def fitDataset(
self,
dataset,
model=None,
update=True,
noiter=300,
conv=None,
grad=None,
damper=1.0,
silent=False,
guess=True,
startvalues=None,
changevars=None,
callback=None,
):
"""Calculate the fit for this current dataset, if a model
is given we use that instead of the current one.
update=True means that the dataset fit info will be overwritten"""
# check case of model, as our names are stupidly kept case sensitive
for m in Fitting.fitterClasses:
if model == m or model == m.lower():
model = m
datatofit = self.data[dataset]
if model == None:
currfitdata = self.getFitData(dataset)
if currfitdata.has_key("model"):
model = currfitdata["model"]
else:
model = self.defaultmodel
else:
currfitdata = None
fitresult, X = Fitting.doFit(
ekindata=datatofit,
fitdata=currfitdata,
model=model,
noiter=noiter,
conv=conv,
grad=grad,
LM_damper=damper,
silent=silent,
guess=guess,
startvalues=startvalues,
changevars=changevars,
callback=callback,
)
if fitresult == None:
print "Fitter returned None.."
return
if update == True:
self.__datatabs_fits__[dataset] = fitresult
return fitresult, X
def fitDataset(self,
dataset,
model=None,
update=True,
noiter=300,
conv=None,
grad=None,
damper=1.0,
silent=False,
guess=True,
startvalues=None,
changevars=None,
callback=None):
"""Calculate the fit for this current dataset, if a model
is given we use that instead of the current one.
update=True means that the dataset fit info will be overwritten"""
#check case of model, as our names are stupidly kept case sensitive
for m in Fitting.fitterClasses:
if model == m or model == m.lower():
model = m
datatofit = self.data[dataset]
if model == None:
currfitdata = self.getFitData(dataset)
if currfitdata.has_key('model'):
model = currfitdata['model']
else:
model = self.defaultmodel
else:
currfitdata = None
fitresult, X = Fitting.doFit(ekindata=datatofit,
fitdata=currfitdata,
model=model,
noiter=noiter,
conv=conv,
grad=grad,
LM_damper=damper,
silent=silent,
guess=guess,
startvalues=startvalues,
changevars=changevars,
callback=callback)
if fitresult == None:
print 'Fitter returned None..'
return
if update == True:
self.__datatabs_fits__[dataset] = fitresult
return fitresult, X
