def test_em_sdss(ngauss=2,
run=756,
field=45,
camcol=1,
filter='r',
row=123.1,
col=724.8,
cocenter=False,
show=False):
import sdsspy
fnum=sdsspy.FILTERNUM[filter]
psfield=sdsspy.read('psField', run=run, camcol=camcol, field=field,
lower=True)
psfkl=sdsspy.read('psField', run=run, camcol=camcol, field=field,
filter=filter)
if psfkl is None:
print 'no such field'
return
im_nonoise=psfkl.rec(row, col, trim=True)
im0,skysig=add_noise_matched(im_nonoise, 1.e8)
ivar=1./skysig**2
dims=im0.shape
cen=[(dims[0]-1.)/2., (dims[1]-1.)/2.]
fwhm=psfield['psf_width'][0,fnum]
sigma_guess=fimage.fwhm2sigma(fwhm)
sigma_guess /= 0.4 # pixels
print 'guess fwhm:',fwhm
gm=gmix_image.gmix_em.GMixEMBoot(im0, ngauss, cen,
sigma_guess=sigma_guess,
ivar=ivar,
cocenter=cocenter)
res=gm.get_result()
gmx=gm.get_gmix()
print 'numiter:',res['numiter']
if show and have_images:
import biggles
biggles.configure('screen','width',1000)
biggles.configure('screen','height',1000)
mod=gmix2image(gmx,im0.shape)
counts=im0.sum()
mod *= counts/mod.sum()
if cocenter:
title='cocenter ngauss: %d' % ngauss
else:
title='free centers: %d' % ngauss
images.compare_images(im0, mod, label1='image',label2='model',
title=title)
print gmx
return res
def test_em(s2n=100., show=False, ngauss=2, offcen=True):
#tol=1.e-6
tol=1.e-6
maxiter=5000
dims=[31,31]
if ngauss==2:
if offcen:
gd = [{'p':0.6,'row':17.1,'col':17.6,'irr':4.0,'irc':0.0,'icc':4.0},
{'p':0.4,'row':14.2,'col':15.4,'irr':3.2,'irc':0.3,'icc':2.0}]
else:
gd = [{'p':0.6,'row':15.1,'col':15.6,'irr':4.0,'irc':0.0,'icc':4.0},
{'p':0.4,'row':15.1,'col':15.6,'irr':3.2,'irc':0.3,'icc':2.0}]
guess=[{'p':0.5+0.02*srandu(),
'row':15+2*srandu(),
'col':15+2*srandu(),
'irr':2.0+0.5*srandu(),
'irc':0.0+0.1*srandu(),
'icc':2.0+0.5*srandu()},
{'p':0.5+0.02*srandu(),
'row':15+2*srandu(),
'col':15+2*srandu(),
'irr':2.0+0.5*srandu(),
'irc':0.0+0.1*srandu(),
'icc':2.0+0.5*srandu()} ]
elif ngauss==1:
gd = [{'p':0.6,'row':17.1,'col':17.6,'irr':4.0,'irc':0.0,'icc':4.0}]
guess=[{'p':0.5+0.02*srandu(),
'row':15+2*srandu(),
'col':15+2*srandu(),
'irr':2.0+0.5*srandu(),
'irc':0.0+0.1*srandu(),
'icc':2.0+0.5*srandu()} ]
else:
raise ValueError("1 or 2 gauss")
counts=1000
im_nonoise = gmix2image_em(gd, dims, counts=counts)
im,skysig=add_noise_matched(im_nonoise,s2n)
# pretend it is poisson
#sky = skysig**2
#im += sky
im_min=im.min()
sky = 0.01 + abs(im_min)
im += sky
verbose=False
gm = gmix_image.GMixEM(im,
guess,
sky=sky,
counts=counts,
maxiter=maxiter,
tol=tol,
verbose=verbose)
gm.write()
print 'truth'
for i,d in enumerate(gd):
print '%i'% i,
for k in ['p','row','col','irr','irc','icc']:
print '%s: %9.6lf' % (k,d[k]),
print
if show and have_images:
model_image=gm.get_model()
msum=model_image.sum()
if msum > 0:
model_image *= counts/msum
images.compare_images(im-sky, model_image,
label1='im', label2='model',
cross_sections=False)
return gm
def test_em_jacob(s2n=100.,
ngauss=2,
offcen=True,
scale=0.27, # ''/pixel
theta=20.0,
show=False):
import fimage
import math
from math import cos,sin,sqrt
from lensing.util import rotate_shape
thetarad=math.radians(theta)
ctheta=cos(thetarad)
stheta=sin(thetarad)
c2theta=cos(2*thetarad)
s2theta=sin(2*thetarad)
e1=0.2
e2=0.1
counts=100.
sigma=5.0 # arcsec
T=2*sigma**2
# for simulation, in pixels
# rotate backwards to the pixel coords
e1pix,e2pix=rotate_shape(e1,e2,-theta)
sigma_pix=sigma/scale
Tpix=2*sigma_pix**2
counts_pix=counts/(scale*scale)
dim=2*5*sigma_pix
dims=[dim]*2
cenpix=[(dim-1.)/2.]*2
print 'sky'
print ' sigma(''):',sigma
print ' e1:',e1,'e2:',e2
print 'pix'
print ' sigma(pix):',sigma_pix
print ' e1:',e1pix,'e2:',e2pix
print 'dims:',dims
print
gmix_pix=GMixCoellip([cenpix[0], cenpix[1], e1pix, e2pix, Tpix, counts_pix])
im0=gmix2image(gmix_pix, dims)
imnoise0,skysig=add_noise_matched(im0,s2n)
im,sky=_em_prep(imnoise0)
jacob={'row0':cenpix[0],
'col0':cenpix[1],
'dudrow':ctheta*scale, 'dudcol':-stheta*scale,
'dvdrow':stheta*scale, 'dvdcol': ctheta*scale}
guess_pix=[{'p':1.0, 'row':cenpix[0], 'col':cenpix[1],
'irr':Tpix/2., 'irc':0.0, 'icc':Tpix/2.}]
gm_pix=gmix_image.GMixEM(im, guess_pix, sky=sky)
print 'pixel result'
print gm_pix
gmix=gm_pix.get_gmix()
print gmix
e1m_pix,e2m_pix,Tm_pix=gmix.get_e1e2T()
sigma_meas_pix = sqrt(Tm_pix/2.)
print 'measured pixels'
print ' sigma:',sigma_meas_pix
print ' e1:',e1m_pix,'e2:',e2m_pix
print
guess=[{'p':1.0, 'row':0.0, 'col':0.0,
'irr':4., 'irc':0.0, 'icc':4.}]
pprint.pprint(guess)
gm=gmix_image.GMixEM(im,
guess,
sky=sky,
jacobian=jacob,
verbose=1)
print 'sky result'
print gm
gmix=gm.get_gmix()
print gmix
print 'measured:'
e1m,e2m,Tm=gmix.get_e1e2T()
sigma_meas = sqrt(Tm/2.)
print ' sigma:',sigma_meas
print ' e1:',e1m,'e2:',e2m