def test_two(self):
a = np.array([ #mixed strategies
[10, 30],
[40, 20]])
val = 25.0
vect1 = [0.5, 0.5]
vect2 = [0.25, 0.75]
game_p, v1, v2 = nash_equilibrium(a)
self.assertTrue(check_matrix(game_p,v1,v2,val,vect1,vect2))
def fourth_test():
a = np.array([ #with saddle point
[2, 7, 2], [2, 3, 2], [2, 1, 8]
])
val = 2
vect1 = [1]
vect2 = [0]
game_p, v1, v2 = nash_equilibrium(a)
return check_matrix(game_p, v1, v2, val, vect1, vect2)
def third_test():
a = np.array([ #with saddle point
[3, 9, 2, 1], [7, 8, 5, 6], [4, 7, 3, 5], [5, 6, 1, 7]
])
val = 5
vect1 = [1]
vect2 = [2]
game_p, v1, v2 = nash_equilibrium(a)
return check_matrix(game_p, v1, v2, val, vect1, vect2)
def second_test():
a = np.array([ #mixed strategies
[10, 30], [40, 20]
])
val = 25.0
vect1 = [0.5, 0.5]
vect2 = [0.25, 0.75]
game_p, v1, v2 = nash_equilibrium(a)
return check_matrix(game_p, v1, v2, val, vect1, vect2)
def test_four(self):
a = np.array([ #with saddle point
[2,7,2],
[2,3,2],
[2,1,8]])
val = 2
vect1 = [1]
vect2 = [0]
game_p, v1, v2 = nash_equilibrium(a)
self.assertTrue(check_matrix(game_p, v1, v2, val, vect1, vect2))
def first_test():
a = np.array([ #mixed strategies
[4, 0, 6, 2, 2, 1], [3, 8, 4, 10, 4, 4], [1, 2, 6, 5, 0, 0],
[6, 6, 4, 4, 10, 3], [10, 4, 6, 4, 0, 9], [10, 7, 0, 7, 9, 8]
])
vect1 = [0.0, 0.12, 0.09, 0.43, 0.33, 0.0]
vect2 = [0.0, 0.0, 0.69, 0.14, 0.14, 0.01]
val = 4.87
game_p, v1, v2 = nash_equilibrium(a)
return check_matrix(game_p, v1, v2, val, vect1, vect2)
def test_three(self):
a = np.array([ #with saddle point
[3,9,2,1],
[7,8,5,6],
[4,7,3,5],
[5,6,1,7]])
val = 5
vect1 = [1]
vect2 = [2]
game_p, v1, v2 = nash_equilibrium(a)
self.assertTrue(check_matrix(game_p,v1,v2,val,vect1,vect2))