Metadata-Version: 1.0
Name: xpol
Version: 1.5.0
Summary: XPOL cross power-spectrum estimator
Home-page: UNKNOWN
Author: Matthieu Tristram
Author-email: tristram@lal.in2p3.fr
License: UNKNOWN
Description: 
        .. image:: https://gitlab.in2p3.fr/uploads/-/system/project/avatar/1371/logo_Xpol.png
        
        .. contents:: **Table of Contents**
        
        
        Xpol
        ====
        
        a Power Spectrum estimator based on cross-correlation between maps.
        
        This is the generalisation to polarisation of `Tristram M. et al., 2005 MNRAS 358 833 <https://arxiv.org/abs/astro-ph/0405575>`_
        
        
        Xpol have been used to derive power spectra for:
        
        * Archeops
        
          - CMB power spectra [Tristram+2005, A&A 436 785]
          - Dust power spectra [Ponthieu+2005, A&A 444 327]
        
        * Planck: 
        
          - CMB power spectra [Planck 2015 results. XI, Couchot+2015]
          - Dust power spectra [Planck Intermediate Paper XXX]
          - CIB power spectra [Planck 2013 results. XXX]
          - SZ power spectra [Planck 2013 results. XXI, Planck 2015 results XXII]
          - SZ-CIB cross-power spectra [Planck 2015 results. XXIII]
        
        
        Download
        ========
        
        .. code:: shell
        
         git clone https://gitlab.in2p3.fr/tristram/Xpol.git /where/to/clone
        
        Install Python
        ==============
        
        Install the python stand-alone module ''xpol'' using
        
        .. code:: shell
        
          pip install -e /where/to/clone
        
        The -e option allow the developer to make changes within the Xpol directory without having
        to reinstall at every changes. If you plan to just use the code and do not develop it, you can
        remove the -e option.
        
        You can find a example of the module usage in test/script_xpol.py
        
        
        Install C
        =========
        
        The code is in C, fully MPI parallelized in CPU and memory (using spherical transform by s2hat).
        
        Librairies needed are :
        
        * HEALPix (http://healpix.jpl.nasa.gov/)
        * cfitsio (http://heasarc.gsfc.nasa.gov/fitsio/fitsio.html)
        * s2hat (http://www.apc.univ-paris7.fr/APC_CS/Recherche/Adamis/MIDAS09/software/s2hat/s2hat.html)
        
        In addition you will need some BLAS/LAPACK optimized routines (MKL, NAG, ...)
        
        
        Equations
        =========
        
        `wiki is here <https://gitlab.in2p3.fr/tristram/Xpol/wikis/home>`_
        
        
        Usage
        =====
        
        `Parameter file <https://gitlab.in2p3.fr/tristram/Xpol/wikis/ParameterFile>`_
        
Platform: UNKNOWN
