Monte-Carlo-Simulator/montecarlo6.py at master · PythonProgramming/Monte-Carlo-Simulator · GitHub

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import random
import matplotlib
import matplotlib.pyplot as plt
#
import time
from matplotlib import style
style.use("ggplot")
def rollDice():
    roll = random.randint(1,100)

    if roll == 100:
        return False
    elif roll <= 50:
        return False
    elif 100 > roll >= 50:
        return True


def doubler_bettor(funds,initial_wager,wager_count):
    global broke_count
    value = funds
    wager = initial_wager
    wX = []
    vY = []
    currentWager = 1

    # since we'll be betting based on previous bet outcome #
    previousWager = 'win'

    # since we'll be doubling #
    previousWagerAmount = initial_wager

    '''
    immediately with these comments, and our previous discussion of how previous outcomes
    do not affect future outcome possibilities, you should realize that this betting method
    offers nothing more than a quicker realization of losses or gains.

    Another way to visualize this quicker realization is actually an increase in risk.
    This bettor will experience extremely unpredictable volatility most likely.
    '''

    while currentWager <= wager_count:
        if previousWager == 'win':
            ##print 'we won the last wager, yay!'
            if rollDice():
                value += wager
                ##print value
                wX.append(currentWager)
                vY.append(value)
            else:
                value -= wager
                previousWager = 'loss'
                ##print value
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)
                if value < 0:
                    ##print 'went broke after',currentWager,'bets'
                    broke_count += 1
                    currentWager += 10000000000000000
        elif previousWager == 'loss':
            ##print 'we lost the last one, so we will be super smart & double up!'
            if rollDice():
                wager = previousWagerAmount * 2
                ##print 'we won',wager
                value += wager
                ##print value
                wager = initial_wager
                previousWager = 'win'
                wX.append(currentWager)
                vY.append(value)
            else:
                wager = previousWagerAmount * 2
                ##print 'we lost',wager
                value -= wager
                ##print value
                previousWager = 'loss'
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)
                if value < 0:
                    ##print 'went broke after',currentWager,'bets'
                    currentWager += 10000000000000000
                    broke_count += 1

        currentWager += 1

    ##print value
    plt.plot(wX,vY)


xx = 0
broke_count = 0

while xx < 1000:
    doubler_bettor(10000,100,100)
    xx+=1

#print 'death rate:',(broke_count/float(xx)) * 100
#print 'survival rate:',100 - ((broke_count/float(xx)) * 100)
plt.axhline(0, color = 'r')
plt.show()
time.sleep(555)


'''
Simple bettor, betting the same amount each time.
'''
def simple_bettor(funds,initial_wager,wager_count):
    value = funds
    wager = initial_wager
    wX = []
    vY = []
    currentWager = 1
    while currentWager <= wager_count:
        if rollDice():
            value += wager
            wX.append(currentWager)
            vY.append(value)
        else:
            value -= wager
            wX.append(currentWager)
            vY.append(value)
        currentWager += 1
    plt.plot(wX,vY)
x = 0


while x < 100:
    simple_bettor(10000,100,1000)
    x += 1

plt.ylabel('Account Value')
plt.xlabel('Wager Count')
plt.show()