Fast and direct raster I/O for Python programmers who use Numpy
Project description
Fast and direct geospatial raster I/O for Python programmers who use Numpy.
This package is aimed at developers who want little more than to read raster images into Numpy arrays or buffers, operate on them in Python (or Cython), and write the results out to new GeoTIFF files.
Rasterio employs GDAL under the hood for file I/O and raster formatting.
Example
Here’s an example of the features rasterio aims to provide. Three bands are read from an image and summed to produce something like a panchromatic band. This new band is then written to a single band TIFF.
import rasterio
import subprocess
# Read raster bands directly to Numpy arrays.
with rasterio.open('rasterio/tests/data/RGB.byte.tif') as src:
r = src.read_band(1)
g = src.read_band(2)
b = src.read_band(3)
assert [b.dtype.type for b in (r, g, b)] == src.dtypes
# Combine arrays using the 'add' ufunc. Expecting that the sum will
# exceed the 8-bit integer range, convert to 16-bit.
r = r.astype(rasterio.uint16)
g = g.astype(rasterio.uint16)
b = b.astype(rasterio.uint16)
total = (r + g + b)/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))
# 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'])Simple access is provided to properties of a geospatial raster file.
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.
rasterio.copy(
'example-total.tif',
'example-total.jpg',
driver='JPEG')
subprocess.call(['open', 'example-total.jpg'])Dependencies
C library dependecies:
GDAL
Python package dependencies (see also requirements.txt):
Numpy
setuptools
six
Development also requires (see requirements-dev.txt)
Cython
nose
Installation
Rasterio is a C extension and there are not yet any binary releases. You’ll need a working compiler (XCode on OS X, etc).
$ pip install numpy
$ pip install rasterioThe Numpy headers are required to run the rasterio setup script. Numpy has to be installed first.
Testing
From the repo directory, run nosetests.
$ nosetestsLicense
See LICENSE.txt
Changes
See CHANGES.txt
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