tjpcov.covariance_gaussian_fsky
===============================

.. py:module:: tjpcov.covariance_gaussian_fsky


Classes
-------

.. autoapisummary::

   tjpcov.covariance_gaussian_fsky.FourierGaussianFsky
   tjpcov.covariance_gaussian_fsky.RealGaussianFsky


Module Contents
---------------

.. py:class:: FourierGaussianFsky(config)

   Bases: :py:obj:`tjpcov.covariance_builder.CovarianceFourier`


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

   Initialize the class with a config file or dictionary.

   :param config: If dict, it returns the configuration
                  dictionary directly. If string, it asumes a YAML file and
                  parses it.
   :type config: dict or str


   .. py:attribute:: cov_type
      :value: 'gauss'



   .. py:attribute:: fsky


   .. py:method:: get_binning_info(binning='linear')

      Get the ells for bins given the sacc object.

      :param binning: Binning type.
      :type binning: str

      :returns:     - ell (array): All the ells covered
                    - ell_eff (array): The effective ells
                    - ell_edges (array): The bandpower edges
      :rtype: tuple



   .. py:method:: get_covariance_block(tracer_comb1, tracer_comb2, include_b_modes=True, for_real=False, lmax=None)

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

      :param tracer_comb1: List of the pair of tracer names of C_ell^1
      :type tracer_comb1: list
      :param tracer_comb2: List of the pair of tracer names of C_ell^2
      :type tracer_comb2: list
      :param include_b_modes: 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.
      :type include_b_modes: bool, optional
      :param for_real: If True, returns the covariance before
                       normalization and binning. It requires setting lmax.
      :type for_real: bool, optional
      :param lmax: Maximum ell up to which to compute the
      :type lmax: int, optional
      :param covariance:

      :returns: The covariance block
      :rtype: array



.. py:class:: RealGaussianFsky(config)

   Bases: :py:obj:`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.

   :param config: If dict, it returns the configuration
                  dictionary directly. If string, it asumes a YAML file and
                  parses it.
   :type config: dict or str


   .. py:attribute:: cov_type
      :value: 'gauss'



   .. py:attribute:: fourier
      :value: None



   .. py:attribute:: fsky


   .. py:method:: _get_fourier_block(tracer_comb1, tracer_comb2)

      Return the Fourier covariance block for two pair of tracers.

      :param tracer_comb1: List of the pair of tracer names of C_ell^1
      :type tracer_comb1: list
      :param tracer_comb2: List of the pair of tracer names of C_ell^2
      :type tracer_comb2: list

      :returns: The Fourier space covariance matrix block
      :rtype: array