noiseTY = noiseY
noisePY = np.sqrt(2.) * noiseTY
kmax = getMax(polComb, tellmaxY, pellmaxY)
i += 1
print((i, tellmaxY, pellmaxY, kmax, "delens:",
delensTolerance))
bin_edges = np.arange(kmin, kmax, dell) + dell
myNls.updateBins(bin_edges)
myNls.updateNoise(beamX,noiseTX,noisePX,tellminX,tellmaxX, \
pellminX,pellmaxX,beamY=beamY,noiseTY=noiseTY, \
noisePY=noisePY,tellminY=tellminY,tellmaxY=tellmaxY, \
pellminY=pellminY,pellmaxY=pellmaxY)
ls, Nls = myNls.getNl(polComb=polComb, halo=halo)
fileName = saveRoot + getFileNameString([
'gradCut', 'polComb', 'beamY', 'noiseY', 'grad',
'tellminY', 'pellminY', 'tellmaxY', 'pellmaxY', 'kmin',
'deg', 'px'
], [
gradCut, polComb, beamY, noiseY, lab, tellminY,
pellminY, tellmaxY, pellmaxY, kmin, deg, px
]) + ".txt"
np.savetxt(fileName, np.vstack((ls, Nls)).transpose())
if (polComb == 'EB' or polComb
== 'TB') and (delensTolerance is not None):
ls, Nls = myNls.iterativeDelens(
polComb, delensTolerance, halo)
pixScaleXarcmin=px,
pixScaleYarcmin=px)
bin_edges = np.arange(kellmin, kellmax, num_ells)
myNls = NlGenerator(lmap, theory, bin_edges, gradCut=gradCut)
myNls.updateNoise(beam, noiseT, noiseP, tellmin, tellmax, pellmin, pellmax)
####
pl = Plotter(scaleY='log') #,scaleX='log')
pl.add(ellkk, 4. * Clkk / 2. / np.pi)
# CHECK THAT NORM MATCHES HU/OK
for polComb, col in zip(polCombList, colorList):
if polComb == 'EB':
lsold, Nlsold, eff = myNls.iterativeDelens(polComb, 1.0, True)
else:
lsold, Nlsold = myNls.getNl(polComb=polComb, halo=halo)
try:
huFile = 'data/hu_' + polComb.lower() + '.csv'
huell, hunl = np.loadtxt(huFile, unpack=True, delimiter=',')
except:
huFile = 'data/hu_' + polComb[::-1].lower() + '.csv'
huell, hunl = np.loadtxt(huFile, unpack=True, delimiter=',')
pl.add(Ls,
4. * crosses[polComb + polComb] / 2. / np.pi,
color=col,
label=polComb)
#pl.add(Ls,4.*Nls[polComb]/2./np.pi,color=col,alpha=0.2)
pl.add(lsold, 4. * Nlsold / 2. / np.pi, color=col, alpha=1.0, ls="-.")
#pl.add(huell,hunl,ls='--',color=col)
