var ga = require('darwin-js')

// Implement on your own
var options = {
  // Always copy over best individual without modification
  // to the next generation.
  elitist: true,
  fitness: (individual) => { 
    // You have the option of returning a Promise here, if
    // G.A. needs to asynchronously reach out to the user, say, for a 
    // subjective rating.
    return fitness
  },
  selection: (population) => {
    // Return an individual population[k].individual based on
    // population[k].fitness.
    var k = ...
    return population[k].individual
  },
  crossover: (parent1, parent2) => {
    // Combine parent1 and parent2 somehow
    return [child1, child2]
  },
  mutation: (individual) => {
    // Mutate individual (or return unchanged)
    ...
    return mutant
  },
  iterations: 10000,
  stop: (fitness) => {
    // Return true if fitness is high enough. Will
    // terminate G.A. even if it hasn't iterated 10000 times.
    return ...
  },
  stats: (fitnesses, best) => {
    console.log("Fitnesses of current generation: " + fitnesses)
    console.log("Best performing individual: %j", best)
  }
}

// Run genetic algorithm
ga.run(options).then((result) => {
  console.log('Best individual: ' + result.best.individual)
  console.log('Best individual\'s fitness: ' + result.best.fitness)
  console.log('Last population: %j', result.population)
}).catch((err) => {
  console.log('Oops: ' + err)
})