public BigInteger CalculateDeterminant(VectorND[] newVectorNds)
{
//Es sind nur quatratische Matrizen erlaubt, daher wird N = M vorausgesetzt
if (N != M)
{
throw new Exception("Non-square matrix!");
}
BigInteger[,] basisArray = new BigInteger[N, N];
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
basisArray[i, j] = newVectorNds[i].values[j];
}
}
BigInteger det;
using (var nativeObject = new NTL_Wrapper())
{
det = nativeObject.Determinant(basisArray, N);
}
//Absolut, da Gitterdeterminanten immer positiv sind
return(BigInteger.Abs(det));
}
private static BigInteger ModInverse(BigInteger a, BigInteger mod)
{
BigInteger b;
using (var nativeObject = new NTL_Wrapper())
{
b = nativeObject.ModInverse(a % mod, mod);
}
return(b);
}
public void LLLReduce()
{
ReductionMethod = ReductionMethods.reduceLLL;
BigInteger[,] basisArray = new BigInteger[N, M];
BigInteger[,] transArray = new BigInteger[N, N];
List <BigInteger[, ]> stepList = new List <BigInteger[, ]>();
for (int i = 0; i < N; i++)
{
for (int j = 0; j < M; j++)
{
basisArray[i, j] = Vectors[i].values[j];
}
}
using (var nativeObject = new NTL_Wrapper())
{
nativeObject.LLLReduce(basisArray, transArray, stepList, N, M, 0.99);
}
ReducedVectors = new VectorND[N];
for (int i = 0; i < N; i++)
{
ReducedVectors[i] = new VectorND(M);
for (int j = 0; j < M; j++)
{
ReducedVectors[i].values[j] = basisArray[i, j];
}
}
if (M == 2 && N == 2)
{
AngleReducedVectors = ReducedVectors[0].AngleBetween(ReducedVectors[1]);
CalculateDensity();
}
UnimodTransVectors = new VectorND[N];
for (int i = 0; i < N; i++)
{
UnimodTransVectors[i] = new VectorND(N);
for (int j = 0; j < N; j++)
{
UnimodTransVectors[i].values[j] = transArray[i, j];
}
}
ReductionSteps = new List <VectorND[]>();
foreach (var step in stepList)
{
VectorND[] stepVectors = new VectorND[N];
for (int i = 0; i < N; i++)
{
stepVectors[i] = new VectorND(M);
for (int j = 0; j < M; j++)
{
stepVectors[i].values[j] = step[i, j];
}
}
ReductionSteps.Add(stepVectors);
}
}
