# capture.py # ---------- # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html # capture.py # ---------- # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html """ Capture.py holds the logic for Pacman capture the flag. (i) Your interface to the pacman world: Pacman is a complex environment. You probably don't want to read through all of the code we wrote to make the game runs correctly. This section contains the parts of the code that you will need to understand in order to complete the project. There is also some code in game.py that you should understand. (ii) The hidden secrets of pacman: This section contains all of the logic code that the pacman environment uses to decide who can move where, who dies when things collide, etc. You shouldn't need to read this section of code, but you can if you want. (iii) Framework to start a game: The final section contains the code for reading the command you use to set up the game, then starting up a new game, along with linking in all the external parts (agent functions, graphics). Check this section out to see all the options available to you. To play your first game, type 'python capture.py' from the command line. The keys are P1: 'a', 's', 'd', and 'w' to move P2: 'l', ';', ',' and 'p' to move """ from game import GameStateData from game import Game from game import Directions from game import Actions from util import nearestPoint from util import manhattanDistance from game import Grid from game import Configuration from game import Agent from game import reconstituteGrid import sys, util, types, time, random import keyboardAgents # If you change these, you won't affect the server, so you can't cheat KILL_POINTS = 0 SONAR_NOISE_RANGE = 13 # Must be odd SONAR_NOISE_VALUES = [i - (SONAR_NOISE_RANGE - 1)/2 for i in range(SONAR_NOISE_RANGE)] SIGHT_RANGE = 5 # Manhattan distance MIN_FOOD = 2 SCARED_TIME = 40 def noisyDistance(pos1, pos2): return int(util.manhattanDistance(pos1, pos2) + random.choice(SONAR_NOISE_VALUES)) ################################################### # YOUR INTERFACE TO THE PACMAN WORLD: A GameState # ################################################### class GameState: """ A GameState specifies the full game state, including the food, capsules, agent configurations and score changes. GameStates are used by the Game object to capture the actual state of the game and can be used by agents to reason about the game. Much of the information in a GameState is stored in a GameStateData object. We strongly suggest that you access that data via the accessor methods below rather than referring to the GameStateData object directly. """ #################################################### # Accessor methods: use these to access state data # #################################################### def getLegalActions( self, agentIndex=0 ): """ Returns the legal actions for the agent specified. """ return AgentRules.getLegalActions( self, agentIndex ) def generateSuccessor( self, agentIndex, action): """ Returns the successor state (a GameState object) after the specified agent takes the action. """ # Copy current state state = GameState(self) # Find appropriate rules for the agent AgentRules.applyAction( state, action, agentIndex ) AgentRules.checkDeath(state, agentIndex) AgentRules.decrementTimer(state.data.agentStates[agentIndex]) # Book keeping state.data._agentMoved = agentIndex state.data.score += state.data.scoreChange state.data.timeleft = self.data.timeleft - 1 return state def getAgentState(self, index): return self.data.agentStates[index] def getAgentPosition(self, index): """ Returns a location tuple if the agent with the given index is observable; if the agent is unobservable, returns None. """ agentState = self.data.agentStates[index] ret = agentState.getPosition() if ret: return tuple(int(x) for x in ret) return ret def getNumAgents( self ): return len( self.data.agentStates ) def getScore( self ): """ Returns a number corresponding to the current score. """ return self.data.score def getRedFood(self): """ Returns a matrix of food that corresponds to the food on the red team's side. For the matrix m, m[x][y]=true if there is food in (x,y) that belongs to red (meaning red is protecting it, blue is trying to eat it). """ return halfGrid(self.data.food, red = True) def getBlueFood(self): """ Returns a matrix of food that corresponds to the food on the blue team's side. For the matrix m, m[x][y]=true if there is food in (x,y) that belongs to blue (meaning blue is protecting it, red is trying to eat it). """ return halfGrid(self.data.food, red = False) def getRedCapsules(self): return halfList(self.data.capsules, self.data.food, red = True) def getBlueCapsules(self): return halfList(self.data.capsules, self.data.food, red = False) def getWalls(self): """ Just like getFood but for walls """ return self.data.layout.walls def hasFood(self, x, y): """ Returns true if the location (x,y) has food, regardless of whether it's blue team food or red team food. """ return self.data.food[x][y] def hasWall(self, x, y): """ Returns true if (x,y) has a wall, false otherwise. """ return self.data.layout.walls[x][y] def isOver( self ): return self.data._win def getRedTeamIndices(self): """ Returns a list of agent index numbers for the agents on the red team. """ return self.redTeam[:] def getBlueTeamIndices(self): """ Returns a list of the agent index numbers for the agents on the blue team. """ return self.blueTeam[:] def isOnRedTeam(self, agentIndex): """ Returns true if the agent with the given agentIndex is on the red team. """ return self.teams[agentIndex] def getAgentDistances(self): """ Returns a noisy distance to each agent. """ if 'agentDistances' in dir(self) : return self.agentDistances else: return None def getDistanceProb(self, trueDistance, noisyDistance): "Returns the probability of a noisy distance given the true distance" if noisyDistance - trueDistance in SONAR_NOISE_VALUES: return 1.0/SONAR_NOISE_RANGE else: return 0 def getInitialAgentPosition(self, agentIndex): "Returns the initial position of an agent." return self.data.layout.agentPositions[agentIndex][1] def getCapsules(self): """ Returns a list of positions (x,y) of the remaining capsules. """ return self.data.capsules ############################################# # Helper methods: # # You shouldn't need to call these directly # ############################################# def __init__( self, prevState = None ): """ Generates a new state by copying information from its predecessor. """ if prevState != None: # Initial state self.data = GameStateData(prevState.data) self.blueTeam = prevState.blueTeam self.redTeam = prevState.redTeam self.data.timeleft = prevState.data.timeleft self.teams = prevState.teams self.agentDistances = prevState.agentDistances else: self.data = GameStateData() self.agentDistances = [] def deepCopy( self ): state = GameState( self ) state.data = self.data.deepCopy() state.data.timeleft = self.data.timeleft state.blueTeam = self.blueTeam[:] state.redTeam = self.redTeam[:] state.teams = self.teams[:] state.agentDistances = self.agentDistances[:] return state def makeObservation(self, index): state = self.deepCopy() # Adds the sonar signal pos = state.getAgentPosition(index) n = state.getNumAgents() distances = [noisyDistance(pos, state.getAgentPosition(i)) for i in range(n)] state.agentDistances = distances # Remove states of distant opponents if index in self.blueTeam: team = self.blueTeam otherTeam = self.redTeam else: otherTeam = self.blueTeam team = self.redTeam for enemy in otherTeam: seen = False enemyPos = state.getAgentPosition(enemy) for teammate in team: if util.manhattanDistance(enemyPos, state.getAgentPosition(teammate)) <= SIGHT_RANGE: seen = True if not seen: state.data.agentStates[enemy].configuration = None return state def __eq__( self, other ): """ Allows two states to be compared. """ if other == None: return False return self.data == other.data def __hash__( self ): """ Allows states to be keys of dictionaries. """ return int(hash( self.data )) def __str__( self ): return str(self.data) def initialize( self, layout, numAgents): """ Creates an initial game state from a layout array (see layout.py). """ self.data.initialize(layout, numAgents) positions = [a.configuration for a in self.data.agentStates] self.blueTeam = [i for i,p in enumerate(positions) if not self.isRed(p)] self.redTeam = [i for i,p in enumerate(positions) if self.isRed(p)] self.teams = [self.isRed(p) for p in positions] def isRed(self, configOrPos): width = self.data.layout.width if type(configOrPos) == type( (0,0) ): return configOrPos[0] < width / 2 else: return configOrPos.pos[0] < width / 2 def halfGrid(grid, red): halfway = grid.width / 2 halfgrid = Grid(grid.width, grid.height, False) if red: xrange = range(halfway) else: xrange = range(halfway, grid.width) for y in range(grid.height): for x in xrange: if grid[x][y]: halfgrid[x][y] = True return halfgrid def halfList(l, grid, red): halfway = grid.width / 2 newList = [] for x,y in l: if red and x <= halfway: newList.append((x,y)) elif not red and x > halfway: newList.append((x,y)) return newList ############################################################################ # THE HIDDEN SECRETS OF PACMAN # # # # You shouldn't need to look through the code in this section of the file. # ############################################################################ COLLISION_TOLERANCE = 0.7 # How close ghosts must be to Pacman to kill class CaptureRules: """ These game rules manage the control flow of a game, deciding when and how the game starts and ends. """ def __init__(self, quiet = False): self.quiet = quiet def newGame( self, layout, agents, display, length, muteAgents, catchExceptions ): initState = GameState() initState.initialize( layout, len(agents) ) starter = random.randint(0,1) print('%s team starts' % ['Red', 'Blue'][starter]) game = Game(agents, display, self, startingIndex=starter, muteAgents=muteAgents, catchExceptions=catchExceptions) game.state = initState game.length = length game.state.data.timeleft = length if 'drawCenterLine' in dir(display): display.drawCenterLine() self._initBlueFood = initState.getBlueFood().count() self._initRedFood = initState.getRedFood().count() return game def process(self, state, game): """ Checks to see whether it is time to end the game. """ if 'moveHistory' in dir(game): if len(game.moveHistory) == game.length: state.data._win = True if state.isOver(): game.gameOver = True if not game.rules.quiet: if state.getRedFood().count() == MIN_FOOD: print 'The Blue team has captured all but %d of the opponents\' dots.' % MIN_FOOD if state.getBlueFood().count() == MIN_FOOD: print 'The Red team has captured all but %d of the opponents\' dots.' % MIN_FOOD if state.getBlueFood().count() > MIN_FOOD and state.getRedFood().count() > MIN_FOOD: print 'Time is up.' if state.data.score == 0: print 'Tie game!' else: winner = 'Red' if state.data.score < 0: winner = 'Blue' print 'The %s team wins by %d points.' % (winner, abs(state.data.score)) def getProgress(self, game): blue = 1.0 - (game.state.getBlueFood().count() / float(self._initBlueFood)) red = 1.0 - (game.state.getRedFood().count() / float(self._initRedFood)) moves = len(self.moveHistory) / float(game.length) # return the most likely progress indicator, clamped to [0, 1] return min(max(0.75 * max(red, blue) + 0.25 * moves, 0.0), 1.0) def agentCrash(self, game, agentIndex): if agentIndex % 2 == 0: print "Red agent crashed" game.state.data.score = -1 else: print "Blue agent crashed" game.state.data.score = 1 def getMaxTotalTime(self, agentIndex): return 900 # Move limits should prevent this from ever happening def getMaxStartupTime(self, agentIndex): return 15 # 15 seconds for registerInitialState def getMoveWarningTime(self, agentIndex): return 1 # One second per move def getMoveTimeout(self, agentIndex): return 3 # Three seconds results in instant forfeit def getMaxTimeWarnings(self, agentIndex): return 2 # Third violation loses the game class AgentRules: """ These functions govern how each agent interacts with her environment. """ def getLegalActions( state, agentIndex ): """ Returns a list of legal actions (which are both possible & allowed) """ agentState = state.getAgentState(agentIndex) conf = agentState.configuration possibleActions = Actions.getPossibleActions( conf, state.data.layout.walls ) return AgentRules.filterForAllowedActions( agentState, possibleActions) getLegalActions = staticmethod( getLegalActions ) def filterForAllowedActions(agentState, possibleActions): return possibleActions filterForAllowedActions = staticmethod( filterForAllowedActions ) def applyAction( state, action, agentIndex ): """ Edits the state to reflect the results of the action. """ legal = AgentRules.getLegalActions( state, agentIndex ) if action not in legal: raise Exception("Illegal action " + str(action)) # Update Configuration agentState = state.data.agentStates[agentIndex] speed = 1.0 # if agentState.isPacman: speed = 0.5 vector = Actions.directionToVector( action, speed ) oldConfig = agentState.configuration agentState.configuration = oldConfig.generateSuccessor( vector ) # Eat next = agentState.configuration.getPosition() nearest = nearestPoint( next ) if agentState.isPacman and manhattanDistance( nearest, next ) <= 0.9 : AgentRules.consume( nearest, state, state.isOnRedTeam(agentIndex) ) # Change agent type if next == nearest: agentState.isPacman = [state.isOnRedTeam(agentIndex), state.isRed(agentState.configuration)].count(True) == 1 applyAction = staticmethod( applyAction ) def consume( position, state, isRed ): x,y = position # Eat food if state.data.food[x][y]: score = -1 if isRed: score = 1 state.data.scoreChange += score state.data.food = state.data.food.copy() state.data.food[x][y] = False state.data._foodEaten = position if (isRed and state.getBlueFood().count() == MIN_FOOD) or (not isRed and state.getRedFood().count() == MIN_FOOD): state.data._win = True # Eat capsule if isRed: myCapsules = state.getBlueCapsules() else: myCapsules = state.getRedCapsules() if( position in myCapsules ): state.data.capsules.remove( position ) state.data._capsuleEaten = position # Reset all ghosts' scared timers if isRed: otherTeam = state.getBlueTeamIndices() else: otherTeam = state.getRedTeamIndices() for index in otherTeam: state.data.agentStates[index].scaredTimer = SCARED_TIME consume = staticmethod( consume ) def decrementTimer(state): timer = state.scaredTimer if timer == 1: state.configuration.pos = nearestPoint( state.configuration.pos ) state.scaredTimer = max( 0, timer - 1 ) decrementTimer = staticmethod( decrementTimer ) def checkDeath( state, agentIndex): agentState = state.data.agentStates[agentIndex] if state.isOnRedTeam(agentIndex): otherTeam = state.getBlueTeamIndices() else: otherTeam = state.getRedTeamIndices() if agentState.isPacman: for index in otherTeam: otherAgentState = state.data.agentStates[index] if otherAgentState.isPacman: continue ghostPosition = otherAgentState.getPosition() if ghostPosition == None: continue if manhattanDistance( ghostPosition, agentState.getPosition() ) <= COLLISION_TOLERANCE: #award points to the other team for killing Pacmen if otherAgentState.scaredTimer <= 0: score = KILL_POINTS if state.isOnRedTeam(agentIndex): score = -score state.data.scoreChange += score agentState.isPacman = False agentState.configuration = agentState.start agentState.scaredTimer = 0 else: score = KILL_POINTS if state.isOnRedTeam(agentIndex): score = -score state.data.scoreChange += score otherAgentState.isPacman = False otherAgentState.configuration = otherAgentState.start otherAgentState.scaredTimer = 0 else: # Agent is a ghost for index in otherTeam: otherAgentState = state.data.agentStates[index] if not otherAgentState.isPacman: continue pacPos = otherAgentState.getPosition() if pacPos == None: continue if manhattanDistance( pacPos, agentState.getPosition() ) <= COLLISION_TOLERANCE: #award points to the other team for killing Pacmen if agentState.scaredTimer <= 0: score = KILL_POINTS if not state.isOnRedTeam(agentIndex): score = -score state.data.scoreChange += score otherAgentState.isPacman = False otherAgentState.configuration = otherAgentState.start otherAgentState.scaredTimer = 0 else: score = KILL_POINTS if state.isOnRedTeam(agentIndex): score = -score state.data.scoreChange += score agentState.isPacman = False agentState.configuration = agentState.start agentState.scaredTimer = 0 checkDeath = staticmethod( checkDeath ) def placeGhost(state, ghostState): ghostState.configuration = ghostState.start placeGhost = staticmethod( placeGhost ) ############################# # FRAMEWORK TO START A GAME # ############################# def default(str): return str + ' [Default: %default]' def parseAgentArgs(str): if str == None or str == '': return {} pieces = str.split(',') opts = {} for p in pieces: if '=' in p: key, val = p.split('=') else: key,val = p, 1 opts[key] = val return opts def readCommand( argv ): """ Processes the command used to run pacman from the command line. """ from optparse import OptionParser usageStr = """ USAGE: python pacman.py EXAMPLES: (1) python capture.py - starts a game with two baseline agents (2) python capture.py --keys0 - starts a two-player interactive game where the arrow keys control agent 0, and all other agents are baseline agents (3) python capture.py -r baselineTeam -b myTeam - starts a fully automated game where the red team is a baseline team and blue team is myTeam """ parser = OptionParser(usageStr) parser.add_option('-r', '--red', help=default('Red team'), default='baselineTeam') parser.add_option('-b', '--blue', help=default('Blue team'), default='baselineTeam') parser.add_option('--redOpts', help=default('Options for red team (e.g. first=keys)'), default='') parser.add_option('--blueOpts', help=default('Options for blue team (e.g. first=keys)'), default='') parser.add_option('--keys0', help='Make agent 0 (first red player) a keyboard agent', action='store_true',default=False) parser.add_option('--keys1', help='Make agent 1 (second red player) a keyboard agent', action='store_true',default=False) parser.add_option('--keys2', help='Make agent 2 (first blue player) a keyboard agent', action='store_true',default=False) parser.add_option('--keys3', help='Make agent 3 (second blue player) a keyboard agent', action='store_true',default=False) parser.add_option('-l', '--layout', dest='layout', help=default('the LAYOUT_FILE from which to load the map layout; use RANDOM for a random maze; use RANDOM to use a specified random seed, e.g., RANDOM23'), metavar='LAYOUT_FILE', default='defaultCapture') parser.add_option('-t', '--textgraphics', action='store_true', dest='textgraphics', help='Display output as text only', default=False) parser.add_option('-q', '--quiet', action='store_true', help='Display minimal output and no graphics', default=False) parser.add_option('-Q', '--super-quiet', action='store_true', dest="super_quiet", help='Same as -q but agent output is also suppressed', default=False) parser.add_option('-z', '--zoom', type='float', dest='zoom', help=default('Zoom in the graphics'), default=1) parser.add_option('-i', '--time', type='int', dest='time', help=default('TIME limit of a game in moves'), default=1200, metavar='TIME') parser.add_option('-n', '--numGames', type='int', help=default('Number of games to play'), default=1) parser.add_option('-f', '--fixRandomSeed', action='store_true', help='Fixes the random seed to always play the same game', default=False) parser.add_option('--record', action='store_true', help='Writes game histories to a file (named by the time they were played)', default=False) parser.add_option('--replay', default=None, help='Replays a recorded game file.') parser.add_option('-x', '--numTraining', dest='numTraining', type='int', help=default('How many episodes are training (suppresses output)'), default=0) parser.add_option('-c', '--catchExceptions', action='store_true', default=False, help='Catch exceptions and enforce time limits') options, otherjunk = parser.parse_args(argv) assert len(otherjunk) == 0, "Unrecognized options: " + str(otherjunk) args = dict() # Choose a display format #if options.pygame: # import pygameDisplay # args['display'] = pygameDisplay.PacmanGraphics() if options.textgraphics: import textDisplay args['display'] = textDisplay.PacmanGraphics() elif options.quiet: import textDisplay args['display'] = textDisplay.NullGraphics() elif options.super_quiet: import textDisplay args['display'] = textDisplay.NullGraphics() args['muteAgents'] = True else: import captureGraphicsDisplay # Hack for agents writing to the display captureGraphicsDisplay.FRAME_TIME = 0 args['display'] = captureGraphicsDisplay.PacmanGraphics(options.red, options.blue, options.zoom, 0, capture=True) import __main__ __main__.__dict__['_display'] = args['display'] args['redTeamName'] = options.red args['blueTeamName'] = options.blue if options.fixRandomSeed: random.seed('cs188') # Special case: recorded games don't use the runGames method or args structure if options.replay != None: print 'Replaying recorded game %s.' % options.replay import cPickle recorded = cPickle.load(open(options.replay)) recorded['display'] = args['display'] replayGame(**recorded) sys.exit(0) # Choose a pacman agent redArgs, blueArgs = parseAgentArgs(options.redOpts), parseAgentArgs(options.blueOpts) if options.numTraining > 0: redArgs['numTraining'] = options.numTraining blueArgs['numTraining'] = options.numTraining nokeyboard = options.textgraphics or options.quiet or options.numTraining > 0 print '\nRed team %s with %s:' % (options.red, redArgs) redAgents = loadAgents(True, options.red, nokeyboard, redArgs) print '\nBlue team %s with %s:' % (options.blue, blueArgs) blueAgents = loadAgents(False, options.blue, nokeyboard, blueArgs) args['agents'] = sum([list(el) for el in zip(redAgents, blueAgents)],[]) # list of agents numKeyboardAgents = 0 for index, val in enumerate([options.keys0, options.keys1, options.keys2, options.keys3]): if not val: continue if numKeyboardAgents == 0: agent = keyboardAgents.KeyboardAgent(index) elif numKeyboardAgents == 1: agent = keyboardAgents.KeyboardAgent2(index) else: raise Exception('Max of two keyboard agents supported') numKeyboardAgents += 1 args['agents'][index] = agent # Choose a layout import layout if options.layout.startswith('RANDOM'): args['layout'] = layout.Layout(randomLayout(int(options.layout[6:])).split('\n')) elif options.layout.lower().find('capture') == -1: raise Exception( 'You must use a capture layout with capture.py') else: args['layout'] = layout.getLayout( options.layout ) if args['layout'] == None: raise Exception("The layout " + options.layout + " cannot be found") args['length'] = options.time args['numGames'] = options.numGames args['numTraining'] = options.numTraining args['record'] = options.record args['catchExceptions'] = options.catchExceptions return args def randomLayout(seed = None): if not seed: seed = random.randint(0,99999999) # layout = 'layouts/random%08dCapture.lay' % seed # print 'Generating random layout in %s' % layout import mazeGenerator return mazeGenerator.generateMaze(seed) import traceback def loadAgents(isRed, factory, textgraphics, cmdLineArgs): "Calls agent factories and returns lists of agents" try: module = __import__(factory) except ImportError: print 'Error: The team "' + factory + '" could not be loaded! ' traceback.print_exc() return [None for i in range(2)] args = dict() args.update(cmdLineArgs) # Add command line args with priority print "Loading Team:", factory print "Arguments:", args # if textgraphics and factoryClassName.startswith('Keyboard'): # raise Exception('Using the keyboard requires graphics (no text display, quiet or training games)') try: createTeamFunc = getattr(module, 'createTeam') except AttributeError: print 'Error: The team "' + factory + '" could not be loaded! ' traceback.print_exc() return [None for i in range(2)] indexAddend = 0 if not isRed: indexAddend = 1 indices = [2*i + indexAddend for i in range(2)] return createTeamFunc(indices[0], indices[1], isRed, **args) def replayGame( layout, agents, actions, display, length, redTeamName, blueTeamName ): rules = CaptureRules() game = rules.newGame( layout, agents, display, length, False, False ) state = game.state display.redTeam = redTeamName display.blueTeam = blueTeamName display.initialize(state.data) for action in actions: # Execute the action state = state.generateSuccessor( *action ) # Change the display display.update( state.data ) # Allow for game specific conditions (winning, losing, etc.) rules.process(state, game) display.finish() def runGames( layout, agents, display, length, numGames, record, numTraining, redTeamName, blueTeamName, muteAgents=False, catchExceptions=False ): rules = CaptureRules() games = [] if numTraining > 0: print 'Playing %d training games' % numTraining for i in range( numGames ): beQuiet = i < numTraining if beQuiet: # Suppress output and graphics import textDisplay gameDisplay = textDisplay.NullGraphics() rules.quiet = True else: gameDisplay = display rules.quiet = False g = rules.newGame( layout, agents, gameDisplay, length, muteAgents, catchExceptions ) g.run() if not beQuiet: games.append(g) g.record = None if record: import time, cPickle, game #fname = ('recorded-game-%d' % (i + 1)) + '-'.join([str(t) for t in time.localtime()[1:6]]) #f = file(fname, 'w') components = {'layout': layout, 'agents': [game.Agent() for a in agents], 'actions': g.moveHistory, 'length': length, 'redTeamName': redTeamName, 'blueTeamName':blueTeamName } #f.close() print "recorded" g.record = cPickle.dumps(components) with open('replay','wb') as f: f.write(g.record) if numGames > 1: scores = [game.state.data.score for game in games] redWinRate = [s > 0 for s in scores].count(True)/ float(len(scores)) blueWinRate = [s < 0 for s in scores].count(True)/ float(len(scores)) print 'Average Score:', sum(scores) / float(len(scores)) print 'Scores: ', ', '.join([str(score) for score in scores]) print 'Red Win Rate: %d/%d (%.2f)' % ([s > 0 for s in scores].count(True), len(scores), redWinRate) print 'Blue Win Rate: %d/%d (%.2f)' % ([s < 0 for s in scores].count(True), len(scores), blueWinRate) print 'Record: ', ', '.join([('Blue', 'Tie', 'Red')[max(0, min(2, 1 + s))] for s in scores]) return games if __name__ == '__main__': """ The main function called when pacman.py is run from the command line: > python capture.py See the usage string for more details. > python capture.py --help """ options = readCommand( sys.argv[1:] ) # Get game components based on input runGames(**options) # import cProfile # cProfile.run('runGames( **options )', 'profile')