Pyviz

Apart from the new website, this is a minor release primarily to catch up with changes in external libraries.

New features:

* Reorganized examples directory as the basis for a completely new website at https://bokeh.github.io/datashader-docs (516).
* Added tf.Images() class to format multiple labeled Datashader images as a table in a Jupyter notebook, now used extensively in the new website.
* Added utility function ``dataframe_from_multiple_sequences(x_values, y_values)`` to convert large numbers of sequences stored as 2D numpy arrays to a NaN-separated pandas dataframe that can be displayed efficiently (see new example in tseries.ipynb) (512).
* Improved streaming support (520).

Bugfixes and compatibility:

* Added support for Dask 0.15 and 0.16 and pandas 0.21 (523,529) and declared minimum required Numba version.
* Improved and fixed issues with various example notebooks, primarily to update for changes in dependencies.
* Changes in network graph support: ignore id field by default to avoid surprising dependence on column name, rename directly_connect_edges to connect_edges for accuracy and conciseness.

Release with bugfixes, changes to match external libraries, and some new features.

Backwards compatibility:
* Minor changes to network graph API, e.g. to ignore weights by default in forcelayout2 (488)
* Fix upper-bound bin error for auto-ranged data (459). Previously, points falling on the upper bound of the plotted area were excluded from the plot, which was consistent with the behavior for individual grid cells, but which was confusing and misleading for the outer boundaries. Points falling on the very outermost boundaries are now folded into the final grid cell, which should be the least surprising behavior.

New or updated examples (.ipynb files in examples/):
* [streaming-aggregation.ipynb](https://anaconda.org/jbednar/streaming-aggregation): Illustrates combining incoming streams of data for display (also see [holoviews streaming](https://anaconda.org/philippjfr/working_with_streaming_data)).
* [landsat.ipynb](https://anaconda.org/jbednar/landsat): simplified using HoloViews; now includes plots of full spectrum for each point via hovering.
* Updated and simplified census-hv-dask (now called census-congressional), census-hv, packet_capture_graph.

New features and improvements
* Updated Bokeh support to work with new bokeh 0.12.10 release (505)
* More options for network/graph plotting (configurable column names, control over weights usage; 488, 494)
* For lines plots (time series, trajectory, networ graphs), switch line-clipping algorithm from Cohen-Sutherland to Liang-Barsky. The performance gains for random lines range from 50-75% improvement for a million lines. (495)
* Added ``tf.Images`` class to format a list of images as an HTML table (492)
* Faster resampling/regridding operations (486)

Known issues:
* examples/dashboard has not yet been updated to match other libraries, and is thus missing functionality like hovering and legends.
* A full website with documentation has been started but is not yet ready for deployment.

Minor bugfix release, primarily updating example notebooks to match API changes in external packages.

Backwards compatibility:

* Made edge bundling retain edge order, to allow indexing, and absolute coordinates, to allow overlaying on external data.
* Updated examples to show that xarray now requires dimension names to match before doing arithmetic or comparisons between arrays.

Known issues:

* If you use Jupyter notebook 5.0 (earlier or later versions should be ok), you will need to override a setting that prevents visualizations from appearing, e.g.: ``jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000 census.ipynb &``
* The dashboard needs to be rewritten entirely to match current Bokeh and HoloViews releases, so that hover and legend support can be restored.

New release of features that may still be in progress, but are already usable:
* Added graph/network plotting support (still may be in flux) (385, 390, 398, 408, 415, 418, 436)
* Improved raster regridding based on gridtools and xarray (still may be in flux); no longer depends on rasterio and scikit-image (383, 389, 423)
* Significantly improved performance for dataframes with categorical fields

New examples (.ipynb files in examples/):
* [osm-1billion](https://anaconda.org/jbednar/osm-1billion): 1-billion-point OSM example, for in-core processing on a 16GB laptop.
* [edge_bundling](https://anaconda.org/jbednar/edge_bundling): Plotting graphs using "edgehammer" bundling of edges to show structure.
* [packet_capture_graph](https://anaconda.org/jbednar/packet_capture_graph): Laying out and visualizing network packets as a graph.

Backwards compatibility:
* Remove deprecated interpolate and colorize functions
* Made raster processing consistently use bin centers to match xarray conventions (requires recent fixes to xarray; only available on a custom channel for now) (422)
* Fixed various limitations and quirks for NaN values
* Made alpha scaling respect min_alpha consistently (371)

Known issues:
* If you use Jupyter notebook 5.0 (earlier or later versions should be ok), you will need to override a setting that prevents visualizations from appearing, e.g.: ``jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000 census.ipynb &``
* The dashboard needs updating to match current Bokeh releases; most parts other than hover and legends, should be functional but it needs a rewrite to use currently recommended approaches.

Major release with extensive optimizations and new plotting-library support, incorporating 9 months of development from 5 main [contributors](https://github.com/bokeh/datashader/graphs/contributors):
- Extensive optimizations for speed and memory usage, providing at least 5X improvements in speed (using the latest Numba versions) and 2X improvements in peak memory requirements. Outlined in 313 and 129.
- Added [HoloViews support](https://anaconda.org/jbednar/holoviews_datashader) for flexible, composable, dynamic plotting, making it simple to switch between datashaded and non-datashaded versions of a Bokeh or Matplotlib plot.
- Added [examples/environment.yml](https://github.com/bokeh/datashader/blob/master/examples/environment.yml) to make it easy to install dependencies needed to run the examples.
- Updated examples to use the now-recommended supported and fast Apache Parquet file format
- Added support for variable alpha for non-categorical aggregates, by specifying a single color rather than a list or colormap 345
- Added [datashader.utils.lnglat_to_meters](https://github.com/bokeh/datashader/blob/master/datashader/utils.pyL142) utility function for working in Web Mercator coordinates with Bokeh
- Added [discussion of why you should be using uniform colormaps](https://anacondausercontent.org/user-content/notebooks/jbednar/plotting_pitfalls?signature=C_divg.WRaRHLPmIEtQ1V1lp0dCBZ34U8Y6.-Nonuniform-colormapping), and examples of using uniform colormaps from the new [colorcet](https://github.com/bokeh/colorcet) package
- Numerous bug fixes and updates, mostly in the examples and Bokeh extension
- Updated reference manual and documentation

New examples (.ipynb files in examples/):
- [holoviews_datashader](https://anaconda.org/jbednar/holoviews_datashader): Using HoloViews to create dynamic Datashader plots easily
- [census-hv-dask](https://anaconda.org/jbednar/census-hv-dask): Using [GeoViews](https://www.continuum.io/blog/developer-blog/introducing-geoviews) for overlaying shape files, demonstrating gerrymandering by race
- [nyc_taxi-paramnb](https://anaconda.org/jbednar/nyc_taxi-paramnb): Using ParamNB to make a simple dashboard
- [lidar](https://anaconda.org/jbednar/lidar): Visualizing point clouds
- [solar](https://anaconda.org/jbednar/solar): Visualizing solar radiation data
- [Dynamic 1D histogram example](https://anaconda.org/jbednar/nyc_taxi-nongeo) (last code cell in examples/nyc_taxi-nongeo.ipynb)
- dashboard: Now includes opensky example (``python dashboard/dashboard.py -c dashboard/opensky.yml``)

Backwards compatibility:
- To improve consistency with Numpy and Python data structures and eliminate issues with an empty column and row at the edge of the aggregated raster, the provided xrange,yrange bounds are now treated as upper exclusive. Results will thus differ between 0.5.0 and earlier versions. See 259 for discussion.

Known issues:
- If you use Jupyter notebook 5.0 (earlier or later versions should be ok), you will need to override a setting that prevents visualizations from appearing, e.g.: ``jupyter notebook --NotebookApp.iopub_data_rate_limit=100000000 census.ipynb &``
- Legend and hover support is currently disabled for the dashboard, due to ongoing development of a simpler approach.

Minor bugfix release to support Bokeh 0.12.1, with some API and defaults changes.
- Added `examples()` function to obtain the notebooks and other examples corresponding to the installed datashader version; see [examples/README.md](https://github.com/bokeh/datashader/blob/master/examples/README.md).
- Updated dashboard example to match changes in Bokeh
- Added default color cycle with distinguishable colors for shading categorical data; now `tf.shade(agg)` with no other arguments should give a usable plot for both categorical and non-categorical data.

Backwards compatibility:
- Replaced confusing `tf.interpolate()` and `tf.colorize()` functions with a single shading function `tf.shade()`. The previous names are still supported, but give deprecation warnings. Calls to the previous functions using keyword arguments can simply be renamed to use `tf.shade`, as all the same keywords are accepted, but calls to `colorize` that used a positional argument for e.g. the `color_key` will now need to use a keyword when calling `shade()`.
- Increased default `threshold` for `tf.dynspread()` to improve visibility of sparse dots
- Increased default `min_alpha` for `tf.shade()` (formerly `tf.colorize()`) to avoid undersaturation

Known issues:
- For Bokeh 0.12.1, some notebooks will give warnings for Bokeh plots when used with Jupyter's "Run All" command. Bokeh 0.12.2 will fix this problem when it is released, but for now you can either downgrade to 0.12.0 or use single-cell execution.
- There are some Bokeh compatibility issues with the dashboard example that are still being investigated and may require a new Bokeh or datashader release in this series.