def test_gmix_exp():
from fimage import model_image
numpy.random.seed(35)
ngauss=3
nsig=7.
#dims=[41,41]
#cen=[(dims[0]-1)/2., (dims[1]-1)/2.]
#cov=[10.5,0.0,10.5]
T = 2*3
e = 0.3
theta = randu()*360.
e1 = e*cos(2*theta*numpy.pi/180.0)
e2 = e*sin(2*theta*numpy.pi/180.0)
Irc = e2*T/2.0
#Icc = (1+e1)*T/2.0
#Irr = (1-e1)*T/2.0
Icc = (1+e1)*T/2.0
Irr = (1-e1)*T/2.0
#T = 2.*3.0
sigma = sqrt(T/2.)
dim = int(2*nsig*sigma)
if (dim % 2) == 0:
dim += 1
dims=array([dim,dim])
print 'dims:',dims
cen=(dims-1)/2.
#cov = [T/2.,0.0,T/2.]
cov = [Irr,Irc,Icc]
# need order='c' since we will use in in C code!
im = model_image('exp',dims,cen,cov,order='c')
sky = 0.01*im.max()
im_fakesky = im + sky
ntry=0
max_try = 10
flags=9999
while flags != 0 and ntry < max_try:
stderr.write('.')
guess = get_exp_guess(cen,cov,ngauss)
gm=gmix_image.GMixEM(im_fakesky, guess, sky=sky, maxiter=5000)
flags = gm.flags
ntry += 1
if ntry == max_try:
raise ValueError("too many tries")
gmix_image.gmix_print(gm.pars)
stderr.write('\n')
model = gmix2image_em(gm.pars,im.shape)
images.compare_images(im, model)
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)
