def test_to_real(self):
"""Test scaling and conversion to real part."""
processor = DataProcessor("memory", [ToReal(scale=1e-3)])
exp_data = ExperimentData(FakeExperiment())
exp_data.add_data(self.result_lvl1)
new_data = processor(exp_data.data[0])
expected_old = {
"memory": [
[[1103260.0, -11378508.0], [2959012.0, -16488753.0]],
[[442170.0, -19283206.0], [-5279410.0, -15339630.0]],
[[3016514.0, -14548009.0], [-3404756.0, -16743348.0]],
],
"metadata": {
"experiment_type": "fake_test_experiment",
"x_values": 0.0
},
}
expected_new = np.array([[1103.26, 2959.012], [442.17, -5279.41],
[3016.514, -3404.7560]])
self.assertEqual(exp_data.data[0], expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
# Test that we can call with history.
new_data, history = processor.call_with_history(exp_data.data[0])
self.assertEqual(exp_data.data[0], expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
self.assertEqual(history[0][0], "ToReal")
self.assertTrue(np.allclose(history[0][1], expected_new))
def test_to_real(self):
"""Test scaling and conversion to real part."""
processor = DataProcessor("memory", [ToReal(scale=1e-3)])
exp_data = ExperimentData(FakeExperiment())
exp_data.add_data(self.result_lvl1)
# Test to real on a single datum
new_data = processor(exp_data.data(0))
expected_old = {
"memory": [
[[1103260.0, -11378508.0], [2959012.0, -16488753.0]],
[[442170.0, -19283206.0], [-5279410.0, -15339630.0]],
[[3016514.0, -14548009.0], [-3404756.0, -16743348.0]],
],
"metadata": {"experiment_type": "fake_test_experiment"},
"job_id": "job-123",
"meas_level": 1,
"shots": 3,
}
expected_new = np.array([[1103.26, 2959.012], [442.17, -5279.41], [3016.514, -3404.7560]])
self.assertEqual(exp_data.data(0), expected_old)
np.testing.assert_array_almost_equal(
unp.nominal_values(new_data),
expected_new,
)
self.assertTrue(np.isnan(unp.std_devs(new_data)).all())
# Test that we can call with history.
new_data, history = processor.call_with_history(exp_data.data(0))
self.assertEqual(exp_data.data(0), expected_old)
np.testing.assert_array_almost_equal(
unp.nominal_values(new_data),
expected_new,
)
self.assertEqual(history[0][0], "ToReal")
np.testing.assert_array_almost_equal(
unp.nominal_values(history[0][1]),
expected_new,
)
# Test to real on more than one datum
new_data = processor(exp_data.data())
expected_new = np.array(
[
[[1103.26, 2959.012], [442.17, -5279.41], [3016.514, -3404.7560]],
[[5131.962, 4438.87], [3415.985, 2942.458], [5199.964, 4030.843]],
]
)
np.testing.assert_array_almost_equal(
unp.nominal_values(new_data),
expected_new,
)
def test_to_imag(self):
"""Test that we can average the data."""
processor = DataProcessor("memory")
processor.append(ToImag(scale=1e-3))
exp_data = ExperimentData(FakeExperiment())
exp_data.add_data(self.result_lvl1)
new_data, error = processor(exp_data.data(0))
expected_old = {
"memory": [
[[1103260.0, -11378508.0], [2959012.0, -16488753.0]],
[[442170.0, -19283206.0], [-5279410.0, -15339630.0]],
[[3016514.0, -14548009.0], [-3404756.0, -16743348.0]],
],
"metadata": {
"experiment_type": "fake_test_experiment"
},
"job_id":
"job-123",
"meas_level":
1,
"shots":
3,
}
expected_new = np.array([
[-11378.508, -16488.753],
[-19283.206000000002, -15339.630000000001],
[-14548.009, -16743.348],
])
self.assertEqual(exp_data.data(0), expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
self.assertIsNone(error)
# Test that we can call with history.
new_data, error, history = processor.call_with_history(
exp_data.data(0))
self.assertEqual(exp_data.data(0), expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
self.assertEqual(history[0][0], "ToImag")
self.assertTrue(np.allclose(history[0][1], expected_new))
# Test to imaginary on more than one datum
new_data, error = processor(exp_data.data())
expected_new = np.array([
[[-11378.508, -16488.753], [-19283.206, -15339.630],
[-14548.009, -16743.348]],
[[-16630.257, -13752.518], [-16031.913, -15840.465],
[-14955.998, -14538.923]],
])
self.assertTrue(np.allclose(new_data, expected_new))
def test_empty_processor(self):
"""Check that a DataProcessor without steps does nothing."""
data_processor = DataProcessor("counts")
datum = data_processor(self.exp_data_lvl2.data(0))
self.assertEqual(datum, {"00": 4, "10": 6})
datum, history = data_processor.call_with_history(self.exp_data_lvl2.data(0))
self.assertEqual(datum, {"00": 4, "10": 6})
self.assertEqual(history, [])
def test_to_imag(self):
"""Test that we can average the data."""
processor = DataProcessor("memory")
processor.append(ToImag(scale=1e-3))
exp_data = ExperimentData(FakeExperiment())
exp_data.add_data(self.result_lvl1)
new_data = processor(exp_data.data[0])
expected_old = {
"memory": [
[[1103260.0, -11378508.0], [2959012.0, -16488753.0]],
[[442170.0, -19283206.0], [-5279410.0, -15339630.0]],
[[3016514.0, -14548009.0], [-3404756.0, -16743348.0]],
],
"metadata": {
"experiment_type": "fake_test_experiment",
"x_values": 0.0
},
}
expected_new = np.array([
[-11378.508, -16488.753],
[-19283.206000000002, -15339.630000000001],
[-14548.009, -16743.348],
])
self.assertEqual(exp_data.data[0], expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
# Test that we can call with history.
new_data, history = processor.call_with_history(exp_data.data[0])
self.assertEqual(exp_data.data[0], expected_old)
self.assertTrue(np.allclose(new_data, expected_new))
self.assertEqual(history[0][0], "ToImag")
self.assertTrue(np.allclose(history[0][1], expected_new))