capture.py

# capture.py
# ----------
# Licensing Information:  You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
#
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# Student side autograding was added by Brad Miller, Nick Hay, and
# Pieter Abbeel (pabbeel@cs.berkeley.edu).


# 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
"""
import traceback
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
import util
import types
import time
import random
import imp
import keyboardAgents
import geneticOptimizer

# If you change these, you won't affect the server, so you can't cheat
KILL_POINTS = .05
FOOD_POINTS = .1
CAPSULE_POINTS = .15
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
TOTAL_FOOD = 60

DUMP_FOOD_ON_DEATH = True  # if we have the gameplay element that dumps dots on death

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]
        # This is usually 60 (always 60 with random maps)
        # However, if layout map is specified otherwise, it could be less
        global TOTAL_FOOD
        TOTAL_FOOD = layout.totalFood

    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 = int(grid.width / 2)
    halfgrid = Grid(grid.width, grid.height, False)
    if red:
        xrange = list(range(halfway))
    else:
        xrange = list(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:
                redCount = 0
                blueCount = 0
                foodToWin = (TOTAL_FOOD/2) - MIN_FOOD
                for index in range(state.getNumAgents()):
                    agentState = state.data.agentStates[index]
                    if index in state.getRedTeamIndices():
                        redCount += agentState.numReturned
                    else:
                        blueCount += agentState.numReturned

                if blueCount >= foodToWin:  # state.getRedFood().count() == MIN_FOOD:
                    print(
                        'The Blue team has returned at least %d of the opponents\' dots.' % foodToWin)
                elif redCount >= foodToWin:  # state.getBlueFood().count() == MIN_FOOD:
                    print(
                        'The Red team has returned at least %d of the opponents\' dots.' % foodToWin)
                else:  # if state.getBlueFood().count() > MIN_FOOD and state.getRedFood().count() > MIN_FOOD:
                    # print('Time is up.')
                    if state.data.score == 0:
                        pass
                        # print('Tie game!')
                    else:
                        winner = 'Red'
                        if state.data.score < 0:
                            winner = 'Blue'
                        # print('The %s team wins by %f 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", file=sys.stderr)
            game.state.data.score = -1
        else:
            print("Blue agent crashed", file=sys.stderr)
            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 next == nearest:
            isRed = state.isOnRedTeam(agentIndex)
            # Change agent type
            agentState.isPacman = [isRed, state.isRed(
                agentState.configuration)].count(True) == 1
            # if he's no longer pacman, he's on his own side, so reset the num carrying timer
            #agentState.numCarrying *= int(agentState.isPacman)
            if agentState.numCarrying > 0 and not agentState.isPacman:
                score = agentState.numCarrying if isRed else -1*agentState.numCarrying
                state.data.scoreChange += score

                agentState.numReturned += agentState.numCarrying
                agentState.numCarrying = 0

                redCount = 0
                blueCount = 0
                for index in range(state.getNumAgents()):
                    agentState = state.data.agentStates[index]
                    if index in state.getRedTeamIndices():
                        redCount += agentState.numReturned
                    else:
                        blueCount += agentState.numReturned
                if redCount >= (TOTAL_FOOD/2) - MIN_FOOD or blueCount >= (TOTAL_FOOD/2) - MIN_FOOD:
                    state.data._win = True

        if agentState.isPacman and manhattanDistance(nearest, next) <= 0.9:
            AgentRules.consume(nearest, state, state.isOnRedTeam(agentIndex))

    applyAction = staticmethod(applyAction)

    def consume(position, state, isRed):
        x, y = position
        # Eat food
        if state.data.food[x][y]:

            # blue case is the default
            teamIndicesFunc = state.getBlueTeamIndices
            score = -1
            if isRed:
                # switch if its red
                score = 1
                teamIndicesFunc = state.getRedTeamIndices

            # go increase the variable for the pacman who ate this
            agents = [state.data.agentStates[agentIndex]
                      for agentIndex in teamIndicesFunc()]
            i = 0
            for agent in agents:
                if agent.getPosition() == position:
                    agent.numCarrying += 1
                    agentIndex = teamIndicesFunc()[i]
                    score = FOOD_POINTS
                    if not state.isOnRedTeam(agentIndex):
                        score = -score
                    state.data.scoreChange += score
                    break  # the above should only be true for one agent...
                i += 1

            # do all the score and food grid maintainenace
            #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

            # blue case is the default
            teamIndicesFunc = state.getBlueTeamIndices
            if isRed:
                # switch if its red
                teamIndicesFunc = state.getRedTeamIndices

            agents = [state.data.agentStates[agentIndex]
                      for agentIndex in teamIndicesFunc()]
            i = 0
            for agent in agents:
                if agent.getPosition() == position:
                    agentIndex = teamIndicesFunc()[i]
                    score = CAPSULE_POINTS
                    if not state.isOnRedTeam(agentIndex):
                        score = -score
                    state.data.scoreChange += score
                    break  # the above should only be true for one agent...
                i += 1

    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 dumpFoodFromDeath(state, agentState, agentIndex):
        if not (DUMP_FOOD_ON_DEATH):
            # this feature is not turned on
            return

        if not agentState.isPacman:
            raise Exception(
                'something is seriously wrong, this agent isnt a pacman!')

        # ok so agentState is this:
        if (agentState.numCarrying == 0):
            return

        # first, score changes!
        # we HACK pack that ugly bug by just determining if its red based on the first position
        # to die...
        dummyConfig = Configuration(agentState.getPosition(), 'North')
        isRed = state.isRed(dummyConfig)

        # the score increases if red eats dots, so if we are refunding points,
        # the direction should be -1 if the red agent died, which means he dies
        # on the blue side
        scoreDirection = (-1)**(int(isRed) + 1)
        #state.data.scoreChange += scoreDirection * agentState.numCarrying

        def onRightSide(state, x, y):
            dummyConfig = Configuration((x, y), 'North')
            return state.isRed(dummyConfig) == isRed

        # we have food to dump
        # -- expand out in BFS. Check:
        #   - that it's within the limits
        #   - that it's not a wall
        #   - that no other agents are there
        #   - that no power pellets are there
        #   - that it's on the right side of the grid
        def allGood(state, x, y):
            width, height = state.data.layout.width, state.data.layout.height
            food, walls = state.data.food, state.data.layout.walls

            # bounds check
            if x >= width or y >= height or x <= 0 or y <= 0:
                return False

            if walls[x][y]:
                return False
            if food[x][y]:
                return False

            # dots need to be on the side where this agent will be a pacman :P
            if not onRightSide(state, x, y):
                return False

            if (x, y) in state.data.capsules:
                return False

            # loop through agents
            agentPoses = [state.getAgentPosition(
                i) for i in range(state.getNumAgents())]
            if (x, y) in agentPoses:
                return False

            return True

        numToDump = agentState.numCarrying
        state.data.food = state.data.food.copy()
        foodAdded = []

        def genSuccessors(x, y):
            DX = [-1, 0, 1]
            DY = [-1, 0, 1]
            return [(x + dx, y + dy) for dx in DX for dy in DY]

        # BFS graph search
        positionQueue = [agentState.getPosition()]
        seen = set()
        while numToDump > 0:
            if not len(positionQueue):
                raise Exception('Exhausted BFS! uh oh')
            # pop one off, graph check
            popped = positionQueue.pop(0)
            if popped in seen:
                continue
            seen.add(popped)

            x, y = popped[0], popped[1]
            x = int(x)
            y = int(y)
            if (allGood(state, x, y)):
                state.data.food[x][y] = True
                foodAdded.append((x, y))
                numToDump -= 1

            # generate successors
            positionQueue = positionQueue + genSuccessors(x, y)

        state.data._foodAdded = foodAdded
        # now our agentState is no longer carrying food
        agentState.numCarrying = 0
        pass

    dumpFoodFromDeath = staticmethod(dumpFoodFromDeath)

    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:
                        AgentRules.dumpFoodFromDeath(
                            state, agentState, agentIndex)

                        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:
                        AgentRules.dumpFoodFromDeath(
                            state, otherAgentState, agentIndex)

                        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 <options>
  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('--red-name', help=default('Red team name'),
                      default='Red')
    parser.add_option('--blue-name', help=default('Blue team name'),
                      default='Blue')
    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<seed> 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_name
    args['blueTeamName'] = options.blue_name

    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 pickle
        recorded = pickle.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
    layouts = []
    for i in range(options.numGames):
        if options.layout == 'RANDOM':
            l = layout.Layout(randomLayout().split('\n'))
        elif options.layout.startswith('RANDOM'):
            l = 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:
            l = layout.getLayout(options.layout)
        if l == None:
            raise Exception("The layout " + options.layout +
                            " cannot be found")

        layouts.append(l)

    args['layouts'] = layouts
    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)


def loadAgents(isRed, factory, textgraphics, cmdLineArgs):
    "Calls agent factories and returns lists of agents"
    try:
        if not factory.endswith(".py"):
            factory += ".py"

        module = imp.load_source('player' + str(int(isRed)), factory)
    except (NameError, ImportError):
        print('Error: The team "' + factory +
              '" could not be loaded! ', file=sys.stderr)
        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! ', file=sys.stderr)
        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(layouts, agents, display, length, numGames, record, numTraining, redTeamName, blueTeamName, muteAgents=False, catchExceptions=False, optimize=False):

    rules = CaptureRules()
    games = []

    if numTraining > 0:
        print('Playing %d training games' % numTraining)

    for i in range(numGames):
        beQuiet = i < numTraining
        layout = layouts[i]
        if beQuiet:
            # Suppress output and graphics
            import textDisplay
            gameDisplay = textDisplay.NullGraphics()
            rules.quiet = True
        else:
            gameDisplay = display
            rules.quiet = False

        ###################
        # TODO: properly integrate options for running optimization
        optimizerRunner = geneticOptimizer.Runner(
            layout, gameDisplay, length, muteAgents, catchExceptions)
        optimizerRunner.run()
        ###################
        g = rules.newGame(layout, agents, gameDisplay,
                          length, muteAgents, catchExceptions)
        g.run()
        if not beQuiet:
            games.append(g)

        g.record = None
        if record:
            import time
            import pickle
            import 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 = pickle.dumps(components)
            with open('replay-%d' % i, '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


def save_score(game):
    with open('score', 'w') as f:
        print(game.state.data.score, file=f)


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
    games = runGames(**options)

    save_score(games[0])
    # import cProfile
    # cProfile.run('runGames( **options )', 'profile')