SNESIM
------

The 'SNESIM' type prior model utilizes the SNESIM algorithm, as
implemented in Fortran available at `Stanford/SCRF <#>`__.

By default a training image (channel structures) from Sebastian
Strebelle's PhD theses is used (if no training image is specified). A
simple 2D type SNESIM prior model can be defined using the following
code:

::

    ip=1; 
    prior{ip}.type='SNESIM';
    prior{ip}.x=[0:.1:10]; % X array 
    prior{ip}.y=[0:.1:20]; % Y array 

and 5 realizations from this prior can be visualized using

::

    for i=1:5;
        m=sippi_prior(prior);
        subplot(1,5,i);
        imagesc(prior{1}.x,prior{1}.y,m{1});axis image
    end

Note that the training image is always assumed to have the same units as
the prior model, so in this case each pixel in the training image is
assumed to be separated by a distance '0.1'.

Optionally 'scaling' and 'rotation' of the training image can be set. To
scale the training image by 0.7 (i.e., structures will appear 30%
smaller) and rotate the training 30 degrees from north use

::

    ip=1; 
    prior{ip}.type='SNESIM';
    prior{ip}.x=[0:.1:10]; % X array 
    prior{ip}.y=[0:.1:20]; % Y array 
    prior{ip}.scaling=.7;
    prior{ip}.rotation=30;

.. figure:: ../../figures/prior_reals_snesim_rotation_scale.png
   :alt: 

Custom training image
~~~~~~~~~~~~~~~~~~~~~

A custom training image can be set using the ``ti`` field, which must be
either a 2D or 3D matrix.

::

    % create TI from image
    EXAMPLE EXAMPLE

    % setup the prior
    ip=1; 
    prior{ip}.type='SNESIM';
    prior{ip}.x=[0:.1:10]; % X array 
    prior{ip}.y=[0:.1:20]; % Y array
    prior{ip}.ti=ti;

Note that the training image MUST consist of integer index values
starting from 0 (i.e. '0', '1', '2', ...).

Complete customization
~~~~~~~~~~~~~~~~~~~~~~

If the ``prior`` structure is returned from
`sippi\_prior <#sippi_prior>`__ using

::

    [m,prior]=sippi_prior(prior);

then an XML structure ``prior{1}.S.XML`` will be available. This allows
a complete customization of all settings available in SGeMS. For
example, the different realizations, using 1, 2, and 3 multiple grids
can be obtained using

::

    ip=1; 
    prior{ip}.type='SNESIM';
    prior{ip}.x=[0:.1:10]; % X array 
    prior{ip}.y=[0:.1:20]; % Y array 
    [m,prior]=sippi_prior(prior);
    for i=1:5;
        prior{ip}.S.XML.parameters.Nb_Multigrids_ADVANCED.value=i;
        subplot(1,3,5);
        imagesc(prior{1}.x,prior{1}.y,m{1});axis image  
    end

.. figure:: ../../figures/prior_reals_snesim_nmgrid.png
   :alt: