X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=TODO;h=4cbf01d47b2c813c7334cccdfb2afd3184f79309;hb=0115adecce0ea5d82facf4bd8d7276a9c51db7b3;hp=25beb4a3d326b8e9ef058c6df97b0c3a41083e50;hpb=cf2618ae859eedc12ec50c6e9d09dd564ac7203b;p=dunshire.git

diff --git a/TODO b/TODO
index 25beb4a..4cbf01d 100644
--- a/TODO
+++ b/TODO
@@ -1,20 +1,66 @@
-1. Add unit testing for crazier things like random invertible matrices.
+1. Make it work on a cartesian product of cones in the correct order.
 
-2. Add real docstrings everywhere.
-
-3. Try to eliminate the code in matrices.py.
-
-4. Make it work on a cartesian product of cones in the correct order.
-
-5. Make it work on a cartesian product of cones in the wrong order
+2. Make it work on a cartesian product of cones in the wrong order
    (apply a perm utation before/after).
 
-6. Rename all of my variables so that they don't conflict with CVXOPT.
-   Maybe x -> xi and y -> gamma in my paper, if that works out.
+3. Make sure we have the dimensions of the PSD cone correct.
 
-7. Make sure we have the dimensions of the PSD cone correct.
+4. Come up with a fast heuristic (like making nu huge and taking e1 as
+   our point) that finds a primal feasible point.
 
-8. Use a positive tolerance when comparing floating point numbers.
+12. Investigate this test failure too. It looks like it was really
+    close to being solved, but we would have needed a fudge factor
+    of three instead of two.
 
-9. Come up with a fast heuristic (like making nu huge and taking e1 as
-   our point) that finds a primal feasible point.
+    ERROR: test_positive_operator_value (test.symmetric_linear_game_test
+                                         .SymmetricLinearGameTest)
+    ----------------------------------------------------------------------
+    Traceback (most recent call last):
+      File "/home/mjo/src/dunshire/test/symmetric_linear_game_test.py",
+      line 550, in test_positive_operator_value
+	self.assertTrue(G.solution().game_value() >= -options.ABS_TOL)
+      File "/home/mjo/src/dunshire/dunshire/games.py", line 515, in solution
+	raise GameUnsolvableException(self, soln_dict)
+    dunshire.errors.GameUnsolvableException: Solution failed with result
+    "unknown."
+    The linear game (L, K, e1, e2) where
+      L = [8.0814704 3.5584693]
+	  [3.9986814 9.3381562],
+      K = Nonnegative orthant in the real 2-space,
+      e1 = [1.3288182]
+	   [0.7458942],
+      e2 = [0.6814326]
+	   [3.3799082],
+      Condition((L, K, e1, e2)) = 41.093597.
+    CVXOPT returned:
+      dual infeasibility: 2.368640021750079e-06
+      dual objective: -7.867137172157051
+      dual slack: 1.1314089173606103e-07
+      gap: 1.1404410161224882e-06
+      iterations: 6
+      primal infeasibility: 1.379959981010593e-07
+      primal objective: -7.867137449574777
+      primal slack: 1.0550559882036034e-08
+      relative gap: 1.4496264027827932e-07
+      residual as dual infeasibility certificate: 0.12711103707156543
+      residual as primal infeasibility certificate: None
+      s:
+	[1.4674968]
+	[0.0000000]
+	[1.4055364]
+	[0.0000000]
+      status: unknown
+      x:
+	[ 7.8671374]
+	[ 1.4674968]
+	[-0.0000000]
+      y:
+	[7.8671372]
+      z:
+	[ 0.0000001]
+	[14.0707905]
+	[ 0.0000002]
+	[ 1.3406728]
+
+13. Add a test to ensure that if we solve the same game twice, we get the
+    same answer back.