Silverback9

오늘은 To be or not to be 문구를 생성하는 프로그램의 내용을 좀더 자세하게 살펴보겠습니다~^^*

이 코드를 만들어 가며 배우는 과정이 아니라 만들어진 이 코드를 분석하며 배우는 과정이라서 단계별로 소화해서 다시 설명하기에는 시간이 많이 걸릴 것 같아요.

그래서 오늘은 , 코드 분석 동영상 강의를 시청자 모드로 편안하게 보시면 어떨까 합니다~^^*

그리고 관련 코드들을 또한 편안한 시선으로 한 번 훑어 보는 것으로 마무리를 하면 어떨까요~^^*

클래스 DNA 정의 파일입니다~^^*

function newChar() {
  let c = floor(random(63, 122));
  if (c === 63) c = 32;
  if (c === 64) c = 46;

  return String.fromCharCode(c);
}

// Constructor (makes a random DNA)
class DNA {
  constructor(num) {
    // The genetic sequence
    this.genes = [];
    this.fitness = 0;
    for (let i = 0; i < num; i++) {
      this.genes[i] = newChar(); // Pick from range of chars
    }
  }

  // Converts character array to a String
  getPhrase() {
    return this.genes.join("");
  }

  // Fitness function (returns floating point % of "correct" characters)
  calcFitness(target) {
    let score = 0;
    for (let i = 0; i < this.genes.length; i++) {
      if (this.genes[i] == target.charAt(i)) {
        score++;
      }
    }
    this.fitness = score / target.length;
  }

  // Crossover
  crossover(partner) {
    // A new child
    let child = new DNA(this.genes.length);

    let midpoint = floor(random(this.genes.length)); // Pick a midpoint

    // Half from one, half from the other
    for (let i = 0; i < this.genes.length; i++) {
      if (i > midpoint) child.genes[i] = this.genes[i];
      else child.genes[i] = partner.genes[i];
    }
    return child;
  }

  // Based on a mutation probability, picks a new random character
  mutate(mutationRate) {
    for (let i = 0; i < this.genes.length; i++) {
      if (random(1) < mutationRate) {
        this.genes[i] = newChar();
      }
    }
  }
}

클래스 Population 정의 파일입니다~

class Population {
  constructor(p, m, num) {
    this.population; // Array to hold the current population
    this.matingPool; // ArrayList which we will use for our "mating pool"
    this.generations = 0; // Number of generations
    this.finished = false; // Are we finished evolving?
    this.target = p; // Target phrase
    this.mutationRate = m; // Mutation rate
    this.perfectScore = 1;

    this.best = "";

    this.population = [];
    for (let i = 0; i < num; i++) {
      this.population[i] = new DNA(this.target.length);
    }
    this.matingPool = [];
    this.calcFitness();
  }

  // Fill our fitness array with a value for every member of the population
  calcFitness() {
    for (let i = 0; i < this.population.length; i++) {
      this.population[i].calcFitness(target);
    }
  }

  // Generate a mating pool
  naturalSelection() {
    // Clear the ArrayList
    this.matingPool = [];

    let maxFitness = 0;
    for (let i = 0; i < this.population.length; i++) {
      if (this.population[i].fitness > maxFitness) {
        maxFitness = this.population[i].fitness;
      }
    }

    // Based on fitness, each member will get added to the mating pool a certain number of times
    // a higher fitness = more entries to mating pool = more likely to be picked as a parent
    // a lower fitness = fewer entries to mating pool = less likely to be picked as a parent
    for (let i = 0; i < this.population.length; i++) {
      let fitness = map(this.population[i].fitness, 0, maxFitness, 0, 1);
      let n = floor(fitness * 100); // Arbitrary multiplier, we can also use monte carlo method
      for (let j = 0; j < n; j++) {
        // and pick two random numbers
        this.matingPool.push(this.population[i]);
      }
    }
  }

  // Create a new generation
  generate() {
    // Refill the population with children from the mating pool
    for (let i = 0; i < this.population.length; i++) {
      let a = floor(random(this.matingPool.length));
      let b = floor(random(this.matingPool.length));
      let partnerA = this.matingPool[a];
      let partnerB = this.matingPool[b];
      let child = partnerA.crossover(partnerB);
      child.mutate(this.mutationRate);
      this.population[i] = child;
    }
    this.generations++;
  }

  getBest() {
    return this.best;
  }

  // Compute the current "most fit" member of the population
  evaluate() {
    let worldrecord = 0.0;
    let index = 0;
    for (let i = 0; i < this.population.length; i++) {
      if (this.population[i].fitness > worldrecord) {
        index = i;
        worldrecord = this.population[i].fitness;
      }
    }

    this.best = this.population[index].getPhrase();
    if (worldrecord === this.perfectScore) {
      this.finished = true;
    }
  }

  isFinished() {
    return this.finished;
  }

  getGenerations() {
    return this.generations;
  }

  // Compute average fitness for the population
  getAverageFitness() {
    let total = 0;
    for (let i = 0; i < this.population.length; i++) {
      total += this.population[i].fitness;
    }
    return total / this.population.length;
  }

  allPhrases() {
    let everything = "";

    let displayLimit = min(this.population.length, 50);

    for (let i = 0; i < displayLimit; i++) {
      everything += this.population[i].getPhrase() + "<br>";
    }
    return everything;
  }
}

메인 파일입니다~^^*

let target;
let popmax;
let mutationRate;
let population;

let bestPhrase;
let allPhrases;
let stats;

function setup() {
  bestPhrase = createP("Best phrase:");
  //bestPhrase.position(10,10);
  bestPhrase.class("best");

  allPhrases = createP("All phrases:");
  allPhrases.position(600, 10);
  allPhrases.class("all");

  stats = createP("Stats");
  //stats.position(10,200);
  stats.class("stats");

  //createCanvas(640, 360);
  target = "To be or not to be.";
  popmax = 200;
  mutationRate = 0.01;

  // Create a population with a target phrase, mutation rate, and population max
  population = new Population(target, mutationRate, popmax);
}

function draw() {
  // Generate mating pool
  population.naturalSelection();
  //Create next generation
  population.generate();
  // Calculate fitness
  population.calcFitness();

  population.evaluate();

  // If we found the target phrase, stop
  if (population.isFinished()) {
    //println(millis()/1000.0);
    noLoop();
  }

  displayInfo();
}

function displayInfo() {
  // Display current status of population
  let answer = population.getBest();

  bestPhrase.html("Best phrase:<br>" + answer);

  let statstext =
    "total generations:     " + population.getGenerations() + "<br>";
  statstext +=
    "average fitness:       " + nf(population.getAverageFitness()) + "<br>";
  statstext += "total population:      " + popmax + "<br>";
  statstext += "mutation rate:         " + floor(mutationRate * 100) + "%";

  stats.html(statstext);

  allPhrases.html("All phrases:<br>" + population.allPhrases());
}

코드 양이 많고, 이미 만들어진 것을 분석해서 이해하려니 좀 부담스럽기는 한데요~^^*

오늘은 이 내용과 좀더 친해지는 시간을 갖는 것에 의미를 두고~^^*

내일 동영상에서 분석 설명하는 부분들을 좀더 자세하게 살펴보면 어떨까요~^^*

오늘 저와 함께 양이 꽤 되는 코드를 편안한 시선으로 훑어봐 주셔서 감사합니다~^^*

내일 부분 부분 part by part and part to part 좀더 자세히 살펴보면 어떨까요~~^^*?

오늘도

멋진 아침 보내시고요!

점심 맛있게 드시고요!

오늘 하루도 삶의 the Best Part가 될 수 있으면 좋겠어요~^^*

네~~^^* 꿈은 이루어 집니다~~^^*