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Name: rasterio
Version: 0.31.0
Summary: Fast and direct raster I/O for use with Numpy and SciPy
Home-page: https://github.com/mapbox/rasterio
Author: Sean Gillies
Author-email: sean@mapbox.com
License: BSD
Description: ========
Rasterio
========
Rasterio reads and writes geospatial raster datasets.
.. image:: https://travis-ci.org/mapbox/rasterio.png?branch=master
:target: https://travis-ci.org/mapbox/rasterio
.. image:: https://coveralls.io/repos/mapbox/rasterio/badge.png
:target: https://coveralls.io/r/mapbox/rasterio
Rasterio employs GDAL under the hood for file I/O and raster formatting. Its
functions typically accept and return Numpy ndarrays. Rasterio is designed to
make working with geospatial raster data more productive and more fun.
Rasterio is pronounced raw-STEER-ee-oh.
Example
=======
Here's a simple example of the basic features rasterio provides. Three bands
are read from an image and summed to produce something like a panchromatic
band. This new band is then written to a new single band TIFF.
.. code-block:: python
import numpy
import rasterio
import subprocess
# Register GDAL format drivers and configuration options with a
# context manager.
with rasterio.drivers():
# Read raster bands directly to Numpy arrays.
#
with rasterio.open('tests/data/RGB.byte.tif') as src:
r, g, b = src.read()
# Combine arrays in place. Expecting that the sum will
# temporarily exceed the 8-bit integer range, initialize it as
# a 64-bit float (the numpy default) array. Adding other
# arrays to it in-place converts those arrays "up" and
# preserves the type of the total array.
total = numpy.zeros(r.shape)
for band in r, g, b:
total += band
total /= 3
# Write the product as a raster band to a new 8-bit file. For
# the new file's profile, we start with the meta attributes of
# the source file, but then change the band count to 1, set the
# dtype to uint8, and specify LZW compression.
profile = src.profile
profile.update(
dtype=rasterio.uint8,
count=1,
compress='lzw')
with rasterio.open('example-total.tif', 'w', **profile) as dst:
dst.write(total.astype(rasterio.uint8), 1)
# At the end of the ``with rasterio.drivers()`` block, context
# manager exits and all drivers are de-registered.
The output:
.. image:: http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg
:width: 640
:height: 581
API Overview
============
Simple access is provided to properties of a geospatial raster file.
.. code-block:: python
with rasterio.drivers():
with rasterio.open('tests/data/RGB.byte.tif') as src:
print(src.width, src.height)
print(src.crs)
print(src.affine)
print(src.count)
print(src.indexes)
# Output:
# (791, 718)
# {u'units': u'm', u'no_defs': True, u'ellps': u'WGS84', u'proj': u'utm', u'zone': 18}
# Affine(300.0379266750948, 0.0, 101985.0,
# 0.0, -300.041782729805, 2826915.0)
# 3
# [1, 2, 3]
A dataset also provides methods for getting extended array slices given
georeferenced coordinates and vice versa.
.. code-block:: python
with rasterio.drivers():
with rasterio.open('tests/data/RGB.byte.tif') as src:
print src.window(**src.window_bounds(((100, 200), (100, 200))))
# Output:
# ((100, 200), (100, 200))
Rasterio CLI
============
Rasterio's command line interface, named "rio", is documented at `cli.rst
<https://github.com/mapbox/rasterio/blob/master/docs/cli.rst>`__. Its ``rio
insp`` command opens the hood of any raster dataset so you can poke around
using Python.
.. code-block:: pycon
$ rio insp tests/data/RGB.byte.tif
Rasterio 0.10 Interactive Inspector (Python 3.4.1)
Type "src.meta", "src.read_band(1)", or "help(src)" for more information.
>>> src.name
'tests/data/RGB.byte.tif'
>>> src.closed
False
>>> src.shape
(718, 791)
>>> src.crs
{'init': 'epsg:32618'}
>>> b, g, r = src.read()
>>> b
masked_array(data =
[[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
...,
[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]
[-- -- -- ..., -- -- --]],
mask =
[[ True True True ..., True True True]
[ True True True ..., True True True]
[ True True True ..., True True True]
...,
[ True True True ..., True True True]
[ True True True ..., True True True]
[ True True True ..., True True True]],
fill_value = 0)
>>> b.min(), b.max(), b.mean()
(1, 255, 44.434478650699106)
Rio Plugins
-----------
Rio provides the ability to create additional subcommands using plugins. See
`cli.rst <https://github.com/mapbox/rasterio/blob/master/docs/cli.rst#rio-plugins>`__
for more information on building plugins.
See the
`plugin registry <https://github.com/mapbox/rasterio/wiki/Rio-plugin-registry>`__
for a list of available plugins.
Installation
============
Dependencies
------------
Rasterio has one C library dependency: GDAL >=1.9. GDAL itself depends on a
number of other libraries provided by most major operating systems and also
depends on the non standard GEOS and PROJ4 libraries.
Python package dependencies (see also requirements.txt): affine, cligj (and
click), enum34, numpy.
Development also requires (see requirements-dev.txt) Cython and other packages.
Installing from binaries
------------------------
OS X
----
Binary wheels with the GDAL, GEOS, and PROJ4 libraries included are available
for OS X versions 10.7+ starting with Rasterio version 0.17. To install, just
run ``pip install rasterio``. These binary wheels are preferred by newer
versions of pip. If you don't want these wheels and want to install from
a source distribution, run ``pip install rasterio --no-use-wheel`` instead.
The included GDAL library is fairly minimal, providing only the format drivers
that ship with GDAL and are enabled by default. To get access to more formats,
you must build from a source distribution (see below).
Binary wheels for other operating systems will be available in a future
release.
Windows
-------
Binary wheels for rasterio and GDAL are created by Christoph Gohlke and are
available from his website.
To install rasterio, simply download both binaries for your system (`rasterio
<http://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio>`__ and `GDAL
<http://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal>`__) and run something like
this from the downloads folder:
.. code-block:: console
$ pip install -U pip
$ pip install GDAL-1.11.2-cp27-none-win32.whl
$ pip install rasterio-0.24.0-cp27-none-win32.whl
Installing from the source distribution
---------------------------------------
Rasterio is a Python C extension and to build you'll need a working compiler
(XCode on OS X etc). You'll also need Numpy preinstalled; the Numpy headers are
required to run the rasterio setup script. Numpy has to be installed (via the
indicated requirements file) before rasterio can be installed. See rasterio's
Travis `configuration
<https://github.com/mapbox/rasterio/blob/master/.travis.yml>`__ for more
guidance.
Linux
-----
The following commands are adapted from Rasterio's Travis-CI configuration.
.. code-block:: console
$ sudo add-apt-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install python-numpy libgdal1h gdal-bin libgdal-dev
$ pip install rasterio
Adapt them as necessary for your Linux system.
OS X
----
For a Homebrew based Python environment, do the following.
.. code-block:: console
$ brew install gdal
$ pip install rasterio
Windows
-------
You can download a binary distribution of GDAL from `here
<http://www.gisinternals.com/release.php>`__. You will also need to download
the compiled libraries and headers (include files).
When building from source on Windows, it is important to know that setup.py
cannot rely on gdal-config, which is only present on UNIX systems, to discover
the locations of header files and libraries that rasterio needs to compile its
C extensions. On Windows, these paths need to be provided by the user. You
will need to find the include files and the library files for gdal and use
setup.py as follows.
.. code-block:: console
$ python setup.py build_ext -I<path to gdal include files> -lgdal_i -L<path to gdal library>
$ python setup.py install
We have had success compiling code using the same version of Microsoft's
Visual Studio used to compile the targeted version of Python (more info on
versions used `here
<https://docs.python.org/devguide/setup.html#windows>`__.).
Note: The GDAL dll (gdal111.dll) and gdal-data directory need to be in your
Windows PATH otherwise rasterio will fail to work.
Testing
-------
From the repo directory, run py.test
.. code-block:: console
$ py.test
Note: some tests do not succeed on Windows (see
`#66
<https://github.com/mapbox/rasterio/issues/66>`__.).
Downstream testing
------------------
If your project depends on Rasterio and uses Travis-CI, you can speed up your
builds by fetching Rasterio and its dependencies as a set of wheels from
GitHub as done in `rio-plugin-example
<https://github.com/sgillies/rio-plugin-example/blob/master/.travis.yml>`__.
.. code-block:: yaml
language: python
env:
- RASTERIO_VERSION=0.26
python:
- "2.7"
- "3.4"
cache:
directories:
- $HOME/.pip-cache/
- $HOME/wheelhouse
before_install:
- sudo add-apt-repository -y ppa:ubuntugis/ppa
- sudo apt-get update -qq
- sudo apt-get install -y libgdal1h gdal-bin
- curl -L https://github.com/mapbox/rasterio/releases/download/$RASTERIO_VERSION/rasterio-travis-wheels-$TRAVIS_PYTHON_VERSION.tar.gz > /tmp/wheelhouse.tar.gz
- tar -xzvf /tmp/wheelhouse.tar.gz -C $HOME
install:
- pip install --use-wheel --find-links=$HOME/wheelhouse -e .[test] --cache-dir $HOME/.pip-cache
script:
- py.test
Documentation
-------------
See https://github.com/mapbox/rasterio/tree/master/docs.
License
-------
See LICENSE.txt
Authors
-------
See AUTHORS.txt
Changes
-------
See CHANGES.txt
Keywords: raster gdal
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: GIS
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