code: def geometric_brownian_motion_jump_diffusion_log_returns(
      params: "ModelParameters",
  ) -> "np.array":
      """Constructs combines a geometric brownian motion process (log returns)
      with a jump diffusion process (log returns) to produce a sequence of gbm
      jump returns.
  
      Parameters
      ----------
      params : ModelParameters
          The parameters for the stochastic model.
  
      Returns
      -------
      `np.array`
          A GBM process with jumps in it
      """
      jump_diffusion = jump_diffusion_process(params)
      geometric_brownian_motion = geometric_brownian_motion_log_returns(
          params
      )
      return np.add(jump_diffusion, geometric_brownian_motion)
  
file_path: tensortrade/tensortrade/stochastic/processes/heston.py
imports: import random
  import numpy
  import pandas
  import scipy
  from tensortrade.stochastic.processes.gbm import geometric_brownian_motion_log_returns
  from tensortrade.stochastic.utils import ModelParameters, generate, convert_to_prices
label_desc: Use image node_id 2 for calling a global function with example usage: geometric_brownian_motion_jump_diffusion_log_returns(params) and returns: np