public void battleWon()
{
experience += 1.0f;
if (experience >= experienceTarget && level < levelCap)
{
level++;
experience = 0.0f;
experienceTarget = experienceTarget * experienceFactor;
EvaluationProtocol.Stats statToUpgrade = distribution[Rng.generateRandomInt(0, distribution.Count - 1)];
baseFactors[statToUpgrade] += growthFactor;
if (Rng.generateRandomInt(0, 1000) > 970)
{
statToUpgrade = distribution[Rng.generateRandomInt(0, distribution.Count - 1)];
baseFactors[statToUpgrade] += growthFactor;
}
}
}
public void modifyStat(EvaluationProtocol.Stats stat, int value)
{
if (stat.Equals(EvaluationProtocol.Stats.Accuracy))
{
accuracy = value;
}
else if (stat.Equals(EvaluationProtocol.Stats.Endurance))
{
endurance = value;
}
else if (stat.Equals(EvaluationProtocol.Stats.Health))
{
health = value;
}
else if (stat.Equals(EvaluationProtocol.Stats.Speed))
{
speed = value;
}
else if (stat.Equals(EvaluationProtocol.Stats.Strength))
{
strength = value;
}
}
public static Boxer createBoxerBasedOnFame(string firstName, string lastName, int townIndex, float elo, WeightClass.WClass wClass)
{
int pointsToGive = EvaluationProtocol.getBoxerPointsFromFame(elo);
int badStatRates = Mathf.RoundToInt((pointsToGive / 3) / 2);
badStatRates = badStatRates < 1 ? 1 : badStatRates;
List <BoxerClass.Type> possibleClasses = BoxerClass.getClassesBasedOnWeight(wClass);
List <EvaluationProtocol.Stats> stats = new List <EvaluationProtocol.Stats>(new EvaluationProtocol.Stats[] {
EvaluationProtocol.Stats.AccuracyGrowth, EvaluationProtocol.Stats.EnduranceGrowth, EvaluationProtocol.Stats.HealthGrowth,
EvaluationProtocol.Stats.SpeedGrowth, EvaluationProtocol.Stats.StrengthGrowth
});
Dictionary <EvaluationProtocol.Stats, int> growthRates = new Dictionary <EvaluationProtocol.Stats, int>();
Dictionary <EvaluationProtocol.Stats, int> statValues = new Dictionary <EvaluationProtocol.Stats, int>();
foreach (EvaluationProtocol.Stats stat in stats)
{
growthRates.Add(stat, badStatRates);
}
BoxerClass.Type bClass = possibleClasses[generateRandomInt(0, possibleClasses.Count - 1)];
List <EvaluationProtocol.Stats> bestStats = BoxerClass.getBuild(bClass);
for (int i = 0; i < 3; i++)
{
int baseStat = Mathf.RoundToInt(pointsToGive / (3 - i));
if (pointsToGive > 1)
{
baseStat = generateRandomInt(baseStat - 1, baseStat + 1);
baseStat = baseStat < 1 ? 1 : baseStat;
baseStat = baseStat > 10 ? 10 : baseStat;
baseStat = (pointsToGive - baseStat) < 2 ? baseStat - 1 : baseStat;
baseStat = baseStat < 1 ? 1 : baseStat;
}
else
{
baseStat = pointsToGive;
}
EvaluationProtocol.Stats stat = bestStats[generateRandomInt(0, bestStats.Count - 1)];
growthRates[stat] = baseStat;
bestStats.RemoveAt(bestStats.IndexOf(stat));
pointsToGive -= baseStat;
}
int acc = EvaluationProtocol.getStatValueFromGrowthRate(growthRates[EvaluationProtocol.Stats.AccuracyGrowth]);
int end = EvaluationProtocol.getStatValueFromGrowthRate(growthRates[EvaluationProtocol.Stats.EnduranceGrowth]);
int hlt = EvaluationProtocol.getStatValueFromGrowthRate(growthRates[EvaluationProtocol.Stats.HealthGrowth]);
int spd = EvaluationProtocol.getStatValueFromGrowthRate(growthRates[EvaluationProtocol.Stats.SpeedGrowth]);
int str = EvaluationProtocol.getStatValueFromGrowthRate(growthRates[EvaluationProtocol.Stats.StrengthGrowth]);
statValues.Add(EvaluationProtocol.Stats.Accuracy, generateRandomInt(acc - 4, acc + 4));
statValues.Add(EvaluationProtocol.Stats.Endurance, generateRandomInt(end - 4, end + 4));
statValues.Add(EvaluationProtocol.Stats.Health, generateRandomInt(hlt - 4, hlt + 4));
statValues.Add(EvaluationProtocol.Stats.Speed, generateRandomInt(spd - 4, spd + 4));
statValues.Add(EvaluationProtocol.Stats.Strength, generateRandomInt(str - 4, str + 4));
return(new Boxer(
new Vector2Int(0, 1), firstName, lastName, townIndex, generateWeightFromClass(wClass), bClass,
statValues[EvaluationProtocol.Stats.Accuracy], growthRates[EvaluationProtocol.Stats.AccuracyGrowth],
statValues[EvaluationProtocol.Stats.Endurance], growthRates[EvaluationProtocol.Stats.EnduranceGrowth],
statValues[EvaluationProtocol.Stats.Health], growthRates[EvaluationProtocol.Stats.HealthGrowth],
statValues[EvaluationProtocol.Stats.Speed], growthRates[EvaluationProtocol.Stats.SpeedGrowth],
statValues[EvaluationProtocol.Stats.Strength], growthRates[EvaluationProtocol.Stats.StrengthGrowth]));
}
public float getStat(EvaluationProtocol.Stats stat)
{
return(baseFactors[stat]);
}
