From: Michael Orlitzky Date: Wed, 5 Oct 2016 17:38:01 +0000 (-0400) Subject: Start to clean up pylint warnings in symmetric_linear_game.py. X-Git-Tag: 0.1.0~213 X-Git-Url: https://gitweb.michael.orlitzky.com/?a=commitdiff_plain;h=dcfe79aa1411f58cda36fff3114986dd77a0c0c3;p=dunshire.git Start to clean up pylint warnings in symmetric_linear_game.py. --- diff --git a/symmetric_linear_game.py b/symmetric_linear_game.py index a8cdabc..29f64ad 100644 --- a/symmetric_linear_game.py +++ b/symmetric_linear_game.py @@ -41,18 +41,25 @@ class SymmetricLinearGame: as a column vector. """ - self._K = K + self._K = K self._C = CartesianProduct(K, K) - n = self._K.dimension() - self._L = matrix(L, (n,n)) - self._e1 = matrix(e1, (n,1)) # TODO: check that e1 and e2 - self._e2 = matrix(e2, (n,1)) # are in the interior of K... - self._h = matrix(0, (2*n,1), 'd') - self._b = matrix(1, (1,1), 'd') - self._c = matrix([-1] + [0]*n, (n+1,1), 'd') - self._G = append_row(append_col(matrix(0,(n,1)), -identity(n)), + self._e1 = matrix(e1, (K.dimension(), 1)) + self._e2 = matrix(e2, (K.dimension(), 1)) + + if not K.contains_strict(self._e1): + raise ValueError('the point e1 must lie in the interior of K') + if not K.contains_strict(self._e2): + raise ValueError('the point e2 must lie in the interior of K') + + self._L = matrix(L, (K.dimension(), K.dimension())) + self._b = matrix([1], tc='d') + # A column of zeros that fits K. + zero = matrix(0, (K.dimension(), 1), tc='d') + self._h = matrix([zero, zero]) + self._c = matrix([-1, zero]) + self._G = append_row(append_col(zero, -identity(K.dimension())), append_col(self._e1, -self._L)) - self._A = matrix([0] + e1, (1, n+1), 'd') + self._A = matrix([0, self._e1], (1, K.dimension() + 1), 'd') def solution(self): soln = solvers.conelp(self._c, @@ -65,16 +72,11 @@ class SymmetricLinearGame: def solve(self): soln = self.solution() - nu = soln['x'][0] - print('Value of the game (player one): {:f}'.format(nu)) - opt1 = soln['x'][1:] + print('Value of the game (player one): {:f}'.format(soln['x'][0])) print('Optimal strategy (player one):') - print(opt1) + print(soln['x'][1:]) - omega = soln['y'][0] - n = self._K.dimension() - opt2 = soln['z'][n:] - print('Value of the game (player two): {:f}'.format(omega)) + print('Value of the game (player two): {:f}'.format(soln['y'][0])) print('Optimal strategy (player two):') - print(opt2) + print(soln['z'][self._K.dimension():])