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---
title: "Benchmark timings for mkin"
author: "Johannes Ranke"
date: Last change 17 February 2023 (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.

The following wrapper function for `mmkin` is used because the way the error
model is specified was changed in mkin version 0.9.49.1.

```{r}
if (packageVersion("mkin") > "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)
  }
}
```

```{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(" 16-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)
```




## 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"), # erroneously used FOMC twice, not fixed for consistency
  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, include = FALSE}
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, version = 2)
# 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)])
```

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