FINAL/p5.py at master · chin/FINAL · GitHub

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#!/usr/bin/python
import sys
import os
import math
import numpy as np
from statistics import mean
from statistics import stdev
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from scipy.stats import norm
import matplotlib.mlab as mlab


N = 10000 #number of simulations

cards_rem = []
n = 0

def sim():
    #create deck of cards
    deck = []
    hand = []
    Suits = ['C', 'D', 'H', 'S']
    for v in range(1,14):
        for s in Suits:
            deck.append( (s,v) )

    #shuffle the deck
    np.random.shuffle(deck)

    #Cards are shuffled and put face down on table
    hand.extend(deck[:4])
    #print(hand)
    deck = deck[4:]

    #print(str(hand[0].suit))
    while deck != []:
        while len(hand) < 4 and deck != []: #add card until we know there are at least 4 in hand
            hand.extend( deck[:1] )
            deck = deck[1:]
        #first and fourth
        if len(hand) >= 4:
            s1, v1 = hand[-4]
            s4, v4 = hand[-1]
            if s1 is s4:
                hand.remove( hand[-2] ) #second card
                hand.remove( hand[-2] ) #third card
            elif v1 == v4:
                hand.remove( hand[-1] ) #fourth card
                hand.remove( hand[-1] ) #third card
                hand.remove( hand[-1] ) #second card
                hand.remove( hand[-1] ) #first card
            else:
                hand.extend( deck[:1] )
                deck = deck[1:]
    cards_rem.extend(hand)
    return len(hand)
    # n +=1


rem = []
while n < N:
    x = sim()
    rem.append(x)
    #print(x)
    n += 1

rem.sort()

print( "Sample mean of remaining cards: ", mean(rem) )
print( "Sample standard deviation of remaining cards: ", stdev(rem) )

#(mu, sigma) = norm.fit(rem)

n, bins, patches = plt.hist(rem, bins='auto', normed=True)
#y = mlab.normpdf(bins, mean(rem), stdev(rem)**2)
avg = mean(rem)
var= stdev(rem)**2
pdf_x = np.linspace(np.min(rem), np.max(rem), 100)
pdf_y = 1.0/np.sqrt(2*np.pi*var)*np.exp(-0.5*(pdf_x-avg)**2/var)

plt.plot(pdf_x, pdf_y, 'k--', linewidth=2)

plt.title('Histogram of cards remaining')
plt.xlabel('No. Cards Remaining')
plt.ylabel('Frequency')
plt.grid(True)
plt.savefig('p5.png')
#plt.close(fig)