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FastLensSim.py
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FastLensSim.py
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import indexTricks as iT
import numpy
from pylens import *
from imageSim import profiles,convolve,SBModels
import distances as D
import cPickle
import indexTricks as iT
import numpy,pylab
from imageSim import profiles,convolve,models
import pylab as plt
from Surveys import Survey
from StochasticObserving import SO
from SignaltoNoise import S2N
class FastLensSim(SO,S2N):
def __init__(self,surveyname,fractionofseeing=1):
#-----------------------------------------------------
### Read in survey
self.surveyname=surveyname
survey=Survey(surveyname)#This stores typical survey in Surveys.Survey
self.survey=survey
self.pixelsize=survey.pixelsize
self.side=survey.side
self.readnoise=survey.readnoise
self.nexposures=survey.nexposures
self.f_sky=survey.f_sky
self.bands=survey.bands
self.strategy=survey.strategy
self.strategyx=survey.strategyx
self.exposuretimes={}
self.zeropoints={}
self.stochasticobservingdata={}
self.gains={}
self.seeing={}
self.psfscale={}
self.psf={}
self.psfFFT={}
self.ET={}
self.SB={}
for i in range(len(survey.bands)):
self.exposuretimes[survey.bands[i]]=survey.exposuretimes[i]
self.zeropoints[survey.bands[i]]=survey.zeropoints[i]
self.gains[survey.bands[i]]=survey.gains[i]
self.stochasticobservingdata[survey.bands[i]]=survey.stochasticobservingdata[i]
self.zeroexposuretime=survey.zeroexposuretime
#-----------------------------------------------------
###do some setup
self.xl=(self.side-1.)/2.
self.yl=(self.side-1.)/2.
self.x,self.y = iT.coords((self.side,self.side))
self.r2 = (self.x-self.xl)**2+(self.y-self.yl)**2
self.pixelunits=False
#-----------------------------------------------------
self.Reset()
def Reset(self):
self.sourcenumbers=[]
#Some objects that need pre-defining as dictionaries
self.magnification={}
self.image={}
self.sigma={}
self.residual={}
self.zeromagcounts={}
self.xs={}
self.ys={}
self.ms={}
self.qs={}
self.ps={}
self.rs={}
self.ns={}
self.bl={}
self.src={}
self.galmodel={}
self.sourcemodel={}
self.model={}
self.totallensedsrcmag={}
self.fakeLens={}
self.image={}
self.sigma={}
self.fakeResidual={}
self.fakeResidual[0]={}
self.SN={}
self.SNRF={}
self.convolvedsrc={}
self.convolvedgal={}
#===========================================================================
def trytoconvert(self,par,p):
try:return par/p
except NameError:print "warning one of the parameters is not defined"
#===========================================================================
def setLensPars(self,m,r,q,n=4,pixelunits=False,reset=True,xb=0,xp=0,jiggle=0):
if reset: self.Reset()
self.rl={}
if pixelunits==False:
for band in r.keys():
self.rl[band]=self.trytoconvert(r[band],self.pixelsize)
self.ml=m
self.ql=q
self.deltaxl=(numpy.random.rand()-0.5)*2*jiggle
self.deltayl=(numpy.random.rand()-0.5)*2*jiggle
if jiggle!=0:
self.deltap=0.+(numpy.random.rand()-0.5)*180
n=(numpy.random.rand()+1)*4
else:
self.deltap=0.
self.nl=n
self.gal=SBModels.Sersic('gal',{'x':self.xl+self.deltaxl,'y':self.yl+self.deltayl,'q':self.ql,'pa':90+self.deltap,'re':self.rl[band],'n':self.nl})
self.xb=xb
self.xp=xp
#===========================================================================
def setSourcePars(self,b,m,x,y,q,p,r,n=1,pixelunits=False,sourcenumber=1):
if pixelunits==False:
x=self.trytoconvert(x,self.pixelsize)
y=self.trytoconvert(y,self.pixelsize)
r=self.trytoconvert(r,self.pixelsize)
b=self.trytoconvert(b,self.pixelsize)
self.xs[sourcenumber]=x+self.xl+self.deltaxl+0.000001
self.ys[sourcenumber]=y+self.yl+self.deltayl+0.000001
self.ms[sourcenumber]=m
self.qs[sourcenumber]=q
self.ps[sourcenumber]=p
self.rs[sourcenumber]=r
self.ns[sourcenumber]=n
self.bl[sourcenumber]=b
self.src[sourcenumber]=SBModels.Sersic('src%i'%sourcenumber,
{'x':self.xs[sourcenumber],'y':self.ys[sourcenumber],\
'q':self.qs[sourcenumber],'pa':self.ps[sourcenumber],\
're':self.rs[sourcenumber],'n':self.ns[sourcenumber]})
self.sourcenumbers.append(sourcenumber)
self.sourcemodel[sourcenumber]={}
self.totallensedsrcmag[sourcenumber]={}
self.fakeResidual[sourcenumber]={}
self.SN[sourcenumber]={}
self.SNRF[sourcenumber]={}
self.convolvedsrc[sourcenumber]={}
#===========================================================================
def lensASource(self,sourcenumber,bands):
src=self.src[sourcenumber]
lens=massmodel.PowerLaw('lens',{},{'x':self.xl+self.deltaxl,'y':self.yl+self.deltayl,'q':self.ql,'pa':90+self.deltap,'b':self.bl[sourcenumber],'eta':1})
es=massmodel.ExtShear('lens',{},{'x':self.xl+self.deltaxl,'y':self.yl+self.deltayl,'pa':self.xp,'b':self.xb})
lenses=[lens,es]
a=51
ox,oy=iT.coords((a,a))
ps=(self.rs[sourcenumber]*(10./a))
ox=(ox-(a-1)/2.)*ps+(self.xs[sourcenumber])
oy=(oy-(a-1)/2.)*ps+(self.ys[sourcenumber])
unlensedsrcmodel=(src.pixeval(ox,oy,csub=5)*(ps**2)).sum()
srcnorm=unlensedsrcmodel.sum()
unlensedsrcmodel/=srcnorm
srcmodel=pylens.lens_images(lenses,src,[self.x,self.y],getPix=True,csub=5)[0]
srcmodel[srcmodel<0]=0
srcmodel/=srcnorm
self.magnification[sourcenumber]=(numpy.sum(numpy.ravel(srcmodel))/numpy.sum(numpy.ravel(unlensedsrcmodel)))
sm={}
for band in bands:
unlensedtotalsrcflux=10**(-(self.ms[sourcenumber][band]-self.zeropoints[band])/2.5)
sm[band]=srcmodel*unlensedtotalsrcflux
if sm[band].max()>0:
self.totallensedsrcmag[sourcenumber][band]=-2.5*numpy.log10(sm[band].sum())+self.zeropoints[band]
else:
self.totallensedsrcmag[sourcenumber][band]=99
return sm
#===========================================================================
def EvaluateGalaxy(self,light,mag,bands):
model={}
lightm=light.pixeval(self.x,self.y,csub=5)
lightm[lightm<0]=0
lightm/=lightm.sum()
for band in bands:
flux=10**(-(mag[band]-self.zeropoints[band])/2.5)
model[band]=lightm*flux
return model
#===========================================================================
def MakeModel(self, bands):
#did you know that self.gal is actually fixed for all bands currently?
self.galmodel=self.EvaluateGalaxy(self.gal,self.ml,bands)
for sourcenumber in self.sourcenumbers:
self.sourcemodel[sourcenumber]=self.lensASource(sourcenumber,bands)
for band in bands:
self.model[band]=self.galmodel[band]*1
for sourcenumber in self.sourcenumbers:
self.model[band]+=self.sourcemodel[sourcenumber][band]
#===========================================================================
def ObserveLens(self,noisy=True,bands=[]):
if bands==[]:bands=self.bands
for band in bands:
if self.seeing[band]!=0:
convolvedgal,self.psfFFT[band] = convolve.convolve(self.galmodel[band],self.psf[band],True)
convolvedgal[convolvedgal<0]=0
self.convolvedgal[band]=convolvedgal
convolvedmodel=convolvedgal*1
convolvedsrc={}
for sourcenumber in self.sourcenumbers:
convolvedsrc[sourcenumber]=convolve.convolve(self.sourcemodel[sourcenumber][band],self.psfFFT[band],False)[0]
convolvedsrc[sourcenumber][convolvedsrc[sourcenumber]<0]=0
self.convolvedsrc[sourcenumber][band]=convolvedsrc[sourcenumber]
convolvedmodel+=convolvedsrc[sourcenumber]
self.zeromagcounts[band]=(10**(-(0-self.zeropoints[band])/2.5))
exposurecorrection=((self.ET[band]*1./self.zeroexposuretime))*self.gains[band]
convolvedmodel*=exposurecorrection
#skybackground per second per square arcsecond
background=(10**(-(self.SB[band]-self.zeropoints[band])/2.5))*(self.pixelsize**2)
tot_bg=background*exposurecorrection
sigma=((convolvedmodel+tot_bg)+self.nexposures*(self.readnoise**0.5)**2)**.5
fakeLens=convolvedmodel*1.
if noisy:fakeLens+=(numpy.random.randn(self.side,self.side)*(sigma))
#convert back to ADU/second:
fakeLens/=exposurecorrection
sigma/=exposurecorrection
self.image[band]=fakeLens*1
self.fakeLens[band]=fakeLens*1
self.sigma[band]=sigma*1
self.fakeResidual[0][band]=fakeLens-convolvedgal
for sourcenumber in self.sourcenumbers:
self.SN[sourcenumber][band]=self.SNfunc(\
convolvedsrc[sourcenumber],sigma)
self.fakeResidual[sourcenumber][band]=\
fakeLens-convolvedmodel+convolvedsrc[sourcenumber]
#===========================================================================
def loadModel(self,ideallens):
self.galmodel,self.sourcemodel,self.model,self.magnification,self.totallensedsrcmag=ideallens
self.image=self.model
#===========================================================================
def loadConvolvedModel(self,ideallens):
self.galmodel,self.sourcemodel,self.model,self.magnification,self.totallensedsrcmag=ideallens
self.image=self.model
#===========================================================================
def makeLens(self,stochastic=True,save=False,noisy=True,stochasticmode="MP",SOdraw=[],bands=[],musthaveallbands=False,MakeModel=True):
if stochastic==True:self.stochasticObserving(mode=stochasticmode,SOdraw=SOdraw,musthaveallbands=musthaveallbands)
if self.seeingtest=="Fail":return None
if bands==[]:bands=self.bands
if MakeModel:
self.MakeModel(bands)
if self.strategy=="resolve":
if stochastic==True:self.stochasticObserving(mode=stochasticmode,SOdraw=SOdraw) #have to rerun stochastic observing now we know the magnification
self.ObserveLens(noisy=noisy)
return [self.galmodel,self.sourcemodel,self.model,self.magnification,self.totallensedsrcmag]
#===========================================================================
def makeColorLens(self,bands=["g_SDSS","r_SDSS","i_SDSS"],recolourize=True):
if self.surveyname=="Euclid" and bands==["g_SDSS","r_SDSS","i_SDSS"]:
bands=["VIS","VIS","VIS"]
import colorImage
goodbands=[]
for band in bands:
try:
self.image[band]
goodbands.append(band)
except KeyError:
pass
bands=goodbands
if len(bands)==1:
bands=[bands[0],bands[0],bands[0]]
if len(bands)==2:
bands=[bands[0],"dummy",bands[1]]
self.ml["dummy"]=(self.ml[bands[0]]+self.ml[bands[2]])/2
self.image["dummy"]=(self.image[bands[0]]+self.image[bands[2]])/2
if recolourize:
self.color = colorImage.ColorImage()
self.color.bMinusr=(self.ml[bands[0]]-self.ml[bands[2]])/4.
self.color.bMinusg=(self.ml[bands[0]]-self.ml[bands[1]])/4.
self.color.nonlin=4.
self.colorimage = self.color.createModel(\
self.image[bands[0]],self.image[bands[1]],self.image[bands[2]])
else:
self.colorimage = self.color.colorize(\
self.image[bands[0]],self.image[bands[1]],self.image[bands[2]])
return self.colorimage
#===========================================================================
def display(self,band="g_SDSS",bands=["g_SDSS","r_SDSS","i_SDSS"]):
if self.surveyname=="Euclid":bands=["VIS","VIS","VIS"]
import pylab as plt
plt.ion()
plt.figure(1)
plt.imshow(self.makeColorLens(bands=bands),interpolation="none")
plt.figure(2)
import colorImage
self.color = colorImage.ColorImage()#sigma-clipped single band residual
plt.imshow(self.color.createModel(self.fakeResidual[0][band],self.fakeResidual[0][band],self.fakeResidual[0][band])[:,:,0],interpolation="none")
plt.figure(3)
plt.imshow(self.fakeResidual[0][band],interpolation="none")
try:
self.fakeResidual[1]["RF"]
plt.figure(4)
plt.imshow(self.fakeResidual[1]["RF"],interpolation="none")
except KeyError: pass
plt.draw()
raw_input()
plt.ioff()
#===========================================================================
def Rank(self,mode,band="g_SDSS",bands=["g_SDSS","r_SDSS","i_SDSS"]):
import pylab as plt
plt.ion()
rank="d"
while rank not in ["0","1","2","3","4","-1","-2","-3"]:
if mode=="colour":
plt.imshow(self.makeColorLens(bands=bands),interpolation="none")
plt.draw()
if mode=="rf":
plt.imshow(self.fakeResidual[0]["RF"],interpolation="none")
plt.draw()
if mode=="best":
plt.imshow(self.fakeResidual[0][band],interpolation="none")
plt.draw()
rank=raw_input()
if rank=="":rank="0"
plt.ioff()
return rank
#===========================================================================