code: def create_A_matrix_stub(model_labels):
      num_obs, _, num_states, _ = get_model_dimensions_from_labels(
          model_labels
      )
  
      obs_labels, state_labels = (
          model_labels["observations"],
          model_labels["states"],
      )
  
      state_combinations = pd.MultiIndex.from_product(
          list(state_labels.values()), names=list(state_labels.keys())
      )
      num_state_combos = np.prod(num_states)
      # num_rows = (np.array(num_obs) * num_state_combos).sum()
      num_rows = sum(num_obs)
  
      cell_values = np.zeros((num_rows, len(state_combinations)))
  
      obs_combinations = []
      for modality in obs_labels.keys():
          levels_to_combine = [[modality]] + [obs_labels[modality]]
          # obs_combinations += num_state_combos * list(itertools.product(*levels_to_combine))
          obs_combinations += list(
              itertools.product(*levels_to_combine)
          )
  
      obs_combinations = pd.MultiIndex.from_tuples(
          obs_combinations, names=["Modality", "Level"]
      )
  
      A_matrix = pd.DataFrame(
          cell_values,
          index=obs_combinations,
          columns=state_combinations,
      )
  
      return A_matrix
  
imports: import numpy
  import pandas
  import seaborn
  import matplotlib.pyplot
  import warnings
  import itertools
label_desc: Use image node_id 29 for calling a global function with example usage: create_A_matrix_stub(model_labels) and returns: A_matrix