def get_normalized_model(self):
"""
For jacobian models
Fit for a flux then run the ydiff on it
"""
from gmix_image.gmix_fit import GMixFitMultiPSFFlux
from . import _render
if self.jacobian is None:
raise ValueError("only works for jacobian")
imlist = [self.image0]
wtlist = [self.image0 * 0 + self.ivar]
jacoblist = [self.jacobian]
gmix_list = [self.get_gmix()]
gm = GMixFitMultiPSFFlux(imlist, wtlist, jacoblist, gmix_list)
res = gm.get_result()
gmix = self.get_gmix()
gmix.set_psum(res["F"])
model = gmix_image.gmix2image(gmix, self.image0.shape, jacob=self.jacobian)
return model
def _fit_psf_flux(self, dindex, sdata):
if self.debug:
print >>stderr,'\tfitting psf flux'
cen_prior=None
if self.use_cenprior:
cen_prior=CenPrior([0.0]*2, [self.cen_width]*2)
gm=GMixFitMultiPSFFlux(sdata['imlist'],
sdata['wtlist'],
sdata['jacob_list'],
sdata['psf_gmix_list'],
cen_prior=cen_prior,
lm_max_try=self.obj_ntry)
res=gm.get_result()
self.data['psf_flags'][dindex] = res['flags']
self.data['psf_iter'][dindex] = res['numiter']
self.data['psf_tries'][dindex] = res['ntry']
if res['flags']==0:
self.data['psf_pars'][dindex,:]=res['pars']
self.data['psf_pars_cov'][dindex,:,:] = res['pcov']
flux=res['pars'][2]
flux_err=sqrt(res['pcov'][2,2])
self.data['psf_flux'][dindex] = flux
self.data['psf_flux_err'][dindex] = flux_err
self.data['psf_flux_s2n'][dindex] = flux/flux_err
print >>stderr,' psf_flux: %g +/- %g' % (flux,flux_err)
n=get_model_names('psf')
for sn in _stat_names:
self.data[n[sn]][dindex] = res[sn]
if self.debug:
fmt='\t\t%s: %g +/- %g'
print >>stderr,fmt % ('psf_flux',flux,flux_err)
