| public static StartCoroutine ( IEnumerator iterationResult ) : Coroutine | ||
| iterationResult | IEnumerator | |
| Résultat | Coroutine | |
internal static void MakeDownloadCall(string url, Action <string> resultCallback)
{
EdExLogger.LoggerInstance.LogWithTimeStamp("Downloading file: " + url);
var www = UnityWebRequest.Get(url);
AppCenterEditor.RaiseStateUpdate(AppCenterEditor.EdExStates.OnHttpReq, url, AppCenterEditorHelper.MSG_SPIN_BLOCK);
Coroutiner.StartCoroutine(PostDownload(www, response =>
{
resultCallback(WriteResultFile(url, response));
}, AppCenterEditorHelper.SharedErrorCallback));
}
private IEnumerator CheckTouch()
{
yield return(new WaitForSeconds(1));
if ((Time.time - matchTileGridModel.lastTouchedTimestamp) >= matchTileGridModel.secondsUntilHint)
{
matchTileGridModel.lastTouchedTimestamp = Time.time;
DisplayHint();
}
Coroutiner.StartCoroutine(CheckTouch());
}
public void Execute()
{
matchTileQueue.Add (removeTile);
if (matchTileQueue.Count == 1)
{
matchTileGridModel.pauseTilesFalling = true;
enumerator = Remove ();
Coroutiner.StartCoroutine (enumerator);
}
}
public IEnumerator DoOneGeneration()
{
_currentGeneration++;
yield return(Coroutiner.StartCoroutine(PerformOneGeneration()));
if (UpdateTest())
{
_prevUpdateGeneration = _currentGeneration;
_prevUpdateTimeTick = DateTime.Now.Ticks;
OnUpdateEvent();
}
}
internal static void MakeDownloadCall(IEnumerable <string> urls, Action <IEnumerable <string> > resultCallback)
{
EdExLogger.LoggerInstance.LogWithTimeStamp("Downloading files: " + string.Join(", ", urls.ToArray()));
var wwws = new List <UnityWebRequest>();
var downloadRequests = new List <DownloadRequest>();
foreach (var url in urls)
{
var www = UnityWebRequest.Get(url);
wwws.Add(www);
downloadRequests.Add(new DownloadRequest(url, www));
}
AppCenterEditor.RaiseStateUpdate(AppCenterEditor.EdExStates.OnHttpReq, "Downloading files", AppCenterEditorHelper.MSG_SPIN_BLOCK);
Coroutiner.StartCoroutine(DownloadFiles(downloadRequests, resultCallback, AppCenterEditorHelper.SharedErrorCallback));
}
// Use this for initialization
public void BuildObjectPool()
{
ContainerObject = new GameObject("ObjectPoolContainer");
//Loop through the object prefabs and make a new list for each one.
//We do this because the pool can only support prefabs set to it in the editor,
//so we can assume the lists of pooled objects are in the same order as object prefabs in the array
Pool = new List <GameObject> [Entries.Count];
for (int i = 0; i < Entries.Count; i++)
{
Build(i);
}
Coroutiner.StartCoroutine(CompleteObjectPool());
}
private IEnumerator AlgorithmThreadMethodMAP()
{
//print("AlgorithThreadMethod()");
//try
//{
_prevUpdateGeneration = 0;
_prevUpdateTimeTick = DateTime.Now.Ticks;
for (; ;)
{
_currentGeneration++;
// print("currentGeneration: " + _currentGeneration);
yield return(Coroutiner.StartCoroutine(PerformOneGeneration()));
// print("Performed one generation");
// OnUpdateEvent ();
if (UpdateTest())
{
_prevUpdateGeneration = _currentGeneration;
_prevUpdateTimeTick = DateTime.Now.Ticks;
OnUpdateEvent();
}
// Check if a pause has been requested.
// Access to the flag is not thread synchronized, but it doesn't really matter if
// we miss it being set and perform one other generation before pausing.
if (_pauseRequestFlag || _genomeListEvaluator.StopConditionSatisfied)
{
// Signal to any waiting thread that we are pausing
// _awaitPauseEvent.Set();
// Reset the flag. Update RunState and notify any listeners of the state change.
// _pauseRequestFlag = false;
// _runState = RunState.Paused;
OnUpdateEvent();
OnPausedEvent();
break;
// Wait indefinitely for a signal to wake up and continue.
// _awaitRestartEvent.WaitOne();
}
}
//}
//catch(ThreadAbortException)
//{ // Quietly exit thread.
//}
}
public void create(bool firstTime = false)
{
leftEyePos = GameObject.Find("leftEye").transform.localPosition;
rightEyePos = GameObject.Find("rightEye").transform.localPosition;
leftEarPos = GameObject.Find("leftEar").transform.localPosition;
rightEarPos = GameObject.Find("rightEar").transform.localPosition;
nosePos = GameObject.Find("nose").transform.localPosition;
mouthPos = GameObject.Find("mouth").transform.localPosition;
if (this.gameObject.name.Contains("LeftHand"))
{
this.location = "left";
initialPositionV3 = this.gameObject.transform.localPosition;
}
else if (this.gameObject.name.Contains("RightHand"))
{
this.location = "right";
initialPositionV3 = this.gameObject.transform.localPosition;
}
else if (this.gameObject.name.Contains("UpperHand"))
{
this.location = "up";
initialPositionV3 = this.gameObject.transform.localPosition;
}
else if (this.gameObject.name.Contains("DownHand"))
{
this.location = "down";
initialPositionV3 = this.gameObject.transform.localPosition;
}
mainScript = this.gameObject.GetComponentInParent <MainScript>();
if (firstTime)
{
Coroutiner.StartCoroutine(StartAnimation(2f, 3f));
}
else
{
Coroutiner.StartCoroutine(StartAnimation(2f / mainScript.myGameDifficulty, 6f / mainScript.myGameDifficulty));
}
}
public IEnumerator EvaluateList(List <TGenome> genomeList)
{
UnityEngine.Debug.Log("TEasdasST!");
//print("StartContinue");
// RunState must be Ready or Paused.
// if (RunState.Ready == _runState) { // Create a new thread and start it running.
// print("RunState ready");
// _runState = RunState.Running;
//
// // FOREVER LOOP
// _currentGeneration++;
//
// UnityEngine.Debug.Log ("Genome List count " + _genomeList.Count);
_genomeList.Clear();
// UnityEngine.Debug.Log ("Genome List count " + _genomeList.Count);
_genomeList.AddRange(genomeList);
// UnityEngine.Debug.Log ("Genome List count " + _genomeList.Count);
// Evaluate genomes.
yield return(Coroutiner.StartCoroutine(_genomeListEvaluator.Evaluate(_genomeList)));
// print("Performed one generation");
// if (UpdateTest ()) {
// _prevUpdateGeneration = _currentGeneration;
// _prevUpdateTimeTick = DateTime.Now.Ticks;
// OnUpdateEvent ();
// }
// FOREVER
// } else if (RunState.Paused == _runState) { // Thread is paused. Resume execution.
// _runState = RunState.Running;
// OnUpdateEvent ();
// _awaitRestartEvent.Set ();
// } else if (RunState.Running == _runState) { // Already running. Log a warning.
// //__log.Warn("StartContinue() called but algorithm is already running.");
// } else {
// throw new SharpNeatException (string.Format ("StartContinue() call failed. Unexpected RunState [{0}]", _runState));
// }
// return null;
}
private IEnumerator evaluateList(IList <TGenome> genomeList)
{
foreach (TGenome genome in genomeList)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
yield return(Coroutiner.StartCoroutine(_phenomeEvaluator.Evaluate(phenome)));
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
}
}
public IEnumerator Until_LateElementCreation_ElementFound()
{
// Arrange
var startTime = Time.time;
const int TIMEOUT = 2, TEST_DELAY = 1;
Coroutiner.StartCoroutine(DelayedSpawnGO(TEST_GO_NAME, TEST_DELAY));
UiElement element = null;
var wait = new UnityDriverWait(_driver, TimeSpan.FromSeconds(TIMEOUT));
// Act
yield return(wait.Until(d =>
d.FindElement(By.Name(TEST_GO_NAME)),
(e) => element = e
));
// Assert
Assert.IsNotNull(element);
Assert.Less(Time.time, startTime + TIMEOUT);
Assert.Greater(Time.time, startTime);
Assert.GreaterOrEqual(Time.time, startTime + TEST_DELAY);
}
private void Build(int i)
{
var objectPrefab = Entries[i];
//create the repository
Pool[i] = new List <GameObject>();
GameObject[] objects = new GameObject[objectPrefab.Count];
//fill it
int n = 0;
for (n = 0; n < objectPrefab.Count; n++)
{
var newObj = GameObject.Instantiate(objectPrefab.Prefab) as GameObject;
newObj.name = objectPrefab.name;
objects[n] = newObj;
PoolObject(newObj, objectPrefab.name);
}
Coroutiner.StartCoroutine(PreloadObjectPoolTextures(objects));
}
/// <summary>
/// Evaluates a list of genomes. Here we select the genomes to be evaluated before invoking
/// _innerEvaluator to evaluate them.
/// </summary>
public IEnumerator Evaluate(IList <TGenome> genomeList)
{
// Select the genomes to be evaluated. Place them in a temporary list of genomes to be
// evaluated after the genome selection loop. The selection is not performed in series
// so that we can wrap parallel execution versions of IGenomeListEvaluator.
List <TGenome> filteredList = new List <TGenome>(genomeList.Count);
foreach (TGenome genome in genomeList)
{
if (_selectionPredicate.Invoke(genome))
{ // Add the genome to the temp list for evaluation later.
filteredList.Add(genome);
}
else
{ // Register that the genome skipped an evaluation.
genome.EvaluationInfo.EvaluationPassCount++;
}
}
// Evaluate selected genomes.
yield return(Coroutiner.StartCoroutine(_innerEvaluator.Evaluate(filteredList)));
}
public IEnumerator Evaluate(IList <TGenome> genomeList)
{
yield return(Coroutiner.StartCoroutine(GameManagerController.inputManagerInstance.simInst.coEvaluator.SubmitGenomesAndWaitUntilTheyAreEvaluated((List <NeatGenome>)genomeList, player)));
#region Log statistics and delete fitness
float totalFitness = 0;
float mxFitness = (float)genomeList[0].EvaluationInfo.Fitness;
float totalComplexity = 0;
float mxComplexity = (float)genomeList[0].Complexity;
foreach (var genome in genomeList)
{
totalFitness += (float)genome.EvaluationInfo.Fitness;
mxFitness = Math.Max(mxFitness, (float)genome.EvaluationInfo.Fitness);
totalComplexity += (float)genome.Complexity;
mxComplexity = Math.Max(mxComplexity, (float)genome.Complexity);
}
Debug.Log(String.Format("Max fitness is {0}; Mean fitnes is {1}; Max complexity is {2}; Mean complexity is {3}",
mxFitness,
totalFitness / genomeList.Count,
mxComplexity,
totalComplexity / genomeList.Count));
#endregion
Debug.Log($"Evaluation {++EvaluationCount} of team {player.Team} has finished");
}
private void GetOAuthToken()
{
Coroutiner.StartCoroutine(SendRequest());
}
/// <summary>
/// 下载协程;
/// </summary>
/// <returns>The base context.</returns>
/// <param name="initCb">下载结束进度.</param>
/// <param name="progressCb">下载进度.</param>
private static IEnumerator _initlizeBaseContext(AssetBundleInitFinish initCb, AssetBundleProgress progressCb)
{
yield return(Coroutiner.StartCoroutine(_initlizeDependData(initCb, progressCb)));
s_bInitlized = true;
}
public void Query(string query, object variables = null, Action <GraphQLResponse> callback = null,
string sToken = "")
{
Coroutiner.StartCoroutine(SendRequest(query, variables, callback, sToken));
}
public IEnumerator Evaluate(IList <TGenome> genomeList)
{
yield return(Coroutiner.StartCoroutine(evaluateList(genomeList)));
}
private IEnumerator evaluateList(IList <TGenome> genomeList)
{
Dictionary <TGenome, TPhenome> dict = new Dictionary <TGenome, TPhenome>();
Dictionary <TGenome, FitnessInfo[]> fitnessDict = new Dictionary <TGenome, FitnessInfo[]>();
for (int i = 0; i < _optimizer.Trials; i++)
{
//Utility.Log("Iteration " + (i + 1));
_phenomeEvaluator.Reset();
dict = new Dictionary <TGenome, TPhenome>();
foreach (TGenome genome in genomeList)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
if (i == 0)
{
fitnessDict.Add(genome, new FitnessInfo[_optimizer.Trials]);
}
dict.Add(genome, phenome);
//if (!dict.ContainsKey(genome))
//{
// dict.Add(genome, phenome);
// fitnessDict.Add(phenome, new FitnessInfo[_optimizer.Trials]);
//}
Coroutiner.StartCoroutine(_phenomeEvaluator.Evaluate(phenome));
}
}
yield return(new WaitForSeconds(_optimizer.TrialDuration));
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
fitnessDict[genome][i] = fitnessInfo;
}
}
}
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
double fitness = 0;
for (int i = 0; i < _optimizer.Trials; i++)
{
fitness += fitnessDict[genome][i]._fitness;
}
var fit = fitness;
fitness /= _optimizer.Trials; // Averaged fitness
if (fit > _optimizer.StoppingFitness)
{
// Utility.Log("Fitness is " + fit + ", stopping now because stopping fitness is " + _optimizer.StoppingFitness);
// _phenomeEvaluator.StopConditionSatisfied = true;
}
if (_optimizer.SelectionHasBeenMade && _optimizer.SelectedGenomeId == genome.Id)
{
if (_optimizer.TimeSinceSelection < Optimizer.DecayTime)
{
fitness += (Optimizer.DecayTime - _optimizer.TimeSinceSelection) * Optimizer.SelectionBoost;
}
}
genome.EvaluationInfo.SetFitness(fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessDict[genome][0]._auxFitnessArr;
}
}
}
public void Execute()
{
enumerator = Allow();
Coroutiner.StartCoroutine(enumerator);
}
// Use this for initialization
void Start()
{
//PlayerPrefs.DeleteAll();
minigames.Add("TaxMan");
minigames.Add("Networking");
minigames.Add("InvestToProgress");
minigames.Add("GovermentWorkOut");
minigames.Add("Censorship");
minigames.Add("TheWorldBalance");
minigames.Add("Bureaucracy");
minigames.Add("JumpTheTradeBarriers");
minigames.Add("Memory");
FillRandomList();
playedGamesList.Add("TaxManPlayed");
playedGamesList.Add("NetworkingPlayed");
playedGamesList.Add("InvestToProgressPlayed");
playedGamesList.Add("GovermentWorkOutPlayed");
playedGamesList.Add("CensorshipPlayed");
playedGamesList.Add("TheWorldBalancePlayed");
playedGamesList.Add("BureaucracyPlayed");
playedGamesList.Add("JumpTheTradeBarriersPlayed");
playedGamesList.Add("MemoryPlayed");
var totalScore = PlayerPrefs.GetFloat("totalScore");
var score = PlayerPrefs.GetFloat("score");
var sceneName = PlayerPrefs.GetString("sceneName");
var fail = PlayerPrefs.GetInt("fail");
Transform mylabel = transform.Find("Score");
Text t = mylabel.GetComponent <Text>();
totalScore += score;
PlayerPrefs.SetFloat("totalScore", totalScore);
t.text = totalScore.ToString();
Transform levelComplete = transform.Find("LevelComplete");
Text lvlComplete = levelComplete.GetComponent <Text>();
lvlComplete.text = "LEVEL COMPLETE: " + score.ToString();
PlayerPrefs.SetInt(sceneName + "Played", 1); //last scene played
foreach (var playedGameName in playedGamesList) //remove all used scenes
{
if (PlayerPrefs.GetInt(playedGameName) == 1)
{
var sceneNameTemp = playedGameName.Substring(0, playedGameName.Length - 6);
minigamesRandomList.Remove(sceneNameTemp);
}
}
if (minigamesRandomList.Count == 0)
{
FillRandomList();
PlayerPrefs.SetInt("Lvl", PlayerPrefs.GetInt("Lvl") + 1);
}
minigamesRandomList.Shuffle();
Debug.Log(fail + "GO LEVEL" + PlayerPrefs.GetInt("Lvl"));
var lives = PlayerPrefs.GetInt("Lives");
var goHeart = GameObject.Find("heart0");
var goHeart1 = GameObject.Find("heart1");
var goHeart2 = GameObject.Find("heart2");
if (lives <= 0) //END GAME
{
Coroutiner.StartCoroutine(finishGame());
}
else
{
if (lives == 2)
{
DestroyImmediate(goHeart2.gameObject);
}
else if (lives == 1)
{
DestroyImmediate(goHeart2.gameObject);
DestroyImmediate(goHeart1.gameObject);
}
if (fail == 1)
{
lives -= 1;
Debug.Log("***Lives: " + lives);
var heart = GameObject.Find("heart" + lives);
PlayerPrefs.SetInt("Lives", lives);
iTween.FadeTo(heart.gameObject, iTween.Hash(
"alpha", 0,
"time", 0.5f,
"oncomplete", "OnCompleteHeartAnimation",
"oncompletetarget", gameObject,
"oncompleteparams", heart.gameObject,
"islocal", true
));
}
Debug.Log("Lives: " + PlayerPrefs.GetInt("Lives"));
}
}
/*
* public IGenomeDecoder<TGenome, TPhenome> GenomeDecoder
* {
* get { return _genomeDecoder; }
* }
*/
public IEnumerator Evaluate(IList <TGenome> genomeList)
{
// As a coroutine so we have good control of real-time waiting periods.
yield return(Coroutiner.StartCoroutine(evaluateList(genomeList)));
}
/// <summary>
/// 初始化资源管理器.
/// </summary>
/// <param name="strUrlDirectory">下载地址.</param>
/// <param name="initCb">结束下载.</param>
/// <param name="progressCb">进度.</param>
public static void InitlizeAssetBundle(string strPreUrlDirectory, string strRealUrlDirectory, AssetBundleInitFinish initCb, AssetBundleProgress progressCb)
{
if (s_bInitlized)
{
DownLoadProgress downLoadProgress = new DownLoadProgress();
downLoadProgress.bDownload = false;
downLoadProgress.bDownloadFinsih = true;
progressCb(downLoadProgress);
//progressCb(100, false);
initCb(true, "");
return;
}
s_strPreHttpDirectory = strPreUrlDirectory;
s_strRealHttpDirectory = strRealUrlDirectory;
#if UNITY_STANDALONE_WIN
s_strPreHttpDirectory += "/StandaloneWindows/";
s_strRealHttpDirectory += "/StandaloneWindows/";
s_strStreamAssetDir += "/StandaloneWindows/";
#elif UNITY_ANDROID
s_strPreHttpDirectory += "/Android/";
s_strRealHttpDirectory += "/Android/";
s_strStreamAssetDir += "/Android/";
#elif UNITY_IPHONE
s_strPreHttpDirectory += "/iPhone/";
s_strRealHttpDirectory += "/iPhone/";
s_strStreamAssetDir = "file://" + Application.dataPath + "/Raw/iPhone/";
#elif UNITY_WP8
s_strPreHttpDirectory += "/WP8Player/";
s_strRealHttpDirectory += "/WP8Player/";
s_strStreamAssetDir += "/WP8Player/";
#elif UNITY_METRO
s_strPreHttpDirectory += "/MetroPlayer";
s_strRealHttpDirectory += "/MetroPlayer";
s_strStreamAssetDir += "/MetroPlayer";
#endif
#if UNITY_EDITOR
s_strStreamAssetDir = "file:///" + s_strStreamAssetDir;
s_strPersistUrlPath = "file:///" + Application.dataPath;
s_strPersistPath = Application.dataPath;
#endif
#if UNITY_EDITOR
// 标记已初始化;
s_bInitlized = true;
// bin文件加载;
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Bytes/", "bytes", false);
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Bytes/", "txt", false);
// Texture文件加载;
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Texture/", "png", false);
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Texture/", "jpg", false);
// Prefab文件加载;
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Prefab/", "prefab", false);
// 场景文件加载;
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Scene/", "unity", false);
// 声音文件加载;
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Sound/", "mp3", false);
AddDirBinaryFilesToAsset("Assets/Artwork/Download/Sound/", "ogg", false);
DownLoadProgress downLoadProgresst = new DownLoadProgress();
downLoadProgresst.bDownload = false;
downLoadProgresst.bDownloadFinsih = true;
progressCb(downLoadProgresst);
// progressCb(100, false);
initCb(true, "");
#else
//Debug.Log ("StreamAsset Path:" + s_strStreamAssetDir);
//Debug.Log ("PersistPath:" + Application.persistentDataPath);
Coroutiner.StartCoroutine(_initlizeBaseContext(initCb, progressCb));
#endif
}
private void BeginTokenUpdater()
{
Coroutiner.StartCoroutine(UpdateToken());
}
private IEnumerator evaluateList(IList <TGenome> genomeList)
{
Debug.Log("Starting new trial");
// ui
//IECManager.SetUIToSelectionState();
Dictionary <TGenome, TPhenome> dict = new Dictionary <TGenome, TPhenome>();
Dictionary <TGenome, FitnessInfo[]> fitnessDict = new Dictionary <TGenome, FitnessInfo[]>();
for (int i = 0; i < _optimizer.Trials; i++)
{
Utility.Log("Iteration " + (i + 1));
Debug.Log("Creating Genomes...");
_phenomeEvaluator.Reset();
dict = new Dictionary <TGenome, TPhenome>();
foreach (TGenome genome in genomeList)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
if (i == 0)
{
fitnessDict.Add(genome, new FitnessInfo[_optimizer.Trials]);
}
dict.Add(genome, phenome);
//if (!dict.ContainsKey(genome))
//{
// dict.Add(genome, phenome);
// fitnessDict.Add(phenome, new FitnessInfo[_optimizer.Trials]);
//}
//Debug.Log("In simpleEvaluator");
Coroutiner.StartCoroutine(_phenomeEvaluator.Evaluate(phenome));
}
}
yield return(new WaitForSeconds(_optimizer.TrialDuration));
Debug.Log("End of trial");
Debug.Log("Getting fitness values...");
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
fitnessDict[genome][i] = fitnessInfo;
}
}
Debug.Log("Done getting fitness values...");
}
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
double fitness = 0;
for (int i = 0; i < _optimizer.Trials; i++)
{
fitness += fitnessDict[genome][i]._fitness;
}
var fit = fitness;
fitness /= _optimizer.Trials; // Averaged fitness
if (fit > _optimizer.StoppingFitness)
{
// Utility.Log("Fitness is " + fit + ", stopping now because stopping fitness is " + _optimizer.StoppingFitness);
// _phenomeEvaluator.StopConditionSatisfied = true;
}
genome.EvaluationInfo.SetFitness(fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessDict[genome][0]._auxFitnessArr;
}
}
Debug.Log("End of Evaluation of Genome list");
}
private IEnumerator evaluateList(IList <TGenome> genomeList)
{
Dictionary <TGenome, TPhenome> dict = new Dictionary <TGenome, TPhenome>();
Dictionary <TGenome, FitnessInfo[]> fitnessDict = new Dictionary <TGenome, FitnessInfo[]>();
for (int i = 0; i < controller.Trials; i++)
{
Utility.Log("Iteration " + (i + 1));
_phenomeEvaluator.Reset();
dict = new Dictionary <TGenome, TPhenome>();
foreach (TGenome genome in genomeList)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ //Bad genome
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
if (i == 0)
{
fitnessDict.Add(genome, new FitnessInfo[controller.Trials]);
}
dict.Add(genome, phenome);
//if (!dict.ContainsKey(genome))
//{
// dict.Add(genome, phenome);
// fitnessDict.Add(phenome, new FitnessInfo[_optimizer.Trials]);
//}
Coroutiner.StartCoroutine(_phenomeEvaluator.Evaluate(phenome));
}
yield return(new WaitForSeconds(controller.TrialDuration / 4));
}
yield return(new WaitForSeconds(controller.TrialDuration));
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
fitnessDict[genome][i] = fitnessInfo;
}
}
}
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
double fitness = 0;
for (int i = 0; i < controller.Trials; i++)
{
fitness += fitnessDict[genome][i]._fitness;
}
var fit = fitness;
fitness /= controller.Trials; //Average fitness
genome.EvaluationInfo.SetFitness(fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessDict[genome][0]._auxFitnessArr;
}
}
}
public void Execute()
{
enumerator = CheckTouch();
Coroutiner.StartCoroutine(enumerator);
}
/// <summary>
/// This is the main function in this class. It translates every genome
/// (neural network description) into a phenome (functional description
/// of the genome which gets input values and returns output values).
/// Then it instantiates units with this phenomes as controllers and
/// allows them a time to do whatever they must. Finally fitness values
/// are assigned for each genome and units are destroyed.
/// </summary>
private IEnumerator evaluateList(IList <TGenome> genomeList)
{
// We do not want to lose track of which phenome corresponds to each
// genome!
Dictionary <TGenome, TPhenome> dict = new Dictionary <TGenome, TPhenome>();
// If there is more than one trial we need to write down the fitness
// value obtained by units in each case.
Dictionary <TGenome, FitnessInfo[]> fitnessDict =
new Dictionary <TGenome, FitnessInfo[]>();
// Units can be tested in several trials to get an average evaluation
for (int i = 0; i < _optimizer.Trials; i++)
{
Utility.Log("Iteration " + (i + 1));
_phenomeEvaluator.Reset();
dict = new Dictionary <TGenome, TPhenome>();
foreach (TGenome genome in genomeList)
{
// Makes a phenome from each genome. In some cases non-viable
// genomes are allowed. Those get fitness = 0.
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
// There may be more than one trial. Every genome needs
// a fitness result for each. So we allocate enough space
// in the dictionary for this (this is why the value in
// the dictionary is an array). Allocation needs only
// happen once, thus if (i == 0).
if (i == 0)
{
fitnessDict.Add(genome, new FitnessInfo[_optimizer.Trials]);
}
dict.Add(genome, phenome);
//if (!dict.ContainsKey(genome))
//{
// dict.Add(genome, phenome);
// fitnessDict.Add(phenome, new FitnessInfo[_optimizer.Trials]);
//}
// This is where the unit is actually instantiated and
// where its fitness is evaluated
Coroutiner.StartCoroutine(_phenomeEvaluator.Evaluate(phenome));
}
}
// The previous coroutine will wait this period of time before
// calculating the fitness values.
yield return(new WaitForSeconds(_optimizer.TrialDuration));
// Now we can store the fitness values.
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
fitnessDict[genome][i] = fitnessInfo;
}
}
}
// Every genome has now a fitness value for each trial. Here we
// process that information and get an average result.
foreach (TGenome genome in dict.Keys)
{
TPhenome phenome = dict[genome];
if (phenome != null)
{
double fitness = 0;
for (int i = 0; i < _optimizer.Trials; i++)
{
fitness += fitnessDict[genome][i]._fitness;
}
var fit = fitness;
fitness /= _optimizer.Trials; // Averaged fitness
// Is any average fitness greated than the fitness target?
if (fit >= _optimizer.StoppingFitness)
{
// Utility.Log("Fitness is " + fit + ",
// stopping now because stopping fitness is " +
// _optimizer.StoppingFitness);
_phenomeEvaluator.StopConditionSatisfied = true;
}
genome.EvaluationInfo.SetFitness(fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessDict[genome][0]._auxFitnessArr;
}
}
}
/// <summary>
/// Progress forward by one generation. Perform one generation/iteration of the evolution algorithm.
/// </summary>
protected override IEnumerator PerformOneGeneration()
{
// Calculate statistics for each specie (mean fitness, target size, number of offspring to produce etc.)
int offspringCount;
SpecieStats[] specieStatsArr = CalcSpecieStats(out offspringCount);
// Create offspring.
List <TGenome> offspringList = CreateOffspring(specieStatsArr, offspringCount);
// Trim species back to their elite genomes.
bool emptySpeciesFlag = TrimSpeciesBackToElite(specieStatsArr);
// Rebuild _genomeList. It will now contain just the elite genomes.
RebuildGenomeList();
// Append offspring genomes to the elite genomes in _genomeList. We do this before calling the
// _genomeListEvaluator.Evaluate because some evaluation schemes re-evaluate the elite genomes
// (otherwise we could just evaluate offspringList).
_genomeList.AddRange(offspringList);
// Evaluate genomes.
yield return(Coroutiner.StartCoroutine(_genomeListEvaluator.Evaluate(_genomeList)));
// Integrate offspring into species.
if (emptySpeciesFlag)
{
// We have one or more terminated species. Therefore we need to fully re-speciate all genomes to divide them
// evenly between the required number of species.
// Clear all genomes from species (we still have the elite genomes in _genomeList).
ClearAllSpecies();
// Speciate genomeList.
_speciationStrategy.SpeciateGenomes(_genomeList, _specieList);
}
else
{
// Integrate offspring into the existing species.
_speciationStrategy.SpeciateOffspring(offspringList, _specieList);
}
//Debug.Assert(!TestForEmptySpecies(_specieList), "Speciation resulted in one or more empty species.");
// Sort the genomes in each specie. Fittest first (secondary sort - youngest first).
SortSpecieGenomes();
// Update stats and store reference to best genome.
UpdateBestGenome();
UpdateStats();
// Determine the complexity regulation mode and switch over to the appropriate set of evolution
// algorithm parameters. Also notify the genome factory to allow it to modify how it creates genomes
// (e.g. reduce or disable additive mutations).
_complexityRegulationMode = _complexityRegulationStrategy.DetermineMode(_stats);
_genomeFactory.SearchMode = (int)_complexityRegulationMode;
switch (_complexityRegulationMode)
{
case ComplexityRegulationMode.Complexifying:
_eaParams = _eaParamsComplexifying;
break;
case ComplexityRegulationMode.Simplifying:
_eaParams = _eaParamsSimplifying;
break;
}
// TODO: More checks.
//Debug.Assert(_genomeList.Count == _populationSize);
}
internal static void MakeGitHubApiCall(string url, Action <string> resultCallback)
{
var www = UnityWebRequest.Get(url);
Coroutiner.StartCoroutine(Post(www, response => { OnGitHubSuccess(resultCallback, response); }, AppCenterEditorHelper.SharedErrorCallback));
}