context("Multistart method for saem.mmkin models")
test_that("multistart works for saem.mmkin models", {
skip_on_cran() # Save CRAN time
set.seed(123456)
saem_sfo_s_multi <- multistart(sfo_saem_1_reduced, n = 8, cores = n_cores)
anova_sfo <- anova(sfo_saem_1,
sfo_saem_1_reduced,
best(saem_sfo_s_multi),
test = TRUE
)
expect_equal(round(anova_sfo, 1)["sfo_saem_1_reduced", "AIC"], 1302.2)
expect_equal(round(anova_sfo, 1)["best(saem_sfo_s_multi)", "AIC"], 1302.2)
expect_true(anova_sfo[3, "Pr(>Chisq)"] > 0.2) # Local: 1, win-builder: 0.4
set.seed(123456)
saem_dfop_sfo_m_multi <- multistart(saem_dfop_sfo_m, n = 8,
cores = n_cores)
expect_known_output(print(saem_dfop_sfo_m_multi),
file = "print_multistart_dfop_sfo.txt")
anova_dfop_sfo <- anova(saem_dfop_sfo_m,
best(saem_dfop_sfo_m_multi))
# With the new starting parameters we do not improve
# with multistart any more
expect_equal(anova_dfop_sfo[2, "AIC"], anova_dfop_sfo[1, "AIC"],
tolerance = 1e-4)
skip_on_travis() # Plots are platform dependent
llhist_sfo <- function() llhist(saem_sfo_s_multi)
parplot_sfo <- function() parplot(saem_sfo_s_multi, ylim = c(0.5, 2))
vdiffr::expect_doppelganger("llhist for sfo fit", llhist_sfo)
vdiffr::expect_doppelganger("parplot for sfo fit", parplot_sfo)
llhist_dfop_sfo <- function() llhist(saem_dfop_sfo_m_multi)
parplot_dfop_sfo <- function() parplot(saem_dfop_sfo_m_multi,
ylim = c(0.5, 2))
vdiffr::expect_doppelganger("llhist for dfop sfo fit", llhist_dfop_sfo)
vdiffr::expect_doppelganger("parplot for dfop sfo fit", parplot_dfop_sfo)
})
