pandem.py

import random
import collections

def num_cards():
    cures = [0] * 48 + [1] * 4
    random.shuffle(cures)
    def split(x, n):
        return [x[i:len(x):n] for i in range(n)]
    cures = [c + [2] for c in split(cures, 5)]
    [random.shuffle(c) for c in cures]
    cures = [item for sublist in cures for item in sublist]
    # print (cures)
    top = [0]
    dis = [9]
    rate = [4,4,3,3,2,2,2]
    while len(cures) > 1:
        def take():
            c = cures.pop()
            if (c == 2):
                rate.pop()
                top[0] = max(0, top[0])
                top[0] += dis[0] + 1
                dis[0] = 0
        def inf():
            dis[0] += 1
            top[0] -= 1
        take()
        take()
        [inf() for i in range(rate[-1])]
        #print(top, dis, rate[-1])
    return max(top[0], 0) + dis[0]


def per_region(l, num_cards, target_set):
    def do_it():
        d = list(range(4)) * 12
        d = random.sample(d, num_cards)
        d = collections.Counter(d)
        if any(d[i] in target_set for i in range(4)):
            return True
        return False
    return sum(1 for x in range(l) if do_it() == True) / l

print ("num_cards", sum(num_cards() for _ in range(1000))/1000)

print ("per_region 0", per_region(10000, 12, [0]))
print ("per_region 1", per_region(10000, 12, [1]))
print ("per_region 01", per_region(10000, 12, [0,1]))
print ("per_region 012", per_region(10000, 12, [0,1,2]))

from matplotlib import pyplot as plt

plt.hist([num_cards() for i in range(1000)])
plt.show()

plt.plot(list(range(10,25)), [per_region(1000, i, [0,1]) for i in range(10,25)])
plt.show()