def test_TauParam_string(self): d1 = dataclasses.TauParam() d1.p0 = 0.5772 d1.p1 = 1.645 d1.p2 = 1.202 d1.p3 = 1.0823 d1.p4 = 2.612 d1.p5 = -1.4604 d1.tau_frac = -0.5 d2 = dataclasses.TauParam() d2.p0 = 0.5772 d2.p1 = 1.645 d2.p2 = 1.202 d2.p3 = 1.0823 d2.p4 = 2.612 d2.p5 = -1.4604 d2.tau_frac = -0.5 self.assertEqual(d1.__str__(), d2.__str__(), "these should be the same.")
def test_TauParam_equality_default_ctor(self): o1 = dataclasses.TauParam() o2 = dataclasses.TauParam() self.assertEqual(o1, o2, "these should be the same.")
dom_cal = i3Calibration.dom_cal dom_status = i3DetectorStatus.dom_status trigger_status = i3DetectorStatus.trigger_status allI3DOMCalibrations = dom_cal.values() allI3DOMStatuses = dom_status.values() # setting dom calibration (if no known input value average from data). # some fields had doms that had nan values. Those values were ignored. # one of the doms was used instead of creating a new one because some # attributes were immutable and would have stayed nan if they were # intializaed in a new object newDOMCalib = allI3DOMCalibrations[1000] tauparam = dataclasses.TauParam() tauparam.p0 = sum([ domcal.tau_parameters.p0 for domcal in allI3DOMCalibrations if not is_nan(domcal.tau_parameters.p0) ]) / len(allI3DOMCalibrations) tauparam.p1 = sum([ domcal.tau_parameters.p1 for domcal in allI3DOMCalibrations if not is_nan(domcal.tau_parameters.p1) ]) / len(allI3DOMCalibrations) tauparam.p2 = sum([ domcal.tau_parameters.p2 for domcal in allI3DOMCalibrations if not is_nan(domcal.tau_parameters.p2) ]) / len(allI3DOMCalibrations) tauparam.p3 = sum([ domcal.tau_parameters.p3 for domcal in allI3DOMCalibrations if not is_nan(domcal.tau_parameters.p3)