def test_faulty_bots_scenario():
rn.seed(1234)
buyer1 = MyopicBuyer("Sarah")
seller1 = DummySeller("Sarah")
buyer2 = FaultyBuyer()
seller2 = DummySeller("Basil")
teams = [(buyer1, seller1), (buyer2, seller2)]
# This code should terminate.. that's all we're testing
simulate(teams, horizon, x_0, 1, price_scale)
def test_simulation_game_with_two_teams_same_strategies():
rn.seed(123)
buyer1 = MyopicBuyer("Sarah")
seller1 = DummySeller("Sarah")
buyer2 = MyopicBuyer("Steve")
seller2 = DummySeller("Steve")
teams = [(buyer1, seller1), (buyer2, seller2)]
mean_revenue, mean_cs = simulate(teams, horizon, x_0, mc_trials, price_scale)
assert mean_revenue[0] == mean_revenue[1] and mean_revenue[0] > 0.
assert mean_cs[0] == mean_cs[1] and mean_cs[0] > 0.
def test_simulation_game_with_two_teams_different_strategies():
rn.seed(1234)
buyer1 = MyopicBuyer("Sarah")
seller1 = DummySeller("Sarah")
buyer2 = MyopicBuyer("Steve")
seller2 = DummySeller("Steve", constant_price=0.1)
teams = [(buyer1, seller1), (buyer2, seller2)]
mean_revenue, mean_cs = simulate(teams, horizon, x_0, mc_trials, price_scale)
# with a very low selling price for team 2, the seller is undervaluing the product and hence makes less revenue
assert mean_revenue[0] > mean_revenue[1] and np.all(mean_revenue > 0.)
# with a very low selling price for team 2, the buyer is making a good deal a lot of the time and has higher
# consumer surplus, on average
assert mean_cs[0] > mean_cs[1] and np.all(mean_cs > 0.)
def test_my_teams_performance():
"""
This function is where you can write a test for your buyer and seller bot, and evaluate performance
"""
rn.seed(123)
buyer1 = TeamNameBuyer()
seller1 = TeamNameSeller()
buyer2 = MyopicBuyer("Steve")
seller2 = DummySeller("Steve")
teams = [(buyer1, seller1), (buyer2, seller2)]
mean_revenue, mean_cs = simulate(teams, horizon, x_0, mc_trials,
price_scale)
print mean_revenue, mean_cs
def test_simulation_game_with_three_teams():
rn.seed(1234)
buyer1 = MyopicBuyer("Sarah")
seller1 = DummySeller("Sarah")
buyer2 = MyopicBuyer("Steve")
seller2 = DummySeller("Steve", constant_price=0.1)
buyer3 = MyopicBuyer("Emanuel")
seller3 = DummySeller("Emanuel", constant_price=1.)
teams = [(buyer1, seller1), (buyer2, seller2), (buyer3, seller3)]
mean_revenue, mean_cs = simulate(teams, horizon, x_0, mc_trials, price_scale)
# with a very low selling price for team 2, the seller is undervaluing the product and hence makes less revenue
# teams 1 and 3 have the same selling strategy, so should get the same sample mean revenue
assert mean_revenue[2] == mean_revenue[0] and mean_revenue[0] > mean_revenue[1]
assert np.all(mean_revenue > 0.)
# with a very low selling price for team 2, the buyer is making a good deal a lot of the time and has higher
# consumer surplus, on average
assert mean_cs[0] > mean_cs[1]
assert np.all(mean_cs > 0.)