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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
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#chads gf shopping pattern
#generate step length for 100/200 steps
n_steps= 200
#define steps for x axis
x_steps = np.random.normal(size=n_steps)
#define steps for y axis
y_steps = np.random.normal(size=n_steps)
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#form the entrire trajectory based on those steps we defined
x_traj = np.cumsum(x_steps) #aggregate to the entire trajectory
y_traj = np.cumsum(y_steps)
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#visualize
plt.figure(figsize= (6,6))
plt.plot(x_traj, y_traj, color='magenta', linewidth= 3, linestyle= ':')
plt.grid()
plt.show()
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#model human knowledge acquisition (like stairs/steps)
t= np.linspace(0,6,10)
wisdom = np.floor(t)
plt.step(t, wisdom, where= 'post', color= 'dodgerblue', linewidth=3, linestyle='-.')
plt.grid()
plt.show()
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#wealth
money = np.exp(t)
plt.plot(t,money, color= 'green', linewidth=3, linestyle='--')
plt.grid()
plt.show()
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