Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval=FALSE---------------------------------------------------------------
# galgo(...,
# start_galgo_callback = callback_default,# `galgo()` is about to start.
# end_galgo_callback = callback_default, # `galgo()` is about to finish.
# start_gen_callback = callback_default, # At the beginning of each generation
# end_gen_callback = callback_default, # At the end of each generation
# report_callback = callback_default, # In the middle of the generation,
# # right after the new mating pool
# # have been created.
# ...)
## -----------------------------------------------------------------------------
library(GSgalgoR)
## -----------------------------------------------------------------------------
my_callback <-
function(userdir = "",
generation,
pop_pool,
pareto,
prob_matrix,
current_time) {
# code starts here
if (generation%%2 == 0)
message(paste0("generation: ",generation,
" current_time: ",current_time))
}
## ----message=FALSE------------------------------------------------------------
library(breastCancerTRANSBIG)
## -----------------------------------------------------------------------------
data(transbig)
train <- transbig
rm(transbig)
expression <- Biobase::exprs(train)
clinical <- Biobase::pData(train)
OS <- survival::Surv(time = clinical$t.rfs, event = clinical$e.rfs)
# use a reduced dataset for the example
expression <- expression[sample(1:nrow(expression), 100), ]
# scale the expression matrix
expression <- t(scale(t(expression)))
## ----message=FALSE------------------------------------------------------------
library(GSgalgoR)
## -----------------------------------------------------------------------------
# Running galgo
GSgalgoR::galgo(generations = 6,
population = 15,
prob_matrix = expression,
OS = OS,
start_galgo_callback = GSgalgoR::callback_default,
end_galgo_callback = GSgalgoR::callback_default,
report_callback = my_callback, # call `my_callback()` in the mile
# of each generation/iteration.
start_gen_callback = GSgalgoR::callback_default,
end_gen_callback = GSgalgoR::callback_default)
## -----------------------------------------------------------------------------
my_save_pop_callback <-
function(userdir = "",
generation,
pop_pool,
pareto,
prob_matrix,
current_time) {
directory <- paste0(tempdir(), "/")
if (!dir.exists(directory)) {
dir.create(directory, recursive = TRUE)
}
filename <- paste0(directory, generation, ".rda")
if (generation%%2 == 0){
save(file = filename, pop_pool)
}
message(paste("solution file saved in",filename))
}
## -----------------------------------------------------------------------------
# Running galgo
GSgalgoR::galgo(
generations = 6,
population = 15,
prob_matrix = expression,
OS = OS,
start_galgo_callback = GSgalgoR::callback_default,
end_galgo_callback = GSgalgoR::callback_default,
report_callback = my_callback,# call `my_callback()`
# in the middle of each generation/iteration.
start_gen_callback = GSgalgoR::callback_default,
end_gen_callback = my_save_pop_callback # call `my_save_pop_callback()`
# at the end of each
# generation/iteration
)
## -----------------------------------------------------------------------------
# Running galgo
GSgalgoR::galgo(
generations = 6,
population = 15,
prob_matrix = expression,
OS = OS,
start_galgo_callback = GSgalgoR::callback_default,
end_galgo_callback = my_save_pop_callback,
report_callback = my_callback, # call `my_callback()`
# in the middle of each generation/iteration
start_gen_callback = GSgalgoR::callback_default,
end_gen_callback = GSgalgoR::callback_default
)
## ----eval=FALSE---------------------------------------------------------------
#
# another_callback <-
# function(userdir = "",
# generation,
# pop_pool,
# pareto,
# prob_matrix,
# current_time) {
# # code starts here
#
# # code ends here
# callback_base_return_pop(userdir,
# generation,
# pop_pool,
# prob_matrix,
# current_time)
# }
## ----sess_info, eval=TRUE-----------------------------------------------------
sessionInfo()
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