Numpy Normal Distribution
>>> mu, sigma = 0, 0.1 # mean and standard deviation
>>> s = np.random.normal(mu, sigma, 1000)
Difficult Dunlin
>>> mu, sigma = 0, 0.1 # mean and standard deviation
>>> s = np.random.normal(mu, sigma, 1000)
def normalize(v):
norm = np.linalg.norm(v)
if norm == 0:
return v
return v / norm