def __init__(self, s2, objmodel, obj_ellip, psfmodel,
psf_ellip=0.0, Tratio_psf=None, fluxfrac1=None,
psf_fwhm=10.0, # in pixels. 4'' seeing in SDSS is this big
verbose=False):
self.verbose=verbose
self['s2'] = s2
self['objmodel'] = objmodel
self['obj_ellip'] = obj_ellip
self['psfmodel'] = psfmodel
if isinstance(psfmodel, (str,unicode)):
self['psf_ellip'] = psf_ellip
self['Tratio_psf'] = Tratio_psf
self['fluxfrac1'] = fluxfrac1
self['psf_fwhm'] = psf_fwhm
self['Tpsf'] = admom.fwhm2mom(psf_fwhm)
else:
self['psf_ellip'] = None
self['Tratio_psf'] = None
self['fluxfrac1'] = None
self['psf_fwhm'] = None
self['Tpsf'] = None
self['Irr_psf'] = None
self['Irc_psf'] = None
self['Icc_psf'] = None
self.randomize()
def regauss_obj(self, obj, filter):
import admom
from sdsspy.atlas.atlas import NoAtlasImageError
run = obj['run']
camcol = obj['camcol']
field = obj['field']
id = obj['id']
c = sdsspy.FILTERNUM[filter]
self.cache_psf(run, camcol, field)
try:
self.cache_atlas(run, camcol, field, id)
except NoAtlasImageError:
# we can safely ignore such errors, but we return
# nothing
return None
im = numpy.array( self.atls['images'][c], dtype='f8')
im -= self.atls['SOFT_BIAS']
rowc=obj['rowc'][c]
colc=obj['colc'][c]
row=rowc - self.atls['row0'][c] - 0.5
col=colc - self.atls['col0'][c] - 0.5
sigsky = self.psfield['skysig'][0,c]
psf = self.psfKLs[c].rec(rowc, colc, trim=True)
# sometimes we get very negative pixels, not sure why
#im=im.clip(-3*sigsky, im.max())
guess_psf=admom.fwhm2mom( obj['psf_fwhm'][c], pixscale=0.4)/2.
guess = guess_psf
if 'm_rr_cc' in obj.dtype.names:
if obj['m_rr_cc'][c] > guess_psf:
guess=obj['m_rr_cc'][c]/2
rg = admom.ReGauss(im, row, col, psf,
sigsky=sigsky, guess=guess, guess_psf=guess_psf,
verbose=self.verbose)
rg.do_all()
# keep these things in case we want to call show()
self.rg=rg
self.im=im
self.psf=psf
return rg
def _measure_psf(self, obj):
fnum = self["fnum"]
rowc = obj["rowc"][fnum]
colc = obj["colc"][fnum]
psf_im = self.psf_kl[fnum].rec(rowc, colc, trim=True)
psf_im = psf_im.astype("f8")
guess_psf = admom.fwhm2mom(obj["psf_fwhm"][fnum], pixscale=0.4) / 2.0
psf_res = self._fit_psf(psf_im, guess_psf, 1.0)
return psf_res
def admom_atlas(type, run, camcol, field, id, filter,
objs=None,
show=False, showmin=0, **keys):
"""
Objs must be for this camcol!
"""
import admom
import sdsspy
c = sdsspy.FILTERNUM[filter]
if objs is None:
sc=SweepCache()
obj = sc.readobj(type, run, camcol, field, id)
else:
w=where1( (objs['field'] == field) & (objs['id'] == id) )
if w.size == 0:
raise ValueError("Object not found objs: "
"%06i-%i-%04i" % (run,camcol,id))
obj = objs[w[0]]
atls = sdsspy.read('fpAtlas',run,camcol,field,id, trim=True)
im = numpy.array( atls['images'][c], dtype='f8') - atls['SOFT_BIAS']
psfield = sdsspy.read('psField', run, camcol, field, lower=True)
rowc=obj['rowc'][c]
colc=obj['colc'][c]
row=rowc - atls['row0'][c] - 0.5
col=colc - atls['col0'][c] - 0.5
sigsky = psfield['skysig'][0,c]
Tguess_psf=admom.fwhm2mom( obj['psf_fwhm'][c], pixscale=0.4)
if obj['m_rr_cc'][c] > Tguess_psf:
Tguess=obj['m_rr_cc'][c]
else:
Tguess=Tguess_psf
out = admom.admom(im,
row,
col,
sky=0.0,
sigsky=sigsky,
Tguess=Tguess)
if show:
import fimage
import biggles
plt=images.view(im, min=showmin, show=False, **keys)
if out['whyflag'] == 0:
levels=7
wrow = out['wrow']
wcol = out['wcol']
model = fimage.model_image('gauss',
im.shape,
[wrow,wcol],
[out['Irr'],out['Irc'],out['Icc']],
counts=im.sum())
cmod = biggles.Contours(model.transpose(), color='grey')
cmod.levels = levels
plt.add(cmod)
plt.show()
return out
