Added bokeh app examples

examples/apps/crossfilter.py

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+import numpy as np
+import pandas as pd
+import holoviews as hv
+import holoviews.plotting.bokeh
+
+from bokeh.layouts import row, widgetbox
+from bokeh.models import Select
+from bokeh.plotting import curdoc, figure
+from bokeh.sampledata.autompg import autompg
+
+df = autompg.copy()
+
+SIZES = list(range(6, 22, 3))
+ORIGINS = ['North America', 'Europe', 'Asia']
+
+# data cleanup
+df.cyl = [str(x) for x in df.cyl]
+df.origin = [ORIGINS[x-1] for x in df.origin]
+
+df['year'] = [str(x) for x in df.yr]
+del df['yr']
+
+df['mfr'] = [x.split()[0] for x in df.name]
+df.loc[df.mfr=='chevy', 'mfr'] = 'chevrolet'
+df.loc[df.mfr=='chevroelt', 'mfr'] = 'chevrolet'
+df.loc[df.mfr=='maxda', 'mfr'] = 'mazda'
+df.loc[df.mfr=='mercedes-benz', 'mfr'] = 'mercedes'
+df.loc[df.mfr=='toyouta', 'mfr'] = 'toyota'
+df.loc[df.mfr=='vokswagen', 'mfr'] = 'volkswagen'
+df.loc[df.mfr=='vw', 'mfr'] = 'volkswagen'
+del df['name']
+
+columns = sorted(df.columns)
+discrete = [x for x in columns if df[x].dtype == object]
+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,)
+options.Points = hv.Options('style', cmap='rainbow', line_color='black')
+
+def create_figure():
+    label = "%s vs %s" % (x.value.title(), y.value.title())
+    kdims = [x.value, y.value]
+
+    opts, style = {}, {}
+    opts['color_index'] = color.value if color.value != 'None' else None
+    if size.value != 'None':
+        opts['size_index'] = size.value
+        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):
+    layout.children[1] = create_figure()
+
+
+x = Select(title='X-Axis', value='mpg', options=quantileable)
+x.on_change('value', update)
+
+y = Select(title='Y-Axis', value='hp', options=quantileable)
+y.on_change('value', update)
+
+size = Select(title='Size', value='None', options=['None'] + quantileable)
+size.on_change('value', update)
+
+color = Select(title='Color', value='None', options=['None'] + quantileable)
+color.on_change('value', update)
+
+controls = widgetbox([x, y, color, size], width=200)
+layout = row(controls, create_figure())
+
+curdoc().add_root(layout)
+curdoc().title = "Crossfilter"

examples/apps/player.py

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+# -*- coding: utf-8 -*-
+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,
+)
+import holoviews as hv
+import holoviews.plotting.bokeh
+
+renderer = hv.Store.renderers['bokeh']
+
+start = 0
+end = 10
+
+hmap = hv.HoloMap({i: hv.Image(np.random.rand(10,10)) for i in range(start, end+1)})
+plot = renderer.get_plot(hmap)
+plot.update(0)
+
+def animate_update():
+    year = slider.value + 1
+    if year > end:
+        year = start
+    slider.value = year
+
+def slider_update(attrname, old, new):
+    plot.update(slider.value)
+
+slider = Slider(start=start, end=end, value=0, step=1, title="Year")
+slider.on_change('value', slider_update)
+
+def animate():
+    if button.label == '► Play':
+        button.label = '❚❚ Pause'
+        curdoc().add_periodic_callback(animate_update, 200)
+    else:
+        button.label = '► Play'
+        curdoc().remove_periodic_callback(animate_update)
+
+button = Button(label='► Play', width=60)
+button.on_click(animate)
+
+layout = layout([
+    [plot.state],
+    [slider, button],
+], sizing_mode='fixed')
+
+curdoc().add_root(layout)

examples/apps/selection_stream.py

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+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')
+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,))
+points = hv.Points(data)
+sel = Selection1D(source=points)
+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.title = 'HoloViews Selection Stream'