code: def get_from_one_beal(cls, N, length, rs=None):
      # Just fit the first of the beal models
      model = cls.get_beal_models()[0]
      sequences = []
      lengths = []
      for i in range(N):
          sequences.append(
              model.sample(length, random_state=check_random_state(rs))[
                  0
              ]
          )
          lengths.append(len(sequences[-1]))
      sequences = np.concatenate(sequences)
      return sequences, lengths
  
file_path: hmmlearn/lib/hmmlearn/tests/test_variational_categorical.py
imports: import numpy
  import pytest
  from sklearn.utils import check_random_state
  from hmmlearn import hmm, vhmm
  from .None import assert_log_likelihood_increasing, compare_variational_and_em_models, vi_uniform_startprob_and_transmat
label_desc: Use image node_id 3 for calling the TestVariationalCategorical obj's underlying member method code with example usage: obj.get_from_one_beal(cls, N, length, rs) and returns: sequences,  lengths