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# 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 :class:`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 :class:`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.

  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

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