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Welcome to CosmoWAP Documentation
=================================

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COSMOlogy with Wide-separation, relAtivistic and Primordial non-gaussian contributions

`CosmoWAP <https://github.com/craddis1/CosmoWAP>`_ is a Python framework for forecasts of large-scale galaxy clustering using 3D power spectrum and/or bispectrum multipoles. The modelling covers relativistic effects, wide-separation corrections, and Primordial non-Gaussianity (PNG) in standard perturbation theory.

The core analytical expressions are derived in Mathematica using `MathWAP <https://github.com/craddis1/MathWAP>`_ and exported as `.py` files. These expressions take a cosmology (via CLASS) and a set of bias models as input. Built around this core is the forecasting machinery: bias modelling with HOD/luminosity functions, theoretical covariances, Fisher matrices, and MCMC modules.


.. toctree::
   :maxdepth: 2
   :caption: Getting Started:

   Installation <install>
   Getting started <getting_started>

.. toctree::
   :maxdepth: 2
   :caption: Biases:

   Survey parameters <surveyparams>
   Luminosity functions <luminosityfuncs>
   Bias modelling <biasmodel>

.. toctree::
   :maxdepth: 2
   :caption: Power Spectra and Bispectra:

   ClassWAP <classwap>
   Power Spectrum <pk>
   Integrated Effects <integrated>
   Bispectrum <bk>

.. toctree::
   :maxdepth: 2
   :caption: Forecasting:

   Gaussian Covariance <covariance>
   Forecasting <forecast>
   SNR <snr>
   Best-fit Bias <bfb>

.. toctree::
   :maxdepth: 2
   :caption: MathWAP:

   Overview <overview>
   Kernels <kernels>
   Power Spectrum <pkmath>
   Bispectrum <bkmath>

.. toctree::
   :maxdepth: 1
   :caption: Reference:

   Citation <citation>

Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`