diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-12 16:34:00 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-12 16:34:00 +0200 |
| commit | 6211f3ef4995657798686d8d4ab43ed9406e8a08 (patch) | |
| tree | 4be80cf595880876d51c9cb85f07464b99bc8c83 /vignettes | |
| parent | c7fcc2f8af47e95cf6164c00a4902340624c13dc (diff) | |
Update vignettes and docs
Diffstat (limited to 'vignettes')
| -rw-r--r-- | vignettes/mkin_benchmarks.rda | bin | 882 -> 0 bytes | |||
| -rw-r--r-- | vignettes/web_only/benchmarks.Rmd | 97 | ||||
| -rw-r--r-- | vignettes/web_only/benchmarks.html | 179 | ||||
| -rw-r--r-- | vignettes/web_only/compiled_models.Rmd | 54 | ||||
| -rw-r--r-- | vignettes/web_only/compiled_models.html | 81 | ||||
| -rw-r--r-- | vignettes/web_only/mkin_benchmarks.rda | bin | 797 -> 885 bytes |
6 files changed, 225 insertions, 186 deletions
diff --git a/vignettes/mkin_benchmarks.rda b/vignettes/mkin_benchmarks.rda Binary files differdeleted file mode 100644 index dbd65850..00000000 --- a/vignettes/mkin_benchmarks.rda +++ /dev/null diff --git a/vignettes/web_only/benchmarks.Rmd b/vignettes/web_only/benchmarks.Rmd index cc28735a..27f5d366 100644 --- a/vignettes/web_only/benchmarks.Rmd +++ b/vignettes/web_only/benchmarks.Rmd @@ -1,5 +1,5 @@ --- -title: "Benchmark timings for mkin on various systems" +title: "Benchmark timings for mkin" author: "Johannes Ranke" output: html_document: @@ -19,10 +19,8 @@ opts_chunk$set(tidy = FALSE, cache = FALSE) library("mkin") ``` -## Systems - Each system is characterized by its CPU type, the operating system type and the -mkin version. +mkin version. Currently only values for one system are available. ```{r} cpu_model <- benchmarkme::get_cpu()$model_name @@ -30,23 +28,37 @@ operating_system <- Sys.info()[["sysname"]] mkin_version <- as.character(packageVersion("mkin")) system_string <- paste0(operating_system, ", ", cpu_model, ", mkin version ", mkin_version) load("~/git/mkin/vignettes/web_only/mkin_benchmarks.rda") -mkin_benchmarks[system_string, c("CPU", "OS", "mkin")] <- c(cpu_model, operating_system, mkin_version) +mkin_benchmarks[system_string, c("CPU", "OS", "mkin")] <- + c(cpu_model, operating_system, mkin_version) if (mkin_version > "0.9.48.1") { - mmkin_bench <- function(models, datasets, error_model = "const") mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + mmkin_bench <- function(models, datasets, error_model = "const") { + mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + } } else { - mmkin_bench <- function(models, datasets, error_model = NULL) mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + mmkin_bench <- function(models, datasets, error_model = NULL) { + mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + } } ``` -```{r timings} +## Test cases + +Parent only: + +```{r parent_only, warning = FALSE} FOCUS_C <- FOCUS_2006_C FOCUS_D <- subset(FOCUS_2006_D, value != 0) -# Parent only -t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_C, FOCUS_D)))[["elapsed"]] -t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_C, FOCUS_D), error_model = "tc"))[["elapsed"]] +parent_datasets <- list(FOCUS_C, FOCUS_D) -# One metabolite +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"]] +``` + +One metabolite: + +```{r one_metabolite} SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO")) @@ -57,10 +69,15 @@ DFOP_SFO <- mkinmod( parent = mkinsub("FOMC", "m1"), 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"]] -t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D), error_model = "obs"))[["elapsed"]] +t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D), + error_model = "tc"))[["elapsed"]] +t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D), + error_model = "obs"))[["elapsed"]] +``` -# Two metabolites, synthetic data +Two metabolites, synthetic data: + +```{r two_metabolites} m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"), M1 = mkinsub("SFO", "M2"), M2 = mkinsub("SFO"), @@ -78,15 +95,51 @@ DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data t6 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a)))["elapsed"] t7 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c)))["elapsed"] -t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), error_model = "tc"))["elapsed"] -t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "tc"))["elapsed"] +t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), + error_model = "tc"))["elapsed"] +t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), + error_model = "tc"))["elapsed"] + +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"] +``` + +```{r results} +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") +``` + +## Results -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"] +Currently, we only have benchmark information on one system, therefore only the mkin +version is shown with the results below. Timings are in seconds, shorter is better. -mkin_benchmarks[system_string, paste0("t", 1:11)] <- c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11) -mkin_benchmarks[, -c(1:3)] +Benchmarks for all available error models are shown. +### Parent only -save(mkin_benchmarks, file = "~/git/mkin/vignettes/mkin_benchmarks.rda") +Constant variance and two-component error model: + +```{r} +print(mkin_benchmarks[, c("mkin", "t1", "t2")], row.names = FALSE) +``` + +### One metabolite + +Constant variance, variance by variable and two-component error model: + +```{r} +print(mkin_benchmarks[, c("mkin", "t3", "t4", "t5")], row.names = FALSE) +``` + +### Two metabolites + +Two different datasets, for each constant variance, variance by variable and +two-component error model are shown: + +```{r} +print(mkin_benchmarks[, c("mkin", paste0("t", 6:11))], row.names = FALSE) ``` diff --git a/vignettes/web_only/benchmarks.html b/vignettes/web_only/benchmarks.html index 337ccbb3..5c9cc67e 100644 --- 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c){try{c="true"===c?!0:"false"===c?!1:"null"===c?null:+c+""===c?+c:M.test(c)?m.parseJSON(c):c}catch(e){}m.data(a,b,c)}else c=void 0}return c}function P(a){var b;for(b in a)if(("data"!==b||!m.isEmptyObject(a[b]))&&"toJSON"!==b)return!1; @@ -1581,40 +1581,43 @@ div.tocify { -<h1 class="title toc-ignore">Benchmark timings for mkin on various systems</h1> +<h1 class="title toc-ignore">Benchmark timings for mkin</h1> <h4 class="author">Johannes Ranke</h4> -<h4 class="date">2020-05-11</h4> +<h4 class="date">2020-05-12</h4> </div> -<div id="systems" class="section level2"> -<h2>Systems</h2> -<p>Each system is characterized by its CPU type, the operating system type and the mkin version.</p> +<p>Each system is characterized by its CPU type, the operating system type and the mkin version. Currently only values for one system are available.</p> <pre class="r"><code>cpu_model <- benchmarkme::get_cpu()$model_name operating_system <- Sys.info()[["sysname"]] mkin_version <- as.character(packageVersion("mkin")) system_string <- paste0(operating_system, ", ", cpu_model, ", mkin version ", mkin_version) load("~/git/mkin/vignettes/web_only/mkin_benchmarks.rda") -mkin_benchmarks[system_string, c("CPU", "OS", "mkin")] <- c(cpu_model, operating_system, mkin_version) +mkin_benchmarks[system_string, c("CPU", "OS", "mkin")] <- + c(cpu_model, operating_system, mkin_version) if (mkin_version > "0.9.48.1") { - mmkin_bench <- function(models, datasets, error_model = "const") mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + mmkin_bench <- function(models, datasets, error_model = "const") { + mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + } } else { - mmkin_bench <- function(models, datasets, error_model = NULL) mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + mmkin_bench <- function(models, datasets, error_model = NULL) { + mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + } }</code></pre> +<div id="test-cases" class="section level2"> +<h2>Test cases</h2> +<p>Parent only:</p> <pre class="r"><code>FOCUS_C <- FOCUS_2006_C FOCUS_D <- subset(FOCUS_2006_D, value != 0) -# Parent only -t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_C, FOCUS_D)))[["elapsed"]] -t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), list(FOCUS_C, FOCUS_D), error_model = "tc"))[["elapsed"]]</code></pre> -<pre><code>## 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)</code></pre> -<pre class="r"><code># One metabolite -SFO_SFO <- mkinmod( +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"]]</code></pre> +<p>One metabolite:</p> +<pre class="r"><code>SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))</code></pre> <pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre> @@ -1627,11 +1630,12 @@ SFO_SFO <- mkinmod( m1 = mkinsub("SFO"))</code></pre> <pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre> <pre class="r"><code>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"]] -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"), +t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D), + error_model = "tc"))[["elapsed"]] +t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D), + error_model = "obs"))[["elapsed"]]</code></pre> +<p>Two metabolites, synthetic data:</p> +<pre class="r"><code>m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"), M1 = mkinsub("SFO", "M2"), M2 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) @@ -1648,78 +1652,59 @@ DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data t6 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a)))["elapsed"] t7 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c)))["elapsed"] -t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), error_model = "tc"))["elapsed"] -t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "tc"))["elapsed"] - -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)] <- c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11) -mkin_benchmarks[, -c(1:3)]</code></pre> -<pre><code>## t1 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.610 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 8.184 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.064 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.296 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.936 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 1.678 -## t2 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 11.019 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 22.889 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 12.558 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 21.239 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 20.545 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 3.837 -## t3 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.764 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.649 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.786 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.510 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.446 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 1.372 -## t4 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 14.347 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 13.789 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 8.461 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 13.805 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 15.335 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 6.071 -## t5 t6 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 9.495 2.623 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 6.395 2.542 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.675 2.723 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.386 2.643 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 6.002 2.635 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 2.709 0.746 -## t7 t8 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 4.587 7.525 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.128 4.632 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.478 4.862 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.374 7.02 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.259 4.737 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 1.208 1.268 -## t9 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 16.621 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 8.171 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.618 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 11.124 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 7.763 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 2.836 -## t10 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 8.576 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 3.676 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 3.579 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 5.388 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 3.427 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 2.019 -## t11 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 31.267 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 5.636 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.574 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.365 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.626 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.50 2.951</code></pre> -<pre class="r"><code>save(mkin_benchmarks, file = "~/git/mkin/vignettes/mkin_benchmarks.rda")</code></pre> +t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), + error_model = "tc"))["elapsed"] +t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), + error_model = "tc"))["elapsed"] + +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"]</code></pre> +<pre class="r"><code>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")</code></pre> +</div> +<div id="results" class="section level2"> +<h2>Results</h2> +<p>Currently, we only have benchmark information on one system, therefore only the mkin version is shown with the results below. Timings are in seconds, shorter is better.</p> +<p>Benchmarks for all available error models are shown.</p> +<div id="parent-only" class="section level3"> +<h3>Parent only</h3> +<p>Constant variance and two-component error model:</p> +<pre class="r"><code>print(mkin_benchmarks[, c("mkin", "t1", "t2")], row.names = FALSE)</code></pre> +<pre><code>## mkin t1 t2 +## 0.9.48.1 3.610 11.019 +## 0.9.49.1 8.184 22.889 +## 0.9.49.2 7.064 12.558 +## 0.9.49.3 7.296 21.239 +## 0.9.49.4 5.936 20.545 +## 0.9.50.2 1.547 3.955</code></pre> +</div> +<div id="one-metabolite" class="section level3"> +<h3>One metabolite</h3> +<p>Constant variance, variance by variable and two-component error model:</p> +<pre class="r"><code>print(mkin_benchmarks[, c("mkin", "t3", "t4", "t5")], row.names = FALSE)</code></pre> +<pre><code>## mkin t3 t4 t5 +## 0.9.48.1 3.764 14.347 9.495 +## 0.9.49.1 4.649 13.789 6.395 +## 0.9.49.2 4.786 8.461 5.675 +## 0.9.49.3 4.510 13.805 7.386 +## 0.9.49.4 4.446 15.335 6.002 +## 0.9.50.2 1.379 6.176 2.713</code></pre> +</div> +<div id="two-metabolites" class="section level3"> +<h3>Two metabolites</h3> +<p>Two different datasets, for each constant variance, variance by variable and two-component error model are shown:</p> +<pre class="r"><code>print(mkin_benchmarks[, c("mkin", paste0("t", 6:11))], row.names = FALSE)</code></pre> +<pre><code>## mkin t6 t7 t8 t9 t10 t11 +## 0.9.48.1 2.623 4.587 7.525 16.621 8.576 31.267 +## 0.9.49.1 2.542 4.128 4.632 8.171 3.676 5.636 +## 0.9.49.2 2.723 4.478 4.862 7.618 3.579 5.574 +## 0.9.49.3 2.643 4.374 7.02 11.124 5.388 7.365 +## 0.9.49.4 2.635 4.259 4.737 7.763 3.427 5.626 +## 0.9.50.2 0.742 1.202 1.269 2.97 2.028 2.959</code></pre> +</div> </div> diff --git a/vignettes/web_only/compiled_models.Rmd b/vignettes/web_only/compiled_models.Rmd index 3f4e0097..f99ea808 100644 --- a/vignettes/web_only/compiled_models.Rmd +++ b/vignettes/web_only/compiled_models.Rmd @@ -56,51 +56,56 @@ issuing Sys.getenv("HOME")
```
-## Comparison with Eigenvalue based solutions
+## Comparison with other solution methods
-First, we build a simple degradation model for a parent compound with one metabolite.
+First, we build a simple degradation model for a parent compound with one metabolite,
+and we remove zero values from the dataset.
```{r create_SFO_SFO}
library("mkin", quietly = TRUE)
SFO_SFO <- mkinmod(
parent = mkinsub("SFO", "m1"),
m1 = mkinsub("SFO"))
+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.
+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.
```{r benchmark_SFO_SFO, fig.height = 3, message = FALSE, warning = FALSE}
if (require(rbenchmark)) {
b.1 <- benchmark(
- "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
- solution_type = "deSolve",
- use_compiled = FALSE, quiet = TRUE),
- "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
- solution_type = "eigen", quiet = TRUE),
- "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
- solution_type = "deSolve", quiet = TRUE),
- replications = 3)
+ "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)
- factor_SFO_SFO <- round(b.1["1", "relative"])
} else {
- factor_SFO_SFO <- NA
print("R package rbenchmark is not available")
}
```
-We see that using the compiled model is by a factor of around
-`r factor_SFO_SFO`
-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 more than a factor of 10 faster
+than using deSolve without compiled code.
-## Model that can not be solved with Eigenvalues
+## Model without analytical solution
-This evaluation is also taken from the example section of mkinfit.
+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.
```{r benchmark_FOMC_SFO, fig.height = 3, warning = FALSE}
if (require(rbenchmark)) {
@@ -109,10 +114,11 @@ if (require(rbenchmark)) { m1 = mkinsub( "SFO"))
b.2 <- benchmark(
- "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
+ "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
use_compiled = FALSE, quiet = TRUE),
- "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
- replications = 3)
+ "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 {
diff --git a/vignettes/web_only/compiled_models.html b/vignettes/web_only/compiled_models.html index 1d50ba7c..31d062bb 100644 --- a/vignettes/web_only/compiled_models.html +++ b/vignettes/web_only/compiled_models.html @@ -11,7 +11,7 @@ <meta name="author" content="Johannes Ranke" /> -<meta name="date" content="2020-04-02" /> +<meta name="date" content="2020-05-12" /> <title>Performance benefit by using compiled model definitions in mkin</title> @@ -1583,7 +1583,7 @@ div.tocify { <h1 class="title toc-ignore">Performance benefit by using compiled model definitions in mkin</h1> <h4 class="author">Johannes Ranke</h4> -<h4 class="date">2020-04-02</h4> +<h4 class="date">2020-05-12</h4> </div> @@ -1593,8 +1593,6 @@ div.tocify { <p>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 <code>mkinmod()</code> function checks for presence of a compiler using</p> <pre class="r"><code>pkgbuild::has_compiler()</code></pre> <p>In previous versions, it used <code>Sys.which("gcc")</code> for this check.</p> -<div id="platform-specific-notes" class="section level3"> -<h3>Platform specific notes</h3> <p>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.</p> <p>On MacOS, which I do not use personally, I have had reports that a compiler is available by default.</p> <p>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</p> @@ -1602,55 +1600,55 @@ div.tocify { <p>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</p> <pre class="r"><code>Sys.getenv("HOME")</code></pre> </div> -</div> -<div id="comparison-with-eigenvalue-based-solutions" class="section level2"> -<h2>Comparison with Eigenvalue based solutions</h2> -<p>First, we build a simple degradation model for a parent compound with one metabolite.</p> +<div id="comparison-with-other-solution-methods" class="section level2"> +<h2>Comparison with other solution methods</h2> +<p>First, we build a simple degradation model for a parent compound with one metabolite, and we remove zero values from the dataset.</p> <pre class="r"><code>library("mkin", quietly = TRUE) SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))</code></pre> <pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre> -<p>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.</p> +<pre class="r"><code>FOCUS_D <- subset(FOCUS_2006_D, value != 0)</code></pre> +<p>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.</p> <pre class="r"><code>if (require(rbenchmark)) { b.1 <- benchmark( - "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, - solution_type = "deSolve", - use_compiled = FALSE, quiet = TRUE), - "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D, - solution_type = "eigen", quiet = TRUE), - "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, - solution_type = "deSolve", quiet = TRUE), - replications = 3) + "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) - factor_SFO_SFO <- round(b.1["1", "relative"]) } else { - factor_SFO_SFO <- NA print("R package rbenchmark is not available") }</code></pre> -<pre><code>## test replications elapsed relative user.self sys.self -## 3 deSolve, compiled 3 3.148 1.000 3.146 0.000 -## 1 deSolve, not compiled 3 28.920 9.187 28.904 0.001 -## 2 Eigenvalue based 3 4.442 1.411 4.439 0.000 -## user.child sys.child -## 3 0 0 -## 1 0 0 -## 2 0 0</code></pre> -<p>We see that using the compiled model is by a factor of around 9 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.</p> +<pre><code>## test replications relative elapsed +## 4 analytical 1 1.000 0.186 +## 3 deSolve, compiled 1 1.769 0.329 +## 2 Eigenvalue based 1 2.371 0.441 +## 1 deSolve, not compiled 1 72.183 13.426</code></pre> +<p>We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.</p> </div> -<div id="model-that-can-not-be-solved-with-eigenvalues" class="section level2"> -<h2>Model that can not be solved with Eigenvalues</h2> -<p>This evaluation is also taken from the example section of mkinfit.</p> +<div id="model-without-analytical-solution" class="section level2"> +<h2>Model without analytical solution</h2> +<p>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.</p> <pre class="r"><code>if (require(rbenchmark)) { FOMC_SFO <- mkinmod( parent = mkinsub("FOMC", "m1"), m1 = mkinsub( "SFO")) b.2 <- benchmark( - "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, + "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D, use_compiled = FALSE, quiet = TRUE), - "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE), - replications = 3) + "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 { @@ -1658,15 +1656,12 @@ SFO_SFO <- mkinmod( print("R package benchmark is not available") }</code></pre> <pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre> -<pre><code>## test replications elapsed relative user.self sys.self -## 2 deSolve, compiled 3 4.879 1.000 4.877 0 -## 1 deSolve, not compiled 3 53.551 10.976 53.525 0 -## user.child sys.child -## 2 0 0 -## 1 0 0</code></pre> -<p>Here we get a performance benefit of a factor of 11 using the version of the differential equation model compiled from C code!</p> -<p>This vignette was built with mkin 0.9.49.9 on</p> -<pre><code>## R version 3.6.3 (2020-02-29) +<pre><code>## test replications relative elapsed +## 2 deSolve, compiled 1 1.00 0.459 +## 1 deSolve, not compiled 1 51.76 23.758</code></pre> +<p>Here we get a performance benefit of a factor of 52 using the version of the differential equation model compiled from C code!</p> +<p>This vignette was built with mkin 0.9.50.2 on</p> +<pre><code>## R version 4.0.0 (2020-04-24) ## Platform: x86_64-pc-linux-gnu (64-bit) ## Running under: Debian GNU/Linux 10 (buster)</code></pre> <pre><code>## CPU model: AMD Ryzen 7 1700 Eight-Core Processor</code></pre> diff --git a/vignettes/web_only/mkin_benchmarks.rda b/vignettes/web_only/mkin_benchmarks.rda Binary files differindex 388a7886..870ecc2b 100644 --- a/vignettes/web_only/mkin_benchmarks.rda +++ b/vignettes/web_only/mkin_benchmarks.rda |