diff options
Diffstat (limited to 'tests')
| -rw-r--r-- | tests/testthat/illparms_hfits_synth.txt | 10 | ||||
| -rw-r--r-- | tests/testthat/print_fits_synth_const.txt | 4 | ||||
| -rw-r--r-- | tests/testthat/summary_hfit_sfo_tc.txt | 34 | ||||
| -rw-r--r-- | tests/testthat/test_mhmkin.R | 34 |
4 files changed, 43 insertions, 39 deletions
diff --git a/tests/testthat/illparms_hfits_synth.txt b/tests/testthat/illparms_hfits_synth.txt index affd1318..7a69645b 100644 --- a/tests/testthat/illparms_hfits_synth.txt +++ b/tests/testthat/illparms_hfits_synth.txt @@ -1,8 +1,4 @@ error -degradation const - SFO - FOMC sd(log_alpha), sd(log_beta) - error -degradation tc - SFO sd(parent_0) - FOMC sd(parent_0), sd(log_alpha), sd(log_beta) +degradation const tc + SFO sd(parent_0) sd(parent_0) + FOMC sd(log_beta) sd(parent_0), sd(log_beta) diff --git a/tests/testthat/print_fits_synth_const.txt b/tests/testthat/print_fits_synth_const.txt index b4bbe6ca..5d076d3d 100644 --- a/tests/testthat/print_fits_synth_const.txt +++ b/tests/testthat/print_fits_synth_const.txt @@ -4,8 +4,6 @@ Status of individual fits: dataset model 1 2 3 4 5 6 SFO OK OK OK OK OK OK - FOMC C OK OK OK OK C + FOMC OK OK OK OK OK OK -C: Optimisation did not converge: -false convergence (8) OK: No warnings diff --git a/tests/testthat/summary_hfit_sfo_tc.txt b/tests/testthat/summary_hfit_sfo_tc.txt index 0a61f75f..0618c715 100644 --- a/tests/testthat/summary_hfit_sfo_tc.txt +++ b/tests/testthat/summary_hfit_sfo_tc.txt @@ -8,7 +8,7 @@ Equations: d_parent/dt = - k_parent * parent Data: -104 observations of 1 variable(s) grouped in 6 datasets +95 observations of 1 variable(s) grouped in 6 datasets Model predictions using solution type analytical @@ -19,7 +19,7 @@ Variance model: Two-component variance function Starting values for degradation parameters: parent_0 log_k_parent - 101 -3 + 94 -2 Fixed degradation parameter values: None @@ -27,7 +27,7 @@ None Starting values for random effects (square root of initial entries in omega): parent_0 log_k_parent parent_0 4 0.0 -log_k_parent 0 0.4 +log_k_parent 0 0.7 Starting values for error model parameters: a.1 b.1 @@ -37,15 +37,15 @@ Results: Likelihood computed by importance sampling AIC BIC logLik - 524 523 -257 + 542 541 -266 Optimised parameters: - est. lower upper -parent_0 100.68 99.27 102.08 -log_k_parent -3.38 -3.55 -3.21 -a.1 0.87 0.59 1.14 -b.1 0.05 0.04 0.06 -SD.log_k_parent 0.21 0.09 0.33 + est. lower upper +parent_0 92.52 89.11 95.9 +log_k_parent -1.66 -2.07 -1.3 +a.1 2.03 1.60 2.5 +b.1 0.09 0.07 0.1 +SD.log_k_parent 0.51 0.22 0.8 Correlation: pr_0 @@ -53,18 +53,18 @@ log_k_parent 0.1 Random effects: est. lower upper -SD.log_k_parent 0.2 0.09 0.3 +SD.log_k_parent 0.5 0.2 0.8 Variance model: est. lower upper -a.1 0.87 0.59 1.14 -b.1 0.05 0.04 0.06 +a.1 2.03 1.60 2.5 +b.1 0.09 0.07 0.1 Backtransformed parameters: - est. lower upper -parent_0 1e+02 99.27 1e+02 -k_parent 3e-02 0.03 4e-02 + est. lower upper +parent_0 92.5 89.1 95.9 +k_parent 0.2 0.1 0.3 Estimated disappearance times: DT50 DT90 -parent 20 68 +parent 4 12 diff --git a/tests/testthat/test_mhmkin.R b/tests/testthat/test_mhmkin.R index e2339f28..da063326 100644 --- a/tests/testthat/test_mhmkin.R +++ b/tests/testthat/test_mhmkin.R @@ -3,8 +3,11 @@ context("Batch fitting and diagnosing hierarchical kinetic models") test_that("Multiple hierarchical kinetic models can be fitted and diagnosed", { skip_on_cran() - fits_synth_const <- suppressWarnings( - mmkin(c("SFO", "FOMC"), ds_sfo[1:6], cores = n_cores, quiet = TRUE)) + fits_synth_const <- mmkin(c("SFO", "FOMC"), ds_fomc[1:6], cores = n_cores, quiet = TRUE) + + expect_known_output( + print(fits_synth_const), + "print_fits_synth_const.txt") fits_synth_tc <- suppressWarnings( update(fits_synth_const, error_model = "tc")) @@ -19,8 +22,8 @@ test_that("Multiple hierarchical kinetic models can be fitted and diagnosed", { print(illparms(hfits)), "illparms_hfits_synth.txt") - expect_equal(which.min(AIC(hfits)), 3) - expect_equal(which.min(BIC(hfits)), 3) + expect_equal(which.min(AIC(hfits)), 4) + expect_equal(which.min(BIC(hfits)), 4) hfit_sfo_tc <- update(hfits[["SFO", "tc"]], covariance.model = diag(c(0, 1))) @@ -38,12 +41,19 @@ test_that("Multiple hierarchical kinetic models can be fitted and diagnosed", { expect_known_output(print(test_summary, digits = 1), "summary_hfit_sfo_tc.txt") - # It depends on the platform exactly which of the datasets fail to converge - # with FOMC, because they were generated to be SFO - skip_on_travis() - - expect_known_output( - print(fits_synth_const), - "print_fits_synth_const.txt") - + hfits_sfo_reduced <- update(hfits, + no_random_effect = illparms(hfits)) + expect_equal( + as.character(illparms(hfits_sfo_reduced)), + rep("", 4)) + + # We can also manually set up an object specifying random effects to be + # excluded. Entries in the inital list have to be by column + no_ranef <- list("parent_0", "log_beta", "parent_0", c("parent_0", "log_beta")) + dim(no_ranef) <- c(2, 2) + + hfits_sfo_reduced_2 <- update(hfits, + no_random_effect = no_ranef) + expect_equivalent(round(anova(hfits_sfo_reduced), 0), + round(anova(hfits_sfo_reduced_2), 0)) }) |