From 7faf98ac5475bb2041d7e434478c58c2f2cec0fd Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 28 Jun 2016 08:23:38 +0200 Subject: Static documentation rebuilt by staticdocs::build_site() --- vignettes/FOCUS_D.html | 17 +++++-------- vignettes/FOCUS_L.html | 56 ++++++++++++++++++++--------------------- vignettes/FOCUS_Z.pdf | Bin 238788 -> 238788 bytes vignettes/compiled_models.html | 51 +++++++++++++++++-------------------- vignettes/mkin.html | 10 ++------ 5 files changed, 59 insertions(+), 75 deletions(-) (limited to 'vignettes') diff --git a/vignettes/FOCUS_D.html b/vignettes/FOCUS_D.html index f3eb6a0c..c7e2047f 100644 --- a/vignettes/FOCUS_D.html +++ b/vignettes/FOCUS_D.html @@ -124,13 +124,8 @@ $(document).ready(function () {

This is just a very simple vignette showing how to fit a degradation model for a parent compound with one transformation product using mkin. After loading the library we look a the data. We have observed concentrations in the column named value at the times specified in column time for the two observed variables named parent and m1.

-
library("mkin")
-
## Loading required package: minpack.lm
-
## Loading required package: rootSolve
-
## Loading required package: inline
-
## Loading required package: methods
-
## Loading required package: parallel
-
print(FOCUS_2006_D)
+
library("mkin")
+print(FOCUS_2006_D)
##      name time  value
 ## 1  parent    0  99.46
 ## 2  parent    0 102.04
@@ -195,10 +190,10 @@ $(document).ready(function () {
 

 
A comprehensive report of the results is obtained using the summary method for mkinfit objects.

 
summary(fit)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:48:50 2016 
-## Date of summary: Tue Jun 28 07:48:50 2016 
+## Date of fit:     Tue Jun 28 08:19:31 2016 
+## Date of summary: Tue Jun 28 08:19:31 2016 
 ## 
 ## Equations:
 ## d_parent = - k_parent_sink * parent - k_parent_m1 * parent
@@ -206,7 +201,7 @@ $(document).ready(function () {
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 1.659 s
+## Fitted with method Port using 153 model solutions performed in 1.706 s
 ## 
 ## Weighting: none
 ## 
diff --git a/vignettes/FOCUS_L.html b/vignettes/FOCUS_L.html
index 8435ce23..05b9bdbd 100644
--- a/vignettes/FOCUS_L.html
+++ b/vignettes/FOCUS_L.html
@@ -233,17 +233,17 @@ FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)

 
Since mkin version 0.9-32 (July 2014), we can use shorthand notation like "SFO" for parent only degradation models. The following two lines fit the model and produce the summary report of the model fit. This covers the numerical analysis given in the FOCUS report.

 
m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
 summary(m.L1.SFO)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:06 2016 
-## Date of summary: Tue Jun 28 07:38:06 2016 
+## Date of fit:     Tue Jun 28 08:19:32 2016 
+## Date of summary: Tue Jun 28 08:19:32 2016 
 ## 
 ## Equations:
 ## d_parent = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.235 s
+## Fitted with method Port using 37 model solutions performed in 0.245 s
 ## 
 ## Weighting: none
 ## 
@@ -326,10 +326,10 @@ summary(m.L1.SFO)

 
plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

 

 
summary(m.L1.FOMC, data = FALSE)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:07 2016 
-## Date of summary: Tue Jun 28 07:38:07 2016 
+## Date of fit:     Tue Jun 28 08:19:34 2016 
+## Date of summary: Tue Jun 28 08:19:34 2016 
 ## 
 ## 
 ## Warning: Optimisation by method Port did not converge.
@@ -341,7 +341,7 @@ summary(m.L1.SFO)

 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 188 model solutions performed in 1.119 s
+## Fitted with method Port using 188 model solutions performed in 1.216 s
 ## 
 ## Weighting: none
 ## 
@@ -423,17 +423,17 @@ plot(m.L2.FOMC, show_residuals = TRUE,
      main = "FOCUS L2 - FOMC")

 

 
summary(m.L2.FOMC, data = FALSE)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:09 2016 
-## Date of summary: Tue Jun 28 07:38:09 2016 
+## Date of fit:     Tue Jun 28 08:19:36 2016 
+## Date of summary: Tue Jun 28 08:19:36 2016 
 ## 
 ## Equations:
 ## d_parent = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 81 model solutions performed in 0.492 s
+## Fitted with method Port using 81 model solutions performed in 0.537 s
 ## 
 ## Weighting: none
 ## 
@@ -493,10 +493,10 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - DFOP")

 

 
summary(m.L2.DFOP, data = FALSE)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:11 2016 
-## Date of summary: Tue Jun 28 07:38:11 2016 
+## Date of fit:     Tue Jun 28 08:19:39 2016 
+## Date of summary: Tue Jun 28 08:19:39 2016 
 ## 
 ## Equations:
 ## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -505,7 +505,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 336 model solutions performed in 2.04 s
+## Fitted with method Port using 336 model solutions performed in 2.267 s
 ## 
 ## Weighting: none
 ## 
@@ -582,10 +582,10 @@ plot(mm.L3)

 
The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index.

 
We can extract the summary and plot for e.g. the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.

 
summary(mm.L3[["DFOP", 1]])

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:13 2016 
-## Date of summary: Tue Jun 28 07:38:13 2016 
+## Date of fit:     Tue Jun 28 08:19:41 2016 
+## Date of summary: Tue Jun 28 08:19:42 2016 
 ## 
 ## Equations:
 ## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -594,7 +594,7 @@ plot(mm.L3)

 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 137 model solutions performed in 0.846 s
+## Fitted with method Port using 137 model solutions performed in 0.924 s
 ## 
 ## Weighting: none
 ## 
@@ -682,17 +682,17 @@ plot(mm.L4)

 

 
The χ2 error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the χ2 test passes is slightly lower for the FOMC model. However, the difference appears negligible.

 
summary(mm.L4[["SFO", 1]], data = FALSE)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:14 2016 
-## Date of summary: Tue Jun 28 07:38:14 2016 
+## Date of fit:     Tue Jun 28 08:19:42 2016 
+## Date of summary: Tue Jun 28 08:19:43 2016 
 ## 
 ## Equations:
 ## d_parent = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.283 s
+## Fitted with method Port using 46 model solutions performed in 0.307 s
 ## 
 ## Weighting: none
 ## 
@@ -742,17 +742,17 @@ plot(mm.L4)

 ##        DT50 DT90
 ## parent  106  352

 
summary(mm.L4[["FOMC", 1]], data = FALSE)

-
## mkin version:    0.9.43 
+
## mkin version:    0.9.43.9000 
 ## R version:       3.3.1 
-## Date of fit:     Tue Jun 28 07:38:14 2016 
-## Date of summary: Tue Jun 28 07:38:15 2016 
+## Date of fit:     Tue Jun 28 08:19:43 2016 
+## Date of summary: Tue Jun 28 08:19:43 2016 
 ## 
 ## Equations:
 ## d_parent = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 66 model solutions performed in 0.383 s
+## Fitted with method Port using 66 model solutions performed in 0.414 s
 ## 
 ## Weighting: none
 ## 
diff --git a/vignettes/FOCUS_Z.pdf b/vignettes/FOCUS_Z.pdf
index efda950f..1f9560b0 100644
Binary files a/vignettes/FOCUS_Z.pdf and b/vignettes/FOCUS_Z.pdf differ
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html
index c3ffb035..cec76ef9 100644
--- a/vignettes/compiled_models.html
+++ b/vignettes/compiled_models.html
@@ -226,13 +226,8 @@ div.tocify {
 
##            gcc 
 ## "/usr/bin/gcc"

 
First, we build a simple degradation model for a parent compound with one metabolite.

-
library("mkin")

-
## Loading required package: minpack.lm

-
## Loading required package: rootSolve

-
## Loading required package: inline

-
## Loading required package: methods

-
## Loading required package: parallel

-
SFO_SFO <- mkinmod(
+
library("mkin")
+SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))

 
## Successfully compiled differential equation model from auto-generated C code.

@@ -255,22 +250,22 @@ mb.1 <- microbenchmark(
 print(mb.1)

 
## Unit: seconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 13.694897 13.774112 13.820936 13.853327 13.883956
-##       Eigenvalue based  2.087861  2.089503  2.116323  2.091145  2.130555
-##      deSolve, compiled  1.794975  1.799892  1.814653  1.804808  1.824492
-##        max neval cld
-##  13.914585     3   c
-##   2.169964     3  b 
-##   1.844177     3 a

+##  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

 
autoplot(mb.1)

-

-
We see that using the compiled model is by a factor of 7.7 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 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:

 
rownames(smb.1) <- smb.1$expr
 smb.1["median"]/smb.1["deSolve, compiled", "median"]

-
##                         median
-## deSolve, not compiled 7.675788
-## Eigenvalue based      1.158652
-## deSolve, compiled     1.000000

+
##                          median
+## deSolve, not compiled 14.010730
+## Eigenvalue based       1.204226
+## deSolve, compiled      1.000000

 
 

 
Benchmark for a model that can not be solved with Eigenvalues

@@ -290,20 +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 29.120048 29.170013 29.246607 29.21998 29.309886
-##      deSolve, compiled  3.338458  3.343954  3.379437  3.34945  3.399926
+##                   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
 ##        max neval cld
-##  29.399796     3   b
-##   3.450402     3  a

+##  54.645498     3   b
+##   3.653319     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 8.7 using the version of the differential equation model compiled from C code!

-
This vignette was built with mkin 0.9.43 on

+

+
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

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

diff --git a/vignettes/mkin.html b/vignettes/mkin.html
index 54605dfc..f9704eda 100644
--- a/vignettes/mkin.html
+++ b/vignettes/mkin.html
@@ -236,14 +236,8 @@ div.tocify {
 

 
Abstract

 
In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance has been developed, based on nonlinear optimisation. The R add-on package mkin (Ranke 2016) implements fitting some of the models recommended in this guidance from within R and calculates some statistical measures for data series within one or more compartments, for parent and metabolites.

-
require(mkin)

-
## Loading required package: mkin

-
## Loading required package: minpack.lm

-
## Loading required package: rootSolve

-
## Loading required package: inline

-
## Loading required package: methods

-
## Loading required package: parallel

-
m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
+
require(mkin)
+m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
                          M1 = mkinsub("SFO", "M2"),
                          M2 = mkinsub("SFO"), 
                          use_of_ff = "max", quiet = TRUE)
-- 
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