// Daniel Shiffman

// http://natureofcode.com

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// Genetic Algorithm, Evolving Shakespeare

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// Demonstration of using a genetic algorithm to perform a search

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// setup()

//  # Step 1: The Population

//    # Create an empty population (an array or ArrayList)

//    # Fill it with DNA encoded objects (pick random values to start)

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// draw()

//  # Step 1: Selection

//    # Create an empty mating pool (an empty ArrayList)

//    # For every member of the population, evaluate its fitness based on some criteria / function,

//      and add it to the mating pool in a manner consistant with its fitness, i.e. the more fit it

//      is the more times it appears in the mating pool, in order to be more likely picked for reproduction.

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//  # Step 2: Reproduction Create a new empty population

//    # Fill the new population by executing the following steps:

//       1. Pick two "parent" objects from the mating pool.

//       2. Crossover -- create a "child" object by mating these two parents.

//       3. Mutation -- mutate the child's DNA based on a given probability.

//       4. Add the child object to the new population.

//    # Replace the old population with the new population

//

//   # Rinse and repeat

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let target;

let popmax;

let mutationRate;

let population;

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let bestPhrase;

let allPhrases;

let stats;

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function setup() {

  createCanvas(640, 240);

  //createCanvas(640, 360);

  target = "To be or not to be.";

  popmax = 200;

  mutationRate = 0.01;

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  // Create a population with a target phrase, mutation rate, and population max

  population = new Population(target, mutationRate, popmax);

}

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function draw() {

  // Generate mating pool

  population.naturalSelection();

  //Create next generation

  population.generate();

  // Calculate fitness

  population.calcFitness();

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  population.evaluate();

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  // If we found the target phrase, stop

  if (population.isFinished()) {

    //println(millis()/1000.0);

    noLoop();

  }

  background(255);

  let answer = population.getBest();

  fill(0);

  textFont("Courier");

  textSize(12);

  text("Best phrase:", 10, 32);

  textSize(24);

  text(answer, 10, 64);

  let statstext =

    "total generations:     " + population.getGenerations() + "\n";

  statstext +=

    "average fitness:       " + nf(population.getAverageFitness(), 0, 2) + "\n";

  statstext += "total population:      " + popmax + "\n";

  statstext += "mutation rate:         " + floor(mutationRate * 100) + "%";

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  textSize(12);

  text(statstext, 10, 96);

  textSize(8);

  text(population.allPhrases(), width / 2, 24);

}

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