.. _`evaluation options`:

Evaluation options
==================

Assume we have created an inference script (:ref:`factor algebra` expression), for example with::

    >>> import symfer as s
    >>> model = s.loadhugin('extended-student.net')
    >>> query = ['H']
    >>> obs = {'S':'s1'}
    >>> ve = s.ve_minweight(model,query)
    >>> ve_obs = s.indextree(obs,ve)

The most straightforward option is to evaluate it using Python::

    >>> s.evaluate(ve_obs)
    Multinom(dom=[{'H': ['h0', 'h1']}],par=[0.0677442825, 0.20725571750000002])

However, the ``ve_obs`` script can also be executed on a separate platform. For this, serialize it to `YAML <http://yaml.org>`_::

    >>> s.dumpyaml(ve_obs, 've_obs.yaml')

The resulting file :download:`ve_obs.yaml <ve_obs_yaml.txt>` can be evaluated, for example, from a shell command line::

    $ evaluate.py ve_obs.yaml
    [0.0677442825, 0.2072557175]
    
Of course, it can also be loaded by a separate Python interpreter again:

    >>> import symfer as s
    >>> ve_obs = s.loadyaml('ve_obs.yaml')

The file can also be evaluated by the Java evaluator :ref:`jsymfer` (also usable as a Java library)::

    $ java -jar jsymfer.jar ve_obs.yaml
    # YAML parsed in 67 ms
    # Inference in 3 ms
    !multinom
    par: [0.067744285, 0.20725572]
    dom:
    - H: [h0, h1]

Instead of serializing to YAML, ``ve_obs`` can also be compiled to C source::

    >>> s.dumpc(ve_obs, 've_obs.c')

From the shell::

    $ gcc ve_obs.c -o ve_obs
    $ ./ve_obs
    [0.067744, 0.207256]

Evaluating an inference script as a generated C file is somewhat faster, and more reliable because of explicit garbage collection. It can also be done from Python using one function call::

    >>> s.evalc(ve_obs)
    Multinom(dom=[{'H': ['h0', 'h1']}],par=[0.067744, 0.207256])