deploy: 0d2c5d9

alpha/.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: d64ad0606c00d935d6d8a4fb6fab342e
+tags: 645f666f9bcd5a90fca523b33c5a78b7

alpha/_sources/extensions/events.rst.txt

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+Event Handling
+==============
+
+Several other classes implement the :class:`.HasEvents` interface.
+In that case, they should provide a :attr:`.HasEvents.EVENTS` list that contains the :class:`Events <.Event>` that they implement.
+
+If you wish to inject your own code, check :meth:`.HasEvents.register_event_handler`.
+As an example, consider the (shortened) implementation of :class:`.SimulationTimer`:
+
+.. code:: python
+
+    class SimulationTimer:
+        _start_time: float # Starting time
+
+        time: Optional[float] = None # Final measure
+
+        def __init__(self, model: Model) -> None:
+            # Start timer with simulation
+            model.register_event_handler(
+                Event.SIMULATION_START, self._start_timer)
+
+            # End timer with simulation
+            model.register_event_handler(
+                Event.SIMULATION_END, self._end_timer)
+
+        def _start_timer(self):
+            # Sets the starting time
+            self._start_time = time.time()
+
+        def _end_timer(self):
+            # Computes the final simulation run
+            self.time = time.time() - self._start_time
+
+This code registers two functions to measure the simulation.
+When the simulation starts, the :meth:`_start_timer` method is called to store the starting time.
+Once the simulation ends, :meth:`_end_timer` takes again the time and subtracts the starting time.
+After the simulation, the :attr:`time` attribute contains the runtime of the simulation.
+
+.. autoclass:: netin.utils.Event
+    :members:
+    :undoc-members:
+.. autoclass:: netin.utils.HasEvents
+    :members:

alpha/_sources/extensions/filters.rst.txt

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+Filters
+==========
+
+.. autoclass:: netin.filters.Filter
+    :members:
+
+.. autoclass:: netin.filters.NoDoubleLinks
+    :members:
+
+.. autoclass:: netin.filters.NoSelfLinks
+    :members:
+
+.. autoclass:: netin.filters.ActiveNodes
+    :members:

alpha/_sources/extensions/index.rst.txt

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+Extending NetIn
+===============
+
+The package provides multiple interfaces to extend its functionalities.
+
+Several classes implement the :class:`.HasEvents` interface which can be used to inject your own code at runtime.
+
+.. toctree::
+   :maxdepth: 2
+
+   events
+
+Alternatively, you can extend the existing class structure to facilitate the existing simulation code, changing only specific modeling details.
+:class:`.Filter` and :class:`.LinkFormationMechanism` provide abstract classes that describe how target nodes are chosen during simulation.
+
+.. toctree::
+   :maxdepth: 2
+
+   filters
+   mechanisms
+
+Both custom and existing implementations (e.g., :class:`.Homophily`) can be used in custom models to reuse the existing simulation logic.
+In that case, only some of the simulation methods have to be reimplemented.
+For this purpose, several abstract base classes define varying levels of modelling abstractions.
+
+.. toctree::
+   :maxdepth: 2
+
+   models

alpha/_sources/extensions/mechanisms.rst.txt

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+Link Formation Mechanisms (LFM)
+===============================
+
+.. autoclass:: netin.link_formation_mechanisms.LinkFormationMechanism
+    :members:
+
+.. autoclass:: netin.link_formation_mechanisms.Uniform
+    :members:
+
+.. autoclass:: netin.link_formation_mechanisms.PreferentialAttachment
+    :members:
+
+.. autoclass:: netin.link_formation_mechanisms.InDegreePreferentialAttachment
+    :members:
+
+.. autoclass:: netin.link_formation_mechanisms.Homophily
+    :members:
+
+.. autoclass:: netin.link_formation_mechanisms.TriadicClosure
+    :members:

alpha/_sources/extensions/models.rst.txt

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+Model
+=====
+
+.. autoclass:: netin.models.Model
+    :members:
+    :private-members:
+
+.. autoclass:: netin.models.BinaryClassModel
+    :members:
+    :private-members:
+
+.. autoclass:: netin.models.UndirectedModel
+    :members:
+    :private-members:
+
+.. autoclass:: netin.models.DirectedModel
+    :members:
+    :private-members:

alpha/_sources/graphs.rst.txt

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+Graphs
+=======
+
+.. autoclass:: netin.graphs.Graph
+   :members:
+   :inherited-members:
+
+.. autoclass:: netin.graphs.DiGraph
+   :members:
+   :inherited-members:

alpha/_sources/index.rst.txt

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+.. NetIn documentation master file, created by
+   sphinx-quickstart on Wed Apr 19 11:08:02 2023.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Network Inequality
+=================================
+
+.. automodule:: netin
+
+Existing models are defined by the following :class:`.Model` class implementations.
+
+
+.. toctree::
+   :maxdepth: 3
+
+   models/index
+
+Each model can be simulated by running the :meth:`.Model.simulate` method, returning the simulated network as a :class:`.Graph` instance.
+
+.. toctree::
+   :maxdepth: 2
+
+   graphs
+
+:class:`Graphs <.Graph>` typically contain node attributes in the form of :class:`NodeVectors <NodeVector>`.
+For most models, these vectors contain the group assignments of nodes to a minority or majority class as :class:`.BinaryClassNodeVector`.
+
+.. toctree::
+   :maxdepth: 2
+
+   node_vectors/index
+
+Besides the implementation of models, `NetIn` offers functionality to analyze existing (or simulated) networks in terms of various inequalities they exhibit.
+
+.. toctree::
+   :maxdepth: 1
+
+   statistics
+
+If you want to create your own custom models or inject your own code during simulation of existing models, `NetIn` is highly extendible.
+It also provides utility functions to visualize networks and inequality results.
+
+.. toctree::
+   :maxdepth: 1
+
+   extensions/index
+   visualizations
+   utilities
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`
+
+.. include:: references.rst

alpha/_sources/models/directed.rst.txt

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+Directed Graph Models
+=====================
+
+.. autoclass:: netin.models.DHModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.DPAModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.DPAHModel
+    :members:
+    :inherited-members:

alpha/_sources/models/index.rst.txt

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+Models
+=======
+
+.. toctree::
+   :maxdepth: 2
+   :glob:
+
+   directed
+   undirected

alpha/_sources/models/undirected.rst.txt

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+Undirected Graph Models
+=======================
+
+.. autoclass:: netin.models.BarabasiAlbertModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.HomophilyModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.PAHModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.PATCHModel
+    :members:
+    :inherited-members:
+
+.. autoclass:: netin.models.CompoundLFM
+    :members:
+    :inherited-members:

alpha/_sources/node_vectors/index.rst.txt

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+Node vectors
+============
+
+.. autoclass:: netin.graphs.NodeVector
+   :members:
+   :inherited-members:
+
+.. autoclass:: netin.graphs.CategoricalNodeVector
+   :members:
+   :inherited-members:
+
+.. autoclass:: netin.graphs.BinaryClassNodeVector
+   :members:
+   :inherited-members:

alpha/_sources/references.rst.txt

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+References
+==========
+
+.. Please follow alphabetical ordering
+
+.. [BarabasiAlbert1999]
+    | A. L. Barabasi and R. Albert "Emergence of scaling in random networks", Science 286, pp 509-512, 1999.
+
+.. [Espin-Noboa2022]
+    | L. Espín-Noboa, C. Wagner, M. Strohmaier, & F. Karimi "Inequality and inequity in network-based ranking and recommendation algorithms" Scientific reports 12(1), 1-14, 2022.
+
+.. [Espin-Noboa2017]
+    | L. Espín-Noboa, F. Lemmerich, M. Strohmaier, & P. Singer, P. "JANUS: A hypothesis-driven Bayesian approach for understanding edge formation in attributed multigraphs" Applied Network Science, 2, 1-20.
+
+.. [Karimi2018]
+    | F. Karimi, M. Génois, C. Wagner, P. Singer, & M. Strohmaier, M "Homophily influences ranking of minorities in social networks", Scientific reports 8(1), 11077, 2018.
+
+.. [Gini]
+    | `Gini coefficient <http://www.statsdirect.com/help/default.htm#nonparametric_methods/gini.htm>`_ and `Implementation <https://github.com/oliviaguest/gini/blob/master/gini.py>`_
+
+.. [Yang2017]
+    | J. Yang, B. Ribeiro, & J. Neville "Should We Be Confident in Peer Effects Estimated From Social Network Crawls?" ICWSM (Vol. 11, No. 1, pp. 708-711), 2017.

alpha/_sources/statistics.rst.txt

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+Statistics
+==========
+
+.. automodule:: netin.stats.distributions
+    :members:
+
+.. automodule:: netin.stats.networks
+    :members:
+
+.. automodule:: netin.stats.ranking
+    :members:

alpha/_sources/utilities.rst.txt

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+Utility Functions
+=================
+
+.. autoclass:: netin.utils.SimulationTimer
+    :members:

alpha/_sources/visualizations.rst.txt

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+Visualization
+=============
+
+.. automodule:: netin.viz.handlers
+    :members: