+++ /dev/null
-# Sage doesn't load ~/.sage/init.sage during testing (sage -t), so we
-# have to explicitly mangle our sitedir here so that "mjo.cone"
-# resolves.
-from os.path import abspath
-from site import addsitedir
-addsitedir(abspath('../../'))
-
-from sage.all import *
-
-def rearrangement_cone(p,n):
- r"""
- Return the rearrangement cone of order ``p`` in ``n`` dimensions.
-
- The rearrangement cone in ``n`` dimensions has as its elements
- vectors of length ``n``. For inclusion in the cone, the smallest
- ``p`` components of a vector must sum to a nonnegative number.
-
- For example, the rearrangement cone of order ``p == 1`` has its
- single smallest component nonnegative. This implies that all
- components are nonnegative, and that therefore the rearrangement
- cone of order one is the nonnegative orthant.
-
- When ``p == n``, the sum of all components of a vector must be
- nonnegative for inclusion in the cone. That is, the cone is a
- half-space in ``n`` dimensions.
-
- INPUT:
-
- - ``p`` -- The number of components to "rearrange."
-
- - ``n`` -- The dimension of the ambient space for the resulting cone.
-
- OUTPUT:
-
- A polyhedral closed convex cone object representing a rearrangement
- cone of order ``p`` in ``n`` dimensions.
-
- EXAMPLES:
-
- The rearrangement cones of order one are nonnegative orthants::
-
- sage: rearrangement_cone(1,1) == Cone([(1,)])
- True
- sage: rearrangement_cone(1,2) == Cone([(0,1),(1,0)])
- True
- sage: rearrangement_cone(1,3) == Cone([(0,0,1),(0,1,0),(1,0,0)])
- True
-
- When ``p == n``, the resulting cone will be a half-space, so we
- expect its lineality to be one less than ``n`` because it will
- contain a hyperplane but is not the entire space::
-
- sage: rearrangement_cone(5,5).lineality()
- 4
-
- TESTS:
-
- todo.
- should be permutation invariant.
- should have the expected lyapunov rank.
- just loop through them all for n <= 10 and p < n?
-
- """
-
- def d(j):
- v = [1]*n # Create the list of all ones...
- v[j] = 1 - p # Now "fix" the ``j``th entry.
- return v
-
- V = VectorSpace(QQ, n)
- G = V.basis() + [ d(j) for j in range(n) ]
- return Cone(G)