@@ -208,14 +208,9 @@ def test_enumpoly_ordered_behavior(
208208 result = gbt .nash .enumpoly_solve (game , use_strategic = False )
209209 assert len (result .equilibria ) == len (mixed_behav_prof_data )
210210 for eq , exp in zip (result .equilibria , mixed_behav_prof_data , strict = True ):
211- print ("FOUND EQ:" , eq )
212- print (eq .max_regret ())
213- print (eq .agent_max_regret ())
214211 assert abs (eq .max_regret ()) <= TOL
215212 assert abs (eq .agent_max_regret ()) <= TOL
216213 expected = game .mixed_behavior_profile (rational = True , data = exp )
217- # print(expected)
218- # print(eq)
219214 for p in game .players :
220215 for i in p .infosets :
221216 for a in i .actions :
@@ -273,14 +268,9 @@ def test_enumpoly_ordered_behavior_PROBLEM_CASE(
273268 result = gbt .nash .enumpoly_solve (game , use_strategic = False )
274269 assert len (result .equilibria ) == len (mixed_behav_prof_data )
275270 for eq , exp in zip (result .equilibria , mixed_behav_prof_data , strict = True ):
276- print ("FOUND EQ:" , eq )
277- print ("found max regret:" , eq .max_regret ())
278- print ("found agent max regret:" , eq .agent_max_regret ())
279271 assert abs (eq .max_regret ()) <= TOL
280272 assert abs (eq .agent_max_regret ()) <= TOL
281273 expected = game .mixed_behavior_profile (rational = True , data = exp )
282- print ("exp max regret:" , eq .max_regret ())
283- print ("exp agent max regret:" , eq .agent_max_regret ())
284274 for p in game .players :
285275 for i in p .infosets :
286276 for a in i .actions :
@@ -876,88 +866,3 @@ def test_logit_solve_lambda():
876866 game = games .read_from_file ("const_sum_game.nfg" )
877867 assert len (gbt .qre .logit_solve_lambda (
878868 game = game , lam = [1 , 2 , 3 ], first_step = 0.2 , max_accel = 1 )) > 0
879-
880-
881- def test_regrets_tmp ():
882-
883- prof_data_doub = []
884- prof_data_doub .append ([[[1 , 0 ], [1 , 0 ]], [[1 , 0 ], [0.5 , 0.5 ]], [[1 , 0 ], [0 , 1 ]]])
885- # prof_data_doub.append([[[1, 0], [1, 0]], [[1, 0], [0, 1]], [[1, 0], [0.33333, 0.6666]]])
886- # prof_data_doub.append([[[1, 0], [1, 0]], [[1, 0], [0.5, 0.5]], [[0, 1], [1, 0]]])
887- # prof_data_doub.append([[[1, 0], [1, 0]], [[1, 0], [0, 1]], [[0.33333, 0.6666], [1, 0]]])
888-
889- prof_data_rat = []
890- prof_data_rat .append ([[[1 , 0 ], [1 , 0 ]], [[1 , 0 ], ["1/2" , "1/2" ]], [[1 , 0 ], [0 , 1 ]]])
891- # prof_data_rat.append([[[1, 0], [1, 0]], [[1, 0], [0, 1]], [[1, 0], ["1/3", "2/3"]]])
892- # prof_data_rat.append([[[1, 0], [1, 0]], [[1, 0], ["1/2", "1/2"]], [[0, 1], [1, 0]]])
893- # prof_data_rat.append([[[1, 0], [1, 0]], [[1, 0], [0, 1]], [["1/3", "2/3"], [1, 0]]])
894-
895- g = games .create_3_player_with_internal_outcomes_efg ()
896-
897- print ()
898- print ("==================" )
899- for p in prof_data_doub :
900- prof = g .mixed_behavior_profile (rational = False , data = p )
901- print (prof .max_regret ())
902- print (prof .agent_max_regret ())
903- print ("==================" )
904- for p in prof_data_rat :
905- prof = g .mixed_behavior_profile (rational = True , data = p )
906- print (prof .max_regret ())
907- print (prof .agent_max_regret ())
908- print ("==================" )
909- for p in prof_data_doub :
910- prof = g .mixed_behavior_profile (rational = False , data = p )
911- print (prof .max_regret ())
912- print (prof .agent_max_regret ())
913-
914-
915- def test_regrets_tmp2 ():
916- g = games .create_3_player_with_internal_outcomes_efg ()
917- prof_data_rat = [[[1 , 0 ], [1 , 0 ]], [[1 , 0 ], ["1/2" , "1/2" ]], [[1 , 0 ], [0 , 1 ]]]
918- profile_rat = g .mixed_behavior_profile (rational = True , data = prof_data_rat )
919- print ()
920- print (profile_rat .max_regret ()) # 3/2
921- profile_rat = g .mixed_behavior_profile (rational = True , data = prof_data_rat )
922- print (profile_rat .max_regret ()) # now different! 0
923-
924-
925- @pytest .mark .parametrize (
926- "game,mixed_behav_prof_data" ,
927- [
928- (
929- games .create_seq_form_STOC_paper_zero_sum_2_player_efg (),
930- [
931- [[0 , 1 ], ["1/3" , "2/3" ], ["2/3" , "1/3" ]],
932- [["5/6" , "1/6" ], ["5/9" , "4/9" ]],
933- ],
934- ),
935- (
936- games .create_3_player_with_internal_outcomes_efg (),
937- [
938- [[1 , 0 ], [1 , 0 ]], [[1 , 0 ], ["1/2" , "1/2" ]],
939- [[1 , 0 ], [0 , 1 ]]
940- ],
941- ),
942- (
943- games .create_STOC_simplified (),
944- [
945- [[0 , 1 ], ["1/3" , "2/3" ], ["2/3" , "1/3" ]],
946- [["5/6" , "1/6" ]],
947- ],
948- ),
949- # (
950- # games.create_STOC_simplified2(),
951- # [
952- # [[1], [1], ["1/3", "2/3"]],
953- # [["5/6", "1/6"]],
954- # ],
955- # ),
956- ],
957- )
958- def test_repeat_max_regret (game : gbt .Game , mixed_behav_prof_data : list ):
959- profile1 = game .mixed_behavior_profile (rational = True , data = mixed_behav_prof_data )
960- mr1 = profile1 .max_regret ()
961- profile2 = game .mixed_behavior_profile (rational = True , data = mixed_behav_prof_data )
962- mr2 = profile2 .max_regret ()
963- assert mr1 == mr2
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