def LensedSimPolMaps(m0,ell,Cell_TT,Cell_EE,Cell_TE,Cell_BB=None,nUp=3,bufferFactor=1):
m = liteMap.getEmptyMapWithDifferentDims(m0,m0.Ny*nUp,m0.Nx*nUp)
T_map,Q_map,U_map =liteMapPol.SimPolMapsFromEandB(m,ell,Cell_TT,Cell_EE,Cell_TE,Cell_BB=Cell_BB,bufferFactor=1)
phi = liteMap.liteMapFromFits("phikappa/phiMapHiRes.fits")
alpha = phi.takeGradient()
iy,ix = numpy.mgrid[0:phi.Ny,0:phi.Nx]
iyf = iy.flatten()
ixf = ix.flatten()
a = numpy.array(alpha.gradX.data/ alpha.gradX.pixScaleX,dtype='int64')
b = numpy.array(alpha.gradY.data/ alpha.gradY.pixScaleY,dtype='int64')
iyLensed = iyf.copy()
ixLensed = ixf.copy()
iyLensed[:] = iyf[:] + b.flatten()
ixLensed[:] = ixf[:] + a.flatten()
id = numpy.where((ixLensed > ixf.max()) | (ixLensed < ixf.min()))
id2 = numpy.where((iyLensed > iyf.max()) | (iyLensed < iyf.min()))
ixLensed[id] = ixf[id]
iyLensed[id2] = iyf[id2]
lensed_T_map=T_map.copy()
lensed_Q_map=Q_map.copy()
lensed_U_map=U_map.copy()
lensed_T_map.data[iyf,ixf] = T_map.data[iyLensed,ixLensed]
lensed_Q_map.data[iyf,ixf] = Q_map.data[iyLensed,ixLensed]
lensed_U_map.data[iyf,ixf] = U_map.data[iyLensed,ixLensed]
lensed_T_mapLo = m0.copy()
lensed_T_mapLo = liteMap.resampleFromHiResMap(lensed_T_map,m0)
lensed_Q_mapLo = m0.copy()
lensed_Q_mapLo = liteMap.resampleFromHiResMap(lensed_Q_map,m0)
lensed_U_mapLo = m0.copy()
lensed_U_mapLo = liteMap.resampleFromHiResMap(lensed_U_map,m0)
return(lensed_T_mapLo,lensed_Q_mapLo,lensed_U_mapLo)
def GenerateAndSaveLensedSimPolMaps(m0,phi,ell,Cell_TT,Cell_EE,Cell_TE,nUp,iterNum,Cell_BB=None,bufferFactor=1):
try:
os.mkdir('unlensedCMBMaps')
os.mkdir('lensedCMBMaps')
except:
pass
m = liteMap.getEmptyMapWithDifferentDims(m0,m0.Ny*nUp,m0.Nx*nUp)
T_map,Q_map,U_map =liteMapPol.SimPolMapsFromEandB(m,ell,Cell_TT,Cell_EE,Cell_TE,Cell_BB=Cell_BB,bufferFactor=1)
T_map.data[:]=T_map.data[:]-numpy.mean(T_map.data[:])
Q_map.data[:]=Q_map.data[:]-numpy.mean(Q_map.data[:])
U_map.data[:]=U_map.data[:]-numpy.mean(U_map.data[:])
T_mapLo = m0.copy()
T_mapLo = liteMap.resampleFromHiResMap(T_map,m0)
T_mapLo.writeFits('unlensedCMBMaps/T_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed T_map low resolution done"
del T_mapLo
Q_mapLo = m0.copy()
Q_mapLo = liteMap.resampleFromHiResMap(Q_map,m0)
Q_mapLo.writeFits('unlensedCMBMaps/Q_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed Q_map low resolution done"
del Q_mapLo
U_mapLo = m0.copy()
U_mapLo = liteMap.resampleFromHiResMap(U_map,m0)
U_mapLo.writeFits('unlensedCMBMaps/U_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed U_map low resolution done"
del U_mapLo
alpha = phi.takeGradient()
iy,ix = numpy.mgrid[0:phi.Ny,0:phi.Nx]
iyf = iy.flatten()
ixf = ix.flatten()
a = numpy.array(alpha.gradX.data/ alpha.gradX.pixScaleX,dtype='int64')
b = numpy.array(alpha.gradY.data/ alpha.gradY.pixScaleY,dtype='int64')
iyLensed = iyf.copy()
ixLensed = ixf.copy()
iyLensed[:] = iyf[:] + b.flatten()
ixLensed[:] = ixf[:] + a.flatten()
id = numpy.where(ixLensed > ixf.max())
id2 = numpy.where(iyLensed > iyf.max())
ixLensed[id] = ixLensed[id] - phi.Nx
iyLensed[id2] = iyLensed[id2] - phi.Ny
id = numpy.where(ixLensed < ixf.min())
id2 = numpy.where(iyLensed < iyf.min())
ixLensed[id] = ixLensed[id] + phi.Nx
iyLensed[id2] = iyLensed[id2] + phi.Ny
lensed_T_map=T_map.copy()
lensed_Q_map=Q_map.copy()
lensed_U_map=U_map.copy()
lensed_T_map.data[iyf,ixf] = T_map.data[iyLensed,ixLensed]
lensed_Q_map.data[iyf,ixf] = Q_map.data[iyLensed,ixLensed]
lensed_U_map.data[iyf,ixf] = U_map.data[iyLensed,ixLensed]
lensed_T_mapLo = m0.copy()
lensed_T_mapLo = liteMap.resampleFromHiResMap(lensed_T_map,m0)
lensed_T_mapLo.writeFits('lensedCMBMaps/lensed_T_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed T_map low resolution done"
del lensed_T_mapLo
lensed_Q_mapLo = m0.copy()
lensed_Q_mapLo = liteMap.resampleFromHiResMap(lensed_Q_map,m0)
lensed_Q_mapLo.writeFits('lensedCMBMaps/lensed_Q_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed Q_map low resolution done"
del lensed_Q_mapLo
lensed_U_mapLo = m0.copy()
lensed_U_mapLo = liteMap.resampleFromHiResMap(lensed_U_map,m0)
lensed_U_mapLo.writeFits('lensedCMBMaps/lensed_U_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed U_map low resolution done"
del lensed_U_mapLo
return
def GenerateAndSaveLensedSimPolMaps(m0,phi,ell,Cell_TT,Cell_EE,Cell_TE,nUp,iterNum,Cell_BB=None,bufferFactor=1):
try:
os.mkdir('unlensedCMBMaps')
os.mkdir('lensedCMBMaps')
except:
pass
m = liteMap.getEmptyMapWithDifferentDims(m0,m0.Ny*nUp,m0.Nx*nUp)
T_map,Q_map,U_map =liteMapPol.SimPolMapsFromEandB(m,ell,Cell_TT,Cell_EE,Cell_TE,Cell_BB=Cell_BB,bufferFactor=1)
T_map.data[:]=T_map.data[:]-numpy.mean(T_map.data[:])
Q_map.data[:]=Q_map.data[:]-numpy.mean(Q_map.data[:])
U_map.data[:]=U_map.data[:]-numpy.mean(U_map.data[:])
T_mapLo = m0.copy()
T_mapLo = liteMap.resampleFromHiResMap(T_map,m0)
T_mapLo.writeFits('unlensedCMBMaps/T_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed T_map low resolution done"
del T_mapLo
Q_mapLo = m0.copy()
Q_mapLo = liteMap.resampleFromHiResMap(Q_map,m0)
Q_mapLo.writeFits('unlensedCMBMaps/Q_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed Q_map low resolution done"
del Q_mapLo
U_mapLo = m0.copy()
U_mapLo = liteMap.resampleFromHiResMap(U_map,m0)
U_mapLo.writeFits('unlensedCMBMaps/U_map_%03d.fits'%(iterNum),overWrite=True)
print "unlensed U_map low resolution done"
del U_mapLo
alpha = phi.takeGradient()
iy,ix = numpy.mgrid[0:phi.Ny,0:phi.Nx]
iyf = iy.flatten()
ixf = ix.flatten()
a = numpy.array(alpha.gradX.data/ alpha.gradX.pixScaleX,dtype='int64')
b = numpy.array(alpha.gradY.data/ alpha.gradY.pixScaleY,dtype='int64')
iyLensed = iyf.copy()
ixLensed = ixf.copy()
iyLensed[:] = iyf[:] + b.flatten()
ixLensed[:] = ixf[:] + a.flatten()
id = numpy.where(ixLensed > ixf.max())
id2 = numpy.where(iyLensed > iyf.max())
ixLensed[id] = ixLensed[id] - phi.Nx
iyLensed[id2] = iyLensed[id2] - phi.Ny
id = numpy.where(ixLensed < ixf.min())
id2 = numpy.where(iyLensed < iyf.min())
ixLensed[id] = ixLensed[id] + phi.Nx
iyLensed[id2] = iyLensed[id2] + phi.Ny
lensed_T_map=T_map.copy()
lensed_Q_map=Q_map.copy()
lensed_U_map=U_map.copy()
lensed_T_map.data[iyf,ixf] = T_map.data[iyLensed,ixLensed]
lensed_Q_map.data[iyf,ixf] = Q_map.data[iyLensed,ixLensed]
lensed_U_map.data[iyf,ixf] = U_map.data[iyLensed,ixLensed]
lensed_T_mapLo = m0.copy()
lensed_T_mapLo = liteMap.resampleFromHiResMap(lensed_T_map,m0)
lensed_T_mapLo.writeFits('lensedCMBMaps/lensed_T_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed T_map low resolution done"
del lensed_T_mapLo
lensed_Q_mapLo = m0.copy()
lensed_Q_mapLo = liteMap.resampleFromHiResMap(lensed_Q_map,m0)
lensed_Q_mapLo.writeFits('lensedCMBMaps/lensed_Q_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed Q_map low resolution done"
del lensed_Q_mapLo
lensed_U_mapLo = m0.copy()
lensed_U_mapLo = liteMap.resampleFromHiResMap(lensed_U_map,m0)
lensed_U_mapLo.writeFits('lensedCMBMaps/lensed_U_map_%03d.fits'%(iterNum),overWrite=True)
print "lensed U_map low resolution done"
del lensed_U_mapLo
return