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Clean and fast and geospatial raster I/O for Python programmers who use Numpy

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Rasterio

Rasterio reads and writes geospatial raster datasets.

https://travis-ci.org/mapbox/rasterio.png?branch=master

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.

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 in place. Expecting that the sum will
    # temporarily 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'])

https://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg

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.

with rasterio.drivers():

    with rasterio.open('rasterio/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]

Rasterio also affords conversion of GeoTIFFs, on copy, to other formats.

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.

$ 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/RGB.byte.tif'
>>> src.shape
(718, 791)
>>> import pprint
>>> pprint.pprint(src.crs)
{u'ellps': u'WGS84',
u'no_defs': True,
u'proj': u'utm',
u'units': u'm',
u'zone': 18}
>>> b = src.read_band(1)
>>> b
array([[0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       ...,
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0]], dtype=uint8)
>>> b.min(), b.max(), b.mean()
(0, 255, 29.94772668847656)

Dependencies

C library dependecies:

  • GDAL

Python package dependencies (see also requirements.txt):

  • affine
  • 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.

To install from the source distribution on PyPI, do the following:

$ pip install -r https://raw.github.com/mapbox/rasterio/master/requirements.txt
$ pip install rasterio

To install from a forked repo, do this (in a virtualenv, preferably):

$ pip install -r requirements-dev.txt
$ pip install -e .

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.

Testing

From the repo directory, run py.test

$ py.test

Documentation

See https://github.com/mapbox/rasterio/tree/master/docs.

License

See LICENSE.txt

Authors

See AUTHORS.txt

Changes

See CHANGES.txt

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Clean and fast and geospatial raster I/O for Python programmers who use Numpy

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