w1l212_randomWalks-segment4.py

class Location(object):
    
    def __init__(self, x, y):
        """x and y are floats"""
        self.x = x
        self.y = y
        
    def move(self, deltaX, deltaY):
        """deltaX and deltaY are floats"""
        return Location(self.x + deltaX, self.y + deltaY)
    
    def getX(self):
        return self.x
    
    def getY(self):
        return self.y
    
    def distFrom(self, other):
        ox = other.x
        oy = other.y
        xDist = self.x - ox
        yDist = self.y - oy
        return (xDist**2 + yDist**2)**0.5
    
    def __str__(self):
        return '<' + str(self.x) + ', ' + str(self.y) + '>'





class Field(object):
    
    def __init__(self):
        self.drunks = {}
        
    def addDrunk(self, drunk, loc):
        if drunk in self.drunks:
            raise ValueError('Duplicate drunk')
        else:
            self.drunks[drunk] = loc
            
    def moveDrunk(self, drunk):
        if not drunk in self.drunks:
            raise ValueError('Drunk not in field')
        xDist, yDist = drunk.takeStep()
        currentLocation = self.drunks[drunk]
        #use move method of Location to get new location
        self.drunks[drunk] = currentLocation.move(xDist, yDist)
        
    def getLoc(self, drunk):
        if not drunk in self.drunks:
            raise ValueError('Drunk not in field')
        return self.drunks[drunk]










import random


class Drunk(object):
    def __init__(self, name):
        self.name = name
    def __str__(self):
        return 'This drunk is named ' + self.name
    
class UsualDrunk(Drunk):
    def takeStep(self):
        stepChoices =\
            [(0.0,1.0), (0.0,-1.0), (1.0, 0.0), (-1.0, 0.0)]
        return random.choice(stepChoices)


def walk(f, d, numSteps):
    start = f.getLoc(d)
    for s in range(numSteps):
        f.moveDrunk(d)
    return(start.distFrom(f.getLoc(d)))



import pylab

 #set line width
pylab.rcParams['lines.linewidth'] = 6
 #set font size for titles
pylab.rcParams['axes.titlesize'] = 20
 #set font size for labels on axes
pylab.rcParams['axes.labelsize'] = 20
 #set size of numbers on x-axis
pylab.rcParams['xtick.major.size'] = 5
 #set size of numbers on y-axis
pylab.rcParams['ytick.major.size'] = 5
 #set size of markers
pylab.rcParams['lines.markersize'] = 10


#Start code added in Segment 4



def drunkTestP(numTrials = 50):
    stepsTaken = [10, 100, 1000, 10000]
    meanDistances = []
    for numSteps in stepsTaken:
        distances = simWalks(numSteps, numTrials)
        meanDistances.append(sum(distances)/len(distances))
    pylab.plot(stepsTaken, meanDistances)
    pylab.title('Mean Distance from Origin')
    pylab.xlabel('Steps Taken')
    pylab.ylabel('Steps from Origin')
    pylab.show()




    
def drunkTestP1(numTrials = 50):
    stepsTaken = [10, 100, 1000, 10000]
    meanDistances = []
    squareRootOfSteps = []
    for numSteps in stepsTaken:
        distances = simWalks(numSteps, numTrials)
        meanDistances.append(sum(distances)/len(distances))
        squareRootOfSteps.append(numSteps**0.5)
    pylab.plot(stepsTaken, meanDistances, 'b-',
               label = 'Mean distance')
    pylab.plot(stepsTaken, squareRootOfSteps, 'g-.',
               label = 'Square root of steps')
    pylab.title('Mean Distance from Origin')
    pylab.xlabel('Steps Taken')
    pylab.ylabel('Steps from Origin')
    pylab.legend()
    pylab.show()







#Look at different kinds of drunks

class UsualDrunk(Drunk):
    def takeStep(self):
        stepChoices =\
            [(0.0,1.0), (0.0,-1.0), (1.0, 0.0), (-1.0, 0.0)]
        return random.choice(stepChoices)

class ColdDrunk(Drunk):
    def takeStep(self):
        stepChoices =\
            [(0.0,0.95), (0.0,-1.0), (1.0, 0.0), (-1.0, 0.0)]
        return random.choice(stepChoices)

class EDrunk(Drunk):
    def takeStep(self):
        deltaX = random.random()
        if random.random() < 0.5:
            deltaX = -deltaX
        deltaY = random.random()
        if random.random() < 0.5:
            deltaY = -deltaY
        return (deltaX, deltaY)

# New version of simWalks

def simWalks(numSteps, numTrials, dClass):
    homer = dClass('Homer')
    origin = Location(0, 0)
    distances = []
    for t in range(numTrials):
        f = Field()
        f.addDrunk(homer, origin)
        distances.append(walk(f, homer, numSteps))
    return distances


def drunkTestP(numTrials = 50):
    stepsTaken = [10, 100, 1000, 10000]
    for dClass in (UsualDrunk, ColdDrunk, EDrunk):
        meanDistances = []
        for numSteps in stepsTaken:
            distances = simWalks(numSteps, numTrials, dClass)
            meanDistances.append(sum(distances)/len(distances))
        pylab.plot(stepsTaken, meanDistances,
                   label = dClass.__name__)
        pylab.title('Mean Distance from Origin')
        pylab.xlabel('Steps Taken')
        pylab.ylabel('Steps from Origin')
        pylab.legend(loc = 'upper left')
    pylab.show()