Extended networkx Tools
Python Package for for visualizing and converting networkx graphs.
Introduction
This package was created for the purpose of examining bidirectional graphs with respect to its convergence rate and edge costs.
Installation
pip install extended-networkx-tools
Documentation
extended-networkx-tools.readthedocs.io
The package
Currently the package contains 3 main modules, Creator
, Analytics
and Visual
.
Creator
Contains tools to create networkx graphs based on given parameters, such as randomly
create an empty graph based on a number of nodes, or specify precisely the
coordinates of nodes and the edges between them.
Analytics
Has tools for analysing the networkx object and extract useful information from it, such
as convergence rate, neighbour matrix, its eigenvalues.
Solver
Used to find simple greedy solutions to a connected graph taken from graph theory. The current approaches are:
path
: Adds edges as a path from the start to end nodecycle
: Adds edges just like the path, but also one edge from the start to end node.complete
: Adds edges between all nodes to all the other nodes, such as the maximum distance between every node is one.
Visual
Is used to print a networkx graph to the screen, with its edges.
Example output graph
AnalyticsGraph
The AnalyticsGraph
class is a helper class that serves the purpose of a wrapper object
that can do all calculations based on changes done to the graph, rather
than recalculating every metric after simple changes. Such as the connectivity state
will stay the same after adding an edge.
There is also options to revert changes and keep previous calculations.
Example usage:
from extended_networkx_tools import Creator, Solver, AnalyticsGraph
g = Creator.from_random(10)
g = Solver.path(g)
ag = AnalyticsGraph(g)
convergence_rate = ag.get_convergence_rate()
ag.remove_edge(4, 5)
ag.revert()
convergence_rate = ag.get_convergence_rate()
Usage
Import
from extended_networkx_tools import Creator, Analytics, Visual, Solver, AnalyticsGraph