public void Create_NoInput_WeightsAreEqualToSpecification()
{
// Each outcome has a weighted probablity as described.
// Apple - 10%, Mango - 15%, Cherry - 20%, Melon - 15%, Peach - 10%, Orange - 20%, Lemon - 10%
WeightedSymbolCollectionFactory factory = new WeightedSymbolCollectionFactory();
var symbols = factory.Create();
WeightedSymbol apple = symbols.Single(y => y.Name == "Apple");
WeightedSymbol mango = symbols.Single(y => y.Name == "Mango");
WeightedSymbol cherry = symbols.Single(y => y.Name == "Cherry");
WeightedSymbol melon = symbols.Single(y => y.Name == "Melon");
WeightedSymbol peach = symbols.Single(y => y.Name == "Peach");
WeightedSymbol orange = symbols.Single(y => y.Name == "Orange");
WeightedSymbol lemon = symbols.Single(y => y.Name == "Lemon");
Assert.AreEqual(apple.Weight, 0.1);
Assert.AreEqual(mango.Weight, 0.15);
Assert.AreEqual(cherry.Weight, 0.2);
Assert.AreEqual(melon.Weight, 0.15);
Assert.AreEqual(peach.Weight, 0.1);
Assert.AreEqual(orange.Weight, 0.2);
Assert.AreEqual(lemon.Weight, 0.1);
}
public void Pick_WeightedSymbolCollectionFactory_RandomPicksMatchesWeightDistribution(int tries)
{
RandomWeightedSymbolPicker randomWeightedSymbolPicker = new RandomWeightedSymbolPicker();
WeightedSymbolCollectionFactory weightedSymbolCollectionFactory = new WeightedSymbolCollectionFactory();
IEnumerable <WeightedSymbol> weightedSymbols = weightedSymbolCollectionFactory.Create();
List <WeightedSymbol> picks = randomWeightedSymbolPicker.Pick(weightedSymbols, tries).ToList();
var picksSymbolGroup = picks.GroupBy(y => y);
foreach (var symbolGroup in picksSymbolGroup)
{
WeightedSymbol weightedSymbol = symbolGroup.Key;
int symbolGroupCount = symbolGroup.Count();
// What is the calculated weight of the symbol we actually picked with the random picker?
double avgPickWeight = symbolGroupCount / (double)tries;
// What is the actual predefined weight?
double wsWeight = symbolGroup.Key.Weight;
const double similarPcnt = 0.01;
// The weights should be very similar. Let's say 1% similar.
double wsWeightMin = wsWeight - wsWeight * similarPcnt;
double wsWeightMax = wsWeight + wsWeight * similarPcnt;
Assert.IsTrue(avgPickWeight >= wsWeightMin);
Assert.IsTrue(avgPickWeight <= wsWeightMax);
}
}
public void Create_NoInput_Returns7Symbols()
{
// Create an ASP.Net Core Web API that simulates a spinning wheel that can land on 7 possible outcomes:
WeightedSymbolCollectionFactory factory = new WeightedSymbolCollectionFactory();
var symbols = factory.Create();
Assert.IsTrue(symbols.Count() == 7);
}
public void Pick_WeightedSymbolCollectionFactory_ResultCountMatchesTries(int tries)
{
RandomWeightedSymbolPicker randomWeightedSymbolPicker = new RandomWeightedSymbolPicker();
WeightedSymbolCollectionFactory weightedSymbolCollectionFactory = new WeightedSymbolCollectionFactory();
IEnumerable <WeightedSymbol> weightedSymbols = weightedSymbolCollectionFactory.Create();
List <WeightedSymbol> picks = randomWeightedSymbolPicker.Pick(weightedSymbols, tries).ToList();
Assert.AreEqual(picks.Count, tries);
}
public void Create_NoInput_ContainsAppleMangoCherryMelonPeachOrangeLemon()
{
// Create an ASP.Net Core Web API that simulates a spinning wheel that can land on 7 possible outcomes:
// ["Apple", "Mango", "Cherry", "Melon", "Peach", "Orange", "Lemon"]
WeightedSymbolCollectionFactory factory = new WeightedSymbolCollectionFactory();
var symbols = factory.Create();
Assert.IsTrue(symbols.Any(y => y.Name == "Apple"));
Assert.IsTrue(symbols.Any(y => y.Name == "Mango"));
Assert.IsTrue(symbols.Any(y => y.Name == "Cherry"));
Assert.IsTrue(symbols.Any(y => y.Name == "Melon"));
Assert.IsTrue(symbols.Any(y => y.Name == "Peach"));
Assert.IsTrue(symbols.Any(y => y.Name == "Orange"));
Assert.IsTrue(symbols.Any(y => y.Name == "Lemon"));
}
public RandomWeightedSymbolPickerController(RandomWeightedSymbolPicker randomWeightedSymbolPicker,
WeightedSymbolCollectionFactory weightedSymbolCollectionFactory)
{
this.randomWeightedSymbolPicker = randomWeightedSymbolPicker;
this.weightedSymbolCollectionFactory = weightedSymbolCollectionFactory;
}
