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Python Geospatial Analysis Cookbook

You're reading from   Python Geospatial Analysis Cookbook Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781783555079
Length 310 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Your Geospatial Python Environment FREE CHAPTER 2. Working with Projections 3. Moving Spatial Data from One Format to Another 4. Working with PostGIS 5. Vector Analysis 6. Overlay Analysis 7. Raster Analysis 8. Network Routing Analysis 9. Topology Checking and Data Validation 10. Visualizing Your Analysis 11. Web Analysis with GeoDjango A. Other Geospatial Python Libraries
B. Mapping Icon Libraries
Index

Finding the Dijkstra shortest path with NetworkX in pure Python


This recipe is a pure Python solution to calculate the shortest path on a network. NetworkX is the library we will use with many algorithms to solve the shortest path problem, including Dijkstra (http://networkx.github.io/). NetworkX relies on numpy and scipy to perform some graph calculations and help with performance. In this recipe, we will only use Python libraries to create our shortest path based on the same input Shapefile used in our previous recipe.

Getting ready

Start with installing NetworkX on your machine with the pip installer as follows:

>> pip install networkx

For the network graph algorithms, NetworkX requires numpy and scipy, so take a look at Chapter 1, Setting Up Your Geospatial Python Environment, for instructions on these. We also use Shapely to generate our geometry outputs to create GeoJSON files, so check whether you have installed Shapely. One hidden requirement is that GDAL/OGR is used in the back...

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