Fast and direct raster I/O for Python programmers who use Numpy
Project description
Fast and direct 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 raster 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.
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(0)
g = src.read_band(1)
b = src.read_band(2)
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, I convert to float32.
r = r.astype(rasterio.float32)
g = g.astype(rasterio.float32)
b = b.astype(rasterio.float32)
total = (r + g + b)/3.0
# 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.
with rasterio.open(
'/tmp/total.tif', 'w',
**dict(
src.meta,
**{'dtype': rasterio.uint8, 'count':1, 'compress': 'lzw'})
) as dst:
dst.write_band(0, total.astype(rasterio.uint8))
# Dump out gdalinfo's report card.
info = subprocess.check_output(['gdalinfo', '-stats', '/tmp/total.tif'])
print(info)Dependencies
C library dependecies:
GDAL
Python package dependencies:
numpy
six
Tests require nose
Testing
From the repo directory, run nosetests.
$ nosetestsLicense
See LICENSE.txt
Changes
See CHANGES.txt
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
File details
Details for the file rasterio-0.1.tar.gz.
File metadata
- Download URL: rasterio-0.1.tar.gz
- Upload date:
- Size: 81.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | aeb12df73e09179f12b70221e3f1ae5fa517367bf84864ee4336cd6e5e51b307 |
|
| MD5 | c54b3b595b80462fb2984081e77ae954 |
|
| BLAKE2b-256 | be30e7e6c08e3ac9cd1d084e271d0bc345a3728c0887f99577c9f4359343d51c |
