Merge pull request #1239 from ioam/deprecate_bokeh_mpl

Remove bokeh matplotlib compatibility

doc/Tutorials/Bokeh_Backend.ipynb

@@ -311,35 +311,8 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "focus": false,
-    "id": "85e1ed20-1e12-4194-822e-c2fe0810ce41"
-   },
-   "source": [
-    "### Matplotlib/Seaborn conversions\n",
-    "\n",
-    "Bokeh also allows converting a subset of existing matplotlib plot types to Bokeh. This allows us to work with some of the Seaborn plot types, including Distribution, Bivariate, and TimeSeries:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "focus": false,
-    "id": "f406d9f0-8488-4b0b-9bf2-95477aad104b"
-   },
-   "outputs": [],
-   "source": [
-    "%%opts Distribution (kde_kws=dict(shade=True))\n",
-    "d1 = np.random.randn(500) + 450\n",
-    "d2 = np.random.randn(500) + 540\n",
-    "sines = np.array([np.sin(np.linspace(0, np.pi*2, 100)) + np.random.normal(0, 1, 100) for _ in range(20)])\n",
-    "hv.Distribution(d1) + hv.Bivariate((d1, d2)) + hv.TimeSeries(sines)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
+    "deletable": true,
+    "editable": true,
     "focus": false,
     "id": "fd1916ba-13a5-404a-8115-f63487b38689"
    },

holoviews/plotting/bokeh/__init__.py

@@ -19,7 +19,7 @@
 
 from .annotation import TextPlot, LineAnnotationPlot, SplinePlot
 from .callbacks import Callback # noqa (API import)
-from .element import OverlayPlot, BokehMPLWrapper
+from .element import OverlayPlot
 from .chart import (PointPlot, CurvePlot, SpreadPlot, ErrorPlot, HistogramPlot,
                     SideHistogramPlot, BoxPlot, BarPlot, SpikesPlot,
                     SideSpikesPlot, AreaPlot, VectorFieldPlot)
@@ -98,25 +98,6 @@
 except ImportError:
     pass
 
-try:
-    from ..mpl.seaborn import TimeSeriesPlot, BivariatePlot, DistributionPlot
-    from ...interface.seaborn import Bivariate, TimeSeries, Distribution
-    Store.register({Distribution: PlotSelector(lambda x: 'bokeh',
-                                               [('mpl', DistributionPlot),
-                                                ('bokeh', BokehMPLWrapper)],
-                                               True),
-                    TimeSeries: PlotSelector(lambda x: 'bokeh',
-                                             [('mpl', TimeSeriesPlot),
-                                              ('bokeh', BokehMPLWrapper)],
-                                             True),
-                    Bivariate: PlotSelector(lambda x: 'bokeh',
-                                        [('mpl', BivariatePlot),
-                                         ('bokeh', BokehMPLWrapper)], True)},
-                   'bokeh')
-except ImportError:
-    pass
-
-
 point_size = np.sqrt(6) # Matches matplotlib default
 Cycle.default_cycles['default_colors'] =  ['#30a2da', '#fc4f30', '#e5ae38',
                                            '#6d904f', '#8b8b8b']

holoviews/plotting/bokeh/element.py

@@ -2,6 +2,7 @@
 from itertools import groupby
 import warnings
 
+import param
 import numpy as np
 import bokeh
 import bokeh.plotting
@@ -18,11 +19,6 @@
 from bokeh.models import LogTicker, BasicTicker
 from bokeh.plotting.helpers import _known_tools as known_tools
 
-try:
-    from bokeh import mpl
-except ImportError:
-    mpl = None
-import param
 
 from ...core import (Store, HoloMap, Overlay, DynamicMap,
                      CompositeOverlay, Element, Dimension)
@@ -1063,99 +1059,6 @@ def _process_legend(self, plot=None):
                 legend.location = pos
 
 
-
-class BokehMPLWrapper(ElementPlot):
-    """
-    Wraps an existing HoloViews matplotlib plot and converts
-    it to bokeh.
-    """
-
-    def __init__(self, element, plot=None, **params):
-        super(ElementPlot, self).__init__(element, **params)
-        if isinstance(element, HoloMap):
-            etype = element.type
-        else:
-            etype = type(element)
-        plot = Store.registry['matplotlib'][etype]
-        params = dict({k: v.default for k, v in self.params().items()
-                       if k in ['bgcolor']})
-        params = dict(params, **self.lookup_options(element, 'plot').options)
-        style = self.lookup_options(element, 'style')
-        self.mplplot = plot(element, style=style, **params)
-
-
-    def initialize_plot(self, ranges=None, plot=None, plots=None):
-        self.mplplot.initialize_plot(ranges)
-
-        plot = plot if plot else self.handles.get('plot')
-        new_plot = mpl.to_bokeh(self.mplplot.state)
-        if plot:
-            update_plot(plot, new_plot)
-        else:
-            plot = new_plot
-
-        self.handles['plot'] = plot
-        if not self.overlaid:
-            self._update_plot(self.keys[-1], plot, self.hmap.last)
-        return plot
-
-
-    def _update_plot(self, key, plot, element=None):
-        """
-        Updates plot parameters on every frame
-        """
-        plot.update(**self._plot_properties(key, plot, element))
-
-    def update_frame(self, key, ranges=None, plot=None, element=None, empty=False):
-        self.mplplot.update_frame(key, ranges)
-
-        reused = isinstance(self.hmap, DynamicMap) and self.overlaid
-        if not reused and element is None:
-            element = self._get_frame(key)
-        else:
-            self.current_key = key
-            self.current_frame = element
-
-        plot = mpl.to_bokeh(self.mplplot.state)
-        update_plot(self.handles['plot'], plot)
-        if not self.overlaid:
-            self._update_plot(key, self.handles['plot'], element)
-
-
-class BokehMPLRawWrapper(BokehMPLWrapper):
-    """
-    Wraps an existing HoloViews matplotlib plot, renders it as
-    an image and displays it as a HoloViews object.
-    """
-
-    def initialize_plot(self, ranges=None, plot=None, plots=None):
-        element = self.hmap.last
-        self.mplplot.initialize_plot(ranges)
-        plot = self._render_plot(element, plot)
-        self.handles['plot'] = plot
-        return plot
-
-    def _render_plot(self, element, plot=None):
-        from .raster import RGBPlot
-        bytestream = BytesIO()
-        renderer = self.mplplot.renderer.instance(dpi=120)
-        renderer.save(self.mplplot, bytestream, fmt='png')
-        group = ('RGB' if element.group == type(element).__name__ else
-                 element.group)
-        rgb = RGB.load_image(bytestream, bare=True, group=group,
-                             label=element.label)
-        plot_opts = self.lookup_options(element, 'plot').options
-        rgbplot = RGBPlot(rgb, **plot_opts)
-        return rgbplot.initialize_plot(plot=plot)
-
-
-    def update_frame(self, key, ranges=None, element=None):
-        element = self.get_frame(key)
-        if key in self.hmap:
-            self.mplplot.update_frame(key, ranges)
-            self.handles['plot'] = self._render_plot(element)
-
-
 class OverlayPlot(GenericOverlayPlot, LegendPlot):
 
     tabs = param.Boolean(default=False, doc="""