noiseP = 56.6
tellmin = 2
tellmax = 3000
gradCut = 10000
pellmin = 2
pellmax = 3000
deg = 10.
px = 0.5
arc = deg*60.
bin_edges = np.arange(10,3000,10)
#theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=False,useTotal=False,lpad=9000)
lmap = lm.makeEmptyCEATemplate(raSizeDeg=arc/60., decSizeDeg=arc/60.,pixScaleXarcmin=px,pixScaleYarcmin=px)
print lmap.data.shape
myNls = NlGenerator(lmap,theory,bin_edges,gradCut=gradCut)
myNls.updateNoise(beam,noiseT,noiseP,tellmin,tellmax,pellmin,pellmax)
#polCombList = ['TT','EE','ET','TE','EB','TB']
#colorList = ['red','blue','green','cyan','orange','purple']
polCombList = ['TT','EE','ET','EB','TB']
colorList = ['red','blue','green','orange','purple']
ellkk = np.arange(2,9000,1)
Clkk = theory.gCl("kk",ellkk)
pl = Plotter(scaleY='log',scaleX='log')
pl.add(ellkk,4.*Clkk/2./np.pi)
#beamRange = np.arange(0.5,5.0,0.5)
beamRange = np.arange(5.0, 10.5, 0.5)
beamscale = lambda b: np.sqrt(8. * np.log(2.)) * 60. * 180. / np.pi / b
kmin = 40
deg = 10.
#px = 0.2
px = 0.5
dell = 10
theory = loadTheorySpectraFromCAMB(cambRoot,
unlensedEqualsLensed=False,
useTotal=False,
lpad=9000)
lmap = lm.makeEmptyCEATemplate(raSizeDeg=deg,
decSizeDeg=deg,
pixScaleXarcmin=px,
pixScaleYarcmin=px)
print((lmap.data.shape))
i = 0
for gradCut in [10000, 2000]:
myNls = NlGenerator(lmap, theory, gradCut=gradCut)
for polComb in ['TT', 'TE', 'EE', 'EB', 'ET', 'TB']:
for beamY in beamRange:
beamell = beamscale(beamY)
for tellmaxY, pellmaxY in [(3000, 5000), (beamell, beamell)]:
for noiseX,beamX,lab,tellminX,tellmaxX,pellminX,pellmaxX in \
[(noiseY,beamY,"sameGrad",tellminY,tellmaxY,pellminY,pellmaxY), \
(30.,7.0,"planckGrad",2,3000,2,3000)]:
kellmin = 2
kellmax = 2000
gradCut = None
degx = 5.
degy = 5.
px = 2.0
TCMB = 2.7255e6
hugeTemplate = lm.makeEmptyCEATemplate(degx,degy,pixScaleXarcmin=px,pixScaleYarcmin=px)
lxMap,lyMap,modLMap,thetaMap,lx,ly = fmaps.getFTAttributesFromLiteMap(hugeTemplate)
nfreq = modLMap.max()
assert nfreq>cmbellmax
assert nfreq>kellmax
from orphics.tools.cmb import loadTheorySpectraFromCAMB
cambRoot = os.environ['HOME']+"/repos/cmb-lensing-projections/data/TheorySpectra/ell28k_highacc"
theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=True,useTotal=False,TCMB = 2.7255e6,lpad=9000)
#theory = loadTheorySpectraFromCAMB(cambRoot,unlensedEqualsLensed=False,useTotal=False,TCMB = 2.7255e6,lpad=9000)
Nlfuncdict={}
Nlfuncdict['TT'] = cmb.get_noise_func(beamArcmin,noiseT,TCMB=TCMB)
Nlfuncdict['EE'] = cmb.get_noise_func(beamArcmin,noiseP,TCMB=TCMB)
Nlfuncdict['BB'] = cmb.get_noise_func(beamArcmin,noiseP,TCMB=TCMB)
import numpy as np
import orphics.analysis.flatMaps as fmaps
import orphics.tools.io as io
import flipper.liteMap as lm
from enlib.fft import fft, ifft
from numpy.fft import fftshift, ifftshift
from enlib.resample import resample_fft, resample_bin
arcX = 20 * 60.
arcY = 10 * 60.
arc = 10. * 60.
px = 0.5
pxDn = 7.5
fineTemplate = lm.makeEmptyCEATemplate(arcX / 60.,
arcY / 60.,
pixScaleXarcmin=px,
pixScaleYarcmin=px)
lxMap, lyMap, modLMap, thetaMap, lx, ly = fmaps.getFTAttributesFromLiteMap(
fineTemplate)
xMap, yMap, modRMap, xx, yy = fmaps.getRealAttributes(fineTemplate)
# sigArc = 3.0
# sig = sigArc*np.pi/180./60.
# fineTemplate.data = np.exp(-modRMap**2./2./sig**2.)
import btip.inpaintStamp as inp
ell, Cl = np.loadtxt("../btip/data/cltt_lensed_Feb18.txt", unpack=True)
ell, Cl = inp.total_1d_power(ell,
Cl,
ellmax=modLMap.max(),
def NFWMatchedFilterSN(clusterCosmology,log10Moverh,c,z,ells,Nls,kellmax,overdensity=500.,critical=True,atClusterZ=True,arcStamp=100.,pxStamp=0.05,saveId=None,verbose=False,rayleighSigmaArcmin=None,returnKappa=False,winAtLens=None):
if rayleighSigmaArcmin is not None: assert rayleighSigmaArcmin>=pxStamp
M = 10.**log10Moverh
lmap = lm.makeEmptyCEATemplate(raSizeDeg=arcStamp/60., decSizeDeg=arcStamp/60.,pixScaleXarcmin=pxStamp,pixScaleYarcmin=pxStamp)
kellmin = 2.*np.pi/arcStamp*np.pi/60./180.
xMap,yMap,modRMap,xx,yy = fmaps.getRealAttributes(lmap)
lxMap,lyMap,modLMap,thetaMap,lx,ly = fmaps.getFTAttributesFromLiteMap(lmap)
cc = clusterCosmology
cmb = False
if winAtLens is None:
cmb = True
comS = cc.results.comoving_radial_distance(cc.cmbZ)*cc.h
comL = cc.results.comoving_radial_distance(z)*cc.h
winAtLens = (comS-comL)/comS
kappaReal, r500 = NFWkappa(cc,M,c,z,modRMap*180.*60./np.pi,winAtLens,overdensity=overdensity,critical=critical,atClusterZ=atClusterZ)
dAz = cc.results.angular_diameter_distance(z) * cc.h
th500 = r500/dAz
#fiveth500 = 10.*np.pi/180./60. #5.*th500
fiveth500 = 5.*th500
# print "5theta500 " , fiveth500*180.*60./np.pi , " arcminutes"
# print "maximum theta " , modRMap.max()*180.*60./np.pi, " arcminutes"
kInt = kappaReal.copy()
kInt[modRMap>fiveth500] = 0.
# print "mean kappa inside theta500 " , kInt[modRMap<fiveth500].mean()
# print "area of th500 disc " , np.pi*fiveth500**2.*(180.*60./np.pi)**2.
# print "estimated integral " , kInt[modRMap<fiveth500].mean()*np.pi*fiveth500**2.
k500 = simps(simps(kInt, yy), xx)
if verbose: print "integral of kappa inside disc ",k500
kappaReal[modRMap>fiveth500] = 0. #### !!!!!!!!! Might not be necessary!
# if cmb: print z,fiveth500*180.*60./np.pi
Ukappa = kappaReal/k500
# pl = Plotter()
# pl.plot2d(Ukappa)
# pl.done("output/kappa.png")
ellmax = kellmax
ellmin = kellmin
Uft = fftfast.fft(Ukappa,axes=[-2,-1])
if rayleighSigmaArcmin is not None:
Prayleigh = rayleigh(modRMap*180.*60./np.pi,rayleighSigmaArcmin)
outDir = "/gpfs01/astro/www/msyriac/plots/"
# io.quickPlot2d(Prayleigh,outDir+"rayleigh.png")
rayK = fftfast.fft(ifftshift(Prayleigh),axes=[-2,-1])
rayK /= rayK[modLMap<1.e-3]
Uft = Uft.copy()*rayK
Upower = np.real(Uft*Uft.conjugate())
# pl = Plotter()
# pl.plot2d(fftshift(Upower))
# pl.done("output/upower.png")
Nls[Nls<0.]=0.
s = splrep(ells,Nls,k=3)
Nl2d = splev(modLMap,s)
Nl2d[modLMap<ellmin]=np.inf
Nl2d[modLMap>ellmax] = np.inf
area = lmap.Nx*lmap.Ny*lmap.pixScaleX*lmap.pixScaleY
Upower = Upower *area / (lmap.Nx*lmap.Ny)**2
filter = np.nan_to_num(Upower/Nl2d)
#filter = np.nan_to_num(1./Nl2d)
filter[modLMap>ellmax] = 0.
filter[modLMap<ellmin] = 0.
# pl = Plotter()
# pl.plot2d(fftshift(filter))
# pl.done("output/filter.png")
# if (cmb): print Upower.sum()
# if not(cmb) and z>2.5:
# bin_edges = np.arange(500,ellmax,100)
# binner = bin2D(modLMap, bin_edges)
# centers, nl2dells = binner.bin(Nl2d)
# centers, upowerells = binner.bin(np.nan_to_num(Upower))
# centers, filterells = binner.bin(filter)
# from orphics.tools.io import Plotter
# pl = Plotter(scaleY='log')
# pl.add(centers,upowerells,label="upower")
# pl.add(centers,nl2dells,label="noise")
# pl.add(centers,filterells,label="filter")
# pl.add(ells,Nls,ls="--")
# pl.legendOn(loc='upper right')
# #pl._ax.set_ylim(0,1e-8)
# pl.done("output/filterells.png")
# sys.exit()
varinv = filter.sum()
std = np.sqrt(1./varinv)
sn = k500/std
if verbose: print sn
if saveId is not None:
np.savetxt("data/"+saveId+"_m"+str(log10Moverh)+"_z"+str(z)+".txt",np.array([log10Moverh,z,1./sn]))
if returnKappa:
return sn,fftfast.ifft(Uft,axes=[-2,-1],normalize=True).real*k500
return sn, k500, std
def getDLnMCMB(ells,Nls,clusterCosmology,log10Moverh,z,concentration,arcStamp,pxStamp,arc_upto,bin_width,expectedSN,Nclusters=1000,numSims=30,saveId=None,numPoints=1000,nsigma=8.,overdensity=500.,critical=True,atClusterZ=True):
import flipper.liteMap as lm
if saveId is not None: from orphics.tools.output import Plotter
M = 10.**log10Moverh
cc = clusterCosmology
stepfilter_ellmax = max(ells)
lmap = lm.makeEmptyCEATemplate(raSizeDeg=arcStamp/60., decSizeDeg=arcStamp/60.,pixScaleXarcmin=pxStamp,pixScaleYarcmin=pxStamp)
xMap,yMap,modRMap,xx,xy = fmaps.getRealAttributes(lmap)
lxMap,lyMap,modLMap,thetaMap,lx,ly = fmaps.getFTAttributesFromLiteMap(lmap)
kappaMap,retR500 = NFWkappa(cc,M,concentration,z,modRMap*180.*60./np.pi,winAtLens,overdensity,critical,atClusterZ)
finetheta = np.arange(0.01,arc_upto,0.01)
finekappa,retR500 = NFWkappa(cc,M,concentration,z,finetheta,winAtLens,overdensity,critical,atClusterZ)
kappaMap = fmaps.stepFunctionFilterLiteMap(kappaMap,modLMap,stepfilter_ellmax)
generator = fmaps.GRFGen(lmap,ells,Nls)
bin_edges = np.arange(0.,arc_upto,bin_width)
binner = bin2D(modRMap*180.*60./np.pi, bin_edges)
centers, thprof = binner.bin(kappaMap)
if saveId is not None:
pl = Plotter()
pl.plot2d(kappaMap)
pl.done("output/"+saveId+"kappa.png")
expectedSNGauss = expectedSN*np.sqrt(numSims)
sigma = 1./expectedSNGauss
amplitudeRange = np.linspace(1.-nsigma*sigma,1.+nsigma*sigma,numPoints)
lnLikes = 0.
bigStamp = 0.
for i in range(numSims):
profiles,totstamp = getProfiles(generator,stepfilter_ellmax,kappaMap,binner,Nclusters)
bigStamp += totstamp
stats = getStats(profiles)
if i==0 and (saveId is not None):
pl = Plotter()
pl.add(centers,thprof,lw=2,color='black')
pl.add(finetheta,finekappa,lw=2,color='black',ls="--")
pl.addErr(centers,stats['mean'],yerr=stats['errmean'],lw=2)
pl._ax.set_ylim(-0.01,0.3)
pl.done("output/"+saveId+"profile.png")
pl = Plotter()
pl.plot2d(totstamp)
pl.done("output/"+saveId+"totstamp.png")
Likes = getAmplitudeLikelihood(stats['mean'],stats['covmean'],amplitudeRange,thprof)
lnLikes += np.log(Likes)
width = amplitudeRange[1]-amplitudeRange[0]
Likes = np.exp(lnLikes)
Likes = Likes / (Likes.sum()*width) #normalize
ampBest,ampErr = cfit(norm.pdf,amplitudeRange,Likes,p0=[1.0,0.5])[0]
sn = ampBest/ampErr/np.sqrt(numSims)
snAll = ampBest/ampErr
if snAll<5.: print "WARNING: ", saveId, " run with mass ", M , " and redshift ", z , " has overall S/N<5. \
Consider re-running with a greater numSims, otherwise estimate of per Ncluster S/N will be noisy."
if saveId is not None:
Fit = np.array([np.exp(-0.5*(x-ampBest)**2./ampErr**2.) for x in amplitudeRange])
Fit = Fit / (Fit.sum()*width) #normalize
pl = Plotter()
pl.add(amplitudeRange,Likes,label="like")
pl.add(amplitudeRange,Fit,label="fit")
pl.legendOn(loc = 'lower left')
pl.done("output/"+saveId+"like.png")
pl = Plotter()
pl.plot2d(bigStamp/numSims)
pl.done("output/"+saveId+"bigstamp.png")
np.savetxt("data/"+saveId+"_m"+str(log10Moverh)+"_z"+str(z)+".txt",np.array([log10Moverh,z,1./sn]))
return 1./sn
import flipper.liteMap as lm
from orphics.theory.cosmology import Cosmology
import numpy as np
import os, sys
import orphics.tools.io as io
import orphics.tools.stats as stats
import orphics.analysis.flatMaps as fmaps
out_dir = os.environ['WWW']
cc = Cosmology(pickling=True, clTTFixFile="../szar/data/cltt_lensed_Feb18.txt")
lmap = lm.makeEmptyCEATemplate(raSizeDeg=20., decSizeDeg=20.)
ells = np.arange(2, 6000, 1)
Cell = cc.clttfunc(ells) #cc.theory.lCl('TT',ells)
lmap.fillWithGaussianRandomField(ells, Cell, bufferFactor=1)
io.highResPlot2d(lmap.data, out_dir + "map.png")
p2d = fmaps.get_simple_power(lmap, lmap.data * 0. + 1.)
lxMap, lyMap, modLMap, thetaMap, lx, ly = fmaps.getFTAttributesFromLiteMap(
lmap)
bin_edges = np.arange(20, 4000, 40)
b = stats.bin2D(modLMap, bin_edges)
cents, cdat = b.bin(p2d)
pl = io.Plotter(scaleX='log', scaleY='log')
pl.add(ells, Cell * ells**2.)
pl.add(cents, cdat * cents**2.)
