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Rasterio
========
.. image:: https://travis-ci.org/mapbox/rasterio.png?branch=master
:target: https://travis-ci.org/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.
Example
-------
Here's an 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 format drivers with a context manager
with rasterio.drivers():
# Read raster bands directly to Numpy arrays.
#
with rasterio.open('rasterio/tests/data/RGB.byte.tif') as src:
b, g, r = map(src.read_band, (1, 2, 3))
# Combine arrays using the 'iadd' ufunc. Expecting that the sum
# will exceed the 8-bit integer range, initialize it as 16-bit.
# Adding other arrays to it in-place converts those arrays up
# and preserves the type of the total array.
total = numpy.zeros(r.shape, dtype=rasterio.uint16)
for band in (r, g, b):
total += band
total /= 3
assert total.dtype == rasterio.uint16
# Write the product as a raster band to a new 8-bit file. For
# keyword arguments, 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.
kwargs = src.meta
kwargs.update(
dtype=rasterio.uint8,
count=1,
compress='lzw')
with rasterio.open('example-total.tif', 'w', **kwargs) as dst:
dst.write_band(1, total.astype(rasterio.uint8))
# At the end of the ``with rasterio.drivers()`` block, context
# manager exits and all drivers are de-registered.
# Dump out gdalinfo's report card and open the image.
info = subprocess.check_output(
['gdalinfo', '-stats', 'example-total.tif'])
print(info)
subprocess.call(['open', 'example-total.tif'])
.. image:: http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg
:width: 640
:height: 581
The rasterio.drivers() function and context manager are new in 0.5. The example
above shows the way to use it to register and de-register drivers in
a deterministic and efficient way. Code written for rasterio 0.4 will continue
to work: opened raster datasets may manage the global driver registry if no
other manager is present.
Simple access is provided to properties of a geospatial raster file.
.. code-block:: python
with rasterio.drivers():
with rasterio.open('rasterio/tests/data/RGB.byte.tif') as src:
print(src.width, src.height)
print(src.crs)
print(src.transform)
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}
# [101985.0, 300.0379266750948, 0.0, 2826915.0, 0.0, -300.041782729805]
# 3
# [1, 2, 3]
Rasterio also affords conversion of GeoTIFFs, on copy, to other formats.
.. code-block:: python
with rasterio.drivers():
rasterio.copy(
'example-total.tif',
'example-total.jpg',
driver='JPEG')
subprocess.call(['open', 'example-total.jpg'])
rio_insp
--------
The rio_insp program opens the hood of any raster dataset so you can poke
around using Python.
.. code-block:: console
$ rio_insp rasterio/tests/data/RGB.byte.tif
Rasterio 0.8 Interactive Inspector (Python 3.3.5)
Type "src.meta", "src.read_band(1)", or "help(src)" for more information.
>>> src.name
'rasterio/tests/data/shade.tif'
>>> src.shape
(1024, 1024)
>>> import pprint
>>> pprint.pprint(src.crs)
{u'a': 6378137,
u'b': 6378137,
u'k': 1,
u'lat_ts': 0,
u'lon_0': 0,
u'nadgrids': u'@null',
u'no_defs': True,
u'proj': u'merc',
u'units': u'm',
u'wktext': True,
u'x_0': 0,
u'y_0': 0}
>>> b = src.read_band(1)
>>> b
array([[255, 255, 255, ..., 0, 0, 0],
[255, 255, 255, ..., 0, 0, 0],
[255, 255, 255, ..., 0, 0, 0],
...,
[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255]], dtype=uint8)
>>> b.min(), b.max(), b.mean()
(0, 255, 224.75362300872803)
Dependencies
------------
C library dependecies:
- GDAL
Python package dependencies (see also requirements.txt):
- Numpy
- setuptools
Development also requires (see requirements-dev.txt)
- Cython
- pytest
Installation
------------
Rasterio is a C extension and to install on Linux or OS X you'll need a working
compiler (XCode on OS X etc). Unofficial Windows binary packages created by
Christoph Gohlke are available `here
<http://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio>`_.
To install from the source distribution on PyPI, do the following:
.. code-block:: console
$ pip install -r https://raw.github.com/mapbox/rasterio/master/requirements.txt
$ pip install rasterio>=0.8
To install from a forked repo, do this (in a virtualenv, preferably):
.. code-block:: console
$ pip install -r requirements-dev.txt
$ python setup.py install
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.
Testing
-------
From the repo directory, run py.test
.. code-block:: console
$ py.test
Documentation
-------------
See https://github.com/mapbox/rasterio/tree/master/docs.
License
-------
See LICENSE.txt
Authors
-------
See AUTHORS.txt
Changes
-------
See CHANGES.txt