--- title: "Benchmark timings for mkin" author: "Johannes Ranke" date: Last change 1 July 2022 (rebuilt `r Sys.Date()`) output: html_document: toc: true toc_float: true code_folding: show fig_retina: null vignette: > %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} library(knitr) opts_chunk$set(tidy = FALSE, cache = FALSE) library("mkin") ``` Each system is characterized by the operating system type, the CPU type, the mkin version, and, as in June 2022 the current R version lead to worse performance, the R version. A compiler was available, so if no analytical solution was available, compiled ODE models are used. Every fit is only performed once, so the accuracy of the benchmarks is limited. ```{r include = FALSE} cpu_model <- benchmarkme::get_cpu()$model_name # Abbreviate CPU identifiers cpu_model <- gsub("AMD ", "", cpu_model) cpu_model <- gsub("Intel\\(R\\) Core\\(TM\\) ", "", cpu_model) cpu_model <- gsub(" Eight-Core Processor", "", cpu_model) cpu_model <- gsub(" CPU @ 2.50GHz", "", cpu_model) operating_system <- Sys.info()[["sysname"]] mkin_version <- as.character(packageVersion("mkin")) R_version <- paste0(R.version$major, ".", R.version$minor) system_string <- paste0(operating_system, ", ", cpu_model, ", mkin ", mkin_version, ", R ", R_version) benchmark_path = normalizePath("~/git/mkin/vignettes/web_only/mkin_benchmarks.rda") load(benchmark_path) # Used for reformatting the data on 2022-06-30 # mkin_benchmarks[, "R"] <- NA # mkin_benchmarks <- mkin_benchmarks[c(2, 1, 15, 3, 4:14)] # mkin_benchmarks[, "CPU"] <- gsub("AMD.*", "Ryzen 7 1700", mkin_benchmarks[, "CPU"]) # mkin_benchmarks[, "CPU"] <- gsub("Intel.*", "i7-4710MQ", mkin_benchmarks[, "CPU"]) # rownames(mkin_benchmarks) <- gsub("AMD Ryzen 7 1700 Eight-Core Processor", "Ryzen 7 1700", rownames(mkin_benchmarks)) # rownames(mkin_benchmarks) <- gsub("Intel\\(R\\) Core\\(TM\\) i7-4710MQ CPU @ 2.50GHz", "i7-4710MQ", rownames(mkin_benchmarks)) # rownames(mkin_benchmarks) <- gsub(" version", "", rownames(mkin_benchmarks)) mkin_benchmarks[system_string, c("CPU", "OS", "mkin", "R")] <- c(cpu_model, operating_system, mkin_version, R_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) } } else { mmkin_bench <- function(models, datasets, error_model = NULL) { mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) } } ``` ## Test cases Parent only: ```{r parent_only, warning = FALSE} 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"]] ``` One metabolite: ```{r one_metabolite, message = FALSE} SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO")) FOMC_SFO <- mkinmod( parent = mkinsub("FOMC", "m1"), m1 = mkinsub("SFO")) 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"]] ``` Two metabolites, synthetic data: ```{r two_metabolites, message = FALSE} m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"), M1 = mkinsub("SFO", "M2"), M2 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), M1 = mkinsub("SFO"), M2 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) SFO_lin_a <- synthetic_data_for_UBA_2014[[1]]$data DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$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"]] ``` ```{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 = benchmark_path) # Hide rownames from kable for results section rownames(mkin_benchmarks) <- NULL ``` ## Results Benchmarks for all available error models are shown. They are intended for improving mkin, not for comparing CPUs or operating systems. All trademarks belong to their respective owners. ### Parent only Constant variance (t1) and two-component error model (t2) for four models fitted to two datasets, i.e. eight fits for each test. ```{r, echo = FALSE} kable(mkin_benchmarks[, c(1:4, 5:6)]) ``` ### One metabolite Constant variance (t3), two-component error model (t4), and variance by variable (t5) for three models fitted to one dataset, i.e. three fits for each test. ```{r, echo = FALSE} kable(mkin_benchmarks[, c(1:4, 7:9)]) ``` ### Two metabolites Constant variance (t6 and t7), two-component error model (t8 and t9), and variance by variable (t10 and t11) for one model fitted to one dataset, i.e. one fit for each test. ```{r, echo = FALSE} kable(mkin_benchmarks[, c(1:4, 10:15)]) ```