def simulateGame(game_state, row, card, bAppend, op_deck=None):
''' takes in game state and chosen row to place given card in if bAppend == True
else if bAppend is false skip appending any specific card.
randomly simulates rest of game and returns score '''
gs_copy = copy.deepcopy(game_state) # deepcopy copies all elements including nested ones
if bAppend == True:
gs_copy = simulate_append_card(gs_copy, row, card, True) # append card to appropriate position in game state
prune_deck_of_cards(gs_copy)
#print gs_copy
if op_deck is None:
global deck # get available cards for placement
tdeck = deck[:]
random.shuffle(tdeck)
else:
# use a specific passed deck (e.g. for consistent unit testing)
tdeck = op_deck[:]
# populate empty slots in game board with random cards
for i in range(1,14):
if gs_copy['properties2']['cards']['items']['position'+str(i)] == None:
gs_copy['properties2']['cards']['items']['position'+str(i)] = tdeck.pop(0)
if gs_copy['properties1']['cards']['items']['position'+str(i)] == None:
gs_copy['properties1']['cards']['items']['position'+str(i)] = tdeck.pop(0)
current_milli_time = lambda: int(round(time.time() * 1000))
stime2 = current_milli_time()
scores = helpers.scoring_helper(gs_copy) # score game board
global loop_elapsed
loop_elapsed += (current_milli_time() - stime2)
p2score = (helpers.scores_arr_to_int(scores)) * -1 # function returns p1's score. Get the inverse of this for AI's EV
global counthands
counthands += 1
if scores[3][1] == False or scores[3][0] == False: # only printing valid results (fouled simulated hands from both players omitted)
if p2score > 0:
global scoringhands
scoringhands += 1
elif p2score == 0:
global zeroscorehands
zeroscorehands += 1
else:
global losinghands
losinghands += 1
else:
global nullscoringhands
nullscoringhands += 1
return p2score
def test_scores_arr_to_int5(self):
# test validation in scores_arr_to_int
print "\nTest #14 scores_arr_to_int - validation #3"
test_scores = [[1, 0, 0], [1, 0, 0], [1, 0, "uh oh!"], [False, False]]
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(None, result)
print "Passed!"
def test_scores_arr_to_int4(self):
# test validation in scores_arr_to_int
print "\nTest #13 scores_arr_to_int - validation #2"
test_scores = ["invalid list length"]
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(None, result)
print "Passed!"
def test_scores_arr_to_int3(self):
# test validation in scores_arr_to_int
print "\nTest #12 scores_arr_to_int - validation #1"
test_scores = "invalid type1"
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(None, result)
print "Passed!"
def test_scores_arr_to_int6(self):
# test validation in scores_arr_to_int
print "\nTest #15 scores_arr_to_int - validation #4"
test_scores = [[1, 0, 0], [1, 0, 0], [1, 0, 0],
[False, "look im not a boolean!"]]
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(None, result)
print "Passed!"
def test_scores_arr_to_int2(self):
# test that function correctly converts scores array to int (p1's score)
print "\nTest #11 scores_arr_to_int #2"
test_scores = [[2, 0, 5], [2, 0, 3], [2, 0, 6], [False, False]]
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(type(1), type(result))
self.assertEqual(-20, result)
print "Passed!"
def test_scores_arr_to_int1(self):
# test that function correctly converts scores array to int (p1's score)
print "\nTest #10 scores_arr_to_int #1"
test_scores = [[1, 3, 0], [1, 0, 0], [2, 0, 0], [False, False]]
result = helpers.scores_arr_to_int(test_scores)
self.assertEqual(type(1), type(result))
self.assertEqual(4, result)
print "Passed!"
def handle_game_logic(game_state, game_id):
'''
Take in game state from frontend and game id as inputs - use game id to get record from database
Compare game state passed to game state from db - validate legitimacy
Based off who went first and cards placed so far determine next action e.g. deal cards, AI, score board
Update game state changes and store in database, call AI helper functions to determine optimal play
Return appropriate response to server e.g. updated game state, cards to be placed, scores array
'''
current_milli_time = lambda: int(round(time.time() * 1000))
# retrieve database for this game
games = db_backend.get_database_collection()
state = games.find_one({'_id': ObjectId(game_id)})
# find if player acted first this round and how many cards have been placed in order to work out current game position
count = 0
playerFirst = state["playerFirst"]
for i in range(0, 13):
for j in range(0, 2):
if game_state['properties' +
str(j + 1)]['cards']['items']['position' +
str(i +
1)] is not None:
count += 1
print "\nCurrent game state:\n", game_state, "\nCards placed:", count
if playerFirst:
# Special case for player's first turn
if count == 0:
cdeck = deck.Deck() # creates deck
cards = cdeck.deal_n(5)
state['deck'] = {} # initialise deck dic within game state
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
state['first5cards'] = cards
# update game state in database
update = games.update({'_id': ObjectId(game_id)}, {'$set': state})
return json.dumps(cards)
# Special case for AI's first turn
elif count == 5:
# remove first 5 cards entry from db now that these have been placed on the board
del state['first5cards']
# recreate deck from deck info in database
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
# validate game state
state = validate_and_update_state(cdeck, count, game_state, state)
if state == 0:
return 0 # raise cherrypy 500 error
# calculate AI's first 5 card placements
cards = cdeck.deal_n(5)
OFCP_AI.loop_elapsed = 0
stime = current_milli_time()
iterations_timer = 4000 # Sets time in ms to spend simulating games.
# As iterations increases diverges to optimal solution
cardPlacementsAI = OFCP_AI.chooseMove(game_state, cards,
iterations_timer)
print "\nTime taken calculating 5 placements:", current_milli_time(
) - stime, "ms"
print "Total time spent scoring hands: ", OFCP_AI.loop_elapsed, "ms"
state = zip_placements_cards(cardPlacementsAI, cards, state)
if state == 1:
# Error with AI placement
return 1
# deal player's next card
card = cdeck.deal_one()
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# records game state in database + remove first5cards key
state['cardtoplace'] = card
update = games.update({'_id': ObjectId(game_id)}, {
'$set': state,
'$unset': {
'first5cards': 1
}
})
del state['deck'] # don't return deck info to frontend
del state['_id']
# state.pop('_id', None)
return json.dumps(state)
# general case for every other round after initial 5 placements by player and AI
elif count < 26:
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
# validate game state
state = validate_and_update_state(cdeck, count, game_state, state)
if state == 0:
return 0 # raise cherrypy 500 error
# AI's next move
card = str(cdeck.deal_one())
OFCP_AI.loop_elapsed = 0
stime = current_milli_time()
iterations_timer = 3000
AI_placement = OFCP_AI.chooseMove(game_state, card,
iterations_timer)
print "\nTime taken calculating 1 placement:", current_milli_time(
) - stime, "ms"
print "Total time spent scoring hands: ", OFCP_AI.loop_elapsed, "ms"
state = zip_placements_cards([AI_placement], [card], state)
if state == 1:
# Error with AI placement
return 1
# deal player's next card
card = cdeck.deal_one()
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# records game state in database
state['cardtoplace'] = card
update = games.update({'_id': ObjectId(game_id)}, {'$set': state})
# print "\nStored game state in database:", state
del state['deck'] # don't return deck info to frontend
del state['_id']
# print "\nReturning state to player:", state
return json.dumps(state)
else:
# game over - validate and score game board
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
# validate game state
state = validate_and_update_state(cdeck, count, game_state, state)
if state == 0:
return 0 # raise cherrypy 500 error
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# score game board
scores_array = helpers.scoring_helper(game_state)
# store p1's score in database
state['score'] += helpers.scores_arr_to_int(scores_array)
print "\nState score recorded as:", state['score'], "!\n"
scores_array.append([state['score']])
print "scores_array was", scores_array
# records game state in database
del state['cardtoplace']
update = games.update({'_id': ObjectId(game_id)}, {'$set': state})
OFCP_AI.reset() # reset AI variables/ states
# scores_array format [ [winnerid, winners_bottom_royalty, losers_bottom_royalty],
# [winnerid, winners_middle_royalty, losers_middle_royalty] ,
# [winnerid, winners_top_royalty, losers_top_royalty] ],
# [p1foulbool, p2foulbool],
# [p1_existing_score]
print '\n Scores -->', scores_array, '\n'
return json.dumps(scores_array)
else:
if count == 0:
# AI acts first, but return player's first 5 cards first while AI calculates
if 'first5cards' not in state:
cdeck = deck.Deck() # creates deck
cards_5_player = cdeck.deal_n(5) # player's first 5 cards
state['deck'] = {} # initialise deck dic within game state
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# validate game state
state = validate_and_update_state(cdeck, count, game_state,
state)
if state == 0:
return 0 # raise cherrypy 500 error
state['first5cards'] = cards_5_player
# update game state in database
update = games.update({'_id': ObjectId(game_id)},
{'$set': state})
return json.dumps(cards_5_player)
else:
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
cards_5_AI = cdeck.deal_n(5)
# validate game state
state = validate_and_update_state(cdeck, count, game_state,
state)
if state == 0:
return 0 # raise cherrypy 500 error
# calculate AI's first 5 card placements
OFCP_AI.loop_elapsed = 0
stime = current_milli_time()
iterations_timer = 4000 # Sets time in ms to spend simulating games.
# As iterations increases diverges to optimal solution
cardPlacementsAI = OFCP_AI.chooseMove(game_state, cards_5_AI,
iterations_timer)
print "\nTime taken calculating 5 placements:", current_milli_time(
) - stime, "ms"
print "Total time spent scoring hands: ", OFCP_AI.loop_elapsed, "ms"
state = zip_placements_cards(cardPlacementsAI, cards_5_AI,
state)
if state == 1:
# Error with AI placement
return 1
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# records game state in database + remove first5cards key
update = games.update({'_id': ObjectId(game_id)},
{'$set': state})
del state['deck'] # don't return deck info to frontend
del state['_id']
# state.pop('_id', None)
return json.dumps(state)
# general case for every other round after initial 5 placements by player and AI
elif count < 26:
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
# validate game state
state = validate_and_update_state(cdeck, count, game_state, state)
if state == 0:
return 0 # raise cherrypy 500 error
# AI's next move
card = str(cdeck.deal_one())
OFCP_AI.loop_elapsed = 0
stime = current_milli_time()
iterations_timer = 3000
AI_placement = OFCP_AI.chooseMove(game_state, card,
iterations_timer)
print "\nTime taken calculating 1 placement:", current_milli_time(
) - stime, "ms"
print "Total time spent scoring hands: ", OFCP_AI.loop_elapsed, "ms"
state = zip_placements_cards([AI_placement], [card], state)
if state == 1:
# Error with AI placement
return 1
# deal player's next card
card = cdeck.deal_one()
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# records game state in database
state['cardtoplace'] = card
update = games.update({'_id': ObjectId(game_id)}, {'$set': state})
# print "\nStored game state in database:", state
del state['deck'] # don't return deck info to frontend
del state['_id']
# print "\nReturning state to player:", state
return json.dumps(state)
else:
# game over - validate and score game board
cdeck = deck.Deck(state['deck']['cards'],
state['deck']['current-position'])
# validate game state
state = validate_and_update_state(cdeck, count, game_state, state)
if state == 0:
return 0 # raise cherrypy 500 error
# update game state with deck info
state['deck']['cards'] = cdeck.cards
state['deck']['current-position'] = cdeck.current_position
# score game board
scores_array = helpers.scoring_helper(game_state)
# store p1's score in database
state['score'] += helpers.scores_arr_to_int(scores_array)
print "\nState score recorded as:", state['score'], "!\n"
scores_array.append([state['score']])
print "scores_array was", scores_array
# records game state in database
del state['cardtoplace']
update = games.update({'_id': ObjectId(game_id)}, {'$set': state})
OFCP_AI.reset() # reset AI variables/ states
# scores_array format [ [winnerid, winners_bottom_royalty, losers_bottom_royalty],
# [winnerid, winners_middle_royalty, losers_middle_royalty] ,
# [winnerid, winners_top_royalty, losers_top_royalty] ],
# [p1foulbool, p2foulbool],
# [p1_existing_score]
print '\n Scores -->', scores_array, '\n'
return json.dumps(scores_array)
