Stripped down setup script to ease testingstackoverflow_71340826

1 files changed, 8 insertions, 162 deletions

diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R
index ec96fbc2..d06c1730 100644
--- a/tests/testthat/setup_script.R
+++ b/tests/testthat/setup_script.R
@@ -21,6 +21,14 @@ SFO_trans <- function(t, parent_0, log_k_parent_sink) {
 SFO_notrans <- function(t, parent_0, k_parent_sink) {
   parent_0 * exp(- k_parent_sink * t)
 }
+
+f_1_nls_trans <- nls(value ~ SFO_trans(time, parent_0, log_k_parent_sink),
+  data = FOCUS_2006_A,
+  start = list(parent_0 = 100, log_k_parent_sink = log(0.1)))
+f_1_nls_notrans <- nls(value ~ SFO_notrans(time, parent_0, k_parent_sink),
+  data = FOCUS_2006_A,
+  start = list(parent_0 = 100, k_parent_sink = 0.1))
+
 f_1_nls_trans <- nls(value ~ SFO_trans(time, parent_0, log_k_parent_sink),
   data = FOCUS_2006_A,
   start = list(parent_0 = 100, log_k_parent_sink = log(0.1)))
@@ -32,41 +40,6 @@ f_1_mkin_trans <- mkinfit("SFO", FOCUS_2006_A, quiet = TRUE)
 f_1_mkin_notrans <- mkinfit("SFO", FOCUS_2006_A, quiet = TRUE,
   transform_rates = FALSE)
 
-# mmkin object of parent fits for tests
-models <- c("SFO", "FOMC", "DFOP", "HS")
-fits <- suppressWarnings( # FOCUS A FOMC was, it seems, in testthat output
-  mmkin(models,
-    list(FOCUS_A = FOCUS_2006_A, FOCUS_C = FOCUS_2006_C, FOCUS_D = FOCUS_2006_D),
-    quiet = TRUE, cores = n_cores))
-
-# One metabolite
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", to = "m1"),
-  m1 = mkinsub("SFO"),
-  use_of_ff = "min", quiet = TRUE)
-SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", to = "m1"),
-  m1 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-SFO_SFO.ff.nosink <- mkinmod(
-  parent = mkinsub("SFO", "m1", sink = FALSE),
-  m1 = mkinsub("SFO"), quiet = TRUE, use_of_ff = "max")
-FOMC_SFO <- mkinmod(parent = mkinsub("FOMC", to = "m1"),
-  m1 = mkinsub("SFO"), quiet = TRUE)
-DFOP_SFO <- mkinmod(parent = mkinsub("DFOP", to = "m1"),
-  m1 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-
-# Avoid warning when fitting a dataset where zero value is removed
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
-
-f_sfo_sfo_desolve <- mkinfit(SFO_SFO, FOCUS_D,
-  solution_type = "deSolve", quiet = TRUE)
-
-f_sfo_sfo_eigen <- mkinfit(SFO_SFO, FOCUS_D,
-  solution_type = "eigen", quiet = TRUE)
-
-f_sfo_sfo.ff <- mkinfit(SFO_SFO.ff, FOCUS_D,
-  quiet = TRUE)
-
 SFO_lin_a <- synthetic_data_for_UBA_2014[[1]]$data
 DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
 
@@ -95,130 +68,3 @@ fit_obs_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "obs", quiet = TR
 fit_tc_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "tc", quiet = TRUE,
   error_model_algorithm = "threestep")
 
-# Mixed models data and fits
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-n <- n_biphasic <- 15
-log_sd <- 0.3
-err_1 = list(const = 1, prop = 0.05)
-tc <- function(value) sigma_twocomp(value, err_1$const, err_1$prop)
-const <- function(value) 2
-
-set.seed(123456)
-SFO <- mkinmod(parent = mkinsub("SFO"))
-k_parent = rlnorm(n, log(0.03), log_sd)
-set.seed(123456)
-ds_sfo <- lapply(1:n, function(i) {
-  ds_mean <- mkinpredict(SFO, c(k_parent = k_parent[i]),
-    c(parent = 100), sampling_times)
-  add_err(ds_mean, tc, n = 1)[[1]]
-})
-
-set.seed(123456)
-FOMC <- mkinmod(parent = mkinsub("FOMC"))
-fomc_pop <- list(parent_0 = 100, alpha = 2, beta = 8)
-fomc_parms <- as.matrix(data.frame(
-    alpha = rlnorm(n, log(fomc_pop$alpha), 0.4),
-    beta = rlnorm(n, log(fomc_pop$beta), 0.2)))
-set.seed(123456)
-ds_fomc <- lapply(1:3, function(i) {
-  ds_mean <- mkinpredict(FOMC, fomc_parms[i, ],
-    c(parent = 100), sampling_times)
-  add_err(ds_mean, tc, n = 1)[[1]]
-})
-
-set.seed(123456)
-DFOP <- mkinmod(parent = mkinsub("DFOP"))
-dfop_pop <- list(parent_0 = 100, k1 = 0.06, k2 = 0.015, g = 0.4)
-dfop_parms <- as.matrix(data.frame(
-  k1 = rlnorm(n, log(dfop_pop$k1), log_sd),
-  k2 = rlnorm(n, log(dfop_pop$k2), log_sd),
-  g = plogis(rnorm(n, qlogis(dfop_pop$g), log_sd))))
-set.seed(123456)
-ds_dfop <- lapply(1:n, function(i) {
-  ds_mean <- mkinpredict(DFOP, dfop_parms[i, ],
-    c(parent = dfop_pop$parent_0), sampling_times)
-  add_err(ds_mean, const, n = 1)[[1]]
-})
-
-set.seed(123456)
-HS <- mkinmod(parent = mkinsub("HS"))
-hs_pop <- list(parent_0 = 100, k1 = 0.08, k2 = 0.01, tb = 15)
-hs_parms <- as.matrix(data.frame(
-  k1 = rlnorm(n, log(hs_pop$k1), log_sd),
-  k2 = rlnorm(n, log(hs_pop$k2), log_sd),
-  tb = rlnorm(n, log(hs_pop$tb), 0.1)))
-set.seed(123456)
-ds_hs <- lapply(1:10, function(i) {
-  ds_mean <- mkinpredict(HS, hs_parms[i, ],
-    c(parent = hs_pop$parent_0), sampling_times)
-  add_err(ds_mean, const, n = 1)[[1]]
-})
-
-set.seed(123456)
-DFOP_SFO <- mkinmod(
-  parent = mkinsub("DFOP", "m1"),
-  m1 = mkinsub("SFO"),
-  quiet = TRUE)
-dfop_sfo_pop <- list(parent_0 = 100,
-  k_m1 = 0.005, f_parent_to_m1 = 0.5,
-  k1 = 0.05, k2 = 0.01, g = 0.5)
-syn_biphasic_parms <- as.matrix(data.frame(
-  k1 = rlnorm(n_biphasic, log(dfop_sfo_pop$k1), log_sd),
-  k2 = rlnorm(n_biphasic, log(dfop_sfo_pop$k2), log_sd),
-  g = plogis(rnorm(n_biphasic, qlogis(dfop_sfo_pop$g), log_sd)),
-  f_parent_to_m1 = plogis(rnorm(n_biphasic,
-      qlogis(dfop_sfo_pop$f_parent_to_m1), log_sd)),
-  k_m1 = rlnorm(n_biphasic, log(dfop_sfo_pop$k_m1), log_sd)))
-ds_biphasic_mean <- lapply(1:n_biphasic,
-  function(i) {
-    mkinpredict(DFOP_SFO, syn_biphasic_parms[i, ],
-      c(parent = 100, m1 = 0), sampling_times)
-  }
-)
-set.seed(123456)
-ds_biphasic <- lapply(ds_biphasic_mean, function(ds) {
-  add_err(ds,
-    sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
-    n = 1, secondary = "m1")[[1]]
-})
-
-# Mixed model fits
-mmkin_sfo_1 <- mmkin("SFO", ds_sfo, quiet = TRUE, error_model = "tc", cores = n_cores)
-mmkin_dfop_1 <- mmkin("DFOP", ds_dfop, quiet = TRUE, cores = n_cores)
-mmkin_biphasic <- mmkin(list("DFOP-SFO" = DFOP_SFO), ds_biphasic, quiet = TRUE, cores = n_cores,
-  error_model = "tc")
-
-# nlme
-dfop_nlme_1 <- nlme(mmkin_dfop_1)
-nlme_biphasic <- nlme(mmkin_biphasic)
-
-# saemix
-sfo_saem_1 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "saemix")
-
-dfop_saemix_1 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin")
-dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix")
-
-saem_biphasic_m <- saem(mmkin_biphasic, transformations = "mkin", quiet = TRUE)
-saem_biphasic_s <- saem(mmkin_biphasic, transformations = "saemix", quiet = TRUE)
-
-# nlmixr saem
-tmp <- suppressMessages(capture.output(nlmixr_saem_biphasic <- nlmixr(mmkin_biphasic, est = "saem",
-    control = nlmixr::saemControl(nBurn = 300, nEm = 100, nmc = 9, print = 0))))
-# The FOCEI fit takes too long...
-#tmp <- capture_output(nlmixr_focei_biphasic <- nlmixr(mmkin_biphasic, est = "focei",
-#    control = nlmixr::foceiControl(print = 0)))
-
-# UBA datasets
-ds_uba <- lapply(experimental_data_for_UBA_2019[6:10],
-  function(x) subset(x$data[c("name", "time", "value")]))
-names(ds_uba) <- paste("Dataset", 6:10)
-sfo_sfo_uba <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-dfop_sfo_uba <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-f_uba_mmkin <- mmkin(list("SFO-SFO" = sfo_sfo_uba, "DFOP-SFO" = dfop_sfo_uba),
-  ds_uba, quiet = TRUE, cores = n_cores)
-f_uba_dfop_sfo_mixed <- mixed(f_uba_mmkin[2, ])
-
-f_uba_sfo_sfo_saem <- saem(f_uba_mmkin["SFO-SFO", ], quiet = TRUE, transformations = "saemix")
-f_uba_dfop_sfo_saem <- saem(f_uba_mmkin["DFOP-SFO", ], quiet = TRUE, transformations = "saemix")