initial tests for lcp mixed strategies

Author: rahulsavani

tests/test_nash.py

@@ -17,6 +17,16 @@
 TOL = 1e-13  # tolerance for floating point assertions
 
 
+def kuhn_poker_lcp_mixed_strategy_prof():
+    alice = [0] * 27
+    alice[1] = "2/3"
+    alice[4] = "1/3"
+    bob = [0] * 64
+    bob[12] = "2/3"
+    bob[30] = "1/3"
+    return [alice, bob]
+
+
 def test_enumpure_strategy():
     """Test calls of enumeration of pure strategies."""
     game = games.read_from_file("poker.efg")
@@ -143,19 +153,28 @@ def test_lcp_strategy_double():
 
 @pytest.mark.nash
 @pytest.mark.nash_lcp_strategy
-def test_lcp_strategy_rational():
+@pytest.mark.parametrize(
+    "game,mixed_strategy_prof_data,stop_after",
+    [
+        # Zero-sum games
+        # (games.create_1_card_poker_efg(), [["1/3", "2/3", 0, 0], ["2/3", "1/3"]]),
+        # (games.create_myerson_2_card_poker_efg(), [["1/3", "2/3", 0, 0], ["2/3", "1/3"]]),
+        # (games.create_kuhn_poker_efg(), kuhn_poker_lcp_mixed_strategy_prof())
+        (games.create_EFG_for_nxn_bimatrix_coordination_game(3), [[[1, 0, 0], [1, 0, 0]]], 1),
+        # Non-zero-sum games
+    ]
+)
+def test_lcp_strategy_rational(game: gbt.Game, mixed_strategy_prof_data: list,
+                               stop_after: typing.Union[None, int]):
     """Test calls of LCP for mixed strategy equilibria, rational precision."""
-    game = games.read_from_file("poker.efg")
-    result = gbt.nash.lcp_solve(game, use_strategic=True, rational=True)
+    result = gbt.nash.lcp_solve(game, use_strategic=True, rational=True, stop_after=stop_after)
+    print(result.equilibria)
     assert len(result.equilibria) == 1
-    expected = game.mixed_strategy_profile(
-        rational=True,
-        data=[
-            [gbt.Rational(1, 3), gbt.Rational(2, 3), gbt.Rational(0), gbt.Rational(0)],
-            [gbt.Rational(2, 3), gbt.Rational(1, 3)],
-        ],
-    )
-    assert result.equilibria[0] == expected
+    eq = result.equilibria[0]
+    assert eq.max_regret() == 0
+    print(eq)
+    expected = game.mixed_strategy_profile(rational=True, data=mixed_strategy_prof_data[0])
+    assert eq == expected
 
 
 def test_lcp_behavior_double():