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.
openstreetmap gis network street-networks shapefile visualization graph overpass-api graphs networkx matplotlib spatial-analysis geospatial maps urban-planning design transportation physics math geographyStellarGraph 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.
machine-learning graphs machine-learning-algorithms networkx graph-data graph-analysis graph-machine-learning link-prediction graph-convolutional-networks gcn saliency-map interpretability geometric-deep-learning graph-neural-networks heterogeneous-networks stellargraph-libraryPymetrix (previously known as Analyx) is a plug-and-play analytics library written in Python. It aims to be lightweight and effective at capturing most of the basic metrics for your website, with the possibility of adding more through the use of extensions. Pymetrix can export data as Time Series and also as Aggregate hits data.
web time-series analytics metrics python3 networkx metrics-library tortoise-orm plugnplayA python package for flow network analysis
network-analysis networkxGraph similarity algorithms based on NetworkX. By default, sudo is required to give permission to install cpp modules into system /usr/local/{lib,include}.
graph tacsim networkx graph-similarity-algorithms numpy scientificGrave 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).
graph-visualization networkxNOTE: 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.
network-analysis tutorial game-of-thrones us-airports networkx graph-algorithmsnxviz 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.
network-visualization networkx network visualizationWhen 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.
graph shapefile conversion networkx network-converter fiona s2gNetworkX 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.
networkx network-graph ruby-gem
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