Datashader

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The major feature of this release is support of raster data via ``Canvas.raster``. To use this feature, you must install the optional dependencies via ``conda install rasterio scikit-image``. Rasterio relies on ``gdal`` whose conda package has some known bugs, including a missing dependency for ``conda install krb5``. InteractiveImage in this release requires bokeh 0.11.1 or earlier, and will not work with bokeh 0.12.

- **PR 160 187** Improved example notebooks and dashboard
- **PR 186 184 178** Add datashader-download-data cli command for grabbing example datasets
- **PR 176 177** Changed census example data to use HDF5 format (slower but more portable)
- **PR 156 173 174** Added Landsat8 and race/ethnicity vs. elevation example notebooks
- **PR 172 159 157 149** Added support for images using ``Canvas.raster`` (requires ``rasterio`` and ``scikit-image``).
- **PR 169** Added legends notebook demonstrating ``create_categorical_legend`` and ``create_ramp_legend`` - **PR 162**. Added notebook example for ``datashader.bokeh_ext.HoverLayer`` - **PR 152**. Added ``alpha``arg to ``tf.interpolate`` - **PR 151 150, etc.** Small bugfixes
- **PR 146 145 144 143** Added streaming example
- Added ``hold`` decorator to utils, ``summarize_aggregate_values`` helper function
- Added `FAQ <http://datashader.readthedocs.io/en/latest/#faq>`_ to docs

Backwards compatibility:

- Removed ``memoize_method`` - Renamed ``datashader.callbacks`` --> ``datashader.bokeh_ext`` - Renamed ``examples/plotting_problems.ipynb`` --> ``examples/plotting_pitfalls.ipynb``

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A major release with significant new functionality and some small backwards-incompatible changes.

New features:

- **PR 124**, `census <https://anaconda.org/jbednar/census/notebook>`_ New census notebook example, showing how to work with categorical data.
- **PR 79**, `tseries <https://anaconda.org/jbednar/tseries>`_, `trajectory <https://anaconda.org/jbednar/trajectory>`_ Added line glyph and ``.any()``reduction, used in new time series and trajectory notebook examples.
- **PR 76, 77, 131** Updated all of the other notebooks in examples/, including `nyc_taxi <https://anaconda.org/jbednar/nyc_taxi/notebook>`_.
- **PR 100, 125:** Improved dashboard example: added categorical data support, census and osm datasets, legend and hover support, better performance, out of core option, and more
- **PR 109, 111:** Add full colormap support via a new ``cmap`` argument to ``interpolate`` and ``colorize`` supports color ranges as lists, plus Bokeh palettes and matplotlib colormaps
- **PR 98:** Added ``set_background`` to make it easier to work with images having a different background color than the default white notebooks
- **PR 119, 121:** Added ``eq_hist`` option for ``how`` in interpolate, performing histogram equalization on the data to reveal structure at every intensity level
- **PR 80, 83, 128**: Greatly improved InteractiveImage performance and responsiveness
- **PR 74, 123:** Added operators for spreading pixels (to make individual datapoints visible, as circles, squares, or arbitrary mask shapes) and compositing (for simple and flexible composition of images)

Backwards compatibility:

- The ``low`` and ``high`` color options to ``interpolate`` and ``colorize`` are now deprecated and will be removed in the next release; use ``cmap=[low,high]`` instead.
- The transfer function ``merge`` has been removed to avoid confusion. ``stack`` and others can be used instead, depending on the use case.
- The default ``how`` for ``interpolate`` and ``colorize`` is now ``eq_hist`` to reveal the structure automatically regardless of distribution.
- ``Pipeline`` now has a default ``dynspread`` step, to make isolated points visible when zooming in, and the default sizes have changed.

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Initial public release.