def test_angles(self):
tp = 2 * np.pi
ro_amp_high_factor = 0.1
ts = '20180508_182642'
te = '20180508_183214'
for angle in np.arange(0, 360, 30):
options_dict = {
'verbose': True,
'rotation_angle': angle * np.pi / 180,
'auto_rotation_angle': True,
'fixed_p01': 0,
'fixed_p10': 0,
'nr_bins': 100,
}
label = 'SSRO_%d_%.2f' % (angle, ro_amp_high_factor * 100)
aut = ma.Singleshot_Readout_Analysis(t_start=ts,
t_stop=te,
label=label,
extract_only=True,
do_fitting=True,
options_dict=options_dict)
aut_angle = aut.proc_data_dict['raw_offset'][2]
aut_angle = aut_angle % tp
aut_snr = aut.fit_res['shots_all'].params['SNR'].value
options_dict['auto_rotation_angle'] = False
opt = ma.Singleshot_Readout_Analysis(t_start=ts,
t_stop=te,
label=label,
extract_only=True,
do_fitting=True,
options_dict=options_dict)
opt_angle = opt.proc_data_dict['raw_offset'][2]
opt_angle = opt_angle % tp
opt_snr = opt.fit_res['shots_all'].params['SNR'].value
da = min(abs(aut_angle - opt_angle),
abs(aut_angle - opt_angle + 2 * np.pi),
abs(aut_angle - opt_angle - 2 * np.pi))
# Check if the angle was found within a few degrees
self.assertLess(da * 180 / np.pi, 9)
# Check if the SNRs roughly make sense
self.assertLess(aut_snr, 1.1)
self.assertLess(opt_snr, 1.1)
self.assertGreater(aut_snr, 0.55)
self.assertGreater(opt_snr, 0.55)
def test_SSRO_analysis_basic_1D_wrong_peak_selected(self):
# This fit failed when I made a typo in the peak selection part
t_start = '20171016_171715'
t_stop = t_start
a = ma.Singleshot_Readout_Analysis(t_start=t_start, t_stop=t_stop,
extract_only=True)
self.assertBetween(a.proc_data_dict['threshold_raw'], -3.3, -3.2)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_raw'],
0.944, decimal=2)
self.assertBetween(a.proc_data_dict['threshold_fit'], -3.3, -3.2)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_fit'],
0.944, decimal=2)
self.assertBetween(a.proc_data_dict['threshold_discr'], -3.3, -3.2)
np.testing.assert_almost_equal(a.proc_data_dict['F_discr'],
0.99, decimal=2)
def test_SSRO_analysis_basic_1D(self):
t_start = '20171016_135112'
t_stop = t_start
a = ma.Singleshot_Readout_Analysis(t_start=t_start, t_stop=t_stop,
options_dict={'plot_init': True})
np.testing.assert_almost_equal(a.proc_data_dict['threshold_raw'],
-3.66, decimal=2)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_raw'],
0.922, decimal=3)
self.assertBetween(a.proc_data_dict['threshold_fit'], -3.69, -3.62)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_fit'],
0.920, decimal=2)
np.testing.assert_almost_equal(a.proc_data_dict['threshold_discr'],
-3.64, decimal=1)
np.testing.assert_almost_equal(a.proc_data_dict['F_discr'],
0.996, decimal=2)
def test_SSRO_analysis_basic_1D_misfit(self):
# This dataset failed before I added additional constraints to the
# guess
t_start = '20171016_181021'
t_stop = t_start
a = ma.Singleshot_Readout_Analysis(t_start=t_start, t_stop=t_stop,
extract_only=True)
self.assertBetween(a.proc_data_dict['threshold_raw'], -1, -0.7)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_raw'],
0.949, decimal=2)
self.assertBetween(a.proc_data_dict['threshold_fit'], -1, -.7)
np.testing.assert_almost_equal(a.proc_data_dict['F_assignment_fit'],
0.945, decimal=2)
self.assertBetween(a.proc_data_dict['threshold_discr'], -1, -.7)
np.testing.assert_almost_equal(a.proc_data_dict['F_discr'],
1.000, decimal=2)
self.assertLess(a.proc_data_dict['residual_excitation'], 0.09)
np.testing.assert_almost_equal(
a.proc_data_dict['measurement_induced_relaxation'], 0.1,
decimal=1)
