GithubHelp home page GithubHelp logo

imclab / shapely Goto Github PK

View Code? Open in Web Editor NEW

This project forked from shapely/shapely

0.0 2.0 0.0 1.63 MB

Python package for manipulation and analysis of features in the Cartesian plane

Home Page: http://toblerity.github.com/shapely/

License: BSD 3-Clause "New" or "Revised" License

shapely's Introduction

Shapely

PostGIS-ish operations outside a database context for Pythoneers and Pythonistas.

http://farm3.staticflickr.com/2738/4511827859_b5822043b7_o_d.png

Shapely is a BSD-licensed Python package for manipulation and analysis of planar geometric objects. 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 execute with blazing speed. Shapely is not concerned with data formats or coordinate systems, but can be readily integrated with packages that are. 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

Warning

Windows users: do not under any circumstances use pip (or easy_install) to uninstall Shapely versions < 1.2.17. Due to the way Shapely used to install its GEOS DLL and a distribute or setuptools bug, your Python installation may be broken by an uninstall command. Shapely 1.2.17 will uninstall safely.

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.

Integration

Shapely does not read or write data files, but it can serialize and deserialize using several well known formats and protocols. The shapely.wkb and shapely.wkt modules provide dumpers and loaders inspired by Python's pickle module.:

>>> from shapely.wkt import dumps, loads
>>> dumps(loads('POINT (0 0)'))
'POINT (0.0000000000000000 0.0000000000000000)'

All linear objects, such as the rings of a polygon (like patch above), 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 always exactly what one wants for plotting shapes with Matplotlib (for example), so Shapely 1.2 adds a xy property for obtaining 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, ...)'

Shapely can also integrate with other Python GIS packages using data modeled after GeoJSON.

>>> import json
>>> from shapely.geometry import mapping, shape
>>> s = shape(json.loads('{"type": "Point", "coordinates": [0.0, 0.0]}'))
>>> s
<shapely.geometry.point.Point object at 0x...>
>>> print(json.dumps(mapping(s)))
{"type": "Point", "coordinates": [0.0, 0.0]}

Development and Testing

Dependecies for developing Shapely are listed in requirements-dev.txt. Cython and Numpy are not required for production installations, only for development. Use of a virtual environment is strongly recommended.:

$ virtualenv .
$ source bin/activate
(env)$ pip install -r requirements-dev.txt
(env)$ python setup.py develop

Shapely uses a Zope-stye suite of unittests and doctests, exercised via setup.py.:

(env)$ python setup.py test

Nosetests won't run the tests properly; Zope doctest suites are not currently supported well by nose.

Support

Please discuss Shapely with us at http://lists.gispython.org/mailman/listinfo/community.

Bugs may be reported at https://github.com/Toblerity/Shapely.

shapely's People

Contributors

ahojnnes avatar allanadair avatar bertrandgervais avatar fredj avatar hobu avatar jeethu avatar maarten-vermeyen avatar marcjansen avatar mindw avatar mwtoews avatar nmichaud avatar olt avatar pelson avatar proppy avatar psagers avatar sgillies avatar takluyver avatar weathergod avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.