X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Fcone%2Ftests.py;h=816215c8473910bd3c1cdf7162f05f321a83af25;hb=3cfc8e228ae337aed975118444a8cbad9a5a7ac3;hp=550beb38744f1d399f492aa5d3ef2f7fcc23febb;hpb=342d9147356f7757bed2f9165a600a9e5ec0a5e2;p=sage.d.git

diff --git a/mjo/cone/tests.py b/mjo/cone/tests.py
index 550beb3..816215c 100644
--- a/mjo/cone/tests.py
+++ b/mjo/cone/tests.py
@@ -15,7 +15,6 @@ from sage.all import *
 
 # The double-import is needed to get the underscore methods.
 from mjo.cone.cone import *
-from mjo.cone.cone import _restrict_to_space
 
 #
 # Tests for _restrict_to_space.
@@ -107,11 +106,11 @@ result). Test all four parameter combinations::
     sage: K = random_cone(max_ambient_dim = 8,
     ....:                 strictly_convex=False,
     ....:                 solid=False)
-    sage: K_S = _restrict_to_space(K, K.span())
-    sage: K_SP = _restrict_to_space(K_S.dual(), K_S.dual().span()).dual()
+    sage: K_S = K._restrict_to_space(K.span())
+    sage: K_SP = K_S.dual()._restrict_to_space(K_S.dual().span()).dual()
     sage: K_SP.is_proper()
     True
-    sage: K_SP = _restrict_to_space(K_S, K_S.dual().span())
+    sage: K_SP = K_S._restrict_to_space(K_S.dual().span())
     sage: K_SP.is_proper()
     True
 
@@ -121,11 +120,11 @@ result). Test all four parameter combinations::
     sage: K = random_cone(max_ambient_dim = 8,
     ....:                 strictly_convex=True,
     ....:                 solid=False)
-    sage: K_S = _restrict_to_space(K, K.span())
-    sage: K_SP = _restrict_to_space(K_S.dual(), K_S.dual().span()).dual()
+    sage: K_S = K._restrict_to_space(K.span())
+    sage: K_SP = K_S.dual()._restrict_to_space(K_S.dual().span()).dual()
     sage: K_SP.is_proper()
     True
-    sage: K_SP = _restrict_to_space(K_S, K_S.dual().span())
+    sage: K_SP = K_S._restrict_to_space(K_S.dual().span())
     sage: K_SP.is_proper()
     True
 
@@ -135,11 +134,11 @@ result). Test all four parameter combinations::
     sage: K = random_cone(max_ambient_dim = 8,
     ....:                 strictly_convex=False,
     ....:                 solid=True)
-    sage: K_S = _restrict_to_space(K, K.span())
-    sage: K_SP = _restrict_to_space(K_S.dual(), K_S.dual().span()).dual()
+    sage: K_S = K._restrict_to_space(K.span())
+    sage: K_SP = K_S.dual()._restrict_to_space(K_S.dual().span()).dual()
     sage: K_SP.is_proper()
     True
-    sage: K_SP = _restrict_to_space(K_S, K_S.dual().span())
+    sage: K_SP = K_S._restrict_to_space(K_S.dual().span())
     sage: K_SP.is_proper()
     True
 
@@ -149,11 +148,11 @@ result). Test all four parameter combinations::
     sage: K = random_cone(max_ambient_dim = 8,
     ....:                 strictly_convex=True,
     ....:                 solid=True)
-    sage: K_S = _restrict_to_space(K, K.span())
-    sage: K_SP = _restrict_to_space(K_S.dual(), K_S.dual().span()).dual()
+    sage: K_S = K._restrict_to_space(K.span())
+    sage: K_SP = K_S.dual()._restrict_to_space(K_S.dual().span()).dual()
     sage: K_SP.is_proper()
     True
-    sage: K_SP = _restrict_to_space(K_S, K_S.dual().span())
+    sage: K_SP = K_S._restrict_to_space(K_S.dual().span())
     sage: K_SP.is_proper()
     True
 
@@ -168,8 +167,8 @@ all parameter combinations::
     ....:                 solid=False,
     ....:                 strictly_convex=False)
     sage: K = Cone(random_sublist(J.rays(), 0.5), lattice=J.lattice())
-    sage: K_W_star = _restrict_to_space(K, J.span()).dual()
-    sage: K_star_W = _restrict_to_space(K.dual(), J.span())
+    sage: K_W_star = K._restrict_to_space(J.span()).dual()
+    sage: K_star_W = K.dual()._restrict_to_space(J.span())
     sage: _look_isomorphic(K_W_star, K_star_W)
     True
 
@@ -180,8 +179,8 @@ all parameter combinations::
     ....:                 solid=True,
     ....:                 strictly_convex=False)
     sage: K = Cone(random_sublist(J.rays(), 0.5), lattice=J.lattice())
-    sage: K_W_star = _restrict_to_space(K, J.span()).dual()
-    sage: K_star_W = _restrict_to_space(K.dual(), J.span())
+    sage: K_W_star = K._restrict_to_space(J.span()).dual()
+    sage: K_star_W = K.dual()._restrict_to_space(J.span())
     sage: _look_isomorphic(K_W_star, K_star_W)
     True
 
@@ -192,8 +191,8 @@ all parameter combinations::
     ....:                 solid=False,
     ....:                 strictly_convex=True)
     sage: K = Cone(random_sublist(J.rays(), 0.5), lattice=J.lattice())
-    sage: K_W_star = _restrict_to_space(K, J.span()).dual()
-    sage: K_star_W = _restrict_to_space(K.dual(), J.span())
+    sage: K_W_star = K._restrict_to_space(J.span()).dual()
+    sage: K_star_W = K.dual()._restrict_to_space(J.span())
     sage: _look_isomorphic(K_W_star, K_star_W)
     True
 
@@ -204,8 +203,8 @@ all parameter combinations::
     ....:                 solid=True,
     ....:                 strictly_convex=True)
     sage: K = Cone(random_sublist(J.rays(), 0.5), lattice=J.lattice())
-    sage: K_W_star = _restrict_to_space(K, J.span()).dual()
-    sage: K_star_W = _restrict_to_space(K.dual(), J.span())
+    sage: K_W_star = K._restrict_to_space(J.span()).dual()
+    sage: K_star_W = K.dual()._restrict_to_space(J.span())
     sage: _look_isomorphic(K_W_star, K_star_W)
     True
 
@@ -225,7 +224,7 @@ combinations of parameters::
     ....:                  solid=True)
     sage: A = random_matrix(QQ, K1.lattice_dim(), algorithm='unimodular')
     sage: K2 = Cone( [ A*r for r in K1.rays() ], lattice=K1.lattice())
-    sage: lyapunov_rank(K1) == lyapunov_rank(K2)
+    sage: K1.lyapunov_rank() == K2.lyapunov_rank()
     True
 
 ::
@@ -235,7 +234,7 @@ combinations of parameters::
     ....:                  solid=False)
     sage: A = random_matrix(QQ, K1.lattice_dim(), algorithm='unimodular')
     sage: K2 = Cone( [ A*r for r in K1.rays() ], lattice=K1.lattice())
-    sage: lyapunov_rank(K1) == lyapunov_rank(K2)
+    sage: K1.lyapunov_rank() == K2.lyapunov_rank()
     True
 
 ::
@@ -245,7 +244,7 @@ combinations of parameters::
     ....:                  solid=True)
     sage: A = random_matrix(QQ, K1.lattice_dim(), algorithm='unimodular')
     sage: K2 = Cone( [ A*r for r in K1.rays() ], lattice=K1.lattice())
-    sage: lyapunov_rank(K1) == lyapunov_rank(K2)
+    sage: K1.lyapunov_rank() == K2.lyapunov_rank()
     True
 
 ::
@@ -255,7 +254,7 @@ combinations of parameters::
     ....:                  solid=False)
     sage: A = random_matrix(QQ, K1.lattice_dim(), algorithm='unimodular')
     sage: K2 = Cone( [ A*r for r in K1.rays() ], lattice=K1.lattice())
-    sage: lyapunov_rank(K1) == lyapunov_rank(K2)
+    sage: K1.lyapunov_rank() == K2.lyapunov_rank()
     True
 
 The Lyapunov rank of a dual cone should be the same as the original
@@ -265,7 +264,7 @@ cone. Check all combinations of parameters::
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=False,
     ....:                 solid=False)
-    sage: lyapunov_rank(K) == lyapunov_rank(K.dual())
+    sage: K.lyapunov_rank() == K.dual().lyapunov_rank()
     True
 
 ::
@@ -274,7 +273,7 @@ cone. Check all combinations of parameters::
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=False,
     ....:                 solid=True)
-    sage: lyapunov_rank(K) == lyapunov_rank(K.dual())
+    sage: K.lyapunov_rank() == K.dual().lyapunov_rank()
     True
 
 ::
@@ -283,7 +282,7 @@ cone. Check all combinations of parameters::
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=True,
     ....:                 solid=False)
-    sage: lyapunov_rank(K) == lyapunov_rank(K.dual())
+    sage: K.lyapunov_rank() == K.dual().lyapunov_rank()
     True
 
 ::
@@ -292,7 +291,7 @@ cone. Check all combinations of parameters::
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=True,
     ....:                 solid=True)
-    sage: lyapunov_rank(K) == lyapunov_rank(K.dual())
+    sage: K.lyapunov_rank() == K.dual().lyapunov_rank()
     True
 
 The Lyapunov rank of a cone ``K`` is the dimension of
@@ -302,7 +301,7 @@ The Lyapunov rank of a cone ``K`` is the dimension of
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=True,
     ....:                 solid=True)
-    sage: lyapunov_rank(K) == len(K.lyapunov_like_basis())
+    sage: K.lyapunov_rank() == len(K.lyapunov_like_basis())
     True
 
 ::
@@ -311,7 +310,7 @@ The Lyapunov rank of a cone ``K`` is the dimension of
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=True,
     ....:                 solid=False)
-    sage: lyapunov_rank(K) == len(K.lyapunov_like_basis())
+    sage: K.lyapunov_rank() == len(K.lyapunov_like_basis())
     True
 
 ::
@@ -320,7 +319,7 @@ The Lyapunov rank of a cone ``K`` is the dimension of
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=False,
     ....:                 solid=True)
-    sage: lyapunov_rank(K) == len(K.lyapunov_like_basis())
+    sage: K.lyapunov_rank() == len(K.lyapunov_like_basis())
     True
 
 ::
@@ -329,7 +328,7 @@ The Lyapunov rank of a cone ``K`` is the dimension of
     sage: K = random_cone(max_ambient_dim=8,
     ....:                 strictly_convex=False,
     ....:                 solid=False)
-    sage: lyapunov_rank(K) == len(K.lyapunov_like_basis())
+    sage: K.lyapunov_rank() == len(K.lyapunov_like_basis())
     True
 
 """