X-Git-Url: https://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=src%2Fdunshire%2Fgames.py;h=10a5eee5b8f34832103f1a564f50150a93b22846;hb=0a16e3c97d7f0e692428126ae1759fe0f925bf8f;hp=3d4b09ad8c0c12ff1bba0294a1c5c87ae8ff72bf;hpb=bd5a4b0c8519de2a938663acdbc080560f829628;p=dunshire.git

diff --git a/src/dunshire/games.py b/src/dunshire/games.py
index 3d4b09a..10a5eee 100644
--- a/src/dunshire/games.py
+++ b/src/dunshire/games.py
@@ -545,10 +545,10 @@ def _random_skew_symmetric_matrix(dims):
 
     """
     strict_ut = [[uniform(-10, 10)*int(i < j) for i in range(dims)]
-                  for j in range(dims)]
+                 for j in range(dims)]
 
-    strict_ut = matrix(strict_ut, (dims,dims))
-    return (strict_ut - strict_ut.trans())
+    strict_ut = matrix(strict_ut, (dims, dims))
+    return strict_ut - strict_ut.trans()
 
 
 def _random_lyapunov_like_icecream(dims):
@@ -556,12 +556,12 @@ def _random_lyapunov_like_icecream(dims):
     Generate a random Lyapunov-like matrix over the ice-cream cone in
     ``dims`` dimensions.
     """
-    a = matrix([uniform(-10,10)], (1,1))
-    b = matrix([uniform(-10,10) for idx in range(dims-1)], (dims-1, 1))
+    a = matrix([uniform(-10, 10)], (1, 1))
+    b = matrix([uniform(-10, 10) for idx in range(dims-1)], (dims-1, 1))
     D = _random_skew_symmetric_matrix(dims-1) + a*identity(dims-1)
     row1 = append_col(a, b.trans())
     row2 = append_col(b, D)
-    return append_row(row1,row2)
+    return append_row(row1, row2)
 
 
 def _random_orthant_params():
@@ -868,14 +868,15 @@ class SymmetricLinearGameTest(TestCase):
         # We only check for positive/negative stability if the game
         # value is not basically zero. If the value is that close to
         # zero, we just won't check any assertions.
+        eigs = eigenvalues_re(L)
         if soln.game_value() > options.ABS_TOL:
             # L should be positive stable
-            ps = all([eig > -options.ABS_TOL for eig in  eigenvalues_re(L)])
-            self.assertTrue(ps)
+            positive_stable = all([eig > -options.ABS_TOL for eig in eigs])
+            self.assertTrue(positive_stable)
         elif soln.game_value() < -options.ABS_TOL:
             # L should be negative stable
-            ns = all([eig < options.ABS_TOL for eig in  eigenvalues_re(L)])
-            self.assertTrue(ns)
+            negative_stable = all([eig < options.ABS_TOL for eig in eigs])
+            self.assertTrue(negative_stable)
 
         # The dual game's value should always equal the primal's.
         dualsoln = game.dual().solution()