X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=src%2Fdunshire%2Fgames.py;h=43fa007c61077c90ef627e9738afbaa09dcde9c1;hb=fa8fa4d690c5f30f7d5fee1818a9b4c15f52c5ff;hp=92a3ffe7b6f684ea134ff88bdf08d745ae7a4944;hpb=f8fecdbad5e7c25c5e87b1b4b652b9fa694f0ace;p=dunshire.git

diff --git a/src/dunshire/games.py b/src/dunshire/games.py
index 92a3ffe..43fa007 100644
--- a/src/dunshire/games.py
+++ b/src/dunshire/games.py
@@ -427,6 +427,12 @@ class SymmetricLinearGame:
         # what happened.
         soln_dict = solvers.conelp(c, G, h, C.cvxopt_dims(), A, b)
 
+        # The optimal strategies are named ``p`` and ``q`` in the
+        # background documentation, and we need to extract them from
+        # the CVXOPT ``x`` and ``z`` variables. The objective values
+        # :math:`nu` and :math:`omega` can also be found in the CVXOPT
+        # ``x`` and ``y`` variables; however, they're stored
+        # conveniently as separate entries in the solution dictionary.
         p1_value = -soln_dict['primal objective']
         p2_value = -soln_dict['dual objective']
         p1_optimal = soln_dict['x'][1:]