class_docstr: :math::
  dx_t &= \mu dt + \sigma dW_t
class_docstr_tok: [":","math",":",":","dx_t","&","=","\\mu","dt","+","\\sigma","dW_t"]
code: def __init__(self, xzero, mu, sigma):
      self.xzero = xzero
      self.mu = mu
      self.sigma = sigma
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 1 to create a new ArithmeticBrownian object from inherited base classes: AffineDiffusion with example: obj = ArithmeticBrownian(xzero, mu, sigma)