Fast and direct raster I/O for use with Numpy and SciPy
Project description
Rasterio reads and writes geospatial raster datasets.
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.
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:
API Overview
Simple access is provided to properties of a geospatial raster file.
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.
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. Its rio insp command opens the hood of any raster dataset so you can poke around using Python.
$ rio insp tests/data/RGB.byte.tif
Rasterio 0.10 Interactive Inspector (Python 3.4.1)
Type "src.meta", "src.read(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 for more information on building plugins.
See the 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 and GDAL) and run something like this from the downloads folder:
$ pip install -U pip
$ pip install GDAL-1.11.2-cp27-none-win32.whl
$ pip install rasterio-0.24.0-cp27-none-win32.whlInstalling 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 for more guidance.
Linux
The following commands are adapted from Rasterio’s Travis-CI configuration.
$ sudo add-apt-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install python-numpy libgdal1h gdal-bin libgdal-dev
$ pip install rasterioAdapt them as necessary for your Linux system.
OS X
For a Homebrew based Python environment, do the following.
$ brew install gdal
$ pip install rasterioWindows
You can download a binary distribution of GDAL from here. 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.
$ python setup.py build_ext -I<path to gdal include files> -lgdal_i -L<path to gdal library>
$ python setup.py installWe 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.).
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
$ py.testNote: some tests do not succeed on Windows (see #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.
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.testDocumentation
License
See LICENSE.txt
Changes
See CHANGES.txt
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