test_that("trying a short ML search: cla_secsse", {
Sys.unsetenv("R_TESTS")
parenthesis <- "(((6:0.2547423371,(1:0.0496153503,4:0.0496153503):0.2051269868):0.1306304758,(9:0.2124135406,5:0.2124135406):0.1729592723):1.151205247,(((7:0.009347664296,3:0.009347664296):0.2101416075,10:0.2194892718):0.1035186448,(2:0.2575886319,8:0.2575886319):0.06541928469):1.213570144);" #nolint
phylotree <- ape::read.tree(file = "", parenthesis)
traits <- c(2, 0, 1, 0, 2, 0, 1, 2, 2, 0)
num_concealed_states <- 3
idparslist <- cla_id_paramPos(traits, num_concealed_states)
idparslist$lambdas[2, ] <- rep(1, 9)
idparslist[[2]][] <- 4
masterBlock <- matrix(5, ncol = 3, nrow = 3, byrow = TRUE)
diag(masterBlock) <- NA
diff.conceal <- FALSE
idparslist[[3]] <- q_doubletrans(traits, masterBlock, diff.conceal)
testthat::expect_output(
startingpoint <- DDD::bd_ML(brts = ape::branching.times(phylotree))
)
intGuessLamba <- startingpoint$lambda0
intGuessMu <- startingpoint$mu0
idparsopt <- c(1)
initparsopt <- c(rep(intGuessLamba, 1))
idparsfix <- c(0, 4, 5)
parsfix <- c(0, 0, 0.01)
tol <- c(1e-04, 1e-05, 1e-07)
maxiter <- 1000 * round((1.25) ^ length(idparsopt))
optimmethod <- "subplex"
cond <- "proper_cond"
root_state_weight <- "proper_weights"
sampling_fraction <- c(1, 1, 1)
# Expect warning because some transitions are set to be impossible
testthat::expect_warning(
model_R <- cla_secsse_ml(
phy = phylotree,
traits = traits,
num_concealed_states = num_concealed_states,
idparslist = idparslist,
idparsopt = idparsopt,
initparsopt = initparsopt,
idparsfix = idparsfix,
parsfix = parsfix,
cond = cond,
root_state_weight = root_state_weight,
sampling_fraction = sampling_fraction,
tol = tol,
maxiter = maxiter,
optimmethod = optimmethod,
num_cycles = 1,
verbose = FALSE)
)
testthat::expect_equal(model_R$ML, -16.1342246206186)
# we have to translate to lambda matrices to test the following:
param_posit <- idparslist
param_posit[[1]] <- secsse::prepare_full_lambdas(traits,
num_concealed_states,
idparslist[[1]])
found_pars <- secsse::extract_par_vals(param_posit,
model_R$MLpars)
testthat::expect_equal(length(found_pars),
max(param_posit[[3]], na.rm = TRUE))
})
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