halo=True,
gradCut=10000,
verbose=True,
loadPickledNormAndFilters=loadFile,
savePickledNormAndFilters=saveFile)
modLMap = qest.N.modLMap
bin_edges = np.arange(2,kellmax,10)
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):
data2d = qest.N.Nlkk[polComb]
centers, Nlbinned = binInAnnuli(data2d, modLMap, bin_edges)
try:
huFile = '/astro/u/msyriac/repos/cmb-lensing-projections/data/NoiseCurvesKK/hu_'+polComb.lower()+'.csv'
huell,hunl = np.loadtxt(huFile,unpack=True,delimiter=',')
except:
huFile = '/astro/u/msyriac/repos/cmb-lensing-projections/data/NoiseCurvesKK/hu_'+polComb[::-1].lower()+'.csv'
huell,hunl = np.loadtxt(huFile,unpack=True,delimiter=',')
pl.add(centers,4.*Nlbinned/2./np.pi,color=col)
pl.add(huell,hunl,ls='--',color=col)
pl.done("tests/output/testbin.png")
for j, polComb in enumerate(polCombList):
kappa = qest.getKappa(polComb)
# pl = Plotter()
# pl.plot2d(fftshift(qest.AL[polComb]))
# pl.done("al.png")
# sys.exit()
reconLm = lensedTLm.copy()
reconLm.data[:, :] = kappa[:, :].real
print "crossing with input"
p2d = ft.powerFromLiteMap(kappaLm, reconLm, applySlepianTaper=False)
centers, means = stats.binInAnnuli(p2d.powerMap, p2d.modLMap,
bin_edges)
listCrossPower[polComb].append(means)
p2d = ft.powerFromLiteMap(reconLm, applySlepianTaper=False)
centers, means = stats.binInAnnuli(p2d.powerMap, p2d.modLMap,
bin_edges)
listReconPower[polComb].append(means)
p2d = ft.powerFromLiteMap(kappaLm, applySlepianTaper=False)
centers, means = stats.binInAnnuli(p2d.powerMap, p2d.modLMap, bin_edges)
if k == 0: totInputPower = (means.copy() * 0.).astype(dtype=np.float64)
totInputPower = totInputPower + means
if rank != 0:
noiseX2dTEB=[nT, nP, nP],
noiseY2dTEB=[nT, nP, nP],
fmaskX2dTEB=[fMask] * 3,
fmaskY2dTEB=[fMask] * 3,
fmaskKappa=fMaskK,
doCurl=False,
TOnly=True,
halo=True,
gradCut=10000,
verbose=True)
# CHECK THAT NORM MATCHES HU/OK
data2d = qest.AL['TT']
modLMap = qest.N.modLMap
bin_edges = np.arange(2, kellmax, 10)
centers, Nlbinned = binInAnnuli(data2d, modLMap, bin_edges)
huFile = '/astro/u/msyriac/repos/cmb-lensing-projections/data/NoiseCurvesKK/hu_tt.csv'
huell, hunl = np.loadtxt(huFile, unpack=True, delimiter=',')
pl = Plotter(scaleY='log', scaleX='log')
pl.add(ellkk, 4. * Clkk / 2. / np.pi)
pl.add(centers, 4. * Nlbinned / 2. / np.pi) #,ls="none",marker="o")
pl.add(huell, hunl, ls='--') #,ls="none",marker="o")
pl.done("testbin.png")
passMap = bigMap[:, :] * window[:, :]
passMap = passMap - passMap.mean()
if k == 0:
pl = Plotter()