From db9ae6a0c9cecb92048fde6f06af1da183c09b5f Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 19 Nov 2020 15:41:24 +0100 Subject: Depend on parallel, doc improvements By depending on parallel instead of importing it, functions to set up and stop a cluster are always available when mkin is loaded. The use of multicore processing in mmkin on Windows is now documented in the help file, which brings mkin closer to a version 1.0 #9. --- docs/dev/articles/FOCUS_D.html | 113 ++++---- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ .../articles/FOCUS_D_files/figure-html/plot-1.png | Bin 101350 -> 81432 bytes .../FOCUS_D_files/figure-html/plot_2-1.png | Bin 15733 -> 24025 bytes docs/dev/articles/FOCUS_L.html | 248 ++++++++-------- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ .../figure-html/unnamed-chunk-10-1.png | Bin 29158 -> 43110 bytes .../figure-html/unnamed-chunk-12-1.png | Bin 54890 -> 84605 bytes .../figure-html/unnamed-chunk-13-1.png | Bin 22017 -> 33489 bytes .../figure-html/unnamed-chunk-15-1.png | Bin 38622 -> 59507 bytes .../figure-html/unnamed-chunk-4-1.png | Bin 23429 -> 35964 bytes .../figure-html/unnamed-chunk-5-1.png | Bin 14826 -> 21999 bytes .../figure-html/unnamed-chunk-6-1.png | Bin 23881 -> 36379 bytes .../figure-html/unnamed-chunk-8-1.png | Bin 27992 -> 42221 bytes .../figure-html/unnamed-chunk-9-1.png | Bin 28432 -> 41739 bytes docs/dev/articles/mkin.html | 11 +- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ .../mkin_files/figure-html/unnamed-chunk-2-1.png | Bin 92716 -> 92716 bytes docs/dev/articles/twa.html | 13 +- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ docs/dev/articles/web_only/FOCUS_Z.html | 245 +++++++++------- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ .../figure-html/FOCUS_2006_Z_fits_1-1.png | Bin 88629 -> 69227 bytes .../figure-html/FOCUS_2006_Z_fits_10-1.png | Bin 133233 -> 109820 bytes .../figure-html/FOCUS_2006_Z_fits_11-1.png | Bin 132503 -> 109050 bytes .../figure-html/FOCUS_2006_Z_fits_11a-1.png | Bin 99562 -> 79154 bytes .../figure-html/FOCUS_2006_Z_fits_11b-1.png | Bin 22624 -> 35734 bytes .../figure-html/FOCUS_2006_Z_fits_2-1.png | Bin 88629 -> 69227 bytes .../figure-html/FOCUS_2006_Z_fits_3-1.png | Bin 88213 -> 69006 bytes .../figure-html/FOCUS_2006_Z_fits_5-1.png | Bin 104162 -> 83658 bytes .../figure-html/FOCUS_2006_Z_fits_6-1.png | Bin 133001 -> 108890 bytes .../figure-html/FOCUS_2006_Z_fits_7-1.png | Bin 132462 -> 108277 bytes .../figure-html/FOCUS_2006_Z_fits_9-1.png | Bin 110760 -> 91586 bytes docs/dev/articles/web_only/NAFTA_examples.html | 321 +++++++++++---------- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ .../NAFTA_examples_files/figure-html/p10-1.png | Bin 80950 -> 80950 bytes .../NAFTA_examples_files/figure-html/p13-1.png | Bin 79358 -> 79355 bytes .../NAFTA_examples_files/figure-html/p15a-1.png | Bin 78259 -> 78261 bytes .../NAFTA_examples_files/figure-html/p16-1.png | Bin 95465 -> 95466 bytes .../NAFTA_examples_files/figure-html/p7-1.png | Bin 103768 -> 103771 bytes docs/dev/articles/web_only/benchmarks.html | 54 ++-- docs/dev/articles/web_only/compiled_models.html | 122 ++++---- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 +++ 50 files changed, 861 insertions(+), 525 deletions(-) create mode 100644 docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/FOCUS_L_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/FOCUS_L_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js (limited to 'docs/dev/articles') diff --git a/docs/dev/articles/FOCUS_D.html b/docs/dev/articles/FOCUS_D.html index 02701431..e526b3a7 100644 --- a/docs/dev/articles/FOCUS_D.html +++ b/docs/dev/articles/FOCUS_D.html @@ -32,7 +32,7 @@ mkin - 0.9.50.3 + 0.9.50.4 @@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Calculation of time weighted average concentrations with mkin

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/twa.rmd + Source: vignettes/twa.rmd
    @@ -162,7 +163,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); diff --git a/docs/dev/articles/web_only/FOCUS_Z.html b/docs/dev/articles/web_only/FOCUS_Z.html index 763ca9be..4cfe6c31 100644 --- a/docs/dev/articles/web_only/FOCUS_Z.html +++ b/docs/dev/articles/web_only/FOCUS_Z.html @@ -32,7 +32,7 @@ mkin - 0.9.50.3 + 0.9.50.4
    @@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Example evaluation of FOCUS dataset Z

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/web_only/FOCUS_Z.rmd + Source: vignettes/web_only/FOCUS_Z.rmd
    @@ -115,35 +116,40 @@

    The data

    The following code defines the example dataset from Appendix 7 to the FOCUS kinetics report (FOCUS Work Group on Degradation Kinetics 2014, 354).

    -
    library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
+
    +library(mkin, quietly = TRUE)
+LOD = 0.5
+FOCUS_2006_Z = data.frame(
+  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
+        42, 61, 96, 124),
+  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
+         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
+  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
+         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
 
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
+FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)

    Parent and one metabolite

    The next step is to set up the models used for the kinetic analysis. As the simultaneous fit of parent and the first metabolite is usually straightforward, Step 1 (SFO for parent only) is skipped here. We start with the model 2a, with formation and decline of metabolite Z1 and the pathway from parent directly to sink included (default in mkin).

    -
    Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
    +
    +Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                Z1 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.2a)
    +
    +plot_sep(m.Z.2a)

    -
    summary(m.Z.2a, data = FALSE)$bpar
    +
    +summary(m.Z.2a, data = FALSE)$bpar
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
 ## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
@@ -152,16 +158,20 @@
 ## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815

    As obvious from the parameter summary (the component of the summary), the kinetic rate constant from parent compound Z to sink is very small and the t-test for this parameter suggests that it is not significantly different from zero. This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify the model by removing the pathway to sink.

    A similar result can be obtained when formation fractions are used in the model formulation:

    -
    Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
    +
    +Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                   Z1 = mkinsub("SFO"),
+                   use_of_ff = "max")
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.2a.ff)
    +
    +plot_sep(m.Z.2a.ff)

    -
    summary(m.Z.2a.ff, data = FALSE)$bpar
    +
    +summary(m.Z.2a.ff, data = FALSE)$bpar
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
 ## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
@@ -171,15 +181,19 @@
 
    Here, the ilr transformed formation fraction fitted in the model takes a very large value, and the backtransformed formation fraction from parent Z to Z1 is practically unity. Here, the covariance matrix used for the calculation of confidence intervals is not returned as the model is overparameterised.
    
 
    A simplified model is obtained by removing the pathway to the sink. 
    
 
    In the following, we use the parameterisation with formation fractions in order to be able to compare with the results in the FOCUS guidance, and as it makes it easier to use parameters obtained in a previous fit when adding a further metabolite.
    
-
    Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
+
    +Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    +m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    
-
    plot_sep(m.Z.3)
    
+
    +plot_sep(m.Z.3)
    
 
    
-
    summary(m.Z.3, data = FALSE)$bpar
    
+
    +summary(m.Z.3, data = FALSE)$bpar
    
 
    ##       Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0  97.01488   2.597342  37.352 2.0106e-24 91.67597 102.3538
 ## k_Z0   2.23601   0.146904  15.221 9.1477e-15  1.95354   2.5593
@@ -191,51 +205,59 @@
 
    
 Metabolites Z2 and Z3
    
 
    As suggested in the FOCUS report, the pathway to sink was removed for metabolite Z1 as well in the next step. While this step appears questionable on the basis of the above results, it is followed here for the purpose of comparison. Also, in the FOCUS report, it is assumed that there is additional empirical evidence that Z1 quickly and exclusively hydrolyses to Z2.
    
-
    Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
    
+
    +Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+               Z2 = mkinsub("SFO"), use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    +m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    
-
    plot_sep(m.Z.5)
    
+
    +plot_sep(m.Z.5)
    
 
    
 
    Finally, metabolite Z3 is added to the model. We use the optimised differential equation parameter values from the previous fit in order to accelerate the optimization.
    
-
    Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
    
+
    +Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                   Z2 = mkinsub("SFO", "Z3"),
+                   Z3 = mkinsub("SFO"),
+                   use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
    
+
    +m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
+                     parms.ini = m.Z.5$bparms.ode,
+                     quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, :
 ## Observations with value of zero were removed from the data
    
 
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation did not converge:
 ## false convergence (8)
    
-
    plot_sep(m.Z.FOCUS)
    
+
    +plot_sep(m.Z.FOCUS)
    
 
    
-
    summary(m.Z.FOCUS, data = FALSE)$bpar
    
+
    +summary(m.Z.FOCUS, data = FALSE)$bpar
    
 
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.838721   1.994275 48.5584 4.0283e-42 92.826878 100.850563
-## k_Z0        2.215400   0.118459 18.7019 1.0414e-23  1.989462   2.466998
-## k_Z1        0.478301   0.028257 16.9267 6.2411e-22  0.424705   0.538662
-## k_Z2        0.451623   0.042138 10.7176 1.6313e-14  0.374336   0.544867
-## k_Z3        0.058694   0.015246  3.8499 1.7804e-04  0.034809   0.098967
-## f_Z2_to_Z3  0.471510   0.058352  8.0804 9.6640e-11  0.357775   0.588283
+## Z0_0       96.839001   1.994273 48.5585 4.0276e-42 92.827060 100.850943
+## k_Z0        2.215367   0.118456 18.7021 1.0410e-23  1.989432   2.466960
+## k_Z1        0.478310   0.028258 16.9265 6.2430e-22  0.424712   0.538673
+## k_Z2        0.451628   0.042139 10.7176 1.6313e-14  0.374337   0.544877
+## k_Z3        0.058692   0.015245  3.8498 1.7806e-04  0.034806   0.098972
+## f_Z2_to_Z3  0.471498   0.058350  8.0805 9.6614e-11  0.357741   0.588294
 ## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736
    
-
    endpoints(m.Z.FOCUS)
    
+
    +endpoints(m.Z.FOCUS)
    
 
    ## $ff
 ##   Z2_Z3 Z2_sink 
-## 0.47151 0.52849 
+##  0.4715  0.5285 
 ## 
 ## $distimes
 ##        DT50    DT90
 ## Z0  0.31288  1.0394
-## Z1  1.44919  4.8141
-## Z2  1.53479  5.0985
-## Z3 11.80955 39.2305
    
+## Z1  1.44916  4.8140
+## Z2  1.53478  5.0984
+## Z3 11.80983 39.2314
    
 
    This fit corresponds to the final result chosen in Appendix 7 of the FOCUS report. Confidence intervals returned by mkin are based on internally transformed parameters, however.
    @@ -243,90 +265,101 @@ Using the SFORB model

    As the FOCUS report states, there is a certain tailing of the time course of metabolite Z3. Also, the time course of the parent compound is not fitted very well using the SFO model, as residues at a certain low level remain.

    Therefore, an additional model is offered here, using the single first-order reversible binding (SFORB) model for metabolite Z3. As expected, the \(\chi^2\) error level is lower for metabolite Z3 using this model and the graphical fit for Z3 is improved. However, the covariance matrix is not returned.

    -
    Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    +
    +Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.mkin.1)
    +
    +plot_sep(m.Z.mkin.1)

    -
    summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    +
    +summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    ## NULL

    Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the assumption that the model fit for the parent compound can be improved by using the SFORB model.

    -
    Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
    +
    +Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.mkin.3)
    +
    +plot_sep(m.Z.mkin.3)

    This results in a much better representation of the behaviour of the parent compound Z0.

    Finally, Z3 is added as well. These models appear overparameterised (no covariance matrix returned) if the sink for Z1 is left in the models.

    -
    Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
    +
    +Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
    +
    +m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.3$bparms.ode,
+                      quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
 ## 3$bparms.ode, : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 3$bparms.ode, : Shapiro-Wilk test for standardized residuals: p = 0.0449
    -
    plot_sep(m.Z.mkin.4)
    +
    +plot_sep(m.Z.mkin.4)

    The error level of the fit, but especially of metabolite Z3, can be improved if the SFORB model is chosen for this metabolite, as this model is capable of representing the tailing of the metabolite decline phase.

    -
    Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    +
    +Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
    +
    +m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
+                      quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
 ## 4$bparms.ode[1:4], : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 4$bparms.ode[1:4], : Shapiro-Wilk test for standardized residuals: p = 0.00785
    -
    plot_sep(m.Z.mkin.5)
    +
    +plot_sep(m.Z.mkin.5)

    The summary view of the backtransformed parameters shows that we get no confidence intervals due to overparameterisation. As the optimized is excessively small, it seems reasonable to fix it to zero.

    -
    m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
    +
    +m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
+                                     k_Z3_bound_free = 0),
+                       fixed_parms = "k_Z3_bound_free",
+                       quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = c(m.Z.mkin.
 ## 5$bparms.ode[1:7], : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = c(m.Z.mkin.
-## 5$bparms.ode[1:7], : Shapiro-Wilk test for standardized residuals: p = 0.00785
    -
    plot_sep(m.Z.mkin.5a)
    +
    +plot_sep(m.Z.mkin.5a)

    As expected, the residual plots for Z0 and Z3 are more random than in the case of the all SFO model for which they were shown above. In conclusion, the model is proposed as the best-fit model for the dataset from Appendix 7 of the FOCUS report.

    A graphical representation of the confidence intervals can finally be obtained.

    -
    mkinparplot(m.Z.mkin.5a)
    +
    +mkinparplot(m.Z.mkin.5a)

    The endpoints obtained with this model are

    -
    endpoints(m.Z.mkin.5a)
    +
    +endpoints(m.Z.mkin.5a)
    ## $ff
 ## Z0_free   Z2_Z3 Z2_sink Z3_free 
 ## 1.00000 0.53656 0.46344 1.00000 
 ## 
 ## $SFORB
 ##     Z0_b1     Z0_b2     Z3_b1     Z3_b2 
-## 2.4471358 0.0075126 0.0800073 0.0000000 
+## 2.4471371 0.0075126 0.0800070 0.0000000 
 ## 
 ## $distimes
 ##      DT50   DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
 ## Z0 0.3043 1.1848  0.35666    0.28325     92.265         NA         NA
 ## Z1 1.5148 5.0320       NA         NA         NA         NA         NA
-## Z2 1.6414 5.4526       NA         NA         NA         NA         NA
+## Z2 1.6414 5.4525       NA         NA         NA         NA         NA
 ## Z3     NA     NA       NA         NA         NA     8.6636        Inf

    It is clear the degradation rate of Z3 towards the end of the experiment is very low as DT50_Z3_b2 (the second Eigenvalue of the system of two differential equations representing the SFORB system for Z3, corresponding to the slower rate constant of the DFOP model) is reported to be infinity. However, this appears to be a feature of the data.

    @@ -357,7 +390,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png index 23d051ce..575def46 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png index d3702fb6..22305ab1 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png index 4a6fce4f..2213f493 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png index dd6537b7..fc5e5556 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png index b986c30b..5c29341c 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png index 23d051ce..575def46 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png index 6e9f4efa..98ce34a7 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png index 146acea9..d04a411e 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png index 47d806c0..29a74490 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png index 7db8b07d..0acfa2a4 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png index 0c698299..ca191b00 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png differ diff --git a/docs/dev/articles/web_only/NAFTA_examples.html b/docs/dev/articles/web_only/NAFTA_examples.html index ebe4b84e..c3192b37 100644 --- a/docs/dev/articles/web_only/NAFTA_examples.html +++ b/docs/dev/articles/web_only/NAFTA_examples.html @@ -95,13 +95,14 @@ -
    + +

    Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance

    Johannes Ranke

    -

    2020-10-15

    +

    2020-11-19

    Source: vignettes/web_only/NAFTA_examples.rmd @@ -123,15 +124,15 @@

    Example on page 5, upper panel

    -
    -p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    +
    +p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p5a)
    +
    +plot(p5a)

    -
    -print(p5a)
    +
    +print(p5a)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 465.21753  56.27506  32.06401 
@@ -157,7 +158,7 @@
 ##          Estimate   Pr(>t)   Lower    Upper
 ## parent_0 9.99e+01 1.41e-26 98.8116 101.0810
 ## k1       2.67e-02 5.05e-06  0.0243   0.0295
-## k2       2.17e-12 5.00e-01  0.0000      Inf
+## k2       2.42e-12 5.00e-01  0.0000      Inf
 ## g        6.47e-01 3.67e-06  0.6248   0.6677
 ## sigma    1.27e+00 8.91e-06  0.8395   1.6929
 ## 
@@ -166,7 +167,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  67.7 2.25e+02 6.77e+01
 ## IORE 58.2 1.07e+03 3.22e+02
-## DFOP 55.5 5.83e+11 3.20e+11
+## DFOP 55.5 5.22e+11 2.86e+11
 ## 
 ## Representative half-life:
 ## [1] 321.51
    @@ -174,15 +175,15 @@

    Example on page 5, lower panel

    -
    -p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    +
    +p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p5b)
    +
    +plot(p5b)

    -
    -print(p5b)
    +
    +print(p5b)
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 94.81123 10.10936  7.55871 
@@ -208,7 +209,7 @@
 ##          Estimate   Pr(>t)   Lower   Upper
 ## parent_0 9.84e+01 1.24e-27 97.8078 98.9187
 ## k1       1.55e-02 4.10e-04  0.0143  0.0167
-## k2       1.04e-11 5.00e-01  0.0000     Inf
+## k2       1.10e-11 5.00e-01  0.0000     Inf
 ## g        6.89e-01 2.92e-03  0.6626  0.7142
 ## sigma    6.48e-01 2.38e-05  0.4147  0.8813
 ## 
@@ -217,7 +218,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  86.6 2.88e+02 8.66e+01
 ## IORE 85.5 7.17e+02 2.16e+02
-## DFOP 83.6 1.09e+11 6.67e+10
+## DFOP 83.6 1.03e+11 6.29e+10
 ## 
 ## Representative half-life:
 ## [1] 215.87
    @@ -225,15 +226,15 @@

    Example on page 6

    -
    -p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    +
    +p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p6)
    +
    +plot(p6)

    -
    -print(p6)
    +
    +print(p6)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 188.45361  51.00699  42.46931 
@@ -259,7 +260,7 @@
 ##          Estimate   Pr(>t)   Lower   Upper
 ## parent_0 9.66e+01 1.57e-25 95.3476 97.8979
 ## k1       2.55e-02 7.33e-06  0.0233  0.0278
-## k2       3.88e-11 5.00e-01  0.0000     Inf
+## k2       3.60e-11 5.00e-01  0.0000     Inf
 ## g        8.61e-01 7.55e-06  0.8314  0.8867
 ## sigma    1.46e+00 6.93e-06  0.9661  1.9483
 ## 
@@ -268,7 +269,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  38.6 1.28e+02 3.86e+01
 ## IORE 34.0 1.77e+02 5.32e+01
-## DFOP 34.1 8.42e+09 1.79e+10
+## DFOP 34.1 9.07e+09 1.93e+10
 ## 
 ## Representative half-life:
 ## [1] 53.17
    @@ -276,15 +277,15 @@

    Example on page 7

    -
    -p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    +
    +p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p7)
    +
    +plot(p7)

    -
    -print(p7)
    +
    +print(p7)
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3661.661 3195.030 3174.145 
@@ -310,7 +311,7 @@
 ##          Estimate   Pr(>t)   Lower    Upper
 ## parent_0 9.89e+01 9.44e-49 95.4640 102.2573
 ## k1       1.81e-02 1.75e-01  0.0116   0.0281
-## k2       2.30e-10 5.00e-01  0.0000      Inf
+## k2       2.89e-10 5.00e-01  0.0000      Inf
 ## g        6.06e-01 2.19e-01  0.4826   0.7178
 ## sigma    7.40e+00 2.97e-15  6.0201   8.7754
 ## 
@@ -319,7 +320,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  94.3 3.13e+02 9.43e+01
 ## IORE 96.7 1.51e+03 4.55e+02
-## DFOP 96.4 5.95e+09 3.01e+09
+## DFOP 96.4 4.75e+09 2.40e+09
 ## 
 ## Representative half-life:
 ## [1] 454.55
    @@ -332,15 +333,15 @@

    Example on page 8

    For this dataset, the IORE fit does not converge when the default starting values used by mkin for the IORE model are used. Therefore, a lower value for the rate constant is used here.

    -
    -p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    +
    +p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p8)
    +
    +plot(p8)

    -
    -print(p8)
    +
    +print(p8)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 1996.9408  444.9237  547.5616 
@@ -387,15 +388,15 @@
 
    
 
    
 Example on page 9, upper panel
    
-
    -p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    
+
    +p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9a)
    
+
    +plot(p9a)
    
 
    
-
    -print(p9a)
    
+
    +print(p9a)
    
 
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 839.35238  88.57064   9.93363 
@@ -421,7 +422,7 @@
 ##          Estimate   Pr(>t)  Lower  Upper
 ## parent_0 9.85e+01 2.54e-20 97.390 99.672
 ## k1       1.38e-01 3.52e-05  0.131  0.146
-## k2       6.69e-13 5.00e-01  0.000    Inf
+## k2       9.03e-13 5.00e-01  0.000    Inf
 ## g        6.52e-01 8.13e-06  0.642  0.661
 ## sigma    7.88e-01 6.13e-02  0.481  1.095
 ## 
@@ -430,7 +431,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  16.9 5.63e+01 1.69e+01
 ## IORE 11.6 3.37e+02 1.01e+02
-## DFOP 10.5 1.86e+12 1.04e+12
+## DFOP 10.5 1.38e+12 7.67e+11
 ## 
 ## Representative half-life:
 ## [1] 101.43
    
@@ -439,15 +440,19 @@
 
    
 
    
 Example on page 9, lower panel
    
-
    -p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    
+
    +p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    
+
    ## Warning in sqrt(diag(covar)): NaNs produced
    
+
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
+
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9b)
    
+
    +plot(p9b)
    
 
    
-
    -print(p9b)
    
+
    +print(p9b)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 35.64867 23.22334 35.64867 
@@ -470,12 +475,12 @@
 ## sigma             1.288 1.76e-04  0.7456  1.830
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7123 1.61e-16 93.1355 96.2891
-## k1         0.0389 1.43e-06  0.0312  0.0485
-## k2         0.0389 6.67e-03  0.0186  0.0812
-## g          0.7742 5.00e-01  0.0000  1.0000
-## sigma      1.5957 2.50e-04  0.9135  2.2779
+##          Estimate Pr(>t)   Lower   Upper
+## parent_0  94.7123     NA 93.1355 96.2891
+## k1         0.0389     NA  0.0266  0.0569
+## k2         0.0389     NA  0.0255  0.0592
+## g          0.5256     NA      NA      NA
+## sigma      1.5957     NA  0.9135  2.2779
 ## 
 ## 
 ## DTx values:
@@ -491,15 +496,16 @@
 
    
 
    
 Example on page 10
    
-
    -p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    
+
    +p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    
+
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p10)
    
+
    +plot(p10)
    
 
    
-
    -print(p10)
    
+
    +print(p10)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 899.4089 336.4348 899.4089 
@@ -522,12 +528,12 @@
 ## sigma              4.90 1.77e-04  2.837   6.968
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 101.7315 1.41e-09 91.6534 111.810
-## k1         0.0495 6.48e-04  0.0303   0.081
-## k2         0.0495 1.67e-02  0.0201   0.122
-## g          0.6634 5.00e-01  0.0000   1.000
-## sigma      8.0152 2.50e-04  4.5886  11.442
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 101.7315 1.41e-09 91.6534 111.8097
+## k1         0.0495 5.63e-03  0.0240   0.1020
+## k2         0.0495 1.93e-03  0.0272   0.0903
+## g          0.4487      NaN  0.0000   1.0000
+## sigma      8.0152 2.50e-04  4.5886  11.4418
 ## 
 ## 
 ## DTx values:
@@ -547,15 +553,15 @@
 
    
 
    
 Example on page 11
    
-
    -p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    
+
    +p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p11)
    
+
    +plot(p11)
    
 
    
-
    -print(p11)
    
+
    +print(p11)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 579.6805 204.7932 144.7783 
@@ -581,7 +587,7 @@
 ##          Estimate   Pr(>t)    Lower    Upper
 ## parent_0 1.05e+02 9.47e-13  99.9990 109.1224
 ## k1       4.41e-02 5.95e-03   0.0296   0.0658
-## k2       7.25e-13 5.00e-01   0.0000      Inf
+## k2       9.94e-13 5.00e-01   0.0000      Inf
 ## g        3.22e-01 1.45e-03   0.2814   0.3650
 ## sigma    3.22e+00 3.52e-04   1.8410   4.5906
 ## 
@@ -590,7 +596,7 @@
 ##          DT50     DT90 DT50_rep
 ## SFO  2.16e+02 7.18e+02 2.16e+02
 ## IORE 9.73e+02 1.37e+08 4.11e+07
-## DFOP 4.21e+11 2.64e+12 9.56e+11
+## DFOP 3.07e+11 1.93e+12 6.97e+11
 ## 
 ## Representative half-life:
 ## [1] 41148171
    
@@ -604,17 +610,20 @@
 
    
 
    
 Example on page 12, upper panel
    
-
    -p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    
+
    +p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    
 
    ## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
+## matrix
+
+## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
 ## matrix
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12a)
    
+
    +plot(p12a)
    
 
    
-
    -print(p12a)
    
+
    +print(p12a)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 695.4440 220.0685 695.4440 
@@ -637,12 +646,12 @@
 ## sigma             3.965     NA    NA    NA
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  100.521 2.74e-10 92.2366 108.805
-## k1          0.124 5.75e-06  0.0958   0.161
-## k2          0.124 6.72e-02  0.0319   0.484
-## g           0.877 5.00e-01  0.0000   1.000
-## sigma       7.048 2.50e-04  4.0349  10.061
+##          Estimate   Pr(>t) Lower Upper
+## parent_0  100.521 2.74e-10    NA    NA
+## k1          0.124 2.53e-05    NA    NA
+## k2          0.124 2.52e-02    NA    NA
+## g           0.793 5.00e-01    NA    NA
+## sigma       7.048 2.50e-04    NA    NA
 ## 
 ## 
 ## DTx values:
@@ -657,23 +666,21 @@
 
    
 
    
 Example on page 12, lower panel
    
-
    -p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    
+
    +p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in qt(alpha/2, rdf): NaNs produced
    
 
    ## Warning in qt(1 - alpha/2, rdf): NaNs produced
    
-
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
-
    ## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12b)
    
+
    +plot(p12b)
    
 
    
-
    -print(p12b)
    
+
    +print(p12b)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 58.90242 19.06353 58.90242 
@@ -697,11 +704,11 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t) Lower Upper
-## parent_0  97.6840    NaN   NaN   NaN
-## k1         0.0589    NaN    NA    NA
-## k2         0.0589    NaN    NA    NA
-## g          0.6902    NaN    NA    NA
-## sigma      3.4323    NaN   NaN   NaN
+## parent_0  97.6840     NA   NaN   NaN
+## k1         0.0589     NA    NA    NA
+## k2         0.0589     NA    NA    NA
+## g          0.6473     NA    NA    NA
+## sigma      3.4323     NA   NaN   NaN
 ## 
 ## 
 ## DTx values:
@@ -716,15 +723,19 @@
 
    
 
    
 Example on page 13
    
-
    -p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    
+
    +p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    
+
    ## Warning in sqrt(diag(covar)): NaNs produced
    
+
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
+
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p13)
    
+
    +plot(p13)
    
 
    
-
    -print(p13)
    
+
    +print(p13)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 174.5971 142.3951 174.5971 
@@ -747,12 +758,12 @@
 ## sigma            3.0811 9.64e-05  1.84296  4.319
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 92.73500 9.25e-15 8.95e+01 9.59e+01
-## k1        0.00258 4.28e-01 1.45e-08 4.61e+02
-## k2        0.00258 3.69e-08 2.20e-03 3.03e-03
-## g         0.00442 5.00e-01 0.00e+00 1.00e+00
-## sigma     3.41172 1.35e-04 2.02e+00 4.80e+00
+##          Estimate Pr(>t)    Lower    Upper
+## parent_0 92.73500     NA 8.95e+01 95.92118
+## k1        0.00258     NA 4.25e-04  0.01569
+## k2        0.00258     NA 1.76e-03  0.00379
+## g         0.16452     NA       NA       NA
+## sigma     3.41172     NA 2.02e+00  4.79960
 ## 
 ## 
 ## DTx values:
@@ -768,19 +779,19 @@
 
    
 
    
 DT50 not observed in the study and DFOP problems in PestDF
    
-
    -p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    
+
    +p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p14)
    
+
    +plot(p14)
    
 
    
-
    -print(p14)
    
+
    +print(p14)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 48.43249 28.67746 27.26248 
@@ -806,7 +817,7 @@
 ##          Estimate   Pr(>t)    Lower    Upper
 ## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
 ## k1       9.53e-03 1.20e-01  0.00638   0.0143
-## k2       7.70e-12 5.00e-01  0.00000      Inf
+## k2       5.33e-12 5.00e-01  0.00000      Inf
 ## g        3.98e-01 2.19e-01  0.30481   0.4998
 ## sigma    1.17e+00 7.68e-06  0.77406   1.5610
 ## 
@@ -815,7 +826,7 @@
 ##          DT50     DT90 DT50_rep
 ## SFO  2.48e+02 8.25e+02 2.48e+02
 ## IORE 4.34e+02 2.22e+04 6.70e+03
-## DFOP 2.41e+10 2.33e+11 9.00e+10
+## DFOP 3.48e+10 3.37e+11 1.30e+11
 ## 
 ## Representative half-life:
 ## [1] 6697.44
    
@@ -824,19 +835,15 @@
 
    
 
    
 N is less than 1 and DFOP fraction parameter is below zero
    
-
    -p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    
+
    +p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15a)
    
+
    +plot(p15a)
    
 
    
-
    -print(p15a)
    
+
    +print(p15a)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 245.5248 135.0132 245.5248 
@@ -860,10 +867,10 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t)    Lower    Upper
-## parent_0 97.96752     NA 94.21914 101.7159
-## k1        0.00952     NA  0.00241   0.0377
-## k2        0.00952     NA  0.00747   0.0121
-## g         0.17247     NA       NA       NA
+## parent_0 97.96751     NA 94.21913 101.7159
+## k1        0.00952     NA  0.00221   0.0411
+## k2        0.00952     NA  0.00626   0.0145
+## g         0.21241     NA  0.00000   1.0000
 ## sigma     4.18778     NA  2.39747   5.9781
 ## 
 ## 
@@ -875,19 +882,19 @@
 ## 
 ## Representative half-life:
 ## [1] 41.33
    
-
    -p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    
+
    +p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15b)
    
+
    +plot(p15b)
    
 
    
-
    -print(p15b)
    
+
    +print(p15b)
    
 
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 106.91629  68.55574 106.91629 
@@ -911,11 +918,11 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t)    Lower    Upper
-## parent_0 1.01e+02     NA 98.24464 1.04e+02
-## k1       4.86e-03     NA  0.00068 3.47e-02
-## k2       4.86e-03     NA  0.00338 6.99e-03
-## g        1.50e-01     NA       NA       NA
-## sigma    2.76e+00     NA  1.58208 3.94e+00
+## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
+## k1       4.86e-03     NA 8.63e-04 2.73e-02
+## k2       4.86e-03     NA 3.21e-03 7.35e-03
+## g        1.88e-01     NA       NA       NA
+## sigma    2.76e+00     NA 1.58e+00 3.94e+00
 ## 
 ## 
 ## DTx values:
@@ -931,17 +938,17 @@
 
    
 
    
 The DFOP fraction parameter is greater than 1
    
-
    -p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    
+
    +p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The representative half-life of the IORE model is longer than the one corresponding
    
 
    ## to the terminal degradation rate found with the DFOP model.
    
 
    ## The representative half-life obtained from the DFOP model may be used
    
-
    -plot(p16)
    
+
    +plot(p16)
    
 
    
-
    -print(p16)
    
+
    +print(p16)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3831.804 2062.008 1550.980 
@@ -966,7 +973,7 @@
 ## $DFOP
 ##          Estimate   Pr(>t)   Lower  Upper
 ## parent_0  88.5333 7.40e-18 79.9836 97.083
-## k1        18.5560 5.00e-01  0.0000    Inf
+## k1        18.8461 5.00e-01  0.0000    Inf
 ## k2         0.0776 1.41e-05  0.0518  0.116
 ## g          0.4733 1.41e-09  0.3674  0.582
 ## sigma      7.1902 2.11e-08  5.2785  9.102
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png
index 3e9c743f..38b251ea 100644
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diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png
index 029e6a17..ce177190 100644
Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p13-1.png differ
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png
index 24cb27d8..c5759a5b 100644
Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png differ
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png
index f3fa460e..b61f28e2 100644
Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png differ
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png
index d6ae1fa4..515e9095 100644
Binary files a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png and b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png differ
diff --git a/docs/dev/articles/web_only/benchmarks.html b/docs/dev/articles/web_only/benchmarks.html
index 5105afcd..ff70847e 100644
--- a/docs/dev/articles/web_only/benchmarks.html
+++ b/docs/dev/articles/web_only/benchmarks.html
@@ -102,7 +102,7 @@
       
    Benchmark timings for mkin
    
                         
    Johannes Ranke
    
             
-            
    2020-11-06
    
+            
    2020-11-19
    
       
       Source: vignettes/web_only/benchmarks.rmd
       
@@ -116,17 +116,17 @@
 
    
 Test cases
    
 
    Parent only:
    
-
    -FOCUS_C <- FOCUS_2006_C
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
+
    +FOCUS_C <- FOCUS_2006_C
+FOCUS_D <- subset(FOCUS_2006_D, value != 0)
 parent_datasets <- list(FOCUS_C, FOCUS_D)
 
 t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets))[["elapsed"]]
 t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets,
-    error_model = "tc"))[["elapsed"]]
    
+    error_model = "tc"))[["elapsed"]]
    
 
    One metabolite:
    
-
    -SFO_SFO <- mkinmod(
+
    +SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))
 FOMC_SFO <- mkinmod(
@@ -137,18 +137,18 @@
   m1 = mkinsub("SFO"))
 t3 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D)))[["elapsed"]]
 t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "tc"))[["elapsed"]]
    
+    error_model = "tc"))[["elapsed"]]
    
 
    ## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...): Optimisation did not converge:
 ## iteration limit reached without convergence (10)
 
 ## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...): Optimisation did not converge:
 ## iteration limit reached without convergence (10)
    
-
    -t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "obs"))[["elapsed"]]
    
+
    +t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
+    error_model = "obs"))[["elapsed"]]
    
 
    Two metabolites, synthetic data:
    
-
    -m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
+
    +m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
                            M1 = mkinsub("SFO", "M2"),
                            M2 = mkinsub("SFO"),
                            use_of_ff = "max", quiet = TRUE)
@@ -173,11 +173,11 @@
 t10 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a),
     error_model = "obs"))[["elapsed"]]
 t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c),
-    error_model = "obs"))[["elapsed"]]
    
-
    -mkin_benchmarks[system_string, paste0("t", 1:11)] <-
+    error_model = "obs"))[["elapsed"]]
    
+
    +mkin_benchmarks[system_string, paste0("t", 1:11)] <-
   c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11)
-save(mkin_benchmarks, file = "~/git/mkin/vignettes/web_only/mkin_benchmarks.rda")
    
+save(mkin_benchmarks, file = "~/git/mkin/vignettes/web_only/mkin_benchmarks.rda")
    
 
    
 
    
 
    
@@ -232,8 +232,8 @@
 
 
 0.9.50.4
-1.753
-3.791
+1.702
+3.717
 
 
 
@@ -294,9 +294,9 @@
 
 
 0.9.50.4
-1.374
-6.974
-2.735
+1.355
+7.015
+2.729
 
 
 
@@ -381,12 +381,12 @@
 
 
 0.9.50.4
-0.766
-1.250
+0.759
+1.245
 1.436
-3.749
-1.878
-2.879
+3.687
+1.886
+3.028
 
 
 
diff --git a/docs/dev/articles/web_only/compiled_models.html b/docs/dev/articles/web_only/compiled_models.html
index 055d0646..3d1c7fcd 100644
--- a/docs/dev/articles/web_only/compiled_models.html
+++ b/docs/dev/articles/web_only/compiled_models.html
@@ -32,7 +32,7 @@
       
       
         mkin
-        0.9.50.3
+        0.9.50.4
       
     
    
 
@@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Performance benefit by using compiled model definitions in mkin

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/web_only/compiled_models.rmd + Source: vignettes/web_only/compiled_models.rmd
    @@ -114,79 +115,86 @@

    How to benefit from compiled models

    When using an mkin version equal to or greater than 0.9-36 and a C compiler is available, you will see a message that the model is being compiled from autogenerated C code when defining a model using mkinmod. Starting from version 0.9.49.9, the mkinmod() function checks for presence of a compiler using

    -
    pkgbuild::has_compiler()
    +
    +pkgbuild::has_compiler()

    In previous versions, it used Sys.which("gcc") for this check.

    On Linux, you need to have the essential build tools like make and gcc or clang installed. On Debian based linux distributions, these will be pulled in by installing the build-essential package.

    On MacOS, which I do not use personally, I have had reports that a compiler is available by default.

    On Windows, you need to install Rtools and have the path to its bin directory in your PATH variable. You do not need to modify the PATH variable when installing Rtools. Instead, I would recommend to put the line

    -
    Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))
    +
    +Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))

    into your .Rprofile startup file. This is just a text file with some R code that is executed when your R session starts. It has to be named .Rprofile and has to be located in your home directory, which will generally be your Documents folder. You can check the location of the home directory used by R by issuing

    -
    Sys.getenv("HOME")
    +
    +Sys.getenv("HOME")

    Comparison with other solution methods

    First, we build a simple degradation model for a parent compound with one metabolite, and we remove zero values from the dataset.

    -
    library("mkin", quietly = TRUE)
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    +
    +library("mkin", quietly = TRUE)
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    FOCUS_D <- subset(FOCUS_2006_D, value != 0)
    +
    +FOCUS_D <- subset(FOCUS_2006_D, value != 0)

    We can compare the performance of the Eigenvalue based solution against the compiled version and the R implementation of the differential equations using the benchmark package. In the output of below code, the warnings about zero being removed from the FOCUS D dataset are suppressed. Since mkin version 0.9.49.11, an analytical solution is also implemented, which is included in the tests below.

    -
    if (require(rbenchmark)) {
-  b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve",
-       use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve", quiet = TRUE),
-    "analytical" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "analytical",
-       use_compiled = FALSE, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.1)
-} else {
-  print("R package rbenchmark is not available")
-}
    +
    +if (require(rbenchmark)) {
+  b.1 <- benchmark(
+    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "deSolve",
+       use_compiled = FALSE, quiet = TRUE),
+    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "eigen", quiet = TRUE),
+    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "deSolve", quiet = TRUE),
+    "analytical" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "analytical",
+       use_compiled = FALSE, quiet = TRUE),
+    replications = 1, order = "relative",
+    columns = c("test", "replications", "relative", "elapsed"))
+  print(b.1)
+} else {
+  print("R package rbenchmark is not available")
+}
    ##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.195
-## 3     deSolve, compiled            1    1.769   0.345
-## 2      Eigenvalue based            1    2.087   0.407
-## 1 deSolve, not compiled            1   42.656   8.318
    +## 4 analytical 1 1.000 0.186 +## 3 deSolve, compiled 1 1.742 0.324 +## 2 Eigenvalue based 1 2.048 0.381 +## 1 deSolve, not compiled 1 42.532 7.911

    We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.

    Model without analytical solution

    This evaluation is also taken from the example section of mkinfit. No analytical solution is available for this system, and now Eigenvalue based solution is possible, so only deSolve using with or without compiled code is available.

    -
    if (require(rbenchmark)) {
-  FOMC_SFO <- mkinmod(
-    parent = mkinsub("FOMC", "m1"),
-    m1 = mkinsub( "SFO"))
-
-  b.2 <- benchmark(
-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
-                                      use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
-} else {
-  factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
-}
    +
    +if (require(rbenchmark)) {
+  FOMC_SFO <- mkinmod(
+    parent = mkinsub("FOMC", "m1"),
+    m1 = mkinsub( "SFO"))
+
+  b.2 <- benchmark(
+    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
+                                      use_compiled = FALSE, quiet = TRUE),
+    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE),
+    replications = 1, order = "relative",
+    columns = c("test", "replications", "relative", "elapsed"))
+  print(b.2)
+  factor_FOMC_SFO <- round(b.2["1", "relative"])
+} else {
+  factor_FOMC_SFO <- NA
+  print("R package benchmark is not available")
+}
    ## Successfully compiled differential equation model from auto-generated C code.
    ##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.474
-## 1 deSolve, not compiled            1   30.909  14.651
    +## 2 deSolve, compiled 1 1.000 0.465 +## 1 deSolve, not compiled 1 30.852 14.346

    Here we get a performance benefit of a factor of 31 using the version of the differential equation model compiled from C code!

    -

    This vignette was built with mkin 0.9.50.3 on

    -
    ## R version 4.0.2 (2020-06-22)
+
    This vignette was built with mkin 0.9.50.4 on
    
+
    ## R version 4.0.3 (2020-10-10)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 10 (buster)
    
 
    ## CPU model: AMD Ryzen 7 1700 Eight-Core Processor
    
@@ -208,7 +216,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); -- cgit v1.2.1