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import numpy as np
steps=2000
draws=np.random.randint(0, 2, size=steps)
# µ±ÔªËØÎª1ʱ£¬direction_stepsΪ1£¬
# µ±ÔªËØÎª0ʱ£¬direction_stepsΪ-1
direction_steps=np.where(draws>0, 1, -1)
# ʹÓÃcumsum()¼ÆËã²½ÊýÀۼƺÍ
distance=direction_steps.cumsum()

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In [141]: # ʹÓÃmax()¼ÆËãÏòǰ×ßµÄ×îÔ¶¾àÀë
          distance.max()
Out[141]: 12
In [142]: # ʹÓÃmin()¼ÆËãÏòºó×ßµÄ×îÔ¶¾àÀë
          distance.min()
Out[142]: -31

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In [143]: # 15Ã×»»Ëã³É²½Êý
          steps=15/0.5
          (np.abs(distance)>=steps).argmax()
Out[143]: 877

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