code: def process_observation(obs, num_modalities, num_observations):
      """
      Helper function for formatting observations
      USAGE NOTES:
      - If `obs` is a 1D numpy array, it must be a one-hot vector, where one entry (the entry of the observation) is 1.0
      and all other entries are 0. This therefore assumes it's a single modality observation. If these conditions are met, then
      this function will return `obs` unchanged. Otherwise, it'll throw an error.
      - If `obs` is an int, it assumes this is a single modality observation, whose observation index is given by the value of `obs`. This function will convert
      it to be a one hot vector.
      - If `obs` is a list, it assumes this is a multiple modality observation, whose len is equal to the number of observation modalities,
      and where each entry `obs[m]` is the index of the observation, for that modality. This function will convert it into an object array
      of one-hot vectors.
      - If `obs` is a tuple, same logic as applies for list (see above).
      - if `obs` is a numpy object array (array of arrays), this function will return `obs` unchanged.
      """
  
      if isinstance(obs, np.ndarray) and not is_obj_array(obs):
          assert (
              num_modalities == 1
          ), "If `obs` is a 1D numpy array, `num_modalities` must be equal to 1"
          assert (
              len(np.where(obs)[0]) == 1
          ), "If `obs` is a 1D numpy array, it must be a one hot vector (e.g. np.array([0.0, 1.0, 0.0, ....]))"
  
      if isinstance(obs, (int, np.integer)):
          obs = onehot(obs, num_observations[0])
  
      if isinstance(obs, tuple) or isinstance(obs, list):
          obs_arr_arr = obj_array(num_modalities)
          for m in range(num_modalities):
              obs_arr_arr[m] = onehot(obs[m], num_observations[m])
          obs = obs_arr_arr
  
      return obs
  
imports: import numpy
  import pandas
  import seaborn
  import matplotlib.pyplot
  import warnings
  import itertools
label_desc: Use image node_id 24 for calling a global function with example usage: process_observation(obs, num_modalities, num_observations) and returns: obs