Diamond cutting implementation#

AUTHORS:

  • Jan Poeschko (2012-07-02): initial version

sage.modules.diamond_cutting.calculate_voronoi_cell(basis, radius=None, verbose=False)#

Calculate the Voronoi cell of the lattice defined by basis

INPUT:

  • basis – embedded basis matrix of the lattice

  • radius – radius of basis vectors to consider

  • verbose – whether to print debug information

OUTPUT:

A Polyhedron instance.

EXAMPLES:

sage: from sage.modules.diamond_cutting import calculate_voronoi_cell
sage: V = calculate_voronoi_cell(matrix([[1, 0], [0, 1]]))
sage: V.volume()
1
sage.modules.diamond_cutting.diamond_cut(V, GM, C, verbose=False)#

Perform diamond cutting on polyhedron V with basis matrix GM and radius C.

INPUT:

  • V – polyhedron to cut from

  • GM – half of the basis matrix of the lattice

  • C – radius to use in cutting algorithm

  • verbose – (default: False) whether to print debug information

OUTPUT:

A Polyhedron instance.

EXAMPLES:

sage: from sage.modules.diamond_cutting import diamond_cut
sage: V = Polyhedron([[0], [2]])
sage: GM = matrix([2])
sage: V = diamond_cut(V, GM, 4)
sage: V.vertices()
(A vertex at (2), A vertex at (0))
sage.modules.diamond_cutting.jacobi(M)#

Compute the upper-triangular part of the Cholesky/Jacobi decomposition of the symmetric matrix M.

Let \(M\) be a symmetric \(n \times n\)-matrix over a field \(F\). Let \(m_{i,j}\) denote the \((i,j)\)-th entry of \(M\) for any \(1 \leq i \leq n\) and \(1 \leq j \leq n\). Then, the upper-triangular part computed by this method is the upper-triangular \(n \times n\)-matrix \(Q\) whose \((i,j)\)-th entry \(q_{i,j}\) satisfies

\[\begin{split}q_{i,j} = \begin{cases} \frac{1}{q_{i,i}} \left( m_{i,j} - \sum_{r<i} q_{r,r} q_{r,i} q_{r,j} \right) & i < j, \\ a_{i,j} - \sum_{r<i} q_{r,r} q_{r,i}^2 & i = j, \\ 0 & i > j, \end{cases}\end{split}\]

for all \(1 \leq i \leq n\) and \(1 \leq j \leq n\). (These equalities determine the entries of \(Q\) uniquely by recursion.) This matrix \(Q\) is defined for all \(M\) in a certain Zariski-dense open subset of the set of all \(n \times n\)-matrices.

Note

This should be a method of matrices.

EXAMPLES:

sage: from sage.modules.diamond_cutting import jacobi
sage: jacobi(identity_matrix(3) * 4)
[4 0 0]
[0 4 0]
[0 0 4]

sage: def testall(M):
....:      Q = jacobi(M)
....:      for j in range(3):
....:          for i in range(j):
....:              if Q[i,j] * Q[i,i] != M[i,j] - sum(Q[r,i] * Q[r,j] * Q[r,r] for r in range(i)):
....:                  return False
....:      for i in range(3):
....:          if Q[i,i] != M[i,i] - sum(Q[r,i] ** 2 * Q[r,r] for r in range(i)):
....:              return False
....:          for j in range(i):
....:              if Q[i,j] != 0:
....:                  return False
....:      return True

sage: M = Matrix(QQ, [[8,1,5], [1,6,0], [5,0,3]])
sage: Q = jacobi(M); Q
[    8   1/8   5/8]
[    0  47/8 -5/47]
[    0     0 -9/47]
sage: testall(M)
True

sage: M = Matrix(QQ, [[3,6,-1,7],[6,9,8,5],[-1,8,2,4],[7,5,4,0]])
sage: testall(M)
True
sage.modules.diamond_cutting.plane_inequality(v)#

Return the inequality for points on the same side as the origin with respect to the plane through v normal to v.

EXAMPLES:

sage: from sage.modules.diamond_cutting import plane_inequality
sage: ieq = plane_inequality([1, -1]); ieq
[2, -1, 1]
sage: ieq[0] + vector(ieq[1:]) * vector([1, -1])
0