X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=src%2Fdunshire%2Fgames.py;h=05ab58cd702c5570221184ed47f5bb16289627c0;hb=769e1c7d09936a617f33d1496782fbbd4299851d;hp=10a5eee5b8f34832103f1a564f50150a93b22846;hpb=0a16e3c97d7f0e692428126ae1759fe0f925bf8f;p=dunshire.git diff --git a/src/dunshire/games.py b/src/dunshire/games.py index 10a5eee..05ab58c 100644 --- a/src/dunshire/games.py +++ b/src/dunshire/games.py @@ -12,11 +12,11 @@ from unittest import TestCase # These are mostly actually needed. from cvxopt import matrix, printing, solvers -from cones import CartesianProduct, IceCream, NonnegativeOrthant -from errors import GameUnsolvableException -from matrices import (append_col, append_row, eigenvalues_re, identity, - inner_product, norm) -import options +from .cones import CartesianProduct, IceCream, NonnegativeOrthant +from .errors import GameUnsolvableException +from .matrices import (append_col, append_row, eigenvalues_re, identity, + inner_product, norm) +from . import options printing.options['dformat'] = options.FLOAT_FORMAT solvers.options['show_progress'] = options.VERBOSE @@ -211,7 +211,6 @@ class SymmetricLinearGame: Examples -------- - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(3) >>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]] >>> e1 = [1,1,1] @@ -232,7 +231,6 @@ class SymmetricLinearGame: Lists can (and probably should) be used for every argument:: - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(2) >>> L = [[1,0],[0,1]] >>> e1 = [1,1] @@ -254,7 +252,6 @@ class SymmetricLinearGame: >>> import cvxopt >>> import numpy - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(2) >>> L = [[1,0],[0,1]] >>> e1 = cvxopt.matrix([1,1]) @@ -275,7 +272,6 @@ class SymmetricLinearGame: otherwise indexed by columns:: >>> import cvxopt - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(2) >>> L = [[1,2],[3,4]] >>> e1 = [1,1] @@ -364,7 +360,6 @@ class SymmetricLinearGame: This example is computed in Gowda and Ravindran in the section "The value of a Z-transformation":: - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(3) >>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]] >>> e1 = [1,1,1] @@ -384,7 +379,6 @@ class SymmetricLinearGame: The value of the following game can be computed using the fact that the identity is invertible:: - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(3) >>> L = [[1,0,0],[0,1,0],[0,0,1]] >>> e1 = [1,2,3] @@ -475,7 +469,6 @@ class SymmetricLinearGame: Examples -------- - >>> from cones import NonnegativeOrthant >>> K = NonnegativeOrthant(3) >>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]] >>> e1 = [1,1,1] @@ -606,7 +599,8 @@ def _random_icecream_params(): return (L, K, matrix(e1), matrix(e2)) -class SymmetricLinearGameTest(TestCase): +# Tell pylint to shut up about the large number of methods. +class SymmetricLinearGameTest(TestCase): # pylint: disable=R0904 """ Tests for the SymmetricLinearGame and Solution classes. """ @@ -849,9 +843,7 @@ class SymmetricLinearGameTest(TestCase): This test theoretically applies to the ice-cream cone as well, but we don't know how to make positive operators on that cone. """ - (_, K, e1, e2) = _random_orthant_params() - - # Ignore that L, we need a nonnegative one. + (K, e1, e2) = _random_orthant_params()[1:] L = _random_nonnegative_matrix(K.dimension()) game = SymmetricLinearGame(L, K, e1, e2) @@ -887,10 +879,7 @@ class SymmetricLinearGameTest(TestCase): """ Test that a Lyapunov game on the nonnegative orthant works. """ - (L, K, e1, e2) = _random_orthant_params() - - # Ignore that L, we need a diagonal (Lyapunov-like) one. - # (And we don't need to transpose those.) + (K, e1, e2) = _random_orthant_params()[1:] L = _random_diagonal_matrix(K.dimension()) self.assert_lyapunov_works(L, K, e1, e2) @@ -900,10 +889,7 @@ class SymmetricLinearGameTest(TestCase): """ Test that a Lyapunov game on the ice-cream cone works. """ - (L, K, e1, e2) = _random_icecream_params() - - # Ignore that L, we need a diagonal (Lyapunov-like) one. - # (And we don't need to transpose those.) + (K, e1, e2) = _random_icecream_params()[1:] L = _random_lyapunov_like_icecream(K.dimension()) self.assert_lyapunov_works(L, K, e1, e2)