X-Git-Url: https://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=TODO;h=ab87751f3168ceecdf739128a222dd766828c377;hb=920c93e69916d70c293c8ab0caccb0b4d8ffb073;hp=d437ac441a1de491a7aa0175aa84409173e44dd3;hpb=0f9f55ce1a40b072bf39016e6f9972df98f6d3dd;p=dunshire.git diff --git a/TODO b/TODO index d437ac4..ab87751 100644 --- a/TODO +++ b/TODO @@ -1,27 +1,23 @@ -1. Add doctests for simple examples like the ones in Dr. Gowda's paper - and the identity operator. +1. Add unit testing for crazier things like random invertible matrices. -2. Add unit testing for crazier things like random invertible matrices. +2. Add real docstrings everywhere. -3. Test that the primal/dual optimal values always agree (this implies - that we always get a solution). +3. Try to eliminate the code in matrices.py. -4. Run the tests with make test. +4. Make it work on a cartesian product of cones in the correct order. -5. Use pylint or whatever to perform static analysis. - -6. Add real docstrings everywhere. - -7. Try to eliminate the code in matrices.py. +5. Make it work on a cartesian product of cones in the wrong order + (apply a perm utation before/after). -8. Make it work on a cartesian product of cones in the correct order. +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. -9. Make it work on a cartesian product of cones in the wrong order - (apply a perm utation before/after). +7. Make sure we have the dimensions of the PSD cone correct. -10. Add (strict) cone containment tests to sanity check e1,e2. +8. Use a positive tolerance when comparing floating point numbers. -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. +9. Come up with a fast heuristic (like making nu huge and taking e1 as + our point) that finds a primal feasible point. -12. Make sure we have the dimensions of the PSD cone correct. +10. Ensure that we only compute eigenvalues of *symmetric* matrices + (so that the eigenvalues are real).