去年看了徐高在国发院的演讲稿《怎样用好最重要的几年？》，很受启发。
我对演讲中的随机游走中趋势项做了计算机的模拟，并参考了MIT的6.0002，源码如下：
from random import choice
import matplotlib.pyplot as plt
class RandomWalk():
"""A class to generate random walks."""
def __init__(self, num_points=5000):
"""Initialize attributes of a walk."""
self.num_points = num_points
# All walks start at (0, 0).
self.x_values = [0]
self.y_values = [0]
def fill_walk(self):
"""Calculate all the points in the walk."""
# Keep taking steps until the walk reaches the desired length.
while len(self.x_values) < self.num_points:
# Decide which direction to go, and how far to go in that direction.
x_direction = choice([1, -1])
x_distance = choice([0, 1])
x_step = x_direction * x_distance
y_direction = choice([1, -1])
y_distance = choice([0, 1])
y_step = y_direction * y_distance
# Reject moves that go nowhere.
if x_step == 0 and y_step == 0:
continue
# Calculate the next x and y values.
next_x = self.x_values[-1] + x_step + 0.01
next_y = self.y_values[-1] + y_step + 0.01
self.x_values.append(next_x)
self.y_values.append(next_y)
rw = RandomWalk(100000)
rw.fill_walk()
plt.style.use("dark_background")
fig, ax = plt.subplots(figsize=(15, 9), dpi = 128)
point_numbers = range(rw.num_points)
ax.scatter(rw.x_values, rw.y_values,c = point_numbers,cmap = plt.cm.Blues,
edgecolors = 'none', s = 5)
ax.scatter(0, 0, c = 'green', edgecolors = 'none', s = 100)
ax.scatter(rw.x_values[-1], rw.x_values[-1], c = 'red', edgecolors = 'none',
s = 100)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
plt.show()
