test_that("M is properly bounded", {
# sim data
data("IBD_simulation_data", package = "discent")
dat <- IBD_simulation_data
# start params
our_start_params <- rep(0.2, 3)
names(our_start_params) <- 1:3
our_start_params <- c(our_start_params, "m" = 1e3)
# run model w/ EXTREMELY TIGHT bounds
inputdisc <- dat %>%
dplyr::filter(deme1 != deme2)
mod1 <- deme_inbreeding_spcoef_vanilla(discdat = inputdisc,
start_params = our_start_params,
learningrate = 1e-3,
m_lowerbound = 999,
m_upperbound = 1001,
b1 = 0.9,
b2 = 0.999,
e = 1e-8,
steps = 1e2,
report_progress = TRUE,
normalize_geodist = FALSE,
return_verbose = TRUE)
testthat::expect_gte(min(mod1$m_run), 999)
testthat::expect_lte(max(mod1$m_run), 1001)
})
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