/// <summary>
///
/// </summary>
private void CombineHalfRandom(IDNAF dna1, IDNAF dna2)
{
for (int i = 0; i < _dnaLength; i++)
{
_genes[i] = Random.Range(0, 10) < 5 ? dna1.Genes[i] : dna2.Genes[i];
}
}
/// <summary>
///
/// </summary>
private void CombineHalf(IDNAF dna1, IDNAF dna2)
{
for (int i = 0; i < _dnaLength; i++)
{
_genes[i] = i < (_dnaLength / 2) ? dna1.Genes[i] : dna2.Genes[i];
}
}
/// <summary>
/// Create child dna by breeding two parents from the mating pool
/// </summary>
/// <param name="dna1"></param>
/// <param name="dna2"></param>
/// <returns></returns>
private IDNAF Breed()
{
IDNAF child = new DNAF();
IDNAF parent1 = _matingPool[UnityEngine.Random.Range(0, _matingPool.Count)];
IDNAF parent2 = _matingPool[UnityEngine.Random.Range(0, _matingPool.Count)];
child.Crossover(parent1, parent2);
return(child);
}
/// <summary>
///
/// </summary>
private void Start()
{
_model = GetComponent <StackModel>();
_analyser = GetComponent <StackAnalyser>();
_dna = _model.Stack.DNA;
/*
* instructionSetArray = new GOLInstructionSet[5];
*
* instructionSetArray[0] = _instSetMO1;
* instructionSetArray[1] = _instSetMO2;
* instructionSetArray[2] = _instSetMO3;
* instructionSetArray[3] = _instSetMO5;
* instructionSetArray[4] = _instSetMO8;
*/
}
/// <summary>
///
/// </summary>
/// <param name="dna"></param>
public void SetDNA(IDNAF dna)
{
_dna = dna;
}
/// <summary>
///
/// </summary>
private void Awake()
{
_dna = new DNAF();
InitializeCells();
}
/// <summary>
///
/// </summary>
private void Update()
{
//check if stack is finished building
//if build not complete, leave function
if (_model.BuildComplete == false)
{
return;
}
//if stack building is complete, get fitness / update
if (_model.BuildComplete == true)
{
//calculate fitness
_analyser.Fitness();
//move the stack position
var generations = _population.Population.Count + 1;
Vector3 vector = new Vector3(1.5f * (_currentStack.RowCount) * (_curCount - 1), 0, 1.5f * (_currentStack.ColumnCount));
_currentStack.transform.localPosition = vector;
_currentStack.transform.parent = gameObject.transform;
//add stack to current generation
AddStackToGeneration(_currentStack);
_curCount++;
//if count == popsize recalculate the mating pool
if (_curCount == _genSize)
{
//add generation to the population history
AddGenToPopulation(_currentGeneration);
//run natural selection to generate breeding pool
UpdateMatingPool();
//reset current population array
_currentGeneration = new CellStack[_genSize];
//reset popcounter
_curCount = 0;
//move population
Vector3 vec = new Vector3(0, 0, 1.5f * (_currentStack.ColumnCount));
foreach (var stack in _population.Population)
{
stack.transform.localPosition += vec;
}
}
//breed new dna from mating pool
IDNAF childdna = Breed();
//turn off/deactivate the stack
_currentStack.gameObject.SetActive(false);
Debug.Log("Generation: " + generations + ", Stack: " + _curCount + " | Fitness= " + _currentStack.Fitness);
//reset the stack and insert new dna
_currentStack = Instantiate(_stackPrefab);
_currentStack.SetDNA(childdna);
_model.SetStack(_currentStack);
//synthesize 4 images from child gene
Texture2D texture1 = _seeds[Mathf.RoundToInt(childdna.GetGene(0))];
Texture2D texture2 = _seeds[Mathf.RoundToInt(childdna.GetGene(1))];
Texture2D texture3 = _seeds[Mathf.RoundToInt(childdna.GetGene(2))];
Texture2D texture4 = _seeds[Mathf.RoundToInt(childdna.GetGene(3))];
Texture2D combined = ImageSynthesizer.CombineFour(texture1, texture2, texture3, texture4, _currentStack.RowCount, _currentStack.ColumnCount);
//place the synthesized image into the stack
_currentStack.SetSeed(combined);
//resets/initializes the model using the synthesized image
_model.ResetModel(combined);
//_model.ResetModel();
//Debug.Log("I reseted the model");
}
}
/// <summary>
///
/// </summary>
/// <param name="dna1"></param>
/// <param name="dna2"></param>
public void Crossover(IDNAF dna1, IDNAF dna2)
{
CombineHalfRandom(dna1, dna2);
Mutate();
}
