tjpcov.covariance_gaussian_fsky#

Module Contents#

Classes#

FourierGaussianFsky

Class to compute the Gaussian CellxCell cov. with the Knox formula.

RealGaussianFsky

Class to compute the Real space Gaussian cov. with the Knox formula.
class tjpcov.covariance_gaussian_fsky.FourierGaussianFsky(config)[source]#

Bases: tjpcov.covariance_builder.CovarianceFourier

Class to compute the Gaussian CellxCell cov. with the Knox formula.

Initialize the class with a config file or dictionary.

Parameters:

config (dict or str) – If dict, it returns the configuration dictionary directly. If string, it asumes a YAML file and parses it.

cov_type = 'gauss'[source]#
get_binning_info(binning='linear')[source]#

Get the ells for bins given the sacc object.

Parameters:

binning (str) – Binning type.

Returns:

  • ell (array): All the ells covered

  • ell_eff (array): The effective ells

  • ell_edges (array): The bandpower edges

Return type:

tuple

get_covariance_block(tracer_comb1, tracer_comb2, include_b_modes=True, for_real=False, lmax=None)[source]#

Compute a single covariance matrix for a given pair of C_ell.

Parameters:

  • tracer_comb1 (list) – List of the pair of tracer names of C_ell^1

  • tracer_comb2 (list) – List of the pair of tracer names of C_ell^2

  • include_b_modes (bool, optional) – If True, return the full SSC with zeros in for B-modes (if any). If False, return the non-zero block. This option cannot be modified through the configuration file to avoid breaking the compatibility with the NaMaster covariance.

  • for_real (bool, optional) – If True, returns the covariance before normalization and binning. It requires setting lmax.

  • lmax (int, optional) – Maximum ell up to which to compute the

  • covariance –

Returns:

The covariance block

Return type:

array

class tjpcov.covariance_gaussian_fsky.RealGaussianFsky(config)[source]#

Bases: tjpcov.covariance_builder.CovarianceProjectedReal

Class to compute the Real space Gaussian cov. with the Knox formula.

It projects the the Fourier space Gaussian covariance into the real space.

Initialize the class with a config file or dictionary.

Parameters:

config (dict or str) – If dict, it returns the configuration dictionary directly. If string, it asumes a YAML file and parses it.

cov_type = 'gauss'[source]#
fourier[source]#
_get_fourier_block(tracer_comb1, tracer_comb2)[source]#

Return the Fourier covariance block for two pair of tracers.

Parameters:

  • tracer_comb1 (list) – List of the pair of tracer names of C_ell^1

  • tracer_comb2 (list) – List of the pair of tracer names of C_ell^2

Returns:

The Fourier space covariance matrix block

Return type:

array