public static IEnumerable <Multiset <T> > GetAllMultisets(List <T> elements, int maxWeightPerElement)
{
int[] indicies = new int[elements.Count];
while (true)
{
for (int i = 0; i < elements.Count; i++)
{
indicies[i]++;
if (indicies[i] > maxWeightPerElement)
{
indicies[i] = 0;
if (i == elements.Count - 1)
{
yield break;
}
}
else
{
break;
}
}
var resultMset = new HashMultiset <T>();
for (int i = 0; i < elements.Count; i++)
{
resultMset[elements[i]] = indicies[i];
}
yield return(resultMset);
}
}
public static Multiset <T> SampleMultisetUniformNaive(List <T> elements, int count)
{
var result = new HashMultiset <T>();
for (int i = 0; i < count; i++)
{
result[elements[Rand.NextInt(0, elements.Count)]]++;
}
return(result);
}
public static IEnumerable <Multiset <T> > GetMultisets <T>(List <T> elements, int weight)
{
Multiset <T> mset = new HashMultiset <T>();
while (true)
{
bool moreResults = mset.NextMultiset(elements, weight);
yield return(new HashMultiset <T>(mset));
if (!moreResults)
{
break;
}
}
}
public static Multiset <Int64> SampleMultisetUrn(Int64 elementCount, int setWeight, double alpha)
{
var result = new HashMultiset <Int64>();
var urn = new CumulativeProbabilityDistribution(elementCount);
for (int i = 0; i < setWeight; i++)
{
var index = urn.Sample();
urn.AddWeightByIndex(index, alpha);
result[index]++;
}
return(result);
}
public override Multiset <long> SampleElectorate(int voteCount)
{
var result = new HashMultiset <long>();
var electorateOffset = new double[Dimensions.Length];
for (int j = 0; j < Dimensions.Length; j++)
{
electorateOffset[j] = Rand.SampleNormal(0.0, Dimensions[j] / (2 * Math.Sqrt((double)this.DistrictMagnitude)));
}
for (int i = 0; i < voteCount; i++)
{
var voterCoords = new double[Dimensions.Length];
for (int j = 0; j < Dimensions.Length; j++)
{
voterCoords[j] = Rand.SampleNormal(electorateOffset[j], Dimensions[j]);
}
List <Tuple <double, int> > distancesByPartyIndex = new List <Tuple <double, int> >();
for (int p = 0; p < PartyCount; p++)
{
double x = 0.0;
for (int j = 0; j < Dimensions.Length; j++)
{
x += Math.Pow(parties[p].Coords[j] - voterCoords[j], 2.0);
}
distancesByPartyIndex.Add(new Tuple <double, int>(Math.Sqrt(x), p));
}
var prefOrder = (from x in distancesByPartyIndex orderby x.Item1 ascending select x.Item2).ToList();
var index = DiscreteMath.GetIndexByPermutation(prefOrder);
result[index]++;
}
return(result);
}
public HashMultiset <Int64> ToMultiset(int totalVotes)
{
var result = new HashMultiset <Int64>();
for (int i = 0; i < PartyCount; i++)
{
for (int j = 0; j < PartyCount; j++)
{
for (int k = 0; k < PartyCount; k++)
{
if (i != j && j != k && i != k)
{
result[DiscreteMath.GetIndexByPermutation(GetRandPermutation(i, j, k))] += (int)(VotesByParty[i, j, k] * (double)totalVotes);
}
}
}
}
return(result);
}