def showRes(x,y,src,psf,img,sig,mask,iflt,vflt,cmat,reg,niter,npix):
oy,ox = iT.coords((npix,npix))
oy -= oy.mean()
ox -= ox.mean()
span = max(x.max()-x.min(),y.max()-y.min())
oy *= span/npix
ox *= span/npix
ox += x.mean()
oy += y.mean()
lmat = psf*src.lmat
rmat = src.rmat
res,fit,model,rhs,regg = aT.getModelG(iflt,vflt,lmat,cmat,rmat,reg,niter=niter)
osrc = src.eval(ox.ravel(),oy.ravel(),fit).reshape(ox.shape)
oimg = img*numpy.nan
oimg[mask] = (lmat*fit)
ext = [0,img.shape[1],0,img.shape[0]]
ext2 = [x.mean()-span/2.,x.mean()+span/2.,y.mean()-span/2.,y.mean()+span/2.]
pylab.figure()
pylab.subplot(221)
img[~mask] = numpy.nan
pylab.imshow(img,origin='lower',interpolation='nearest',extent=ext)
pylab.colorbar()
pylab.subplot(222)
pylab.imshow(oimg,origin='lower',interpolation='nearest',extent=ext)
pylab.colorbar()
pylab.subplot(223)
pylab.imshow((img-oimg)/sig,origin='lower',interpolation='nearest',extent=ext)
pylab.colorbar()
pylab.subplot(224)
pylab.imshow(osrc,origin='lower',interpolation='nearest',extent=ext2)
pylab.colorbar()
return osrc
def doFit(p=None,doReg=True,updateReg=True,checkImgs=True,levMar=False):
global reg
# Check if using levMar-style parameters
if p is not None:
for i in range(len(p)):
pars[i].value = p[i]
# If the parameter is out-of-bounds return a bad fit
try:
a = pars[i].logp
except:
return iflt/sflt
for l in lenses:
l.setPars()
xl,yl = pylens.getDeflections(lenses,coords)
src.update(xl,yl,doReg=doReg)
lmat = PSFm*src.lmat
if doReg==True:
rmat = src.rmat
else:
rmat = None
nupdate = 0
if doReg==True and updateReg==True:
nupdate = 10
res,fit,model,_,regg = aT.getModelG(ifltm,vfltm,lmat,cmatm,rmat,reg,nupdate)
reg = regg[0]
if checkImgs is False:
if levMar:
res = res**0.5+ifltm*0.
return -0.5*res
# This checks is images are formed outside of the masked region
xl,yl = pylens.getDeflections(lenses,[xflt,yflt])
oimg,pix = src.eval(xl,yl,fit,domask=False)
oimg = PSF*oimg
res = (iflt-oimg)/sflt
if levMar:
return res
return -0.5*(res**2).sum()