Remove the broken isomorphism tests leaving the reduction test working.

diff --git a/mjo/cone/cone.py b/mjo/cone/cone.py
index 3f5a4fed4e1c49853f00eafcf6084744223ca296..48e6f4363aadcf3f668603fa2e8019fdb9e107d2 100644 (file)
--- a/mjo/cone/cone.py
+++ b/mjo/cone/cone.py
@@ -37,32 +37,6 @@ def span_iso(K):
         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())
@@ -424,12 +398,10 @@ def lyapunov_rank(K):
 
         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, 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
-        True
         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