code: def heston_model_levels(params: "ModelParameters") -> "np.array":
      """Generates price levels corresponding to the Heston model.
  
      The Heston model is the geometric brownian motion model with stochastic
      volatility. This stochastic volatility is given by the cox ingersoll ross
      process. Step one on this method is to construct two correlated GBM
      processes. One is used for the underlying asset prices and the other is used
      for the stochastic volatility levels.
  
      Parameters
      ----------
      params : ModelParameters
          The parameters for the stochastic model.
  
      Returns
      -------
      `np.array`
          The prices for an underlying following a Heston process
  
      Warnings
      --------
          This method is dodgy! Need to debug!
      """
      # Get two correlated brownian motion sequences for the volatility parameter and the underlying asset
      # brownian_motion_market, brownian_motion_vol = get_correlated_paths_simple(param)
      brownian, cir_process = cox_ingersoll_ross_heston(params)
      (
          brownian,
          brownian_motion_market,
      ) = heston_construct_correlated_path(params, brownian)
  
      heston_market_price_levels = [params.all_s0]
      for i in range(1, params.all_time):
          drift = (
              params.gbm_mu
              * heston_market_price_levels[i - 1]
              * params.all_delta
          )
          vol = (
              cir_process[i - 1]
              * heston_market_price_levels[i - 1]
              * brownian_motion_market[i - 1]
          )
          heston_market_price_levels.append(
              heston_market_price_levels[i - 1] + drift + vol
          )
      return np.array(heston_market_price_levels), np.array(cir_process)
  
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 6 for calling a global function with example usage: heston_model_levels(params) and returns: np,  np