X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=dunshire%2Fgames.py;h=1f672abeb3870f45b13a8d9d169e8df0f1059d98;hb=299bf2d606eb245ec78f2e20826836c0bb5bfc07;hp=c841caae752b9075ee28030d2a15df5d42354308;hpb=3ee9db27adb69d68871ef26ec22ef144f351e99d;p=dunshire.git diff --git a/dunshire/games.py b/dunshire/games.py index c841caa..1f672ab 100644 --- a/dunshire/games.py +++ b/dunshire/games.py @@ -222,7 +222,7 @@ class SymmetricLinearGame: e2 = [ 1] [ 2] [ 3], - Condition((L, K, e1, e2)) = 31.834895. + Condition((L, K, e1, e2)) = 31.834... Lists can (and probably should) be used for every argument:: @@ -241,7 +241,7 @@ class SymmetricLinearGame: [ 1], e2 = [ 1] [ 1], - Condition((L, K, e1, e2)) = 1.707107. + Condition((L, K, e1, e2)) = 1.707... The points ``e1`` and ``e2`` can also be passed as some other enumerable type (of the correct length) without much harm, since @@ -264,7 +264,7 @@ class SymmetricLinearGame: [ 1], e2 = [ 1] [ 1], - Condition((L, K, e1, e2)) = 1.707107. + Condition((L, K, e1, e2)) = 1.707... However, ``L`` will always be intepreted as a list of rows, even if it is passed as a :class:`cvxopt.base.matrix` which is @@ -286,7 +286,7 @@ class SymmetricLinearGame: [ 1], e2 = [ 1] [ 1], - Condition((L, K, e1, e2)) = 6.073771. + Condition((L, K, e1, e2)) = 6.073... >>> L = cvxopt.matrix(L) >>> print(L) [ 1 3] @@ -302,7 +302,7 @@ class SymmetricLinearGame: [ 1], e2 = [ 1] [ 1], - Condition((L, K, e1, e2)) = 6.073771. + Condition((L, K, e1, e2)) = 6.073... """ def __init__(self, L, K, e1, e2): @@ -346,7 +346,7 @@ class SymmetricLinearGame: str(self._K), indented_e1, indented_e2, - self._condition()) + self.condition()) def _zero(self): @@ -419,13 +419,13 @@ class SymmetricLinearGame: >>> print(SLG.solution()) Game value: -6.1724138 Player 1 optimal: - [ 0.5517241] - [-0.0000000] - [ 0.4482759] + [ 0.551...] + [-0.000...] + [ 0.448...] Player 2 optimal: - [0.4482759] - [0.0000000] - [0.5517241] + [0.448...] + [0.000...] + [0.551...] The value of the following game can be computed using the fact that the identity is invertible:: @@ -439,13 +439,13 @@ class SymmetricLinearGame: >>> print(SLG.solution()) Game value: 0.0312500 Player 1 optimal: - [0.0312500] - [0.0625000] - [0.0937500] + [0.031...] + [0.062...] + [0.093...] Player 2 optimal: - [0.1250000] - [0.1562500] - [0.1875000] + [0.125...] + [0.156...] + [0.187...] """ # The cone "C" that appears in the statement of the CVXOPT @@ -505,7 +505,13 @@ class SymmetricLinearGame: # objectives match (within a tolerance) and that the # primal/dual optimal solutions are within the cone (to a # tolerance as well). - if abs(p1_value - p2_value) > options.ABS_TOL: + # + # The fudge factor of two is basically unjustified, but + # makes intuitive sense when you imagine that the primal + # value could be under the true optimal by ``ABS_TOL`` + # and the dual value could be over by the same amount. + # + if abs(p1_value - p2_value) > 2*options.ABS_TOL: raise GameUnsolvableException(self, soln_dict) if (p1_optimal not in self._K) or (p2_optimal not in self._K): raise GameUnsolvableException(self, soln_dict) @@ -513,7 +519,7 @@ class SymmetricLinearGame: return Solution(p1_value, p1_optimal, p2_optimal) - def _condition(self): + def condition(self): r""" Return the condition number of this game. @@ -541,7 +547,7 @@ class SymmetricLinearGame: >>> e1 = [1] >>> e2 = e1 >>> SLG = SymmetricLinearGame(L, K, e1, e2) - >>> actual = SLG._condition() + >>> actual = SLG.condition() >>> expected = 1.8090169943749477 >>> abs(actual - expected) < options.ABS_TOL True @@ -580,7 +586,7 @@ class SymmetricLinearGame: e2 = [ 1] [ 1] [ 1], - Condition((L, K, e1, e2)) = 44.476765. + Condition((L, K, e1, e2)) = 44.476... """ # We pass ``self._L`` right back into the constructor, because