public void Instantiate(String jsonWithTypes, String ALYCOMBOOK, String allCardsWithAbility) { liteParser = new HSCardsParser(jsonWithTypes); fullParser = new HSCardsParser(allCardsWithAbility, 0); fullCParser = new HSCombosParser(); fullCParser.PopulateFromJson(ALYCOMBOOK); HSBuilder = new HoningStoneBuilder(); cardOperator = new HSCardOperator(); cartTable = new Dictionary <string, CardObject>(); cardsDataSet = cardOperator.generateCardVectors(fullParser, out dataID); // Populate all card table foreach (string key in liteParser.objects.Keys) { List <CardObject> cards_objects = liteParser.objects[key]; HSBuilder.GenCardTableObject(ref cards_objects, ref cartTable); } honingOBJS = new Dictionary <string, HS_HONING_OBJ>(); heroes = new String[9]; heroes[0] = "Shaman"; heroes[1] = "Mage"; heroes[2] = "Warrior"; heroes[3] = "Druid"; heroes[4] = "Rogue"; heroes[5] = "Priest"; heroes[6] = "Paladin"; heroes[7] = "Warlock"; heroes[8] = "Hunter"; for (int i = 0; i < 9; i++) { HS_HONING_OBJ h_obj = new HS_HONING_OBJ(); h_obj.calibration(heroes[i], liteParser, HSBuilder, fullCParser, cardsDataSet, cartTable, cardOperator); honingOBJS.Add(heroes[i], h_obj); } dataID.Clear(); liteParser.objects.Clear(); fullParser.objects.Clear(); fullCParser.combos_by_quantity.Clear(); dataID = null; liteParser.objects = null; fullParser.objects = null; fullCParser.combos_by_quantity = null; GC.Collect(); GC.WaitForPendingFinalizers(); }
void ValidationTests() { HSCardsParser parser = new HSCardsParser("jsonWithTypes.json"); HoningStoneBuilder builder = new HoningStoneBuilder(); Dictionary <String, CardObject> cardTable = new Dictionary <string, CardObject>(); HSCardOperator op = new HSCardOperator(); // Populate all card table foreach (string key in parser.objects.Keys) { List <CardObject> cards_objects = parser.objects[key]; builder.GenCardTableObject(ref cards_objects, ref cardTable); } HSCombosParser combosParser = new HSCombosParser(); //combosParser.PopulateFromHoningNetwork(ref decksParser, ref cardTable, 5); combosParser.PopulateFromJson("ALYCOMBOOK.json"); int maxComboSize = 10; //int maxMana = 50; int maxCombos = 100; Random rand = new Random(); foreach (String hero in parser.objects.Keys) { if (hero == "Neutral") { continue; } HoningNetwork <String> net = new HoningNetwork <string>(); List <CardObject> heroCards = parser.objects[hero]; List <CardObject> neutral = parser.objects["Neutral"]; builder.PopulateFromCardData(ref net, ref heroCards); builder.BuildThirdLevel(ref net, ref heroCards); builder.PopulateFromCardData(ref net, ref neutral); builder.BuildThirdLevel(ref net, ref neutral); HSHoningBayes fixedBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardTable); fixedBayes.SaveKNNDataset("ARSDataset.dataset"); Dataset fixedDataset = new Dataset("ARSDataset.dataset", ','); KNNEfficiency fixedKNN = new KNNEfficiency(fixedDataset); HSHoningBayes dynamicBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardTable); List <String> Terminals = net.getTerminalList(); // Random Honing config HSCardExpasionConfiguration config = new HSCardExpasionConfiguration(fixedBayes, fixedKNN); config.cutByManaCost = false; config.max_lowerlevel_to_expand = 1; config.giver_inflation = false; // Guided Honing config HSCardExpasionConfiguration configGuided = new HSCardExpasionConfiguration(fixedBayes, fixedKNN); configGuided.cutByManaCost = false; configGuided.max_lowerlevel_to_expand = 1; configGuided.giver_inflation = false; // Tests i and ii control variables double ihs = 0.0f; double iihs = 0.0f; double[] surprise_vec; Double[] comboArray; // Tests i and ii control variables // Tests i, ii, iii, iv, v control variables int mana = 50; double surprise; double efficiency; double creativity; List <String> combo; // Tests i, ii, iii, iv, v control variables int combosize = 5; for (int combos = 0; combos < maxCombos; combos++) { //for (int mana = 2; mana <= maxMana; mana++) //{ //for (int combosize = 2; combosize <= maxComboSize; combosize++) // { // Honing shared seed int RandomicSeed = rand.Next(Terminals.Count); String seed = Terminals[RandomicSeed]; //-------------------------------------------------------------------------------------------------------------------------- // Surpresa estática // (i)totalmente aleatorio (sem honing) /* List<String> randomComboList = new List<String>(); * while(randomComboList.Count < combosize) * { * int randNode = rand.Next(Terminals.Count); * randomComboList.Add(Terminals[randNode]); * } * * // Surprise * ComboNode node = ToComboNode(randomComboList); * * fixedBayes.CalculateSurprise(ref node, 1, out surprise_vec, out surprise, false); * * // update surprise * if (surprise > ihs) * ihs = surprise; * * // Calculate efficiency * fixedBayes.GenerateComboVector(ref node, out comboArray); * Instance target = new Instance(comboArray); * efficiency = fixedKNN.getKNearestWinrates(target, 5); * efficiency /= 100; * * // Calculate creativity * creativity = ((surprise / ihs) + efficiency) / 2; * * //-------------------------------------------------------------------------------------------------------------------------- * * // (ii)honing velho aleatorio * Dictionary<String, String> shcombolist = new Dictionary<String, String>(); * Dictionary<String, HoningNode<String>> honingOut; * List<String> bridges; * net.getMfList(seed, out bridges); * net.recruitNeurds(bridges, out honingOut, "terminal"); * * List<String> comboH = new List<string>(); * * int limit = combosize; * if(honingOut.Count < combosize) * limit = honingOut.Count; * for (int i = 0; i < limit; i++) * comboH.Add(honingOut.ElementAt(i).Key); * * // Surprise * node = ToComboNode(comboH); * * fixedBayes.CalculateSurprise(ref node, 1, out surprise_vec, out surprise, false); * * // update surprise * if (surprise > iihs) * iihs = surprise; * * // Calculate efficiency * fixedBayes.GenerateComboVector(ref node, out comboArray); * target = new Instance(comboArray); * efficiency = fixedKNN.getKNearestWinrates(target, 5); * efficiency /= 100; * * // Calculate creativity * creativity = ((surprise / iihs) + efficiency) / 2; * * //-------------------------------------------------------------------------------------------------------------------------- * * // (iii)honing novo aleatorio * HoningTest( * config, * fixedBayes, * fixedKNN, * mana, * combosize, * net, * cardTable, * seed, * op, * ExpansionGeneralPolitics.Random, * out combo, * out creativity, * out efficiency, * out surprise);*/ //-------------------------------------------------------------------------------------------------------------------------- // (iv)busca pela aresta com maior valor eficiência + surpresa (GULOSO) HoningTest( configGuided, fixedBayes, fixedKNN, mana, combosize, net, cardTable, seed, op, ExpansionGeneralPolitics.Weight, out combo, out creativity, out efficiency, out surprise); Console.WriteLine("Cluster honing finished runing."); //-------------------------------------------------------------------------------------------------------------------------- //-------------------------------------------------------------------------------------------------------------------------- // Surpresa dinâmica // (i)totalmente aleatorio (sem honing) // (ii)honing velho aleatorio // (iii)honing novo aleatorio // (iv)busca pela aresta com maior valor eficiência + surpresa //} } //} } }
void ValidationTests(String cardsJson, String combosFile, String knnDatase, int k) { HSCardsParser parser = new HSCardsParser(cardsJson); HoningStoneBuilder builder = new HoningStoneBuilder(); Dictionary <String, CardObject> cardTable = new Dictionary <string, CardObject>(); HSCardOperator op = new HSCardOperator(); // Populate all card table foreach (string key in parser.objects.Keys) { List <CardObject> cards_objects = parser.objects[key]; builder.GenCardTableObject(ref cards_objects, ref cardTable); } HSCombosParser combosParser = new HSCombosParser(); //combosParser.PopulateFromHoningNetwork(ref decksParser, ref cardTable, 5); combosParser.PopulateFromJson(combosFile); Random rand = new Random(); foreach (String hero in parser.objects.Keys) { // To write results System.IO.StreamWriter file = new System.IO.StreamWriter(hero + "_results.dat"); if (hero == "Neutral") { continue; } List <String> honingCombo; List <String> highestComboI = new List <String>(); List <String> highestComboII = new List <String>();; List <String> highestComboIII = new List <String>();; HoningNetwork <String> net = new HoningNetwork <string>(); List <CardObject> heroCards = parser.objects[hero]; List <CardObject> neutral = parser.objects["Neutral"]; builder.PopulateFromCardData(ref net, ref heroCards); builder.BuildThirdLevel(ref net, ref heroCards); builder.PopulateFromCardData(ref net, ref neutral); builder.BuildThirdLevel(ref net, ref neutral); HSHoningBayes fixedBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardTable); //fixedBayes.SaveKNNDataset("ARSDataset.dataset"); Dataset fixedDataset = new Dataset(knnDatase, ','); KNNEfficiency fixedKNN = new KNNEfficiency(fixedDataset); HSHoningBayes dynamicBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardTable); Dictionary <String, HoningNode <String> > dic = net.getNetwork(); Dictionary <String, String> selfAbilityFilter = op.GenerateAbilityFilter(); Dictionary <String, String> TerminalsDic = op.GetRealComboPotential(ref dic, ref cardTable, ref selfAbilityFilter, 3); List <String> Terminals = TerminalsDic.Keys.ToList(); double[] surprise_vec; Double[] comboArray; // Tests i and ii control variables // Tests i, ii, iii, iv, v control variables int mana = 10; double surprise; double efficiency; double creativity; List <String> combo = new List <string>(); // Tests i, ii, iii, iv, v control variables // Test I double highestCreativityA = 0.0; // Test II double highestCreativityB = 0.0; // Test III double highestCreativityC = 0.0; double highSurp = 0.0; double highestEfficience = 0.0; String seed = ""; foreach (String c in Terminals) { Console.WriteLine("Hero: " + hero); Console.WriteLine("Seed: " + c); file.WriteLine("Hero: " + hero); file.WriteLine("Seed: " + c); // Test all reacheable seeds seed = c; //-------------------------------------------------------------------------------------------------------------------------- // (i)totalmente aleatorio (sem honing) int totalMana = 0; List <String> randomComboList = new List <String>(); randomComboList.Add(seed.ToLower()); int manaCost = 0; Int32.TryParse(cardTable[seed.ToLower()].cost, out manaCost); totalMana += manaCost; while (totalMana < mana) { int randNode = rand.Next(Terminals.Count); Int32.TryParse(cardTable[Terminals[randNode]].cost, out manaCost); if (manaCost + totalMana <= mana) { randomComboList.Add(Terminals[randNode]); totalMana += manaCost; } } // Surprise ComboNode node = ToComboNode(randomComboList); fixedBayes.CalculateSurprise(ref node, 1, out surprise_vec, out surprise, false); // Calculate efficiency fixedBayes.GenerateComboVector(ref node, out comboArray); Instance target = new Instance(comboArray); efficiency = fixedKNN.getKNearestWinrates(target, k); efficiency /= 100; if (surprise > highSurp) { highSurp = surprise; } if (efficiency > highestEfficience) { highestEfficience = efficiency; } // Calculate creativity creativity = op.CalculateCreativity(surprise / highSurp, efficiency); // Write in file bool update = false; if (creativity > highestCreativityA) { highestCreativityA = creativity; update = true; } Console.WriteLine("I: " + creativity + " " + surprise / highSurp + " " + efficiency); file.WriteLine("I: " + creativity + " " + surprise + " " + efficiency); foreach (String st in randomComboList) { Console.Write(st + "|"); file.Write(st + "|"); if (update) { highestComboI.Add(st); } } Console.WriteLine(); file.WriteLine(); //-------------------------------------------------------------------------------------------------------------------------- // (ii)honing novo aleatorio honingCombo = op.GenerateCardClusterRandom(c, ref cardTable, ref net, ref selfAbilityFilter, ref fixedBayes, ref fixedKNN, mana, k, highSurp, out creativity, out surprise, out efficiency).Keys.ToList(); update = false; if (creativity > highestCreativityB) { highestCreativityB = creativity; update = true; } if (efficiency > highestEfficience) { highestEfficience = efficiency; } file.WriteLine("II: " + creativity + " " + surprise + " " + efficiency); Console.WriteLine("II: " + creativity + " " + surprise + " " + efficiency); foreach (String st in honingCombo) { Console.Write(st + "|"); file.Write(st + "|"); if (update) { highestComboI.Add(st); } } file.WriteLine(); Console.WriteLine(); //-------------------------------------------------------------------------------------------------------------------------- // (iii)honing novo (E+S) honingCombo = op.GenerateCardCluster(c, ref cardTable, ref net, ref selfAbilityFilter, ref fixedBayes, ref fixedKNN, mana, k, ref highSurp, out creativity, out surprise, out efficiency).Keys.ToList(); update = false; if (creativity > highestCreativityC) { highestCreativityC = creativity; update = true; } if (efficiency > highestEfficience) { highestEfficience = efficiency; } file.WriteLine("III: " + creativity + " " + surprise + " " + efficiency); Console.WriteLine("III: " + creativity + " " + surprise + " " + efficiency); foreach (String st in honingCombo) { Console.Write(st + "|"); file.Write(st + "|"); if (update) { highestComboI.Add(st); } } file.WriteLine(); Console.WriteLine(); Console.WriteLine("----------------------------------------------------------------"); } file.Close(); } }
void ValidationTests(String cardsJson, String combosFile, int k) { HSCardsParser parser = new HSCardsParser(cardsJson); HoningStoneBuilder builder = new HoningStoneBuilder(); Dictionary <String, CardObject> cardTable = new Dictionary <string, CardObject>(); HSCardOperator op = new HSCardOperator(); HSCardsParser fullParser = new HSCardsParser("allCardsWithAbility.json", 0); Dictionary <String, int> dataID; Dictionary <String, double[]> cardDatasetFull = op.generateCardVectors(fullParser, out dataID); // Populate all card table foreach (string key in parser.objects.Keys) { List <CardObject> cards_objects = parser.objects[key]; builder.GenCardTableObject(ref cards_objects, ref cardTable); } HSCombosParser combosParser = new HSCombosParser(); //combosParser.PopulateFromHoningNetwork(ref decksParser, ref cardTable, 5); combosParser.PopulateFromJson(combosFile); Random rand = new Random(); List <CardObject> neutral = parser.objects["Neutral"]; foreach (String hero in parser.objects.Keys) { // To write results System.IO.StreamWriter file = new System.IO.StreamWriter(hero + "_results.dat"); if (hero != "Mage") { continue; } List <String> honingCombo; HoningNetwork <String> net = new HoningNetwork <string>(); List <CardObject> heroCards = parser.objects[hero]; builder.PopulateFromCardData(ref net, ref heroCards); builder.BuildThirdLevel(ref net, ref heroCards); builder.PopulateFromCardData(ref net, ref neutral); builder.BuildThirdLevel(ref net, ref neutral); HSHoningBayes fixedBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardDatasetFull, ref cardTable, 100000); fixedBayes.SaveKNNDataset(hero + "_data.dataset"); Dataset fixedDataset = new Dataset(hero + "_data.dataset", ','); KNNEfficiency fixedKNN = new KNNEfficiency(fixedDataset); Dictionary <String, HoningNode <String> > dic = net.getNetwork(); Dictionary <String, String> selfAbilityFilter = op.GenerateAbilityFilter(); Dictionary <String, String> TerminalsDic = op.GetComboPotential(ref dic, ref cardTable, ref selfAbilityFilter, 123123); List <String> Terminals = TerminalsDic.Keys.ToList(); double[] surprise_vec; Double[] comboArray; // Tests i and ii control variables // Tests i, ii, iii, iv, v control variables int mana = 10; double surprise; double efficiency; double fitness; double creativity; double normCreativity; double normSurprise; double normEfficiency; List <String> combo = new List <string>(); double highSurp = 0.0; double minSurp = double.MaxValue; double highEff = 0.0; double minEff = double.MaxValue; // Tests i, ii, iii, iv, v control variables String seed = ""; // Calibrating surprise Console.WriteLine("----------------------------------------------------------------------"); Console.WriteLine("- Calibrating surprise! -"); for (int i = 0; i < 100; i++) { int totalMana = 0; List <String> randomComboList = new List <String>(); int manaCost = 0; while (totalMana < mana) { int randNode = rand.Next(Terminals.Count); Int32.TryParse(cardTable[Terminals[randNode]].cost, out manaCost); if (manaCost + totalMana <= mana) { randomComboList.Add(Terminals[randNode]); totalMana += manaCost; } } // Surprise ComboNode node = ToComboNode(randomComboList); fixedBayes.CalculateSurprise(ref node, 1, out surprise_vec, ref cardDatasetFull, out surprise, false); // Calculate efficiency fixedBayes.GenerateComboVector(ref node, ref cardDatasetFull, out comboArray); Instance target = new Instance(comboArray); efficiency = fixedKNN.getKNearestWinrates(target, k); if (surprise > highSurp) { highSurp = surprise; } if (surprise < minSurp) { minSurp = surprise; } if (efficiency > highEff) { highEff = efficiency; } if (efficiency < minEff) { minEff = efficiency; } } Console.WriteLine("- Surprise calibrated! -"); foreach (String c in Terminals) { Console.WriteLine("----------------------------------------------------------------------"); Console.WriteLine("Hero: " + hero); Console.WriteLine("Seed: " + c); Console.WriteLine(); file.WriteLine("----------------------------------------------------------------------"); file.WriteLine(); file.WriteLine("Hero: " + hero); file.WriteLine("Seed: " + c); // Test all reacheable seeds seed = c; //-------------------------------------------------------------------------------------------------------------------------- // (i)totalmente aleatorio (sem honing) int totalMana = 0; List <String> randomComboList = new List <String>(); randomComboList.Add(seed.ToLower()); int manaCost = 0; Int32.TryParse(cardTable[seed.ToLower()].cost, out manaCost); totalMana += manaCost; while (totalMana < mana) { int randNode = rand.Next(Terminals.Count); Int32.TryParse(cardTable[Terminals[randNode]].cost, out manaCost); if (manaCost + totalMana <= mana) { randomComboList.Add(Terminals[randNode]); totalMana += manaCost; } } // Surprise ComboNode node = ToComboNode(randomComboList); fixedBayes.CalculateSurprise(ref node, 1, out surprise_vec, ref cardDatasetFull, out surprise, false); // Calculate efficiency fixedBayes.GenerateComboVector(ref node, ref cardDatasetFull, out comboArray); Instance target = new Instance(comboArray); efficiency = fixedKNN.getKNearestWinrates(target, k); // Calculate creativity fitness = op.CalculateFitness(surprise, ref highSurp, ref minSurp, out normSurprise, ref highEff, ref minEff, out normEfficiency, efficiency); creativity = surprise + efficiency; normCreativity = normSurprise + normEfficiency; Console.WriteLine("Test I:\n"); Console.WriteLine("Fitness: " + fitness + "\nRaw creativity: " + creativity + "\nNormalized creativity: " + normCreativity + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); Console.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); Console.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); Console.WriteLine("Cards:\n"); file.WriteLine("Test I:\n"); file.WriteLine("Fitness: " + creativity + "\nRaw creativity: " + surprise + efficiency + "\nNormalized creativity: " + normEfficiency + normSurprise + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); file.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); file.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); file.WriteLine(); file.WriteLine("Cards: "); file.WriteLine(); foreach (String st in randomComboList) { Console.Write("(" + st + ") "); file.Write("(" + st + ") "); } Console.WriteLine("\n"); file.WriteLine("\n"); //-------------------------------------------------------------------------------------------------------------------------- // (ii)honing novo aleatorio honingCombo = op.GenerateCardClusterRandom( c, ref cardTable, ref net, ref selfAbilityFilter, ref fixedBayes, ref fixedKNN, ref cardDatasetFull, mana, k, ref highSurp, ref minSurp, ref highEff, ref minEff, out fitness, out surprise, out efficiency, out normSurprise, out normEfficiency).Keys.ToList(); creativity = surprise + efficiency; normCreativity = normSurprise + normEfficiency; Console.WriteLine("Test II:\n"); Console.WriteLine("Fitness: " + fitness + "\nRaw creativity: " + creativity + "\nNormalized creativity: " + normCreativity + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); Console.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); Console.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); Console.WriteLine("Cards:\n"); file.WriteLine("Test I:\n"); file.WriteLine("Fitness: " + creativity + "\nRaw creativity: " + surprise + efficiency + "\nNormalized creativity: " + normEfficiency + normSurprise + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); file.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); file.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); file.WriteLine(); file.WriteLine("Cards: "); file.WriteLine(); foreach (String st in honingCombo) { Console.Write("(" + st + ") "); file.Write("(" + st + ") "); } Console.WriteLine("\n"); file.WriteLine("\n"); //-------------------------------------------------------------------------------------------------------------------------- // (iii)honing novo (E+S) honingCombo = op.GenerateCardCluster( c, ref cardTable, ref net, ref selfAbilityFilter, ref fixedBayes, ref fixedKNN, ref cardDatasetFull, mana, k, ref highSurp, ref minSurp, ref highEff, ref minEff, out fitness, out surprise, out efficiency, out normSurprise, out normEfficiency).Keys.ToList(); creativity = surprise + efficiency; normCreativity = normSurprise + normEfficiency; Console.WriteLine("Test III:\n"); Console.WriteLine("Fitness: " + fitness + "\nRaw creativity: " + creativity + "\nNormalized creativity: " + normCreativity + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); Console.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); Console.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); Console.WriteLine("Cards:\n"); file.WriteLine("Test I:\n"); file.WriteLine("Fitness: " + creativity + "\nRaw creativity: " + surprise + efficiency + "\nNormalized creativity: " + normEfficiency + normSurprise + "\nSurprise " + surprise + "\nNormalized surprise: " + normSurprise + "\nEfficiency: " + efficiency + "\nNormalized efficiency: " + normEfficiency); file.WriteLine("Highest surprise: " + highSurp + "\nLowest surprise: " + minSurp); file.WriteLine("Highest efficiency: " + highEff + "\nLowest efficiency: " + minEff + "\n"); file.WriteLine(); file.WriteLine("Cards: "); file.WriteLine(); foreach (String st in honingCombo) { Console.Write("(" + st + ") "); file.Write("(" + st + ") "); } Console.WriteLine("\n"); file.WriteLine("\n"); } file.Close(); } }
void ValidationTests(String cardsJson, String combosFile, int k) { HSCardsParser parser = new HSCardsParser(cardsJson); HoningStoneBuilder builder = new HoningStoneBuilder(); Dictionary <String, CardObject> cardTable = new Dictionary <string, CardObject>(); HSCardOperator op = new HSCardOperator(); HSCardsParser fullParser = new HSCardsParser("allCardsWithAbility.json", 0); Dictionary <String, int> dataID; Dictionary <String, double[]> cardDatasetFull = op.generateCardVectors(fullParser, out dataID); // Populate all card table foreach (string key in parser.objects.Keys) { List <CardObject> cards_objects = parser.objects[key]; builder.GenCardTableObject(ref cards_objects, ref cardTable); } HSCombosParser combosParser = new HSCombosParser(); //combosParser.PopulateFromHoningNetwork(ref decksParser, ref cardTable, 5); combosParser.PopulateFromJson(combosFile); Random rand = new Random(); List <CardObject> neutral = parser.objects["Neutral"]; String currentDirectory = "results"; bool exists = System.IO.Directory.Exists(currentDirectory); if (!exists) { System.IO.Directory.CreateDirectory(currentDirectory); } // boxplot files System.IO.StreamWriter Fitness = new System.IO.StreamWriter(currentDirectory + "//fit.txt"); System.IO.StreamWriter Efficiency = new System.IO.StreamWriter(currentDirectory + "//eff.txt"); System.IO.StreamWriter Surprise = new System.IO.StreamWriter(currentDirectory + "//sur.txt"); System.IO.StreamWriter Creativity = new System.IO.StreamWriter(currentDirectory + "//crea.txt"); System.IO.StreamWriter fileNormEfficiency = new System.IO.StreamWriter(currentDirectory + "//norm_eff.txt"); System.IO.StreamWriter fileNormSurprise = new System.IO.StreamWriter(currentDirectory + "//norm_sur.txt"); System.IO.StreamWriter fileNormCreativity = new System.IO.StreamWriter(currentDirectory + "//norm_crea.txt"); Fitness.WriteLine("Hero Algorithm Value"); Efficiency.WriteLine("Hero Algorithm Value"); Surprise.WriteLine("Hero Algorithm Value"); Creativity.WriteLine("Hero Algorithm Value"); fileNormEfficiency.WriteLine("Hero Algorithm Value"); fileNormSurprise.WriteLine("Hero Algorithm Value"); fileNormCreativity.WriteLine("Hero Algorithm Value"); foreach (String hero in parser.objects.Keys) { if (hero == "Neutral") { continue; } List <String> honingCombo; HoningNetwork <String> net = new HoningNetwork <string>(); List <CardObject> heroCards = parser.objects[hero]; builder.PopulateFromCardData(ref net, ref heroCards); builder.BuildThirdLevel(ref net, ref heroCards); builder.PopulateFromCardData(ref net, ref neutral); builder.BuildThirdLevel(ref net, ref neutral); HSHoningBayes fixedBayes = new HSHoningBayes(hero.ToLower(), ref combosParser, ref net, ref cardDatasetFull, ref cardTable, 100000); fixedBayes.SaveKNNDataset(hero + "_data.dataset"); Dataset fixedDataset = new Dataset(hero + "_data.dataset", ','); KNNEfficiency fixedKNN = new KNNEfficiency(fixedDataset); Dictionary <String, HoningNode <String> > dic = net.getNetwork(); Dictionary <String, String> selfAbilityFilter = op.GenerateAbilityFilter(); Dictionary <String, String> TerminalsDic = op.GetComboPotential(ref dic, ref cardTable, ref selfAbilityFilter, 10); List <String> Terminals = TerminalsDic.Keys.ToList(); // Tests i, ii, iii, iv, v control variables int mana = 10; double surprise; double efficiency; double fitness; double creativity; double normCreativity; double normSurprise; double normEfficiency; List <String> combo = new List <string>(); double highSurp = 0.0; double minSurp = double.MaxValue; double highEff = 0.0; double minEff = double.MaxValue; // Tests i, ii, iii, iv, v control variables String seed = ""; Console.WriteLine("----------------------------------------------------------------------"); Console.WriteLine("- Loading calibrated surprise! -"); string[] lines = System.IO.File.ReadAllLines(hero + "_calibration.cal"); char[] delim = new char[1]; delim[0] = ' '; String highSurprise = lines[0].Split(delim).Last(); String minSurprise = lines[1].Split(delim).Last(); String highEfficiency = lines[2].Split(delim).Last(); String minEfficiency = lines[3].Split(delim).Last(); double.TryParse(highSurprise, out highSurp); double.TryParse(minSurprise, out minSurp); double.TryParse(highEfficiency, out highEff); double.TryParse(minEfficiency, out minEff); int seedCount = 1; int totalTestsPerSeed = 10; // Foreach percentage for (int percentage = 20; percentage <= 100; percentage += 20) { // To write results System.IO.StreamWriter resultFile = new System.IO.StreamWriter(currentDirectory + "//" + hero + "_results_II_" + percentage + ".dat"); // To calculate statistics List <result> listres = new List <result>(); foreach (String c in Terminals) { //String c = Terminals.First(); Console.WriteLine("----------------------------------------------------------------------"); Console.WriteLine("Hero: " + hero); Console.WriteLine("Seed: " + c); Console.WriteLine("Seed " + seedCount + " of " + Terminals.Count); Console.WriteLine(); // Test all reacheable seeds seed = c; for (int i = 0; i < totalTestsPerSeed; i++) { // (iii)honing novo (E+S) honingCombo = op.GenerateCardCluster( c, ref cardTable, ref net, ref selfAbilityFilter, ref fixedBayes, ref fixedKNN, ref cardDatasetFull, mana, k, percentage, false, ref highSurp, ref minSurp, ref highEff, ref minEff, out fitness, out surprise, out efficiency, out normSurprise, out normEfficiency).Keys.ToList(); creativity = surprise + efficiency; normCreativity = normSurprise + normEfficiency; result res = new result(honingCombo, fitness, creativity, normCreativity, surprise, normSurprise, efficiency, normEfficiency, highSurp, minSurp, highEff, minEff); listres.Add(res); } seedCount++; } // Renormalize and recalibrate limits List <result> renormalizedResults = renormalizeSimple(listres, ref highSurp, ref minSurp, ref minEff, ref highEff); // Write to file foreach (result r in renormalizedResults) { r.writeIntoFile(resultFile); } //extractViableSeeds(op, hero, 0, 1, meanFitness, meanEfficiency, meanSurprise, meanCreativity); writeForBoxPlot(hero, renormalizedResults, "II" + percentage, Fitness, Efficiency, Surprise, Creativity, fileNormEfficiency, fileNormSurprise, fileNormCreativity); resultFile.Close(); } // end statistics } // end hero // boxplot closing Fitness.Close(); Efficiency.Close(); Surprise.Close(); Creativity.Close(); fileNormCreativity.Close(); fileNormEfficiency.Close(); fileNormSurprise.Close(); }