code: def qwc_complement_adj_matrix(binary_observables):
      """Obtains the adjacency matrix for the complementary graph of the qubit-wise commutativity
      graph for a given set of observables in the binary representation.
  
      The qubit-wise commutativity graph for a set of Pauli words has a vertex for each Pauli word,
      and two nodes are connected if and only if the corresponding Pauli words are qubit-wise
      commuting.
  
      Args:
          binary_observables (array[array[int]]): a matrix whose rows are the Pauli words in the
              binary vector representation
  
      Returns:
          array[array[int]]: the adjacency matrix for the complement of the qubit-wise commutativity graph
  
      Raises:
          ValueError: if input binary observables contain components which are not strictly binary
  
      **Example**
  
      >>> binary_observables
      array([[1., 0., 1., 0., 0., 1.],
             [0., 1., 1., 1., 0., 1.],
             [0., 0., 0., 1., 0., 0.]])
  
      >>> qwc_complement_adj_matrix(binary_observables)
      array([[0., 1., 1.],
             [1., 0., 0.],
             [1., 0., 0.]])
      """
  
      if isinstance(binary_observables, (list, tuple)):
          binary_observables = np.asarray(binary_observables)
  
      if not np.array_equal(
          binary_observables, binary_observables.astype(bool)
      ):
          raise ValueError(
              f"Expected a binary array, instead got {binary_observables}"
          )
  
      m_terms = np.shape(binary_observables)[0]
      adj = np.zeros((m_terms, m_terms))
  
      for i in range(m_terms):
          for j in range(i + 1, m_terms):
              adj[i, j] = int(
                  not is_qwc(
                      binary_observables[i], binary_observables[j]
                  )
              )
              adj[j, i] = adj[i, j]
  
      return adj
  
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 18 for calling a global function with example usage: qwc_complement_adj_matrix(binary_observables) and returns: adj