code: def expected_entropy_grad_ising_xx(param):
      """
      Return the analytical gradient entropy for the IsingXX.
      """
      eig_1 = (
          1
          + np.sqrt(
              1 - 4 * np.cos(param / 2) ** 2 * np.sin(param / 2) ** 2
          )
      ) / 2
      eig_2 = (
          1
          - np.sqrt(
              1 - 4 * np.cos(param / 2) ** 2 * np.sin(param / 2) ** 2
          )
      ) / 2
      eigs = [eig_1, eig_2]
      eigs = np.maximum(eigs, 1e-08)
  
      return -(
          (np.log(eigs[0]) + 1)
          * (
              np.sin(param / 2) ** 3 * np.cos(param / 2)
              - np.sin(param / 2) * np.cos(param / 2) ** 3
          )
          / np.sqrt(
              1 - 4 * np.cos(param / 2) ** 2 * np.sin(param / 2) ** 2
          )
      ) - (
          (np.log(eigs[1]) + 1)
          * (
              np.sin(param / 2)
              * np.cos(param / 2)
              * (np.cos(param / 2) ** 2 - np.sin(param / 2) ** 2)
          )
          / np.sqrt(
              1 - 4 * np.cos(param / 2) ** 2 * np.sin(param / 2) ** 2
          )
      )
  
imports: import numpy
  import pytest
  import pennylane
  from pennylane.workflow import INTERFACE_MAP
  from pennylane.measurements import Shots
  from pennylane.measurements.vn_entropy import VnEntropyMP
label_desc: Use image node_id 2 for calling a global function with example usage: expected_entropy_grad_ising_xx(param) and returns: unknown