Metadata-Version: 1.1
Name: rasterio
Version: 0.1
Summary: Fast and direct raster I/O for Python programmers who use Numpy
Home-page: https://github.com/sgillies/rasterio
Author: Sean Gillies
Author-email: sean@mapbox.com
License: BSD
Description: rasterio
        ========
        
        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.
        
        .. code-block:: python
        
            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.
        
        .. code-block:: console
        
            $ nosetests
        
        License
        -------
        
        See LICENSE.txt
        
        Authors
        -------
        
        See AUTHORS.txt
        
        Changes
        -------
        
        See CHANGES.txt
        
        
Keywords: raster gdal
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: GIS
