diff options
Diffstat (limited to 'tests')
| -rw-r--r-- | tests/testthat/setup_script.R | 170 |
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") |