def __call__(self, TEBlms):
TQUlms = SM.TEB2TQUlms(_type, self.cov.lib_skyalm, TEBlms)
for i, f in enumerate(_type):
self.cov.apply_alm(f, TQUlms[i], inplace=True)
ret = SM.apply_pinvTEBmat(_type, self.lib_alm, self.cov.cls,
TEBlms) + SM.TQU2TEBlms(
_type, self.lib_alm, TQUlms)
return filtTEBlms(ret, self.cov)
def calc_prep(maps, cov, *args, **kwargs):
"""
Pre operation for primordial CMB modes.
R^t Ni data projected onto T E alms
"""
print "This is calc prep for %s W. Filtering" % _type, _prefix
TQUalms = np.empty((len(_type), cov.lib_skyalm.alm_size), dtype=complex)
for i, f in enumerate(_type):
_map = cov.apply_map(f, maps[i], inplace=False)
TQUalms[i] = cov.apply_Rt(f, _map)
return filtTEBlms(SM.TQU2TEBlms(_type, cov.lib_skyalm, TQUalms), cov)
def apply_fini_BINV(soltn, cov, maps, **kwargs):
"""
Output TEB skyalms shaped
B^t Cov^-1 d = B^t Ni data - (B^t Ni B) MLIK(data)
= B^t Ni (data - B MLIK(data))
"""
TQUmlik = SM.TEB2TQUlms(_type, cov.lib_skyalm,
apply_fini_MLIK(soltn, cov, maps, **kwargs))
for i, f in enumerate(_type):
_map = maps[i] - cov.apply_R(f, TQUmlik[i])
cov.apply_map(f, _map, inplace=True)
TQUmlik[i] = cov.apply_Rt(f, _map)
del _map
return SM.TQU2TEBlms(_type, cov.lib_skyalm, TQUmlik)
def MLIK2BINV(soltn, cov, maps, **kwargs):
"""
Output TEB skyalms shaped
B^t Cov^-1 d = B^t Ni data - (B^t Ni B) MLIK(data)
= B^t Ni (data - B MLIK(data))
"""
assert len(soltn) == TEBlen(_type)
assert len(maps) == TQUlen(_type), (maps.shape, _type)
TQUmlik = SM.TE2TQUlms(_type, cov.lib_skyalm, soltn)
for i, f in enumerate(_type):
_map = maps[i] - cov.apply_R(f, TQUmlik[i])
cov.apply_map(f, _map, inplace=True)
TQUmlik[i] = cov.apply_Rt(f, _map)
del _map
return opfilt_cinv.filtTEBlms(SMwBB.TQU2TEBlms(_type, cov.lib_skyalm, TQUmlik),cov)
def MLIK2BINV(soltn, cov, maps, **kwargs):
"""
Output TEB skyalms shaped
R^t Cov^-1 d = R^t Ni data - (R^t Ni R) MLIK(data)
= R^t Ni (data - R MLIK(data))
"""
assert len(soltn) == TEBlen(_type)
assert len(maps) == TQUlen(_type)
TQUmlik = SM.TEB2TQUlms(_type, cov.lib_skyalm, soltn)
for i, f in enumerate(_type):
_map = maps[i] - cov.apply_R(f, TQUmlik[i])
cov.apply_map(f, _map, inplace=True)
TQUmlik[i] = cov.apply_Rt(f, _map)
del _map
return SM.TQU2TEBlms(_type, cov.lib_skyalm, TQUmlik)
def apply_Rts(self, TQUtype, _maps):
"""
Apply tranposed transfer function, from T Q U real space to T E B skyalm.
B^t X
"""
assert TQUtype in ['T', 'QU', 'TQU']
assert _maps.shape == (len(TQUtype), self.lib_datalm.shape[0],
self.lib_datalm.shape[1]), (self.npix, TQUtype,
_maps.shape)
TEBtype = {'T': 'T', 'QU': 'EB', 'TQU': 'TEB'}[TQUtype]
alms = ffs_specmat.TQU2TEBlms(
TQUtype, self.lib_skyalm,
np.array([self._upg(self.lib_datalm.map2alm(_m)) for _m in _maps]))
TEBret = np.zeros_like(alms)
for i, f in enumerate(TEBtype):
for j, g in enumerate(TEBtype):
cl_t = self.cltransf_dict.get(f + g, None) # transposed
if cl_t is not None:
TEBret[i] += self.lib_skyalm.almxfl(alms[j], cl_t)
return TEBret