code: def _initialize_sufficient_statistics(self):
      stats = super()._initialize_sufficient_statistics()
      stats["post"] = np.zeros(self.n_components)
      stats["obs"] = np.zeros((self.n_components, self.n_features))
      return stats
  
imports: import functools
  import inspect
  import warnings
  import numpy
  from scipy import special
  from scipy.stats import multinomial, poisson
  from sklearn.utils import check_random_state
  from .base import BaseHMM, _AbstractHMM
  from .stats import log_multivariate_normal_density
  from .utils import fill_covars, log_normalize
label_desc: Use image node_id 4 for calling the BasePoissonHMM obj's underlying member method code with example usage: obj._initialize_sufficient_statistics() and returns: stats