class_docstr: Tests the _generalized_pauli_decompose via pauli_decompose function
docstr: Tests that the matrix decomposes into a linear combination of tensors,
  the identity matrix, and Pauli matrices.
docstr_tok: ["Tests","that","the","matrix","decomposes","into","a","linear","combination","of","tensors",",","the","identity","matrix",",","and","Pauli","matrices","."]
code: def test_observable_types_general(self, matrix, hide_identity):
      """Tests that the matrix decomposes into a linear combination of tensors,
      the identity matrix, and Pauli matrices."""
      shape = matrix.shape
      num_qubits = int(np.ceil(np.log2(max(shape))))
      allowed_obs = (Tensor, Identity, PauliX, PauliY, PauliZ)
  
      decomposed_coeff, decomposed_obs = qml.pauli_decompose(
          matrix, hide_identity, check_hermitian=False
      ).terms()
  
      assert all((isinstance(o, allowed_obs) for o in decomposed_obs))
  
      linear_comb = sum(
          [
              decomposed_coeff[i]
              * qml.matrix(o, wire_order=range(num_qubits))
              for i, o in enumerate(decomposed_obs)
          ]
      )
      assert np.allclose(matrix, linear_comb[: shape[0], : shape[1]])
  
      if not hide_identity:
          tensors = filter(
              lambda obs: isinstance(obs, Tensor), decomposed_obs
          )
          assert all(
              len(tensor.obs) == num_qubits for tensor in tensors
          )
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.operation import Tensor
  from pennylane.ops import Identity, PauliX, PauliY, PauliZ
  from pennylane.pauli import pauli_sentence, PauliWord, PauliSentence
  from pennylane.pauli.conversion import _generalized_pauli_decompose
label_desc: Use image node_id 9 for calling the TestPhasedDecomposition obj's underlying member method code with example usage: obj.test_observable_types_general(matrix, hide_identity) without return types