diff options
Diffstat (limited to 'tests/testthat')
| -rw-r--r-- | tests/testthat/test_FOCUS_D_UBA_expertise.R | 2 | ||||
| -rw-r--r-- | tests/testthat/test_deSolve.R | 19 | ||||
| -rw-r--r-- | tests/testthat/test_mixed.R | 20 | ||||
| -rw-r--r-- | tests/testthat/test_mkinpredict_SFO_SFO.R | 14 |
4 files changed, 54 insertions, 1 deletions
diff --git a/tests/testthat/test_FOCUS_D_UBA_expertise.R b/tests/testthat/test_FOCUS_D_UBA_expertise.R index faf473c4..323fb7b3 100644 --- a/tests/testthat/test_FOCUS_D_UBA_expertise.R +++ b/tests/testthat/test_FOCUS_D_UBA_expertise.R @@ -40,7 +40,7 @@ test_that("Fits without internal transformations are correct for FOCUS D", { fit.ff.notrans <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, transform_fractions = FALSE, transform_rates = FALSE, quiet = TRUE, solution_type = "deSolve"), - "sum of formation fractions") + "The sum of formation fractions may exceed one") expect_equivalent(round(fit.ff.notrans$bparms.optim, c(2, 4, 4, 4)), c(99.60, 0.0987, 0.0053, 0.5145)) diff --git a/tests/testthat/test_deSolve.R b/tests/testthat/test_deSolve.R new file mode 100644 index 00000000..3d15de35 --- /dev/null +++ b/tests/testthat/test_deSolve.R @@ -0,0 +1,19 @@ +context("Solutions with deSolve") + +test_that("Solutions with deSolve work if we have no observations at time zero", { + skip_on_cran() + + # For testing purposes, we replace 0 values in the time column with 0.1 + # This confused mkinfit with solution_type "deSolve" up to version 0.1.3.0 + FOCUS_D_nozero <- FOCUS_D + FOCUS_D_nozero[FOCUS_D$time == 0, "time"] <- c(0.1, 0.1) + + f_sfo_sfo_nozero <- mkinfit(SFO_SFO, FOCUS_D_nozero, quiet = TRUE) + f_sfo_sfo_nozero_deSolve <- mkinfit(SFO_SFO, FOCUS_D_nozero, + solution_type = "deSolve", quiet = TRUE) + expect_equal( + parms(f_sfo_sfo_nozero), + parms(f_sfo_sfo_nozero_deSolve) + ) +}) + diff --git a/tests/testthat/test_mixed.R b/tests/testthat/test_mixed.R index b9715096..99a5fd3a 100644 --- a/tests/testthat/test_mixed.R +++ b/tests/testthat/test_mixed.R @@ -102,15 +102,35 @@ test_that("Reading spreadsheets, finding ill-defined parameters and covariate mo error_model = "const") lambda_sforb_saem_pH <- saem(lambda_sforb, covariates = covariates, covariate_models = list(log_k_lambda_bound_free ~ pH)) + expect_equal( as.character(illparms(lambda_sforb_saem_pH)), c("sd(lambda_free_0)", "sd(log_k_lambda_free_bound)")) lambda_endpoints <- endpoints(lambda_sforb_saem_pH) + expect_equal(lambda_endpoints$covariates$pH, 6.45) expect_equal( round(as.numeric(lambda_endpoints$distimes), 0), c(47, 422, 127, 7, 162)) + + # We should get the same endpoints when the covariates are centered + lambda_sforb_saem_pH_centered <- saem(lambda_sforb, covariates = covariates, + covariate_models = list(log_k_lambda_bound_free ~ pH), center_covariates = "median") + lambda_endpoints_centered <- endpoints(lambda_sforb_saem_pH_centered) + + expect_equal(lambda_endpoints_centered$covariates$pH, 6.45) + expect_equal( + round(as.numeric(lambda_endpoints_centered$distimes), 0), + c(47, 422, 127, 7, 162)) + + # Also check endpoints obtained for a different pH + lambda_endpoints_centered_7 <- endpoints(lambda_sforb_saem_pH_centered, covariates = c(pH = 7)) + expect_equal(lambda_endpoints_centered_7$covariates$pH, 7) + expect_equal( + round(as.numeric(lambda_endpoints_centered_7$distimes), 0), + c(39, 283, 85, 7, 106)) + }) test_that("SFO-SFO saemix specific analytical solution work", { diff --git a/tests/testthat/test_mkinpredict_SFO_SFO.R b/tests/testthat/test_mkinpredict_SFO_SFO.R index d0dc7cdb..bf1043a3 100644 --- a/tests/testthat/test_mkinpredict_SFO_SFO.R +++ b/tests/testthat/test_mkinpredict_SFO_SFO.R @@ -11,6 +11,10 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul m1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
ot = seq(0, 100, by = 1)
+ r.1.a <- subset(as.data.frame(mkinpredict(SFO_SFO.1,
+ c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1),
+ c(parent = 100, m1 = 0), ot, solution_type = "analytical")),
+ time %in% c(1, 10, 50, 100))
r.1.e <- subset(as.data.frame(mkinpredict(SFO_SFO.1,
c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1),
c(parent = 100, m1 = 0), ot, solution_type = "eigen")),
@@ -20,6 +24,10 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul c(parent = 100, m1 = 0), ot, solution_type = "deSolve")),
time %in% c(1, 10, 50, 100))
+ r.2.a <- subset(as.data.frame(mkinpredict(SFO_SFO.2,
+ c(k_parent = 0.2, f_parent_to_m1 = 0.5, k_m1 = 0.1),
+ c(parent = 100, m1 = 0), ot, solution_type = "analytical")),
+ time %in% c(1, 10, 50, 100))
r.2.e <- subset(as.data.frame(mkinpredict(SFO_SFO.2,
c(k_parent = 0.2, f_parent_to_m1 = 0.5, k_m1 = 0.1),
c(parent = 100, m1 = 0), ot, solution_type = "eigen")),
@@ -29,6 +37,12 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul c(parent = 100, m1 = 0), ot, solution_type = "deSolve")),
time %in% c(1, 10, 50, 100))
+ # Compare analytical and deSolve for minimum use of formation fractions
+ dev.1.a_d.percent = 100 * (r.1.a[-1] - r.1.d[-1])/r.1.a[-1]
+ dev.1.a_d.percent = as.numeric(unlist((dev.1.a_d.percent)))
+ dev.1.a_d.percent = ifelse(is.na(dev.1.a_d.percent), 0, dev.1.a_d.percent)
+ expect_equivalent(dev.1.a_d.percent < tol, rep(TRUE, length(dev.1.a_d.percent)))
+
# Compare eigen and deSolve for minimum use of formation fractions
dev.1.e_d.percent = 100 * (r.1.e[-1] - r.1.d[-1])/r.1.e[-1]
dev.1.e_d.percent = as.numeric(unlist((dev.1.e_d.percent)))
|