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Planar geometries, predicates, and operations

Project description

http://gispython.org/images/shapely-med.png

Shapely is a BSD-licensed Python package for manipulation and analysis of planar geometries. It is not concerned with data formats or coordinate systems. It is based on the widely deployed GEOS (the engine of PostGIS) and JTS (from which GEOS is ported) libraries. This C dependency is traded for the ability to analyze geometries with blazing speed.

In a nutshell: Shapely lets you do PostGIS-ish stuff outside the context of a database using idiomatic Python. For more details, see:

Dependencies

Shapely 1.2 depends on:

  • Python >=2.5,<3
  • libgeos_c >=3.1 (3.0 and below have not been tested, YMMV)

Installation

Windows users should use the executable installer, which contains the required GEOS DLL. Other users should acquire libgeos_c by any means, make sure that it is on the system library path, and install from the Python package index:

$ pip install Shapely

or from a source distribution with the setup script:

$ python setup.py install

Usage

Here is the canonical example of building an approximately circular patch by buffering a point:

>>> from shapely.geometry import Point
>>> patch = Point(0.0, 0.0).buffer(10.0)
>>> patch
<shapely.geometry.polygon.Polygon object at 0x...>
>>> patch.area
313.65484905459385

See the manual for comprehensive usage snippets and the dissolve.py and intersect.py example apps.

Numpy integration

All linear geometries, such as the rings of a polygon, provide the Numpy array interface:

>>> from numpy import asarray
>>> ag = asarray(patch.exterior)
>>> ag
array([[  1.00000000e+01,   0.00000000e+00],
       [  9.95184727e+00,  -9.80171403e-01],
       [  9.80785280e+00,  -1.95090322e+00],
       ...
       [  1.00000000e+01,   0.00000000e+00]])

That yields a numpy array of [x, y] arrays. This is not exactly what one wants for plotting shapes with Matplotlib, so Shapely 1.2 adds a xy geometry property for getting separate arrays of coordinate x and y values:

>>> x, y = patch.exterior.xy
>>> ax = asarray(x)
>>> ax
array([  1.00000000e+01,   9.95184727e+00,   9.80785280e+00,  ...])

Numpy arrays can also be adapted to Shapely linestrings:

>>> from shapely.geometry import asLineString
>>> asLineString(ag).length
62.806623139095073
>>> asLineString(ag).wkt
'LINESTRING (10.0000000000000000 0.0000000000000000, ...)'

Testing

Shapely uses a Zope-stye suite of unittests and doctests, excercised like:

$ python setup.py test

Support

For current information about this project, see the wiki.

If you have questions, please consider joining our community list:

http://trac.gispython.org/projects/PCL/wiki/CommunityList

Credits

Shapely is written by:

  • Sean Gillies
  • Aron Bierbaum
  • Kai Lautaportti

Patches contributed by:

  • Howard Butler
  • Frédéric Junod
  • Eric Lemoine
  • Jonathan Tartley
  • Kristian Thy
  • Oliver Tonnhofer

Additional help from:

  • Justin Bronn (GeoDjango) for ctypes inspiration
  • Martin Davis (JTS)
  • Sandro Santilli, Mateusz Loskot, Paul Ramsey, et al (GEOS Project)

Major portions of this work were supported by a grant (for Pleiades) from the U.S. National Endowment for the Humanities (http://www.neh.gov).

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