Installing shapely, matplotlib, and descartes

A large part of geospatial analysis and visualization is made possible using Shapely, matplotlib, GDAL, OGR, and descartes, which are installed later. Most of the recipes here will use these libraries extensively so setting them up is necessary to complete our exercises.

Shapely (http://toblerity.org/shapely) provides pure spatial analysis of geometries using the Cartesian coordinate system as is used by AutoCAD, for those of you familiar with CAD-like programs. The benefit of using a flat coordinate system is that all the rules of Euclidean geometry and analytic geometry are applied. For a quick refresher in the coordinate systems that we all learned in school, here is a little image to quickly jolt your memory.

The classic overlay analysis and other geometric computations is where Shapely shines using the GEOS library as its workhorse in the background.

As for matplotlib (http://matplotlib.org/), it is the plotting engine that renders nice graphs and data to your screen as an image or scalable vector graphic (svg). The uses of matplotlib are only limited to your imagination. So, like the name partially implies, matplotlib enables you to plot your data on a graph or even on a map. For those of you familiar with MATLAB, you will find matplotlib quite similar in functionality.

The descartes library provides a nicer integration of Shapely geometry objects with Matplotlib. Here, you will see that descartes opens the fill and patch of matplotlib plots to work with the geometries from Shapely and saves you from typing them individually.

$ sudo apt-get install freetype* libpng-dev libjpeg8-dev

(pygeoan_cb)mdiener@mdiener-VirtualBox:~/venv$ python
Python 2.7.3 (default,  Feb 27 2014, 19:58:35)
[GCC 4.6.3] on linux2
Type “help”,  “copyright”, “credits”, or  “license” for more information.
>>> import shapely
>>> import matplotlib
>>> import descartes
>>>

# type exit() to return
>>> exit()