From 48c463680b51fa767b4cd7bd62865f192d0354ac Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Sat, 6 Feb 2021 18:30:32 +0100 Subject: Reintroduce interface to saemix Also after the upgrade from buster to bullseye of my local system, some test results for saemix have changed. --- tests/testthat/test_mixed.R | 135 +++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 134 insertions(+), 1 deletion(-) (limited to 'tests/testthat/test_mixed.R') diff --git a/tests/testthat/test_mixed.R b/tests/testthat/test_mixed.R index 6f28d0c3..0eb1f0d5 100644 --- a/tests/testthat/test_mixed.R +++ b/tests/testthat/test_mixed.R @@ -1,9 +1,98 @@ context("Nonlinear mixed-effects models") +test_that("Parent fits using saemix are correctly implemented", { + skip_if(!saemix_available) + + expect_error(saem(fits), "Only row objects") + # Some fits were done in the setup script + mmkin_sfo_2 <- update(mmkin_sfo_1, fixed_initials = c(parent = 100)) + expect_error(update(mmkin_sfo_1, models = c("SFOOO")), "Please supply models.*") + + sfo_saem_2 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "mkin") + sfo_saem_3 <- expect_error(saem(mmkin_sfo_2, quiet = TRUE), "at least two parameters") + s_sfo_s1 <- summary(sfo_saem_1) + s_sfo_s2 <- summary(sfo_saem_2) + + sfo_nlme_1 <- expect_warning(nlme(mmkin_sfo_1), "not converge") + s_sfo_n <- summary(sfo_nlme_1) + + # Compare with input + expect_equal(round(s_sfo_s2$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) + # k_parent is a bit different from input 0.03 here + expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), 0.035) + expect_equal(round(s_sfo_s2$confint_back["k_parent", "est."], 3), 0.035) + + # But the result is pretty unanimous between methods + expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), + round(s_sfo_s2$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), + round(s_sfo_n$confint_back["k_parent", "est."], 3)) + + mmkin_fomc_1 <- mmkin("FOMC", ds_fomc, quiet = TRUE, error_model = "tc", cores = n_cores) + fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE) + ci_fomc_s1 <- summary(fomc_saem_1)$confint_back + + fomc_pop <- as.numeric(fomc_pop) + expect_true(all(ci_fomc_s1[, "lower"] < fomc_pop)) + expect_true(all(ci_fomc_s1[, "upper"] > fomc_pop)) + + mmkin_fomc_2 <- update(mmkin_fomc_1, state.ini = 100, fixed_initials = "parent") + fomc_saem_2 <- saem(mmkin_fomc_2, quiet = TRUE, transformations = "mkin") + ci_fomc_s2 <- summary(fomc_saem_2)$confint_back + + expect_true(all(ci_fomc_s2[, "lower"] < fomc_pop[2:3])) + expect_true(all(ci_fomc_s2[, "upper"] > fomc_pop[2:3])) + + s_dfop_s1 <- summary(dfop_saemix_1) + s_dfop_s2 <- summary(dfop_saemix_2) + s_dfop_n <- summary(dfop_nlme_1) + + dfop_pop <- as.numeric(dfop_pop) + expect_true(all(s_dfop_s1$confint_back[, "lower"] < dfop_pop)) + expect_true(all(s_dfop_s1$confint_back[, "upper"] > dfop_pop)) + expect_true(all(s_dfop_s2$confint_back[, "lower"] < dfop_pop)) + expect_true(all(s_dfop_s2$confint_back[, "upper"] > dfop_pop)) + + dfop_mmkin_means_trans <- apply(parms(mmkin_dfop_1, transformed = TRUE), 1, mean) + dfop_mmkin_means <- backtransform_odeparms(dfop_mmkin_means_trans, mmkin_dfop_1$mkinmod) + + # We get < 22% deviations by averaging the transformed parameters + rel_diff_mmkin <- (dfop_mmkin_means - dfop_pop) / dfop_pop + expect_true(all(rel_diff_mmkin < 0.22)) + + # We get < 50% deviations with transformations made in mkin + rel_diff_1 <- (s_dfop_s1$confint_back[, "est."] - dfop_pop) / dfop_pop + expect_true(all(rel_diff_1 < 0.5)) + + # We get < 12% deviations with transformations made in saemix + rel_diff_2 <- (s_dfop_s2$confint_back[, "est."] - dfop_pop) / dfop_pop + expect_true(all(rel_diff_2 < 0.12)) + + mmkin_hs_1 <- mmkin("HS", ds_hs, quiet = TRUE, error_model = "const", cores = n_cores) + hs_saem_1 <- saem(mmkin_hs_1, quiet = TRUE) + ci_hs_s1 <- summary(hs_saem_1)$confint_back + + hs_pop <- as.numeric(hs_pop) + # expect_true(all(ci_hs_s1[, "lower"] < hs_pop)) # k1 is overestimated + expect_true(all(ci_hs_s1[, "upper"] > hs_pop)) + + mmkin_hs_2 <- update(mmkin_hs_1, state.ini = 100, fixed_initials = "parent") + hs_saem_2 <- saem(mmkin_hs_2, quiet = TRUE) + ci_hs_s2 <- summary(hs_saem_2)$confint_back + + #expect_true(all(ci_hs_s2[, "lower"] < hs_pop[2:4])) # k1 again overestimated + expect_true(all(ci_hs_s2[, "upper"] > hs_pop[2:4])) + + # HS would likely benefit from implemenation of transformations = "saemix" +}) + test_that("Print methods work", { expect_known_output(print(fits[, 2:3], digits = 2), "print_mmkin_parent.txt") expect_known_output(print(mmkin_biphasic_mixed, digits = 2), "print_mmkin_biphasic_mixed.txt") expect_known_output(print(nlme_biphasic, digits = 1), "print_nlme_biphasic.txt") + + skip_if(!saemix_available) + expect_known_output(print(sfo_saem_1, digits = 1), "print_sfo_saem_1.txt") }) test_that("nlme results are reproducible to some degree", { @@ -20,6 +109,50 @@ test_that("nlme results are reproducible to some degree", { dfop_sfo_pop <- as.numeric(dfop_sfo_pop) ci_dfop_sfo_n <- summary(nlme_biphasic)$confint_back - # expect_true(all(ci_dfop_sfo_n[, "lower"] < dfop_sfo_pop)) # k2 is overestimated + expect_true(all(ci_dfop_sfo_n[, "lower"] < dfop_sfo_pop)) expect_true(all(ci_dfop_sfo_n[, "upper"] > dfop_sfo_pop)) }) + +test_that("saem results are reproducible for biphasic fits", { + + skip_if(!saemix_available) + test_summary <- summary(saem_biphasic_s) + test_summary$saemixversion <- "Dummy 0.0 for testing" + test_summary$mkinversion <- "Dummy 0.0 for testing" + test_summary$Rversion <- "Dummy R version for testing" + test_summary$date.fit <- "Dummy date for testing" + test_summary$date.summary <- "Dummy date for testing" + test_summary$time <- c(elapsed = "test time 0") + + expect_known_output(print(test_summary, digits = 2), "summary_saem_biphasic_s.txt") + + dfop_sfo_pop <- as.numeric(dfop_sfo_pop) + no_k1 <- c(1, 2, 3, 5, 6) + no_k2 <- c(1, 2, 3, 4, 6) + no_k1_k2 <- c(1, 2, 3, 6) + + ci_dfop_sfo_s_s <- summary(saem_biphasic_s)$confint_back + # k1 and k2 are overestimated + expect_true(all(ci_dfop_sfo_s_s[no_k1_k2, "lower"] < dfop_sfo_pop[no_k1_k2])) + expect_true(all(ci_dfop_sfo_s_s[, "upper"] > dfop_sfo_pop)) + + # k1 and k2 are not fitted well + ci_dfop_sfo_s_m <- summary(saem_biphasic_m)$confint_back + expect_true(all(ci_dfop_sfo_s_m[no_k2, "lower"] < dfop_sfo_pop[no_k2])) + expect_true(all(ci_dfop_sfo_s_m[no_k1, "upper"] > dfop_sfo_pop[no_k1])) + + # I tried to only do few iterations in routine tests as this is so slow + # but then deSolve fails at some point (presumably at the switch between + # the two types of iterations) + #saem_biphasic_2 <- saem(mmkin_biphasic, solution_type = "deSolve", + # control = list(nbiter.saemix = c(10, 5), nbiter.burn = 5), quiet = TRUE) + + skip("Fitting with saemix takes around 10 minutes when using deSolve") + saem_biphasic_2 <- saem(mmkin_biphasic, solution_type = "deSolve", quiet = TRUE) + + # As with the analytical solution, k1 and k2 are not fitted well + ci_dfop_sfo_s_d <- summary(saem_biphasic_2)$confint_back + expect_true(all(ci_dfop_sfo_s_d[no_k2, "lower"] < dfop_sfo_pop[no_k2])) + expect_true(all(ci_dfop_sfo_s_d[no_k1, "upper"] > dfop_sfo_pop[no_k1])) +}) + -- cgit v1.2.1