Merge 0a0320f into b095fb7

holoviews/plotting/bokeh/__init__.py

@@ -33,6 +33,9 @@
 
 Store.renderers['bokeh'] = BokehRenderer.instance()
 
+if len(Store.renderers) == 1:
+    Store.current_backend = 'bokeh'
+
 associations = {Overlay: OverlayPlot,
                 NdOverlay: OverlayPlot,
                 GridSpace: GridPlot,

holoviews/plotting/bokeh/examples/apps/apps/crossfilter.py → holoviews/plotting/bokeh/examples/apps/crossfilter.py

@@ -1,3 +1,10 @@
+"""
+An example demonstrating how to put together a crossfilter app based
+on the Auto MPG dataset. Demonstrates how to dynamically generate
+bokeh plots using the HoloViews API and replacing the bokeh plot
+based on the current widget selections.
+"""
+
 import numpy as np
 import pandas as pd
 import holoviews as hv
@@ -35,7 +42,6 @@
 continuous = [x for x in columns if x not in discrete]
 quantileable = [x for x in continuous if len(df[x].unique()) > 20]
 
-hv.Store.current_backend = 'bokeh'
 renderer = hv.Store.renderers['bokeh']
 options = hv.Store.options(backend='bokeh')
 options.Points = hv.Options('plot', width=800, height=600, size_index=None,)
@@ -52,7 +58,6 @@ def create_figure():
         opts['scaling_factor'] = (1./df[size.value].max())*200
     points = hv.Points(df, kdims=kdims, label=label)(plot=opts, style=style)
     plot = renderer.get_plot(points)
-    plot.initialize_plot()
     return plot.state
 
 def update(attr, old, new):

holoviews/plotting/bokeh/examples/apps/apps/player.py → holoviews/plotting/bokeh/examples/apps/player.py

@@ -1,11 +1,13 @@
 # -*- coding: utf-8 -*-
+"""
+Example of a simple player widget demonstrating how to connnect
+a simple HoloViews plot with custom widgets and combine them
+into a bokeh layout.
+"""
 import numpy as np
 from bokeh.io import curdoc
 from bokeh.layouts import layout
-from bokeh.models import (
-    ColumnDataSource, HoverTool, SingleIntervalTicker, Slider, Button, Label,
-    CategoricalColorMapper,
-)
+from bokeh.models import Slider, Button
 import holoviews as hv
 import holoviews.plotting.bokeh
 

holoviews/plotting/bokeh/examples/apps/apps/selection_stream.py → holoviews/plotting/bokeh/examples/apps/selection_stream.py

@@ -1,10 +1,15 @@
+"""
+Example app demonstrating how to use the HoloViews API to generate
+a bokeh app with complex interactivity. Uses a Selection1D stream
+to compute the mean y-value of the current selection.
+"""
+
 import numpy as np
 import holoviews as hv
 import holoviews.plotting.bokeh
 from holoviews.streams import Selection1D
 
-hv.Store.current_backend = 'bokeh'
-renderer = hv.Store.renderers['bokeh'].instance(mode='server')
+renderer = hv.Store.renderers['bokeh']
 hv.Store.options(backend='bokeh').Points = hv.Options('plot', tools=['box_select'])
 
 data = np.random.multivariate_normal((0, 0), [[1, 0.1], [0.1, 1]], (1000,))
@@ -13,5 +18,6 @@
 mean_sel = hv.DynamicMap(lambda index: hv.HLine(points['y'][index].mean()
                                                 if index else -10),
                          kdims=[], streams=[sel])
-doc,_ = renderer((points * mean_sel))
+
+doc = renderer.app((points * mean_sel))
 doc.title = 'HoloViews Selection Stream'

holoviews/plotting/bokeh/renderer.py

@@ -4,10 +4,13 @@
 import param
 from param.parameterized import bothmethod
 
+
+from bokeh.application.handlers import FunctionHandler
+from bokeh.application import Application
 from bokeh.charts import Chart
 from bokeh.document import Document
 from bokeh.embed import notebook_div
-from bokeh.io import load_notebook, curdoc
+from bokeh.io import load_notebook, curdoc, show
 from bokeh.models import (Row, Column, Plot, Model, ToolbarBox,
                           WidgetBox, Div, DataTable, Tabs)
 from bokeh.plotting import Figure
@@ -92,6 +95,28 @@ def get_widget(self_or_cls, plot, widget_type, **kwargs):
             return super(BokehRenderer, self_or_cls).get_widget(plot, widget_type, **kwargs)
 
 
+    @bothmethod
+    def app(self_or_cls, plot, notebook=False):
+        """
+        Creates a bokeh app from a HoloViews object or plot. By
+        default simply uses attaches plot to bokeh's curdoc and
+        returns the Document, if notebook option is supplied creates
+        an Application instance, displays it and returns it.
+        """
+        renderer = self_or_cls.instance(mode='server')
+        if not notebook:
+            doc, _ = renderer(plot)
+            return doc
+
+        def modify_doc(doc):
+            renderer(plot, doc=doc)
+
+        handler = FunctionHandler(modify_doc)
+        app = Application(handler)
+        show(app)
+        return app
+
+
     def server_doc(self, plot, doc=None):
         """
         Get server document.

holoviews/plotting/mpl/__init__.py

@@ -81,6 +81,9 @@ def get_color_cycle():
 
 Store.renderers['matplotlib'] = MPLRenderer.instance()
 
+if len(Store.renderers) == 1:
+    Store.current_backend = 'matplotlib'
+
 # Defines a wrapper around GridPlot and RasterGridPlot
 # switching to RasterGridPlot if the plot only contains
 # Raster Elements

holoviews/plotting/plotly/__init__.py

@@ -13,6 +13,9 @@
 
 Store.renderers['plotly'] = PlotlyRenderer.instance()
 
+if len(Store.renderers) == 1:
+    Store.current_backend = 'plotly'
+
 Store.register({Points: PointPlot,
                 Scatter: PointPlot,
                 Curve: CurvePlot,