code: def observables_to_binary_matrix(
      observables, n_qubits=None, wire_map=None
  ):
      """Converts a list of Pauli words to the binary vector representation and yields a row matrix
      of the binary vectors.
  
      The dimension of the binary vectors will be implied from the highest wire being acted on
      non-trivially by the Pauli words in observables.
  
      Args:
          observables (list[Union[Identity, PauliX, PauliY, PauliZ, Tensor]]): the list of Pauli
              words
          n_qubits (int): number of qubits to specify dimension of binary vector representation
          wire_map (dict): dictionary containing all wire labels used in the Pauli words as keys, and
              unique integer labels as their values
  
  
      Returns:
          array[array[int]]: a matrix whose rows are Pauli words in binary vector representation
  
      **Example**
  
      >>> observables_to_binary_matrix([PauliX(0) @ PauliY(2), PauliZ(0) @ PauliZ(1) @ PauliZ(2)])
      array([[1., 1., 0., 0., 1., 0.],
             [0., 0., 0., 1., 1., 1.]])
      """
  
      m_cols = len(observables)
  
      if wire_map is None:
          all_wires = Wires.all_wires(
              [pauli_word.wires for pauli_word in observables]
          )
          wire_map = {i: c for c, i in enumerate(all_wires)}
  
      n_qubits_min = max(wire_map.values()) + 1
      if n_qubits is None:
          n_qubits = n_qubits_min
      elif n_qubits < n_qubits_min:
          raise ValueError(
              f"n_qubits must support the highest mapped wire index {n_qubits_min},"
              f" instead got n_qubits={n_qubits}."
          )
  
      binary_mat = np.zeros((m_cols, 2 * n_qubits))
  
      for i in range(m_cols):
          binary_mat[i, :] = pauli_to_binary(
              observables[i], n_qubits=n_qubits, wire_map=wire_map
          )
  
      return binary_mat
  
imports: from functools import lru_cache, reduce, singledispatch
  from itertools import product
  from typing import List, Union
  from warnings import warn
  import numpy
  import pennylane
  from pennylane.operation import Tensor
  from pennylane.ops import Hamiltonian, Identity, PauliX, PauliY, PauliZ, Prod, SProd
  from pennylane.tape import OperationRecorder
  from pennylane.wires import Wires
label_desc: Use image node_id 17 for calling a global function with example usage: observables_to_binary_matrix(observables, n_qubits, wire_map) and returns: binary_mat