Can be used with optimize_design to improve convergence speed.
shuffle_with_constraints(src = TRUE, dst = TRUE)Expression to define possible source locations in the samples/locations
table. Usually evaluated based on
BatchContainer$get_samples(include_id = TRUE, as_tibble = FALSE) as an environment
(see also with()). A single source location is selected from rows where the
expression evaluates toTRUE.
Expression to define possible destination locations in the
samples/locations table. Usually evaluated based on BatchContainer$get_samples() as an
environment.
Additionally a special variable .src is available in this environment which
describes the selected source row from the table.
Returns a function which accepts a BatchContainer and an iteration
number (i). This function returns a list with two names: src vector of length
2 and dst vector of length two. See BatchContainer$move_samples().
set.seed(43)
samples <- data.frame(
id = 1:100,
sex = sample(c("F", "M"), 100, replace = TRUE),
group = sample(c("treatment", "control"), 100, replace = TRUE)
)
bc <- BatchContainer$new(
dimensions = c("plate" = 5, "position" = 25)
)
scoring_f <- function(samples) {
osat_score(
samples,
"plate",
c("sex", "group")
)$score
}
# in this example we treat all the positions in the plate as equal.
# when shuffling we enforce that source location is non-empty,
# and destination location has a different plate number
bc <- optimize_design(
bc,
scoring = scoring_f,
samples,
shuffle_proposal = shuffle_with_constraints(
# source is non-empty location
!is.na(.sample_id),
# destination has a different plate
plate != .src$plate
),
max_iter = 10
)
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#> Checking variances of 1-dim. score vector.
#> ... (455.222) - OK
#> Initial score: 172.8
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#> Achieved score: 158.8 at iteration 3
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#> Achieved score: 138.8 at iteration 4
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#> Achieved score: 136.8 at iteration 8
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