diff --git a/articles/Integrating-User-Defined-Functions-into-rxode2.html b/articles/Integrating-User-Defined-Functions-into-rxode2.html index 9a51fc26b..81296ca54 100644 --- a/articles/Integrating-User-Defined-Functions-into-rxode2.html +++ b/articles/Integrating-User-Defined-Functions-into-rxode2.html @@ -249,8 +249,8 @@

R based user functionsprint(mb) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> withoutC 7.760670 7.850127 8.865908 7.943766 8.381508 18.791067 100 -#> withC 2.065371 2.116055 2.459296 2.209885 2.731708 7.061306 100 +#> withoutC 7.701525 7.813865 8.461994 7.918655 8.117391 13.764794 100 +#> withC 2.073338 2.119453 2.482253 2.237564 2.741033 6.938021 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 f04d3aee6..ad1388ed8 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 4b2824d56..2cf6f19c4 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/rxode2-cmt.html b/articles/rxode2-cmt.html index bbd33a9f6..5fdbca967 100644 --- a/articles/rxode2-cmt.html +++ b/articles/rxode2-cmt.html @@ -157,7 +157,7 @@

Advanced Features, Model Types, Techni

Changing rxode2 compartment numbers

-

2023-12-03

+

2023-12-05

Source: vignettes/rxode2-cmt.Rmd
rxode2-cmt.Rmd
@@ -380,8 +380,8 @@

How rxode2 assigns compartment n 
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
 summary(pbpk)
-
#> rxode2 2.0.14.9000 model named rx_a9ab0a308fe15e1ad382edd63f19620d model (ready). 
-#> DLL: /tmp/Rtmp5mYcCf/rxode2/rx_a9ab0a308fe15e1ad382edd63f19620d__.rxd/rx_a9ab0a308fe15e1ad382edd63f19620d_.so
+
#> rxode2 2.0.14.9000 model named rx_e83f7a9651e77506967130f7b1c210ca model (ready). 
+#> DLL: /tmp/RtmpE4aPra/rxode2/rx_e83f7a9651e77506967130f7b1c210ca__.rxd/rx_e83f7a9651e77506967130f7b1c210ca_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -731,7 +731,7 @@ 
Appending compartments to the model
 
 ode.1c.ka$simulationModel

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

-
#> rxode2 2.0.14.9000 model named rx_a34f770c8ba668b242ec15fd28a802d9 model (ready). 
+
#> rxode2 2.0.14.9000 model named rx_e282a6cb08725b6bc480b4e3d4df4b56 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 89b245b0b..1450b00e7 100644
--- a/articles/rxode2-covariates.html
+++ b/articles/rxode2-covariates.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Covariates

             
-            
2023-12-03

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

diff --git a/articles/rxode2-data-frame.html b/articles/rxode2-data-frame.html
index 73a97d5b2..76461fe5e 100644
--- a/articles/rxode2-data-frame.html
+++ b/articles/rxode2-data-frame.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Data Frames

             
-            
2023-12-03

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

diff --git a/articles/rxode2-datasets.html b/articles/rxode2-datasets.html
index b62ea742c..fe67d1ada 100644
--- a/articles/rxode2-datasets.html
+++ b/articles/rxode2-datasets.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Event Types

             
-            
2023-12-03

+            
2023-12-05

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

diff --git a/articles/rxode2-event-table.html b/articles/rxode2-event-table.html
index d1f676411..bc620b706 100644
--- a/articles/rxode2-event-table.html
+++ b/articles/rxode2-event-table.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
Easy rxode2 Event Tables

             
-            
2023-12-03

+            
2023-12-05

       
       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 29fc91536..3ed66b28f 100644
--- a/articles/rxode2-event-types.html
+++ b/articles/rxode2-event-types.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 Event Types

             
-            
2023-12-03

+            
2023-12-05

       
       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 b9a59accb..42176da80 100644
--- a/articles/rxode2-events-classic.html
+++ b/articles/rxode2-events-classic.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
Classic rxode2 Events

             
-            
2023-12-03

+            
2023-12-05

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

diff --git a/articles/rxode2-intro.html b/articles/rxode2-intro.html
index ff6fe94ff..9e55143d4 100644
--- a/articles/rxode2-intro.html
+++ b/articles/rxode2-intro.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
Introduction to rxode2

             
-            
2023-12-03

+            
2023-12-05

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

diff --git a/articles/rxode2-model-types.html b/articles/rxode2-model-types.html
index c6a45165e..0665d071e 100644
--- a/articles/rxode2-model-types.html
+++ b/articles/rxode2-model-types.html
@@ -162,7 +162,7 @@ 
Advanced Features, Model Types, Techni
   

       
rxode2 additional model types

             
-            
2023-12-03

+            
2023-12-05

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

@@ -237,18 +237,18 @@ 
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 bbf9ea12e..04181079c 100644
--- a/articles/rxode2-nesting.html
+++ b/articles/rxode2-nesting.html
@@ -157,7 +157,7 @@ 
Advanced Features, Model Types, Techni
   

       
Nesting levels in rxode2

             
-            
2023-12-03

+            
2023-12-05

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

@@ -312,24 +312,24 @@ 
Uncertainty in Model parametersdimnames(tMat) <- list(names(theta), names(theta))
 
 tMat

-
#>               TKA          TCl           V2            Q           V3
-#> TKA   0.091283564 -0.068572309 -0.021058603  0.051974567  0.035090728
-#> TCl  -0.068572309  0.159500450  0.021955940 -0.033815812  0.019583567
-#> V2   -0.021058603  0.021955940  0.038136753 -0.015179898  0.017702364
-#> Q     0.051974567 -0.033815812 -0.015179898  0.179281300  0.084678596
-#> V3    0.035090728  0.019583567  0.017702364  0.084678596  0.094222614
-#> Kin  -0.021023944  0.046353050  0.004554589 -0.052996743 -0.044415064
-#> Kout -0.007146270 -0.001840578  0.012059396 -0.006507225 -0.004639813
-#> EC50  0.001406257 -0.055571475  0.003785865  0.032559017 -0.019434394
+
#>              TKA          TCl           V2            Q          V3
+#> TKA   0.11351272 -0.046152020  0.027935822  0.022304492 -0.01180844
+#> TCl  -0.04615202  0.058314039 -0.020962093 -0.002400837 -0.03939416
+#> V2    0.02793582 -0.020962093  0.040095192 -0.032248068 -0.02460253
+#> Q     0.02230449 -0.002400837 -0.032248068  0.100788522  0.02896160
+#> V3   -0.01180844 -0.039394160 -0.024602530  0.028961599  0.17871543
+#> Kin   0.05598072 -0.037818788  0.018273854  0.014698885  0.01211345
+#> Kout  0.04256859  0.028764542 -0.017538342  0.053881910 -0.06229732
+#> EC50  0.03982818 -0.035924606  0.003886435  0.041573070 -0.07322727
 #>               Kin         Kout         EC50
-#> TKA  -0.021023944 -0.007146270  0.001406257
-#> TCl   0.046353050 -0.001840578 -0.055571475
-#> V2    0.004554589  0.012059396  0.003785865
-#> Q    -0.052996743 -0.006507225  0.032559017
-#> V3   -0.044415064 -0.004639813 -0.019434394
-#> Kin   0.097337411 -0.010167878 -0.001557061
-#> Kout -0.010167878  0.027566158  0.019229527
-#> EC50 -0.001557061  0.019229527  0.064498809

+#> TKA   0.055980719  0.042568594  0.039828180
+#> TCl  -0.037818788  0.028764542 -0.035924606
+#> V2    0.018273854 -0.017538342  0.003886435
+#> Q     0.014698885  0.053881910  0.041573070
+#> V3    0.012113446 -0.062297320 -0.073227270
+#> Kin   0.157348093 -0.008763337  0.055861453
+#> Kout -0.008763337  0.105270344  0.036356337
+#> EC50  0.055861453  0.036356337  0.161512221

Nesting Variability @@ -407,16 +407,16 @@

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 -0.148 -0.132 -0.000571 -#> 2 1 2 -0.148 -0.132 -0.000571 -#> 3 1 3 -0.148 -0.132 -0.000571 -#> 4 1 4 -0.148 -0.132 -0.000571 -#> 5 1 5 -0.148 -0.132 -0.000571 -#> 6 1 6 -0.148 -0.132 -0.000571 -#> 7 1 7 -0.148 -0.132 -0.000571 -#> 8 1 8 -0.148 -0.132 -0.000571 -#> 9 1 9 -0.148 -0.132 -0.000571 -#> 10 1 10 -0.148 -0.132 -0.000571 +#> 1 1 1 -0.0391 -0.0265 -0.00221 +#> 2 1 2 -0.0391 -0.0265 -0.00221 +#> 3 1 3 -0.0391 -0.0265 -0.00221 +#> 4 1 4 -0.0391 -0.0265 -0.00221 +#> 5 1 5 -0.0391 -0.0265 -0.00221 +#> 6 1 6 -0.0391 -0.0265 -0.00221 +#> 7 1 7 -0.0391 -0.0265 -0.00221 +#> 8 1 8 -0.0391 -0.0265 -0.00221 +#> 9 1 9 -0.0391 -0.0265 -0.00221 +#> 10 1 10 -0.0391 -0.0265 -0.00221 #> # 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>, @@ -433,17 +433,17 @@

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 -0.148 -0.000571 0.702 -0.915 0.0816 0.0896 0 0 -#> 2 1 1 0.1 -0.148 -0.000571 -0.277 -0.0671 0.0816 0.0896 1.25 0.00269 -#> 3 1 1 4 -0.148 -0.000571 0.702 -0.915 0.0816 0.0896 39.4 3.93 -#> 4 1 1 4.1 -0.148 -0.000571 -0.277 -0.0671 0.0816 0.0896 49.6 4.04 -#> 5 1 1 8 -0.148 -0.000571 0.702 -0.915 0.0816 0.0896 36.3 7.33 -#> 6 1 1 8.1 -0.148 -0.000571 -0.277 -0.0671 0.0816 0.0896 23.3 7.39 +#> sim.id id time inv.Cl inv.Ka eye.Cl eye.Ka iov.Cl iov.Ka C2 +#> <int> <int> [h] <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 1 0 -0.0391 -0.00221 -0.0365 -0.0566 0.0675 -0.0702 0 +#> 2 1 1 0.1 -0.0391 -0.00221 -0.362 0.0975 0.0675 -0.0702 -2.56 +#> 3 1 1 4 -0.0391 -0.00221 -0.0365 -0.0566 0.0675 -0.0702 -81.7 +#> 4 1 1 4.1 -0.0391 -0.00221 -0.362 0.0975 0.0675 -0.0702 -86.0 +#> 5 1 1 8 -0.0391 -0.00221 -0.0365 -0.0566 0.0675 -0.0702 -235. +#> 6 1 1 8.1 -0.0391 -0.00221 -0.362 0.0975 0.0675 -0.0702 -169. #> # 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> +#> # i 11 more variables: C3 <dbl>, CL <dbl>, KA <dbl>, ef0 <dbl>, depot <dbl>, +#> # centr <dbl>, peri <dbl>, eff <dbl>, occ <fct>, eye <fct>, inv <fct>

There are multiple investigators in a study; Each investigator has a number of individuals enrolled at their site. rxode2 automatically determines the number of investigators and then will @@ -462,63 +462,63 @@

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     -0.1480315     -0.1323712  -0.0005714332     0.08559259
-#> 2      1  2     -0.1480315     -0.1323712  -0.0005714332     0.08559259
-#> 3      1  3     -0.1480315     -0.1323712  -0.0005714332     0.08559259
-#> 4      1  4     -0.1480315     -0.1323712  -0.0005714332     0.08559259
-#> 5      1  5     -0.1480315     -0.1323712  -0.0005714332     0.08559259
-#> 6      1  6     -0.1480315     -0.1323712  -0.0005714332     0.08559259
+#> 1      1  1    -0.03911994    -0.02646643    -0.00220576     -0.1141159
+#> 2      1  2    -0.03911994    -0.02646643    -0.00220576     -0.1141159
+#> 3      1  3    -0.03911994    -0.02646643    -0.00220576     -0.1141159
+#> 4      1  4    -0.03911994    -0.02646643    -0.00220576     -0.1141159
+#> 5      1  5    -0.03911994    -0.02646643    -0.00220576     -0.1141159
+#> 6      1  6    -0.03911994    -0.02646643    -0.00220576     -0.1141159
 #>   eye.Cl(eye==1) eye.Cl(eye==2) eye.Ka(eye==1) eye.Ka(eye==2) iov.Cl(occ==1)
-#> 1     0.70186234    -0.27732005   -0.915347545    -0.06709872     0.08164632
-#> 2     0.12461103    -0.22840762   -0.183417034    -0.05335536     0.02906715
-#> 3    -0.11718627     0.08188798    0.009429659     0.15021773     0.24113638
-#> 4     0.06090385    -0.32973251    0.139530066    -0.18749762     0.03151548
-#> 5     0.10903320     0.02315588   -0.279554496    -0.35864036     0.01036085
-#> 6    -0.27158388    -0.15547165   -0.153497112    -0.06469808     0.04908725
-#>   iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2)       V2      V3      TCl
-#> 1    0.294447042    0.089582665     0.13833348 40.31123 296.704 18.12202
-#> 2   -0.018486651    0.004075217     0.10875214 40.31123 296.704 18.12202
-#> 3    0.127857862   -0.060962525    -0.09452202 40.31123 296.704 18.12202
-#> 4   -0.203070657    0.025916649     0.37173955 40.31123 296.704 18.12202
-#> 5   -0.006504903   -0.043367120    -0.12604635 40.31123 296.704 18.12202
-#> 6    0.051101039   -0.097513628    -0.11446093 40.31123 296.704 18.12202
-#>        eta.Cl       TKA       eta.Ka        Q       Kin     Kout     EC50
-#> 1  0.18588661 0.1850192 -0.201815537 10.26808 0.7761331 1.285074 200.3064
-#> 2  0.24056866 0.1850192 -0.003196246 10.26808 0.7761331 1.285074 200.3064
-#> 3  0.13228555 0.1850192 -0.629686258 10.26808 0.7761331 1.285074 200.3064
-#> 4 -0.38391078 0.1850192  0.560212037 10.26808 0.7761331 1.285074 200.3064
-#> 5  0.14257398 0.1850192 -0.150690952 10.26808 0.7761331 1.285074 200.3064
-#> 6  0.09652758 0.1850192 -0.549121466 10.26808 0.7761331 1.285074 200.3064
+#> 1 -0.03645376 -0.36231031 -0.05659512 0.09754696 0.067525518 +#> 2 -0.15423162 0.17628371 0.17033619 -0.25543769 0.003339573 +#> 3 0.01370540 -0.12667985 -0.36326997 -0.46382367 -0.040701460 +#> 4 0.20520923 -0.13916146 -0.24406546 0.14638320 0.126635992 +#> 5 0.62095573 0.16708951 -0.03264761 -0.30743926 0.066111000 +#> 6 -0.01113059 0.07142361 0.04510525 -0.09699871 0.007549183 +#> iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2) V2 V3 TCl +#> 1 0.047393997 -0.070219903 -0.075319128 40.22524 297.4692 18.60184 +#> 2 0.044187327 -0.003843144 0.107574203 40.22524 297.4692 18.60184 +#> 3 0.130975748 0.122989836 -0.074852264 40.22524 297.4692 18.60184 +#> 4 -0.084189574 -0.163824725 -0.020576261 40.22524 297.4692 18.60184 +#> 5 0.003705417 0.065585679 0.003578391 40.22524 297.4692 18.60184 +#> 6 -0.038608539 0.161036185 0.144121117 40.22524 297.4692 18.60184 +#> eta.Cl TKA eta.Ka Q Kin Kout EC50 +#> 1 -0.1047263 -0.1221477 -0.08809663 10.26499 1.051154 0.6049542 199.646 +#> 2 0.6465167 -0.1221477 0.02602436 10.26499 1.051154 0.6049542 199.646 +#> 3 -0.4423746 -0.1221477 -0.24399657 10.26499 1.051154 0.6049542 199.646 +#> 4 -0.1156852 -0.1221477 -0.38145785 10.26499 1.051154 0.6049542 199.646 +#> 5 -0.3741853 -0.1221477 0.08673172 10.26499 1.051154 0.6049542 199.646 +#> 6 -0.1652379 -0.1221477 0.17428125 10.26499 1.051154 0.6049542 199.646 
 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    0.001613993     -0.1655022      0.1074734     0.02238288
-#> 2      2  2    0.001613993     -0.1655022      0.1074734     0.02238288
-#> 3      2  3    0.001613993     -0.1655022      0.1074734     0.02238288
-#> 4      2  4    0.001613993     -0.1655022      0.1074734     0.02238288
-#> 5      2  5    0.001613993     -0.1655022      0.1074734     0.02238288
-#> 6      2  6    0.001613993     -0.1655022      0.1074734     0.02238288
+#> 1      2  1      0.1016724    -0.05768568    -0.08969302     0.03548156
+#> 2      2  2      0.1016724    -0.05768568    -0.08969302     0.03548156
+#> 3      2  3      0.1016724    -0.05768568    -0.08969302     0.03548156
+#> 4      2  4      0.1016724    -0.05768568    -0.08969302     0.03548156
+#> 5      2  5      0.1016724    -0.05768568    -0.08969302     0.03548156
+#> 6      2  6      0.1016724    -0.05768568    -0.08969302     0.03548156
 #>   eye.Cl(eye==1) eye.Cl(eye==2) eye.Ka(eye==1) eye.Ka(eye==2) iov.Cl(occ==1)
-#> 1    -0.06492477      0.2103290   -0.258234272    -0.65555476     0.05581626
-#> 2     0.29221373      0.1291948   -0.001047067    -0.06049668     0.18612125
-#> 3     0.18355366      0.2809128   -0.006091777    -0.07121414    -0.07860149
-#> 4     0.51729297     -0.2746913    0.296216014     0.19018619    -0.01220883
-#> 5     0.09854127      0.1244885    0.051972718     0.02492854    -0.05869592
-#> 6    -0.21757059      0.1180519    0.265363855    -0.02517008     0.21103990
+#> 1    0.250679613    0.399887417    -0.18995157    -0.22979544    0.053010451
+#> 2   -0.193811345   -0.006759532    -0.28266541    -0.01564961    0.015378941
+#> 3    0.371815629   -0.399223456    -0.16225912    -0.15531978   -0.042915258
+#> 4    0.079688048    0.133151472     0.05655038    -0.01512107   -0.009710154
+#> 5    0.249691829    0.042461982    -0.02856142    -0.10260240    0.092573502
+#> 6   -0.004927963    0.031402455    -0.12693507    -0.29047920   -0.243391645
 #>   iov.Cl(occ==2) iov.Ka(occ==1) iov.Ka(occ==2)       V2       V3      TCl
-#> 1     0.08770510  -0.1213494181    -0.07194749 40.40494 296.9874 18.59039
-#> 2    -0.06866621  -0.0034025289     0.03800002 40.40494 296.9874 18.59039
-#> 3    -0.12655918  -0.0784557848     0.12632977 40.40494 296.9874 18.59039
-#> 4    -0.03565934  -0.0007239254    -0.16161576 40.40494 296.9874 18.59039
-#> 5     0.02553487   0.1917256083    -0.31148491 40.40494 296.9874 18.59039
-#> 6     0.01985213  -0.0201123515    -0.16279535 40.40494 296.9874 18.59039
-#>        eta.Cl       TKA      eta.Ka        Q      Kin      Kout     EC50
-#> 1 -0.30400507 0.1844716  0.11056784 10.33659 1.137549 0.9891969 200.0611
-#> 2  0.49634073 0.1844716 -0.05259496 10.33659 1.137549 0.9891969 200.0611
-#> 3 -0.07096015 0.1844716 -0.10609177 10.33659 1.137549 0.9891969 200.0611
-#> 4  0.08067657 0.1844716  0.25228398 10.33659 1.137549 0.9891969 200.0611
-#> 5  0.24616432 0.1844716  0.01271617 10.33659 1.137549 0.9891969 200.0611
-#> 6 -0.05820859 0.1844716  0.33222285 10.33659 1.137549 0.9891969 200.0611
+#> 1 0.05409047 0.04639233 -0.016095257 40.13468 297.0358 18.65192 +#> 2 0.10716852 -0.19118988 0.031572133 40.13468 297.0358 18.65192 +#> 3 -0.11725361 0.08095280 0.009272479 40.13468 297.0358 18.65192 +#> 4 0.06973915 0.11504560 0.128600039 40.13468 297.0358 18.65192 +#> 5 -0.21141943 -0.13882216 -0.107488100 40.13468 297.0358 18.65192 +#> 6 -0.19620243 0.01039522 -0.073640426 40.13468 297.0358 18.65192 +#> eta.Cl TKA eta.Ka Q Kin Kout EC50 +#> 1 0.073463560 0.2512785 -0.1195763 10.76278 0.3278979 1.321924 199.9834 +#> 2 0.006689739 0.2512785 -0.4004964 10.76278 0.3278979 1.321924 199.9834 +#> 3 0.121008344 0.2512785 0.2765039 10.76278 0.3278979 1.321924 199.9834 +#> 4 -0.277748970 0.2512785 0.2491093 10.76278 0.3278979 1.321924 199.9834 +#> 5 -0.216971611 0.2512785 -0.5772672 10.76278 0.3278979 1.321924 199.9834 +#> 6 -0.345436538 0.2512785 -0.1102403 10.76278 0.3278979 1.321924 199.9834

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 668521277..acbb541ea 100644 --- a/articles/rxode2-pipeline.html +++ b/articles/rxode2-pipeline.html @@ -157,7 +157,7 @@
Advanced Features, Model Types, Techni

rxode2 in a pipeline

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Source: vignettes/rxode2-pipeline.Rmd
rxode2-pipeline.Rmd
diff --git a/articles/rxode2-plot.html b/articles/rxode2-plot.html index 80386a362..f2bc5a5ad 100644 --- a/articles/rxode2-plot.html +++ b/articles/rxode2-plot.html @@ -159,7 +159,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

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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 4488265db..bd0d09772 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 b2e76dca3..02d5dca91 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 64b3cd09c..08167a148 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 11b757c6f..5a23368d2 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 3bf855491..8e775c13d 100644 --- a/articles/rxode2-prior-data.html +++ b/articles/rxode2-prior-data.html @@ -157,7 +157,7 @@
Advanced Features, Model Types, Techni

Using Prior Data for ODE solving

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Source: vignettes/rxode2-prior-data.Rmd
rxode2-prior-data.Rmd
@@ -242,33 +242,33 @@

Using prior data for solving#> ── Solved rxode2 object ── #> ── Parameters ($params): ── #> # A tibble: 12 × 7 -#> id tka tcl tv eta.ka eta.cl eta.v -#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 0.451 1.02 3.45 -0.781 0.0848 -0.154 -#> 2 2 0.451 1.02 3.45 -0.557 -0.116 -0.351 -#> 3 3 0.451 1.02 3.45 -0.170 -0.748 0.187 -#> 4 4 0.451 1.02 3.45 -0.382 -0.158 0.222 -#> 5 5 0.451 1.02 3.45 -0.161 -0.536 0.198 -#> 6 6 0.451 1.02 3.45 -0.405 0.0630 -0.159 -#> 7 7 0.451 1.02 3.45 0.216 0.476 -0.375 -#> 8 8 0.451 1.02 3.45 -0.630 0.000678 0.0844 -#> 9 9 0.451 1.02 3.45 1.05 -0.0449 -0.0207 -#> 10 10 0.451 1.02 3.45 0.918 0.250 -0.199 -#> 11 11 0.451 1.02 3.45 0.698 -0.119 -0.0334 -#> 12 12 0.451 1.02 3.45 0.103 -0.148 -0.208 +#> id tka tcl tv eta.ka eta.cl eta.v +#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 0.451 1.02 3.45 -0.111 1.08 0.0949 +#> 2 2 0.451 1.02 3.45 0.790 -0.884 0.294 +#> 3 3 0.451 1.02 3.45 0.592 -0.0302 -0.325 +#> 4 4 0.451 1.02 3.45 -1.55 0.183 0.430 +#> 5 5 0.451 1.02 3.45 -0.895 -0.608 0.0572 +#> 6 6 0.451 1.02 3.45 0.422 -0.362 -0.0614 +#> 7 7 0.451 1.02 3.45 0.0178 -0.000737 -0.338 +#> 8 8 0.451 1.02 3.45 -0.852 0.0517 -0.115 +#> 9 9 0.451 1.02 3.45 0.970 1.31 -0.0144 +#> 10 10 0.451 1.02 3.45 -0.0596 0.0197 0.465 +#> 11 11 0.451 1.02 3.45 1.23 0.483 0.104 +#> 12 12 0.451 1.02 3.45 2.27 0.178 -0.0347 #> ── Initial Conditions ($inits): ── #> depot center #> 0 0 #> ── First part of data (object): ── #> # A tibble: 132 × 8 -#> id time ka cl v cp depot center -#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 0 0.719 3.01 27.0 0 320. 0 -#> 2 1 0.25 0.719 3.01 27.0 1.92 267. 51.9 -#> 3 1 0.57 0.719 3.01 27.0 3.86 212. 104. -#> 4 1 1.12 0.719 3.01 27.0 6.12 143. 165. -#> 5 1 2.02 0.719 3.01 27.0 7.92 74.9 214. -#> 6 1 3.82 0.719 3.01 27.0 8.27 20.5 223. +#> id time ka cl v cp depot center +#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 0 1.41 8.13 34.6 0 320. 0 +#> 2 1 0.25 1.41 8.13 34.6 2.66 225. 91.9 +#> 3 1 0.57 1.41 8.13 34.6 4.73 144. 164. +#> 4 1 1.12 1.41 8.13 34.6 6.23 66.3 216. +#> 5 1 2.02 1.41 8.13 34.6 6.26 18.7 217. +#> 6 1 3.82 1.41 8.13 34.6 4.47 1.49 155. #> # ℹ 126 more rows ## Of course the fasest way to solve if you don't care about the rxode2 extra parameters is @@ -280,33 +280,33 @@

Using prior data for solving## solved data dplyr::as_tibble(solveData) #> # A tibble: 132 × 8 -#> id time ka cl v cp depot center -#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> -#> 1 1 0 1.43 2.37 20.9 0 320. 0 -#> 2 1 0.25 1.43 2.37 20.9 4.54 224. 94.9 -#> 3 1 0.57 1.43 2.37 20.9 8.24 141. 172. -#> 4 1 1.12 1.43 2.37 20.9 11.3 64.3 236. -#> 5 1 2.02 1.43 2.37 20.9 12.3 17.7 257. -#> 6 1 3.82 1.43 2.37 20.9 10.7 1.34 224. -#> 7 1 5.1 1.43 2.37 20.9 9.32 0.215 195. -#> 8 1 7.03 1.43 2.37 20.9 7.49 0.0135 157. -#> 9 1 9.05 1.43 2.37 20.9 5.96 0.000750 125. -#> 10 1 12.1 1.43 2.37 20.9 4.21 0.00000922 88.0 +#> id time ka cl v cp depot center +#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> +#> 1 1 0 1.71 1.89 30.2 0 320. 0 +#> 2 1 0.25 1.71 1.89 30.2 3.67 208. 111. +#> 3 1 0.57 1.71 1.89 30.2 6.48 120. 195. +#> 4 1 1.12 1.71 1.89 30.2 8.65 46.9 261. +#> 5 1 2.02 1.71 1.89 30.2 9.36 10.0 282. +#> 6 1 3.82 1.71 1.89 30.2 8.65 0.458 261. +#> 7 1 5.1 1.71 1.89 30.2 7.99 0.0510 241. +#> 8 1 7.03 1.71 1.89 30.2 7.08 0.00187 214. +#> 9 1 9.05 1.71 1.89 30.2 6.24 0.0000585 188. +#> 10 1 12.1 1.71 1.89 30.2 5.14 0.000000303 155. #> # ℹ 122 more rows data.table::data.table(solveData) -#> id time ka cl v cp depot center -#> 1: 1 0.00 1.432501 2.368460 20.90624 0.000000 3.199920e+02 0.00000 -#> 2: 1 0.25 1.432501 2.368460 20.90624 4.538880 2.236698e+02 94.89089 -#> 3: 1 0.57 1.432501 2.368460 20.90624 8.235471 1.414251e+02 172.17270 -#> 4: 1 1.12 1.432501 2.368460 20.90624 11.299036 6.432153e+01 236.22032 -#> 5: 1 2.02 1.432501 2.368460 20.90624 12.300463 1.771909e+01 257.15637 -#> --- -#> 128: 12 5.07 1.848827 1.806708 33.37071 7.521671 2.723616e-02 251.00351 -#> 129: 12 7.07 1.848827 1.806708 33.37071 6.750496 6.749527e-04 225.26884 -#> 130: 12 9.03 1.848827 1.806708 33.37071 6.070879 1.801074e-05 202.58956 -#> 131: 12 12.05 1.848827 1.806708 33.37071 5.155165 6.836463e-08 172.03152 -#> 132: 12 24.15 1.848827 1.806708 33.37071 2.677546 -1.208373e-09 89.35161

+#> id time ka cl v cp depot center +#> 1: 1 0.00 1.7144281 1.894881 30.15945 0.000000 3.199920e+02 0.00000 +#> 2: 1 0.25 1.7144281 1.894881 30.15945 3.667532 2.084479e+02 110.61077 +#> 3: 1 0.57 1.7144281 1.894881 30.15945 6.481148 1.204305e+02 195.46789 +#> 4: 1 1.12 1.7144281 1.894881 30.15945 8.650838 4.690556e+01 260.90455 +#> 5: 1 2.02 1.7144281 1.894881 30.15945 9.355834 1.002568e+01 282.16685 +#> --- +#> 128: 12 5.07 0.9835705 2.109641 29.75338 8.027812 2.189436e+00 238.85453 +#> 129: 12 7.07 0.9835705 2.109641 29.75338 7.024162 3.062054e-01 208.99254 +#> 130: 12 9.03 0.9835705 2.109641 29.75338 6.120830 4.454303e-02 182.11538 +#> 131: 12 12.05 0.9835705 2.109641 29.75338 4.942216 2.284322e-03 147.04762 +#> 132: 12 24.15 0.9835705 2.109641 29.75338 2.095704 1.520669e-08 62.35429
diff --git a/articles/rxode2-prior-data_files/figure-html/unnamed-chunk-5-1.png b/articles/rxode2-prior-data_files/figure-html/unnamed-chunk-5-1.png index ca81c5f1d..41f808f5e 100644 Binary files a/articles/rxode2-prior-data_files/figure-html/unnamed-chunk-5-1.png and b/articles/rxode2-prior-data_files/figure-html/unnamed-chunk-5-1.png differ diff --git a/articles/rxode2-rxUse.html b/articles/rxode2-rxUse.html index f73eb96e6..70f365d00 100644 --- a/articles/rxode2-rxUse.html +++ b/articles/rxode2-rxUse.html @@ -159,7 +159,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

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Source: vignettes/rxode2-rxUse.Rmd
rxode2-rxUse.Rmd
diff --git a/articles/rxode2-shiny.html b/articles/rxode2-shiny.html index ab1697abd..9eef362d8 100644 --- a/articles/rxode2-shiny.html +++ b/articles/rxode2-shiny.html @@ -157,7 +157,7 @@
Advanced Features, Model Types, Techni

rxode2 and Shiny

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Source: vignettes/rxode2-shiny.Rmd
rxode2-shiny.Rmd
diff --git a/articles/rxode2-sim-var.html b/articles/rxode2-sim-var.html index 1303db964..7d4c6e74e 100644 --- a/articles/rxode2-sim-var.html +++ b/articles/rxode2-sim-var.html @@ -157,7 +157,7 @@
Advanced Features, Model Types, Techni

rxode2 Simulation

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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 ca355d563..1408b4dfe 100644 --- a/articles/rxode2-single-subject.html +++ b/articles/rxode2-single-subject.html @@ -157,7 +157,7 @@
Advanced Features, Model Types, Techni

Single Subject ODE solving -- differences from multiple subject

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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 694b4f841..e7669db17 100644 --- a/articles/rxode2-speed.html +++ b/articles/rxode2-speed.html @@ -159,7 +159,7 @@
Advanced Features, Model Types, Techni

Matthew Fidler

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Source: vignettes/rxode2-speed.Rmd
rxode2-speed.Rmd
@@ -262,8 +262,8 @@

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

 summary(mod1$simulationModel)
-#> rxode2 2.0.14.9000 model named rx_f6df81dba92d362c7c658b7dd040332b model (✔ ready). 
-#> DLL: /tmp/Rtmp5mYcCf/rxode2/rx_f6df81dba92d362c7c658b7dd040332b__.rxd/rx_f6df81dba92d362c7c658b7dd040332b_.so
+#> rxode2 2.0.14.9000 model named rx_4080a1bccb3d88a72efd4eb95d275c3f model (✔ ready). 
+#> DLL: /tmp/RtmpE4aPra/rxode2/rx_4080a1bccb3d88a72efd4eb95d275c3f__.rxd/rx_4080a1bccb3d88a72efd4eb95d275c3f_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -281,8 +281,8 @@ 
A note about t
 #> })
 summary(mod1$simulationIniModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.0.14.9000 model named rx_6a9a6e920d2935cba8f2ef73c0cfff04 model (✔ ready). 
-#> DLL: /tmp/Rtmp5mYcCf/rxode2/rx_6a9a6e920d2935cba8f2ef73c0cfff04__.rxd/rx_6a9a6e920d2935cba8f2ef73c0cfff04_.so
+#> rxode2 2.0.14.9000 model named rx_79be712c1b8cfdbd11414aac387b190c model (✔ ready). 
+#> DLL: /tmp/RtmpE4aPra/rxode2/rx_79be712c1b8cfdbd11414aac387b190c__.rxd/rx_79be712c1b8cfdbd11414aac387b190c_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -308,8 +308,8 @@ 
A note about t
 #> })
 summary(mod2f$simulationModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.0.14.9000 model named rx_2084cc55ccb1d18e4ccfa62790e1b6c6 model (✔ ready). 
-#> DLL: /tmp/Rtmp5mYcCf/rxode2/rx_2084cc55ccb1d18e4ccfa62790e1b6c6__.rxd/rx_2084cc55ccb1d18e4ccfa62790e1b6c6_.so
+#> rxode2 2.0.14.9000 model named rx_39f78bb08fb42ed8474af31e234006ed model (✔ ready). 
+#> DLL: /tmp/RtmpE4aPra/rxode2/rx_39f78bb08fb42ed8474af31e234006ed__.rxd/rx_39f78bb08fb42ed8474af31e234006ed_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -365,8 +365,8 @@ 
A note about t
 #> })
 summary(mod2f$simulationIniModel)
 #> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
-#> rxode2 2.0.14.9000 model named rx_1915c92e164f682e9bc352ac7211dc46 model (✔ ready). 
-#> DLL: /tmp/Rtmp5mYcCf/rxode2/rx_1915c92e164f682e9bc352ac7211dc46__.rxd/rx_1915c92e164f682e9bc352ac7211dc46_.so
+#> rxode2 2.0.14.9000 model named rx_5453804681c56967a6be1d8cd0005130 model (✔ ready). 
+#> DLL: /tmp/RtmpE4aPra/rxode2/rx_5453804681c56967a6be1d8cd0005130__.rxd/rx_5453804681c56967a6be1d8cd0005130_.so
 #> NULL
 #> 
 #> Calculated Variables:
@@ -552,10 +552,10 @@ 
Compare the times between all
 print(bench)
 #> Unit: milliseconds
 #>               expr       min        lq      mean    median        uq       max
-#>           runFor() 274.52428 280.08363 288.84306 282.51682 285.47158 417.21426
-#>        runSapply() 274.58491 281.29385 292.28574 283.44581 288.11469 420.43549
-#>  runSingleThread()  28.13222  28.37132  29.85955  28.58462  28.80817  48.79048
-#>       run2Thread()  16.78064  17.41015  18.47267  17.65783  17.96191  27.98068
+#>           runFor() 271.77932 277.34620 284.72932 279.38768 282.35578 326.61336
+#>        runSapply() 273.07732 277.02475 288.05530 279.45924 283.12016 398.42309
+#>  runSingleThread()  27.44159  27.56624  28.56416  27.68545  27.97961  47.53934
+#>       run2Thread()  16.31126  16.55615  18.04028  16.70647  17.06553  27.88397
 #>  neval
 #>    100
 #>    100
@@ -582,10 +582,10 @@ 
Compare the times between all
 print(bench)
 #> Unit: milliseconds
 #>          expr      min       lq     mean   median       uq      max neval
-#>  runThread(1) 28.10950 28.39885 29.47866 29.60013 29.77615 40.06624   100
-#>  runThread(2) 16.86474 17.50823 19.40572 17.87759 18.27338 30.41207   100
-#>  runThread(3) 18.45526 19.11944 19.94110 19.68277 20.13565 26.65370   100
-#>  runThread(4) 16.20638 16.49846 19.26556 17.16621 18.25278 37.58492   100
+#> runThread(1) 27.52315 27.74998 28.83332 28.43341 29.14889 37.38419 100 +#> runThread(2) 16.35291 16.88591 19.05743 17.39389 19.59169 28.23953 100 +#> runThread(3) 17.63698 18.94453 19.71197 19.56353 20.12006 25.34988 100 +#> runThread(4) 15.90711 16.26722 18.68598 16.79267 17.36888 41.41148 100

 autoplot(bench)

@@ -674,8 +674,8 @@

Increasing speed with compiler o print(bench) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> standardCompile 198.4301 316.9086 326.3612 321.0555 338.1012 398.3201 100 -#> fastCompile 191.7812 319.8152 327.5245 323.8790 334.6548 385.4462 100 +#> standardCompile 191.6286 306.4533 312.6785 309.1190 317.2356 362.8603 100 +#> fastCompile 190.9105 304.4759 309.0352 305.7667 310.6558 355.6306 100 autoplot(bench)

@@ -769,7 +769,7 @@

A real life exampleStoplapply <- Sys.time() print(Stoplapply - Startlapply) -#> Time difference of 13.77648 secs

+#> Time difference of 12.40183 secs

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

@@ -810,7 +810,7 @@ 
A real life exampleres <- rxSolve(rx, ev, omega=omega, returnType="data.table")
 endParallel <- Sys.time()
 print(endParallel - startParallel)
-#> Time difference of 0.1125503 secs
+#> Time difference of 0.1078572 secs

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