ou.py

import numpy as np


class OUProcess(object):
  """Ornstein-Uhlenbeck process"""


  def __init__(self, x_size, mu=0, theta=0.15, sigma=0.3):
    self.x = np.ones(x_size) * mu
    self.x_size = x_size
    self.mu = mu
    self.theta = theta
    self.sigma = sigma


  def noise(self):
    dx = self.theta * (self.mu - self.x) + self.sigma * np.random.randn(self.x_size)
    self.x = self.x + dx
    return self.x