def compute_coupling_coefficients(self,
fla1,
fla2,
flb1=None,
flb2=None,
lmax=None,
n_iter=3,
l_toeplitz=-1,
l_exact=-1,
dl_band=-1):
"""
Computes coupling coefficients of the Gaussian covariance \
between the power spectra of two pairs of NmtField objects \
(fla1, fla2, flb1 and flb2). Note that you can reuse this \
workspace for the covariance of power spectra between any \
pairs of fields as long as the fields have the same masks \
as those passed to this function, and as long as the binning \
scheme used are also the same.
:param NmtField fla1,fla2: fields contributing to the first \
power spectrum whose covariance you want to compute.
:param NmtField flb1,flb2: fields contributing to the second \
power spectrum whose covariance you want to compute. If \
None, fla1,fla2 will be used.
:param n_iter: number of iterations when computing a_lms.
:param l_toeplitz: if a positive number, the Toeplitz approximation \
described in Louis et al. 2020 (arXiv:2010.14344) will be used. \
In that case, this quantity corresponds to ell_toeplitz in Fig. \
3 of that paper.
:param l_exact: if `l_toeplitz>0`, this quantity corresponds to \
ell_exact in Fig. 3 of Louis et al. 2020. Ignored if \
`l_toeplitz<=0`.
:param dl_band: if `l_toeplitz>0`, this quantity corresponds to \
Delta ell_band in Fig. 3 of Louis et al. 2020. Ignored if \
`l_toeplitz<=0`.
"""
if flb1 is None:
flb1 = fla1
if flb2 is None:
flb2 = fla2
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
ns = fla1.fl.cs.n_eq
if (fla2.fl.cs.n_eq != ns) or (flb1.fl.cs.n_eq != ns) or \
(flb2.fl.cs.n_eq != ns):
raise ValueError("Everything should have the same resolution!")
if lmax is None:
lmax = lib.get_lmax_from_cs_py(fla1.fl.cs)
_toeplitz_sanity(l_toeplitz, l_exact, dl_band, lmax, fla1, flb1)
self.wsp = lib.covar_workspace_init_py(fla1.fl, fla2.fl, flb1.fl,
flb2.fl, lmax, n_iter,
l_toeplitz, l_exact, dl_band)
def read_from(self, fname):
"""
Reads the contents of an NmtCovarianceWorkspace object from a file (encoded using an internal binary format).
:param str fname: input file name
"""
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
self.wsp = lib.read_covar_workspace(fname)
def read_from(self, fname):
"""
Reads the contents of an NmtCovarianceWorkspace object \
from a FITS file.
:param str fname: input file name
"""
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
self.wsp = lib.read_covar_workspace(fname)
def read_from(self, fname, force_spin0_only=False):
"""
Reads the contents of an NmtCovarianceWorkspace object \
from a FITS file.
:param str fname: input file name
:param bool force_spin0_only: if `True`, only spin-0 \
combinations will be read and stored.
"""
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
self.wsp = lib.read_covar_workspace(fname, int(force_spin0_only))
def compute_coupling_coefficients(self, wa, wb):
"""
Computes coupling coefficients of the Gaussian covariance between the power spectra computed using wa and wb (two NmtWorkspace objects).
:param NmtWorkspace wa,wb: workspaces used to compute the two power spectra whose covariance matrix you want to compute.
"""
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
ns = wa.wsp.nside
if wa.wsp.nside != wb.wsp.nside:
raise ValueError("Everything should have the same resolution!")
if (wa.wsp.ncls != 1) or (wb.wsp.ncls != 1):
raise ValueError("Gaussian covariances only supported for spin-0 fields")
self.wsp = lib.covar_workspace_init_py(wa.wsp, wb.wsp)
def compute_coupling_coefficients(self,
fla1,
fla2,
flb1=None,
flb2=None,
lmax=None,
n_iter=3):
"""
Computes coupling coefficients of the Gaussian covariance \
between the power spectra of two pairs of NmtField objects \
(fla1, fla2, flb1 and flb2). Note that you can reuse this \
workspace for the covariance of power spectra between any \
pairs of fields as long as the fields have the same masks \
as those passed to this function, and as long as the binning \
scheme used are also the same.
:param NmtField fla1,fla2: fields contributing to the first \
power spectrum whose covariance you want to compute.
:param NmtField flb1,flb2: fields contributing to the second \
power spectrum whose covariance you want to compute. If \
None, fla1,fla2 will be used.
:param n_iter: number of iterations when computing a_lms.
"""
if flb1 is None:
flb1 = fla1
if flb2 is None:
flb2 = fla2
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None
ns = fla1.fl.cs.n_eq
if (fla2.fl.cs.n_eq != ns) or (flb1.fl.cs.n_eq != ns) or \
(flb2.fl.cs.n_eq != ns):
raise ValueError("Everything should have the same resolution!")
if lmax is None:
lmax = lib.get_lmax_from_cs_py(fla1.fl.cs)
self.wsp = lib.covar_workspace_init_py(fla1.fl, fla2.fl, flb1.fl,
flb2.fl, lmax, n_iter)
def __del__(self):
if self.wsp is not None:
lib.covar_workspace_free(self.wsp)
self.wsp = None