# numpy and matplotlib imported, seed set # Simulate random walk 500 times all_walks = [] for i in range(500) : random_walk = [0] for x in range(100) : step = random_walk[-1] dice = np.random.randint(1,7) if dice <= 2: step = max(0, step - 1) elif dice <= 5: step = step + 1 else: step = step + np.random.randint(1,7) if np.random.rand() <= 0.001 : step = 0 random_walk.append(step) all_walks.append(random_walk) # Create and plot np_aw_t np_aw_t = np.transpose(np.array(all_walks)) # Select last row from np_aw_t: ends ends = np_aw_t[-1, :] # Plot histogram of ends, display plot plt.hist(ends) plt.show()
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