def test_QuadraticFit_string(self):
fit1 = dataclasses.QuadraticFit()
fit1.quad_fit_a = 1.618
fit1.quad_fit_b = 1.645
fit1.quad_fit_c = 1.20205
fit2 = dataclasses.QuadraticFit()
fit2.quad_fit_a = 1.618
fit2.quad_fit_b = 1.645
fit2.quad_fit_c = 1.20205
self.assertEqual(fit1.__str__(), fit2.__str__(),
"these should be the same.")
def test_QuadraticFit_equality(self):
fit1 = dataclasses.QuadraticFit()
fit1.quad_fit_a = 1.618
fit1.quad_fit_b = 1.645
fit1.quad_fit_c = 1.20205
fit2 = dataclasses.QuadraticFit()
fit2.quad_fit_a = 1.618
fit2.quad_fit_b = 1.645
fit2.quad_fit_c = 1.20205
self.assertEqual(fit1, fit2, "these should be the same.")
def test_QuadraticFit_equality_default_ctor(self):
o1 = dataclasses.QuadraticFit()
o2 = dataclasses.QuadraticFit()
self.assertEqual(o1, o2, "these should be the same.")
if not is_nan(domcal.combined_spe_charge_distribution.gaus_mean)
]) / len(allI3DOMCalibrations)
combinedSPEChargeDistribution.gaus_width = sum([
domcal.combined_spe_charge_distribution.gaus_width
for domcal in allI3DOMCalibrations
if not is_nan(domcal.combined_spe_charge_distribution.gaus_width)
]) / len(allI3DOMCalibrations)
combinedSPEChargeDistribution.compensation_factor = 1 # no data for spe distribution for these DOMs so use 1 for now
combinedSPEChargeDistribution.slc_gaus_mean = sum([
domcal.combined_spe_charge_distribution.slc_gaus_mean
for domcal in allI3DOMCalibrations
if not is_nan(domcal.combined_spe_charge_distribution.slc_gaus_mean)
]) / len(allI3DOMCalibrations)
newDOMCalib.combined_spe_charge_distribution = combinedSPEChargeDistribution
freqQuadFit1 = dataclasses.QuadraticFit()
freqQuadFit2 = dataclasses.QuadraticFit()
dataFreqQuadFit1 = [domcal.atwd_freq_fit[0] for domcal in allI3DOMCalibrations]
dataFreqQuadFit2 = [domcal.atwd_freq_fit[1] for domcal in allI3DOMCalibrations]
freqQuadFit1.quad_fit_a = sum([
item.quad_fit_a for item in dataFreqQuadFit1 if not is_nan(item.quad_fit_a)
]) / len(dataFreqQuadFit1)
freqQuadFit1.quad_fit_b = sum([
item.quad_fit_b for item in dataFreqQuadFit1 if not is_nan(item.quad_fit_b)
]) / len(dataFreqQuadFit1)
freqQuadFit1.quad_fit_c = sum([
item.quad_fit_c for item in dataFreqQuadFit1 if not is_nan(item.quad_fit_c)
]) / len(dataFreqQuadFit1)
freqQuadFit2.quad_fit_a = sum([
item.quad_fit_a for item in dataFreqQuadFit2 if not is_nan(item.quad_fit_a)
]) / len(dataFreqQuadFit2)