Scoring
==================

.. currentmodule:: structify_net


The scoring submodule contains a collection of scoring function to describe graphs. The scoring function are used to compare graphs.

 The scoring function are defined in the :mod:`scoring` module.

- :data:`scoring.default_scores`: contains all available scores in a dictionary {name: score}.
- :data:`scoring.size`: contains additional scores describing the size of the graphs (number of nodes, number of edges)
- :data:`scoring.score_names`: contains a dictionary to convert plain score names to short latex names.

The function :func:`scoring.get_default_scores` return the default_scores in a convenient way, see below

Example of code on a single graph:

.. code-block:: python

   import structify_net.scoring
   g=nx.karate_club_graph()
   score=scoring.hierarchy(g)
   scores = scoring.compute_all_scores(g)

Example of code on a graph model:

.. code-block:: python

   import structify_net.scoring
   model=zoo.sort_nestedness(nodes=100)
   model.scores(m=1000)
   model.scores(m=1000,scores={"coreness":scoring.coreness},epsilons=[0,0.1,0.2],runs=3,)


Individual scoring functions
----------------------------

.. autosummary::

   scoring.has_giant_component
   scoring.giant_component_ratio
   scoring.transitivity
   scoring.average_clustering
   scoring.average_shortest_path_length
   scoring.modularity
   scoring.degree_heterogeneity
   scoring.is_degree_heterogeneous
   scoring.robustness
   scoring.degree_assortativity
   scoring.hierarchy
   scoring.boundaries
   scoring.coreness

Useful functions
----------------

.. autosummary::

   scoring.compute_all_scores
   scoring.scores_for_graphs
   scoring.scores_for_generators
   scoring.scores_for_rank_models
   scoring.scores_for_rank_functions
   scoring.compare_graphs
   scoring.get_default_scores