mapi,mapq,mapu=hp.synfast(spectra[1:],nside,fwhm=0,pixwin=True,new=True)
noisei1=np.random.randn(12*nside**2)*sigI
noiseq1=np.random.randn(12*nside**2)*sigQU
noiseu1=np.random.randn(12*nside**2)*sigQU
noisei2=np.random.randn(12*nside**2)*sigI
noiseq2=np.random.randn(12*nside**2)*sigQU
noiseu2=np.random.randn(12*nside**2)*sigQU
allmapsi1[i,:]=mapi[~mask]+noisei1[~mask]
allmapsq1[i,:]=mapq[~mask]+noiseq1[~mask]
allmapsu1[i,:]=mapu[~mask]+noiseu1[~mask]
allmapsi2[i,:]=mapi[~mask]+noisei2[~mask]
allmapsq2[i,:]=mapq[~mask]+noiseq2[~mask]
allmapsu2[i,:]=mapu[~mask]+noiseu2[~mask]
############ Auto
covii=qml.cov_from_maps(allmapsi1,allmapsi1)
coviq=qml.cov_from_maps(allmapsi1,allmapsq1)
coviu=qml.cov_from_maps(allmapsi1,allmapsu1)
covqi=qml.cov_from_maps(allmapsq1,allmapsi1)
covqq=qml.cov_from_maps(allmapsq1,allmapsq1)
covqu=qml.cov_from_maps(allmapsq1,allmapsu1)
covui=qml.cov_from_maps(allmapsu1,allmapsi1)
covuq=qml.cov_from_maps(allmapsu1,allmapsq1)
covuu=qml.cov_from_maps(allmapsu1,allmapsu1)
bigmatmc=np.array([[covii,coviq,coviu],[covqi,covqq,covqu],[covui,covuq,covuu]])
newmatmc=qml.allmat2bigmat(bigmatmc)
clf()
imshow(np.log10(np.abs(newmatmc)),interpolation='nearest')
colorbar()
############ Cross
mask=(np.arange(12*nside**2) >= nbpixok)
#### maps simulation
nbmc=1000
npix=np.size(where(mask==False))
allmapsi=np.zeros((nbmc,npix))
allmapsq=np.zeros((nbmc,npix))
allmapsu=np.zeros((nbmc,npix))
for i in np.arange(nbmc):
pyquad.progress_bar(i,nbmc)
mapi,mapq,mapu=hp.synfast(spectra[1:],nside,fwhm=0,pixwin=True,new=True)
allmapsi[i,:]=mapi[~mask]
allmapsq[i,:]=mapq[~mask]
allmapsu[i,:]=mapu[~mask]
covii=qml.cov_from_maps(allmapsi,allmapsi)
coviq=qml.cov_from_maps(allmapsi,allmapsq)
coviu=qml.cov_from_maps(allmapsi,allmapsu)
covqi=qml.cov_from_maps(allmapsq,allmapsi)
covqq=qml.cov_from_maps(allmapsq,allmapsq)
covqu=qml.cov_from_maps(allmapsq,allmapsu)
covui=qml.cov_from_maps(allmapsu,allmapsi)
covuq=qml.cov_from_maps(allmapsu,allmapsq)
covuu=qml.cov_from_maps(allmapsu,allmapsu)
clf()
subplot(3,3,1)
imshow(covii,interpolation='nearest')
title('II')