def test_basis_encoding3(self):
""" Input Validation """
x = [1, 0.5]
basis = encode.BasisEncoding()
with self.assertRaises(AssertionError):
basis.circuit(x)
def test_combine1(self):
x = np.array([1, 0, 0, 0, 0, 0, 0, 1])
encoder = encode.BasisEncoding()
model = TreeTensorNetwork()
full_circuit = combine(x, encoder, model)
print(full_circuit)
self.assertTrue(isinstance(full_circuit, qiskit.QuantumCircuit))
def test_basis_encoding1(self):
""" n_qubits """
x = [1, 0, 0, 0, 1, 1, 1]
basis = encode.BasisEncoding()
n_qubits = basis.n_qubits(x)
self.assertEqual(len(x), n_qubits, 'Error in n_qubits')
def test_combine9(self):
""" With measurement argument --- ProbabilityThreshold """
x = np.array([1, 0, 0, 1])
encoder = encode.BasisEncoding()
model = TreeTensorNetwork()
measure = measurement.ProbabilityThreshold(3)
full_circuit = combine(x, encoder, model, measure)
print(full_circuit)
self.assertTrue(isinstance(full_circuit, qiskit.QuantumCircuit))
def test_combine8(self):
""" With measurement argument --- Expecation """
x = np.array([1, 0, 0, 1])
encoder = encode.BasisEncoding()
model = TreeTensorNetwork()
Y_obs = Observable.Y()
measure = measurement.Expectation(0, observable=Y_obs)
full_circuit = combine(x, encoder, model, measure)
print(full_circuit)
self.assertTrue(isinstance(full_circuit, qiskit.QuantumCircuit))
def test_run(self):
X = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1],
[1, 0, 0, 0]])
encoder = encode.BasisEncoding()
model = TreeTensorNetwork()
measure = measurement.Probability(0)
predictions = run(X, encoder, model, measure)
right_length = (len(predictions) == len(X))
right_type = isinstance(predictions, np.ndarray)
self.assertTrue(right_length and right_type)
def test_basis_encoding2(self):
""" Default """
x = [1, 0, 0, 0, 1, 1, 1]
basis = encode.BasisEncoding()
circuit = basis.circuit(x)
counts = get_counts(circuit)
key = None
value = None
for k, v in counts.items():
key = k
expected_dirac_label = '1000111'
self.assertEqual(len(counts.items()), 1)
self.assertEqual(key, expected_dirac_label)