def _sync(self, obj):
for dbiso in obj.isotopes:
r = dbiso.results[-1]
uv = r.Iso
ee = r.IsoEr
bv = r.Bkgd
be = r.BkgdEr
key = dbiso.Label
n = dbiso.NumCnts
iso = Isotope(name=key, value=uv, error=ee, n=n)
det =dbiso.detector
iso.ic_factor=ufloat(det.ICFactor, det.ICFactorEr)
iso.fit = r.fit.Label.lower()
iso.baseline = Baseline(name=key,
reverse_unpack=True,
dbrecord=dbiso.baseline,
unpack=True,
unpacker=lambda x: x.PeakTimeBlob,
error_type='SEM',
fit='average')
iso.baseline.set_filter_outliers_dict()
iso.blank = Blank(name=key, value=bv, error=be)
self.isotopes[key] = iso
def _sync(self, obj):
for dbiso in obj.isotopes:
r = dbiso.results[-1]
uv = r.Iso
ee = r.IsoEr
bv = r.Bkgd
be = r.BkgdEr
key = dbiso.Label
iso = Isotope(name=key, value=uv, error=ee)
iso.baseline = Baseline(name=key,
reverse_unpack=True,
dbrecord=dbiso.baseline,
unpacker=lambda x: x.PeakTimeBlob,
fit='average_SEM')
iso.blank = Blank(name=key, value=bv, error=be)
self.isotopes[key] = iso
def _sync(self, obj):
arar = obj.araranalyses[-1]
if arar:
self.j = ufloat(arar.JVal, arar.JEr)
self.age = arar.Age
self.age_err = arar.ErrAge
self.age_err_wo_j = arar.ErrAgeWOErInJ
self.rad40_percent = ufloat(arar.PctRad, arar.PctRadEr)
for dbiso in obj.isotopes:
r = dbiso.results[-1]
uv = r.Iso
ee = r.IsoEr
bv = r.Bkgd
be = r.BkgdEr
key = dbiso.Label
n = dbiso.NumCnts
iso = Isotope(name=key, value=uv, error=ee, n=n)
det =dbiso.detector
iso.ic_factor=ufloat(det.ICFactor, det.ICFactorEr)
iso.fit = r.fit.Label.lower()
iso.baseline = Baseline(name=key,
reverse_unpack=True,
dbrecord=dbiso.baseline,
unpack=True,
unpacker=lambda x: x.PeakTimeBlob,
error_type='SEM',
fit='average')
iso.baseline.set_filter_outliers_dict()
iso.blank = Blank(name=key, value=bv, error=be)
self.isotopes[key] = iso
