def read_from(self, fname):
"""
Reads the contents of an NmtCovarianceWorkspaceFlat 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_flat_free(self.wsp)
self.wsp = None
self.wsp = lib.read_covar_workspace_flat(fname)
def read_from(self, fname):
"""
Reads the contents of an NmtCovarianceWorkspaceFlat object from a \
FITS file.
:param str fname: input file name
"""
if self.wsp is not None:
lib.covar_workspace_flat_free(self.wsp)
self.wsp = None
self.wsp = lib.read_covar_workspace_flat(fname)
def compute_coupling_coefficients(self, wa, wb):
"""
Computes coupling coefficients of the Gaussian covariance between the power spectra computed using wa and wb (two NmtWorkspaceFlat objects).
:param NmtWorkspaceFlat wa,wb: workspaces used to compute the two power spectra whose covariance matrix you want to compute.
"""
if (wa.wsp.fs.nx != wb.wsp.fs.nx) or (wa.wsp.fs.ny != wb.wsp.fs.ny):
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")
if self.wsp is not None:
lib.covar_workspace_flat_free(self.wsp)
self.wsp = None
self.wsp = lib.covar_workspace_flat_init_py(wa.wsp, wb.wsp)
def compute_coupling_coefficients(self,
fla1,
fla2,
bin_a,
flb1=None,
flb2=None,
bin_b=None):
"""
Computes coupling coefficients of the Gaussian covariance between \
the power spectra of two pairs of NmtFieldFlat 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 NmtFieldFlat fla1,fla2: fields contributing to the first \
power spectrum whose covariance you want to compute.
:param NmtBinFlat bin_a: binning scheme for the first power \
spectrum.
:param NmtFieldFlat flb1,flb2: fields contributing to the second \
power spectrum whose covariance you want to compute. If None, \
fla1,fla2 will be used.
:param NmtBinFlat bin_b: binning scheme for the second power \
spectrum. If none, bin_a will be used.
"""
if flb1 is None:
flb1 = fla1
if flb2 is None:
flb2 = fla2
if bin_b is None:
bin_b = bin_a
if (fla1.fl.fs.nx != fla2.fl.fs.nx) or \
(fla1.fl.fs.ny != fla2.fl.fs.ny) or \
(fla1.fl.fs.nx != flb1.fl.fs.nx) or \
(fla1.fl.fs.ny != flb1.fl.fs.ny) or \
(fla1.fl.fs.nx != flb2.fl.fs.nx) or \
(fla1.fl.fs.ny != flb2.fl.fs.ny):
raise ValueError("Everything should have the same resolution!")
if self.wsp is not None:
lib.covar_workspace_flat_free(self.wsp)
self.wsp = None
self.wsp = lib.covar_workspace_flat_init_py(fla1.fl, fla2.fl,
bin_a.bin, flb1.fl,
flb2.fl, bin_b.bin)
def __del__(self):
if self.wsp is not None:
lib.covar_workspace_flat_free(self.wsp)
self.wsp = None
