Nothing
context("(4) Diagnostics functions")
skip_on_cran()
# the plotting functions are imported from BayesTools and tested henceforth
# test objects - assuming that the fit function worked properly
saved_files <- paste0("fit_", 1:4, ".RDS")
saved_fits <- list()
for(i in seq_along(saved_files)){
saved_fits[[i]] <- readRDS(file = file.path("../results/fits", saved_files[i]))
}
test_that("Parameter plots work", {
p1 <- diagnostics(saved_fits[[1]], parameter = "mu", type = "trace")
p2 <- diagnostics(saved_fits[[1]], parameter = "sigma", type = "autocorelation")
p3 <- diagnostics(saved_fits[[1]], parameter = "delta", type = "density")
p4 <- diagnostics(saved_fits[[1]], parameter = "rho", type = "trace")
p5 <- diagnostics(saved_fits[[1]], parameter = "nu", type = "autocorelation")
# ggplot
for(i in 1:8){
expect_doppelganger(paste0("diagnostics_mu_",i), p1[[i]])
expect_doppelganger(paste0("diagnostics_sigma_",i), p2[[i]])
if(i %in% 1:4){
expect_null(p3[[i]])
}else{
expect_doppelganger(paste0("diagnostics_delta_",i), p3[[i]])
}
if(i %in% c(1,2,5,6)){
expect_null(p4[[i]])
}else{
expect_doppelganger(paste0("diagnostics_rho_",i), p4[[i]])
}
if(i %in% c(1,3,5,7)){
expect_null(p5[[i]])
}else{
expect_doppelganger(paste0("diagnostics_nu_",i), p5[[i]])
}
}
})
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