code: def __init__(self, ax, data, means, index, start_index, link):
      self.data = data
      (self.line,) = ax.plot([], [], "k-")
      self.index = index
      self.ax = ax
      self.ax.set_xlim(0, data.shape[0])
      self.ax.set_ylim(
          np.min(data) - 0.1 * np.std(data),
          np.max(data) + 0.1 * np.std(data),
      )
      self.start_index = start_index
      self.means = means
      self.link = link
  
imports: import sys
  import numpy
  import pandas
  import scipy.stats
  from scipy import optimize
  from ..None import inference
  from ..None import families
  from ..None import output
  from ..None import tsm
  from ..None import data_check
  from ..None import covariances
  from ..None import results
  from ..None import gas
  from .kalman import *
  from .llm import *
label_desc: Use image node_id 1 to create a new BBVINLLMAnimate object from inherited base classes: object with example: obj = BBVINLLMAnimate(ax, data, means, index, start_index, link)