public void InitializePanelWithTrainerData() {
DebugBot.DebugFunctionCall("TFitnessUI; InitializePanelWithTrainerData(); ", debugFunctionCalls);
Player currentPlayer = trainerModuleScript.gameController.masterTrainer.PlayerList[trainerModuleScript.gameController.masterTrainer.CurPlayer-1];
// SET PENDING values from trainer data:
if(pendingFitnessManager == null) {
pendingFitnessManager = new FitnessManager(currentPlayer);
//CopyFitnessComponentList(currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.masterFitnessCompList, pendingFitnessManager.masterFitnessCompList);
InitializePanelFitnessCompList();
}
if(pendingMiniGameManager == null) {
pendingMiniGameManager = new MiniGameManager(currentPlayer);
}
currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.UpdatePopulationSize(); // Tie this into Population!!!!!
currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.SetMasterFitnessComponentList(); // add fitnessComp lists from brain and minigame
pendingFitnessManager.SetMasterFitnessComponentList();
// OLD:
List<FitnessComponent> dataFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.masterFitnessCompList;
CopyFitnessComponentList(dataFitnessComponentList, pendingFitnessManager.masterFitnessCompList);
// NEW:
List<FitnessComponent> dataBrainFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.brainFitnessComponentList;
CopyFitnessComponentList(dataBrainFitnessComponentList, pendingFitnessManager.brainFitnessComponentList);
List<FitnessComponent> dataGameFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.gameFitnessComponentList;
CopyFitnessComponentList(dataGameFitnessComponentList, pendingFitnessManager.gameFitnessComponentList);
InitializePanelFitnessCompList();
valuesChanged = false;
applyPressed = false;
UpdateUIWithCurrentData();
}
public void CreateFitnessComponentEvaluationGroup(FitnessManager fitnessManager, int genomeIndex)
{
for (int i = 0; i < fitnessManager.fitnessComponentDefinitions.Count; i++)
{
switch (fitnessManager.fitnessComponentDefinitions[i].type)
{
case FitnessComponentType.DistanceToEnemy:
FitCompDistanceToEnemy fitCompDistanceToTargetSquared = new FitCompDistanceToEnemy(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompDistanceToTargetSquared);
break;
case FitnessComponentType.Random:
FitCompRandom fitCompRandom = new FitCompRandom(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompRandom);
break;
case FitnessComponentType.WinLoss:
FitCompWinLoss fitCompWinLoss = new FitCompWinLoss(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompWinLoss);
break;
default:
Debug.LogError("No such component type! (" + fitnessManager.fitnessComponentDefinitions[i].type.ToString() + ")");
break;
}
}
fitnessManager.AddNewFitCompEvalGroup(this, genomeIndex);
}
private void SetUpDefaultFitnessComponents(Challenge.Type challengeType, FitnessManager fitnessManager)
{
switch (challengeType)
{
case Challenge.Type.Test:
FitnessComponentDefinition newComponent = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(newComponent);
break;
case Challenge.Type.Racing:
FitnessComponentDefinition newComponentRacing = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(newComponentRacing);
break;
case Challenge.Type.Combat:
FitnessComponentDefinition newComponentCombat = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(newComponentCombat);
break;
default:
Debug.LogError("ChallengeType Not Found! " + challengeType.ToString());
break;
}
fitnessManager.SetPendingFitnessListFromMaster(); // make pending list a copy of the primary
}
private void EnvironmentCrossover()
{
List <EnvironmentGenome> newGenGenomeList = new List <EnvironmentGenome>(); // new population!
FitnessManager fitnessManager = teamsConfig.environmentPopulation.fitnessManager;
TrainingSettingsManager trainingSettingsManager = teamsConfig.environmentPopulation.trainingSettingsManager;
float mutationChance = trainingSettingsManager.mutationChance;
float mutationStepSize = trainingSettingsManager.mutationStepSize;
// Keep top-half peformers + mutations:
for (int x = 0; x < teamsConfig.environmentPopulation.environmentGenomeList.Count; x++)
{
if (false) //x == 0) {
// Top performer stays
{
EnvironmentGenome parentGenome = teamsConfig.environmentPopulation.environmentGenomeList[fitnessManager.rankedIndicesList[x]];
parentGenome.index = 0;
newGenGenomeList.Add(parentGenome);
}
else
{
int parentIndex = fitnessManager.GetAgentIndexByLottery();
EnvironmentGenome parentGenome = teamsConfig.environmentPopulation.environmentGenomeList[parentIndex];
EnvironmentGenome newGenome = parentGenome.BirthNewGenome(parentGenome, newGenGenomeList.Count, teamsConfig.challengeType, mutationChance, mutationStepSize);
newGenGenomeList.Add(newGenome);
}
}
for (int i = 0; i < teamsConfig.environmentPopulation.environmentGenomeList.Count; i++)
{
teamsConfig.environmentPopulation.environmentGenomeList[i] = newGenGenomeList[i];
}
}
private void AgentCrossover(int playerIndex)
{
List <BrainGenome> newGenBrainGenomeList = new List <BrainGenome>(); // new population!
FitnessManager fitnessManager = teamsConfig.playersList[playerIndex].fitnessManager;
TrainingSettingsManager trainingSettingsManager = teamsConfig.playersList[playerIndex].trainingSettingsManager;
// Keep top-half peformers + mutations:
for (int x = 0; x < teamsConfig.playersList[playerIndex].agentGenomeList.Count; x++)
{
if (x == 0)
{
BrainGenome parentGenome = teamsConfig.playersList[playerIndex].agentGenomeList[fitnessManager.rankedIndicesList[x]].brainGenome;
//parentGenome.index = 0;
newGenBrainGenomeList.Add(parentGenome);
}
else
{
BrainGenome newBrainGenome = new BrainGenome();
int parentIndex = fitnessManager.GetAgentIndexByLottery();
BrainGenome parentGenome = teamsConfig.playersList[playerIndex].agentGenomeList[parentIndex].brainGenome;
newBrainGenome.SetToMutatedCopyOfParentGenome(parentGenome, trainingSettingsManager);
newGenBrainGenomeList.Add(newBrainGenome);
}
}
for (int i = 0; i < teamsConfig.playersList[playerIndex].agentGenomeList.Count; i++)
{
teamsConfig.playersList[playerIndex].agentGenomeList[i].brainGenome = newGenBrainGenomeList[i];
}
}
private void SetUpDefaultFitnessComponents(FitnessManager fitnessManager)
{
FitnessComponentDefinition newComponentCombat = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(newComponentCombat);
//fitnessManager.SetPendingFitnessListFromMaster(); // make pending list a copy of the primary
}
public void BuildTexturesFitnessPerGen(FitnessManager fitnessManager)
{
//DataManager dataManager = player.dataManager;
//BuildTexturesFitnessBasic(dataManager);
//BuildTexturesFitnessAgentsLastGen(dataManager);
//BuildTexturesFitnessComponents(dataManager);
BuildTexturesFitnessBasic(fitnessManager);
}
// Constructor Methods:
public Trial() {
DebugBot.DebugFunctionCall("Trial; Trial(); Constructor", debugFunctionCalls);
miniGameManager = new MiniGameManager(playerRef);
fitnessManager = new FitnessManager(playerRef);
//miniGameManager.playerRef = playerRef;
//miniGameManager.gameType = MiniGameManager.MiniGameType.None;
//masterMiniGame.Shout (); // DEBUG METHOD
numberOfPlays = 1;
maxEvaluationTimeSteps = 30;
power = 1f;
weight = 1f;
}
// Constructor Methods:
public Trial()
{
DebugBot.DebugFunctionCall("Trial; Trial(); Constructor", debugFunctionCalls);
miniGameManager = new MiniGameManager(playerRef);
fitnessManager = new FitnessManager(playerRef);
//miniGameManager.playerRef = playerRef;
//miniGameManager.gameType = MiniGameManager.MiniGameType.None;
//masterMiniGame.Shout (); // DEBUG METHOD
numberOfPlays = 1;
maxEvaluationTimeSteps = 30;
power = 1f;
weight = 1f;
}
// Representative system will be expanded later - for now, just defaults to Top # of performers
public PlayerPopulation(int index, BodyGenome bodyTemplate, int numGenomes, int numPerfReps)
{
this.index = index;
// Re-Factor:
bodyGenomeTemplate = new BodyGenome();
bodyGenomeTemplate.CopyBodyGenomeFromTemplate(bodyTemplate);
//graphKing = new TheGraphKing();
popSize = numGenomes;
//this.numBaseline = numBaseline;
// Create blank AgentGenomes for the standard population
agentGenomeList = new List <AgentGenome>();
historicGenomePool = new List <AgentGenome>();
//baselineGenomePool = new List<AgentGenome>();
for (int j = 0; j < numGenomes; j++)
{
AgentGenome agentGenome = new AgentGenome(j);
agentGenome.InitializeBodyGenomeFromTemplate(bodyGenomeTemplate);
agentGenome.InitializeRandomBrainFromCurrentBody(0.2f);
agentGenomeList.Add(agentGenome);
}
//RepopulateBaselineGenomes();
//AppendBaselineGenomes();
// Representatives:
numPerformanceReps = numPerfReps;
//Debug.Log("historicGenomePool count b4: " + historicGenomePool.Count.ToString());
int numStartingHistoricalReps = 20;
for (int h = 0; h < numStartingHistoricalReps; h++)
{
historicGenomePool.Add(agentGenomeList[h]); // init
}
//Debug.Log("historicGenomePool count after: " + historicGenomePool.Count.ToString());
ResetRepresentativesList();
fitnessManager = new FitnessManager();
SetUpDefaultFitnessComponents(fitnessManager, this.index);
//fitnessManager.ResetHistoricalData();
//fitnessManager.ResetCurrentHistoricalDataLists();
fitnessManager.InitializeForNewGeneration(agentGenomeList.Count);
trainingSettingsManager = new TrainingSettingsManager(0.075f, 0.04f, 0.015f, 0.003f);
}
private void SetUpDefaultFitnessComponents(Challenge.Type challengeType, FitnessManager fitnessManager)
{
switch (challengeType)
{
case Challenge.Type.Test:
//FitnessComponentDefinition fitTest1 = new FitnessComponentDefinition(FitnessComponentType.WinLoss, FitnessComponentMeasure.Last, 1f, true);
//fitnessManager.fitnessComponentDefinitions.Add(fitTest1);
//FitnessComponentDefinition fitTest2 = new FitnessComponentDefinition(FitnessComponentType.DistanceToTargetSquared, FitnessComponentMeasure.Avg, 1f, false);
//fitnessManager.fitnessComponentDefinitions.Add(fitTest2);
FitnessComponentDefinition fitTest1 = new FitnessComponentDefinition(FitnessComponentType.ContactHazard, FitnessComponentMeasure.Avg, 1f, false);
fitnessManager.fitnessComponentDefinitions.Add(fitTest1);
FitnessComponentDefinition fitTest2 = new FitnessComponentDefinition(FitnessComponentType.DistToOrigin, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitTest2);
FitnessComponentDefinition fitTest3 = new FitnessComponentDefinition(FitnessComponentType.Velocity, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitTest3);
break;
case Challenge.Type.Racing:
FitnessComponentDefinition fitCompRacing1 = new FitnessComponentDefinition(FitnessComponentType.ContactHazard, FitnessComponentMeasure.Avg, 1f, false);
fitnessManager.fitnessComponentDefinitions.Add(fitCompRacing1);
FitnessComponentDefinition fitCompRacing2 = new FitnessComponentDefinition(FitnessComponentType.Velocity, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompRacing2);
break;
case Challenge.Type.Combat:
FitnessComponentDefinition fitCompCombat1 = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 0.1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat1);
FitnessComponentDefinition fitCompCombat2 = new FitnessComponentDefinition(FitnessComponentType.Health, FitnessComponentMeasure.Avg, 0.5f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat2);
FitnessComponentDefinition fitCompCombat3 = new FitnessComponentDefinition(FitnessComponentType.DamageInflicted, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat3);
FitnessComponentDefinition fitCompCombat4 = new FitnessComponentDefinition(FitnessComponentType.WinLoss, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat4);
break;
default:
Debug.LogError("ChallengeType Not Found! " + challengeType.ToString());
break;
}
fitnessManager.SetPendingFitnessListFromMaster(); // make pending list a copy of the primary
}
public void InitializePanelWithTrainerData()
{
DebugBot.DebugFunctionCall("TFitnessUI; InitializePanelWithTrainerData(); ", debugFunctionCalls);
Player currentPlayer = trainerModuleScript.gameController.masterTrainer.PlayerList[trainerModuleScript.gameController.masterTrainer.CurPlayer - 1];
// SET PENDING values from trainer data:
if (pendingFitnessManager == null)
{
pendingFitnessManager = new FitnessManager(currentPlayer);
//CopyFitnessComponentList(currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.masterFitnessCompList, pendingFitnessManager.masterFitnessCompList);
InitializePanelFitnessCompList();
}
if (pendingMiniGameManager == null)
{
pendingMiniGameManager = new MiniGameManager(currentPlayer);
}
currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.UpdatePopulationSize(); // Tie this into Population!!!!!
currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.SetMasterFitnessComponentList(); // add fitnessComp lists from brain and minigame
pendingFitnessManager.SetMasterFitnessComponentList();
// OLD:
List <FitnessComponent> dataFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.masterFitnessCompList;
CopyFitnessComponentList(dataFitnessComponentList, pendingFitnessManager.masterFitnessCompList);
// NEW:
List <FitnessComponent> dataBrainFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.brainFitnessComponentList;
CopyFitnessComponentList(dataBrainFitnessComponentList, pendingFitnessManager.brainFitnessComponentList);
List <FitnessComponent> dataGameFitnessComponentList = currentPlayer.masterTrialsList[currentPlayer.currentTrialForEdit].fitnessManager.gameFitnessComponentList;
CopyFitnessComponentList(dataGameFitnessComponentList, pendingFitnessManager.gameFitnessComponentList);
InitializePanelFitnessCompList();
valuesChanged = false;
applyPressed = false;
UpdateUIWithCurrentData();
}
/*public void RepopulateBaselineGenomes() {
* if (baselineGenomePool == null) {
* baselineGenomePool = new List<AgentGenome>();
* }
* else {
* baselineGenomePool.Clear();
* }
*
*
* for (int j = 0; j < numBaseline; j++) {
*
* AgentGenome baselineGenome = new AgentGenome(j);
* baselineGenome.InitializeBodyGenomeFromTemplate(bodyGenomeTemplate);
* float increment = (float)j / (float)(numBaseline - 1);
* float weightScale = 0f; // how much to scale initial random weights
* baselineGenome.InitializeRandomBrainFromCurrentBody(increment * (float)j * weightScale);
* baselineGenomePool.Add(baselineGenome);
* }
* }*/
private void SetUpDefaultFitnessComponents(FitnessManager fitnessManager, int index)
{
//FitnessComponentDefinition fitCompCombat1 = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 0.0f, true);
//fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat1);
if (index == 0)
{
FitnessComponentDefinition fitCompCombat2 = new FitnessComponentDefinition(FitnessComponentType.DistanceToEnemy, FitnessComponentMeasure.Avg, 1f, false);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat2);
}
else
{
//FitnessComponentDefinition fitCompCombat1 = new FitnessComponentDefinition(FitnessComponentType.Random, FitnessComponentMeasure.Avg, 1f, true);
//fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat1);
FitnessComponentDefinition fitCompCombat3 = new FitnessComponentDefinition(FitnessComponentType.DistanceToEnemy, FitnessComponentMeasure.Avg, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitCompCombat3);
}
FitnessComponentDefinition fitComp4 = new FitnessComponentDefinition(FitnessComponentType.WinLoss, FitnessComponentMeasure.Last, 1f, true);
fitnessManager.fitnessComponentDefinitions.Add(fitComp4);
//fitnessManager.SetPendingFitnessListFromMaster(); // make pending list a copy of the primary
}
// Representative system will be expanded later - for now, just defaults to Top # of performers
public PlayerPopulation(Challenge.Type challengeType, BodyGenome bodyTemplate, int numGenomes, int numBaseline, int numReps)
{
bodyGenomeTemplate = new BodyGenome();
bodyGenomeTemplate.CopyBodyGenomeFromTemplate(bodyTemplate);
graphKing = new TheGraphKing();
popSize = numGenomes;
this.numBaseline = numBaseline;
// Create blank AgentGenomes for the standard population
agentGenomeList = new List <AgentGenome>();
historicGenomePool = new List <AgentGenome>();
baselineGenomePool = new List <AgentGenome>();
for (int j = 0; j < numGenomes; j++)
{
AgentGenome agentGenome = new AgentGenome(j);
agentGenome.InitializeBodyGenomeFromTemplate(bodyGenomeTemplate);
agentGenome.InitializeRandomBrainFromCurrentBody(0.0f);
agentGenomeList.Add(agentGenome);
}
RepopulateBaselineGenomes();
AppendBaselineGenomes();
// Representatives:
numPerformanceReps = numReps;
ResetRepresentativesList();
historicGenomePool.Add(agentGenomeList[0]); // init
fitnessManager = new FitnessManager();
SetUpDefaultFitnessComponents(challengeType, fitnessManager);
fitnessManager.ResetHistoricalData();
fitnessManager.ResetCurrentHistoricalDataLists();
fitnessManager.InitializeForNewGeneration(agentGenomeList.Count);
trainingSettingsManager = new TrainingSettingsManager(0.01f, 0.8f, 0.2f, 0.005f);
}
//public int numBaselineReps = 0;
public EnvironmentPopulation(EnvironmentGenome templateGenome, int numGenomes, int numReps)
{
this.templateGenome = templateGenome;
popSize = numGenomes;
//this.numBaseline = numBaseline;
environmentGenomeList = new List <EnvironmentGenome>();
historicGenomePool = new List <EnvironmentGenome>();
//baselineGenomePool = new List<EnvironmentGenome>();
for (int e = 0; e < numGenomes; e++)
{
// Create new environmentGenome
EnvironmentGenome envGenome = new EnvironmentGenome(e);
envGenome.InitializeRandomGenomeFromTemplate(templateGenome);
// Add to envGenomesList:
environmentGenomeList.Add(envGenome);
// Create parallel initial batch of genomes to be used as baseline comparison
//EnvironmentGenome baseGenome = new EnvironmentGenome(e);
//baseGenome.InitializeRandomGenomeFromTemplate(templateGenome);
//baselineGenomePool.Add(baseGenome);
}
//AppendBaselineGenomes();
// Representatives:
numPerformanceReps = numReps;
ResetRepresentativesList();
historicGenomePool.Add(environmentGenomeList[0]); // init
fitnessManager = new FitnessManager();
SetUpDefaultFitnessComponents(fitnessManager);
//fitnessManager.ResetHistoricalData();
fitnessManager.InitializeForNewGeneration(environmentGenomeList.Count);
trainingSettingsManager = new TrainingSettingsManager(0.25f, 0.05f, 0f, 0f);
}
public void SetStatusFromData(TrainingManager trainerRef)
{
this.trainerRef = trainerRef;
int focusPop = trainerRef.evaluationManager.exhibitionTicketList[trainerRef.evaluationManager.exhibitionTicketCurrentIndex].focusPopIndex;
if (focusPop < 1)
{
// env
currentFitnessManagerRef = trainerRef.teamsConfig.environmentPopulation.fitnessManager;
}
else
{
currentFitnessManagerRef = trainerRef.teamsConfig.playersList[focusPop - 1].fitnessManager;
}
Debug.Log("FitnessUI SetStatusFromData! numFitComps: " + currentFitnessManagerRef.pendingFitnessComponentDefinitions.Count.ToString());
// FITNESS COMPONENTS LIST!
foreach (Transform child in transformFitnessCompTableSpace)
{
GameObject.Destroy(child.gameObject);
}
for (int i = 0; i < currentFitnessManagerRef.pendingFitnessComponentDefinitions.Count; i++)
{
GameObject fitnessComponentListRow = (GameObject)Instantiate(goFitnessCompRowPrefab);
FitnessCompRowUI fitnessComponentRowScript = fitnessComponentListRow.GetComponent <FitnessCompRowUI>();
fitnessComponentRowScript.fitnessIndex = i; // CHANGE LATER!!!!!!!
fitnessComponentRowScript.trainerRef = trainerRef;
fitnessComponentRowScript.fitnessFunctionUI = this;
fitnessComponentRowScript.SetStatusFromData();
fitnessComponentListRow.transform.SetParent(transformFitnessCompTableSpace);
}
buttonNewComponentType.GetComponentInChildren <Text>().text = newComponentType.ToString();
}
public void CreateFitnessComponentEvaluationGroup(FitnessManager fitnessManager, int genomeIndex)
{
for (int i = 0; i < fitnessManager.fitnessComponentDefinitions.Count; i++)
{
switch (fitnessManager.fitnessComponentDefinitions[i].type)
{
case FitnessComponentType.DistanceToTargetSquared:
FitCompDistanceToTargetSquared fitCompDistanceToTargetSquared = new FitCompDistanceToTargetSquared(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompDistanceToTargetSquared);
break;
case FitnessComponentType.Velocity:
FitCompVelocity fitCompVelocity = new FitCompVelocity(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompVelocity);
break;
case FitnessComponentType.ContactHazard:
FitCompContactHazard fitCompContactHazard = new FitCompContactHazard(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompContactHazard);
break;
case FitnessComponentType.DamageInflicted:
FitCompDamageInflicted fitCompDamageInflicted = new FitCompDamageInflicted(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompDamageInflicted);
break;
case FitnessComponentType.Health:
FitCompHealth fitCompHealth = new FitCompHealth(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompHealth);
break;
case FitnessComponentType.Random:
FitCompRandom fitCompRandom = new FitCompRandom(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompRandom);
break;
case FitnessComponentType.WinLoss:
FitCompWinLoss fitCompWinLoss = new FitCompWinLoss(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompWinLoss);
break;
case FitnessComponentType.DistToOrigin:
FitCompDistFromOrigin fitCompDistFromOrigin = new FitCompDistFromOrigin(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompDistFromOrigin);
break;
case FitnessComponentType.Altitude:
FitCompAltitude fitCompAltitude = new FitCompAltitude(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompAltitude);
break;
case FitnessComponentType.Custom:
FitCompCustom fitCompCustom = new FitCompCustom(fitnessManager.fitnessComponentDefinitions[i]);
fitCompList.Add(fitCompCustom);
break;
default:
Debug.LogError("No such component type! (" + fitnessManager.fitnessComponentDefinitions[i].type.ToString() + ")");
break;
}
}
fitnessManager.AddNewFitCompEvalGroup(this, genomeIndex);
}
/*public void BuildTexturesCurAgentPerTick(Player player, MiniGameManager miniGameManager, int agentIndex) {
* DataManager dataManager = player.dataManager;
* BuildTexturesCurAgentBrainDiagramTick(player, miniGameManager, agentIndex);
* }
*
* public void BuildTexturesCurAgentPerAgent(Player player, int agentIndex) {
* DataManager dataManager = player.dataManager;
* BuildTexturesCurAgentBrainDiagramAgent(player, agentIndex);
* }*/
//#region fitness graph methods
public void BuildTexturesFitnessBasic(FitnessManager fitnessManager)
{
int texWidthAlltime = fitnessManager.alltimeBaselineVersusAvgScoreRatiosList.Count;
texFitnessAlltime.Resize(texWidthAlltime, 1);
int texWidthCurrent = fitnessManager.curBaselineVersusAvgScoreRatiosList.Count;
texFitnessCurrent.Resize(texWidthCurrent, 1);
for (int y = 0; y < 1; y++) // not needed for this due to 1 pixel height
{
for (int x = 0; x < texWidthAlltime; x++)
{
float pixValueMinRatio = fitnessManager.alltimeBaselineVersusMinScoreRatiosList[x];
float pixValueAvgRatio = fitnessManager.alltimeBaselineVersusAvgScoreRatiosList[x];
float pixValueMaxRatio = fitnessManager.alltimeBaselineVersusMaxScoreRatiosList[x];
float valueRange = fitnessManager.alltimeMaxRatioValue - fitnessManager.alltimeMinRatioValue;
if (valueRange == 0f)
{
pixValueMinRatio = 1f;
pixValueAvgRatio = 1f;
pixValueMaxRatio = 1f;
}
else
{
pixValueMinRatio = (pixValueMinRatio - fitnessManager.alltimeMinRatioValue) / valueRange;
pixValueAvgRatio = (pixValueAvgRatio - fitnessManager.alltimeMinRatioValue) / valueRange;
pixValueMaxRatio = (pixValueMaxRatio - fitnessManager.alltimeMinRatioValue) / valueRange;
}
texFitnessAlltime.SetPixel(x, y, new Color(pixValueMinRatio, pixValueMaxRatio, pixValueAvgRatio));
}
// CURRENT!!!::::
for (int x = 0; x < texWidthCurrent; x++)
{
float pixValueMinRatio = fitnessManager.curBaselineVersusAvgScoreRatiosList[x];
float pixValueAvgRatio = fitnessManager.curBaselineVersusAvgScoreRatiosList[x];
float pixValueMaxRatio = fitnessManager.curBaselineVersusAvgScoreRatiosList[x];
float valueRange = fitnessManager.curMaxRatioValue - fitnessManager.curMinRatioValue;
if (valueRange == 0f)
{
pixValueMinRatio = 1f;
pixValueAvgRatio = 1f;
pixValueMaxRatio = 1f;
}
else
{
pixValueMinRatio = (pixValueMinRatio - fitnessManager.curMinRatioValue) / valueRange;
pixValueAvgRatio = (pixValueAvgRatio - fitnessManager.curMinRatioValue) / valueRange;
pixValueMaxRatio = (pixValueMaxRatio - fitnessManager.curMinRatioValue) / valueRange;
}
texFitnessCurrent.SetPixel(x, y, new Color(pixValueMinRatio, pixValueMaxRatio, pixValueAvgRatio));
}
}
texFitnessAlltime.Apply();
texFitnessCurrent.Apply();
//string fitValues = "Raw: ";
//for (int x = 0; x < texWidth; x++) {
// fitValues += dataManager.generationDataList[x].avgAgentScoreRaw.ToString() + ", ";
//}
Debug.Log("TheGraphKing BuildTexturesFitnessBasic Length: " + texFitnessAlltime.width.ToString() + ", cur: " + texFitnessCurrent.width.ToString());
}
