= np.random.normal(mu, sigma, 1000)
hist, edges = np.histogram(measured, density=True, bins=50)...= np.random.lognormal(mu, sigma, 1000)
hist, edges = np.histogram(measured, density=True, bins=50)...= np.random.gamma(k, theta, 1000)
hist, edges = np.histogram(measured, density=True, bins=50)
x...make_plot("Gamma Distribution (k=7.5, θ=1)", hist, edges, x, pdf, cdf)
# 韦伯分布
lam, k = 1, 1.25
measured...= lam*(-np.log(np.random.uniform(0, 1, 1000)))**(1/k)
hist, edges = np.histogram(measured, density