def test_detector_response(xes: fd.ERSource):
r = xes.detector_response('photon', xes.data_tensor[0],
xes.ptensor_from_kwargs()).numpy()
assert r.shape == (n_events, xes.dimsizes['photon_detected'])
# r is p(S1 | detected quanta) as a function of detected quanta
# so the sum over r isn't meaningful (as long as we're frequentists)
# Maximum likelihood est. of detected quanta is correct
max_is = r.argmax(axis=1)
domain = xes.domain('photon_detected').numpy()
found_mle = np_lookup_axis1(domain, max_is)
np.testing.assert_array_less(
np.abs(xes.data['photon_detected_mle'] - found_mle), 0.5)
def test_domain_detected(xes: fd.ERSource):
dd = xes.domain('photon_detected').numpy()
np.testing.assert_equal(dd.min(axis=1),
np.floor(xes.data['photon_detected_min']).values)