X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=TODO;h=e8bf9e55b3f09348b157b6dd295fb18442542cbc;hb=f5b5ef66e41ae0538eb32e4b8420c36a23b95361;hp=d437ac441a1de491a7aa0175aa84409173e44dd3;hpb=0f9f55ce1a40b072bf39016e6f9972df98f6d3dd;p=dunshire.git

diff --git a/TODO b/TODO
index d437ac4..e8bf9e5 100644
--- a/TODO
+++ b/TODO
@@ -1,27 +1,9 @@
-1. Add doctests for simple examples like the ones in Dr. Gowda's paper
-   and the identity operator.
+1. Make it work on a cartesian product of cones in the correct order.
 
-2. Add unit testing for crazier things like random invertible matrices.
-
-3. Test that the primal/dual optimal values always agree (this implies
-   that we always get a solution).
-
-4. Run the tests with make test.
-
-5. Use pylint or whatever to perform static analysis.
-
-6. Add real docstrings everywhere.
-
-7. Try to eliminate the code in matrices.py.
-
-8. Make it work on a cartesian product of cones in the correct order.
-
-9. 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).
 
-10. Add (strict) cone containment tests to sanity check e1,e2.
-
-11. 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.
 
-12. 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.