Remove _basically_the_same from cone.py.

diff --git a/mjo/cone/cone.py b/mjo/cone/cone.py
index c1b7ffdcbdc4e6a8e585b38e5493fe1d4060f3c8..5f058ca9a8c055f972ffffaa216975517e0dc723 100644 (file)
--- a/mjo/cone/cone.py
+++ b/mjo/cone/cone.py
@@ -8,89 +8,6 @@ addsitedir(abspath('../../'))
 from sage.all import *
 
 
-def _basically_the_same(K1, K2):
-    r"""
-    Test whether or not ``K1`` and ``K2`` are "basically the same."
-
-    This is a hack to get around the fact that it's difficult to tell
-    when two cones are linearly isomorphic. We have a proposition that
-    equates two cones, but represented over `\mathbb{Q}`, they are
-    merely linearly isomorphic (not equal). So rather than test for
-    equality, we test a list of properties that should be preserved
-    under an invertible linear transformation.
-
-    OUTPUT:
-
-    ``True`` if ``K1`` and ``K2`` are basically the same, and ``False``
-    otherwise.
-
-    EXAMPLES:
-
-    Any proper cone with three generators in `\mathbb{R}^{3}` is
-    basically the same as the nonnegative orthant::
-
-        sage: K1 = Cone([(1,0,0), (0,1,0), (0,0,1)])
-        sage: K2 = Cone([(1,2,3), (3, 18, 4), (66, 51, 0)])
-        sage: _basically_the_same(K1, K2)
-        True
-
-    Negating a cone gives you another cone that is basically the same::
-
-        sage: K = Cone([(0,2,-5), (-6, 2, 4), (0, 51, 0)])
-        sage: _basically_the_same(K, -K)
-        True
-
-    TESTS:
-
-    Any cone is basically the same as itself::
-
-        sage: K = random_cone(max_ambient_dim = 8)
-        sage: _basically_the_same(K, K)
-        True
-
-    After applying an invertible matrix to the rows of a cone, the
-    result should be basically the same as the cone we started with::
-
-        sage: K1 = random_cone(max_ambient_dim = 8)
-        sage: A = random_matrix(QQ, K1.lattice_dim(), algorithm='unimodular')
-        sage: K2 = Cone( [ A*r for r in K1.rays() ], lattice=K1.lattice())
-        sage: _basically_the_same(K1, K2)
-        True
-
-    """
-    if K1.lattice_dim() != K2.lattice_dim():
-        return False
-
-    if K1.nrays() != K2.nrays():
-        return False
-
-    if K1.dim() != K2.dim():
-        return False
-
-    if K1.lineality() != K2.lineality():
-        return False
-
-    if K1.is_solid() != K2.is_solid():
-        return False
-
-    if K1.is_strictly_convex() != K2.is_strictly_convex():
-        return False
-
-    if len(K1.lyapunov_like_basis()) != len(K2.lyapunov_like_basis()):
-        return False
-
-    C_of_K1 = K1.discrete_complementarity_set()
-    C_of_K2 = K2.discrete_complementarity_set()
-    if len(C_of_K1) != len(C_of_K2):
-        return False
-
-    if len(K1.facets()) != len(K2.facets()):
-        return False
-
-    return True
-
-
-
 def _restrict_to_space(K, W):
     r"""
     Restrict this cone a subspace of its ambient space.