code: def tbats_forecast(
      mod, h
  ):  # this function is the same as bats_forecast
      fcst = np.zeros(h)
      xx = np.zeros((h, mod["x"].shape[1]))
      w = mod["w_transpose"][0]
  
      fcst[0] = np.dot(w, mod["x"][-1])
      xx[0] = np.dot(mod["F"], mod["x"][-1])
  
      if h > 1:
          for t in range(1, h):
              xx[t] = np.dot(mod["F"], xx[t - 1])
              fcst[t] = np.dot(w, xx[t - 1])
  
      res = {"mean": fcst}
  
      return res
  
imports: import warnings
  from functools import partial
  import numpy
  import pandas
  import scipy.linalg
  import statsmodels.api
  from numba import njit
  from numpy.polynomial.polynomial import Polynomial
  from scipy.special import inv_boxcox
  from scipy.stats import boxcox
  from scipy.optimize import minimize
  from statsmodels.tsa.stattools import adfuller
  from .arima import auto_arima_f
  from .utils import NOGIL, CACHE
label_desc: Use image node_id 17 for calling a global function with example usage: tbats_forecast(mod, h) and returns: res