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Tokyo.SciPy#3 ガチャとは心の所作


http://partake.in/events/ac0fcc7d-a289-4e2a-bb8e-1965aab8b17b

Python数値計算系モジュールNumpyを用いてガチャコンプに関する正しい確率認識をしましょうというスライドを作りました。
ソースを置いておきます。宜しければご覧下さい。


import numpy as np
import pylab as plt

def gachaMain(weight, trialNum):
    length = len(weight)
    sumWeight = sum(weight)
    return [gachaDo(weight, length, sumWeight) for i in range(trialNum)]

def gachaDo(weight, length, sumWeight):
    cnt = 0
    gachaCompStatus = [0] * length
    while 0 in gachaCompStatus:
        cnt += 1
        rnd = np.random.randint(sumWeight) + 1
        for i in range(length + 1):
            if sum(weight[:i]) < rnd and rnd <= sum(weight[:i + 1]):
                gachaCompStatus[i] += 1
                break
    return cnt

iter = 10000

plt.subplot(221)
gachaWeight = [1, 1, 1, 1, 1, 1]
gachaCompData = gachaMain(gachaWeight, iter)
plt.hist(gachaCompData)
plt.figtext(0.35, 0.85, 'Weight = ' + str(gachaWeight))
plt.figtext(0.35, 0.83, 'mean:' + str(np.mean(gachaCompData)))
plt.figtext(0.35, 0.81, 'std:' + str(np.std(gachaCompData)))

plt.subplot(222)
gachaWeight = [100, 50, 10, 10, 3, 1]
gachaCompData = gachaMain(gachaWeight, iter)
plt.hist(gachaCompData)
plt.figtext(0.78, 0.85, 'Weight = ' + str(gachaWeight))
plt.figtext(0.78, 0.83, 'mean:' + str(np.mean(gachaCompData)))
plt.figtext(0.78, 0.81, 'std:' + str(np.std(gachaCompData)))

plt.subplot(223)
gachaWeight = [5, 5, 3, 3, 2, 1]#sum weight := 19
gachaCompData = gachaMain(gachaWeight, iter)
plt.hist(gachaCompData)
plt.figtext(0.35, 0.4, 'Weight = ' + str(gachaWeight))
plt.figtext(0.35, 0.37, 'mean:' + str(np.mean(gachaCompData)))
plt.figtext(0.35, 0.35, 'std:' + str(np.std(gachaCompData)))

plt.subplot(224)
gachaWeight = [10, 3, 2, 2, 1, 1]#sum weight := 19
gachaCompData = gachaMain(gachaWeight, iter)
plt.hist(gachaCompData)
plt.figtext(0.78, 0.4, 'Weight = ' + str(gachaWeight))
plt.figtext(0.78, 0.37, 'mean:' + str(np.mean(gachaCompData)))
plt.figtext(0.78, 0.35, 'std:' + str(np.std(gachaCompData)))

plt.show()