
Function to mutate offspring with adaptive mutation and network constraints
Source:R/RcppExports.R
mutation_cpp.Rd
Function to mutate offspring with adaptive mutation and network constraints
Examples
genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
population <- BioGA::initialize_population_cpp(genomic_data,
population_size = 5)
fitness <- BioGA::evaluate_fitness_cpp(genomic_data, population,
c(1.0, 0.5))
selected_parents <- BioGA::selection_cpp(population, fitness,
num_parents = 2)
#> Current front size: 1
offspring <- BioGA::crossover_cpp(selected_parents,
offspring_size = 2)
BioGA::mutation_cpp(offspring, mutation_rate = 0.1, iteration = 1,
max_iterations = 100)
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,] 1.096839 -0.640706 0.1813035 -0.1388914 0.3796395 -0.5023235 0.8951257
#> [2,] 1.096839 -0.640706 0.1813035 -0.1388914 0.3796395 -0.5259514 0.8951257
#> [,8] [,9] [,10]
#> [1,] 0.6443765 0.5194072 0.6886403
#> [2,] 0.6443765 0.5194072 0.6886403