def initSim(ht,prof,ref_freq,bw,rf = None,filename= None,source='fake',noise = None):
if rf is None:
rf = np.abs(bw)/2.0
if ht.ndim == 1:
ht = ht[None,:]
CS = pycyc.CyclicSolver()
CS.ht0 = ht
if filename:
CS.filename = filename
else:
CS.filename = 'sim%s_%.1fMHz_%.1fms' % (source,bw,1000.0/ref_freq)
CS.nchan = ht.shape[1]
CS.nlag = CS.nchan
CS.nphase = prof.shape[0]
CS.nbin = CS.nphase
CS.nharm = CS.nphase/2 + 1
CS.source = source
CS.nspec = ht.shape[0]
CS.dynamic_spectrum = np.zeros((CS.nspec,CS.nchan))
CS.optimized_filters = np.zeros((CS.nspec,CS.nchan),dtype='complex')
CS.intrinsic_profiles = np.zeros((CS.nspec,CS.nbin))
CS.nopt = 0
CS.nloop = 0
CS.nopt = 0
CS.ref_freq = ref_freq
CS.bw = bw
CS.ref_phase = 0
CS.rf = rf
CS.hf_prev = np.ones((CS.nchan,),dtype='complex')
CS.pp_int = np.zeros((CS.nphase)) #intrinsic profile
CS.pp_ref = prof.copy()
CS.ph_ref = pycyc.phase2harm(CS.pp_ref)
CS.ph_ref = pycyc.normalize_profile(CS.ph_ref)
CS.ph_ref[0] = 0
CS.s0 = CS.ph_ref.copy()
CS.data = np.empty((CS.nspec,1,CS.nchan,CS.nphase), dtype='complex')
for k in range(CS.nspec):
CS.data[k,0,:,:] = pycyc.cs2ps(CS.modelCS(ht[k,:]))
if noise is not None:
signal = np.abs(CS.data).sum()
CS.noise = noise
rn = (np.random.randn(CS.data.shape[0],CS.data.shape[1],CS.data.shape[2],CS.data.shape[3]).astype('complex')
+1j*np.random.randn(CS.data.shape[0],CS.data.shape[1],CS.data.shape[2],CS.data.shape[3]))
rnpow = np.abs(rn).sum()
fact = signal/rnpow
CS.data = CS.data + rn*(fact/noise)
return CS
def initSim(ht,prof=std_prof,ref_freq=ref_freq,bw=bw,noise = None):
CS = pycyc.CyclicSolver()
CS.ht0 = ht
CS.filename = 'sim1643'
CS.nchan = ht.shape[0]
CS.nlag = CS.nchan
CS.nphase = prof.shape[0]
CS.nharm = CS.nphase/2 + 1
CS.source = 'J1643-1224sim'
CS.nspec = 1
CS.dynamic_spectrum = np.zeros((CS.nspec,CS.nchan))
CS.optimized_filters = np.zeros((CS.nspec,CS.nchan),dtype='complex')
CS.nopt = 0
CS.ref_freq = ref_freq
CS.bw = bw
CS.ref_phase = 0
CS.rf = rf
CS.hf_prev = np.ones((CS.nchan,),dtype='complex')
CS.pp_int = np.zeros((CS.nphase)) #intrinsic profile
CS.pp_ref = prof.copy()
CS.ph_ref = pycyc.phase2harm(CS.pp_ref)
CS.ph_ref = pycyc.normalize_profile(CS.ph_ref)
CS.ph_ref[0] = 0
CS.s0 = CS.ph_ref.copy()
csm = CS.modelCS(ht)
CS.data = pycyc.cs2ps(csm)[None,None,:,:]
CS.cs = csm.copy()
if noise is not None:
fact = CS.data.std()*noise
CS.data += (np.random.randn(CS.data.shape[2],CS.data.shape[3]).astype('complex')+1j*np.random.randn(CS.data.shape[2],CS.data.shape[3]))*fact
return CS
def initSim(ht,
prof,
ref_freq,
bw,
rf=None,
filename=None,
source='fake',
noise=None):
if rf is None:
rf = np.abs(bw) / 2.0
if ht.ndim == 1:
ht = ht[None, :]
CS = pycyc.CyclicSolver()
CS.ht0 = ht
if filename:
CS.filename = filename
else:
CS.filename = 'sim%s_%.1fMHz_%.1fms' % (source, bw, 1000.0 / ref_freq)
CS.nchan = ht.shape[1]
CS.nlag = CS.nchan
CS.nphase = prof.shape[0]
CS.nbin = CS.nphase
CS.nharm = CS.nphase / 2 + 1
CS.source = source
CS.nspec = ht.shape[0]
CS.dynamic_spectrum = np.zeros((CS.nspec, CS.nchan))
CS.optimized_filters = np.zeros((CS.nspec, CS.nchan), dtype='complex')
CS.intrinsic_profiles = np.zeros((CS.nspec, CS.nbin))
CS.nopt = 0
CS.nloop = 0
CS.nopt = 0
CS.ref_freq = ref_freq
CS.bw = bw
CS.ref_phase = 0
CS.rf = rf
CS.hf_prev = np.ones((CS.nchan, ), dtype='complex')
CS.pp_int = np.zeros((CS.nphase)) #intrinsic profile
CS.pp_ref = prof.copy()
CS.ph_ref = pycyc.phase2harm(CS.pp_ref)
CS.ph_ref = pycyc.normalize_profile(CS.ph_ref)
CS.ph_ref[0] = 0
CS.s0 = CS.ph_ref.copy()
CS.data = np.empty((CS.nspec, 1, CS.nchan, CS.nphase), dtype='complex')
for k in range(CS.nspec):
CS.data[k, 0, :, :] = pycyc.cs2ps(CS.modelCS(ht[k, :]))
if noise is not None:
signal = np.abs(CS.data).sum()
CS.noise = noise
rn = (np.random.randn(CS.data.shape[0], CS.data.shape[1],
CS.data.shape[2],
CS.data.shape[3]).astype('complex') +
1j * np.random.randn(CS.data.shape[0], CS.data.shape[1],
CS.data.shape[2], CS.data.shape[3]))
rnpow = np.abs(rn).sum()
fact = signal / rnpow
CS.data = CS.data + rn * (fact / noise)
return CS