A base callback function that returns a galgo.Obj

base_return_pop_callback(
  userdir = "",
  generation,
  pop_pool,
  pareto,
  prob_matrix,
  current_time
)

Arguments

userdir	the default directory used by `galgo()` to store files
generation	a number indicating the number of iterations of the galgo algorithm
pop_pool	a `data.frame` with the solution vectors, number of clusters and their ranking.
pareto	the solutions found by Galgo across all generations in the solution space
prob_matrix	a `matrix` or `data.frame`. Must be an expression matrix with features in rows and samples in columns
current_time	an `POSIXct` object

Value

an object of class galgo

Examples

# load example dataset

library(breastCancerTRANSBIG)
data(transbig)
Train <- transbig
rm(transbig)
#> Warning: object 'transbig' not found
expression <- Biobase::exprs(Train)
clinical <- Biobase::pData(Train)
OS <- survival::Surv(time = clinical$t.rfs, event = clinical$e.rfs)
# We will use a reduced dataset for the example
expression <- expression[sample(1:nrow(expression), 100), ]

# Now we scale the expression matrix
expression <- t(scale(t(expression)))

# Run galgo with base_return_pop_callback assigned to the end_galgo_callback
# hook-point
# By using this callback galgo() return a `galgo,Obj` object.
output <- galgoR::galgo(generations = 5,
population = 15,
prob_matrix = expression,
OS = OS,
end_galgo_callback = base_return_pop_callback
)
#> Using CPU for computing pearson distance
#> Generation 1 Non-dominated solutions:
#>            k                      rnkIndex    CrowD
#> result.4   7 0.084590350 257.1524        1 1.195919
#> result.6   7 0.003680792 317.3117        1      Inf
#> result.8  10 0.005842896 292.0617        1 1.012713
#> result.11  6 0.099653514 216.1316        1      Inf
#> Generation 2 Non-dominated solutions:
#>            k                      rnkIndex     CrowD
#> result.6   7 0.003680792 317.3117        1       Inf
#> result.11  6 0.099653514 216.1316        1       Inf
#> result.4   7 0.084590350 257.1524        1 0.9224728
#> result.13  7 0.014630474 269.6885        1 0.8038738
#> result.8  10 0.005842896 292.0617        1 0.2587913
#> Generation 3 Non-dominated solutions:
#>            k                      rnkIndex     CrowD
#> result.6   7 0.003680792 317.3117        1       Inf
#> result.11  6 0.099653514 216.1316        1       Inf
#> result.4   7 0.084590350 257.1524        1 1.0030396
#> result.13  7 0.014630474 269.6885        1 0.8771233
#> result.8  10 0.005842896 292.0617        1 0.2729658
#> Generation 4 Non-dominated solutions:
#>            k                      rnkIndex     CrowD
#> result.11  6 0.099653514 216.1316        1       Inf
#>           10 0.002507672 461.5718        1       Inf
#> result.4   7 0.084590350 257.1524        1 0.8639862
#> result.13  7 0.014630474 269.6885        1 0.7675283
#> result.6   7 0.003680792 317.3117        1 0.4062790
#> result.8  10 0.005842896 292.0617        1 0.2018596
#> Generation 5 Non-dominated solutions:
#>            k                       rnkIndex     CrowD
#>           10 0.002507672 461.57176        1       Inf
#>            2 0.118741912  75.50483        1       Inf
#> result.4   7 0.084590350 257.15245        1 0.7624803
#> result.13  7 0.014630474 269.68853        1 0.6741793
#> result.11  6 0.099653514 216.13165        1 0.6552316
#> result.6   7 0.003680792 317.31173        1 0.3947242
#> result.8  10 0.005842896 292.06171        1 0.1869448