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Metadata-Version: 1.1
Name: rasterio
Version: 0.36.0
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-Content-Type: UNKNOWN
Description: ========
        Rasterio
        ========
        
        Rasterio reads and writes geospatial raster data files.
        
        .. image:: https://travis-ci.org/mapbox/rasterio.png?branch=master
           :target: https://travis-ci.org/mapbox/rasterio
        
        .. image:: https://coveralls.io/repos/github/mapbox/rasterio/badge.svg?branch=master
           :target: https://coveralls.io/github/mapbox/rasterio?branch=master
        
        Rasterio employs GDAL to read and writes files using GeoTIFF and many other
        formats. Its API uses familiar Python and SciPy interfaces and idioms like
        context managers, iterators, and ndarrays.
        
        Documentation is published at https://mapbox.github.io/rasterio/.
        
        Example
        =======
        
        Here's an example of some basic features that Rasterio provides. Three bands
        are read from an image and averaged to produce something like a panchromatic
        band.  This new band is then written to a new single band TIFF.
        
        .. code-block:: python
        
            import numpy as np
            import rasterio
        
            # 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 = np.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)
        
        The output:
        
        .. image:: http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg
           :width: 640
           :height: 581
        
        API Overview
        ============
        
        Rasterio gives access to properties of a geospatial raster file.
        
        .. code-block:: python
        
            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)
        
            # Printed:
            # (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 rasterio dataset also provides methods for getting extended array slices given
        georeferenced coordinates and vice versa.
        
        
        .. code-block:: python
        
            with rasterio.open('tests/data/RGB.byte.tif') as src:
                print src.window(**src.window_bounds(((100, 200), (100, 200))))
        
            # Printed:
            # ((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(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)
        
        Rio Plugins
        -----------
        
        Rio provides the ability to create subcommands using plugins.  See
        `cli.rst <https://github.com/mapbox/rasterio/blob/master/docs/cli.rst#rio-plugins>`__
        for more information on building plugins.
        
        See the
        `plugin registry <https://github.com/mapbox/rasterio/wiki/Rio-plugin-registry>`__
        for a list of available plugins.
        
        
        Installation
        ============
        
        Please install Rasterio in a `virtual environment
        <https://www.python.org/dev/peps/pep-0405/>`__ so that its requirements don't
        tamper with your system's Python.
        
        Dependencies
        ------------
        
        Rasterio has a 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. How to meet this
        requirement will be explained below.
        
        Rasterio's Python dependencies are listed in its requirements.txt file.
        
        Development also requires (see requirements-dev.txt) Cython and other packages.
        
        Binary Distributions
        --------------------
        
        Use a binary distributions that directly or indirectly provide GDAL if
        possible.
        
        Linux
        +++++
        
        Rasterio distributions are available from UbuntuGIS and Anaconda's conda-forge
        channel.
        
        `Manylinux1 <https://github.com/pypa/manylinux>`__ distributions may be
        available in the future.
        
        OS X
        ++++
        
        Binary distributions with GDAL, GEOS, and PROJ4 libraries included are available
        for OS X versions 10.7+ starting with Rasterio version 0.17. To install,
        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).
        
        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-2.0.2-cp27-none-win32.whl
            $ pip install rasterio-0.34.0-cp27-cp27m-win32.whl
        
        Source Distributions
        --------------------
        
        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 libgdal1h gdal-bin libgdal-dev
            $ pip install -U pip
            $ 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 upgrade
            $ brew install gdal
            $ pip install -U pip
            $ pip install --no-use-wheel rasterio
        
        Alternatively, you can install GDAL binaries from `kyngchaos
        <http://www.kyngchaos.com/software/frameworks#gdal_complete>`__.  You will then
        need to add the installed location ``/Library/Frameworks/GDAL.framework/Programs``
        to your system path.
        
        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.
        
        Development and Testing
        -----------------------
        
        See `CONTRIBUTING.rst <CONTRIBUTING.rst/>`__.
        
        Documentation
        -------------
        
        See `docs/ <docs/>`__.
        
        License
        -------
        
        See `LICENSE.txt <LICENSE.txt>`__.
        
        Authors
        -------
        
        See `AUTHORS.txt <AUTHORS.txt>`__.
        
        Changes
        -------
        
        See `CHANGES.txt <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 :: Cython
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: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Multimedia :: Graphics :: Graphics Conversion
Classifier: Topic :: Scientific/Engineering :: GIS