def run_test():
"""
Run the test suite of Tic-Tac-Toe.
"""
suite = TestSuite()
board = provided.TTTBoard(3)
scores = [[0 for dummy_col in range(3)] for dummy_row in range(3)]
mc_trial = tic_tac_toe.mc_trial
mc_update_scores = tic_tac_toe.mc_update_scores
get_best_move = tic_tac_toe.get_best_move
mc_move = tic_tac_toe.mc_move
for dummy in range(3):
board_clone = board.clone()
mc_trial(board_clone, provided.PLAYERX)
suite.run_test(board_clone.check_win() != None, True, \
"Test #1: mc_trial")
print board_clone
mc_update_scores(scores, board_clone, provided.PLAYERX)
print scores
best_move = get_best_move(board, scores)
print best_move
move = mc_move(board, provided.PLAYERX, 3)
print move
board = provided.TTTBoard(3, False, \
[[provided.PLAYERX, provided.EMPTY, provided.EMPTY], \
[provided.PLAYERO, provided.PLAYERO, provided.EMPTY], \
[provided.EMPTY, provided.PLAYERX, provided.EMPTY]])
print board
print mc_move(board, provided.PLAYERX, tic_tac_toe.NTRIALS)
suite.report_results()
def run_test():
"""
https://class.coursera.org/principlescomputing1-004/forum/thread?thread_id=681
https://class.coursera.org/principlescomputing1-004/forum/thread?thread_id=697
https://class.coursera.org/principlescomputing1-004/forum/thread?thread_id=700
"""
suite = TestSuite()
state_1 = ClickerState()
suite.run_test(state_1.wait(45.0), None, 'Wrong wait #1')
suite.run_test(state_1.buy_item('item', 1.0, 3.5), None,
"Error with buy item")
suite.run_test(state_1.__str__(), ("Time: 45.0 Current Cookies: 44.0 CPS: 4.5 Total Cookies: 45.0 History (length: 2): [(0.0, None, 0.0, 0.0), (45.0, 'item', 1.0, 45.0)]"),\
"Different message from test1")
state_2 = ClickerState()
suite.run_test(state_2.wait(45.0), None, 'Wrong wait #2')
suite.run_test(state_2.__str__(), ("Time: 45.0 Current Cookies: 45.0 CPS: 1.0 Total Cookies: 45.0 History (length: 1): [(0.0, None, 0.0, 0.0)]"),\
"Different message from test2")
state_3 = simulate_clicker(
provided.BuildInfo({'Cursor': [15.0, 0.10000000000000001]}, 1.15),
5000.0, strategy_none)
suite.run_test(state_3.__str__(), ("Time: 5000.0 Current Cookies: 5000.0 CPS: 1.0 Total Cookies: 5000.0 History (length: 1): [(0.0, None, 0.0, 0.0)]"),\
"Different message from test3")
# For the cheap strategy, you need to choose the item that has the lowest cost (cheapest) each time.
# This may change throughout the simulation because an item's cost increases after you buy an item.
#
# OwlTest tells you that:
#
# A - cost 5.0, CPS increment: 1.0
# B - cost: 50000.0, CPS increment 3.0
# C - cost: 500.0, CPS increment 2.0
#
# - Since you start with 500000.0 cookies, you can definitely build all of them (A, B and C).
# - Of the items that can be built, append the item costs to a list. [5.0, 50000.0, 500.0]
# - Find the cheapest item cost. 5.0
# - Return the name of the item which costs this amount. A
state_4 = strategy_cheap(
500000.0, 1.0, [(0.0, None, 0.0, 0.0)], 5.0,
provided.BuildInfo(
{
'A': [5.0, 1.0],
'C': [50000.0, 3.0],
'B': [500.0, 2.0]
}, 1.15))
suite.run_test(state_4, ("A"), "expect A from test 4")
# For the expensive strategy, this is just the opposite. Choose the item that has the highest cost
# (most expensive) each time. However, you also need to factor in how much time is left when
# deciding which item you can buy.
state_5 = strategy_expensive(
500000.0, 1.0, [(0.0, None, 0.0, 0.0)], 5.0,
provided.BuildInfo(
{
'A': [5.0, 1.0],
'C': [50000.0, 3.0],
'B': [500.0, 2.0]
}, 1.15))
suite.run_test(state_5, ("C"), "expect C from test 5")
# To achieve this, ensure that the simulate_clicker function continues to loop until the strategy function is either:
# 1) beyond the time limit (not equal to - since it can still buy items with 0.0 seconds remaining); or
# 2) returns None (because it no longer wants to buy any items)
#
state_6 = simulate_clicker(
provided.BuildInfo({'Cursor': [15.0, 50.0]}, 1.15), 16.0,
strategy_cursor_broken)
suite.run_test(state_6.__str__(), (
"Time: 16.0 Current Cookies: 13.9125 CPS: 151.0 Total Cookies: 66.0 History (length: 4): [(0.0, None, 0.0, 0.0), (15.0, 'Cursor', 15.0, 15.0), (16.0, 'Cursor', 17.25, 66.0), (16.0, 'Cursor', 19.8375, 66.0)]"
), "Different message from test6")
state_7 = simulate_clicker(provided.BuildInfo({\
'Cursor': [15.0, 0.10000000000000001],\
'Portal': [1666666.0, 6666.0],\
'Shipment': [40000.0, 100.0],\
'Grandma': [100.0, 0.5],\
'Farm': [500.0, 4.0],\
'Time Machine': [123456789.0, 98765.0],\
'Alchemy Lab': [200000.0, 400.0],\
'Factory': [3000.0, 10.0],\
'Antimatter Condenser': [3999999999.0, 999999.0],\
'Mine': [10000.0, 40.0]}, 1.15), 10000000000.0,\
strategy_expensive)
suite.run_test(str(state_7.get_cookies()), '2414.64612076',
"Expect value 2414.64612076 from test 7.1")
suite.run_test(str(state_7.get_cps()), '133980795.7',
"Expect value 133980795.7 from test 7.2")
suite.run_test(str(state_7._total_cookies), '6.83676443443e+17',
"Expect value 6.83676443443e+17 from test 7.3")
#print str(state_7.get_history())
# Best score from strategy
# https://class.coursera.org/principlescomputing1-004/forum/thread?thread_id=#3
#
state_8 = simulate_clicker(provided.BuildInfo({\
'Cursor': [15.0, 0.10000000000000001],\
'Portal': [1666666.0, 6666.0],\
'Shipment': [40000.0, 100.0],\
'Grandma': [100.0, 0.5],\
'Farm': [500.0, 4.0],\
'Time Machine': [123456789.0, 98765.0],\
'Alchemy Lab': [200000.0, 400.0],\
'Factory': [3000.0, 10.0],\
'Antimatter Condenser': [3999999999.0, 999999.0],\
'Mine': [10000.0, 40.0]}, 1.15), 10000000000.0,\
strategy_best)
print 'Best score from strategy ' + str(state_8._total_cookies)
suite.report_results()
