Skip to main content

Fast and direct raster I/O for use with Numpy and SciPy

Project description

Rasterio reads and writes geospatial raster datasets.

https://travis-ci.org/mapbox/rasterio.png?branch=master https://coveralls.io/repos/mapbox/rasterio/badge.png

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(CPL_DEBUG=True):

    # Read raster bands directly to Numpy arrays.
    #
    with rasterio.open('tests/data/RGB.byte.tif') as src:
        b, g, r = src.read()

    # 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

    # 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'])
http://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.

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]

Rasterio also affords conversion of GeoTIFFs to other formats.

with rasterio.drivers():

    rasterio.copy(
        'example-total.tif',
        'example-total.jpg',
        driver='JPEG')

subprocess.call(['open', 'example-total.jpg'])

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_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)

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.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 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 rasterio

Adapt them as necessary for your Linux system.

OS X

For a Homebrew based Python environment, do the following.

$ brew install gdal
$ pip install rasterio

Windows

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 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.).

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.test

Note: some tests do not succeed on Windows (see #66.).

Documentation

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

License

See LICENSE.txt

Authors

See AUTHORS.txt

Changes

See CHANGES.txt

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rasterio-0.24.1.tar.gz (969.2 kB view details)

Uploaded Source

Built Distributions

rasterio-0.24.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (16.0 MB view details)

Uploaded CPython 3.4m macOS 10.10+ intel macOS 10.10+ x86-64 macOS 10.6+ intel macOS 10.9+ intel macOS 10.9+ x86-64

rasterio-0.24.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (16.0 MB view details)

Uploaded CPython 2.7 macOS 10.10+ intel macOS 10.10+ x86-64 macOS 10.6+ intel macOS 10.9+ intel macOS 10.9+ x86-64

File details

Details for the file rasterio-0.24.1.tar.gz.

File metadata

  • Download URL: rasterio-0.24.1.tar.gz
  • Upload date:
  • Size: 969.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for rasterio-0.24.1.tar.gz
Algorithm Hash digest
SHA256 764adbeaf9b8abf7dde9ce0609a3321d45981a4349b9170dcfa6a75f5984675c
MD5 6390050782fc6659ab295ee8eb311b1a
BLAKE2b-256 de2a1d856eeeff136e3b2df6eb29b74599e9a5e18e01ee865f90a72961b1571f

See more details on using hashes here.

File details

Details for the file rasterio-0.24.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for rasterio-0.24.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 5e50629dd26091ed5668e66b19a4cc71ab63b70d8197f93ccda553881a51cd4f
MD5 48337bcd2131ad4b8b77ad63d8275fe9
BLAKE2b-256 d6616e05f766cd330e9d83451008178c0c587f8383fecfe8d9d8e553f5596fdc

See more details on using hashes here.

File details

Details for the file rasterio-0.24.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for rasterio-0.24.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 c9ce251d16601d87532868678a40055e3be6134a9717f1bd5f4d59ded852ce68
MD5 ed646bae8a1ea1c462abce95f7bab33b
BLAKE2b-256 d612972b77c86778d18f0b3448241dd5d4b67622b66ceb182211c509f2bec72d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page