#' Inferring trajectories with Control: identity
#'
#' This control method will return the gold standard.
#'
#' @param dummy_param This parameter does not do anything.
ti_identity <- dynwrap::create_ti_method_r(
dynwrap::definition(
method = dynwrap::def_method(id = "identity"),
wrapper = dynwrap::def_wrapper(input_required = c("counts", "dataset"))
),
# describe packages needed by method
package_loaded = c("dplyr", "tidyr", "purrr", "dynwrap", "dynutils"),
# function to run the method with
run_fun = function(
counts,
priors,
seed = NA,
verbose = FALSE
) {
dataset <- priors$dataset
if (length(seed) > 0 && is.finite(seed)) set.seed(seed)
# TIMING: done with preproc
tl <- add_timing_checkpoint(NULL, "method_afterpreproc")
# TIMING: done with method
tl <- tl %>% add_timing_checkpoint("method_aftermethod")
# return output
wrap_data(
cell_ids = dataset$cell_ids,
cell_info = dataset$cell_info
) %>% add_trajectory(
milestone_ids = dataset$milestone_ids,
milestone_network = dataset$milestone_network,
divergence_regions = dataset$divergence_regions,
progressions = dataset$progressions
) %>% add_timings(
timings = tl %>% add_timing_checkpoint("method_afterpostproc")
)
}
)
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