def _run_em(self):
# only run admom if not sent
if self.ares is None:
self._run_admom()
if self.ares is None:
self.result = {"flags": GMIXEM_ERROR_ADMOM_FAILED}
return
im, sky, guess0 = self._do_prep()
ntry = self.maxtry_em
for i in xrange(ntry):
guess = self._perturb_gmix(guess0)
gm = GMixEM(im, guess, sky=sky, maxiter=self.maxiter, tol=self.tol, cocenter=self.cocenter)
flags = gm.get_flags()
if flags == 0:
break
if flags != 0:
print >> stderr, "em flags after", ntry, "tries:"
gmix_image.printflags("em", flags)
self._fitter = gm
gmix = gm.get_gmix()
self.result = {
"gmix": gmix,
"flags": gm.get_flags(),
"numiter": gm.get_numiter(),
"fdiff": gm.get_fdiff(),
"ntry": i + 1,
}
if flags == 0:
stats = self.get_stats()
self.result.update(stats)
def process(self):
c=self['filternum']
self.set_admom()
ntrials = len(self['psf']['trials'])
chi2arr=zeros(ntrials) + 1.e9
gmlist=[]
im=self.psf.copy()
im_min = im.min()
if im_min <= 0:
im -= im_min
sky=0.001*im.max()
im += sky
else:
sky = im_min
for i,trial in enumerate(self['psf']['trials']):
#prior,width = self.get_prior_turb(trial)
guess = self.get_em_guess(trial)
if self['verbose']:
wlog('guess')
gmix_print(guess,title='guess:')
gm = gmix_image.GMixEM(im,guess,
sky=sky,
maxiter=4000,
tol=1.e-6,
coellip=False,
cocenter=False) # true required for deconv
chi2arr[i] = gm.get_fdiff()
if self['verbose']:
gmix_print(gm.pars,title='pars:')
wlog("chi2/pdeg:",chi2arr[i])
gmlist.append(gm)
w=chi2arr.argmin()
self.gm = gmlist[w]
flags = gm.get_flags()
if flags != 0:
printflags('em',flags)
raise ValueError("error")
if self['verbose']:
gmix_print(gm.pars,title='popt:')
wlog("\n")
wlog("numiter gmix:",gm.numiter)
def process(self):
c=self['filternum']
self.set_admom()
ntrials = len(self['psf']['trials'])
chi2arr=zeros(ntrials) + 1.e9
gmlist=[]
for i,trial in enumerate(self['psf']['trials']):
ngauss=trial['ngauss']
if ngauss==3:
prior,width = self.get_prior_turb(trial)
elif ngauss==2:
prior,width = self.get_prior_2generic(trial)
else:
raise ValueError("only have ngauss in [2,3] now")
#prior,width = self.get_prior_2psfield(trial)
#prior,width = self.get_prior_test(trial)
if self['verbose']:
print_pars(prior,front="guess: ")
gm = gmix_image.GMixFitCoellip(self.psf, self['skysig'],
prior,width, verbose=False)
#gm = gmix_image.gmix_fit.GMixFitCoellipNoPrior(self.psf, self['skysig'],
# prior, verbose=False)
if gm.flags != 0:
gmix_image.printflags("flags:",gm.flags)
raise ValueError("error")
chi2arr[i] = gm.get_chi2per(gm.popt)
if self['verbose']:
print_pars(gm.popt,front="pars: ")
print_pars(gm.perr,front="perr: ")
wlog("chi2/pdeg:",chi2arr[i])
gmlist.append(gm)
w=chi2arr.argmin()
self.gm = gmlist[w]
wlog('w:',w)
if self['verbose']:
print_pars(chi2arr,front='chi2/deg: ')
wlog("\n")
print_pars(gm.popt,front='popt: ')
print_pars(gm.perr,front='perr: ')
#wlog("s2n:",s2n)
wlog("numiter gmix:",gm.numiter)
ngauss=(len(gm.popt)-4)/2
def _run_em(self):
guess0 = self._get_guess()
ntry = self.maxtry
for i in xrange(ntry):
guess = self._perturb_dlist(guess0)
gm = GMixEM(
self.image,
guess,
jacobian=self.jacobian,
sky=self.sky,
maxiter=self.maxiter,
tol=self.tol,
cocenter=self.cocenter,
)
flags = gm.get_flags()
if flags == 0:
break
if flags != 0:
print >> stderr, "em flags after", ntry, "tries:"
gmix_image.printflags("em", flags)
self._fitter = gm
gmix = gm.get_gmix()
self.result = {
"gmix": gmix,
"pars": gmix.get_pars(),
"flags": flags,
"numiter": gm.get_numiter(),
"fdiff": gm.get_fdiff(),
"ntry": i + 1,
}
if flags == 0:
stats = self.get_stats()
self.result.update(stats)
def test_fit_dev_e1e2(ngauss=4, s2n=1.e5):
import biggles
import admom
import fimage
numpy.random.seed(35)
ptype='e1e2'
e = 0.2
theta = 23.7
e1,e2 = etheta2e1e2(e,theta)
print >>stderr,"e:",e,"e1:",e1,"e2:",e2
nsig=15
#nsig=7
npars=2*ngauss+4
nsigma_vals=20
f='test-opt-dev-bysigma'
f += '-s2n%d' % s2n
f += '.rec'
pngf=f.replace('.rec','.png')
if not os.path.exists(f):
data=numpy.zeros(nsigma_vals,dtype=[('sigma','f8'),('pars','f8',npars)])
#sigvals = numpy.linspace(1.5,5.0,nsigma_vals)
sigvals = numpy.linspace(3.,5.0,nsigma_vals)
#sigvals=array([3.0])
for isigma,sigma in enumerate(sigvals):
print '-'*70
print 'sigma:',sigma
T = 2*sigma**2
cov = ellip2mom(T, e=e, theta=theta)
dim = int(2*nsig*sigma)
if (dim % 2) == 0:
dim += 1
dims=array([dim,dim])
cen=(dims-1)/2.
im0 = model_image('dev',dims,cen,cov,nsub=16)
im,skysig = fimage.add_noise(im0, s2n, check=True)
dim = int(2*nsig*sigma)
if (dim % 2) == 0:
dim += 1
dims=array([dim,dim])
cen=(dims-1)/2.
ares = admom.admom(im0,cen[0],cen[1],guess=T/2,nsub=16)
Tadmom=ares['Irr'] + ares['Icc']
if ngauss == 4:
Tmax = Tadmom*100
# 0.02620127 0.09348825 0.23987656 0.63958437
p0 = array([cen[0],
cen[1],
e1,
e2,
0.026,
0.093,
0.24,
0.64,
Tmax,
Tmax*0.18,
Tmax*0.04,
Tmax*0.0027])
else:
p0 = array([cen[0],
cen[1],
e1,
e2,
1./ngauss,
1./ngauss,
1./ngauss,
Tadmom*4.9,
Tadmom*0.82,
Tadmom*0.18])
print_pars(p0, front='guess: ')
verbose=False
gf=gmix_fit.GMixFitCoellip(im, p0,
ptype=ptype,
verbose=verbose)
chi2per = gf.get_chi2per(gf.popt,skysig)
print 'numiter:',gf.numiter
print_pars(gf.popt, front='popt: ')
if gf.perr is not None:
print_pars(gf.perr, front='perr: ')
print 'chi2/deg:',chi2per
if gf.flags != 0:
gmix_image.printflags('fit',gf.flags)
raise RuntimeError("failed")
data['sigma'][isigma] = sigma
data['pars'][isigma,:] = gf.popt
tvals = gf.popt[4+ngauss:]
tmax=tvals.max()
print 't ratios:',tvals/tmax
print 'p values:',gf.popt[4:4+ngauss]
print 'T vals/Tadmom:',tvals/Tadmom
# plot the last one
gmix = gmix_fit.pars2gmix_coellip_pick(gf.popt,ptype=ptype)
model = gmix2image_em(gmix,im.shape)
images.compare_images(im,model)
else:
data=eu.io.read(f)
biggles.configure('fontsize_min', 1.0)
biggles.configure('linewidth',1.0) # frame only
nrows=3
ncols=4
tab=biggles.Table(nrows,ncols)
for par in xrange(npars):
plt=biggles.FramedPlot()
plt.add(biggles.Curve(data['sigma'],data['pars'][:,par]))
plt.add(biggles.Points(data['sigma'],data['pars'][:,par],
type='filled circle'))
plt.xlabel = r'$\sigma$'
plt.ylabel = 'p%d' % par
tab[par//ncols,par%ncols] = plt
tab.show()
tab.write_img(1024,1024,pngf)
