Metadata-Version: 2.1
Name: extended-networkx-tools
Version: 0.13.0rc1
Summary: Tools package for extending functionality of the networkx package.
Home-page: https://github.com/vonNiklasson/extended-networkx-tools
Author: Johan Niklasson, Oskar Hahr
Author-email: jnikl@kth.se, ohahr@kth.se
License: MIT
Description: # 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
        
        ```shell
        pip install extended-networkx-tools
        ```
        
        ## Documentation
        
        [extended-networkx-tools.readthedocs.io](https://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 node
        - ``cycle``: 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][examplegraph]
        
        [examplegraph]: docs/source/_static/example-graph.png "Example 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**:
        
        ```python
        from extended_networkx_tools import Creator, Solver, AnalyticsGraph
        
        # Create a random graph with a path
        g = Creator.from_random(10)
        g = Solver.path(g)
        
        # Convert the graph to an AnalytcsGraph object
        ag = AnalyticsGraph(g)
        
        convergence_rate = ag.get_convergence_rate() # Calcualtes the convergence rate from scratch
        ag.remove_edge(4, 5)    # Removes an edge
        ag.revert()             # Revert the changes
        convergence_rate = ag.get_convergence_rate() # Doesn't calculate it since it's saved from previous state
        ```
        
        ## Usage
        
        ### Import
        
        
        ```python
        from extended_networkx_tools import Creator, Analytics, Visual, Solver, AnalyticsGraph
        ```
        
        
Keywords: graph,distributed average consensus,convergence rate,networkx
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
