class_docstr: Tests for differentiating a state vector.
docstr: Test state differentiation for a single parameter.
docstr_tok: ["Test","state","differentiation","for","a","single","parameter","."]
code: def test_simple_state_derivative(self):
      """Test state differentiation for a single parameter."""
      x = 1.2
      tape = qml.tape.QuantumScript([qml.RX(x, wires=0)], [qml.state()])
      jac = adjoint_jacobian(tape)
      expected = [-0.5 * np.sin(x / 2), -0.5j * np.cos(x / 2)]
      assert qml.math.allclose(jac, expected)
  
      dy = np.array([0.5, 2.0])
      vjp = adjoint_vjp(tape, dy)
      expected_vjp = dy[0] * expected[0] + dy[1] * expected[1]
      assert qml.math.allclose(expected_vjp, vjp)
  
imports: import pytest
  import pennylane
  from pennylane.devices.qubit import adjoint_jacobian, adjoint_jvp, adjoint_vjp
  from pennylane.tape import QuantumScript
  import pennylane.numpy
label_desc: Use image node_id 1 for calling the TestAdjointJacobianState obj's underlying member method code with example usage: obj.test_simple_state_derivative() without return types