all
 print(bench)
 #> Unit: milliseconds
 #>               expr       min        lq      mean    median        uq       max
-#>           runFor() 272.68192 279.27422 293.81865 283.77730 296.50623 431.60477
-#>        runSapply() 271.76756 279.56641 289.78392 281.80045 290.21712 399.43239
-#>  runSingleThread()  27.14962  27.43392  28.53953  27.65254  28.09581  46.61663
-#>       run2Thread()  16.18853  16.43165  17.36998  16.73554  17.11031  27.44037
+#>           runFor() 275.27445 282.72659 296.32924 285.36428 296.59053 421.94861
+#>        runSapply() 275.42242 282.27560 289.41330 284.19744 288.66425 340.32593
+#>  runSingleThread()  27.80331  28.08948  28.58767  28.33210  28.62940  34.20171
+#>       run2Thread()  16.46957  16.92515  18.70476  17.21281  17.81127  30.40426
 #>  neval
 #>    100
 #>    100
@@ -583,10 +583,10 @@ 
Compare the times between all
 print(bench)
 #> Unit: milliseconds
 #>          expr      min       lq     mean   median       uq      max neval
-#>  runThread(1) 27.13695 27.62539 28.89258 28.21513 28.89024 50.12725   100
-#>  runThread(2) 16.32435 16.75297 18.91421 17.30626 18.75373 29.18771   100
-#>  runThread(3) 17.49259 18.48256 19.99102 20.16053 20.75537 25.10859   100
-#>  runThread(4) 16.21415 16.76762 18.08898 17.12330 17.54657 37.09393   100
+#> runThread(1) 27.88072 28.08433 29.26498 28.41125 29.54402 48.86065 100 +#> runThread(2) 16.53631 16.85069 18.65513 17.31703 17.76293 32.22483 100 +#> runThread(3) 17.98543 19.65418 20.38128 20.00796 20.52825 26.88089 100 +#> runThread(4) 16.21520 16.54979 18.03119 17.11132 17.37072 36.57811 100

 autoplot(bench)

@@ -675,8 +675,8 @@

Increasing speed with compiler o print(bench) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> standardCompile 191.3855 300.3776 305.9900 301.8742 306.8112 354.7742 100 -#> fastCompile 193.4735 301.5670 307.5617 303.9288 309.4961 355.8324 100 +#> standardCompile 189.9879 310.2717 315.7530 312.1834 316.6587 372.8248 100 +#> fastCompile 194.8383 309.7847 316.1023 313.0658 319.1076 386.9029 100 autoplot(bench)

@@ -770,7 +770,7 @@

A real life exampleStoplapply <- Sys.time() print(Stoplapply - Startlapply) -#> Time difference of 11.60301 secs

+#> Time difference of 13.49471 secs

By applying some of the new parallel solving concepts you can simply run the same simulation both with less code and faster:

@@ -811,7 +811,7 @@ 
A real life exampleres <- rxSolve(rx, ev, omega=omega, returnType="data.table")
 endParallel <- Sys.time()
 print(endParallel - startParallel)
-#> Time difference of 0.104939 secs
+#> Time difference of 0.1269417 secs

You can see a striking time difference between the two methods; A few things to keep in mind: