set.seed(1)
library("bbotk")
lgr::threshold("warn")
# Define the objective to optimize
objective <- ObjectiveRFun$new(
fun = function(xs) {
z <- exp(-xs$x^2 - xs$y^2) + 2 * exp(-(2 - xs$x)^2 - (2 - xs$y)^2)
list(Obj = z)
},
domain = ps(x = p_dbl(-2, 4), y = p_dbl(-2, 4)),
codomain = ps(Obj = p_dbl(tags = "maximize"))
)
# Get a new OptimInstance
oi <- OptimInstanceSingleCrit$new(objective,
terminator = trm("evals", n_evals = 100)
)
s = sel("best")
s$prime(oi$search_space)
mies_init_population(inst = oi, mu = 6)
oi$archive
# Default: get individuals
mies_select_from_archive(oi, n_select = 2, rows = 1:6, selector = s)
# Alternatively: get rows within archive
mies_select_from_archive(oi, n_select = 2, rows = 1:6, selector = s,
get_indivs = FALSE)
# Rows gotten from archive are relative from *all* rows, not from archive[rows]:
mies_select_from_archive(oi, n_select = 2, rows = 3:6, selector = s,
get_indivs = FALSE)
##
# When using additional components: mies_select_from_archive learns about
# additional components from primed selector.
# Get a new OptimInstance
oi <- OptimInstanceSingleCrit$new(objective,
terminator = trm("evals", n_evals = 100)
)
mies_init_population(inst = oi, mu = 6,
additional_component_sampler = Sampler1DRfun$new(
param = ps(additional = p_dbl(-1, 1)), rfun = function(n) -1
)
)
oi$archive
# Wrong: using selector primed only on search space. The resulting
# individuals do not have the additional component.
mies_select_from_archive(oi, n_select = 2, rows = 1:6, selector = s)
# Correct: selector must be primed on search space + additional component
mies_prime_operators(oi$search_space, selectors = list(s),
additional_components = ps(additional = p_dbl(-1, 1)))
mies_select_from_archive(oi, n_select = 2, rows = 1:6, selector = s)
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