fix tests

src/qibo/hamiltonians/hamiltonians.py

@@ -116,6 +116,7 @@ def exp(self, a):
 
     def expectation(self, state, normalize=False):
         if isinstance(state, self.backend.tensor_types):
+            state = self.backend.cast(state)
             shape = tuple(state.shape)
             if len(shape) == 1:  # state vector
                 return self.backend.calculate_expectation_state(self, state, normalize)
@@ -175,6 +176,7 @@ def energy_fluctuation(self, state):
         Return:
             Energy fluctuation value (float).
         """
+        state = self.backend.cast(state)
         energy = self.expectation(state)
         h = self.matrix
         h2 = Hamiltonian(nqubits=self.nqubits, matrix=h @ h, backend=self.backend)

tests/test_hamiltonians.py

@@ -449,7 +449,7 @@ def test_hamiltonian_energy_fluctuation(backend):
     ham = hamiltonians.XXZ(nqubits=2, backend=backend)
     # take ground state and zero state
     ground_state = ham.ground_state()
-    zero_state = np.ones(2**2) / np.sqrt(2**2)
+    zero_state = backend.np.ones(2**2) / np.sqrt(2**2)
     # collect energy fluctuations
     gs_energy_fluctuation = ham.energy_fluctuation(ground_state)
     zs_energy_fluctuation = ham.energy_fluctuation(zero_state)

tests/test_hamiltonians_symbolic.py

@@ -317,6 +317,7 @@ def test_symbolic_hamiltonian_state_expectation_different_nqubits(
 
 def test_hamiltonian_expectation_from_samples(backend):
     """Test Hamiltonian expectation value calculation."""
+    backend.set_seed(0)
     obs0 = 2 * Z(0) * Z(1) + Z(0) * Z(2)
     obs1 = 2 * Z(0) * Z(1) + Z(0) * Z(2) * I(3)
     h0 = hamiltonians.SymbolicHamiltonian(obs0, backend=backend)

tests/test_measurements_probabilistic.py

@@ -146,8 +146,9 @@ def test_measurementresult_apply_bitflips(backend, i, p0, p1):
 
     c = models.Circuit(3)
     c.add(gates.M(*range(3)))
-    state = backend.np.zeros(8)
+    state = np.zeros(8)
     state[0] = 1.0
+    state = backend.cast(state)
     result = CircuitResult(state, c.measurements, backend)
     result._samples = backend.cast(np.zeros((10, 3)), dtype="int32")
     backend.set_seed(123)