private void ChangeDifficultyParameter(DifficultyParameter difficultyParameter, int newValue)
{
Assert.IsTrue(newValue >= GameConstants.MinDifficulty && newValue <= GameConstants.MaxDifficulty);
DifficultyCoefs[difficultyParameter] = newValue;
EventLogger.PrintToLog("Difficulty Changed: " + difficultyParameter + " Value: " + newValue);
print("Difficulty Changed: " + difficultyParameter + " Value: " + newValue);
}
public float GetDifficultyMultiplier(DifficultyParameter difficultyParameter)
{
// returned values for parameters between 1 to 5 are the following:
// 0.44 | 0.67 | 1 | 1.5 | 2.25
int difficultyDifference = GameConstants.MidDifficulty - DifficultyCoefs[difficultyParameter];
float difficultyMultiplier = Mathf.Pow(GameConstants.DifficultyCoef, difficultyDifference);
return(difficultyMultiplier);
}
public float GetAverageDifficultyLevel()
{
float avgDifficulty = 0.0f;
for (DifficultyParameter curParam = 0; curParam < DifficultyParameter.DpCount; ++curParam)
{
avgDifficulty += DifficultyCoefs[curParam];
}
avgDifficulty /= (int)DifficultyParameter.DpCount;
return(avgDifficulty);
}
private void RandomDiffAdjustment(bool isIncrement)
{
//TODO LEARN remove below code after ML is implemented
//start
int numRetries = 3;
for (int i = 0; i < numRetries; ++i)
{
DifficultyParameter selectedDifficultyParameter = (DifficultyParameter)Random.Range(0, (int)DifficultyParameter.DpCount);
int oldValue = DifficultyCoefs[selectedDifficultyParameter];
if (isIncrement ? oldValue <GameConstants.MaxDifficulty : oldValue> GameConstants.MinDifficulty)
{
ChangeDifficultyParameter(selectedDifficultyParameter, oldValue + GameConstants.DifficultyStep * (isIncrement ? 1 : -1));
break;
}
}
//end
}
private void DetermineInitialDifficultyLevels()
{
//pull avg difficulty from questionnaire
float initialDifficultyGoal = QuestionnaireManager.DeterminedInitialDifficultyCoef;
//TODO LATER temporarily, we're automatically trying to match starting difficulty level
//with the determined initial difficulty
//by increasing difficulty coefficients until we're close enough to the initial difficulty
const int diffParamCount = (int)DifficultyParameter.DpCount;
int[] difficultyWeights = Enumerable.Repeat(GameConstants.MinDifficulty, diffParamCount).ToArray();
int currentWeightIndex = 0;
float achievedDifficultyCoef = GameConstants.MinDifficulty;
int requiredIncrementCount = 0;
while (achievedDifficultyCoef < initialDifficultyGoal)
{
requiredIncrementCount += GameConstants.DifficultyStep;
difficultyWeights[currentWeightIndex] += GameConstants.DifficultyStep;
currentWeightIndex = (currentWeightIndex + 1) % diffParamCount;
achievedDifficultyCoef = (float)(GameConstants.MinDifficulty * diffParamCount + requiredIncrementCount) / diffParamCount;
}
print("Target: " + initialDifficultyGoal + ", Achieved: " + achievedDifficultyCoef);
//shuffle the array
new System.Random().Shuffle(difficultyWeights);
DifficultyCoefs = new Dictionary <DifficultyParameter, int>(diffParamCount);
for (DifficultyParameter curParam = 0; curParam < DifficultyParameter.DpCount; ++curParam)
{
//TODO LEARN these multipliers have to be pulled out from our learning data (from existing player models)
DifficultyCoefs.Add(curParam, difficultyWeights[(int)curParam]);
print("Param: " + curParam + " Weight: " + DifficultyCoefs[curParam]);
}
print("Average Difficulty: " + GetAverageDifficultyLevel());
}
