try: os.makedirs(args.outDir) except OSError: pass print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'] # fill in pulsar class global psr psr = [PALpulsarInit.pulsar(pulsargroup[key],addGmatrix=True, addNoise=True) for key in pulsargroup] if args.best != 0: print 'Using best {0} pulsars'.format(args.best) rms = np.array([p.rms() for p in psr]) ind = np.argsort(rms) psr = [psr[ii] for ii in ind[0:args.best]] for p in psr: print 'Pulsar {0} has {1} ns weighted rms'.format(p.name,p.rms()*1e9) npsr = len(psr) pfile.close()
# parse arguments (args, x) = parser.parse_args() ##### Begin Code ##### print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'] # fill in pulsar class psr = [ PALpulsarInit.pulsar(pulsargroup[key], addNoise=True) for key in pulsargroup ] # close hdf5 file pfile.close() # number of pulsars npsr = len(psr) # make sure all pulsar have same reference time tt = [] for p in psr: tt.append(np.min(p.toas)) # find reference time
# parse arguments (args, x) = parser.parse_args() ##### Begin Code ##### print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'] # fill in pulsar class psr = [ PALpulsarInit.pulsar(pulsargroup[key], addNoise=True, addGmatrix=True) for key in pulsargroup ] # close hdf5 file pfile.close() # number of pulsars npsr = len(psr) # make sure all pulsar have same reference time tt = [] for p in psr: tt.append(np.min(p.toas)) # find reference time
try: os.makedirs(args.outDir) except OSError: pass print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'] # fill in pulsar class global psr psr = [PALpulsarInit.pulsar(pulsargroup[key],addGmatrix=True, addNoise=True) for key in pulsargroup] if args.best != 0: print 'Using best {0} pulsars'.format(args.best) rms = np.array([p.rms() for p in psr]) ind = np.argsort(rms) psr = [psr[ii] for ii in ind[0:args.best]] for p in psr: print 'Pulsar {0} has {1} ns weighted rms'.format(p.name,p.rms()*1e9) npsr = len(psr) # get injection parameters if args.inj:
if not os.path.exists(args.outDir): try: os.makedirs(args.outDir) except OSError: pass print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'][args.pname] # fill in pulsar class psr = PALpulsarInit.pulsar(pulsargroup, addGmatrix=True) # initialize fourier design matrix if args.nmodes != 0: F, f = PALutils.createfourierdesignmatrix(psr.toas, args.nmodes, freq=True) Tspan = psr.toas.max() - psr.toas.min() ##fsred = np.array([1.599558028614668e-07, 5.116818355403073e-08]) # 1855 #fsred = np.array([9.549925860214369e-08]) # 1909 #fsred = np.array([1/Tspan, 9.772372209558111e-08]) # 1909 # #F = np.zeros((psr.ntoa, 2*len(fsred))) #F[:,0::2] = np.cos(2*np.pi*np.outer(psr.toas, fsred)) #F[:,1::2] = np.sin(2*np.pi*np.outer(psr.toas, fsred)) # get G matrices
if not os.path.exists(args.outDir): try: os.makedirs(args.outDir) except OSError: pass print 'Reading in HDF5 file' # import hdf5 file pfile = h5.File(args.h5file, 'r') # define the pulsargroup pulsargroup = pfile['Data']['Pulsars'][args.pname] # fill in pulsar class psr = PALpulsarInit.pulsar(pulsargroup, addGmatrix=True) # initialize fourier design matrix if args.nmodes != 0: F, f = PALutils.createfourierdesignmatrix(psr.toas, args.nmodes, freq=True) # get G matrices psr.G = PALutils.createGmatrix(psr.dmatrix) # pre compute diagonalized efac + equad white noise model efac = np.dot(psr.G.T, np.dot(np.diag(psr.err**2), psr.G)) equad = np.dot(psr.G.T, psr.G) L = np.linalg.cholesky(equad) Linv = np.linalg.inv(L) sand = np.dot(Linv, np.dot(efac, Linv.T)) u,s,v = np.linalg.svd(sand)