public void LearningMultiplier()
{
var special = new FastLearner();
data.AddSpecial(special);
int increment = 10;
data.IncrementFreeScore(increment);
Assert.AreEqual(data.FreeScore, increment * (1f + special.GetLearningMultiplier()));
}
/// <summary>
/// Generates a Special Employee, by generating Skills Special, etc. for the Employee.
/// </summary>
/// <param name="empDef">The EmployeeDefinition this Employee is built upon.</param>
/// <returns>Employee Data for the EmployeeDefinition</returns>
public virtual EmployeeData GenerateSpecialEmployee(EmployeeDefinition empDef)
{
EmployeeData employee = new EmployeeData
{
EmployeeDefinition = empDef,
Skills = GenerateSkills(),
hireableDays = empDef.SpawnLikelihood == 1 ? -1 : rnd.Next(3, 7)
};
foreach (var special in empDef.EmployeeSpecials)
{
var matches = EmployeeSpecials.Where(s => s.Name == special).ToList();
if (matches.Any())
{
var instance = (EmployeeSpecial)Activator.CreateInstance(matches.First());
employee.AddSpecial(instance);
}
}
addSpecials(employee);
LevelUpSkills(employee.Skills);
employee.Salary = calcSalary(employee);
employee.Prize = calcPrize(employee);
return(employee);
}
private static void addSpecials(EmployeeData employee)
{
if (RandomUtils.RollDice(20) == 13)
{
EmployeeSpecial special;
do
{
special = (EmployeeSpecial)Activator.CreateInstance(EmployeeSpecials.RandomElement());
} while (!special.IsLearnable() || employee.GetSpecials().Any(e => e.GetType() == special.GetType()));
employee.AddSpecial(special);
}
}