diff options
Diffstat (limited to 'tests/testthat/setup_script.R')
| -rw-r--r-- | tests/testthat/setup_script.R | 16 |
1 files changed, 12 insertions, 4 deletions
diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R index def52697..8d8ba3e9 100644 --- a/tests/testthat/setup_script.R +++ b/tests/testthat/setup_script.R @@ -57,18 +57,26 @@ DFOP_SFO <- mkinmod(parent = mkinsub("DFOP", to = "m1"), # Avoid warning when fitting a dataset where zero value is removed FOCUS_D <- subset(FOCUS_2006_D, value != 0) +# We do not want warnings about non-normality of residuals here +suppressWarnings( f_sfo_sfo_desolve <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE) +) +suppressWarnings( f_sfo_sfo_eigen <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "eigen", quiet = TRUE) - +) +suppressWarnings( 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 -f_2_mkin <- mkinfit("DFOP", DFOP_par_c, quiet = TRUE) +# We also suppress the warning about non-normality of residuals here, the data +# were generated with a different error model, so no wonder! +f_2_mkin <- suppressWarnings(mkinfit("DFOP", DFOP_par_c, quiet = TRUE)) f_2_nls <- nls(value ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = subset(DFOP_par_c, name == "parent")) f_2_anova <- lm(value ~ as.factor(time), data = subset(DFOP_par_c, name == "parent")) @@ -86,9 +94,9 @@ m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), fit_nw_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, quiet = TRUE) -# We know direct optimization is OK and direct needs 4 sec versus 5.5 for threestep and 6 for IRLS +# We know direct optimization is OK and direct is faster than the default d_3 fit_obs_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "obs", quiet = TRUE, error_model_algorithm = "direct") -# We know threestep is OK, and threestep (and IRLS) need 4.8 se versus 5.6 for direct +# We know threestep is OK, and threestep (and IRLS) is faster here fit_tc_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "tc", quiet = TRUE, error_model_algorithm = "threestep") |