Use "..." for floating point output in doctests.

[dunshire.git] / dunshire / games.py

diff --git a/dunshire/games.py b/dunshire/games.py
index e25db28a8e7349e88b9bdd18f16d0eea0b5c03c1..1f672abeb3870f45b13a8d9d169e8df0f1059d98 100644 (file)
--- 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):
@@ -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
@@ -586,7 +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