code: def _ps_to_sparse_index(pauli_words, wires):
      """Represent the Pauli words sparse structure in a matrix of shape n_words x n_wires."""
      indices = np.zeros((len(pauli_words), len(wires)))
      for i, pw in enumerate(pauli_words):
          if not pw.wires:
              continue
          wire_indices = np.array(wires.indices(pw.wires))
          indices[i, wire_indices] = [
              pauli_to_sparse_int[pw[w]] for w in pw.wires
          ]
      return indices
  
imports: import warnings
  from copy import copy
  from functools import reduce, lru_cache
  from typing import Iterable
  import numpy
  from scipy import sparse
  import pennylane
  from pennylane import math
  from pennylane.typing import TensorLike
  from pennylane.wires import Wires
  from pennylane.operation import Tensor
  from pennylane.ops import Hamiltonian, Identity, PauliX, PauliY, PauliZ, prod, s_prod
label_desc: Use image node_id 3 for calling a global function with example usage: _ps_to_sparse_index(pauli_words, wires) and returns: indices