code: def updateTBATSGMatrix(
      g, gamma_bold, alpha, beta, k_vector, gamma_one_v, gamma_two_v
  ):
      # This function also updates gamma_bold
      adjBeta = 0
      g[0, 0] = alpha
  
      if beta is not None:
          g[1, 0] = beta
          adjBeta = 1
  
      endPos = 0
      for k, gamma_one, gamma_two in zip(
          k_vector, gamma_one_v, gamma_two_v
      ):
          gamma_bold[0, endPos : endPos + k] = gamma_one
          gamma_bold[0, endPos + k : endPos + 2 * k] = gamma_two
          endPos += 2 * k
  
      g[
          (adjBeta + 1) : (adjBeta + gamma_bold.shape[1] + 1), 0
      ] = gamma_bold.ravel()
  
      return g
  
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 11 for calling a global function with example usage: updateTBATSGMatrix(g, gamma_bold, alpha, beta, k_vector, gamma_one_v, gamma_two_v) and returns: g