import pylab # Load experimental and cosmology settings (p, cosmo) import experiment p = experiment.p cosmo = experiment.cosmo # (For testing) RESCALE_CLUSTER_SIZE = 1 # Enlarge cluster angular size by this factor RESCALE_TSZ_AMP = 1 # Scale cluster tSZ signal amplitude by this factor RESCALE_KSZ_AMP = 1 # Scale cluster kSZ signal amplitude by this factor nsims = p['nsims'] # number of CMB simulations # Make directories for maps, results etc. mapDir = fist.check_dir_exists(experiment.mapDir) clusterDir = fist.check_dir_exists('sims/cluster') # Get experimental settings template, power_2d, beams, ninvs, freqs = fist.experiment_settings(p) mask=p['mask'] masks=[] print mask for k in freqs: if mask['apply']:
# Load data and instrumental specifications template, power_2d, beams, ninvs, freqs = fist.experiment_settings(p) # Speed up FFT by measuring #t=time.time() fft.rfft(ninvs[0].copy(),axes=[-2,-1],flags=['FFTW_MEASURE']) template_l = fft.fft(ninvs[0],axes=[-2,-1]) fft.irfft(template_l,axes=[-2,-1],flags=['FFTW_MEASURE']) #Create a directory for the results of the chain resultDir = fist.check_dir_exists('results') for n in range(nsims): datamaps=[] count=0 for k in freqs: datamaps+=[fist.litemap_from_fits(mapDir+'/data_%03d_%d.fits'%(n,k))] mask=fist.litemap_from_fits(mapDir+'/mask_%d.fits'%(k)) ninvs[count]*=mask.data count+=1