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| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dengraph-0.1.dev0 |
| نام | dengraph |
| نسخه کتابخانه | 0.1.dev0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Eileen Kuehn, Max Fischer |
| ایمیل نویسنده | maxfischer2781@gmail.com |
| آدرس صفحه اصلی | UNKNOWN |
| آدرس اینترنتی | https://pypi.org/project/dengraph/ |
| مجوز | UNKNOWN |
dengraph - Density-based Graph Clustering
=========================================
|travis| |codecov| |landscape|
DenGraph performs a density-based graph clustering.
The algorithm was proposed as an extension for DBSCAN to support overlapping clusters.
The approach is based around the neighbourhood of a node.
The neighbourhood is defined by the *number* of reachable nodes within a given *distance*.
Therefore, large groups of items which are close to each other form clusters.
As DenGraph is a non-partitioning approach, isolated, distinct and uncommon items are left unclustered.
Instead, they are treated as noise.
Quick Overview
--------------
To use ``dengraph`` for clustering your data, two steps are required:
- Your data must be provided via the ``dengraph.graph.Graph`` interface.
See the ``dengraph.graphs`` module for appropriate containers and examples.
- The graph must be fed to ``dengraph.dengraph.DenGraphIO``.
.. code:: python
>>> from dengraph.graphs.distance_graph import DistanceGraph
>>> from dengraph.dengraph import DenGraphIO
>>> # Graph with defined nodes, edges from distance function
>>> graph = DistanceGraph(
... nodes=(1, 2, 3, 4, 5, 10, 11, 13, 14, 15, 17, 22, 23, 24, 25, 28, 29, 30, 31),
... distance=lambda node_from, node_to: abs(node_from - node_to)
... )
>>> # Cluster the graph
>>> clustered_data = DenGraphIO(graph, cluster_distance=2, core_neighbours=3).clusters
>>> # And print clusters
>>> for cluster in sorted(clustered_data, key=lambda clstr: min(clstr)):
... print(sorted(cluster))
[1, 2, 3, 4, 5]
[11, 13, 14, 15, 17]
[22, 23, 24, 25]
[28, 29, 30, 31]
Further Information
-------------------
At the moment, you must refer to the module and class documentation.
- See ``dengraph.dengraph.DenGraphIO`` for an explanation of clustering settings.
- See ``dengraph.graph.Graph`` for documentation of the graph interface.
Useful Classes
..............
We provide several implementations and tools for the ``Graph`` interface:
- Create a graph from a list of nodes and a distance function via ``dengraph.graphs.distance_graph.DistanceGraph``
- Create a graph from adjacency lists via ``dengraph.graphs.adjacency_graph.AdjacencyGraph``
- Read a distance matrix to a graph via ``dengraph.graphs.graph_io.csv_graph_reader``
Frequently Asked Questions
--------------------------
- Why is there no ``DenGraphHO`` class?
We haven't implemented that one yet.
It's on our Todo.
- Why is there no ``DenGraph`` class?
The original DenGraph algorithm is non-deterministic for unordered graphs.
Since border nodes can belong to only one cluster, the first cluster wins - results depend on iteration order.
The ``DenGraphIO`` algorithm does not have this issue and performs equally well.
- Why is ``DenGraphO`` the same class as ``DenGraphIO``?
Algorithmically, ``DenGraphIO`` is basically ``DenGraphO`` *plus* the option to insert/remove/modify nodes/edges.
In the static case (just initialisation), both are equivalent.
At the moment, we don't have any optimisations based on immutability of ``DenGraphO``.
The alias exists so that applications can distinguish between the two, possibly benefiting from future optimisations.
Acknowledgement
---------------
This module is based on several publications:
- [1] T. Falkowski, A. Barth, and M. Spiliopoulou, "DENGRAPH: A Density-based Community Detection Algorithm," presented at the IEEE/WIC/ACM International Conference on Web Intelligence (WI'07), 2007, pp. 112–115.
- [2] T. Falkowski, A. Barth, and M. Spiliopoulou, “Studying community dynamics with an incremental graph mining algorithm,” AMCIS 2008 Proceedings, 2008.
- [3] N. Schlitter, T. Falkowski, and J. Lässig, "DenGraph-HO - a density-based hierarchical graph clustering algorithm.," Expert Systems, vol. 31, no. 5, pp. 469–479, 2014.
.. |travis| image:: https://travis-ci.org/MaineKuehn/dengraph.svg?branch=master
:target: https://travis-ci.org/MaineKuehn/dengraph
:alt: Unit Tests
.. |codecov| image:: https://codecov.io/gh/MaineKuehn/dengraph/branch/master/graph/badge.svg
:target: https://codecov.io/gh/MaineKuehn/dengraph
:alt: Code Coverage
.. |landscape| image:: https://landscape.io/github/MaineKuehn/dengraph/master/landscape.svg?style=flat
:target: https://landscape.io/github/MaineKuehn/dengraph/master
:alt: Code Health
نحوه نصب
نصب پکیج whl dengraph-0.1.dev0:
pip install dengraph-0.1.dev0.whl
نصب پکیج tar.gz dengraph-0.1.dev0:
pip install dengraph-0.1.dev0.tar.gz