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()
ym = y[mask]
coords = [xm,ym]
PSF = pT.getPSFMatrix(psf,img.shape)
PSFm = pT.maskPSFMatrix(PSF,mask)
iflt = img.flatten()
sflt = sig.flatten()
vflt = sflt**2
xflt = x.flatten()
yflt = y.flatten()
src = aT.AdaptiveSource(ifltm/sfltm,ifltm.size/Npnts)
xl,yl = pylens.getDeflections(lenses,coords)
src.update(xl,yl)
osrc = showRes(xl,yl,src,PSFm,img,sig,mask,ifltm,vfltm,cmatm,1e-5,1,400)
pylab.show()
'''
G,L,S,offsets,shear = numpy.load(guiFile)
pars = []
cov = []
lenses = []
for name in L.keys():
model = L[name]
lpars = {}
for key in 'x','y','q','pa','b','eta':
lo,hi = model[key]['lower'],model[key]['upper']
val = dic[name+' '+key][a1,a2,a3]
from pylens import MassModels,pylens
from scipy.special import gamma,gammainc
import itertools
import numpy as np, pylab as pl
sersic = lambda n,Re,k,R: np.exp(-k*((R/Re)**(1./n))) * (k**(2.*n)) / (2.*np.pi*n*gamma(2.*n)* gammainc(2.*n,k*(240./Re)**(1./n)) * Re**2)
x,y=np.linspace(-20,20,700),np.linspace(-20,20,700)
ii = np.array(list(itertools.product(x,y)))
lens = MassModels.PowerLaw('Lens1', {'x':0,'y':0,'q':1,'pa':0,'b':10,'eta':0.7})
xd,yd = pylens.getDeflections(lens,ii.T)
rl = np.sqrt(xd**2. + yd**2.)
SB = sersic(4,30,(2.*4-0.324), rl)
#pl.figure()
#pl.scatter(ii[:,0],ii[:,1],c=SB,edgecolors='none',s=100)
#pl.figure()
#pl.scatter(xd,yd,c=SB,edgecolors='none',s=100)
# caustic?
# source relative to galaxy?
DXs,DYs = np.linspace(0.1,1,3), np.linspace(0.1,1,3)
jj = np.array(list(itertools.product(DXs,DYs)))
for i in range(jj.shape[0]):
DX,DY=jj[i]
rl = np.sqrt((xd-DX)**2. + (yd-DY)**2.)
SB = sersic(4,30,(2.*4-0.324), rl)
pl.figure()
pl.scatter(ii[:,0],ii[:,1],c=SB,edgecolors='none',s=100)
pl.scatter(0,0,color='White')
