simple_like
================================================

Generate a simple 2pt likelihood given data, theory and covariance with no cuts

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| File        | likelihood/2pt/cosebis/simple_like.py |
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| Attribution | Chieh-An Lin                          |
+-------------+---------------------------------------+
|             | Tilman Troester                       |
+-------------+---------------------------------------+
|             | Marika Asgari                         |
+-------------+---------------------------------------+
|             | Catherine Heymans                     |
+-------------+---------------------------------------+
| URL         |                                       |
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This is a simple likelihood calculation that was set up for COSEBIs. In principle it could be used for any statistic
 provided you don't want to make any cuts to the data, theory and covariance (If you want to do something more complex 
 use 2pt_like.py).  It first reads in the tomographic data vector and covariance matrix from the block.  
 The theory is then also extracted and ordered according to the CosmoSIS convention.  
 The likelihood (data-model)^T C^{-1} (data-model) is returned.



Assumptions
-----------

 - The tomographic data and covariance are ordered in the standard CosmoSIS format



Setup Parameters
----------------

.. list-table::
   :header-rows: 1

   * - Name
     - Type
     - Default
     - Description

   * - data_set
     - str
     - En n
     - Space-separated list of statistic name and angle name to look in for data
   * - data_file
     - str
     - 
     - Name of FITS file containing the data and covariance matrix
   * - like_name
     - str
     - cosebis
     - The name of the likelihood to save e.g. 'like_name = cosebis' will return cosebis_like to the likelihood block
   * - theory_section
     - str
     - cosebis
     - Name of the block section that is storing the theory that you want to compare the data_set to


Input values
----------------

.. list-table::
   :header-rows: 1

   * - Section
     - Name
     - Type
     - Default
     - Description

   * - cosebis
     - En
     - real 1d
     - 
     - The theory predictions
   * - 
     - n
     - real 1d
     - 
     - If cosebis used, the COSEBIs mode
   * - 
     - bin_{i}_{j}
     - real 1d
     - 
     - For various i,j depending what is found in the file, the theory predictions for this value.


Output values
----------------


.. list-table:: Output values
   :header-rows: 1

   * - Section
     - Name
     - Type
     - Description

   * - likelihoods
     - cosebis_like
     - real
     - Gaussian likelihood value. Name can be changed in parameter file (see above).