code: def geometric_brownian_motion_jump_diffusion_levels(
      params: "ModelParameters",
  ) -> "np.array":
      """Converts a sequence of gbm jmp returns into a price sequence which
      evolves according to a geometric brownian motion but can contain jumps
      at any point in time.
  
      Parameters
      ----------
      params : ModelParameters
          The parameters for the stochastic model.
  
      Returns
      -------
      `np.array`
          The price levels.
      """
      return convert_to_prices(
          params,
          geometric_brownian_motion_jump_diffusion_log_returns(params),
      )
  
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 3 for calling a global function with example usage: geometric_brownian_motion_jump_diffusion_levels(params) and returns: convert_to_prices