from sage.all import *
+def project_span(K):
+ r"""
+ Project ``K`` into its own span.
+
+ EXAMPLES::
+
+ sage: K = Cone([(1,)])
+ sage: project_span(K) == K
+ True
+
+ sage: K2 = Cone([(1,0)])
+ sage: project_span(K2).rays()
+ N(1)
+ in 1-d lattice N
+ sage: K3 = Cone([(1,0,0)])
+ sage: project_span(K3).rays()
+ N(1)
+ in 1-d lattice N
+ sage: project_span(K2) == project_span(K3)
+ True
+
+ TESTS:
+
+ The projected cone should always be solid::
+
+ sage: K = random_cone()
+ sage: K_S = project_span(K)
+ sage: K_S.is_solid()
+ True
+
+ If we do this according to our paper, then the result is proper::
+
+ sage: K = random_cone()
+ sage: K_S = project_span(K)
+ sage: P = project_span(K_S.dual()).dual()
+ sage: P.is_proper()
+ True
+
+ """
+ F = K.lattice().base_field()
+ Q = K.lattice().quotient(K.sublattice_complement())
+ vecs = [ vector(F, reversed(list(Q(r)))) for r in K.rays() ]
+
+ L = None
+ if len(vecs) == 0:
+ L = ToricLattice(0)
+
+ return Cone(vecs, lattice=L)
+
+
def rename_lattice(L,s):
r"""
Change all names of the given lattice to ``s``.
sage: phi(K).dim() == phi(K).lattice_dim()
True
- The isomorphism should be an inner product space isomorphism, and
- thus it should preserve dual cones (and commute with the "dual"
- operation). But beware the automatic renaming of the dual lattice.
- OH AND YOU HAVE TO SORT THE CONES::
-
- sage: K = random_cone(max_dim=10, strictly_convex=False, solid=True)
- sage: L = K.lattice()
- sage: rename_lattice(L, 'L')
- sage: (phi, phi_inv) = span_iso(K)
- sage: sorted(phi_inv( phi(K).dual() )) == sorted(K.dual())
- True
-
- We may need to isomorph twice to make sure we stop moving down to
- smaller spaces. (Once you've done this on a cone and its dual, the
- result should be proper.) OH AND YOU HAVE TO SORT THE CONES::
-
- sage: K = random_cone(max_dim=10, strictly_convex=False, solid=False)
- sage: L = K.lattice()
- sage: rename_lattice(L, 'L')
- sage: (phi, phi_inv) = span_iso(K)
- sage: K_S = phi(K)
- sage: (phi_dual, phi_dual_inv) = span_iso(K_S.dual())
- sage: J_T = phi_dual(K_S.dual()).dual()
- sage: phi_inv(phi_dual_inv(J_T)) == K
- True
-
"""
phi_domain = K.sublattice().vector_space()
phi_codo = VectorSpace(phi_domain.base_field(), phi_domain.dimension())
sage: K = random_cone(max_dim=15, solid=False, strictly_convex=False)
sage: actual = lyapunov_rank(K)
- sage: (phi1, phi1_inv) = span_iso(K)
+ sage: (phi1, _) = span_iso(K)
+ sage: K_S = phi1(K)
+ sage: (phi2, _) = span_iso(K_S.dual())
+ sage: J_T = phi2(K_S.dual()).dual()
+ sage: l = K.linear_subspace().dimension()
+ sage: codim = K.lattice_dim() - K.dim()
+ sage: expected = lyapunov_rank(J_T) + K.dim()*(l + codim) + codim**2
+ sage: actual == expected
+ True
+
+ Repeat the previous test with different ``random_cone()`` params::
+
+ sage: K = random_cone(max_dim=15, solid=False, strictly_convex=True)
+ sage: actual = lyapunov_rank(K)
+ sage: (phi1, _) = span_iso(K)
+ sage: K_S = phi1(K)
+ sage: (phi2, _) = span_iso(K_S.dual())
+ sage: J_T = phi2(K_S.dual()).dual()
+ sage: l = K.linear_subspace().dimension()
+ sage: codim = K.lattice_dim() - K.dim()
+ sage: expected = lyapunov_rank(J_T) + K.dim()*(l + codim) + codim**2
+ sage: actual == expected
+ True
+
+ sage: K = random_cone(max_dim=15, solid=True, strictly_convex=False)
+ sage: actual = lyapunov_rank(K)
+ sage: (phi1, _) = span_iso(K)
+ sage: K_S = phi1(K)
+ sage: (phi2, _) = span_iso(K_S.dual())
+ sage: J_T = phi2(K_S.dual()).dual()
+ sage: l = K.linear_subspace().dimension()
+ sage: codim = K.lattice_dim() - K.dim()
+ sage: expected = lyapunov_rank(J_T) + K.dim()*(l + codim) + codim**2
+ sage: actual == expected
+ True
+
+ sage: K = random_cone(max_dim=15, solid=True, strictly_convex=True)
+ sage: actual = lyapunov_rank(K)
+ sage: (phi1, _) = span_iso(K)
sage: K_S = phi1(K)
- sage: (phi2, phi2_inv) = span_iso(K_S.dual())
+ sage: (phi2, _) = span_iso(K_S.dual())
sage: J_T = phi2(K_S.dual()).dual()
- sage: phi1_inv(phi2_inv(J_T)) == K
+ sage: l = K.linear_subspace().dimension()
+ sage: codim = K.lattice_dim() - K.dim()
+ sage: expected = lyapunov_rank(J_T) + K.dim()*(l + codim) + codim**2
+ sage: actual == expected
True
+
+ sage: K = random_cone(max_dim=15)
+ sage: actual = lyapunov_rank(K)
+ sage: (phi1, _) = span_iso(K)
+ sage: K_S = phi1(K)
+ sage: (phi2, _) = span_iso(K_S.dual())
+ sage: J_T = phi2(K_S.dual()).dual()
sage: l = K.linear_subspace().dimension()
sage: codim = K.lattice_dim() - K.dim()
sage: expected = lyapunov_rank(J_T) + K.dim()*(l + codim) + codim**2
sage: actual == expected
True
+ And test with the project_span function::
+
+ sage: K = random_cone(max_dim=15)
+ sage: actual = lyapunov_rank(K)
+ sage: K_S = project_span(K)
+ sage: P = project_span(K_S.dual()).dual()
+ sage: l = K.linear_subspace().dimension()
+ sage: codim = K.lattice_dim() - K.dim()
+ sage: expected = lyapunov_rank(P) + K.dim()*(l + codim) + codim**2
+ sage: actual == expected
+ True
+
"""
return len(LL(K))
projects / sage.d.git / blobdiff