class_docstr: differential equation:
  
  :math::
  dx_t = f(t,x)dt + \sigma(t,x)dW_t
  
  integral:
  
  :math::
  x_T = x_0 + \int_{0}^{T}f(t,S)dt + \int_0^T  \sigma(t,S)dW_t
  
  TODO: check definition, affine, what about jump diffusion?
class_docstr_tok: ["differential","equation",":",":","math",":",":","dx_t","=","f","(","t",",","x",")","dt","+","\\sigma","(","t",",","x",")","dW_t","integral",":",":","math",":",":","x_T","=","x_0","+","\\int_","{","0","}","^","{","T","}","f","(","t",",","S",")","dt","+","\\int_0^T","\\sigma","(","t",",","S",")","dW_t","TODO",":","check","definition",",","affine",",","what","about","jump","diffusion","?"]
code: def __init__(self):
      pass
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 1 to create a new AffineDiffusion object from inherited base classes: Diffusion with example: obj = AffineDiffusion()