code: def fix_norm_and_length(vector):
      
      # normalize
      norm_vector = vector / np.linalg.norm(vector)
  
      # pad with zeros
      num_bits = get_bits_needed(len(vector))
      state_vector = np.zeros(2 ** num_bits, dtype=complex)
      for i in range(len(vector)):
          state_vector[i] = norm_vector[i]
  
      return state_vector
docs: Create a normalized and zero padded version of vector.
  
      :param 1darray vector: a vector with at least one nonzero component.
      :return: a vector that is the normalized version of vector,
               padded at the end with the smallest number of 0s necessary
               to make the length of the vector :math:`2^m`
               for some positive integer :math:`m`.
      :rtype: 1darray