elif options.whichtdi == 'optimal': IIs = ['AE', 'AT', 'ET'] if csddir not in glob.glob(csddir): os.system('mkdir %s' % csddir) for day in options.days: print "~~~~~~~ Day %d ~~~~~~~" % day orfids = [(options.tditype, options.tdigen, II[0], options.tditype, options.tdigen, II[1], options.f0, options.df, options.Nf, day) for II in IIs] orfpaths = [( orfdir + 'tdiI_%s_%s_%s_tdiJ_%s_%s_%s_lmax_20_f0_%f_df_%f_Nf_%d/data_nlon_120_nlat_61/orf_d%03d.pkl' % orfid) for orfid in orfids] orfs = [AS.OrfMultipleMoments(orfpath) for orfpath in orfpaths] PIJs = [AS.Convolve(orf, skymap, options.GWslope) for orf in orfs] P12, P13, P23 = PIJs fdata = P12.Offset1 + P12.Cadence1 * np.arange(P12.data.shape[0]) f = AS.Coarsable(fdata, Offset1=P12.Offset1, Cadence1=P12.Cadence1) csddict = {'f': f, 'AE': P12, 'AT': P13, 'ET': P23} file = open(csddir + 'd%03d.pkl' % day, 'wb') cpkl.dump(csddict, file, -1) file.close()
import numpy as np import cPickle as cpkl import synthlisa import myLISAmodule as mlisar import AnisotropySearch as AS days = range(1, 365 + 1) csddir = 'csd_ana' Ppath = '' norm_factor = '' #If orfdir = '' GWSpectralSlope, H0 = 0, 1.0 IJs = ['AE', 'AT', 'ET'] file = open(Ppath, 'rb') skymap = cpkl.load(file) file.close() for day in days: csddict = {} for IJ in IJs: orf = AS.OrfMultipleMoments(orfdir + '/' + IJ + '/d%03d.pkl' % day) csddict[IJ] = AS.Convolve(orf, skymap, GWSpectralslope, H0) csddict['f'] = orf.f if csddir not in glob.glob(csddir): os.system('mkdir %s' % csddir) file = open(csddir + '/d%03d.pkl' % day, 'wb') cpkl.dump(csddict, file, -1) file.close()