tjpcov.covariance_fourier_ssc_fsky
==================================

.. py:module:: tjpcov.covariance_fourier_ssc_fsky


Classes
-------

.. autoapisummary::

   tjpcov.covariance_fourier_ssc_fsky.FourierSSCHaloModelFsky


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

.. py:class:: FourierSSCHaloModelFsky(config)

   Bases: :py:obj:`tjpcov.covariance_fourier_ssc.FourierSSCHaloModel`


   Class to compute the CellxCell Halo Model Super Sample Covariance
       with the fsky approximation.

   The SSC is computed in CCL with the "linear bias" approximation using
   :func:`pyccl.halos.halo_model.halomod_Tk3D_SSC_linear_bias`.

   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: 'SSC'



   .. py:attribute:: fsky


   .. py:method:: _get_sigma2_B(cosmo, a_arr, tr=None)

      Returns the variance of the projected linear density field,
          for the fsky/disk approximation case.

      :param cosmo: a Cosmology object.
      :type cosmo: :class:`~pyccl.cosmology.Cosmology`
      :param a_arr: an array of
                    scale factor values at which to evaluate
                    the projected variance.
      :type a_arr: :obj:`float`, `array` or :obj:`None`
      :param tr: dictionary containing the
                 tracer name combinations.
      :type tr: :obj:`dict`

      :returns: projected variance.
      :rtype: - (:obj:`float` or `array`)