Displaying 1 to 9 from 9 results

osmnx - OSMnx: Python for street networks

  •    Python

Retrieve, construct, analyze, and visualize street networks from OpenStreetMap: full overview. You can just as easily download and work with building footprints, elevation data, street bearings/orientations, and network routing.

stellargraph - StellarGraph - Machine Learning on Graphs

  •    Python

StellarGraph is a Python library for machine learning on graphs and networks. StellarGraph is built on TensorFlow 2 and its Keras high-level API, as well as Pandas and NumPy. It is thus user-friendly, modular and extensible. It interoperates smoothly with code that builds on these, such as the standard Keras layers and scikit-learn, so it is easy to augment the core graph machine learning algorithms provided by StellarGraph. It is thus also easy to install with pip or Anaconda.

flownetwork - A python package for flow network analysis

  •    Jupyter

A python package for flow network analysis

graphsim - Graph similarity algorithms based on NetworkX.

  •    Python

Graph similarity algorithms based on NetworkX. By default, sudo is required to give permission to install cpp modules into system /usr/local/{lib,include}.




grave - Grave—dead simple graph visualization

  •    Python

Grave is a graph visualization package combining ideas from Matplotlib, NetworkX, and seaborn. Its goal is to provide a network drawing API that covers the most use cases with sensible defaults and simple style configuration. Currently, it supports drawing graphs from NetworkX. Released under the 3-Clause BSD license (see LICENSE).

pydata-networkx - A short tutorial on network analysis using Game of Thrones, US Airports and python!

  •    Jupyter

NOTE: This repo will be updated before the tutorial so make sure to pull new changes. If you have the Anaconda distribution of Python 3 installed, then run the commands below.

nxviz - Visualization Package for NetworkX

  •    Python

nxviz is a graph visualization package for NetworkX. With nxviz, you can create beautiful graph visualizations by a declarative API. Here's an example. We recommend using conda.

s2g - (S)hapefile to(2) (G)raph/network converter in Python

  •    Python

When we process GIS data, a non-trivial problem is the conversion from shape lines to graph or network data structure. The latter may benefit from these out-of-box graphical libraries such as networkx and igraph. But the conversion is a headache to components open communities. This mostly urges me to finish this tiny but useful library. You have two alternative ways to construct the graph. One is reading from a raw shapefiles with LineString objects. (Under the hood, I involve fiona to read geometries and shapely to analyze the data.). Currently, this tool only supports conversion to undirected graph.


networkx.rb - A Ruby implementation of Python's well known Graph library "networkx"

  •    Ruby

NetworkX is a very popular Python library, that handles various use-cases of the Graph Data Structure. This project intends to provide a working alternative to the Ruby community, by closely mimicing as many features as possible. This project has begun just now, and a v0.1.0 release with basic Graph classes can be expected by January 2018.






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