Metadata-Version: 1.1
Name: rasterio
Version: 0.25.0
Summary: Fast and direct raster I/O for use with Numpy and SciPy
Home-page: https://github.com/mapbox/rasterio
Author: Sean Gillies
Author-email: sean@mapbox.com
License: BSD
Description: ========
        Rasterio
        ========
        
        Rasterio reads and writes geospatial raster datasets.
        
        .. image:: https://travis-ci.org/mapbox/rasterio.png?branch=master
           :target: https://travis-ci.org/mapbox/rasterio
        
        .. image:: https://coveralls.io/repos/mapbox/rasterio/badge.png
           :target: https://coveralls.io/r/mapbox/rasterio
        
        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.
        
        .. code-block:: python
        
            import numpy
            import rasterio
            import subprocess
        
            # Register GDAL format drivers and configuration options with a
            # context manager.
            with rasterio.drivers():
        
                # Read raster bands directly to Numpy arrays.
                #
                with rasterio.open('tests/data/RGB.byte.tif') as src:
                    r, g, b = src.read()
        
                # Combine arrays in place. Expecting that the sum will
                # temporarily exceed the 8-bit integer range, initialize it as
                # a 64-bit float (the numpy default) array. Adding other
                # arrays to it in-place converts those arrays "up" and
                # preserves the type of the total array.
                total = numpy.zeros(r.shape)
                for band in r, g, b:
                    total += band
                total /= 3
        
                # Write the product as a raster band to a new 8-bit file. For
                # the new file's profile, 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.
                profile = src.profile
                profile.update(
                    dtype=rasterio.uint8,
                    count=1,
                    compress='lzw')
        
                with rasterio.open('example-total.tif', 'w', **profile) as dst:
                    dst.write(total.astype(rasterio.uint8), 1)
        
            # At the end of the ``with rasterio.drivers()`` block, context
            # manager exits and all drivers are de-registered.
        
        The output:
        
        .. image:: http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg
           :width: 640
           :height: 581
        
        API Overview
        ============
        
        Simple access is provided to properties of a geospatial raster file.
        
        .. code-block:: python
        
            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]
        
        A dataset also provides methods for getting extended array slices given
        georeferenced coordinates and vice versa.
        
        
        .. code-block:: python
            
            with rasterio.drivers():
                with rasterio.open('tests/data/RGB.byte.tif') as src:
                    print src.window(**src.window_bounds(((100, 200), (100, 200))))
            # Output:
            # ((100, 200), (100, 200))
        
        Rasterio CLI
        ============
        
        Rasterio's command line interface, named "rio", is documented at `cli.rst
        <https://github.com/mapbox/rasterio/blob/master/docs/cli.rst>`__. Its ``rio
        insp`` command opens the hood of any raster dataset so you can poke around
        using Python.
        
        .. code-block:: pycon
        
            $ 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
        <http://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio>`__ and `GDAL
        <http://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal>`__) and run something like
        this from the downloads folder:
        
        .. code-block:: console
        
            $ 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
        <https://github.com/mapbox/rasterio/blob/master/.travis.yml>`__ for more
        guidance.
        
        Linux
        -----
        
        The following commands are adapted from Rasterio's Travis-CI configuration.
        
        .. code-block:: console
        
            $ 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.
        
        .. code-block:: console
        
            $ brew install gdal
            $ pip install rasterio
        
        Windows
        -------
        
        You can download a binary distribution of GDAL from `here
        <http://www.gisinternals.com/release.php>`__.  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.
        
        .. code-block:: console
        
            $ 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
        <https://docs.python.org/devguide/setup.html#windows>`__.).
        
        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
        
        .. code-block:: console
        
            $ py.test
        
        
        Note: some tests do not succeed on Windows (see
        `#66
        <https://github.com/mapbox/rasterio/issues/66>`__.).
        
        
        Documentation
        -------------
        
        See https://github.com/mapbox/rasterio/tree/master/docs.
        
        License
        -------
        
        See LICENSE.txt
        
        Authors
        -------
        
        See AUTHORS.txt
        
        Changes
        -------
        
        See CHANGES.txt
        
Keywords: raster gdal
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
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 :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: GIS
